[27] IMPACT OF 16S RRNA-BASED MOLECULAR IDENTIFICATION OF BACTERIA ON INFECTIOUS DISEASE DIAGNOSIS
How to Cite the Article: Rupali Gehlot & Deepak K. Sinha (2026). Impact Of 16s Rrna-Based Molecular Identification of Bacteria on Infectious Disease Diagnosis. International Journal of Multidisciplinary Research & Reviews, 5(6),331-349. https://doi.org/10.56815/ijmrr.v5i6.2026.331-349
Abstract
16S rRNA sequencing enhances infectious disease diagnosis by enabling rapid pathogen detection and supports appropriate antimicrobial therapy. The technique also contributes to improved epidemiological surveillance and better understanding of bacterial diversity and evolution. Its advantages, limitations such as sequencing cost, technical expertise requirements, and database inconsistencies continue to restrict widespread implementation in routine laboratories. The identification of bacterial pathogens plays a critical role in the diagnosis and management of infectious diseases. Traditional phenotypic and biochemical identification methods are often timeconsuming and may fail to accurately identify rare, slow-growing, or phenotypically atypical bacteria. The present study examines the impact of 16S rRNA-based molecular identification on clinical microbiology and infectious disease diagnosis. The 16S rRNA gene is highly conserved among bacterial species while containing variable regions that enable precise differentiation and phylogenetic classification. This molecular approach has significantly improved the accuracy, speed, and reliability of bacterial identification compared to conventional culture-based techniques The study highlights the usefulness of 16S rRNA sequencing in identifying difficult-to-culture organisms, detecting novel bacterial species, and reducing diagnostic errors in clinical laboratories. The methodology involved a comprehensive review and comparative analysis of published literature related to molecular bacterial identification, sequencing procedures, diagnostic efficiency, and microbial taxonomy and biology by providing accurate bacterial classification, improving diagnostic precision, and supporting effective patient management in infectious disease diagnosis and treatment.
