Kristina Marx (Bremen / DE), Naomi Hoenisch Gravel (Tuebingen / DE), Juliane Walz (Tuebingen / DE), Torsten Mueller (Bremen / DE), Pierre-Olivier Schmit (Wissembourg / FR), Daniel Hornburg (San Jose, CA / US)
Introduction
The identification of peptide antigens presented by the major histocompatibility complex (MHC) provides important insights for the understanding of cancer, infectious or autoimmune diseases and for the design and development of the corresponding immunotherapies. However, the analysis of low-abundance peptides and their diverse sequences is still a challenge. In recent years, the tremendous increase of MS instruments sensitivity, coming along with more effective, multi-dimensional ("4D") acquisition modes allowing to efficiently target singly and multiply- charged precursors, has really boosted the number of immunopeptides that can be detected in an immunopeptidomics experiment. Nowadays, most of the proteomics applications use data independent acquisition for improved identification. Here we demonstrate the use of dia-PASEF methods to further deepen the analysis of immunopeptides.
Methods
For method optimization varying concentrations of acute myeloid leukemia cell line EoL (HLA-A*24:02; A*298:02; B*35:03; B*44:03; C*04:01; C*16:01) were used. HLA class I ligands were isolated via immunoaffinity chromatography using the pan HLA class I-specific W6/32 monoclonal antibody. Chromatographic separation was done with a nanoElute 2 (Bruker) with gradient time of 22 or 45 minutes on a 25 cm / 75 µm ID column, pre-fitted nanoZero connection and integrated emitter tip (Aurora, IonOptics) coupled to a CaptiveSpray Ultra ionization source (Bruker). Samples were analyzed using 300Hz PASEF and dia-PASEF methods with varying parameters for method optimization on a timsTOF Ultra (Bruker). Raw data were processed in Spectronaut 19.
Preliminary Data
Data Dependent Analysis (DDA) is still widely used for immunopeptidomics studies for their compatibilities with DeNovo sequencing and their ability to be used with very large antigen sequence databases. Using a high sensitivity PASEF method for low sample amounts on the timsTOF SCP with additional inclusion of singly charged precursors (>700 m/z) resulted in improved identification of class I immunopeptides. We have further optimized the method on the timsTOF Ultra to improve the sensitivity and speed of the analysis. This opens the door for the use of shorter gradients (45 min and 22 min) without losing identifications and sensitivity compared to previous set-ups. Data independent analysis acquisition methods, however, are becoming the standard approach for proteomics analysis and can be used for immunopeptidomics when the database size allows for it. Here, we evaluate the use of dia-PASEF methods for immunopeptidomics to increase immunopeptide identifications especially on low sample inputs. In addition, we discuss the challenges of using unspecific searches in dia workflows.