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A microbial signature following bariatric surgery is robustly consistent across multiple cohorts

Bariatric surgery induces significant shifts in the gut microbiota which could potentially contribute to weight loss and metabolic benefits. The aim of this study was to characterize a microbial signature following Roux-en-Y Gastric bypass (RYGB) surgery using novel and existing gut microbiota seque...

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Autores principales: Fouladi, Farnaz, Carroll, Ian M., Sharpton, Thomas J., Bulik-Sullivan, Emily, Heinberg, Leslie, Steffen, Kristine J., Fodor, Anthony A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8224199/
https://www.ncbi.nlm.nih.gov/pubmed/34159880
http://dx.doi.org/10.1080/19490976.2021.1930872
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author Fouladi, Farnaz
Carroll, Ian M.
Sharpton, Thomas J.
Bulik-Sullivan, Emily
Heinberg, Leslie
Steffen, Kristine J.
Fodor, Anthony A.
author_facet Fouladi, Farnaz
Carroll, Ian M.
Sharpton, Thomas J.
Bulik-Sullivan, Emily
Heinberg, Leslie
Steffen, Kristine J.
Fodor, Anthony A.
author_sort Fouladi, Farnaz
collection PubMed
description Bariatric surgery induces significant shifts in the gut microbiota which could potentially contribute to weight loss and metabolic benefits. The aim of this study was to characterize a microbial signature following Roux-en-Y Gastric bypass (RYGB) surgery using novel and existing gut microbiota sequence data. We generated 16S rRNA gene and metagenomic sequences from fecal samples from patients undergoing RYGB surgery (n = 61 for 16S rRNA gene and n = 135 for metagenomics) at pre-surgical baseline and one, six, and twelve-month post-surgery. We compared these data with three smaller publicly available 16S rRNA gene and one metagenomic datasets from patients who also underwent RYGB surgery. Linear mixed models and machine learning approaches were used to examine the presence of a common microbial signature across studies. Comparison of our new sequences with previous longitudinal studies revealed strikingly similar profiles in both fecal microbiota composition (r = 0.41 ± 0.10; p < .05) and metabolic pathways (r = 0.70 ± 0.05; p < .001) early after surgery across multiple datasets. Notably, Veillonella, Streptococcus, Gemella, Fusobacterium, Escherichia/Shigella, and Akkermansia increased after surgery, while Blautia decreased. Machine learning approaches revealed that the replicable gut microbiota signature associated with RYGB surgery could be used to discriminate pre- and post-surgical samples. Opportunistic pathogen abundance also increased post-surgery in a consistent manner across cohorts. Our study reveals a robust microbial signature involving many commensal and pathogenic taxa and metabolic pathways early after RYGB surgery across different studies and sites. Characterization of the effects of this robust microbial signature on outcomes of bariatric surgery could provide insights into the development of microbiome-based interventions for predicting or improving outcomes following surgery.
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spelling pubmed-82241992021-07-01 A microbial signature following bariatric surgery is robustly consistent across multiple cohorts Fouladi, Farnaz Carroll, Ian M. Sharpton, Thomas J. Bulik-Sullivan, Emily Heinberg, Leslie Steffen, Kristine J. Fodor, Anthony A. Gut Microbes Research Paper Bariatric surgery induces significant shifts in the gut microbiota which could potentially contribute to weight loss and metabolic benefits. The aim of this study was to characterize a microbial signature following Roux-en-Y Gastric bypass (RYGB) surgery using novel and existing gut microbiota sequence data. We generated 16S rRNA gene and metagenomic sequences from fecal samples from patients undergoing RYGB surgery (n = 61 for 16S rRNA gene and n = 135 for metagenomics) at pre-surgical baseline and one, six, and twelve-month post-surgery. We compared these data with three smaller publicly available 16S rRNA gene and one metagenomic datasets from patients who also underwent RYGB surgery. Linear mixed models and machine learning approaches were used to examine the presence of a common microbial signature across studies. Comparison of our new sequences with previous longitudinal studies revealed strikingly similar profiles in both fecal microbiota composition (r = 0.41 ± 0.10; p < .05) and metabolic pathways (r = 0.70 ± 0.05; p < .001) early after surgery across multiple datasets. Notably, Veillonella, Streptococcus, Gemella, Fusobacterium, Escherichia/Shigella, and Akkermansia increased after surgery, while Blautia decreased. Machine learning approaches revealed that the replicable gut microbiota signature associated with RYGB surgery could be used to discriminate pre- and post-surgical samples. Opportunistic pathogen abundance also increased post-surgery in a consistent manner across cohorts. Our study reveals a robust microbial signature involving many commensal and pathogenic taxa and metabolic pathways early after RYGB surgery across different studies and sites. Characterization of the effects of this robust microbial signature on outcomes of bariatric surgery could provide insights into the development of microbiome-based interventions for predicting or improving outcomes following surgery. Taylor & Francis 2021-06-23 /pmc/articles/PMC8224199/ /pubmed/34159880 http://dx.doi.org/10.1080/19490976.2021.1930872 Text en © 2021 The Author(s). Published with license by Taylor & Francis Group, LLC. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Paper
Fouladi, Farnaz
Carroll, Ian M.
Sharpton, Thomas J.
Bulik-Sullivan, Emily
Heinberg, Leslie
Steffen, Kristine J.
Fodor, Anthony A.
A microbial signature following bariatric surgery is robustly consistent across multiple cohorts
title A microbial signature following bariatric surgery is robustly consistent across multiple cohorts
title_full A microbial signature following bariatric surgery is robustly consistent across multiple cohorts
title_fullStr A microbial signature following bariatric surgery is robustly consistent across multiple cohorts
title_full_unstemmed A microbial signature following bariatric surgery is robustly consistent across multiple cohorts
title_short A microbial signature following bariatric surgery is robustly consistent across multiple cohorts
title_sort microbial signature following bariatric surgery is robustly consistent across multiple cohorts
topic Research Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8224199/
https://www.ncbi.nlm.nih.gov/pubmed/34159880
http://dx.doi.org/10.1080/19490976.2021.1930872
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