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Cao G, Song Z, Hong Y, Yang Z, Song Y, Chen Z, Chen Z, Cai Z. Large-scale targeted metabolomics method for metabolite profiling of human samples. Anal Chim Acta 2020; 1125:144-151. [PMID: 32674760 DOI: 10.1016/j.aca.2020.05.053] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2020] [Revised: 05/14/2020] [Accepted: 05/21/2020] [Indexed: 12/18/2022]
Abstract
Targeted metabolomics has significant advantages for quantification but suffers from reduced metabolite coverage. In this study, we developed a large-scale targeted metabolomics method and expanded its applicability to various human samples. This approach initially involved unbiased identification of metabolites in human cells, tissues and body fluids using ultra high-performance liquid chromatography (UHPLC) coupled to high-resolution Orbitrap mass spectrometry (MS). Targeted metabolomics method was established with utility of UHPLC-triple quadrupole MS, which enables targeted profiling of over 400 biologically important metabolites (e.g., amino acids, sugars, nucleotides, dipeptides, coenzymes, and fatty acids), covering 92 metabolic pathways (e.g., Krebs cycle, glycolysis, amino acids metabolism, ammonia recycling, and one-carbon metabolism). The present method displayed better sensitivity, repeatability and linearity than the Orbitrap MS-based untargeted metabolomics approach and demonstrated excellent performance in lung cancer biomarker discovery, in which 107 differential metabolites were able to discriminate between carcinoma and adjacent normal tissues, implicating the Warburg effect, alteration of redox state, and nucleotide metabolism of lung cancer. This new method is flexible and expandable and offers many advantages for metabolomics analysis, such as wide metabolite coverage, good repeatability and linearity and excellent capability in biomarker discovery, making it useful for both basic and clinical metabolic research.
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Affiliation(s)
- Guodong Cao
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong, China
| | - Zhengbo Song
- Department of Thoracic Oncology, Zhejiang Cancer Hospital, Hangzhou, China
| | - Yanjun Hong
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong, China; HKBU Institute of Research and Continuing Education, Shenzhen, China.
| | - Zhiyi Yang
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong, China
| | - Yuanyuan Song
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong, China
| | - Zhongjian Chen
- Department of Thoracic Oncology, Zhejiang Cancer Hospital, Hangzhou, China
| | - Zhaobin Chen
- Shenzhen Nanshan Center for Disease Control and Prevention, Shenzhen, China
| | - Zongwei Cai
- State Key Laboratory of Environmental and Biological Analysis, Department of Chemistry, Hong Kong Baptist University, Hong Kong, China; HKBU Institute of Research and Continuing Education, Shenzhen, China.
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52
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Liu X, Zhou L, Shi X, Xu G. New advances in analytical methods for mass spectrometry-based large-scale metabolomics study. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2019.115665] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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53
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Wang X, Gu H, Palma-Duran SA, Fierro A, Jasbi P, Shi X, Bresette W, Tasevska N. Influence of Storage Conditions and Preservatives on Metabolite Fingerprints in Urine. Metabolites 2019; 9:metabo9100203. [PMID: 31569767 PMCID: PMC6836253 DOI: 10.3390/metabo9100203] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Revised: 09/12/2019] [Accepted: 09/18/2019] [Indexed: 12/15/2022] Open
Abstract
Human urine, which is rich in metabolites, provides valuable approaches for biomarker measurement. Maintaining the stability of metabolites in urine is critical for accurate and reliable research results and subsequent interpretation. In this study, the effect of storage temperature (4, 22, and 40 °C), storage time (24 and 48 h), and use of preservatives (boric acid (BA), thymol) and para-aminobenzoic acid (PABA) on urinary metabolites in the pooled urine samples from 20 participants was systematically investigated using large-scale targeted liquid chromatography tandem mass spectrometry (LC-MS/MS)-based metabolomics. Statistical analysis of 158 reliably detected metabolites showed that metabolites in urine with no preservative remained stable at 4 °C for 24 and 48 h as well as at 22 °C for 24 h, but significant metabolite differences were observed in urine stored at 22 °C for 48 h and at 40 °C. The mere addition of BA caused metabolite changes. Thymol was observed to be effective in maintaining metabolite stability in urine in all the conditions designed, most likely due to the inhibitory effect of thymol on urine microbiota. Our results provide valuable urine preservation guidance during sample storage, which is essential for obtaining reliable, accurate, and reproducible analytical results from urine samples.
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Affiliation(s)
- Xinchen Wang
- Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology, Nanchang 330013, China.
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA.
| | - Haiwei Gu
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA.
| | | | - Andres Fierro
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA.
| | - Paniz Jasbi
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA.
| | - Xiaojian Shi
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA.
| | - William Bresette
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA.
| | - Natasha Tasevska
- College of Health Solutions, Arizona State University, Phoenix, AZ 85004, USA.
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54
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Shi X, Wang S, Jasbi P, Turner C, Hrovat J, Wei Y, Liu J, Gu H. Database-Assisted Globally Optimized Targeted Mass Spectrometry (dGOT-MS): Broad and Reliable Metabolomics Analysis with Enhanced Identification. Anal Chem 2019; 91:13737-13745. [PMID: 31556994 DOI: 10.1021/acs.analchem.9b03107] [Citation(s) in RCA: 50] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Affiliation(s)
- Xiaojian Shi
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Shuai Wang
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
- Department of Vascular Surgery, The First Hospital of Jilin University, Jilin University, Changchun, Jilin Province 130021, People’s Republic of China
| | - Paniz Jasbi
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Cassidy Turner
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Jonathan Hrovat
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Yiping Wei
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
- Department of Thoracic Surgery, The Second Affiliated Hospital of Nanchang University, Nanchang, Jiangxi Province 330006, People’s Republic of China
| | - Jingping Liu
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
- Key Laboratory of Transplant Engineering and Immunology, West China Hospital, Sichuan University, Chengdu, Sichuan Province 610041, People’s Republic of China
| | - Haiwei Gu
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
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55
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Pang H, Jia W, Hu Z. Emerging Applications of Metabolomics in Clinical Pharmacology. Clin Pharmacol Ther 2019; 106:544-556. [DOI: 10.1002/cpt.1538] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2019] [Accepted: 05/18/2019] [Indexed: 12/20/2022]
Affiliation(s)
- Huanhuan Pang
- School of Pharmaceutical Sciences Tsinghua University Beijing China
| | - Wei Jia
- Cancer Biology Program University of Hawaii Cancer Center Honolulu Hawaii USA
| | - Zeping Hu
- School of Pharmaceutical Sciences Tsinghua University Beijing China
- Tsinghua‐Peking Joint Center for Life Sciences Tsinghua University Beijing China
- Beijing Frontier Research Center for Biological Structure Tsinghua University Beijing China
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Zhong F, Xu M, Zhu J. Development and application of time staggered/mass staggered-globally optimized targeted mass spectrometry. J Chromatogr B Analyt Technol Biomed Life Sci 2019; 1120:80-88. [DOI: 10.1016/j.jchromb.2019.04.051] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2019] [Revised: 04/20/2019] [Accepted: 04/27/2019] [Indexed: 01/24/2023]
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Jasbi P, Mitchell NM, Shi X, Grys TE, Wei Y, Liu L, Lake DF, Gu H. Coccidioidomycosis Detection Using Targeted Plasma and Urine Metabolic Profiling. J Proteome Res 2019; 18:2791-2802. [DOI: 10.1021/acs.jproteome.9b00100] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Affiliation(s)
- Paniz Jasbi
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Natalie M. Mitchell
- School of Life Sciences, Mayo Clinic Collaborative Research Building, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Xiaojian Shi
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Thomas E. Grys
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Phoenix, Arizona 85054, United States
| | - Yiping Wei
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Li Liu
- Department of Biomedical Informatics, Arizona State University, Tempe, Arizona 85259, United States
- Department of Neurology, Mayo Clinic, Scottsdale, Arizona 85259, United States
| | - Douglas F. Lake
- School of Life Sciences, Mayo Clinic Collaborative Research Building, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Haiwei Gu
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
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Hamid SS, Wakayama M, Ichihara K, Sakurai K, Ashino Y, Kadowaki R, Soga T, Tomita M. Metabolome profiling of various seaweed species discriminates between brown, red, and green algae. PLANTA 2019; 249:1921-1947. [PMID: 30891648 DOI: 10.1007/s00425-019-03134-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Accepted: 03/07/2019] [Indexed: 06/09/2023]
Abstract
MAIN CONCLUSION Among seaweed groups, brown algae had characteristically high concentrations of mannitol, and green algae were characterised by fructose. In red algae, metabolite profiles of individual species should be evaluated. Seaweeds are metabolically different from terrestrial plants. However, general metabolite profiles of the three major seaweed groups, the brown, red, and green algae, and the effect of various extraction methods on metabolite profiling results have not been comprehensively explored. In this study, we evaluated the water-soluble metabolites in four brown, five red, and two green algae species collected from two sites in northern Japan, located in the Sea of Japan and the Pacific Ocean. Freeze-dried seaweed samples were processed by methanol-water extraction with or without chloroform and analysed by capillary electrophoresis- and liquid chromatography-mass spectrometry for metabolite characterisation. The metabolite concentration profiles showed distinctive characteristic depends on species and taxonomic groups, whereas the extraction methods did not have a significant effect. Taxonomic differences between the various seaweed metabolite profiles were well defined using only sugar metabolites but no other major compound types. Mannitol was the main sugar metabolites in brown algae, whereas fructose, sucrose, and glucose were found at high concentrations in green algae. In red algae, individual species had some characteristic metabolites, such as sorbitol in Pyropia pseudolinearis and panose in Dasya sessilis. The metabolite profiles generated in this study will be a resource and provide guidance for nutraceutical research studies because the information about metabolites in seaweeds is still very limited compared to that of terrestrial plants.
