Abstract

Complex gene regulation requires responses that depend not only on the current levels of input signals but also on signals received in the past. In digital electronics, logic circuits with this property are referred to as sequential logic, in contrast to the simpler combinatorial logic without such internal memory. In molecular biology, memory is implemented in various forms such as biochemical modification of proteins or multistable gene circuits, but the design of the regulatory interface, which processes the input signals and the memory content, is often not well understood. Here, we explore design constraints for such regulatory interfaces using coarse-grained nonlinear models and stochastic simulations of detailed biochemical reaction networks. We test different designs for biological analogs of the most versatile memory element in digital electronics, the JK-latch. Our analysis shows that simple protein-protein interactions and protein-DNA binding are sufficient, in principle, to implement genetic circuits with the capabilities of a JK-latch. However, it also exposes fundamental limitations to its reliability, due to the fact that biological signal processing is asynchronous, in contrast to most digital electronics systems that feature a central clock to orchestrate the timing of all operations. We describe a seemingly natural way to improve the reliability by invoking the master-slave concept from digital electronics design. This concept could be useful to interpret the design of natural regulatory circuits, and for the design of synthetic biological systems.

Highlights

  • It is notoriously difficult to decipher the gene regulatory program of even simple organisms

  • We choose the original design of Gardner et al [22] as memory unit (Fig. 1D), since our focus is on general questions of biological signal processing with such a memory unit, not so much on practical concerns for synthetic biology implementations

  • In principle, that gene regulatory circuits can perform logical operations involving internal memory, it is not known to what extent this capability is used in natural systems

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Summary

Introduction

It is notoriously difficult to decipher the gene regulatory program of even simple organisms. Despite the ongoing massive innovation in quantitative biology, the current experimental approaches typically do not characterize the relevant set of regulatory interactions in sufficient quantitative detail to directly read out the system behavior (the physiology) from the data. The conundrum is that guidance by theoretical hypotheses about how a regulatory system functions is essential to understand the system, while we already need some understanding of the design principles of biological signal processing to generate such hypotheses. Insight into these design principles may be gained from the synthetic biology approach of combining biomolecular parts to obtain various functions [3,4]. The salient question is which types of signal processing functions are relevant for biological organisms?

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