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Primordial evolvability: Impasses and challenges
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... The principles of evolution and selection have been extensively studied for the case in which template molecules are the units of selection following Eigen's formulation of the quasi-species model [11]. In contrast, there is no well-established theory for the evolution of autocatalytic networks [65]. Below, we extend our discussion of autocatalytic reaction systems considered so far and review what conditions on these systems allow for variation, heredity, and differential fitness. ...
... The evolvability of the autocatalytic network has been debated between critics [65,67] and advocates [2,87]. It was pointed out by Vasas and colleagues [65,67] that autocatalytic networks, specifically based on the GARD model, were not evolvable in the sense that the network compositions were not heritable. ...
... The evolvability of the autocatalytic network has been debated between critics [65,67] and advocates [2,87]. It was pointed out by Vasas and colleagues [65,67] that autocatalytic networks, specifically based on the GARD model, were not evolvable in the sense that the network compositions were not heritable. However, later work together with Kauffman, which considered another model, did indeed show that non-evolvability is not necessarily true for autocatalytic networks in general [14]-particularly, the conditions for the evolvability of a specific autocatalytic network were identified. ...
Understanding the emergence of life from (primitive) abiotic components has arguably been one of the deepest and yet one of the most elusive scientific questions. Notwithstanding the lack of a clear definition for a living system, it is widely argued that heredity (involving self-reproduction) along with compartmentalization and metabolism are key features that contrast living systems from their non-living counterparts. A minimal living system may be viewed as “a self-sustaining chemical system capable of Darwinian evolution”. It has been proposed that autocatalytic sets of chemical reactions (ACSs) could serve as a mechanism to establish chemical compositional identity, heritable self-reproduction, and evolution in a minimal chemical system. Following years of theoretical work, autocatalytic chemical systems have been constructed experimentally using a wide variety of substrates, and most studies, thus far, have focused on the demonstration of chemical self-reproduction under specific conditions. While several recent experimental studies have raised the possibility of carrying out some aspects of experimental evolution using autocatalytic reaction networks, there remain many open challenges. In this review, we start by evaluating theoretical studies of ACSs specifically with a view to establish the conditions required for such chemical systems to exhibit self-reproduction and Darwinian evolution. Then, we follow with an extensive overview of experimental ACS systems and use the theoretically established conditions to critically evaluate these empirical systems for their potential to exhibit Darwinian evolution. We identify various technical and conceptual challenges limiting experimental progress and, finally, conclude with some remarks about open questions.
... The ways in which energy and matter are put to work within ecosystems (the fluxes) are at least as important as measuring overall inputs and outputs (the flows) (Waring 1989). Beginning near the end of the twentieth century, Robert Ulanowicz (1980Ulanowicz ( , 1986Ulanowicz ( , 1997 showed that stable ecosystems can emerge and maintain themselves without attaining a static equilibrium. This set the stage for ecosystems to be open-ended with respect to how many species could coexist-as long as the metabolic loop remains closed, the ecosystem functions. ...
... where A ¼ ascendancy (power, potential, information, organization); C ¼ capacity (H max ); (E + H + S) ¼ what actually happens (H obs ); E ¼ export (moving materials from one place to another inside the system, part of d i S); H ¼ redundancy (of E, also part of d i S); and S ¼ entropy production of the system as a whole (dS). Like organisms, ecosystems are maintained through time by the exploitation of "entropy gradients" or "resource gradients" in the surroundings (Collier 1986(Collier , 1988(Collier , 1990(Collier , 2000Wicken 1987;Ulanowicz 1980Ulanowicz , 1986Ulanowicz , 1988Ulanowicz , 1997Matsuno 1989Matsuno , 1995Matsuno , 1996Matsuno , 1998Matsuno , 2000Maurer and Brooks 1991;Hirata 1993;Depew and Weber 1995) degrading those necessary resources as a result (Gladyshev 1996;Ulanowicz 1997;Brooks and McLennan 2000). In doing so, ecosystems are persistent, stable, and resilient. ...
... where A ¼ ascendancy (power, potential, information, organization); C ¼ capacity (H max ); (E + H + S) ¼ what actually happens (H obs ); E ¼ export (moving materials from one place to another inside the system, part of d i S); H ¼ redundancy (of E, also part of d i S); and S ¼ entropy production of the system as a whole (dS). Like organisms, ecosystems are maintained through time by the exploitation of "entropy gradients" or "resource gradients" in the surroundings (Collier 1986(Collier , 1988(Collier , 1990(Collier , 2000Wicken 1987;Ulanowicz 1980Ulanowicz , 1986Ulanowicz , 1988Ulanowicz , 1997Matsuno 1989Matsuno , 1995Matsuno , 1996Matsuno , 1998Matsuno , 2000Maurer and Brooks 1991;Hirata 1993;Depew and Weber 1995) degrading those necessary resources as a result (Gladyshev 1996;Ulanowicz 1997;Brooks and McLennan 2000). In doing so, ecosystems are persistent, stable, and resilient. ...
Humanity is facing an existential crisis from global climate change. Evolutionary biology has a critical role to play in how we respond. The problem fundamentally involves two evolvable variables: Ecosystems, which we depend on for survival; and Us, who have the capacity to alter those ecosystems in a way that threatens our survival. Ecosystems are complex higher-order metabolic systems, closed-loop networks of interacting inheritance systems each with their own capacities for exploiting and exploring their surroundings. Collectively, this gives rise to an Evolutionary Commons, an emergent property of ecosystems that acts as a storehouse of potential that can be unleashed when the conditions change. Evolutionary potential is what makes ecosystems robust, relatively immune to the fate of any given inheritance system, without losing the ability to break apart and reform when disturbed in proportion to the capacities for ecological fitting of their constituent members. Putting evolution to work for humanity is about recognizing that the fundamental resource in the biosphere for coping with change is the potential stored in the evolutionary commons. For our own well-being, our economic policies and strategies should reflect this. To persist indefinitely, we must preserve the biosphere, and to do this we must preserve as many elements of the evolutionary process as possible. Darwinism Then and Now is fundamentally a story about coping with change by changing. Evolution is the only way the biosphere has coped with global climate change before, and the only way it will do it again. To sustain ourselves, we must exploit the biosphere without destroying the evolutionary potential to explore. We propose the Four Laws of Biotics to guide our efforts and discuss how they inform efforts in conservation biology, coping with emerging diseases, the circular economy, and the economics of well-being.
... Another interesting difference in the use of evolutionary terminology in the origins field is that between the use and justification of evolutionary terminology in experimental work and computational work. Computational approaches to studying the origin and early development of life are often focused on the general conditions for self-replication and the requirements for self-replication to be evolutionary [137][138][139][140][141][142][143][144]. Several papers by Vasas and coauthors represent an especially clear example of explicit justification of the use of evolutionary terminology [136][137][138][139]. Their work presents one of the few examples where it is explicitly stated that care should be taken in applying evolutionary terms beyond evolutionary biology [140], something that they have put to effect in arguing that autocatalytic networks can evolve under the right conditions [142]. ...
... Several papers by Vasas and coauthors represent an especially clear example of explicit justification of the use of evolutionary terminology [136][137][138][139]. Their work presents one of the few examples where it is explicitly stated that care should be taken in applying evolutionary terms beyond evolutionary biology [140], something that they have put to effect in arguing that autocatalytic networks can evolve under the right conditions [142]. Most interestingly, however, is their discussion of the requirements for evolution in [141], where they specify that for a chemical system to evolve requires not just selection, but also open-ended evolution, which is itself possible on the condition of "a very rich combinational generative mechanism. . . [with] unlimited heredity; namely, that the number of possible heritable types should more than astronomically exceed the number of individuals in the population. . . ...
The role of evolutionary theory at the origin of life is an extensively debated topic. The origin and early development of life is usually separated into a prebiotic phase and a protocellular phase, ultimately leading to the Last Universal Common Ancestor. Most likely, the Last Universal Common Ancestor was subject to Darwinian evolution, but the question remains to what extent Darwinian evolution applies to the prebiotic and protocellular phases. In this review, we reflect on the current status of evolutionary theory in origins of life research by bringing together philosophy of science, evolutionary biology, and empirical research in the origins field. We explore the various ways in which evolutionary theory has been extended beyond biology; we look at how these extensions apply to the prebiotic development of (proto)metabolism; and we investigate how the terminology from evolutionary theory is currently being employed in state-of-the-art origins of life research. In doing so, we identify some of the current obstacles to an evolutionary account of the origins of life, as well as open up new avenues of research.
... Fundamental inherited space-time is the realm of all possible capacities. Realized inherited space-time is the realm of achieved capacities; the difference between them is the realm of evolutionary potential, or evolvability (Sniegowski and Murphy 2006;Daniels et al. 2008;Vasas et al. 2015;Murray 2018, 2019;Hansen et al. 2019). This is the space in which evolutionary creativity occurs, and from which emerge modularities, hierarchical structure, and developmental stability domains (Szathmary 2015). ...
... The point of the game of life is to stay alive; it is not a matter of "they who die with the most toys win," but of "they who live longest win." This is the window of vitality (Ulanowicz 1997) for evolvable life on this planet. ...
