Improved sgRNA design in bacteria via genome-wide activity profiling

Multiplex CRISPR-Cas Genome Editing: Next-Generation Microbial Strain Engineering

Genome editing is a crucial technology for obtaining desired phenotypes in a variety of species, ranging from microbes to plants, animals, and humans. With the advent of CRISPR-Cas technology, it has become possible to edit the intended sequence by modifying the target recognition sequence in guide RNA (gRNA). By expressing multiple gRNAs simultaneously, it is possible to edit multiple targets at the same time, allowing for the simultaneous introduction of various functions into the cell. This can significantly reduce the time and cost of obtaining engineered microbial strains for specific traits. In this review, we investigate the resolution of multiplex genome editing and its application in engineering microorganisms, including bacteria and yeast. Furthermore, we examine how recent advancements in artificial intelligence technology could assist in microbial genome editing and engineering. Based on these insights, we present our perspectives on the future evolution and potential impact of multiplex genome editing technologies in the agriculture and food industry.

Cell-Free Protein Expression in Polymer Materials

While synthetic biology has advanced complex capabilities such as sensing and molecular synthesis in aqueous solutions, important applications may also be pursued for biological systems in solid materials. Harsh processing conditions used to produce many synthetic materials such as plastics make the incorporation of biological functionality challenging. One technology that shows promise in circumventing these issues is cell-free protein synthesis (CFPS), where core cellular functionality is reconstituted outside the cell. CFPS enables genetic functions to be implemented without the complications of membrane transport or concerns over the cellular viability or release of genetically modified organisms. Here, we demonstrate that dried CFPS reactions have remarkable tolerance to heat and organic solvent exposure during the casting processes for polymer materials. We demonstrate the utility of this observation by creating plastics that have spatially patterned genetic functionality, produce antimicrobials in situ, and perform sensing reactions. The resulting materials unlock the potential to deliver DNA-programmable biofunctionality in a ubiquitous class of synthetic materials.

CRISPR-COPIES: an in silico platform for discovery of neutral integration sites for CRISPR/Cas-facilitated gene integration

The CRISPR/Cas system has emerged as a powerful tool for genome editing in metabolic engineering and human gene therapy. However, locating the optimal site on the chromosome to integrate heterologous genes using the CRISPR/Cas system remains an open question. Selecting a suitable site for gene integration involves considering multiple complex criteria, including factors related to CRISPR/Cas-mediated integration, genetic stability, and gene expression. Consequently, identifying such sites on specific or different chromosomal locations typically requires extensive characterization efforts. To address these challenges, we have developed CRISPR-COPIES, a COmputational Pipeline for the Identification of CRISPR/Cas-facilitated intEgration Sites. This tool leverages ScaNN, a state-of-the-art model on the embedding-based nearest neighbor search for fast and accurate off-target search, and can identify genome-wide intergenic sites for most bacterial and fungal genomes within minutes. As a proof of concept, we utilized CRISPR-COPIES to characterize neutral integration sites in three diverse species: Saccharomyces cerevisiae, Cupriavidus necator, and HEK293T cells. In addition, we developed a user-friendly web interface for CRISPR-COPIES (https://biofoundry.web.illinois.edu/copies/). We anticipate that CRISPR-COPIES will serve as a valuable tool for targeted DNA integration and aid in the characterization of synthetic biology toolkits, enable rapid strain construction to produce valuable biochemicals, and support human gene and cell therapy applications.

HyCas9-12aGEP: an efficient genome editing platform for Corynebacterium glutamicum

Corynebacterium glutamicum plays a crucial role as a significant industrial producer of metabolites. Despite the successful development of CRISPR-Cas9 and CRISPR-Cas12a-assisted genome editing technologies in C. glutamicum, their editing resolution and efficiency are hampered by the diverse on-target activities of guide RNAs (gRNAs). To address this problem, a hybrid CRISPR-Cas9-Cas12a genome editing platform (HyCas9-12aGEP) was developed in C. glutamicum in this study to co-express sgRNA (corresponding to SpCas9 guide RNA), crRNA (corresponding to FnCas12a guide RNA), or hfgRNA (formed by the fusion of sgRNA and crRNA). HyCas9-12aGEP improves the efficiency of mapping active gRNAs and outperforms both CRISPR-Cas9 and CRISPR-Cas12a in genome editing resolution and efficiency. In the experiment involving the deletion of the cg0697-0740 gene segment, an unexpected phenotype was observed, and HyCas9-12aGEP efficiently identified the responsible genotype from more than 40 genes. Here, HyCas9-12aGEP greatly improve our capability in terms of genome reprogramming in C. glutamicum.

Software-based screening for efficient sgRNAs in Lactococcus lactis

BACKGROUND

The two essential editing elements in the clustered regularly interspaced short palindromic repeats (CRISPR) editing system are promoter and single-guide RNA (sgRNA), the latter of which determines whether Cas protein can precisely target a specific location to edit the targeted gene. Therefore, the selection of sgRNA is crucial to the efficiency of the CRISPR editing system. Various online prediction tools for sgRNA are currently available. These tools can predict all possible sgRNAs of the targeted gene and rank sgRNAs according to certain scoring criteria according to the demands of the user.

RESULTS

We designed sgRNAs for Lactococcus lactis NZ9000 LLNZ_RS02020 (ldh) and LLNZ_RS10925 (upp) individually using online prediction software - CRISPOR - and successfully constructed a series of knockout strains to allow comparison of the knockout efficiency of each sgRNA and analyze the differences between software predictions and actual experimental results.

CONCLUSION

Our experimental results showed that the actual editing efficiency of the screened sgRNAs did not match the predicted results - a phenomenon that suggests that established findings from eukaryotic studies are not universally applicable to prokaryotes. Software prediction can still be used as a tool for the initial screening of sgRNAs before further selection of suitable sgRNAs through experimental experience. © 2023 Society of Chemical Industry.

A CRISPRi-based genetic resource to study essential Staphylococcus aureus genes

IMPORTANCE

Staphylococcus aureus is an important clinical pathogen that causes a high number of antibiotic-resistant infections. The study of S. aureus biology, and particularly of the function of essential proteins, is of particular importance to develop new approaches to combat this pathogen. We have optimized a clustered regularly interspaced short palindromic repeat interference (CRISPRi) system that allows efficient targeting of essential S. aureus genes. Furthermore, we have used that system to construct a library comprising 261 strains, which allows the depletion of essential proteins encoded by 200 genes/operons. This library, which we have named Lisbon CRISPRi Mutant Library, should facilitate the study of S. aureus pathogenesis and biology.

