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GEN FEATURE: Leveraging Modern Electronics to Streamline CRISPR Workflows


By Kiana Aran, PhD

The adoption of CRISPR-Cas systems in therapeutics development has led to the rapid emergence of several clinical candidates for treating rare and challenging diseases, including sickle-cell anemia, β-thalassemia, Duchenne muscular dystrophy, and ocular diseases. Translation into the clinic has been facilitated by a robust preclinical framework of genome editing tools, empowering nearly any R&D team to streamline gRNA design and synthesis, select the most desirable Cas protein for its application, and characterize on- and off-target editing in live cells.

These tools form the foundation for a typical preclinical CRISPR editing workflow. In general, this workflow involves the following steps: 1) CRISPR-Cas system selection, 2) gRNA design (and synthesis, in the case of ribonucleoprotein transfection), 3) transfection into live cells, 4) single-cell cloning, 5) screening, and 6) on-/off target analysis. This basic workflow has been shown to be useful in a broad array of experimental conditions. It has accommodated many Cas-gRNA combinations, various transfection or cell culture conditions, and PCR- or NGS-based techniques for assessing on-/off-target editing.

While seemingly straightforward, this now-routine, entrenched workflow has its drawbacks. It can be labor-, time-, and cost-intensive. For example, difficulties can arise in gRNA design and selection, a task that has been eased by the introduction of several in silico algorithms and frameworks. These tools allow the manipulation of many parameters, including PAM positioning, GC content, secondary structures, and mismatches. Nonetheless, gRNAs that appear perfect on a computer often perform poorly, resulting in minimal editing or undesirable off-target effects in cells.

When problems arise in CRISPR editing workflows, researchers often resort to awkward and time-consuming troubleshooting approaches. These may involve focusing on in silico gRNA optimization and redesign, tweaking of transfection conditions, or switching strategies for Cas-gRNA delivery or expression. Furthermore, conventional workflows don’t include in vitro assays for Cas-gRNA complex formation or target binding, forcing many researchers to operate and optimize with incomplete information.

In vitro methods

In principle, the issues encountered in the traditional straight-to-cell approach can be addressed using in vitro methods, commonly used in small-molecule and biopharmaceutical development pipelines. Though not often used in CRISPR-Cas editing workflows, in vitro assays can provide indispensable insights into gRNA binding affinity, target or nontarget DNA binding affinity, and cleavage efficiency, bridging the growing knowledge gap between the in silico and cell-based worlds.

Currently, there are several reconstituted CRISPR-Cas systems for assessing in vitro activity. Gel-based cleavage assays help determine the cleavage efficiency of Cas-gRNA ribonucleoproteins (RNPs). However, these assays can be low in throughput and sensitivity, further slowing already cumbersome editing workflows. More rapid, sensitive, and specific assays have been developed. One is Sherlock Biosciences’ Specific High-sensitivity Enzymatic Reporter unlocking (SHERLOCK) technology. Another is Tolo Biotech’s one-HOur Low-cost Multipurpose highly Efficient System (HOLMES). SHERLOCK and HOLMES rely on isothermal T7 RNA polymerase-mediated and PCR-based amplification, respectively. Both assays use a fluorescent reporter to detect CRISPR-Cas cleavage.

By providing a better understanding of cleavage activity, such assays would be valuable to conventional CRISPR-Cas editing workflows. However, an ideal in vitro assay would also provide insight into other biochemical steps, such as Cas-gRNA complex formation and RNP recognition of target DNA sequences upstream of target cleavage. In addition, reliance on fluorescence-based assays and optical assays, in general, requires amplification, resulting in additional time, reagents, and instrumentation.

Chip-based methods

Recently, the detection of biological activities has gone through a transformation, trading optics-based methods for chip-based electrical methods. One of the chip-based electrical methods is embodied by the Biosignal Processing Unit (BPU), a technology developed by Cardea Bio. It facilitates rapid, highly sensitive translation of biological activity into digital information.

The BPU is a graphene transistor that can be functionalized with a wide range of biomolecules. Performing biochemical reactions (such as a binding interaction or catalysis) near the graphene surface of the BPU alters its electrical characteristics, resulting in real-time electrical signal output. All of this happens without amplification, which is usually required with optical methods. Because measurements are in real time, kinetics data can also be collected, providing robust insights into the molecular dynamics of DNA, RNA, protein, or any other type of biomolecule.


In 2019, we introduced CRISPR-Chip to the world, a biosensor that combines CRISPR-Cas with the BPU platform to detect target sequences of interest within a genomic DNA context (Figure 1). CRISPR-Chip allows researchers to understand and optimize CRISPR-Cas performance, including gRNA interaction, target recognition, and cleavage.

