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化学信息学与肯德里克质量分析相结合以增强大豆代谢组学中的注释并识别代谢途径

Chemical Informatics Combined with Kendrick Mass Analysis to Enhance Annotation and Identify Pathways in Soybean Metabolomics.

作者信息

Wood Troy D, Tiede Erin R, Izydorczak Alexandra M, Zemaitis Kevin J, Ye Heng, Nguyen Henry T

机构信息

Department of Chemistry, University at Buffalo, State University of New York, Buffalo, NY 14260-3000, USA.

Division of Plant Sciences and National Center for Soybean Biotechnology, University of Missouri, Columbia, MO 65211, USA.

出版信息

Metabolites. 2025 Jan 24;15(2):73. doi: 10.3390/metabo15020073.

DOI:10.3390/metabo15020073
PMID:39997698
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11857611/
Abstract

BACKGROUND

Among abiotic stresses to agricultural crops, drought stress is the most prolific and has worldwide detrimental impacts. The soybean () is one of the most important sources of nutrition to both livestock and humans. Different plant introductions (PI) of soybeans have been identified to have different drought tolerance levels.

OBJECTIVES

Here, two soybean lines, Pana (drought sensitive) and PI 567731 (drought tolerant) were selected to identify chemical compounds and pathways which could be targets for metabolomic analysis induced by abiotic stress.

METHODS

Extracts from the two lines are analyzed by direct infusion electrospray ionization Fourier transform ion cyclotron resonance mass spectrometry. The high mass resolution and accuracy of the method allows for identification of ions from hundreds of different compounds in each cultivar. The exact / of these species were filtered through SoyCyc and the Human Metabolome Database to identify possible molecular formulas of the ions. Next, the exact / values were converted into Kendrick masses and their Kendrick mass defects (KMD) computed, which were then sorted from high to low KMD. This latter process assists in identifying many additional molecular formulas, and is noted to be particularly useful in identifying formulas whose mass difference corresponds to two hydrogen atoms.

RESULTS

In this study, more than 460 ionic formulas were identified in Pana, and more than 340 ionic formulas were identified in PI 567731, with many of these formulas reported from soybean for the first time.

CONCLUSIONS

Using the SoyCyc matches, the metabolic pathways from each cultivar were compared, providing lists of molecular targets available to profile effects of abiotic stress on these soybean cultivars. Key metabolites include chlorophylls, pheophytins, mono- and diacylglycerols, cycloeucalenone, squalene, and plastoquinones and involve pathways which include the anabolism and catabolism of chlorophyll, glycolipid desaturation, and biosynthesis of phytosterols, plant sterols, and carotenoids.

摘要

背景

在影响农作物生长的非生物胁迫中,干旱胁迫最为常见,且在全球范围内造成了有害影响。大豆是牲畜和人类最重要的营养来源之一。已确定不同的大豆植物引进品种(PI)具有不同的耐旱水平。

目的

本研究选取了两个大豆品系,帕纳(干旱敏感型)和PI 567731(耐旱型),以确定可能成为非生物胁迫诱导代谢组学分析靶点的化合物和途径。

方法

通过直接进样电喷雾电离傅里叶变换离子回旋共振质谱法对这两个品系的提取物进行分析。该方法的高质量分辨率和准确性使得能够识别每个品种中数百种不同化合物的离子。通过SoyCyc和人类代谢组数据库筛选这些物质的确切质荷比(m/z),以确定离子可能的分子式。接下来,将确切的m/z值转换为肯德里克质量,并计算其肯德里克质量缺陷(KMD),然后按KMD从高到低排序。后一过程有助于识别许多其他分子式,并且特别适用于识别质量差对应于两个氢原子的分子式。

结果

在本研究中,在帕纳中鉴定出460多个离子分子式,在PI 567731中鉴定出340多个离子分子式,其中许多分子式是首次在大豆中报道。

结论

利用SoyCyc匹配结果,比较了每个品种的代谢途径,提供了可用于分析非生物胁迫对这些大豆品种影响的分子靶点列表。关键代谢物包括叶绿素、脱镁叶绿素、单酰甘油和二酰甘油、环桉烯酮、角鲨烯以及质体醌,涉及的途径包括叶绿素的合成与分解代谢、糖脂去饱和以及植物甾醇、植物固醇和类胡萝卜素的生物合成。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ed9/11857611/ac03c1d52732/metabolites-15-00073-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ed9/11857611/f7f40faade66/metabolites-15-00073-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ed9/11857611/ac03c1d52732/metabolites-15-00073-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ed9/11857611/f7f40faade66/metabolites-15-00073-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7ed9/11857611/ac03c1d52732/metabolites-15-00073-g002.jpg

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