Evolutionary systems biology (ESB) aims to integrate methods from systems biology and evolutionary biology to go beyond the current limitations in both fields. This article clarifies some conceptual difficulties of this integration project, and shows how they can be overcome. The main challenge we consider involves the integration of evolutionary biology with developmental dynamics, illustrated with two examples. First, we examine historical tensions between efforts to define general evolutionary principles and (...) articulation of detailed mechanistic explanations of specific traits. Next, these tensions are further clarified by considering a recent case from another field focused on developmental dynamics: stem cell biology. In the stem cell case, incompatible explanatory aims block integration. Experimental approaches aim at mechanistic explanation while dynamical system models offer explanation in terms of general principles. We then discuss an ESB case in which integration succeeds: search for general attractors using a dynamical systems framework synergizes with the experimental search for detailed mechanisms. Contrasts between the positive and negative cases suggest general lessons for achieving an integrated understanding of developmental and evolutionary dynamics. The key integrative move is to acknowledge two complementary aims, both relevant to explanation: identifying the space of possible dynamic states and trajectories, and mechanistic understanding of causal interactions underlying a specific phenomenon of interest. These two aims can support one another in a joint project characterizing dynamic aspects of evolving lineages. This more inclusive project can lead to insights that cannot be reached by either approach in isolation. (shrink)

Evolutionary systems biology (ESB) is a rapidly growing integrative approach that has the core aim of generating mechanistic and evolutionary understanding of genotype‐phenotype relationships at multiple levels. ESB's more specific objectives include extending knowledge gained from model organisms to non‐model organisms, predicting the effects of mutations, and defining the core network structures and dynamics that have evolved to cause particular intracellular and intercellular responses. By combining mathematical, molecular, and cellular approaches to evolution, ESB adds new insights (...) and methods to the modern evolutionary synthesis, and offers ways in which to enhance its explanatory and predictive capacities. This combination of prediction and explanation marks ESB out as a research manifesto that goes further than its two contributing fields. Here, we summarize ESB via an analysis of characteristic research examples and exploratory questions, while also making a case for why these integrative efforts are worth pursuing. (shrink)

To understand how complex dynamic systems, living or non-living, linguistic or non-linguistic, come to be organized as systems, to understand how their inherent dynamic nature gives rise to organisations and forms that have found a balance between potentiality for change and evolution on the one hand, and requisite stability in a given environment on the other, is the main ambition of the study of evolutionary systems. The aim of the present volume is to elucidate the scientific (...) and philosophical backgrounds that play a role in one of the major debates taking place in that field, namely that on the relation between selection and self-organization. The book represents a genuine interdisciplinary forum in which the major representatives of evolutionary systems take part. Audience: This volume will be interest to biologists, philosophers of science, systems scientists, mathematicians, physicists, sociologists of science. It is highly recommended to those interested in an interdisciplinary and complex approach to evolution, as well as to those interested in developing a genuinely historical viewpoint in the sciences. (shrink)

Evolutionary systems biology is an emerging hybrid approach that integrates methods, models, and data from evolutionary and systems biology. Drawing on themes that arose at a cross-disciplinary meeting on ESB in 2013, we discuss in detail some of the explanatory friction that arises in the interaction between evolutionary and systems biology. These tensions appear because of different modeling approaches, diverse explanatory aims and strategies, and divergent views about the scope of the (...) evolutionary synthesis. We locate these discussions in the context of long-running philosophical deliberations on explanation, modeling, and theoretical synthesis. We show how many of the issues central to ESB’s progress can be understood as general philosophical problems. The benefits of addressing these philosophical issues feed back into philosophy too, because ESB provides excellent examples of scientific practice for the development of philosophy of science and philosophy of biology. (shrink)

