Scientific Reports (Feb 2023)

Red cabbage extract-mediated colorimetric sensor for swift, sensitive and economic detection of urease-positive bacteria by naked eye and Smartphone platform

  • Cagla Celik,
  • Naim Yagiz Demir,
  • Memed Duman,
  • Nilay Ildiz,
  • Ismail Ocsoy

DOI
https://doi.org/10.1038/s41598-023-28604-1
Journal volume & issue
Vol. 13, no. 1
pp. 1 – 10

Abstract

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Abstract The bacterial pathogens have caused various serious infectious diseases in the human body, and even some threats to human life by leading to deaths. Enterobacteriaceae species especially urease positive ones, Proteus mirabilis (P. mirabilis) and Klebsiella pneumoniae (K. pneumoniae), show resistance to antibiotics and cause respiratory and urinary tract infections. We have developed natural indicator-incorporated colorimetric urease tests with a naked eye and smartphone readout to rapidly, sensitively and economically detect P. mirabilis and K. pneumoniae. We utilized anthocyanin found as a predominant component in red cabbage (Brassica oleracea) extract as a natural pH indicator instead of toxic and synthetic indicators. As a mechanistic explanation for the detection of P. mirabilis and K. pneumoniae, urease enzymes secreted from the P. mirabilis and K. pneumoniae hydrolyze urea to produce ammonia (NH3), which increases the pH value of the reaction environment and leads to deprotonation from anthocyanins. The changes in the molecular structure and electronic structure of anthocyanins are responsible for revealing many different colors. We demonstrated how some reaction parameters including the concentration of the bacteria (colony-forming unit, CFU), the concentration of anthocyanin in the tests, initial color and pH values (pHs) of the tests influence their detection performance. We further developed a 3D-printed smartphone platform with smartphone based digital image processing software to improve the detection limit and shorten the detection time. We claim that natural indicator-incorporated rapid urease tests providing colorimetric readout evaluated by the human eye and smartphone imaging processing has great potential in practical use and they can be implemented in clinics.