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The Volatilome in Metabolomics
Published in Raquel Cumeras, Xavier Correig, Volatile organic compound analysis in biomedical diagnosis applications, 2018
Raquel Cumeras, Xavier Correig
The human metabolome database is a freely available electronic database containing detailed information about small molecule metabolites found in the human body. The database contains 42,003 metabolite entries including water-soluble and lipid soluble metabolites as well as metabolites that would be regarded as either abundant (> 1 uM) or relatively rare (<1 nM). Additionally, 5,701 protein sequences are linked to these metabolite entries. Even though HMBD integrates databases of almost all the human tissues or biofluids, it doesn’t have a specific entry for breath or volatilome.
Therapeutic Strategies and Future Research
Published in Mark A. Mentzer, Mild Traumatic Brain Injury, 2020
The Human Metabolome Database (HMDB) database, supported by the University of Alberta and Genome Canada (Human metabolome database version 2.5) contains links to chemical, clinical, and biochemical/molecular biological data, with links to protein and DNA sequences. This systems approach to biological studies promises rapid streamlining of previously tedious processes.
Methods of Metabolite Identification Using MS/MS Data
Published in Journal of Computer Information Systems, 2022
Myungjae Kwak, Kyungwoo Kang, Yingfeng Wang
Metabolites are the intermediate and end products of metabolism, which is the set of life-sustaining chemical reactions in living organisms.2 A metabolite is typically a small-molecular compound less than 1500 Da in the metabolome.2 A diverse set of metabolites exist in nature. For example, it was reported that there are more than 200,000 plant metabolites alone.3,4 The number of metabolites predicted in HMDB (Human Metabolome Database) 4.0 is. 114,1005 It is well known that physiological and pathological changes in human body are mapped to specific metabolic changes. For example, certain metabolic changes are identified in cancerous tissues.1,6 Once those mappings are completely identified, it would be possible to greatly improve disease diagnosis, prognosis, and selection of therapeutic strategies by profiling metabolites. Metabolomics is a scientific branch of studying the set of metabolites present within a living organism, cell, or tissue. It focuses on identifying the complete set of metabolites in a biological system.7 It also studies metabolic changes to disease, disease progression, medication, or environmental effects.7 Profiling metabolites can be used as a direct way of observing metabolic activities. Metabolomics is a study for detecting, identifying, and quantifying metabolites. It has advanced many medical and scientific areas such as microbiology8–10, pharmacy11–14, and medical science.15–19
An overview of the current progress, challenges, and prospects of human biomonitoring and exposome studies
Published in Journal of Toxicology and Environmental Health, Part B, 2019
Mariana Zuccherato Bocato, João Paulo Bianchi Ximenez, Christian Hoffmann, Fernando Barbosa
In metabolomics, raw data are subjected to a pre-processing step according to the type of analytical platform used. For NMR, data processing includes phasing, baseline correction, alignment, and normalization. Commercial software and algorithms such as PERCH (PERCH Solution Company Ltd.), ChenomxRMNSuite (Chenomx Inc.), MestReNova (MestreLab Research), MetaboLab, AutoFit, TopSpin (Bruker Corp.) and MATLAB (The MathWorks Inc.) are routinely employed. On the other hand, using MS techniques, data processing includes spectral deconvolution, dataset creation, grouping, alignment, filling of data gaps, normalization, and transformation of data (Sussulini 2017). The obtained data are preprocessed with the utilization of free tools such as XCMS, MZmine, MAVENeMetaboAnalyst, as well as commercial software SIMCA-P, SAS (Alden et al. 2017). Numerous databases are available to aid in the identification of metabolites (Human metabolome database (HMDB)), METLIN, NIST MS Library, KEGG (Kamburov et al. 2011; Wishart et al. 2007). However, a critical limitation of nontarget analysis of metabolites of exogenous origin such as pollutants is the lack of sufficient sensitivity of instrumentation used to obtain data (MS with higher resolution power, example q-TOF or Orbitrap). These analytes are usually found in clinical specimens in concentrations lower than femtogram.
Non-targeted metabolomics in sport and exercise science
Published in Journal of Sports Sciences, 2019
Liam M. Heaney, Kevin Deighton, Toru Suzuki
Through recent technological and methodological advances in the field of metabolomics, it has been possible to characterise, quantitate and identify an increasing number of analytes. Development and publication of open-source searchable metabolite databases have been possible through the increased availability of metabolite properties (e.g., molecular mass and analytical assay characteristics – discussed in more detail later). Perhaps the most relevant to human investigations is the Human Metabolome Database (HMDB) which was first published in 2007 (Wishart et al., 2007) and has since been updated, with the latest edition released in 2013 (Wishart et al., 2013). HMDB describes over 40,000 metabolites and each is represented with a “metabocard” that details associated chemical, biochemical, clinical and enzymatic data, with links to website resources of additional information (The Human Metabolome Database, 2016). Databases such as HMDB have greatly assisted in the identification and understanding of physiological relevance for metabolites that have been discovered through non-targeted strategies.