Organization of chemical reactions into dividing and metabolizing units: the chemotons

The cell as a semiotic system that realizes closure to efficient causation: The semiotic (M, R) system

Robert Rosen defines organisms as material systems closed to efficient causation, and proposes the replicative (M, R) system as a model for them. Recently, we presented a cell model that realizes Rosen's formal model, based on Hofmeyr's analysis of the functional organization of cell biochemistry and on Rosen's construction of the replication function. In this article we propose a cell model that, starting from the same biochemical processes, replaces the replication function with a set of semiotic relations between some of the elements that participate in cellular processes. The result is a cell model that constitutes a semiotic system that realizes closure to efficient causation: a semiotic (M, R) system. We compare the models of closure that correspond to the replicative (M, R) system and the semiotic (M, R) system. Additionally, we discuss the role that the genetic code and protein synthesis play in the semiotic closure to efficient causation. Finally, we outline the method to extend this analysis to more complex organisms.

Heritable epigenetic changes are constrained by the dynamics of regulatory architectures

Interacting molecules create regulatory architectures that can persist despite turnover of molecules. Although epigenetic changes occur within the context of such architectures, there is limited understanding of how they can influence the heritability of changes. Here, I develop criteria for the heritability of regulatory architectures and use quantitative simulations of interacting regulators parsed as entities, their sensors, and the sensed properties to analyze how architectures influence heritable epigenetic changes. Information contained in regulatory architectures grows rapidly with the number of interacting molecules and its transmission requires positive feedback loops. While these architectures can recover after many epigenetic perturbations, some resulting changes can become permanently heritable. Architectures that are otherwise unstable can become heritable through periodic interactions with external regulators, which suggests that mortal somatic lineages with cells that reproducibly interact with the immortal germ lineage could make a wider variety of architectures heritable. Differential inhibition of the positive feedback loops that transmit regulatory architectures across generations can explain the gene-specific differences in heritable RNA silencing observed in the nematode Caenorhabditis elegans. More broadly, these results provide a foundation for analyzing the inheritance of epigenetic changes within the context of the regulatory architectures implemented using diverse molecules in different living systems.

The tri-flow adaptiveness of codes in major evolutionary transitions

Life codes increase in both number and variety with biological complexity. Although our knowledge of codes is constantly expanding, the evolutionary progression of organic, neural, and cultural codes in response to selection pressure remains poorly understood. Greater clarification of the selective mechanisms is achieved by investigating how major evolutionary transitions reduce spatiotemporal and energetic constraints on transmitting heritable code to offspring. Evolution toward less constrained flows is integral to enduring flow architecture everywhere, in both engineered and natural flow systems. Beginning approximately 4 billion years ago, the most basic level for transmitting genetic material to offspring was initiated by protocell division. Evidence from ribosomes suggests that protocells transmitted comma-free or circular codes, preceding the evolution of standard genetic code. This rudimentary information flow within protocells is likely to have first emerged within the geo-energetic and geospatial constraints of hydrothermal vents. A broad-gauged hypothesis is that major evolutionary transitions overcame such constraints with tri-flow adaptations. The interconnected triple flows incorporated energy-converting, spatiotemporal, and code-based informational dynamics. Such tri-flow adaptations stacked sequence splicing code on top of protein-DNA recognition code in eukaryotes, prefiguring the transition to sexual reproduction. Sex overcame the spatiotemporal-energetic constraints of binary fission with further code stacking. Examples are tubulin code and transcription initiation code in vertebrates. In a later evolutionary transition, language reduced metabolic-spatiotemporal constraints on inheritance by stacking phonetic, phonological, and orthographic codes. In organisms that reproduce sexually, each major evolutionary transition is shown to be a tri-flow adaptation that adds new levels of code-based informational exchange. Evolving biological complexity is also shown to increase the nongenetic transmissibility of code.

Small-molecule autocatalysis drives compartment growth, competition and reproduction

Sustained autocatalysis coupled to compartment growth and division is a key step in the origin of life, but an experimental demonstration of this phenomenon in an artificial system has previously proven elusive. We show that autocatalytic reactions within compartments-when autocatalysis, and reactant and solvent exchange outpace product exchange-drive osmosis and diffusion, resulting in compartment growth. We demonstrate, using the formose reaction compartmentalized in aqueous droplets in an emulsion, that compartment volume can more than double. Competition for a common reactant (formaldehyde) causes variation in droplet growth rate based on the composition of the surrounding droplets. These growth rate variations are partially transmitted after selective division of the largest droplets by shearing, which converts growth-rate differences into differences in droplet frequency. This shows how a combination of properties of living systems (growth, division, variation, competition, rudimentary heredity and selection) can arise from simple physical-chemical processes and may have paved the way for the emergence of evolution by natural selection.

Multistable Protocells Can Aid the Evolution of Prebiotic Autocatalytic Sets

We present a simple mathematical model that captures the evolutionary capabilities of a prebiotic compartment or protocell. In the model, the protocell contains an autocatalytic set whose chemical dynamics is coupled to the growth-division dynamics of the compartment. Bistability in the dynamics of the autocatalytic set results in a protocell that can exist with two distinct growth rates. Stochasticity in chemical reactions plays the role of mutations and causes transitions from one growth regime to another. We show that the system exhibits 'natural selection', where a 'mutant' protocell in which the autocatalytic set is active arises by chance in a population of inactive protocells, and then takes over the population because of its higher growth rate or 'fitness'. The work integrates three levels of dynamics: intracellular chemical, single protocell, and population (or ecosystem) of protocells.

