9 research outputs found

    Matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and Bayesian phylogenetic analysis to characterize Candida clinical isolates

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    Clinical Candida isolates from two different hospitals in Rome were identified and clustered by MALDI-TOF MS system and their origin and evolution estimated by Bayesian phylogenetic analysis. The different species of Candida were correctly identified and clustered separately, confirming the ability of these techniques to discriminate between different Candida species. Focusing MALDI-TOF analysis on a single Candida species, Candida albicans and Candida parapsilosis strains clustered differently for hospital setting as well as for period of isolation than Candida glabrata and Candida tropicalis isolates. The evolutionary rates of C. albicans and C. parapsilosis (1.93Ă—10(-2) and 1.17Ă—10(-2)substitutions/site/year, respectively) were in agreement with a higher rate of mutation of these species, even in a narrow period, than what was observed in C. glabrata and C. tropicalis strains (6.99Ă—10(-4) and 7.52Ă—10(-3)substitutions/site/year, respectively). C. albicans resulted as the species with the highest between and within clades genetic distance values in agreement with the temporal-related clustering found by MALDI-TOF and the high evolutionary rate 1.93Ă—10(-2)substitutions/site/year

    Multi-drug resistant Pseudomonas aeruginosa nosocomial strains: Molecular epidemiology and evolution

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    Pseudomonas aeruginosa causes a wide variety of nosocomial infections. In the study, phylogenetic, selective pressure analysis and homology modelling were applied to oprD efflux pump gene with the aim to characterize multi-drug resistant strains circulating in the nosocomial setting, their transmission dynamics and ongoing evolution. One hundred ninety-three consecutive inpatients with Pseudomonas aeruginosa infection were enrolled at the University Campus Bio-Medico of Rome, between January 2015 and December 2016. oprD gene was sequenced in 20 nosocomial multi-drug resistant P. aeruginosa strains. Phylogeographic, selective pressure, residue conservation analysis and homology modelling were performed. Clinical epidemiological data were extracted from patient medical records. Multi-drug resistant strains accounted for the 36% of total strains and were responsible of 20 cases of nosocomial infections. P. aeruginosa infections occurred prevalently in the West area, especially at the location IIIW and in the Geriatric ward. The time of the most recent common ancestor indicated that strains could have been introduced in the hospital since the end of the year 2009 with the most probable location in general surgery ward. By selective pressure analysis, 29 positions under diversifying selection have been identified and mapped onto the OprD model. Most of the observed residue substitutions are predicted to be destabilizing and some of them occurred in the Loops 2 and 3 that are involved in solute selection and carbapenem susceptibility. The molecular and evolutionary analysis of Multi-drug resistant strains circulating in the nosocomial setting may provide useful insights into the epidemiology and the mechanisms leading to resistance, contributing to infection control improvement
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