Extracellularly Detectable Electrochemical Signals of Living Cells Originate from Metabolic Reactions

  • Koo, K.-M.
  • Kim, C.-D.
  • Kim, H.
  • Cho, Y.-W.
  • Suhito, I.R.
  • ... Kim, Tae-Hyoung
Citations

WEB OF SCIENCE

17
Citations

SCOPUS

17

초록

Direct detection of cellular redox signals has shown immense potential as a novel living cell analysis tool. However, the origin of such signals remains unknown, which hinders the widespread use of electrochemical methods for cellular research. In this study, the authors found that intracellular metabolic pathways that generate adenosine triphosphate (ATP) are the main contributors to extracellularly detectable electrochemical signals. This is achieved through the detection of living cells (4,706 cells/chip, linearity: 0.985) at a linear range of 7,466–48,866. Based on this discovery, the authors demonstrated that the cellular signals detected by differential pulse voltammetry (DPV) can be rapidly amplified with a developed medium containing metabolic activator cocktails (MACs). The DPV approach combined with MAC treatment shows a remarkable performance to detect the effects of the anticancer drug CPI-613 on cervical cancer both at a low drug concentration (2 µm) and an extremely short treatment time (1 hour). Furthermore, the senescence of mesenchymal stem cells could also be sensitively quantified using the DPV+MAC method even at a low passage number (P6). Collectively, their findings unveiled the origin of redox signals in living cells, which has important implications for the characterization of various cellular functions and behaviors using electrochemical approaches. © 2023 The Authors. Advanced Science published by Wiley-VCH GmbH.

키워드

drug screeningelectrochemical detectionlive cell sensingmetabolic reactionstem cell senescence
제목
Extracellularly Detectable Electrochemical Signals of Living Cells Originate from Metabolic Reactions
저자
Koo, K.-M.Kim, C.-D.Kim, H.Cho, Y.-W.Suhito, I.R.Kim, Tae-Hyoung
DOI
10.1002/advs.202207084
발행일
2023-03
유형
Article
저널명
Advanced Science
10
9