Heritable epigenetic changes are constrained by the dynamics of regulatory architectures

Interacting molecules create regulatory architectures that can persist despite turnover of molecules. Although epigenetic changes occur within the context of such architectures, there is limited understanding of how they can influence the heritability of changes. Here I develop criteria for the heritability of regulatory architectures and use quantitative simulations of interacting regulators parsed as entities, their sensors and the sensed properties to analyze how architectures influence heritable epigenetic changes. Information contained in regulatory architectures grows rapidly with the number of interacting molecules and its transmission requires positive feedback loops. While these architectures can recover after many epigenetic perturbations, some resulting changes can become permanently heritable. Such stable changes can (1) alter steady-state levels while preserving the architecture, (2) induce different architectures that persist for many generations, or (3) collapse the entire architecture. Architectures that are otherwise unstable can become heritable through periodic interactions with external regulators, which suggests that the evolution of mortal somatic lineages with cells that reproducibly interact with the immortal germ lineage could make a wider variety of regulatory architectures heritable. Differential inhibition of the positive feedback loops that transmit regulatory architectures across generations can explain the gene-specific differences in heritable RNA silencing observed in the nematode C. elegans, which range from permanent silencing to recovery from silencing within a few generations and subsequent resistance to silencing. More broadly, these results provide a foundation for analyzing the inheritance of epigenetic changes within the context of the regulatory architectures implemented using diverse molecules in different living systems.

Decorated Vesicles as Prebiont Systems (a Hypothesis)

Decorated vesicles in deep, seafloor basalts form abiotically, but show at least four life-analogous features, which makes them a candidate for origin of life research. These features are a physical enclosure, carbon-assimilatory catalysts, semi-permeable boundaries, and a source of usable energy. The nanometer-to-micron-sized spherules on the inner walls of decorated vesicles are proposed to function as mineral proto-enzymes. Chemically, these structures resemble synthetic FeS clusters shown to convert CO2, CO and H2 into methane, formate, and acetate. Secondary phyllosilicate minerals line the vesicles' inner walls and can span openings in the vesicles and thus can act as molecular sieves between the vesicles' interior and the surrounding aquifer. Lastly, basalt glass in the vesicle walls takes up protons, which replace cations in the silicate framework. This results in an inward proton flux, reciprocal outward flux of metal cations, more alkaline pH inside the vesicle than outside, and production of more phyllosilicates. Such life-like features could have been exploited to move decorated vesicles toward protolife systems. Decorated vesicles are proposed as study models of prebiotic systems that are expected to have existed on the early Earth and Earth-like exoplanets. Their analysis can lead to better understanding of changes in planetary geocycles during the origin of life.

The protometabolic nature of prebiotic chemistry

The field of prebiotic chemistry has been dedicated over decades to finding abiotic routes towards the molecular components of life. There is nowadays a handful of prebiotically plausible scenarios that enable the laboratory synthesis of most amino acids, fatty acids, simple sugars, nucleotides and core metabolites of extant living organisms. The major bottleneck then seems to be the self-organization of those building blocks into systems that can self-sustain. The purpose of this tutorial review is having a close look, guided by experimental research, into the main synthetic pathways of prebiotic chemistry, suggesting how they could be wired through common intermediates and catalytic cycles, as well as how recursively changing conditions could help them engage in self-organized and dissipative networks/assemblies (i.e., systems that consume chemical or physical energy from their environment to maintain their internal organization in a dynamic steady state out of equilibrium). In the article we also pay attention to the implications of this view for the emergence of homochirality. The revealed connectivity between those prebiotic routes should constitute the basis for a robust research program towards the bottom-up implementation of protometabolic systems, taken as a central part of the origins-of-life problem. In addition, this approach should foster further exploration of control mechanisms to tame the combinatorial explosion that typically occurs in mixtures of various reactive precursors, thus regulating the functional integration of their respective chemistries into self-sustaining protocellular assemblies.

Using neurons to maintain autonomy: Learning from C. elegans

Understanding how biological organisms are autonomous-maintain themselves far from equilibrium through their own activities-requires understanding how they regulate those activities. In multicellular animals, such control can be exercised either via endocrine signaling through the vasculature or via neurons. In C. elegans this control is exercised by a well-delineated relatively small but distributed nervous system that relies on both chemical and electric transmission of signals. This system provides resources to integrate information from multiple sources as needed to maintain the organism. Especially important for the exercise of neural control are neuromodulators, which we present as setting agendas for control through more traditional electrical signaling. To illustrate how the C. elegans nervous system integrates multiple sources of information in controlling activities important for autonomy, we focus on feeding behavior and responses to adverse conditions. We conclude by considering how a distributed nervous system without a centralized controller is nonetheless adequate for autonomy.

