CRISPR Journal最新文献

Small Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR-associated (Cas) effectors are key to developing gene editing therapies due to the packaging constraints of viral vectors. While Cas9 and Cas12a CRISPR-Cas effectors have advanced into select clinical applications, their size is prohibitive for efficient delivery of both nuclease and guide RNA in a single viral vector. Type V Cas12f effectors present a solution given their small size. In this study, we describe a novel set of miniature (<490AA) Cas12f nucleases that cleave double-stranded DNA in human cells. We determined their optimal trans-activating RNA empirically through rational modifications, which resulted in an optimal single guide RNA. We show that these nucleases have broad protospacer adjacent motif (PAM) preferences, allowing for expanded genome targeting. The unique characteristics of these novel nucleases add to the diversity of the miniature CRISPR-Cas toolbox while the expanded PAM allows for the editing of genomic locations that could not be accessed with existing Cas12f nucleases.

The first fruits of the CRISPR-Cas revolution are starting to enter the clinic, with gene editing therapies offering solutions to previously incurable genetic diseases. The success of such applications hinges on control over the mutations that are generated, which are known to vary depending on the targeted locus. In this review, we present the current state of understanding and predicting CRISPR-Cas cutting, base editing, and prime editing outcomes in mammalian cells. We first provide an introduction to the basics of DNA repair and machine learning that the models rely on. We then overview the datasets and methods created for characterizing edits at scale, as well as the insights that have been derived from them. The predictions generated from these models serve as a foundation for designing efficient experiments across the broad contexts where these tools are applied.

The CRISPR-Cas9 system has been deployed for precision mutagenesis in an ever-growing number of species, including agricultural crops and forest trees. Its application to closely linked genes with extremely high sequence similarities has been less explored. In this study, we used CRISPR-Cas9 to mutagenize a tandem array of seven Nucleoredoxin1 (NRX1) genes spanning ∼100 kb in Populus tremula × Populus alba. We demonstrated efficient multiplex editing with one single guide RNA in 42 transgenic lines. The mutation profiles ranged from small insertions and deletions and local deletions in individual genes to large genomic dropouts and rearrangements spanning tandem genes. We also detected complex rearrangements including translocations and inversions resulting from multiple cleavage and repair events. Target capture sequencing was instrumental for unbiased assessments of repair outcomes to reconstruct unusual mutant alleles. The work highlights the power of CRISPR-Cas9 for multiplex editing of tandemly duplicated genes to generate diverse mutants with structural and copy number variations to aid future functional characterization.

The worldwide proliferation of the SARS-CoV-2 virus in the past 3 years has allowed the virus to accumulate numerous mutations. Dangerous lineages have emerged one after another, each leading to a new wave of the pandemic. In this study, we have developed the THRASOS pipeline to rapidly discover lineage-specific mutation signatures and thus advise the development of Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-based diagnostic tests. We also optimized a strategy to modify loop-mediated isothermal amplification amplicons for downstream use with Cas12 and Cas13 for future multiplexing. The close ancestry of the BA.1 and BA.2 variants of SARS-CoV-2 (Omicron) made these excellent candidates for the development of a first test using this workflow. With a quick turnaround time and low requirements for laboratory equipment, the test we have created is ideally suited for settings such as mobile clinics lacking equipment such as Next-Generation Sequencers or Sanger Sequencers and the personnel to run these devices.

Almost all of Earth's oceans are now impacted by multiple anthropogenic stressors, including the spread of nonindigenous species, harmful algal blooms, and pathogens. Early detection is critical to manage these stressors effectively and to protect marine systems and the ecosystem services they provide. Molecular tools have emerged as a promising solution for marine biomonitoring. One of the latest advancements involves utilizing CRISPR-Cas technology to build programmable, rapid, ultrasensitive, and specific diagnostics. CRISPR-based diagnostics (CRISPR-Dx) has the potential to allow robust, reliable, and cost-effective biomonitoring in near real time. However, several challenges must be overcome before CRISPR-Dx can be established as a mainstream tool for marine biomonitoring. A critical unmet challenge is the need to design, optimize, and experimentally validate CRISPR-Dx assays. Artificial intelligence has recently been presented as a potential approach to tackle this challenge. This perspective synthesizes recent advances in CRISPR-Dx and machine learning modeling approaches, showcasing CRISPR-Dx potential to progress as a rising molecular tool candidate for marine biomonitoring applications.

CRISPR-Cas systems provide immunity against mobile genetic elements (MGEs) through sequence-specific targeting by spacer sequences encoded in CRISPR arrays. Spacers are highly variable between microbial strains and can be acquired rapidly, making them well suited for use in strain typing of closely related organisms. However, no tools are currently available to automate the process of reconstructing strain histories using CRISPR spacers. We therefore developed the CRISPR Comparison Toolkit (CCTK) to enable analyses of array relationships. The CCTK includes tools to identify arrays, analyze relationships between arrays using CRISPRdiff and CRISPRtree, and predict targets of spacers. CRISPRdiff visualizes arrays and highlights the similarities between them. CRISPRtree infers a phylogenetic tree from array relationships and presents a hypothesis of the evolutionary history of the arrays. The CCTK unifies several CRISPR analysis tools into a single command line application, including the first tool to infer phylogenies from array relationships.