Biology subjects

Sharma, A.

Publications and source records attributed to Sharma, A..

431 records · Page 24Linked to original sources

bioRxiv2018

Chicago and Dovetail Hi-C proximity ligation yield chromosome length scaffolds of Ixodes scapularis genome

A high-quality genome sequence is essential for understanding an organism on molecular level. However, the larger genomes with substantial repetitive sequences are challenging to assemble with the sequencing technologies. Hi-C technique is changing the genome architecture landscape by providing links across a variety of length scales, spanning even whole chromosomes. Ixodes scapularis haploid genome is 2.1 gbp and the current assembly consists of 369,495 scaffolds representing 57% of the genome. The fragmented genome poses challenges with functional gene analysis and an improved assembly is needed. We therefore used the Hi C technique to achieve chromosomal level assembly of tick genome. With Chicago and Dovetail Hi C assemblies, we were able to achieve 28 >10Mb sequences that correspond to 28 chromosomes in I. scapularis.

genomics↗

bioRxiv2018

A conserved role of the insulin-like signaling pathway in uric acid pathologies revealed in Drosophila melanogaster

Elevated uric acid (UA) is a key factor for disorders, including gout or kidney stones and result from abrogated expression of Urate Oxidase (Uro) and diet. To understand the genetic pathways influencing UA metabolism we established a Drosophila melanogaster model with elevated UA using Uro knockdown. Reduced Uro expression resulted in the accumulation of UA concretions and diet-dependent shortening of lifespan. Inhibition of insulin-like signaling (ILS) pathway genes reduced UA and concretion load. In humans, SNPs in the ILS genes AKT2 and FOXO3 were associated with UA levels or gout, supporting a conserved role for ILS in modulating UA metabolism. Downstream of the ILS pathway UA pathogenicity was mediated partly by NADPH Oxidase, whose inhibition attenuated the reduced lifespan and concretion accumulation. Thus, genes in the ILS pathway represent potential therapeutic targets for treating UA associated pathologies, including gout and kidney stones.\n\nHighlightsO_LIIn Drosophila high uric acid (UA) levels shorten lifespan and cause UA aggregation\nC_LIO_LIConserved in flies and humans, the ILS pathway associates with UA pathologies\nC_LIO_LIFoxO dampens concretion formation by reducing UA levels and ROS formation\nC_LIO_LIInhibition of NOX alleviates the lifespan attenuation and UA aggregation\nC_LI

pathology↗

bioRxiv2018

Temporal Multiple Kernel Learning (tMKL) model for predicting resting state FC via characterizing fMRI connectivity dynamics

Over the last decade there has been growing interest in understanding the brain activity in the absence of any task or stimulus captured by the resting-state functional magnetic resonance imaging (rsfMRI). These resting state patterns are not static, but exhibit complex spatio-temporal dynamics. In the recent years substantial effort has been put to characterize different FC configurations while brain states makes transitions over time. The dynamics governing this transitions and their relationship with stationary functional connectivity remains elusive. Over the last years a multitude of methods has been proposed to discover and characterize FC dynamics and one of the most accepted method is sliding window approach. Moreover, as these FC configurations are observed to be cyclically repeating in time there was further motivation to use of a generic clustering scheme to identify latent states of dynamics. We discover the underlying lower-dimensional manifold of the temporal structure which is further parameterized as a set of local density distributions, or latent transient states. We propose an innovative method that learns parameters specific to these latent states using a graph-theoretic model (temporal Multiple Kernel Learning, tMKL) and finally predicts the grand average functional connectivity (FC) of the unseen subjects by leveraging a state transition Markov model. tMKL thus learns a mapping between the underlying anatomical network and the temporal structure. Training and testing were done using the rs-fMRI data of 46 healthy participants and the results establish the viability of the proposed solution. Parameters of the model are learned via state-specific optimization formulations and yet the model performs at par or better than state-of-the-art models for predicting the grand average FC. Moreover, the model shows sensitivity towards subject-specific anatomy. The proposed model performs significantly better than the established models of predicting resting state functional connectivity based on whole-brain dynamic mean-field model, single diffusion kernel model and another version of multiple kernel learning model. In summary, We provide a novel solution that does not make strong assumption about underlying data and is generally applicable to resting or task data to learn subject specific state transitions and successful characterization of SC-dFC-FC relationship through an unifying framework.

