Stages of emerging life--five principles of early organization

Principles of Molecular Evolution: Concepts from Non-equilibrium Thermodynamics for the Multilevel Theory of Learning

We present a non-equilibrium thermodynamics approach to the multilevel theory of learning for the study of molecular evolution. This approach allows us to study the explicit time dependence of molecular evolutionary processes and their impact on entropy production. Interpreting the mathematical expressions, we can show that two main contributions affect entropy production of molecular evolution processes which can be identified as mutation and gene transfer effects. Accordingly, our results show that the optimal adaptation of organisms to external conditions in the context of evolutionary processes is driven by principles of minimum entropy production. Such results can also be interpreted as the basis of some previous postulates of the theory of learning. Although our macroscopic approach requires certain simplifications, it allows us to interpret molecular evolutionary processes using thermodynamic descriptions with reference to well-known biological processes.

Understanding the Role of Layered Minerals in the Emergence and Preservation of Proto-Proteins and Detection of Traces of Early Life

ConspectusThe origin of life remains one of the most profound mysteries in science. Over millennia, theories have evolved, yet the question persists: How did life emerge from inanimate matter? At its core, the study of life's origin offers insights into our place in the universe and the nature of life itself. By delving into the chemical and geological processes that led to life's emergence, scientists gain a deeper understanding of the fundamental principles that govern living systems. This knowledge not only expands our scientific understanding but also has profound implications for fields ranging from astrobiology to synthetic biology.This research employs a multidisciplinary approach, combining a diverse array of techniques, from space missions to wet laboratory experiments to theoretical modeling. Investigations into the formation of the first proto-biomolecules are tailored to explore both the complex molecular processes that underpin life and the geological contexts in which these processes may have occurred. While laboratory experiments are aimed at mimicking the processes of early planets, not every process and sample is attainable. To this end, we demonstrate the use of molecular modeling techniques to complement experimental efforts and extraterrestrial missions. The simulations enable researchers to test hypotheses and explore scenarios that are difficult or impossible to replicate in the laboratory, bridging gaps in our understanding of prebiotic processes across vast time and space scales.Minerals, particularly layered structures like clays and hydrotalcites, play diverse and pivotal roles in the origin of life. They concentrate organic species, catalyze polymerization reactions (such as peptide formation), and provide protective environments for the molecules. Minerals have also been suggested to have acted as primitive genetic materials. Nevertheless, they may lack the ability for long-term information replication. Instead, we suggest that minerals may act as transcribers of information encoded in environmental cyclic phenomena, such as tidal or seasonal changes. We argue that extensive protection of the produced polymer will immobilize it, making it inactive for any further function. Therefore, in order to generate a functional polymer, it is essential that it remains mobile and chemically active. Furthermore, we suggest a route to the identification of pseudobiosignatures, a polymer that was polymerized on the same mineral surface and consequently retained through overprotection.This Account presents a comprehensive evaluation of the current understanding of the role of layered mineral surfaces on life's origin and biosignature preservation. It highlights the complexity of mineral-organic interactions and proposes pathways for proto-biomolecule emergence and methods for identifying and interpreting potential biosignatures. Ultimately, the quest to uncover the origin of life continues to drive scientific exploration and innovation, offering profound insights into the fundamental nature of existence and our place in the universe.

Limits on the evolutionary rates of biological traits

This paper focuses on the maximum speed at which biological evolution can occur. I derive inequalities that limit the rate of evolutionary processes driven by natural selection, mutations, or genetic drift. These rate limits link the variability in a population to evolutionary rates. In particular, high variances in the fitness of a population and of a quantitative trait allow for fast changes in the trait's average. In contrast, low variability makes a trait less susceptible to random changes due to genetic drift. The results in this article generalize Fisher's fundamental theorem of natural selection to dynamics that allow for mutations and genetic drift, via trade-off relations that constrain the evolutionary rates of arbitrary traits. The rate limits can be used to probe questions in various evolutionary biology and ecology settings. They apply, for instance, to trait dynamics within or across species or to the evolution of bacteria strains. They apply to any quantitative trait, e.g., from species' weights to the lengths of DNA strands.

Mathematical Models of Chiral Symmetry-breaking – A Review of General Theories, and Adiabatic Approximations of the APED System

We review the literature surrounding chiral symmetry-breaking in chemical systems, with a focus on understanding the mathematical models underlying these chemical processes. We comment in particular on the toy model of Sandars, Viedma’s crystal grinding systems and the APED model. We include a few new results based on asymptotic analysis of the APED system.

The Resolved Mutual Information Function as a Structural Fingerprint of Biomolecular Sequences for Interpretable Machine Learning Classifiers

In the present article we propose the application of variants of the mutual information function as characteristic fingerprints of biomolecular sequences for classification analysis. In particular, we consider the resolved mutual information functions based on Shannon-, Rényi-, and Tsallis-entropy. In combination with interpretable machine learning classifier models based on generalized learning vector quantization, a powerful methodology for sequence classification is achieved which allows substantial knowledge extraction in addition to the high classification ability due to the model-inherent robustness. Any potential (slightly) inferior performance of the used classifier is compensated by the additional knowledge provided by interpretable models. This knowledge may assist the user in the analysis and understanding of the used data and considered task. After theoretical justification of the concepts, we demonstrate the approach for various example data sets covering different areas in biomolecular sequence analysis.

