Biology subjects

Verma, R. K.

Publications and source records attributed to Verma, R. K..

14 recordsLinked to original sources

bioRxiv2025

Tissue-Specific Experimental Evolution Reveals Adaptive Trade-Offs in the Plant Vascular Pathogen Clavibacter michiganensis

The plant pathogenic bacterium Clavibacter michiganensis (Cm) is a systemic vascular pathogen that colonizes both xylem vessels and the intracellular apoplast during different stages of infection. To identify traits and loci associated with adaptation to these distinct host microenvironments, we conducted tissue-specific experimental evolution. Twenty independent Cm lineages were repeatedly passaged in either tomato stems or leaves to promote adaptation to vascular or apoplastic lifestyles, respectively. After fifteen passages, adapted clones were characterized for virulence and virulence-related traits. These characterizations demonstrated clear differential associations of virulence-associated traits with the adapted tissue. The majority of vascular-adapted clones displayed enhanced surface attachment, reduced cellulase activity, reduced exopolysaccharide (EPS) production, and attenuated virulence on tomato compared to the parent clone. On the other hand, apoplast-adapted clones displayed reduced biofilm formation and enhanced EPS production while maintaining their virulence on tomato. Whole-genome sequencing of all adapted clones revealed candidate loci linked to tissue adaptation. Notably, six of ten vascular-adapted clones carried two independent mutations in CMM_1284, a putative HipB/XRE-type transcriptional regulator. A CMM_1284 marker exchange mutant displayed phenotypes similar to vascular-adapted clones, suggesting a role for this regulator in vascular colonization. Together, these findings highlight the role of phenotypic plasticity in tissue adaptation of plant pathogens, showing that tissue-specific adaptation involves modulation of surface attachment, EPS production, and cell wall-degrading enzymes. They further reveal a regulated trade-off between vascular persistence, supported by strong surface attachment, and systemic virulence, which depends on bacterial dispersal and migration.

microbiology↗

bioRxiv2025

Discovery of Prognostic Biomarkers in Gastric Cancer Through Machine Learning and Bioinformatics Analysis of Gene Expression Data

Gastric cancer (GC) often gets diagnosed in its advanced stages, resulting in poorer prognoses. To identify potential biomarkers in GC, we used fifteen datasets from NCBI-GEO and integrated them into a complete dataset. From the complete dataset, we extracted a subset of only the known cancer driver genes. Using Recursive Feature Elimination (RFE), mutual information (MI), and tree-based (TB) method (SelectFromModel), we extracted top gene features using RFE (10, 20, 30, 40, and 50) and 50 features each from MI and TB method. Subsequently, we applied machine learning classifiers to these selected gene features to classify cancer and normal samples. The SVC classifiers demonstrated better performance when utilizing the top 50 gene features using RFE and MI, while the AB classifier achieved the highest performance using TB for the complete dataset and for driver datasets, RF performed well using 40 features using RFE and SVC, and ET showed up better performance using 50 features using MI and TB feature selection for the test dataset. After combining all the genes from both datasets from and from all three feature selection methods, only 115 showed differentially expressed genes. A Lasso-penalized Cox regression model was applied to narrow down the gene selection to fourteen. This study highlights the effectiveness of integrating machine learning and bioinformatics analysis to identify new biomarkers for GC.

bioinformatics↗

bioRxiv2025

Co-mutation based genetic networks to infer temporal mutation dynamics in ancient human mitochondrial genomes

The evolution of modern humans is as fascinating as it is complicated. Various environmental and socio-political factors have played a significant role in shaping different migratory paths and lifestyles in ancient times and the establishment of current sub-populations around the globe. These factors have impacted the molecular evolution of mitochondrial DNA (mtDNA). To account for the role of genetic background and variable sites in shaping the migratory and evolutionary paths, we analyzed the ancient mtDNA as spatiotemporal co-mutation networks. Haplogroup-based analysis of the variable sites suggests a transition from hunter-gatherer to agrarian lifestyle during the Copper-Bronze transition period. Furthermore, the genetic interaction networks showed that COX and CYB genes behaved diversely with time and that there is an interplay of the genetic interactions with NADH Dehydrogenase genes specific to each age. We performed a phylogeny (tree) based gene network analysis and examined polymorphism to divergence ratios to complement the co-mutation networks. The tree-based gene networks exhibit similar topology with reduced co-mutation among the genes. The more traditional polymorphism/divergence analysis indicated that the CYB gene has been under long-term purifying selection. In contrast, other genes (ATP6, COX, NADH hydrogenases) have undergone episodes of purifying selection corresponding to different ages. We believe this network-based exploratory study provides insights into early lifestyle transitions and haplogroup establishment of the current human population.

evolutionary biology↗

bioRxiv2025

Outcrossing Complicates Mutation Purging by Trapping Single Nucleotide Polymorphisms in Structural Variant Mutations