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Affiliation(s)
- Shahlizah Sahul Hamid
- Institute for Advanced Biosciences, Keio University, 246-2, Kakuganji-Mizukami, Tsuruoka, Yamagata, 997-0052, Japan
- Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, 252-8520, Japan
| | - Masataka Wakayama
- Institute for Advanced Biosciences, Keio University, 246-2, Kakuganji-Mizukami, Tsuruoka, Yamagata, 997-0052, Japan.
- Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, 252-8520, Japan.
| | - Kensuke Ichihara
- Muroran Marine Station, Field Science Centre for Northern Biosphere, Hokkaido University, 1-133-31, Funami-cho, Muroran, Hokkaido, 051-0013, Japan
| | - Katsutoshi Sakurai
- Yamagata Prefecture Fisheries Experiment Station, Kamo Ookuzure 594, Tsuruoka, Yamagata, 997-1204, Japan
| | - Yujin Ashino
- Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, 252-8520, Japan
| | - Rie Kadowaki
- Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, 252-8520, Japan
| | - Tomoyoshi Soga
- Institute for Advanced Biosciences, Keio University, 246-2, Kakuganji-Mizukami, Tsuruoka, Yamagata, 997-0052, Japan
- Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, 252-8520, Japan
| | - Masaru Tomita
- Institute for Advanced Biosciences, Keio University, 246-2, Kakuganji-Mizukami, Tsuruoka, Yamagata, 997-0052, Japan
- Systems Biology Program, Graduate School of Media and Governance, Keio University, Fujisawa, 252-8520, Japan
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Scoville DK, Li CY, Wang D, Dempsey JL, Raftery D, Mani S, Gu H, Cui JY. Polybrominated Diphenyl Ethers and Gut Microbiome Modulate Metabolic Syndrome-Related Aqueous Metabolites in Mice. Drug Metab Dispos 2019; 47:928-940. [PMID: 31123037 DOI: 10.1124/dmd.119.086538] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2019] [Accepted: 05/07/2019] [Indexed: 12/13/2022] Open
Abstract
Polybrominated diphenyl ethers (PBDEs) are persistent environmental toxicants associated with increased risk for metabolic syndrome. Intermediary metabolism is influenced by the intestinal microbiome. To test the hypothesis that PBDEs reduce host-beneficial intermediary metabolites in an intestinal microbiome-dependent manner, 9-week old male conventional (CV) and germ-free (GF) C57BL/6 mice were orally gavaged once daily with vehicle, BDE-47, or BDE-99 (100 μmol/kg) for 4 days. Intestinal microbiome (16S rDNA sequencing), liver transcriptome (RNA-Seq), and intermediary metabolites in serum, liver, as well as small and large intestinal contents (SIC and LIC; LC-MS) were examined. Changes in intermediary metabolite abundances in serum, liver, and SIC, were observed under basal conditions (CV vs. GF mice) and by PBDE exposure. PBDEs altered the largest number of metabolites in the LIC; most were regulated by PBDEs in GF conditions. Importantly, intestinal microbiome was necessary for PBDE-mediated decreases in branched-chain and aromatic amino acid metabolites, including 3-indolepropionic acid, a tryptophan metabolite recently shown to be protective against inflammation and diabetes. Gene-metabolite networks revealed a positive association between the hepatic glycan synthesis gene α-1,6-mannosyltransferase (Alg12) mRNA and mannose, which are important for protein glycosylation. Glycome changes have been observed in patients with metabolic syndrome. In LIC of CV mice, 23 bacterial taxa were regulated by PBDEs. Correlations of certain taxa with distinct serum metabolites further highlight a modulatory role of the microbiome in mediating PBDE effects. In summary, PBDEs impact intermediary metabolism in an intestinal microbiome-dependent manner, suggesting that dysbiosis may contribute to PBDE-mediated toxicities that include metabolic syndrome.
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Affiliation(s)
- David K Scoville
- Department of Environmental and Occupational Health Sciences (D.K.S., C.Y.L., J.L.D., J.Y.C.) and Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine (D.W., D.R.), University of Washington, Seattle, Washington; Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China (D.W.); Albert Einstein College of Medicine, Bronx, New York (S.M.); and Arizona Metabolomics Laboratory, School of Nutrition and Health Promotion, College of Health Solutions, Arizona State University, Phoenix, Arizona (H.G.)
| | - Cindy Yanfei Li
- Department of Environmental and Occupational Health Sciences (D.K.S., C.Y.L., J.L.D., J.Y.C.) and Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine (D.W., D.R.), University of Washington, Seattle, Washington; Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China (D.W.); Albert Einstein College of Medicine, Bronx, New York (S.M.); and Arizona Metabolomics Laboratory, School of Nutrition and Health Promotion, College of Health Solutions, Arizona State University, Phoenix, Arizona (H.G.)
| | - Dongfang Wang
- Department of Environmental and Occupational Health Sciences (D.K.S., C.Y.L., J.L.D., J.Y.C.) and Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine (D.W., D.R.), University of Washington, Seattle, Washington; Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China (D.W.); Albert Einstein College of Medicine, Bronx, New York (S.M.); and Arizona Metabolomics Laboratory, School of Nutrition and Health Promotion, College of Health Solutions, Arizona State University, Phoenix, Arizona (H.G.)
| | - Joseph L Dempsey
- Department of Environmental and Occupational Health Sciences (D.K.S., C.Y.L., J.L.D., J.Y.C.) and Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine (D.W., D.R.), University of Washington, Seattle, Washington; Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China (D.W.); Albert Einstein College of Medicine, Bronx, New York (S.M.); and Arizona Metabolomics Laboratory, School of Nutrition and Health Promotion, College of Health Solutions, Arizona State University, Phoenix, Arizona (H.G.)
| | - Daniel Raftery
- Department of Environmental and Occupational Health Sciences (D.K.S., C.Y.L., J.L.D., J.Y.C.) and Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine (D.W., D.R.), University of Washington, Seattle, Washington; Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China (D.W.); Albert Einstein College of Medicine, Bronx, New York (S.M.); and Arizona Metabolomics Laboratory, School of Nutrition and Health Promotion, College of Health Solutions, Arizona State University, Phoenix, Arizona (H.G.)
| | - Sridhar Mani
- Department of Environmental and Occupational Health Sciences (D.K.S., C.Y.L., J.L.D., J.Y.C.) and Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine (D.W., D.R.), University of Washington, Seattle, Washington; Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China (D.W.); Albert Einstein College of Medicine, Bronx, New York (S.M.); and Arizona Metabolomics Laboratory, School of Nutrition and Health Promotion, College of Health Solutions, Arizona State University, Phoenix, Arizona (H.G.)
| | - Haiwei Gu
- Department of Environmental and Occupational Health Sciences (D.K.S., C.Y.L., J.L.D., J.Y.C.) and Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine (D.W., D.R.), University of Washington, Seattle, Washington; Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China (D.W.); Albert Einstein College of Medicine, Bronx, New York (S.M.); and Arizona Metabolomics Laboratory, School of Nutrition and Health Promotion, College of Health Solutions, Arizona State University, Phoenix, Arizona (H.G.)
| | - Julia Yue Cui
- Department of Environmental and Occupational Health Sciences (D.K.S., C.Y.L., J.L.D., J.Y.C.) and Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine (D.W., D.R.), University of Washington, Seattle, Washington; Department of Laboratorial Science and Technology, School of Public Health, Peking University, Beijing, P. R. China (D.W.); Albert Einstein College of Medicine, Bronx, New York (S.M.); and Arizona Metabolomics Laboratory, School of Nutrition and Health Promotion, College of Health Solutions, Arizona State University, Phoenix, Arizona (H.G.)
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Yan Z, Li T, Wei B, Wang P, Wan J, Wang Y, Yan R. High-resolution MS/MS metabolomics by data-independent acquisition reveals urinary metabolic alteration in experimental colitis. Metabolomics 2019; 15:70. [PMID: 31041724 DOI: 10.1007/s11306-019-1534-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Accepted: 04/24/2019] [Indexed: 10/26/2022]
Abstract
INTRODUCTION Traditional high-resolution MS1 based untargeted metabolomics suffers from low sensitivity, while low-resolution MS/MS based multiple reaction monitoring increases sensitivity at the cost of metabolite coverage and the mass accuracy. OBJECTIVES To evaluate and apply the high-resolution MS/MS level untargeted metabolomics. METHODS SWATH based data-independent acquisition (DIA) was optimized to obtain MS/MS of all precursor ions. RESULTS SWATH-MS/MS could rescue MS1 obscured or saturated metabolites and potentially provide diagnostic fragments to differentiate isomers. For SWATH-MS/MS, 4944 out of 21492 (23.0%) and 2289 out of 12831 (17.8%) fragment ion features significantly changed (Fold change > 1.5, P < 0.05) between Normal and experimental acute ulcerative colitis (UC) groups in positive and negative ion mode, respectively. For SWATH-MS1, 1022 out of 4818 (21.2%) and 353 out of 2266 (15.6%) features significantly changed in positive and negative ion mode, respectively. By deciphering the metabolite profiles with high-resolution MS/MS, it allows versatile post-acquisition data mining such as open detection of different sub-metabolome. The method revealed a global urinary metabolic alteration and increased glucuronide and sulfate sub-metabolome in UC. The major limitation of untargeted SWATH-MS/MS is increased interferences derived from wider Q1 isolation window. CONCLUSIONS SWATH-MS/MS is a versatile metabolomics strategy, merging the coverage of high-resolution untargeted metabolomics and the sensitivity of MS/MS.
