Diagnostic Accuracy of CRISPR-Based Rapid Assays for Detection of Multi-Drug-Resistant Tuberculosis
DOI:
https://doi.org/10.66021/pakmcr1071Keywords:
Multidrug-Resistant Tuberculosis (MDR-TB); CRISPR-Cas Diagnostics; Cas12/Cas13/Cas14; Isothermal Amplification (RPA/LAMP); Point-of-Care Testing (POCT); Single Nucleotide Polymorphism (SNP) Discrimination; Molecular Diagnostics.Abstract
Multidrug-resistant tuberculosis (MDR-TB) remains a major global public health threat, driven by delayed diagnosis, limited drug susceptibility testing capacity, and the slow turnaround time of conventional culture-based methods. This study reviews and synthesizes current evidence on the diagnostic accuracy and clinical utility of CRISPR-based rapid molecular assays for the detection of Mycobacterium tuberculosis and associated drug resistance mutations. Traditional diagnostic platforms such as smear microscopy, culture, and GeneXpert MTB/RIF Ultra, while widely used, are constrained by either low sensitivity in paucibacillary disease or limited resistance profiling and infrastructural dependency. CRISPR-Cas–based diagnostics, particularly those utilizing Cas12, Cas13, and Cas14 effectors integrated with isothermal amplification techniques such as RPA and LAMP, demonstrate significant improvements in turnaround time, sensitivity, and point-of-care applicability. Meta-analytic evidence indicates pooled sensitivities of approximately 91–93% and specificities of 97–98% for tuberculosis detection, with even higher accuracy reported for rifampicin and isoniazid resistance-associated mutations such as rpoB S531L and katG S315T. The diagnostic workflow enables rapid detection within one hour, with the added advantage of single nucleotide polymorphism discrimination critical for MDR-TB identification. Furthermore, CRISPR-based platforms show strong performance in extrapulmonary and paucibacillary samples, where conventional diagnostics often underperform. Their compatibility with portable, lyophilized, and low-cost formats enhances feasibility for decentralized and resource-limited healthcare settings. Despite these advantages, challenges remain in large-scale enzyme production, standardization, sample preparation, and regulatory harmonization.




