Biology subjects

Levy, S.

Publications and source records attributed to Levy, S..

36 records · Page 2Linked to original sources

bioRxiv2021

Exploration and analysis of R-loop mapping data with RLBase

R-loops are three-stranded nucleic acid structures formed from the hybridization of RNA and DNA during nascent transcription. In 2012, Ginno et al. introduced the first R-loop mapping method, DNA:RNA immunoprecipitation (DRIP) sequencing. Since that time, dozens of studies have implemented R-loop mapping and new high-resolution techniques have been developed. The resulting datasets have tremendous potential to reveal the causes and consequences of R-loops genome-wide. However, poor quality and variability between mapping approaches pose serious barriers to the meta-analysis of these data. In our recent work, we reprocessed 693 R-loop mapping samples, devising new quality methods, defining a set of high-confidence mapping samples, and then deriving R-loop regions, consensus sites of R-loop formation. This analysis yielded the largest R-loop data resource to date along with novel computational approaches for R-loop mapping analysis. Now, we introduce RLBase, an innovative web server which builds upon those data and software by providing users with the capability to (1) explore hundreds of public R-loop mapping datasets, (2) explore consensus R-loop regions, (3) analyze user-supplied datasets to generate an HTML quality report, and (4) download all the processed data for the 693 samples we previously reprocessed and standardized. In addition to RLBase, we also describe the other software which, along with RLBase, provides a computational framework for R-loop bioinformatics. RLBase, and the rest of these software (termed "RLSuite"), are provided freely under an MIT license and made publicly available: https://gccri.bishop-lab.uthscsa.edu/rlsuite/. RLBase is directly accessible via the following URL: https://gccri.bishop-lab.uthscsa.edu/rlbase/.

bioinformatics↗

bioRxiv2021

Betacoronavirus-specific alternate splicing

Viruses can subvert a number of cellular processes in order to block innate antiviral responses, and many viruses interact with cellular splicing machinery. SARS-CoV-2 infection was shown to suppress global mRNA splicing, and at least 10 SARS-CoV-2 proteins bind specifically to one or more human RNAs. Here, we investigate 17 published experimental and clinical datasets related to SARS-CoV-2 infection as well as datasets from the betacoronaviruses SARS-CoV and MERS as well as Streptococcus pneumonia, HCV, Zika virus, Dengue virus, influenza H3N2, and RSV. We show that genes showing differential alternative splicing in SARS-CoV-2 have a similar functional profile to those of SARS-CoV and MERS and affect a diverse set of genes and biological functions, including many closely related to virus biology. Additionally, the differentially spliced transcripts of cells infected by coronaviruses were more likely to undergo intron-retention, contain a pseudouridine modification and a smaller number of exons than differentially spliced transcripts in the control groups. Viral load in clinical COVID-19 samples was correlated with isoform distribution of differentially spliced genes. A significantly higher number of ribosomal genes are affected by DAS and DGE in betacoronavirus samples, and the betacoronavirus differentially spliced genes are depleted for binding sites of RNA-binding proteins. Our results demonstrate characteristic patterns of differential splicing in cells infected by SARS-CoV-2, SARS-CoV, and MERS, potentially modifying a broad range of cellular functions and affecting a diverse set of genes and biological functions.

genomics↗

bioRxiv2021

The calcifying interface in a stony coral's primary polyp: An interplay between seawater and an extracellular calcifying space

Stony coral exoskeletons build the foundation to the most biologically diverse yet fragile marine ecosystems on earth, coral reefs. Understanding corals biomineralization mechanisms is therefore crucial for coral reef management and for using coral skeletons in geochemical studies. In this study, we combine in-vivo and cryo-electron microscopy with single-cell RNA-seq data to gain novel insights into the calcifying micro-environment that facilitates biomineralization in primary polyps of the stony coral Stylophora pistillata. We show an intimate involvement of seawater in this micro-environment. We further document increased tissue permeability and a highly dispersed cell packing in the tissue secreting the coral skeleton (i.e. calicoblastic). We also observe an extensive filopodial network containing carbon-rich vesicles extruding from some of the calicoblastic cells. Single-cell RNA-Seq data interrogation shows that calicoblastic cells express genes involved in filopodia and vesicle structure and function. These observations provide a new conceptual framework for resolving stony corals biomineralization processes.

