METLIN: A Technology Platform for Identifying Knowns and Unknowns

Guijas, Carlos; Montenegro-Burke, J. Rafael; Domingo-Almenara, Xavier; Palermo, Amelia; Warth, Benedikt; Hermann, Gerrit; Koellensperger, Gunda; Huan, Tao; Uritboonthai, Winnie; Aisporna, Aries E.; Wolan, Dennis W.; Spilker, Mary E.; Benton, H. Paul; Siuzdak, Gary

doi:10.1021/acs.analchem.7b04424

Cited by 760 publications

(595 citation statements)

References 47 publications

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“…For unknown metabolites, MS/MS fragmentation was performed by LC‐MS/MS by rerunning samples on a more sensitive mass detector (VION, Waters) using product ion scans with three N 2 collision‐induced dissociation energies (14, 28, and 42 V). Structure elucidation was performed by using existing databases, including the Human Metabolome Database (HMDB), Metlin, CMF‐ID, and Sirius . The identified ions were classified according to defined criteria for metabolomics at levels I–IV …”

Section: Methodsmentioning

confidence: 99%

Combined Markers to Assess Meat Intake—Human Metabolomic Studies of Discovery and Validation

Cuparencu

Rinnan

Dragsted

2019

Molecular Nutrition Food Res

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Scope Biomarkers of red meat may clarify the relationship between meat intake and health. This paper explores the discovery of biomarkers of intake for three types of meat with varying heme iron content. Candidate biomarkers for red and general meat are further evaluated based on defined validation criteria. Methods and results In a randomized cross‐over meal study, healthy volunteers consume a randomized sequence of four test meals: chicken, pork, beef, and a control made of egg white and pea. Fasting and postprandial urine samples are collected to cover 48 h and profiled by untargeted LC‐ESI‐qTOF‐MS metabolomics. The profiles following the meal challenges are explored by univariate and multivariate analyses. Nine red, four white, and eight general meat biomarkers are selected as putative biomarkers, originating from collagen degradation, flavour compounds, and amino acid metabolism. Heme‐related metabolites are masked by the chlorophyll content of the control meal. The candidate biomarkers are confirmed in an independent meal study and validated for plausibility, robustness, time‐response, and prediction performance. Combinations of biomarkers are more efficient than single markers in predicting meat intake. Conclusion New combinations of partially validated biomarkers are proposed to assess terrestrial meat intake and thus help disentangle the effects of meat consumption on human health.

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Section: Methodsmentioning

confidence: 99%

Combined Markers to Assess Meat Intake—Human Metabolomic Studies of Discovery and Validation

Cuparencu

Rinnan

Dragsted

2019

Molecular Nutrition Food Res

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“…TOF peak lists were generated using SCiLS Lab (v2019a, Bremen, Germany). Metabolites, amino acids, and proteins were identified by matching accurate mass data with Metlin (http://metlin.scripps.edu/index.php), the Human Metabolome Database (http://www.hmdb.ca), and the MaTisse database, allowing a window of 4 ppm for metabolites or amino acids.…”

Section: Methodsmentioning

confidence: 99%

Derangements of amino acids in cachectic skeletal muscle are caused by mitochondrial dysfunction

