Dataset Information

Characterization of cerebrospinal fluid via data-independent acquisition mass spectrometry

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) applying to CSF DIA of three replicates. The DDA and DIA methods for CSF were conducted with the same nanoLC parameters using a 180 minute gradient. Compared to a conventional DDA method, our DIA approach both increased the number of identified protein groups with 1574 compared to DDA with 648 over 50 % with a comprehensive spectral library (generated with DDA measurements from five native CSF and 54 substantia nigra fractions) and decreased the coefficient of variation to 6 %, compared to 11 % with a DDA method. We also could show that a sample specific spectral library generated only from native CSF 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 eleven 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.

INSTRUMENT(S): Q Exactive

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cerebrospinal Fluid

SUBMITTER: Katalin Barkovits

LAB HEAD: Katrin Marcus

PROVIDER: PXD010698 | Pride | 2018-09-17

REPOSITORIES: Pride

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Characterization of Cerebrospinal Fluid via Data-Independent Acquisition Mass Spectrometry.

Barkovits Katalin K Linden Andreas A Galozzi Sara S Schilde Lukas L Pacharra Sandra S Mollenhauer Brit B Stoepel Nadine N Steinbach Simone S May Caroline C Uszkoreit Julian J Eisenacher Martin M Marcus Katrin K

Journal of proteome research 20180912 10

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, d ...[more]

PMID: 30207155

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Project description:A quadrupole time-of-flight mass spectrometry coupled with a trapped ion mobility mass spectrometer operated in parallel accumulation-serial fragmentation mode has recently emerged as proteome profiling platform capable of providing four dimensional features of elution time, collision cross section, precursor and fragment ion masses of peptides. The PASEF mode has demonstrated its superior performance by providing nearly 100% ion sampling efficiency both in data-dependent acquisition and data-independent acquisition modes without sacrificing sensitivity. In addition, the substantial gain in selectivity has been proven in targeted measurements using PASEF integrated parallel reaction monitoring mode. However, because these are emerging technologies in the field of proteomics, their applicability to clinical samples has been less investigated. Cerebrospinal fluid is in direct contact with brain and has been shown to contain biomarkers related to a variety of neurological diseases although the proteomics data have been mainly generated using orbitrap-based mass spectrometers. Thus, we acquired in-depth proteome profiles of human CSF in DDA mode to generate a spectral library of 3,478 proteins. The benefit of applying the spectral library to PRM experiments was demonstrated by using CSF samples from 15 Alzheimer’s disease patients and 19 controls and utilizing the spectral library to determine elution times and ion mobility values of targeting peptide. Further, we acquired DIA data from the same CSF samples, and analyzed using the spectral library without additional efforts to generate study-specific library, which also resulted in sensitive protein identification compared to a library-free approach. Overall, we established resource of CSF proteome profiles with 4D features and demonstrated the significant gain for designing and analyzing targeted and DIA studies, which is expected to facilitate 4D proteomics of CSF to study various neurological disorders.

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