arXiv subjects

Eugene V. Koonin

Publications and source records attributed to Eugene V. Koonin.

At least 19 recordsLinked to original sources

arXiv2026

The Emergence of Life in the Light of Evolution

The origin of life is often framed primarily as a chemical problem, yet life s defining feature is evolution. Advances in geochemistry, prebiotic chemistry and molecular biology have suggested diverse scenarios for the emergence of genomes, metabolism and cellular compartments on the early Earth, but most of these models ignore the relevance of a population genetics perspective. Here, we argue that origin of life research must expand from asking simply how life began to exploring how it evolved from pre biological systems. Synthesizing evidence from comparative genomics, phylogenetics, biochemistry, and geoscience, we emphasize that the last universal common ancestor (LUCA) was already a complex, ecologically adapted population of cells far removed from the starting point of life, implying a deep, pre LUCA evolutionary history. We highlight how population genetics, ecology, and synthetic biology can constrain origin of life scenarios by making explicit the roles of selection, drift, mutation, horizontal gene transfer, parasites and compartmentalization in shaping early communities. Finally, we outline an evolutionary research agenda spanning proto metabolic autocatalytic networks, protocells, and the emergence of translation and the transition to DNA genomes, such that qualitative models can be formalized through evolution driven hypotheses testable with theory and laboratory experiments, including those with synthetic cells.

q-bio.PE↗

arXiv2026

A generative model for bipartite gene-sharing networks

Gene-sharing networks provide a powerful framework to study the evolution of viruses and mobile genetic elements. These bipartite networks, which link genes to the genomes that contain them, exhibit characteristic degree distributions: a scale-free distribution for genes and an exponential-like decay for genomes. Here, we propose a mechanistic model that explains these patterns through fundamental evolutionary processes including horizontal gene transfer, capture of new genes, emergence of new genomes, and gene loss. Using a mean-field approximation, we derive analytical expressions for the asymptotic gene and genome degree distributions, recapitulating a power-law distribution for genes and an exponential distribution for genomes. Numerical simulations validate these predictions and yield parameter values that closely fit empirical data from dsDNA viruses, RNA viruses, and prokaryotic pangenomes. This simple model with only two parameters provides a generative framework for bipartite gene-sharing networks, offering qualitative and quantitative insights into the main evolutionary forces driving genome plasticity. Setting the gene loss rate to zero, the gene and genome degree distributions of the model closely fit the empirically observed distributions. Thus, evolution of viruses appears to be dominated by gene gain, in agreement with the results of independent reconstructions of viral evolution.

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arXiv2026

The selfish ribosome

The ribosome is responsible for protein synthesis in all cells, and is the largest energy consumer in the cell. We propose that the ribosome originated as a mutualistic symbiont of an RNA-dependent RNA polymerase ribozyme, supplying peptides that enhanced replication. As life transitioned from the RNA to the RNA-protein world, autonomous replicators became irreversibly addicted to the ribosome for producing replication proteins. Subsequent evolution is construed as a ribosomal takeover, whereby the ribosome evolved to consume most of the resources of the cell, while other cellular componentry ensured the propagation of the ribosome. Under this perspective, the ribosome is the ultimate biological selfish element.

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arXiv2021

Thermodynamics of Evolution and the Origin of Life

We outline a phenomenological theory of evolution and origin of life by combining the formalism of classical thermodynamics with a statistical description of learning. The maximum entropy principle constrained by the requirement for minimization of the loss function is employed to derive a canonical ensemble of organisms (population), the corresponding partition function (macroscopic counterpart of fitness) and free energy (macroscopic counterpart of additive fitness). We further define the biological counterparts of temperature (biological temperature) as the measure of stochasticity of the evolutionary process and of chemical potential (evolutionary potential) as the amount of evolutionary work required to add a new trainable variable (such as an additional gene) to the evolving system. We then develop a phenomenological approach to the description of evolution, which involves modeling the grand potential as a function of the biological temperature and evolutionary potential. We demonstrate how this phenomenological approach can be used to study the "ideal mutation" model of evolution and its generalizations. Finally, we show that, within this thermodynamics framework, major transitions in evolution, such as the transition from an ensemble of molecules to an ensemble of organisms, that is, the origin of life, can be modeled as a special case of bona fide physical phase transitions that are associated with the emergence of a new type of grand canonical ensemble and the corresponding new level of description

