Receptor crosstalk improves concentration sensing of multiple ligands

Cells need to reliably sense external ligand concentrations to achieve various biological functions such as chemotaxis or signaling. The molecular recognition of ligands by surface receptors is degenerate in many systems leading to crosstalk between different receptors. Crosstalk is often thought of as a deviation from optimal specific recognition, as the binding of non-cognate ligands can interfere with the detection of the receptor's cognate ligand, possibly leading to a false triggering of a downstream signaling pathway. Here we quantify the optimal precision of sensing the concentrations of multiple ligands by a collection of promiscuous receptors. We demonstrate that crosstalk can improve precision in concentration sensing and discrimination tasks. To achieve superior precision, the additional information about ligand concentrations contained in short binding events of the non-cognate ligand should be exploited. We present a proofreading scheme to realize an approximate estimation of multiple ligand concentrations that reaches a precision close to the derived optimal bounds. Our results help rationalize the observed ubiquity of receptor crosstalk in molecular sensing

Geometry And Topology Of Optimal Flow Networks

Hidden inside the design of a living network is the key to its function: above all else, nature searches for a pathway to survival. Every naturally evolved network is a step in the path to reach an optimized state, even if it has not yet been achieved, and in the physicist\u27s view, some energy function that is in the process of becoming minimized. The problem is figuring what exactly is being minimized, weighing the contributions from operational costs, performance, and robustness to disturbances. Understanding the structural rules for these networks has profound implications for artificial network design in fields ranging from transportation to medicine. The focus of this work is transport networks in biological systems, specifically plant and animal vasculature. The overarching themes are adaptation, optimality, and the link between structure and function in complex networks. We first examine hierarchy in networks, showing that such organization may allow networks to maintain functionality in unstable conditions such as perturbative damage or fluctuating loads. We then turn our attention to principles of optimization in perfusive flow networks. We show that including perfusion dynamics on top of the simple flow equations allows us to identify the geometric rules controlling the structure of uniformly perfusing networks