Biology subjects

Sharma, A.

Publications and source records attributed to Sharma, A..

At least 397 records · Page 22Linked to original sources

bioRxiv2020

Improved reference genome of the arboviral vector Aedes albopictus

The Asian tiger mosquito Aedes albopictus is globally expanding and has become the main vector for human arboviruses in Europe. Here we present AalbF2, a dramatically improved assembly of the Ae. albopictus genome that has revealed widespread viral insertions, novel microRNAs and piRNA clusters, the sex determining locus, new immunity genes, and has enabled genome-wide studies of geographically diverse Ae. albopictus populations and analyses of the developmental and stage-dependent network of expression data. Additionally, we built the first physical map for this species with 75% of the assembled genome anchored to the chromosomes. These up-to-date resources of the genome provide a foundation to improve understanding of the adaptation potential and the epidemiological relevance of this species and foster the development of innovative control measures. One Sentence SummaryLong-read and Hi-C-based de novo assembly of the arboviral vector Aedes albopictus genome fosters deeper understanding of its biological features.

genomics↗

bioRxiv2020

Spatial segregation and cooperation in radially expanding microbial colonies under antibiotic stress

Antibiotic resistance in microbial communities reflects a combination of processes operating at different scales. The molecular mechanisms underlying antibiotic resistance are increasingly understood, but less is known about how these molecular events give rise to spatiotemporal behavior on longer length scales. In this work, we investigate the population dynamics of bacterial colonies comprised of drug-resistant and drug-sensitive cells undergoing range expansion under antibiotic stress. Using the opportunistic pathogen E. faecalis with plasmid-encoded ({beta}-lactamase) resistance as a model system, we track colony expansion dynamics and visualize spatial pattern formation in fluorescently labeled populations exposed to ampicillin, a commonly-used {beta}-lactam antibiotic. We find that the radial expansion rate of mixed communities is approximately constant over a wide range of drug concentrations and initial population compositions. Fluorescence imaging of the final populations shows that resistance to ampicillin is cooperative, with sensitive cells surviving in the presence of resistant cells even at drug concentrations lethal to sensitive-only communities. Furthermore, despite the relative invariance of expansion rate across conditions, the populations exhibit a diverse range of spatial segregation patterns, with both the spatial structure and the population composition depending on drug concentration, initial composition, and initial population size. Agent based models indicate that the observed dynamics are consistent with long-range cooperation, despite the fact that {beta}-lactamase remains cell-associated in E. faecalis, and experiments confirm that resistant colonies provide a protective effect to sensitive cells on length scales multiple times the size of a single colony. Furthermore, in the limit of small inoculum sizes, we experimentally show that populations seeded with (on average) no more than a single resistant cell can produce mixed communities in the presence of drug. While biophysical models of diffusion-limited drug degradation suggest that individual resistant cells offer only short-range protection to neighboring sensitive cells, we show that long-range protection may arise from synergistic effects of multiple resistant cells, even when they represent only a small fraction of a colonys surface area. Our results suggest that {beta}-lactam resistance can be cooperative even in spatially extended systems where genetic segregation typically disfavors exploitation of locally produced public goods.

microbiology↗

bioRxiv2020

Short chain fatty acid butyrate promotes virus infection by repressing interferon stimulated genes

