Building Biology Brick by Brick: Synthetic Biology's LEGO Approach for Startups

In a recent episode of talk is biotech! with Guru Singh, founder and CEO of Scispot, an illuminating metaphor emerged: synthetic biology is like building with LEGO. Singh, who leads Scispot (often described as "the best tech stack for biotech"), has built an AI-driven platform that helps over 100 life science startups manage and supercharge their R&D data. During his conversation with Kevin Chen, CEO and co-founder of Hyasynth Bio, Singh explored how today's biotech entrepreneurs are engineering living systems in a modular way.

Chen, whose company specializes in producing cannabinoids through engineered microorganisms, likened the process of designing a microorganism to customizing a car or a LEGO set: first pick a "chassis" (a base organism such as yeast or bacteria) and then snap in "BioBricks" (standardized genetic parts) to create new functions. This article unpacks that LEGO-like approach to synthetic biology, shows how startups like Hyasynth Bio apply it in the real world, and highlights how AI-powered tools like Scispot's platform can accelerate these efforts for early-stage founders.

Synthetic Biology as a LEGO Game: The Basics

Synthetic biology is a revolutionary field that treats living cells almost like programmable hardware. Instead of circuits and code, the components are DNA and genes. The central idea is modularity: much as LEGO pieces can be mixed and matched to build complex structures, biological parts can be assembled to engineer organisms with novel capabilities.

In practice, synthetic biology often involves inserting a dozen or more genes into microbes to make them produce drugs, chemicals, or biofuels they normally would not create. This engineering mindset contrasts with traditional genetic engineering in its emphasis on standardized parts and design principles, making synthetic biology more systematic and predictable.

BioBricks: The Standardized Building Blocks

The term BioBricks refers to standardized DNA sequences (often encoding proteins or regulatory elements) that behave as modular building blocks. Just as LEGO bricks have uniform connectors, BioBricks are designed to fit together seamlessly in various combinations. The concept was first introduced in 2003 at MIT by Tom Knight, laying the groundwork for the Registry of Standard Biological Parts.

Today, thousands of such parts exist, including promoters (DNA switches controlling gene activity), enzymes, sensors, and more. All are catalogued so that bioengineers can plug-and-play to construct new biological "circuits." In essence, BioBricks are to synthetic biology what standardized components are to electronics: they enable abstraction and reuse.

A BioBrick is essentially a man-made elementary DNA sequence that can be readily assembled into more complex biological systems. These pieces share common interface sequences, allowing researchers to snap them together inside a host cell to achieve a desired function. This standardization was a key innovation of early synthetic biology, enabling a true plug-and-play approach to biological engineering.

Chassis Organisms: The Foundation Platforms

In the LEGO analogy, the chassis is the base platform onto which parts are added, similar to a car frame or a blank LEGO board. In synthetic biology, a chassis is the living cell or organism that houses the engineered genetic circuit. Common chassis choices are well-studied, laboratory-friendly microbes.

Escherichia coli bacteria and baker's yeast (Saccharomyces cerevisiae) are two of the most popular chassis organisms used by bio-startups and academic labs alike. Each chassis has unique strengths, so selecting the right one is a strategic decision much like choosing the base for a LEGO project:

E. coli: The Synthetic Biology Workhorse

E. coli is often considered the workhorse of synthetic biology. It grows extremely fast, has a "plastic" (versatile) metabolism, and is one of the best-characterized organisms on Earth. Decades of research mean there's a huge toolkit of genetic parts and methods available for E. coli. It's also relatively easy to culture and generally harmless in lab strains.

However, as a simple prokaryote, E. coli cannot perform certain complex protein modifications (like glycosylation) that more complex cells can. This can be a limitation if the engineered product is a large protein or needs eukaryotic-style processing.

