Energy consumption and cooperation for optimal sensing

A group of international researchers composed of Wave Ngampruetikorn and David Schwab at City University New York and Greg Stephens in the physics department of the Vrije Universiteit Amsterdam, discovered that the strategies for organizing cellular chemical sensors (chemoreceptors) to maximize sensitivity depend both on how reliable these sensors are as well as the statistics of the quantities they sense.  

03/19/2020 | 1:32 PM

Chemical sensing is essential to biological function: bacteria infer the location of foods and toxins from chemical levels and our immune response relies on the ability to detect foreign molecules (often at very small concentrations). But we don't fully understand how cells perform these tasks so reliably. Greg Stephens and his group developed a model to understand the principles enabling such performance and their findings were recently published in Nature Communications.

Sensory estimations
Stephens explains: "Cells contain many sensory receptors on their surface which you can think of as analogous to the multiple airspeed meters - pitot tubes - that protrude from an airplane's nose. With multiple sensors, a natural question is how does a cell arrange the couplings between sensors in order to achieve the best overall sensory estimate."

Energy is precious
The researchers also wanted to understand under what conditions it would be important for the cell to spend energy. Stephens: "As with all living systems, energy is often a very precious commodity. Different sensory arrangements require different amounts of energy in the sensing process."

Understanding living systems
To answer these questions the researchers introduced a model which was simple enough to explore qualitatively but complex enough to illustrate the key phenomena, an approach to understanding living systems which is rooted in the tradition of theoretical physics. Stephens: "Our model develops the conceptually new domain of nonequilibrium sensing dynamics, thus providing a novel view on important earlier works in a variety of systems, from neural networks, to animal development and time-telling from multiple readout genes. We use the tools and concepts of statistical physics and information theory, which offer a quantitative language for understanding the trade-offs between energy consumption, interactions and information."

Energy not always improves performance
They found that the strategies for organizing cellular chemical sensors (chemoreceptors) to maximize sensitivity depend both on how reliable these sensors are as well as the statistics of the quantities they sense. Surprisingly, allowing a sensor complex to consume energy (nonequilibrium) does not always improve performance: energy consumption is only useful when the sensors themselves are reliable and the signals are redundant. Redundancy occurs when the signals at the two sensor sites are highly correlated, as might happen with two chemical species which are both products of the same process.

Stephens concludes: "Living systems are incredibly diverse in the phenomenology of their behaviour. Unlike particle physics or gravitation we don’t know the fundamental principles of life, or even if they exist.  In the context of optimal sensing, our work here provides a framework for seeking such principles."