Combinatorial mutagenesis en masse optimizes the genome editing activities of SpCas9

Quantifying higher-order epistasis: beware the chimera

Epistasis, or interactions in which alleles at one locus modify the fitness effects of alleles at other loci, plays a fundamental role in genetics, protein evolution, and many other areas of biology. Epistasis is typically quantified by computing the deviation from the expected fitness under an additive or multiplicative model using one of several formulae. However, these formulae are not all equivalent. Importantly, one widely used formula - which we call the chimeric formula - measures deviations from a multiplicative fitness model on an additive scale, thus mixing two measurement scales. We show that for pairwise interactions, the chimeric formula yields a different magnitude, but the same sign (synergistic vs. antagonistic) of epistasis compared to the multiplicative formula that measures both fitness and deviations on a multiplicative scale. However, for higher-order interactions, we show that the chimeric formula can have both different magnitude and sign compared to the multiplicative formula - thus confusing negative epistatic interactions with positive interactions, and vice versa. We resolve these inconsistencies by deriving fundamental connections between the different epistasis formulae and the parameters of the multivariate Bernoulli distribution . Our results demonstrate that the additive and multiplicative epistasis formulae are more mathematically sound than the chimeric formula. Moreover, we demonstrate that the mathematical issues with the chimeric epistasis formula lead to markedly different biological interpretations of real data. Analyzing multi-gene knockout data in yeast, multi-way drug interactions in E. coli , and deep mutational scanning (DMS) of several proteins, we find that 10 - 60% of higher-order interactions have a change in sign with the multiplicative or additive epistasis formula. These sign changes result in qualitatively different findings on functional divergence in the yeast genome, synergistic vs. antagonistic drug interactions, and and epistasis between protein mutations. In particular, in the yeast data, the more appropriate multiplicative formula identifies nearly 500 additional negative three-way interactions, thus extending the trigenic interaction network by 25%.

A high-throughput synthetic biology approach for studying combinatorial chromatin-based transcriptional regulation

The construction of synthetic gene circuits requires the rational combination of multiple regulatory components, but predicting their behavior can be challenging due to poorly understood component interactions and unexpected emergent behaviors. In eukaryotes, chromatin regulators (CRs) are essential regulatory components that orchestrate gene expression. Here, we develop a screening platform to investigate the impact of CR pairs on transcriptional activity in yeast. We construct a combinatorial library consisting of over 1,900 CR pairs and use a high-throughput workflow to characterize the impact of CR co-recruitment on gene expression. We recapitulate known interactions and discover several instances of CR pairs with emergent behaviors. We also demonstrate that supervised machine learning models trained with low-dimensional amino acid embeddings accurately predict the impact of CR co-recruitment on transcriptional activity. This work introduces a scalable platform and machine learning approach that can be used to study how networks of regulatory components impact gene expression.

Mutational rescue of the activity of high-fidelity Cas9 enzymes

Programmable DNA endonucleases derived from bacterial genetic defense systems, exemplified by CRISPR-Cas9, have made it significantly easier to perform genomic modifications in living cells. However, unprogrammed, off-target modifications can have serious consequences, as they often disrupt the function or regulation of non-targeted genes and compromise the safety of therapeutic gene editing applications. High-fidelity mutants of Cas9 have been established to enable more accurate gene editing, but these are typically less efficient. Here, we merge the strengths of high-fidelity Cas9 and hyperactive Cas9 variants to provide an enzyme, which we dub HyperDriveCas9, that yields the desirable properties of both parents. HyperDriveCas9 functions efficiently in mammalian cells and introduces insertion and deletion mutations into targeted genomic regions while maintaining a favorable off-target profile. HyperDriveCas9 is a precise and efficient tool for gene editing applications in science and medicine.

Plant Functional Genomics Based on High-Throughput CRISPR Library Knockout Screening: A Perspective

Plant biology studies in the post-genome era have been focused on annotating genome sequences' functions. The established plant mutant collections have greatly accelerated functional genomics research in the past few decades. However, most plant genome sequences' roles and the underlying regulatory networks remain substantially unknown. Clustered, regularly interspaced short palindromic repeat (CRISPR)-associated systems are robust, versatile tools for manipulating plant genomes with various targeted DNA perturbations, providing an excellent opportunity for high-throughput interrogation of DNA elements' roles. This study compares methods frequently used for plant functional genomics and then discusses different DNA multi-targeted strategies to overcome gene redundancy using the CRISPR-Cas9 system. Next, this work summarizes recent reports using CRISPR libraries for high-throughput gene knockout and function discoveries in plants. Finally, this work envisions the future perspective of optimizing and leveraging CRISPR library screening in plant genomes' other uncharacterized DNA sequences.