Genome Editing, Transcriptional Regulation, and Forward Genetic Screening Using CRISPR-Cas12a Systems in Yarrowia lipolytica

Class II Type V endonucleases have increasingly been adapted to develop sophisticated and easily accessible synthetic biology tools for genome editing, transcriptional regulation, and functional genomic screening in a wide range of organisms. One such endonuclease, Cas12a, presents itself as an attractive alternative to Cas9-based systems. The ability to mature its own guide RNAs (gRNAs) from a single transcript has been leveraged for easy multiplexing, and its lack of requirement of a tracrRNA element, also allows for short gRNA expression cassettes. To extend these functionalities into the industrially relevant oleaginous yeast Yarrowia lipolytica, we developed a set of CRISPR-Cas12a vectors for easy multiplexed gene knockout, repression, and activation. We further extended the utility of this CRISPR-Cas12a system to functional genomic screening by constructing a genome-wide guide library targeting every gene with an eightfold coverage. Pooled CRISPR screens conducted with this library were used to profile Cas12a guide activities and develop a machine learning algorithm that could accurately predict highly efficient Cas12a gRNA. In this protocols chapter, we first present a method by which protein coding genes may be functionally disrupted via indel formation with CRISPR-Cas12a systems. Further, we describe how Cas12a fused to a transcriptional regulator can be used in conjunction with shortened gRNA to achieve transcriptional repression or activation. Finally, we describe the design, cloning, and validation of a genome-wide library as well as a protocol for the execution of a pooled CRISPR screen, to determine guide activity profiles in a genome-wide context in Y. lipolytica. The tools and strategies discussed here expand the list of available synthetic biology tools for facile genome engineering in this industrially important host.

Engineering E. coli strains using antibiotic-resistance-gene-free plasmids

We created a generalizable pipeline for antibiotic-resistance-gene-free plasmid (ARGFP)-based cloning using a dual auxotrophic- and essential-gene-based selection strategy. We use auxotrophic selection to construct plasmids in engineered E. coli DH10B cloning strains and both auxotrophic- and essential-gene-based selection to (1) select for recombinant strains and (2) maintain a plasmid in E. coli Nissle 1917, a common chassis for engineered probiotic applications, and E. coli MG1655, the laboratory "wild-type" E. coli strain. We show that our approach has comparable efficiency to that of antibiotic-resistance-gene-based cloning. We also show that the double-knockout Nissle and MG1655 strains are simple to transform with plasmids of interest. Notably, we show that the engineered Nissle strains are amenable to long-term plasmid maintenance in repeated culturing as well as in the mouse gut, demonstrating the potential for broad applications while minimizing the risk of antibiotic resistance spread via horizontal gene transfer.

A rugged yet easily navigable fitness landscape

Fitness landscape theory predicts that rugged landscapes with multiple peaks impair Darwinian evolution, but experimental evidence is limited. In this study, we used genome editing to map the fitness of >260,000 genotypes of the key metabolic enzyme dihydrofolate reductase in the presence of the antibiotic trimethoprim, which targets this enzyme. The resulting landscape is highly rugged and harbors 514 fitness peaks. However, its highest peaks are accessible to evolving populations via abundant fitness-increasing paths. Different peaks share large basins of attraction that render the outcome of adaptive evolution highly contingent on chance events. Our work shows that ruggedness need not be an obstacle to Darwinian evolution but can reduce its predictability. If true in general, the complexity of optimization problems on realistic landscapes may require reappraisal.

Quantum biological insights into CRISPR-Cas9 sgRNA efficiency from explainable-AI driven feature engineering

CRISPR-Cas9 tools have transformed genetic manipulation capabilities in the laboratory. Empirical rules-of-thumb have been developed for only a narrow range of model organisms, and mechanistic underpinnings for sgRNA efficiency remain poorly understood. This work establishes a novel feature set and new public resource, produced with quantum chemical tensors, for interpreting and predicting sgRNA efficiency. Feature engineering for sgRNA efficiency is performed using an explainable-artificial intelligence model: iterative Random Forest (iRF). By encoding quantitative attributes of position-specific sequences for Escherichia coli sgRNAs, we identify important traits for sgRNA design in bacterial species. Additionally, we show that expanding positional encoding to quantum descriptors of base-pair, dimer, trimer, and tetramer sequences captures intricate interactions in local and neighboring nucleotides of the target DNA. These features highlight variation in CRISPR-Cas9 sgRNA dynamics between E. coli and H. sapiens genomes. These novel encodings of sgRNAs enhance our understanding of the elaborate quantum biological processes involved in CRISPR-Cas9 machinery.

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.

A generalizable Cas9/sgRNA prediction model using machine transfer learning with small high-quality datasets

The CRISPR/Cas9 nuclease from Streptococcus pyogenes (SpCas9) can be used with single guide RNAs (sgRNAs) as a sequence-specific antimicrobial agent and as a genome-engineering tool. However, current bacterial sgRNA activity models struggle with accurate predictions and do not generalize well, possibly because the underlying datasets used to train the models do not accurately measure SpCas9/sgRNA activity and cannot distinguish on-target cleavage from toxicity. Here, we solve this problem by using a two-plasmid positive selection system to generate high-quality data that more accurately reports on SpCas9/sgRNA cleavage and that separates activity from toxicity. We develop a machine learning architecture (crisprHAL) that can be trained on existing datasets, that shows marked improvements in sgRNA activity prediction accuracy when transfer learning is used with small amounts of high-quality data, and that can generalize predictions to different bacteria. The crisprHAL model recapitulates known SpCas9/sgRNA-target DNA interactions and provides a pathway to a generalizable sgRNA bacterial activity prediction tool that will enable accurate antimicrobial and genome engineering applications.

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.

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.

High-Density Guide RNA Tiling and Machine Learning for Designing CRISPR Interference in Synechococcus sp. PCC 7002

While CRISPRi was previously established in Synechococcus sp. PCC 7002 (hereafter 7002), the design principles for guide RNA (gRNA) effectiveness remain largely unknown. Here, 76 strains of 7002 were constructed with gRNAs targeting three reporter systems to evaluate features that impact gRNA efficiency. Correlation analysis of the data revealed that important features of gRNA design include the position relative to the start codon, GC content, protospacer adjacent motif (PAM) site, minimum free energy, and targeted DNA strand. Unexpectedly, some gRNAs targeting upstream of the promoter region showed small but significant increases in reporter expression, and gRNAs targeting the terminator region showed greater repression than gRNAs targeting the 3' end of the coding sequence. Machine learning algorithms enabled prediction of gRNA effectiveness, with Random Forest having the best performance across all training sets. This study demonstrates that high-density gRNA data and machine learning can improve gRNA design for tuning gene expression in 7002.

