DNA参考试剂在微生物组分析中分离偏差:一项全球多实验室研究。

IF 4.6 2区 生物学 Q1 MICROBIOLOGY
mSystems Pub Date : 2025-10-17 DOI:10.1128/msystems.00466-25
Saba Anwar, Matthew Lamaudiere, Jack Hassall, Jacob Dehinsilu, Ravneet K Bhuller, Georgina L Hold, Xabier Vázquez-Campos, Alexander Mahnert, Christine Moissl-Eichinger, Birgit Gallé, Gudrun Kainz, Petra Pjevac, Bela Hausmann, Jasmin Schwarz, Gudrun Kohl, David Berry, Sarah J Vancuren, Emma Allen-Vercoe, Nynne Nielsen, Nikolaj Sørensen, Aron Eklund, Henrik Bjørn Nielsen, René Riedel, Jannike Lea Krause, Hyun-Dong Chang, Suenie Park, Ho-Yeon Song, Hoonhee Seo, Asad Ul-Haq, Sukyung Kim, Yongbin Kwon, Sunwha Park, Xavier Soberon, Eugenia Silva-Herzog, Joost A M Verlouw, Pascal Arp, Mila Jhamai, Robert Kraaij, Anoecim R Geelen, Quinten R Ducarmon, Wiep Klaas Smits, Ed J Kuijper, Romy D Zwittink, Niels van Best, John Penders, Giang Le, Christel Driessen, Jolanda Kool, Sudarshan A Shetty, Susana Fuentes, Mehmet Demirci, Akin Yigin, Celina Whalley, Andrew D Beggs, Christopher Quince, Rob James, Sebastien Raguideau, Martin Gordon, Ryan Mate, Martin Fritzsche, Nathan P Danckert, Jesus Miguens Blanco, Julian R Marchesi, Marcus Rauch, R Anthony Williamson, Angélique B Van't Wout, Angelika Kritz, Stephan Rosecker, Richard Stevens, Lynette Laws, Lizbeth Sayavedra, Stefano Romano, Andrea Telatin, David Baker, Arjan Narbad, Stephanie L Servetas, Jason G Kralj, Samuel P Forry, Monique E Hunter, Jennifer N Dootz, Scott A Jackson, Christopher E Mason, Daniel J Butler, Christopher Mozsary, Jonathan Foox, Namita Damle, Aidan Resh, Amanda Busswitz, Peter Lenz, Shane Sontag, Andrew Cross, Christian Sanchez, Mingsheng Guo, Kayla Olson, Eric A Smith, Alex J La Reau, Tonya Ward, Scott Kuersten, Fred Hyde, Irina Khrebtukova, Gary Schroth, Sjoerd Rijpkema, Gregory C A Amos, Chrysi Sergaki
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引用次数: 0

摘要

在分析人类肠道微生物组时,分析方法引入的技术偏差阻碍了转化研究,降低了数据的可靠性和研究的可比性。在这里,通过一项涉及23个实验室的全球研究,我们分析了广泛的测序和生物信息学方法,用于分类分析由20种常见肠道细菌组成的两种定义良好的DNA参考试剂(rr)。通过霰弹枪和16S rRNA基因扩增子测序,我们旨在分离偏倚来源并了解其对微生物组谱分析准确性的影响。重要的是,建立了最低质量标准(MQC)并用于评估分析性能。我们发现,霰弹枪测序数据集的可变性大于16S rRNA基因扩增子测序,并且在湿法和干法实验室步骤中分离了偏倚来源,如测序深度、引物和数据库选择、稀疏和16S拷贝数调整。本研究提出了明确的rr和MQC,以对抗技术偏见,为可靠和可比的微生物组研究铺平了道路。该基准文件强调了世界各地和各部门微生物组数据的真实可变性水平,强调了使用世卫组织国际DNA肠道参考试剂(rs)以提高微生物组研究数据质量的迫切需要。这项全球研究是同类研究中的第一项,揭示了该领域偏见的现实,全面测试了世界各地领先实验室使用的方法,同时也为工作流程优化提供了途径,以加速创新和转化研究,并推动该领域向前发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DNA reference reagents isolate biases in microbiome profiling: a global multi-lab study.

When profiling the human gut microbiome, technical biases introduced by analytical approaches impede translational research, reducing data reliability and study comparability. Here, through a global study involving 23 labs, we analyzed a wide range of sequencing and bioinformatic approaches for the taxonomic profiling of two well-defined DNA reference reagents (RRs) comprised of 20 common gut bacteria. Through both shotgun and 16S rRNA gene amplicon sequencing, we aimed to isolate sources of bias and understand their impact on microbiome profiling accuracy. Importantly, minimum quality criteria (MQC) were established and are used to evaluate profiling performance. We found that the variability of shotgun sequencing data sets was greater than that of 16S rRNA gene amplicon sequencing and isolated sources of bias in wet and dry lab steps, such as sequencing depth, primer and database choices, rarefaction, and 16S copy number adjustment. This study presents well-defined RRs and MQC to combat technical bias, paving the way for reliable and comparable microbiome research.IMPORTANCEThis benchmark paper highlights the true level of variability in microbiome data across the world and across sectors, underscoring the critical need for the use of WHO International DNA Gut Reference Reagents (RRs) to elevate the quality of data in microbiome research. This global study is the first of its kind, revealing the reality of the bias in the field, comprehensively testing methodologies used by leading laboratories across the world, but also providing avenues for workflow optimization, to accelerate innovation and translational research and move the field forward.

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来源期刊
mSystems
mSystems Biochemistry, Genetics and Molecular Biology-Biochemistry
CiteScore
10.50
自引率
3.10%
发文量
308
审稿时长
13 weeks
期刊介绍: mSystems™ will publish preeminent work that stems from applying technologies for high-throughput analyses to achieve insights into the metabolic and regulatory systems at the scale of both the single cell and microbial communities. The scope of mSystems™ encompasses all important biological and biochemical findings drawn from analyses of large data sets, as well as new computational approaches for deriving these insights. mSystems™ will welcome submissions from researchers who focus on the microbiome, genomics, metagenomics, transcriptomics, metabolomics, proteomics, glycomics, bioinformatics, and computational microbiology. mSystems™ will provide streamlined decisions, while carrying on ASM''s tradition of rigorous peer review.
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