High-throughput screening of genetic and cellular drivers of syncytium formation induced by the spike protein of SARS-CoV-2

Mapping mutations and discovering cellular determinants that cause the spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) to induce infected cells to form syncytia would facilitate the development of strategies for blocking the formation of such cell-cell fusion. Here we describe high-throughput screening methods based on droplet microfluidics and the size-exclusion selection of syncytia, coupled with large-scale mutagenesis and genome-wide knockout screening via clustered regularly interspaced short palindromic repeats (CRISPR), for the large-scale identification of determinants of cell-cell fusion. We used the methods to perform deep mutational scans in spike-presenting cells to pinpoint mutable syncytium-enhancing substitutions in two regions of the spike protein (the fusion peptide proximal region and the furin-cleavage site). We also used a genome-wide CRISPR screen in cells expressing the receptor angiotensin-converting enzyme 2 to identify inhibitors of clathrin-mediated endocytosis that impede syncytium formation, which we validated in hamsters infected with SARS-CoV-2. Finding genetic and cellular determinants of the formation of syncytia may reveal insights into the physiological and pathological consequences of cell-cell fusion.

A top variant identification pipeline for protein engineering

Understanding the fitness of protein variants with combinatorial mutations is critical for effective protein engineering. In this issue of Cell Systems, Chu et al. present TopVIP, a top variant identification pipeline that enables accurate picking of the greatest number of best-performing protein variants with high-fitness leveraging zero-shot predictor and low-N iterative sampling.

Accurate top protein variant discovery via low-N pick-and-validate machine learning

A strategy to obtain the greatest number of best-performing variants with least amount of experimental effort over the vast combinatorial mutational landscape would have enormous utility in boosting resource producibility for protein engineering. Toward this goal, we present a simple and effective machine learning-based strategy that outperforms other state-of-the-art methods. Our strategy integrates zero-shot prediction and multi-round sampling to direct active learning via experimenting with only a few predicted top variants. We find that four rounds of low-N pick-and-validate sampling of 12 variants for machine learning yielded the best accuracy of up to 92.6% in selecting the true top 1% variants in combinatorial mutant libraries, whereas two rounds of 24 variants can also be used. We demonstrate our strategy in successfully discovering high-performance protein variants from diverse families including the CRISPR-based genome editors, supporting its generalizable application for solving protein engineering tasks. A record of this paper's transparent peer review process is included in the supplemental information.

Engineering Cas9: next generation of genomic editors

The Cas9 endonuclease of the CRISPR/Cas type IIA system from Streptococcus pyogenes is the heart of genome editing technology that can be used to treat human genetic and viral diseases. Despite its large size and other drawbacks, S. pyogenes Cas9 remains the most widely used genome editor. A vast amount of research is aimed at improving Cas9 as a promising genetic therapy. Strategies include directed evolution of the Cas9 protein, rational design, and domain swapping. The first generation of Cas9 editors comes directly from the wild-type protein. The next generation is obtained by combining mutations from the first-generation variants, adding new mutations to them, or refining mutations. This review summarizes and discusses recent advances and ways in the creation of next-generation genomic editors derived from S. pyogenes Cas9. KEY POINTS: • The next-generation Cas9-based editors are more active than in the first one. • PAM-relaxed variants of Cas9 are improved by increased specificity and activity. • Less mutagenic and immunogenic variants of Cas9 are created.

Discovery of regulatory motifs in 5' untranslated regions using interpretable multi-task learning models

The sequence in the 5' untranslated regions (UTRs) is known to affect mRNA translation rates. However, the underlying regulatory grammar remains elusive. Here, we propose MTtrans, a multi-task translation rate predictor capable of learning common sequence patterns from datasets across various experimental techniques. The core premise is that common motifs are more likely to be genuinely involved in translation control. MTtrans outperforms existing methods in both accuracy and the ability to capture transferable motifs across species, highlighting its strength in identifying evolutionarily conserved sequence motifs. Our independent fluorescence-activated cell sorting coupled with deep sequencing (FACS-seq) experiment validates the impact of most motifs identified by MTtrans. Additionally, we introduce "GRU-rewiring," a technique to interpret the hidden states of the recurrent units. Gated recurrent unit (GRU)-rewiring allows us to identify regulatory element-enriched positions and examine the local effects of 5' UTR mutations. MTtrans is a powerful tool for deciphering the translation regulatory motifs.

