1
|
Yang PJ, Tsai EM, Hou MF, Lee YJ, Wang TN. Global untargeted and individual targeted plasma metabolomics of breast cancer recurrence modified by hormone receptors. Breast Cancer 2024; 31:659-670. [PMID: 38652345 DOI: 10.1007/s12282-024-01579-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Accepted: 03/26/2024] [Indexed: 04/25/2024]
Abstract
BACKGROUND Breast cancer is a heterogeneous and complex etiological disease. Understanding perturbations of circulating metabolites could improve prognosis. METHODS We recruited breast cancer patients from Kaohsiung Medical University (KMU) to perform untargeted (case-control design) and targeted (patient cohort) metabolomics analyses in the discovery and validation phases to evaluate interaction effects between clinical factors and plasma metabolites using multivariable Cox proportional hazards model. RESULTS In the discovery phase, partial least squares-discriminant analysis (PLS-DA) showed that plasma metabolites were significantly different between recurrent and non-recurrent breast cancer patients. Metabolite set enrichment analysis (MSEA) and metabolomic pathway analysis (MetPA) showed that valine, leucine, and isoleucine degradation was the significant pathway, and volcano plot showed significant ten upregulated and two downregulated metabolites between recurrent and non-recurrent cases. Combined with receiver operating characteristic (ROC) curve and biological significance, creatine, valine, methionine, and mannose were selected for the validation phase. In this patient cohort with 41 new-recurrent vs. 248 non-recurrent breast cancer cases, followed for 720.49 person-years, compared with low level of valine, high valine level was significantly negatively associated with recurrent breast cancer (aHR: 0.36, 95% CI: 0.18-0.72, P = 0.004), especially in ER-negative and PR-negative status. There were interaction effects between valine and ER (Pinteraction = 0.006) as well as PR (Pinteraction = 0.002) on recurrent breast cancer. After Bonferroni correction, stratification effects between valine and hormone receptors were still significant. CONCLUSION Our study revealed that plasma metabolites were significantly different between recurrent and non-recurrent patients, proposing therapeutic insights for breast cancer prognosis.
Collapse
Affiliation(s)
- Pei-Jing Yang
- Department of Public Health, College of Health Science, Kaohsiung Medical University, No. 100, Shin-Chuan 1St Road, Sanmin Dist., Kaohsiung, 80708, Taiwan
| | - Eing-Mei Tsai
- Graduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, No.100, Shin-Chuan 1st Road, Sanmin Dist., Kaohsiung, 80708, Taiwan
- Department of Obstetrics and Gynecology, Kaohsiung Medical University Chung-Ho Memorial Hospital, No.100, Tzyou 1st Road, Sanmin Dist., Kaohsiung, 80756, Taiwan
| | - Ming-Feng Hou
- Division of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Chung-Ho Memorial Hospital, No.100, Tzyou 1st Road, Sanmin Dist., Kaohsiung, 80756, Taiwan
- Department of Biomedical Science and Environmental Biology, College of Life Science, Kaohsiung Medical University, No.100, Shin-Chuan 1st Road, Sanmin Dist., Kaohsiung, 80708, Taiwan
| | - Yen-Jung Lee
- Center for Research Resources and Development, Kaohsiung Medical University, No.100, Shin-Chuan 1st Road, Sanmin Dist., Kaohsiung, 80708, Taiwan
| | - Tsu-Nai Wang
- Department of Public Health, College of Health Science, Kaohsiung Medical University, No. 100, Shin-Chuan 1St Road, Sanmin Dist., Kaohsiung, 80708, Taiwan.
- Research Center for Environmental Medicine, Kaohsiung Medical University, No.100, Shin-Chuan 1st Road, Sanmin Dist., Kaohsiung, 80708, Taiwan.
| |
Collapse
|
2
|
Rosenberger T, Bell AM, Reifferscheid G, Smith KEC, Schäffer A, Ternes TA, Buchinger S. Extrapolation of cytotoxic masked effects in planar in vitro assays. Anal Bioanal Chem 2024; 416:3519-3532. [PMID: 38656365 DOI: 10.1007/s00216-024-05302-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 04/08/2024] [Accepted: 04/15/2024] [Indexed: 04/26/2024]
Abstract
The masking of specific effects in in vitro assays by cytotoxicity is a commonly known phenomenon. This may result in a partial or complete loss of effect signals. For common in vitro assays, approaches for identifying and quantifying cytotoxic masking are partly available. However, a quantification of cytotoxicity-affected signals is not possible. As an alternative, planar bioassays that combine high-performance thin layer chromatography with in vitro assays, such as the planar yeast estrogen screen (p-YES), might allow for a quantification of cytotoxically affected signals. Affected signals form a typical ring structure with a supressed or completely lacking centre that results in a double peak chromatogram. This study investigates whether these double peaks can be used for fitting a peak function to extrapolate the theoretical, unaffected signals. The precision of the modelling was evaluated for four individual peak functions, using 42 ideal, undistorted peaks from estrogenic model compounds in the p-YES. Modelled ED50-values from bisphenol A (BPA) experiments with cytotoxically disturbed signals were 13 times higher than for the apparent data without compensation for cytotoxicity (320 ± 63 ng versus 24 ± 17 ng). This finding has a high relevance for the modelling of mixture effects according to concentration addition that requires unaffected, complete dose-response relationships. Finally, we applied the approach to results of a p-YES assay on leachate samples of an elastomer material used in water engineering. In summary, the fitting approach enables the quantitative evaluation of cytotoxically affected signals in planar in vitro assays and also has applications for other fields of chemical analysis like distorted chromatography signals.
Collapse
Affiliation(s)
- Timothy Rosenberger
- Department G - Qualitative Hydrology, Federal Institute of Hydrology (BfG), Am Mainzer Tor 1, 56068, Koblenz, Germany
| | - Anna Maria Bell
- Department G - Qualitative Hydrology, Federal Institute of Hydrology (BfG), Am Mainzer Tor 1, 56068, Koblenz, Germany
| | - Georg Reifferscheid
- Department G - Qualitative Hydrology, Federal Institute of Hydrology (BfG), Am Mainzer Tor 1, 56068, Koblenz, Germany
| | - Kilian E C Smith
- Environmental Chemistry - Department of Water, Environment, Construction and Safety, University of Applied Sciences Magdeburg-Stendal, Breitscheidstraße 2, 39114, Magdeburg, Germany
| | - Andreas Schäffer
- Institute for Environmental Research, RWTH Aachen University, Worringerweg 1, 52074, Aachen, Germany
| | - Thomas A Ternes
- Department G - Qualitative Hydrology, Federal Institute of Hydrology (BfG), Am Mainzer Tor 1, 56068, Koblenz, Germany
| | - Sebastian Buchinger
- Department G - Qualitative Hydrology, Federal Institute of Hydrology (BfG), Am Mainzer Tor 1, 56068, Koblenz, Germany.
| |
Collapse
|
3
|
Zhou J, Li J, Gao W, Zhang S, Wang C, Lin J, Zhang S, Yu J, Tang K. Combination of continuous wavelet transform and genetic algorithm-based Otsu for efficient mass spectrometry peak detection. Biochem Biophys Res Commun 2022; 624:75-80. [PMID: 35940130 DOI: 10.1016/j.bbrc.2022.07.083] [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: 07/16/2022] [Revised: 07/20/2022] [Accepted: 07/21/2022] [Indexed: 11/28/2022]
Abstract
Mass spectrometry (MS) data is susceptible to random noises and alternating baseline, posing great challenges to spectral peak detection, especially for weak peaks and overlapping peaks. Herein, an efficient peak detection algorithm combining continuous wavelet transform (CWT) and genetic algorithm-based threshold segmentation (denoted as WSTGA) for mass spectrometry was proposed. Firstly, Mexican Hat wavelet was selected as the mother wavelet by comparing the matching degree between the difference of Gaussian (DOG) and different wavelets. Subsequently, the ridges and valleys were identified from 2D wavelet coefficient matrix. Afterward, an improved threshold segmentation method, Otsu method based on genetic algorithm, was introduced to find optimal segmentation threshold and achieve better image segmentation, overcoming the deficiency of traditional Otsu method that cannot handle long-tailed unimodal histograms. Finally, the characteristic peaks were successfully identified by utilizing the ridge-valley lines in wavelet space and original spectrum. Receiver operating characteristic (ROC) curve, area under curve (AUC) and F₁ measure are used as criterions to evaluate performance of peak detection algorithms. Compared with multi-scale peak detection (MSPD) and CWT and image segmentation (CWT-IS) methods, all the results showed that WSTGA can achieve better peak detection. More importantly, the experimental results from MALDI-TOF spectra demonstrated that WSTGA can effectively detect more weak peaks and overlapping peaks while maintaining a lower false peak detection rate than MSPD and CWT-IS methods, indicating its great advantages in characteristic peak identification.
