title: Advancing Urinary Protein Biomarker Discovery by Data-Independent Acquisition on a Quadrupole-Orbitrap Mass Spectrometer.
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.
authors.affiliation: Departments of Pathology, Boston Children's Hospital and Harvard Medical School , Boston, Massachusetts 02115, United States.
authors.forename: Jan
authors.initials: J
authors.lastname: Muntel
authors.affiliation: Thermo Fisher Scientific, 28199 Bremen, Germany.
authors.forename: Yue
authors.initials: Y
authors.lastname: Xuan
authors.affiliation: Departments of Pathology, Boston Children's Hospital and Harvard Medical School , Boston, Massachusetts 02115, United States.
authors.forename: Sebastian T
authors.initials: ST
authors.lastname: Berger
authors.affiliation: Biognosys AG, Wagistrasse 25, CH-8952 Schlieren, Switzerland.
authors.forename: Lukas
authors.initials: L
authors.lastname: Reiter
authors.affiliation: Division of Emergency Medicine, Boston Children's Hospital , Boston, Massachusetts 02115, United States.
authors.forename: Richard
authors.initials: R
authors.lastname: Bachur
authors.affiliation: 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.
authors.forename: Alex
authors.initials: A
authors.lastname: Kentsis
authors.affiliation: Departments of Pathology, Boston Children's Hospital and Harvard Medical School , Boston, Massachusetts 02115, United States.
authors.forename: Hanno
authors.initials: H
authors.lastname: Steen
mesh_terms: D015746:Abdominal Pain / Q000175:diagnosis / Q000503:physiopathology / Q000652:urine*; D015415:Biomarkers / Q000652:urine; D002648:Child; D057225:Data Mining / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D013058:Mass Spectrometry / Q000379:methods / Q000706:statistics & numerical data*; D010048:Ovarian Cysts / Q000175:diagnosis / Q000503:physiopathology / Q000652:urine*; D019151:Peptide Library; D012680:Sensitivity and Specificity; D014552:Urinary Tract Infections / Q000175:diagnosis / Q000503:physiopathology / Q000652:urine*
chemical_list: D015415:Biomarkers; D019151:Peptide Library
keywords: DIA; QE; biomarker discovery; spectral library; urine proteomics