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...

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Published in	PloS one Vol. 6; no. 10; p. e25792
Main Authors	Brown, Christopher T., Davis-Richardson, Austin G., Giongo, Adriana, Gano, Kelsey A., Crabb, David B., Mukherjee, Nabanita, Casella, George, Drew, Jennifer C., Ilonen, Jorma, Knip, Mikael, Hyöty, Heikki, Veijola, Riitta, Simell, Tuula, Simell, Olli, Neu, Josef, Wasserfall, Clive H., Schatz, Desmond, Atkinson, Mark A., Triplett, Eric W.
Format	Journal Article
Language	English
Published	United States Public Library of Science 17.10.2011 Public Library of Science (PLoS)
Subjects	Aberration Aerobic respiration Amino acids Autoantibodies Autoimmune diseases Autoimmunity Autoimmunity - genetics Bacteria Bacteroidetes Biochemistry Biodegradation Biology Bowel disease Butyrates - metabolism Carbohydrate metabolism Carbohydrates Case-Control Studies Colon Comparative analysis Consortia Crohn's disease Crohns disease Data mining Data processing Databases, Nucleic Acid Deoxyribonucleic acid Diabetes Diabetes mellitus Diabetes Mellitus, Type 1 - etiology Diabetes Mellitus, Type 1 - immunology Digestive system DNA Fatty acids Fatty Acids, Volatile - biosynthesis Firmicutes Flagella Gastrointestinal Tract - microbiology Genes Hospitals Humans Immunology Intestinal microflora Kinases Laboratories Lactic acid Lactobacillus Medicine Metabolism Metagenome - genetics Metagenomics - methods Microbiota Mucin Mucins - metabolism Open reading frames Pediatrics Phages Physiological aspects Physiology Prophages Protein metabolism Protein turnover RNA RNA, Ribosomal, 16S Rodents rRNA 16S Science Small intestine Statistical analysis Statistical methods Sulfur Synthesis Type 1 diabetes Florida United States > US
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Abstract	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.
AbstractList	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. 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.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.
Audience	Academic
Author	Veijola, Riitta Schatz, Desmond Neu, Josef Drew, Jennifer C. Atkinson, Mark A. Knip, Mikael Wasserfall, Clive H. Triplett, Eric W. Giongo, Adriana Crabb, David B. Casella, George Davis-Richardson, Austin G. Simell, Tuula Simell, Olli Gano, Kelsey A. Hyöty, Heikki Brown, Christopher T. Mukherjee, Nabanita Ilonen, Jorma
AuthorAffiliation	7 Department of Pediatrics, Turku University Hospital, Turku, Finland 1 Department of Microbiology and Cell Science, University of Florida, Gainesville, Florida, United States of America 8 Department of Pediatrics, University of Florida, Gainesville, Florida, United States of America 2 Department of Statistics, University of Florida, Gainesville, Florida, United States of America East Carolina University School of Medicine, United States of America 4 Hospital for Children and Adolescents, University of Helsinki, Helsinki, Finland 5 Department of Virology, Tampere University Hospital, Tampere, Finland 6 Department of Pediatrics, University of Oulu, Oulu, Finland 9 Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, Florida, United States of America 3 Department of Clinical Microbiology, University of Kuopio, Kuopio, Finland
AuthorAffiliation_xml	– name: 3 Department of Clinical Microbiology, University of Kuopio, Kuopio, Finland – name: 4 Hospital for Children and Adolescents, University of Helsinki, Helsinki, Finland – name: 8 Department of Pediatrics, University of Florida, Gainesville, Florida, United States of America – name: East Carolina University School of Medicine, United States of America – name: 2 Department of Statistics, University of Florida, Gainesville, Florida, United States of America – name: 7 Department of Pediatrics, Turku University Hospital, Turku, Finland – name: 5 Department of Virology, Tampere University Hospital, Tampere, Finland – name: 6 Department of Pediatrics, University of Oulu, Oulu, Finland – name: 9 Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, Florida, United States of America – name: 1 Department of Microbiology and Cell Science, University of Florida, Gainesville, Florida, United States of America
