1
|
Zhang X, Li Z, Zhao C, Chen T, Wang X, Sun X, Zhao X, Lu X, Xu G. Leveraging Unidentified Metabolic Features for Key Pathway Discovery: Chemical Classification-driven Network Analysis in Untargeted Metabolomics. Anal Chem 2024; 96:3409-3418. [PMID: 38354311 DOI: 10.1021/acs.analchem.3c04591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/16/2024]
Abstract
Untargeted metabolomics using liquid chromatography-electrospray ionization-high-resolution tandem mass spectrometry (UPLC-ESI-MS/MS) provides comprehensive insights into the dynamic changes of metabolites in biological systems. However, numerous unidentified metabolic features limit its utilization. In this study, a novel approach, the Chemical Classification-driven Molecular Network (CCMN), was proposed to unveil key metabolic pathways by leveraging hidden information within unidentified metabolic features. The method was demonstrated by using the herbivore-induced metabolic response in corn silk as a case study. Untargeted metabolomics analysis using UPLC-MS/MS was performed on wild corn silk and two genetically modified lines (pre- and postinsect treatment). Global annotation initially identified 256 (ESI-) and 327 (ESI+) metabolites. MS/MS-based classifications predicted 1939 (ESI-) and 1985 (ESI+) metabolic features into the chemical classes. CCMNs were then constructed using metabolic features shared classes, which facilitated the structure- or class annotation for completely unknown metabolic features. Next, 844/713 significantly decreased and 1593/1378 increased metabolites in ESI-/ESI+ modes were defined in response to insect herbivory, respectively. Method validation on a spiked maize sample demonstrated an overall class prediction accuracy rate of 95.7%. Potential key pathways were prescreened by a hypergeometric test using both structure- and class-annotated differential metabolites. Subsequently, CCMN was used to deeply amend and uncover the pathway metabolites deeply. Finally, 8 key pathways were defined, including phenylpropanoid (C6-C3), flavonoid, octadecanoid, diterpenoid, lignan, steroid, amino acid/small peptide, and monoterpenoid. This study highlights the effectiveness of leveraging unidentified metabolic features. CCMN-based key pathway analysis reduced the bias in conventional pathway enrichment analysis. It provides valuable insights into complex biological processes.
Collapse
Affiliation(s)
- Xiuqiong Zhang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116023, P. R. China
| | - Zaifang Li
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116023, P. R. China
| | - Chunxia Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116023, P. R. China
| | - Tiantian Chen
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116023, P. R. China
| | - Xinxin Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116023, P. R. China
| | - Xiaoshan Sun
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116023, P. R. China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116023, P. R. China
| | - Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116023, P. R. China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, P. R. China
- University of Chinese Academy of Sciences, Beijing 100049, P. R. China
- Liaoning Province Key Laboratory of Metabolomics, Dalian 116023, P. R. China
| |
Collapse
|
2
|
Lv Z, Wang B, Wang B, Zhang H. In vivo comprehensive metabolite profiling of esculetin and esculin derived from chicory in hyperuricemia rats using ultra-high-performance liquid chromatography coupled with quadrupole-orbitrap high-resolution mass spectrometry. J Sep Sci 2024; 47:e2300664. [PMID: 38010472 DOI: 10.1002/jssc.202300664] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Revised: 11/08/2023] [Accepted: 11/11/2023] [Indexed: 11/29/2023]
Abstract
Chicory, renowned for its multifaceted benefits, houses two vital coumarins, esculetin and esculin, both instrumental in reducing uric acid. This study emphasizes the metabolic pathways of esculetin and esculin under both standard and hyperuricemia conditions. Hyperuricemia was induced in Sprague-Dawley rats using oxonic acid potassium salt (300 mg·kg-1 ) and a 10% fructose water regimen over 21 days. Leveraging the ultra-high-performance liquid chromatography-Q Exactive hybrid quadrupole-orbitrap high resolution mass spectrometry, we analyzed the fragmentation behaviors of esculetin and esculin in rat bio-samples. Post oral-intake of esculetin or esculin, a notable dip in serum uric acid levels was observed in hyperuricemia rats. The investigation unveiled 24 esculetin metabolites and 14 for esculin. The metabolic pathways of both compounds were hydrolysis, hydroxylation, hydrogenation, dehydroxylation, glucuronidation, sulfation, and methylation. Interestingly, certain metabolites presented variations between standard and hyperuricemia rats, indicating that elevated levels of uric acid may affect enzyme activity linked to these metabolic reactions. This is the first systematic study on comparison of metabolic profiles of esculetin and esculin in both normal and hyperuricemia states, which was helpful to enrich our understanding of the complicated structure-activity relationships between esculin and esculetin and shed light to their action mechanism.
Collapse
Affiliation(s)
- Zheng Lv
- Institute of Traditional Medicine Analysis, Shandong Academy of Chinese Medicine, Jinan, P. R. China
- High-level Key Discipline of Traditional Medicine Analysis of the National Administration of Traditional Chinese Medicine, Jinan, P. R. China
| | - Boyang Wang
- Institute of Traditional Medicine Analysis, Shandong Academy of Chinese Medicine, Jinan, P. R. China
- High-level Key Discipline of Traditional Medicine Analysis of the National Administration of Traditional Chinese Medicine, Jinan, P. R. China
| | - Bianli Wang
- Institute of Traditional Medicine Analysis, Shandong Academy of Chinese Medicine, Jinan, P. R. China
- High-level Key Discipline of Traditional Medicine Analysis of the National Administration of Traditional Chinese Medicine, Jinan, P. R. China
| | - Huimin Zhang
- Institute of Traditional Medicine Analysis, Shandong Academy of Chinese Medicine, Jinan, P. R. China
- High-level Key Discipline of Traditional Medicine Analysis of the National Administration of Traditional Chinese Medicine, Jinan, P. R. China
| |
Collapse
|
3
|
Yu M, Dolios G, Petrick L. Reproducible untargeted metabolomics workflow for exhaustive MS2 data acquisition of MS1 features. J Cheminform 2022; 14:6. [PMID: 35172886 PMCID: PMC8848943 DOI: 10.1186/s13321-022-00586-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 02/03/2022] [Indexed: 01/16/2023] Open
Abstract
Unknown features in untargeted metabolomics and non-targeted analysis (NTA) are identified using fragment ions from MS/MS spectra to predict the structures of the unknown compounds. The precursor ion selected for fragmentation is commonly performed using data dependent acquisition (DDA) strategies or following statistical analysis using targeted MS/MS approaches. However, the selected precursor ions from DDA only cover a biased subset of the peaks or features found in full scan data. In addition, different statistical analysis can select different precursor ions for MS/MS analysis, which make the post-hoc validation of ions selected following a secondary analysis impossible for precursor ions selected by the original statistical method. Here we propose an automated, exhaustive, statistical model-free workflow: paired mass distance-dependent analysis (PMDDA), for reproducible untargeted mass spectrometry MS2 fragment ion collection of unknown compounds found in MS1 full scan. Our workflow first removes redundant peaks from MS1 data and then exports a list of precursor ions for pseudo-targeted MS/MS analysis on independent peaks. This workflow provides comprehensive coverage of MS2 collection on unknown compounds found in full scan analysis using a “one peak for one compound” workflow without a priori redundant peak information. We compared pseudo-spectra formation and the number of MS2 spectra linked to MS1 data using the PMDDA workflow to that obtained using CAMERA and RAMclustR algorithms. More annotated compounds, molecular networks, and unique MS/MS spectra were found using PMDDA compared with CAMERA and RAMClustR. In addition, PMDDA can generate a preferred ion list for iterative DDA to enhance coverage of compounds when instruments support such functions. Finally, compounds with signals in both positive and negative modes can be identified by the PMDDA workflow, to further reduce redundancies. The whole workflow is fully reproducible as a docker image xcmsrocker with both the original data and the data processing template.
