Unraveling CRISPR-Cas9 genome engineering parameters via a library-on-library approach

Guide RNA structure design enables combinatorial CRISPRa programs for biosynthetic profiling

Engineering metabolism to efficiently produce chemicals from multi-step pathways requires optimizing multi-gene expression programs to achieve enzyme balance. CRISPR-Cas transcriptional control systems are emerging as important tools for programming multi-gene expression, but poor predictability of guide RNA folding can disrupt expression control. Here, we correlate efficacy of modified guide RNAs (scRNAs) for CRISPR activation (CRISPRa) in E. coli with a computational kinetic parameter describing scRNA folding rate into the active structure (rS = 0.8). This parameter also enables forward design of scRNAs, allowing us to design a system of three synthetic CRISPRa promoters that can orthogonally activate (>35-fold) expression of chosen outputs. Through combinatorial activation tuning, we profile a three-dimensional design space expressing two different biosynthetic pathways, demonstrating variable production of pteridine and human milk oligosaccharide products. This RNA design approach aids combinatorial optimization of metabolic pathways and may accelerate routine design of effective multi-gene regulation programs in bacterial hosts.

Genome-scale CRISPR-Cas9 screening in stem cells: theories, applications and challenges

Due to the rapid development of stem cell technology, there have been tremendous advances in molecular biological and pathological research, cell therapy as well as organoid technologies over the past decades. Advances in genome editing technology, particularly the discovery of clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-related protein 9 (Cas9), have further facilitated the rapid development of stem cell researches. The CRISPR-Cas9 technology now goes beyond creating single gene editing to enable the inhibition or activation of endogenous gene loci by fusing inhibitory (CRISPRi) or activating (CRISPRa) domains with deactivated Cas9 proteins (dCas9). These tools have been utilized in genome-scale CRISPRi/a screen to recognize hereditary modifiers that are synergistic or opposing to malady mutations in an orderly and fair manner, thereby identifying illness mechanisms and discovering novel restorative targets to accelerate medicinal discovery investigation. However, the application of this technique is still relatively rare in stem cell research. There are numerous specialized challenges in applying large-scale useful genomics approaches to differentiated stem cell populations. Here, we present the first comprehensive review on CRISPR-based functional genomics screening in the field of stem cells, as well as practical considerations implemented in a range of scenarios, and exploration of the insights of CRISPR-based screen into cell fates, disease mechanisms and cell treatments in stem cell models. This review will broadly benefit scientists, engineers and medical practitioners in the areas of stem cell research.

Machine learning-inferred and energy landscape-guided analyses reveal kinetic determinants of CRISPR/Cas9 gene editing

The CRISPR/Cas nucleases system is widely considered the most important tool in genome engineering. However, current methods for predicting on/off-target effects and designing guide RNA (gRNA) rely on purely data-driven approaches or focus solely on the system's thermal equilibrium properties. Nonetheless, experimental evidence suggests that the process is kinetically controlled rather than being in equilibrium. In this study, we utilized a vast amount of available data and combined random forest, a supervised ensemble learning algorithm, and free energy landscape analysis to investigate the kinetic pathways of R-loop formation in the CRISPR/Cas9 system and the intricate molecular interactions between DNA and the Cas9 RuvC and HNH domains. The study revealed (a) a novel three-state kinetic mechanism, (b) the unfolding of the activation state of the R-loop being the most crucial kinetic determinant and the key predictor for on- and off-target cleavage efficiencies, and (c) the nucleotides from positions +13 to +16 being the kinetically critical nucleotides. The results provide a biophysical rationale for the design of a kinetic strategy for enhancing CRISPR/Cas9 gene editing accuracy and efficiency.

CRISPRlnc: a machine learning method for lncRNA-specific single-guide RNA design of CRISPR/Cas9 system

CRISPR/Cas9 is a promising RNA-guided genome editing technology, which consists of a Cas9 nuclease and a single-guide RNA (sgRNA). So far, a number of sgRNA prediction softwares have been developed. However, they were usually designed for protein-coding genes without considering that long non-coding RNA (lncRNA) genes may have different characteristics. In this study, we first evaluated the performances of a series of known sgRNA-designing tools in the context of both coding and non-coding datasets. Meanwhile, we analyzed the underpinnings of their varied performances on the sgRNA's specificity for lncRNA including nucleic acid sequence, genome location and editing mechanism preference. Furthermore, we introduce a support vector machine-based machine learning algorithm named CRISPRlnc, which aims to model both CRISPR knock-out (CRISPRko) and CRISPR inhibition (CRISPRi) mechanisms to predict the on-target activity of targets. CRISPRlnc combined the paired-sgRNA design and off-target analysis to achieve one-stop design of CRISPR/Cas9 sgRNAs for non-coding genes. Performance comparison on multiple datasets showed that CRISPRlnc was far superior to existing methods for both CRISPRko and CRISPRi mechanisms during the lncRNA-specific sgRNA design. To maximize the availability of CRISPRlnc, we developed a web server (http://predict.crisprlnc.cc) and made it available for download on GitHub.

Tuft cells and fibroblasts promote thymus regeneration through ILC2-mediated type 2 immune response

The thymus is a primary lymphoid organ that is essential for the establishment of adaptive immunity through generation of immunocompetent T cells. In response to various stress signals, the thymus undergoes acute but reversible involution. However, the mechanisms governing its recovery are incompletely understood. Here, we used a dexamethasone-induced acute thymic involution mouse model to investigate how thymic hematopoietic cells (excluding T cells) contribute to thymic regeneration. scRNA-seq analysis revealed marked transcriptional and cellular changes in various thymic populations and highlighted thymus-resident innate lymphoid cells type 2 (ILC2) as a key cell type involved in the response to damage. We identified that ILC2 are activated by the alarmins IL-25 and IL-33 produced in response to tissue damage by thymic tuft cells and fibroblasts, respectively. Moreover, using mouse models deficient in either tuft cells and/or IL-33, we found that these alarmins are required for effective thymus regeneration after dexamethasone-induced damage. We also demonstrate that upon their damage-dependent activation, thymic ILC2 produce several effector molecules linked to tissue regeneration, such as amphiregulin and IL-13, which in turn promote thymic epithelial cell differentiation. Collectively, our study elucidates a previously undescribed role for thymic tuft cells and fibroblasts in thymus regeneration through activation of the type 2 immune response.

Epigenetic profiles guide improved CRISPR/Cas9-mediated gene knockout in human T cells

Genetic modification of specific genes is emerging as a useful tool to enhance the functions of antitumor T cells in adoptive immunotherapy. Current advances in CRISPR/Cas9 technology enable gene knockout during in vitro preparation of infused T-cell products through transient transfection of a Cas9-guide RNA (gRNA) ribonucleoprotein complex. However, selecting optimal gRNAs remains a major challenge for efficient gene ablation. Although multiple in silico tools to predict the targeting efficiency have been developed, their performance has not been validated in cultured human T cells. Here, we explored a strategy to select optimal gRNAs using our pooled data on CRISPR/Cas9-mediated gene knockout in human T cells. The currently available prediction tools alone were insufficient to accurately predict the indel percentage in T cells. We used data on the epigenetic profiles of cultured T cells obtained from transposase-accessible chromatin with high-throughput sequencing (ATAC-seq). Combining the epigenetic information with sequence-based prediction tools significantly improved the gene-editing efficiency. We further demonstrate that epigenetically closed regions can be targeted by designing two gRNAs in adjacent regions. Finally, we demonstrate that the gene-editing efficiency of unstimulated T cells can be enhanced through pretreatment with IL-7. These findings enable more efficient gene editing in human T cells.

