Journal articles: 'Targeted and untargeted metabolomics'

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Zhou, Jinna, Donghai Hou, Weiqiu Zou, Jinhu Wang, Run Luo, Mu Wang, and Hong Yu. "Comparison of Widely Targeted Metabolomics and Untargeted Metabolomics of Wild Ophiocordyceps Sinensis." Molecules 27, no. 11 (June 6, 2022): 3645. http://dx.doi.org/10.3390/molecules27113645.

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The authors of this paper conducted a comparative metabolomic analysis of Ophiocordyceps sinensis (OS), providing the metabolic profiles of the stroma (OSBSz) and sclerotia (OSBSh) of OS by widely targeted metabolomics and untargeted metabolomics. The results showed that 778 and 1449 metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. The metabolites in OSBSz and OSBSh are significantly differentiated; 71 and 96 differentially expressed metabolites were identified by the widely targeted metabolomics and untargeted metabolomics approaches, respectively. This suggests that these 71 metabolites (riboflavine, tripdiolide, bromocriptine, lumichrome, tetrahymanol, citrostadienol, etc.) and 96 metabolites (sancycline, vignatic acid B, pirbuterol, rubrophen, epalrestat, etc.) are potential biomarkers. 4-Hydroxybenzaldehyde, arginine, and lumichrome were common differentially expressed metabolites. Using the widely targeted metabolomics approach, the key pathways identified that are involved in creating the differentiation between OSBSz and OSBSh may be nicotinate and nicotinamide metabolism, thiamine metabolism, riboflavin metabolism, glycine, serine, and threonine metabolism, and arginine biosynthesis. The differentially expressed metabolites identified using the untargeted metabolomics approach were mainly involved in arginine biosynthesis, terpenoid backbone biosynthesis, porphyrin and chlorophyll metabolism, and cysteine and methionine metabolism. The purpose of this research was to provide support for the assessment of the differences between the stroma and sclerotia, to furnish a material basis for the evaluation of the physical effects of OS, and to provide a reference for the selection of detection methods for the metabolomics of OS.

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Chen, Li, Fanyi Zhong, and Jiangjiang Zhu. "Bridging Targeted and Untargeted Mass Spectrometry-Based Metabolomics via Hybrid Approaches." Metabolites 10, no. 9 (August 27, 2020): 348. http://dx.doi.org/10.3390/metabo10090348.

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This mini-review aims to discuss the development and applications of mass spectrometry (MS)-based hybrid approaches in metabolomics. Several recently developed hybrid approaches are introduced. Then, the overall workflow, frequently used instruments, data handling strategies, and applications are compared and their pros and cons are summarized. Overall, the improved repeatability and quantitative capability in large-scale MS-based metabolomics studies are demonstrated, in comparison to either targeted or untargeted metabolomics approaches alone. In summary, we expect this review to serve as a first attempt to highlight the development and applications of emerging hybrid approaches in metabolomics, and we believe that hybrid metabolomics approaches could have great potential in many future studies.

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Gross, Thomas, Mark Mapstone, Ricardo Miramontes, Robert Padilla, Amrita K. Cheema, Fabio Macciardi, Howard J. Federoff, and Massimo S. Fiandaca. "Toward Reproducible Results from Targeted Metabolomic Studies: Perspectives for Data Pre-processing and a Basis for Analytic Pipeline Development." Current Topics in Medicinal Chemistry 18, no. 11 (August 28, 2018): 883–95. http://dx.doi.org/10.2174/1568026618666180711144323.

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Contemporary metabolomics experiments generate a rich array of complex high-dimensional data. Consequently, there have been concurrent efforts to develop methodological standards and analytical workflows to streamline the generation of meaningful biochemical and clinical inferences from raw data generated using an analytical platform like mass spectrometry. While such considerations have been frequently addressed in untargeted metabolomics (i.e., the broad survey of all distinguishable metabolites within a sample of interest), this methodological scrutiny has seldom been applied to data generated using commercial, targeted metabolomics kits. We suggest that this may, in part, account for past and more recent incomplete replications of previously specified biomarker panels. Herein, we identify common impediments challenging the analysis of raw, targeted metabolomic abundance data from a commercial kit and review methods to remedy these issues. In doing so, we propose an analytical pipeline suitable for the pre-processing of data for downstream biomarker discovery. Operational and statistical considerations for integrating targeted data sets across experimental sites and analytical batches are discussed, as are best practices for developing predictive models relating pre-processed metabolomic data to associated phenotypic information.

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Wei, Yiping, Paniz Jasbi, Xiaojian Shi, Cassidy Turner, Jonathon Hrovat, Li Liu, Yuri Rabena, Peggy Porter, and Haiwei Gu. "Early Breast Cancer Detection Using Untargeted and Targeted Metabolomics." Journal of Proteome Research 20, no. 6 (May 25, 2021): 3124–33. http://dx.doi.org/10.1021/acs.jproteome.1c00019.

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Szeremeta, Michal, Karolina Pietrowska, Anna Niemcunowicz-Janica, Adam Kretowski, and Michal Ciborowski. "Applications of Metabolomics in Forensic Toxicology and Forensic Medicine." International Journal of Molecular Sciences 22, no. 6 (March 16, 2021): 3010. http://dx.doi.org/10.3390/ijms22063010.

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Forensic toxicology and forensic medicine are unique among all other medical fields because of their essential legal impact, especially in civil and criminal cases. New high-throughput technologies, borrowed from chemistry and physics, have proven that metabolomics, the youngest of the “omics sciences”, could be one of the most powerful tools for monitoring changes in forensic disciplines. Metabolomics is a particular method that allows for the measurement of metabolic changes in a multicellular system using two different approaches: targeted and untargeted. Targeted studies are focused on a known number of defined metabolites. Untargeted metabolomics aims to capture all metabolites present in a sample. Different statistical approaches (e.g., uni- or multivariate statistics, machine learning) can be applied to extract useful and important information in both cases. This review aims to describe the role of metabolomics in forensic toxicology and in forensic medicine.

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Allwood, James William, Alex Williams, Henriette Uthe, Nicole M. van Dam, Luis A. J. Mur, Murray R. Grant, and Pierre Pétriacq. "Unravelling Plant Responses to Stress—The Importance of Targeted and Untargeted Metabolomics." Metabolites 11, no. 8 (August 22, 2021): 558. http://dx.doi.org/10.3390/metabo11080558.

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Climate change and an increasing population, present a massive global challenge with respect to environmentally sustainable nutritious food production. Crop yield enhancements, through breeding, are decreasing, whilst agricultural intensification is constrained by emerging, re-emerging, and endemic pests and pathogens, accounting for ~30% of global crop losses, as well as mounting abiotic stress pressures, due to climate change. Metabolomics approaches have previously contributed to our knowledge within the fields of molecular plant pathology and plant–insect interactions. However, these remain incredibly challenging targets, due to the vast diversity in metabolite volatility and polarity, heterogeneous mixtures of pathogen and plant cells, as well as rapid rates of metabolite turn-over. Unravelling the systematic biochemical responses of plants to various individual and combined stresses, involves monitoring signaling compounds, secondary messengers, phytohormones, and defensive and protective chemicals. This demands both targeted and untargeted metabolomics approaches, as well as a range of enzymatic assays, protein assays, and proteomic and transcriptomic technologies. In this review, we focus upon the technical and biological challenges of measuring the metabolome associated with plant stress. We illustrate the challenges, with relevant examples from bacterial and fungal molecular pathologies, plant–insect interactions, and abiotic and combined stress in the environment. We also discuss future prospects from both the perspective of key innovative metabolomic technologies and their deployment in breeding for stress resistance.

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Lim, Vuanghao, Sara Ghorbani Gorji, Venea Dara Daygon, and Melissa Fitzgerald. "Untargeted and Targeted Metabolomic Profiling of Australian Indigenous Fruits." Metabolites 10, no. 3 (March 19, 2020): 114. http://dx.doi.org/10.3390/metabo10030114.

