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Title: Gut bacteria responding to dietary change encode sialidases that exhibit preference for red meat-associated carbohydrates

Abstract

Dietary habits have been associated with alterations of the human gut resident microorganisms contributing to obesity, diabetes and cancer. In Western diets, red meat is a frequently eaten food, but long-term consumption has been associated with increased risk of disease. Red meat is enriched in N-glycolylneuraminic acid (Neu5Gc) that cannot be synthesized by humans. However, consumption can cause Neu5Gc incorporation into cell surface glycans, especially in carcinomas. As a consequence, an inflammatory response is triggered when Neu5Gc-containing glycans encounter circulating anti-Neu5Gc antibodies. Although bacteria can use free sialic acids as a nutrient source, it is currently unknown if gut microorganisms contribute to releasing Neu5Gc from food. Iin this work, we found that a Neu5Gc-rich diet induces changes in the gut microbiota, with Bacteroidales and Clostridiales responding the most. Genome assembling of mouse and human shotgun metagenomic sequencing identified bacterial sialidases with previously unobserved substrate preference for Neu5Gc-containing glycans. X-ray crystallography revealed key amino acids potentially contributing to substrate preference. Additionally, we verified that mouse and human sialidases were able to release Neu5Gc from red meat. The release of Neu5Gc from red meat using bacterial sialidases could reduce the risk of inflammatory diseases associated with red meat consumption, including colorectal cancermore » and atherosclerosis.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1];  [1];  [2];  [2];  [2];  [1]; ORCiD logo [1];  [1];  [1];  [1]; ORCiD logo [1]; ORCiD logo [1]
  1. Univ. of California, San Diego, CA (United States)
  2. New England Biolabs, Ipswich, MA (United States)
Publication Date:
Research Org.:
Argonne National Lab. (ANL), Argonne, IL (United States). Advanced Photon Source (APS)
Sponsoring Org.:
USDOE Office of Science (SC); National Institutes of Health (NIH); National Science Foundation (NSF); Program Science Without Borders Bex
OSTI Identifier:
1600797
Grant/Contract Number:  
R01GM32373; IOS-1444435; T32GM8806
Resource Type:
Accepted Manuscript
Journal Name:
Nature Microbiology
Additional Journal Information:
Journal Volume: 4; Journal Issue: 12; Journal ID: ISSN 2058-5276
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
ENGLISH
Subject:
59 BASIC BIOLOGICAL SCIENCES; Gastrointestinal diseases; Microbiome; Risk factors

Citation Formats

Zaramela, Livia S., Martino, Cameron, Alisson-Silva, Frederico, Rees, Steven D., Diaz, Sandra L., Chuzel, Léa, Ganatra, Mehul B., Taron, Christopher H., Secrest, Patrick, Zuñiga, Cristal, Huang, Jianbo, Siegel, Dionicio, Chang, Geoffrey, Varki, Ajit, and Zengler, Karsten. Gut bacteria responding to dietary change encode sialidases that exhibit preference for red meat-associated carbohydrates. United States: N. p., 2019. Web. https://doi.org/10.1038/s41564-019-0564-9.
Zaramela, Livia S., Martino, Cameron, Alisson-Silva, Frederico, Rees, Steven D., Diaz, Sandra L., Chuzel, Léa, Ganatra, Mehul B., Taron, Christopher H., Secrest, Patrick, Zuñiga, Cristal, Huang, Jianbo, Siegel, Dionicio, Chang, Geoffrey, Varki, Ajit, & Zengler, Karsten. Gut bacteria responding to dietary change encode sialidases that exhibit preference for red meat-associated carbohydrates. United States. https://doi.org/10.1038/s41564-019-0564-9
Zaramela, Livia S., Martino, Cameron, Alisson-Silva, Frederico, Rees, Steven D., Diaz, Sandra L., Chuzel, Léa, Ganatra, Mehul B., Taron, Christopher H., Secrest, Patrick, Zuñiga, Cristal, Huang, Jianbo, Siegel, Dionicio, Chang, Geoffrey, Varki, Ajit, and Zengler, Karsten. Mon . "Gut bacteria responding to dietary change encode sialidases that exhibit preference for red meat-associated carbohydrates". United States. https://doi.org/10.1038/s41564-019-0564-9. https://www.osti.gov/servlets/purl/1600797.
@article{osti_1600797,
title = {Gut bacteria responding to dietary change encode sialidases that exhibit preference for red meat-associated carbohydrates},
author = {Zaramela, Livia S. and Martino, Cameron and Alisson-Silva, Frederico and Rees, Steven D. and Diaz, Sandra L. and Chuzel, Léa and Ganatra, Mehul B. and Taron, Christopher H. and Secrest, Patrick and Zuñiga, Cristal and Huang, Jianbo and Siegel, Dionicio and Chang, Geoffrey and Varki, Ajit and Zengler, Karsten},
abstractNote = {Dietary habits have been associated with alterations of the human gut resident microorganisms contributing to obesity, diabetes and cancer. In Western diets, red meat is a frequently eaten food, but long-term consumption has been associated with increased risk of disease. Red meat is enriched in N-glycolylneuraminic acid (Neu5Gc) that cannot be synthesized by humans. However, consumption can cause Neu5Gc incorporation into cell surface glycans, especially in carcinomas. As a consequence, an inflammatory response is triggered when Neu5Gc-containing glycans encounter circulating anti-Neu5Gc antibodies. Although bacteria can use free sialic acids as a nutrient source, it is currently unknown if gut microorganisms contribute to releasing Neu5Gc from food. Iin this work, we found that a Neu5Gc-rich diet induces changes in the gut microbiota, with Bacteroidales and Clostridiales responding the most. Genome assembling of mouse and human shotgun metagenomic sequencing identified bacterial sialidases with previously unobserved substrate preference for Neu5Gc-containing glycans. X-ray crystallography revealed key amino acids potentially contributing to substrate preference. Additionally, we verified that mouse and human sialidases were able to release Neu5Gc from red meat. The release of Neu5Gc from red meat using bacterial sialidases could reduce the risk of inflammatory diseases associated with red meat consumption, including colorectal cancer and atherosclerosis.},
doi = {10.1038/s41564-019-0564-9},
journal = {Nature Microbiology},
number = 12,
volume = 4,
place = {United States},
year = {2019},
month = {9}
}

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