Integrating automation with synthetic biology expertise, Davide Annese in the Earlham Biofoundry. is helping the bioscience community reduce manual labour, speed up process, and increase precision.
When Davide Annese first stepped inside the Earlham Biofoundry, he was a synthetic biology researcher at the University of Cambridge, looking to streamline the time-consuming, labour-intensive process of generating large numbers of transgenic plants. Seeking a solution, he turned to the Biofoundry to help him develop a semi-automated pipeline for transforming Agrobacterium, dramatically reducing manual labour and speeding up the process.
Inspired by the potential of automation to accelerate synthetic and engineering biology, Davide joined the Earlham Biofoundry in early 2025. He now creates automated robotic workflows for the bioscience community, helping them to navigate some of the same hurdles he once faced.
“Automation is a big step forwards for engineering biology,” says Davide. “It can significantly increase speed, throughput and accuracy compared with manual workflows.
For example, in a past project at the University of Cambridge, we were screening a library of around 400 transcription factors, which involved a repetitive process of assembling plasmids, transforming them sequentially into E. coli, Agrobacterium and plants, and then carrying out the screening.
Doing this all manually took more than nine months, but by automating the Agrobacterium transformation at the Biofoundry, we can now do the same in just a month or two, leaving us more time to focus on downstream analysis.”
Davide Annese, left, with Carolina Grandellis, Head of the Earlham Biofoundry, right.
By integrating mechanical pipetting with automated heating, mixing and shaking, robotic workflows eliminate human errors and increase the accuracy and reproducibility of experiments. This precision allows reaction volumes to be reduced, cutting down reagent costs and the quantity of DNA needed, making high-throughput synthetic biology far more affordable for smaller laboratories.
Davide’s time is now split between automation, the wet lab and the office. He particularly enjoys scripting the robotic platforms – translating manual protocols designed for humans into machine-readable code. Alongside programming, he runs and maintains the equipment, ensuring that it is calibrated and working correctly. He also has the daily challenge of troubleshooting pipelines, which often involves liaising with colleagues and the automation platforms’ manufacturers.
Beyond the lab, Davide works directly with researchers from industry and academia, using a consultative approach to understand their needs and guide them.
“When we have a new project or enquiry, we usually kick off with a couple of meetings to establish the client or collaborator’s objectives, how many samples they have and how often they want to run them,” Davide says. “These meetings enable us to share our expertise, assess whether automation is the best solution and discuss what we can do to help them.”
Because developing automated pipelines takes time and money, unviable or risky workflows may not be worth the investment. “Once I see a protocol, I can usually tell whether it’s something we can automate,” he points out. “We’re very open and honest about what’s possible, so having these early conversations means our insights can help users decide what’s best for them.”
The Biofoundry has a flexible service model so, once a pipeline is established, users can either access the platforms and run the experiments themselves or hand over to Davide and the team to run them.
Having a specialist on hand is essential for keeping operations running smoothly and solving problems whenever they arise. While most biofoundries employ automation experts, Davide’s mix of automation and biology expertise is particularly valuable. "If you only have an engineer, they might not be able to recognise whether an issue is down to a technical problem with the robot or a fundamental biological process,” he explains. “Because I understand the science as well as the machinery, we can troubleshoot on site in real time. I usually know straight away whether an error has spoiled a sample or if it’s recoverable, saving precious time.”
Automation is a big step forwards for engineering biology, it can significantly increase speed, throughput and accuracy compared with manual workflows.
The Earlham Biofoundry also benefits from its location at Norwich Research Park. The campus brings together world-class plant, crop, food and health sciences, alongside core strengths in genomics and bioinformatics, which has enabled the Biofoundry to establish a clear niche in plant engineering biology and agricultural biotechnology.
“No other UK biofoundry has such a high density of plant and crop researchers right on its doorstep,” Davide highlights. “Having access to that specialist expertise – working alongside neighbours like the John Innes Centre and The Sainsbury Laboratory – puts us in an ideal position to help solve complex agricultural challenges by integrating high-throughput and automation into plant biotechnology.”
Davide and colleagues across Earlham Institute are currently co-leading a project aiming to create artificial chromosomes for potato, in collaboration with the John Innes Centre and the University of Manchester. These could allow researchers to stack multiple genes for useful traits such as disease resistance, drought resistance and salt tolerance.
The project addresses two common challenges in plant biotechnology. “Researchers typically rely on the same few regulatory elements, but when you introduce multiple copies, it often triggers gene silencing,” Davide explains. “At the same time, we need to drive gene expression in specific tissues while keeping it lower elsewhere, as overexpression can be toxic. So it’s critical to choose the right regulatory sequences.”
To characterise how different regulatory elements behave under various conditions, the Biofoundry developed a high-throughput automated pipeline to rapidly build a combinatorial library of promoters and terminators from potato. The team has already generated around 100 constructs and is now working closely with Norwich-based biotech non-profit 2Blades to test the constructs in plant cell assays.
Looking ahead, advances in artificial intelligence (AI) are opening up new possibilities for laboratory automation. In library screening, for example, predictive modelling can help narrow down which variants are likely to perform most efficiently, reducing the number of physical samples to screen by several fold. At the same time, AI-powered scripting tools can translate natural-language protocols into machine-readable code in hours rather than days.
“It’s such a fast-moving area, which makes it an exciting space to work in,” says Davide. “There’s always something new to learn.”
Earlham Institute is expanding its AI capabilities, with two new research leaders in this space recently appointed and collaborative links to computational expertise across the Research Park. For Davide and colleagues, the next step is exploring what AI can unlock for the automated lab.
Authored by Dr Mimi Tanimoto, writing for Earlham Institute
