Chang Liu, Ph.D. - US grants

? DESCRIPTION (provided by applicant): 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.

? DESCRIPTION (provided by applicant): 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.

Project Summary/Abstract Cells that can count how many times they have cycled would be widely applicable both as research tools to study variations in cell cycle control and as control systems for activating synthetic genetic programs after a defined delay. We propose to develop a genetic device that achieves both programmable and accurate cell cycle counting in human cells. To achieve programmability so that the maximum count can be extended at will, we will use sequence programmable CRISPR guide RNAs to record and execute each counting step. To achieve accuracy, we will arrange these steps so that two CRISPR enzymes execute alternating steps, and we will separate these steps temporally by co-opting a natural circuit by which cells limit DNA replication to once per cell cycle. At the end of this study, we will have advanced genetic counter design to a stage where counters can be employed for certain basic science applications in human cells, and will have revealed the ways in which the counter can be further developed so that it is sufficiently robust for long-term biological and therapeutic applications.

Project Summary/Abstract It is hard to overstate the importance of monoclonal antibodies in the life sciences. Antibodies are critical tools in biomedical research and diagnostics (e.g. western blotting, immunoprecipitation, cytometry, biomarker discovery, and histology), are one of the most rapidly growing class of therapeutics, and are the basis for myriad new strategies in cancer therapy, such as checkpoint inhibitors that are revolutionizing treatment. Unfortunately, current methods for the generation of custom antibodies, including animal immunization and phage display, are slow, costly, inaccessible to most researchers, and often unsuccessful. We propose Autonomously EvolvinG Yeast-displayed antibodieS (AEGYS), a system for the continuous and rapid evolution of high-quality antibodies against custom antigens that requires only the simple culturing of yeast cells. We believe this can be achieved by combining cutting-edge generative machine learning algorithms for antibody library design with a new technology for in vivo continuous evolution and a yeast antigen-presenting cell that we will engineer. If successful, AEGYS should have a transformative impact across the whole of biomedicine by turning monoclonal antibody generation into a rapid, scalable, and accessible process where any lab with standard molecular biology capabilities can generate custom antibodies on demand simply by ?immunizing? a test tube of yeast cells with an antigen. We anticipate that this democratization of antibody generation will also result in an explosion of crowdsourced antibody sequence data that will train our machine learning algorithms to design better antibody libraries for AEGYS, starting a virtuous cycle. We ourselves will use AEGYS to generate a panel of subtype- and conformation-specific nanobodies against biogenic amine receptors including those that respond to acetylcholine, adrenaline, dopamine, and other neurotransmitters, so that we can understand their role in neurobiology and addiction.!

Project Summary/Abstract Over the past five years, my lab has made significant strides in the development of genetic systems capable of driving the rapid mutation and evolution of user-selected genes of interest in vivo. These systems have allowed us and others to quickly and scalably evolve enzymes, proteins, and antibodies to address a range of problems spanning from studying drug resistance to creating affinity reagents on demand. These systems have also begun to allow us to use rapid mutational accumulation as a method for tracing cell lineage in developing animals. One of our key accomplishments has been the invention of an orthogonal DNA replication system (OrthoRep). In OrthoRep, an error-prone orthogonal DNA polymerase (DNAP) exclusively replicates a special cytosolic plasmid encoding only genes of interest (GOIs), driving their continuous evolution fully in vivo. This MIRA will integrate our lab?s work on OrthoRep and support its further development and application in the next five years. In particular, we will grow the core OrthoRep technology in order to accelerate GOI evolution in yeast even more than we currently have, attempt to establish OrthoRep in mammalian cells in order to extend the range of problems OrthoRep can directly address, apply OrthoRep to the engineering of bespoke Cas9s to extend the range and efficacy of targeting, apply OrthoRep to improve the capabilities of a lineage tracing tool developed by my lab, and apply OrthoRep to the generation of mutually orthogonal collections of aminoacyl- tRNA synthetase (aaRS)/tRNA pairs to support genetic code expansion efforts also ongoing in my lab. We hope the set of activities proposed for this MIRA will solidify OrthoRep as an exceptionally powerful genetic system for evolving enzymes and proteins capable of solving high-reward problems in the chemical, biological, and biomedical sciences.

I. Project Summary/Abstract Over the past five years, my lab has made significant strides in the development of genetic systems capable of driving the rapid mutation and evolution of user-selected genes of interest in vivo. These systems have allowed us and others to quickly and scalably evolve enzymes, proteins, and antibodies to address a range of problems spanning from studying drug resistance to creating affinity reagents on demand. These systems have also begun to allow us to use rapid mutational accumulation as a method for tracing cell lineage in developing animals. One of our key accomplishments has been the invention of an orthogonal DNA replication system (OrthoRep). In OrthoRep, an error-prone orthogonal DNA polymerase (DNAP) exclusively replicates a special cytosolic plasmid encoding only genes of interest (GOIs), driving their continuous evolution fully in vivo. The parent MIRA grant will integrate our lab?s work on OrthoRep and support its further development and application in the next five years. In particular, we will grow the core OrthoRep technology in order to accelerate GOI evolution in yeast even more than we currently have, attempt to establish OrthoRep in mammalian cells in order to extend the range of problems OrthoRep can directly address, apply OrthoRep to the engineering of bespoke Cas9s to extend the range and efficacy of targeting, apply OrthoRep to improve the capabilities of a lineage tracing tool developed by my lab, and apply OrthoRep to the generation of mutually orthogonal collections of aminoacyl- tRNA synthetase (aaRS)/tRNA pairs to support genetic code expansion efforts also ongoing in my lab. We hope the set of activities proposed for this MIRA will solidify OrthoRep as an exceptionally powerful genetic system for evolving enzymes and proteins capable of solving high-reward problems in the chemical, biological, and biomedical sciences.