A dataset for developing proteomic tools for pathogen detection via differential cell lysis of whole blood samples
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...
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Veröffentlicht in: | Scientific data 2024-10, Vol.11 (1), p.1105-8, Article 1105 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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. |
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ISSN: | 2052-4463 2052-4463 |
DOI: | 10.1038/s41597-024-03834-8 |