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

In comparison, bronchitis and bacillus samples feature notable variability in proposed taxa candidates. For bronchitis, TaxIt could identify the expected Avian infectious bronchitis virus (strain Beaudette CK) strain. Despite applying a small correction based on weighting, however, final candidate selection is not limited to a single strain but additionally includes a closely related strain, namely Avian infectious bronchitis virus (strain Beaudette US) ( Figure 3A) . Nevertheless, TaxIt provides a highly constrained selection of candidates in the first place. In contrast, the Pipasic-based strategy results in considerably more initial candidates and eventually promotes an incorrect strain, namely Avian infectious bronchitis virus (strain 6/82) (Figure 3B ). Since no unique PSMs are available for the bronchitis sample, strain-level identification was not possible with this strategy.