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. 2025 Sep 12;53(17):gkaf907. doi: 10.1093/nar/gkaf907

A NanoLock-enabled, Craspase-based strategy for highly sensitive RNA detection

Yumeng Xiao 1, Junyu Chen 2, Xincan Hou 3, Hongwei Wang 4, Kundi Zhang 5, Sujuan Xu 6, Tao Jiang 7, Yangao Huo 8,✉, Fengyu Zhang 9,✉, Lichuan Gu 10,✉
PMCID: PMC12445650  PMID: 40966498

Abstract

Rapid and sensitive detection of RNA is important in fields such as biomedical research and clinical diagnostics. However, current methods typically involve an amplification process, require substantial time, and are susceptible to aerosol contamination. Herein, we introduce a NanoLock-powered, amplification-free assay based on the type III-E clustered regularly interspaced short palindromic repeats (CRISPR)–CRISPR-associated system for rapid, highly sensitive, and specific RNA diagnostics. This innovative platform, designated CRISPR-guided caspase (Craspase)–NanoLock–Csx30 (CNC), harmoniously integrates the precise protease activity of Craspase with the remarkable luminescent sensitivity of NanoLock, creating a novel and streamlined approach for RNA detection. The CNC platform exhibited exceptional sensitivity in detecting severe acute respiratory syndrome coronavirus-2 N gene RNA through the integration of three guide RNAs, achieving a detection limit of 250 fM in just 10 min without amplification. Preliminary studies further revealed the platform's extended diagnostic potential for detecting influenza A virus and human immunodeficiency virus. These findings collectively establish the CNC platform as an appealing tool for infectious disease detection and significantly broaden the scope of CRISPR-based diagnostic applications.

Graphical Abstract

Graphical Abstract.

Graphical Abstract

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Introduction

A rapid, accurate, and sensitive method for detecting RNA is essential for the early diagnosis of diseases and the effective management of pathogen epidemics [1, 2]. The gold standard, real-time polymerase chain reaction (RT-PCR) has been extensively used clinically to detect low-abundance nucleic acids [3, 4]. However, this method involves an amplification process, requires considerable time and sophisticated instrumentation, and demands technical expertise [5, 6]. Furthermore, there is a risk of aerosol contamination during the process. Consequently, the detection process can only be performed in specialized laboratories by trained professionals, thereby limiting its applicability in point-of-care diagnostics [7, 8]. To address this issue, various isothermal amplification methods have emerged as efficient alternatives to RT-PCR. These methods simplify instrument requirements by eliminating the need for complex thermal cycling and reducing detection time [9–11]. However, these applications are still limited by the complexity of primer design.

Studies of clustered regularly interspaced short palindromic repeats (CRISPR)–CRISPR-associated (Cas) systems have provided new possibilities for nucleic acid detection [12, 13]. The specific binding of a target nucleic acid sequence to the CRISPR–Cas guide RNA triggers the endonuclease activity or secondary messenger production of associated Cas proteins [14]. Several nucleic acid detection methods using CRISPR–Cas systems have been developed and widely implemented, including RNA-activated RNase in the CRISPR–Cas13 systems [15, 16] and DNA-activated DNase in the CRISPR–Cas12 systems [17, 18]. Additionally, the CRISPR–Cas10 systems, featuring RNA-activated DNase and oligoadenylate cyclase, have been modified and used for diagnostic purposes [19–22].

The recently discovered type III-E CRISPR–Cas system exibits unique RNA-activated protease activity [23, 24]. This system is composed of three primary components: Cas7-11 (also known as gRAMP for giant repeat-associated mysterious protein), crRNA, and Csx29. These components collectively form a stable ternary complex known as “Craspase”, which stands for “CRISPR-guided caspase” [25, 26]. Upon binding of the cognate target RNA (CTR) to the crRNA within Cas7-11, the mismatched 3′ anti-tag of the CTR induces a large conformation rearrangement of Csx29 through sequence-non-specific contacts. This rearrangement exposes the protease pocket of Csx29, activates its catalytic activity towards Csx30, and subsequently releases the cytotoxic N-terminal domain of Csx30. This highly specific mechanism ensures that protease activity is initiated exclusively upon accurate and precise recognition of the target RNA [27, 28]. Moreover, Cas7-11–crRNA exhibits minimal cytotoxicity and off-target effects when used as an RNA editing tool in cells, highlighting the potential reliability of Craspase for RNA manipulation.

