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Related Concept Videos

Microbial Biosensors01:17

Microbial Biosensors

Microbial biosensors are analytical devices that utilize living microbes to detect specific substances through measurable signals. These devices consist of two main components: biosensing organisms and signal-transducing elements. Biosensing organisms, such as Escherichia coli or Saccharomyces cerevisiae, are typically housed in multiwell plates connected to transducers, enabling rapid, real-time detection of target analytes.Signal Generation MechanismWhen a target analyte—such as...

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Biosensor for Detection of Antibiotic Resistant Staphylococcus Bacteria
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Published on: May 8, 2013

Detecting and tracking nosocomial methicillin-resistant Staphylococcus aureus using a microfluidic SERS biosensor.

Xiaonan Lu1, Derrick R Samuelson, Yuhao Xu

  • 1School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, Washington 99164-7520, United States.

Analytical Chemistry
|January 19, 2013
PubMed
Summary

Rapidly detect and differentiate methicillin-resistant Staphylococcus aureus (MRSA) using a novel lab-on-a-chip system. This surface-enhanced Raman scattering (SERS) method offers ultrafast, automated, and reliable detection for improved infection diagnosis and surveillance.

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Area of Science:

  • Microfluidics and Spectroscopy
  • Bacteriology and Infectious Diseases
  • Medical Diagnostics

Background:

  • Rapid detection of methicillin-resistant Staphylococcus aureus (MRSA) is crucial for managing infections and surveillance.
  • Traditional methods can be time-consuming, delaying diagnosis and treatment.
  • Differentiating MRSA from methicillin-sensitive S. aureus (MSSA) is essential for effective patient care.

Purpose of the Study:

  • To develop and validate a microfluidics chip coupled with surface-enhanced Raman scattering (SERS) spectroscopy for rapid MRSA and MSSA detection.
  • To assess the system's performance using clinical isolates from China and the United States.
  • To establish a SERS-based model for bacterial identification, differentiation, and quantification.

Main Methods:

  • Development of an optofluidic lab-on-a-chip system integrating microfluidics and SERS spectroscopy (532 nm).
  • Analysis of 58 clinical isolates (21 MSSA, 37 MRSA) using the developed SERS platform.
  • Comparison with polymerase chain reaction (PCR) and multilocus sequence typing (MLST) for validation.
  • Development of SERS-based dendrogram and partial least-squares regression models.

Main Results:

  • The SERS lab-on-a-chip system detected and differentiated MRSA and MSSA within 3.5 hours.
  • High spectral reproducibility (differentiation index 3.43-4.06) demonstrated interlaboratory feasibility.
  • A SERS-based dendrogram model achieved 95% recognition rate for S. aureus isolates and correlated well with MLST.
  • Quantification of MRSA in mixtures was achieved with high accuracy (5-100%).

Conclusions:

  • The microfluidics-SERS optofluidic platform provides ultrafast, automated, and reliable detection and differentiation of MRSA and MSSA.
  • This technology is suitable for rapid diagnosis, epidemiological surveillance, and outbreak investigation of S. aureus infections.
  • The system offers advantages over traditional genotyping methods for bacterial identification.