V. Life's Evolutionary Development Organizes Itself: A 2020s Genesis Synthesis
B. Systems Biology Integrates: Genomes, Networks, Symbiosis, Deep Homology
Malod-Dognin, Noel and Natasa Przulj. Functional Geometry of Protein Interactomes. Bioinformatics. 35/19, 2019. Barcelona Supercomputing Center life scientists show how these metabolic processes can similarly be found to exhibit common network topologies, which can then be modeled by simplical complexes just like the brain. See also Centralities in Simplical Complexes: Applications to Protein Interaction Networks by Ernesto Estrada and Grant Ross in the Journal of Theoretical Biology (438/46, 2018).
Markowetz, Florian and Michael Boutros, eds. Systems Genetics: Linking Genotypes and Phenotypes. Cambridge: Cambridge University Press, 2015. Leading researchers from Europe and the US provide a comprehensive survey of novel abilities to treat whole genomes, as now distinguished by gene regulatory networks, so as to better reveal how organisms form and flourish. A typical, notable chapter is Phenotype State Spaces and Strategies for Exploring Them by Andreas Hadjiprocopis and Rune Linding, whence evolution is an optimization endeavor due to self-organizing criticalities.
Medford, June and Diane McCarthy. Growing Beyond: Designing Plants to Serve Human and Environmental Interests. Current Opinion in Systems Biology. 5/82, 2017. In a section on Synthetic Biology, Colorado State University biologists look ahead from 20 years of molecular, cellular and system biology studies to see how they might avail an evolutionary reconception of nature’s fauna to enhance planetary viability. See also Bacterial Cancer Therapies, Protein Glycosylation in Prokaryotes, Control Systems for Diabetes.
Plant synthetic biology provides a pathway toward the design and construction of sustainable systems for life on earth. Traditional plant selection and breeding techniques have long enabled people to modify and enhance plant traits for human uses. However, these techniques are limited to traits that already exist in plants. Synthetic biology allows us to break free of this constraint and develop plants with entirely novel traits and redesigned biochemical pathways. Further, evolution itself provides a tool for the development of new and enhanced traits. While a plant's multicellular nature and long lifespan present challenges to synthetic biology research, the unique value of plant synthetic biology as a pathway toward sustainable systems outweighs the challenges. (Abstract)
Medina, Miguel. Systems Biology for Molecular Life Sciences and its Impact in Biomedicine. Cellular and Molecular Life Sciences. 70/6, 2013. A University of Malaga, Spain, biologist begins an extensive paper with historical roots from Vladimir Vernadsky, Ludwig Bertalanffy, Conrad Waddington, and Ilya Prigogine to Ramon Margalef, Per Bak, Brain Goodwin, Murray Gell-Mann, Stuart Kauffman, and others. By turns, a prior mechanistic reduction is to be now leavened through an admission of life’s equal preference for integral organisms. A signal advance of the past years is the recognition of the total extent that nested networks grace and serve anatomical and physiological vitality. Of importance is the profusion of “-omic” classes which endow a genetic essence to other forms and functions such as interactomes in cells, bodily metabolomes, and brainy connectomes. A large benefit is lately accruing by reconceptions of cellular cancers as dynamic, scale-free complexities.
Modern systems biology is already contributing to a radical transformation of molecular life sciences and biomedicine, and it is expected to have a real impact in the clinical setting in the next years. In this review, the emergence of systems biology is contextualized with a historic overview, and its present state is depicted. The present and expected future contribution of systems biology to the development of molecular medicine is underscored. Concerning the present situation, this review includes a reflection on the “inflation” of biological data and the urgent need for tools and procedures to make hidden information emerge. Descriptions of the impact of networks and models and the available resources and tools for applying them in systems biology approaches to molecular medicine are provided as well. The actual current impact of systems biology in molecular medicine is illustrated, reviewing two cases, namely, those of systems pharmacology and cancer systems biology. Finally, some of the expected contributions of systems biology to the immediate future of molecular medicine are commented. (Abstract)
Medina, Monica. Genomes, Phylogeny, and Evolutionary Systems Biology. Proceedings of the National Academy of Sciences. 102/Supplement 1, 2005. An article from a Sackler Colloquium on “Systematics and the Origin of Species: On Ernst Mayr’s 100th Anniversary” which describes “a new age of evolutionary research” made possible as genomes become sequenced and available online. This “postgenomics era” is now filling in and clarifying the eukaryotic tree of life from Genome to Transcriptome, Proteome, Interactome, Metabolome, and Phenome.
Mesarovic, M., et al. Search for Organizing Principles. IEE Proceedings – Systems Biology. 1/1, 2004. The inaugural issue of this new journal. As biological science struggles to gain theoretical roots in an inhospitable universe, a deliberate shift is underway from a reduction phase to a reassembly of all the genetic and cellular components. The same cannot be said for other fields that seem stuck in a fragment phase – there is not yet a Systems Physics, Systems Cosmology, or Systems Psychology.
Meyers, Robert A., ed. Systems Biology. Weinheim: Wiley-VCH, 2012. Among the spate of editions as this approach flourishes, a 700 page tutorial volume with main sections on its biological basis, evolution, modeling, medicine and disease, organisms. After conceptual overviews, topics include Embryogenomics, Interactome, Systematics, Proteins, Neuronal Dynamics, Plants, Synthetic Biology, and so on. Chapters such as Fractals in Biology and Medicine, and Chaos in Biochemistry and Physiology show how well the complexity and networks sciences describe integral genomes, cells and persons.