In the pursuit of high-sensitivity detection, the signal outputs from methods developed using CRISPR–Cas systems hold considerable promise [29]. Both the intensity and the background level of the biomarker are of paramount importance in achieving enhanced sensitivity in biomolecular detection [30, 31]. The newly engineered luciferase, NanoLuc (NLuc), which is derived from the deep-sea shrimp Oplophorus gracilirostris, has emerged as a highly promising bioluminescent reporter, capable of producing ∼150-fold brighter light signals than traditional Firefly luciferase and Renilla luciferase [32–34]. This remarkable performance is attributed to its improved efficiency in converting chemical energy into light, combined with the use of a more stable synthetic substrate, furimazine [32]. These properties make NLuc an ideal reporter for a wide range of detection applications. To fully leverage this powerful reporter, many recent studies have effectively modified it and developed various NLuc-based systems, such as NanoBit, tripart NLuc, and NanoLock, for a range of biological applications [35–38].

Herein, we established an amplification-free RNA detection platform that combined the specific protein cleavage activity of Craspase with the highly sensitive and remarkable luminescent characteristics of NanoLock, designated as the Craspase–NanoLock–Csx30 (CNC) platform. This cost-effective diagnostic platform exhibited exceptional sensitivity and robustness, achieving the detection limit of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) N gene RNA at 250 fM in 10 min, without amplification. Notably, the CNC platform also demonstrated superior diagnostic performance in preliminary evaluations for influenza A virus (IAV) and human immunodeficiency virus (HIV) detection.

Materials and methods

Reagents, strains, and plasmids

T7 RNA polymerase and an NTP mixture were purchased from New England Biolabs (Beijing, China) and Sangon Biotech (Shanghai, China), respectively. Other biochemical reagents were purchased from Sigma-Aldrich (St. Louis, MO, USA).

Two plasmids, pET-Duet-DiCas7-11 (Desulfonema ishimotonii) and pET-28a-DiCsx29, were provided by Professor Tao Jiang at the National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences [28]. Other genes used in this study were synthesized by GenScript (Nanjing, China) before being constructed using the Gibson assembly method [39]. The genes of SmBiT–LgBiT–Csx301–565–HiBiTm (SLCH1–565), SmBiT–LgBiT–Csx30296–565–HiBiTm (SLCH296–565), SmBiT–LgBiT–Csx30363–565–HiBiTm (SLCH363–565), and SmBiT–LgBiT–Csx30396–565–HiBiTm (SLCH396–565) were cloned into a pET-28a vector with an N-terminal 6× His tag. Full-length DiCsx29 was cloned into a modified pET-28a vector with an N-terminal CL7-Sumo tag. The crRNA template was cloned into a pCDF-Duet vector with an upstream T7 promoter. The corresponding sequences above are listed in Supplementary Tables S1 and S2. The N genes of seven coronaviruses are shown in Supplementary Table S3, and all strains, plasmids, and primers are detailed in Supplementary Table S4.

Protein expression and purification

For DiCraspase expression, the three plasmids pET-Duet-DiCas7-11, pCDF-Duet-crRNA, and pET-28a-CL7-Sumo-DiCsx29 were transformed into expression strain Escherichia coli BL21(DE3). The expression strain was cultured at 37°C in Luria–Bertani medium (5 g of yeast extract, 10 g of tryptone, and 10 g of NaCl) with a final concentration of 100 μg/ml ampicillin, 100 μg/ml streptomycin, and 100 μg/ml kanamycin. When the optical density at 600 nm reached 0.6, the temperature was lowered to 18°C, and a final concentration of 0.3 mM isopropyl-β-d-1-thiogalactopyranoside was added for overnight expression. Cells were collected, resuspended in lysis buffer (25 mM Tris–HCl pH 7.5, 300 mM NaCl, and 5% glycerol) and lysed using a high-pressure homogenizer at 4°C. After centrifugation at 28 500 × g for 50 min, the supernatant was loaded onto the Im7 column (Biortus Biosciences, Wuxi, China) for purification. The DiCraspase complex was digested by CL7-ULP1 (purified in our laboratory) for 30 min before being eluted by the lysis buffer. The sample was subsequently loaded onto a heparin column (GE Healthcare), where the bound protein was eluted using a linear gradient of 0–100% elution buffer consisting of 25 mM Tris–HCl (pH 7.5) and 1 M NaCl. The peak fractions were then collected and pooled. For final purification, the DiCraspase complex was subjected to size-exclusion chromatography using Superdex 200 (GE Healthcare) and eluted with a buffer consisting of 25 mM Tris–HCl (pH 7.5) and 150 mM NaCl.

