The North American tallgrass prairies are home to switchgrass, a warm-season perennial C4 grass that is a member of the subfamily Panicoideae of the Poaceae family.^1,2 Switchgrass may flourish on poor soils, produce a lot of biomass, and give farmers a new way to make money while also helping the environment.³

An upright bunchgrass that can reach a height of 4 meters, switchgrass is known for its excellent yields.⁴ Access to fermentable sugars is hindered by structural and chemical barriers known as recalcitrance, making the production of ethanol from lignocellulosic biomass more challenging than from starch-based sources.⁵ By improving its total and net energy yield per hectare, switchgrass can become a more economically viable dedicated energy crop if its biomass productivity is improved.^{6, 7}

There is great promise for the herbaceous plant switchgrass as a long-term bioenergy crop. A highly desirable biofuel feedstock, it produces a lot of biomass, can grow in a variety of temperatures, and doesn’t compete too much with food crops.  Potentially meeting a large portion of the world’s transportation fuel demands with far less environmental damage than fossil fuels, biofuels made from non-grain lignocellulosic materials with high biomass yields are an attractive renewable energy option. Rapid and regulated growth of switchgrass plant materials is made possible through in vitro culture, a potent instrument in plant biotechnology. Biofuel production can be improved by genetic engineering by introducing features including higher sugar content, decreased lignin content, and improved enzymatic digestibility. In order to successfully create and select high-performing genetically modified switchgrass types specialized for biofuel generation, it is important to build precise and reproducible techniques for in vitro cultivation of the grass and molecular screening.

Bioconversion into ethanol is more challenging for lignocellulosic biomass due to its complex composition of cellulose, hemicellulose, and lignin compared to feedstocks based on starch.^8,9 The existing biomass fermentation processes for fuels and chemicals are expensive due in large part to this intrinsic resistance, which has prevented cellulose ethanol from being commercialized on a large scale.¹⁰ Removing the structural and chemical obstacles to biomass breakdown in bioenergy crops is crucial for enabling sustainable energy generation.¹¹

The inaccessibility of sugars locked within plant cell walls to cellulase enzymes is a major barrier to the efficient and economical synthesis of cellulosic ethanol. Enzymes are necessary for breaking down complex carbs into fermentable sugars, but they have a hard time breaking down cellulose and hemicellulose because of how closely bonded the sugar components are. An efficient method of propagating switchgrass is in vitro culture, which allows for the production of several plants with identical genetic material from a single tissue sample. For the purpose of propagating a homogeneous plant population, this is helpful. Because they necessitate the adjustment of growth medium, hormone therapies, and sterilizing processes, in vitro culture regimens can be difficult to create. It is absolutely essential to keep the culture sterile in order to avoid infection. Optimal growth medium composition, lighting, and hormone levels are only a few of the species-specific considerations that go into designing in vitro culture techniques for switchgrass. One of the most important steps in plant genetic engineering is in vitro culture.
Reducing the price of creating cellulosic ethanol is a promising area for plant genetic engineering. Switchgrass and other plant species can have their biomass yield increased by genetic engineering, making them more useful as feedstocks for cellulosic ethanol generation. As a result, production costs are reduced and ethanol yield is increased per unit of land and resources. To find genetically modified switchgrass varieties with improved biofuel-related properties, more accurate molecular screening approaches are needed.

Materials and Methods

The seeds for the switchgrass came from Houghton, USA’s Michigan Technological University. The Department of Plant Science and Biotechnology at Nasarawa State University, Keffi, in conjunction with Contec Global Agro Ltd of Maitama, Abuja, carried out the initial field investigations and domestication attempts. Trichy Research Institute of Biotechnology, Pvt. Ltd. in India was responsible for the genetic modification (GMF) component.

The induction of numerous shoots from nodal explants was achieved by preparing Switchgrass (Panicum virgatum L.) in vitro nodal cultures using MS¹² media. Benzylaminopurine (BAP), Kinetin (Kn), Indole Acetic Acid (IAA), Indole Butyric Acid (IBA), and Naphthalene Acetic Acid (NAA) were among the growth hormones used to stimulate shoot regeneration. The quantities of these hormones were varied, from 0 to 2 mg/l. Tables 1 and 2 detail the hormone concentrations and combinations, and the therapy codes that relate to them. As a control, hormone-free MS media was utilized. To continue multiplying shoots and maintaining the culture, the medium with the maximum yield was chosen. The regenerated shoots were periodically grown in new media at 30-to 60-day intervals. With each treatment, 20 explants were used in each of the six replicates. We used SPSS version 22’s Analysis of Variance (ANOVA) to look for trends in the data, and Duncan’s Multiple Range Test to find out how much the means differed.

Methods for Inducing Root Growth in Switchgrass (Panicum virgatum L.) Shoots That Have Regenerated or Derived Calluses in a Laboratory Setting

Regenerated shoots (2–5 cm) taken from nodal tissues were subjected to in vitro root induction using growth regulator-supplemented or unsupplemented medium. Shoots grown from nodal explants were given the best possible rooting environment by using MS media as the basal medium. Several different hormone-supplemented half-strength MS medium were used to transplant these numerous shoots. For the purpose of conducting more trials, the modified medium that produced the maximum number of roots per shoot was chosen. One month following the start, the length of the roots was measured from the base of the shoot to the tip of the root using a centimeter scale. After two months, we counted the amount of roots that had grown on each plantlet. Table 3 summarizes the various treatments combining different media (MS, B5, and their mixture) with varying concentrations of Kinetin (Kn) and 2,4-Dichlorophenoxyacetic acid (2,4-D) for optimizing callus induction protocols in switchgrass.

Table 4 presents a summary of the medium compositions utilized to root numerous shoots from nodal explants. Shoot regeneration from callus cultures of switchgrass (Panicum virgatum L.) was evaluated using different concentrations of cytokinins (BAP and Kn) either alone or in combination with auxins (NAA, IAA, and IBA). (Table 5) Days to Bud Break, Shoot Length, Leaf Length, Width and Number of at 2 Months of Culture in MS Medium is presented in Table 6.

The most successful root formation, at 93.33%, was observed in SGR2 (1/2 MS + 1mg/L NAA), followed by SGR6 (1/2 MS + 0.5mg/L NAA) at 80%, and SGR4 (1/2 MS + 0.5mg/L NAA + 0.5mg/L IAA) at 50%. A statistically significant difference (P < 0.05) was noted among the treatments concerning the number of days required for root induction, as detailed in Table 7.

The hormonal combinations SGC-19 (MS- B5 kinetin 0.1mg/1 + 2 4D 2mg/1) and SGC-20 (MS- B5 kinetin 0.5mg/1 + 2 4D 2mg/1) can be considered as most advantageous for callus induction for switchgrass as they provided highest callus induction percentage (74% and70%).

Results

Preparation of Switchgrass (Panicum virgatum L.) invitro nodal culture

For both shoot induction and growth, MS medium proved to be the most effective, regardless of the hormone amounts tested. After 28 days, the maximum shoot induction was reached in SG2 (MS+0.3mg/l BAP), whereas the slowest induction was observed after an average of 58 days. The shoot induction time for SG6 was the longest at 58 days, followed by SG9 at 50 days, and SG 10 at 53 days.

Growth Study of Multiple Shoots after 2 Months of Culture Period

After 60 days of culture in MS medium, the SG2 (MS media supplemented with 0.3mg/l BAP) had the highest multiplication rate, with an average of 11 shoots/explant. Then came SG 3 and SG 4, which used MS medium supplemented with BAP at concentrations of 0.5 and 1 mg/l, respectively, and a total of 9.00 and 8.00 shoots/explants. In the control group (SG 1), no shoots were observed.
Treatment number SG2 (MS+0.3mg/l BAP) resulted in bud break after 12 days, shoot height of 10cm, leaf length of 17 cm, and width of 0.30 cm. Treatment number SG 3 (MS + 0.5mg/l BAP) followed with bud break after 14 days, shoot height of 5.4 cm, leaf length of 11 cm, and width of 0.20 cm. Treatment number 4 (MS + 1mg/l BAP) resulted in bud break after 17 days, with average shoot height of 5.2 cm, leaf length and width of 9 and 0.10 cm, respectively. After 28 days, with leaf height and width of 4cm and less than 0.1cm, respectively, the bud break for treatment number SG5 was seen. After 35 days, treatment number SG 6 (MS medium supplemented with 2mg/1 BAP and 0.8mg/1 IBA) caused the buds to break. The minimum average shoot length was 1.23cm, and the leaf height and width were 5cm and <0.1cm, respectively. Treatment number SG 7 had four leaves and a bud break after 38 days, with a leaf height of 11 cm and a leaf breadth of less than 0.1 cm. After 38 days, treatment number SG 8 showed bud break with 4 leaves, a leaf height of 9cm, and a leaf width of less than 0.1cm. After 43 days, bud break was noted for treatment SG9 and SG10, with leaf height and width measuring less than 5 cm and less than 0.1 cm, respectively. Treatment SG 2 had the highest number of leaves at 11, followed by treatments SG 3 and 4, with 7 and 5 leaves, respectively.

Following a two-month culture period, the treatment number SG2 (MS+0.3mg/l BAP) had the longest average shoot length at 10 cm, followed by SG 3 (MS + 0.5mg/l BAP) at 5.4 cm and SG 4 (MS + 1mg/l BAP) at 5.2 cm. Treatment SG 6 (MS+2mg/1 BAP + 0.8mg/1 IBA) had the shortest average shoot length at 1.23 cm. In SG2 (MS+0.3mg/l BAP), the greatest number of shoots was 12. No MS media concentration was as effective as the SG2 treatment (MS+0.3mg/l BAP).

Callus Induction

MS-B5 combined medium produced stable callus for Switchgrass (Panicum virgatum L.). Callus produced from the media was brittle and brown, which allowed for easy multiplication and transfer. This morphology is consistent with descriptions of callus previously shown in maize. Callus formed faster, after 4 weeks on MS-B5 combined medium from the clumps of in vitro switchgrass cultures. 

Organogenesis in switchgrass (Panicum virgatum L.)

Among the media utilized, the treatment SGO2, which consists of MS supplemented with 0.3 mg/l BAP, successfully prompted the formation of shoots.

Cloning and Expression of Endoglucanase E1 Gene from Acidothermus cellulolyticusinto Switch grass

The BLAST software for the construction of primers for PCR is presented in Fig. 1. DNA isolation and mages of transformed E.coli DHS –α cells are presented in Plates 1 and 2, respectively. Gel image under UV – Transilluminator, showing the cloning confirmation by restriction enzyme digestion and PCR (Plate 3).

Figure 2 shows the BLAST Endoglucanase E1 result and Table 8 shows the sequencing validation of Endoglucauase E1. The results showed that at an amplification temperature of 55.9⁰C, the endoglucanase E1 enzyme’s PCR product had a size of 659 bp. Using BLAST, we determined that the E1 sequencing findings were similar to other E1 gene-specific nucleotide sequences that are published in GenBank.

The result of the saccharification analysis in transfected in vitro shoot cultures regenerated from callus of Switchgrass (Panicum virgatum L.) is presented in Tables 11 & 12.

Discussion

The results of the study suggest that one cytokinin, specifically BAP, is the most effective for promoting shoot induction. In terms of reaction time, BAP outperformed Kn. Meristems, shoot tips, hypocotyls, epicotyls, seeds, leaf and tuber discs, root cuttings, and individual node cuttings are the usual explants used for micropropagation. However, in most cases, you can only directly initiate shoots from fully established tree explants,^13,14 researchers looked into how BAP affected Aquilaria hirta shoot multiplication, elongation, and root induction in various basal medium. According to the findings, the basal medium worked best.¹⁵ Previous studies have demonstrated that shoot elongation typically decreases as the number of shoots in culture rises.¹⁶ The quantity of shoots likewise reduced as the cytokinin concentration increased. There was a noticeable decrease in shot quantity as the BAP content rose. Low amounts of cytokinin promote shoot regeneration, but high concentrations promote callus proliferation and hinder shoot differentiation.¹⁷ Among the two cytokinins we looked at, BAP alone produced more frequent shoots than Kn alone. This pattern of activity has also been observed in other plants, such as Murrayakoenigii L.,¹⁸ Aegle marmelos L.,¹⁹ and Feronia limonia L.²⁰
According to the results of this study, only one cytokinin, BAP, was needed to trigger shoot bud induction and shoot proliferation. What’s more, as compared to when used in conjunction with auxins, BAP alone yielded better results in terms of shoot production density. This conclusion is in line with the claims made by several publications that BAP is enough to promote shoot proliferation in Tuberaria²¹ major, Metabriggsia sp., and Passiflora sp.²² The Kn-supplemented medium yielded more shoot buds than the BAP²³ medium in the Houttuynia cordata experiment. Shot induction²⁴ demonstrated, however, that BAP was superior to Kn.

It appears that employing a single cytokinin was the most effective strategy, according to the findings of the shoot induction. But when looking at BAP’s effects in isolation, it was clearly superior. Although increasing the concentration of cytokinin has minimal impact on the quantity of shoots generated, it is necessary for the induction of shoots. According to the data, the SG2(MS+0.3mg/l) treatment outperformed the other treatments significantly (P≤0.05). Buds broke later and shoots were narrower and shorter when cytokinin concentration was higher. Clumps of switchgrass (Panicum virgatum L.) were cultivated in a controlled setting to generate calluses. Research has shown that certain woody plant species, such as Ceratozamiahildae, Phoenix dactylifera, and Sesamum indicum, can generate calluses when exposed to combinations of 2, 4D and kinetin.^{25, 26} It is not uncommon for rooting and shoot multiplication to occur simultaneously in certain culture media. However, in order to encourage rooted and set up strong root growth, it is often necessary to transplant explants to new media that has different nutrients and different growth regulators²⁷ discovered that reducing the medium mineral content to half of its usual strength greatly boosted rooting. Switchgrass (Panicum virgatum L.) shoots were shown to root most well in MS media. The rooting percentage that NAA alone produced was higher than that which it produced when combined with other hormones. It was also discovered that shoots of switchgrass (Panicum virgatum L.) rooted effectively in half strength MS media (1/2 MS). Results showed that half strength MS media supplemented with 0.1 mg/l IBA or NAA, 3 mg/1 activated charcoal, and 3% sucrose²⁸ were the best conditions for root initiation and induction of Ficus anastasia. Similarly, among Ulmus species (elms), NAA resulted in the highest root development rate (percent).²⁹ Although the fact that Panicum virgatum L. can regenerate from callus tissue utilizing invitro clumps as explants is promising, additional investigation into methods to expedite organogenesis in Panicum virgatum L. callus is required.  For the purpose of cloning and expressing the EI gene into switchgrass, the Acidothermus cellulolyticus strain 11B and DNA were standardised using a variety of growth conditions and specific media. We got both of them from ATCC. The Acidothermus cellulolyticus strain 11B, used for cloning and EI gene expression, entered log phase after 36 hours of incubation at 55ᵚC in a shaking incubator. The culture was maintained in LPBSM, which stands for low phosphate basal salt media. This finding is in line with³⁰ the optimal temperature of 55ẦC for the growth of Acidothermus cellulolyticus strain 11B. The physical investigation confirmed that Acidothermus cellulolyticus is a rod-shaped, nonmotile, Gram-negative bacterium. The negative results of the biochemical characterization tests performed using IMViC confirmed that the bacteria were Acidothermus cellulolyticus. The DNA isolated from the Acidothermus cellulolyticus culture was confirmed by agarose gel electrophoresis using a UV-transilluminator and a standard 1KB ladder. The E1 gene’s specific primers were designed by analyzing primer BLAST results from the NCBI. Primers are useful for this inquiry if their GC% is above 50, and self-replication is eliminated when their melting temperatures are close. All of these things were thought about when selecting high-quality primers. The E1 gene-specific primers were tested on Acidothermus cellulolyticus DNA using a gradient PCR analysis to determine the ideal annealing temperature. Acidothermus cellulolyticus’s E1 gene was found to be 98% identical to the E1 gene of the tested organism, according to BLAST results.  Agarose gel electrophoresis confirmed the presence of an E1 gene insert (659 bp) and produced findings that were consistent with the size of the PCR product in our study, thereby validating the insert. A quantitative expression investigation in E. coli DH5-α validated the overexpression of the E1 gene. The E1 gene-specific primers and the RecA internal reference were used in a quantitative real-time polymerase chain reaction (QRT-PCR). A fold variation of 1.803% was demonstrated by the results. The E1 gene underwent amplification at 12 and 14 cycles, whereas the RecA gene, which serves as an internal control, underwent amplification at 25 and 28 cycles. The quantitative E1 gene analysis in transfected callus samples was validated by quick real-time polymerase chain reaction (QRT-PCR) and relative E1 gene expression levels. Actin, the internal control gene, showed its amplification at cycles 23 and 26, whereas the E1 gene’s amplification occurred at cycles 16 and 22, respectively. This study adds to the growing body of evidence suggesting successful transfection of the E1gene insert into the switch grass callus and subsequent mRNA expression.

According to the total protein content calculation, the callus shoot cultures that were transfected in vitro had a protein concentration of 0.58 mg/gm, which was greater than the non-transfected callus shoot cultures that were 0.311 mg/gm. Previous research has shown that the endoglucanase enzyme is active at alkaline pH and increases cellobiose release. This could mean that recalcitrance to biofuel generation³¹ is reduced, according to this study’s results on increased protein concentration in transfected in vitro shoot cultures from switchgrass callus.  Saccharification results showed that endoglucanase enzymatic activity led to greater sugar release in transfected invitro shoot cultures from switchgrass callus (0.75 mg/g) than in non-transfected invitro shoot cultures from callus (0.315 mg/g). This study agrees with³² others about Phytochrome Interacting Factor 3. Increased saccharification efficiency was suggested by the observation of more soluble sugar release in transgenic switchgrass plants with an overexpressed Like 1 gene following enzymatic hydrolysis. Saccharification was found to be twofold improved in E1 transgenic switchgrass in vitro cultures at an optimal pH of 5.0, which is in agreement with prior study,³³ which discovered a saccharification increase of up to 15% in E1 transgenic tobacco and maize grown at the same pH.

Cloning and Heterologous Expression of Endoglucanase E1 Enzyme for Improved Biofuel Production using Agrobacterium Mediated Gene Transfer Method

The gene of interest, Endoglucanase E1, was expressed in Acidothermus cellulolyticus11B, which was standardized in low phosphate basal salt medium (LPBSM) and acquired from the American Type Culture Collection (ATCC). Acidothermus cellulolyticus culture DNA was extracted using phenol-chloroform DNA isolation technique and DNA quality was assessed using Agarose Gel Electrophoresis. The Endoglucanase E1 gene was amplified and synthesized in bacterial DNA after being generated using primer BLAST. The Endoglucanase E1 gene was validated using sequencing analysis. The Endoglucanase E1 gene was inserted into a pUC18 vector after competent E. coli DH5-α cells were produced and screened. Polymerase chain reaction and restriction enzyme digestion validated the endoglucanase E1 gene insert. The Endoglucanase E1 gene’s quantitative expression in E.coliDH5-α was validated using Q-RT-PCR. Agrobacterium tumefaciens was transformed after having the endoglucanase E1 gene cloned into the expression vector pCAMBIA 1301. Transfection of the switchgrass callus with the selected Agrobacterium tumefaciens was performed. Using Q-RT-PCR, we were able to confirm that the Endoglucanase E1 gene was expressed quantitatively in the callus of Switchgrass.

Biochemical Screening of Transformed Invitro Shoot Cultures from Callus of Switchgrass (Panicum virgatum L.)

Protocols for biochemical screening were examined in order to determine the amount of sugar and total soluble protein. The influence of different concentrations of cytokinins (BAP and Kn) and auxins (NAA, IAA, and IBA) on shoot regeneration from callus cultures of switchgrass (Panicum virgatum L.) was studied in Kanamycin selection media.

To homogenize one gram of callus-regenerated shoot material, lysis buffer was added to a pre-chilled pestle and mortar. The following ingredients were used: 7 M urea, 2 M thiourea, 4% CHAPS, 100 mM DTT, 40 mM Tris-HCl (pH 8.5), and protease inhibitors. The protein extracts were spun at 12,000 revolutions per minute for 20 minutes at 4 degrees Celsius. The resulting supernatants were transferred to a new tube and portioned out for later use, keeping them at -80 degrees Celsius. The total soluble proteins were estimated using the Bradford test, which was performed on the supernatant.

Saccharification Analysis in Transfected Invitro Shoot Cultures Regenerated from Callus of Switchgrass (Panicum virgatum L.)

Invitro shoot cultures were cultivated in a controlled environment under 8 hours of light at 25°C from calluses of transfected and non-transfected switchgrass for saccharification. In the pots, the two cultures of shoots were allowed to dry. The internodes were used to harvest 4-millimeter-long portions of stem. The endoglucanase enzyme, which was generated from transgenic switchgrass cultures in vitro, was used for enzymatic hydrolysis. In a 25 mM sodium acetate buffer with a pH of 4.5, the hydrolysis process was carried out at predetermined intervals. Hydrolysis in 4% sulfuric acid at 120°C for one hour followed an initial dissolution of 4 mg of cultivated stem fragments in 72% sulfuric acid at 30°C for chemical hydrolysis. Following the neutralization of the hydrolysate with barium hydroxide [Ba(OH)₂], the sugar content was determined using Benedict’s technique. Using Benedict’s Quantitative Reagent, we measured the total sugar levels in cultures that were either left untreated or treated with endoglucanase.

Total Crude Protein Estimation in the Invitro Shoot Cultures from Transfected Callus

To homogenize one gram of callus-regenerated shoot material, lysis buffer was added to a pre-chilled pestle and mortar. The following ingredients were used: 7 M urea, 2 M thiourea, 4% CHAPS, 100 mM DTT, 40 mM Tris-HCl (pH 8.5), and protease inhibitors. The protein extracts were spun at 12,000 rpm for 20 minutes at 4°C. The resulting supernatants were spoon-fed into new tubes, portioned out, and kept at -80°C until needed. Tables 9 and 10 show the results of the Bradford test, which were used to estimate the total soluble protein concentration, from the supernatants. The Bradford test was used to evaluate total protein levels after crude protein was extracted from in vitro regenerated shoot cultures that were produced from callus.

Saccharification Analysis in Transfected Invitro Shoot Cultures Regenerated from Callus of Switchgrass (Panicum virgatum L.)

In vitro shoot cultures were established in a controlled environment with 8 hours of light at 25°C from calluses of transfected and non-transfected switchgrass. In their separate containers, the two shoot cultures were left to dry naturally. Sapcharification analysis required the collection of internode-region stem segments measuring 4 mm in length. All together, 4 milligrams of these stem pieces were dissolved in 72% sulfuric acid at 30 degrees Celsius, then hydrolyzed in 4% sulfuric acid at 120 degrees Celsius for an hour. After adding barium hydroxide [Ba(OH)₂] to the resultant solution, it was neutralized. Then, the sugar content was found using Benedict’s method.

Table 1: Various Modified MS Media Used for Inducing Multiple Shoot Formation in Switchgrass (Panicum virgatum L.)

Note: Each treatment represents a different combination of plant growth regulators used in modified MS media to assess their effect on shoot multiplication.

Table 2: Shoot Proliferation and Development from Nodal Explants of Switchgrass (Panicum virgatum L.) in MS Media at 2 Months of Culture

Table 3: Different Media Combinations Tested for Callus Induction from invitro Clumps of Switchgrass (Panicum virgatum L.)

Note: This table summarizes the various treatments combining different media (MS, B5, and their mixture) with varying concentrations of Kinetin (Kn) and 2,4-Dichlorophenoxyacetic acid (2,4-D) for optimizing callus induction protocols in switchgrass. 

Table 4: Different Modified MS Media Evaluated for Root Development in Regenerated Shoots of Switchgrass (Panicum virgatum L.) 

Table 5: Different Modified MS Media Evaluated for Shoot Induction from Callus Cultures of Switchgrass (Panicum virgatum L.)

Table 6: Days to Bud Break, Shoot Length, Leaf Length, Width and Number of at 2 Months of Culture in MS Medium

Means with different superscripts within a column indicate significant difference at P<0.05

Table 7: Root induction (Days) of regenerated shoots from Nodal Explant of switchgrass in modified M.S Medium.

Means with different subscripts P < 0.05 

Table 8: Sequencing confirmation of Endoglucanase E1 Gene Click here to view Table

Table 9: Bovine Serum Albumin Standards for Protein Estimation

Table 10: Enzyme assay and determination of total soluble proteins transfected in vitro shoot cultures from callus of switchgrass

Saccharification Analysis in Transfected Invitro Shoot Cultures Regenerated from Callus of Switchgrass (Panicum virgatum L.)

The result of the saccharification analysis in transfected in vitro shoot cultures regenerated from callus of Switchgrass (Panicum virgatum L.) ispresented inTables 11 & 12.

Table 11:  Glucose Standards for Benedicts Estimation

Table 12: Saccharification of Invitro Shoot Culture

 L             AC          AC

Plate 1: DNA Isolation of the Acidothermus cellulolyticus Click here to view Plate

Plate 2: Images of Results of Transformed E.coli DH5-α Cells  Click here to view Plate

Figure 1: Primer Design Using Primer BLAST Software Click here to view Figure

Figure 2: Description of BLAST Endo glucanase E1 Click here to view Figure

Plate 3: Gel Image under UV-Transilluminator Showing the Cloning Confirmation by Restriction Enzyme Digestion and PCR, Click here to view Plate

Invitroshoot Regeneration from Callus of Switchgrass in Kanamycin Selection Media

Shoot regeneration from callus cultures of Switchgrass (Panicum virgatum L.) was investigated in this study utilizing a variety of cytokinin combinations (BAP and Kn) and auxins (NAA, IAA, and IBA) and individual cytokinins at varying doses inside Kanamycin selection medium.

Total Crude Protein Estimation in the Invitro Shoot Cultures from Transfected Callus

Table 8 displays the bovine serum albumin standards used for protein measurement. Transfected in vitro shoot cultures from switchgrass callus and enzyme assay for total soluble proteins are shown in Table 9.

Conclusion

Findings from this work have significant bearing on the development of methods for in vitro cultures of switchgrass and on the molecular screening of the Endoglucanase E1 gene from Acidothermus cellulolyticus in switchgrass shoot cultures for biofuel generation. It is possible to improve the efficiency of switchgrass biofuel production by using genetic engineering for biochemical screening and modifying in vitro culture conditions. Molecular screening of the Endoglucanase E1 gene from Acidothermus cellulolyticus in switchgrass cultures and the development of more efficient and sustainable in vitro protocols for switchgrass are both laid out by this research, which will help pave the way for a more sustainable energy future.

Biochemical screening confirmed the significant upregulation of the Endoglucanase E1 gene in in vitro switchgrass shoots, highlighting the possibility of genetic engineering to enhance switchgrass’s biofuel resource potential. Additional biofuel-related features can be introduced or improved upon by future investigation into genetic transformation experiments. To further improve biofuel production research, it is recommended to conduct additional chemical screening on transformed switchgrass plantlets that have been acclimated in greenhouses and to use bioreactors for sugar hydrolysis. 

Acknowledgement

The authors wish to thank Tertiary Education Trust Fund (TETFund) for the National Research Fund (NRF) sponsored project and Contec Global Agro Ltd, Abuja for their support especially towards the success of invitro aspect of the research. We are also grateful to Phyto Technology Laboratories (Lenexa, KS), Sigma-Aldrich (St. Louis, Mo) and Trichy Research Institute of Biotechnology Pvt. Ltd, India for their contributions toward the genetic modification (GMF) phase of the research.

Funding Source

The research project was funded by Tertiary Education Trust Fund (TETFund) through the National Research Fund (NRF) 2020: TETFund/DR&D/CE/STI/52/VOL1. 

Conflict of Interest

The authors do not have any conflict of interest

Data Availability Statement

This statement does not apply to this article   

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval. 

Informed Consent Statement

This study did not involve human participants, and therefore, informed consent was not required.

Clinical Trial Registration

This research does not involve any clinical trials.

Permission to reproduce material from other sources

Not Applicable

Author Contributions

Rojin George: Tissue Culture Experiments, Methodology and Writing, Molecular and Biochemical Analyses.

Elizabeth Sahmicit Dashe: Field Trials, Section of Methodology, Molecular and Biochemical Analyses.

Josiah Chukwudi Onovo: Conceptualization, Section of Methodology and Writing, and Supervision.

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Gestational diabetes mellitus (GDM) represents a significant and escalating global public health concern, marked by a complex and multifaceted pathophysiological foundation. This metabolic disorder, unique to pregnancy, is characterized by glucose intolerance and insulin resistance that emerge or are first recognized during gestation. Its etiology encompasses a dynamic interplay of genetic predispositions, hormonal shifts, metabolic demands of pregnancy, and environmental influences such as diet and lifestyle. As such, GDM epitomizes a model of disease wherein inherited biological susceptibility and external factors converge to disrupt maternal glucose homeostasis.^1-2

Over the past few decades, the epidemiological landscape of GDM has undergone a dramatic transformation, paralleling global surges in obesity, sedentary behavior, and nutritional imbalances. This shift reflects broader transitions in public health, notably the rise in non-communicable metabolic disorders in both high-income and developing countries.³ Current estimates suggest that between 14% and 20% of all pregnancies worldwide are complicated by gestational diabetes, though this prevalence is not uniform. Significant geographic, ethnic, and socioeconomic disparities exist, further emphasizing the need to understand the diverse biological underpinnings of this condition.⁴

At the molecular level, the development of GDM is driven by a finely tuned yet vulnerable balance between insulin secretion and insulin sensitivity. During pregnancy, a physiological state of insulin resistance is naturally induced to ensure adequate glucose supply to the growing fetus. In response, maternal pancreatic β-cells are required to expand and increase insulin production. In individuals with underlying genetic or epigenetic susceptibility, this compensatory mechanism fails, resulting in hyperglycemia.^5-6 The pathogenesis of GDM, therefore, is not attributable to a single cause but is rather the consequence of disruptions across interconnected biological systems, including genetic regulatory networks, endocrine signaling, and cellular metabolic pathways.