Kunzke

Buck

Prade

et al. 2019

J cachexia sarcopenia muscle

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Background Cachexia is the direct cause of at least 20% of cancer‐associated deaths. Muscle wasting in skeletal muscle results in weakness, immobility, and death secondary to impaired respiratory muscle function. Muscle proteins are massively degraded in cachexia; nevertheless, the molecular mechanisms related to this process are poorly understood. Previous studies have reported conflicting results regarding the amino acid abundances in cachectic skeletal muscle tissues. There is a clear need to identify the molecular processes of muscle metabolism in the context of cachexia, especially how different types of molecules are involved in the muscle wasting process. Methods New in situ ‐omics techniques were used to produce a more comprehensive picture of amino acid metabolism in cachectic muscles by determining the quantities of amino acids, proteins, and cellular metabolites. Using matrix‐assisted laser desorption/ionization (MALDI) mass spectrometry imaging, we determined the in situ concentrations of amino acids and proteins, as well as energy and other cellular metabolites, in skeletal muscle tissues from genetic mouse cancer models (n = 21) and from patients with cancer (n = 6). Combined results from three individual MALDI mass spectrometry imaging methods were obtained and interpreted. Immunohistochemistry staining for mitochondrial proteins and myosin heavy chain expression, digital image analysis, and transmission electron microscopy complemented the MALDI mass spectrometry imaging results. Results Metabolic derangements in cachectic mouse muscle tissues were detected, with significantly increased quantities of lysine, arginine, proline, and tyrosine (P = 0.0037, P = 0.0048, P = 0.0430, and P = 0.0357, respectively) and significantly reduced quantities of glutamate and aspartate (P = 0.0008 and P = 0.0124). Human skeletal muscle tissues revealed similar tendencies. A majority of altered amino acids were released by the breakdown of proteins involved in oxidative phosphorylation. Decreased energy charge was observed in cachectic muscle tissues (P = 0.0101), which was related to the breakdown of specific proteins. Additionally, expression of the cationic amino acid transporter CAT1 was significantly decreased in the mitochondria of cachectic mouse muscles (P = 0.0133); this decrease may play an important role in the alterations of cationic amino acid metabolism and decreased quantity of glutamate observed in cachexia. Conclusions Our results suggest that mitochondrial dysfunction has a substantial influence on amino acid metabolism in cachectic skeletal muscles, which appears to be triggered by diminished CAT1 expression, as well as the degradation of mitochondrial proteins. These findings provide new insights into the pathobiochemistry of muscle wasting.

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“…The most‐recent version (HMDB 4.0) contains about 114,100 metabolites to greatly expand recognition of the metabolites. Other widely used database, such as METLIN (Guijas et al, ), NIST (Simon‐Manso et al, ), MassBank (Horai et al, ), also aided novel metabolites identification. Special databases recently appeared, such as Serum Metabolome Databases (Psychogios et al, ) and ReSpect database for phytochemicals (Sawada et al, ).…”

Section: Superiority Of Ms‐based Metabolomicsmentioning

confidence: 99%

Novel applications of mass spectrometry‐based metabolomics in herbal medicines and its active ingredients: Current evidence

Wang

Ren

Zhang

et al. 2019

Mass Spectrometry Reviews

100

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Current evidence shows that herbal medicines could be beneficial for the treatment of various diseases. However, the complexities present in chemical compositions of herbal medicines are currently an obstacle for the progression of herbal medicines, which involve unclear bioactive compounds, mechanisms of action, undetermined targets for therapy, non‐specific features for drug metabolism, etc. To overcome those issues, metabolomics can be a great to improve and understand herbal medicines from the small‐molecule metabolism level. Metabolomics could solve scientific difficulties with herbal medicines from a metabolic perspective, and promote drug discovery and development. In recent years, mass spectrometry‐based metabolomics was widely applied for the analysis of herbal constituents in vivo and in vitro. In this review, we highlight the value of mass spectrometry‐based metabolomics and metabolism to address the complexity of herbal medicines in systems pharmacology, and to enhance their biomedical value in biomedicine, to shed light on the aid that mass spectrometry‐based metabolomics can offer to the investigation of its active ingredients, especially, to link phytochemical analysis with the assessment of pharmacological effect and therapeutic potential. © 2019 Wiley Periodicals, Inc. Mass Spec Rev

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METLIN: A Technology Platform for Identifying Knowns and Unknowns

Cited by 760 publications

References 47 publications

Combined Markers to Assess Meat Intake—Human Metabolomic Studies of Discovery and Validation

Combined Markers to Assess Meat Intake—Human Metabolomic Studies of Discovery and Validation

Derangements of amino acids in cachectic skeletal muscle are caused by mitochondrial dysfunction

Novel applications of mass spectrometry‐based metabolomics in herbal medicines and its active ingredients: Current evidence

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