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arXiv2021

Towards a Theory of Evolution as Multilevel Learning

We apply the theory of learning to physically renormalizable systems in an attempt to develop a theory of biological evolution, including the origin of life, as multilevel learning. We formulate seven fundamental principles of evolution that appear to be necessary and sufficient to render a universe observable and show that they entail the major features of biological evolution, including replication and natural selection. These principles also follow naturally from the theory of learning. We formulate the theory of evolution using the mathematical framework of neural networks, which provides for detailed analysis of evolutionary phenomena. To demonstrate the potential of the proposed theoretical framework, we derive a generalized version of the Central Dogma of molecular biology by analyzing the flow of information during learning (back-propagation) and predicting (forward-propagation) the environment by evolving organisms. The more complex evolutionary phenomena, such as major transitions in evolution, in particular, the origin of life, have to be analyzed in the thermodynamic limit, which is described in detail in the accompanying paper.

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arXiv2021

Alternating active-dormitive strategy enables overtaking by disadvantaged prey through Parrondo's paradox

Dormancy is a costly adaptive strategy that is widespread among living organisms inhabiting diverse environments. We explore mathematical models of predator-prey systems, in order to assess the impact of prey dormancy on the competition between two types of prey, a perennially active (PA) and capable of entering dormancy (dormitive). Both the active form and the dormant form of the dormitive prey are individually at a disadvantage compared to the PA prey and would go extinct due to their low growth rate, energy waste on the production of dormant prey, and inability of the latter to grow autonomously. However, the dormitive prey can paradoxically outcompete the PA prey with superior traits and even cause its extinction by alternating between the two losing strategies. This outcome recapitulates the game-theoretic Parrondo's paradox, where two losing strategies combine to achieve a winning outcome. We observed higher fitness of the dormitive prey in rich environments because a large predator population in a rich environment cannot be supported by the prey without adopting an evasive strategy, that is, dormancy. In such environments, populations experience large-scale fluctuations, which can be survived by dormitive but not by PA prey. Dormancy of the prey appears to be a natural evolutionary response to self-destructive over-predation that stabilizes evolving predator-prey systems through Parrondo's paradox.

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arXiv2020

Punctuated equilibrium as the default mode of evolution of large populations on fitness landscapes dominated by saddle points in the weak-mutation limit

Punctuated equilibrium is a mode of evolution in which phenetic change occurs in rapid bursts that are separated by much longer intervals of stasis during which mutations accumulate but no major phenotypic change occurs. Punctuated equilibrium has been originally proposed within the framework of paleobiology, to explain the lack of transitional forms that is typical of the fossil record. Theoretically, punctuated equilibrium has been linked to self-organized criticality (SOC), a model in which the size of avalanches in an evolving system is power-law distributed, resulting in increasing rarity of major events. We show here that, under the weak-mutation limit, a large population would spend most of the time in stasis in the vicinity of saddle points in the fitness landscape. The periods of stasis are punctuated by fast transitions, in lnNe time (Ne, effective population size), when a new beneficial mutation is fixed in the evolving population, which moves to a different saddle, or on much rarer occasions, from a saddle to a local peak. Thus, punctuated equilibrium is the default mode of evolution under a simple model that does not involve SOC or other special conditions.

