Mycobacterium tuberculosis Detection Using CRISPR Technology: An Updated Systematic Review and Meta-analysis

Area of Science:

• Molecular Diagnostics
• Microbiology
• Genetics

Background:

• Tuberculosis (TB) diagnosis requires rapid and precise methods.
• Clustered regularly interspaced short palindromic repeats (CRISPR) technology offers high specificity and adaptability for pathogen detection.

Purpose of the Study:

• To systematically review and meta-analyze the diagnostic accuracy of CRISPR-based techniques for identifying Mycobacterium tuberculosis (MTB).

Main Methods:

• A systematic literature search was performed across major databases (Medline, Scopus, Embase, Web of Science).
• Studies were assessed for quality using the Joanna Briggs Institute checklist.
• Data synthesis and subgroup analyses were conducted using R v 4.3.1.

Main Results:

• 14 studies including 2175 MTB strains were analyzed.
• CRISPR techniques demonstrated pooled sensitivity of 0.93 and specificity of 0.97.
• Excellent diagnostic accuracy was indicated by an area under the curve (AUC) of 0.97 on the SROC curve.

Conclusions:

• CRISPR-based methods exhibit significant diagnostic accuracy for MTB detection.
• Performance varies with CRISPR variants and methodologies.
• Further research is needed to optimize CRISPR for diverse clinical and research applications.