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

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

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)

Knox, Margaret. The Genie Gene. Scientific American. December, 2014. A popular report on the discovery by Jennifer Doudna, UC Berkeley and Emmanuelle Carpentier, Umea University, Sweden of a revolutionary way to easily alter and edit genetic material. Known as CRISPR for “clustered, regularly interspaced, short palindromic repeats,” it mimics how bacteria employ immune defenses. The innovative research has won prizes, large grants, and is seen as a breakthrough medical advance.

Kösoglu-Kind,, Busra, et al.. A biological sequence comparison algorithm using quantum computers. arXiv:2303.13608. This entry by University of Applied Sciences in Economics and Management, Dusseldorf, IBM, Armonk, USA, European Organization for Nuclear Research (CERN), Geneva and IBM, I München, Germany computer scientists is an example of the latest frontiers of our Earthuman endeavors to provide rapid, whole scale genome sequences, and to gain new, beneficial abilities going forward.

Genetic information is encoded in a linear sequence of nucleotides, where mutations refer to changes in the DNA or RNA nucleotide sequence. Thus careful monitoring of virulence-enhancing mutations is essential. However, vast classical computing power is required to analyze large genetic sequences. Inspired by human perception of vision and pixel perception of images on quantum computers, we leverage these techniques to implement a pairwise sequence analysis. We present a method to display and analyze the similarity between two genome sequences on a quantum computer where a similarity score is calculated to determine the similarity between nucleotides. (Excerpt)

Krane, Dan and Michael Raymer. Fundamental Concepts of Bioinformatics. San Francisco: Benjamin Cummings, 2003. A general introductory text for this merger of computers and biology.

Lajoie, Marc, et al. Overcoming Challenges in Engineering the Genetic Code. Journal of Molecular Biology. 428/5B, 2016. Harvard Medical School and Yale University systems geneticists including George Church consider issues and concerns such as do we really know what we are doing, how and why to carefully proceed, and so on. And as someone who had a day job for decades as an engineer, this term is quite inapt for such genomic, biological, organismic mediations going forward. What better word might serve our own “evolutionary” narrative so as to begin, as we are meant to do, a new genesis recreation?

Withstanding 3.5 billion years of genetic drift, the canonical genetic code remains such a fundamental foundation for the complexity of life that it is highly conserved across all three phylogenetic domains. Genome engineering technologies are now making it possible to rationally change the genetic code, offering resistance to viruses, genetic isolation from horizontal gene transfer, and prevention of environmental escape by genetically modified organisms. We discuss the biochemical, genetic, and technological challenges that must be overcome in order to engineer the genetic code. (Abstract)

Lale, Rahmi, et al. A Universal Approach to Gene Expression Engineering. Synthetic Biology. 7/1, 2022. Twelve Norwegian University of Science and Technology, Trondheim and Bielefeld University Germany biochemists come up with a versatile method to parse genomic processes, as they gain a wider influence, so to better analyze and enhance. Thus a global intellect proceeds apace to intentionally continue and advance life’s grand genesis.

In this study, we provide a universal approach to Gene Expression Engineering (GeneEE) for creating artificial expression systems which creates artificial 5ʹ regulatory sequences (ARES). The ARES recruit RNA polymerase, related sigma factors and ribosomal proteins that result in a wide range of expression levels. To showcase the universality of the approach, we demonstrate that 200-nucleotide (nt)-long DNA with random composition can be used to generate functional expression systems in six bacterial species. (Abstract excerpt)

We demonstrate that using the GeneEE approach, artificial gene expression systems can be created in all seven investigated microbes utilizing six markers/reporters. The GeneEE approach relies on nature’s ability to detect functional sequences among a set of DNA with random DNA composition. In this aspect, the approach can be applied in any HoI, making it a universal and versatile strategy for creating artificial gene expres-sion systems capable of functionally expressing a wide range of CDSs in a variety of host microorganisms. (11)

Lau, Yu Heng, et al. Large-Scale Recoding of a Bacterial Genome by Iterative Recombineering of Synthetic DNA. Nucleic Acids Research. 45/11, 2017. As the quote notes, a 13 person team from colleges and companies including Jeffrey Way, Pamela Silver, and Elena Schafer, move beyond gene sequencing onto initial surveys of how to edit, reconceive, and expand the generative capacities of nucleotide systems. But “engineering” is an inappropriate, off-putting term. Rather as humankinder altogether begins to engage, decipher, and modify evolution’s original genetic literacy, as it seems we are meant to do, a better image might be as creative co-authors and curators as we learn to read and write this natural language.

The ability to rewrite large stretches of genomic DNA enables the creation of new organisms with customized functions. However, few methods currently exist for accumulating such widespread genomic changes in a single organism. In this study, we demonstrate a rapid approach for rewriting bacterial genomes with modified synthetic DNA. (Abstract) The next widely anticipated breakthrough in genetic engineering is the ability to rapidly rewrite the genomes of industrially relevant microbes, plants, and animals. Rewriting entire genomes will deepen our understanding of the genetic code and dramatically transform human health, food and energy production, and our environment. A major challenge identified by the Genome Project-Write consortium is the efficiency of building and testing large modified genomes. (1)

Lawson, Christopher, et al. Common Principles and Best Practices for Engineering Microbiomes. Nature Reviews Microbiology. 17/725, 2019. In a Tractability and Translation section, a thirteen member team from the Universities of Wisconsin, Montana, Tennessee, Minnesota, Purdue, UC Santa Barbara, Michigan, Delft, and Lawrence Berkeley Labs scope out procedures as our composite human intellect begins to manage and make anew our microbial inhabitants. Some are symbiotic, but others are viral invasive. Thus, an historic phase of palliative and beneficial apply, with all due respects, is in commencement. See also Scientists’ Warning to Humanity: Microorganisms and Climate Change by Ricardo Cavicchioli, et al in this journal (June 18, 2019).

In a Tractability and Translation section, a thirteen member team from the Universities of Wisconsin, Montana, Tennessee, Minnesota, Purdue, UC Santa Barbara, Michigan, Delft, and Lawrence Berkeley Labs scope out procedures as our composite human intellect begins to manage and make anew our microbial inhabitants. Some are symbiotic, but others are viral invasive. Thus, an historic phase of palliative and beneficial apply, with all due respects, is in commencement. See also Scientists’ Warning to Humanity: Microorganisms and Climate Change by Ricardo Cavicchioli, et al in this journal (June 18, 2019).

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