Landauer in the age of synthetic biology: energy consumption and information processing in biochemical networks

Abstract

A central goal of synthetic biology is to design sophisticated synthetic cellular circuits that can perform complex computations and information processing tasks in response to specific inputs. The tremendous advances in our ability to understand and manipulate cellular information processing networks raises several fundamental physics questions: How do the molecular components of cellular circuits exploit energy consumption to improve information processing? Can one utilize ideas from thermodynamics to improve the design of synthetic cellular circuits and modules? Here, we summarize recent theoretical work addressing these questions. Energy consumption in cellular circuits serves five basic purposes: (1) increasing specificity, (2) manipulating dynamics, (3) reducing variability, (4) amplifying signal, and (5) erasing memory. We demonstrate these ideas using several simple examples and discuss the implications of these theoretical ideas for the emerging field of synthetic biology. We conclude by discussing how it may be possible to overcome these limitations using "post-translational" synthetic biology that exploits reversible protein modification.

9 pages, 4 figures

References in corpus (13)

• Thermodynamic uncertainty relation for biomolecular processes
• High-precision test of Landauer's principle in a feedback trap
• Work and information processing in a solvable model of Maxwell's demon
• The thermodynamics of prediction
• Thermodynamic costs of information processing in sensory adaption
• Efficiency of cellular information processing
• Thermodynamics of statistical inference by cells
• Information-theoretic vs. thermodynamic entropy production in autonomous sensory networks
• The free energy cost of reducing noise while maintaining a high sensitivity
• Thermodynamic limits to information harvesting by sensory systems
• Correlations between the dynamics of parallel tempering and the free-energy landscape in spin glasses
• Generalized Landauer Bound as Universal Thermodynamic Entropy in Continuous Phase Transitions
• Prediction and Dissipation in Biochemical Sensing

Cited by in corpus (24)

• Stochastic thermodynamics of computation
• Thermodynamic Bound on the Asymmetry of Cross-Correlations
• Identifying feasible operating regimes for early T-cell recognition: The speed, energy, accuracy trade-off in kinetic proofreading and adaptive sorting
• Linear Irreversible Thermodynamics and Onsager Reciprocity for Information-driven Engines
• The free energy requirements of biological organisms; implications for evolution
• Energy consumption and cooperation for optimal sensing
• Landauer Principle and Thermodynamics of Computation
• Thermodynamic bounds on spectral perturbations, with applications to oscillations and relaxation dynamics
• Universal energy-accuracy tradeoffs in nonequilibrium cellular sensing
• Time-reversal symmetry breaking in the chemosensory array reveals mechanisms for dissipation-enhanced cooperative sensing
• Temporal precision of molecular events with regulation and feedback
• On non-ideal chemical-reaction networks and phase separation
• Optimal inference strategies and their implications for the linear noise approximation
• The Fitness Value of Information with Delayed Phenotype Switching: Optimal Performance with Imperfect Sensing
• A thermodynamic paradigm for solution demixing inspired by nuclear transport in living cells
• Fate of Duplicated Neural Structures
• Dissipation at limited resolutions: Power law and detection of hidden dissipative scales
• Minimal informational requirements for fitness
• Optimal temporal patterns for dynamical cellular signaling
• Revisiting thermodynamics in computation and information theory
• Chemotaxing E. coli do not count single molecules
• Implementing Non-Equilibrium Networks with Active Circuits of Duplex Catalysts
• Optimizing Energetic cost of Uncertainty in a Driven System With and Without Feedback
• Energy cost of dynamical stabilization: stored versus dissipated energy