Diversification of the CRISPR Toolbox: Applications of CRISPR-Cas Systems Beyond Genome Editing

Abstract

The discovery of CRISPR has revolutionized the field of genome engineering, but the potential of this technology is far from reaching its limits. In this review, we explore the broad range of applications of CRISPR technology to highlight the rapid expansion of the field beyond gene editing alone. It has been demonstrated that CRISPR technology can control gene expression, spatiotemporally image the genome in vivo, and detect specific nucleic acid sequences for diagnostics. In addition, new technologies are under development to improve CRISPR quality controls for gene editing, thereby improving the reliability of these technologies for therapeutics and beyond. These are just some of the many CRISPR tools that have been developed in recent years, and the toolbox continues to diversify.

Introduction

The discovery and implementation of CRISPR-Cas enzymatic systems have revolutionized genome engineering by providing programable and straightforward tools to manipulate genomes in prokaryotic and eukaryotic organisms.¹ CRISPR-Cas systems endogenously serve as a form of adaptive immunity against invading nucleic acids in both bacteria and archaea.² This immunity functions in three main steps: adaptation, expression, and interference.³

In the adaptation phase, immunological memory is created by inserting the invading nucleic acid fragment as a new spacer into the CRISPR array.^2,4 In the expression phase, the CRISPR array, containing variable spacer sequences and interspaced by conserved repeat sequences, is transcribed and processed to yield short CRISPR RNAs (crRNAs). These crRNAs specific to the foreign nucleic acid sequence form an effector complex with CRISPR-associated (Cas) proteins that searches the cell for foreign nucleic acids.⁵ Many CRISPR-Cas nucleases require a protospacer adjacent motif (PAM), a short sequence adjacent to the spacer target sequence within the target nucleic acid.⁶ Upon Cas–crRNA complex target recognition through base pairing, the complex is activated, and the foreign nucleic acid is cleaved.

Enzymes within the CRISPR systems are diverse in their mechanisms. Although all known CRISPR-Cas systems share a conserved mechanism for the adaptation phase,^7,8 they differ in their interference mechanisms.⁹ More specifically, CRISPR systems vary by their effector modules used in the interference phase, which can be either protein subunits or protein complexes bound to a crRNA that orchestrates the cleavage of the target nucleic acid molecule.⁹ Recent classifications divided CRISPR enzymes into two classes. Class 1 comprises types I, III, and IV, which all have multi-Cas protein effector modules that associate with the crRNA molecule and bind to the target nucleic acid for subsequent cleavage. Class 2 includes types II, V, and VI, where single multisubunit proteins complex with the corresponding crRNA to mediate the interaction with their specific nucleic acid target.¹⁰

In recent years, CRISPR-Cas systems have been mainly exploited for their DNA targeting capabilities. The type II CRISPR enzyme Cas9, adopted from the immune system of Streptococcus pyogenes (SpCas9), is the most widely used CRISPR enzyme for genome engineering.^1,11 In the interference phase, Cas9 associates with a crRNA and a short trans-activating CRISPR RNA (tracrRNA) sequence that forms a partial duplex with the crRNA.¹² This complex probes double-stranded DNA (dsDNA) when it encounters a three-nucleotide 5′-NGG-3′ PAM, and if there is crRNA/DNA sequence complementary, Cas9 is activated and cleaves the dsDNA between three and seven nucleotides upstream from the PAM.^12,13

The two RNA components (tracrRNA and the crRNA) have been engineered into a single guide RNA (sgRNA or gRNA),¹³ simplifying the CRISPR design process and allowing for precise and flexible genome engineering with modulation of the 20-nucleotide spacer sequence.

One critical component of CRISPR-Cas9 and other Cas-based technology is gRNA design. The DNA, unwound by Cas9, is probed by the gRNA sequence adjacent to the PAM.^13,14 The first few nucleotides are referred to as the “seed” sequence, where Cas9 is most sensitive to mismatches. If there is full seed region complementarity, Cas9 is more likely to remain bound to the DNA and mediate cleavage, which can lead to off-target effects.¹⁵ Partial complementarity between Cas9–gRNA complexes and the seed region of DNA sequence increase dissociation of Cas9,^15,16 such that single nucleotide changes, although having little impact on the DNA association, increase the Cas9–gRNA–DNA rates from <0.006/s to >2/s.¹⁵ The elucidation of these kinetics has allowed for more precise gRNA designs to minimize off-target cleavage activity, critical for the development of tailored and effective CRISPR-Cas9 gene therapies.

Conformational dynamics studies of Cas9 have elucidated some of the additional mechanisms behind on- and off-target binding and cleavage.^14–16 For example, the Cas9–gRNA complex spontaneously transitions between three conformational states when bound to DNA, which is governed primarily by the mobility of the catalytic HNH domain. Importantly, a proofreading mechanism between the HNH domain and the gRNA–DNA heteroduplex serves as the final checkpoint before cleavage.¹⁶ Engineered Cas9 variants have been shown to improve the final proofreading mechanism and reduce the mismatch tolerance and the off-target effects.¹⁷

In addition, researchers have expanded the CRISPR-Cas editing toolbox by introducing additional Cas enzymes, such as Cas12a,^18–20 which displays enhanced editing efficiencies compared with Cas9.^19,20 Cas12a is a class 2 enzyme that recognizes a T-rich PAM and operates without a tracrRNA and targets dsDNA. However, unlike Cas9, the cleavage occurs in the PAM distal region of the spacer and is staggered five nucleotides between strands.²¹ In addition, the type VI crRNA-guided Cas13 RNAse has been employed to bypass the risk of unintended gene mutations by editing the transcriptome.²² Although Cas13 does not recognize a PAM, a non-G protospacer flanking site improves Cas13 targeting.²³

Despite off-target concerns, CRISPR-Cas9–based genome engineering has taken center stage in the field of gene therapy with promising curative potential for pathologies such as heart disease,²⁴ Duchenne muscular dystrophy,²⁵ sickle cell disease, and other β-hemoglobinopathies.^26–28 In addition, base editing through CRISPR strategies enables single base pair changes (A-T to G-C and from C-G to T-A), opening new horizons for gene therapy.^29,30 Beyond advances to therapeutics, CRISPR-based gene drives have opened new doors, allowing scientists to circumvent the constraints of Mendelian inheritance.^31–33

Furthermore, the incorporation of CRISPR-Cas genome editing systems in plant research and agriculture has erased many barriers that previously hindered crop improvement.³⁴ With a rapidly increasing world population, rising demands in plant-based biomaterials, and the unprecedented impact of global climate change upon crop yield and food production, additional pressure has been placed upon agriculture,³⁵ and CRISPR editing tools hold promise to ignite a new era in precision agriculture.