Advancing genome editing with artificial intelligence: opportunities, challenges, and future directions

Clustered regularly interspaced short palindromic repeat (CRISPR)-based genome editing (GED) technologies have unlocked exciting possibilities for understanding genes and improving medical treatments. On the other hand, Artificial intelligence (AI) helps genome editing achieve more precision, efficiency, and affordability in tackling various diseases, like Sickle cell anemia or Thalassemia. AI models have been in use for designing guide RNAs (gRNAs) for CRISPR-Cas systems. Tools like DeepCRISPR, CRISTA, and DeepHF have the capability to predict optimal guide RNAs (gRNAs) for a specified target sequence. These predictions take into account multiple factors, including genomic context, Cas protein type, desired mutation type, on-target/off-target scores, potential off-target sites, and the potential impacts of genome editing on gene function and cell phenotype. These models aid in optimizing different genome editing technologies, such as base, prime, and epigenome editing, which are advanced techniques to introduce precise and programmable changes to DNA sequences without relying on the homology-directed repair pathway or donor DNA templates. Furthermore, AI, in collaboration with genome editing and precision medicine, enables personalized treatments based on genetic profiles. AI analyzes patients' genomic data to identify mutations, variations, and biomarkers associated with different diseases like Cancer, Diabetes, Alzheimer's, etc. However, several challenges persist, including high costs, off-target editing, suitable delivery methods for CRISPR cargoes, improving editing efficiency, and ensuring safety in clinical applications. This review explores AI's contribution to improving CRISPR-based genome editing technologies and addresses existing challenges. It also discusses potential areas for future research in AI-driven CRISPR-based genome editing technologies. The integration of AI and genome editing opens up new possibilities for genetics, biomedicine, and healthcare, with significant implications for human health.

Low dose ribosomal DNA P-loop mutation affects development and enforces autophagy in Arabidopsis

Arabidopsis contains hundreds of ribosomal DNA copies organized within the nucleolar organizing regions (NORs) in chromosomes 2 and 4. There are four major types of variants of rDNA, VAR1-4, based on the polymorphisms of 3' external transcribed sequences. The variants are known to be differentially expressed during plant development. We created a mutant by the CRISPR-Cas9-mediated excision of ~ 25 nt from predominantly NOR4 ribosomal DNA copies, obtaining mosaic mutational events on ~ 5% of all rDNA copies. The excised region consists of P-loop and Helix-82 segments of 25S rRNA. The mutation led to allelic, dosage-dependent defects marked by lateral root inhibition, reduced size, and pointy leaves, all previously observed for defective ribosomal function. The mutation in NOR4 led to dosage compensation from the NOR2 copies by elevated expression of VAR1 in mutants and further associated single-nucleotide variants, thus, resulting in altered rRNA sub-population. Furthermore, the mutants exhibited rRNA maturation defects specifically in the minor pathway typified by 32S pre-rRNA accumulation. Density-gradient fractionation and subsequent RT-PCR of rRNA analyses revealed that mutated copies were not incorporated into the translating ribosomes. The mutants in addition displayed an elevated autophagic flux as shown by the autophagic marker GFP-ATG8e, likely related to ribophagy.

TREX2 enables efficient genome disruption mediated by paired CRISPR-Cas9 nickases that generate 3'-overhanging ends

Paired SpCas9 nickases (SpCas9n) are an effective strategy to reduce off-target effect in genome editing. However, this approach is not efficient with 3'-overhanging ends, limiting its applications. In order to expand the utility of paired SpCas9n in genome editing, we tested the effect of the TREX2 3'-5' exonuclease on repair of 3'-overhanging ends. We found ectopic overexpression of Trex2 stimulates the efficiency of paired SpCas9n in genome disruption with 3'-overhanging ends up to 400-fold with little stimulation of off-target editing. TREX2 overexpressed preferentially deletes entire 3' overhangs but has no significant effect on 5' overhangs. Trex2 overexpression also stimulates genome disruption by paired SpCas9n that potentially generate short 3'-overhanging ends at overlapping SpCas9n target sites, suggesting sequential nicking of overlapping target sites by SpCas9n. This approach is further simplified with improved efficiency and safety by fusion of TREX2 and particularly its DNA-binding-deficient mutant to SpCas9n. Junction analysis at overlapping targets revealed the different extent of end resection of 3' single-stranded DNA (ssDNA) by free TREX2 and TREX2 fused to SpCas9n. SpCas9n-TREX2 fusion is more convenient and safer than overexpression of free TREX2 to process 3'-overhanging ends for efficient genome disruption by paired SpCas9n, allowing practical use of this TREX2-based strategy in genome editing.

Applications of Innovation Technologies for Personalized Cancer Medicine: Stem Cells and Gene-Editing Tools

Personalized medicine is a new approach toward safer and even cheaper treatments with minimal side effects and toxicity. Planning a therapy based on individual properties causes an effective result in a patient's treatment, especially in a complex disease such as cancer. The benefits of personalized medicine include not only early diagnosis with high accuracy but also a more appropriate and effective therapeutic approach based on the unique clinical, genetic, and epigenetic features and biomarker profiles of a specific patient's disease. In order to achieve personalized cancer therapy, understanding cancer biology plays an important role. One of the crucial applications of personalized medicine that has gained consideration more recently due to its capability in developing disease therapy is related to the field of stem cells. We review various applications of pluripotent, somatic, and cancer stem cells in personalized medicine, including targeted cancer therapy, cancer modeling, diagnostics, and drug screening. CRISPR-Cas gene-editing technology is then discussed as a state-of-the-art biotechnological advance with substantial impacts on medical and therapeutic applications. As part of this section, the role of CRISPR-Cas genome editing in recent cancer studies is reviewed as a further example of personalized medicine application.

Germline Editing of Drosophila Using CRISPR-Cas9-Based Cytosine and Adenine Base Editors

Target-AID, BE3, and ABE7.10 base editors fused to the catalytically modified Cas9 and xCas9(3.7) were tested for germline editing of the fruit fly Drosophila melanogaster. We developed a guide RNA-expressing construct, white-4gRNA, targeting splice sites in the white gene, an X-chromosome located gene. Using white-4gRNA flies and transgenic lines expressing Target-AID, BE3, and ABE7.10 base editors, we tested the efficiency of stable germline gene editing at three different temperatures. Classical Cas9 generating insertions/deletions by non-homologous end joining served as a reference. Our data indicate that gene editing is most efficient at 28°C, the highest temperature suitable for fruit flies. Finally, we created a new allele of the core circadian clock gene timeless using Target-AID. This base edited mutant allele timSS308-9FL had a disrupted circadian clock with a period of ∼29 h. The white-4gRNA expressing fly can be used to test new generations of base editors for future applications in Drosophila.

gRNA Design: How Its Evolution Impacted on CRISPR/Cas9 Systems Refinement

Over the past decade, genetic engineering has witnessed a revolution with the emergence of a relatively new genetic editing tool based on RNA-guided nucleases: the CRISPR/Cas9 system. Since the first report in 1987 and characterization in 2007 as a bacterial defense mechanism, this system has garnered immense interest and research attention. CRISPR systems provide immunity to bacteria against invading genetic material; however, with specific modifications in sequence and structure, it becomes a precise editing system capable of modifying the genomes of a wide range of organisms. The refinement of these modifications encompasses diverse approaches, including the development of more accurate nucleases, understanding of the cellular context and epigenetic conditions, and the re-designing guide RNAs (gRNAs). Considering the critical importance of the correct performance of CRISPR/Cas9 systems, our scope will emphasize the latter approach. Hence, we present an overview of the past and the most recent guide RNA web-based design tools, highlighting the evolution of their computational architecture and gRNA characteristics over the years. Our study explains computational approaches that use machine learning techniques, neural networks, and gRNA/target interactions data to enable predictions and classifications. This review could open the door to a dynamic community that uses up-to-date algorithms to optimize and create promising gRNAs, suitable for modern CRISPR/Cas9 engineering.

