V. Life's Corporeal Evolution Develops, Encodes and Organizes Itself: An EarthWinian Genesis Synthesis

B. Systems Biology Unites: EvoDevo, Genomes, Cells, Networks, Symbiosis, Homology, Inherency

Tickle, Cheryll and Araxi Urrutia. Perspectives on the History of Evo-Devo and the Contemporary Research Landscape in the Genomics Era. Philosophical Transactions of the Royal Society B. Vol.372/Iss.1713, 2016. University of Bath developmental biologists introduce a themed Evo-Devo in the Genomics Era, and the Origins of Morphological Diversity issue. Among the authoritative papers, we review Origin of Animal Multicellularity by Thomas Cavalier-Smith, Human Evolution: A Tale from Ancient Genomes by Bastien Llamas, et al, and here note Deep Homology in the Age of Next-Generation Sequencing by Patrick Tschopp and Clifford Tabin, Abstract below.

The principle of homology is central to conceptualizing the comparative aspects of morphological evolution. The distinctions between homologous or non-homologous structures have become blurred, however, as modern evolutionary developmental biology (evo-devo) has shown that novel features often result from modification of pre-existing developmental modules, rather than arising completely de novo. With this realization in mind, the term ‘deep homology’ was coined, in recognition of the remarkably conserved gene expression during the development of certain animal structures that would not be considered homologous by previous strict definitions. At its core, it can help to formulate an understanding of deeper layers of ontogenetic conservation for anatomical features that lack any clear phylogenetic continuity. (Tschopp/Tabin)

Tiraihi, Ali, et al. Self-Organization of Developing Embryo Using Scale-Invariant Approach. Theoretical Biology and Medical Modelling. 8/17, 2011. As ancient tribal warriors now play nuclear chicken in civilization’s cradle, yet as scientific collaboration and online literature becomes globally accessible, Iranian researchers from Shaheed Behshti University, Sharif University of Technology, and Tarbiat Modares University (see below), each Tehran, can achieve this world class scientific contribution. From the land of polymath Islamic scholar Avicenna (c. 980-1037), exactly a millennium later, appears once again a grand mathematical quantification of life’s dynamically creative development. As traditional wisdom east and west, south and north, perennially knows, as Galileo put so well, a dual naturalness of genotype and phenotype, by so many names, graces an organic, textual, genesis creation.

Background: Self-organization is a fundamental feature of living organisms at all hierarchical levels from molecule to organ. It has also been documented in developing embryos. Methods: In this study, a scale-invariant power law (SIPL) method has been used to study self-organization in developing embryos. The SIPL coefficient was calculated using a centro-axial skew symmetrical matrix (CSSM) generated by entering the components of the Cartesian coordinates; for each component, one CSSM was generated. A basic square matrix (BSM) was constructed and the determinant was calculated in order to estimate the SIPL coefficient. This was applied to developing C. elegans during early stages of embryogenesis. The power law property of the method was evaluated using the straight line and Koch curve and the results were consistent with fractal dimensions.

Results and conclusion: The fractal dimensions of both the straight line and Koch curve showed consistency with the SIPL coefficients, which indicated the power law behavior of the SIPL method. The results showed that the ABp sublineage had a higher SIPL coefficient than EMS, indicating that ABp is more organized than EMS. The fractal dimension was determined using DLA was higher in ABp than in EMS and its value was consistent with type 1 cluster formation, while that in EMS was consistent with type 2.

Welcome to Tarbiat Modares University website. Tarbiat Modares is the first and only graduate school in Iran. The university primary mission is to train academic staff and researchers for universities and higher education centers throughout the country. Since its establishment in 1982, the university has made numerous achievements in academic excellence and innovative research at national and international levels. It has also established several academic relations with distinguished home and foreign academic and industrial institutions. This includes student exchange agreements, publication of books and journals and holding national and international meetings and conferences.

