Nejvíce citovaný článek - PubMed ID 16448051
Feature-based molecular networking (FBMN) is a popular analysis approach for liquid chromatography-tandem mass spectrometry-based non-targeted metabolomics data. While processing liquid chromatography-tandem mass spectrometry data through FBMN is fairly streamlined, downstream data handling and statistical interrogation are often a key bottleneck. Especially users new to statistical analysis struggle to effectively handle and analyze complex data matrices. Here we provide a comprehensive guide for the statistical analysis of FBMN results, focusing on the downstream analysis of the FBMN output table. We explain the data structure and principles of data cleanup and normalization, as well as uni- and multivariate statistical analysis of FBMN results. We provide explanations and code in two scripting languages (R and Python) as well as the QIIME2 framework for all protocol steps, from data clean-up to statistical analysis. All code is shared in the form of Jupyter Notebooks ( https://github.com/Functional-Metabolomics-Lab/FBMN-STATS ). Additionally, the protocol is accompanied by a web application with a graphical user interface ( https://fbmn-statsguide.gnps2.org/ ) to lower the barrier of entry for new users and for educational purposes. Finally, we also show users how to integrate their statistical results into the molecular network using the Cytoscape visualization tool. Throughout the protocol, we use a previously published environmental metabolomics dataset for demonstration purposes. Together, the protocol, code and web application provide a complete guide and toolbox for FBMN data integration, cleanup and advanced statistical analysis, enabling new users to uncover molecular insights from their non-targeted metabolomics data. Our protocol is tailored for the seamless analysis of FBMN results from Global Natural Products Social Molecular Networking and can be easily adapted to other mass spectrometry feature detection, annotation and networking tools.
Untargeted mass spectrometry (MS) experiments produce complex, multidimensional data that are practically impossible to investigate manually. For this reason, computational pipelines are needed to extract relevant information from raw spectral data and convert it into a more comprehensible format. Depending on the sample type and/or goal of the study, a variety of MS platforms can be used for such analysis. MZmine is an open-source software for the processing of raw spectral data generated by different MS platforms. Examples include liquid chromatography-MS, gas chromatography-MS and MS-imaging. These data might typically be associated with various applications including metabolomics and lipidomics. Moreover, the third version of the software, described herein, supports the processing of ion mobility spectrometry (IMS) data. The present protocol provides three distinct procedures to perform feature detection and annotation of untargeted MS data produced by different instrumental setups: liquid chromatography-(IMS-)MS, gas chromatography-MS and (IMS-)MS imaging. For training purposes, example datasets are provided together with configuration batch files (i.e., list of processing steps and parameters) to allow new users to easily replicate the described workflows. Depending on the number of data files and available computing resources, we anticipate this to take between 2 and 24 h for new MZmine users and nonexperts. Within each procedure, we provide a detailed description for all processing parameters together with instructions/recommendations for their optimization. The main generated outputs are represented by aligned feature tables and fragmentation spectra lists that can be used by other third-party tools for further downstream analysis.
- MeSH
- chromatografie kapalinová metody MeSH
- hmotnostní spektrometrie * metody MeSH
- iontová mobilní spektrometrie metody MeSH
- metabolomika metody MeSH
- plynová chromatografie s hmotnostně spektrometrickou detekcí metody MeSH
- reprodukovatelnost výsledků MeSH
- software * MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
In the modern "omics" era, measurement of the human exposome is a critical missing link between genetic drivers and disease outcomes. High-resolution mass spectrometry (HRMS), routinely used in proteomics and metabolomics, has emerged as a leading technology to broadly profile chemical exposure agents and related biomolecules for accurate mass measurement, high sensitivity, rapid data acquisition, and increased resolution of chemical space. Non-targeted approaches are increasingly accessible, supporting a shift from conventional hypothesis-driven, quantitation-centric targeted analyses toward data-driven, hypothesis-generating chemical exposome-wide profiling. However, HRMS-based exposomics encounters unique challenges. New analytical and computational infrastructures are needed to expand the analysis coverage through streamlined, scalable, and harmonized workflows and data pipelines that permit longitudinal chemical exposome tracking, retrospective validation, and multi-omics integration for meaningful health-oriented inferences. In this article, we survey the literature on state-of-the-art HRMS-based technologies, review current analytical workflows and informatic pipelines, and provide an up-to-date reference on exposomic approaches for chemists, toxicologists, epidemiologists, care providers, and stakeholders in health sciences and medicine. We propose efforts to benchmark fit-for-purpose platforms for expanding coverage of chemical space, including gas/liquid chromatography-HRMS (GC-HRMS and LC-HRMS), and discuss opportunities, challenges, and strategies to advance the burgeoning field of the exposome.