In the process of “buying” time, life not only disturbs material space but creates an abstract space specifying the capacity to engage functionally with the surroundings. This capacity space emerges from the inheritance system, which provides the material information and therefore causal capacity for organisms to impose themselves on their surroundings for survival and reproduction. The realm of all possible inheritances represents potential capacity; the realm of actual inheritances is realized capacity. In the evolving expanding space, realized capacity grows but potential capacity grows even more, ensuring an ever-present realm of possibilities—an “adjacent possible”—for the inheritance system to explore given opportunities presented by the nature of the conditions. Opportunity space emerges from the conditions, but capacity space (nature of the organism) limits how these opportunities may be used. Fitness space is the intersection between capacity and opportunity, the subset of realized opportunity space that supports survival and reproduction. The portion of fundamental fitness space accessed by organisms at any given time and place is realized fitness space; the difference between these is proportional to how “sloppy” fitness space is, i.e., how much capacity there is to do something new when conditions change. Within sloppy fitness space, the historically conservative and largely autonomous nature of inheritance produces reproductive over-run, creating natural selection in proportion to the degree of conflict between organisms and the environment (i.e., Darwin’s Necessary Misfit). The primary mechanism for life to resolve this conflict is ecological fitting, an umbrella term for a fundamental phenomenon that allows living systems to cope with the conditions by exploring novel portions of fitness space using preexisting information they inherited from their ancestors.
... Herbal extracts or secondary metabolites isolated from them have been found to exhibit immunostimulatory or immunosuppressive effects in the tumor microenvironment [9]. R. obtusifolius, also known as broad-leaved dock, is a wild plant widely growing in Armenia and worldwide. ...
The increase in the incidence of cancer in Armenia and around the world is a serious problem, and the chemical interventions used in cancer therapy, which partially have a therapeutic effect, are often accompanied by the destruction of normal body cells. Therefore, it is necessary to search for new alternative treatments that will be highly effective and accompanied by a small number of side effects. From this point of view, several medicinal plants used in traditional medicine can be considered new, effective means of treating cancer, since they have an immunostimulating effect on individual parts of the human immune system. Considering all this, the work aimed to study the quantitative changes in the production of interleukin-2 in the blood and tumor of rats under the influence of plant extracts in an experimental model of DMBA (7,12-dimethylbenz[a]anthracene)-induced breast cancer, as well as cell cultures of breast cancer and lungs. We showed that Hypericum alpestre and Rumex obtusifolius extracts have a pronounced anticancer effect by increasing interleukin-2 (IL-2) levels in the blood and tumors of rats. They also brought quantitative changes in phosphoinositol-3-kinase (PI3K), which plays a key role in cancer development. This could be the basis for developing new anticancer or cancer-preventing drugs derived from more potent H. alpestre and R. obtusifolius herbs.
... However, the corresponding description of evolutionary mechanisms provided no explanation for the pathways by which nucleic acid replication as well as the expression of genetic information could have been established in the emergence of life process. A living entity capable of evolving according to these laws must be equipped with a genetic storage system that allows it to overcome the very limited evolutionary possibilities of autocatalytic sets [65,66]. This condition means that random variation (mutation) could emerge and be transmitted to offspring while undergoing a selection process. ...
This work addresses the kinetic requirements for compensating the entropic cost of self-organization and natural selection, thereby revealing a fundamental principle in biology. Metabolic and evolutionary features of life cannot therefore be separated from an origin of life perspective. Growth, self-organization, evolution and dissipation processes need to be metabolically coupled and fueled by low-entropy energy harvested from the environment. The evolutionary process requires a reproduction cycle involving out-of-equilibrium intermediates and kinetic barriers that prevent the reproductive cycle from proceeding in reverse. Model analysis leads to the unexpectedly simple relationship that the system should be fed energy with a potential exceeding a value related to the ratio of the generation time to the transition state lifetime, thereby enabling a process mimicking natural selection to take place. Reproducing life’s main features, in particular its Darwinian behavior, therefore requires satisfying constraints that relate to time and energy. Irreversible reaction cycles made only of unstable entities reproduce some of these essential features, thereby offering a physical/chemical basis for the possible emergence of autonomy. Such Emerging Autonomous Systems (EASs) are found to be capable of maintaining and reproducing their kind through the transmission of a stable kinetic state, thereby offering a physical/chemical basis for what could be deemed an epigenetic process.
... The transition of protocells from ecosystems of smallmolecule ACs to ecosystems that also include cooperating, template-replicating polymers does not require a genome or the coordination of cellular and genomic replication. Even without genomes, offspring protocells could resemble their parents due to analogue or compositional inheritance [72,73], where ACs in parent ACEs have enough members that, by random segregation, all offspring ACEs have a full complement of ACs. The origin of the genome can be viewed as a transition to digital inheritance [74], where information comes to be locked in the covalent bonds of a single chromosome [75]. ...
Prior research on evolutionary mechanisms during the origin of life has mainly assumed the existence of populations of discrete entities with information encoded in genetic polymers. Recent theoretical advances in autocatalytic chemical ecology establish a broader evolutionary framework that allows for adaptive complexification prior to the emergence of bounded individuals or genetic encoding. This framework establishes the formal equivalence of cells, ecosystems and certain localized chemical reaction systems as autocatalytic chemical ecosystems (ACEs): food-driven (open) systems that can grow due to the action of autocatalytic cycles (ACs). When ACEs are organized in meta-ecosystems, whether they be populations of cells or sets of chemically similar environmental patches, evolution, defined as change in AC frequency over time, can occur. In cases where ACs are enriched because they enhance ACE persistence or dispersal ability, evolution is adaptive and can build complexity. In particular, adaptive evolution can explain the emergence of self-bounded units (e.g. protocells) and genetic inheritance mechanisms. Recognizing the continuity between ecological and evolutionary change through the lens of autocatalytic chemical ecology suggests that the origin of life should be seen as a general and predictable outcome of driven chemical ecosystems rather than a phenomenon requiring specific, rare conditions.
... The model is an innovative and resourceful approach but is not without controversy largely because it depends on mathematical properties (based on a first order differential equation) [26][27][28] rather than on established chemical and biophysical properties of amphiphiles. Indeed, the language used to describe the model raises a number of ambiguities which are characteristic of the assumptions adopted in such an approach. ...
The unique biophysical and biochemical properties of lipids render them crucial in most models of the origin of life (OoL). Many studies have attempted to delineate the prebiotic pathways by which lipids were formed, how micelles and vesicles were generated, and how these micelles and vesicles became selectively permeable towards the chemical precursors required to initiate and support biochemistry and inheritance. Our analysis of a number of such studies highlights the extremely narrow and limited range of conditions by which an experiment is considered to have successfully modeled a role for lipids in an OoL experiment. This is in line with a recent proposal that bias is introduced into OoL studies by the extent and the kind of human intervention. It is self-evident that OoL studies can only be performed by human intervention, and we now discuss the possibility that some assumptions and simplifications inherent in such experimental approaches do not permit determination of mechanistic insight into the roles of lipids in the OoL. With these limitations in mind, we suggest that more nuanced experimental approaches than those currently pursued may be required to elucidate the generation and function of lipids, micelles and vesicles in the OoL.
... After 30 years of expanding research under the evolvability banner, it is time to take stock of what we have learned and to assess the influence and novelty of the concept itself. There is no shortage of reviews, perspectives, and assessments of evolvability (e.g., Alberch 1991;Wagner and Altenberg 1996;Love 2003;Nehaniv 2003;Hansen and Houle 2004;Schlichting and Murren 2004;Hansen 2006Hansen , 2016Sniegowski and Murphy 2006;Hendrikse et al. 2007;Sterelny 2007Sterelny , 2011Pigliucci 2008;Brookfield 2009;Wagner 2010;Pavličev and Wagner 2012;Brown 2014;Kopp and Matuszewki 2014;Brigandt 2015;Vasas et al. 2015;Minelli 2017;Payne and Wagner 2019;Hansen and Pélabon 2021;Porto 2021;Watson 2021;Love et al. 2022;Nuño de la Rosa and Villegas 2022;Riederer et al. 2022), and the concept, if not always the term, has been instrumental in some influential books with structural perspectives on evolution (Kauffman 1993;Dennett 1995;Maynard Smith and Szathmáry 1995;Dawkins 1996;Raff 1996;Gerhart and Kirschner 1997;Gould 2002;A. Wagner 2005;G. ...
Essays on evolvability from the perspectives of quantitative and population genetics, evolutionary developmental biology, systems biology, macroevolution, and the philosophy of science.
Evolvability—the capability of organisms to evolve—wasn't recognized as a fundamental concept in evolutionary theory until 1990. Though there is still some debate as to whether it represents a truly new concept, the essays in this volume emphasize its value in enabling new research programs and facilitating communication among the major disciplines in evolutionary biology. The contributors, many of whom were instrumental in the development of the concept of evolvability, synthesize what we have learned about it over the past thirty years. They focus on the historical and philosophical contexts that influenced the emergence of the concept and suggest ways to develop a common language and theory to drive further evolvability research.
The essays, drawn from a workshop on evolvability hosted in 2019–2020 by the Center of Advanced Study at the Norwegian Academy of Science and Letters, in Oslo, provide scientific and historical background on evolvability. The contributors represent different disciplines of evolutionary biology, including quantitative and population genetics, evolutionary developmental biology, systems biology, and macroevolution, as well as the philosophy of science. This plurality of approaches allows researchers in disciplines as diverse as developmental biology, molecular biology, and systems biology to communicate with those working in mainstream evolutionary biology. The contributors also discuss key questions at the forefront of research on evolvability.
