functional relationships within the system (Hofmeyr, 2018). Similarly, process structuralism distinguishes between different kinds of morphogenetic fields based on the functional relations that determine their structure (Webster & Goodwin, 1982, 1996). In both cases, different systems (organisms or morphogenetic fields) are categorized by the relational properties that characterize their organization. Such *relational explanations* are perfectly scientific; but they are not mechanistic. They do not explain the behavior of a system in terms of cause and effect, but rather tell us what kind of a system it is in terms of its relational properties.

The organizational account of organismic agency relies on material, efficient, *and formal (be)causes*—mechanistic *and relational explanations*—which complement each other. Organizational closure, achieved through the closure of constraints, is the defining relational property of living systems. It is a formal (be)cause. However, it is not simply imposed on the material flows constituting the organism. Instead, it is continually regenerated, constantly (re)emerging over time through the dialectic dynamic interactions of material processes and the constraints they generate (DiFrisco, 2014; DiFrisco & Mossio, 2020). These processes represent the material and efficient (be)causes of the organism.

In contrast to all the above, population-level evolutionary genetics relies on *statistical explanations* that are neither structural nor mechanistic, accounting for their phenomena in terms of statistical relevance or conditional dependence instead (see Woodward, 2019). The agential perspective adds a *fourth kind of explanation* to evolutionary theory—*naturalistic teleological explanation* (Walsh, 2015)—thus completing the Aristotelian repertoire of (be)causes.

Natural teleological explanation does not describe any large-scale trends or tendencies in evolution. It applies exclusively at the level of the evolutionary individual. While mechanistic explanations show how specific causes *produce* their effects (answering the question “how” something happens), teleological explanations account for the means that are *conducive to* the attainment of the organism’s goals (answering the question “why” something happens). The latter kind of questions are often the most relevant in evolutionary biology, but have been considered philosophically troublesome for a very long time. This does not have to be case (Walsh, 2015). Goal-oriented behavior is empirically observable. The goals of an organism do not exert any pull on it from the future, but naturally emerge from its interactions with its experienced environment (the individual’s struggle for existence).

For these reasons, naturalistic teleological explanation does not suffer from any of the problems that usually render teleological explanations problematic. First, it does not imply non-actual (e.g., future) causes of present effects. Second, it does not imply any intentionality (or even cognitive abilities). Third, it is based on a naturalized notion of normativity (see Sect. 8.2, and Mossio et al., 2009a). Goal-oriented behaviors arise because the organism strives to maintain organizational closure and continuity in order to continue living, to reproduce, and to evolve. It does this by autonomously selecting actions from its behavioral repertoire in response to opportunities and obstacles in its experienced environment (see Sect. 8.6). Put simply, naturalistic teleological explanation is a necessary part of any agential theory of
evolution, because of the immanence of *rules which are generated by the agents themselves* (Walsh, 2015).

This leads us to the third and last issue, which consists of a number of method-
ological challenges concerning the mathematical and conceptual tools we use to
study evolving systems. These tools are often borrowed from physics (as discussed,
e.g., in Fontana & Buss, 1996, or Knuuttila & Loettgers, 2016), and most of them
were originally developed within a strictly Newtonian paradigm. Let us take dynam-
ical systems theory as an example, which is used to support dynamic mechanistic
explanations in evo-devo (see Brigandt, 2015; DiFrisco & Jaeger, 2019). In this
framework, we first prestate the space of possible trajectories of a system (its con-
figuration space) before homing in on those that are actually realized in specific
circumstances through validation of the model with empirical data (see, e.g., Jaeger
& Crombach, 2012; Jaeger et al., 2012; Jaeger & Monk, 2014; Crombach & Jaeger,
2021). This is classical “physics in a box.” It is a very powerful approach for simu-
lating developmental processes, but breaks down at the level of whole-cell or whole-
organism models, since traditional dynamical systems models cannot deal with
systems based on organizational closure. In fact, it cannot deal with self-constructing
systems in general (Fontana & Buss, 1994, 1996).

Organizational closure, considered in a dynamic context, leads to the continuous
(re)generation of the rules and constraints that determine the behavior of the system.
Therefore, systems with organizational closure require models that rewrite their
own equations and boundary conditions based on principles generated from *within*
themselves. This recursiveness lies at the heart of Rosen's (1991) conjecture that
organisms cannot be completely captured by any finite algorithm. Although recur-
sive formalisms (such as Lambda calculus), which allow for operations on opera-
tors, can be used for simulating organized systems with closure (Fontana & Buss,
1994, 1996; Mossio et al., 2009b), this still falls short of capturing the full potential
of an evolvable living system. The reason for this is because the different processes
and constraints that constitute an organism not only recursively influence but mutu-
ally depend on each other for their very existence (see Sect. 8. 2). Organisms *embody*
their self-generated rules in a way which is impossible to fully implement within
any predefined computational environment with its externally specified hardware
and syntactic rules (Rosen, 1991). It may be the case that to fully capture an organ-
ism with its capabilities of survival, reproduction, and open-ended evolution, we'd
have to actualize a synthetic, evolvable reproducer with a complete life cycle in the
laboratory.

8.8 Conclusion

What I have presented here remains a very tentative outline of an agential approach to evolution (cf. Walsh, 2015). It rests on the organizational account of reproduction and organismal agency (Moreno & Mossio, 2015; Mossio & Pontarotti, 2020; Mossio, this volume; Pontarotti, this volume), as well as the perspective of the
reproducer and its life cycle as the fundamental unit of evolution by natural selec-
tion (Griesemer, 2006). The major implication of the theory is that all evolving
systems are agents (or involve agents among their parts), which implies that under-
standing organismic agency is absolutely fundamental for understanding evolution.
These are strong claims that must be supported by strong evidence. Unfortunately,
we have barely begun to study agency and its role in evolution, and many obstacles
remain on the road to a more mature, robust, and empirically supported theory.

Some of these challenges are philosophical: they concern the nature of the new
account, its mathematical methodology, and the kind of explanations we need to
understand the role of organismic agency in evolution. What should be clear by now
is that an agential theory will look very different from what we are used to calling a
scientific theory within the traditional Newtonian paradigm. Instead of providing a
mechanistic explanation of agency and its evolution in terms of efficient causation
only, this new theory will rely on all Aristotelian aitia or (be)causes: material, effi-
cient, formal, and final. Final (be)causes will be incorporated in the form of natural-
istic teleological explanations for the behavior of individual evolutionary units
(reproducers) engaged in their struggle for existence. I must emphasize again: this
kind of teleology does *not* imply any large-scale goal-directedness in evolution.
Whether macroevolutionary trends exist or not is not at issue here. Naturalistic tele-
ological explanation strictly only applies to the goal-directedness of an individual's
behavior.

Some of the challenges are empirical. These apply at two different levels. To
fully understand Darwinian evolution—and its underlying struggle for existence—
we need a naturalistic account of organismic agency. Organizational closure through
the closure of constraints, and organizational continuity enabling the continual
(re)emergence of organization and the completion of the life cycle, provides the
most detailed and convincing explanation for agency and its role in evolution that
we have today. Yet, they still remain largely disconnected from the empirical study
of regulatory processes in systems and synthetic biology. The first challenge will be
to cross this divide in order to test the organizational account empirically. The sec-
ond challenge resides at the level of the organism's goal-oriented behavior, which is
itself an empirical observable (Walsh, 2015). Now that we have a philosophical
justification to do so, we can apply naturalistic teleological explanations to account
for the means that are conducive to the pursuit of an organism's goals. In a way, this
is already common practice in ecological research. What remains to be done is to
embed this existing practice as a research program within the agential perspective
on evolution.

Despite all the remaining challenges—and the speculative nature of the argu-
ment—I hope to have convinced the reader that it is worthwhile to take process and
agency more seriously in the study of evolution. Most current research remains
restricted to traditional structural and functional approaches, with genetic replica-
tors as their focus. Processual and even more so agential perspectives remain
severely understudied, mainly because of theoretical objections and prejudices that
do not hold up under closer scrutiny. This unnecessarily limits the scope and depth
of evolutionary research today. Efforts to provide extended synthetic accounts do
not really solve this issue, because the problem is the attempt at synthesis itself. Evolution is a process that generates diversity. Why not embrace an equally diverse approach to evolutionary explanation? An agential theory properly contextualizes and enriches existing structural, functional, and processual approaches. It provides *a fourth perspective on evolution, a truly organismic angle*. All four illuminate each other's limitations and domains of applicability, and each provides its own episodic approach (Griesemer, 2006; Wimsatt, 2007). Together, they address a much greater range of evolutionary phenomena than any single perspective could ever cover on its own.

**Acknowledgments** James Griesemer, Andrea Loettgers, James DiFrisco, Rick Gawne, Jannie Hofmeyr, and Denis Walsh provided extremely useful comments on earlier versions of this manuscript. This chapter ties together strands of thinking that have deeply fascinated me since the earliest days of my career. I thank the late Brian Goodwin for igniting many of those sparks. Eva Neumann-Held and Christoph Rehmann-Sutter not only published the volume in which Griesemer's reproducer perspective was published but also organized the symposium which originally set me on my journey. I thank Nick Monk for his long-term collaboration on our own processual perspective. I thank my collaborators Dan Brooks and James DiFrisco for countless illuminating discussions and for introducing me to Bill Wimsatt and his perspectival philosophy. I thank Denis Walsh for his essential moral and intellectual support last year in Paris and beyond. I thank Jannie Hofmeyr for the all too brief time we had discussing the nature of living organization last year in Stellenbosch. I thank my collaborator Andrea Loettgers for taking my emergent view of life to the next level. Last but not least, I thank Matteo Mossio for introducing me to the organizational account, for inviting me to contribute to this volume, and for his helpful criticisms of my arguments. I truly stand on the shoulders of giants.

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Chapter 9

On the Evolutionary Development
of Biological Organization from Complex
Prebiotic Chemistry

Kepa Ruiz-Mirazo and Alvaro Moreno

**Abstract** In this chapter we offer a critical analysis of organizational models about the process of origins of life and, thereby, a reflection about life itself (understood in a general, minimal sense). We begin by demarcating the idea of organization as an explanatory construct, linking it to the complex relationships and transformations that the material parts of (proto-)biological systems establish to maintain themselves under non-equilibrium dynamic conditions. The diverse ways in which this basic idea has been applied within the prebiotic field are then reviewed in relative detail. We distinguish between “network” and “protocell” approaches, discussing their specific implications and explaining the greater relevance of the latter in the current state of affairs. Despite the key role that such organizational approaches play (and should keep playing) to advance on the problem of primordial biogenesis, the second half of our contribution is devoted to argue that they must be combined with other explanatory accounts, which go beyond the physiology of any single (proto-)organism. With that aim, we underline the fundamental differences between the autonomous, metabolic dynamics that individual (proto-)cells perform and the evolutionary and ecological dynamics that take place in a collective and transgenerational dimension. Apart from obvious gaps in the characteristic temporal and spatial scales involved, the corresponding causal and interactive regimes also reveal themselves as neatly distinct, what is reflected in the unpaired functional integration and the agent behavior displayed by biological individuals. Nevertheless, any living organism (and life in a wider, general sense) derives from the deep interweaving of those two phenomenological domains: namely, the “individual-metabolic” and the “collective-evolutionary” domains. At the end of the chapter, we propose the principle of dynamical decoupling as the core idea to develop a more comprehensive

K. Ruiz-Mirazo (✉)
Department of Philosophy, University of the Basque Country, Bilbao, Spain
Biofisika Institute (CSIC, UPV-EHU), Leioa, Spain
e-mail: kepa.ruiz-mirazo@ehu.eus

A. Moreno
Department of Philosophy, University of the Basque Country, Bilbao, Spain
Donostia International Physics Centre (DIPC), San Sebastián, Spain
theoretical framework to understand how this intricate, causally asymmetric con-
nection must be articulated during the actual process of biogenesis (as it happened
here on Earth or anywhere else in the universe), so that life's minimal complexity
threshold is reached.

**Keywords** Primordial biogenesis · Prebiotic transitions · Molecular reaction networks · Protocell models · Organizational integration · Minimal metabolism · Regulation · Origins of agency · Functional domain · Reproduction · Material/ trans-generational constraints · Pre-Darwinian evolution · Sedimentation · Proto- phylogenies · Dynamical decoupling · Informational records · Genetic code · Biological organization

9.1 Introduction: Organization as an Explanatory Construct
in Origins-of-Life Research

Most of the research work in the field of prebiotic chemistry has been focused, so
far, on discovering reaction mechanisms and transformation pathways for the abi-
otic synthesis of biopolymers, their monomers, or some other biologically relevant
molecules. In addition, the replicative and catalytic properties of those molecules
have been explored in considerable detail (for an extensive review, see Ruiz-Mirazo
et al., 2014). However, all that body of empirical and theoretical knowledge tells us
very little, unfortunately, about the main transitions during the process of primordial
biogenesis. Somehow, Miller's (1953) famous experiment was a turning point in the
field that has been transformed, over the last decades, into a wider and more solid
platform to approach the problem of origins of life, but further progress has been
quite modest, really: like Sutherland (2017) says, all what we have achieved so far
(including his own investigations) is just «the end of the beginning» in terms of
solving the question.

Many authors consider that *natural selection*, combined with long enough time
periods, up to the geological scale, could lead all the way, from populations of bio-
molecules (in particular, if the latter developed the capacity for multiplication, vari-
ation, and heredity (Maynard Smith, 1986; Szathmáry & Maynard Smith, 1997)) to
living cells. Yet, this involves a huge assumption, based on the premise that the
principles of Darwinian evolution can be readily applied to bare sets of molecular
replicators. There is ample evidence, indeed, to support that molecular structures,
like RNA strands, undergo artificial evolution in vitro, being able to reach pre-
established target motifs (e.g., ribozymes with specific features (Bartel & Szostak,
1993; Johnston et al., 2001; Tjhung et al., 2020)) or even follow a potentially end-
less process (Lincoln & Joyce, 2009). Nevertheless, there are no obvious results
showing evolutionary dynamics that bring about a relevant increase in the complex-
ity of the individuals that constitute those populations, even when replicators are
used in combination with protocellular structures (e.g., Chen et al., 2005; Mansy
et al., 2008 – see also the more recent review: (Joyce & Szostak, 2018)). Therefore,
although hopes still remain for an “RNA world” (the hypothesis that all started from RNA molecules (Crick, 1968; Orgel, 1968; Gilbert, 1986)) which could turn into a full-fledged biological world (Higgs & Lehman, 2015; Joyce & Szostak, 2018; Krishnamurthy, 2020), more and more skeptical voices are rising, advocating the need to conceive alternative scenarios (Ruiz-Mirazo et al., 2017; Le Vay & Mutschler, 2019; Kroiss et al., 2019; Preiner et al., 2020). Among other reasons, it could well be the case that a molecularly richer, more varied, and heterogeneous prebiotic milieu is required, right from the beginning, to trigger off those evolutionary processes that may lead to an open-ended increase in functional/phenotypic diversity, as it was argued more extensively in (Wicken, 1987; Moreno & Ruiz-Mirazo, 2009; Ruiz-Mirazo et al., 2008, 2020).