Challenges of CRISPR/Cas-Based Cell Therapy for Type 1 Diabetes: How Not to Engineer a "Trojan Horse"

Type 1 diabetes mellitus (T1D) is an autoimmune disease caused by the destruction of insulin-producing β-cells in the pancreas by cytotoxic T-cells. To date, there are no drugs that can prevent the development of T1D. Insulin replacement therapy is the standard care for patients with T1D. This treatment is life-saving, but is expensive, can lead to acute and long-term complications, and results in reduced overall life expectancy. This has stimulated the research and development of alternative treatments for T1D. In this review, we consider potential therapies for T1D using cellular regenerative medicine approaches with a focus on CRISPR/Cas-engineered cellular products. However, CRISPR/Cas as a genome editing tool has several drawbacks that should be considered for safe and efficient cell engineering. In addition, cellular engineering approaches themselves pose a hidden threat. The purpose of this review is to critically discuss novel strategies for the treatment of T1D using genome editing technology. A well-designed approach to β-cell derivation using CRISPR/Cas-based genome editing technology will significantly reduce the risk of incorrectly engineered cell products that could behave as a "Trojan horse".

CRISPR genetic toolkits of classical food microorganisms: Current state and future prospects

Production of food-related products using microorganisms in an environmentally friendly manner is a crucial solution to global food safety and environmental pollution issues. Traditional microbial modification methods rely on artificial selection or natural mutations, which require time for repeated screening and reproduction, leading to unstable results. Therefore, it is imperative to develop rapid, efficient, and precise microbial modification technologies. This review summarizes recent advances in the construction of gene editing and metabolic regulation toolkits based on the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated proteins (CRISPR-Cas) systems and their applications in reconstructing food microorganism metabolic networks. The development and application of gene editing toolkits from single-site gene editing to multi-site and genome-scale gene editing was also introduced. Moreover, it presented a detailed introduction to CRISPR interference, CRISPR activation, and logic circuit toolkits for metabolic network regulation. Moreover, the current challenges and future prospects for developing CRISPR genetic toolkits were also discussed.

Quantification of evolved DNA-editing enzymes at scale with DEQSeq

We introduce DEQSeq, a nanopore sequencing approach that rationalizes the selection of favorable genome editing enzymes from directed molecular evolution experiments. With the ability to capture full-length sequences, editing efficiencies, and specificities from thousands of evolved enzymes simultaneously, DEQSeq streamlines the process of identifying the most valuable variants for further study and application. We apply DEQSeq to evolved libraries of Cas12f-ABEs and designer-recombinases, identifying variants with improved properties for future applications. Our results demonstrate that DEQSeq is a powerful tool for accelerating enzyme discovery and advancing genome editing research.

Refining chimeric antigen receptors via barcoded protein domain combination pooled screening

Chimeric antigen receptor (CAR)-T cells represent a promising frontier in cancer immunotherapy. However, the current process for developing new CAR constructs is time consuming and inefficient. To address this challenge and expedite the evaluation and comparison of full-length CAR designs, we have devised a novel cloning strategy. This strategy involves the sequential assembly of individual CAR domains using blunt ligation, with each domain being assigned a unique DNA barcode. Applying this method, we successfully generated 360 CAR constructs that specifically target clinically validated tumor antigens CD19 and GD2. By quantifying changes in barcode frequencies through next-generation sequencing, we characterize CARs that best mediate proliferation and expansion of transduced T cells. The screening revealed a crucial role for the hinge domain in CAR functionality, with CD8a and IgG4 hinges having opposite effects in the surface expression, cytokine production, and antitumor activity in CD19- versus GD2-based CARs. Importantly, we discovered two novel CD19-CAR architectures containing the IgG4 hinge domain that mediate superior in vivo antitumor activity compared with the construct used in Kymriah, a U.S. Food and Drug Administration (FDA)-approved therapy. This novel screening approach represents a major advance in CAR engineering, enabling accelerated development of cell-based cancer immunotherapies.