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.

Application of combined CRISPR screening for genetic and chemical-genetic interaction profiling in Mycobacterium tuberculosis

CRISPR screening, including CRISPR interference (CRISPRi) and CRISPR-knockout (CRISPR-KO) screening, has become a powerful technology in the genetic screening of eukaryotes. In contrast with eukaryotes, CRISPR-KO screening has not yet been applied to functional genomics studies in bacteria. Here, we constructed genome-scale CRISPR-KO and also CRISPRi libraries in Mycobacterium tuberculosis (Mtb). We first examined these libraries to identify genes essential for Mtb viability. Subsequent screening identified dozens of genes associated with resistance/susceptibility to the antitubercular drug bedaquiline (BDQ). Genetic and chemical validation of the screening results suggested that it provided a valuable resource to investigate mechanisms of action underlying the effects of BDQ and to identify chemical-genetic synergies that can be used to optimize tuberculosis therapy. In summary, our results demonstrate the potential for efficient genome-wide CRISPR-KO screening in bacteria and establish a combined CRISPR screening approach for high-throughput investigation of genetic and chemical-genetic interactions in Mtb.

Engineering Endosymbiotic Growth of E. coli in Mammalian Cells

Endosymbioses are cellular mergers in which one cell lives within another cell and have led to major evolutionary transitions, most prominently to eukaryogenesis. Generation of synthetic endosymbioses aims to provide a defined starting point for studying fundamental processes in emerging endosymbiotic systems and enable the engineering of cells with novel properties. Here, we tested the potential of different bacteria for artificial endosymbiosis in mammalian cells. To this end, we adopted the fluidic force microscopy technology to inject diverse bacteria directly into the cytosol of HeLa cells and examined the endosymbiont-host interactions by real-time fluorescence microscopy. Among them, Escherichia coli grew exponentially within the cytoplasm, however, at a faster pace than its host cell. To slow down the intracellular growth of E. coli, we introduced auxotrophies in E. coli and demonstrated that the intracellular growth rate can be reduced by limiting the uptake of aromatic amino acids. In consequence, the survival of the endosymbiont-host pair was prolonged. The presented experimental framework enables studying endosymbiotic candidate systems at high temporal resolution and at the single cell level. Our work represents a starting point for engineering a stable, vertically inherited endosymbiosis.

DNA Free CRISPR/DCAS9 Based Transcriptional Activation System for UGT76G1 Gene in Stevia rebaudiana Bertoni Protoplasts

The UDP-glycosyltransferase 76G1 (UGT76G1) is responsible for the conversion of stevioside to rebaudioside A. Four single guide RNAs (sgRNAs) were designed from the UGT76G1 proximal promoter region of stevia by using the online-based tool, benchling. The dCas9 fused with VP64 as a transcriptional activation domain (TAD) was produced and purified for the formation of ribonucleoproteins (RNPs) by mixing with the in vitro transcribed sgRNAs. Protoplast yield was the highest from leaf mesophyll of in vitro grown stevia plantlets (3.16 × 10⁶/g of FW) using ES5 (1.25% cellulase R-10 and 0.75% macerozyme R-10). The RNPs were delivered into the isolated protoplasts through the Polyethylene glycol (PEG)-mediated transfection method. The highest endogenous activation of the UGT76G1 gene was detected at 27.51-fold after 24 h of transfection with RNP30 consisting of CRISPR/dCas9-TAD with sgRNA30 and a similar activation level was obtained using RNP18, RNP33, and RNP34, produced using sgRNA18, sgRNA33, and sgRNA34, respectively. Activation of UGT76G1 by RNP18 led to a significant increase in the expression of the rate-limiting enzyme UGT85C2 by 2.37-fold and there was an increasing trend in the expression of UGT85C2 using RNP30, RNP33, and RNP34. Successful application of CRISPR/dCas9-TAD RNP in activating specific genes can avoid the negative integration effects of introduced DNA in the host genome.

Recent advances in high-throughput metabolic engineering: Generation of oligonucleotide-mediated genetic libraries

The preparation of genetic libraries is an essential step to evolve microorganisms and study genotype-phenotype relationships by high-throughput screening/selection. As the large-scale synthesis of oligonucleotides becomes easy, cheap, and high-throughput, numerous novel strategies have been developed in recent years to construct high-quality oligo-mediated libraries, leveraging state-of-art molecular biology tools for genome editing and gene regulation. This review presents an overview of recent advances in creating and characterizing in vitro and in vivo genetic libraries, based on CRISPR/Cas, regulatory RNAs, and recombineering, primarily for Escherichia coli and Saccharomyces cerevisiae. These libraries' applications in high-throughput metabolic engineering, strain evolution and protein engineering are also discussed.

Genome-wide functional screens enable the prediction of high activity CRISPR-Cas9 and -Cas12a guides in Yarrowia lipolytica

Genome-wide functional genetic screens have been successful in discovering genotype-phenotype relationships and in engineering new phenotypes. While broadly applied in mammalian cell lines and in E. coli, use in non-conventional microorganisms has been limited, in part, due to the inability to accurately design high activity CRISPR guides in such species. Here, we develop an experimental-computational approach to sgRNA design that is specific to an organism of choice, in this case the oleaginous yeast Yarrowia lipolytica. A negative selection screen in the absence of non-homologous end-joining, the dominant DNA repair mechanism, was used to generate single guide RNA (sgRNA) activity profiles for both SpCas9 and LbCas12a. This genome-wide data served as input to a deep learning algorithm, DeepGuide, that is able to accurately predict guide activity. DeepGuide uses unsupervised learning to obtain a compressed representation of the genome, followed by supervised learning to map sgRNA sequence, genomic context, and epigenetic features with guide activity. Experimental validation, both genome-wide and with a subset of selected genes, confirms DeepGuide's ability to accurately predict high activity sgRNAs. DeepGuide provides an organism specific predictor of CRISPR guide activity that with retraining could be applied to other fungal species, prokaryotes, and other non-conventional organisms.

