Direct infusion nanoelectrospray high-resolution mass spectrometry (DI-nESI-HRMS) is a promising tool for high-throughput metabolomics analysis. However, metabolite assignment is limited by the inadequate mass accuracy and chemical space of the metabolome database. Here, a serum metabolome characterization method was proposed to make full use of the potential of DI-nESI-HRMS. Different from the widely used database search approach, unambiguous formula assignments were achieved by a reaction network combined with mass accuracy and isotopic patterns filter. To provide enough initial known nodes, an initial network was directly constructed by known metabolite formulas. Then experimental formula candidates were screened by the predefined reaction with the network. The effects of sources and scales of networks on assignment performance were investigated. Further, a scoring rule for filtering unambiguous formula candidates was proposed. The developed approach was validated by a pooled serum sample spiked with reference standards. The coverage and accuracy rates for the spiked standards were 98.9% and 93.6%, respectively. A total of 1958 monoisotopic features were assigned with unique formula candidates for the pooled serum, which is twice more than the database search. Finally, a case study of serum metabolomics in diabetes was carried out using the developed method.

中文翻译：

---

通过直接输注高分辨率质谱法发现血清代谢组的策略

直接注入纳米电喷雾高分辨率质谱 (DI-nESI-HRMS) 是一种很有前途的高通量代谢组学分析工具。然而，代谢物分配受到代谢组数据库质量准确度和化学空间不足的限制。在此，提出了一种血清代谢组学表征方法，以充分利用 DI-nESI-HRMS 的潜力。与广泛使用的数据库搜索方法不同，通过结合质量精度和同位素模式过滤器的反应网络实现了明确的分子式分配。为了提供足够的初始已知节点，初始网络直接由已知代谢物公式构建。然后通过与网络的预定义反应筛选实验候选配方。研究了网络来源和规模对分配绩效的影响。此外，还提出了一种用于过滤明确候选公式的评分规则。所开发的方法通过掺有参考标准的混合血清样本进行了验证。加标标准品的覆盖率和准确率分别为 98.9% 和 93.6%。共有 1958 个单一同位素特征被分配了混合血清的独特候选分子式，比数据库搜索多两倍。最后，使用开发的方法对糖尿病血清代谢组学进行了案例研究。分别为 9% 和 93.6%。共有 1958 个单一同位素特征被分配了混合血清的独特候选分子式，比数据库搜索多两倍。最后，使用开发的方法对糖尿病血清代谢组学进行了案例研究。分别为 9% 和 93.6%。共有 1958 个单一同位素特征被分配了混合血清的独特候选分子式，比数据库搜索多两倍。最后，使用开发的方法对糖尿病血清代谢组学进行了案例研究。