Evolutionary developmental biology (evo-devo) is considered a ‘mechanistic science,’ in that it causally explains morphological evolution in terms of changes in developmental mechanisms. Evo-devo is also an interdisciplinary and integrative approach, as its explanations use contributions from many fields and pertain to different levels of organismal organization. Philosophical accounts of mechanistic explanation are currently highly prominent, and have been particularly able to capture the integrative nature of multifield and multilevel explanations. However, I argue that evo-devo demonstrates the need (...) for a broadened philosophical conception of mechanisms and mechanistic explanation. Mechanistic explanation (in terms of the qualitative interactions of the structural parts of a whole) has been developed as an alternative to the traditional idea of explanation as derivation from laws or quantitative principles. Against the picture promoted by Carl Craver, that mathematical models describe but usually do not explain, my discussion of cases from the strand of evo-devo which is concerned with developmental processes points to qualitative phenomena where quantitative mathematical models are an indispensable part of the explanation. While philosophical accounts have focused on the actual organization and operation of mechanisms, properties of developmental mechanisms that are about how a mechanism reacts to modifications are of major evolutionary significance, including robustness, phenotypic plasticity, and modularity. A philosophical conception of mechanisms is needed that takes into account quantitative changes, transient entities and the generation of novel types of entities, feedback loops and complex interaction networks, emergent properties, and, in particular, functional-dynamical aspects of mechanisms, including functional (as opposed to structural) organization and distributed, system-wide phenomena. I conclude with general remarks on philosophical accounts of explanation. (shrink)

Many scientists and philosophers of science are troubled by the relative isolation of developmental from evolutionary biology. Reconciling the science of development with the science of heredity preoccupied a minority of biologists for much of the twentieth century, but these efforts were not corporately successful. Mainly in the past fifteen years, however, these previously dispersed integrating programmes have been themselves synthesized and so reinvigorated. Two of these more recent synthesizing endeavours are evolutionary developmental biology and developmental (...) systems theory. While the former is a bourgeoning and scientifically well-respected biological discipline, the same cannot be said of DST, which is virtually unknown among biologists. In this review, we provide overviews of DST and EDB, summarize their key tenets, examine how they relate to one another and to the study of epigenetics, and survey the impact that DST and EDB have had on biological theory and practice. (shrink)

1 The Zero-Force Evolutionary Law 2 Randomness, Hierarchy, and Constraint 3 Diversity 4 Complexity 5 Evidence, Predictions, and Tests 6 Philosophical Foundations 7 Implications.

Does biology have general laws that apply to all levels of biological organisation, across all evolutionary time? In their book “Biology’s first law: the tendency for diversity and complexity to increase in evolutionary systems” (2010), Daniel McShea and Robert Brandon propose that the most fundamental law of biology is that all levels of biological organisation have an underlying tendency to become more complex and diverse over time. A range of processes, most notably selection, can (...) prevent the expression of this tendency, but they predict that, on average, we should see that lineages tend toward greater diversity and complexity, driven by fundamentally neutral processes. Their hypothesis can be summarised as “diversity is easy, stasis is hard”. Here, I consider evidence for this “zero force evolutionary law”. It provides a fair description of evolutionary change at the genomic level, but the predictions of the proposed law are not met for broad scale patterns in the evolution of the animal kingdom. (shrink)

The comprehension of living organisms in all their complexity poses a major challenge to the biological sciences. Recently, systems biology has been proposed as a new candidate in the development of such a comprehension. The main objective of this paper is to address what systems biology is and how it is practised. To this end, the basic tools of a systems biological approach are explored and illustrated. In addition, it is questioned whether systems (...) class='Hi'>biology ‘revolutionizes’ molecular biology and ‘transcends’ its assumed reductionism. The strength of this claim appears to depend on how molecular and systems biology are characterised and on how reductionism is interpreted. Doing credit to molecular biology and to methodological reductionism, it is argued that the distinction between molecular and systems biology is gradual rather than sharp. As such, the classical challenge in biology to manage, interpret and integrate biological data into functional wholes is further intensified by systems biology’s use of modelling and bioinformatics, and by its scale enlargement. (shrink)