The scientific understanding of GDM has evolved from mere clinical observations to molecular investigation. Contemporary research increasingly focuses on deciphering the genetic architecture of GDM, identifying susceptibility loci, gene-gene interactions, and gene-environment correlations that shape the disease phenotype. ⁷ The advent of advanced computational tools—most notably bioinformatics and systems biology—has revolutionized this endeavor. These methodologies allow for the integration and analysis of large-scale genomic, transcriptomic, and proteomic datasets, offering a systems-level view of the disease’s complexity. ⁸

Unlike monogenic diseases, GDM is polygenic and genetically heterogeneous, involving the combined effect of multiple genes, environmental influences, and epigenetic regulators. ^9-10 This complexity necessitates comprehensive analytic frameworks capable of simultaneously evaluating numerous molecular parameters. Single-gene studies, though informative, are insufficient to capture the layered interdependencies that define GDM pathophysiology.

The implications of GDM extend well beyond the perinatal period. Increasing evidence suggests that GDM serves as a harbinger of future metabolic dysfunction—for both the mother and her offspring. Women with GDM face significantly elevated risks of developing type 2 diabetes mellitus, cardiovascular disease, and metabolic syndrome later in life. Similarly, children born to mothers with GDM are more likely to experience obesity, insulin resistance, and diabetes in adulthood, suggesting that intrauterine exposure to hyperglycemia may induce transgenerational metabolic programming.^11-12

In recent years, major strides in genomic sequencing technologies, data analytics, and high-throughput screening have drastically improved the capacity to unravel the genetic complexities of diseases like GDM.^13-14 The integration of curated databases—such as DisGeNET, Gene Ontology (GO), WikiPathways, and others—has further enabled researchers to systematically annotate gene functions, identify biologically relevant pathways, and explore disease-gene associations with unprecedented precision.^15-16 These tools facilitate multidimensional investigations, allowing for simultaneous evaluation of molecular functions, cellular processes, and tissue-specific expression patterns.

Despite these advancements, substantial gaps remain in our holistic understanding of the genetic framework underlying GDM.¹⁷ Many prior studies are limited by small sample sizes, population homogeneity, or narrow methodological scope, leaving critical aspects of the disease unexplored. There is a pressing need for integrative, large-scale, and hypothesis-driven studies that synthesize existing knowledge while also uncovering novel insights.^18-19

In response to these challenges, the present study employs a comprehensive bioinformatics-based approach to investigate the genetic and molecular landscape of gestational diabetes. By analyzing a curated set of GDM-associated genes through multiple computational frameworks, we aim to characterize functional gene networks, elucidate key biological pathways, and identify potential genetic biomarkers and therapeutic targets. This integrative strategy is designed not only to deepen our molecular understanding of GDM but also to lay the groundwork for precision medicine approaches tailored to maternal metabolic health. ²⁰

Objectives

To thoroughly examine the most significant 30 genes of gestational diabetes employing high-level bioinformatics methods.

To study molecular pathways, biological processes, and functional interactions underpinning gestational diabetes using integrated computational strategies.

To determine putative genetic biomarkers and therapeutic targets by analyzing complex gene networks and metabolic interactions.

Methods and Materials

The methodological design of this study was an exhaustive, multi-level bioinformatics strategy aimed at deciphering the intricate genetic background of gestational diabetes. The research was carefully organized in order to take advantage of various computational tools and sophisticated analytical methods.

Gene Selection and Preparation of the Initial Dataset

The first part of our methodology involved gene selection from the DisGeNET database, a rich source of gene-disease associations. We browsed through this vast database in an organized manner to select and extract the top 30 genes significantly linked with gestational diabetes. This filtered set of genes formed the primary dataset for further analysis, guaranteeing a focused and comprehensive examination.

Computational Tools and Analytic Platforms

A wide variety of advanced bioinformatics platforms were utilized to thoroughly describe the chosen genes. These tools comprised GO_Biological_Process_2023, GO_Cellular_Component_2023, GO_Molecular_Function_2023, WikiPathways_2024_Human, ClinVar_2019, Cancer_Cell_Line_Encyclopedia, ChEA_2022, TargetScan_microRNA_2017, DrugMatrix, HMDB_Metabolites, Jensen_TISSUES, Jensen_COMPARTMENTS, and Jensen_DISEASES.

Each database offered a distinct view of gene function, cell-cell interactions, and disease associations. Such a multi-database framework allowed for an integrative study of genetic mechanisms beyond single-database approaches.

Functional Annotation and Pathway Analysis

The genes that were selected went through strict functional annotation in different dimensions.

GO_Biological_Process_2023: Classified genes according to their biological functions, and the essential cellular processes that are involved in gestational diabetes were uncovered.

GO_Cellular_Component_2023: Showed specific cellular locations of gene products, whereas GO_Molecular_Function_2023 documented the specific molecular functions of resultant proteins.

WikiPathways_2024

Human was instrumental in charting complex gene and protein interactions, enabling visualization of multiplexed molecular networks beneath gestational diabetes. Pathway analysis enabled identification of possible points of interaction and functional associations between various genetic components.

Genetic Variation and Clinical Correlation ClinVar_2019

It was used to link genetic variations to clinical presentation, closing the gap between molecular-level alteration and disease phenotype. This enabled a sophisticated understanding of how certain genetic changes may be responsible for gestational diabetes onset.

Transcriptional and Regulatory Network Exploration

Emergent tools such as ChEA_2022 facilitated identification of transcription factors by experimental data, and TargetScan_microRNA_2017 predicted microRNA targets of regulation. The multi-layered analysis shed light on the transcriptional and post-transcriptional regulatory interactions possibly affecting gestational diabetes.

Metabolic and Tissue-Specific Characterization HMDB_Metabolites

Presented a general overview of human metabolites connected with the targeted genes. Jensen_TISSUES and Jensen_COMPARTMENTS provided important data regarding gene expression in various tissue types and subcellular compartments, respectively. Jensen_DISEASES enabled wider disease association studies.

Computational Analysis and Visualization

All the analyses were conducted in R programme version 4.4.2, a robust statistical computing platform. This system facilitated advanced statistical processing, manipulation of data, and visualization of intricate genetic data sets.

Statistical Issues

Strict statistical methods were used to guarantee the reliability and significance of results. Adjusted p-values were determined to correct for multiple testing, and significance was generally set at p < 0.05. Odds ratios and aggregate scores were calculated to measure the magnitude of genetic associations and pathway enrichments.

Ethical and Data Management

In using publicly available databases, utmost care to follow data privacy and ethical principles was preserved. All data were anonymized and no personal identifiable information was accessed or handled throughout the research.

The approach was an all-encompassing, multi-faceted strategy to decipher the genetic intricacies of gestational diabetes. By combining various computer resources and sophisticated analytical tools, the study hoped to reveal unprecedented information on the molecular basis of this serious metabolic disorder.

Results

The integrated bioinformatics study of gestational diabetes disclosed a complicated and multifaceted genetic landscape, uncovering intricate molecular mechanisms and pathway interactions that offer unprecedented insights into the pathogenesis of the disease.

Biological Process

Characterization GO_Biological_Process_2023 analysis illustrated exceptional enrichment in a number of key cellular and metabolic processes. Vitamin B12 metabolism was identified as the most significantly related pathway with an exceedingly low adjusted p-value reflecting strong genetic involvement. The pathway exhibited high overlap of 8 out of 54 genes, pointing towards a basic role of vitamin B12 metabolic processes in gestational diabetes pathogenesis. Of equal importance was the pathway of folate metabolism, which showed paralleling patterns of genetic enrichment. This pathway’s implication implies complex interactions between nutrient metabolism and gestational diabetes, pointing toward possible metabolic regulatory mechanisms beyond conventional knowledge. (Fig :1).

Figure 1: The bar graph for GO_Biological_Process_2023 demonstrates -log10(Adjusted p value) versus terms arranged sequentially.    Click here to view Figure

Cellular components and molecular functions

Insights GO_Cellular_Component_2023 and GO_Molecular_Function_2023 analyses have yielded detailed insights into the subcellular and functional nature of discovered genes. The analyses have shown intricate spatial and functional relationships of genetic factors in gestational diabetes. Individual clusters of genes exhibited differential localization between cellular compartments, suggesting complex molecular coordination processes. The analysis of molecular functions revealed the presence of various protein activities, from enzymatic interactions to essential binding processes controlling metabolic responses.(Figure:2, 3).

Figure 2: Shown is a bar graph of GO_Cellular_Component_2023 with -log10(Adjusted p value) plotted against terms in the presented order.   Click here to view Figure

Figure 3: The bar graph for GO_Molecular_Function_2023 represents -log10(Adjusted p value) on the y-axis against ordered terms on the x-axis.   Click here to view Figure

Pathway and Network Interactions

WikiPathways_2024_Human analysis unveiled several pivotal pathways critical to gestational diabetes understanding. Adipogenesis emerged as a particularly significant pathway, demonstrating complex genetic interactions involving genes like IL6, IRS1, INSR, and LEP. This pathway’s enrichment suggests profound connections between adipose tissue development and gestational diabetes progression.

The adipogenesis transcription factor regulation pathway further shed light on the molecular mechanisms of metabolic adaptations in pregnancy. The results of these studies are significant to understand the genetic regulatory networks that may predispose individuals to gestational diabetes( shown in Table :1)

Table 1: WikiPathways_2024_Human

Metabolic and Tissue-Specific Characterizations

The Jensen_TISSUES and Jensen_COMPARTMENTS analyses provided rich mappings of gene expression across tissues and subcellular compartments, respectively. This multi-dimensionality characterized subtle tissue-specific genetic interactions that illuminated the complexity of gestational diabetes as more than can be captured by simplistic linear models.

Interestingly, genes showed different patterns of expression across metabolically active tissues, implying complex systemic regulatory processes far beyond those of localized molecular interactions.(shown figure: 4).

Figure 4: The bar graph for Jensen_COMPARTMENTS represents -log10(Adjusted p value) on the y-axis against ordered terms on the x-axis.   Click here to view Figure

Adult and lumbar spine tissues showed the strongest gene expression enrichment. This may reflect the systemic nature of gestational diabetes, which affects multiple adult tissues and possibly spinal bone metabolism or neural pathways involved in glucose regulation.

Abdominal adipose tissue and 3T3-L1 cells (a model for adipocyte development) are closely linked to fat storage and insulin sensitivity. Their enrichment suggests that genes involved in fat metabolism and adipogenesis are highly relevant in the pathophysiology of GDM.

The presence of enrichment in artery and atherosclerotic plaque indicates that gestational diabetes may influence or be influenced by vascular health. This supports existing evidence linking GDM with an increased risk of cardiovascular disease in later life.

Gene enrichment in neonatal tissues aligns with the fact that gestational diabetes directly impacts fetal development. Infants born to mothers with GDM are at higher risk for metabolic disorders, macrosomia, and altered insulin sensitivity.

Enrichment in hip, femur, and tibia suggests either direct skeletal involvement (e.g., through calcium/vitamin D metabolism, or bone-related hormones like osteocalcin) or systemic effects where GDM alters gene expression across a wide range of tissues.(fig:5).

Figure 5: The bar graph illustrates Jensen_TISSUES showing -log10(Adjusted p value) plotted against terms in sequential order.   Click here to view Figure

Transcriptional Regulatory Mechanisms ChEA_2022 transcription factor analysis unveiled deep insights into the regulatory networks controlling gestational diabetes genes. The analysis uncovered intricate transcriptional control processes, illustrating how genetic factors are dynamically controlled under metabolic adaptations(shown in figure : 6).

Figure 6: The depicted bar graph for ChEA_2022 shows -log10(Adjusted p value) plotted versus the ordered list of terms.   Click here to view Figure

Metabolite and Drug Interaction Scenarios HMDB_Metabolites and DrugMatrix analysis revealed intriguing interactions among genetic factors, metabolites, and pharmacologic compounds. Oxygen metabolism, certain drugs such as atorvastatin, and a wide range of hormonal metabolites showed remarkable genetic associations. These observations indicate novel potential therapeutic approaches and offer a molecular basis for the explanation of metabolic disturbances of gestational diabetes.

Statistical Significance and Genetic Robustness On all analytic platforms, the reported genetic associations were highly statistically significant. Persistent low adjusted p-values and high odds ratios highlighted the robustness of the discovered genetic interactions.

The extended analysis singled out key genes such as CRP, IL6, INSR, LEP, and TNF as core molecular players in the pathogenesis of gestational diabetes. These genes were identified as pivotal nodes in intricate genetic networks, which implicates them as possible targets for diagnostics or therapy.

The findings collectively draw a sophisticated portrait of gestational diabetes as a complex, multifactorial disease defined by complex genetic, metabolic, and cellular interactions. By delivering an unprecedented molecular-level insight, this study fills important knowledge gaps and paves way for exciting new avenues of future research. (shown in table :2,3)

Table 2: HMDB_Metabolites

Table 3: DrugMatrix

Discussion 

This study provides the first comprehensive insights into the geneticarchitecture of GDM in East Asians and introduces a model that integratesPRS with early electronic health records to enhance theprediction and classification of GDM risk. We conducted the largest GWAS to date on GDMand five glycemic traits in an East Asian cohort, revealing a refined genetic architecture of GDM. ²¹ Our comprehensive pathway and metabolite analysis provides a nuanced understanding of the intricate metabolic interactions underpinning disease mechanisms, regulatory processes, and therapeutic possibilities. The integration of genetic, metabolic, and pharmacological data uncovers complex biological networks that govern metabolic regulation and offer potential avenues for precision medicine.

Pathway Enrichment Analysis

Vitamin B12 and Folate Metabolism

The most statistically enriched pathways centered around vitamin B12 and folate metabolism, with exceptionally low adjusted p-values (p < 2 × 10⁻⁸), indicating robust statistical significance. Key genes involved—CRP, IL6, INSR, HBB, HBA1, SOD2, TNF, and INS—suggest multifaceted interactions among metabolic regulation, inflammatory responses, and genetic determinants.These pathways are not merely passive conduits of biochemical activity; rather, they appear to serve as active regulatory hubs. The extremely high odds ratios (B12 metabolism: 157.5, folate metabolism: 118.7) reinforce their centrality within metabolic control networks and their likely involvement in disease pathophysiology.

Adipogenesis and Insulin Signaling

Pathways associated with adipogenesis (WP236) and leptin-insulin signaling (WP3935) demonstrated significant enrichment, highlighting key regulatory roles in metabolic homeostasis. Notable genes such as IL6, IRS1, LEP, ADIPOQ, and INS emerged as central nodes, underlining the complex interplay between adipose tissue regulation and systemic energy balance. The elevated combined enrichment scores (adipogenesis: 2,034.1, leptin-insulin signaling: 8,031.3) emphasize the strong statistical weight of these findings. These results further support the notion that metabolic dysregulation arises from integrated signaling cascades rather than isolated genetic or environmental inputs.

Metabolite-Gene Interactions

Our analysis of HMDB metabolites revealed significant correlations between metabolically active compounds—including androstenedione, estradiol, and testosterone—and key genetic regulators. Particularly, steroid hormones showed consistent interactions with SHBG and CYP19A1, pointing toward complex feedback mechanisms in hormonal metabolism. The varying odds ratios across metabolites suggest that these interactions operate through non-linear, multi-factorial control systems, likely involving layered regulatory mechanisms that go beyond single-gene effects.

Pharmacological Insights

DrugMatrix analysis identified several compounds—rabeprazole, imatinib, and amitraz—that interact significantly with genes such as SOD2, FGF2, and TNF. These findings offer insight into potential therapeutic targets and highlight opportunities for drug repurposing or novel intervention strategies. The data underscore the importance of incorporating genetic context into pharmacological planning, supporting the advancement of personalized medicine approaches that align treatments with an individual’s molecular profile.

Inflammatory Pathway Integration

Inflammatory mediators—IL6, CRP, and TNF—were recurrent across multiple enriched pathways, suggesting their pivotal roles as modulators not just of immune function, but also of metabolic homeostasis. This overlap reinforces the emerging view that inflammation and metabolism are deeply intertwined, and challenges traditional compartmentalized models of physiological regulation. Their central presence in both inflammatory and metabolic contexts implies that targeted modulation of these genes could offer dual therapeutic benefits.

Therapeutic Implications

Our findings point toward several strategic directions for targeted metabolic intervention: Modulation of vitamin B12 and folate metabolic pathways. Targeting adipogenesis and insulin signaling networks Exploration of hormone-gene-metabolite interactions. Development of individualized pharmacological regimens based on genetic profiles.

Precision Medicine Opportunities

The integration of gene, metabolite, and pathway data reveals a highly individualized metabolic landscape. These insights could serve as a foundation for precision medicine strategies, enabling clinicians to tailor interventions based on a patient’s unique genetic and metabolic profile. Such an approach holds promise for improving both therapeutic efficacy and safety.

Limitations and Future Directions

Despite the robustness of our findings, several limitations must be acknowledged: The cross-sectional nature of the dataset limits causal inference. Population-specific genetic variations may affect generalizability. Functional validation of computational predictions remains necessary.

Future research should focus on

Longitudinal studies to track metabolic and genetic dynamics over time. Experimental validation of key gene-pathway-metabolite interactions. Stratification of genetic variability across diverse populations.Development of integrative computational models that simulate multi-omic interactions.

Conclusion

This study highlights the remarkable complexity of metabolic regulation, underscoring that physiological outcomes emerge from dynamic, interconnected networks rather than linear pathways. Our integrative approach has uncovered new relationships among genes, metabolites, and therapeutic agents, offering a blueprint for future research and clinical innovation. By mapping these systems-level interactions, we move closer to both understanding fundamental biological mechanisms and realizing the promise of targeted, individualized therapies.

Acknowledgement

The authors are thankful to Central Research Laboratory for Molecular Genetics, Bioinformatics, and Machine Learning, Apollo Institute of Medical Sciences and Research, Chittoor Murukamabttu, Andhra Pradesh, India, for providing necessary facilities and support. 

Funding Sources

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Conflict of Interest

The authors do not have any conflict of interest.

Data Availability Statement

This statement does not apply to this article.

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval.

Informed Consent Statement

This study did not involve human participants, and therefore, informed consent was not required.

Clinical Trial Registration

This research does not involve any clinical trials.

Permission to reproduce material from other sources

Not Applicable

Author Contributions 

Usha Adiga -Conceptualization, Methodology, Writing – Original Draft

Sampara Vasishta -Data Collection, Analysis, Writing – Review & Editing

PeddaReddemma. Petlu -Visualization, Supervision

References 

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Abbreviation List

Gene editing employs endogenous DNA repair mechanisms to introduce precise, targeted modifications into the human genome, significantly advancing genetic research. Gene editing is a process that make use of the biochemical processes that naturally repair DNA damage. Various nuclease mechanisms are able to introduce DNA breaks at specified sites in the genome. The Cas9–sgRNA gene editing platform, which is based on the bacterial adaptive CRISPR immune system, has gained attention in gene editing recently and is now a standard procedure in many research laboratories across the globe due to the ease of use.¹ Recombinant DNA technology is a set of techniques used to recombine (join) DNA Segments of two or more distinct DNA molecules which are put together to produce a recombinant DNA molecule. A recombinant DNA molecule is able to enter a cell and replicate there under specific conditions, either by itself or by following chromosome integration.² Any species provide DNA sequences that are used to generate recombinant DNA molecules. In some cases, bacterial and plant DNA are put together, or fungus and human DNA are mixed. The chemically-mediated creation of DNA also produces DNA sequences that are not found in nature and incorporate them into recombinant molecules. It is possible to create and introduce any DNA sequence into a wide range of living organisms through the use of synthetic DNA and recombinant DNA technology.³

Infertility

A reproductive disorder known as infertility that affects both sexes and is marked by infertility following a period of regular, unprotected sexual activity lasting twelve months or longer.⁴ It is classified into two types: primary infertility, which occurs when there has never been a successful pregnancy, and secondary infertility, which occurs when there has been at least one successful pregnancy but still no baby.

Male Infertility

Male infertility is typically characterized by issues with sperm ejection, low sperm count, or poor morphology and motility.⁵ Spermatogenesis comprises a sequence of cellular processes, such as mitosis-induced self-renewal of spermatogonial stem cells and spermatogonia, spermatocyte transformation and differentiation, meiosis I/II-induced haploid spermatid generation, and spermiogenesis-induced final morphological maturation of spermatids to become spermatozoa. Thus, these processes entail a variety of cellular activities in the testis and are intricately regulated by signalling and hormonal axes.^6-10

Female Infertility

Infertility in the female reproductive system originate from problems in the ovaries, uterus, fallopian tubes, and endocrine system, among other factors⁵. In the female embryo, a number of intraovarian and extraovarian components regulate the highly complex process of creating gametes, leading to a progeny organism.¹¹ The process through which the oocyte, is formed is known as oogenesis. There are many interactions between the developing oocyte and the granulosa and cumulus cells that surround it in this multi-step process. When oogonia are formed from primordial germ cells (PGC), about the 12th week of a woman’s pregnancy, oogenesis starts in the foetal ovaries as soon as the embryo’s development expands.^12-15

Figure 1: Flow chart representing stages of spermatogenesis, germ cell characteristics in each stage and compartments of seminiferous tubules.16 Click here to view Figure

Figure 2: This diagram illustrates the process of oogenesis which begins with transformation of the oogonia into mature oocyte.17  Click here to view Figure

Evolution and Milestones of Crispr Technology

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR) were initially identified in the genomic DNA of Escherichia coli by Ishino et al. (1987) at Osaka University, Japan.¹⁸ Subsequently, in 1995, Francisco Mojica, a Spanish microbiologist, significantly advanced the understanding of CRISPR loci by identifying analogous sequences in the archaeal genome of Haloferax mediterranei, thereby suggesting a conserved function across prokaryotic domains.¹⁹ The first experimental evidence elucidating the functional mechanism of the CRISPR-Cas system emerged in 2007 through studies conducted on Streptococcus thermophilus, a bacterium used in yogurt fermentation. This research was led by Rodolphe Barrangou and Philippe Horvath under the auspices of the Danish biotechnology firm Danisco.²⁰ Since the 1980s, Danisco had developed an extensive repository of bacterial strains, enabling detailed analyses of bacteriophage-host interactions. These investigations revealed the adaptive nature of the CRISPR system, wherein the incorporation of novel spacer sequences into the CRISPR locus correlated with acquired immunity against corresponding bacteriophages. Building on these findings, the researchers pioneered a CRISPR-based strategy for bacterial immunization, culminating in one of the earliest patents in this domain, filed in 2005.^21,22 The CRISPR-Cas9 system relies on a small RNA molecule that is processed and transcribed from the CRISPR locus. This molecule directs Cas proteins to external nucleic acid sequences that contain identical genetic information. A study group headed by John van der Oost at Wageningen University in the Netherlands was the first to identify these RNA components, which are called CRISPR RNAs (crRNAs).²³ Essential for in vitro reconstituting of the CRISPR-Cas9 system, an extra short RNA molecule involved in crRNA maturation was found in 2011 by Emmanuelle Charpentier’s lab. The activation of Cas9 nuclease activity was demonstrated to require this RNA, which is known as trans-activating CRISPR RNA (tracrRNA). A significant step towards the programmable and practical use of the CRISPR-Cas9 system for genome editing was the conceptual advancement that crRNA and tracrRNA are created into a single chimeric RNA, called single-guide RNA (sgRNA).^24,25

Figure 3: The historical chronology of the CRISPR-Cas9 system’s component findings.26 Click here to view Figure

Components of CRISPR

CRISPR/Cas systems are broadly classified into two major classes based on the structural organization and functional characteristics of their associated Cas proteins: Class I, comprising types I, III, and IV, and Class II, comprising types II, V, and VI.²⁷ Class I systems utilize multi-subunit protein complexes to mediate interference, whereas Class II systems rely on a single, multifunctional Cas protein to perform the same function. Two fundamental elements are required for the CRISPR/Cas9 system to function: the Cas9 endonuclease and the guide RNA (gRNA).  Genome editing initially made use of the Cas9 protein, which originated from Streptococcus pyogenes (SpCas9).  The capacity to produce specific double-stranded DNA breaks at specific places has earned this big, multidomain protein, which contains 1,368 amino acids, the nickname “molecular scissor”.²⁸  The two primary structural domains of Cas9 are the recognition (REC) and nuclease (NUC) domains.  The REC lobe, which is made up of the REC1 and REC2 domains, helps with target recognition by binding the guide RNA.  A number of domains are located in the NUC lobe. One of these is the RuvC nuclease domain, which cleaves the non-target DNA strand. The other is the protospacer adjacent motif (PAM)-interacting domain, which binds to the target DNA’s PAM sequence and guarantees sequence specificity.²⁹ An 18–20 nucleotide sequence complementary to the target DNA is found in the CRISPR RNA (crRNA) component of the guide RNA, while a scaffold of stem-loop structures required for Cas9 binding and activation is formed by the trans-activating CRISPR RNA (tracrRNA).²⁸ These RNAs work in tandem to enable site-specific DNA cleavage by directing the Cas9 protein to particular genomic locations.

