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MicroPhenoDB Associates Metagenomic Data with Pathogenic Microbes, Microbial Core Genes, and Human Disease Phenotypes

Microbes play important roles in human health and disease. The interaction between microbes and hosts is a reciprocal relationship, which remains largely under-explored. Current computational resources lack manually and consistently curated data to connect metagenomic data to pathogenic microbes, mi...

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Detalles Bibliográficos
Autores principales: Yao, Guocai, Zhang, Wenliang, Yang, Minglei, Yang, Huan, Wang, Jianbo, Zhang, Haiyue, Wei, Lai, Xie, Zhi, Li, Weizhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377004/
https://www.ncbi.nlm.nih.gov/pubmed/33418085
http://dx.doi.org/10.1016/j.gpb.2020.11.001
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author Yao, Guocai
Zhang, Wenliang
Yang, Minglei
Yang, Huan
Wang, Jianbo
Zhang, Haiyue
Wei, Lai
Xie, Zhi
Li, Weizhong
author_facet Yao, Guocai
Zhang, Wenliang
Yang, Minglei
Yang, Huan
Wang, Jianbo
Zhang, Haiyue
Wei, Lai
Xie, Zhi
Li, Weizhong
author_sort Yao, Guocai
collection PubMed
description Microbes play important roles in human health and disease. The interaction between microbes and hosts is a reciprocal relationship, which remains largely under-explored. Current computational resources lack manually and consistently curated data to connect metagenomic data to pathogenic microbes, microbial core genes, and disease phenotypes. We developed the MicroPhenoDB database by manually curating and consistently integrating microbe-disease association data. MicroPhenoDB provides 5677 non-redundant associations between 1781 microbes and 542 human disease phenotypes across more than 22 human body sites. MicroPhenoDB also provides 696,934 relationships between 27,277 unique clade-specific core genes and 685 microbes. Disease phenotypes are classified and described using the Experimental Factor Ontology (EFO). A refined score model was developed to prioritize the associations based on evidential metrics. The sequence search option in MicroPhenoDB enables rapid identification of existing pathogenic microbes in samples without running the usual metagenomic data processing and assembly. MicroPhenoDB offers data browsing, searching, and visualization through user-friendly web interfaces and web service application programming interfaces. MicroPhenoDB is the first database platform to detail the relationships between pathogenic microbes, core genes, and disease phenotypes. It will accelerate metagenomic data analysis and assist studies in decoding microbes related to human diseases. MicroPhenoDB is available through http://www.liwzlab.cn/microphenodb and http://lilab2.sysu.edu.cn/microphenodb.
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spelling pubmed-83770042021-08-24 MicroPhenoDB Associates Metagenomic Data with Pathogenic Microbes, Microbial Core Genes, and Human Disease Phenotypes Yao, Guocai Zhang, Wenliang Yang, Minglei Yang, Huan Wang, Jianbo Zhang, Haiyue Wei, Lai Xie, Zhi Li, Weizhong Genomics Proteomics Bioinformatics Database Microbes play important roles in human health and disease. The interaction between microbes and hosts is a reciprocal relationship, which remains largely under-explored. Current computational resources lack manually and consistently curated data to connect metagenomic data to pathogenic microbes, microbial core genes, and disease phenotypes. We developed the MicroPhenoDB database by manually curating and consistently integrating microbe-disease association data. MicroPhenoDB provides 5677 non-redundant associations between 1781 microbes and 542 human disease phenotypes across more than 22 human body sites. MicroPhenoDB also provides 696,934 relationships between 27,277 unique clade-specific core genes and 685 microbes. Disease phenotypes are classified and described using the Experimental Factor Ontology (EFO). A refined score model was developed to prioritize the associations based on evidential metrics. The sequence search option in MicroPhenoDB enables rapid identification of existing pathogenic microbes in samples without running the usual metagenomic data processing and assembly. MicroPhenoDB offers data browsing, searching, and visualization through user-friendly web interfaces and web service application programming interfaces. MicroPhenoDB is the first database platform to detail the relationships between pathogenic microbes, core genes, and disease phenotypes. It will accelerate metagenomic data analysis and assist studies in decoding microbes related to human diseases. MicroPhenoDB is available through http://www.liwzlab.cn/microphenodb and http://lilab2.sysu.edu.cn/microphenodb. Elsevier 2020-12 2021-01-06 /pmc/articles/PMC8377004/ /pubmed/33418085 http://dx.doi.org/10.1016/j.gpb.2020.11.001 Text en © 2021 Beijing Institute of Genomics, Chinese Academy of Sciences and Genetics Society of China https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Database
Yao, Guocai
Zhang, Wenliang
Yang, Minglei
Yang, Huan
Wang, Jianbo
Zhang, Haiyue
Wei, Lai
Xie, Zhi
Li, Weizhong
MicroPhenoDB Associates Metagenomic Data with Pathogenic Microbes, Microbial Core Genes, and Human Disease Phenotypes
title MicroPhenoDB Associates Metagenomic Data with Pathogenic Microbes, Microbial Core Genes, and Human Disease Phenotypes
title_full MicroPhenoDB Associates Metagenomic Data with Pathogenic Microbes, Microbial Core Genes, and Human Disease Phenotypes
title_fullStr MicroPhenoDB Associates Metagenomic Data with Pathogenic Microbes, Microbial Core Genes, and Human Disease Phenotypes
title_full_unstemmed MicroPhenoDB Associates Metagenomic Data with Pathogenic Microbes, Microbial Core Genes, and Human Disease Phenotypes
title_short MicroPhenoDB Associates Metagenomic Data with Pathogenic Microbes, Microbial Core Genes, and Human Disease Phenotypes
title_sort microphenodb associates metagenomic data with pathogenic microbes, microbial core genes, and human disease phenotypes
topic Database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8377004/
https://www.ncbi.nlm.nih.gov/pubmed/33418085
http://dx.doi.org/10.1016/j.gpb.2020.11.001
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