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Selected Australian native fruits such as Davidson’s plum, finger lime and native pepperberry have been reported to demonstrate potent antioxidant activity. However, comprehensive metabolite profiling of these fruits is limited, therefore the compounds responsible are unknown, and further, the compounds of nutritional value in these native fruits are yet to be described. In this study, untargeted and targeted metabolomics were conducted using the three fruits, together with assays to determine their antioxidant activities. The results demonstrate that targeted free and hydrolysed protein amino acids exhibited high amounts of essential amino acids. Similarly, important minerals like potassium were detected in the fruit samples. In antioxidant activity, Davidson’s plum reported the highest activity in ferric reducing power (FRAP), finger lime in antioxidant capacity (ABTS), and native pepperberry in free radical scavenging (DPPH) and phosphomolybdenum assay. The compounds responsible for the antioxidant activity were tentatively identified using untargeted GC×GC-TOFMS and UHPLC-QqQ-TOF-MS/MS metabolomics. A clear discrimination into three clusters of fruits was observed using principal component analysis (PCA) and partial least squares (PLS) analysis. The correlation study identified a number of compounds that provide the antioxidant activities. GC×GC-TOFMS detected potent aroma compounds of limonene, furfural, and 1-R-α-pinene. Based on the untargeted and targeted metabolomics, and antioxidant assays, the nutritional potential of these Australian bush fruits is considerable and supports these indigenous fruits in the nutraceutical industry as well as functional ingredients for the food industry, with such outcomes benefiting Indigenous Australian communities.

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Martin, Malia J., Ryan S. Pralle, Isabelle R. Bernstein, Michael J. VandeHaar, Kent A. Weigel, Zheng Zhou, and Heather M. White. "Circulating Metabolites Indicate Differences in High and Low Residual Feed Intake Holstein Dairy Cows." Metabolites 11, no. 12 (December 14, 2021): 868. http://dx.doi.org/10.3390/metabo11120868.

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Selection for more feed efficient dairy cows is key to improving sustainability and profitability of dairy production; however, underlying mechanisms contributing to individual animal feed efficiency are not fully understood. The objective of this study was to identify circulating metabolites, and pathways associated with those metabolites, that differ between efficient and inefficient Holstein dairy cows using targeted metabolite quantification and untargeted metabolomics. The top and bottom fifteen percent of cows (n = 28/group) with the lowest and highest residual feed intake in mid-lactation feed efficiency trials were grouped retrospectively as high-efficient (HE) and low-efficient (LE). Blood samples were collected for quantification of energy metabolites, markers of hepatic function, and acylcarnitines, in addition to a broader investigation using untargeted metabolomics. Short-chain acylcarnitines, C3-acylcarnitine, and C4-acylcarntine were lower in HE cows (n = 18/group). Untargeted metabolomics and multivariate analysis identified thirty-nine differential metabolites between HE and LE (n = 8/group), of which twenty-five were lower and fourteen were higher in HE. Pathway enrichment analysis indicated differences in tryptophan metabolism. Combined results from targeted metabolite quantification and untargeted metabolomics indicate differences in fatty acid and amino acid metabolism between HE and LE cows. These differences may indicate post-absorptive nutrient use efficiency as a contributor to individual animal variation in feed efficiency.

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CREEK, DARREN J., and MICHAEL P. BARRETT. "Determination of antiprotozoal drug mechanisms by metabolomics approaches." Parasitology 141, no. 1 (June 5, 2013): 83–92. http://dx.doi.org/10.1017/s0031182013000814.

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SUMMARYThe discovery, development and optimal utilization of pharmaceuticals can be greatly enhanced by knowledge of their modes of action. However, many drugs currently on the market act by unknown mechanisms. Untargeted metabolomics offers the potential to discover modes of action for drugs that perturb cellular metabolism. Development of high resolution LC-MS methods and improved data analysis software now allows rapid detection of drug-induced changes to cellular metabolism in an untargeted manner. Several studies have demonstrated the ability of untargeted metabolomics to provide unbiased target discovery for antimicrobial drugs, in particular for antiprotozoal agents. Furthermore, the utilization of targeted metabolomics techniques has enabled validation of existing hypotheses regarding antiprotozoal drug mechanisms. Metabolomics approaches are likely to assist with optimization of new drug candidates by identification of drug targets, and by allowing detailed characterization of modes of action and resistance of existing and novel antiprotozoal drugs.

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Lee, Yu Ra, Ki-Yong An, Justin Jeon, Nam Kyu Kim, Ji Won Lee, Jongki Hong, and Bong Chul Chung. "Untargeted Metabolomics and Polyamine Profiling in Serum before and after Surgery in Colorectal Cancer Patients." Metabolites 10, no. 12 (November 27, 2020): 487. http://dx.doi.org/10.3390/metabo10120487.

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Colorectal cancer is one of the most prevalent cancers in Korea and globally. In this study, we aimed to characterize the differential serum metabolomic profiles between pre-operative and post-operative patients with colorectal cancer. To investigate the significant metabolites and metabolic pathways associated with colorectal cancer, we analyzed serum samples from 68 patients (aged 20–71, mean 57.57 years). Untargeted and targeted metabolomics profiling in patients with colorectal cancer were performed using liquid chromatography-mass spectrometry. Untargeted analysis identified differences in sphingolipid metabolism, steroid biosynthesis, and arginine and proline metabolism in pre- and post-operative patients with colorectal cancer. We then performed quantitative target profiling of polyamines, synthesized from arginine and proline metabolism, to identify potential polyamines that may serve as effective biomarkers for colorectal cancer. Results indicate a significantly reduced serum concentration of putrescine in post-operative patients compared to pre-operative patients. Our metabolomics approach provided insights into the physiological alterations in patients with colorectal cancer after surgery.

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Sharma, Bharti, and Dinesh Kumar Yadav. "Metabolomics and Network Pharmacology in the Exploration of the Multi-Targeted Therapeutic Approach of Traditional Medicinal Plants." Plants 11, no. 23 (November 25, 2022): 3243. http://dx.doi.org/10.3390/plants11233243.

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Metabolomic is generally characterized as a comprehensive and the most copious analytical technique for the identification of targeted and untargeted metabolite diversity in a biological system. Recently, it has exponentially been used for phytochemical analysis and variability among plant metabolites, followed by chemometric analysis. Network pharmacology analysis is a computational technique used for the determination of multi-mechanistic and therapeutic evaluation of chemicals via interaction with the genomes involved in targeted or untargeted diseases. In considering the facts, the present review aims to explore the role of metabolomics and network pharmacology in the scientific validation of therapeutic claims as well as to evaluate the multi-targeted therapeutic approach of traditional Indian medicinal plants. The data was collected from different electronic scientific databases such as Google Scholar, Science Direct, ACS publication, PubMed, Springer, etc., using different keywords such as metabolomics, techniques used in metabolomics, chemometric analysis, a bioinformatic tool for drug discovery and development, network pharmacology, methodology and its role in biological evaluation of chemicals, etc. The screened articles were gathered and evaluated by different experts for their exclusion and inclusion in the final draft of the manuscript. The review findings suggest that metabolomics is one of the recent most precious and effective techniques for metabolite identification in the plant matrix. Various chemometric techniques are copiously used for metabolites discrimination analysis hence validating the unique characteristic of herbal medicines and their derived products concerning their authenticity. Network pharmacology remains the only option for the unique and effective analysis of hundreds of chemicals or metabolites via genomic interaction and thus validating the multi-mechanistic and therapeutic approach to explore the pharmacological aspects of herbal medicines for the management of the disease.

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Ismail, Showalter, and Fiehn. "Inborn Errors of Metabolism in the Era of Untargeted Metabolomics and Lipidomics." Metabolites 9, no. 10 (October 21, 2019): 242. http://dx.doi.org/10.3390/metabo9100242.