Endogenous CRISPR-Cas mediated in situ genome editing: State-of-the-art and the road ahead for engineering prokaryotes

The CRISPR-Cas systems have shown tremendous promise as heterologous tools for genome editing in various prokaryotes. However, the perturbation of DNA homeostasis and the inherent toxicity of Cas9/12a proteins could easily lead to cell death, which led to the development of endogenous CRISPR-Cas systems. Programming the widespread endogenous CRISPR-Cas systems for in situ genome editing represents a promising tool in prokaryotes, especially in genetically intractable species. Here, this review briefly summarizes the advances of endogenous CRISPR-Cas-mediated genome editing, covering aspects of establishing and optimizing the genetic tools. In particular, this review presents the application of different types of endogenous CRISPR-Cas tools for strain engineering, including genome editing and genetic regulation. Notably, this review also provides a detailed discussion of the transposon-associated CRISPR-Cas systems, and the programmable RNA-guided transposition using endogenous CRISPR-Cas systems to enable editing of microbial communities for understanding and control. Therefore, they will be a powerful tool for targeted genetic manipulation. Overall, this review will not only facilitate the development of standard genetic manipulation tools for non-model prokaryotes but will also enable more non-model prokaryotes to be genetically tractable.

Kinesin family member 2A gates nociception

Nociceptive axons undergo remodeling as they innervate their targets during development and in response to environmental insults and pathological conditions. How is nociceptive morphogenesis regulated? Here, we show that the microtubule destabilizer kinesin family member 2A (Kif2a) is a key regulator of nociceptive terminal structures and pain sensitivity. Ablation of Kif2a in sensory neurons causes hyperinnervation and hypersensitivity to noxious stimuli in young adult mice, whereas touch sensitivity and proprioception remain unaffected. Computational modeling predicts that structural remodeling is sufficient to explain the phenotypes. Furthermore, Kif2a deficiency triggers a transcriptional response comprising sustained upregulation of injury-related genes and homeostatic downregulation of highly specific channels and receptors at the late stage. The latter effect can be predicted to relieve the hyperexcitability of nociceptive neurons, despite persisting morphological aberrations, and indeed correlates with the resolution of pain hypersensitivity. Overall, we reveal a critical control node defining nociceptive terminal structure, which is regulating nociception.

Digital data storage on DNA tape using CRISPR base editors

While the archival digital memory industry approaches its physical limits, the demand is significantly increasing, therefore alternatives emerge. Recent efforts have demonstrated DNA's enormous potential as a digital storage medium with superior information durability, capacity, and energy consumption. However, the majority of the proposed systems require on-demand de-novo DNA synthesis techniques that produce a large amount of toxic waste and therefore are not industrially scalable and environmentally friendly. Inspired by the architecture of semiconductor memory devices and recent developments in gene editing, we created a molecular digital data storage system called "DNA Mutational Overwriting Storage" (DMOS) that stores information by leveraging combinatorial, addressable, orthogonal, and independent in vitro CRISPR base-editing reactions to write data on a blank pool of greenly synthesized DNA tapes. As a proof of concept, this work illustrates writing and accurately reading of both a bitmap representation of our school's logo and the title of this study on the DNA tapes.

A fusion framework of deep learning and machine learning for predicting sgRNA cleavage efficiency

CRISPR/Cas9 system is a powerful tool for genome editing. Numerous studies have shown that sgRNAs can strongly affect the efficiency of editing. However, it is still not clear what rules should be followed for designing sgRNA with high cleavage efficiency. At present, several machine learning or deep learning methods have been developed to predict the cleavage efficiency of sgRNAs, however, the prediction accuracy of these tools is still not satisfactory. Here we propose a fusion framework of deep learning and machine learning, which first deals with the primary sequence and secondary structure features of the sgRNAs using both convolutional neural network (CNN) and recurrent neural network (RNN), and then uses the features extracted by the deep neural network to train a conventional machine learning model with LGBM. As a result, the new approach overwhelmed previous methods. The Spearman's correlation coefficient between predicted and measured sgRNA cleavage efficiency of our model (0.917) is improved by over 5% compared with the most advanced method (0.865), and the mean square error reduces from 7.89 × 10-3 to 4.75 × 10-3. Finally, we developed an online tool, CRISep (http://www.cuilab.cn/CRISep), to evaluate the availability of sgRNAs based on our models.

Tissue-specific knockout in Drosophila neuromuscular system reveals ESCRT's role in formation of synapse-derived extracellular vesicles

Tissue-specific gene knockout by CRISPR/Cas9 is a powerful approach for characterizing gene functions in animal development. However, this approach has been successfully applied in only a small number of Drosophila tissues. The Drosophila motor nervous system is an excellent model system for studying the biology of neuromuscular junction (NMJ). To expand tissue-specific CRISPR to the Drosophila motor system, here we present a CRISPR-mediated tissue-restricted mutagenesis (CRISPR-TRiM) toolkit for knocking out genes in motoneurons, muscles, and glial cells. We validated the efficacy of this toolkit by knocking out known genes in each tissue, demonstrated its orthogonal use with the Gal4/UAS binary expression system, and showed simultaneous knockout of multiple redundant genes. Using these tools, we discovered an essential role for SNARE pathways in NMJ maintenance. Furthermore, we demonstrate that the canonical ESCRT pathway suppresses NMJ bouton growth by downregulating the retrograde Gbb signaling. Lastly, we found that axon termini of motoneurons rely on ESCRT-mediated intra-axonal membrane trafficking to lease extracellular vesicles at the NMJ.

Benchmarking deep learning methods for predicting CRISPR/Cas9 sgRNA on- and off-target activities

In silico design of single guide RNA (sgRNA) plays a critical role in clustered regularly interspaced, short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) system. Continuous efforts are aimed at improving sgRNA design with efficient on-target activity and reduced off-target mutations. In the last 5 years, an increasing number of deep learning-based methods have achieved breakthrough performance in predicting sgRNA on- and off-target activities. Nevertheless, it is worthwhile to systematically evaluate these methods for their predictive abilities. In this review, we conducted a systematic survey on the progress in prediction of on- and off-target editing. We investigated the performances of 10 mainstream deep learning-based on-target predictors using nine public datasets with different sample sizes. We found that in most scenarios, these methods showed superior predictive power on large- and medium-scale datasets than on small-scale datasets. In addition, we performed unbiased experiments to provide in-depth comparison of eight representative approaches for off-target prediction on 12 publicly available datasets with various imbalanced ratios of positive/negative samples. Most methods showed excellent performance on balanced datasets but have much room for improvement on moderate- and severe-imbalanced datasets. This study provides comprehensive perspectives on CRISPR/Cas9 sgRNA on- and off-target activity prediction and improvement for method development.