Semigroup models for biochemical reaction networks

The catalytic reaction system (CRS) formalism by Hordijk and Steel is a versatile method to model autocatalytic biochemical reaction networks. It is particularly suited, and has been widely used, to study self-sustainment and self-generation properties. Its distinguishing feature is the explicit assignment of a catalytic function to chemicals that are part of the system. In this work, it is shown that the subsequent and simultaneous catalytic functions give rise to an algebraic structure of a semigroup with the additional compatible operation of idempotent addition and a partial order. The aim of this article is to demonstrate that such semigroup models are a natural setup to describe and analyze self-sustaining CRS. The basic algebraic properties of the models are established and the notion of the function of any set of chemicals on the whole CRS is made precise. This leads to a natural discrete dynamical system on the power set of chemicals, which is obtained by iteratively considering the self-action on a set of chemicals by its own function. The fixed points of this dynamical system are proven to correspond to self-sustaining sets of chemicals, which are functionally closed. Finally, as the main application, a theorem on the maximal self-sustaining set and a structure theorem on the set of functionally closed self-sustaining sets of chemicals are proven.

An algebraic characterization of self-generating chemical reaction networks using semigroup models

The ability of a chemical reaction network to generate itself by catalyzed reactions from constantly present environmental food sources is considered a fundamental property in origin-of-life research. Based on Kaufmann's autocatalytic sets, Hordijk and Steel have constructed the versatile formalism of catalytic reaction systems (CRS) to model and to analyze such self-generating networks, which they named reflexively autocatalytic and food-generated. Recently, it was established that the subsequent and simultaenous catalytic functions of the chemicals of a CRS give rise to an algebraic structure, termed a semigroup model. The semigroup model allows to naturally consider the function of any subset of chemicals on the whole CRS. This gives rise to a generative dynamics by iteratively applying the function of a subset to the externally supplied food set. The fixed point of this dynamics yields the maximal self-generating set of chemicals. Moreover, the set of all functionally closed self-generating sets of chemicals is discussed and a structure theorem for this set is proven. It is also shown that a CRS which contains self-generating sets of chemicals cannot have a nilpotent semigroup model and thus a useful link to the combinatorial theory of finite semigroups is established. The main technical tool introduced and utilized in this work is the representation of the semigroup elements as decorated rooted trees, allowing to translate the generation of chemicals from a given set of resources into the semigroup language.

The transition from animal to human culture-simulating the social protocell hypothesis

The origin of human cumulative culture is commonly envisioned as the appearance (some 2.0-2.5 million years ago) of a capacity to faithfully copy the know-how that underpins socially learned traditions. While certainly plausible, this story faces a steep 'startup problem'. For example, it presumes that ape-like early Homo possessed specialized cognitive capabilities for faithful know-how copying and that early toolmaking actually required such a capacity. The social protocell hypothesis provides a leaner story, where cumulative culture may have originated even earlier-as cumulative systems of non-cumulative traditions ('institutions' and 'cultural lifestyles'), via an emergent group-level channel of cultural inheritance. This channel emerges as a side-effect of a specific but in itself unremarkable suite of social group behaviours. It is independent of faithful know-how copying, and an ancestral version is argued to persist in Pan today. Hominin cultural lifestyles would thereby have gained in complexity and sophistication, eventually becoming independent units of selection (socionts) via a cultural evolutionary transition in individuality, abstractly similar to the origin of early cells. We here explore this hypothesis by simulating its basic premises. The model produces the expected behaviour and reveals several additional and non-trivial phenomena as fodder for future work. This article is part of the theme issue 'Human socio-cultural evolution in light of evolutionary transitions'.

Using enactive robotics to think outside of the problem-solving box: How sensorimotor contingencies constrain the forms of emergent autononomous habits

We suggest that the influence of biology in 'biologically inspired robotics' can be embraced at a deeper level than is typical, if we adopt an enactive approach that moves the focus of interest from how problems are solved to how problems emerge in the first place. In addition to being inspired by mechanisms found in natural systems or by evolutionary design principles directed at solving problems posited by the environment, we can take inspiration from the precarious, self-maintaining organization of living systems to investigate forms of cognition that are also precarious and self-maintaining and that thus also, like life, have their own problems that must be be addressed if they are to persist. In this vein, we use a simulation to explore precarious, self-reinforcing sensorimotor habits as a building block for a robot's behavior. Our simulations of simple robots controlled by an Iterative Deformable Sensorimotor Medium demonstrate the spontaneous emergence of different habits, their re-enactment and the organization of an ecology of habits within each agent. The form of the emergent habits is constrained by the sensory modality of the robot such that habits formed under one modality (vision) are more similar to each other than they are to habits formed under another (audition). We discuss these results in the wider context of: (a) enactive approaches to life and mind, (b) sensorimotor contingency theory, (c) adaptationist vs. structuralist explanations in biology, and (d) the limits of functionalist problem-solving approaches to (artificial) intelligence.

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.

