Excerpt

Introduction

A current vision in the development of antiaging measures is to consider aging as a disease that can be cured like a disease (De Magalhães 2014; Werfel, Ingber, and Bar-Yam 2015). Typical manifestations of biological aging are accumulating deleterious mutations in older age. Here we associate with aging an increasing accumulation of “errors” in the genetic and cellular “code” that steers fundamental biological processes. Errors may be wrong signaling pathways, insufficient accuracy in reproduction events, imprecise copying processes, or imprecise cellular sensing of concentrations outside the cells, to name a few. If errors in the code exceed a certain threshold, their accumulation will compromise the function of the biological unit.

Our approach is to explore the conjecture that aging of living organisms might be intrinsically unavoidable owing to fundamental principles from physics so that aging can be delayed but not completely reversed or healed like a disease. A possible rationale could proceed along the following line of argument:

• Living organisms are information processing.

• Owing to fundamental trade-offs between cost for the use of resources and precision in its performance, this information processing is inherently error prone and defective.

• As a result, errors will accumulate, either upon the interaction of many defective subsystems or in the reproduction of defective structures.

• Admittedly, different sources of stochastic fluctuations need not automatically add up to a noisy output of reactions if the sources are anticorrelated. In addition, nature has invented a repertoire of repair mechanisms to counteract a rapid accumulation of errors. However, repair mechanisms are information processing, and thus defective, themselves.

• Because “information” in biological systems is physically implemented, its processing costs energy (or other kinds of resources, such as space or time); the higher the required precision, the higher the costs.

• Although the size of external reservoirs is practically infinite for any organism, only a finite amount is accessible within a finite period of time.

• Given these circumstances, one may wonder for how long the accessible energy suffices to pay the price for the required precision and maintaining the errors at a finite but tolerably low fraction such that the functioning of the whole organism is guaranteed.

Bibliography

Arnold, C., P. F. Stadler, and S. J. Prohaska. 2013. “Chromatin Computation: Epigenetic Inheritance as a Pattern Reconstruction Problem.” Journal of Theoretical Biology 336:61–74.

Barato, A. C., and U. Seifert. 2015. “Thermodynamic Uncertainty Relation for Biomolecular Processes.” Physical Review Letters 114 (15): 158101.

————. 2016. “Cost and Precision of Brownian Clocks.” Physical Review X 6 (4): 041053.

————. 2017. “Coherence of Biochemical Oscillations Is Bounded by Driving Force and Network Topology.” Physical Review E 95 (6): 062409.

Bennett, C. H. 2003. “Notes on Landauer’s Principle, Reversible Computation, and Maxwell's Demon.” Studies In History and Philosophy of Science Part B: Studies In History and Philosophy of Modern Physics 34 (3): 501–510.

Bruggeman, F. J., N. Blüthgen, and H. V. Westerhoff. 2009. “Noise Management by Molecular Networks.” PLoS Computational Biology 5 (9): e1000506.

Cepeda, S. A., G. Rieckh, and G. Tkačik. 2015. “Stochastic Proofreading Mechanism Alleviates Crosstalk in Transcriptional Regulation.” Physical Review Letters 115 (24): 248101.

De Magalhães, J. P. 2014. “The Scientific Quest for Lasting Youth: Prospects for Curing Aging.” Rejuvenation Research 17 (5): 458–467.

Farajnia, S., T. Deboer, J. H. T. Rohling, J. H. Meijer, and S. Michel. 2014. “Aging of the Suprachiasmatic Clock.” The Neuroscientist (Los Angeles, CA) 20 (1): 44–55.

Gingrich, T. R., J. M. Horowitz, N. Perunov, and J. L. England. 2016. “Dissipation Bounds All Steady-State Current Fluctuations.” Physical Review Letters 116 (12): 120601.

Hopfield, J. J. 1974. “Kinetic Proofreading: A New Mechanism for Reducing Errors in Biosynthetic Processes Requiring High Specificity.” Proceedings of the National Academy of Sciences of the United States of America 71 (10): 4135–4139.

Kubo, R., M. Toda, and N. Hashitsume. 2012. Statistical Physics II: Nonequilibrium Statistical Mechanics. Vol. 31. New York: Springer Science & Business Media.

Landauer, R. 1996. “The Physical Nature of Information.” Physics Letters A 217 (4): 188–193.

Ouldridge, T. E., C. C. Govern, and P. R. ten Wolde. 2017. “Thermodynamics of Computational Copying in Biochemical Systems.” Physical Review X 7 (2): 021004.

Ouldridge, T. E., and P. R. ten Wolde. 2017. “Fundamental Costs in the Production and Destruction of Persistent Polymer Copies.” Physical Review Letters 118 (15): 158103.

Pietzonka, P., A. C. Barato, and U. Seifert. 2016. “Universal Bound on the Efficiency of Molecular Motors.” Journal of Statistical Mechanics: Theory and Experiment 2016 (12): 124004.

Pietzonka, P., F. Ritort, and U. Seifert. 2017. “Finite-time generalization of the thermodynamic uncertainty relation.” Physical Review E 96 (1): 012101.

Prohaska, S. J., P. F. Stadler, and D. C. Krakauer. 2010. “Innovation in Gene Regulation: The Case of Chromatin Computation.” Journal of Theoretical Biology 265 (1): 27–44.

Seifert, U. 2017. “Stochastic Thermodynamics: From Principles to the Cost of Precision.” Physica A: Statistical Mechanics and Its Applications.

Tănase-Nicola, S., P. B. Warren, and P. R. ten Wolde. 2006. “Signal Detection, Modularity, and the Correlation between Extrinsic and Intrinsic Noise in Biochemical Networks.” Physical Review Letters 97 (6): 068102.

ten Wolde, P. R., N. B. Becker, T. E. Ouldridge, and A. Mugler. 2016. “Fundamental Limits to Cellular Sensing.” Journal of Statistical Physics 162 (5): 1395–1424.

Tkačik, G., and W. Bialek. 2016. “Information Processing in Living Systems.” Annual Review of Condensed Matter Physics 7:89–117.

Voit, M., and H. Meyer-Ortmanns. 2018. “On the Fate of Dynamical Systems under a Trade-off between Cost and Precision.” arXiv:1810.04084v1.

Voit, M., and H. Meyer-Ortmanns. 2019. “How Aging May Be an Unavoidable Fate of Dynamical Systems.” New Journal of Physics 21 (4): 043045.

Werfel, J., D. E. Ingber, and Y. Bar-Yam. 2015. “Programmed Death Is Favored by Natural Selection in Spatial Systems.” Physical Review Letters 114 (23): 238103.

BACK TO The Energetics of Computing in Life & Machines