BackgroundThe origin and stability of cooperation is a hot topic in social and behavioural sciences. A complicated conundrum exists as defectors have an advantage over cooperators, whenever cooperation is costly so consequently, not cooperating pays off. In addition, the discovery that humans and some animal populations, such as lions, are polymorphic, where cooperators and defectors stably live together -- while defectors are not being punished--, is even more puzzling. Here we offer a novel explanation based on a Threshold Public Good Game (PGG) that includes the interaction of individual and group level selection, where individuals can contribute to multiple collective actions, in our model group hunting and group defense.ResultsOur results show that there are polymorphic equilibria in Threshold PGGs; that multi-level selection does not select for the most cooperators per group but selects those close to the optimum number of cooperators (in terms of the Threshold PGG). In particular for medium cost values division of labour evolves within the group with regard to the two types of cooperative actions (hunting vs. defense). Moreover we show evidence that spatial population structure promotes cooperation in multiple PGGs. We also demonstrate that these results apply for a wide range of non-linear benefit function types.ConclusionsWe demonstrate that cooperation can be stable in Threshold PGG, even when the proportion of so called free riders is high in the population. A fundamentally new mechanism is proposed how laggards, individuals that have a high tendency to defect during one specific group action can actually contribute to the fitness of the group, by playing part in an optimal resource allocation in Threshold Public Good Games. In general, our results show that acknowledging a multilevel selection process will open up novel explanations for collective actions.

The problem of the origin of life is not only one of structure but also that of dynamics. Ever since the seminal result of Manfred Eigen in 1971 showing that early template replication suffers from an error threshold, research has tackled the issue of how early genomes could have been dynamically stable without highly evolved mechanisms such as accurate replication and chromosomes. We review the theory of the origin, maintenance and enhancement of the RNA world as an evolving population of dynamical systems. Investigation of sequence space has revealed how structures are allocated in sequence space and how this affects the nature of the error threshold that sets the selectively maintainable genome length. New applications of old dynamical theory are still possible: the application of Gause's principle of competitive exclusion, based on resource utilisation, to RNA replication predicts that at most four pairs (plus and minus strands) can stably be maintained on four nucleotides. Other mechanisms of early template coexistence should be regarded as additional means to raise the number of coexisting species above the number set by the competitive exclusion principle. One such example is the hypercycle in which templates were postulated to help replication of the next member in a cycle superimposed on individual replication cycles. Although the hypercycle is ecologically unstable it is evolutionarily unstable because it cannot efficiently compete against emerging parasites. Population structure can modify this conclusion but not without further qualification. The simplest form of population structure is limited diffusion on a surface. This simple mechanism can ensure the coexistence of competing ribozymes contributing to surface metabolism as well as the spread of efficient replicases despite the parasite problem. Hypercyclescan only be saved by active compartmentalization when replicators are enclosed in reproducing protocells. Once there are protocells there is no need for internal hypercyclic organization, however. Finally we review two crucial adaptations that enhanced the RNA world: chromosomes and enzymatic metabolism. Interestingly, it was shown that these two have been presumably coevolutionarily linked because protocells harbouring unlinked, competing ribozymes are better off if the ribozymes remain inefficient but generalists. The appearance of chromosomes alleviates intragenomic conflict and is enabling constraint for the emergence of specific and efficient enzymes.The possibility of an RNA world, a period in the origin of life on Earth, when RNA molecules acted both as enzymes and as genetic material, was suggested well before the name was coined by Gilbert in 1986 1 . The history of the research on the origin of life 2 tells us that the potential prebiotic importance of RNA was suggested as early as in the late 50's. When it became established that living cells harbour much more RNA than DNA some biologist have proposed that RNA preceded DNA during evolution 3,4 . The discovery of the details of protein ...