A cleavage rule for selection of increased-fidelity SpCas9 variants with high efficiency and no detectable off-targets

Streptococcus pyogenes Cas9 (SpCas9) has been employed as a genome engineering tool with a promising potential within therapeutics. However, its off-target effects present major safety concerns for applications requiring high specificity. Approaches developed to date to mitigate this effect, including any of the increased-fidelity (i.e., high-fidelity) SpCas9 variants, only provide efficient editing on a relatively small fraction of targets without detectable off-targets. Upon addressing this problem, we reveal a rather unexpected cleavability ranking of target sequences, and a cleavage rule that governs the on-target and off-target cleavage of increased-fidelity SpCas9 variants but not that of SpCas9-NG or xCas9. According to this rule, for each target, an optimal variant with matching fidelity must be identified for efficient cleavage without detectable off-target effects. Based on this insight, we develop here an extended set of variants, the CRISPRecise set, with increased fidelity spanning across a wide range, with differences in fidelity small enough to comprise an optimal variant for each target, regardless of its cleavability ranking. We demonstrate efficient editing with maximum specificity even on those targets that have not been possible in previous studies.

Parallel engineering and activity profiling of a base editor system

Selecting the most suitable existing base editors and engineering new variants for installing specific base conversions with maximal efficiency and minimal undesired edits are pivotal for precise genome editing applications. Here, we present a platform for creating and analyzing a library of engineered base editor variants to enable head-to-head evaluation of their editing performance at scale. Our comprehensive comparison provides quantitative measures on each variant's editing efficiency, purity, motif preference, and bias in generating single and multiple base conversions, while uncovering undesired higher indel generation rate and noncanonical base conversion for some of the existing base editors. In addition to engineering the base editor protein, we further applied this platform to investigate a hitherto underexplored engineering route and created guide RNA scaffold variants that augment the editor's base-editing activity. With the unknown performance and compatibility of the growing number of engineered parts including deaminase, CRISPR-Cas enzyme, and guide RNA scaffold variants for assembling the expanding collection of base editor systems, our platform addresses the unmet need for an unbiased, scalable method to benchmark their editing outcomes and accelerate the engineering of next-generation precise genome editors.

Frankenstein Cas9: engineering improved gene editing systems

The discovery of CRISPR-Cas9 and its widespread use has revolutionised and propelled research in biological sciences. Although the ability to target Cas9's nuclease activity to specific sites via an easily designed guide RNA (gRNA) has made it an adaptable gene editing system, it has many characteristics that could be improved for use in biotechnology. Cas9 exhibits significant off-target activity and low on-target nuclease activity in certain contexts. Scientists have undertaken ambitious protein engineering campaigns to bypass these limitations, producing several promising variants of Cas9. Cas9 variants with improved and alternative activities provide exciting new tools to expand the scope and fidelity of future CRISPR applications.

Engineering and Design of Programmable Genome Editors

Programmable genome editors are enzymes that can be targeted to a specific location in the genome for making site-specific alterations or deletions. The engineering, design, and development of sequence-specific editors has resulted in a dramatic increase in the precision of editing for nucleotide sequences. These editors can target specific locations in a genome, in vivo. The genome editors are being deployed for the development of genetically modified organisms for agriculture and industry, and for gene therapy of inherited human genetic disorders, cancer, and immunotherapy. Experimental and computational studies of structure, binding, activity, dynamics, and folding, reviewed here, have provided valuable insights that have the potential for increasing the functional efficiency of these gene/genome editors. Biochemical and biophysical studies of the specificities of natural and engineered genome editors reveal that increased binding affinity can be detrimental because of the increase of off-target effects and that the engineering and design of genome editors with higher specificity may require modulation and control of the conformational dynamics.

Machine learning-coupled combinatorial mutagenesis enables resource-efficient engineering of CRISPR-Cas9 genome editor activities

The genome-editing Cas9 protein uses multiple amino-acid residues to bind the target DNA. Considering only the residues in proximity to the target DNA as potential sites to optimise Cas9’s activity, the number of combinatorial variants to screen through is too massive for a wet-lab experiment. Here we generate and cross-validate ten in silico and experimental datasets of multi-domain combinatorial mutagenesis libraries for Cas9 engineering, and demonstrate that a machine learning-coupled engineering approach reduces the experimental screening burden by as high as 95% while enriching top-performing variants by ∼7.5-fold in comparison to the null model. Using this approach and followed by structure-guided engineering, we identify the N888R/A889Q variant conferring increased editing activity on the protospacer adjacent motif-relaxed KKH variant of Cas9 nuclease from Staphylococcus aureus (KKH-SaCas9) and its derived base editor in human cells. Our work validates a readily applicable workflow to enable resource-efficient high-throughput engineering of genome editor’s activity.

