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Title: Single cell metabolite detection using inertial microfluidics-assisted ion mobility mass spectrometry
Authors: Zhang, Leicheng
Xu, Tengfei
Zhang, Jingtao
Wong, Stephen Choong Chee
Ritchie, Mark
Hou, Han Wei
Wang, Yulan
Keywords: Science::Medicine
Engineering::Mechanical engineering
Issue Date: 2021
Source: Zhang, L., Xu, T., Zhang, J., Wong, S. C. C., Ritchie, M., Hou, H. W. & Wang, Y. (2021). Single cell metabolite detection using inertial microfluidics-assisted ion mobility mass spectrometry. Analytical Chemistry, 93(30), 10462-10468.
Journal: Analytical Chemistry 
Abstract: Single-cell metabolite measurement remains highly challenging due to difficulties related to single cell isolation, metabolite detection, and identification of low levels of metabolites. Here, as a first step of the technological development, we propose a novel strategy integrating spiral inertial microfluidics and ion mobility mass spectrometry (IM-MS) for single-cell metabolite detection and identification. Cells in methanol suspension are inertially focused into a single stream in the spiral microchannel. This stream of separated cells is delivered to the nanoelectrospray needle to be lysed and ionized and subsequently analyzed in real time by IM-MS. This analytical system enables six to eight single-cell metabolic fingerprints to be collected per minute, including gas-phase collisional cross section (CCS) measurements as an additional molecular descriptor, giving increased confidence in metabolite identification. As a proof of concept, the metabolic profiles of three types of cancer cells (U2OS, HepG2, and HepG2.215) were successfully screened, and 19 distinct lipids species were identified with CCS value filtering. Furthermore, principal component analysis (PCA) showed differentiation of the three cancer cell lines, mainly due to cellular surface phospholipids. Taken together, our technology platform offers a simple and efficient method for single-cell lipid profiling, with additional ion mobility separation of lipids significantly improving the confidence toward identification of metabolites.
ISSN: 0003-2700
DOI: 10.1021/acs.analchem.1c00106
Schools: Lee Kong Chian School of Medicine (LKCMedicine) 
School of Mechanical and Aerospace Engineering 
School of Civil and Environmental Engineering 
Research Centres: Singapore Phenome Centre 
Rights: © 2021 American Chemical Society. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:CEE Journal Articles
LKCMedicine Journal Articles
MAE Journal Articles

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