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Biofoundries, factories of genetic products, are core of a Nation’s Synthetic Biology capabilities

Biotechnologies, including synthetic biology, are going to be foundational to the 21st century economy. Synthetic biology is already a multi-billion-dollar industry with broad range of applications in health and medical sector, energy, chemical, environmental, food and agriculture.  By the end of the decade, syn-bio products are predicted to be more than a third of global output of manufacturing industries with $30 trillion value. It is also predicted to transform defense with on-demand bio-production of novel drugs, new materials, food, fuels, sensors, and coatings whatever suits the military’s needs.


Synthetic biology can be defined as engineering approach to biology. And it aims to re-design of natural biological systems for useful purposes as well as design and construction of new biological parts, devices, and systems.


How it does it? Any organism’s sensing, metabolic, and decision-making capabilities depend on unique sequence of DNA bases within their genome. These DNA base pair sequences determine how a cell grows and what goes on inside it or what it produces. By changing an organism’s genome sequence, we can alter these cellular functions, and thereby engineer them.


Let’s now consider some of the technologies and tools of synthetic biology which allow us to engineer biological systems. The first technology is to read DNA or DNA Sequencing, that determines the order of the DNA base pairs or biological instructions that are contained in a strand of DNA.


A difference from the expected sequence of a gene is called a variant or mutation. Comparing healthy and mutated DNA sequences scientists can diagnose different diseases including cancers and deliver more individualized medical care. The rapid speed of modern DNA sequencing technology has enabled sequencing of complete genomes of numerous types and species of life, including microbes, animals, plants, and the human genome.


The second is gene editing technology, and CRISPR has become one of the most popular gene editing tools as it is fast, cheap, and easy to use. It can locate, cut, and replace DNA sequences at specific locations modifying the function of that gene. CRISPR uses modified RNA sequence to recognize DNA sequence in genome and bind to it.  The RNA also binds to the Cas9 enzyme that cuts the DNA at the targeted location. CRISPR enables Gene therapy that add, delete, or correct genetic material to treat a disease.


Next technology is DNA synthesis that is the natural or artificial creation of DNA molecules. We have already seen natural creation, during cell division DNA helix splits itself and each strand of DNA serve as a pattern for duplicating the sequence of bases. This is natural DNA synthesis process is called DNA replication as it self-replicates or make copies of itself.


Traditionally Artificial DNA synthesis techniques were chemical and relied on toxic chemicals and generated hazardous waste. Further it could synthesize short DNA or RNA molecules called oligonucleotides about 200 bases long. Lengthy sequences resulted in more errors and low yield of correct sequences. To assemble even a small gene, scientists used to synthesize it in short segments and then stitch them together. This was also prone to failure and often required multiple attempts. Therefore, traditional DNA synthesis particularly in long strands, was slower and expensive.


New DNA synthesis technique is called Enzymatic DNA synthesis (EDS). This technique employs DNA-synthesizing enzyme found in cells of the immune system. This enzyme can naturally add nucleotides to an existing DNA molecule in water, where DNA is most stable. The improved precision of this technique allow synthesis of DNA strands several thousand bases long or size of a medium-sized gene.


This technology has enabled development of DNA printers. Earlier scientists would search out sections of DNA code in nature, cut the DNA out of existing organisms, and then insert it into a new host organism in a ‘cut-and paste’ process. DNA printers can build artificial DNA from scratch with any DNA code you want. You don’t need to find DNA in nature anymore, you just buy it in from the internet. There are also several commercial companies that provide DNA synthesis services.


Most synthetic biology companies are coming up with artificial DNA codes that can be inserted into microbes, plants or animals forcing them to make industrially useful compounds. The self-replicating property of DNA allow this to be scaled up, to millions of  ‘programmed cell factories’ filling a big industrial vat.


In effect Synthetic biology has turned the bioscience into the future manufacturing paradigm where Companies can engineer and manufacture an infinite quantity of things, cell by cell, from scratch. These bioengineered microorganisms, plants and animals can produce pharmaceuticals, repair defective genes, develop new generations of vaccines, destroy cancer cells, detect toxic chemicals, break down pollutants, and generate hydrogen for the post petroleum economy.


Synthetic biology engineering Design-Build-Test-Learn (DBTL) cycle

Modern  synthetic biology engineering principles recognize the Design-Build-Test-Learn (DBTL) cycle—a loop used recursively to obtain a design that satisfies the desired specifications (e.g., a particular titer, rate, yield or product). The DBTL cycle’s first step is to design (D) a biological system expected to meet the desired outcome. That design is built (B) in the next phase from DNA parts into an appropriate microbial chassis using synthetic biology tools. The next phase involves testing (T) whether the built biological system indeed works as desired in the original design, via a variety of assays: e.g., measurement of production or/and omics (transcriptomics, proteomics, metabolomics) data profiling. It is extremely rare that the first design behaves as desired, and further attempts are typically needed to meet the desired specification. The Learn (L) step leverages the data previously generated to inform the next Design step so as to converge to the desired specification faster than through a random search process.


