Keynote 2 - Applying a Proteoform profiling method

Keynote 2 - Applying a Proteoform profiling method for neurological disorder biomarker discovery Jerome Vialaret1, Sylvain Lehmann1, Audrey Gabelle1,2, P.O Schmit and Christophe Hirtz1 1

Laboratoire de Biochimie et Protéomique Clinique, Institut de Médecine Régénératrice et de Biothérapie, CHU de Montpellier - Hôpital St. Eloi, Montpellier, France2 Centre Mémoire Ressources Recherche, CHU Montpellier, hôpital Gui de Chauliac, Montpellier. Université Montpellier I, Montpellier, F-34000 France.

Abstract Measuring the intact mass of proteins in tissue samples or biofluids has the advantage over bottom-up approaches to allow to reveal more directly major biological processes like alternative splicing, proteolytic processing or modification of PTM pattern distribution. MS profiling bring the information relative to the different proteoforms distribution encoded in the intact mass of proteins. Objectives:In this study we used the last-generation UHRQ-Tof to set up a protein profiling approach with the objective of detecting and identifying proteoforms that can discriminate neurological disorders. Material and Methods: Describe sample origin CSF samples were obtained from patients with ethical consent (i.e. patient who had a lumbar puncture to investigate headaches or memory complaints but for whom the etiological research was negative). 3 different groups were selected based on established diagnosis. Starting from 500µL of CSF, abundant proteins were depleted using specific protein precipitation and supernatant was cleaned on C18 cartridges before LC-MS injection. Samples were separated on a 2.1x150 mm (Phenomenex Aeris C4) and a 0.1x500 mm (Thermo ProSwift RP-4H) columns using Ultimate nano-RSLC system (Thermo Fischer Scientific). MS profiling was perfomed using impact II benchtop UHR-Q-Tof (Bruker Daltonics) via a CaptiveSpray nanoBooster ion source or ESI source (Bruker Daltonics), and operated in MS and auto MS/MS modes. Internal or external calibration was used. Data have been automatically processed (calibration with XXX, protein signal extraction with Dissect™ software, deconvolution and obtention of monoisotopic masses with SNAP™ software) using data Analysis 4.2 (Bruker Daltonics). Statistical analyses were performed on a modified version of the Profile Analysis 2.1 Software. Identifications were realized using the Top-Down Sequencing search functionality of BioTools 3.2 (Bruker Daltonics) and with Mascot 2.4 (Matrix Science). Results: Using High-Quality threshold protein detection, we detected over 1500 proteoforms (up to 35Kda proteins) with very high reproducibility. After specify statistical study, auto-LC MS/MS run based on a Scheduled Precursor List enabled the identification of XX proteoforms of interest. Current identified proteins are known to be linked to neuropathologies process as expected.

Conclusions: Thanks to the last generation UHRQ-TOF, combining large spectral dynamic range and high spectral quality in complex mixtures, we were able to deliver high-quality proteoform distribution. This new proteomic approach led to complementary biological information with classical bottom-up approaches. Neurological biomarkers identification based on our top-down approach allowed to identify up to XX differential regulated MS peaks and with their identification/validation.