Golden Gate Cloning of Synthetic CRISPR RNA Spacer Sequences.

Prokaryotes use CRISPR-Cas systems to interfere with viruses and other mobile genetic elements. CRISPR arrays comprise repeated DNA elements and spacer sequences that can be engineered for custom target sites. These arrays are transcribed into precursor CRISPR RNAs (pre-crRNAs) that undergo maturation steps to form individual CRISPR RNAs (crRNAs). Each crRNA contains a single spacer that identifies the target cleavage site for a large variety of Cas protein effectors. Precise manipulation of spacer sequences within CRISPR arrays is crucial for advancing the functionality of CRISPR-based technologies. Here, we describe a protocol for the design and creation of a minimal, plasmid-based CRISPR array to enable the expression of specific, synthetic crRNAs. Plasmids contain entry spacer sequences with two type IIS restriction sites and Golden Gate cloning enables the efficient exchange of these spacer sequences. Factors that influence the compatibility of the CRISPR arrays with native or recombinant Cas proteins are discussed.

Protocol for NT-CRISPR: A Method for Efficient Genome Engineering in Vibrio natriegens.

Vibrio natriegens is a gram-negative bacterium, which has received increasing attention due to its very fast growth with a doubling time of under 10 min under optimal conditions. To enable a wide range of projects spanning from basic research to biotechnological applications, we developed NT-CRISPR as a new method for genome engineering. This book chapter provides a step-by-step protocol for the use of this previously published tool. NT-CRISPR combines natural transformation with counterselection through CRISPR-Cas9. Thereby, genomic regions can be deleted, foreign sequences can be integrated, and point mutations can be introduced. Furthermore, up to three simultaneous modifications are possible.

Genotype from Phenotype: Using CRISPR Screens to Dissect Lymphoma Biology.

Genome-wide screens are a powerful technique to dissect the complex network of genes regulating diverse cellular phenotypes. The recent adaptation of the CRISPR-Cas9 system for genome engineering has revolutionized functional genomic screening. Here, we present protocols used to introduce Cas9 into human lymphoma cell lines, produce high-titer lentivirus of a genome-wide sgRNA library, transduce and culture cells during the screen, select cells with a specified phenotype, isolate genomic DNA, and prepare a custom library for next-generation sequencing. These protocols were tailored for loss-of-function CRISPR screens in human B-cell lymphoma cell lines but are highly amenable for other experimental purposes.

The Evolution of Nucleic Acid-Based Diagnosis Methods from the (pre-)CRISPR to CRISPR era and the Associated Machine/Deep Learning Approaches in Relevant RNA Design.

Nucleic acid tests (NATs) are considered as gold standard in molecular diagnosis. To meet the demand for onsite, point-of-care, specific and sensitive, trace and genotype detection of pathogens and pathogenic variants, various types of NATs have been developed since the discovery of PCR. As alternatives to traditional NATs (e.g., PCR), isothermal nucleic acid amplification techniques (INAATs) such as LAMP, RPA, SDA, HDR, NASBA, and HCA were invented gradually. PCR and most of these techniques highly depend on efficient and optimal primer and probe design to deliver accurate and specific results. This chapter starts with a discussion of traditional NATs and INAATs in concert with the description of computational tools available to aid the process of primer/probe design for NATs and INAATs. Besides briefly covering nanoparticles-assisted NATs, a more comprehensive presentation is given on the role CRISPR-based technologies have played in molecular diagnosis. Here we provide examples of a few groundbreaking CRISPR assays that have been developed to counter epidemics and pandemics and outline CRISPR biology, highlighting the role of CRISPR guide RNA and its design in any successful CRISPR-based application. In this respect, we tabularize computational tools that are available to aid the design of guide RNAs in CRISPR-based applications. In the second part of our chapter, we discuss machine learning (ML)- and deep learning (DL)-based computational approaches that facilitate the design of efficient primer and probe for NATs/INAATs and guide RNAs for CRISPR-based applications. Given the role of microRNA (miRNAs) as potential future biomarkers of disease diagnosis, we have also discussed ML/DL-based computational approaches for miRNA-target predictions. Our chapter presents the evolution of nucleic acid-based diagnosis techniques from PCR and INAATs to more advanced CRISPR/Cas-based methodologies in concert with the evolution of deep learning (DL)- and machine learning (ml)-based computational tools in the most relevant application domains.