Classical mutational theories centered on single nucleotide polymorphisms suggest that outcrossing enhances the purging of deleterious mutations by promoting recombination. However, larger structural variants, such as insertions, deletions, and inversions, can suppress recombination and create linkage blocks. Using experimental evolution and whole-genome long- and short-read sequencing, we characterized structural and nucleotide mutation landscapes in three Caenorhabditis elegans strains following repeated mutagen exposure and recovery. We found substantial strain-specific differences in structural variant accumulation and mutation retention. The strain with the highest outcrossing propensity exhibited the greatest structural variant burden and a higher fraction of single nucleotide polymorphisms within structural variant intervals. Consistent with this pattern, our population genetic simulations showed that structural variants can persist more readily under higher outcrossing rates. Together, these results indicate that structural variant architecture may influence mutation retention dynamics and highlight strain-specific constraints on purging following mutagenesis in C. elegans.

bioinformatics↗

bioRxiv2024

Machine Learning-Based Identification of B4GALNT1 as a Key Player in Hepatocellular Carcinoma: A Comprehensive Bioinformatics and Structural Analysis

Liver hepatocellular carcinoma (LIHC) is one of the most frequent types of malignant cancer in the globe. The identification of new biomarkers for the LIHC is critical. We used TCGA-LIHC gene expression datasets for this study. Several feature selection methods were used to find the top gene signatures that distinguish LIHC cancer from normal samples. Eleven machine learning algorithms were used on these selected characteristics, and model performance evaluation revealed that Naive Bayes Classifiers (AUC = 0.965) performs the best for a selection of 55 protein coding genes. Among 55 protein coding genes we found B4GALNT1 (Beta-1,4-N-acetyl-galactosaminyltransferase 1) which is differentially regulated in LIHC. With several evidence B4GALNT1 plays crucial role in tumorigenesis in many cancers, therefore we conducted systematic bioinformatics approach with mutational and structural analysis of B4GALNT1 in LIHC. Moreover, survival analysis, immune cell infiltration, most significant associated methylated CpG probe and access the accuracy of B4GALNT1 conducted to find the potential role of B4GALNT1. The results suggested that B4GALNT1 was significantly expressed in most cancers including LIHC. Finally, 16 missense mutations identified through cBioportal, Cosmic Database, and Human Variant Database, among which 6 mutations (P64Q, S131F, A311S, R340Q, D478H, and P507Q) found to be deleterious when analysed by in-silico prediction algorithms such as SIFT, PolyPhen2, I Mutent2 and CADD in LIHC. Molecular Dynamics simulation analysis was performed to understand the atomic details of the structure and functional changes. Results from this study suggest the impact of these missense variants on the structure of the B4GALNT1 protein and its pathogenic relevance. Our study demonstrated that B4GALNT1 may be evaluated as a novel target for liver cancer therapy because it has been found to be overexpressed in Liver and correlates with a poor prognosis.

bioinformatics↗

bioRxiv2023

Thrombospondin-1 promotes fibro-adipogenic stromal expansion and contractile dysfunction of the diaphragm in obesity

Pulmonary disorders impact 40-80% of individuals with obesity. Respiratory muscle dysfunction is linked to these conditions; however, its pathophysiology remains largely undefined. Mice subjected to diet-induced obesity (DIO) develop diaphragmatic weakness. Increased intra-diaphragmatic adiposity and extracellular matrix (ECM) content correlate with reductions in contractile force. Thrombospondin-1 (THBS1) is an obesity-associated matricellular protein linked with muscular damage in genetic myopathies. THBS1 induces proliferation of fibro-adipogenic progenitors (FAPs)--mesenchymal cells that differentiate into adipocytes and fibroblasts. We hypothesized that THBS1 drives FAP-mediated diaphragm remodeling and contractile dysfunction in DIO. We tested this by comparing effects of dietary challenge on diaphragms of wild-type (WT) and Thbs1 knockout (Thbs1-/-) mice. Bulk and single-cell transcriptomics demonstrated DIO-induced stromal expansion in WT diaphragms. Diaphragm FAPs displayed upregulation of ECM and TGF{beta}-related expression signatures, and augmentation of a Thy1-expressing sub-population previously linked to type 2 diabetes. Despite similar weight gain, Thbs1-/- mice were protected from these transcriptomic changes, and from obesity-induced increases in diaphragm adiposity and ECM deposition. Unlike WT controls, Thbs1-/-diaphragms maintained normal contractile force and motion after DIO challenge. These findings establish THBS1 as a necessary mediator of diaphragm stromal remodeling and contractile dysfunction in overnutrition, and potential therapeutic target in obesity-associated respiratory dysfunction.

