Ecology-guided prediction of cross-feeding interactions in the human gut microbiome

Understanding a complex microbial ecosystem such as the human gut microbiome requires information about both microbial species and the metabolites they produce and secrete. Here, the authors propose an ecology-based computational method to predict hundreds of new experimentally untested cross-feedin...

Full description

Bibliographic Details
Main Authors:	Akshit Goyal, Tong Wang, Veronika Dubinkina, Sergei Maslov
Format:	Article
Language:	English
Published:	Nature Publishing Group 2021-02-01
Series:	Nature Communications
Online Access:	https://doi.org/10.1038/s41467-021-21586-6

id	doaj-b6e3f2f488c24fc98ae27509782db76e
record_format	Article
spelling	doaj-b6e3f2f488c24fc98ae27509782db76e2021-03-11T11:31:32ZengNature Publishing GroupNature Communications2041-17232021-02-0112111010.1038/s41467-021-21586-6Ecology-guided prediction of cross-feeding interactions in the human gut microbiomeAkshit Goyal0Tong Wang1Veronika Dubinkina2Sergei Maslov3Physics of Living Systems, Department of Physics, Massachusetts Institute of TechnologyDepartment of Physics, University of Illinois at Urbana-ChampaignDepartment of Bioengineering and Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-ChampaignDepartment of Physics, University of Illinois at Urbana-ChampaignUnderstanding a complex microbial ecosystem such as the human gut microbiome requires information about both microbial species and the metabolites they produce and secrete. Here, the authors propose an ecology-based computational method to predict hundreds of new experimentally untested cross-feeding interactions in the human gut microbiome.https://doi.org/10.1038/s41467-021-21586-6
collection	DOAJ
language	English
format	Article
sources	DOAJ
author	Akshit Goyal Tong Wang Veronika Dubinkina Sergei Maslov
spellingShingle	Akshit Goyal Tong Wang Veronika Dubinkina Sergei Maslov Ecology-guided prediction of cross-feeding interactions in the human gut microbiome Nature Communications
author_facet	Akshit Goyal Tong Wang Veronika Dubinkina Sergei Maslov
author_sort	Akshit Goyal
title	Ecology-guided prediction of cross-feeding interactions in the human gut microbiome
title_short	Ecology-guided prediction of cross-feeding interactions in the human gut microbiome
title_full	Ecology-guided prediction of cross-feeding interactions in the human gut microbiome
title_fullStr	Ecology-guided prediction of cross-feeding interactions in the human gut microbiome
title_full_unstemmed	Ecology-guided prediction of cross-feeding interactions in the human gut microbiome
title_sort	ecology-guided prediction of cross-feeding interactions in the human gut microbiome
publisher	Nature Publishing Group
series	Nature Communications
issn	2041-1723
publishDate	2021-02-01
description	Understanding a complex microbial ecosystem such as the human gut microbiome requires information about both microbial species and the metabolites they produce and secrete. Here, the authors propose an ecology-based computational method to predict hundreds of new experimentally untested cross-feeding interactions in the human gut microbiome.
url	https://doi.org/10.1038/s41467-021-21586-6
work_keys_str_mv	AT akshitgoyal ecologyguidedpredictionofcrossfeedinginteractionsinthehumangutmicrobiome AT tongwang ecologyguidedpredictionofcrossfeedinginteractionsinthehumangutmicrobiome AT veronikadubinkina ecologyguidedpredictionofcrossfeedinginteractionsinthehumangutmicrobiome AT sergeimaslov ecologyguidedpredictionofcrossfeedinginteractionsinthehumangutmicrobiome
_version_	1724225529247170560

Ecology-guided prediction of cross-feeding interactions in the human gut microbiome

Similar Items