3 research outputs found

    p53 Gene Repair with Zinc Finger Nucleases Optimised by Yeast 1-Hybrid and Validated by Solexa Sequencing

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    The tumor suppressor gene p53 is mutated or deleted in over 50% of human tumors. As functional p53 plays a pivotal role in protecting against cancer development, several strategies for restoring wild-type (wt) p53 function have been investigated. In this study, we applied an approach using gene repair with zinc finger nucleases (ZFNs). We adapted a commercially-available yeast one-hybrid (Y1H) selection kit to allow rapid building and optimization of 4-finger constructs from randomized PCR libraries. We thus generated novel functional zinc finger nucleases against two DNA sites in the human p53 gene, near cancer mutation ‘hotspots’. The ZFNs were first validated using in vitro cleavage assays and in vivo episomal gene repair assays in HEK293T cells. Subsequently, the ZFNs were used to restore wt-p53 status in the SF268 human cancer cell line, via ZFN-induced homologous recombination. The frequency of gene repair and mutation by non-homologous end-joining was then ascertained in several cancer cell lines, using a deep sequencing strategy. Our Y1H system facilitates the generation and optimisation of novel, sequence-specific four- to six-finger peptides, and the p53-specific ZFN described here can be used to mutate or repair p53 in genomic loci

    The propagation of perturbations in rewired bacterial gene networks.

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    What happens to gene expression when you add new links to a gene regulatory network? To answer this question, we profile 85 network rewirings in E. coli. Here we report that concerted patterns of differential expression propagate from reconnected hub genes. The rewirings link promoter regions to different transcription factor and σ-factor genes, resulting in perturbations that span four orders of magnitude, changing up to ∼70% of the transcriptome. Importantly, factor connectivity and promoter activity both associate with perturbation size. Perturbations from related rewirings have more similar transcription profiles and a statistical analysis reveals ∼20 underlying states of the system, associating particular gene groups with rewiring constructs. We examine two large clusters (ribosomal and flagellar genes) in detail. These represent alternative global outcomes from different rewirings because of antagonism between these major cell states. This data set of systematically related perturbations enables reverse engineering and discovery of underlying network interactions.Funding was provided by FP7 ERC 201249 ZINC-HUBS (R.B.), Spanish grants MICINNBFU2010-17953 (M.I.), MINECO TIN2011-22826 (R.C., S.H.), ISCIII COMBIOMEDRD07/0067/0001 (R.C., S.H.). Y.S. was funded by a Swiss National Science FoundationFellowship (PBSKP3_134331/1) and by the Marie Curie Action (FP7 PIEF-GA-2011-298348). M.I. was funded by New Investigator Award No. WT102944 from theWellcome Trust U

    The propagation of perturbations in rewired bacterial gene networks.

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    What happens to gene expression when you add new links to a gene regulatory network? To answer this question, we profile 85 network rewirings in E. coli. Here we report that concerted patterns of differential expression propagate from reconnected hub genes. The rewirings link promoter regions to different transcription factor and σ-factor genes, resulting in perturbations that span four orders of magnitude, changing up to ∼70% of the transcriptome. Importantly, factor connectivity and promoter activity both associate with perturbation size. Perturbations from related rewirings have more similar transcription profiles and a statistical analysis reveals ∼20 underlying states of the system, associating particular gene groups with rewiring constructs. We examine two large clusters (ribosomal and flagellar genes) in detail. These represent alternative global outcomes from different rewirings because of antagonism between these major cell states. This data set of systematically related perturbations enables reverse engineering and discovery of underlying network interactions.Funding was provided by FP7 ERC 201249 ZINC-HUBS (R.B.), Spanish grants MICINNBFU2010-17953 (M.I.), MINECO TIN2011-22826 (R.C., S.H.), ISCIII COMBIOMEDRD07/0067/0001 (R.C., S.H.). Y.S. was funded by a Swiss National Science FoundationFellowship (PBSKP3_134331/1) and by the Marie Curie Action (FP7 PIEF-GA-2011-298348). M.I. was funded by New Investigator Award No. WT102944 from theWellcome Trust U
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