The main alternative to the “RNA world” has traditionally been the “metabolism-first” hypothesis (De Duve, 1991; Dyson, 1999; Morowitz, 1999; Shapiro, 2000), which defends a completely different plan of attack and explanatory framework for life’s origin. The key question, according to this approach, would be discovering the combination of energy inputs, material components, and chemical transformation processes that put together a self-maintaining system in non-equilibrium, precarious conditions, in transition toward minimal (unicellular) organisms. It is in this context, precisely, where the idea of *organization* comes to the center of stage, as a fundamental mereological construct through which complex systems, like living cells (or their precursors, “protocells” or “proto-metabolisms”), demand a proper characterization. The work of a number of classical authors in theoretical biology (Rosen, 1971, 1991; Varela et al., 1974; Maturana & Varela, 1980; Ganti, 1975, 2003; Eigen & Schuster, 1979; Kauffman, 1986, 1993; Fontana & Buss, 1994, 1996), trying to determine the idiosyncratic nature of biological organization, in its most elementary and general sense, in contrast to other types of organization one may find in the natural world, also helped to elaborate and support this view. A view that has been reinforced in recent times, as well, with the advent of new research programs like “systems biology” (Kitano, 2002; Westerhoff & Palsson, 2004) and “systems chemistry” (von Kiedrowski, 2005; Ludlow & Otto, 2008) that insist on the irreducible complexity of biological and proto-biological entities (de la Escosura et al., 2015; Kroiss et al., 2019). This does not always mean defending metabolism as the first or most important landmark in the prebiotic process, but it stands much closer to that way of framing the question, as an investigation into the intricate material and energetic couplings that enable non-equilibrium, dynamic systems whose emergence and maintenance rely on the strong functional integration of a variety of molecular components in continuous transformation (Ruiz-Mirazo et al., 2017; Lauber et al., 2021).

In this chapter we will briefly review the different organizational approaches that have been pursued within the field of origins of life and their relative success, classifying them in two main groups: *network models* and *protocell models*. These two types of model can be both experimental (in vitro) and theoretical/computational (in silico): the fundamental feature that distinguishes them relates to the degree of diversity and interdependence required among the various processes, material components, and constraints that constitute the system. Although protocellular models
tend to be more demanding and encompassing in that sense (and, therefore, more interesting in order to develop a complete theory of biogenesis), they are also more complicated to handle and analyze. In any case, we will try to show how the concept of organization, in its various meanings, can be used both as *explanans* (i.e., to describe intermediate hypothetical model-systems, taken as necessary conjectures or stages to make sense of such a long and complex transition) and *explanandum* (i.e., to account for the end result, prokaryotic cell organization, taken as factual “minimal life”).

However, the most important message of our chapter is to remark that the *organizational* framework, being of primary and central importance, is not sufficient to elucidate the nature of the living phenomenon nor the way it came to be, from physics and chemistry. Although the inert and the living worlds are of course linked, in various ways and diverse planes, the jump between their corresponding phenomenologies is too big, or too high, to be taken in just a few steps. Even if the first stages of primordial biogenesis should already involve organized individuals (for the reasons suggested above, see again, in particular Moreno & Ruiz-Mirazo, 2009), additional explanatory principles, beyond the sphere of individual organizations, must be at work for prebiotic systems to overcome the bottlenecks that were surely present throughout such an intricate process. More precisely, increases in complexity (including the internal complexity of the individual organizations leading the process) require dynamics and interactions that take place at the level of population dynamics, as we will see, to ensure minimal robustness at the intermediate phases, paying back for the energetic and material costs involved.<fnref n="1" />

Regulation, for instance, understood in a biologically relevant sense (i.e., not simply as chemical feedback but as a hierarchy of controls operating in minimally adaptive systems, so they can select among a diversity of metabolic/behavioral regimes in response to changes in internal/external variables (Bich et al., 2016)), appears as a key property to be developed by protocells, on their way toward more autonomous, efficient, and sophisticated cells. Although the presence of regulatory mechanisms has also deep implications in terms of how each individual is organized, the appearance and stabilization of such mechanisms cannot be conceived but as the result of an *evolutionary* process. Namely, a process in which a large population of similar, precarious but proliferating systems, in a variable and challenging environment, try various (constitutive or behavioral) options, and come out with “a solution” that spreads and eventually becomes built-in, hard-wired in each system

<footnote n="1">¹This makes our position quite different from other authors', like Varela's (1979) or Rosen's (1991) who defended that the living phenomenon could be fully captured in terms of the organization that each organism continuously realizes. In more pragmatic terms, the conception that we will defend here, based on our previous work on the nature of life (Ruiz-Mirazo et al., 2004, 2010), highlights that there are yet many hard issues to address in the field of origins (as well as in theoretical biology) related to the intricate link between the physiological, ecological, and evolutionary spheres of the living. That move also makes more understandable the huge gap in complexity that still lies between our current prebiotic (or “bottom-up”) models/systems and any real cell.</footnote>
(i.e., it is adopted as a reliable mechanism by all subsequent individuals in the popu-
lation). Similarly, genetic mechanisms are incardinated within individual organiza-
tions, where they play their fundamental physiological roles (as a guide for protein
synthesis, more prominently), but their raison d'être and functional contribution do
not make full sense unless it is considered in the context of a wider and longer evo-
lutionary pathway, an open pathway that transcends any of those particular indi-
viduals (Ruiz-Mirazo et al., 2020).

Therefore, we will put forward the thesis that complex chemical systems (self-
producing and self-reproducing protocells) progressively transform into hypercom-
plex biological organisms (living cells) thanks to a combination of factors that
operate not only at different spatial/temporal scales and with different weights but
also following intrinsically different dynamic principles. Some of these principles
have to do with the composition, architecture, and necessarily interactive self-
maintaining dynamics of the individuals involved, whereas some others have to do
with their reproduction, inheritance, diversification, and open, collective dynamics.
Accordingly, organizational aspects will be primarily associated to the develop-
ment – and adequate coupling – of basic control mechanisms at the molecular and
physiological description levels (Ruiz-Mirazo et al., 2017), while evolutionary and
ecological aspects (Moreno, 2016) will rather cover the “propagation” (Kauffman,
2000) and “sedimentation” (Walsh, 2018) processes working at the level of the pop-
ulation, or the whole ecosystem/biosphere. We will argue that, even if they seem
quite orthogonal to each other, these two phenomenological domains must actually
get tied up during the process of origins of life, establishing a mutual – though caus-
ally asymmetric – connection that is further reinforced once biological evolution
takes off. Our discussion will reveal, in any case, how much ground science must
still cover in order to solve the problem of primordial biogenesis.

## 9.2 Organizational Accounts at the Onset of Prebiotic Evolution: Network Versus Protocell Models

As we just advanced in the introduction, tackling the problem of origins of life from
an organizational perspective implies a theoretical scheme according to which dif-
ferent molecular components and transformation processes come together to consti-
tute prebiotic systems that maintain themselves and proliferate in non-equilibrium
conditions, on their way toward living organisms. Depending on the diversity and
complexity of the material components/transformations involved, as well as on their
relationships and interactive properties, one can propose a variety of architectures to
characterize such systems. A complete organizational theory of biogenesis should
provide a plausible sequence of transitions, starting from relatively simple systems
toward increasingly complex ones (both in terms of molecular ingredients and
architectural/interactive features), with the aim to bridge the gap currently observed
in nature between physical-chemical and biological phenomena.
Living beings, as pointed out so wisely by Kant, long before the development of modern biology, have a very special kind of organization, in which even the mere existence of many fundamental system parts cannot be taken for granted, since they result from the collective transformation dynamics of the whole. This idea is, in our view, of central importance to understand biological phenomena, and, thus, it must also play a key role in any explanation of the process of biogenesis. Yet, what Kant did not anticipate is that the roots of this complex dynamic behavior could actually be found in the domain of physics and chemistry: in other words, that matter is inherently active, given the adequate conditions, as it became apparent in the study of non-equilibrium self-organization and self-assembly processes last century (Nicolis & Prigogine, 1977; Lehn, 1995) and has been, thereafter, reinforced (Showalter & Epstein, 2015; Semenov et al., 2016). These processes, being necessary to understand the workings of any cell (Karsenti, 2008), are nevertheless not sufficient. The capacity for self-maintenance characteristic of biological organisms, their surprising endurance as non-equilibrium, dissipative systems, involves not only the organization of already existing parts into a whole but a proper *metabolism*: continuous constructive and reconstructive transformations, which actually synthesize the key ingredients that rule its complex behavior (i.e., a diversity of material constraints that operate on those same transformations (Ruiz-Mirazo & Moreno, 2004; Lauber et al., 2021)).

This circularity or cyclic/self-referential, collective dynamics was the theoretical target of a number of classical models of minimal biological organization (Rosen, 1971; Varela et al., 1974; Ganti, 1975; Pattee, 1977; Kauffman, 1986). Although the direct impact of such abstract models on the research field of prebiotic chemistry has been relatively modest, we consider that they can still be helpful to draw a conceptual distinction between two general approaches to the problem of origins of life, when this is envisaged in terms of the emergence of metabolic organizations. On the one hand, one can identify the *network* approach, in which the dynamics of a population of reacting molecules in homogenous – typically aqueous solution – conditions is explored, assuming a more or less concentrated “organic chemistry soup” where the potential couplings/interactions among those molecular components can be captured through mathematical mappings or graphs.<fnref n="2" /> On the other hand, we find the *protocell* approach, in which both physical and chemical transformations take place in heterogeneous conditions – typically a mixture of aqueous and organic domains, like a lipid vesicle suspension – where the couplings/interactions among the system components must be analyzed making use of additional tools, since they are also influenced by spatial constraints on their free movement/diffusion. With variations (which we will not go into here – see Moreno & Ruiz-Mirazo, 1999;

<footnote n="2">²Some “network” models/theories would not work, strictly speaking, in homogeneous 3D conditions, but on surfaces. For instance, the classical proposal of Wächtershäuser (1988, 1990) would constitute a two-dimensional metabolism working on the surface of pyrite. However, we are not going to pay special attention to this type of scenario here. It could be interesting in terms of finding synthetic pathways to generate some organic compounds, but they are severely limited for any further organizational developments (Ruiz-Mirazo et al., 2020; Lauber et al., 2021).</footnote>
Hofmeyr, 2007; Cornish-Bowden & Cárdenas, 2020 for more detailed reviews), Rosen's *M-R systems* or Kauffman's *autocatalytic sets* would represent the former (i.e., network approaches) and Maturana and Varela's *autopoiesis* or Ganti's *chemoton* the latter (protocell approaches). Let us briefly review, with a critical eye, the effective progress made in the prebiotic research camp, over the years, by following these two general organizational schemes.

### 9.2.1 Network Models

Most empirical approximations to the problem of origins of life have been championed by chemists (organic synthetic chemists, in particular), whose main interest is deciphering abiotic reaction pathways that could lead to various, specific biomolecules (Ruiz-Mirazo et al., 2014). This, although important to address, does not lead very far in terms of understanding the first biologically relevant *organizations*, as we said above. Nevertheless, in recent years, with the advent of systems biology and systems chemistry, an increased awareness in the community about the importance of dealing with complex mixtures in a prebiotic context has brought about a much more compelling research scene (Ashkenasy et al., 2017; Kroiss et al., 2019; Wolos et al., 2020), in which strongly reductionist approximations to the problem (e.g., working with one type of molecule, or one type of chemistry – even if this is claimed to be fundamental for life) are no longer valid.

There were some remarkable achievements associated with the idea of autocatalytic networks in the past (e.g., von Kiedrowski's (1986) self-replicating oligonucleotides, or the analogous oligopeptide systems developed by Ghadiri's group (Lee et al., 1996)), but these were just networks of oligomer-pairs with a template that coupled through a single, potentially autocatalytic recognition mechanism, rather than a collectively or reflexively autocatalytic network. Subsequent expansions toward more complex systems (employing combinations of more diverse components and higher-order catalytic and cross-catalytic mechanisms operating in parallel, within the same pot) led to interesting, emergent properties at the collective level (for a review, see Dadon et al., 2008). Similar investigations have also been carried out with populations of different RNA molecules designed to build cooperative relationships among them in order to achieve some collective autocatalytic behavior (see, e.g., Vaidya et al. (2012) or, more recently, Ameta et al. (2021)). Nevertheless, despite their obvious interest, we consider that these emergent phenomena are not so relevant, prebiotically speaking. Although they do reflect a complex global dynamic behavior that could not be predicted from the pieces of the puzzle (like in self-organizing phenomena, in which the more pieces you mix, the more difficult it becomes inferring, from individual molecular/mechanistic properties, what will happen at the overall, network level), their potential to build minimally robust,
integrated material organizations is still unclear.<fnref n="3" /> Many similarities can be drawn with the general case of dynamic combinatorial libraries (DCLs), and more so if they are under non-equilibrium conditions: the higher compositional diversity one introduces, the more interesting (and difficult-to-predict/analyze) phenomena one obtains (Corbett et al., 2006; Reek & Otto, 2010) but, without more demanding systems requirements (in particular, without the development of spatial and energetic control mechanisms) where do those phenomena lead to?

Many of these works, in addition, are not so concerned about the prebiotic plausibility of the components used. They are just demonstrating that chemistry is much wider than biology, in terms of molecular structures and nontrivial combinations thereby. Nevertheless, complex dynamic behavior does not immediately lead to molecules and transformation processes that establish and develop functional relationships, like those so characteristic of living organisms (see Sect. 9.3.1). The key question does not seem to be molecular and interactive diversity per se but playing with the biologically relevant type of diversity, with the aim to open a new window of dynamic behavior, performed by more complexly organized systems. Yet, this combination of material ingredients and conditions for viability does not come for free: they need to be physically constructed and maintained. Unlike self-organizing phenomena, which often run spontaneously (given some initial/boundary conditions), biological organization involves a thermodynamic effort right from the beginning (that is probably the reason why proto-metabolisms are not so easy to implement).

A good number of labs and researchers are actually focusing on how fundamental metabolic cycles and synthetic pathways (as they are realized in biochemistry, or in similar versions) could run under prebiotic conditions (i.e., in the absence of enzymes, making use of alternative catalysts) (Keller et al., 2014, 2016; Coggins & Powner, 2017; Muchowska et al., 2017, 2019; Springsteen et al., 2018; Stubbs et al., 2020). These groups are opening the origins-of-life field in a really interesting direction, demonstrating that there could be a natural bridge (or several bridges, right now under exploration) between organic chemistry and biochemistry, to be then reinforced through the development of proteins and enzymes, but not necessarily dependent on the latter at the very beginning. The importance of considering metabolism as the central problem in biogenesis is that the material and thermodynamic hurdles involved become apparent: they actually turn to be the main focus of research. However, the results obtained on these lines, though highly promising, are still far from “minimal metabolisms” because they have not managed to couple the

<footnote n="3">³By an “integrated material organization,” we mean a molecular system where all components are strongly interdependent and constitute a coherent, operational unit that self-maintains. Minimal robustness, in this context, requires the combination of different physical and chemical factors. More precisely, compositional and interactive diversity, along with phase heterogeneity (the coupling of chemistries taking place in various reaction domains) seems critical to achieve this kind of collective and operational molecular interdependences (Ruiz-Mirazo et al., 2017; Lauber et al., 2021).</footnote>
reactions with adequate, endogenously synthesized material constraints that should act as first-order control mechanisms on those same reactions. This is crucial, as we will expand below, for any material organization to be able to *construct* itself autonomously (see Ruiz-Mirazo & Moreno, 2004, 2012 and also Lauber et al., 2021).

