A Multiplex Electrochemical Biosensor for Bloodstream Infection Diagnosis

Area of Science:

• Biomedical Engineering
• Clinical Diagnostics
• Microbiology

Background:

• Accurate and timely detection of bacterial pathogens is crucial for effective clinical management of infections.
• Current methods for bloodstream infection diagnosis can be time-consuming, delaying appropriate treatment.
• There is a need for rapid, sensitive, and specific diagnostic tools for bacterial pathogens directly in patient samples.

Purpose of the Study:

• To develop and validate an electrochemical biosensor for direct detection and identification of bacterial pathogens in human blood.
• To assess the analytical performance of the biosensor, including limit of detection and specificity.
• To demonstrate the feasibility of the biosensor for rapid diagnosis of bloodstream infections using clinical isolates.

Main Methods:

• Development of a multiplex electrochemical biosensor utilizing species-specific 16S ribosomal RNA (rRNA) sequences for bacterial identification.
• Direct detection of bacterial pathogens in human blood samples without the need for preamplification.
• Systematic evaluation of analytical performance characteristics, including limit of detection and probe cross-reactivity.
• Validation using bacterial clinical isolates spiked into whole blood and positive blood culture samples.

Main Results:

• The electrochemical biosensor successfully detected and identified bacterial species directly from human blood samples.
• The biosensor demonstrated high specificity by targeting unique 16S rRNA sequences.
• Analytical performance, including limit of detection and specificity, was systematically evaluated.
• The biosensor achieved 100% concordance with standard microbiological analysis in identifying bacterial species in spiked blood and blood culture samples.

Conclusions:

• The developed electrochemical biosensor offers a rapid and accurate method for diagnosing bloodstream infections.
• Direct detection of bacterial 16S rRNA sequences without preamplification simplifies the diagnostic workflow.
• This technology holds significant potential for improving patient outcomes through timely and precise pathogen identification.