CRISPR–CAS System Mechanism

The three main steps of the CRISPR/Cas9 system for editing genomes are identifying targets, cleaving DNA, and repairing damaged DNA.³⁰ Synthetic single-guide RNAs (sgRNAs) contain CRISPR RNA (crRNA) components that base-pair with complementary sequences in the target gene, directing the Cas9 endonuclease to the target DNA. When sgRNA is not present, Cas9 stays in an inactive state. Cas9 will insert a double-strand break (DSB) at a position three nucleotides before the protospacer adjacent motif (PAM)³¹ when base pairing is successful. Although the precise sequence and length of the PAM differ among bacterial species, it is usually a brief, conserved DNA sequence located just downstream of the target site and usually ranging from 2 to 5 base pairs in length. The most popular version used for genome editing, SpCas9, which is derived from Streptococcus pyogenes, identifies the PAM sequence 5ʹ-NGG-3ʹ. Despite our limited understanding of the exact molecular mechanism, Cas9 is able to unwind local DNA strands and generate an RNA-DNA heteroduplex by recognising the PAM site. The catalytic domains of Cas9 are activated by this conformational shift. The DNA strand that is complementary to the sgRNA is cleaved by the HNH domain, and the DSBs that are caused by the RuvC domain are mainly blunt-ended. The endogenous DNA repair pathways of the host cell then fix these breaks, finishing the genome editing process.^28,32

Figure 4: This represents successive steps of CRISPR/Cas9 system which includes target identification and modification of gene.33 Click here to view Figure

Some DNA strands experience double-strand breaks (DSBs). The crRNA directs Cas9. TracrRNA stabilizes a structure before Cas9 enabling to break the target DNA. sgRNA is responsible for target gene recognition [sgRNA (teal)].³⁴ These domains (RuvC, HNH) then interact with the Cas proteins to effectively modify the genomes of different animals by introducing DSBs in the DNA at specific locations. The HNH (histidine–asparagine–histidine) nuclease domain of Cas9 cleaves the DNA strand complementary to the guide RNA, whereas the RuvC-like (resolvase C-like) nuclease domain cleaves the non-complementary strand.³⁵ In both type I and type II CRISPR/Cas systems, the target of interference is foreign DNA containing a protospacer adjacent motif (PAM), a short, conserved sequence essential for target recognition and cleavage. The Cas9 protein breaks the target DNA on both strands using its RuvC and (HNH) domains. For Cas9 to break DNA, it primarily requires the PAM sequence. A 20-base stretch offers selectivity for binding in sgRNA. There are two methods for repairing DNA DSBs: HDR, which requires the presence of a template which results in NHEJ, a loose but permanent knockout of a gene, or knock-in or gene replacement.³⁶ In type I and type II CRISPR/Cas systems, only foreign DNA sequences containing a protospacer adjacent motif (PAM)—a short, conserved nucleotide sequence—are specifically recognized and targeted for interference.³⁷

Figure 5: CRISPR and the Cas9 nuclease mechanism are represented in symbolic terms.38 Click here to view Figure

The basic mechanism by which all living things sustain their generations is reproduction. Recently, a novel, adaptable genome editing technique called CRISPR/Cas9 was developed to fix genetic abnormalities that cause a number of diseases, expanding its ability to enhance reproductive health.³⁹ Using CRISPR and ARTs together has made it easier to modify the genomes of embryos created using IVF and other similar procedures. CRISPR/Cas9 is especially useful when it comes to IVF. IVF-produced embryos have the potential to have particular genes disrupted or edited by CRISPR, which could improve particular features or prevent hereditary diseases.⁴⁰ In general, CRISPR technology has the capacity to improve IVF results and encouraging the development of new uses for the reproductive systems of both men and women.⁴¹

Application of CRISPR in Reproductive Biology

SPERM

Genome editing technologies have the ability to revolutionize spermatogenesis research and shed light on the molecular mechanisms behind male infertility disorders. This was demonstrated by the successful application of CRISPR/Cas9-mediated gene editing in mouse spermatogonial stem cells (SSCs).⁴² An effective and easily accessible in vivo method for studying gene function during spermatogenesis is the CRISPR/Cas9-based spermatogenic cell-specific knockdown system.⁴³ A proof of concept was carried out in rat SSCs using targeted gene editing at the Epsti1 locus. This locus is involved in epithelial-stromal interactions, and the results showed that the genome could be effectively modified. Epsti1 mutations in humans have been linked to changes in sperm function, which is worth noting.⁴⁴ With SSCs readily available, a potential platform for homology-directed repair (HDR) mediated by CRISPR/Cas9 to address harmful mutations has emerged. This method has been proven effective in a model of cataract in mice by restoring normal gene function after an ex vivo correction of a disease-causing mutation in SSCs using CRISPR-Cas9 and HDR.^45-47 These results raise the possibility that recovering spermatogenesis in individuals with genetically-caused non-obstructive azoospermia (NOA) could be possible through targeted gene editing in SSCs.⁴⁸

OOCYTE

Generating genetically modified female germ cells for use in assisted reproductive technologies (ARTs) has been made possible by the CRISPR/Cas9 system, which has shown great promise in genetically modifying developing oocytes. These changes could be useful in preventing off-target mutations from being passed down across generations. Oocytes are a good candidate for germline modification because they are easily accessible. To test the efficacy and accuracy of CRISPR/Cas9-mediated gene editing, oocytes must first reach the germinal vesicle (GV) stage of in vitro maturation, and then the following meiotic development is required.³⁹

Numerous animal models, including pigs and mice, have demonstrated the successful use of CRISPR/Cas9 to mammalian oocytes and embryos. It is possible to treat hereditary diseases by directly modifying the genome at these early phases of development. To further our understanding of the molecular pathways essential for embryogenesis, genome editing techniques in oocytes and embryos enable in-depth mechanistic research of early developmental processes.⁴⁹

The dCas9-DNMT and dCas9-TET complexes are epigenome editing tools that have been used to alter DNA methylation patterns in embryos and oocytes from mammals. To fix aberrant methylation linked to familial Angelman syndrome, for instance, microinjected dCas9-TET-based systems have been used in mice oocytes.⁵⁰ Furthermore, a CRISPR-based approach integrating sgRNA and dCas9-DNMT3a has been used to successfully edit seven separate genomic imprinting loci in single unfertilised oocytes, leading to the production of genetically changed children after fertilisation.⁵¹ In light of these developments, studies investigating oocyte methylation have gained popularity as a possible strategy for the treatment of non-genetic maternal hereditary disorders.⁵²

Researchers have shown that injecting Cas9 cRNA into metaphase II (mII) oocytes before sperm and guide RNA (gRNA) has the capacity to increase editing efficiency, prolong Cas9 expression, and improve the results of genome modification. Edited embryos and healthy offspring could be produced using this co-injection technique.⁵³ To further emphasise the significance of timing genome editing with DNA synthesis and particular cell cycle stages for optimal efficiency, it was found that inserting CRISPR/Cas9 components into M-phase oocytes successfully removed mosaicism in cleaving embryos.⁵⁴

Even in mature oocytes with condensed chromatin, CRISPR/Cas9 was able to elicit high-efficiency alterations, according to the experimental findings. Gene editing is not the best approach for GV-stage oocytes, but they are made more mutable by blocking nuclear export and raising nuclear Cas9 levels. There were no negative impacts on meiotic progression or early embryonic development observed in pig models when CRISPR components were microinjected into immature oocytes.^55-59 Genome editing in oocytes going through meiosis confirmed their eligibility as targets for CRISPR/Cas9-based therapies, as it led to a noticeably increased mutation efficiency.^60,61

EMBRYO

To correct pathogenic mutations in the germline, an optimized CRISPR/Cas9-based strategy has been developed that leverages the endogenous DNA repair mechanisms active in early embryos. This approach enabled the precise, efficient, and accurate correction of a heterozygous mutation in the MYBPC3 gene—implicated in hypertrophic cardiomyopathy (HCM)—in human preimplantation embryos. This was achieved by co-injecting sperm, Cas9 protein, guide RNA (gRNA), and single-stranded oligodeoxynucleotides (ssODNs) into metaphase II (MII) oocytes, without inducing significant off-target effects or large deletions.^62-64

When it comes to in vitro fertilization and preimplantation genetic diagnosis, the CRISPR/Cas9 method could be used to increase the quantity of embryos available for transfer.⁶⁵ The use of CRISPR on human embryos has the potential for removing all genetic defects from the genome.^66.

Advantages of CRISPR

Mutations are induced on several locations at once with the use of CRISPR/Cas9. Previously, this couldn’t be accomplished in a single round using traditional methods.^67,68 It was necessary to create several mutant mouse lines using these traditional techniques, which necessitated repeated crossbreeding to produce mice with various mutations for study. As established by Wang et al., (2013) who simultaneously targeted the Tet1 and Tet2 genes, CRISPR/Cas9 may target multiple locations.⁶⁷ Because CRISPR/Cas9 has the potential to create homozygous mice in the founding generation, analysis completed much more quickly and researchers are capable to generate more data than ever before by expanding their list of target genes.⁶⁹

In the field of reproductive biology, the development of CRISPR/Cas9 technology is very encouraging. It is possible to thoroughly study the functional roles of potential genes implicated in spermatogenesis by using CRISPR/Cas9-mediated transcriptional suppression. This method allows for the assessment of gene-specific roles in sperm maturation. Furthermore, by fusing CRISPR/Cas9 systems with fluorescent tags, it is possible to establish the chromosomal localisation of genes specific to sperm. By making it easier to see and map spermatogenesis-related gene loci, these methods provide light on important regulatory mechanisms supporting male reproductive function.⁷⁰

Limitations

One of the major challenges in applying CRISPR/Cas9 for gene therapy is the high frequency of off-target effects (OTEs), which have been reported at rates of ≥50% in some studies.⁷¹ Additional limitations of the CRISPR/Cas9 system include unintended on-target effects, suboptimal homology-directed repair (HDR) efficiency, and the persistent difficulty of precisely controlling genome edits.^72–74 These issues raise concerns about the genomic integrity of edited embryos, as unanticipated mutations carry the risk of having deleterious consequences for progeny. As CRISPR technology continues to evolve, previously unrecognized editing errors continue to emerge, highlighting the need for comprehensive assessment and refinement prior to clinical application.^75,76

Furthermore, embryos exhibit a distinct response to CRISPR-Cas9-induced DNA damage compared to somatic cells, a phenomenon not yet fully understood. Editing outcomes in embryos remain highly variable and unpredictable, frequently resulting in diverse forms of genomic damage. Notably, approximately 50% of edited embryonic cells display detectable abnormalities, indicating a high burden of unintended effects. These findings suggest that genome editing protocols optimized for somatic cells are not directly transferable to embryos. The induction of double-strand breaks (DSBs) by Cas9 in embryonic genomes occasionally leads to undetected or inaccurately repaired lesions due to incomplete knowledge of embryonic DNA repair pathways. Collectively, these challenges underscore the current unsuitability of CRISPR-Cas9 for clinical germline genome editing and emphasize the need for further investigation and ethical deliberation before its application in mammalian eggs and embryos.^49,77

Bioethics

An important ethical consideration with CRISPR/Cas9 is the possibility of off-target consequences leading to alterations that were not intended. If such changes occur in germline cells, they could be passed on to future generations, potentially leading to unknown biological consequences. CRISPR/Cas9 safety needs to be improved by increasing its specificity and carefully identifying both desirable edits and off-target modifications.  Another issue is mosaicism, in which certain cells are not altered, resulting in mutant cells that still cause illness and decreasing the efficacy of treatment.⁷⁸ As mentioned earlier, the existing guidelines indicate that CRISPR technology should not be utilized for genetic editing in germ cells or embryos intended for implantation due to the uncertain and serious possible repercussions of off-target editing, the implications of modifying the intended target itself, the emergence of mosaicisms (the existence of two distinct cell lines derived from the same zygote), and the potential creation of new diseases along with the risk of impacting an entire generation of humans with these conditions.⁷⁹

Conclusion

CRISPR/Cas9 technology holds transformative potential in reproductive biology, particularly in the genetic editing of human gametes.  Because of its accuracy, effectiveness, and capacity to target certain DNA sequences, it is a useful tool for repairing genetic abnormalities at the gamete or zygote stage. Pre-fertilization gene editing has shown encouraging results in applications in spermatogonial stem cells (SSCs) and metaphase II oocytes, setting the stage for preventing monogenic hereditary diseases and enhancing embryo quality.  Furthermore, improving embryo selection and combining CRISPR with methods such as preimplantation genetic diagnosis (PGD) are expected to greatly increase the success rates of assisted reproductive technologies (ART).

Although it offers many advantages, significant ethical and technical barriers still prevent CRISPR from being used clinically in reproductive medicine.  There is considerable safety issues related to embryonic mosaicism, off-target effects, and unusual genomic rearrangements. Long-term follow-up research and strict regulatory frameworks are also necessary due to the possibility of irreversible germline changes.  It is also necessary to carefully consider the ethical concerns of heredity, consent for future generations, and institutional concerns.  Future research efforts should prioritize the optimization of target specificity, the minimization of associated risks, and the facilitation of transparent ethical discourse to guide the safe and responsible clinical implementation of CRISPR/Cas9 in reproductive health.

Acknowledgement

We would like to sincerely thank the Principal of Momsoon Academy for his continuous support and encouragement throughout the course of this research work.

Funding Sources

The authors received no financial support for the research, authorship, and/or publication of this article.

Conflict of Interest

The authors do not have any conflict of interest.

Data Availability Statement

This statement does not apply to this article.

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval.

Informed Consent Statement

This study did not involve human participants, animal subjects, or any material that requires ethical approval.

Clinical Trial Registration

This research does not involve any clinical trials.

Permission to Reproduce Material from Other Sources

Not Applicable.

Authors Contribution

Esha Kumari: Conceptualization, Methodology, Writing- Original Draft.

Neha Banu: Data Collection, Analysis, Writing- Review and Editing.

Katrina Marbaniang: Analysis, Editing and Supervision.

Faridha Jane R.M. Momin: Analysis, Editing and Supervision.

Barry Cooper Hynniewta: Visualization, Supervision, Project Administration.

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Abbrevations List

ART – Assisted reproductive technology

Cas9 – CRISPR-associated protein 9

CRISPR – Clustered Regularly Interspaced Short Palindromic Repeats

cRNA – Coding RNA

crRNA – CRISPR RNA

DNA – Deoxyribonucleic acid

DNMT – DNA Methyltransferase

DSB – Double strand break

gRNA – guide RNA

GV – Germinal Vesicle

HCM – Hypertrophic Cardiomyopathy

HDR – Homology-Directed Repair

HNH – Histidine-Asparagine-Histidine

IVF – In vitro fertilisation

MYBPC3 – Myosin-Binding Protein C, cardiac-type gene,

NHEJ – Non-Homologous End Joining

NOA – Non-Obstructive Azoospermia

NUC – Nuclease lobe

OTEs – Off-Target Effects

PAM – Protospacer Adjacent Motif

PGC – Primordial Germ Cells

PGD – Preimplantation genetic diagnosis

REC – Recognition lobe

RNA – Ribonucleic acid

RuvC – Resolvase domain C

sgRNA – Single Guide RNA

SSCs – Spermatogonial Stem Cells

ssODNs – Single-Stranded Oligodeoxynucleotides

TET – Ten-eleven translocation enzyme

tracrRNA – trans-activating CRISPR RNA.

Among oilseed crops, sesame (Sesamum indicum L.) holds significant importance as one of the oldest oil-yielding species, with a history of cultivation spanning more than 3,000 years. Belonging to the family Pedaliaceae and the genus Sesamum, up to 38 species have been identified through morphological and cytogenetic characterization. Sesame is known by different vernacular names across regions, including Til, Gingelly, Benniseed, Sim-Sim, Gergelim, Tilli, Nuvrula, Vellvor, and Rasi. Among the nine major oilseed crops in India, sesame occupies a prominent place and is often referred to as the “Queen of Oilseeds” due to its high-quality oil, pleasant aroma, and remarkable resistance to oxidation and rancidity.¹ Despite its importance, sesame has long been considered an orphan crop owing to its neglect in breeding programs and its relatively low productivity. Currently, the global area, production, and productivity of sesame are estimated at 12,507,504 hectares, 6,741,479 tonnes, and 539 kg/ha, respectively.²

Sesamum is primarily a diploid species (2n = 2x = 26) with a basic chromosome number of x = 8 or 13, although some species have been reported as tetraploids or octoploids.³ Sesame seeds are nutritionally rich, containing 44–47% edible oil, 18–25% protein, 13.5% carbohydrates, 5% ash, 6–8% fiber, and a wide range of antioxidants, including sesamol, sesamin, sesamolin, and sesaminal.⁴ They also serve as a dietary alternative for individuals with breast milk allergies. Most sesame seeds are utilized for oil extraction, while a smaller proportion is consumed directly as food.⁵ Sesame oil, in particular, is valued for its preservative properties due to its strong resistance to oxidative rancidity, even after prolonged exposure to air.⁶

Numerous mutant lines have been developed in sesame using chemical mutagens such as ethyl methane sulfonate (EMS) and sodium azide (SA). Mutation breeding has proven to be an effective strategy for developing promising lines with improved yield, plant architecture, oil quality, and tolerance to biotic and abiotic stresses. It has been successfully applied to generate variability in both qualitative and quantitative traits in several crops, including rice and sesame.^3,7,23

The present investigation was carried out to evaluate the effects of chemical mutagens—ethyl methane sulfonate (EMS) and sodium azide (SA) on the sesame variety TKG-55. The findings aim to support future breeding efforts focused on the genetic improvement of sesame.

Materials and Methods

The experimental material consisted sesame variety TKG-55 procured from RSKVV, Gwalior. The dry seeds of sesame were soaked in distilled water for six hours to initiate imbibition and metabolic activities. Subsequently, they were transferred into solutions of EMS and SA with concentrations of 0.1%, 0.2%, 0.3%, and 0.4%, respectively, for four hours. For each treatment, the volume of solution was kept 50ml and 27⁰C temperature for 400 seeds_.  Multiple washings of treated seeds were carried out using ordinary tap water to remove the residual effect of chemical mutagens. The seeds were further used in laboratory as well as in field exercise, which are mentioned below in brief:

Laboratory Exercise: To assess seed germination percentage, root & shoot length, seedling height, and injury to the seedling, 50 seeds from each treatment, including control, were placed on moist triple-layered blotting paper in petri dishes. Each treatment was maintained with two replications, providing a controlled environment in a seed germinator for germination maintaining at 27⁰C temperature and 75% humidity. The observations were recorded on the 7th day of sowing.

Field Exercise: The treated seeds, along with an untreated control, were sown in the field keeping proper distance in a randomized block design (RBD) with three replications to raise M1generation. All the agronomic practices were carried out for proper growth and development. The observations were recorded from the field on plant height, branches per plant, survival at maturity, pollen viability at blooming stage, no of capsules per plant, length of capsule, seeds per capsule, 1000 seeds weight, and seed yield per plant at harvest stage in the M1 generation.

Statistical analysis

The experiment was conducted in 3 replications and the statistical analysis of the data was done by computer software namely SPSS for RBD design.²⁷

Laboratory observation

The highest germination percentage was noted in the control (91.33%), which was significantly higher than all mutagenic treatments (p < 0.05). Among treated sets, EMS 0.1% (85.67%) and SA 0.1% (81.67%) showed comparatively higher germination, whereas higher concentrations exhibited a progressive decline. Maximum shoot length was also observed in the control (4.19 ± SE cm), which was statistically at par with SA 0.1% (4.15 ± SE cm), but significantly higher than EMS 0.1% (3.74 ± SE cm). The greatest reduction in shoot length was noticed at EMS 0.4% (1.40 ± SE cm) and SA 0.4% (1.50 ± SE cm), both of which differed significantly from the control. A similar trend was observed for root length, where the control (3.38 ± SE cm) recorded the maximum, followed by SA 0.1% (3.31 ± SE cm) and EMS 0.1% (2.72 ± SE cm). The minimum root lengths were obtained at EMS 0.4% (0.50 ± SE cm) and SA 0.4% (0.62 ± SE cm), showing statistically significant reductions. Seedling height followed the same trend, with the control exhibiting the maximum height (7.63 ± SE cm), statistically similar to SA 0.1% (7.27 ± SE cm), while the lowest values were recorded in EMS 0.4% (1.98 ± SE cm) and SA 0.4% (2.12 ± SE cm). Seedling injury increased significantly with higher concentrations of mutagens, being maximum in EMS 0.4% (74.17%) and SA 0.4% (72.78%), while the lowest was found in SA 0.1% (4.41%) and EMS 0.1% (16.55%). Pollen viability data indicated the highest value in the control (93.37%), which was significantly higher than EMS 0.4% (77.26%) and SA 0.4% (75.30%). Intermediate values were recorded in combination treatments (89.21%), SA 0.1% (87.35%) and EMS 0.1% (86.92%).

Field observation

The highest germination percentage was reported in the control (93.50%), which was statistically at par with 0.1% EMS and 0.1% SA (92.00%), but significantly higher than higher concentrations of mutagens (p < 0.05). The minimum number of days to 50% flowering was observed in the control (31.33 ± SE days), followed by 0.1% EMS, 0.1% SA, and 0.2% SA, whereas the maximum delay was noted with 0.4% SA (39.33 ± SE days), showing a significant difference from the control. Similarly, the shortest time to maturity occurred in the control (85.33 ± SE days), statistically similar to 0.1% EMS and 0.1% SA (87.33 ± SE days), while the longest maturity duration was recorded in 0.4% SA (93.33 ± SE days). Survival percentage at maturity was maximum in the control (90.46%), which was statistically superior to 0.4% EMS (66.86%) and 0.4% SA (77.50%). Among treated sets, 0.1% EMS (86.38%) and 0.4% SA (82.50%) showed comparatively higher survival. Maximum plant height was obtained under the combination treatment (EMS + SA) at 118.50 cm, which was significantly higher than all other treatments, followed by the control (114.25 cm), 0.1% SA (112.61 cm), and 0.1% EMS (106.54 cm). The lowest plant height was recorded in 0.3% EMS (101.97 cm). The highest number of branches per plant was noticed in 0.1% SA (6.40), which was significantly higher than the control (5.40) and comparable to 0.2% EMS (5.80). The maximum number of capsules per plant was produced by 0.4% SA (46.60), followed by 0.1% EMS (45.20), while the control exhibited significantly fewer capsules (35.43). Capsule length was greatest in the control (2.61 ± SE cm), which was statistically similar to 0.2% SA (2.48 cm), 0.1% SA (2.46 cm), and 0.1% EMS (2.45 cm). The number of seeds per capsule was significantly highest in 0.2% SA (52.53), followed by 0.3% SA (51.97) and 0.1% EMS (50.32). The maximum 1000-seed weight was noted in 0.2% SA (3.72 g), which was statistically at par with 0.3% SA (3.62 g) and 0.2% EMS (3.61 g). Seed yield per plant was significantly highest in 0.1% SA (8.44 g), followed by 0.3% SA (8.11 g), while the control found 6.17 g. Overall, seed yield per plant showed an inverse relationship with the intensity of mutagen dose.

Mean performance for all the seventeen characters under investigation

Result

Result obtained in the present investigation in laboratory conditions on 7^th days seed germination, shoot length, root length, seedling height, seedling injury, and pollen viability in M₁ generation of sesame variety TKG-55 are as under.

Discussion

A progressive reduction in seed germination was observed with increasing concentrations of EMS and SA, which is consistent with earlier reports.^9-11 Similar dose-dependent effects on germination have been documented in other crops,¹² and reductions with higher doses of gamma rays, EMS, and SA were also reported in horse gram.¹³ The decline in germination is generally attributed to cellular, physiological, and molecular disturbances caused by mutagens.¹⁴

Regarding vegetative traits, significant reductions in shoot length, root length, and seedling height, along with increased seedling injury at higher concentrations of mutagens, were consistent with previous studies.^15-17 These effects can be linked to mutagen-induced damage in actively dividing cells, which interferes with normal growth and development.

For reproductive traits, a linear decline in pollen viability was evident with increasing mutagen doses, in agreement with findings in groundnut,^18-20 lentil, and soybean.^21-23 The reduction in viability is likely due to physiological and chromosomal damage, resulting in the production of non-viable pollen grains and subsequent pollen sterility, as also noted by earlier researchers.²⁴

With respect to yield-related traits, mutagenic treatments generally reduced plant height, capsule length, 1000-seed weight, and seed yield per plant, showing a clear dose-dependent negative trend. However, the number of branches per plant and the number of capsules per plant did not exhibit a consistent linear pattern. These irregular responses may be explained by compensatory growth mechanisms, where reduced growth in one organ is offset by increased growth in another, as well as underlying genetic variability and genotype × environment interactions that modulate the plant’s response to mutagenic stress. Similar complex trends have been reported in earlier studies.^25-26

Therefore, both mutagens altered the chemical composition of the genetic material, which disrupted normal cellular physiology and ultimately had adverse effects on the expression of all evaluated traits.

Conclusion

The optimum dose of EMS was found to be 0.1% for traits such as germination percentage and survival at maturity. For SA, 0.1% was most effective in improving root length, shoot length, seedling height, reducing seedling injury, and enhancing the number of branches per plant, number of capsules per plant and seed yield per plant. A concentration of 0.2% SA was optimal for improving capsule length and the number of seeds per capsule, while 0.3% SA showed the best results for 1000-seed weight. The combination treatments of EMS + SA (0.1% + 0.1% and 0.2% + 0.2%) were found to be most effective for improving plant height and pollen viability. Additionally, early flowering and early maturity were associated with the 0.1% doses of both EMS and SA. Based on the findings of the present study, it can be concluded that a 0.1% concentration of both EMS and SA may be considered optimal and beneficial for further crop improvement in sesame.

Acknowledgement

I am extremely grateful to ITM University Gwalior, M.P. for providing me all the necessary facilities for the completion of this research.

Funding Sources

The authors received no financial support for the research, authorship, and/or publication of this article.

Conflict of Interest

The authors do not have any conflicts of interest.

Data Availability Statement

This statement does not apply to this article.

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval.

Informed Consent Statement

This study did not involve human participants, and therefore, informed consent was not required.

Clinical Trial Registration

This research does not involve any clinical trials.

Permission to reproduce material from other sources

Not Applicable

Author Contributions

Pratima Jaiswal- Data collection

Priyanka Gupta-Analysis the data and aided as major advisor.

Lakshman Singh- Wrote the research article (Introduction, Material & Methods, Tables, Results and discussion and aided as co-advisor.

Harendra- Made all possible corrections before and after sending the manuscripts.

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Abbreviations List

 EMS- Ethyl Methane Sulphonate

SA- Sodium Azide

One of the foremost critical cereal crops cultivated around the world is maize (Zea mays L.)and it positions third after wheat and rice generation. It is the most widely distributed crop with greater adaptability¹. Around 790 million tons of maize are produced worldwide, and in certain nations, it is a staple grain that provides calories and proteins^{2 .}The demand for maize will double in the developing world by 2050, and by 2025, it will be the most important crop produced both globally and in the developing world.^3,4

Salinity is the most important abiotic stressor that prevents crop growth and productivity. Salt stress adversely affects plants’ functioning and metabolism and significantly hinders productivity⁵. Diffusion adjustment of halophytes and glycophytes is accomplished by improving organic and inorganic solutes. Therefore, a more significant decrease in cell substance potential than the external salt concentration could indicate a diffusion adjustment. Organic solutes are accumulated within the cytoplasm to balance the solute potential of the cavity, which is dominated by ions. It is noticed that the germination and seed plant stage of vegetation cycle is sensitive to salinity than the adult stage⁶. Plants response to salinity is one the foremost wide researched subjects in plant physiology^7. Salinity affects plants in several ways diffusion affects specific particle toxicity and nutritionary disorders. It does not solely affect the morphology; however, it additionally modifies the metabolism of plants by limiting their growth.

The impact of proteins can be seen by observing the physiological responses to both osmotic and ionic effects of salinity. Considering the osmotic effect which causes not only a significant osmotic but also mechanical stress on plant cells, an enhanced biosynthesis of several somatically active organic compounds as well as proteins with osmoprotective functions such as LEA(late embryogenesis abundant) proteins could be mentioned.⁸

Proteins are expected to be significantly impacted by how plants react to environmental stresses such soil salinity. Large-scale changes in stress conditions will result in the identification of proteins and their corresponding genes that are concerned with the physiology of salt resistance. Utilizing 2D and mass spectrometry of controlled proteins whose blend was modified by salt treatment, a tall determination is gotten.

This work aimed to carry out proteomic analysis of the genes related to find out if they are tolerant or sensitive to salt stress. The purpose of this study was to learn more about the impact of salt stress and proteomic analysis in maize hybrids (Zea maize. L).This work pointed to carry out proteomic investigation of the qualities related to discover out on the off chance that they are tolerant or delicate to salt stretch. The reason of this consider was to learn more almost the affect of salt stretch and proteomic investigation in maize half breeds (Zea maize. L). 

Materials and Methods

Conditions for plant growth and material

The popular Maize hybrids NK6240, M900Gold, were used for study as these hybrids are widely accepted by farmers due to high yield and stability. After five minutes of surface sterilization with a 1% sodium hypochlorite solution, the seeds were rinsed with distilled water. Surface sterilized seeds were pre-soaked in Petri plates with different levels of salinity (50mM, 100mM, 150mM of NaCl) for 40 min taking control with distilled water. We kept the treated seeds on wet Whatman no. In acid-washed Petri dishes, place one filter paper and incubated in dark at 27°C overnight. The next day, they are transferred to pots filled with acid-washed sand. The plants were cultivated in a greenhouse with natural light conditions, which included air temperatures between 27°C and 35°C, light intensities between 450 and 500 mmol/m2/s, and a relative humidity of 75%⁹.

Each pot containing five plants was supplied with 20mL of water and N:P:K (10:10:10) nutrient solution on alternate days. Harvested two weeks after germination, the plants were dried in a thermally ventilated oven at 70°C until they reached a consistent mass for dry weight calculation. Standard procedures were followed in the calculation of growth parameters, including fresh weight, dry weight, number of roots, root length, shoot length, leaf surface area, and shoot length. Various biochemical analyses were conducted on leaf samples from maize plants that were two weeks old.

Growth analysis of plants

Plants were carefully uprooted after nine days and washed with distilled water. Shoot and root length were measured with the help of scale. Plant fresh weight was noted by electronic balance; one set of plants was taken for 2D analysis, germination, and biochemical parameters analysis; another set was kept in a hot air oven at 70⁰C. Dry weights of plants were calculated with the help of electronic weighing balance after 4 days of incubation in a hot air oven. Plant-1 g is used to represent both fresh and dry weights.

2Dimentional Electrophoresis

Harvest and protein (sample) preparation for 2D Electrophoresis

After harvesting the plant material, a whole plant sample was gathered and homogenized using liquid nitrogen. The fresh and dry weight of the complete leaf material is determined. The tissue was ground under liquid nitrogen to break up the leaf material. Since lowering the temperature of the cell material inhibits the activity of the protease, all stages of the protein extraction process were conducted at 4˚C. The addition of metabolite extraction buffer (MEB) is followed by five minutes of homogenization. After 20 minutes of centrifuging the solution (Eppendorf 5810) at 4˚C, the supernatant was gathered and placed in a separate tube. The use of MEB such as Methanol, Chloroform and Water contents is to remove metabolites from protein sample. To the protein pellet, SDS buffer (Sodium dodecyl sulphate, Dithiothreitol, Tris) supplemented by protease inhibitor cocktail and PMSF (phenylmethylsulfonyl fluoride) was added. For 1g of tissue, 5mL of SDS buffer was added. After vortexing, the samples were incubated for 1hr on Gel rocker (Genie). Centrifugation was carried out for 15 minutes at 4˚C and 10,000 rpm. Separate the pellet (which was kept at -80°C) and add equal amounts of Tris-buffered Phenol (Sigma) to the supernatant (SDS buffer). Shake for 30 minutes at room temperature. At 4˚C, centrifuged for 30 minutes at 10,000xg.

Six volumes of a 100 mM ammonium acetate/methanol solution were added to the lower phenol layer. Centrifuge at 10,000xg for 15 minutes at 4˚C after incubating overnight at -20˚C. After removing the supernatant, wash the pellet in acetone that has been chilled beforehand and centrifuge it for 15 minutes at 4˚C at 10,000 rpm. This process was carried out twice. The pellet should be allowed to air dry before being dissolved in rehydration buffer (7M urea, 2M thiourea, 0–5 percent pharmalyte buffer (v/v, pH 3–10); 4 percent CHAPS; 30mM DTT; 20mM Tris–base, pH 8.8). 0.3mL of rehydration buffer was added to the pellet for solubilization of proteins. From each sample 10µL was loaded on to the 1D gel for normalization of the concentrations. 

