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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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V. Life's Evolutionary Development Organizes Itself: A 2020s Genesis Synthesis

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

Shubin, Neil. Gene Regulatory Networks and Network Models in Development and Evolution. Proceedings of the National Academy of Sciences. 114/Vol. 23, 2017. An introduction to this September 2015 Sackler Colloquium organized by Shubin in honor and memory of Eric Davidson (1937-2015), the CalTech biologist (search both) who since the early 2000s studied and advocated the genomic and evolutionary importance of active nucleotide connectivities. Among the papers are Causes and Evolutionary Consequences of Primordial Germ-cell Specification in Metazoans, Gene Regulation During Drosophila Eggshell Patterning, Applying Gene Regulatory Network Logic to the Evolution of Social Behavior (search Baran) and Assessing Regulatory Information in Developmental Gene Regulatory Networks by Eric Davidson and Isabelle Peter (abstract next). This “conceptual revolution” is now in full force as many more entries in the new section attest.

Gene regulatory networks (GRNs) provide a transformation function between the static genomic sequence and the spatial specifications operating development. We address regulatory information at different levels of network organization from single node to subcircuit to large-scale GRNs and how design features such as architecture, hierarchical organization, and cis-regulatory logic contribute to developmental functions. Using subcircuits from the sea urchin endomesoderm GRN, we evaluate by Boolean modeling and in silico perturbations the import of circuit features. Thus, we begin to see how regulatory information encoded at individual nodes is integrated at all levels of network organization to control developmental process. (IP & ED Abstract excerpt)

Soyer, Orkun, ed. Evolutionary Systems Biology. Berlin: Springer, 2012. A collection edited by the University of Exeter biologist to provide a better notice throughout life’s long course of how so much interactive, dynamically generative phenomena is going on. The publisher waxes “This book tries to decipher evolutionary design principles and the origins of systems level properties in biology, such as modularity, robustness, and network connectivity.” Typical chapters are Paulien Hogeweg’s “Toward a Theory of Multilevel Evolution: Long-Term Information Integration Shapes the Mutational Lindscape and Enhances Evolvability,” and “Building Synthetic systems to Learn Nature’s Design Principles” by Eric Davidson, et al. In "On the Search for Design Principles in Biological Principles in Biological Systems" Juan Poyatos, Logic of Genomic Systems Laboratory, Spanish National Biotechnology Centre, agrees that the 1960s project of General Systems Theory is at last confirmed for there are indeed independent, universal laws or program that repeat in kind across life's emergent scale. So might we now consider another integral school designated as “Systems Evolution?” For a follow-up synopsis, see “Evolutionary Systems Biology: What It Is and Why It Matters” by Soyer and Maureen O’Malley in BioEssays (Online May, 2013).

Most of evolutionary theory has abstracted away from how information is coded in the genome and how this information is transformed into traits on which selection takes place. While in the earliest stages of biological evolution, in the RNA world, the mapping from the genotype into function was largely predefined by the physical–chemical properties of the evolving entities (RNA replicators, e.g. from sequence to folded structure and catalytic sites), in present-day organisms, the mapping itself is the result of evolution. I will review results of several in silico evolutionary studies which examine the consequences of evolving the genetic coding, and the ways this information is transformed, while adapting to prevailing environments. Such multilevel evolution leads to long-term information integration. Through genome, network, and dynamical structuring, the occurrence and/or effect of random mutations becomes nonrandom, and facilitates rapid adaptation. This is what does happen in the in silico experiments. Is it also what did happen in biological evolution? I will discuss some data that suggest that it did. (Hogeweg Abstract)

