The hidden simplicity of biology

The Winding Road from Origin to Emergence (of Life)

Humanity's strive to understand why and how life appeared on planet Earth dates back to prehistoric times. At the beginning of the 19th century, empirical biology started to tackle this question yielding both Charles Darwin's Theory of Evolution and the paradigm that the crucial trigger putting life on its tracks was the appearance of organic molecules. In parallel to these developments in the biological sciences, physics and physical chemistry saw the fundamental laws of thermodynamics being unraveled. Towards the end of the 19th century and during the first half of the 20th century, the tensions between thermodynamics and the "organic-molecules-paradigm" became increasingly difficult to ignore, culminating in Erwin Schrödinger's 1944 formulation of a thermodynamics-compliant vision of life and, consequently, the prerequisites for its appearance. We will first review the major milestones over the last 200 years in the biological and the physical sciences, relevant to making sense of life and its origins and then discuss the more recent reappraisal of the relative importance of metal ions vs. organic molecules in performing the essential processes of a living cell. Based on this reassessment and the modern understanding of biological free energy conversion (aka bioenergetics), we consider that scenarios wherein life emerges from an abiotic chemiosmotic process are both thermodynamics-compliant and the most parsimonious proposed so far.

Chapter 1: The Astrobiology Primer 3.0

The Astrobiology Primer 3.0 (ABP3.0) is a concise introduction to the field of astrobiology for students and others who are new to the field of astrobiology. It provides an entry into the broader materials in this supplementary issue of Astrobiology and an overview of the investigations and driving hypotheses that make up this interdisciplinary field. The content of this chapter was adapted from the other 10 articles in this supplementary issue and thus represents the contribution of all the authors who worked on these introductory articles. The content of this chapter is not exhaustive and represents the topics that the authors found to be the most important and compelling in a dynamic and changing field.

Chapter 2: What Is Life?

The question "What is life?" has existed since the beginning of recorded history. However, the scientific and philosophical contexts of this question have changed and been refined as advancements in technology have revealed both fine details and broad connections in the network of life on Earth. Understanding the framework of the question "What is life?" is central to formulating other questions such as "Where else could life be?" and "How do we search for life elsewhere?" While many of these questions are addressed throughout the Astrobiology Primer 3.0, this chapter gives historical context for defining life, highlights conceptual characteristics shared by all life on Earth as well as key features used to describe it, discusses why it matters for astrobiology, and explores both challenges and opportunities for finding an informative operational definition.

The calculus of codes - From entropy, complexity, and information to life

Exploring the core components that define living systems and their operational mechanisms within emerging biological entities is a complex endeavor. In the realm of biological systems literature, the terms matter, energy, information, complexity, and entropy are frequently referenced. However, possessing these concepts alone does not guarantee a comprehensive understanding or the ability to reconstruct the intricate nature of life. This study aims to illuminate the trajectory of these organic attributes, presenting a theoretical framework that delves into the integrated role of these concepts in biology. We assert that Code Biology serves as a pivotal steppingstone for unraveling the mechanisms underlying life. Biological codes (BCs) emerge not only from the interplay of matter and energy but also from Information. Contrary to deriving information from the former elements, we propose that information holds its place as a fundamental physical aspect. Consequently, we propose a continuum perspective called Calculus of Fundamentals involving three fundamentals: Matter, Energy, and Information, to depict the dynamics of BCs. To achieve this, we emphasize the necessity of studying Entropy and Complexity as integral organic descriptors. This perspective also facilitates the introduction of a mathematical theoretical framework that aids in comprehending continuous changes, the driving dynamics of biological fundamentals. We posit that Energy, Matter, and Information constitute the essential building blocks of living systems, and their interactions are governed by Entropy and Complexity analyses, redefined as biological descriptors. This interdisciplinary perspective of Code Biology sheds light on the intricate interplay between the controversial phenomenon of life and advances the idea of constructing a theory rooted in information as an organic fundamental.