developmental biology↗

bioRxiv2021

Systemic Tissue and Cellular Disruption from SARS-CoV-2 Infection revealed in COVID-19 Autopsies and Spatial Omics Tissue Maps

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) virus has infected over 115 million people and caused over 2.5 million deaths worldwide. Yet, the molecular mechanisms underlying the clinical manifestations of COVID-19, as well as what distinguishes them from common seasonal influenza virus and other lung injury states such as Acute Respiratory Distress Syndrome (ARDS), remains poorly understood. To address these challenges, we combined transcriptional profiling of 646 clinical nasopharyngeal swabs and 39 patient autopsy tissues, matched with spatial protein and expression profiling (GeoMx) across 357 tissue sections. These results define both body-wide and tissue-specific (heart, liver, lung, kidney, and lymph nodes) damage wrought by the SARS-CoV-2 infection, evident as a function of varying viral load (high vs. low) during the course of infection and specific, transcriptional dysregulation in splicing isoforms, T cell receptor expression, and cellular expression states. In particular, cardiac and lung tissues revealed the largest degree of splicing isoform switching and cell expression state loss. Overall, these findings reveal a systemic disruption of cellular and transcriptional pathways from COVID-19 across all tissues, which can inform subsequent studies to combat the mortality of COVID-19, as well to better understand the molecular dynamics of lethal SARS-CoV-2 infection and other viruses.

microbiology↗

bioRxiv2020

Computer Designed PRC2 Inhibitor, EBdCas9, Reveals Functional TATA boxes in Distal Promoter Regions

The critical process in development, bifurcation of cellular fates, requires epigenetic H3K27me3 marks propagated by PRC2 complex. However, the precise chromatin loci of functional H3K27me3 marks are not yet known. Here we identify critical PRC2 functional sites at a single nucleosome resolution. We fused a computationally designed protein, EED binder (EB) that competes with EZH2 and thereby disrupts PRC2 function, to dCas9 (EBdCas9) to direct PRC2 inhibition at a precise locus using gRNA. We targeted EBdCas9 to 4 different genes (TBX18, p16, CDX2 and GATA3) and observed epigenetic remodeling at a single nucleosome resolution resulting in gene activation. Remarkably, while traditional TATA box is located 30bp upstream of TSS, we identified a functional TATA box, >500bp of TSS, normally repressed by PRC2 complex. Deletion of this TATA box eliminates EBdCas9 dependent TBP recruitment and transcriptional activation. Targeting EBdCas9 to CDX2 and GATA3 results in trophoblast trans-differentiation. EBdCas9 technology is broadly applicable for epigenetic regulation at a single locus to control gene expression. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=189 SRC="FIGDIR/small/385922v1_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@1da108borg.highwire.dtl.DTLVardef@17447ddorg.highwire.dtl.DTLVardef@11a188forg.highwire.dtl.DTLVardef@426022_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2020

Coordinated interactions between endothelial cells and macrophages in the islet microenvironment promote beta cell regeneration

Endogenous {beta} cell regeneration could alleviate diabetes, but proliferative stimuli within the islet microenvironment are incompletely understood. We previously found that {beta} cell recovery following hypervascularization-induced {beta} cell loss involves interactions with endothelial cells (ECs) and macrophages (M{Phi}s). Here we show that proliferative ECs modulate M{Phi} infiltration and phenotype during {beta} cell loss, and recruited M{Phi}s are essential for {beta} cell recovery. Furthermore, VEGFR2 inactivation in quiescent ECs accelerates islet vascular regression during {beta} cell recovery and leads to increased {beta} cell proliferation without changes in M{Phi} phenotype or number. Transcriptome analysis of {beta} cells, ECs, and M{Phi}s reveals that {beta} cell proliferation coincides with elevated expression of extracellular matrix remodeling molecules and growth factors likely driving activation of proliferative signaling pathways in {beta} cells. Collectively, these findings suggest a new {beta} cell regeneration paradigm whereby coordinated interactions between intra-islet M{Phi}s, ECs, and extracellular matrix mediate {beta} cell self-renewal.