Contributors:J. David Aponte, W. Scott Armbruster, Geir H. Bolstad, Salomé Bourg, Ingo Brigandt, Anne Calof, James M. Cheverud, Josselin Clo, Frietson Galis, Mark Grabowski, Rebecca Green, Benedikt Hallgrímsson, Thomas F. Hansen, Agnes Holstad, David Houle, David Jablonski, Arthur Lander, Arnaud LeRouzic, Alan C. Love, Ralph Marcucio, Michael B. Morrissey, Laura Nuño de la Rosa, Øystein H. Opedal, Mihaela Pavličev, Christophe Pélabon, Jane M. Reid, Heather Richbourg, Jacqueline L. Sztepanacz, Masahito Tsuboi, Cristina Villegas, Marta Vidal-García, Kjetil L. Voje, Andreas Wagner, Günter P. Wagner, Nathan M. Young
... Computer simulations showed that such self-reproducing vesicles segregate into multiple populations, each characterized by a distinct metabolism, proving that heritable reproduction can be supported by a network of molecular interactions (i.e., compositional heredity) and does not require nucleic acids (Segré et al., 2001). However, further analysis of evolutionary dynamics indicated that lineages of vesicles described by (Vasas et al., 2015). The main factor that limits evolvability in the GARD model is the lack of covalent bond catalysis capable of generating novel kinds of molecules that have not existed in the environment before. ...
This book invites readers to embark on a journey into the world of agency encompassing humans, other organisms, cells, intracellular molecular agents, colonies, populations, ecological systems, and artificial autonomous systems. We combine mechanistic and non-mechanistic approaches in the analysis of the function and evolution of organisms, their subagents, and multi-organism systems, and in this way offer a theoretical platform for integrating biosemiotics with both natural science and the humanities/social sciences. Agents are autonomous systems that incorporate knowledge on how to make sense of their environment and use it to achieve their goals. The functions of all agents are supported by mechanisms at the lowest level; however, the explanatory power of mechanistic analysis is not sufficient for complex agents. Non-mechanistic methods rely on the goal-directedness of agents whose dynamics follow self-stabilized dynamic attractors. The properties of attractors depend on stable or slowly changing factors, and such dependencies can be interpreted as sign relations if they are adaptive in nature. Agents can replace or redirect mechanisms on demand in order to preserve their functions; for performing higher-level semiotic functions, mechanisms are thus only means. We assume that mechanism and semiosis are not mutually exclusive, and that simple agents can interpret signs mechanistically. This assumption allows us to extend semiotic analysis to all agents, including ribosomes in cells, computers, and robots. This book challenges established traditions in natural science and the humanities/social sciences: semiotics no longer appears as restricted to humans and rational thinking, and biology is no longer limited to rely exclusively on mechanistic reasoning.
... Computer simulations showed that such self-reproducing vesicles segregate into multiple populations, each characterized by a distinct metabolism, proving that heritable reproduction can be supported by a network of molecular interactions (i.e., compositional heredity) and does not require nucleic acids (Segré et al. 2001). However, further analysis of evolutionary dynamics indicated that lineages of vesicles described by the GARD model do not have sufficient evolvability and thus cannot support open-ended evolution (Vasas et al. 2015). ...
The origin of life involves a transition from a merely physical world into the world of semiotic agency
. Attempts to explain the origin of life by synthesis of such organic molecules as peptides or nucleic acids is baseless, because amino acids and nucleotides are products of the evolving life
rather than parts from which the first living system was assembled. We follow the footsteps of Oparin and Dyson in reconstructing primordial self-propagating functional molecular networks. Such networks were initially non-genetic and presumably similar to “lipid world” vesicles. Components of these networks were simple catalysts resembling contemporary coenzymes which might have colonized the surface of small oil droplets in water, where oil (mostly alkanes) was both a substrate and nutrient. Coenzyme-like molecules (CLMs) changed the surface properties of oil droplets, and in this way created favorable conditions for their own self-reproduction. Heredity was supported by a transfer of CLMs
to daughter oil droplets following an accidental split of parental droplets. Niche-dependent self-reproduction and natural selection were necessary conditions for the emergence of cooperation between different kinds of CLMs
that inhabited the same oil droplet. Eventually, some CLMs
formed polymers and their adaptive evolution resulted in the emergence of template-based synthesis similar to that of nucleic acids. Oil droplets eventually transformed into the outer membrane of cells via engulfing water, stabilization of the surface, and osmoregulation. As a result, the metabolism was internalized, allowing cells to accumulate free-floating resources, which was a necessary condition for the emergence of protein
synthesis. This scenario covers a long evolutionary path from simple but already functional and evolvable molecules to cellular organisms comparable to the Last Universal Common Ancestor (LUCA
).
... Other similar models also contributed to this theory (32)(33)(34)(35)(36), including the chemical organization theory (37) and the graded autocatalysis replication domain model (38). The former is closely related to RAF theory (see Hordijk et al. (39) for a detailed comparison), whereas the latter suffers from lacking evolvability (see Vasas et al. (40,41) for detailed critical analyses). In addition, many of the biological observations mentioned in the previous paragraph can be put into the framework of RAF theory (15,(17)(18)(19)(20). ...
Explaining origins of life requires us to explain how self-replication arises. Specifically, how can self-replicating entities develop spontaneously from chemical reaction systems in which no reaction is self-replicating? Previous models either supply a framework for minimal living systems or only consider catalyzed reactions, and thus fail to provide a comprehensive theory. We establish a general model for chemical reaction systems that properly accounts for energetics, kinetics and conservation laws. We find that (1) some systems are collectively-catalytic (e.g., the citric acid cycle), while others self-replicate as a whole (e.g., the formose reaction); (2) side reactions do not always inhibit such systems; (3) many alternative chemical universes often contain one or more such systems; (4) in some self-replicating systems, the entropy of certain parts spontaneously decreases; (5) complex self-replicating molecules emerge spontaneously from simple reaction systems through a sequence of transitions. Together these results start to explain origins of prebiotic evolution.
... With the emergence of these prebiotic metabolisms, it is generally considered that the further step in the evolution of life, i.e., the transition to living matter, might have occurred with the encapsulation of these organic molecules within micelles or vesicles [34]. Although several mathematical models have been proposed to account for the development of evolvable systems from prebiotic chemistries [231], but see also [258,259], lipid micelles have been demostrated to form spontaneously through a self-assembly process starting from free fatty acids and minerals [98]. Also, with the availability of free ribonucleotides from the primordial nonenzymatic reactions (and this seems to be plausible, see [206,240,20], it was shown that RNA polymers can form in the presence of montmorillonite, a clay present in hydrothermal vents [75,126]. ...
The origin of primordial metabolism and its expansion to form the metabolic networks extant today represent excellent systems to study the impact of natural selection and the potential adaptive role of novel compounds. Here we present the current hypotheses made on the origin of life and ancestral metabolism and present the theories and mechanisms by which the large chemical diversity of plants might have emerged along evolution. In particular, we provide a survey of statistical methods that can be used to detect signatures of selection at the gene and population level, and discuss potential and limits of these methods for investigating patterns of molecular adaptation in plant metabolism.
... In general, compartmentalization itself (transient or not) is not a sufficient property for a system to be a true evolutionary unit (cf. [32,33]). ...
Complexity of life forms on the Earth has increased tremendously, primarily driven by subsequent evolutionary transitions in individuality, a mechanism in which units formerly being capable of independent replication combine to form higher-level evolutionary units. Although this process has been likened to the recursive combination of pre-adapted sub-solutions in the framework of learning theory, no general mathematical formalization of this analogy has been provided yet. Here we show, building on former results connecting replicator dynamics and Bayesian update, that (i) evolution of a hierarchical population under multilevel selection is equivalent to Bayesian inference in hierarchical Bayesian models and (ii) evolutionary transitions in individuality, driven by synergistic fitness interactions, is equivalent to learning the structure of hierarchical models via Bayesian model comparison. These correspondences support a learning theory-oriented narrative of evolutionary complexification: the complexity and depth of the hierarchical structure of individuality mirror the amount and complexity of data that have been integrated about the environment through the course of evolutionary history.
... Other similar models also contributed to this theory (32)(33)(34)(35)(36), including the chemical organization theory (37) and the graded autocatalysis replication domain model (38). The former is closely related to RAF theory (see (39) for a detailed comparison), while the latter suffers from laking evolvability (see (40,41) for detailed critical analyses). In addition, many of the biological observations mentioned in the previous paragraph can be put into the framework of RAF theory (15,(17)(18)(19)(20). ...
Explaining the origin of life requires us to elucidate how self-replication arises. To be specific, how can a self-replicating entity develop spontaneously from a chemical reaction system in which no reaction is self-replicating? Previously proposed mathematical models either supply an explicit framework for a minimal living system or consider only catalyzed reactions, and thus fail to provide a comprehensive theory. Here, we set up a general mathematical model for chemical reaction systems that properly accounts for energetics, kinetics, and the conservation law. We found that (1) some systems are collectively-catalytic, a mode whereby reactants are transformed into end products with the assistance of intermediates (as in the citric acid cycle), whereas some others are self-replicating, that is, different parts replicate each other and the system self-replicates as a whole (as in the formose reaction, in which sugar is replicated from formaldehyde); (2) side reactions do not always inhibit such systems; (3) randomly chosen chemical universes (namely, random artificial chemistries) often contain one or more such systems; (4) it is possible to construct a self-replicating system in which the entropy of some parts spontaneously decreases, in a manner similar to that discussed by Schrödinger; and (5) complex self-replicating molecules can emerge spontaneously and relatively easily from simple chemical reaction systems through a sequence of transitions. Together, these results start to explain the origins of prebiotic evolution.
