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Wevers D, Ramautar R, Clark C, Hankemeier T, Ali A. Opportunities and challenges for sample preparation and enrichment in mass spectrometry for single-cell metabolomics. Electrophoresis 2023; 44:2000-2024. [PMID: 37667867 DOI: 10.1002/elps.202300105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 08/08/2023] [Accepted: 08/19/2023] [Indexed: 09/06/2023]
Abstract
Single-cell heterogeneity in metabolism, drug resistance and disease type poses the need for analytical techniques for single-cell analysis. As the metabolome provides the closest view of the status quo in the cell, studying the metabolome at single-cell resolution may unravel said heterogeneity. A challenge in single-cell metabolome analysis is that metabolites cannot be amplified, so one needs to deal with picolitre volumes and a wide range of analyte concentrations. Due to high sensitivity and resolution, MS is preferred in single-cell metabolomics. Large numbers of cells need to be analysed for proper statistics; this requires high-throughput analysis, and hence automation of the analytical workflow. Significant advances in (micro)sampling methods, CE and ion mobility spectrometry have been made, some of which have been applied in high-throughput analyses. Microfluidics has enabled an automation of cell picking and metabolite extraction; image recognition has enabled automated cell identification. Many techniques have been used for data analysis, varying from conventional techniques to novel combinations of advanced chemometric approaches. Steps have been set in making data more findable, accessible, interoperable and reusable, but significant opportunities for improvement remain. Herein, advances in single-cell analysis workflows and data analysis are discussed, and recommendations are made based on the experimental goal.
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Affiliation(s)
- Dirk Wevers
- Wageningen University and Research, Wageningen, The Netherlands
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Rawi Ramautar
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Charlie Clark
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Thomas Hankemeier
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
| | - Ahmed Ali
- Metabolomics and Analytics Centre, Leiden Academic Centre for Drug Research, Leiden, The Netherlands
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Hakoda H, Kiritani S, Kokudo T, Yoshimura K, Iwano T, Tanimoto M, Ishizawa T, Arita J, Akamatsu N, Kaneko J, Takeda S, Hasegawa K. Probe electrospray ionization mass spectrometry-based rapid diagnosis of liver tumors. J Gastroenterol Hepatol 2022; 37:2182-2188. [PMID: 35945170 DOI: 10.1111/jgh.15976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Revised: 07/28/2022] [Accepted: 08/03/2022] [Indexed: 12/09/2022]
Abstract
BACKGROUND AND AIM Prompt differential diagnosis of liver tumors is clinically important and sometimes difficult. A new diagnostic device that combines probe electrospray ionization-mass spectrometry (PESI-MS) and machine learning may help provide the differential diagnosis of liver tumors. METHODS We evaluated the diagnostic accuracy of this new PESI-MS device using tissues obtained and stored from previous surgically resected specimens. The following cancer tissues (with collection dates): hepatocellular carcinoma (HCC, 2016-2019), intrahepatic cholangiocellular carcinoma (ICC, 2014-2019), and colorectal liver metastasis (CRLM, 2014-2019) from patients who underwent hepatic resection were considered for use in this study. Non-cancerous liver tissues (NL) taken from CRLM cases were also incorporated into the analysis. Each mass spectrum provided by PESI-MS was tested using support vector machine, a type of machine learning, to evaluate the discriminatory ability of the device. RESULTS In this study, we used samples from 91 of 139 patients with HCC, all 24 ICC samples, and 103 of 202 CRLM samples; 80 NL from CRLM cases were also used. Each mass spectrum was obtained by PESI-MS in a few minutes and was evaluated by machine learning. The sensitivity, specificity, and diagnostic accuracy of the PESI-MS device for discriminating HCC, ICC, and CRLM from among a mix of all three tumors and from NL were 98.9%, 98.1%, and 98.3%; 87.5%, 93.1%, and 92.6%; and 99.0%, 97.9%, and 98.3%, respectively. CONCLUSION This study demonstrated that PESI-MS and machine learning could discriminate liver tumors accurately and rapidly.
