TL;DR (bioRxiv)

1. Sequencing has scaled far faster than our ability to experimentally establish gene function, which is needed to understand and engineer biology

2. We built JERBOA, a toolkit of 3,888 transposon variants, to systematically identify genome-wide genetics that work in new organisms

3. JERBOA enabled transposon mutagenesis in 43 bacteria across twelve phyla. We demonstrated its utility in Comamonas testosteroni, a PET plastic and lignin waster stream degrader, producing the first genome-wide genetic map of its aromatic metabolism and validating key transport systems, catabolic operons, and gene regulation

The Gap Between Reading Genomes and Understanding Them

Over the last decade, biologists have learned how to read genomes at extraordinary scale. Microbial sequencing is now routine, fast, and cheap. Entire genomes can be generated in days, annotated electronically, and deposited into public repositories.

Public databases now contain hundreds of thousands of microbial genome sequences. Yet, we still don’t know what most of those genes actually do.

Yes, we can assign function to many genes computationally. Sequence homology, conserved domains, and protein structure can give us predictions which are useful as an informed guess. But when you are trying to understand mechanism of action or engineer a strain, you need to know what a gene does with more certainty.

The best way to figure out what a gene does is to disrupt it and see if something breaks or gets better.

For a small number of model organisms, this kind of experimental validation is routine. For more than 99.9% of the microbial world, we simply don’t have the tools to do this.

Why Genome-Wide Genetics Breaks Down

For more than thirty years, transposon mutagenesis has been the backbone of genome-wide functional genetics. Transposons are mobile genetic elements that randomly insert themselves across the genome. Since a bacterial genome is packed with genes, transposons usually insert into genes, inactivating them and creating what we call a knockout. You can use a functional transposon to generate large collections of mutant strains that collectively represent a genome-wide knockout library. This library can then be screened under specific conditions: classically, to isolate mutants that grow well under a given condition, thereby implicating a gene’s function; or, in the modern era of DNA sequencing, to comprehensively track the abundance of all mutants across the genome, where changes in abundance reveal which genes help or hurt the organism under that condition.

In model organisms like E. coli, this approach works reliably. Outside a small set of non-model microbes, however, existing transposon systems usually fail.

Transposon activity is not governed by a single variable. Productive mutagenesis requires a narrow balance across multiple host-dependent parameters. The transposase must be expressed strongly enough to drive insertion but not so strongly that it becomes toxic. The selectable marker must function in the host’s physiology. The regulatory sequences controlling both must be recognized by the host’s transcriptional machinery. Promoters that work well in one bacterium can be silent or disruptive in another.

We do not have a general model that predicts how these parameters interact across diverse species. Establishing genome-wide genetics in a new organism remains an empirical exercise. Researchers test a handful of constructs, iterate slowly, and often abandon the effort altogether. When this process fails, genomes remain electronically annotated but experimentally unverified, limiting our ability to move from sequence to mechanism.

Treating Genetics as a Search Problem

Rather than trying to design the right transposon in advance, we reframed the challenge: finding a functional transposon system is a search problem across a large combinatorial space. Build many variants, screen them in parallel, and let the data reveal what works.

We built JERBOA (Jumping Element libRaries with Broad hOst rAnge), a toolkit comprising 3,888 transposon variants. These variants span two transposases, six antibiotic resistance markers, and eighteen promoters drawn from mobile genetic elements across diverse bacterial lineages. The promoters were selected to span a range of expression strengths rather than a single presumed optimum, and to reflect regulatory sequences that have already functioned across multiple hosts. All of these variants were tagged with a unique DNA barcode.

All barcoded variants were delivered together in a single pooled experiment. Sequencing then revealed which specific combinations successfully generated genomic insertions in each organism.

Instead of guessing what should work, we let the data tell us what actually does.

What Worked Across Microbial Diversity

We applied this screen to 92 non-model bacteria spanning twelve phyla. Functional transposon insertions were observed in 43 of them, including seven species with no previously reported genetic tools of any kind.

Intriguing patterns emerged. Closely related organisms often favored similar promoter and transposase combinations. In several cases, variants that performed well in one member of a genus or family also performed well in others, suggesting that genetic access may scale by lineage more often than previously assumed. This effect was not universal, but it was reproducible enough to be practically useful.

The result was not a universal transposon. It was a repeatable way to discover functional genome-wide genetics in new organisms without months of bespoke optimization. By making these measurements across a wide range of microbes, we are starting to build a model for how gene expression and transposon mutagenesis behave across diverse species.

When Experimental Causality Becomes Possible

We showcased this toolkit on Comamonas testosteroni KF-1, a bacterium involved in PET plastic and lignin degradation.

Using the top-performing transposon identified with JERBOA, we generated the first genome-wide mutant library in this organism. The library contained 73,195 unique insertion sites and covered 92% of annotated genes.

We then grew this pooled mutant library on breakdown molecules either from PET plastic (terephthalate) or lignin (4-hydroxybenzoate), and compared it with a control carbon source. By measuring tracking these 73,195 transposon insertions across the genome, we were able to:

• Experimentally validate the tctA/tctB transport system and tph operon for terephthalate utilization

• Distinguish the 4,5-meta cleavage pathway for protocatechuate metabolism from alternative annotated pathways

• Identify additional genes whose roles were misassigned or missed entirely by electronic annotation alone

In several cases, disruptions to regulatory genes improved growth on plastic-derived substrates, revealing biology that would not have been apparent using computational tools (sequence or structure-based prediction) alone.

What Comes After Sequencing

The point is not that we made one bacterium tractable. The point is that genome-scale genetics in non-model bacteria no longer requires years of bespoke optimization. When finding a working transposon becomes a systematic search, understanding what a gene does can finally start scaling with sequencing.

At Cultivarium, we want to move from artisanal methods to systematic frameworks, putting us on the path to reducing the time and cost of studying and engineering biology. Our goal is to harness the genetic potential of the biosphere by turning non-model organisms into tractable laboratory systems.

The preprint is available on bioRxiv. Plasmids are available via Addgene (soon as a kit). Code for transposon sequencing analysis is available on GitHub.

If you are working with a microbe that has no tools but too much potential, we can help you! Reach out via partnerships@cultivarium.org

TL;DR (bioRxiv)

1. Sporosarcina pasteurii is the most studied biocement bacterium, but despite 70+ patents and decades of research, nobody had been able to genetically modify it

2. We report the first genetic toolkit: replicating plasmids, DNA delivery, promoters, reporters, and genome-wide transposon libraries covering 92% of genes

3. The breakthrough came from looking sideways—an environmental Sporosarcina relative helped us identify what works in the canonical strain

4. These tools convert biocement from a black box into a programmable system

The Built World Has a Cement Problem

Cement is the third-largest emitter on Earth, trailing only China and the United States. Roughly 6–8% of global emissions come from a single material humanity can’t stop using.

We’ve loved cement since Roman times; it’s one of the most transformative materials humans have ever deployed. We’ve industrialized it so completely that every bridge, highway, and skyscraper carries a thermal and carbon history baked into the material.

So the world needs alternatives that deliver comparable strength and durability. And they must draw on lower-carbon inputs such as ground limestone, waste streams, agricultural feedstocks, or even urea.

That’s where biocement comes in—and with it, a strange little bacterium that’s been studied for decades but remained stubbornly out of reach.

The Microbe That Makes Rocks

Sporosarcina pasteurii is the most intensely studied bacterium for microbially induced calcium carbonate precipitation (MICP). Applications include sealing leaks in subsurface infrastructure, stabilizing soils and aggregates, forming alternative building panels and components. Feed it urea and calcium salts, and it precipitates calcium carbonate. Those minerals bind loose particles into stone-like materials. Biocement. And S. pasteurii has a set of traits that make it strangely perfect for the job: extremely high urease activity, tolerance to high pH and ammonia, the ability to form endospores for shelf-stable products, and negatively charged cell surfaces that nucleate calcite crystals.

More than 70 patents reference this organism. Researchers have worked on it for decades—yet it remained genetically intractable.

The Genetic Wall Nobody Could Break

At the American Society for Microbiology meeting earlier this year, a researcher summarized the state of the art:

This was a lab serious about biocement. They had built autonomous systems that spray cells and feedstocks over sand-like substrates, studied the biochemistry enough to identify putative urea transporters and carbon exporters, and explored how urea helps cells maintain osmotic balance. In other words: everything except genetic engineering tools. When asked what they’d do with these tools, the answers were immediate: modify urease to tune its kinetics, improve urea uptake, systematically knock out genes to understand how urea enters cells, how crystals form, how sporulation is triggered.

