VIII. Earth Earns: An Open CoCreative Earthropocene to Astropocene PediaVerse

2. Second Genesis: EarthWise LifeKinder Transitions to a New Intentional, BioGenetic Questiny

Haimovich, Adrian, et al. Genomes by Design. Nature Reviews Genetics. 16/501, 2015. Yale University systems biologists entertain a novel phase of not only “reading” nucleotide sequences, but of taking up their “writing” anew. We cite this frontier article as a sample among thousands across a proliferation of genetic, biological, informatics, journals and beyond. See also The Genome Project-Write by Jef Boeke, et al in Science (Online June 2016) about a consortium led by George Church, and Genotype Specification Language by Erin Wilson, et al in ACS Synthetic Biology (5/6, 2016).

Next-generation DNA sequencing has revealed the complete genome sequences of numerous organisms, establishing a fundamental and growing understanding of genetic variation and phenotypic diversity. Engineering at the gene, network and whole-genome scale aims to introduce targeted genetic changes both to explore emergent phenotypes and to introduce new functionalities. Expansion of these approaches into massively parallel platforms establishes the ability to generate targeted genome modifications, elucidating causal links between genotype and phenotype, as well as the ability to design and reprogramme organisms. In this Review, we explore techniques and applications in genome engineering, outlining key advances and defining challenges. (Abstract)

Harteveld, Zander, et al. Exploring “dark-matter” protein folds using deep learning. Cell Systems. November, 2024. This entry by ten École Polytechnique Fédérale de Lausanne and Swiss Institute of Bioinformatics computer scientists achieves a notable example (see quotes) of an imminent ecosmic passage from a long vicarious, selective evolutionary phase to a second, sentient, intentional, ethically guided Earthumanity evolitionary procreativity. In certain regard, the actual Genesis word is used.

De novo protein design explores uncharted sequence and structure space to generate novel versions not sampled by evolution. We present a convolutional variational autoencoder that learns patterns of protein structure, dubbed Genesis. We coupled Genesis with trRosetta to design sequences protein folds and found that they can reconstruct distance and angle distributions for five native folds and three novel folds. Our approach addresses the backbone designability problem, showing that small neural networks can efficiently learn structural patterns in proteins. (Excerpt)

Evolution is a gradual process that has sampled a small fraction of possible protein sequence spaces. In many instances, natural sequences collapse into 3D structures that as a finite set of protein folds. To explore novel sequences that fold into 3D conformations outside the natural repertoire and amenable to new functionalities, de novo protein design strategies have been developed. These structure-based protein design approaches rely on a two-step process where (1) the protein fold is outlined and corresponding back bones are generated, and (2) amino acid (aa) sequences are searched to fit the generated backbones. (1)

Genesis-trRosetta presents a modular approach for designing de novo proteins where control over the shape is desired. Our method could create custom protein backbones that conform to structured protein interfaces and nanomaterials. Therefore, we anticipate that the versatility and speed of the Genesis-trRosetta method, combined with other new DNN tools for protein design and engineering, can facilitate exploring the vast protein universe and serve as a valuable resource for future research. (12)

Hartmann, Jonas and Roberto Mayor. Self-organized collective cell behaviors as design principles for synthetic developmental biology. Seminars in Cell and Development Biology. 141/63, 2024. We cite this paper by University College London system biologists as a leading edge instance of an intentional turn to and inclusion of life’s inherent vitality as much due to this implicate domain of generative agencies. That is, a recognition that much more is going on beyond than just cellular metabolisms.

Over the past two decades, molecular cell biology has graduated from a mostly analytic science to one with substantial synthetic capability. This success is built on a deep understanding of the structure and function of biomolecules and molecular mechanisms. Here, we review some of the central concepts and recent progress in tissue patterning, morphogenesis and collective cell migration and discuss their value for synthetic developmental biology, emphasizing in particular the power of (guided) self-organization and the role of theoretical advances in making developmental insights applicable in synthesis.

