Comparison of Integrases Identifies Bxb1-GA Mutant as the Most Efficient Site-Specific Integrase System in Mammalian Cells.

Phage-derived integrases can catalyze irreversible, site-specific integration of transgenic payloads into a chromosomal locus, resulting in mammalian cells that stably express transgenes or circuits of interest. Previous studies have demonstrated high-efficiency integration by the Bxb1 integrase in mammalian cells. Here, we show that a point mutation (Bxb1-GA) in Bxb1 target sites significantly increases Bxb1-mediated integration efficiency at the Rosa26 locus in Chinese hamster ovary cells, resulting in the highest integration efficiency reported with a site-specific integrase in mammalian cells. Bxb1-GA point mutant sites do not cross-react with Bxb1 wild-type sites, enabling their use in applications that require orthogonal pairs of target sites. In comparison, we test the efficiency and orthogonality of ϕC31 and Wß integrases, and show that Wß has an integration efficiency between those of Bxb1-GA and wild-type Bxb1. Our data present a toolbox of integrases for inserting payloads such as gene circuits or therapeutic transgenes into mammalian cell lines.

A multi-landing pad DNA integration platform for mammalian cell engineering.

Engineering mammalian cell lines that stably express many transgenes requires the precise insertion of large amounts of heterologous DNA into well-characterized genomic loci, but current methods are limited. To facilitate reliable large-scale engineering of CHO cells, we identified 21 novel genomic sites that supported stable long-term expression of transgenes, and then constructed cell lines containing one, two or three 'landing pad' recombination sites at selected loci. By using a highly efficient BxB1 recombinase along with different selection markers at each site, we directed recombinase-mediated insertion of heterologous DNA to selected sites, including targeting all three with a single transfection. We used this method to controllably integrate up to nine copies of a monoclonal antibody, representing about 100 kb of heterologous DNA in 21 transcriptional units. Because the integration was targeted to pre-validated loci, recombinant protein expression remained stable for weeks and additional copies of the antibody cassette in the integrated payload resulted in a linear increase in antibody expression. Overall, this multi-copy site-specific integration platform allows for controllable and reproducible insertion of large amounts of DNA into stable genomic sites, which has broad applications for mammalian synthetic biology, recombinant protein production and biomanufacturing.

The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.

The systematic translation of cancer genomic data into knowledge of tumour biology and therapeutic possibilities remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacological annotation is available. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacological profiles for 24 anticancer drugs across 479 of the cell lines, this collection allowed identification of genetic, lineage, and gene-expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Together, our results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents. The generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of 'personalized' therapeutic regimens.