High-throughput proteomics is an effective methodology for identifying a variety of virulence factors of pathogens. Proteomic data are commonly evaluated against annotated sequences present in publicly available database repositories. A proteogenomic approach can be used if annotated sequences are not available or to identify novel proteins/peptides. However, a single genome is commonly utilized in proteomic and proteogenomic analyses. We pose the question of whether utilizing a number of different genome assemblies of a bacterial pathogen would be beneficial. Here, we used previously obtained shot-gun label-free nano-LC‒MS/MS data of the exoprotein fraction of four reference ERIC I–IV genotypes of Paenibacillus larvae and evaluated them against publicly available annotated sequences (from NCBI-protein, RefSeq, UniProt) together with an array of protein sequences generated using a six-frame direct translation of 15 genomic assemblies available in GenBank. The wide search through 18 database components reliably identified 453 protein hits. UpSet analysis categorized the hits into 50 groups based on the success protein identification by databases. The relatively high variability in successful identification among the genome assemblies facilitated the mining of markers based on uniqueness and contrasting results prior to considering proteome differences. Data evaluation provided novel and interesting markers that can be studied further.