Despite its explanatory clout, the theory of evolution has thus far compiled a modest record with respect to predictive power—that other major hallmark of scientific theories. This is considered by many to be an acceptable limitation of a theory that deals with events and processes that are intrinsically random. However, whether this is an inherent restriction or simply the sign of an incomplete theory is an open question. In an attempt to help answer that question, we propose a classification scheme (...) for several types of prediction that might occur with regard to evolutionary systems, then explore the nature of these predictions in a system that simulates the evolution of neural architectures. This provides a platform from which to consider the relevance of such observations for real biological systems and illuminates a variety of key issues pertaining to prediction in those environments. (shrink)

In my field, animal developmental biology, and in what could be regarded as its “deep time derivative,” the evolutionary biology of the animal body plan, there exist two kinds of experimentally supported causal explanation. These can be described as “rooted” and “unrooted.” Rooted causal explanation provides logical links to and from the genomic regulatory code, extending right into the genomic sequences that control regulatory gene expression. The genomic regulatory code ultimately determines the developmental process in a direct (...) way, since subsequent developmental events all depend directly and specifically on what regulatory genes are being expressed and where in the developing organism they are being expressed.. (shrink)

Evolutionary developmental biologists categorize many different kinds of things, from ontogenetic stages to modules of gene activity. The process of categorization—the establishment of “kinds”—is an implicit part of describing the natural world in consistent, useful ways, and has an essentially practical rather than philosophical basis. Kinds commonly serve one of three purposes: they may function (1) as practical tools for communication; (2) to support prediction and generalization; or (3) as a basis for theoretical discussions. Beyond the minimal requirement that (...) classifications reflect biological reality, what sorts of kinds or classification will be useful in advancing a research program depends on the epistemological context. Thus, the important meaning of “natural” in “natural kinds” is not “natural with respect to nature,” but “natural with respect to the question.” This conclusion arises from the recognition that the proper role of concepts (e.g. natural kind, module, homology, model) is not to answer biological questions, but rather to help frame them. From a scientist’s perspective, arguing about the wording (or existence) of a single definition of “natural” or “kind” is beside the point: we get more work done by letting the question at hand determine what kinds of kinds are natural, on the basis of their ability to help answer it. We should be content to let “natural kinds” remain vague, multivalent, and–therefore broadly useful. For a philosopher like Hacking, the diverse, disparate, and ultimately incommensurable uses of the term “natural kind” have diluted its value so far that it loses all meaning. For practicing scientists, however, defining useful kinds in the context of particular questions and systems remains a productive epistemological strategy. (shrink)

En este ambicioso libro, el biólogo Daniel W. McShea y el filósofo de la biología Robert N. Brandon desafían las explicaciones explícitas encontradas en la litera-tura acerca del origen de la diversidad y la complejidad en los seres vivos. Estas explicaciones recurren en su mayoría a la acción de la selección natural, como ser, a la selección diversificadora/disruptiva, a la selección de niveles superiores favoreciendo a especies/clados con mayor propensión a la especiación, o a las ventajas de una mayor división (...) del trabajo, entre otras alternativas (p. 1). Si bien estas explicaciones pueden ser correctas, no constituirían toda la historia, según los autores, pues habría una tendencia de fondo no reconocida en la literatura (pero invocada en las explicaciones de casos concretos) hacia un aumento de la diversidad y la complejidad. Esta tendencia surgiría simplemente de que las variaciones azarosas, cuando se heredan, se acumulan en diferentes direcciones en diferentes poblaciones, con el resultado de que la diversidad se incrementa. Para expresar esta tendencia, los autores proponen una ley, que denominan ZFEL (por zero-force evolutionary law) y que formulan de la siguiente manera: “En cualquier sistema evolutivo en el que hay variación azarosa y he-rencia, en ausencia de fuerzas y constricciones, la diversidad y la complejidad tenderán a aumentar” (p. 4). (shrink)

