Mass spectrometry-based metabolomics: a guide for annotation, quantification and best reporting practices

Nature Methods, Journal Year: 2021, Volume and Issue: 18(7), P. 747 - 756

Published: July 1, 2021

Language: Английский

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Systematic classification of unknown metabolites using high-resolution fragmentation mass spectra

Nature Biotechnology, Journal Year: 2020, Volume and Issue: 39(4), P. 462 - 471

Published: Nov. 23, 2020

Language: Английский

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Metabolic reaction network-based recursive metabolite annotation for untargeted metabolomics

Nature Communications, Journal Year: 2019, Volume and Issue: 10(1)

Published: April 3, 2019

Abstract Large-scale metabolite annotation is a challenge in liquid chromatogram-mass spectrometry (LC-MS)-based untargeted metabolomics. Here, we develop metabolic reaction network (MRN)-based recursive algorithm (MetDNA) that expands annotations without the need for comprehensive standard spectral library. MetDNA based on rationale seed metabolites and their reaction-paired neighbors tend to share structural similarities resulting similar MS2 spectra. characterizes initial using small library of spectra, utilizes experimental spectra as surrogate annotate neighbor metabolites, which subsequently serve basis analysis. Using different LC-MS platforms, data acquisition methods, biological samples, showcase utility versatility demonstrate about 2000 can cumulatively be annotated from one experiment. Our results substantially annotation, enabling quantitative assessment pathways facilitating integrative multi-omics

Language: Английский

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Acylcarnitines: Nomenclature, Biomarkers, Therapeutic Potential, Drug Targets, and Clinical Trials

Pharmacological Reviews, Journal Year: 2022, Volume and Issue: 74(3), P. 506 - 551

Published: June 16, 2022

Acylcarnitines are fatty acid metabolites that play important roles in many cellular energy metabolism pathways. They have historically been used as diagnostic markers for inborn errors of oxidation and being intensively studied metabolism, deficits mitochondrial peroxisomal β -oxidation activity, insulin resistance, physical activity. increasingly identified indicators metabolic studies diseases, including disorders, cardiovascular diabetes, depression, neurologic certain cancers. The US Food Drug Administration-approved drug L-carnitine, along with short-chain acylcarnitines (acetylcarnitine propionylcarnitine), is now widely a dietary supplement. In light their growing importance, we undertaken an extensive review provided detailed description identity, nomenclature, classification, biochemistry, pathophysiology, supplementary use, potential targets, clinical trials. We also summarize these updates the Human Metabolome Database, which includes information on structures, chemical formulae, chemical/spectral properties, descriptions, pathways 1240 acylcarnitines. This work lays solid foundation identifying, characterizing, understanding human biosamples. discuss emerging opportunities using biomarkers interventions or supplements wide-ranging indications. opportunity to identify new targets involved controlling acylcarnitine levels discussed. SIGNIFICANCE STATEMENT: provides comprehensive overview acylcarnitines, structure use disease pharmaceutical agents. present updated contained Database website well substantial mapping known biochemical associated thereby providing strong further clarification physiological roles.

Language: Английский

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The METLIN small molecule dataset for machine learning-based retention time prediction

Nature Communications, Journal Year: 2019, Volume and Issue: 10(1)

Published: Dec. 20, 2019

Abstract Machine learning has been extensively applied in small molecule analysis to predict a wide range of molecular properties and processes including mass spectrometry fragmentation or chromatographic retention time. However, current approaches for time prediction lack sufficient accuracy due limited available experimental data. Here we introduce the METLIN (SMRT) dataset, an experimentally acquired reverse-phase chromatography dataset covering up 80,038 molecules. To demonstrate utility this deployed deep model annotation. Results showed that 70 $$\%$$ % cases, correct identity was ranked among top 3 candidates based on their predicted We anticipate will enable community apply machine first principles strategies generate better models prediction.

Language: Английский

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Retip: Retention Time Prediction for Compound Annotation in Untargeted Metabolomics

Analytical Chemistry, Journal Year: 2020, Volume and Issue: 92(11), P. 7515 - 7522

Published: May 11, 2020

Unidentified peaks remain a major problem in untargeted metabolomics by LC-MS/MS. Confidence peak annotations increases combining MS/MS matching and retention time. We here show how times can be predicted from molecular structures. Two large, publicly available data sets were used for model training machine learning: the Fiehn hydrophilic interaction liquid chromatography set (HILIC) of 981 primary metabolites biogenic amines,and RIKEN plant specialized metabolome annotation (PlaSMA) database 852 secondary that uses reversed-phase (RPLC). Five different learning algorithms have been integrated into Retip R package: random forest, Bayesian-regularized neural network, XGBoost, light gradient-boosting (LightGBM), Keras building time prediction models. A complete workflow was developed R. It freely downloaded GitHub repository (https://www.retip.app). outperformed other test with minimum overfitting, verified small error differences between training, test, validation sets. yielded mean absolute 0.78 min HILIC 0.57 RPLC. is mass spectrometry software tools MS-DIAL MS-FINDER, allowing compound workflow. In application on mouse blood plasma samples, we found 68% reduction number candidate structures when searching all isomers MS-FINDER identification software. Retention rate subsequently leads to an improved biological interpretation data.