Collapse
Affiliation(s)
- Junfei Zhou
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, PR China; Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis of Zhejiang Province, Institute of Mass Spectrometry, School of Materials Science and Chemical Engineering, Ningbo University, Ningbo, PR China
| | - Junhui Li
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, PR China; Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis of Zhejiang Province, Institute of Mass Spectrometry, School of Materials Science and Chemical Engineering, Ningbo University, Ningbo, PR China
| | - Wenqing Gao
- Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis of Zhejiang Province, Institute of Mass Spectrometry, School of Materials Science and Chemical Engineering, Ningbo University, Ningbo, PR China.
| | - Shun Zhang
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, PR China; Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, 2019E10020, Ningbo, PR China
| | - Chenlu Wang
- Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis of Zhejiang Province, Institute of Mass Spectrometry, School of Materials Science and Chemical Engineering, Ningbo University, Ningbo, PR China
| | - Jing Lin
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, PR China; Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, 2019E10020, Ningbo, PR China
| | - Sijia Zhang
- Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo, PR China; Key Laboratory of Diagnosis and Treatment of Digestive System Tumors of Zhejiang Province, 2019E10020, Ningbo, PR China
| | - Jiancheng Yu
- Faculty of Electrical Engineering and Computer Science, Ningbo University, Ningbo, PR China; Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis of Zhejiang Province, Institute of Mass Spectrometry, School of Materials Science and Chemical Engineering, Ningbo University, Ningbo, PR China.
| | - Keqi Tang
- Zhejiang Engineering Research Center of Advanced Mass Spectrometry and Clinical Application, Key Laboratory of Advanced Mass Spectrometry and Molecular Analysis of Zhejiang Province, Institute of Mass Spectrometry, School of Materials Science and Chemical Engineering, Ningbo University, Ningbo, PR China.
| |
Collapse
|
4
|
Tsai J, Wang S, Chang C, Chen C, Wen C, Chen G, Kuo C, Tseng YJ, Chen C. Identification of traumatic acid as a potential plasma biomarker for sarcopenia using a metabolomics-based approach. J Cachexia Sarcopenia Muscle 2022; 13:276-286. [PMID: 34939349 PMCID: PMC8818620 DOI: 10.1002/jcsm.12895] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/07/2020] [Revised: 08/30/2021] [Accepted: 11/21/2021] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND The pathogenesis of sarcopenia is complex and has not been well explored. Identifying biomarkers is a promising strategy for exploring the mechanism of sarcopenia. This study aimed to identify potential biomarkers of sarcopenia through a metabolomic analysis of plasma metabolites in elderly subjects (≥65 years of age) vs. younger adults (<65 years of age). METHODS Of the 168 candidates in the Comprehensive Geriatric Assessment and Frailty Study of Elderly Outpatients, 24 elderly subjects (≥65 years of age) with sarcopenia were age and sex matched with 24 elderly subjects without sarcopenia. In addition, 24 younger adults were recruited for comparison. Muscle strength, gait speed, and metabolic and inflammatory parameters, including plasma tumour necrosis factor-α, C-reactive protein, irisin, and growth differentiation factor 15 (GDF-15) levels were assessed. Metabolomic analysis was carried out using the plasma metabolites. RESULTS Seventy-two participants were enrolled, including 10 (41.6%) men and 14 (58.3%) women in both groups of elderly subjects. The median ages of elderly subjects with and without sarcopenia were 82 (range: 67-88) and 81.5 (range: 67-87) years, respectively. Among the 242 plasma metabolic peaks analysed among these three groups, traumatic acid was considered as a sarcopenia-related metabolite. The plasma traumatic acid signal intensity level was significantly higher in elderly subjects with sarcopenia than in elderly subjects without sarcopenia [591.5 (inter-quartile range, IQR: 491.5-664.5) vs. 430.0 (IQR: 261.0-599.5), P = 0.0063]. The plasma concentrations of traumatic acid were 15.8 (IQR: 11.5-21.7), 21.1 (IQR: 16.0-25.8), and 24.3 (IQR: 18.0-29.5) ppb in younger adults [age range: 23-37 years, 12 (50%) men], elderly subjects without sarcopenia, and elderly subjects with sarcopenia, respectively, thereby depicting an increasing tendency (P for trend = 0.034). This pattern was similar to that of GDF-15, a recognized sarcopenia-related factor. Plasma traumatic acid concentrations were also positively correlated with the presence of hypertension (r = 0.25, P = 0.034), glucose AC (r = 0.34, P = 0.0035), creatinine (r = 0.40, P = 0.0006), and GDF-15 levels (r = 0.25, P = 0.0376), but negatively correlated with the Modification of Diet in Renal Disease-simplify-glomerular filtration rate (r = -0.50, P < 0.0001). Similarly, plasma GDF-15 concentrations were associated with these factors. CONCLUSIONS Traumatic acid might represent a potential plasma biomarker of sarcopenia. However, further studies are needed to validate the results and investigate the underlying mechanisms.
Collapse
Affiliation(s)
- Jaw‐Shiun Tsai
- Department of Family MedicineNational Taiwan University Hospital, National Taiwan UniversityTaipeiTaiwan
- Department of Family Medicine, College of MedicineNational Taiwan UniversityTaipeiTaiwan
| | - San‐Yuan Wang
- Master Program in Clinical Genomics and Proteomics, College of PharmacyTaipei Medical UniversityTaipeiTaiwan
| | - Chin‐Hao Chang
- Department of Medical ResearchNational Taiwan University HospitalTaipeiTaiwan
| | - Chin‐Ying Chen
- Department of Family MedicineNational Taiwan University Hospital, National Taiwan UniversityTaipeiTaiwan
- Department of Family Medicine, College of MedicineNational Taiwan UniversityTaipeiTaiwan
| | - Chiung‐Jung Wen
- Department of Family Medicine, College of MedicineNational Taiwan UniversityTaipeiTaiwan
- Department of Geriatrics and GerontologyNational Taiwan University HospitalTaipeiTaiwan
| | - Guan‐Yuan Chen
- Department and Graduate Institute of Forensic Medicine, College of MedicineNational Taiwan UniversityTaipeiTaiwan
| | - Ching‐Hua Kuo
- The Metabolomics Core Laboratory, Center of Genomic MedicineNational Taiwan UniversityTaipeiTaiwan
- School of Pharmacy, College of MedicineNational Taiwan UniversityTaipeiTaiwan
- Department of PharmacyNational Taiwan University Hospital, National Taiwan UniversityTaipeiTaiwan
| | - Y. Jane Tseng
- The Metabolomics Core Laboratory, Center of Genomic MedicineNational Taiwan UniversityTaipeiTaiwan
- School of Pharmacy, College of MedicineNational Taiwan UniversityTaipeiTaiwan
- Department of Computer Science and Information EngineeringNational Taiwan UniversityTaipeiTaiwan
- Graduate Institute of Biomedical Electronics and BioinformaticsNational Taiwan UniversityTaipeiTaiwan
| | - Ching‐Yu Chen
- Department of Family MedicineNational Taiwan University Hospital, National Taiwan UniversityTaipeiTaiwan
- Department of Family Medicine, College of MedicineNational Taiwan UniversityTaipeiTaiwan
| |
Collapse
|
5
|
Telu KH, Marupaka R, Andriamaharavo NR, Simón-Manso Y, Liang Y, Mirokhin YA, Bukhari TH, Preston RJ, Kashi L, Kelman Z, Stein SE. Creation and filtering of a recurrent spectral library of CHO cell metabolites and media components. Biotechnol Bioeng 2021; 118:1491-1510. [PMID: 33404064 PMCID: PMC8048470 DOI: 10.1002/bit.27661] [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] [Received: 08/22/2020] [Revised: 12/02/2020] [Accepted: 12/13/2020] [Indexed: 02/02/2023]
Abstract
This paper reports the first implementation of a new type of mass spectral library for the analysis of Chinese hamster ovary (CHO) cell metabolites that allows users to quickly identify most compounds in any complex metabolite sample. We also describe an annotation methodology developed to filter out artifacts and low‐quality spectra from recurrent unidentified spectra of metabolites. CHO cells are commonly used to produce biological therapeutics. Metabolic profiles of CHO cells and media can be used to monitor process variability and look for markers that discriminate between batches of product. We have created a comprehensive library of both identified and unidentified metabolites derived from CHO cells that can be used in conjunction with tandem mass spectrometry to identify metabolites. In addition, we present a workflow that can be used for assigning confidence to a NIST MS/MS Library search match based on prior probability of general utility. The goal of our work is to annotate and identify (when possible), all liquid chromatography‐mass spectrometry generated metabolite ions as well as create automatable library building and identification pipelines for use by others in the field.
