Single-cell multi-element analysis reveals element distribution pattern in human sperm.
Xiangwei TianXun LiNian LiuWenbin CuiLingna ZhengYingying GuoYanwei LiuLi-Gang HuMeng WangYong LiangYongguang YinYong CaiGuibin JiangLei JinPublished in: Chemical communications (Cambridge, England) (2023)
Multiple elements in human sperm have been demonstrated to play significant roles in the reproductive process, but their simultaneous detection in single cells remains challenging. We propose a novel analytical procedure using single-cell inductively coupled plasma-time of flight-mass spectrometry (scICP-TOF-MS) to simultaneously quantify multiple elements of individual sperm cells. A promising label-free cell identification strategy based on the endogenous element was developed to obtain valid data. The element contents exhibited varied degrees of heterogeneity in single cells. Machine learning-based analysis of the multi-dimension dataset indicated different distribution patterns and physiological roles among the simultaneously detected elements.
Keyphrases
- single cell
- induced apoptosis
- label free
- cell cycle arrest
- machine learning
- rna seq
- high throughput
- endoplasmic reticulum stress
- oxidative stress
- signaling pathway
- cell death
- electronic health record
- high performance liquid chromatography
- mesenchymal stem cells
- cell therapy
- minimally invasive
- pi k akt
- artificial intelligence
- real time pcr