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Asymmetric Directory Subscription Line. Analog Directory Super Line. Alternative Digit Serial Line. 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.
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. These indicator compounds then stimulate an appropriate response mechanism to return the substance level to within the desired window. Darwinian evolution is one commonly cited biological learning process e.
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.
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. 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. While these four pillars of lyfe are derived from observations of life as we know it after all, life must be a subset of lyfe , this new definition is far more expansive. The four pillars constitute necessary and sufficient requirements of the lyving state while remaining divorced from the specific components that make up the system.
This is illustrated by the fact that there are numerous systems that perform the same pillars but are quite distinct in form as will be discussed in Section 2. There may even be a class of systems, still undiscovered and undescribed, that performs all four pillars of lyfe and some fifth pillar as well. Such systems might be deemed super-lyfe. While the discovery of super-lyfe would certainly be paradigm-shifting, we remain agnostic about its existence for now.
We take this moment to emphasize that our definition of lyfe applies at the system level. The pillars that can be ascribed to a certain system depend specifically on the boundaries with which we use to refer to that system. For example, which pillars do viruses perform? A single virus in isolation cannot perform any of the pillars.
Viruses in a system consisting of viruses, bacteria, and nutrients can perform autocatalysis and, through the coercion of their bacterial hosts, dissipation. Viruses in a biosphere that is coevolving with its environment will cause not only autocatalysis and dissipation but learning through evolution as well.
In certain ecosystems, viruses may even impart homeostatic attributes to the system by introducing auxiliary metabolic genes to their hosts and recycling organic matter via lysis [ 45 ]. Like others have suggested [ 46 , 47 ], we contend that the living state may best be assessed at an ecosystem or planetary scale. As an example of a pillar being manifested at the system level, consider learning.
One might suggest that learning rate naturally applies to individual species, but in our opinion it is more effectively interpreted at the system level.
This is because every species evolves in concert with other species and its abiotic environment. Hence, when one species learns, other species in the system that do not become extinct must also learn.
Even though humans are doing a great deal of learning, other species that we share the planet with are learning how to cope with the consequences and changes due to our learning e.
We note also that the importance and relevance of the pillars are separate from the ease with which we can measure their presence. In particular, biosignatures from distant exoplanets will likely not be sufficient to reveal the autocatalytic property, unless those signatures are collected over very long periods. Hence, for this pillar there is a difference between significance this property is fundamental to the definition of lyfe and ease of measurement it may not be easy to assess.
However, sometimes the autocatalytic property reveals itself in dramatic fashion. As we write, the world as we know it is being turned upside down by an entity that is both considered not to be alive and comprises only a small RNA genome and a small set of proteins.
Every chart that has tracked COVID has shown exponential growth autocatalysis in the first phase, demonstrating how tiny biological entities can show extreme nonlinear dynamical changes in a short time.
We define lyfe as any system that performs all four pillars and sublyfe as any system that performs some but not all of those functions see Figure 5. A Venn diagram of the four pillars of lyfe. Sublyfe regions 1—8 is any system that performs some but not all of the pillars, while lyfe region 9 is any system that performs all four.
Autocatalysis and learning require a continuous supply of free energy and are thus contingent on dissipation; however, homeostasis can occur even in equilibrium systems and therefore does not always require dissipation. See text for examples of each region. Below, we list examples of phenomena that correspond to the numbered regions in Figure 5. 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.
Another relevant example would by the exponential growth of products in nonlinear chemical reactions e. 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. 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. 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. This system cannot replicate but consumes free energy, is capable of primitive learning, and can regulate its local temperature.
Dissipation, autocatalysis, and homeostasis: Thermal Gray—Scott reaction—diffusion spots. Certain nonequilibrium chemical patterns have been shown to grow exponentially and also regulate their local temperature [ 52 , 53 , 54 , 55 ]. Regarding homeostasis in equilibrium systems region 2 in Figure 5 , there are some delicate subtleties. Our contention that homeostasis occurs in such isolated systems is simply the fact that they are the archetype of stability by definition. However, the point is arguable from both sides.
