Hypercycle

RNA World with Inhibitors

During the evolution of the RNA World, compartments, which were fragments of space surrounded by a primitive lipid membrane, had to have emerged. These led eventually to the formation of modern cellular membranes. Inside these compartments, another process had to take place-switching from RNA to DNA as a primary storage of genetic information. The latter part needed a handful of enzymes for the DNA to be able to perform its function. A natural question arises, i.e., how the concentration of all vital molecules could have been kept in check without modern cellular mechanisms. The authors propose a theory on how it could have worked during early stages, using only short RNA molecules, which could have emerged spontaneously. The hypothesis was analysed mathematically and tested against different scenarios by using computer simulations.

Selectively advantageous instability in biotic and pre-biotic systems and implications for evolution and aging

Rules of biology typically involve conservation of resources. For example, common patterns such as hexagons and logarithmic spirals require minimal materials, and scaling laws involve conservation of energy. Here a relationship with the opposite theme is discussed, which is the selectively advantageous instability (SAI) of one or more components of a replicating system, such as the cell. By increasing the complexity of the system, SAI can have benefits in addition to the generation of energy or the mobilization of building blocks. SAI involves a potential cost to the replicating system for the materials and/or energy required to create the unstable component, and in some cases, the energy required for its active degradation. SAI is well-studied in cells. Short-lived transcription and signaling factors enable a rapid response to a changing environment, and turnover is critical for replacement of damaged macromolecules. The minimal gene set for a viable cell includes proteases and a nuclease, suggesting SAI is essential for life. SAI promotes genetic diversity in several ways. Toxin/antitoxin systems promote maintenance of genes, and SAI of mitochondria facilitates uniparental transmission. By creating two distinct states, subject to different selective pressures, SAI can maintain genetic diversity. SAI of components of synthetic replicators favors replicator cycling, promoting emergence of replicators with increased complexity. Both classical and recent computer modeling of replicators reveals SAI. SAI may be involved at additional levels of biological organization. In summary, SAI promotes replicator genetic diversity and reproductive fitness, and may promote aging through loss of resources and maintenance of deleterious alleles.

Onset model of mutually catalytic self-replicative systems formed by an assembly of polynucleotides

Self-replicability is a unique attribute observed in all living organisms, and the question of how the life was physically initiated could be equivalent to the question of how self-replicating informative polymers were formed in the abiotic material world. It has been suggested that the present DNA and proteins world was preceded by an RNA world in which genetic information of RNA molecules was replicated by the mutual catalytic function of RNA molecules. However, the important question of how the transition occurred from a material world to the very early pre-RNA world remains unsolved both experimentally and theoretically. We present an onset model of mutually catalytic self-replicative systems formed in an assembly of polynucleotides. A quantitative expression of the critical condition for the onset of growing fluctuation towards self-replication in this model is obtained by analytical and numerical calculations.

The simple emergence of complex molecular function

At odds with a traditional view of molecular evolution that seeks a descent-with-modification relationship between functional sequences, new functions can emerge de novo with relative ease. At early times of molecular evolution, random polymers could have sufficed for the appearance of incipient chemical activity, while the cellular environment harbours a myriad of proto-functional molecules. The emergence of function is facilitated by several mechanisms intrinsic to molecular organization, such as redundant mapping of sequences into structures, phenotypic plasticity, modularity or cooperative associations between genomic sequences. It is the availability of niches in the molecular ecology that filters new potentially functional proposals. New phenotypes and subsequent levels of molecular complexity could be attained through combinatorial explorations of currently available molecular variants. Natural selection does the rest. This article is part of the theme issue 'Emergent phenomena in complex physical and socio-technical systems: from cells to societies'.

RNA World Modeling: A Comparison of Two Complementary Approaches

Simple Summary

Despite years of dedicated research, scientists are still not sure what the first ”living” cell would have looked like. One of the most well-known hypotheses is the RNA world hypothesis, which assumes that, in the beginning, life relied on RNA molecules instead of DNA as information carriers and primitive enzymes. The population of such RNAs is made up of self-replicating molecules (replicases) that could make copies of themselves and parasite molecules that could only be copied by replicases. In this study, we further investigated the interplay between these hypothetical prebiotic RNA species, since it plays a crucial role in generating diversity and complexity in prebiotic molecular evolution. We compared two approaches that are commonly used to investigate such simple prebiotic systems, representing different modeling and observation scales—namely, microscopic and macroscopic. In both cases, we were able to obtain consistent results.

