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Mass Spectrometry Proteotyping of Streptococcus pneumoniae and commensal Streptococcus: identification of biomarkers for infectious strain characterization

Authors Lucia Gonzales-Siles
Roger Karlsson
Fredrik Boulund
Hedvig E Jakobsson
Francisco Salvà-Serra
M Gomila
A Bousquets
Erik Kristiansson
Edward R.B. Moore
Published in 26th ECCMID 2016 Amsterdam, The Netherlands. 9 - 12 April 2016
Publication year 2016
Published at Department of Mathematical Sciences, Mathematical Statistics
Institute of Biomedicine, Department of Infectious Medicine
Language en
Subject categories Microbiology, Functional genomics, Biological Systematics


Background: Streptococcus pneumoniae (pneumococcus) is the leading cause of community-acquired pneumonia, with morbidity and mortality worldwide. S. pneumoniae belongs to the S. mitis-Group (viridans streptococci), phenotypically and genotypically similar to commensal species of the upper respiratory tract, S. mitis, S. oralis, and S. pseudopneumoniae, causing problems for identifications in clinical laboratories. In this project, we apply state-of-the-art proteomics for Streptococcus spp. 'proteotyping'; identifying and characterizing protein biomarkers for species-level identification, antibiotic resistance, virulence and strain typing for epidemiological analyses (1). Material/methods: Bacterial proteins, from intact bacteria or cell fractions, are bound to a membrane surface, using patented (WO2006068619) FlowCell (LPITM) technology. Peptides are generated from the bound proteins, by enzymatic digestion, separated and analyzed, using LC-MS/MS. The mass spectra profiles are compared to reference peptide sequences and whole genome sequence (wgs) data of the NCBI RefSeq Database. The S. mitis-Group specie, S. pneumoniae, S. mitis, S. oralis, S. psedopneumoniae, as well as the more distantly-related, Group A Streptococcus (GAS) species, S. pyogenes , were analyzed individually and in mixtures, to demonstrate the resolution of proteotyping for differentiating bacteria. Results: Using proteotyping protocols, S. pneumoniae were detected and differentiated from other streptococci, S. mitis, S. oralis, S. psedopneumoniae and the more distant relative, S. pyogenes, by identification of unique discriminatory peptides. Metabolic protein biomarkers were identified, including for antibiotic resistance and virulence. It was possible to find discriminatory biomarkers for a target species when analyzing 1:1 mixes of S. pneumoniae and other species from the S. mitis-Group. The different strains of S. pneumoniae, analyzed in different ratio combinations, were successfully differentiated and identified. For successful proteotyping, a comprehensive and accurate genomic database was observed to be key for obtaining reliable peptide matching and proteotyping data. Importantly, because of observed high rates of misclassified wgs data in the public databases, the taxonomic classifications of genomes in GenBank were analyzed against reference type strain genomes of target species by calculating wgs similarities, using Average Nucleotide Identity with BLAST (ANIb). While wgs data for S. pneumoniae were confirmed to be classified correctly, approximately one-third of wgs data for other species of the S. mitis-Group were determined to be misclassified. Streptococci strains that could not be identified, using standard genotypic and phenotypic approaches, were characterized by proteotyping and genome sequencing to establish their taxonomy and biomarker features to enhance species database matching. Conclusions: Proteotyping enables differentiation, identification and characterization of pneumococcus from the most closely related species attaining, as well, strain-level discrimination from single LC-MS/MS analyses. The protocol enhances identification and characterization of pathogenic bacterial isolates through identifications of expressed biomarkers, ultimately for cultivation-independent analyses of clinical samples. 1) Karlsson et al., 2015. Syst Appl Microbiol. 38:246-257.

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