Yeast: The Eukaryotic Powerhouse

Yeast (such as S. cerevisiae) is a single-celled fungus, a simple eukaryote that makes it more complex than bacteria but still easy to grow. Yeasts have been used for brewing and baking for millennia, so scientists know they are robust and safe. They don't grow as rapidly as bacteria, but they offer the ability to properly fold and modify more complex proteins, which is crucial for certain biotechnologies.

Yeast cells are appealing for synthetic biology: quick to culture, non-toxic, and robust enough to be freeze-dried. Yeast's eukaryotic machinery allows it to produce molecules that bacteria might struggle with. For example, S. cerevisiae can perform some of the chemical steps and folding needed for plant or mammalian molecules.

Advanced Chassis Options

Other chassis options include mammalian cells (such as Chinese Hamster Ovary cells) used when human-like protein processing is needed, or even plant cells and algae for certain applications. But for many early-stage startups, working with a fast-growing microbe chassis is the most practical route to get a prototype up and running.

Chassis Organism	Key Advantages	Key Limitations	Example Uses
E. coli (bacterium)	Very fast growth (20-30 min generation time); huge library of genetic tools available; simple to engineer; well-characterized physiology; lab strains are safe	Cannot perform complex post-translational modifications; doesn't thrive at extreme pH or temperature; limited ability to secrete proteins	Production of insulin and other proteins; industrial enzymes; biofuel precursors
S. cerevisiae (yeast)	Eukaryotic cell can fold and modify complex proteins; tolerates diverse growth conditions; robust and safe; relatively fast-growing for a eukaryote; extensive brewing knowledge available	Slower growth than bacteria; slightly more demanding to genetically modify; can produce ethanol as byproduct	Production of complex chemicals like anti-malarial compounds; cannabinoid biosynthesis; recombinant proteins requiring folding
CHO or HEK mammalian cells	Human-like cellular machinery for proper protein folding and glycosylation; essential for biopharmaceuticals	Very slow growth; expensive culture conditions; difficult to genetically manipulate; not suitable for small molecules	Manufacturing therapeutic antibodies and complex human proteins

Many other chassis exist, from Bacillus subtilis bacteria for secreting enzymes to cell-free systems using extracted enzymes in test tubes. However, early startups typically start with well-proven hosts like E. coli or yeast before exploring more exotic chassis options.

Snapping Genetic "Bricks" Together

Once a chassis is selected, engineers get to work adding the BioBricks, the modular genetic parts that confer new functions. These parts can be thought of as the "features" or modules one adds to a base model. In the LEGO analogy, if the chassis is a car frame, the BioBricks are the engine, wheels, and accessories you plug into it to create a fully functional vehicle.

In biology, a BioBrick might be:

• A gene coding for an enzyme that produces a desired chemical

• A promoter sequence that acts as an on/off switch to control when a gene is active

• A reporter like Green Fluorescent Protein that lights up to signal a successful assembly

• A regulatory circuit that senses some condition (such as the presence of a sugar or toxin) and triggers a response

  
  

Each piece has a defined role, and critically, they have standardized interfaces so that one can be connected to another without re-engineering every time. BioBricks in the registry adhere to common assembly standards (similar to how USB ports plug into any brand of computer). This standardization allows for a true plug-and-play approach.

As described in synthetic biology literature, BioBricks are standard synthetic DNA sequences of known structure and function that can be used as LEGO-like building blocks, which can be combined to yield new biological systems when inserted into a chassis. By mixing and matching genetic parts, scientists can design a biological machine to order.

The Iterative Design Process

Building with BioBricks is an iterative, experimental process. Researchers may try multiple combinations of parts and fine-tune their "DNA code" through cycles of design-build-test. Modern techniques like gene synthesis (ordering DNA sequences from vendors) and high-throughput cloning have greatly accelerated this prototyping cycle. What used to take months in the early 2000s, manually splicing DNA fragments, can now sometimes be accomplished in weeks or even days, thanks to automation and standardized parts.

