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Nandy D, Craig SJC, Cai J, Tian Y, Paul IM, Savage JS, Marini ME, Hohman EE, Reimherr ML, Patterson AD, Makova KD, Chiaromonte F. Metabolomic profiling of stool of two-year old children from the INSIGHT study reveals links between butyrate and child weight outcomes. Pediatr Obes 2022; 17:e12833. [PMID: 34327846 PMCID: PMC8647636 DOI: 10.1111/ijpo.12833] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 05/11/2021] [Accepted: 06/09/2021] [Indexed: 12/19/2022]
Abstract
BACKGROUND Metabolomic analysis is commonly used to understand the biological underpinning of diseases such as obesity. However, our knowledge of gut metabolites related to weight outcomes in young children is currently limited. OBJECTIVES To (1) explore the relationships between metabolites and child weight outcomes, (2) determine the potential effect of covariates (e.g., child's diet, maternal health/habits during pregnancy, etc.) in the relationship between metabolites and child weight outcomes, and (3) explore the relationship between selected gut metabolites and gut microbiota abundance. METHODS Using 1 H-NMR, we quantified 30 metabolites from stool samples of 170 two-year-old children. To identify metabolites and covariates associated with children's weight outcomes (BMI [weight/height2 ], BMI z-score [BMI adjusted for age and sex], and growth index [weight/height]), we analysed the 1 H-NMR data, along with 20 covariates recorded on children and mothers, using LASSO and best subset selection regression techniques. Previously characterized microbiota community information from the same stool samples was used to determine associations between selected gut metabolites and gut microbiota. RESULTS At age 2 years, stool butyrate concentration had a significant positive association with child BMI (p-value = 3.58 × 10-4 ), BMI z-score (p-value = 3.47 × 10-4 ), and growth index (p-value = 7.73 × 10-4 ). Covariates such as maternal smoking during pregnancy are important to consider. Butyrate concentration was positively associated with the abundance of the bacterial genus Faecalibacterium (p-value = 9.61 × 10-3 ). CONCLUSIONS Stool butyrate concentration is positively associated with increased child weight outcomes and should be investigated further as a factor affecting childhood obesity.
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Affiliation(s)
- Debmalya Nandy
- Department of StatisticsPenn State UniversityUniversity ParkPAUSA,Present address:
Department of Biostatistics and Informatics, Colorado School of Public HealthUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| | - Sarah J. C. Craig
- Department of BiologyPenn State UniversityUniversity ParkPAUSA,Center for Medical GenomicsPenn State UniversityUniversity ParkPAUSA
| | - Jingwei Cai
- Department of Molecular ToxicologyPenn State UniversityUniversity ParkPAUSA,Present address:
Department of Drug Metabolism and PharmacokineticsGenentech Inc.South San FranciscoCaliforniaUSA
| | - Yuan Tian
- Department of Molecular ToxicologyPenn State UniversityUniversity ParkPAUSA
| | - Ian M. Paul
- Center for Medical GenomicsPenn State UniversityUniversity ParkPAUSA,Department of PediatricsPenn State College of MedicineHersheyPAUSA
| | - Jennifer S. Savage
- Department of Nutritional SciencesPenn State UniversityUniversity ParkPAUSA,Center for Childhood Obesity ResearchPenn State UniversityUniversity ParkPAUSA
| | - Michele E. Marini
- Center for Childhood Obesity ResearchPenn State UniversityUniversity ParkPAUSA
| | - Emily E. Hohman
- Center for Childhood Obesity ResearchPenn State UniversityUniversity ParkPAUSA
| | - Matthew L. Reimherr
- Department of StatisticsPenn State UniversityUniversity ParkPAUSA,Center for Medical GenomicsPenn State UniversityUniversity ParkPAUSA
| | - Andrew D. Patterson
- Department of Molecular ToxicologyPenn State UniversityUniversity ParkPAUSA,Department of Biochemistry & Molecular BiologyPenn State UniversityUniversity ParkPAUSA
| | - Kateryna D. Makova
- Department of BiologyPenn State UniversityUniversity ParkPAUSA,Center for Medical GenomicsPenn State UniversityUniversity ParkPAUSA
| | - Francesca Chiaromonte
- Department of StatisticsPenn State UniversityUniversity ParkPAUSA,Center for Medical GenomicsPenn State UniversityUniversity ParkPAUSA,Institute of EconomicsEMbeDS, Sant'Anna School of Advanced StudiesPisaItaly