## 9.2.2 Protocell Models

Network approaches are mostly concerned with chemical reactions (in particular, their stoichiometry and kinetics). Yet, the problem of origins of life is not only chemical: physics also plays a fundamental, complementary role in it. In support of that claim, one can always bring to the fore the fact that all biological systems heavily rely upon boundaries and compartments, as their universal cellular character indicates, which has deep energetic and thermodynamic implications (Harold, 1986, 2001). Following this premise (more explicitly stated in footnote 3), the protocell research camp has flourished in the last couple of decades. There were, of course, remarkable pioneers earlier on, starting from one of the founders of the origins-of-life field, Oparin, but also including other key figures, like Deamer or Luisi, who defended the prebiotic importance of lipid compartments in times when it was still a rather marginal line of work (for a nice review on the history of the field, see: Hanczyc, 2009). The situation changed with the turn of the century, when the “lipid world” hypothesis was introduced (Segré et al., 2001) and highly influential researchers, like Jack Szostak, coming from the RNA-camp, started investigating protocellular systems in depth (Szostak et al., 2001).

This contributed to widen the field of origins of life, embracing in the same move some of the non-reductionist postulates coming from the field of systems biology (Ruiz-Mirazo et al., 2014, 2017). Indeed, the assumption that protocellularity is central in the early stages of biogenesis brings forward a concept of prebiotic individual that goes definitely beyond the molecular level: rather than populations of molecules as such, what one should consider is populations of molecular *organisations* constructed within compartments. Or, more accurately expressed, one should consider molecular organizations that also build their own boundaries and constantly traffic with matter and energy through them to achieve a precarious self-maintenance, with potential to propagate through reproduction and evolve as a protocell population. Taking seriously into account a global constraint, like a vesicle membrane, that derives *from* and exerts spatial control *on* a set of encapsulated chemical species/transformations (introducing new rules for dynamic behavior that need not be strictly stoichiometric – e.g., osmotic and volume effects, generation/management of electrochemical gradients) has far-reaching implications, both in a proto-metabolic and in proto-evolutionary sense. Unfortunately, many chemists feel out of their “comfort zone” working with colloidal systems (like lipid vesicle suspensions), hence their traditional reluctance to investigate this domain. But postponing the problem of compartmentalization to later stages in biogenesis only makes it
worse (Piedrafita et al., 2012; Szostak, 2012), and the community is beginning to
realize this.

Thus, during the last two decades, there has been a remarkable increase in the scientific exploration of protocellular systems, in diverse directions, and taking up both bottom-up and top-down approaches. The development of synthetic biology, in particular the “synthetic cell” research program, has also contributed to this expansion (de la Escosura et al., 2015), even if most of that work is far from being prebiotic, and often just recreates biochemical processes under well-controlled, artificial conditions (e.g., through the use of synthetic liposomes). Nevertheless, understanding the principles of organization underlying real, prokaryotic cells (the *end result*, from an origins perspective) or simpler, hypothetical versions of them (the *intermediate steps*) also requires making use of material components and conditions that are alternative to the standard, biological ones. In this vein, we will briefly review here experimental work that is especially interesting from a particular theoretical perspective on biology and primordial biogenesis, the “autonomy perspective” (that we embrace and have contributed to develop (Ruiz-Mirazo & Moreno, 2004, 2012; Moreno & Mossio, 2015)),<fnref n="4" /> but without paying so much attention on whether the material aspects involved in those (proto-)cellular systems exactly match the actual biochemistry and biophysics that we know on planet Earth.<fnref n="5" /> The autonomy view, when focused on the process of biogenesis, is particularly interested in finding paths toward prebiotic systems whose internal complexity (i.e., the diversity of components and interrelations among them) is organized in such a way as to achieve their own sustainability. Namely, systems that can build – at least, part of – the boundary conditions that allow for their existence as precarious organizations in far from equilibrium conditions.

Maturana and Varela (1980) and their theory of *autopoiesis*, forerunners in this way of thinking, were more concerned about capturing the “organizational core” of the living phenomenon than to understand its origins. There were others, like Luisi, who took up the job of trying to implement those ideas in an empirical research program that could illuminate biogenesis (Luisi & Varela, 1989; Walde et al., 1994; Luisi, 2006; Bich & Green, 2018). That research program, established 30 years ago, is still active and giving interesting results, e.g., Hardy et al. (2015); Post and Fletcher (2020). The main motivation that articulates this type of investigation (which blends very nicely with our conception of the origins of life as the evolutionary development of autonomous, protocellular systems (Ruiz-Mirazo & Moreno, 2004; Shirt-Ediss et al., 2017; Ruiz-Mirazo et al., 2020)) is the exploration of how

<footnote n="4">⁴The idea that biological organisms are autonomous systems has deep historical roots, although the modern explicit use of it can be attributed to the Chilean biologist Francisco Varela (Varela, 1979). The general claim is that the property of autonomy can be naturalized and applied to molecular systems with an organization that produces and maintains itself.</footnote>

<footnote n="5">⁵This is often taken as a criterion for prebiotic plausibility, but we consider it is somewhat narrow-
minded (too Earth-chauvinist, as it is commonly expressed), especially from the wider perspective
that fields like astrobiology, artificial life, and synthetic biology have given to the problem of
origins.</footnote>
the generative power of chemistry (typically, autocatalysis) can be coupled to the (self-assembly) dynamics of the compartment, so that relatively simple protocells stay in non-equilibrium conditions, through that mutual reinforcement, becoming *active* and, potentially, *reproductive* systems.<fnref n="6" /> This (the capacity to make thermodynamically viable the synthesis, growth, and reproduction of a system) is of fundamental importance not only to understand how chemistry may get organized *biologically* but, furthermore, to realize how such an achievement actually requires the unfolding an evolutionary dimension – an aspect that was utterly disregarded by the autopoietic school.

Other “bottom-up” approaches, like the one pursued by the Szostak’s lab, have provided key insights into protocell growth and division processes, usually in the context of a population of vesicles competing for the available lipid monomer, either through osmotic effects (Chen et al., 2004), differences in the membrane lipid composition (Budin & Szostak, 2011), or internal synthesis of a hydrophobic compound (e.g., a dipeptide) that could spontaneously join the membrane (Adamala & Szostak, 2013). However, despite some interesting excursions into aspects like vesicle homeostasis (Engelhart et al., 2016) or membrane functionalization, combining lipids with peptides and RNA (Izgu et al., 2016), this group has not focused on the development of autonomous protocell behavior, as such, but on finding an adequate companion for RNA evolution, so that natural selection starts operating at a supra-molecular level. Yet, as we already argued above, when an evolutionary scenario is advocated as necessary to tackle the origins-of-life problem, this should be done taking into account the organizational complexity of the primitive individuals involved (like it is shown, for instance, in Piedrafita et al., 2017). On those lines, a former researcher of Szostak’s lab, Sheref Mansy, has recently established an independent line of research that is more directly tackling the issue of how complex should the “original protocells” be. In other words, is there a minimal threshold of complexity, like we suggest in Ruiz-Mirazo et al. (2017) and Lauber et al. (2021) for prebiotic evolution to get started? How many different constraints (i.e., material controls) must be put together to reach the platform for taking off? The Mansy group are pushing quite promisingly in this direction, in an effort to combine compartments, catalysts, energy currencies within the same experimental system (Bonfio et al., 2017, 2018), keeping also an eye on how chemical diversity can contribute to protocell growth and division processes (Toparlak et al., 2021).

In addition to these “bottom-up” strategies that start from scratch, so to speak (i.e., from physics and chemistry), other researchers take minimal-life exemplars (microorganisms or parasites) and try to simplify or deconstruct them. From such a “top-down” perspective (which should show us the finish line for the process of primordial biogenesis), there have been very interesting results in the last years, as well. The new Craig Venter *Mycoplasma* construct (Hutchison et al., 2016) was of course a landmark, in that regard: it has provided plenty of opportunities for further

<footnote n="6">⁶That coupling between chemistry and compartment may actually be considered as the key feature to define what a “protocell” is (Ruiz-Mirazo, 2011).</footnote>
exploration, not only about its physiology and metabolism (a highly complex, genetically instructed metabolism, as one could expect (Breuer et al., 2019)), but also about its reproductive potential or reliability (Pelletier et al., 2021). Although these minimalist approaches push in a direction in which both the autonomy of the cells (i.e., their actual capacity to survive in “free-living,” changeful environmental conditions) and their reliable reproduction (i.e., their ability to generate “normal offspring”) are taken to the limit, their study is critical to discern, precisely, the boundaries of biology. In a similar vein, “semisynthetic” constructs, like the biore-actors developed by Noireaux et al. (2011) or, more recently, Blanken et al. (2020), are also very informative. These involve biomolecules and other parts/subsystems of biological organisms under compartmentalized (in vesiculo) artificial conditions, with the aim to investigate the complementary relationship between membrane and endogenous reaction pathways, specifically focusing on the implications for auton-omous behavior – an illuminating and very interesting line of work for the future.

Nevertheless, in order to conclude this section, we must acknowledge that the empirical evidence available to date is still clearly insufficient to elaborate a mini-mally consistent and complete organizational account for the origins of life, in the sense of establishing a plausible sequence of transitions that cover all the ground from complex, non-equilibrium chemical systems to the simplest biological ones. There are theoretical models (in particular, protocell models – from the classical (Varela et al., 1974; Ganti, 1975; Dyson, 1982) to much more recent and refined ones (Ono & Ikegami, 1999; Castellanos et al., 2004; Macía & Solé, 2007; Mavelli & Ruiz-Mirazo, 2007; Ruiz-Mirazo & Mavelli, 2008; Van Segbroek et al., 2009; Mavelli, 2012; Shirt-Ediss et al., 2015; Piedrafita et al., 2017; Pechuan et al., 2018; Attal & Schwartz, 2021) that try to fill in the current holes and open new avenues of research. The advantage of the latter (as compared to strict molecular simulations of prebiotic chemistry, usually linked to the network models reviewed above – or to other protocell models that tackle evolutionary dynamics but simplify so much organizational aspects that cannot be called properly “protocellular,” e.g., Kamimura and Kaneko (2010, 2019) is that they offer a richer picture in terms of “constraint-based” or “rule-based” modeling techniques (see Lauber et al., 2021 and references therein). Thus, they are probably much closer to the complex reality of the first protocells that were involved in the process of biogenesis. Yet, without more solid, ample, and informative experimental results, it is very difficult to move forward through theoretical-computational approaches.

Furthermore, by focusing on the organization of individual protocells, like most of the previous works do, we may be limiting ourselves, “hitting a wall” that is there, but not so easy to see. In other words, we may be overlooking a fundamental bottleneck that needs to be addressed at the population level, as will be discussed in the remaining of the chapter. The crux of the matter will be finding the adequate balance between the two perspectives, organizational and evolutionary, and how they actually get intermingled. The discussion that we open here, in any case, points at one of the most difficult issues in the problem of origins of life, for which scien-tific insights and methods are still to be developed, so our aim is just to pose it in conceptual terms and draw some implications for future research.
## 9.3 The Interweaving of Organizational and Evolutionary Processes in Biogenesis: A Complementary but Causally Asymmetric Relationship

The historical dimension of life is a commonplace, a recurrent theme. While life is manifested in the form of organisms (and associations of organisms, whose spatial borders are often not so trivial to determine), the complexity of their material components and organization seems inexplicable unless appealing to a long process of evolution, beyond the time span of each of those individuals. «Nothing in biology makes sense, except in the light of evolution», as Dobzhansky famously remarked. This means that we must consider systems that, before disintegration, reproduce the essential features of their organization (what is usually understood, in general terms, as “heredity”) and generate, in this way, a set of causal entailments that propagates in time and space, transcending the limits of such an organization (i.e., of the actual organization that constitutes each individual). The collection of temporally similar systems brought about through reproduction across “successive generations” constitutes a “lineage” (or a “phylogeny” – when genetic mechanisms are under focus). In that context, where the analysis must obviously scale up to a “population” level, variability also tends to be assumed (linked to some inevitable, random modifications) in the reproductive success of the individuals (i.e., their “fitness”), which leads (through a combination of selective pressures and cooperative dynamics) to a highly complex phenomenon that shows both long-term maintenance, in a basic sense, but also continuous change and diversification along the way.

In contrast to the intricate molecular and energetic couplings that constitute the organizational core (i.e., the metabolism/physiology) of organismic processes, as we discussed in the first part of this chapter, evolutionary processes cover a completely different dimension of the phenomenon of life, where causal connections extend across much larger temporal and spatial scales. In fact, the interesting point is not just that evolutionary processes are spatially and temporally wider than organismic processes: they are also ontologically different. They concern population dynamics, in which remarkably looser “organism-environment” and “organism-organism” causal interactions (i.e., less demanding or stringent than the molecular interactions *within* each organism) are the key. An additional peculiarity is that the relevant effects of these interactions can only be adequately analyzed statistically and, even more importantly, through a very long time window: a time window during which most of the causally responsible entities or agents (the actual organisms, the “tokens”) have already disappeared, after participating in a *sedimentation* process of the most successful lineages (i.e., the “types,” which are conserved).<fnref n="7" /> Thus,

<footnote n="7">⁷We will use here the term “sedimentation” (Walsh, 2018, personal communication) as a generalization of the idea of “selection.” Evolution does not only result from competition dynamics but also from cooperative relationships among the individuals/agents of a population, which play an active role in the process (Walsh, 2015). The idea of sedimentation conveys long temporal scales, in which different types of hereditary mechanisms, with different degrees of reliability (i.e., different “trans-generational depth,” genetic and nongenetic) could be operating in parallel (Danchin et al., 2019).</footnote>
the organismic and the evolutionary dimensions of life, despite being deeply entan-
gled (and necessarily so, as we will expand below), hold an essential asymmetry:
the former relies on molecular components, processes, and interactions that con-
tinuously sustain each other in a tightly cyclic, self-constructing, and self-referential
manner, whereas the latter is the result of an open, long-term, and much wider
process of sorting out that takes place in populations of reproducing agents, across
many successive generations (Ruiz-Mirazo et al., 2020).