Case Study: Brewing Cannabinoids in Yeast - Hyasynth Bio's LEGO Moment

How do these abstract concepts translate into a real startup's journey? Hyasynth Bio, co-founded by Kevin Chen, offers a compelling example. The company's mission is to produce cannabinoids (the active compounds found in cannabis, like CBD and THC) without farming any cannabis plants. Instead of growing acres of crops, Hyasynth engineers microbes to biosynthesize these valuable molecules in fermenters, essentially brewing cannabinoids in yeast like one would brew beer.

Choosing the Right Chassis

Chen's team started with selecting a chassis: they chose baker's yeast (S. cerevisiae) as their living factory. Yeast was an appropriate choice because producing cannabinoids is a complex, multi-step biochemical process typically performed by cannabis plants (which are eukaryotes). Yeast, being a eukaryotic microorganism, has cellular machinery more similar to plants than bacteria do.

During the talk is biotech! podcast, Chen explained that they "took genes from cannabis plants and put them into yeast," literally transferring the genetic instructions for making cannabinoids into the yeast's genome. Those genes serve as the BioBricks in this case: each gene encodes an enzyme that performs one step in the cannabinoid production pathway.

Engineering Cellular Factories

By loading brewer's yeast with a comprehensive suite of cannabis plant genes, the team effectively transformed yeast cells into tiny cannabinoid factories. The result is remarkable: yeast that can produce CBD (cannabidiol), THC (tetrahydrocannabinol), and even rarer cannabinoids, entirely through fermentation.

According to company announcements, Hyasynth's proprietary yeast strains and enzymes can generate pure cannabinoids (not synthetic versions) without relying on cannabis plants, including major compounds like CBD and THC. The company has achieved scalable production of CBD and is working on rare cannabinoids that are found only in trace amounts in plants.

These rare molecules are of particular interest because some have potential medical benefits but would be prohibitively expensive to extract from plants. By engineering yeast, Hyasynth can produce them in a controlled, sustainable way, opening up new possibilities for research and therapeutic applications.

Standing on the Shoulders of Giants

This approach mirrors a broader trend in synthetic biology: using microbes to produce valuable compounds that traditionally come from agriculture or petroleum. Years ago, Jay Keasling's lab similarly engineered yeast with a dozen genes (some from sweet wormwood plants) to produce the antimalarial drug precursor artemisinic acid, a breakthrough that became one of synthetic biology's first major success stories.

Even earlier, the biotech industry's "golden molecule," human insulin, was first produced by inserting the insulin gene into bacteria, turning E. coli into a factory for life-saving medicine. Hyasynth Bio is effectively building on these pioneering efforts, applying the LEGO-like assembly of genes into a yeast chassis to create an entirely new supply chain for cannabinoids.

Startup Advantages

From a startup perspective, the implications are transformative. By leveraging synthetic biology, a small company can bio-manufacture compounds that previously required large farms or complex extractions. This can mean faster development cycles, lower environmental impact, and the ability to innovate on molecules (creating analogs or improved variants) rather than being limited to what nature produces.

Chen's venture, for example, can explore novel cannabinoids that plants make only in minute quantities by tweaking which enzyme "bricks" they include or modifying the pathways. This level of customization would be nearly impossible through conventional cultivation. It's the biotech equivalent of customizing a LEGO creation beyond any standard kit.

The AI Edge: Tools Accelerating Synthetic Bio Innovation

While synthetic biology provides the blueprint to build life forms "brick by brick," executing this vision in a laboratory still involves massive data tracking, experimentation, and complex workflows. This is where modern digital tools, especially those leveraging artificial intelligence, become game-changers for biotech founders.

Scispot: An Operating System for Biotech Labs

Guru Singh's startup Scispot exemplifies a platform designed to support the biological "building" process with an integrated, AI-driven approach. Singh, who brings extensive experience in biotech data management, founded Scispot to address the fragmented nature of laboratory operations. In essence, Scispot offers an operating system for the lab, a comprehensive software stack that combines electronic lab notebook (ELN) functionality, data management, workflow automation, and AI analytics.