Mutation Rates, Mutation Frequencies, and Proofreading-Repair Activities in RNA Virus Genetics

The error rate displayed during template copying to produce viral RNA progeny is a biologically relevant parameter of the replication complexes of viruses. It has consequences for virus-host interactions, and it represents the first step in the diversification of viruses in nature. Measurements during infections and with purified viral polymerases indicate that mutation rates for RNA viruses are in the range of 10-3 to 10-6 copying errors per nucleotide incorporated into the nascent RNA product. Although viruses are thought to exploit high error rates for adaptation to changing environments, some of them possess misincorporation correcting activities. One of them is a proofreading-repair 3' to 5' exonuclease present in coronaviruses that may decrease the error rate during replication. Here we review experimental evidence and models of information maintenance that explain why elevated mutation rates have been preserved during the evolution of RNA (and some DNA) viruses. The models also offer an interpretation of why error correction mechanisms have evolved to maintain the stability of genetic information carried out by large viral RNA genomes such as the coronaviruses.

Population Disequilibrium as Promoter of Adaptive Explorations in Hepatitis C Virus

Replication of RNA viruses is characterized by exploration of sequence space which facilitates their adaptation to changing environments. It is generally accepted that such exploration takes place mainly in response to positive selection, and that further diversification is boosted by modifications of virus population size, particularly bottleneck events. Our recent results with hepatitis C virus (HCV) have shown that the expansion in sequence space of a viral clone continues despite prolonged replication in a stable cell culture environment. Diagnosis of the expansion was based on the quantification of diversity indices, the occurrence of intra-population mutational waves (variations in mutant frequencies), and greater individual residue variations in mutant spectra than those anticipated from sequence alignments in data banks. In the present report, we review our previous results, and show additionally that mutational waves in amplicons from the NS5A-NS5B-coding region are equally prominent during HCV passage in the absence or presence of the mutagenic nucleotide analogues favipiravir or ribavirin. In addition, by extending our previous analysis to amplicons of the NS3- and NS5A-coding region, we provide further evidence of the incongruence between amino acid conservation scores in mutant spectra from infected patients and in the Los Alamos National Laboratory HCV data banks. We hypothesize that these observations have as a common origin a permanent state of HCV population disequilibrium even upon extensive viral replication in the absence of external selective constraints or changes in population size. Such a persistent disequilibrium—revealed by the changing composition of the mutant spectrum—may facilitate finding alternative mutational pathways for HCV antiviral resistance. The possible significance of our model for other genetically variable viruses is discussed.

A model of autowave self-organization as a hierarchy of active media in the biological evolution

Within the framework of the active media concept, we develop a biophysical model of autowave self-organization which is treated as a hierarchy of active media in the evolution of the biosphere. We also propose a mathematical model of the autowave process of speciation in a flow of mutations for the three main taxonometric groups (prokaryotes, unicellular and multicellular eukaryotes) with a naturally determined lower boundary of living matter (the appearance of prokaryotes) and an open upper boundary for the formation of new species. It is shown that the fluctuation-bifurcation description of the evolution for the formation of new taxonometric groups as a trajectory of transformation of small fluctuations into giant ones adequately reflects the process of self-organization during the formation of taxa. The major concepts of biological evolution, conditions of hierarchy formation as a fundamental manifestation of self-organization and complexity in the evolution of biological systems are considered.

On the emergence of cognition: from catalytic closure to neuroglial closure

In an analogous manner as occurred during the development of a connected metabolism that at some point reached characteristics associated with what is called "life"-due mainly to a catalytic closure phenomenon when chemicals started to autocatalyze themselves forming a closed web of chemical reactions-it is here proposed that cognition and consciousness (or features associated with them) arose as a consequence of another type of closure within the nervous system, the brain especially. Proper brain function requires an efficient web of connections and once certain complexity is attained due to the number and coordinated activities of the brain cell networks, the emergent properties of cognition and consciousness take place. Seeking to identify main features of the nervous system organization for optimal function, it is here proposed that while catalytic closure yielded life, neuroglial closure produced cognition/consciousness.

Physicochemical Foundations of Life that Direct Evolution: Chance and Natural Selection are not Evolutionary Driving Forces

The current framework of evolutionary theory postulates that evolution relies on random mutations generating a diversity of phenotypes on which natural selection acts. This framework was established using a top-down approach as it originated from Darwinism, which is based on observations made of complex multicellular organisms and, then, modified to fit a DNA-centric view. In this article, it is argued that based on a bottom-up approach starting from the physicochemical properties of nucleic and amino acid polymers, we should reject the facts that (i) natural selection plays a dominant role in evolution and (ii) the probability of mutations is independent of the generated phenotype. It is shown that the adaptation of a phenotype to an environment does not correspond to organism fitness, but rather corresponds to maintaining the genome stability and integrity. In a stable environment, the phenotype maintains the stability of its originating genome and both (genome and phenotype) are reproduced identically. In an unstable environment (i.e., corresponding to variations in physicochemical parameters above a physiological range), the phenotype no longer maintains the stability of its originating genome, but instead influences its variations. Indeed, environment- and cellular-dependent physicochemical parameters define the probability of mutations in terms of frequency, nature, and location in a genome. Evolution is non-deterministic because it relies on probabilistic physicochemical rules, and evolution is driven by a bidirectional interplay between genome and phenotype in which the phenotype ensures the stability of its originating genome in a cellular and environmental physicochemical parameter-depending manner.

