Infectious bursal disease virus (IBDV) is the pathogen responsible for infectious bursal disease (IBD), also known as Gumboro. This disease is highly contagious and has a considerable impact on young chickens, leading to huge economic losses in the poultry industry (Müller et al., 1992). IBDV belongs to the genus Avibirnavirus within the family Birnaviridae (Müller et al., 1979a). It is a nonenveloped, icosahedral virus with a double-stranded RNA genome divided into two segments, A and B (Müller et al., 1979a). Segment A (∼3.3 kb) encodes the viral proteins VP2, VP3, VP4, and VP5 (Lejal et al., 2000, Manning and Leong, 1990, Manning et al., 1990), whereas 2.9 kb segment B encodes the RNA-dependent RNA polymerase (VP1), which is crucial for viral replication (Yu et al., 2013). Among the two identified IBDV serotypes, only serotype I strains are virulent in chickens and are categorized into classical, very virulent, and antigenic variants (Chettle et al., 1989, Cosgrove, 1962, Jackwood and Saif, 1987).

The disease has a brief incubation period. Chickens younger than three weeks typically do not exhibit clinical signs but are immunosuppressed, whereas those between three and six weeks are most susceptible to clinical disease (Müller et al., 1979b). Clinical signs are nonspecific, but gross and microscopic lesions are characteristic, including inflammation and atrophy of the bursa of Fabricius and immunosuppression (Müller et al., 1979b). Similar but less severe lesions can occur in the spleen, thymus, cecal tonsils, and harderian gland (Saif, 1991). Immunosuppression caused by IBDV can result in secondary infections caused by opportunistic pathogens, decreased effectiveness of vaccination programs for other diseases, and negative responses to live attenuated vaccines (Becht, 1980, Saif, 1991). Despite extensive vaccination efforts, recurrent IBDV outbreaks with high mortality rates continue to be reported in Egypt and worldwide (El-Batrawi, 1990, Samy et al., 2020, Shehata et al., 2017).

Although isolation and identification of the causative agent provide a definitive diagnosis, this is not typically attempted for routine diagnostics owing to the difficulty of isolating the virus (WOAH, 2024). The laboratory diagnosis of IBD relies primarily on detecting specific antibodies to the virus or the virus itself in tissues via immunological or molecular methods (Aliy et al., 2020). In comparison to other standard laboratory procedures, serological assays for the diagnosis of IBD, such as enzyme-linked immunosorbent assay (ELISA), virus-neutralization (VN) assays and agar gel precipitin (AGP), have the potential to offer high specificity and sensitivity, as well as ease of operation (Jackwood and Saif, 1987, Snyder et al., 1992, Tsukamoto et al., 1995). Nevertheless, the extended time frame for antigen–antibody interaction, enzymatic conversion of substrates, multiple washing stages between distinct procedures, and the necessity for specific instrumentation could restrict the applicability of these assays (Nurulfiza et al., 2011). The application of classical molecular techniques for the detection of IBDV RNA in clinical specimens, such as Northern blotting, is constrained by a deficiency in sensitivity; in contrast, PCR-based methodologies are regarded as the most sensitive molecular techniques (Banda et al., 2004, Clementi et al., 1995, Hernández et al., 2011, Kerachian et al., 2019, Kong et al., 2009, Li et al., 2007). However, PCR-based methodologies, such as RT-PCR and RT-qPCR, have different disadvantages including the necessity for sophisticated laboratory apparatus and skilled operators (Khan et al., 2018). In accordance with the World Health Organization (WHO), the optimal diagnostic approach should be rapid, specific, sensitive, instrument-free, and cost-effective (Zhan et al., 2022). The limitations of conventional detection assays have led to an increased utilization of CRISPR-mediated nucleic acid detection method, such as SHERLOCK, as a means of detection (Zhan et al., 2022).

The clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) system is an adaptive, small RNA-based immune system in prokaryotes that protects against infectious viruses and plasmids (Barrangou and Marraffini, 2014, Deveau et al., 2010). This system recognizes and cleaves exogenous nucleic acid sequences via nucleases guided by CRISPR RNA (crRNA) (Li et al., 2015, Makarova et al., 2011). The CRISPRCas system is valued as a genome editing and diagnostic tool for nucleic acid detection (Cao et al., 2021, Chuang et al., 2021). CRISPRCas systems are categorized into two primary classes: six types and forty-eight subtypes (Makarova et al., 2020). Class 1 systems are composed of multi-Cas protein complexes, which may be categorized into three classes (I, III, and IV) and 22 subtypes (Makarova et al., 2020). On the other hand, Class 2 systems consist of a single multidomain crRNA-binding protein, comprising three distinct types (II, V, and VI) and a total of 26 subtypes. (Pinilla-Redondo et al., 2020, Shmakov et al., 2015). The Cas13a effector protein, which is part of the VI-A subtype, functions as an RNA-guided RNase, where Cas13a forms a complex with crRNA to cleave single-stranded RNA (Gootenberg et al., 2017, O'Connell, 2019).

The specific high-sensitivity enzymatic reporter unlocking (SHERLOCK) platform was developed for the rapid and sensitive detection of pathogens (Gootenberg et al., 2017). This method has the ability to identify both target RNA and target DNA with an extremely high level of sensitivity and can accurately distinguish single-base mismatches (Gootenberg et al., 2017). SHERLOCK utilizes the collateral activity of Cas13a, which, when triggered by the target RNA sequence, indiscriminately breaks down non-target RNA molecules, including those that are labeled with fluorescent tags, indicating the presence of the particular RNA (Caliendo and Hodinka, 2017, Gootenberg et al., 2017). The SHERLOCK platform is primarily a qualitative rather than a quantitative diagnostic tool, as it provides a binary (positive/negative) readout based on the presence or absence of target nucleic acids (Gootenberg et al., 2017). While its exceptional sensitivity enables detection at attomolar concentrations (Chen et al., 2018), it does not inherently quantify viral load like real-time PCR (Kellner et al., 2019). However, recent advancements incorporating fluorescence or lateral flow readouts with semi-quantitative interpretation may allow for limited viral load estimation under optimized conditions (Myhrvold et al., 2018). Regarding strain discrimination, SHERLOCK's specificity depends on crRNA design; when targeting conserved genomic regions, it detects all strains uniformly, but carefully engineered crRNAs can distinguish between field and vaccine strains by exploiting genetic polymorphisms (Patchsung et al., 2020). Studies have demonstrated this capability for various viruses, including Zika and Dengue strain differentiation (Barnes et al., 2020). The platform's modular crRNA design permits rapid reconfiguration to track emerging variants, making it particularly valuable for surveillance applications where strain-specific detection is required (Myhrvold et al., 2018). The SHERLOCK system has successfully detected various viral diseases, such as Dengue, Zika, Hepatitis, Influenza, Ebola, Pneumonia, African Swine Flu, and COVID-19, and distinguished pathogenic bacteria (Barnes et al., 2020, Casati et al., 2022, Ding et al., 2022, Gootenberg et al., 2017, Liu et al., 2019, Myhrvold et al., 2018, Yuan et al., 2020, Zhan et al., 2022).

The present study describes the development of a field-applicable, ultrasensitive IBD diagnostic tool using the CRISPR-based nucleic acid detection platform SHERLOCK. The data on the specificity and sensitivity of the assay as well as the applicability of the assay for clinical diagnosis are presented and discussed.