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A Sourcebook for the Worldwide Discovery of a Creative Organic Universe
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Genesis Vision
Learning Planet
Organic Universe
Earth Life Emerge
Genesis Future
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VIII. Pedia Sapiens: A New Genesis Future

2. Second Genesis: Life Begins Anew via an EarthWise CoCreativity

Srinvasarao, Mohan, et al. Biologically Inspired Far-from-Equilibrium Materials. MRS Bulletin. 44/2, 2019. In this international Materials Research Society main publication, systems chemists MS, Georgia Tech, Germano Iannacchione, Worcester PolyTech, and Atad Parikh, UC Davis introduce a special issue with this title. What is notable today is a fertile integration and avail of these life-like, thermodynamic energies and activities into this older inorganic, metallurgical field. See also herein, Bioinspired Nonequilibrium Search for Novel Materials by Arvind Murugan and Heinrich Jaeger, and Nature’s Functional Nanomaterials by Bodo Wilts, et al.

Traditional approaches to materials synthesis have largely relied on uniform, equilibrated phases leading to static “condensed-matter” structures. Departures from these modes of materials design are pervasive in biology. From the folding of proteins to the reorganization of self-regulating cytoskeletal networks, biological materials reflect a major shift in emphasis from equilibrium thermodynamics to out-of-equilibrium regimes. Here, highly structured dynamical states that are out of equilibrium facilitate the creation of new materials capable of performing life-like functions such as complex and cooperative processes, self-replication, and self-repair, ultimately biological principles of spatiotemporal modes of self-assembly. (Srinvasarao Abstract excerpts)

Searching for materials with improved or novel properties involves an iterative process to successively narrow the gap between some initial starting point and the desired design target. This can be viewed as an optimization problem in a high-dimensional space, often with dozens of material parameters that need to be tuned. To tackle this, the evolutionary process in biology has been a source of inspiration for effective search algorithms. Here, we go beyond black box algorithms and take a broader view of computational evolution strategies. We discuss recent strategies that exploit knowledge about the material configuration statistics and highlight advantages by way of time-varying environments. Throughout, we emphasize that the search strategies themselves can be viewed as a nonequilibrium dynamical process in design space. (Murugan Abstract)

Swiegers, Gerhard, ed.. Bioinspiration and Biomimicry in Chemistry. Boca Raton: CRC Press, 2012. An international authorship considers our novel capabilities to reinvent, foster, and continue the well-being of biosphere and its human members through an intentional, ethical apply of natural bioprinciples. With Forewords by Jean-Marie Lehn, Nobel laureate in Chemistry, and Janine Benyus, whose 1997 Biomimicry initiated the endeavor, chapters evoke self-assembly, functional hierarchies, cooperativity in biochemicals, bionanotechnology, biomineralization, catalysis and so on. A final chapter proposes we ought to make use of life’s complex system dynamics of emergence, autonomous agents, non-equilibrium processes, and more.

As recognition implies information, supramolecular chemistry has brought forward the concept that chemistry is also in information science, information being stored at the molecular level and processed at the supramolecular level. On this basis, supramolecular chemistry is actively exploring systems undergoing self-organization, that, systems capable of generating, spontaneously but in an information-controlled manner, well defined functional architectures by self-assembly from their components, thus behaving as programmed chemical systems. (Lehn, xvii-xviii)

Tack, Drew, et al. Evolving Bacterial Fitness with an Expanded Genetic Code. Nature Scientific Reports. 8/3288, 2018. National Institute for Science and Technology and UT Austin, Center for Systems and Synthetic Biology researchers broach another way that life’s billion year default genomic system can now and henceforth be modified, edited, rewritten by our collaborative worldwise capabilities. What an epochal, auspicious, singular moment this can be as a genesis cosmos begins a new procreative phase by way of our intentional, respectful agency.

Since the fixation of the genetic code, evolution has largely been confined to 20 proteinogenic amino acids. The development of orthogonal translations that allow for the codon-specific incorporation of noncanonical amino acids may provide a means to expand the code, but these translation systems cannot be superimposed on cells that have spent billions of years optimizing their genomes with the canonical code. We have therefore carried out directed evolution experiments with an orthogonal translation system that inserts 3-nitro-L-tyrosine across from amber codons, creating a 21 amino acid genetic code in which the amber stop codon ambiguously encodes either 3-nitro-L-tyrosine or stop. While the evolved lineages had not resolved the ambiguous coding of the amber codon, the improvements in fitness allowed new amber codons to populate protein coding sequences. (Abstract edits)

Overall, our method provides one of the first experiments investigating how a new genetic code is adopted by an organism, and evolved lineages may represent evolutionary intermediates to the adoption of a new amino acid. All lineages overcame the fitness burden associated with 3nY toxicity, but ncAA addiction was required to enforce an active OTS. Further experimentation using the method described here, or similar approaches, will provide insight into the recoding of the genetic code during evolution, and may allow the evolution of biochemically unique organisms. (9)

Toda, Satoshi, et al. Programming Self-Organizing Multicellular Structures with Synthetic Cell-Cell Signaling. Science. 361/156, 2018. UC San Francisco and Stanford University researchers begin to intentionally carry forth nature’s innate capacities to arrange, grow and evolve itself. To wit, a genesis procreation is initiated by this work and many other efforts to read, avail and apply of these dynamic encodings. See also a commentary on this paper, Living Shapes Engineered by Jesse Tordoff and Ron Weiss, in Nature (559/184, 2018).

