Single Cell Mass Spectrometry With a Robotic Micromanipulation System for Cell Metabolite Analysis

被引:14
作者
Chen, Anqi [1 ,2 ]
Yan, Mingyue [1 ,2 ]
Feng, Jiaxin [3 ]
Bi, Lei [1 ,2 ]
Chen, La [1 ,2 ]
Hu, Shundi [1 ,2 ]
Hong, Huanhuan [1 ,2 ]
Shi, Lulu [1 ,2 ]
Li, Gangqiang [1 ,2 ]
Jin, Baiye [4 ]
Zhang, Xinrong [3 ]
Wen, Luhong [1 ,2 ]
机构
[1] Ningbo Univ, Res Inst Adv Technol, Ningbo 315211, Zhejiang, Peoples R China
[2] China Innovat Instrument Co Ltd, Ningbo 315000, Zhejiang, Peoples R China
[3] Tsinghua Univ, Dept Chem, Beijing 100084, Peoples R China
[4] Zhejiang Univ, Affiliated Hosp 1, Sch Med, Dept Urol, Hangzhou, Zhejiang, Peoples R China
基金
中国国家自然科学基金;
关键词
Single cell mass spectrometry; metabolic profiling; robotic micromanipulation; sub nano-liter extraction; MS2; analysis;
D O I
10.1109/TBME.2021.3093097
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Objective: The increasing demand for unraveling cellular heterogeneity has boosted single cell metabolomics studies. However, current analytical methods are usually labor-intensive and hampered by lack of accuracy and efficiency. Methods: we developed a first-ever automated single cell mass spectrometry system (named SCMS) that facilitated the metabolic profiling of single cells. In particular, extremely small droplets of sub nano-liter were generated to extract the single cells, and the underlying mechanism was verified theoretically and experimentally. This was crucial to minimize the dilution of the trace cellular contents and enhance the analytical sensitivity. Based on the precise 3D positioning of the pipette tip, we established a visual servoing robotic micromanipulation platform on which single cells were sequentially extracted, aspirated, and ionized, followed by the mass spectrometry analyses. Results: With the SCMS system, inter-operator variability was eliminated and working efficiency was improved. The performance of the SCMS system was validated by the experiments on bladder cancer cells. MS and MS2 analyses of single cells enable us to identify several cellular metabolites and the underlying inter-cell heterogeneity. Conclusion: In contrast to traditional methods, the SCMS system functions without human intervention realizes a robust single cell metabolic analysis. Significance: the SCMS system upgrades the way how single cell metabolites were analyzed, and has the potential to be a powerful tool for single cell metabolomics studies.
引用
收藏
页码:325 / 333
页数:9
相关论文
共 33 条
[1]   Potent Neutralizing Antibodies against SARS-CoV-2 Identified by High-Throughput Single-Cell Sequencing of Convalescent Patients' B Cells [J].
Cao, Yunlong ;
Su, Bin ;
Guo, Xianghua ;
Sun, Wenjie ;
Deng, Yongqiang ;
Bao, Linlin ;
Zhu, Qinyu ;
Zhang, Xu ;
Zheng, Yinghui ;
Geng, Chenyang ;
Chai, Xiaoran ;
He, Runsheng ;
Li, Xiaofeng ;
Lv, Qi ;
Zhu, Hua ;
Deng, Wei ;
Xu, Yanfeng ;
Wang, Yanjun ;
Qiao, Luxin ;
Tan, Yafang ;
Song, Liyang ;
Wang, Guopeng ;
Du, Xiaoxia ;
Gao, Ning ;
Liu, Jiangning ;
Xiao, Junyu ;
Su, Xiao-dong ;
Du, Zongmin ;
Feng, Yingmei ;
Qin, Chuan ;
Qin, Chengfeng ;
Jin, Ronghua ;
Xie, X. Sunney .
CELL, 2020, 182 (01) :73-+
[2]   Detection of Urothelial Bladder Carcinoma via Microfluidic Immunoassay and Single-Cell DNA Copy-Number Alteration Analysis of Captured Urinary-Exfoliated Tumor Cells [J].
Chen, Anqi ;
Fu, Guanghou ;
Xu, Zhijie ;
Sun, Yukun ;
Chen, Xiaoyi ;
Cheng, Kok Suen ;
Neoh, Kuang Hong ;
Tang, Zhewen ;
Chen, Shifu ;
Liu, Ming ;
Huang, Tanxiao ;
Dai, Yun ;
Wang, Qibo ;
Jin, Jing ;
Jin, Baiye ;
Han, Ray P. S. .
CANCER RESEARCH, 2018, 78 (14) :4073-4085
[3]   Advances in mass spectrometry based single-cell metabolomics [J].
Duncan, Kyle D. ;
Fyrestam, Jonas ;
Lanekoff, Ingela .
ANALYST, 2019, 144 (03) :782-793
[4]   Single-cell transcriptome analysis reveals cell lineage specification in temporal-spatial patterns in human cortical development [J].
Fan, Xiaoying ;
Fu, Yuanyuan ;
Zhou, Xin ;
Sun, Le ;
Yang, Ming ;
Wang, Mengdi ;
Chen, Ruiguo ;
Wu, Qian ;
Yong, Jun ;
Dong, Ji ;
Wen, Lu ;
Qiao, Jie ;
Wan, Xiaoqun ;
Tang, Fuchou .