Design: At the most abstract level, the engineer must determine the arrangement of sensors, actuators, regulatory relationships, and/or enzymatic pathways that will be used to implement a desired behavior. An arrangement is then mapped onto the set of DNA or RNA components that are available, or new components are engineered with the desired specifications while ensuring that there are not conflicts between the components selected in the arrangement. Finally, the components in the arrangement must be linearized, i.e., an order must be determined for genes to appear in the DNA sequence.


The design stage of synthetic biology involves model construction, data mining, the sequence design of synthetic promoters, terminators, enzymes, the metabolic design of pathways and metabolisms, as well as the process design of cell production and fermentation.


With the mass amounts of omics data and biofoundry data available, model construction tools have been developed, including COBRA for constructing biochemical constraint-based models and FluxML for constructing 13C metabolic flux analysis models.


Moreover, PartsGenie is an open-source online software for optimizing synthetic biology parts and bridging design, optimization, application, storage algorithms and databases. MAPPs can be used for mapping reference networks into a graph and search for shortest pathways between two metabolites . novoPathFinder can be used to design pathways based on stoichiometric networks under specific constraints. The robot programming language PR-PR can be used in procedure standardization and sharing among biofoundries, and ease communications between protocols and equipment


Build: The build stage creates organisms modified with the designed nucleic sequence(s). First, the sequence(s) are synthesized (created) or assembled to produce actual physical samples, and the host organisms are cultured (grown) to be ready to receive these sequences. The sequences are then delivered to the organism by one of a variety of protocols.


Both of these stages have a number of issues in yield and quality assurance. Many protocols require a “magic touch” by which some practitioners get reliable results and others frequently build systems with problematic flaws. Next-generation sequencing may help to address issues of quality control, but planning, resourcing, and executing build protocols effectively is still an open and challenging problem.


The build stage of synthetic biology involves DNA assembly, genome editing, genome regulation, and automation. Recently developed automation platforms have substantially accelerated our capabilities in reconstructing engineered strains, but automation requires development of technologies that are simple, modular, multiplexable, and efficient.


Automation-friendly DNA assembly tools include the methyltransferase-assisted BioBrick that uses a site-specific DNA methyltransferase together with endonucleases and allows consecutive constructions without gel purification. Twin-Primer Assembly (TPA) that is an enzyme free in vitro DNA assembly method and could assemble 10-fragments with no sensitivity to junction errors and GC contents, Gibson and NEBuilder assembly that is an homology-based in vitro method and is able to clone large DNA parts with high GC contents, Ligase Cycling Reaction (LCR) that employs bridging oligonucleotides to provide overlaps and allows automated assembly in consecutive steps, and yeast in vivo assembly that relies on the high homology recombination efficiency of S. cerevisiae


Many of these DNA assembly tools have already been utilized in automation. For example, Q-metric has been developed to standardizes automated DNA assembly methods, and computes suitable assembly robotic practices, metrics and protocols based on output, cost and time. Amyris Inc. managed to use transformation-associated recombination (TAR)-based biofoundries to assembly 1500 DNA constructs per week with fidelities over 90%.


Efficient and multiplexable genome engineering tools include mutiplexed genome disruption, integration, base editing, SCRaMbLE, automation. For example, Zhang et al. reported the efficient GTR-CRISPR system that managed to simultaneously disrupt six genes in three days and improve yeast production of free fatty acid by 30-fold in 10 days


Test: Finally, the behavior of the newly constructed organism or organisms is assayed (measured) to determine how well it corresponds with the original specification, and to help debug misbehavior such that the next iteration of the design can be closer to the desired behavior.


Here, one of the biggest challenges is in relating assay data to the original specification: many assays produce data in great volume, but the mapping back to the original specification is often qualitative or relative. Likewise, it is often not clear how to relate the observed behavior to predictive models that can provide principled guidance in how to adjust the design phase in order to produce improved results.


The test stage of synthetic biology involves cell culture, cell sorting and cell analysis, and automation has also posed special requirements on the test workflow.


Learn: The Learn phase of the DBTL cycle has traditionally been the most weakly supported and developed, despite its critical importance to accelerate the full cycle. The reasons are multiple, although their relative importance is not entirely clear. Arguably, the main drivers of the lack of emphasis on the L phase are: the lack of predictive power for biological systems behavior, the reproducibility problems plaguing biological experiments, and the traditionally moderate emphasis on mathematical training for synthetic biologists.


