Improving phylogeny reconstruction at the strain level using peptidome datasets

摘要: Typical bacterial strain differentiation methods are often challenged by high genetic similarity between strains. To address this problem, we introduce a novel in silico peptide fingerprinting method based on conventional wet-lab protocols that enables the identification of potential strain-specific peptides. These can be further investigated using vitro approaches, laying foundation for development biomarker detection and application-specific methods. This aims at reducing large amounts comparative data to binary matrices while maintaining phylogenetic resolution. The underlying case study concerns Bacillus cereus group, namely thuringiensis, anthracis Results show trees cytoplasmic extracellular peptidomes only marginally conflict with those whole proteomes, as inferred established Genome-BLAST Distance Phylogeny (GBDP) method. Hence, these results indicate two approaches most likely used complementarily even other organismal groups. obtained confirm previous reports about misclassification many strains within B. group. Moreover, our was able separate resolution, similarly GBDP benchmarked via Bayesian inference both Maximum Likelihood Parsimony. In addition presented phylogenomic applications, whole-peptide might also become valuable complementary technique digital DNA-DNA hybridization, notably classification species subspecies level future.