Most of evolutionary theory has abstracted away from how information is coded in the genome and how this information is transformed into traits on which selection takes place. While in the earliest stages of biological evolution, in the RNA world, the mapping from the genotype into function was largely predefined by the physical–chemical properties of the evolving entities (RNA replicators, e.g. from sequence to folded structure and catalytic sites), in present-day organisms, the mapping itself is the result of evolution. I will review results of several in silico evolutionary studies which examine the consequences of evolving the genetic coding, and the ways this information is transformed, while adapting to prevailing environments. Such multilevel evolution leads to long-term information integration. Through genome, network, and dynamical structuring, the occurrence and/or effect of random mutations becomes nonrandom, and facilitates rapid adaptation. This is what does happen in the in silico experiments. Is it also what did happen in biological evolution? I will discuss some data that suggest that it did. (Hogeweg Abstract)

Spirin, Victor, et al. A Metabolic Network in the Evolutionary Context: Multiscale Structure and Modularity. Proceedings of the National Academy of Sciences. 103/8774, 2006. A collaboration of Harvard, MIT, Moscow State University and the Russian Academy of Sciences finds that the universal system dynamics are able to distinguish organic function from genomes to metabolisms in a recursive way that reemploys “independent and easily interchangeable units.”

The enormous complexity of biological networks has led to the suggestion that networks are built of modules that perform particular functions and are “reused” in evolution in a manner similar to reusable domains in protein structures or modules of electronic circuits. (8774)

Stephanou, Angelique, et al. Systems Biology, Systems Medicine, Systems Pharmacology. Acta Biotheretica. 66/4, 2018. University of Grenoble, North Wales Cancer Centre, University of Paris and University of Warwick system physicians advise how a turn to an integral “omics” perspective can much inform and guide these palliative services.

Systems biology is today such a widespread discipline that it becomes difficult to propose a clear definition of what it really is. For some, it remains restricted to the genomic field. For many, it designates the integrated approach or the corpus of computational methods employed to handle the vast amount of biological or medical data and investigate the complexity of the living. Systems biology, with its subfields of medicine, pharmacology and others, aims at making sense of complex observations/experimental and clinical datasets to improve our understanding of diseases and their treatments without putting aside the context in which they appear and develop.. (Abstract)

Stolovitzky, Gustavo, et al, eds. The Challenges of Systems Biology. Annals of the New York Academy of Sciences. Volume 1158, 2009. Papers from the Second Dialogue on Reverse Engineering Assessment and Methods (DREAM2) conference in New York City, December 2007, that try to identify and enhance “Community Efforts to Harness Biological Complexity.” By these lights, it is said to be important to recognize, at its onset, the worldwide locus of this historic revolution.

Stone, J. R. and Brian Hall. A System for Analyzing Features in Studies Integrating Ecology, Development, and Evolution. Biology and Philosophy. 21/1, 2006. A 16 class matrix is outlined to join isomorphic, allometric, homoplastic, and like properties.

Ecology is being introduced to Evolutionary Developmental Biology to enhance organism-, population-, species-, and higher-taxon-level studies. This exciting, burgeoning troika will revolutionize how investigators consider relationships among environment, ontogeny, and evolution. (25)

Strohman, Richard. Maneuvering in the Complex Path from Genotype to Phenotype. Science. 296/701, 2002. The emeritus professor of molecular and cell biology at the University of California at Berkeley is a leader in articulating the nascent paradigm shift from particulate genes and selection alone to rule-based self-organizing systems as equally involved in a complementary fashion as genotype develops into organism. (And their existence then implies a different genesis universe.) More on Strohman’s views, and other researchers in this regard, can be found at: www.cswe.org/publications/jswe/03-2strohman.htm#t.

Human disease phenotypes are controlled not only by genes but by lawful self-organizing networks that display system-wide dynamics. (701) At the center of this effort is a need to understand the formal relationship between genes and proteins as agents, and the dynamics of the complex systems of which they are composed. (701)

Stumpf, Michael, et al. Evolution at the System Level: The Natural History of Protein Interaction Networks. Trends in Ecology and Evolution. 22/7, 2007. Another pervasive feature to appreciate as living entities are being put back together.