Detecting life signatures with RNA sequence similarity measures

The RNA World is currently the most plausible hypothesis for explaining the origins of life on Earth. The supporting body of evidence is growing and it comes from multiple areas, including astrobiology, chemistry, biology, mathematics, and, in particular, from computer simulations. Such methods frequently assume the existence of a hypothetical species on Earth, around three billion years ago, with a base sequence probably dissimilar from any in known genomes. However, it is often hard to verify whether or not a hypothetical sequence has the characteristics of biological sequences, and is thus likely to be functional. The primary objective of the presented research was to verify the possibility of building a computational 'life probe' for determining whether a given genetic sequence is biological, and assessing the sensitivity of such probes to the signatures of life present in known biological sequences. We have proposed decision algorithms based on the normalized compression distance (NCD) and Levenshtein distance (LD). We have validated the proposed method in the context of the RNA World hypothesis using short genetic sequences shorter than the error threshold value (i.e., 100 nucleotides). We have demonstrated that both measures can be successfully used to construct life probes that are significantly better than a random decision procedure, while varying from each other when it comes to detailed characteristics. We also observed that fragments of sequences related to replication have better discriminatory power than sequences having other molecular functions. In a broader context, this shows that the signatures of life in short RNA samples can be effectively detected using relatively simple means.

Hidden long evolutionary memory in a model biochemical network

We introduce a minimal model for the evolution of functional protein-interaction networks using a sequence-based mutational algorithm, and apply the model to study neutral drift in networks that yield oscillatory dynamics. Starting with a functional core module, random evolutionary drift increases network complexity even in the absence of specific selective pressures. Surprisingly, we uncover a hidden order in sequence space that gives rise to long-term evolutionary memory, implying strong constraints on network evolution due to the topology of accessible sequence space.

Some mechanistic requirements for major transitions

Major transitions in nature and human society are accompanied by a substantial change towards higher complexity in the core of the evolving system. New features are established, novel hierarchies emerge, new regulatory mechanisms are required and so on. An obvious way to achieve higher complexity is integration of autonomous elements into new organized systems whereby the previously independent units give up their autonomy at least in part. In this contribution, we reconsider the more than 40 years old hypercycle model and analyse it by the tools of stochastic chemical kinetics. An open system is implemented in the form of a flow reactor. The formation of new dynamically organized units through integration of competitors is identified with transcritical bifurcations. In the stochastic model, the fully organized state is quasi-stationary whereas the unorganized state corresponds to a population with natural selection. The stability of the organized state depends strongly on the number of individual subspecies, n, that have to be integrated: two and three classes of individuals, [Formula: see text] and [Formula: see text], readily form quasi-stationary states. The four-membered deterministic dynamical system, [Formula: see text], is stable but in the stochastic approach self-enhancing fluctuations drive it into extinction. In systems with five and more classes of individuals, [Formula: see text], the state of cooperation is unstable and the solutions of the deterministic ODEs exhibit large amplitude oscillations. In the stochastic system self-enhancing fluctuations lead to extinction as observed with [Formula: see text] Interestingly, cooperative systems in nature are commonly two-membered as shown by numerous examples of binary symbiosis. A few cases of symbiosis of three partners, called three-way symbiosis, have been found and were analysed within the past decade. Four-way symbiosis is rather rare but was reported to occur in fungus-growing ants. The model reported here can be used to illustrate the interplay between competition and cooperation whereby we obtain a hint on the role that resources play in major transitions. Abundance of resources seems to be an indispensable prerequisite of radical innovation that apparently needs substantial investments. Economists often claim that scarcity is driving innovation. Our model sheds some light on this apparent contradiction. In a nutshell, the answer is: scarcity drives optimization and increase in efficiency but abundance is required for radical novelty and the development of new features.This article is part of the themed issue 'The major synthetic evolutionary transitions'.

Quasispecies on Fitness Landscapes

Selection-mutation dynamics is studied as adaptation and neutral drift on abstract fitness landscapes. Various models of fitness landscapes are introduced and analyzed with respect to the stationary mutant distributions adopted by populations upon them. The concept of quasispecies is introduced, and the error threshold phenomenon is analyzed. Complex fitness landscapes with large scatter of fitness values are shown to sustain error thresholds. The phenomenological theory of the quasispecies introduced in 1971 by Eigen is compared to approximation-free numerical computations. The concept of strong quasispecies understood as mutant distributions, which are especially stable against changes in mutations rates, is presented. The role of fitness neutral genotypes in quasispecies is discussed.

Evaluation of novel design strategies for developing zinc finger nucleases tools for treating human diseases

Zinc finger nucleases (ZFNs) are associated with cell death and apoptosis by binding at countless undesired locations. This cytotoxicity is associated with the binding ability of engineered zinc finger domains to bind dissimilar DNA sequences with high affinity. In general, binding preferences of transcription factors are associated with significant degenerated diversity and complexity which convolutes the design and engineering of precise DNA binding domains. Evolutionary success of natural zinc finger proteins, however, evinces that nature created specific evolutionary traits and strategies, such as modularity and rank-specific recognition to cope with binding complexity that are critical for creating clinical viable tools to precisely modify the human genome. Our findings indicate preservation of general modularity and significant alteration of the rank-specific binding preferences of the three-finger binding domain of transcription factor SP1 when exchanging amino acids in the 2nd finger.