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Inborn errors of metabolism (IEMs) are a group of inherited diseases with variable incidences. IEMs are caused by disrupting enzyme activities in specific metabolic pathways by genetic mutations, either directly or indirectly by cofactor deficiencies, causing altered levels of compounds associated with these pathways. While IEMs may present with multiple overlapping symptoms and metabolites, early and accurate diagnosis of IEMs is critical for the long-term health of affected subjects. The prevalence of IEMs differs between countries, likely because different IEM classifications and IEM screening methods are used. Currently, newborn screening programs exclusively use targeted metabolic assays that focus on limited panels of compounds for selected IEM diseases. Such targeted approaches face the problem of false negative and false positive diagnoses that could be overcome if metabolic screening adopted analyses of a broader range of analytes. Hence, we here review the prospects of using untargeted metabolomics for IEM screening. Untargeted metabolomics and lipidomics do not rely on predefined target lists and can detect as many metabolites as possible in a sample, allowing to screen for many metabolic pathways simultaneously. Examples are given for nontargeted analyses of IEMs, and prospects and limitations of different metabolomics methods are discussed. We conclude that dedicated studies are needed to compare accuracy and robustness of targeted and untargeted methods with respect to widening the scope of IEM diagnostics.

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Bonte, Ramon, Michiel Bongaerts, Serwet Demirdas, Janneke G. Langendonk, Hidde H. Huidekoper, Monique Williams, Willem Onkenhout, Edwin H. Jacobs, Henk J. Blom, and George J. G. Ruijter. "Untargeted Metabolomics-Based Screening Method for Inborn Errors of Metabolism using Semi-Automatic Sample Preparation with an UHPLC- Orbitrap-MS Platform." Metabolites 9, no. 12 (November 26, 2019): 289. http://dx.doi.org/10.3390/metabo9120289.

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Routine diagnostic screening of inborn errors of metabolism (IEM) is currently performed by different targeted analyses of known biomarkers. This approach is time-consuming, targets a limited number of biomarkers and will not identify new biomarkers. Untargeted metabolomics generates a global metabolic phenotype and has the potential to overcome these issues. We describe a novel, single platform, untargeted metabolomics method for screening IEM, combining semi-automatic sample preparation with pentafluorophenylpropyl phase (PFPP)-based UHPLC- Orbitrap-MS. We evaluated analytical performance and diagnostic capability of the method by analysing plasma samples of 260 controls and 53 patients with 33 distinct IEM. Analytical reproducibility was excellent, with peak area variation coefficients below 20% for the majority of the metabolites. We illustrate that PFPP-based chromatography enhances identification of isomeric compounds. Ranked z-score plots of metabolites annotated in IEM samples were reviewed by two laboratory specialists experienced in biochemical genetics, resulting in the correct diagnosis in 90% of cases. Thus, our untargeted metabolomics platform is robust and differentiates metabolite patterns of different IEMs from those of controls. We envision that the current approach to diagnose IEM, using numerous tests, will eventually be replaced by untargeted metabolomics methods, which also have the potential to discover novel biomarkers and assist in interpretation of genetic data.

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Madrid-Gambin, Francisco, Sergio Oller-Moreno, Luis Fernandez, Simona Bartova, Maria Pilar Giner, Christopher Joyce, Francesco Ferraro, Ivan Montoliu, Sofia Moco, and Santiago Marco. "AlpsNMR: an R package for signal processing of fully untargeted NMR-based metabolomics." Bioinformatics 36, no. 9 (January 13, 2020): 2943–45. http://dx.doi.org/10.1093/bioinformatics/btaa022.

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Abstract Summary Nuclear magnetic resonance (NMR)-based metabolomics is widely used to obtain metabolic fingerprints of biological systems. While targeted workflows require previous knowledge of metabolites, prior to statistical analysis, untargeted approaches remain a challenge. Computational tools dealing with fully untargeted NMR-based metabolomics are still scarce or not user-friendly. Therefore, we developed AlpsNMR (Automated spectraL Processing System for NMR), an R package that provides automated and efficient signal processing for untargeted NMR metabolomics. AlpsNMR includes spectra loading, metadata handling, automated outlier detection, spectra alignment and peak-picking, integration and normalization. The resulting output can be used for further statistical analysis. AlpsNMR proved effective in detecting metabolite changes in a test case. The tool allows less experienced users to easily implement this workflow from spectra to a ready-to-use dataset in their routines. Availability and implementation The AlpsNMR R package and tutorial is freely available to download from http://github.com/sipss/AlpsNMR under the MIT license. Supplementary information Supplementary data are available at Bioinformatics online.

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Chanukuppa, Venkatesh, Tushar H. More, Khushman Taunk, Ravindra Taware, Tathagata Chatterjee, Sanjeevan Sharma, and Srikanth Rapole. "Serum metabolomic alterations in multiple myeloma revealed by targeted and untargeted metabolomics approaches: a pilot study." RSC Advances 9, no. 51 (2019): 29522–32. http://dx.doi.org/10.1039/c9ra04458b.

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Chávez-Márquez, Alejandra, Alfonso A. Gardea, Humberto González-Rios, and Luz Vazquez-Moreno. "Characterization of Cabernet Sauvignon Wines by Untargeted HS-SPME GC-QTOF-MS." Molecules 27, no. 5 (March 7, 2022): 1726. http://dx.doi.org/10.3390/molecules27051726.

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Untargeted metabolomics approaches are emerging as powerful tools for the quality evaluation and authenticity of food and beverages and have been applied to wine science. However, most fail to report the method validation, quality assurance and/or quality control applied, as well as the assessment through the metabolomics-methodology pipeline. Knowledge of Mexican viticulture, enology and wine science remains scarce, thus untargeted metabolomics approaches arise as a suitable tool. The aim of this study is to validate an untargeted HS-SPME-GC-qTOF/MS method, with attention to data processing to characterize Cabernet Sauvignon wines from two vineyards and two vintages. Validation parameters for targeted methods are applied in conjunction with the development of a recursive analysis of data. The combination of some parameters for targeted studies (repeatability and reproducibility < 20% RSD; linearity > 0.99; retention-time reproducibility < 0.5% RSD; match-identification factor < 2.0% RSD) with recursive analysis of data (101 entities detected) warrants that both chromatographic and spectrometry-processing data were under control and provided high-quality results, which in turn differentiate wine samples according to site and vintage. It also shows potential biomarkers that can be identified. This is a step forward in the pursuit of Mexican wine characterization that could be used as an authentication tool.

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Tsugawa, Hiroshi, Aya Satoh, Haruki Uchino, Tomas Cajka, Makoto Arita, and Masanori Arita. "Mass Spectrometry Data Repository Enhances Novel Metabolite Discoveries with Advances in Computational Metabolomics." Metabolites 9, no. 6 (June 24, 2019): 119. http://dx.doi.org/10.3390/metabo9060119.

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Mass spectrometry raw data repositories, including Metabolomics Workbench and MetaboLights, have contributed to increased transparency in metabolomics studies and the discovery of novel insights in biology by reanalysis with updated computational metabolomics tools. Herein, we reanalyzed the previously published lipidomics data from nine algal species, resulting in the annotation of 1437 lipids achieving a 40% increase in annotation compared to the previous results. Specifically, diacylglyceryl-carboxyhydroxy-methylcholine (DGCC) in Pavlova lutheri and Pleurochrysis carterae, glucuronosyldiacylglycerol (GlcADG) in Euglena gracilis, and P. carterae, phosphatidylmethanol (PMeOH) in E. gracilis, and several oxidized phospholipids (oxidized phosphatidylcholine, OxPC; phosphatidylethanolamine, OxPE; phosphatidylglycerol, OxPG; phosphatidylinositol, OxPI) in Chlorella variabilis were newly characterized with the enriched lipid spectral databases. Moreover, we integrated the data from untargeted and targeted analyses from data independent tandem mass spectrometry (DIA-MS/MS) acquisition, specifically the sequential window acquisition of all theoretical fragment-ion MS/MS (SWATH-MS/MS) spectra, to increase the lipidomic annotation coverage. After the creation of a global library of precursor and diagnostic ions of lipids by the MS-DIAL untargeted analysis, the co-eluted DIA-MS/MS spectra were resolved in MRMPROBS targeted analysis by tracing the specific product ions involved in acyl chain compositions. Our results indicated that the metabolite quantifications based on DIA-MS/MS chromatograms were somewhat inferior to the MS1-centric quantifications, while the annotation coverage outperformed those of the untargeted analysis of the data dependent and DIA-MS/MS data. Consequently, integrated analyses of untargeted and targeted approaches are necessary to extract the maximum amount of metabolome information, and our results showcase the value of data repositories for the discovery of novel insights in lipid biology.