Genetics would be transformative but it remained unavailable. Without genetic tools, industrial efforts have relied almost entirely on process engineering—reactor tricks and adaptive evolution. Engineers can tweak conditions, but nobody can rationally engineer the biology. The field has been, you might say, set in stone.

The Soil Strain That Changed Everything

Here’s the twist: the breakthrough didn’t come from a new trick—it came from looking sideways. It wasn’t about banging our heads against the wall on the canonical 1889 strain. Cultivarium’s environmental isolations yielded a Sporosarcina relative that was unusually permissive to plasmid-based screening, and this environmental cousin helped us identify which genetic elements would function in S. pasteurii itself. The broader lesson is one we keep learning at Cultivarium: search the environment for engineerable variants, not just the textbook strain. The 99% of biology that exists outside model organisms isn’t just a source of new capabilities—it can also be the key to unlocking the organisms we already have.

Laying the Foundation

We report the first genetic toolkit for S. pasteurii: a replicating plasmid, a conjugation-based DNA delivery protocol, a panel of constitutive promoters spanning three orders of magnitude, synthetic inducible promoters, and fluorescent reporters and antibiotic markers. To show that the system works, we deleted the entire urease gene cluster—about 5.7 kilobases—eliminating urease activity and biocement formation entirely. We also built a genome-wide transposon library with more than 15,000 unique insertion sites across approximately 92% of genes, which has already revealed surprises: a transporter knockout that unexpectedly looks to improve growth on urea, hinting at genetic complexity the field hasn’t mapped, yet.

What We Can Build Now

With genetic tools, S. pasteurii becomes a true platform organism. Here’s some of what Cultivarium scientists have been most excited about: understanding and rationally engineering the fundamental biology of biocement formation, modifying ureolysis rates and reducing ammonia emissions, systematically mapping genotype-to-phenotype relationships with highly-multiplexed pooled libraries, and pairing genetic engineering with process innovations like green urea feedstocks and ammonia capture for fertilizer production.

But S. pasteurii is just the beginning. Making biocement useful and widespread will require solving many problems, and genetics is just the first enabling step. Genetics will help us study this fascinating biology in the detail it deserves—so that we can invent better solutions, not just tweak the ones we inherited.

Our hope is that this work inspires researchers across biology, materials science, engineering, and design to keep exploring how organisms can make desirable materials—and to help create a built environment that reinforces, rather than erodes, the ecosystems it sits on.

If you’re working on biocement, MICP, or biomineralizing microbes—and want to explore what’s now realistically possible with genetic engineering tools—reach out at partnerships@cultivarium.org

We’re collaborating with teams in materials science, biology, and industrial design who want to move this field past the limits of the last 30 years.

If you want more stories from the 99% of biology that never makes the news, subscribe to Off Media below.

Cultivarium is turning 5. And we’re evolving to double down on our niche.

This has been an unusual journey from day one: non-model microbes, non-model roles, and non-model structure. Yet our team has pulled through challenges that sometimes had nothing to do with science itself.

I’m incredibly proud of the work from this group of intrepid scientists and engineers who have come on this journey. One achievement stands out: while it took us six months to find space during the Great Lab Space Glut of 2020, we only needed a single year in the lab to deliver our two-year milestones with overwhelming success. Since then, we’ve made it our baseline to over-deliver, ahead of schedule, while being under budget. We started from scratch—no existing platform, no tools from academia—and in record time we have produced a slew of public assets including preprint manuscripts, plasmids, code, protocols, and data.

The early years of a new scientific organization are not unlike working with a non-model organism: you don’t really know the growth curve, the stress responses, or the quirks of the environment until you’ve lived in it.

We’ve lived it. We’ve run the first experiment like this in the world.

And now, as we enter our fifth year—alongside a new three-year program with the Wellcome Trust that kicked off this past May—we’re ready for our speciation event.

The Long Arc: How We Got Here

My vision for Cultivarium started long before the organization existed. I studied electrical engineering as an undergraduate and jumped into biomedical engineering for my PhD with Jim Collins—learning computational systems, and synthetic biology while still holding onto the stylings of an engineer. Later, in George Church’s lab, I built engineering frameworks around new enzyme-based technologies and turned Vibrio natriegens from a curiosity into a genetically tractable speed demon.

These experiences taught me something crucial: straddling the disparate fields of biology and traditional engineering could be powerful—and excellence at their intersection necessarily takes time.

During the pandemic, I was part of an incredible team that stood up, from scratch, one of the fastest and largest clinical-serving labs with industrial-grade lab automation—PCR testing and viral sequencing at a scale I hope we will never need again. I loved every exhausting minute of it: the urgency, the scale, the mission. It showed me the convergence I’d been building toward: a way to bring this intensity to unblocking the bottlenecks that hold biological research back.

Those years collectively were Step 1—or 20 years of my life—of a longer trajectory I didn’t yet have a name for.

Step 2: Build the Tools for the 99% of Biology We Can’t Touch

Cultivarium is Step 2.

The north star has been clear from the start: a new age of applied biology where we can understand and engineer any organism, of any complexity, in any domain. Right now, biology runs on less than 1% of life we’ve domesticated—mostly because DNA delivery, genetic tools, and engineering workflows break the moment you step off the familiar path.

The other 99%? You can look, but you can’t touch.

So the Cultivarium team built the capabilities we each wished we had. Brief highlights: POSSUM for systematic discovery of working plasmids. An electroporation platform with active learning that effectively teaches itself to get DNA into new organisms. PRISM for capturing experimental know-how multimodally. We have a full pipeline of projects and capabilities, including AI and robotics tooling, that we’re working furiously to make accessible for the broader community. We will have more to announce on this front very soon.

This has been—as microbiologists call it—our lag phase. Only in the last year have we started to bend into exponential growth, both in capabilities and in what we’ve learned about the space of non-model biology.

The Vomit Comet Problem

Internally, I’ve often described Cultivarium and these experiments in metascience as a vomit comet. It’s an amazing feeling while you’re suspended—the freedom and the means to build without the usual gravitational pulls. But weightlessness has a time limit. Eventually the parabola ends, and you must choose where you land.

Our choice reflects an uncompromising stance on the work we do:

• If an effort is best as open-ended exploration, it belongs in academia.

• If an effort can clearly recruit venture investment, it is best as a startup.

We continue to position Cultivarium’s work squarely in the vast gulf of foundational research—work that, when intensely built, has the ability to drive academic science and accelerate industrial applications. These are the genuine gaps in the R&D ecosystem: important work that needs to happen but that neither traditional path can sustain.

Some of the most impactful innovations come from non-model systems so we’re going to remain here in the trench and keep working.

A New Old Path: Frontier Research Contractors

This is why our next step—the Frontier Research Contractor (FRC) model—makes sense.

Today, we are announcing that we have joined the FRC Launchpad, a program run by Renaissance Philanthropy and supported by the UK’s Advanced Research and Invention Agency (ARIA).

FRC comes from a lineage worth knowing. ARPA’s biggest wins—the internet, autonomous vehicles, stealth aircraft—didn’t just come from good program managers. They came from exceptional contractors who shared three traits rarely found together: they were novelty-seeking, they built real technology for actual users, and they used more flexible team structures than academia allowed.

Bolt, Beranek & Newman (BBN) was one such contractor. They built the ARPAnet—not because they had the most funding, but because they’d spent years on adjacent contracts that positioned them perfectly when the opportunity arrived. They pursued an ambitious technical vision by offering their capabilities to others, productizing what made sense, and partnering where needed—without trying to fit an academic mold or pitch a market slide to venture capitalists before the science was ready.

An FRC operates the same way. We’ll keep pursuing our north star technical vision, but we’ll do it by building useful products for others along the way.

This is how we speciate. We’re making this mutation in our organizational DNA to give us a chance to adapt and thrive in the current environment. In a future post I’ll elaborate on what I think the “focused research” model got right and what comes next.

Why Now? The British Are Shooting Their Shot

My first conversation with ARIA was over a year ago. In the last few months, I’ve spent a lot of my time in the UK—learning from Science Conveners, chatting with Independent Scientists, discussing AI for Science, and having conversations from Cambridge to King’s Cross to White City.