Phylogeny and evolution of RNA structure

Darwin's conviction that all living beings on Earth are related and the graph of relatedness is tree-shaped has been essentially confirmed by phylogenetic reconstruction first from morphology and later from data obtained by molecular sequencing. Limitations of the phylogenetic tree concept were recognized as more and more sequence information became available. The other path-breaking idea of Darwin, natural selection of fitter variants in populations, is cast into simple mathematical form and extended to mutation-selection dynamics. In this form the theory is directly applicable to RNA evolution in vitro and to virus evolution. Phylogeny and population dynamics of RNA provide complementary insights into evolution and the interplay between the two concepts will be pursued throughout this chapter. The two strategies for understanding evolution are ultimately related through the central paradigm of structural biology: sequence ⇒ structure ⇒ function. We elaborate on the state of the art in modeling both phylogeny and evolution of RNA driven by reproduction and mutation. Thereby the focus will be laid on models for phylogenetic sequence evolution as well as evolution and design of RNA structures with selected examples and notes on simulation methods. In the perspectives an attempt is made to combine molecular structure, population dynamics, and phylogeny in modeling evolution.

Life's Order, Complexity, Organization, and Its Thermodynamic-Holistic Imperatives

In memoriam Jeffrey S. Wicken (1942-2002)-the evolutionarily minded biochemist, who in the 1970/80s strived for a synthesis of biological and physical theories to fathom the tentative origins of life. Several integrative concepts are worth remembering from Wicken's legacy. (i) Connecting life's origins and complex organization to a preexisting physical world demands a thermodynamically sound transition. (ii) Energetic 'charging' of the prebiosphere must precede the emergence of biological organization. (iii) Environmental energy gradients are exploited progressively, approaching maximum interactive structure and minimum dissipation. (iv) Dynamic self-assembly of prebiotic organic matter is driven by hydrophobic tension between water and amphiphilic building blocks, such as aggregating peptides from non-polar amino acids and base stacking in nucleic acids. (v) The dynamics of autocatalytic self-organization are facilitated by a multiplicity of weak interactions, such as hydrogen bonding, within and between macromolecular assemblies. (vi) The coevolution of (initially uncoded) proteins and nucleic acids in energy-coupled and metabolically active so-called 'microspheres' is more realistic as a kinetic transition model of primal biogenesis than 'hypercycle replication' theories for nucleic acid replicators on their own. All these considerations blend well with the current understanding that sunlight UV-induced photo-electronic excitation of colloidal metal sulfide particles appears most suitable as a prebiotic driver of organic synthesis reactions, in tight cooperation with organic, phase-separated, catalytic 'microspheres'. On the 'continuist vs. miraculist' schism described by Iris Fry for origins-of-life considerations (Table 1), Wicken was a fervent early protagonist of holistic 'continuist' views and agenda.

The relationship between the error catastrophe, survival of the flattest, and natural selection

BACKGROUND

The quasispecies model is a general model of evolution that is generally applicable to replication up to high mutation rates. It predicts that at a sufficiently high mutation rate, quasispecies with higher mutational robustness can displace quasispecies with higher replicative capacity, a phenomenon called "survival of the flattest". In some fitness landscapes it also predicts the existence of a maximum mutation rate, called the error threshold, beyond which the quasispecies enters into error catastrophe, losing its genetic information. The aim of this paper is to study the relationship between survival of the flattest and the transition to error catastrophe, as well as the connection between these concepts and natural selection.

RESULTS

By means of a very simplified model, we show that the transition to an error catastrophe corresponds to a value of zero for the selective coefficient of the mutant phenotype with respect to the master phenotype, indicating that transition to the error catastrophe is in this case similar to the selection of a more robust species. This correspondence has been confirmed by considering a single-peak landscape in which sequences are grouped with respect to their Hamming distant from the master sequence. When the robustness of a class is changed by modification of its quality factor, the distribution of the population changes in accordance with the new value of the robustness, although an error catastrophe can be detected at the same values as in the general case. When two quasispecies of different robustness competes with one another, the entry of one of them into error catastrophe causes displacement of the other, because of the greater robustness of the former. Previous works are explicitly reinterpreted in the light of the results obtained in this paper.

CONCLUSIONS

The main conclusion of this paper is that the entry into error catastrophe is a specific case of survival of the flattest acting on phenotypes that differ in the trade-off between replicative ability and mutational robustness. In fact, entry into error catastrophe occurs when the mutant phenotype acquires a selective advantage over the master phenotype. As both entry into error catastrophe and survival of the flattest are caused by natural selection when mutation rate is increased, we propose differentiating between them by the level of selection at which natural selection acts. So we propose to consider the transition to error catastrophe as a phenomenon of intra-quasispecies selection, and survival of the flattest as a phenomenon of inter-quasispecies selection.

Quasispecies-like behavior observed in catalytic RNA populations evolving in a test tube

BACKGROUND

During the RNA World, molecular populations were probably very small and highly susceptible to the force of strong random drift. In conjunction with Muller's Ratchet, this would have imposed difficulties for the preservation of the genetic information and the survival of the populations. Mechanisms that allowed these nascent populations to overcome this problem must have been advantageous.

RESULTS

Using continuous in vitro evolution experimentation with an increased mutation rate imposed by MnCl2, it was found that clonal 100-molecule populations of ribozymes clearly exhibit certain characteristics of a quasispecies. This is the first time this has been seen with a catalytic RNA. Extensive genotypic sampling from two replicate lineages was gathered and phylogenetic networks were constructed to elucidate the structure of the evolving RNA populations. A common distribution was found in which a mutant sequence was present at high frequency, surrounded by a cloud of mutant with lower frequencies. This is a typical distribution of quasispecies. Most of the mutants in these clouds were connected by short Hamming distance values, indicating their close relatedness.