Our purpose in this essay is to introduce new concepts in a wide and recursive view of the systemic consequences of the following biological facts that I and we have presented that can be resumed as: that as living systems we human beings are molecular autopoietic system; that living systems live only as long as they find themselves in a medium that provides them with all the conditions that make the realization of their living possible, that is, in (...) the continuous conservation of their relation of adaptation to the circumstances in which they find themselves; that as a living system exists only in a relation of adaptation with the medium that operates as its ecological niche, its reproduction necessarily occurs as a process of systemic duplication or multiplication of the ecological organism-niche unity that it integrates; that the worlds of doings that we generate as languaging beings in our conversations, explanations, reflections and theories are part of our ecological niche; and that we human beings as living beings that exist in languaging, are biological–cultural beings in which our cultural and our biological manners of existences can be distinguished but cannot be separated. Of the systemic consequences of these biological facts that we consider in this essay, we wish to mention two as the principal: that the diversification of manners of living produced in biological evolution is the result of differential survival in a changing medium through the conservation of adaptation, and not through competitive survival of the best; and that we in our living as languaging human beings are the epistemological fundament of all that we do and know as such. (shrink)

Among the many causes of an event, how do we distinguish the important ones? Are there ways to distinguish among causes on principled grounds that integrate both practical aims and objective knowledge? Psychologist Tania Lombrozo has suggested that causal explanations “identify factors that are ‘exportable’ in the sense that they are likely to subserve future prediction and intervention” (Lombrozo 2010, 327). Hence portable causes are more important precisely because they provide objective information to prediction and intervention as practical aims. However, (...) I argue that this is only part of the epistemology of causal selection. Recent work on portable causes has implicitly assumed them to be portable within the same causal system at a later time. As a result, it has appeared that the objective content of causal selection includes only facts about the causal structure of that single system. In contrast, I present a case study from systems biology in which scientists are searching for causal factors that are portable across rather than within causal systems. By paying careful attention to how these biologists find portable causes, I show that the objective content of causal selection can extend beyond the immediate systems of interest. In particular, knowledge of the evolutionary history of gene networks is necessary for correctly identifying causal patterns in these networks that explain cellular behavior in a portable way. (shrink)

Despite the productivity of basic cancer research, cancer continues to be a health burden to society because this research has not yielded corresponding clinical applications. Many proposed solutions to this dilemma have revolved around implementing organizational and policy changes related to cancer research. Here I argue for a different solution: a new conceptualization of causation in cancer. Neither the standard molecular biomarker approaches nor evolutionary biology approaches to cancer fully capture its complex causal dynamics, even when considered jointly. (...) These approaches map on to Ernst Mayr’s proximate–ultimate distinction, which is an inadequate conceptualization of causation in biological systems and makes it difficult to connect developmental and evolutionary viewpoints. I propose looking to evolutionary developmental biology to overcome the distinction and integrate the proximate and ultimate causal frameworks. I use the concepts of modularity and evolvability to show how an EvoDevo perspective can be manifested in cancer translational research. This perspective on causation in cancer is better suited for integrating the complexity of current empirical results and can facilitate novel developments in the investigation and clinical treatment of cancer. (shrink)

Despite wide acceptance that the attributes of living creatures have appeared through a cumulative evolutionary process guided chiefly by natural selection, many human activities have seemed analytically inaccessible through such an approach. Prominent evolutionary biologists, for example, have described morality as contrary to the direction of biological evolution, and moral philosophers rarely regard evolution as relevant to their discussions. -/- The Biology of Moral Systems adopts the position that moral questions arise out of conflicts of interest, (...) and that moral systems are ways of using confluences of interest at lower levels of social organiation to deal with conflicts of interest at higher levels. Moral systems are described as systems of indirect reciprocity: humans gain and lose socially and reproductively not only by direct transactions, but also by the reputations they gain from the everyday flow of social interactions. -/- The author develops a general theory of human interests, using senescence and effort theory from biology, to help analye the patterning of human lifetimes. He argues that the ultimate interests of humans are reproductive, and that the concept of morality has arisen within groups because of its contribution to unity in the context, ultimately, of success in intergroup competition. He contends that morality is not easily relatable to universals, and he carries this argument into a discussion of what he calls the greatest of all moral problems, the nuclear arms race. (shrink)