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Affiliation(s)
- Zhixiang Yan
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, China
- Zhuhai UM Science & Technology Research Institute, Zhuhai, 519080, China
| | - Ting Li
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, China
- Zhuhai UM Science & Technology Research Institute, Zhuhai, 519080, China
| | - Bin Wei
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, China
- Zhuhai UM Science & Technology Research Institute, Zhuhai, 519080, China
| | - Panpan Wang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, China
- Zhuhai UM Science & Technology Research Institute, Zhuhai, 519080, China
| | - Jianbo Wan
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, China
| | - Yitao Wang
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, China
| | - Ru Yan
- State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Taipa, Macao, China.
- Zhuhai UM Science & Technology Research Institute, Zhuhai, 519080, China.
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Fei Q, Wang D, Jasbi P, Zhang P, Nagana Gowda GA, Raftery D, Gu H. Combining NMR and MS with Chemical Derivatization for Absolute Quantification with Reduced Matrix Effects. Anal Chem 2019; 91:4055-4062. [DOI: 10.1021/acs.analchem.8b05611] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Qiang Fei
- College of Chemistry, Jilin University, Changchun 130021, P. R. China
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington 98109, United States
| | - Dongfang Wang
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington 98109, United States
- Chongqing Blood Center, Chongqing 400015, P. R. China
| | - Paniz Jasbi
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
| | - Ping Zhang
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington 98109, United States
- College of Plant Protection, Southwest University, Chongqing 400715, P. R. China
| | - G. A. Nagana Gowda
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington 98109, United States
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington, Seattle, Washington 98109, United States
- Department of Chemistry, University of Washington, Seattle, Washington 98109, United States
- Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, United States
| | - Haiwei Gu
- Arizona Metabolomics Laboratory, College of Health Solutions, Arizona State University, Scottsdale, Arizona 85259, United States
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Li Z, Li Y, Tang YJ, Shui W. Exploiting High-Resolution Mass Spectrometry for Targeted Metabolite Quantification and 13C-Labeling Metabolism Analysis. Methods Mol Biol 2019; 1859:171-184. [PMID: 30421229 DOI: 10.1007/978-1-4939-8757-3_9] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Quantification of targeted metabolites, especially trace metabolites and structural isomers, in complex biological materials is an ongoing challenge for metabolomics. In this chapter, we summarize high-resolution mass spectrometry-based approaches mainly used for targeted metabolite and metabolomics analysis, and then introduce an MS1/MS2-combined PRM workflow for quantification of central carbon metabolism intermediates, amino acids, and shikimate pathway-related metabolites. Major steps in the workflow, including cell culture, metabolite extraction, LC-MS analysis and data processing, are described. Furthermore, we adapt this new approach to a dynamic 13C-labeling experiment and demonstrate its unique advantage in capturing and correcting isotopomer labeling curves to facilitate nonstationary 13C-labeling metabolism analysis.
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Affiliation(s)
- Zhucui Li
- iHuman Institute, ShanghaiTech University, Shanghai, China
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yujing Li
- College of Life Sciences, Nankai University, Tianjin, China
| | - Yinjie J Tang
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Wenqing Shui
- iHuman Institute, ShanghaiTech University, Shanghai, China.
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Fang C, Fernie AR, Luo J. Exploring the Diversity of Plant Metabolism. TRENDS IN PLANT SCIENCE 2019; 24:83-98. [PMID: 30297176 DOI: 10.1016/j.tplants.2018.09.006] [Citation(s) in RCA: 153] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/08/2018] [Revised: 09/05/2018] [Accepted: 09/11/2018] [Indexed: 05/23/2023]
Abstract
Plants produce a huge array of metabolites, far more than those produced by most other organisms. Unraveling this diversity and its underlying genetic variation has attracted increasing research attention. Post-genomic profiling platforms have enabled the marriage and mining of the enormous amount of phenotypic and genetic diversity. We review here achievements to date and challenges remaining that are associated with plant metabolic research using multi-omic strategies. We focus mainly on strategies adopted in investigating the diversity of plant metabolism and its underlying features. Recent advances in linking metabotypes with phenotypic and genotypic traits are also discussed. Taken together, we conclude that exploring the diversity of metabolism could provide new insights into plant evolution and domestication.
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Affiliation(s)
- Chuanying Fang
- Hainan Key Laboratory for Sustainable Utilization of Tropical Bioresource, Institute of Tropical Agriculture and Forestry, Hainan University, Haikou 570288, China
| | - Alisdair R Fernie
- Max-Planck-Institute of Molecular Plant Physiology, Potsdam-Golm 144776, Germany; Center of Plant System Biology and Biotechnology, 4000 Plovdiv, Bulgaria.
| | - Jie Luo
- Hainan Key Laboratory for Sustainable Utilization of Tropical Bioresource, Institute of Tropical Agriculture and Forestry, Hainan University, Haikou 570288, China; National Key Laboratory of Crop Genetic Improvement and National Center of Plant Gene Research (Wuhan), Huazhong Agricultural University, Wuhan 430070, China.
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64
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Jasbi P, Baker O, Shi X, Gonzalez LA, Wang S, Anderson S, Xi B, Gu H, Johnston CS. Daily red wine vinegar ingestion for eight weeks improves glucose homeostasis and affects the metabolome but does not reduce adiposity in adults. Food Funct 2019; 10:7343-7355. [DOI: 10.1039/c9fo01082c] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
This is the first study to investigate the effects of vinegar on adiposity and glycemia using both anthropometrics and metabolomics.
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Affiliation(s)
- Paniz Jasbi
- College of Health Solutions
- Arizona State University
- Phoenix
- USA
| | - Olivia Baker
- College of Health Solutions
- Arizona State University
- Phoenix
- USA
| | - Xiaojian Shi
- College of Health Solutions
- Arizona State University
- Phoenix
- USA
| | | | - Shuai Wang
- College of Health Solutions
- Arizona State University
- Phoenix
- USA
| | - Summer Anderson
- College of Health Solutions
- Arizona State University
- Phoenix
- USA
| | - Bowei Xi
- Department of Statistics
- Purdue University
- West Lafayette
- USA
| | - Haiwei Gu
- College of Health Solutions
- Arizona State University
- Phoenix
- USA
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65
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Jasbi P, Wang D, Cheng SL, Fei Q, Cui JY, Liu L, Wei Y, Raftery D, Gu H. Breast cancer detection using targeted plasma metabolomics. J Chromatogr B Analyt Technol Biomed Life Sci 2019; 1105:26-37. [DOI: 10.1016/j.jchromb.2018.11.029] [Citation(s) in RCA: 55] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2018] [Revised: 11/27/2018] [Accepted: 11/30/2018] [Indexed: 12/11/2022]
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66
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Li H, Xu M, Zhu J. Headspace Gas Monitoring of Gut Microbiota Using Targeted and Globally Optimized Targeted Secondary Electrospray Ionization Mass Spectrometry. Anal Chem 2018; 91:854-863. [DOI: 10.1021/acs.analchem.8b03517] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Affiliation(s)
- Haorong Li
- Department of Chemistry and Biochemistry, Miami University, 651 E. High Street, Oxford, Ohio 45056, United States
| | - Mengyang Xu
- Department of Chemistry and Biochemistry, Miami University, 651 E. High Street, Oxford, Ohio 45056, United States
| | - Jiangjiang Zhu
- Department of Chemistry and Biochemistry, Miami University, 651 E. High Street, Oxford, Ohio 45056, United States
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67
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Simultaneously targeted and untargeted multicomponent characterization of Erzhi Pill by offline two-dimensional liquid chromatography/quadrupole-Orbitrap mass spectrometry. J Chromatogr A 2018; 1584:87-96. [PMID: 30473109 DOI: 10.1016/j.chroma.2018.11.024] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2018] [Revised: 10/19/2018] [Accepted: 11/15/2018] [Indexed: 11/24/2022]
Abstract
Large-scale targeted and untargeted metabolites characterization can be achieved by feat of different liquid chromatography/mass spectrometry (LC-MS) platforms by multiple MS experiments or using data-independent acquisition followed by precursor-product ions matching based on certain algorithms. The resulting insufficiency in efficiency and availability greatly restricts the applicability of these strategies in large-scale profiling and identification of various metabolites. A strategy simultaneously enabling both the targeted and untargeted metabolites characterization is established on a Q Exactive hybrid quadrupole-Orbitrap mass spectrometer, by integrating precursor ions list-triggered data-dependent MS2 acquisition (PIL/dd-MS2) of the targeted components and using the "If idle-pick others" (IIPO) function to induce untargeted metabolites fragmentation. A compounds-specific mass defect filter (MDF) algorithm is proposed as a method to generate the PIL. As a proof of concept, this strategy coupled with offline two-dimensional liquid chromatography (2D-LC) was applied to identify the multicomponents of a traditional Chinese medicine formula Erzhi Pill (EZP). A rigid MDF vehicle was elaborated by orthogonal screening of the integer mass and integer mass-dependent dynamic mass defects considering a variation of 20 ppm. The Full MS/dd-MS2 method enabling PIL and IIPO exhibited better performance than Full MS/dd-MS2 and Targeted SIM/dd-MS2 (selected ion monitoring) in respect of the sensitivity in identifying the targeted components and the ability to characterize more untargeted ones. As a consequence, 270 components were separated from EZP, and 146 thereof were selectively characterized. In conclusion, it is a practical, multifaced strategy facilitating the in-depth metabolites profiling and characterization of complex herbal and biological samples.