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Affiliation(s)
- Hiroyuki Hakoda
- Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Sho Kiritani
- Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Takashi Kokudo
- Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Kentaro Yoshimura
- Department of Anatomy and Cell Biology, Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, Yamanashi, Japan
| | - Tomohiko Iwano
- Department of Anatomy and Cell Biology, Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, Yamanashi, Japan
| | - Meguri Tanimoto
- Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Takeaki Ishizawa
- Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Junichi Arita
- Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Nobuhisa Akamatsu
- Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Junichi Kaneko
- Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Sen Takeda
- Department of Anatomy and Cell Biology, Interdisciplinary Graduate School of Medicine and Engineering, University of Yamanashi, Yamanashi, Japan.,Department of Anatomy, Teikyo University School of Medicine, Tokyo, Japan
| | - Kiyoshi Hasegawa
- Hepato-Biliary-Pancreatic Surgery Division, Department of Surgery, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
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Fukuhara S, Iwasaki E, Iwano T, Machida Y, Tamagawa H, Kawasaki S, Seino T, Yokose T, Endo Y, Yoshimura K, Kashiwagi K, Kitago M, Ogata H, Takeda S, Kanai T. New strategy for evaluating pancreatic tissue specimens from endoscopic ultrasound-guided fine needle aspiration and surgery. JGH OPEN 2021; 5:953-958. [PMID: 34386605 PMCID: PMC8341188 DOI: 10.1002/jgh3.12617] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Revised: 07/03/2021] [Accepted: 07/07/2021] [Indexed: 01/07/2023]
Abstract
Background and Aim Preoperative histological evaluation of pancreatic neoplasms is important for guiding the resection strategy and preventing postoperative adverse events. However, conventional endoscopic methods have technical limitations that reduce the accuracy of the histopathological examination. Probe electrospray ionization mass spectrometry (PESI‐MS) may be a useful technique for rapidly evaluating small specimens. Methods This single‐center prospective study included patients with pancreatic neoplasms between October 2018 and December 2019. Pancreatic ductal adenocarcinoma (PDAC) specimens were obtained via endoscopic ultrasound‐guided fine needle aspiration (EUS‐FNA) and non‐neoplastic tissue was obtained via surgery. Specimens were subjected to PESI‐MS and the mass spectra were analyzed using partial least squares regression‐discriminant analysis. Results The study included 40 patients with 20 nonneoplastic specimens and 19 PDAC specimens (1 case of neuroendocrine carcinoma was omitted). All nonneoplastic specimens were sufficient for PESI‐MS analysis, although only 7 of 19 PDAC specimens were sufficient for PESI‐MS analysis because of poor sample quality or insufficient quantity (<1 mg). Among the 27 analyzed cases, the mass spectra clearly differentiated between the PDAC and nonneoplastic specimens. Conclusions This study revealed that PESI‐MS could differentiate between PDAC and nonneoplastic specimens, even in cases where EUS‐FNA produced very small specimens.
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Affiliation(s)
- Seiichiro Fukuhara
- Center for Diagnostic and Therapeutic Endoscopy Keio University School of Medicine Tokyo Japan
| | - Eisuke Iwasaki
- Division of Gastroenterology and Hepatology, Department of Internal Medicine Keio University School of Medicine Tokyo Japan
| | - Tomohiko Iwano
- Department of Anatomy and Cell Biology University of Yamanashi Faculty of Medicine Yamanashi Japan
| | - Yujiro Machida
- Division of Gastroenterology and Hepatology, Department of Internal Medicine Keio University School of Medicine Tokyo Japan
| | - Hiroki Tamagawa
- Division of Gastroenterology and Hepatology, Department of Internal Medicine Keio University School of Medicine Tokyo Japan
| | - Shintaro Kawasaki
- Division of Gastroenterology and Hepatology, Department of Internal Medicine Keio University School of Medicine Tokyo Japan
| | - Takashi Seino
- Division of Gastroenterology and Hepatology, Department of Internal Medicine Keio University School of Medicine Tokyo Japan
| | - Takahiro Yokose