Screening combinatorial mutants is too massive for wet-lab experiment alone. Here the authors present a machine learning-coupled combinatorial mutagenesis approach to vastly reduce experimental burden for engineering Cas9 genome editing enzymes.

High-fidelity KKH variant of Staphylococcus aureus Cas9 nucleases with improved base mismatch discrimination

The Cas9 nuclease from Staphylococcus aureus (SaCas9) holds great potential for use in gene therapy, and variants with increased fidelity have been engineered. However, we find that existing variants have not reached the greatest accuracy to discriminate base mismatches and exhibited much reduced activity when their mutations were grafted onto the KKH mutant of SaCas9 for editing an expanded set of DNA targets. We performed structure-guided combinatorial mutagenesis to re-engineer KKH-SaCas9 with enhanced accuracy. We uncover that introducing a Y239H mutation on KKH-SaCas9's REC domain substantially reduces off-target edits while retaining high on-target activity when added to a set of mutations on REC and RuvC domains that lessen its interactions with the target DNA strand. The Y239H mutation is modelled to have removed an interaction from the REC domain with the guide RNA backbone in the guide RNA-DNA heteroduplex structure. We further confirmed the greatly improved genome-wide editing accuracy and single-base mismatch discrimination of our engineered variants, named KKH-SaCas9-SAV1 and SAV2, in human cells. In addition to generating broadly useful KKH-SaCas9 variants with unprecedented accuracy, our findings demonstrate the feasibility for multi-domain combinatorial mutagenesis on SaCas9's DNA- and guide RNA- interacting residues to optimize its editing fidelity.

Facile Assembly of Combinatorial Mutagenesis Libraries Using Nicking Mutagenesis

Combinatorial mutagenesis is a method where multiple user-defined mutations are encoded at defined positions in a sequence. Combinatorial mutagenic libraries can be used in a variety of applications including evaluating fundamental questions about molecular evolution, directed evolution workflows for enzyme engineering, and in better understanding of biological processes like antibody affinity maturation. Here, we show a method of combinatorial mutagenesis utilizing the template-based nicking mutagenesis with several modifications. We show an example for generating a combinatorial library with 14 mutated positions, a total of 16,384 library variants, and a protocol for the generation of large, user-defined combinatorial libraries. The reader can use this protocol to create such libraries in 2 days.

Strategies for optimization of the CRISPR-based genome editing system for enhanced editing specificity

The clustered regularly interspaced short palindromic repeats (CRISPR) system is inarguably the most valuable gene editing tool ever discovered. Currently, three classes of CRISPR-based genome editing systems have been developed for gene editing, including CRISPR/Cas nucleases, base editors (BEs) and prime editors (PEs). Ever-evolving CRISPR technology plays an important role in medicine; however, the biggest obstacle to its use in clinical practice is the induction of off-target effects (OTEs) during targeted editing. Therefore, continuous improvement and optimization of the CRISPR system for reduction of OTEs is a major focus in the field of CRISPR research. This review aims to provide a comprehensive guide for optimization of the CRISPR-based genome editing system.

Facilitating Machine Learning-Guided Protein Engineering with Smart Library Design and Massively Parallel Assays

Protein design plays an important role in recent medical advances from antibody therapy to vaccine design. Typically, exhaustive mutational screens or directed evolution experiments are used for the identification of the best design or for improvements to the wild-type variant. Even with a high-throughput screening on pooled libraries and Next-Generation Sequencing to boost the scale of read-outs, surveying all the variants with combinatorial mutations for their empirical fitness scores is still of magnitudes beyond the capacity of existing experimental settings. To tackle this challenge, in-silico approaches using machine learning to predict the fitness of novel variants based on a subset of empirical measurements are now employed. These machine learning models turn out to be useful in many cases, with the premise that the experimentally determined fitness scores and the amino-acid descriptors of the models are informative. The machine learning models can guide the search for the highest fitness variants, resolve complex epistatic relationships, and highlight bio-physical rules for protein folding. Using machine learning-guided approaches, researchers can build more focused libraries, thus relieving themselves from labor-intensive screens and fast-tracking the optimization process. Here, we describe the current advances in massive-scale variant screens, and how machine learning and mutagenesis strategies can be integrated to accelerate protein engineering. More specifically, we examine strategies to make screens more economical, informative, and effective in discovery of useful variants.