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Pinu, Farhana. "Grape and Wine Metabolomics to Develop New Insights Using Untargeted and Targeted Approaches." Fermentation 4, no. 4 (November 7, 2018): 92. http://dx.doi.org/10.3390/fermentation4040092.

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Chemical analysis of grape juice and wine has been performed for over 50 years in a targeted manner to determine a limited number of compounds using Gas Chromatography, Mass-Spectrometry (GC-MS) and High Pressure Liquid Chromatography (HPLC). Therefore, it only allowed the determination of metabolites that are present in high concentration, including major sugars, amino acids and some important carboxylic acids. Thus, the roles of many significant but less concentrated metabolites during wine making process are still not known. This is where metabolomics shows its enormous potential, mainly because of its capability in analyzing over 1000 metabolites in a single run due to the recent advancements of high resolution and sensitive analytical instruments. Metabolomics has predominantly been adopted by many wine scientists as a hypothesis-generating tool in an unbiased and non-targeted way to address various issues, including characterization of geographical origin (terroir) and wine yeast metabolic traits, determination of biomarkers for aroma compounds, and the monitoring of growth developments of grape vines and grapes. The aim of this review is to explore the published literature that made use of both targeted and untargeted metabolomics to study grapes and wines and also the fermentation process. In addition, insights are also provided into many other possible avenues where metabolomics shows tremendous potential as a question-driven approach in grape and wine research.

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Mohd Kamal, Khairunnisa, Mohd Hafidz Mahamad Maifiah, Nusaibah Abdul Rahim, Yumi Zuhanis Has-Yun Hashim, Muhamad Shirwan Abdullah Sani, and Kamalrul Azlan Azizan. "Bacterial Metabolomics: Sample Preparation Methods." Biochemistry Research International 2022 (April 12, 2022): 1–14. http://dx.doi.org/10.1155/2022/9186536.

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Metabolomics is a comprehensive analysis of metabolites existing in biological systems. As one of the important “omics” tools, the approach has been widely employed in various fields in helping to better understand the complex cellular metabolic states and changes. Bacterial metabolomics has gained a significant interest as bacteria serve to provide a better subject or model at systems level. The approach in metabolomics is categorized into untargeted and targeted which serves different paradigms of interest. Nevertheless, the bottleneck in metabolomics has been the sample or metabolite preparation method. A custom-made method and design for a particular species or strain of bacteria might be necessary as most studies generally refer to other bacteria or even yeast and fungi that may lead to unreliable analysis. The paramount aspect of metabolomics design comprises sample harvesting, quenching, and metabolite extraction procedures. Depending on the type of samples and research objective, each step must be at optimal conditions which are significantly important in determining the final output. To date, there are no standardized nor single designated protocols that have been established for a specific bacteria strain for untargeted and targeted approaches. In this paper, the existing and current developments of sample preparation methods of bacterial metabolomics used in both approaches are reviewed. The review also highlights previous literature of optimized conditions used to propose the most ideal methods for metabolite preparation, particularly for bacterial cells. Advantages and limitations of methods are discussed for future improvement of bacterial metabolomics.

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Tranfo, Giovanna, Enrico Marchetti, Daniela Pigini, Alfredo Miccheli, Mariangela Spagnoli, Fabio Sciubba, Giorgia Conta, Alberta Tomassini, and Luigi Fattorini. "Targeted and untargeted metabolomics applied to occupational exposure to hyperbaric atmosphere." Toxicology Letters 328 (August 2020): 28–34. http://dx.doi.org/10.1016/j.toxlet.2020.03.022.

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Robbat, Albert, Nicole Kfoury, Eugene Baydakov, and Yuriy Gankin. "Optimizing targeted/untargeted metabolomics by automating gas chromatography/mass spectrometry workflows." Journal of Chromatography A 1505 (July 2017): 96–105. http://dx.doi.org/10.1016/j.chroma.2017.05.017.

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Kelly, Patricia E., H. Jene Ng, Gillian Farrell, Shona McKirdy, Richard K. Russell, Richard Hansen, Zahra Rattray, Konstantinos Gerasimidis, and Nicholas J. W. Rattray. "An Optimised Monophasic Faecal Extraction Method for LC-MS Analysis and Its Application in Gastrointestinal Disease." Metabolites 12, no. 11 (November 14, 2022): 1110. http://dx.doi.org/10.3390/metabo12111110.

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Liquid chromatography coupled with mass spectrometry (LC-MS) metabolomic approaches are widely used to investigate underlying pathogenesis of gastrointestinal disease and mechanism of action of treatments. However, there is an unmet requirement to assess faecal metabolite extraction methods for large-scale metabolomics studies. Current methods often rely on biphasic extractions using harmful halogenated solvents, making automation and large-scale studies challenging. The present study reports an optimised monophasic faecal extraction protocol that is suitable for untargeted and targeted LC-MS analyses. The impact of several experimental parameters, including sample weight, extraction solvent, cellular disruption method, and sample-to-solvent ratio, were investigated. It is suggested that a 50 mg freeze-dried faecal sample should be used in a methanol extraction (1:20) using bead beating as the means of cell disruption. This is revealed by a significant increase in number of metabolites detected, improved signal intensity, and wide metabolic coverage given by each of the above extraction parameters. Finally, we addressed the applicability of the method on faecal samples from patients with Crohn’s disease (CD) and coeliac disease (CoD), two distinct chronic gastrointestinal diseases involving metabolic perturbations. Untargeted and targeted metabolomic analysis demonstrated the ability of the developed method to detect and stratify metabolites extracted from patient groups and healthy controls (HC), highlighting characteristic changes in the faecal metabolome according to disease. The method developed is, therefore, suitable for the analysis of patients with gastrointestinal disease and can be used to detect and distinguish differences in the metabolomes of CD, CoD, and HC.

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Li, Yangyang, Wei Zhu, Qingyuan Xiang, Jeongim Kim, Craig Dufresne, Yufeng Liu, Tianlai Li, and Sixue Chen. "Creation of a Plant Metabolite Spectral Library for Untargeted and Targeted Metabolomics." International Journal of Molecular Sciences 24, no. 3 (January 23, 2023): 2249. http://dx.doi.org/10.3390/ijms24032249.

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Large-scale high throughput metabolomic technologies are indispensable components of systems biology in terms of discovering and defining the metabolite parts of the system. However, the lack of a plant metabolite spectral library limits the metabolite identification of plant metabolomic studies. Here, we have created a plant metabolite spectral library using 544 authentic standards, which increased the efficiency of identification for untargeted metabolomic studies. The process of creating the spectral library was described, and the mzVault library was deposited in the public repository for free download. Furthermore, based on the spectral library, we describe a process of creating a pseudo-targeted method, which was applied to a proof-of-concept study of Arabidopsis leaf extracts. As authentic standards become available, more metabolite spectra can be easily incorporated into the spectral library to improve the mzVault package.

