Skip to main content
NCBI home page
Poultry Science logoLink to Poultry Science
. 2025 May 1;104(8):105241. doi: 10.1016/j.psj.2025.105241

Detection method for identifying duck hepatitis A virus 3 virulent and attenuated strains based on RPA CRISPR single-base recognition system

Lei Chen a,1, Qiaoli Zhang a,1, Wenbo Sun b, Michael G Mauk c, Qingmei Li d,⁎
PMCID: PMC12149595  PMID: 40398301

Abstract

Duck viral hepatitis is very common in China, causing significant impact and economic losses to the duck farming industry. Currently, DHAV-3 has become the main factor causing duck viral hepatitis in China. However, the existing DHAV-3 vaccines cannot completely rule out the potential risk of the vaccine strain becoming more virulent. Due to the high similarity in genomic sequences between wild strains and vaccine strains (with only a few base differences), traditional detection methods struggle to accurately differentiate them, severely interfering with disease control decisions. Therefore, simultaneously detecting both the virulent strain and the attenuated strain of DHAV-3 is crucial for evaluating vaccine efficacy, monitoring virus mutations, and optimizing control strategies. This study, using the DHAV-3 SD70 attenuated strain as an example, developed a highly sensitive and rapid detection method to identify and distinguish between the DHAV-3 virulent and SD70 attenuated strains, providing a new strategy for identifying both strains. Currently, there are no literature reports on the detection methods for the two strains. Therefore, we propose a single-base recognition system strategy based on RPA-CRISPR. DHAV-3 virulent and attenuated strains were specifically identified by this method based on only a few different base sequences. This method can detect two target genes as low as 10° copy/μL within 35 min. In addition, when this method was used for samples analysis, the results of this method, sequencing results, and the results provided by the company were compared and found to be consistent. This method has the advantages of fast speed, simple operation, high specificity and sensitivity, which can be used for the detection of DHAV-3 virulence strain and SD70 attenuated strain, and lays a technical foundation for disease control, vaccine evaluation and mutation monitoring.

Keywords: DHAV-3 virulent and attenuated strains, RPA-CRISPR, Single-base recognition

Introduction

Duck viral hepatitis (DVH) is an acute, highly lethal, and infectious duck disease characterized by hemorrhagic liver disease, often accompanied by neurological symptoms (Geller et al., 2019; Hu et al., 2016; Lin et al., 2015; Niu et al., 2019). Duck hepatitis A virus (DHAV), a member of Avihepatovirus in the family Picornaviridae, has been widely present in duck farms since it been isolated in China (Zhao et al., 2024; Zhou et al., 2022). There are reports that the infection rate of DHAV-3 exceeds that of DHAV-1, making it the primary factor causing DHAV infection in China (Fu et al., 2024; Wen et al., 2019; Wen et al., 2018). The wide spread of DHAV-3 has reduced duck production and caused huge economic losses to duck farms. The extensive vaccination of live attenuated vaccines is the main means of prevention and control at present, but the phenomenon of vaccine strains' virulence returning to strength or wild strains breaking through the immune protection occurs from time to time (Kang et al., 2018; Wu et al., 2020; Ye et al., 2023). Although the SD70 candidate vaccine developed in 2020 showed good preventive effects, there are only 24 nucleotide differences in its genome compared to the parental virulence strain, distributed in the coding regions of VP1, 2C, and 2A2 proteins, which may pose a risk of virulence recovery (Jakubiec and Jupin, 2007; Wu et al., 2020). In addition, the antigenic differences between attenuated strains and prevalent wild strains may weaken the efficacy of immune protection (Kim et al., 2009), and when vaccine strains are co infected with virulent strains, clinical medication decisions and vaccine efficacy evaluations face difficulties due to the lack of specific identification techniques (Shawki et al., 2024).