Torres-Sosa, Christian, et al. Criticality Is an Emergent Property of Genetic Networks that Exhibit Evolvability. PLoS Computational Biology. 8/9, 2012. Biotechnologists Torres-Sosa and Maximinia Aldana, Universidad Nacional Autónoma de México, Cuernavaca, and Sui Huang, Institute for Systems Biology, Seattle describe how a self-organized critical state, a key functional property for living organisms, naturally emerges from a dynamic evolution. This distinction is then seen as a robust verification of life’s oriented temporal development. Once again, to record, such an expansive evolutionary synthesis begs inclusion of these prior, innate generative propensities.

Accumulating experimental evidence suggests that the gene regulatory networks of living organisms operate in the critical phase, namely, at the transition between ordered and chaotic dynamics. Such critical dynamics of the network permits the coexistence of robustness and flexibility which are necessary to ensure homeostatic stability (of a given phenotype) while allowing for switching between multiple phenotypes (network states) as occurs in development and in response to environmental change. However, the mechanisms through which genetic networks evolve such critical behavior have remained elusive. Here we present an evolutionary model in which criticality naturally emerges from the need to balance between the two essential components of evolvability: phenotype conservation and phenotype innovation under mutations.

We simulated the Darwinian evolution of random Boolean networks that mutate gene regulatory interactions and grow by gene duplication. The mutating networks were subjected to selection for networks that both (i) preserve all the already acquired phenotypes (dynamical attractor states) and (ii) generate new ones. Our results show that this interplay between extending the phenotypic landscape (innovation) while conserving the existing phenotypes (conservation) suffices to cause the evolution of all the networks in a population towards criticality. Furthermore, the networks produced by this evolutionary process exhibit structures with hubs (global regulators) similar to the observed topology of real gene regulatory networks. Thus, dynamical criticality and certain elementary topological properties of gene regulatory networks can emerge as a byproduct of the evolvability of the phenotypic landscape. (Abstract)

Dynamically critical systems are those which operate at the border of a phase transition between two behavioral regimes often present in complex systems: order and disorder. Critical systems exhibit remarkable properties such as fast information processing, collective response to perturbations or the ability to integrate a wide range of external stimuli without saturation. Recent evidence indicates that the genetic networks of living cells are dynamically critical. This has far reaching consequences, for it is at criticality that living organisms can tolerate a wide range of external fluctuations without changing the functionality of their phenotypes. Therefore, it is necessary to know how genetic criticality emerged through evolution. Here we show that dynamical criticality naturally emerges from the delicate balance between two fundamental forces of natural selection that make organisms evolve: (i) the existing phenotypes must be resilient to random mutations, and (ii) new phenotypes must emerge for the organisms to adapt to new environmental challenges. The joint effect of these two forces, which are essential for evolvability, is sufficient in our computational models to generate populations of genetic networks operating at criticality. Thus, natural selection acting as a tinkerer of evolvable systems naturally generates critical dynamics. (Author Summary)

Uller, Tobias, et al. Developmental Bias and Evolution: A Regulatory Network Perspective. Genetics. 209/4, 2017. Five senior biologists, TU Lund University, Armin Moczek Indiana University, Richard Watson University of Southampton, Paul Brakefield Cambridge University and Kevin Laland University of St. Andrews propose a way to evoke life’s “directionality” by a factoring in novel appreciations of gene regulatory networks. Organism phenotypes as characteristics of an organism due to interactions of its genotype with its environment can thus be influenced and guided by this integrative quality. A prime feature is the presence of “analogous structures” which repeat, rise and further trace a homologous continuity.

Phenotypic variation is generated by the processes of development, with some variants arising more readily than others - a phenomenon known as “developmental bias.” Developmental bias and natural selection have often been portrayed as alternative explanations but developmental bias can evolve through natural selection, and bias and selection jointly influence phenotypic evolution. Here we describe recent theory on regulatory networks that explains why the influence of genetic and environmental perturbation on phenotypes is typically not uniform, and may even be biased toward adaptive phenotypic variation. We show how bias produced by developmental processes constitutes an evolving property able to impose direction on adaptive evolution and influence patterns of taxonomic and phenotypic diversity. We argue that it is not sufficient to accommodate developmental bias into evolutionary theory merely as a constraint on adaptation. A regulatory network perspective on phenotypic evolution thus helps to integrate the generation of phenotypic variation with natural selection, leaving evolutionary biology better placed to explain how organisms adapt and diversify. (Abstract excerpt)

Van Speybroeck, Linda, et al. The Conceptual Challenge of Systems Biology. BioEssays. 27/12, 2005. A report on the symposium Towards a Philosophy of Systems Biology held at the Vrije Universiteit of Amsterdam, the Netherlands in June, 2005 which explored this historic shift of perspective and method.