CONCLUSIONS

The quasispecies nature of mutant RNA clouds facilitates the recovery of genotypes under pressure of being removed from the population by random drift. The empirical populations therefore evolved a genotypic resiliency despite a high mutation rate by adopting the characteristics of quasispecies, implying that primordial RNA pools could have used this strategy to avoid extinction.

The basic reproductive ratio of life

Template-directed polymerization of nucleotides is believed to be a pathway for the replication of genetic material in the earliest cells. We assume that activated monomers are produced by prebiotic chemistry. These monomers can undergo spontaneous polymerization, a system that we call "prelife." Adding template-directed polymerization changes the equilibrium structure of prelife if the rate constants meet certain criteria. In particular, if the basic reproductive ratio of sequences of a certain length exceeds one, then those sequences can attain high abundance. Furthermore, if many sequences replicate, then the longest sequences can reach high abundance even if the basic reproductive ratios of all sequences are less than one. We call this phenomenon "subcritical life." Subcritical life suggests that sequences long enough to be ribozymes can become abundant even if replication is relatively inefficient. Our work on the evolution of replication has interesting parallels to infection dynamics. Life (replication) can be seen as an infection of prelife.

On the origin of life in the zinc world: 1. Photosynthesizing, porous edifices built of hydrothermally precipitated zinc sulfide as cradles of life on Earth

BACKGROUND

The complexity of the problem of the origin of life has spawned a large number of possible evolutionary scenarios. Their number, however, can be dramatically reduced by the simultaneous consideration of various bioenergetic, physical, and geological constraints.

RESULTS

This work puts forward an evolutionary scenario that satisfies the known constraints by proposing that life on Earth emerged, powered by UV-rich solar radiation, at photosynthetically active porous edifices made of precipitated zinc sulfide (ZnS) similar to those found around modern deep-sea hydrothermal vents. Under the high pressure of the primeval, carbon dioxide-dominated atmosphere ZnS could precipitate at the surface of the first continents, within reach of solar light. It is suggested that the ZnS surfaces (1) used the solar radiation to drive carbon dioxide reduction, yielding the building blocks for the first biopolymers, (2) served as templates for the synthesis of longer biopolymers from simpler building blocks, and (3) prevented the first biopolymers from photo-dissociation, by absorbing from them the excess radiation. In addition, the UV light may have favoured the selective enrichment of photostable, RNA-like polymers. Falsification tests of this hypothesis are described in the accompanying article (A.Y. Mulkidjanian, M.Y. Galperin, Biology Direct 2009, 4:27).

CONCLUSION

The suggested "Zn world" scenario identifies the geological conditions under which photosynthesizing ZnS edifices of hydrothermal origin could emerge and persist on primordial Earth, includes a mechanism of the transient storage and utilization of solar light for the production of diverse organic compounds, and identifies the driving forces and selective factors that could have promoted the transition from the first simple, photostable polymers to more complex living organisms.

Prelife catalysts and replicators

Life is based on replication and evolution. But replication cannot be taken for granted. We must ask what there was prior to replication and evolution. How does evolution begin? We have proposed prelife as a generative system that produces information and diversity in the absence of replication. We model prelife as a binary soup of active monomers that form random polymers. 'Prevolutionary' dynamics can have mutation and selection prior to replication. Some sequences might have catalytic activity, thereby enhancing the rates of certain prelife reactions. We study the selection criteria for these prelife catalysts. Their catalytic efficiency must be above certain critical values. We find a maintenance threshold and an initiation threshold. The former is a linear function of sequence length, and the latter is an exponential function of sequence length. Therefore, it is extremely hard to select for prelife catalysts that have long sequences. We compare prelife catalysis with a simple model for replication. Assuming fast template-based elongation reactions, we can show that replicators have selection thresholds that are independent of their sequence length. Our calculation demonstrates the efficiency of replication and provides an explanation of why replication was selected over other forms of prelife catalysis.

The capabilities of chaos and complexity

To what degree could chaos and complexity have organized a Peptide or RNA World of crude yet necessarily integrated protometabolism? How far could such protolife evolve in the absence of a heritable linear digital symbol system that could mutate, instruct, regulate, optimize and maintain metabolic homeostasis? To address these questions, chaos, complexity, self-ordered states, and organization must all be carefully defined and distinguished. In addition their cause-and-effect relationships and mechanisms of action must be delineated. Are there any formal (non physical, abstract, conceptual, algorithmic) components to chaos, complexity, self-ordering and organization, or are they entirely physicodynamic (physical, mass/energy interaction alone)? Chaos and complexity can produce some fascinating self-ordered phenomena. But can spontaneous chaos and complexity steer events and processes toward pragmatic benefit, select function over non function, optimize algorithms, integrate circuits, produce computational halting, organize processes into formal systems, control and regulate existing systems toward greater efficiency? The question is pursued of whether there might be some yet-to-be discovered new law of biology that will elucidate the derivation of prescriptive information and control. “System” will be rigorously defined. Can a low-informational rapid succession of Prigogine’s dissipative structures self-order into bona fide organization?