Author_xml	– sequence: 1 givenname: Christopher T. surname: Brown fullname: Brown, Christopher T. – sequence: 2 givenname: Austin G. surname: Davis-Richardson fullname: Davis-Richardson, Austin G. – sequence: 3 givenname: Adriana surname: Giongo fullname: Giongo, Adriana – sequence: 4 givenname: Kelsey A. surname: Gano fullname: Gano, Kelsey A. – sequence: 5 givenname: David B. surname: Crabb fullname: Crabb, David B. – sequence: 6 givenname: Nabanita surname: Mukherjee fullname: Mukherjee, Nabanita – sequence: 7 givenname: George surname: Casella fullname: Casella, George – sequence: 8 givenname: Jennifer C. surname: Drew fullname: Drew, Jennifer C. – sequence: 9 givenname: Jorma surname: Ilonen fullname: Ilonen, Jorma – sequence: 10 givenname: Mikael surname: Knip fullname: Knip, Mikael – sequence: 11 givenname: Heikki surname: Hyöty fullname: Hyöty, Heikki – sequence: 12 givenname: Riitta surname: Veijola fullname: Veijola, Riitta – sequence: 13 givenname: Tuula surname: Simell fullname: Simell, Tuula – sequence: 14 givenname: Olli surname: Simell fullname: Simell, Olli – sequence: 15 givenname: Josef surname: Neu fullname: Neu, Josef – sequence: 16 givenname: Clive H. surname: Wasserfall fullname: Wasserfall, Clive H. – sequence: 17 givenname: Desmond surname: Schatz fullname: Schatz, Desmond – sequence: 18 givenname: Mark A. surname: Atkinson fullname: Atkinson, Mark A. – sequence: 19 givenname: Eric W. surname: Triplett fullname: Triplett, Eric W.
BackLink	https://www.ncbi.nlm.nih.gov/pubmed/22043294$$D View this record in MEDLINE/PubMed
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ContentType	Journal Article
Copyright	COPYRIGHT 2011 Public Library of Science 2011 Brown et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Brown et al. 2011
Copyright_xml	– notice: COPYRIGHT 2011 Public Library of Science – notice: 2011 Brown et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: https://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. – notice: Brown et al. 2011
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Notes	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Conceived and designed the experiments: CTB AGD-R AG KAG DBC JI MK HH RV TS OS JN CHW DS MAA EWT. Performed the experiments: CTB ABD-R AG KAG DBC EWT. Analyzed the data: CTB AGD-R AG NM GC EWT. Contributed reagents/materials/analysis tools: CTB AGD-R DBC JI MK HH RV TS OS DS. Wrote the paper: CTB AGD-R AG JCD JN MAA EWT.
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Snippet	Recent studies have suggested a bacterial role in the development of autoimmune disorders including type 1 diabetes (T1D). Over 30 billion nucleotide bases of...
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SubjectTerms	Aberration Aerobic respiration Amino acids Autoantibodies Autoimmune diseases Autoimmunity Autoimmunity - genetics Bacteria Bacteroidetes Biochemistry Biodegradation Biology Bowel disease Butyrates - metabolism Carbohydrate metabolism Carbohydrates Case-Control Studies Colon Comparative analysis Consortia Crohn's disease Crohns disease Data mining Data processing Databases, Nucleic Acid Deoxyribonucleic acid Diabetes Diabetes mellitus Diabetes Mellitus, Type 1 - etiology Diabetes Mellitus, Type 1 - immunology Digestive system DNA Fatty acids Fatty Acids, Volatile - biosynthesis Firmicutes Flagella Gastrointestinal Tract - microbiology Genes Hospitals Humans Immunology Intestinal microflora Kinases Laboratories Lactic acid Lactobacillus Medicine Metabolism Metagenome - genetics Metagenomics - methods Microbiota Mucin Mucins - metabolism Open reading frames Pediatrics Phages Physiological aspects Physiology Prophages Protein metabolism Protein turnover RNA RNA, Ribosomal, 16S Rodents rRNA 16S Science Small intestine Statistical analysis Statistical methods Sulfur Synthesis Type 1 diabetes
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Title	Gut Microbiome Metagenomics Analysis Suggests a Functional Model for the Development of Autoimmunity for Type 1 Diabetes
URI	https://www.ncbi.nlm.nih.gov/pubmed/22043294 https://www.proquest.com/docview/1310006419 https://www.proquest.com/docview/901642624 https://pubmed.ncbi.nlm.nih.gov/PMC3197175 https://doaj.org/article/e4052e7814af4d9680f764624ed81c2e http://dx.doi.org/10.1371/journal.pone.0025792
Volume	6
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