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Lee, Yu Ra, Eunju Im, Haksoon Kim, Bark Lynn Lew, Woo-Young Sim, Jeongae Lee, Han Bin Oh, Ki Jung Paeng, Jongki Hong, and Bong Chul Chung. "Untargeted Metabolomics and Steroid Signatures in Urine of Male Pattern Baldness Patients after Finasteride Treatment for a Year." Metabolites 10, no. 4 (March 30, 2020): 131. http://dx.doi.org/10.3390/metabo10040131.

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Male pattern baldness (MPB) has been associated with dihydrotestosterone (DHT) expression. Finasteride treats MPB by inhibiting 5-alpha reductase and blocking DHT production. In this study, we aimed to identify metabolic differences in urinary metabolomics profiles between MPB patients after a one-year treatment with finasteride and healthy controls. Untargeted and targeted metabolomics profiling was performed using liquid chromatography-mass spectrometry (LC-MS). We hypothesized that there would be changes in overall metabolite concentrations, especially steroids, in the urine of hair loss patients treated with finasteride and normal subjects. Untargeted analysis indicated differences in steroid hormone biosynthesis. Therefore, we conducted targeted profiling for steroid hormone biosynthesis to identify potential biomarkers, especially androgens and estrogens. Our study confirmed the differences in the concentration of urinary androgens and estrogens between healthy controls and MPB patients. Moreover, the effect of finasteride was confirmed by the DHT/T ratio in urine samples of MPB patients. Our metabolomics approach provided insight into the physiological alterations in MPB patients who have been treated with finasteride for a year and provided evidence for the association of finasteride and estrogen levels. Through a targeted approach, our results suggest that urinary estrogens must be studied in relation to MPB and post-finasteride syndrome.

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Darshi, Manjula, Benjamin Van Espen, and Kumar Sharma. "Metabolomics in Diabetic Kidney Disease: Unraveling the Biochemistry of a Silent Killer." American Journal of Nephrology 44, no. 2 (2016): 92–103. http://dx.doi.org/10.1159/000447954.

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The development of new therapies for chronic diseases, such as diabetic kidney disease (DKD), will continue to be hampered by lack of sufficient biomarkers that will provide insights and will be responsive to treatment interventions. The recent application of metabolomic technologies, such as nuclear magnetic resonance and mass spectroscopy, has allowed large-scale analysis of small molecules to be interrogated in a targeted or untargeted manner. Recent advances from both human and animal studies that have arisen from metabolomic analysis have recognized that mitochondrial function and fatty acid oxidation play key roles in the development and progression of DKD. Although many challenges in the technology for clinical chronic kidney disease (CKD) are yet to be validated, there will very likely be ongoing major contributions of metabolomics to develop new biochemical understanding for diabetic and CKD. The clinical application of metabolomics and accompanying bioinformatic tools will likely be a cornerstone of personalized medicine triumphs for CKD.

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Yang, Jieping, Venu Lagishetty, Patrick Kurnia, Susanne M. Henning, Aaron I. Ahdoot, and Jonathan P. Jacobs. "Microbial and Chemical Profiles of Commercial Kombucha Products." Nutrients 14, no. 3 (February 5, 2022): 670. http://dx.doi.org/10.3390/nu14030670.

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Kombucha is an increasingly popular functional beverage that has gained attention for its unique combination of phytochemicals, metabolites, and microbes. Previous chemical and microbial composition analyses of kombucha have mainly focused on understanding their changes during fermentation. Very limited information is available regarding nutrient profiles of final kombucha products in the market. In this study, we compared the major chemicals (tea polyphenols, caffeine), antioxidant properties, microbial and metabolomic profiles of nine commercial kombucha products using shotgun metagenomics, internal transcribed spacer sequencing, untargeted metabolomics, and targeted chemical assays. All of the nine kombucha products showed similar acidity but great differences in chemicals, metabolites, microbes, and antioxidant activities. Most kombucha products are dominated by the probiotic Bacillus coagulans or bacteria capable of fermentation including Lactobacillus nagelii, Gluconacetobacter, Gluconobacter, and Komagataeibacter species. We found that all nine kombuchas also contained varying levels of enteric bacteria including Bacteroides thetaiotamicron, Escherischia coli, Enterococcus faecalis, Bacteroides fragilis, Enterobacter cloacae complex, and Akkermansia muciniphila. The fungal composition of kombucha products was characterized by predominance of fermenting yeast including Brettanomyces species and Cyberlindnera jadinii. Kombucha varied widely in chemical content assessed by global untargeted metabolomics, with metabolomic variation being significantly associated with metagenomic profiles. Variation in tea bases, bacteria/yeast starter cultures, and duration of fermentation may all contribute to the observed large differences in the microbial and chemical profiles of final kombucha products.

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Chaby, Lauren E., Heather C. Lasseter, Kévin Contrepois, Reza M. Salek, Christoph W. Turck, Andrew Thompson, Timothy Vaughan, Magali Haas, and Andreas Jeromin. "Cross-Platform Evaluation of Commercially Targeted and Untargeted Metabolomics Approaches to Optimize the Investigation of Psychiatric Disease." Metabolites 11, no. 9 (September 8, 2021): 609. http://dx.doi.org/10.3390/metabo11090609.

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Metabolomics methods often encounter trade-offs between quantification accuracy and coverage, with truly comprehensive coverage only attainable through a multitude of complementary assays. Due to the lack of standardization and the variety of metabolomics assays, it is difficult to integrate datasets across studies or assays. To inform metabolomics platform selection, with a focus on posttraumatic stress disorder (PTSD), we review platform use and sample sizes in psychiatric metabolomics studies and then evaluate five prominent metabolomics platforms for coverage and performance, including intra-/inter-assay precision, accuracy, and linearity. We found performance was variable between metabolite classes, but comparable across targeted and untargeted approaches. Within all platforms, precision and accuracy were highly variable across classes, ranging from 0.9–63.2% (coefficient of variation) and 0.6–99.1% for accuracy to reference plasma. Several classes had high inter-assay variance, potentially impeding dissociation of a biological signal, including glycerophospholipids, organooxygen compounds, and fatty acids. Coverage was platform-specific and ranged from 16–70% of PTSD-associated metabolites. Non-overlapping coverage is challenging; however, benefits of applying multiple metabolomics technologies must be weighed against cost, biospecimen availability, platform-specific normative levels, and challenges in merging datasets. Our findings and open-access cross-platform dataset can inform platform selection and dataset integration based on platform-specific coverage breadth/overlap and metabolite-specific performance.

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Hwangbo, Nathan, Xinyu Zhang, Daniel Raftery, Haiwei Gu, Shu-Ching Hu, Thomas J. Montine, Joseph F. Quinn, et al. "Predictive Modeling of Alzheimer’s and Parkinson’s Disease Using Metabolomic and Lipidomic Profiles from Cerebrospinal Fluid." Metabolites 12, no. 4 (March 22, 2022): 277. http://dx.doi.org/10.3390/metabo12040277.

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In recent years, metabolomics has been used as a powerful tool to better understand the physiology of neurodegenerative diseases and identify potential biomarkers for progression. We used targeted and untargeted aqueous, and lipidomic profiles of the metabolome from human cerebrospinal fluid to build multivariate predictive models distinguishing patients with Alzheimer’s disease (AD), Parkinson’s disease (PD), and healthy age-matched controls. We emphasize several statistical challenges associated with metabolomic studies where the number of measured metabolites far exceeds sample size. We found strong separation in the metabolome between PD and controls, as well as between PD and AD, with weaker separation between AD and controls. Consistent with existing literature, we found alanine, kynurenine, tryptophan, and serine to be associated with PD classification against controls, while alanine, creatine, and long chain ceramides were associated with AD classification against controls. We conducted a univariate pathway analysis of untargeted and targeted metabolite profiles and find that vitamin E and urea cycle metabolism pathways are associated with PD, while the aspartate/asparagine and c21-steroid hormone biosynthesis pathways are associated with AD. We also found that the amount of metabolite missingness varied by phenotype, highlighting the importance of examining missing data in future metabolomic studies.