Information Transmission via Molecular Communication in Astrobiological Environments

The ubiquity of information transmission via molecular communication between cells is comprehensively documented on Earth; this phenomenon might even have played a vital role in the origin(s) and early evolution of life. Motivated by these considerations, a simple model for molecular communication entailing the diffusion of signaling molecules from transmitter to receiver is elucidated. The channel capacity C (maximal rate of information transmission) and an optimistic heuristic estimate of the actual information transmission rate ℐ are derived for this communication system; the two quantities, especially the latter, are demonstrated to be broadly consistent with laboratory experiments and more sophisticated theoretical models. The channel capacity exhibits a potentially weak dependence on environmental parameters, whereas the actual information transmission rate may scale with the intercellular distance d as ℐ ∝ d-4 and could vary substantially across settings. These two variables are roughly calculated for diverse astrobiological environments, ranging from Earth's upper oceans (C ∼ 3.1 × 103 bits/s; ℐ ∼ 4.7 × 10-2 bits/s) and deep sea hydrothermal vents (C ∼ 4.2 × 103 bits/s; ℐ ∼ 1.2 × 10-1 bits/s) to the hydrocarbon lakes and seas of Titan (C ∼ 3.8 × 103 bits/s; ℐ ∼ 2.6 × 10-1 bits/s).

Karyotype as code of codes: An inheritance platform to shape the pattern and scale of evolution

Organismal evolution displays complex dynamics in phase and scale which seem to trend towards increasing biocomplexity and diversity. For over a century, such amazing dynamics have been cleverly explained by the apparently straightforward mechanism of natural selection: all diversification, including speciation, results from the gradual accumulation of small beneficial or near-neutral alterations over long timescales. However, although this has been widely accepted, natural selection makes a crucial assumption that has not yet been validated. Specifically, the informational relationship between small microevolutionary alterations and large macroevolutionary changes in natural selection is unclear. To address the macroevolution-microevolution relationship, it is crucial to incorporate the concept of organic codes and particularly the "karyotype code" which defines macroevolutionary changes. This concept piece examines the karyotype from the perspective of two-phased evolution and four key components of information management. It offers insight into how the karyotype creates and preserves information that defines the scale and phase of macroevolution and, by extension, microevolution. We briefly describe the relationship between the karyotype code, the genetic code, and other organic codes in the context of generating evolutionary novelties in macroevolution and imposing constraints on them as biological routines in microevolution. Our analyses suggest that karyotype coding preserves many organic codes by providing system-level inheritance, and similar analyses are needed to classify and prioritize a large number of different organic codes based on the phases and scales of evolution. Finally, the importance of natural information self-creation is briefly discussed, leading to a call to integrate information and time into the relationship between matter and energy.

Is Darwinian selection a retrograde driving force of evolution?

Modern science has still not provided a satisfactory empirical explanation for the increasing complexity of living organisms through evolutionary history. As no agreed-upon definitions of the complexity exist, the working definition of biological complexity has been formulated. There is no theoretical reason to expect evolutionary lineages to increase in complexity over time, and there is no empirical evidence that they do so. In our discussion we have assumed the hypothesis that at the origins of life, evolution had to first involve autocatalytic systems that only subsequently acquired the capacity of genetic heredity. We discuss the role of Darwinian selection in evolution and pose the hypothesis that Darwinian selection acts predominantly as a retrograde driving force of evolution. In this context we understand the term retrograde evolution as a degeneration of living systems from higher complexity towards living systems with lower complexity. With the proposed hypothesis we have closed the gap between Darwinism and Lamarckism early in the evolutionary process. By Lamarckism, the action of a special principle called complexification force is understood here rather than inheritance of acquired characteristics.

