TeselaGen Mike Fero, CEO of TeselaGen, at SynBioBeta SF 2017.
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TeselaGen: Building the Information Technology Backbone for Synthetic Biology

As synthetic biology continues to come into its own, software is instrumental for transforming the field into a full-blown engineering discipline. TeselaGen is one software startup that is using a platform to shape the future of synbio.

TeselaGen applies principles of thinking from electrical engineering into their enterprise software, allowing users to seamlessly automate the design, building, and testing of DNA constructs. Although TeselaGen is only just starting to roll out the first phases of its multi-modular platform, the startup already has a growing list of industry users, including Dow AgroSciences, Amgen, Genomatica, and Arzeda.

TeselaGen has been collaborating with Dow AgroSciences since April of 2016, when the software startup and the agriculture giant embarked upon a joint endeavor to create a secure and streamlined molecular biology design platform. Their collaboration has been focusing on accelerating discovery and improving the productivity of research into crop protection. In August this year, the two companies publicized the success of their efforts and announced that the project is entering a new phase of development. The new phase of collaboration extends its focus to industrial-scale cloning, as well as making the platform compatible with future implementations of machine learning technology.

The most recent adopter of TeselaGen’s software is computational protein engineering company Arzeda. Beyond merely licensing TeselaGen’s tech, Arzeda will also work with their fellow startup to improve TeselaGen’s design platform. Arzeda will be able to streamline their protein-design workflow while providing TeselaGen insight into Arzeda’s sophisticated computational platform for engineering novel enzymes and metabolic pathways.

Check out our interview with Mike Fero, CEO of TeselaGen, who spoke at SynBioBeta SF 2017:

Why is synthetic biology such an exciting field to be part of at the moment?

I think the CRISPR/Cas9 discovery has changed the landscape significantly. It represents a technological jump that when combined with steady progress in other areas makes for a very dynamic environment for all of us involved in manipulating DNA in some way, shape or form.

Tell us about your background, how did you become interested in biological design automation platforms?

I had a grant from the NIH that enabled me to move my research focus from physics to biology. What an eye opener that was. I was soon drawn not only into the somewhat descriptive discipline of systems biology, but the also very interesting and quite challenging world of biotechnology and its fairly synonymous cousin synthetic biology. I have a great deal of experience with software and automated big data acquisition and analysis systems from my physics days at CERN and SLAC. Bringing that experience to biology seemed like a nice way to contribute to the bio economy and make a positive contribution.

Can you tell us about TeselaGen’s software platforms for biomanufacturing?

Well, we hope to be that platform whereby if you want to touch a piece of DNA, to manipulate it in any way in a forward engineering sense, then you will come to our platform as the starting point.  We are building the platform in four phases. Phase I, the “Design” module, has made it to version 1.0 and is in regular use at our industrial customer sites. Phase II, the “Build” module, is nearing completion right now and Beta will be available by years end. (It is in the Build module where links to automation systems can be made.) Phase III, the “Test” module, will be rolled out in 2018. We have also jump-started the Phase IV “Evolve” module which uses machine learning to help users converge to optimized designs. That work is being done in collaboration with a few select industrial partners.

What challenges persist in your field, and what progress has your team – or other peers – made in overcoming them?

From a software development point of view, it is the rapidly shifting set of frameworks and tools that we can utilize for building web based applications: lots to keep up with!

From a business point of view, we really are inventing a new paradigm for biotechnology. The thinking we are incorporating into our platform comes from electrical engineering, not biology. It takes a bit of engagement to demonstrate just how enabling this way of working really is. I think Dow was very surprised at a ten-fold improvement in productivity. That is the kind of validation we love, real experience that shows just how enabling our platform can be for our customers.

What are the upcoming milestones and long-term priorities for your company?

We have some development milestones and feature requests we are working on with Ag-tech and Industrial-tech partners. All else being equal, we put our customer priorities first. That said, we will also be focusing very sharply over the next 12 months on building a stable, robust architecture behind the basic four-module platform. We are already getting requests for further domain-specific add-on modules focused on particular application areas… so longer term we will start planning and building those add-on modules for things like antibody library design, protein engineering, metabolic engineering, gene editing, and gene stacking. Also, we are not resting on our laurels with version 1.0 of the Design module. It will undergo some big upgrades as we move it from version 1.0 to version 2.0, including a revolutionary hierarchical design-build interface that should enable optimized DNA library construction of any length and combinatorial depth. It will be very cool.


Christine Stevenson

Christine Stevenson is a freelance science writer and adjunct professor of biology at the Maricopa Community Colleges in the Phoenix metropolitan area. She holds an M.S. in Biology from Arizona State University and has a background in both wet lab research and venture capital consulting. She lives in Tempe, AZ with her dogs, cats, chickens, and goat.

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