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68
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Zhou J, Yin Y. Strategies for large-scale targeted metabolomics quantification by liquid chromatography-mass spectrometry. Analyst 2018; 141:6362-6373. [PMID: 27722450 DOI: 10.1039/c6an01753c] [Citation(s) in RCA: 152] [Impact Index Per Article: 25.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Advances in liquid chromatography-mass spectrometry (LC-MS) instruments and analytical strategies have brought about great progress in targeted metabolomics analysis. This methodology is now capable of performing precise targeted measurement of dozens or hundreds of metabolites in complex biological samples. Classic targeted quantification assay using the multiple reaction monitoring (MRM) mode has been the foundation of high-quality metabolite quantitation. However, utilization of this strategy in biological studies has been limited by its relatively low metabolite coverage and throughput capacity. A number of methods for large-scale targeted metabolomics assay which have been developed overcome these limitations. These strategies have enabled extended metabolite coverage which is defined as targeting of large numbers of metabolites, while maintaining reliable quantification performance. These recently developed techniques thus bridge the gap between traditional targeted metabolite quantification and untargeted metabolomics profiling, and have proven to be powerful tools for metabolomics study. Although the LC-MRM-MS strategy has been used widely in large-scale metabolomics quantification analysis due to its fast scan speed and ideal analytic stability, there are still drawbacks which are due to the low resolution of the triple quadrupole instruments used for MRM assays. New approaches have been developed to expand the options for large-scale targeted metabolomics study, using high-resolution instruments such as parallel reaction monitoring (PRM). MRM and PRM-based techniques are now attractive strategies for quantitative metabolomics analysis and high-throughput biomarker discovery. Here we provide an overview of the major developments in LC-MS-based strategies for large-scale targeted metabolomics quantification in biological samples. The advantages of LC-MRM/PRM-MS based analytical strategies which may be used in multiplexed and high throughput quantitation for a wide range of metabolites are highlighted. In particular, PRM and MRM strategies are compared, and we summarize the work flow commonly used for large-scale targeted metabolomics analysis including sample preparation, LC separation and data analysis, as well as recent applications in biological studies.
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Affiliation(s)
- Juntuo Zhou
- Institute of Systems Biomedicine, Department of Pathology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.
| | - Yuxin Yin
- Institute of Systems Biomedicine, Department of Pathology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China.
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69
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Xu J, Li J, Zhang R, He J, Chen Y, Bi N, Song Y, Wang L, Zhan Q, Abliz Z. Development of a metabolic pathway-based pseudo-targeted metabolomics method using liquid chromatography coupled with mass spectrometry. Talanta 2018; 192:160-168. [PMID: 30348373 DOI: 10.1016/j.talanta.2018.09.021] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Revised: 09/06/2018] [Accepted: 09/08/2018] [Indexed: 12/14/2022]
Abstract
The pseudo-targeted metabolomics approach was developed recently which combined the advantages of untargeted and targeted analysis. However, the current pseudo-targeted analysis method has limitations due to the technical characteristics. In this study, a novel metabolic pathway-based pseudo-targeted approach was proposed for urine metabolomics analysis using an ultra-high-performance liquid chromatography (UPLC)-MS/MS system operated in the multiple reaction monitoring (MRM) mode. MRM ion pairs were acquired from urine samples through untargeted analysis using UPLC-HRMS, as well as by searching for metabolites in related pathways in relevant databases and from previous relevant research, including amino acids, fatty acids, nucleosides, carnitines, glycolysis metabolites, and steroids. This improved pseudo-targeted method exhibited good repeatability and precision, and no complicated peak alignment was required. As a proof of concept, the developed novel method was applied to the discovery of urine biomarkers for patients with esophageal squamous cell carcinoma (ESCC). The results showed that ESCC patients had altered acylcarnitines, amino acids, nucleosides, and steroid derivative levels et al. compared to those of healthy controls. The novelty of this study lies in the fact that it provides an approach for acquiring MRM ion pairs not only from untargeted MS analysis but also from targeted searching for metabolites in related metabolic pathways. By improving the detection limit of low-abundance metabolites, it enlarges the range for the discovery of potential biomarkers. Our work provides a foundation for achieving pseudo-targeted metabolomics analysis on the widely used LC-MS/MS MRM platform.
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Affiliation(s)
- Jing Xu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, PR China
| | - Jiangshuo Li
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, PR China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, PR China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, PR China
| | - Yanhua Chen
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, PR China
| | - Nan Bi
- Department of Radiation Oncology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100021, PR China
| | - Yongmei Song
- State Key Laboratory of Molecular Oncology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100021, PR China
| | - Luhua Wang
- Department of Radiation Oncology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100021, PR China
| | - Qimin Zhan
- State Key Laboratory of Molecular Oncology, Cancer Institute & Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100021, PR China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, PR China; Centre for Bioimaging & Systems Biology, Minzu University of China, Beijing 100081, PR China.
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70
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Wang L, Su B, Zeng Z, Li C, Zhao X, Lv W, Xuan Q, Ouyang Y, Zhou L, Yin P, Peng X, Lu X, Lin X, Xu G. Ion-Pair Selection Method for Pseudotargeted Metabolomics Based on SWATH MS Acquisition and Its Application in Differential Metabolite Discovery of Type 2 Diabetes. Anal Chem 2018; 90:11401-11408. [PMID: 30148611 DOI: 10.1021/acs.analchem.8b02377] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
The pseudotargeted metabolomics method integrates advantages of nontargeted and targeted analysis because it can acquire data of metabolites in the multireaction monitoring (MRM) mode of mass spectrometry (MS) without needing standards. The key is the ion-pair information collection from samples to be analyzed. It is well-known that sequential windowed acquisition of all theoretical Fragment ion (SWATH) MS mode can acquire MS2 information to a maximum extent. To expediently acquire as many ion-pairs as possible with optimal collision energy (CE), an ion-pair selection approach based on SWATH MS acquisition with variable isolation windows was developed in this study. Initially, nontargeted acquisition of all metabolites information in plasma Standard Reference Material (SRM 1950) was performed by ultra high-performance liquid chromatography (UHPLC)-quadrupole time-of-flight (Q-TOF) MS platform with three CEs. With the help of software tool, the ion-pairs of unique metabolites were gained. Then they were validated in scheduled MRM coupled with UHPLC. After removing false positive, the ion-pairs with an optimal CE was integrated. A total of 1373 unique metabolite ion-pairs were obtained at positive ion mode. And repeatability of the established pseudotargeted approach was evaluated by intraday and interday precision. The results demonstrated the method was stable, reliable, and suitable for metabolomics study. As an application example, alterations of serum metabolites in Type 2 diabetes were investigated by using the established method. This work provides a pseudotargeted ion-pair selection method based on SWATH MS acquisition with the characters of increased metabolite coverage, suitable CE, and convenient processing.
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Affiliation(s)
- Lichao Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road , Dalian 116023 , P. R. China.,State Key Laboratory of Fine Chemicals , Dalian University of Technology , Dalian 116023 , P. R. China.,University of Chinese Academy of Sciences , Beijing 100049 , P. R. China
| | - Benzhe Su
- School of Computer Science & Technology , Dalian University of Technology , Dalian 116024 , P. R. China
| | - Zhongda Zeng
- CAS Key Laboratory of Separation Science for Analytical Chemistry , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road , Dalian 116023 , P. R. China
| | - Chao Li
- School of Computer Science & Technology , Dalian University of Technology , Dalian 116024 , P. R. China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road , Dalian 116023 , P. R. China.,University of Chinese Academy of Sciences , Beijing 100049 , P. R. China
| | - Wangjie Lv
- CAS Key Laboratory of Separation Science for Analytical Chemistry , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road , Dalian 116023 , P. R. China.,University of Chinese Academy of Sciences , Beijing 100049 , P. R. China
| | - Qiuhui Xuan
- CAS Key Laboratory of Separation Science for Analytical Chemistry , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road , Dalian 116023 , P. R. China.,University of Chinese Academy of Sciences , Beijing 100049 , P. R. China
| | - Yang Ouyang
- CAS Key Laboratory of Separation Science for Analytical Chemistry , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road , Dalian 116023 , P. R. China.,University of Chinese Academy of Sciences , Beijing 100049 , P. R. China
| | - Lina Zhou
- CAS Key Laboratory of Separation Science for Analytical Chemistry , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road , Dalian 116023 , P. R. China.,University of Chinese Academy of Sciences , Beijing 100049 , P. R. China
| | - Peiyuan Yin
- CAS Key Laboratory of Separation Science for Analytical Chemistry , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road , Dalian 116023 , P. R. China.,University of Chinese Academy of Sciences , Beijing 100049 , P. R. China
| | - Xiaojun Peng
- State Key Laboratory of Fine Chemicals , Dalian University of Technology , Dalian 116023 , P. R. China
| | - Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road , Dalian 116023 , P. R. China.,University of Chinese Academy of Sciences , Beijing 100049 , P. R. China
| | - Xiaohui Lin
- School of Computer Science & Technology , Dalian University of Technology , Dalian 116024 , P. R. China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry , Dalian Institute of Chemical Physics, Chinese Academy of Sciences , 457 Zhongshan Road , Dalian 116023 , P. R. China.,University of Chinese Academy of Sciences , Beijing 100049 , P. R. China
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71
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Shin IS, Jo E, Jang IS, Yoo HS. Quantitative Analyses of the Functional Constituents in SanYangSam and SanYangSanSam. J Pharmacopuncture 2018; 20:274-279. [PMID: 30151297 PMCID: PMC6104717 DOI: 10.3831/kpi.2017.20.033] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2017] [Revised: 11/21/2017] [Accepted: 11/24/2017] [Indexed: 11/12/2022] Open
Abstract
Objective SanYangSam and SanYangSanSam are traditional Korea-medical herbs that are grown from Panax ginseng C.A. Meyer. In our previous studies, we found that the functional compounds in SanYangSam and SanYangSanSam were different and depended on the type and the cultivation environment of ginseng. This study aimed to profile the functional constituents in SanYangSam and SanYangSanSam. Methods To profile the functional aspects of the many compounds that have therapeutic activities in SanYangSam and SanYangSanSam extracts, we used liquid chromatography tandem mass spectrometry and quadrupole orthogonal acceleration time-of-flight mass spectrometry. Results A total of four major compounds were detected; two of which were the natural flavonoids kaempferol and quercetin. Among others, two polyacetylene compounds, including panaxydol and panaxynol, were detected. Conclusion In this study, we found that panaxydol, one of the polyacetylene constituents of ginseng, is a candidate anti-cancer agent in SanYangSam and SanYangSanSam pharmacopuncture. In addition, we found that the panaxydol levels in the SanYangSanSam extract were over 30 times those in the SanYangSam extract.