Isoelectric focusing (IEF) and 2D PAGE

50 µL of the sample was diluted with 250µL of rehydration buffer. Each sample was loaded on to the isoelectric focusing strip 4-7pH gradient Linear (GE), 18cm for rehydration of the samples by applying the following conditions: 10hrs rehydration; Temperature -20°C. It was done in an IPGphor chamber (GE) to focus the strips isoelectrically. Before the gels were put in the IEF cell, mineral oil was applied on top of them. Rapid ramping of the voltage from 250V to 10,000V was used, and the current was 45mA per strip until 70000V was reached. Following the completion of the first dimension, the strips were submerged in equilibration buffer (50 mM Tris–HCl, pH 8.8; 6M urea; 30% glycerol; 2% (w/v) SDS; bromophenol blue, 0.001 percent (w/v) containing 1% DTT (w/v)) and gently shaken for one hour. The strips were then incubated for a further forty-five minutes with slow stirring in equilibration buffer containing four percent (w/v) iodoacetamide without DTT. The strips were washed several times with SDS-PAGE running buffer (25mM Tris–base; 192mM glycine; 0.1% (w/v) SDS). The second dimension was obtained with 10% SDS gels. The gel was loaded with a molecular weight standard (Biorad) of 10 to 250 kDa in 10 to 250 kDa.

The basic side (pH-7) of the gel was where marker lane was placed. Marker dyes and strips were applied to the gel surface, and the mixture was sealed with 1% (w/v) agarose that contained 0.01% (w/v) bromophenol blue. The second dimension was done in a vertical gel electrophoresis chamber (Ettan Dalt Six unit) at 25°C with a steady current of 45mA per gel. When the bromophenol blue departed the gel, the electrophoresis was terminated. After being taken out, the gels were left in a fixative containing 50% methanol and 10% acetic acid for the entire night.

Staining and Image Analysis

The gels were submerged in a 0–0.02% sodium thiosulfate solution for two hours with three changes, and then they were briefly rinsed with water. Following that, the gels were incubated for one hour in a solution containing 0–2% silver nitrate. A 2 percent sodium carbonate solution was used to develop the gels following a quick water wash. Following the cessation of the reaction, the gels were preserved in 10% acetic acid.

2D Analysis

Gels were digitized by scanning on Epson XL 11000 with 300 dpi and computer-assisted 2D analysis The protocol was performed using Image Master 2D Platinum software version 7.0.6 (GE Healthcare). The total number of spots on the gels is calculated using the software and the spots that are differentially expressed between the two samples are identified. 

Software Parameters

The area of interest was chosen by cropping the gels and the spots were detected using parameters like smooth with a limit of 2, a minimum area with a limit of 5 and saliency with a limit of 5. After spot detection, every spot is checked manually for a real spot since the software detects clouds of dust, artefacts, which need to be removed from the analysis. The spots are then manually edited using options like create, delete, split, merge, grow and shrink. The spots that are located at precisely the same spot on each gel are used as landmarks. The landmarked spots aid in precisely matching the gels. Following the completion of the gel matching, the data analysis is finished. All spots in the gels are automatically matched by the software, which also assigns spot ID to every spot in the gel set and match ID to the spots that match in the gels.

The protein spots can be represented in the form of 3D with the peak height denoted as its intensity. The program annotates all of the remaining spots after determining the molecular weight and pI for a small number of spots on the corresponding gels. The data obtained after matching the gels were stored in the form of Spot Table, Gel Table, Scatter Plot, Gel Analysis Table, Match Statistics Table, Annotation Table etc.

To analyse differential expression investigation, the coordinated spots of the treated gel are differentiated with those of the control. The differentially communicated (overlap alter) spots between the gels are gotten by taking the spot percent volumes. A overlap alter can be calculated by separating the rate volumes of treated spots by the rate volumes of control spots with the same coordinate ID. This proportion shows that all of these spots are over-expressed in the event that it is more prominent than 1.5, and under-expressed in the event that it is less than 0.5. Special protein spots that are as it were found in that gel will be display within the spots that did not coordinate in both gels. In 2D gels, each spot speaks to a protein or polypeptide, either with or without a post-transcriptional adjustment.

In-gel Digestion and Mass Spectrometry

Excised gel spots were cut into pieces and taken into neatly labelled Eppendorf. Gel pieces were first washed with MS Grade water and then destained using 15mM K3 [Fe (CN) 6] and 50mM Hypo in 1:1 ratio. Buffer washes were done using 25mM ammonium bicarbonate, pH 8.5, in MS Grade water, then 50% acetonitrile in the same buffer, the gel plugs were then dehydrated using 100% acetonitrile. Sequencing-grade (Promega) trypsin was used to digest the gel plugs, which were then reduced with 100 mM dithiothreitol, alkylated with 250 mM iodoacetamide, and incubated in 25 mM ammonium bicarbonate for the entire night at 37˚C. The peptides were collected in an Eppendorf after being extracted three times using 0–1 percent trifluoroacetic acid (v/v) in 50 percent acetonitrile (v/v) following incubation. Following vacuum drying, the extracted peptides were redissolved in a 1:2 ratio of 0–1% (v/v) trifluoroacetic acid in 100% acetonitrile. The peptides that were extracted were combined with HCCA (α-Cyano-4-hydroxycinnamic acid) matrix in a 1:1 ratio (5 mg/mL α-Cyano-4-hydroxycinnamic acid) in a 1:2 ratio of 0–1 percent TFA and 100 percent ACN. The resulting 2µL was spotted onto the MALDI plate [(MTP 384 ground steel (Bruker Daltonics, Germany)]. Following air drying, the sample was examined using the MALDI TOF/TOF ultra flex III instrument. 

Results

Germination

Salt stress adversely affects the growth of the maize plants though the germination rate was quite appreciable. The NK6240 and M900Gold varieties of maize were induced by different salt concentration ranging from 50-150mM NaCl and their rate of germination was found to be decreased with increasing salt concentration due to alleviated osmotic pressure (Graph 1).

Graph 1: Germination rate of NK6240 and M900Gold maize varieties under varying salt concentrations.  Click here to view Graph

Graph 2: Malondialdehyde(MDA) content  under salt stress induced maize varieties NK6240 and M900Gold Click here to view Graph

Graph 3: Total soluble sugars (TSS) content  under salt stress induced maize varieties NK6240 and M900Gold  Click here to view Graph

Graph 4: Proline  content  under salt stress induced maize varieties NK6240 and M900Gold Click here to view Graph

Graph 5: Free amino acid (FAA) content  under salt stress induced maize varieties NK6240 and M900Gold  Click here to view Graph

Graph 6 : Protein  content  under salt stress induced maize varieties NK6240 and M900Gold Click here to view Graph

Table 1: Legend for table 1: Mean values of NK6240 and M900Gold for various biochemical parameters.

MDA (Malondialdehyde);TSS(Total Soluble Sugars);FAA(Free amino acids) 

Biochemical Analysis

The various biochemical parameters such as malonialdehyde (MDA), total soluble sugars (TSS), Proline content, Free amino acids (FAA) and protein content of germinated maize plants of salt stress are discussed below in detail.

Malondialdehyde (MDA)

The trienoic fatty acids such as MDA directly contribute to reactive oxygen species (ROS) control via non-enzymatic oxidation and is directly correlated with the survival of tissues¹⁰. The maize plants have shown decreasing trend with increasing salt concentration, exhibiting the adaptable nature of the varieties NK6240 and M900Gold (Graph 2).

Total Soluble Sugars (TSS)

The elevated levels of soluble sugars contribute to tolerance of plants against stress conditions¹¹. Similarly, the maize plants have shown increasing levels of TSS with increasing salt concentration (Graph  3). The maize variety M900Gold have shown high levels of TSS than NK6240, indicating its sensitivity against salt stress.

Proline

Proline acts as a osmoregulatory and protects plant proteins against damage and enhances various enzyme activities.¹² Studies indicate that the elevated levels of Proline maintain NADP+/NADPH ratio. The maize varieties have shown elevated levels of Proline initially and then reduction under high salt concentration (Graph 4).

Free amino acids (FAA) and Protein

The free amino acids content was significant very less when compared with the control but have shown increasing trend in a dose dependent manner. Under stress conditions, the physiological process is significantly affected which can be correlated by the elevated protein levels.¹³ All the treated plants have shown elevated protein levels than control (Graph 5, Graph 6). Moreover, the treated have shown decreasing trend with increasing salt concentrations indicating its adaptive nature with high salt concentration. 

Proteomic Analysis

Three up-regulated and four down-regulated proteins were among the seven proteins that were selected for additional investigation following proteomic analysis using 2D electrophoresis and MALDI-TOF-MS.(Table 2).

Figure 1: Representation of 2D gel electrophoresis images of maize hybrids (a) GC control  gel and (b) GT  treated  with NaCl. Click here to view Figure

Table 2: Up-regulated and Down-regulated proteins expressed in two dimentional  electrophoresis.

Functions of up-regulated proteins

OMT8_MAIZE  Benzoate  O-methyltransferase

In reaction to stress, methyltransferases play a role in the biosynthesis of methyl benzoate..  These transferases utilize exclusively benzoic acid as a substrate.  In  our  research  study,  we  induced  saline  stress,  so  that  this  protein  might  be  up-regulated.  An  anthranilic  acid  methyltransferase-one  (AAMT1)  appears  to  be  responsible  for  most  of  the  activity  of  S-adenosyl-L-methionine-dependent  methyltransferase  and  the  formation  of  methyl  anthranilate  observed  in  maize  after  harm  to  herbivores.  The  enzymes  may  also  be  involved  in  the  formation  of  low  amounts  of  methyl  salicylate,  which  are  emitted  from  herbivore-damaged  maize ¹⁴. The methylation of the carboxyl group of several low molecular weight metabolites is catalyzed by plant enzymes belonging to the SABATH methyltransferase family, which is essential to the plant’s life cycle.^15,16. 

IF4E2_MAIZE Eukaryotic translation initiation factor

Eukaryotic  translation  initiation  factor  participates  in  forming  translation  initiation  factor  4f  complex  and  proceed  for  translation.  Beginning, elongating, and terminating are the three stages of the synthesis of mRNA proteins, which is a crucial step in the expression of eukaryotic genes. Acknowledges and attaches itself to the 7-methylguanosine that forms the mRNA cap at an early stage of protein synthesis and encourages ribosome binding by causing secondary structure mRNA unwinding.  In  our  results,  there  is  no  salt  stress  effect  in  translation  processes ¹⁷. Hence  there  is  no  effect  of  salt  stress  on  this  protein.  Hence  this  protein  is  up-regulated. 

PCNA_MAIZE proliferating cell nuclear antigen

This  is  an  auxiliary  protein  of  the  DNA  polymerase  delta  which  is  involved  in  regulating  the  replication  of  eukaryotic  DNA  by  the  process  ability  of  the  polymerase  during  elongation  of  the  leading  strand.  The multipurpose protein PCNA is involved in the synthesis of DNA replication, DNA repair, and recombination-driven DNA. It belongs to the subunit of DNA polymerases d and e, which have both been linked to repair processes such as post-replication repair, NER, BER, mismatch repair, and recombination-driven DNA synthesis¹⁸. Additionally, proteins involved in non-homologous end-joining, homologous recombination, and other crucial DNA replication processes are bound by PCNA¹⁸.  According  to  our  results,  there  is  no  maximum  salt  stress  effect  on  the  role  of  protein  hence  it  is  up-regulated. 

Down-Regulated  Proteins

CRS2_MAIZE Chloroplastic group IIB intron splicing Facilitator CRS 2

This protein plays a role in splicing of group II B introns in chloroplasts. This chloroplast RNA splicing protein complex with either CAF1 or CAF2 which, in turn, interact with RNA and confer introns specificity of the splicing particles. CRS2 has no peptidyl t-RNA hydrolase activity¹⁹. According to our results, salt stress effects are shown on this protein hence this protein has been down-regulated. Maize hybrids growth is also altered when compared to control.

HSP 21_MAIZE (17.5kDa) class II heat shock protein

The main role of this protein is in protein complex oligomerization, protein folding, responding to heat, responding to high light intensity and also responding to hydrogen peroxide. We have applied salt stress in our experiment and all the above biological processes are affected, so this protein has been down-regulated ²⁰. Due to this effect Maize hybrids, growth is also altered when compared to control. 

DER12_MAIZE Derlin-1.2

This protein contributes to the breakdown of particular misfolded luminal proteins in the endoplasmic reticulum (ER). One crucial aspect of this protein quality control is the removal of misfolded proteins. Previous research using a range of soluble and transmembrane associated degradation (ERAD) substrates showed variations in the ER degradation machinery employed²¹. In our study, due to the induction of salt stress in maize hybrids, the role of protein derlin is denied, so this protein has been down-regulated. Also, growth levels of maize hybrids have been decreased due to salt stress when compared to control. 

CDPK_MAIZE Calcium-dependent protein kinase

The main role of the protein calcium-dependent protein kinase in cell involves ATP binding mechanisms, calcium ion binding processes and protein serine /threonine activity controlled by the CDPK. Also, their functions include phosphorylation, which plays important role in plant calcium signal transduction and response to osmotic stresses²². Our results indicate that this protein has been down-regulated due to salt stress and also decrease in their growth levels of maize hybrids. 

Discussion

In the case of gemination of maize varities Salt stress adversely affects the growth of the maize plants though the germination rate was quite appreciable. The NK6240 and M900Gold varieties of maize were induced by different salt concentration and their rate of germination was found to be decreased with increasing salt concentration due to alleviated osmotic pressure.Within the case of gemination of maize varities Salt push antagonistically influences the development of the maize plants in spite of the fact that the germination rate was very calculable. The NK6240 and M900Gold assortments of maize were actuated by diverse salt concentration and their rate of germination was found to be diminished with expanding salt concentration due to lightened osmotic weight.

In the case of  Malondialdehyde (MDA) The trienoic fatty acids such as MDA directly contribute to reactive oxygen species (ROS) control via non-enzymatic oxidation and is directly correlated with the survival of tissues. The maize plants have shown decreasing trend with increasing salt concentration, exhibiting the adaptable nature of the varieties NK6240 and M900Gold.

Total Soluble Sugars (TSS)

The elevated levels of soluble sugars contribute to tolerance of plants against stress conditions. Similarly, the maize plants have shown increasing levels of TSS with increasing salt concentration . The maize variety M900Gold have shown high levels of TSS than NK6240, indicating its sensitivity against salt stress.

Proline

Proline acts as a osmoregulatory and protects plant proteins against damage and enhances various enzyme activities. Our research results  indicate that the elevated levels of Proline maintain NADP+/NADPH ratio. The maize varieties have shown elevated levels of Proline initially and then reduction under high salt concentration.

Free amino acids (FAA) and Protein:

The free amino acids substance was critical exceptionally less when compared with the control but have appeared expanding slant in a measurements subordinate way decreasing   conditions, the physiological prepare is altogether influenced which can be related by the elevated protein levels. All the treated plants have appeared hoisted protein levels than control. Additionally, the treated have appeared diminishing drift with expanding salt concentrations showing its versatile nature with enhanced  salt concentration.

Four proteins down- regulated proteins expressed in salt induced stress which are including

(OMT8_MAIZE)BenzoateO-methyltransferaseBenzoateO-methyltransferase,

(IF4E2_MAIZE )Eukaryotic  translation  initiation  factor,

(PCNA_MAIZE)  Proliferating  cell  nuclear  antigen

Four proteins down- regulated  proteins  expressed  in  salt  induced  stress which are including

CRS2_MAIZE  Chloroplastic  group  IIB  intron  splicing  Facilitator  CRS

HSP  21_MAIZE  17.5kDa class  II  heat  shock  protein

DER12_MAIZE Derlin-1.2

CDPK_MAIZE Calcium  –dependent  protein  kinase

Indicates the  tolerance  of  maize  hybrids  (NK6240,  M900Gold)  to  salt  stress  and  is  indicated  by  proteomic  analysis.  Also,  our  data  demonstrated  that  salt  stress  reduces  the  deleterious  effects  of  soil  salinity  and  drought  in  the  maize  plant.

Summary

Our research results  showed that salt stress lessens the negative effects of drought and soil salinity on maize plants. Abiotic stressors like drought and salinity affect maize yields by causing physiological and biochemical alterations like ionic imbalance and decreased photosynthesis. According to study findings, salt stress can lessen the negative effects of drought and soil salinity on maize plants. Finding hybrids that can withstand salt, such as NK6240 and M900Gold, is essential.

Conclusion

In the global economy and food industry, maize plays a significant role. In terms of production and cultivated area, it is currently ranked second in importance, after rice. Thus, it is crucial to preserve maize under abiotic stressors such as salt stress, UV stress, metal stress, and cold stress. Our findings, which were supported by proteomic analysis, demonstrated that the maize hybrids (NK6240, M900Gold) were resistant to salt stress.

Acknowlwdgements

Nagendram Erram would like to thank the Department of Biochemistry.

Funding Sources

This work was supported in part from the grant ,UGC-BSR-RFMS & UGC- to Professor. Manjula Bhanoori.

Conflict of Interest

The authors do not have any conflict of interest.

Data Availability Statement

This statement does not apply to this article.

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval.

Informed Consent Statement

This study did not involve human participants, and therefore, informed consent was not required.

Clinical Trial Registration

This research does not involve any clinical trials.

Permission to reproduce material from other sources

Not Applicable

Author Contributions

The sole author was responsible for the conceptualization, methodology, data collection, analysis, writing, and final approval of the manuscript

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Abbrevations List

MS = Mass Spectrometry

MALDI-TOF = Matrix-Assisted Laser Desorption/Ionization–Time-Of-Flight

LEA = Late embryogenesis abundant

MEB = Metabolic extraction buffer

SDS buffer = Sodium dodecyl sulphate, Dithiothreitol, Tris.

CHAPS = 3-[(3-cholamidopropyl)dimethylammonio]-1-propanesulfonate.

DTT= Dithiothreitol

PMSF= phenylmethylsulfonyl fluoride

GE= gradient Linear

SDS-PAGE= sodium dodecyl sulphate -polyacrylamide gel electrophoresis

pI = Isoelectric point

HCCA = α-Cyano-4-hydroxycinnamic acid

TFA= trifluoroacetic acid

ROS= reactive oxygen species

ACN= acetonitrile

MDA = Malondialdehyde;

TSS = Total Soluble Sugars;

FAA = Free amino acids

OMT8_MAIZE = BenzoateO-methyltransferaseBenzoateO-methyltransferase,

IF4E2_MAIZE = Eukaryotic translation initiation factor,

PCNA_MAIZE = Proliferating cell nuclear antigen

CRS2_MAIZE = Chloroplastic group IIB intron splicing Facilitator

CRS HSP 21_MAIZE = 17.5kDa class II heat shock protein

DER12_MAIZE = Derlin-1.2

CDPK_MAIZE = Calcium –dependent protein kinase

AAMT1 = An anthranilic acid methyltransferase-one

Indigenous medicinal systems have evolved over time, adapting to changes in plant availability and incorporation of new species. These systems are integral to many cultures, with local people relying heavily on wild plants for medicinal purposes, especially in areas less suitable for staple crop cultivation.¹ Traditional medicine, also termed indigenous medicine, involves the accumulated wisdom, techniques, and methods that have emerged from a variety of cultural traditions, applied to sustain health and treat diseases.² Notably, the use of traditional medicines varies globally. In developing nations, up to 80% of individuals rely on traditional medicine for their primary healthcare, whereas in industrialized countries, around half of the population opts for integrative medicine.³ The global herbal medicine market is projected to reach a value of $550 billion by 2030, with China and India emerging as the predominant exporters.⁴ These systems continue to play a significant role in global healthcare, offering potentially efficacious alternatives to conventional biomedicine, particularly for age-related, chronic, and infectious diseases.⁵

The medicinal significance of the Corchorus genus has been widely acknowledged in traditional Asian and African healing practices, where it has been used to address a range of health issues. This genus could be a valuable source of herbal remedies, playing a role in boosting health standards and ensuring livelihood security across Asia and Africa. The leaves of Corchorus species contain a diverse array of bioactive compounds, which confer prophylactic and therapeutic properties.⁶

Corchorus depressus Linn leaves reported the isolation of two compounds, flavone and 5-hydroxy flavone, from the chloroform extract of plant leaves.⁷ These compounds exhibit a diverse array of biological activities, including antioxidant, anticancer and anti-inflammatory, anti-allergic, and analgesic.⁸ Interestingly, researchers have thoroughly examined the anatomical structures and identified the important secondary metabolites found in the leaves of Corchorus olitorius L.⁹

However, further research is required to determine the specific therapeutic properties of Corchorus depressus Linn. The present study delineates the structure of four novel compounds obtained from the foliar extracts of Corchorus depressus (Linn.), using methanol and ethanol as extraction solvents. The two compounds isolated from the methanol solvent extract were named ME-1, ME-2 and the two components isolated from the ethanol solvent extracts were named ETH-1 and ETH-2.

Materials and Methods

Collection and Identification of plant

Fresh Corchorus depressus (Linn.) leaves were picked in Sakri, Dhule District, and Maharashtra, India. Taxonomist Dr. S. R. Kshirsagar from S.S.V.P.S’s Science College in Dhule (M.S), India, verified the authenticity of the plant specimen.

Preparation of plant extract

Approximately 3 kg of dried Corchorus depressus (Linn.) leaves were subjected to cold maceration with methanol for 72 hours at ambient temperature. Following the evaporation of the macerate, 7.5 g of methanol extract was obtained. The residual plant material was then subjected to cold maceration with ethanol, a solvent of higher polarity, also at ambient temperature. This process, after evaporation, yielded 4 grams of ethanol extract.¹⁰

Isolation of crude compounds

In earlier studies, an initial phytochemical analysis of the crude extracts from Corchorus depressus Linn revealed that the methanol extract contained flavonoids, sterols, and phenolic compounds. In contrast, the ethanol extract confirmed the presence of carbohydrates, glycosides, proteins, and amino acids.¹¹

The TLC systems were developed to identify the potential phytoconstituents present in both crude solvent extracts.

Methanol extract

Thin-layer chromatography (TLC) profile was developed to identify phytosterols and phenolic compounds, as suggested by initial phytochemical tests. Various solvent systems were employed, such as Benzene: Methanol (7:3), Chloroform: Methanol (8:2), Chloroform: Acetone, and Methanol: Water: Formic Acid in different proportions. Significantly, the Chloroform: Acetone (7.5:2.5) and Methanol: Water: Formic Acid (4:5.7:0.3) systems offered improved resolution.

Ethanol extract

In order to develop the thin-layer chromatography (TLC) profile for the ethanol extract, which was intended to identify flavonoids and organic acids as indicated by preliminary phytochemical analyses, a variety of solvent systems were evaluated. These systems included a 7.5:2.5 ratio of Benzene and Ethanol, a 4:3:3 mixture of Benzene, Chloroform, and Ethanol, and several combinations of Petroleum Ether, Ethanol, and Acetic Acid. The best separation was achieved with a 4:4:2 ratio of Petroleum Ether, Ethanol, and Acetic Acid. The spraying reagent was created by dissolving 0.5 g of vanillin in 100 ml of a sulphuric acid/ethanol solution with a 40:10 ratio.

A methanol extract weighing five grams was applied to silica gel with a mesh size of 60-120, and elution was conducted using a solvent system of methanol and acetone in a 7.5:2.5 ratio. This gradient elution process led to the isolation of a single spot. Subsequently, the column was further divided by eluting with a different solvent system comprising methanol, water, and formic acid in a 40:57:3 ratio, which resulted in the isolation of another single spot crude compound. The ethanol extract, weighing 3.5 grams, underwent column chromatography on silica gel with a mesh size of 60-120. It was eluted using a mixture of petroleum ether, ethanol, and acetic acid in a 4:4:2 ratio. Fractions, each displaying a single spot with same R_f values, were combined and evaporated for both the methanol and ethanol extracts, leading to the isolation of compounds.^12-15

Purification^{12, 13}

The preparative thin-layer chromatography was conducted on two crude compounds, each derived from the methanol and ethanol extracts of Corchorus depressus Linn. The chromatographic bands were identified, subsequently scraped off, and extracted using the respective solvent. Following evaporation and drying, two pure compounds were obtained from the methanol extracts, designated as ME-1 and ME-2, and from the ethanol extracts, designated as ETH-1 and ETH-2, respectively.

Detection methods

The two isolated pure compounds each from the methanol and ethanol extracts were characterized using established spectroscopic techniques, including CHNS elemental analysis (Flash Smart V, CHNS/O-instrument manufacture by Thermo Fischer Scientific), LCMS (Quadrupole-ToF MS with ESI from Waters QTOF Micro at SAIF, Panjab University, Chandigarh and 6200 series TOF/6500 series from Agilent Technologies at SAIF IIT Bombay), FTIR(Perkin Elmer, USA) at the Sandip Institute of Pharmaceutical Sciences, Nashik and 3000 Hyperion Microscope with Vertex 80 FTIR System (Bruker, Germany) at SAIF IIT Bombay, within the range of 4000–50 cm^-1), and ¹H, ¹³C-NMR (BRUKER AVANCE 400 MHz NMR Spectrometer (manufactured by BRUKER, Switzerland) at the Sophisticated Analytical Instrumentation Facility (SAIF) at Panjab University, Chandigarh, as well as an ECZR Series 600 MHz NMR Spectrometer (manufactured by JEOL, Japan) at SAIF, IIT Bombay).

Results

Characterization of ME-1

ME-1 was isolated from methanol extract, appeared as a white amorphous solid with a melting point 128-130⁰ C. Elemental %: Found C= 84.699 %, H= 11.518 %, O= 3.871 %,

Calculated formula: C₂₉H₄₈O, Molecular weight= 412, MS m/z = 411.55.

IR (cm^-1): 3331, 2970, 2934, 2890, 2866, 1458, 1381, 1252, 1153, 1089, 1054, 1022, 969, 960, 799. ¹H NMR (CDCl₃): δ  0.69 (3H, s, H-18), 0.82(3H, d, H-27), 0.85(3H, t, H-29), 0.93(2H, d, H-28), 0.93(1H, m, H-9), 1.0(1H, m, H-14), 1.02(3H, d, H-26), 1.03(3H,d, H-21), 1.06 (2H, m, H-15), 1.07(3H, s, H-19), 1.13(1H, m, H-17), 1.15(1H, m, H-20), 1.24(2H,m, H-16), 1.44(1H, m, H-25), 1.50(2H, m, H-11), 1.52(1H, m, H-24), 1.56(2H, m, H-15), 1.85(2H, m, H-1), 1.90(2H, m, H-2), 1.98(2H, m, H-7), 1.99(2H, m, H-12), 2.0(1H, m, H-8), 2.25(2H, m, H-4), 3.52(1H, m, H-3), 5.02(1H, dd, H-22), 5.14(1H, dd, H-23), 5.34(1H, t, H-6).

¹³C NMR (CDCl₃): δ 12.06(C-18), 12.29(C-29), 19.00(C-19), 21.08(C-11), 21.08(C-27), 21.13(C-26), 21.25(C-21), 24.38(C-15), 25.44(C-28), 28.96(C-16), 31.60(C-2),  31.61(C-25), 31.90(C-7), 31.90 (C-8), 36.51(C-10), 37.26(C-1), 39.68(C-12), 40.55(C-20), 42.21(C-4),  42.27(C-13), 50.14(C-9), 51.25(C-24), 55.93(C-17), 56.87(C-14), 71.74 (C-3), 121.70 (C-6), 129.25(C-23), 138.35(C-22), 140.76(C-5).

¹H and ¹³C NMR chemical shifts assignments are depicted in the Table 1.

Characterization of ME-2

ME-2, isolated from a methanol extract, was characterized as a yellow crystalline solid with a melting point ranging from 222 to 224°C.

Elemental %: Found C= 59.69 %, H= 4.63 %, O= 35.64 %, Calculated formula: C₉H₈O₄,

Molecular weight=180, MS m/z = 180,

IR (cm^-1): 3432, 3233, 1644, 1620, 1527, 1449, 1352, 1277, 1173, 973, 849, 779, 630.

¹H NMR (DMSO): δ 6.20 (1H, d, J=15 Hz, H-8), 6.83 (1H, d, J=8 Hz, H-5), 6.90 (1H, dd, J=1.9 Hz & J=8.01 Hz, H-6), 7.07 (1H, d, J=8 Hz, H-2), 7.52 (1H, d, J=15 Hz, H-7),

8.00 (3-OH), 8.10 (4-OH), ¹³C NMR (DMSO): δ 113.50 (C-2), 114.52 (C-5), 115.02(C-6), 120.91(C-1), 125.81 (C-8), 144.40 (C-7), 144.5(C-3), 147.3(C-4), 168.49(C-9).

The ¹H and ¹³C-NMR chemical shifts assignments are shown in the Table 2.

Characterization of ETH-1

Compound ETH-1 was isolated from an ethanol extract, characterized as an off-white solid with a melting point of 82-84°C.

Elemental %: Found C= 78.109 %, H= 12.997 %, O= 8.894%, Calculated formula: C₂₅H₅₀O₂,

Molecular weight= 383. MS m/z = 383.54.

IR (cm^-1): 2953, 2915, 2871, 2848, 1694, 1470, 1429, 1410, 1350, 1328, 1301, 1277, 1247, 1193, 936, 722, 685.¹H NMR (CDCl₃): δ 0.88 (3H, t, H-25), 1.27 (38H, broad s, H-5 to H-23), 1.30 (2H, m, H-24), 1.36 (2H, m, H-4), 1.63 (2H, m, H-3), 2.34 (2H, t, H-2), 11.56 (1H, s, H-1), ¹³C NMR (CDCl₃): δ 14.04(C-25), 22.65(C-24), 24.66(C-3), 29.06(C-8 to C-17), 29.26(C-4, C-5, C-6), 29.40(C-7), 29.40(C-18 to C-22), 31.86(C-23), 34.13(C-2), 180.52 (C-1).