How can the discoveries made in the biological sciences play a role in a discussion on the foundation of ethics? This book responds to this question by examining how evolutionism can explain and justify the existence of ethical normativity and the emergence of particular moral systems. Written by a team of philosophers and scientists, the essays collected in this volume deal with the limits of evolutionary explanations, the justifications of ethics, and methodological issues concerning evolutionary accounts of (...) ethics, among other topics. They offer deep insights into the origin and purpose of human moral capacities and of moral systems. (shrink)

The genetic code has evolved from its initial non-degenerate wobble version until reaching its present state of degeneracy. By using the stereochemical hypothesis, we revisit the problem of codon assignations to the synonymy classes of amino-acids. We obtain these classes with a simple classifier based on physico-chemical properties of nucleic bases, like hydrophobicity and molecular weight. Then we propose simple RNA ring structures that present, overlap included, one and only one codon by synonymy class as solutions of a combinatory variational (...) problem. We compare these solutions to sequences of present RNAs considered as relics, with a high interspecific invariance, like invariant parts of tRNAs and micro-RNAs. We conclude by emphasizing some optimal properties of the genetic code. (shrink)

"The evolutionary vision" is a term coined by economist Kenneth E. Boulding to describe a unified view of evolution that encompasses all levels of reality, from the cosmic or physical through the biological, ecological, and sociobiological to the sociocultural. It focuses less on systems or any particular entity than on the processes through which they evolve. In this volume various approaches to the self-organization of matter and information are outlined by authors who are among the chief developers of (...) this new paradigm. They focus on the general laws governing evolutionary dynamics across all levels of evolution, including the evolution of humans and human systems. (shrink)

The increasing place of evolutionary scenarios in functional biology is one of the major indicators of the present encounter between evolutionary biology and functional biology (such as physiology, biochemistry and molecular biology), the two branches of biology which remained separated throughout the twentieth century. Evolutionary scenarios were not absent from functional biology, but their places were limited, and they did not generate research programs. I compare two examples of these past scenarios (...) with two present-day ones. At least three characteristics distinguish present and past efforts: An excellent description of the systems under study, a rigorous use of the evolutionary models, and the possibility to experimentally test the evolutionary scenarios. These three criteria allow us to distinguish the domains in which the encounter is likely to be fruitful, and those where the obstacles to be overcome are high and in which the proposed scenarios have to be considered with considerable circumspection. (shrink)

The practical criteria by which developmental biologists choose their model systems have evolutionary correlates. The result is a sample that is not merely small, but biased in particular ways, for example towards species with rapid, highly canalized development. These biases influence both data collection and interpretation, and our views of how development works and which aspects of it are important.

The necessary but not sufficient conditions for biological informational concepts like signs, symbols, memories, instructions, and messages are (1) an object or referent that the information is about, (2) a physical embodiment or vehicle that stands for what the information is about (the object), and (3) an interpreter or agent that separates the referent information from the vehicle’s material structure, and that establishes the stands-for relation. This separation is named the epistemic cut, and explaining clearly how the stands-for relation is (...) realized is named the symbol-matter problem. (4) A necessary physical condition is that all informational vehicles are material boundary conditions or constraints acting on the lawful dynamics of local systems. It is useful to define a dependency hierarchy of information types: (1) syntactic information (i.e., communication theory), (2) heritable information acquired by variation and natural selection, (3) non-heritable learned or creative information, and (4) measured physical information in the context of natural laws. High information storage capacity is most reliably implemented by discrete linear sequences of non-dynamic vehicles, while the execution of information for control and construction is a non-holonomic dynamic process. The first epistemic cut occurs in self-replication. The first interpretation of base sequence information is by protein folding; the last interpretation of base sequence information is by natural selection. Evolution has evolved senses and nervous systems that acquire non-heritable information, and only very recently after billions of years, the competence for human language. Genetic and human languages are the only known complete general purpose languages. They have fundamental properties in common, but are entirely different in their acquisition, storage and interpretation. (shrink)