Four SLCHs were expressed under the same conditions as DiCraspase. For SLCH purification, the supernatant was loaded onto an Ni-NTA column (GE Healthcare, Pittsburgh, PA, USA) and the bound protein was eluted with an elution buffer (25 mM Tris–HCl pH 7.5, 300 mM NaCl, and 250 mM imidazole) and dialyzed against SD buffer (10 mM Tris–HCl pH 7.5, 300 mM NaCl, and 10% glycerol).

Protein purity was examined using 15% (w/v) sodium dodecylsulfate–polyacrylamide gel electrophoresis (SDS–PAGE), and protein concentration was quantified using the Bradford assay (Beyotime, Shanghai, China). The DiCraspase and SLCHs were finally concentrated, aliquoted, and stored at −80°C.

Detection of the CNC platform using SDS–PAGE

The CTR (with a mismatched 3′ anti-tag) and non-cognate target RNA (NTR; with a matched 3′ anti-tag) were synthesized by Sangon Biotech (Sangon, Shanghai, China) and were dissolved in RNA-free H2O. The purified 6 μM SLCH was incubated with 50 nM DiCraspase and CTR/NTR in a reaction buffer [25 mM Tris–HCl pH 7.5, 300 mM NaCl, 100 mM EDTA, and 1 mM dithiothreitol (DTT)] at 37°C for 20 min. The reaction was stopped by adding 2× loading buffer (100 mM Tris–HCl pH 6.8, 200 mM DTT, 4% SDS, 0.2% Bromophenol Blue, and 20% glycerol) before conducting the analysis using 15% (w/v) SDS–PAGE.

Real-time detection of the CNC platform through luminescence

The entire reaction process was continuously monitored using a microplate reader at 460 nm (BioTek, SynergyMx, VT, USA). For each measurement, 100 pM SLCH and 50 nM DiCraspase were mixed in the reaction buffer for a one-pot reaction. After adding RNA to be tested, 45 μl of the sample was promptly transferred into a 96-well white microplate (SPL, Korea) that had previously been supplemented with an equal volume of 40 μM furimazine substrate (TargetMol, Shanghai, China). The scan was performed at 37°C for 30 min, with readings taken at 1 min intervals.

Sensitivity analysis of the CNC platform

The RNA to be tested was diluted in a gradient using RNA-free H2O and was stored at −20°C for later use. The sample without RNA served as the blank control. Nasal and throat swabs were collected from healthy volunteers following standardized protocols from the Centers for Disease Control and Prevention (CDC). The swabs were processed in 20 mM Tris–HCl (pH 7.5) containing 300 mM NaCl, 100 mM EDTA, 20 U of RNase inhibitor, 100 mM DTT, and 1% Triton X-100. For saliva assays, samples were diluted to 10% (v/v) in the same buffer and heat-denatured at 95°C for 5 min. After buffer preparation, 100 pM SLCH, 50 nM DiCraspase, and varying concentrations of target RNA were spiked into the solutions immediately, and the assay was conducted as described above.

In vitro transcription assays

DNA templates of seven coronaviruses [SARS-CoV-2, SARS-CoV, Middle Eastern respiratory syndrome coronavirus (MERS-CoV), human coronavirus (HCoV)-229E HCoV-OC43, HCoV-NL63, and HCoV-HKU1] were amplified from pET-29b plasmids using PCR with Phusion High-Fidelity DNA polymerase (New England Biolabs, Ipswich, MA, USA). The mutated SARS-CoV-2 N genes were generated using the QuikChange method [40]. After amplification, PCR products were purified using a Plasmid Mini Kit (Omega, USA), and their concentrations were determined using a Nanodrop spectrophotometer (Biofuture, K5600, Beijing, China).

For in vitro transcription (IVT) assays [41], 30 nM DNA template, 200 nM T7 RNA polymerase, and 500 μM NTP mixture were mixed in a transcription buffer (40 mM Tris–HCl pH 7.5, 30 mM MgCl2, 2.5 mM DTT, and 5% glycerol). Transcription processes were performed at 37°C for ∼1 h.