- Klíčová slova
- chemical space, chromatography, environmental exposures, exposome, high-resolution mass spectrometry, metabolomics, non-targeted analysis, toxicants,
- MeSH
- expozom MeSH
- hmotnostní spektrometrie * metody MeSH
- lidé MeSH
- metabolomika MeSH
- proteomika metody MeSH
- vystavení vlivu životního prostředí MeSH
- Check Tag
- lidé MeSH
- Publikační typ
- časopisecké články MeSH
- přehledy MeSH
BACKGROUND: The availability of soil phosphorus (P) often limits the productivities of wet tropical lowland forests. Little is known, however, about the metabolomic profile of different chemical P compounds with potentially different uses and about the cycling of P and their variability across space under different tree species in highly diverse tropical rainforests. RESULTS: We hypothesised that the different strategies of the competing tree species to retranslocate, mineralise, mobilise, and take up P from the soil would promote distinct soil 31P profiles. We tested this hypothesis by performing a metabolomic analysis of the soils in two rainforests in French Guiana using 31P nuclear magnetic resonance (NMR). We analysed 31P NMR chemical shifts in soil solutions of model P compounds, including inorganic phosphates, orthophosphate mono- and diesters, phosphonates, and organic polyphosphates. The identity of the tree species (growing above the soil samples) explained > 53% of the total variance of the 31P NMR metabolomic profiles of the soils, suggesting species-specific ecological niches and/or species-specific interactions with the soil microbiome and soil trophic web structure and functionality determining the use and production of P compounds. Differences at regional and topographic levels also explained some part of the the total variance of the 31P NMR profiles, although less than the influence of the tree species. Multivariate analyses of soil 31P NMR metabolomics data indicated higher soil concentrations of P biomolecules involved in the active use of P (nucleic acids and molecules involved with energy and anabolism) in soils with lower concentrations of total soil P and higher concentrations of P-storing biomolecules in soils with higher concentrations of total P. CONCLUSIONS: The results strongly suggest "niches" of soil P profiles associated with physical gradients, mostly topographic position, and with the specific distribution of species along this gradient, which is associated with species-specific strategies of soil P mineralisation, mobilisation, use, and uptake.
- Klíčová slova
- Diversity, Metabolomics, P metabolomic niche, Phosphorus, Rainforest,
- MeSH
- deštný prales MeSH
- fosfáty MeSH
- fosfor * MeSH
- mikrobiota * MeSH
- půda MeSH
- stromy MeSH
- Publikační typ
- časopisecké články MeSH
- Geografické názvy
- Francouzská Guyana MeSH
- Názvy látek
- fosfáty MeSH
- fosfor * MeSH
- půda MeSH
Non-targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) is a widely used tool for metabolomics analysis, enabling the detection and annotation of small molecules in complex environmental samples. Data-dependent acquisition (DDA) of product ion spectra is thereby currently one of the most frequently applied data acquisition strategies. The optimization of DDA parameters is central to ensuring high spectral quality, coverage, and number of compound annotations. Here, we evaluated the influence of 10 central DDA settings of the Q Exactive mass spectrometer on natural organic matter samples from ocean, river, and soil environments. After data analysis with classical and feature-based molecular networking using MZmine and GNPS, we compared the total number of network nodes, multivariate clustering, and spectrum quality-related metrics such as annotation and singleton rates, MS/MS placement, and coverage. Our results show that automatic gain control, microscans, mass resolving power, and dynamic exclusion are the most critical parameters, whereas collision energy, TopN, and isolation width had moderate and apex trigger, monoisotopic selection, and isotopic exclusion minor effects. The insights into the data acquisition ergonomics of the Q Exactive platform presented here can guide new users and provide them with initial method parameters, some of which may also be transferable to other sample types and MS platforms.
Background: Idiopathic intracranial hypertension (IIH) is characterized by increased intracranial pressure occurring predominantly in women with obesity. The pathogenesis is not understood. We have applied untargeted metabolomic analysis using ultrahigh-performance liquid chromatography-mass spectrometry to characterize the cerebrospinal fluid (CSF) and serum in IIH compared to control subjects. Methods and findings: Samples were collected from IIH patients (n = 66) with active disease at baseline and again at 12 months following therapeutic weight loss. Control samples were collected from gender- and weight-matched healthy controls (n = 20). We identified annotated metabolites in CSF, formylpyruvate and maleylpyruvate/fumarylpyruvate, which were present at lower concentrations in IIH compared to control subjects and returned to values observed in controls following weight loss. These metabolites showed the opposite trend in serum at baseline. Multiple amino acid metabolic pathways and lipid classes were perturbed in serum and CSF in IIH alone. Serum lipid metabolite pathways were significantly increased in IIH. Conclusions: We observed a number of differential metabolic pathways related to amino acid, lipid, and acylpyruvate metabolism, in IIH compared to controls. These pathways were associated with clinical measures and normalized with disease remission. Perturbation of these metabolic pathways provides initial understanding of disease dysregulation in IIH.
