Guide-target mismatch effects on dCas9-sgRNA binding activity in living bacterial cells

Graded-CRISPRi, a Tool for Tuning the Strengths of CRISPRi-Mediated Knockdowns in Vibrio natriegens Using gRNA Libraries

In recent years, the fast-growing bacterium Vibrio natriegens has gained increasing attention as it has the potential to become a next-generation chassis for synthetic biology. A wide range of genetic parts and genome engineering methods have already been developed. However, there is still a need for a well-characterized tool to effectively and gradually reduce the expression levels of native genes. To bridge this gap, we created graded-CRISPRi, a system utilizing gRNA variants that lead to varying levels of repression strength. By incorporating multiple gRNA sequences into our design, we successfully extended this concept to simultaneously repress four distinct reporter genes. Furthermore, we demonstrated the capability of using graded-CRISPRi to target native genes, thereby examining the effect of various knockdown levels on growth.

CRISPR/Cas9 gene editing: a novel strategy for fighting drug resistance in respiratory disorders

Respiratory disorders are among the conditions that affect the respiratory system. The healthcare sector faces challenges due to the emergence of drug resistance to prescribed medications for these illnesses. However, there is a technology called CRISPR/Cas9, which uses RNA to guide DNA targeting. This technology has revolutionized our ability to manipulate and visualize the genome, leading to advancements in research and treatment development. It can effectively reverse epigenetic alterations that contribute to drug resistance. Some studies focused on health have shown that targeting genes using CRISPR/Cas9 can be challenging when it comes to reducing drug resistance in patients with respiratory disorders. Nevertheless, it is important to acknowledge the limitations of this technology, such as off-target effects, immune system reactions to Cas9, and challenges associated with delivery methods. Despite these limitations, this review aims to provide knowledge about CRISPR/Cas9 genome editing tools and explore how they can help overcome resistance in patients with respiratory disorders. Additionally, this study discusses concerns related to applications of CRISPR and provides an overview of successful clinical trial studies.

CRISPR-Cas9 delivery strategies and applications: Review and update

Nowadays, a significant part of the investigations carried out in the medical field belong to cancer treatment. Generally, conventional cancer treatments, including chemotherapy, radiotherapy, and surgery, which have been used for a long time, are not sufficient, especially in malignant cancers. Because genetic mutations cause cancers, researchers are trying to treat these diseases using genetic engineering tools. One of them is clustered regularly interspaced short palindromic repeats (CRISPR), a powerful tool in genetic engineering in the last decade. CRISPR, which forms the CRISPR-Cas structure with its endonuclease protein, Cas, is known as a part of the immune system (adaptive immunity) in bacteria and archaea. Among the types of Cas proteins, Cas9 endonuclease has been used in many scientific studies due to its high accuracy and efficiency. This review reviews the CRISPR system, focusing on the history, classification, delivery methods, applications, new generations, and challenges of CRISPR-Cas9 technology.

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.

Vector enabled CRISPR gene editing - A revolutionary strategy for targeting the diversity of brain pathologies

Brain pathologies are considered one of the greatest contributors of death and disability worldwide. Neurodegenerative Alzheimer's disease is the second leading cause of death in adults, whilst brain cancers including glioblastoma multiforme in adults, and pediatric-type high-grade gliomas in children remain largely untreatable. A further compounding issue for patients with brain pathologies is that of long-term neuropsychiatric sequela - as a symptom or arising from high dose therapeutic intervention. The major challenge to effective, low dose treatment is finding therapeutics that successfully cross the blood-brain barrier and target aberrant cellular processes, while having minimum effect on essential cellular processes, and healthy bystander cells. Following over 30 years of research, CRISPR technology has emerged as a biomedical tour de force with the potential to revolutionise the treatment of both neurological and cancer related brain pathologies. The aim of this review is to take stock of the progress made in CRISPR technology in relation to treating brain pathologies. Specifically, we will describe studies which look beyond design, synthesis, and theoretical application; and focus instead on in vivo studies with translation potential. Along with discussing the latest breakthrough techniques being applied within the CRISPR field, we aim to provide a prospective on the knowledge gaps that exist and challenges that still lay ahead for CRISPR technology prior to successful application in the brain disease treatment field.

