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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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VIII. Earth Earns: An Open Participatory Earthropocene to Astropocene CoCreative Future

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

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)

Karr, Jonathan, et al. A Whole-Cell Computational Model Predicts Phenotype from Genotype. Cell. 150/2, 2012. The New York Times for July 20, 2012 cites this work as the “first computational simulation of an entire organism.” Researchers from Stanford University and the Venter Institute claim to demonstrate how “complex phenotypes can be modeled by integrating cell processes into a single model.”

Understanding how complex phenotypes arise from individual molecules and their interactions is a primary challenge in biology that computational approaches are poised to tackle. We report a whole-cell computational model of the life cycle of the human pathogen Mycoplasma genitalium that includes all of its molecular components and their interactions. An integrative approach to modeling that combines diverse mathematics enabled the simultaneous inclusion of fundamentally different cellular processes and experimental measurements. Our whole-cell model accounts for all annotated gene functions and was validated against a broad range of data. The model provides insights into many previously unobserved cellular behaviors, including in vivo rates of protein-DNA association and an inverse relationship between the durations of DNA replication initiation and replication. In addition, experimental analysis directed by model predictions identified previously undetected kinetic parameters and biological functions. We conclude that comprehensive whole-cell models can be used to facilitate biological discovery. (Abstract)

Kelsey, Gavin, et al. Single-Cell Epigenomics: Recording the Past and Predicting the Future. Science. 358/69, 2017. Kelsey and Wolf Reik, Babraham Institute, UK, with Oliver Stegle, European Bioinformatics Institute, contribute another way that next generation abilities for genetic reading and writing from relative word to sentence to paragraph to organism bode well for life’s second, intentionally enscripted genesis.

Single-cell multi-omics has recently emerged as a powerful technology by which different layers of genomic output—and hence cell identity and function—can be recorded simultaneously. Integrating various components of the epigenome into multi-omics measurements allows for studying cellular heterogeneity at different time scales and for discovering new layers of molecular connectivity between the genome and its functional output. Together with techniques in which cell lineage is recorded, this multilayered information will provide insights into a cell’s past history and its future potential. This will allow new levels of understanding of cell fate decisions, identity, and function in normal development, physiology, and disease. (Abstract)

Kendig, Catherine and Todd Eckdahl. Reengineering Metaphysics: Modularity, Parthood and Evolvability in Metabolic Engineering. Philosophy, Theory, and Practice in Biology. Volume 9, 2017. Michigan State University and Missouri Western State University philosophical biologists propose an increased attention to life’s widespread avail of nested modules as a basis for synthetic formations. From symbiotic bacteria to neighborhood communities, this natural reciprocity appears as most beneficial method.

The premise of biological modularity is an ontological claim that appears to come out of practice. We understand that the biological world is modular because we can manipulate different parts of organisms in ways that would only work if there were discrete parts that were interchangeable. This is the foundation of the BioBrick assembly method widely used in synthetic biology. It is one of a number of methods that allows practitioners to construct and reconstruct biological pathways and devices using DNA libraries of standardized parts with known functions. In this paper, we investigate how the practice of synthetic biology reconfigures biological understanding of the key concepts of modularity and evolvability. We illustrate how this practice approach takes engineering knowledge and uses it to try to understand biological organization by showing how the construction of functional parts and processes can be used in synthetic experimental evolution. We introduce a new approach within synthetic biology that uses the premise of a parts-based ontology together with that of organismal self-organization to optimize orthogonal metabolic pathways in E. coli. We then use this and other examples to help characterize semisynthetic categories of modularity, parthood, and evolvability within the discipline. (Abstract)

Khakzad, Hamed, et al.. A new age in protein design empowered by deep learning. Cell Systems. 14/11, 2023. Université de Lorraine, CNRS, École Polytechnique Fédérale de Lausanne, and Oxford University bioscholars introduce this historic EarthWise advance by way of an integrative merger of personal and computer abilities. See also Becoming fluent in proteins (14/11) and Deep learning and CRISPR-Cas13d ortholog discovery for optimized RNA targeting (14/12) in this journal, and Quantum biological insights into CRISPR-Cas9 sgRNA efficiency from explainable-AI driven feature engineering by Jaclyn Noshay, et al in
Nucleic Acids Research (51/19, 2023.)

Deep learning methods have produced a breakthrough in protein structure prediction, leading to high-quality design models . Deep neural networks can now learn and extract the fundamental features of protein structures, predict how they interact with other biomolecules, and create new effective drugs for treating disease. We review recent developments and technology and provide examples of their performance. (Excerpt)

Knott, Gavin and Jennifer Doudna. CRISPR-Cas Guides the Future of Genetic Engineering. Science. 361/866, 2018. In a special section on Revolutionary Technologies, UC Berkeley geneticists (JD is the co-founder in 2012 of this new era) post a current review and preview as this genomic editorial ability gains a wide manner of monitored human avail and benefit. See also herein Emerging Applications for DNA Writers and Molecular Recorders by Fahim Farzadfard and Timothy Lu (second abstract).

The diversity, modularity, and efficacy of CRISPR-Cas systems are driving a biotechnological revolution. RNA-guided Cas enzymes have been adopted as tools to manipulate the genomes of cultured cells, animals, and plants, accelerating the pace of fundamental research and enabling clinical and agricultural breakthroughs. We describe the basic mechanisms that set the CRISPR-Cas toolkit apart from other programmable gene-editing technologies, highlighting the diverse and naturally evolved systems now functionalized as biotechnologies. We discuss the rapidly evolving landscape of CRISPR-Cas applications, from gene editing to transcriptional regulation, imaging, and diagnostics. Continuing functional dissection and an expanding landscape of applications position CRISPR-Cas tools at the cutting edge of nucleic acid manipulation that is rewriting biology. (GK & JD Abstract)

Natural life is encoded by evolvable, DNA-based memory. Recent advances in dynamic genome-engineering technologies, which we collectively refer to as in vivo DNA writing, have opened new avenues for investigating and engineering biology. This Review surveys these technological advances, outlines their prospects and emerging applications, and discusses the features and current limitations of these technologies for building various genetic circuits for processing and recording information in living cells. (FF & TL Abstract)

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