The learn stage of synthetic biology involves systems biology analysis and machine learning. Automation platforms can generate massive amount of data, that need to be analyzed and integrated back to the design stage to refine the models and guide the following iterative DBTL cycles through standardized procedures.


Bioengineering processes – pipetting very small quantities of liquids, introducing genetic material into cells, screening engineered micro-organisms, etc. – have always required a high level of precision, meaning they were very time-consuming



The ability to exploit this amazing building capacity is now being accelerated by the new field of engineering biology, which applies engineering principles such as standardization, modularization and robustness to the genetic engineering of complex living systems for specific applications. New robotic workflows and technology platforms are being established, resulting in different types of laboratories focused solely on accelerating and prototyping biological designs for engineering-biology applications. Such facilities today are called biofoundries, and they are being rapidly established worldwide.


By automating and systematizing these laborious processes, biofoundries significantly accelerate and improve the accuracy of R&I cycles, from the engineering of a new strain of yeast to production and verification of the result. Most importantly, they also provide the opportunity to design and test thousands of microbial prototypes at the same time. A robotic arm transfers small plastic trays with thousands of tiny wells and as many samples from one instrument to another. After creating genetic variation across hundreds of thousands of variants of yeast and bacterial strains, all these options can be assessed simultaneously using automated protocols and data analysis software in order to select the best models.


A typical biofoundry would rely heavily on automation, performing common and repetitive tasks in a high-throughput manner, dropping the cost and increasing efficiency. Ideally, all the work can be done locally at the biofoundry with minimal work input from a user. Starting from a certain amount of genetic designs, the foundry personnel should synthesize or order the DNA, make the constructs, transform the organism in question, select the correctly engineered strains, and evaluate the behavior and characteristics of each construct (using reporter systems, assays, metabolite detection, or some other custom-made techniques).


A biofoundry allows scientists to program cells on a high-throughput scale, opening up new development opportunities for the yeast and fermentation industry. They constitute a more efficient use of equipment, as they can in theory work 24/7 with minimal input from the personnel.


To accelerate the DBTL cycle, integrated infrastructure with strong automation and computer-aided design capabilities – biofoundries – were established in multiple research centers around the globe. Today, twenty-six prestigious academic institutions, including Harvard University and Imperial College London, have set up biofoundries.


The infrastructure within current biofoundries varies, but is based primarily around high-throughput liquid-handling robots that allow millions of computer-controlled liquid manipulations, automating many of the processes needed to genetically engineer living systems. Coupled to this are also high-throughput biological measurement instruments that provide the data needed to inform the biodesign process. These biodesign and prototyping facilities are analogous to those developed for computers in the 1970s that led to the ICT revolution and as such are key to a future global biomanufacturing capability and the prospects for a sustainable bioeconomy.


Uniquely, biofoundries can prototype engineered microbes to convert waste from one industrial process into an input for another, opening doors for sustainable manufacturing difficult to reach without biology. Such engineered microbes can then, for example, convert methane gas released from flues into protein-rich biomass for animal feed in adjacent biorefinery facilities. Another example is the highly efficient production of fatty acids and diesel from glucose by metabolically engineered bacterium, which opens up the possibility of not relying on plant oil or animal fat to produce biodiesel.


Development of such efficient microbial cell factories can be streamlined within biofoundries. Other applications include microbial cell factories producing commodity chemicals, bioplastics, protein-based foods and antibiotics to name but a few, as part of a transition to more sustainable bio-based manufacturing systems using engineered cells. Applications also extend to low-cost bio-based sensors and diagnostics that can be rapidly prototyped and optimized before deployment. These include new environmental biosensors for detecting water contamination like arsenic and lead, as well as disease, in resource-poor environments.


Other healthcare applications include novel vaccine prototyping, the development of new cell-based therapies for cancer treatment and the engineering of living probiotic drug delivery and disease detection systems. For instance, our body’s communities of microbes offer new therapeutic interventions where, for example, communities within our gut can be engineered to maximize nutrient absorption and disease detection, while regulating the intimate relationship between gut, mental and immunological health. All of these applications require engineered cells or communities of engineered microbes that can be designed, prototyped and developed within biofoundries.


Biofoundries have arisen at numerous sites globally with the intention of positively impacting society and enabling economic growth and stability. A globally networked system of biofoundries will form a collaborative community to help ensure that biofoundries are responsible, open, transparent and safe in their activities.

Global Biofoundry Alliance (GBA)

A global alliance was formed in 2019 to promote open source development of both software and hardware, and sharing of protocols, best practices, and standards. The vision is to enable rapid prototyping of engineered biological systems in an agile and reliable manner.