It was found that two strains have highly similar sequences, with only a few different bases. This poses a huge challenge for accurately identifying virulent and attenuated strains. Given that there are only a few base differences between virulence and attenuated strains, traditional detection methods such as virus culture, ELISA, polymerase chain reaction (PCR) could not distinguish the different bases between two strains. At present, there are no literature reports on the detection methods of DHAV-3 virulent and attenuated strains. In this context, the CRISPR Cas (clustered regularly spaced short palindromic repeat sequences and their related proteins) system, as an emerging gene editing and detection technology (Gootenberg et al., 2018; Gootenberg et al., 2017; Liu et al., 2022), provides the possibility for precise identification of DHAV-3 virulence and attenuated strains with its excellent single base recognition ability. The CRISPR Cas system can specifically target and recognize individual base changes in target DNA/RNA sequences (Liu et al., 2023; Wang et al., 2023), which enables it to accurately identify target genes in highly similar sequence backgrounds, thus achieving effective identification between DHAV-3 virulence strains and attenuated strains (van Dongen et al., 2020). However, when there are trace amounts of target gene in the sample, relying solely on CRISPR technology may not accurately detect the target (He et al., 2023). Therefore, the application of amplification technology is crucial for improving the detection sensitivity of CRISPR biosensors. At present, many reports have combined isothermal amplification techniques such as RPA (recombinase polymerase amplification) or LAMP (loop mediated isothermal amplification) with CRISPR, which not only avoids false positive results caused by non-specific amplification, but also significantly improves specificity and sensitivity (K. Zhang et al., 2024; Zhang et al., 2024). This is of great significance for timely detection of pathogens and control of transmission in the early stages of infection.

Here, we proposed a single-base recognition system strategy based on RPA CRISPR for identifying DHAV-3 virulent and attenuated strains. By comparing the virulent strain of DHAV-3 with the sequences of attenuated strain, the 2C gene was ultimately selected as the specific gene for identifying the two strains. Using conventional primers to amplify the 2C gene of vaccine strains, the product is recognized by Cas12a-crRNA, thereby activating the trans-cleavage activity of Cas12a protein and cleaving the ssDNA probe. Similarly, amplifying the 2C gene of wild-type strains with T7-labeled primers results in the product being recognized by Cas13a-crRNA, which cleaves the ssRNA probe and generates a fluorescent signal. This method can rapidly identify the virulent and attenuated strains of DHAV-3 in diseased duck samples, providing technical support and reliable on-site detection methods for the rapid identification and diagnosis of virulent and attenuated DHAV-3 strains.

Materials and methods

Strains and plasmids preparation

All strains, including DHAV-3 virulent and attenuated strains, DHAV-1, Riemerella anatipestifer 1 (RA-1), Riemerella anatipestifer 2 (RA-2), and Novel duck reovirus (NDRV), were collected from Shandong Hekangyuan Group Co., Ltd. The recombinant plasmid pCE3-DHAV-3 virulent and pCE3-DHAV-3 attenuated were constructed. The concentration of the recombinant plasmid was 500 ng/μL, and the corresponding copy number was 1.0 × 1012. It was used as the standard experimental group of RPA-CRISPR single base recognition system.

Design and optimization of primers and crRNAs

All the sequences were obtained from the NCBI database (http://www.ncbi.nlm.nih.gov/). We selected DHAV-3 virulent strains and SD70 attenuated strain that were prevalent and isolated in China, and compared the sequences between DHAV-3 virulent and attenuated strains in the region using NCBI Blast from NCBI GenBank. Firstly, the targets were screened and CRISPR Cas12a/Cas13a experiments were conducted using sequences with differences in 2A2, 2C, and VP1 bases between virulent and attenuated strains as targets. Based on this, we designed RPA specific primers and crRNAs to identify DHAV-3 strains and differentiate between virulence and attenuated strains, and the sequences were shown in supplementary material Table S1.

Establishment of RPA-CRISPR single-base recognition system

The detection method consists of RPA amplification and CRISPR cas12a/cas13a detection. And the whole process was carried out in a centrifuge tube. Firstly, based on the screened crRNA, the optimal concentration ratio of Cas protein to crRNA was determined. Next, a RPA volume gradient of 50 μL-12.5 μL was established to optimize the reaction. Finally, the optimal reaction times for RPA and CRISPR were screened separately.