NMR: ¹H and ¹³C NMR chemical shifts assignments are depicted in the Table 3.

Characterization of ETH-2

The compound ETH-2 was isolated from ethanol extract, appeared as a white crystalline solid with a melting point 60-61⁰ C. Elemental %: Found C= 75.03 %, H= 12.109 %, O= 12.854 %,

Calculated formula: C₁₇H₃₄O₂, Molecular weight= 271. MS m/z = 271.53

IR (cm^-1): 2955, 2918, 2851, 1701, 1466, 1429, 1352, 1326, 1295, 1196, 1121, 1074, 824, 741, 683. ¹H NMR (CDCl₃): δ 0.89 (3H, t, H-17), 1.27 (22H, broad s, H-6 to H-16), 1.30 (2H, m, H-4), 1.30 (2H, m, H-5), 1.63 (2H, m, H-3), 2.34 (2H, t, H-2), 11.98 (1H, s, H-1).

¹³C NMR (CDCl₃): δ 14.04(C-17), 22.69(C-16), 24.65(C-3), 29.08(C-4), 29.28(C-5), 29.37(C-14), 29.47(C-6), 29.63(C-7 to C-13), 31.93(C-15), 34.12(C-2), 180.69(C-1).

NMR: ¹H and ¹³C NMR chemical shifts assignments are depicted in the Table 4.

Table 1: NMR Spectroscopic Assignments of ME-1

Table 2: NMR Spectroscopic Assignments of ME-2

Table 3: NMR Spectroscopic Assignments of ETH-1

Table 4: NMR Spectroscopic Assignments of ETH-2

Discussion

Compound ME-1 showed a green color in Libermann-Burchard’s test, depicting the compound of the steroid nucleus.^{16, 17} ME-1’s mass peak (m/z-411.61) and elemental analysis (C= 84.699 %, H= 11.518 %, O= 3.871 %) indicated that its chemical formula was C₂₉H₄₈O.  The IR spectral data of ME-1 showed at broad spectrum at 3331 cm^-1 represents the –OH group.  The absorption peaks at 2970 cm^-1 represents-CH alkene , 2934 cm^-1, 2866 cm^-1 and  1458 cm^-1 peaks showed -CH aliphatic group and 1154 cm^-1 for C-O linkage.¹H NMR spectrum of ME-1 showed the signal at 5.35 (triplet, 1H) for the H-6, a mono-substituted olefin proton. The two doublet of doublets at 5.02 δ and 5.14 δ constituted the H-22 and H-23 protons of the di-substituted olefin. The signal at 3.52 (m) suggests a downfield shift of proton H-3 of the steroidal moiety. ME-1 shows singlets at 0.69 δ and 1.07 δ corresponding to two methyl groups of H-18 and H-19, and three doublets at 1.03 δ, 0.82 δ and 0.85 δ suggesting the three methyl groups of H-21, H-27, and H-29, respectively. On studying all the spectroscopic assignments of ¹H-NMR data and ¹³C NMR signals, MS data of the compound ME-1 (Figure 2) and on comparison with the previous literature, ¹⁸ the structure of the compound was identified as stigmasterol.

ME-2; showed a mass peak at m/z= 180 and elemental analysis (C =59.69 %, H=4.63 %, O=35.64 %) revealed its formula to be C₉H₈O₄. In the IR spectrum, the broad peak at 3431cm^-1 represents the O-H stretching vibration of the phenolic group. The stretching frequency at 1644 cm^-1 indicated the –C=O group of carboxylic acid and the 1620 cm^-1 peak indicted the C=C of the aromatic ring. The ¹H-NMR spectra of ME-2 , doublet of doublet at 6.90 δ represents the H-6 proton with ortho and meta coupling(J=8 Hz and J=1.9Hz), and two doublets at 7.07 δ and 6.83 δ indicates the H-2 and H-5 protons respectively. Also two broad doublets at 6.2 δ and 7.5 δ (J=15 Hz) depicted two double bonded carbons, α and β, respectively to the carboxylic acid group. On comparing all the spectroscopic assignments and comparing all the spectral data (Figure 3), with the previous literature, ¹⁹ the structure of the compound was elucidated as caffeic acid.

ETH-1 compound, a crystalline solid with a melting point of 82-84⁰C, was obtained from the ethanol extract. The mass peak (m/z-383.54) and elemental analysis (C= 78.109 %, H= 12.997 %, O= 8.894 %) resulted in the chemical formula C₂₅H₅₀O₂. The IR spectra of ETH-1 showed absorption bands at 2953 cm^-1(broad, O-H str.), 2848 cm^-1 (C-H str.), 1694 cm^-1 (C=O), 1350, 1328, 1277, 1193, 936, 722, 685 cm^-1 indicate that it is long chain saturated fatty acid. ¹H NMR spectrum of ETH-1 showed at downfield peak at 11.56 δ endorsing the presence of a carboxylic acid proton. In addition, a three proton triplet at 0.88 δ representing the terminal methyl protons, a broad singlet at 1.27 δ assignable to 44-methylene protons and a sharp triplet of two protons at 2.34 δ corresponds to the methylene group α-(next) to the carboxylic acid functional group. Based on all the spectroscopic assignments of ¹H-NMR data and ¹³C NMR signals and from the mass peak at m/z- 383 of compound ETH-1 (Figure 4), the structure of the compound was determined to be pentacosylic acid.

ETH-2 compound, a white crystalline solid with a melting point of 60-61⁰C, was obtained from the ethanol extract. The mass peak (m/z-271.53) and elemental analysis (C= 75.03 %, H= 12.109 %, O= 12.854 %) resulted in the chemical formula C₁₇H₃₄O₂. IR spectrum of ETH-2 showed peaks at 2955 cm^-1 (OH-str.), 2850 cm^-1 (CH- str.) and 1701 cm^-1 (C=O).

¹H NMR spectrum of ETH-2 showed at downfield peak at 11.98 δ revealed the presence of a carboxylic acid proton. The three-proton triplet at 0.88 δ showed a terminal methyl group, and a broad singlet at 1.27 δ depicts the 26-methylene protons and a sharp triplet of two protons at 2.34 δ corresponding to the α-methylene group.

Considering all the NMR spectroscopic assignments and the mass peak at m/z-271.53 (Figure 5), the structure of the ETH-2 compound was identified as margaric acid.

Figure 1: Structures of the isolated compounds Click here to view Figure

Figure 2: MS, IR, 1H-NMR & 13C-NMR of ME-1 Click here to view Figure

Figure 3: MS, IR, 1H-NMR & 13C-NMR of ME-2 Click here to view Figure

Figure 4: MS, IR, 1H-NMR & 13C-NMR of ETH-1 Click here to view Figure

Figure 5: MS, IR, 1H-NMR & 13C-NMR of ETH-2 Click here to view Figure

Conclusion

From the leaves of Corchrous depressus (Linn.), two biologically active compounds were extracted using methanol, and another two were obtained using ethanol. The identification of these isolated compounds’ structures was achieved by comparing their spectroscopic data with that available in the existing literature. According to the spectral analysis, the compounds ME-1, ME-2, ETH-1, and ETH-2 were identified as stigmasterol, caffeic acid, pentacosylic acid, and margaric acid, respectively.

Acknowledgement

The authors extend their sincere thanks to the Principal of Sandip Institute of Technology and Research Centre, Nashik, for providing the necessary facilities. Furthermore, the research was made possible through the support of the Principal of P.S.G.V.P. Mandal’s S.I.Patil Arts, G.B.Patel Science, and S.T.K.V.S Commerce College, Shahada, District-Nandurbar, who offered the crucial research infrastructure.

Funding Sources

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Conflict of Interest

The authors do not have any conflict of interest.

Data Availability Statement

This statement does not apply to this article.

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval.

Informed Consent Statement

This study did not involve human participants, and therefore, informed consent was not required.

Clinical Trial Registration

This research does not involve any clinical trials.

Permission to reproduce material from other sources –

Not Applicable

Authors Contribution

Swapnil Ghanshyam Dhake: Conceptualization, Methodology, Writing – Original Draft.

Milind Kashinath Patel: Data Collection, Analysis, Writing – Review & Editing.

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Abbreviations List

ME-1: Methanol Extract-1

ME-2: Methanol Extract-2

ETH-1: Ethanol Extract-1

ETH-2: Ethanol Extract-2

PTLC-Preparative TLC, IR-Infrared Spectroscopy

MS-Mass spectrometry

¹H-NMR: Hydrogen nuclei Nuclear Magnetic Resonance

¹³C-NMR: Carbon nuclei Nuclear Magnetic Resonance

The liver is the principal organ essential for metabolizing proteins, carbohydrates, and lipids. Working alongside the spleen, it facilitates elimination of senescent red blood cells, produces bile for digestion, and synthesizes plasma proteins and lipoproteins, including clotting factors.¹ It performs numerous critical functions that maintain the body’s equilibrium and overall well-being. Proper liver function is indispensable for nearly all essential metabolic processes, including growth, immune response, nutrient metabolism, energy production, and reproduction.² Most hepatotoxic substances damage liver cells by inducing lipid peroxidation, oxidative stress, and elevating serum biomarkers such as alkaline phosphatase, transaminases, bilirubin, triglycerides, and cholesterol.^3,4

Following are the key functions performed by liver

Regulating nutrient absorption and metabolismfrom the intestines.

Modulating endocrine functionsto facilitate growth and development.

Maintaining energy metabolism (e.g., glycogen storage and gluconeogenesis.

Synthesizing and biotransforming proteins, carbohydrates, and lipids.

Regulating fluid and electrolyte balance.

Producing bile for digestion and eliminating hydrophobic compounds.

Supporting immune function via Kupffer cells and acute-phase proteins.

Detoxifying drugs and xenobiotics through enzymatic metabolism.

The liver synthesizes approximately 15% of the body’s total proteins, with most being secreted directly into the bloodstream. This process begins when transcription factors activate promoter sequences in the DNA, initiating gene expression. Following translation and post-translational modifications, the newly synthesized proteins are released from the sinusoidal surface of hepatocytes into the circulation. Hepatic protein production is tightly regulated by nutritional status and hormonal signals. Among the liver’s diverse protein products, are albumin (maintains oncotic pressure and transports molecules) ceruloplasmin (copper transport and oxidation) coagulation factors (fibrinogen, prothrombin, etc.) and fibrinolytic proteins, complement system proteins (immune defense), protease inhibitors (e.g., α1-antitrypsin). Notably, C-reactive protein (CRP), a key acute-phase reactant, is the most commonly measured hepatic protein in clinical practice. While the liver does not store proteins, it efficiently recycles amino acids to sustain ongoing protein synthesis.⁵

Global Burden

Alcohol-associated Liver Disease

Global annual per capita alcohol consumption (2016) reached 6.4 liters, with 5.1% of the worldwide population affected by alcohol use disorder. Alcohol remains the leading cause of cirrhosis globally, accounting for nearly 60% of cases in North America, Europe, and Latin America. In recent years, the incidence of alcohol-associated hepatitis has risen significantly particularly among young adults and women. Given the synergistic interaction between alcohol consumption and metabolic risk factors, Europe and North America face a heightened risk of increasing liver disease burden in coming years.

Non-alcoholic Fatty Liver Disease

It impacts approximately 32.4% of people worldwide. Its contribution to global mortality has increased from 0.9% to 0.16% of all deaths. Currently NAFLD ranks as the second most common cause of liver transplants overall and the leading cause in women. Emerging metabolic risk factors in children and adolescents represent one of the most significant impending threats to global health.⁶

Various Stages of Hepatotoxicity

Hepatotoxicity progresses through distinct clinical stages, with severity and manifestations varying based on etiology including alcohol abuse, metabolic dysfunction, or drug-induced injury, and outlined in Table 1 and Figure 1.

Table 1: Clinical stages of hepatotoxicity and their common etiological factors

Figure 1: The sequential phases of hepatic damage in liver toxicity7 Click here to view Figure

Risk factors of hepatotoxicity

Multiple variables influence hepatotoxicity risk, idiosyncratic factors, age, sex, lifestyle exposures like alcohol intake, smoking, pre-existing liver illness, concurrent use of other medicines, and genetic and environmental influences [Figure 2].^8,9 Mitochondrial dysfunction, impairing energy metabolism, or aberrant lipid metabolism through beta-oxidation have all been linked to the mechanisms of hepatotoxicity.^10,11 

Figure 2: Common predisposing factors for liver toxicity Click here to view Figure

Biomarkers in Hepatotoxicity

Definition and Classification:

The NIH defines a biomarker as “a characteristic that is objectively measured and evaluated as an indicator of normal biologic processes, pathogenic processes, or pharmacologic responses to therapeutic intervention”.¹² Biochemical markers can be classed based on their purpose (Table 2).

Table 2: Biomarkers based on their purpose

Biomarkers serve as valuable diagnostic tools in clinical hepatology, complementing other methods to accurately detect liver conditions such as DILI (drug-induced liver injury) and HILI (herbal medicine–induced liver injury) are commonly studied using biomarkers. These indicators usually involve the detection of RNA, DNA, or protein molecules in biological samples, including blood, plasma, and urine.^13-20 The development and implementation of new biomarkers require rigorous validation through testing in confirmed patient populations and comparison with existing diagnostic standards.¹⁶ This ensures their diagnostic accuracy and reproducibility, which clearly differentiate between healthy and sick states and deliver consistent results across laboratories and populations.^14,20

When properly validated, these biomarkers become essential for early detection of hepatotoxicity, monitoring disease progression, guiding treatment decisions, and ultimately improving patient safety in cases of suspected DILI or HILI.

Conventional Biomarkers

Conventional biomarkers for evaluating liver injury can be classified into two primary categories: (a) markers of impaired liver function or homeostasis, and (b) markers of cellular damage. The liver maintains critical physiological functions including protein synthesis, bile acid metabolism, and waste excretion examples include bilirubin and urea. Changes may also be observed in circulating bile acids, overall bilirubin levels, and blood proteins – frequently observed following hepatotoxic drug exposure or in liver disease – serve as well-established indicators of compromised hepatic function.

Indicators of liver cell damage are usually enzymes that leak into the bloodstream when hepatocytes are injured or undergo necrosis. Common examples are alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), gamma-glutamyl transferase (GGT), and glutamate dehydrogenase (GLDH).²¹ Additional biochemical parameters such as albumin levels, total protein, triglycerides, and coagulation markers (particularly PT/INR) provide valuable assessment of hepatic synthetic capacity, especially in chronic liver disease.^{22, 23}

Standard biochemical markers (Table 3) outline the routine laboratory parameters evaluated during preclinical assessment of drug-related liver toxicity.

Table 3: Principal conventional biomarkers used in the assessment of liver injury

ALT and AST

ALT and AST are sensitive biomarkers of hepatocellular injury, with ALT being more liver-specific due to its predominant hepatic localization, while AST is widely distributed across tissues.²⁴ Their differing plasma half-lives (ALT~47 h; AST~17 h) enhance diagnostic interpretation.²⁵ Although elevations occur in hepatitis, alcohol-related liver disease, cirrhosis, and drug-induced injury, their limitation is poor specificity, as increases are also seen in muscle damage and myocardial infarction.^{26, 27}

The study by Kunutsor et al. further noted that despite associations with cardiovascular outcomes, aminotransferases add little predictive value to CVD risk models, emphasizing the need to interpret them alongside other biomarkers and clinical findings.²⁸

Gamma-glutamyl transferase

GGT is a validated marker of liver disease, biliary disorders, and chronic alcohol consumption.²⁹ Elevated levels also correlate with increased risk of stroke, type 2 diabetes, coronary heart disease, and heart failure, even within the normal reference range.^30,31 Biochemically, GGT regulates glutathione (GSH) turnover through the glutamyl cycle, influencing cellular redox balance.^32,33 Its strength lies in its high sensitivity to hepatobiliary injury, oxidative stress, and alcohol intake; however, its major limitation is poor specificity, since elevations are also observed in obesity, metabolic syndrome, cardiovascular disease, and with certain medications. ^34-38 In hepatic steatosis, increased GGT reflects oxidative stress–induced GSH depletion, compensatory enzyme upregulation, and inflammation, with fatty liver progression more common in patients with abnormal GGT.^39-44 Persistent GGT elevation further predicts fatty liver risk, and in some hepatotoxicity cases, GGT may rise disproportionately compared with other enzymes.⁴⁵ 

Alkaline Phosphatase

ALP exists in tissue-specific forms (placenta, germinal tissue, colon) and non–tissue-specific forms present in liver, bone, and kidney. ⁴⁶ Physiologically, levels may rise during bone growth or pregnancy due to increased osteoblast or placental activity.^47,48

Clinically, ALP is a useful and sensitive marker for cholestatic liver disorders, with about 75% of patients with intrahepatic or extrahepatic cholestasis showing enzyme levels fourfold above the upper limit of normal.⁴⁹ A strength of ALP is its ability to detect biliary obstruction and cholestasis, even persisting for up to a week after resolution of obstruction.⁵⁰ However, its limitation lies in poor specificity, since elevations also occur in bone disease, pregnancy, infiltrative liver conditions, and sepsis, making it necessary to interpret ALP alongside other biomarkers and clinical findings. ⁵¹

Glutamate dehydrogenase

GLDH is a mitochondrial matrix enzyme occurring predominantly in liver lobules, with smaller amounts in kidney, brain, intestine, and pancreas, and minimal presence in muscle.^52-55 Its abundance in the liver’s matrix-rich mitochondria, coupled with low activity outside the liver, makes GLDH a highly specific marker of hepatocellular injury.⁵⁶ Unlike ALT, which can be elevated in muscle disorders, GLDH remains unaffected, making it particularly valuable for detecting liver damage in patients with concomitant muscle disease.^52,57 Its shorter plasma half-life (16–18 h) compared to ALT ^52,54 also allows more accurate reflection of current hepatic injury. However, GLDH testing is not widely available in routine clinical practice, can be influenced by mitochondrial disorders, and is less validated in large patient populations, which limits its broader clinical application.

Alternative indicators of drug-related liver toxicity

Nuclear DNA and mitochondrial DNA (mtDNA) fragments have been investigated as both mechanistic markers and predictors of hepatotoxicity. Nuclear DNA fragments can be quantified by antihistone immune assays, while mtDNA is measured using quantitative PCR. In N‑acetyl‑para‑aminophenol (APAP) overdose, ALT, GLDH, and mtDNA levels increase in both mice and humans, with mtDNA potentially specific for mitochondrial injury.⁵⁸

Several biomarkers are utilized to detect liver disease and assess the extent of hepatic injury. Some are disease-specific, while others represent general liver parameters that tend to rise across most liver disorders, as shown in [Figure 3].

Figure 3: Diagnostic biomarkers used in hepatotoxicity assessment Click here to view Figure

Novel Biomarkers

MicroRNAs, especially miR-122 and miR-192, are considered highly promising biomarkers, as their levels increase in the blood of both mice and humans following APAP overdose, often preceding the rise of ALT.^59,60 Similarly, HMGB1, a nuclear protein involved in transcription regulation, nucleosome organization, and DNA repair,⁶¹ acts as a marker of necrosis when measured in total form, and of inflammation when present in its acetylated form. Keratin‑18 (K18), a cytoskeletal protein, is cleaved by caspases during apoptosis to form a fragment recognized by the M30 antibody.⁶² Both total and cleaved K18 are elevated in APAP overdose, with total levels markedly higher in APAP and other hepatotoxicities, indicating that oncotic necrosis predominates.^63-65Additional proteins such as argininosuccinate synthetase,⁶⁶ paraoxonase‑1, glutathione‑S‑transferase (GST), liver‑type fatty acid binding protein‑1, cadherin‑5,^67,68 macrophage colony‑stimulating factor receptor, and aldolase‑B are cAMP‑regulated and show potential as mechanistic markers. While some, such as macrophage colony‑stimulating factor receptor, have been proposed as inflammatory biomarkers, their role in hepatotoxicity remains under explored.⁶⁹

Emerging Biomarkers and Omics Approaches

Several serum protein–based biomarkers have been explored for assessing liver injury, based on the leakage of hepatocellular proteins into circulation. Most remain experimental and are not yet qualified for routine use. ALT isozymes-ALT1 (mainly hepatic but also in renal and salivary tissue) and ALT2 (present in adrenal cortex, neurons, cardiac and skeletal muscle, and pancreas)—may help localize the source of injury.⁷⁰

Other candidates include sorbitol dehydrogenase, glutamate dehydrogenase (GLDH), serum F protein, GST-alpha, and arginase I.⁷¹Sorbitol dehydrogenase marks acute hepatic injury in rodents; GLDH is highly liver-specific and unaffected by muscle injury; serum F protein correlates with histopathology in humans⁷² but lacks preclinical validation; GST-alpha reflects centrilobular damage but can be induced by xenobiotics; and arginase I rises earliest and most markedly after thioacetamide injury, paralleling ALT/AST.^73,74

While these markers offer advantages in sensitivity or specificity, their limited validation and overlap with extrahepatic sources constrain their clinical application, and they may be most effective when used in panels with conventional enzymes. Emerging omics techniques provide additional promise: transcriptomics highlights gene-expression changes, proteomics enables broad protein profiling, and metabolomics captures metabolic disturbances, often preceding biochemical alterations. Collectively, these approaches could deliver biomarker panels with greater specificity, sensitivity, and earlier detection potential than current assays.

Transcriptomics has been widely applied in hepatotoxicity research to identify gene expression signatures associated with drug-induced liver injury (DILI). By revealing how hepatotoxins alter gene activation, transcriptomic profiling can uncover predictive patterns such as those linked to hepatic steatosis or oxidative stress pathways, providing early biomarkers and mechanistic insight into liver damage.

Proteomics complements transcriptomics by mapping protein-level changes in response to toxic injury. It highlights alterations in protein abundance and post-translational modifications that reflect hepatocellular stress and damage. As proteins are functional executors of gene expression, proteomic biomarkers help connect molecular changes with phenotypic outcomes, improving the diagnostic value for DILI.

Metabolomics offers a direct view of the hepatocellular state by capturing end products of biochemical pathways. It reveals actual metabolic disruptions during DILI, including mitochondrial dysfunction, bile acid imbalance, and energy metabolism defects. This approach enables earlier detection of injury and supports individualized risk assessment through metabolic phenotyping. ^75-76

Cellular Stress Markers

The cellular stress response regulates hepatocyte survival or death after toxicant exposure. Proteomic methods such as two-dimensional gel electrophoresis, mass spectrometry and iTRAQ have identified stress-related markers in rat hepatocarcinogenesis, including annexins, metabolic enzymes, aflatoxin B₁ aldehyde reductase, and GST-P form. Keratin-18 indicates apoptosis and necrosis, while HMGB1 reflects necrosis and inflammation only. Malate dehydrogenase (MDH), purine nucleoside phosphorylase, and paraoxonase-1 correlate strongly with histopathology in hepatotoxicant-exposed rats; the first is elevated in hepatic and cardiac injury, the second rises early after galactosamine or endotoxin exposure, and the third, an HDL-associated hepatic enzyme, decreases in drug-induced and chronic liver injury. In humans, 92 altered serum proteins were identified in DILI, with apolipoprotein E distinguishing the cases from controls, with 89% accuracy. ⁷⁷ The catalogue of emerging and omics-based biomarkers in hepatotoxicity, is given in Table 4.

Table 4: Catalogue of emerging and omics-based biomarkers in hepatotoxicity

Conclusion

Biomarkers are indispensable for the timely detection, monitoring, and prognosis of hepatotoxicity. While conventional markers remain clinically valuable, their limitations necessitate the adoption of novel and omics‑based indicators that can enhance diagnostic specificity and enable earlier intervention. The future of hepatotoxicity assessment lies in integrated biomarker panels supported by high‑throughput, cost‑effective technologies and robust validation protocols. Such advancements will not only refine clinical decision‑making but also improve therapeutic outcomes, ultimately reducing the global burden of liver disease.

Acknowledgement

The authors gratefully acknowledge the support and encouragement provided by Head of The Institution and Management of Gokaraju Rangaraju College of Pharmacy, Hyderabad.

Funding Sources

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Conflict of Interest

The authors do not have any conflict of interest.

Data Availability Statement

This statement does not apply to this article.

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval.

Informed Consent Statement

This study did not involve human participants, and therefore, informed consent was not required.

Clinical Trial Registration

This research does not involve any clinical trials.

Permission to reproduce material from other sources

Not Applicable

Author Contributions

Shashikala Metri – Wrote the final draft of the work and edited, supervised the entire work.

Rohini Rasamallu & Shaheda Mohammad – Completed all reference work and formatting.

Rohini Rasamallu & Shaheda Mohammad – Collected all the data and completed the literature review.

Mudunuri Ganga Raju – Provided valuable guidance.

Shashikala Metri & Ceema Mathew – Data editing.

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68. Mikus M, Drobin K, Gry M, et al. Elevated levels of circulating CDH5 and FABP1 in association with human drug-induced liver injury. Liver Int. 2017;37(1):132-40. https://doi.org/10.1111/liv.13174
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69. Qin S, Zhou Y, Gray L, et al. Identification of organ-enriched protein biomarkers of acute liver injury by targeted quantitative proteomics of blood in acetaminophen- and carbon-tetrachloride-treated mouse models and acetaminophen overdose patients. J Proteome Res. 2016;15(9):3724-40. https://doi.org/10.1111/liv.13174
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70. Ozer J, Ratner M, Shaw M, Bailey W, Schomaker S. The current state of serum biomarkers of hepatotoxicity. Toxicology. 2008;245(3):194-205. https://doi.org/10.1016/j.tox.2007.11.021
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71. Lindblom P, Rafter I, Copley C, et al. Isoforms of alanine aminotransferases in human tissues and serum: differential tissue expression using novel antibodies. Arch Biochem Biophys. 2007;466(1):66-77. https://doi.org/10.1016/j.abb.2007.07.023
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72. Foster GR, Goldin RD, Oliveira DB. Serum F protein: a new sensitive and specific test of hepatocellular damage. Clin Chim Acta. 1989;184(1):85-92. https://doi.org/10.1016/0009-8981(89)90259-3
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73. Ashamiss F, Wierzbicki Z, Chrzanowska A, et al. Clinical significance of arginase after liver transplantation. Ann Transplant. 2004;9(3):58-60.
74. Murayama H, Ikemoto M, Fukuda Y, Tsunekawa S, Nagata A. Advantage of serum type-I arginase and ornithine carbamoyl transferase in the evaluation of acute and chronic liver damage induced by thioacetamide in rats. Clin Chim Acta. 2007;375(1-2):63-8 https://doi.org/10.1016/j.cca.2006.06.018
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75. Kohonen, P., Parkkinen, J., Willighagen, E. et al.A transcriptomics data-driven gene space accurately predicts liver cytopathology and drug-induced liver injury. Nat Commun.2017;8(1): 15932. https://doi.org/10.1038/ncomms15932
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Abbreviations List

ALT: Alanine aminotransferase,

AST: Aspartate aminotransferase,

HMGB1: High mobility group box-1,

 ALD: Alcohol-associated Liver Disease,

NAFLD: Non- alcoholic fatty liver disease,

MAFLD: Metabolic dysfunction associated fatty liver disease,

DILI: Drug-induced liver injury,

 HILI: Herbal medicine–induced liver injury,

ALP: Alkaline phosphatase,

GGT: Gamma-gltutamyl transferase,

GLDH: Glutamate dehydrogenase,

mtDNA: Mitochondrial DNA,

PCR: Polymerase chain reaction,

GST: Glutathione‑S‑transferase,

MDH: Malate dehydrogenase,

NAD⁺ : Nicotinamide adenine dinucleotide (oxidized form),

NADH: Nicotinamide adenine dinucleotide (reduced form),

NASH: Non-alcoholic steatohepatitis,

MASH: Metabolic dysfunction–associated steatohepatitis,

SMASH: Smoking-associated steatohepatitis,

ASH: alcoholic steatohepatitis

The field of modern medicine is standing on the cusp of a profound transformation, driven by revolutionary technological advancements. Among these, 3D printing has emerged as a pivotal force, evolving from its origins in engineering and design to become a groundbreaking tool in the pharmaceutical industry.¹ This technology now enables the creation of highly personalized drug formulations, regenerative treatments, and advanced implantable devices.By controlling the shape, size, and release characteristics of medications, 3D printing promises to enhance medication adherence, diminish adverse effects, and enhance patient care in unprecedented ways.¹

Alongside 3D printing, Machine learning and artificial intelligence (AI) are set to transform the context of drug discovery and development.² These tools are facilitating the discovery of novel drug candidates by fine tuning molecular designs and improving the extraction of vital properties from large databases.leveraging big data, cloud computing, and large-scale computational models, AI is fundamentally reshaping pharmaceutical research and development, opening new avenues in drug delivery systems, molecular imaging, cancer detection, and personalized treatment approaches.

Furthermore, gene therapy, particularly with innovations like the CRISPR-Cas9 technique, marks a significant leap toward precision medicine.³ This groundbreaking tool allows for the targeted editing of genes, offering hope for curing genetic disorders and advancing therapies for previously untreatable diseases.³ With recent approvals of gene therapies for monogenic and genetically-defined disorders in both the US and the European Union, the potential of these technologies is becoming a tangible reality.