Collapse
Affiliation(s)
- Kelly H Telu
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Ramesh Marupaka
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Nirina R Andriamaharavo
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Yamil Simón-Manso
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Yuxue Liang
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Yuri A Mirokhin
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Tallat H Bukhari
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| | - Renae J Preston
- Biomolecular Labeling Laboratory, Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland, Rockville, Maryland, USA
| | - Lila Kashi
- Biomolecular Labeling Laboratory, Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland, Rockville, Maryland, USA
| | - Zvi Kelman
- Biomolecular Labeling Laboratory, Institute for Bioscience and Biotechnology Research, National Institute of Standards and Technology and the University of Maryland, Rockville, Maryland, USA
| | - Stephen E Stein
- Mass Spectrometry Data Center, Biomolecular Measurement Division, National Institute of Standards and Technology, Gaithersburg, Maryland, USA
| |
Collapse
|
6
|
Chen PY, Hsieh MJ, Liao YH, Lin YC, Hou YT. Liver-on-a-chip platform to study anticancer effect of statin and its metabolites. Biochem Eng J 2021. [DOI: 10.1016/j.bej.2020.107831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
|
7
|
Lin YC, Chen YT, Li KY, Chen MJ. Investigating the Mechanistic Differences of Obesity-Inducing Lactobacillus kefiranofaciens M1 and Anti-obesity Lactobacillus mali APS1 by Microbolomics and Metabolomics. Front Microbiol 2020; 11:1454. [PMID: 32733406 PMCID: PMC7360855 DOI: 10.3389/fmicb.2020.01454] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Accepted: 06/04/2020] [Indexed: 12/27/2022] Open
Abstract
Many studies have investigated the anti-obesity effects of probiotics in animal models and humans. However, few studies have focused on the mechanisms of obesity-inducing probiotics. In a previous study, we demonstrated that specific bacterial strains isolated from kefir, Lactobacillus kefirnofaciens M1 and Lactobacillus mali APS1, possess obesity and anti-obesity effects, respectively, in high-fat diet (HFD)-induced obese mice. Thus, in the present study, we systematically investigated whether APS1 and M1 affect energy homeostasis and lipid metabolism in HFD-induced obese mice and how this might be achieved. We observed that the M1/APS1 intervention influenced fat accumulation by regulating adipogenesis and inflammation-related marker expression both in vitro and in a HFD induced C57BL/6J mice model. We also observed putative links between key taxa and possible metabolic processes of the gut microbiota. Notably, families Christensenellaceae and S24_7 were negatively correlated with body weight gain through increase in the essential esterized carnitine for energy expenditure. These results suggest the importance of specific probiotic interventions affecting leanness and obesity of subjects under a HFD, which are operated by modulating the tripartite relationship among the host, microbiota, and metabolites.
Collapse
Affiliation(s)
- Yu-Chun Lin
- Livestock Research Institute, Council of Agriculture, Executive Yuan, Tainan, Taiwan.,Department of Animal Science and Technology, National Taiwan University, Taipei, Taiwan
| | - Yung-Tsung Chen
- Institute of Biotechnology, National Taiwan University, Taipei, Taiwan
| | - Kuan-Yi Li
- Department of Animal Science and Technology, National Taiwan University, Taipei, Taiwan
| | - Ming-Ju Chen
- Department of Animal Science and Technology, National Taiwan University, Taipei, Taiwan
| |
Collapse
|
8
|
Hsu WH, Wang SJ, Chao YM, Chen CJ, Wang YF, Fuh JL, Chen SP, Lin YL. Urine metabolomics signatures in reversible cerebral vasoconstriction syndrome. Cephalalgia 2020; 40:735-747. [DOI: 10.1177/0333102419897621] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background The pathophysiology of reversible cerebral vasoconstriction syndrome is unclear. An unbiased systems-based approach might help to illustrate the metabolite profiling and underlying pathophysiology. Methods Urine samples were collected from reversible cerebral vasoconstriction syndrome patients and matched controls recruited in Taipei Veterans General Hospital. 1H-Nuclear magnetic resonance was used to initially explore the metabolic profile, and liquid chromatography tandem mass spectrometry was then used to identify metabolic alterations in reversible cerebral vasoconstriction syndrome. Untargeted metabolite screening was randomly performed on 10 reversible cerebral vasoconstriction syndrome patients and 10 control subjects in the discovery phase. The selected untargeted metabolites were further validated on 47 reversible cerebral vasoconstriction syndrome patients during their ictal stage (with 40 of them having remission samples) and 47 controls in the replication phase. Results and conclusion Six metabolites-hippurate, citrate, 1,3,7-trimethyluric acid, ascorbic acid, D-glucurono-6,3-lactone, and D- threo-isocitric acid-with t-test derived p-value < 0.05 and VIP score >1, were identified as potential urine signatures that can well distinguish reversible cerebral vasoconstriction syndrome subjects at ictal stage from controls. Among them, citrate, hippurate, ascorbic acid, and D-glucurono-6,3-lactone were significantly lower, and 1,3,7-trimethyluric acid and D- threo-isocitric acid were higher in reversible cerebral vasoconstriction syndrome patients. Of these, four selected metabolites, citrate, D-glucurono-6,3-lactone, ascorbic acid, and 1,3,7-trimethyluric acid, returned to normal levels in remission. These metabolites are related to pathways associated with free radical scavenging, with the hub molecules being associated with endothelial dysfunction or sympathetic overactivity. Whether these metabolites and their implicated networks play a role in the pathogenesis of reversible cerebral vasoconstriction syndrome remains to be confirmed.