My takeaway is simple: this is the most dynamic science ecosystem in the world right now.

There’s talk that UK science is “bleeding to death.” But that’s only because extraordinary talent and ambition are still pumping furiously. And there is hope: the UK is doing something the US isn’t—experimentation with its own innovation ecosystem.

ARIA embodies this. They’re trying new things, learning from them, and iterating—all with partners. And they’re doing it within their first three years. Contrast that with existing systems, even new ones, which are structurally opaque with little sign of movement. ARIA runs the equivalent of Fast Grants, ARPA Seedlings, and full DARPA-like programs. This is exactly the environment where experimenting with an FRC model makes sense.

I now see a boldness that I always associated with us. They’re doing science to win, whereas it increasingly feels like we’re playing to not lose. My fellow Americans, the British are coming. They’re shooting their shot. And I believe it will be heard around the world.

Through this program, Cultivarium will be looking for where our capabilities—DNA delivery, non-model genetics, protocol translation, AI-robotic experimentation—can serve ambitious new directions across ARIA’s Opportunity Spaces. We are going to play offense, and we’re gearing up to go earn it.

Open for Business

We’ll continue collaborating with academic labs, for-profits, and federal agencies. But we’re also opening our doors more deliberately.

We believe the real fruits of applied biology are yet to come, and reaching them requires building a taller ladder for everyone. That means working on the bottlenecks.

We’d love to see new types of organizations continue to spring up around us. More metascience experiments can be run so that we’re not all depending on subsidizing science through face creams and glowing plants. Critically, all efforts should be measured.

Cultivarium is a group of professional scientists and engineers unified to tackle the essential aspects of biological engineering. We seek the challenges that have been overlooked as underrated, too hard, and unglamorous, because we believe these are the things that must exist before the field can realize the full promise of engineered lifeforms.

This is our speciation event.

The mission hasn’t changed. The scope has expanded. And if we get this right, we’ll help unlock the 99% of biology the world still can’t touch to bring in the next age of applied biology. We’re certain that there’s a 100% chance it will be Not Boring.

We’ve spent four years building tools for organisms no one else could work with. Now we’re ready to build for anyone bold enough to try.

TL;DR (bioRxiv)

• DNA delivery—not editing—is the rate limiting step for studying and engineering organisms in our biosphere.

• Existing electroporators are black-box tools built for E. coli, not for the thousands of microbes we already know how to culture.

• We built a fully programmable, robotic, active-learning workcell to make DNA delivery systematically measurable so that we can collect data towards making it predictable.

• This platform discovers electroporation conditions and functional plasmids simultaneously across diverse non-model organisms.

• Using this system, we improved DNA delivery in Cupriavidus necator by 8.6× over the state of the art, in just three weeks.

• It’s our first step toward a universal framework for entering any organism—and unlocking the rest of biology.

The story behind the paper

Exploring biology isn’t held back by a lack of imagination or ambition. It’s held back by a bottleneck that few dare to tackle - DNA delivery.

We talk a lot about accelerating biology—cheaper DNA synthesis, automated assays, large-scale sequencing, AI agents—but none of it matters if you can’t get DNA into the organism you want to study. You can culture thousands of microbes. You can design constructs, assemble pathways, even write whole genomes. But the fundamental questions about how an organism operates goes unanswered unless you can get synthetic DNA across the membrane. Without this, you can look but you can’t touch.

When we went searching for a framework—a systematic way to establish DNA delivery across species—we found almost nothing. Scientists often start with conjugation from E. coli and hope for the best. Other methods—chemical competence, natural competence, electroporation, biolistics—appear sporadically in the literature as organism-specific methods. There are no general rules, little quantitative data, and nothing close to a predictive model.

We wanted a method that could apply broadly, across as many microbes as possible. That led us to electroporation: a biophysical approach where an electrical pulse temporarily opens pores and DNA is electrophoresed into the cell… in theory. In practice, the field provides little in the way of biophysical understanding or guidance about which buffers, voltages, resistances, or capacitances matter.

If we wanted to learn about electroporation—even for one microbial strain—we needed many measurements. And to get those measurements, we needed instrumentation that didn’t exist. So we built it.

What began as a search for DNA delivery protocols became a multi‑year effort to design the assays, hardware, robotics, and machine‑learning infrastructure that now form the basis of a self‑driving laboratory workcell for discovering DNA delivery in non‑model microbes.

The Bottleneck We Couldn’t Ignore

DNA delivery is biology’s silent rate‑limiter. We can enumerate microbes using sequencing and we can synthesize pools of synthetic DNA, but without a reliable way to introduce DNA into a new organism, we remain observers rather than engineers. Phenomena remain descriptions rather than explanations.

Once we recognized this, we reframed the challenge: not “How do we electroporate this microbe?” but “How do we systematically learn to electroporate any microbe?”

That required three things:

1. A standardized, information‑rich assay.

2. Hardware capable of exposing, measuring, and varying the full electroporation parameter space.

3. A robotic and computational system capable of exploring that space efficiently.

None of these existed. So we built all three.

Building a Platform the Field Never Built

Modern commercial electroporators hide nearly everything that matters. They work well for E. coli, yeast, or mammalian cells—but what about everything else? Three knobs and a few numbered programs aren’t enough. There’s no way to programmatically control or systematically vary all the parameters for the electrical stimulus and to record the pulse.

We needed an instrument that behaved like a scientific tool, not a black box. That required custom high‑voltage architecture, including large capacitors reminiscent of 32‑oz craft beers—big enough to deliver precise, programmable pulses across a 96‑well plate. We needed a fully programmable system that could generate custom waveforms, control timing down to microseconds, and record the resulting traces.

Then we integrated this custom hardware with the rest of the laboratory: liquid handling, plating, incubation, and imaging. These are all controled by robotics powered by modern multimodal perception, Video‑Language Models (VLMs) and Vision‑Language‑Lab‑Action (VLLA) models, to interpret sensor data, press buttons on legacy instruments, and close the loop between instruction and action. Natural language became a control layer for scientists to do the experimentation they wanted. The system could explore, measure, and iterate—exactly what is required to explore biology.

An Initial Framework for Electroporation

We began by building a compact, informative 24‑condition screen—combinatorial variations of buffers, voltages, and waveforms—designed to provide the first measurable foothold for any new organism. This screen revealed electroporation conditions for bacteria that had no prior genetic tools.

But DNA delivery isn’t just about the pulse; it’s also about the plasmid. So we paired the electroporation screen with POSSUM, our pooled library of plasmids carrying diverse origins of replication and selection markers. With one experiment, we could determine both which electroporation conditions work and which plasmids replicate.

Finally, we incorporated active learning—a machine‑learning approach that lets the system choose conditions based on both exploration and knowledge extracted from the literature.

Using this self‑driving DNA delivery system, we improved electroporation for Cupriavidus necator by 8.6× over the published protocol—first described 31 years ago—in just three weeks. The updated method is available in our preprint for researchers working on bioplastics, carbon capture, valorization, and bioremediation.

Getting to a Predictive Model of DNA Delivery

Electroporation was our proving ground—the clearest illustration of what happens when a field lacks measurement, models, and systematic tools. DNA delivery remained artisanal not because it was unknowable, but because no one had built the instrumentation required to know it.

Now that we’ve built the hardware, robotics, and active‑learning pipeline for self‑driving experimentation, we can collect the kind of data required to learn DNA delivery at scale.

This is our long‑term goal: a predictive framework for DNA delivery across the entire tree of life. A way to transform genetic tractability from a bespoke art into a discoverable property. A way to reliably unlock organisms with extraordinary abilities—those that remediate toxins, fix carbon in extreme chemistries, regenerate tissues, metabolize plastics, tolerate vacuum or radiation, and survive desiccation for years.

Our system can already execute multiple Cultivarium assays end‑to‑end, and electroporation is now part of that unified framework. We will grow this platform into a self‑driving genetic‑tractability workcell—one designed not merely to run experiments, but to learn from them.

The Road Ahead

The deeper story is that this entire system—instrumentation, robotics, multimodal perception, and active learning—is the foundation of a self‑driving genetic‑tractability workcell. A modular unit capable of executing Cultivarium‑scale assays with minimal human intervention and full scientific intent.

