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J Proteome Res. 2015 Nov 6;14(11):4752-62. doi: 10.1021/acs.jproteome.5b00826. Epub 2015 Oct 22.

Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer.

Author information

1
Departments of Pathology, Boston Children's Hospital and Harvard Medical School , Boston, Massachusetts 02115, United States.
2
Thermo Fisher Scientific, 28199 Bremen, Germany.
3
Biognosys AG, Wagistrasse 25, CH-8952 Schlieren, Switzerland.
4
Division of Emergency Medicine, Boston Children's Hospital , Boston, Massachusetts 02115, United States.
5
Molecular Pharmacology & Chemistry Program, Sloan Kettering Institute, Department of Pediatrics, Memorial Sloan Kettering Cancer Center and Weill Medical College of Cornell University , New York, New York 10065, United States.

Abstract

The promises of data-independent acquisition (DIA) strategies are a comprehensive and reproducible digital qualitative and quantitative record of the proteins present in a sample. We developed a fast and robust DIA method for comprehensive mapping of the urinary proteome that enables large scale urine proteomics studies. Compared to a data-dependent acquisition (DDA) experiments, our DIA assay doubled the number of identified peptides and proteins per sample at half the coefficients of variation observed for DDA data (DIA = ∼8%; DDA = ∼16%). We also tested different spectral libraries and their effects on overall protein and peptide identifications and their reproducibilities, which provided clear evidence that sample type-specific spectral libraries are preferred for reliable data analysis. To show applicability for biomarker discovery experiments, we analyzed a sample set of 87 urine samples from children seen in the emergency department with abdominal pain. The whole set was analyzed with high proteome coverage (∼1300 proteins/sample) in less than 4 days. The data set revealed excellent biomarker candidates for ovarian cyst and urinary tract infection. The improved throughput and quantitative performance of our optimized DIA workflow allow for the efficient simultaneous discovery and verification of biomarker candidates without the requirement for an early bias toward selected proteins.

KEYWORDS:

DIA; QE; biomarker discovery; spectral library; urine proteomics

PMID:
26423119
PMCID:
PMC4993212
DOI:
10.1021/acs.jproteome.5b00826
[Indexed for MEDLINE]
Free PMC Article

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