Language: Английский

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Metabolite discovery through global annotation of untargeted metabolomics data

Nature Methods, Journal Year: 2021, Volume and Issue: 18(11), P. 1377 - 1385

Published: Oct. 28, 2021

Language: Английский

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Photoaging enhanced the adverse effects of polyamide microplastics on the growth, intestinal health, and lipid absorption in developing zebrafish

Environment International, Journal Year: 2021, Volume and Issue: 158, P. 106922 - 106922

Published: Oct. 8, 2021

The safety of microplastics (MPs) and associated health effects has been one the major concerns worldwide. However, role photoaging toward risk MPs in water ecosystems remains inconclusive yet. In this study, size polyamide (PA, ∼32.50 μm) was obviously decreased after containing fulvic acid (FA) humic (HA) (∼19.75 ∼24.30 μm, respectively). Nanoplastics were formed (4.65% 2.03%, respectively) hydrophilia colloidal stability improved due to formation oxygen-containing functional groups. FA-aged PA exhibited higher inhibition on body length weight developing zebrafish than HA-aged pristine PA. Photoaged intestine more difficult be depurated by zebrafish, leading disappearance intestinal folding, shedding enterocytes, emaciation microvilli. Dietary lipid digestion larvae inhibited aged oxidative stress-triggered peroxidation lipase activities bile acids secretion. Exposure photoaged down-regulated genes (cd36, dgat1a, dgat2, mttp, etc.) with triglyceride resynthesis transportation, resulting maladsorption growth inhibition. Our findings highlight potential negative environmentally diet nutrient assimilation fish.

Language: Английский

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Metabolomics study of COVID-19 patients in four different clinical stages

Scientific Reports, Journal Year: 2022, Volume and Issue: 12(1)

Published: Jan. 31, 2022

Abstract SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) is the strain causing pandemic COVID-19 (coronavirus disease 2019). To understand pathobiology of in humans it necessary to unravel metabolic changes that are produced individuals once infection has taken place. The goal this work provide new information about altered biomolecule profile and with biological pathways patients different clinical situations due infection. This done via metabolomics using HPLC–QTOF–MS analysis plasma samples at COVID-diagnose from a total 145 adult patients, divided into stages based on their subsequent outcome (25 negative controls (non-COVID); 28 positive asymptomatic not requiring hospitalization; 27 mild defined by time hospital lower than 10 days; 36 severe over 20 days and/or admission ICU; 29 fatal or deceased). Moreover, follow up between 2 3 months after discharge were also obtained hospitalized prognosis. final biomarkers can help better how illness evolves predict patient could progress metabolites an early stage In present work, several found as potential distinguish end-stage early-stage (or non-COVID) groups. These mainly involved metabolism carnitines, ketone bodies, fatty acids, lysophosphatidylcholines/phosphatidylcholines, tryptophan, bile acids purines, but omeprazole. addition, levels these decreased “normal” values discharge, suggesting some them prognosis diagnose.

Language: Английский

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Reverse metabolomics for the discovery of chemical structures from humans

Nature, Journal Year: 2023, Volume and Issue: 626(7998), P. 419 - 426

Published: Dec. 5, 2023

Abstract Determining the structure and phenotypic context of molecules detected in untargeted metabolomics experiments remains challenging. Here we present reverse as a discovery strategy, whereby tandem mass spectrometry spectra acquired from newly synthesized compounds are searched for public datasets to uncover associations. To demonstrate concept, broadly explored multiple classes metabolites humans, including N -acyl amides, fatty acid esters hydroxy acids, bile conjugated acids. Using repository-scale analysis 1,2 , discovered that some acids associated with inflammatory bowel disease (IBD). Validation using four distinct human IBD cohorts showed cholic Glu, Ile/Leu, Phe, Thr, Trp or Tyr increased Crohn’s disease. Several these related structures affected pathways IBD, such interferon-γ production CD4 + T cells 3 agonism pregnane X receptor 4 . Culture bacteria belonging Bifidobacterium Clostridium Enterococcus genera produced amidates. Because searching repositories has only recently become possible, this approach can now be used general strategy discover other animal ecosystems.

Language: Английский

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