A Meta-Analysis of gRNA Library Screens Enables an Improved Understanding of the Impact of gRNA Folding and Structural Stability on CRISPR-Cas9 Activity

CRISPR systems are known to be inhibited by unwanted secondary structures that form within the guide RNA (gRNA). The minimum free energy of predicted secondary structures has been used in prediction algorithms. However, the types of structures as well as the degree to which a predicted structure can inhibit Cas9/gRNA activity is not well characterized. Here, we perform a meta-analysis of 39 published CRISPR-Cas9 data sets to understand better the role of secondary structures in inhibiting gRNA activity. We (1) identify two distinct inhibitory structures that can form, (2) measure the prevalence of these structures in existing gRNA library data sets, and (3) provide free energy cutoffs at which these structures become inhibitory. First, we show that hairpins that form within the targeting portion (spacer) of the gRNA, having a minimum free energy of <-5 kcal/mol, negatively impact gRNA activity. Second, we demonstrate that a longer hairpin can form between the spacer and the nexus portion of the gRNA scaffold. A duplex stability of this longer hairpin of <-15 kcal/mol negatively impacts gRNA activity. These cutoffs help to explain conflicting impacts of free energy values in different data sets, as well as provide a guideline for future gRNA designs.

A systematic mapping study on machine learning techniques for the prediction of CRISPR/Cas9 sgRNA target cleavage

CRISPR/Cas9 technology has greatly accelerated genome engineering research. The CRISPR/Cas9 complex, a bacterial immune response system, is widely adopted for RNA-driven targeted genome editing. The systematic mapping study presented in this paper examines the literature on machine learning (ML) techniques employed in the prediction of CRISPR/Cas9 sgRNA on/off-target cleavage, focusing on improving support in sgRNA design activities and identifying areas currently being researched.

This area of research has greatly expanded recently, and we found it appropriate to work on a Systematic Mapping Study (SMS), an investigation that has proven to be an effective secondary study method. Unlike a classic review, in an SMS, no comparison of methods or results is made, while this task can instead be the subject of a systematic literature review that chooses one theme among those highlighted in this SMS. The study is illustrated in this paper. To the best of the authors' knowledge, no other SMS studies have been published on this topic.

Fifty-seven papers published in the period 2017–2022 (April, 30) were analyzed. This study reveals that the most widely used ML model is the convolutional neural network (CNN), followed by the feedforward neural network (FNN), while the use of other models is marginal. Other interesting information has emerged, such as the wide availability of both open code and platforms dedicated to supporting the activity of researchers or the fact that there is a clear prevalence of public funds that finance research on this topic.

Repurposing CRISPR-Cas Systems as Genetic Tools for the Enterobacteriales

Over the last decade, the study of CRISPR-Cas systems has progressed from a newly discovered bacterial defense mechanism to a diverse suite of genetic tools that have been applied across all domains of life. While the initial applications of CRISPR-Cas technology fulfilled a need to more precisely edit eukaryotic genomes, creative "repurposing" of this adaptive immune system has led to new approaches for genetic analysis of microorganisms, including improved gene editing, conditional gene regulation, plasmid curing and manipulation, and other novel uses. The main objective of this review is to describe the development and current state-of-the-art use of CRISPR-Cas techniques specifically as it is applied to members of the Enterobacteriales. While many of the applications covered have been initially developed in Escherichia coli, we also highlight the potential, along with the limitations, of this technology for expanding the availability of genetic tools in less-well-characterized non-model species, including bacterial pathogens.

High-efficiency delivery of CRISPR-Cas9 by engineered probiotics enables precise microbiome editing

Antibiotic resistance threatens our ability to treat infectious diseases, spurring interest in alternative antimicrobial technologies. The use of bacterial conjugation to deliver CRISPR-cas systems programmed to precisely eliminate antibiotic-resistant bacteria represents a promising approach but requires high in situ DNA transfer rates. We have optimized the transfer efficiency of conjugative plasmid TP114 using accelerated laboratory evolution. We hence generated a potent conjugative delivery vehicle for CRISPR-cas9 that can eliminate > 99.9% of targeted antibiotic-resistant Escherichia coli in the mouse gut microbiota using a single dose. We then applied this system to a Citrobacter rodentium infection model, achieving full clearance within four consecutive days of treatment.

Development of CRISPR-Cas9 knock-in tools for free fatty acid production using the fast-growing cyanobacterial strain Synechococcus elongatus UTEX 2973

Synechococcus elongatus UTEX 2973 has one of the fastest measured doubling time of cyanobacteria making it an important candidate for metabolic engineering. Traditional genetic engineering methods, which rely on homologous recombination, however, are inefficient, labor-intensive, and time-consuming due to the oligoploidy or polyploidy nature of cyanobacteria and the reliance on unique antibiotic resistance markers. CRISPR-Cas9 has emerged as an effective and versatile editing platform in a wide variety of organisms, but its application for cyanobacterial engineering is limited by the inherent toxicity of Cas9 resulting in poor transformation efficiencies. Here, we demonstrated that a single-plasmid CRISPR-Cas9 system, pCRISPOmyces-2, can effectively knock-in a truncated thioesterase gene from Escherichia coli to generate free fatty acid (FFA) producing mutants of Syn2973. To do so, three parameters were evaluated on the effect of generating recipient colonies after conjugation with pCRISPOmyces-2-based plasmids: 1) a modified conjugation protocol termed streaked conjugation, 2) the deletion of the gene encoding RecJ exonuclease, and 3) single guide RNA (sgRNA) sequence. With the use of the streaked conjugation protocol and a ΔrecJ mutant strain of Syn2973, the conjugation efficiency for the pCRISPomyces-2 plasmid could be improved by 750-fold over the wildtype (WT) for a conjugation efficiency of 2.0 × 10^-6 transconjugants/recipient cell. While deletion of the RecJ exonuclease alone increased the conjugation efficiency by 150-fold over the WT, FFA generation was impaired in FFA-producing mutants with the ΔrecJ background, and the large number of poor FFA-producing isolates indicated the potential increase in spontaneous mutation rates. The sgRNA sequence was found to be critical in achieving the desired CRISPR-Cas9-mediated knock-in mutation as the sgRNA impacts conjugation efficiency, likelihood of homogenous recombinants, and free fatty acid production in engineered strains.

