Defining Lyfe in the Universe: From Three Privileged Functions to Four Pillars
Abstract
:1. Introduction: The Need for a New Definition of Life
1.1. Privileged Functions at the Origin of Life
1.2. The Event Horizon in Origins-of-Life Research
1.3. Historical vs. Synthetic vs. Universal Origin Narratives
2. The Definition of Lyfe
- Life represents life as we know it; it uses the specific disequilibria and classes of components of earthly life. Life is an autocatalytic network of organometallic chemicals in aqueous solution that records and processes information about its environment in molecular form and achieves dynamical order by dissipating any subset of the following disequilibria: redox gradients, chemiosmotic gradients, visible/thermal photons, etc.
- Lyfe represents any hypothetical phenomenon in the universe that fulfills the fundamental processes of the living state, regardless of the disequilibria or components that it harnesses or uses. Lyfe is any hypothetical phenomenon that maintains a low-entropy state via dissipation and disequilibria conversions, utilizes autocatalytic networks to achieve nonlinear growth and proliferation, employs homeostatic regulatory mechanisms to maintain stability and mitigate external perturbations, and acquires and processes functional information about its environment.
- Dissipation—Lyfe cannot exist at equilibrium. The second law of thermodynamics, in the presence of free energy transduction mechanisms, permits the coupling of exergonic processes to the endergonic, organized configurations of lyfe.Using an array of nanoscale molecular machines, life dissipates external chemical disequilibria and/or converts low-entropy photons into high-entropy waste heat, transducing these disequilibria into other disequilibria (e.g., endergonically building up proton gradients and high ). To perform useful work, life converts , which dissipates the disequilibrium [28,29].
- Autocatalysis—The ability of a system to exhibit exponential growth of representative measures of size or population in ideal conditions. The property of autocatalysis can appear in different forms—including self-catalysis, cross-catalysis, and network autocatalysis—as long as the effect leads to exponential growth of a suitable metric under ideal conditions.A cultured system of microorganisms exhibits autocatalytic population growth due to cellular replication in resource-abundant conditions.
- Homeostasis—The ability of a system to maintain key internal variables within ranges of ideal set points. In a dynamic world of perturbations, coupled with the exponential growth described above, a lyving system must have means to limit the variation of its internal systems when external conditions change.Life performs homeostasis with networks of sensors, receptors, and effectors. The substance under homeostatic regulation (e.g., calcium ions) typically binds with receptors and promotes the release of further substances (e.g., hormones). These indicator compounds then stimulate an appropriate response mechanism to return the substance level to within the desired window.
- Learning—The ability of a system to record information about its external and internal environment, process that information, and carry out actions that feed back positively on its probability of surviving/proliferating.Darwinian evolution is one commonly cited biological learning process (e.g., [30,31,32]) among a much larger set of learning processes that living systems perform. For example, there are widely studied examples of biological learning within the realm of neuroscience, permitted by a range of neuronal and synaptic interactions (e.g., [33,34,35]). In addition, there is a growing list of non-neural learning systems, including gene regulatory networks [36,37,38], protein interaction networks [39,40], and other epigenetic mechanisms (e.g., [41,42]). Many examples fall under the general framework of associative learning, which has been exhibited by non-neural organisms such as slime moulds [43,44]. Darwinism mingles with these other learning processes (and perhaps other hitherto undiscovered forms) to create the incredible diversity and complexity of the biosphere. Hence, “learning” is an umbrella term for this large and incompletely understood set of processes.
2.1. Sublyfe
- Dissipation only: Thermal diffusion, or any thermodynamically irreversible process.
- Homeostasis only: An ideal gas at equilibrium. An isolated system such as this always relaxes back to equilibrium after an internal or external fluctuation.
- Dissipation and autocatalysis: Fire is a frequently discussed example of dissipation and autocatalysis. It exhibits homeostasis of certain variables (e.g., burn temperature naturally stays within certain bounds), but its inability to fully regulate its behavior or learn from experience keeps it relegated to the nonliving world. Another relevant example would by the exponential growth of products in nonlinear chemical reactions (e.g., the formose reaction).
- Dissipation and homeostasis: A damped harmonic oscillator converts kinetic energy to thermal energy and always returns to its equilibrium position.
- Dissipation and learning: An artificial neural network is an example system that learns and is dissipative but does not necessarily exhibit autocatalytic growth or homeostasis (e.g., it does not by itself maintain the temperature of its own hardware). One could argue that their usefulness compels us to produce them at an exponential rate, but that is another discussion.
- Dissipation, autocatalysis, and learning: A living system that wipes itself out by tragedy of the commons. Examples might include invasive species introduced to an island that destroy their food sources so fast that the food sources are damaged beyond recovery. One might also suggest anthropic climate change as another example. Note that these cases depend critically on where one draws the boundary of the system (e.g., to include humans or not). Indeed, this form of sublyfe or sublife is less likely to occur because if the system is capable of learning, then in principle it could learn how to regulate itself homeostatically (unless it cannot learn fast enough).
- Dissipation, homeostasis, and learning: A “smart” house thermostat that monitors occupant behavior over time. This system cannot replicate but consumes free energy, is capable of primitive learning, and can regulate its local temperature.
- All four: Lyfe (which includes life).
2.2. Lyfe and Origins-of-Life Studies
3. Imagining Lyfe
3.1. Examples of Alternative Components in Origins-of-Life Hypotheses
3.2. Lyfe on Titan
3.3. Mechanotrophs
4. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
Abbreviations
LUCA | Last Universal Common Ancestor |
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Bartlett, S.; Wong, M.L. Defining Lyfe in the Universe: From Three Privileged Functions to Four Pillars. Life 2020, 10, 42. https://doi.org/10.3390/life10040042
Bartlett S, Wong ML. Defining Lyfe in the Universe: From Three Privileged Functions to Four Pillars. Life. 2020; 10(4):42. https://doi.org/10.3390/life10040042
Chicago/Turabian StyleBartlett, Stuart, and Michael L. Wong. 2020. "Defining Lyfe in the Universe: From Three Privileged Functions to Four Pillars" Life 10, no. 4: 42. https://doi.org/10.3390/life10040042
APA StyleBartlett, S., & Wong, M. L. (2020). Defining Lyfe in the Universe: From Three Privileged Functions to Four Pillars. Life, 10(4), 42. https://doi.org/10.3390/life10040042