SCIENCE ADVANCES, 2020, 6 (34)
[5]   Mannose Promotes Metabolic Discrimination Osteosarcoma Cells at Single-Cell Level by Mass Spectrometry [J].
Fang, Zhuyin ;
Wang, Ruihua ;
Zhao, Hansen ;
Yao, Huan ;
Ouyang, Jin ;
Zhang, Xinrong .
ANALYTICAL CHEMISTRY, 2020, 92 (03) :2690-2696
[6]   Quantitation of Glucose-phosphate in Single Cells by Microwell-Based Nanoliter Droplet Microextraction and Mass Spectrometry [J].
Feng, Jiaxin ;
Zhang, Xiaochao ;
Huang, Liang ;
Yao, Huan ;
Yang, Chengdui ;
Ma, Xiaoxiao ;
Zhang, Sichun ;
Zhang, Xinrong .
ANALYTICAL CHEMISTRY, 2019, 91 (09) :5613-5620
[7]   MassBank: a public repository for sharing mass spectral data for life sciences [J].
Horai, Hisayuki ;
Arita, Masanori ;
Kanaya, Shigehiko ;
Nihei, Yoshito ;
Ikeda, Tasuku ;
Suwa, Kazuhiro ;
Ojima, Yuya ;
Tanaka, Kenichi ;
Tanaka, Satoshi ;
Aoshima, Ken ;
Oda, Yoshiya ;
Kakazu, Yuji ;
Kusano, Miyako ;
Tohge, Takayuki ;
Matsuda, Fumio ;
Sawada, Yuji ;
Hirai, Masami Yokota ;
Nakanishi, Hiroki ;
Ikeda, Kazutaka ;
Akimoto, Naoshige ;
Maoka, Takashi ;
Takahashi, Hiroki ;
Ara, Takeshi ;
Sakurai, Nozomu ;
Suzuki, Hideyuki ;
Shibata, Daisuke ;
Neumann, Steffen ;
Iida, Takashi ;
Tanaka, Ken ;
Funatsu, Kimito ;
Matsuura, Fumito ;
Soga, Tomoyoshi ;
Taguchi, Ryo ;
Saito, Kazuki ;
Nishioka, Takaaki .
JOURNAL OF MASS SPECTROMETRY, 2010, 45 (07) :703-714
[8]   Genomic and Transcriptomic Landscape of Triple-Negative Breast Cancers: Subtypes and Treatment Strategies [J].
Jiang, Yi-Zhou ;
Ma, Ding ;
Suo, Chen ;
Shi, Jinxiu ;
Xue, Mengzhu ;
Hu, Xin ;
Xiao, Yi ;
Yu, Ke-Da ;
Liu, Yi-Rong ;
Yu, Ying ;
Zheng, Yuanting ;
Li, Xiangnan ;
Zhang, Chenhui ;
Hu, Pengchen ;
Zhang, Jing ;
Hua, Qi ;
Zhang, Jiyang ;
Hou, Wanwan ;
Ren, Luyao ;
Bao, Ding ;
Li, Bingying ;
Yang, Jingcheng ;
Yao, Ling ;
Zuo, Wen-Jia ;
Zhao, Shen ;
Gong, Yue ;
Ren, Yi-Xing ;
Zhao, Ya-Xin ;
Yang, Yun-Song ;
Niu, Zhenmin ;
Cao, Zhi-Gang ;
Stover, Daniel G. ;
Verschraegen, Claire ;
Kaklamani, Virginia ;
Daemen, Anneleen ;
Benson, John R. ;
Takabe, Kazuaki ;
Bai, Fan ;
Li, Da-Qiang ;
Wang, Peng ;
Shi, Leming ;
Huang, Wei ;
Shao, Zhi-Ming .
CANCER CELL, 2019, 35 (03) :428-+
[9]   Single-Cell Multiomics: Multiple Measurements from Single Cells [J].
Macaulay, Iain C. ;
Ponting, Chris P. ;
Voet, Thierry .
TRENDS IN GENETICS, 2017, 33 (02) :155-168
[10]   Therapy-Induced Evolution of Human Lung Cancer Revealed by Single-Cell RNA Sequencing [J].
Maynard, Ashley ;
McCoach, Caroline E. ;
Rotow, Julia K. ;
Harris, Lincoln ;
Haderk, Franziska ;
Kerr, D. Lucas ;
Yu, Elizabeth A. ;
Schenk, Erin L. ;
Tan, Weilun ;
Zee, Alexander ;
Tan, Michelle ;
Gui, Philippe ;
Lea, Tasha ;
Wu, Wei ;
Urisman, Anatoly ;
Jones, Kirk ;
Sit, Rene ;
Kolli, Pallav K. ;
Seeley, Eric ;
Gesthalter, Yaron ;
Le, Daniel D. ;
Yamauchi, Kevin A. ;
Naeger, David M. ;
Bandyopadhyay, Sourav ;
Shah, Khyati ;
Cech, Lauren ;
Thomas, Nicholas J. ;
Gupta, Anshal ;
Gonzalez, Mayra ;
Do, Hien ;
Tan, Lisa ;
Bacaltos, Bianca ;
Gomez-Sjoberg, Rafael ;
Gubens, Matthew ;
Jahan, Thierry ;
Kratz, Johannes R. ;
Jablons, David ;
Neff, Norma ;
Doebele, Robert C. ;
Weissman, Jonathan ;
Blakely, Collin M. ;
Darmanis, Spyros ;
Bivona, Trever G. .
CELL, 2020, 182 (05) :1232-+