Revisiting In-Gas Transformations of Quinate Conjugates Through the LC-qTOF-MS and Molecular Networking Topology

IF 1.8 3区 化学 Q4 BIOCHEMICAL RESEARCH METHODS
Nakisani Babra Moyo, Ntakadzeni Edwin Madala
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引用次数: 0

Abstract

Rationale

The emergence of computational metabolomics tools such as molecular networking and machine learning–based platforms like SIRIUS has significantly advanced MS-based metabolomics studies. These tools enable rapid metabolite identification by deciphering complex fragmentation patterns and chemical transformations occurring during mass spectrometry analysis.

Methods

In this study, methanolic extracts of Viscum combreticola, a plant recently shown to contain a rich composition of cinnamic acid–quinates conjugates, were analyzed using the LC-qTOF-MS in combination with a molecular networking approach to explore the chemical complexity of quinate conjugates.

Results

Findings of this study through molecular networking topology revealed that quinic acid undergoes a series of in-gas chemical transformations, including dehydration (–H2O) and decarboxylation (–CO2). These transformations yield unique product ions, some of which are associated with other organic acids, such as isocitric acid. By employing the MS2 search option on the GNPS2 platform, molecules exhibiting these product ions were readily identified in this study. Therefore, highlighting the potential of this function in GNPS2 for tracing unique fragmentation patterns synonymous with certain molecules that can be used to confirm their identity visually.

Conclusion

The MS2 search function can aid in the discovery of new compounds containing the diagnostic ions of interest that could otherwise be easily missed with manual annotation. This study presents a potential validation approach of looking at multiple product ions to confirm the identity of a molecule, particularly in the presence of other compounds with similar fragmentation pathways or shared fragment ions.

Abstract Image

通过LC-qTOF-MS和分子网络拓扑重新审视醌类共轭物的气体变换
计算代谢组学工具的出现,如分子网络和基于机器学习的平台,如SIRIUS,极大地推进了基于ms的代谢组学研究。这些工具通过解析质谱分析过程中发生的复杂碎片模式和化学转化,实现了代谢物的快速鉴定。方法采用LC-qTOF-MS结合分子网络方法,对最近发现的含有丰富肉桂酸-醌类缀合物的combreticola植物的甲醇提取物进行分析,探讨醌类缀合物的化学复杂性。结果本研究通过分子网络拓扑结构发现,奎宁酸在气体中经历了一系列的化学转化,包括脱水(-H2O)和脱羧(-CO2)。这些转化产生独特的产物离子,其中一些与其他有机酸相关,如异柠檬酸。通过在GNPS2平台上使用MS2搜索选项,在本研究中很容易识别出具有这些产物离子的分子。因此,强调GNPS2中该功能的潜力,用于追踪与某些分子同义的独特碎片模式,可用于视觉上确认其身份。结论MS2检索功能可以帮助发现含有诊断离子的新化合物,否则人工注释很容易遗漏。这项研究提出了一种潜在的验证方法,通过观察多个产物离子来确认分子的身份,特别是在其他具有类似碎片路径或共享碎片离子的化合物存在的情况下。
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来源期刊
CiteScore
4.10
自引率
5.00%
发文量
219
审稿时长
2.6 months
期刊介绍: Rapid Communications in Mass Spectrometry is a journal whose aim is the rapid publication of original research results and ideas on all aspects of the science of gas-phase ions; it covers all the associated scientific disciplines. There is no formal limit on paper length ("rapid" is not synonymous with "brief"), but papers should be of a length that is commensurate with the importance and complexity of the results being reported. Contributions may be theoretical or practical in nature; they may deal with methods, techniques and applications, or with the interpretation of results; they may cover any area in science that depends directly on measurements made upon gaseous ions or that is associated with such measurements.
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