Specificity and sensitivity analysis

DHAV-1, NDRV, RA-1, and RA-2 were evaluated using DHAV-3 virulent and attenuated strains as controls, and blank controls were added to test the specificity of the method. In sensitivity experiments, the solution was diluted in EB buffer to concentrations ranging from 104-0.5 copies/μL.

Samples detection

To determine and validate the usability of the method, 30 identified samples were provided by Shandong Hekangyuan Group Co., Ltd (Table S2). The samples were tested using RPA-CRISPR single-base recognition system and compared the results with the sequencing results of the samples.

Results

Principle of the RPA-CRISPR single-base recognition system

This study adopted a fast and convenient RPA-CRISPR Cas12a/Cas13a single-base recognition system to identify DHAV-3 virulent and attenuated strains. DHAV-3 attenuated strain had a high sequence homology with the virulent strain. Therefore, specific RPA primers and crRNAs were designed and screened from a region with significant nucleotide sequence differences. The 2C gene of attenuated strain was amplified using conventional primers, and the product was recognized by Cas12a-crRNA, thereby activating Cas12a protein to cleave ssDNA probe activity. Similarly, the 2C gene of virulent strain was amplified by primers labeled with T7 and its product was recognized by Cas13a-crRNA, allowing Cas13a to cleave the ssRNA probe and generate a fluorescent signal. This method enables the reaction to be carried out in one tube, avoiding false positive results caused by aerosol contamination.

Design and construction of RPA-CRISPR single-base recognition system

The RPA-CRISPR single-base recognition system was composed of dual RPA amplification and CRISPR detection, and the optimal reaction system and reaction program for this detection method were determined. We designed specific crRNAs for the 2A2, 2C, and VP1 gene mutation regions for experiments. The results are shown in the Figs. 1, 2, and it was found that crRNAs in the VP1 and 2A2 regions cannot accurately distinguish between virulent and attenuated strains. Therefore, we chose the 2C gene as the target gene to distinguish between the two. The efficiency of RPA amplification played a crucial role in detection, and three pairs of RPA specific primers were designed according to the requirements. Based on the experimental results, the FR2 and T7-FR3 combination was selected for their superior performance (Fig. 3A and B). Considering the high sequence similarity between attenuated and virulent strains, we designed three crRNAs for the 2C gene sequences of the two strains (Fig. 3C). The most 12a-crRNA-2 and 13a-crRNA-2 were selected as the best crRNAs for subsequent experiments (Fig. 3D and E).To ensure the non-interference between the CRISPR Cas12a and Cas13a systems, the orthogonal anti-cleavage activities of Cas12a and Cas13a were verified. As the results shown in Fig. 3F and G, indicated that the probes of both systems were specific.

Fig. 1.

Fig 1

Open in a new tab

Schematic of RPA-CRISPR single-base recognition system. The dual RPA method was used to amplify two target genes. Target activated Cas12a/Cas13a can induce fluorescence emission of two colors through orthogonal cleavage of DNA and RNA reporter genes. When no fluorescence signal is detected, it indicates that the sample does not either DHAV-3 virulent strain or attenuated strain. When only ROX or FAM fluorescence is detected, the sample is only DHAV-3 virulent strain or attenuated strain. If both FAM and ROX fluorescence signals are detected simultaneously, it indicates the presence of both DHAV-3 virulent and attenuated strains in the sample.

Fig. 2.

Fig 2

Open in a new tab

Determination of target genes. (A) CRISPR Cas12a/Cas13a experiments were conducted on attenuated strain 2A2, 2C, and VP1 genes as targets. (B) CRISPR Cas12a/Cas13a experiments were conducted on virulent strain 2A2, 2C, and VP1 genes as targets.

Fig. 3.