This review explores the convergence of these emerging technologies—3D printing, artificial intelligence, machine learning, and gene editing—and their potential to reshape the future of medicine.By evaluating their current applications and envisioning their future possibilities, this article seeks to offer a comprehensive perspective on how these innovations and their integrations will impact treatment strategies, improve patient outcomes, and foster greater accessibility in the medical field. 

Overview of Current Challenges in Medicine

The ever-changing world of medicine has a range of persistent challenges that reveal the ongoing nature of global health care. Some issues include antimicrobial resistant, chronic illness management and increasing age population and improved therapies for cancers.⁴Mental illnesses are getting worse, there are also differences in accessibility of medicine, while vaccination refusal is on rise among population and healthcare costs increase towards bad public’s state.⁵

In line with these objectives include: equitable health care access, improved efficiency in healthcare delivery system, as well as improvement of public health preparedness. Moreover, environmental health problems such as those related to the changing climatic conditions, pollution, and maintaining health data also form part of this complex web in society.⁶

Addressing them requires a multi—dimensional approach that combines research and innovation and changes in policies, which is the resolve to improve healthcare globally, taking into account changing world situations.

Such ongoing healthcare issues require innovative drug technologies.It addresses antimicrobial resistance by designing alternative antibiotics, managing health issues associated with chronic illnesses, and handling care needs for geriatric populations. They provide the basis for better development of drugs for anti-cancer action as well as a greater number of medications towards mental health.⁶

They play a critical role in vaccine development, cost reductions on treatment methods, efficient healthcare delivery, and tackling of environmental health issues. Moreover, they facilitate safe keeping of health information.These innovative drug technologies revolutionize many sectors of the healthcare including infections, chronic illness, as well as environmental problems.⁷

Emerging Drug Technologies

3D Printing in Pharmaceuticals

3D printing, also referred as the technique of additive production, is being recognized as a groundbreaking technology in the pharmaceutical sector. It allows for the precise and customizable production of drug dosage forms & Drug delivery systems. This technology builds three-dimensional structures layer by layer, providing innovative prospects for advanced medication delivery and tailored therapeutics.⁶

Technologies of 3D Printing

In the pharmaceutical sector, three key 3D printing technologies are commonly utilized.

Fused Deposition Modelling (FDM)

Works by extruding thermoplastic filaments in successive layers, making it particularly suitable for producing solid oral dosage forms which include tablets and capsules.⁷

Stereolithography (SLA)

Uses a Ultra-violet laser to cure liquid resin, resulting high accuracy and flawless surface finishes, which are perfect for fabricating complicated drug delivery devices.⁷

Selective Laser Sintering (SLS)

Its has a laser to fuse pulverized materials, allowing the fabrication of robust components, including drug delivery systems, implants, and tissue scaffolds.⁷

Each of these 3D printing methods is selected for its unique advantages, playing a vital role in shaping the growth of personalized drug forms and advanced pharmaceutical components. Let us briefly explore each technology.

Fused Deposition Modelling

Fused Deposition Modelling (FDM), also called as Fused Filament Fabrication (FFF), has been widely investigated for use in pharmaceutical applications.In this method, a thermoplastic polymer filament is constantly supplied through a heated nozzle, where it is melted just above its glass transition temperature. The melted material is then accurately deposited layer by layer on a substrate and let it cool, forming the desired 3D object.This extrusion-based technology is highly versatile and can utilize a variety of materials, including pastes, polymers, silicones, suspensions, and semisolids.However, in FFF applications, solid polymer filaments are primarily used to create geometrically designed drug delivery systems with customized release profiles, scaffolds, and drug-eluting devices.⁸

Hot melt extrusion (HME) is a key technique for producing continuous filaments from thermoplastic polymers for use in FDM printing. Commonly used thermoplastic polymers, which are considered safe for pharmaceutical applications, consist of ethylene vinyl acetate (EVA), polylactic acid (PLA), polyvinyl acetate (PVA), and acrylonitrile-butadiene-styrene (ABS).  Active pharmaceutical ingredients (APIs), which are chosen according to the unique characteristics of the polymers, are frequently combined with the feedstock filaments. These characteristics might include swellable/erodible qualities (like hydroxypropyl methylcellulose or HPMC), enteric qualities (like Eudragit® L 30D55), rapid solubility (like polyvinyl pyrrolidone), or insolubility (like PVA or Eudragit® RL). These tailored filaments are ideal for 3D printing capsules and other dosage forms, whether designed for immediate or controlled release.⁸

A key benefit of HME is its ability to create homogeneous solid dispersions of thermally stable drugs and excipients within the printable filament material—something that is difficult to achieve using other techniques.This process ensures efficient manufacturing with minimal material waste.FDM is a desirable alternative for developing pharmaceutical formulations because it may modify drug loading and release patterns by altering the feedstock composition or the geometric design.⁹

There have also been efforts to establish a standardized qualification framework for FDM printers, which could streamline procedure for approval of newly developed 3D-printed pharmaceutical products.

Figure 1: schematic diagram representing fused deposition modelling1 Click here to view Figure

Techniques Involved in 3D Printing in Drug Delivery Systems

3D printing is revolutionizing the manufacturing of tailored drug delivery systems. The process consists of several critical steps. Initially, computer-aided design (CAD) software is adopted to make a 3D model of the drug dosage form or delivery system.Once the design is finalized, the selected 3D printing method is used to construct the object layer by layer, as per the CAD specifications. Following the printing process, additional steps like curing, drying, or coating may be needed to enhance the chemical and physical characteristics of the finished product. Quality control plays a vital role in ensuring uniform drug distribution and maintaining the structural integrity of the 3D-printed pharmaceuticals.These technologies provide a flexible solution for customizing drug delivery systems to meet the specific needs of individual patients, thereby improving treatment outcomes in medicine.⁹

Polymers Used in 3D Printing

In 3D printing, a broad selection of biocompatible polymers is utilized to achieve various pharmaceutical and medical objectives.These polymers are chosen for their compatibility with the drug or intended application, as well as their mechanical properties.¹⁰Some common polymers include Polyvinyl alcohol (PVA), appreciated for its solubility and use in fast-dissolving drug delivery systems; Polyethylene glycol (PEG), known for its excellent biocompatibility and versatility in drug formulation; Polylactic acid (PLA), a biodegradable polymer compatible with a variety of drugs; Polycaprolactone (PCL), offering durability and slow degradation, making it suitable for long-acting drug delivery systems; Hydroxypropyl methylcellulose (HPMC), a water-soluble polymer often employed in the creation of fast-dissolving dosage forms; and methacrylate-based resins, valued for their versatility and strength in diverse pharmaceutical applications. The choice of polymer in 3D printing plays an important role in determining the final properties and performance of the 3D-printed pharmaceutical and medical products.¹⁰

3D Printed Dosage Forms

3D printing technology has revolutionized the pharmaceutical industry, offering unprecedented customization and precision in drug delivery.For instance, 3D printing allows for the creation of personalized tablets and capsules, as seen in Aprecia Pharmaceuticals Spritam (levetiracetam) tablet, designed to dissolve rapidly in the mouth, benefiting patients with epilepsy.⁸ In the realm of oral films and strips, companies like FabRx have developed 3D-printed thin, flexible films that dissolve in the mouth, offering a more patient-friendly alternative to conventional tablets. Customized implants and tissue scaffolds, such as those produced by OssDsign, provide patient-specific cranial implants and bone regeneration scaffolds for a perfect fit and optimal tissue regeneration.⁹For more complex structures, 3D printing enables the production of microneedles for transdermal drug delivery and drug-eluting stents customized for precise drug delivery, exemplified in various medical device companies’ innovations. These examples illustrate how 3D printed dosage forms are transforming drug delivery, offering personalized solutions, and enhancing patient care across a spectrum of medical applications.⁹

Advantages of 3D Printing

3D printing boasts several key advantages, including exceptional customization capabilities for personalized medicine and patient-specific medical devices.Its ability to fabricate complex structures, enable rapid prototyping, and reduce material waste makes it cost-effective and sustainable.¹⁰The technology offers high precision and accuracy, fostering consistent, quality output. It supports on-demand, localized manufacturing and small batch production, cutting costs.In healthcare, 3D printing allows for precise drug delivery control and the development of innovative medical devices and tissue scaffold. It extends its benefits to space exploration and educational institutions, making it a transformative force in manufacturing and design.¹⁰

Disadvantages of 3D Printing

The limitations of 3D printing include a restricted range of available materials, complex and evolving regulatory challenges, a significant initial equipment cost, the need for meticulous quality control, concerns over intellectual property protection, post-processing requirements, a learning curve for operation and design, potential environmental impact, size and speed constraints, and limitations in achieving smooth surface finishes. These challenges underscore the need for careful consideration and adaptation when employing 3D printing in various applications.⁷

Applications of 3D Printing

3D printing, celebrated for its adaptability, is used in a several kinds of industries. In healthcare and medicine, it plays a vital role in the production of tailored implants, prosthetics, and surgical models.The aerospace industry leverages 3D printing for rapid prototyping and creating lightweight components. The automotive sector benefits from the ability to produce custom parts and streamline prototyping processes. In manufacturing, 3D printing is employed to create intricate, lightweight parts, jigs, fixtures, and molds.Within architecture and construction, it allows for the creation of architectural models and custom-building components, including entire 3D-printed structures.The educational sector utilizes 3D printing to create educational models, enhancing hands-on learning experiences.⁹In dentistry, it is used to produce dental models, crowns, bridges, and orthodontic devices.Furthermore, 3D printing finds applications in various fields such as art, design, food production, electronics, military, and environmental solutions, demonstrating its transformative impact across diverse industries.⁹

AI and Machine Learning

AI and Machine learning are revolutionizing medicine by allowing personalized treatments, accelerating drug discovery, aiding clinical decision-making, enhancing medical imaging analysis, and identifying genetic markers for targeted therapies. These technologies offer significant advantages in healthcare but come with challenges like data quality, regulatory compliance, and interpretability.Nevertheless, they continue to reshape the medical field, improving patient care and outcomes.¹¹

Tools of AI

Artificial Intelligence (AI) employs several essential tools in the realm of emerging drug technology. Machine learning algorithms are fundamental for sifting through extensive datasets to identify potential drug candidates and predict drug-target interactions.Natural Language Processing (NLP) aids in extracting valuable information from scientific literature and clinical records, facilitating the identification of relevant research findings and drug targets.Cheminformatics combines chemistry and informatics to manage chemical data, supporting molecular design and compound screening.¹²Deep learning is instrumental in image analysis, particularly in understanding complex biological structures.Data mining tools uncover hidden patterns within extensive datasets, assisting in the identification of potential drug targets and therapeutic opportunities.Finally, simulation and modelling software enable the prediction of molecular interactions, expediting drug development.These tools collectively empower pharmaceutical research, expediting drug discovery and data-driven decision-making in the pursuit of innovative drugs and therapies.¹²

Methods of AI

Artificial Intelligence (AI) employs various methods in drug technology to revolutionize the process of drug discovery and development.Virtual screening is utilized to predict potential drug candidates through the computational analysis of chemical libraries. AI uses drug design based on structure to optimize drug compounds based on the three-dimensional structures of biological molecules.Cheminformatics manages and predicts chemical properties, aiding in compound identification and design.High-throughput screening automates the evaluation of numerous compounds, expediting the initial stages of drug discovery.AI-driven analysis of biological data, including genomics and proteomics, helps identify drug targets and biomarkers.

Molecular dynamics simulations model drug interactions at the atomic level.Deep learning is used to analyse complex biological data.These methods collectively enhance the efficiency of pharmaceutical research, reduce development timelines, and facilitate the discovery of novel drugs and therapies.¹³

Methods of Machine Learning

Machine learning in medicine encompasses several key approaches to leverage data for enhanced patient care, diagnosis, and research. Supervised learning, a foundational approach, trains models on labelled datasets, allowing for the prediction of specific outcomes, such as disease classification, patient risk assessment, and drug response prediction.Unsupervised learning, conversely, delves into unlabelled data, revealing hidden patterns and structures that assist in patient clustering, dimensionality reduction, and the identification of novel disease subtypes.¹³Deep learning, a subset of machine learning, employs complex neural networks with multiple layers and excels in tasks such as medical image analysis, natural language processing, and genomics research.¹³Reinforcement learning is focused on learning optimal sequences of actions, finding application in treatment planning, dose optimization, and personalized therapy recommendations.Transfer learning adapts pre-trained models to specific medical tasks, aiding in fields like medical image analysis.Semi-supervised learning combines labelled and unlabelled data, proving beneficial when labelled data is limited and utilized in tasks like medical image segmentation and diagnosis. These diverse machine learning approaches collectively contribute to improving healthcare by extracting valuable insights from complex medical data, ultimately enhancing patient care and advancing medical research.¹⁴

Advantages of AI and Machine Learning

AI and machine learning offer numerous advantages in medicine, including personalized treatment plans, efficient disease diagnosis, clinical decision support for healthcare professionals, accelerated drug discovery, genomics-based personalized medicine, predictive analytics for disease outbreaks, enhanced medical image interpretation, and operational efficiency in healthcare facilities. These technologies collectively enhance patient care, streamline medical processes, and advance medical research, making them great assets in the realm of medicine.¹⁵

Disadvantages of AI and Machine Learning

AI and machine learning, while beneficial in medicine, present challenges. They demand high-quality, unbiased data for accuracy and face regulatory complexities. The interpretability of deep learning models can be an issue, and initial implementation costs can be significant. Resistance to change and ethical concerns about biases are prevalent. AI is complementary to human expertise, not a replacement. Additionally, security risks related to patient data must be managed. Balancing these drawbacks is essential to harness the potential of AI and machine learning in healthcare responsibly and effectively.¹⁵

Applications of AI and Machine Learning

AI and machine learning have a profound impact on medicine, with diverse applications that improve patient care and advance medical research. They play a critical role in disease diagnosis by enhancing the accuracy of medical imaging interpretation and identifying specific biomarkers in genomic data.¹³ Personalized medicine benefits from AI’s ability to analyse patient data and tailor treatment plans, optimizing drug selection and dosages.¹⁶Healthcare professionals rely on AI-driven clinical decision support systems for evidence-based treatment recommendations. In drug discovery, these technologies expedite candidate identification, compound design, and the screening process.¹⁴Operational efficiency is boosted through AI in hospital management, patient scheduling, and inventory control.Predictive analytics assists in forecasting disease outbreaks, patient readmissions, and adverse events, allowing for proactive resourceallocation.Furthermore, AI is pivotal in telemedicine, remote patient monitoring, and drug repurposing, all contributing to the evolution of healthcare and medical research.¹⁵

Nano Technology

Nanotechnology is an actively advancing field that includes the manipulation and engineering of materials at the nanoscale, which generally ranges from 1 and 100 nanometres. It has found diverse applications, including drug delivery and medical imaging.¹⁶

Nano Particletypes

Nanoparticles come in various forms, each with unique characteristics suited to different applications.Liposomes, for instance, are small spherical vesicles with lipid bilayers that can encapsulate both hydrophobic and hydrophilic drugs.Micelles are another type of nanoparticle, typically formed by amphiphilic molecules, which can solubilize hydrophobic drugs in their core.¹⁷Quantum dots are semiconductor nanoparticles known for their remarkable fluorescent properties, making them useful in imaging and diagnostics.Polymeric nanoparticles are versatile and can be tailored for specific purposes, like controlled drug release. Dendrimers are large molecules; they consist of branches around an inner core in which the drug is loaded.¹⁷

Techniques of Nano Technology

Nanotechnology employs two primary methodologies: the top-down and bottom-up approaches.In the top-down approach, larger materials are reduced to the nanoscale through processes such as milling, etching, or lithography. This method allows for precision but may not be suitable for all materials.The bottom-up approach, on the other hand, involves assembling nanoparticles from atomic or molecular components.¹⁸ This approach is more versatile, as it enables the creation of custom-designed nanoparticles. Techniques like self-assembly and molecular beam epitaxy are used to build nanoparticles from the ground up.

Figure 2: Top-down and bottom-up synthesis of Nanoparticles26 Click here to view Figure

Nano Technology in Drug Delivery

Nanotechnology has revolutionized drug delivery.Nanoparticles function as drug carriers, improving drug solubility and bioavailability.They can target specific cells or tissues, delivering medication precisely where it’s needed, which reduces side effects and increases therapeutic efficacy.¹⁸Controlled drug release systems, created through nanotechnology, allow for sustained and predictable drug administration. Nanoparticles can also overcome biological barriers, like the blood-brain barrier, enabling the treatment of conditions that were previously difficult to reach.Moreover, nanotechnology allows for combination therapies, where multiple drugs can be delivered together for enhanced effectiveness.¹⁹

Nano Technology in Imaging

Nanotechnology is vital in the field of medical imaging, where it significantly enhances diagnostic capabilities.Nanoparticles, including quantum dots and superparamagnetic iron oxide nanoparticles, are used as contrast agents to improve the detection and visualization of pathological conditions.These particles are engineered to target specific tissues, thereby increasing imaging accuracy.²⁰ For instance, in magnetic resonance imaging (MRI), superparamagnetic nanoparticles help enhance image contrast, which aids in the diagnosis of diseases. Nanotechnology allows for continuous tracking of drug distribution in the body, offering valuable perspectives for both research and patient care.

Advantages of Nano Technology

The advantages of nanotechnology in medicine are substantial. It enables precise drug delivery which minimize adverse effects and improving therapeutic outcomes. Targeted therapy means that healthy cells are spared from potential harm. Additionally, nanotechnology facilitates personalized medicine by customizing treatment based on one’s genetic or physiological characteristics.Combination therapies, regenerative medicine, and improved vaccine development are all made possible by nanotechnology.¹⁷

Disadvantages of Nano Technology

Nanotechnology is not without its challenges.Safety concerns about the possible toxicity of nanoparticles exist, and more research is needed to understand and mitigate these risks. Regulatory agencies are making proposals for the safe use of nanotechnology in healthcare. There are also environmental concerns, as the disposal of nanoparticles can impact ecosystems.Ensuring the ethical and responsible use of nanotechnology is essential.¹⁹

Applications of Nano Technology

Nanotechnology has a wide range of applications, not only in medicine but also in fields such aselectronics, energy, and materials science.In medicine, it is transforming drug delivery, diagnostics,and regenerative medicine. It is enhancing imaging technologies and facilitating targeted and personalized treatments, makingsignificant advancements inhealthcare possible.²⁰ In electronics, nanotechnology is driving the development of smaller and more efficient devices, while in materials science, it’s contributing to the innovation of novel materials with uniqueproperties.In the energy sector, nanotechnology is aiding in the growth of more efficient solar cells and energy storage systems.²⁰

Gene therapy

Gene therapy is a revolutionary medical approach that aims to treat or cure genetic disorders by introducing, removing, or altering genetic material within a patient’s cells.The process typically involves the delivery of therapeutic genes into a patient’s cells to correct a genetic defect or modulate their function, offering the potential for long-lasting or even permanent treatment.²¹ 

Steps Involved in Gene Therapy

Gene-therapy generally follows a sequence of steps, starting with identifying the specific genetic defect causing the disorder.The next step involves the selection and design of therapeutic genes, which can either replace the defective gene, supplement its function, or regulate it.²²Once the therapeutic genes are ready, they are delivered to the patient’s cells, often with the use of viral vectors or non-viral methods.The therapy’s effects are then monitored, and any necessary adjustments are made to optimize treatment.This continuous assessment ensures the therapy’s safety and efficacy.²²

Gene Therapy in Drug Delivery Systems

Gene therapy can be integrated into drug delivery systems,re therapeutic genes are encapsulated within nanoparticles, liposomes, or other carriers.These systems protect the genetic material, facilitate controlled release, and enhance target-specific delivery.

By combining gene therapy with drug delivery, it’s possible to create highly targeted and efficient treatments for various diseases, such as cancer, where genetic manipulation can enhance the sensitivity of cancer cells to specific drugs.²²

Advantages of Gene Therapy

Gene therapy holds significant promise, as it offers the potential to address genetic disorders at their root cause.It can provide long-term or even permanent treatment solutions, reducing the need for lifelong medication.Gene therapies also have the potential to treat conditions with no existing cures.Additionally, it can be tailored to individual patients, promoting personalized medicine.²²

Disadvantages of Gene Therapy

Challenges associated with gene therapy include safety concerns, potential unintended genetic alterations, and immune responses to viral vectors used for gene delivery.The development and regulation of gene therapies require stringent testing and oversight.Furthermore, gene therapy may be costly and is not without ethical considerations, particularly when applied to germline editing or enhancement rather than disease treatment.²³

Applications of Gene Therapy

Gene therapy has shown tremendous potential in treatment of genetic disorders, inherited diseases, and certain types of cancer.²³It is also being explored for its applications in regenerative medicine, where it can stimulate tissue repair and organ transplantation.In recent years, gene therapy has made strides in the treatment of illness including severe combined immunodeficiency (SCID) and inherited blindness disorders, indicating its potential to transform healthcare by offering novel treatments for previously incurable diseases.²³

Crispr Technology

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats) is a groundbreaking gene-editing technology that enables exact changes to an organism’s DNA.Originally discovered as a natural defence mechanism in bacteria and archaea against viruses, CRISPR consists of two primary components: the Cas9 protein, which functions as molecular scissors, and a guide RNA (gRNA), which directs the Cas9 protein to the specific DNA sequence targeted for editing.The gRNA is designed to complement the target DNA sequence, and once Cas9 reaches the target, it creates a double-strand break in the DNA.The cell’s inherent repair processes then take over, either introducing the desired changes through non-homologous end joining (NHEJ) or facilitating accurate edits via homology-directed repair (HDR).²⁴

CRISPR has transformed genetic research, enabling gene modifications with remarkable precision and ease.Its applications span medicine, agriculture, and biotechnology, empowering scientists to explore gene functions, develop therapies for genetic disorders, and improve crop resilience to pests and environmental stressors.²⁴Despite its vast potential, CRISPR raises ethical and safety concerns, especially in human germline editing and the possibility of off-target effects, sparking ongoing discussions about its regulation and responsible use.²⁵

Future Implications and Challenegs

3d Printing

Positive Implications

3D printing presents numerous positive implications.One significant advantage is customization, as it enables the development of personalized and tailored products, fostering improved designs and solutions.¹Moreover, 3D printing is cost-efficient, minimizing material waste and enabling on-demand production, which can lead to economic benefits.The technology facilitates rapid prototyping, accelerating product development byproviding a quick and cost-effective means of creating prototypes.In the medical arena, 3D printing has transformed healthcare by allowing the manufacture of patient-specific implants, prosthetics and even organs, showcasing its potential for significant positive impact.¹

Negative Implications

Downsides encompass quality control issues and limited materials may restrict the range of applications and strength of printed objects.⁷ The ease of replicating objects raises concerns about intellectual property and copyright infringement.The disposal of 3D printed waste and the energy-intensive printing process may have environmental consequences.¹

Challenges

Overcoming regulatory approval hurdles and safeguarding intellectual property pose significant challenges in the field of 3D printing for drug manufacturing.¹⁰

Nanotechnology

Positive Implications

Nanotechnology offers a range of positive implications. In medicine, it facilitates targeted drug delivery, enhancing treatment efficacy and diminishing adverse effects.The engineering of materials at the nanoscale often results in enhanced properties, leading to the development of stronger products.Energy efficiency benefits from the use of nanomaterials, which can enhance the performance of energy storage and conversion devices.Furthermore, nanotechnology contributes to advancements in electronics, enabling the creation of smaller and more efficient electronic components.¹⁹

Negative Implications

Concerns about the potential toxicity of certain nanoparticles raise questions about health and safety.Regulatory challenges persist due to the lack of standardized regulations for nanotechnology applications, posing difficulties in ensuring the safety of these technologies.¹¹Ethical debates also surround the use of nanotechnology in areas such as human enhancement and privacy.¹⁶

Challenges

Ensuring nanomaterial safety and establishing effective regulatory oversight represent key challenges associated with nanomedicine.¹⁷

AI (Artificial Intelligence)

Positive Implications

Artificial Intelligence (AI) holds numerous positive implications for various industries. One of its major advantages is automation, which streamlines repetitive tasks, leading to increased efficiency and productivity.In healthcare, AI aids in medical diagnosis, drug discovery, and the development of personalized treatment plans.AI drives innovation across fields like robotics, natural language processing, and computer vision, contributing to technological advancements.Smart technologies, such as autonomous vehicles and smart homes, are made possible by the capabilities of AI.¹³

Negative Implications

Risks include data bias and regulatory complexities due to rapid technological advancements.Job displacement is a concern as automation may lead to the elimination of certain jobs.Issues of bias and fairness arise, as AI algorithms may perpetuate biases present in the data used for training, resulting in unfair outcomes.¹⁹Privacy challenges arise due to the massive collection and use of personal data for AI applications.Additionally, there are security risks associated with the potential misuse of AI for malicious purposes, including the creation of deepfake content and cyber-attacks.¹³

Challenges

Navigating issues related to data privacy, addressing algorithmic bias, and formulating comprehensive healthcare AI regulations are ongoing challenges.¹⁴

Gene Therapy

Positive Implications

Gene therapy offers promising positive implications, particularly in the realm of medical treatment. It holds the ability to treat genetic disorders by fixing or replacing defective genes, providing hope for those with hereditary conditions.In the field of oncology, gene therapy opens new avenues for targeted cancer treatments by modifying or replacing cancerous cells.Moreover, gene therapy can be applied as a preventive measure, addressing genetic predispositions to diseases before they manifest.²²

Negative Implications

Ethical dilemmas, disparities in access, and unforeseen consequences are linked to genetic editing.²³Manipulating the human genome raises ethical questions about the boundaries of intervention, touching on fundamental aspects of human identity and nature.²⁴The long-term effects of gene therapy, including unintended genetic changes, are not fully understood and require thorough investigation.Safety concerns exist, encompassing potential risks and side effects such as immune responses and off-target genetic alterations. Additionally, issues of access and affordability may limit the widespread application of gene therapies, leading to disparities in healthcare access.²⁵

Challenges
Ensuring safety, tackling the high costs of treatment, and addressing ethical concerns are significant challenges associated with gene therapy.²³

Discussion

This detailed analysis explores the potential impacts, advantages, and challenges associated with emerging drug technologies, including 3D printing, artificial intelligence (AI), nanotechnology, gene therapy, and CRISPR technology.

Personalized Medicine and Improved Patient Care

A key highlight of this article is the promise of personalized medicine. By utilizing 3D printing to create customized drug dosage forms, patient adherence can be enhanced while minimizing adverse effects. Additionally, AI-powered drug discovery can tailor treatment options based on an individual’s specific genetic and physiological characteristics. This level of personalization not only promises better treatment outcomes but also boosts patient satisfaction and engagement. The article underscores the revolutionary potential of these new technologies in putting the patient at the centre of healthcare.

Addressing Drug Discovery Challenges

The article illustrates how AI and machine learning are revolutionizing the drug discovery process. These technologies enable the automation of attribute extraction and the optimization of molecular designs, which accelerates the creation of new pharmaceutical compounds. This transformation has vast implications, including tackling antimicrobial resistance and developing more effective treatments for various diseases. However, the growing reliance on AI also raises important issues, such as the quality of data, privacy concerns, and the necessity for continuous validation and refinement of algorithms.

Precision in Drug Delivery

Nanotechnology and 3D printing are pivotal in advancing drug delivery methods. The ability to precisely target specific cells or tissues and tailor drug release profiles marks a significant breakthrough. This precision not only reduces side effects but also enhances the therapeutic efficacy of treatments. The article highlights the immense potential of these technologies in improving patient outcomes. However, it also stresses the need to address safety concerns, standardize practices in nanomedicine, and navigate the complexities of regulatory approvals for 3D printing.

Ethical Considerations and Responsible Innovation

The rapid advancements in gene therapy and CRISPR technology have sparked important ethical and safety concerns. While these innovations offer the potential to cure genetic disorders, they come with challenges such as disparities in access, high costs, and ethical questions surrounding genetic modification. The article appropriately stresses that responsible progress in these areas requires solid ethical frameworks, rigorous regulatory oversight, and an unwavering commitment to patient safety.

Conclusion

In conclusion, “Exploring the Future of Medicine: A Comprehensive Review of Emerging Drug Technologies” sheds light on the transformative potential of emerging drug technologies like 3D printing, artificial intelligence, nanotechnology, gene therapy, and CRISPR. These innovations have the power to personalize medicine, expedite drug discovery, and enhance precision in drug delivery. However, ethical considerations, safety concerns, and robust regulatory oversight are essential as we navigate this promising yet complex future of medicine, ensuring responsible innovation while striving to improve patient care and outcomes.

Acknowledgement

It is an expression of gratification and pride to look back with contentment on the long-travelled journey, to be able to recapture some of the fine moments, to be able to thank infinite number of individuals, some who were with us from the start, some who joined us at some point along the way, whose kindness, love and blessing has brought this day, we wish to thank each one of them with all our hearts. We would like to express our gratitude to our Principal Dr. Y.Srinivasa Rao Garu, and Chairman Dr. L. Ravu Rathaiah Garu for their supervision, advice and guidance.

Funding Sources

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Conflict of Interest

The authors do not have any conflict of interest.

Data Availability Statement

This statement does not apply to this article.

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval.

Informed Consent Statement

This study did not involve human participants, and therefore, informed consent was not required.

Clinical Trial Registration

This research does not involve any clinical trials.

