定量微生物组分析将肠道菌群群落变化与微生物载量的关联分析
Title：
Quantitative microbiome profiling links gut community variation to microbial load
Abstract：
Current sequencing-based analyses of faecal microbiota quantify microbial taxa and metabolic pathways as fractions of the sample sequence library generated by each analysis1,2. Although these relative approaches permit detection of disease-associated microbiome variation, they are limited in their ability to reveal the interplay between microbiota and host health3,4. Comparative analyses of relative microbiome data cannot provide information about the extent or directionality of changes in taxa abundance or metabolic potential5. If microbial load varies substantially between samples, relative profiling will hamper attempts to link microbiome features to quantitative data such as physiological parameters or metabolite concentrations5,6. Saliently, relative approaches ignore the possibility that altered overall microbiota abundance itself could be a key identifier of a disease-associated ecosystem configuration7. To enable genuine characterization of host–microbiota interactions, microbiome research must exchange ratios for counts4,8,9. Here we build a workflow for the quantitative microbiome profiling of faecal material, through parallelization of amplicon sequencing and flow cytometric enumeration of microbial cells. We observe up to tenfold differences in the microbial loads of healthy individuals and relate this variation to enterotype differentiation. We show how microbial abundances underpin both microbiota variation between individuals and covariation with host phenotype. Quantitative profiling bypasses compositionality effects in the reconstruction of gut microbiota interaction networks and reveals that the taxonomic trade-off between Bacteroides and Prevotella is an artefact of relative microbiome analyses. Finally, we identify microbial load as a key driver of observed microbiota alterations in a cohort of patients with Crohn’s disease10, here associated with a low-cell-count Bacteroides enterotype (as defined through relative profiling)11,12.
All Authors：
Doris Vandeputte, Gunter Kathagen , Kevin D’hoe, Sara Vieira-Silva , Mireia Valles-Colomer , João Sabino, Jun Wang, , Raul Y Tito, Lindsey De Commer , Youssef Darzi , Séverine Vermeire, Gwen Falony , Jeroen Raes
First Authors：
Doris Vandeputte, Gunter Kathagen , Kevin D’hoe, Sara Vieira-Silva
Correspondence：
Gwen Falony , Jeroen Raes
内容要点：
现有基于相对值的菌群分析方法局限性大，并行使用扩增子测序和流式细胞仪计数，可量化分析菌群。由此发现健康个体之间的肠道微生物载量差异可高达10倍，且与肠型分化有关。 并说明微生物丰度会强化个体间菌群差异和宿主表型相关变异。本文量化分析避免了肠道菌群相互作用网络重建的组合性影响，揭示拟杆菌和普氏菌间的分类取舍并不靠谱。在克罗恩病人队列中，观察到微生物载量是菌群差异的主要驱动因素，这与低细胞计数拟杆菌肠型相关。