The concept of tissues as heterogeneous populations of cell types with diverse phenotypes is now well recognised thanks to single-cell transcriptomics. Although individual cell specialisation often arises from protein-mediated physiology, the understanding of differential translation remains limited. Current scRNA-seq technology upon which this is largely based can result in low sampling for many transcripts, leading to poor accuracy of digital mRNA counts and by extension, estimations of protein abundance.
Macrophages are innate immune cells with diverse functional and molecular phenotypes and important in a variety of diseases, including cancer, yet largely unexplored at the single-cell proteome level because of the limitations mentioned above.
Here, Specht et al further improve their earlier SCoPE-MS method using multiplexed LC-ESI-MS/MS (and including IonOpticks Aurora Series columns) for single-cell proteomics, to develop SCoPE2. This substantially increases quantitative accuracy and throughput, lowering cost and hands-on time through automated, miniaturised sample preparation.
Analysing the emergence of cellular heterogeneity as homogeneous monocytes differentiate into macrophage-like cells, the method’s output enables identification of 1490 single cells by type, in 10 days of instrument time.
Furthermore, the data suggests that even when originating from homogeneous monocytes exposed to identical environmental conditions, macrophage proteomes are found to be heterogeneous across a continuous gradient of proteome states, correlating to a polarization axis that was previously described to emerge in the presence of cytokines.
Such data could support clinical applications such as biomarker discovery across a range of diseases, and permit inferring direct causal mechanisms underlying the functions of protein networks. The more cells and proteoforms are quantified, the fewer assumptions are needed for this type of analysis.
Read the full paper
Single-cell proteomic and transcriptomic analysis of macrophage heterogeneity using SCoPE2.
Genome Biol. 22, 27 Jan 2021. doi: https://doi.org/10.1186/s13059-021-02267-5
Harrison Specht, Edward Emmott, Aleksandra A. Petelski, R. Gray Huffman, David H. Perlman, Marco Serra, Peter Kharchenko, Antonius Koller & Nikolai Slavov.
Commentary by Jarrod Sandow, PhD.
About the author
Jarrod has a background in biotechnology and completed his PhD at the Institute of Medical and Veterinary Science in Adelaide. He is a co-inventor of IonOpticks’ core technology and is driven towards developing innovative solutions for the global proteomics research community that will enable scientists and clinicians to discover more from their samples to accelerate advances in biological and medical research.