Evolution is the ultimate design algorithm behind biology and if sped up, could have enormous utility in bioengineering. I propose a unique strategy, called orthogonal replication (OrthoRep), to achieve fast and scalable targeted gene evolution in vivo so that the evolutionary process can be routinely applied for biomolecular engineering. The idea is to create a cell, starting with yeast, that has a second replication system consisting of a special DNA plasmid replicated by a dedicated DNA polymerase (DNAP). The second system would be orthogonal to genomic replication such that the dedicated DNAP (ortho-DNAP) only replicates the special plasmid (ortho-plasmid) and not the host genome. The ortho-DNAP could then be engineered to mutate the ortho-plasmid at rates far exceeding what the genome could tolerate. Our analysis suggests that OrthoRep could accelerate evolution by enormous amounts, as a gene encoded on the ortho-plasmid could in principle be forced to diversify ~106-fold faster than if it were encoded on the genome of yeast. We have successfully established OrthoRep in Saccharomyces cerevisiae, and we will continue its development by engineering highly error- prone ortho-DNAPs to reach maximum rates of asexual gene evolution. We will also add sexual evolution to ortho-plasmid, spurred by fortuitous observations of our ortho-plasmids' natural tendency to recombine. Finally, we will engineer copy number control for the ortho-plasmid to enable a broader array of selectable functions, especially negative selections. Once OrthoRep is developed, I propose to apply it to the rapid evolution of in vivo biosensors. Metabolic engineering has great potential for biomedicine, as it promises to move multi-gene biosynthetic pathways that synthesize complex drugs from dif?cult natural sources into cheap microbial production hosts. However, when a multi-gene biosynthesis pathway is transferred into a microbe, an array of rational and combinatorial optimization steps are inevitably needed. Optimization requires the ability to detect product production, but there are no high-throughput assays capable of this. Our OrthoRep system will remove this key roadblock in metabolic engineering by evolving in vivo biosensors for small molecules of interest nearly on-demand. We will evolve in vivo biosensors for four molecules, taxadiene, casbene, amorphadiene, and parthenolide, whose ef?cient production in yeast offer different challenges to metabolic engineering. Not only will these biosensors be directly useful for microbial production of these drug and drug precursors, lessons learned will help us solidify OrthoRep as a potentially transformative evolutionary engineering technology that can be broadly applied.

Public Health Relevance

Much like recombinant insulin did for protein therapeutics, metabolic engineering promises to usher in an era where complex small molecule drugs are routinely produced in heterologous microbial hosts such as yeast. The proposed work aims to develop and apply a scalable rapid evolution system pioneered by my group to the parallel evolution of several in vivo biosensors that will detect and report on natural products whose cheap biosynthesis is desired. This will streamline the metabolic engineering pipeline, allowing us to realize the promise of metabolic engineering to transform medicine through the cheap production of scarce small molecule drugs.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
NIH Director’s New Innovator Awards (DP2)
Project #
1DP2GM119163-01
Application #
8954098
Study Section
Special Emphasis Panel ()
Program Officer
Gerratana, Barbara
Project Start
2015-09-30
Project End
2020-05-31
Budget Start
2015-09-30
Budget End
2020-05-31
Support Year
1
Fiscal Year
2015
Total Cost
$2,317,500
Indirect Cost
$817,500
Name
University of California Irvine
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
046705849
City
Irvine
State
CA
Country
United States
Zip Code
92697
Liu, Chang C; Jewett, Michael C; Chin, Jason W et al. (2018) Toward an orthogonal central dogma. Nat Chem Biol 14:103-106
Ravikumar, Arjun; Arzumanyan, Garri A; Obadi, Muaeen K A et al. (2018) Scalable, Continuous Evolution of Genes at Mutation Rates above Genomic Error Thresholds. Cell :
Arzumanyan, Garri A; Gabriel, Kristin N; Ravikumar, Arjun et al. (2018) Mutually Orthogonal DNA Replication Systems In Vivo. ACS Synth Biol 7:1722-1729