Cargando…

Achieving pan-microbiome biological insights via the dbBact knowledge base

16S rRNA amplicon sequencing provides a relatively inexpensive culture-independent method for studying microbial communities. Although thousands of such studies have examined diverse habitats, it is difficult for researchers to use this vast trove of experiments when interpreting their own findings...

Descripción completa

Detalles Bibliográficos
Autores principales: Amir, Amnon, Ozel, Eitan, Haberman, Yael, Shental, Noam
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359611/
https://www.ncbi.nlm.nih.gov/pubmed/37326027
http://dx.doi.org/10.1093/nar/gkad527
_version_ 1785075922989219840
author Amir, Amnon
Ozel, Eitan
Haberman, Yael
Shental, Noam
author_facet Amir, Amnon
Ozel, Eitan
Haberman, Yael
Shental, Noam
author_sort Amir, Amnon
collection PubMed
description 16S rRNA amplicon sequencing provides a relatively inexpensive culture-independent method for studying microbial communities. Although thousands of such studies have examined diverse habitats, it is difficult for researchers to use this vast trove of experiments when interpreting their own findings in a broader context. To bridge this gap, we introduce dbBact – a novel pan-microbiome resource. dbBact combines manually curated information from studies across diverse habitats, creating a collaborative central repository of 16S rRNA amplicon sequence variants (ASVs), which are assigned multiple ontology-based terms. To date dbBact contains information from more than 1000 studies, which include 1500000 associations between 360000 ASVs and 6500 ontology terms. Importantly, dbBact offers a set of computational tools allowing users to easily query their own datasets against the database. To demonstrate how dbBact augments standard microbiome analysis we selected 16 published papers, and reanalyzed their data via dbBact. We uncovered novel inter-host similarities, potential intra-host sources of bacteria, commonalities across different diseases and lower host-specificity in disease-associated bacteria. We also demonstrate the ability to detect environmental sources, reagent-borne contaminants, and identify potential cross-sample contaminations. These analyses demonstrate how combining information across multiple studies and over diverse habitats leads to better understanding of underlying biological processes.
format Online
Article
Text
id pubmed-10359611
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-103596112023-07-22 Achieving pan-microbiome biological insights via the dbBact knowledge base Amir, Amnon Ozel, Eitan Haberman, Yael Shental, Noam Nucleic Acids Res Data Resources and Analyses 16S rRNA amplicon sequencing provides a relatively inexpensive culture-independent method for studying microbial communities. Although thousands of such studies have examined diverse habitats, it is difficult for researchers to use this vast trove of experiments when interpreting their own findings in a broader context. To bridge this gap, we introduce dbBact – a novel pan-microbiome resource. dbBact combines manually curated information from studies across diverse habitats, creating a collaborative central repository of 16S rRNA amplicon sequence variants (ASVs), which are assigned multiple ontology-based terms. To date dbBact contains information from more than 1000 studies, which include 1500000 associations between 360000 ASVs and 6500 ontology terms. Importantly, dbBact offers a set of computational tools allowing users to easily query their own datasets against the database. To demonstrate how dbBact augments standard microbiome analysis we selected 16 published papers, and reanalyzed their data via dbBact. We uncovered novel inter-host similarities, potential intra-host sources of bacteria, commonalities across different diseases and lower host-specificity in disease-associated bacteria. We also demonstrate the ability to detect environmental sources, reagent-borne contaminants, and identify potential cross-sample contaminations. These analyses demonstrate how combining information across multiple studies and over diverse habitats leads to better understanding of underlying biological processes. Oxford University Press 2023-06-16 /pmc/articles/PMC10359611/ /pubmed/37326027 http://dx.doi.org/10.1093/nar/gkad527 Text en © The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Data Resources and Analyses
Amir, Amnon
Ozel, Eitan
Haberman, Yael
Shental, Noam
Achieving pan-microbiome biological insights via the dbBact knowledge base
title Achieving pan-microbiome biological insights via the dbBact knowledge base
title_full Achieving pan-microbiome biological insights via the dbBact knowledge base
title_fullStr Achieving pan-microbiome biological insights via the dbBact knowledge base
title_full_unstemmed Achieving pan-microbiome biological insights via the dbBact knowledge base
title_short Achieving pan-microbiome biological insights via the dbBact knowledge base
title_sort achieving pan-microbiome biological insights via the dbbact knowledge base
topic Data Resources and Analyses
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10359611/
https://www.ncbi.nlm.nih.gov/pubmed/37326027
http://dx.doi.org/10.1093/nar/gkad527
work_keys_str_mv AT amiramnon achievingpanmicrobiomebiologicalinsightsviathedbbactknowledgebase
AT ozeleitan achievingpanmicrobiomebiologicalinsightsviathedbbactknowledgebase
AT habermanyael achievingpanmicrobiomebiologicalinsightsviathedbbactknowledgebase
AT shentalnoam achievingpanmicrobiomebiologicalinsightsviathedbbactknowledgebase