Collapse
Affiliation(s)
- Miao Yu
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Georgia Dolios
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Lauren Petrick
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.,The Institute for Exposomic Research, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| |
Collapse
|
4
|
Nika MC, Aalizadeh R, Thomaidis NS. Non-target trend analysis for the identification of transformation products during ozonation experiments of citalopram and four of its biodegradation products. JOURNAL OF HAZARDOUS MATERIALS 2021; 419:126401. [PMID: 34182420 DOI: 10.1016/j.jhazmat.2021.126401] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 05/25/2021] [Accepted: 06/11/2021] [Indexed: 06/13/2023]
Abstract
During ozonation in wastewater treatment plants, ozone reacts with emerging pollutants, which are partially removed through the secondary treatment, as long as, with their biotransformation products, triggering the formation of ozonation transformation products (TPs). Although the transformation of parent compounds (PCs) and their metabolites has been reported in the literature, the probable transformation of biotransformation products has not been investigated so far. This study evaluates the fate of citalopram (CTR) and four of its biotransformation products (DESCTR, CTRAM, CTRAC and CTROXO) during ozonation experiments. A Gaussian curve-based trend analysis was performed for the first time for the automated detection of TPs in ozone concentrations ranging from 0.06 to 12 mg/L. In total 46 ozonation TPs were detected; 7 TPs of CTR, 10 of DESCTR, 9 of CTRAM, 12 of CTRAC and 8 of CTROXO and were structurally elucidated based on their high resolution tandem mass spectra interpretation and tandem mass spectra similarity with the respective PC. Results have demonstrated that the examined compounds follow common transformation pathways in reaction with ozone and that common TPs were formed through the ozonation of different structurally-alike compounds. Moreover, the toxicity of the identified TPs was predicted with an in-house risk assessment program.
Collapse
Affiliation(s)
- Maria-Christina Nika
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece.
| | - Reza Aalizadeh
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece
| | - Nikolaos S Thomaidis
- Laboratory of Analytical Chemistry, Department of Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis Zografou, 15771 Athens, Greece.
| |
Collapse
|
5
|
Gadara D, Coufalikova K, Bosak J, Smajs D, Spacil Z. Systematic Feature Filtering in Exploratory Metabolomics: Application toward Biomarker Discovery. Anal Chem 2021; 93:9103-9110. [PMID: 34156818 DOI: 10.1021/acs.analchem.1c00816] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Exploratory mass spectrometry-based metabolomics generates a plethora of features in a single analysis. However, >85% of detected features are typically false positives due to inefficient elimination of chimeric signals and chemical noise not relevant for biological and clinical data interpretation. The data processing is considered a bottleneck to unravel the translational potential in metabolomics. Here, we describe a systematic workflow to refine exploratory metabolomics data and reduce reported false positives. We applied the feature filtering workflow in a case/control study exploring common variable immunodeficiency (CVID). In the first stage, features were detected from raw liquid chromatography-mass spectrometry data by XCMS Online processing, blank subtraction, and reproducibility assessment. Detected features were annotated in metabolomics databases to produce a list of tentative identifications. We scrutinized tentative identifications' physicochemical properties, comparing predicted and experimental reversed-phase liquid chromatography (LC) retention time. A prediction model used a linear regression of 42 retention indices with the cLogP ranging from -6 to 11. The LC retention time probes the physicochemical properties and effectively reduces the number of tentatively identified metabolites, which are further submitted to statistical analysis. We applied the retention time-based analytical feature filtering workflow to datasets from the Metabolomics Workbench (www.metabolomicsworkbench.org), demonstrating the broad applicability. A subset of tentatively identified metabolites significantly different in CVID patients was validated by MS/MS acquisition to confirm potential CVID biomarkers' structures and virtually eliminate false positives. Our exploratory metabolomics data processing workflow effectively removes false positives caused by the chemical background and chimeric signals inherent to the analytical technique. It reduced the number of tentatively identified metabolites by 88%, from initially detected 6940 features in XCMS to 839 tentative identifications and streamlined consequent statistical analysis and data interpretation.