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Sun Y, Kong L, Zhang AH, Han Y, Sun H, Yan GL, Wang XJ. A Hypothesis From Metabolomics Analysis of Diabetic Retinopathy: Arginine-Creatine Metabolic Pathway May Be a New Treatment Strategy for Diabetic Retinopathy. Front Endocrinol (Lausanne) 2022; 13:858012. [PMID: 35399942 PMCID: PMC8987289 DOI: 10.3389/fendo.2022.858012] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Accepted: 03/01/2022] [Indexed: 12/31/2022] Open
Abstract
Diabetic retinopathy is one of the serious complications of diabetes, which the leading causes of blindness worldwide, and its irreversibility renders the existing treatment methods unsatisfactory. Early detection and timely intervention can effectively reduce the damage caused by diabetic retinopathy. Metabolomics is a branch of systems biology and a powerful tool for studying pathophysiological processes, which can help identify the characteristic metabolic changes marking the progression of diabetic retinopathy, discover potential biomarkers to inform clinical diagnosis and treatment. This review provides an update on the known metabolomics biomarkers of diabetic retinopathy. Through comprehensive analysis of biomarkers, we found that the arginine biosynthesis is closely related to diabetic retinopathy. Meanwhile, creatine, a metabolite with arginine as a precursor, has attracted our attention due to its important correlation with diabetic retinopathy. We discuss the possibility of the arginine-creatine metabolic pathway as a therapeutic strategy for diabetic retinopathy.
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Affiliation(s)
- Ye Sun
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ling Kong
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ai-Hua Zhang
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Ying Han
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Hui Sun
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Guang-Li Yan
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
| | - Xi-Jun Wang
- National Chinmedomics Research Center and National Traditional Chinese Medicine (TCM) Key Laboratory of Serum Pharmacochemistry, Department of Pharmaceutical Analysis, Heilongjiang University of Chinese Medicine, Harbin, China
- State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Macau, Macau SAR, China
- National Engineering Laboratory for the Development of Southwestern Endangered Medicinal Materials, Guangxi Botanical Garden of Medicinal Plant, Nanning, China
- *Correspondence: Xi-Jun Wang,
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Du Y, Fan P, Zou L, Jiang Y, Gu X, Yu J, Zhang C. Serum Metabolomics Study of Papillary Thyroid Carcinoma Based on HPLC-Q-TOF-MS/MS. Front Cell Dev Biol 2021; 9:593510. [PMID: 33598460 PMCID: PMC7882692 DOI: 10.3389/fcell.2021.593510] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Accepted: 01/08/2021] [Indexed: 12/24/2022] Open
Abstract
This study examined metabolite profile differences between serum samples of thyroid papillary carcinoma (PTC) patients and healthy controls, aiming to identify candidate biomarkers and pathogenesis pathways in this cancer type. Serum samples were collected from PTC patients (n = 80) and healthy controls (n = 80). Using principal component analysis (PCA), partial least squares discrimination analysis(PLS-DA), orthogonal partial least square discriminant analysis (OPLS-DA), t-tests, and the volcano plot, a model of abnormal metabolic pathways in PTC was constructed. PCA, PLS-DA, and OPLS-DA analysis revealed differences in serum metabolic profiles between the PTC and control group. OPLS-Loading plot analysis, combined with Variable importance in the projection (VIP)>1, Fold change (FC) > 1.5, and p < 0.05 were used to screen 64 candidate metabolites. Among them, 22 metabolites, including proline betaine, taurocholic acid, L-phenylalanine, retinyl beta-glucuronide, alpha-tocotrienol, and threonine acid were upregulated in the PTC group; meanwhile, L-tyrosine, L-tryptophan, 2-arachidonylglycerol, citric acid, and other 42 metabolites were downregulated in this group. There were eight abnormal metabolic pathways related to the differential metabolites, which may be involved in the pathophysiology of PTC. Six metabolites yielded an area under the receiver operating curve of >0.75, specifically, 3-hydroxy-cis-5-tetradecenoylcarnitine, aspartylphenylalanine, l-kynurenine, methylmalonic acid, phenylalanylphenylalanine, and l-glutamic acid. The Warburg effect was observed in PTC. The levels of 3-hydroxy-cis-5-tetradecenoylcarnitine, aspartylphenylalanine, l-kynurenine, methylmalonic acid, phenylalanine, and L-glutamic acid may help distinguish PTC patients from healthy controls. Aspartic acid metabolism, glutamic acid metabolism, urea cycle, and tricarboxylic acid cycle are involved in the mechanism of PTC.