RNA purification and spectrophotometry

After IVT, the mRNA products were purified using the MiniBEST Universal RNA Extraction Kit (TaKaRa, Dalian, China) according to the manufacturer's instructions. To calculate the RNA concentration, we diluted 200-fold purified RNA in a TE buffer (10 mM Tris–HCl pH 8.0, and 1 mM EDTA) and used a spectrophotometer (METASH, UV-6000PC, Shanghai, China) to determine the absorbance of optical density at 260 nm. RNA concentration (μg/μl) = OD260 × dilution factor × 40/1000.

Specificity analysis of the CNC platform

The transcribed RNA of seven coronaviruses (SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV-OC43, HCoV-HKU1, HCoV-229E, and HCoV-NL63) was diluted to a final concentration of 50 pM with RNA-free H2O. The SLCH cleavage assays were conducted as previously described.

Results

Design of the CNC platform for RNA detection

Various approaches using the CRISPR–Cas system have consistently led to breakthroughs in gene manipulation, providing new perspectives on nucleic acid detection [31, 42]. As a newly discovered system, the effector of the type III-E CRISPR–Cas system, namely Craspase, exhibits unique RNA-activated protease activity. The protease activity of Csx29 within the Craspase complex is triggered by the 3′ anti-tag of the CTR, resulting in the specific cleavage of its substrate Csx30 [24]. This particular characteristic led us to explore its potential for nucleic acid detection.

Our approach is inspired by the exceptional research on NanoLock conducted by Li et al. [38]. NanoLock, ingeniously modified from NLuc, consists of a high-affinity but non-functional inhibitory peptide (HiBiTm), a large fragment of NLuc (LgBiT), a caspase cleavage sequence, and a low-affinity yet functional agonist peptide (SmBiT). This system operates in a dark-to-bright mechanism used for detecting caspase activity. Based on this concept, we developed a sensitive sensor named SmBiT–LgBiT–Csx30–HiBiTm (SLCH) by integrating the DiCraspase substrate DiCsx30 into the NanoLock framework (Supplementary Fig. S1). In the absence of the CTR, DiCraspase remains inactive and does not cleave DiCsx30 within the SLCH. Consequently, the HiBiTm peptide predominantly binds to LgBiT, resulting in a non-functional luciferase and a negative result, even in the presence of the substrate furimazine. In contrast, when the CTR is present, the protease activity of DiCraspase is activated. DiCraspase cleaves the DiCsx30 within the SLCH and releases the inhibitory peptide HiBiTm from LgBiT. Subsequently, the SmBiT peptide binds to LgBiT to form a functional luciferase. This enzymatic complex catalyzes the conversion of furimazine into furimamide, accompanied by the emission of light energy, leading to a positive result (Fig. 1).

Figure 1.

Figure 1.

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Principle and operation for RNA detection using the CNC platform.

A minimal mismatch of four nucleotides to the 5′ handle and minimal matching of the first 12 nucleotides to the spacer of the crRNA by the CTR are essential for triggering the protease activity of DiCraspase toward DiCsx30, as indicated by a previous study [28]. Therefore, we designed a crRNA-1 that specifically targets the SARS-CoV-2 N gene sequence (CTR1 SARS-CoV-2, located at nucleic acid position 28 559–28 599 within the genome) (Fig. 2A; Supplementary Table S2). Additionally, an NTR was designed based on the aforementioned crRNA-1 to serve as a negative control, namely NTR1 SARS-CoV-2 (Fig. 2B; Supplementary Table S2). Subsequently, we co-expressed DiCas7-11, crRNA-1, and DiCsx29 in E. coli and purified a stable DiCraspase-1 (Fig. 2C).

Figure 2.

Figure 2.

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CNC platform for detecting the CTR1 SARS-CoV-2. (A) Schematic representation of the designed crRNA-1/CTR1 SARS-CoV-2 pairs specific to the SARS-CoV-2 N gene. (B) Schematic representation of the designed crRNA-1/NTR1 SARS-CoV-2 pairs. (C) Plasmid construction and purification of the DiCraspase-1 complex. Ce, whole-cell lysate; S, supernatant; Fl, flow through; W, wash; Elu, elution. (D) SDS–PAGE analysis of the CNC platform, using CTR1 SARS-CoV-2 and NTR1 SARS-CoV-2. (E) Luminescence signals for CTR1 SARS-CoV-2 and NTR1 SARS-CoV-2 were obtained at a concentration of 50 pM. CTR1 SARS-CoV-2, cognate target RNA with a mismatched 3′ anti-tag; NTR1 SARS-CoV-2, non-cognate target RNA with a matched 3′ anti-tag. The values shown represent the mean ± standard deviation (SD) of the results obtained from three independent experiments.

