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V. Life's Evolutionary Development Organizes Itself: A 2020s Genesis Synthesis

B. Systems Biology Integrates: Genomes, Networks, Symbiosis, Deep Homology

Temkin, Ilya and Niles Eldredge. Networks and Hierarchies: Approaching Complexity in Evolutionary Theory. Serrelli, E. and N. Gontier, eds. Macroevolution. Switzerland: Springer, 2015. A Smithsonian Natural History Museum zoologist and the American Museum of Natural History paleontologist provide a latest synoptic chapter (search Serrelli for book) of the “Hierarchy Theory of Evolution” that Eldredge has advanced since the 1980s. Google this phrase for its informative website.

This expansion of the hierarchy theory of evolution provides a new perspective in which biological phenomena are conceptualized. In this work, we (1) attempt to revise the ontology of levels of biological organization and clarify the relationship between the economic and genealogical hierarchies; (2) explore the implications of network theory for evolutionary dynamics in a hierarchical context; and (3) elucidate evolutionary causality by disentangling abiotic drivers from proximal evolutionary processes (the origin and sorting of variation) and their integration across hierarchies. We suggest that a pervasive pattern of stability in living systems across scale results from the architecture of nature’s economy itself — biological systems consisting of hierarchically nested, complex networks are extremely robust to extrinsic perturbations. We further argue that instances of evolution are episodic and rapid; they are transient between equilibrial states that ensue when network stability is compromised by sufficiently strong disturbances affecting biological entities at multiple levels of organization. We also claim that environmental abiotic factors are ultimately responsible for these perturbations that, when filtered through the economic hierarchy, shape the patterns of diversity and disparity of life as we know it. (Abstract)

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.

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)

Witzany, Gunther. Natural Genome Editing from a Biocommunicative Perspective. Biosemiotics. 4/3, 2011. As the Abstract below conveys, the prolific biophilosopher continues to advance this approach and school that moves beyond neoDarwinism to appreciate gene sequences in a way as an informative “language-like text.”

Natural genome editing from a biocommunicative perspective is the competent agent-driven generation and integration of meaningful nucleotide sequences into pre-existing genomic content arrangements, and the ability to (re-)combine and (re-)regulate them according to context-dependent (i.e. adaptational) purposes of the host organism. Natural genome editing integrates both natural editing of genetic code and epigenetic marking that determines genetic reading patterns. As agents that edit genetic code and epigenetically mark genomic structures, viral and subviral agents have been suggested because they may be evolutionarily older than cellular life.

This hypothesis that viruses and viral-like agents edit genetic code is developed according to three well investigated examples that represent key evolutionary inventions in which non-lytic viral swarms act symbiotically in a persistent lifestyle within cellular host genomes: origin of eukaryotic nucleus, adaptive immunity, placental mammals. Additionally an abundance of various RNA elements cooperate in a variety of steps and substeps as regulatory and catalytic units with multiple competencies to act on the genetic code. Most of these RNA agents such as transposons, retroposons and small non-coding RNAs act consortially and are remnants of persistent viral infections that now act as co-opted adaptations in cellular key processes.

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