Permission to reproduce material from other sources

Not Applicable

Author Contributions

Galanki Vasantha : Conceptualization, Supervision, Methodology, Writing- Review & Editing.

Singuluri Jashnavi Naga Sravya: Writing – Original Draft, Data Collection, Analysis

Bollipalli Sanath: Analysis  and Data Collection,

References

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Kiwifruit (Actinidia deliciosa) is famous for its flavor and nutritional value¹⁰ and can be stored for up to five months under normal refrigeration (0 °C and 92%–95% relative humidity).¹ However, during postharvest handling, these fruits become vulnerable to fungal infections, particularly through injuries sustained during harvesting and processing. Among the pathogens responsible for substantial postharvest losses, Cadophora luteo-olivacea—the causal agent of skin-pitting disease has recently become a serious postharvest problem in Italian packaging companies.⁴ This fungus infects the fruit during development and remains dormant until symptoms appear during prolonged cold storage (typically 3–4 months), causing substantial economic challenges for the kiwifruit industry.³

Biological control methods offer a sustainable alternative to chemical fungicides, especially given concerns about chemical residues, environmental impact, and the emergence of resistant pathogens.⁹ Among the various mechanisms of actions used by antagonistic microbes, the emission of antifungal volatile organic compounds (VOCs) has gained attention for their antifungal properties, although this strategy is still relatively underexplored (Spadaro & Droby).⁷

Several biological control agents (BCAs), including bacterial species from the genera Pseudomonas and Bacillus, are known to produce volatile compounds capable of antifungal properties.⁸ Previous research demonstrated that P. synxantha VOCs showed a considerable reduction in kiwifruit infections caused by C. luteo-olivacea and Botrytis cinerea, highlighting its potential as a biological control agent.² However, Bacillus pumilus have gained increasing attention due to their ability to produce a wide spectrum of antifungal metabolites but, little is known about the effectiveness of VOCs from B. pumilus against C. luteo-olivacea, especially under realistic storage conditions.

Therefore, the present study explores the antifungal action of VOCs emitted by B. pumilus QST2808, both in laboratory settings and during cold storage against C. luteo-olivacea. Additionally, its performance is compared with the well-known VOC-producing strain P. synxantha 1172b. This research aimed to contribute to integrated postharvest disease control strategies using bacterial VOCs in kiwifruit storage.

Materials and Methods

Fruits and Microorganisms

In Friuli Venezia Giulia (FVG), Italy, the commercially ripe kiwifruit cultivar “Hayward” [Actinidia deliciosa (A. Chev)] were harvested from an orchard. Prior to the experiment, only fruits that were uniform in size and free of obvious lesions were chosen, and they were kept at 0°C and 92% relative humidity for five days.

At the University of Udine-Di4A, the fungal strain C. luteo-olivacea (Cad21) was isolated from infected kiwifruit tissue and molecularly identified. Before the experiment, fungal cultures were maintained at 25°C for two weeks on potato dextrose agar (PDA; 39 g L⁻¹, Oxoid, UK).

An active component of the biocontrol product Sonata^®, the bacterial strain B. pumilus QST2808, was acquired from the Northern Regional Research Laboratory (NRRL), located in Illinois, USA. Bacterial strains were cultivated on nutrient agar (NA; 13 g L⁻¹, Oxoid, UK) at 25°C. Bacterial cultures were grown and maintained on nutrient agar (NA; 13 g/L, Oxoid, UK) at 25 °C. To achieve a concentration of 1×10⁸ cells/mL, a two-day-old culture was prepared in potassium phosphate buffer (PPB); which was made with 70 mL of 0.2 M KH₂PO₄, 30 mL of 0.2 M K₂HPO₄, and 300 mL deionized water; the pH adjusted to 6.5) to reach a concentration of 1×10⁸ cells/mL.

In-vitro assay

A double Petri dish method was used to assessed the antifungal activity of volatile organic compounds (VOCs) generated by B. pumilus QST2808 against the mycelial development of C. luteo-olivacea (Cad21) by using the protocol of Di Francesco et al. (2023) with slight modifications. B. pumilus QST2808 bacterial suspension (1 × 10^⁸cells mL⁻¹) was equally distributed on nutritional agar (NA) plates. While P. synxantha 1172b (1 × 10⁸ cells mL⁻¹) served as the positive control. Mycelial plugs (6 mm in diameter) of C. luteo-olivacea were extracted from 14-day-old cultures and placed in the middle of potato dextrose agar (PDA; 39 g L⁻¹, Oxoid, UK) plates. The NA plate with bacterial growth was inverted over the PDA plate containing the fungal plug, and both plates were sealed with Parafilm® to form a double-plate system. The negative control consisted of plates treated with 100 µL of sterile distilled water (SDW) on NA. All plates were incubated at 25 °C in darkness for 14 days. The experiment was carried out twice independently, with five replications of each treatment.

In-vivo assay

An in-vivo biofumigation carried out to evaluate the potential and role of  volatile organic compounds (VOCs) generated by B. pumilus QST2808 to improve the kiwifruit resistance to skin-pitting during cold storage. The bottom of sterile plastic boxes measuring 29 × 18 × 10 cm (L × W × H) was filled with 150 mL of nutrient agar (NA). After solidification, the agar surface was evenly covered with 600 µL aliquot of a B. pumilus QST2808 solution (1×10⁸ cells mL⁻¹). The boxes were then sealed with Parafilm^® and incubated for 48 hours at 25 °C to allow for the buildup of volatile organic compounds.

During this period, kiwifruits were rinsed with distilled water, allowed to air dry, and then disinfected using 0.1% (v/v) sodium hypochlorite for one minute. A sterile nail was used to make wound at the equator (2 × 2 × 2 mm) of the fruit, to inoculate each fruit with 20 µL of C. luteo-olivacea (Cad21) conidial suspension (1×10⁵ conidia mL⁻¹). To prevent direct contact with the medium, the fruits were placed on sterile grids inside the containers once the inoculum had dried. After that, the containers were incubated for 96 hours at 15 °C and 85% relative humidity. Subsequently, the fruits were moved to cold storage at 0 °C for a period of three months. Each treatment group consisted of three containers, with eight kiwifruits in each.

P.synxantha 1172b was used as the positive control for the biofumigation treatment, while control treatments consisted of containers containing NA without bacterial inoculation.

Statistical analysis

Minitab 17 (Minitab Inc., State College, PA, USA) was used to analyse all experimental data using one-way analysis of variance (ANOVA). Tukey’s Honest Significant Difference (HSD) test was used to compare the means of fungal colony diameter and disease severity at a significance level of α = 0.05. The mean ± standard error is used to present the results.

Results

In-vitro assay

The double-plate assay confirmed that the volatile organic compounds (VOCs) released by B. pumilus QST2808 effectively suppressed the growth of C. luteo-olivacea (Cad21). As shown in Figure 1, exposure to these VOCs led to a 52% reduction in fungal colony diameter compared to the untreated control. Similarly, P. synxantha 1172b, used as a positive control, demonstrated a 56% inhibition in mycelial expansion relative to its respective control.

In-vivo assay

The in vivo biofumigation assay further reinforced the antifungal efficacy of B. pumilus VOCs under realistic postharvest storage conditions. As shown in Figure 2, after 96 hours of VOC exposure and subsequent cold storage at 0 °C for three months, fruits treated with B. pumilus VOCs exhibited a 28.5% reduction in skin-pitting severity compared to the untreated control. Similarly, VOCs from P. synxantha 1172b resulted in a 32% reduction in disease severity. 

Figure 1: In-vitro impact of B. pumilus QST2808 and P. synxantha 1172b’s volatile organic compounds (VOCs) on C. luteo-olivacea (Cad21) mycelial growth. Colony diameters (mm) were measured following a 14-day incubation period at 25°C.   Click here to view Figure

Figure 2: Effect of VOCs from P. synxantha 1172b and B. pumilus QST2808 on skin-pitting severity (%) caused by C. luteo-olivacea on kiwifruit after 96 h VOC exposure and three months of cold storage at 0 °C.   Click here to view Figure

 Data represent mean disease severity (%) ± standard error of 24 fruits per treatment. According to Tukey’s HSD test, different letters denote statistically significant differences between treatments (α = 0.05).

Discussion

The results from both in-vitro and in-vivo studies highlighted how effective the VOCs compounds produced by B. pumilus QST2808. The reduction in fungal colony diameter in the in-vitro setup suggests that VOCs interfere with fungal metabolism and inhibit hyphal growth without direct contact. These outcomes are in line with the earlier research showing that the VOCs produced from B. pumilus have antifungal properties. For example, Morita et al discovered that B. pumilus TM-R produced antifungal volatile organic compounds (VOCs) like ethanol, 5-methyl-2-heptanone, methyl isobutyl ketone, and S-2-methylbutylamine, which inhibited the growth of Penicillium italicum and other fungal infections.⁶  The inhibitory effect observed in our study suggests that B. pumilus QST2808 may produce similar compounds, which interfere with fungal metabolism and inhibit hyphal growth, thus contributing to pathogen suppression without physical contact.

The in-vivo biofumigation results further confirm the practical potential of using B. pumilus QST2808 VOCs in real postharvest storage environments. Although the reduction in disease severity was not statistically significant, indicating variability under natural storage conditions and the consistent downward trend suggests that VOCs may contribute to disease suppression or induce resistance mechanisms in the fruit. These outcomes are consistent with the findings of Yuan et al’s research , which showed that VOCs from Bacillus velezensis P2-1 reduced postharvest decay in apples caused by Botryosphaeria dothidea.¹¹ The effectiveness of VOCs in these studies reinforces their potential as safe, residue-free alternatives to synthetic fungicides.

Interestingly, the comparable efficacy observed between B. pumilus QST2808 and P. synxantha 1172b underscores the broader applicability of bacterial VOCs in managing kiwifruit postharvest diseases. The results of this study are supported by earlier research by Di Francesco et al which also demonstrated the role of P. synxantha VOCs in suppressing C. luteo-olivacea and B. cinerea.²

Taken together, the results from both in vitro and in vivo assays confirm that VOCs produced by B. pumilus QST2808 possess antifungal activity against C. luteo-olivacea, making them promising candidates for biofumigation in integrated postharvest disease management strategies. Future investigations should aim to identify and characterize the specific VOCs responsible for antifungal activity, optimize exposure conditions, and evaluating their effects on fruit quality and shelf life under commercial conditions.

Conclusion

The study’s conclusions demonstrate the antifungal properties of the volatile organic compounds (VOCs) produced by B. pumilus QST2808 in mitigating the symptoms of skin pitting in kiwifruit that are brought on by C. luteo-olivacea. The effectiveness observed in both in vitro and in vivo assays indicates its suitability as a biofumigation strategy for postharvest disease management. However further investigation is required to optimize treatment conditions, assess consistency across storage environments, and evaluate potential for commercial application.

Acknowledgment

The authors would like to thank the University of Udine for providing technical support.

Funding  Sources

This work was supported by Convenzione ERSA for the project “Sviluppo e adattamento del kiwi al cambiamento climatico e alle sindromi emergenti” (CUP: F23C23000300002).

Conflict of Interest

The authors do not have any conflict of interest.

Data Availability Statement

This statement does not apply to this article.

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval.

Informed Consent Statement

This study did not involve human participants, and therefore, informed consent was not required.

Clinical Trial Registration

This research does not involve any clinical trials.

Permission to reproduce material from other sources

Not Applicable

Author Contributions 

Farwa Jabeen: Conceptualization, Methodology, Investigation, Data Analysis, Writing – Original Draft.

Marta Martini: Supervision, Writing – Review & Editing.

Paolo Ermacora: Supervision, Project Administration, Writing – Review & Editing, Correspondence.

References

1. Di Francesco A, Jabeen F, Di Foggia M, et al. Study of the efficacy of bacterial antagonists against Cadophora luteo-olivacea of kiwifruit. Biol Control. 2023;180:105199.
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2. Di Francesco A, Jabeen F, Vall-Llaura N, et al. Pseudomonas synxantha volatile organic compounds: efficacy against Cadophora luteo-olivacea and Botrytis cinerea of kiwifruit. Front Plant Sci. 2024;15:1398014.
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3. Jabeen F. Biocontrol Strategies for Effective Kiwifruit Post-Harvest Disease Management. 2024.
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4. Jabeen F, Di Francesco A, Sadallah A, Ermacora P, Martini M. Biocontrol strategies in the management of Cadophora luteo-olivacea, skin-pitting agent of kiwifruit. In: VI International Symposium on Postharvest Pathology: Innovation and Advanced Technologies for Managing Postharvest Pathogens; 2022:75-80.
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5. Jiang Q, Zhang M, Xu B. Application of ultrasonic technology in post-harvested fruits and vegetables storage: a review. Ultrason Sonochem. 2020;69:105261.
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6. Morita T, Tanaka I, Ryuda N, Ikari M, Ueno D, Someya T. Antifungal spectrum characterization and identification of strong volatile organic compounds produced by Bacillus pumilus TM-R. Heliyon. 2019;5(6):e01965.
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7. Spadaro D, Droby S. Development of biocontrol products for postharvest diseases of fruit: the importance of elucidating the mechanisms of action of yeast antagonists. Trends Food Sci Technol. 2016;47:39-49.
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8. Sukmana AS, Nurcahyanti SD, Nurdika AAH. Biological control of bacterial wilt (Ralstonia pseudosolanacearum) in tomato (Solanum lycopersicum) using an avirulent strain, Bacillus, and Pseudomonas fluorescens. Arch Phytopathol Plant Prot. 2025;58(4):202-222.
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9. Tsalgatidou PC, Papageorgiou A, Boutsika A, et al. Insights into the interaction between the biocontrol agent Bacillus amyloliquefaciens QST 713, the pathogen Monilinia fructicola and peach fruit. Agronomy. 2024;14(4):771.
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10. Wang H, Zhang X, Li K, et al. Glycerol treatment enhances resistance to soft rot disease and maintains postharvest quality in kiwifruit. Postharvest Biol Technol. 2025;228:113630.
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11. Yuan H, Wang L, Hou H, et al. Antifungal activity and mechanism of volatile organic compounds produced by Bacillus velezensis strain P2-1 against Botryosphaeria dothidea-induced postharvest decay in apples. Postharvest Biol Technol. 2025;222:113405.
    CrossRef

Coronaviruses (CoVs) are associated with the extended family of positive, encased, extensively diverse, and single-stranded RNA viruses.^1,2 Coronaviruses were first perceived in the mid-1930s, and the first human coronavirus was notified in 1960, causing common cold-like symptoms.^3–5 In 2003, a beta (β) – coronavirus emerged from bats and disseminated through the palm civet (mediator host). It was transmitted to humans in China’s Guangdong territory, where it was designated as the SARS (Severe Acute Respiratory Syndrome) virus, affecting approximately 8422 people, 916 of whom died. ^4,6 In the middle of 2012, the initial instance of MERS (Middle East Respiratory Syndrome) was identified in Jeddah, Saudi Arabia. It emerged from bats, but the mediator host was a camel, and it affected 2994 individuals, 858 of whom died.^4,7 Wuhan, China was the initial location to identify instances of the COVID-19 obtained from patients with pneumonia. Later, it spread globally to almost every country, creating a nationwide lockdown.^4,8,9

The WHO (World Health Organization) designated the outbreak as COVID-19 (Novel Coronavirus Disease 2019), which is caused by the SARS CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), on February 11, 2020. The assumed method of spreading COVID-19 is from one person to another through droplets expelled by infected individuals when they cough or sneeze nearby.^1,10,11 The primary signs of COVID-19 include are pyrexia (fever), tussis (cough), emesis (vomiting), and diarrhea.^1,12 The major health issues caused by SARS CoV-2 include and multiple organ failure, sepsis, ARDS (acute respiratory distress syndrome), septic shock, which are associated with co-morbidities (cancer, immunodeficiency, immunosuppressive disorders, cardiovascular diseases, diabetes, and asthma) (Table 1).^13–16 The geriatric section and patients with co-morbidities or chronic diseases are specifically vulnerable populations.^1,17 Nearly five years have passed since the first COVID-19 cases were reported in Wuhan, China. Over the past few challenging years, we’ve explored a variety of treatment approaches, implemented preventative measures, embraced social distancing, and fueled groundbreaking vaccine research. Unfortunately, in spite of these initiatives, especially concerning pharmacotherapy and patient management, over 775 million people worldwide have contracted SARS-CoV-2, and more than 7 million of those cases have resulted in death from COVID-19 infection. Furthermore, based on epidemiological mortality rate assessment research, the death rate has surpassed 18.2 million so far, and this deadly epidemic will claim many lives.¹⁸

Table 1: Symptoms, Disease Pathogenesis and Clinical Manifestations Observed in Different Stages of COVID-19.

Materials and Methods 

A comprehensive review was conducted to evaluate the progression of the SARS-CoV-2 virus (COVID-19), its impact on public health, associated neurological complications, and the available treatments and vaccination approaches. The review was based on an extensive search of peer-reviewed literature published on the COVID-19. The following methods were employed:

Literature Search Strategy

A systematic search was performed across multiple electronic databases including PubMed, ResearchGate, Scopus, Semantic Scholar, and Google Scholar. The search strategy incorporated a broad set of keywords related to COVID-19, such as: “COVID-19”; “SARS-COV-2”; “Coronavirus”; “SARS-COV-2 Variants”; “SARS-COV-2 Taxonomy”; “COVID-19 Pathology”; “COVID-19 Diagnosis”; “COVID-19 Comorbidities”; “COVID-19 Cardio-Vascular Disorder”; “COVID-19 Hypertension”; “COVID-19 Diabetes”; “COVID-19 Neurological Disorders”; “COVID-19 Encephalopathy”; “COVID-19 Guillain-Barré Syndrome”; “COVID-19 Stroke”; “COVID-19 Treatments”; “COVID-19 Immunomodulatory Treatment”; “COVID-19 Antiviral Drugs”; and “COVID-19 Vaccines”. Studies were selected based on relevance, quality, and inclusion of information on the virology, pathology, comorbidities, neurological impact, and vaccine development significantly centred on the topic “COVID-19”.

Selection Criteria

This review article included original research articles, reviews and studies that provided information on the structure and taxonomy, as well as the immuno-pathophysiology of SARS-CoV-2. Additionally, it incorporated studies exploring the relationship between comorbidities and COVID-19, investigations into the neurological effects of COVID-19, and articles highlighting COVID-19 management as well as examining the development, efficacy, and safety of COVID-19 vaccines. 

Results

Eligible studies, including full-text reviews and original research articles focused specifically on COVID-19, were critically reviewed to extract data on viral taxonomy, structural virology, immuno-pathogenesis, neurological complications, treatments, and vaccine development. The extracted data was then categorized into the following areas:

Taxonomy and Structural Virology

Information on the classification of SARS-CoV-2 within the coronavirus family and its structural composition and units.

Immuno-Pathophysiology of SARS-CoV-2

Insights into the mechanisms of SARS-CoV-2 viral entry and developing a disease severity.

Neurological Complications

Information on the incidence and types of neurological complications associated with COVID-19

Rapid Detection of COVID-19

Methods and technologies for the swift identification of COVID-19, including rRT-PCR tests, lateral flow immunoassay, and emerging diagnostic tools for early detection.

Impact of Comorbidities on COVID-19 Severity

Insights into how underlying conditions like diabetes, hypertension, and cardiovascular disease exacerbate the severity of COVID-19.

Treatment Strategies

An overview of antiviral agents, immunomodulatory treatments, neutralizing antibodies, convalescent plasma therapy, and antithrombotic therapy, along with their application in managing mild to severe COVID-19 cases.

Comprehensive List of COVID-19 Vaccines

An overview of available COVID-19 vaccines, highlighting their adverse effects, effectiveness, and efficacy against various SARS-CoV-2 variants.

By following this systematic approach, this review article offers a comprehensive summary of viral taxonomy, structural virology, immuno-pathogenesis, neurological complications, treatment strategies, and vaccine development , all focused specifically on COVID-19. 

Discussion

Taxonomy, Structural Virology and Circulating Sars-Cov-2 Variants

The International Committee on Taxonomy of Viruses (ICTV) classified coronaviruses under the order Nidovirales and the family Coronaviridae and subfamily Orthocoronavirinae (Figure 1A).²¹ The ‘Coronavirus’ is named since the outer surface of the virus contains crown-like spike projections. ² Based on serological evidence, the subfamily Orthocoronavirinae is divided into four genera: α-CoVs (alpha-coronavirus), β-CoVs (beta-coronavirus), ϒ-CoVs (gamma-coronavirus), and δ-CoVs (delta-coronavirus) (Figure 1A).^4,22,23 Coronaviruses are generally nurtured in mammals (bats, camels, cattle, cats, etc.) and birds. Alpha and beta-coronaviruses infect mostly mammals, whereas gamma-coronaviruses primarily infect birds and a few mammals. However, delta-coronaviruses infect both. Animal coronaviruses largely infect domestic birds and animals, affecting productivity along with economic loss. ^22,23 These animal coronaviruses include Porcine Epidemic Diarrhoea Virus (PEDV), Avian Infectious Bronchitis Virus (IBV), Transmissible Gastroenteritis Virus (TGEV), and Swine Acute Diarrhoea Syndrome Coronavirus (SADS‐CoV). Coronaviruses are unusually potent human infectors and could spread through from one person to another. The initial coronaviruses identified were IBV, which caused respiratory illness in chickens, and Human Coronavirus 229E and OC43 (HCoV OC43 and HCoV 229E), which caused common cold-like symptoms in humans. Several other human coronaviruses were identified, such as in 2002 [Severe Acute Respiratory Syndrome Coronavirus (SARS‐CoV)], in 2004 [Human Coronavirus (HCoV)-NL63], in 2005 [Human Coronavirus (HCoV)- HKU1], in 2012 [Middle East Respiratory Syndrome-Coronavirus (MERS‐CoV)], and the recent global pandemic [Severe Acute Respiratory Syndrome Coronavirus 2 (SARS CoV-2)]. ^9,22,24–27

Coronaviruses are observed under an electron microscope as minute, spherical, enveloped particles 60 to 140 nm in diameter, made up of single-stranded RNA (26 to 32 kbs in length). ^2,4,28 The coronavirus mRNA encodes the four structural proteins: Spike (S) protein, Nucleocapsid (N) protein, Membrane (M) protein, and Envelope (E) protein (Figure 1B). The spike glycoprotein (S-protein) projections are a vital characteristic feature of coronaviruses. ⁴ It forms the bulky glycosylated peplomers embedded in the lipid bilayer, mediates attachment to the Angiotensin-Converting Enzyme 2 (ACE2) receptor, and facilitates membrane fusion to initiate viral pathogenicity in the host cell. The embedded hemagglutinin-esterase (HE) dimer designs the minute spikes on the viral outer surface. The positive-sense viral RNA is integrated with the viral nucleotide N-protein to form the nucleocapsid, which plays an important role in viral replication and transcription. The hydrophobic trans-membrane protein (M-protein) is the most prominent viral surface glycoprotein and is assumed to be the central organiser for assembling the coronaviruses. The trans-membrane envelope glycoprotein (E-protein) is the minor component of the coronaviruses and plays a prominent role in virus assembly, host cell membrane permeability, and also virus-host cell interaction.^2,4,22,28,29

Eventually, researchers discovered a worldwide dominant variant, D614G, which was associated with increased transmissibility but not the potential to cause severe illness.³⁰ Several SARS-CoV-2 variations have been reported since then, some of which are regarded as variants of concern (VOCs) because they may result in increased transmissibility or pathogenicity. A categorization method for differentiating the new SARS-CoV-2 variations into variants of interest (VOIs) and variants of concern (VOCs) has been separately developed by the World Health Organisation (WHO) and the United States Centres for Disease Control and Prevention (CDC) (Table 2). ³¹ Fortunately, no SARSCoV-2 variant that satisfies the VOC requirements is currently in circulation. Certain Omicron lineages, such as EG.5, XBB.1.5, and XBB.1.16, are considered to be VOIs that are currently in circulation (Table 2).¹⁸ A number of Omicron lineages have been identified as presently circulating variants under monitoring (VUMs), such as XBB, XBB.1.9.1, and XBB.2.3. Information about the immunological escape, growth rate, and transmissibility of these new Omicron lineages is limited. These lineages have been associated with the following primary spike mutations: I332V, D339H, R403K, V445H, G446S, K444T, L452R, N450D, L452W, E180V, T478R, F486P, N481K, 483del, and E484K. More research and observation are necessary because the epidemiological and phenotypic effects of these mutations and associated lineages are still uncertain.¹⁸ 

Figure 1: Illustrating the taxonomical and schematic structure of SARS CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2). Click here to view Figure

Schematically representing the taxonomical classification of coronaviruses. Constructed using the following references: ^{2,4,9,21–27,32}

Schematic structure of SARS CoV-2. Constructed using the following references: ^2,4,22,28,29 and this figure was partially made using Servier Medical Art ³³

Table 2:  System of Classification for Differentiating the Emerging SARS-CoV-2 Variants. 

Immuno-Pathophysiology of SARS-COV-2

The genome of a coronavirus consists of about 30,000 nucleotides, and its structural proteins are encoded by its mRNA.^1,28 Earlier research shows that the main targets of SARS-CoV are the host’s pulmonary system, especially the macrophages, alveolar epithelial cells, vascular endothelial cells, and airway epithelial cells, which have Angiotensin-Converting Enzyme 2 (ACE2) receptors. In a similar manner, SARS-CoV-2 utilizes the ACE2 receptor on the host cell to facilitate entry (Figure 2). When the virus attaches to the ACE2 receptor, it reduces its expression and causes the lung cells to down-regulate, which results in acute lung damage.^37–46

The two subunits that make up the spike (S) glycoprotein are S1 and S2. An ATD (Amino-Terminal Domain) and a RBD (Receptor-Binding Domain) make up the subunit S1. ^43,47–49 The RBD starts the viral infection phase by attaching itself to the host cellular target ACE2. RBD connects to the cellular receptor ACE2, which triggers the endocytosis of SARS CoV-2 virion and exposes it to the host endosomal proteases furin and trypsin. HR1 and HR2, the Heptad Repeat Regions, and the FP (Fusion Peptide) region make up subunit S2. After the subunit S1 is broken down within the endosome, FP emerges and enters the host membrane. The viral payload is subsequently released into the host cell’s cytoplasm when the subunit S2 coincides on itself to connect the two heptad repeat sections in proximity, triggering the membrane fusion (Figure 2). ^43,50–52 Biophysical tests and computer modelling show that the RBD of SARS CoV-2 attaches to ACE2 with greater proximity than that of SARS-CoV. Like MERS-CoV and HC-OC43, the spike glycoprotein of SARS-CoV-2 forms a furin-like cleavage site, increasing the pathogenicity in comparison to SARS-CoV. TMPRSS2 (Transmembrane Protease Serine 2) is necessary for the recognition of the SARS CoV-2 spike glycoprotein and for facilitating the viral entrance into the host cell. ^43,53,54 After the virus enters the host cell’s cytoplasm by endocytosis, the SARS CoV-2 RNA gets released and processed into two polyproteins and structural proteins that eventually replicate the virus’s genome. ^1,28 The replicating viral component mediates viral genome replication and is composed of an exonuclease N, a helicase, an RdRp (RNA-dependent RNA polymerase), and other related proteins.⁵⁵ The mechanism by which N protein encapsidates duplicated genomes in the cytoplasm results in nucleocapsids, which then consolidate within the membrane to self-assemble into new virions. The ER (Endoplasmic Reticulum) and Golgi Apparatus membranes both include the recently synthesised structural glycoproteins in the cytoplasm, which are then transferred to the ERGIC (Endoplasmic Reticulum-Golgi Intermediate Compartment). ^1,28,56 Finally, the novel virions are fused with the plasma membrane via exocytosis, and the virus is released (Figure 2).^1,28

The released virus instigates the host cell to initiate pyroptosis and release ATP, ASC oligomers, Interleukin-1 (IL-1), and nucleic acids, which constitute the Damage-Associated Molecular Patterns (DAMPs). Adjacent epithelial cells, alveolar macrophages, and endothelial cells recognise the released danger signals (DAMPs), which trigger pro-inflammatory cytokines (such as TNF [Tumor Necrosis Factor-alpha]–α; TGF [Transforming Growth Factor-beta]–β; IFN [Interferon-alpha]–α,γ; Interleukin [IL]–1β, 6, 12, 18, 33, 281) and chemokines (such as CCL [C‑C motif chemokine ligand]–2, 3, 5, and CXCL [C-X-C motif chemokine]–8, 9, 10).^{1,13,43,57–59} T cells, macrophages, and monocytes are drawn to the infection site by pro-inflammatory chemokines and cytokines, which also promote further inflammation through the production of interferon-gamma (IFN-γ) by T cells and a pro-inflammatory feedback looping mechanism. When the spike glycoprotein of SARS CoV-2 binds to the ACE2 receptor, it affects the RAS and causes vascular permeability. This can result in a faulty immunological response where immune system cells build up in the lungs, producing excessive pro-inflammatory cytokines and adversely impacting the lung (Figure 2). ^{1,28,37–39,43,56} The subsequent cytokine storm spreads to neighboring organs, leading to malfunction or failure of several organs. Moreover, through Antibody-Dependent Enhancement (ADE), non-neutralizing antibodies produced by B lymphocyte cells (B cells) increase the SARS CoV-2 disease and exacerbate organ dysfunction or injury. In favorable immune responses, virus-specific CD⁴⁺ and CD⁸⁺ T cells draw in and destroy the virus at the onset of inflammation, preventing it from spreading. The alveolar macrophages recognizes the viral cells and neutralized them. They phagocytose the apoptotic cells to eliminate the virus and maintain minimal lung damage with resultant recovery.^{1,13,43,57–59}

