International Journal of Science, Engineering and TechnologyAuthors: Assistant Professor Apurva, Assistant Professor Dr. Bhawna Negi, Assistant Professor Swati Trivedi, Assistant Professor Iti Sharma
Abstract: Urinary tract infections (UTIs) are among the most common bacterial infections and contribute substantially to antimicrobial use in community and hospital settings. Conventional diagnosis relies on clinical assessment, urinalysis and urine culture, with culture-based identification and antimicrobial susceptibility testing often requiring 24–72 hours. This delay can encourage empirical antibiotic prescribing and may be particularly problematic when infections are caused by resistant or less commonly detected organisms. Clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated (Cas) proteins have emerged as programmable nucleic-acid recognition tools that can be coupled with amplification methods and simple signal readouts. Cas12-based systems detect target DNA and can generate collateral cleavage of reporter molecules, whereas Cas13-based systems recognise RNA targets and can provide an alternative route for rapid detection. In UTI applications, these platforms may support identification of common uropathogens, including Escherichia coli, and detection of selected antimicrobial resistance determinants. Early studies have demonstrated rapid genotypic resistance testing and urine-to-result workflows, while newer approaches are exploring direct pathogen identification and susceptibility assessment from urine. However, CRISPR assays do not automatically replace culture: detection of a resistance gene does not always predict the full resistance phenotype, and absence of a targeted gene does not prove susceptibility. Sample preparation, target coverage, mixed infections, contamination control, clinical validation, cost and regulatory requirements remain important challenges. This review summarises the biological basis of CRISPR diagnostics, current approaches for uropathogen and resistance-marker detection, potential clinical applications, limitations and priorities for translation into routine diagnostic services.