Bacterial resistance to CRISPR-Cas antimicrobials

In the age of antibiotic resistance and precise microbiome engineering, CRISPR-Cas antimicrobials promise to have a substantial impact on the way we treat diseases in the future. However, the efficacy of these antimicrobials and their mechanisms of resistance remain to be elucidated. We systematically investigated how a target E. coli strain can escape killing by episomally-encoded CRISPR-Cas9 antimicrobials. Using Cas9 from Streptococcus pyogenes (SpCas9) we studied the killing efficiency and resistance mutation rate towards CRISPR-Cas9 antimicrobials and elucidated the underlying genetic alterations. We find that killing efficiency is not correlated with the number of cutting sites or the type of target. While the number of targets did not significantly affect efficiency of killing, it did reduce the emergence of chromosomal mutations conferring resistance. The most frequent target of resistance mutations was the plasmid-encoded SpCas9 that was inactivated by bacterial genome rearrangements involving translocation of mobile genetic elements such as insertion elements. This resistance mechanism can be overcome by re-introduction of an intact copy of SpCas9. The work presented here provides a guide to design strategies that reduce resistance and improve the activity of CRISPR-Cas antimicrobials.

Genome dependent Cas9/gRNA search time underlies sequence dependent gRNA activity

CRISPR-Cas9 is a powerful DNA editing tool. A gRNA directs Cas9 to cleave any DNA sequence with a PAM. However, some gRNA sequences mediate cleavage at higher efficiencies than others. To understand this, numerous studies have screened large gRNA libraries and developed algorithms to predict gRNA sequence dependent activity. These algorithms do not predict other datasets as well as their training dataset and do not predict well between species. Here, to better understand these discrepancies, we retrospectively examine sequence features that impact gRNA activity in 44 published data sets. We find strong evidence that gRNA sequence dependent activity is largely influenced by the ability of the Cas9/gRNA complex to find the target site rather than activity at the target site and that this drives sequence dependent differences in gRNA activity between different species. This understanding will help guide future work to understand Cas9 activity as well as efforts to identify optimal gRNAs and improve Cas9 variants.

Transcription-Factor-based Biosensor Engineering for Applications in Synthetic Biology

Transcription-factor-based biosensors (TFBs) are often used for metabolite detection, adaptive evolution, and metabolic flux control. However, designing TFBs with superior performance for applications in synthetic biology remains challenging. Specifically, natural TFBs often do not meet real-time detection requirements owing to their slow response times and inappropriate dynamic ranges, detection ranges, sensitivity, and selectivity. Furthermore, designing and optimizing complex dynamic regulation networks is time-consuming and labor-intensive. This Review highlights TFB-based applications and recent engineering strategies ranging from traditional trial-and-error approaches to novel computer-model-based rational design approaches. The limitations of the applications and these engineering strategies are additionally reviewed.

Genome editing by miniature CRISPR/Cas12f1 enzyme in Escherichia coli

The clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated (Cas) system is a valuable genome editing tool for microorganisms. However, the commonly used Cas9 nuclease derived from Streptococcus pyogenes (SpCas9) is not applicable to many industrially relevant bacteria, due to its cytotoxicity and large size (1368 amino acids [aa]). We developed an alternative genome editing system using a miniature Cas12f1 nuclease (529 aa) derived from an uncultured archaeon, Un1Cas12f1. When editing four dispensable genes in Escherichia coli MG1655 and BW25113, the CRISPR/Un1Cas12f1 system showed higher efficiency (63%-100%) than the CRISPR/SpCas9 system (50%-79%). The CRISPR/Un1Cas12f1 genome editing system is expected to be applied to the genome editing of a wide variety of bacteria.

Gene Silencing Through CRISPR Interference in Bacteria: Current Advances and Future Prospects

Functional genetic screening is an important method that has been widely used to explore the biological processes and functional annotation of genetic elements. CRISPR/Cas (Clustered regularly interspaced short palindromic repeat sequences/CRISPR-associated protein) is the newest tool in the geneticist’s toolbox, allowing researchers to edit a genome with unprecedented ease, accuracy, and high-throughput. Most recently, CRISPR interference (CRISPRi) has been developed as an emerging technology that exploits the catalytically inactive Cas9 (dCas9) and single-guide RNA (sgRNA) to repress sequence-specific genes. In this review, we summarized the characteristics of the CRISPRi system, such as programmable, highly efficient, and specific. Moreover, we demonstrated its applications in functional genetic screening and highlighted its potential to dissect the underlying mechanism of pathogenesis. The recent development of the CRISPRi system will provide a high-throughput, practical, and efficient tool for the discovery of functionally important genes in bacteria.

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

As an effective programmable DNA targeting tool, CRISPR-Cas9 system has been adopted in varieties of biotechnological applications. However, the off-target effects, derived from the tolerance towards guide-target mismatches, are regarded as the major problems in engineering CRISPR systems. To understand this, we constructed two sgRNA libraries carrying saturated single- and double-nucleotide mismatches in living bacteria cells, and profiled the comprehensive landscape of in vivo binding affinity of dCas9 toward DNA target guided by each individual sgRNA with particular mismatches. We observed a synergistic effect in seed, where combinatorial double mutations caused more severe activity loss compared with the two corresponding single mutations. Moreover, we found that a particular mismatch type, dDrG (D = A, T, G), only showed moderate impairment on binding. To quantitatively understand the causal relationship between mismatch and binding behaviour of dCas9, we further established a biophysical model, and found that the thermodynamic properties of base-pairing coupled with strand invasion process, to a large extent, can account for the observed mismatch-activity landscape. Finally, we repurposed this model, together with a convolutional neural network constructed based on the same mechanism, as a predictive tool to guide the rational design of sgRNA in bacterial CRISPR interference.

Core Hairpin Structure of SpCas9 sgRNA Functions in a Sequence- and Spatial Conformation-Dependent Manner

The clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 system is a widely used genome-editing tool with great clinical potential. However, its application is limited because of low editing efficiency of some target sequences and off-target effects. As this system contains only the Cas9 protein and a single-guide RNA (sgRNA; engineered from crRNA and tracrRNA), the structure and function of these components should be studied in detail to address the current clinical needs. Consequently, we investigated the structural and sequence features of the core hairpin (the first stem loop of sgRNA) of SpCas9 sgRNA. We showed that the core hairpin structure of sgRNA is essential for SpCas9/sgRNA-mediated DNA cleavage and that the internal loop structure in the core hairpin plays a vital role in target DNA cleavage. We observed that the root stem structure within the core hairpin preferentially forms Watson-Crick base pairs and should be of a specific length to maintain an appropriate spatial conformation for Cas9 binding. However, the length of the leaf stem structure of the core hairpin is flexible, having a variable nucleotide composition. Furthermore, extension of the leaf stem structure enhances the DNA cleavage activity of the Cas9/sgRNA complex, and this could be used to enhance the efficiency of gene editing. These observations provide insight into the sgRNA/Cas9 interaction, indicating that sgRNA modification could be a strategy for improved DNA editing efficiency, and optimized sgRNA can be further used for genome-wide functional screening and clinical application.