Abstract

The origin of life remains one of the major scientific questions in modern biology. Among many hypotheses aiming to explain how life on Earth started, RNA world is probably the most extensively studied. It assumes that, in the very beginning, RNA molecules served as both enzymes and as genetic information carriers. However, even if this is true, there are many questions that still need to be answered—for example, whether the population of such molecules could achieve stability and retain genetic information for many generations, which is necessary in order for evolution to start. In this paper, we try to answer this question based on the parasite–replicase model (RP model), which divides RNA molecules into enzymes (RNA replicases) capable of catalyzing replication and parasites that do not possess replicase activity but can be replicated by RNA replicases. We describe the aforementioned system using partial differential equations and, based on the analysis of the simulation, surmise general rules governing its evolution. We also compare this approach with one where the RP system is modeled and implemented using a multi-agent modeling technique. We show that approaching the description and analysis of the RP system from different perspectives (microscopic represented by MAS and macroscopic depicted by PDE) provides consistent results. Therefore, applying MAS does not lead to erroneous results and allows us to study more complex situations where many cases are concerned, which would not be possible through the PDE model.

Historical Perspective on the Discovery of the Quasispecies Concept

Viral quasispecies are dynamic distributions of nonidentical but closely related mutant and recombinant viral genomes subjected to a continuous process of genetic variation, competition, and selection that may act as a unit of selection. The quasispecies concept owes its theoretical origins to a model for the origin of life as a collection of mutant RNA replicators. Independently, experimental evidence for the quasispecies concept was obtained from sampling of bacteriophage clones, which revealed that the viral populations consisted of many mutant genomes whose frequency varied with time of replication. Similar findings were made in animal and plant RNA viruses. Quasispecies became a theoretical framework to understand viral population dynamics and adaptability. The evidence came at a time when mutations were considered rare events in genetics, a perception that was to change dramatically in subsequent decades. Indeed, viral quasispecies was the conceptual forefront of a remarkable degree of biological diversity, now evident for cell populations and organisms, not only for viruses. Quasispecies dynamics unveiled complexities in the behavior of viral populations,with consequences for disease mechanisms and control strategies. This review addresses the origin of the quasispecies concept, its major implications on both viral evolution and antiviral strategies, and current and future prospects.

Learning vector quantization as an interpretable classifier for the detection of SARS-CoV-2 types based on their RNA sequences

We present an approach to discriminate SARS-CoV-2 virus types based on their RNA sequence descriptions avoiding a sequence alignment. For that purpose, sequences are preprocessed by feature extraction and the resulting feature vectors are analyzed by prototype-based classification to remain interpretable. In particular, we propose to use variants of learning vector quantization (LVQ) based on dissimilarity measures for RNA sequence data. The respective matrix LVQ provides additional knowledge about the classification decisions like discriminant feature correlations and, additionally, can be equipped with easy to realize reject options for uncertain data. Those options provide self-controlled evidence, i.e., the model refuses to make a classification decision if the model evidence for the presented data is not sufficient. This model is first trained using a GISAID dataset with given virus types detected according to the molecular differences in coronavirus populations by phylogenetic tree clustering. In a second step, we apply the trained model to another but unlabeled SARS-CoV-2 virus dataset. For these data, we can either assign a virus type to the sequences or reject atypical samples. Those rejected sequences allow to speculate about new virus types with respect to nucleotide base mutations in the viral sequences. Moreover, this rejection analysis improves model robustness. Last but not least, the presented approach has lower computational complexity compared to methods based on (multiple) sequence alignment.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s00521-021-06018-2.

Chessboard and Chess Piece Recognition With the Support of Neural Networks

Chessboard and chess piece recognition is a computer vision problem that has not yet been efficiently solved. Digitization of a chess game state from a picture of a chessboard is a task typically performed by humans or with the aid of specialized chessboards and pieces. However, those solutions are neither easy nor convenient. To solve this problem, we propose a novel algorithm for digitizing chessboard configurations.

We designed a method of chessboard recognition and pieces detection that is resistant to lighting conditions and the angle at which images are captured, and works correctly with numerous chessboard styles. Detecting the board and recognizing chess pieces are crucial steps of board state digitization.

The algorithm achieves 95% accuracy (compared to 60% for the best alternative) for positioning the chessboard in an image, and almost 95% for chess pieces recognition. Furthermore, the sub-process of detecting straight lines and finding lattice points performs extraordinarily well, achieving over 99.5% accuracy (compared to the 74% for the best alternative).