... They also admit that the system size is unknown. They claim that the most exciting form of evolvability is indefinite, open-ended on going evolution, possibly leading to an increase in complexity, at least in certain lineages [19]. ...
Background:
This essay highlights critical aspects of the plausibility of pre-Darwinian evolution. It is based on a critical review of some better-known open, far-from-equilibrium system-based scenarios supposed to explain processes that took place before Darwinian evolution had emerged and that resulted in the origin of the first systems capable of Darwinian evolution. The researchers' responses to eight crucial questions are reviewed. The majority of the researchers claim that there would have been an evolutionary continuity between chemistry and "biology". A key question is how did this evolution begin before Darwinian evolution had begun? In other words the question is whether pre-Darwinian evolution is plausible.
Results:
Strengths and weaknesses of the reviewed scenarios are presented. They are distinguished between metabolism-first, replicator-first and combined metabolism-replicator models. The metabolism-first scenarios show major issues, the worst concerns heredity and chirality. Although the replicator-first scenarios answer the heredity question they have their own problems, notably chirality. Among the reviewed combined metabolism-replicator models, one shows the fewest issues. In particular, it seems to answer the chiral question, and eventually implies Darwinian evolution from the very beginning. Its main hypothesis needs to be validated with experimental data.
Conclusion:
From this critical review it is that the concept of "pre-Darwinian evolution" appears questionable, in particular because it is unlikely if not impossible that any evolution in complexity over time may work without multiplication and heritability allowing the emergence of genetically and ecologically diverse lineages on which natural selection may operate. Only Darwinian evolution could have led to such an evolution. Thus, Pre-Darwinian evolution is not plausible according to the author. Surely, the answer to the question posed in the title is a prerequisite to the understanding of the origin of Darwinian evolution.
Reviewers:
This article was reviewed by Purificacion Lopez-Garcia, Anthony Poole, Doron Lancet, and Thomas Dandekar.
... The foregoing sections portray evidence for the capacity of mutually catalytic networks embodied in lipid GARD assemblies to undergo self-reproduction, bequeathing their compositional information. This conviction is shared both by proponents [15,70,115] and critics [27,116]. But selfsustainment and replication/reproduction are only one of the two essential characteristics of life by the NASA definition, the other being a capacity to evolve. ...
Life is that which replicates and evolves, but there is no consensus on how life emerged. We advocate a systems protobiology view, whereby the first replicators were assemblies of spontaneously accreting, heterogeneous and mostly non-canonical amphiphiles. This view is substantiated by rigorous chemical kinetics simulations of the graded autocatalysis replication domain (GARD) model, based on the notion that the replication or reproduction of compositional information predated that of sequence information. GARD reveals the emergence of privileged non-equilibrium assemblies (composomes), which portray catalysis-based homeostatic (concentration-preserving) growth. Such a process, along with occasional assembly fission, embodies cell-like reproduction. GARD pre-RNA evolution is evidenced in the selection of different composomes within a sparse fitness landscape, in response to environmental chemical changes. These observations refute claims that GARD assemblies (or other mutually catalytic networks in the metabolism first scenario) cannot evolve. Composomes represent both a genotype and a selectable phenotype, anteceding present-day biology in which the two are mostly separated. Detailed GARD analyses show attractor-like transitions from random assemblies to self-organized composomes, with negative entropy change, thus establishing composomes as dissipative systems-hallmarks of life. We show a preliminary new version of our model, metabolic GARD (M-GARD), in which lipid covalent modifications are orchestrated by non-enzymatic lipid catalysts, themselves compositionally reproduced. M-GARD fills the gap of the lack of true metabolism in basic GARD, and is rewardingly supported by a published experimental instance of a lipid-based mutually catalytic network. Anticipating near-future far-reaching progress of molecular dynamics, M-GARD is slated to quantitatively depict elaborate protocells, with orchestrated reproduction of both lipid bilayer and lumenal content. Finally, a GARD analysis in a whole-planet context offers the potential for estimating the probability of life's emergence. The invigorated GARD scrutiny presented in this review enhances the validity of autocatalytic sets as a bona fide early evolution scenario and provides essential infrastructure for a paradigm shift towards a systems protobiology view of life's origin.
... In general, compartmentalization itself (transient or not) is not a sufficient property for a system to be a true evolutionary unit (cf. [32,33]). ...
Complexity of life forms on Earth has increased tremendously, primarily driven by subsequent evolutionary transitions in individuality, a mechanism in which units formerly being capable of independent replication combine to form higher-level evolutionary units. Although this process has been likened to the recursive combination of pre-adapted sub-solutions in the framework of learning theory, no general mathematical formalization of this analogy has been provided yet. Here we show, building on former results connecting replicator dynamics and Bayesian update, that (i) evolution of a hierarchical population under multilevel selection is equivalent to Bayesian inference in hierarchical Bayesian models, and (ii) evolutionary transitions in individuality, driven by synergistic fitness interactions, is equivalent to learning the structure of hierarchical models via Bayesian model comparison. These correspondences support a learning theory oriented narrative of evolutionary complexification: the complexity and depth of the hierarchical structure of individuality mirrors the amount and complexity of data that has been integrated about the environment through the course of evolutionary history.
... It has to first discover ways to reduce the error rate, but it has to do so using the limited palette of molecules it can currently produce and replicate. This is a very tough call (Czaran et al 2015, Kun et al 2015, Maynard-Smith and Szathmary 1995, Vasas et al 2015, and in a sense it is the ultimate chicken and egg problem if we equate the chicken with the currently feasible set of molecules and the egg with the current information limit. More complex molecules are needed to evolve mechanisms that can reduce the error rate, but such complex molecules cannot be built until the error rate is reduced sufficiently to permit them. ...
Recent advances suggest that the concept of information might hold the key to unravelling the mystery of life's nature and origin. Fresh insights from a broad and authoritative range of articulate and respected experts focus on the transition from matter to life, and hence reconcile the deep conceptual schism between the way we describe physical and biological systems. A unique cross-disciplinary perspective, drawing on expertise from philosophy, biology, chemistry, physics, and cognitive and social sciences, provides a new way to look at the deepest questions of our existence. This book addresses the role of information in life, and how it can make a difference to what we know about the world. Students, researchers, and all those interested in what life is and how it began will gain insights into the nature of life and its origins that touch on nearly every domain of science.
... The later study found that GARD systems can respond to selection (but not always), and that this selection response is more favourable when the matrix instance is highly mutualistic (i.e. when off-diagonal values are higher than diagonal values). A recent attempt to extend the 2010 paper by attempting to map GARD into the quasispecies formalism [45] presents an argument on GARD's putative limited evolvability. The paper failed however to designate compotypes as selection targets, even thought it was previously shown that only compotypes can be mapped into quasispecies [32], and used atypical GARD parameters. ...
An intriguing question in evolution is what would happen if one could “replay” life’s tape. Here, we explore the following hypothesis: when replaying the tape, the details (“decorations”) of the outcomes would vary but certain “invariants” might emerge across different life-tapes sharing similar initial conditions. We use large-scale simulations of an in silico model of pre-biotic evolution called GARD (Graded Autocatalysis Replication Domain) to test this hypothesis. GARD models the temporal evolution of molecular assemblies, governed by a rates matrix (i.e. network) that biases different molecules’ likelihood of joining or leaving a dynamically growing and splitting assembly. Previous studies have shown the emergence of so called compotypes, i.e., species capable of replication and selection response. Here, we apply networks’ science to ascertain the degree to which invariants emerge across different life-tapes under GARD dynamics and whether one can predict these invariant from the chemistry specification alone (i.e. GARD’s rates network representing initial conditions). We analysed the (complex) rates’ network communities and asked whether communities are related (and how) to the emerging species under GARD’s dynamic, and found that the communities correspond to the species emerging from the simulations. Importantly, we show how to use the set of communities detected to predict species emergence without performing any simulations. The analysis developed here may impact complex systems simulations in general.
... Our aim is to provide a comparative review of the field's most important models. We will confine our focus on models of linear polymer replicators (string replicators) and will not survey models dealing only with higher-level (compositional) dynamics such as the GARD model [7][8][9] or the models of autocatalytic sets [10][11][12], as those models can be understood as special cases of others discussed in this paper (for critical analyses of GARD, see [13,14]). ...
