Structural and functional changes in the gut microbiota associated to Clostridium difficile infection - PubMed (original) (raw)
Structural and functional changes in the gut microbiota associated to Clostridium difficile infection
Ana E Pérez-Cobas et al. Front Microbiol. 2014.
Abstract
Antibiotic therapy is a causative agent of severe disturbances in microbial communities. In healthy individuals, the gut microbiota prevents infection by harmful microorganisms through direct inhibition (releasing antimicrobial compounds), competition, or stimulation of the host's immune defenses. However, widespread antibiotic use has resulted in short- and long-term shifts in the gut microbiota structure, leading to a loss in colonization resistance in some cases. Consequently, some patients develop Clostridium difficile infection (CDI) after taking an antibiotic (AB) and, at present, this opportunistic pathogen is one of the main causes of antibiotic-associated diarrhea in hospitalized patients. Here, we analyze the composition and functional differences in the gut microbiota of C. difficile infected (CDI) vs. non-infected patients, both patient groups having been treated with AB therapy. To do so we used 16S rRNA gene and metagenomic 454-based pyrosequencing approaches. Samples were taken before, during and after AB treatment and were checked for the presence of the pathogen. We performed different analyses and comparisons between infected (CD+) vs. non-infected (CD-) samples, allowing proposing putative candidate taxa and functions that might protect against C. difficile colonization. Most of these potentially protective taxa belonged to the Firmicutes phylum, mainly to the order Clostridiales, while some candidate protective functions were related to aromatic amino acid biosynthesis and stress response mechanisms. We also found that CDI patients showed, in general, lower diversity and richness than non-infected, as well as an overrepresentation of members of the families Bacteroidaceae, Enterococcaceae, Lactobacillaceae and Clostridium clusters XI and XIVa. Regarding metabolic functions, we detected higher abundance of genes involved in the transport and binding of carbohydrates, ions, and others compounds as a response to an antibiotic environment.
Keywords: C. difficile infection; Gut microbiota; bacterial composition; colonization resistance; metabolic functions.
Figures
Figure 1
Fecal microbiota composition in CDI patients (F, G, and H). The composition of each sample is based on the RDP taxonomic assignment of the 16S rDNA sequences. The phylum and the genus level are shown for the most abundant bacterial groups (>5%).
Figure 2
Cluster analysis based on OTUs (97%) of CDI patients (F, G, and H). The approximate unbiased (AU) _p_-values are shown.
Figure 3
Correspondence analyses. (A) Detrended correspondence analysis (DCA) based on taxa abundance and composition of CD+ samples of patients (F, G, and H) (red square) and CD− samples of patients (A, B, C, D, and E), during treatment (blue square). Gray triangle indicates taxa distribution. (B) Correspondence analysis (CA) based on the functional profile (TIGRFAMs) of the same samples. Gray triangle indicates functions.
Figure 4
Bayesian network of microbial composition in CD− samples of patients (A–E), during treatment, and the candidate protective taxa. The significant positive correlations (_p_-value < 0.01) between the candidate protective taxa and other members of the bacterial community are shown. The correlation coefficients are indicated. Gray and white nodes represent candidate and correlated taxa, respectively. Candidate taxa with no-correlations are not included.
Figure 5
Bayesian network of microbiota potential functions in CD− samples of patients (A–E), during treatment, and the protective candidate taxa. The significant positive correlations (_p_-value < 0.01) between the candidate protective functions and other functions of the gut ecosystem are shown. Each node represents a specific function with the corresponding subrole color. The candidate protective function nodes are indicated by numbers: (1) Chorismate mutase; (2) Stage IV sporulation protein B; (3) Anti-sigma F factor; (4) Agmatine deiminase; (5) rrf2 family protein; (6) Redox-active disulfide protein 2; (7) Glutamate decarboxylase; (8) Doubled CXXCH domain; (9) Indolepyruvate ferredoxin oxidoreductase; (10) RNA polymerase sigma-70 factor, Bacteroides expansion family 1; (11) UDP-N-acetylglucosamine 4,6-dehydratase.
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