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Learning to quantify uncertainty in off-target activity for CRISPR guide RNAs.
CRISPR-based genome editing technologies have revolutionised the field of molecular biology, offering unprecedented opportunities for precise genetic manipulation. However, off-target effects remain a significant challenge, potentially leading to unintended consequences and limiting the applicability of CRISPR-based genome editing technologies in clinical settings. Current literature predominantly focuses on point predictions for off-target activity, which may not fully capture the range of possible outcomes and associated risks. Here, we present crispAI, a neural network architecture-based approach for predicting uncertainty estimates for off-target cleavage activity, providing a more comprehensive risk assessment and facilitating improved decision-making in single guide RNA (sgRNA) design. Our approach makes use of the count noise model Zero Inflated Negative Binomial (ZINB) to model the uncertainty in the off-target cleavage activity data. In addition, we present the first-of-its-kind genome-wide sgRNA efficiency score, crispAI-aggregate, enabling prioritization among sgRNAs with similar point aggregate predictions by providing richer information compared to existing aggregate scores. We show that uncertainty estimates of our approach are calibrated and its predictive performance is superior to the state-of-the-art in silico off-target cleavage activity prediction methods. The tool and the trained models are available at https://github.com/furkanozdenn/crispr-offtarget-uncertainty.
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Paving the way towards precise and safe CRISPR genome editing.
As the possibilities of CRISPR-Cas9 technology have been revealed, we have entered a new era of research aimed at increasing its specificity and safety. This stage of technology development is necessary not only for its wider application in the clinic but also in basic research to better control the process of genome editing. Research during the past eight years has identified some factors influencing editing outcomes and led to the development of highly specific endonucleases, modified guide RNAs and computational tools supporting experiments. More recently, large-scale experiments revealed a previously overlooked feature: Cas9 can generate reproducible mutation patterns. As a result, it has become apparent that Cas9-induced double-strand break (DSB) repair is nonrandom and can be predicted to some extent. Here, we review the present state of knowledge regarding the specificity and safety of CRISPR-Cas9 technology to define gRNA, protein and target-related problems and solutions. These issues include sequence-specific off-target effects, immune responses, genetic variation and chromatin accessibility. We present new insights into the role of DNA repair in genome editing and define factors influencing editing outcomes. In addition, we propose practical guidelines for increasing the specificity of editing and discuss novel perspectives in improvement of this technology.
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CRISPR-GPT for agentic automation of gene-editing experiments.
Performing effective gene-editing experiments requires a deep understanding of both the CRISPR technology and the biological system involved. Meanwhile, despite their versatility and promise, large language models (LLMs) often lack domain-specific knowledge and struggle to accurately solve biological design problems. We present CRISPR-GPT, an LLM agent system to automate and enhance CRISPR-based gene-editing design and data analysis. CRISPR-GPT leverages the reasoning capabilities of LLMs for complex task decomposition, decision-making and interactive human-artificial intelligence (AI) collaboration. This system incorporates domain expertise, retrieval techniques, external tools and a specialized LLM fine tuned with open-forum discussions among scientists. CRISPR-GPT assists users in selecting CRISPR systems, experiment planning, designing guide RNAs, choosing delivery methods, drafting protocols, designing assays and analysing data. We showcase the potential of CRISPR-GPT by knocking out four genes with CRISPR-Cas12a in a human lung adenocarcinoma cell line and epigenetically activating two genes using CRISPR-dCas9 in a human melanoma cell line. CRISPR-GPT enables fully AI-guided gene-editing experiment design and analysis across different modalities, validating its effectiveness as an AI co-pilot in genome engineering.
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Genome editing of bread wheat using biolistic delivery of CRISPR/Cas9 in vitro transcripts or ribonucleoproteins.