The Use of CRISPR/Cas9 as a Tool to Study Human Infectious Viruses

Clustered regularly interspaced short palindromic repeats (CRISPR) systems are a set of versatile gene-editing toolkit that perform diverse revolutionary functions in various fields of application such as agricultural practices, food industry, biotechnology, biomedicine, and clinical research. Specially, as a novel antiviral method of choice, CRISPR/Cas9 system has been extensively and effectively exploited to fight against human infectious viruses. Infectious diseases including human immunodeficiency virus (HIV), hepatitis B virus (HBV), human papillomavirus (HPV), and other viruses are still global threats with persistent potential to probably cause pandemics. To facilitate virus removals, the CRISPR/Cas9 system has already been customized to confer new antiviral capabilities into host animals either by modifying host genome or by directly targeting viral inherent factors in the form of DNA. Although several limitations and difficulties still need to be conquered, this technology holds great promises in the treatment of human viral infectious diseases. In this review, we will first present a brief biological feature of CRISPR/Cas9 systems, which includes a description of CRISPR/Cas9 structure and composition; thereafter, we will focus on the investigations and applications that employ CRISPR/Cas9 system to combat several human infectious viruses and discuss challenges and future perspectives of using this new platform in the preclinical and clinical settings as an antiviral strategy.

Reduced off-target effect of NG-BE4max by using NG-HiFi system

Recently, a rationally engineered SpCas9 variant (SpCas9-NG) that can recognize a minimal NG protospacer adjacent motif (PAM) was reported to expand the targeting scope in genome editing. However, increased genome-wide off-target mutations with this variant compared with SpCas9 were reported in previous studies. In addition, lower base editing frequencies and higher unintended off-target mutations were also found in Hoxc13-ablated rabbits generated by NG-BE4max in our study. Here, a high-fidelity base editor, NG-HiFi, in comparison to NG-BE4max, showed retention of on-target activity while exhibiting significantly decreased off-target activity in Hoxc13-ablated rabbits. Collectively, the improved specificity and reduced off-target effect of SpCas9-NG assisted in cytidine base editing with the NG-HiFi system, providing a promising tool to precisely model human diseases in rabbits.

Advances in Enhanced Menaquinone-7 Production From Bacillus subtilis

The production of nutraceutical compounds through biosynthetic approaches has received considerable attention in recent years. For example, Menaquinone-7 (MK-7), a sub-type of Vitamin K2, biosynthesized from Bacillus subtilis (B. subtilis), proved to be more efficiently produced than the conventional chemical synthesis techniques. This is possible due to the development of B. subtilis as a chassis cell during the biosynthesis stages. Hence, it is imperative to provide insights on the B. subtilis membrane permeability modifications, biofilm reactors, and fermentation optimization as advanced techniques relevant to MK-7 production. Although the traditional gene-editing method of homologous recombination improves the biosynthetic pathway, CRISPR-Cas9 could potentially resolve the drawbacks of traditional genome editing techniques. For these reasons, future studies should explore the applications of CRISPRi (CRISPR interference) and CRISPRa (CRISPR activation) system gene-editing tools in the MK-7 anabolism pathway.

CRISPR/Cas-Based Epigenome Editing: Advances, Applications, and Clinical Utility

The epigenome dynamically regulates gene expression and guides cellular differentiation throughout the lifespan of eukaryotic organisms. Recent advances in clustered regularly interspaced palindromic repeats (CRISPR)/Cas-based epigenome editing technologies have enabled researchers to site-specifically program epigenetic modifications to endogenous DNA and histones and to manipulate the architecture of native chromatin. As a result, epigenome editing has helped to uncover the causal relationships between epigenetic marks and gene expression. As epigenome editing tools have continued to develop, researchers have applied them in new ways to explore the function of the epigenome in human health and disease. In this review, we discuss the recent technical improvements in CRISPR/Cas-based epigenome editing that have advanced clinical research and examine how these technologies could be improved for greater future utility.

Extensible combinatorial CRISPR screening in mammalian cells

The CRISPR-Cas system coupled with Combinatorial Genetics En Masse (CombiGEM) enables systematic analysis of high-order genetic perturbations that are important for understanding biological processes and discovering therapeutic target combinations. Here, we present detailed steps and technical considerations for building multiplexed guide RNA libraries and carrying out a combinatorial CRISPR screen in mammalian cells. We also present an analytical pipeline, CombiPIPE, for mapping two- and three-way genetic interactions. For complete details on the use and execution of this protocol, please refer to Zhou et al. (2020).

