Polarity-Specific Profiling of Metabolites in Single Cells by Probe Electrophoresis Mass Spectrometry.
Lili SongKonstantin ChinginMeng WangDacai ZhongHuanwen ChenJia-Quan XuPublished in: Analytical chemistry (2022)
Sensitive analysis of metabolites in a single cell is of fundamental significance for the better understanding of biological variability, differential susceptibility in disease therapy, and cell-to-cell heterogeneity as well. Herein, polarity-specific profiling of metabolites in a single cell was implemented by probe electrophoresis mass spectrometry (PEMS), which combined electrophoresis sampling of metabolites from a single cell and nanoelectrospray ionization-mass spectrometry (nanoESI-MS) analysis of the sampled metabolites. Enhanced extraction of either negatively or positively charged metabolites from a single cell was achieved by applying a DC voltage offset of +2.0 and -2.0 V to the probe, respectively. The experimental data demonstrated that PEMS features high throughput (≥200 peaks) and high sensitivity (≥10-times signal enhancement for [Choline + H] + , [Glutamine + H] + , [Arginine + H] + , etc.) in comparison with direct nanoESI-MS analysis. The biological effects of CdSe quantum dots (QDs) and γ-radiation on Allium cepa cells were investigated by PEMS, which revealed that CdSe QDs lead to the increase of intracellular amines while γ-radiation causes the decrease of intracellular acids. Therefore, this work provides an alternative platform to probe novel insights of cells by sensitive analysis of polarity-specific metabolites in a single cell.
Keyphrases
- single cell
- quantum dots
- ms ms
- high throughput
- mass spectrometry
- rna seq
- induced apoptosis
- cell cycle arrest
- liquid chromatography
- gas chromatography
- sensitive detection
- living cells
- high resolution
- high performance liquid chromatography
- nitric oxide
- capillary electrophoresis
- endoplasmic reticulum stress
- signaling pathway
- cell death
- stem cells
- radiation therapy
- mesenchymal stem cells
- immune response
- reactive oxygen species
- electronic health record
- artificial intelligence
- bone marrow
- big data
- atomic force microscopy