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Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment
BACKGROUND: Colonization by the pathogen Clostridium difficile often occurs in the background of a disrupted microbial community. Identifying specific organisms conferring resistance to invasion by C. difficile is desirable because diagnostic and therapeutic strategies based on the human microbiota...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5684761/ https://www.ncbi.nlm.nih.gov/pubmed/29132405 http://dx.doi.org/10.1186/s40168-017-0368-1 |
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author | Pakpour, Sepideh Bhanvadia, Amit Zhu, Roger Amarnani, Abhimanyu Gibbons, Sean M. Gurry, Thomas Alm, Eric J. Martello, Laura A. |
author_facet | Pakpour, Sepideh Bhanvadia, Amit Zhu, Roger Amarnani, Abhimanyu Gibbons, Sean M. Gurry, Thomas Alm, Eric J. Martello, Laura A. |
author_sort | Pakpour, Sepideh |
collection | PubMed |
description | BACKGROUND: Colonization by the pathogen Clostridium difficile often occurs in the background of a disrupted microbial community. Identifying specific organisms conferring resistance to invasion by C. difficile is desirable because diagnostic and therapeutic strategies based on the human microbiota have the potential to provide more precision to the management and treatment of Clostridium difficile infection (CDI) and its recurrence. METHODS: We conducted a longitudinal study of adult patients diagnosed with their first CDI. We investigated the dynamics of the gut microbiota during antibiotic treatment, and we used microbial or demographic features at the time of diagnosis, or after treatment, to predict CDI recurrence. To check the validity of the predictions, a meta-analysis using a previously published dataset was performed. RESULTS: We observed that patients’ microbiota “before” antibiotic treatment was predictive of disease relapse, but surprisingly, post-antibiotic microbial community is indistinguishable between patients that recur or not. At the individual OTU level, we identified Veillonella dispar as a candidate organism for preventing CDI recurrence; however, we did not detect a corresponding signal in the conducted meta-analysis. CONCLUSION: Although in our patient population, a candidate organism was identified for negatively predicting CDI recurrence, results suggest the need for larger cohort studies that include patients with diverse demographic characteristics to generalize species that robustly confer colonization resistance against C. difficile and accurately predict disease relapse. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40168-017-0368-1) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5684761 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-56847612017-11-20 Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment Pakpour, Sepideh Bhanvadia, Amit Zhu, Roger Amarnani, Abhimanyu Gibbons, Sean M. Gurry, Thomas Alm, Eric J. Martello, Laura A. Microbiome Research BACKGROUND: Colonization by the pathogen Clostridium difficile often occurs in the background of a disrupted microbial community. Identifying specific organisms conferring resistance to invasion by C. difficile is desirable because diagnostic and therapeutic strategies based on the human microbiota have the potential to provide more precision to the management and treatment of Clostridium difficile infection (CDI) and its recurrence. METHODS: We conducted a longitudinal study of adult patients diagnosed with their first CDI. We investigated the dynamics of the gut microbiota during antibiotic treatment, and we used microbial or demographic features at the time of diagnosis, or after treatment, to predict CDI recurrence. To check the validity of the predictions, a meta-analysis using a previously published dataset was performed. RESULTS: We observed that patients’ microbiota “before” antibiotic treatment was predictive of disease relapse, but surprisingly, post-antibiotic microbial community is indistinguishable between patients that recur or not. At the individual OTU level, we identified Veillonella dispar as a candidate organism for preventing CDI recurrence; however, we did not detect a corresponding signal in the conducted meta-analysis. CONCLUSION: Although in our patient population, a candidate organism was identified for negatively predicting CDI recurrence, results suggest the need for larger cohort studies that include patients with diverse demographic characteristics to generalize species that robustly confer colonization resistance against C. difficile and accurately predict disease relapse. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s40168-017-0368-1) contains supplementary material, which is available to authorized users. BioMed Central 2017-11-13 /pmc/articles/PMC5684761/ /pubmed/29132405 http://dx.doi.org/10.1186/s40168-017-0368-1 Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Pakpour, Sepideh Bhanvadia, Amit Zhu, Roger Amarnani, Abhimanyu Gibbons, Sean M. Gurry, Thomas Alm, Eric J. Martello, Laura A. Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment |
title | Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment |
title_full | Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment |
title_fullStr | Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment |
title_full_unstemmed | Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment |
title_short | Identifying predictive features of Clostridium difficile infection recurrence before, during, and after primary antibiotic treatment |
title_sort | identifying predictive features of clostridium difficile infection recurrence before, during, and after primary antibiotic treatment |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5684761/ https://www.ncbi.nlm.nih.gov/pubmed/29132405 http://dx.doi.org/10.1186/s40168-017-0368-1 |
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