1
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Day F, O'Sullivan J, Ramzan F, Pook C. Polar metabolomics using trichloroacetic acid extraction and porous graphitic carbon stationary phase. Metabolomics 2024; 20:77. [PMID: 39014104 PMCID: PMC11252196 DOI: 10.1007/s11306-024-02146-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Accepted: 06/24/2024] [Indexed: 07/18/2024]
Abstract
INTRODUCTION Accurately identifying and quantifying polar metabolites using untargeted metabolomics has proven challenging in comparison to mid to non-polar metabolites. Hydrophilic interaction chromatography and gas chromatography-mass spectrometry are predominantly used to target polar metabolites. OBJECTIVES This study aims to demonstrate a simple one-step extraction combined with liquid chromatography-mass spectrometry (LC-MS) that reliably retains polar metabolites. METHODS The method involves a MilliQ + 10% trichloroacetic acid extraction from 6 healthy individuals serum, combined with porous graphitic carbon liquid chromatography-mass spectrometry (LC-MS). The coefficient of variation (CV) assessed retention reliability of polar metabolites with logP as low as - 9. QreSS (Quantification, Retention, and System Suitability) internal standards determined the method's consistency and recovery efficiency. RESULTS The method demonstrated reliable retention (CV < 0.30) of polar metabolites within a logP range of - 9.1 to 5.6. QreSS internal standards confirmed consistent performance (CV < 0.16) and effective recovery (70-130%) of polar to mid-polar metabolites. Quality control dilution series demonstrated that ~ 80% of annotated metabolites could be accurately quantified (Pearson's correlation coefficient > 0.80) within their concentration range. Repeatability was demonstrated through clustering of repeated extractions from a single sample. CONCLUSION This LC-MS method is better suited to covering the polar segment of the metabolome than current methods, offering a reliable and efficient approach for accurate quantification of polar metabolites in untargeted metabolomics.
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Affiliation(s)
- Francesca Day
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Justin O'Sullivan
- Liggins Institute, The University of Auckland, Auckland, New Zealand
- The Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
- Australian Parkinson's Mission, Garvan Institute of Medical Research, 384 Victoria Street, Sydney, Darlinghurst, NSW, 2010, Australia
- A*STAR Singapore Institute for Clinical Sciences, Singapore, Singapore
| | - Farha Ramzan
- Liggins Institute, The University of Auckland, Auckland, New Zealand
| | - Chris Pook
- Liggins Institute, The University of Auckland, Auckland, New Zealand.
- School of Chemical Sciences, University of Auckland, 23 Symonds St., Auckland, 1010, New Zealand.
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2
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Aly AA, Górecki T. Two-dimensional liquid chromatography with reversed phase in both dimensions: A review. J Chromatogr A 2024; 1721:464824. [PMID: 38522405 DOI: 10.1016/j.chroma.2024.464824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2023] [Revised: 03/14/2024] [Accepted: 03/16/2024] [Indexed: 03/26/2024]
Abstract
Two-dimensional liquid chromatography (2D-LC), and in particular comprehensive two-dimensional liquid chromatography (LC×LC), offers increased peak capacity, resolution and selectivity compared to one-dimensional liquid chromatography. It is commonly accepted that the technique produces the best results when the separation mechanisms in the two dimensions are completely orthogonal; however, the use of similar separation mechanisms in both dimensions has been gaining popularity as it helps avoid difficulties related to mobile phase incompatibility and poor column efficiency. The remarkable advantages of using reversed phase in both dimensions (RPLC×RPLC) over other separation mechanisms made it a promising technique in the separation of complex samples. This review discusses some physical and practical considerations in method development for 2D-LC involving the use of RP in both dimensions. In addition, an extensive overview is presented of different applications that relied on RPLC×RPLC and 2D-LC with reversed phase column combinations to separate components of complex samples in different fields including food analysis, natural product analysis, environmental analysis, proteomics, lipidomics and metabolomics.
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Affiliation(s)
- Alshymaa A Aly
- Analytical Chemistry Department, Faculty of Pharmacy, Minia University, Menia Governorate, Arab Republic of Egypt; Department of Chemistry, University of Waterloo, ON, Canada
| | - Tadeusz Górecki
- Department of Chemistry, University of Waterloo, ON, Canada.
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3
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Sun CK, Tsai TH. Pharmacokinetic and pharmacodynamic herb-drug interactions of common over-the-counter pain medications. Biomed Chromatogr 2023:e5591. [PMID: 36710381 DOI: 10.1002/bmc.5591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 12/13/2022] [Accepted: 12/15/2022] [Indexed: 01/31/2023]
Abstract
Pain is one of the most common reasons for seeking medical intervention, and self-medication with over-the-counter medications and/or traditional herbal remedies has become increasingly popular. In this review, original articles on understanding possible herb-drug interactions between traditional herbs and four major pain medications-acetaminophen, aspirin, ibuprofen and naproxen-are compiled and analyzed. In terms of analytical methods, high-performance liquid chromatography using an isocratic eluent system coupled to biological sample clean-up is the most common, while a wide variety of detectors have been observed, including a photodiode array, variable wavelength detector, electrochemical detector and tandem mass spectrometer. Both synergistic and anti-synergistic effects were observed for acetaminophen and aspirin, while only synergistic effects have been found for naproxen. Currently, no interactions have been reported for ibuprofen.
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Affiliation(s)
- Chung-Kai Sun
- Institute of Traditional Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Tung-Hu Tsai
- Institute of Traditional Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Graduate Institute of Acupuncture Science, China Medical University, Taichung, Taiwan.,School of Pharmacy, Kaohsiung Medical University, Kaohsiung, Taiwan
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4
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Creydt M, Fischer M. Food metabolomics: Latest hardware-developments for nontargeted food authenticity and food safety testing. Electrophoresis 2022; 43:2334-2350. [PMID: 36104152 DOI: 10.1002/elps.202200126] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 08/10/2022] [Accepted: 09/05/2022] [Indexed: 12/14/2022]
Abstract
The analytical requirements for food testing have increased significantly in recent years. On the one hand, because food fraud is becoming an ever-greater challenge worldwide, and on the other hand because food safety is often difficult to monitor due to the far-reaching trade chains. In addition, the expectations of consumers on the quality of food have increased, and they are demanding extensive information. Cutting-edge analytical methods are required to meet these demands. In this context, non-targeted metabolomics strategies using mass and nuclear magnetic resonance spectrometers (mass spectrometry [MS]) have proven to be very suitable. MS-based approaches are of particular importance as they provide a comparatively high analytical coverage of the metabolome. Accordingly, the efficiency to address even challenging issues is high. A variety of hardware developments, which are explained in this review, have contributed to these advances. In addition, the potential of future developments is highlighted, some of which are currently not yet commercially available or only used to a comparatively small extent but are expected to gain in importance in the coming years.
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Affiliation(s)
- Marina Creydt
- Hamburg School of Food Science - Institute of Food Chemistry, University of Hamburg, Hamburg, Germany
| | - Markus Fischer
- Hamburg School of Food Science - Institute of Food Chemistry, University of Hamburg, Hamburg, Germany
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5
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Delvaux A, Rathahao-Paris E, Alves S. Different ion mobility-mass spectrometry coupling techniques to promote metabolomics. MASS SPECTROMETRY REVIEWS 2022; 41:695-721. [PMID: 33492707 DOI: 10.1002/mas.21685] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Metabolomics has become increasingly popular in recent years for many applications ranging from clinical diagnosis, human health to biotechnological questioning. Despite technological advances, metabolomic studies are still currently limited by the difficulty of identifying all metabolites, a class of compounds with great chemical diversity. Although lengthy chromatographic analyses are often used to obtain comprehensive data, many isobar and isomer metabolites still remain unresolved, which is a critical point for the compound identification. Currently, ion mobility spectrometry is being explored in metabolomics as a way to improve metabolome coverage, analysis throughput and isomer separation. In this review, all the steps of a typical workflow for untargeted metabolomics are discussed considering the use of an ion mobility instrument. An overview of metabolomics is first presented followed by a brief description of ion mobility instrumentation. The ion mobility potential for complex mixture analysis is discussed regarding its coupling with a mass spectrometer alone, providing gas-phase separation before mass analysis as well as its combination with different separation platforms (conventional hyphenation but also multidimensional ion mobility couplings), offering multidimensional separation. Various instrumental and analytical conditions for improving the ion mobility separation are also described. Finally, data mining, including software packages and visualization approaches, as well as the construction of ion mobility databases for the metabolite identification are examined.
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Affiliation(s)
- Aurélie Delvaux
- Faculté des Sciences et de l'Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), Sorbonne Université, Paris, 75005, France
| | - Estelle Rathahao-Paris
- Faculté des Sciences et de l'Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), Sorbonne Université, Paris, 75005, France
- Département Médicaments et Technologies pour la Santé (DMTS), SPI, Université Paris-Saclay, CEA, INRAE, Gif-sur-Yvette, 91191, France
| | - Sandra Alves
- Faculté des Sciences et de l'Ingénierie, Institut Parisien de Chimie Moléculaire (IPCM), Sorbonne Université, Paris, 75005, France
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Yan S, Bhawal R, Yin Z, Thannhauser TW, Zhang S. Recent advances in proteomics and metabolomics in plants. MOLECULAR HORTICULTURE 2022; 2:17. [PMID: 37789425 PMCID: PMC10514990 DOI: 10.1186/s43897-022-00038-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 06/20/2022] [Indexed: 10/05/2023]
Abstract
Over the past decade, systems biology and plant-omics have increasingly become the main stream in plant biology research. New developments in mass spectrometry and bioinformatics tools, and methodological schema to integrate multi-omics data have leveraged recent advances in proteomics and metabolomics. These progresses are driving a rapid evolution in the field of plant research, greatly facilitating our understanding of the mechanistic aspects of plant metabolisms and the interactions of plants with their external environment. Here, we review the recent progresses in MS-based proteomics and metabolomics tools and workflows with a special focus on their applications to plant biology research using several case studies related to mechanistic understanding of stress response, gene/protein function characterization, metabolic and signaling pathways exploration, and natural product discovery. We also present a projection concerning future perspectives in MS-based proteomics and metabolomics development including their applications to and challenges for system biology. This review is intended to provide readers with an overview of how advanced MS technology, and integrated application of proteomics and metabolomics can be used to advance plant system biology research.