Collapse
Affiliation(s)
- Darshak Gadara
- RECETOX Centre, Faculty of Science, Masaryk University, Brno 62500, Czech Republic
| | - Katerina Coufalikova
- RECETOX Centre, Faculty of Science, Masaryk University, Brno 62500, Czech Republic
| | - Juraj Bosak
- Department of Biology, Faculty of Medicine, Masaryk University, Brno 62500, Czech Republic
| | - David Smajs
- Department of Biology, Faculty of Medicine, Masaryk University, Brno 62500, Czech Republic
| | - Zdenek Spacil
- RECETOX Centre, Faculty of Science, Masaryk University, Brno 62500, Czech Republic
| |
Collapse
|
6
|
Pan HQ, Zhou H, Miao S, Guo DA, Zhang XL, Hu Q, Mao XH, Ji S. Plant metabolomics for studying the effect of two insecticides on comprehensive constituents of Lonicerae Japonicae Flos. Chin J Nat Med 2021; 19:70-80. [PMID: 33516454 DOI: 10.1016/s1875-5364(21)60008-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Indexed: 11/30/2022]
Abstract
Pesticides' overuse and misuse have been reported to induce ingredient variations in herbal medicine, which is now gaining attention in the medicinal field as a form of alternative medicine. To date, available studies on pesticide-induced ingredient variations of herbal medicine are limited only on a few compounds and remain most others unexamined. In this study, a plant metabolomics-based strategy was performed to systematically explore the effects of two frequently used insecticides on the comprehensive constituents of Lonicerae Japonicae Flos (LJF), the flower buds of Lonicera japonica Thunb. Field trials were designed on a cultivating plot of L. japonica with controls and treatments of imidacloprid (IMI) and compound flonicamid and acetamiprid (CFA). Unbiased metabolite profiling was conducted by ultra-high performance liquid chromatography/quadrupole-Orbitrap mass spectrometer. After data pretreatment by automatic extraction and screening, a data matrix of metabolite features was submitted for statistical analyses. Consequently, 29 metabolic markers, including chlorogenic acids, iridoids and organic acid-glucosides were obtained and characterized. The relative quantitative assay was subsequently performed to monitor their variations across flowering developments. This is the first study that systematically explored the insecticide-induced metabolite variations of LJF while taking into account the inherent variability of flowering development. The results were beneficial for holistic quality assessment of LJF and significant for guiding scientific use of pesticides in the large-scale cultivation.
Collapse
Affiliation(s)
- Hui-Qin Pan
- NMPA Key Laboratory for Quality Control of Traditional Chinese Medicine, Shanghai Institute for Food and Drug Control, Shanghai 201203, China; Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Heng Zhou
- NMPA Key Laboratory for Quality Control of Traditional Chinese Medicine, Shanghai Institute for Food and Drug Control, Shanghai 201203, China
| | - Shui Miao
- NMPA Key Laboratory for Quality Control of Traditional Chinese Medicine, Shanghai Institute for Food and Drug Control, Shanghai 201203, China
| | - De-An Guo
- Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China
| | - Xiao-Li Zhang
- Shanghai Kaibao Pharmaceutical Co., Ltd., Shanghai 201401, China
| | - Qing Hu
- NMPA Key Laboratory for Quality Control of Traditional Chinese Medicine, Shanghai Institute for Food and Drug Control, Shanghai 201203, China
| | - Xiu-Hong Mao
- NMPA Key Laboratory for Quality Control of Traditional Chinese Medicine, Shanghai Institute for Food and Drug Control, Shanghai 201203, China
| | - Shen Ji
- NMPA Key Laboratory for Quality Control of Traditional Chinese Medicine, Shanghai Institute for Food and Drug Control, Shanghai 201203, China.
| |
Collapse
|
7
|
Zhu D, Kebede B, Chen G, McComb K, Frew R. Changes in milk metabolome during the lactation of dairy cows based on 1H NMR and UHPLC–QToF/MS. Int Dairy J 2020. [DOI: 10.1016/j.idairyj.2020.104836] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
|
8
|
Impact of freeze-drying and subsequent storage on milk metabolites based on 1H NMR and UHPLC-QToF/MS. Food Control 2020. [DOI: 10.1016/j.foodcont.2019.107017] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
|
9
|
Ju R, Liu X, Zheng F, Zhao X, Lu X, Lin X, Zeng Z, Xu G. A graph density-based strategy for features fusion from different peak extract software to achieve more metabolites in metabolic profiling from high-resolution mass spectrometry. Anal Chim Acta 2020; 1139:8-14. [PMID: 33190713 DOI: 10.1016/j.aca.2020.09.029] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Revised: 09/08/2020] [Accepted: 09/14/2020] [Indexed: 01/01/2023]
Abstract
In metabolomics study, it is not easy to extract the metabolites from data of ultra high-performance liquid chromatography-high-resolution mass spectrometry, especially for those with low abundance. Different software for peak recognition and matching use different algorithms, leading to different extract results. Therefore, integration of results from different software can obtain richer metabolome information, but the redundant features should be removed. In this study, an integrated strategy of fusing features and removing redundancy based on graph density (FRRGD) was proposed. A graph is used to cover the ion features generated by two open access software (XCMS, MZmine 2) and a software (SIEVE) from an instrument vendor, and redundant features were removed by searching the maximal complete sub-graphs. A standard mixture containing 41 metabolites and a spontaneous urine were utilized to develop the method and demonstrate its usefulness. For the standard mixture, 19, 19 and 27 metabolites were extracted by XCMS, MZmine 2 and SIEVE, respectively. After fusion by FRRGD, 37 metabolites were obtained. For the diluted spontaneous urine sample, 1103, 1500 and 387 metabolites were extracted by XCMS, MZmine 2 and SIEVE, respectively, FRRGD produced 1619 metabolites which were much more than individual software, significantly increasing metabolome coverage. The proposed FRRGD shows a great prospect as a new data processing strategy for metabolomics study.
Collapse
Affiliation(s)
- Ran Ju
- School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, China
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Fujian Zheng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Xiaohui Lin
- School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, China.
| | - Zhongda Zeng
- Dalian ChemDataSolution Information Technology Co. Ltd, Dalian, 116023, China.