CRISPR-Cas "Non-Target" Sites Inhibit On-Target Cutting Rates

CRISPR-Cas systems have become ubiquitous for genome editing in eukaryotic as well as bacterial systems. Cas9 forms a complex with a guide RNA (gRNA) and searches DNA for a matching sequence (target site) next to a protospacer adjacent motif (PAM). Once found, Cas9 cuts the DNA. Cas9 is revolutionary for the ability to change the RNA sequence and target a new site easily. However, while algorithms have been developed to predict gRNA-specific Cas9 activity, a fundamental biological understanding of gRNA-specific activity is lacking. The number of PAM sites in the genome is effectively a large pool of inhibitory substrates, competing with the target site for the Cas9/gRNA complex. We demonstrate that increasing the number of non-target sites for a given gRNA reduces on-target activity in a dose-dependent manner. Furthermore, we show that the use of Cas9 mutants with increased PAM specificity toward a smaller subset of PAMs (or smaller pool of competitive substrates) improves cutting rates, while increased PAM promiscuity decreases cutting rates. Decreasing the potential search space by increasing PAM specificity provides a path toward improving on-target activity for slower high-fidelity Cas9 variants. Engineering improved PAM specificity to reduce the competitive search space offers an alternative strategy to engineer Cas9 variants with increased specificity and maintained on-target activity.

Bacterial genome editing by coupling Cre-lox and CRISPR-Cas9 systems

The past decade has been a golden age for microbiology, marked by the discovery of an unprecedented increase in the number of novel bacterial species. Yet gaining biological knowledge of those organisms has not kept pace with sequencing efforts. To unlock this genetic potential there is an urgent need for generic (i.e. non-species specific) genetic toolboxes. Recently, we developed a method, termed chassis-independent recombinase-assisted genome engineering (CRAGE), enabling the integration and expression of large complex gene clusters directly into the chromosomes of diverse bacteria. Here we expand upon this technology by incorporating CRISPR-Cas9 allowing precise genome editing across multiple bacterial species. To do that we have developed a landing pad that carries one wild-type and two mutant lox sites to allow integration of foreign DNA at two locations through Cre-lox recombinase-mediated cassette exchange (RMCE). The first RMCE event is to integrate the Cas9 and the DNA repair protein genes RecET, and the second RMCE event enables the integration of customized sgRNA and a repair template. Following this workflow, we achieved precise genome editing in four different gammaproteobacterial species. We also show that the inserted landing pad and the entire editing machinery can be removed scarlessly after editing. We report here the construction of a single landing pad transposon and demonstrate its functionality across multiple species. The modular design of the landing pad and accessory vectors allows design and assembly of genome editing platforms for other organisms in a similar way. We believe this approach will greatly expand the list of bacteria amenable to genetic manipulation and provides the means to advance our understanding of the microbial world.

Programmable cross-ribosome-binding sites to fine-tune the dynamic range of transcription factor-based biosensor

Currently, predictive translation tuning of regulatory elements to the desired output of transcription factor (TF)-based biosensors remains a challenge. The gene expression of a biosensor system must exhibit appropriate translation intensity, which is controlled by the ribosome-binding site (RBS), to achieve fine-tuning of its dynamic range (i.e. fold change in gene expression between the presence and absence of inducer) by adjusting the translation level of the TF and reporter. However, existing TF-based biosensors generally suffer from unpredictable dynamic range. Here, we elucidated the connections and partial mechanisms between RBS, translation level, protein folding and dynamic range, and presented a design platform that predictably tuned the dynamic range of biosensors based on deep learning of large datasets cross-RBSs (cRBSs). In doing so, a library containing 7053 designed cRBSs was divided into five sub-libraries through fluorescence-activated cell sorting to establish a classification model based on convolutional neural network in deep learning. Finally, the present work exhibited a powerful platform to enable predictable translation tuning of RBS to the dynamic range of biosensors.

High-Throughput Functional Genomics for Energy Production

Functional genomics remains a foundational field for establishing genotype-phenotype relationships that enable strain engineering. High-throughput (HTP) methods accelerate the Design-Build-Test-Learn cycle that currently drives synthetic biology towards a forward engineering future. Trackable mutagenesis techniques including transposon insertion sequencing and CRISPR-Cas-mediated genome editing allow for rapid fitness profiling of a collection, or library, of mutants to discover beneficial mutations. Due to the relative speed of these experiments compared to adaptive evolution experiments, iterative rounds of mutagenesis can be implemented for next-generation metabolic engineering efforts to design complex production and tolerance phenotypes. Additionally, the expansion of these mutagenesis techniques to novel bacteria are opening up industrial microbes that show promise for establishing a bio-based economy.

A How-To Guide for Mode of Action Analysis of Antimicrobial Peptides

Antimicrobial peptides (AMPs) are a promising alternative to classical antibiotics in the fight against multi-resistant bacteria. They are produced by organisms from all domains of life and constitute a nearly universal defense mechanism against infectious agents. No drug can be approved without information about its mechanism of action. In order to use them in a clinical setting, it is pivotal to understand how AMPs work. While many pore-forming AMPs are well-characterized in model membrane systems, non-pore-forming peptides are often poorly understood. Moreover, there is evidence that pore formation may not happen or not play a role in vivo. It is therefore imperative to study how AMPs interact with their targets in vivo and consequently kill microorganisms. This has been difficult in the past, since established methods did not provide much mechanistic detail. Especially, methods to study membrane-active compounds have been scarce. Recent advances, in particular in microscopy technology and cell biological labeling techniques, now allow studying mechanisms of AMPs in unprecedented detail. This review gives an overview of available in vivo methods to investigate the antibacterial mechanisms of AMPs. In addition to classical mode of action classification assays, we discuss global profiling techniques, such as genomic and proteomic approaches, as well as bacterial cytological profiling and other cell biological assays. We cover approaches to determine the effects of AMPs on cell morphology, outer membrane, cell wall, and inner membrane properties, cellular macromolecules, and protein targets. We particularly expand on methods to examine cytoplasmic membrane parameters, such as composition, thickness, organization, fluidity, potential, and the functionality of membrane-associated processes. This review aims to provide a guide for researchers, who seek a broad overview of the available methodology to study the mechanisms of AMPs in living bacteria.