Collapse
Affiliation(s)
- Wei-Hsiang Hsu
- Department of Chinese Pharmaceutical Sciences and Chinese Medicine Resources, China Medical University, Taichung
| | - Shuu-Jiun Wang
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei
- Brain Research Center, National Yang-Ming University, Taipei
- Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei
- Institute of Brain Science, National Yang-Ming University, Taipei
| | - Yen-Ming Chao
- Department of Chinese Pharmaceutical Sciences and Chinese Medicine Resources, China Medical University, Taichung
| | - Chao-Jung Chen
- Graduate Institute of Integrated Medicine, China Medical University, Taichung
| | - Yen-Feng Wang
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei
- Brain Research Center, National Yang-Ming University, Taipei
- Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei
| | - Jong-Ling Fuh
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei
- Brain Research Center, National Yang-Ming University, Taipei
- Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei
| | - Shih-Pin Chen
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei
- Brain Research Center, National Yang-Ming University, Taipei
- Faculty of Medicine, School of Medicine, National Yang-Ming University, Taipei
- Division of Translational Research, Department of Medical Research, Taipei Veterans General Hospital, Taipei
- Institute of Clinical Medicine, National Yang-Ming University, Taipei
| | - Yun-Lian Lin
- Department of Chinese Pharmaceutical Sciences and Chinese Medicine Resources, China Medical University, Taichung
- Department of Pharmacy, National Taiwan University, Taipei
| |
Collapse
|
9
|
Hsu WH, Lee CH, Chao YM, Kuo CH, Ku WC, Chen CC, Lin YL. ASIC3-dependent metabolomics profiling of serum and urine in a mouse model of fibromyalgia. Sci Rep 2019; 9:12123. [PMID: 31431652 PMCID: PMC6702159 DOI: 10.1038/s41598-019-48315-w] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Accepted: 07/30/2019] [Indexed: 12/27/2022] Open
Abstract
Fibromyalgia (FM) is characterized by chronic widespread pain. The pathogenesis of FM remains unclear. No specific biomarkers are available. Animal models of FM may provide an opportunity to explore potential biomarkers in a relative homogenous disease condition. Here, we probed the metabolomics profiles of serum and urine in a mouse model of FM induced by intermittent cold stress (ICS). We focused on the role of acid-sensing ion channel 3 (ASIC3) in the metabolomics profiling because ICS treatment induced chronic widespread muscle pain lasting for 1 month in wild-type (Asic3+/+) but not Asic3-knockout (Asic3−/−) mice. Serum and urine samples were collected from both genotypes at different ICS stages, including before ICS (basal level) and post-ICS at days 10 (middle phase, P10) and 40 (recovery phase, P40). Control naïve mice and ICS-induced FM mice differed in 1H-NMR- and LC-MS-based metabolomics profiling. On pathway analysis, the leading regulated pathways in Asic3+/+ mice were taurine and hypotaurine, cysteine and methionine, glycerophospholipid, and ascorbate and aldarate metabolisms, and the major pathways in Asic3−/− mice involved amino acid-related metabolism. Finally, we developed an algorithm for the impactful metabolites in the FM model including cis-aconitate, kynurenate, taurine, pyroglutamic acid, pyrrolidonecarboxylic acid, and 4-methoxyphenylacetic acid in urine as well as carnitine, deoxycholic acid, lysoPC(16:0), lysoPC(20:3), oleoyl-L-carnitine, and trimethylamine N-oxide in serum. Asic3−/− mice were impaired in only muscle allodynia development but not other pain symptoms in the ICS model, so the ASIC3-dependent metabolomics changes could be useful for developing diagnostic biomarkers specific to chronic widespread muscle pain, the core symptom of FM. Further pharmacological validations are needed to validate these metabolomics changes as potential biomarkers for FM diagnosis and/or treatment responses.
Collapse
Affiliation(s)
- Wei-Hsiang Hsu
- Department of Chinese Pharmaceutical Sciences and Chinese Medicine Resources, China Medical University, Taichung, 40402, Taiwan
| | - Cheng-Han Lee
- Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan
| | - Yen-Ming Chao
- Department of Chinese Pharmaceutical Sciences and Chinese Medicine Resources, China Medical University, Taichung, 40402, Taiwan
| | - Ching-Hua Kuo
- Department of Pharmacy, National Taiwan University, Taipei, 100, Taiwan
| | - Wei-Chi Ku
- School of Medicine, College of Medicine, Fu Jen Catholic University, New Taipei, 24205, Taiwan
| | - Chih-Cheng Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei, 115, Taiwan. .,Taiwan Mouse Clinic - National Comprehensive Mouse Phenotyping and Drug Testing Center, Academia Sinica, Taipei, 115, Taiwan.
| | - Yun-Lian Lin
- Department of Chinese Pharmaceutical Sciences and Chinese Medicine Resources, China Medical University, Taichung, 40402, Taiwan.
| |
Collapse
|
10
|
Chen CHS, Kuo TC, Kuo HC, Tseng YJ, Kuo CH, Yuan TH, Chan CC. Metabolomics of Children and Adolescents Exposed to Industrial Carcinogenic Pollutants. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2019; 53:5454-5465. [PMID: 30971086 DOI: 10.1021/acs.est.9b00392] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Studies on metabolomes of carcinogenic pollutants among children and adolescents are limited. We aim to identify metabolic perturbations in 107 children and adolescents (aged 9-15) exposed to multiple carcinogens in a polluted area surrounding the largest petrochemical complex in Taiwan. We measured urinary concentrations of eight carcinogen exposure biomarkers (heavy metals and polycyclic aromatic hydrocarbons (PAHs) represented by 1-hydroxypyrene), and urinary oxidative stress biomarkers and serum acylcarnitines as biomarkers of early health effects. Serum metabolomics was analyzed using a liquid chromatography mass spectrometry-based method. Pathway analysis and "meet-in-the-middle" approach were applied to identify potential metabolites and biological mechanisms linking carcinogens exposure with early health effects. We found 10 potential metabolites possibly linking increased exposure to IARC group 1 carcinogens (As, Cd, Cr, Ni) and group 2 carcinogens (V, Hg, PAHs) with elevated oxidative stress and deregulated serum acylcarnitines, including inosine monophosphate and adenosine monophosphate (purine metabolism), malic acid and oxoglutaric acid (citrate cycle), carnitine (fatty acid metabolism), and pyroglutamic acid (glutathione metabolism). Purine metabolism was identified as the possible mechanism affected by children and adolescents' exposure to carcinogens. These findings contribute to understanding the health effects of childhood and adolescence exposure to multiple industrial carcinogens during critical periods of development.
