Excerpt

Introduction

The rise of cellular systems pervades the evolution of complex life beyond simple catalytic networks of molecules (Szathmáry and Smith 1995; Schuster 1999; Lane 2015). The physical conditions under which such systems appear are largely unknown. Especially intriguing is that the cycles of growth and self-replication, along with the increase of complexity, seem to be in contradiction to the laws of thermodynamics as we know them. Because real systems display an enormous degree of complexity, researchers have proposed the study of much simpler, even artificial, chemical systems that mimic the properties of living beings and can be much more easily understood. These systems are known as protocellular systems. In addition, protocellular entities are the starting point of a biological landscape where a spatially well-defined structure provides a scaffold for efficient, confined chemical reactions to occur. Spatial compartmentalization creates a natural separation between an “inside” world and the external environment. The protocellular agent thus involves the emergence of a dynamical set of boundary conditions allowing the cooperative replication of a whole macromolecular assembly. Along with a reliable compartment (Deamer 2005), a metabolic component needs to be included. Such a metabolic part plays the role of building new materials from available energy and promoting compartment instabilities leading to self-replication. The compartment is usually assumed to be formed in a water-dominated environment and built from the spontaneous assembly of surfactant molecules (Mouritsen 2005). These molecules have a polar nature, with a hydrophilic and a hydrophobic terminal that are attracted or repelled by water molecules, respectively. In contrast with equilibrium aggregates defining closed vesicles as a natural energy minimization process, protocell replication requires an out-of-equilibrium context to allow for a process of growth followed by destabilization and, eventually, splitting into two new daughter cells (Fellermann et al. 2015; Zwicker et al. 2017).

Despite the modeling efforts and experimental trials, a reliable self-replication cycle as described earlier is still missing (Solé 2016; Serra and Villani 2017). Most examples require necessary extrinsic factors to trigger instability. An obvious obstacle here is the potentially vast parameter space involved (including, for example, reaction rates, temperature, and other physical variables or molecular properties, such as surfactant geometry) and our ignorance about the domains in that space where cell division is physically allowed. One potential path to reach such parameter domains has been recently obtained by means of directed evolution of lipid vesicles (Points et al. 2018) in a new form of what Lee Cronin dubbed inorganic evolution (Gutierrez et al. 2014).

A major obstacle in tackling the creation of these self-replicating agents is the absence of a thermodynamic theory of their cell cycles (Fellermann et al. 2015). Important advances have been made over the years regarding the thermodynamics of living processes (Morowitz 1968, 1993; Deamer 1997), and recently, interesting, fresh approaches relating thermodynamics, information, and the essential biochemical reactions have been proposed, opening the door to a deeper understanding of the essential thermodynamics of biological processes (Smith 2008a, 2008b, 2008c; England 2013). In this chapter, we characterize a driven, out-of-equilibrium chemical system able to satisfy two crucial conditions for living systems: to capture material resources and turn them into building blocks (grow and divide) by the use of externally provided free energy (a metabolic machinery) and to keep its components together and distinguish itself from the environment (Kauffman 2003; Ganti 2003; Solé, Rasmussen, and M. A. Bedau 2007; Rasmussen et al. 2008; Ruiz-Mirazo, Briones, and Escosura 2014). We show that the successive cycles of growth and division have the formal properties of a thermodynamic cycle, where all the parameters can be computed from its defining energy landscape.

Bibliography

Bachmann, P. A., P. L. Luisi, and J. Lang. 1992. “Autocatalytic Self-Replicating Micelles as Models for Prebiotic Structures.” Nature 357:57–59.

Crooks, G. E. 1999. “Entropy Production Fluctation Theorem and the Nonequilibrium Work Relation for Free Energy Differences.” Physical Reviews E 60 (3): 2721–2726.

Deamer, D. 1997. “The First Living Systems: A Bioenergetic Perspective.” Microbiology and Molecular Biology Reviews 61:239.