On the roles of function and selection in evolving systems

Physical laws-such as the laws of motion, gravity, electromagnetism, and thermodynamics-codify the general behavior of varied macroscopic natural systems across space and time. We propose that an additional, hitherto-unarticulated law is required to characterize familiar macroscopic phenomena of our complex, evolving universe. An important feature of the classical laws of physics is the conceptual equivalence of specific characteristics shared by an extensive, seemingly diverse body of natural phenomena. Identifying potential equivalencies among disparate phenomena-for example, falling apples and orbiting moons or hot objects and compressed springs-has been instrumental in advancing the scientific understanding of our world through the articulation of laws of nature. A pervasive wonder of the natural world is the evolution of varied systems, including stars, minerals, atmospheres, and life. These evolving systems appear to be conceptually equivalent in that they display three notable attributes: 1) They form from numerous components that have the potential to adopt combinatorially vast numbers of different configurations; 2) processes exist that generate numerous different configurations; and 3) configurations are preferentially selected based on function. We identify universal concepts of selection-static persistence, dynamic persistence, and novelty generation-that underpin function and drive systems to evolve through the exchange of information between the environment and the system. Accordingly, we propose a "law of increasing functional information": The functional information of a system will increase (i.e., the system will evolve) if many different configurations of the system undergo selection for one or more functions.

Planetary Scale Information Transmission in the Biosphere and Technosphere: Limits and Evolution

Information transmission via communication between agents is ubiquitous on Earth, and is a vital facet of living systems. In this paper, we aim to quantify this rate of information transmission associated with Earth's biosphere and technosphere (i.e., a measure of global information flow) by means of a heuristic order-of-magnitude model. By adopting ostensibly conservative values for the salient parameters, we estimate that the global information transmission rate for the biosphere might be ∼1024 bits/s, and that it may perhaps exceed the corresponding rate for the current technosphere by ∼9 orders of magnitude. However, under the equivocal assumption of sustained exponential growth, we find that information transmission in the technosphere can potentially surpass that of the biosphere ∼90 years in the future, reflecting its increasing dominance.

Searching for Life, Mindful of Lyfe's Possibilities

We are embarking on a new age of astrobiology, one in which numerous interplanetary missions and telescopes will be designed, built, and launched with the explicit goal of finding evidence for life beyond Earth. Such a profound aim warrants caution and responsibility when interpreting and disseminating results. Scientists must take care not to overstate (or over-imply) confidence in life detection when evidence is lacking, or only incremental advances have been made. Recently, there has been a call for the community to create standards of evidence for the detection and reporting of biosignatures. In this perspective, we wish to highlight a critical but often understated element to the discussion of biosignatures: Life detection studies are deeply entwined with and rely upon our (often preconceived) notions of what life is, the origins of life, and habitability. Where biosignatures are concerned, these three highly related questions are frequently relegated to a low priority, assumed to be already solved or irrelevant to the question of life detection. Therefore, our aim is to bring to the fore how these other major astrobiological frontiers are central to searching for life elsewhere and encourage astrobiologists to embrace the reality that all of these science questions are interrelated and must be furthered together rather than separately. Finally, in an effort to be more inclusive of life as we do not know it, we propose tentative criteria for a more general and expansive characterization of habitability that we call genesity.

A Drive towards Thermodynamic Efficiency for Dissipative Structures in Chemical Reaction Networks

Dissipative accounts of structure formation show that the self-organisation of complex structures is thermodynamically favoured, whenever these structures dissipate free energy that could not be accessed otherwise. These structures therefore open transition channels for the state of the universe to move from a frustrated, metastable state to another metastable state of higher entropy. However, these accounts apply as well to relatively simple, dissipative systems, such as convection cells, hurricanes, candle flames, lightning strikes, or mechanical cracks, as they do to complex biological systems. Conversely, interesting computational properties-that characterize complex biological systems, such as efficient, predictive representations of environmental dynamics-can be linked to the thermodynamic efficiency of underlying physical processes. However, the potential mechanisms that underwrite the selection of dissipative structures with thermodynamically efficient subprocesses is not completely understood. We address these mechanisms by explaining how bifurcation-based, work-harvesting processes-required to sustain complex dissipative structures-might be driven towards thermodynamic efficiency. We first demonstrate a simple mechanism that leads to self-selection of efficient dissipative structures in a stochastic chemical reaction network, when the dissipated driving chemical potential difference is decreased. We then discuss how such a drive can emerge naturally in a hierarchy of self-similar dissipative structures, each feeding on the dissipative structures of a previous level, when moving away from the initial, driving disequilibrium.