Five Years of Progress in CRISPR Clinical Trials (2019-2024).

In July 2019, Victoria Gray became the first patient with sickle cell disease to receive a CRISPR-based cell therapy as a volunteer in the exa-cel clinical trial, sponsored by Vertex Pharmaceuticals and CRISPR Therapeutics. Barely four years later, the ensuing therapy, branded as Casgevy, received approval from regulatory agencies in Europe, the United States, and the Middle East, ushering in a new era of CRISPR-based medicines. During this period, scores of other clinical trials have been launched, including many actively recruiting patients across phase 1, phase 2, and phase 3 clinical trials around the world. In this brief Perspective, we collate the latest information on therapeutic clinical trials featuring CRISPR, base and prime editing, across a range of both in vivo and ex vivo gene and cell therapies.

Widespread Impact of Natural Genetic Variations in CRISPR-Cas9 Outcomes.

The clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) is a genome editing tool widely used in biological research and clinical therapeutics. Natural human genetic variations, through altering the sequence context of CRISPR-Cas9 target regions, can significantly affect its DNA repair outcomes and ultimately lead to different editing efficiencies. However, these effects have not been systematically studied, even as CRISPR-Cas9 is broadly applied to primary cells and patient samples that harbor such genetic diversity. Here, we present comprehensive investigations of natural genetic variations on CRISPR-Cas9 outcomes across the human genome. The utility of our analysis is illustrated in two case studies, on both preclinical discoveries of CD33 knockout in chimeric antigen receptor-T cell therapy and clinical applications of transthyretin (TTR) inactivation for treating TTR amyloidosis. We further expand our analysis to genome-scale, population-stratified common variants that may lead to gene editing disparity. Our analyses demonstrate pitfalls of failing to account for the widespread genetic variations in Cas9 target selection and how they can be effectively examined and avoided using our method. To facilitate broad access to our analysis, a web platform CROTONdb is developed, which provides predictions for all possible CRISPR-Cas9 target sites in the coding and noncoding regulatory regions, spanning over 5.38 million guide RNA targets and 90.82 million estimated variant effects. We anticipate CROTONdb having broad clinical utilities in gene and cellular therapies.

Tracking the progeny of bacterial persisters using a CRISPR-based genomic recorder.

The rise of antimicrobial failure is a global emergency, and causes beyond typical genetic resistance must be determined. One probable factor is the existence of subpopulations of transiently growth-arrested bacteria, persisters, that endure antibiotic treatment despite genetic susceptibility to the drug. The presence of persisters in infected hosts has been successfully established, notably through the development of fluorescent reporters. It is proposed that infection relapse is caused by persisters resuming growth after cessation of the antibiotic treatment, but to date, there is no direct evidence for this. This is because no tool or reporter currently exists to track the extent to which infection relapse is initiated by regrowth of persisters in the host. Indeed, once they have transitioned out of the persister state, the progeny of persisters are genetically and phenotypically identical to susceptible bacteria in the population, making it virtually impossible to ascertain the source of relapse. We designed pSCRATCH (plasmid for Selective CRISPR Array expansion To Check Heritage), a molecular tool that functions to record the state of antibiotic persistence in the genome of Salmonella persisters. We show that pSCRATCH successfully marks persisters by adding spacers in their CRISPR arrays and the genomic label is stable in persister progeny after exit from persistence. We further show that in a Salmonella infection model the system enables the discrimination of treatment failure originating from persistence versus resistance. Thus, pSCRATCH provides proof of principle for stable marking of persisters and a prototype for applications to more complex infection models and other pathogens.

CRISPR-GEM: A Novel Machine Learning Model for CRISPR Genetic Target Discovery and Evaluation.

