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Добірка наукової літератури з теми "Metabolomic, NMR, biomedical research, biochemistry"

Автор: Grafiati

Опубліковано: 10 березня 2023

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Статті в журналах з теми "Metabolomic, NMR, biomedical research, biochemistry"

Cardoso, Sara, Telma Afonso, Marcelo Maraschin, and Miguel Rocha. "WebSpecmine: A Website for Metabolomics Data Analysis and Mining." Metabolites 9, no. 10 (October 19, 2019): 237. http://dx.doi.org/10.3390/metabo9100237.

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Metabolomics data analysis is an important task in biomedical research. The available tools do not provide a wide variety of methods and data types, nor ways to store and share data and results generated. Thus, we have developed WebSpecmine to overcome the aforementioned limitations. WebSpecmine is a web-based application designed to perform the analysis of metabolomics data based on spectroscopic and chromatographic techniques (NMR, Infrared, UV-visible, and Raman, and LC/GC-MS) and compound concentrations. Users, even those not possessing programming skills, can access several analysis methods including univariate, unsupervised and supervised multivariate statistical analysis, as well as metabolite identification and pathway analysis, also being able to create accounts to store their data and results, either privately or publicly. The tool’s implementation is based in the R project, including its shiny web-based framework. Webspecmine is freely available, supporting all major browsers. We provide abundant documentation, including tutorials and a user guide with case studies.

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Nandania, Jatin, Gopal Peddinti, Alberto Pessia, Meri Kokkonen, and Vidya Velagapudi. "Validation and Automation of a High-Throughput Multitargeted Method for Semiquantification of Endogenous Metabolites from Different Biological Matrices Using Tandem Mass Spectrometry." Metabolites 8, no. 3 (August 5, 2018): 44. http://dx.doi.org/10.3390/metabo8030044.

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The use of metabolomics profiling to understand the metabolism under different physiological states has increased in recent years, which created the need for robust analytical platforms. Here, we present a validated method for targeted and semiquantitative analysis of 102 polar metabolites that cover major metabolic pathways from 24 classes in a single 17.5-min assay. The method has been optimized for a wide range of biological matrices from various organisms, and involves automated sample preparation and data processing using an inhouse developed R-package. To ensure reliability, the method was validated for accuracy, precision, selectivity, specificity, linearity, recovery, and stability according to European Medicines Agency guidelines. We demonstrated an excellent repeatability of retention times (CV < 4%), calibration curves (R2 ≥ 0.980) in their respective wide dynamic concentration ranges (CV < 3%), and concentrations (CV < 25%) of quality control samples interspersed within 25 batches analyzed over a period of one year. The robustness was demonstrated through a high correlation between metabolite concentrations measured using our method and the NIST reference values (R2 = 0.967), including cross-platform comparability against the BIOCRATES AbsoluteIDQp180 kit (R2 = 0.975) and NMR analyses (R2 = 0.884). We have shown that our method can be successfully applied in many biomedical research fields and clinical trials, including epidemiological studies for biomarker discovery. In summary, a thorough validation demonstrated that our method is reproducible, robust, reliable, and suitable for metabolomics studies.

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Emwas, Abdul-Hamid, Raja Roy, Ryan T. McKay, Leonardo Tenori, Edoardo Saccenti, G. A. Nagana Gowda, Daniel Raftery, et al. "NMR Spectroscopy for Metabolomics Research." Metabolites 9, no. 7 (June 27, 2019): 123. http://dx.doi.org/10.3390/metabo9070123.

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Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.

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Yilmaz, Ali, and Marcel Utz. "Characterisation of oxygen permeation into a microfluidic device for cell culture by in situ NMR spectroscopy." Lab on a Chip 16, no. 11 (2016): 2079–85. http://dx.doi.org/10.1039/c6lc00396f.

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Date, Yasuhiro, Chiaki Ishikawa, Makoto Umeda, Yusuke Tarumoto, Megumi Okubo, Yasuaki Tamura, and Hiroshi Ono. "Sugarcane Metabolome Compositional Stability in Pretreatment Processes for NMR Measurements." Metabolites 12, no. 9 (September 14, 2022): 862. http://dx.doi.org/10.3390/metabo12090862.

