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Exploiting CRISPR-Cas nucleases to produce sequence-specific antimicrobials.

ABSTRACT: Antibiotics target conserved bacterial cellular pathways or growth functions and therefore cannot selectively kill specific members of a complex microbial population. Here, we develop programmable, sequence-specific antimicrobials using the RNA-guided nuclease Cas9 (refs.1,2) delivered by a bacteriophage. We show that Cas9, reprogrammed to target virulence genes, kills virulent, but not avirulent, Staphylococcus aureus. Reprogramming the nuclease to target antibiotic resistance genes destroys staphylococcal plasmids that harbor antibiotic resistance genes and immunizes avirulent staphylococci to prevent the spread of plasmid-borne resistance genes. We also show that CRISPR-Cas9 antimicrobials function in vivo to kill S. aureus in a mouse skin colonization model. This technology creates opportunities to manipulate complex bacterial populations in a sequence-specific manner.

SUBMITTER: Bikard D

PROVIDER: S-EPMC4317352 | biostudies-literature | 2014 Nov

REPOSITORIES: biostudies-literature

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Exploiting CRISPR-Cas nucleases to produce sequence-specific antimicrobials.

Bikard David D Euler Chad W CW Jiang Wenyan W Nussenzweig Philip M PM Goldberg Gregory W GW Duportet Xavier X Fischetti Vincent A VA Marraffini Luciano A LA

Nature biotechnology 20141005 11

Antibiotics target conserved bacterial cellular pathways or growth functions and therefore cannot selectively kill specific members of a complex microbial population. Here, we develop programmable, sequence-specific antimicrobials using the RNA-guided nuclease Cas9 (refs.1,2) delivered by a bacteriophage. We show that Cas9, reprogrammed to target virulence genes, kills virulent, but not avirulent, Staphylococcus aureus. Reprogramming the nuclease to target antibiotic resistance genes destroys st ...[more]

PMID: 25282355

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Project description:BackgroundGenome editing technologies developed around the CRISPR-Cas9 nuclease system have facilitated the investigation of a broad range of biological questions. These nucleases also hold tremendous promise for treating a variety of genetic disorders. In the context of their therapeutic application, it is important to identify the spectrum of genomic sequences that are cleaved by a candidate nuclease when programmed with a particular guide RNA, as well as the cleavage efficiency of these sites. Powerful new experimental approaches, such as GUIDE-seq, facilitate the sensitive, unbiased genome-wide detection of nuclease cleavage sites within the genome. Flexible bioinformatics analysis tools for processing GUIDE-seq data are needed.ResultsHere, we describe an open source, open development software suite, GUIDEseq, for GUIDE-seq data analysis and annotation as a Bioconductor package in R. The GUIDEseq package provides a flexible platform with more than 60 adjustable parameters for the analysis of datasets associated with custom nuclease applications. These parameters allow data analysis to be tailored to different nuclease platforms with different length and complexity in their guide and PAM recognition sequences or their DNA cleavage position. They also enable users to customize sequence aggregation criteria, and vary peak calling thresholds that can influence the number of potential off-target sites recovered. GUIDEseq also annotates potential off-target sites that overlap with genes based on genome annotation information, as these may be the most important off-target sites for further characterization. In addition, GUIDEseq enables the comparison and visualization of off-target site overlap between different datasets for a rapid comparison of different nuclease configurations or experimental conditions. For each identified off-target, the GUIDEseq package outputs mapped GUIDE-Seq read count as well as cleavage score from a user specified off-target cleavage score prediction algorithm permitting the identification of genomic sequences with unexpected cleavage activity.ConclusionThe GUIDEseq package enables analysis of GUIDE-data from various nuclease platforms for any species with a defined genomic sequence. This software package has been used successfully to analyze several GUIDE-seq datasets. The software, source code and documentation are freely available at http://www.bioconductor.org/packages/release/bioc/html/GUIDEseq.html .

Dataset Information

Exploiting CRISPR-Cas nucleases to produce sequence-specific antimicrobials.

Publications

Exploiting CRISPR-Cas nucleases to produce sequence-specific antimicrobials.

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