cell biology↗

bioRxiv2020

Multi-Platform Assessment of DNA Sequencing Performance using Human and Bacterial Reference Genomes in the ABRF Next-Generation Sequencing Study

Massively parallel DNA sequencing is a critical tool for genomics research and clinical diagnostics. Here, we describe the Association of Biomolecular Resource Facilities (ABRF) Next-Generation Sequencing Phase II Study to measure quality and reproducibility of DNA sequencing. Replicates of human and bacterial reference DNA samples were generated across multiple sequencing platforms, including well-established technologies such as Illumina, ThermoFisher Ion Torrent, and Pacific Biosciences, as well as emerging technologies such as BGI, Genapsys, and Oxford Nanopore. A total of 202 datasets were generated to investigate the performance of a total of 16 sequencing platforms, including mappability of reads, coverage and error rates in difficult genomic regions, and detection of small-scale polymorphisms and large-scale structural variants. This study provides a comprehensive baseline resource for continual benchmarking as chemistries, methods, and platforms evolve for DNA sequencing.

genomics↗

bioRxiv2020

A large accessory protein interactome is rewired across environments

To characterize how protein-protein interaction (PPI) networks change, we quantified the relative PPI abundance of 1.6 million protein pairs in yeast across 9 growth conditions, with replication, for a total of 44 million measurements. Our multi-condition screen identified 13,764 pairwise PPIs, a 3-fold increase over PPIs identified in one condition. A few "immutable" PPIs are present across all conditions, while most "mutable" PPIs are rarely observed. Immutable PPIs aggregate into highly connected "core" network modules, with most network remodeling occurring within a loosely connected "accessory" module. Mutable PPIs are less likely to co-express, co-localize, and be explained by simple mass action kinetics, and more likely to contain proteins with intrinsically disordered regions, implying that environment-dependent association and binding is critical to cellular adaptation. Our results show that protein interactomes are larger than previously thought and contain highly dynamic regions that reorganize to drive or respond to cellular changes.

systems biology↗

bioRxiv2020

Host, Viral, and Environmental Transcriptome Profiles of the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)

The Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused thousands of deaths worldwide, including >18,000 in New York City (NYC) alone. The sudden emergence of this pandemic has highlighted a pressing clinical need for rapid, scalable diagnostics that can detect infection, interrogate strain evolution, and identify novel patient biomarkers. To address these challenges, we designed a fast (30-minute) colorimetric test (LAMP) for SARS-CoV-2 infection from naso/oropharyngeal swabs, plus a large-scale shotgun metatranscriptomics platform (total-RNA-seq) for host, bacterial, and viral profiling. We applied both technologies across 857 SARS-CoV-2 clinical specimens and 86 NYC subway samples, providing a broad molecular portrait of the COVID-19 NYC outbreak. Our results define new features of SARS-CoV-2 evolution, nominate a novel, NYC-enriched viral subclade, reveal specific host responses in interferon, ACE, hematological, and olfaction pathways, and examine risks associated with use of ACE inhibitors and angiotensin receptor blockers. Together, these findings have immediate applications to SARS-CoV-2 diagnostics, public health, and new therapeutic targets.

molecular biology↗

bioRxiv2020

Genetic determinants of EGFR-Driven Lung Cancer Growth and Therapeutic Response In Vivo