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Affiliation(s)
- Shijuan Yan
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | - Ruchika Bhawal
- Proteomics and Metabolomics Facility, Institute of Biotechnology, Cornell University, 139 Biotechnology Building, 526 Campus Road, Ithaca, NY, 14853, USA
| | - Zhibin Yin
- Guangdong Key Laboratory for Crop Germplasm Resources Preservation and Utilization, Agro-biological Gene Research Center, Guangdong Academy of Agricultural Sciences, Guangzhou, China
| | | | - Sheng Zhang
- Proteomics and Metabolomics Facility, Institute of Biotechnology, Cornell University, 139 Biotechnology Building, 526 Campus Road, Ithaca, NY, 14853, USA.
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7
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Xia Q, Zhou C, Wu Z, Pan D, Cao J. Proposing processomics as the methodology of food quality monitoring: Re-conceptualization, opportunities, and challenges. Curr Opin Food Sci 2022. [DOI: 10.1016/j.cofs.2022.100823] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
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8
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Pičmanová M, Moses T, Cortada-Garcia J, Barrett G, Florance H, Pandor S, Burgess K. Rapid HILIC-Z ion mobility mass spectrometry (RHIMMS) method for untargeted metabolomics of complex biological samples. Metabolomics 2022; 18:16. [PMID: 35229219 PMCID: PMC8885480 DOI: 10.1007/s11306-022-01871-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 01/19/2022] [Indexed: 11/03/2022]
Abstract
INTRODUCTION Recent advances in high-throughput methodologies in the 'omics' and synthetic biology fields call for rapid and sensitive workflows in the metabolic phenotyping of complex biological samples. OBJECTIVE The objective of this research was to evaluate a straightforward to implement LC-MS metabolomics method using a commercially available chromatography column that provides increased throughput. Reducing run time can potentially impact chromatography and therefore the effects of ion mobility spectrometry to expand peak capacity were also evaluated. Additional confidence provided via collision cross section measurements for detected features was also explored. METHODS A rapid untargeted metabolomics workflow was developed with broad metabolome coverage, combining zwitterionic-phase hydrophilic interaction chromatography (HILIC-Z) with drift tube ion mobility-quadrupole time-of-flight (DTIM-qTOF) mass spectrometry. The analytical performance of our method was explored using extracts from complex biological samples, including a reproducibility study on chicken serum and a simple comparative study on a bacterial metabolome. RESULTS The method is acronymised RHIMMS for rapid HILIC-Z ion mobility mass spectrometry. We present the RHIMMS workflow starting with data acquisition, followed by data processing and analysis. RHIMMS demonstrates improved chromatographic separation for a selection of metabolites with wide physicochemical properties while maintaining reproducibility at better than 20% over 200 injections at 3.5 min per sample for the selected metabolites, and a mean of 13.9% for the top 50 metabolites by intensity. Additionally, the combination of rapid chromatographic separation with ion mobility allows improved annotation and the ability to distinguish isobaric compounds. CONCLUSION Our results demonstrate RHIMMS to be a rapid, reproducible, sensitive and high-resolution analytical platform that is highly applicable to the untargeted metabolomics analysis of complex samples.
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Affiliation(s)
- Martina Pičmanová
- Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
| | - Tessa Moses
- EdinOmics, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
| | - Joan Cortada-Garcia
- Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
| | - Georgina Barrett
- Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK
| | - Hannah Florance
- Agilent Technologies UK Limited, Cheadle Royal Business Park Stockport, Cheshire, SK8 3GR, UK
| | - Sufyan Pandor
- Agilent Technologies UK Limited, Cheadle Royal Business Park Stockport, Cheshire, SK8 3GR, UK
| | - Karl Burgess
- Institute of Quantitative Biology, Biochemistry and Biotechnology, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK.
- EdinOmics, University of Edinburgh, Max Born Crescent, Edinburgh, EH9 3BF, UK.
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9
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Defining Blood Plasma and Serum Metabolome by GC-MS. Metabolites 2021; 12:metabo12010015. [PMID: 35050137 PMCID: PMC8779220 DOI: 10.3390/metabo12010015] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2021] [Revised: 12/18/2021] [Accepted: 12/21/2021] [Indexed: 01/04/2023] Open
Abstract
Metabolomics uses advanced analytical chemistry methods to analyze metabolites in biological samples. The most intensively studied samples are blood and its liquid components: plasma and serum. Armed with advanced equipment and progressive software solutions, the scientific community has shown that small molecules’ roles in living systems are not limited to traditional “building blocks” or “just fuel” for cellular energy. As a result, the conclusions based on studying the metabolome are finding practical reflection in molecular medicine and a better understanding of fundamental biochemical processes in living systems. This review is not a detailed protocol of metabolomic analysis. However, it should support the reader with information about the achievements in the whole process of metabolic exploration of human plasma and serum using mass spectrometry combined with gas chromatography.
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10
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Ndolo SM, Zachariah M, Molefi L, Phaladze N, Sichilongo KF. Mass spectrometry based metabolomics for small molecule metabolites mining and confirmation as potential biomarkers for schistosomiasis - case of the Okavango Delta communities in Botswana. Expert Rev Proteomics 2021; 19:61-71. [PMID: 34846232 DOI: 10.1080/14789450.2021.2012454] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Metabolomics for identifying schistosomiasis biomarkers in noninvasive samples at various infection stages is being actively explored. The literature on the traditional detection of schistosomiasis in human specimens is well documented. However, state-of-the-art technologies based on mass spectrometry have simplified the use of biomarkers for diagnostics. This review examines methods currently in use for the metabolomics of small molecules using separation science and mass spectrometry. AREA COVERED This article highlights the evolution of traditional diagnostic methods for schistosomiasis based on inter alia microscopy, immunology, and polymerase chain reaction. An exhaustive literature search of metabolite mining, focusing on separation science and mass spectrometry, is presented. A comparative analysis of mass spectrometry methods was undertaken, including a projection for the future. EXPERT COMMENTARY Mass spectrometry metabolomics for schistosomiasis will lead to biomarker discovery for noninvasive human samples. These biomarkers, together with those from other neglected tropical diseases, such as malaria and sleeping sickness, could be incorporated as arrays on a single biosensor chip and inserted into smartphones, in order to improve surveillance, monitoring, and management.
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Affiliation(s)
- Sedireng M Ndolo
- College of Open Schooling, Botswana Open University, Gaborone Regional Campus, Gaborone, Botswana
| | - Matshediso Zachariah
- School of Allied Health Professions, Faculty of Health Sciences, University of Botswana, Gaborone, Botswana
| | - Lebotse Molefi
- School of Allied Health Professions, Faculty of Health Sciences, University of Botswana, Gaborone, Botswana
| | - Nthabiseng Phaladze
- School of Nursing, Faculty of Health Sciences, University of Botswana, Gaborone, Botswana
| | - Kwenga F Sichilongo
- Chemistry Department, Faculty of Science, University of Botswana, Gaborone, Botswana
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11
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Guo Y, Liu F, Chen M, Tian Q, Tian X, Xiong Q, Huang C. Huangjinsan ameliorates adenine-induced chronic kidney disease by regulating metabolic profiling. J Sep Sci 2021; 44:4384-4394. [PMID: 34688222 DOI: 10.1002/jssc.202100542] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 10/01/2021] [Accepted: 10/19/2021] [Indexed: 11/08/2022]
Abstract
Chronic kidney disease is an increasingly serious public health problem worldwide. Our recent studies have shown that Huangjinsan has a renal protective effect on chronic kidney disease, but the specific mechanism by which this effect occurs is not clear. To study the therapeutic effect of Huangjinsan on chronic kidney disease and to explore its possible mechanism of action through nontargeted metabolomics methods, a chronic kidney disease rat model was induced by adenine, and the Huangjinsan extract was given by oral gavage. Body weight, the kidney index, pathological sections, and a series of biochemical indicators were measured. High-performance liquid chromatography quadrupole time-of-flight mass spectrometry was used to analyze the changes in the plasma metabolome. Huangjinsan significantly reduced indicators of kidney damage, including total protein, albumin, the total protein to creatinine ratio, and the albumin to creatinine ratio in urine, as well as IL-2, MCP-1α, and blood urea levels in plasma. Based on nontargeted metabolomics, 13 metabolites related to chronic kidney disease were discovered. These metabolites are closely related to glycerophospholipid metabolism, arginine and proline metabolism, and sphingolipid metabolism. We found that Huangjinsan can restore the renal function of adenine-induced chronic kidney disease by regulating the metabolic profile.
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Affiliation(s)
- Yuejiao Guo
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, P. R. China
| | - Fang Liu
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, P. R. China.,University of Chinese Academy of Sciences, Beijing, P. R. China
| | - MingCang Chen
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, P. R. China.,University of Chinese Academy of Sciences, Beijing, P. R. China
| | - Qiang Tian
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, P. R. China
| | - Xiaoting Tian
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, P. R. China.,University of Chinese Academy of Sciences, Beijing, P. R. China
| | - Qiang Xiong
- College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, P. R. China
| | - Chenggang Huang
- Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, P. R. China.,University of Chinese Academy of Sciences, Beijing, P. R. China
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12
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Furlani IL, da Cruz Nunes E, Canuto GAB, Macedo AN, Oliveira RV. Liquid Chromatography-Mass Spectrometry for Clinical Metabolomics: An Overview. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1336:179-213. [PMID: 34628633 DOI: 10.1007/978-3-030-77252-9_10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/28/2023]
Abstract
Metabolomics is a discipline that offers a comprehensive analysis of metabolites in biological samples. In the last decades, the notable evolution in liquid chromatography and mass spectrometry technologies has driven an exponential progress in LC-MS-based metabolomics. Targeted and untargeted metabolomics strategies are important tools in health and medical science, especially in the study of disease-related biomarkers, drug discovery and development, toxicology, diet, physical exercise, and precision medicine. Clinical and biological problems can now be understood in terms of metabolic phenotyping. This overview highlights the current approaches to LC-MS-based metabolomics analysis and its applications in the clinical research.
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Affiliation(s)
- Izadora L Furlani
- Núcleo de Pesquisa em Cromatografia (Separare), Department of Chemistry, Federal University of São Carlos, São Carlos, SP, Brazil
| | - Estéfane da Cruz Nunes
- Department of Analytical Chemistry, Institute of Chemistry, Federal University of Bahia, Salvador, BA, Brazil
| | - Gisele A B Canuto
- Department of Analytical Chemistry, Institute of Chemistry, Federal University of Bahia, Salvador, BA, Brazil
| | - Adriana N Macedo
- Department of Chemistry, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
| | - Regina V Oliveira
- Núcleo de Pesquisa em Cromatografia (Separare), Department of Chemistry, Federal University of São Carlos, São Carlos, SP, Brazil.