Regarding the construction of the substrate SLCH, we tested four SLCHs with the full-length sequence (residues 1–565) and three specific fragments (residues 296–565, 363–565, and 396–565) of DiCsx30 according to the study by Strecker et al. [43]. Only two of the four proteins, SmBiT–LgBiT–DiCsx30363–565–HiBiTm (SLCH363–565) and SmBiT–LgBiT–DiCsx30396–565–HiBiTm (SLCH396–565), were successfully purified, whereas the other two were insoluble, possibly due to incorrect folding (Supplementary Fig. S2). SLCH396–565 exhibited the highest yield and was selected for the subsequent RNA detection experiment. As expected, the substrate SLCH396–565 was effectively cleaved by DiCraspase-1 in the presence of CTR1 SARS-CoV-2, but not NTR1 SARS-CoV-2, as confirmed using SDS–PAGE (Fig. 2D). There was a notable surge in luminescence intensity in the presence of CTR1 SARS-CoV-2 using a microplate reader at 460 nm (Fig. 2E). Conversely, NTR1 SARS-CoV-2 failed to trigger the protease activity of DiCraspase-1 to cleave the substrate SLCH396–565 for generating a detectable luminescence signal (Fig. 2E). These findings suggested that the CNC platform could be further optimized for RNA detection.

Optimal operating conditions of the detection platform

To obtain the optimal reaction conditions of the CNC platform, we tested the temperature, pH value, and the concentration of DiCraspase-1 and SLCH396–565. The temperature range tested was from 20°C to 55°C, while the pH range tested was from 5.5 to 8.0. The CNC platform exhibited peak performance at a temperature of ∼37°C (Fig. 3A), where the enzyme activity was most efficient. In the determination of the optimal pH value, we observed a distinct enhancement in the performance of the system when the pH was set at 7.5 (Fig. 3B). The concentrations of DiCraspase-1 and the substrate SLCH396–565, as well as the composition of the reaction buffer were critical determinants for the signal-to-noise ratio of this platform. Therefore, we conducted a comprehensive analysis of their effects on the CNC platform. The data analysis indicated that the optimal concentrations for DiCraspase-1 and the substrate SLCH396–565 were 50 nM and 100 pM, respectively (Fig. 3C, D). Furthermore, the CNC platform showed a wide tolerance for different buffers (Supplementary Table S5; Supplementary Fig. S3). These optimized parameters were adopted for performing the subsequent experiments.

Figure 3.

Figure 3.

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Optimization of the CNC platform for detection of CTR1 SARS-CoV-2 . (A and B) Effects of temperature (A) and pH values (B) on the CNC platform. CTR1 SARS-CoV-2 to be detected was added at a concentration of 50 pM in the reactions. The signal was generated using a microplate reader at 10 min. Activities at 37°C (A) and pH 7.5 (B) were set at 100%. (C and D) Influence of DiCraspase-1 enzyme concentration (C) and substrate SLCH396–565 concentration (D) on the efficacy of the CNC platform. CTR1 SARS-CoV-2 to be detected was added at a concentration of 50 pM in the reactions. The signal was generated using a microplate reader at 10 min, under conditions of 37°C and pH 7.5. Blank refers to reactions without RNA. The blue star marks the optimal reaction temperature, pH, and protein concentrations (DiCraspase-1 and SLCH396–565) used in the experiment. The measurements were performed in triplicate, with the error bars representing the SDs.

Sensitivity analysis of the CNC platform

Under the optimal conditions, we tested the sensitivity of the CNC platform. We explored its response to various CTR1 SARS-CoV-2 concentrations using a microplate reader. As shown in Fig. 4A, the platform produced real-time luminescence signals when CTR1 SARS-CoV-2 concentrations exceeded a specific threshold, while no signal was detected in the control group that lacked CTR1 ARS-CoV-2. Notably, the CNC platform generated clearly detectable luminescence signals within 10 min of reaction. Given this rapid response, we established 10 min as the optimal detection time point. Comparative analysis against the control with no RNA revealed that the platform achieved a detection sensitivity of 2.5 pM (Fig. 4B). Next, we transcribed the SARS-CoV-2 N gene RNA (namely RNAN SARS-CoV-2) through IVT techniques (Supplementary Fig. S4A) to assess the sensitivity. The results indicated that the sensitivity remained at 2.5 pM when using the RNAN SARS-CoV-2 for detection (Supplementary Fig. S4B, C).

