Unsupervised Discovery and Comparison of Structural Families Across Multiple Samples in Untargeted Metabolomics.
Unsupervised Discovery and Comparison of Structural Families Across Multiple Samples in Untargeted Metabolomics.
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DOI：
10.1021/acs.analchem.7b01391
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发表时间：
2017-07-18
影响因子：
7.4
通讯作者：
Rogers S
中科院分区：
文献类型：
--
作者：
van der Hooft JJJ;Wandy J;Young F;Padmanabhan S;Gerasimidis K;Burgess KEV;Barrett MP;Rogers S
在非靶向代谢组学方法中，无法在结构上注释相关特征并将其映射到生化途径，这阻碍了许多代谢组学实验的充分利用。此外，样本间的可变代谢内容导致统计上难以处理的稀疏特征矩阵。在这里，我们介绍解决上述两个问题的MS 2LDA+。以前，我们提出了MS 2LDA，它提取生物化学相关的分子亚结构（“Mass 2 Motifs”）从收集的碎片光谱作为一组共同出现的分子片段和中性损失，从而识别代谢组学的构建块。在这里，我们扩展了MS 2LDA，以在一次分析中处理多个代谢组学实验，从而得到MS 2LDA+。通过将样本中的Mass 2 Motifs联系起来，我们揭示了结构相关代谢物家族患病率的变异性。我们验证了两个不同的样本组之间的子结构的差异患病率，并将其应用于粪便样本。随后，在一个尿液样本组中，我们根据其方差对Mass 2 Motifs进行排名，以评估外源性衍生的子结构是否在最具变异性的Mass 2 Motifs中。事实上，我们可以将30个最具变异性的Mass 2 Motifs中的22个归因于外源性衍生的子结构，包括对乙酰氨基酚/对乙酰氨基酚硫醇盐和二甲基邻苯三酚。总的来说，我们在结构上表征了101个具有生化或化学相关子结构的Mass 2基序。最后，我们将发现的代谢物家族与全扫描特征强度信息相结合，以深入了解大多数样品中存在的核心代谢物和现在通过其共同子结构连接的小子集中存在的罕见代谢物。我们得出结论，通过对样品中代谢物的生化分组，MS 2LDA+有助于代谢物的结构注释，并通过使用Mass 2 Motif患病率指导分析的优先级。
In untargeted metabolomics approaches, the inability to structurally annotate relevant features and map them to biochemical pathways is hampering the full exploitation of many metabolomics experiments. Furthermore, variable metabolic content across samples result in sparse feature matrices that are statistically hard to handle. Here, we introduce MS2LDA+ that tackles both above-mentioned problems. Previously, we presented MS2LDA, which extracts biochemically relevant molecular substructures (“Mass2Motifs”) from a collection of fragmentation spectra as sets of co-occurring molecular fragments and neutral losses, thereby recognizing building blocks of metabolomics. Here, we extend MS2LDA to handle multiple metabolomics experiments in one analysis, resulting in MS2LDA+. By linking Mass2Motifs across samples, we expose the variability in prevalence of structurally related metabolite families. We validate the differential prevalence of substructures between two distinct samples groups and apply it to fecal samples. Subsequently, within one sample group of urines, we rank the Mass2Motifs based on their variance to assess whether xenobiotic-derived substructures are among the most-variant Mass2Motifs. Indeed, we could ascribe 22 out of the 30 most-variant Mass2Motifs to xenobiotic-derived substructures including paracetamol/acetaminophen mercapturate and dimethylpyrogallol. In total, we structurally characterized 101 Mass2Motifs with biochemically or chemically relevant substructures. Finally, we combined the discovered metabolite families with full scan feature intensity information to obtain insight into core metabolites present in most samples and rare metabolites present in small subsets now linked through their common substructures. We conclude that by biochemical grouping of metabolites across samples MS2LDA+ aids in structural annotation of metabolites and guides prioritization of analysis by using Mass2Motif prevalence.
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Balcke, Gerd Ulrich
影响因子：
14.9
作者：
Wishart DS;Jewison T;Guo AC;Wilson M;Knox C;Liu Y;Djoumbou Y;Mandal R;Aziat F;Dong E;Bouatra S;Sinelnikov I;Arndt D;Xia J;Liu P;Yallou F;Bjorndahl T;Perez-Pineiro R;Eisner R;Allen F;Neveu V;Greiner R;Scalbert A
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