Cancer genome sequencing has uncovered substantial complexity in the mutational landscape of tumors. Given this complexity, experimental approaches are necessary to establish the impact of combinations of genetic alterations on tumor biology and to uncover genotype-dependent effects on drug sensitivity. In lung adenocarcinoma, EGFR mutations co-occur with many putative tumor suppressor gene alterations, however the extent to which these alterations contribute to tumor growth and their response to therapy in vivo has not been explored experimentally. By integrating a novel mouse model of oncogenic EGFR-driven Trp53-deficient lung adenocarcinoma with multiplexed CRISPR-Cas9-mediated genome editing and tumor barcode sequencing, we quantified the effects of inactivation of ten putative tumor suppressor genes. Inactivation of Apc, Rb1, or Rbm10 most strongly promoted tumor growth. Unexpectedly, inactivation of Lkb1 or Setd2 - which are the strongest drivers of tumor growth in an oncogenic Kras-driven model - reduced EGFR-driven tumor growth. These results are consistent with the relative frequency of these tumor suppressor gene alterations in human EGFR- and KRAS-driven lung adenocarcinomas. Furthermore, Keap1 inactivation reduces the sensitivity of EGFR-driven Trp53-deficient tumors to the EGFR inhibitor osimertinib. Importantly, in human EGFR/TP53 mutant lung adenocarcinomas, mutations in the KEAP1 pathway correlated with decreased time on tyrosine kinase inhibitor treatment. Our study highlights how genetic alterations can have dramatically different biological consequences depending on the oncogenic context and that the fitness landscape can shift upon drug treatment.

cancer biology↗

bioRxiv2020

The murine Microenvironment Cell Population counter method to estimate abundance of tissue-infiltrating immune and stromal cell populations in murine samples using gene expression

Quantifying tissue-infiltrating immune and stromal cells provides clinically relevant information for various diseases, notably cancer. While numerous methods allow to quantify immune or stromal cells in human tissue samples based on transcriptomic data, very few are available for mouse studies. Here, we introduce murine Microenvironment Cell Population counter (mMCP-counter), a method based on highly specific transcriptomic markers that allow to accurately quantify 12 immune and 4 stromal murine cell populations. We validated mMCP-counter with flow cytometry data. We also showed that mMCP-counter outperforms existing methods. We showed in mouse models of mesothelioma and kidney cancer that mMCP-counter quantification scores are predictive of response to immune checkpoint blockade Finally, we illustrated mMCP-counters potential to analyze immune impacts of Alzheimers disease. mMCP-counter is available as an R package from GitHub: https://github.com/cit-bioinfo/mMCP-counter.

bioinformatics↗

bioRxiv2020

Cell-type specific outcome representation in primary motor cortex

Adaptive movements are critical to animal survival. To guide future actions, the brain monitors different outcomes, including achievement of movement and appetitive goals. The nature of outcome signals and their neuronal and network realization in motor cortex (M1), which commands the performance of skilled movements, is largely unknown. Using a dexterity task, calcium imaging, optogenetic perturbations, and behavioral manipulations, we studied outcome signals in murine M1. We find two populations of layer 2-3 neurons, "success"- and "failure" related neurons that develop with training and report end-result of trials. In these neurons, prolonged responses were recorded after success or failure trials, independent of reward and kinematics. In contrast, the initial state of layer-5 pyramidal tract neurons contains a memory trace of the previous trials outcome. Inter-trial cortical activity was needed to learn new task requirements. These M1 reflective layer-specific performance outcome signals, can support reinforcement motor learning of skilled behavior.

neuroscience↗

bioRxiv2019

Signaling via GABAB receptors regulates early development and neurogenesis in the basal metazoan Nematostella vectensis

