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Related Experiment Video

Updated: Jan 30, 2026

Electroantennographic Bioassay as a Screening Tool for Host Plant Volatiles
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Printable QR code paper microfluidic colorimetric assay for screening volatile biomarkers.

Alison Burklund1, Harrison K Saturley-Hall1, Flavio A Franchina2

  • 1Thayer School of Engineering, Dartmouth College, Hanover, NH 03755, USA.

Biosensors & Bioelectronics
|January 15, 2019
PubMed
Summary

A novel QR code paper microfluidic assay rapidly identifies E. coli bloodstream infections by detecting volatile indole biomarkers. This telemedicine platform offers faster diagnostics using mobile devices and printable microarrays.

Keywords:
Gas Chromatography - Mass SpectrometryMobile HealthPaper MicrofluidicsSepsisVolatile Organic Compounds

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Area of Science:

  • Biomarker detection
  • Microfluidics
  • Point-of-care diagnostics

Background:

  • Rapid identification of E. coli is crucial for bloodstream infections.
  • Current diagnostic methods can be time-consuming.
  • Volatile biomarkers offer a potential avenue for faster detection.

Purpose of the Study:

  • To develop a QR code paper microfluidic colorimetric assay for rapid E. coli identification.
  • To detect volatile indole, a biomarker produced by E. coli.
  • To leverage mobile devices for instant diagnosis and data collection.

Main Methods:

  • A printable microarray of reaction regions was designed.
  • p-dimethylaminocinnamaldehyde reagent was used to detect indole.
  • Assay results were confirmed using headspace solid-phase microextraction (HS-SPME) and GC×GC-ToFMS.

Main Results:

  • The assay quantitatively detected indole in E. coli culture headspace within 12 hours.
  • Detected indole concentration averaged 27.0 ± 3.1 ppm.
  • GC×GC-ToFMS confirmed indole concentration averaged 32.3 ± 5.2 ppm.

Conclusions:

  • The QR code paper microfluidic platform enables rapid, species-level identification of E. coli.
  • This novel approach integrates telemedicine and diagnostics using volatile biomarkers.
  • The platform has potential for real-time diagnostics in low-resource settings.