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13
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Mass spectrometry based metabolomics of volume-restricted in-vivo brain samples: Actual status and the way forward. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116365] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
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14
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Baggio G, Groves RA, Chignola R, Piacenza E, Presentato A, Lewis IA, Lampis S, Vallini G, Turner RJ. Untargeted Metabolomics Investigation on Selenite Reduction to Elemental Selenium by Bacillus mycoides SeITE01. Front Microbiol 2021; 12:711000. [PMID: 34603239 PMCID: PMC8481872 DOI: 10.3389/fmicb.2021.711000] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 08/16/2021] [Indexed: 12/02/2022] Open
Abstract
Bacillus mycoides SeITE01 is an environmental isolate that transforms the oxyanion selenite (SeO 3 2 - ) into the less bioavailable elemental selenium (Se0) forming biogenic selenium nanoparticles (Bio-SeNPs). In the present study, the reduction of sodium selenite (Na2SeO3) by SeITE01 strain and the effect ofSeO 3 2 - exposure on the bacterial cells was examined through untargeted metabolomics. A time-course approach was used to monitor both cell pellet and cell free spent medium (referred as intracellular and extracellular, respectively) metabolites in SeITE01 cells treated or not withSeO 3 2 - . The results show substantial biochemical changes in SeITE01 cells when exposed toSeO 3 2 - . The initial uptake ofSeO 3 2 - by SeITE01 cells (3h after inoculation) shows both an increase in intracellular levels of 4-hydroxybenzoate and indole-3-acetic acid, and an extracellular accumulation of guanosine, which are metabolites involved in general stress response adapting strategies. Proactive and defensive mechanisms againstSeO 3 2 - are observed between the end of lag (12h) and beginning of exponential (18h) phases. Glutathione and N-acetyl-L-cysteine are thiol compounds that would be mainly involved in Painter-type reaction for the reduction and detoxification ofSeO 3 2 - to Se0. In these growth stages, thiol metabolites perform a dual role, both acting against the toxic and harmful presence of the oxyanion and as substrate or reducing sources to scavenge ROS production. Moreover, detection of the amino acids L-threonine and ornithine suggests changes in membrane lipids. Starting from stationary phase (24 and 48h), metabolites related to the formation and release of SeNPs in the extracellular environment begin to be observed. 5-hydroxyindole acetate, D-[+]-glucosamine, 4-methyl-2-oxo pentanoic acid, and ethanolamine phosphate may represent signaling strategies following SeNPs release from the cytoplasmic compartment, with consequent damage to SeITE01 cell membranes. This is also accompanied by intracellular accumulation of trans-4-hydroxyproline and L-proline, which likely represent osmoprotectant activity. The identification of these metabolites suggests the activation of signaling strategies that would protect the bacterial cells fromSeO 3 2 - toxicity while it is converting into SeNPs.
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Affiliation(s)
- Greta Baggio
- Department of Biotechnology, University of Verona, Verona, Italy
- Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Ryan A. Groves
- Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Roberto Chignola
- Department of Biotechnology, University of Verona, Verona, Italy
| | - Elena Piacenza
- Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University of Palermo, Palermo, Italy
| | - Alessandro Presentato
- Department of Biological, Chemical and Pharmaceutical Sciences and Technologies (STEBICEF), University of Palermo, Palermo, Italy
| | - Ian A. Lewis
- Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Silvia Lampis
- Department of Biotechnology, University of Verona, Verona, Italy
| | - Giovanni Vallini
- Department of Biotechnology, University of Verona, Verona, Italy
| | - Raymond J. Turner
- Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
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15
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Enko D, Zelzer S, Herrmann M, Krause R, Meinitzer A. Implementation of a Dual-Column Liquid Chromatography-Tandem Mass-Spectrometry Method for the Quantification of Isavuconazole in Clinical Practice. J Lab Physicians 2021; 13:123-128. [PMID: 34483556 PMCID: PMC8409122 DOI: 10.1055/s-0041-1730755] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Objectives
Therapeutic drug monitoring (TDM) of isavuconazole, which is a novel broad-spectrum antimycoticum against invasive fungal infections, ensures an effective exposure of the drug and minimizes the risk of toxicity. This study is aimed at evaluating the analytical performance of a dual-column liquid chromatography-tandem mass-spectrometry (LC-MS/MS) method for isavuconazole quantification.
Materials and Methods
The method was performed on a Voyager TSQ Quantum triple quadrupole instrument equipped with an Ultimate 3000 chromatography system (Thermo Fisher Scientific, San Jose, California, United States). Analytical and preanalytical requirements of the isavuconazole LC-MS/MS method were evaluated. Sample stability measurements were performed at room temperature (RT) and in serum tubes with separator gel.
Results
The isavuconazole LC-MS/MS method was linear over the concentration range of 0.2 to 12.8 mg/L. The coefficient of determination (
r2
) always exceeded 0.999. Within- and between-run precision ranged between 1.4 to 2.9% and 1.5 to 3.0%, the recovery between 93.9 and 102.7%. At RT, serum samples were stable for 3 days. Isavuconazole serum concentrations were significantly lower after incubation (18 hours) in serum tubes with separator gel at RT.
Conclusion
The dual-column isavuconazole LC-MS/MS is a reliable tool for the TDM of isavuconazole. Serum samples are stable for at least 3 days and should be collected in tubes without separator gel.
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Affiliation(s)
- Dietmar Enko
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria.,Institute of Clinical Chemistry and Laboratory Medicine, General Hospital Hochsteiermark, Leoben, Austria
| | - Sieglinde Zelzer
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Markus Herrmann
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Robert Krause
- Department of Internal Medicine, Section of Infectious Diseases and Tropical Medicine, Medical University of Graz, Graz, Austria
| | - Andreas Meinitzer
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
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16
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Ultra-high-performance liquid chromatography high-resolution mass spectrometry variants for metabolomics research. Nat Methods 2021; 18:733-746. [PMID: 33972782 DOI: 10.1038/s41592-021-01116-4] [Citation(s) in RCA: 129] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2019] [Accepted: 03/12/2021] [Indexed: 02/03/2023]
Abstract
Ultra-high-performance liquid chromatography high-resolution mass spectrometry (UHPLC-HRMS) variants currently represent the best tools to tackle the challenges of complexity and lack of comprehensive coverage of the metabolome. UHPLC offers flexible and efficient separation coupled with high-sensitivity detection via HRMS, allowing for the detection and identification of a broad range of metabolites. Here we discuss current common strategies for UHPLC-HRMS-based metabolomics, with a focus on expanding metabolome coverage.
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17
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Hernández-Mesa M, Le Bizec B, Dervilly G. Metabolomics in chemical risk analysis – A review. Anal Chim Acta 2021; 1154:338298. [DOI: 10.1016/j.aca.2021.338298] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 02/01/2021] [Accepted: 02/02/2021] [Indexed: 12/14/2022]
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18
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Rampler E, Abiead YE, Schoeny H, Rusz M, Hildebrand F, Fitz V, Koellensperger G. Recurrent Topics in Mass Spectrometry-Based Metabolomics and Lipidomics-Standardization, Coverage, and Throughput. Anal Chem 2021; 93:519-545. [PMID: 33249827 PMCID: PMC7807424 DOI: 10.1021/acs.analchem.0c04698] [Citation(s) in RCA: 81] [Impact Index Per Article: 27.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Evelyn Rampler
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
- Vienna Metabolomics Center (VIME), University of Vienna, Althanstraße 14, 1090 Vienna, Austria
- University of Vienna, Althanstraße 14, 1090 Vienna, Austria
| | - Yasin El Abiead
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
| | - Harald Schoeny
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
| | - Mate Rusz
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
- Institute of Inorganic
Chemistry, University of Vienna, Währinger Straße 42, 1090 Vienna, Austria
| | - Felina Hildebrand
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
| | - Veronika Fitz
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
| | - Gunda Koellensperger
- Department of Analytical
Chemistry, Faculty of Chemistry, University of Vienna, Währinger Str. 38, 1090 Vienna, Austria
- Vienna Metabolomics Center (VIME), University of Vienna, Althanstraße 14, 1090 Vienna, Austria
- University of Vienna, Althanstraße 14, 1090 Vienna, Austria
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19
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Use of Untargeted Metabolomics to Explore the Air Pollution-Related Disease Continuum. Curr Environ Health Rep 2021; 8:7-22. [PMID: 33420964 DOI: 10.1007/s40572-020-00298-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/18/2020] [Indexed: 01/24/2023]
Abstract
PURPOSE OF REVIEW The purpose of this review is to summarize the application of untargeted metabolomics to identify the perturbation of metabolites or metabolic pathways associated with air pollutant exposures. RECENT FINDINGS Twenty-three studies were included in this review, in adults, children, or pregnant women. The most commonly measured air pollutant is particulate matter smaller than 2.5 μm. Size-fractioned particles, particle chemical species, gas pollutants, or organic compounds were also investigated. The reviewed studies used a wide range of air pollution measurement techniques and metabolomics analyses. Identified metabolites were primarily related to oxidative stress and inflammatory responses, and a few were related to the alterations of steroid metabolic pathways. The observed metabolic perturbations can differ by disease status, sex, and age. Air pollution-related metabolic changes were also associated with health outcomes in some studies. Our review shows that air pollutant exposures are associated with metabolic pathways primarily related to oxidative stress, inflammation, as assessed through untargeted metabolomics in 23 studies. More metabolomic studies with larger sample sizes are needed to identify air pollution components most responsible for adverse health effects, elaborate on mechanisms for subpopulation susceptibility, and link air pollution exposure to specific adverse health effects.
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20
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21
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Martins MCM, Mafra V, Monte-Bello CC, Caldana C. The Contribution of Metabolomics to Systems Biology: Current Applications Bridging Genotype and Phenotype in Plant Science. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1346:91-105. [DOI: 10.1007/978-3-030-80352-0_5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
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22
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Biostimulants for Plant Growth and Mitigation of Abiotic Stresses: A Metabolomics Perspective. Metabolites 2020; 10:metabo10120505. [PMID: 33321781 PMCID: PMC7764227 DOI: 10.3390/metabo10120505] [Citation(s) in RCA: 63] [Impact Index Per Article: 15.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 11/27/2020] [Accepted: 12/03/2020] [Indexed: 12/15/2022] Open
Abstract
Adverse environmental conditions due to climate change, combined with declining soil fertility, threaten food security. Modern agriculture is facing a pressing situation where novel strategies must be developed for sustainable food production and security. Biostimulants, conceptually defined as non-nutrient substances or microorganisms with the ability to promote plant growth and health, represent the potential to provide sustainable and economically favorable solutions that could introduce novel approaches to improve agricultural practices and crop productivity. Current knowledge and phenotypic observations suggest that biostimulants potentially function in regulating and modifying physiological processes in plants to promote growth, alleviate stresses, and improve quality and yield. However, to successfully develop novel biostimulant-based formulations and programs, understanding biostimulant-plant interactions, at molecular, cellular and physiological levels, is a prerequisite. Metabolomics, a multidisciplinary omics science, offers unique opportunities to predictively decode the mode of action of biostimulants on crop plants, and identify signatory markers of biostimulant action. Thus, this review intends to highlight the current scientific efforts and knowledge gaps in biostimulant research and industry, in context of plant growth promotion and stress responses. The review firstly revisits models that have been elucidated to describe the molecular machinery employed by plants in coping with environmental stresses. Furthermore, current definitions, claims and applications of plant biostimulants are pointed out, also indicating the lack of biological basis to accurately postulate the mechanisms of action of plant biostimulants. The review articulates briefly key aspects in the metabolomics workflow and the (potential) applications of this multidisciplinary omics science in the biostimulant industry.