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arXiv2019

The sounds of science: a symphony for many instruments and voices

This paper is a celebration of the frontiers of science. Goodenough, the maestro who transformed energy usage and technology through the invention of the lithium ion battery, opens the programme, reflecting on the ultimate limits of battery technology. This applied theme continues through the subsequent pieces on energy related topics (the sodium ion battery and artificial fuels, by Mansson) and the ultimate challenge for 3 dimensional printing the eventual production of life, by Atala. A passage by Alexander follows, reflecting on a related issue: How might an artificially produced human being behave? Next comes a consideration of consiousness and free will by Allen and Lidstrom. Further voices and new instruments enter as Bowen, Mauranyapin and Madsen discuss whether dynamical processes of single molecules might be observed in their native state. The exploitation of chaos in science and technology, applications of Bose Einstein condensates and a consideration of the significance of entropy follow in pieces by Reichl, Rasel and Allen, respectively. Katsnelson and Koonin then discuss the potential generalisation of thermodynamic concepts in the context of biological evolution. Entering with the music of the cosmos, Yasskin discusses whether we might be able to observe torsion in the geometry of the universe. The crescendo comes with the crisis of singularities, their nature and whether they can be resolved through quantum effects, in the composition of Coley. The climax is Krenn, Melvin and Zeilinger consideration of how computer code can be autonomously surprising and creative. In a harmonious counterpoint, Yampolskiy concludes that such code is not yet able to take responsibility for coauthoring a paper.

physics.pop-ph↗

arXiv2019

On the feasibility of saltational evolution

Is evolution always gradual or can it make leaps? We examine a mathematical model of an evolutionary process on a fitness landscape and obtain analytic solutions for the probability of multi-mutation leaps, that is, several mutations occurring simultaneously, within a single generation in one genome, and being fixed all together in the evolving population. The results indicate that, for typical, empirically observed combinations of the parameters of the evolutionary process, namely, effective population size, mutation rate, and distribution of selection coefficients of mutations, the probability of a multi-mutation leap is low, and accordingly, the contribution of such leaps is minor at best. However, we show that, taking sign epistasis into account, leaps could become an important factor of evolution in cases of substantially elevated mutation rates, such as stress-induced mutagenesis in microbes. We hypothesize that stress-induced mutagenesis is an evolvable adaptive strategy.

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arXiv2018

Physical foundations of biological complexity

Biological systems reach hierarchical complexity that has no counterpart outside the realm of biology. Undoubtedly, biological entities obey the fundamental physical laws. Can today's physics provide an explanatory framework for understanding the evolution of biological complexity? We argue here that the physical foundation for understanding the origin and evolution of complexity can be envisaged at the interface between the theory of frustrated states resulting in pattern formation in glass-like media and the theory of self-organized criticality (SOC). On the one hand, SOC has been shown to emerge in spin glass systems of high dimensionality. On the other hand, SOC is often viewed as the most appropriate physical description of evolutionary transitions in biology. We unify these two faces of SOC by showing that emergence of complex features in biological evolution typically if not always is triggered by frustration that is caused by competing interactions at different organizational levels. Competing interactions and frustrated states permeate biology at all organizational levels and are tightly linked to the ubiquitous competition for limiting resources. This perspective extends from the comparatively simple phenomena occurring in glasses to large-scale events of biological evolution, such as major evolutionary transitions. We therefore submit that frustration caused by competing interactions in multidimensional systems is the general driving force behind the emergence of complexity, within and beyond the domain of biology.

cond-mat.stat-mech↗

arXiv2018

Towards physical principles of biological evolution

Biological systems reach organizational complexity that far exceeds the complexity of any known inanimate objects. Biological entities undoubtedly obey the laws of quantum physics and statistical mechanics. However, is modern physics sufficient to adequately describe, model and explain the evolution of biological complexity? Detailed parallels have been drawn between statistical thermodynamics and the population-genetic theory of biological evolution. Based on these parallels, we outline new perspectives on biological innovation and major transitions in evolution, and introduce a biological equivalent of thermodynamic potential that reflects the innovation propensity of an evolving population. Deep analogies have been suggested to also exist between the properties of biological entities and processes, and those of frustrated states in physics, such as glasses. We extend such analogies by examining frustration-type phenomena, such as conflicts between different levels of selection, in biological evolution. We further address evolution in multidimensional fitness landscapes from the point of view of percolation theory and suggest that percolation at level above the critical threshold dictates the tree-like evolution of complex organisms. Taken together, these multiple connections between fundamental processes in physics and biology imply that construction of a meaningful physical theory of biological evolution might not be a futile effort.

