Constraint Closure Drove Major Transitions in the Origins of Life

Mixed anhydrides at the intersection between peptide and RNA autocatalytic sets: evolution of biological coding

We present a scenario for the origin of biological coding, a semiotic relationship between chemical information stored in one location that links to chemical information stored in a separate location. Coding originated from cooperation between two, originally separate, collectively autocatalytic sets (CASs), one for nucleic acids and one for peptides. Upon interaction, a series of RNA folding-directed processes led to their joint cooperativity. The aminoacyl adenylate was the first covalent association made by these two CASs and solidified their interdependence, and is a palimpsest of this era, a relic of the original semiotic relationship between RNA and proteins. Coding was driven by selection pressure to eliminate waste in CASs. Eventually a 1 : 1 relationship between single amino acids and short RNA pieces was established, i.e. the 'genetic code'. The two classes of aaRS enzymes are remnants of the complementary information in two RNA strands, as postulated by Rodin and Ohno. Every stage in the evolution of coding was driven by the downward selection on the components of a system to satisfy the Kantian whole. Coding was engendered because there were two chemically distinct classes of polymers needed for open-ended evolution; systems with only one polymer cannot exhibit this characteristic. Coding is thus synonymous with life as we know it.

Free energy and inference in living systems

Organisms are non-equilibrium, stationary systems self-organized via spontaneous symmetry breaking and undergoing metabolic cycles with broken detailed balance in the environment. The thermodynamic free-energy (FE) principle describes an organism's homeostasis as the regulation of biochemical work constrained by the physical FE cost. By contrast, recent research in neuroscience and theoretical biology explains a higher organism's homeostasis and allostasis as Bayesian inference facilitated by the informational FE. As an integrated approach to living systems, this study presents an FE minimization theory overarching the essential features of both the thermodynamic and neuroscientific FE principles. Our results reveal that the perception and action of animals result from active inference entailed by FE minimization in the brain, and the brain operates as a Schrödinger's machine conducting the neural mechanics of minimizing sensory uncertainty. A parsimonious model suggests that the Bayesian brain develops the optimal trajectories in neural manifolds and induces a dynamic bifurcation between neural attractors in the process of active inference.

Super-Exponential Growth in Models of a Binary String World

The Theory of the Adjacent Possible (TAP) equation has been proposed as an appropriate description of super-exponential growth phenomena, where a phase of slow growth is followed by a rapid increase, leading to a "hockey stick" curve. This equation, initially conceived to describe the growth in time of the number of new types of artifacts, has also been applied to several natural phenomena. A possible drawback is that it may overestimate the number of new artifact types, since it does not take into account the fact that interactions, among existing types, may produce types which have already been previously discovered. We introduce here a Binary String World (BSW) where new string types can be generated by interactions among (at most two) already existing types. We introduce a continuous limit of the TAP equation for the BSW; we solve it analytically and show that it leads to divergence in finite time. We also introduce a criterion to distinguish this type of behavior from the familiar exponential growth, which diverges only as t → ∝. In the BSW, it is possible to directly model the generation of new types, and to check whether the newborns are actually novel types, thus discarding the rediscoveries of already existing types. We show that the type of growth is still TAP-like, rather than exponential, although of course in simulations one never can observes true divergence. We also show that this property is robust with respect to some changes in the model, as long as it deals with types (and not with individuals).

Overcoming the limits of natural computation in biological evolution toward the maximization of system efficiency

The goal-directedness of biological evolution is realized via the anticipatory achievement of the final state of the system that corresponds to the condition of its perfection in self-maintenance and in adaptability. In the course of individual development, a biological system maximizes its power via synergistic effects and becomes able to perform external work most efficiently. In this state, defined as stasis, robust self-maintaining configurations act as attractors resistant to external and internal perturbations. This corresponds to the local energy–time constraints that most efficiently fit the integral optimization of the whole system. In evolution, major evolutionary transitions that establish new states of stasis are achieved via codepoiesis, a process in which the undecided statements of existing coding systems form the basis for the evolutionary unfolding of the system by assigning new values to them. The genetic fixation of this macroevolutionary process leads to new programmes of individual development representing the process of natural computation. The phenomenon of complexification in evolution represents a metasystem transition that results in maximization of a system’s power and in the ability to increase external work performed by the system.

Schrödinger and the Possible Existence of Different Types of Life

Eighty years ago, Nobel Prize-winner physicist Erwin Schrödinger gave three lectures in Dublin’s Trinity College, titled What is Life? The physical aspect of the living cell to explain life in terms of the chemistry and physics laws. Life definitions rely on the cellular theory, which poses in the first place that life is made up of cells. The recent discovery of giant viruses, along with the development of synthetic cells at the beginning of century 21st, has challenged the current idea of what life is. Thus, rather than having arrived at a close answer to Schrödinger’s question, modern biology has touched down at a novel scenario in which several types of life—as opposed to only one—actually might exist on Earth and possibly the Universe. Eighty years after the Dublin lectures, the Schrödinger question could be: “What are lives”?