Screening for functional regulatory variants in open chromatin using GenIE-ATAC

Understanding the effects of genetic variation in gene regulatory elements is crucial to interpreting genome function. This is particularly pertinent for the hundreds of thousands of disease-associated variants identified by GWAS, which frequently sit within gene regulatory elements but whose functional effects are often unknown. Current methods are limited in their scalability and ability to assay regulatory variants in their endogenous context, independently of other tightly linked variants. Here, we present a new medium-throughput screening system: genome engineering based interrogation of enhancers assay for transposase accessible chromatin (GenIE-ATAC), that measures the effect of individual variants on chromatin accessibility in their endogenous genomic and chromatin context. We employ this assay to screen for the effects of regulatory variants in human induced pluripotent stem cells, validating a subset of causal variants, and extend our software package (rgenie) to analyse these new data. We demonstrate that this methodology can be used to understand the impact of defined deletions and point mutations within transcription factor binding sites. We thus establish GenIE-ATAC as a method to screen for the effect of gene regulatory element variation, allowing identification and prioritisation of causal variants from GWAS for functional follow-up and understanding the mechanisms of regulatory element function.

Endogenous CRISPR/Cas systems for genome engineering in the acetogens Acetobacterium woodii and Clostridium autoethanogenum

Acetogenic bacteria can play a major role in achieving Net Zero through their ability to convert CO₂ into industrially relevant chemicals and fuels. Full exploitation of this potential will be reliant on effective metabolic engineering tools, such as those based on the Streptococcus pyogenes CRISPR/Cas9 system. However, attempts to introduce cas9-containing vectors into Acetobacterium woodii were unsuccessful, most likely as a consequence of Cas9 nuclease toxicity and the presence of a recognition site for an endogenous A. woodii restriction-modification (R-M) system in the cas9 gene. As an alternative, this study aims to facilitate the exploitation of CRISPR/Cas endogenous systems as genome engineering tools. Accordingly, a Python script was developed to automate the prediction of protospacer adjacent motif (PAM) sequences and used to identify PAM candidates of the A. woodii Type I-B CRISPR/Cas system. The identified PAMs and the native leader sequence were characterized in vivo by interference assay and RT-qPCR, respectively. Expression of synthetic CRISPR arrays, consisting of the native leader sequence, direct repeats, and adequate spacer, along with an editing template for homologous recombination, successfully led to the creation of 300 bp and 354 bp in-frame deletions of pyrE and pheA, respectively. To further validate the method, a 3.2 kb deletion of hsdR1 was also generated, as well as the knock-in of the fluorescence-activating and absorption-shifting tag (FAST) reporter gene at the pheA locus. Homology arm length, cell density, and the amount of DNA used for transformation were found to significantly impact editing efficiencies. The devised workflow was subsequently applied to the Type I-B CRISPR/Cas system of Clostridium autoethanogenum, enabling the generation of a 561 bp in-frame deletion of pyrE with 100% editing efficiency. This is the first report of genome engineering of both A. woodii and C. autoethanogenum using their endogenous CRISPR/Cas systems.

Position-dependent sequence motif preferences of SpCas9 are largely determined by scaffold-complementary spacer motifs

Streptococcus pyogenes Cas9 (SpCas9) nuclease exhibits considerable position-dependent sequence preferences. The reason behind these preferences is not well understood and is difficult to rationalise, since the protein establishes interactions with the target-spacer duplex in a sequence-independent manner. We revealed here that intramolecular interactions within the single guide RNA (sgRNA), between the spacer and the scaffold, cause most of these preferences. By using in cellulo and in vitro SpCas9 activity assays with systematically designed spacer and scaffold sequences and by analysing activity data from a large SpCas9 sequence library, we show that some long (>8 nucleotides) spacer motifs, that are complementary to the RAR unit of the scaffold, interfere with sgRNA loading, and that some motifs of more than 4 nucleotides, that are complementary to the SL1 unit, inhibit DNA binding and cleavage. Furthermore, we show that intramolecular interactions are present in the majority of the inactive sgRNA sequences of the library, suggesting that they are the most important intrinsic determinants of the activity of the SpCas9 ribonucleoprotein complex. We also found that in pegRNAs, sequences at the 3' extension of the sgRNA that are complementary to the SL2 unit are also inhibitory to prime editing, but not to the nuclease activity of SpCas9.

Identification of early flowering mutant gene in Phalaenopsis amabilis (L.) Blume for sgRNA construction in CRISPR/Cas9 genome editing system

Phalaenopsis amabilis (L.) Blume commonly called Moth Orchid (Orchidaceae) is a natural orchid species designated as the National Flower of Indonesia for its beautiful flower shape and long-lasting flowering period. Basically, P. amabilis has a long vegetative phase that cause late flowering, about 2 to 3 years for flowering, hence a method to shorten vegetative period is desired. The latest technological approach that can be used to accelerate flowering of P. amabilis is the CRISPR/Cas9 genome editing method to inactivate the GAI (Gibberellic Acid Insensitive) gene as a mutant gene that can accelerate the regulation of FLOWERING TIME (FT) genes flowering biosynthesis pathway. The approach that needs to be taken is to silence the GAI gene with a knockout system which begins with identifying and characterizing the GAI target gene in the P. amabilis which will be used as a single guide RNA. CRISPR/Cas9 mediated knockout efficiency is highly dependent on the properties of the sgRNA used. SgRNA consists of a target sequence, determining its specificity performance. We executed phylogenetic clustering for the PaGAI protein with closely related orchid species such as Dendrobium capra, Dendrobium cultivars and Cymbidium sinensis. SWISS-Model as tool webserver for protein structure homology modeling. Results show that P. amabilis has a specific domain with the occurrence of point mutations in the two conservative domains. Therefore, a single guide RNA reconstruction needs to be implemented.

Using traditional machine learning and deep learning methods for on- and off-target prediction in CRISPR/Cas9: a review

CRISPR/Cas9 (Clustered Regularly Interspaced Short Palindromic Repeats and CRISPR-associated protein 9) is a popular and effective two-component technology used for targeted genetic manipulation. It is currently the most versatile and accurate method of gene and genome editing, which benefits from a large variety of practical applications. For example, in biomedicine, it has been used in research related to cancer, virus infections, pathogen detection, and genetic diseases. Current CRISPR/Cas9 research is based on data-driven models for on- and off-target prediction as a cleavage may occur at non-target sequence locations. Nowadays, conventional machine learning and deep learning methods are applied on a regular basis to accurately predict on-target knockout efficacy and off-target profile of given single-guide RNAs (sgRNAs). In this paper, we present an overview and a comparative analysis of traditional machine learning and deep learning models used in CRISPR/Cas9. We highlight the key research challenges and directions associated with target activity prediction. We discuss recent advances in the sgRNA-DNA sequence encoding used in state-of-the-art on- and off-target prediction models. Furthermore, we present the most popular deep learning neural network architectures used in CRISPR/Cas9 prediction models. Finally, we summarize the existing challenges and discuss possible future investigations in the field of on- and off-target prediction. Our paper provides valuable support for academic and industrial researchers interested in the application of machine learning methods in the field of CRISPR/Cas9 genome editing.