Fig 3

Open in a new tab

Construction of RPA-CRISPR single-base recognition system. (A-B) Screening of RPA primers. Detection fluorescence values with different RPA primers. (C) Schematic diagram of crRNAs design. (D-E) Real-time fluorescence curves on various crRNAs to assess effectiveness. 12a-crRNA-2 and 13a-crRNA-2 were used as crRNAs for the experiments. (F-G) Probe specificity confirmation. When there were corresponding target genes in the Cas12a and Cas13a systems, the Cas protein only cleaved the corresponding probe, and there was no mutual interference between the two reactions.

Additionally, to ensure the optimal reaction ratio between Cas protein and crRNA in the system, we designed multiple gradients and found that the best performance was achieved when the ratio of Cas protein to crRNA in the system was 2:1 (Fig. 4A). Subsequently, various RPA volume gradients were tested in repeated experiments to identify the optimal RPA volume. As Fig. 4B depicted, when the RPA volume was reduced to 25 μL, the fluorescence signal remained robust. Finally, we optimized the optimal reaction time for the detection, and the results are presented in Fig. 4D and E. The best performance was achieved when the RPA reaction was conducted for 15 min, followed by a CRISPR reaction time of 20 min, resulting in a total reaction time of 35 min.

Fig. 4.

Fig 4

Open in a new tab

Optimization of RPA-CRISPR single-base recognition system. (A) The optimal reaction ratio between Cas protein and crRNA in the system was screened, and the optimal ratio of Cas protein to crRNA in the system was ultimately determined to be 2:1. (B) RPA reaction volume optimization. Different lowercase letters indicate significant difference between members of each group. (C-D) Screening for optimal response times. (C) Under the conventional CRISPR reaction time of 1 h, RPA reaction time was screened with a time gradient (5 min, 10 min, 15 min, 20 min, 25 min), and the results showed that the amount of fluorescence tended to remain unchanged after 15 min. (N.s. indicates no difference between the two groups.) (D) Under the RPA reaction time of 15 min, RPA-CRISPR reactions were performed at different CRISPR reaction times (10 min, 15 min, 20 min, 25 min, 30 min), and the results showed that the fluorescence level tended to remain unchanged after 20 min.

Evaluation of specificity, sensitivity and repeatability

In order to assess the specificity of the method, we used it to detect DHAV-3 attenuated strain, DHAV-1, DHAV-3 virulent strain, NDRV, RA-1, RA-2, and no template control (NTC) respectively. As shown in Fig. 5A, FAM channel or Rox channel generated signals only when DHAV-3 attenuated strain or virulent strain was present. However, no fluorescence signal was observed for other pathogens, demonstrating that the method had good specificity. After serial dilutions of two standard recombinant plasmids, the sensitivity of the experimental method was determined using recombinant plasmids at concentrations ranging from 104 to 0.5 copies/μL as templates. As shown in Fig. 5B, it was able to detect both the DHAV-3 attenuated strain and wild strain at a concentration of 10° copy/μL. At the same time, we conducted five independent replicate experiments to confirm the stability of this method.

Fig. 5.

Fig 5

Open in a new tab

Evaluation of specificity and sensitivity of the RPA-CRISPR single-base recognition system. The specificity of the system on the analysis of DHAV-3 virulent and attenuated strains RNA against other pathogens (n = 3). (B) Determination of the limit of detection of the system on DHAV-3 virulent and attenuated strains standards plasmid. ****p < 0.0001 (n = 5).

Samples detection

30 samples from Shandong Hekangyuan Group Co., Ltd. were detected by using this method and sequencing, respectively. As shown in Fig. 6 and Table 1, the results of this method, sequencing results, and the results provided by the company were compared and found to be consistent, indicating that this method is accurate and reliable in identifying DHAV-3 virulent and attenuated strains.

Fig. 6.

Fig 6

Open in a new tab

Clinical samples detection with the RPA-CRISPR single-base recognition system. Heat map of detection results using the method on 30 clinical samples. (“+”, positive; “-”, negative).

Table 1.

The results of RPA-CRISPR single-base recognition system and sequencing for samples detection.