The GBA provides an opportunity for knowledge-sharing and open technology development to increase discovery, but also for developing common standards and reference materials. Each biofoundry is unique and typically has a degree of specialization in the cell type and process it employs. Working together also enables the expansion of the cell type portfolio to best ensure an appropriate “chassis” (used to define a cell for a specific application) is identifiable with an existing knowledge base on which to build bespoke solutions. Familiarity with the expertise offered at each facility highlights those best skilled for addressing particular challenges across the diverse sectors of medicine, materials, chemicals, fuels, food and the environment. A shared understanding of expertise and capabilities offered will also open the door to the possibility of unique international collaborations to develop chemicals, materials and healthcare applications of global importance.


Among the 28 public foundries of the Alliance, 8 are in Asia, with 4 in China, 2 in South Korea and 1 each in Japan and Singapore. The biofoundries, such as the London and Singapore biofoundries, provide cost-effective access to high-cost equipment and small-scale prototype evaluation to other academic laboratories and companies.


The unification of the global biofoundries into an open-technology alliance also offers scalability for rapid progress in large projects beyond the capability or capacity of any single entity. The frequency of this requirement is likely to increase as costs for DNA synthesis decline, and researchers adopt even more ambitious goals in the face of ever-more complex challenges. A networked alliance of compatible biofoundries enables streamlined exchange of people and expertise to collaborate in addressing these challenges. As collaborations are best suited in pre-existing relationships, the alliance offers the opportunity for such an extended network of individuals to develop such relationships in the event a collaboration of global importance is required.


Establishment of public biofoundries requires substantial public investment, time, and trained personnel and thus, they are typically found in nations, particularly those in Asia, with a national synthetic biology program and a well-defined bioeconomy roadmap. Biofoundries can significantly accelerate the engineering of biological systems by providing higher reproducibility and throughput and ease of sharing of standardized protocols.


As other nations, such as India, formulate their bioeconomy strategies, biofoundries have the potential to be at the core of a nation’s synthetic biology capabilities. The vital role that biofoundries play in synthetic biology is evident from some of the success stories from the existing biofoundries. For instance, in the eminent “10 molecules in 90 days” pressure test taken on by the Foundry at the Broad Institute, six of the challenged molecules or their close relatives were successfully produced within the given time constraint.


In another study, the biofoundry at the University of Manchester produced 17 potential material monomers in 85 days. The London Biofoundry contributed to the rapid development and validation of automated SARS-CoV-2 clinical diagnostics.


Apart from a demonstration of capabilities, such drills also identified key bottlenecks in further accelerating the engineering process. These include gaps in computer-aided design tools, time needed for DNA synthesis, and complicated analytical methods for product characterization and measurement.


One potential scenario where global collaboration might be crucial would be an unforeseen global pandemic. Biofoundries could then collaborate for large-scale vaccine production and the Alliance could be harnessed to help. It also offers unparalleled training and sharing opportunities, including exchange programs, open technology development and collaborative testing of common protocols. These facilities are now training young researchers in technologies that will dominate the research landscape and underpin biomanufacturing in the years to come.


While academic research continues to improve the efficiency and reliability of the engineering methods and platforms, there are already a few commercial enterprises with business models centered upon developing customized enzymes or microbial hosts, such as the US-based Ginkgo Bioworks and Zymergen. Such platform companies not only pioneered the technology translation, but also contributed towards advancing process automation, data curation, and production scale-up. With strong in-house capabilities of discovery, engineering and production, they will be the powerhouses in driving synthetic biology applications in a variety of sectors.


Lab platform Opentrons

The Opentrons platform currently offers life science companies and hospitals access to three core services. The first is its original offering: the OT-2 lab robot, a system with a starting price of $5,000 that can be customized to each lab’s needs to automate entire workflows, eliminating the need for manual pipetting.

Biopharma labs can also access the Opentrons biofoundry to perform genome-scale cell engineering processes to discover and develop new therapeutics. The biofoundry was developed through Opentrons’ synthetic biology-focused subsidiary Neochromosome, with tech support from the recently acquired Zenith AI.

Finally, thanks to another of its subsidiaries, Pandemic Response Lab, hospitals and health systems can outsource their molecular diagnostic testing needs to Opentrons’ own labs. (The Pandemic Response Lab was launched last summer with an initial purpose of helping New York City mitigate the then-skyrocketing demand for fast, affordable COVID-19 testing.)

“Biology opens the door to solve many of humanity’s grand challenges. For far too long, scientists and clinicians have been locked in by slow, expensive and overly complex lab solutions that underpin their work,” said CEO Jon Brennan-Badal. “Opentrons’ platform provides the key to unlock their potential. We are enabling more R&D, more testing, more biology to unleash innovation in life sciences and healthcare.”


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About Rajesh Uppal

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