Butyrate is an abundant metabolite produced by the gut microbiota and is known to modulate multiple immune system pathways and inflammatory diseases. However, studies of its effects on virus infection of cells are limited and enigmatic. We found that butyrate increases cellular infection and virus replication in influenza virus, reovirus, and human immunodeficiency virus infections. Further exploring this phenomenon, we found that addition of butyrate to cells deficient in type I interferon (IFN) signaling did not increase susceptibility to virus infection. Accordingly, we discovered that butyrate suppressed levels of specific IFN stimulated gene (ISG) products in human and mouse cells. Butyrate did not inhibit IFN-induced phosphorylation of transcription factors STAT1 and STAT2 or their translocation to the nucleus, indicating that IFN signaling was not disrupted. Rather, our data are suggestive of a role for inhibition of histone deacetylase activity by butyrate in limiting ISG induction. Global transcript analysis revealed that butyrate increases expression of more than 800 cellular genes, but represses IFN-induced expression of 60% of ISGs. Overall, we identify a new mechanism by which butyrate promotes virus infection via repression of ISGs. Our findings also add to the growing body of evidence showing that individual ISGs respond differently to type I IFN induction depending on the cellular environment, including the presence of butyrate. ImportanceButyrate is a lipid produced by intestinal bacteria that can regulate inflammation throughout the body. Here we show for the first time that butyrate influences the innate antiviral immune response mediated by type I IFNs. A majority of antiviral genes induced by type I IFNs were repressed in the presence of butyrate, resulting in increased virus infection and replication in cells. This suggests that butyrate could be broadly used as a tool to increase growth of virus stocks for research and for the generation of vaccines. Our research also indicates that metabolites produced by the gut microbiome can have complex effects on cellular physiology as demonstrated by the dampening of an inflammatory innate immune pathway by butyrate resulting in a pro-viral cellular environment.

microbiology↗

bioRxiv2020

Attractor-like spatial representations in the Subicular Complex network

Distinct computations are performed at multiple brain regions during encoding of the spatial environments. Neural representations in the hippocampal, entorhinal and head direction (HD) networks during spatial navigation have been clearly documented, while the representational properties of the Subicular Complex (SC) network is rather unexplored, even though it has extensive anatomical connections with various brain regions involved in spatial information processing. Here, we report a global cue controlled highly coherent representation of the cue-conflict environment in the SC network, along with strong coupling between HD cells and Spatial cells. We propose that the attractor dynamics in the SC network might play a critical role in orientation of the spatial representations, thus providing a "reference map" of the environment for further processing at other networks.

neuroscience↗

bioRxiv2020

A repository of web-based bioinformatics resources developed in India

IndiaBioDb (https://webs.iiitd.edu.in/raghava/indiabiodb/) is a manually curated comprehensive repository of bioinformatics resources developed and maintained by Indian researchers. This repository maintains information about 543 freely accessible functional resources that include around 258 biological databases. Each entry provides a complete detail about a resource that includes the name of resources, web link, detail of publication, information about the corresponding author, name of institute, type of resource. A user-friendly searching module has been integrated, which allows users to search our repository on any field. In order to retrieve categorized information, we integrate the browsing facility in this repository. This database can be utilized for extracting the useful information regarding the present scenario of bioinformatics inclusive of all research labs funded by government and private bodies of India. In addition to web interface, we also developed mobile to facilitate the scientific community.

bioinformatics↗

bioRxiv2020

Multi-Object Tracking in Heterogeneous environments (MOTHe) for animal space-use studies

O_LIVideo recordings of animals are used for many areas of research such as collective movement, animal space-use, animal censuses and behavioural neuroscience. They provide us with behavioural data at scales and resolutions not possible with manual observations. Many automated methods are being developed to extract data from these high-resolution videos. However, the task of animal detection and tracking for videos taken in natural settings remains challenging due to heterogeneous environments. C_LIO_LIWe present an open-source end-to-end pipeline called Multi-Object Tracking in Heterogenous environments (MOTHe), a python-based application that uses a basic convolutional neural network for object detection. MOTHe allows researchers with minimal coding experience to track multiple animals in their natural habitats. It identifies animals even when individuals are stationary or partially camouflaged. C_LIO_LIMOTHe has a command-line-based interface with one command for each action, for example, finding animals in an image and tracking each individual. Parameters used by the algorithm are well described in a configuration file along with example values for different types of tracking scenario. MOTHe doesnt require any sophisticated infrastructure and can be run on basic desktop computing units. C_LIO_LIWe demonstrate MOTHe on six video clips from two species in their natural habitat - wasp colonies on their nests (up to 12 individuals per colony) and antelope herds in four different types of habitats (up to 156 individuals in a herd). Using MOTHe, we are able to detect and track all individuals in these animal group videos. MOTHes computing time on a personal computer with 4 GB RAM and i5 processor is 5 minutes for a 30-second long ultra-HD (4K resolution) video recorded at 30 frames per second. C_LIO_LIMOTHe is available as an open-source repository with a detailed user guide and demonstrations at Github (https://github.com/tee-lab/MOTHe). C_LI

ecology↗

bioRxiv2019

Identification of regulators of poly-ADP-ribose polymerase (PARP) inhibitor response through complementary CRISPR knockout and activation screens