Organization needs organization: Understanding integrated control in living organisms

Organization figures centrally in the understanding of biological systems advanced by both new mechanists and proponents of the autonomy framework. The new mechanists focus on how components of mechanisms are organized to produce a phenomenon and emphasize productive continuity between these components. The autonomy framework focuses on how the components of a biological system are organized in such a way that they contribute to the maintenance of the organisms that produce them. In this paper we analyze and compare these two accounts of organization and argue that understanding biological organisms as cohesively integrated systems benefits from insights from both. To bring together the two accounts, we focus on the notions of control and regulation as bridge concepts. We start from a characterization of biological mechanisms in terms of constraints and focus on a specific type of mechanism, control mechanisms, that operate on other mechanisms on the basis of measurements of variables in the system and its environment. Control mechanisms are characterized by their own set of constraints that enable them to sense conditions, convey signals, and effect changes on constraints in the controlled mechanism. They thereby allow living organisms to adapt to internal and external variations and to coordinate their parts in such a manner as to maintain viability. Because living organisms contain a vast number of control mechanisms, a central challenge is to understand how they are themselves organized. With the support of examples from both unicellular and multicellular systems we argue that control mechanisms are organized heterarchically, and we discuss how this type of control architecture can, without invoking top-down and centralized forms of organizations, succeed in coordinating internal activities of organisms.

An open source computational workflow for the discovery of autocatalytic networks in abiotic reactions

A central question in origins of life research is how non-entailed chemical processes, which simply dissipate chemical energy because they can do so due to immediate reaction kinetics and thermodynamics, enabled the origin of highly-entailed ones, in which concatenated kinetically and thermodynamically favorable processes enhanced some processes over others. Some degree of molecular complexity likely had to be supplied by environmental processes to produce entailed self-replicating processes. The origin of entailment, therefore, must connect to fundamental chemistry that builds molecular complexity. We present here an open-source chemoinformatic workflow to model abiological chemistry to discover such entailment. This pipeline automates generation of chemical reaction networks and their analysis to discover novel compounds and autocatalytic processes. We demonstrate this pipeline's capabilities against a well-studied model system by vetting it against experimental data. This workflow can enable rapid identification of products of complex chemistries and their underlying synthetic relationships to help identify autocatalysis, and potentially self-organization, in such systems. The algorithms used in this study are open-source and reconfigurable by other user-developed workflows.

Fusion-Induced Growth of Biomimetic Polymersomes: Behavior of Poly(dimethylsiloxane)-Poly(ethylene oxide) Vesicles in Saline Solutions Under High Agitation

Giant unilamellar vesicles serve as membrane models and primitive mockups of natural cells. With respect to the latter use, amphiphilic polymers can be used to replace phospholipids in order to introduce certain favorable properties, ultimately allowing for the creation of truly synthetic cells. These new properties also enable the employment of new preparation procedures that are incompatible with the natural amphiphiles. Whereas the growth of lipid compartments to micrometer dimensions has been well established, growth of their synthetic analogs remains underexplored. Here, the influence of experimental parameters like salt type/concentration and magnitude of agitation on the fusion of nanometer-sized vesicles made of poly(dimethylsiloxane)-poly(ethylene oxide) graft copolymer (PDMS-g-PEO) is investigated in detail. To this end, dynamic light scattering, microscopy, and membrane mixing assays are employed, and the process at different time and length scales is analyzed. This optimized method is used as an easy tool to obtain giant vesicles, equipped with membrane and cytosolic biomachinery, in the presence of salts at physiological concentrations.

Automated Exploration of Prebiotic Chemical Reaction Space: Progress and Perspectives

Prebiotic chemistry often involves the study of complex systems of chemical reactions that form large networks with a large number of diverse species. Such complex systems may have given rise to emergent phenomena that ultimately led to the origin of life on Earth. The environmental conditions and processes involved in this emergence may not be fully recapitulable, making it difficult for experimentalists to study prebiotic systems in laboratory simulations. Computational chemistry offers efficient ways to study such chemical systems and identify the ones most likely to display complex properties associated with life. Here, we review tools and techniques for modelling prebiotic chemical reaction networks and outline possible ways to identify self-replicating features that are central to many origin-of-life models.

When Is a Reaction Network a Metabolism? Criteria for Simple Metabolisms That Support Growth and Division of Protocells

With the aim of better understanding the nature of metabolism in the first cells and the relationship between the origin of life and the origin of metabolism, we propose three criteria that a chemical reaction system must satisfy in order to constitute a metabolism that would be capable of sustaining growth and division of a protocell. (1) Biomolecules produced by the reaction system must be maintained at high concentration inside the cell while they remain at low or zero concentration outside. (2) The total solute concentration inside the cell must be higher than outside, so there is a positive osmotic pressure that drives cell growth. (3) The metabolic rate (i.e., the rate of mass throughput) must be higher inside the cell than outside. We give examples of small-molecule reaction systems that satisfy these criteria, and others which do not, firstly considering fixed-volume compartments, and secondly, lipid vesicles that can grow and divide. If the criteria are satisfied, and if a supply of lipid is available outside the cell, then continued growth of membrane surface area occurs alongside the increase in volume of the cell. If the metabolism synthesizes more lipid inside the cell, then the membrane surface area can increase proportionately faster than the cell volume, in which case cell division is possible. The three criteria can be satisfied if the reaction system is bistable, because different concentrations can exist inside and out while the rate constants of all the reactions are the same. If the reaction system is monostable, the criteria can only be satisfied if there is a reason why the rate constants are different inside and out (for example, the decay rates of biomolecules are faster outside, or the formation rates of biomolecules are slower outside). If this difference between inside and outside does not exist, a monostable reaction system cannot sustain cell growth and division. We show that a reaction system for template-directed RNA polymerization can satisfy the requirements for a metabolism, even if the small-molecule reactions that make the single nucleotides do not.