neuroscience↗

bioRxiv2018

Structural basis for cholesterol transport-like activity of the Hedgehog receptor Patched

Hedgehog protein signals mediate tissue patterning and maintenance via binding to and inactivation of their common receptor Patched, a twelve-transmembrane protein that otherwise would suppress activity of the seven-transmembrane protein, Smoothened. Loss of Patched function, the most common cause of basal cell carcinoma, permits unregulated activation of Smoothened and of the Hedgehog pathway. A cryo-EM structure of the Patched protein reveals striking transmembrane domain similarities to prokaryotic RND transporters. The extracellular domain mediates association of Patched monomers in an unusual dimeric architecture that implies curvature in the associated membrane. A central conduit with cholesterol-like contents courses through the extracellular domain and resembles that used by other RND proteins to transport substrates, suggesting Patched activity in cholesterol transport. Patched expression indeed reduces cholesterol activity in the inner leaflet of the plasma membrane, in a manner antagonized by Hedgehog stimulation and with implications for regulation of Smoothened.

biophysics↗

bioRxiv2018

Regulation of transcription factor SP1 by β-catenin destruction complex modulates Wnt response

The ubiquitous transcription factor Specificity protein 1 (SP1) is heavily modified post-translationally. These modifications are critical for switching its functions and modulation of its transcriptional activity, DNA-binding and stability. However the mechanism governing the stability of SP1 by cellular signaling pathways is not well understood. Here, we provide biochemical and functional evidences that SP1 is an integral part of the Wnt signaling pathway. We identified a phosphodegron motif in SP1 that is specific to mammals. In absence of Wnt signaling, GSK3{beta} kinase mediated phosphorylation and {beta}-TrCP E3 ubiquitin ligase mediated ubiquitination is required to induce SP1 degradation. When Wnt signaling is on, SP1 is stabilized in {beta}-catenin-dependent manner. SP1 directly interacts with {beta}-catenin and Wnt signaling induces the stabilization of SP1 by impeding its interaction with {beta}-TrCP and AXIN1, components of the destruction complex. Wnt signaling suppresses ubiquitination and subsequent proteosomal degradation of SP1. Furthermore, SP1 regulates Wnt-dependent stability of {beta}-catenin and their mutual stabilization is critical for target gene expression, suggesting a feedback mechanism. Upon stabilization SP1 and {beta}-catenin co-occupy the promoters of TCFL2/{beta}-catenin target genes. Collectively, this study uncovers a direct link between SP1 and {beta}-catenin in Wnt signaling pathway.

molecular biology↗

bioRxiv2018

sFlt-1 commutes unfolded protein response into endoplasmic reticulum stress in trophoblast cells in preeclamptic pregnancies

Preeclampsia (PE) and its subtypes (early and late onset) are serious concerns all across the globe affecting about 8% of total pregnancies and accounts for approximately 60,000 deaths annually with a predominance in developing under-developed and countries. The two-stage model in the progression of this disease, deficient spiral artery remodelling and an imbalance between angiogenic (VEGF) and anti-antigenic factor(s) (sFlt-1) are well established facts pertaining to this disease. The presence of increased sFlt-1, high oxidative stress and Endoplasmic reticulum stress (ER stress) have been proposed in preeclamptic pregnancies. Recently, the role of endoplasmic reticulum stress in the onset of the variant forms of PE highlighted a new window to explore further. In our previous studies, we demonstrated that sFlt-1 can induce apoptosis and oxidative stress in trophoblast cells. However the role of sFlt-1, in inducing ER stress is not known so far. In the present study, we for the first time demonstrated significant ER stress in the placental cells (BeWo Cells) (in vitro) when exposed to sera from preeclamptic pregnancies having increased concentration of sFlt-1. The expression of ER stress markers (GRP78, eIF2, XBP1, ATF6 and CHOP) at both transcript and protein levels were compared (between preeclamptic and normotensive non-proteinuric women) at three different time points (8h, 14h and 24hrs), analyzed and found to be significant (p<0.05).\n\nConclusionOur results suggested that sFlt-1, released from placental cells in preeclampsia may be one of the various factors having potential to induce endoplasmic reticulum stress in BeWo cells.

developmental biology↗

bioRxiv2018

Myosin Heavy Chain-embryonic is a crucial regulator of skeletal muscle development and differentiation.