Deep learning in CRISPR-Cas systems: a review of recent studies

In genetic engineering, the revolutionary CRISPR-Cas system has proven to be a vital tool for precise genome editing. Simultaneously, the emergence and rapid evolution of deep learning methodologies has provided an impetus to the scientific exploration of genomic data. These concurrent advancements mandate regular investigation of the state-of-the-art, particularly given the pace of recent developments. This review focuses on the significant progress achieved during 2019-2023 in the utilization of deep learning for predicting guide RNA (gRNA) activity in the CRISPR-Cas system, a key element determining the effectiveness and specificity of genome editing procedures. In this paper, an analytical overview of contemporary research is provided, with emphasis placed on the amalgamation of artificial intelligence and genetic engineering. The importance of our review is underscored by the necessity to comprehend the rapidly evolving deep learning methodologies and their potential impact on the effectiveness of the CRISPR-Cas system. By analyzing recent literature, this review highlights the achievements and emerging trends in the integration of deep learning with the CRISPR-Cas systems, thus contributing to the future direction of this essential interdisciplinary research area.

Computational design of CRISPR guide RNAs to enable strain-specific control of microbial consortia

Microbes naturally coexist in complex, multistrain communities. However, extracting individual microbes from and specifically manipulating the composition of these consortia remain challenging. The sequence-specific nature of CRISPR guide RNAs can be leveraged to accurately differentiate microorganisms and facilitate the creation of tools that can achieve these tasks. We developed a computational program, ssCRISPR, which designs strain-specific CRISPR guide RNA sequences with user-specified target strains, protected strains, and guide RNA properties. We experimentally verify the accuracy of the strain specificity predictions in both Escherichia coli and Pseudomonas spp. and show that up to three nucleotide mismatches are often required to ensure perfect specificity. To demonstrate the functionality of ssCRISPR, we apply computationally designed CRISPR-Cas9 guide RNAs to two applications: the purification of specific microbes through one- and two-plasmid transformation workflows and the targeted removal of specific microbes using DNA-loaded liposomes. For strain purification, we utilize gRNAs designed to target and kill all microbes in a consortium except the specific microbe to be isolated. For strain elimination, we utilize gRNAs designed to target only the unwanted microbe while protecting all other strains in the community. ssCRISPR will be of use in diverse microbiota engineering applications.

Exploring and engineering PAM-diverse Streptococci Cas9 for PAM-directed bifunctional and titratable gene control in bacteria

The RNA-guided Cas9s serve as powerful tools for programmable gene editing and regulation; their targeting scopes and efficacies, however, are always constrained by the PAM sequence stringency. Most Streptococci Cas9s, including the prototype SpCas9 from S. pyogenes, specifically recognize a canonical NGG PAM via a conserved RxR PAM-binding motif within the PAM-interaction (PI) domain. Here, SpCas9-based mining unveils three distinct and rarely presented PAM-binding motifs (QxxxR, QxQ and RxQ) among Streptococci Cas9 orthologs. With the catalytically-dead QxxxR-containing SedCas9 from S. equinus, we dissect its NAG PAM specificity and elucidate its underlying recognition mechanism via computational prediction and mutagenesis analysis. Replacing the SedCas9 PI domain with alternate PAM-binding motifs rewires its PAM specificity to NGG or NAA. Moreover, a semi-rational design with minimal mutation creates a SedCas9-NQ variant showing robust activity towards expanded NNG and NAA PAMs, based upon which we engineered a compact ω-SedCas9-NQ transcriptional regulator for PAM-directed bifunctional and titratable gene control. The ω-SedCas9-NQ mediated metabolic reprogramming of endogenous genes in Escherichia coli affords a 2.6-fold increase of 4-hydroxycoumarin production. This work reveals new Cas9 scaffolds with distinct PAM-binding motifs for PAM relaxation and creates a new PAM-diverse Cas9 variant for versatile gene control in bacteria.