A common theme in the self-organization of multicellular tissues is the use of cell-cell signaling networks to induce morphological changes. We used the modular synNotch juxtacrine signaling platform to engineer artificial genetic programs in which specific cell-cell contacts induced changes in cadherin cell adhesion. Despite their simplicity, these minimal intercellular programs were sufficient to yield assemblies with hallmarks of natural developmental systems: robust self-organization into multi-domain structures, well-choreographed sequential assembly, cell type divergence, symmetry breaking, and the capacity for regeneration upon injury. These results provide insights into the evolution of multi-cellularity and demonstrate the potential to engineer customized self-organizing tissues or materials. (Abstract)

Voegle, Kilian, et al. Genetically Encoded Membranes for Bottom-Up Biology. ChemSystemsChem. Online August, 2019. Technische Universitat Munchen biophysicists including Friedrich Simmel discuss ways to achieve synthetic self-assembled cellular compartments such as external feeding and fusion, chemical reactions, lipid metabolisms, peptide basal, and more. Graphic illustrations impress with how readily our human capabilities seem suited for such an intelligent, intentional take up and over, in a respectful Gaiaspheric manner, of life’s Earthly and cosmic evolutionary gestation.

The creation of self‐replicating cell‐mimicking systems – artificial cells – is one of the major goals of bottom‐up synthetic biology. An essential aspect is the presence of membranous compartments which can grow and divide in synchrony with the internal dynamics of the cells. In the context of autonomously self‐replicating systems, genetically encoded membranes are of particular interest. Herein, we discuss typical approaches taken for the creation of cell‐like microcompartments via self‐assembly of amphiphiles. We address some of the challenges associated with the generation of phospholipid or peptide‐based membranes via genetic and enzymatic processes. (Abstract)

Artificial living systems are often conceived as compartmentalized chemical systems that are able to grow and divide, replicate and pass on genetic information, which would convey the potential for Darwinian evolution. The creation of such systems necessarily involves the realization and study of out of equilibrium chemical reaction networks that control molecular self‐assembly and self‐organization processes. A key challenge in this context is the encapsulation of the systems and the coupling and coordination of their internal gene replication and metabolism with the dynamics of the compartment resulting in growth and division. (1)

Wang, Lei and Peter Schultz. Expanding the Genetic Code. Angewandte Chemie. 44/1, 2005. An international journal of chemistry and biology, wherein this extensive paper is listed as Protein Science. In a genesis perspective, this work is an example of life through its cerebral human phase beginning to intentionally recreate itself anew.

By removing the limitations imposed by the existing 20 amino acid code, it should be possible to generate proteins and perhaps entire organisms with new or enhanced properties. (35)

Wang, Yueqiang, et al. Genome Writing: Current Progress and Related Applications. Genomics, Proteomics & Bioinformatics. Online February, 2018. Genetic researchers based at the Guangdong Provincial Key Laboratory of Genome Read and Write, Shenzhen and similar labs across China proceed with an especial emphasis on literary and editorial features as they come to distinguish our nascent abilities to embellish and continue life’s genetic narrative.

The ultimate goal of synthetic biology is to build customized cells or organisms to meet specific industrial or medical needs. The most important part of the customized cell is a synthetic genome. Advanced genomic writing technologies are required to build such an artificial genome. Recently, the partially-completed synthetic yeast genome project represents a milestone in this field. In this mini review, we briefly introduce the techniques for de novo genome synthesis and genome editing. Furthermore, we summarize recent research progresses and highlight several applications in the synthetic genome field. Finally, we discuss current challenges and future prospects. (Abstract)

Ward, Thomas. Artificial Enzymes Made to Order: Combination of Computational Design and Directed Evolution. Angewandte Chemie International. 47/7802, 2008. We note this work by a University of Basel chemist as one sample from myriad efforts (note the page number in just this journal) of the phenomenal human take up and over of materiality and its future organic enhancement. An approach employed is known as the “RosettaMatch computational algorithm.” But within our tacit scientific, philosophical, and religious Ptolemaic mindset that denies, indeed cannot even contain, such abilities and purpose, this remains mostly unbeknownst. (see also Winpenny herein)

