Literature DB >> 34006335

Identifying biases and their potential solutions in human microbiome studies.

Jacob T Nearing1, André M Comeau2, Morgan G I Langille3,4.   

Abstract

Advances in DNA sequencing technology have vastly improved the ability of researchers to explore the microbial inhabitants of the human body. Unfortunately, while these studies have uncovered the importance of these microbial communities to our health, they often do not result in similar findings. One possible reason for the disagreement in these results is due to the multitude of systemic biases that are introduced during sequence-based microbiome studies. These biases begin with sample collection and continue to be introduced throughout the entire experiment leading to an observed community that is significantly altered from the true underlying microbial composition. In this review, we will highlight the various steps in typical sequence-based human microbiome studies where significant bias can be introduced, and we will review the current efforts within the field that aim to reduce the impact of these biases. Video abstract.

Entities:  

Keywords:  Amplicon; Bias; Contamination; Metagenomics; Methodology; Microbiome

Year:  2021        PMID: 34006335     DOI: 10.1186/s40168-021-01059-0

Source DB:  PubMed          Journal:  Microbiome        ISSN: 2049-2618            Impact factor:   14.650


  108 in total

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Authors:  Ana Durbán; Juan J Abellán; Nuria Jiménez-Hernández; Marta Ponce; Julio Ponce; Teresa Sala; Giuseppe D'Auria; Amparo Latorre; Andrés Moya
Journal:  Microb Ecol       Date:  2010-08-24       Impact factor: 4.552

2.  Microbiome Diagnostics.

Authors:  Robert Schlaberg
Journal:  Clin Chem       Date:  2020-01-01       Impact factor: 8.327

3.  Differences in microbial signatures between rectal mucosal biopsies and rectal swabs.

Authors:  Félix Araújo-Pérez; Amber N McCoy; Charles Okechukwu; Ian M Carroll; Kevin M Smith; Kim Jeremiah; Robert S Sandler; Gary N Asher; Temitope O Keku
Journal:  Gut Microbes       Date:  2012-10-11

4.  Stool consistency is strongly associated with gut microbiota richness and composition, enterotypes and bacterial growth rates.

Authors:  Doris Vandeputte; Gwen Falony; Sara Vieira-Silva; Raul Y Tito; Marie Joossens; Jeroen Raes
Journal:  Gut       Date:  2015-06-11       Impact factor: 23.059

5.  Colonic Transit Time Is a Driven Force of the Gut Microbiota Composition and Metabolism: In Vitro Evidence.

Authors:  William Tottey; David Feria-Gervasio; Nadia Gaci; Brigitte Laillet; Estelle Pujos; Jean-François Martin; Jean-Louis Sebedio; Benoit Sion; Jean-François Jarrige; Monique Alric; Jean-François Brugère
Journal:  J Neurogastroenterol Motil       Date:  2017-01-30       Impact factor: 4.924

6.  Inter-personal diversity and temporal dynamics of dental, tongue, and salivary microbiota in the healthy oral cavity.

Authors:  Robert G Beiko; Dilani B Senadheera; Michael W Hall; Natasha Singh; Kester F Ng; David K Lam; Michael B Goldberg; Howard C Tenenbaum; Josh D Neufeld
Journal:  NPJ Biofilms Microbiomes       Date:  2017-01-26       Impact factor: 7.290

7.  Comparison of stool versus rectal swab samples and storage conditions on bacterial community profiles.

Authors:  Christine M Bassis; Nicholas M Moore; Karen Lolans; Anna M Seekatz; Robert A Weinstein; Vincent B Young; Mary K Hayden
Journal:  BMC Microbiol       Date:  2017-03-31       Impact factor: 3.605

8.  Inter-niche and inter-individual variation in gut microbial community assessment using stool, rectal swab, and mucosal samples.