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Affiliation(s)
- Yang Du
- Department of Breast and Thyroid Surgery, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China
| | - Peizhi Fan
- Department of Breast and Thyroid Surgery, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China
| | - Lianhong Zou
- Hunan Provincial Key Laboratory of Emergency and Critical Care Metabonomics, Institute of Emergency Medicine, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China
| | - Yu Jiang
- Hunan Provincial Key Laboratory of Emergency and Critical Care Metabonomics, Institute of Emergency Medicine, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China
| | - Xiaowen Gu
- Department of Breast and Thyroid Surgery, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China
| | - Jie Yu
- Department of Breast and Thyroid Surgery, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China
| | - Chaojie Zhang
- Department of Breast and Thyroid Surgery, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, China
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Manier SK, Wagmann L, Flockerzi V, Meyer MR. Toxicometabolomics of the new psychoactive substances α-PBP and α-PEP studied in HepaRG cell incubates by means of untargeted metabolomics revealed unexpected amino acid adducts. Arch Toxicol 2020; 94:2047-2059. [PMID: 32313995 PMCID: PMC7303098 DOI: 10.1007/s00204-020-02742-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Accepted: 04/06/2020] [Indexed: 01/06/2023]
Abstract
Toxicometabolomics, essentially applying metabolomics to toxicology of endogenous compounds such as drugs of abuse or new psychoactive substances (NPS), can be investigated by using different in vitro models and dedicated metabolomics techniques to enhance the number of relevant findings. The present study aimed to study the toxicometabolomics of the two NPS α-pyrrolidinobutiophenone (1-phenyl-2-(pyrrolidin-1-yl)butan-1-one, α-PBP) and α-pyrrolidinoheptaphenone (1-phenyl-2-(pyrrolidin-1-yl)heptan-1-one, α-PEP, PV8) in HepaRG cell line incubates. Evaluation was performed using reversed-phase and normal-phase liquid chromatography coupled with high-resolution mass spectrometry in positive and negative ionization mode, respectively, to analyze cells and cell media. Statistical evaluation was performed using one-way ANOVA, principal component discriminant function analysis, as well as hierarchical clustering. In general, the analysis of cells did not mainly reveal any features, but the parent compounds of the drugs of abuse. For α-PBP an increase in N-methylnicotinamide was found, which may indicate hepatotoxic potential of the substance. After analysis of cell media, significant features led to the identification of several metabolites of both compounds. Amino acid adducts with glycine and alanine were found, and these have not been described in any study before and are likely to appear in vivo. Additionally, significant changes in the metabolism of cholesterol were revealed after incubation with α-PEP. In summary, the application of metabolomics techniques after HepaRG cells exposure to NPS did not lead to an increased number of identified drug metabolites compared to previously published studies, but gave a wider perspective on the physiological effect of the investigated compounds on human liver cells.
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Affiliation(s)
- Sascha K Manier
- Department of Experimental and Clinical Toxicology, Institute of Experimental and Clinical Pharmacology and Toxicology, Center for Molecular Signaling (PZMS), Saarland University, 66421, Homburg, Germany
| | - Lea Wagmann
- Department of Experimental and Clinical Toxicology, Institute of Experimental and Clinical Pharmacology and Toxicology, Center for Molecular Signaling (PZMS), Saarland University, 66421, Homburg, Germany
| | - Veit Flockerzi
- Department of Experimental and Clinical Pharmacology, Institute of Experimental and Clinical Pharmacology and Toxicology, Center for Molecular Signaling (PZMS), Saarland University, 66421, Homburg, Germany
| | - Markus R Meyer
- Department of Experimental and Clinical Toxicology, Institute of Experimental and Clinical Pharmacology and Toxicology, Center for Molecular Signaling (PZMS), Saarland University, 66421, Homburg, Germany.
