Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'.
Metabolite signal identification in accurate mass metabolomics data with MZedDB, an interactive m/z annotation tool utilising predicted ionisation behaviour 'rules'.
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DOI：
10.1186/1471-2105-10-227
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发表时间：
2009-07-21
影响因子：
3
通讯作者：
Zubair H
中科院分区：
文献类型：
--
作者：
Draper J;Enot DP;Parker D;Beckmann M;Snowdon S;Lin W;Zubair H
使用质谱仪(MS)技术的代谢组学实验测量复杂生物样品粗提物中电离分子的质量电荷比(m/z)和强度，以生成高维代谢物‘指纹’或代谢物‘图谱’数据。高分辨率的MS仪器常规运行，质量精确度为<；5ppm(百万分之五)，从而为使用包含代谢物质量信息的数据库进行信号假定注释提供了一种潜在的直接方法。大多数数据库界面只支持简单的查询，默认假设是分子在电离时要么获得一个质子，要么失去一个质子。事实上，许多电离产物不仅是分子同位素，而且是盐/溶剂加合物和原始代谢物的中性损失碎片，这一事实扰乱了注释过程。这份报告描述了一种注释策略，该策略将允许基于预测在电喷雾电离(ESI)期间形成的所有潜在电离产品进行搜索。从公众可访问的数据库中获得的代谢物‘结构’被转换成一种通用格式，以在MZeDB中生成一个全面的档案。“规则”是从化学信息中衍生出来的，这些信息使MzzDB能够生成一份加合物和中性损失片段的列表，推测这些加合物和中性损失片段能够为每个结构形成，并动态计算每个潜在电离产物的准确分子量，以便根据准确的质量为注释搜索提供目标。我们证明，代表由不同生物基质产生的电离产物群体的数据矩阵包含很大比例(有时为50%)的分子同位素、盐加合物和中性损失碎片。ESI-MS数据特征的相关性分析证实了m/z信号的预测关系。MZDDB中集成的同位素枚举器可以验证准确的同位素模式分布，以证实实验数据。我们的结论是，尽管超高精度的质谱仪提供了对生物提取物的化学多样性的主要洞察，但通过使用计算的分子公式对现有数据库进行简单、自动的查询，不可能对大部分信号进行便捷的注释。考虑到预测的电离行为和任何样品的生物来源，对MzzDB进行参数化处理，极大地提高了ESI-MS数据中潜在注释的频率和准确性。
Metabolomics experiments using Mass Spectrometry (MS) technology measure the mass to charge ratio (m/z) and intensity of ionised molecules in crude extracts of complex biological samples to generate high dimensional metabolite 'fingerprint' or metabolite 'profile' data. High resolution MS instruments perform routinely with a mass accuracy of < 5 ppm (parts per million) thus providing potentially a direct method for signal putative annotation using databases containing metabolite mass information. Most database interfaces support only simple queries with the default assumption that molecules either gain or lose a single proton when ionised. In reality the annotation process is confounded by the fact that many ionisation products will be not only molecular isotopes but also salt/solvent adducts and neutral loss fragments of original metabolites. This report describes an annotation strategy that will allow searching based on all potential ionisation products predicted to form during electrospray ionisation (ESI). Metabolite 'structures' harvested from publicly accessible databases were converted into a common format to generate a comprehensive archive in MZedDB. 'Rules' were derived from chemical information that allowed MZedDB to generate a list of adducts and neutral loss fragments putatively able to form for each structure and calculate, on the fly, the exact molecular weight of every potential ionisation product to provide targets for annotation searches based on accurate mass. We demonstrate that data matrices representing populations of ionisation products generated from different biological matrices contain a large proportion (sometimes > 50%) of molecular isotopes, salt adducts and neutral loss fragments. Correlation analysis of ESI-MS data features confirmed the predicted relationships of m/z signals. An integrated isotope enumerator in MZedDB allowed verification of exact isotopic pattern distributions to corroborate experimental data. We conclude that although ultra-high accurate mass instruments provide major insight into the chemical diversity of biological extracts, the facile annotation of a large proportion of signals is not possible by simple, automated query of current databases using computed molecular formulae. Parameterising MZedDB to take into account predicted ionisation behaviour and the biological source of any sample improves greatly both the frequency and accuracy of potential annotation 'hits' in ESI-MS data.
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影响因子：
14.9
作者：
Grafahrend-Belau, Eva;Weise, Stephan;Koschuetzki, Dirk;Scholz, Uwe;Junker, Bjoern H.;Schreiber, Falk
通讯作者：
Schreiber, Falk
影响因子：
3
作者：
Lange E;Tautenhahn R;Neumann S;Gröpl C
通讯作者：
Gröpl C
影响因子：
7.4
作者：
Moco, Sofia;Bino, Raoul J.;de Vos, C. H. Ric
通讯作者：
de Vos, C. H. Ric
影响因子：
30.8
作者：
Keurentjes, Joost J. B.;Fu, Jingyuan;Koornneef, Maarten
通讯作者：
Koornneef, Maarten
DOI：
10.1089/15362310260256882
发表时间：
2002-01-01
期刊：
OMICS A Journal of Integrative Biology
影响因子：
--
作者：
Aharoni, Asaph;De Vos, C. H. Ric;Goodenowe, Dayan B.
通讯作者：
Goodenowe, Dayan B.