For resource-strapped early-stage biotech companies, using such a platform can drastically increase efficiency. Instead of juggling spreadsheets, paper notebooks, and ad-hoc analysis tools, founders can unify all their experimental data and protocols on one digital hub. Scispot's system connects across instruments and cloud databases, turning fragmented lab operations into a connected data pipeline.

Notably, the platform is built to be AI-ready: the data captured is formatted and stored in ways that machine learning models (or "LabGPT"-style assistants) can readily utilize. This forward-thinking approach ensures that startups can leverage AI capabilities from day one rather than retrofitting their data systems later.

Concrete AI Applications in Synthetic Biology

Here are several specific ways AI and digital platforms are boosting synthetic biology R&D:

Automated Data Analysis

Rather than manually analyzing experiment results, scientists can let AI sift through data to spot trends or anomalies. Scispot's AI integration enables on-demand insights such as trend analysis across experiments and anomaly detection in large datasets. In a synthetic biology project, this might mean quickly identifying which genetic construct out of dozens yielded the highest compound production, or flagging an outlier fermentation run that suggests contamination issues.

Natural-Language Query and Knowledge Capture

Modern lab platforms increasingly allow researchers to query their data or protocols in plain English. Scispot's Scibot assistant, for example, lets users ask questions about their lab's data and instantly retrieve answers or summaries. A founder could literally type, "Which yeast strain had the highest CBD titer in the past month?" and get an immediate answer if the data is properly captured in the system. This saves valuable time and ensures institutional knowledge isn't lost. It's like having an AI librarian for your lab notebook, one that never forgets a result.

Workflow Automation and Error Reduction

By integrating inventory management, protocols, and instruments, AI-driven systems can auto-schedule tasks and enforce consistency. Scispot's platform can connect to lab instruments and even trigger inventory re-ordering when supplies run low. This kind of automation is vital when building something as intricate as a new organism. There are many steps (gene cloning, culture growth, assays) where mistakes or delays can creep in. An integrated system reduces manual transcriptions (preventing errors) and can even recommend optimized workflows.

As Singh describes it, labs can become "fully connected, AI-driven, and audit-ready" environments, which is especially important for regulated biotech work where documentation and compliance are critical.

Democratizing Advanced Capabilities

Crucially, tools like Scispot are accessible to startups. They are no-code or low-code platforms, meaning founders don't need a dedicated IT team to implement them. In the same way cloud computing leveled the playing field for tech startups (allowing a two-person team to rent server power that was once available only to large corporations), AI-ready lab software levels the field for bio startups.

A small synthetic biology company can design its data infrastructure from day one to be machine-learning compatible, which pays dividends when optimizing strains or scaling up production. Labs can incorporate advanced AI capabilities into their existing workflows without costly system upgrades, a significant advantage for young companies watching every dollar.

Implications for Biotech Founders

The convergence of the LEGO-like synthetic biology paradigm with advanced digital tools is democratizing what biotech startups can achieve. For founders or aspiring entrepreneurs in this space, several key takeaways emerge:

Think in Modular Designs

Just as software startups think in terms of APIs and modules, biotech startups can think in terms of chassis and BioBricks. Identify existing biological parts that can be repurposed for your idea (many are open-source in repositories). Designing your project as a series of interchangeable genetic modules not only speeds up development but also helps in troubleshooting. You can swap out one "brick" if it underperforms without overhauling the entire system.

This modular approach also makes it easier to explain your technology to investors and partners, as you can break down complex biological processes into understandable components and demonstrate how each contributes to the overall function.

Leverage Precedent, but Innovate on Combinations

Synthetic biology has a growing library of successes, from insulin production in E. coli to anti-malarials and cannabinoids in yeast. These examples point to what chassis and pathways work for certain products. As a founder, you can build on these proven bricks (for example, using a known enzyme for a pathway step) while adding your novel twist.