Whitesides, George. Bioinspiration: Something for Everyone. Interface Focus. 5/4, 2015. In an issue on Bioinspiration of New Technologies, the Harvard University polychemist leads with a copious, procreative survey. At the outset, the concept and approach of drawing upon guidance from the natural wisdom of living systems to intentionally carry forward for a better world is extolled. The paper goes on about soft matter, self-assembly, mesoscale structures, information and energy, reaction networks, covalent synthesis, and so on, much from his own laboratory

Bioinspiration — using phenomena in biology to stimulate research in non-biological science and technology—is a strategy that suggests new areas for research. Beyond its potential to nucleate new ideas, bioinspiration has two other interesting characteristics. It can suggest subjects in research that are relatively simple technically; it can also lead to areas in which results can lead to useful function more directly than some of the more familiar areas now fashionable in chemistry. Bioinspired research thus has the potential to be accessible to laboratories that have limited resources, to offer routes to new and useful function, and to bridge differences in technical and cultural interactions of different geographical regions. (Abstract)

Woolfson, Adrian. Synthetic Life. Daedalus. Winter, 2008. The University of Cambridge physician and CEO of ProteinLogic explores, some eight years of genome sequencing technology after his book Life Without Genes, what august potentials are now within imagination as human ingenuity may take over metazoan creation.

With the basic universal algorithmic machine and synthetic tool in place, humanity will at that point enter a new age of mathematical cartography: the constructional, and principally computational, science of synthetic life will enable the delineation of qualitatively different types of maps than those created by conventional cartographers. These new virtual maps will allow us to catalog the creatures that, like Ebenezer Scrooge’s Christmas ghosts, inhabit both the past, present, and future, and which populate the knotted and twisted mathematical landscapes of the ‘library of all possible creatures’ – a single definitive and exhaustive inventory of all living possibility. (82)

Yang, Kevin, et al. Machine Learning in Protein Enginering. arXiv:1811.10775. Caltech biochemists including Frances Arnold, who co-received the 2018 Nobel Prize in Chemistry for this breakthrough work, explain in tutorial fashion the agile utility and procreative promise of this novel computational method.

Machine learning-guided protein engineering is a new paradigm that enables the optimization of complex protein functions. Machine-learning methods use data to predict protein function without requiring a detailed model of the underlying physics or biological pathways. They accelerate protein engineering by learning from information contained in all measured variants and using it to select variants that are likely to be improved. In this review, we introduce the steps required to collect protein data, train machine-learning models, and use trained models to guide engineering. (Abstract)

Protein engineering seeks to design or discover proteins whose properties, useful for technological, scientific, or medical applications, have not been needed or optimized in nature. We can envision the mapping of protein sequence to a desired function or functions as a “fitness landscape” over the high-dimensional space of possible protein sequences. The fitness represents a protein’s performance: expression level, catalytic activity, or other properties of interest to the protein engineer. The landscape determines the range of properties available to different sequences as well as the ease with which they can be optimized. Protein engineering seeks to identify sequences corresponding to high fitnesses on these landscapes. (1)

Inspired by natural evolution, directed evolution climbs a fitness landscape by accumulating beneficial mutations in an iterative protocol of mutation and selection, as illustrated in Figure 1a. The first step is sequence diversification using techniques such as random mutagenesis, site-saturation mutagenesis, or recombination to generate a library of modified sequences starting from the parent sequence(s). The second step is screening or selection to identify variants with improved properties for the next round of diversification. The steps are repeated until fitness goals are achieved. (2)

Yewdall, Amy, et al. The Hallmarks of Living Systems: Towards Creating Artificial Cells. Interface Focus. 8/5, 2018. In a lead paper for this special issue, Eindhoven University of Technology and Radboud University biochemists including Jan van Hest consider an open frontier of life’s intentional human (re)creation and advance. Five phases are identified: energy transduction, information processing, growth and division, adaptability, and compartmentalization. Along with the first four, the last is seen as most important with regard to membrane complexity, shape, activity, mobility with biomimetic guidance from dimers, cytosols, and other protein and cellular assemblies. As the Abstract notes, this initiative going forward can be seen as a respectful passage to our intended evolitionary continuance. See also an issue introduction The Artificial Cell by its editors Paul Beales, Barbara Ciani and Stephen Mann.

Despite the astonishing diversity and complexity of living systems, they all share five common hallmarks: compartmentalization, growth and division, information processing, energy transduction and adaptability. In this review, we give not only examples of how cells satisfy these requirements for life and the ways in which it is possible to emulate these characteristics in engineered platforms, but also the gaps that remain to be bridged. The bottom-up synthesis of life-like systems continues to be driven forward by the advent of new technologies, by the discovery of biological phenomena through their transplantation to experimentally simpler constructs and by providing insights into one of the oldest questions posed by mankind, the origin of life on Earth. (Abstract)

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