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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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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

Asgari, Ehsaneddin and Mohammad Mofrad. Continuous Distributed Representation of Biological Sequences for Deep Proteomics and Genomics. PLoS One. November, 2015. A publication from M. Mofrad’s UC Berkeley Molecular Cell Biomechanics laboratory which is guided by a premise that this anatomy and physiology may be best studied if nature and life is seen to be suffused with a linguistic quality. Herein the synthesis is broached by way of deep neural learning, textual analysis, and bioinformatics. The second quote is from Asgari’s Life Language Processing web page. Search the Iranian-American authors, and other lab members, for additional papers.

Nature uses certain languages to describe biological sequences such as DNA, RNA, and proteins. Much like humans adopt languages to communicate, biological organisms use sophisticated languages to convey information within and between cells. Inspired by this conceptual analogy, we adopt existing methods in natural language processing (NLP) to gain a deeper understanding of the “language of life” with the ultimate goal to discover functions encoded within biological sequences. (2) Distributed representation has proved one of the most successful approaches in machine learning. The main idea in this approach is encoding and storing information about an item within a system through establishing its interactions with other members. Distributed representation was originally inspired by the structure of human memory, where the items are stored in a “content-addressable” fashion. Content-based storing allows for efficiently recalling items from partial descriptions. Since the content-addressable items and their properties are stored within a close proximity, such a system provides a viable infrastructure to generalize features attributed to an item. (2)

Nature uses certain languages to describe biological sequences such as DNA, RNA, and proteins. Much like humans adopt languages to communicate, biological organisms use sophisticated languages to convey information within and between cells. Inspired by this conceptual analogy, we adopt existing methods in natural language processing (NLP) to gain a deeper understanding of the "language of life'' with the ultimate goal to discover functions encoded within biological sequences. The language of life is still far from well-understood and could benefit from the modern techniques of computational linguistics and machine learning. In Life Language Processing (LLP) project we are interested in statistical linguistic modeling of life sequences. (www.llp.berkeley.edu)

Ashe, Alyson, et al, eds. How does Epigenetics Influence the Course of Evolution? Philosophical Transaction of the Royal Society B. April, 2021. The editors are AA and Benjamin Oldroyd, University of Sydney, and Vincent Colot, CNRS, Paris and here introduce this special issue which surveys an expanding array of influences upon “genomic” phenomena beyond nucleotides alone. See, for example< The Impact of Epigenetic Information on Genome Evolution by V. Soojin, et al and Epigenetic Inheritance and Evolution by Laurent Loison.

Epigenetics is the study of changes in gene activity that are transmitted through cell divisions but cannot be explained by changes in DNA sequence. Epigenetic mechanisms are central to development of genome integrity and for the ability of animals and plants to adjust to environments without the need for genetic change. However, because epigenetic states are somewhat reset at every generation, their effect has previously been seen as a minor contribution to evolutionary change. The papers in this theme issue describe how epigenetic variations make direct and indirect contributions to evolutionary processes including adaptation to new environments, climate change, species invasiveness, sex chromosome differentiation, and onto speciation. (Issue summary)

Balleza, Enrique, et al. Critical Dynamics in Genetic Regulatory Networks. PLoS One. 3/6, 2008. A team from the Universidad Nacional Autónoma de México, University of Calgary, and Institute for Systems Biology, Seattle, including Stuart Kauffman, find the natural universality of critically poised self-organized nonlinear phenomena to be equally and effectively present in genomes. As the extended Abstract conveys, these heretofore unnoticed qualities impart an inherent stability along with environmental and evolutionary responsiveness. By these insights across genetic research, a new relational dimension is being added beyond nucleotide molecules alone.

The coordinated expression of the different genes in an organism is essential to sustain functionality under the random external perturbations to which the organism might be subjected. To cope with such external variability, the global dynamics of the genetic network must possess two central properties. (a) It must be robust enough as to guarantee stability under a broad range of external conditions, and (b) it must be flexible enough to recognize and integrate specific external signals that may help the organism to change and adapt to different environments. This compromise between robustness and adaptability has been observed in dynamical systems operating at the brink of a phase transition between order and chaos. Such systems are termed critical. Thus, criticality, a precise, measurable, and well characterized property of dynamical systems, makes it possible for robustness and adaptability to coexist in living organisms.

