Kavli Affiliate: Jos W. Zwanikken
| First 5 Authors: Tamara Mijatović, Aimée R. Kok, Jos W. Zwanikken, Marianne Bauer,
| Summary:
Transcription factor concentrations provide signals to cells that allow them
to regulate gene expression to make correct cell fate decisions. Calculations
for noise bounds in gene regulation suggest that clustering or cooperative
binding of transcription factors decreases signal-to-noise ratios at binding
sites. However, clustering of transcription factor molecules around binding
sites is frequently observed. We develop two complementary models for
clustering transcription factors at binding site sensors that allow us to study
information transfer from a signal to a variable relevant to development,
namely future cell fates, on the example of the signal morphogen Bicoid in
early fly development. We find that weak cooperativity or clustering can allow
for maximal information transfer, especially about the relevant variable. Why
clustering is beneficial for transfer depends on how long the binding site
sensor measures the signal before affecting downstream gene expression: for
short measurements, clustering allows for the implementation of a switch, while
for long measurements, weak clustering allows the sensor to access maximal
developmental information provided in a nonlinear signal. Finally, we find that
clustering can facilitate binding site sensors to achieve an optimal bound to
molecular sensing, the information bottleneck (IB) bound. This IB optimality
appears consistent with a biologically intuitive optimization.
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