Deep sampling of gRNA in the human genome and deep-learning-informed prediction of gRNA activities

Life science studies involving clustered regularly interspaced short palindromic repeat (CRISPR) editing generally apply the best-performing guide RNA (gRNA) for a gene of interest. Computational models are combined with massive experimental quantification on synthetic gRNA-target libraries to accurately predict gRNA activity and mutational patterns. However, the measurements are inconsistent between studies due to differences in the designs of the gRNA-target pair constructs, and there has not yet been an integrated investigation that concurrently focuses on multiple facets of gRNA capacity. In this study, we analyzed the DNA double-strand break (DSB)-induced repair outcomes and measured SpCas9/gRNA activities at both matched and mismatched locations using 926,476 gRNAs covering 19,111 protein-coding genes and 20,268 non-coding genes. We developed machine learning models to forecast the on-target cleavage efficiency (AIdit_ON), off-target cleavage specificity (AIdit_OFF), and mutational profiles (AIdit_DSB) of SpCas9/gRNA from a uniformly collected and processed dataset by deep sampling and massively quantifying gRNA capabilities in K562 cells. Each of these models exhibited superlative performance in predicting SpCas9/gRNA activities on independent datasets when benchmarked with previous models. A previous unknown parameter was also empirically determined regarding the "sweet spot" in the size of datasets used to establish an effective model to predict gRNA capabilities at a manageable experimental scale. In addition, we observed cell type-specific mutational profiles and were able to link nucleotidylexotransferase as the key factor driving these outcomes. These massive datasets and deep learning algorithms have been implemented into the user-friendly web service http://crispr-aidit.com to evaluate and rank gRNAs for life science studies.

Engineered CRISPR-OsCas12f1 and RhCas12f1 with robust activities and expanded target range for genome editing

The type V-F CRISPR-Cas12f system is a strong candidate for therapeutic applications due to the compact size of the Cas12f proteins. In this work, we identify six uncharacterized Cas12f1 proteins with nuclease activity in mammalian cells from assembled bacterial genomes. Among them, OsCas12f1 (433 aa) from Oscillibacter sp. and RhCas12f1 (415 aa) from Ruminiclostridium herbifermentans, which respectively target 5' T-rich Protospacer Adjacent Motifs (PAMs) and 5' C-rich PAMs, show the highest editing activity. Through protein and sgRNA engineering, we generate enhanced OsCas12f1 (enOsCas12f1) and enRhCas12f1 variants, with 5'-TTN and 5'-CCD (D = not C) PAMs respectively, exhibiting much higher editing efficiency and broader PAMs, compared with the engineered variant Un1Cas12f1 (Un1Cas12f1_ge4.1). Furthermore, by fusing the destabilized domain with enOsCas12f1, we generate inducible-enOsCas12f1 and demonstate its activity in vivo by single adeno-associated virus delivery. Finally, dead enOsCas12f1-based epigenetic editing and gene activation can also be achieved in mammalian cells. This study thus provides compact gene editing tools for basic research with remarkable promise for therapeutic applications.

Optimization of Cas9 activity through the addition of cytosine extensions to single-guide RNAs

The precise regulation of the activity of Cas9 is crucial for safe and efficient editing. Here we show that the genome-editing activity of Cas9 can be constrained by the addition of cytosine stretches to the 5'-end of conventional single-guide RNAs (sgRNAs). Such a 'safeguard sgRNA' strategy, which is compatible with Cas12a and with systems for gene activation and interference via CRISPR (clustered regularly interspaced short palindromic repeats), leads to the length-dependent inhibition of the formation of functional Cas9 complexes. Short cytosine extensions reduced p53 activation and cytotoxicity in human pluripotent stem cells, and enhanced homology-directed repair while maintaining bi-allelic editing. Longer extensions further decreased on-target activity yet improved the specificity and precision of mono-allelic editing. By monitoring indels through a fluorescence-based allele-specific system and computational simulations, we identified optimal windows of Cas9 activity for a number of genome-editing applications, including bi-allelic and mono-allelic editing, and the generation and correction of disease-associated single-nucleotide substitutions via homology-directed repair. The safeguard-sgRNA strategy may improve the safety and applicability of genome editing.

Application of Nicotinamide to Culture Medium Improves the Efficiency of Genome Editing in Hexaploid Wheat

Histone acetylation is the earliest and most well-characterized of post-translation modifications. It is mediated by histone acetyltransferases (HAT) and histone deacetylases (HDAC). Histone acetylation could change the chromatin structure and status and further regulate gene transcription. In this study, nicotinamide, a histone deacetylase inhibitor (HDACi), was used to enhance the efficiency of gene editing in wheat. Transgenic immature and mature wheat embryos harboring a non-mutated GUS gene, the Cas9 and a GUS-targeting sgRNA were treated with nicotinamide in two concentrations (2.5 and 5 mM) for 2, 7, and 14 days in comparison with a no-treatment control. The nicotinamide treatment resulted in GUS mutations in up to 36% of regenerated plants, whereas no mutants were obtained from the non-treated embryos. The highest efficiency was achieved when treated with 2.5 mM nicotinamide for 14 days. To further validate the impact of nicotinamide treatment on the effectiveness of genome editing, the endogenous TaWaxy gene, which is responsible for amylose synthesis, was tested. Utilizing the aforementioned nicotinamide concentration to treat embryos containing the molecular components for editing the TaWaxy gene, the editing efficiency could be increased to 30.3% and 13.3%, respectively, for immature and mature embryos in comparison to the 0% efficiency observed in the control group. In addition, nicotinamide treatment during transformation progress could also improve the efficiency of genome editing approximately threefold in a base editing experiment. Nicotinamide, as a novel approach, may be employed to improve the editing efficacy of low-efficiency genome editing tools such as base editing and prime editing (PE) systems in wheat.

IVT generation of guideRNAs for Cas9-enrichment Nanopore Sequencing

Generating high-coverage sequencing coverage at select genomic loci has extensive applications in both research science and genetic medicine. Long-read sequencing technologies (e.g. nanopore sequencing) have expanded our ability to generate sequencing data in regions (e.g. repetitive elements) that are difficult to interrogate with short-read sequencing methods. In work presented here, we expand on our previous work using CRISPR/Cas9 for targeted nanopore sequencing by using in vitro transcribed guideRNAs, with 1100 guideRNAs in a single experiment. This approach decreases the cost per guideRNA, increases the number of guideRNAs that can be multiplexed in a single experiment, and provides a way to rapidly screen numerous guideRNAs for cutting efficiency. We apply this strategy in multiple patient-derived pancreatic cancer cell lines, demonstrating its ability to unveil structural variation in "deletion hotspots" around the tumor suppressor genes p16 (CDKN2A), and SMAD4.

Digital data storage on DNA tape using CRISPR base editors

While the archival digital memory industry approaches its physical limits, the demand is significantly increasing, therefore alternatives emerge. Recent efforts have demonstrated DNA's enormous potential as a digital storage medium with superior information durability, capacity, and energy consumption. However, the majority of the proposed systems require on-demand de-novo DNA synthesis techniques that produce a large amount of toxic waste and therefore are not industrially scalable and environmentally friendly. Inspired by the architecture of semiconductor memory devices and recent developments in gene editing, we created a molecular digital data storage system called "DNA Mutational Overwriting Storage" (DMOS) that stores information by leveraging combinatorial, addressable, orthogonal, and independent in vitro CRISPR base-editing reactions to write data on a blank pool of greenly synthesized DNA tapes. As a proof of concept, we wrote both a bitmap representation of our school's logo and the title of this study on the DNA tapes, and accurately recovered the stored data.

