A synthetic biology based cell line engineering pipeline

An ideal host cell line for deriving cell lines of high recombinant protein production should be stable, predictable, and amenable to rapid cell engineering or other forms of phenotypical manipulation. In the past few years we have employed genomic information to identify “safe harbors” for exogenous gene integration in CHO cells, deployed systems modeling and optimization to design pathways and control strategies to modify important aspects of recombinant protein productivity, and established a synthetic biology approach to implement genetic changes, all with the goal of creating a pipeline to produce “designer” cell lines. Chinese hamster ovary (CHO) cells are the preferred platform for protein production. However, the Chinese hamster genome is unstable in its ploidy, is subject to long and short deletions, duplications, and translocations. In addition, gene expression is subject to epigenetic changes including DNA methylation, histone modification and heterochromatin invasion, thus further complicating transgene expression for protein production in cell lines. With these issues in mind, we set out to engineer a CHO cell line highly amenable to stable protein production using a synthetic biology approach. We compiled karyotyping and chromosome number data of several CHO cell lines and sublines, identified genomic regions with high a frequency of gain and loss of copy number using comparative genome hybridization (CGH), and verified structural variants using sequencing data. We further used ATAC (Assay for Transposase-Accessible Chromatin) sequencing to study chromatin accessibility and epigenetic stability within the CHO genome. RNA-seq data from multiple cell lines were also used to identify regions with high transcriptional activity. Analysis of these data allowed the identification of several “safe harbor” loci that could be used for cell engineering. Based on results of the data analysis and identification of “safe harbors”, we engineered an IgG producing cell line with a single copy of the product transgene as a template cell line. This product gene site is flanked by sequences for recombinase mediated cassette exchange, therefore allowing easy substitution of the IgG producing gene for an alternative product gene. Furthermore, a “landing pad” for multi-gene cassette insertion was integrated into the genome at an additional site. Together, these sites allowed engineering of new cell lines producing a fusion protein and Erythropoietin to be generated from the template cell line. To enable rapid assembly of product transgenes and genetic elements for engineering cell attributes into multi-gene cassettes, we adopted a golden-gate based synthetic biology approach. The assembly of genetic parts into multi-gene cassettes in a LEGO-like fashion allowed different combinations of genes under the control of various promoters to be generated quickly for introduction into the template cell line. Using this engineered CHO cell line, we set out to study metabolism and product protein glycosylation for cell engineering. To guide the selection of genetic elements for cell engineering, we developed a multi-compartment kinetic model, as well as a flux model of energy metabolism and glycosylation. The transcriptome meta-data was used extensively to identify genes and isoforms expressed in the cell line and to estimate the enzyme levels in the model. The flux model was used to identify and the LEGO-like platform was used to implement the genetic changes that can alter the glycosylation pattern of the IgG produced by the template cell line. Concurrently we employed a systems optimization approach to identify the genetic alterations in the metabolic pathway to guide cell metabolism toward a favorable state. The model prediction is being implemented experimentally using the synthetic biology approach. In conclusion, we have illustrated a pipeline of rational cell line engineering that integrates genomic science, systems engineering and synthetic biology approaches. The promise, the technical challenges and possible limitations will be discussed in this presentation

Synthetic biology to access and expand nature's chemical diversity

Bacterial genomes encode the biosynthetic potential to produce hundreds of thousands of complex molecules with diverse applications, from medicine to agriculture and materials. Accessing these natural products promises to reinvigorate drug discovery pipelines and provide novel routes to synthesize complex chemicals. The pathways leading to the production of these molecules often comprise dozens of genes spanning large areas of the genome and are controlled by complex regulatory networks with some of the most interesting molecules being produced by non-model organisms. In this Review, we discuss how advances in synthetic biology — including novel DNA construction technologies, the use of genetic parts for the precise control of expression and for synthetic regulatory circuits — and multiplexed genome engineering can be used to optimize the design and synthesis of pathways that produce natural products

Minimum Information about a Biosynthetic Gene cluster

A wide variety of enzymatic pathways that produce specialized metabolites in bacteria, fungi and plants are known to be encoded in biosynthetic gene clusters. Information about these clusters, pathways and metabolites is currently dispersed throughout the literature, making it difficult to exploit. To facilitate consistent and systematic deposition and retrieval of data on biosynthetic gene clusters, we propose the Minimum Information about a Biosynthetic Gene cluster (MIBiG) data standard.Chemistry and Chemical Biolog

