Rapid advances in proteomics methods and technologies have enabled global and unbiased quantification of the molecular actuators of biological processes -- proteins -- in single-cells. By quantifying proteomic variability in single-cells, phenotypic inferences have been made to investigate the diversity of ostensibly homogeneous populations of cells, such as emergent polarizations in resting macrophages. Still, there remains an untapped potential to reverse these investigations, and instead use phenotypic variability from naturally heterogeneous cells to discover proteins novely associated with function. The variability of cellular responses, such as macrophages to an inflammatory stimulus, is likely explained by the variability in their respective initial proteomes. Here we demonstrate an approach that enables the inference of functional regulators of lipopolysacharide (LPS)-induced nucleocytoplasmic transport in THP-1 macrophages. We accomplished this by analyzing the proteomes of 3,412 single-macrophage nuclei before and up to 60 minutes after 1 ug/mL LPS stimulation, thus yielding a distribution of initial nuclear proteomes and enabling the probabilistic quantification of nucleocytoplasmic protein transport in response to brief LPS stimulation. We found that simple biophysical constraints, such as the quantity of nuclear pores, partially explain the variability in LPS-induced nucleocytoplasmic transport (P < 1e-15, r = 0.48). However, many other proteins were highly associated with the response. We evaluated the single-nucleus derived associations for 16 proteins, and found them to be highly predictive of their functional effects in validations by genetic perturbation. Together these results demonstrate the potential for (sub-)single-cell proteomics to infer functional regulation.
[doi:10.25345/C5959CK32]
[dataset license: CC0 1.0 Universal (CC0 1.0)]
Keywords: single-cell ; single-nucleus ; plexDIA ; protein transport ; macrophage
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Nikolai Slavov, Northeastern University, USA |
Submitting User: | jderks |
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Owner | Reanalyses | |
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