Quantifying information accumulation encoded in the dynamics of biochemical signaling

Ying Tang, Adewunmi Adelaja, Felix X.-F. Ye, Eric Deeds, Roy Wollman () and Alexander Hoffmann ()
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Ying Tang: University of California
Adewunmi Adelaja: University of California
Felix X.-F. Ye: Johns Hopkins University
Eric Deeds: University of California
Roy Wollman: University of California
Alexander Hoffmann: University of California

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

Abstract: Abstract Cellular responses to environmental changes are encoded in the complex temporal patterns of signaling proteins. However, quantifying the accumulation of information over time to direct cellular decision-making remains an unsolved challenge. This is, in part, due to the combinatorial explosion of possible configurations that need to be evaluated for information in time-course measurements. Here, we develop a quantitative framework, based on inferred trajectory probabilities, to calculate the mutual information encoded in signaling dynamics while accounting for cell-cell variability. We use it to understand NFκB transcriptional dynamics in response to different immune threats, and reveal that some threats are distinguished faster than others. Our analyses also suggest specific temporal phases during which information distinguishing threats becomes available to immune response genes; one specific phase could be mapped to the functionality of the IκBα negative feedback circuit. The framework is generally applicable to single-cell time series measurements, and enables understanding how temporal regulatory codes transmit information over time.

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-21562-0

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DOI: 10.1038/s41467-021-21562-0

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