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Single Cell Metabolite Detection Using Inertial Microfluidics-Assisted Ion Mobility Mass Spectrometry.
Zhang, Leicheng; Xu, Tengfei; Zhang, Jingtao; Wong, Stephen Choong Chee; Ritchie, Mark; Hou, Han Wei; Wang, Yulan.
Afiliación
  • Zhang L; Singapore Phenome Center, Lee Kong Chian School of Medicine, Nanyang Technological University, 639798 Singapore.
  • Xu T; School of Civil and Environmental Engineering, Nanyang Technological University, 639798 Singapore.
  • Zhang J; Singapore Phenome Center, Lee Kong Chian School of Medicine, Nanyang Technological University, 639798 Singapore.
  • Wong SCC; Waters Pacific Pte Ltd, Science Park 2, 117528 Singapore.
  • Ritchie M; Waters Pacific Pte Ltd, Science Park 2, 117528 Singapore.
  • Hou HW; Singapore Phenome Center, Lee Kong Chian School of Medicine, Nanyang Technological University, 639798 Singapore.
  • Wang Y; School of Mechanical & Aerospace Engineering, Nanyang Technological University, 639798 Singapore.
Anal Chem ; 93(30): 10462-10468, 2021 08 03.
Article en En | MEDLINE | ID: mdl-34289696
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.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Microfluídica / Espectrometría de Movilidad Iónica Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Anal Chem Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Microfluídica / Espectrometría de Movilidad Iónica Tipo de estudio: Diagnostic_studies Límite: Humans Idioma: En Revista: Anal Chem Año: 2021 Tipo del documento: Article