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Affiliation(s)
- Il-Soo Shin
- East-West Cancer Center, Daejeon University, Daejeon, Republic of Korea
| | - Eunbi Jo
- Division of Bioconvergence Analysis, Korea Basic Science Institute, Daejeon, 305-333 Republic of Korea
| | - Ik-Soon Jang
- Division of Bioconvergence Analysis, Korea Basic Science Institute, Daejeon, 305-333 Republic of Korea
| | - Hwa-Seung Yoo
- East-West Cancer Center, Daejeon University, Daejeon, Republic of Korea
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72
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Shan J, Peng L, Qian W, Xie T, Kang A, Gao B, Di L. Integrated Serum and Fecal Metabolomics Study of Collagen-Induced Arthritis Rats and the Therapeutic Effects of the Zushima Tablet. Front Pharmacol 2018; 9:891. [PMID: 30154719 PMCID: PMC6102586 DOI: 10.3389/fphar.2018.00891] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Accepted: 07/23/2018] [Indexed: 11/18/2022] Open
Abstract
The Zushima tablet (ZT) has been used for decades in the clinical treatment of rheumatoid arthritis (RA) in China. However, its therapeutic mechanism is unclear. In this study, we aimed to explore the distinctive metabolic patterns in collagen-induced arthritis (CIA) rats and evaluate the therapeutic effects of ZT on RA using untargeted serum and fecal metabolomics approaches based on gas chromatography coupled with mass spectrometry. Body weight, hind paw swelling, TNF-α and IL-1β levels, arthritis scores, and histopathological parameters were assessed. In the metabolomics study, 31 altered metabolites in the serum and 30 in the feces were identified by comparing the model with the control group using statistical processing. These altered metabolites revealed that the tricarboxylic acid cycle, glycolysis metabolism, fatty acid metabolism, and purine metabolism were disturbed in CIA rats, and most of these altered metabolites including l-isoleucine, l-aspartic acid, pyruvic acid, cholic acid, and hypoxanthine, were rectified by ZT. Furthermore, short-chain fatty acids in feces were quantitatively determined, and the results showed that ZT could regulate the levels of propionate, butyrate, and valerate in CIA rats. Then, gut microbiota were analyzed by 16S rRNA analysis. Our results showed that Firmicutes and Bacteroidetes were the most abundant bacteria in rats. The levels of 19 types of bacteria at the family level were altered in RA rats, and most of them could be regulated by ZT. This study demonstrated that metabolomics analysis is a powerful tool for providing novel insight into RA and for elucidating the potential mechanism of ZT.
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Affiliation(s)
- Jinjun Shan
- Jiangsu Key Laboratory of Pediatric Respiratory Disease, Institute of Pediatrics, Nanjing University of Chinese Medicine, Nanjing, China.,Medical Metabolomics Center, Nanjing University of Chinese Medicine, Nanjing, China
| | - Linxiu Peng
- State Key Laboratory Cultivation Base for TCM Quality and Efficacy, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China
| | - Wenjuan Qian
- State Key Laboratory Cultivation Base for TCM Quality and Efficacy, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China
| | - Tong Xie
- Jiangsu Key Laboratory of Pediatric Respiratory Disease, Institute of Pediatrics, Nanjing University of Chinese Medicine, Nanjing, China.,Medical Metabolomics Center, Nanjing University of Chinese Medicine, Nanjing, China
| | - An Kang
- State Key Laboratory Cultivation Base for TCM Quality and Efficacy, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China.,Jiangsu Key Laboratory for Functional Substance of Chinese Medicine, Nanjing, China
| | - Bei Gao
- Genome Center of UC Davis, NIH West Coast Metabolomics Center, Davis, CA, United States
| | - Liuqing Di
- Jiangsu Key Laboratory of Pediatric Respiratory Disease, Institute of Pediatrics, Nanjing University of Chinese Medicine, Nanjing, China.,State Key Laboratory Cultivation Base for TCM Quality and Efficacy, School of Pharmacy, Nanjing University of Chinese Medicine, Nanjing, China.,Jiangsu Key Laboratory for Functional Substance of Chinese Medicine, Nanjing, China
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73
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Nandania J, Peddinti G, Pessia A, Kokkonen M, Velagapudi V. Validation and Automation of a High-Throughput Multitargeted Method for Semiquantification of Endogenous Metabolites from Different Biological Matrices Using Tandem Mass Spectrometry. Metabolites 2018; 8:E44. [PMID: 30081599 PMCID: PMC6161248 DOI: 10.3390/metabo8030044] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2018] [Revised: 07/27/2018] [Accepted: 08/03/2018] [Indexed: 12/28/2022] Open
Abstract
The use of metabolomics profiling to understand the metabolism under different physiological states has increased in recent years, which created the need for robust analytical platforms. Here, we present a validated method for targeted and semiquantitative analysis of 102 polar metabolites that cover major metabolic pathways from 24 classes in a single 17.5-min assay. The method has been optimized for a wide range of biological matrices from various organisms, and involves automated sample preparation and data processing using an inhouse developed R-package. To ensure reliability, the method was validated for accuracy, precision, selectivity, specificity, linearity, recovery, and stability according to European Medicines Agency guidelines. We demonstrated an excellent repeatability of retention times (CV < 4%), calibration curves (R² ≥ 0.980) in their respective wide dynamic concentration ranges (CV < 3%), and concentrations (CV < 25%) of quality control samples interspersed within 25 batches analyzed over a period of one year. The robustness was demonstrated through a high correlation between metabolite concentrations measured using our method and the NIST reference values (R² = 0.967), including cross-platform comparability against the BIOCRATES AbsoluteIDQp180 kit (R² = 0.975) and NMR analyses (R² = 0.884). We have shown that our method can be successfully applied in many biomedical research fields and clinical trials, including epidemiological studies for biomarker discovery. In summary, a thorough validation demonstrated that our method is reproducible, robust, reliable, and suitable for metabolomics studies.
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Affiliation(s)
- Jatin Nandania
- Metabolomics Unit, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, HiLIFE, Tukholmankatu 8, Biomedicum 2U, 00290 Helsinki, Finland.
- Roche Diagnostics GmbH, Nonnenwald 2, 82377 Penzberg, Germany.
| | - Gopal Peddinti
- Computational Systems Medicine group, University of Helsinki, 00290 Helsinki, Finland.
- Technical Research Center of Finland, P.O. Box 1000, 02044 Espoo, Finland.
| | - Alberto Pessia
- Metabolomics Unit, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, HiLIFE, Tukholmankatu 8, Biomedicum 2U, 00290 Helsinki, Finland.
- Network Pharmacology for Precision Medicine Group, University of Helsinki, 00290 Helsinki, Finland.
| | - Meri Kokkonen
- Metabolomics Unit, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, HiLIFE, Tukholmankatu 8, Biomedicum 2U, 00290 Helsinki, Finland.
- Finnish Customs Laboratory, Tekniikantie 13, 02150 Espoo, Finland.
| | - Vidya Velagapudi
- Metabolomics Unit, Institute for Molecular Medicine Finland (FIMM), University of Helsinki, HiLIFE, Tukholmankatu 8, Biomedicum 2U, 00290 Helsinki, Finland.
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Alterations of eicosanoids and related mediators in patients with schizophrenia. J Psychiatr Res 2018; 102:168-178. [PMID: 29674269 DOI: 10.1016/j.jpsychires.2018.04.002] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Revised: 03/22/2018] [Accepted: 04/04/2018] [Indexed: 02/08/2023]
Abstract
Schizophrenia (SCZ) is a multifactorial psychiatric disorder. Currently, its molecular pathogenesis remains largely unknown, and no reliable test for diagnosis and therapy monitoring is available. Polyunsaturated fatty acids (PUFAs) and their derived eicosanoid signaling abnormalities are relevant to the pathophysiology of schizophrenia. However, comprehensive analysis of eicosanoids and related mediators for schizophrenia is very rare. In this study, we applied a targeted liquid chromatography-mass spectrometry based method to monitor 158 PUFAs, eicosanoids and related mediators from enzyme-dependent or independent pathways, in the serum samples of 109 healthy controls, and 115 schizophrenia patients at baseline and after an 8-week period of antipsychotic therapy. Twenty-three metabolites were identified to be significantly altered in SCZ patients at baseline compared to healthy controls, especially arachidonic acid (AA) derived eicosanoids. These disturbances may be related to altered immunological reactions and neurotransmitter signaling. After 8-week antipsychotic treatment, there were 22 metabolites, especially AA and linoleic acid derived eicosanoids, significantly altered in posttreatment patients. Some metabolites, such as several AA derived prostaglandins, thromboxanes, and di-hydroxy-eicosatrienoic acids were reversed toward normal levels after treatment. Based on univariate analysis and orthogonal partial least-squares discriminant analysis, anandamide, oleoylethanolamine, and AA were selected as a panel of potential biomarkers for differentiating baseline SCZ patients from controls, which showed a high sensitivity (0.907), good specificity (0.843) and excellent area under the receiver operating characteristic curve (0.940). This study provided a new perspective to understand the pathophysiological mechanism and identify potential biomarkers of SCZ.