Myosin heavy chains (MyHCs) are contractile proteins that are part of the thick filaments of the functional unit of the skeletal muscle, the sarcomere. In addition to MyHCs that are part of the adult muscle contractile network, two MyHCs - MyHC-embryonic and -perinatal are expressed during muscle development and are only transiently expressed in the adult during regeneration. The functions performed by these MyHCs has been a long-standing question and using a targeted mouse allele, we have characterized the role of MyHC-embryonic. Analysis of loss-of-function mice reveals that lack of MyHC-embryonic leads to mis-regulation of other MyHCs, alterations in fiber size, fiber number and fiber type at neonatal stages. We also find that loss of MyHC-embryonic leads to mis-regulation of genes involved in muscle differentiation. A broad theme from these studies is that loss of MyHC-embryonic has distinct effects on different muscles, possibly reflecting the unique fiber type composition of different muscles. Most significantly, our results indicate that MyHC-embryonic is required during embryonic and fetal myogenesis to regulate myogenic progenitor and myoblast differentiation in a non-cell autonomous manner via Mitogen Activated Protein Kinase (MAPKinase) and Fibroblast Growth Factor (FGF) signaling. Thus, our results signify that MyHC-embryonic is a key regulator of myogenic differentiation during embryonic, fetal and neonatal myogenesis.

developmental biology↗

bioRxiv2018

A simple genetic basis for managing maternally transmitted symbionts

Maternal transmission of intracellular microbes is pivotal in establishing long-term, intimate symbioses. For germline microbes that exert negative reproductive effects on their hosts, selection can theoretically favor the spread of host genes that counteract the microbes harmful effects. Here, we leverage a major difference in bacterial (Wolbachia pipientis) titers between closely-related wasp species with forward genetic, transcriptomic, and cytological approaches to map two quantitative trait loci that suppress bacterial titers via a maternal effect. Fine mapping and knockdown experiments identify the gene Wolbachia density suppressor (Wds), which dominantly suppresses bacterial transmission from mother to embryo. Wds evolved by lineage-specific non-synonymous changes driven by positive selection. Collectively, our findings demonstrate that a genetically simple change arose by Darwinian selection in less than a million years to regulate maternally transmitted bacteria via a dominant, maternal effect gene.

evolutionary biology↗

bioRxiv2017

sFlt-1 (sVEGFR1) induces placental endoplasmic reticulum stress in trophoblast cell: implications for the complications in preeclampsia - an in vitro study

BackgroundThe concentration of sFlt-1, a major anti-angiogenic protein in maternal circulation has been seen to be raised in preeclamptic pregnancies. Endoplasmic reticulum (ER) stress represents one of the three (immunological, oxidative and ER stress) major stresses which placenta undergoes during pregnancies. The present study is designed to investigate the role of sFlt-1 in induction of ER stress in trophoblast cells.\n\nMaterials and MethodsMaternal serum levels of anti-angiogenic protein sFlt-1 and central regulator of unfolded protein response GRP78 was measured using sandwich ELISA. The expression of various ER stress markers (GRP78, eIF2, XBP1, ATF6 and apoptotic protein CHOP) were analyzed depending on various treatments given to the trophoblast cells using Immunofluorescence, western blot and q-RT PCR.\n\nResultsIncreased expression of ER stress markers (GRP78, eIF2, XBP1 ATF6 and apoptotic protein CHOP) was detected in the placental trophoblast cells treated with raised concentration of sFlt-1.\n\nConclusionSignificant upregulated expression of ER stress markers in trophoblast cells exposed with increased concentration of sFlt-1 suggested that it may be one of the anti-angiogenic factors present in maternal sera which not only contributes to oxidative stress but also may cause endoplasmic reticulum stress.

