Navigating natural variation in herbivory-induced secondary metabolism in coyote tobacco populations using MS/MS structural analysis
Navigating natural variation in herbivory-induced secondary metabolism in coyote tobacco populations using MS/MS structural analysis
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DOI：
10.1073/pnas.1503106112
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发表时间：
2015-07-28
影响因子：
11.1
通讯作者：
Gaquerel, Emmanuel
中科院分区：
文献类型：
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作者：
Li, Dapeng;Baldwin, Ian T.;Gaquerel, Emmanuel
自然变异在揭示表型性状进化的决定因素方面非常有用，但很少用无偏见的代谢分析来分析，以了解其影响如何在生化途径水平上组织起来。衰减烟草（Nicotiana attenuata）是一种野生烟草物种，其原生种群在与昆虫相互作用的重要性状上具有高度的遗传多样性。为了解决这些人群中存在的化学多样性，我们开发了一个代谢组学和计算管道来注释叶片的代谢反应，以Manducasexta草食动物。我们选择了来自美国西南部的不同人群的43个加入的种子，包括良好的特点犹他州第30代自交系加入，并在温室中生长183株标准化的草食动物诱导。从每株植物的诱导叶片产生的代谢配置文件，使用高通量超高效液相色谱（UHPLC）-四极飞行时间质谱（qTOFMS）方法，处理，以系统地推断生化相关的代谢物之间的协变模式，以及未知的，最后组装映射自然变异。浏览这张地图揭示了代谢分支特异性的变化，令人惊讶的是，只有部分重叠与茉莉酸积累多态性和偏离经典的茉莉酸信号。片段化分析，通过无差别串联质谱（idMS/MS）进行了10个加入，跨越了很大比例的方差中发现的完整的加入数据集，和化合物光谱计算组装成光谱相似性网络。通过这种网络方法捕获的生物信息有助于挖掘具有高度自然变异的未知物质的质谱数据，如强烈的食草诱导的酚类衍生物的注释所示，并且可以指导途径分析。
Natural variation can be extremely useful in unraveling the determinants of phenotypic trait evolution but has rarely been analyzed with unbiased metabolic profiling to understand how its effects are organized at the level of biochemical pathways. Native populations of Nicotiana attenuata, a wild tobacco species, have been shown to be highly genetically diverse for traits important for their interactions with insects. To resolve the chemodiversity existing in these populations, we developed a metabolomics and computational pipeline to annotate leaf metabolic responses to Manduca sexta herbivory. We selected seeds from 43 accessions of different populations from the southwestern United States-including the well-characterized Utah 30th generation inbred accession-and grew 183 plants in the glasshouse for standardized herbivory elicitation. Metabolic profiles were generated from elicited leaves of each plant using a high-throughput ultra HPLC (UHPLC)-quadrupole TOFMS (qTOFMS) method, processed to systematically infer covariation patterns among biochemically related metabolites, as well as unknown ones, and finally assembled to map natural variation. Navigating this map revealed metabolic branch-specific variations that surprisingly only partly overlapped with jasmonate accumulation polymorphisms and deviated from canonical jasmonate signaling. Fragmentation analysis via indiscriminant tandem mass spectrometry (idMS/MS) was conducted with 10 accessions that spanned a large proportion of the variance found in the complete accession dataset, and compound spectra were computationally assembled into spectral similarity networks. The biological information captured by this networking approach facilitates the mining of the mass spectral data of unknowns with high natural variation, as demonstrated by the annotation of a strongly herbivory-inducible phenolic derivative, and can guide pathway analysis.