Biology subjects

Taur, Y.

Publications and source records attributed to Taur, Y..

6 recordsLinked to original sources

bioRxiv2022

The TaxUMAP atlas: efficient display of large clinical microbiome data reveals ecological competition involved in protection against bacteremia

The microbiome is associated with health and disease, but causal effects are hard to quantify-- especially in humans where controlled experiments are nearly impossible. Akin to natural experiments, closely monitored patients offer an alternative to characterize microbiome effects. We present TaxUMAP, a taxonomically-informed visualization method to effectively display diverse microbiome states. TaxUMAP charts a microbiome atlas from 1,870 cancer patients as they progress through therapy-induced perturbations, and quantifies the microbiome contribution to patients risk for life-threatening bacteremia. We find that the lowest diversity states (gut dominations) that follow antibiotic treatments are stable, and that diverse communities harbor more diverse antimicrobial resistance genes than dominations. We reveal that certain Klebsiella species are associated with reduced risk for bacteremia, an effect driven by bacterial competition that we validate experimentally in vitro and in vivo. TaxUMAP effectively maps longitudinal microbiome data that can facilitate research into causal microbiome effects on human health. HIGHLIGHTSO_LITaxUMAP charts an atlas of patients microbiome states and their clinical context to reveal new causal effects. C_LIO_LIAntibiotics deplete the biodiversity and reduce the number of different antimicrobial resistance genes in the gut microbiome. C_LIO_LICertain Klebsiella species are associated with lower risk of bacteremia by other gut-borne pathogens. C_LIO_LIThese Klebsiella outcompete other gram-negative pathogens in vivo. C_LI

microbiology↗

bioRxiv2021

A compilation of fecal microbiome shotgun metagenomics from hospitalized patients undergoing hematopoietic cell transplantation

Hospitalized patients receiving hematopoietic cell transplants provide a unique opportunity to study how the human gut microbiome changes in response to perturbations, and how the resulting changes in the microbiome feedback on its living host. We previously compiled a large-scale longitudinal dataset of stool microbiome compositions from these patients and associated metadata1. In that dataset the microbiome analysis was limited to the taxonomic composition of the bacterial population obtained from 16S rRNA gene sequencing. Here, we augment those data with shotgun metagenomic sequences from a nested subset of 395 stool samples. We provide accession numbers that link each sample to the paired-end sequencing files deposited in a public repository, which can be directly accessed by the online services of PATRIC2 to be analyzed without the users having to download or transfer the files. We provide examples that show how shotgun sequencing enriches microbiome analyses beyond the taxonomic composition such as the analysis of gene functions including virulence factors and antibiotic resistances, and the assembly of genomes from metagenomic data.

systems biology↗

bioRxiv2021

Customization of a dada2-based pipeline for fungal Internal Transcribed Spacer 1 (ITS 1) amplicon datasets

Identification and analysis of fungal communities commonly rely on internal transcribed spacer (ITS)-based amplicon sequencing. Currently, there is no gold standard to infer and classify fungal constituents, in part since methodologies have been adapted from analyses of bacterial communities. To achieve high resolution inference of fungi in clinical samples, we customized a DADA2-based pipeline using a mock community of eleven medically relevant fungi. While DADA2 allowed the discrimination of ITS1 sequences differing by a single nucleotide, quality filtering, sequencing bias, and database selection were identified as key variables determining the accuracy of sample inference. By fine-tuning quality filtering, we decreased the number of wrongly discarded sequences attributed to Aspergillus species, Saccharomyces cerevisiae, and Candida glabrata reads. We confirmed this effect in patient samples. By adapting a wobble nucleotide in the ITS1 forward primer region, we further increased the yield of S. saccharomyces and C. glabrata sequences. Finally, we showed that a BLAST-based algorithm based on the UNITE+INSD or the NCBI NT database achieved a higher reliability in species-level taxonomic annotation than the naive Bayesian classifier implemented in DADA2. These steps optimized a robust fungal ITS1 sequencing pipeline that, in most instances, enables species level-assignment of community members.

bioinformatics↗

bioRxiv2021

Candida albicans Isolates 529L and CHN1 Exhibit Stable Colonization of the Murine Gastrointestinal Tract