The Multiple Paths to Multiple Life

We argue for multiple forms of life realized through multiple different historical pathways. From this perspective, there have been multiple origins of life on Earth—life is not a universal homology. By broadening the class of originations, we significantly expand the data set for searching for life. Through a computational analogy, the origin of life describes both the origin of hardware (physical substrate) and software (evolved function). Like all information-processing systems, adaptive systems possess a nested hierarchy of levels, a level of function optimization (e.g., fitness maximization), a level of constraints (e.g., energy requirements), and a level of materials (e.g., DNA or RNA genome and cells). The functions essential to life are realized by different substrates with different efficiencies. The functional level allows us to identify multiple origins of life by searching for key principles of optimization in different material form, including the prebiotic origin of proto-cells, the emergence of culture, economic, and legal institutions, and the reproduction of software agents.

Informational architecture across non-living and living collectives

Collective behavior is widely regarded as a hallmark property of living and intelligent systems. Yet, many examples are known of simple physical systems that are not alive, which nonetheless display collective behavior too, prompting simple physical models to often be adopted to explain living collective behaviors. To understand collective behavior as it occurs in living examples, it is important to determine whether or not there exist fundamental differences in how non-living and living systems act collectively, as well as the limits of the intuition that can be built from simpler, physical examples in explaining biological phenomenon. Here, we propose a framework for comparing non-living and living collectives as a continuum based on their information architecture: that is, how information is stored and processed across different degrees of freedom. We review diverse examples of collective phenomena, characterized from an information-theoretic perspective, and offer views on future directions for quantifying living collective behaviors based on their informational structure.

The N-space Episenome unifies cellular information space-time within cognition-based evolution

Self-referential cellular homeostasis is maintained by the measured assessment of both internal status and external conditions based within an integrated cellular information field. This cellular field attachment to biologic information space-time coordinates environmental inputs by connecting the cellular senome, as the sum of the sensory experiences of the cell, with its genome and epigenome. In multicellular organisms, individual cellular information fields aggregate into a collective information architectural matrix, termed a N-space Episenome, that enables mutualized organism-wide information management. It is hypothesized that biological organization represents a dual heritable system constituted by both its biological materiality and a conjoining N-space Episenome. It is further proposed that morphogenesis derives from reciprocations between these inter-related facets to yield coordinated multicellular growth and development. The N-space Episenome is conceived as a whole cell informational projection that is heritable, transferable via cell division and essential for the synchronous integration of the diverse self-referential cells that constitute holobionts.

Symmetry breaking and functional incompleteness in biological systems

Symmetry-based explanations using symmetry breaking (SB) as the key explanatory tool have complemented and replaced traditional causal explanations in various domains of physics. The process of spontaneous SB is now a mainstay of contemporary explanatory accounts of large chunks of condensed-matter physics, quantum field theory, nonlinear dynamics, cosmology, and other disciplines. A wide range of empirical research into various phenomena related to symmetries and SB across biological scales has accumulated as well. Led by these results, we identify and explain some common features of the emergence, propagation, and cascading of SB-induced layers across the biosphere. These features are predicated on the thermodynamic openness and intrinsic functional incompleteness of the systems at stake and have not been systematically analyzed from a general philosophical and methodological perspective. We also consider possible continuity of SB across the physical and biological world and discuss the connection between Darwinism and SB-based analysis of the biosphere and its history.

The Dynamical Emergence of Biology From Physics: Branching Causation via Biomolecules

Biology differs fundamentally from the physics that underlies it. This paper proposes that the essential difference is that while physics at its fundamental level is Hamiltonian, in biology, once life has come into existence, causation of a contextual branching nature occurs at every level of the hierarchy of emergence at each time. The key feature allowing this to happen is the way biomolecules such as voltage-gated ion channels can act to enable branching logic to arise from the underlying physics, despite that physics per se being of a deterministic nature. Much randomness occurs at the molecular level, which enables higher level functions to select lower level outcomes according to higher level needs. Intelligent causation occurs when organisms engage in deduction, enabling prediction and planning. This is possible because ion channels enable action potentials to propagate in axons. The further key feature is that such branching biological behavior acts down to cause the underlying physical interactions to also exhibit a contextual branching behavior.

