Using topology to tame the complex biochemistry of genetic networks

Abstract

Living cells are controlled by networks of interacting genes, proteins and biochemicals. Cells use the emergent collective dynamics of these networks to probe their surroundings, perform computations and generate appropriate responses. Here, we consider genetic networks, interacting sets of genes that regulate one another’s expression. It is possible to infer the interaction topology of genetic networks from high-throughput experimental measurements. However, such experiments rarely provide information on the detailed nature of each interaction. We show that topological approaches provide powerful means of dealing with the missing biochemical data. We first discuss the biochemical basis of gene regulation, and describe how genes can be connected into networks. We then show that, given weak constraints on the underlying biochemistry, topology alone determines the emergent properties of certain simple networks. Finally, we apply these approaches to the realistic example of quorum-sensing networks: chemical communication systems that coordinate the responses of bacterial populations.

Logical-continuous modelling of post-translationally regulated bistability of curli fiber expression in Escherichia coli

“…In order to understand the principles of its regulation, a thorough combination of wet-lab experimentation and mathematical modelling is required. Many computational studies of bistable systems focused either on the network topology [ 17 , 18 ] or on reaction kinetics [ 19 , 21 ]. Here, we combined these two approaches.…”

“…[ 14 – 16 ]). Consequently, it is a well-suited approach for investigating bistable systems, where there is evidence that qualitative properties, in particular the network topology, are crucial determinants [ 17 , 18 ]. However, the low detail resolution of such models only allows for a preliminary understanding, and the biological interpretation of the results is not always straightforward.…”

Breast cancer causes and treatment: where are we going wrong?

“…Rather, the system is very complex, allowing for nonlinear, nontargeted, and chaotic elements, including the emergence of unpredictable responses determined by epigenetic influences layered onto an underlying genetic background. 73 , 74 In relation to the breast, it is part of the reproductive system, and is unique in that it only becomes fully formed in early life after puberty. Breast tissue changes with hormonal fluctuation during the menstrual cycle and during pregnancy.…”

Inference for the physical sciences

“…The next six papers consider statistical tools for particular problems and are discussed in more detail below [35,36,44,45,51,52]. waves [47], systems biology [53], biological physics (time series) [37] and atmospheric physics [54]. The last paper of the issue [55] addresses the challenging and exciting problem of inferring an appropriate, interpretable, dynamical model (for symbolic time-series data), given relatively weak constraints on the structure of that model.…”

“…We first consider methods to probe biological networks [53]: in this review, the operation of regulatory networks is explained and the inference of biochemical reactions is placed in their network context. Little & Jones [37] discuss the noisy steppy signals that are produced in the measurements of some cellular and molecular systems: example experimental methods and data types are outlined and tools for probing them are described.…”