Endosymbiosis and organellogenesis are virtually unknown among prokaryotes. The single presumed example is the endosymbiogenetic origin of mitochondria, which is hidden behind the event horizon of the last eukaryotic common ancestor. While eukaryotes are monophyletic, it is unlikely that during billions of years, there were no other prokaryote-prokaryote endosymbioses as symbiosis is extremely common among prokaryotes, e.g., in biofilms. Therefore, it is even more precarious to draw conclusions about potentially existing (or once existing) prokaryotic endosymbioses based on a single example.It is yet unknown if the bacterial endosymbiont was captured by a prokaryote or by a (proto-)eukaryote, and if the process of internalization was parasitic infection, slow engulfment, or phagocytosis. In this review, we accordingly explore multiple mechanisms and processes that could drive the evolution of unicellular microbial symbioses with a special attention to prokaryote-prokaryote interactions and to the mitochondrion, possibly the single prokaryotic endosymbiosis that turned out to be a major evolutionary transition. We investigate the ecology and evolutionary stability of inter-species microbial interactions based on dependence, physical proximity, cost-benefit budget, and the types of benefits, investments, and controls. We identify challenges that had to be conquered for the mitochondrial host to establish a stable eukaryotic lineage. Any assumption about the initial interaction of the mitochondrial ancestor and its contemporary host based solely on their modern relationship is rather perilous. As a result, we warn against assuming an initial mutually beneficial interaction based on modern mitochondria-host cooperation. This assumption is twice fallacious: (i) endosymbioses are known to evolve from exploitative interactions and (ii) cooperativity does not necessarily lead to stable mutualism. We point out that the lack of evidence so far on the evolution of endosymbiosis from mutual syntrophy supports the idea that mitochondria emerged from an exploitative (parasitic or phagotrophic) interaction rather than from syntrophy.Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The snowdrift (or chicken) game emerges as a new paradigm in the study of nonkin cooperation in animals. Many situations, for example, cooperative hunting, group foraging, territorial defense, predator watching, or parental care, can be adequately described as a snowdrift game. In this paper, we investigate the asynchronous version of the game in which, contrary to the rather unrealistic assumption of simultaneous moves, one of the players acts first and the other responds by knowing its decision. Players are assigned to be first or second movers randomly and with the same probability. We found that both a synergistic effect of cooperation (i.e., cooperative effort is better than the sum of the individual efforts) and population structure (low dispersal, spatial confinement, or group formation) are crucial for mutual cooperation to emerge. Otherwise, only one of the players will carry the burden of cooperation.

Understanding the mechanisms that promote the assembly and maintenance of host-beneficial microbiomes is an open problem. Empirical evidence supports the idea that animal and plant hosts can combine ‘private resources’ with the ecological phenomenon known as ‘community bistability’ to favour some microbial strains over others. We briefly review evidence showing that hosts can: (i) protect the growth of beneficial strains in an isolated habitat, (ii) use antibiotics to suppress non-beneficial, competitor strains, and (iii) provide resources that only beneficial strains are able to translate into an increased rate of growth, reproduction, or antibiotic production. We then demonstrate in a spatially explicit, individual-based model that these three mechanisms act similarly by selectively promoting the initial proliferation of preferred strains, that is, by acting as a private resource. The faster early growth of preferred strains, combined with the phenomenon of ‘community bistability,’ allows those strains to continue to dominate the microbiome even after the private resource is withdrawn or made public. This is because after a beneficial colony reaches a sufficiently large size, it can resist invasion by parasites without further private support from the host. We further explicitly model localized microbial interactions and diffusion dynamics, and we show that an intermediate level of antibiotic diffusion is the most efficient mechanism in promoting preferred strains and that there is a wide range of parameters under which hosts can promote the assembly of a self-sustaining defensive microbiome. This in turn supports the idea that hosts readily evolve to promote host-beneficial defensive microbiomes.

The RNA world is a very likely interim stage of the evolution after the first replicators and before the advent of the genetic code and translated proteins. Ribozymes are known to be able to catalyze many reaction types, including cofactor-aided metabolic transformations. In a metabolically complex RNA world, early division of labor between genes and enzymes could have evolved, where the ribozymes would have been transcribed from the genes more often than the other way round, benefiting the encapsulating cells through this dosage effect. Here we show, by computer simulations of protocells harboring unlinked RNA replicators, that the origin of replicational asymmetry producing more ribozymes from a gene template than gene strands from a ribozyme template is feasible and robust. Enzymatic activities of the two modeled ribozymes are in trade-off with their replication rates, and the relative replication rates compared to those of complementary strands are evolvable traits of the ribozymes. The degree of trade-off is shown to have the strongest effect in favor of the division of labor. Although some asymmetry between gene and enzymatic strands could have evolved even in earlier, surface-bound systems, the shown mechanism in protocells seems inevitable and under strong positive selection. This could have preadapted the genetic system for transcription after the subsequent origin of chromosomes and DNA.

Motivation Machine learning (ML) methods are motivated by the need to automate information extraction from large data sets in order to support human users in data-driven tasks. This is an attractive approach for integrative joint analysis of vast amounts of omics data produced in next generation sequencing and other -omics assays. A systematic assessment of the current literature can help to identify key trends and potential gaps in methodology and applications. We surveyed the literature on ML multi-omic data integration and quantitatively explored the goals, techniques and data involved in this field. We were particularly interested in examining how researchers use ML to deal with the volume and complexity of these datasets. Results Our main finding is that the methods used are those that address the challenges of datasets with few samples and many features. Dimensionality reduction methods are used to reduce the feature count alongside models that can also appropriately handle relatively few samples. Popular techniques include autoencoders, random forests and support vector machines. We also found that the field is heavily influenced by the use of The Cancer Genome Atlas data set, which is accessible and contains many diverse experiments. Availability All data and processing scripts are available at this GitLab repository: https://gitlab.com/polavieja_lab/ml_multi-omics_review/ or in Zenodo: https://doi.org/10.5281/zenodo.7361807 Supplementary information Supplementary data are available at Bioinformatics online.

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