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Sugarcane is essential for global sugar production and its compressed juice is a key raw material for industrial products. Sugarcane juice includes various metabolites with abundances and compositional balances influencing product qualities and functionalities. Therefore, understanding the characteristic features of the sugarcane metabolome is important. However, sugarcane compositional variability and stability, even in pretreatment processes for nuclear magnetic resonance (NMR)-based metabolomic studies, remains elusive. The objective of this study is to evaluate sugarcane juice metabolomic variability affected by centrifugation, filtration, and thermal pretreatments, as well as the time-course changes for determining optimal conditions for NMR-based metabolomic approach. The pretreatment processes left the metabolomic compositions unchanged, indicating that these pretreatments are compatible with one another and the studied metabolomes are comparable. The thermal processing provided stability to the metabolome for more than 32 h at room temperature. Based on the determined analytical conditions, we conducted an NMR-based metabolomic study to discriminate the differences in the harvest period and allowed for successfully identifying the characteristic metabolome. Our findings denote that NMR-based sugarcane metabolomics enable us to provide an opportunity to collect a massive amount of data upon collaboration between multiple researchers, resulting in the rapid construction of useful databases for both research purposes and industrial use.

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Bazzano, Marilena, Luca Laghi, Chenglin Zhu, Enrica Lotito, Stefano Sgariglia, Beniamino Tesei, and Fulvio Laus. "Exercise Induced Changes in Salivary and Serum Metabolome in Trained Standardbred, Assessed by 1H-NMR." Metabolites 10, no. 7 (July 21, 2020): 298. http://dx.doi.org/10.3390/metabo10070298.

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In the present study, data related to the metabolomics of saliva and serum in trained standardbred horses are provided for the first time. Metabolomic analysis allows to analyze all the metabolites within selected biofluids, providing a better understanding of biochemistry modifications related to exercise. On the basis of the current advances observed in metabolomic research on human athletes, we aimed to investigate the metabolites’ profile of serum and saliva samples collected from healthy standardbred horses and the relationship with physical exercise. Twelve trained standardbred horses were sampled for blood and saliva before (T0) and immediately after (T1) standardized exercise. Metabolomic analysis of both samples was performed by 1H-NMR spectroscopy. Forty-six metabolites in serum and 62 metabolites in saliva were detected, including alcohols, amino acids, organic acids, carbohydrates and purine derivatives. Twenty-six and 14 metabolites resulted to be significantly changed between T0 and T1 in serum and saliva, respectively. The findings of 2-hydroxyisobutyrate and 3-hydroxybutyrate in serum and GABA in equine saliva, as well as their modifications following exercise, provide new insights about the physiology of exercise in athletic horses. Glycerol might represent a novel biomarker for fitness evaluation in sport horses.

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Brennan, Lorraine. "Metabolomics in nutrition research–a powerful window into nutritional metabolism." Essays in Biochemistry 60, no. 5 (December 15, 2016): 451–58. http://dx.doi.org/10.1042/ebc20160029.

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Metabolomics is the study of small molecules present in biological samples. In recent years it has become evident that such small molecules, called metabolites, play a key role in the development of disease states. Furthermore, metabolomic applications can reveal information about alterations in certain metabolic pathways under different conditions. Data acquisition in metabolomics is usually performed using nuclear magnetic resonance (NMR)-based approaches or mass spectrometry (MS)-based approaches with a more recent trend including the application of multiple platforms in order to maximise the coverage in terms of metabolites measured. The application of metabolomics is rapidly increasing and the present review will highlight applications in nutrition research.

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Huang, Katherine, Natalie Thomas, Paul R. Gooley, and Christopher W. Armstrong. "Systematic Review of NMR-Based Metabolomics Practices in Human Disease Research." Metabolites 12, no. 10 (October 12, 2022): 963. http://dx.doi.org/10.3390/metabo12100963.

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Nuclear magnetic resonance (NMR) spectroscopy is one of the principal analytical techniques for metabolomics. It has the advantages of minimal sample preparation and high reproducibility, making it an ideal technique for generating large amounts of metabolomics data for biobanks and large-scale studies. Metabolomics is a popular “omics” technology and has established itself as a comprehensive exploratory biomarker tool; however, it has yet to reach its collaborative potential in data collation due to the lack of standardisation of the metabolomics workflow seen across small-scale studies. This systematic review compiles the different NMR metabolomics methods used for serum, plasma, and urine studies, from sample collection to data analysis, that were most popularly employed over a two-year period in 2019 and 2020. It also outlines how these methods influence the raw data and the downstream interpretations, and the importance of reporting for reproducibility and result validation. This review can act as a valuable summary of NMR metabolomic workflows that are actively used in human biofluid research and will help guide the workflow choice for future research.