Collapse
Affiliation(s)
- Chi-Hsin S Chen
- Institute of Occupational Medicine and Industrial Hygiene, College of Public Health , National Taiwan University , No. 17, Xu-Zhou Road , Taipei 10055 , Taiwan
| | - Tien-Chueh Kuo
- The Metabolomics Core Laboratory, Center of Genomic Medicine , National Taiwan University , No. 1, Sec. 4, Roosevelt Road , Taipei 10617 , Taiwan
- Graduate Institute of Biomedical Electronics and Bioinformatics, College of Electrical Engineering and Computer Science , National Taiwan University , No. 1, Sec. 4, Roosevelt Road , Taipei 10617 , Taiwan
| | - Han-Chun Kuo
- The Metabolomics Core Laboratory, Center of Genomic Medicine , National Taiwan University , No. 1, Sec. 4, Roosevelt Road , Taipei 10617 , Taiwan
| | - Yufeng J Tseng
- Graduate Institute of Biomedical Electronics and Bioinformatics, College of Electrical Engineering and Computer Science , National Taiwan University , No. 1, Sec. 4, Roosevelt Road , Taipei 10617 , Taiwan
- Department of Computer Science and Information Engineering, College of Electrical Engineering and Computer Science , National Taiwan University ., No. 1, Sec. 4, Roosevelt Road , Taipei 10617 , Taiwan
| | - Ching-Hua Kuo
- School of Pharmacy, College of Medicine , National Taiwan University , No. 33, Linsen S. Road , Taipei 10055 , Taiwan
| | - Tzu-Hsuen Yuan
- Institute of Occupational Medicine and Industrial Hygiene, College of Public Health , National Taiwan University , No. 17, Xu-Zhou Road , Taipei 10055 , Taiwan
| | - Chang-Chuan Chan
- Institute of Occupational Medicine and Industrial Hygiene, College of Public Health , National Taiwan University , No. 17, Xu-Zhou Road , Taipei 10055 , Taiwan
| |
Collapse
|
11
|
Sun CY, Lin CJ, Pan HC, Lee CC, Lu SC, Hsieh YT, Huang SY, Huang HY. Clinical association between the metabolite of healthy gut microbiota, 3-indolepropionic acid and chronic kidney disease. Clin Nutr 2018; 38:2945-2948. [PMID: 30612852 DOI: 10.1016/j.clnu.2018.11.029] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2018] [Revised: 11/20/2018] [Accepted: 11/30/2018] [Indexed: 01/14/2023]
Abstract
BACKGROUND & AIMS Emerging evidence indicates that gut microbiota serves an important role in the development and progression of chronic kidney disease (CKD). Changes to the gut microbial flora can cause the generation of uremic toxins, which contribute to chronic kidney injury. The aim of the current study was to explore the clinical association between metabolites and CKD. METHODS Between August 2013 and January 2015, a two-phase case-control study was conducted to analyze the clinical association between metabolites and CKD in a community health program. The first phase of the study was a prospective case-control survey designed for comparing the differences in the metabolome profile of patients with (n = 10) and without (n = 10) estimated glomerular filtration rate (eGFR) rapid decline (a yearly decline >20%). The second phase of the study was a cross-sectional case-control study, which checked and compared the metabolites, indoxyl sulfate and p-cresol sulfate levels between healthy subjects (n = 144) and CKD patients (n = 140). RESULTS In the first phase of the study, it was revealed that IPA levels of patients with rapid renal function decline were significantly reduced compared with the control patients (n = 10 for each group). The second phase furthered checked and compared the IPA, indoxyl sulfate and p-cresol sulfate levels between healthy subjects (n = 144) and CKD patients (n = 140). The results showed that the average level of indoxyl sulfate (2738.2 vs. 541.0 ng/ml, P < 0.01) and p-cresol sulfate (1442.8 vs. 1394.6 ng/ml, P < 0.01) were significantly higher in the CKD patients, while the average level of IPA was significantly higher (49.8 vs. 34.7 ng/ml, P < 0.01) in the control patients. CONCLUSIONS Our results suggest that IPA might be an important biomarker and renal protector against the development of CKD.
Collapse
Affiliation(s)
- Chiao-Yin Sun
- Department of Nephrology, Chang Gung Memorial Hospital, Keelung, Taiwan; Kidney Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan; School of Medicine, Chang Gung University, Taoyuan, Taiwan; Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, Taiwan.
| | - Cheng-Jui Lin
- Division of Nephrology, Department of Internal Medicine, Mackay Memorial Hospital, Taipei, Taiwan; Mackay Junior College of Medicine, Nursing and Management, Taipei, Taiwan
| | - Heng-Chih Pan
- Department of Nephrology, Chang Gung Memorial Hospital, Keelung, Taiwan; Kidney Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Chin-Chan Lee
- Department of Nephrology, Chang Gung Memorial Hospital, Keelung, Taiwan; School of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Shang-Chieh Lu
- Department of Nephrology, Chang Gung Memorial Hospital, Keelung, Taiwan; Kidney Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan; Community Medicine Research Center, Chang Gung Memorial Hospital, Keelung, Taiwan
| | - Yu-Ting Hsieh
- Department of Nephrology, Chang Gung Memorial Hospital, Keelung, Taiwan; Kidney Research Center, Chang Gung Memorial Hospital, Taoyuan, Taiwan
| | - Shih-Yi Huang
- Graduate Institute of Metabolism and Obesity Sciences, Taipei Medical University, Taipei, Taiwan
| | - Hui-Yu Huang
- Graduate Institute of Metabolism and Obesity Sciences, Taipei Medical University, Taipei, Taiwan; Department of Food Science, Nutrition, and Nutraceutical Biotechnology, Shih-Chien University, Taipei, Taiwan
| |
Collapse
|
12
|
Chen MX, Wang SY, Kuo CH, Tsai IL. Metabolome analysis for investigating host-gut microbiota interactions. J Formos Med Assoc 2018; 118 Suppl 1:S10-S22. [PMID: 30269936 DOI: 10.1016/j.jfma.2018.09.007] [Citation(s) in RCA: 105] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2018] [Accepted: 09/05/2018] [Indexed: 02/07/2023] Open
Abstract
Dysbiosis of the gut microbiome is associated with host health conditions. Many diseases have shown to have correlations with imbalanced microbiota, including obesity, inflammatory bowel disease, cancer, and even neurodegeneration disorders. Metabolomics studies targeting small molecule metabolites that impact the host metabolome and their biochemical functions have shown promise for studying host-gut microbiota interactions. Metabolome analysis determines the metabolites being discussed for their biological implications in host-gut microbiota interactions. To facilitate understanding the critical aspects of metabolome analysis, this article reviewed (1) the sample types used in host-gut microbiome studies; (2) mass spectrometry (MS)-based analytical methods and (3) useful tools for MS-based data processing/analysis. In addition to the most frequently used sample type, feces, we also discussed others biosamples, such as urine, plasma/serum, saliva, cerebrospinal fluid, exhaled breaths, and tissues, to better understand gut metabolite systemic effects on the whole organism. Gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), and capillary electrophoresis-mass spectrometry (CE-MS), three powerful tools that can be utilized to study host-gut microbiota interactions, are included with examples of their applications. After obtaining big data from MS-based instruments, noise removal, peak detection, missing value imputation, and data analysis are all important steps for acquiring valid results in host-gut microbiome research. The information provided in this review will help new researchers aiming to join this field by providing a global view of the analytical aspects involved in gut microbiota-related metabolomics studies.
Collapse
Affiliation(s)
- Michael X Chen
- Department of Laboratory Medicine and Pathology, The University of British Columbia, Canada; Island Medical Program, University of Victoria, Canada
| | - San-Yuan Wang
- Master Program in Clinical Pharmacogenomics and Pharmacoproteomics, College of Pharmacy, Taipei Medical University, Taipei, Taiwan
| | - Ching-Hua Kuo
- School of Pharmacy, College of Medicine, National Taiwan University, Taipei, Taiwan; The Metabolomics Core Laboratory, NTU Centers of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan; Department of Pharmacy, National Taiwan University Hospital, Taipei, Taiwan
| | - I-Lin Tsai
- Master Program in Clinical Pharmacogenomics and Pharmacoproteomics, College of Pharmacy, Taipei Medical University, Taipei, Taiwan; Department of Biochemistry and Molecular Cell Biology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan; Graduate Institute of Medical Sciences, College of Medicine, Taipei Medical University, Taipei, Taiwan; International PhD Program for Cell Therapy and Regeneration Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan.
| |
Collapse
|
13
|
Wang PS, Kuo CH, Yang HC, Liang YJ, Huang CJ, Sheen LY, Pan WH. Postprandial Metabolomics Response to Various Cooking Oils in Humans. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2018; 66:4977-4984. [PMID: 29716192 DOI: 10.1021/acs.jafc.8b00530] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Lipids account for a high proportion of dietary calories, which greatly affect human health. As a result of differences in composition of fatty acid of individual cooking oils, certain biological effects of these oils may vary. This study aimed to compare postprandial metabolomic profiles of six commonly consumed cooking oils/fats. Adopting a switch-over experimental design ( n = 15), we carried out a human feeding study with six groups (control without oils, soybean oil, olive oil, palm oil, camellia oil, and tallow) and collected fasting and postprandial serum samples. The metabolomic profile was measured by ultra-high-pressure liquid chromatography-quadrupole time of flight. We observed significant differences between the control group and experimental groups for 33 serum metabolites (false discovery rate; p < 0.05), which take part in lipid digestion, fatty acid metabolism, metabolism of pyrimidines and pyrimidine nucleosides, amino acid metabolism, neurobiology, and antioxidation. Sparse partial least squares discriminant analysis revealed distinct metabolomics patterns between monounsaturated fatty acid (MUFA) and saturated fatty acid oils, between soybean oil, olive oil, and palm oil, and between two MUFA-rich oils (olive and camellia oils). The present metabolomics study suggests shared and distinct metabolisms of various cooking oils/fats.