This protocol is an extension to: Nat. Protoc. 9, 2395-2410 (2014); doi:10.1038/nprot.2014.157; published online 18 September 2014In recent years, CRISPR/Cas9 has emerged as a powerful tool for improving crop traits. Conventional plant genome editing mainly relies on plasmid-carrying cassettes delivered by Agrobacterium or particle bombardment. Here, we describe DNA-free editing of bread wheat by delivering in vitro transcripts (IVTs) or ribonucleoprotein complexes (RNPs) of CRISPR/Cas9 by particle bombardment. This protocol serves as an extension of our previously published protocol on genome editing in bread wheat using CRISPR/Cas9 plasmids delivered by particle bombardment. The methods we describe not only eliminate random integration of CRISPR/Cas9 into genomic DNA, but also reduce off-target effects. In this protocol extension article, we present detailed protocols for preparation of IVTs and RNPs; validation by PCR/restriction enzyme (RE) and next-generation sequencing; delivery by biolistics; and recovery of mutants and identification of mutants by pooling methods and Sanger sequencing. To use these protocols, researchers should have basic skills and experience in molecular biology and biolistic transformation. By using these protocols, plants edited without the use of any foreign DNA can be generated and identified within 9-11 weeks.
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Balanced Training Sets Improve Deep Learning-Based Prediction of CRISPR sgRNA Activity.
CRISPR-Cas systems have transformed the field of synthetic biology by providing a versatile method for genome editing. The efficiency of CRISPR systems is largely dependent on the sequence of the constituent sgRNA, necessitating the development of computational methods for designing active sgRNAs. While deep learning-based models have shown promise in predicting sgRNA activity, the accuracy of prediction is primarily governed by the data set used in model training. Here, we trained a convolutional neural network (CNN) model and a large language model (LLM) on balanced and imbalanced data sets generated from CRISPR-Cas12a screening data for the yeast Yarrowia lipolytica and evaluated their ability to predict high- and low-activity sgRNAs. We further tested whether prediction performance can be improved by training on imbalanced data sets augmented with synthetic sgRNAs. Lastly, we demonstrated that adding synthetic sgRNAs to inherently imbalanced CRISPR-Cas9 data sets from Y. lipolytica and Komagataella phaffii leads to improved performance in predicting sgRNA activity, thus underscoring the importance of employing balanced training sets for accurate sgRNA activity prediction.
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The application of a heat-inducible CRISPR/Cas12b (C2c1) genome editing system in tetraploid cotton (G. hirsutum) plants.
The CRISPR/Cas9 and Cas12a (Cpf1) tools have been used on a large scale for genome editing. A new effector with a single nuclease domain, a relatively small size, low-frequency off-target effects and cleavage capability under high temperature has been recently established and designated CRISPR/Cas12b (C2c1). Cas12b has also shown temperature inducibility in mammalian systems. Therefore, this system is potentially valuable for editing the genomes of plant species, such as cotton, that are resistant to high temperatures. Using this new system, mutants of upland cotton were successfully generated following Agrobacterium-mediated genetic transformation under a range of temperatures. Transformants (explants infected by Agrobacterium) exposed to 45 °C for 4 days showed the highest editing efficiency. No off-target mutation was detected by whole-genome sequencing. Genome edits by AacCas12b in T0 generation were faithfully passed to the T1 generation. Taken together, CRISPR/Cas12b is therefore an efficient and precise tool for genome editing in cotton plants.
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CRISPR/dCas9-mediated epigenetic modification reveals differential regulation of histone acetylation on Aspergillus niger secondary metabolite.
Epigenetic studies on secondary metabolites (SMs) mainly relied so far on non-selective epigenetic factors deletion or feeding epigenetic inhibitors in Aspergillus niger. Although technologies developed for epigenome editing at specific loci now enable the direct study of the functional relevance of precise gene regulation and epigenetic modification, relevant assays are limited in filamentous fungi. Herein, we show that CRISPR/dCas9-mediated histone epigenetic modification systems efficiently reprogramed the expression of target genes in A. niger. First, we constructed a p300-dCas9 system and demonstrated the activation of a EGFP fluorescent reporter. Second, by precisely locating histone acetylase p300 on ATG adjacent region of secondary metabolic gene breF, the transcription of breF was activated. Third, p300-dCas9 was guided to the native polyketide synthase (PKS) gene fuml, which increased production of the compound fumonisin B2 detected by HPLC and LC-MS. Then, endogenous histone acetylase GcnE-dCas9 and histone deacetylases HosA-dCas9 and RpdA-dCas9 repressed the transcription of breF. Finally, by targeting HosA-dCa9 fusion to pigment gene fwnA, we confirmed that histone deacetylase HosA activated the expression of fwnA, accelerated the synthesis of melanin. Targeted epigenome editing is a promising technology and this study is the first time to apply the epigenetic CRISPR/dCas9 system on regulating the expression of the secondary metabolic genes in A. niger.
