The co-infection of DENV-1 and DENV-3 during endemic outbreaks can be potentially fatal and complicate the diagnostic process. In our study, we have focused on the development of a multiepitope vaccine against DENV-1 and DENV-3 co-infection, utilizing non-structural protein 1 (NS1) and envelope protein (E) as key antigens. B cell and T cell epitopes were predicted for their immunogenicity, antigenicity, and ability to elicit an IFN-γ response. The final construct showed predicted stability (Instability Index: 30.63), antigenicity (0.5509), non-allergenicity, and hydrophilic character (GRAVY: −0.226) based on computational assessments. Tertiary structural validation revealed 90.1% of residues in a favoured region. Molecular docking revealed a stronger binding of the DENV-TLR3 complex. The receptor and vaccine have stable interactions, according to molecular dynamics simulations and free energy estimations (-90 kJ/mol). Strong B and T cell memory responses were demonstrated by immune simulations, accompanied by increased levels of IgG, IFN-γ, and TGF-β. The codon-optimized sequence was successfully cloned into the pcDNA™3.1/V5-His-TOPO® expression vector for potential experimental validation. As a result of this in silico approach, a targeted vaccine for DENV-1 and DENV-3 co-infections is possible, which merits further experimental evaluation.

The presence of several mobile genetic elements (MGEs) endows Escherichia coli with a highly plastic genome. Since antibiotic resistance genes (ARGs) and virulence genes are abundantly present on the MGEs (mobilome), a comprehensive study of the mobilome is necessary to understand its full potential in the dissemination of ARGs and virulence genes to other pathogens. Here, we have analysed the mobilome, resistome (ARGs) and virulome (virulence genes) of multidrug-resistant (MDR) and drug-susceptible, genetically similar E. coli strains isolated from a prominent urban river. Our results revealed that despite a similar chromosomal backbone, both strains possessed a diverse mobilome – genomic islands (GIs), prophages, plasmids, insertion sequences (ISs) and CRISPR-Cas elements. Most of the ARGs of drug-susceptible and MDR E. coli were present on the chromosome. Among the MGEs, many ARGs of MDR E. coli were present on the plasmids and GIs, but in drug-susceptible E. coli, ARGs were present only on the GIs. None of the virulence genes of drug-susceptible E. coli were present on any MGE, but only on the chromosome. However, in the MDR strain, besides the chromosome, many virulence genes were present on the GIs. The presence of such genes on MGEs reflects a public health emergency, as these genes can be easily disseminated to other microbes of the urban rivers by horizontal gene transfer and reach the human and animal gut through the domestic water supply system.

Dengue viruses (DENVs) usually cause a mild febrile illness which might flare up in some patients as dengue haemorrhagic fever (DHF) or dengue shock syndrome. Altered expression of autoimmune markers and development of autoimmune diseases was observed in patients exhibiting prolonged dengue symptoms, suggesting a possible correlation between DENVs and autoimmune diseases. Molecular mimicry of the blood coagulation pathway proteins by DENVs might be a potential factor underlying clinical manifestations of DHF. Inhibition of protein-protein interactions (PPIs) in DENV mimicry proteins and human proteins can potentially treat both DHF and, associated autoimmune diseases. In this study, we have performed a systematic in silico analysis of human proteins interacting with DENV mimicry proteins (HPIDMP) as novel drug targets. Potential inhibitors of the HPIDMP were discerned from the DrugBank database following stringent parameters. The protein–ligand interactions were predicted using molecular docking and evaluated with decoy-based validation, molecular dynamics simulations, and MM-PBSA binding free energy calculations. RAF1 targeting drugs Sorafenib and Regorafenib exhibited the most consistent interaction profile across all computational analyses, followed by the SIRT1-targeting compounds selisistat and resveratrol, which demonstrated moderate but consistent computational support. In contrast, the MYH9–artenimol and HSPE1–phenethyl isothiocyanate systems showed comparatively weaker support. On the basis of our results, we propose Sorafenib and Regorafenib as the most promising candidates for in vitro or clinical studies for treatment of DHF and/or DENV-associated autoimmune diseases, followed by Selisistat and Resveratrol. Thus these DrugBank molecules can be incorporated in clinical studies or in vitro testing for treatment of DHF and/or DENV-associated autoimmune diseases. Also, the methods adopted in this study can guide the repurposing of known drugs to treat other pathogen-associated autoimmune diseases.