IVT generation of guideRNAs for Cas9-enrichment Nanopore Sequencing

Generating high-coverage sequencing coverage at select genomic loci has extensive applications in both research science and genetic medicine. Long-read sequencing technologies (e.g. nanopore sequencing) have expanded our ability to generate sequencing data in regions (e.g. repetitive elements) that are difficult to interrogate with short-read sequencing methods. In work presented here, we expand on our previous work using CRISPR/Cas9 for targeted nanopore sequencing by using in vitro transcribed guideRNAs, with 1100 guideRNAs in a single experiment. This approach decreases the cost per guideRNA, increases the number of guideRNAs that can be multiplexed in a single experiment, and provides a way to rapidly screen numerous guideRNAs for cutting efficiency. We apply this strategy in multiple patient-derived pancreatic cancer cell lines, demonstrating its ability to unveil structural variation in "deletion hotspots" around the tumor suppressor genes p16 ( CDKN2A ), and SMAD4 .

Prediction of Base Editing Efficiencies and Outcomes Using DeepABE and DeepCBE

Adenine base editors (ABEs) and cytosine base editors (CBEs) have been widely used to introduce disease-relevant point mutations at target DNA sites of interest. However, the introduction of point mutations using base editors can be difficult due to low editing efficiencies and/or the existence of multiple target nucleotides within the base editing window at the target site. Thus, previous works have relied heavily on experimentally evaluating the base editing efficiencies and outcomes using time-consuming and labor-intensive multi-step experimental processes. DeepABE and DeepCBE are deep learning-based computational models to predict the efficiencies and outcome frequencies of ABE and CBE at given target DNA sites, in silico. Here, we describe the step-by-step procedure for the accurate determination of specific target nucleotides for ABE or CBE editing on the online available web tool, (DeepBaseEditor, https://deepcrispr.info/DeepBaseEditor ).

Increasing Genome Editing Efficiency of Cas9 Nucleases by the Simultaneous Use of Transcriptional Activators and Histone Acetyltransferase Activator

The CRISPR-Cas9 system shows diverse levels of genome editing activities on eukaryotic chromatin, and high-efficiency sgRNA targets are usually desired in application. In this study, we show that chromatin open status is a pivotal determinant of the Cas9 editing activity in mammalian cells, and increasing chromatin accessibility can efficiently improve Cas9 genome editing. However, the strategy that increases chromatin openness by fusing the VP64 transcriptional activation domain at the C-terminus of Cas9 can only promote genome editing activity slightly at most tested CRISPR-Cas9 targets in Lenti-X 293T cells. Under the enlightenment that histone acetylation increases eukaryotic chromatin accessibility, we developed a composite strategy to further improve genome editing by activating histone acetylation. We demonstrate that promoting histone acetylation using the histone acetyltransferase activator YF-2 can improve the genome editing by Cas9 and, more robustly, by the Cas9 transcriptional activator (Cas9-AD). This strategy holds great potential to enhance CRISPR-Cas9 genome editing and to enable broader CRISPR gRNA target choices for experiments in eukaryotes.

Cognate microglia-T cell interactions shape the functional regulatory T cell pool in experimental autoimmune encephalomyelitis pathology

Microglia, the parenchymal brain macrophages of the central nervous system, have emerged as critical players in brain development and homeostasis. The immune functions of these cells, however, remain less well defined. We investigated contributions of microglia in a relapsing-remitting multiple sclerosis paradigm, experimental autoimmune encephalitis in C57BL/6 x SJL F₁ mice. Fate mapping-assisted translatome profiling during the relapsing-remitting disease course revealed the potential of microglia to interact with T cells through antigen presentation, costimulation and coinhibition. Abundant microglia-T cell aggregates, as observed by histology and flow cytometry, supported the idea of functional interactions of microglia and T cells during remission, with a bias towards regulatory T cells. Finally, microglia-restricted interferon-γ receptor and major histocompatibility complex mutagenesis significantly affected the functionality of the regulatory T cell compartment in the diseased central nervous system and remission. Collectively, our data establish critical non-redundant cognate and cytokine-mediated interactions of microglia with CD4⁺ T cells during autoimmune neuroinflammation.

Evaluation of efficiency prediction algorithms and development of ensemble model for CRISPR/Cas9 gRNA selection

MOTIVATION

The CRISPR/Cas9 system is widely used for genome editing. The editing efficiency of CRISPR/Cas9 is mainly determined by the guide RNA (gRNA). Although many computational algorithms have been developed in recent years, it is still a challenge to select optimal bioinformatics tools for gRNA design in different experimental settings.

RESULTS

We performed a comprehensive comparison analysis of 15 public algorithms for gRNA design, using 16 experimental gRNA datasets. Based on this analysis, we identified the top-performing algorithms, with which we further implemented various computational strategies to build ensemble models for performance improvement. Validation analysis indicates that the new ensemble model had improved performance over any individual algorithm alone at predicting gRNA efficacy under various experimental conditions.

AVAILABILITY AND IMPLEMENTATION

The new sgRNA design tool is freely accessible as a web application via https://crisprdb.org. The source code and stand-alone version is available at Figshare (https://doi.org/10.6084/m9.figshare.21295863) and Github (https://github.com/wang-lab/CRISPRDB).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Integration of CRISPR/Cas9 with artificial intelligence for improved cancer therapeutics

Gene editing has great potential in treating diseases caused by well-characterized molecular alterations. The introduction of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)–based gene-editing tools has substantially improved the precision and efficiency of gene editing. The CRISPR/Cas9 system offers several advantages over the existing gene-editing approaches, such as its ability to target practically any genomic sequence, enabling the rapid development and deployment of novel CRISPR-mediated knock-out/knock-in methods. CRISPR/Cas9 has been widely used to develop cancer models, validate essential genes as druggable targets, study drug-resistance mechanisms, explore gene non-coding areas, and develop biomarkers. CRISPR gene editing can create more-effective chimeric antigen receptor (CAR)-T cells that are durable, cost-effective, and more readily available. However, further research is needed to define the CRISPR/Cas9 system’s pros and cons, establish best practices, and determine social and ethical implications. This review summarizes recent CRISPR/Cas9 developments, particularly in cancer research and immunotherapy, and the potential of CRISPR/Cas9-based screening in developing cancer precision medicine and engineering models for targeted cancer therapy, highlighting the existing challenges and future directions. Lastly, we highlight the role of artificial intelligence in refining the CRISPR system's on-target and off-target effects, a critical factor for the broader application in cancer therapeutics.

BoostMEC: predicting CRISPR-Cas9 cleavage efficiency through boosting models

BACKGROUND

In the CRISPR-Cas9 system, the efficiency of genetic modifications has been found to vary depending on the single guide RNA (sgRNA) used. A variety of sgRNA properties have been found to be predictive of CRISPR cleavage efficiency, including the position-specific sequence composition of sgRNAs, global sgRNA sequence properties, and thermodynamic features. While prevalent existing deep learning-based approaches provide competitive prediction accuracy, a more interpretable model is desirable to help understand how different features may contribute to CRISPR-Cas9 cleavage efficiency.

RESULTS

We propose a gradient boosting approach, utilizing LightGBM to develop an integrated tool, BoostMEC (Boosting Model for Efficient CRISPR), for the prediction of wild-type CRISPR-Cas9 editing efficiency. We benchmark BoostMEC against 10 popular models on 13 external datasets and show its competitive performance.

CONCLUSIONS

BoostMEC can provide state-of-the-art predictions of CRISPR-Cas9 cleavage efficiency for sgRNA design and selection. Relying on direct and derived sequence features of sgRNA sequences and based on conventional machine learning, BoostMEC maintains an advantage over other state-of-the-art CRISPR efficiency prediction models that are based on deep learning through its ability to produce more interpretable feature insights and predictions.

