1. Characterization of Cerebrospinal Fluid via Data-Independent Acquisition Mass Spectrometry
- Author
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Andreas Linden, Katrin Marcus, Brit Mollenhauer, Simone Steinbach, Sara Galozzi, Nadine Stoepel, Sandra Pacharra, Katalin Barkovits, Caroline May, Martin Eisenacher, Julian Uszkoreit, and Lukas Schilde
- Subjects
0301 basic medicine ,Alternative methods ,Proteomics ,Chromatography ,Protein biomarkers ,Proteome ,Chemistry ,Selected reaction monitoring ,Reproducibility of Results ,General Chemistry ,Mass spectrometry ,Biochemistry ,Mass Spectrometry ,Substantia Nigra ,03 medical and health sciences ,030104 developmental biology ,Cerebrospinal fluid ,Humans ,Data-independent acquisition ,Biomarker discovery ,Biomarkers ,Hydrocephalus - Abstract
Cerebrospinal fluid (CSF) is in direct contact with the brain and serves as a valuable specimen to examine diseases of the central nervous system through analyzing its components. These include the analysis of metabolites, cells as well as proteins. For identifying new suitable diagnostic protein biomarkers bottom-up data-dependent acquisition (DDA) mass spectrometry-based approaches are most popular. Drawbacks of this method are stochastic and irreproducible precursor ion selection. Recently, data-independent acquisition (DIA) emerged as an alternative method. It overcomes several limitations of DDA, since it combines the benefits of DDA and targeted methods like selected reaction monitoring (SRM). We established a DIA method for in-depth proteome analysis of CSF. For this, four spectral libraries were generated with samples from native CSF ( n = 5), CSF fractionation (15 in total) and substantia nigra fractionation (54 in total) and applied to three CSF DIA replicates. The DDA and DIA methods for CSF were conducted with the same nanoLC parameters using a 180 min gradient. Compared to a conventional DDA method, our DIA approach increased the number of identified protein groups from 648 identifications in DDA to 1574 in DIA using a comprehensive spectral library generated with DDA measurements from five native CSF and 54 substantia nigra fractions. We also could show that a sample specific spectral library generated from native CSF only increased the identification reproducibility from three DIA replicates to 90% (77% with a DDA method). Moreover, by utilizing a substantia nigra specific spectral library for CSF DIA, over 60 brain-originated proteins could be identified compared to only 11 with DDA. In conclusion, the here presented optimized DIA method substantially outperforms DDA and could develop into a powerful tool for biomarker discovery in CSF. Data are available via ProteomeXchange with the identifiers PXD010698, PXD010708, PXD010690, PXD010705, and PXD009624.
- Published
- 2018