"Minimal metabolism": A key concept to investigate the origins and nature of biological systems

The systems view on life and its emergence from complex chemistry has remarkably increased the scientific attention on metabolism in the last two decades. However, during this time there has not been much theoretical discussion on what constitutes a metabolism and what role it actually played in biogenesis. A critical and updated review on the topic is here offered, including some references to classical models from last century, but focusing more on current and future research. Metabolism is considered as intrinsically related to the living but not necessarily equivalent to it. More precisely, the idea of "minimal metabolism", in contrast to previous, top-down conceptions, is formulated as a heuristic construct, halfway between chemistry and biology. Thus, rather than providing a complete or final characterization of metabolism, our aim is to encourage further investigations on it, particularly in the context of life's origin, for which some concrete methodological suggestions are provided. Also see the video abstract here: https://youtu.be/DP7VMKk2qpA.

Genetically controlled membrane synthesis in liposomes

Lipid membranes, nucleic acids, proteins, and metabolism are essential for modern cellular life. Synthetic systems emulating the fundamental properties of living cells must therefore be built upon these functional elements. In this work, phospholipid-producing enzymes encoded in a synthetic minigenome are cell-free expressed within liposome compartments. The de novo synthesized metabolic pathway converts precursors into a variety of lipids, including the constituents of the parental liposome. Balanced production of phosphatidylethanolamine and phosphatidylglycerol is realized, owing to transcriptional regulation of the activity of specific genes combined with a metabolic feedback mechanism. Fluorescence-based methods are developed to image the synthesis and membrane incorporation of phosphatidylserine at the single liposome level. Our results provide experimental evidence for DNA-programmed membrane synthesis in a minimal cell model. Strategies are discussed to alleviate current limitations toward effective liposome growth and self-reproduction.

How to Build a Biological Machine Using Engineering Materials and Methods

We present work in 3D printing electric motors from basic materials as the key to building a self-replicating machine to colonise the Moon. First, we explore the nature of the biological realm to ascertain its essence, particularly in relation to the origin of life when the inanimate became animate. We take an expansive view of this to ascertain parallels between the biological and the manufactured worlds. Life must have emerged from the available raw material on Earth and, similarly, a self-replicating machine must exploit and leverage the available resources on the Moon. We then examine these lessons to explore the construction of a self-replicating machine using a universal constructor. It is through the universal constructor that the actuator emerges as critical. We propose that 3D printing constitutes an analogue of the biological ribosome and that 3D printing may constitute a universal construction mechanism. Following a description of our progress in 3D printing motors, we suggest that this engineering effort can inform biology, that motors are a key facet of living organisms and illustrate the importance of motors in biology viewed from the perspective of engineering (in the Feynman spirit of “what I cannot create, I cannot understand”).

Towards Design of Self-Organizing Biomimetic Systems

The ability of designing biosynthetic systems with well-defined functional biomodules from scratch is an ambitious and revolutionary goal to deliver innovative, engineered solutions to future challenges in biotechnology and process systems engineering. In this work, several key challenges including modularization, functional biomodule identification, and assembly are discussed. In addition, an in silico protocell modeling approach is presented as a foundation for a computational model-based toolkit for rational analysis and modular design of biomimetic systems.

Defining Lyfe in the Universe: From Three Privileged Functions to Four Pillars

Motivated by the need to paint a more general picture of what life is-and could be-with respect to the rest of the phenomena of the universe, we propose a new vocabulary for astrobiological research. Lyfe is defined as any system that fulfills all four processes of the living state, namely: dissipation, autocatalysis, homeostasis, and learning. Life is defined as the instance of lyfe that we are familiar with on Earth, one that uses a specific organometallic molecular toolbox to record information about its environment and achieve dynamical order by dissipating certain planetary disequilibria. This new classification system allows the astrobiological community to more clearly define the questions that propel their research-e.g., whether they are developing a historical narrative to explain the origin of life (on Earth), or a universal narrative for the emergence of lyfe, or whether they are seeking signs of life specifically, or lyfe at large across the universe. While the concept of "life as we don't know it" is not new, the four pillars of lyfe offer a novel perspective on the living state that is indifferent to the particular components that might produce it.

Glycemia Regulation: From Feedback Loops to Organizational Closure

Endocrinologists apply the idea of feedback loops to explain how hormones regulate certain bodily functions such as glucose metabolism. In particular, feedback loops focus on the maintenance of the plasma concentrations of glucose within a narrow range. Here, we put forward a different, organicist perspective on the endocrine regulation of glycaemia, by relying on the pivotal concept of closure of constraints. From this perspective, biological systems are understood as organized ones, which means that they are constituted of a set of mutually dependent functional structures acting as constraints, whose maintenance depends on their reciprocal interactions. Closure refers specifically to the mutual dependence among functional constraints in an organism. We show that, when compared to feedback loops, organizational closure can generate much richer descriptions of the processes and constraints at play in the metabolism and regulation of glycaemia, by making explicit the different hierarchical orders involved. We expect that the proposed theoretical framework will open the way to the construction of original mathematical models, which would provide a better understanding of endocrine regulation from an organicist perspective.