Hernandez-Espinosa, Nancy, et al. Stimulus-responsive Self-assembly of Protein-based Fractals by Computational Design. Nature Chemistry. 11/7, 2019. A team of nineteen Rutgers University biochemists provide a good example of an intentional avail of nature’s animate propensity to form fractional self-similarity topologies as its preferred topology. In addition to biomolecular compounds, these geometric features need be factored as a vital aspect of novel procreations. By way of late 2010s display graphics, fractal zooms are shown which course through many scalar dimensions.

Hoang, Tuan-Hao, et al. On Synergistic Interactions between Evolution, Development and Layered Learning. IEEE Transactions on Evolutionary Computation. 15/3, 2011. Computation theorists Hoang, Le Quy Don Technical University, Hanoi, with Robert McKay, Seoul National University, Daryl Essam, University of New South Wales, and Nquyen Xuan Hoai, Hanoi University, survey in retrospect life’s evolution as a developmental process distinguished by incremental learning stages. Since nature knows best, such principles and procedures ought to be applied to improve our civilizational problem solving abilities going forward. And again if to wonder, might worldwide projects of this kind represent a generative cosmos just now passing to a profound revolutionary phase as a “second genesis,” via our intentional new creation?

We investigate interactions between evolution, development and lifelong layered learning in a combination we call evolutionary developmental evaluation (EDE), using a specific implementation, developmental tree-adjoining grammar guided genetic programming (GP). The approach is consistent with the process of biological evolution and development in higher animals and plants, and is justifiable from the perspective of learning theory. In experiments, the combination is synergistic, outperforming algorithms using only some of these mechanisms. It is able to solve GP problems that lie well beyond the scaling capabilities of standard GP. The solutions it finds are simple, succinct, and highly structured. We conclude this paper with a number of proposals for further extension of EDE systems. (Abstract)

We concentrate on four aspects of evolutionary development in complex organisms: an underlying evolutionary mechanism, a developmental mechanism, multiple evaluations throughout development, and layered learn of increasingly complex problems. Implementing them in a genetic programming system, we investigate their performance, in particular investigating whether they interact synergistically to solve more complex problems than the individual components can handle. (287)

Holtzman, Liad and Charles Gersbach. Editing the Epigenome: Reshaping the Genomic Landscape. Annual Review of Genomics and Human Genetics. Vol. 19, 2018. Duke University, Center for Genomic and Computational Biology researchers advance novel abilities to delve into, do over, and make better every aspect of our genetic origins. In this chapter, ways to edit even epigenetic phenomena are explored. But rather than “re-engineering,” a term used, a sense of “re-scripting” – respectfully clarifying, removing typos, improving fates – would seem more appropriate.

The eukaryotic epigenome has an instrumental role in determining and maintaining cell identity and function. Epigenetic components such as DNA methylation, histone tail modifications, chromatin accessibility, and DNA architecture are tightly correlated with central cellular processes, while their dysregulation manifests in aberrant gene expression and disease. This review summarizes these technologies and insights from recent studies, describes the complex relationship between epigenetic components and gene regulation, and highlights caveats and promises of the emerging field of epigenome editing, including applications for translational purposes, such as epigenetic therapy and regenerative medicine. (Abstract excerpt)

Hoshika, Shuichi, et al. Hachinoji DNA and RNA: A Genetic System with Eight Building Blocks. Science. 363/884, 2019. A sixteen person collaboration from co-author Steven Benner’s Foundation for Applied Molecular Evolution, Florida, Indiana University, UT Austin, DNA Software, Ann Arbor, and the University of Chicago reports this doubling of the genetic alphabet to show how facile it can be done. The work merited a review DNA Gets a New – Bigger – Genetic Alphabet by Carl Zimmer in the New York Times for February 21, 2019.