Universal scaling across biochemical networks on Earth

The application of network science to biology has advanced our understanding of the metabolism of individual organisms and the organization of ecosystems but has scarcely been applied to life at a planetary scale. To characterize planetary-scale biochemistry, we constructed biochemical networks using a global database of 28,146 annotated genomes and metagenomes and 8658 cataloged biochemical reactions. We uncover scaling laws governing biochemical diversity and network structure shared across levels of organization from individuals to ecosystems, to the biosphere as a whole. Comparing real biochemical reaction networks to random reaction networks reveals that the observed biological scaling is not a product of chemistry alone but instead emerges due to the particular structure of selected reactions commonly participating in living processes. We show that the topology of biochemical networks for the three domains of life is quantitatively distinguishable, with >80% accuracy in predicting evolutionary domain based on biochemical network size and average topology. Together, our results point to a deeper level of organization in biochemical networks than what has been understood so far.

Biological evolution as defense of 'self'

Although the origin of self-referential consciousness is unknown, it can be argued that the instantiation of self-reference was the commencement of the living state as phenomenal experientiality. As self-referential cognition is demonstrated by all living organisms, life can be equated with the sustenance of cellular homeostasis in the continuous defense of 'self'. It is proposed that the epicenter of 'self' is perpetually embodied within the basic cellular form in which it was instantiated. Cognition-Based Evolution argues that all of biological and evolutionary development represents the perpetual autopoietic defense of self-referential basal cellular states of homeostatic preference. The means by which these states are attained and maintained is through self-referential measurement of information and its communication. The multicellular forms, either as biofilms or holobionts, represent the cellular attempt to achieve maximum states of informational distinction and energy efficiency through individual and collective means. In this frame, consciousness, self-consciousness and intelligence can be identified as forms of collective cellular phenotype directed towards the defense of fundamental cellular self-reference.

Criticality Distinguishes the Ensemble of Biological Regulatory Networks

The hypothesis that many living systems should exhibit near-critical behavior is well motivated theoretically, and an increasing number of cases have been demonstrated empirically. However, a systematic analysis across biological networks, which would enable identification of the network properties that drive criticality, has not yet been realized. Here, we provide a first comprehensive survey of criticality across a diverse sample of biological networks, leveraging a publicly available database of 67 Boolean models of regulatory circuits. We find all 67 networks to be near critical. By comparing to ensembles of random networks with similar topological and logical properties, we show that criticality in biological networks is not predictable solely from macroscale properties such as mean degree ⟨K⟩ and mean bias in the logic functions ⟨p⟩, as previously emphasized in theories of random Boolean networks. Instead, the ensemble of real biological circuits is jointly constrained by the local causal structure and logic of each node. In this way, biological regulatory networks are more distinguished from random networks by their criticality than by other macroscale network properties such as degree distribution, edge density, or fraction of activating conditions.

Field studies reveal functions of chemical mediators in plant interactions

Plants are at the trophic base of most ecosystems, embedded in a rich network of ecological interactions in which they evolved. While their limited range and speed of motion precludes animal-typical behavior, plants are accomplished chemists, producing thousands of specialized metabolites which may function to convey information, or even to manipulate the physiology of other organisms. Plants' complex interactions and their underlying mechanisms are typically dissected within the controlled environments of growth chambers and glasshouses, but doing so introduces conditions alien to plants evolved in natural environments, such as being pot-bound, and receiving artificial light with a spectrum very different from sunlight. The mechanistic understanding gained from a reductionist approach provides the tools required to query and manipulate plant interactions in real-world settings. The few tests conducted in natural ecosystems and agricultural fields have highlighted the limitations of studying plant interactions only in artificial environments. Here, we focus on three examples of known or hypothesized chemical mediators of plants' interactions: the volatile phytohormone ethylene (ET), more complex plant volatile blends, and as-yet-unknown mediators transferred by common mycorrhizal networks (CMNs). We highlight how mechanistic knowledge has advanced research in all three areas, and the critical importance of field work if we are to put our understanding of chemical ecology on rigorous experimental and theoretical footing, and demonstrate function.

