Computational studies on conditions of the emergence of autopoietic protocells

Constructal thermodynamics and its semantic ontology in autopoietic, digital, and computational architectural and urban space open systems

This paper explores the intersections of constructal thermodynamics, and its semantic ontology within the context of autopoietic, digital and computational design in protocell inspired numerical architectural and urban narratives that are examined here as open systems. Constructal law is the thermodynamic theory based on the analysis of fluxes across the boundaries of an open system. Protocells, as dynamic, autopoietic and adaptive open finite size systems, serve in this paper as a compelling metaphor and design model for responsive and sustainable manmade architectural and urban environments. The ability of protocells to harness energy, minimize entropy, and adapt to environmental changes mirrors the principles of constructal thermodynamics, which govern the flow and distribution of resources in complex self-organizing information open systems in nature. By applying these principles to digital architecture, this study investigates how relational dynamics between spaces, materials, and functions can create adaptive designs that "go with the flow" of ecological and cultural systems. The research demonstrates using the Gouy-Stodola theorem as a variational principle, how protocell-inspired processes facilitate exergy-efficient designs, minimizing waste while maximizing resilience and flexibility. The present paper argues -through an applied case study- for a paradigm where protocell digital architecture serves not only as an ecological and material model but mainly as a spatial narrative driver, blending constructal and digital tools with cultural mythos. Finally, this paper exploring simultaneously the semantic complexity and ontology of such systems, in turn, connects these constructal driven digital designs to broader poly-narratives, embedding cultural, symbolic, philosophical and functional predicates into architectural forms.

Provenance of life: Chemical autonomous agents surviving through associative learning

We present a benchmark study of autonomous, chemical agents exhibiting associative learning of an environmental feature. Associative learning systems have been widely studied in cognitive science and artificial intelligence but are most commonly implemented in highly complex or carefully engineered systems, such as animal brains, artificial neural networks, DNA computing systems, and gene regulatory networks, among others. The ability to encode environmental information and use it to make simple predictions is a benchmark of biological resilience and underpins a plethora of adaptive responses in the living hierarchy, spanning prey animal species anticipating the arrival of predators to epigenetic systems in microorganisms learning environmental correlations. Given the ubiquitous and essential presence of learning behaviors in the biosphere, we aimed to explore whether simple, nonliving dissipative structures could also exhibit associative learning. Inspired by previous modeling of associative learning in chemical networks, we simulated simple systems composed of long- and short-term memory chemical species that could encode the presence or absence of temporal correlations between two external species. The ability to learn this association was implemented in Gray-Scott reaction-diffusion spots, emergent chemical patterns that exhibit self-replication and homeostasis. With the novel ability of associative learning, we demonstrate that simple chemical patterns can exhibit a broad repertoire of lifelike behavior, paving the way for in vitro studies of autonomous chemical learning systems, with potential relevance to artificial life, origins of life, and systems chemistry. The experimental realization of these learning behaviors in protocell or coacervate systems could advance a new research direction in astrobiology, since our system significantly reduces the lower bound on the required complexity for autonomous chemical learning.

Motility at the origin of life: its characterization and a model

Due to recent advances in synthetic biology and artificial life, the origin of life is currently a hot topic of research. We review the literature and argue that the two traditionally competing replicator-first and metabolism-first approaches are merging into one integrated theory of individuation and evolution. We contribute to the maturation of this more inclusive approach by highlighting some problematic assumptions that still lead to an ximpoverished conception of the phenomenon of life. In particular, we argue that the new consensus has so far failed to consider the relevance of intermediate time scales. We propose that an adequate theory of life must account for the fact that all living beings are situated in at least four distinct time scales, which are typically associated with metabolism, motility, development, and evolution. In this view, self-movement, adaptive behavior, and morphological changes could have already been present at the origin of life. In order to illustrate this possibility, we analyze a minimal model of lifelike phenomena, namely, of precarious, individuated, dissipative structures that can be found in simple reaction-diffusion systems. Based on our analysis, we suggest that processes on intermediate time scales could have already been operative in prebiotic systems. They may have facilitated and constrained changes occurring in the faster- and slower-paced time scales of chemical self-individuation and evolution by natural selection, respectively.

Achievements and open questions in the self-reproduction of vesicles and synthetic minimal cells

Supramolecular chemistry was enriched, about twenty years ago, by the discovery of the self-reproduction of micelles and vesicles. The dynamic aspects and complexity of these systems makes them good models for biological compartments. For example, the self-reproduction of vesicles suggests that the growth in size and number of a vesicle population resembles the pattern of living cells in several aspects, but it take place solely due to physical forces. Several reports demonstrate that reverse micelles, micelles, sub-micrometric and giant vesicles can self-reproduce, generating new particles at the expenses of a suitable precursor. Recently, similar studies are in progress on more complex vesicle-based systems, namely semi-synthetic minimal cells. These are artificial cell-like compartments that are built by filling liposomes with the minimal number of biomolecules, such as DNA, ribosomes, enzymes, etc., in order to construct a living cell in the laboratory. This approach aims to investigate the minimal requirements for molecular systems in order to display some living properties, while it finds relevance in origins of life studies and in synthetic (constructive) biology.

Intramolecular RNA replicase: possibly the first self-replicating molecule in the RNA world

Although there is more and more evidence suggested the existence of an RNA World during the origin of life, the scenario concerning the origin of the RNA World remains blurry. Usually it is speculated that it originated from a prebiotic nucleotide pool, during which a self-replicating RNA synthesis ribozyme may have emerged as the first ribozyme - the RNA replicase. However, there is yet no ersuasive supposition for the mechanism for the self-favouring feature of the replicase, thus the speculation remains unconvincing. Here we suggest that intramolecular catalysis is a possible solution. Two RNA synthesis ribozymes may be integrated into one RNA molecule, as two functional domains which could catalyze the copy of each other. Thus the RNA molecule could self-replicate and be referred to as "intramolecular replicase" here. Computational simulation to get insight into the dynamic mechanism of emergence of the intramolecular replicase from a nucleotide pool is valuable and would be included in a following work of our group.