The Informational Substrate of Chemical Evolution: Implications for Abiogenesis

A key aspect of biological evolution is the capacity of living systems to process information, coded in deoxyribonucleic acid (DNA), and used to direct how the cell works. The overall picture that emerges today from fields such as developmental, synthetic, and systems biology indicates that information processing in cells occurs through a hierarchy of genes regulating the activity of other genes through complex metabolic networks. There is an implicit semiotic character in this way of dealing with information, based on functional molecules that act as signs to achieve self-regulation of the whole network. In contrast to cells, chemical systems are not thought of being able to process information, yet they must have preceded biological organisms, and evolved into them. Hence, there must have been prebiotic molecular assemblies that could somehow process information, in order to regulate their own constituent reactions and supramolecular organization processes. The purpose of this essay is then to reflect about the distinctive features of information in living and non-living matter, and on how the capacity of biological organisms for information processing was possibly rooted in a particular type of chemical systems (here referred to as autonomous chemical systems), which could self-sustain and reproduce through organizational closure of their molecular building blocks.

Template-Directed Nonenzymatic Primer Extension Using 2-Methylimidazole-Activated Morpholino Derivatives of Guanosine and Cytidine

Efforts to develop self-replicating nucleic acids have led to insights into the origin of life and have also suggested potential pathways to the design of artificial life forms based on non-natural nucleic acids. The template-directed nonenzymatic polymerization of activated ribonucleotide monomers is generally slow because of the relatively weak nucleophilicity of the primer 3'-hydroxyl. To circumvent this problem, several nucleic acids based on amino-sugar nucleotides have been studied, and as expected, the more-nucleophilic amine generally results in faster primer extension. Extending this logic, we have chosen to study morpholino nucleic acid (MoNA), because the secondary amine of the morpholino-nucleotides is expected to be highly nucleophilic. We describe the synthesis of 2-methylimidazole-activated MoNA monomers from their corresponding ribonucleoside 5'-monophosphates and the synthesis of an RNA primer with a terminal MoNA nucleotide. We show that the activated G and C MoNA monomers enable rapid and efficient extension of the morpholino-terminated primer on homopolymeric and mixed-sequenced RNA templates. Our results show that MoNA is a non-natural informational polymer that is worthy of further study as a candidate self-replicating material.

Primordial sex facilitates the emergence of evolution

Compartments are ubiquitous throughout biology, and they have very likely played a crucial role at the origin of life. Here we assume that a protocell, which is a compartment enclosing functional components, requires N such components in order to be evolvable. We calculate the timescale in which a minimal evolvable protocell is produced. We show that when protocells fuse and share information, the timescales polynomially in N By contrast, in the absence of fusion, the worst-case scenario is exponential in N We discuss the implications of this result for the origin of life and other biological processes.

Directed Growth of Biomimetic Microcompartments

Contemporary biological cells are sophisticated and highly compartmentalized. Compartmentalization is an essential principle of prebiotic life as well as a key feature in bottom-up synthetic biology research. In this review, the dynamic growth of compartments as an essential prerequisite for enabling self-reproduction as a fundamental life process is discussed. The micrometer-sized compartments are focused on due to their cellular dimensions. Two types of compartments are considered, membraneless droplets and membrane-bound microcompartments. Growth mechanisms of aqueous droplets such as protein (condensates) or macromolecule-rich droplets (aqueous two phase systems) and coacervates are discussed, for which growth occurs via Ostwald ripening or coalescence. For membrane-bound compartments, vesicles are considered, which are composed of fatty acids, lipids, or polymers, where directed growth can occur via fusion or uptake of material from the surrounding. The development of novel approaches for growth of biomimetic microcompartments can eventually be utilized to construct new synthetic cells.

Gene-Expressing Liposomes as Synthetic Cells for Molecular Communication Studies

The bottom-up branch of synthetic biology includes-among others-innovative studies that combine cell-free protein synthesis with liposome technology to generate cell-like systems of minimal complexity, often referred to as synthetic cells. The functions of this type of synthetic cell derive from gene expression, hence they can be programmed in a modular, progressive and customizable manner by means of ad hoc designed genetic circuits. This experimental scenario is rapidly expanding and synthetic cell research already counts numerous successes. Here, we present a review focused on the exchange of chemical signals between liposome-based synthetic cells (operating by gene expression) and biological cells, as well as between two populations of synthetic cells. The review includes a short presentation of the "molecular communication technologies," briefly discussing their promises and challenges.

Is Research on "Synthetic Cells" Moving to the Next Level?

"Synthetic cells" research focuses on the construction of cell-like models by using solute-filled artificial microcompartments with a biomimetic structure. In recent years this bottom-up synthetic biology area has considerably progressed, and the field is currently experiencing a rapid expansion. Here we summarize some technical and theoretical aspects of synthetic cells based on gene expression and other enzymatic reactions inside liposomes, and comment on the most recent trends. Such a tour will be an occasion for asking whether times are ripe for a sort of qualitative jump toward novel SC prototypes: is research on "synthetic cells" moving to a next level?

