Color-coded droplets and microscopic image analysis for multiplexed antibiotic susceptibility testing

Yunjin Jeong, Haewook Jang, Junwon Kang, Juhong Nam, Kyoungseob Shin, Sunghoon Kwon, Jungil Choi

Research output: Contribution to journalArticlepeer-review

9 Scopus citations

Abstract

Since the discovery of antibiotics, the emergence of antibiotic resistance has become a global issue that is threatening society. In the era of antibiotic resistance, finding the proper antibiotics through antibiotic susceptibility testing (AST) is crucial in clinical settings. However, the current clinical process of AST based on the broth microdilution test has limitations on scalability to expand the number of antibiotics that are tested with various concentrations. Here, we used color-coded droplets to expand the multiplexing of AST regarding the kind and concentration of antibiotics. Color type and density differentiate the kind of antibiotics and concentration, respectively. Microscopic images of a large view field contain numbers of droplets with different testing conditions. Image processing analysis detects each droplet, decodes color codes, and measures the bacterial growth in the droplet. Testing E. coli ATCC 25922 with ampicillin, gentamicin, and tetracycline shows that the system can provide a robust and scalable platform for multiplexed AST. Furthermore, the system can be applied to various drug testing systems, which require several different testing conditions.

Original languageEnglish
Article number283
JournalBiosensors
Volume11
Issue number8
DOIs
StatePublished - Aug 2021

Keywords

  • Antibiotic resistance
  • Color code
  • Droplet
  • Image processing
  • Multiplexed

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