Project Description

Every system that is genetically engineered harbors a potentially fatal vulnerability. The source of life's great diversity - spontaneous mutation - is for the synthetic biologist the source of constant apprehension and risk. The relentlessness of genetic mutation has discouraged previous attempts at ever overcoming this perpetually looming menace. Whether in a multifaceted genetic circuit or a simple protein expression platform, mutation is inevitable, and once it disrupts function, the organism will no longer experience the burden of transgene expression, causing the mutant to outcompete whatever has the intended sequence. Evolution and mutation work hand in hand to select against the maintenance of synthetic DNA sequences. Indeed, the mantra has been that time, in the form of mutation and evolution, will always find a way to erode and ultimately destroy everything that an engineer builds, no matter how ingeniously it may designed.

This year, here at Vanderbilt iGEM we are fighting back. We are proposing a novel approach based on rationally designed genomic architectures that promises to offer synthetic biologists unprecedented control over the evolutionary stability of their creations. At the heart of our strategy is an advanced computational algorithm that integrates decades worth of scientific data in order to identify and correct the highly-mutation prone 'hotspots' that lurk in every gene. Our strategy has a strong foundation in a rich literature from the fields of cancer biology and others that have annotated and characterized mutation hotspots for almost every conceivable source of mutagen, from ultraviolet radiation to recombination to polymerase errors.

When combined with synthetic DNA technology, our process becomes a simple and reliable optimization that is universally applicable to any coding gene being expressed in any organism. Our project first demonstrates the power of this rational synthetic gene design strategy by employing several canonical as well as highly original protocols for assaying DNA damage and its effects on the stability of artificial genetic elements. From these techniques, we can quantify everything from the selective subset of mutation types occurring on an in vitro level, up to how mutational loss of function translates at the scale of populations of genetically modified organisms.

To complement our work, we have harnessed our algorithm for use in what is becoming one of the most important tools for engineering biological molecules: directed evolution experiments. Not only can our engineered changes increase evolutionary stability in applications such as transgenic bioreactors, but it can also construct gene sequences that are more prone to mutate, thus accelerating studies into how to use evolutionary selection to produce tailored functional modifications to proteins.

Finally, we have investigated ways to build new genetically modified strains that exhibit greatly increased resistance to mutation. Combining our sequence-based strategies with the introduction of exogenous genes and removal of endogenous genes has enabled us to produce an expression platform for synthetic genes that not only has enhanced DNA repair mechanisms, but also has an entire artificial pathway introduced for the elimination of mutant strains from a population.

While any single engineered change to reduce mutation may still fail, when our innovative approaches to modulating evolutionary stability are taken in combination, they offer an unprecedented hope for taming evolutionary entropy. More than a victory for synthetic biology, we prove that through rational design principles- exactly what mutation most virulently tries to uproot- and with enough clever innovations, it is possible to defend against what seemed like an inevitability of nature. Score one for engineering.

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