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Lin, Chuwei, Aneirin Alan Lott, Wei Zhu, Craig P. Dufresne, and Sixue Chen. "Mitogen-Activated Protein Kinase 4-Regulated Metabolic Networks." International Journal of Molecular Sciences 23, no. 2 (January 14, 2022): 880. http://dx.doi.org/10.3390/ijms23020880.

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Mitogen-activated protein kinase 4 (MPK4) was first identified as a negative regulator of systemic acquired resistance. It is also an important kinase involved in many other biological processes in plants, including cytokinesis, reproduction, and photosynthesis. Arabidopsis thaliana mpk4 mutant is dwarf and sterile. Previous omics studies including genomics, transcriptomics, and proteomics have revealed new functions of MPK4 in different biological processes. However, due to challenges in metabolomics, no study has touched upon the metabolomic profiles of the mpk4 mutant. What metabolites and metabolic pathways are potentially regulated by MPK4 are not known. Metabolites are crucial components of plants, and they play important roles in plant growth and development, signaling, and defense. Here we used targeted and untargeted metabolomics to profile metabolites in the wild type and the mpk4 mutant. We found that in addition to the jasmonic acid and salicylic acid pathways, MPK4 is involved in polyamine synthesis and photosynthesis. In addition, we also conducted label-free proteomics of the two genotypes. The integration of metabolomics and proteomics data allows for an insight into the metabolomic networks that are potentially regulated by MPK4.

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Jandrić, Z., M. Islam, D. K. Singh, and A. Cannavan. "Authentication of Indian citrus fruit/fruit juices by untargeted and targeted metabolomics." Food Control 72 (February 2017): 181–88. http://dx.doi.org/10.1016/j.foodcont.2015.10.044.

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Kim, Moo Jung, Mee Youn Lee, Jong Cheol Shon, Yong Sung Kwon, Kwang-Hyeon Liu, Choong Hwan Lee, and Kang-Mo Ku. "Untargeted and targeted metabolomics analyses of blackberries – Understanding postharvest red drupelet disorder." Food Chemistry 300 (December 2019): 125169. http://dx.doi.org/10.1016/j.foodchem.2019.125169.

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Koulis, Georgios A., Aristeidis S. Tsagkaris, Reza Aalizadeh, Marilena E. Dasenaki, Eleni I. Panagopoulou, Spyros Drivelos, Michał Halagarda, Constantinos A. Georgiou, Charalampos Proestos, and Nikolaos S. Thomaidis. "Honey Phenolic Compound Profiling and Authenticity Assessment Using HRMS Targeted and Untargeted Metabolomics." Molecules 26, no. 9 (May 8, 2021): 2769. http://dx.doi.org/10.3390/molecules26092769.

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Honey consumption is attributed to potentially advantageous effects on human health due to its antioxidant capacity as well as anti-inflammatory and antimicrobial activity, which are mainly related to phenolic compound content. Phenolic compounds are secondary metabolites of plants, and their content in honey is primarily affected by the botanical and geographical origin. In this study, a high-resolution mass spectrometry (HRMS) method was applied to determine the phenolic profile of various honey matrices and investigate authenticity markers. A fruitful sample set was collected, including honey from 10 different botanical sources (n = 51) originating from Greece and Poland. Generic liquid–liquid extraction using ethyl acetate as the extractant was used to apply targeted and non-targeted workflows simultaneously. The method was fully validated according to the Eurachem guidelines, and it demonstrated high accuracy, precision, and sensitivity resulting in the detection of 11 target analytes in the samples. Suspect screening identified 16 bioactive compounds in at least one sample, with abscisic acid isomers being the most abundant in arbutus honey. Importantly, 10 markers related to honey geographical origin were revealed through non-targeted screening and the application of advanced chemometric tools. In conclusion, authenticity markers and discrimination patterns were emerged using targeted and non-targeted workflows, indicating the impact of this study on food authenticity and metabolomic fields.

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Le Mao, Inès, Grégory Da Costa, and Tristan Richard. "<sup>1</sup>H-NMR metabolomics for wine screening and analysis." OENO One 57, no. 1 (January 3, 2023): 15–31. http://dx.doi.org/10.20870/oeno-one.2023.57.1.7134.

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The number of metabolomic studies has grown steadily over the last twenty years. Among the fields of application, food sciences are broadly represented. Proton NMR (1H-NMR) is a commonly used technique for metabolomics and is particularly suitable for wine analysis, because the major wine constituents are highly dependent on biotic and abiotic conditions. 1H-NMR-based metabolomics were used first to guarantee the authenticity of wines, and more recently to determine the impact of viticultural or oenological practices using both targeted and untargeted protocols. This state-of-the-art review covers the different analytical methodologies developed to ensure wine traceability from sample preparation to 1H-NMR spectrum analysis. The potential applications of 1H-NMR spectroscopy in oenology, from wine authenticity control to the monitoring of winemaking, are described. The challenges and perspectives of the deployment of NMR for oenological monitoring are also discussed.

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Bhargava, Pavan, and Peter A. Calabresi. "Metabolomics in multiple sclerosis." Multiple Sclerosis Journal 22, no. 4 (January 11, 2016): 451–60. http://dx.doi.org/10.1177/1352458515622827.

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Multiple sclerosis (MS) is a chronic demyelinating disorder of the central nervous system with inflammatory and degenerative components. The cause of MS remains unknown although genetic and environmental factors appear to play a role in its etiopathogenesis. Metabolomics is a new “omics” technology that aims at measuring small molecules in various biological matrices and can provide information that is not readily obtained from genomics, transcriptomics, or proteomics. Currently, several different analytical platforms exist for metabolomics, and both untargeted and targeted approaches are being employed. Methods of analysis of metabolomics data are also being developed and no consensus currently exists on the optimal approach to analysis and interpretation of these data. Metabolomics has the potential to provide putative biomarkers, insights into the pathophysiology of the disease, and to aid in precision medicine for patients with MS.

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Rubić, Ivana, Richard Burchmore, Stefan Weidt, Clement Regnault, Josipa Kuleš, Renata Barić Rafaj, Tomislav Mašek, et al. "Multi Platforms Strategies and Metabolomics Approaches for the Investigation of Comprehensive Metabolite Profile in Dogs with Babesia canis Infection." International Journal of Molecular Sciences 23, no. 3 (January 29, 2022): 1575. http://dx.doi.org/10.3390/ijms23031575.

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Canine babesiosis is an important tick-borne disease worldwide, caused by parasites of the Babesia genus. Although the disease process primarily affects erythrocytes, it may also have multisystemic consequences. The goal of this study was to explore and characterize the serum metabolome, by identifying potential metabolites and metabolic pathways in dogs naturally infected with Babesia canis using liquid and gas chromatography coupled to mass spectrometry. The study included 12 dogs naturally infected with B. canis and 12 healthy dogs. By combining three different analytical platforms using untargeted and targeted approaches, 295 metabolites were detected. The untargeted ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) metabolomics approach identified 64 metabolites, the targeted UHPLC-MS/MS metabolomics approach identified 205 metabolites, and the GC-MS metabolomics approach identified 26 metabolites. Biological functions of differentially abundant metabolites indicate the involvement of various pathways in canine babesiosis including the following: glutathione metabolism; alanine, aspartate, and glutamate metabolism; glyoxylate and dicarboxylate metabolism; cysteine and methionine metabolism; and phenylalanine, tyrosine, and tryptophan biosynthesis. This study confirmed that host–pathogen interactions could be studied by metabolomics to assess chemical changes in the host, such that the differences in serum metabolome between dogs with B. canis infection and healthy dogs can be detected with liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) methods. Our study provides novel insight into pathophysiological mechanisms of B. canis infection.