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Alborghetti, Marcos Rodrigo, Maria Elvira P. Corrêa, Andreia Aparecida da Silva, Eliana C. M. Miranda, Carmino A. De Souza, Mauricio L. Sforça, and Ana Carolina de Mattos Zeri. "Metabolomic Model For Chronic Gvhd Diagnosis." Blood 122, no. 21 (November 15, 2013): 3304. http://dx.doi.org/10.1182/blood.v122.21.3304.3304.

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Abstract Introduction Metabolomics is an essential tool for Translational Medicine, with a holistic non targeted approach, which provides information from the metabolic profile that can be used as a potential biomarker for a certain feature. The identification of biomarker profiles can be translated into simplified tests for the early diagnosis of diseases such as graft-versus-host disease (GVHD). Aim To evaluate the feasibility of a diagnostic protocol for chronic GVHD (cGVHD) based on the metabolic profile of blood serum from patients (pts) submitted to hematopoietic stem cell transplantation (HSCT). Methodology The study included a prospective, nested cohort of 41 adult pts who had undergone first full-match allogeneic HSCT at Hospital de Cl’nicas/ University of Campinas between August, 2011-January, 2013 and had signed the Consent Form. Blood serum samples were prospectively collected on the day of hospitalization (D-8), day of transplantation (D0), NADIR phase (D+10) and D+100 post-HSCT. The Nuclear Magnetic Resonance (NMR)-based metabolomic experiments were performed at the Brazilian Biosciences National Laboratory (LNBio/CNPEM). Samples were previously filtered on a 3 kDa cut off filter, diluted 3X on 100 mM phosphate buffer pH 7.4, referenced with 10% D2O and 0.5 mM DSS (4,4-dimethyl-4-silapentane-1-sulfonic acid) for further absolute quantification of metabolites. The acquisition of 1D spectra was performed on a Agilent/Varian INOVA spectrometer operating at 1H resonance frequency of 600MHz. The spectra processing, identification and quantification of metabolites were performed by using the application package Chenomx NMR Suite and the target profiling approach (Chenomx, Inc). Samples from pts who developed chronic GVHD, at anytime, were marked as “cGVHD group”, and those who did not develop chronic GVHD, “cGVHD-free group” . Blood samples from pts who died up to 200 days after HSCT and did not develop chronic GVHD were excluded from the analysis, as were also all samples from pts whose sample collection was lacking at least in one period. T-tests (p<0.05) were applied at each sampling time in order to select metabolites and perform Principal Component Analysis (PCA), hierarchical clustering and calculate Receiver Operating Characteristic (ROC) curve for cGVHD diagnosis model using the software Pirouette¨ 4.0 (Infometrix, Inc) and the web tools MetaboAnalyst 2.0 and ROCCET. Results Median age was 41(18-69) years old and 61% were male. 18/41(44%) pts matched the inclusion criteria for the study. 6/18 (33%) pts had undergone cGVHD therapy. Seventy-three metabolites were identified and quantified in the blood serum samples. 8 metabolites were selected by T-test application at each studied time (2 metabolites from D-8, 2 from D0, 3 from D+10 and 1 from D+100). Using the selected metabolites the PCA showed clear separation between pts from “cGVHD” and “cGVHD-free” groups as well as hierarchical clustering (Fig. 1), confirmed by ROC analysis as a high sensitivity and specificity model for cGVHD diagnosis (AUC 0.99 and CI 0.93-1.00) (Fig. 2). Conclusion Metabolic differences were found in both studied groups. These differences may be used as a biomarker profile for cGVHD diagnosis up 100 days post-HSCT. Our results demonstrated that the statistical model using combined prospective time-series analysis is a powerful metabolomic model for early cGVHD diagnosis. Disclosures: Alborghetti: Sao Paulo Research Foundation: Research Funding. da Silva:Coordination for the Improvement of Higher Education Personnel (CAPES): Research Funding.

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Eom, Jun Sik, Shin Ja Lee, Hyun Sang Kim, You Young Choi, Sang Ho Kim, Yoo Gyung Lee, and Sung Sill Lee. "Metabolomics Comparison of Hanwoo (Bos taurus coreanae) Biofluids Using Proton Nuclear Magnetic Resonance Spectroscopy." Metabolites 10, no. 8 (August 14, 2020): 333. http://dx.doi.org/10.3390/metabo10080333.