- Department of Surgery Keio University School of Medicine Tokyo Japan
| | - Yutaka Endo
- Department of Surgery Keio University School of Medicine Tokyo Japan
| | - Kentaro Yoshimura
- Department of Anatomy and Cell Biology University of Yamanashi Faculty of Medicine Yamanashi Japan
| | - Kazuhiro Kashiwagi
- Center for Preventive Medicine Keio University School of Medicine Tokyo Japan
| | - Minoru Kitago
- Department of Surgery Keio University School of Medicine Tokyo Japan
| | - Haruhiko Ogata
- Center for Diagnostic and Therapeutic Endoscopy Keio University School of Medicine Tokyo Japan
| | - Sen Takeda
- Department of Anatomy and Cell Biology University of Yamanashi Faculty of Medicine Yamanashi Japan
| | - Takanori Kanai
- Division of Gastroenterology and Hepatology, Department of Internal Medicine Keio University School of Medicine Tokyo Japan
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Iwano T, Yoshimura K, Inoue S, Odate T, Ogata K, Funatsu S, Tanihata H, Kondo T, Ichikawa D, Takeda S. Breast cancer diagnosis based on lipid profiling by probe electrospray ionization mass spectrometry. Br J Surg 2020; 107:632-635. [PMID: 32246473 PMCID: PMC7216899 DOI: 10.1002/bjs.11613] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Accepted: 03/08/2020] [Indexed: 12/14/2022]
Affiliation(s)
- T Iwano
- Department of Anatomy and Cell Biology, Faculty of Medicine, Yamanashi, Japan
| | - K Yoshimura
- Department of Anatomy and Cell Biology, Faculty of Medicine, Yamanashi, Japan
| | - S Inoue
- Department of Digestive , Breast and Endocrine Surgery, Yamanashi, Japan
| | - T Odate
- Department of Pathology, University of Yamanashi, Chu, Yamanashi, Japan
| | - K Ogata
- Shimadzu Corporation, Nakagyo, Kyoto, Japan
| | - S Funatsu
- Shimadzu Corporation, Nakagyo, Kyoto, Japan
| | - H Tanihata
- Shimadzu Corporation, Nakagyo, Kyoto, Japan
| | - T Kondo
- Department of Pathology, University of Yamanashi, Chu, Yamanashi, Japan
| | - D Ichikawa
- Department of Digestive , Breast and Endocrine Surgery, Yamanashi, Japan
| | - S Takeda
- Department of Anatomy and Cell Biology, Faculty of Medicine, Yamanashi, Japan
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Zhang Q, Zhu Y, Tian Y, Yu Q, Wang X. Induced Self-aspiration Electrospray Ionization Mass Spectrometry for Flexible Sampling and Analysis. Anal Chem 2020; 92:4600-4606. [PMID: 32096631 DOI: 10.1021/acs.analchem.0c00143] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Electrospray ionization (ESI) operating in pulse mode can enhance the utilization efficiency of the electrospray ions by a mass spectrometer. Herein, a novel ionization technique called induced self-aspiration-electrospray ionization (ISA-ESI) was developed based on self-aspiration sampling and capacitive induction. The sample solution polarized in a strong electric field was pulsed drawn into a capillary that was connected to a subambient chamber. The sample solution with polarized ions forms a charged liquid column, which can initiate an electrospray when reaching the capillary outlet. In addition to the self-aspiration ability, the use of a constant high voltage supply and no electrical contact with the solution can also simplify the sampling and ionization operation, enabling a convenient ESI mass spectrometry analysis. The developed ISA-ESI source has been used for multidimensional monitoring of chemical reactions as well as liquid extraction surface analysis of plant tissues. It was expected that this special ionization method could be extended to automated high-throughput ESI-MS analysis.
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Affiliation(s)
- Qian Zhang
- Division of Advanced Manufacturing, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China.,State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China
| | - Yanping Zhu
- Division of Advanced Manufacturing, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China
| | - Yuan Tian
- Division of Advanced Manufacturing, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China
| | - Quan Yu
- Division of Advanced Manufacturing, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China
| | - Xiaohao Wang
- Division of Advanced Manufacturing, Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China.,State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instrument, Tsinghua University, Beijing 100084, China
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