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
| |
Collapse
|
10
|
Senan O, Aguilar-Mogas A, Navarro M, Capellades J, Noon L, Burks D, Yanes O, Guimerà R, Sales-Pardo M. CliqueMS: a computational tool for annotating in-source metabolite ions from LC-MS untargeted metabolomics data based on a coelution similarity network. Bioinformatics 2020; 35:4089-4097. [PMID: 30903689 PMCID: PMC6792096 DOI: 10.1093/bioinformatics/btz207] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2018] [Revised: 01/30/2019] [Accepted: 03/21/2019] [Indexed: 11/26/2022] Open
Abstract
Motivation The analysis of biological samples in untargeted metabolomic studies using LC-MS yields tens of thousands of ion signals. Annotating these features is of the utmost importance for answering questions as fundamental as, e.g. how many metabolites are there in a given sample. Results Here, we introduce CliqueMS, a new algorithm for annotating in-source LC-MS1 data. CliqueMS is based on the similarity between coelution profiles and therefore, as opposed to most methods, allows for the annotation of a single spectrum. Furthermore, CliqueMS improves upon the state of the art in several dimensions: (i) it uses a more discriminatory feature similarity metric; (ii) it treats the similarities between features in a transparent way by means of a simple generative model; (iii) it uses a well-grounded maximum likelihood inference approach to group features; (iv) it uses empirical adduct frequencies to identify the parental mass and (v) it deals more flexibly with the identification of the parental mass by proposing and ranking alternative annotations. We validate our approach with simple mixtures of standards and with real complex biological samples. CliqueMS reduces the thousands of features typically obtained in complex samples to hundreds of metabolites, and it is able to correctly annotate more metabolites and adducts from a single spectrum than available tools. Availability and implementation https://CRAN.R-project.org/package=cliqueMS and https://github.com/osenan/cliqueMS. Supplementary information Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Oriol Senan
- Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Spain
| | - Antoni Aguilar-Mogas
- Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Spain
| | - Miriam Navarro
- Department of Electronic Engineering, Metabolomics Platform, IISPV, Universitat Rovira i Virgili, Tarragona, Spain.,CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM), Madrid, Spain
| | - Jordi Capellades
- Department of Electronic Engineering, Metabolomics Platform, IISPV, Universitat Rovira i Virgili, Tarragona, Spain.,CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM), Madrid, Spain
| | - Luke Noon
- CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM), Madrid, Spain.,Centro de Investigación Príncipe Felipe, Valencia, Spain
| | - Deborah Burks
- CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM), Madrid, Spain.,Centro de Investigación Príncipe Felipe, Valencia, Spain
| | - Oscar Yanes
- Department of Electronic Engineering, Metabolomics Platform, IISPV, Universitat Rovira i Virgili, Tarragona, Spain.,CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM), Madrid, Spain
| | - Roger Guimerà
- Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Spain.,ICREA, Barcelona, Spain
| | - Marta Sales-Pardo
- Department of Chemical Engineering, Universitat Rovira i Virgili, Tarragona, Spain
| |
Collapse
|
11
|
A classification of liquid chromatography mass spectrometry techniques for evaluation of chemical composition and quality control of traditional medicines. J Chromatogr A 2019; 1609:460501. [PMID: 31515074 DOI: 10.1016/j.chroma.2019.460501] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2019] [Revised: 08/06/2019] [Accepted: 08/29/2019] [Indexed: 12/25/2022]
Abstract
Natural products (NPs) and traditional medicines (TMs) are used for treatment of various diseases and also to develop new drugs. However, identification of drug leads within the immense biodiversity of living organisms is a challenging task that requires considerable time, labor, and computational resources as well as the application of modern analytical instruments. LC-MS platforms are widely used for both drug discovery and quality control of TMs and food supplements. Moreover, a large dataset generated during LC-MS analysis contains valuable information that could be extracted and handled by means of various data mining and statistical tools. Novel sophisticated LC-MS based approaches are being introduced every year. Therefore, this review is prepared for the scientists specialized in pharmacognosy and analytical chemistry of NPs as well as working in related areas, in order to navigate them in the world of diverse LC-MS based techniques and strategies currently employed for NP discovery and dereplication, quality control, pattern recognition and sample comparison, and also in targeted and untargeted metabolomic studies. The suggested classification system includes the following LC-MS based procedures: elemental composition determination, isotopic fine structure analysis, mass defect filtering, de novo identification, clustering of the compounds in Molecular Networking (MN), diagnostic fragment ion (or neutral loss) filtering, manual dereplication using MS/MS data, database-assisted peak annotation, annotation of spectral trees, MS fingerprinting, feature extraction, bucketing of LC-MS data, peak profiling, predicted metabolite screening, targeted quantification of biomarkers, quantitative analysis of multi-component system, construction of chemical fingerprints, multi-targeted and untargeted metabolite profiling.
Collapse
|
12
|
Ju R, Liu X, Zheng F, Zhao X, Lu X, Zeng Z, Lin X, Xu G. Removal of false positive features to generate authentic peak table for high-resolution mass spectrometry-based metabolomics study. Anal Chim Acta 2019; 1067:79-87. [PMID: 31047152 DOI: 10.1016/j.aca.2019.04.011] [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: 01/27/2019] [Revised: 03/23/2019] [Accepted: 04/07/2019] [Indexed: 01/15/2023]
Abstract
In metabolomics research, false positive features from non-sample sources and noises usually exist in the peak table, they will make the results of screening differential metabolites or biomarkers unreliable. In this study, a method to remove false positive features (rFPF) was developed to improve the quality of the peak table. rFPF recognizes real peak profiles based on the information entropy and statistical correlation, and eliminates false positive features from non-sample sources and noises. A standard mixture with 42 standards (14 isotopic labeled internal standards and 28 common standards) and a urine sample were applied to evaluate the effectiveness of the rFPF method. The analysis results of metabolite standards showed that more than 92% false positive features were removed by rFPF, but target standards completely remained. The analysis results of urine sample showed that the number of features was significantly reduced from 7182 to 2522. Interestingly, 98% of the identified metabolites remained after removing false positive features. The proposed rFPF shows great prospects as a new data handling method for metabolomics studies. The MATLAB code and data can be downloaded from http://app.ifc.dicp.ac.cn/Confirmation/Authentication.html.
Collapse
Affiliation(s)
- Ran Ju
- School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, China
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Fujian Zheng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China
| | - Zhongda Zeng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China; Dalian ChemDataSolution Information Technology Co. Ltd, Dalian, 116023, China.
| | - Xiaohui Lin
- School of Computer Science and Technology, Dalian University of Technology, Dalian, 116024, China.
