Fourier Transform Infrared Spectroscopy Application for Outbreak Typing in a Referral Intensive Care Unit: Phylogenetic Analysis and Clustering Cut-Off Definition.

Recently has emerged as a multi-resistant fungal pathogen, with a significant clinical impact, and is able to persist for a long time on human skin and hospital environments. It is a critical issue on the WHO fungal priority list and therefore it is fundamental to reinforce hospital surveillance protocols to limit nosocomial outbreaks. The purpose of this study was to apply Fourier transform infrared spectroscopy (FT-IR) to investigate the phylogenetic relationships among isolated strains from a outbreak at the University Intensive Care Unit of a Tertiary University hospital in Turin (Italy).

Application of Fourier Transform Infrared Spectroscopy to Discriminate Two Closely Related Bacterial Species: and Sensu Stricto.

Fourier transform infrared spectroscopy (FTIRS) is a diagnostic technique historically used in the microbiological field for the characterization of bacterial strains in relation to the specific composition of their lipid, protein, and polysaccharide components. For each bacterial strain, it is possible to obtain a unique absorption spectrum that represents the fingerprint obtained based on the components of the outer cell membrane. In this study, FTIRS was applied for the first time as an experimental diagnostic tool for the discrimination of two pathogenic species belonging to the group, and sensu stricto; these are two closely related species that are not so easy to differentiate using classical microbiological methods, representing an innovative technology in the field of animal health.

Application of FT-IR Spectroscopy for Mycobacterium abscessus complex subspecies differentiation.

Mycobacterium abscessus complex (MABSC) subspecies differentiation improves patients' therapy and outcome. Fourier-Transform-Infrared Spectroscopy (FT-IRS) was applied for subspecies discrimination of 15 strains on different media: Löwenstein-Jensen showed the best resolution power; Linear Discriminant Analysis model differentiated M. abscessus susbsp.

A multi-center validation study on the discrimination of sg.1, sg. 2-15 and non- isolates from water by FT-IR spectroscopy.

This study developed and validated a method, based on the coupling of Fourier-transform infrared spectroscopy (FT-IR) and machine learning, for the automated serotyping of serogroup 1, serogroups 2-15 as well as their successful discrimination from non-. As presents significant intra- and inter-species heterogeneities, careful data validation strategies were applied to minimize late-stage performance variations of the method across a large microbial population. A total of 244 isolates were analyzed.