1. Academic Validation
  2. Metabolic Footprinting-Based DNA-AuNP Encoders for Extracellular Metabolic Response Profiling

Metabolic Footprinting-Based DNA-AuNP Encoders for Extracellular Metabolic Response Profiling

  • Anal Chem. 2023 May 8. doi: 10.1021/acs.analchem.3c01109.
Guangpei Qi 1 Haixia Zou 1 Xiaohong Peng 2 Shiliang He 3 Qiqi Zhang 1 Wei Ye 1 Yizhou Jiang 1 Wentao Wang 1 Guangli Ren 4 Xiangmeng Qu 1
Affiliations

Affiliations

  • 1 Key Laboratory of Sensing Technology and Biomedical Instruments of Guangdong Province and School of Biomedical Engineering, Sun Yat-Sen University, Shenzhen 518107, China.
  • 2 YueYang Central Hospital, YueYang 414000, China.
  • 3 College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen 518118, China.
  • 4 Department of Pediatrics, General Hospital of Southern Theater Command of PLA, Guangzhou 510010, China.
Abstract

Metabolic footprinting as a convenient and non-invasive cell metabolomics strategy relies on monitoring the whole extracellular metabolic process. It covers nutrient consumption and metabolite secretion of in vitro Cell Culture, which is hindered by low universality owing to pre-treatment of the cell medium and special equipment. Here, we report the design and a variety of applicability, for quantifying extracellular metabolism, of fluorescently labeled single-stranded DNA (ssDNA)-AuNP encoders, whose multi-modal signal response is triggered by extracellular metabolites. We constructed metabolic response profiling of cells by detecting extracellular metabolites in different tumor cells and drug-induced extracellular metabolites. We further assessed the extracellular metabolism differences using a machine learning algorithm. This metabolic response profiling based on the DNA-AuNP encoder strategy is a powerful complement to metabolic footprinting, which significantly applies potential non-invasive identification of tumor cell heterogeneity.

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