IV. Ecosmomics: Independent, UniVersal, Complex Network Systems and a Genetic Code-Script Source

B. Our Own HumanVerse (Epi) Genomic Heredity

Lane, Nick and William Martin. The Energetics of Genome Complexity. Nature. 467/929, 2010. University College London, and Heinrich-Heine University geneticists propose a novel explanation of how cellular life originally prospered and grew together beyond rudimentary bacteria.

All complex life is composed of eukaryotic (nucleated) cells. The eukaryotic cell arose from prokaryotes just once in four billion years, and otherwise prokaryotes show no tendency to evolve greater complexity. Why Not? Prokaryotic genome size is constrained by bioenergetics. The endosymbiosis that give rise to mitochondria restructured the distribution of DNA in relation to bioenergetic membranes, permitting a remarkable 200,000-fold expansion in the number of genes expressed. This vast leap in genomic capacity was strictly dependent on mitochondrial power, and prerequisite to eukaryote complexity: the key innovation en route to multicellular life. (Abstract, 929)

The transition to complex life on Earth was a unique event that hinged on a bioenergetic jump afforded by spatially combinatorial relations between two cells and two genomes (endosymbiosis), rather than natural selection acting on mutations accumulated gradually among physically isolated prokaryotic individuals. Given the energetic nature of these arguments, the same is likely to be true of any complex life elsewhere. (933)

Ledford, Heidi. Riding the Crispr Wave. Nature. 531/136, 2016. A news report in a special section Crispr Everywhere about advances of this simple gene-splicing and editing technique with revolutionary potentials for genetic, medicinal and reproductive futures.

Levin, Michael and Christopher Martyniuk. The Bioelectric Code: An Ancient Computational Medium for Dynamic Control of Growth and Form. Biosystems. Online August, 2017. Tufts University and University of Florida biologists advance a broadly conceived project, with colleagues, to seek out and specify novel prescriptive means, agencies or informed forces which serve evolutionary organisms. The paper and task is imaginative and engaging as it elucidates more ways that life avails beside genes alone. As the second quote alludes, by way of computational analogies a doubleness of an independent, malleable program and resultant biological form and function can be perceived. See also, e.g., Endogenous Bioelectric Signaling Networks: Exploiting Voltage Gradients for control of Growth and Form by Leven, Giovanni Pezzulo and Joshua Finkelstein in Annual Review of Biomedical Engineering (19/353, 2017) and Physiological Inputs Regulate Species-Specific Anatomy During Embryogenesis and Regeneration by Kelly Sullivan, Maya Emmons-Bell, and Levin in Communicative & Integrative Biology (9/4, 2016) for more applications.

What determines large-scale anatomy? DNA does not directly specify geometrical arrangements of tissues and organs, and a process of encoding and decoding for morphogenesis is required. Moreover, many species can regenerate and remodel their structure despite drastic injury. The ability to obtain the correct target morphology from a diversity of initial conditions reveals that the morphogenetic code implements a rich system of pattern-homeostatic processes. Here, we describe an important mechanism by which cellular networks implement pattern regulation and plasticity: bioelectricity. All cells, not only nerves and muscles, produce and sense electrical signals; in vivo, these processes form bioelectric circuits that harness individual cell behaviors toward specific anatomical endpoints. We review emerging progress in reading and re-writing anatomical information encoded in bioelectrical states, and discuss the approaches to this problem from the perspectives of information theory, dynamical systems, and computational neuroscience. (Abstract)

This kind of generalized plasticity in servide to specific outcomes is closely related to a key insight that drove the development of the computer science revolution – the independence of hardware and software, and the ability to run the same software on different hardware, or obtain different behavior from the same hardware by changing the software. If bioelectric dynamics running on genome-specified ion channel complements in cells can be treated as a kind of software, the next revolution in biology could be likewise driven in part by the realization that we do not have to manipulate living systems at the level of their “machine code” (affecting specific molecules), but at the level of information – re-writing the encoded goal states and thus gaining a more top-down control over growth and form with myriad applications in biomedicine and robust technology. (15)

Lewontin, Richard. The Third Helix. Cambridge: Harvard University Press, 2000. As a response to the Human Genome hype, the renowned Harvard geneticist advises that DNA alone is not sufficient to specify even a folded protein much less an entire organism.

Liu, Shuming, et al. From Nucleosomes to Compartments: Physicochemical Interactions Underlying Chromatin Organization. Annual Review of Biophysics.. Volume 53, 2024. MIT system biologists add a latest chapter about life’s serial metabolic developments which can be traced to informative and topological genomic expressions. See also The Geometry of Chromatin by Subhash Kak at arXiv:2402.09408.

Chromatin organization plays a critical role in cellular function by regulating access to genetic information. However, its folding is hard to analyze due to a complex, multiscale nature. Advances have been made in vitro systems, individual nucleosomes, and the role of physicochemical forces in stabilization. But the resemblance between in vitro and in vivo chromatin conformations and internucleosomal interactions are subjects of debate. This article reviews experimental and computational studies which highlight intrinsic interactions between nucleosomes and their roles in chromatin folding. (Abstract).

Chromatin is a complex of DNA and protein found in eukaryotic cells.[1] The primary function is to package long DNA molecules into compact, denser structures. A nucleosome is a section of DNA that is wrapped around a core of proteins.

Longabaugh, William, et al. Computational Representation of Developmental Genetic Regulatory Networks. Developmental Biology. 283/1, 2005. Whereby ubiquitous complex system characteristics are similarly apparent in dynamic genomes. The authors then describe a freely available software package they have devised for their three-dimensional study: www.biotapestry.org.

