An iterative and automated computational pipeline for untargeted strain-level identification using MS/MS spectra from pathogenic samples

Mathias Kuhring; Joerg Doellinger; Andreas Nitsche; Thilo Muth; Bernhard Y. Renard

Using TaxIt, the expected B. subtilis str. 168 strain is identified correctly in the reduced as well as in the complete sample (Supplementary item 1 - Figure S3 and S4) . Pipasic consistently misses the correct strain and species in favor of incorrect strains such as Bacillus cereus SJ1 and Bacillus cereus B4264. The unique-PSMs-based strategy includes the correct strain B. subtilis str. 168 into the final candidate list of the bacillus 1k sample. However, it fails to separate the strain from several distinct species due to equal amounts of unique PSMs (Supplementary item 1 -Figure S3) . Furthermore, the data analysis on the complete bacillus sample results in the incorrect species Paenisporosarcina quisquiliarum being predominantly present in terms of uniquely assigned PSMs.