CRISPR gene editing strategies are shaping cell therapies through precise and tunable control over gene expression. However, limitations in safely delivering high quantities of CRISPR machinery demand careful target gene selection to achieve reliable therapeutic effects. Informed target gene selection requires a thorough understanding of the involvement of target genes in gene regulatory networks (GRNs) and thus their impact on cell phenotype. Effective decoding of these complex networks has been achieved using machine learning models, but current techniques are limited to single cell types and focus mainly on transcription factors, limiting their applicability to CRISPR strategies. To address this, we present CRISPR-GEM, a multilayer perceptron (MLP) based synthetic GRN constructed to accurately predict the downstream effects of CRISPR gene editing. First, input and output nodes are identified as differentially expressed genes between defined experimental and target cell/tissue types, respectively. Then, MLP training learns regulatory relationships in a black-box approach allowing accurate prediction of output gene expression using only input gene expression. Finally, CRISPR-mimetic perturbations are made to each input gene individually, and the resulting model predictions are compared to those for the target group to score and assess each input gene as a CRISPR candidate. The top scoring genes provided by CRISPR-GEM therefore best modulate experimental group GRNs to motivate transcriptomic shifts toward a target group phenotype. This machine learning model is the first of its kind for predicting optimal CRISPR target genes and serves as a powerful tool for enhanced CRISPR strategies across a range of cell therapies.

CRISPR is easy: Exposure to Last Week Tonight enhances knowledge about gene editing.

Experts have called for public engagement with the governance of controversial scientific research and discoveries, including CRISPR, the technology that enables gene editing. Though engaging and informing citizens who are not interested in the issue is a challenge, recent studies suggest humor has potential to close interest and knowledge gaps. We tested this potential by exposing individuals (N = 303) to one of three videos (an edited clip from Last Week Tonight, an edited clip from 60 Minutes, or control) that contained broadly overlapping facts about gene editing in an online survey. Results show that while exposure to the Last Week Tonight clip did not increase attentiveness to the issue of human gene editing among individuals with lower levels of interest in science, exposure to the humorous clip caused a modest improvement in issue knowledge. Positive main effects on perceived knowledge were found for both treatments. More research is needed but findings suggest that the use of humor in science communication offers potential, though perhaps limited, for broadening public engagement with emerging areas of science.

Systematic Comparison of CRISPR and shRNA Screens to Identify Essential Genes Using a Graph-Based Unsupervised Learning Model.

Generally, essential genes identified using shRNA and CRISPR are not always the same, raising questions about the choice between these two screening platforms. To address this, we systematically compared the performance of CRISPR and shRNA to identify essential genes across different gene expression levels in 254 cell lines. As both platforms have a notable false positive rate, to correct this confounding factor, we first developed a graph-based unsupervised machine learning model to predict common essential genes. Furthermore, to maintain the unique characteristics of individual cell lines, we intersect essential genes derived from the biological experiment with the predicted common essential genes. Finally, we employed statistical methods to compare the ability of these two screening platforms to identify essential genes that exhibit differential expression across various cell lines. Our analysis yielded several noteworthy findings: (1) shRNA outperforms CRISPR in the identification of lowly expressed essential genes; (2) both screening methodologies demonstrate strong performance in identifying highly expressed essential genes but with limited overlap, so we suggest using a combination of these two platforms for highly expressed essential genes; (3) notably, we did not observe a single gene that becomes universally essential across all cancer cell lines.

Engineering of HEK293T Cell Factory for Lentiviral Production by High-Throughput Selected Genes.

Lentiviral vectors (LVs) are crucial tools in gene therapy and bioproduction, but high-yield LV production systems are urgently needed. Using clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 high-throughput screening, we identified nine critical genes (LDAH, GBP3, BPIFC, NHLRC1, NHLRC3, ZNF425, TTC37, LRRC4B, and SPINK6) from 17,501 genes that limit LV packaging and formation. Knocking out these genes in HEK293T cells significantly increased virus production, with LDAH knockout exhibiting a 6.63-fold increase. Studies on multigene knockouts demonstrated that the cumulative effects of different gene knockouts can significantly enhance lentivirus production in HEK293T cells. Triple knockout of GBP3, BPIFC, and LDAH increased LV titer by ∼8.33-fold, and knockout (or knockdown) of GBP3, NHLRC1, and NHLRC3 increased LV titer by ∼6.53-fold. This study established HEK293T cell lines with multiple genes knockout for efficient LV production, providing reliable technical support for LV production and application and offering new perspectives for studying LV packaging mechanisms and related virus research.

Affordable Pricing of CRISPR Treatments is a Pressing Ethical Imperative.