q-bio.OT↗

arXiv2012

Universal pacemaker of genome evolution

Molecular clock (MC) is a central concept of molecular evolution according to which each gene evolves at a characteristic, near constant rate. Numerous evolutionary studies have demonstrated the validity of MC but also have shown that MC is substantially overdispersed, i.e. lineage-specific deviations of the evolutionary rate of the given gene from the clock greatly exceed the expectation from the sampling error. A fundamental observation of comparative genomics that appears to complement the MC is that the distribution of evolution rates across orthologous genes in pairs of related genomes remains virtually unchanged throughout the evolution of life, from bacteria to mammals. The conservation of this distribution implies that the relative evolution rates of all genes remain nearly constant, or in other words, that evolutionary rates of different genes are strongly correlated within each evolving genome. We hypothesized that this correlation is not a simple consequence of MC but could be better explained by a model we dubbed Universal PaceMaker (UPM) of genome evolution. The UPM model posits that the rate of evolution changes synchronously across genome-wide sets of genes in all evolving lineages. We sought to differentiate between the MC and UPM models by fitting thousands of phylogenetic trees for bacterial and archaeal genes to supertrees that reflect the dominant trend of vertical descent in the evolution of archaea and bacteria and that were constrained according to the two models. The goodness of fit for the UPM model was better than the fit for the MC model, with overwhelming statistical significance. These results reveal a universal pacemaker of genome evolution that could have been in operation throughout the history of life.

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arXiv2011

Are there laws of genome evolution?

Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law-like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics, such as the birth-death-innovation model. These models do not explicitly incorporate selection, therefore the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. Although a complete physical theory of evolutionary biology is inconceivable, the universals of genome evolution might qualify as 'laws of evolutionary genomics' in the same sense 'law' is understood in modern physics.

q-bio.PE↗

arXiv2011

Predictability of evolutionary trajectories in fitness landscapes

Experimental studies on enzyme evolution show that only a small fraction of all possible mutation trajectories are accessible to evolution. However, these experiments deal with individual enzymes and explore a tiny part of the fitness landscape. We report an exhaustive analysis of fitness landscapes constructed with an off-lattice model of protein folding where fitness is equated with robustness to misfolding. This model mimics the essential features of the interactions between amino acids, is consistent with the key paradigms of protein folding and reproduces the universal distribution of evolutionary rates among orthologous proteins. We introduce mean path divergence as a quantitative measure of the degree to which the starting and ending points determine the path of evolution in fitness landscapes. Global measures of landscape roughness are good predictors of path divergence in all studied landscapes: the mean path divergence is greater in smooth landscapes than in rough ones. The model-derived and experimental landscapes are significantly smoother than random landscapes and resemble additive landscapes perturbed with moderate amounts of noise; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. We suggest that smoothness and the substantial deficit of peaks in the fitness landscapes of protein evolution are fundamental consequences of the physics of protein folding.

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arXiv2009

Exceptional error minimization in putative primordial genetic codes

We investigated the error-minimization properties of putative primordial codes that consisted of 16 supercodons, with the third base being completely redundant, using a previously derived cost function and the error minimization percentage as the measure of a code's robustness to mistranslation. It is shown that, when the 16-supercodon table is populated with 10 putative primordial amino acids, inferred from the results of abiotic synthesis experiments and other evidence independent of the code evolution, and with minimal assumptions used to assign the remaining supercodons, the resulting 2-letter codes are nearly optimal in terms of the error minimization level. The results of the computational experiments with putative primordial genetic codes that contained only two meaningful letters in all codons and encoded 10 to 16 amino acids indicate that such codes are likely to have been nearly optimal with respect to the minimization of translation errors. This near-optimality could be the outcome of extensive early selection during the co-evolution of the code with the primordial, error-prone translation system, or a result of a unique, accidental event. Under this hypothesis, the subsequent expansion of the code resulted in a decrease of the error minimization level that became sustainable owing to the evolution of a high-fidelity translation system.

