Biology subjects

Taylor, B. P.

Publications and source records attributed to Taylor, B. P..

7 recordsLinked to original sources

bioRxiv2025

SARS-CoV-2 Intra-host Variation Shows Evidence of Transmission and Convergent Evolution in a University Surveillance Cohort

Monitoring and understanding the transmission and evolution of SARS-CoV-2 remains a significant pub-lic health priority. Within-host genetic variation provides insight into viral evolution during infection and may help infer transmission events. In this study, we analyzed intrahost variation in SARS-CoV-2 genome sequences from Boston Universitys testing mandate. Focusing on intrahost single nucleotide variants (iSNVs), we inferred transmission events and assessed the selective forces shaping within-host viral evolution. To minimize false-positive iSNVs resulting from systematic biases, we implemented stringent data filtering and developed a heuristic to exclude contamination-derived artifacts arising from batched sequencing. We find that intrahost variation is limited and infrequently transmitted during acute infections, suggesting that shared iSNVs serve as highly specific but insensitive markers of transmission. We also observed incomplete purifying selection shaping within-host diversity, with the loci most affected changing among variants of concern. Finally, we identified a highly recurrent iSNV (G11083T) which may represent a site of positive selection. Our results highlight that within host variation provides insight towards within host pathogen evolution, in spite of a limited use towards genomic epidemiology. IMPACT STATEMENTSARS-CoV-2 is the most extensively sequenced pathogen to date, yet much of its genomic data remains underutilized. Intrahost variation, in particular, is less studied than consensus-level variation, partly because most datasets lack technical sequencing replicates to control false-positive signals. Using genomic data from a university testing mandate and applying rigorous filtering to systematically minimize false-positive iSNVs in a data-driven manner, we obtain insights into SARS-CoV-2 evolution and transmission from intrahost variation. Our work underscores the potential to use existing, large-scale datasets to better understand pathogen evolution in situ. DATA SUMMARYAll sequence data have been deposited in the Sequence Read Archive (SRA) of the national center for biotechnology information (NCBI), under the project accession number PRJNA892225. All code is open-access and available in GitHub at: https://github.com/Leacavalli/Sars-cov-2-Intrahost-Variation. Any additional supporting data has been provided within the article.

genomics↗

bioRxiv2022

Enterobacteriaceae isolated from patients share antibiotic resistance conferring plasmids recently acquired from those isolated from sinks in the same treatment room

Identifying how and where pathogens acquire antibiotic resistance is crucial to developing effective strategies to limit its spread. Many bacterial species carry and share plasmids harboring antibiotic resistant genes. Plasmids are mobile genetic elements whose horizontal transmission is difficult to assess through genomic comparison due to assembly issues when using short-read sequencing alone. In this study, we use hybrid assembly to fully assemble plasmids that are shared between different Enterobacteriaceae isolated from patients and sinks in the same hospital rooms. We isolated and sequenced pairs of carbapenem resistant Enterobacter hormaechei subsp. xiangfangensis and Klebsiella pneumoniae from patients and sinks within the same hospital room. The isolate pairs share plasmids that putatively confer antibiotic resistance, including carbapenem resistance. These plasmids differ by few mutations and structural changes, while the isolates carry unique plasmids. Together, this suggests that plasmids can act as vectors of antibiotic resistance spread from sink reservoirs to patients.

microbiology↗

bioRxiv2022

Beyond consensus sequence: a quantitative scheme for inferring transmission using deep sequencing in a bacterial transmission model

Genomic surveillance provides a data source complementary to contact tracing to resolve putative transmission chains. However, the role of within-host diversity in transmission is understudied due to a lack of experimental and clinical datasets that capture within-host diversity in both donors and recipients. Here, we assess the utility of deep-sequenced genomic surveillance within a mouse transmission model where the gastrointestinal pathogen Citrobacter rodentium was controllably spread during co-housing of infected and naive animals. We observed that within-host variants were maintained over multiple transmission steps until fixation or elimination. We present a model for inferring the likelihood that a given pair of samples are linked by transmission, by comparing the allelic frequency at variant genomic loci. Our data affirm that within-host single nucleotide variants (iSNVs) can repeatedly pass from donor to recipient along the transmission chain, and the mere sharing of iSNVs between different transmission pairs offers limited confidence in identifying a transmission pair. Beyond the presence and absence of within-host variants, we show that differences arising in the relative abundance of iSNVs can infer transmission pairs with high precision. An important component of our approach is that the inference is based solely on sequence data, without incorporating epidemiological or demographic data for context. Our model, which substantially reduces the number of comparisons a contact tracer needs to consider, may enhance the accuracy of contact tracing and other epidemiological processes, including early detection of emerging transmission clusters.

genomics↗

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↗

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↗