As of today, the most credible scientific paradigm pertaining to the origin of life on Earth is undoubtedly the RNA World scenario. It is built on the assumption that catalytically active replicators (most probably RNA-like macromolecules) may have been responsible for booting up life almost four billion years ago. The many different incarnations of nucleotide sequence (string) replicator models proposed recently are all attempts to explain on this basis how the genetic information transfer and the functional diversity of prebiotic replicator systems may have emerged, persisted and evolved into the first living cell. We have postulated three necessary conditions for an RNA World model system to be a dynamically feasible representation of prebiotic chemical evolution: (1) it must maintain and transfer a sufficient diversity of information reliably and indefinitely, (2) it must be ecologically stable and (3) it must be evolutionarily stable. In this review, we discuss the best-known prebiotic scenarios and the corresponding models of string-replicator dynamics and assess them against these criteria. We suggest that the most popular of prebiotic replicator systems, the hypercycle, is probably the worst performer in almost all of these respects, whereas a few other model concepts (parabolic replicator, open chaotic flows, stochastic corrector, metabolically coupled replicator system) are promising candidates for development into coherent models that may become experimentally accessible in the future.
... Parasites are replicators that receive catalysis from another species but do not reciprocate the catalytic aid [10]. Short-circuits, which can be of different nature, are catalytic connections generating inner and smaller catalytic sub-cycles [13,28]. Short-circuits have been suggested to pose a serious problem towards the growth of hypercycle systems, since smallest and thus fastest catalytic cycles may outcompete the larger and slower ones, thus constraining hypercycles' size, complexity, and functionality. ...
It is known that hypercycles are sensitive to the so-called parasites and short-circuits. While the impact of parasites has been widely investigated for well-mixed and spatial hypercycles, the effect of short-circuits in hypercycles remains poorly understood. In this article we analyze the mean field and spatial dynamics of two small, asymmetric hypercycles with short-circuits. Specifically, we analyze a two-member hypercycle where one of the species contains an autocatalytic loop, as the simplest hypercycle with a short-circuit. Then, we extend this system by adding another species that closes a three-member hypercycle while keeping the autocatalytic short-circuit and the two-member cycle. The mean field model allows us to discard the presence of stable or unstable periodic orbits for both systems. We characterize the bifurcations and transitions involved in the dominance of the short-circuits i.e., in the reduction of the hypercycles’ size. The spatial simulations reveal a random-like and mixed distribution of the replicators in the all-species coexistence, ruling out the presence of large-scale spatial patterns such as spirals or spots typical of larger, oscillating hypercycles. A MonteCarlo sampling of the parameter space for the well-mixed and the spatial models reveals that the probability of finding stable hypercycles with short-circuits drastically diminishes from the two-member to the three-member system, especially at growing degradation rates of the replicators. These findings pose a big constrain in the increase of hypercycle’s size and complexity under the presence of inner cycles, suggesting the importance of a rapid growth of hypercycles able to generate spatial structures (e.g., rotating spirals) prior to the emergence of inner cycles. Our results can also be useful for the future design and implementation of synthetic cooperative systems containing catalytic short-circuits.
... 76 and 77), or they might self-assemble to be a functional ribozyme. 78 Vasas et al. 79 analyzed the kinetic stability of a simple two-membered autocatalytic loop, in which each member catalyzes the inclusion of one noncatalytic molecule. If there are large differences in catalytic efficiencies (as it is probable in the prebiotic context), the system shows kinetic instability. ...
... 76 and 77), or they might self-assemble to be a functional ribozyme. 78 Vasas et al. 79 analyzed the kinetic stability of a simple two-membered autocatalytic loop, in which each member catalyzes the inclusion of one noncatalytic molecule. If there are large differences in catalytic efficiencies (as it is probable in the prebiotic context), the system shows kinetic instability. ...
The RNA world hypothesis of the origin of life, in which RNA emerged as both enzyme and information carrier, is receiving solid experimental support. The prebiotic synthesis of biomolecules, the catalytic aid offered by mineral surfaces, and the vast enzymatic repertoire of ribozymes are only pieces of the origin of life puzzle; the full picture can only emerge if the pieces fit together by either following from one another or coexisting with each other. Here, we review the theory of the origin, maintenance, and enhancement of the RNA world as an evolving population of dynamical systems. The dynamical view of the origin of life allows us to pinpoint the missing and the not fitting pieces: (1) How can the first self-replicating ribozyme emerge in the absence of template-directed information replication? (2) How can nucleotide replicators avoid competitive exclusion despite utilizing the very same resources (nucleobases)? (3) How can the information catastrophe be avoided? (4) How can enough genes integrate into a cohesive system in order to transition to a cellular stage? (5) How can the way information is stored and metabolic complexity coevolve to pave to road leading out of the RNA world to the present protein-DNA world?
© 2015 New York Academy of Sciences.
The nineteenth century saw a major transition in thinking from a static universe made perfect by a divine creator to one full of change. The transition was led by biologists, most notably Charles Darwin. Darwin’s panoramic vision of evolution involved the interaction between two major factors, the Nature of the Organism and Nature of the Conditions, with the former predominating over the latter due to the historically conservative and autonomous nature of organisms and their inheritance systems. From this emerges a “struggle for existence” producing Natural Selection—an outcome of the interaction favoring any organism adequate enough to cope with the conditions by surviving and reproducing. In today’s terms, Darwinism was a theory of complex systems, which he attempted to communicate using two great visual metaphors, the Tree of Life and Entangled Bank. In Darwin’s day, complexity was not in style; good theories were simple with deterministic lawlike behavior. Furthermore, social styles that originated in the eighteenth century including Naturalism, Modernism, and Romanticism, sought progress and perfection in explanations of the natural world. Within the scientific community, the mix of these social preferences and general acceptance of the notion of biological evolution led to several research programs aimed at “fixing” or replacing Darwinism. By the end of the nineteenth century, four distinct theoretical frameworks—Geographic differentiation, Orthogenesis, neo-Lamarckism, and neo-Darwinism—had emerged as rivals in the race to replace Darwin.
The twentieth century saw neo-Darwinism absorb its competitors and coalesce into the Hardened Modern Synthesis. Vernon Kellogg helped usher in this new era with Darwinism Today, proclaiming in 1907 that Darwinism was of critical historical importance but little actual scientific value and anticipating that new experimental and mathematical data would resolve the struggle among competing frameworks to replace it. Kellogg was prescient in proclaiming that the core question was how the right adaptation always arose at the right time, which became the major focus of twentieth-century evolutionary biology. Darwin’s notion that preexisting variation was the fuel for coping with environmental change was abandoned in favor of something more heroic and aspirational, satisfying the ultramodernist styles of the time. In the ensuing decades, neo-Darwinian pan-adaptationism became the Modern Synthesis, permeating all corners of biology, especially ecology and behavior. By the 1980s, the Modern Synthesis hardened further. Natural selection was entrenched as a sharp-edged tool rather than Darwin’s blunt instrument; a creative force from which function follows the conditions and form follows function. The Nature of the Conditions became the dominant explanation for everything, the Nature of the Organism relegated to an epiphenomenon. Evolutionary explanations became increasingly ecological and ahistorical, focused on how every trait was an adaptation to the conditions, and how the conditions were structured to accommodate organisms in the form of preexisting niches or zones. Seventy-five years on, Darwinism seemed to be as dead as Kellogg asserted.
This book presents a unified evolutionary framework based on three sets of metaphors that will help to consolidate discussions on evolutionary transitions.
Evolution is the unifying principle of life, making identifying ways to apply evolutionary principles to tackle existence-threatening crises such as climate change crucial. A more cohesive evolutionary framework will further the discussions in this regard and also accelerate the process itself.
This book lays out a framework based on three dualistic classes of metaphors – time, space, and conflict resolution. Evolutionary transitions theory shows how metaphors can help us understand selective diversification, as Darwin described with his “tree of life”. Moreover, the recently proposed Stockholm paradigm demonstrates how metaphors can help shed light on the emergence of complex ecosystems that Darwin highlighted with his “tangled bank” metaphor. Taken together, these ideas offer proactive measures for coping with existential crises for humanity, such as climate change.
The book will appeal to biologists, philosophers and historians alike.
A good portion of the ‘protein universe’ embodies the ‘dark proteome’. The latter comprises proteins not amenable to experimental structure determination by existing means and inaccessible to homology modeling. Hence, the dark proteome has remained largely unappreciated. Intrinsically disordered proteins (IDPs) that lack rigid 3D structure are a major component of this dark proteome across all three kingdoms of life. Despite lack of structure, IDPs play critical roles in numerous important biological processes. Furthermore, IDPs serve as crucial constituents of proteinaceous membrane‐less organelles (PMLOs), where they often serve as drivers and controllers of biological liquid‐liquid phase transitions responsible for the PMLO biogenesis. In this perspective, we discuss the role of IDPs in i) the origin of prebiotic life and the evolution of the first independent primordial living unit akin to Tibor Gánti's chemoton, which preceded the Last Universal Common Ancestor (LUCA), ii) role in multicellularity and hence, in major evolutionary transitions, and iii), their role in phenotypic switching, and the emergence of new traits and adaptive opportunities via non‐genetic, protein‐based, mechanisms. The emerging picture suggests that, despite being major constituents of the dark matter, IDPs may be the dark horse in the protein universe.
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Significance
Today’s lifeforms are based on informational polymers, namely proteins and nucleic acids. It is thought that simple chemical processes on the early earth could have polymerized monomer units into short random sequences. It is not clear, however, what physical process could have led to the next level—to longer chains having particular sequences that could increase their own concentrations. We study polymers of hydrophobic and polar monomers, such as today’s proteins. We find that even some random sequence short chains can collapse into compact structures in water, with hydrophobic surfaces that can act as primitive catalysts, and that these could elongate other chains. This mechanism explains how random chemical polymerizations could have given rise to longer sequence-dependent protein-like catalytic polymers.