Collapse
Affiliation(s)
| | - Ching-Hua Kuo
- School of Pharmacy, College of Medicine , National Taiwan University , 33 Linsen South Road , Zhongzheng District, Taipei 10055 , Taiwan
- The Metabolomics Core Laboratory, Center of Genomic Medicine , National Taiwan University , 2 Syu-jhou Road , Taipei 10055 , Taiwan
| | | | | | | | | | | |
Collapse
|
14
|
Chen YT, Yang NS, Lin YC, Ho ST, Li KY, Lin JS, Liu JR, Chen MJ. A combination of Lactobacillus mali APS1 and dieting improved the efficacy of obesity treatment via manipulating gut microbiome in mice. Sci Rep 2018; 8:6153. [PMID: 29670255 PMCID: PMC5906640 DOI: 10.1038/s41598-018-23844-y] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Accepted: 03/21/2018] [Indexed: 02/06/2023] Open
Abstract
The difficulty of long-term management has produced a high rate of failure for obesity patients. Therefore, improving the efficacy of current obesity treatment is a significant goal. We hypothesized that combining a probiotic Lactobacillus mali APS1 intervention with dieting could improve the efficacy of obesity and hepatic steatosis treatment compared to dieting alone. Mice were fed a high-fat diet for 6 weeks and then treated with: saline + normal diet and APS1 + normal diet (NDAPS1) for 3 weeks. NDAPS1 accelerated body weight loss and reduced caloric intake and fat accumulation. The fecal microbiome showed that accelerating weight loss by NDAPS1 resulted in restoring intestinal microbiota toward a pre-obese state, with alteration of specific changes in the obesity-associated bacteria. APS1 manipulated the gut microbiome's obesity-associated metabolites, followed by regulation of lipid metabolism, enhancement of energy expenditure and inhibition of appetite. The specific hepatic metabolites induced by the APS1-manipulated gut microbiome also contributed to the amelioration of hepatic steatosis. Our results highlighted a possible microbiome and metabolome that contributed to accelerating weight loss following treatment with a combination of APS1 and dieting and suggested that probiotics could serve as a potential therapy for modulating physiological function and downstream of the microbiota.
Collapse
Affiliation(s)
- Yung-Tsung Chen
- Institute of Biotechnology, National Taiwan University, Taipei City, 106, Taiwan
| | - Ning-Sun Yang
- Institute of Biotechnology, National Taiwan University, Taipei City, 106, Taiwan.,Agricultural Biotechnology Research Center, Academia Sinica, Taipei City, 115, Taiwan
| | - Yu-Chun Lin
- Department of Animal Science and Technology, National Taiwan University, Taipei City, 106, Taiwan.,Taiwan Livestock Research Institute, Council of Agriculture, Executive Yuan, Tainan City, 71246, Taiwan
| | - Shang-Tse Ho
- Department of Animal Science and Technology, National Taiwan University, Taipei City, 106, Taiwan
| | - Kuan-Yi Li
- Department of Animal Science and Technology, National Taiwan University, Taipei City, 106, Taiwan
| | - Jin-Seng Lin
- SynbioTech Incorporation, Kaohsiung City, 821, Taiwan
| | - Je-Ruei Liu
- Institute of Biotechnology, National Taiwan University, Taipei City, 106, Taiwan.,Department of Animal Science and Technology, National Taiwan University, Taipei City, 106, Taiwan
| | - Ming-Ju Chen
- Department of Animal Science and Technology, National Taiwan University, Taipei City, 106, Taiwan.
| |
Collapse
|
15
|
Liang J, Sun W. Elution-extrusion countercurrent chromatography separation of six pairs of isomeric iridoids fromCornus officinalisSieb. et Zucc. guided by ion current extraction in mass spectrometry. J Sep Sci 2018; 41:2279-2287. [DOI: 10.1002/jssc.201701516] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2017] [Revised: 01/28/2018] [Accepted: 02/06/2018] [Indexed: 11/05/2022]
Affiliation(s)
- Jinru Liang
- Biomedicine Key Laboratory of Shaanxi province; Northwest University; Xi'an China
- NICM Health Research Institute; Western Sydney University; Penrith Australia
| | - Wenji Sun
- Biomedicine Key Laboratory of Shaanxi province; Northwest University; Xi'an China
| |
Collapse
|
16
|
Liang J, Qiao B, Syed N, Sun W. A mass spectrometry guided elution-extrusion counter-current chromatography protocol for isolation of eighteen terpenoids from Fructus Corni and assessment of their anti-glioma activities. Microchem J 2018. [DOI: 10.1016/j.microc.2017.12.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
|
17
|
Ji H, Zeng F, Xu Y, Lu H, Zhang Z. KPIC2: An Effective Framework for Mass Spectrometry-Based Metabolomics Using Pure Ion Chromatograms. Anal Chem 2017; 89:7631-7640. [PMID: 28621925 DOI: 10.1021/acs.analchem.7b01547] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Distilling accurate quantitation information on metabolites from liquid chromatography coupled with mass spectrometry (LC-MS) data sets is crucial for further statistical analysis and biomarker identification. However, it is still challenging due to the complexity of biological systems. The concept of pure ion chromatograms (PICs) is an effective way of extracting meaningful ions, but few toolboxes provide a full processing workflow for LC-MS data sets based on PICs. In this study, an integrated framework, KPIC2, has been developed for metabolomics studies, which can detect pure ions accurately, align PICs across samples, group PICs to identify isotope and potential adducts, fill missing peaks and do multivariate pattern recognition. To evaluate its performance, MM48, metabolomics quantitation, and Soybean seeds data sets have been analyzed using KPIC2, XCMS, and MZmine2. KPIC2 can extract more true ions with fewer detecting features, have good quantification ability on a metabolomics quantitation data set, and achieve satisfactory classification on a soybean seeds data set through kernel-based OPLS-DA and random forest. It is implemented in R programming language, and the software, user guide, as well as example scripts and data sets are available as an open source package at https://github.com/hcji/KPIC2 .
Collapse
Affiliation(s)
- Hongchao Ji
- College of Chemistry and Chemical Engineering, Central South University , Changsha 410083, PR China
| | - Fanjuan Zeng
- College of Chemistry and Chemical Engineering, Central South University , Changsha 410083, PR China
| | - Yamei Xu
- College of Chemistry and Chemical Engineering, Central South University , Changsha 410083, PR China
| | - Hongmei Lu
- College of Chemistry and Chemical Engineering, Central South University , Changsha 410083, PR China
| | - Zhimin Zhang
- College of Chemistry and Chemical Engineering, Central South University , Changsha 410083, PR China
| |
Collapse
|
18
|
Borman RP, Wang Y, Nguyen MD, Ganesana M, Lee ST, Venton BJ. Automated Algorithm for Detection of Transient Adenosine Release. ACS Chem Neurosci 2017; 8:386-393. [PMID: 28196418 DOI: 10.1021/acschemneuro.6b00262] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Spontaneous adenosine release events have been discovered in the brain that last only a few seconds. The identification of these adenosine events from fast-scan cyclic voltammetry (FSCV) data is difficult due to the random nature of adenosine release. In this study, we develop an algorithm that automatically identifies and characterizes adenosine transient features, including event time, concentration, and duration. Automating the data analysis reduces analysis time from 10 to 18 h to about 40 min per experiment. The algorithm identifies adenosine based on its two oxidation peaks, the time delay between them, and their current vs time peak ratios. In order to validate the program, four data sets from three independent researchers were analyzed by the algorithm and then compared to manual identification by an analyst. The algorithm resulted in 10 ± 4% false negatives and 9 ± 3% false positives. The specificity of the algorithm was verified by comparing calibration data for adenosine triphosphate (ATP), histamine, hydrogen peroxide, and pH changes and these analytes were not identified as adenosine. Stimulated histamine release in vivo was also not identified as adenosine. The code is modular in design and could be easily adjusted to detect features of spontaneous dopamine or other neurochemical transients in FSCV data.