Biosensor-assisted titratable CRISPRi high-throughput (BATCH) screening for over-production phenotypes

With rapid advances in the development of metabolic pathways and synthetic biology toolkits, a persisting challenge in microbial bioproduction is how to optimally rewire metabolic fluxes and accelerate the concomitant high-throughput phenotype screening. Here we developed a biosensor-assisted titratable CRISPRi high-throughput (BATCH) screening approach that combines a titratable mismatch CRISPR interference and a biosensor mediated screening for high-production phenotypes in Escherichia coli. We first developed a programmable mismatch CRISPRi that could afford multiple levels of interference efficacy with a one-pot sgRNA pool (a total of 16 variants for each target gene) harboring two consecutive random mismatches in the seed region of sgRNA spacers. The mismatch CRISPRi was demonstrated to enable almost a full range of gene knockdown when targeting different positions on genes. As a proof-of-principle demonstration of the BATCH screening system, we designed doubly mismatched sgRNA pools targeting 20 relevant genes in E. coli and optimized a PadR-based p-coumaric acid biosensor with broad dynamic range for the eGFP fluorescence guided high-production screening. Using sgRNA variants for the combinatorial knockdown of pfkA and ptsI, the p-coumaric acid titer was increased by 40.6% to o 1308.6 mg/l from glycerol in shake flasks. To further demonstrate the general applicability of the BATCH screening system, we recruited a HpdR-based butyrate biosensor that facilitated the screening of E. coli strains achieving 19.0% and 25.2% increase of butyrate titer in shake flasks with sgRNA variants targeting sucA and ldhA, respectively. This work reported the establishment of a plug-and-play approach that enables multilevel modulation of metabolic fluxes and high-throughput screening of high-production phenotypes.

From DNA-protein interactions to the genetic circuit design using CRISPR-dCas systems

In the last decade, the CRISPR-Cas technology has gained widespread popularity in different fields from genome editing and detecting specific DNA/RNA sequences to gene expression control. At the heart of this technology is the ability of CRISPR-Cas complexes to be programmed for targeting particular DNA loci, even when using catalytically inactive dCas-proteins. The repertoire of naturally derived and engineered dCas-proteins including fusion proteins presents a promising toolbox that can be used to construct functional synthetic genetic circuits. Rational genetic circuit design, apart from having practical relevance, is an important step towards a deeper quantitative understanding of the basic principles governing gene expression regulation and functioning of living organisms. In this minireview, we provide a succinct overview of the application of CRISPR-dCas-based systems in the emerging field of synthetic genetic circuit design. We discuss the diversity of dCas-based tools, their properties, and their application in different types of genetic circuits and outline challenges and further research directions in the field.

HUGE pipeline to measure temporal genetic variation in Drosophila suzukii populations for genetic biocontrol applications

Understanding the fine-scale genome sequence diversity that exists within natural populations is important for developing models of species migration, temporal stability, and range expansion. For invasive species, agricultural pests, and disease vectors, sequence diversity at specific loci in the genome can impact the efficacy of next-generation genetic biocontrol strategies. Here we describe a pipeline for haplotype-resolution genetic variant discovery and quantification from thousands of Spotted Wing Drosophila (Drosophila suzukii, SWD) isolated at two field sites in the North-Central United States (Minnesota) across two seasons. We observed highly similar single nucleotide polymorphism (SNP) frequencies at each genomic location at each field site and year. This supports the hypotheses that SWD overwinters in Minnesota, is annually populated by the same source populations or a combination of both theories. Also, the stable genetic structure of SWD populations allows for the rational design of genetic biocontrol technologies for population suppression.