- Klíčová slova
- arginine metabolism, idiopathic intracranial hypertension, intracranial pressure, lipid metabolism, metabolomics,
- MeSH
- aminokyseliny MeSH
- hmotnostní úbytek MeSH
- lidé MeSH
- lipidy MeSH
- pseudotumor cerebri * mozkomíšní mok komplikace MeSH
- studie případů a kontrol MeSH
- Check Tag
- lidé MeSH
- ženské pohlaví MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- aminokyseliny MeSH
- lipidy MeSH
- MeSH
- hmotnostní spektrometrie metody MeSH
- software * MeSH
- Publikační typ
- dopisy MeSH
In Mediterranean ecosystems, the projected rainfall reduction of up to 30% may alter plant-soil interactions, particularly litter decomposition and Home Field Advantage (HFA). We set up a litter transplant experiment in the three main forests encountered in the northern part of the Medi-terranean Basin (dominated by either Quercus ilex, Quercus pubescens, or Pinus halepensis) equipped with a rain exclusion device, allowing an increase in drought either throughout the year or concentrated in spring and summer. Senescent leaves and needles were collected under two precipitation treatments (natural and amplified drought plots) at their "home" forest and were left to decompose in the forest of origin and in other forests under both drought conditions. MS-based metabolomic analysis of litter extracts combined with multivariate data analysis enabled us to detect modifications in the composition of litter specialized metabolites, following amplified drought treatment. Amplified drought altered litter quality and metabolomes, directly slowed down litter decomposition, and induced a loss of home field (dis)advantage. No indirect effect mediated by a change in litter quality on decomposition was observed. These results may suggest major alterations of plant-soil interactions in Mediterranean forests under amplified drought conditions.
- Klíčová slova
- Home Field Advantage (HFA), Mediterranean forest, experimental drought, litter quality, metabolomics,
- Publikační typ
- časopisecké články MeSH
In nematodes that invade the gastro-intestinal tract of the ruminant, the process of larval exsheathment marks the transition from the free-living to the parasitic stages of these parasites. To investigate the secretome associated with larval exsheathment, a closed in vitro system that effectively reproduces the two basic components of an anaerobic rumen environment (CO2 and 39 °C) was developed to trigger exsheathment in one of the most pathogenic and model gastrointestinal parasitic nematodes, Haemonchus contortus (barber's pole worm). This study reports the use of multimodal untargeted metabolomics and lipidomics methodologies to identify the metabolic signatures and compounds secreted during in vitro larval exsheathment in the H. contortus infective third-stage larva (iL3). A combination of statistical and chemoinformatic analyses using three analytical platforms revealed a panel of metabolites detected post exsheathment and associated with amino acids, purines, as well as select organic compounds. The major lipid classes identified by the non-targeted lipidomics method applied were lysophosphatidylglycerols, diglycerides, fatty acyls, glycerophospholipids, and a triglyceride. The identified metabolites may serve as metabolic signatures to improve tractability of parasitic nematodes for characterizing small molecule host-parasite interactions related to pathogenesis, vaccine and drug design, as well as the discovery of metabolic biomarkers.
- Klíčová slova
- Haemonchus contortus, exsheathment, helminth, lipidomics, metabolomics, parasite,
- MeSH
- Haemonchus * MeSH
- hlístice * MeSH
- larva MeSH
- přežvýkavci MeSH
- sekretom MeSH
- zvířata MeSH
- Check Tag
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
Eurasian spruce bark beetle, Ips typographus, is an aggressive pest among spruce vegetation. I. typographus host trees colonization is mediated by aggregation pheromone, consisting of 2-methyl-3-buten-2-ol and cis-verbenol produced in the beetle gut. Other biologically active compounds such as ipsdienol and verbenone have also been detected. 2-Methyl-3-buten-2-ol and ipsdienol are produced de-novo in the mevalonate pathway and cis-verbenol is oxidized from α-pinene sequestrated from the host. The pheromone production is presumably connected with further changes in the primary and secondary metabolisms in the beetle. To evaluate such possibilities, we obtained qualitative metabolomic data from the analysis of beetle guts in different life stages. We used Ultra-high-performance liquid chromatography-electrospray ionization-high resolution tandem mass spectrometry (UHPLC-ESI-HRMS/MS). The data were dereplicated using metabolomic software (XCMS, Camera, and Bio-Conductor) and approximately 3000 features were extracted. The metabolite was identified using GNPS databases and de-novo annotation in Sirius program followed by manual curation. Further, we obtained differential gene expression (DGE) of RNA sequencing data for mevalonate pathway genes and CytochromeP450 (CyP450) genes from the gut tissue of the beetle to delineate their role on life stage-specific pheromone biosynthesis. CyP450 gene families were classified according to subclasses and given individual expression patterns as heat maps. Three mevalonate pathway genes and five CyP450 gene relative expressions were analyzed using quantitative real-time (qRT) PCR, from the gut tissue of different life stage male/female beetles, as extended knowledge of related research article (Ramakrishnan et al., 2022). This data provides essential information on pheromone biosynthesis at the molecular level and supports further research on pheromone biosynthesis and detoxification in conifer bark beetles.
- Klíčová slova
- Bark beetle, De-novo, Gut tissue, Omics, Pheromone biosynthesis, Spruce,
- Publikační typ
- časopisecké články MeSH