Collapse
Affiliation(s)
- Ryan P. Borman
- Department of Chemistry, University of Virginia, Charlottesville, Virginia 22904, United States
| | - Ying Wang
- Department of Chemistry, University of Virginia, Charlottesville, Virginia 22904, United States
| | - Michael D. Nguyen
- Department of Chemistry, University of Virginia, Charlottesville, Virginia 22904, United States
| | | | - Scott T. Lee
- Department of Chemistry, University of Virginia, Charlottesville, Virginia 22904, United States
| | - B. Jill Venton
- Department of Chemistry, University of Virginia, Charlottesville, Virginia 22904, United States
| |
Collapse
|
19
|
Chen XP, Fan RJ, Zhang F, Li ZQ, Xu B, Guo YL. Chromatographic peak reconstruction algorithm to improve qualitative and quantitative analysis of trace pesticide residues. RAPID COMMUNICATIONS IN MASS SPECTROMETRY : RCM 2016; 30:2655-2663. [PMID: 27723938 DOI: 10.1002/rcm.7762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2016] [Revised: 09/19/2016] [Accepted: 10/05/2016] [Indexed: 06/06/2023]
Abstract
RATIONALE In order to improve analysis of analytes in trace amounts in a complex matrix, we developed a novel post-processing method, named Chromatographic Peak Reconstruction (CPR), to process the recorded data from gas chromatography/time-of-flight mass spectrometry (GC/TOFMS). METHODS For a trace ion, the relative deviation (δ) between the adjacent scanned mass-to-charge ratios (m/z) was found to be inversely proportional to its MS peak intensity. Based on this relationship, the thresholds of δ value within the specified intensity segments were estimated by the CPR and used to screen out the suspicious scan-points in the extracted ion chromatographic (EIC) peak. Then, the intensities of these suspicious scan-points were calibrated to reconstruct a new EIC peak. RESULTS In the qualitative analysis of 118 pesticides, 107 out of the test pesticides can be confirmed. The corrected response ratios of the qualitative ion (q) over the quantitative ion (Q), q/Q, became closer to their references. In the quantitative analysis of 10 test pesticides at 5 ppb, the relative errors of the calculated concentrations after using the CPR were below ±1.55%, down from ±2.29% without using the CPR. CONCLUSIONS The developed CPR showed great potential in the analysis of trace analytes in complex matrices. It was proved to be a helpful data processing method for the monitoring of trace pesticide residues. Copyright © 2016 John Wiley & Sons, Ltd.
Collapse
Affiliation(s)
- Xiu-Ping Chen
- Department of Chemistry, Innovative Drug Research Center, Shanghai University, 99 Shangda Road, Shanghai, 200444, China
- State Key Laboratory of Organometallic Chemistry and National Center for Organic Mass Spectrometry in Shanghai, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai, 200032, China
| | - Ruo-Jing Fan
- State Key Laboratory of Organometallic Chemistry and National Center for Organic Mass Spectrometry in Shanghai, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai, 200032, China
| | - Fang Zhang
- State Key Laboratory of Organometallic Chemistry and National Center for Organic Mass Spectrometry in Shanghai, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai, 200032, China
| | - Zhong-Quan Li
- State Key Laboratory of Organometallic Chemistry and National Center for Organic Mass Spectrometry in Shanghai, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai, 200032, China
| | - Bin Xu
- Department of Chemistry, Innovative Drug Research Center, Shanghai University, 99 Shangda Road, Shanghai, 200444, China
| | - Yin-Long Guo
- State Key Laboratory of Organometallic Chemistry and National Center for Organic Mass Spectrometry in Shanghai, Shanghai Institute of Organic Chemistry, Chinese Academy of Sciences, 345 Lingling Road, Shanghai, 200032, China
| |
Collapse
|
20
|
Huang YT, Lin YW, Chiu HM, Chiang BH. Curcumin Induces Apoptosis of Colorectal Cancer Stem Cells by Coupling with CD44 Marker. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2016; 64:2247-2253. [PMID: 26906122 DOI: 10.1021/acs.jafc.5b05649] [Citation(s) in RCA: 41] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
This study investigated the effect of curcumin on colorectal cancer stem cells (CCSCs) and its possible mechanism. Comparison of the metabolic profiles of human adenomatous polyp (N = 61) and colorectal cancer (CRC) (N = 57) tissue found statistically significant differences (p < 0.05) in their composition of adenosine monophosphate (AMP), adenine, 5'-methythioadenosine, 3-hydroxybutyric acid, prostaglandin E2, threonine, and glutamine. Our cell culture model study found that curcumin treatment (50 μM for 48 h) did indeed increase apoptosis of CRC cells as well as of CCSCs, but at a significant level only in CD44(+) cells. Further metabolic profile studies of the CRC, CD44(+), and CD44(-) cells indicated that curcumin treatment increased glyceraldehyde and hydroxypropionic acid in CD44(-) cells but decreased glutamine content in both curcumin-treated CRC and CD44(+) cells. Based on our comparison of the metabolic profiles of human tissues and cancer cells, we suggest that curcumin might couple with CD44 and that curcumin-CD44(+) coupling at the cell membrane might have some blocking effect on the transport of glutamine into the cells, thus decreasing the glutamine content in the CD44(+) cells and inducing apoptosis.
Collapse
Affiliation(s)
- Yu-Ting Huang
- Institute of Food Science and Technology, College of Bio-resources and Agriculture, National Taiwan University , Taipei 10617, Taiwan
| | - Yu-Wei Lin
- Institute of Food Science and Technology, College of Bio-resources and Agriculture, National Taiwan University , Taipei 10617, Taiwan
| | - Han-Mo Chiu
- Department of Internal Medicine, National Taiwan University Hospital, College of Medicine, National Taiwan University , Taipei 10051, Taiwan
| | - Been-Huang Chiang
- Institute of Food Science and Technology, College of Bio-resources and Agriculture, National Taiwan University , Taipei 10617, Taiwan
| |
Collapse
|
21
|
Lai YS, Chen WC, Kuo TC, Ho CT, Kuo CH, Tseng YJ, Lu KH, Lin SH, Panyod S, Sheen LY. Mass-Spectrometry-Based Serum Metabolomics of a C57BL/6J Mouse Model of High-Fat-Diet-Induced Non-alcoholic Fatty Liver Disease Development. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2015; 63:7873-7884. [PMID: 26262841 DOI: 10.1021/acs.jafc.5b02830] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Obesity, dyslipidemia, insulin resistance, oxidative stress, and inflammation are key clinical risk factors for the progression of non-alcoholic fatty liver disease (NAFLD). Currently, there is no comprehensive metabolic profile of a well-established animal model that effectively mimics the etiology and pathogenesis of NAFLD in humans. Here, we report the pathophysiological and metabolomic changes associated with NAFLD development in a C57BL/6J mouse model in which NAFLD was induced by feeding a high-fat diet (HFD) for 4, 8, 12, and 16 weeks. Serum metabolomic analysis was conducted using ultrahigh-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UHPLC-QTOF-MS) and gas chromatography-mass spectrometry (GC-MS) to establish a metabolomic profile. Analysis of the metabolomic profile in combination with principal component analysis revealed marked differences in metabolites between the control and HFD group depending upon NAFLD severity. A total of 30 potential biomarkers were strongly associated with the development of NAFLD. Among these, 11 metabolites were mainly related to carbohydrate metabolism, hepatic biotransformation, collagen synthesis, and gut microbial metabolism, which are characteristics of obesity, as well as significantly increased serum glucose, total cholesterol, and hepatic triglyceride levels during the onset of NAFLD (4 weeks). At 8 weeks, 5 additional metabolites that are chiefly involved in perturbation of lipid metabolism and insulin secretion were found to be associated with hyperinsulinemia, hyperlipidemia, and hepatic steatosis in the mid-term of NAFLD progression. At the end of 12 and 16 weeks, 14 additional metabolites were predominantly correlated to abnormal bile acid synthesis, oxidative stress, and inflammation, representing hepatic inflammatory infiltration during NAFLD development. These results provide potential biomarkers for early risk assessment of NAFLD and further insights into NAFLD development.