Multi-agent approach to sequence structure simulation in the RNA World hypothesis

The origins of life on Earth have been the subject of inquiry since the early days of philosophical thought and are still intensively investigated by the researchers around the world. One of the theories explaining the life emergence, that gained the most attention recently is the RNA World hypothesis, which assumes that life on Earth was sparked by replicating RNA chains. Since wet lab analysis is time-consuming, many mathematical and computational approaches have been proposed that try to explain the origins of life. Recently proposed one, based on the work by Takeuchi and Hogeweg, addresses the problem of interplay between RNA replicases and RNA parasitic species, which is crucial for understanding the first steps of prebiotic evolution. In this paper, the aforementioned model has been extended and modified by introducing RNA sequence (structure) information and mutation rate close to real one. It allowed to observe the simple evolution mechanisms, which could have led to the more complicated systems and eventually, to the formation of the first cells. The main goal of this study was to determine the conditions that allowed the spontaneous emergence and evolution of the prebiotic replicases equipped with simple functional domains within a large population. Here we show that polymerase ribozymes could have appeared randomly and then quickly started to copy themselves in order for the system to reach equilibrium. It has been shown that evolutionary selection works even in the simplest systems.

Synthetic Symbiosis under Environmental Disturbances

The power of synthetic biology is immense. Will it, however, be able to withstand the environmental pressures once released in the wild. As new technologies aim to do precisely the same, we use a much simpler model to test mathematically the effect of a changing environment on a synthetic biological system. We assume that the system is successful if it maintains proportions close to what we observe in the laboratory. Extreme deviations from the expected equilibrium are possible as the environment changes. Our study provides the conditions and the designer specifications which may need to be incorporated in the synthetic systems if we want such “ecoblocs” to survive in the wild.

By virtue of complex ecologies, the behavior of mutualisms is challenging to study and nearly impossible to predict. However, laboratory engineered mutualistic systems facilitate a better understanding of their bare essentials. On the basis of an abstract theoretical model and a modifiable experimental yeast system, we explore the environmental limits of self-organized cooperation based on the production and use of specific metabolites. We develop and test the assumptions and stability of the theoretical model by leveraging the simplicity of an artificial yeast system as a simple model of mutualism. We examine how one-off, recurring, and permanent changes to an ecological niche affect a cooperative interaction and change the population composition of an engineered mutualistic system. Moreover, we explore how the cellular burden of cooperating influences the stability of mutualism and how environmental changes shape this stability. Our results highlight the fragility of mutualisms and suggest interventions, including those that rely on the use of synthetic biology.

IMPORTANCE The power of synthetic biology is immense. Will it, however, be able to withstand the environmental pressures once released in the wild. As new technologies aim to do precisely the same, we use a much simpler model to test mathematically the effect of a changing environment on a synthetic biological system. We assume that the system is successful if it maintains proportions close to what we observe in the laboratory. Extreme deviations from the expected equilibrium are possible as the environment changes. Our study provides the conditions and the designer specifications which may need to be incorporated in the synthetic systems if we want such “ecoblocs” to survive in the wild.

Molecular shape as a key source of prebiotic information

One of the most striking features of a living system is the self-sustaining functional inner organization, which is only possible when a source of internal references is available from which the system is able to self-organize components and processes. Internal references are intrinsically related to biological information, which is typically understood as genetic information. However, the organization in living systems supports a diversity of intricate processes that enable life to endure, adapt and reproduce because of this organization. In a biological context, information refers to a complex relationship between internal architecture and system functionality. Nongenetic processes, such as conformational recognition, are not considered biological information, although they exert important control over cell processes. In this contribution, we discuss the informational nature in the recognition of molecular shape in living systems. Thus, we highlight supramolecular matching as having a theoretical key role in the origin of life. Based on recent data, we demonstrate that the transfer of molecular conformation is a very likely dynamic of prebiotic information, which is closely related to the origin of biological homochirality and biogenic systems. In light of the current hypothesis, we also revisit the central dogma of molecular biology to assess the consistency of the proposal presented here. We conclude that both spatial (molecular shape) and sequential (genetic) information must be represented in this biological paradigm.