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Li WW, Yang Y, Dai QG, Lin LL, Xie T, He LL, Tao JL, Shan JJ, Wang SC. Non-invasive urinary metabolomic profiles discriminate biliary atresia from infantile hepatitis syndrome. Metabolomics 2018; 14:90. [PMID: 30830373 DOI: 10.1007/s11306-018-1387-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2018] [Accepted: 06/14/2018] [Indexed: 12/26/2022]
Abstract
INTRODUCTION Neonatal cholestatic disorders are a group of hepatobiliary diseases occurring in the first 3 months of life. The most common causes of neonatal cholestasis are infantile hepatitis syndrome (IHS) and biliary atresia (BA). The clinical manifestations of the two diseases are too similar to distinguish them. However, early detection is very important in improving the clinical outcome of BA. Currently, a liver biopsy is the only proven and effective method used to differentially diagnose these two similar diseases in the clinic. However, this method is invasive. Therefore, sensitive and non-invasive biomarkers are needed to effectively differentiate between BA and IHS. We hypothesized that urinary metabolomics can produce unique metabolite profiles for BA and IHS. OBJECTIVES The aim of this study was to characterize urinary metabolomic profiles in infants with BA and IHS, and to identify differences among infants with BA, IHS, and normal controls (NC). METHODS Urine samples along with patient characteristics were obtained from 25 BA, 38 IHS, and 38 NC infants. A non-targeted gas chromatography-mass spectrometry (GC-MS) metabolomics method was used in conjunction with orthogonal partial least squares discriminant analysis (OPLS-DA) to explore the metabolomic profiles of BA, IHS, and NC infants. RESULTS In total, 41 differentially expressed metabolites between BA vs. NC, IHS vs. NC, and BA vs. IHS were identified. N-acetyl-D-mannosamine and alpha-aminoadipic acid were found to be highly accurate at distinguishing between BA and IHS. CONCLUSIONS BA and IHS infants have specific urinary metabolomic profiles. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be used to discriminate BA from IHS.
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Affiliation(s)
- Wei-Wei Li
- Department of Pediatrics, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
- Medical Metabolomics Center, Nanjing University of Chinese Medicine, Nanjing, China
| | - Yan Yang
- TCM Department, Beijing Children's Hospital Affiliated to Capital Medical University, Beijing, China
| | - Qi-Gang Dai
- Department of Pediatrics, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
| | - Li-Li Lin
- Department of Pediatrics, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
- Medical Metabolomics Center, Nanjing University of Chinese Medicine, Nanjing, China
| | - Tong Xie
- Department of Pediatrics, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
- Medical Metabolomics Center, Nanjing University of Chinese Medicine, Nanjing, China
| | - Li-Li He
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Jia-Lei Tao
- Department of Pediatrics, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China
- Medical Metabolomics Center, Nanjing University of Chinese Medicine, Nanjing, China
| | - Jin-Jun Shan
- Department of Pediatrics, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
- Medical Metabolomics Center, Nanjing University of Chinese Medicine, Nanjing, China.
| | - Shou-Chuan Wang
- Department of Pediatrics, Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, China.
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Centini R, Tsang M, Iwata T, Park H, Delrow J, Margineantu D, Iritani BM, Gu H, Liggitt HD, Kang J, Kang L, Hockenbery DM, Raftery D, Iritani BM. Loss of Fnip1 alters kidney developmental transcriptional program and synergizes with TSC1 loss to promote mTORC1 activation and renal cyst formation. PLoS One 2018; 13:e0197973. [PMID: 29897930 PMCID: PMC5999084 DOI: 10.1371/journal.pone.0197973] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2017] [Accepted: 05/13/2018] [Indexed: 12/16/2022] Open
Abstract
Birt-Hogg-Dube' Syndrome (BHDS) is a rare genetic disorder in humans characterized by skin hamartomas, lung cysts, pneumothorax, and increased risk of renal tumors. BHDS is caused by mutations in the BHD gene, which encodes for Folliculin, a cytoplasmic adapter protein that binds to Folliculin interacting proteins-1 and -2 (Fnip1, Fnip2) as well as the master energy sensor AMP kinase (AMPK). Whereas kidney-specific deletion of the Bhd gene in mice is known to result in polycystic kidney disease (PKD) and renal cell carcinoma, the roles of Fnip1 in renal cell development and function are unclear. In this study, we utilized mice with constitutive deletion of the Fnip1 gene to show that the loss of Fnip1 is sufficient to result in renal cyst formation, which was characterized by decreased AMPK activation, increased mTOR activation, and metabolic hyperactivation. Using RNAseq, we found that Fnip1 disruption resulted in many cellular and molecular changes previously implicated in the development of PKD in humans, including alterations in the expression of ion and amino acid transporters, increased cell adhesion, and increased inflammation. Loss of Fnip1 synergized with Tsc1 loss to hyperactivate mTOR, increase Erk activation, and greatly accelerate the development of PKD. Our results collectively define roles for Fnip1 in regulating kidney development and function, and provide a model for how loss of Fnip1 contributes to PKD and perhaps renal cell carcinoma.
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Affiliation(s)
- Ryan Centini
- The Department of Comparative Medicine, University of Washington, Seattle, Washington, United States of America
| | - Mark Tsang
- The Department of Comparative Medicine, University of Washington, Seattle, Washington, United States of America
| | - Terri Iwata
- The Department of Comparative Medicine, University of Washington, Seattle, Washington, United States of America
| | - Heon Park
- The Department of Comparative Medicine, University of Washington, Seattle, Washington, United States of America
| | - Jeffrey Delrow
- Genomics and Bioinformatics Shared Resources, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Daciana Margineantu
- Clinical Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Brandon M. Iritani
- The Department of Comparative Medicine, University of Washington, Seattle, Washington, United States of America
| | - Haiwei Gu
- Department of Anesthesiology and Pain Medicine, Mitochondria and Metabolism Center, Northwest Metabolomics Research Center, University of Washington, Seattle, Washington, United States of America
| | - H. Denny Liggitt
- The Department of Comparative Medicine, University of Washington, Seattle, Washington, United States of America
| | - Janella Kang
- The Department of Comparative Medicine, University of Washington, Seattle, Washington, United States of America
| | - Lim Kang
- The Department of Comparative Medicine, University of Washington, Seattle, Washington, United States of America
| | - David M. Hockenbery
- Clinical Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Daniel Raftery
- Department of Anesthesiology and Pain Medicine, Mitochondria and Metabolism Center, Northwest Metabolomics Research Center, University of Washington, Seattle, Washington, United States of America
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington, United States of America
| | - Brian M. Iritani
- The Department of Comparative Medicine, University of Washington, Seattle, Washington, United States of America
- * E-mail:
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Zha H, Cai Y, Yin Y, Wang Z, Li K, Zhu ZJ. SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery. Anal Chem 2018; 90:4062-4070. [PMID: 29485856 DOI: 10.1021/acs.analchem.7b05318] [Citation(s) in RCA: 88] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
The complexity of metabolome presents a great analytical challenge for quantitative metabolite profiling, and restricts the application of metabolomics in biomarker discovery. Targeted metabolomics using multiple-reaction monitoring (MRM) technique has excellent capability for quantitative analysis, but suffers from the limited metabolite coverage. To address this challenge, we developed a new strategy, namely, SWATHtoMRM, which utilizes the broad coverage of SWATH-MS technology to develop high-coverage targeted metabolomics method. Specifically, SWATH-MS technique was first utilized to untargeted profile one pooled biological sample and to acquire the MS2 spectra for all metabolites. Then, SWATHtoMRM was used to extract the large-scale MRM transitions for targeted analysis with coverage as high as 1000-2000 metabolites. Then, we demonstrated the advantages of SWATHtoMRM method in quantitative analysis such as coverage, reproducibility, sensitivity, and dynamic range. Finally, we applied our SWATHtoMRM approach to discover potential metabolite biomarkers for colorectal cancer (CRC) diagnosis. A high-coverage targeted metabolomics method with 1303 metabolites in one injection was developed to profile colorectal cancer tissues from CRC patients. A total of 20 potential metabolite biomarkers were discovered and validated for CRC diagnosis. In plasma samples from CRC patients, 17 out of 20 potential biomarkers were further validated to be associated with tumor resection, which may have a great potential in assessing the prognosis of CRC patients after tumor resection. Together, the SWATHtoMRM strategy provides a new way to develop high-coverage targeted metabolomics method, and facilitates the application of targeted metabolomics in disease biomarker discovery. The SWATHtoMRM program is freely available on the Internet ( http://www.zhulab.cn/software.php ).