Although Cas9-based genome engineering has expedited many research disciplines and biotechnological industries, it also offers various alternative and innovative applications. This review details the broad spectrum of CRISPR-Cas applications, including gene expression modulation, live-cell imaging, nonediting-based therapeutics, and diagnostics. In addition, we discuss advancements in machine learning and CRISPR-Cas9 quality controls, which are crucial for the expansion of the CRISPR toolbox and are implemented alongside strategies involving editing as well as nonediting technologies.

Gene Expression Control Mediated by CRISPR Systems

CRISPR-based gene regulation

Before the use of CRISPR-Cas systems, zinc finger proteins (ZFPs)³⁶ and transcription activator-like effectors, or TALEs,³⁷ were employed for genome engineering. These programmable DNA binding proteins are fused to endonuclease domains, such as Fok1, to target specific DNA sequences and cut them. Depending on the fusion protein created, ZFPs and TALEs could also be used to interfere with transcriptional regulation^36,37 and gain a better understanding of gene function as well as further expand our knowledge of cis-regulatory motifs.^38–40 These systems rely on DNA–protein binding and require a laborious re-engineering process for each of the target loci,⁴¹ which is particularly challenging when considering multiloci studies. In comparison, CRISPR-Cas systems offer more versatility and programmability, making CRISPR-Cas systems more suitable for gene regulation studies.⁴²

Nuclease “dead” Cas9, or dCas9, is a widely employed Cas9 mutant in CRISPR genome regulation. Like Cas9, dCas9 uses a gRNA to bind to a target sequence. However, two point mutations (D10A and H840A) in the respective endonuclease domains (RuvC and HNH) result in the inactivation of the DNA cleavage mechanism.⁴³ Direct control of gene expression has a broad range of applications in basic research, therapeutics, and agriculture. In 2013, Qi et al. implemented a strategy referred to as CRISPRi (CRISPR interference) that employs dCas9 to bind to specific cis-regulatory sequences and block transcription (Fig. 1A).⁴³ CRISPRi was successfully employed in Escherichia coli. However, a moderate response was seen when tested in mammalian cell lines (approximately twofold), indicating the need for further optimization in eukaryotes.⁴³

FIG. 1.

Schematic of the general mechanism of CRISPRi and CRISPRa. (A) dCas9 associates with specific sgRNA and binds to target sequences without cleaving, which, in turn, inhibits transcription initiation. dCas9 can also be used to inhibit transcription elongation (not shown). (B) dCas9 is modified to contain a protein complex capable of recruiting transcription factors, such as VP64 or p65. Upon recognition of the CRISPR target sequence, which is upstream of a gene of interest, transcriptional machinery is recruited, and gene expression increases, thereby activating that gene. CRISPRi, CRISPR interference; sgRNA, single guide RNA.

After this study, Gilbert et al. observed a 5- to 15-fold repression of genes in the human cells by fusing dCas9 to KRAB, a chromatin modifier involved gene transcription silencing.⁴⁴ In addition, chimeric versions of dCas9 with tandem repeats of the repressing domain SRDX have also been used to successfully suppress gene expression in plants,⁴⁵ expanding the potential applications of CRISPRi to both plants and animals.

dCas9 can also be leveraged to activate endogenous gene expression (CRISPRa) by integrating transcriptional activator modules (Fig. 1B).^44,46–50 In 2013, Bikard et al. fused dCas9 with the omega subunit of RNA polymerase, a known transcriptional activator that recruits RNA polymerase to ignite transcription in E. coli.⁴⁶ VP64, a complex containing four copies of the herpes virus transcriptional activation domain, VP16,⁵¹ has also been fused with dCas9 to activate gene transcription increase transcription of endogenous genes in plant and animal systems.^{44,47–50,52} Although early attempts led to less than twofold increases in gene activation using HEK293T cells,⁴⁹ further optimization of dCas9/VP64 chimeras significantly increased gene activation efficiency for a panel of genes between 3- and 820-fold, depending on the gene target (Fig. 2A).^47,48,50

FIG. 2.

Various CRISPR-based gene expression activator systems. (A) dCas9 is fused with VP64, a tetrameric protein of the herpes simplex VP16 transcriptional activator domain. Target gene regulatory sequences through its programmable gRNA. The VP64 domain acts as a transcriptional activator. (B) dCas9 is fused with a tripartite activator containing VP64, p65, and Rta. (C) The sgRNA of a dCas9/VP64 fusion domain is engineered with two aptamers that bind to the positive transcriptional regulator MS2. (D) dCas9 is engineered with an antibody peptide chain that binds to VP64. sgRNA, single guide RNA.