Inhibitors of poly-ADP-ribose polymerase 1 (PARPi) are highly effective in killing cells deficient in the homologous recombination (HR) DNA repair pathway, such as those lacking BRCA2. In light of this, PARPi have been utilized in recent years to treat BRCA2-mutant tumors, with many patients deriving impressive clinical benefit. However, positive response to PARPi is not universal, even among patients with HR-deficient tumors. Here, we present the results of three genome-wide CRISPR knockout and activation screens which provide an unbiased look at genetic determinants of PARPi response in wildtype or BRCA2-knockout cells. Strikingly, we reveal that depletion of the histone acetyltransferase TIP60, a top hit from our screens, robustly reverses the PARPi sensitivity caused by BRCA2 deficiency. Mechanistically, we show that TIP60 depletion rewires double strand break repair in BRCA2-deficient cells by promoting 53BP1 binding to double strand breaks to suppress end resection. Our work provides a comprehensive set of putative biomarkers that serve to better understand and predict PARPi response, and identifies a novel pathway of PARPi resistance in BRCA2-deficient cells.

molecular biology↗

bioRxiv2019

Integrative genomic analysis unifying epigenetic inheritance in adaptation and canalization

Epigenetic inheritance, especially its biomedical and evolutionary significance, is an immensely interesting but highly controversial subject. Notably, a recent analysis of existing multi-omics has supported the mechanistic plausibility of epigenetic inheritance and its implications in disease and evolution. The evolutionary support stemmed from the specific finding that genes associated with cold induced inheritance and with latitudinal adaptation in mice are exceptionally common. Here, a similar gene set overlap analysis is presented that integrates cold induced inheritance with evolutionary adaptation and genetic canalization in cold environment in Drosophila. Genes showing differential expression in inheritance specifically overrepresent gene sets associated with differential and allele specific expression, though not with genome-wide genetic differentiation, in adaptation. On the other hand, the differentiated outliers uniquely overrepresent genes dysregulated by radicicol, a decanalization inducer. Both gene sets in turn exclusively show enrichment of genes that accumulate, in intended experimental lines, de novo mutations, a potential source of canalization. Successively, the three gene sets distinctively overrepresent genes exhibiting, between mutation accumulation lines, invariable expression, a potential signal for canalization. Sequentially, the four gene sets solely display enrichment of genes grouped in gene ontology under transcription factor activity, a signature of regulatory canalization. Cumulatively, the analysis suggests that epigenetic inheritance possibly contributes to evolutionary adaptation in the form of cis regulatory variations, with trans variations arising in the course of genetic canalization.

genomics↗

bioRxiv2019

Robustness and lethality in multilayer biological molecular networks

Robustness is a prominent feature of most biological systems. In a cell, the structure of the interactions between genes, proteins, and metabolites has a crucial role in maintaining the cells functionality and viability in presence of external perturbations and noise. Despite advances in characterizing the robustness of biological systems, most of the current efforts have been focused on studying homogeneous molecular networks in isolation, such as protein-protein or gene regulatory networks, neglecting the interactions among different molecular substrates. Here we propose a comprehensive framework for understanding how the interactions between genes, proteins and metabolites contribute to the determinants of robustness in a heterogeneous biological network. We integrate heterogeneous sources of data to construct a multilayer interaction network composed of a gene regulatory layer, and protein-protein interaction layer and a metabolic layer. We design a simulated perturbation process to characterize the contribution of each gene to the overall systems robustness, defined as its influence over the global network. We find that highly influential genes are enriched in essential and cancer genes, confirming the central role of these genes in critical cellular processes. Further, we determine that the metabolic layer is more vulnerable to perturbations involving genes associated to metabolic diseases. By comparing the robustness of the network to multiple randomized network models, we find that the real network is comparably or more robust than expected in the random realizations. Finally, we analytically derive the expected robustness of multilayer biological networks starting from the degree distributions within or between layers. These results provide new insights into the non-trivial dynamics occurring in the cell after a genetic perturbation is applied, confirming the importance of including the coupling between different layers of interaction in models of complex biological systems.