————. 2005. “A Giant Step towards Artificial Life?” Trends in Biotechnology 23:336–338.

England, J. 2013. “Statistical Physics of Self-Replication.” Journal of Chemical Physics 139:121923.

Evans, D. Fennell, and H. Wennerstrøm. 1994. The Colloidal Domain: Where Physics, Chemistry, Biology, and Technology Meet. Berlin: VCH.

Fellermann, H., B. Corominas-Murtra, P. L. Hansen, J. H. Ipsen, R. V. Solé, and S. Rasmussen. 2015. “Non-Equilibrium Thermodynamics of Self-Replication Protocells.” arXiv 1503.04683.

Ganti, T. 2003. The Principles of Life. Oxford: Oxford University Press.

Gutierrez, J. M. P., T. Hinkley, J. W. Taylor, K. Yanev, and L. Cronin. 2014. “Evolution of Oil Droplets in a Chemorobotic Platform.” Nature Communications 5:5571.

Kauffman, S. 2003. “Molecular Autonomous Agents.” Philosophical Transactions of the Royal Society of London, Series A 361:1089–1099.

Lane, N. 2015. The Vital Question: Energy, Evolution, and the Origins of Complex Life. New York: W. W. Norton.

Morowitz, H. J. 1968. Energy Flow in Biology. New York: Academic Press.

————. 1993. Beginnings of Cellular Life: Metabolism Recapitulates Biogenesis. New Haven, CT: Yale University Press.

Mouritsen, O. 2005. Life—as a Matter of Fat: The Emerging Science of Lipidomics. Berlin: Springer.

Points, L. J., J. W. Taylor, J. Grizou, K. Donkers, and L. Cronin. 2018. “Artificial Intelligence Exploration of Unstable Protocells Leads to Predictable Properties and Discovery of Collective Behavior.” Proceedings of the National Academy of Sciences of the United States of America 115:885–890.

Rasmussen, S., M. A. Bedau, L. Chen, D. Deamer, D. Krakauer, N. Packard, and P. Stadler, eds. 2008. Proto-cells: Bridging Nonliving and Living Matter. Cambridge, MA: MIT Press.

Ruiz-Mirazo, K., C. Briones, and A. de la Escosura. 2014. “Prebiotic Systems Chemistry: New Perspectives for the Origins of Life.” Chemical Reviews 114 (1): 285–366.

Schuster, P. 1999. “How Does Complexity Arise in Evolution?” Complexity 2:22–30.

Serra, R., and M. Villani. 2017. Modelling Protocells: The Emergent Synchronization of Reproduction and Molecular Replication. Berlin: Springer.

Smith, E. 2008a. “Thermodynamics of Natural Selection I: Energy Flow and the Limits on Organization.” Journal of Theoretical Biology 252:185–197.

————. 2008b. “Thermodynamics of Natural Selection II: Chemical Carnot Cycles.” Journal of Theoretical Biology 252:198–212.

————. 2008c. “Thermodynamics of Natural Selection III: Landauer’s Principle in Computation and Chemistry.” Journal of Theoretical Biology 252:213–220.

Solé, R. V. 2016. “Synthetic Transitions: Towards a New Synthesis.” Philosophical Transactions of the Royal Society of London, Series B 371 (1701): 20150438.

Solé, R. V., S. Rasmussen, and eds. M. A. Bedau. 2007. “Towards the Artificial Cell.” Philosophical Transactions of the Royal Society of London, Series B 362.

Szathmáry, E., and J. M. Smith. 1995. The Major Transitions in Evolution. London: W. H. Freeman Spektrum.

Zwicker, D., R. Seyboldt, C. A. Weber, A. A. Hyman, and F. Jülicher. 2017. “Growth and Division of Active Droplets Provides a Model for Protocells.” Nature Physics 13:408–413.

BACK TO The Energetics of Computing in Life & Machines