We report DNA- and RNA- like systems built from eight nucleotide “letters” (hence the name “hachimoji”) that form four orthogonal pairs. These synthetic systems meet the structural requirements needed to support Darwinian evolution, including a polyelectrolyte backbone, predictable thermodynamic stability, and stereoregular building blocks that fit a Schrödinger aperiodic crystal. Measured thermodynamic parameters predict the stability of hachimoji duplexes, allowing hachimoji DNA to increase the information density of natural terran DNA. These results expand the scope of molecular structures that might support life, including life throughout the cosmos. (Abstract)

Huang, Po-Ssu, et al. The Coming of Age of de novo Protein Design. Nature. 537/320, 2016. We cite this work by University of Washington biochemists as an instance of the advent of seemingly unlimited human abilities to begin anew a second intentional genesis by virtue of taking up nature’s own omics code

There are 20200 possible amino-acid sequences for a 200-residue protein, of which the natural evolutionary process has sampled only an infinitesimal subset. De novo protein design explores the full sequence space, guided by the physical principles that underlie protein folding. Computational methodology has advanced to the point that a wide range of structures can be designed from scratch with atomic-level accuracy. Almost all protein engineering so far has involved the modification of naturally occurring proteins; it should now be possible to design new functional proteins from the ground up to tackle current challenges in biomedicine and nanotechnology. (Abstract)

In general usage, de novo is a Latin expression meaning "from the beginning," "afresh," "anew," "beginning again." In biology and chemistry, a term for any method that makes predictions about biological features using only a computational model without extrinsic comparison to existing data. In this context, it may be sometimes interchangeable with the Latin ab initio.

Jackel, Christian, et al. Protein Design by Directed Evolution. Annual Review of Biophysics. 37/153, 2008. ETH Zurich chemists facilitate a Darwinian selectivity of candidate protein molecules as another instance of a genesis universe entering a new sensate phase of its self-creation of animate, personal materiality.

Jeschek, Markus, et al. Directed Evolution of Artificial Metalloenzynes for in vivo Metathesis. Nature. 537/661, 2016. Guided by studies of biocatalysis, ETH Zurich biochemists look forward to life’s next frontier of intentionally designed metabolisms. We note this among many similar papers to wonder if we creative peoples ought to consider ourselves, individually and globally, as “cosmic catalysts” whom are meant to initiate and carry forth a new genesis creation?

Jorgenson, Tyler, et al. Self-Assembly of Hierarchical DNA Nanotube Architectures with Well-Defined Geometries. ACS Nano. 11/2, 2017. We cite this by Johns Hopkins University chemical engineers in co-author Rebecca Schulman’s DNA Technology and Intelligent Materials Group among many similar articles to convey the innate, expanding versatilities of nucleotide molecules.

An essential motif for the assembly of biological materials such as actin at the scale of hundreds of nanometers and beyond is a network of one-dimensional fibers with well-defined geometry. Here, we demonstrate the programmed organization of DNA filaments into micron-scale architectures where component filaments are oriented at preprogrammed angles. We assemble L-, T-, and Y-shaped DNA origami junctions that nucleate two or three micron length DNA nanotubes at high yields. The angles between the nanotubes mirror the angles between the templates on the junctions, demonstrating that nanoscale structures can control precisely how micron-scale architectures form. The ability to precisely program filament orientation could allow the assembly of complex filament architectures in two and three dimensions, including circuit structures, bundles, and extended materials. (Abstract)

Karalkar, Nilesh and Steven Benner. The Challenge of Synthetic Biology: Synthetic Darwinism and the Aperiodic Crystal Structure. Current Opinion in Chemical Biology. 46/188, 2018. Foundation for Applied Molecular Evolution, Florida biochemists (search SB) continue to scope out a “natural genesis 2.0” passage from olden trial and error contingencies to a radical phase of our aware, collaborative, informed future (re)creation. This respectful, palliative enhancement will involve an expanded nucleotide alphabet and whole scale rewrite of life’s genomic code-script program.

Our grand challenge here is to reproduce the Darwinism of terran biology, but on molecular platforms different from standard DNA. Access to Darwinism distinguishes the living from the non-living state. However, theory suggests that any biopolymer able to support Darwinism must (a) be able to form Schrödinger's `aperiodic crystal’, where different molecular components pack into a single crystal lattice, and (b) have a polyelectrolyte backbone. In 1953, the descriptive biology of Watson and Crick suggested DNA met Schrödinger’s criterion, forming a linear crystal with geometrically similar building blocks supported on a polyelectrolye backbone. At the center of genetics were nucleobase pairs that fit into that crystal lattice by having both size complementarity and hydrogen bonding complementarity to enforce a constant geometry. (Abstract)

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