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高通量肠道微生物组研究中的人类非靶向代谢组学:乙醇与甲醇

Human Untargeted Metabolomics in High-Throughput Gut Microbiome Research: Ethanol vs Methanol.

作者信息

Zuffa Simone, Charron-Lamoureux Vincent, Brennan Caitriona, Ambre Madison, Knight Rob, Dorrestein Pieter C

机构信息

Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, California 92093, United States.

Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, California 92093, United States.

出版信息

Anal Chem. 2025 Mar 11;97(9):4945-4953. doi: 10.1021/acs.analchem.4c05142. Epub 2025 Feb 27.

DOI:10.1021/acs.analchem.4c05142
PMID:40015251
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11912123/
Abstract

Untargeted metabolomics is frequently performed on human fecal samples in conjunction with sequencing to unravel the gut microbiome functionality. As sample collection efforts are rapidly expanding, with individuals often collecting specimens at home, metabolomics experiments should adapt to accommodate the safety and needs of bulk off-site collections and improve high throughput. Here, we show that a 95% ethanol, safe to be shipped and handled, extraction part of the Matrix Method pipeline recovers comparable amounts of metabolites as a validated 50% methanol extraction, preserving metabolic profile differences between investigated subjects. Additionally, we show that the fecal metabolome remains relatively stable when stored in 95% ethanol for up to 1 week at room temperature. Finally, we suggest a metabolomics data analysis workflow based on robust centered log ratio transformation, which removes the variance introduced by possible different sample weights and concentrations, allowing for reliable and integration-ready untargeted metabolomics experiments in gut microbiome research.

摘要

非靶向代谢组学经常与测序一起在人类粪便样本上进行,以揭示肠道微生物群的功能。随着样本采集工作迅速扩大,个体常常在家中采集样本,代谢组学实验应做出调整,以适应大量异地样本采集的安全性和需求,并提高通量。在这里,我们表明,基质方法流程中95%乙醇的提取部分(95%乙醇运输和处理安全)可回收与经过验证的50%甲醇提取相当数量的代谢物,保留了被研究对象之间的代谢谱差异。此外,我们表明,粪便代谢组在室温下于95%乙醇中储存长达1周时仍相对稳定。最后,我们提出了一种基于稳健中心对数比变换的代谢组学数据分析工作流程,该流程消除了可能因不同样本重量和浓度引入的方差,从而在肠道微生物群研究中实现可靠且可整合的非靶向代谢组学实验。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd6d/11912123/120884f60593/ac4c05142_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd6d/11912123/a2f99c2b9b08/ac4c05142_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd6d/11912123/4aeebc13ff1a/ac4c05142_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd6d/11912123/a8999df972b6/ac4c05142_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd6d/11912123/120884f60593/ac4c05142_0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd6d/11912123/a2f99c2b9b08/ac4c05142_0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd6d/11912123/4aeebc13ff1a/ac4c05142_0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd6d/11912123/a8999df972b6/ac4c05142_0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd6d/11912123/120884f60593/ac4c05142_0004.jpg

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Gut microbial factors predict disease severity in a mouse model of multiple sclerosis.
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