One might argue that at the instant a fluctuation occurs, there is a momentary creation of free energy. However, harnessing such a fluctuation would require measurement and information-processing, and, as [ 56 ] showed, to accomplish this in a finite memory system requires erasure, which cannot be done for free and hence there is in fact no free energy created by fluctuations of an equilibrium system.
In general, any perturbation of such a system will disappear in finite time as the system re-relaxes, hence we allow for homeostasis in equilibrium systems in contrast, biological homeostatic processes generally occur through the consumption of free energy.
There are several notable macromolecular complexes that are both dissipative and autocatalytic but not necessarily homeostatic regions 3 and 6 of Figure 5. We already discussed viruses above, which are protein—gene complexes. Amyloids prions are essentially peptide conformational viruses, since they propagate via a pathological spread of their own conformation on existing peptides of different conformation [ 57 , 58 , 59 ].
If we also consider the biochemical examples of self-replicating micelles and droplets [ 64 , 65 ], we see that the subset of entities that are dissipative and autocatalytic potentially deserve a dedicated category of their own. We note that such a category would also include phenomena at higher levels in the hierarchy of life. For instance, Internet memes are clearly autocatalytic and dissipative given the computational energetic costs involved in their proliferation and communication.
Furthermore, the social-media-membership-plus-meme system learns collectively, placing it in region 6 of Figure 5. Furthermore, in analogy to biological viruses, misinformation stories that are only weakly correlated with reality can be amplified by various effects to the point of causing disruptive socio-political impacts.
In this subsection, we have presented a list of increasingly lyfe-like phenomena, which may give the illusion that the origins of lyfe always proceed in a simple, stepwise manner—i. In our view, it is also plausible that relatively simple systems capable of rudimentary information processing can arise de novo and that the ability of these systems to optimize over time their dissipative, autocatalytic, and homeostatic traits will determine their ultimate fate see also [ 66 ].
For instance, the first life on Earth almost certainly did not use DNA for information storage or any recognizable enzymes in its metabolic network. After innumerable tugs of war between chance and necessity, evolution produced the familiar macromolecules that we observe today.
In Section 2. With regard to the origins-of-life narratives discussed in Section 1. Directly connected to life are instances of lyfe that share two of the three mechanisms with life. Two steps removed from life are instances of lyfe that share only one of the three mechanisms with life.
Furthermore, at the opposite vertex is a lyfe form completely unlike earthly life. Within the paradigm of privileged functions at the origins of life, life represents one solution to those functions in component-space, and lyfe encompasses any living system that uses other components to accomplish the same tasks. Life, being the sought-after end-product of origins-of-life hypotheses one such shown by the dotted purple trajectory , is positioned at the apex.
The tier directly below life contains two common components to life. The tier below that contains one common component. The final tier contains no common components. Rotating this shape allows any combination to assume the apex, suggestive of our position that lyfe can be just as valid a target of origins-of-life research as life. In Figure 6 , life is positioned at the apex, because this is the end goal of most origins-of-life hypotheses.
In origins-of-life narratives that involve stepwise emergence, an abiotic system might follow a trajectory that moves from one vertex to another, finally arriving at life.
The more detailed reasons for why a system might traverse these alternative pathways or not are a vast topic of philosophical debate, beyond the scope of the present work. As discussed in Section 1. In the spirit of metaphor, we would like to highlight two analogies that are helpful when considering these issues. The first is the striking differences in composition and structure between scaffolding and finished products.
The second is an analogy between biological evolution and the history of locomotives Figure 7. An analogy between the history of trains and biological evolution, presented in a form resembling Figure 2.