Antimicrobial resistance (AMR) is a global public health threat that has severely jeopardised years of progress in controlling infectious diseases. The last few years have witnessed a dramatic expansion in the high-throughput "-omics" technologies, such as genomics, transcriptomics, proteomics, metabolomics, etc. The multi-omics approaches have established that AMR develops due to complex interactions among various biomolecules, including genetic variations, regulatory networks, differential protein expressions, metabolic adaptations, and environmental pressure. But the scale, heterogeneity and high dimensionality of data generated via multi-omics analyses far exceed the capacity of traditional statistical and rule-based analytical methods. Thus, Artificial Intelligence (AI) is needed for extracting meaningful patterns from the complex high-dimensional biological data generated during multi-omics analyses. Artificial intelligence (AI), encompassing machine learning and deep learning techniques, is a robust way to combine different types of -omics data, model non-linear dependencies, and get predictive and mechanistic insights into AMR. This chapter provides a comprehensive and critical overview of the role of AI in multi-omics analysis of AMR, conceptual foundations, methodological advances, representative applications and translational implications. Additionally, significant applications of AI-driven multi-omics AMR research are discussed. Finally, limitations of this strategy and future directions are examined. To fully realise the potential of AI-driven multi-omics strategies for combating AMR, it will be necessary to address their limitations through standardised data generation, robust validation, and interdisciplinary collaboration.

The Biogeochemical cycles are crucial for aquatic ecosystems, particularly the functioning of nutrient cycles. Growing anthropogenic pressure alters their functioning, causing accelerated eutrophication. Understanding the scale of alteration in ecological functions could assist with combat strategies. Bacterial communities regulate the transition of functional traits in aquatic ecosystems. However, current knowledge is still elusive regarding the variability of the environmental drivers dictating the functional roles in dynamic regimes like littoral zones. This study assessed how seasonal and circumlimnal conditions influenced sediment characteristics, bacterioplankton communities, and putative ecological functions (specifically biogeochemical cycling of carbon, nitrogen, and sulphur) in the hypertrophic freshwater Lake Pichola (Rajasthan, India). Findings suggest a significant seasonal drivers’ influence on sediment characteristics, while the anthropopressure-aided niche partitioning promoted species richness and diversity in the hypertrophic lake. Proteobacteria, Bacteroidota, and Firmicutes were abundant phyla; chemoheterotrophy and fermentation are the dominant potential putative functions; methylotrophy, nitrate reduction, and sulfate reduction are prominent nutrient cycling biogeochemical functions. Redundancy analysis accurately explained the influence of sediment characteristics on the variability of biogeochemical functions. Shifts in bacterioplankton communities were evident within circumlimnal regimes with greater anthropogenic stress, promoting higher abundance and diversity of putative bacteria orchestrating the ecological functions. This study emphasizes the importance of considering the interplay among the functional traits and environmental factors dynamics in littoral sediments for studying biogeochemical transformation in lakes.

Metagenomics has revealed an unprecedented viral diversity in human gut although, most of the sequence data remains uncharacterized. In this study, we mined a collection of 1090 metagenome assembled "high quality" viral genomes (> 90% completeness, as determined by CheckV) derived from human fecal samples. Sequence analysis revealed eight new species spanning seven genera within the class, Caudoviricetes and nineteen new species from fourteen genera within the ssDNA virus family, Microviridae. Additionally, four "high quality" genomes were not found in any of the four major viral databases, NCBI viral RefSeq, IMG-VR, Gut Phage Database (GPD) and Gut Virome Database (GVD). Further, annotation and KEGG pathway analysis of the "high-quality" genomes identified seven core genes (antB, dnaB, DNMT1, DUT, xlyAB, xtmB and xtmA) associated with metabolism and fundamental viral processes. Moreover, genes for virulence, host-takeover, drug resistance, tRNA, tmRNA and CRISPR elements were also detected. Host prediction analysis suggest bacterial hosts for approximately 40% of the genomes. Overall, this study reports the discovery of novel viral genomes and provides a comprehensive genome profiling of human gut viruses in a subpopulation from India. These findings serve as a foundation for future biological investigations to elucidate the role of these viruses in host physiology.