Collapse
Affiliation(s)
| | | | | | - Chi-Tang Ho
- Department of Food Science, Rutgers University , New Brunswick, New Jersey 08901, United States
| | | | | | | | | | | | | |
Collapse
|
22
|
The metabolome profiling and pathway analysis in metabolic healthy and abnormal obesity. Int J Obes (Lond) 2015; 39:1241-8. [PMID: 25907313 DOI: 10.1038/ijo.2015.65] [Citation(s) in RCA: 93] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/23/2014] [Revised: 03/23/2015] [Accepted: 04/12/2015] [Indexed: 12/20/2022]
Abstract
OBJECTIVES Mechanisms of the development of abnormal metabolic phenotypes among obese population are not yet clear. In this study, we aimed to screen metabolomes of both healthy and subjects with abnormal obesity to identify potential metabolic pathways that may regulate the different metabolic characteristics of obesity. METHODS We recruited subjects with body mass index (BMI) over 25 from the weight-loss clinic of a central hospital in Taiwan. Metabolic healthy obesity (MHO) is defined as without having any form of hyperglycemia, hypertension and dyslipidemia, while metabolic abnormal obesity (MAO) is defined as having one or more abnormal metabolic indexes. Serum-based metabolomic profiling using both liquid chromatography-mass spectrometry and gas chromatography-mass spectrometry of 34 MHO and MAO individuals with matching age, sex and BMI was performed. Conditional logistic regression and partial least squares discriminant analysis were applied to identify significant metabolites between the two groups. Pathway enrichment and topology analyses were conducted to evaluate the regulated pathways. RESULTS A differential metabolite panel was identified to be significantly differed in MHO and MAO groups, including L-kynurenine, glycerophosphocholine (GPC), glycerol 1-phosphate, glycolic acid, tagatose, methyl palmitate and uric acid. Moreover, several metabolic pathways were relevant in distinguishing MHO from MAO groups, including fatty acid biosynthesis, phenylalanine metabolism, propanoate metabolism, and valine, leucine and isoleucine degradation. CONCLUSION Different metabolomic profiles and metabolic pathways are important for distinguishing between MHO and MAO groups. We have identified and discussed the key metabolites and pathways that may prove important in the regulation of metabolic traits among the obese, which could provide useful clues to study the underlying mechanisms of the development of abnormal metabolic phenotypes.
Collapse
|
23
|
Wang SY, Kuo CH, Tseng YJ. Ion Trace Detection Algorithm to Extract Pure Ion Chromatograms to Improve Untargeted Peak Detection Quality for Liquid Chromatography/Time-of-Flight Mass Spectrometry-Based Metabolomics Data. Anal Chem 2015; 87:3048-55. [DOI: 10.1021/ac504711d] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Affiliation(s)
- San-Yuan Wang
- Department of Computer Science
and Information Engineering, ‡The Metabolomics
Core Laboratory, Center of Genomic Medicine, §School of Pharmacy, College of Medicine, ∥Department of Pharmacy,
National Taiwan University Hospital, ⊥Graduate Institute of Biomedical
Electronics and Bioinformatics, #Drug Research Center, College of Medicine, National Taiwan University, 106 Taipei, Taiwan
| | - Ching-Hua Kuo
- Department of Computer Science
and Information Engineering, ‡The Metabolomics
Core Laboratory, Center of Genomic Medicine, §School of Pharmacy, College of Medicine, ∥Department of Pharmacy,
National Taiwan University Hospital, ⊥Graduate Institute of Biomedical
Electronics and Bioinformatics, #Drug Research Center, College of Medicine, National Taiwan University, 106 Taipei, Taiwan
| | - Yufeng J. Tseng
- Department of Computer Science
and Information Engineering, ‡The Metabolomics
Core Laboratory, Center of Genomic Medicine, §School of Pharmacy, College of Medicine, ∥Department of Pharmacy,
National Taiwan University Hospital, ⊥Graduate Institute of Biomedical
Electronics and Bioinformatics, #Drug Research Center, College of Medicine, National Taiwan University, 106 Taipei, Taiwan
| |
Collapse
|
24
|
Smolinska A, Hauschild AC, Fijten RRR, Dallinga JW, Baumbach J, van Schooten FJ. Current breathomics--a review on data pre-processing techniques and machine learning in metabolomics breath analysis. J Breath Res 2014; 8:027105. [PMID: 24713999 DOI: 10.1088/1752-7155/8/2/027105] [Citation(s) in RCA: 130] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
We define breathomics as the metabolomics study of exhaled air. It is a strongly emerging metabolomics research field that mainly focuses on health-related volatile organic compounds (VOCs). Since the amount of these compounds varies with health status, breathomics holds great promise to deliver non-invasive diagnostic tools. Thus, the main aim of breathomics is to find patterns of VOCs related to abnormal (for instance inflammatory) metabolic processes occurring in the human body. Recently, analytical methods for measuring VOCs in exhaled air with high resolution and high throughput have been extensively developed. Yet, the application of machine learning methods for fingerprinting VOC profiles in the breathomics is still in its infancy. Therefore, in this paper, we describe the current state of the art in data pre-processing and multivariate analysis of breathomics data. We start with the detailed pre-processing pipelines for breathomics data obtained from gas-chromatography mass spectrometry and an ion-mobility spectrometer coupled to multi-capillary columns. The outcome of data pre-processing is a matrix containing the relative abundances of a set of VOCs for a group of patients under different conditions (e.g. disease stage, treatment). Independently of the utilized analytical method, the most important question, 'which VOCs are discriminatory?', remains the same. Answers can be given by several modern machine learning techniques (multivariate statistics) and, therefore, are the focus of this paper. We demonstrate the advantages as well the drawbacks of such techniques. We aim to help the community to understand how to profit from a particular method. In parallel, we hope to make the community aware of the existing data fusion methods, as yet unresearched in breathomics.
Collapse
Affiliation(s)
- A Smolinska
- Department of Toxicology, Nutrition and Toxicology Research Institute Maastricht (NUTRIM), Maastricht University, PO Box 616, 6200 MD Maastricht, the Netherlands. Top Institute Food and Nutrition, Wageningen, the Netherlands
| | | | | | | | | | | |
Collapse
|
25
|
Dallinga JW, Smolinska A, van Schooten FJ. Analysis of volatile organic compounds in exhaled breath by gas chromatography-mass spectrometry combined with chemometric analysis. Methods Mol Biol 2014; 1198:251-263. [PMID: 25270934 DOI: 10.1007/978-1-4939-1258-2_16] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
Analysis of exhaled breath samples reveals the presence of many volatile organic compounds (VOCs). The VOC composition of the breath, the so-called breath profile, contains a variety of information including the health status and condition of the organism that produced the sample. Therefore, breath profiling can be used in diagnosing and monitoring disease and other characteristics of the organism, such as phenotype, diet, and exercise. Among various techniques available for breath analysis, GC-MS provides the most extensive information with regard to the qualitative and quantitative presence of VOCs in breath.
Collapse
Affiliation(s)
- Jan W Dallinga
- Department of Toxicology, Maastricht University, 616, Maastricht, MD, 6200, The Netherlands
| | | | | |
Collapse
|