The second generation of CRISPRa, generated by Tanenbaum et al., was further enhanced using a single-chain antibody peptide pair to recruit transcriptional activation modules to the dCas9 bound sequences (Fig. 2D). This dCas9 version termed “SunTag” exhibited a more robust activation response than dCas9/VP64 complexes alone, even when targeting poorly expressed genes.⁵⁰ Another method uses a tripartite complex termed “dCas9–VPR” containing the transcriptional activators VP64, p65, and Rta, which significantly increases gene expression compared with using VP64 alone (Fig. 2B).⁴⁷ An alternative CRISPRa strategy employs a synergistic activation mediator (SAM) that adds protein-interacting RNA aptamers to the tetraloop and stem-loop 2 of the sgRNA (Fig. 2C)⁴⁸ that can then associate with the MS2 bacteriophage coat proteins to recruit VP64 and activate gene expression.⁴⁸ This approach allows a more simple cloning design as the VP64 motif is not required to be fused to dCas9.⁵³

Research has shown CRISPRa methods (SAM, SunTag, and VPR) perform similarly when activating gene expression, although the SAM strategy generally exhibited the highest activation levels.⁵⁴ This study also demonstrated that multi-gRNA targeting allowed for further enhanced gene activation in vivo.⁵⁴ Additional research continues to improve CRISPR-based gene regulation techniques.^55,56

The generation of chimeric dCas9 variants with proteins capable of altering epigenetic marks further expands the capabilities of CRISPR for gene regulation. This strategy closely resembles epigenetic modulation with ZFPs and TALEs.^57–59 The dCas9–KRAB chimeric fusion has been used to negatively regulate an enhancer in the globin gene regulatory region in human leukemia cell lines, resulting in deacetylation and methylation of this genomic portion.⁶⁰ In addition, dCas9 has also been fused with human acetyltransferase to activate gene expression at targeted loci and induce transcription at both proximal and distal enhancers, proving that this module can control gene expression by altering the epigenetic state of the locus.⁶¹ Whereas dCas9/VP64 effectively activates proximal enhancers. No significant effect is seen when targeting distal enhancers. This suggests an advantage for CRISPR-based epigenetic control when targeting distal regulatory regions.⁶²

Mirroring Cas9, Cas12a (previously Cpf1) has also emerged as an effective system for genome editing and CRISPR-mediated gene regulation in plants and animals.⁶³ Cas12a is a class II CRISPR enzyme requiring a crRNA guide, with an A/T-rich PAM sequence offering additional possibilities for sequence targeting. Furthermore, it displays both DNAse and RNAse activities and independently processes its own precursor crRNA.²¹ Similar to dCas9, the DNAse “dead” Cas12a (dCas12a) has been employed for multiplexed CRISPRi.⁶⁴ Notably, dCas12a-induced gene repression in E. coli was more effective for crRNAs, specifically targeting the antisense strand of its target genes.⁶⁴

Integration of CRISPR-Cas systems and machine learning for genome-wide studies

In virtually any living system, the control of gene expression is a multilayered process in which many players act in an exquisitely coordinated manner. The incorporation of CRISPR into our toolset has opened new avenues to better understand the intricacies of gene regulation. One key advantage of CRISPR systems is the ease of programmability, which has made the construction of gRNA libraries more feasible. Furthermore, next-generation sequencing (NGS) allows for more facile readouts of large-pooled screens, drastically reducing time and increasing depth in multiloci screenings.

Initial studies employing CRISPRi/CRISPRa could modulate gene expression for one or several genes. These advancements have paved the way for genome-wide approaches, employing gRNA libraries with 10 to 1000 gRNAs per gene.⁶⁵ Gilbert et al. describe one such genome-wide map of molecular pathways to understanding gene dosage (up-/downregulation) and its downstream effects.⁶⁵ This study first employed an algorithm to construct 2 gRNA libraries and implemented CRISPRa and CRISPRi screen targeting 49 genes implicated in ricin susceptibility. This method identified essential loci and several tumor suppressor genes, which are potential targets for drug therapies. Since then, other CRISPR-based genome-scale gene regulation studies have been performed.⁴⁸

Fulco et al. employed machine learning alongside CRISPRi to explore the functions of cis-regulatory elements, ultimately examining over one megabase of sequence to identify nine distal enhancers of the transcription factor genes MYC and GATA1.⁶⁶ Klann et al. leveraged CRISPR-based regulation to identify epigenetic marks through CRISPR-Cas9–based epigenomic regulatory element screening in the native chromosome context. This was done by fusing dCas9 (1) with the human acetyltransferase p300 (dCas9–p300), which catalyzes robust transcriptional activation, or (2) with dCas9–KRAB that mediates negative gene regulation in the native chromosome.⁶⁷

The capacity to process the large data sets at the genome-wide scale through machine learning and computational biology has furthered genome-wide CRISPR-based gene expression studies and possible applications. In 2016, Horlbeck et al. used predictive computational modeling to design highly effective gRNAs to delineate various molecular pathways.⁶⁸ This in silico approach improved upon a previous method that used libraries containing 10 sgRNAs per gene and only required 5 sgRNAs per gene.⁶⁵ In addition, machine learning has also been applied to improve gRNA design rules for CRISPRi studies in E. coli and uncovered that a significant number of the gRNAs in the library (∼92,000 gRNAs) produce strong fitness defects.⁶⁹ This was due to the binding of gRNAs to low identity off-target sites containing a 5-nucleotide gRNA seed sequence, regardless of the other 15 nucleotides in the spacer.

The combination of machine learning and CRISPR technology has also been employed to gain insights into protein structure and function associated with human diseases. In 2018, Pan et al. used data sets from previous large-scale CRISPR-Cas9 and RNAi fitness screens of human cancer cell lines to reveal novel protein complexes originating from new genes with unknown functions.⁷⁰ This study was based on the understanding that protein interactors tend to share correlated fitness levels when depleted.

Moreover, machine learning has also been exploited to better understand and predict CRISPR-induced genome editing,⁷¹ and minimize off-target editing in crop species, which further expands the array of applications of CRISPR technologies.⁷² For instance, Young et al. combined computational in silico prediction of off-target sites in the complex maize genome, confirmation of off-target cleavage, and surveillance of off-target site candidates in cell culture to identify the best gRNA design to mitigate off-target editing and prevent off-target cleavage in plants.

