In-depth organic mass cytometry reveals differential contents of 3-hydroxybutanoic acid at the single-cell level.
Shaojie QinYi ZhangMingying ShiDaiyu MiaoJiansen LuLu WenYu BaiPublished in: Nature communications (2024)
Comprehensive single-cell metabolic profiling is critical for revealing phenotypic heterogeneity and elucidating the molecular mechanisms underlying biological processes. However, single-cell metabolomics remains challenging because of the limited metabolite coverage and inability to discriminate isomers. Herein, we establish a single-cell metabolomics platform for in-depth organic mass cytometry. Extended single-cell analysis time guarantees sufficient MS/MS acquisition for metabolite identification and the isomers discrimination while online sampling ensures the high-throughput of the method. The largest number of identified metabolites (approximately 600) are achieved in single cells and fine subtyping of MCF-7 cells is first demonstrated by an investigation on the differential levels of 3-hydroxybutanoic acid among clusters. Single-cell transcriptome analysis reveals differences in the expression of 3-hydroxybutanoic acid downstream antioxidative stress genes, such as metallothionein 2 (MT2A), while a fluorescence-activated cell sorting assay confirms the positive relationship between 3-hydroxybutanoic acid and target proteins; these results suggest that the heterogeneity of 3-hydroxybutanoic acid provides cancer cells with different ability to resist surrounding oxidative stress. Our method paves the way for deep single-cell metabolome profiling and investigations on the physiological and pathological processes that occur during cancer.
Keyphrases
- single cell
- high throughput
- rna seq
- induced apoptosis
- ms ms
- oxidative stress
- mass spectrometry
- cell cycle arrest
- squamous cell carcinoma
- poor prognosis
- healthcare
- social media
- endoplasmic reticulum stress
- high resolution
- papillary thyroid
- single molecule
- gene expression
- stress induced
- ischemia reperfusion injury
- anti inflammatory
- bioinformatics analysis