Rapid evaporative ionization mass spectrometry (REIMS) was investigated for its suitability as a general identification system for bacteria and fungi. Strains of 28 clinically relevant bacterial species were analyzed in negative ion mode, and corresponding data was subjected to unsupervised and supervised multivariate statistical analyses. The created supervised model yielded correct cross-validation results of 95.9%, 97.8%, and 100% on species, genus, and Gram-stain level, respectively. These results were not affected by the resolution of the mass spectral data. Blind identification tests were performed for strains cultured on different culture media and analyzed using different instrumental platforms which led to 97.8-100% correct identification. Seven different Escherichia coli strains were subjected to different culture conditions and were distinguishable with 88% accuracy. In addition, the technique proved suitable to distinguish five pathogenic Candida species with 98.8% accuracy without any further modification to the experimental workflow. These results prove that REIMS is sufficiently specific to serve as a culture condition-independent tool for the identification and characterization of microorganisms.

27Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has been shown to quickly and accurately 28 speciate microorganisms based upon their species-specific lipid profile. Previous work by members of 29 this group showed that the use of a handheld bipolar probe allowed REIMS to analyse microbial 30 cultures directly from culture plates, without any prior preparation. However, this method of analysis 31 would likely be unsuitable for a high-throughput clinical microbiology laboratory. Here, we report on 32 the creation of a customised platform which enables automated, high-throughput REIMS analysis, 33 which requires minimal user input and operation; and suitable for use in clinical microbiology 34 laboratories. The ability of this high-throughput platform to speciate clinically important 35 microorganisms was tested through the analysis of 375 different clinical isolates, collected from 36 distinct patient samples, from 25 microbial species. After optimisation of our data analysis approach, 37we achieved substantially similar results between the two REIMS approaches. For handheld bipolar 38 probe REIMS a speciation accuracy of 96.3% was achieved, whilst for high-throughput REIMS, an 39 accuracy of 93.9% was achieved. Thus, high-throughput REIMS offers an alternative mass 40 spectrometry based method for the rapid and accurate identification of clinically important 41 microorganisms in clinical laboratories without any pre-analysis preparative steps.

An identification system for microorganisms based on recently developed rapid evaporative ionisation mass spectrometry (REIMS) is presented. Nine bacterial species cultured on various growth media were correctly identified to family-, genus-, and species-level based on their different mass spectral fingerprints using a cross-validated maximum margin criterion model.