Casgevy, the world's first approved CRISPR-based cell therapy, has been priced at $2.2 million per patient. Although this hefty price tag was widely anticipated, the extremely high cost of this and other cell and gene therapies poses a major ethical issue in terms of equitable access and global health. In this Perspective, we argue that lowering the prices of future CRISPR therapies is an urgent ethical imperative. Although we focus on Casgevy as a case study, much of our analysis can be extrapolated to the controversies over affordable access to other gene and cell therapies. First, we explain why this first-of-its-kind CRISPR therapy might be so expensive. We then analyze the ethical issues of equity and global health of early CRISPR treatments. Next, we discuss potential solutions to lower the prices of CRISPR gene therapies. We conclude that the approval of CRISPR transforms our obligations of justice and compels us to bring future gene therapies to the maximum possible number of patients with serious genetic diseases at affordable prices.

Structural variation of types IV-A1- and IV-A3-mediated CRISPR interference.

CRISPR-Cas mediated DNA-interference typically relies on sequence-specific binding and nucleolytic degradation of foreign genetic material. Type IV-A CRISPR-Cas systems diverge from this general mechanism, using a nuclease-independent interference pathway to suppress gene expression for gene regulation and plasmid competition. To understand how the type IV-A system associated effector complex achieves this interference, we determine cryo-EM structures of two evolutionarily distinct type IV-A complexes (types IV-A1 and IV-A3) bound to cognate DNA-targets in the presence and absence of the type IV-A signature DinG effector helicase. The structures reveal how the effector complexes recognize the protospacer adjacent motif and target-strand DNA to form an R-loop structure. Additionally, we reveal differences between types IV-A1 and IV-A3 in DNA interactions and structural motifs that allow for in trans recruitment of DinG. Our study provides a detailed view of type IV-A mediated DNA-interference and presents a structural foundation for engineering type IV-A-based genome editing tools.

The CRISPR-dCas9 interference system suppresses inhA gene expression in Mycobacterium smegmatis.

CRISPR-dead Cas9 interference (CRISPRi) has become a valuable tool for precise gene regulation. In this study, CRISPRi was designed to target the inhA gene of Mycobacterium smegmatis (Msm), a gene necessary for mycolic acid synthesis. Our findings revealed that sgRNA2 induced with 100 ng/ml aTc achieved over 90% downregulation of inhA gene expression and inhibited bacterial viability by approximately 1,000-fold. Furthermore, CRISPRi enhanced the susceptibility of M. smegmatis to isoniazid and rifampicin, which are both 50% and 90% lower than those of the wild-type strain or other strains, respectively. This study highlights the ability of CRISPRi to silence the inhA gene, which impacts bacterial viability and drug susceptibility. The findings provide valuable insights into the utility of CRISPRi as an alternative tool for gene regulation. CRISPRi might be further assessed for its synergistic effect with current anti-tuberculosis drugs and its possible implications for combating mycobacterial infections, especially drug-resistant tuberculosis.

A digital CRISPR-dCas9-based gene remodeling biocomputer programmed by dietary compounds in mammals.

CRISPR-dCas9 (dead Cas9 protein) technology, combined with chemical molecules and light-triggered genetic switches, offers customizable control over gene perturbation. However, these simple ON/OFF switches cannot precisely determine the sophisticated perturbation process. Here, we developed a resveratrol and protocatechuic acid-programmed CRISPR-mediated gene remodeling biocomputer (REPACRISPR) for conditional endogenous transcriptional regulation of genes in vitro and in vivo. Two REPACRISPR variants, REPACRISPRi and REPACRISPRa, were designed for the logic control of gene inhibition and activation, respectively. We successfully demonstrated the digital computations of single or multiplexed endogenous gene transcription by using REPACRISPRa. We also established mathematical models to predict the dose-responsive transcriptional levels of a target endogenous gene controlled by REPACRISPRa. Moreover, high levels of endogenous gene activation in mice mediated by the AND logic gate demonstrated computational control of CRISPR-dCas9-based epigenome remodeling in mice. This CRISPR-based biocomputer expands the synthetic biology toolbox and can potentially advance gene-based precision medicine. A record of this paper's transparent peer review process is included in the supplemental information.

CRISPR-mediated megabase-scale transgene de-duplication to generate a functional single-copy full-length humanized DMD mouse model.

