Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease

Dysregulation of the gut microbiome has been implicated in the progression of many diseases. This study explored the role of microbial and metabolic signatures, and their interaction between the Human inflammatory bowel disease (IBD) and healthy controls (HCs) based on the combination of machine lea...

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Autor principal:	Guangcai Liang
Formato:	article
Lenguaje:	EN
Publicado:	KeAi Communications Co., Ltd. 2021
Materias:	Inflammatory bowel disease Gut microbiome Metabolic pathways Machine learning Diagnosis Biotechnology TP248.13-248.65 Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/6d99c5297f2a4fb6908f8821b502c9d6
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spelling	oai:doaj.org-article:6d99c5297f2a4fb6908f8821b502c9d62021-11-12T04:42:24ZAltered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease2405-805X10.1016/j.synbio.2021.10.003https://doaj.org/article/6d99c5297f2a4fb6908f8821b502c9d62021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2405805X21000661https://doaj.org/toc/2405-805XDysregulation of the gut microbiome has been implicated in the progression of many diseases. This study explored the role of microbial and metabolic signatures, and their interaction between the Human inflammatory bowel disease (IBD) and healthy controls (HCs) based on the combination of machine learning and traditional statistical analysis, using data collected from the Human Microbiome Project (HMP) and the Integrative Human Microbiome Project (iHMP). It was showed that the microbial and metabolic signatures of IBD patients were significantly different from those of HCs. Compared to HCs, IBD subjects were characterized by 25 enriched species and 6 depleted species. Furthermore, a total of 17 discriminative pathways were identified between the IBD and HC groups. Those differential pathways were mainly involved in amino acid, nucleotide biosynthesis, and carbohydrate degradation. Notably, co-occurrence network analysis revealed that non-predominant bacteria Ruminococcus_obeum and predominant bacteria Faecalibacterium_prausnitzii formed the same broad and strong co-occurring relationships with pathways. Moreover, the essay identified a combinatorial marker panel that could distinguish IBD from HCs. Receiver Operating Characteristic (ROC) and Decision Curve Analysis (DCA) confirmed the high accuracy (AUC = 0.966) and effectiveness of the model. Meanwhile, an independent cohort used for external validation also showed the identical high efficacy (AUC = 0.835). These findings showed that the gut microbes may be relevant to the pathogenesis and pathophysiology, and offer universal utility as a non-invasive diagnostic test in IBD.Guangcai LiangKeAi Communications Co., Ltd.articleInflammatory bowel diseaseGut microbiomeMetabolic pathwaysMachine learningDiagnosisBiotechnologyTP248.13-248.65Biology (General)QH301-705.5ENSynthetic and Systems Biotechnology, Vol 6, Iss 4, Pp 377-383 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Inflammatory bowel disease Gut microbiome Metabolic pathways Machine learning Diagnosis Biotechnology TP248.13-248.65 Biology (General) QH301-705.5
spellingShingle	Inflammatory bowel disease Gut microbiome Metabolic pathways Machine learning Diagnosis Biotechnology TP248.13-248.65 Biology (General) QH301-705.5 Guangcai Liang Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease
description	Dysregulation of the gut microbiome has been implicated in the progression of many diseases. This study explored the role of microbial and metabolic signatures, and their interaction between the Human inflammatory bowel disease (IBD) and healthy controls (HCs) based on the combination of machine learning and traditional statistical analysis, using data collected from the Human Microbiome Project (HMP) and the Integrative Human Microbiome Project (iHMP). It was showed that the microbial and metabolic signatures of IBD patients were significantly different from those of HCs. Compared to HCs, IBD subjects were characterized by 25 enriched species and 6 depleted species. Furthermore, a total of 17 discriminative pathways were identified between the IBD and HC groups. Those differential pathways were mainly involved in amino acid, nucleotide biosynthesis, and carbohydrate degradation. Notably, co-occurrence network analysis revealed that non-predominant bacteria Ruminococcus_obeum and predominant bacteria Faecalibacterium_prausnitzii formed the same broad and strong co-occurring relationships with pathways. Moreover, the essay identified a combinatorial marker panel that could distinguish IBD from HCs. Receiver Operating Characteristic (ROC) and Decision Curve Analysis (DCA) confirmed the high accuracy (AUC = 0.966) and effectiveness of the model. Meanwhile, an independent cohort used for external validation also showed the identical high efficacy (AUC = 0.835). These findings showed that the gut microbes may be relevant to the pathogenesis and pathophysiology, and offer universal utility as a non-invasive diagnostic test in IBD.
format	article
author	Guangcai Liang
author_facet	Guangcai Liang
author_sort	Guangcai Liang
title	Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease
title_short	Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease
title_full	Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease
title_fullStr	Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease
title_full_unstemmed	Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease
title_sort	altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease
publisher	KeAi Communications Co., Ltd.
publishDate	2021
url	https://doaj.org/article/6d99c5297f2a4fb6908f8821b502c9d6
work_keys_str_mv	AT guangcailiang alteredgutbacterialandmetabolicsignaturesandtheirinteractionininflammatoryboweldisease
_version_	1718431236078174208

Altered gut bacterial and metabolic signatures and their interaction in inflammatory bowel disease

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