systems biology↗

bioRxiv2019

Membrane constriction and thinning by sequential ESCRT-III polymerization

The Endosomal Sorting Complexes Required for Transport (ESCRTs) mediate diverse membrane remodeling events. These activities typically require ESCRT-III proteins to stabilize negatively-curved membranes, although recent work has indicated that certain ESCRT-IIIs also participate in positive-curvature membrane shaping reactions. ESCRT-IIIs polymerize into membrane-binding filaments, but the structural basis for negative versus positive membrane curvature shaping by these proteins remains poorly understood. To learn how ESCRT-IIIs shape membranes, we determined structures of human membrane-bound CHMP1B-only, membrane-bound CHMP1B+IST1, and IST1-only filaments by electron cryomicroscopy. Our structures show how CHMP1B first polymerizes into a single-stranded helical filament, shaping membranes into moderate-curvature tubules. Subsequently, IST1 assembles a second strand upon the CHMP1B filament, further constricting the membrane tube and reducing its diameter nearly to the fission point. Each step of constriction, moreover, thins the underlying bilayer and lowers the barrier to membrane fission. Together, our structures reveal how a two-component, sequential polymerization mechanism drives membrane tubulation, tube constriction, and bilayer thinning.

biophysics↗

bioRxiv2019

Next generation sequencing reveals NRAP as a candidate gene for hypertrophic cardiomyopathy in elderly patients

Hypertrophic cardiomyopathy (HCM) is a genetic disorder that affects people of all ages, with the elderly population being inadequately studied. It is primarily caused by gene variants that encode proteins involved in the structure and function of the heart muscle. The identification of genes associated with elderly HCM requires ethnic-specific genomic sequences from Wellderly individuals. Currently, no Indian Wellderly dataset is available. To address this, we collected and sequenced the Indian Wellderly population. We built a novel Indian database of healthy aging nucleotide sequences (named i-DHANS) and is newly accessible at IndiCardiome. Utilizing this database and Indian HCM cohort, we identified nebulin-related anchoring protein (NRAP) as a gene associated with elderly HCM. NRAP is crucial for the assembly of myofibrils and transmission of force from the sarcomere to the extracellular matrix. Our functional analysis showed that the identified NRAP variant had significantly reduced interactions with its interacting partners, such as Kelch-like protein 41 (KLHL41) and -actinin, implying a loss of function. In summary, our findings indicate that NRAP is a new elderly cardiomyopathy gene, and our Indian Wellderly database is a valuable resource for identifying ethnic-specific genes for various diseases.

genomics↗

bioRxiv2019

Supervised learning of protein thermal stability using sequence mining and distribution statistics of network centrality

MotivationIt is expected that the difference in the thermal stability of mesophilic and thermophilic proteins arises, in part at least, from the differences in their molecular structures and amino acid compositions. Existing machine learning approaches for supervised classification of proteins rely on the features derived from the structural networks and the amino acid sequences. However, the network features used leave out several important network centrality values, the statistic used is a simple average and the sequence features used are hand-picked leading to an accuracy of 90%.\n\nResultsWe show that discriminating sub-sequences of the amino acid sequences can significantly improve classification accuracy compared to the existing approaches of counting amino acids, di-peptide or even tri-peptide bonds. We identify notions of network centrality, specifically that depends on the distances between C atoms, that appears to correlate better with thermal stability compared to the existing network features. We also show how to generate better statistics from the node- and edge-wise centrality values that more accurately captures the variations in their values for different types of proteins. These improved feature selection techniques make it possible to classify between thermophilic and mesophilic proteins with 96% accuracy and 99% area under ROC.\n\nAvailabilityThe dataset and source code used are available at https://github.com/ankits0207/Protein_Classification_BIO699\n\nContactdbera@iiitd.ac.in\n\nonline.

