微生物群
生物
人体微生物群
人类微生物组计划
菌血症
基因组
计算生物学
生物信息学
进化生物学
抗生素
遗传学
基因
作者
Jonas Schluter,Ana Djukovic,Bradford P. Taylor,Jinyuan Yan,Chaojun Duan,Grant A. Hussey,Chen Liao,Sneh Sharma,Emily Fontana,Luigi A. Amoretti,Roberta J. Wright,Anqi Dai,Jonathan U. Peled,Ying Taur,Miguel‐Angel Perales,Benjamin A. Siranosian,Ami S. Bhatt,Marcel R.M. van den Brink,Eric G. Pamer,João B. Xavier
标识
DOI:10.1016/j.chom.2023.05.027
摘要
Longitudinal microbiome data provide valuable insight into disease states and clinical responses, but they are challenging to mine and view collectively. To address these limitations, we present TaxUMAP, a taxonomically informed visualization for displaying microbiome states in large clinical microbiome datasets. We used TaxUMAP to chart a microbiome atlas of 1,870 patients with cancer during therapy-induced perturbations. Bacterial density and diversity were positively associated, but the trend was reversed in liquid stool. Low-diversity states (dominations) remained stable after antibiotic treatment, and diverse communities had a broader range of antimicrobial resistance genes than dominations. When examining microbiome states associated with risk for bacteremia, TaxUMAP revealed that certain Klebsiella species were associated with lower risk for bacteremia localize in a region of the atlas that is depleted in high-risk enterobacteria. This indicated a competitive interaction that was validated experimentally. Thus, TaxUMAP can chart comprehensive longitudinal microbiome datasets, enabling insights into microbiome effects on human health.
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