This article explores the remote scientific possibility of something like “cosmic mind” or “cosmic minds.” Descartes proposed his famous dualism, res cogitans (mental reality) plus res extensa (physical reality). With Isaac Newton and classical physics, res extensa won in Western science and with it, we lost our minds; we lost our subjective pole. Quantum mechanics has seemed to many, since its formulation in the Schrödinger equation in 1926, to hint beyond physics to a role for the human conscious observer in quantum measurement. At least two interpretations of quantum mechanics, or its extension—the latter by Penrose and Hameroff, and the former by myself—suggest a new panpsychism where conscious awareness and possibly free will occur at quantum measurements anywhere in the universe. If so, then we live in a vastly participatory universe. More: entangled quantum variables may conceivably share some form of consciousness and free will, whether embodied in us, or living forms elsewhere in the universe, or disembodied; hence, something like cosmic mind or minds are not ruled out. If true, life anywhere in the universe will have evolved with mind and free will. Souls are not impossible.
Incluye bibliografía e índice
Background
The quasispecies model refers to information carriers that undergo self-replication with errors. A quasispecies is a steady-state population of biopolymer sequence variants generated by mutations from a master sequence. A quasispecies error threshold is a minimal replication accuracy below which the population structure breaks down. Theory and experimentation of this model often refer to biopolymers, e.g. RNA molecules or viral genomes, while its prebiotic context is often associated with an RNA world scenario. Here, we study the possibility that compositional entities which code for compositional information, intrinsically different from biopolymers coding for sequential information, could show quasispecies dynamics.ResultsWe employed a chemistry-based model, graded autocatalysis replication domain (GARD), which simulates the network dynamics within compositional molecular assemblies. In GARD, a compotype represents a population of similar assemblies that constitute a quasi-stationary state in compositional space. A compotype's center-of-mass is found to be analogous to a master sequence for a sequential quasispecies. Using single-cycle GARD dynamics, we measured the quasispecies transition matrix (Q) for the probabilities of transition from one center-of-mass Euclidean distance to another. Similarly, the quasispecies¿ growth rate vector (A) was obtained. This allowed computing a steady state distribution of distances to the center of mass, as derived from the quasispecies equation. In parallel, a steady state distribution was obtained via the GARD equation kinetics. Rewardingly, a significant correlation was observed between the distributions obtained by these two methods. This was only seen for distances to the compotype center-of-mass, and not to randomly selected compositions. A similar correspondence was found when comparing the quasispecies time dependent dynamics towards steady state. Further, changing the error rate by modifying basal assembly joining rate of GARD kinetics was found to display an error catastrophe, similar to the standard quasispecies model. Additional augmentation of compositional mutations leads to the complete disappearance of the master-like composition.Conclusions
Our results show that compositional assemblies, as simulated by the GARD formalism, portray significant attributes of quasispecies dynamics. This expands the applicability of the quasispecies model beyond sequence-based entities, and potentially enhances validity of GARD as a model for prebiotic evolution.
The hypercycle is a system of replicators, whose members are auto- and cross-catalytic: replication of each member is catalyzed by at least one other member of the system. Therefore, the kinetics of growth of every member is at least second order. In ecology such systems are called mutualistic whose members are cooperating with each other. The dynamics of such systems are described broadly by the replicator equation. In chemistry hypercycles are often confused with collectively autocatalytic systems in which the members catalyze each other’s formation rather than replication (growth being therefore first-order). Examples of this confusion abound in the literature. The trouble is that such category errors mistakenly imply that the available theories of hypercycles and cooperation are applicable, although in fact they are not. Cooperation in population biology means a higher-order interaction among agents with (at least the capacity of) multiplication. From the point of evolution, what matters is the genetic effects on the cooperative act. As systems chemistry has one of its roots in the theoretical biology, insights from this field ought to be respected even by experimentalists, let alone theoreticians.
Maynard Smithis analysis of units of evolution is compared to traditional approaches generalizing Darwinis principles. Maynard Smithis key principle of multiplication is elaborated into a general account of the process of reproduction that integrates concepts of heredity and development and is applicable to all levels of the biological hierarchy. The amended analysis suggests a new unit of evolution, the ireproducer,i which generalizes the concept of a replicator. The theory of evolutionary transition, the evolutionary origin of new levels of biological organization, is revised to reflect these amendments to the analysis of units. A three-stage scenario for evolutionary transition is suggested.
In this paper we explore the question of whether there is an optimal set up for a putative prebiotic system leading to open-ended evolution (OEE) of the events unfolding within this system. We do so by proposing two key innovations. First, we introduce a new index that measures OEE as a function of the likelihood of events unfolding within a universe given its initial conditions. Next, we apply this index to a variant of the graded autocatalysis replication domain (GARD) model, Segre et al. (P Natl Acad Sci USA 97(8):4112-4117, 2000; Markovitch and Lancet Artif Life 18(3), 2012), and use it to study - under a unified and concise prebiotic evolutionary framework - both a variety of initial conditions of the universe and the OEE of species that evolve from them.
Evolvability in its simplest form is the ability of a population to respond to directional selection. More interestingly it means that some lineages show open-ended evolution by accumulating novel adaptations, and that some lineages complexity can increase indefinitely. Unlimited heredity is a precondition for such rich open-endedness, another one seems to be (analogous to) chemical combinatorics. The richness of matter seems to be a source of challenges and opportunities not yet matched in artificial algorithms. However, some "artificial" systems can be more evolvable than natural ones because for the former the whole population is not under the constraint to survive in the wild. A form of artificial selection may happen even in the brain of replicable patterns that yield complex adaptations within the lifetime of the individual.
The common opinion has been that evolution results in the continuing development of more complex forms of life, generally
understood as more complex organisms. The arguments supporting that opinion have recently come under scrutiny and been found
wanting. Nevertheless, the appearance of increasing complexity remains. So, is there some sense in which evolution does grow
complexity? Artificial life simulations have consistently failed to reproduce even the appearance of increasing complexity,
which poses a challenge. Simulations, as much as scientific theories, are obligated at least to save the appearances! We suggest
a relation between these two problems, understanding biological complexity growth and the failure to model even its appearances.
We present a different understanding of that complexity which evolution grows, one that genuinely runs counter to entropy
and has thus far eluded proper analysis in information-theoretic terms. This complexity is reflected best in the increase
in niches within the biosystem as a whole. Past and current artificial life simulations lack the resources with which to grow
niches and so to reproduce evolution’s complexity. We propose a more suitable simulation design integrating environments and
organisms, allowing old niches to change and new ones to emerge.
KeywordsBiological complexity–Diffusion–Niche construction–Artificial life–Open-ended evolution
Autocatalytic sets are often considered a necessary (but not sufficient) condition for the origin and early evolution of life. Although the idea of autocatalytic sets was already conceived of many years ago, only recently have they gained more interest, following advances in creating them experimentally in the laboratory. In our own work, we have studied autocatalytic sets extensively from a computational and theoretical point of view.
We present results from an initial study of the dynamics of self-sustaining autocatalytic sets (RAFs). In particular, simulations of molecular flow on autocatalytic sets are performed, to illustrate the kinds of dynamics that can occur. Next, we present an extension of our (previously introduced) algorithm for finding autocatalytic sets in general reaction networks, which can also handle inhibition. We show that in this case detecting autocatalytic sets is fixed parameter tractable. Finally, we formulate a generalized version of the algorithm that can also be applied outside the context of chemistry and origin of life, which we illustrate with a toy example from economics.
Having shown theoretically (in previous work) that autocatalytic sets are highly likely to exist, we conclude here that also in terms of dynamics such sets are viable and outcompete non-autocatalytic sets. Furthermore, our dynamical results confirm arguments made earlier about how autocatalytic subsets can enable their own growth or give rise to other such subsets coming into existence. Finally, our algorithmic extension and generalization show that more realistic scenarios (e.g., including inhibition) can also be dealt with within our framework, and that it can even be applied to areas outside of chemistry, such as economics.
Our current understanding of evolution is so tightly linked to template-dependent replication of DNA and RNA molecules that the old idea from Oparin of a self-reproducing 'garbage bag' ('coacervate') of chemicals that predated fully-fledged cell-like entities seems to be farfetched to most scientists today. However, this is exactly the kind of scheme we propose for how Darwinian evolution could have occurred prior to template replication.
We cannot confirm previous claims that autocatalytic sets of organic polymer molecules could undergo evolution in any interesting sense by themselves. While we and others have previously imagined inhibition would result in selectability, we found that it produced multiple attractors in an autocatalytic set that cannot be selected for. Instead, we discovered that if general conditions are satisfied, the accumulation of adaptations in chemical reaction networks can occur. These conditions are the existence of rare reactions producing viable cores (analogous to a genotype), that sustains a molecular periphery (analogous to a phenotype).
We conclude that only when a chemical reaction network consists of many such viable cores, can it be evolvable. When many cores are enclosed in a compartment there is competition between cores within the same compartment, and when there are many compartments, there is between-compartment competition due to the phenotypic effects of cores and their periphery at the compartment level. Acquisition of cores by rare chemical events, and loss of cores at division, allows macromutation, limited heredity and selectability, thus explaining how a poor man's natural selection could have operated prior to genetic templates. This is the only demonstration to date of a mechanism by which pre-template accumulation of adaptation could occur.