A first-principles model of early evolution: emergence of gene families, species, and preferred protein folds

In this work we develop a microscopic physical model of early evolution where phenotype—organism life expectancy—is directly related to genotype—the stability of its proteins in their native conformations—which can be determined exactly in the model. Simulating the model on a computer, we consistently observe the “Big Bang” scenario whereby exponential population growth ensues as soon as favorable sequence–structure combinations (precursors of stable proteins) are discovered. Upon that, random diversity of the structural space abruptly collapses into a small set of preferred proteins. We observe that protein folds remain stable and abundant in the population at timescales much greater than mutation or organism lifetime, and the distribution of the lifetimes of dominant folds in a population approximately follows a power law. The separation of evolutionary timescales between discovery of new folds and generation of new sequences gives rise to emergence of protein families and superfamilies whose sizes are power-law distributed, closely matching the same distributions for real proteins. On the population level we observe emergence of species—subpopulations that carry similar genomes. Further, we present a simple theory that relates stability of evolving proteins to the sizes of emerging genomes. Together, these results provide a microscopic first-principles picture of how first-gene families developed in the course of early evolution.

Here, we address the question of how Darwinian evolution of organisms determines molecular evolution of their proteins and genomes. We developed a microscopic ab initio model of early biological evolution where the fitness (essentially lifetime) of an organism is explicitly related to the evolving sequences of its proteins. The main assumption of the model is that the death rate of an organism is determined by the stability of the least stable of their proteins. A lattice model is used to calculate stability of all proteins in a genome from their amino acid sequence. The simulation of the model starts from 100 identical organisms, each carrying the same random gene, and proceeds via random mutations, gene duplication, organism births via replication, and organism deaths. We find that exponential population growth is possible only after the discovery of a very small number of specific advantageous protein structures. The number of genes in the evolving organisms depends on the mutation rate, demonstrating the intricate relationship between the genome sizes and protein stability requirements. Further, the model explains the observed power-law distributions of protein family and superfamily sizes, as well as the scale-free character of protein structural similarity graphs. Together, these results and their analysis suggest a plausible comprehensive scenario of emergence of the protein universe in early biological evolution.

Understanding protein evolution: from protein physics to Darwinian selection

Efforts in whole-genome sequencing and structural proteomics start to provide a global view of the protein universe, the set of existing protein structures and sequences. However, approaches based on the selection of individual sequences have not been entirely successful at the quantitative description of the distribution of structures and sequences in the protein universe because evolutionary pressure acts on the entire organism, rather than on a particular molecule. In parallel to this line of study, studies in population genetics and phenomenological molecular evolution established a mathematical framework to describe the changes in genome sequences in populations of organisms over time. Here, we review both microscopic (physics-based) and macroscopic (organism-level) models of protein-sequence evolution and demonstrate that bridging the two scales provides the most complete description of the protein universe starting from clearly defined, testable, and physiologically relevant assumptions.

Bootstrapping the energy flow in the beginning of life

This paper suggests that the energy flow on which all living structures depend only started up slowly, the low-energy, initial phase starting up a second, slightly more energetic phase, and so on. In this way, the build up of the energy flow follows a bootstrapping process similar to that found in the development of computers, the first generation making possible the calculations necessary for constructing the second one, etc. In the biogenetic upstart of an energy flow, non-metals in the lower periods of the Periodic Table of Elements would have constituted the most primitive systems, their operation being enhanced and later supplanted by elements in the higher periods that demand more energy. This bootstrapping process would put the development of the metabolisms based on the second period elements carbon, nitrogen and oxygen at the end of the evolutionary process rather than at, or even before, the biogenetic event.

Two approaches to the study of the origin of life

This paper compares two approaches that attempt to explain the origin of life, or biogenesis. The more established approach is one based on chemical principles, whereas a new, yet not widely known approach begins from a physical perspective. According to the first approach, life would have begun with--often organic--compounds. After having developed to a certain level of complexity and mutual dependence within a non-compartmentalised organic soup, they would have assembled into a functioning cell. In contrast, the second, physical type of approach has life developing within tiny compartments from the beginning. It emphasises the importance of redox reactions between inorganic elements and compounds found on two sides of a compartmental boundary. Without this boundary, "life" would not have begun, nor have been maintained; this boundary--and the complex cell membrane that evolved from it--forms the essence of life.

Stochastic innovation as a mechanism by which catalysts might self-assemble into chemical reaction networks

We develop a computer model for how two different chemical catalysts in solution, A and B, could be driven to form AB complexes, based on the concentration gradients of a substrate or product that they share in common. If A's product is B's substrate, B will be attracted to A, mediated by a common resource that is not otherwise plentiful in the environment. By this simple physicochemical mechanism, chemical reactions could spontaneously associate to become chained together in solution. According to the model, such catalyst self-association processes may resemble other processes of "stochastic innovation," such as Darwinian evolution in biology, that involve a search among options, a selection among those options, and then a lock-in of that selection. Like Darwinian processes, this simple chemical process exhibits cooperation, competition, innovation, and a preference for consistency. This model may be useful for understanding organizational processes in prebiotic chemistry and for developing new kinds of self-organization in chemically reacting systems.

