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. 2017 Aug;63(8):1398-1408.
doi: 10.1373/clinchem.2016.269647. Epub 2017 Jun 6.

A Genoproteomic Approach to Detect Peptide Markers of Bacterial Respiratory Pathogens

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A Genoproteomic Approach to Detect Peptide Markers of Bacterial Respiratory Pathogens

Honghui Wang et al. Clin Chem. 2017 Aug.

Abstract

Background: Rapid identification of respiratory pathogens may facilitate targeted antimicrobial therapy. Direct identification of bacteria in bronchoalveolar lavage (BAL) by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry is confounded by interfering substances. We describe a method to identify unique peptide markers of 5 gram-negative bacteria by liquid chromatography-tandem mass spectrometry (LC-MS/MS) for direct pathogen identification in BAL.

Methods: In silico translation and digestion were performed on 14-25 whole genomes representing strains of Acinetobacter baumannii, Moraxella catarrhalis, Pseudomonas aeruginosa, Stenotrophomonas maltophilia, and Klebsiella pneumoniae. Peptides constituting theoretical core peptidomes in each were identified. Rapid tryptic digestion was performed; peptides were analyzed by LC-MS/MS and compared with the theoretical core peptidomes. High-confidence core peptides (false discovery rate <1%) were identified and analyzed with the lowest common ancestor search to yield potential species-specific peptide markers. The species specificity of each peptide was verified with protein BLAST. Further, 1 or 2 pathogens were serially diluted into pooled inflamed BAL, and a targeted LC-MS/MS assay was used to detect 25 peptides simultaneously.

Results: Five unique peptides with the highest abundance for each pathogen distinguished these pathogens with varied detection sensitivities. Peptide markers for A. baumannii and P. aeruginosa, when spiked simultaneously into inflamed BAL, were detected with as few as 3.6 (0.2) × 103 and 2.2 (0.6) × 103 colony-forming units, respectively, by targeted LC-MS/MS.

Conclusions: This proof-of-concept study shows the feasibility of identifying unique peptides in BAL for 5 gram-negative bacterial pathogens, and it may provide a novel approach for rapid direct identification of bacterial pathogens in BAL.

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Conflict of interest statement

Authors’ Disclosures or Potential Conflicts of Interest: Upon manuscript submission, all authors completed the author disclosure form. Disclosures and/or potential conflicts of interest:

Employment or Leadership: None declared.

Consultant or Advisory Role: None declared.

Stock Ownership: None declared.

Honoraria: None declared.

Research Funding: The Intramural Research Program of the Clinical Center and National Heart, Lung and Blood Institute, National Institutes of Health.

Expert Testimony: None declared.

Patents: None declared.

Other Remuneration: S.K. Drake, WASPaLM Congress 2015.

Figures

Fig. 1.
Fig. 1.. MALDI-TOF MS spectra of a single clone culture of P. aeruginosa without (A) and with BAL (B).
Approximately 1 × 108 bacterial cells were spiked into 1 mL of BAL, spun, decanted, washed (ethanol), and then lysed (formic acid, acetonitrile). Two microliters of the 2 lysates were spotted on the MALDI target. Intense peaks at (3375, 3446, and 3490 Da) in the BAL matrix depressed the P. aeruginosa spectrum.
Fig. 2.
Fig. 2.. Relative quantification of peptide markers in spiked inflamed bronchoalveolar lavage (BAL) specimens for 5 bacteria as either 1 or 2 pathogens.
Actual CFU estimates are found in Table 1 in the online Data Supplement.
Fig. 3.
Fig. 3.. Representative LC-MS/MS chromatograms of peptide markers from 5 bacterial pathogens.
On the left side of the figure, the transition rank order of the labeled peptide is shown. The native peptides detected with decreasing bacteria CFU are shown from the left to the right in each row.
Fig. 4.
Fig. 4.. LC-MS/MS chromatograms of 2 peptide markers from frozen clinical BAL sample known to be culture-positive for P. aeruginosa.
Retention times and transition rank order of the native (top row) and spiked labeled peptide (bottom row) are well matched. The rdotp scores determine the spectra similarity between the analyte precursor and isotope-labeled precursor.

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