Figure 4.

Figure 4.

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Sensitivity analysis of the CNC platform. (A) Luminescence signal intensity of the CNC platform at different concentrations of CTR1 SARS-CoV-2. (B) Luminescence signal intensity generated by different concentrations of CTR1 SARS-CoV-2 in (A) at 10 min. (C) Schematic representation of the SARS-CoV-2 N gene, and the relative positions of the CTR (1), CTR (2), and CTR (3) regions. (D) Luminescence signal intensity was measured for the combination of three DiCraspases (with a total DiCraspase concentration of 50 nM per reaction) in response to varying concentrations of RNAN SARS-CoV-2. (E) Luminescence signal intensity generated by different concentrations of RNAN SARS-CoV-2 in (D) at 10 min. NTC, no target control. The measurements were performed in triplicate. The error bars represent the SDs. The statistical analysis was performed using a t-test. Statistical significance was defined as follows: ns (not significant) for P > 0.05, * forP ≤ 0.05, **P for ≤ 0.01, ***P for ≤ 0.001, and **** for P ≤ 0.0001.

A previous study reported that the combination of multiple crRNAs targeting distinct regions of the target RNA could enhance CRISPR activation and improve detection sensitivity [44]. Therefore, in addition to the above tested region, we chose another two regions of the SARS-CoV-2 N gene (located at nucleic acid positions 28 688–28 728 and 28 921–28 961 within the genome) (Fig. 4C; Supplementary Fig. S5) and purified the corresponding DiCraspases bearing the designed crRNA for further evaluation (DiCraspase-2 and DiCraspase-3) (Supplementary Fig. S6). First, we assessed the detection limit for RNAN SARS-CoV-2 using DiCraspase-2 and DiCraspase-3 independently, both of which exhibited a consistent sensitivity of 2.5 pM (Supplementary Fig. S7). Then, we combined our three DiCraspases in equal amounts while keeping the total protein concentration the same as the single DiCraspase-1 and tested its detection limit for RNAN SARS-CoV-2. Notably, the result showed that the combination of three DiCraspases significantly enhanced the detection sensitivity, achieving a detection limit of 250 fM (Fig. 4D, E). Compared with CRISPR–Cas-based nuclease detection systems (Supplementary Table S6), our CNC platform offered an innovative strategy by effectively integrating protease activity with luminescence detection, enabling fM-level RNA detection without amplification in just 10 min. Additionally, the SLCH396–565 substrate provided distinct advantages in terms of ease of production and cost efficiency.

Analysis of specificity and anti-interference capability of the CNC platform

To evaluate the system's sequence specificity, we prepared the RNAN SARS-CoV-2 variants containing single-point or double-point mutations mismatched to crRNA of DiCraspase-1 using IVT, and assessed the protease activity of DiCraspase-1 towards these RNAN SARS-CoV-2 variants (Supplementary Fig. S8). The results demonstrated that single-point mutations at positions 20–22 and double-point mutations spanning positions 13–22 mismatched to crRNA of DiCraspase-1 significantly reduced the CNC platform's detection capability (Supplementary Fig. S9A, B).

Furthermore, we evaluated the detection specificity for other RNA viruses, namely SARS-CoV-2, SARS-CoV, MERS-CoV, HCoV-OC43, HCoV-HKU1, HCoV-229E, and HCoV-NL63. As shown in Fig. 5A, a distinct and intense cleavage band for SLCH396–565 was observed on SDS–PAGE only in the presence of the RNAN SARS-CoV-2, indicating no cross-reactivity with other coronavirus RNAs. Moreover, real-time luminescence scanning also showed the same specificity of the CNC platform (Fig. 5B).

Figure 5.

Figure 5.