Life, Information, Entropy, and Time: Vehicles for Semantic Inheritance

Attempts to understand how information content can be included in an accounting of the energy flux of the biosphere have led to the conclusion that, in information transmission, one component, the semantic content, or "the meaning of the message," adds no thermodynamic burden over and above costs arising from coding, transmission and translation. In biology, semantic content has two major roles. For all life forms, the message of the genotype encoded in DNA specifies the phenotype, and hence the organism that is tested against the real world through the mechanisms of Darwinian evolution. For human beings, communication through language and similar abstractions provides an additional supra-phenotypic vehicle for semantic inheritance, which supports the cultural heritages around which civilizations revolve. The following three postulates provide the basis for discussion of a number of themes that demonstrate some important consequences. (i) Information transmission through either pathway has thermodynamic components associated with data storage and transmission. (ii) The semantic content adds no additional thermodynamic cost. (iii) For all semantic exchange, meaning is accessible only through translation and interpretation, and has a value only in context. (1) For both pathways of semantic inheritance, translational and copying machineries are imperfect. As a consequence both pathways are subject to mutation and to evolutionary pressure by selection. Recognition of semantic content as a common component allows an understanding of the relationship between genes and memes, and a reformulation of Universal Darwinism. (2) The emergent properties of life are dependent on a processing of semantic content. The translational steps allow amplification in complexity through combinatorial possibilities in space and time. Amplification depends on the increased potential for complexity opened by 3D interaction specificity of proteins, and on the selection of useful variants by evolution. The initial interpretational steps include protein synthesis, molecular recognition, and catalytic potential that facilitate structural and functional roles. Combinatorial possibilities are extended through interactions of increasing complexity in the temporal dimension. (3) All living things show a behavior that indicates awareness of time, or chronognosis. The ∼4 billion years of biological evolution have given rise to forms with increasing sophistication in sensory adaptation. This has been linked to the development of an increasing chronognostic range, and an associated increase in combinatorial complexity. (4) Development of a modern human phenotype and the ability to communicate through language, led to the development of archival storage, and invention of the basic skills, institutions and mechanisms that allowed the evolution of modern civilizations. Combinatorial amplification at the supra-phenotypical level arose from the invention of syntax, grammar, numbers, and the subsequent developments of abstraction in writing, algorithms, etc. The translational machineries of the human mind, the "mutation" of ideas therein, and the "conversations" of our social intercourse, have allowed a limited set of symbolic descriptors to evolve into an exponentially expanding semantic heritage. (5) The three postulates above open interesting epistemological questions. An understanding of topics such dualism, the élan vital, the status of hypothesis in science, memetics, the nature of consciousness, the role of semantic processing in the survival of societies, and Popper's three worlds, require recognition of an insubstantial component. By recognizing a necessary linkage between semantic content and a physical machinery, we can bring these perennial problems into the framework of a realistic philosophy. It is suggested, following Popper, that the ∼4 billion years of evolution of the biosphere represents an exploration of the nature of reality at the physicochemical level, which, together with the conscious extension of this exploration through science and culture, provides a firm epistemological underpinning for such a philosophy.

Recombination in primeval genomes: a step forward but still a long leap from maintaining a sizable genome

A stubborn question in early molecular evolution is how to sustain the "minimum" informational length required for the basic features of life with a putative low-copying fidelity RNA polymerase ribozyme. Proposals to circumvent the information crisis have primarily focused on networks of cooperative molecules or compartmentalization of non-cooperative unlinked templates, but success has been very limited so far. Lehman (2003) has recently suggested that recombination--a frequently ignored player in early evolution--could have been crucial to building up primeval genomes of sizable length. Here we investigate this claim by assuming (without loss of generality) that genes were already enclosed in a compartment (vesicle, protocell). The numerical results show a quite intricate interplay among mutation, recombination, and gene redundancy. Provided that the minimum number of gene copies per protocell was enough for recombination to recreate wildtype templates--but not too high to impose an unbearable burden of mutants--informational content could have increased by at least 25% by keeping the same mutational load as that for a population without recombination. However, the upper bound of informational length would still be far from the "minimal life" provisions.

Evolutionary dynamics of invasion and escape

Whenever life wants to invade a new habitat or escape from a lethal selection pressure, some mutations may be necessary to yield sustainable replication. We imagine situations like (i) a parasite infecting a new host, (ii) a species trying to invade a new ecological niche, (iii) cancer cells escaping from chemotherapy, (iv) viruses or microbes evading anti-microbial therapy, and also (v) the repeated attempts of combinatorial chemistry in the very beginning of life to produce self-replicating molecules. All such seemingly unrelated situations have a common structure in terms of Darwinian dynamics: a replicator with a basic reproductive ratio less than one attempts to find some mutations that allow indefinite survival. We develop a general theory, based on multitype branching processes, to describe the evolutionary dynamics of invasion and escape.

Noisy clues to the origin of life

The origin of stable self-replicating molecules represents a fundamental obstacle to the origin of life. The low fidelity of primordial replicators places restrictions on the quantity of information encoded in a primitive nucleic acid alphabet. Further difficulties for the origin of life are the role of drift in small primordial populations, reducing the rate of fixation of superior replicators, and the hostile conditions increasing developmental noise. Thus, mutation, noise and drift are three different stochastic effects that are assumed to make the evolution of life improbable. Here we show, to the contrary, how noise present in hostile early environments can increase the probability of faithful replication, by amplifying selection in finite populations. Noise has negative consequences in infinite populations, whereas in finite populations, we observe a synergistic interaction among noise sources. Hence, two factors formerly considered inimical to the origin of life-developmental noise and drift in small populations-can in combination give rise to conditions favourable to robust replication.