SAMPLE NUMBER ATTENUATED STRAIN FLUORESCENCE VALUE VIRULENT STRAIN FLUORESCENCE VALUE RPA-CRISPR SINGLE-BASE RECOGNITION SYSTEM RESULTS SEQUENCING RESULTS
S1 – 1.99 DHAV-3 virulent strain DHAV-3 virulent strain
S2 – 2.19 DHAV-3 virulent strain DHAV-3 virulent strain
S3 – – – –
S4 – 1.38 DHAV-3 virulent strain DHAV-3 virulent strain
S5 – – – –
S6 1.31 – DHAV-3 attenuated strain DHAV-3 attenuated strain
S7 2.44 3.20 DHAV-3 attenuated and virulent strains DHAV-3 attenuated and virulent strains
S8 1.73 2.11 DHAV-3 attenuated and virulent strains DHAV-3 attenuated and virulent strains
S9 – – – –
S10 – 2.16 DHAV-3 virulent strain DHAV-3 virulent strain
S11 – – – –
S12 2.07 3.01 DHAV-3 attenuated and virulent strains DHAV-3 attenuated and virulent strains
S13 1.58 – DHAV-3 attenuated strain DHAV-3 attenuated strain
S14 – 2.43 DHAV-3 virulent strain DHAV-3 virulent strain
S15 – – – –
S16 1.46 2.02 DHAV-3 attenuated and virulent strains DHAV-3 attenuated and virulent strains
S17 – 2.91 DHAV-3 virulent strain DHAV-3 virulent strain
S18 1.35 – DHAV-3 attenuated strain DHAV-3 attenuated strain
S19 – – – –
S20 1.75 2.43 DHAV-3 attenuated and virulent strains DHAV-3 attenuated and virulent strains
S21 1.86 – DHAV-3 attenuated strain DHAV-3 attenuated strain
S22 – 1.58 DHAV-3 virulent strain DHAV-3 virulent strain
S23 1.95 1.92 DHAV-3 attenuated and virulent strains DHAV-3 attenuated and virulent strains
S24 – – – –
S25 1.63 1.55 DHAV-3 attenuated and virulent strains DHAV-3 attenuated and virulent strains
S26 1.85 2.22 DHAV-3 attenuated and virulent strains DHAV-3 attenuated and virulent strains
S27 – – – –
S28 – 1.53 DHAV-3 virulent strain DHAV-3 virulent strain
S29 2.70 3.20 DHAV-3 attenuated and virulent strains DHAV-3 attenuated and virulent strains
S30 3.29 – DHAV-3 attenuated strain DHAV-3 attenuated strain
Open in a new tab

Discussion

As a major duck meat producer in the world, the prevalence of DHAV-3 in farms has intensified in recent years, and the high pathogenicity of its virulent strain to ducklings has caused serious economic losses (Liu et al., 2019; Ren et al., 2019; Zhang et al., 2017). Although the extensive vaccination of live attenuated vaccines is the main means of prevention and control at present, the phenomenon of vaccine strains' virulence returning to strength or wild strains breaking through the immune protection occurs from time to time. It is urgent to establish a technical system for accurately identifying virulent strains and attenuated strains to guide the epidemic early warning and precise prevention and control.

However, the genome homology between DHAV-3 virulent strain and attenuated strain is extremely high, traditional detection methods such as RT-qPCR and ELISA are difficult to distinguish subtle base differences. Now no specific detection method for DHAV-3 virulent and attenuated strain has been reported. In this study, the virulence related single base markers were screened based on the genome alignment of multiple strains, and the RPA-CRISPR single base recognition system was successfully constructed. Results showed that the system can distinguish single base variations through crRNA mediated specific recognition, and its sensitivity is 10° copy/μL, and the detection results are completely consistent with the sequencing results. Compared with the traditional method, this technology has higher sensitivity (Wang et al., 2024) and does not need complex thermal cycle equipment, and can complete the detection within 35 min. It can significantly reduce the risk of aerosol pollution in one centrifuge tube, providing a new approach for on-site monitoring on farms.

