journal article·2024-11Open access

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

Fugang Liu, Jiaqing Liu, Yang Luo, Siyi Wu, Xu Liu, Haoran Chen, Zhewen Luo, Haitao Yuan, Feng Shen, Fangfang Zhu, Jian Ye

Advanced Science· Volume 11· Issue 41

Abstract

Abstract 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.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Biosensors and Analytical Detection · CRISPR and Genetic Engineering · Gold and Silver Nanoparticles Synthesis and Applications

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Biomedical Engineering Shanghai Jiao Tong University Shanghai 200030 China

State Key Laboratory of Systems Medicine for Cancer Shanghai Cancer Institute Ren Ji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200032 China

Institute of Medical Robotics Shanghai Jiao Tong University Shanghai 200240 China

Shanghai Key Laboratory of Gynecologic Oncology Ren Ji Hospital School of Medicine Shanghai Jiao Tong University Shanghai 200127 China

Funding

National Natural Science Foundation of China · Shanghai Jiao Tong University

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