A basic property of life is its capacity to experience Darwinian evolution. The replicator concept is at the core of genetics-first theories of the origin of life, which suggest that self-replicating oligonucleotides or their similar ancestors may have been the first "living" systems and may have led to the evolution of an RNA world. But problems with the nonenzymatic synthesis of biopolymers and the origin of template replication have spurred the alternative metabolism-first scenario, where self-reproducing and evolving proto-metabolic networks are assumed to have predated self-replicating genes. Recent theoretical work shows that "compositional genomes" (i.e., the counts of different molecular species in an assembly) are able to propagate compositional information and can provide a setup on which natural selection acts. Accordingly, if we stick to the notion of replicator as an entity that passes on its structure largely intact in successive replications, those macromolecular aggregates could be dubbed "ensemble replicators" (composomes) and quite different from the more familiar genes and memes. In sharp contrast with template-dependent replication dynamics, we demonstrate here that replication of compositional information is so inaccurate that fitter compositional genomes cannot be maintained by selection and, therefore, the system lacks evolvability (i.e., it cannot substantially depart from the asymptotic steady-state solution already built-in in the dynamical equations). We conclude that this fundamental limitation of ensemble replicators cautions against metabolism-first theories of the origin of life, although ancient metabolic systems could have provided a stable habitat within which polymer replicators later evolved.
There is no theoretical reason to expect evolutionary lineages to increase in complexity with time, and no empirical evidence that they do so. Nevertheless, eukaryotic cells are more complex than prokaryotic ones, animals and plants are more complex than protists, and so on. This increase in complexity may have been achieved as a result of a series of major evolutionary transitions. These involved changes in the way information is stored and transmitted.
Replicators of interest in chemistry, biology and culture are briefly surveyed from a conceptual point of view. Systems with limited heredity have only a limited evolutionary potential because the number of available types is too low. Chemical cycles, such as the formose reaction, are holistic replicators since replication is not based on the successive addition of modules. Replicator networks consisting of catalytic molecules (such as reflexively autocatalytic sets of proteins, or reproducing lipid vesicles) are hypothetical ensemble replicators, and their functioning rests on attractors of their dynamics. Ensemble replicators suffer from the paradox of specificity: while their abstract feasibility seems to require a high number of molecular types, the harmful effect of side reactions calls for a small system size. No satisfactory solution to this problem is known. Phenotypic replicators do not pass on their genotypes, only some aspects of the phenotype are transmitted. Phenotypic replicators with limited heredity include genetic membranes, prions and simple memetic systems. Memes in human culture are unlimited hereditary, phenotypic replicators, based on language. The typical path of evolution goes from limited to unlimited heredity, and from attractor-based to modular (digital) replicators.
The continuity of abiotically formed bilayer membranes with similar structures in contemporary cellular life, and the requirement for microenvironments in which large and small molecules could be compartmentalized, support the idea that amphiphilic boundary structures contributed to the emergence of life. As an extension of this notion, we propose here a 'Lipid World' scenario as an early evolutionary step in the emergence of cellular life on Earth. This concept combines the potential chemical activities of lipids and other amphiphiles, with their capacity to undergo spontaneous self-organization into supramolecular structures such as micelles and bilayers. In particular, the documented chemical rate enhancements within lipid assemblies suggest that energy-dependent synthetic reactions could lead to the growth and increased abundance of certain amphiphilic assemblies. We further propose that selective processes might act on such assemblies, as suggested by our computer simulations of mutual catalysis among amphiphiles. As demonstrated also by other researchers, such mutual catalysis within random molecular assemblies could have led to a primordial homeostatic system displaying rudimentary life-like properties. Taken together, these concepts provide a theoretical framework, and suggest experimental tests for a Lipid World model for the origin of life.
We hypothesize that life began not with the first self-reproducing molecule or metabolic network, but as a prebiotic ecology of co-evolving populations of macromolecular aggregates (composomes). Each composome species had a particular molecular composition resulting from molecular complementarity among environmentally available prebiotic compounds. Natural selection acted on composomal species that varied in properties and functions such as stability, catalysis, fission, fusion and selective accumulation of molecules from solution. Fission permitted molecular replication based on composition rather than linear structure, while fusion created composomal variability. Catalytic functions provided additional chemical novelty resulting eventually in autocatalytic and mutually catalytic networks within composomal species. Composomal autocatalysis and interdependence allowed the Darwinian co-evolution of content and control (metabolism). The existence of chemical interfaces within complex composomes created linear templates upon which self-reproducing molecules (such as RNA) could be synthesized, permitting the evolution of informational replication by molecular templating. Mathematical and experimental tests are proposed.
Different ways in which evolution can be modelled will be reviewed. Two
asexual models -- `Muller's ratchet' and a model due to Eigen and
Schuster -- both lead to the conclusion that the accuracy of replication
must reach a limiting value, but the details are different. In classic
population genetics models, difficulties arise if fitnesses depend on
interactions with others. Two approaches -- `trait group' methods, and
game theory -- are discussed. If the interacting individuals are
relatives, there is again a choice between the exact
`neighbour-modulated fitness' approach and the more intuitive `inclusive
fitness' method. A more drastic change in the nature of the model arises
if the units of the evolving system are not individual organisms, but
either genes or species. There are conceptual difficulties which must be
clarified before species selection can be analysed mathematically.
Some evolutionary innovations may originate non-adaptively as exaptations, or pre-adaptations, which are by-products of other adaptive traits. Examples include feathers, which originated before they were used in flight, and lens crystallins, which are light-refracting proteins that originated as enzymes. The question of how often adaptive traits have non-adaptive origins has profound implications for evolutionary biology, but is difficult to address systematically. Here we consider this issue in metabolism, one of the most ancient biological systems that is central to all life. We analyse a metabolic trait of great adaptive importance: the ability of a metabolic reaction network to synthesize all biomass from a single source of carbon and energy. We use novel computational methods to sample randomly many metabolic networks that can sustain life on any given carbon source but contain an otherwise random set of known biochemical reactions. We show that when we require such networks to be viable on one particular carbon source, they are typically also viable on multiple other carbon sources that were not targets of selection. For example, viability on glucose may entail viability on up to 44 other sole carbon sources. Any one adaptation in these metabolic systems typically entails multiple potential exaptations. Metabolic systems thus contain a latent potential for evolutionary innovations with non-adaptive origins. Our observations suggest that many more metabolic traits may have non-adaptive origins than is appreciated at present. They also challenge our ability to distinguish adaptive from non-adaptive traits.
The seemingly innocent observation that the activities of organisms bring about changes in environments is so obvious that it seems an unlikely focus for a new line of thinking about evolution. Yet niche construction--as this process of organism-driven environmental modification is known--has hidden complexities. By transforming biotic and abiotic sources of natural selection in external environments, niche construction generates feedback in evolution on a scale hitherto underestimated--and in a manner that transforms the evolutionary dynamic. It also plays a critical role in ecology, supporting ecosystem engineering and influencing the flow of energy and nutrients through ecosystems. Despite this, niche construction has been given short shrift in theoretical biology, in part because it cannot be fully understood within the framework of standard evolutionary theory. Wedding evolution and ecology, this book extends evolutionary theory by formally including niche construction and ecological inheritance as additional evolutionary processes. The authors support their historic move with empirical data, theoretical population genetics, and conceptual models. They also describe new research methods capable of testing the theory. They demonstrate how their theory can resolve long-standing problems in ecology, particularly by advancing the sorely needed synthesis of ecology and evolution, and how it offers an evolutionary basis for the human sciences. Already hailed as a pioneering work by some of the world's most influential biologists, this is a rare, potentially field-changing contribution to the biological sciences.
It is our utmost pleasure to launch the Journal of Systems Chemistry. What systems chemistry exactly is will be known in a
few years from now when one is able to sketch the scope and vision of the field also based on upcoming contributions to our
journal. How systems chemistry came up is more easy to tell. In this editorial we therefore focus predominantly on how the
term "Systems Chemistry" came into being and how its scope evolved over recent years. It is perhaps not surprising that the
term emerged within the communities researching the origin and synthesis of life, as this is probably the most challenging
question in Systems Chemistry. The field however encompasses much more than just this subject - it offers a plethora of new
opportunities for the discovery of life-like dynamic signatures in all areas in chemistry.
It is widely accepted that autocatalysis constitutes a crucial facet of effective replication and evolution (e.g., in Eigen's hypercycle model). Other models for early evolution (e.g., by Dyson, Gánti, Varela, and Kauffman) invoke catalytic networks, where cross-catalysis is more apparent. A key question is how the balance between auto- (self-) and cross- (mutual) catalysis shapes the behavior of model evolving systems. This is investigated using the graded autocatalysis replication domain (GARD) model, previously shown to capture essential features of reproduction, mutation, and evolution in compositional molecular assemblies. We have performed numerical simulations of an ensemble of GARD networks, each with a different set of lognormally distributed catalytic values. We asked what is the influence of the catalytic content of such networks on beneficial evolution. Importantly, a clear trend was observed, wherein only networks with high mutual catalysis propensity (p(mc)) allowed for an augmented diversity of composomes, quasi-stationary compositions that exhibit high replication fidelity. We have reexamined a recent analysis that showed meager selection in a single GARD instance and for a few nonstationary target compositions. In contrast, when we focused here on compotypes (clusters of composomes) as targets for selection in populations of compositional assemblies, appreciable selection response was observed for a large portion of the networks simulated. Further, stronger selection response was seen for high p(mc) values. Our simulations thus demonstrate that GARD can help analyze important facets of evolving systems, and indicate that excess mutual catalysis over self-catalysis is likely to be important for the emergence of molecular systems capable of evolutionlike behavior.