bioinformatics↗

bioRxiv2019

Multi-omics data analysis implicating epigenetic inheritance in evolution and disease

Recent evidence surprisingly suggests existence of germline mediated epigenetic inheritance in diverse species including mammals. The evolutionary and health implications as well as the mechanistic plausibility of epigenetic inheritance are subjects of immense current interest and controversy, with integrative analysis expected to provide valuable insights. Here, an unbiased gene set enrichment analysis of existing multi-omics data is presented that readily supports a role of sperm DNA methylome in evolution and disease, as also in developmental mechanisms. In mice, differentially methylated sperm genes in cold induced inheritance specifically overrepresent genes associated with cold adaptation. Similarly, in humans, differentially methylated sperm genes associate with disease and adaptation in general, with specific disease association supported by prior evidence. Further, the sperm genes, like disease and adaptation genes, overrepresent genes known to exhibit higher mutability, loss-of-function intolerance, and haploinsufficiency. Finally, both mouse and human sperm genes show enrichment for genes that retain sperm methylation during development and are developmentally expressed. Together, the present analysis provides one-stop evidence to suggest that sperm DNA methylome acts as a melting pot of gene-environment interaction, inheritance, evolution, and health and disease.

genomics↗

bioRxiv2019

The periphery and the core properties explain the omnigenic model in the human interactome

Understanding the connectivity patterns of genes in a localized disease neighborhood or disease module in a molecular interaction network (interactome) is a key step toward advancing the knowledge about molecular mechanisms underlying a complex disease. In this work, we introduce a framework that detects peripheral and core regions of a disease in the human interactome. We leverage gene expression data on 104 diseases and analyze the connectivity of differentially expressed genes (quantified by a p-value < 0.05) and their topological membership in the network to distinguish between peripheral and core genes. Per definition, peripheral and core genes are topologically different and we show that they also differ biologically. Core genes are more enriched for Genome-wide association study (GWAS) and Online Mendelian Inheritance in Man (OMIM) data, whereas peripheral genes are more shared across different disease states and their overlap helps predict disease proximity in the human interactome. Based on this observation, we propose a flower model to explain the organization of genes in the human interactome, with core genes of different diseases as the petals and the peripheral genes as the (shared) stem. We show that this network model is an important step towards finding novel drug targets and improving disease classification. Overall, we were able to demonstrate how perturbations percolate through the human interactome and contribute to peripheral and core regions, an important novel feature of the omnigenic model.

systems biology↗

bioRxiv2019

Sex differences in seizure at presentation in glioma population

Seizures are common presenting symptoms of primary brain tumors. Mechanisms of epileptogenesis are still unknown and are believed to be multifactorial. Previous studies have indicated correlation of seizure with tumor location. Recent investigations of our group have shown image-based parameters have sex-specific implications for patient outcome. In this retrospective study, we examined the association of tumor location with the probability and risk of seizure in male and female glioma patients.

cancer biology↗

bioRxiv2019

Sex Differences in Predictors of Seizure in Contrast-Enhancing Gliomas at Clinical Presentation: A Network Approach

