Related Experiment Video
Updated: May 12, 2026

Multiplex PCR and Reverse Line Blot Hybridization Assay mPCR/RLB
Published on: August 6, 2011
Multiplex detection of bacterial pathogens by PCR/SERS assay
Nana Lyu1, Phani Rekha Potluri1, Vinoth Kumar Rajendran1
1School of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia. yuling.wang@mq.edu.au.
Abstract:
Bacterial infections are a leading cause of death globally. The detection of DNA sequences correlated to the causative pathogen has become a vital tool in medical diagnostics. In practice, PCR-based assays for the simultaneous detection of multiple pathogens currently rely on probe-based quantitative strategies that require expensive equipment but have limited sensitivity or multiplexing capabilities. Hence, novel approaches to address the limitations of the current gold standard methods are still in high demand. In this study, we propose a simple multiplex PCR/SERS assay for the simultaneous detection of four bacterial pathogens, namely P. aeruginosa, S. aureus, S. epidermidis, and M. smegmatis. Wherein, specific primers for amplifying each target gDNA were applied, followed by applying SERS nanotags functionalized with complementary DNA probes and Raman reporters for specific identification of the target bacterial pathogens. The PCR/SERS assay showed high specificity and sensitivity for genotyping bacterial pathogen gDNA, whereby as few as 100 copies of the target gDNA could be detected. With high sensitivity and the convenience of standard PCR amplification, the proposed assay shows great potential for the sensitive detection of multiple pathogen infections to aid clinical decision-making.
More Related Videos
11:09Multiplex Detection of Bacteria in Complex Clinical and Environmental Samples using Oligonucleotide-coupled Fluorescent Microspheres
Published on: October 23, 2011
05:25Author Spotlight: Expanding the Scope of Multiplex Immunoassays for Lyme Borreliosis Diagnostics and Pathogen Research
Published on: July 14, 2023
Related Concept Videos
Methods of Classification and Identification
Automated Microbial Diagnostics