Gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes.

Recent studies have suggested a bacterial role in the development of autoimmune disorders including type 1 diabetes (T1D). Over 30 billion nucleotide bases of Illumina shotgun metagenomic data were analyzed from stool samples collected from four pairs of matched T1D case-control subjects collected a...

Full description

Bibliographic Details
Main Authors: Christopher T Brown, Austin G Davis-Richardson, Adriana Giongo, Kelsey A Gano, David B Crabb, Nabanita Mukherjee, George Casella, Jennifer C Drew, Jorma Ilonen, Mikael Knip, Heikki Hyöty, Riitta Veijola, Tuula Simell, Olli Simell, Josef Neu, Clive H Wasserfall, Desmond Schatz, Mark A Atkinson, Eric W Triplett
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2011-01-01
Series:PLoS ONE
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22043294/pdf/?tool=EBI
id doaj-e4052e7814af4d9680f764624ed81c2e
record_format Article
spelling doaj-e4052e7814af4d9680f764624ed81c2e2021-03-04T01:27:50ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-01-01610e2579210.1371/journal.pone.0025792Gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes.Christopher T BrownAustin G Davis-RichardsonAdriana GiongoKelsey A GanoDavid B CrabbNabanita MukherjeeGeorge CasellaJennifer C DrewJorma IlonenMikael KnipHeikki HyötyRiitta VeijolaTuula SimellOlli SimellJosef NeuClive H WasserfallDesmond SchatzMark A AtkinsonEric W TriplettRecent studies have suggested a bacterial role in the development of autoimmune disorders including type 1 diabetes (T1D). Over 30 billion nucleotide bases of Illumina shotgun metagenomic data were analyzed from stool samples collected from four pairs of matched T1D case-control subjects collected at the time of the development of T1D associated autoimmunity (i.e., autoantibodies). From these, approximately one million open reading frames were predicted and compared to the SEED protein database. Of the 3,849 functions identified in these samples, 144 and 797 were statistically more prevalent in cases and controls, respectively. Genes involved in carbohydrate metabolism, adhesions, motility, phages, prophages, sulfur metabolism, and stress responses were more abundant in cases while genes with roles in DNA and protein metabolism, aerobic respiration, and amino acid synthesis were more common in controls. These data suggest that increased adhesion and flagella synthesis in autoimmune subjects may be involved in triggering a T1D associated autoimmune response. Extensive differences in metabolic potential indicate that autoimmune subjects have a functionally aberrant microbiome. Mining 16S rRNA data from these datasets showed a higher proportion of butyrate-producing and mucin-degrading bacteria in controls compared to cases, while those bacteria that produce short chain fatty acids other than butyrate were higher in cases. Thus, a key rate-limiting step in butyrate synthesis is more abundant in controls. These data suggest that a consortium of lactate- and butyrate-producing bacteria in a healthy gut induce a sufficient amount of mucin synthesis to maintain gut integrity. In contrast, non-butyrate-producing lactate-utilizing bacteria prevent optimal mucin synthesis, as identified in autoimmune subjects.https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22043294/pdf/?tool=EBI
collection DOAJ
language English
format Article
sources DOAJ
author Christopher T Brown
Austin G Davis-Richardson
Adriana Giongo
Kelsey A Gano
David B Crabb
Nabanita Mukherjee
George Casella
Jennifer C Drew
Jorma Ilonen
Mikael Knip
Heikki Hyöty
Riitta Veijola
Tuula Simell
Olli Simell
Josef Neu
Clive H Wasserfall
Desmond Schatz
Mark A Atkinson
Eric W Triplett
spellingShingle Christopher T Brown
Austin G Davis-Richardson
Adriana Giongo
Kelsey A Gano
David B Crabb
Nabanita Mukherjee
George Casella
Jennifer C Drew
Jorma Ilonen
Mikael Knip
Heikki Hyöty
Riitta Veijola
Tuula Simell
Olli Simell
Josef Neu
Clive H Wasserfall
Desmond Schatz
Mark A Atkinson
Eric W Triplett
Gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes.
PLoS ONE
author_facet Christopher T Brown
Austin G Davis-Richardson
Adriana Giongo
Kelsey A Gano
David B Crabb
Nabanita Mukherjee
George Casella
Jennifer C Drew
Jorma Ilonen
Mikael Knip
Heikki Hyöty
Riitta Veijola
Tuula Simell
Olli Simell
Josef Neu
Clive H Wasserfall
Desmond Schatz
Mark A Atkinson
Eric W Triplett
author_sort Christopher T Brown
title Gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes.
title_short Gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes.
title_full Gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes.
title_fullStr Gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes.
title_full_unstemmed Gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes.
title_sort gut microbiome metagenomics analysis suggests a functional model for the development of autoimmunity for type 1 diabetes.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2011-01-01
description Recent studies have suggested a bacterial role in the development of autoimmune disorders including type 1 diabetes (T1D). Over 30 billion nucleotide bases of Illumina shotgun metagenomic data were analyzed from stool samples collected from four pairs of matched T1D case-control subjects collected at the time of the development of T1D associated autoimmunity (i.e., autoantibodies). From these, approximately one million open reading frames were predicted and compared to the SEED protein database. Of the 3,849 functions identified in these samples, 144 and 797 were statistically more prevalent in cases and controls, respectively. Genes involved in carbohydrate metabolism, adhesions, motility, phages, prophages, sulfur metabolism, and stress responses were more abundant in cases while genes with roles in DNA and protein metabolism, aerobic respiration, and amino acid synthesis were more common in controls. These data suggest that increased adhesion and flagella synthesis in autoimmune subjects may be involved in triggering a T1D associated autoimmune response. Extensive differences in metabolic potential indicate that autoimmune subjects have a functionally aberrant microbiome. Mining 16S rRNA data from these datasets showed a higher proportion of butyrate-producing and mucin-degrading bacteria in controls compared to cases, while those bacteria that produce short chain fatty acids other than butyrate were higher in cases. Thus, a key rate-limiting step in butyrate synthesis is more abundant in controls. These data suggest that a consortium of lactate- and butyrate-producing bacteria in a healthy gut induce a sufficient amount of mucin synthesis to maintain gut integrity. In contrast, non-butyrate-producing lactate-utilizing bacteria prevent optimal mucin synthesis, as identified in autoimmune subjects.
url https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/22043294/pdf/?tool=EBI
work_keys_str_mv AT christophertbrown gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT austingdavisrichardson gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT adrianagiongo gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT kelseyagano gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT davidbcrabb gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT nabanitamukherjee gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT georgecasella gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT jennifercdrew gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT jormailonen gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT mikaelknip gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT heikkihyoty gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT riittaveijola gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT tuulasimell gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT ollisimell gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT josefneu gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT clivehwasserfall gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT desmondschatz gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT markaatkinson gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
AT ericwtriplett gutmicrobiomemetagenomicsanalysissuggestsafunctionalmodelforthedevelopmentofautoimmunityfortype1diabetes
_version_ 1714809540403265536