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, 116023, China.
| |
Collapse
|
13
|
Fu Y, Zhang Y, Zhou Z, Lu X, Lin X, Zhao C, Xu G. Screening and Determination of Potential Risk Substances Based on Liquid Chromatography–High-Resolution Mass Spectrometry. Anal Chem 2018; 90:8454-8461. [DOI: 10.1021/acs.analchem.8b01153] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Affiliation(s)
- Yanqing Fu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanhui Zhang
- School of Computer Science & Technology, Dalian University of Technology, Dalian 116023, China
| | - Zhihui Zhou
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaohui Lin
- School of Computer Science & Technology, Dalian University of Technology, Dalian 116023, China
| | - Chunxia Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
- University of Chinese Academy of Sciences, Beijing 100049, China
| |
Collapse
|
14
|
Zhao X, Zeng Z, Chen A, Lu X, Zhao C, Hu C, Zhou L, Liu X, Wang X, Hou X, Ye Y, Xu G. Comprehensive Strategy to Construct In-House Database for Accurate and Batch Identification of Small Molecular Metabolites. Anal Chem 2018; 90:7635-7643. [DOI: 10.1021/acs.analchem.8b01482] [Citation(s) in RCA: 62] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Zhongda Zeng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
- Dalian ChemDataSolution Information Technology Co. Ltd, Dalian 116023, China
| | - Aiming Chen
- Dalian ChemDataSolution Information Technology Co. Ltd, Dalian 116023, China
| | - Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Chunxia Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Chunxiu Hu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Lina Zhou
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Xiaolin Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Xiaoli Hou
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Yaorui Ye
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science, Dalian 116023, China
| |
Collapse
|
15
|
Wei DD, Wang JS, Duan JA, Kong LY. Metabolomic Assessment of Acute Cholestatic Injuries Induced by Thioacetamide and by Bile Duct Ligation, and the Protective Effects of Huang-Lian-Jie-Du-Decoction. Front Pharmacol 2018; 9:458. [PMID: 29867467 PMCID: PMC5952270 DOI: 10.3389/fphar.2018.00458] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Accepted: 04/18/2018] [Indexed: 12/22/2022] Open
Abstract
Huang-Lian-Jie-Du-Decoction, a traditional Chinese formula, has been reported to protect liver from various injuries. Two cholestasis models of rats induced by thioacetamide and by bile duct ligation were established and treated with Huang-Lian-Jie-Du-Decoction. Nuclear Magnetic Resonance-based urinary metabolic profiles were analyzed by orthogonal partial least squares discriminant analysis and univariate analysis to excavate differential metabolites associated with the injuries of the two models and the treatment effects of Huang-Lian-Jie-Du-Decoction. The two cholestatic models shared common metabolic features of excessive fatty acid oxidation, insufficient glutathione regeneration and disturbed gut flora, with specific characteristics of inhibited urea cycle and DNA damage in thioacetamide-intoxicated model, and perturbed Kreb's cycle and inhibited branched chain amino acid oxidation in bile duct ligation model. With good treatment effects, Huang-Lian-Jie-Du-Decoction could regain the balance of the disturbed metabolic status common in the two cholestasis injuries, e.g., unbalanced redox system and disturbed gut flora; and perturbed urea cycle in thioacetamide-intoxicated model and energy crisis (disturbed Kreb's cycle and oxidation of branched chain amino acid) in bile duct ligation model, respectively.
Collapse
Affiliation(s)
- Dan-Dan Wei
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing, China.,State Key Laboratory of Natural Medicines, Department of Natural Medicinal Chemistry, China Pharmaceutical University, Nanjing, China
| | - Jun-Song Wang
- Center for Molecular Metabolism, Nanjing University of Science and Technology, Nanjing, China
| | - Jin-Ao Duan
- Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Ling-Yi Kong
- State Key Laboratory of Natural Medicines, Department of Natural Medicinal Chemistry, China Pharmaceutical University, Nanjing, China
| |
Collapse
|
16
|
Guo W, Tan HY, Wang N, Wang X, Feng Y. Deciphering hepatocellular carcinoma through metabolomics: from biomarker discovery to therapy evaluation. Cancer Manag Res 2018; 10:715-734. [PMID: 29692630 PMCID: PMC5903488 DOI: 10.2147/cmar.s156837] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is the third most common cause of death from cancer, with increasing prevalence worldwide. The mortality rate of HCC is similar to its incidence rate, which reflects its poor prognosis. At present, the diagnosis of HCC is still mostly dependent on invasive biopsy, imaging methods, and serum α-fetoprotein (AFP) testing. Because of the asymptomatic nature of early HCC, biopsy and imaging methods usually detect HCC at the middle–late stages. AFP has limited sensitivity and specificity, as many other nonmalignant liver diseases can also result in a very high serum level of AFP. Therefore, better biomarkers with higher sensitivity and specificity at earlier stages are greatly needed. Since metabolic reprogramming is an essential hallmark of cancer and the liver is the metabolic hub of living systems, it is useful to investigate HCC from a metabolic perspective. As a noninvasive and nondestructive approach, metabolomics provides holistic information on dynamically metabolic responses of living systems to both endogenous and exogenous factors. Therefore, it would be conducive to apply metabolomics in investigating HCC. In this review, we summarize recent metabolomic studies on HCC cellular, animal, and clinicopathologic models with attention to metabolomics as a biomarker in cancer diagnosis. Recent applications of metabolomics with respect to therapeutic and prognostic evaluation of HCC are also covered, with emphasis on the potential of treatment by drugs from natural products. In the last section, the current challenges and trends of future development of metabolomics on HCC are discussed. Overall, metabolomics provides us with novel insight into the diagnosis, prognosis, and therapeutic evaluation of HCC.
Collapse
Affiliation(s)
- Wei Guo
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong
| | - Hor Yue Tan
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong
| | - Ning Wang
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong.,Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, China
| | - Xuanbin Wang
- Laboratory of Chinese Herbal Pharmacology, Oncology Center, Renmin Hospital, Hubei University of Medicine, Shiyan, China.,Hubei Key Laboratory of Wudang Local Chinese Medicine Research, Hubei University of Medicine, Shiyan, China
| | - Yibin Feng
- School of Chinese Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong.,Shenzhen Institute of Research and Innovation, The University of Hong Kong, Shenzhen, China.,Laboratory of Chinese Herbal Pharmacology, Oncology Center, Renmin Hospital, Hubei University of Medicine, Shiyan, China.,Hubei Key Laboratory of Wudang Local Chinese Medicine Research, Hubei University of Medicine, Shiyan, China
| |
Collapse
|
17
|
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.