However, the application of this system in farms still faces challenges: first, viral RNA extraction relies on a rapid nucleic acid purification kit, and the complex matrix of duck manure samples in the on-site environment may affect the extraction efficiency; Secondly, the reading of CRISPR fluorescence signal can be supported by portable fluorescence detection equipment (Zhang et al., 2024). In the future, visual detection of test strips can be developed to enhance practicability. Nevertheless, the establishment of this method has achieved the molecular identification of DHAV-3 virulent strains and SD70 attenuated strains for the first time, and its core value is to provide a highly sensitive technical tool for monitoring the genetic stability of toxic strains and epidemiological tracking of wild strains during vaccine production.

Conclusion

In short, we proposed a single-base recognition system based on RPA-CRISPR Cas12a/Cas13a for rapid detection and differentiation of DHAV-3 virulent strains and SD70 attenuated strain, which could be completed within 35 min and had a sensitivity of up to 10° copy/μL. The high specificity and sensitivity of this method provided a new strategy for field detection and identification of DHAV-3 virulent strains and SD70 attenuated strain. It plays an important role in DHAV-3 control, precision drug use, vaccine safety evaluation, and detection.

CRediT authorship contribution statement

Lei Chen: Conceptualization, Funding acquisition, Methodology. Qiaoli Zhang: Methodology, Writing – original draft. Wenbo Sun: Validation, Formal analysis. Michael G. Mauk: Writing – review & editing. Qingmei Li: Methodology, Writing – review & editing.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgement

This work was supported by the National Key Research and Development Program of China (2024YFE0111700).

Footnotes

The appropriate scientific section: Microbiology and Food Safety

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.psj.2025.105241.

Appendix. Supplementary materials

mmc1.docx (20.5KB, docx)