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Wang, Bingfeng, Shini Yang, Lei Xu, Xue Wang, Lu Mi, Kewen Wang, Xiaojun Liao, and Zhenzhen Xu. "Evaluation Study on Extraction of Anthocyanins from Red Cabbage Using High Pressure CO2 + H2O: A Fuzzy Logic Model and Metabolomic Analysis." Sustainability 14, no. 3 (January 25, 2022): 1369. http://dx.doi.org/10.3390/su14031369.

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In this work, a fuzzy logic model was developed to elucidate the extraction performance of high-pressure CO2 + H2O compared with traditional H2O extraction and aqueous ethanol extraction. The high-pressure CO2 + H2O group acquired the highest comprehensive score considering yield, quality and stability. Both targeted and untargeted metabolomics results proved that the polarity of water was slightly modified; in particular, with the evidence from the untargeted metabolomics data, a higher proportion of water-insoluble compounds (2-methylindole, 3-formylindole, guanine, tyrosine and tryptophan) obtained by high-pressure CO2 + H2O extraction compared with traditional H2O extraction has been reported for the first time. Finally, the “3I” extraction mechanism of high-pressure CO2 + H2O is proposed, which offers an improvement in the solid–liquid mass transfer efficiency of phytochemicals, improving the polarity of solution and the isolation of O2.

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Stevens, Victoria L., Elise Hoover, Ying Wang, and Krista A. Zanetti. "Pre-Analytical Factors that Affect Metabolite Stability in Human Urine, Plasma, and Serum: A Review." Metabolites 9, no. 8 (July 25, 2019): 156. http://dx.doi.org/10.3390/metabo9080156.

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Metabolomics provides a comprehensive assessment of numerous small molecules in biological samples. As it integrates the effects of exogenous exposures, endogenous metabolism, and genetic variation, metabolomics is well-suited for studies examining metabolic profiles associated with a variety of chronic diseases. In this review, we summarize the studies that have characterized the effects of various pre-analytical factors on both targeted and untargeted metabolomic studies involving human plasma, serum, and urine and were published through 14 January 2019. A standardized protocol was used for extracting data from full-text articles identified by searching PubMed and EMBASE. For plasma and serum samples, metabolomic profiles were affected by fasting status, hemolysis, collection time, processing delays, particularly at room temperature, and repeated freeze/thaw cycles. For urine samples, collection time and fasting, centrifugation conditions, filtration and the use of additives, normalization procedures and multiple freeze/thaw cycles were found to alter metabolomic findings. Consideration of the effects of pre-analytical factors is a particularly important issue for epidemiological studies where samples are often collected in nonclinical settings and various locations and are subjected to time and temperature delays prior being to processed and frozen for storage.

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Montis, Andrea, Florence Souard, Cédric Delporte, Piet Stoffelen, Caroline Stévigny, and Pierre Van Antwerpen. "Targeted and Untargeted Mass Spectrometry-Based Metabolomics for Chemical Profiling of Three Coffee Species." Molecules 27, no. 10 (May 14, 2022): 3152. http://dx.doi.org/10.3390/molecules27103152.

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While coffee beans have been studied for many years, researchers are showing a growing interest in coffee leaves and by-products, but little information is currently available on coffee species other than Coffea arabica and Coffea canephora. The aim of this work was to perform a targeted and untargeted metabolomics study on Coffea arabica, Coffea canephora and Coffea anthonyi. The application of the recent high-resolution mass spectrometry-based metabolomics tools allowed us to gain a clear overview of the main differences among the coffee species. The results showed that the leaves and fruits of Coffea anthonyi had a different metabolite profile when compared to the two other species. In Coffea anthonyi, caffeine levels were found in lower concentrations while caffeoylquinic acid and mangiferin-related compounds were found in higher concentrations. A large number of specialized metabolites can be found in Coffea anthonyi tissues, making this species a valid candidate for innovative healthcare products made with coffee extracts.

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Bingol, Kerem. "Recent Advances in Targeted and Untargeted Metabolomics by NMR and MS/NMR Methods." High-Throughput 7, no. 2 (April 18, 2018): 9. http://dx.doi.org/10.3390/ht7020009.

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Shen, Shanshan, Junlan Huang, Tiehan Li, Yuming Wei, Shanshan Xu, Yujie Wang, and Jingming Ning. "Untargeted and targeted metabolomics reveals potential marker compounds of an tea during storage." LWT 154 (January 2022): 112791. http://dx.doi.org/10.1016/j.lwt.2021.112791.

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Garcia-Aloy, Mar, Nelli Groff, Domenico Masuero, Mauro Nisi, Antonio Franco, Furio Battelini, Urska Vrhovsek, and Fulvio Mattivi. "Exploratory Analysis of Commercial Olive-Based Dietary Supplements Using Untargeted and Targeted Metabolomics." Metabolites 10, no. 12 (December 19, 2020): 516. http://dx.doi.org/10.3390/metabo10120516.

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The market of olive-based dietary supplements (OBDS) is composed of a broad range of natural extracts claiming different health effects and often sold without a clear statement on their chemical composition. The aim of this survey was to characterize the chemical profiles of 14 commercially available OBDS. As many as 378 compounds were tentatively annotated in the analyzed samples. Although for most of metabolites the annotation at level I was prevented due to the lack of the analytical standard, the spectra obtained from high-resolution tandem mass spectrometry (MS/MS) measurements were very informative, allowing annotation of dozens of metabolites at level II or III. A targeted method allowed the quantification of 26 selected compounds. A large qualitative and quantitative variability was observed. The products obtained from buds by glyceric maceration were those with the lowest concentrations of all the quantified elements. The dose of 5 mg of hydroxytyrosol, corresponding to the European Food Safety Authority (EFSA) health claim, was only reached by four products, all of them originating from the olive fruit or the leaves. If we also take into consideration oleuropein, two additional products provide this daily amount. This work demonstrates the high complexity and diversity in the composition of OBDS.

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Fernández-Peralbo, M. A., and M. D. Luque de Castro. "Preparation of urine samples prior to targeted or untargeted metabolomics mass-spectrometry analysis." TrAC Trends in Analytical Chemistry 41 (December 2012): 75–85. http://dx.doi.org/10.1016/j.trac.2012.08.011.

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Mrakic-Sposta, Simona, Gerardo Bosco, and Alessandra Vezzoli. "Commentary on: “Targeted and untargeted metabolomics applied to occupational exposure to hyperbaric atmosphere”." Toxicology Letters 330 (September 2020): 71–72. http://dx.doi.org/10.1016/j.toxlet.2020.05.021.

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Cajka, Tomas, and Oliver Fiehn. "Toward Merging Untargeted and Targeted Methods in Mass Spectrometry-Based Metabolomics and Lipidomics." Analytical Chemistry 88, no. 1 (December 16, 2015): 524–45. http://dx.doi.org/10.1021/acs.analchem.5b04491.

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Longnecker, Krista, and Elizabeth B. Kujawinski. "Intracellular Metabolites in Marine Microorganisms during an Experiment Evaluating Microbial Mortality." Metabolites 10, no. 3 (March 12, 2020): 105. http://dx.doi.org/10.3390/metabo10030105.

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Metabolomics is a tool with immense potential for providing insight into the impact of biological processes on the environment. Here, we used metabolomics methods to characterize intracellular metabolites within marine microorganisms during a manipulation experiment that was designed to test the impact of two sources of microbial mortality, protozoan grazing and viral lysis. Intracellular metabolites were analyzed with targeted and untargeted mass spectrometry methods. The treatment with reduced viral mortality showed the largest changes in metabolite concentrations, although there were organic compounds that shifted when the impact of protozoan grazers was reduced. Intracellular concentrations of guanine, phenylalanine, glutamic acid, and ectoine presented significant responses to changes in the source of mortality. Unexpectedly, variability in metabolite concentrations were not accompanied by increases in microbial abundance which indicates that marine microorganisms altered their internal organic carbon stores without changes in biomass or microbial growth. We used Weighted Correlation Network Analysis (WGCNA) to identify correlations between the targeted and untargeted mass spectrometry data. This analysis revealed multiple unknown organic compounds were correlated with compatible solutes, also called osmolytes or chemical chaperones, which emphasizes the dominant role of compatible solutes in marine microorganisms.