Genetic inheritance in modern cells is due to template-directed replication of nucleic acids. However, the difficulty of prebiotic synthesis of long information-carrying polymers like RNA raises the question of whether some other form of heredity is possible without polymers. As an alternative, the lipid world theory has been proposed, which considers non-covalent assemblies of lipids, such as micelles and vesicles. Assemblies store information in the form of a non-random molecular composition, and this information is passed on when the assemblies divide, i.e. the assemblies show compositional inheritance. Here, we vary several important assumptions of previous lipid world models and show that compositional inheritance is relevant more generally than the context in which it was originally proposed. Our models assume that interaction occurs between nearest neighbour molecules only, and account for spatial segregation of molecules of different types within the assembly. We also draw a distinction between a self-assembly model, in which the composition is determined by mutually favourable interaction energies between the molecules, and a catalytic model, in which the composition is determined by mutually favourable catalysis. We show that compositional inheritance occurs in both models, although the self-assembly case seems more relevant if the molecules are simple lipids. In the case where the assemblies are composed of just two types of molecules, there is a strong analogy with the classic two-allele Moran model from population genetics. This highlights the parallel between compositional inheritance and genetic inheritance.
This addresswas presented by Freeman J. Dyson as the NishinaMemorial
Lecture at the University of Tokyo, on October 17, 1984, and at Yukawa
Institute for Theoretical Physics, on October 23, 1984.
This article investigates the possibility that the emergence of reflexively autocatalytic sets of peptides and polypeptides may be an essentially inevitable collective property of any sufficiently complex set of polypeptides. The central idea is based on the connectivity properties of random directed graphs. In the set of amino acid monomer and polymer species up to some maximum length, M, the number of possible polypeptides is large, but, for specifiable "legitimate" end condensation, cleavage and transpeptidation exchange reactions, the number of potential reactions by which the possible polypeptides can interconvert is very much larger. A directed graph in which arrows from smaller fragments to larger condensation products depict potential synthesis reactions, while arrows from the larger peptide to the smaller fragments depict the reverse cleavage reactions, comprises the reaction graph for such a system. Polypeptide protoenzymes are able to catalyze such reactions. The distribution of catalytic capacities in peptide space is a fundamental problem in its own right, and in its bearing on the existence of autocatalytic sets of proteins. Using an initial idealized hypothesis that an arbitrary polypeptide has a fixed a priori probability of catalyzing any arbitrary legitimate reaction to assign to each polypeptide those reactions, if any, which it catalyzes, the probability that the set of polypeptides up to length M contains a reflexively autocatalytic subset can be calculated and is a percolation problem on such reaction graphs. Because, as M increases, the ratio of reactions among the possible polypeptides to polypeptides rises rapidly, the existence of such autocatalytic subsets is assured for any fixed probability of catalysis. The main conclusions of this analysis appear independent of the idealizations of the initial model, introduce a novel kind of parallel selection for peptides catalyzing connected sequences of reactions, depend upon a new kind of minimal critical complexity whose properties are definable, and suggest that the emergence of self replicating systems may be a self organizing collective property of critically complex protein systems in prebiotic evolution. Similar principles may apply to the emergence of a primitive connected metabolism. Recombinant DNA procedures, cloning random DNA coding sequences into expression vectors, afford a direct avenue to test the distribution of catalytic capacities in peptide space, may provide a new means to select or screen for peptides with useful properties, and may ultimately lead toward the actual construction of autocatalytic peptide sets.
A generalized phenomenological model is presented for stereospecific recognition between biological receptors and their ligands. We ask what is the distribution of binding constants psi(K) between an arbitrary ligand and members of a large receptor repertoire, such as immunoglobulins or olfactory receptors. For binding surfaces with B potential subsite and S different types of subsite configurations, the number of successful elementary interactions obeys a binomial distribution. The discrete probability function psi(K) is then derived with assumptions on alpha, the free energy contribution per elementary interaction. The functional form of psi(K) may be universal, although the parameter values could vary for different ligand types. An estimate of the parameter values of psi(K) for iodovanillin, an analog of odorants and immunological haptens, is obtained by equilibrium dialysis experiments with nonimmune antibodies. Based on a simple relationship, predicted by the model, between the size of a receptor repertoire and its average maximal affinity toward an arbitrary ligand, the size of the olfactory receptor repertoire (Nolf) is calculated as 300-1000, in very good agreement with recent molecular biological studies. A very similar estimate, Nolf = 500, is independently derived by relating a theoretical distribution of maxima for psi(K) with published human olfactory threshold variations. The present model also has implications to the question of olfactory coding and to the analysis of specific anosmias, genetic deficits in perceiving particular odorants. More generally, the proposed model provides a better understanding of ligand specificity in biological receptors and could help in understanding their evolution.
Mutually catalytic sets of simple organic molecules have been suggested to be capable of self-replication and rudimentary chemical evolution. Previous models for the behavior of such sets have analyzed the global properties of short biopolymer ensembles by using graph theory and a mean field approach. In parallel, experimental studies with the autocatalytic formation of amphiphilic assemblies (e.g., lipid vesicles or micelles) demonstrated self-replication properties resembling those of living cells. Combining these approaches, we analyze here the kinetic behavior of small heterogeneous assemblies of spontaneously aggregating molecules, of the type that could form readily under prebiotic conditions. A statistical formalism for mutual rate enhancement is used to numerically simulate the detailed chemical kinetics within such assemblies. We demonstrate that a straightforward set of assumptions about kinetically enhanced recruitment of simple amphiphilic molecules, as well as about the spontaneous growth and splitting of assemblies, results in a complex population behavior. The assemblies manifest a significant degree of homeostasis, resembling the previously predicted quasi-stationary states of biopolymer ensembles (Dyson, F. J. (1982) J. Mol. Evol. 18, 344-350). Such emergent catalysis-driven, compositionally biased entities may be viewed as having rudimentary "compositional genomes." Our analysis addresses the question of how mutually catalytic metabolic networks, devoid of sequence-based biopolymers, could exhibit transfer of chemical information and might undergo selection and evolution. This computed behavior may constitute a demonstration of natural selection in populations of molecules without genetic apparatus, suggesting a pathway from random molecular assemblies to a minimal protocell.
A Graded Autocatalysis Replication Domain (GARD) model is proposed, which provides a rigorous kinetic analysis of simple chemical sets that manifest mutual catalysis. It is shown that catalytic closure can sustain self replication up to a critical dilution rate, lambda c, related to the graded extent of mutual catalysis. We explore the behavior of vesicles containing GARD species whose mutual catalysis is governed by a previously published statistical distribution. In the population thus generated, some GARD vesicles display a significantly higher replication efficiency than most others. GARD thus represents a simple model for primordial chemical selection of mutually catalytic sets.
Non-covalent compositional assemblies, made of monomeric mutually catalytic molecules, constitute an alternative to alphabet-based informational biopolymers as a mechanism of primordial inheritance. Such assemblies appear implicitly in many "Metabolism First" origin of life scenarios, and more explicitly in the Graded Autocatalysis Replication Domain (GARD) model [Segréet al. (2000). Proc. Natl Acad. Sci. U.S.A.97, 4112-4117]. In the present work, we provide a detailed analysis of the quantitative molecular roots of such behavior. It is demonstrated that the fidelity of reproduction provided by a newly defined heritability measure eta(*)(s), strongly depends on the values of molecular recognition parameters and on assembly size. We find that if the catalytic rate acceleration coefficients are distributed normally, transfer of compositional information becomes impossible, due to frequent "compositional error catastrophes". In contrast, if the catalytic acceleration rates obey a lognormal distribution, as actually predicted by a statistical formalism for molecular repertoires, high reproduction fidelity is obtained. There is also a clear dependence on assembly size N, whereby maximal eta is seen in a narrow range around N approximately 3.5 N(G)/lambda, where N(G)is the size of the primordial molecular repertoire and lambda is a molecular interaction statistical parameter. Such relationships help define the physicochemical conditions that could underlie the early steps in pre-biotic evolution.
There are more uses for a screwdriver than you can calculate
- S Kauffman
Kauffman, S., 2011. There are more uses for a screwdriver than you can calculate. URL:
http://www.wbur.org/npr/135113346/there-are-more-uses-for-a-screwdriver-thanyou-can-calculate.
The Latest on the Best, Essays on Evolution and Optimality
- Maynard Smith
Maynard Smith, J., 1987. How to model evolution. In: Dupré, J. (Ed.), The Latest on
the Best, Essays on Evolution and Optimality.. MIT Press, Cambridge,
pp. 119-131.
- V Vasas
- C Fernando
- M Santos
- S Kauffman
- E Szathmáry
Vasas, V., Fernando, C., Santos, M., Kauffman, S., Szathmáry, E., 2012. Evolution
before genes. Biol. Direct 7, 1.
The principles of life
- T Gánti
Gánti, T., 2003. The principles of life. Oxford Univ. Press, Oxford.