Microbial taxonomic and metabolic alterations during faecal microbiota transplantation to treat Clostridium difficile infection

Lee Kellingray, Gwénaëlle Le Gall, Marianne Defernez, Ian L.P. Beales, Ngozi Franslem-Elumogo, Arjan Narbad

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Objectives: This study aimed to examine changes to the microbiota composition and metabolic profiles of seven patients with recurrent Clostridium difficile infection (rCDI), following treatment with faecal microbiota transplant (FMT).

Methods: 16S rDNA sequencing and 1H NMR were performed on faecal samples from the patients (pre-, post-FMT, and follow-up) and the associated donor samples. Sparse partial-least-square analysis was used to identify correlations between the two datasets.

Results: The patients’ microbiota post-FMT tended to shift towards the donor microbiota, specifically through proportional increases of Bacteroides, Blautia, and Ruminococcus, and proportional decreases of Enterococcus, Escherichia, and Klebsiella. However, although cured of infection, one patient, who suffers from chronic alcohol abuse, retained the compositional characteristics of the pre-FMT microbiota. Following FMT, increased levels of short-chain fatty acids, particularly butyrate and acetate, were observed in all patients. Sparse partial-least-square analysis confirmed a positive correlation between butyrate and Bacteroides, Blautia, and Ruminococcus, with a negative correlation between butyrate and Klebsiella and Enterococcus.

Conclusions: Clear differences were observed in the microbiota composition and metabolic profiles between donors and rCDI patients, which were largely resolved in patients following FMT. Increased levels of butyrate appear to be a factor associated with resolution of rCDI.
Original languageEnglish
Pages (from-to)107-118
JournalJournal of Infection
Issue number2
Early online date7 May 2018
Publication statusPublished - Aug 2018


  • Clostridium difficile
  • Faecal microbiota transplantation
  • Metataxonomics
  • Metabonomics
  • Alcohol abuse
  • Sparse partial-least-square analysis

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