The study of evolution has entered a revolutionary new era, where quantitative and predictive methods are transforming the traditionally qualitative and retrospective approaches of the past. Genomic sequencing and modern computational techniques are permitting quantitative comparisons between variation in the natural world and predictions rooted in neo-Darwinian theory, revealing the shortcomings of current evolutionary theory, particularly with regard to large-scale phenomena like macroevolution. Current research spanning and uniting diverse fields and exploring the physical and chemical nature of organisms across temporal, spatial, and organizational scales is replacing the model of evolution as a passive filter selecting for random changes at the nucleotide level with a paradigm in which evolution is a dynamic process both constrained and driven by the informational architecture of organisms across scales, from DNA and chromatin regulation to interactions within and between species and the environment.
Prebiotic chemical reactions would have been greatly aided by a process whereby living materials could have been recycled under conditions of limiting resources. Recombination of RNA fragments is a viable means of recycling but has not been demonstrated. Using systems based on the Azoarcus group I intron ribozyme, computational Monte Carlo studies indicate that a moderate level of recycling activity, spontaneous or catalyzed, leads to the most robust selection scenarios. It is interesting that recycling leads to a threshold effect where a dominant species suddenly jumps to fixation. In conjunction, laboratory studies with the Azoarcus ribozyme corroborate these results, showing that mixtures of scrambled and/or deleteriously mutated molecules can recycle their component fragments to generate fully functional recombinase ribozymes. These studies highlight the importance of recombination and recycling jointly in the advent of living systems.
The activation-polymerization-epimerization-depolymerization (APED) model of Plasson et al. has recently been proposed as a mechanism for the evolution of homochirality on prebiotic Earth. The dynamics of the APED model in two-dimensional spatially-extended systems is investigated for various realistic reaction parameters. It is found that the APED system allows for the formation of isolated homochiral proto-domains surrounded by a racemate. A diffusive slowdown of the APED network induced, for example, through tidal motion or evaporating pools and lagoons leads to the stabilization of homochiral bounded structures as expected in the first self-assembled protocells.
Many models for the origin of life have focused on understanding how evolution can drive the refinement of a preexisting enzyme, such as the evolution of efficient replicase activity. Here we present a model for what was, arguably, an even earlier stage of chemical evolution, when polymer sequence diversity was generated and sustained before, and during, the onset of functional selection. The model includes regular environmental cycles (e.g. hydration-dehydration cycles) that drive polymers between times of replication and functional activity, which coincide with times of different monomer and polymer diffusivity. Template-directed replication of informational polymers, which takes place during the dehydration stage of each cycle, is considered to be sequence-independent. New sequences are generated by spontaneous polymer formation, and all sequences compete for a finite monomer resource that is recycled via reversible polymerization. Kinetic Monte Carlo simulations demonstrate that this proposed prebiotic scenario provides a robust mechanism for the exploration of sequence space. Introduction of a polymer sequence with monomer synthetase activity illustrates that functional sequences can become established in a preexisting pool of otherwise non-functional sequences. Functional selection does not dominate system dynamics and sequence diversity remains high, permitting the emergence and spread of more than one functional sequence. It is also observed that polymers spontaneously form clusters in simulations where polymers diffuse more slowly than monomers, a feature that is reminiscent of a previous proposal that the earliest stages of life could have been defined by the collective evolution of a system-wide cooperation of polymer aggregates. Overall, the results presented demonstrate the merits of considering plausible prebiotic polymer chemistries and environments that would have allowed for the rapid turnover of monomer resources and for regularly varying monomer/polymer diffusivities.
We investigate the possibility that prebiotic homochirality can be achieved exclusively through chiral-selective reaction rate parameters without any other explicit mechanism for chiral bias. Specifically, we examine an open network of polymerization reactions, where the reaction rates can have chiral-selective values. The reactions are neither autocatalytic nor do they contain explicit enantiomeric cross-inhibition terms. We are thus investigating how rare a set of chiral-selective reaction rates needs to be in order to generate a reasonable amount of chiral bias. We quantify our results adopting a statistical approach: varying both the mean value and the rms dispersion of the relevant reaction rates, we show that moderate to high levels of chiral excess can be achieved with fairly small chiral bias, below 10%. Considering the various unknowns related to prebiotic chemical networks in early Earth and the dependence of reaction rates to environmental properties such as temperature and pressure variations, we argue that homochirality could have been achieved from moderate amounts of chiral selectivity in the reaction rates.
Although it has been notoriously difficult to pin down precisely what is it that makes life so distinctive and remarkable, there is general agreement that its informational aspect is one key property, perhaps the key property. The unique informational narrative of living systems suggests that life may be characterized by context-dependent causal influences, and, in particular, that top-down (or downward) causation-where higher levels influence and constrain the dynamics of lower levels in organizational hierarchies-may be a major contributor to the hierarchal structure of living systems. Here, we propose that the emergence of life may correspond to a physical transition associated with a shift in the causal structure, where information gains direct and context-dependent causal efficacy over the matter in which it is instantiated. Such a transition may be akin to more traditional physical transitions (e.g. thermodynamic phase transitions), with the crucial distinction that determining which phase (non-life or life) a given system is in requires dynamical information and therefore can only be inferred by identifying causal architecture. We discuss some novel research directions based on this hypothesis, including potential measures of such a transition that may be amenable to laboratory study, and how the proposed mechanism corresponds to the onset of the unique mode of (algorithmic) information processing characteristic of living systems.
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