The development of CRISPR screens has transformed the bottlenecks associated with functional genomic studies. The limitations no longer lie in the number of transformable target genes, thanks to massive gRNA libraries. The primary bottleneck now lies in data analysis, which can be significantly alleviated with the introduction of machine learning to identify relationships between many gene targets, which may have been otherwise overlooked, even by experts.

Therapeutic applications of inducible CRISPR-based gene modulation

Therapeutic applications of CRISPR-Cas9 editing have attracted a lot of attention, and many strategies are currently being broadly developed. In addition to gene therapy, CRISPR-based gene regulation technologies have garnered interest as potential therapeutics due to their modularity and versatility. Therapeutics involving transcriptional activation of genes associated with a disease or to identify novel drug targets are all promising avenues for CRISPR–gene regulation-based therapies.

Previous research has used chemically, or light-inducible versions of ZFP and TALEs to control gene expression,^73,74 and similar CRISPR-based approaches have been adopted based on this principle. Light and chemically inducible therapies can facilitate spatiotemporal control, allowing for precise targeting of a specific location in the body. Toward this end, a light-activated CRISPR/dCas9 system was designed to trigger transcription by binding to a promoter sequence in HEK293T cells. This was achieved by creating CRY2-VP64 heterodimer proteins and dCas9–CIBN fusion proteins. CRY2 undergoes a conformational shift when exposed to UV light, allowing it to heterodimerize to C1B1. This activates transcription through VP64, thus inducing gene expression when exposed to UV light.⁴² Additional chemically inducible split gene expression using rapamycin-binding domains and dCas9 has also been generated, showing that chemical induction can also be used to regulate transcription of multiple genes in HEK293FT cell lines.⁷⁵

Beyond these strategies, CRISPR technology has been implemented in cancer and HIV therapeutic research. CRISPR-based fitness screens have been used in known cancer cell lines to identify target genes essential for specific cancer cell growth.⁷⁶ CRISPRa has also been used to reverse HIV latency, thus minimizing antiviral treatment resistance.⁷⁷

Another potential therapeutic application lies in the treatment of haploinsufficiency, where loss-of-function mutations in one allele (heteroallelic conditions) can lead to reduced gene dosage and cause cancer, neurological, immunological, and kidney diseases.⁷⁸ CRISPR-based therapies have been proposed to address the haploinsufficiency of Sim1, a transcription factor essential in hypothalamus development, which has been implicated in severe obesity in humans. Activation of the intact Sim1 allele could correct faulty gene dosage. This also addresses the DNA packaging limitations associated with recombinant adeno-associated virus gene therapies for gene dosage pathologies. In a mouse model, dCas9–VP64 chimeras targeted the promoter of a distal Sim1 enhancer and reversed the obesity induced by haploinsufficiency of the Sim1 mouse gene.⁷⁹

Like many CRISPR-Cas9–based therapeutic approaches, CRISPR gene regulation must overcome the hurdles of off-target gRNA effects. Because of its nuclease deficient nature, dCas9 is less likely to produce unwanted mutations. However, unwanted changes in the overall transcription profile can produce severe toxicity. gRNA design and QC tools such as RNA-seq and CHIP-seq can assist in the identification of CRISPRa off-targets, which were undetectable in the mouse model CRISPRa studies targeting distal enhancers of Sim1.⁷⁹ Another limitation of CRISPRa/CRISPRi-based therapies is nucleosome occupancy, which, when high, has been shown to decrease Cas9 and dCas9 targeting efficiency.^80,81 This limits the potential therapeutic targets to more active regulatory regions of the genome, where nucleosome occupancy is low.

CRISPR-Based Diagnostics

DNA diagnostics

In 2017, a strategy involving two dCas9 molecules, each linked to half of a split firefly luciferase (NFluc and CFluc), was developed to detect specific DNA sequences in vitro with high specificity and sensitivity. Through their respective gRNAs, the two dCas9 enzymes are directed to two target sites within proximity to one another, which then allows the NFluc and CFluc halves to reconstitute an active luciferase that serves as reporter output. This method was employed to detect the Mycobacterium tuberculosis genome, the primary pathogen in human tuberculosis infection. One of the advantages of this method is the possibility to discriminate between target and nontarget due, in part, to the requirement of two gRNAs for genome recognition and luciferase reconstitution.⁸²

An additional technique has also been reported to detect specific DNA sequences with Cas12a. Upon specific recognition of its target sequence within dsDNA, Cas12a is activated and can indiscriminately digest ssDNA. Along with isothermal amplification, researchers have levied the nondiscriminatory cleavage activity of Cas12a to develop a method for sensitive DNA detection (Fig. 3A). This method, coined DNA endonuclease targeted CRISPR trans-reporter (DETECTR), is capable of detecting viral DNA (human papillomavirus) and SARS-CoV-2 directly from clinical samples.⁸³

FIG. 3.

General Cas12a and Cas13a molecular diagnostic strategies. (A) DETECTR and HOLMES can be used to identify specific DNA sequences. The target DNA sequence is amplified using PCR and RPA or other isothermal amplification. Once amplified, Cas12a binds to its targeted DNA samples, thus activating its single-stranded DNA cleavage activity. Activated Cas12a cleaves single-stranded DNA reporter, which emits a fluorescent signal when cleaved. (B) SHERLOCK can detect DNA and RNA sequences with Cas13. RPA or RT-RPA followed by T7 transcription is used to create amplified RNA fragments. Upon binding to target RNA, Cas13 collateral ssDNA cleavage is activated, and the fluorescent reporter's cleavage results in a signal readout. DETECTR, DNA endonuclease targeted CRISPR trans-reporter; HOLMES, HOur Low-cost Multipurpose Highly Efficient System; RT-RPA, reverse-transcription recombinase polymerase amplification.

