Cargando…
Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut
Clostridioides difficile colonizes up to 30–40% of community-dwelling adults without causing disease(1,2). C. difficile infections (CDIs) are the leading cause of antibiotic-associated diarrhea in the U.S.(3,4) and typically develop in individuals following disruption of the gut microbiota due to an...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cold Spring Harbor Laboratory
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168307/ https://www.ncbi.nlm.nih.gov/pubmed/37162960 http://dx.doi.org/10.1101/2023.04.28.538771 |
_version_ | 1785038832537698304 |
---|---|
author | Carr, Alex Baliga, Nitin S. Diener, Christian Gibbons, Sean M. |
author_facet | Carr, Alex Baliga, Nitin S. Diener, Christian Gibbons, Sean M. |
author_sort | Carr, Alex |
collection | PubMed |
description | Clostridioides difficile colonizes up to 30–40% of community-dwelling adults without causing disease(1,2). C. difficile infections (CDIs) are the leading cause of antibiotic-associated diarrhea in the U.S.(3,4) and typically develop in individuals following disruption of the gut microbiota due to antibiotic or chemotherapy treatments(2). Further treatment of CDI with antibiotics is not always effective and can lead to antibiotic resistance and recurrent infections (rCDI)(5,6). The most effective treatment for rCDI is the reestablishment of an intact microbiota via fecal microbiota transplants (FMTs)(7). However, the success of FMTs has been difficult to generalize because the microbial interactions that prevent engraftment and facilitate the successful clearance of C. difficile are still only partially understood(8). Here we show how microbial community-scale metabolic models (MCMMs) accurately predicted known instances of C. difficile colonization susceptibility or resistance. MCMMs provide detailed mechanistic insights into the ecological interactions that govern C. difficile engraftment, like cross-feeding or competition involving metabolites like succinate, trehalose, and ornithine, which differ from person to person. Indeed, three distinct C. difficile metabolic niches emerge from our MCMMs, two associated with positive growth rates and one that represents non-growth, which are consistently observed across 14,862 individuals from four independent cohorts. Finally, we show how MCMMs can predict personalized engraftment and C. difficile growth suppression for a probiotic cocktail (VE303) designed to replace FMTs for the treatment rCDI(9,10). Overall, this powerful modeling approach predicts personalized C. difficile engraftment risk and can be leveraged to assess probiotic treatment efficacy. MCMMs could be extended to better understand personalized engraftment of other opportunistic bacterial pathogens, beneficial probiotic organisms, or more complex microbial consortia. |
format | Online Article Text |
id | pubmed-10168307 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Cold Spring Harbor Laboratory |
record_format | MEDLINE/PubMed |
spelling | pubmed-101683072023-05-10 Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut Carr, Alex Baliga, Nitin S. Diener, Christian Gibbons, Sean M. bioRxiv Article Clostridioides difficile colonizes up to 30–40% of community-dwelling adults without causing disease(1,2). C. difficile infections (CDIs) are the leading cause of antibiotic-associated diarrhea in the U.S.(3,4) and typically develop in individuals following disruption of the gut microbiota due to antibiotic or chemotherapy treatments(2). Further treatment of CDI with antibiotics is not always effective and can lead to antibiotic resistance and recurrent infections (rCDI)(5,6). The most effective treatment for rCDI is the reestablishment of an intact microbiota via fecal microbiota transplants (FMTs)(7). However, the success of FMTs has been difficult to generalize because the microbial interactions that prevent engraftment and facilitate the successful clearance of C. difficile are still only partially understood(8). Here we show how microbial community-scale metabolic models (MCMMs) accurately predicted known instances of C. difficile colonization susceptibility or resistance. MCMMs provide detailed mechanistic insights into the ecological interactions that govern C. difficile engraftment, like cross-feeding or competition involving metabolites like succinate, trehalose, and ornithine, which differ from person to person. Indeed, three distinct C. difficile metabolic niches emerge from our MCMMs, two associated with positive growth rates and one that represents non-growth, which are consistently observed across 14,862 individuals from four independent cohorts. Finally, we show how MCMMs can predict personalized engraftment and C. difficile growth suppression for a probiotic cocktail (VE303) designed to replace FMTs for the treatment rCDI(9,10). Overall, this powerful modeling approach predicts personalized C. difficile engraftment risk and can be leveraged to assess probiotic treatment efficacy. MCMMs could be extended to better understand personalized engraftment of other opportunistic bacterial pathogens, beneficial probiotic organisms, or more complex microbial consortia. Cold Spring Harbor Laboratory 2023-05-09 /pmc/articles/PMC10168307/ /pubmed/37162960 http://dx.doi.org/10.1101/2023.04.28.538771 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Carr, Alex Baliga, Nitin S. Diener, Christian Gibbons, Sean M. Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut |
title | Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut |
title_full | Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut |
title_fullStr | Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut |
title_full_unstemmed | Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut |
title_short | Personalized Clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut |
title_sort | personalized clostridioides difficile engraftment risk prediction and probiotic therapy assessment in the human gut |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168307/ https://www.ncbi.nlm.nih.gov/pubmed/37162960 http://dx.doi.org/10.1101/2023.04.28.538771 |
work_keys_str_mv | AT carralex personalizedclostridioidesdifficileengraftmentriskpredictionandprobiotictherapyassessmentinthehumangut AT baliganitins personalizedclostridioidesdifficileengraftmentriskpredictionandprobiotictherapyassessmentinthehumangut AT dienerchristian personalizedclostridioidesdifficileengraftmentriskpredictionandprobiotictherapyassessmentinthehumangut AT gibbonsseanm personalizedclostridioidesdifficileengraftmentriskpredictionandprobiotictherapyassessmentinthehumangut |