Biology subjects

Weinstock, G.

Publications and source records attributed to Weinstock, G..

8 recordsLinked to original sources

bioRxiv2024

Correlation measures in metagenomic data: the blessing of dimensionality

Microbiome analysis has revolutionized our understanding of various biological processes, spanning human health, epidemiology (including antimicrobial resistance and horizontal gene transfer), as well as environmental and agricultural studies. At the heart of microbiome analysis lies the characterization of microbial communities through the quantification of microbial taxa and their dynamics. In the study of bacterial abundances, it is becoming more relevant to consider their relationship, to embed these data in the framework of network theory, allowing characterization of features like node relevance, pathway and community structure. In this study, we address the primary biases encountered in reconstructing networks through correlation measures, particularly in light of the compositional nature of the data, within-sample diversity, and the presence of a high number of unobserved species. These factors can lead to inaccurate correlation estimates. To tackle these challenges, we employ simulated data to demonstrate how many of these issues can be mitigated by applying typical transformations designed for compositional data. These transformations enable the use of straightforward measures like Pearsons correlation to correctly identify positive and negative relationships among relative abundances, especially in high-dimensional data, without having any need for further corrections. However, some challenges persist, such as addressing data sparsity, as neglecting this aspect can result in an underestimation of negative correlations.

systems biology↗

bioRxiv2023

Comprehensive analysis of network reconstruction approaches based on correlation in metagenomic data

Microbiome analysis is transforming our understanding of biological processes related to human health, epidemiology (antimicrobial resistance, horizontal gene transfer) environmental and agricultural studies. At the core of microbiome analysis is the description of microbial communities based on quantification of microbial taxa and dynamics. In the study of bacterial abundances, it is becoming more relevant to consider their relationship, to embed these data in the framework of network theory, allowing characterization of features like node relevance, pathway and community structure. In this work we characterize the principal biases in reconstructing networks from correlation measures, associated with the compositional character of relative abundance data, the diversity of abundances and the presence of unobserved species within a single sample, that might lead to wrong correlation estimates. We show how most of these problems can be overcome by applying typical transformations for compositional data, that allow the application of simple measures such as Pearsons correlation to correctly identify the positive and negative relationships between relative abundances, when data dimensionality is sufficiently high. Some issues remain, like the role of data sparsity, that if not properly addressed can lead to imbalances in correlation coefficient distribution.

systems biology↗

bioRxiv2022

The microbial community dynamics of cocaine sensitization in two behaviorally divergent strains of collaborative cross mice

The gut-brain axis is increasingly recognized as an important pathway involved in cocaine use disorder. Microbial products of the murine gut have been shown to affect striatal gene expression, and depletion of the microbiome by antibiotic treatment alters cocaine-induced behavioral sensitization in C57BL/6J male mice. Some reports suggest that cocaine-induced behavioral sensitization is correlated with drug self-administration behavior in mice. Here we profile the composition of the naive microbiome and its response to cocaine sensitization in two Collaborative Cross (CC) strains. These strains display extremely divergent behavioral responses to cocaine sensitization. A high-responding strain, CC004/TauUncJ (CC04), has a gut microbiome that contains a greater amount of Lactobacillus than the cocaine-nonresponsive strain CC041/TauUncJ (CC41). The gut microbiome of CC41 is characterized by an abundance of Eisenbergella, Robinsonella and Ruminococcus. In response to cocaine, CC04 has an increased Barnsiella population, while the gut microbiome of CC41 displays no significant changes. PICRUSt functional analysis of the functional potential of the gut microbiome in CC04 shows a significant number of potential gut-brain modules altered after exposure to cocaine, specifically those encoding for tryptophan synthesis, glutamine metabolism, and menaquinone synthesis (vitamin K2). Depletion of the microbiome by antibiotic treatment revealed an altered cocaine-sensitization response following antibiotics in female CC04 mice. Depleting the microbiome by antibiotic treatment in males revealed increased infusions for CC04 during a cocaine intravenous self-administration dose-response curve. Together these data suggest that genetic differences in cocaine-related behaviors may involve the microbiome. FUNDINGU01DA043809 to JAB, GMW P50DA039841 to EJC

animal behavior and cognition↗

bioRxiv2022

Oncogenic YAP mediates changes in chromatin accessibility and activity that drive cell cycle gene expression and cell migration