In this work we investigate the dynamical properties of the gene transcription networks reported for S. cerevisiae, E. coli, and B. subtilis, as well as the network of segment polarity genes of D. melanogaster, and the network of flower development of A. thaliana. We use hundreds of microarray experiments to infer the nature of the regulatory interactions among genes, and implement these data into the Boolean models of the genetic networks. Our results show that, to the best of the current experimental data available, the five networks under study indeed operate close to criticality. The generality of this result suggests that criticality at the genetic level might constitute a fundamental evolutionary mechanism that generates the great diversity of dynamically robust living forms that we observe around us. (Abstract)

Bancaud, Aurelien, et al. Molecular Crowing Affects Diffusion and Binding of Nuclear Proteins in Heterochromatin and Reveals the Fractal Organization of Chromatin. EMBO Journal. 28/3785, 2009. “Chromatin” is a composite of DNA, RNA and proteins that makes up the nucleus of a cell. A research team at the European Molecular Biology Laboratory EMBL, Heidelberg, led by Jan Ellenberg, finds its architectural dynamics to exhibit an optimum packing density due to self-similarities across several scales and versions. Cellular nuclei self-organize their components and phases into this most efficient mode. These insights have achieved peer notice such as “Fractal Geometry in the Nucleus” by Jamey McNally and Davide Mazza (EMBO Journal 29/2, 2010), Claire Ainsworth’s “Cells Go Fractal: Mathematical Patterns Rule the Behavior of Molecules in the Nucleus” (Nature News September 4, 2009), and especially Erez Lieberman-Aiden, et al “Comprehensive Mapping of Long-range Interactions Reveals Folding Principles of the Human Genome” (Science 326/289, 2009).

The kinetic signatures of these crowding consequences allow us to derive a fractal model of chromatin organization, which explains why the dynamics of soluble nuclear proteins are affected independently of their size. This model further shows that the fractal architecture differs between heterochromatin and euchromatin, and predicts that chromatin proteins use different target-search strategies in the two compartments. We propose that fractal crowding is a fundamental principle of nuclear organization, particularly of heterochromatin maintenance. (Abstract, 3785)

Bapteste, Eric, et al. Networks: Expanding Evolutionary Thinking. Trends in Genetics. 29/8, 2013. A report on a Future of Phylogenetic Networks meeting in October 2012 in London about pervasive applications of this natural geometry to life’s variegated development course. In essence, trees become nuanced into more branchy, webby networks. See for example In the Light of Deep Coalescence: Revisiting Trees Within Networks by Jiafan Zhu, et al at arXiv:1606.07350 as an organic interconnectivity becomes increasingly evident. The term reticulate which means “resembling a network” is often used to describe.

Bateson, Patrick. New Thinking about Biological Evolution. Biological Journal of the Linnean Society. 112/2, 2013. The senior University of Cambridge zoologist is tapping into and trying to express a growing awareness that historic revisions and advances are much underway about how life developed from chemicals and microbes to primates and us. In regard, four areas and approaches are noted – organisms seem able to “constrain” their subsequent states, the major transitions scale due to novel informational sources, an Evo-Devo reunion of evolution and embryology, and signs of Lamarck-like epigenetic influences. A 21st century genesis-like synthesis is thus gaining robustness and veracity in our midst.

The article focuses on the active role of the organism in the subsequent evolution of its descendants. Choice, control of the environment, adaptability, and mobility all play their part. This growth area in biology and other active centres of research on epigenetics and different forms of inheritance are re-invigorating evolutionary biology. Many evolutionary biologists have taken the view that an understanding of development is irrelevant to theories of evolution. However, the integration of several disciplines now suggests that the orthodoxy is misplaced. (Abstract)

My sense is that the theories of biological evolution have been reinvigorated by the convergence of different disciplines. The combination of developmental and behavioral biology, ecology, evolutionary biology, and now microbiology has shown how important the active roles of the organism are in the evolution of its descendants. The combination of molecular biology, palaeontology, and evolutionary biology has shown important an understanding of developmental biology is in explaining the constraints on variability and the direction of evolutionary change. In other words, evolutionary theory is evolving. (6)

Bizzarri, Mariano, et al. Theoretical Aspects of Systems Biology. Progress in Biophysics and Molecular Biology. 112/1-2, 2013. Keywords are Systems Biology, Biophysical Constraints, Complexity, Fractals, Non-Linearity, Morphogenetic Fields. A decade on, Sapienza University of Rome research physicians provide a cogent survey of this holistic reassembly to better understand life’s genomic and metabolic essences. Actually, after many decades of identifying all the molecular, cellular, and organismic pieces, a new obvious phase is entered to put them back together via their interconnective networks and constant modularity, namely “putting genes in context.” The august discovery to then be made is that a similarly invariant topology and vitality can be observed at each and every nested scale and instance. A breakthrough payoff is to treat cancers as dynamic complexities, for example in Seminars in Cancer Biology, 21/3, 2011. See also by Bizzarri, et al (Quote 2) “Physical Forces and Non-linear Dynamics Mould Fractal Cell Shape” in Histology and Histopathology 28/2, 2013, and “Systems Biology for Molecular Life Sciences and its Impact in Biomedicine” by Miguel Medina herein.

