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Single-cell lipidomics with high structural specificity by mass spectrometry

Single-cell analysis is critical to revealing cell-to-cell heterogeneity that would otherwise be lost in ensemble analysis. Detailed lipidome characterization for single cells is still far from mature, especially when considering the highly complex structural diversity of lipids and the limited samp...

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Autores principales: Li, Zishuai, Cheng, Simin, Lin, Qiaohong, Cao, Wenbo, Yang, Jing, Zhang, Minmin, Shen, Aijun, Zhang, Wenpeng, Xia, Yu, Ma, Xiaoxiao, Ouyang, Zheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8129106/
https://www.ncbi.nlm.nih.gov/pubmed/34001877
http://dx.doi.org/10.1038/s41467-021-23161-5
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author Li, Zishuai
Cheng, Simin
Lin, Qiaohong
Cao, Wenbo
Yang, Jing
Zhang, Minmin
Shen, Aijun
Zhang, Wenpeng
Xia, Yu
Ma, Xiaoxiao
Ouyang, Zheng
author_facet Li, Zishuai
Cheng, Simin
Lin, Qiaohong
Cao, Wenbo
Yang, Jing
Zhang, Minmin
Shen, Aijun
Zhang, Wenpeng
Xia, Yu
Ma, Xiaoxiao
Ouyang, Zheng
author_sort Li, Zishuai
collection PubMed
description Single-cell analysis is critical to revealing cell-to-cell heterogeneity that would otherwise be lost in ensemble analysis. Detailed lipidome characterization for single cells is still far from mature, especially when considering the highly complex structural diversity of lipids and the limited sample amounts available from a single cell. We report the development of a general strategy enabling single-cell lipidomic analysis with high structural specificity. Cell fixation is applied to retain lipids in the cell during batch treatments prior to single-cell analysis. In addition to tandem mass spectrometry analysis revealing the class and fatty acyl-chain for lipids, batch photochemical derivatization and single-cell droplet treatment are performed to identify the C=C locations and sn-positions of lipids, respectively. Electro-migration combined with droplet-assisted electrospray ionization enables single-cell mass spectrometry analysis with easy operation but high efficiency in sample usage. Four subtypes of human breast cancer cells are correctly classified through quantitative analysis of lipid C=C location or sn-position isomers in ~160 cells. Most importantly, the single-cell deep lipidomics strategy successfully discriminates gefitinib-resistant cells from a population of wild-type human lung cancer cells (HCC827), highlighting its unique capability to promote precision medicine.
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spelling pubmed-81291062021-06-01 Single-cell lipidomics with high structural specificity by mass spectrometry Li, Zishuai Cheng, Simin Lin, Qiaohong Cao, Wenbo Yang, Jing Zhang, Minmin Shen, Aijun Zhang, Wenpeng Xia, Yu Ma, Xiaoxiao Ouyang, Zheng Nat Commun Article Single-cell analysis is critical to revealing cell-to-cell heterogeneity that would otherwise be lost in ensemble analysis. Detailed lipidome characterization for single cells is still far from mature, especially when considering the highly complex structural diversity of lipids and the limited sample amounts available from a single cell. We report the development of a general strategy enabling single-cell lipidomic analysis with high structural specificity. Cell fixation is applied to retain lipids in the cell during batch treatments prior to single-cell analysis. In addition to tandem mass spectrometry analysis revealing the class and fatty acyl-chain for lipids, batch photochemical derivatization and single-cell droplet treatment are performed to identify the C=C locations and sn-positions of lipids, respectively. Electro-migration combined with droplet-assisted electrospray ionization enables single-cell mass spectrometry analysis with easy operation but high efficiency in sample usage. Four subtypes of human breast cancer cells are correctly classified through quantitative analysis of lipid C=C location or sn-position isomers in ~160 cells. Most importantly, the single-cell deep lipidomics strategy successfully discriminates gefitinib-resistant cells from a population of wild-type human lung cancer cells (HCC827), highlighting its unique capability to promote precision medicine. Nature Publishing Group UK 2021-05-17 /pmc/articles/PMC8129106/ /pubmed/34001877 http://dx.doi.org/10.1038/s41467-021-23161-5 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Li, Zishuai
Cheng, Simin
Lin, Qiaohong
Cao, Wenbo
Yang, Jing
Zhang, Minmin
Shen, Aijun
Zhang, Wenpeng
Xia, Yu
Ma, Xiaoxiao
Ouyang, Zheng
Single-cell lipidomics with high structural specificity by mass spectrometry
title Single-cell lipidomics with high structural specificity by mass spectrometry
title_full Single-cell lipidomics with high structural specificity by mass spectrometry
title_fullStr Single-cell lipidomics with high structural specificity by mass spectrometry
title_full_unstemmed Single-cell lipidomics with high structural specificity by mass spectrometry
title_short Single-cell lipidomics with high structural specificity by mass spectrometry
title_sort single-cell lipidomics with high structural specificity by mass spectrometry
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8129106/
https://www.ncbi.nlm.nih.gov/pubmed/34001877
http://dx.doi.org/10.1038/s41467-021-23161-5
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