Metabolite identification is the greatest challenge when analysing metabolomics data, as only a small proportion of metabolite reference standards exist. Clustering MS/MS spectra is a common method to identify similar compounds, however interrogation of underlying signature fragmentation patterns within clusters can be problematic. Previously published high-resolution LC-MS/MS data from the bioluminescent beetle (Photinus pyralis) provided an opportunity to mine new specialized metabolites in the lucibufagin class, compounds important for defense against predation. We aimed to 1) provide a workflow for hierarchically clustering MS/MS spectra for metabolomics data enabling users to cluster, visualise and easily interrogate the identification of underlying cluster ion profiles, and 2) use the workflow to identify key fragmentation patterns for lucibufagins in the hemolymph of P. pyralis. Features were aligned to their respective MS/MS spectra, then product ions were dynamically binned and resulting spectra were hierarchically clustered and grouped based on a cutoff distance threshold. Using the simplified visualization and the interrogation of cluster ion tables the number of lucibufagins was expanded from 17 to a total of 29.

代谢组学数据分析时，代谢物鉴定是最大的挑战，因为只有一小部分代谢物参考标准存在。 MS/MS 谱图聚类是识别相似化合物的常用方法，但是对簇内潜在特征碎片模式的询问可能会出现问题。先前发表的来自生物发光甲虫（ Photinus Pyralis ）的高分辨率 LC-MS/MS 数据为挖掘 lucibufagin 类新的专门代谢物提供了机会，这些化合物对于防御捕食非常重要。我们的目标是 1) 提供代谢组学数据的 MS/MS 谱图分层聚类工作流程，使用户能够聚类、可视化并轻松询问潜在簇离子谱的识别，以及 2) 使用该工作流程来识别荧光素中的关键碎片模式。萤火虫的血淋巴。将特征与其各自的 MS/MS 谱图对齐，然后对产物离子进行动态分箱，并根据截止距离阈值对所得谱图进行分层聚类和分组。使用简化的可视化和簇离子表的询问，lucibufagins 的数量从 17 种扩大到总共 29 种。