The natural world consists of hierarchical levels of complexity that range from subatomic particles and molecules to ecosystems and beyond. This implies that, in order to explain the features and behavior of a whole system, a theory might be required that would operate at the corresponding hierarchical level, i.e. where self-organization processes take place. In the past, biological research has focused on questions that could be answered by a reductionist program of genetics. The organism (and its development) was considered an epiphenomenona of its genes. However, a profound rethinking of the biological paradigm is now underway and it is likely that such a process will lead to a conceptual revolution emerging from the ashes of reductionism. This revolution implies the search for general principles on which a cogent theory of biology might rely. Because much of the logic of living systems is located at higher levels, it is imperative to focus on them. Indeed, both evolution and physiology work on these levels. Thus, by no means Systems Biology could be considered a ‘simple’ ‘gradual’ extension of Molecular Biology. (Abstract, Bizzarri 1)

Cell shape is mainly determined by biophysical constraints, interacting according to non-linear dynamics upon the basic units provided by the genome. In turn, the specific configuration a cell acquires plays a fundamental, permissive role in modulating gene expression and many other complex biological functions. Cell shape is tightly connected to cell activity and can be considered the most critical determinant of cell function. As a consequence, measurable parameters describing shape could be considered as ‘omics’ descriptors of the specific level of observation represented by the cell-stroma system. Such an approach promises to formalize some of the underlying basic mechanisms and, ultimately, provide a holistic understanding of the biological processes. (Abstract, Bizzarri 2)

Bogdan, Paul, et al. Biological Networks Across Scales. Integrative & Comparative Biology. 61/6, 2022. Eleven coauthors across the USA including Gustavo Caetano-Anolles and Hyunji Kim post a lead paper in this special NSF Rules of Life edition. A long subtitle is The Theoretical and Empirical Foundations for Time-Varying Networks that Connect Structure and Function across Levels of Biological Organization. As a capsule, a central theme these studies is to include the primary anatomical and physiological presence of dynamic multiplex webworks, as if a missing element until now, as they serve to give form and function to the evolving and metabolic cellular components. We note again that by so doing the occasion of a universal repetition in kind of an iconic node and link commonality becomes increasingly evident.

Many biological systems scale in size and complexity so to exhibit a temporal network structure that emerges and self-organizes as it interacts with an environment. Living networks are everywhere from gene regulatory phases, protein interactions for physiology and metabolism, neural networks, onto animal groupings and social migrations. In particular, there may be structural features that result in homeostatic networks with specific higher-order statistics (multifractal spectrum). Here, we explore an opportunity for discovering universal laws which connect the structure of biological networks with their organism function. (Abstract excerpt)

Boogerd, Fred, et al, eds. Systems Biology: Philosophical Foundations. Amsterdam: Elsevier/Academic Press, 2007. A broad technical survey of theoretical approaches and methodologies.

Breuker, Casper, et al. Functional Evo-Devo. Trends in Ecology and Evolution. 21/9, 2006. Both conceptual and data-based advances in the reunion of evolutionary phylogeny with ontological development can be fostered by new appreciations of a pervasive modularity. But as also evident in the accompanying Klaus Hofmann, et al article, consideration is not yet given to why organisms have such propensities, where might this come from and what kind of natural universe.

Biological systems consist of parts that are recognizable because they are integrated internally and are relatively distinct from other such parts. In general, the concept of modularity refers to this property of integration within, and relative autonomy among, the parts or modules. Modularity is studied most often in a structural context, where it refers to the spatial arrangement of physical parts at different organizational levels from molecules to entire organisms. However, modularity also exists in contexts that are based on different kinds of interactions, such as pathways in metabolic networks, gene regulatory interactions, developmental and functional interactions among traits, and even behavioral interactions among individuals. (489)

Briscoe, James and James Sharpe. Genetics of Systems Biology. Current Opinion in Genetics and Development. 22/6, 2012. An introduction to an issue on this subject with articles such as The Importance of Geometry in Mathematical Models of Developing Systems, Evolution in Developmental Phenotype Space, and Towards a Statistical Mechanics of Cell Fate Decisions (search Ojalvo).

Caetano-Anolles, Gustavo, ed. Evolutionary Genomics and Systems Biology. New York: Wiley-Blackwell, 2010. This comprehensive survey by leading practitioners is a good example of the breadth, robustness and maturity of an historic, integral revision just beginning its course. Typical, notable papers are “The Role of Information in Evolutionary Genomics of Bacteria” by Antoine Danchin and Agnieszka Sekowska, “Genotypes and Phenotypes in the Evolution of Molecules” by Peter Schuster, and Eivind Almaas’ “Evolution of Metabolic Networks.”

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