How to: identify non-tuberculous Mycobacterium species using MALDI-TOF mass spectrometry.

BACKGROUND: The implementation of MALDI-TOF MS for microorganism identification has changed the routine of the microbiology laboratories as we knew it. Most microorganisms can now be reliably identified within minutes using this inexpensive, user-friendly methodology. However, its application in the identification of mycobacteria isolates has been hampered by the structure of their cell wall. Improvements in the sample processing method and in the available database have proved key factors for the rapid and reliable identification of non-tuberculous mycobacteria isolates using MALDI-TOF MS. AIMS: The main objective is to provide information about the proceedings for the identification of non-tuberculous isolates using MALDI-TOF MS and to review different sample processing methods, available databases, and the interpretation of the results. SOURCES: Results from relevant studies on the use of the available MALDI-TOF MS instruments, the implementation of innovative sample processing methods, or the implementation of improved databases are discussed. CONTENT: Insight about the methodology required for reliable identification of non-tuberculous mycobacteria and its implementation in the microbiology laboratory routine is provided. IMPLICATIONS: Microbiology laboratories where MALDI-TOF MS is available can benefit from its capacity to identify most clinically interesting non-tuberculous mycobacteria in a rapid, reliable, and inexpensive manner.

Impact of updating the MALDI-TOF MS database on the identification of nontuberculous mycobacteria.

Conventional identification of mycobacteria species is slow, laborious and has low discriminatory power. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has proved highly effective for identifying conventional bacteria, and it may also be useful for identifying mycobacteria. The aim of this study was to evaluate and compare MALDI-TOF MS with currently recommended molecular methods for the identification of nontuberculous mycobacteria (NTM), applying Mycobacteria Libraries v3.0 (ML3.0) and v2.0 (ML2.0). A total of 240 clinical isolates of 41 NTM species grown on solid media were analysed: 132 isolates of slow-growing mycobacteria and 108 of rapid-growing mycobacteria. MALDI-TOF MS, using ML3.0, identified 192 (80%) NTM isolates with a score ≥1.7, encompassing 35 (85.4%) different species, that is, 17 (7.1%; p = 0.0863) isolates and 15 (36.6%; p = 0.0339) species more than currently recommended molecular techniques (polymerase chain reaction reverse hybridization). All these isolates were correctly identified according to molecular identification methods. The application of ML3.0 also identified 15 (6.2%) NTM isolates more than ML2.0 (p < 0.01). The scores obtained with MALDI-TOF MS using ML3.0 (mean score: 1.960) were higher in 147 (61.2%) isolates than when using ML2.0 (mean score: 1.797; p < 0.01). Three of the species analysed were not included in either database, so they were not recognized by this system. In conclusion, MALDI-TOF MS identified more isolates and species than the recommended polymerase chain reaction reverse hybridization assays. Although the new ML3.0 is not the definitive database, it yielded better results than ML2.0. This shows that the updating of the MALDI-TOF MS database plays an essential role in mycobacterial identification. Copyright © 2017 John Wiley & Sons, Ltd.