Turbulent coherent structures and early life below the Kolmogorov scale

Major evolutionary transitions, including the emergence of life, likely occurred in aqueous environments. While the role of water’s chemistry in early life is well studied, the effects of water’s ability to manipulate population structure are less clear. Population structure is known to be critical, as effective replicators must be insulated from parasites. Here, we propose that turbulent coherent structures, long-lasting flow patterns which trap particles, may serve many of the properties associated with compartments — collocalization, division, and merging — which are commonly thought to play a key role in the origins of life and other evolutionary transitions. We substantiate this idea by simulating multiple proposed metabolisms for early life in a simple model of a turbulent flow, and find that balancing the turnover times of biological particles and coherent structures can indeed enhance the likelihood of these metabolisms overcoming extinction either via parasitism or via a lack of metabolic support. Our results suggest that group selection models may be applicable with fewer physical and chemical constraints than previously thought, and apply much more widely in aqueous environments.

Models of the origin of life generally require a mechanism to structure emerging populations. Here, Krieger et al. develop spatial models showing that coherent structures arising in turbulent flows in aquatic environments could have provided compartments that facilitated the origin of life.

VirDB: Crowdsourced Database for Evaluation of Dynamical Viral Infection Models

Background:

Open science is an emerging movement underlining the importance of transparent, high quality research where results can be verified and reused by others. However, one of the biggest problems in replicating experiments is the lack of access to the data used by the authors. This problem also occurs during mathematical modeling of a viral infections. It is a process that can provide valuable insights into viral activity or into a drug’s mechanism of action when conducted correctly.

Objective:

We present the VirDB database (virdb.cs.put.poznan.pl), which has two primary objectives. First, it is a tool that enables collecting data on viral infections that could be used to develop new dynamic models of infections using the FAIR data sharing principles. Second, it allows storing references to descriptions of viral infection models, together with their evaluation results.

Methods:

To facilitate the fast population of database and the ease of exchange of scientific data, we decided to use crowdsourcing for collecting data. Such approach has already been proved to be very successful in projects such as Wikipedia.

Conclusion:

VirDB builds on the concepts and recommendations of Open Science and shares data using the FAIR principles. Thanks to this storing data required for designing and evaluating models of viral infections which can be freely available on the Internet.

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.

The mitochondrial genome of Endoconidiophora resinifera is intron rich

Endoconidiophora resinifera (=Ceratocystis resinifera) is a blue-stain fungus that occurs on conifers. The data showed that the Endoconidiophora resinifera mitochondrial genome is one of the largest mitochondrial genomes (>220 kb) so far reported among members of the Ascomycota. An exceptional large number of introns (81) were noted and differences among the four strains were restricted to minor variations in intron numbers and a few indels and single nucleotide polymorphisms. The major differences among the four strains examined are due to size polymorphisms generated by the absence or presence of mitochondrial introns. Also, these mitochondrial genomes encode the largest cytochrome oxidase subunit 1 gene (47.5 kb) reported so far among the fungi. The large size for this gene again can be attributed to the large number of intron insertions. This study reports the first mitochondrial genome for the genus Endoconidiophora, previously members of this genus were assigned to Ceratocystis. The latter genus has recently undergone extensive taxonomic revisions and the mitochondrial genome might provide loci that could be applied as molecular markers assisting in the identification of taxa within this group of economically important fungi. The large mitochondrial genome also may provide some insight on mechanisms that can lead to mitochondrial genome expansion.

Modeling Biological Systems Using Crowdsourcing

Crowdsourcing is a very effective technique for outsourcing work to a vast network usually comprising anonymous people. In this study, we review the application of crowdsourcing to modeling systems originating from systems biology. We consider a variety of verified approaches, including well-known projects such as EyeWire, FoldIt, and DREAM Challenges, as well as novel projects conducted at the European Center for Bioinformatics and Genomics. The latter projects utilized crowdsourced serious games to design models of dynamic biological systems, and it was demonstrated that these models could be used successfully to involve players without domain knowledge. We conclude the review of these systems by providing 10 guidelines to facilitate the efficient use of crowdsourcing.

Models of Replicator Proliferation Involving Differential Replicator Subunit Stability

Several models for the origin of life involve molecules that are capable of self-replication, such as self-replicating polymers composed of RNA or DNA or amino acids. Here we consider a hypothetical replicator (AB) composed of two subunits, A and B. Programs written in Python and C programming languages were used to model AB replicator abundance as a function of cycles of replication (iterations), under specified hypothetical conditions. Two non-exclusive models describe how a reduced stability for B relative to A can have an advantage for replicator activity and/or evolution by generating free A subunits. In model 1, free A subunits associate with AB replicators to create AAB replicators with greater activity. In simulations, reduced stability of B was beneficial when the replication activity of AAB was greater than two times the replication activity of AB. In model 2, the free A subunit is inactive for some number of iterations before it re-creates the B subunit. A re-creates the B subunit with an equal chance of creating B or B', where B' is a mutant that increases AB' replicator activity relative to AB. In simulations, at moderate number of iterations (< 15), a shorter survival time for B is beneficial when the stability of B is greater than the inactive time of A. The results are consistent with the hypothesis that reduced stability for a replicator subunit can be advantageous under appropriate conditions.