Optimization of multi-site nicking mutagenesis for generation of large, user-defined combinatorial libraries

Generating combinatorial libraries of specific sets of mutations are essential for addressing protein engineering questions involving contingency in molecular evolution, epistatic relationships between mutations, as well as functional antibody and enzyme engineering. Here we present optimization of a combinatorial mutagenesis method involving template-based nicking mutagenesis, which allows for the generation of libraries with >99% coverage for tens of thousands of user-defined variants. The non-optimized method resulted in low library coverage, which could be rationalized by a model of oligonucleotide annealing bias resulting from the nucleotide mismatch free-energy difference between mutagenic oligo and template. The optimized method mitigated this thermodynamic bias using longer primer sets and faster annealing conditions. Our updated method, applied to two antibody fragments, delivered between 99.0% (32451/32768 library members) to >99.9% coverage (32757/32768) for our desired libraries in 2 days and at an approximate 140-fold sequencing depth of coverage.

In Vitro Assays for Comparing the Specificity of First- and Next-Generation CRISPR/Cas9 Systems

CRISPR/Cas9 has revolutionized the ability to edit cellular DNA and is poised to transform the treatment of genetic diseases. One of the major concerns regarding its therapeutic use is the potential for off-target DNA cleavage, which could have detrimental consequences in vivo. To circumvent this, a number of strategies have been employed to develop next-generation CRISPR/Cas9 systems with improved specificity. These include the development of new protein variants of Cas9, as well as chemically modified guide RNA molecules. Here, we provide detailed protocols for two in vitro methods that enable the specificity of first- and next-generation CRISPR/Cas9 systems to be compared, and we demonstrate their applicability to evaluating chemically modified guide RNAs. One of these assays allows the specificity of different guide RNA/Cas9 complexes to be compared on a set of known off-target DNA sequences, while the second provides a broad specificity profile based on cleavage of a massive library of potential off-target DNA sequences. Collectively, these assays may be used to evaluate the specificity of different CRISPR/Cas9 systems on any DNA target sequence in a time- and cost-effective manner.

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.

High-Throughput Protein Engineering by Massively Parallel Combinatorial Mutagenesis

Exploring how combinatorial mutations can be combined to optimize protein functions is important to guide protein engineering. Given the vast combinatorial space of changing multiple amino acids, identifying the top-performing variants from a large number of mutants might not be possible without a high-throughput gene assembly and screening strategy. Here we describe the CombiSEAL platform, a strategy that allows for modularization of any protein sequence into multiple segments for mutagenesis and barcoding, and seamless single-pot ligations of different segments to generate a library of combination mutants linked with concatenated barcodes at one end. By reading the barcodes using next-generation sequencing, activities of each protein variant during the protein selection process can be easily tracked in a high-throughput manner. CombiSEAL not only allows the identification of better protein variants but also enables the systematic analyses to distinguish the beneficial, deleterious, and neutral effects of combining different mutations on protein functions.

In silico Method in CRISPR/Cas System: An Expedite and Powerful Booster

The CRISPR/Cas system has stood in the center of attention in the last few years as a revolutionary gene editing tool with a wide application to investigate gene functions. However, the labor-intensive workflow requires a sophisticated pre-experimental and post-experimental analysis, thus becoming one of the hindrances for the further popularization of practical applications. Recently, the increasing emergence and advancement of the in silico methods play a formidable role to support and boost experimental work. However, various tools based on distinctive design principles and frameworks harbor unique characteristics that are likely to confuse users about how to choose the most appropriate one for their purpose. In this review, we will present a comprehensive overview and comparisons on the in silico methods from the aspects of CRISPR/Cas system identification, guide RNA design, and post-experimental assistance. Furthermore, we establish the hypotheses in light of the new trends around the technical optimization and hope to provide significant clues for future tools development.

Applications of CRISPR in a Microbial Cell Factory: From Genome Reconstruction to Metabolic Network Reprogramming

The well-designed microbial cell factory finds wide applications in chemical, pharmaceutical, and food industries due to its sustainable and environmentally friendly features. Recently, the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated proteins (CRISPR-Cas) systems have been developed into powerful tools to perform genome editing and transcriptional regulation in prokaryotic and eukaryotic cells. Accordingly, these tools are useful to build microbial cell factories not only by reconstructing the genome but also by reprogramming the metabolic network. In this review, we summarize the recent significant headway and potential uses of the CRISPR technology in the construction of efficient microbial cell factories. Moreover, the future perspectives on the improvement and upgradation of CRISPR-based tools are also discussed.