Susaki, Etsuo, et al. Next-Generation Mammalian Genetics toward Organism-Level Systems Biology. npj Systems Biology. 3/15, 2017. In this Nature journal, University of Tokyo and RIKEN Quantitative Biology Center, Osaka researchers propose curative advances such as Site-Specific Endonucleases by which to read and edit mouse genomes.

Systems Biology is a natural extension of molecular and cellular biology, which consists of multi-stage processes beginning with a (1) comprehensive identification and (2) quantitative analysis of individual system components and their networked interaction, which leads to the ability to (3) control existing systems toward the desired state and (4) design new systems based on an understanding of the underlying structural and dynamical principles. (1)

Organism-level systems biology in mammals aims to identify, analyze, control, and design molecular and cellular networks executing various biological functions in mammals. In particular, system-level identification and analysis of molecular and cellular networks can be accelerated by next-generation mammalian genetics. Mammalian genetics without crossing, where all production and phenotyping studies of genome-edited animals are completed within a single generation drastically reduce the time, space, and effort of conducting the systems research. Next-generation mammalian genetics is based on recent technological advancements in genome editing and developmental engineering. (Abstract)

Takeuchi, Nobuto and Paulien Hogeweg. Evolutionary Dynamics of RNA-like Replicator Systems: A Bioinformatic Approach to the Origin of Life. Physics of Life Reviews. 9/3, 2012. While new sciences of epigenetic phenomena serve to trace genomic activity upward into organism complexities, a parallel effort is extending, via such computational methods, the roots of replication deeper into biomolecule and chemical precursor domains. As a result, National Center for Biotechnology Information, NIH, and Theoretical Biology and Bioinformatics Group, Utrecht University, researchers contribute to this on-going perception of natural realms increasingly distinguished by an inherent informational essence. Paulien Hogeweg (search) is a pioneer in this endeavor and coined the term “bioinformatics” in the 1970s.

We review computational studies on prebiotic evolution, focusing on informatic processes in RNA-like replicator systems. In particular, we consider the following processes: the maintenance of information by replicators with and without interactions, the acquisition of information by replicators having a complex genotype-phenotype map, the generation of information by replicators having a complex genotype-phenotype-interaction map, and the storage of information by replicators serving as dedicated templates. Focusing on these informatic aspects, we review studies on quasi-species, error threshold, RNA-folding genotype-phenotype map, hypercycle, multilevel selection (including spatial self-organization, classical group selection, and compartmentalization), and the origin of DNA-like replicators. In conclusion, we pose a future question for theoretical studies on the origin of life. (Abstract)

Tauber, Alfred. Expanding Immunology: Defensive versus Ecological Perspectives. Perspectives in Biology and Medicine. 51/2, 2008. In a review of Elling Ulvestad’s Defending Life: The Nature of Host-Parasite Relations, the Boston University philosophical hematologist outlines a long paradigm revolution in immunology that has lately reached substantiation. For most of the last century, immune responses were held to occur between white cells and pathogens in defense of the host self. In this age of bioinformatics and systems biology, the whole organism-environment complex is now the relevant milieu. In addition to components alone, dynamic interactions are of equal importance in the sense of a figure/ground ecology. Beginning with Niels Jerne’s idiotypic network theory of an interlocking lattice of antibodies and lymphocytes, the new immunology is founded upon endemic self-organization. A good bibliography is appended for this epochal shift, of which this crucial field offers a microcosmic example.

An obvious challenge for a more comprehensive biology reiterates the problem of defining the principles of information, which grounds the self-organization of organic systems. How to articulate that problem and its solution should hold the attention of systems biologists and their critics, for without a philosophy and accompanying language to address the nature of form, one cannot proceed to establish a truly novel science. (281)

Tauber, Alfred. The Immune System and Its Ecology. Philosophy of Science. 75/2, 2008. Another lucid review of the historical shift with regard to organism and environment responses from a reduced, particulate self at war to an holistic, dynamic conversation. As noted elsewhere, the field of theoretical immunology can be appreciated as an example of this readjustment apparent in many other natural domains, and indeed for science as a whole.

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