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Manier SK, Meyer MR. Impact of the used solvent on the reconstitution efficiency of evaporated biosamples for untargeted metabolomics studies. Metabolomics 2020; 16:34. [PMID: 32124055 PMCID: PMC7052028 DOI: 10.1007/s11306-019-1631-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 12/31/2019] [Indexed: 11/28/2022]
Abstract
INTRODUCTION Untargeted metabolomics intends to objectively analyze a wide variety of compounds. Their diverse physicochemical properties make it difficult to choose an appropriate reconstitution solvent after sample evaporation without influencing the chromatography or hamper column sorbent integrity. OBJECTIVES The study aimed to identify the most appropriate reconstitution solvent for blood plasma samples in terms of feature recovery, four endogenous compounds, and one selected internal standard. METHODS We investigated several reconstitution solvent mixtures containing acetonitrile and methanol to resolve human plasma extract and evaluated them concerning the peak areas of tryptophan-d5, glucose, creatinine, palmitic acid, and the phophatidylcholine PC(P-16:0/P-16:0), as well as the total feature count RESULTS: Results indicated that acetonitrile containing 30% methanol was best suited to match all tested criteria at least for human blood plasma samples. CONCLUSION Despite identifying the mixture of acetonitrile and methanol being suitable as solvent for human blood plasma extracts, we recommend to systematically test for an appropriate reconstitution solvent for each analyzed biomatrix.
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Affiliation(s)
- Sascha K Manier
- Department of Experimental and Clinical Toxicology, Center for Molecular Signaling (PZMS), Institute of Experimental and Clinical Pharmacology and Toxicology, Saarland University, 66421, Homburg, Germany
| | - Markus R Meyer
- Department of Experimental and Clinical Toxicology, Center for Molecular Signaling (PZMS), Institute of Experimental and Clinical Pharmacology and Toxicology, Saarland University, 66421, Homburg, Germany.
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Kim MH, Ha IJ, Kim E, Kim K. Integrated targeted serum metabolomic profile and its association with gender, age, disease severity, and pattern identification in acne. PLoS One 2020; 15:e0228074. [PMID: 31951642 PMCID: PMC6968861 DOI: 10.1371/journal.pone.0228074] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 01/07/2020] [Indexed: 11/24/2022] Open
Abstract
Background Westernized diet and nutritional metabolism are important in acne pathogenesis, especially in adult patients. However, clinical and basic data are lacking. Pattern identification (PI) is a tool that results in a diagnostic conclusion based on a cluster of concurrent symptoms and signs in traditional medicine. Acne can be classified by PI. However, whether the metabolomic profile differs according to the PI of acne is unknown. Metabolomic data would help clarify the pathogenesis of acne. Methods We conducted a cross-sectional study involving 40 healthy controls and 60 subjects with acne. We evaluated androgens, serum lipids, essential amino acids, nonessential amino acids, other amino acids, and pro-inflammatory cytokines of all subjects and compared the metabolomic profiles between acne subjects and healthy controls, and in subgroups according to gender, age, severity, and PI. Results Dehydroepiandrosterone sulfate and serum fatty acids were significantly higher in female subjects, adolescents, and those with disharmony of the thoroughfare and conception vessels. The total essential and nonessential amino acids were significantly lower in the overall, female, adult, severe, and phlegm-stasis group. The latter group exhibited elevated serum levels of interleukin-1β and -6. Conclusions This is the first study to investigate serum lipids, amino acids, and cytokines in subjects with acne. We analyzed the differences between metabolomic profiles to determine the diagnostic value of PI. Prospective studies with more patients are needed to confirm the characteristics of each PI and lipidomic data will enrich knowledge concerning lipid mechanism.