In this article, I am concerned with the public engagements of Julian Huxley, Lancelot Hogben, and J. B. S. Haldane. I analyze how they used the new insights into the genetics of heredity to argue against any biological foundations for antidemocratic ideologies, be it Nazism, Stalinism, or the British laissez-faire and class system. The most striking fact—considering the abuse of biological knowledge they contested—is that these biologists presented genetics itself as inherently democratic. Arguing from genetics, they developed an understanding of (...) diversity that cuts across divisions of race, class, or gender. Human diversity rightly understood was advantageous for societal progress. Huxley, Hogben, and Haldane did not hold identical political ideals, but they all argued for democratic reforms and increased planning geared toward greater social equality, and they did so under the label of scientific humanism. Huxley took issue with the notion that evolutionary history does not carry any moral lessons for human societies. Rather than being its antithesis, evolution was the basis of human sociality. In fact, the entire future progress of individuals and communities toward a democratic world order needed to be founded on the cosmic principles of evolution—a process that had to be guided by the biological expert with a strong sense of social responsibility. (shrink)

Evolutionary psychology tends to be associated with a massively modular cognitive architecture. On this framework of human cognition, an assembly of specialized information processors called modules developed under selection pressures encountered throughout the phylogenic history of hominids. The coordinated activity of domain-specific modules carries out all the processes of belief fixation, abstract reasoning, and other facets of central cognition. Against the massive modularity thesis, I defend an account of systemic functional adaptedness, according to which non-modular systems emerged because (...) of adaptive problems imposed by the intrinsic physiology of the evolving human brain. The proposed reformulation of evolutionary theorizing draws from neural network models and Cummins’ (1975) account of systemic functions to identify selection pressures that gave rise to non-modular, domain-general mechanisms in cognitive architecture. (shrink)

Evolutionary epistemology has experienced a continuous rise over the last decades. Important new theoretical considerations and novel empirical findings have been integrated into the existing framework. In this paper, I would like to suggest three lines of research that I believe will significantly contribute to further advance EE: ontogenetic considerations, key ideas from cognitive biology, and the framework of the Extended Evolutionary Synthesis. EE, in particular the program of the evolution of epistemological mechanisms, seeks to provide a (...) phylogenetic account of the generation of cognitive processes underlying knowledge creation. Traditionally, EE and EEM have been oriented towards an account of evolutionary theory that mainly drew from the tenets of the Modern Synthesis. The Modern Synthesis largely dismisses ontogenetic processes and considers them irrelevant for evolutionary explanations. If anything, the role of development in evolution is believed to be that of a constraint. There is, however, ample evidence for a tight intertwinement of developmental and evolutionary processes. Organisms employ their cognitive apparatus to interact with the environment in order to achieve a fully functioning perceptual and cognitive nervous system. Also, ontogeny provides generative potentials to enable variations that natural selection can act upon. EEM’s agenda may, therefore, strongly benefit from bringing together ontogenetic and phylogenetic approaches. To grapple with this challenge, an alternative vision of the evolutionary theory termed Extended Evolutionary Synthesis could be used. This extended evolutionary theory explores relationships between the processes of individual development and phenotypic change during evolution and can provide a more suitable framework for EEM to draw from. In recent years, cognitive biology has gained momentum as an independent research field. Cognitive biology builds on the concepts of EEM and understands knowledge as a biogenic phenomenon. Its main objective is also the formulation of substantiated interrelations between cognition and evolution but it focuses on cognitive functionality at all levels of biological organization. It thus employs a “vertical” approach that encompasses nested hierarchies which span from single molecules, cells, and tissues to the organismal level, communities, and societies. In contrast to cognitive biology, EEM is here understood to adopt a “horizontal” approach that focuses on phylogenetic explanations of cognition and knowledge acquisition. Linking EEM with the key ideas of cognitive biology could make EEM’s research program stronger as it can more easily accommodate phylogenetic and ontogenetic questions within a hierarchical, multilevel perspective. This is of particular importance for a more comprehensive account of cognition since living systems are subject to context-dependent causal influences from different organizational levels. In addition to EEM, there is a second program of EE. This program has been labeled evolutionary epistemology of theories and understands the increase in human knowledge, such as scientific theories, as naturalistic accounts of evolution. Both, EEM and EET initially drew from the core concepts of the Modern Synthesis. Several scholars have severely criticized the analogies made between EET and the Neo-Darwinian key processes of evolution. In particular processes of random mutation, the rate of variation, natural selection as the unique driving force, and the adaptationist agenda are believed to reveal disanalogies. In contrast to the Modern Synthesis, the Extended Evolutionary Synthesis not only recognizes developmental processes but also ecological interactions and systems dynamics as well as social and cultural evolutionary reciprocity as important evolutionary processes. Concepts of the Extended Evolutionary Synthesis are therefore expected to be more fruitful for re-conceptualizing parallels between scientific theorizing and biological evolution. (shrink)