How can all this get started? And in what sense does the origin of such a com-
plex, asymmetric entanglement help us understand the unfolding of a biological
domain? Well, a central issue that must be highlighted straightaway (in line with
what we just described in the previous section) is that the first chemical systems
with potential to start turning biological were relatively complex but still precarious,
given their far-from-equilibrium nature. How were these systems, then, capable of
increasing their stability and robustness? We should realize that this is not a trivial
task, especially if it requires an effort of synthesis of progressively more complex
molecular ancillary. Fortunately, steady self-maintenance in this context would be
the exception, rather than the rule: vesicles in heterogeneous, changing conditions
naturally tend to undergo fission and fusion processes and more so if they are cou-
pled with physical gradients and chemical reactions (see, e.g., Carrara et al., 2012;
Oglêcka et al., 2014; Toparlak et al., 2021) for an experimental survey of this type
of scenario). In other words, it is more realistic to consider that the large majority of
such primitive protocells were very dynamic (favoring either growth or shrinkage,
potential division, intermingling, decay, etc.) not organized for the stabilization of a
steady state – like it is often assumed in theoretical models about minimally autono-
mous (autopoietic) protocells. Therefore, one should imagine this setting as a mess
of diverse “populations” of organizationally similar systems, i.e., groups of growing
and dividing protocells with their own suite of dynamic and plastic behaviors, which
also brought about many processes of merging and content reshuffling (e.g., through
vesicle fusion).

The advantage of such a scenario is twofold: (i) on the one hand, protocells
would have an intrinsic tendency to grow and divide, to reproduce and propagate;<fnref n="8" />
(ii) this intense activity would be an obvious source of novelties, which could even-
tually be kept in the system if they contributed to the far-from-equilibrium mainte-
nance of a given type of protocell (including here the first point, too – i.e.,
*maintenance through reproduction*). Nevertheless, these mechanisms for preserva-
tion through statistical reproduction and generation of molecular novelties (that
could be recruited for the protocellular organization) were probably quite poor dur-
ing the initial stages. Under such conditions, the main “driving forces” for prebiotic
complexification would depend on some specific boundary conditions (a range of
temperatures, osmolarity, pH values, gradients, etc.) that could sustain protocell

<footnote n="8">⁸By “reproduction” (or “propagation” (Kauffman, 2000)) of an organization, we mean here the process through which a complex system (in this case, a protocell) generates physically detached similar systems (i.e., other protocells with a similar material composition and organization).</footnote>
synthesis and dynamics, rather than on the robustness of their internal self-
constructing organization or on their agency.

Anyhow, that incipient capacity for propagation of an organization could explain that, at a given stage, growth and fission led to the generation of protocells capable to reproduce through some primitive (still statistical, stochastic) mechanisms of transmission of their compositional and organizational identity (as suggested, for instance, by Segre and Lancet (2000) through their “composome” idea).<fnref n="9" /> The iteration of self-reproducing cycles would generate a somewhat longer-term continuity of a specific *type* – the incipient lineage – constituted by populations of similar self-reproducing protocells. At the level of each protocell – as a particular *token* – the mechanisms involved in its reliable reproduction would trigger a diachronic succession of similar self-reproducing organizations, and in this way the innovations may have been retained beyond the particular fate of each individual protocell (Ruiz-Mirazo et al., 2020).

Hence reproduction (viz., growth and fission ending up in at least one new, phys-
ically separated, similar entity) would become the way in which the system displays
its own far-from-equilibrium self-maintaining dynamics, and, at the same time, the
consequence of these dynamics is the maintenance of a similar type of protocells (a
particular “protocell lineage”) through the continuity of generations. Interestingly,
some proto-organismic innovations could be thus stabilized, and, even more impor-
tantly, this trans-generational continuity (type preservation) would also allow orga-
nizational changes, because it may have involved the accumulation of variations
across long time periods. All this, of course, would be enhanced if molecular mech-
anisms to record (at least, to some extent) the increasing complexity of the protocell
were developed, in parallel, at the molecular level (e.g., template mechanisms) giv-
ing way to progressively more reliable “hereditary” transmission of various fea-
tures – even if the evolutionary (trans-generational) depth of these mechanisms
would be rather small at those early stages (nothing comparable to later, genetic
mechanisms).

The central issue here, in a situation in which nature must have faced a huge
bottleneck (perhaps the biggest bottleneck it has ever faced), would be to develop
material constraints that would enable these systems to solve two fundamental prob-
lems at once: (i) increase the robustness of the precarious individuals/agents and (ii)
preserve the level of complexity they reach, in a way that is both operational for
each individual, during its existence as a protocell (its “proto-ontogeny”), and for
the collection of individuals it may bring about (its “proto-phylogeny” or “proto-
lineage”). Solving these two problems requires obviously higher metabolic effi-
ciency of the protocells, which is necessary both to ensure maintenance against
perturbations and reliable reproduction. But the key is to realize that the solution is
not at reach for any kind of metabolism: a remarkable threshold of molecular and
organizational complexity must be reached, and systems below that threshold will

<footnote n="9">⁹This proposal was made in the wider context of a “lipid world” (Segré et al., 2001), some of whose assumptions we share, but some others we don’t (in particular, the open-ended character of the evolution that such systems could implement – see: (Ruiz-Mirazo et al., 2008)).</footnote>
naturally tend to decay. Von Neumann's idea of the "universal constructor," of course, resonates with force in this context (i.e., the problem of determining the logic of a system, the architecture of relationships among its operational modules, so that it builds itself, avoiding disintegration, across generations – see McMullin (2000) and Ruiz-Mirazo et al. (2008) for a more extended discussion). Yet the way this issue was originally posed avoided many aspects that had to do with the physical/material implementation of the systems that could become universal constructors, which might be crucial, as von Neumann (1966 [1948]) himself acknowledged. By focusing on the question of primordial biogenesis, we are precisely trying to naturalize the problem, going all the way back to its primary roots, and taking up a conceptual but unmistakably nonabstract standpoint.

Thus, as we were saying, evolutionary changes are the consequence of a long, historical series of causal actions performed by particular protocells belonging to a "proto-population" (or a family of protocells). Most of these changes (generated through a large number of reproductive cycles in a pool of similar systems) will be lost; but some variations in certain protocells will contribute to an increase in organizational integration and adaptive potential, generating more stable and somewhat deeper lineages (proto-phylogenies). In this way, trans-generational continuity may afford the maintenance and slow transformation of protocell lineages, facilitating the appearance of new protocellular types, whose organization is metabolically more efficient and has more and more control over external conditions. This is why reproduction with heredity is so important for the progressive complexification of such proto-organisms, allowing for their transition toward full-fledged biological organisms. Therefore, the evolutionary dimension indirectly (but with an increasing weight) affects the composition and organization of new generations of protocells, and more so as their reproductive capacities become more reliable, enabling higher and higher levels of sustainable organizational complexity.

In Sect. 9.4, below, we will give a rationale about the actual transition from these initial stages toward a situation in which the interweaving between the organismic and evolutionary dynamics becomes really profound, inextricable, as it is necessary for the unfolding of biological phenomena. But, once the complementarity between these two dimensions of life has been brought to the fore, let us say a few more words on the asymmetry involved in their relationship. Metabolic organization (the core of the individual dimension) is run and maintained in each (proto-)organism through a set of "rate-dependent" causal connections (Pattee 1977): namely, causal connections that crucially depend on specific conditions of distance, velocity, and energy requirements. In Ruiz-Mirazo et al. (2017), following Ruiz-Mirazo and Moreno (2004), we propose a minimal set of (first-order) control mechanisms that would be necessary to keep basic autonomous systems, like these protocells, in far-from-equilibrium conditions (kinetic, spatial, and energetic control mechanisms, more specifically). In any case, what is important to highlight for the discussion here is that this kind of organization can only stand robustly and efficiently on its own feet if, and only if, its constituent parts are highly *integrated*. The idea of organizational integration (as it was discussed in the first part of the chapter) expresses the fact that the different parts and processes of a system are highly interdependent:
there is a need to coordinate the distances, times, rates, and energies involved in all of them. And when the system's complexity increases, the need to introduce regulatory mechanisms that reorganize some parts in differentiated levels (constraints on top of constraints) also becomes apparent (again, see Sect. 9.4, below, for further explanations).

Thus, the pressure for integration is inherent in any system whose identity is based on a far-from-equilibrium, cyclic set of synthetic processes (always coupled to matter and energy sources from the environment), namely, on a logic of self-construction that depends on the specific energy requests and the actual rates of their (always precarious) constitutive/interactive dynamics. That is why such systems cannot increase in complexity unless they enlarge the web of endogenous (higher-order) constraints and their assorted integration—including mechanisms to control the relationship with the environment (which will lead to the development of minimal forms of agency). In sharp contrast with this, the maintenance of an evolutionary process, per se, is much less demanding. Or, rather, it is demanding but in a completely different way: what matters there is the reliability in the transmission of constraints across generations, within the dynamics of populations of reproducing systems, all of which is averaged out in a very long and complex sedimentation process. In this context, part of the causal connections operate as if they were “rate-independent” (Pattee, 1977), even if they must be continuously supported by the set of (rate-dependent) cyclic causal connections that constitute, maintain, and reproduce each protocell in far-from-equilibrium conditions. As the mechanisms of heredity (or “control on variability” (Ruiz-Mirazo et al., 2017)) become more and more reliable, the relevant historical series (i.e., the “trans-generational depth” or the average number of generations through which those constraints do no suffer relevant changes (Danchin et al., 2019)) becomes longer, more relevant, and profound in evolutionary terms. This has very important implications for “open-ended evolution” (Ruiz-Mirazo et al., 2008), as we will recall in the next section, but a fundamental related issue must be explicitly addressed first: functional expansion and diversification.

### 9.3.1 *Trans-generational Constraints and the Expansion of Functional Space*

The emergence of a functional domain (a world where material systems exist by virtue of what they do – i.e., by virtue of their dynamic causal effects (Mossio et al., 2009; Moreno & Mossio, 2015)) is important in this prebiotic context precisely because it is behind the key fact that during biogenesis chemical diversity gets reduced and narrows down to a relatively small subspace of “the molecularly possible.” As the rich mess of prebiotic processes and material transforms into more elaborate chemical organizations, a progressive selection takes place, favoring those molecular components capable of putting together cohesive far-from-equilibrium systems. Regardless of the time this may take, only those components that have
allowed further complexification will be retained, and that has some important implications. In particular, it means that the chemical diversity will suffer a significant decrease, as this is a condition for systemic and highly integrated material organizations. The development of the necessary mechanisms of control (spatial, catalytic, energetic) actually requires fixing some of the molecular rules and components operating in these systems. More specifically, a subset of chemicals and reaction processes must be chosen both to generate components of control (internal constraints) and to be amenable to that autonomous control.

This, in our account, coincides with the emergence of “minimal metabolisms” (Lauber et al., 2021) and is actually the first moment in natural history where one can begin to speak properly in terms of *functions*, the claim being that these don’t emerge “one-by-one” (Ruiz-Mirazo et al., 2017): a combination of endogenously produced and tightly coupled constraints (operating as first-order control mechanisms on the underlying, far-from-equilibrium reaction network) must come together, from the very beginning, so as to constitute a minimally robust chemical system, similar to the protocell systems that we described at the end of Sect. 9.2. Therefore, the basic idea of “functional organization” (as an enduring form of self-maintenance) is deeply linked to that of material control and organizational integration. In this context, we should remark that the appearance of self-reproducing protocells already requires, as a precondition, the existence of populations of proto-cells with – still strongly limited but – nontrivial functional domains. The reason is that the reproduction of a protocellular and minimal metabolic organization involves managing quite a number of processes, like the duplication of certain structures of the system, coordinated with surface increase (and other modifications) in the compartment, as well as with an adequate temporal and spatial allocation of the components during growth (so as to ensure that, when fission actually occurs, the new entity is able to repeat a similar self-productive cycle). In other words, reproduction requires a fair degree of control of the proto-metabolic processes, since growth and fission are the specific expression of the self-production regime of these protocells (Mavelli & Ruiz-Mirazo, 2007). One could say that spatial, kinetic, and energy control mechanisms, including the suitable coordination among them, constitute the necessary functional basis for any reliable trans-generational propagation of proto-cell organization (Moreno, 2019).

One should also recognize that the very idea of reproduction (see footnote 8) implies, right from the start, a minimal degree of reliability or “inheritance,” namely, the new, spatially separated entity has to be molecularly and organizationally similar to the parental entity. The first forms of reproduction would have been statistical, which means that similarity among the different members of the progeny was ensured only partially – at some percentage, so to speak. As it is argued in (Danchin et al., 2019), an increase in the reliability of reproduction was most probably a consequence of a stronger degree of functional integration, and this, in turn, through reproductive steps, resulted in the selection – or sedimentation – of the most efficiently integrated protocells, which nicely illustrates how the aforementioned link between evolutionary and physiological (proto-metabolic/protocellular) processes can be, in practice, coherently articulated.
Conversely, the incipient connection between these two phenomenological dimensions (that will develop and get reinforced throughout primordial biogenesis) has really interesting and far-reaching consequences with regard to the functional domain itself, which can expand through novel ways of contributing to maintenance that become available to those protocellular populations. Indeed, such a connection opens the door to a completely new set of functionalities, which lie beyond the strictly physiological sphere of each protocell. A function in this extended functional domain can acquire “temporal/historical depth,” in so far as some feature/property of the system is linked to the new ways of ensuring organizational maintenance across generations. This allows to establish a natural conceptual bridge between the *organizational* and the *evolutionary* interpretations of function (Saborido et al., 2011). Indeed, from this stage onward, it makes sense to say that a trait (a component, a mechanism, a property of the organization) X in a population is there because it has been selected/sedimented through a complex evolutionary pathway. In other words, in our prebiotic context, X would be there because those protocells that bear X – and were capable to transmit it to their offspring – have a (relatively long-term) history of reproductive success through which X remains in the population. In this sense, we must open ourselves to the possibility that there are functions whose contribution to the current individual organization of the system is not so obvious, and they should be analyzed in a wider time frame, i.e., there could be functional traits that contribute to the maintenance of the *type* and, thus, only indirectly to the maintenance of any particular *token*.

Let us explain how, in just a couple of paragraphs, before moving on. As we have discussed, the possibility that some protocells managed to achieve relatively reliable reproduction cycles would depend critically on the synthesis of a number of material constraints controlling the processes of growth and fission. Certainly, there would be an organizational and material continuity between the initial, “mother protocell” and its subsequent offspring and, in this sense, the functional role of the constraints more specifically involved in the reproductive processes would not be distinguishable, in principle, from the nonreproductive functions. However, more and more reliable self-reproductive systems require additional control mechanisms: in particular, hereditary mechanisms that should be focused in managing the variability generated in these protocells, preserving the level of complexity reached and making “statistical numbers,” so to speak, “no-longer-statistical.” But this, in turn, requires, as we will expand in the next section, a *dynamic decoupling* with regard to the current organization and the specific times, rates, and energies required by each individual metabolism. In a concurrent way, the organizational architecture of the protocells must be profoundly modified, through a *hierarchical coupling* with these new mechanisms that can no longer be considered, simply, as the result of the constructive power of each individual but rather as the result of a much more complex evolutionary process in which whole populations are involved.

