Dataset Information

Unbiased mapping of human cerebrospinal fluid proteome dynamics - Profile data

ABSTRACT: Our purpose is to explore the dynamics of a clinically relevant proteome by determining protein turnover, synthesis and breakdown. ]. The alteration of protein turnover represents a new type of biological information which might provide unique insight in disease pathophysiology, e.g. Alzheimer disease (AD), amyotrophic lateral sclerosis or diabetes. The use of tracer methods makes it however possible to follow protein synthesis on a proteome-scale based on the incorporation of stable isotope-labeled precursors such as 13C6-leucine. The latest mass spectrometry (MS) technologies on quantitative approach called stable isotope labeling kinetics (SILK) was applied to humans after the intravenous administration of 13C6-leucine. The SILK approach has therefore the potential to generate unique in vivo information that is not accessible using classical quantitative techniques. As a matter of fact, the concentration of a given protein in a tissue or a biological fluid is the combination of multiple events and mechanisms. The translation rate at the cellular level is obviously the initial determinant which will directly impact the presence/absence of a given protein. Translation is dependent on transcription and its genetic and epigenetic regulation. Transcriptomics is therefore one of the way to follow protein synthesis, but it is known that it reflects only partially protein concentration. In fact, many subsequent events will modify protein presence starting by post-translational maturation (which in case of pathologic mutation could lead to proteins misfolding, degradation or mis-trafficking. In our study, we are focusing on CSF proteins which originate locally from resident cells (lymphocytes...) or after compartment transfer, from central nervous system (CNS) and systemic tissues. In this work, we relied on high resolution MS (HRMS) to follow the kinetics incorporation of labelled Leucine in thousands of peptides corresponding to hundreds of proteins and their isoforms. This new approach necessitated first to develop original data processing and modelling of protein turnover which is the foundation for the SILK analysis of other types of samples, including blood and urine. The information that derived from this type of large scale analysis will help build a new vision of human physiology based on protein turnovers, and compartment transfer investigation.

INSTRUMENT(S): maXis

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cerebrospinal Fluid

SUBMITTER: Jerome Vialaret

LAB HEAD: Sylvain Lehmann

PROVIDER: PXD012502 | Pride | 2020-01-22

REPOSITORIES: Pride

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In Vivo Large-Scale Mapping of Protein Turnover in Human Cerebrospinal Fluid.

Lehmann Sylvain S Hirtz Christophe C Vialaret Jérôme J Ory Maxence M Combes Guillaume Gras GG Corre Marine Le ML Badiou Stéphanie S Cristol Jean-Paul JP Hanon Olivier O Cornillot Emmanuel E Bauchet Luc L Gabelle Audrey A Colinge Jacques J

Analytical chemistry 20191202 24

The extraction of accurate physiological parameters from clinical samples provides a unique perspective to understand disease etiology and evolution, including under therapy. We introduce a new methodologic framework to map patient proteome dynamics in vivo, either proteome-wide or in large targeted panels. We applied it to ventricular cerebrospinal fluid (CSF) and could determine the turnover parameters of almost 200 proteins, whereas a handful were known previously. We covered a large number o ...[more]

PMID: 31730336

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Project description:Our purpose is to explore the dynamics of a clinically relevant proteome by determining protein turnover, synthesis and breakdown. ]. The alteration of protein turnover represents a new type of biological information which might provide unique insight in disease pathophysiology, e.g. Alzheimer disease (AD), amyotrophic lateral sclerosis or diabetes. The use of tracer methods makes it however possible to follow protein synthesis on a proteome-scale based on the incorporation of stable isotope-labeled precursors such as 13C6-leucine. The latest mass spectrometry (MS) technologies on quantitative approach called stable isotope labeling kinetics (SILK) was applied to humans after the intravenous administration of 13C6-leucine. The SILK approach has therefore the potential to generate unique in vivo information that is not accessible using classical quantitative techniques. As a matter of fact, the concentration of a given protein in a tissue or a biological fluid is the combination of multiple events and mechanisms. The translation rate at the cellular level is obviously the initial determinant which will directly impact the presence/absence of a given protein. Translation is dependent on transcription and its genetic and epigenetic regulation. Transcriptomics is therefore one of the way to follow protein synthesis, but it is known that it reflects only partially protein concentration. In fact, many subsequent events will modify protein presence starting by post-translational maturation (which in case of pathologic mutation could lead to proteins misfolding, degradation or mis-trafficking. In our study, we are focusing on CSF proteins which originate locally from resident cells (lymphocytes...) or after compartment transfer, from central nervous system (CNS) and systemic tissues. In this work, we relied on high resolution MS (HRMS) to follow the kinetics incorporation of labelled Leucine in thousands of peptides corresponding to hundreds of proteins and their isoforms. This new approach necessitated first to develop original data processing and modelling of protein turnover which is the foundation for the SILK analysis of other types of samples, including blood and urine. The information that derived from this type of large scale analysis will help build a new vision of human physiology based on protein turnovers, and compartment transfer investigation.

			Action	DRS
	281474976713245.mgf	Mgf
	F002190.baf	Other
	F002190.dat	Other
	SILAV_F1_14a_01_1582.baf	Other
	SILAV_F1_14b_01_1521.baf	Other