Innovation often comes from recombining existing parts in new ways or targeting niches (like rare cannabinoids) that others have overlooked. This approach reduces technical risk while still enabling breakthrough applications.

Implement AI and Lab Automation Early

Implementing a digital lab stack from the outset can save enormous time later. Early-stage teams often start with ad-hoc data handling, but transitioning to a platform like Scispot sooner rather than later means your experiments will be systematically documented and analyzed from day one.

This not only improves R&D efficiency through features like automated trend analysis but also creates a treasure trove of data that impresses investors and partners. It demonstrates that your startup operates like a cutting-edge organization capable of scaling. Moreover, having AI assistance can surface insights that a small team might miss, essentially acting as a force multiplier for your scientific talent.

Scale Smart, Not Just Fast

Synthetic biology startups face unique scale-up challenges because biology can be less predictable than software code. The LEGO analogy reminds us that robust systems come from solid foundations and well-tested components. It's better to get a prototype organism working reliably in a small fermenter than to rush into a 1,000-liter production run that fails.

Tools (both biological and computational) exist to simulate and optimize conditions. Founders should iteratively test their engineered strains using high-throughput screening and use AI models to predict optimal conditions, rather than brute-forcing their way to scale. Treat scaling as another design challenge, where each new level (like increasing fermentation volume or tweaking a pathway for higher yield) is approached methodically, with data to guide decisions.

Build Strategic Partnerships

The modular nature of synthetic biology makes it particularly well-suited for partnerships. You might focus on perfecting one type of BioBrick or chassis optimization while partnering with companies that excel in other aspects of the biotech stack. This collaborative approach can accelerate development while reducing costs and risks.

The Future of Modular Biology

The LEGO approach to synthetic biology is still in its early stages, but the potential applications are vast. As the library of standardized BioBricks grows and AI tools become more sophisticated, we can expect to see:

Accelerated Innovation Cycles

The combination of standardized biological parts and AI-driven optimization will continue to shorten the time from concept to prototype. What once took years might soon be accomplished in months or even weeks.

New Application Areas

As chassis organisms become more diverse and BioBricks more sophisticated, synthetic biology will expand into new domains. We're already seeing applications in sustainable materials, environmental remediation, and personalized medicine. The modular approach makes it easier to adapt existing solutions to new problems.

Enhanced Accessibility

Just as cloud computing democratized software development, the combination of standardized biological parts and AI-powered lab tools is democratizing biotechnology. Smaller teams with limited resources can now tackle problems that once required large, well-funded research organizations.

Conclusion

Synthetic biology's promise is often described in grand terms, but at its core, it can be understood in a wonderfully approachable way: building new biology the way one would build with LEGO bricks. This mindset of picking a sturdy chassis and then mixing and matching functional genetic bricks is empowering a new generation of biotech startups to go from wild idea to working prototype faster than ever before.

Companies like Hyasynth Bio have demonstrated that what was once science fiction (yeast producing cannabis compounds) is now achievable through clever bio-design. Enabling this revolution are AI-powered tools and lab platforms that remove much of the guesswork and grunt work from the process, allowing even small teams to operate with the sophistication of major pharmaceutical laboratories.

For early-stage founders, the landscape has never been more encouraging. If biology is like LEGO, many of the pieces you need are already on the table. With the right digital toolkit, you can rapidly assemble, test, and iterate on your biotech creation. What used to require a fully staffed laboratory can now be accomplished by a lean startup plugging into cloud labs, repositories of DNA parts, and AI assistants.

The result is that bold innovators can focus on the big picture: imagining new solutions at the intersection of biology and technology and then building them brick by brick, cell by cell, into something the world has never seen before. The future of biotechnology is modular, accessible, and limited only by our imagination and ingenuity.

As discussions like those featured on talk is biotech! continue to showcase, the convergence of synthetic biology's modular approach with AI-powered tools is creating unprecedented opportunities for entrepreneurs willing to think creatively about the building blocks of life itself.