Integrated microfluidic systems for sample preparation and detection of respiratory pathogen Bordetella pertussis

Carlos de la Rosa1, Ranjit Prakash, Peter A Tilley

  • 1Schulich School of Engineering, Department of Electrical and Computer Engineering, 2500 University Drive, NW. Calgary, Alberta, Canada. T2N 1N4.

Insights

This study presents an integrated microfluidic system for Bordetella pertussis detection. The device efficiently pre-concentrates and lyses bacteria using dielectrophoresis and electroporation for pathogen analysis.

Area of Science:

  • Biotechnology
  • Microfluidics
  • Pathogen Detection

Background:

  • Bordetella pertussis detection requires efficient sample preparation.
  • Current methods for sample manipulation and lysis can be time-consuming and complex.

Purpose of the Study:

  • To develop an integrated microfluidic system for combined manipulation, pre-concentration, and lysis of Bordetella pertussis.
  • To demonstrate a complete chip-based approach for pathogen detection.

Main Methods:

  • Development of a microfluidic device utilizing dielectrophoresis for pre-concentration and electroporation for cell lysis.
  • Optimization of pre-concentration parameters including flow rate and initial cell concentration.
  • Evaluation of electroporation effectiveness on Bordetella pertussis viability and cell disruption.

Main Results:

  • The microfluidic device achieved a 6.7x pre-concentration of Bordetella pertussis cells from 200 microl to 20 microl at optimal conditions.
  • On-chip electroporation effectively lysed Bordetella pertussis cells, confirmed by transmission electron microscopy.
  • Integrated system demonstrated successful genetic amplification and detection of pre-concentrated pathogens.

Conclusions:

  • The integrated microfluidic system offers an efficient and complete solution for Bordetella pertussis sample preparation and detection.
  • Dielectrophoresis and electroporation are effective tools for on-chip manipulation and lysis of bacterial pathogens.
  • This chip-based approach has potential for rapid and sensitive pathogen detection systems.