Over the next year, we’ll begin opening access to this platform as a Cultivarium‑operated cloud lab. Scientists will be able to submit organisms, constructs, or hypotheses and receive data, protocols, and actionable insights back—without needing specialized automation expertise. Tools that help us learn biology faster should help everyone learn biology faster.

Electroporation was our test case—an area where assumptions were weak, models nonexistent, and systematic measurement missing. It showed that once the right instrumentation exists, biology becomes legible at resolutions and throughput that human‑only experimentation and traditional literature have not reached.

Now imagine applying this same philosophy—frameworks, measurement, automation, and predictive modeling—to every major bottleneck in studying and engineering new organisms.

That’s the next frontier for Cultivarium: a world where genetic tractability is discoverable, DNA delivery is predictable, and the full diversity of biology is accessible to science and engineering.

TL;DR (bioRxiv)

1. Toolkit for genetic engineering of Ideonella sakaiensis (aka Piscinibacter sakaiensis)

2. Whole-genome, barcoded mutant library for high-throughput functional genomics

3. Mutants with improved DNA delivery

4. Uncovered genetic pathways for PET degradation, bioplastic production, and biofilm formation

5. PRISM videos available to distribute expertise to work with this microbe

6. We can do great science together—with dedicated experts at Cultivarium and across the academic ecosystem.

The story behind the paper

At Cultivarium, our mission is to speed up experimentation and engineering across the tree of life. Most of biology runs on a few model organisms, but the world’s problems—in this example plastic waste—often demand novel biology outside of that small circle.

This story, now available on bioRxiv, starts with one such outsider: Ideonella sakaiensis (aka Piscinibacter sakaiensis), a bacterium discovered 9 years ago in a Japanese recycling facility. When scientists first found it, Ideonella did something almost magical—it could eat plastic bottles. Specifically, it could degrade and metabolize polyethylene terephthalate (PET), one of the most common and persistent plastics on Earth.

Since then, Ideonella has become a symbol of hope in the fight against plastic waste. But there’s been one major problem: nobody could easily engineer it. Without tools to modify its DNA, the field turned to workarounds—expressing its plastic-degrading enzymes (PETase and MHETase) in E. coli or Pseudomonas. At the international Metabolic Engineering Conference in 2025, one speaker bluntly summarized the state of the field:

“Because Ideonella is not engineerable, we decided to engineer E. coli to degrade PET.”

This caught our attention because this is exactly the problem that Cultivarium was built to solve.

A hot collaboration from a cold email

In June 2023, shortly after we released our POSSUM, a scalable toolkit for identifying functional plasmids across microbes, Victoria Sajtovich from the Max Planck Institute for Terrestrial Microbiology (Marburg, Germany) reached out. She had been studying Ideonella and wondered if we could work together to find a replicating plasmid.

We were intrigued. We had tried growing two “identical” Ideonella strains from two different culture collections (NITE in Japan and DSMZ in Germany) and found, to our surprise, that they grew differently. Same name, different biology.

Victoria traveled to Cultivarium and spent a week in the lab with our team. She showed us how to culture Ideonella and we showed her how to run POSSUM experiments. We ran the experiment over a few focused days and after a weekend sequencing run, we found a working plasmid and selectable marker. What might have taken a researcher in a lab a year of searching took only a few days of hands-on work.

That moment was a tangible proof point of our ambition at Cultivarium: tools to compress the time to biological discovery by orders of magnitude.

From plasmids to a genome-wide mutant library

Once Ideonella was transformable, we went further. Using a transposon system, we created a genome-wide, randomly barcoded mutant library of 353,908 uniquely trackable strains. With sequencing, each mutant can be tracked even when all of them are mixed together, enabling pooled functional screens where we can measure the effect of each gene in different conditions.

Together with Felipe-Andres Piedra at Baylor College of Medicine, who developed a sensitive PET degradation assay (bioRxiv, AEM), we used this library to profile Ideonella’s genetic response to growing directly on PET. In high-throughput experiments spanning several weeks, we tracked biofilm and planktonic populations as they colonized and consumed PET films.

The results revealed the genes that matter most: those involved in PET metabolism, transport, and a surprising connection to PHB (a biodegradable bioplastic) biosynthesis. We also found mutants that improved degradation by forming denser biofilms—especially those lacking pilT, a gene that normally controls the bacterium’s pili retraction. These mutants stuck better to PET and degraded it faster.

Making laboratory strains that are easier to engineer

We didn’t stop at understanding degradation. Using the same mutant library, we ran a second screen to identify variants more amenable to DNA delivery. That effort surfaced a set of genes—especially those involved in the bacterium’s surface S-layer and restriction-modification systems—that, when disrupted, allowed plasmid DNA to enter more efficiently. These more transformable mutants could help researchers probe the genome and test DNA constructs to study and engineer Ideonella far more easily.

Sharing the knowledge, not just the results

Every experiment we ran carried lessons—about subtle media differences, strain variation, and the small details that determine success or failure. Those lessons inspired Cultivarium Lab Lore, an effort to source hard-won tacit knowledge of working with non-model microbes from scientists in the form of digital post-it notes that scientists can discuss, akin to Reddit.

These efforts also motivated PRISM, our platform for AI-transcribed and error-checked audio+video recordings of protocols (site). You can now watch and learn Ideonella PET-growth methods directly from Felipe’s lab through PRISM here. Sharing these multimodal protocols that scientists can study, without relying only on a Methods written in prose or bottlenecked by traveling to a specific lab, is how we make progress reproducible and accelerate the next wave of discovery.

The bigger picture

By developing the first functional plasmid, a transposon system, and a genome-wide barcoded library, we’ve turned Ideonella from an icon of curiosity into an engineerable chassis for studying PET biochemistry, ecology, and synthetic biology. This means researchers can now explore its metabolism in detail, optimize plastic degradation, or even redirect its carbon flow toward useful molecules.

We’d like to make these materials broadly available to the scientific ecosystem. Molecular assets will be distributed via Addgene and the mutant library through Cultivarium, for as long as we have the supply. We’d love to see a distributed network form to propagate these assets robustly throughout the community.

This is just the beginning. Ideonella is the first in a series of organism-centric vignettes that we’ll be sharing, each highlighting Cultivarium’s tooling to study and engineer remarkable microbes in record time.

If you want to go deeper on your organism of interest, reach out. We can work with you, whether in academic or industry, to unlock the genetic potential of the biosphere. Together, we can make the extraordinary accessible.

At Cultivarium, we’re building tools to help scientists move fast with non-model microbes. These are the wild, wonderful organisms that haven’t benefited from decades of research and toolkits behind them, like E. coli or S. cerevisiae. But they might be faster, tougher, or better suited for the job you have in mind.

Our latest proof point? A rapid survey (BioRxiv preprint) of plasmids for Vibrio natriegens, the fastest-growing free-living organism. However, this story begins much earlier, with a profound passion for organisms that many scientists have overlooked.

The Microbes That Time Forgot

While the scientific world has spent decades perfecting E. coli and S. cerevisiae, we've been captivated by the vast microbial universe that remains largely unexplored. These "non-model" organisms—the bacteria, archaea, and fungi that are not typically listed in textbooks—often possess extraordinary capabilities that could revolutionize biotechnology.

The challenge? Working with non-model microbes is notoriously difficult. Scientists need genetic tools, such as plasmids, promoters, and origins of replication, that function reliably in their organism of choice. For well-studied microbes like E. coli, these tools have been refined over the course of several decades. For everything else, researchers often start from scratch, spending months or years just to get basic genetic manipulation working.

This is exactly the barrier we've dedicated Cultivarium to breaking down.

Vnat: Enter the Speed Demon

We’ve been in love with Vibrio natriegens (affectionately, Vnat) for nearly a decade. What makes V. natriegens special? Pure speed. This bacterium doubles every 10 minutes under optimal conditions, twice as fast as E. coli. That might not sound revolutionary until you consider the cumulative impact: if every biology lab in the world could cut its experimental timelines in half, the acceleration in scientific discovery would be staggering.

Back in 2012, when the Cultivarium team was just a couple of postdocs at Harvard, it took four years to establish foundational resources for Vnat (2016): the closed genome, delivery and molecular tools, and a roadmap to whole-genome functional genetics using CRISPRi. Why did we do all that? We believe that Vnat could accelerate science itself, and we wanted to share this as soon as possible. It would take us another 3 years (2019) to scale up the initial work and publish it in a journal (most of the time was spent here).