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23
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Nong F, Luo S, Liang Y, Zhao Z, Xing S, Wen B, Zhou L. Evaluation of the effect of Dahuang-Mudan decoction on TNBS-induced colitis using UPLC-QTOF/MS-based metabolomic analysis. Biomed Chromatogr 2020; 35:e5003. [PMID: 33063880 DOI: 10.1002/bmc.5003] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Revised: 08/28/2020] [Accepted: 10/06/2020] [Indexed: 12/19/2022]
Abstract
Dahuang-Mudan decoction (DMD) is a formula that has been widely used as a complementary treatment for inflammatory bowel disease (IBD). However, the mechanism of action of DMD in IBD has not been clearly elucidated. Therefore, we developed a metabolomics-based method to evaluate the effects and potential mechanisms of DMD in a 2,4,6-trinitobenzene sulfonic acid (TNBS)-induced colitis model. The ultra-high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC/QTOF-MS) method combined with multiple analysis approaches including principal component analysis, partial least square discriminant analysis and orthogonal partial least square discriminant analysis were used to investigate the different urinary metabolites. We identified 29 potential biomarkers of TNBS-induced colitis that returned to normal conditions after DMD administration. Pathway analysis indicated that changes in these metabolites were associated with cysteine and methionine metabolism, citric acid cycle, glycolysis and glycolic regeneration, pyruvate metabolism, biosynthesis of valine, leucine and isoleucine, biosynthesis of primary bile acids, glycine, serine and threonine metabolism, caffeine metabolism, arginine and proline metabolism and phenylalanine metabolism. It is worth noting that DMD has potential therapeutic effects on TNBS-induced colitis, which functions by restoring the balance of multiple disturbed pathways to a normal condition. This study suggests the reliability of metabolomics-based approaches to identifying biomarkers and pathways, which facilitate further investigation of the potential mechanisms of DMD.
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Affiliation(s)
- Feifei Nong
- Pi-Wei Institute, Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shuang Luo
- School of Pharmaceutical Science, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yuqi Liang
- Pi-Wei Institute, Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Zhongxiang Zhao
- School of Pharmaceutical Science, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Shangping Xing
- School of Pharmaceutical Science, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Bin Wen
- Pi-Wei Institute, Science and Technology Innovation Center, Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Lian Zhou
- School of Pharmaceutical Science, Guangzhou University of Chinese Medicine, Guangzhou, China
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24
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Abstract
Metabolomics is the comprehensive study of small-molecule metabolites. Obtaining a wide coverage of the metabolome is challenging because of the broad range of physicochemical properties of the small molecules. To study the compounds of interest spectroscopic (NMR), spectrometric (MS) and separation techniques (LC, GC, supercritical fluid chromatography, CE) are used. The choice for a given technique is influenced by the sample matrix, the concentration and properties of the metabolites, and the amount of sample. This review discusses the most commonly used analytical techniques for metabolomic studies, including their advantages, drawbacks and some applications.
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25
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Twenty years of supramolecular solvents in sample preparation for chromatography: achievements and challenges ahead. Anal Bioanal Chem 2020; 412:6037-6058. [PMID: 32206847 DOI: 10.1007/s00216-020-02559-y] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2020] [Revised: 02/20/2020] [Accepted: 02/28/2020] [Indexed: 02/06/2023]
Abstract
Supramolecular solvents (SUPRAS) have progressively become a suitable alternative to organic solvents for sample preparation in chromatographic analysis. The inherent properties of these nanostructured solvents (e.g. different polarity microenvironments, multiple binding sites, possibility of tailoring their properties, etc.) offer multiple opportunities for the development of innovative sample treatment platforms not approachable by conventional solvents. In this review, major achievements attained in the combination SUPRAS-chromatography in the last 20 years as well as the challenges that should be addressed in the near future are critically discussed. Among achievements, particular attention is paid to the theoretical and practical knowledge gained that has helped make substantial progress in the area. In this respect, advances in the understanding of the mechanisms involved in SUPRAS formation and SUPRAS-solute interactions driving extractions are discussed, with a view to the setting up of knowledge-based extraction procedures. Likewise, the strategies followed to improve the compatibility of SUPRAS extracts with liquid and gas chromatography and adapt SUPRAS-based extractions to different formats are presented. Ongoing efforts to apply SUPRAS in multicomponent extractions and synthesize tailored SUPRAS for the development of innovative sample treatments are highlighted. Among challenges identified, discussion is focused on the automation of SUPRAS-based sample treatment and the elucidation of SUPRAS nanostructures, which are considered essential for their acceptance in routine labs and the design of tailored SUPRAS with programmed functions. Graphical abstract.
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26
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Liu K, Fang J, Jin J, Zhu S, Xu X, Xu Y, Ye B, Lin SH, Xu X. Serum Metabolomics Reveals Personalized Metabolic Patterns for Macular Neovascular Disease Patient Stratification. J Proteome Res 2020; 19:699-707. [PMID: 31755721 DOI: 10.1021/acs.jproteome.9b00574] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
The macular neovascular disease is a group disorder with complex pathogenesis of neovascularization for vision impairment and irreversible blindness, posing great challenges to precise diagnosis and management. We prospectively recruited participants with age-related macular degeneration (AMD), polypoidal choroidal vasculopathy (PCV), and pathological myopia (PM) and compared with cataract patients without fundus diseases as a control group. The serum metabolome was profiled by gas chromatography coupled with time-of-flight mass spectrometry (GC-TOFMS) analysis. Multivariate statistical methods as well as data mining were performed for interpretation of macular neovascularization. A total of 446 participants with macular neovascularization and 138 cataract subjects as the control group were enrolled in this study. By employing GC-TOFMS, 131 metabolites were identified and 33 differentiating metabolites were highlighted in patients with macular neovascularization. For differential diagnosis, three panels of specific metabolomics-based biomarkers provided areas under the curve of 0.967, 0.938, and 0.877 in the discovery phase (n = 328) and predictive values of 87.3%, 79%, and 85.7% in the test phase (n = 256). Personalized pathway dysregulation scores measurement using Lilikoi package in R language revealed the pentose phosphate pathway and mitochondrial electron transport chain as the most important pathways in AMD; purine metabolism and glycolysis were identified as the major disturbed pathways in PCV, while the altered thiamine metabolism and purine metabolism may contribute to PM phenotypes. Serum metabolomics are powerful for characterizing metabolic disturbances of the macular neovascular disease. Differences in metabolic pathways may reflect an underlying macular neovascular disease and serve as therapeutic targets for macular neovascular treatment.
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Affiliation(s)
- Kun Liu
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai General Hospital , Shanghai Engineering Center for Visual Science and Photomedicine , Shanghai 200040 , China
| | - Junwei Fang
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai General Hospital , Shanghai Engineering Center for Visual Science and Photomedicine , Shanghai 200040 , China.,College of Basic Medical Sciences , Shanghai Jiao Tong University School of Medicine , Shanghai 200025 , China
| | - Jing Jin
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai General Hospital , Shanghai Engineering Center for Visual Science and Photomedicine , Shanghai 200040 , China
| | - Shaopin Zhu
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai General Hospital , Shanghai Engineering Center for Visual Science and Photomedicine , Shanghai 200040 , China
| | - Xiaoyin Xu
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai General Hospital , Shanghai Engineering Center for Visual Science and Photomedicine , Shanghai 200040 , China
| | - Yupeng Xu
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai General Hospital , Shanghai Engineering Center for Visual Science and Photomedicine , Shanghai 200040 , China
| | - Bin Ye
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai General Hospital , Shanghai Engineering Center for Visual Science and Photomedicine , Shanghai 200040 , China
| | - Shu-Hai Lin
- College of Basic Medical Sciences , Shanghai Jiao Tong University School of Medicine , Shanghai 200025 , China.,State Key Laboratory of Cellular Stress Biology, School of Life Sciences , Xiamen University , Xiamen , Fujian 361005 , China
| | - Xun Xu
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine; Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai General Hospital , Shanghai Engineering Center for Visual Science and Photomedicine , Shanghai 200040 , China
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27
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Pezzatti J, Boccard J, Codesido S, Gagnebin Y, Joshi A, Picard D, González-Ruiz V, Rudaz S. Implementation of liquid chromatography-high resolution mass spectrometry methods for untargeted metabolomic analyses of biological samples: A tutorial. Anal Chim Acta 2020; 1105:28-44. [PMID: 32138924 DOI: 10.1016/j.aca.2019.12.062] [Citation(s) in RCA: 72] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Revised: 11/18/2019] [Accepted: 12/20/2019] [Indexed: 12/23/2022]
Abstract
Untargeted metabolomics is now widely recognized as a useful tool for exploring metabolic changes taking place in biological systems under different conditions. By its nature, this is a highly interdisciplinary field of research, and mastering all of the steps comprised in the pipeline can be a challenging task, especially for those researchers new to the topic. In this tutorial, we aim to provide an overview of the most widely adopted methods of performing LC-HRMS-based untargeted metabolomics of biological samples. A detailed protocol is provided in the Supplementary Information for rapidly implementing a basic screening workflow in a laboratory setting. This tutorial covers experimental design, sample preparation and analysis, signal processing and data treatment, and, finally, data analysis and its biological interpretation. Each section is accompanied by up-to-date literature to guide readers through the preparation and optimization of such a workflow, as well as practical information for avoiding or fixing some of the most frequently encountered pitfalls.