Collapse
|
18
|
Fu Y, Zhao C, Lu X, Xu G. Nontargeted screening of chemical contaminants and illegal additives in food based on liquid chromatography–high resolution mass spectrometry. Trends Analyt Chem 2017. [DOI: 10.1016/j.trac.2017.07.014] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
|
19
|
A multiple-dimension liquid chromatography coupled with mass spectrometry data strategy for the rapid discovery and identification of unknown compounds from a Chinese herbal formula (Er-xian decoction). J Chromatogr A 2017; 1518:59-69. [DOI: 10.1016/j.chroma.2017.08.072] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2017] [Revised: 08/17/2017] [Accepted: 08/24/2017] [Indexed: 12/22/2022]
|
20
|
Mahieu NG, Patti GJ. Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites. Anal Chem 2017; 89:10397-10406. [PMID: 28914531 DOI: 10.1021/acs.analchem.7b02380] [Citation(s) in RCA: 183] [Impact Index Per Article: 26.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is now routine to detect tens of thousands of features from biological samples. Poor understanding of the data, however, has complicated interpretation and masked the number of unique metabolites actually being measured in an experiment. Here we place an upper bound on the number of unique metabolites detected in Escherichia coli samples analyzed with one untargeted metabolomics method. We first group multiple features arising from the same analyte, which we call "degenerate features", using a context-driven annotation approach. Surprisingly, this analysis revealed thousands of previously unreported degeneracies that reduced the number of unique analytes to ∼2961. We then applied an orthogonal approach to remove nonbiological features from the data using the 13C-based credentialing technology. This further reduced the number of unique analytes to less than 1000. Our 90% reduction in data is 5-fold greater than previously published studies. On the basis of the results, we propose an alternative approach to untargeted metabolomics that relies on thoroughly annotated reference data sets. To this end, we introduce the creDBle database ( http://creDBle.wustl.edu ), which contains accurate mass, retention time, and MS/MS fragmentation data as well as annotations of all credentialed features.
Collapse
Affiliation(s)
- Nathaniel G Mahieu
- Department of Chemistry, Washington University , St. Louis, Missouri 63130, United States
| | - Gary J Patti
- Department of Chemistry, Washington University , St. Louis, Missouri 63130, United States
| |
Collapse
|
21
|
Yu L, Ye T, Bai YL, Cai WJ, Ding J, Yuan BF, Feng YQ. Profiling of potential brassinosteroids in different tissues of rape flower by stable isotope labeling - liquid chromatography/mass spectrometry analysis. Anal Chim Acta 2017; 1037:55-62. [PMID: 30292315 DOI: 10.1016/j.aca.2017.08.038] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2017] [Revised: 08/17/2017] [Accepted: 08/21/2017] [Indexed: 10/18/2022]
Abstract
Brassinosteroids (BRs) play crucial roles in a variety of physiological processes in plants. The full elucidation of the functions of RBs relies on sensitive detection and accurate measurement of BRs in plants. However, the identification and quantification of BRs are challenging due to their low abundance as well as poor ionization efficiencies during mass spectrometry-based analysis. Herein, we developed a highly sensitive and selective strategy for profiling potential BRs in plants by stable isotope labeling liquid chromatography multiple reaction monitoring scan mass spectrometry (SIL-LC-MRM-MS) analysis. In the strategy, we used a pair of stable isotope labeling reagents 4-phenylaminomethyl-benzeneboronic acid (4-PAMBA) and d5-4-phenylaminomethyl-benzeneboronic acid (4-PAMBA-d5) that can react with C22-C23 cis-diol on BRs for profiling potential BRs in plant tissues. The 4-PAMBA and 4-PAMBA-d5 labeled BRs could generate two characteristic neutral loss under collision induced dissociation (CID), respectively, which is used to establish the MRM-based detection and screening. The precursor ions of BRs labeled with 4-PAMBA and 4-PAMBA-d5 were set according to the reported structures of BRs, and the corresponding product ions were predicted by subtracting the lost neutral loss. In this respect, corresponding precursor ions and product ions in MRM transitions are formed. The peak pairs with a fixed mass difference, similar retention times and intensities were assigned as potential BRs. Using the developed SIL-LC-MRM-MS strategy, we successfully found 13 potential BR in different tissues of rape flower. Taken together, the SIL-LC-MRM-MS analytical strategy is promising for profiling potential BRs as well as other compounds that have the same functional moiety from complex biological samples.
Collapse
Affiliation(s)
- Lei Yu
- Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education), Department of Chemistry, Wuhan University, Wuhan 430072, PR China
| | - Tiantian Ye
- Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education), Department of Chemistry, Wuhan University, Wuhan 430072, PR China
| | - Ya-Li Bai
- Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education), Department of Chemistry, Wuhan University, Wuhan 430072, PR China
| | - Wen-Jing Cai
- Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education), Department of Chemistry, Wuhan University, Wuhan 430072, PR China
| | - Jun Ding
- Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education), Department of Chemistry, Wuhan University, Wuhan 430072, PR China
| | - Bi-Feng Yuan
- Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education), Department of Chemistry, Wuhan University, Wuhan 430072, PR China
| | - Yu-Qi Feng
- Key Laboratory of Analytical Chemistry for Biology and Medicine (Ministry of Education), Department of Chemistry, Wuhan University, Wuhan 430072, PR China.
| |
Collapse
|
22
|
DeFelice BC, Mehta SS, Samra S, Čajka T, Wancewicz B, Fahrmann JF, Fiehn O. Mass Spectral Feature List Optimizer (MS-FLO): A Tool To Minimize False Positive Peak Reports in Untargeted Liquid Chromatography-Mass Spectroscopy (LC-MS) Data Processing. Anal Chem 2017; 89:3250-3255. [PMID: 28225594 DOI: 10.1021/acs.analchem.6b04372] [Citation(s) in RCA: 115] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Untargeted metabolomics by liquid chromatography-mass spectrometry generates data-rich chromatograms in the form of m/z-retention time features. Managing such datasets is a bottleneck. Many popular data processing tools, including XCMS-online and MZmine2, yield numerous false-positive peak detections. Flagging and removing such false peaks manually is a time-consuming task and prone to human error. We present a web application, Mass Spectral Feature List Optimizer (MS-FLO), to improve the quality of feature lists after initial processing to expedite the process of data curation. The tool utilizes retention time alignments, accurate mass tolerances, Pearson's correlation analysis, and peak height similarity to identify ion adducts, duplicate peak reports, and isotopic features of the main monoisotopic metabolites. Removing such erroneous peaks reduces the overall number of metabolites in data reports and improves the quality of subsequent statistical investigations. To demonstrate the effectiveness of MS-FLO, we processed 28 biological studies and uploaded raw and results data to the Metabolomics Workbench website ( www.metabolomicsworkbench.org ), encompassing 1481 chromatograms produced by two different data processing programs used in-house (MZmine2 and later MS-DIAL). Post-processing of datasets with MS-FLO yielded a 7.8% automated reduction of total peak features and flagged an additional 7.9% of features, per dataset, for review by the user. When manually curated, 87% of these additional flagged features were verified false positives. MS-FLO is an open source web application that is freely available for use at http://msflo.fiehnlab.ucdavis.edu .