We weren't the only ones who recognized this potential. This microbe attracted attention from major players, including Synthetic Genomics Institute, where Matt Weinstock (now CTO of Novel Bio) developed a commercial version called Vmax. Matt's team has now launched CyClone, a commercialized strain designed to be even more user-friendly.

Can Vnat really be the new E.coli? That vision is now closer to materializing, and we would like to help bring it to fruition.

The Switching Cost Problem

But here's the catch that's holding back widespread adoption of any new microbial host: switching costs. Most scientists have invested years perfecting their experimental workflows around specific plasmids and genetic parts. They're understandably reluctant to abandon their tried-and-true setup for a new organism unless they're confident it will work with their existing toolkit.

This creates a chicken-and-egg problem. Scientists won't upgrade to other organisms without compatible genetic tools, but tool development relies on usage to drive innovation. Someone needs to systematically determine what works and implement it quickly enough to accelerate, rather than hinder, research progress.

POSSUM: A Parallel Approach

Enter Cultivarium’s POSSUM: Plasmid Origins and Selectable Markers for Undomesticated Microbes. It's a mouthful, but it works.

Instead of testing plasmids one at a time, we create a library of them, each with a different origin of replication (ORI) and antibiotic resistance markers, and introduce them all at once. Then, we sequence all surviving colonies together to read out which plasmid “survived” in the microbe. The surviving plasmids tell us which ORI and antibiotic work. This experiment is one complex DNA sample going into a microbe (all plasmids together, including an internal control), and one DNA sample loaded on the sequencer at the end (DNA from all colonies together, including the internal control).

It’s like casting a net of options and seeing which ones come back with a catch.

CyClone Meets POSSUM

CyClone is a new lab strain of Vnat being commercialized by Novel Bio. It’s designed to produce plasmid DNA quickly, which can be valuable for applications ranging from basic research to the manufacturing of therapeutics.

But switching your cloning system from E. coli to Vnat isn’t trivial. Could you use the same plasmids? The same antibiotic selection markers? What concentration of antibiotics should you use? Answering those questions used to be a slow process. When we worked on the original Vnat strain, it took nine months to build and test, one by one, just a small fraction of the plasmids we have in POSSUM. We need faster and more comprehensive answers.

We applied POSSUM to wildtype and CyClone Vnat strains. We treated CyClone like any unknown microbe. No assumptions. We ran the assay and got a clear picture of the working parts and protocol in under a week. Origins of replication, antibiotic resistances, it was all there. Our POSSUM results matched nicely with what was previously published about Vnat and extended upon what Novel Bio has set in their user manual.

The key value isn't only the speed of the assay, it's the confidence derived from the outputs. POSSUM lowers the switching cost barrier by building trust with scientists who might otherwise hesitate to switch to a new system. It provides researchers with a data-backed menu of what works.

The Bigger Picture

The CyClone project represents something larger than just characterizing one organism. It's a demonstration of how systematic, high-throughput approaches can accelerate the adoption of any non-model microbe. What might appear to be a trickle of testing individual organisms is part of our larger effort to explore the vast and largely unexplored microbial universe.

Every time we find a microbe with interesting properties, whether it's a bacterium that can degrade plastic, a fungus that produces a novel chemotherapy, or an archaea that is the most radiation-resistant organism, we face the same fundamental questions. How can we manipulate their genomes to learn from or harness them? The only thing holding us back is the time and effort required to develop tools for each of these organisms.

POSSUM and similar technologies can compress this timeline from years to weeks. It's infrastructure for a future where scientists work with the best microbe for the job, not just the best-studied microbe. The future of biotechnology isn't just about the few well-studied model organisms; it's about systematically exploring the entire tree of life.

Take a look at the BioRxiv preprint for the scientific details. And, if you’re working with a new microbe and are unsure where to start, let’s talk. Reach out to me and the team at info@cultivarium.org.

Read more about POSSUM
📜 BioRxiv preprint
📣 Cultivarium blog post

Learn about CyClone
🧬CyClone product overview

The Lab Lore Problem

We've all been there. You find a promising protocol buried in the methods section of a paper. You follow it precisely - or so you think - yet somehow your results look nothing like what was published. The authors wrote "cells were gently resuspended," but what exactly constitutes "gentle"? They wrote "incubate until turbid," but failed to mention the specific visual cues they used to judge turbidity under their particular lighting conditions. These gaps aren't oversights—they're the inevitable result of trying to compress embodied knowledge into text.

At Cultivarium, we're working with nearly 500 different microbes, many of which have their own unique requirements. For example, some require precise wavelengths of light to thrive; others need specific gas mixtures; some aggregate in ways that confound standard protocols. When you're engineering organisms that have never seen the inside of a traditional lab, you quickly discover that the scientific literature, for all its rigor, simply cannot capture the full art of laboratory practice.

To address this challenge, we have leveraged Large Language Model (LLM)-based tools that organize and synthesize the vast, fragmented landscape of microbiological methods literature. Our internal LLM-based knowledge stack has helped us bootstrap our work across a wide range of organisms, revealing how different labs approach similar problems. But even the most advanced language models can't extract knowledge that was never written down.

This shouldn’t come as a surprise- scientific papers are narratives, crafted to tell compelling stories within the constraints of academic publishing. They represent filtered versions of reality, shaped by publication bias, word limits, and the need to present messy experimental journeys in a clean narrative. While the recent advancements in AI reasoning agents for science are intriguing resources for parsing scientific literature, a critical bottleneck remains upstream of the process: documentation.

So how do we document better? As an initial step, we added a "Lab Lore" section on the Cultivarium Portal. This section serves as a digital repository for the sticky notes that accumulate in every lab notebook, capturing the tricks and insights that never make it into publications. But we've come to realize this isn't enough. There are simply too many nuances that resist textual description, such as the angle at which you hold a pipette when working with aggregating cells, the subtle color change that signals the perfect moment to stop a reaction, and the rhythm of mixing that prevents foam formation in a particular medium. These are the kinds of tacit knowledge that can take months or years to transfer between scientists, if it ever happens at all.

Introducing PRISM: Protocol Recording for Improved Scientific Methodology

Today, we're announcing beta access to PRISM, an AI-powered lab assistant that captures what experimentalists actually see and do in the laboratory. With cutting-edge LLMs, PRISM transforms the traditional protocol from a static text document into a rich, multimodal record of scientific practice.

Here's how it works: Before beginning an experiment, a scientist dons a pair of glasses that capture both audio and visual data. As they work, they narrate their actions by calling out key observations. PRISM then processes this raw footage, converting it into a step-by-step protocol. The software highlights any missing details and synchronizes the video with each step of the protocol. Users can then edit and fine-tune the output, assisted by AI suggestions.

The result is a detailed multimodal protocol that others can read, listen to, and watch to see how an expert handles each step. When a protocol says "resuspend cells," viewers can observe the precise pipetting technique. When it mentions checking for contamination, they can see what contamination actually looks like in that specific experimental context.

PRISM captures science as it actually happens, including the failures, the adjustments, and the intuitive decisions that experienced researchers make without conscious thought.

Why Now? The Convergence of Need and Capability

As a non-profit, Cultivarium occupies a unique position in the scientific ecosystem. Unlike commercial entities driven by immediate profit considerations, we have the freedom to take a longer-term approach and collaborate with the scientific community to determine what is genuinely needed. Our goal is to address fundamental research challenges through our own experience while actively collaborating with the broader scientific community for input and co-development.

PRISM represents the first module in what we envision as a comprehensive suite of tools for capturing and scaling scientific expertise. But it's also immediately useful. For anyone working with non-model organisms, where every technique must be adapted or invented, PRISM offers a way to document and share hard-won methodological insights. For collaborations between labs, it provides a richer medium for knowledge transfer than any methods section could achieve. For education, it opens up new possibilities for training the next generation of scientists in techniques that have traditionally required extensive hands-on mentorship.

The Future of Laboratory Automation

While PRISM's immediate value lies in better documentation and knowledge sharing, we see it as laying crucial groundwork for a more ambitious goal. Most current laboratory automation focuses on scaling up established processes - taking something that works and doing it 100 or 1,000 times. But what about automating actual R&D, the kind that goes from 0 to 1?