Figure 1. The CRISPR-Chip contains multiple transistors arranged into

three separate channels. One transistor is magnified to show how a

Cas protein can be linked to the surface of a graphene transistor.

The graphene surface of the BPU is functionalized with pyrenbutyric acid (PBA), which electrostatically interacts with the graphene and can be covalently coupled via carbodiimide crosslinking to any Cas protein. Unfunctionalized areas of the PBA are blocked by coupling to an inert molecule, amino-polyethylene glycol 5-alcohol, that doesn’t interfere with any downstream biochemical reaction or electrical detection.

Following the blocking reaction, gRNA can be introduced, allowing Cas-gRNA RNP formation near the surface of the graphene chip to be measured.Biological activity that occurs near the surface of the graphene results in a current between the drain and source electrodes—a current that may be distinguished from a baseline signal (Figure 1). Finally, additional reagents, such as PCR-amplified target DNA or reaction components, can be added to measure binding interactions or cleavage reactions.


CRISPR-Complete is a workflow that uses the CRISPR-Chip to help optimize CRISPR-Cas designs before embarking on expensive and time-consuming cell-based assays (Figure 2). It also helps rank, order, and prioritize Cas-gRNA candidates, thus derisking cell-based editing assays.

Figure 2. CRISPR-Complete can measure the binding between gRNA and a Cas protein, as well as the binding of Cas-gRNA complexes to PCR-amplified target DNA sequences or unamplified genomic DNA. In addition, CRISPR-Complete can measure the cleavage of target amplicons by Cas-gRNA complexes.

The workflow measures binding between candidate gRNAs and Cas proteins of interest, assesses binding interactions between Cas-gRNA complexes and target amplicons, demonstrates cleavage of Cas-gRNA complexes at target amplicons, and confirms binding of Cas-gRNA complexes to unamplified DNA sequences in a genomic context.

The technology offers insight into which gRNAs to select, which Cas protein to use, and which DNA sequence to target—a cluster of options cannot be deconvoluted using conventional CRISPR-Cas editing workflows or data from cell-based assays. Unlike other in vitro assays, cleavage can also be correlated with detailed gRNA or target DNA binding data and measured sensitively, without amplification and without the reagents or instruments required for optics-based methods.

Figure 3 shows both raw and processed data generated from a representative CRISPR-Complete workflow. This experiment measured the cleavage of a Cas-gRNA complex at target and nontarget amplicons. As various components of our reconstituted Cas-gRNA system are added stepwise, there is a real-time change in the electrical characteristics of the graphene chip (Figure 3A). This data is calibrated to a baseline and processed to generate an I response, which measures the change in current between the baseline and end state (Figure 3B). Triplicate reactions are run on distinct transistors to ensure the validity of the observed results.

A reduced I response is synonymous with amplicon cleavage in this experiment. As shown in Figure 3B, the RNP using gRNA #1 cleaves its target amplicon (purple box) and as expected, does not cleave a nontarget amplicon (orange box).

In the case of gRNA #1, Cas-gRNA complex formation, RNP cleavage at a target amplicon, and discrimination against cleavage at a nontarget amplicon were all validated. If cleavage of the target amplicon was not seen, the upstream steps of RNP formation and target amplicon binding to further optimize or redesign this Cas-gRNA complex could be further investigated.

The platform has been used to assist small and large biotechnology companies in rapidly identifying high-affinity gRNAs, determining target amplicon binding, and comparing cleavage activity across different Cas9 vendors. As demonstrated above, CRISPR-Complete provides biological insights into cleavage efficiency, the upstream process of Cas-gRNA RNP formation, and target DNA binding. These insights enable gRNA optimization for Cas-gRNA complex formation and confirmation of binding to and cleavage of target amplicon sequences.

Figure 3. CRISPR-Complete can detect CIRSPR-Cas function on target and notarget amplicons. (A) Step 1 is where we monitor Cas characteristics. Step 2 is where we introduce gRNA and the target sequence and monitor their direct interaction. Step 3 is where we begin the cleaving process and monitor that activity. (B) The I response was measured by subtracting the I response at step 33 from the I response at step 29 in panel A and plotted in the blue box. Another reaction, gRNA #1 + nontarget amplicon (red box), was tested in parallel and processed similarly.

Kiana Aran, PhD, is the scientific advisor and a board member of CRISPR QC. She is also an associate professor of medical diagnostics and therapeutics at the Keck Graduate Institute.

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