BackgroundBrain tumor related epilepsy (BTE) is a major co-morbidity related to the management of patients with brain cancer. Despite published practice guidelines recommending against anti-epileptic drug (AED) utilization in patients with gliomas, there is heterogeneity in prescription practices of AEDs in these patients. In an attempt to impact BTE management, we statistically analyzed clinically relevant attributes (sex, age, tumor size, tumor growth kinetics, and tumor location) pertaining to seizure at presentation and used them to build a computational machine learning model to predict the probability of a seizure (at presentation).\n\nMethodsFrom our clinical data repository, we identified 223 patients (females, n=86; males, n=137) with pathologically-determined glioma and known seizure status at clinical presentation. Non-parametric and Fishers Exact tests were used to identify statistical differences in clinical characteristics. We utilized a random forest machine learning method for generating our predictive models by entire cohort and separated by male and female.\n\nFindingsPatients were divided into those that presented with seizure (SP, n=96, 43%; F, n= 28; M, n= 68) and those that presented without seizure (nSP, n=127, 57%, F n=58, M n=69). Females presented with seizures significantly less often than males (x2=6{middle dot}28, p=0{middle dot}01). SP patients had significantly smaller T1Gd radius compared to nSP (SP 11{middle dot}30mm, nSP 18.66mm, p<0{middle dot}0001). Tumor size and patient age were significant negative predictors for SP; patients with larger tumors, older age and less tumor diffusivity (p/D) were at lower risk for SP.\n\nInterpretationDespite heterogeneity across our patient cohort, there is strong evidence of a role for patient sex, tumor size, tumor invasion, and patient age in predicting the incidence of seizures at diagnosis. Future studies, with prospectively detailed data collection, may provide clearer insights into the incidence of seizures through a patients treatment course.

cancer biology↗

bioRxiv2019

A Willow Sex Chromosome Reveals Convergent Evolution of Complex Palindromic Repeats

BackgroundSex chromosomes in a wide variety of species share common characteristics, including the presence of suppressed recombination surrounding sex determination loci. They have arisen independently in numerous lineages, providing a conclusive example of convergent evolution. Mammalian sex chromosomes contain multiple palindromic repeats across the non-recombining region that facilitate sequence conservation through gene conversion, and contain genes that are crucial for sexual reproduction. Plant sex chromosomes are less well understood, and in particular it is not clear how coding sequence conservation is maintained in the absence of homologous recombination.\n\nResultsHere we present the first evidence of large palindromic structures in a plant sex chromosome, based on a highly contiguous assembly of the W chromosome of the dioecious shrub Salix purpurea. Two consecutive palindromes span over a region of 200 kb, with conspicuous 20 kb stretches of highly conserved sequences among the four arms. The closely-related species S. suchowensis also has two copies of a portion of the palindrome arm and provides strong evidence for gene conversion. Four genes in the palindrome are homologous to genes in the SDR of the closely-related genus Populus, which is located on a different chromosome. These genes show distinct, floral-biased expression patterns compared to paralogous copies on autosomes.\n\nConclusionThe presence of palindromic structures in sex chromosomes of mammals and plants highlights the intrinsic importance of these features in adaptive evolution in the absence of recombination. Convergent evolution is driving both the independent establishment of sex chromosomes as well as their fine-scale sequence structure.

genomics↗

bioRxiv2019

Non-genetic intra-tumor heterogeneity is a major predictor of phenotypic heterogeneity and ongoing evolutionary dynamics in lung tumors

Impacts of genetic and non-genetic intra-tumor heterogeneity (ITH) on tumor phenotypes and evolvability remain debated. We analyzed ITH in lung squamous cell carcinoma (LUSC) at the levels of genome, transcriptome, tumor-immune interactions, and histopathological characteristics by multi-region profiling and using single-cell sequencing data. Overall, in LUSC genomic heterogeneity alone was a weak indicator of intra-tumor non-genetic heterogeneity at immune and transcriptomic levels that impacted multiple cancer-related pathways including those related to proliferation and inflammation, which in turn contributed to intra-tumor regional differences in histopathology and subtype classification. Genome, transcriptome, and immune-level heterogeneity influenced different aspects of tumor evolution. Tumor subclones had substantial differences in proliferation score, suggestive of non-neutral clonal dynamics. Scores for proliferation and other cancer-related pathways also showed intra-tumor regional differences, sometimes even within the same subclones. Neo-epitope burden negatively correlated with immune infiltration, indicating potential immune-mediated purifying selection on acquired mutations in these tumors. Taken together, our observations suggest that non-genetic heterogeneity is a major determinant of heterogeneity in histopathological characteristics and impacts evolutionary dynamics in lung cancer.

cancer biology↗