CasPlay provides a gRNA-barcoded CRISPR-based display platform for antibody repertoire profiling

Protein display technologies link proteins to distinct nucleic acid sequences (barcodes), enabling multiplexed protein assays via DNA sequencing. Here, we develop Cas9 display (CasPlay) to interrogate customized peptide libraries fused to catalytically inactive Cas9 (dCas9) by sequencing the guide RNA (gRNA) barcodes associated with each peptide. We first confirm the ability of CasPlay to characterize antibody epitopes by recovering a known binding motif for a monoclonal anti-FLAG antibody. We then use a CasPlay library tiling the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) proteome to evaluate vaccine-induced antibody reactivities. Using a peptide library representing the human virome, we demonstrate the ability of CasPlay to identify epitopes across many viruses from microliters of patient serum. Our results suggest that CasPlay is a viable strategy for customized protein interaction studies from highly complex libraries and could provide an alternative to phage display technologies.

Specificity of oligonucleotide gene therapy (OGT) agents

Oligonucleotide gene therapy (OGT) agents (e. g. antisense, deoxyribozymes, siRNA and CRISPR/Cas) are promising therapeutic tools. Despite extensive efforts, only few OGT drugs have been approved for clinical use. Besides the problem of efficient delivery to targeted cells, hybridization specificity is a potential limitation of OGT agents. To ensure tight binding, a typical OGT agent hybridizes to the stretch of 15-25 nucleotides of a unique targeted sequence. However, hybrids of such lengths tolerate one or more mismatches under physiological conditions, the problem known as the affinity/specificity dilemma. Here, we assess the scale of this problem by analyzing OGT hybridization-dependent off-target effects (HD OTE) in vitro, in animal models and clinical studies. All OGT agents except deoxyribozymes exhibit HD OTE in vitro, with most thorough evidence of poor specificity reported for siRNA and CRISPR/Cas9. Notably, siRNA suppress non-targeted genes due to (1) the partial complementarity to mRNA 3'-untranslated regions (3'-UTR), and (2) the antisense activity of the sense strand. CRISPR/Cas9 system can cause hundreds of non-intended dsDNA breaks due to low specificity of the guide RNA, which can limit therapeutic applications of CRISPR/Cas9 by ex-vivo formats. Contribution of this effects to the observed in vivo toxicity of OGT agents is unclear and requires further investigation. Locked or peptide nucleic acids improve OGT nuclease resistance but not specificity. Approaches that use RNA marker dependent (conditional) activation of OGT agents may improve specificity but require additional validation in cell culture and in vivo.

To indel or not to indel: Factors influencing mutagenesis during chromosomal break end joining

Chromosomal DNA double-strand breaks (DSBs) are the effective lesion of radiotherapy and other clastogenic cancer therapeutics, and are also the initiating event of many approaches to gene editing. Ligation of the DSBs by end joining (EJ) pathways can restore the broken chromosome, but the repair junctions can have insertion/deletion (indel) mutations. The indel patterns resulting from DSB EJ are likely defined by the initial structure of the DNA ends, how the ends are processed and synapsed prior to ligation, and the factors that mediate the ligation step. In this review, we describe key factors that influence these steps of DSB EJ in mammalian cells, which is significant both for understanding mutagenesis resulting from clastogenic cancer therapeutics, and for developing approaches to manipulating gene editing outcomes.

Accounting for small variations in the tracrRNA sequence improves sgRNA activity predictions for CRISPR screening

CRISPR technology is a powerful tool for studying genome function. To aid in picking sgRNAs that have maximal efficacy against a target of interest from many possible options, several groups have developed models that predict sgRNA on-target activity. Although multiple tracrRNA variants are commonly used for screening, no existing models account for this feature when nominating sgRNAs. Here we develop an on-target model, Rule Set 3, that makes optimal predictions for multiple tracrRNA variants. We validate Rule Set 3 on a new dataset of sgRNAs tiling essential and non-essential genes, demonstrating substantial improvement over prior prediction models. By analyzing the differences in sgRNA activity between tracrRNA variants, we show that Pol III transcription termination is a strong determinant of sgRNA activity. We expect these results to improve the performance of CRISPR screening and inform future research on tracrRNA engineering and sgRNA modeling.

Transcriptional regulation of the thymus master regulator Foxn1

FOXN1 is a transcription factor critical for the development of both thymic epithelial cell (TEC) and hair follicle cell (HFC) compartments. However, mechanisms controlling its expression remain poorly understood. To address this question, we performed thorough analyses of the evolutionary conservation and chromatin status of the Foxn1 locus in different tissues and states and identified several putative cis-regulatory regions unique to TECs versus HFCs. Furthermore, experiments using genetically modified mice with specific deletions in the Foxn1 locus and additional bioinformatic analyses helped us identify key regions and transcription factors involved in either positive or negative regulation of Foxn1 in both TECs and HFCs. Specifically, we identified SIX1 and FOXN1 itself as key factors inducing Foxn1 expression in embryonic and neonatal TECs. Together, our data provide important mechanistic insights into the transcriptional regulation of the Foxn1 gene in TEC versus HFC and highlight the role of FOXN1 in its autoregulation.

An oligonucleotide/oligosaccharide-binding-fold protein enhances the alternative splicing event producing thylakoid membrane-bound ascorbate peroxidase in Nicotiana tabacum

The stromal and thylakoid membrane-bound ascorbate peroxidase isoforms are produced by the alternative splicing event of the 3'-terminal region of the APXII gene in spinach (Spinacia oleracea) and tobacco (Nicotiana tabacum), but not in Arabidopsis (Arabidopsis thaliana). However, all alternative splicing variants were detected in APXII gene-transformed Arabidopsis, indicating the occurrence of its regulatory mechanisms in Arabidopsis. The efficiency of this alternative splicing event in producing thylakoid membrane-bound ascorbate peroxidase mRNA is regulated by a splicing regulatory cis element, but trans splicing regulatory factor(s) for alternative splicing remain unclear. To identify this factor, we conducted a forward genetic screen using Arabidopsis in combination with a luciferase reporter system to evaluate the alternative splicing efficiency of thylakoid membrane-bound ascorbate peroxidase mRNA production. We isolated 9 mutant lines that showed low efficiency of the AS in producing thylakoid membrane-bound ascorbate peroxidase mRNA compared with that in the control plants. From one mutant [APXII alternative splicing inhibition (apsi1)], the causal gene responsible for the phenotype, AT5G38890 (oligonucleotide/oligosaccharide-binding-fold protein, APSI1), was identified. The levels of thylakoid membrane-bound ascorbate peroxidase mRNA from the transformed APXII gene decreased and increased in APSI1 knockout and APSI1-overexpressing plants, respectively. APSI1 was localized to the nucleus and specifically bound to the splicing regulatory cis element sequence. Tobacco plants that disrupted the closest homologs of APSI1 showed low levels of endogenous thylakoid membrane-bound ascorbate peroxidase mRNA. These results indicate that APSI1 is an enhancing component of the alternative splicing event of APXII.

Resensitization of Fosfomycin-Resistant Escherichia coli Using the CRISPR System

Antimicrobial resistance is a public health burden with worldwide impacts and was recently identified as one of the major causes of death in 2019. Fosfomycin is an antibiotic commonly used to treat urinary tract infections, and resistance to it in Enterobacteriaceae is mainly due to the metalloenzyme FosA3 encoded by the fosA3 gene. In this work, we adapted a CRISPR-Cas9 system named pRE-FOSA3 to restore the sensitivity of a fosA3+ Escherichia coli strain. The fosA3+ E. coli strain was generated by transforming synthetic fosA3 into a nonpathogenic E. coli TOP10. To mediate the fosA3 disruption, two guide RNAs (gRNAs) were selected that used conserved regions within the fosA3 sequence of more than 700 fosA3+ E. coli isolates, and the resensitization plasmid pRE-FOSA3 was assembled by cloning the gRNA into pCas9. gRNA_195 exhibited 100% efficiency in resensitizing the bacteria to fosfomycin. Additionally, the edited strain lost the ampicillin resistance encoded in the same plasmid containing the synthetic fosA3 gene, despite not being the CRISPR-Cas9 target, indicating plasmid clearance. The in vitro analysis presented here points to a path that can be explored to assist the development of effective alternative methods of treatment against fosA3+ bacteria.