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Affiliation(s)
- Julian Pezzatti
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel-Servet 1, 1211, Geneva, Switzerland
| | - Julien Boccard
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel-Servet 1, 1211, Geneva, Switzerland; Swiss Centre for Applied Human Toxicology (SCAHT), Switzerland
| | - Santiago Codesido
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel-Servet 1, 1211, Geneva, Switzerland
| | - Yoric Gagnebin
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel-Servet 1, 1211, Geneva, Switzerland
| | - Abhinav Joshi
- Department of Cell Biology, Faculty of Science, University of Geneva, 1211, Geneva, Switzerland
| | - Didier Picard
- Department of Cell Biology, Faculty of Science, University of Geneva, 1211, Geneva, Switzerland
| | - Víctor González-Ruiz
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel-Servet 1, 1211, Geneva, Switzerland; Swiss Centre for Applied Human Toxicology (SCAHT), Switzerland
| | - Serge Rudaz
- Institute of Pharmaceutical Sciences of Western Switzerland, University of Geneva, Rue Michel-Servet 1, 1211, Geneva, Switzerland; Swiss Centre for Applied Human Toxicology (SCAHT), Switzerland.
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28
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Wang G, Haringa C, Tang W, Noorman H, Chu J, Zhuang Y, Zhang S. Coupled metabolic-hydrodynamic modeling enabling rational scale-up of industrial bioprocesses. Biotechnol Bioeng 2019; 117:844-867. [PMID: 31814101 DOI: 10.1002/bit.27243] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2019] [Revised: 11/28/2019] [Accepted: 11/30/2019] [Indexed: 12/13/2022]
Abstract
Metabolomics aims to address what and how regulatory mechanisms are coordinated to achieve flux optimality, different metabolic objectives as well as appropriate adaptations to dynamic nutrient availability. Recent decades have witnessed that the integration of metabolomics and fluxomics within the goal of synthetic biology has arrived at generating the desired bioproducts with improved bioconversion efficiency. Absolute metabolite quantification by isotope dilution mass spectrometry represents a functional readout of cellular biochemistry and contributes to the establishment of metabolic (structured) models required in systems metabolic engineering. In industrial practices, population heterogeneity arising from fluctuating nutrient availability frequently leads to performance losses, that is reduced commercial metrics (titer, rate, and yield). Hence, the development of more stable producers and more predictable bioprocesses can benefit from a quantitative understanding of spatial and temporal cell-to-cell heterogeneity within industrial bioprocesses. Quantitative metabolomics analysis and metabolic modeling applied in computational fluid dynamics (CFD)-assisted scale-down simulators that mimic industrial heterogeneity such as fluctuations in nutrients, dissolved gases, and other stresses can procure informative clues for coping with issues during bioprocessing scale-up. In previous studies, only limited insights into the hydrodynamic conditions inside the industrial-scale bioreactor have been obtained, which makes case-by-case scale-up far from straightforward. Tracking the flow paths of cells circulating in large-scale bioreactors is a highly valuable tool for evaluating cellular performance in production tanks. The "lifelines" or "trajectories" of cells in industrial-scale bioreactors can be captured using Euler-Lagrange CFD simulation. This novel methodology can be further coupled with metabolic (structured) models to provide not only a statistical analysis of cell lifelines triggered by the environmental fluctuations but also a global assessment of the metabolic response to heterogeneity inside an industrial bioreactor. For the future, the industrial design should be dependent on the computational framework, and this integration work will allow bioprocess scale-up to the industrial scale with an end in mind.
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Affiliation(s)
- Guan Wang
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, People's Republic of China
| | - Cees Haringa
- Transport Phenomena, Chemical Engineering Department, Delft University of Technology, Delft, The Netherlands.,DSM Biotechnology Center, Delft, The Netherlands
| | - Wenjun Tang
- DSM Biotechnology Center, Delft, The Netherlands
| | - Henk Noorman
- DSM Biotechnology Center, Delft, The Netherlands.,Bioprocess Engineering, Department of Biotechnology, Delft University of Technology, Delft, The Netherlands
| | - Ju Chu
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, People's Republic of China
| | - Yingping Zhuang
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, People's Republic of China
| | - Siliang Zhang
- State Key Laboratory of Bioreactor Engineering, East China University of Science and Technology, Shanghai, People's Republic of China
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29
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Lv W, Shi X, Wang S, Xu G. Multidimensional liquid chromatography-mass spectrometry for metabolomic and lipidomic analyses. Trends Analyt Chem 2019. [DOI: 10.1016/j.trac.2018.11.001] [Citation(s) in RCA: 30] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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30
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Manzi M, Riquelme G, Zabalegui N, Monge ME. Improving diagnosis of genitourinary cancers: Biomarker discovery strategies through mass spectrometry-based metabolomics. J Pharm Biomed Anal 2019; 178:112905. [PMID: 31707200 DOI: 10.1016/j.jpba.2019.112905] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2019] [Revised: 09/27/2019] [Accepted: 10/01/2019] [Indexed: 12/24/2022]
Abstract
The genitourinary oncology field needs integration of results from basic science, epidemiological studies, clinical and translational research to improve the current methods for diagnosis. MS-based metabolomics can be transformative for disease diagnosis and contribute to global health parity. Metabolite panels are promising to translate metabolomic findings into the clinics, changing the current diagnosis paradigm based on single biomarker analysis. This review article describes capabilities of the MS-based oncometabolomics field for improving kidney, prostate, and bladder cancer detection, early diagnosis, risk stratification, and outcome. Published works are critically discussed based on the study design; type and number of samples analyzed; data quality assessment through quality assurance and quality control practices; data analysis workflows; confidence levels reported for identified metabolites; validation attempts; the overlap of discriminant metabolites for the different genitourinary cancers; and the translation capability of findings into clinical settings. Ongoing challenges are discussed, and future directions are delineated.
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Affiliation(s)
- Malena Manzi
- Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2390, C1425FQD, Ciudad de Buenos Aires, Argentina; Departamento de Química Biológica, Facultad de Farmacia y Bioquímica, Universidad de Buenos Aires, Junín 956, C1113AAD, Ciudad de Buenos Aires, Argentina
| | - Gabriel Riquelme
- Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2390, C1425FQD, Ciudad de Buenos Aires, Argentina; Departamento de Química Inorgánica, Analítica y Química Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, C1428EGA, Buenos Aires, Argentina
| | - Nicolás Zabalegui
- Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2390, C1425FQD, Ciudad de Buenos Aires, Argentina; Departamento de Química Inorgánica, Analítica y Química Física, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Ciudad Universitaria, C1428EGA, Buenos Aires, Argentina
| | - María Eugenia Monge
- Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Godoy Cruz 2390, C1425FQD, Ciudad de Buenos Aires, Argentina.
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31
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Borgsmüller N, Gloaguen Y, Opialla T, Blanc E, Sicard E, Royer AL, Le Bizec B, Durand S, Migné C, Pétéra M, Pujos-Guillot E, Giacomoni F, Guitton Y, Beule D, Kirwan J. WiPP: Workflow for Improved Peak Picking for Gas Chromatography-Mass Spectrometry (GC-MS) Data. Metabolites 2019; 9:metabo9090171. [PMID: 31438611 PMCID: PMC6780109 DOI: 10.3390/metabo9090171] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2019] [Revised: 08/18/2019] [Accepted: 08/20/2019] [Indexed: 02/02/2023] Open
Abstract
Lack of reliable peak detection impedes automated analysis of large-scale gas chromatography-mass spectrometry (GC-MS) metabolomics datasets. Performance and outcome of individual peak-picking algorithms can differ widely depending on both algorithmic approach and parameters, as well as data acquisition method. Therefore, comparing and contrasting between algorithms is difficult. Here we present a workflow for improved peak picking (WiPP), a parameter optimising, multi-algorithm peak detection for GC-MS metabolomics. WiPP evaluates the quality of detected peaks using a machine learning-based classification scheme based on seven peak classes. The quality information returned by the classifier for each individual peak is merged with results from different peak detection algorithms to create one final high-quality peak set for immediate down-stream analysis. Medium- and low-quality peaks are kept for further inspection. By applying WiPP to standard compound mixes and a complex biological dataset, we demonstrate that peak detection is improved through the novel way to assign peak quality, an automated parameter optimisation, and results in integration across different embedded peak picking algorithms. Furthermore, our approach can provide an impartial performance comparison of different peak picking algorithms. WiPP is freely available on GitHub (https://github.com/bihealth/WiPP) under MIT licence.
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Affiliation(s)
- Nico Borgsmüller
- Core Unit Bioinformatics, Berlin Institute of Health, 10178 Berlin, Germany
- Berlin Institute of Health Metabolomics Platform, 10178 Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
| | - Yoann Gloaguen
- Core Unit Bioinformatics, Berlin Institute of Health, 10178 Berlin, Germany
- Berlin Institute of Health Metabolomics Platform, 10178 Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
| | - Tobias Opialla
- Berlin Institute of Health Metabolomics Platform, 10178 Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
- Integrative Proteomics and Metabolomics, Berlin Institute for Medical Systems Biology, Max Delbrück Center for Molecular Medicine, 13125 Berlin, Germany
| | - Eric Blanc
- Core Unit Bioinformatics, Berlin Institute of Health, 10178 Berlin, Germany
- Charité - Universitätsmedizin Berlin, 10178 Berlin, Germany
| | - Emilie Sicard
- Université Clermont Auvergne, INRA, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, 63000 Clermont - Ferrand, France
| | - Anne-Lise Royer
- LABERCA, Oniris, INRA, Université Bretagne - Loire, 44307 Nantes, France
| | - Bruno Le Bizec
- LABERCA, Oniris, INRA, Université Bretagne - Loire, 44307 Nantes, France
| | - Stéphanie Durand
- Université Clermont Auvergne, INRA, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, 63000 Clermont - Ferrand, France
| | - Carole Migné
- Université Clermont Auvergne, INRA, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, 63000 Clermont - Ferrand, France
| | - Mélanie Pétéra
- Université Clermont Auvergne, INRA, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, 63000 Clermont - Ferrand, France
| | - Estelle Pujos-Guillot
- Université Clermont Auvergne, INRA, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, 63000 Clermont - Ferrand, France
| | - Franck Giacomoni
- Université Clermont Auvergne, INRA, UNH, Plateforme d'Exploration du Métabolisme, MetaboHUB Clermont, 63000 Clermont - Ferrand, France
| | - Yann Guitton
- LABERCA, Oniris, INRA, Université Bretagne - Loire, 44307 Nantes, France
| | - Dieter Beule
- Core Unit Bioinformatics, Berlin Institute of Health, 10178 Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany
- Charité - Universitätsmedizin Berlin, 10178 Berlin, Germany
| | - Jennifer Kirwan
- Berlin Institute of Health Metabolomics Platform, 10178 Berlin, Germany.
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, 13125 Berlin, Germany.