Somehow, we are facing a scenario in which the organization of individual entities transforms the way in which evolution occurs and evolution also transforms, more and more profoundly, those individuals. But what should be especially underlined here is that all this takes place in the context of – and thanks to – the capacity
of these protocellular systems to enlarge and diversify, enormously, the space of
possible functions though which they are realized (starting from that initial, mini-
mal set that we mentioned above). Although a good part of such a space will be
filled by strictly physiological control mechanisms, some other regions will not
simply belong anymore to individual “tokens” but to the “types,” the lineages, that
consolidate through longer-and-longer-term population dynamics. Therefore, the
main problem at this stage (and from this stage onward) is not dealing with chemi-
cal diversity, heterogeneity, and messiness (what is classically regarded as the com-
binatorial explosion of molecular interactions and transformations) but dealing with
an increasingly rich space of functionalities, expanding in different – though inter-
connected – directions. A fundamental issue will be addressed next, in Sect. 9.4.

9.4 “Dynamical Decoupling”: A Key Principle to Understand the Evolutionary Development of Complex Material Organizations

Taming complexity in systems that develop numerous functionalities and thus, a large space of possible dynamic states/behaviors is not a trivial task. These systems can realize in multiple ways their basic constitutive regime, as self-constructing protocells (minimal metabolisms) in constant interaction with a variable environment, shifting from one stationary state to another, depending on the conditions that they meet at any given time. More precisely, dynamic multistability poses a remarkable organizational challenge in an evolutionary setting like the one we just described above: the challenge of how to navigate efficiently that space without wasting time and resources that could be critical for the persistence of the individuals involved. This is a problem that cannot be taken for granted, nor assumed to be spontaneously solved by nature: it requires work, literally (viz., in a thermodynamic sense), and time, plenty of time, to develop the necessary mechanisms. In line with other authors that have previously addressed it (in particular Christensen, 2007), we consider that simple feedback mechanisms, or even combinations of positive and negative feedbacks, if they work “online” (at the same rates/conditions in which metabolic processes take place), are not sufficient to deal with it. Let us try to explain, briefly, why.

In principle, when facing perturbations, a functional system can restore its con-
stitutive and behavioral coherence through self-organization<fnref n="10" />, namely, through par-
allel local interactions that generate emergent outcomes (without making use of
specifically devoted mechanisms of regulation or higher-order controls). Yet, this
solution only works when the number of different functions to be coordinated is not
very high. As the complexity of a system increases, these dynamically coupled

<footnote n="10">¹⁰In the context of our discussion here, this would apply to *minimal metabolisms* (i.e., *basic “self-construction”*).</footnote>
(“online”) mechanisms become clearly insufficient. As Christensen (2007) rightly points out (reasoning in a cognitive context but using arguments that are perfectly applicable at a much more basic level), self-organization has intrinsic limitations to achieve functional coordination. The reason is that the process of reaching a certain global state, in such a case, depends on the reliable concatenation of state changes through local interactions, and those cascades of events add a delay as the functional diversity of the system increases. Nevertheless, robust global coherence/behavior against variations requires selecting very precisely a given dynamical attractor and maintaining the system there during a given period of time. Therefore, if the organization of the system stays “flat” and “online,” it faces an obvious dilemma: either its capacity to generate multiple finely differentiated global states is limited, or, instead, the system will have to sacrifice the reliability of attaining a specific state out of that multiple choice. In Christensen’s own words, “slow action and poor targeting capacity severely limit the capacity of self-organization to achieve the kind of coherence that functional complexity requires (...) Consequently, the most effective means for achieving the type of global coherence required for functional complexity is through regulation, including feedback mechanisms and instructive signals operating at both local and larger scales. The key feature that distinguishes regulation from self-organization is the presence of a functionally specialized system that differentially specifies one or a restricted set of states from the range of possible states the regulated system might take, based on the sensing of system conditions and the production of control signals that induce changes in functional state” (Christensen, 2007, pp. 265–266).

In Bich et al. (2016) we argued, precisely, that (biological) regulation involves second-order control hierarchies that necessarily work “offline” in a relevant sense, or to a relevant extent. In other words, achieving effective control when the complexity of a system is very high requires a subsystem that is endogenously synthesized but operationally decoupled from the dynamics of the controlled processes, so that it can be modified without disrupting those underlying synthetic processes (Bechtel, 2007; Bich et al., 2016). Minimal metabolisms, as generally characterized in Lauber et al. (2021), do not constitute completely “flat” organizations, in the sense that they do require first-order controls (i.e., a set of elementary constraints) to operate. But regulation involves constraints on constraints, which make decoupling mechanisms effectively feasible in an autonomous organization. Basic, first-order controls are required to put the system together, but they are too closely engaged in the metabolic dynamics to be able to work “offline.” The question that we must address here, in any case, is why minimal forms of regulation, interpreted precisely in this vein (i.e., already implying a *dynamically decoupled* but *hierarchically coupled* individual system organization), were necessary during primordial biogenesis and how they were actually implemented in the (pre-Darwinian) evolutionary context of protocell populations described above.

As for the first point, we concluded the previous section highlighting that self-reproducing protocell systems demand, right from the beginning, a rather elaborate set of basic functions (those first-order, material constraints acting as “process controllers”: catalysts, compartments, etc.) just to realize themselves and that the
prebiotic evolutionary dynamics they bring about would contribute to expand their potentially available space for functionalities (including trans-generational constraints – such as hereditary mechanisms of various kinds). We consider that this hypothetical but plausible protocellular scenario is, indeed, complex enough to defend the need for second-order control mechanisms that help those systems navigate an internal dynamic space with multiple stationary states. The reason why such mechanisms should be considered as “second order” is because they must operate on top of the basic set of functions that already put together the constitutive regime of the system, with a variety of accessible dynamic attractors. In brief, the new controllers must be constituted by material constraints operating on other material constraints: there is no other way for nature to do it. And the reason why this action is “offline” has to do with the second point, which we must address now: how were such *hierarchical* autonomous organizations (Pattee, 1973) actually implemented for the first time?

In concrete operational terms, regulation is commonly understood as the harnessing of a system according to a set of rules (e.g., «in case of situation X, do Y»). Contrary to what occurs in artificially designed systems, where the rules are a collection of external norms, in natural (biological or infra-biological) systems, the idea of regulation points to an internal set of constraints that *functionally select* some specific dynamical configuration of the system, among several possibilities, as we expressed above (and as some other authors have also argued, to distinguish this estate of affairs from strict or minimal autopoiesis (Di Paolo, 2005)). Yet, what kind of “function” is this? In principle, it looks physiological, difficult to distinguish from the other, elementary ones – since it is exerted in ontogenic time scales, as an adaptive response of the individual, here and now, to a given environmental challenge: e.g., «if this nutrient is detected, swim up its gradient» or «if this toxin is found, do not absorb it». Nevertheless, these behavioral *shortcuts* are quite more complex than direct controls on a process. In fact, when one thinks carefully about their emergence, they cannot be easily understood outside an evolutionary perspective: regulatory mechanisms definitely seem to require a different time scale to appear and get stabilized in the population. They look anticipatory, when they are analyzed at the scale of a single individual – who “seems to know,” in advance, the outcome of its actions. Instead, these self-imposed instructions most probably come from a history of interactions that have taken place in the population and are linked to the persistence of those individuals, but throughout many generations.

As we explain in more detail in Bich et al. (2016), the nature of regulatory mechanisms is not straightforward: they involve material gears to shift from one constitutive regime to another depending on circumstances that must be associated to internal/external variables but without responding directly (through online mechanisms) to those actual variables (e.g., the concentrations of metabolites in the system). The system must “detect” internal/external circumstances selectively, which means distinguishing some inputs as “signals” that will trigger a rapid shift (the adaptive shortcut) to a given behavior (an alternative stationary state). Thus, it is not easy to describe in detail how these regulatory meta-constraints (including the molecular machinery that determines accurately when and how their action should
be executed) could have appeared. Further empirical and theoretical research needs to be carried out on this topic, within a pre-Darwinian evolutionary setting where different stages are distinguished and compared to the pre-regulatory (i.e., minimal metabolic protocell) phase. Yet, it seems quite reasonable to conjecture that regulatory mechanisms should be the result of a long series of “trials and errors,” in the context of protocell population dynamics in which subsequent generations of prebiotic individuals were developing, competing for resources, probing their local environments, etc. How it actually happened, putting all the pieces of the mechanism together, avoiding potential disintegration pathways, overcoming external perturbations, and keeping internal coherence, will not be obvious, but if it came about, the regulatory device would for sure be retained, because of its immediate contribution to the persistence of those protocellular systems that integrate it in their organization.

Interestingly, regulatory mechanisms may constitute one of the most prominent pieces of evidence to demonstrate that a sedimentation process is taking place at larger and longer scales, with very important implications at the level of the individual, here and now. The history of interactions of a population of similar protocells with their environment (including the interactions among them) gets eventually distilled or condensed into a relatively complex, built-in mechanism that ensures higher robustness and better adaptivity (quicker responses) by the members of the population to certain variations in the medium. In other words, regulatory meta-controls somehow reflect, also due to the intrinsic dynamical decoupling they involve, the interweaving between the physiological and the evolutionary dimensions of biological (in this case, proto-biological) phenomena. This interweaving is asymmetric, as we discussed in Sect. 9.3, because the physiological sphere always has causal priority (real self-constructing individuals are the material agents performing all relevant interactions, after all) even if the evolutionary sedimentation process, working at larger and longer scales, has a deep impact on the physiological mechanisms and organization of the resulting individuals.

However, regulation by itself is not enough to ensure reliability in the transmission of increasingly complex molecular and organization features to the offspring (including the regulatory apparatus itself, which could also face the risk of getting lost on the way). Hereditary mechanisms must be specifically developed for such a fundamental task. The conservation of system features across generations can be implemented through different means (and then interpreted according to different theoretical frameworks – e.g., Bonduriansky and Day (2018) or Mossio and Pontarotti (2020)), but we are particularly referring here to *molecular records* (Pattee, 1969, 1977) that, through their template properties, are capable of replication with conservation of their monomeric sequences. These hereditary mechanisms would be completely futile if they were not linked to concrete functionalities of the protocells in evolution, in either metabolic or global reproductive terms. Under the hypothesis of an “RNA world,” the same kind of molecule could be carrying catalytic power (“proto-phenotype”) and replicative potential (“proto-genotype”), but such a reductionist interpretation does not fit in our account. From a more encompassing organizational perspective, like the one we embrace here, the phenotype-genotype mapping would be quite more complex, right from the beginning.
In such a context, as primordial biogenesis proceeded forward, protocells would inherit, among many other components, molecular records whose functionality would be the result of a longer and longer evolutionary process, beyond the “life span” of each of them. At the same time, each hereditary record would play a key causal role in the metabolic organization of the protocell where it exists. In other words, a trans-generational constraint of this kind also embodies two different temporal scales: one that corresponds to its causal activity in the current physiological processes of the protocell and another one that corresponds to the long evolutionary history that has shaped the specificity of its functional sequence. Thus, hereditary mechanisms bring some other kind of dynamical decoupling into these systems. Records are *dynamically decoupled* from (but *functionally connected* to) the metabolic organization because (like regulatory mechanisms) they have been shaped in a different temporal and spatial domain. But in contrast to the rest of the system components, which functionally depend on each other (in the sense that the effects of some components generate and transform the others), hereditary records are not strictly generated within the metabolic organization of each protocell (although they are physically constructed, repaired, and replicated by it). More exactly, they are materially regenerated, preserved, and used within that metabolic organization, but they are not *informationally* generated within each protocell. And yet, it is precisely for this reason that the specific sequence of those hereditary components – what will come to be their “informational content” – allows for a much more robust and efficient mechanism of reproduction, even if the complexity of the metabolism would be much higher at these later stages. Eventually, “genetically instructed metabolisms” would introduce a completely different way of exploring innovations and variation in time: “open-ended evolution” (Ruiz-Mirazo et al., 2008).

As hereditary mechanisms (and phenotype-genotype mappings, in general) develop in protocell populations, regulation can also be applied, in turn, to all the processes in which those material records (which are meta-constraints, too, of course – but with their own specificities (Pattee, 1977, 1982)) are involved. In fact, the constructive and transformative power of combining these two different modes of dynamical decoupling, as it is reflected in the basic organizational architecture shared by all living beings (prokaryotic cell metabolisms, already endowed with a translation apparatus and a common genetic code), was surely crucial to reach the “hypercomplexity” that life required to maintain itself on the surface of the Earth in the long run (a situation that, we guess, should be similar anywhere in the universe, since the problems addressed here would apply to any material organization dwelling close to the von Neumann threshold).<fnref n="11" />

<footnote n="11">¹¹A more extended analysis and conceptual reflection on these issues lie beyond the scope of this contribution but should be an interesting topic for future work.</footnote>
## 9.5 Concluding Remarks

The aim of this chapter has been, as indicated in the title, to provide a theoretical framework, a plausible and reasonable account to understand how a biological domain could unfold from complex, nonliving matter. We are convinced that such an intricate transition must be a very long process, involving myriads of molecular systems that generate a great diversity of reaction networks which, over time, lead to increasingly complex material organizations. As this process of biogenesis proceeds, something quite intriguing happens: the phenomena taking place at a given stage, being based on the previous, somehow manage to redefine the conditions, the rules of the game, bringing about systems/organizations that overcome in efficiency and performance the preceding ones and ruthlessly eradicate the latter, leaving no traces behind. However, at a given stage, things radically change: systems sharing an organization with a set of fundamental features similar to what we call nowadays "prokaryotic life" come about and that evolutionary dynamics of "continuous substitution of the old by the new" stops. Not only because there is an unprecedented explosion of diversity and proliferation of these systems (probably all over the surface of the planet) but also because, from that moment onward, subsequent organizational innovations do not (perhaps, cannot) erase this basic type of organization. Instead, all novel biological complexifications become dependent and supported by prokaryotic life – they become, so to speak, curlicues, "convoluted redefinitions" of that same type of phenomenon. Hence, the target of any theory of primordial biogenesis should be to explain how such a fundamental but far-from-trivial material organization (genetically instructed metabolic cells) could naturally emerge.

Within this general context, we have focused the discussion on several key issues. The scientific work reviewed in Sect. 9.2 was mostly related to the early stages of the process: in particular, we collected evidence on how under favorable environmental conditions catalytically driven sets of reactions could turn into self-sustaining protocellular systems, which probably constitute, at those first steps, just a mess of growing and shrinking individuals, only later leading to more sequential fission and fusion events. Then, in the following sections, we explained how, over time, some of such protocells could manage to reproduce their characteristic type of organization, opening in this way a completely new scenario, which has not been explored empirically yet. On the one hand, more and more integrated functional systems (protocellular *individuals* of higher complexity) should start developing. But, on the other hand, lineages of different families of protocells (evolutionary *populations*) would also begin to form. These two apparently orthogonal dimensions of the phenomenon, unfolding in very different scales (both spatially and temporally), get nevertheless deeply entangled. And, through that entanglement, a really powerful driving force is generated that overcomes the apparent physical and material bottlenecks present at those stages, bringing about much more integrated protocells. In turn, these new protocells would not only be more robust but also capable of more reliable reproduction, which would then increase the weight of evolutionary aspects in the process.
Finally, we also discussed the importance of having protocells that develop hier-
archical relationships within their organization, namely, complex functional mecha-
nisms that operate on top of the (first-order) controllers of metabolic processes (i.e.,
only indirectly on metabolism), at rates significantly different from the ones involved
in those basic transformation processes, and thus, look as if they were working
“offline.” Embodied in two very different modes, regulation and heredity, this
*dynamic decoupling principle* also seems to play two complementary roles in pre-
biotic evolution: in the first case, enhancing individual (i.e., ontogenetic) adaptive-
ness, and in the second, increasing lineage (i.e., phylogenetic) fidelity. Nevertheless,
both modes (an effective combination of the two, more precisely speaking) are
apparently crucial to complete the process of primordial biogenesis, leading eventu-
ally to complex material organizations similar to prokaryotic cells. The physiologi-
cal plasticity of these cells, together with their capacity for open-ended evolution,
lies at the heart of the impressive robustness and long-term sustainability of the
phenomenon of life. Modeling all these prebiotic transitions, from initial families of
minimal metabolic protocells, to full-fledged living organisms (individuals with a
translation apparatus, a complex, code-mediated, phenotype-genotype mapping,
etc.) is still a great challenge for science. But making the challenge conceivable,
under realistic assumptions, is a first, necessary step to tackle it.

