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Chemodetection in fluctuating environments: Receptor coupling, buffering, and antagonism

Significance Cells have to reliably process biochemical signals in the presence of many different sources of information. For instance, immune cells have to discriminate foreign peptides from many potentially similar self-peptides, which sometimes lead to the absence of active decision even in the presence of infection (a process called antagonism). In this article, we mathematically formalize this chemodetection problem. By contrasting two types of models for ligand detection (independent or coupled receptors) we show that if environmental noise is not statistically negligible (e.g., “long-tailed”), antagonism can be advantageous to buffer undesirable fluctuations in environmental composition. Variability in the chemical composition of the extracellular environment can significantly degrade the ability of cells to detect rare cognate ligands. Using concepts from statistical detection theory, we formalize the generic problem of detection of small concentrations of ligands in a fluctuating background of biochemically similar ligands binding to the same receptors. We discover that in contrast with expectations arising from considerations of signal amplification, inhibitory interactions between receptors can improve detection performance in the presence of substantial environmental variability, providing an adaptive interpretation to the phenomenon of ligand antagonism. Our results suggest that the structure of signaling pathways responsible for chemodetection in fluctuating and heterogeneous environments might be optimized with respect to the statistics and dynamics of environmental composition. The developed formalism stresses the importance of characterizing nonspecific interactions to understand function in signaling pathways.