Candida albicans is a pathobiont that colonizes multiple niches in the body including the gastrointestinal (GI) tract, but is also responsible for both mucosal and systemic infections. Despite its prevalence as a human commensal, the murine GI tract is generally refractory to colonization with the C. albicans reference isolate SC5314. Here, we identify two C. albicans isolates, 529L and CHN1, that stably colonize the murine GI tract in three different animal facilities under conditions where SC5314 is lost from this niche. Analysis of the bacterial microbiota did not show notable differences between mice colonized with the three C. albicans strains. We compared the genotypes and phenotypes of these three strains and identified thousands of SNPs and multiple phenotypic differences, including their ability to grow and filament in response to nutritional cues. Despite striking filamentation differences under laboratory conditions, however, analysis of cell morphology in the GI tract revealed that the three isolates exhibited similar filamentation properties in this in vivo niche. Notably, we found that SC5314 is more sensitive to the antimicrobial peptide CRAMP, and the use of CRAMP-deficient mice increased the ability of SC5314 to colonize the GI tract relative to CHN1 and 529L. These studies provide new insights into how strain-specific differences impact C. albicans traits in the host and advance CHN1 and 529L as relevant strains to study C. albicans pathobiology in its natural host niche. IMPORTANCEUnderstanding how fungi colonize the GI tract is increasingly recognized as highly relevant to human health. The animal models used to study Candida albicans commensalism commonly rely on altering the host microbiome (via antibiotic treatment or defined diets) to establish successful GI colonization by the C. albicans reference isolate SC5314. Here, we characterize two C. albicans isolates that can colonize the murine GI tract without antibiotic treatment and can therefore be used as tools for studying fungal commensalism. Importantly, experiments were replicated in three different animal facilities and utilized three different mouse strains. Differential colonization between fungal isolates was not associated with alterations in the bacterial microbiome but rather with distinct responses to CRAMP, a host antimicrobial peptide. This work emphasizes the importance of C. albicans intra-species variation as well as host anti-microbial defense mechanisms in defining commensal interactions.

microbiology↗

bioRxiv2019

The gut microbiota influences circulatory immune cell dynamics in humans

The gut microbiota influences development and homeostasis of the mammalian immune system1-3, can alter immune cell compositions in mice4-7, and is associated with responses to immunotherapy that rely on the activity of peripheral immune cells8-12. Still, our understanding of how the microbiota modulates immune cells dynamics remains limited, particularly in humans where a lack of deliberate manipulations makes inference challenging. Here we study hundreds of hospitalized--and closely monitored--patients receiving hematopoietic cell transplantation as they recover from chemotherapy and stem cell engraftment. This aggressive treatment causes large shifts in both circulatory immune cell and microbiota populations, allowing the relationships between the two to be studied simultaneously. We analyzed daily changes in white blood cells from 2,235 patients, and 10,680 longitudinal microbiota samples to identify bacteria associated with those changes. Bayesian inference and validation across patient cohorts revealed consistent associations between gut bacteria and white blood cell dynamics in the context of immunomodulatory medications, clinical metadata and homeostatic feedbacks. We contrasted the potency of fermentatively active, obligate anaerobic bacteria with that of medications with known immunomodulatory mechanism to estimate the potential of the microbiota to influence peripheral immune cell dynamics. Our analysis establishes and quantifies the link between the gut microbiota and the human immune system, with implications for microbiota-driven modulation of immunity.

microbiology↗

bioRxiv2019

Antibiotic-induced shifts in fecal microbiota density and composition during hematopoietic stem cell transplantation

BackgroundDramatic microbiota changes and loss of commensal anaerobic bacteria are associated with adverse outcomes in hematopoietic cell transplantation (HCT) recipients. In this study, we demonstrate these dynamic changes at high-resolution through daily stool sampling and assess the impact of individual antibiotics on those changes.\n\nMethodsWe collected 272 longitudinal stool samples (with mostly daily frequency) from 18 patients undergoing HCT and determined their composition by multi-parallel 16S rRNA gene sequencing, as well as density of bacteria in stool by qPCR. We calculated microbiota volatility to quantify rapid shifts and developed a new dynamic systems inference method to assess the specific impact of antibiotics.\n\nResultsThe greatest shifts in microbiota composition occurred between stem cell infusion and reconstitution of healthy immune cells. Piperacillin-tazobactam caused the most severe declines among obligate anaerobes.\n\nConclusionsOur approach of daily sampling, bacterial density determination and dynamic systems modeling allowed us to infer the independent effects of specific antibiotics on the microbiota of HCT patients.

microbiology↗