Proteogenius

What is Proteogenius?

Proteogenius is TFF's generative AI powered pipeline and platform. Generative AI has the potential to revolutionize biology by enabling researchers to synthesize DNA and thus organisms with unprecedented phenotypic ability. DNA is the blueprint of life, containing the genetic information that governs the traits and characteristics of all living organisms. Being able to accurately predict organism characteristics from DNA sequence is the holy grail of biology, and we are applying this technology to the organisms most commonly used as protein production factories - microbes.

Our team has previously developed innovative methods to collect orders of magnitude more DNA sequence data than typically possible. Proteogenius can then analyze these large datasets to identify patterns and predict how different genetic modifications will affect an organism's traits and characteristics. This enables our researchers to generate novel DNA sequences to design organisms with specific traits or characteristics, such as higher protein yields.

Our patented technology can synthesize DNA sequences more efficiently and accurately, testing them in silico before setting foot in a lab. Traditional methods of DNA synthesis can be time-consuming and error-prone, requiring multiple rounds of chemical synthesis and purification. Proteogenius, on the other hand, can synthesize DNA sequences in a single step, using algorithms to optimize the synthesis process and reduce errors. This has the potential to make DNA synthesis faster, cheaper, and more accessible, opening up new possibilities for genetic engineering and synthetic biology.

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Why does creating efficient microbes matter?

For a single input unit of a carbon source, a microbe optimized for precision fermentation will output the maximum amount of protein. What this equals is protein at the lowest input cost possible. This means that proteins previously not commercially cost viable become, for the very first time, practical to produce and brought to market at scale. Learn more about why it matters here.