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Clinical proteomics approaches rely mostly on the absolute quantification of specific targeted proteins and/or on global proteome quantification following a bottom-up approach [1, 2]. These quantitative data picture a global proteome in a steady-state. In this context, disease-relevant proteins or biomarkers are identified via detected differences in concentrations between sample or patient classes. In this work, the dynamical feature of the proteome was explored by focusing on protein turnover, synthesis and breakdown. SILK approach was developed and applied to human thanks to the use of heavy amino acid infusion: 13C6-Leucine. Briefly, after intravenous infusion of this non-radioactive tracer in Alzheimer’s disease (AD) patients and controls, blood and cerebrospinal fluid (CSF) was collected in kinetically for up to 36 hours. Associated to mass spectrometry (MS) and combined to a 2-compartment mathematical model, this SILK approach allows to quantify the production and clearance of proteins in vivo. Starting with more than 1200 proteins identified, the SILK approach using large-scale unbiased MS allows to follow in parallel kinetics of more than 200 proteins. The first SILK kinetics established on control patient permit to sort proteins with fast/moderate and slow turnover in human cerebrospinal fluid.
Intravenous administration of stable isotope labeled amino acid (¹³C6-leucine) to humans recently made it possible to study the metabolism of specific biomarkers in cerebrospinal fluid (CSF) using targeted mass spectrometry (MS). This labeling approach could be of great interest for monitoring many leucine-containing peptides in parallel, using high-resolution MS. This will make it possible to quantify the rates of synthesis and clearance of a large range of proteins in humans with a view to obtaining new insights into protein metabolism processes and the pathophysiology of diseases such as Alzheimer's disease.
It has been shown that certain disease states can be characterized by disturbances in protein production, accumulation, or clearance. In the central nervous system (CNS), alterations in metabolism of proteins such as amyloid-beta (Aβ), alpha-synuclein, or Tau may be the cause of neurodegenerative diseases such as Alzheimer's disease (AD) (Bateman, 2006). The SILAV approach based on the administration of a stable isotope labeled amino acid (13C6-leucine) in patients, kinetics sampling and high-resolution tandem mass spectrometry analysis allow to quantify the rates of synthesis and clearance of a large scale of proteins in humans. Using these unique capabilities, it can be used to get new insights of the physiopathology of neurodegenerative disease. Method: In vivo labeling was performed following the protocol of Bateman et al. CSF was collected kinetically every 3 hour during 24 hours, aliquoted and stored at-80°C. 40uL of CSF sample was denaturated (8M urea), reduced (DTT), alkylated (IAA), digested overnight (37°C) with LysC/trypsin mix (promega), and desalted with C18 tips. Tryptic peptide mix was fractionated using Strong Cation eXchange chromatography (SCX) and eluted in 5 distinct fractions. Denaturation, digestion, SCX prefractionation and clean up steps were automatized on 96-well plates with BRAVO assayMap (Agilent). Analysis of the CSF samples have been performed using Nano-RSLC (Dionex) coupled to Q-TOF Impact II (Bruker Daltonics) at 60K of resolution (1222 m/z). 13C6-leucine incorporation rates have been calculated using skyline software. Preliminary data: The aim of this study was to follow, for the first time, a maximum of peptides containing Leucine during 24 hours and then evaluate their rate of synthesis in contrast with previous targeted metabolic approaches (Bateman 2006). Knowing that direct analysis of CSF samples present a limited number of identified proteins (<200 proteins), our prefractionation approach allowed the identification of up to 1000 proteins, with a good sequence coverage (> 4500 peptides). Finally, 2300 peptides containing leucine, corresponding to 500 proteins were monitored using a skyline software homemade analysis method. Thanks to the SCX prefractionation, MS spectra obtained were more easy to analyze and allowed an automated integration of MS peptides peaks