Evaluation of the system Axima/Saramis MALDI-TOF MS bioMérieux in a clinical laboratory

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Romano Mattei *
Claudia Vicario
Maria Nardone
Arnaldo Savarino
(*) Corresponding Author:
Romano Mattei | r.mattei@usl2.toscana.it


Introduction. Mass Spectrometry technology “Matrix-assisted laser desorption Ionisation/Time-of-Flight (MALDI-TOF MS)” offers a promising new approach for identification of bacteria and fungi of clinical interest. The objective of this study is to evaluate the comparison of microbial identifications obtained with the system Axima/Saramis bioMérieux and identifications obtained by conventional manual or automatic (Vitek 2- bioMérieux).The work was divided into a pilot phase in which the staff has been trained and are set instrument parameters and an operational phase. Methods. MALDI-TOF is a system for the detection and identification of species-specific highly conserved proteins (ribosomal DNA and ligands). Part of a bacterial colony, is deposited on a polymeric substrate, extracted by the addition of the matrix (acid α-Cyano-4-hydroxycinnamic) and analyzed by MALDI-TOF.The mass spectra obtained are compared with the database Saramis (Anagnostec) containing the reference spectra of common pathogens. Results. During the pilot phase were analyzed 303 microorganisms (281 bacteria and 22 fungi), of which 207 (68.3%) correctly identified to species level, 35 (11.6%) identified as a species but not the main one and 49 (16.2%) did not identified. In the second phase of the study were analyzed microorganisms 1417 (1341 bacteria and 76 fungi) in a period of 60 days in 1240 (87.5%) correctly identified to species level, 121 (8.5%) identified as a species but not the main one and 41 (2.9%) unidentified. Conclusions. By reducing the response time (15 min/1 sample), the use of MALDI-TOF system, bioMérieux facilitates the workflow in the clinical laboratory, and positive impact on length of stay and costs. In addition, the rapid identification of yeasts at the species level is definitely a value added important and independent execution of test sensitivity. Finally, a good operator training translates into improved overall system performance.

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