Li et al. reported a similar method for dsDNA detection. This approach, termed 1-HOur Low-cost Multipurpose Highly Efficient System (HOLMES), detects target DNA sequences by first amplifying them through PCR or isothermal amplification methods. The target amplicon is then incubated with Cas12a, which is complexed with a gRNA complementary to the target DNA. Upon complex formation (Cas12a–gRNA–DNA target), trans-cleavage activity of Cas12a is activated, and the complex begins to cleave a quenched fluorescent ssDNA fluorescent reporter.⁸⁴ A second generation of the HOLMES method integrates amplification and CRISPR-based detection steps.⁸⁵ The two Cas12a-based methods, although similar in process, differ in their amplification steps. Although HOLMES employs PCR for amplification, DETECTR employs isothermal amplification techniques such as recombinase polymerase amplification.

An additional CRISPR–Cas12a-derived biosensing platform can detect a diverse array of small molecules with high sensitivity.⁸⁶ In this publication, bacterial allosteric transcription factors (aTFs), which have evolved to respond to various small molecules to improve bacterial survival chances, were combined with CRISPR–Cas12a's ability to cleave ssDNA. In this approach, coined CaT-SMelor, an aTF is complexed with a cellulose-binding domain that interacts with a specific dsDNA. This DNA molecule also contains the Cas12a PAM and target sequence. The DNA–aTF cellulose-binding domain elements are all immobilized on microsatellite cellulose (MC). In the target small molecule's presence, the aTF undergoes a conformational change that releases the dsDNA. This allows the dsDNA and Cas12a to interact and, therefore, activates Cas12a trans-cleavage activity of ssDNA. This process is detected through an ssDNA quenched reporter that fluoresces once digested by Cas12a. Not only was this system sensitive, but it also allowed for rapid and high-throughput analysis of small molecules.⁸⁶

All these CRISPR-Cas–based approaches for nucleic acid and small molecule detection are more programmable and rapid than many traditional diagnostics methods. However, they all rely on optical readouts, which often require bulky laboratory equipment.

Recent research has led to the development of digital DNA detection methods using CRISPR-Cas systems. One such method immobilized dCas9 on a graphene-based field-effect transistor to detect specific DNA sequences.⁸⁷ Notably, DNA amplification is not required in this technology, becoming the first CRISPR-based amplification-free detection system. This method, termed CRISPR-Chip, could detect and discriminate two pathogenic exon deletions in genomic DNA samples from patients with Duchene muscular dystrophy. Although previous methods largely depend on amplification (PCR and or isothermal amplification techniques), this technology avoids the requirement and access for laboratory resources and infrastructure, opening the door for its application in agriculture or point-of-care diagnostics. In addition, this technology has recently been further improved by utilizing Cas9 and a Cas9 ortholog (MgaCas9) to detect single nucleotide mutations implicated in sickle cell disease and amyotrophic lateral sclerosis without the need of an initial target amplification step.⁸⁸

Another study employed programable smart materials composed of a hydrogel with ssDNA as the linker between polymers. This hydrogel is degradable in the presence of the trans-cleaving Cas12a. Upon degradation, the fuse characteristics of the hydrogel are lost, and the electrical signal was modulated. The same study reported a microfluidic paper device, which could be used for point-of-care CRISPR-based diagnostics.⁸⁹ In addition to potential diagnostic applications, this strategy could provide a new avenue for controlling the release of biologically active molecules from hydrogel, transducing electronic signals, and actuation of microfluidic valves.⁸⁹ At this stage, this technique has only been used with a short DNA trigger and requires preamplification steps if used in the context of gene detection.

RNA diagnostics

In 2017, Gootenberg et al. reported sequence-specific RNA detection through Specific high Sensitivity Enzymatic Reporter UnLOCKing, dubbed SHERLOCK. This method detects specific RNA and DNA sequences at attomolar sensitivity using Cas13 and isothermal amplification (Fig. 3B).⁹⁰ Cas13 is activated when it binds to a specific RNA sequence, determined by the crRNA. After this activation, Cas13 begins collateral cleavage of all RNA, detecting an RNA probe that fluoresces when cut.⁹⁰

SHERLOCK initially detected Zika and dengue viruses, single-nucleotide polymorphisms, and cancer mutations with estimated costs of $0.61 per test, creating a fast and cost-efficient method with vast diagnostic applications.⁹⁰ In 2018, Gootenberg published SHERLOCK v2, improving upon their initial process by using Cas13 and Csm6 (another CRISPR-associated enzyme). SHERLOCK v2 exhibited increased signal sensitivity and gave measurable signals with inputs as low as two attomolar.⁹¹

Additional research has continued to improve upon SHERLOCK by combining it with another method, coined HUDSON (heat unextracted diagnostic samples to obliterate nucleases).⁹² It is employed to facilitate the lysis and deactivation of ribonucleases in clinical viral samples, allowing SHERLOCK-based detection to occur directly from bodily fluids through a colorimetric readout with no instrumentation. These assays successfully differentiated between multiple dengue virus and Zika virus strains.⁹²

The incorporation of CRISPR strategies for virus monitoring (e.g., Zika and dengue) has facilitated field-deployable platforms for low-resource areas. One method combined toehold switch RNA sensors with CRISPR-Cas9 technology on a paper-based system to create a low-cost and rapid diagnostic technique. In this strategy, nucleic acid sequence-based amplification (coined “NASBA”) is used with Cas9 cleavage for strain differentiation. When cleavage occurs, nucleic acid sequences no longer contain the trigger region required for toehold activation, and no amplification occurs.⁹³

CRISPR-based detection of SARS-CoV-2 infection from RNA extracts from respiratory swabs has demonstrated facile and rapid designs for diagnostics. One group reported a lateral flow assay using DETECR methodology. This assay was fast (<40 min), and high accuracy was validated by both synthetic and clinical samples from patients with SARS-CoV-2 infection and patients with other viral respiratory infections.⁹⁴ Unfortunately, the need for further microfluidics platform optimization, and the need for lyophilized reagents, remains a challenge for this approach to mass testing.