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Barbosa-Cornelio R, Cantor F, Coy-Barrera E, Rodríguez D. Tools in the Investigation of Volatile Semiochemicals on Insects: From Sampling to Statistical Analysis. INSECTS 2019; 10:insects10080241. [PMID: 31390759 PMCID: PMC6723273 DOI: 10.3390/insects10080241] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 07/28/2019] [Accepted: 08/02/2019] [Indexed: 12/16/2022]
Abstract
The recognition of volatile organic compounds (VOCs) involved in insect interactions with plants or other organisms is essential for constructing a holistic comprehension of their role in ecology, from which the implementation of new strategies for pest and disease vector control as well as the systematic exploitation of pollinators and natural enemies can be developed. In the present paper, some of the general methods employed in this field are examined, focusing on their available technologies. An important part of the investigations conducted in this context begin with VOC collection directly from host organisms, using classical extraction methods, by the employment of adsorption materials used in solid-phase micro extraction (SPME) and direct-contact sorptive extraction (DCSE) and, subsequently, analysis through instrumental analysis techniques such as gas chromatography (GC), nuclear magnetic resonance (NMR) and mass spectrometry (MS), which provide crucial information for determining the chemical identity of volatile metabolites. Behavioral experiments, electroantennography (EAG), and biosensors are then carried out to define the semiochemicals with the best potential for performing relevant functions in ecological relationships. Chemical synthesis of biologically-active VOCs is alternatively performed to scale up the amount to be used in different purposes such as laboratory or field evaluations. Finally, the application of statistical analysis provides tools for drawing conclusions about the type of correlations existing between the diverse experimental variables and data matrices, thus generating models that simplify the interpretation of the biological roles of VOCs.
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Affiliation(s)
- Ricardo Barbosa-Cornelio
- Biological Control Laboratory, Facultad de Ciencias Básicas y Aplicadas, Universidad Militar Nueva Granada, Cajicá 250247, Colombia
- Bioorganic Chemistry Laboratory, Facultad de Ciencias Básicas y Aplicadas, Universidad Militar Nueva Granada, Cajicá 250247, Colombia
| | - Fernando Cantor
- Biological Control Laboratory, Facultad de Ciencias Básicas y Aplicadas, Universidad Militar Nueva Granada, Cajicá 250247, Colombia
| | - Ericsson Coy-Barrera
- Bioorganic Chemistry Laboratory, Facultad de Ciencias Básicas y Aplicadas, Universidad Militar Nueva Granada, Cajicá 250247, Colombia.
| | - Daniel Rodríguez
- Biological Control Laboratory, Facultad de Ciencias Básicas y Aplicadas, Universidad Militar Nueva Granada, Cajicá 250247, Colombia.
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Monge ME, Dodds JN, Baker ES, Edison AS, Fernández FM. Challenges in Identifying the Dark Molecules of Life. ANNUAL REVIEW OF ANALYTICAL CHEMISTRY (PALO ALTO, CALIF.) 2019; 12:177-199. [PMID: 30883183 PMCID: PMC6716371 DOI: 10.1146/annurev-anchem-061318-114959] [Citation(s) in RCA: 47] [Impact Index Per Article: 9.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Metabolomics is the study of the metabolome, the collection of small molecules in living organisms, cells, tissues, and biofluids. Technological advances in mass spectrometry, liquid- and gas-phase separations, nuclear magnetic resonance spectroscopy, and big data analytics have now made it possible to study metabolism at an omics or systems level. The significance of this burgeoning scientific field cannot be overstated: It impacts disciplines ranging from biomedicine to plant science. Despite these advances, the central bottleneck in metabolomics remains the identification of key metabolites that play a class-discriminant role. Because metabolites do not follow a molecular alphabet as proteins and nucleic acids do, their identification is much more time consuming, with a high failure rate. In this review, we critically discuss the state-of-the-art in metabolite identification with specific applications in metabolomics and how technologies such as mass spectrometry, ion mobility, chromatography, and nuclear magnetic resonance currently contribute to this challenging task.
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Affiliation(s)
- María Eugenia Monge
- Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), C1425FQD, Ciudad de Buenos Aires, Argentina
| | - James N Dodds
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Erin S Baker
- Department of Chemistry, North Carolina State University, Raleigh, North Carolina 27695, USA
| | - Arthur S Edison
- Department of Genetics, Department of Biochemistry and Molecular Biology, and Complex Carbohydrate Research Center, University of Georgia, Athens, Georgia 30602, USA
| | - Facundo M Fernández
- School of Chemistry and Biochemistry, Georgia Institute of Technology and Petit Institute for Biochemistry and Bioscience, Atlanta, Georgia 30332, USA;
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A new optimization strategy for MALDI FTICR MS tissue analysis for untargeted metabolomics using experimental design and data modeling. Anal Bioanal Chem 2019; 411:3891-3903. [PMID: 31093699 DOI: 10.1007/s00216-019-01863-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2019] [Revised: 03/27/2019] [Accepted: 04/23/2019] [Indexed: 12/13/2022]
Abstract
Ultra-high-resolution imaging mass spectrometry using matrix-assisted laser desorption ionization (MALDI) MS coupled to a Fourier transform ion cyclotron resonance (FTICR) mass analyzer is a powerful technique for the visualization of small molecule distribution within biological tissues. The FTICR MS provides ultra-high resolving power and mass accuracy that allows large molecular coverage and molecular formula assignments, both essential for untargeted metabolomics analysis. These performances require fine optimizations of the MALDI FTICR parameters. In this context, this study proposes a new strategy, using experimental design, for the optimization of ion transmission voltages and MALDI parameters, for tissue untargeted metabolomics analysis, in both positive and negative ionization modes. These experiments were conducted by assessing the effects of nine factors for ion transmission voltages and four factors for MALDI on the number of peaks, the weighted resolution, and the mean error within m/z 150-1000 mass range. For this purpose, fractional factorial designs were used with multiple linear regression (MLR) to evaluate factor effects and to optimize parameter values. The optimized values of ion transmission voltages (RF amplitude TOF, RF amplitude octopole, frequency transfer optic, RF frequency octopole, deflector plate, funnel 1, skimmer, funnel RF amplitude, time-of-flight, capillary exit), MALDI parameters (laser fluence, number of laser shots), and detection parameters (data size, number of scans) led to an increase of 32% and 18% of the number of peaks, an increase of 8% and 39% of the resolution, and a decrease of 56% and 34% of the mean error in positive and negative ionization modes, respectively. Graphical abstract.
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Feussner K, Feussner I. Comprehensive LC-MS-Based Metabolite Fingerprinting Approach for Plant and Fungal-Derived Samples. Methods Mol Biol 2019; 1978:167-185. [PMID: 31119663 DOI: 10.1007/978-1-4939-9236-2_11] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Liquid chromatography-mass spectrometry (LC-MS)-based nontargeted metabolome approaches aim to detect chemotypes as markers for stress, disease, developmental, or genetic perturbation. Herein, we present a metabolite fingerprinting workflow, which is applicable for the analysis of tissues and fluids derived from plants and fungi. This is based on a broad metabolite coverage by a two-phase extraction and the separate analysis of polar, and nonpolar compounds by positive as well as negative electrospray ionization. For analysis of the resulting comprehensive data sets, the interactive and user-friendly data mining software MarVis-Suite is used. It supports statistical analysis, adduct correction, data merging, as well as visualization of multivariate data. Finally, MarVis shapes marker identification to the organism of interest. Therefore, it provides access to the species-specific databases KEGG and BioCyc and to custom databases tailored by the user.
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Affiliation(s)
- Kirstin Feussner
- Department of Plant Biochemistry, Albrecht-von-Haller-Institute for Plant Sciences, University of Goettingen, Goettingen, Germany.,Service Unit for Metabolomics and Lipidomics, Goettingen Center for Molecular Biosciences (GZMB), University of Goettingen, Goettingen, Germany
| | - Ivo Feussner
- Department of Plant Biochemistry, Albrecht-von-Haller-Institute for Plant Sciences, University of Goettingen, Goettingen, Germany. .,Service Unit for Metabolomics and Lipidomics, Goettingen Center for Molecular Biosciences (GZMB), University of Goettingen, Goettingen, Germany. .,Department of Plant Biochemistry, Goettingen Center for Molecular Biosciences (GZMB), University of Goettingen, Goettingen, Germany.
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Cao D, Xu C, Xue Y, Ruan Q, Yang B, Liu Z, Cui H, Zhang L, Zhao Z, Jin J. The therapeutic effect of Ilex pubescens extract on blood stasis model rats according to serum metabolomics. JOURNAL OF ETHNOPHARMACOLOGY 2018; 227:18-28. [PMID: 30142425 DOI: 10.1016/j.jep.2018.08.026] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/17/2018] [Revised: 08/15/2018] [Accepted: 08/19/2018] [Indexed: 06/08/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Ilex pubescens Hook. et Arn (MDQ), a traditional Chinese herb, is used in the treatment of cardiovascular diseases. However, the mechanisms underlying the preventive effect of MDQ on blood stasis remain unclear. AIM OF THE STUDY In this study, serum metabolomics integrated with a biochemical assay strategy were established to evaluate the preventive effect and mechanism of action of MDQ on rats with acute blood stasis. MATERIALS AND METHODS Forty-nine rats were divided into seven groups: the control group, model group, aspirin treatment group (30 mg/kg), clopidogrel treatment group (8 mg/kg) and three MDQ treatment groups (250, 500 and 1000 mg/kg). A hybrid quadrupole time of flight mass spectrometry (QTOF/MS) coupled to ultra-high-performance liquid chromatography (UPLC) was applied for profiling the serum metabolites. The multivariate data analysis techniques using unsupervised principal component analysis (PCA) and supervised orthogonal projections to latent structures discriminant analysis (OPLS-DA) were used for pattern recognition and distinguishing variabilities among groups. RESULTS MDQ protected the rats against blood stasis, as evidenced by the restoration of the anti-platelet aggregation activity, fibrinogen concentration, prothrombin time, thrombin time, activated partial thromboplastin time, endothelial nitric oxide synthase, endothelin, thromboxane B2 and 6-keto-prostaglandin F1α. The combination of PCA and OPLS-DA revealed deviations in eighteen differential biomarkers in serum. The identified biomarkers were primarily engaged in the metabolic pathways including arachidonic acid metabolism, glycerophospholipid metabolism, phospholipid biosynthesis and bile acid biosynthesis. The levels of eleven biomarkers showed significant alterations and a tendency to be restored to normal values in MDQ-treated blood stasis rats. Moreover, a correlation network diagram was constructed to show the serum biomarkers perturbed by MDQ. CONCLUSIONS These results suggested that MDQ had preventive effects on blood stasis in rats via arachidonic acid metabolism and glycerophospholipid metabolism.
