A metagenome-wide association study of gut microbiome in patients with AMD, ASD, RA, T2D & VKH diseases.

Clinical studies have already illustrated the associations between gut microbes and diseases, yet fundamental questions remain unclear that how we can universalize this knowledge. Considering the important role of human gut microbial composition in maintaining overall health, it is important to understand the microbial diversity and altered disease conditions of the human gut. Metagenomics provides a way to analyze and understand the microbes and their role in a community manner. It provides qualitative as well as quantitative measurements, in terms of relative abundance. Various studies are already going on to find out the association between microbes and diseases; still, the mined knowledge is limited. Considering the current scenario, using the targeted metagenomics approach, we analyzed the gut microbiome of 99 samples from healthy and diseased individuals. Our metagenomic analysis mainly targeted five diseased microbiomes (i.e., Age-related macular degeneration, Autism spectrum disorder, Rheumatoid arthritis, Type 2 diabetes and Vogt-Koyanagi harada), with compare to healthy microbiome, and reported disease-associated microbiome shift in different conditions.

In-silico mining to glean SNPs of pharmaco-clinical importance: an investigation with reference to the Indian populated SNPs.

Drugs pharmacology is defined by pharmacokinetics and pharmacodynamics and both of them are affected by genetic variability. Genetic variability varies from population to population, and sometimes even within the population, it exists. Single nucleotide polymorphisms (SNPs) are one of the major genetic variability factors which are found to be associated with the pharmacokinetics and pharmacodynamics process of a drug and are responsible for variable drug response and clinical phenotypes. Studies of SNPs can help to perform genome-wide association studies for their association with pharmacological and clinical events, at the same time; their information can direct genome-wide association studies for their use as biomarkers. With the aim to mine and characterize Indian populated SNPs of pharmacological and clinical importance. Two hundred six candidate SNPs belonging to 43 genes were retrieved from Indian Genome Variation Database. The distribution pattern of considered SNPs was observed against all five world super-populations (AFR, AMR, EAS, EUR, and SAS). Further, their annotation was done through SNP-nexus by considering Human genome reference builds - hg38, pharmacological and clinical information was supplemented by PharmGKB and ClinVar database. At last, to find out the association between SNPs linkage disequilibrium was observed in terms of r2. Overall, the study reported 53 pharmaco-clinical active SNPs and found 24 SNP-pairs as potential markers, and recommended their clinical and experimental validation. Supplementary Information: The online version contains supplementary material available at 10.1007/s40203-023-00154-4.

Mining of molecular insights of CYP2A6 and its variants complex with coumarin (CYP2A6*-coumarin) using molecular dynamics simulation.

CYP2A6 is a very important enzyme that plays a crucial role in nicotine compounds and is responsible for the metabolism of more than 3% drugs of total metabolized drugs by the CYP family and reported as one of very important pharmacogenes. CYP2A6 is highly polymorphic in nature and reported with more than 40 variants, most of these variants are SNPs originated and population specific. It has been well observed and reported that the presence of these population-specific non-synonymous SNPs in CYP2A6 alters the rate of drug metabolism and as a functional consequence, drugs produce an abnormal response. Though genomics and pharmacogenomics studies are there, very less is known about the structural effects of these SNPs on molecular-interaction and folding of CYP2A6. To fill the knowledge gap, SNPs based four variants, i.e., CYP2A6*2, CYP2A6*18, CYP2A6*21, and CYP2A6*35, which are frequently reported in the South Asian population, were considered for the study. Coumarin (DB04665), a well reported drug, is considered as a model substance, and the effect of all four variants on 'CYP2A6*-coumarin' complex was studied. MD simulation-based analysis (at 200 ns) was performed and comparative analysis with respect to wild type 'CYP2A6-coumarin' complex was done. Though observation didn't find any global effect on complete complex but found some crucial minor-local alteration in interaction and folding process. It is assumed that the change due to SNPs in the single amino acid did not bring global change in physiochemical properties of CYP2A6* but caused local-trivial changes which are very crucial for its metabolic activity.Communicated by Ramaswamy H. Sarma.

Investigation of molecular interaction and conformational stability of disease concomitant to HLA-DRß3.