YAP, the key protein effector of the Hippo pathway, is a transcriptional co-activator that controls the expression of cell cycle genes, promotes cell growth and proliferation and regulates organ size. YAP modulates gene transcription by binding to distal enhancers, but the mechanisms of gene regulation by YAP-bound enhancers remain poorly understood. Here we show that constitute active YAP5SA leads to widespread changes in chromatin accessibility in untransformed MCF10A cells. Newly accessible regions include YAP-bound enhancers that mediate activation of cycle genes regulated by the Myb-MuvB (MMB) complex. By CRISPR-interference we identify a role for YAP-bound enhancers in phosphorylation of Pol II at Ser5 at MMB-regulated promoters, extending previously published studies that suggested YAP primarily regulates the pause-release step and transcriptional elongation. YAP5SA also leads to less accessible "closed" chromatin regions, which are not directly YAP-bound but which contain binding motifs for the p53 family of transcription factors. Diminished accessibility at these regions is, at least in part, a consequence of reduced expression and chromatin-binding of the p53 family member {Delta}Np63 resulting in downregulation of {Delta}Np63-target genes and promoting YAP-mediated cell migration. In summary, our studies uncover changes in chromatin accessibility and activity that contribute to the oncogenic activities of YAP.

molecular biology↗

bioRxiv2019

Improving characterization of understudied human microbiomes using targeted phylogenetics

Whole genome bacterial sequences are required to better understand microbial functions, niches-pecific bacterial metabolism, and disease states. Although genomic sequences are available for many of the human-associated bacteria from commonly tested body habitats (e.g. stool), as few as 13% of bacterial-derived reads from other sites such as the skin map to known bacterial genomes. To facilitate a better characterization of metagenomic shotgun reads from under-represented body sites, we collected over 10,000 bacterial isolates originating from 14 human body habitats, identified novel taxonomic groups based on full length 16S rRNA sequences, clustered the sequences to ensure that no individual taxonomic group was over-selected for sequencing, prioritized bacteria from under-represented body sites (such as skin, respiratory and urinary tract), and sequenced and assembled genomes for 665 new bacterial strains. Here we show that addition of these genomes improved read mapping rates of HMP metagenomic samples by nearly 30% for the previously under-represented phylum Fusobacteria, and 27.5% of the novel genomes generated here had high representation in at least one of the tested HMP samples, compared to 12.5% of the sequences in the public databases, indicating an enrichment of useful novel genomic sequences resulting from the prioritization procedure. As our understanding of the human microbiome continues to improve and to enter the realm of therapy developments, targeted approaches such as this to improve genomic databases will increase in importance from both an academic and clinical perspective. ImportanceThe human microbiome plays a critically important role in health and disease, but current understanding of the mechanisms underlying the interactions between the varying microbiome and the different host environments is lacking. Having access to a database of fully sequenced bacterial genomes provides invaluable insights into microbial functions, but currently sequenced genomes for the human microbiome have largely come from a limited number of body sites (primarily stool), while other sites such as the skin, respiratory tract and urinary tracts are under-represented, resulting in as little as 13% of bacterial-derived reads mapping to known bacterial genomes. Here, we sequenced and assembled 665 new bacterial genomes, prioritized from a larger database to select under-represented body sites and bacterial taxa in the existing databases. As a result, we substantially improve mapping rates for samples from the Human Microbiome Project and provide an important contribution to human bacterial genomic databases for future studies.

microbiology↗

bioRxiv2019

Approaches for integrating heterogeneous RNA-seq data reveals cross-talk between microbes and genes in asthmatic patients

