Automatic identification of mixed bacterial species fingerprints in a MALDI-TOF mass-spectrum

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry has been broadly adopted by routine clinical microbiology laboratories for bacterial species identification. An isolated colony of the targeted microorganism is the single prerequisite. Currently, MS-based microbial identification directly from clinical specimens can not be routinely performed, as it raises two main challenges: (i) the nature of the sample itself may increase the level of technical variability and bring heterogeneity with respect to the reference database and (ii) the possibility of encountering polymicrobial samples that will yield a 'mixed' MS fingerprint. In this article, we introduce a new method to infer the composition of polymicrobial samples on the basis of a single mass spectrum. Our approach relies on a penalized non-negative linear regression framework making use of species-specific prototypes, which can be derived directly from the routine reference database of pure spectra.