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Characterization of Clostridioides difficile Strains, the Disease Severity, and the Microbial Changes They Induce
Background: Clostridioides difficile infection (CDI) is a major nosocomial disease. The characteristics of different strains, the disease severity they cause, their susceptibility to antibiotics, and the changes they inflict on gut microbiome, have not been comprehensively studied in Israel. Methods...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7766075/ https://www.ncbi.nlm.nih.gov/pubmed/33353133 http://dx.doi.org/10.3390/jcm9124099 |
Sumario: | Background: Clostridioides difficile infection (CDI) is a major nosocomial disease. The characteristics of different strains, the disease severity they cause, their susceptibility to antibiotics, and the changes they inflict on gut microbiome, have not been comprehensively studied in Israel. Methods: A severity score was calculated for 70 patients. Stool samples were tested for toxins presence using a special kit. Bacteria were isolated, identified by matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) and antibiotic susceptibility tests were performed for several antibiotics. Strains were classified by Multi-locus sequence typing (MLST), and changes in gut microbiome were tested. Results: ST04 (22.5%) and ST37 (12.7%) were the most frequent strains. Clade (phylogenetic lineage) 1 was the most (81.4%) prevalent. We found significant associations between ST and age (p = 0.024) and between ST and moxifloxacin susceptibility (p = 0.001). At the clade level, we found significant associations with binary toxin gene occurrence (p = 0.002), and with susceptibility to both metronidazole and vancomycin (p = 0.024, 0.035, respectively). Differences in intestine microbiome were affected by age, clades’ distribution and STs. Conclusions: By defining the characteristics of the different strains and clades, clinicians can choose medical interventions based on the predicted response or disease severity associated with each strain, enabling new advances in the field of personalized medicine. |
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