Collapse
Affiliation(s)
- Brian C DeFelice
- University of California, Davis , West Coast Metabolomics Center, 451 E. Health Sciences Drive, Rm 1300, Davis, California 95616, United States
| | - Sajjan Singh Mehta
- University of California, Davis , West Coast Metabolomics Center, 451 E. Health Sciences Drive, Rm 1300, Davis, California 95616, United States
| | - Stephanie Samra
- University of California, Davis , West Coast Metabolomics Center, 451 E. Health Sciences Drive, Rm 1300, Davis, California 95616, United States
| | - Tomáš Čajka
- University of California, Davis , West Coast Metabolomics Center, 451 E. Health Sciences Drive, Rm 1300, Davis, California 95616, United States
| | - Benjamin Wancewicz
- University of California, Davis , West Coast Metabolomics Center, 451 E. Health Sciences Drive, Rm 1300, Davis, California 95616, United States
| | - Johannes F Fahrmann
- University of California, Davis , West Coast Metabolomics Center, 451 E. Health Sciences Drive, Rm 1300, Davis, California 95616, United States.,Department of Clinical Cancer Prevention, University of Texas MD Anderson Cancer Center , 6767 Bertner Avenue, Houston, Texas 77030-2603, United States
| | - Oliver Fiehn
- University of California, Davis , West Coast Metabolomics Center, 451 E. Health Sciences Drive, Rm 1300, Davis, California 95616, United States.,Department of Biochemistry, Faculty of Sciences, King Abdulaziz University , Abdullah Sulayman, Jeddah 21589, Saudi Arabia
| |
Collapse
|
23
|
Andra SS, Austin C, Patel D, Dolios G, Awawda M, Arora M. Trends in the application of high-resolution mass spectrometry for human biomonitoring: An analytical primer to studying the environmental chemical space of the human exposome. ENVIRONMENT INTERNATIONAL 2017; 100:32-61. [PMID: 28062070 PMCID: PMC5322482 DOI: 10.1016/j.envint.2016.11.026] [Citation(s) in RCA: 95] [Impact Index Per Article: 13.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2016] [Revised: 11/23/2016] [Accepted: 11/27/2016] [Indexed: 05/05/2023]
Abstract
Global profiling of xenobiotics in human matrices in an untargeted mode is gaining attention for studying the environmental chemical space of the human exposome. Defined as the study of a comprehensive inclusion of environmental influences and associated biological responses, human exposome science is currently evolving out of the metabolomics science. In analogy to the latter, the development and applications of high resolution mass spectrometry (HRMS) has shown potential and promise to greatly expand our ability to capture the broad spectrum of environmental chemicals in exposome studies. HRMS can perform both untargeted and targeted analysis because of its capability of full- and/or tandem-mass spectrum acquisition at high mass accuracy with good sensitivity. The collected data from target, suspect and non-target screening can be used not only for the identification of environmental chemical contaminants in human matrices prospectively but also retrospectively. This review covers recent trends and advances in this field. We focus on advances and applications of HRMS in human biomonitoring studies, and data acquisition and mining. The acquired insights provide stepping stones to improve understanding of the human exposome by applying HRMS, and the challenges and prospects for future research.
Collapse
Affiliation(s)
- Syam S Andra
- Exposure Biology, Senator Frank R. Lautenberg Environmental Health Sciences Laboratory, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Christine Austin
- Exposure Biology, Senator Frank R. Lautenberg Environmental Health Sciences Laboratory, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Dhavalkumar Patel
- Exposure Biology, Senator Frank R. Lautenberg Environmental Health Sciences Laboratory, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Georgia Dolios
- Exposure Biology, Senator Frank R. Lautenberg Environmental Health Sciences Laboratory, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Mahmoud Awawda
- Exposure Biology, Senator Frank R. Lautenberg Environmental Health Sciences Laboratory, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Manish Arora
- Exposure Biology, Senator Frank R. Lautenberg Environmental Health Sciences Laboratory, Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| |
Collapse
|
24
|
What can we do to refine the redundant data in LC–MS and GC–MS based metabolomics? Bioanalysis 2017; 9:235-238. [DOI: 10.4155/bio-2016-0272] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022] Open
|
25
|
Fu Y, Zhou Z, Kong H, Lu X, Zhao X, Chen Y, Chen J, Wu Z, Xu Z, Zhao C, Xu G. Nontargeted Screening Method for Illegal Additives Based on Ultrahigh-Performance Liquid Chromatography-High-Resolution Mass Spectrometry. Anal Chem 2016; 88:8870-7. [PMID: 27480407 DOI: 10.1021/acs.analchem.6b02482] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Identification of illegal additives in complex matrixes is important in the food safety field. In this study a nontargeted screening strategy was developed to find illegal additives based on ultrahigh-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS). First, an analytical method for possible illegal additives in complex matrixes was established including fast sample pretreatment, accurate UHPLC separation, and HRMS detection. Second, efficient data processing and differential analysis workflow were suggested and applied to find potential risk compounds. Third, structure elucidation of risk compounds was performed by (1) searching online databases [Metlin and the Human Metabolome Database (HMDB)] and an in-house database which was established at the above-defined conditions of UHPLC-HRMS analysis and contains information on retention time, mass spectra (MS), and tandem mass spectra (MS/MS) of 475 illegal additives, (2) analyzing fragment ions, and (3) referring to fragmentation rules. Fish was taken as an example to show the usefulness of the nontargeted screening strategy, and six additives were found in suspected fish samples. Quantitative analysis was further carried out to determine the contents of these compounds. The satisfactory application of this strategy in fish samples means that it can also be used in the screening of illegal additives in other kinds of food samples.