We believe that recording a raw feed of scientific practice is essential for developing genuine artificial intelligence for science. Parsing literature is valuable for understanding what has been tried, and for drawing connections between disparate findings. However, we scientists know that papers shaped by publication pressures often portray successful outcomes, rather than the countless micro-decisions and adaptations that made success possible.

By capturing the ground truth of laboratory work – the false starts, the on-the-fly adjustments, the visual and tactile cues that guide expert judgment – PRISM defines a new kind of training data for science. This data could eventually enable AI systems that not only execute predefined protocols, but can also adapt to the unexpected, recognize when something isn't working, and even generate novel approaches to experimental challenges.

JOIN US: A Call for Collaboration

PRISM works today. We're using it in our labs to capture protocols for our diverse microbial collection, building the foundation for a new kind of scientific knowledge base. However, we designed it to be larger than the Cultivarium team.

The PRISM tool we’re making accessible today is not the final product - it is the beginning of an R&D process that is better done in collaboration. We're actively seeking partners and co-developers who want to help expand PRISM beyond our initial use cases, and build the vision and action models for the laboratory. If you're passionate about shaping how science is taught, shared, and automated in the coming decades, we want to hear from you. Contact us to explore collaboration opportunities, request early access, or share your vision for the future of scientific methodology.

We’re looking to work with:

• Research groups working with challenging organisms or protocols

• Institutions focused on reproducibility and training

• Educators interested in new ways to teach laboratory skills

• Data scientists/ML experts with ideas for enhancing PRISM's capabilities

• Scientists frustrated by the limitations of written protocols

• Funding organizations supporting reproducibility and scientific methods development

• Science communicators seeking to fundamentally transform how we share scientific knowledge.

We're particularly interested in feedback on:

• Protocol types that would benefit most from multimodal capture

• Integration with existing laboratory workflows

• Features that would make PRISM indispensable for your research

• Novel applications we haven't considered

From an Art to a Science

The scientific challenges we face, from understanding microbial dark matter to engineering biology for sustainability, require new approaches to working. They need us to move beyond the limitations of text-based knowledge transfer and embrace richer forms of scientific communication, because – despite our best efforts – sometimes great science falls into the gaps between what we write and what we do.

It is time to patch up these gaps. The countless small expertises that make discovery possible should no longer be lost between the sections of our publications. By recording and indexing experiments for deeper study by both humans and machines, we can avoid the false dichotomy between glorifying human taste and holding our breath for artificial superintelligence. The way forward is about augmenting, not replacing human expertise. Together, we can move the art of science to a science.

Access PRISM here, or book a demo.

Stay tuned for the next part of this series. As we continue to develop PRISM, we'll also dive deeper into our roadmap for revolutionizing laboratory R&D through true 0-to-1 automation. it's not about repackaging existing automation platforms, but reimagining how artificial intelligence can participate in the creative process of scientific discovery.

At Cultivarium, we are on a mission to open the microbial universe to exploration at scale. A significant part of that universe is comprised of fungi and archaea, whose superpowers have only begun to be understood and harnessed by researchers worldwide.

Fungi and archaea represent some of the most fascinating yet understudied branches of the tree of life. Fungi can transform into different morphologies depending on their environment, produce an astonishing array of bioactive compounds, and break down almost anything, from plastics to pollutants. Archaea, the ancient microbes that thrive in extreme environments where nothing else survives, hold genetic secrets that could revolutionize biotechnology and our understanding of evolution. These organisms have been quietly shaping our planet for billions of years, yet we've only been able to study a few of them in the lab. There’s little doubt that we’ve barely scratched the surface of their capabilities.

We believe that dramatically increasing the breadth of research about fungi will produce breakthroughs with profound benefits to society in areas like:

• Human health and medicine - developing novel antifungal treatments to combat the global surge affecting over 300 million people annually, and new compounds for chronic diseases

• Sustainable agriculture - creating resilient crops and natural pesticides to protect against worms and insects

• Environmental remediation - harnessing their metabolism to degrade biomass, pollutants, and even radioactive waste

• Industrial biotechnology - leveraging them as production chassis for food, drugs, materials, and other chemicals for a circular bioeconomy

• Climate change mitigation - sequestering carbon underground in symbiosis with plants

Cultivarium is an engineering firm that helps biotech innovators harness the latent power of the microbial universe in record time. We are unique in that we purposefully explore the whole tree of life, not just the few well-known bacteria or yeasts. We are developing tools and technologies to efficiently investigate hundreds of non-model microbes.

Our ultimate goal is a flourishing bioeconomy that heals our people and planet. To achieve this, we need to develop accessible tools for genetic engineering, establish standardized protocols for growth and manipulation, and foster vibrant research communities that can collaborate effectively across disciplines.

Despite their growing scientific importance, however, research progress on fungi and archaea has been severely hampered by two things: 1) the limited number of model species, and 2) insufficient foundational research tools available to scientists working in the field.

We're enormously proud to receive support from Wellcome to build out our tools and resources for the fungal research community. Wellcome has a longstanding commitment to the ecosystem as a champion and convener. They are leaders in tackling global health challenges, funding vital scientific research, and building bridges between communities to tackle ambitious challenges.

Wellcome is committing more than £50 million to help biologists explore the crucial roles of fungi in human health and climate solutions. Our three-year project will dramatically reduce the time and expertise required to work with non-model fungi and archaea, democratize access to tools, and accelerate research along four main fronts:

1. Community engagement and data science

   • Creating advisory committees from industry, academia, and public health

   • Building digital tools for community knowledge sharing

2. Digital atlas of fungal growth

   • Developing a programmable biosphere to study fungi’s diverse lifecycle programs

   • Sharing this hardware with our global network to accelerate data collection

3. High-throughput DNA delivery methods

   • Building custom hardware for multiple DNA delivery modalities

   • Sharing this infrastructure with our global network for genetic manipulation

4. Molecular toolboxes for functional genomics

   • Assembling genetic libraries that are robust for diverse species

   • Sharing these assets with our global network for application development

I believe that in a few years, we'll look back on today's announcement as a catalyst for a Cambrian explosion of compelling biotechnologies.

What makes this support particularly special is the community we're building together. The fungal and archaea research communities are filled with passionate, innovative scientists who have made remarkable discoveries despite the comparatively fewer resources and tools they’ve had access to historically. By creating enabling technology and shared infrastructure, we're cultivating a collaborative ecosystem where knowledge flows freely, enabling everyone to advance together. This approach empowers the collective talent across the globe, from established institutions to emerging labs, with the same powerful tools and datasets.

Oh, and one more thing: if you're reading this and want to explore possibilities beyond E. coli and S. cerevisiae, you can think of us as your capable and experienced partner. We'd love to hear about what you're working on to see if we can help.

We're proud that our partners get to answers dramatically faster than doing this work from scratch themselves. We can tell you which strain, plasmid, and protocols are worth your time, and save you years of work, even if what we tell you is what doesn’t work. We want to increase the momentum from an exciting newly discovered microbe to a powerful technology for society. If it can be done, Cultivarium will show you how. Our goal is always to provide an evidence-based plan that you can be confident in pursuing.

Over the last 3 years, I’ve connected with members of the National Security Commission on Emerging Biotechnology (NSCEB) to discuss the intersection between biotechnologies and national security.

I’m pleased to see that NSCEB's final published recommendation aligns with several of Cultivarium's aims, and we're prepared to accelerate our efforts to secure America's lead in emerging biotechnologies.

In support of the report's key recommendations, Cultivarium is advancing in three strategic areas:

1. Expanding Biological Capabilities

We're developing the unique expertise to harness the millions of microbes that can be used for producing new materials, breaking down unwanted chemicals, and creating targeted therapies. We’re now working to program over 300 different bacteria, each with unique capabilities, which far exceeds the handful used today in most of academia and industry. Stay tuned - we’ll be announcing a new multi-year effort in the coming weeks to tackle a new kingdom of life!

2. Building Foundational Infrastructure

We've been busy building a suite of tools– molecular techniques, computational platforms, and bespoke hardware– as enabling technologies for life scientists. We’ve been able to bring down the time and cost of engineering a new-to-the-lab microbe by >10-fold, compressing research from months to days. We’re working with select partners to access our technologies and we’re excited to see their applications mature in both the academic and industrial ecosystem. Reach out for access!

