The EGFR demonstrates linear signal transmission

Signal integration and integral feedback control with biochemical reaction networks

Biochemical reaction networks perform a variety of signal processing functions, one of which is computing the integrals of signal values. This is often used in integral feedback control, where it enables a system's output to respond to changing inputs, but to then return exactly back to some pre-determined setpoint value afterward. To gain a deeper understanding of how biochemical networks are able to both integrate signals and perform integral feedback control, we investigated these abilities for several simple reaction networks. We found imperfect overlap between these categories, with some networks able to perform both tasks, some able to perform integration but not integral feedback control, and some the other way around. Nevertheless, networks that could either integrate or perform integral feedback control shared key elements. In particular, they included a chemical species that was neutrally stable in the open loop system (no feedback), meaning that this species does not have a unique stable steady-state concentration. Neutral stability could arise from zeroth order decay reactions, binding to a partner that was produced at a constant rate (which occurs in antithetic control), or through a long chain of covalent cycles. Mathematically, it arose from rate equations for the reaction network that were underdetermined when evaluated at steady-state.

Signaling pathways as linear transmitters

One challenge in biology is to make sense of the complexity of biological networks. A good system to approach this is signaling pathways, whose well-characterized molecular details allow us to relate the internal processes of each pathway to their input-output behavior. In this study, we analyzed mathematical models of three metazoan signaling pathways: the canonical Wnt, MAPK/ERK, and Tgfβ pathways. We find an unexpected convergence: the three pathways behave in some physiological contexts as linear signal transmitters. Testing the results experimentally, we present direct measurements of linear input-output behavior in the Wnt and ERK pathways. Analytics from each model further reveal that linearity arises through different means in each pathway, which we tested experimentally in the Wnt and ERK pathways. Linearity is a desired property in engineering where it facilitates fidelity and superposition in signal transmission. Our findings illustrate how cells tune different complex networks to converge on the same behavior.

The Effect of Nanoparticles on the Cluster Size Distributions of Activated EGFR Measured with Photobleaching Image Correlation Spectroscopy

The epidermal growth factor receptor (EGFR) is an important cell surface receptor in normal physiology and disease. Recent work has shown that EGF-gold nanoparticle conjugates can influence cell behaviour, but the underlying mechanism at the receptor quaternary structural level remains poorly understood.In the present work, the cluster density and cluster size of activated (phosphorylated) EGFR clusters in HeLa cells were determined with photobleaching image correlation spectroscopy. EGFR activation was probed via immunofluorescence-detected phosphorylation of tyrosines (pY-mAb) located in the kinase domain of EGFR (Y845) and at the EGFR cytoplasmic tail (Y1173). Cell activation was probed via nuclear extracellular-regulated kinase (ERK) phosphorylation. The cluster size of activated EGFR was 1.3-2.4 pY-mAb/cluster in unstimulated HeLa cells. EGF or nanorod treatment led to an increase in EGFR oligomers containing multiple phosphotyrosines (>2 phosphotyrosines per EGFR oligomer, average cluster size range = 3-5 pY-mAb/cluster) which paralleled increases in nuclear p-ERK. In contrast, EGF-nanorods decreased the contribution from higher-order phospho-clusters and decreased nuclear p-ERK relative to the nanorod control. These studies provide direct evidence that targeted nanotechnology can manipulate receptor organization and lead to changes in receptor activation and subsequent signalling processes.

Signaling Tug-of-War Delivers the Whole Message

How do cells transmit biochemical signals accurately? It turns out, pushing and pulling can go a long way.

Push-Pull and Feedback Mechanisms Can Align Signaling System Outputs with Inputs

Many cell signaling systems, including the yeast pheromone response system, exhibit "dose-response alignment" (DoRA), in which output of one or more downstream steps closely matches the fraction of occupied receptors. DoRA can improve the fidelity of transmitted dose information. Here, we searched systematically for biochemical network topologies that produced DoRA. Most networks, including many containing feedback and feedforward loops, could not produce DoRA. However, networks including "push-pull" mechanisms, in which the active form of a signaling species stimulates downstream activity and the nominally inactive form reduces downstream activity, enabled perfect DoRA. Networks containing feedbacks enabled DoRA, but only if they also compared feedback to input and adjusted output to match. Our results establish push-pull as a non-feedback mechanism to align output with variable input and maximize information transfer in signaling systems. They also suggest genetic approaches to determine whether particular signaling systems use feedback or push-pull control.