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Takis, Panteleimon, Antonio Taddei, Riccardo Pini, Stefano Grifoni, Francesca Tarantini, Paolo Bechi, and Claudio Luchinat. "Fingerprinting Acute Digestive Diseases by Untargeted NMR Based Metabolomics." International Journal of Molecular Sciences 19, no. 11 (October 23, 2018): 3288. http://dx.doi.org/10.3390/ijms19113288.

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Precision medicine may significantly contribute to rapid disease diagnosis and targeted therapy, but relies on the availability of detailed, subject specific, clinical information. Proton nuclear magnetic resonance (1H–NMR) spectroscopy of body fluids can extract individual metabolic fingerprints. Herein, we studied 64 patients admitted to the Florence main hospital emergency room with severe abdominal pain. A blood sample was drawn from each patient at admission, and the corresponding sera underwent 1H–NMR metabolomics fingerprinting. Unsupervised Principal Component Analysis (PCA) analysis showed a significant discrimination between a group of patients with symptoms of upper abdominal pain and a second group consisting of patients with diffuse abdominal/intestinal pain. Prompted by this observation, supervised statistical analysis (Orthogonal Partial Least Squares–Discriminant Analysis (OPLS-DA)) showed a very good discrimination (>90%) between the two groups of symptoms. This is a surprising finding, given that neither of the two symptoms points directly to a specific disease among those studied here. Actually herein, upper abdominal pain may result from either symptomatic gallstones, cholecystitis, or pancreatitis, while diffuse abdominal/intestinal pain may result from either intestinal ischemia, strangulated obstruction, or mechanical obstruction. Although limited by the small number of samples from each of these six conditions, discrimination of these diseases was attempted. In the first symptom group, >70% discrimination accuracy was obtained among symptomatic gallstones, pancreatitis, and cholecystitis, while for the second symptom group >85% classification accuracy was obtained for intestinal ischemia, strangulated obstruction, and mechanical obstruction. No single metabolite stands up as a possible biomarker for any of these diseases, while the contribution of the whole 1H–NMR serum fingerprint seems to be a promising candidate, to be confirmed on larger cohorts, as a first-line discriminator for these diseases.

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Shah, Rohan M., Snehal R. Jadhav, Laura Phan, Kelton Tremellen, Cuong D. Tran, and David J. Beale. "Plasma Metabolic and Lipidomic Fingerprinting of Individuals with Increased Intestinal Permeability." Metabolites 12, no. 4 (March 29, 2022): 302. http://dx.doi.org/10.3390/metabo12040302.

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The dual-sugar intestinal permeability test is a commonly used test to assess changes in gut barrier function. However, it does not identify functional changes and the exact mechanism of damage caused by the increased intestinal permeability. This study aims to explore the application of untargeted metabolomics and lipidomics to identify markers of increased intestinal permeability. Fifty fasting male participants (18–50 years) attended a single visit to conduct the following procedures: assessment of anthropometric measures, assessment of gastrointestinal symptoms, intestinal permeability test, and assessment of blood samples 90 min post-administration of the intestinal permeability test. Rhamnose and lactulose were analysed using gas chromatography-mass spectrometry (GC-MS). Untargeted polar metabolites and lipidomics were assessed by liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QToF MS). There was an elevated lactulose/rhamnose ratio in 27 subjects, indicating increased permeability compared to the remaining 23 control subjects. There were no significant differences between groups in characteristics such as age, body mass index (BMI), weight, height, and waist conference. Fourteen metabolites from the targeted metabolomics data were identified as statistically significant in the plasma samples from intestinal permeability subjects. The untargeted metabolomics and lipidomics analyses yielded fifteen and fifty-one statistically significant features, respectively. Individuals with slightly elevated intestinal permeability had altered energy, nucleotide, and amino acid metabolism, in addition to increased glutamine levels. Whether these biomarkers may be used to predict the early onset of leaky gut warrants further investigation.

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Palevich, Nikola, Paul H. Maclean, Paul M. Candy, Wendy Taylor, Ivona Mladineo, and Mingshu Cao. "Untargeted Multimodal Metabolomics Investigation of the Haemonchus contortus Exsheathment Secretome." Cells 11, no. 16 (August 15, 2022): 2525. http://dx.doi.org/10.3390/cells11162525.

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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.

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Ten-Doménech, Isabel, Teresa Martínez-Sena, Marta Moreno-Torres, Juan Daniel Sanjuan-Herráez, José V. Castell, Anna Parra-Llorca, Máximo Vento, Guillermo Quintás, and Julia Kuligowski. "Comparing Targeted vs. Untargeted MS2 Data-Dependent Acquisition for Peak Annotation in LC–MS Metabolomics." Metabolites 10, no. 4 (March 26, 2020): 126. http://dx.doi.org/10.3390/metabo10040126.

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One of the most widely used strategies for metabolite annotation in untargeted LCMS is based on the analysis of MSn spectra acquired using data-dependent acquisition (DDA), where precursor ions are sequentially selected from MS scans based on user-selected criteria. However, the number of MSn spectra that can be acquired during a chromatogram is limited and a trade-off between analytical speed, sensitivity and coverage must be ensured. In this research, we compare four different strategies for automated MS2 DDA, which can be easily implemented in the frame of standard QA/QC workflows for untargeted LC–MS. These strategies consist of (i) DDA in the MS working range; (ii) iterated DDA split into several m/z intervals; (iii) dynamic iterated DDA of (pre)selected potentially informative features; and (iv) dynamic iterated DDA of (pre)annotated metabolic features using a reference database. Their performance was assessed using the analysis of human milk samples as model example by comparing the percentage of LC–MS features selected as the precursor ion for MS2, the number, and class of annotated features, the speed and confidence of feature annotation, and the number of LC runs required.

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Kim, Suji, Won-Jun Jang, Hyerim Yu, Jihyun Kim, Sang-Ki Lee, Chul-Ho Jeong, and Sooyeun Lee. "Revealing Metabolic Perturbation Following Heavy Methamphetamine Abuse by Human Hair Metabolomics and Network Analysis." International Journal of Molecular Sciences 21, no. 17 (August 21, 2020): 6041. http://dx.doi.org/10.3390/ijms21176041.

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Abstract:

Methamphetamine (MA) is a highly addictive central nervous system stimulant. Drug addiction is not a static condition but rather a chronically relapsing disorder. Hair is a valuable and stable specimen for chronic toxicological monitoring as it retains toxicants and metabolites. The primary focus of this study was to discover the metabolic effects encompassing diverse pathological symptoms of MA addiction. Therefore, metabolic alterations were investigated in human hair following heavy MA abuse using both targeted and untargeted mass spectrometry and through integrated network analysis. The statistical analyses (t-test, variable importance on projection score, and receiver-operator characteristic curve) demonstrated that 32 metabolites (in targeted metabolomics) as well as 417 and 224 ion features (in positive and negative ionization modes of untargeted metabolomics, respectively) were critically dysregulated. The network analysis showed that the biosynthesis or metabolism of lipids, such as glycosphingolipids, sphingolipids, glycerophospholipids, and ether lipids, as well as the metabolism of amino acids (glycine, serine and threonine; cysteine and methionine) is affected by heavy MA abuse. These findings reveal crucial metabolic effects caused by MA addiction, with emphasis on the value of human hair as a diagnostic specimen for determining drug addiction, and will aid in identifying robust diagnostic markers and therapeutic targets.

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Journal articles on the topic 'Targeted and untargeted metabolomics'

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