Bacterial Genetic Engineering by Means of Recombineering for Reverse Genetics

Serving a robust platform for reverse genetics enabling the in vivo study of gene functions primarily in enterobacteriaceae, recombineering -or recombination-mediated genetic engineering-represents a powerful and relative straightforward genetic engineering tool. Catalyzed by components of bacteriophage-encoded homologous recombination systems and only requiring short ∼40–50 base homologies, the targeted and precise introduction of modifications (e.g., deletions, knockouts, insertions and point mutations) into the chromosome and other episomal replicons is empowered. Furthermore, by its ability to make use of both double- and single-stranded linear DNA editing substrates (e.g., PCR products or oligonucleotides, respectively), lengthy subcloning of specific DNA sequences is circumvented. Further, the more recent implementation of CRISPR-associated endonucleases has allowed for more efficient screening of successful recombinants by the selective purging of non-edited cells, as well as the creation of markerless and scarless mutants. In this review we discuss various recombineering strategies to promote different types of gene modifications, how they are best applied, and their possible pitfalls.

On-target activity predictions enable improved CRISPR-dCas9 screens in bacteria

The ability to block gene expression in bacteria with the catalytically inactive mutant of Cas9, known as dCas9, is quickly becoming a standard methodology to probe gene function, perform high-throughput screens, and engineer cells for desired purposes. Yet, we still lack a good understanding of the design rules that determine on-target activity for dCas9. Taking advantage of high-throughput screening data, we fit a model to predict the ability of dCas9 to block the RNA polymerase based on the target sequence, and validate its performance on independently generated datasets. We further design a novel genome wide guide RNA library for E. coli MG1655, EcoWG1, using our model to choose guides with high activity while avoiding guides which might be toxic or have off-target effects. A screen performed using the EcoWG1 library during growth in rich medium improved upon previously published screens, demonstrating that very good performances can be attained using only a small number of well designed guides. Being able to design effective, smaller libraries will help make CRISPRi screens even easier to perform and more cost-effective. Our model and materials are available to the community through crispr.pasteur.fr and Addgene.

Massively parallel CRISPRi assays reveal concealed thermodynamic determinants of dCas12a binding

The versatility of CRISPR-Cas endonucleases as a tool for biomedical research has led to diverse applications in gene editing, programmable transcriptional control, and nucleic acid detection. Most CRISPR-Cas systems, however, suffer from off-target effects and unpredictable nonspecific binding that negatively impact their reliability and broader applicability. To better evaluate the impact of mismatches on DNA target recognition and binding, we develop a massively parallel CRISPR interference (CRISPRi) assay to measure the binding energy between tens of thousands of CRISPR RNA (crRNA) and target DNA sequences. By developing a general thermodynamic model of CRISPR-Cas binding dynamics, our results unravel a comprehensive map of the energetic landscape of nuclease-dead Cas12a (dCas12a) from Francisella novicida as it inspects and binds to its DNA target. Our results reveal concealed thermodynamic factors affecting dCas12a DNA binding, which should guide the design and optimization of crRNA that limits off-target effects, including the crucial role of an extended protospacer adjacent motif (PAM) sequence and the impact of the specific base composition of crRNA-DNA mismatches. Our generalizable approach should also provide a mechanistic understanding of target recognition and DNA binding when applied to other CRISPR-Cas systems.

Determinants for Efficient Editing with Cas9-Mediated Recombineering in Escherichia coli

In E. coli, editing efficiency with Cas9-mediated recombineering varies across targets due to differences in the level of Cas9:gRNA-mediated DNA double-strand break (DSB)-induced cell death. We found that editing efficiency with the same gRNA and repair template can also change with target position, cas9 promoter strength, and growth conditions. Incomplete editing, off-target activity, nontargeted mutations, and failure to cleave target DNA even if Cas9 is bound also compromise editing efficiency. These effects on editing efficiency were gRNA-specific. We propose that differences in the efficiency of Cas9:gRNA-mediated DNA DSBs, as well as possible differences in binding of Cas9:gRNA complexes to their target sites, account for the observed variations in editing efficiency between gRNAs. We show that editing behavior using the same gRNA can be modified by mutating the gRNA spacer, which changes the DNA DSB activity. Finally, we discuss how variable editing with different gRNAs could limit high-throughput applications and provide strategies to overcome these limitations.

Genome-Wide CRISPRi-Based Identification of Targets for Decoupling Growth from Production

Growth decoupling can be used to optimize microbial production of biobased compounds by inhibiting excess biomass formation and redirect carbon flux from growth to product formation. However, identifying suitable genetic targets through rational design is challenging. Here, we conduct a genome-wide CRISPRi screen to discover growth switches suitable for decoupling growth and production. Using an sgRNA library covering 12 238 loci in the Escherichia coli genome, we screen for targets that inhibit growth while allowing for continued protein production. In total, we identify 1332 sgRNAs that simultaneously decrease growth and maintain or increase accumulation of GFP. The top target sibB/ibsB shows more than 5-fold increase in GFP accumulation and 45% decrease in biomass formation. Overall, our genome-wide CRISPRi screen provides key targets for growth decoupling, and the approach can be applied to improve biobased production in other microorganisms.

Establishment of CRISPR interference in Methylorubrum extorquens and application of rapidly mining a new phytoene desaturase involved in carotenoid biosynthesis

The methylotrophic bacterium Methylorubrum extorquens AM1 holds a great potential of a microbial cell factory in producing high value chemicals with methanol as the sole carbon and energy source. However, many gene functions remain unknown, hampering further rewiring of metabolic networks. Clustered regularly interspaced short palindromic repeat interference (CRISPRi) has been demonstrated to be a robust tool for gene knockdown in diverse organisms. In this study, we developed an efficient CRISPRi system through optimizing the promoter strength of Streptococcus pyogenes-derived deactivated cas9 (dcas9). When the dcas9 and sgRNA were respectively controlled by medium PR/tetO and strong PmxaF-g promoters, dynamic repression efficacy of cell growth through disturbing a central metabolism gene glyA was achieved from 41.9 to 96.6% dependent on the sgRNA targeting sites. Furthermore, the optimized CRISPRi system was shown to effectively decrease the abundance of exogenous fluorescent protein gene mCherry over 50% and to reduce the expression of phytoene desaturase gene crtI by 97.7%. We then used CRISPRi technology combined with 26 sgRNAs pool to rapidly discover a new phytoene desaturase gene META1_3670 from 2470 recombinant mutants. The gene function was further verified through gene deletion and complementation as well as phylogenetic tree analysis. In addition, we applied CRISPRi to repress the transcriptional level of squalene-hopene cyclase gene shc involved in hopanoid biosynthesis by 64.9%, which resulted in enhancing 1.9-fold higher of carotenoid production without defective cell growth. Thus, the CRISPRi system developed here provides a useful tool in mining functional gene of M. extorquens as well as in biotechnology for producing high-valued chemicals from methanol. KEY POINTS: Developing an efficient CRISPRi to knockdown gene expression in C1-utilizing bacteria CRISPRi combined with sgRNAs pool to rapidly discover a new phytoene desaturase gene Improvement of carotenoid production by repressing a competitive pathway.

