AI-generated summary
This text provides an overview of key concepts and technologies in synthetic biology and biomanufacturing, highlighting the integration of artificial intelligence (AI) and automation in biological research and production. AI-assisted protein design enables the creation or prediction of proteins with specific functions, supported by advanced biological foundational models trained on extensive data. The Design-Build-Test-Learn (DBTL) cycle, a core iterative process in synthetic biology, is increasingly automated through robotics and software in biofoundries, enhancing speed, reducing costs, and improving reproducibility. Digital twin biological models simulate biological systems computationally, aiding experimental validation, while DNA synthesis and genome writing facilitate the creation of designed genetic sequences and entire genomes.
The text also covers critical tools and methods such as CRISPR-Cas for precise gene editing, metabolic engineering to optimize biochemical pathways, and cell chassis as platforms for genetic modification. Concepts like codon optimization improve protein production efficiency, and cell-free systems offer simplified biological production without living cells, reducing complexity and risks. Biomanufacturing relies on bioreactors to scale production, with strategies like scale-up and scale-out to maintain economic viability. Additionally, regulatory frameworks such as Good Manufacturing Practices (GMP) ensure quality and safety. The discussion touches on biosecurity concerns, gene drives, and genetically modified organisms (GMOs), emphasizing ethical considerations and the importance of data interoperability across platforms. Overall, the text outlines the multidisciplinary, technology-driven landscape of modern synthetic biology and its industrial applications.
Glossary of Synthetic Biology, as support for the report https://www.fundacionbankinter.org/en/ftf-informes/synthetic-biology/
AI-Assisted Protein Design: The use of artificial intelligence to generate or predict new proteins with specific functions.
Biofoundry: Automated facility that integrates robotics, software, and biology to accelerate and scale the DBTL cycle.
Biological Data Interoperability: The ability to integrate, share, and reuse experimental data across platforms and organizations.
Biological Foundational Models: Advanced artificial intelligence models trained on large volumes of biological data to predict molecular structures or functions.
Biosecurity: A set of measures aimed at preventing the improper, malicious or accidental use of biological technologies.
Biomanufacturing: Industrial production based on living organisms or biological systems, usually in bioreactors.
Bioreactor: Industrial equipment where microorganisms or modified cells are grown to produce compounds at scale.
Cell Chassis: A base organism used as a platform to introduce genetic modifications and produce a specific molecule.
Cell-Free Systems: Biological production platforms that do not use complete living cells, reducing complexity and biological risks.
Codon Optimization: Modification of the genetic sequence to improve the production efficiency of a protein in a specific organism.
CRISPR-Cas: A gene-editing system inspired by bacterial defense mechanisms. It allows you to locate a specific DNA sequence and cut it precisely to deactivate genes, correct mutations or introduce new genetic instructions.
Its impact has been enormous because it has made genome editing faster, cheaper, and more accessible. Still, CRISPR works best on small changes or one-off modifications. Inserting long strands of DNA is still difficult: the fragment must enter the right place, integrate without errors, remain stable, and express the desired function within a living cell.
DBTL (Design–Build–Test–Learn) cycle: Core iterative cycle in synthetic biology: designing a solution → building it genetically → testing it → learning from the results to optimize the next iteration.
DBTL Automation: Use of robotics, software, and automated analysis to execute the Design-Build-Test-Learn cycle with greater speed, lower cost, and less experimental variability.
Digital Twin Biological: Computational model that simulates the behavior of a biological system before its experimental validation.
DNA Synthesis: Artificial production of digitally designed DNA sequences.
Genome Writing: The synthesis and assembly of large genetic fragments or digitally designed complete genomes.
Gene Expression: The process by which the information contained in a gene is converted into a functional protein.
Gene Drive: A genetic system designed to spread rapidly in natural populations. A sensitive concept from an ethical and regulatory point of view.
Gene Promoter: A DNA sequence that regulates when and how much a gene is expressed.
Genetically Modified Organism (GMO): An organism whose genetic material has been altered by genetic engineering.
GMP (Good Manufacturing Practices): Regulatory standards that guarantee quality, safety and consistency in pharmaceutical and biotechnological production.
Knock-in: Specific insertion of a gene into the genome of an organism.
Knock-out: Specific deletion or deactivation of a gene to alter a biological function.
Metabolic Engineering: Systematic modification of metabolic pathways to increase yield or introduce new productive functions.
Metabolic Pathway: A sequence of biochemical reactions within a cell that converts a substrate into a specific product.
Precision Fermentation: The use of genetically engineered microorganisms to produce specific proteins or compounds with a high degree of control.
Productivity: The rate at which a biological system produces the desired compound. Key indicator of industrial competitiveness.
Scale-out: A strategy of increasing production by replicating multiple modular units rather than increasing the size of a single bioreactor.
Scale-up: The process of moving a biological solution from the laboratory to industrial production while maintaining performance and economic viability.
Titer: Concentration of the desired product within a bioreactor. Key indicator of economic viability.
Yield: Amount of product obtained per unit of raw material used.