Autocatalytic Networks at the Basis of Life's Origin and Organization

Life is more than the sum of its constituent molecules. Living systems depend on a particular chemical organization, i.e., the ways in which their constituent molecules interact and cooperate with each other through catalyzed chemical reactions. Several abstract models of minimal life, based on this idea of chemical organization and also in the context of the origin of life, were developed independently in the 1960s and 1970s. These models include hypercycles, chemotons, autopoietic systems, (M,R)-systems, and autocatalytic sets. We briefly compare these various models, and then focus more specifically on the concept of autocatalytic sets and their mathematical formalization, RAF theory. We argue that autocatalytic sets are a necessary (although not sufficient) condition for life-like behavior. We then elaborate on the suggestion that simple inorganic molecules like metals and minerals may have been the earliest catalysts in the formation of prebiotic autocatalytic sets, and how RAF theory may also be applied to systems beyond chemistry, such as ecology, economics, and cognition.

The origin and early evolution of life in chemical composition space

Life can be viewed as a localized chemical system that sits in the basin of attraction of a metastable dynamical attractor state that remains out of equilibrium with the environment. To explore the implications of this conception, I introduce an abstract coordinate system, chemical composition (CC Space), which summarizes the degree to which chemical systems are out of equilibrium with the bulk environment. A system's chemical disequilibrium (CD) is defined to be proportional to the Euclidean distance between the composition of a small region of physical space, a pixel, and the origin of CC space. Such a model implies that new living states arise through chance changes in local chemical concentration ("mutations") that cause chemical systems to move in CC space and enter the basin of attraction of a life state. The attractor of a life state comprises an autocatalytic set of chemicals whose essential ("keystone") species are produced at a higher rate than they are lost to the environment by diffusion, such that spatial growth of the life state is expected. This framework suggests that new life states are most likely to form at the interface between different physical phases, where the rate of diffusion of keystone species is tied to the low-diffusion regime, whereas food and waste products are subject to the more diffusive regime. Once life nucleates, for example on a mineral surface, it will tend to grow and generate variants as a result of additional mutations that find alternative life states. By jumping from life state to life state, systems can eventually occupy areas of CC space that are too far out of equilibrium with the environment to ever arise in a single mutational step. Furthermore, I propose that variation in the capacity of different surface associated life states to persist and compete may systematically favor states that have higher chemical disequilibrium. The model also suggests a simple and predictable path from surface-associated life to cell-like individuation. This dynamical systems theoretical framework provides an integrated view of the origin and early evolution of life and supports novel empirical approaches.

Single molecules can operate as primitive biological sensors, switches and oscillators

Background

Switch-like and oscillatory dynamical systems are widely observed in biology. We investigate the simplest biological switch that is composed of a single molecule that can be autocatalytically converted between two opposing activity forms. We test how this simple network can keep its switching behaviour under perturbations in the system.

Results

We show that this molecule can work as a robust bistable system, even for alterations in the reactions that drive the switching between various conformations. We propose that this single molecule system could work as a primitive biological sensor and show by steady state analysis of a mathematical model of the system that it could switch between possible states for changes in environmental signals. Particularly, we show that a single molecule phosphorylation-dephosphorylation switch could work as a nucleotide or energy sensor. We also notice that a given set of reductions in the reaction network can lead to the emergence of oscillatory behaviour.

Conclusions

We propose that evolution could have converted this switch into a single molecule oscillator, which could have been used as a primitive timekeeper. We discuss how the structure of the simplest known circadian clock regulatory system, found in cyanobacteria, resembles the proposed single molecule oscillator. Besides, we speculate if such minimal systems could have existed in an RNA world.

Electronic supplementary material

The online version of this article (10.1186/s12918-018-0596-4) contains supplementary material, which is available to authorized users.

Mathematical modelling of microbes: metabolism, gene expression and growth

The growth of microorganisms involves the conversion of nutrients in the environment into biomass, mostly proteins and other macromolecules. This conversion is accomplished by networks of biochemical reactions cutting across cellular functions, such as metabolism, gene expression, transport and signalling. Mathematical modelling is a powerful tool for gaining an understanding of the functioning of this large and complex system and the role played by individual constituents and mechanisms. This requires models of microbial growth that provide an integrated view of the reaction networks and bridge the scale from individual reactions to the growth of a population. In this review, we derive a general framework for the kinetic modelling of microbial growth from basic hypotheses about the underlying reaction systems. Moreover, we show that several families of approximate models presented in the literature, notably flux balance models and coarse-grained whole-cell models, can be derived with the help of additional simplifying hypotheses. This perspective clearly brings out how apparently quite different modelling approaches are related on a deeper level, and suggests directions for further research.

Autocatalytic confusion clarified

There is frequent confusion about the terms autocatalytic reaction, autocatalytic cycle, and autocatalytic set. As the use of the same adjective implies, these three systems do indeed share common properties, in particular their potential for exponential growth. However, the ways in which they achieve this potential are different, giving rise to different internal network structures and dynamics. Therefore, care should be taken which term is used in which context. Here, we explain and discuss the similarities and differences between the three systems in detail, in an effort to avoid any further confusion. We then also discuss the relevance of these autocatalytic systems for possible origin of life scenarios, with an emphasis on how autocatalytic sets may have played an important role in this.