Directed Evolution of CRISPR/Cas Systems for Precise Gene Editing

CRISPR technology is a universal tool for genome engineering that has revolutionized biotechnology. Recently identified unique CRISPR/Cas systems, as well as re-engineered Cas proteins, have rapidly expanded the functions and applications of CRISPR/Cas systems. The structures of Cas proteins are complex, containing multiple functional domains. These protein domains are evolutionarily conserved polypeptide units that generally show independent structural or functional properties. In this review, we propose using protein domains as a new way to classify protein engineering strategies for these proteins and discuss common ways to engineer key domains to modify the functions of CRISPR/Cas systems.

A Three-Way Combinatorial CRISPR Screen for Analyzing Interactions among Druggable Targets

We present a CRISPR-based multi-gene knockout screening system and toolkits for extensible assembly of barcoded high-order combinatorial guide RNA libraries en masse. We apply this system for systematically identifying not only pairwise but also three-way synergistic therapeutic target combinations and successfully validate double- and triple-combination regimens for suppression of cancer cell growth and protection against Parkinson's disease-associated toxicity. This system overcomes the practical challenges of experimenting on a large number of high-order genetic and drug combinations and can be applied to uncover the rare synergistic interactions between druggable targets.

Suppression of unwanted CRISPR-Cas9 editing by co-administration of catalytically inactivating truncated guide RNAs

CRISPR-Cas9 nucleases are powerful genome engineering tools, but unwanted cleavage at off-target and previously edited sites remains a major concern. Numerous strategies to reduce unwanted cleavage have been devised, but all are imperfect. Here, we report that off-target sites can be shielded from the active Cas9•single guide RNA (sgRNA) complex through the co-administration of dead-RNAs (dRNAs), truncated guide RNAs that direct Cas9 binding but not cleavage. dRNAs can effectively suppress a wide-range of off-targets with minimal optimization while preserving on-target editing, and they can be multiplexed to suppress several off-targets simultaneously. dRNAs can be combined with high-specificity Cas9 variants, which often do not eliminate all unwanted editing. Moreover, dRNAs can prevent cleavage of homology-directed repair (HDR)-corrected sites, facilitating scarless editing by eliminating the need for blocking mutations. Thus, we enable precise genome editing by establishing a flexible approach for suppressing unwanted editing of both off-targets and HDR-corrected sites.

Application of combinatorial optimization strategies in synthetic biology

In the first wave of synthetic biology, genetic elements, combined into simple circuits, are used to control individual cellular functions. In the second wave of synthetic biology, the simple circuits, combined into complex circuits, form systems-level functions. However, efforts to construct complex circuits are often impeded by our limited knowledge of the optimal combination of individual circuits. For example, a fundamental question in most metabolic engineering projects is the optimal level of enzymes for maximizing the output. To address this point, combinatorial optimization approaches have been established, allowing automatic optimization without prior knowledge of the best combination of expression levels of individual genes. This review focuses on current combinatorial optimization methods and emerging technologies facilitating their applications.

Rationally engineered Staphylococcus aureus Cas9 nucleases with high genome-wide specificity

RNA-guided CRISPR-Cas9 proteins have been widely used for genome editing, but their off-target activities limit broad application. The minimal Cas9 ortholog from Staphylococcus aureus (SaCas9) is commonly used for in vivo genome editing; however, no variant conferring high genome-wide specificity is available. Here, we report rationally engineered SaCas9 variants with highly specific genome-wide activity in human cells without compromising on-target efficiency. One engineered variant, referred to as SaCas9-HF, dramatically improved genome-wide targeting accuracy based on the genome-wide unbiased identification of double-stranded breaks enabled by sequencing (GUIDE-seq) method and targeted deep sequencing analyses. Among 15 tested human endogenous sites with the canonical NNGRRT protospacer adjacent motif (PAM), SaCas9-HF rendered no detectable off-target activities at 9 sites, minimal off-target activities at 6 sites, and comparable on-target efficiencies to those of wild-type SaCas9. Furthermore, among 4 known promiscuous targeting sites, SaCas9-HF profoundly reduced off-target activities compared with wild type. When delivered by an adeno-associated virus vector, SaCas9-HF also showed reduced off-target effects when targeting VEGFA in a human retinal pigmented epithelium cell line compared with wild type. Then, we further altered a previously described variant named KKH-SaCas9 that has a wider PAM recognition range. Similarly, the resulting KKH-HF remarkably reduced off-target activities and increased on- to off-target editing ratios. Our finding provides an alternative to wild-type SaCas9 for genome editing applications requiring exceptional genome-wide precision.