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Affiliation(s)
- Haihong Zha
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry , Chinese Academy of Sciences , Shanghai , 200032 People's Republic of China.,University of Chinese Academy of Sciences , Beijing , 100049 People's Republic of China
| | - Yuping Cai
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry , Chinese Academy of Sciences , Shanghai , 200032 People's Republic of China.,University of Chinese Academy of Sciences , Beijing , 100049 People's Republic of China
| | - Yandong Yin
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry , Chinese Academy of Sciences , Shanghai , 200032 People's Republic of China
| | - Zhuozhong Wang
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry , Chinese Academy of Sciences , Shanghai , 200032 People's Republic of China.,Department of Epidemiology and Biostatistics, School of Public Health , Harbin Medical University , Harbin , 150086 People's Republic of China
| | - Kang Li
- Department of Epidemiology and Biostatistics, School of Public Health , Harbin Medical University , Harbin , 150086 People's Republic of China
| | - Zheng-Jiang Zhu
- Interdisciplinary Research Center on Biology and Chemistry, Shanghai Institute of Organic Chemistry , Chinese Academy of Sciences , Shanghai , 200032 People's Republic of China
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78
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Advances in analytical tools for high throughput strain engineering. Curr Opin Biotechnol 2018; 54:33-40. [PMID: 29448095 DOI: 10.1016/j.copbio.2018.01.027] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2018] [Revised: 01/24/2018] [Accepted: 01/28/2018] [Indexed: 01/09/2023]
Abstract
The emergence of inexpensive, base-perfect genome editing is revolutionising biology. Modern industrial biotechnology exploits the advances in genome editing in combination with automation, analytics and data integration to build high-throughput automated strain engineering pipelines also known as biofoundries. Biofoundries replace the slow and inconsistent artisanal processes used to build microbial cell factories with an automated design-build-test cycle, considerably reducing the time needed to deliver commercially viable strains. Testing and hence learning remains relatively shallow, but recent advances in analytical chemistry promise to increase the depth of characterization possible. Analytics combined with models of cellular physiology in automated systems biology pipelines should enable deeper learning and hence a steeper pitch of the learning cycle. This review explores the progress, advances and remaining bottlenecks of analytical tools for high throughput strain engineering.
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79
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Tugizimana F, Steenkamp PA, Piater LA, Dubery IA. Mass spectrometry in untargeted liquid chromatography/mass spectrometry metabolomics: Electrospray ionisation parameters and global coverage of the metabolome. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2018; 32:121-132. [PMID: 28990281 DOI: 10.1002/rcm.8010] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2017] [Revised: 09/25/2017] [Accepted: 09/28/2017] [Indexed: 06/07/2023]
Abstract
RATIONALE Liquid chromatography coupled to mass spectrometry (LC/MS) is a dominant analytical platform in metabolomics, because of the high sensitivity and resolution, thus enabling large-scale coverage of metabolomes. Correspondingly, electrospray ionisation (ESI) is the favoured ionisation method in untargeted LC/MS metabolomics given the ability to produce large numbers of ions. In the workflow of LC/ESI-MS metabolomics, maximising the ionisation efficiency over a wide mass range is inevitably an essential and determining step, subsequently defining the extent of coverage of the metabolome under investigation. Thus in this study, electronic factors related to the functioning of the ESI source, namely the capillary and sample cone voltages, were explored to investigate the influence on the data acquired in metabolomic investigations. METHODS Hydromethanolic samples from an untargeted study (sorghum plants responding dynamically to fungal infection) were analysed on a high-resolution/definition LC/ESI-MS system. Here the capillary and sample cone voltages of the ZSpray™ ESI source were varied between 1.5-3.0 kV and 10.0-40.0 V, respectively. The acquired data were processed with MarkerLynx™ software and analysed using central composite design response surface methodology and chemometric approaches (principal component analysis and orthogonal projection latent structures-discriminant analysis). RESULTS The results evidently demonstrate that both capillary and sampling cone voltages not only significantly influence the recorded MS signals with regard to the number and abundance of features, but also the overall structure of the collected data. This consequently impacts on the information extracted from the data and thus affects coverage of the metabolome. CONCLUSIONS The observations postulate in that, untargeted LC/MS metabolomics, 'what you see is what you ionise'. Although there is convergence of collected data under different ESI conditions, the nuances observed indicate that the exploration of different ion source settings could be the best trade-off in expanding and maximising the metabolome coverage in untargeted metabolomic experiments.
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Affiliation(s)
- Fidele Tugizimana
- Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg, South Africa
| | - Paul A Steenkamp
- Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg, South Africa
| | - Lizelle A Piater
- Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg, South Africa
| | - Ian A Dubery
- Department of Biochemistry, University of Johannesburg, Auckland Park, Johannesburg, South Africa
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80
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Li WW, Shan JJ, Lin LL, Xie T, He LL, Yang Y, Wang SC. Disturbance in Plasma Metabolic Profile in Different Types of Human Cytomegalovirus-Induced Liver Injury in Infants. Sci Rep 2017; 7:15696. [PMID: 29146975 PMCID: PMC5691185 DOI: 10.1038/s41598-017-16051-8] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2017] [Accepted: 11/06/2017] [Indexed: 02/08/2023] Open
Abstract
Human cytomegalovirus (HCMV) infection in infants is a global problem and the liver is a target organ of HCMV invasion. However, the mechanism by which HCMV causes different types of liver injury is unclear, and there are many difficulties in the differential diagnosis of HCMV infantile cholestatic hepatopathy (ICH) and extrahepatic biliary atresia (EHBA). We established a non-targeted gas chromatography-mass spectrometry metabolomics method in conjunction with orthogonal partial least squares-discriminate analysis based on 127 plasma samples from healthy controls, and patients with HCMV infantile hepatitis, HCMV ICH, and HCMV EHBA to explore the metabolite profile of different types of HCMV-induced liver injury. Twenty-nine metabolites related to multiple amino acid metabolism disorder, nitrogen metabolism and energy metabolism were identified. Carbamic acid, glutamate, L-aspartic acid, L-homoserine, and noradrenaline for HCMV ICH vs. HCMV EHBA were screened as potential biomarkers and showed excellent discriminant performance. These results not only revealed the potential pathogenesis of HCMV-induced liver injury, but also provided a feasible diagnostic tool for distinguishing EHBA from ICH.
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Affiliation(s)
- Wei-Wei Li
- Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Pediatrics, Nanjing, 210023, China.,Jiangsu Key Laboratory of Pediatric Respiratory Disease, Institute of Pediatics, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Jin-Jun Shan
- Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Pediatrics, Nanjing, 210023, China.,Jiangsu Key Laboratory of Pediatric Respiratory Disease, Institute of Pediatics, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Li-Li Lin
- Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Pediatrics, Nanjing, 210023, China.,Jiangsu Key Laboratory of Pediatric Respiratory Disease, Institute of Pediatics, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Tong Xie
- Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Pediatrics, Nanjing, 210023, China.,Jiangsu Key Laboratory of Pediatric Respiratory Disease, Institute of Pediatics, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Li-Li He
- Affiliated Hospital of Integrated Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, 210023, China
| | - Yan Yang
- Beijing Children's Hospital Affiliated to Capital Medical University, TCM Department, Beijing, 100045, China.
| | - Shou-Chuan Wang
- Affiliated Hospital of Nanjing University of Chinese Medicine, Department of Pediatrics, Nanjing, 210023, China.
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81
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Schelli K, Zhong F, Zhu J. Comparative metabolomics revealing Staphylococcus aureus metabolic response to different antibiotics. Microb Biotechnol 2017; 10:1764-1774. [PMID: 28815967 PMCID: PMC5658637 DOI: 10.1111/1751-7915.12839] [Citation(s) in RCA: 43] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2017] [Revised: 04/27/2017] [Accepted: 07/02/2017] [Indexed: 12/14/2022] Open
Abstract
It is known that changes in bacterial metabolism can contribute to the modulation of bacterial susceptibility to antibiotics. Understanding how bacterial metabolism is impacted by antibiotics may improve our understanding of the antibiotic mechanism of actions from a metabolic perspective. Here, we utilized a mass spectrometry‐based targeted metabolic profiling technique to characterize the metabolome of a pair of isogenic methicillin‐susceptible and resistant Staphylococcus aureus (MSSA and MRSA) strains RN450 and 450M treated with the sublethal dose of three antibiotics from different classes (β‐lactams, aminoglycosides and quinolones). These treatments induced a set of metabolic alterations after 6 h of co‐incubation with antibiotics. Similar and divergent metabolic perturbations were observed from different antibiotics to the tested strains. Different metabolic response from MSSA and MRSA to the same antibiotics was also detected in the study and indicated the potentially different stress response mechanism in MSSA and MRSA metabolism. This work has shown that a complex set of metabolic changes can be induced by a variety of antibiotics, and the comparative metabolomics strategy can provide a good understanding of this process from a metabolic perspective.
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Affiliation(s)
- Katie Schelli
- Department of Chemistry and Biochemistry, Miami University, 651 E High St., Oxford, OH, 45056, USA
| | - Fanyi Zhong
- Department of Chemistry and Biochemistry, Miami University, 651 E High St., Oxford, OH, 45056, USA
| | - Jiangjiang Zhu
- Department of Chemistry and Biochemistry, Miami University, 651 E High St., Oxford, OH, 45056, USA
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Chen Y, Zhou Z, Yang W, Bi N, Xu J, He J, Zhang R, Wang L, Abliz Z. Development of a Data-Independent Targeted Metabolomics Method for Relative Quantification Using Liquid Chromatography Coupled with Tandem Mass Spectrometry. Anal Chem 2017; 89:6954-6962. [PMID: 28574715 DOI: 10.1021/acs.analchem.6b04727] [Citation(s) in RCA: 35] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Quantitative metabolomics approaches can significantly improve the repeatability and reliability of metabolomics investigations but face critical technical challenges, owing to the vast number of unknown endogenous metabolites and the lack of authentic standards. The present study contributes to the development of a novel method known as "data-independent targeted quantitative metabolomics" (DITQM), which was used to investigate the label-free quantitative metabolomics of multiple known and unknown metabolites in biofluid samples. This approach initially involved the acquisition of MS/MS data for all metabolites in biosamples using a sequentially stepped targeted MS/MS (sst-MS/MS) method, in which multiple product ion scans were performed by selecting all ions in the targeted mass ranges as the precursor ions. Subsequently, scheduled multiple reaction monitoring (MRM) by LC-MS/MS of the metabolome was established for 1658 characteristic ion pairs of 1324 metabolites. For sensitive and accurate quantification of these metabolites, mixed calibration curves were generated using sequentially diluted standard reference plasma samples using established MRM methods. Relative concentrations of all metabolites in each sample were calculated without using individual authentic standards. To evaluate the reliability and applicability of this new method, the performance of DITQM was validated by comparison to absolute quantification of 12 acylcarnitines using authentic standards and traditional metabolomics analysis for lung cancer. The results proved that the DITQM protocol is more reliable and can significantly improve clustering effects and repeatability in biomarker discovery. In this study, we established a novel methodology to standardize and quantify large-scale metabolome, providing a new choice for metabolomics research and its clinical applications.