Exoplanet Biosignatures: Future Directions

We introduce a Bayesian method for guiding future directions for detection of life on exoplanets. We describe empirical and theoretical work necessary to place constraints on the relevant likelihoods, including those emerging from better understanding stellar environment, planetary climate and geophysics, geochemical cycling, the universalities of physics and chemistry, the contingencies of evolutionary history, the properties of life as an emergent complex system, and the mechanisms driving the emergence of life. We provide examples for how the Bayesian formalism could guide future search strategies, including determining observations to prioritize or deciding between targeted searches or larger lower resolution surveys to generate ensemble statistics and address how a Bayesian methodology could constrain the prior probability of life with or without a positive detection. Key Words: Exoplanets-Biosignatures-Life detection-Bayesian analysis. Astrobiology 18, 779-824.

Woodpeckers and Diamonds: Some Aspects of Evolutionary Convergence in Astrobiology

Jared Diamond's argument against extraterrestrial intelligence from evolutionary contingency is subjected to critical scrutiny. As with the earlier arguments of George Gaylord Simpson, it contains critical loopholes that lead to its unraveling. From the point of view of the contemporary debates about biological evolution, perhaps the most contentious aspect of such arguments is their atemporal and gradualist usage of the space of all possible biological forms (morphospace). Such usage enables the translation of the adaptive value of a trait into the probability of its evolving. This procedure, it is argued, is dangerously misleading. Contra Diamond, there are reasons to believe that convergence not only plays an important role in the history of life, but also profoundly improves the prospects for search for extraterrestrial intelligence success. Some further considerations about the role of observation selection effects and our scaling of complexity in the great debate about contingency and convergence are given. Taken together, these considerations militate against the pessimism of Diamond's conclusion, and suggest that the search for traces and manifestations of extraterrestrial intelligences is far from forlorn. Key Words: Astrobiology-Evolution-Contingency-Convergence-Complex life-SETI-Major evolutionary transitions-Selection effects-Jared Diamond. Astrobiology 18, 491-502.

Origin of life in a digital microcosm

While all organisms on Earth share a common descent, there is no consensus on whether the origin of the ancestral self-replicator was a one-off event or whether it only represented the final survivor of multiple origins. Here, we use the digital evolution system Avida to study the origin of self-replicating computer programs. By using a computational system, we avoid many of the uncertainties inherent in any biochemical system of self-replicators (while running the risk of ignoring a fundamental aspect of biochemistry). We generated the exhaustive set of minimal-genome self-replicators and analysed the network structure of this fitness landscape. We further examined the evolvability of these self-replicators and found that the evolvability of a self-replicator is dependent on its genomic architecture. We also studied the differential ability of replicators to take over the population when competed against each other, akin to a primordial-soup model of biogenesis, and found that the probability of a self-replicator outcompeting the others is not uniform. Instead, progenitor (most-recent common ancestor) genotypes are clustered in a small region of the replicator space. Our results demonstrate how computational systems can be used as test systems for hypotheses concerning the origin of life.This article is part of the themed issue 'Reconceptualizing the origins of life'.

Formal Definitions of Unbounded Evolution and Innovation Reveal Universal Mechanisms for Open-Ended Evolution in Dynamical Systems

Open-ended evolution (OEE) is relevant to a variety of biological, artificial and technological systems, but has been challenging to reproduce in silico. Most theoretical efforts focus on key aspects of open-ended evolution as it appears in biology. We recast the problem as a more general one in dynamical systems theory, providing simple criteria for open-ended evolution based on two hallmark features: unbounded evolution and innovation. We define unbounded evolution as patterns that are non-repeating within the expected Poincare recurrence time of an isolated system, and innovation as trajectories not observed in isolated systems. As a case study, we implement novel variants of cellular automata (CA) where the update rules are allowed to vary with time in three alternative ways. Each is capable of generating conditions for open-ended evolution, but vary in their ability to do so. We find that state-dependent dynamics, regarded as a hallmark of life, statistically out-performs other candidate mechanisms, and is the only mechanism to produce open-ended evolution in a scalable manner, essential to the notion of ongoing evolution. This analysis suggests a new framework for unifying mechanisms for generating OEE with features distinctive to life and its artifacts, with broad applicability to biological and artificial systems.