cell biology↗

bioRxiv2023

Allelic variations in a serine protease effector within Clavibacter michiganensis populations determine pathogen host range

Plant pathogenic bacteria often have a narrow host range, which can vary among different isolates within a population. Here we investigated the host range of the tomato pathogen Clavibacter michiganensis (Cm). We determined the genome sequences of 40 tomato Cm isolates and screened them for pathogenicity on tomato and eggplant. Our screen revealed that out of the tested isolates, five were unable to cause disease on any of the hosts, 33 were exclusively pathogenic on tomato, and two were capable of infecting both tomato and eggplant. Through comparative genomic analyses, we identified that the five non-pathogenic isolates lacked the chp/tomA pathogenicity island, which has previously been associated with virulence in tomato. In addition, we found that the two eggplant-pathogenic isolates encode a unique allelic variant of the serine protease chpG (chpGC), an effector that is recognized in eggplant. Introduction of chpGC into a chpG inactivation mutant in the eggplant-non-pathogenic strain Cm101, failed to complement the mutant, which retained its ability to cause disease in eggplant and failed to elicit hypersensitive response (HR). Conversely, introduction of the chpG variant from Cm101 into an eggplant pathogenic isolate (CmC48), eliminated its pathogenicity on eggplant, and enabled CmC48 to elicit HR. Our study demonstrates that allelic variation in the chpG effector gene is a key determinant of host range plasticity within Cm populations.

microbiology↗

bioRxiv2023

Higher-order co-mutation interactions in mitochondrial genomes

Pair-wise co-mutation networks of the mitochondrial genome have already provided ample evidences about the roles of genetic interactions in the manifestation of phenotype under altered environmental conditions. Here, we present a method to construct and analyze higher-order interactions, namely, 3-uniform hypergraphs of the mitochondrial genome for different altitude populations to decipher the role of co-mutating variable sites beyond pair-wise interactions. While the weights distribution of such gene hyperedges manifested power-law for all the altitudes, we identified altitude-specific genes based on gene hyperedge weight. This framework of hypergraphs serves a promising avenue for future investigation of nuclear genomes in context of phenotypic association and genetic disorders.

systems biology↗

bioRxiv2022

Modelling SARS-CoV-2 spike-protein mutation effects on ACE2 binding

The binding affinity of the SARS-CoV-2 spike (S)-protein {Delta}{Delta}Gbind to the human membrane protein ACE2 is critical for virus function and evolution. Computational structure-based screening of new S-protein mutations for ACE2 binding lends promise to rationalize virus function directly from protein structure and ideally aid early detection of potentially concerning variants. We used a computational protocol based on cryo-electron microscopy structures of the S-protein to estimate the ACE2-binding that gave good trend agreement with experimental ACE2 affinities. We then expanded predictions to all possible S-protein mutations in 21 different S-protein-ACE2 complexes (400,000 {Delta}{Delta}Gbind data points in total), using mutation group comparisons to reduce systematic errors. We show that mutations that have arisen in major variants as a group maintain ACE2 affinity significantly more than random mutations in the total protein, at the interface, and at evolvable sites, with differences between variant mutations being small relative to these effects. Omicron mutations as a group had a modest change in binding affinity compared to mutations in other major variants. The single-mutation effects are consistent with ACE2 binding being optimized and maintained in omicron, despite increased importance of other selection pressures (antigenic drift). As epistasis, glycosylation and in vivo conditions will modulate these effects, computational predictive SARS-CoV-2 evolution remains far from achieved, but the feasibility of large-scale computation is substantially aided by using many structures and comparison of mutation groups rather than single mutation effects, which are very uncertain. Our results demonstrate substantial challenges but indicate ways to improve the quality of computer models for assessing SARS-CoV-2 mutation effects.

biophysics↗

bioRxiv2021

Role of mitochondrial genetic interactions in determining adaptation to high altitude in human population around the globe

Physiological and haplogroup studies performed to understand high-altitude adaptation in humans are limited to individual genes and polymorphic sites. Due to stochastic evolutionary forces, the frequency of a polymorphism is affected by changes in the frequency of a near-by polymorphism on the same DNA sample making them connected in terms of evolution. Here, first we provide a method to model these mitochondrial polymorphisms as "co-mutation networks" for three high-altitude populations, Tibetan, Ethiopian and Andean. Then, by transforming these co-mutation networks into weighted and undirected gene-gene interaction (GGI) networks, we were able to identify functionally enriched genetic interactions of CYB and CO3 genes in Tibetan and Andean populations, while NADH dehydrogenase genes in Ethiopian population playing a significant role in high altitude adaptation. These co-mutation based genetic networks provide insights into the role of different set of genes in high-altitude adaptation human sub-populations.

bioinformatics↗

bioRxiv2021

Unravelling cotton RNAseq repositories to the fiber development specific modules and their alliance with the fiber-related traits