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The aim of this study was to identify the metabolomic profiles of rumen fluid, serum, and urine from Hanwoo (Bos taurus coreanae), using proton nuclear magnetic resonance (1H-NMR) spectroscopy. In all, 189, 110, and 188 metabolites were identified in rumen fluid, serum, and urine, and 107, 49, and 99 were quantified, respectively. Organic acids, carbohydrates, and aliphatic acyclic compound metabolites were present at the highest concentrations in rumen fluid, serum, and urine, respectively. In addition, acetate, glucose, and urea were the most highly concentrated individual metabolites in rumen fluid, serum, and urine, respectively. In all, 77 metabolites were commonly identified, and 19 were quantified across three biofluids. Metabolic pathway analysis showed that the common quantified metabolites could provide relevant information about three main metabolic pathways, phenylalanine, tyrosine, and tryptophan biosynthesis; caffeine metabolism; and histidine metabolism. These results can be useful as reference values for future metabolomic research on Hanwoo biofluids in Korea.

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Більше джерел

Дисертації з теми "Metabolomic, NMR, biomedical research, biochemistry"

HOLLYFIELD, JENNIFER LYNNE. "DOSE-DEPENDENT EFFECTS OF OXYGEN ON METABOLISM IN RAT CORTICO-HIPPOCAMPAL BRAIN TISSUE SLICES." Wright State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=wright1242417163.

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Romick-Rosendale, Lindsey Elizabeth. "USE OF NMR-BASED METABONOMICS TO STUDY ANIMAL MODELS AND HUMAN DISEASE." Miami University / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=miami1321891202.

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Liu, Jianmin. "Structural Investigation of the Complex of Filamin A Repeat 21 with Integrin αIIb and β3 Cytoplasmic Tails – A Potential “Transmission” to Regulate Cell Migration". Cleveland State University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=csu1263314406.

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Marin, Cordoba Roberto. "Chromium Carcinogenesis: Characterization of DNA damaging Intermediates by EPR ³¹P NMR, HPLC, ESI-MS and Magnetic Susceptibility." Ohio University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1261417590.

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Shamaev, Alexei E. "Synthesis, Photochemical Properties and DNA Binding Studies of DNA Cleaving Agents Based on Chiral Dipyridine Dihydrodioxins Salts." Bowling Green State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1445859853.

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Licari, Cristina. "1H-NMR-based metabolomic applications in biomedical research." Doctoral thesis, 2020. http://hdl.handle.net/2158/1217996.

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NMR spectroscopy represents a powerful, versatile and reproducible technique for the analysis of complex biological matrices. In fact, virtually, all biologically relevant molecules are characterized by at least one NMR signal with a specific intensity, frequency (or chemical shift) and magnetic relaxation properties, all reflecting the chemical environment surrounding the detected nucleus. In a high-throughput vision of metabolomic analysis, the very high reproducibility, the minimal sample preparation required, and the possibility to simultaneously detect all metabolites presenting NMR active nuclei, make NMR spectroscopy one of the most suitable techniques for the analysis of any type of biological matrix, enabling the rapid and global evaluation of an NMR spectrum in its entirety or the determination of the concentrations of all metabolic features that are above the μM detection limit. The NMR versatility allowed a wide variety of metabolomic applications in life science research, especially for both human and veterinary biomedicine. As metabolites indicate intermediate and end-points of gene expression and cell activity, under the combined influence of external stimuli, metabolomics can provide a holistic approach to understand the phenotype of a certain biological system, holding promises for both clinical and precision medicine. In this context, the presented thesis aims at demonstrating the potential of untargeted NMR-based metabolomic approach in biomedical research, addressing different topics, mainly regarding the use of untargeted NMR-based metabolomic on body fluids to disentangle characteristic fingerprints and/or metabolic markers for different types of both human and animal diseases or healthy conditions; also with the aim of paving the way to personalized individual’s healthcare. Considering the occasional misunderstandings present in the literature about the different aims of “fingerprinting” and “profiling” approaches of the untargeted analysis, and the different tools to achieve them, this thesis also proposes a study where we demonstrate that the criticism on the main drawbacks of the commonly used bucketing procedure of NMR spectra are not valid when an untargeted metabolomic analysis is planned via a fingerprinting approach. In conclusion, the results presented in this thesis contribute to the demonstration that untargeted NMR-based metabolomics, coupled with biochemistry, analytical chemistry, bioinformatic tools and statistical analysis, can be considered as a comprehensive analytical technique with reasonable and actual prospects of being implemented in biomedical research.

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