3. Cultivating Biotechnology Talent

Our team draws expertise from microbiology, molecular biology, computational biology, and engineering. But it’s our shared fervor about the knowledge and beneficial outcomes we can unlock that drives our high velocity of progress. We've prioritized knowledge transfer and resource sharing with students and early-career researchers to invest in developing the next generation of biotechnologists who will create breakthrough innovations and essential products. Engage with our outreach programs!

Cultivarium was designed to bridge the gap between fundamental research and real-world applications. Our unique position in the ecosystem enables us to develop long-term strategic priorities for an entire scientific field, rather than being influenced by short-term academic or commercial pressures. We’ve been able to accomplish all this with the visionary and generous support of Convergent Research.

We're committed to positioning biotechnology as a force for positive global impact, and we look forward to hearing from everyone who shares this goal.

Contact us!

The field of microbiology is vast and constantly evolving. Yet as a recent article in Nature points out, approximately half of all published microbial literature focus on just ten species. In fact, the same report estimates that 74% of microbial species are not even studied. This dire statistic highlights a critical need to expand experimental accessibility to the microbial world.

To address this gap and accelerate discovery, we're excited to announce a powerful new feature on the Cultivarium Portal: Reported Methods, a comprehensive overview of reported genetic methods for an organism, making it easier than ever to explore available tools and delve into relevant research.

Explore Genetic Methods with Ease

This new section offers a curated list of genetic methods for each organism, including techniques such as electroporation, transposon mutagenesis, and CRISPRi.

Navigate Literature Efficiently

The table highlights the oldest and newest publications for each method, and you can access the full publication list by clicking on the underlined sections. Papers can be directly accessed via link to full text, or saved to revisit later.

Expand Your Research Horizons

If an organism currently lacks reported genetic methods, we provide guidance on closely related organisms with established genetic tractability to help you explore alternative avenues and identify new leads for your research.

Contribute to the Database

We believe that community involvement is crucial for building a comprehensive and valuable resource. We invite you to contribute to the database by submitting any feedback or additional publications via this Feedback form. Your input helps us improve the accuracy and comprehensiveness of our platform, benefiting the broader research community

.

Explore the "Reported Methods" section today and unlock a world of genetic insights! Click here to request Portal access.

The team met with over 2,000 participants from around the world, engaging in discussions about how young scientists are leveraging synthetic biology to tackle global challenges.

“Attending the iGEM Jamboree was a fantastic experience—seeing so many innovative teams working on non-model microbes was inspiring,” said Stephanie Brumwell, PhD, Scientist at Cultivarium. “I loved connecting with these creative young researchers and look forward to seeing Cultivarium's resources empower even more groundbreaking work in this field!”

At the Cultivarium booth, participants were invited to demo the latest Portal features, share lab lore, and test their gaming skills in a quick round of Microbe Mayhem. Cultivarium also presented a talk highlighting the open-source tools available to iGEMers passionate about non-model microbes.

Jamboree highlights also included the iGEM startup village, panel discussions, and fun costume sightings (including but not limited to: a ski-sized spoon, a banana hat, and one student dressed as corn).

This year, Cultivarium sponsored 11 teams from 6 countries, with projects spanning a range of topics from oncology, fashion and cosmetics, to food and nutrition. Learn more about future iGEM sponsorship opportunities, and register your interest here.

Congrations to all iGEM teams! From prize winners to special award recipients to medalists, you’ve all raised the bar in synthetic biology and inspired us with your achievements🏆. We’re excited to see where your journey takes you next!

Webinar Title: Cultivating Diverse Microbes for Laboratory Study and Genetic Engineering

Time: Thursday, October 3, 2024 12:00 PM ET

Key Highlights:

• Open-source tools to expand access to novel microorganisms

• Rapid identification of methods for culturing and DNA delivery

• Cultivarium Portal: Actionable insights for non-model microbes

At Cultivarium, we make it a point to share both what does and doesn’t work.

The not-so-secret rule of thumb in biology is that most experiments are very (very) likely to initially fail. Effectively, this means that the vast majority of research yields a marginal amount of positive results. This is especially true in the field of non-model organisms, where there are few prior publications available to help guide the research.

For a mathematician or a physicist, this degree of inherent failure and uncertainty is mind boggling (try describing your last cloning experiment to a physicist, probabilities and all).

For a biologist, this is just another day in the lab.

One would think that in a field so prone to failure, life scientists would find a way to collectively leverage negative data. Unfortunately, this is not the case. As recently highlighted in Nature, negative results are a critical but often overlooked part of the research ecosystem. An immense amount of resources (as much as $28 billion USD per year) are wasted due to low reproducibility of research findings, slowing down scientific progress. In the best-case scenario, negative results are painstakingly collected from publications. More often, they simply don’t make the cut.

At Cultivarium, we know that every day counts when working with non-model microbes— so we make it a point to share negative results. We share what we learn about what doesn’t work so you don’t have to try it yourself, saving precious time and money. We also learn from our own failures, and use negative results to iteratively improve the tools we develop.

For each organism we bring into our lab, we carefully document and publish all our findings onto the Portal. This includes culture media with no detected growth, plasmids that fail to replicate, and promoters that do not… promote. The Portal offers the flexibility to include or exclude negative results in view, depending on the user’s needs. Leading by example, we hope our Portal can catalyze community effort to share and learn from negative results.

Click here to request Portal access.

Cultivarium, the focused research organization creating open-source tools to expand access to uncharacterized microorganisms, and ATCC, the world's premier biological materials management and standards organization, today announced a groundbreaking collaboration to help iGEM 2024 teams access non-model microbes for biotechnology. The annual iGEM Competition involves multidisciplinary student teams from across the globe that compete for medals and awards by designing, building, and testing genetically engineered systems using standard biological parts called BioBricks. Working in and outside the lab, iGEM teams aim to create sophisticated synthetic biology projects that can positively contribute to their communities and the world.

Cultivarium and ATCC are committing to empowering the creativity of iGEM teams with diverse and innovative microbial resources to expand the horizons of synthetic biology research. iGEM teams will gain access to a rich selection of non-model microbes curated by ATCC and Cultivarium's expertise and technologies for new frontiers in bioengineering. During the past 20 years, 70,000+ iGEM participants have entered 5,000 synthetic biology projects for the competition, some of which have led to doctoral thesis topics and the launch of new companies and research endeavors.

"We are delighted to join forces with ATCC to support iGEM teams in their pursuit of scientific discovery and innovation," said Henry Lee, PhD, co-founder and chief executive officer at Cultivarium. "By pairing Cultivarium's capabilities and ATCC's enormous and taxonomically diverse collection of microbes we can support iGEM teams to be bold, creative and drive breakthroughs in synthetic biology."

"At ATCC, we are committed to advancing scientific research and education globally," said Ruth Cheng, PhD, senior vice president and general manager of research and industrial solutions at ATCC. "We are proud to contribute our expertise and ATCC's authenticated microbes to develop the next generation of talent applying synthetic biology across industries such as agriculture, food production, climate change, and human health."

Together, Cultivarium and ATCC are poised to revolutionize the landscape of synthetic biology by equipping iGEM teams with the tools and resources needed to tackle global challenges and unlock the full potential of non-model microbes.

Read the original article on PR Newswire

Our team was on the ground in Atlanta June 13-17 showcasing our open-access tools to the microbial community. After five days of inspiring sessions and vigorous scientific discussions with 300+ fellow microbiologists, the Cultivarium team walked away with a refreshed sense of purpose in unlocking the potential of novel microbes.

“Many attendees who came up to us were interested in gaining access to databases or computational tools that would help in working with hard-to-grow organisms.” reflected JooHee Choi, PhD, Project Manager at Cultivarium. “People sometimes have things [organisms] in the freezer but they’re not sure how to work with them in the lab.”

Conference highlights included talks on utilizing bacterial genomics for sustainable climate solutions, and AI-based approaches for accelerating microbial research. Program Manager Elise Ledieu-Dherbécourt, PhD, also gave a joint talk with ATCC at the ASM Microbe 2024 Industry & Science Showcase, sharing Cultivarium’s high-throughput approach to onboarding diverse microbes.

Read details on the talk and find the slides here.

Since starting Cultivarium, we’ve collected many “almost” stories from fellow microbiologists who ventured into exciting new microbes in their startup or thesis research and then dropped them in disappointment.