Efficient Single-Nucleotide Microbial Genome Editing Achieved Using CRISPR/Cpf1 with Maximally 3'-End-Truncated crRNAs

Mismatch tolerance, a cause of the off-target effect, impedes accurate genome editing with the CRISPR/Cas system. Herein, we observed that oligonucleotide-directed single-base substitutions could be rarely introduced in the microbial genome using CRISPR/Cpf1-mediated negative selection. Because crRNAs have the ability to recognize and discriminate among specific target DNA sequences, we systematically compared the effects of modified crRNAs with 3′-end nucleotide truncations and a single mismatch on the genomic cleavage activity of FnCpf1 inEscherichia coli. Five nucleotides could be maximally truncated at the crRNA 3′-end for the efficient cleavage of the DNA targets of galK and xylB in the cells. However, target cleavage in the genome was inefficient when a single mismatch was simultaneously introduced in the maximally 3′-end-truncated crRNA. Based on these results, we assumed that the maximally truncated crRNA-Cpf1 complex can distinguish between single-base-edited and unedited targets in vivo. Compared to other crRNAs with shorter truncations, maximally 3′-end-truncated crRNAs showed highly efficient single-base substitutions (>80%) in the DNA targets of galK and xylB. Furthermore, the editing efficiency for the 24 bases in both galK and xylB showed success rates of 79 and 50%, respectively. We successfully introduced single-nucleotide indels in galK and xylB with editing efficiencies of 79 and 62%, respectively. Collectively, the maximally truncated crRNA-Cpf1 complex could perform efficient base and nucleotide editing regardless of the target base location or mutation type; this system is a simple and efficient tool for microbial genome editing, including indel correction, at the single-nucleotide resolution.

CRISPR/dCas9-Based Systems: Mechanisms and Applications in Plant Sciences

RNA-guided genomic transcriptional regulation tools, namely clustered regularly interspaced short palindromic repeats interference (CRISPRi) and CRISPR-mediated gene activation (CRISPRa), are a powerful technology for gene functional studies. Deriving from the CRISPR/Cas9 system, both systems consist of a catalytically dead Cas9 (dCas9), a transcriptional effector and a single guide RNA (sgRNA). This type of dCas9 is incapable to cleave DNA but retains its ability to specifically bind to DNA. The binding of the dCas9/sgRNA complex to a target gene results in transcriptional interference. The CRISPR/dCas9 system has been explored as a tool for transcriptional modulation and genome imaging. Despite its potential applications and benefits, the challenges and limitations faced by the CRISPR/dCas9 system include the off-target effects, protospacer adjacent motif (PAM) sequence requirements, efficient delivery methods and the CRISPR/dCas9-interfered crops being labeled as genetically modified organisms in several countries. This review highlights the progression of CRISPR/dCas9 technology as well as its applications and potential challenges in crop improvement.

Genome-scale target identification in Escherichia coli for high-titer production of free fatty acids

To construct a superior microbial cell factory for chemical synthesis, a major challenge is to fully exploit cellular potential by identifying and engineering beneficial gene targets in sophisticated metabolic networks. Here, we take advantage of CRISPR interference (CRISPRi) and omics analyses to systematically identify beneficial genes that can be engineered to promote free fatty acids (FFAs) production in Escherichia coli. CRISPRi-mediated genetic perturbation enables the identification of 30 beneficial genes from 108 targets related to FFA metabolism. Then, omics analyses of the FFAs-overproducing strains and a control strain enable the identification of another 26 beneficial genes that are seemingly irrelevant to FFA metabolism. Combinatorial perturbation of four beneficial genes involving cellular stress responses results in a recombinant strain ihfA^L−-aidB⁺-ryfA^M−-gadA^H−, producing 30.0 g L⁻¹ FFAs in fed-batch fermentation, the maximum titer in E. coli reported to date. Our findings are of help in rewiring cellular metabolism and interwoven intracellular processes to facilitate high-titer production of biochemicals.

Identification of gene targets is one of the major challenges to construct superior microbial cell factory for chemical synthesis. Here, the authors employ CRISPRi and omics analyses for genome-scale target genes identification for high-titer production of free fatty acids in E. coli.