Infections due to multidrug-resistant (MDR) Escherichia coli are associated with severe morbidity and mortality, worldwide. Microbial drug resistance is a complex phenomenon which is conditioned by an interplay of several genomic, transcriptomic and proteomic factors. Here, we have conducted an integrated transcriptomics and proteomics analysis of MDR E. coli to identify genes which are differentially expressed at both mRNA and protein levels. Using RNA-Seq and SWATH-LC MS/MS it was discerned that 763 genes/proteins exhibited differential expression. Of these, 52 genes showed concordance in differential expression at both mRNA and protein levels with 41 genes exhibiting overexpression and 11 genes exhibiting under expression. Bioinformatic analysis using GO-terms, COG and KEGG functional annotations revealed that the concordantly overexpressed genes of MDR E. coli were involved primarily in biosynthesis of secondary metabolites, aminoacyl-tRNAs and ribosomes. Protein-protein interaction (PPI) network analysis of the concordantly overexpressed genes revealed 81 PPI networks and 10 hub proteins. The hub proteins (rpsI, aspS, valS, lysS, accC, topA, rpmG, rpsR, lysU, and spmB) were found to be involved in aminoacylation of tRNA and lysyl-tRNA and, translation. Further, it was discerned that three hub proteins - smpB, rpsR, and topA were non homologous to human proteins and were involved in several biological pathways directly and/or indirectly related to antibiotic stress. Also, absence of homology ensures a little cross-reactivity of their inhibitors/drugs with human proteins and undesirable side effects. Thus, these proteins might be explored as novel drug targets against both drug-resistant and -sensitive populations of E. coli.

In search for better synthetic antioxidants, aminic organoselenides carrying amine and benzamide groups at ortho-positions to the selenium atom were synthesized from alkyl halides and in situ generated sodiumselenolates as nucleophile by the sodium borohydride reduction of corresponding diselenides. The single crystal X-ray structure of one compound showed the weak intramolecular Se & sdot;& sdot;& sdot;H interactions with free amine group. The presence of Se & sdot;& sdot;& sdot;H interactions was further confirmed using natural bond orbital (NBO) and atoms in molecules (AIM) calculations, respectively. The glutathione peroxidase enzyme (GPx)-like antioxidant activity of all compounds was evaluated using thiophenol assay. The best antioxidant exhibited nearly 5 and 10 times greater activities than Oct2Se2 and Ph2Se2 used as references, respectively. The most active catalysts carrying a strong electron-donating group were further investigated at different concentrations of thiol for determining the catalytic parameters. These GPx mimics have shown anti-ferroptotic activity in a 4-OH-tamoxifen (TAM) inducible GPx4 knockout cell line and protected cells from cell death induced by loss of GPx4 enzyme. In silico molecular docking studies showed that all antioxidants demonstrated promising Moldock scores with human 15-lipoxygenase-2 enzyme.