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RIG-I is responsible for activation of type I interferon pathway in Seneca Valley virus-infected porcine cells to suppress viral replication.
BACKGROUND: Retinoic acid-inducible gene I (RIG-I) is a key cytosolic receptor of the innate immune system. Seneca valley virus (SVV) is a newly emerging RNA virus that infects pigs causing significant economic losses in pig industry. RIG-I plays different roles during different viruses infections. The role of RIG-I in SVV-infected cells remains unknown. Understanding of the role of RIG-I during SVV infection will help to clarify the infection process of SVV in the infected cells. METHODS: In this study, we generated a RIG-I knockout (KO) porcine kidney PK-15 cell line using the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/CRISPR-associated protein-9 nuclease (Cas9) genome editing tool. The RIG-I gene sequence of RIG-I KO cells were determined by Sanger sequencing method, and the expression of RIG-I protein in the RIG-I KO cells were detected by Western bloting. The activation status of type I interferon pathway in Sendai virus (SeV)- or SVV-infected RIG-I KO cells was investigated by measuring the mRNA expression levels of interferon (IFN)-β and IFN-stimulated genes (ISGs). The replicative state of SVV in the RIG-I KO cells was evaluated by qPCR, Western bloting, TCID50 assay and indirect immunofluorescence assay. RESULTS: Gene editing of RIG-I in PK-15 cells successfully resulted in the destruction of RIG-I expression. RIG-I KO PK-15 cells had a lower expression of IFN-β and ISGs compared with wildtype (WT) PK-15 cells when stimulated by the model RNA virus SeV. The amounts of viral RNA and viral protein as well as viral yields in SVV-infected RIG-I WT and KO cells were determined and compared, which showed that knockout of RIG-I significantly increased SVV replication and propagation. Meanwhile, the expression of IFN-β and ISGs were considerably decreased in RIG-I KO cells compared with that in RIG-I WT cells during SVV infection. CONCLUSION: Altogether, this study indicated that RIG-I showed an antiviral role against SVV and was essential for activation of type I IFN signaling during SVV infection. In addition, this study suggested that the CRISPR/Cas9 system can be used as an effective tool to modify cell lines to increase viral yields during SVV vaccine development.
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CT-Finder: A Web Service for CRISPR Optimal Target Prediction and Visualization.
The CRISPR system holds much promise for successful genome engineering, but therapeutic, industrial, and research applications will place high demand on improving the specificity and efficiency of this tool. CT-Finder (http://bioinfolab.miamioh.edu/ct-finder) is a web service to help users design guide RNAs (gRNAs) optimized for specificity. CT-Finder accommodates the original single-gRNA Cas9 system and two specificity-enhancing paired-gRNA systems: Cas9 D10A nickases (Cas9n) and dimeric RNA-guided FokI nucleases (RFNs). Optimal target candidates can be chosen based on the minimization of predicted off-target effects. Graphical visualization of on-target and off-target sites in the genome is provided for target validation. Major model organisms are covered by this web service.
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Anti-CRISPR-Based and CRISPR-Based Genome Editing of Sulfolobus islandicus Rod-Shaped Virus 2.
Genetic engineering of viruses has generally been challenging. This is also true for archaeal rod-shaped viruses, which carry linear double-stranded DNA genomes with hairpin ends. In this paper, we describe two different genome editing approaches to mutate the Sulfolobus islandicus rod-shaped virus 2 (SIRV2) using the archaeon Sulfolobus islandicus LAL14/1 and its derivatives as hosts. The anti-CRISPR (Acr) gene acrID1, which inhibits CRISPR-Cas subtype I-D immunity, was first used as a selection marker to knock out genes from SIRV2M, an acrID1-null mutant of SIRV2. Moreover, we harnessed the endogenous CRISPR-Cas systems of the host to knock out the accessory genes consecutively, which resulted in a genome comprised solely of core genes of the 11 SIRV members. Furthermore, infection of this series of knockout mutants in the CRISPR-null host of LAL14/1 (Δarrays) confirmed the non-essentiality of the deleted genes and all except the last deletion mutant propagated as efficiently as the WT SIRV2. This suggested that the last gene deleted, SIRV2 gp37, is important for the efficient viral propagation. The generated viral mutants will be useful for future functional studies including searching for new Acrs and the approaches described in this case are applicable to other viruses.
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