Human leucocyte antigen DRß3 is associated with specific autoimmune thyroid disease and plays a vital role in the progression of Grave's disease. The available crystallographic structure of the HLA DRA, DRß3*0101, was selected and used to generate mutation at position 57 from valine amino acid to Aspartic acid (D), Glutamic acid (E), Alanine (A), and Serine (S) amino acids by computational modeling approach. Mutant models were minimized, and stable conformation was chosen based on the lowest root mean square deviation value. Molecular docking assessed the best binding affinity of ligands C1, C2, C3, and C4 with wild-type and mutant HLA-DRß3 models. Molecular dynamics simulation studies were executed to evaluate the stability of selected hits with wild-type and mutant dock complexes. The C3 has shown good binding affinity with wild-type and selected mutants; V57A, V57E, and V57D. Structural and molecular dynamics insights reveal the differences between wild-type and mutant-type HLA-DRß3, which could help design novel antagonist molecules against autoimmune thyroid disorder.Communicated by Ramaswamy H. Sarma.

Identification and annotation of milk associated genes from milk somatic cells using expression and RNA-seq data.

It is of interest to identify and annotate milk associated genes using expression profiling and RNA-Seq data from milk somatic cells. RNA-Seq data was pre-processed and mapping was done to identify differentially expressed genes (DEG). The functional insights about the up and down regulated genes were gleaned using the protein-protein interaction Network in the STRING database followed by CytoHubba analysis in Cytoscope. Gene ontology, annotation and pathway enrichment was completed using ShinyGO, David tool and QTL analysis. These analysis shows that 21 genes are linked with the secretion of milk.

Repurposing of FDA approved drugs and their validation against potential drug targets for Salmonella enterica through molecular dynamics simulation.

Salmonella is a widely distributed pathogen causing infection of intestinal tract, typhoid, and paratyphoid fever. Number of drugs was developed against salmonella, but in the last few decades due to the emergence of drug resistant strains, most of these drugs became dormant. As a result Salmonellosis emerges as a trivial cause of human mortality worldwide; therefore, there is an urgent need for unexploited drug targets and drugs to treat Salmonellosis. As development of new drug molecules is very time consuming and costly, drug repurposing is in consideration as a better alternative. With the aim to identify a new drug molecule against the Salmonella through repurposing approach, we utilized 14 well reported druggable targets known to play a vital role in the life cycle of pathogens. These targets were used to screen DrugBank and got 53 FDA approved drugs against them. To find the interaction between considered target proteins and screened drugs, molecular docking was performed. Fourteen docked drug-target complexes with reasonable binding affinities were subjected to Molecular Dynamics Simulation (MDS) at 150 ns, using Amber18. At the end MMPBSA and MMGBSA calculations were performed for all stable complexes and finally, got 3 precise and favourable complexes, i.e. ArcB-Cefpiramide, MrcB-Cefoperazone, and PhoQ-Carindacillin. Rigorous structural and energetic analysis for these complexes validates the potential of drug molecules to act as therapeutic drugs against Salmonella enterica. With this study we hypothesize that the drugs Cefpiramide (DB00430), Cefoperazone (DB01329) and Carindacillin (DB09319) will be the good repurposed-drugs for the treatment of Salmonellosis. Communicated by Ramaswamy H. Sarma.

Up regulated virulence genes in M. tuberculosis H37Rv gleaned from genome wide expression profiles.

Identification of up regulated virulence genes in M. tuberculosis H37Rv using genome wide expression profiles is of interest in drug discovery for the disease. Hence, we report 17 up-regulated PPIN (Protein-Protein Interaction Network) enriched potential virulence linked genes using expression data available at the Gene Expression Omnibus (GEO) database for further consideration.

An in silico analysis of deleterious single nucleotide polymorphisms and molecular dynamics simulation of disease linked mutations in genes responsible for neurodegenerative disorder.

Mutation in two genes deglycase gene (DJ-1) and retromer complex component gene (VPS35) are linked with neurodegenerative disorder such as Parkinson's disease, Huntington's disease, and Alzheimer's disease. DJ-1 gene located at 1p36 chromosomal position and involved in PD pathogenesis through many pathways including mitochondrial dysfunction and oxidative injury. VPS35 gene located at 16q13-q21 chromosomal position and the two pathways, the Wnt signaling pathway, and retromer-mediated DMT1 missorting are proposed for basis of VPS35 related PD. The study focuses on identifying most deleterious SNPs through computational analysis. Result obtained from various bioinformatics tools shows that D149A is most deleterious in DJ-1 and A54W, R365H, and V717M are most deleterious in VPS35. To understand the functionality of protein comparative modeling of DJ-1 and VPS35 native and mutants was done by MODELLER. The generated structures are validated by two web servers-ProSa and RAMPAGE. Molecular dynamic simulation (MDS) analysis done for the most validated structures to know the functional and structural nature of native and mutants protein of DJ-1 and VPS35. Native structure of DJ-1 and VPS35 show more flexibility through MDS analysis. DJ-1 D149A mutant structures become more compact which shows the structural perturbation and loss of DJ-1 protein function which in turn are probable cause for PD. A54W, R365H, and V717M mutant protein of VPS35 also shows compactness which cause structure perturbation and absence of retromer function which likely to be linked to PD pathogenesis. This in silico study may provide a new insight for fundamental molecular mechanism involved in Parkinson's disease. Communicated by Ramaswamy H. Sarma.