Simulation Modeling to Compare High-Throughput, Low-Iteration Optimization Strategies for Metabolic Engineering

Increasing the final titer of a multi-gene metabolic pathway can be viewed as a multivariate optimization problem. While numerous multivariate optimization algorithms exist, few are specifically designed to accommodate the constraints posed by genetic engineering workflows. We present a strategy for optimizing expression levels across an arbitrary number of genes that requires few design-build-test iterations. We compare the performance of several optimization algorithms on a series of simulated expression landscapes. We show that optimal experimental design parameters depend on the degree of landscape ruggedness. This work provides a theoretical framework for designing and executing numerical optimization on multi-gene systems

Genetic engineering of sex chromosomes for batch cultivation of non-transgenic, sex-sorted males.

The field performance of Sterile Insect Technique (SIT) is improved by sex-sorting and releasing only sterile males. This can be accomplished by resource-intensive separation of males from females by morphology. Alternatively, sex-ratio biasing genetic constructs can be used to selectively remove one sex without the need for manual or automated sorting, but the resulting genetically engineered (GE) control agents would be subject to additional governmental regulation. Here we describe and demonstrate a genetic method for the batch production of non-GE males. This method could be applied to generate the heterogametic sex (XY, or WZ) in any organism with chromosomal sex determination. We observed up to 100% sex-selection with batch cultures of more than 103 individuals. Using a stringent transgene detection assay, we demonstrate the potential of mass production of transgene free males

Predicting thresholds for population replacement gene drives

Abstract Background Threshold-dependent gene drives (TDGDs) could be used to spread desirable traits through a population, and are likely to be less invasive and easier to control than threshold-independent gene drives. Engineered Genetic Incompatibility (EGI) is an extreme underdominance system previously demonstrated in Drosophila melanogaster that can function as a TDGD when EGI agents of both sexes are released into a wild-type population. Results Here we use a single generation fitness assay to compare the fecundity, mating preferences, and temperature-dependent relative fitness to wild-type of two distinct genotypes of EGI agents. We find significant differences in the behavior/performance of these EGI agents that would not be predicted a priori based on their genetic design. We report a surprising temperature-dependent change in the predicted threshold for population replacement in an EGI agent that drives ectopic expression of the developmental morphogen pyramus. Conclusions The single-generation fitness assay presented here could reduce the amount of time required to estimate the threshold for TDGD strategies for which hybrid genotypes are inviable. Additionally, this work underscores the importance of empirical characterization of multiple engineered lines, as behavioral differences can arise in unique genotypes for unknown reasons

Engineered Streptomyces platensis Strains That Overproduce Antibiotics Platensimycin and Platencin▿

Platensimycin, which is isolated from Streptomyces platensis MA7327, and platencin, which is isolated from S. platensis MA7339, are two recently discovered natural products that serve as important antibiotic leads. Here we report on the identification of S. platensis MA7327 as a dual producer of both platensimycin and platencin. A PCR-based approach was used to locate and clone the locus involved in platensimycin and platencin production, including ptmR1, which encodes a putative GntR-like transcriptional regulator. Deletion of this gene from the producing organism allowed us to isolate strains that overproduce platensimycin and platencin with yields of 323 ± 29 mg/liter and 255 ± 30 mg/liter, respectively. These results illustrate the effectiveness of genetic manipulation for the rational engineering of improvements in titers

Presentation_1_Modeling-informed Engineered Genetic Incompatibility strategies to overcome resistance in the invasive Drosophila suzukii.pdf

Engineered Genetic Incompatibility (EGI) is an engineered extreme underdominance genetic system wherein hybrid animals are not viable, functioning as a synthetic speciation event. There are several strategies in which EGI could be leveraged for genetic biocontrol of pest populations. We used an agent-based model of Drosophila suzukii (Spotted Wing Drosophila) to determine how EGI would fare with high rates of endemic genetic resistance alleles. We discovered a surprising failure mode wherein field-generated females convert an incompatible male release program into a population replacement gene drive. Local suppression could still be attained in two seasons by tailoring the release strategy to take advantage of this effect, or alternatively in one season by altering the genetic design of release agents. We show in this work that data from modeling can be utilized to recognize unexpected emergent phenomena and a priori inform genetic biocontrol treatment design to increase efficacy.</p