CRISPR/Cas9 suppression of OsAT10, a rice BAHD acyltransferase, reduces p-coumaric acid incorporation into arabinoxylan without increasing saccharification

Ester-linked hydroxycinnamic acids ferulic acid (FA) and para-coumaric acid (p-CA) play important roles in crosslinking within cell wall arabinoxylans (AX) and between AX and lignin in grass cell walls. The addition of hydroxycinnamates to AX, is mediated by the Mitchell clade of BAHD acyl-coenzyme A-utilizing transferases. Overexpression of OsAT10 (a Mitchell clade BAHD acyl transferase) in rice, has previously been shown to increase p-CA content in AX in leaves and stems, leading to increased cell wall digestibility, potentially associated with a concomitant decrease in FA content. To investigate the physiological role of OsAT10 we established CRISPR/Cas9 rice knock-out mutants devoid of OsAT10. Our analysis of hydroxycinnamic acid content in wild type plants revealed that AX associated p-CA is found almost exclusively in rice husks, with very little found in other tissues. Mutant plants were essentially devoid of ester-linked p-CA associated with AX, indicating that OsAT10 represents the major enzyme responsible for the addition of p-CA to arabinoxylan in rice plants. We found no change in the digestibility of rice husk lacking AX-associated p-CA, suggesting that the changes in digestibility seen in OsAT10 overexpressing plants were solely due to compensatory decreases in AX-associated FA.

ORAI3 is dispensable for store-operated Ca2+ entry and immune responses by lymphocytes and macrophages

Ca2+ signals regulate the function of many immune cells and promote immune responses to infection, cancer, and autoantigens. Ca2+ influx in immune cells is mediated by store-operated Ca2+ entry (SOCE) that results from the opening of Ca2+ release-activated Ca2+ (CRAC) channels. The CRAC channel is formed by three plasma membrane proteins, ORAI1, ORAI2, and ORAI3. Of these, ORAI1 is the best studied and plays important roles in immune function. By contrast, the physiological role of ORAI3 in immune cells remains elusive. We show here that ORAI3 is expressed in many immune cells including macrophages, B cells, and T cells. To investigate ORAI3 function in immune cells, we generated Orai3-/- mice. The development of lymphoid and myeloid cells in the thymus and bone marrow was normal in Orai3-/- mice, as was the composition of immune cells in secondary lymphoid organs. Deletion of Orai3 did not affect SOCE in B cells and T cells but moderately enhanced SOCE in macrophages. Orai3-deficient macrophages, B cells, and T cells had normal effector functions in vitro. Immune responses in vivo, including humoral immunity (T cell dependent or independent) and antitumor immunity, were normal in Orai3-/- mice. Moreover, Orai3-/- mice showed no differences in susceptibility to septic shock, experimental autoimmune encephalomyelitis, or collagen-induced arthritis. We conclude that despite its expression in myeloid and lymphoid cells, ORAI3 appears to be dispensable or redundant for physiological and pathological immune responses mediated by these cells.

Exonucleases: Degrading DNA to Deal with Genome Damage, Cell Death, Inflammation and Cancer

Although DNA degradation might seem an unwanted event, it is essential in many cellular processes that are key to maintaining genomic stability and cell and organism homeostasis. The capacity to cut out nucleotides one at a time from the end of a DNA chain is present in enzymes called exonucleases. Exonuclease activity might come from enzymes with multiple other functions or specialized enzymes only dedicated to this function. Exonucleases are involved in central pathways of cell biology such as DNA replication, repair, and death, as well as tuning the immune response. Of note, malfunctioning of these enzymes is associated with immune disorders and cancer. In this review, we will dissect the impact of DNA degradation on the DNA damage response and its links with inflammation and cancer.

SgRNA-RF: Identification of SgRNA On-Target Activity With Imbalanced Datasets

Single-guide RNA is a guide RNA (gRNA), which guides the insertion or deletion of uridine residues into kinetoplastid during RNA editing. It is a small non-coding RNA that can be combined with pre -mRNA pairing. SgRNA is a critical component of the CRISPR/Cas9 gene knockout system and play an important role in gene editing and gene regulation. It is important to accurately and quickly identify highly on-target activity sgRNAs. Due to its importance, several computational predictors have been proposed to predict sgRNAs on-target activity. All these methods have clearly contributed to the development of this very important field. However, they also have certain limitations. In the paper, we developed a new classifier SgRNA-RF, which extracts the features of nucleic acid composition and structure of on-target activity sgRNA sequence and identified by random forest algorithm. In addition to solving an imbalanced dataset, this paper proposed a new method called CS-Smote. We compared sgRNA-RF with state-of-the-art predictors on the five datasets, and found SgRNA-RF significantly improved the identification accuracy, with accuracies of 0.8636,0.9161,0.894,0.938,0.965,0.77,0.979,0.973, respectively. The user-friendly web server that implements sgRNA-RF is freely available at http://server.malab.cn/sgRNA-RF/.

From design to validation of CRISPR/gRNA primers towards genome editing

CRISPR (Clustered Regularly Interspaced Short Palindromic Repeats)/Cas9 (CRISPR-associated system) is used to edit specific genomic sequences with precision and efficacy. There are many online platforms/software for the design of gRNAs and related primers. However, there are concerns in design regarding off-site deletions besides knocking out sequences in the target genes. Nonetheless, a well known robust platform for CRISPR/gRNA primers design is CRISPRdirect. We demonstrate the use of this tool in the design of CRISPR/gRNA primers for soluble starch synthases (SSS) II-1, 2, and 3 genes in the Oryza sativa genome followed by the PCR-mediated amplification of SSS genes with corresponding confirmation towards genome editing having improved phenotype features.

CRISPR/Cas9 gRNA activity depends on free energy changes and on the target PAM context

A major challenge of CRISPR/Cas9-mediated genome engineering is that not all guide RNAs (gRNAs) cleave the DNA efficiently. Although the heterogeneity of gRNA activity is well recognized, the current understanding of how CRISPR/Cas9 activity is regulated remains incomplete. Here, we identify a sweet spot range of binding free energy change for optimal efficiency which largely explains why gRNAs display changes in efficiency at on- and off-target sites, including why gRNAs can cleave an off-target with higher efficiency than the on-target. Using an energy-based model, we show that local gRNA-DNA interactions resulting from Cas9 "sliding" on overlapping protospacer adjacent motifs (PAMs) profoundly impact gRNA activities. Combining the effects of local sliding for a given PAM context with global off-targets allows us to better identify highly specific, and thus efficient, gRNAs. We validate the effects of local sliding on gRNA efficiency using both public data and in-house data generated by measuring SpCas9 cleavage efficiency at 1024 sites designed to cover all possible combinations of 4-nt PAM and context sequences of 4 gRNAs. Our results provide insights into the mechanisms of Cas9-PAM compatibility and cleavage activation, underlining the importance of accounting for local sliding in gRNA design.