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Affiliation(s)
- Di Cao
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Chuncao Xu
- School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou 510006, China
| | - Yuanyuan Xue
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Qingfeng Ruan
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Bao Yang
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Zhongqiu Liu
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Hui Cui
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Lei Zhang
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China
| | - Zhongxiang Zhao
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou 510006, China.
| | - Jing Jin
- School of Pharmaceutical Sciences, Sun Yat-Sen University, Guangzhou 510006, China.
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Cui L, Lu H, Lee YH. Challenges and emergent solutions for LC-MS/MS based untargeted metabolomics in diseases. MASS SPECTROMETRY REVIEWS 2018; 37:772-792. [PMID: 29486047 DOI: 10.1002/mas.21562] [Citation(s) in RCA: 192] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/22/2017] [Accepted: 02/02/2018] [Indexed: 05/03/2023]
Abstract
In the past decade, advances in liquid chromatography-mass spectrometry (LC-MS) have revolutionized untargeted metabolomics analyses. By mining metabolomes more deeply, researchers are now primed to uncover key metabolites and their associations with diseases. The employment of untargeted metabolomics has led to new biomarker discoveries and a better mechanistic understanding of diseases with applications in precision medicine. However, many major pertinent challenges remain. First, compound identification has been poor, and left an overwhelming number of unidentified peaks. Second, partial, incomplete metabolomes persist due to factors such as limitations in mass spectrometry data acquisition speeds, wide-range of metabolites concentrations, and cellular/tissue/temporal-specific expression changes that confound our understanding of metabolite perturbations. Third, to contextualize metabolites in pathways and biology is difficult because many metabolites partake in multiple pathways, have yet to be described species specificity, or possess unannotated or more-complex functions that are not easily characterized through metabolomics analyses. From a translational perspective, information related to novel metabolite biomarkers, metabolic pathways, and drug targets might be sparser than they should be. Thankfully, significant progress has been made and novel solutions are emerging, achieved through sustained academic and industrial community efforts in terms of hardware, computational, and experimental approaches. Given the rapidly growing utility of metabolomics, this review will offer new perspectives, increase awareness of the major challenges in LC-MS metabolomics that will significantly benefit the metabolomics community and also the broader the biomedical community metabolomics aspire to serve.
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Affiliation(s)
- Liang Cui
- Translational 'Omics and Biomarkers Group, KK Research Centre, KK Women's and Children's Hospital, Singapore, Singapore
- Infectious Diseases-Interdisciplinary Research Group, Singapore-MIT Alliance for Research and Technology, Singapore, Singapore
| | - Haitao Lu
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Yie Hou Lee
- Translational 'Omics and Biomarkers Group, KK Research Centre, KK Women's and Children's Hospital, Singapore, Singapore
- OBGYN-Academic Clinical Program, Duke-NUS Medical School, Singapore, Singapore
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Metabolomics in chronic kidney disease: Strategies for extended metabolome coverage. J Pharm Biomed Anal 2018; 161:313-325. [PMID: 30195171 DOI: 10.1016/j.jpba.2018.08.046] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2018] [Revised: 08/22/2018] [Accepted: 08/23/2018] [Indexed: 12/16/2022]
Abstract
Chronic kidney disease (CKD) is becoming a major public health issue as prevalence is increasing worldwide. It also represents a major challenge for the identification of new early biomarkers, understanding of biochemical mechanisms, patient monitoring and prognosis. Each metabolite contained in a biofluid or tissue may play a role as a signal or as a driver in the development or progression of the pathology. Therefore, metabolomics is a highly valuable approach in this clinical context. It aims to provide a representative picture of a biological system, making exhaustive metabolite coverage crucial. Two aspects can be considered: analytical and biological coverage. From an analytical point of view, monitoring all metabolites within one run is currently impossible. Multiple analytical techniques providing orthogonal information should be carried out in parallel for coverage improvement. The biological aspect of metabolome coverage can be enhanced by using multiple biofluids or tissues for in-depth biological investigation, as the analysis of a single sample type is generally insufficient for whole organism extrapolation. Hence, recording of signals from multiple sample types and different analytical platforms generates massive and complex datasets so that chemometric tools, including data fusion approaches and multi-block analysis, are key tools for extracting biological information and for discovery of relevant biomarkers. This review presents the recent developments in the field of metabolomic analysis, from sampling and analytical strategies to chemometric tools, dedicated to the generation and handling of multiple complementary metabolomic datasets enabling extended metabolite coverage to improve our biological knowledge of CKD.
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Shulaev V, Isaac G. Supercritical fluid chromatography coupled to mass spectrometry – A metabolomics perspective. J Chromatogr B Analyt Technol Biomed Life Sci 2018; 1092:499-505. [DOI: 10.1016/j.jchromb.2018.06.021] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2018] [Revised: 06/10/2018] [Accepted: 06/11/2018] [Indexed: 10/14/2022]
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Halbfeld C, Baumbach JI, Blank LM, Ebert BE. Multi-capillary Column Ion Mobility Spectrometry of Volatile Metabolites for Phenotyping of Microorganisms. Methods Mol Biol 2018; 1671:229-258. [PMID: 29170963 DOI: 10.1007/978-1-4939-7295-1_15] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/26/2023]
Abstract
Rational strain engineering requires solid testing of phenotypes including productivity and ideally contributes thereby directly to our understanding of the genotype-phenotype relationship. Actually, the test step of the strain engineering cycle becomes the limiting step, as ever advancing tools for generating genetic diversity exist. Here, we briefly define the challenge one faces in quantifying phenotypes and summarize existing analytical techniques that partially overcome this challenge. We argue that the evolution of volatile metabolites can be used as proxy for cellular metabolism. In the simplest case, the product of interest is a volatile (e.g., from bulk alcohols to special fragrances) that is directly quantified over time. But also nonvolatile products (e.g., from bulk long-chain fatty acids to natural products) require major flux rerouting that result potentially in altered volatile production. While alternative techniques for volatile determination exist, rather few can be envisaged for medium to high-throughput analysis required for phenotype testing. Here, we contribute a detailed protocol for an ion mobility spectrometry (IMS) analysis that allows volatile metabolite quantification down to the ppb range. The sensitivity can be exploited for small-scale fermentation monitoring. The insights shared might contribute to a more frequent use of IMS in biotechnology, while the experimental aspects are of general use for researchers interested in volatile monitoring.
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Affiliation(s)
- Christoph Halbfeld
- iAMB-Institute of Applied Microbiology, ABBt-Aachen Biology and Biotechnology, RWTH Aachen University, Worringer Weg 1, 52074, Aachen, Germany
| | - Jörg Ingo Baumbach
- Faculty of Applied Chemistry, Reutlingen University, 72762, Reutlingen, Germany
| | - Lars M Blank
- iAMB-Institute of Applied Microbiology, ABBt-Aachen Biology and Biotechnology, RWTH Aachen University, Worringer Weg 1, 52074, Aachen, Germany.
| | - Birgitta E Ebert
- iAMB-Institute of Applied Microbiology, ABBt-Aachen Biology and Biotechnology, RWTH Aachen University, Worringer Weg 1, 52074, Aachen, Germany
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Tebani A, Afonso C, Bekri S. Advances in metabolome information retrieval: turning chemistry into biology. Part I: analytical chemistry of the metabolome. J Inherit Metab Dis 2018; 41:379-391. [PMID: 28840392 PMCID: PMC5959978 DOI: 10.1007/s10545-017-0074-y] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2017] [Revised: 06/28/2017] [Accepted: 07/14/2017] [Indexed: 12/20/2022]
Abstract
Metabolites are small molecules produced by enzymatic reactions in a given organism. Metabolomics or metabolic phenotyping is a well-established omics aimed at comprehensively assessing metabolites in biological systems. These comprehensive analyses use analytical platforms, mainly nuclear magnetic resonance spectroscopy and mass spectrometry, along with associated separation methods to gather qualitative and quantitative data. Metabolomics holistically evaluates biological systems in an unbiased, data-driven approach that may ultimately support generation of hypotheses. The approach inherently allows the molecular characterization of a biological sample with regard to both internal (genetics) and environmental (exosome, microbiome) influences. Metabolomics workflows are based on whether the investigator knows a priori what kind of metabolites to assess. Thus, a targeted metabolomics approach is defined as a quantitative analysis (absolute concentrations are determined) or a semiquantitative analysis (relative intensities are determined) of a set of metabolites that are possibly linked to common chemical classes or a selected metabolic pathway. An untargeted metabolomics approach is a semiquantitative analysis of the largest possible number of metabolites contained in a biological sample. This is part I of a review intending to give an overview of the state of the art of major metabolic phenotyping technologies. Furthermore, their inherent analytical advantages and limits regarding experimental design, sample handling, standardization and workflow challenges are discussed.
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Affiliation(s)
- Abdellah Tebani
- Department of Metabolic Biochemistry, Rouen University Hospital, 76000, Rouen, France
- Normandie Université, UNIROUEN, CHU Rouen, IRIB, INSERM U1245, 76000, Rouen, France
- Normandie Université, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000, Rouen, France
| | - Carlos Afonso
- Normandie Université, UNIROUEN, INSA Rouen, CNRS, COBRA, 76000, Rouen, France
| | - Soumeya Bekri
- Department of Metabolic Biochemistry, Rouen University Hospital, 76000, Rouen, France.
- Normandie Université, UNIROUEN, CHU Rouen, IRIB, INSERM U1245, 76000, Rouen, France.
