Exogenous DNA can be a template to precisely edit a cell’s genome. However, the delivery of in vitro -produced DNA to target cells can be inefficient, and low abundance of template DNA may underlie the low rate of precise editing. One potential tool to produce template DNA inside cells is a retron, a bacterial retroelement involved in phage defense. However, little effort has been directed at optimizing retrons to produce designed sequences. Here, we identify modifications to the retron non-coding RNA that result in more abundant reverse transcribed DNA. By testing architectures of the retron operon that enable efficient reverse transcription, we find that gains in DNA production are portable from prokaryotic to eukaryotic cells and result in more efficient genome editing. Finally, we show that retron RT-DNA can be used to precisely edit cultured human cells. These experiments provide a general framework to produce DNA using retrons for genome modification.

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The cumbersome encoding of digital data to cellular DNA hinders the use of cells as living hard drives. A new approach transfers digital information directly into cellular DNA by converting electrical signals into stable and interpretable changes in the genomes of bacterial populations.

Efficient metabolic engineering and the development of mitochondrial therapeutics often rely upon the specific and strong import of foreign proteins into mitochondria. Fusing a protein to a mitochondria-bound signal peptide is a common method to localize proteins to mitochondria, but this strategy is not universally effective, with particular proteins empirically failing to localize. To help overcome this barrier, this work develops a generalizable and open-source framework to design proteins for mitochondrial import and quantify their specific localization. This Python-based pipeline quantitatively assesses the colocalization of different proteins previously used for precise genome editing in a high-throughput manner to reveal signal peptide–protein combinations that localize well in mitochondria.

Efficient metabolic engineering and the development of mitochondrial therapeutics often rely upon the specific and strong import of foreign proteins into mitochondria. Fusing a protein to a mitochondria-bound signal peptide is a common method to localize proteins to mitochondria, but this strategy is not universally effective with particular proteins empirically failing to localize. To help overcome this barrier, this work develops a generalizable and open-source framework to design proteins for mitochondrial import and quantify their specific localization. By using a Python-based pipeline to quantitatively assess the colocalization of different proteins previously used for precise genome editing in a high-throughput manner, we reveal signal peptide-protein combinations that localize well in mitochondria and, more broadly, general trends about the overall reliability of commonly used mitochondrial targeting signals.

Osteosarcoma (OSA) is the most prevalent primary bone tumor and accounts for approximately 2% of childhood cancers. Approximately 40% of all OSA patients succumb to metastatic disease within 5 years. Canine OSA occurs about 10 times more frequently than human OSA and has been shown to be very similar to pediatric OSA biologically, histologically, molecularly, and in treatment. This suggests that canine OSA is an excellent pre-clinical model to investigate better treatment options for metastatic OSA. We compared in-vitro markers of metastatic potential with gene expression data in eight canine OSA cell lines to identify molecular pathways that will be potential chemotherapeutic targets to treat and prevent metastatic OSA. The metastatic potential of 8 canine OSA cell lines was characterized utilizing Incucyte Zoom based migration and invasion scratch wound assays. Gene expression analysis was performed using Affymetrix GeneChip Canine Genome 2.0 Arrays. Genes that were statistically correlated with migratory and invasive phenotypes were used to enrich molecular pathways described in several databases utilizing Enrichr software. Altered pathways and associated targeted agents that would inhibit the pathways enriched by the correlated gene sets were identified. Chemotherapeutics targeting significantly enriched pathways were screened for their ability to inhibit metastatic potential. Dasatinib and Stattic were the only inhibitors screened to date that inhibit migration of the osteosarcoma cell lines at clinically relevant doses. The remaining significantly correlated pathways will be targeted as well as rational combinations of pathways. An orthotopic murine model is currently being tested to further explore the utility of efficacious chemotherapeutics in-vivo. Pathway Inhibition and Anti-Migratory EffectsPathwayP-ValueTargeted AgentIC50 vs MigrationMap Kinase0.0037Selumetinib>25 uM *Focal Adhesion0.0059Dasatinib18 nM - 214 nMErbb2/30.0214Lapatinib>8 uM *TubulinControlPaclitaxel7 nM - 54 nMmTOR0.0054Rapamycin>20 nM *STAT30.0004Stattic2.4 uM - 4.6 uMBMPR2<0.0005Tacrolimus>12.5 nM *ALK<0.0005Crizotinib>900 nM *VEGFR0.0226VandetanibTBDITK<0.0005IbrutinibTBDPDPK10.0011CelecoxibTBD* We were not able to reach an IC50 at clinically relevant doses Citation Format: Laird Klippenstein, Jared S. Fowles, Sierra K. Lear, Daniel L. Gustafson. Identification and utilization of molecular pathways correlated with osteosarcoma metastasis to predict targeted therapies. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 1542.

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