Multiplexed CRISPR technologies for gene editing and transcriptional regulation

Multiplexed CRISPR technologies, in which numerous gRNAs or Cas enzymes are expressed at once, have facilitated powerful biological engineering applications, vastly enhancing the scope and efficiencies of genetic editing and transcriptional regulation. In this review, we discuss multiplexed CRISPR technologies and describe methods for the assembly, expression and processing of synthetic guide RNA arrays in vivo. Applications that benefit from multiplexed CRISPR technologies, including cellular recorders, genetic circuits, biosensors, combinatorial genetic perturbations, large-scale genome engineering and the rewiring of metabolic pathways, are highlighted. We also offer a glimpse of emerging challenges and emphasize experimental considerations for future studies.

C-RNNCrispr: Prediction of CRISPR/Cas9 sgRNA activity using convolutional and recurrent neural networks

CRISPR/Cas9 is a hot genomic editing tool, but its success is limited by the widely varying target efficiencies among different single guide RNAs (sgRNAs). In this study, we proposed C-RNNCrispr, a hybrid convolutional neural networks (CNNs) and bidirectional gate recurrent unit network (BGRU) framework, to predict CRISPR/Cas9 sgRNA on-target activity. C-RNNCrispr consists of two branches: sgRNA branch and epigenetic branch. The network receives the encoded binary matrix of sgRNA sequence and four epigenetic features as inputs, and produces a regression score. We introduced a transfer learning approach by using small-size datasets to fine-tune C-RNNCrispr model that were pre-trained from benchmark dataset, leading to substantially improved predictive performance. Experiments on commonly used datasets showed C-RNNCrispr outperforms the state-of-the-art methods in terms of prediction accuracy and generalization. Source codes are available at https://github.com/Peppags/C_RNNCrispr.

Prediction of sgRNA on-target activity in bacteria by deep learning

BACKGROUND

One of the main challenges for the CRISPR-Cas9 system is selecting optimal single-guide RNAs (sgRNAs). Recently, deep learning has enhanced sgRNA prediction in eukaryotes. However, the prokaryotic chromatin structure is different from eukaryotes, so models trained on eukaryotes may not apply to prokaryotes.

RESULTS

We designed and implemented a convolutional neural network to predict sgRNA activity in Escherichia coli. The network was trained and tested on the recently-released sgRNA activity dataset. Our convolutional neural network achieved excellent performance, yielding average Spearman correlation coefficients of 0.5817, 0.7105, and 0.3602, respectively for Cas9, eSpCas9 and Cas9 with a recA coding region deletion. We confirmed that the sgRNA prediction models trained on prokaryotes do not apply to eukaryotes and vice versa. We adopted perturbation-based approaches to analyze distinct biological patterns between prokaryotic and eukaryotic editing. Then, we improved the predictive performance of the prokaryotic Cas9 system by transfer learning. Finally, we determined that potential off-target scores accumulated on a genome-wide scale affect on-target activity, which could slightly improve on-target predictive performance.

CONCLUSIONS

We developed convolutional neural networks to predict sgRNA activity for wild type and mutant Cas9 in prokaryotes. Our results show that the prediction accuracy of our method is improved over state-of-the-art models.

A Broad-Host-Range CRISPRi Toolkit for Silencing Gene Expression in Burkholderia

Genetic tools are critical to dissecting the mechanisms governing cellular processes, from fundamental physiology to pathogenesis. Members of the genus Burkholderia have potential for biotechnological applications but can also cause disease in humans with a debilitated immune system. The lack of suitable genetic tools to edit Burkholderia GC-rich genomes has hampered the exploration of useful capacities and the understanding of pathogenic features. To address this, we have developed CRISPR interference (CRISPRi) technology for gene silencing in Burkholderia, testing it in B. cenocepacia, B. multivorans, and B. thailandensis. Tunable expression was provided by placing a codon-optimized dcas9 from Streptococcus pyogenes under control of a rhamnose-inducible promoter. As a proof of concept, the paaABCDE operon controlling genes necessary for phenylacetic acid degradation was targeted by plasmid-borne gRNAs, resulting in near complete inhibition of growth on phenylacetic acid as the sole carbon source. This was supported by reductions in paaA mRNA expression. The utility of CRISPRi to probe other functions at the single cell level was demonstrated by knocking down phbC and fliF, which dramatically reduces polyhydroxybutyrate granule accumulation and motility, respectively. As a hallmark of the mini-CTX system is the broad host-range of integration, we putatively identified 67 genera of Proteobacteria that might be amenable to modification with our CRISPRi toolkit. Our CRISPRi toolkit provides a simple and rapid way to silence gene expression to produce an observable phenotype. Linking genes to functions with CRISPRi will facilitate genome editing with the goal of enhancing biotechnological capabilities while reducing Burkholderia's pathogenic arsenal.

Efficient inter-species conjugative transfer of a CRISPR nuclease for targeted bacterial killing

The selective regulation of bacteria in complex microbial populations is key to controlling pathogenic bacteria. CRISPR nucleases can be programmed to kill bacteria, but require an efficient and broad-host range delivery system to be effective. Here, using an Escherichia coli and Salmonella enterica co-culture system, we show that plasmids based on the IncP RK2 conjugative system can be used as delivery vectors for a TevSpCas9 dual nuclease. Notably, a cis-acting plasmid that encodes the conjugation and CRISPR machinery conjugates from E. coli to S. enterica with high frequency compared to a trans system that separates conjugation and CRISPR machinery. In culture conditions that enhance cell-to-cell contact, conjugation rates approach 100% with the cis-acting plasmid. Targeting of single or multiplexed sgRNAs to non-essential genes results in high S. enterica killing efficiencies. Our data highlight the potential of cis-acting conjugative plasmids as a delivery system for CRISPR nucleases or other microbial-altering agents for targeted bacterial killing.