References

  1. Fu Q., Han X., Zhu C., Jiao W., Liu R., Feng Z., Huang Y. Development of the first officially licensed live attenuated duck hepatitis A virus type 3 vaccine strain HB80 in China and its protective efficacy against DHAV-3 infection in ducks. Poult. Sci. 2024;(10):103. doi: 10.1016/j.psj.2024.104087. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Geller R., Chen X., Chen Y., Liu C., Li X., Liu H., Zhang Y. Improved one-tube RT-PCR method for simultaneous detection and genotyping of duck hepatitis A virus subtypes 1 and 3. PLoS One. 2019;(8):14. doi: 10.1371/journal.pone.0219750. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Gootenberg J.S., Abudayyeh O.O., Kellner M.J., Joung J., Collins J.J., Zhang F. Multiplexed and portable nucleic acid detection platform with Cas13, Cas12a, and Csm6. Science. 2018;360(6387):439–444. doi: 10.1126/science.aaq0179. (1979) [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Gootenberg J.S., Abudayyeh O.O., Lee J.W., Essletzbichler P., Dy A.J., Joung J., Zhang F. Nucleic acid detection with CRISPR-Cas13a/C2c2. Science. 2017;356(6336):438–442. doi: 10.1126/science.aam9321. (1979) [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. He Y., Hu Q., San S., Kasputis T., Splinter M.G.D., Yin K., Chen J. CRISPR-based biosensors for human health: a novel strategy to detect emerging infectious diseases. TrAC Trends Anal. Chem. 2023:168. doi: 10.1016/j.trac.2023.117342. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Hu Q., Zhu D., Ma G., Cheng A., Wang M., Chen S., Chen X. A one-step duplex rRT-PCR assay for the simultaneous detection of duck hepatitis A virus genotypes 1 and 3. J. Virol. Methods. 2016;236:207–214. doi: 10.1016/j.jviromet.2016.07.011. [DOI] [PubMed] [Google Scholar]
  7. Jakubiec A., Jupin I. Regulation of positive-strand RNA virus replication: the emerging role of phosphorylation. Virus Res. 2007;129(2):73–79. doi: 10.1016/j.virusres.2007.07.012. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Kang M., Roh J.H., Jang H.K. Protective efficacy of a bivalent live attenuated vaccine against duck hepatitis A virus types 1 and 3 in ducklings. Vet. Microbiol. 2018;214:108–112. doi: 10.1016/j.vetmic.2017.12.018. [DOI] [PubMed] [Google Scholar]
  9. Kim M.C., Kim M.J., Kwon Y.K., Lindberg A.M., Joh S.J., Kwon H.M., Kwon J.H. Development of duck hepatitis A virus type 3 vaccine and its use to protect ducklings against infections. Vaccine. 2009;27(48):6688–6694. doi: 10.1016/j.vaccine.2009.08.092. [DOI] [PubMed] [Google Scholar]
  10. Lin S.L., Cong R.C., Zhang R.H., Chen J.H., Xia L.L., Xie Z.J., Jiang S.J. Circulation and in vivo distribution of duck hepatitis A virus types 1 and 3 in infected ducklings. Arch. Virol. 2015;161(2):405–416. doi: 10.1007/s00705-015-2648-z. [DOI] [PubMed] [Google Scholar]
  11. Liu N., Liu R., Zhang J. CRISPR-Cas12a-mediated label-free electrochemical aptamer-based sensor for SARS-CoV-2 antigen detection. Bioelectrochemistry. 2022:146. doi: 10.1016/j.bioelechem.2022.108105. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Liu R., Shi S., Huang Y., Chen Z., Chen C., Cheng L., Fu Q. Comparative pathogenicity of different subtypes of duck hepatitis A virus in Pekin ducklings. Vet. Microbiol. 2019;228:181–187. doi: 10.1016/j.vetmic.2018.11.030. [DOI] [PubMed] [Google Scholar]
  13. Liu Y., Liu H., Yu G., Sun W., Aizaz M., Yang G., Chen L. One-tube RPA-CRISPR Cas12a/Cas13a rapid detection of methicillin-resistant Staphylococcus aureus. Anal. Chim. Acta. 2023:1278. doi: 10.1016/j.aca.2023.341757. [DOI] [PubMed] [Google Scholar]
  14. Niu Y., Ma H., Ding Y., Li Z., Sun Y., Li M., Shi Y. The pathogenicity of duck hepatitis A virus types 1 and 3 on ducklings. Poult. Sci. 2019;98(12):6333–6339. doi: 10.3382/ps/pez455. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Ren Y., Yue H., Zhu L., Kan R., Tang C., Zhang B. A reverse transcription-insulated isothermal PCR assay for the detection of duck hepatitis A virus type 3 based on the POCKIT™ system. J. Virol. Methods. 2019;270:126–130. doi: 10.1016/j.jviromet.2019.05.006. [DOI] [PubMed] [Google Scholar]