The development of combinatorial arrayed reactions for multiplexed evaluation of nucleic acids, also known as CARMEN, has shown that CRISPR-based nucleic acid detection can also be used for pathogen detection. Specifically, this strategy uses droplets containing CRISPR reagents, pairing with microarrayed droplets of amplified samples. CARMEN–Cas13 allows for large batch testing (4500 crRNA-target pairs to be tested on a single array) and has been able to differentiate 169 human-associated viruses and can be easily adjusted to diagnose SARS-CoV-2 infection.⁹⁵

In addition, CRISPR-Cas systems can be used to detect microRNAs (miRNAs), which are often involved in plant^96,97 and animal diseases.^98,99 In 2018, Qiu et al. combined isothermal amplification and Cas 9 to detect miRNAs with single-base specificity in a method coined rolling circle amplification CRISPR-split-HRP (RCH). Using clinical sample serum, this method was able to differentiate between healthy patients from nonsmall cell lung cancer patients, becoming the first publication to detect miRNAs using CRISPR-Cas systems. miRNAs are linked to many key biological processes, but they are often difficult to detect. This method, however, offers a promising diagnostic tool.¹⁰⁰

CRISPR-Based Imaging

For decades, scientists have attempted to image the three-dimensional (3D) spatiotemporal organization of genomes accurately to observe allelic and gene-specific activation, repression, or DNA damage/repair due to their significance in processes such as morphogenesis, disease, or adaptation.¹⁰¹ Chromosomal rearrangements and architectural substructure have been linked to illness and also impact enhancer-promoter interactions.^102–105 One classical method used for 3D imaging is fluorescent in situ hybridization (FISH).¹⁰⁶ In addition, NGS approaches such as Hi-C have been used to analyze allele-specific chromatin structures.¹⁰⁷ These methods, however, have their limitations when performing live-cell imaging as they rely on cross-linking and chemical modifications of the cells and nuclei, potentially leading to cell death and/or genome alterations.^108–110 Upon discovering CRISPR systems, scientists have used dCas9 to live image the genome's 3D organization (Fig. 4).

FIG. 4.

Schematic of the general CRISPR imaging system. dCas9 is fused with a fluorescent protein. This fluorescent dCas9 is coexpressed with sequence-specific sgRNA, establishing a detectable fluorescent signal at the gene of interest in vivo.

One of the first instances of using the CRISPR–dCas9 system for genomic imaging was conducted in 2013 by Chen et al. using an optimized sgRNA bound to a dCas9–EGFP (enhanced green fluorescent protein) fluorescent fusion protein (Fig. 5A). After insertion into the cell through transfection, the dCas9–EGFP system's coexpression allowed targeted fluorescent images of genomic loci. Specifically, this method was used to study telomere dynamics and coding regions in live cells. While dCas9–EGFP was found to be as effective as FISH in repetitive genomic regions, the fluorescent signal was not sufficient to easily detect nonrepetitive regions.

FIG. 5.

Schematic of popular CRISPR-based imaging systems. (A) A dCas9/EGFP fusion protein binds to a targeted sequence. (B) A dCas9/fluorescent protein fusion protein is engineered with an sgRNA containing an extra stem loop and fluorescent YFP protein chain. (C) sgRNA is engineered to have a dual fret-MBs system, leading to the illumination of the genetic locus of interest upon binding. EGFP, enhanced green fluorescent protein; FRET, fluorescence resonance energy transfer; MBs, molecular beacons; MCP, the bacteriophage MS2 coat protein; YFP, yellow fluorescent protein.

To target nonrepetitive regions of the genome, researchers engineered multiple sgRNAs were engineered to target every 5 kb of the nonrepetitive region in the MUC4 gene.¹¹¹ They found they could effectively label nonrepetitive using 26–36 unique sgRNAs. However, the research community has argued that it often is challenging to introduce that many gRNAs into the cell and could, in addition, interfere with the loci being imaged.^111,112

The SunTag strategy for modulating gene expression has also been used for genome imaging.¹¹³ The protein scaffold can recruit up to 24 GFP molecules to a single locus, creating an 18-fold improvement in GFP visualization. This vast improvement allowed for clear imaging at lower signal intensities, which decreased phototoxicity and allowed for longer imaging intervals in live cells.⁵⁰ This method for imaging could provide a technique that could imagine nonrepetitive regions with fewer gRNAs.

In 2017, Qin et al. engineered a CRISPR/dCas9 system (sgRNA 14x-MS2) to target low-repeat containing genomic loci with a single sgRNA. To do this, researchers engineered a sgRNA with multiple MS2 stem-loop sequences that are then bound to multiple the bacteriophage MS2 coat protein (MCP)–YFP (yellow fluorescent protein) complexes, creating a stronger fluorescent signal per sgRNA compared to a conventional sgRNA¹¹² (Fig. 5B). In 2018, Chen et al. created CRISPR-Tag, in which an engineered CRISPR tag (made up of seven sgRNA sequences) was inserted throughout the 3′UTR or intron of the gene of interest through CRISPR knock-in. Then, a programmable dCas9–GFP fusion protein binds to the CRISPR tags inserted into the gene of interest.¹¹⁴

CRISPR-imaging techniques have also been used to study the dynamics of CRISPR protein activity.^115,116 In 2015, Knight et al. used a fluorescently labeled dCas9 to measure CRISPR diffusion and chromatin binding, providing insight into how CRISPR-Cas systems integrate into the genome.¹¹⁵ In 2019, Wang et al. used a technique termed “LiveFISH” to study double-stranded breaks integral to CRISPR-Cas genome editing by using fluorescent gRNA probes complexed with dCas9.¹¹⁶ In addition, this method was able to detect genomic nucleic acid transcripts as well as chromosomal abnormalities by programming the LiveFISH RNA to target repetitive regions in the genome.¹¹⁶

