The Energetic Cost of Information Transfer between Cells: A New Tool for Studying Cellular Networks

The Energetic Cost of Information Transfer between Cells: A New Tool for Studying Cellular Networks

Understanding the intricate communication processes between cells and molecular components is vital for comprehending the behaviors and functions of living organisms. Recent research conducted by scientists at Yale University introduces a groundbreaking tool for studying cellular networks and exploring the energetic cost of information transfer. This article critically analyzes the study and its implications, providing insights into the findings and potential future applications.

The study by Benjamin B. Machta and Samuel J. Bryant draws inspiration from previous research carried out in the late 90s, particularly the work of Simon Laughlin and his colleagues. Laughlin’s team attempted to determine the energy expenditure of neurons during information transmission. Machta explains that their findings indicated energy costs ranging between 104-107 KBT/bit, significantly higher than the ‘fundamental’ Landauer bound. This raises the question of whether biological systems are simply wasteful or if there are additional costs involved. The researchers aim to uncover these costs and determine their significance.

Another objective of Machta and Bryant’s study was to explore why distinct physical mechanisms are employed for communication in different situations. Neurons primarily use electrical signals to communicate, while other cell types utilize diffusion of chemicals. The researchers sought to understand the energy costs associated with each mechanism on a per-bit basis. Utilizing relatively simple models, they calculated lower bounds on the energy required to power a channel and drive physical currents in biological systems. They discovered that a geometric factor, determined by the size of the sender and receiver, contributes to the overall cost. For example, for electrical signaling, the cost per bit scales with the distance between sender and receiver, as well as the sizes of the sender and receiver. The calculations emphasize that these costs can be significantly higher than the lower bounds suggested by simpler arguments.

Overall, Machta and his colleagues’ calculations confirm the high energetic cost associated with the transfer of information between cells. These estimations could potentially explain the observed high cost of information processing in experimental studies. The researchers acknowledge that their explanation is not as “fundamental” as the Landauer bound, as it depends on the geometry and physical details of neurons and ion channels. However, if these details are significant, it suggests that the efficiency of biological systems should be reconsidered. Neurons, for example, may be operating at the limits of information and energy, rather than being inherently inefficient. While these calculations do not definitively prove the efficiency of any specific system, they do highlight the potential for substantial energy costs when transmitting information through space.

Machta and his colleagues’ recent work has the potential to inform new and interesting biological studies. In addition to estimating energetic costs, the researchers introduced a “phase diagram” that represents situations where the selective use of specific communication strategies is optimal. This diagram has the potential to enhance our understanding of the design principles behind different cell signaling strategies. For instance, it may shed light on why neurons utilize chemical diffusion at synapses but rely on electrical signals for long-range communication. Furthermore, it could help explain why E. coli bacteria employ diffusion to communicate information about their chemical environment. The researchers are currently working on applying this framework to understand the energetics of concrete signal transduction systems, as real systems involve complex information processing networks.

The study conducted by Machta and Bryant introduces a valuable tool for studying cellular networks and calculating the energetic cost of information transfer. By critically analyzing and estimating these costs, the researchers provide insights into the efficiency and functional limitations of biological systems. Their findings open up new possibilities for understanding the design principles of cell signaling strategies and may lead to further advancements in biological studies. The complex nature of cellular communication requires continuous research and exploration to unravel the mysteries of life’s fundamental processes.


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