Moreno, Alvaro. A Systemic Approach to the Origin of Biological Organization. Boogerd, Fred, et al, eds. Systems Biology: Philosophical Foundations. Amsterdam: Elsevier/Academic Press, 2007. What does “nontrivial self-organization” mean? The University of the Basque Country philosopher of science describes in such abstract terms an extant nature which by its innate propensities, especially a “functional recursivity” of referring to and repeating its own “metabolic closure,” engenders a sequential scale of developmental autonomy. Two complementary realms of genotype and phenotype are said to involve an informational prescription and transmission, which then repeats at each phase and instance. Selective processes only occur later on after this original structuring is in effect. Which all begs translation into what kind of human universe is being revealed. Compare with recent work by Szathmary, Weiss, Butner, et al, for glimpses of a greater reality that conveys the same story over and over.
At the beginning, the driving force towards complexity was nothing but the confluence of several principles of ordering, such as self-assembly, template replication, or self-organization, merged in the framework of what I have called a nontrivial self-maintaining organization. The key of this process is functional recursivity, namely, the fact that every novelty capable of contributing to a more efficient autonomy, defined as a form of self-constructing organization, which maintains its identity through its interactions with its environment. (243)
Morris, Melody, et al. Logic-Based Models for the Analysis of Cell Signaling Networks. Biochemistry. 49/3216, 2010. MIT Center for Cell Decision Process bioengineers of coauthor Doug Lauffenburger’s Research Group (Google for papers) employ Boolean algebraic “truth tables” of OR, AND and NOT options to study how living networks go about their activities. A list of applicable programs such as BooleanNet, GinSim, CellNetOptimizer, and others are cited. Still another entry into genome, proteomes, interactomes, and the –omics lifescape is achieved, which proceeds to expand and reinterpret living systems by way of such genetic nonlinear relational dynamics.
Computational models are increasingly used to analyze the operation of complex biochemical networks, including those involved in cell signaling networks. Here we review recent advances in applying logic-based modeling to mammalian cell biology. Logic-based models represent biomolecular networks in a simple and intuitive manner without describing the detailed biochemistry of each interaction. (Abstract) With accelerating pace, molecular biology and biochemistry are identifying complex patterns of interactions among intracellular and extracellular biomolecules. With respect to cell signaling in eukaryotes, the focus of this review, complex multicomponent networks involving many shared components govern how a cell will respond to diverse environmental cues. Thus, mathematical and computational modeling is increasingly playing a role in data interpretation and attempts to extract general biological understanding. (3216)
Mousavian, Zaynab, et al. Information Theory in Systems Biology. Seminars in Cell & Developmental Biology. Volume 51, 2016. In a special issue edited by Ali Masoudi-Nejad and Hector Zenil with this title, University of Tehran biochemists lead with two papers, Part I: Gene Regulatory and Metabolic Networks, and Part II: Protein–Protein Interaction and Signaling Networks, which seek a vital synthesis between these approaches. See also Methods of Information Theory and Algorithmic Complexity for Network Biology by Zenil, et al, in the same issue, see second quote.
“A Mathematical Theory of Communication”, was published in 1948 by Claude Shannon to establish a framework that is now known as information theory. In recent decades, information theory has gained much attention in the area of systems biology. The aim of this paper is to provide a systematic review of those contributions that have applied information theory in inferring or understanding of biological systems. Based on the type of system components and the interactions between them, we classify the biological systems into 4 main classes: gene regulatory, metabolic, protein–protein interaction and signaling networks. In the first part of this review, we attempt to introduce most of the existing studies on two types of biological networks, including gene regulatory and metabolic networks, which are founded on the concepts of information theory. (Part I Abstract)
Moya, Andres, et al. Goethe’s Dream. EMBO Reports. 10/S1, 2009. In this issue on Systems Biology and the Virtual Physiological Human, University of Valencia biologists begin by reminding that Immanuel Kant (1724-1804) defined organisms as having “an intrinsic purpose, because they are self-organized in such a way that every part is a function of the whole.” Reference is then made to Johann von Goethe (1749-1832) whose holistic vista led him to write that while a living entity can be dissected into elements, its life only exists as an integral entity. In accord, this is our worldwide 21st century project to complete by systematically reassembling all the molecules, microbes, organs, anatomies and physiologies.
Nadeau, Joseph and Aimee Dudley. Systems Genetics. Science. 331/1015, 2011. Within the scientific revolution to reconceive every field by way of complex network dynamics, Institute for Systems Biology, Seattle, researchers pursue their theoretical application to active genetic phenomena. As a consequence, the historic shift in understanding genomes from particulate nucleotides to equally real dynamical interrelations, indeed as DNA/AND, is much underway. View the ISB website noted above and click on Nadeau Group or Dudley Group for more info.
In contrast to the networks of molecular and physical interactions that dominate the field of systems biology, systems genetics focuses on networks of interactions between genes and traits, as well as between traits themselves. (1015) an essential but not yet fully exploited application of systems genetics is the inference of higher-order functionality in complex systems from patterns of covariation among underlying molecular and physiological phenotypes. (1015)