In this study, a Liquid Chromatography-Mass Spectrometry (LC-MS) method for the identification of clinically relevant () complex organisms is tested using a set of microbial Type strains. This methodology is based on profiling proteins derived from complex isolates. These protein profiles are then used as markers of species differentiation. To test the resolving power, speed, and accuracy of this assay four ATCC type strains and 32 recent clinical isolates of closely related species collected at ARUP laboratories (10 clinical isolate strains of subsp. , 10 subsp. , 2 subsp. and 10 ) were subjected to this approach. Using multiple deconvolution algorithms, we identified hundreds of individual proteins, with subpopulations of these used as species-specific markers. This assay identified 150, 130, 140 and 110 proteoforms with isocratic elution and 230, 180, 200 and 190 proteoforms with gradient elution for (ATCC 19977), (DSM 45103), (DSM 45149) and (ATCC 35752) respectively. Taxonomic species were identified correctly down to the species level with 100% accuracy. The ability to differentiate at sub-species level can in-turn be helpful for patient management. Data analysis showed ~7-17 proteoforms potentially able to differentiate between subspecies. Here, we present a proof-of-principle study employing a rapid mass spectrometry-based method to identify the clinically most common species within the species complex.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959847PMC
http://dx.doi.org/10.3389/fcimb.2022.809348DOI Listing

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