The metabotropic gamma-amino-butyric acid B receptor (GABABR) is a G protein-coupled receptor that mediates neuronal inhibition by the neurotransmitter GABA. Here, we identified putative GABAB receptors and signaling modulators in the basal sea anemone Nematostella vectensis. Activation of GABABR signaling reversibly arrests planula-to-polyp transformation during early development and affects the neurogenic program. We identified four Nematostella GABABR homologs that have the conserved 3D extracellular domains and residues needed for binding of GABA and the GABABR agonist baclofen. Transcriptomic analysis, combined with spatial analysis of baclofen-treated planulae, revealed that baclofen down-regulated pro-neural factors such as NvSoxB(2), NvNeuroD1 and NvElav1. Baclofen also inhibited neuron development and extended neurites, resulting in an under-developed and less organized nervous system. Our results shed light on cnidarian development and suggest an evolutionarily conserved function for GABABR in regulation of neurogenesis, highlighting Nematostella as a new model system to study GABABR signaling.

molecular biology↗

bioRxiv2018

Detection of early stage pancreatic cancer using 5-hydroxymethylcytosine signatures in circulating cell free DNA

Pancreatic cancers are typically diagnosed at late stage where disease prognosis is poor as exemplified by a 5-year survival rate of 8.2%. Earlier diagnosis would be beneficial by enabling surgical resection or earlier application of therapeutic regimens. We investigated the detection of pancreatic ductal adenocarcinoma (PDAC) in a non-invasive manner by interrogating changes in 5-hydroxymethylation cytosine status (5hmC) of circulating cell free DNA in the plasma of a PDAC cohort (n=51) in comparison with a non-cancer cohort (n=41). We found that 5hmC sites are enriched in a disease and stage specific manner in exons, 3UTRs and transcription termination sites. Our data show that 5hmC density is reduced in promoters and histone H3K4me3-associated sites with progressive disease suggesting increased transcriptional activity. 5hmC density is differentially represented in thousands of genes, and a stringently filtered set of the most significant genes points to biology related to pancreas (GATA4, GATA6, PROX1, ONECUT1) and/or cancer development (YAP1, TEAD1, PROX1, ONECUT1, ONECUT2, IGF1 and IGF2). Regularized regression models were built using 5hmC densities in statistically filtered genes or a comprehensive set of highly variable 5hmC counts in genes and performed with an AUC = 0.94-0.96 on training data. We were able to test the ability to classify PDAC and non-cancer samples with the Elastic net and Lasso models on two external pancreatic cancer 5hmC data sets and found validation performance to be AUC = 0.74-0.97. The findings suggest that 5hmC changes enable classification of PDAC patients with high fidelity and are worthy of further investigation on larger cohorts of patient samples.

cancer biology↗

bioRxiv2018

Single-cell copy number variant detection reveals the dynamics and diversity of adaptation

Copy number variants (CNVs) are a pervasive, but understudied source of genetic variation and evolutionary potential. Long-term evolution experiments in chemostats provide an ideal system for studying the molecular processes underlying CNV formation and the temporal dynamics of de novo CNVs. Here, we developed a fluorescent reporter to monitor gene amplifications and deletions at a specific locus with single-cell resolution. Using a CNV reporter in nitrogen-limited chemostats, we find that GAP1 CNVs are repeatedly generated and selected during the early stages of adaptive evolution resulting in predictable dynamics of CNV selection. However, subsequent diversification of populations defines a second phase of evolutionary dynamics that cannot be predicted. Using whole genome sequencing, we identified a variety of GAP1 CNVs that vary in size and copy number. Despite GAP1s proximity to tandem repeats that facilitate intrachromosomal recombination, we find that non-allelic homologous recombination (NAHR) between flanking tandem repeats occurs infrequently. Rather, breakpoint characterization revealed that for at least 50% of GAP1 CNVs, origin-dependent inverted-repeat amplification (ODIRA), a DNA replication mediated process, is the likely mechanism. We also find evidence that ODIRA generates DUR3 CNVs, indicating that it may be a common mechanism of gene amplification. We combined the CNV reporter with barcode lineage tracking and found that 103-104 independent CNV-containing lineages initially compete within populations, which results in extreme clonal interference. Our study introduces a novel means of studying CNVs in heterogeneous cell populations and provides insight into the underlying dynamics of CNVs in evolution.