Pharmacogenes (PGx-genes): Current understanding and future directions.

Individual specific variable drug response against similar drugs raises a significant challenge for the effective and safe treatment of many human diseases. Pharmacogenomics is the branch which try to deal with these challenge by relating drug response to patient specific genome in order to better customize patient treatments. Pharmacogenomics based research focus on the whole genome, but since last few years after realizing the importance, it mainly centralized towards genes of pharmacological importance called pharmacogenes, and try to explore association between their variants and variable drug response in world's different population. This research was initiated with the resulted data from human genome based research projects and later on assisted by exome sequencing projects. Simultaneously, it was boost-up with the participation of various pharmacogenomics groups lead by PGRN. By realizing the significance of pharmacogenes, and their variant related information, in health science, scientific communities are already started to look for genes of pharmacogenomics importance with different aspect. This article aims to provide an inclusive insight on current state of knowledge of pharmacogenes, recent trends and progress in the understanding of the pharmacogenes and the implications for personalized medicine.

TPMT Polymorphism: When Shield Becomes Weakness.

Thiopurine methyltransferase (TPMT) is a cytoplasmic transmethylase present in both prokaryotes and eukaryotes. In humans, it shows its presence in almost all of the tissues, predominantly in liver and kidney. TPMT is one of the important metabolic enzymes of phase II metabolic pathway and catalyzes methylation of thiopurine drugs such as azathioprine, 6-thioguanine and 6-mercaptopurine, which are used to treat patients with neoplasia and autoimmune disease as well as transplant recipients. In this sense, TPMT acts as shield against toxic effect of these drugs. Pharmacogenomic studies revealed that genetic polymorphism in TPMT is responsible for variable and, in some cases, adverse drug reaction. Those human groups who carry variants of TPMT (i.e., [Formula: see text], [Formula: see text], [Formula: see text]) are at high risk, because they are unable to metabolize thiopurine drugs thus becoming a weakness of patients against these drugs. Keeping in the mind the importance of TPMT, this review discusses the existence and distribution of various TPMT variants throughout different ethnic groups and risk of adverse drug reactions to them, and how they can avoid this risk of side effects. The review also highlighted factors responsible for variable reactions of TPMT, how this TPMT polymorphism can be considered in drug designing process to avoid toxic effects, designing precautions against them and more importantly designing personalized medicine.

Single nucleotide polymorphism and its dynamics for pharmacogenomics.

Pharmacogenomics is the study of how the genetic makeup determines the response to a therapeutic intervention. It has the capability to revolutionize the practice of medicine by personalized approach for treatment through the use of novel diagnostic tools. Pharmacogenomic based approaches reduce the trial-and-error approach and restrict the exposure of patients to those drugs which are not effective or are toxic for them. Single Nucleotide Polymorphisms (SNPs) hold the key in defining the risk of an individual's susceptibility to various illnesses and response to drugs. There is an ongoing process of identifying the common, biologically relevant SNPs, in particular those that are associated with the risk of disease and adverse drug reaction. The identification and characterization of these SNPs are necessary before their use as genetic tools. Most of the ongoing SNP related studies are biased deliberately towards coding regions and the data generated from them are therefore unlikely to reflect genome wide distribution of SNPs. To avoid this biasing towards the coding regions SNP, SNP consortium protocol was designed. Though, projects like the HapMap increase credibility and use of SNPs, still there are some concern like the required sample (patient) sizes, the number of SNPs required for mapping, number of association studies, the cost of SNP genotyping, and the interpretation and explanation of results are some of the challenges that surround this field.

In silico prediction of drug targets in phytopathogenic Pseudomonas syringae pv. phaseolicola: charting a course for agrigenomics translation research.