While the materials that trains are built from have changed over time, their purpose and functions have remained constant. Shinkansen image: Daylight Wikimedia Commons. Given that train components can be swapped wholesale for one another by human hands, this analogy may appear inappropriate with regard to the commonly held view of biological evolution as a gradual process that is driven by the natural selection of minute tweaks to pre-existing elements.
It is quite possible that at the earliest stages of life, such transitions were rampant, as primitive living systems battled for supremacy in a relatively flat fitness landscape, trading components with ease via horizontal transfers of information and material.
In his book Seven Clues to the Origin of Life , ref. A rope of hemp fibers at one end could gradually transform into a rope with only sisal fibers in it, by hemp fibers fading out and sisal fibers fading in. In our opinion, the truth is probably closest to a hybrid of these rope and onion concepts. Layers of function accumulating around the rope core would prevent core components from being lost from the rope.
Core systems that interface with many higher subsystems become so functionally entwined with the various modules that any changes to the core systems would be detrimental or catastrophic to the coherent whole. This can be true even if there are superior candidate systems for the core.
For example, many European cities grew organically over long periods and now have a somewhat fractal organization. Compare this to the much more planned grid structures of American cities.
Changing the fundamental structure of European cities is now too costly so they are stuck with their undesigned layouts. It is also quite plausible that the modern components of core biochemical systems performed different functions originally. The biosphere is replete with examples of such exaptation: the shift in function or co-optation of a component for another use. Feathers originally granted warmth and signaling abilities before they became tools of flight; wings were likely used to augment running speed before being used for flight [ 74 ]; the water oxidizing complex that ushered in the age of oxygenic photosynthesis may have originally been used for manganese oxidation [ 75 ].
For further examples of exaptation, see the seminal work by [ 76 ] and citations therein. This narrow approach is necessarily blind to scenarios where life-likeness could begin using alternative components, as might have occurred not only on Earth but elsewhere in the universe. So, when investigating the emergence of life, what are we looking for if not specific biomolecules?
The definition of lyfe offers an answer: we seek a system that exhibits dissipation, autocatalysis, homeostasis, and learning. By basing the criteria for lyfe on generic processes—rather than specific components that perform specific tasks—we open our minds to the exploration of all systems that display these emergent properties, freeing ourselves from the restrictions of precise chemical recipes whose prescriptions contain assumptions that may limit our explorations of the emergence of life-like behavior in the universe.
The origins-of-life community has suggested many hypotheses that involve stepwise emergence through lyfe-like phases. Using our classification, these emergent systems could be classified as lyfe or sublyfe because they utilize radically different components than present-day life to achieve one or more of the four pillars of lyfe. This section describes a few salient examples of origins hypotheses that utilize alternative components at the origin of life.
Some authors have hypothesized that the earliest metabolic systems may have been thioester-driven [ 70 ] also note the concerns raised by [ 78 ] , rather than phosphate-driven, due to the inaccessibility of inorganic phosphate on the early Earth [ 79 ] also note contradictory opinions [ 80 ]. However, ref. Within the biosphere, a phosphate-independent metabolism exists that heavily depends on iron-sulfur and transition metal enzymes—which themselves have been linked to geochemical scenarios for the emergence of biochemistry [ 82 , 83 , 84 ].
Network-based algorithms suggest that various environmental parameters could result in a thioester-based proto-metabolic network similar to the reductive tricarboxylic acid cycle [ 85 ]. Thus, the thioester world, if it ever existed, would have been a primitive but thriving biosphere of lyfeforms. Self-replicating clay minerals have been suggested as the first informational structures of life [ 86 , 87 ]. These crystal genotypes can manifest as phenotypes that affect the environment in which the crystal is growing as well as the catalytic power of the crystal [ 73 ].
Of particular interest is the autocatalytic potential of clay—organic systems. For example, it has been suggested that the origin of life could have involved iron-rich clays that could perform light-induced charge transfer to reduce CO 2 to functional organic molecules [ 69 ]. Clay minerals are also known to promote polynucleotide synthesis [ 88 , 89 ]. Thus, this scientific narrative has clay minerals providing the scaffold for organic biochemistry: a clay—organic form of lyfe.
