Refining advanced sample preparation and nanoLC-MS/MS analysis techniques for single-cell proteomics

Introduction: Recent advancements, such as the integration of TIMS coupled to a high sensitivity mass spectrometer (TimsQTOF) with automated processes, have significantly enhanced the precision and efficiency of single-cell proteome analysis. In addition, the control of ion populations is advancing in tandem with instrumental innovations, enabling the creation of new precursor scan designs and the management of their fragmentation concurrently with their accumulation. Notably, the emergence of DIA-PASEF (Data-Independent Acquisition - Parallel Accumulation Serial Fragmentation) technology allows for the successive isolation and fragmentation of all precursors within selected mass windows, significantly enhancing analytical efficiency and depth.

Methods: After five washes with frozen PBS, freshly prepared HeLa cells were diluted to a final concentration of approximately 200 cells/µL. Sorting, lysis, and digestion were performed using the CellenONE instrument (Cellenion, Lyon). To optimize the sample preparation, various parameters were adjusted: the protein-to-protease digestion ratio (1:1, 1:10, 1:20, and 1:50), digestion times (30 minutes, 1 hour, 1.5 hours, and 2 hours), robot humidity levels (75%, 85%, and 90%), and the final volume of peptide recovery (1 µL, 2 µL, 3 µL, and 3.5 µL). Additionally, different sample plates, namely the proteoCHIP and EVO96, were evaluated as targets for the sample preparation workflow. Peptide mixtures were separated on an Aurora C18-RP 100Å (75µm x 250mmx1.5µm) and C18-RP 120Å (75µmx50cmx1.7µm) (IonOpticks) columns using a nanoElute 2 coupled to a timsTOFUltra (Bruker Daltonics) mass spectrometer. Separation was performed on a gradient from 5 to 35% ACN in 0.1% FA over 30min and 14min at 0.25µL/min. Data Independent Acquisition – PASEF (DIA-PASEF) and Slice-PASEF were performed followed by a comparative analysis to assess the performance of the direct-DIA against the spectral library processing using DIA-NN.

Results: Following the extensive method optimizations, more than 3500 proteins could be identified in single HeLa cells. We observe a non-significant difference between data processing with and without spectral libraries. Building on these advancements, our focus is now on demonstrating that the optimized workflow can be successfully applied to characterize the cellular heterogeneity in B-cell mantle lymphomas. Promising preliminary results allow us to aim at reaching a proteome depth of 1200 proteins in single B-lymphocytes.

Conclusion: While still requiring method refinements at all steps of the workflow, SCP starts delivering biological valuable results and the proteome coverage reached is compatible with its application for a deeper understanding of to diseases characterized by cellular heterogeneity.