The French molecular biologist François Jacob outlined a theory of evolution as tinkering. From a methodological point of view, his approach can be seen as a biologic specification of the relation between laws, describing coherently the dynamics of a system, and contingent boundary conditions on this dynamics. From a semiotic perspective, tinkering is a pragmatic concept well-known from the information-theoretic anthropology of Claude Lévi-Strauss. In idealized contrast to an engineer, the tinkerer has to accept the concrete restrictions on his material (...) resources as only gradually changeable constraints on his projects. Jacobian biopragmatics examines evolution as a biologic analogue to human tinkering devoid of any projecting subjectivity. To validate this analogy, four basic principles concerning main formal aspects of evolutionary objects, agents, histories, and consistency criteria are proposed. (shrink)

In recent years, immune systems have sparked considerable interest within the philosophy of science. One issue that has received increased attention is whether other phyla besides vertebrates display an adaptive immune system. Particularly the discovery of CRISPR-Cas9-based systems has triggered a discussion about how to classify adaptive immune systems. One question that has not been addressed yet is the transgenerational aspect of the CRISPR-Cas9-based response. If immunity is acquired and inherited, how to distinguish evolutionary from immunological (...) adaptation? To shed light on this issue and obtain conceptual clarity, I will investigate the inheritance of small RNA responses to pathogens in the nematode C. elegans as a further potential instantiation of a transgenerational adaptive immune system. I will explore how to make sense of systems that lie at the crossroads between genetic, immunological, and evolutionary spheres and explore the consequences of a transgenerational perspective on immune systems for immunology and its philosophy. (shrink)

The formal framework of Kauffman (1991) depicts the constraints of self-organization on the evolution of complex systems and the relation of self-organization to selection. We discuss his treatment of 'generic constraints' as sources of order (section 2) and the relation between adaptation and organization (section 3). We then raise a number of issues, including the role of adaptation in explaining order (section 4) and the limitations of formal approaches in explaining the distinctively biological (section 5). The principal question we (...) pose is the relation of generic constraints on evolution to more specific local constraints, imposed, for example, by the characteristic materials out of which organisms are constructed, the accidental features characteristic of the Bauplan of a lineage, and the local vicissitudes of adaptation. We offer no answer to this large question. (shrink)

The purinergic signalling system, which utilises ATP, related nucleotides and adenosine as transmitter molecules, appeared very early in evolution: release mechanisms and ATP‐degrading enzymes are operative in bacteria, and the first specific receptors are present in single cell eukaryotic protozoa and algae. Further evolution of the purinergic signalling system resulted in the development of multiple classes of purinoceptors, several pathways for release of nucleotides and adenosine, and a system of ectonucleotidases controlling extracellular levels of purinergic transmitters. The purinergic signalling system (...) is expressed in virtually all types of tissues and cells, where it mediates numerous physiological reactions and contributes to pathological responses in a variety of diseases. (shrink)

