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Biologically inspired engineering of microorganisms
Jay Konieczka, enEvolv
<https://www.youtube.com/watch?v=VlWj9gfpS5Q&t=0s&list=PLHpV_30XFQ8RN0v_PIiPKnf8c_QHVztFM&index=55>
We engineer microbes to produce products both together with partners and our own proprietary targets. We have technology inside the cell that allows us to build and screen billions of genomic designs in a matter of a month. This is without heavy investment in automation.
The challenge in engineering microbes is the complexity of biology. We're all familiar with the design-build-test-analyze loop. We all know this. As you iterate through this process, you have to be very aware now of-- we're beyond the scope of optimizing a single pathway. We're looking at a whole organism. It requires a tremendous amount of throughput. Our platform does exactly that.
We have variation technology which delivers mutations in a massively parallel fashion. Then we screen the cells on a high-throughput selection mechanism. And then we analyze, characterize and learn from them, and then we influence the net xesign phase.
The variation technology is actually MAGE. It allows us to deliver massively parallel mutations single point mutations and arrays of point mutations, insertions, deletions, at multiple loci in the genome simultaneously. Our cultures have every strain in the culture that are unique from each other. So it's combinatorial and you have to screen through the haystack.
We have allosteric transcription factors that we engineered to recognize specific and desired target molecules. That's how we do sscreening. In some cases, within weeks, we can turn around a sensor or a panel of sensors that respond in different fashions to the production of our target molecules. These drive gene expression. We use reporters or selection markers, like GFP, and those strains that produce more, we can immediately see that in the population and select for that.
The sweet spot is right there at the build and test cycle. If you were to do this with robotics, then you would need like $10M in equipment just to get to 10,000 designs per month. But for us, we can do 1 billion strains per month. This scales linearly. We could do this with traditional automation but it's not necessary.
Our tech is portable. We are in multiple species. Raising series B round. Because of high probability of success, we're taking on projects that we wouldn't do with traditional methods. As a result we're growing and raising our series B round of funding.
# Q&A
Q: .. doing hte permutations all together in one tube. When you're trying to optimize production of something that can float out of the cell and into other cells, can you identify winners?
A: There's a couple of ways we approach that. At the end of the day, when you want to look at an end product that is diffusable, you have to separate the cells, like microencapsulation. There's other tactics sometimes like engineering a sensor for an upstream metabolite that we make sure doesn't leak at least not quickly, and then optimize for that.
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