Smartphone-based polydiacetylene colorimetric sensor for point-of-care diagnosis of bacterial infections

Yue Zhou, Yumeng Xue, Xubo Lin, Menglong Duan, Weili Hong, Lina Geng, Jin Zhou*, Yubo Fan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

The rapid progress in point-of-care testing (POCT) has become a promising decentralized patient-centered approach for the control of infectious diseases, especially in resource-limited settings. POCT devices should be inexpensive, rapid, simple operation and preferably require no power supply. Here, we developed a simple bacterial sensing platform that can be operated by a smartphone for bacteria identification and antimicrobial susceptibility testing (AST) based on using a polydiacetylene (PDA) arrayed membrane chip. Each PDA array produced a unique color ‘fingerprint’ pattern for each bacteria based on different modes of action of toxins from bacteria on biomimetic lipid bilayers within PDA-lipid assemblies. We show that the PDA-based device can detect viable cells of bacteria as low as 104 ​CFU/mL within 1.5 ​h compared with several days of conventional bacterial identification, with the aid of a smartphone app. The device can also be used for an antimicrobial susceptibility test (AST) for at least two broad-spectrum antimicrobials within 4 ​h and provide identification of antimicrobial susceptibility and resistance, enabling the selection of appropriate therapies. This PDA-based sensing platform provides an alternative way for bacterial detection and could be used as a portable and inexpensive POCT device for the rapid detection of bacterial infection in limited-resource settings.

Original languageEnglish
Pages (from-to)140-152
Number of pages13
JournalSmart Materials in Medicine
Volume5
Issue number1
DOIs
Publication statusPublished - Mar 2024

Keywords

  • Antimicrobial susceptibility testing (AST)
  • Bacterial infection
  • Point-of-care (POCT)
  • Polydiacetylene (PDA)
  • Smartphone-based detection

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