Sputum induction is a non-invasive method to evaluate the airway environment, particularly for asthma. RNA sequencing (RNAseq) can be used on sputum, but it can be challenging to interpret because sputum contains a complex and heterogeneous mixture of human cells and exogenous (microbial) material. In this study, we developed a methodology that integrates dimensionality reduction and statistical modeling to grapple with the heterogeneity. We use this to relate bulk RNAseq data from 115 asthmatic patients with clinical information, microscope images, and single-cell profiles. First, we mapped sputum RNAseq to human and exogenous sources. Next, we decomposed the human reads into cell-expression signatures and fractions of these in each sample; we validated the decomposition using targeted single-cell RNAseq and microscopy. We observed enrichment of immune-system cells (neutrophils, eosinophils, and mast cells) in severe asthmatics. Second, we inferred microbial abundances from the exogenous reads and then associated these with clinical variables -- e.g., Haemophilus was associated with increased white blood cell count and Candida, with worse lung function. Third, we applied a generative model, Latent Dirichlet allocation (LDA), to identify patterns of gene expression and microbial abundances and relate them to clinical data. Based on this, we developed a method called LDA-link that connects microbes to genes using reduced-dimensionality LDA topics. We found a number of known connections, e.g. between Haemophilus and the gene IL1B, which is highly expressed by mast cells. In addition, we identified novel connections, including Candida and the calcium-signaling gene CACNA1E, which is highly expressed by eosinophils. These results speak to the mechanism by which gene-microbe interactions contribute to asthma and define a strategy for making inferences in heterogeneous and noisy RNAseq datasets.

genomics↗

bioRxiv2018

Systems genetic discovery of host-microbiome interactions reveals mechanisms of microbial involvement in disease

The role of the microbiome in health and disease involves complex networks of host genetics, genomics, microbes and environment. Identifying the mechanisms of these interactions has remained challenging. Systems genetics in the laboratory mouse enables data-driven discovery of network components and mechanisms of host-microbial interactions underlying multiple disease phenotypes. To examine the interplay among the whole host genome, transcriptome and microbiome, we mapped quantitative trait loci and correlated the abundance of cecal mRNA, luminal microflora, physiology and behavior in incipient strains of the highly diverse Collaborative Cross mouse population. The relationships that are extracted can be tested experimentally to ascribe causality among host and microbe in behavior and physiology, providing insight into disease. Application of this strategy in the Collaborative Cross population revealed experimentally validated mechanisms of microbial involvement in models of autism, inflammatory bowel disease and sleep disorder.\n\neTOC BlurbHost genetic diversity provides a variable selection environment and physiological context for microbiota and their interaction with host physiology. Using a highly diverse mouse population Bubier et al. identified a variety of host, microbe and potentially disease interactions.\n\nHighlights* 18 significant species-specific QTL regulating microbial abundance were identified\n* Cis and trans eQTL for 1,600 cecal transcripts were mapped in the Collaborative Cross\n* Sleep phenotypes were highly correlated with the abundance of B.P. Odoribacter\n* Elimination of sleep-associated microbes restored normal sleep patterns in mice.

genetics↗

bioRxiv2016

Ancient hybridization and strong adaptation to viruses across African vervet monkey populations

Vervet monkeys (genus Chlorocebus, also known as African green monkeys), are highly abundant in savannahs and riverine forests throughout sub-Saharan Africa. They are amongst the most widely distributed nonhuman primates, show considerable phenotypic diversity, and have long been an important biomedical model for a variety of human diseases1 and in vaccine research2-4. They are particularly interesting for HIV/AIDS research as they are the most abundant natural hosts of simian immunodeficiency virus (SIV), a close relative of HIV. Here we present the first genome-wide survey of polymorphism in vervets, using sequencing data from 163 individuals sampled from across Africa and the Caribbean islands where vervets were introduced during the colonial era. We find high diversity, within and between taxa, and clear evidence that taxonomic divergence was reticulate rather than following a simple branching pattern. A scan for diversifying selection across vervet taxa yields gene enrichments much stronger than in similar studies on humans5. In particular, we report strong and highly polygenic selection signals affecting viral processes -- in line with recent evidence that proposes a driving role for viruses in protein evolution in mammals6. Furthermore, selection scores are highly elevated in genes whose human orthologs interact with HIV, and in genes that show a response to experimental SIV infection in vervet monkeys but not in rhesus macaques, suggesting that part of the signal reflects taxon-specific adaptation to SIV. Intriguingly, rather than affecting genes with antiviral and inflammatory-related functions7, selection in vervets appears to have primarily targeted genes involved in the transcriptional regulation of viruses, and in particular those that are harmful only under immunodeficiency, suggesting adaptation to living with SIV rather than defense against infection.

evolutionary biology↗