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Specificity and anti-interference of the CNC platform. (A and B) SDS–PAGE analysis (A) and luminescence signal intensity scanning analysis (B) of the cleavage of SLCH396–565 mediated by the N gene RNA from seven coronaviruses. The RNA concentrations were 1 nM in (A) and 50 pM in (B). (C) Influence of unspecific RNA on the CNC platform. Detection efficiency without unspecific RNAs was set as 100%. RNAN SARS-CoV-2 to be detected was used at a concentration of 10 pM in these reactions, while unspecific RNA was used at concentrations of 500 pM, 1 nM, and 2 nM. (D–F) The detection sensitivity of the CNC platform in response to varying concentrations of RNAN SARS-CoV-2 in the presence of nasal swabs (D), throat swabs (E), and 10% saliva (F). The values represent the mean ± SD of the results obtained from three independent experiments. The data collection and analysis were conducted at 10 min. The statistical analysis was performed using a t-test. Statistical significance was defined as follows: ns (not significant) for P > 0.05, * for P ≤ 0.05, ** for P ≤ 0.01, *** for P ≤ 0.001, and **** for P ≤ 0.0001.

In clinical testing, samples collected from individuals typically consist of complex components, resulting in the target RNA accounting for only a tiny fraction of the total RNA. Additionally, human tissues comprise diverse components that can potentially interfere with detection. Therefore, ensuring that the detection system is sufficiently robust to resist such interference is crucial.

The tolerance of the CNC platform to non-specific RNAs was assessed by introducing different proportions of an unspecific RNA sample. The result showed that our system maintained an 80% efficiency rate, with the RNAN SARS-CoV-2 accounting for 0.5% mol/mol of the total sample (Fig. 5C). Additionally, to test the potential impact of contaminants commonly present in clinical samples, we dissolved the RNAN SARS-CoV-2 in nasal swab and throat swab samples, as well as in 10% saliva collected from healthy individuals, and tested the detection sensitivity under these conditions. As shown in Fig. 5D–F, a consistent detection limit of 250 fM was maintained across all tested media. These results confirmed the anti-interference capability of the CNC platform, suggesting its effectiveness in overcoming potential interference from the components of real samples.

Extension of the CNC platform for the detection of other RNA viruses

Upon the remarkable success of the CNC platform in SARS-CoV-2 detection, we sought to investigate its potential applicability for the detection of other RNA viruses. To systematically evaluate the versatility and sensitivity of the CNC platform, we selected IAV and HIV for detection [45, 46]. Specifically, we selected the conserved regions within the nucleocapsid (NP) gene of the IAV genome and the gag gene of the HIV genome and designed the corresponding CTR and crRNA (Supplementary Table S2; Supplementary Fig. S10).

The results demonstrated that the CNC platform exhibited exceptional sensitivity in detecting CTRIAV and CTRHIV, achieving a remarkable detection limit of 1 pM (Fig. 6A, B) and 2.5 pM (Fig. 6C, D), respectively. These results substantially validated the platform's applicability beyond SARS-CoV-2 detection, positioning it as a highly promising candidate for developing advanced RNA diagnostic tools.

Figure 6.

Figure 6.

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CNC platform for the detection of IAV and HIV. (A) Luminescence signal intensity of the CNC platform on different concentrations of CTRIAV. (B) Luminescence signal intensity generated by different concentrations of CTRIAV in (A) at 10 min. (C) Luminescence signal intensity of the CNC platform on different concentrations of CTRHIV. (D) Luminescence signal intensity generated by different concentrations of CTRHIV in (C) at 10 min. NTC, no target control. The measurements were performed in triplicate. The error bars represent the SDs. The statistical analysis was performed using a t-test. Statistical significance was defined as follows: ns (not significant) for P > 0.05, * for P ≤ 0.05, ** for P ≤ 0.01, *** for P ≤ 0.001, and ****for P ≤ 0.0001.

Discussion

CRISPR–Cas systems are a cutting-edge technology with inherent sensitivity, specificity, flexibility, and user-friendly operation properties. Some CRISPR–Cas systems and their orthologous proteins, such as Cas12 and Cas13, have contributed to advancing CRISPR–Cas-based diagnostic approaches, primarily based on the nuclease function of CRISPR effectors targeting nucleic acid reporters [15, 17]. Recently, a novel type III-E CRISPR–Cas system was discovered, which encodes an RNA-activated protease effector named Craspase [25]. When target RNA with a mismatched 3′ anti-tag binds to Craspase, the protease activity of Csx29 in the Craspase was activated, and its substrate Csx30 was cleaved at a specific site by Csx29 [24]. This CRISPR-linked proteolytic mechanism enables the development of novel platforms through modified Csx30 protein constructs, expanding the potential applications of CRISPR–Cas systems in diagnostics.