To further improve imaging signals, Mao et al. in 2019 created CRISPR/dual-fret molecular beacon (MB) using MBs, a type of fluorogenic probe. In this system, sgRNAs were modified to harbor MTS (a sequence not in the human genome) that binds to MBs.¹¹⁸ After dCas9 and the sgRNAs target the locus of interest in the cells, the MBs bind to the dual-MTS sgRNA (Fig. 5C). These MBs contain a fluorescence resonance energy transfer (FRET) pair that requires both MBs to bind to the sgRNA, thus creating a stronger signal and decreasing background noise. This method was able to image nonrepetitive regions of the genome using only three unique sgRNAs, indicating higher sensitivity when compared with that of fluorescent-based CRISPR/dCas9 imaging systems.^117–119

In addition, increasing efficiency and specificity to yield more accurate chromosome CRISPR-based images with higher definition has also been a topic of study. One such method uses CRISPR-Sirius, a CRISPR-based imaging system with an optimized stable gRNA.¹²⁰ To increase gRNA stability, they created thermostable groups of eight MS2 aptamers and mutated the MS2 aptamers to prevent complications associated with misfolding and recombination.¹²⁰ This system was more efficient than the existing sgRNA-3′-14xMS2 system.^112,120

Strategies based on allelic differences in living cells have attracted many groups' attention because of their potential in diagnostics and basic research. In Maass et al., researchers engineered a live-cell allele-specific DNA imaging technique called SNP-CLING (single nucleotide polymorphism CRISPR live-cell imaging) by designing two to three sgRNAs for each allele. Each sgRNA was bound with RNA aptamer motifs, bound to an RNA-binding protein with a fluorophore. This method could image both allelic positioning and allele-specific interactions in mouse embryonic stem cells in real time.¹⁰⁹

CRISPR-based imaging systems can also be applied for monitoring multiple genomic loci simultaneously in the same cells with different fluorescent proteins. This was demonstrated in Ma et al., where researchers created the CRISPRainbow system, where six unique genomic loci were simultaneously targeted fluorescently tagged dCas9/gRNA systems. To do this, three different hairpins were fused to the different sgRNAs in varying combinations. Two fluorescent proteins were then bound to each of the sgRNAs, forming three primary colors (blue, green, and red), and three secondary colors (cyan, magenta, and yellow, and a combination of the three primary colors formed white).¹²¹

Fu et al. describe another method to image multiple loci. Researchers designed a CRISPR/dCas9 imaging system using MS2 and PP7 aptamers, sgRNAs that target two separate loci of interest, dCas9, and MCP and the bacteriophage PP7 coat protein (PCP) (which bind to Ms2 and PP7) fused to EGFP and mCherry, respectively.¹⁰¹ Overall, CRISPR-based DNA imaging is flexible, relatively easy to engineer for different loci, and efficient.

dCas9-based CRISPR imaging systems can three-dimensionally image genomic regions and chromosomes and RNA in vivo.¹²² Other CRISPR-Cas proteins have been employed for RNA visualization, including Cas13-based CRISPR systems.¹²³ In Yang et al., researchers used CRISPR-dPspCas13b and CRISPR-dPguCas13b to image RNA in vivo. To determine whether the dCas13-EGFP systems were binding to the correct targets in cells, researchers tagged a local locus with mRuby3. Two dCas13 proteins, dPspCas13b and dPguCas13b, were found to effectively label NEAT1 RNA, with dPspCas13b being more efficient at labeling than dPguCas13b.

Next, researchers optimized guide RNA length, targeting position, and the type of fluorescent protein fused when used in conjunction with dPspCas13b. After engineering dPspCas13b-3xEGFP, and dPspCas13b-3xsfGFP-3xNLS, they successfully labeled mRNAs in the cytoplasm and the nucleus that contained a minimum of eight repeats accurately. They compared this imaging system with current MS2–MCP-based systems and found the CRISPR-based approach (with a single gRNA) yielded a higher signal-to-noise ratio but was more efficient than the MS2–MCP system. The two Cas13b subtypes (dPspCas13b and dPguCas13b) can also be used in conjunction to label two unique RNAs.¹²⁴ This dCas13-based system was also used in conjunction with a dCas9-based DNA imaging system to label the SATlll gene, targeting the genomic loci with dCas9 and then associated mRNA with dCas13. This allowed for dual live imaging of DNA and RNA simultaneously. All these strategies exemplify that CRISPR-based imaging systems are efficient, flexible, and effective in living cells.

Quality Control of CRISPR-Cas9-Induced Primary Outcomes

As described in this review, CRISPR-Cas9 systems have been repurposed to benefit a wide array of biotechnology-based fields. However, CRISPR-Cas9 is still primarily used to edit genes. This editing's primary outcome is forming a double-strand break (DSB) at a defined genomic locus in live cells, tissues, or whole organisms. These induced DSBs are repaired by four main cellular repair pathways.¹²⁵ Two of these pathways, classical nonhomologous end joining (NHEJ)¹²⁶ and alternative NHEJ (alt-NHEJ), also known as microhomology-mediated end joining,¹²⁷ can leave small nucleotide insertions, deletions, or a combination of both at the DSB repair site.

A commonality of most CRISPR systems is the RNA dependence of the genomic site-specific targeting. For wild-type Cas9, the gRNA has been shown to dictate the InDel formation potential. Elegant studies have demonstrated that Cas9/gRNA-mediated cleavage is induced following the “zipping” of the gRNA with its target site. This zipping leads to complete complementarity in base-pairing between the gRNA and the target DNA and forming the stable Cas9/gRNA/target DNA ternary complex.^128,129 This ternary complex is essential for allosteric activation of Cas9 nuclease activity. After that, InDel formation occurs through complex processes.

