Improving phylogeny reconstruction at the strain level using peptidome datasets

  • 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 in vitro approaches, laying a foundation for the development of biomarker detection and applicationspecific methods. This novel method aims at reducing large amounts of comparative peptide data to binary matrices while maintaining a high phylogenetic resolution. The underlying case study concerns the Bacillus cereus group, namely the differentiation of Bacillus thuringiensis, Bacillus anthracis and Bacillus cereus strains. Results show that trees based on cytoplasmic and extracellular peptidomes are only marginally in conflict with those based on whole proteomes, as inferred by the established Genome-BLAST Distance Phylogeny (GBDP) method.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 in vitro approaches, laying a foundation for the development of biomarker detection and applicationspecific methods. This novel method aims at reducing large amounts of comparative peptide data to binary matrices while maintaining a high phylogenetic resolution. The underlying case study concerns the Bacillus cereus group, namely the differentiation of Bacillus thuringiensis, Bacillus anthracis and Bacillus cereus strains. Results show that trees based on cytoplasmic and extracellular peptidomes are only marginally in conflict with those based on whole proteomes, as inferred by the established Genome-BLAST Distance Phylogeny (GBDP) method. Hence, these results indicate that the two approaches can most likely be used complementarily even in other organismal groups. The obtained results confirm previous reports about the misclassification of many strains within the B. cereus group. Moreover, our method was able to separate the B. anthracis strains with high resolution, similarly to the GBDP results as benchmarked via Bayesian inference and both Maximum Likelihood and Maximum Parsimony. In addition to the presented phylogenomic applications, wholepeptide fingerprinting might also become a valuable complementary technique to digital DNA-DNA hybridization, notably for bacterial classification at the species and subspecies level in the future.show moreshow less

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Metadaten
Author:Aitor Blanco-Míguez, Jan P. Meier-KolthoffORCiDGND, Alberto Gutiérrez-Jácome, Markus Göker, Florentino Fdez-Riverola, Borja Sánchez, Anália Lourenço
URN:urn:nbn:de:bvb:384-opus4-1067475
Frontdoor URLhttps://opus.bibliothek.uni-augsburg.de/opus4/106747
ISSN:1553-7358OPAC
Parent Title (English):PLoS Computational Biology
Publisher:Public Library of Science (PLoS)
Place of publication:San Francisco, CA
Type:Article
Language:English
Year of first Publication:2016
Publishing Institution:Universität Augsburg
Release Date:2023/08/14
Tag:Computational Theory and Mathematics; Cellular and Molecular Neuroscience; Genetics; Molecular Biology; Ecology; Modeling and Simulation; Ecology, Evolution, Behavior and Systematics
Volume:12
Issue:12
First Page:e1005271
DOI:https://doi.org/10.1371/journal.pcbi.1005271
Institutes:Fakultät für Angewandte Informatik
Fakultät für Angewandte Informatik / Institut für Informatik
Fakultät für Angewandte Informatik / Institut für Informatik / Lehrstuhl für Biomedizinische Informatik, Data Mining und Data Analytics
Dewey Decimal Classification:0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik
Licence (German):CC-BY 4.0: Creative Commons: Namensnennung (mit Print on Demand)