  16. Shawki M.M., Abido O.Y., Saif M.A., Sobh M.S., Gado A.R., Elnaggar A., El-Shall N.A. Comparative pathogenicity of duck hepatitis A virus genotype 3 in different duck breeds: implications of the diagnosis and prevention of duck viral hepatitis. Comp. Immunol. Microbiol. Infect. Dis. 2024:114. doi: 10.1016/j.cimid.2024.102256. [DOI] [PubMed] [Google Scholar]
  17. van Dongen J.E., Berendsen J.T.W., Steenbergen R.D.M., Wolthuis R.M.F., Eijkel J.C.T., Segerink L.I. Point-of-care CRISPR/Cas nucleic acid detection: recent advances, challenges and opportunities. Biosens. Bioelectron. 2020:166. doi: 10.1016/j.bios.2020.112445. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Wang H., Sun Y., Zhou Y., Liu Y., Chen S., Sun W., Chen L. Unamplified system for sensitive and typing detection of ASFV by the cascade platform that CRISPR-Cas12a combined with graphene field-effect transistor. Biosens. Bioelectron. 2023:240. doi: 10.1016/j.bios.2023.115637. [DOI] [PubMed] [Google Scholar]
  19. Wang Y., Wang Y., Bi Z., Liu Y., Meng C., Zhu J., Li C. Simultaneous detection of novel goose parvovirus and novel duck reovirus by SYBR Green I-based duplex real-time quantitative polymerase chain reaction. 3 Biotech. 2024;14(11):288. doi: 10.1007/s13205-024-04139-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Wen X., Guo J., Sun D., Wang M., Cao D., Cheng A., Rehman M.U. Mutations in VP0 and 2C proteins of Duck Hepatitis A Virus type 3 attenuate viral infection and virulence. Vaccines. 2019;7(3) doi: 10.3390/vaccines7030111. (Basel) [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Wen X., Zhu D., Cheng A., Wang M., Chen S., Jia R., Chen X. Molecular epidemiology of duck hepatitis a virus types 1 and 3 in China, 2010-2015. Transbound. Emerg. Dis. 2018;65(1):10–15. doi: 10.1111/tbed.12741. [DOI] [PubMed] [Google Scholar]
  22. Wu F., Lu F., Fan X., Pan Q., Zhao S., Sun H., Zhang X. Development of a live attenuated duck hepatitis A virus type 3 vaccine (strain SD70) Vaccine. 2020;38(30):4695–4703. doi: 10.1016/j.vaccine.2020.05.030. [DOI] [PubMed] [Google Scholar]
  23. Ye L., Zhou S., Zhang H., Zhang T., Yang D., Hong X. A meta-analysis for vaccine protection rate of duck hepatitis a virus in mainland China in 2009–2021. BMC Vet. Res. 2023;19(1) doi: 10.1186/s12917-023-03744-8. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Zhang K., Li Q., Wang K., Zhang Q., Ma C., Yang G., Chen L. RPA-CRISPR-Cas-mediated dual lateral flow assay for the point-of-care testing of HPV16 and HPV18. Bioconjug. Chem. 2024;35(11):1797–1804. doi: 10.1021/acs.bioconjchem.4c00375. [DOI] [PubMed] [Google Scholar]
  25. Zhang Q., Yu G., Ding X., Zhang K., Sun W., Li Q., Chen L. A rapid simultaneous detection of duck hepatitis A virus 3 and novel duck reovirus based on RPA CRISPR Cas12a/Cas13a. Int. J. Biol. Macromol. 2024:274. doi: 10.1016/j.ijbiomac.2024.133246. [DOI] [PubMed] [Google Scholar]
  26. Zhang Q., Yu G., Ding X., Zhang K., Sun W., Li Q., Chen L. A rapid simultaneous detection of duck hepatitis A virus 3 and novel duck reovirus based on RPA CRISPR Cas12a/Cas13a. Int. J. Biol. Macromol. 2024;274(Pt 1) doi: 10.1016/j.ijbiomac.2024.133246. [DOI] [PubMed] [Google Scholar]
  27. Zhang R., Xia L., Chen J., Gong Y., Zhang L., Li P., Jiang S. Molecular epidemiology and genetic diversity of duck hepatitis A virus type 3 in Shandong province of China, 2012–2014. Acta Virol. 2017;61(04):463–472. doi: 10.4149/av_2017_409. [DOI] [PubMed] [Google Scholar]
  28. Zhao S., Wu B., Wang Q., Wei X., Liu X., Tang Y., Diao Y. Advances in the Duck Hepatitis A virus and lessons learned from those in recent years. Microb. Pathog. 2024:197. doi: 10.1016/j.micpath.2024.107018. [DOI] [PubMed] [Google Scholar]
  29. Zhou S., Li S., Wang Y., Li X., Zhang T. Duck hepatitis A virus prevalence in mainland China between 2009 and 2021: a systematic review and meta-analysis. Prev. Vet. Med. 2022:208. doi: 10.1016/j.prevetmed.2022.105730. [DOI] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

mmc1.docx (20.5KB, docx)

Articles from Poultry Science are provided here courtesy of Elsevier

RESOURCES