title: Changes of poultry faecal microbiota associated with Clostridium difficile colonisation.
abstract: Bacterial, fungal and archaeal microbiota was analysed in 143 chicken faecal samples from a single poultry farm. After DHPLC (denaturing high performance liquid chromatography) 15 bacterial groups, 10 fungal groups and a single archaeal species were differentiated. Samples were grouped into two clusters with significantly different frequencies of C. difficile positive and negative samples in each cluster. Acidaminococcus intestini, described here for the first time as a part of poultry faecal microbiota, was significantly more likely present in C. difficile negative samples, while presence/absence of some other microorganisms (Enterococcus cecorum, Lactobacillus galinarum, Moniliella sp. and Trichosporon asahii) was close to significance. Two other groups not reported previously for poultry, Coprobacillus sp. and Turicibacter sp. did not differ significantly between C. difficile positive and negative samples. Differences in microbiota diversity depend on animal age, but not on the presence of C. difficile. With machine learning (WEKA J48) we have defined specific combinations of microbial groups predictive for C. difficile colonisation. Microbial groups associated with C. difficile colonisation in poultry are different than those reported for humans and include bacteria as well as fungi. Also with this approach A. intestini was found to be most strongly related to C. difficile negative samples.
authors.affiliation: Centre of Excellence for Integrated Approaches in Chemistry and Biology of Proteins, 1000 Ljubljana, Slovenia.
authors.forename: Jure
authors.initials: J
authors.lastname: Skraban
authors.forename: Saso
authors.initials: S
authors.lastname: Dzeroski
authors.forename: Bernard
authors.initials: B
authors.lastname: Zenko
authors.forename: Livija
authors.initials: L
authors.lastname: Tusar
authors.forename: Maja
authors.initials: M
authors.lastname: Rupnik
mesh_terms: D045850:Acidaminococcus / Q000502:physiology; D000367:Age Factors; D000818:Animals; D001105:Archaea / Q000145:classification / Q000502:physiology; D001185:Artificial Intelligence; D001419:Bacteria / Q000145:classification; D044822:Biodiversity; D016360:Clostridioides difficile / Q000145:classification / Q000502:physiology*; D016000:Cluster Analysis; D005243:Feces / Q000382:microbiology*; D005658:Fungi / Q000145:classification / Q000502:physiology; D007422:Intestines / Q000382:microbiology; D064307:Microbiota / Q000502:physiology*; D011200:Poultry / Q000382:microbiology*