The number one reason for a promising microbe to be dropped is the lack of basic tools and protocols. And the absolute most basic tool - the one that can rescue an organism from oblivion - is a plasmid.

Just one good plasmid.

It is hard to find a reliable plasmid that works in a new organism, one that’s not a relative of E. coli.

But how can that be? Surely one of thousands of available plasmids can work? Sadly, the most commonly used plasmids either originated from E. coli, engineered specifically for E. coli, or were only tested in E. coli. Good luck trying them all, one by one, to find the one that works in your marine/soil/alligator gut bacterium.

But even if you’re willing to try, it’s hard to know where to start. To get even one plasmid into one colony, you’ll need the right origin of replication, the right antibiotic selective marker and the right DNA delivery protocol - all at the same (!) time.

Enter Cultivarium.

Our mission is exactly that - to make non-model microbes more accessible by building tools that reduce the time, labor and cost of current bottlenecks.

For example?

Cultivarium’s first tool - Possum aka Plasmid Origins and Selectable Markers for Undomesticated Microbes (acronyms selected democratically by the team).

The bottom line?

You can try this on any microbe you can grow in the lab. It will save you time and labor to find a plasmid that works in your organism because it tests many plasmids at the same time.

How does it work?

It’s a one-sample conjugation with a sequencing readout.

Instead of trying each plasmid - each ORI and each marker in each organism - we took a combinatorial (multiplexing) approach; we’ve made a single sample to use. It’s a mix of many plasmids with many (barcoded) origins of replication. You deliver one sample (all plasmids at once) into your microbe. You collect all the colonies that survived and mix them into a single sample. You sequence this sample to find out which plasmids made it in. We also provide the collection of all genetic parts if you want to swap things in and out.

What organisms did you try so far?

In a single run of this assay in extremophile bacteria - salt-loving, high-pH, and some electrically active bacteria that have little protocols or tools - we found working plasmids for species where none were ever reported (Halomonas alkaliphila, Halomonas neptunia, and Shewanella electrodiphila) and came up with plasmids we didn’t know we can use in others (Duganella zoogloeoides, Pseudomonas alcaliphila, Shewanella oneidensis and Shewanella putrefaciens).

What do I need to get started?

To run our assay in your microbe, you’ll need the toolkit (we make it available through Addgene), our protocol (we make it open access on BioRxiv), and access to sequencing (that’s on you). The code is publicly available on GitHub.

Big shout out to Charlie Gilbert, Stephanie Brumwell, Alex Crits-Cristoph, and Shinyoung Clair Kang!

Cultivarium, the focused research organization creating open-source tools to expand access to uncharacterized microorganisms, and ATCC, the premier global biological materials management and standards organization, have entered a multi-phase research collaboration to expand the use of non-model microorganisms. The collaboration seeks to expand the utility of ATCC’s microbiology reference materials to accelerate biomanufacturing and biotechnology research and development by making more microorganisms accessible.

The study of non-model organisms has already yielded transformative molecular tools, including green fluorescent protein (GFP), the enzyme Taq polymerase, and the CRISPR/Cas9 gene editing system. And yet, today’s bioeconomy relies on a handful of model microbes among the large number of species identified.

"We believe ATCC’s collection of authenticated biological materials has untapped potential that could hold the key to solving problems in industries such as agriculture, food production, climate, materials, and medicine," said Ruth Cheng, Ph.D., senior vice president and general manager, research & industrial solutions, ATCC. "By working with Cultivarium, we can expand the use of understudied microorganisms."

"The ATCC collection of cell and microbial reference materials is a global standard that has been the basis of incredible scientific breakthroughs," said Henry Lee, Ph.D., co-founder, and chief executive officer, Cultivarium. "Our goal is to expand the reach of ATCC's collection by making these organisms genetically tractable to the life science community. This is the first, but vital, step in accelerating the growth of the bioeconomy."

Cultivarium’s experts will continue to delve into ATCC’s vast collection of microorganisms with a focus on promising but currently under-utilized strains with remarkable characteristics. Cultivarium will generate open-source protocols, data sets, and tools that will be published on the Cultivarium portal. Authenticated strains and their associated genomic data can be accessed through ATCC.

About Cultivarium

Cultivarium is creating open-source life science tools to expand access to novel microorganisms, inspire new research avenues, and push the frontiers of biotechnology. A Convergent Research Focused Research Organization (FRO), Cultivarium’s five-year mission is to generate and share foundational genomic resources and bioengineering techniques for making new microorganisms accessible to research and development organizations. For more information, visit www.cultivarium.org.

About ATCC

ATCC is a premier global biological materials and information resource and standards organization and the leading developer and supplier of authenticated cell lines, microorganisms, and associated data for academia, industry, and government. With a history of scientific contributions spanning nearly a century, ATCC offers an unmatched combination of being the world’s largest and most diverse collection of biological reference materials and data, and is a mission-driven, trusted partner that supports and encourages scientific collaboration. ATCC products, services, partnerships, and people provide the global scientific community with credible, advanced model systems to support complex research and innovations in basic science, drug discovery, translational medicine, and public health. ATCC is a 501(c)3 nonprofit organization headquartered in Manassas, Virginia, and a research and technology center of excellence in Gaithersburg, Maryland. For more information, visit www.atcc.org.

Read the press release on PR Newswire

When Henry (Lee, our CEO) decided to pick up a new microbe for his postdoc research, he was not expecting this project to take 6 years. After all, this was the fastest-growing free-living bacteria known! If this won’t accelerate scientific discovery (and postdoctoral success) - what will??

Yea, so it did grow fast.

It grew so fast that it would have cut routine microbiology research time in half, because this Vibrio strain has a doubling time of ~10 minutes - half that of E.coli. But it also came with no user manual; no finalized genome sequence, no plasmids or genetic protocols, and few publications or academic groups to lean on.

Welcome to the world of non-model organisms! You’re in for a multi-disciplinary, go-figure-it-out adventure!

Why is it so hard?

If you ask any life scientist if you should try researching a non-model organism (for any reason) - you’d get that “good luck with that'' face. Researching a new organism is a notoriously difficult task across all fields of biology. Why is that?

It’s hard because every organism is a special snowflake.

Yes, every organism has unique features that should be explored. Selecting organisms for research has traditionally been a bespoke, empirical, trial-and-error journey. Model organisms have either been historically domesticated (S. cerevisiae) or a life-long tour-de-force by individual believers who paved the way for the rest of us (C. elegans). It’s a career-defining task, at the end of which you will be the expert on organism X.

It’s hard because you don’t know where to start.

To reach what most people consider the exciting part of studying a new organism (it can breathe rocks!), you’ll first need to overcome many less exciting serious technical challenges. Those challenges usually take so much time, money and labor to overcome that most organisms (and researchers) never cross the finish line. For example, most molecular biology methods start with a growing culture, so until you define a culture protocol you can’t do much of anything. Once you can grow an organism, you need to insert DNA to do genetics. But you don’t have a protocol, and even if you did - you don’t know which plasmid replicates properly or what antibiotics to use for selection. It can take months or years to figure this out on your own.

It’s hard because there’s no research community.

By definition, most non-model organisms are unexplored. So you would have none of the support that a mainstream-organism research community would provide, such as centralized databases, cited literature, collaborators and dedicated conferences. It can be quite a lonely journey.

It’s hard because you can’t get funding.

Since no one yet knows what makes your organism extraordinary, it is extremely hard to get funding to explore non-model organisms. Academic leads are reluctant to have students work for years to get very basic systems working, and will have a hard time securing funds for such groundwork. While industry is more likely to adopt organisms with proven potential, they won’t fund the basic science required to prove that potential.

We started Cultivarium to make it easier for any researcher to explore non-model microbes.

Cultivarium is trying to relieve the pain associated with using non-model microbial organisms. We are developing open source tools and assays designed for use in multiple microbes to minimize trial-and-error time in new species.

We are a new type of nonprofit startup for science research and development: a Focused Research Organization (FRO). That means we are a non-profit organization that thinks and works like a startup. This unique structure helps us effectively invest time and resources into solving the foundational problem in the field of non-model organisms and to release open-source data, protocols, and tools on our portal for the benefit of the scientific community. We couldn’t be more excited to achieve these goals through team-based science.

Sounds like a nice way to do science? It is. We invite you to tell us what you think, use our tools, and expand our collective knowledge of the biosphere.