IN VIVO LARGE SCALE MAPPING OF PROTEIN TURNOVER IN THE HUMAN CEREBROSPINAL FLUID

Sylvain Lehmann (1, 2) , Christophe Hirtz (1) , Jérôme Vialaret (1, 2) , Maxence Ory (3) , Guillaume Gras Combes (2, 4) , Marine Le Corre (4, 2) , Stéphanie Badiou (5, 2) , Jean-Paul Cristol (5, 2) , Olivier Hanon (6, 7) , Emmanuel Cornillot (3) , Luc Bauchet (8, 4) , Audrey Gabelle (1, 9, 2) , Jacques Colinge (3, 2)

1 Cellules Souches, Plasticité Cellulaire, Médecine Régénératrice et Immunothérapies (IRMB)
2 CHRU Montpellier - Centre Hospitalier Régional Universitaire [Montpellier]
3 IRCM - U1194 Inserm - UM - Institut de Recherche en Cancérologie de Montpellier
4 Service de Neurochirurgie [CHRU Montpellier]
5 PhyMedExp - Physiologie & médecine expérimentale du Cœur et des Muscles [U 1046]
6 Dpt Gériatrie [CHU Broca]
7 UPD5 - Université Paris Descartes - Paris 5
8 INM - Institut des Neurosciences de Montpellier
9 CMRR - Centres Mémoire de Ressources et de Recherche Montpellier

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 of neuron biology- and immune system-related proteins, including many biomarkers and drug targets. This first large data set unraveled a significant relationship between turnover and protein origin that relates to our ability to investigate organ physiology with protein-labeling strategy specifics. Our data constitute the first draft of CSF proteome dynamics as well as a repertoire of peptides for the community to design new analyses. The disclosed methods apply to other fluids or tissues provided sequential sample collection can be performed. We show that the proposed mathematical modeling applies to other analytical methods in the field.

Domaines: Génomique, Transcriptomique et Protéomique [q-bio.GN]; Neurobiologie

Sylvain Lehmann, Christophe Hirtz, Jérôme Vialaret, Maxence Ory, Guillaume Gras Combes, et al.. IN VIVO LARGE SCALE MAPPING OF PROTEIN TURNOVER IN THE HUMAN CEREBROSPINAL FLUID. Analytical Chemistry, 2019, 91 (24), pp.15500-15508. ⟨10.1021/acs.analchem.9b03328⟩. ⟨hal-02368099⟩