Today, Systems Biology is widely promoted as a valid alternative to reductionism, as it interprets life in terms of complex systems in which genes trade places with the biochemical networks in which they reside. (1305) Conceptually, Systems biology shows a growing liaison (with its tensions and passions) between two discourses. While a ‘mechanistic discourse’ remains popular, the ‘complexity discourse’ is taken more seriously, as witnessed by the ease with which concepts such as holism, self-organization, closure, non-linearity and causal distribution are considered as applicable to living systems. (1307)

Vidal, Marc. A Unifying View of 21st Century Systems Biology. FEBS Letters. 583/24, 2009. In a special issue from the 2009 Nobel Symposium on Systems Biology, the Dana Farber Cancer Institute and Harvard Medical School geneticist proposes guidelines for this novel emphasis, still scoping itself out, of the equally real, pervasive interrelations between the myriad molecules and cells of the 20th century.

The idea that multi-scale dynamic complex systems formed by interacting macromolecules and metabolites, cells, organs and organisms underlie some of the most fundamental aspects of life was proposed by a few visionaries half a century ago. We are witnessing a powerful resurgence of this idea made possible by the availability of nearly complete genome sequences, ever improving gene annotations and interactome network maps, the development of sophisticated informatic and imaging tools, and importantly, the use of engineering and physics concepts such as control and graph theory. Alongside four other fundamental “great ideas” as suggested by Sir Paul Nurse, namely, the gene, the cell, the role of chemistry in biological processes, and evolution by natural selection, systems-level understanding of “What is Life” may materialize as one of the major ideas of biology. (Abstract)

In summary, it was realized relatively early on and concomitantly with the development of the field of molecular biology that complex interconnections between macromolecules, both at local and global levels, might be able to generate systems properties or behaviors that would ultimately be recognized and understood as fundamental to life. (3892)

Vidal, Marc, et al. Interactome Networks and Human Disease. Cell. 144/986, 2011. In this Review of Systems Biology issue, Vidal with co-authors Micheal Cusick and Albert-Laszlo Barabasi, also of the Dana-Farber Cancer Institute, and other Boston medical schools and universities, contend that the study and health of everything organic going forward ought to fully appreciate the presence of systemic interdynamics everywhere. In such regards, cells are to be understood as suffused by internal molecular and component networks, any disruption of which is a sign of and can cause disease.

Complex biological systems and cellular networks may underlie most genotype to phenotype relationships. Here, we review basic concepts in network biology, discussing different types of interactome networks and the insights that can come from analyzing them. We elaborate on why interactome networks are important to consider in biology, how they can be mapped and integrated with each other, what global properties are starting to emerge from interactome network models, and how these properties may relate to human disease. (986) Cells can accordingly be envisioned as complex webs of macromolecular interactions, the full complement of which constitutes the “interactome” network. (987)

Voit, Eberhard, et al. The Intricate Side of Systems Biology. Proceedings of the National Academy of Sciences. 103/9452, 2006. A prospectus for the continuation of specific genetic research programs which can now be enhanced by the mathematical and computational capabilities of nonlinear dynamical networks.