Herein, we combined the precise protein cleavage capabilities of the type III-E CRISPR–Cas effector Craspase with the exceptionally sensitive luminescent characteristics of NanoLock to establish a novel platform for RNA-specific detection. Our innovative CNC platform demonstrated exceptional sensitivity for the SARS-CoV-2 N gene, achieving a detection limit of 250 fM in 10 min, without amplification. Compared with previous studies utilizing the nuclease activity of CRISPR–Cas systems, our study provided a new RNA detection method that demonstrated significant cost efficiency advantages through the use of highly sensitive SLCH396–565 as a signal reporter, enabling real-time nucleic acid detection.

Additionally, the platform's exceptional specificity enabled precise discrimination between SARS-CoV-2 and other coronavirus RNAs, while maintaining consistent performance even in the presence of potential interfering substances. Furthermore, preliminary evaluations have demonstrated the platform's superior diagnostic capabilities in detecting IAV and HIV, showcasing its versatile application potential for developing advanced RNA diagnostic tools.

Overall, amplification-free approaches offer significant advantages, including reduced contamination risks and simplified workflow requirements. However, their current sensitivity remains lower than amplification-based methods. To address this limitation, future research will focus on enhancing sensitivity by combining efficient crRNAs, developing immobilization systems, using upgraded detection devices, and utilizing more effective Craspase orthologs.

Supplementary Material

gkaf907_Supplemental_File
gkaf907_supplemental_file.pdf (1.6MB, pdf)

Acknowledgements

Author contributions: Yumeng Xiao (Formal analysis [lead], Investigation [lead], Validation [lead], Writing – original draft [lead], Writing – review & editing [lead]), Junyu Chen (Investigation [supporting]), Xincan Hou (Investigation [supporting]), Hongwei Wang (Visualization [supporting]), Kundi Zhang (Formal analysis [supporting]), Sujuan Xu (Writing – review & editing [supporting]), Tao Jiang (Methodology [supporting], Supervision [supporting]), Yangao Huo (Formal analysis [supporting], Funding acquisition [supporting], Methodology [supporting], Supervision [supporting], Writing – review & editing [supporting]), Fengyu Zhang (Funding acquisition [supporting], Investigation [supporting], Supervision [supporting], Writing – review & editing [supporting]), Lichuan Gu (Conceptualization [lead], Formal analysis [lead], Funding acquisition [lead], Methodology [lead], Project administration [lead], Supervision [lead], Writing – review & editing [lead]).

Contributor Information

Yumeng Xiao, State Key Laboratory of Microbial Technology, Shandong University, 72 Binhai Road, Qingdao 266237, China.

Junyu Chen, State Key Laboratory of Microbial Technology, Shandong University, 72 Binhai Road, Qingdao 266237, China.

Xincan Hou, State Key Laboratory of Microbial Technology, Shandong University, 72 Binhai Road, Qingdao 266237, China.

Hongwei Wang, State Key Laboratory of Microbial Technology, Shandong University, 72 Binhai Road, Qingdao 266237, China.

Kundi Zhang, State Key Laboratory of Microbial Technology, Shandong University, 72 Binhai Road, Qingdao 266237, China.

Sujuan Xu, State Key Laboratory of Microbial Technology, Shandong University, 72 Binhai Road, Qingdao 266237, China.

Tao Jiang, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing 100101, China.

Yangao Huo, National Laboratory of Macromolecules, Institute of Biophysics, Chinese Academy of Sciences, 15 Datun Road, Beijing 100101, China.

Fengyu Zhang, State Key Laboratory of Microbial Technology, Shandong University, 72 Binhai Road, Qingdao 266237, China.

Lichuan Gu, State Key Laboratory of Microbial Technology, Shandong University, 72 Binhai Road, Qingdao 266237, China.

Supplementary data

Supplementary data are available at NAR online.

Conflict of interest

The authors have filed a patent application for the utilization of the CNC platform for RNA detection.

Funding

The Key Technologies Research and Development Program (CN) [2024YFC27007400]; the Key Technology Research and Development Program of Shandong Province [2020CXGC011305]; the National Natural Science Foundation of China [32371276 and 32400148]; Instrument Improvement Funds of Shandong University Public Technology Platform [ts20220107]; and Strategic Priority Research Program of the Chinese Academy of Sciences [XDB37010301].

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

gkaf907_Supplemental_File
gkaf907_supplemental_file.pdf (1.6MB, pdf)

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Articles from Nucleic Acids Research are provided here courtesy of Oxford University Press

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