Ecology and Evolution in the RNA World Dynamics and Stability of Prebiotic Replicator Systems

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.

Prebiotic selection for motifs in a model of template-free elongation of polymers within compartments

The transition from prelife where self-replication does not occur, to life which exhibits self-replication and evolution, has been a subject of interest for many decades. Membranes, forming compartments, seem to be a critical component of this transition as they provide several concurrent benefits. They maintain localized interactions, generate electro-chemical gradients, and help in selecting cooperative functions as they arise. These functions pave the way for the emergence and maintenance of simple metabolic cycles and polymers. In the context of origin of life, evolution of information-carrying molecules and RNA based enzymes within compartments has been subject to intensive theoretical and experimental research. Hence, many experimental efforts aim to produce compartments that contain elongating polynucleotides (also referred to as protocells), which store information and perform catalysis. Despite impressive experimental progress, we are still relatively ignorant about the dynamics by which elongating polynucleotides can produce more sophisticated behaviors. Here we perform computer simulations to couple information production through template-free elongation of polymers with dividing compartments. We find that polymers with a simple ability—biasing the concentration of monomers within their own compartment—can acquire a selective advantage in prelife. We further investigate whether such a mechanism allows for cooperative dynamics to dominate over purely competitive ones. We show that under this system of biased monomer addition, even without template-directed self-replication, genetic motifs can emerge, compete, cooperate, and ultimately survive within the population.

Simulating the origins of life: The dual role of RNA replicases as an obstacle to evolution

Despite years of study, it is still not clear how life emerged from inanimate matter and evolved into the complex forms that we observe today. One of the most recognized hypotheses for the origins of life, the RNA World hypothesis, assumes that life was sparked by prebiotic replicating RNA chains. In this paper, we address the problems caused by the interplay between hypothetical prebiotic RNA replicases and RNA parasitic species. We consider the coexistence of parasite RNAs and RNA replicases as well as the impact of parasites on the further evolution of replicases. For these purposes, we used multi-agent modeling techniques that allow for realistic assumptions regarding the movement and spatial interactions of modeled species. The general model used in this study is based on work by Takeuchi and Hogeweg. Our results confirm that the coexistence of parasite RNAs and replicases is possible in a spatially extended system, even if we take into consideration more realistic assumptions than Takeuchi and Hogeweg. However, we also showed that the presence of trade-off that takes into the account an RNA folding process could still pose a serious obstacle to the evolution of replication. We conclude that this might be a cause for one of the greatest transitions in life that took place early in evolution-the separation of the function between DNA templates and protein enzymes, with a central role for RNA species.

Trustworthy Online Shopping with Price Impact

Internet shopping is one of the main pillars of electronic commerce.According to the literature, the Internet Shopping Optimization Problem (ISOP)has been defined in order to optimize the global cost of online purchase, taking into account both the cost of products and shipping. In this study, it was decided to propose and analyze a very interesting, and really substantial, extension of the ISOP.Namely, trust factors were subjected to careful analysis from the customer point of view. The analysis is based on a specially prepared questionnaire, supplemented by the information from the literature and our own observations. Thus, it was possible to propose a definition of a new mathematical model of the problem, and to prove its affiliation to the class of strongly NP-hard problems. In addition, the heuristic algorithm is proposed, which can be used to solve the problem.

New evolutionary insights into the non-enzymatic origin of RNA oligomers

We outline novel findings on the non-enzymatic polymerization of nucleotides under plausible prebiotic conditions and on the spontaneous onset of informational complexity in the founding molecule, RNA. We argue that the unique ability of 3', 5' cyclic guanosine monophosphate to form stacked architectures and polymerize in a self-sustained manner suggests that this molecule may serve as the 'seed of life' from which all self-replicating oligonucleotides can be derived via a logically complete sequence of simple events. WIREs RNA 2017, 8:e1400. doi: 10.1002/wrna.1400 For further resources related to this article, please visit the WIREs website.