**Acknowledgments** This research work has been supported with grants from the Basque Government (ref.: IT 1228-19, recently extended to: IT1668-22) and the Spanish Ministry of Science and Innovation (PID2019-104576GB-I00), as well as from the John Templeton Foundation (Project Title: "Integration and Individuation in the Origin of Agency and Cognition" – Grant 62220). KR-M also takes part in a Horizon 2020 Marie Curie ITN ("ProtoMet" – Grant Agreement no. 813873) from the European Commission. We would like to thank Cliff Hooker and Juli Peretó, as well as the editor of the book, Matteo Mossio, for carefully reading a first manuscript of this contribution and providing critical feedback that certainly helped us improve it.

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**Chapter 10**
# Organization and Inheritance in Twenty-First-Century Evolutionary Biology

Gaëlle Pontarotti

**Abstract** During the last few years, various authors have called for the elaboration of a theoretical framework that would better take into account the role of organisms in evolutionary dynamics. In this paper, I argue that an organism-centered evolutionary theory, which implies the rehabilitation of an organizational thinking in evolutionary biology and should be associated with what I will call a heuristic of collaboration, may be completed by an organizational perspective of biological inheritance. I sketch this organizational perspective – which allows going beyond gene-centrism –, show how it grounds a systemic concept of heritable variation suited to the new evolutionary framework, and highlight some of its explanatory value and theoretical implications for evolutionary thinking.

**10.1 Introduction**

The gene-centered theory of evolution is sometimes presented as obsolete. Associated with twentieth century's modern synthesis, it is accused to outlook the role of organisms and of their properties in evolutionary dynamics (Walsh, 2006; Nicholson, 2014). Many authors have therefore recently called for the elaboration of a more organism-centered evolutionary biology (Walsh, 2010; Laland et al., 2015), notably in the context of an extended evolutionary synthesis (Pigliucci & Müller, 2010). Such biology is notably expected to integrate non-genetic channels of inheritance in its models but also to make some room to the concept of agency (Walsh, 2015) and biological organization (Müller, 2017) insofar as organisms – at the center of its preoccupations – are generally considered as paragons of organized and purposive biological systems. The objective of this paper is to argue that an organism-centered evolutionary biology may be enriched by a not only extended but also organizational perspective of biological inheritance, to sketch this perspective and to highlight its theoretical implications for evolutionary thinking.

<footnote>G. Pontarotti (✉)
Institut d'Histoire et de Philosophie des Sciences et des Techniques (IHPST, CNRS/Paris1),
Paris, France</footnote>
The argument is structured as follows. In Sect. 10.2, I briefly present the contemporary literature which invites departing from a gene-centered evolutionary theory and embracing a more organism-centered framework. I further suggest that an organizational perspective of biological inheritance appears as a missing ingredient in this theoretical movement that not only involves the return of an organizational thinking in evolutionary biology but that also follows a more global perspective shift, from a heuristic of replication – in which evolution is thought as a competition among self-replicating objects endowed with their own adaptive value – toward a heuristic of collaboration – in which biological objects are necessarily considered as parts of integrated wholes and cannot replicate independently. In Sect. 10.3, I rest on earlier studies (Pontarotti, 2015; Mossio & Pontarotti, 2019) to sketch an organizational perspective of biological inheritance suited to an organism-centered evolutionary biology, and I notably highlight that this perspective grounds a systemic concept of heritable variation appropriate to the new evolutionary biology's framework. In Sect. 10.4, I evoke some theoretical implications of an organizational account of inheritance for evolutionary thinking. I show how this account allows making sense of the evolution of “non-standard” biological systems<fnref n="1" /> and how it induces a change of perspective, in the wake of earlier contributions, as far as lines, fitness, selection, and evolution are concerned.

## 10.2 Toward a More Organization-Centered Framework for Twenty-First-Century Evolutionary Biology

In this Section, I briefly present the literature announcing a perspective shift, from gene-centrism toward organism-centrism, in evolutionary biology. I then highlight that an organism-centered evolutionary biology is expected to make important room for the concept of organization in its explanations. Consequently, I argue that it may be completed by an organizational perspective of biological inheritance.

### 10.2.1 *An Extended Evolutionary Synthesis to Fill in the Explanatory Gaps of the Gene-Centered Framework*

The theoretical framework of evolutionary biology has been seriously challenged for the last few years. Many authors have indeed advocated the necessity to adopt an extended evolutionary synthesis (EES) in order to overcome some of the theoretical and explanatory limitations of modern synthesis (MS) (Pigliucci & Müller, 2010).

<footnote n="1">¹The concept of non-standard biological systems usually refers to symbiotic associations or to insect colonies including abiotic parts (mounds). Here, it will designate all biological systems whose parts cannot simply be accounted by classical interactionist accounts (gene/environment). For more details, see Sect. 10.4.</footnote>
EES is described as a movement of conceptual and disciplinary extension (Pigliucci & Müller, 2010) but also as an alternative ecological-developmental perspective to evolution (Laland et al., 2015). In this respect, EES is not just an extension of MS but rather a “distinctively different framework for understanding evolution” (Laland et al., 2015). EES is meant to be more inclusive than MS. Indeed, while the latter makes sense of evolutionary phenomena through the articulation of Neo-Darwinism, Mendelism, and population genetics,<fnref n="2" /> the former is willing to include new elements in evolutionary thinking, notably concepts of evolutionary-developmental biology (e.g., plasticity), an extended vision of inheritance, as well as ideas about evolvability (Pigliucci, 2009, p. 218).

Let us go into more details. While MS ignores developmental processes, EES intends to shed light on the developmental origin of organismal variations. It stresses on the role of developmental constraints regarding the diversification of forms<fnref n="3" /> (Müller, 2017) and that of plasticity – “the capacity of organisms to develop altered phenotypes in reaction to different environmental conditions” (Müller, 2017, p. 5) – on evolutionary dynamics. Besides, while MS is based on a genetic account of inheritance according to which the trans-generational reoccurrence of features is exclusively underpinned by the replication of genes, EES integrates data about so-called non-genetic inheritance, for example, epigenetic and behavioral transmission. The framework also takes into account niche construction (Laland et al., 2015), namely, the fact that organisms modify their surroundings in such a way that they alter the selection pressure exerted on their offspring (Odling-Smee et al., 2003). This inclusion stresses on the “reciprocal causality” (Müller, 2017) at play in evolution, which means that organisms are not only submitted to independent selective forces but that they also define the selective pressures exerted on them and their offspring.

More generally, EES is meant to go beyond some “basic restrictions and methodological commitments” of MS (Pigliucci & Müller, 2010, p. 13). According to MS, evolution is a gradual process mainly driven by the selection of small and random genetic variations correlated with phenotypic differences (Mayr, 1998). ESS, as for it, intends to overcome gradualism (Pigliucci & Müller, 2010; Laland et al., 2015; Müller, 2017) in highlighting that evolutionary change can follow various paths (Pigliucci & Müller, 2010). As mentioned above, EES also aims at going beyond externalism, the hypothesis according to which independent selection

<footnote n="2">²Beyond the articulation of Mendelian genetics and Neo-Darwinian evolutionary theory through the mediation of population genetics, MS refers to the agreement of various disciplines – systematics, zoology, botany, paleontology, and natural history – on a set of core hypothesis (e.g., gradualism, creativity of natural selection, etc.).</footnote>

<footnote n="3">³It is important to make a clear distinction between the hypothesis of organismal origin of variation, according to which variation is originated and constrained by organisms themselves (and their developmental processes), and trade-off adaptationism, which states that organisms are trade-offs of adapted traits (e.g., trades between traits enhancing survival and traits enhancing reproduction). In the first case, organisms (and developmental processes) impose constraints on variation and have a key explanatory value in evolutionary theory. In the second case, natural selection is still the main explanans of organismal characteristics (for a detailed analysis, see Huneman, 2017).</footnote>
pressures are the main drivers of evolutionary change (Pigliucci & Müller, 2010; Müller, 2017). Finally, while MS is based on statistical analysis, EES appears as a causal-mechanistic framework (Pigliucci & Müller, 2010). In this perspective, evolution is not primarily portrayed as a change in gene frequencies mainly caused by natural selection (Dobzhansky, 1937) but as a change in phenotypes partly driven by developmental processes (Helanterä & Uller, 2010). These processes are thought to “share responsibility” with natural selection in the determination of evolutionary trajectories (direction and rate of evolution, origin of variation, etc.) (Laland et al., 2015). Genes, as for them, are sometimes described as followers (West-Eberhard, 2003; Pigliucci, 2009).

### 10.2.2 Focus on Organisms and Introduction of an Organizational Thinking

In this context, the focus of evolutionary biology changes radically. Evolution is not anymore thought as a matter of genetic dynamics but rather of organismal changes. Organisms – which are often described as developmental systems – appear as key causal agents in evolution. As summarized by Laland and colleagues (2015), EES is “characterized by the central role of the organism in the evolutionary process and by the view that the direction of evolution does not depend on selection alone and need not start with mutation.” While MS explains biological evolution by focusing on the scale of genes, EES is grounded on the assumption that “the organisms themselves represent the determinants of selectable variation and innovation” (Pigliucci & Müller, 2010, p. 13). In brief, EES represents a “different way of thinking about evolution, historically rooted in the organicist tradition” (Müller, 2017). As a result, it is meant to better take into account the role of organisms’ properties in the determination evolutionary trajectories.

On this specific point, the literature about EES meets other studies dedicated to the return of organisms in evolutionary biology (Bateson, 2005; Walsh, 2006, 2015).<fnref n="4" /> For example, Walsh (2006) analyzes that contemporary evolutionary biology has forgotten organisms in asking how supra-organismal entities (populations) change under the effect of sub-organismal entities (genes, replicators). He calls for the development of a Kantian-flavored biology which would take into account organismal properties in its explanations. Inspired by West-Eberhard’s contribution (2003), Walsh also suggests that phenotypic accommodation can sometimes precede genotypic one, and that genes can thus be followers in evolution (Walsh, 2006, p. 778). In a way, all these contributions follow considerations early on made by Mayr (1963, p. 184), who claimed that changes in gene frequencies is an effect and not a cause of evolution. To him, describing evolution as a change in gene

<footnote n="4">⁴For a general appraisal regarding the return of organisms in evolutionary biology, see Huneman (2010) and Nicholson (2014).</footnote>
frequencies amounts to neglect the mechanisms that cause organisms and popula-
tions' transformations.

To sum up, “the emerging view of evolution” presents organisms as “the primary agents of evolutionary change” (Nicholson, 2014). In this perspective, organisms are thought as a major *explanans* – and not only *explanandum* – of evolutionary processes (Huneman, 2010); organismal properties do not only appear as elements that should be explained, but they are also – and crucially – conceived as elements which contribute to the explanation of evolutionary phenomena. Now, if one considers, in line with an old tradition usually thought of as tracing back to Kant (1790), that the most fundamental and distinctive property of organisms is to be (self)organized, the emerging view of evolution should involve the rehabilitation of the concept of organization and the introduction of an organizational thinking in evolutionary biologists’ toolkit.

10.2.3 *From a Heuristic of Replication to a Heuristic of Collaboration*

These elements, I argue, are part of a more global perspective shift that is more or
less implicitly announced in the literature. Such shift takes its distance with what I
will hereinafter call a heuristic<fnref n="5" /> of replication (atomistic, gene-eye view) and
embraces what I will name a heuristic of collaboration (systemic view).

The *heuristic of replication*, embodied by Dawkins’s work on the selfish gene (1976, 1982), states that evolution can be conceived as a process mainly driven by the selection of virtually<fnref n="6" /> atomized units endowed with intrinsic capacities of self-replication and with their own adaptive value. It corresponds to what Walsh (2015) calls the Replicator biology. The *heuristic of collaboration*, as for it, rests on the hypothesis that biological objects cannot be considered otherwise than as parts of integrated wholes: they cannot replicate, evolve, and have any adaptive value independently from these wholes. In other words, this heuristic implies that heritable variations cannot be considered as virtually atomized traits correlated to virtually atomized genes (or replicators) but rather as parts of systems including interdependent elements.

The push toward the heuristic of collaboration subtly emerged in various contri-
butions. It notably appeared in Gould and Lewontin's (1979) critique of the adapta-
tionist program which considers organisms as aggregates of virtually atomized

<footnote n="5">⁵A heuristic is not a faithful account of reality but rather a theoretical tool that is supposed to help scientists grasping something from the objects that they study.</footnote>

<footnote n="6">⁶The adverb “virtually” should be understood in the context of a given heuristic. It denotes the fact that even if biologists have always been aware that evolution takes place among organisms and that heritable variations are necessarily located in integrated biological systems, these elements were overlooked in theoretical models (see, e.g., Dobzhansky, 1970, p. 65, who recognizes the limits of considering traits as independent entities).</footnote>
traits. It was also expressed in Lewontin's argument according to which the only biological entities able to self-replicate are not genes but organisms as complex systems (1993) or in developmental systems theory, which states that full developmental systems, and not genes alone, can replicate (Griffiths & Gray, 1994). More recently and in a similar vein, Fox Keller noted that DNA is neither stable nor able to replicate independently from a full cellular machinery (2000, pp. 26–27). Turner (2000, 2004), as for him, proposed a physiological interpretation of Dawkins' extended phenotype (1982). He argued that selection does not target replicators but rather whole systems able to self-maintain through the collaboration of various internal and external physiological parts which specify how flows of matter and energy are channeled. Finally, one can mention Walsh's (2010) elaboration of an alternative Neo-Darwinism that would not focus on replicators but on organisms and the various calls that are made for a "shift toward a network thinking" in evolutionary biology (Bapteste & Huneman, 2018). Even if all these approaches should not be conflated, they all reflect some endeavor toward the elaboration of an evolutionary biology focusing on integrated wholes and on networks and not on atomized objects, be they genes, or traits associated with these genes.

### 10.2.4 A Missing Organizational Perspective of Biological Inheritance?

Finally, the integration of an organizational thinking in evolutionary biology cannot be limited to the inclusion of organismal properties (and developmental timescales) in theoretical models. It might also require the integration of organizational concerns at the level of inheritance, which is traditionally thought as a key element for evolution (Lewontin, 1970; Sterelny, 2001).