This metastable mineral is hypothesized to have been a constituent of Hadean submarine alkaline hydrothermal vents. Due to its reduction-oxidation capabilities, green rust is thought to have been an important driver of organosynthesis in these contexts [ 90 ]. Within its flexible, anhydrous interlayers, nitrate can be converted to ammonium [ 91 , 92 ], and it is hypothesized that inorganic carbon can be converted to pyruvate, which can then be aminated to alanine. At the same time, the theory suggests that green rust could act as a primitive inorganic pyrophosphatase—making it one of the first nanoengines of life [ 93 ].
If green rust or a similar mineral played the role of a molecular machine at the emergence of life, then that protometabolic system could be classified as lyfe. In emergence hypotheses that occur in hydrothermal systems, compartmentalization is not achieved through spontaneously assembling lipid membranes but by a maze of inorganic mineral pore spaces.
Only after the invention of lipid biosynthesis and the subsequent invention of cell wall biochemistry did life-like cells emerge and escape their hydrothermal confines [ 95 ]. However, before they became free-living prokaryotes, the complex chemical networks lodged inside their mineral enclosures could still be considered alyve or subalyve before achieving all four pillars of lyfe.
It is a longstanding problem that RNA synthesis and polymerization is a challenge in most abiotic environments e. Amyloid-based replicators offer an alternative to RNA: their monomers are more readily synthesized in prebiotic scenarios; they are stable under early Earth conditions; they are self-assembling, replicative, catalytic, and may be capable of adapting to changes in their environment [ 57 , 58 ].
Although amyloidosis is most famously known for being associated with human diseases [ 99 ], modern life uses functional amyloidal proteins to its benefit, from biofilm formation to dehydration resistance to long-term memory [ 58 ]. Other worlds that feature potentially similar habitats—for instance, hydrothermal systems on Europa or Enceladus—may be inhabited by living creatures that are biochemically similar to life.
However, on worlds that occupy radically different physical and chemical spaces to those of Earth, any exobiology that exists would surely be lyfe, not life. One intriguing possibility is Titan, the only other world in the Solar System known to possess stable bodies of liquid on its surface.
Addressing the final difference in more detail, ref. However, this may not rule out the possibility that lyfe-like entities can construct them. Alternatively, membranes may not be required for lyfe on Titan because the extraordinarily low temperatures already prevent the dissolution of macromolecules, and membrane-like structures would inhibit the diffusion of metabolites in and out of a cold, stationary lyving system [ ].
Should such a membrane-less exobiological entity exist, it would certainly be a provocative example of lyfe. Earthly life utilizes various external free energy sources, from redox couples to solar radiation to gradients of proton density and even electron density e. Macroscopic organisms are known to exploit abiotic sources of mechanical work and use them to their advantage; examples of this include salmon hitching rides on turbulent eddies to swim upstream [ , ], birds catching thermals to higher altitudes, and humans building wind turbines and hydroelectric power plants.
However, there is no cataloged example of an organism that transduces mechanical work directly into its metabolism. We find this rather surprising, since the reverse process is such a fundamental component of all life, i. This rotational motion is most well known for synthesizing ATP from ADP and P i , but it is also used to produce cellular movement in fluid environments.
This occurs through the flagellar motor proteins, close relatives of the ATP synthases [ , ]. Flagellar motors dissipate the free energy of ATP hydrolysis in eukaryotes, or ion motive forces in prokaryotes, for the production of rotational motion. Rotation of the central rotor causes the flagellar filament to spin, and the structure of the filament allows the rotational motion to produce translational movement of the organism in water this motion has been compared to the mechanism by which corks are thrust from a bottle by the rotation of a corkscrew [ ].
Why could this process not be reversed to power a mechanotrophic organism? We would greatly appreciate your contribution if you would like to submit your own!
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