BACKGROUND: The development of sequence-specific precision treatments like CRISPR gene editing therapies for Duchenne muscular dystrophy (DMD) requires sequence humanized animal models to enable the direct clinical translation of tested strategies. The current available integrated transgenic mouse model containing the full-length human DMD gene, Tg(DMD)72Thoen/J (hDMDTg), has been found to have two copies of the transgene per locus in a tail-to-tail orientation, which does not accurately simulate the true (single) copy number of the DMD gene. This duplication also complicates analysis when testing CRISPR therapy editing outcomes, as large genetic alterations and rearrangements can occur between the cut sites on the two transgenes. RESULTS: To address this, we performed long read nanopore sequencing on hDMDTg mice to better understand the structure of the duplicated transgenes. Following that, we performed a megabase-scale deletion of one of the transgenes by CRISPR zygotic microinjection to generate a single-copy, full-length, humanized DMD transgenic mouse model (hDMDTgSc). Functional, molecular, and histological characterisation shows that the single remaining human transgene retains its function and rescues the dystrophic phenotype caused by endogenous murine Dmd knockout. CONCLUSIONS: Our unique hDMDTgSc mouse model simulates the true copy number of the DMD gene, and can potentially be used for the further generation of DMD disease models that would be better suited for the pre-clinical assessment and development of sequence specific CRISPR therapies.

SpacerPlacer: ancestral reconstruction of CRISPR arrays reveals the evolutionary dynamics of spacer deletions.

Bacteria employ CRISPR-Cas systems for defense by integrating invader-derived sequences, termed spacers, into the CRISPR array, which constitutes an immunity memory. While spacer deletions occur randomly across the array, newly acquired spacers are predominantly integrated at the leader end. Consequently, spacer arrays can be used to derive the chronology of spacer insertions. Reconstruction of ancestral spacer acquisitions and deletions could help unravel the coevolution of phages and bacteria, the evolutionary dynamics in microbiomes, or track pathogens. However, standard reconstruction methods produce misleading results by overlooking insertion order and joint deletions of spacers. Here, we present SpacerPlacer, a maximum likelihood-based ancestral reconstruction approach for CRISPR array evolution. We used SpacerPlacer to reconstruct and investigate ancestral deletion events of 4565 CRISPR arrays, revealing that spacer deletions occur 374 times more frequently than mutations and are regularly deleted jointly, with an average of 2.7 spacers. Surprisingly, we observed a decrease in the spacer deletion frequency towards both ends of the reconstructed arrays. While the resulting trailer-end conservation is commonly observed, a reduced deletion frequency is now also detectable towards the variable leader end. Finally, our results point to the hypothesis that frequent loss of recently acquired spacers may provide a selective advantage.

In vivo CRISPR screens identify Mga as an immunotherapy target in triple-negative breast cancer.

Immune evasion is not only critical for tumor initiation and progression, but also determines the efficacy of immunotherapies. Through iterative in vivo CRISPR screens with seven syngeneic tumor models, we identified core and context-dependent immune evasion pathways across cancer types. This valuable high-confidence dataset is available for the further understanding of tumor intrinsic immunomodulators, which may lead to the discovery of effective anticancer therapeutic targets. With a focus on triple-negative breast cancer (TNBC), we found that Mga knock-out significantly enhances antitumor immunity and inhibits tumor growth. Transcriptomics and single-cell RNA sequencing analyses revealed that Mga influences various immune-related pathways in the tumor microenvironment. Our findings suggest that Mga may play a role in modulating the tumor immune landscape, though the precise mechanisms require further investigation. Interestingly, we observed that low MGA expression in breast cancer patients correlates with a favorable prognosis, particularly in those with active interferon-γ signaling. These observations provide insights into tumor immune escape mechanisms and suggest that further exploration of MGA's function could potentially lead to effective therapeutic strategies in TNBC.

CRISPR for companion diagnostics in low-resource settings.

New point-of-care tests (POCTs), which are especially useful in low-resource settings, are needed to expand screening capacity for diseases that cause significant mortality: tuberculosis, multiple cancers, and emerging infectious diseases. Recently, clustered regularly interspaced short palindromic repeats (CRISPR)-based diagnostic (CRISPR-Dx) assays have emerged as powerful and versatile alternatives to traditional nucleic acid tests, revealing a strong potential to meet this need for new POCTs. In this review, we discuss CRISPR-Dx assay techniques that have been or could be applied to develop POCTs, including techniques for sample processing, target amplification, multiplex assay design, and signal readout. This review also describes current and potential applications for POCTs in disease diagnosis and includes future opportunities and challenges for such tests. These tests need to advance beyond initial assay development efforts to broadly meet criteria for use in low-resource settings.