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Affiliation(s)
- Yanhua Chen
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050, P. R. China
| | - Zhi Zhou
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050, P. R. China
| | - Wei Yang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050, P. R. China.,Center for DMPK Research of Herbal Medicines, Institute of Chinese Materia Medica, China Academy of Chinese Medical Sciences , Beijing 100700, P. R. China
| | - Nan Bi
- Cancer Institute and Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100021, P. R. China
| | - Jing Xu
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050, P. R. China
| | - Jiuming He
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050, P. R. China
| | - Ruiping Zhang
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050, P. R. China
| | - Lvhua Wang
- Cancer Institute and Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100021, P. R. China
| | - Zeper Abliz
- State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College , Beijing 100050, P. R. China.,Centre for Bioimaging & Systems Biology, Minzu University of China , Beijing 100081, P. R. China
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83
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What can we do to refine the redundant data in LC–MS and GC–MS based metabolomics? Bioanalysis 2017; 9:235-238. [DOI: 10.4155/bio-2016-0272] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
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84
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Transcriptomic, proteomic, and metabolomic landscape of positional memory in the caudal fin of zebrafish. Proc Natl Acad Sci U S A 2017; 114:E717-E726. [PMID: 28096348 DOI: 10.1073/pnas.1620755114] [Citation(s) in RCA: 58] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Regeneration requires cells to regulate proliferation and patterning according to their spatial position. Positional memory is a property that enables regenerating cells to recall spatial information from the uninjured tissue. Positional memory is hypothesized to rely on gradients of molecules, few of which have been identified. Here, we quantified the global abundance of transcripts, proteins, and metabolites along the proximodistal axis of caudal fins of uninjured and regenerating adult zebrafish. Using this approach, we uncovered complex overlapping expression patterns for hundreds of molecules involved in diverse cellular functions, including development, bioelectric signaling, and amino acid and lipid metabolism. Moreover, 32 genes differentially expressed at the RNA level had concomitant differential expression of the encoded proteins. Thus, the identification of proximodistal differences in levels of RNAs, proteins, and metabolites will facilitate future functional studies of positional memory during appendage regeneration.
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85
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Gorrochategui E, Jaumot J, Lacorte S, Tauler R. Data analysis strategies for targeted and untargeted LC-MS metabolomic studies: Overview and workflow. Trends Analyt Chem 2016. [DOI: 10.1016/j.trac.2016.07.004] [Citation(s) in RCA: 187] [Impact Index Per Article: 23.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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86
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Nontargeted diagnostic ion network analysis (NINA): A software to streamline the analytical workflow for untargeted characterization of natural medicines. J Pharm Biomed Anal 2016; 131:40-47. [PMID: 27521988 DOI: 10.1016/j.jpba.2016.08.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2016] [Revised: 07/27/2016] [Accepted: 08/04/2016] [Indexed: 12/13/2022]
Abstract
The characterization of herbal prescriptions serves as a foundation for quality control and regulation of herbal medicines. Previously, the characterization of herbal chemicals from natural medicines often relied on the analysis of signature fragment ions from the acquired tandem mass spectrometry (MS/MS) spectra with prior knowledge of the herbal species present in the herbal prescriptions of interest. Nevertheless, such an approach is often limited to target components, and it risks missing the critical components that we have no prior knowledge of. We previously reported a "diagnostic ion-guided network bridging" strategy. It is a generally applicable and robust approach to analyze unknown substances from complex mixtures in an untargeted manner. In this study, we have developed a standalone software named "Nontargeted Diagnostic Ion Network Analysis (NINA)" with a graphical user interface based on a strategy for post-acquisition data analysis. NINA allows one to rapidly determine the nontargeted diagnostic ions (NIs) by summarizing all of the fragment ions shared by the precursors from the acquired MS/MS spectra. A NI-guided network using bridging components that possess two or more NIs can then be established via NINA. With such a network, we could sequentially identify the structures of all the NIs once a single compound has been identified de novo. The structures of NIs can then be used as "priori" knowledge to narrow the candidates containing the sub-structure of the corresponding NI from the database hits. Subsequently, we applied the NINA software to the characterization of a model herbal prescription, Re-Du-Ning injection, and rapidly identified 56 herbal chemicals from the prescription using an ultra-performance liquid chromatography quadrupole time-of-flight system in the negative mode with no knowledge of the herbal species or herbal chemicals in the mixture. Therefore, we believe the applications of NINA will greatly facilitate the characterization of complex mixtures, such as natural medicines, especially when no advance information is available. In addition to herbal medicines, the NINA-based workflow will also benefit many other fields, such as environmental analysis, nutritional science, and forensic analysis.
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87
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Deng L, Gu H, Zhu J, Nagana Gowda GA, Djukovic D, Chiorean EG, Raftery D. Combining NMR and LC/MS Using Backward Variable Elimination: Metabolomics Analysis of Colorectal Cancer, Polyps, and Healthy Controls. Anal Chem 2016; 88:7975-83. [PMID: 27437783 DOI: 10.1021/acs.analchem.6b00885] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) play important roles in metabolomics. The complementary features of NMR and MS make their combination very attractive; however, currently the vast majority of metabolomics studies use either NMR or MS separately, and variable selection that combines NMR and MS for biomarker identification and statistical modeling is still not well developed. In this study focused on methodology, we developed a backward variable elimination partial least-squares discriminant analysis algorithm embedded with Monte Carlo cross validation (MCCV-BVE-PLSDA), to combine NMR and targeted liquid chromatography (LC)/MS data. Using the metabolomics analysis of serum for the detection of colorectal cancer (CRC) and polyps as an example, we demonstrate that variable selection is vitally important in combining NMR and MS data. The combined approach was better than using NMR or LC/MS data alone in providing significantly improved predictive accuracy in all the pairwise comparisons among CRC, polyps, and healthy controls. Using this approach, we selected a subset of metabolites responsible for the improved separation for each pairwise comparison, and we achieved a comprehensive profile of altered metabolite levels, including those in glycolysis, the TCA cycle, amino acid metabolism, and other pathways that were related to CRC and polyps. MCCV-BVE-PLSDA is straightforward, easy to implement, and highly useful for studying the contribution of each individual variable to multivariate statistical models. On the basis of these results, we recommend using an appropriate variable selection step, such as MCCV-BVE-PLSDA, when analyzing data from multiple analytical platforms to obtain improved statistical performance and a more accurate biological interpretation, especially for biomarker discovery. Importantly, the approach described here is relatively universal and can be easily expanded for combination with other analytical technologies.
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Affiliation(s)
- Lingli Deng
- Department of Information Engineering, East China University of Technology , 418 Guanglan Avenue, Nanchang, Jiangxi Province 330013, China.,Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States
| | - Haiwei Gu
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States.,Jiangxi Key Laboratory for Mass Spectrometry and Instrumentation, East China University of Technology , 418 Guanglan Avenue, Nanchang, Jiangxi Province 330013, China
| | - Jiangjiang Zhu
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States
| | - G A Nagana Gowda
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States
| | - Danijel Djukovic
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States
| | - E Gabriela Chiorean
- Department of Medicine, University of Washington , 825 Eastlake Avenue East, Seattle, Washington 98109, United States.,Indiana University Melvin and Bren Simon Cancer Center , 535 Barnhill Drive, Indianapolis, Indiana 46202, United States
| | - Daniel Raftery
- Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington , 850 Republican Street, Seattle, Washington 98109, United States.,Department of Chemistry, Purdue University , 560 Oval Drive, West Lafayette, Indiana 47907, United States.,Public Health Sciences Division, Fred Hutchinson Cancer Research Center , 1100 Fairview Avenue North, Seattle, Washington 98109, United States
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88
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An improved pseudotargeted metabolomics approach using multiple ion monitoring with time-staggered ion lists based on ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry. Anal Chim Acta 2016; 927:82-8. [DOI: 10.1016/j.aca.2016.05.008] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2016] [Revised: 04/30/2016] [Accepted: 05/02/2016] [Indexed: 01/13/2023]
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89
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Cajka T, Fiehn O. Toward Merging Untargeted and Targeted Methods in Mass Spectrometry-Based Metabolomics and Lipidomics. Anal Chem 2015; 88:524-45. [PMID: 26637011 DOI: 10.1021/acs.analchem.5b04491] [Citation(s) in RCA: 528] [Impact Index Per Article: 58.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Affiliation(s)
- Tomas Cajka
- UC Davis Genome Center-Metabolomics, University of California Davis , 451 Health Sciences Drive, Davis, California 95616, United States
| | - Oliver Fiehn
- UC Davis Genome Center-Metabolomics, University of California Davis , 451 Health Sciences Drive, Davis, California 95616, United States.,King Abdulaziz University , Faculty of Science, Biochemistry Department, P.O. Box 80203, Jeddah 21589, Saudi Arabia
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