It is argued that multiscale approaches are necessary for an explanatory modeling of biological systems. A first step, besides common to the multiscale modeling of physical and living systems, is a bottom-up integration based on the notions of effective parameters and minimal models. Top-down effects can be accounted for in terms of effective constraints and inputs. Biological systems are essentially characterized by an entanglement of bottom-up and top-down influences following from their evolutionary history. A self-consistent multiscale (...) scheme is proposed to capture the ensuing circular causality. Its differences with standard mean-field self-consistent equations and slow-fast decompositions are discussed. As such, this scheme offers a way to unravel the multilevel architecture of living systems and their regulation. Two examples, genome functions and biofilms, are detailed. (shrink)

The CRISPR-Cas systems of bacterial and archaeal adaptive immunity have become a household name among biologists and even the general public thanks to the unprecedented success of the new generation of genome editing tools utilizing Cas proteins. However, the fundamental biological features of CRISPR-Cas are of no lesser interest and have major impacts on our understanding of the evolution of antivirus defense, host-parasite coevolution, self versus non-self discrimination and mechanisms of adaptation. CRISPR-Cas systems present the best known case (...) in point for Lamarckian evolution, i.e. generation of heritable, adaptive genomic changes in response to encounters with external factors, in this case, foreign nucleic acids. CRISPR-Cas systems employ multiple mechanisms of self versus non-self discrimination but, as is the case with immune systems in general, are nevertheless costly because autoimmunity cannot be eliminated completely. In addition to the autoimmunity, the fitness cost of CRISPR-Cas systems appears to be determined by their inhibitory effect on horizontal gene transfer, curtailing evolutionary innovation. Hence the dynamic evolution of CRISPR-Cas loci that are frequently lost and acquired by archaea and bacteria. Another fundamental biological feature of CRISPR-Cas is its intimate connection with programmed cell death and dormancy induction in microbes. In this and, possibly, other immune systems, active immune response appears to be coupled to a different form of defense, namely, “altruistic” shutdown of cellular functions resulting in protection of neighboring cells. Finally, analysis of the evolutionary connections of Cas proteins reveals multiple contributions of mobile genetic elements to the origin of various components of CRISPR-Cas systems, furthermore, different biological systems that function by genome manipulation appear to have evolved convergently from unrelated MGE. The shared features of adaptive defense systems and MGE, namely the ability to recognize and cleave unique sites in genomes, make them ideal candidates for genome editing and engineering tools. (shrink)

Progress has become a suspect concept in evolutionary biology, not the least because the core concepts of neo-Darwinism do not support the idea that evolution is progressive. There have been a number of attempts to account for directionality in evolution through additions to the core hypotheses of neo-Darwinism, but they do not establish progressiveness, and they are somewhat of an ad hoc collection. The standard account of fitness and adaptation can be rephrased in terms of information theory. From (...) this, an information of adaptation can be defined in terms of a fitness function. The information of adaptation is a measure of the mutual information between biota and their environment. If the actual state of adaptation lags behind the state of optimal adaptation, then it is possible for the information of adaptation to increase indefinitely. Since adaptations are functional, this suggests the possibility of progressive evolution in the sense of increasing adaptation. Keywords: evolution, information, adaptation, fitness, entropy, progress.. (shrink)

In this article I consider the challenges for exporting causal knowledge raised by complex biological systems. In particular, James Woodward’s interventionist approach to causality identified three types of stability in causal explanation: invariance, modularity, and insensitivity. I consider an example of robust degeneracy in genetic regulatory networks and knockout experimental practice to pose methodological and conceptual questions for our understanding of causal explanation in biology. †To contact the author, please write to: Department of History and Philosophy of Science, (...) University of Pittsburgh, 1017 Cathedral of Learning, Pittsburgh, PA 15260; e‐mail: [email protected]. (shrink)