In COVID-19 patients, respiratory failure was reported due to damage to the respiratory centers of the brainstem. Molecular mimicry of three brainstem pre-Botzinger complex proteins (DAB1, AIFM and SURF1) was regarded as the underlying reason for respiratory failure and the autoimmune neurological sequelae. Of the three brainstem proteins mimicked by SARS CoV-2, corresponding sequences to two of the mimicry peptides were located in the N-protein of SARS CoV-2. N-protein is important for viral RNA synthesis and genome packaging. Here, we have used molecular modeling, docking and MD simulations to discern potential drugs which can inhibit molecular mimicry of DAB1 by SARS CoV-2 and also eliminate it by interfering in genome packaging. The binding site (drug target) for molecular docking was defined as the amino acid sequence extending from position 168–185 of the N-protein which was a SLiM region and also included the mimicry hexapeptide. Molecular docking after MD simulations was used to discern probable inhibitors of the drug-target from FDA-approved neurological drugs in the Broad Institute’s Drug Repurposing Hub. Our results revealed that an anti-anxiety drug afobazole qualified the ADMET parameters, formed a stable complex with the drug-target and exhibited the highest binding energy (-88.21 kJ/mol). This suggests that afobazole can be repurposed against SARS CoV-2 for disrupting molecular mimicry of human DAB1 protein and also eliminate the etiopathological agent by interfering in viral genome packaging.

Motivation:Prediction of antimicrobial resistance in Pseudomonas aeruginosa using machine learning and genomic sequences holds the potential to serve as comparable alternatives to laboratory based detection if not better. Additionally, model interpretability can further enhance the potential of these models paving way for their reproducibility. Results:We have developed a machine-learning based 2-tier pipeline to predict resistance phenotype in P. aeruginosa using only genomic sequences as input in the form of k-mers. Our Decision Tree Model yields an accuracy of 79% and area under the receiver operating characteristic curve of 0.77 with a 70% specificity and 84% sensitivity. We have interpreted the model's predictions using explainable AI as an attempt to bridge the gap between computational prediction and biological insight. Through these interpretations we have gathered antibiotic specific k-mer signatures pushing phenotype towards resistance. Availability and implementation:The curated dataset and related codes are available on request.

Metagenomics has revealed an unprecedented viral diversity in human gut although, most of the sequence data remains to be characterized. In this study, we mined a collection of 1090 metagenome assembled “high quality” genomes of human gut viruses. Sequence analysis has revealed eight new species from seven genera of the class, Caudoviricetes and nineteen new species from fourteen genera of the ssDNA virus family, Microviridae. In addition, four “high quality” genomes were identified, which do not show similarity to sequences present in any of the four major viral databases, NCBI viral RefSeq, IMG-VR, Gut Phage Database (GPD) and Gut Virome Database (GVD). Further, annotation of the “high-quality” genomes and KEGG pathway analysis has identified antB , dnaB , DNMT1 , DUT , xlyAB , xtmB and xtmA as the most widespread viral and Auxiliary Metabolic Genes (AMGs). Genes for virulence, host-takeover, drug resistance, tRNA, tmRNA and CRISPR elements were also found. Bacterial hosts are predicted for around 40% of the analyzed genomes. Overall, we report identification of new viral genomes and genome analyses of human gut viruses, which will be useful for biological characterization to establish their significance in physiology.IMPORTANCE Multiple studies have found that dysbiosis of gut virome is associated with conditions such as metabolic syndromes, autoimmune disorders and infectious diseases. In the interest of its therapeutic and diagnostic potential, intestinal virome warrants detailed investigation. However, limited ability to culture gut viruses becomes one of the challenges for their biological characterization and fully understanding their role in physiology. Sequence analysis and host prediction methods provide opportunities to understand gut viruses, their functional potential and devise ways for further characterization.

The enzymes of the mevalonate pathway need to be improved to achieve high yields of isoprenoids in the yeast Saccharomyces cerevisiae. The red yeast Rhodosporidium toruloides produces high levels of carotenoids and may have evolved to carry a naturally high flux of isoprenoids. Enzymes from such yeasts are likely to be promising candidates for improvement. Towards this end, we have systematically investigated the various enzymes of the mevalonate pathway of R. toruloides and custom synthesized, expressed, and evaluated six key enzymes in S. cerevisiae. The two nodal enzymes geranyl pyrophosphate synthase (RtGGPPS) and truncated HMG-CoA reductase (RttHMG) of R. toruloides showed a significant advantage to the cells for isoprenoid production as seen by a visual carotenoid screen. These two were analyzed further, and attempts were also made at further improvement. RtGGPPS was confirmed to be superior to the S. cerevisiae enzyme, as seen from in vitro activity determinations and in vivo production of the heterologous diterpenoid sclareol. Four mutants were created through rational mutagenesis but were unable to improve the activity further. In the case of RttHMG, functional evaluation of the enzyme revealed that it was very unstable despite functioning very well in S. cerevisiae. We succeeded in stabilizing the enzyme through mutation of a conserved serine in the catalytic region, which did not alter the enzyme activity per se. In vivo evaluation of the mutant revealed that it could enable better sclareol yields. Therefore, these two enzymes from the red yeast are excellent candidates for heterologous isoprenoid production.

