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Typing and Characterization of Bacteria Using Bottom-up Tandem Mass Spectrometry Proteomics

Boulund, Fredrik, 1985 (author)
Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper,Department of Mathematical Sciences,University of Gothenburg,Chalmers tekniska högskola,Chalmers University of Technology
Karlsson, Roger, 1975 (author)
Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital,Göteborgs universitet,University of Gothenburg
Gonzales-Siles, L. (author)
Göteborgs universitet,University of Gothenburg
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Johnning, Anna, 1985 (author)
Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper,Department of Mathematical Sciences,Chalmers tekniska högskola,Chalmers University of Technology,University of Gothenburg
Karami, N. (author)
Göteborgs universitet,University of Gothenburg
Al-Bayati, O. (author)
Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital
Ahren, C. (author)
Göteborgs universitet,University of Gothenburg
Moore, Edward R.B. 1954 (author)
Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper,Department of Mathematical Sciences,Sahlgrenska universitetssjukhuset,Sahlgrenska University Hospital,University of Gothenburg
Kristiansson, Erik, 1978 (author)
Gothenburg University,Göteborgs universitet,Institutionen för matematiska vetenskaper,Department of Mathematical Sciences,University of Gothenburg,Chalmers tekniska högskola,Chalmers University of Technology
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 (creator_code:org_t)
2017
2017
English.
In: Molecular & Cellular Proteomics. - 1535-9476 .- 1535-9484. ; 16:6, s. 1052-1063
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • Methods for rapid and reliable microbial identification are essential in modern healthcare. The ability to detect and correctly identify pathogenic species and their resistance phenotype is necessary for accurate diagnosis and efficient treatment of infectious diseases. Bottom-up tandem mass spectrometry (MS) proteomics enables rapid characterization of large parts of the expressed genes of microorganisms. However, the generated data are highly fragmented, making downstream analyses complex. Here we present TCUP, a new computational method for typing and characterizing bacteria using proteomics data from bottom-up tandem MS. TCUP compares the generated protein sequence data to reference databases and automatically finds peptides suitable for characterization of taxonomic composition and identification of expressed antimicrobial resistance genes. TCUP was evaluated using several clinically relevant bacterial species (Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, Streptococcus pneumoniae, Moraxella catarrhalis, and Haemophilus influenzae), using both simulated data generated by in silico peptide digestion and experimental proteomics data generated by liquid chromatography-tandem mass spectrometry (MS/MS). The results showed that TCUP performs correct peptide classifications at rates between 90.3 and 98.5% at the species level. The method was also able to estimate the relative abundances of individual species in mixed cultures. Furthermore, TCUP could identify expressed beta-lactamases in an extended spectrum beta-lactamase-producing (ESBL) E.coli strain, even when the strain was cultivated in the absence of antibiotics. Finally, TCUP is computationally efficient, easy to integrate in existing bioinformatics workflows, and freely available under an open source license for both Windows and Linux environments.

Subject headings

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin (hsv//swe)
MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine (hsv//eng)
NATURVETENSKAP  -- Biologi -- Mikrobiologi (hsv//swe)
NATURAL SCIENCES  -- Biological Sciences -- Microbiology (hsv//eng)

Keyword

searching sequence databases
antimicrobial resistance
pseudomonas-aeruginosa
escherichia-coli
protein database
identification
classification
spectra
genomes
genes
Biochemistry & Molecular Biology

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ref (subject category)
art (subject category)

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