Single Cell mass spectrometry: Towards quantification of small molecules in individual cells

Lan, Yunpeng; Zou, Zhu; Yang, Zhibo

doi:10.1016/j.trac.2024.117657

TrAC Trends in Analytical Chemistry

2024

DOI: 10.1016/j.trac.2024.117657

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Single Cell mass spectrometry: Towards quantification of small molecules in individual cells

Yunpeng Lan,

Zhu Zou,

Zhibo Yang

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2024

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Cited by 8 publications

References 188 publications

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A Single‐Cell Metabolic Profiling Characterizes Human Aging via SlipChip‐SERS

Liu,

Luo

et al. 2024

Advanced Science

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Metabolic dysregulation is a key driver of cellular senescence, contributing to the progression of systemic aging. The heterogeneity of senescent cells and their metabolic shifts are complex and unexplored. A microfluidic SlipChip integrated with surface‐enhanced Raman spectroscopy (SERS), termed SlipChip‐SERS, is developed for single‐cell metabolism analysis. This SlipChip‐SERS enables compartmentalization of single cells, parallel delivery of saponin and nanoparticles to release intracellular metabolites and to realize SERS detection with simple slipping operations. Analysis of different cancer cell lines using SlipChip‐SERS demonstrated its capability for sensitive and multiplexed metabolic profiling of individual cells. When applied to human primary fibroblasts of different ages, it identified 12 differential metabolites, with spermine validated as a potent inducer of cellular senescence. Prolonged exposure to spermine can induce a classic senescence phenotype, such as increased senescence‐associated β‐glactosidase activity, elevated expression of senescence‐related genes and reduced LMNB1 levels. Additionally, the senescence‐inducing capacity of spermine in HUVECs and WRL‐68 cells is confirmed, and exogenous spermine treatment increased the accumulation and release of H2O2. Overall, a novel SlipChip‐SERS system is developed for single‐cell metabolic analysis, revealing spermine as a potential inducer of senescence across multiple cell types, which may offer new strategies for addressing ageing and ageing‐related diseases.

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A Single‐Cell Metabolic Profiling Characterizes Human Aging via SlipChip‐SERS

Liu,

Luo

et al. 2024

Advanced Science

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Single‐Cell Simultaneous Metabolome and Transcriptome Profiling Revealing Metabolite‐Gene Correlation Network

Mao,

Xia,

et al. 2024

Advanced Science

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Metabolic studies at the single cell level can directly define the cellular phenotype closest to physiological or disease states. However, the current single cell metabolome (SCM) study using mass spectroscopy has difficulty giving a complete view of the metabolic activity in the cell, and the prediction of the metabolism‐phenotype relationship is limited by the potential inconsistency between transcriptomic and metabolic levels. Here, the single‐cell simultaneous metabolome and transcriptome profiling method (scMeT‐seq) is developed at one single cell, based on sub‐picoliter sampling from the cell for the initial metabolome profiling followed by single cell transcriptome sequencing. This design not only provides sufficient cytoplasm for SCM but also nicely keeps the cellular viability for the accurate transcriptomic analysis in the same cell. Integrative analysis of scMeT‐seq reveals both dynamical and cell state‐specific associations between metabolome and transcriptome in the macrophages with defined metabolic perturbations. Moreover, metabolite signatures are mapped to the single‐cell trajectory and gene correlation network of macrophage transition, which allows the unsupervised functional interpretation of metabolome. Thus, the established scMeT‐seq should lead to a new perspective in metabolic research by transforming metabolomics from a metabolite snapshot to a functional approach.

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Metabolomics‐driven approaches for identifying therapeutic targets in drug discovery

Pan,

Yin,

Liu

et al. 2024

MedComm

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Identification of therapeutic targets can directly elucidate the mechanism and effect of drug therapy, which is a central step in drug development. The disconnect between protein targets and phenotypes under complex mechanisms hampers comprehensive target understanding. Metabolomics, as a systems biology tool that captures phenotypic changes induced by exogenous compounds, has emerged as a valuable approach for target identification. A comprehensive overview was provided in this review to illustrate the principles and advantages of metabolomics, delving into the application of metabolomics in target identification. This review outlines various metabolomics‐based methods, such as dose–response metabolomics, stable isotope‐resolved metabolomics, and multiomics, which identify key enzymes and metabolic pathways affected by exogenous substances through dose‐dependent metabolite–drug interactions. Emerging techniques, including single‐cell metabolomics, artificial intelligence, and mass spectrometry imaging, are also explored for their potential to enhance target discovery. The review emphasizes metabolomics' critical role in advancing our understanding of disease mechanisms and accelerating targeted drug development, while acknowledging current challenges in the field.

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Single Cell mass spectrometry: Towards quantification of small molecules in individual cells

Cited by 8 publications

References 188 publications

A Single‐Cell Metabolic Profiling Characterizes Human Aging via SlipChip‐SERS

A Single‐Cell Metabolic Profiling Characterizes Human Aging via SlipChip‐SERS

Single‐Cell Simultaneous Metabolome and Transcriptome Profiling Revealing Metabolite‐Gene Correlation Network

Metabolomics‐driven approaches for identifying therapeutic targets in drug discovery

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