Pseudomonas syringae pv. phaseolicola is a major plant pathogen causing halo blight disease and has world-wide importance. The emerging post-genomics field of agrigenomics, together with the availability of whole genome sequences of a number of pathogens and host organisms, offer the promise for identification of potential drug targets using sequence comparison approaches. On the other hand, lack of gene expression data for most of the phytopathogenic microbes still remains a formidable barrier. The present study aimed at the prediction of drug targets in Pseudomonas syringae pv. phaseolicola by exploiting the knowledge of Codon Usage bias for gene expression subtractively, supported by gene expression analysis and sequence comparisons. Based on screening of the Database of Essential Genes using blastx, 158 of the total 5172 genes of P. syringae pv. phaseolicola were enlisted as vitally essential genes. Similarity search for these 158 essential genes against available host-plant sequences (Phaseolous vulgaris) led to the identification of homologues of 21 genes in the host genome, thus leaving behind a subset of 137 genes. Expression analysis of these 137 genes using RSCU(gene,) validated by microarray gene expression data suggested 22 genes had higher expression levels in the cell, and therefore their products have been identified as putative drug targets. The gene ontology analysis of these 22 genes revealed their indispensable roles in pivotal metabolic pathways of P. syringae pv. phaseolicola. Upon comparison of the sequences of these genes with other soil bacteria, we identified two genes that were unique to P. syringae pv. phaseolicola. The products of these genes can potentially be utilized for drug development so as to control the halo blight disease and thereby accelerate translation research in the nascent field of agrigenomics.

Phylogenetic footprinting: a boost for microbial regulatory genomics.

Phylogenetic footprinting is a method for the discovery of regulatory elements in a set of homologous regulatory regions, usually collected from multiple species. It does so by identifying the best conserved motifs in those homologous regions. There are two popular sets of methods-alignment-based and motif-based, which are generally employed for phylogenetic methods. However, serious efforts have lacked to develop a tool exclusively for phylogenetic footprinting, based on either of these methods. Nevertheless, a number of software and tools exist that can be applied for prediction of phylogenetic footprinting with variable degree of success. The output from these tools may get affected by a number of factors associated with current state of knowledge, techniques and other resources available. We here present a critical apprehension of various phylogenetic approaches with reference to prokaryotes outlining the available resources and also discussing various factors affecting footprinting in order to make a clear idea about the proper use of this approach on prokaryotes.

In silico prediction of drug targets in Vibrio cholerae.

Identification of potential drug targets is the first step in the process of modern drug discovery, subjected to their validation and drug development. Whole genome sequences of a number of organisms allow prediction of potential drug targets using sequence comparison approaches. Here, we present a subtractive approach exploiting the knowledge of global gene expression along with sequence comparisons to predict the potential drug targets more efficiently. Based on the knowledge of 155 known virulence and their coexpressed genes mined from microarray database in the public domain, 357 coexpressed probable virulence genes for Vibrio cholerae were predicted. Based on screening of Database of Essential Genes using blastn, a total of 102 genes out of these 357 were enlisted as vitally essential genes, and hence good putative drug targets. As the effective drug target is a protein which is only present in the pathogen, similarity search of these 102 essential genes against human genome sequence led to subtraction of 66 genes, thus leaving behind a subset of 36 genes whose products have been called as potential drug targets. The gene ontology analysis using Blast2GO of these 36 genes revealed their roles in important metabolic pathways of V. cholerae or on the surface of the pathogen. Thus, we propose that the products of these genes be evaluated as target sites of drugs against V. cholerae in future investigations.

Prediction of miRNA targets, affected proteins and their homologs in Glycine max.

microRNAs are small noncoding RNA gene products about 20-24nt long that are processed by Dicer from precursors with a characteristic hairpin secondary structure. As miRNAs affect the morphology of plants and animals by the posttranscriptional regulation of genes involved in critical developmental events, it has been proposed that precise regulation of miRNAs activity during various stages of growth and in specific cell types is of central importance for normal plant development. In our work we focus on the plant miRNAs and predict the miRNA targets, affected proteins by miRNA and miRNA homologs of Glycine max. Our analyses were based on sequence complementarities between miRNAs and mRNAs. As a result, we predicted 573 targets for 44 mature miRNAs sequences among 69 mature miRNAs sequences were published in database. Study of affected proteins revealed that for very less number of miRNAs, protein products are known and they mostly involved in diverse physiological process like as element of photosynthesis system. Homology analyses for miRNAs suggested that 22 miRNAs of Glycine max show 418 miRNA homologs for different plant species.

Comparative microarray data analysis for the expression of genes in the pathway of glioma.

Our present work focuses on the set of genes, which are involved in primary brain tumors - the glioma pathway. These gliomas are mostly malignant (cancerous) in nature and are difficult to be cured and that's why they attract the attention of all the workers. To understand the relative functionality of these genes, we analyzed the expression pattern of all genes, using gene expression data, at genomic level, and then to check their universality in all other cancers, we compared their expression levels and patterns in all other types of cancers by using gene expression graphs, and observed their expression levels in all these cancers, whether they are over or under expressed. We found that every gene has its own unique expression pattern and level and on that basis it can be classified. We also found that oncogenes and tumor suppressor genes that were involved in the glioma pathway were showing similar expression patterns in other cancers too but their expression level is low.