"Living" under the challenge of information decay: the stochastic corrector model vs. hypercycles

The combined problem of having a large genome size when the accuracy of replication was a limiting factor is probably the most difficult transition to explain at the late stages of RNA world. One solution has been to suggest the existence of a cyclically coupled system of autocatalytic and cross-catalytic molecular mutualists, where each member helps the following member and receives help from the preceding one (i.e., a "hypercycle"). However, such a system is evolutionarily unstable when mutations are taken into account because it lacks individuality. In time, the cooperating networks of genes should have been encapsulated in a cell-like structure. But once the cell was invented, it closely aligned genes' common interests and helped to reduce gene selfishness, so there was no need for hypercycles. A simple package of competing genes, described by the "stochastic corrector model" (SCM), could have provided the solution. Until now, there is no clear demonstration that the proposed mechanisms (compartmentalized hypercycles and the stochastic corrector model) do in fact solve the error threshold problem. Here, we present a Monte Carlo model to test the viability of protocell populations that enclose a hypercyclic (HPC) or a non-hypercyclic (SCM) system when faced with realistic mutation rates before the evolution of efficient enzymic machinery for replication. The numerical results indicate that both systems are efficient information integrators and are able to overcome the danger of information decay in the absence of accurate replication. However, a population of SCM protocells can tolerate higher deleterious mutation rates and reaches an equilibrium mutational load lower than that in a population of HPC protocells.

The lipid world

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.

Compositional genomes: prebiotic information transfer in mutually catalytic noncovalent assemblies

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.

Isomorphism of quasispecies and percolation models

Population dynamics of tRNA-like macromolecules and viruses have been interpreted by Eigen (1971, Naturwissenschaften58, 465-526) on the basis of the "quasispecies" model. The present paper contains a qualitative analysis of the similarities between Eigen's quasispecies model and percolation models. In fact, different phenomena characterized by an analogous inner structure can conceivably be described by quite similar mathematical formalisms. The occurrence of a threshold in specific processes predicted by the models is considered first. Secondly, Ising's model of ferromagnetism is taken into account in the last section. An interpretation of the above-mentioned biological theory in terms of percolation, implying a zeroth-order approximation to the real situation, might be a point of departure to a deeper insight obtainable with more refined approaches. A better comprehension of biological phenomena might in any case arise from a percolative approach, even if the description of the systems is simplified. An overview of some quasispecies results and some plausible applications are presented.

Prebiotic cytosine synthesis: a critical analysis and implications for the origin of life

A number of theories propose that RNA, or an RNA-like substance, played a role in the origin of life. Usually, such hypotheses presume that the Watson-Crick bases were readily available on prebiotic Earth, for spontaneous incorporation into a replicator. Cytosine, however, has not been reported in analyses of meteorites nor is it among the products of electric spark discharge experiments. The reported prebiotic syntheses of cytosine involve the reaction of cyanoacetylene (or its hydrolysis product, cyanoacetaldehyde), with cyanate, cyanogen, or urea. These substances undergo side reactions with common nucleophiles that appear to proceed more rapidly than cytosine formation. To favor cytosine formation, reactant concentrations are required that are implausible in a natural setting. Furthermore, cytosine is consumed by deamination (the half-life for deamination at 25 degrees C is approximately 340 yr) and other reactions. No reactions have been described thus far that would produce cytosine, even in a specialized local setting, at a rate sufficient to compensate for its decomposition. On the basis of this evidence, it appears quite unlikely that cytosine played a role in the origin of life. Theories that involve replicators that function without the Watson-Crick pairs, or no replicator at all, remain as viable alternatives.

Reverse transcriptase: mediator of genomic plasticity

Reverse transcription has been an important mediator of genomic change. This influence dates back more than three billion years, when the RNA genome was converted into the DNA genome. While the current cellular role(s) of reverse transcriptase are not yet completely understood, it has become clear over the last few years that this enzyme is still responsible for generating significant genomic change and that its activities are one of the driving forces of evolution. Reverse transcriptase generates, for example, extra gene copies (retrogenes), using as a template mature messenger RNAs. Such retrogenes do not always end up as nonfunctional pseudogenes but form, after reinsertion into the genome, new unions with resident promoter elements that may alter the gene's temporal and/or spatial expression levels. More frequently, reverse transcriptase produces copies of nonmessenger RNAs, such as small nuclear or cytoplasmic RNAs. Extremely high copy numbers can be generated by this process. The resulting reinserted DNA copies are therefore referred to as short interspersed repetitive elements (SINEs). SINEs have long been considered selfish DNA, littering the genome via exponential propagation but not contributing to the host's fitness. Many SINEs, however, can give rise to novel genes encoding small RNAs, and are the migrant carriers of numerous control elements and sequence motifs that can equip resident genes with novel regulatory elements [Brosius J. and Gould S.J., Proc Natl Acad Sci USA 89, 10706-10710, 1992]. Retrosequences, such as SINEs and portions of retroelements (e.g., long terminal repeats, LTRs), are capable of donating sequence motifs for nucleosome positioning, DNA methylation, transcriptional enhancers and silencers, poly(A) addition sequences, determinants of RNA stability or transport, splice sites, and even amino acid codons for incorporation into open reading frames as novel protein domains. Retroposition can therefore be considered as a major pacemaker for evolution (including speciation). Retroposons, with their unique properties and actions, form the molecular basis of important evolutionary concepts, such as exaptation [Gould S.J. and Vrba E., Paleobiology 8, 4-15, 1982] and punctuated equilibrium [Elredge N. and Gould S.J. in Schopf T.J.M. (ed). Models in Paleobiology. Freeman, Cooper, San Francisco, 1972, pp. 82-115].