Comparison of whole-genome sequencing-based analysis methods for taxonomic classification of isolates unclassified by MALDI-TOF MS

Taxonomic identification of clinical isolates is routinely achieved using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). If the species cannot be reliably identified, whole-genome sequencing can be applied. The aim of this study was to compare the results of approaches for taxonomic assignment for classification of isolates that are difficult to identify. Fifty-seven isolates were included in the study. The isolates were whole-genome sequenced and de novo assembled. Assembly-based classification was performed with the Genome Taxonomy Database Toolkit (GTDB-Tk), BLAST against 16S rRNA gene databases, the Type (Strain) Genome Server (TYGS), and ribosomal MLST (rMLST). Read-based classification was performed with MetaPhlAn4 and Kraken2. Thirty-two isolates were assigned to the same species with all four assembly-based classifiers, while the remaining 25 showed diverging assignments. When evaluating the results for the latter isolates, GTDB-Tk performed better than the other classifiers regarding which assignments were most likely correct. Of the read-based classifiers, MetaPhlAn4 performed better than Kraken2. Our evaluation identified GTDB-Tk to be the strongest tool for taxonomic assignment of isolates that are difficult to identify. Disagreements between classifiers are likely due to database limitations, wrongly assigned taxonomy, or unreliable 16S rRNA gene-based assignments.