Both the initial DSB and the subsequent InDel repair events are difficult to predict based on the cleavage efficiency and the repair outcomes at the cut site.¹²⁵ The most common InDel outcomes are minor deletions or insertions (<30 bp). In addition to these commonly detected outcomes of gene editing, recent studies have shown that deletions of several kilobases, along with complex rearrangements, are also found to be elicited by CRISPR-Cas9. These more dramatic events occur at frequencies of up to 10%; however, they arise through currently unclear mechanisms.^130,131 Despite advances in incorporating vast knowledge of Cas9/gRNA-induced InDels into design algorithms, the Cas9:gRNA cutting efficiency, for instance, still varies considerably between algorithm-based gRNA designs, and in many cases, designs are nonfunctional.^71,132,133

In this regard, respondents from a recent global survey among CRISPR-Cas9 users from various scientific disciplines, including academia, biotech, biopharma, and life science, showed that the primary experimental Cas9/gRNA objective was the establishment of out-of-frame causing InDels (https://www.future-science.com/doi/10.2144/btn-2019-0084).

Since most knockout applications require that both the efficiency and nature of InDel editing are accurately determined, the need for cost-efficient, sensitive, and accurate InDel profiling methods remains in place. Furthermore, it has become increasingly clear that both off-target and unintended on-target events occur after gene editing.¹²⁵ Therefore, as CRISPR-Cas9 technologies move from “bench to bedside,” the need to minimize safety concerns while maximizing CRISPR-based therapeutics' efficiency has become increasingly important. A gold standard for identifying and detecting Cas9/gRNA-induced InDel outcomes has yet to be defined. However, through initiatives such as the NIST Genome Editing Consortium (https://www.nist.gov/programs-projects/nist-genome-editing-consortium), there is hope that standards and guidelines will be provided. Guidelines, which define a gold standard, would lower risk and increase confidence in InDel detection methodologies as routine genome editing analytical resources in academic, clinically translational, and commercial settings.

As a complement to the analytical standardization aspect of the NIST Genome Editing Consortium, considerable research efforts have been invested in improving the specificity of CRISPR-Cas systems through protein engineering of Cas9 aimed at minimizing off-target binding, improving gRNA and Cas protein stability, and kinetics of CRISPR-Cas activity.^68,134–136 The biotechnology industry has also adapted to the need for CRISPR quality control, as evident by the recent rapidly growing number of suppliers of good laboratory practice-grade gene-editing tools and reagents. Likewise, it becomes increasingly essential from an analytical perspective that accurate and sensitive detection of the primary Cas9/gRNA-induced outcomes is conducted. Cobo Technologies, for example, performs quality control of CRISPR-Cas9–generated outcomes in cells, tissues, and whole organisms by a proprietary triprimer amplification principle coined InDel detection by amplicon analysis (IDAA).¹³⁷

Alternatively, CRISPR-Cas9 validation can be confirmed by Sanger sequencing-based service providers such as Genescripts “Genomic DNA Sequencing” services (https://www.genscript.com/genomic-DNA-sequencing.html), NGS-based services provided by Eurofins “Inview CRISPR Check” (https://eurofinsgenomics.eu/en/next-generation-sequencing/ngs-built-for-you/inview-crispr-check), or Genewiz “CRISPR Validation” service (https://www.genewiz.com/en-GB/Public/Services/Next-Generation-Sequencing/CRISPR-Validation) and an amplification free digital detection method.⁸⁷ This convergence of CRISPR-Cas systems with digital technologies can also enable genome-wide screening for various genetic mutations through multiplex gene targeting methods (such as that described in Zhang et al.⁶⁴).

Discussion and Potential Future Applications

The simple yet powerful gene-editing technology based on the CRISPR toolbox and its virtually universal applicability has ignited a revolution in life sciences that is impacting basic research, therapeutics, and diagnostics. In this review, we have discussed some of the most recent advancements and applications that CRISPR technologies have to offer. However, it is unquestionable that this is just the tip of the iceberg as new CRISPR-based technologies are constantly being reported.

The easy reconfiguration of the acting modules, the requirement of very little equipment, the low cost, and logistical feasibility for its use as, for example, rapid point-of-care diagnostics, sensing device or therapeutics are precious features that put CRISPR systems ahead of other platforms and make it an excellent option for its deployment in the field.^{93,94,138,139} In this regard, CRISPR technologies have been used to detect viruses,^94,138 treat infections,¹⁴⁰ or leveraged to treat antibiotic resistance.¹⁴¹ These innovations are just a taste of the potential to detect, monitor, and treat a wide array of human diseases and plant pests.

Nevertheless, there remain some challenges ahead that require attention. The mining and dissection of other CRISPR systems, the identification of PAM-less Cas proteins,¹⁴² or the increase in sequence targeting specificity to minimize off-target effects will undoubtedly increase the impact and potential of this technology and make it more suitable for specific applications. However, we cannot be oblivious to the fact that more comprehensive legislation will certainly also assist.¹⁴³ In contrast, the convergence of CRISPR technology with biosensor systems will continue revolutionizing CRISPR-based applications' quality and scope. The need for amplification is bypassed using digital detection instead of traditional optical detection methods, thus vastly expanding which technologies can be field deployable.

Although CRISPR-Cas systems have gained much popularity for genome editing purposes, this technology is poised to revolutionize multiple fields such as diagnostics, therapeutics, agriculture and breeding,¹⁴⁴ gene regulation, imaging, or RNA biology, just to mention a few. In summary, we have just started to scratch the surface of the great potential that this technology offers us now and in the years to come.

Author Disclosure Statement

E.P.B. and J.O.B. are cofounders of CoboTechnologies Aps. and hold ownerships in the company. E.P.B. acts as a scientific advisor of CoboTechnologies Aps. E.P.B. declares that a patent application covering the IDAA method is pending.

Funding Information

This work was funded through NSF #GR750012, NIH #GR750002 and Cardea sponsored research #GR720020.