Authors:  Roshonda B Jones; Xiangzhu Zhu; Emili Moan; Harvey J Murff; Reid M Ness; Douglas L Seidner; Shan Sun; Chang Yu; Qi Dai; Anthony A Fodor; M Andrea Azcarate-Peril; Martha J Shrubsole
Journal:  Sci Rep       Date:  2018-03-07       Impact factor: 4.379

9.  A spatial gradient of bacterial diversity in the human oral cavity shaped by salivary flow.

Authors:  Diana M Proctor; Julia A Fukuyama; Peter M Loomer; Gary C Armitage; Stacey A Lee; Nicole M Davis; Mark I Ryder; Susan P Holmes; David A Relman
Journal:  Nat Commun       Date:  2018-02-14       Impact factor: 14.919

10.  Rectal swabs are a reliable proxy for faecal samples in infant gut microbiota research based on 16S-rRNA sequencing.

Authors:  Marta Reyman; Marlies A van Houten; Kayleigh Arp; Elisabeth A M Sanders; Debby Bogaert
Journal:  Sci Rep       Date:  2019-11-05       Impact factor: 4.379

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  9 in total

1.  GenBank as a Source to Monitor and Analyze Host-Microbiome Data.

Authors:  Vivek Ramanan; Shanti Mechery; Indra Neil Sarkar
Journal:  Bioinformatics       Date:  2022-07-08       Impact factor: 6.931

2.  Adaptation of gut microbiome and host metabolic systems to lignocellulosic degradation in bamboo rats.

Authors:  Kangpeng Xiao; Xianghui Liang; Haoran Lu; Xiaobing Li; Zhipeng Zhang; Xingbang Lu; Hai Wang; Yafei Meng; Ayan Roy; Wen Luo; Xuejuan Shen; David M Irwin; Yongyi Shen
Journal:  ISME J       Date:  2022-05-14       Impact factor: 11.217

3.  Microbiome differential abundance methods produce different results across 38 datasets.

Authors:  Jacob T Nearing; Gavin M Douglas; Molly G Hayes; Jocelyn MacDonald; Dhwani K Desai; Nicole Allward; Casey M A Jones; Robyn J Wright; Akhilesh S Dhanani; André M Comeau; Morgan G I Langille
Journal:  Nat Commun       Date:  2022-01-17       Impact factor: 14.919

4.  The crewed journey to Mars and its implications for the human microbiome.

Authors:  Torben Kuehnast; Carmel Abbott; Manuela R Pausan; David A Pearce; Christine Moissl-Eichinger; Alexander Mahnert
Journal:  Microbiome       Date:  2022-02-07       Impact factor: 14.650

5.  Increasing transparency and reproducibility in stroke-microbiota research: A toolbox for microbiota analysis.

Authors:  Adam Sorbie; Rosa Delgado Jiménez; Corinne Benakis
Journal:  iScience       Date:  2022-02-26

6.  Inferring Species Compositions of Complex Fungal Communities from Long- and Short-Read Sequence Data.

Authors:  Yiheng Hu; Laszlo Irinyi; Minh Thuy Vi Hoang; Tavish Eenjes; Abigail Graetz; Eric A Stone; Wieland Meyer; Benjamin Schwessinger; John P Rathjen
Journal:  mBio       Date:  2022-04-11       Impact factor: 7.786

7.  Guideline for the analysis of the microbial communities of the human upper airways.

Authors:  Leonardo Mancabelli; Tecla Ciociola; Gabriele Andrea Lugli; Chiara Tarracchini; Federico Fontanta; Alice Viappiani; Francesca Turroni; Andrea Ticinesi; Tiziana Meschi; Stefania Conti; Marco Ventura; Christian Milani
Journal:  J Oral Microbiol       Date:  2022-07-28       Impact factor: 5.833

8.  Sequencing introduced false positive rare taxa lead to biased microbial community diversity, assembly, and interaction interpretation in amplicon studies.

Authors:  Yangyang Jia; Shengguo Zhao; Wenjie Guo; Ling Peng; Fang Zhao; Lushan Wang; Guangyi Fan; Yuanfang Zhu; Dayou Xu; Guilin Liu; Ruoqing Wang; Xiaodong Fang; He Zhang; Karsten Kristiansen; Wenwei Zhang; Jianwei Chen
Journal:  Environ Microbiome       Date:  2022-08-17

9.  Does filter pore size introduce bias in DNA sequence-based plankton community studies?

Authors:  Guolin Ma; Ramiro Logares; Yuanyuan Xue; Jun Yang
Journal:  Front Microbiol       Date:  2022-09-26       Impact factor: 6.064

  9 in total

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