Large-scale single-cell analyses are of fundamental importance in order to capture biological heterogeneity within complex cell systems, but have largely been limited to RNA-based technologies. Here we present a comprehensive benchmarked experimental and computational workflow, which establishes global single-cell mass spectrometry-based proteomics as a tool for large-scale single-cell analyses. By exploiting a primary leukemia model system, we demonstrate both through pre-enrichment of cell populations and through a non-enriched unbiased approach that our workflow enables the exploration of cellular heterogeneity within this aberrant developmental hierarchy. Our approach is capable of consistently quantifying ~1000 proteins per cell across thousands of individual cells using limited instrument time. Furthermore, we develop a computational workflow (SCeptre) that effectively normalizes the data, integrates available FACS data and facilitates downstream analysis. The approach presented here lays a foundation for implementing global single-cell proteomics studies across the world.

Key words: acute myeloid leukemia / computational biology / proteomics / single-cell approaches / tandem mass tags (TMT)Final character count: 47,782 AbstractIn recent years, cellular life science research has experienced a significant shift, moving away from conducting bulk cell interrogation towards single-cell analysis. It is only through single cell analysis that a complete understanding of cellular heterogeneity, and the interplay between various cell types that are fundamental to specific biological phenotypes, can be achieved. Single-cell assays at the protein level have been predominantly limited to targeted, antibody-based methods. However, here we present an experimental and computational pipeline, which establishes a comprehensive single-cell mass spectrometry-based proteomics workflow.By exploiting a leukemia culture system, containing functionally-defined leukemic stem cells, progenitors and terminally differentiated blasts, we demonstrate that our workflow is able to explore the cellular heterogeneity within this aberrant developmental hierarchy. We show our approach is capable to quantifying hundreds of proteins across hundreds of single cells using limited instrument time. Furthermore, we developed a computational pipeline (SCeptre), that effectively clusters the data and permits the extraction of cell-specific proteins and functional pathways. This proof-of-concept work lays the foundation for future global single-cell proteomics studies. Duployez et al, 2019;Ng et al, 2016), their accuracy has proven limitation when used as a proxy for protein levels (Vogel & Marcotte, 2012; Khan et al, 2013). Therefore, to gain a thorough understanding of what occurs in a cell at the protein level, on a global scale, MSbased approaches are the sole way to accomplish this. Being the cellular workhorses, there is much knowledge to be gained from mechanisms occurring at the protein level, either through enzyme activity, post-translational modifications or protein degradation/proteolysis; hence the great need for protein level approaches at the single-cell level.A few years ago, a novel type of flow cytometry was established; by combining traditional flow cytometry workflows with mass spectrometry, a new analysis method termed Mass Cytometry was developed, more commonly referred to as CyTOF (Newell et al, 2012;Bodenmiller et al, 2012). This allows the simultaneous readout of tens of markers simultaneously, allowing single-cell analysis of pre-defined sets of proteins or posttranslational modifications (PTMs). This method, however, relies heavily on previously