Caractérisation Compréhensive du Protéome de la Sueur et l'Identification de Potentiels Biomarqueurs de la Mucoviscidose : Optimisation de la Préparation d'Echantillons à parti d'une Nouvelle Approche Protéomique Basée sur la MS

Cystic Fibrosis (CF) is a hereditary disease responsible for the obstruction of channels transporting mucus fluids. The sweat test (ST), consisting of measuring Cl- levels in the sweat, allows to characterise patients with CF as they present high levels of chloride in their sweat. Although the combination of ST with multiple diagnosis approaches, a small fraction of the diagnosis remains inconclusive. MS-based proteomics allows to identify and quantify various proteins in the sweat simultaneously. This capability is crucial for discovering new CF biomarkers in the sweat and evaluating the effectiveness of therapeutic drugs by tracking changes in these biomarkers’ concentrations over time. The current sample preparation method consists of preconcentrating proteins via acetonitrile (ACN) precipitation and then solubilising them to subsequently reduce, alkylate, digest and finally analyse resulting peptides in an LC-TIMS-TOF instrument. Despite the efficiency of ACN precipitation, a significant amount of proteins is lost in the eliminated supernatant, reducing thus detection sensitivity. To address this limitation, we have investigated the “One Pot” sample preparation method, which allows direct preparation of sweat samples without ACN precipitation to recover all sweat proteins. The comparison between both sample preparation results showed 1289 proteins identified and quantified in both approaches, including 1114 common proteins and 167 exclusive One Pot proteins, against only 13 exclusive ACN precipitation proteins. Furthermore, proteins prepared with the One Pot approach showed an average signal intensity 1.6 times higher than those prepared with ACN precipitation. These results not only demonstrate the high sensitivity offered by the One Pot approach but also support its potential for automated, high-throughput analysis when paired with a sample preparation robot, a goal currently being in progress with the Mantis® robot.