Open AccessExploring ecological modelling to investigate factors governing the colonization success in nosocomial environment of Candida albicans and other pathogenic yeasts
Author(s) -
Laura Corte,
Luca Roscini,
Claudia Colabella,
Carlo Tascini,
Alessandro Leonildi,
Emanuela Sozio,
Francesco Menichetti,
Maria Merelli,
Claudio Scarparo,
Wieland Meyer,
Gianluigi Cardinali,
Matteo Bassetti
Publication year - 2016
Publication title -
scientific reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.24
H-Index - 213
ISSN - 2045-2322
DOI - 10.1038/srep26860
Subject(s) - biofilm , candida albicans , colonization , microbiology and biotechnology , biology , isolation (microbiology) , corpus albicans , ecology , bacteria , genetics
Two hundred seventy seven strains from eleven opportunistic species of the genus Candida , isolated from two Italian hospitals, were identified and analyzed for their ability to form biofilm in laboratory conditions. The majority of Candida albicans strains formed biofilm while among the NCAC species there were different level of biofilm forming ability, in accordance with the current literature. The relation between the variables considered, i.e. the departments and the hospitals or the species and their ability to form biofilm, was tested with the assessment of the probability associated to each combination. Species and biofilm forming ability appeared to be distributed almost randomly, although some combinations suggest a potential preference of some species or of biofilm forming strains for specific wards. On the contrary, the relation between biofilm formation and species isolation frequency was highly significant (R 2 around 0.98). Interestingly, the regression analyses carried out on the data of the two hospitals separately were rather different and the analysis on the data merged together gave a much lower correlation. These findings suggest that, harsh environments shape the composition of microbial species significantly and that each environment should be considered per se to avoid less significant statistical treatments.