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通过脉冲宏转录组学在一份人类粪便样本中鉴定新型低聚果糖细菌消费者。

Identification of novel fructo-oligosaccharide bacterial consumers by pulse metatranscriptomics in a human stool sample.

作者信息

Prattico Catherine, Gonzalez Emmanuel, Dridi Lharbi, Jazestani Shiva, Low Kristin E, Abbott D Wade, Maurice Corinne F, Castagner Bastien

机构信息

Department of Microbiology & Immunology, Faculty of Medicine and Health Sciences, McGill University, Montréal, Québec, Canada.

Canadian Centre for Computational Genomics, McGill Genome Centre, McGill University, Montréal, Québec, Canada.

出版信息

mSphere. 2025 Jan 28;10(1):e0066824. doi: 10.1128/msphere.00668-24. Epub 2024 Dec 19.

DOI:10.1128/msphere.00668-24
PMID:39699190
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11774028/
Abstract

UNLABELLED

Dietary fibers influence the composition of the human gut microbiota and directly contribute to its downstream effects on host health. As more research supports the use of glycans as prebiotics for therapeutic applications, the need to identify the gut bacteria that metabolize glycans of interest increases. Fructo-oligosaccharide (FOS) is a common diet-derived glycan that is fermented by the gut microbiota and has been used as a prebiotic. Despite being well studied, we do not yet have a complete picture of all FOS-consuming gut bacterial taxa. To identify new bacterial consumers, we used a short exposure of microbial communities in a stool sample to FOS or galactomannan as the sole carbon source to induce glycan metabolism genes. We then performed metatranscriptomics, paired with whole metagenomic sequencing, and 16S amplicon sequencing. The short incubation was sufficient to cause induction of genes involved in carbohydrate metabolism, like carbohydrate-active enzymes (CAZymes), including glycoside hydrolase family 32 genes, which hydrolyze fructan polysaccharides like FOS and inulin. Interestingly, FOS metabolism transcripts were notably overexpressed in species not previously reported to be fructan consumers. We therefore validated the ability of different species to ferment fructans by monitoring their growth and fermentation in defined media. This pulse metatranscriptomics approach is a useful method to find novel consumers of prebiotics and increase our understanding of prebiotic metabolism by CAZymes in the gut microbiota.

IMPORTANCE

Complex carbohydrates are key contributors to the composition of the human gut microbiota and play an essential role in the microbiota's effects on host health. Understanding which bacteria consume complex carbohydrates, or glycans, provides a mechanistic link between dietary prebiotics and their beneficial health effects, an essential step for their therapeutic application. Here, we used a pulse metatranscriptomics pipeline to identify bacterial consumers based on glycan metabolism induction in a human stool sample. We identified novel consumers of fructo-oligosaccharide among species, expanding our understanding of this well-known glycan. Our approach can be applied to identify consumers of understudied glycans and expand our prebiotic repertoire. It can also be used to study prebiotic glycans directly in stool samples in distinct patient populations to help delineate the prebiotic mechanism.

摘要

未标记

膳食纤维会影响人类肠道微生物群的组成,并直接促成其对宿主健康的下游影响。随着越来越多的研究支持将聚糖用作治疗应用的益生元,识别能够代谢相关聚糖的肠道细菌的需求也在增加。低聚果糖(FOS)是一种常见的饮食来源聚糖,可被肠道微生物群发酵,并已用作益生元。尽管已得到充分研究,但我们尚未完全了解所有消耗FOS的肠道细菌分类群。为了识别新的细菌消费者,我们让粪便样本中的微生物群落短暂接触FOS或半乳甘露聚糖作为唯一碳源,以诱导聚糖代谢基因。然后我们进行了宏转录组学分析,并结合了全宏基因组测序和16S扩增子测序。短暂培养足以诱导参与碳水化合物代谢的基因,如碳水化合物活性酶(CAZyme),包括糖苷水解酶家族32基因,该基因可水解低聚果糖和菊粉等果聚糖多糖。有趣的是,FOS代谢转录本在以前未被报道为果聚糖消费者的物种中显著过表达。因此,我们通过监测不同物种在特定培养基中的生长和发酵情况,验证了它们发酵果聚糖的能力。这种脉冲宏转录组学方法是一种有用的方法,可用于发现益生元的新消费者,并增进我们对肠道微生物群中CAZyme对益生元代谢的理解。

重要性

复杂碳水化合物是人类肠道微生物群组成的关键贡献者,并且在微生物群对宿主健康的影响中起着至关重要的作用。了解哪些细菌消耗复杂碳水化合物或聚糖,为饮食益生元和它们有益的健康影响之间提供了一个机制联系,这是它们治疗应用的关键一步。在这里,我们使用了一种脉冲宏转录组学流程,根据人类粪便样本中的聚糖代谢诱导来识别细菌消费者。我们在多个物种中识别出了低聚果糖的新消费者,扩展了我们对这种知名聚糖的理解。我们的方法可用于识别研究较少的聚糖的消费者,并扩大我们的益生元库。它还可用于直接在不同患者群体的粪便样本中研究益生元聚糖,以帮助阐明益生元机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d393/11774028/81dfc2ff5c1b/msphere.00668-24.f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d393/11774028/3e185ffe9a5b/msphere.00668-24.f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d393/11774028/d65fcd4b9e3f/msphere.00668-24.f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d393/11774028/79d6358809d0/msphere.00668-24.f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d393/11774028/81dfc2ff5c1b/msphere.00668-24.f004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d393/11774028/3e185ffe9a5b/msphere.00668-24.f001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d393/11774028/d65fcd4b9e3f/msphere.00668-24.f002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d393/11774028/79d6358809d0/msphere.00668-24.f003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d393/11774028/81dfc2ff5c1b/msphere.00668-24.f004.jpg

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本文引用的文献

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SACCHARIS v2: Streamlining Prediction of Carbohydrate-Active Enzyme Specificities Within Large Datasets.SACCHARIS v2:在大型数据集内简化碳水化合物活性酶特异性预测。
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