Identification of pathogens from native urine samples by MALDI-TOF/TOF tandem mass spectrometry.

16S rRNA sequencing MALDI-TOF/TOF Pathogen identification Proteomics Sample preparation Urine

Journal

Clinical proteomics
ISSN: 1542-6416
Titre abrégé: Clin Proteomics
Pays: England
ID NLM: 101184586

Informations de publication

Date de publication:
2020
Historique:
received: 10 05 2020
accepted: 17 06 2020
entrez: 26 6 2020
pubmed: 26 6 2020
medline: 26 6 2020
Statut: epublish

Résumé

Reliable high-throughput microbial pathogen identification in human urine samples is crucial for patients with cystitis symptoms. Currently employed methods are time-consuming and could lead to unnecessary or inadequate antibiotic treatment. Purpose of this study was to assess the potential of mass spectrometry for uropathogen identification from a native urine sample. In total, 16 urine samples having more than 10 Here we present advantages and disadvantages of bottom-up proteomics, using MALDI-TOF/TOF tandem mass spectrometry, for culture-independent identification of uropathogens (e.g. directly from urine samples). The direct approach provided reliable identification of bacteria at the genus level in monobacterial samples. Taxonomic identifications obtained by proteomics were compared both to standard urine culture test used in clinics and genomic test based on 16S rRNA sequencing. Our findings indicate that mass spectrometry has great potential as a reliable high-throughput tool for microbial pathogen identification in human urine samples. In this case, the MALDI-TOF/TOF, was used as an analytical tool for the determination of bacteria in urine samples, and the results obtained emphasize high importance of storage conditions and sample preparation method impacting reliability of MS2 data analysis. The proposed method is simple enough to be utilized in existing clinical settings and is highly suitable for suspected single organism infectious etiologies. Further research is required in order to identify pathogens in polymicrobial urine samples.

Sections du résumé

BACKGROUND BACKGROUND
Reliable high-throughput microbial pathogen identification in human urine samples is crucial for patients with cystitis symptoms. Currently employed methods are time-consuming and could lead to unnecessary or inadequate antibiotic treatment. Purpose of this study was to assess the potential of mass spectrometry for uropathogen identification from a native urine sample.
METHODS METHODS
In total, 16 urine samples having more than 10
RESULTS RESULTS
Here we present advantages and disadvantages of bottom-up proteomics, using MALDI-TOF/TOF tandem mass spectrometry, for culture-independent identification of uropathogens (e.g. directly from urine samples). The direct approach provided reliable identification of bacteria at the genus level in monobacterial samples. Taxonomic identifications obtained by proteomics were compared both to standard urine culture test used in clinics and genomic test based on 16S rRNA sequencing.
CONCLUSIONS CONCLUSIONS
Our findings indicate that mass spectrometry has great potential as a reliable high-throughput tool for microbial pathogen identification in human urine samples. In this case, the MALDI-TOF/TOF, was used as an analytical tool for the determination of bacteria in urine samples, and the results obtained emphasize high importance of storage conditions and sample preparation method impacting reliability of MS2 data analysis. The proposed method is simple enough to be utilized in existing clinical settings and is highly suitable for suspected single organism infectious etiologies. Further research is required in order to identify pathogens in polymicrobial urine samples.

Identifiants

pubmed: 32581661
doi: 10.1186/s12014-020-09289-4
pii: 9289
pmc: PMC7310424
doi:

Types de publication

Journal Article

Langues

eng

Pagination

25

Informations de copyright

© The Author(s) 2020.

Déclaration de conflit d'intérêts

Competing interestsThe authors declare that they have no competing interest.

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Auteurs

Damir Oros (D)

Department of Biochemical Engineering, Faculty of Food Technology and Biotechnology, Zagreb University, 10000 Zagreb, Croatia.

Marina Ceprnja (M)

Biochemical Laboratory, Special Hospital Agram, Polyclinic Zagreb, 10000 Zagreb, Croatia.

Jurica Zucko (J)

Department of Biochemical Engineering, Faculty of Food Technology and Biotechnology, Zagreb University, 10000 Zagreb, Croatia.

Mario Cindric (M)

Division of Molecular Medicine, Ruder Boskovic Institute, Zagreb, Croatia.

Amela Hozic (A)

Division of Molecular Medicine, Ruder Boskovic Institute, Zagreb, Croatia.

Jasenka Skrlin (J)

Department for Clinical Microbiology and Hospital Infection, University Hospital Dubrava, 10000 Zagreb, Croatia.

Karmela Barisic (K)

Faculty of Pharmacy and Biochemistry, Zagreb University, Zagreb, Croatia.

Ena Melvan (E)

Department of Biological Science, Faculty of Science, Macquarie University, Sydney, Australia.

Ksenija Uroic (K)

Department of Biochemical Engineering, Faculty of Food Technology and Biotechnology, Zagreb University, 10000 Zagreb, Croatia.

Blazenka Kos (B)

Department of Biochemical Engineering, Faculty of Food Technology and Biotechnology, Zagreb University, 10000 Zagreb, Croatia.

Antonio Starcevic (A)

Department of Biochemical Engineering, Faculty of Food Technology and Biotechnology, Zagreb University, 10000 Zagreb, Croatia.

Classifications MeSH