Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models

Gut microbes have been identified as potential markers in distinguishing patients from controls in colorectal cancer, ulcerative colitis, and Crohn’s disease individually, whereas there lacks a systematic analysis to investigate the exclusive microbial shifts of these enteropathies with similar cli...

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Autores principales:	Puzi Jiang, Sicheng Wu, Qibin Luo, Xing-ming Zhao, Wei-Hua Chen
Formato:	article
Lenguaje:	EN
Publicado:	American Society for Microbiology 2021
Materias:	Microbiology QR1-502
Acceso en línea:	https://doaj.org/article/978ae8e56d464405892e6379b6365232
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spelling	oai:doaj.org-article:978ae8e56d464405892e6379b63652322021-12-02T18:50:25ZMetagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models2379-507710.1128/mSystems.00112-21https://doaj.org/article/978ae8e56d464405892e6379b63652322021-06-01T00:00:00Zhttps://journals.asm.org/doi/10.1128/mSystems.00112-21https://doaj.org/toc/2379-5077 Gut microbes have been identified as potential markers in distinguishing patients from controls in colorectal cancer, ulcerative colitis, and Crohn’s disease individually, whereas there lacks a systematic analysis to investigate the exclusive microbial shifts of these enteropathies with similar clinical symptoms. Our meta-analysis and cross-disease comparisons identified consistent microbial alterations in each enteropathy, revealed microbial ecosystems among marker bacteria in distinct states, and demonstrated the necessity and feasibility of metagenome-based multidisease classifications.Puzi JiangSicheng WuQibin LuoXing-ming ZhaoWei-Hua ChenAmerican Society for MicrobiologyarticleMicrobiologyQR1-502ENmSystems, Vol 6, Iss 3 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Microbiology QR1-502
spellingShingle	Microbiology QR1-502 Puzi Jiang Sicheng Wu Qibin Luo Xing-ming Zhao Wei-Hua Chen Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models
description	Gut microbes have been identified as potential markers in distinguishing patients from controls in colorectal cancer, ulcerative colitis, and Crohn’s disease individually, whereas there lacks a systematic analysis to investigate the exclusive microbial shifts of these enteropathies with similar clinical symptoms. Our meta-analysis and cross-disease comparisons identified consistent microbial alterations in each enteropathy, revealed microbial ecosystems among marker bacteria in distinct states, and demonstrated the necessity and feasibility of metagenome-based multidisease classifications.
format	article
author	Puzi Jiang Sicheng Wu Qibin Luo Xing-ming Zhao Wei-Hua Chen
author_facet	Puzi Jiang Sicheng Wu Qibin Luo Xing-ming Zhao Wei-Hua Chen
author_sort	Puzi Jiang
title	Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models
title_short	Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models
title_full	Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models
title_fullStr	Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models
title_full_unstemmed	Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models
title_sort	metagenomic analysis of common intestinal diseases reveals relationships among microbial signatures and powers multidisease diagnostic models
publisher	American Society for Microbiology
publishDate	2021
url	https://doaj.org/article/978ae8e56d464405892e6379b6365232
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Metagenomic Analysis of Common Intestinal Diseases Reveals Relationships among Microbial Signatures and Powers Multidisease Diagnostic Models

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