Developmental genetic regulatory networks (GRNs) have unique architectural characteristics. They are typically large-scale, multilayered, and organized in a nested, hierarchy of regulatory network kernels, function-specific building blocks, and structural gene batteries. (1)

Marijuan, Pedro. Information and the Unfolding of Social Life: Molecular-Biological Resonances Reaching Up to the Economy. BioSystems. 46/1, 1998. A universal convergence is noted from “cellular signaling systems and vertebrate nervous systems” to “entrepreneurial accounting systems.”

Mattick, John. RNA Out of the Mist. Trends in Genetics. 19/3, 2023. Looking back 50 years, the veteran University of New South Wales geneticist reviews some 50 years of research studies as twists, turns and progress, in which he participated, toward current appreciations of the vital functions played by this major nucleotide.

RNA has long been regarded as the intermediate between genes and proteins. It was a surprise then to discover that eukaryotic genes are mosaics of mRNA sequences with by large tracts of transcribed but untranslated sequences, and that multicellular organisms express long ‘intergenic’ and antisense noncoding RNAs (lncRNAs). The emerging picture is that most lncRNAs are the products of genetic loci termed ‘enhancers’, which marshal generic effector proteins to their sites of action to control cell fate decisions during development. (Excerpt)

Maynard Smith, John and Eors Szathmary. The Orgins of Life. Oxford: Oxford University Press, 1999. A popular update of the authors’ 1995 treatise on major nested, informed transitions, which is reviewed more in A Genesis Evolutionary Synthesis, and by 2010 has become a major structural contribution to this imminent advance.

McGillivray, Patrick, et al. Network Analysis as a Grand Unifier in Biomedical Data Science. Annual Review of Biomedical Data Science. Vol. 1, 2018. In this new Annual Review edition, a team of Yale University biochemists, bioinformaticians, and geneticists including Mark Gerstein show how common network processes and topologies can similarly be applied with benefit to genomic and physiological realms. Sections such as Networked Systems are at the Core of Human Biology, Making Sense of Complexity in Biomolecular Networks, Network Motifs, Logic, and Stability, and Prediction using Machine Learning and Neural Networks via text and graphic displays offer a state of the art tutorial for later 2010 advances. By so doing, once again a nascent sense of a universal recurrence across molecule, organelle, cell, organ, entity, and population phases, as illustrations depict, of the same intricate dynamics becomes evident.

Biomedical data scientists study many types of networks, ranging neural nets to those created by molecular interactions. However an issue of interpretation exists. Here we show that molecular biological networks can be read in several straightforward ways. First, we divide a network into smaller components with individual pathways and modules. Second, we compute global statistics describing the network as a whole. Third, we can compare networks which can be within the same context (e.g., gene regulatory networks) or cross-disciplinary (e.g. governmental hierarchies). By studying the relationships between variants in networks, we can begin to interpret many common diseases, such as cancer and heart disease. (Abstract excerpt, edits)

Meadows, Jennifer and Kerstin Lindblad-Toh. Dissecting Evolution and Disease Using Comparative Vertebrate Genomics. Nature Reviews Genetics. 18/624, 2017. We cite this entry by Uppsala University and MIT/Harvard researchers (KLT credits below) to show how a worldwide biological science can achieve by theory and technique a retrospective reconstruction of the genetic endowment of prior evolutionary species. A full page graphic Figure 1 is entitled A Snapshot of Vertebrate Genome Sequencing Projects as they proceed from fish and reptiles to birds, mammals and onto human beings. Might one via a woman’s bicameral faculty ask and imagine what this whole scenario could be on its own? What kind of procreative ecosmos evolves to a sentient, collaborative global species able look back and do this?

With the generation of more than 100 sequenced vertebrate genomes in less than 25 years, the key question arises of how these resources can be used to inform new or ongoing projects. In the past, this diverse collection of sequences from human as well as model and non-model organisms has been used to annotate the human genome and to increase the understanding of human disease. In the future, comparative vertebrate genomics in conjunction with additional genomic resources will yield insights into the processes of genome function, evolution, speciation, selection and adaptation, as well as the quantification of species diversity. In this Review, we discuss how the genomics of non-human organisms can provide insights into vertebrate biology and how this can contribute to the understanding of human physiology and health. (Abstract)

Kerstin Lindblad-Toh is a professor in comparative genomics at Uppsala University and the director of Science for Life Laboratory Uppsala. As also the scientific director of vertebrate genome biology at the Broad Institute (Harvard/MIT) she is responsible for the 29 Mammals Project to annotate the human genome for functional constraint, as well as a large number of vertebrate genome projects. These include the dog disease-mapping group which has developed several SNP chips used to identify canine disease genes. The Science for Life Laboratory has a vision of being an internationally leading center that develops, applies, and provides access to large-scale technologies for molecular biosciences, with a focus on translational medicine and on evolutionary and systems biology. (KLT website)

Meinesz, Alexandre. How Life Began: Evolution’s Three Geneses. Chicago: University of Chicago, 2008. Reviewed in The Symbiotic Cell and noted here for this cogent quote of how well literature terms describe genetic activity.

To describe the characteristics of these modes of transmitting information, with their errors, mixings, and exchanges, scientists use printing terms: replication, transcription, recombination, transposition, translocation, reshuffling, inversion. These words apply to parts of the “book” (in this case, the nuclei) that constitutes the totality of the information of life: chapters (or, chromosomes), pages (parts of chromosomes), paragraphs (genes), lines (sequences of nucleotides), words (triplets of nucleotides), and letters (nucleotides). (106)

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