4.7 Article

Color-Coded Droplets and Microscopic Image Analysis for Multiplexed Antibiotic Susceptibility Testing

期刊

BIOSENSORS-BASEL
卷 11, 期 8, 页码 -

出版社

MDPI
DOI: 10.3390/bios11080283

关键词

droplet; color code; antibiotic resistance; image processing; multiplexed

资金

  1. National Research Foundation of Korea (NRF) - Korean government [NRF-2019R1C1C1009326, 2021R1I1A1A01058783, 2019R1A2C1084419]
  2. BK21 FOUR program of the Education and Research Program for Future ICT Pioneers, Seoul National University
  3. Ministry of Science and ICT (MSIT) [2020M3H1A1073304]
  4. Global Research Development Center Program through the NRF - Ministry of Science and ICT (MSIT) [2015K1A4A3047345]
  5. Ministry of Science and ICT (MSIT) of the Republic of Korea
  6. National Research Foundation of Korea [NRF-2020R1A3B3079653]
  7. National Research Foundation of Korea [2019R1A2C1084419, 2021R1I1A1A01058783] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

The emergence of antibiotic resistance is a global issue threatening society. Using color-coded droplets to expand the multiplexing of AST can differentiate the type and concentration of antibiotics, providing a robust and scalable platform for testing multiple conditions efficiently. The system can be applied to various drug testing systems, showing promising results for future applications.
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.

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