developmental biology↗

bioRxiv2017

Diminished Cortical Thickness is Associated with Impulsive Choice in Adolescence

Adolescence is characterized by both maturation of brain structure and increased risk of negative outcomes from behaviors associated with impulsive decision-making. One important index of impulsive choice is delay discounting (DD), which measures the tendency to prefer smaller rewards available soon over larger rewards delivered after a delay. However, it remains largely unknown how individual differences in structural brain development may be associated with impulsive choice during adolescence. Leveraging a unique large sample of 427 human youths (208 males and 219 females) imaged as part of the Philadelphia Neurodevelopmental Cohort, we examined associations between delay discounting and cortical thickness within structural covariance networks. These structural networks were derived using non-negative matrix factorization, an advanced multivariate technique for dimensionality reduction, and analyzed using generalized additive models with penalized splines to capture both linear and nonlinear developmental effects. We found that impulsive choice, as measured by greater discounting, was most strongly associated with diminished cortical thickness in structural brain networks that encompassed the ventromedial prefrontal cortex, orbitofrontal cortex, temporal pole, and temporoparietal junction. Furthermore, structural brain networks predicted DD above and beyond cognitive performance. Taken together, these results suggest that reduced cortical thickness in regions known to be involved in value-based decision-making is a marker of impulsive choice during the critical period of adolescence.\n\nSIGNIFICANCERisky behaviors during adolescence, such as initiation of substance use or reckless driving, are a major source of morbidity and mortality. In this study, we present evidence from a large sample of youths that diminished cortical thickness in specific structural brain networks is associated with impulsive choice. Notably, the strongest association between impulsive choice and brain structure was seen in regions implicated in value-based decision-making; namely, the ventromedial prefrontal and orbitofrontal cortices. Moving forward, such neuroanatomical markers of impulsivity may aid in the development of personalized interventions targeted to reduce risk of negative outcomes resulting from impulsivity during adolescence.

neuroscience↗

bioRxiv2017

Controllability in an islet specific regulatory network identifies the transcriptional factor NFATC4, which regulates Type 2 Diabetes associated genes

Probing the dynamic control features of biological networks represents a new frontier in capturing the dysregulated pathways in complex diseases. Here, using patient samples obtained from a pancreatic islet transplantation program, we constructed a tissue-specific gene regulatory network and used the control centrality (Cc) concept to identify the high control centrality (HiCc) pathways, which might serve as key pathobiological pathways for Type 2 Diabetes (T2D). We found that HiCc pathway genes were significantly enriched with modest GWAS p-values in the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study. We identified variants regulating gene expression (expression quantitative loci, eQTL) of HiCc pathway genes in islet samples. These eQTL genes showed higher levels of differential expression compared to non-eQTL genes in low, medium and high glucose concentrations in rat islets. Among genes with highly significant eQTL evidence, NFATC4 belonged to four HiCc pathways. We asked if the expressions of T2D-associated candidate genes from GWAS and literature are regulated by Nfatc4 in rat islets. Extensive in vitro silencing of Nfatc4 in rat islet cells displayed reduced expression of 16, and increased expression of 4 putative downstream T2D genes. Overall, our approach uncovers the mechanistic connection of NFATC4 with downstream targets including a previously unknown one, TCF7L2, and establishes the HiCc pathways relationship to T2D.

systems biology↗

bioRxiv2017

A systems approach to refine disease taxonomy by integrating phenotypic and molecular networks

The International Classification of Diseases (ICD) relies on clinical features and lags behind the current understanding of the molecular specificity of disease pathobiology, necessitating approaches that incorporate growing biomedical data for classifying diseases to meet the needs of precision medicine. Our analysis revealed that the heterogeneous molecular diversity of disease chapters and the blurred boundary between disease categories in ICD should be further investigated. Here, we propose a new classification of diseases (NCD) by developing an algorithm that predicts the additional categories of a disease by integrating multiple networks consisting of disease phenotypes and their molecular profiles. With statistical validations from phenotype-genotype associations and interactome networks, we demonstrate that NCD improves disease specificity owing to its overlapping categories and polyhierarchical structure. Furthermore, NCD captures the molecular diversity of diseases and defines clearer boundaries in terms of both phenotypic similarity and molecular associations, establishing a rational strategy to reform disease taxonomy.

bioinformatics↗

bioRxiv2017

Conserved patterns of somatic mutations in human peripheral blood cells

With growing interest in monitoring mutational processes in normal tissues, tumor heterogeneity, and cancer evolution under therapy, the ability to accurately and economically detect ultra-rare mutations is becoming increasingly important. However, this capability has often been compromised by significant sequencing, PCR and DNA preparation error rates. Here, we describe FERMI (Fast Extremely Rare Mutation Identification) - a novel method designed to eliminate majority of these sequencing and library preparation errors in order to significantly improve rare somatic mutation detection. This method leverages barcoded targeting probes to capture and sequence DNA of interest with single copy resolution. The variant calls from the barcoded sequencing data then further filtered in a position-dependent fashion against an adaptive, context-aware null model in order to distinguish true variants. As a proof of principle, we employ FERMI to probe bone marrow biopsies from leukemia patients, and show that rare mutations and clonal evolution can be tracked throughout cancer treatment, including during historically intractable periods like minimum residual disease. Importantly, FERMI is able to accurately detect nascent clonal expansions within leukemias in a manner that may facilitate the early detection and characterization of cancer relapse.

