Cargando…
Evaluation of different mucosal microbiota leads to gut microbiota-based prediction of type 1 diabetes in NOD mice
Type 1 diabetes (T1D) is a progressive autoimmune disease in which the insulin-producing beta cells are destroyed by auto-reactive T cells. Recent studies suggest that microbiota are closely associated with disease development. We studied gut, oral and vaginal microbiota longitudinally in non-obese...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193974/ https://www.ncbi.nlm.nih.gov/pubmed/30337545 http://dx.doi.org/10.1038/s41598-018-33571-z |
_version_ | 1783364140846284800 |
---|---|
author | Hu, Youjia Peng, Jian Li, Fangyong Wong, F. Susan Wen, Li |
author_facet | Hu, Youjia Peng, Jian Li, Fangyong Wong, F. Susan Wen, Li |
author_sort | Hu, Youjia |
collection | PubMed |
description | Type 1 diabetes (T1D) is a progressive autoimmune disease in which the insulin-producing beta cells are destroyed by auto-reactive T cells. Recent studies suggest that microbiota are closely associated with disease development. We studied gut, oral and vaginal microbiota longitudinally in non-obese diabetic (NOD) mice. We showed that the composition of microbiota is very different at the different mucosal sites and between young and adult mice. Gut microbiota are more diverse than oral or vaginal microbiota and the changes were more evident in the mice before and after onset of diabetes. Using alpha-diversity, Gram-positive/Gram-negative ratio as well as the relative abundance of Bacteroidetes and Erysipelotrichaceae in the gut microbiota, at 8 weeks of age, we formulated a predictive algorithm for T1D development in a cohort of 63 female NOD mice. Using this algorithm, we obtained 80% accuracy of prediction of diabetes onset, in two independent experiments, totaling 29 mice, with Area Under the Curve of 0.776 by ROC analysis. Interestingly, we did not find differences in peripheral blood mononuclear cells of the mice at 8 weeks of age, regardless of later diabetes development. Our results suggest that the algorithm could potentially be used in early prediction of future T1D development. |
format | Online Article Text |
id | pubmed-6193974 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-61939742018-10-24 Evaluation of different mucosal microbiota leads to gut microbiota-based prediction of type 1 diabetes in NOD mice Hu, Youjia Peng, Jian Li, Fangyong Wong, F. Susan Wen, Li Sci Rep Article Type 1 diabetes (T1D) is a progressive autoimmune disease in which the insulin-producing beta cells are destroyed by auto-reactive T cells. Recent studies suggest that microbiota are closely associated with disease development. We studied gut, oral and vaginal microbiota longitudinally in non-obese diabetic (NOD) mice. We showed that the composition of microbiota is very different at the different mucosal sites and between young and adult mice. Gut microbiota are more diverse than oral or vaginal microbiota and the changes were more evident in the mice before and after onset of diabetes. Using alpha-diversity, Gram-positive/Gram-negative ratio as well as the relative abundance of Bacteroidetes and Erysipelotrichaceae in the gut microbiota, at 8 weeks of age, we formulated a predictive algorithm for T1D development in a cohort of 63 female NOD mice. Using this algorithm, we obtained 80% accuracy of prediction of diabetes onset, in two independent experiments, totaling 29 mice, with Area Under the Curve of 0.776 by ROC analysis. Interestingly, we did not find differences in peripheral blood mononuclear cells of the mice at 8 weeks of age, regardless of later diabetes development. Our results suggest that the algorithm could potentially be used in early prediction of future T1D development. Nature Publishing Group UK 2018-10-18 /pmc/articles/PMC6193974/ /pubmed/30337545 http://dx.doi.org/10.1038/s41598-018-33571-z Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Hu, Youjia Peng, Jian Li, Fangyong Wong, F. Susan Wen, Li Evaluation of different mucosal microbiota leads to gut microbiota-based prediction of type 1 diabetes in NOD mice |
title | Evaluation of different mucosal microbiota leads to gut microbiota-based prediction of type 1 diabetes in NOD mice |
title_full | Evaluation of different mucosal microbiota leads to gut microbiota-based prediction of type 1 diabetes in NOD mice |
title_fullStr | Evaluation of different mucosal microbiota leads to gut microbiota-based prediction of type 1 diabetes in NOD mice |
title_full_unstemmed | Evaluation of different mucosal microbiota leads to gut microbiota-based prediction of type 1 diabetes in NOD mice |
title_short | Evaluation of different mucosal microbiota leads to gut microbiota-based prediction of type 1 diabetes in NOD mice |
title_sort | evaluation of different mucosal microbiota leads to gut microbiota-based prediction of type 1 diabetes in nod mice |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6193974/ https://www.ncbi.nlm.nih.gov/pubmed/30337545 http://dx.doi.org/10.1038/s41598-018-33571-z |
work_keys_str_mv | AT huyoujia evaluationofdifferentmucosalmicrobiotaleadstogutmicrobiotabasedpredictionoftype1diabetesinnodmice AT pengjian evaluationofdifferentmucosalmicrobiotaleadstogutmicrobiotabasedpredictionoftype1diabetesinnodmice AT lifangyong evaluationofdifferentmucosalmicrobiotaleadstogutmicrobiotabasedpredictionoftype1diabetesinnodmice AT wongfsusan evaluationofdifferentmucosalmicrobiotaleadstogutmicrobiotabasedpredictionoftype1diabetesinnodmice AT wenli evaluationofdifferentmucosalmicrobiotaleadstogutmicrobiotabasedpredictionoftype1diabetesinnodmice |