It is generally asserted that EES notably relies on an extended vision of inheritance (Pigliucci & Müller, 2010; Laland et al., 2015). This means that the framework takes into account, in addition to genetic replication and transmission, various channels involved in the reoccurrence of traits across generations (Jablonka & Lamb, 2005; Danchin et al., 2011). Epigenetic inheritance (through the maintenance of epigenetic marks such as DNA methylation) can underpin the return of phenotypic outcomes such as defense against predators and pathogens (Holeski et al., 2012) and floral symmetry (Cubas et al., 1999). Behavioral inheritance takes place when social interactions mediate the reoccurrence of behavioral traits (Galef & Laland, 2005), notably those involved in the determination of the feeding niche (Slagsvold & Wiebe, 2007). Symbiotic transmission, which can be considered as a second mode of genetic inheritance (Gilbert et al., 2012), is linked, in many insects, to the trans-generational maintenance of metabolic capacities (Douglas, 2009).
The integration, in the evolutionary framework, of multifarious channels of
inheritance and therefore of multifarious heritable variations<sup>7</sup> could have major
theoretical consequences. It could notably weaken the statement that heritable vari-
ation is always small and random (Jablonka & Lamb, 2005). In this respect, it would
damage the MS's core hypothesis which states that natural selection of small and
random heritable variation is the main determinant of evolutionary change.<sup>8</sup>
However, the inclusion of extended inheritance into evolutionary theory comes with
some requirements. First, it demands the *elaboration of a consistent theoretical
framework* regarding inheritance. This framework should include more than genetic
mechanisms, but it should not result from a mere cumulative approach (Merlin,
2017) which would basically consist in integrating, into biological legacies, any-
thing that appears as a “good” transmitted across generations (developmental
resources, developmental factor, source of information). Such approach would
make sense from a metaphorical point of view,<sup>9</sup> but it would be theoretically unsat-
isfactory insofar as it would turn inheritance into a vague, ill-defined concept
(Mossio & Pontarotti, 2019). Some of the accounts of extended inheritance outlined
during the last few years have intended to establish this consistent framework
(Griesemer, 2000; Jablonka, 2002; Pontarotti 2015; Mossio & Pontarotti, 2019).

Second, one could also consider that a framework suited to an evolutionary biol-
ogy characterized by an organizational thinking should make some room to the
concept of organization. While different extended perspectives of inheritance could
be compatible with the emerging view of evolution, an organizational approach,
beyond overcoming genocentrism, would be fully consistent with an organization-
minded evolutionary biology. Besides, it would notably present the advantage of
implying a theoretically fecund systemic concept of heritable variation, as explained
in Sect. 10.3. In this respect, it would unambiguously participate in the perspective
shift from a heuristic of replication (atomistic, gene-eye view) to a heuristic of col-
laboration (systemic view).

<footnote n="7"><sup>7</sup>Inheritance usually refers to the transmission of traits – eye color and liver metabolic capacities – across generations of organisms. When compared with other instances in the population, these traits can be considered as heritable *variations*. For example, we can say that inheritance is responsible for the recurrence of a *trait* like a specific eye color in a lineage but also that it is responsible for the recurrence of variation in eye color when the whole population is taken into account. This variation can be linked to differential adaptive value. On this topic, Mameli (2005, p. 367) makes a distinction between inheritance of features and inheritance of differences (“‘trait’ can be used to refer to a particular value (being 176 cm tall) as well as to sets of possible values (height)”.)</footnote>

<footnote n="8"><sup>8</sup>This consequence is made obvious by a famous historical episode: that of the temporary eclipse of Darwinism at the dawn of the twentieth century, caused by the mutationist vision of heritable variation adopted by the first Mendelians (Huxley, 2010 [1942], p. 22; Gayon, 1992a, p. 14).</footnote>

<footnote n="9"><sup>9</sup>It is useful to remind that, according to historians, biological inheritance was initially a meta-
phorical concept (López-Beltrán, 1994; van der Lugt & de Miramon, 2008). It was indeed imported
from the legal sphere into the medical vocabulary to refer to diseases that appeared to be transmit-
ted like goods from parents to offspring.</footnote>
## 10.3 An Organizational Perspective of Biological Inheritance

In this section, I present an organizational account of inheritance that has been elaborated in earlier studies (Pontarotti, 2015; Pontarotti 2017; Mossio & Pontarotti, 2019). I show that, beyond overcoming genocentrism, opening a way to explain organisms’ stability and bounding the phenomenon of biological (extended) inheritance, this account appears as a key ingredient for an organism- and organization-centered evolutionary biology grounded on a heuristic of collaboration.

### 10.3.1 Principles of an Organizational Perspective of Biological Inheritance

The organizational account of biological inheritance is grounded on recent theoretical studies dedicated to biological autonomy and putting emphasis on the concept of biological organization (Mossio & Moreno, 2010; Montévil & Mossio, 2015; Moreno & Mossio, 2015). These studies place themselves in the wake of earlier contributions which conceive of biological systems as organized beings (Kant, 1790; Bichat, 1801; Bernard, 1885; Bertalanffy, 1968; Kauffman, 1995).<fnref n="10" /> According to them, biological systems include differentiated parts (cells, tissues, organs) that collaborate in order to maintain the system to which they belong.

In this view, biological systems are more precisely conceptualized as far from equilibrium open thermodynamical systems which maintain themselves through exchanges of matter and energy with their environment. They display differentiated parts that are interdependent<fnref n="11" /> for their maintenance and that collectively channel flows of matter and energy so as to maintain themselves and the system to which they belong. These parts are called functional constraints insofar as they are said to perform biological function (Mossio et al., 2009). They notably display stability with respect to the process they harness in a given system (Montévil & Mossio, 2015). For example, the cardiovascular system can be depicted as an organized (or functional) constraint given that (1) it contributes to channel flows of matter and energy in the organism, (2) it is dependent on the organisms’ other parts (e.g., the digestive system, the respiratory system, etc.) to maintain the organism (and, thereby, itself) as a whole, and (3) it exhibits stability with respect to the process that it harnesses, namely, blood circulation.

<footnote n="10">¹⁰ It is important to specify that these contributions are not equivalent even if they all conceive of living beings as organized ones. To Kant, for example, purposiveness and “self-organization” are regulative concepts necessary to make sense of the movement observed in some natural objects. This transcendental consideration is not endorsed by the other authors. In addition, while Bichat considers that living beings are animated by vital forces, Bernard rejects this concept. Bertalanffy’s approach, as for it, is characterized by thermodynamics considerations.</footnote>

<footnote n="11">¹¹ See Sect. 10.4 for an analysis of the concept of “interdependence”.</footnote>
The constraints that constitute an organized system are involved in a Kantian-flavored circular causality: they produce each other in the system that they contribute to maintain and which reciprocally contributes to their maintenance. The loop of interdependencies among a set of constraints is referred to as “organizational closure”. Organization, in this context, is defined as closure of constraints and is associated with intrinsic teleology (Mossio & Bich, 2014).

Organization as closure of constraints is a theoretical principle that allows explaining how a biological system maintains itself in an environment with which it exchanges flows of matter and energy. In this respect, it plays the role of *explanans* for the stability of biological systems and their constitutive parts. The theoretical principle of organization as closure of constraints can therefore be used to conceive of biological inheritance, which traditionally refers to the like-begets-like phenomenon (Darwin, 1859) and more globally to the idea of trans-generational stability.

From an organizational point of view, biological inheritance refers to the continuity, across generation breaks, of organizational patterns displayed by biological systems (Mossio & Pontarotti, 2019). It does not primarily designate the reoccurrence of – virtually atomized – traits underpinned by the replication of, virtually atomized, genetic factors but rather the trans-generational *conservation of functional networks*.<fnref n="12" /> Because organized constraints collectively channel flows of matter and energy in such a way that they maintain themselves and the system to which they belong, inheritance can also be described, in this context, as the cross-generation conservation of specific regimes of flow of matter and energy channeling (Pontarotti, 2017).

### 10.3.2 Inheritance and Organization: Toward the Conception of Multifarious Heritable Variations

The organizational perspective of inheritance is compatible with the hypothesis according to which inherited objects can be multifarious: traditional organs such as hearts but also epigenetics marks, external artifacts produced by organisms or symbols. As argued elsewhere (Pontarotti, 2016; Mossio & Pontarotti, 2019), the concept of (inherited) organized constraints is abstract enough to be applied to objects

<footnote n="12">¹²One may object that the concept of constraints is too narrow to include, in biological legacies, elements that appear as not functional but that are traditionally thought as heritable (e.g., short-sightedness). The question of inheritance of prima facie nonfunctional or dysfunctional traits has been addressed in another paper (Mossio & Pontarotti, 2019). To sum up, from an organizational point of view, heritable dysfunctional objects are still falling under the definition of constraint when they contribute to the maintenance of a given organizational regime, even if it is in a poorer way (e.g., short-sightedness refers to a poorer way of perceiving the environment). Besides, non-functional traits (e.g., eye color) are considered as “subordinary hereditary characteristic” when they are one aspect of an object (e.g., the eye) which is itself functional.</footnote>
which are not traditional organs; similarly, the concept of biological organization as closure of constraints applies to natural systems which depart from traditional organisms. It more precisely permits going beyond the common and simplified vision, reminded by Dupré & O'Malley (2007, p. 834), according to which biological systems are free-living cells or coordinated groups of cells containing the same genome.

In other words, an organizational perspective of biological inheritance allows conceiving of non-standard biological systems exhibiting multifarious heritable variations. Non-standard biological systems usually refer to symbiotic associations or to insect colonies including abiotic parts. In this paper, it designates all biological systems whose parts cannot simply be accounted by classical interactionist accounts (gene/environment). In other words, it refers to biological systems – such as human beings – that are more than groups of coordinated cells containing the same genome and that possibly include symbiotic and/or behavioral parts (involving or not the use of artifacts).

For pragmatic reason, it can be argued that non-standard biological system can undergo two kinds of variation: *genetic mutations* (changes in a DNA sequences) and *non-genetic acquisitions* (development of a new behavior, recruitment of new microorganisms, etc.) The first are conserved through *genetic inheritance* and the second through *non-genetic inheritance*. In this view, a functional variation appearing in a biological lineage is not necessarily due to a genetic mutation and can be conserved through non-genetic channels. For example, a heritable metabolic change in the capacity to degrade cellulose can be due to a mutation in some DNA sequences, to the acquisition of a cooking technique, to the acquisition of some microorganisms, etc. It can be conserved through various genetic and non-genetic mechanisms.

### 10.3.3 Inheritance and Organization: An Approach Suited to the Heuristic of Collaboration

When compared to other accounts that widen the scope of inheritance beyond geno-centrism (Jablonka, 2002; Bonduriansky, 2012; Griffiths & Stotz, 2013), the organizational perspective presents some important and specific characteristics that make it more suited to the emerging organisms-centered view of evolution.

- *Extension without dilution.* First, it extends inheritance beyond genetics while keeping it clearly bounded and thereby avoids its dilution into the vague concept of biological stability.<fnref n="13" /> Indeed, it offers tools to distinguish inheritance – conservation

<footnote n="13">¹³While the concept of extended inheritance first appears as theoretically and explanatorily fecund (insofar as it promises to overcome the limitations of gene-centrism), it can lead to consider as inherited any elements being stable across generations and having some causal influence on the reoccurrence of traits. In other words, it can lead to think about inheritance as a concept synonymous with stability (Mossio & Pontarotti, 2019). As a result, the extension of inheritance can</footnote>
of functional patterns across generations – from stability of environment, stability of ecosystems, etc. The organizational perspective only grants the status of heritable objects to those elements which can fall under the definition of functional constraints (e.g., hearts, nests, etc.) at a given scale. It regards stable flows of matter and energy (e.g., nutrients) and stable functional elements whose (physical) persistence is not primarily explained by their being part of a networks of interdependent constraints (e.g., persisting caves used as shelters), as part of stable environments (Mossio & Pontarotti, 2019). In this respect, the organizational account specifically defines inheritance and environmental stability as two different phenomena. It clarifies that stable biological (or biologically relevant) objects are either part of a heritable organization or part of a stable environment but not both at the same time (Pontarotti, 2022).

- *Collective stability*. Second, the organizational perspective invites to invalidate the classical distinction between hereditary factors (genes), understood as the causes of heredity, and hereditary traits (observable features), conceived as effects of the former. This distinction has been expressed through the opposition between the genotype and the phenotype since Johannsen's (1911) seminal contribution and has been a structuring one in the twentieth century. However, it appears as irrelevant in the presented theoretical framework, where genes and other biological constraints belong to a network of interdependent objects involved in a circular causality (Pontarotti et al., 2022). In an organizational view, distinguishing supposedly causal factors from supposedly epiphenomenal traits makes no sense. Inheritance is not a matter of (selfish) replication but rather of systemic, and therefore collective, stability.

While the genetic theory explains the stability of organismal traits by that of DNA sequences<fnref n="14" /> supposedly endowed with self-replicative and causal properties (Dawkins, 1976), an organizational perspective distributes the explanation for traits stability to various interdependent parts conceived as functional constraints: DNA sequences involved in the production of proteins, cells, socially learned behaviors, microorganisms performing some metabolic work in the system they constitute with their hosts, etc. On this point, the organizational perspective appears in line with the previously mentioned heuristic of collaboration. It also somehow echoes older “dynamical” or “energetist” conceptions of inheritance rejecting atomistic approach (Gayon, 1992b, pp. 432–433). Among them, Thompson’s vision (1942) is critical about the fact of attributing to individual particles something that is due to the “energy of their collocation”, while Nanney’s conception (1957) suggests that inheritance can refer to the behavior of a full system.

<footnote>conceal the fact that the concept initially designates a specific phenomenon – the stability of organismal traits – which is explained by the presence of some specific causal factors (López-Beltrán, 1994). When thinking about extended inheritance, the challenge is therefore to include more than genes in inheritance while avoiding to turn it into an all-inclusive concept.</footnote>

<footnote n="14">¹⁴ Mendelian genes are theoretical units but genes have been conceived of as DNA sequences since the middle of the twentieth century.</footnote>
Other extended accounts of inheritance evoke the replication of elements belonging to organized biological systems (Jablonka, 2002) and state that replication is a collective matter (Griffiths & Gray, 2004). However, these accounts do not rest on a clear concept of biological organization and/or do not put the concept of organization at their core. This prevents them from clearly bounding extended inheritance and from proposing a theoretically informed explanation of biological transgenerational stability.

- *Systemic heritable variation.* The organizational perspective further and more importantly has the specificity of implying a systemic concept of heritable variation, which is also consistent with a heuristic of collaboration. Conceiving of inheritance as the conservation of functional patterns indeed implies that heritable variations cannot be considered per se but should first and foremost be conceptualized as changes affecting complete biological networks. Insofar as parts of biological systems are thought as constraints which are interdependent for their maintenance within and across generations, new heritable variations should be considered as events that modify organizational regimes and that ground new organizational deals (Pontarotti, 2017).

