Biology subjects

Hussey, G. A.

Publications and source records attributed to Hussey, G. A..

3 recordsLinked to original sources

bioRxiv2022

The MTIST platform: a microbiome time series inference standardized test simulation, dataset, and scoring systems

The human gut microbiome is promising therapeutic target, but development of interventions is hampered by limited understanding of the microbial ecosystem. Therefore, recent years have seen a surge in the engineering of inference algorithms seeking to unravel rules of ecological interactions from metagenomic data. Research groups score algorithmic performance in a variety of different ways, however, there exists no unified framework to score and rank each inference approach. The machine learning field presents a useful solution to this issue: a unified set of validation data and accompanying scoring metric. Here, we present MTIST: a platform for benchmarking microbial ecosystem inference tools. We use a generalized Lotka-Volterra framework to simulate microbial abundances over time, akin to what would be obtained by quantitative metagenomic sequencing studies or lab experiments, to generate a massive in silico training dataset (MTIST) for algorithmic validation, as well as an "ecological sign" score (ES score) to rate them. MTIST comprises 24,570 time series of microbial abundance data packaged into 648 datasets. Together, the MTIST dataset and the ES score serve as a platform to develop and compare microbiome ecosystem inference approaches.

microbiology↗

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

Gut microbiome dysbiosis during COVID-19 is associated with increased risk for bacteremia and microbial translocation.

The microbial populations in the gut microbiome have recently been associated with COVID-19 disease severity. However, a causal impact of the gut microbiome on COVID-19 patient health has not been established. Here we provide evidence that gut microbiome dysbiosis is associated with translocation of bacteria into the blood during COVID-19, causing life-threatening secondary infections. Antibiotics and other treatments during COVID-19 can potentially confound microbiome associations. We therefore first demonstrate in a mouse model that SARS-CoV-2 infection can induce gut microbiome dysbiosis, which correlated with alterations to Paneth cells and goblet cells, and markers of barrier permeability. Comparison with stool samples collected from 96 COVID-19 patients at two different clinical sites also revealed substantial gut microbiome dysbiosis, paralleling our observations in the animal model. Specifically, we observed blooms of opportunistic pathogenic bacterial genera known to include antimicrobial-resistant species in hospitalized COVID-19 patients. Analysis of blood culture results testing for secondary microbial bloodstream infections with paired microbiome data obtained from these patients indicates that bacteria may translocate from the gut into the systemic circulation of COVID-19 patients. These results are consistent with a direct role for gut microbiome dysbiosis in enabling dangerous secondary infections during COVID-19.

microbiology↗