A dataset for developing proteomic tools for pathogen detection via differential cell lysis of whole blood samples

Sci Data. 2024 Oct 9;11(1):1105. doi: 10.1038/s41597-024-03834-8.

Abstract

This data descriptor presents a curated dataset for pathogen detection and identification (Staphylococcus aureus, Pseudomonas aeruginosa, and Candida albicans) directly from whole-blood samples. The dataset was created using differential cell lysis combined with rapid extraction, digestion, and mass spectrometry-based proteomics. Our method offers a rapid diagnostic alternative to traditional culture, enabling timely disease management, such as sepsis. Highlighting our dataset's uniqueness, it features a three-tier structure: Spectral Libraries of Pathogens for identifying peptide peaks for putative biomarkers; Spiked pathogen in blood MS data for biomarker panel optimization through varied concentration samples; and Parallel Reaction Monitoring (PRM) data from sepsis patients for validating our biomarker panel, achieving 83.3% sensitivity within seven hours without microbial enrichment culture. This dataset serves as a comprehensive reference for bioinformatic tool development and biomarker panel proposals, advancing microbial detection, antimicrobial resistance, and epidemiological studies.

Publication types

  • Dataset

MeSH terms

  • Biomarkers* / blood
  • Candida albicans*
  • Humans
  • Mass Spectrometry
  • Proteomics* / methods
  • Pseudomonas aeruginosa*
  • Sepsis* / blood
  • Sepsis* / diagnosis
  • Sepsis* / microbiology
  • Staphylococcus aureus*

Substances

  • Biomarkers