Chandipura virus (CHPV) is an emerging pathogen of Indian subcontinent. It is a vector borne virus and belongs to Rhabdovirus family. In recent past several outbreaks reported from the states of “Maharastha”, “Gujrat”, “Andra Pradesh” causing more than 300 deaths of children below 15 years and case-fatality rate was more than 50 https://doi.org/10.1101/2022.03.02.482698 ). We summarize that abacavir, tenofovir, AZT and nevirapine are effective inhibitors of CHPV and a combination therapy may be designed to treat the disease.

The synthesis of diarylamine-based organoselenium compounds via the nucleophilic substitution reactions has been described. Symmetrical monoselenides and diselenides were conveniently synthesized by the reduction of their corresponding selenocyanates using sodium borohydride. Selenocyanates were obtained from 2-chloro acetamides by the nucleophilic displacement with potassium selenocyanate. Selenides were synthesized by treating the 2-chloro acetamides with in situ generated sodium butyl selenolate as nucleophile. Further, the newly synthesized organoselenium compounds were evaluated for their glutathione peroxidase (GPx)-like activity in thiophenol assay. This study revealed that the methoxy-substituted organoselenium compounds showed significant effect on the GPx-like activity. The catalytic parameters for the most efficient catalysts were also determined. The anti-ferroptotic activity for all GPx-mimics evaluated in a 4-OH-tamoxifen (TAM) inducible GPx4 knockout cell line using liproxstatin as standard. Aminic organoselenium compounds such as symmetrical selenides and diselenides are conveniently obtained by the reduction of their corresponding selenocyanates using sodium borohydride. These compounds show very good glutathione peroxidase (GPx)-like antioxidant activity. They also exhibit anti-ferroptotic activity in a TAM-inducible GPx4 conditional knockout cell lines and prevent the accumulation of phospholipid hydroperoxide (LOOH) in biological membranes. image

Alternaria leaf blight (ALB), caused by a necrotrophic fungus Alternaria brassicae is a serious disease of oleiferous Brassicas resulting in significant yield losses worldwide. No robust resistance against A. brassicae has been identified in the Brassicas. Natural accessions of Arabidopsis show a spectrum of responses to A. brassicae ranging from high susceptibility to complete resistance. To understand the molecular mechanisms of resistance/ susceptibility, we analysed the comparative changes in the transcriptome profile of Arabidopsis accessions with contrasting responses- at different time points post-infection. Differential gene expression, GO enrichment, pathway enrichment, and weighted gene co-expression network analysis (WGCNA) revealed reprogramming of phenylpropanoid biosynthetic pathway involving lignin, hydroxycinnamic acids, scopoletin, anthocyanin genes to be highly associated with resistance against A. brassicae. T-DNA insertion mutants deficient in the biosynthesis of coumarin scopoletin exhibited enhanced susceptibility to A. brassicae. The supplementation of scopoletin to medium or exogenous application resulted in a significant reduction in the A. brassicae growth. Our study provides new insights into the transcriptome dynamics in A. brassicae-challenged Arabidopsis and demonstrates the involvement of coumarins in plant immunity against the Brassica pathogen A. brassicae.

Data Record for Genome annotation and ontology of phylogroup D E. coli drug resistant isolates from anthroprogenic river Yamuna, India.