Fractional response analysis reveals logarithmic cytokine responses in cellular populations

Karol Nienałtowski, Rachel E. Rigby, Jarosław Walczak, Karolina E. Zakrzewska, Edyta Głów, Jan Rehwinkel and Michał Komorowski ()
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Karol Nienałtowski: Institute of Fundamental Technological Research, Polish Academy of Sciences
Rachel E. Rigby: University of Oxford
Jarosław Walczak: Institute of Fundamental Technological Research, Polish Academy of Sciences
Karolina E. Zakrzewska: Institute of Fundamental Technological Research, Polish Academy of Sciences
Edyta Głów: Institute of Fundamental Technological Research, Polish Academy of Sciences
Jan Rehwinkel: University of Oxford
Michał Komorowski: Institute of Fundamental Technological Research, Polish Academy of Sciences

Nature Communications, 2021, vol. 12, issue 1, 1-10

Abstract: Abstract Although we can now measure single-cell signaling responses with multivariate, high-throughput techniques our ability to interpret such measurements is still limited. Even interpretation of dose–response based on single-cell data is not straightforward: signaling responses can differ significantly between cells, encompass multiple signaling effectors, and have dynamic character. Here, we use probabilistic modeling and information-theory to introduce fractional response analysis (FRA), which quantifies changes in fractions of cells with given response levels. FRA can be universally performed for heterogeneous, multivariate, and dynamic measurements and, as we demonstrate, quantifies otherwise hidden patterns in single-cell data. In particular, we show that fractional responses to type I interferon in human peripheral blood mononuclear cells are very similar across different cell types, despite significant differences in mean or median responses and degrees of cell-to-cell heterogeneity. Further, we demonstrate that fractional responses to cytokines scale linearly with the log of the cytokine dose, which uncovers that heterogeneous cellular populations are sensitive to fold-changes in the dose, as opposed to additive changes.

Date: 2021
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DOI: 10.1038/s41467-021-24449-2

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