This implies that a new heritable variation theoretically limits or enables further variations in the considered organizational pattern, within and across generations, following whether it turns out to increase or reduce the cost of a function. For example, the acquisition of a new metabolic capacity to degrade cellulose could be energetically costly for a system and therefore limit the possibly for further variations, but it could on the contrary reduce the energetic cost of the function and therefore leave some room for further changes. The termites that come to rely on fungi to digest cellulose become free from constraints on the digestion rates faced by the termites that rely only on intestinal digestion (Turner, 2004, p. 335). They can mobilize energy at much higher rates than their competitors (Turner, 2004, p. 339). The fact of counting on symbionts to perform part of the digestive process – a phenomenon that some authors call functional “outsourcing” (Turner, 2004, p. 335; Bouchard, 2013, p. 261) – can enable or limit further modifications in the considered systems. If the acquisition of the symbionts reduces the cost of nutrition or if it provides the system with more energy, this system may undergo other costly variations.

These considerations notably require admitting, in accordance with the life-history theory, that there is a trade-off for the allocation of resources among the parts of biological systems involved in survival and reproduction (Stearns, 1992, Fabian & Flatt, 2012). They also somehow appear in line with the thesis according to which biological systems are integrated wholes in which parts cannot be individually optimized (Gould & Lewontin, 1979), even if Gould and Lewontin's conception should not be conflated with the trade-off adaptationism endorsed by the life-history theory (see footnote 3).
## 10.4 Explanatory Value and Theoretical Implications of an Organizational Perspective on Biological Inheritance for Evolutionary Thinking

In this last section, I show that an organizational account of biological inheritance, beyond being a key ingredient for the elaboration of an organization-centered evolutionary biology, can modify perspectives and shed new light on various evolutionary phenomena.

### 10.4.1 Stabilization of Non-genetic Acquisitions and Evolution of Non-standard Biological Systems

It has been argued that non-genetic inheritance could have an impact on evolutionary trajectories (Jablonka & Lamb, 2005; Bonduriansky & Day, 2018). It has also been said that it is “crucial to make sense of the evolution of complex biological individuals” such as symbiotic associations or insects colonies including mounds and fungi (Bouchard, 2013, p. 259). However, non-genetic elements are generally thought as relatively labile when compared with genes (see Richards et al., 2010 for epigenetic marks), and non-genetic inheritance is sometimes referred to as transgenerational plasticity (Mesoudi et al., 2013). This seems to prevent non-genetic *acquisitions* from having any impact on evolutionary dynamics. Actually, such conclusion relies on a theoretical commitment toward a gene-centered evolutionary biology, based on a heuristic of replication where biological stability is thought as a property of virtually atomized objects able to make faithful copies of their structure and thought on the model of Dawkins’s replicators (1976). Endorsing this view, Sterelny (2001) argues that, to have an effect on cumulative evolution mainly driven by natural selection, non-genetic inheritance should present the same properties as genetic inheritance and should notably ensure the reconstruction of highly variable replicators exhibiting stability and having a common evolutionary fate.

An organization-centered biology, based on a heuristic of collaboration where heritable variations are not conceived as virtually atomized and self-replicating elements, leads to a very different conclusion. More precisely, an organizational perspective of biological inheritance, grounded on the idea of collective stability, opens a way to make sense of the stabilization of prima facie labile non-genetic *acquisitions* in the course of evolution and, thereby, of the evolution of non-standard biological systems (as defined in Sect. 10.3). As explained above, an organizational account of biological inheritance implies that heritable variation – be it a genetic mutation or a (plastic) non-genetic acquisition – grounds a new organizational deal and can have systemic consequences. In modifying a system’s access to flows of matter and energy (access to new resources, increased or decreased cost of a
function, functional redundancy<fnref n="15" />), it determines the possibility for further varia-
tions in this system. When these further variations occur, the other original parts of
the system may not be able to survive without the earlier changes, even if these
changes are non-genetic acquisitions (e.g., epigenetic marks, socially acquired
behaviors). More generally, a systemic vision of heritable variation allows outlining
three conditions favoring the stabilization of non-genetic inherited elements and the
consequent evolution of non-standard biological systems. These conditions are
those which increase the *interdependence* of parts, namely, environmental changes,
random functional losses, and appearance of other costly functional variations.

For example, an insect can acquire microorganisms that perform cellulose degra-
dation via so-called facultative symbiosis, where both host and symbionts car repro-
duce independently (Moran et al., 2008). But the host-symbiont association can
become irreversible in the case of an environmental change (food shortage that
would favor the systems that are more performant for digestion), in the case of a
functional loss (if the insect loses the capacity to digest cellulose) or if a costly
variation arises in the system.<fnref n="16" /> Another speculative example is the acquisition of
sewing techniques and of clothing traditions in humans. Under some climates, these
heritable acquisitions can be considered as a functional innovation regarding ther-
moregulation. In some circumstances (loss of genetic capacity to perform thermo-
regulation, costly variation, environmental change), this acquisition can become
more crucial for the maintenance of other parts of the systems, such as hearts.
Finally, one can imagine a situation where the decreased cost of the digestive func-
tion, related to the acquisition of cooking techniques destroying toxins, leaves some
rooms for costly mutations linked to the development of brain. This is what is sug-
gested by the tenants of the expensive tissue hypothesis (Aiello & Wheeler, 1995).

Before concluding, it is important to make some clarifications regarding the con-
cept of *interdependence*. According to the recent literature dedicated to biological
autonomy and biological organization, the constitutive constraints of biological sys-
tems are, by definition, interdependent. However interdependence can take different
forms and meanings. According to a first meaning, two objects are interdependent
when they are conserved by producing each other (*reciprocal production and sym-
metrical dependence involving joined conservation*). For example, the liver of an
organism cannot be conserved without the activity of the heart within and across
generations, and vice versa: the liver and the heart are therefore produced by each
other, and if the former is destroyed, the latter is also destroyed. However, reciprocal
production can also come with asymmetrical dependence. For example, the

<footnote n="15">¹⁵ Note that methylation marks seem to be involved in the silencing of redundant genetic elements (Rapp & Wendel, 2005, p. 82).</footnote>

<footnote n="16">¹⁶ More generally, the case of symbiosis, which is a paradigmatic example to think about organiza-
tional inheritance (Pontarotti, 2016), provides many examples of conditions leading to the
increased interdependence of parts. For example, the loss of genes in vertically transmitted symbi-
onts is said to be at the origin of plasts and mitochondria (Sachs, 2013, p. 632). Besides, a host can
come to tolerate a parasite if even more dangerous parasites are present in the environment (van
Baalen & Jansen, 2001).</footnote>
conservation of hunting tools participating in the food channeling process, in a human lineage, can depend on the conservation of hearts, and vice versa, but in some conditions (food abundance), hearts can be maintained without these manufactured tools. According to a second meaning, two objects are interdependent when they are maintained in a joint way, notably at the trans-generational timescale, even if they do not necessarily produce each other (mere joined conservation). For example, in an organism, the kidneys can be conserved if eyes are destroyed during the life cycle, but the kidneys and eyes can be jointly maintained at the trans-generational timescale: if the former reoccurs, the latter will in principle also reoccur. In this case, the kidneys are not directly dependent on the eye for their production and conservation,<fnref n="17" /> but the elements needed to rebuild the kidneys and to rebuild the eyes (notably DNA sequences) are conserved together.<fnref n="18" /> According to a third meaning, two objects are interdependent when they need to interact for the maintenance of a given organizational regime (and therefore for their maintenance as organizational constraints in this given regime) even if they can otherwise be maintained without one another. For example, the heart of an organism involved in a facultative symbiosis can be dependent on some microorganisms for the maintenance of a given pattern of matter and energy channeling, but not for its maintenance within and across generations (joined action for the maintenance of a given organizational regime).

These distinctions are important if one wants to apply the organizational framework to think about biological inheritance and the evolution of non-standard biological systems. They contribute to clarify that parts of biological systems exhibiting multifarious variations are minimally interdependent according to the third meaning (joined action for the maintenance of a given organizational regime) but that they can become interdependent in the first and strongest meaning (reciprocal production and symmetrical dependence involving joined conservation) in the circumstances mentioned above (environmental changes; random functional losses; appearance of other costly functional variations). This strongest kind of interdependence involves the common fate of parts (not mediated by bottleneck), a property which is one of the main hallmarks of biological individuals (Bouchard, 2013; Godfrey-Smith, 2009).

<footnote n="17">¹⁷ However, the kidneys are fully dependent on sensitive organs more globally. One can therefore consider that there is interdependence in the strong sense (reciprocal production) between kidneys and sensitive organs.</footnote>

<footnote n="18">¹⁸ This is what happens when objects that do not have any function (which do not comply with the definition of constraints) are conserved. These objects are conserved jointly with others which have, as for them, a clear function (e.g., DNA sequences used to build eye color are jointly conserved with sequences used to build pupil). They can be considered as “subordinate hereditary characteristics” (Mossio & Pontarotti, 2019).</footnote>
### 10.4.2 Perspectives on Fitness, Natural Selection, and Evolution

As explained above, the organizational perspective on biological inheritance appears as a major ingredient for an evolutionary biology based on a heuristic of collaboration. Below, I sketch how its integration into evolutionary thinking could induce, in the wake of earlier contributions, a change of perspective with regards to lineages, fitness, selection, and evolution.

First and foremost, assuming that inheritance is a matter of conservation of functional patterns – regardless of the parts being involved – and not of replication of genetic elements, implies that evolutionary biology should track *functional lineages* and not genetic ones. In this view, specialists should more precisely track the fate of integrated networks, not of virtually atomized alleles correlated with phenotypic variations. The key units of the living world are not elements heuristically depicted as selfish individuals eager to self-replicate but rather as parts collaborating with others in the context of organized networks. The stability of these parts is not linked to their intrinsic capacity of making faithful copies of themselves: it is related to their being integrated in networks channeling flows of matter and energy.

In this context, *fitness* cannot be thought of as the property of atomized objects but must be attributed to full organized systems whose spatial boundaries are outlined by interdependent constraints. It cannot be conceptualized, like in twentieth-century evolutionary biology, as a matter of differential replication (of genes) or as a matter of differential reproduction (of genetically homogenous organisms), but it should rather be thought as the differential capacity of integrated networks to channel flows of matter and energy in order to maintain themselves within and across generations.<fnref n="19" /> In accordance with earlier studies (van Valen, 1975, p. 267), fitness can therefore be said to rest on the differential quantity of energy controlled by a biological system. Put another way, it can refer to differential management of resources (Pontarotti, 2017). Finally, it can globally be envisioned as a matter of differential expansion (van Valen, 1989, p. 7), some systems being more capable than others to make more of themselves in space and time (through reproduction, growth, etc.), depending on their performance in resources channeling.

From this point of view, *natural selection* does not target genes but networks with differential performances as far as resources management – and therefore spatiotemporal maintenance and expansion – is concerned. It selects among networks exhibiting differential efficiency regarding the control of material and energetic flows. This line of argument is consistent with the idea according to which natural selection targets effects and not structures as such, in a given environment (Rosenberg, 1994). It also somehow meets the hypothesis of physiological selection advanced by Turner (2004) when thinking about the evolution of “extended organisms” such as termite-fungi-mound systems. It is important to no note, here, that

<footnote n="19">¹⁹For details about intergeneration breaks and therefore about temporal limits of organized systems involved in evolution, see Mossio & Pontarotti, 2019.</footnote>
according to Turner, genes should not be primarily considered as replicators but rather as specifiers<fnref n="20" /> of future functions, as elements, among others, specifying how flows of matter and energy are channeled (Turner, 2004).

The *evolution* of non-standard biological systems, as for it, can be thought on the model of the evolution which took place before the appearance of DNA. In a world inhabited by autocatalytic sets of molecules, what matters, for evolution, is not the differential replication of discrete entities but the variations impacting network's efficiency regarding maintenance (Kauffman, 1995). The point can be summarized as follows: "if the result (of a variation in an autocatalytic set of molecules) were a more efficient network – one better able to sustain itself amid a harsh environment – then these mutations would be rewarded, the altered web crowding out its weaker competitors" (Kauffman, 1995, p. 73). In this view, evolution can no more be defined as a change in gene frequencies (Dobzhansky, 1937) or as a change in developmental programs during phylogeny (Oster & Alberch, 1982, p. 444). It must rather be viewed as a process leading to changes in regimes of canalization of flows of matter and energy through time (Pontarotti, 2017), as a change in organizational regimes.

It should also be noted that an organizational account of biological inheritance makes it possible to articulate three elements that were conceived separately in modern synthesis but that an organism-centered evolutionary biology is willing to link again: development, inheritance, and evolution (Walsh, 2010; Nicholson, 2014). Indeed, such an account makes no theoretical distinction between hereditary factors (genotype) and developed traits (phenotype), considering all of them as inherited organized constraints. It also acknowledges a continuity regarding the processes involved in the conservation of biological systems within and across generations (Mossio & Pontarotti, 2019).

Finally, let us go back to the role of natural selection in this theoretical context. This role would be limited by theoretical models, based on a heuristic of collaboration, in which the dynamics of interdependence between parts of biological systems would be more important than multi-level selection of selfish elements in the determination of biological evolution. These models would, for example, take their distance with Szathmáry and Maynard Smith (1995) work on evolutionary transitions. The latter indeed clearly relies on a heuristic of replication and insists on the role of multilevel selection in the appearance of new kinds of individuals, an event in which elements which could initially replicate independently become interdependent for their own replication. The collaborative point of view associated with the integration of an organizational thinking in evolutionary biology would rather be in line with the literature about constructive neutral evolution (Lukes et al., 2011). The latter indeed offers a perspective in which evolution principally rests on games of interdependence: "In this conception, mutation is not a source of raw materials, but

<footnote n="20">²⁰“Specifiers are the catalytic surfaces that specify particular types of chemical reactions. These can be affected both by translated information in replicators (genes) and by environmental conditions” (Turner, 2004, p. 342).</footnote>
an agent that introduces novelty, while selection is not an agent that shapes features, but a stochastic sieve" (Stoltzfus, 2012). This reduced role for natural selection would be consistent with the main statements of EES which gives an important explanatory role to the internal dynamics of organized systems.

## 10.5 Conclusion

In this paper, I have argued that the emerging organism-centered evolutionary biology, which theoretically makes some important room to the concept of organization, is missing some organizational perspective of inheritance, the latter being known as a key ingredient for evolutionary processes. I have outlined an organizational account of biological inheritance, and I have detailed the systemic concept of heritable variation (genetic mutation and non-genetic acquisition) that it contributes to ground. Finally, I have sketched some implications of an organizational perspective of biological inheritance for an evolutionary theory which would be based on a heuristic of collaboration rather than on a heuristic of replication. The big picture set in this article deserves being developed in future contributions. For instance, it will be important to further analyze the link between organization and developmental mechanisms, the latter being at the center of extended evolutionary synthesis. Organization, as presented in this paper, makes abstraction of mechanistic and temporal details. But these details could be of great relevance for the elaboration of a theoretical framework which would better take into account the causal role of organized biological systems in evolutionary dynamics.

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