Literature DB >> 35285497

Multi-Omics Strategies for Investigating the Microbiome in Toxicology Research.

Ethan W Morgan1, Gary H Perdew2, Andrew D Patterson1,2.   

Abstract

Microbial communities on and within the host contact environmental pollutants, toxic compounds, and other xenobiotic compounds. These communities of bacteria, fungi, viruses, and archaea possess diverse metabolic potential to catabolize compounds and produce new metabolites. Microbes alter chemical disposition thus making the microbiome a natural subject of interest for toxicology. Sequencing and metabolomics technologies permit the study of microbiomes altered by acute or long-term exposure to xenobiotics. These investigations have already contributed to and are helping to re-interpret traditional understandings of toxicology. The purpose of this review is to provide a survey of the current methods used to characterize microbes within the context of toxicology. This will include discussion of commonly used techniques for conducting omic-based experiments, their respective strengths and deficiencies, and how forward-looking techniques may address present shortcomings. Finally, a perspective will be provided regarding common assumptions that currently impede microbiome studies from producing causal explanations of toxicologic mechanisms.
© The Author(s) 2022. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  gut microbiome; metabolism; metabolomics; microbiome

Mesh:

Substances:

Year:  2022        PMID: 35285497      PMCID: PMC9154275          DOI: 10.1093/toxsci/kfac029

Source DB:  PubMed          Journal:  Toxicol Sci        ISSN: 1096-0929            Impact factor:   4.109


  267 in total

1.  Production of Ah receptor ligands in rat fecal suspensions containing tryptophan or indole-3-carbinol.

Authors:  G H Perdew; C F Babbs
Journal:  Nutr Cancer       Date:  1991       Impact factor: 2.900

2.  Systematic improvement of amplicon marker gene methods for increased accuracy in microbiome studies.

Authors:  Daryl M Gohl; Pajau Vangay; John Garbe; Allison MacLean; Adam Hauge; Aaron Becker; Trevor J Gould; Jonathan B Clayton; Timothy J Johnson; Ryan Hunter; Dan Knights; Kenneth B Beckman
Journal:  Nat Biotechnol       Date:  2016-07-25       Impact factor: 54.908

3.  Role of AhR in regulating cancer stem cell-like characteristics in choriocarcinoma.

Authors:  Chenchun Wu; Shuran Yu; Qianxia Tan; Peng Guo; Huining Liu
Journal:  Cell Cycle       Date:  2018-10-18       Impact factor: 4.534

4.  Microbial single-cell RNA sequencing by split-pool barcoding.

Authors:  Anna Kuchina; Leandra M Brettner; Luana Paleologu; Charles M Roco; Alexander B Rosenberg; Alberto Carignano; Ryan Kibler; Matthew Hirano; R William DePaolo; Georg Seelig
Journal:  Science       Date:  2020-12-17       Impact factor: 47.728

5.  Multi-Omics Reveals that Lead Exposure Disturbs Gut Microbiome Development, Key Metabolites, and Metabolic Pathways.

Authors:  Bei Gao; Liang Chi; Ridwan Mahbub; Xiaoming Bian; Pengcheng Tu; Hongyu Ru; Kun Lu
Journal:  Chem Res Toxicol       Date:  2017-03-16       Impact factor: 3.739

6.  Gut microbiota from twins discordant for obesity modulate metabolism in mice.

Authors:  Vanessa K Ridaura; Jeremiah J Faith; Federico E Rey; Jiye Cheng; Alexis E Duncan; Andrew L Kau; Nicholas W Griffin; Vincent Lombard; Bernard Henrissat; James R Bain; Michael J Muehlbauer; Olga Ilkayeva; Clay F Semenkovich; Katsuhiko Funai; David K Hayashi; Barbara J Lyle; Margaret C Martini; Luke K Ursell; Jose C Clemente; William Van Treuren; William A Walters; Rob Knight; Christopher B Newgard; Andrew C Heath; Jeffrey I Gordon
Journal:  Science       Date:  2013-09-06       Impact factor: 47.728

7.  Glycan-based shaping of the microbiota during primate evolution.

Authors:  Patricia Bastos-Amador; Jessica Ann Thompson; Sumnima Singh; Mauro Truglio; Bahtiyar Yilmaz; Silvia Cardoso; Daniel Sobral; Miguel P Soares
Journal:  Elife       Date:  2021-05-19       Impact factor: 8.140

8.  "Available upon request": not good enough for microbiome data!

Authors:  Morgan G I Langille; Jacques Ravel; W Florian Fricke
Journal:  Microbiome       Date:  2018-01-10       Impact factor: 14.650

9.  High-throughput fitness screening and transcriptomics identify a role for a type IV secretion system in the pathogenesis of Crohn's disease-associated Escherichia coli.

Authors:  Sarah Hordienko; Steven Gould; Wael Elhenawy; Alexander M Oberc; Caressa N Tsai; Troy P Hubbard; Matthew K Waldor; Brian K Coombes
Journal:  Nat Commun       Date:  2021-04-01       Impact factor: 14.919

Review 10.  Data standards can boost metabolomics research, and if there is a will, there is a way.

Authors:  Philippe Rocca-Serra; Reza M Salek; Masanori Arita; Elon Correa; Saravanan Dayalan; Alejandra Gonzalez-Beltran; Tim Ebbels; Royston Goodacre; Janna Hastings; Kenneth Haug; Albert Koulman; Macha Nikolski; Matej Oresic; Susanna-Assunta Sansone; Daniel Schober; James Smith; Christoph Steinbeck; Mark R Viant; Steffen Neumann
Journal:  Metabolomics       Date:  2015-11-17       Impact factor: 4.290

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  1 in total

Review 1.  Potential roles of gut microbes in biotransformation of natural products: An overview.

Authors:  Yucui Zhao; Xinqin Zhong; Junyuan Yan; Congying Sun; Xin Zhao; Xiaoying Wang
Journal:  Front Microbiol       Date:  2022-09-29       Impact factor: 6.064

  1 in total

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