Yet, even DNA sequence-based identification of moulds has WY 14643 company several limitations. The DNA extraction yield may be relatively low because mould cells are hard to lyse. PCR amplification may fail due to the presence of PCR inhibitors in mould cultures. Moreover, although it may technically succeed, the molecular identification of moulds would require at least 5 to 7 days in the routine clinical laboratory setting. This delay negatively impacts the patients’ prognosis. Finally, only some clinical laboratories routinely use a molecular approach for microorganism identification. In 2007, only 17% of the US clinical laboratories performed molecular analysis. Therefore the identification of moulds remains problematic and misidentifications likely occur in the routine setting. A novel microorganism identification method has emerged in bacteriology that is based on MALDI-TOF mass spectrum analysis. This MALDI-TOF MS-based identification technique analyzes the protein content from treated or intact cells of microorganisms under the form of a spectrum that is considered as a protein fingerprint specific of a micro-organism. An unknown microorganism is identified by comparing its spectrum with the spectra in the reference library. MALDI-TOF MS-based identification is simple, fast, and accurate and has a high throughput for most bacteria. Numerous bacteriologists found that its identification accuracy outperformed that of conventional methods in the routine clinical laboratory setting. A few preliminary studies aimed to identify moulds using MALDI-TOF MS. However, each used only specific mould genera and culture conditions. Different extraction methods, types of matrix, and instruments were also used. This heterogeneity is particularly detrimental because mass spectra are influenced by culture conditions, extraction procedures, the type of matrix, and the spectrometer used. Our study therefore sought to elaborate a standardized procedure suitable for the MALDI-TOF MS-based identification of clinically relevant moulds in the routine laboratory setting. In the first step, the operating procedures for MALDI-TOF MS-based identification were optimized and validated on a large panel of clinically relevant moulds. In the second step, we evaluated the performances of this MALDI-TOF MS-based approach for the identification of mould clinical isolates prospectively collected from the routine activity of the Marseille teaching hospital laboratory. Moulds were considered regardless of their phylogeny and relation to any specific clinical situation. This is the first demonstration that a standardized MALDITOF procedure is capable to identify a large array of distinct mould species that are routinely isolated in the clinical laboratory setting. In this setting, MALDI-TOF MS-based identification has already revolutionized the identification of bacteria and yeasts. A growing number of clinical laboratories are now equipped with MALDI-TOF MS-based solutions for the MALDI-TOF MSbased identification of micro-organisms. Yet the lack of standardized procedure applicable to the routine identification of moulds isolated in the clinical laboratory routine remained the major gap in commercialized solutions to date.