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Gonzalez-Riano C, Sanz-Rodríguez M, Escudero-Ramirez J, Lorenzo MP, Barbas C, Cubelos B, Garcia A. Target and untargeted GC–MS based metabolomic study of mouse optic nerve and its potential in the study of neurological visual diseases. J Pharm Biomed Anal 2018; 153:44-56. [DOI: 10.1016/j.jpba.2018.02.015] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2017] [Revised: 02/05/2018] [Accepted: 02/07/2018] [Indexed: 11/29/2022]
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Hemmler D, Heinzmann SS, Wöhr K, Schmitt-Kopplin P, Witting M. Tandem HILIC-RP liquid chromatography for increased polarity coverage in food analysis. Electrophoresis 2018; 39:1645-1653. [DOI: 10.1002/elps.201800038] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2018] [Revised: 03/09/2018] [Accepted: 03/09/2018] [Indexed: 11/11/2022]
Affiliation(s)
- Daniel Hemmler
- Chair of Analytical Food Chemistry; Technische Universität München; Freising Germany
- Research Unit Analytical BioGeoChemistry (BGC); Helmholtz Zentrum München; Neuherberg Germany
| | - Silke S. Heinzmann
- Research Unit Analytical BioGeoChemistry (BGC); Helmholtz Zentrum München; Neuherberg Germany
| | - Katrin Wöhr
- Research Unit Analytical BioGeoChemistry (BGC); Helmholtz Zentrum München; Neuherberg Germany
| | - Philippe Schmitt-Kopplin
- Chair of Analytical Food Chemistry; Technische Universität München; Freising Germany
- Research Unit Analytical BioGeoChemistry (BGC); Helmholtz Zentrum München; Neuherberg Germany
| | - Michael Witting
- Chair of Analytical Food Chemistry; Technische Universität München; Freising Germany
- Research Unit Analytical BioGeoChemistry (BGC); Helmholtz Zentrum München; Neuherberg Germany
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Zhang P, Zhang W, Lang Y, Qu Y, Chu F, Chen J, Cui L. Mass spectrometry-based metabolomics for tuberculosis meningitis. Clin Chim Acta 2018; 483:57-63. [PMID: 29678632 DOI: 10.1016/j.cca.2018.04.022] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2018] [Revised: 04/14/2018] [Accepted: 04/16/2018] [Indexed: 02/07/2023]
Abstract
Tuberculosis meningitis (TBM) is a prevalent form of extra-pulmonary tuberculosis that causes substantial morbidity and mortality. Diagnosis of TBM is difficult because of the limited sensitivity of existing laboratory techniques. A metabolomics approach can be used to investigate the sets of metabolites of both bacteria and host, and has been used to clarify the mechanisms underlying disease development, and identify metabolic changes, leadings to improved methods for diagnosis, treatment, and prognostication. Mass spectrometry (MS) is a major analysis platform used in metabolomics, and MS-based metabolomics provides wide metabolite coverage, because of its high sensitivity, and is useful for the investigation of Mycobacterium tuberculosis (Mtb) and related diseases. It has been used to investigate TBM diagnosis; however, the processes involved in the MS-based metabolomics approach are complex and flexible, and often consist of several steps, and small changes in the methods used can have a huge impact on the final results. Here, the process of MS-based metabolomics is summarized and its applications in Mtb and Mtb-related diseases discussed. Moreover, the current status of TBM metabolomics is described.
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Affiliation(s)
- Peixu Zhang
- Department of Neurology, First Hospital, Jilin University, Changchun 130021, PR China
| | - Weiguanliu Zhang
- Department of Neurology, First Hospital, Jilin University, Changchun 130021, PR China
| | - Yue Lang
- Department of Neurology, First Hospital, Jilin University, Changchun 130021, PR China
| | - Yan Qu
- Blood Bank, Jilin Women and Children Health Hospital, Changchun 130021, PR China
| | - Fengna Chu
- Department of Neurology, First Hospital, Jilin University, Changchun 130021, PR China
| | - Jiafeng Chen
- Department of Neurology, First Hospital, Jilin University, Changchun 130021, PR China
| | - Li Cui
- Department of Neurology, First Hospital, Jilin University, Changchun 130021, PR China.
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Forsberg EM, Huan T, Rinehart D, Benton HP, Warth B, Hilmers B, Siuzdak G. Data processing, multi-omic pathway mapping, and metabolite activity analysis using XCMS Online. Nat Protoc 2018; 13:633-651. [PMID: 29494574 PMCID: PMC5937130 DOI: 10.1038/nprot.2017.151] [Citation(s) in RCA: 164] [Impact Index Per Article: 27.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LC)-mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5-10 min, depending on user experience; data processing typically takes 1-3 h, and data analysis takes ∼30 min.
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Affiliation(s)
- Erica M Forsberg
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, California, USA
- Department of Chemistry and Biochemistry, San Diego State University, San Diego, California, USA
| | - Tao Huan
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, California, USA
| | - Duane Rinehart
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, California, USA
| | - H Paul Benton
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, California, USA
| | - Benedikt Warth
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, California, USA
- Department of Food Chemistry and Toxicology, University of Vienna, Vienna, Austria
| | - Brian Hilmers
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, California, USA
| | - Gary Siuzdak
- Center for Metabolomics and Mass Spectrometry, The Scripps Research Institute, La Jolla, California, USA
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Parastar H, Garreta-Lara E, Campos B, Barata C, Lacorte S, Tauler R. Chemometrics comparison of gas chromatography with mass spectrometry and comprehensive two-dimensional gas chromatography with time-of-flight mass spectrometry Daphnia magna
metabolic profiles exposed to salinity. J Sep Sci 2018; 41:2368-2379. [DOI: 10.1002/jssc.201701336] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2017] [Revised: 02/17/2018] [Accepted: 02/20/2018] [Indexed: 12/20/2022]
Affiliation(s)
- Hadi Parastar
- Department of Chemistry; Sharif University of Technology; Tehran Iran
| | | | - Bruno Campos
- Department of Environmental Chemistry; IDAEA-CSIC; Barcelona Spain
| | - Carlos Barata
- Department of Environmental Chemistry; IDAEA-CSIC; Barcelona Spain
| | - Silvia Lacorte
- Department of Environmental Chemistry; IDAEA-CSIC; Barcelona Spain
| | - Roma Tauler
- Department of Environmental Chemistry; IDAEA-CSIC; Barcelona Spain
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Mhlongo MI, Piater LA, Madala NE, Labuschagne N, Dubery IA. The Chemistry of Plant-Microbe Interactions in the Rhizosphere and the Potential for Metabolomics to Reveal Signaling Related to Defense Priming and Induced Systemic Resistance. FRONTIERS IN PLANT SCIENCE 2018; 9:112. [PMID: 29479360 PMCID: PMC5811519 DOI: 10.3389/fpls.2018.00112] [Citation(s) in RCA: 169] [Impact Index Per Article: 28.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2017] [Accepted: 01/22/2018] [Indexed: 05/21/2023]
Abstract
Plant roots communicate with microbes in a sophisticated manner through chemical communication within the rhizosphere, thereby leading to biofilm formation of beneficial microbes and, in the case of plant growth-promoting rhizomicrobes/-bacteria (PGPR), resulting in priming of defense, or induced resistance in the plant host. The knowledge of plant-plant and plant-microbe interactions have been greatly extended over recent years; however, the chemical communication leading to priming is far from being well understood. Furthermore, linkage between below- and above-ground plant physiological processes adds to the complexity. In metabolomics studies, the main aim is to profile and annotate all exo- and endo-metabolites in a biological system that drive and participate in physiological processes. Recent advances in this field has enabled researchers to analyze 100s of compounds in one sample over a short time period. Here, from a metabolomics viewpoint, we review the interactions within the rhizosphere and subsequent above-ground 'signalomics', and emphasize the contributions that mass spectrometric-based metabolomic approaches can bring to the study of plant-beneficial - and priming events.
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Affiliation(s)
- Msizi I. Mhlongo
- Department of Biochemistry, University of Johannesburg, Johannesburg, South Africa
| | - Lizelle A. Piater
- Department of Biochemistry, University of Johannesburg, Johannesburg, South Africa
| | - Ntakadzeni E. Madala
- Department of Biochemistry, University of Johannesburg, Johannesburg, South Africa
| | - Nico Labuschagne
- Department of Plant and Soil Sciences, University of Pretoria, Pretoria, South Africa
| | - Ian A. Dubery
- Department of Biochemistry, University of Johannesburg, Johannesburg, South Africa
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Abstract
LC-MS untargeted analysis is a valuable tool in the field of metabolic profiling (metabonomics/metabolomics), and the applications of this technology have grown rapidly over the past decade. LC-MS offers advantages over other analytical platforms such as speed, sensitivity, relative ease of sample preparation, and large dynamic range. As with any analytical approach, there are still drawbacks and challenges to overcome, but advances are constantly being made regarding both column chemistries and instrumentation. There are numerous untargeted LC-MS approaches which can be used in this ever-growing research field; these can be optimized depending on sample type and the nature of the study or biological question. Some of the main LC-MS approaches for the untargeted analysis of biological samples will be described in detail in the following protocol.
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Affiliation(s)
- Elizabeth J Want
- Computational and Systems Medicine, Imperial College London, London, UK.
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Gomes NG, Pereira DM, Valentão P, Andrade PB. Hybrid MS/NMR methods on the prioritization of natural products: Applications in drug discovery. J Pharm Biomed Anal 2018; 147:234-249. [DOI: 10.1016/j.jpba.2017.07.035] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2017] [Revised: 07/27/2017] [Accepted: 07/28/2017] [Indexed: 12/17/2022]
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50
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Two complementary reversed-phase separations for comprehensive coverage of the semipolar and nonpolar metabolome. Anal Bioanal Chem 2017; 410:1287-1297. [PMID: 29256075 DOI: 10.1007/s00216-017-0768-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2017] [Accepted: 11/13/2017] [Indexed: 12/17/2022]
Abstract
Although it is common in untargeted metabolomics to apply reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) methods that have been systematically optimized for lipids and central carbon metabolites, here we show that these established protocols provide poor coverage of semipolar metabolites because of inadequate retention. Our objective was to develop an RPLC approach that improved detection of these metabolites without sacrificing lipid coverage. We initially evaluated columns recently released by Waters under the CORTECS line by analyzing 47 small-molecule standards that evenly span the nonpolar and semipolar ranges. An RPLC method commonly used in untargeted metabolomics was considered a benchmarking reference. We found that highly nonpolar and semipolar metabolites cannot be reliably profiled with any single method because of retention and solubility limitations of the injection solvent. Instead, we optimized a multiplexed approach using the CORTECS T3 column to analyze semipolar compounds and the CORTECS C8 column to analyze lipids. Strikingly, we determined that combining these methods allowed detection of 41 of the total 47 standards, whereas our reference RPLC method detected only 10 of the 47 standards. We then applied credentialing to compare method performance at the comprehensive scale. The tandem method showed more than a fivefold increase in credentialing coverage relative to our RPLC benchmark. Our results demonstrate that comprehensive coverage of metabolites amenable to reversed-phase separation necessitates two reconstitution solvents and chromatographic methods. Thus, we suggest complementing HILIC methods with a dual T3 and C8 RPLC approach to increase coverage of semipolar metabolites and lipids for untargeted metabolomics. Graphical abstract Analysis of semipolar and nonpolar metabolites necessitates two reversed-phase chromatography (RPLC) methods, which extend metabolome coverage more than fivefold for untargeted profiling. HILIC hydrophilic interaction liquid chromatography.
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