The Narrow Road to the Deep Past: In Search of the Chemistry of the Origin of Life

The sequence of events that gave rise to the first life on our planet took place in the Earth's deep past, seemingly forever beyond our reach. Perhaps for that very reason the idea of reconstructing our ancient story is tantalizing, almost irresistible. Understanding the processes that led to synthesis of the chemical building blocks of biology and the ways in which these molecules self-assembled into cells that could grow, divide and evolve, nurtured by a rich and complex environment, seems at times insurmountably difficult. And yet, to my own surprise, simple experiments have revealed robust processes that could have driven the growth and division of primitive cell membranes. The nonenzymatic replication of RNA is more complicated and less well understood, but here too significant progress has come from surprising developments. Even our efforts to combine replicating compartments and genetic materials into a full protocell model have moved forward in unexpected ways. Fortunately, many challenges remain before we will be close to a full understanding of the origin of life, so the future of research in this field is brighter than ever!

Permeability-driven selection in a semi-empirical protocell model: the roots of prebiotic systems evolution

The origin-of-life problem has been traditionally conceived as the chemical challenge to find the type of molecule and free-solution reaction dynamics that could have started Darwinian evolution. Different autocatalytic and ‘self-replicative’ molecular species have been extensively investigated, together with plausible synthetic pathways that might have led, abiotically, to such a minimalist scenario. However, in addition to molecular kinetics or molecular evolutionary dynamics, other physical and chemical constraints (like compartmentalization, differential diffusion, selective transport, osmotic forces, energetic couplings) could have been crucial for the cohesion, functional integration, and intrinsic stability/robustness of intermediate systems between chemistry and biology. These less acknowledged mechanisms of interaction and molecular control might have made the initial pathways to prebiotic systems evolution more intricate, but were surely essential for sustaining far-from-equilibrium chemical dynamics, given their functional relevance in all modern cells. Here we explore a protocellular scenario in which some of those additional constraints/mechanisms are addressed, demonstrating their ‘system-level’ implications. In particular, an experimental study on the permeability of prebiotic vesicle membranes composed of binary lipid mixtures allows us to construct a semi-empirical model where protocells are able to reproduce and undergo an evolutionary process based on their coupling with an internal chemistry that supports lipid synthesis.

The Transition to Minimal Consciousness through the Evolution of Associative Learning

The minimal state of consciousness is sentience. This includes any phenomenal sensory experience - exteroceptive, such as vision and olfaction; interoceptive, such as pain and hunger; or proprioceptive, such as the sense of bodily position and movement. We propose unlimited associative learning (UAL) as the marker of the evolutionary transition to minimal consciousness (or sentience), its phylogenetically earliest sustainable manifestation and the driver of its evolution. We define and describe UAL at the behavioral and functional level and argue that the structural-anatomical implementations of this mode of learning in different taxa entail subjective feelings (sentience). We end with a discussion of the implications of our proposal for the distribution of consciousness in the animal kingdom, suggesting testable predictions, and revisiting the ongoing debate about the function of minimal consciousness in light of our approach.

Relative Rates of Surface and Volume Synthesis Set Bacterial Cell Size

Many studies have focused on the mechanisms underlying length and width determination in rod-shaped bacteria. Here, we focus instead on cell surface area to volume ratio (SA/V) and demonstrate that SA/V homeostasis underlies size determination. We propose a model whereby the instantaneous rates of surface and volume synthesis both scale with volume. This model predicts that these relative rates dictate SA/V and that cells approach a new steady-state SA/V exponentially, with a decay constant equal to the volume growth rate. To test this, we exposed diverse bacterial species to sublethal concentrations of a cell wall biosynthesis inhibitor and observed dose-dependent decreases in SA/V. Furthermore, this decrease was exponential and had the expected decay constant. The model also quantitatively describes SA/V alterations induced by other chemical, nutritional, and genetic perturbations. We additionally present evidence for a surface material accumulation threshold underlying division, sensitizing cell length to changes in SA/V requirements.

How a life-like system emerges from a simple particle motion law

Self-structuring patterns can be observed all over the universe, from galaxies to molecules to living matter, yet their emergence is waiting for full understanding. We discovered a simple motion law for moving and interacting self-propelled particles leading to a self-structuring, self-reproducing and self-sustaining life-like system. The patterns emerging within this system resemble patterns found in living organisms. The emergent cells we found show a distinct life cycle and even create their own ecosystem from scratch. These structures grow and reproduce on their own, show self-driven behavior and interact with each other. Here we analyze the macroscopic properties of the emerging ecology, as well as the microscopic properties of the mechanism that leads to it. Basic properties of the emerging structures (size distributions, longevity) are analyzed as well as their resilience against sensor or actuation noise. Finally, we explore parameter space for potential other candidates of life. The generality and simplicity of the motion law provokes the thought that one fundamental rule, described by one simple equation yields various structures in nature: it may work on different time- and size scales, ranging from the self-structuring universe, to emergence of living beings, down to the emergent subatomic formation of matter.