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  2. Viability-Informed Single-Cell Mass Spectrometry for More Comprehensive Metabolic Analysis

Viability-Informed Single-Cell Mass Spectrometry for More Comprehensive Metabolic Analysis

  • Anal Chem. 2026 Feb 10;98(5):4213-4221. doi: 10.1021/acs.analchem.5c07083.
Simin Cheng 1 Danni Wu 1 2 Xinxin Wang 3 Siyuan Tan 1 Lulu Feng 1 Xiaoping Yu 2 Xiaoyun Gong 1 Xinhua Dai 1
Affiliations

Affiliations

  • 1 Technology Innovation Center of Mass Spectrometry for State Market Regulation, Center for Advanced Measurement Science, National Institute of Metrology, Beijing 100029, China.
  • 2 College of Life Sciences, China Jiliang University, Hangzhou 310018, China.
  • 3 Faculty of Medicine, Dalian University of Technology, Dalian 116024, China.
Abstract

The viability of cells is a key indicator of cellular function and physiological integrity. There are great metabolic differences between live and dead cells. However, most mass spectrometric metabolic studies overlook this issue, leading to a potential misunderstanding of biological systems. Here, we propose the development of a high-throughput and label-free viability-informed single-cell mass spectrometry (ViSCMS) technique for the simultaneous measurement of cell viability and metabolic profiles. The signal of phosphocholine (PC) 34:1 was used for the confirmation of cell events. Glutathione (GSH) was identified as an intrinsic marker to further accurately distinguish live and dead cells. The viability rates obtained by ViSCMS were in good concordance with those of conventional AO/PI staining (mean bias: 0.33%). Excellent reproducibility (SD < 3%) was achieved across multiple cell lines with varied viability rates. The practicality of the method was demonstrated by the successful subtyping of six colorectal Cancer (CRC) cell lines. The subtyping could only be achieved when the viability of cells was taken into consideration. Furthermore, clear viability-dependent metabolic differences were observed on HCT116 cells when treated with an Anticancer drug. The results provided insights into how tumor cells adapt to chemotherapy stress at the single-cell level.

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