Unlocking molecular diversity from DNA

 
 
 
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Cell-free synthetic biology

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What iT IS

The basic premise of cell-free synthetic biology is to utilize the components of a living cell, but not necessarily the cell itself, for understanding biological phenomena or making things from biology. While cells are great at self-replication, engineering and manipulating them can be a challenge.

history

Cell-free synthetic biology is built off of an old technology, cell-free systems. Simply, DNA gets transcribed to mRNA and translated to protein in a cell-free system. Before we knew about manipulating cells, we used cell-free systems to understand biology. In fact, the Nobel Prize in 1968 was given for the utilization of cell-free systems to decipher the amino acid code.

WHAT WE’VE DONE

Tierra has been perfecting the science of making cell-free systems, starting from technology originally developed by its founders at Caltech and supported by DARPA. We uniquely have multiple cell-free systems representing the diversity of life, spanning gram-positive, gram-negative, and eukaryotic species. Our cell-free systems are optimized for conducting complex biochemistry. We combine multiple cell-free systems with automation, metagenomics, and learning to build our platform.

 

Making molecules, not just predicting them

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MULTIPLE SHOTS ON GOAL VS. CELLS

Going from DNA to molecule in cells is an inherently experimental and time-consuming process. Even with the best automation, the time for cells to grow, protein expression toxicity, and the compatibility of the cell are all uncontrollable variables. This leads to high failure rates (50%+), high recurring costs ($100/attempt), and low throughput (1 fermentation).

In our cell-free platform, each micro-fermentation takes 8 hours or less and scales by liquid handling to 1,000/day. Because cell-free systems are open systems, we can experimentally change conditions and add additives to tune protein expression and molecule production. Changing cell compatibility is as simple as changing our extracts. This means exponentially more shots on goal to successfully produce proteins and molecules.

MAKING STUFF VS. THEORY

Simply put, every run of our platform makes an end material - a molecule. This means that compared to purely theoretical approaches, every data point our system generates is experimentally validated and tied to a physical, testable material. In biology, the gold standard is an activity assay, or identifying what a molecule does. Our data is intricately tied to material to conduct downstream testing.

Scalable production

Tierra can scale production of identified enzymes and small molecules from the micro-scale (uL, ug) to testing scale (mL, mg). The most valuable materials can be deployed at (L, kg) scale.

 

Real, actionable, and consistent data

DEEP INSIGHT INTO PROTEIN EXPRESSION DYNAMICS

Every reaction produces data characterizing transcription, translation, and protein production. This lets us obtain information on all reactions, not just those that work.

Consistent DATA AND CLOSED-LOOP LEARNING

Our cell-free systems are a reagent, not a living organism. Utilizing extensive QA/QC and automation, we can generate validated data that is consistent run-to-run, letting us conduct closed-loop learning an a manner impossible to do with cells.

 
 

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