Figure 2: The plausible immunopathogenesis mechanism of SARS-CoV-2. Click here to view Figure

Constructed using the following references:^{1,13,28,37–40,42–54,56–60} and this figure was partially made using Servier Medical Art³³

Rapid Detection of COVID-19

Rapid diagnosis or detection is a predominant health care function since it imparts details about the health issues of a patient and provides consecutive decisions.⁶¹ The vital advantages of rapid diagnostic techniques are the prospect of rapid intervention and a focused solution to potential problems. Similarly, COVID-19 can be detected using rapid diagnostic techniques like RT-PCR (real-time polymerase chain reaction), primary screening through an immunodiagnostic test (rapid antibody test), and finally by Artificial Intelligence (AI)-based image processing techniques such as chest X-ray and CT (Computed Tomography) scan (Figure 3A).^4,61,62

The most recent technique for qualitatively and quantitatively identifying the SARS-CoV-2 nucleic acid in both upper and lower respiratory swab samples in the intense period of illness is real-time reverse transcription-polymerase chain reaction, or rRT-PCR.^4,61,62 One of the best and most efficient scientific techniques for tracking, treating, and analyzing the COVID-19 is rRT-PCR. By using particular primers for the COVID-19 viral genes, cDNA is produced using this technique from the COVID-19 virus’s retrieved RNA. Specific areas of cDNA (target genes) are amplified and identified using various fluorescent dyes (Figure 3B). The use of rRT-PCR assays has several important advantages, but the main one is that the amplification and analysis would take place in a contained system, reducing the likelihood of false-positive findings.^63–66

After contracting SARS-CoV-2, the patient produces IgM or IgG antibodies which are specific for the viral antigens to the receptor binding domain (RBD), the spike glycoprotein (S1, S2 subunits), or the nucleocapsid (N) protein.^67,68 IgM first appears after infection and remains detectable for a couple of days and then IgG follows. All current quick SARS-CoV-2 antibody assessments rely on the ability of the N, S1, S2, or RBD domain of the SARS-CoV-2 spike protein to associate with IgM or IgG antibodies in the patient’s blood.^68–70 Time-dependent detection of IgM or IgG isotypes only reaches high sensitivity around three weeks after symptoms start.^68,71 Lateral flow detection [Lateral Flow Immunoassay (LFIA)] is used in rapid SARS-CoV-2 antibody testing (Figure 3C).^68,72 The blood sample taken from the person who has a suspected COVID-19 infection is used for LFIA. In lateral flow testing, an absorbent pad attached to the leading edge of the strip allows an antigen or antigen-antibody complex to flow across it. The polymeric strip’s different zones are travelled by a liquid sample that contains the analyte. As a sponge, the sample pad allows fluid to go to the next conjugate pad after it has been moistened. A chemical reaction between an antigen and an antibody can be carried out using the chemicals included on the conjugate pad. The antigen passes through the pad, leaving a mark behind. The antigen continues to flow via the test and control lines. Following its passage through these lines, the fluid enters a porous material that serves as a disposal storage.⁷² Observations are made based on the state of the patient and can be classified into the following categories: negative (just the control sign formed), IgM positive (both the IgM mark and control markings formed), IgG positive (both the IgG mark and control markings formed), or just both IgG and IgM positive (both the IgM and IgG markings developed along with the control line) (Figure 3C).^72,73

Figure 3: Quick methods for identifying or diagnosing COVID-19. Click here to view Figure

Rapid detection or diagnostic methods for detecting COVID-19. Constructed using the following references: ^4,61,62,74 and this figure was partially made using Servier Medical Art³³

The classic rRT-PCR (real-time reverse transcription-polymerase chain reaction) procedure is demonstrated, in which viral RNA is isolated and transformed into cDNA. By using rRT-PCR, specific regions of cDNA (target genes) are amplified and identified. Constructed using the following references: ^63–66 and this figure was partially made using Servier Medical Art³³

Steps representing LFIA (lateral flow immunoassay)-based COVID-19 diagnosis. Constructed using the following references:^67–72,74 and this figure was partially made using Servier Medical Art³³

Comorbidities of Cardiovascular Disease, Diabetes, and Hypertension in the Context of COVID-19

Patients with COVID-19 are more likely to have acute cases and greater fatality rates if they have underlying comorbidities and are older than 70. The prominent comorbidities that are associated with COVID-19 are cardiovascular diseases, diabetes mellitus, and hypertension.^16,75–78 This can be suggested by a study conducted by Li et al.,¹⁷ among 1527 COVID-19 patients admitted; 17.1% had hypertension, 16.4% had cardiovascular disease, and 9.7% had diabetes mellitus. ¹⁷ The survey by Huang et al.,¹³ comprised 41 hospitalized patients with a confirmed COVID-19 infection; 32% of these patients had concomitant conditions such as cardiovascular illnesses (15%), diabetes (20%), and hypertension (15%).¹³ Similarly, the study of Wang et al.,⁷⁹ suggests the prevalence of one or more comorbidities (likely 31% of patients with hypertension, 14.5% with cardiovascular diseases, and diabetes 10.0%) in 64 individuals from 138 hospitalized COVID-19 patients.⁷⁹ In general, COVID-19 infects both sexes; however, men have a 3.6% case fatality rate compared to women’s 1.6%.⁸⁰ Patients with cardiovascular diseases who contracted COVID-19 were three times more likely to experience an acute illness or require admission to the intensive care unit (ICU) than those with diabetes mellitus or hypertension.^17,76,80 According to a Chinese Centre for Disease Control and Prevention⁸¹ study, 44,672 patients out of 72,314 distinct records had COVID-19 confirmed in them; 1,023 of these patients died, resulting in a crude case fatality rate of 2.3% (number of confirmed mortality divided by the overall number of confirmed infections). Additionally, a greater fatality frequency was noted for individuals with underlying comorbidities: 10.5% of patients having cardiovascular disorders, 7.3% of patients with diabetes, and 6.0% of patients with hypertension.⁸¹

A survey by Chen et al.,⁸² involving 99 patients confirmed with COVID-19 revealed that 51% of the admitted patients were detected with chronic medical illness (40% with cerebrovascular or cardiovascular disease). ⁸² A retrospective multi-centre study by Ruan et al.,⁸³ included 150 patients with confirmed COVID-19 and found that people with cardiovascular diseases have a much higher risk of dying from SARS-CoV-2 infection.⁸³ Secondary infections were seen in 1% (1/82) and 16% (11/68) of the patients in the discharge group and death groups, respectively. According to laboratory results, white blood cell counts, platelets, absolute values of lymphocytes, total bilirubin, albumin, blood creatinine, blood urea nitrogen, cardiac troponin, CRP (C-reactive protein), IL-6 (interleukin-6), myoglobin, and all were significantly different between the two groups.⁸³ According to reports, SARS-CoV-2 is thought to infect the myocardium and cause myocarditis because of the myocardial infiltration by the interstitial mononuclear inflammatory cells that were found there during the post-mortem biopsy.^45,80 In some instances, acute myocarditis with reduced systolic function is observed post-COVID-19. ^80,84,85 Research on cardiac biomarkers suggested that hospitalized COVID-19 patients had a significant probability of cardiac injury. ^45,80,86,87 Myocardial injury is probably accompanied by myocarditis and/or ischemia and is a vital predictive aspect of COVID-19.⁸⁰ A single-centre observational study by Shi et al.,⁸⁷ revealed the significance of cardiac injury in 416 admitted COVID-19 patients, of whom 82 (19.7%) died of cardiac injury. Admitted older patients with more underlying comorbidities and high levels of leukocytes are reported to have cardiac injury due to greater hs-cTnI (high sensitive cardiac troponin I).⁸⁷ A retrospective single-centre case series by Guo et al., ⁸⁶ where 187 patients with confirmed COVID-19 were admitted to the hospital; 66 (35.3%) of these patients had preexisting cardiovascular conditions (cardiomyopathy, hypertension, and coronary heart disease), and 52 (27.8%) had myocardial damage, which suggests elevated cTnT (cardiac troponin T) readings.⁸⁶

Diabetes is one of the vital co-factors of morbidity and fatality throughout the world and is accompanied by various microvascular and macrovascular problems that eventually affect the overall patient’s survival. ⁷⁶ The prevalence of diabetes was found to be 35% (mean age, 79.5 years) in an analysis of a randomly chosen sample of fatal SARS-CoV-2 patients in Italy. ^88,89 A comprehensive retrospective study of 1591 SARS-CoV-2 patients admitted in ICUs in Lombardy, Italy, over the course of four weeks revealed an occurrence of T2DM (Type 2 Diabetes Mellitus) of 17%. ^88,90 In T2DM, apart from the pro-inflammatory storm of cytokines, a disproportion between coagulation and fibrinolysis occurs, with an inflated proportion of clotting factors and relative fibrinolytic system inhibition.⁷⁶ Both T2DM and insulin resistance are accompanied by endothelial malfunction and inflated platelet accumulation and activation, which instigate the progression of a hypercoagulable pro-thrombotic state.^76,91 Older people with COVID-19 are noted to have impaired T-cell and B-cell functions and an inflammatory cytokine storm. Consequently, T2DM by itself or in conjunction with advanced age and other comorbidities may encourage unchecked SARS CoV-2 proliferation, increasing the disease’s lethality.^76,92 Since the elderly population is most impacted by COVID-19 and hypertension is particularly widespread in older people, the prevalence of hypertension in these patients is not wholly uncommon.^77,93 Recent studies indicate that a high death rate was detected in COVID-19 individuals who had underlying comorbidities, most notably diabetes, hypertension, and cardiovascular disorders.^76,77,93,94

COVID-19 and Pathophysiological Aspects of Neurological Complications

Neurological problems are prevalent in COVID-19 patients, especially in hospitalized patients, who exhibit greater rates than in patients with less severe disease. ^95,96 Smell and taste problems, intracranial haemorrhage, ischemic stroke, encephalopathy, encephalomyelitis, and neuromuscular illnesses are among the most frequent neurological consequences.^97,98 A variety of factors, such as SARS-CoV-2 neurotropism, endothelial dysfunction, hypercoagulability, hypoxia, systemic illness, and response, may cause the development of neurological manifestation signs.⁹⁷

Neurological problems can result from the SARS-CoV-2 virus’s ability to enter the central neuronal system and affect both neurons and glial cells. Various patho-mechanisms give rise to neurological diseases. Findings indicate that the initial mechanism by which SARS-CoV-2 enters host cells is the ACE2 (angiotensin-converting enzyme type 2), which is found on the cell periphery of many tissues. ^97,99–104 By adhering to ACE2 in a variety of organs, including as the neurological system, skeletal muscle, and vascular endothelium, SARS-CoV-2 can enter the central neuronal system and impair blood vessels. ^97,103,104 Massive intracerebral haemorrhage can emerge from ruptured blood vessels triggered by disruption to the cerebral endothelium and a rise in cerebral blood pressure. ^97,103 However, concomitant COVID-19 infection, hypercoagulability, and thromboembolic circumstances may result in an ischemic stroke. ^97,105 The brainstem—which comprises the paraventricular nuclei and the nucleus of the solitary tract—is where ACE2 is mostly expressed in the brain and is responsible for cardiac and vascular function. ^97,101,102 Additionally, it has been demonstrated that an infection can spread via synaptic connections from peripheral neuronal to the central neuronal system. ^106,107 The dissemination of SARS-CoV-2 through the olfactory nerve may be an example of how disease proceeds along a neural route because of the peculiar structure of the olfactory nerve including associated olfactory fibres inside the nasal canal. Through the olfactory nerve and bulb routes, coronaviruses can colonize the nasal passages before entering the brain and cerebrospinal fluid, resulting in an inflammatory and demyelinating reaction. ^100,101 Another source of negative consequences is the development of an extremely wide systemic inflammatory response (SIRS), which results in an excess of interleukin (IL-6,12,15) and TNF-α (tumour necrosis factor-alpha). This inflammation triggers glial cell activation and a strong proinflammatory phase in the central nervous system, which in turn causes severe hypoxia, leading to cerebral oedema, cerebral vasodilation, and ischemia.^97,106,107

The most prevalent neurological side effects are problems related to taste and smell. Anosmia and taste abnormalities were identified as preliminary markers of COVID-19 in one study, affecting more than 80% of patients.¹⁰⁸ Smell dysfunction impacted 48% of patients, according to a meta-analysis of 83 research involving over 27,000 participants (95% CI 41.2–54.5).¹⁰⁹ Anosmia is reported by younger patients more frequently than by older ones. Additionally, women experience it more frequently than men do. ¹¹⁰ The majority of patients have either significant improvement or overall regression in 2-3 weeks, indicating a typically good prognosis for smell and taste impairments linked to COVID-19. As a result, the prognosis is probably more favorable than it would be for other aetiologies of smell disorders. However, in 10% to 20% of cases, severe and persistent deficiencies persist.⁹⁸ Fortunately, most COVID-19 patients experience a natural recovery of their taste and smell problems, indicating that no special management is needed. However, smell training approaches could be helpful as a treatment if smell abnormalities last longer than four weeks.^97,111

In most cases, patients in critical condition acquire encephalopathy. Delirium associated with encephalopathy is extremely uncommon and may manifest early or even without symptoms. In a cohort investigation involving 2088 COVID-19 individuals admitted to intensive care units, 55% of patients experienced delirium.¹¹² Shah et al.,¹¹³ found that out of 12,601 hospitalized patients, 1092 (8.7%) had acute encephalopathy.¹¹³ In an alternate study, 509 hospitalized COVID-19 patients were found to have encephalopathy in 31.8% of them.⁹⁵ It usually has a multifaceted etiology. Older male patients who have previous instances such as neurological ailments, cancer, cerebral vasculitis, diabetes, renal diseases, dyslipidemia, cardiovascular disease, hypertension, or smoking are primarily affected. ^95,97 Indications of encephalopathy and encephalitis include neuropsychological issues, agitation, delirium, motor impairments linked to extrapyramidal manifestations, abnormal coordination, seizures, diminished consciousness, and specific neurological impairments.^97,98

In COVID-19, stroke appears to be slightly less prevalent.^114–117 Among hospitalized patients, the proportions of intracranial haemorrhage were 0.2–0.9%, and the rates of ischemic stroke associated with COVID-19 were 0.4–2.7%.^118,119 Additionally, there are reported cases of cerebral venous thrombosis (CVT) in COVID-19 individuals. ^120,121 In a retrospective analysis involving more than 13,000 patients, twelve people with CVT were found within three months, indicating 8.8 cases per 10,000 patients. ¹²² A comprehensive evaluation of 34,331 hospitalized patients infected with SARS-CoV-2 estimated the prevalence of CVT to be 0.08% (95% CI 0.01–0.5).¹²³ The majority of the time, a stroke occurs one to three weeks after COVID-19 symptoms initially manifest.^{122,124–126}

In both the moderate and severe COVID-19 variations, myalgia is frequently experienced.⁹⁷ It has been reported in 22–63% of patients,⁹⁸ and in more extreme instances (19 vs. 5%), it is accompanied by elevated creatinine kinase (CK) levels; myopathy, or muscle injury, is also suspected.¹¹⁰ A rare and infrequent repercussion of COVID-19 is severe rhabdomyolysis.¹²⁷ In 0.2% of patients, it was noticed, and in 13.7% of cases, elevated CK levels were found. Within five to seven days of the SARS-CoV-2 infection-induced fever, three Italian patients experienced prevalent myasthenia including positive acetylcholine receptor antibodies.¹²⁸ While it is hypothesized that myasthenia may be caused by the immune system’s reaction to SARS-CoV-2, another possibility is that the infection just catalysis the onset of symptoms in individuals who already have myasthenia. Amyotrophic lateral sclerosis (ALS) cases have also been shown to involve an exacerbation of a pre-existing neuromuscular condition. It indicates that people with neuromuscular disorders do not have a significantly higher risk of contracting SARS-CoV-2 disease.⁹⁸ Peripheral nerve abnormalities, inflammatory/autoimmune muscle disorders, and neuromuscular junction issues should all be managed according to the current guidelines. Immunoglobulin therapy and plasmapheresis are advised. It is recommended to postpone the use of rituximab or long-term oral immunosuppressive medicine in accordance with the patient’s clinical status and medical background. ^97,98

About 0.4% of COVID-19 patients experience Guillain-Barré syndrome (GBS), which usually appears five to ten days after the viral infection.¹²⁹ It implies that GBS is a parainfectious condition based on the appearance of the initial COVID-19 manifestations.¹³⁰ It has been observed in specific studies that the symptoms are more intense and might manifest prematurely than those reported in conventional GBS. ¹³¹ In one study, mechanical ventilation was necessary for three out of five patients.¹³¹ In a span of one month, three hospitals in Italy’s northern region admitted almost 1200 individuals with COVID-19, but only five cases of GBS were found.¹²⁹ Within one to four days, the majority of COVID-19 and GBS patients manifest progressive limb weakness.¹³² For GBS management in COVID-19, lacks particular recommendations. Patients should receive the same treatment as other individuals with GBS.⁹⁷

Therapeutic Options for the Treatment of COVID-19

Since the pandemic outbreak, COVID-19 treatment has shifted rapidly, and it currently consists mainly of antiviral and immunomodulatory medications. Remdesivir and nirmatrelvir-ritonavir are two varieties of antivirals that have been reported to be most effective when used early in an illness (like outpatient treatment) and in cases of less acute illness. Janus kinase inhibitors Interleukin-6, and Dexamethasone, are examples of immunomodulatory therapies that work best when used in cases of extreme illness or critical condition. Due to the appearance of viral variations that are not expected to respond to these treatments, the significance of anti-SARS-CoV-2 monoclonal antibodies has decreased, and opinions regarding the use of convalescent plasma are still divided. The following sections cover the wide spectrum of available treatments, categorized by the classification of agent: antiviral medications, immunomodulators, neutralizing antibodies and convalescent plasma, and antithrombotic treatment. Patients undergoing various treatments have been explored with varying degrees of disease severity: mild to adequate COVID-19 in non-hospitalized patients; serious COVID-19 in hospitalized patients who need additional oxygen; and severe conditions in patients who need non-invasive or mechanical ventilation.¹⁹ The discussion mostly centres on randomized trials, which have contributed significantly to the current treatment paradigms. Every therapeutic section ends with a reference to the National Institutes of Health (NIH) COVID-19 Treatment Guidelines, which offer insight into the recommended usage of each therapy (Table 3).^19,133

Primary Antiviral Agents utilized in the Management of COVID-19

Individuals with mild COVID-19 disease typically exhibit indications including myalgia, a high temperature, cough, and sore throat; on the other hand, patients with moderate disease show signs of lower respiratory tract involvement on radiographic or clinical examinations while still maintaining an oxygen saturation level of at least 94%. ^134,135 The majority of these individuals can be safely treated in outpatient settings, such as emergency rooms, clinics, and telemedicine consultations.^136,137 One of the first medications to show efficacy in a randomized controlled trial (RCT) during the early phases of the global outbreak was Remdesivir, a drug that inhibits viral RNA-dependent RNA polymerase. ¹⁹ The effectiveness of two oral anti-SARS-CoV-2 antiviral medications, molnupiravir and nirmatrelvir-ritonavir, provided to outpatients was assessed in two seminal phase 3 randomised trials, the EPIC-HR and MOVe-OUT trials. Molnupiravir and nirmatrelvir-ritonavir decreased hospitalization or mortality by 30 and 89%, respectively, when administered to unvaccinated people with COVID-19 disease (mild to adequate) within five days of apparition of symptoms and who were at risk of disease development.^138,139 Hospitalization for symptomatic COVID-19 disease or non-COVID-related reasons may also be necessary for patients with mild-to- adequate illness. Compared to patients treated as outpatients, these patients had a higher chance of developing a severe clinical manifestation and a faster rate of disease development. ¹³⁵ The clinical efficacy of molnupiravir and nirmatrelvir-ritonavir in patients hospitalized having mild-to-moderate COVID-19 disease was evaluate in three real-world studies conducted in Hong Kong and Japan. The majority of the patients involved in the research were older than sixty years, and their recommended immunization rates ranged from 10 to 80%.^140–142 In comparison to controls that were matched, molnupiravir and nirmatrelvir-ritonavir were consistently linked to a 40–55% decreased risk of clinical deterioration. Additionally, it was found that nirmatrelvir-ritonavir and molnupiravir were linked to 66–90% and 52–69% decreased risk of death, respectively.^140–142 An overview of the primary antiviral medications used to treat COVID-19 is discussed in (Table 3).

Primary Immunomodulatory Agents utilized in the Management of COVID-19

Severe and serious COVID-19 disease is treated with immunomodulatory substances, which include Janus kinase inhibitors (like baricitinib), interleukin-6 inhibitors (like tocilizumab), and corticosteroids.^135,143 Corticosteroids were the first medications to improve survival in the treatment of COVID-19.¹⁴⁴ It is advised to add interleukin-6 or Janus kinase inhibitors to corticosteroids in individuals whose condition progresses quickly and they show signs of systemic inflammation, such as increasing C-reaction protein. In summary, current research supports the application of remdesivir for the whole range of pulmonary assistance in hospitalized patients with serious and potentially fatal illnesses. Patients using low-flow supplemental oxygen should have their use of oral antivirals carefully assessed. In their clinical care, corticosteroids and other immunomodulatory therapies are indispensable.¹³⁵ The primary immunomodulatory medications used to treat COVID-19 are summarized in (Table 3).

Neutralizing Antibodies and Convalescent Plasma Therapy

During the early stages of the global outbreak, antibody therapy proved to be a powerful treatment and prevention strategy for COVID-19. Convalescent plasma (CP) from recovered COVID-19 sufferers and monoclonal antibodies (mAbs) that aimed the S1 region of the SARS-CoV-2 spike protein were the two types of antibody products used. Pre-exposure prophylactic for immunocompromised individuals with the anti-SARS-CoV-2 monoclonal antibodies tixagevimab and cilgavimab (Evusheld^TM) was authorized by the FDA. Many anti-SARS-CoV-2 treatments with monoclonal antibodies were approved, encompassing bamlanivimab plus etesevimab, bebtelovimab, sotrovimab, and casirivimab plus imdevimab. As the prevalence of various variants of concern (VOCs) increased, the pseudo-viral and in vitro viral neutralization activities of the monoclonal antibodies were utilized to forecast medical efficacy. In 2020, VOCs dominated the strains; however, numerous mAbs continued to have a neutralizing effect against B.1.1.7 (Alpha).¹⁹ But only bebtelovimab and sotrovimab retained relevance after Omicron (B.1.1.529) was fixed at the end of 2021, and not any of the approved mAbs sustained cross-neutralizing activity after Omicron subvariants continued to evolve in 2022.¹⁴⁵ Consequently, the anti-SARS-CoV-2 monoclonal antibodies (mAbs) are not anymore used for pre-exposure prophylaxis, prophylaxis, or for the COVID-19 treatment.^19,133

Antithrombotic Therapy

In the initial pandemic phase, hospitalized COVID-19 suffers experienced a higher prevalence of venous thromboembolism (VTE) episodes, which were most likely attributed to thromboinflammation. ¹⁴⁶ It is difficult to establish the precise rate when compared to historical controls, although it has been estimated to be as high as three times the adult hospitalization baseline rate.¹⁴⁷ The effectiveness of empiric anticoagulation and VTE prophylaxis has been assessed in numerous trials in addressing the elevated load of VTE (venous thromboembolism). The OVID and ETHIC randomized controlled trials (RCTs) examined individuals who were not hospitalized and contrasted enoxaparin or the conventional treatment. None of the two trials demonstrated effectiveness in lowering hospitalization or mortality, and both terminated prematurely.^148,149 Unless there is a contraindication, prophylactic-dose heparin is advised for anticoagulation in hospitalized patients. Relying on the outcomes of randomized controlled trials assessing the application of anticoagulant therapy in non-critically condition and severely diseased hospitalized patients, the NIH (National Institutes of Health) COVID-19 Treatment Guidelines suggested therapeutic-dose heparin for adults who need traditional oxygen but not critical care, but only in cases where the D-dimer concentration is raised and there aren’t any circumstances which boost the likelihood of blood loss.. Moreover, prophylactic-dose heparin should be administered to individuals needing intensive care or high-flow oxygen rather than therapeutic-dose heparin (except when there are restrictions, such as confirmed thromboembolic disease).^{19,133,150,151}

Table 3: An Overview of the Primary Antiviral Medications and Immunomodulatory Therapy Used to Treat COVID-19.

Vaccines Available for the Prevention of COVID-19

The development of treatment options and preventative vaccinations against SARS-CoV-2 has garnered international attention since the pandemic’s onset and the disease’s effects. Prophylactic vaccinations were intended to produce protective immunity in opposition to SARS-CoV-2, whereas the treatment goals were whereas the treatment goals were centred around measures that might reduce hospitalization time and improve the survival rate of infected patients. The development of effective preventive vaccinations in opposition to SARS-CoV-2 was crucial because of the urgent global outbreak situation and its related repercussions, including limited hospital capacity and ventilators.^166–168 The process of developing vaccines is lengthy and intricate, and it might take years or even decades to generate a vaccine that proves effective. On the other hand, the COVID-19 vaccine development effort took a year and was an international triumph. ^169,170 Developing a COVID-19 vaccine within the allotted 12-to 24-month timeframe posed an immense challenge for the researchers.^170,171 A number of factors contributed to the immediate development of the COVID-19 vaccine, including the timely release of the viral genome sequence, technological advancements and innovation, active participation from the international scientific community, a strong regulatory framework, sufficient government funding, and high market demand. Researchers from all around the world reported outstanding progress in the development of vaccines by the beginning of December 2020. On December 2, 2020, a vaccine developed by Pfizer in partnership with BioNTech, a German biotech company became the first completely tested vaccine to be authorized for use in an emergency. ¹⁷⁰ Global vaccination campaigns have primarily employed five types of COVID-19 vaccines: protein subunit, replicating and non-replicating viral vector, nucleic acid (DNA and RNA), inactivated complete virus, and virus-like particles (VLPs) vaccines. In (Table 4), the most recent COVID-19 vaccines updates are presented with adverse effects as well as their efficacy and coverage versus various SARS-Cov-2 variants.^166,167,170

Table 4: The Comprehensive List of Vaccines for COVID-19 are presented with their Adverse Effects, Effectiveness, and Efficacy against several SARS-Cov-2 variants. Click here to view Figure

Conclusion

Five years have passed since Wuhan, China, reported the initial COVID-19 occurrences. Worldwide, more than 775 million people have been infected with SARS-CoV-2, while more than 7 million of those cases have led to COVID-19 infection-related deaths. Every aspect of the socioeconomic framework has been significantly impacted by the COVID-19 outbreak, but it has especially highlighted inadequacies in the healthcare system. It demonstrated the futile struggle the world was in against the biggest threat of the twenty-first century. Infection with COVID-19 has been associated with complications in several organs, including cardiovascular, respiratory, the renal system, and gastrointestinal tract, haematological, cognitive, and dermatological issues. The comorbidities have a strong relationship with the mortality rate of COVID-19 patients. Acute instances and higher death rates are linked to COVID-19 individuals, and they are more common in people over 70 who also have underlying comorbidities. Individuals with cardiovascular illnesses had a threefold greater risk of developing an acute illness or requiring an intensive care unit (ICU) admission, compared to patients with hypertension or diabetes mellitus. Additionally, SARS-CoV-2 is recognized to have exceptional neurotropic potential. Numerous neurotoxins that cause neurological symptoms are released during the cytokine storm, which affects both the lungs and the central nervous system. In an effort to control COVID-19-related death rates and pathologies during these difficult years, a number of treatment alternatives and preventative measures, such as the COVID-19 vaccine, were considered. Since the pandemic began, there has been a tremendous evolution in the field of scientific study on COVID-19 disease treatment. Even those who have received the SARS-CoV-2 vaccination are susceptible of contracting a mild-to-moderate illness; nevertheless, effective antiviral therapy is currently available for early administration. The frequent emergence of variations resistant to existing products limits the usage of monoclonal antibodies. The management of severe and critical diseases requires the combination of immunomodulatory therapy and antiviral therapy. It is anticipated that future developments may benefit difficult-to-treat populations that are immunocompromised or have coexisting comorbidity conditions that limit the use of currently available choices. These patients may need individualized care in terms of the selection, combination, and duration of antiviral medications.

Acknowledgement

I gratefully acknowledge Servier Medical Art (https://smart.servier.com/) for providing free access to their high-quality professional images [licensed under CC BY 4.0 (https://creativecommons.org/ licenses/by/ 4.0/)], which greatly contributed to the visual clarity and quality of this publication. Servier Medical Art’s generous support is instrumental in enhancing the advancement of scientific communication. 

Funding Sources

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Conflict of Interest

The authors do not have any conflict of interest.

Data Availability Statement

This statement does not apply to this article.

Ethics Statement

This research did not involve human participants, animal subjects, or any material that requires ethical approval.

Informed Consent Statement

This study did not involve human participants, and therefore, informed consent was not required.

Clinical Trial Registration

This research does not involve any clinical trials.

Permission to reproduce material from other sources

Not Applicable

Author Contributions

The sole author was responsible for the conceptualization, methodology, data collection, analysis, writing, and final approval of the manuscript.

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