Cotton fiber development is still an intriguing question to understand the fiber commitment and development. Here, we remapped >350 publicly available cotton RNA sequencing data on recently published cotton genome with [~]400 fold coverage. The differentially expressed genes were clustered in six modules whose functions are specific to commitment, initiation, elongation and Secondary Cell Wall (SCW) fiber development stages. Gene Ontology analysis of commitment and initiation specific modules suggests enrichment of genes involved in organ development. The modules specific for elongation and SCW showed significant enrichment of hydroxyproline-rich proteins and hydrolases. Transcription factors (TFs) binding frequency of defined modules suggested that homeodomain, MYB and NAC expresses at commitment stages but their expression was governed by other TFs. We also mined the stage-specific transcriptional biomarker and Exclusively Expressed Transcripts (EETs) for fiber. These EETs were positively selected during fiber evolution and cotton domestication. The extensive expression profiling of six EETs in 100 cotton genotypes at different fiber developmental stages using nCounter assay and their correlation with eight fiber-related suggests that several EETs are correlated with different fiber quality-related traits. Thus, our study reveals several important genes and pathways that may be important for cotton fiber development and future improvement of cotton.

plant biology↗

bioRxiv2019

Altitude-wise analysis of co-occurrence networks of mitochondrial genome in Asian population

Networks have been established as an extremely powerful framework to understand and predict the behavior of many large-scale complex systems. We have studied network motifs, the basic structural elements of networks, to describe the possible role of co-occurrence of genomic variations behind high altitude adaptation in the Asian human population. Mitochondrial DNA (mt-DNA) variations have been acclaimed as one of the key players in understanding the biological mechanisms behind adaptation to extreme conditions. To explore the cumulative effects and variations in the mitochondrial genome with the variation in the altitude, we investigated human mt-DNA sequences from the NCBI database at different altitudes under the co-occurrence motifs framework. Analysis of the co-occurrence motifs using similarity clusteringrevealed a clear distinction between lower and higher altitude regions. In addition, the previously known high altitude markers 3394 and 7697 (which are definitive sites of haplogroup M9a1a1c1b) were found to co-occur within their own gene complexes indicating the impact of intra-genic constraint on co-evolution of nucleotides. Furthermore, an ancestral RSRS50 variant 10398 was found to co-occur only at higher altitudes supporting the fact that a separate route of colonization at these altitudes might have taken place. Overall, our analysis revealed the presence of co-occurrence interactions specific to high altitude at a whole mitochondrial genome level. This study, combined with the classical haplogroups analysis is useful in understanding the role of co-occurrence of mitochondrial variations in high altitude adaptation.

systems biology↗

bioRxiv2019

Distinct antagonist-bound inactive states underlie the divergence in the structures of the dopamine D2 and D3 receptors

Understanding how crystal structures reflect the range of possible G protein-coupled receptor (GPCR) states is critical for rational drug discovery (RDD). Combining computational simulations with mutagenesis and binding studies, we find that the structure of the dopamine D2 receptor (D2R)/risperidone complex captures an inactive receptor conformation that accommodates some but not all antagonist scaffolds. Indeed, we find that eticlopride binds D2R in a configuration very similar to that seen in the D3R structure, in a pose that is incompatible with the D2R/risperidone structure. Moreover, our simulations reveal that extracellular loops 1 and 2 (EL1 and EL2) are highly dynamic, with spontaneous transitions of EL2 from the helical conformation in the D2R/risperidone structure to an extended conformation similar to that in the D3R/eticlopride structure. Our results highlight previously unappreciated conformational diversity and dynamics in the inactive state of a GPCR with potential functional implications. These findings are also of paramount importance for RDD as limiting a virtual screen to one state will miss relevant ligands.

biophysics↗

bioRxiv2018

Impact of mitochondrial epistatic interactions on evolution of different human subpopulations

Investigation of human mitochondrial (mt) genome variation has been shown to provide insights to the human history and natural selection. By analyzing 24,167 human mt-genome samples, collected for five continents, we have developed a co-mutation network model to investigate characteristic human evolutionary patterns. The analysis highlighted richer co-mutating regions of the mt-genome, suggesting the presence of epistasis. Specifically, a large portion of COX genes was found to co-mutate in Asian and American populations, whereas, in African, European, and Oceanic populations, there was greater co-mutation bias in hypervariable regions. Interestingly, this study demonstrated hierarchical modularity as a crucial agent for these co-mutation networks. More profoundly, our ancestry-based co-mutation module analyses showed that mutations cluster preferentially in known mitochondrial haplogroups. Contemporary human mt-genome nucleotides most closely resembled the ancestral state, and very few of them were found to be ancestral-variants. Overall, these results demonstrated that subpopulation-based biases may favor mitochondrial gene specific epistasis.

synthetic biology↗