genetics↗

bioRxiv2017

Inert and seed-competent tau monomers elucidate the structural origins of aggregation

Tauopathies feature progressive accumulation of tau amyloids. Pathology may begin when these amplify from a protein template, or seed, whose structure is unknown. We have purified and characterized distinct forms of tau monomer--inert (Mi) and seed-competent (Ms). Recombinant Ms triggered intracellular tau aggregation, induced tau fibrillization in vitro, and self-assembled. Ms from Alzheimers disease also seeded aggregation and self-assembled in vitro to form seed-competent multimers. We used crosslinking with mass spectrometry to probe structural differences in Mi vs. Ms. Crosslinks informed models of local peptide structure within the repeat domain which suggest relative inaccessibility of residues that drive aggregation (VQIINK/VQIVYK) in Mi, and exposure in Ms. Limited proteolysis supported this idea. Although tau monomer has been considered to be natively unstructured, our findings belie this assumption and suggest that initiation of pathological aggregation could begin with conversion of tau monomer from an inert to a seed-competent form.

neuroscience↗

bioRxiv2017

Engagement rules that underpin DBL-DARC interactions for ingress of Plasmodium knowlesi and Plasmodium vivax into human erythrocytes

The molecular mechanisms by which P. knowlesi and P. vivax invade human red blood cells have long been studied. Malaria parasite erythrocytic stages comprise of repeated bursts of parasites via cyclical invasion of host RBCs using dedicated receptor-ligand interactions. A family of erythrocyte-binding proteins (EBPs) from P. knowlesi and P. vivax attach to human Duffy antigen receptor for chemokines (DARC) via their Duffy binding-like domains (Pv-DBL and Pk-DBL respectively) for invasion. Here, we provide a comprehensive overview that presents new insights on the atomic resolution interactions that underpin the binding of human DARC with Pk/Pv-DBLs. Based on extensive structural and biochemical data, we provide a novel, testable and overarching interaction model that rationalizes even contradictory pieces of evidence that have so far existed in the literature on Pk/Pv-DBL/DARC binding determinants. We address the conundrum of how parasite-encoded Pk/Pv-DBLs recognize human DARC via its two sulfated tyrosine residues. We collate evidence for two distinct DARC integration sites on Pk/Pv-DBLs that together likely engage the DARCs sulfated extracellular domain. These analyses are important for both malaria vaccine and inhibitor development efforts that are targeted at abrogating Pk/Pv-DBL/DARC coupling as one avenue to prevent invasion of P. vivax into human red blood cells.

microbiology↗

bioRxiv2017

The multiplex network of human diseases

Untangling the complex interplay between phenotype and genotype is crucial to the effective characterization and subtyping of diseases. Here we build and analyze the multiplex network of 779 human diseases, which consists of a genotype-based layer and a phenotype-based layer. We show that diseases with common genetic constituents tend to share symptoms, and uncover how phenotype information helps boost genotype information. Moreover, we offer a flexible classification of diseases that considers their molecular underpinnings alongside their clinical manifestations. We detect cohesive groups of diseases that have high intra-group similarity at both the molecular and the phenotypic level. Inspecting these disease classes, we demonstrate the underlying pathways that connect diseases mechanistically. We observe monogenic disorders grouped together with complex diseases for which they increase the risk factor. We propose potentially new disease associations that arise as a unique feature of the information flow within and across the two layers.

bioinformatics↗

bioRxiv2016

Binary Relation Extraction from Biomedical Literature using Dependency Trees and SVMs

The goal of Biomedical relation extraction is to uncover high-quality relations from life science literature with diverse applications in the fields of Biology and Medicine. In the last decade, several methods can be found in published literature ranging from binary to complex relation extraction. In this work, we present a binary relation extraction system that relies on sentence level dependency features. We use a novel approach to map dependency tree based rules to feature vectors that can be used to train a classifier. We build a SVM classifier using these feature vectors and our experimental results show that it outperforms simple co-occurrence and rule-based systems. Through our experiments, using two 'real-world' examples, we quantify the positive impact of improved relation extraction on Literature Based Discovery.

bioinformatics↗