A Bayesian model-based investigation of Candida albicans colonization in a preclinical mouse model.
Abstract
Receipt of broad-spectrum antibiotics enhances Candida albicans colonization of the GI tract, a risk factor for haematogenously-disseminated candidiasis. To understand how antibiotics influence C. albicans colonization, we treated mice orally with vancomycin or a combination of penicillin, streptomycin, and gentamicin (PSG) and then inoculated them with C. albicans by gavage. Only PSG treatment resulted in sustained, high-level GI colonization with C. albicans. Furthermore, PSG reduced bacterial diversity in the colon much more than vancomycin. Both antibiotic regimens significantly reduced IL-17A, IL-21, IL-22 and IFN-c mRNA levels in the terminal ileum but had limited effect on the GI fungal microbiome. Through a series of models that employed Bayesian model averaging, we investigated the associations between antibiotic treatment, GI microbiota, and host immune response and their collective impact on C. albicans colonization. Our analysis revealed that bacterial genera were typically associated with either C. albicans colonization or altered cytokine expression but not with both. The only exception was Veillonella, which was associated with both increased C. albicans colonization and reduced IL-21 expression. Overall, antibiotic-induced changes in the bacterial microbiome were much more consistent determinants of C. albicans colonization than either the GI fungal microbiota or the GI immune response.
Table of Contents:
Paper: Read the paper at Scientific Reports.
Shankar, J. et al. Using Bayesian modelling to investigate factors governing antibiotic-induced Candida albicans colonization of the GI tract. Sci. Rep. 5, 8131; DOI:10.1038/srep08131 (2015) Available at: http://dx.doi.org/10.1038/srep08131.Data: Download the data associated with the project.
Methods: Learn about the laboratory, bioinformatics and statistical analysis.
Results: Scan through the results from the descriptive and Bayesian modelling.
Code: Check out the code used for data processing and Bayesian modelling.