q-bio.GN↗

arXiv2008

Origin and evolution of the genetic code: The universal enigma

The genetic code is nearly universal, and the arrangement of the codons in the standard codon table is highly non-random. The three main concepts on origin and evolution of the code are the stereochemical theory; the coevolution theory; and the error minimization theory. These theories are not mutually exclusive and are also compatible with the frozen accident hypothesis. Mathematical analysis of the structure and possible evolutionary trajectories of the code shows that it is highly robust to translational error but there is a huge number of more robust codes, so that the standard code potentially could evolve from a random code via a short sequence of codon series reassignments. Thus, much of the evolution that led to the standard code can be interpreted as a combination of frozen accident with selection for translational error minimization although contributions from coevolution of the code with metabolic pathways and/or weak affinities between amino acids and nucleotide triplets cannot be ruled out. However, such scenarios for the code evolution are based on formal schemes whose relevance to the actual primordial evolution is uncertain, so much caution in interpretation is necessary. A real understanding of the code's origin and evolution is likely to be attainable only in conjunction with a credible scenario for the evolution of the coding principle itself and the translation system.

q-bio.GN↗

arXiv2007

The cosmological model of eternal inflation and the transition from chance to biological evolution in the history of life: The possibility of chance emergence of the replication and translation systems, and the protein superfolds

Evolution of life on earth was governed, primarily, by natural selection, with major contribution of other evolutionary processes, such as neutral variation, exaptation, and gene duplication. However, for biological evolution to take off, a certain minimal degree of complexity is required such that a replicating genome encodes means for its own replication with sufficient rate and fidelity. In all existing life forms, this is achieved by dedicated proteins, polymerases (replicases), that are produced by the elaborate translation system. However, evolution of the coupled system of replication and translation does not appear possible without pre-existing efficient replication; hence a chicken-egg type paradox. I argue that the many-worlds-in-one version of the cosmological model of eternal inflation implies that emergence of replication and translation, as well as the major protein folds, by chance alone, as opposed to biological evolution, is a realistic possibility and could provide for the onset of biological evolution. Hence an RNA world, as it is currently conceived, might have never existed although catalytic activities of RNA were, probably, critical for the onset of biological evolution and its early stages.

q-bio.PE↗

arXiv2006

Mathematical modeling of tumor therapy with oncolytic viruses: Effects of parametric heterogeneity on cell dynamics

One of the mechanisms that ensure cancer robustness is tumor heterogeneity, and its effects on tumor cells dynamics have to be taken into account when studying cancer progression. There is no unifying theoretical framework in mathematical modeling of carcinogenesis that would account for parametric heterogeneity. Here we formulate a modeling approach that naturally takes stock of inherent cancer cell heterogeneity and illustrate it with a model of interaction between a tumor and an oncolytic virus. We show that several phenomena that are absent in homogeneous models, such as cancer recurrence, tumor dormancy, an others, appear in heterogeneous setting. We also demonstrate that, within the applied modeling framework, to overcome the adverse effect of tumor cell heterogeneity on cancer progression, a heterogeneous population of an oncolytic virus must be used. Heterogeneity in parameters of the model, such as tumor cell susceptibility to virus infection and virus replication rate, can lead to complex, time-dependent behaviors of the tumor. Thus, irregular, quasi-chaotic behavior of the tumor-virus system can be caused not only by random perturbations but also by the heterogeneity of the tumor and the virus. The modeling approach described here reveals the importance of tumor cell and virus heterogeneity for the outcome of cancer therapy. It should be straightforward to apply these techniques to mathematical modeling of other types of anticancer therapy.

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