Dataset Information

Proteomes of paired human cerebrospinal fluid and plasma

ABSTRACT: Shotgun proteomics using liquid chromatography tandem mass spectrometry (LC MS/MS) can characterize in-depth human cerebrospinal fluid (CSF) and plasma proteomes. Nonetheless, association between the proteomes in each compartment has not been described to the full extent using such technology due to sample size limitations. We deployed MS-based proteomics in paired CSF and plasma samples volunteered by 120 elders with (n = 72) and without cognitive impairment (n = 48) to comprehensively examine the compartmental differences and the influence of blood-brain barrier (BBB) integrity. We further tested the hypothesis that BBB breakdown can be identified from CSF and plasma proteome alterations in non-demented elders.

INSTRUMENT(S): LTQ Orbitrap Elite

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Blood Plasma, Cerebrospinal Fluid

SUBMITTER: Loïc Dayon

LAB HEAD: Loïc Dayon

PROVIDER: PXD009589 | Pride | 2019-02-15

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	CSF_Pool_Pool_Pool_Pool_Pool_Pool_01_Plate01.raw	Raw
	CSF_Pool_Pool_Pool_Pool_Pool_Pool_01_Plate02.raw	Raw
	CSF_Pool_Pool_Pool_Pool_Pool_Pool_02_Plate01.raw	Raw
	CSF_Pool_Pool_Pool_Pool_Pool_Pool_02_Plate02.raw	Raw
	CSF_Pool_S002_S028_S071_S111_Pool_01.raw	Raw

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Publications

Proteomes of Paired Human Cerebrospinal Fluid and Plasma: Relation to Blood-Brain Barrier Permeability in Older Adults.

Dayon Loïc L Cominetti Ornella O Wojcik Jérôme J Galindo Antonio Núñez AN Oikonomidi Aikaterini A Henry Hugues H Migliavacca Eugenia E Kussmann Martin M Bowman Gene L GL Bowman Gene L GL Popp Julius J

Journal of proteome research 20190215 3

The systems-level relationship between the proteomes of cerebrospinal fluid (CSF) and plasma has not been comprehensively described so far. Recently developed shotgun proteomic workflows allow for deeper characterization of the proteomes from body fluids in much larger sample size. We deployed state-of-the-art mass spectrometry-based proteomics in paired CSF and plasma samples volunteered by 120 elders with and without cognitive impairment to comprehensively characterize and examine compartmenta ...[more]

PMID: 30702894

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Project description:Being inspired by metabolomic data processing, we have developed a bioinformatic pipeline that optimizes the processing of mass spectral data obtained from isobaric Tandem Mass Tag (TMT) experiments. Our method focuses on the tandem mass spectral level by first quantifying and then identifying (QtI), while preserving unidentified spectra for further investigations. The raw datasets were previously generated [1, 2]. Two-proteome model experiments were considered where identical pools of human CSF or plasma samples were mixed with E. coli samples at different concentrations. E. coli protein extract was spiked in 400 µL of CSF at amounts of 0, 2, 3, 5, 6.25, and 7.5 µg. Such sets of 6 spiked CSF samples were prepared in triplicate for comparison using sixplex isobaric tagging and analyzed in triplicates on two independent but identical LC MS/MS, for a total of 18 raw files [1]; this experiment is called “CSF-E.coli”. E. coli protein extract was spiked at 0, 2.5, 5, 6.25, 12.5, and 25 µg in 30 µL human plasma. Such sets of 6 spiked plasma samples were prepared in quadruplicate for comparison using sixplex isobaric tagging and analyzed in triplicates on one LC MS/MS, for a total of 12 raw files [2]; this experiment is referred as “Plasma-E.coli”.The so-called “96samples-CSF” experiment consists of 16 replicate TMT sixplex experiments measuring identical CSF samples from the pool described above [2], analyzed in triplicates on one LCMS/MS for a total of 48 raw files. The so-called “96samples-plasma” experiment consists of 16 replicate TMT sixplex experiments measuring identical plasma samples from the pool described before, analyzed in triplicates on one LC MS/MS for a total of 48 raw files [1]. References: [1] Dayon, L., Núñez Galindo, A., Corthésy, J., Cominetti, O. & Kussmann, M. Comprehensive and scalable highly automated MS-based proteomic workflow for clinical biomarker discovery in human plasma. J. Proteome Res. 13, 3837-3845 (2014). [2] Núñez Galindo, A., Kussmann, M. & Dayon, L. Proteomics of Cerebrospinal Fluid: Throughput and Robustness Using a Scalable Automated Analysis Pipeline for Biomarker Discovery. Anal. Chem. 87, 10755-10761 (2015).