Biochemical feedback leads to dynamical transitions between cellular states, reminiscent of phase transitions in statistical physics. Yet it is unknown whether cells exhibit the scaling properties associated with phase transitions, and if they do, to which universality class or classes they belong. Here we show using a generic birth-death model that biochemical feedback near a bifurcation point exhibits the scaling exponents of the Ising universality class in the mean-field limit. The theory allows us to calculate an effective order parameter, temperature, external field, and heat capacity from T cell fluorescence data without fitting. Experiments agree with the scaling predictions, suggesting that this type of nonequilibrium criticality plays an important role in cell biology .
Positive feedback in biochemical networks can lead to a bifurcation in state space. Universality implies that if molecules are well mixed, this bifurcation should exhibit the critical scaling behavior of the Ising universality class in the mean-field limit. Making this statement quantitative requires the appropriate mapping between the biochemical parameters and the Ising parameters. Here we derive this mapping rigorously and uniquely for a broad class of stochastic birth-death models with feedback, and show that the expected static and dynamic critical exponents emerge. The generality of the mapping allows us to extract the order parameter, effective temperature, magnetic field, and heat capacity from T cell flow cytometry data without needing to know the underlying molecular details. We find that T cells obey critical scaling relations and exhibit critical slowing down, and that the heat capacity determines molecule number from fluorescence data. We demonstrate that critical scaling holds even as our system is driven out of its steady state, via the Kibble-Zurek mechanism for driven critical systems. Our approach places a ubiquitous biological mechanism into a known class of physical systems and is immediately applicable to other biological data .
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Biochemical feedback leads to dynamical transitions between cellular states, reminiscent of phase transitions in statistical physics. Yet it is unknown whether cells exhibit the scaling properties associated with phase transitions, and if they do, to which universality class or classes they belong. Here we show using a generic birth-death model that biochemical feedback near a bifurcation point exhibits the scaling exponents
Positive feedback in biochemical networks can lead to a bifurcation in state space. Universality implies that if molecules are well mixed, this bifurcation should exhibit the critical scaling behavior
R
The theory
Making this statement quantitative requires the appropriate mapping between the biochemical parameters and the Ising parameters. Here we derive this mapping rigorously and uniquely for a broad class of stochastic birth-death models with feedback, and show that the expected static and dynamic critical exponents emerge. The generality of the mapping
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calculate an effective
extract the
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temperature, external
effective temperature, magnetic
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fluorescence data without fitting. Experiments agree with the scaling predictions, suggesting that this type of nonequilibrium criticality plays an important role in cell biology
flow cytometry data without needing to know the underlying molecular details. We find that T cells obey critical scaling relations and exhibit critical slowing down, and that the heat capacity determines molecule number from fluorescence data. We demonstrate that critical scaling holds even as our system is driven out of its steady state, via the Kibble-Zurek mechanism for driven critical systems. Our approach places a ubiquitous biological mechanism into a known class of physical systems and is immediately applicable to other biological data