Collapse
Affiliation(s)
- Yanqing Fu
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science , Dalian 116023, China.,University of Chinese Academy of Sciences , Beijing 100049, China
| | - Zhihui Zhou
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science , Dalian 116023, China.,University of Chinese Academy of Sciences , Beijing 100049, China
| | - Hongwei Kong
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science , Dalian 116023, China.,University of Chinese Academy of Sciences , Beijing 100049, China
| | - Xin Lu
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science , Dalian 116023, China.,University of Chinese Academy of Sciences , Beijing 100049, China
| | - Xinjie Zhao
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science , Dalian 116023, China.,University of Chinese Academy of Sciences , Beijing 100049, China
| | - Yihui Chen
- Xiangshan Entry-Exit Inspection and Quarantine Bureau, Ningbo 315000, China
| | - Jia Chen
- Hangzhou Pooke Testing Technology Company, Limited, Hangzhou 310000, China
| | - Zeming Wu
- Thermo Fisher Scientific, China, Application Center, Shanghai 210623, China
| | - Zhiliang Xu
- Hangzhou Pooke Testing Technology Company, Limited, Hangzhou 310000, China
| | - Chunxia Zhao
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science , Dalian 116023, China.,University of Chinese Academy of Sciences , Beijing 100049, China
| | - Guowang Xu
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Science , Dalian 116023, China.,University of Chinese Academy of Sciences , Beijing 100049, China
| |
Collapse
|
26
|
An improved pseudotargeted metabolomics approach using multiple ion monitoring with time-staggered ion lists based on ultra-high performance liquid chromatography/quadrupole time-of-flight mass spectrometry. Anal Chim Acta 2016; 927:82-8. [DOI: 10.1016/j.aca.2016.05.008] [Citation(s) in RCA: 37] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2016] [Revised: 04/30/2016] [Accepted: 05/02/2016] [Indexed: 01/13/2023]
|
27
|
Qiu S, Yang WZ, Yao CL, Qiu ZD, Shi XJ, Zhang JX, Hou JJ, Wang QR, Wu WY, Guo DA. Nontargeted metabolomic analysis and “commercial-homophyletic” comparison-induced biomarkers verification for the systematic chemical differentiation of five different parts of Panax ginseng. J Chromatogr A 2016; 1453:78-87. [DOI: 10.1016/j.chroma.2016.05.051] [Citation(s) in RCA: 72] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2016] [Revised: 04/19/2016] [Accepted: 05/12/2016] [Indexed: 01/10/2023]
|
28
|
Ghaste M, Mistrik R, Shulaev V. Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics. Int J Mol Sci 2016; 17:ijms17060816. [PMID: 27231903 PMCID: PMC4926350 DOI: 10.3390/ijms17060816] [Citation(s) in RCA: 107] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2016] [Revised: 05/14/2016] [Accepted: 05/17/2016] [Indexed: 02/02/2023] Open
Abstract
Metabolomics, along with other "omics" approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data.
Collapse
Affiliation(s)
- Manoj Ghaste
- Department of Biological Sciences, College of Arts and Sciences, University of North Texas, Denton, TX 76203, USA.
| | | | - Vladimir Shulaev
- Department of Biological Sciences, College of Arts and Sciences, University of North Texas, Denton, TX 76203, USA.
| |
Collapse
|
29
|
Luo P, Dai W, Yin P, Zeng Z, Kong H, Zhou L, Wang X, Chen S, Lu X, Xu G. Multiple reaction monitoring-ion pair finder: a systematic approach to transform nontargeted mode to pseudotargeted mode for metabolomics study based on liquid chromatography-mass spectrometry. Anal Chem 2015; 87:5050-5. [PMID: 25884293 DOI: 10.1021/acs.analchem.5b00615] [Citation(s) in RCA: 110] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
Pseudotargeted metabolic profiling is a novel strategy combining the advantages of both targeted and untargeted methods. The strategy obtains metabolites and their product ions from quadrupole time-of-flight (Q-TOF) MS by information-dependent acquisition (IDA) and then picks targeted ion pairs and measures them on a triple-quadrupole MS by multiple reaction monitoring (MRM). The picking of ion pairs from thousands of candidates is the most time-consuming step of the pseudotargeted strategy. Herein, a systematic and automated approach and software (MRM-Ion Pair Finder) were developed to acquire characteristic MRM ion pairs by precursor ions alignment, MS(2) spectrum extraction and reduction, characteristic product ion selection, and ion fusion. To test the reliability of the approach, a mixture of 15 metabolite standards was first analyzed; the representative ion pairs were correctly picked out. Then, pooled serum samples were further studied, and the results were confirmed by the manual selection. Finally, a comparison with a commercial peak alignment software was performed, and a good characteristic ion coverage of metabolites was obtained. As a proof of concept, the proposed approach was applied to a metabolomics study of liver cancer; 854 metabolite ion pairs were defined in the positive ion mode from serum. Our approach provides a high throughput method which is reliable to acquire MRM ion pairs for pseudotargeted metabolomics with improved metabolite coverage and facilitate more reliable biomarkers discoveries.
Collapse
Affiliation(s)
- Ping Luo
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Weidong Dai
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Peiyuan Yin
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Zhongda Zeng
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Hongwei Kong
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Lina Zhou
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Xiaolin Wang
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Shili Chen
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Xin Lu
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| | - Guowang Xu
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning 116023, China
| |
Collapse
|
30
|
Yin P, Xu G. Current state-of-the-art of nontargeted metabolomics based on liquid chromatography-mass spectrometry with special emphasis in clinical applications. J Chromatogr A 2014; 1374:1-13. [PMID: 25444251 DOI: 10.1016/j.chroma.2014.11.050] [Citation(s) in RCA: 81] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2014] [Revised: 11/16/2014] [Accepted: 11/17/2014] [Indexed: 12/21/2022]
Abstract
Metabolomics, as a part of systems biology, has been widely applied in different fields of life science by studying the endogenous metabolites. The development and applications of liquid chromatography (LC) coupled with high resolution mass spectrometry (MS) greatly improve the achievable data quality in non-targeted metabolic profiling. However, there are still some emerging challenges to be covered in LC-MS based metabolomics. Here, recent approaches about sample collection and preparation, instrumental analysis, and data handling of LC-MS based metabolomics are summarized, especially in the analysis of clinical samples. Emphasis is put on the improvement of analytical techniques including the combination of different LC columns, isotope coded derivatization methods, pseudo-targeted LC-MS method, new data analysis algorithms and structural identification of important metabolites.
Collapse
Affiliation(s)
- Peiyuan Yin
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China
| | - Guowang Xu
- Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.
| |
Collapse
|