evolutionary biology↗

bioRxiv2018

Tumor regression mediated by oncogene withdrawal or erlotinib stimulates infiltration ofinflammatory immune cells in EGFR mutant lung tumors

Epidermal Growth Factor Receptor (EGFR) tyrosine kinase inhibitors (TKIs) like erlotinib are effective for treating patients with EGFR mutant lung cancer; however, drug resistance inevitably emerges. Approaches to combine immunotherapies and targeted therapies to overcome or delay drug resistance have been hindered by limited knowledge of the effect of erlotinib on tumor-infiltrating immune cells. Using mouse models, we studied the immunological profile of mutant EGFR-driven lung tumors before and after erlotinib treatment. We found that erlotinib triggered the recruitment of inflammatory T cells into the lungs. Interestingly, this phenotype could be recapitulated by tumor regression mediated by deprivation of the EGFR oncogene indicating that tumor regression alone was sufficient for these immunostimulatory effects. Erlotinib treatment also led to increased maturation of myeloid cells and an increase in CD40+ dendritic cells. Our findings lay the foundation for understanding the effects of TKIs on the tumor microenvironment and highlights potential avenues for investigation of targeted and immuno-therapy combination strategies to treat EGFR mutant lung cancer.

cancer biology↗

bioRxiv2017

Comprehensive Benchmarking and Ensemble Approaches for Metagenomic Classifiers

BackgroundOne of the main challenges in metagenomics is the identification of microorganisms in clinical and environmental samples. While an extensive and heterogeneous set of computational tools is available to classify microorganisms using whole genome shotgun sequencing data, comprehensive comparisons of these methods are limited. In this study, we use the largest (n=35) to date set of laboratory-generated and simulated controls across 846 species to evaluate the performance of eleven metagenomics classifiers. We also assess the effects of filtering and combining tools to reduce the number of false positives.\n\nResultsTools were characterized on the basis of their ability to (1) identify taxa at the genus, species, and strain levels, (2) quantify relative abundance measures of taxa, and (3) classify individual reads to the species level. Strikingly, the number of species identified by the eleven tools can differ by over three orders of magnitude on the same datasets. However, various strategies can ameliorate taxonomic misclassification, including abundance filtering, ensemble approaches, and tool intersection. Indeed, leveraging tools with different heuristics is beneficial for improved precision. Nevertheless, these strategies were often insufficient to completely eliminate false positives from environmental samples, which are especially important where they concern medically relevant species and where customized tools may be required.\n\nConclusionsThe results of this study provide positive controls, titrated standards, and a guide for selecting tools for metagenomic analyses by comparing ranges of precision and recall. We show that proper experimental design and analysis parameters, including depth of sequencing, choice of classifier or classifiers, database size, and filtering, can reduce false positives, provide greater resolution of species in complex metagenomic samples, and improve the interpretation of results.

genomics↗

bioRxiv2017

Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans

A detailed understanding of the genome-wide variability of single-nucleotide germline mutation rates is essential to studying human genome evolution. Here we use [~]36 million singleton variants from 3,560 whole-genome sequences to infer fine-scale patterns of mutation rate heterogeneity. Mutability is jointly affected by adjacent nucleotide context and diverse genomic features of the surrounding region, including histone modifications, replication timing, and recombination rate, sometimes suggesting specific mutagenic mechanisms. Remarkably, GC content, DNase hypersensitivity, CpG islands, and H3K36 trimethylation are associated with both increased and decreased mutation rates depending on nucleotide context. We validate these estimated effects in an independent dataset of [~]46,000 de novo mutations, and confirm our estimates are more accurate than previously published estimates based on ancestrally older variants without considering genomic features. Our results thus provide the most refined portrait to date of the factors contributing to genome-wide variability of the human germline mutation rate.

genomics↗