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Affiliation(s)
- Min Hee Kim
- Department of Ophthalmology & Otolaryngology & Dermatology, College of Korean Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - In Jin Ha
- Korean Medicine Clinical Trial Center, Kyung Hee University Korean Medicine Hospital, Seoul, Republic of Korea
| | - Eunok Kim
- Korean Medicine Clinical Trial Center, Kyung Hee University Korean Medicine Hospital, Seoul, Republic of Korea
- College of Korean Medicine, Kyung Hee University, Seoul, Republic of Korea
| | - Kyuseok Kim
- Department of Ophthalmology & Otolaryngology & Dermatology, College of Korean Medicine, Kyung Hee University, Seoul, Republic of Korea
- Korean Medicine Clinical Trial Center, Kyung Hee University Korean Medicine Hospital, Seoul, Republic of Korea
- * E-mail:
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Untargeted metabolomics by high resolution mass spectrometry coupled to normal and reversed phase liquid chromatography as a tool to study the in vitro biotransformation of new psychoactive substances. Sci Rep 2019; 9:2741. [PMID: 30808896 PMCID: PMC6391464 DOI: 10.1038/s41598-019-39235-w] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Accepted: 01/21/2019] [Indexed: 12/20/2022] Open
Abstract
In 2016, several synthetic cathinones were seized by the State Bureau of Criminal Investigation Bavaria in Germany. Due to their previous appearances in other countries their metabolism was already investigated in human urine as well as different in vitro models. These investigations were conducted using ordinary metabolism studies for drugs of abuse by using general knowledge about drug metabolism and visual comparison of mass spectra. The present study aimed to use untargeted metabolomics to support and improve those methods that highly depend on the investigators experience. Incubations were conducted using pooled human liver microsomes (pHLM) and the two cathinones 1-phenyl-2-(1-pyrrolidinyl)-1-butanone and 1-phenyl-2-(1-pyrrolidinyl)-1-heptanone. Samples were analyzed by LC-HRMS/MS using a metabolomics workflow consisting of a reversed phase or normal phase separation followed by electrospray ionization and full scan in positive or negative mode. LC-MS data was afterwards statistically evaluated using principal component analysis, t-distributed stochastic neighborhood embedding, and hierarchical clustering. Significant features were then identified using MS/MS. The workflow revealed 24 significant features after 1-phenyl-2-(1-pyrrolidinyl)-1-butanone and 39 after 1-phenyl-2-(1-pyrrolidinyl)-1-heptanone incubation, consisting of adducts, artifacts, isomers, and metabolites. The applied untargeted metabolomics strategy was able to find almost all of the metabolites that were previously described for 1-phenyl-2-(1-pyrrolidinyl)-1-butanone in literature as well as three additional metabolites. Concerning 1-phenyl-2-(1-pyrrolidinyl)-1-heptanone biotransformation in pHLM, merely four metabolites described in primary human hepatocytes and human urine were not found. This study revealed that untargeted metabolomics workflows are well suited to support biotransformation studies at least of the investigated compounds in pHLM.
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Manier SK, Keller A, Meyer MR. Automated optimization of XCMS parameters for improved peak picking of liquid chromatography-mass spectrometry data using the coefficient of variation and parameter sweeping for untargeted metabolomics. Drug Test Anal 2018; 11:752-761. [PMID: 30479047 DOI: 10.1002/dta.2552] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Revised: 11/15/2018] [Accepted: 11/22/2018] [Indexed: 01/25/2023]
Abstract
Accurate peak picking and further processing is a current challenge in the analysis of untargeted metabolomics using liquid chromatography-mass spectrometry (LC-MS) data. The optimization of these processes is crucial to obtain proper results. This study investigated and optimized the detection of peaks by XCMS, a widely used R package for peak picking and processing of high-resolution LC-MS metabolomics data by their coefficient of variation using neat standard solutions of drug like compounds. The obtained results were additionally verified by using fortified pooled plasma samples. Settings of the mass spectrometer were optimized by recommendations in literature to enable a reliable detection of the investigated analytes. XCMS parameters were evaluated using a comprehensive parameter sweeping approach. The optimization steps were statistically evaluated and further visualized after principal component analysis (PCA). Concerning the lower concentrated solution in methanol samples, the optimization of both mass spectrometer and XCMS parameters improved the median coefficient of variation from 24% to 7%, retention time fluctuation from 9.3 seconds to 0.54 seconds, and fluctuation of the mass to charge ratio (m/z) from m/z 0.00095 to m/z 0.00028. The number of parent compounds and their related species annotated by CAMERA increased from 88 to 113 while the total amount of features decreased from 3282 to 428. Optimized MS settings such as increased resolution led to a higher specificity of peak picking. PCA supported these findings by showing the best clustering of samples after optimization of both mass spectrometer and XCMS parameters. The results implied that peak picking needs to be individually adapted for the experimental set up. Reducing unwanted variation in the data set was most successful after combining high resolving power with strict peak picking settings.
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Affiliation(s)
- Sascha K Manier
- Department of Experimental and Clinical Toxicology, Institute of Experimental and Clinical Pharmacology and Toxicology, Saarland University, Center for Molecular Signaling (PZMS), 66421, Homburg, Germany
| | - Andreas Keller
- Chair of Clinical Bioinformatics, Saarland University, Saarbruecken, Germany
| | - Markus R Meyer
- Department of Experimental and Clinical Toxicology, Institute of Experimental and Clinical Pharmacology and Toxicology, Saarland University, Center for Molecular Signaling (PZMS), 66421, Homburg, Germany
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