Wagner, Gunter. What is “Homology Thinking” and What is it For? Journal of Experimental Zoology B. Online October, 2015. The Yale University theoretical biologist and author of Homology, Genes, and Evolutionary Innovation (2014) continues his task to identify and explain life’s persistent use of similar, ramifying forms and functions across the phyla. As the quotes allude, this recurrence infers a strong parallel between an organism’s developmental processes and evolution’s emergent course. In both cases, a steady sense of individuality and individuation accrues. As a surmise, along with deep homology (Shubin), convergence (Conway), symbiosis (Margulis) and more features (see Cosmo Sapiens 2014), the mid 19th century view of a universal gestation (Stott) grows in present veracity. See also Conceptualizing Language from a Homological Perspective by Sergio Balari and Guillermo Lorenzo In Frontiers in Ecology and Evolution V3/A58, 2015.

In this paper I examine the thesis by Marc Ereshefsky (Biology & Philosophy 27/382, 2012) that, in evolutionary biology, there is a third style of thinking, besides the well-known “population thinking” and “tree thinking.” Ereshefsky proposes “homology thinking” as a third approach, focused on the transformation of organismal phenotypes. In this short commentary, I aim at identifying the underlying biological assumptions for homology thinking and how they can be put to work in a research program within evolutionary biology. I propose that homology thinking is based on three insights: 1) multicellular organisms consist of developmentally individualized parts (sub-systems); 2) that developmental individuation entails evolutionary individuation, that is, variational quasi-independence; and 3) these individuated body parts are inherited, though indirectly, and form lineages that are recognized as homologies. These facts support a research program focused on the modification and origination of individuated body parts that supplements and puts into perspective the population genetic and phylogenetic approaches to the study of evolution.

Developmental individuality entails evolutionary individuality, and thus developmentally
individuated cells are recognized as homologous cell types across species. The opposite implication is also true, without developmental individuation there is no evolutionary individuality of the cell type and it can not be recognized as a different entity. (2) The evolutionary individuality of body parts, in turn, is what is recognized as homology of body parts across species. This observation leads us to the next element of homology thinking, and that is the recognition that individualized body parts tend to be inherited between generations, at least at the phenomenological level, which means that they are either recreated in each generation and thus form a lineage, or are recreated in a regular trans-generational pattern as in the case of complex life cycles. Homologs form lineages and have phylogenetic continuity. (2)

Walhout, Marian, et al, eds. Handbook of Systems Biology. Cambridge, MA: Academic Press, 2012. A comprehensive volume with a new emphasis on –omics and networks by contributors such as Alfred Barabasi, Erik Davidson, Reka Albert, and Andreas Wagner,. Typical chapters are Interactome Networks, Transcriptional Network Logic, Genotype Networks and Evolutionary Innovations, and Reconstruction of Genome-Scale Metabolic Networks. Each entry comes with extensive references.

Westerhoff, Hans and Bernhard Palsson. The Evolution of Molecular Biology into Systems Biology. Nature Biotechnology. 22/10, 2004. An historical perspective from the 1930’s which took two paths – a main emphasis on discrete macromolecules culminating in the human genome sequence, and a lesser, relational notice of self-organizing and systemic interactions.

We have agreed that contemporary systems biology has an historical root outside mainstream molecular biology, ranging from basic principles of self-organization in nonequilibrium thermodynamics, through large-scale flux and kinetic models to ‘genetic circuit’ thinking in molecular biology. “Systems thinking’ differs from ‘component thinking’ and requires the development of new conceptual frameworks. (1251)

Westerhoff, Hans, et al. Systems Biology: The Elements and Principles of Life. FEBS Letters. 583/24, 2011. this Nobel Symposium on Systems Biology issue, Manchester Centre for Integrative Systems Biology, The University of Manchester, and Netherlands Institute for Systems Biology, University of Amsterdam researchers contribute to on-going efforts to situate, define, contrast, and move forward with this 21st century endeavor.

Systems Biology has a mission that puts it at odds with traditional paradigms of physics and molecular biology, such as the simplicity requested by Occam’s razor and minimum energy/maximal efficiency. By referring to biochemical experiments on control and regulation, and on flux balancing in yeast, we show that these paradigms are inapt. Systems Biology does not quite converge with biology either: Although it certainly requires accurate ‘stamp collecting’, it discovers quantitative laws. Systems Biology is a science of its own, discovering own fundamental principles, some of which we identify here. (Abstract)

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