一种基于轨道阱质谱的土壤氨基化合物综合超灵敏同位素校准方法

IF 6.7 1区 化学 Q1 CHEMISTRY, ANALYTICAL
Tao Li, Yuhua Li, Erika Salas, Ye Tian, Xiaofei Liu, Wolfgang Wanek
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引用次数: 0

摘要

结合氨基化合物(氨基酸和氨基糖聚合物)占土壤有机氮的很大比例(约40%),因此是植物和微生物营养的重要氮源。由于在接近天然土壤条件下达到的同位素富集水平较低,并且缺乏一些关键氨基化合物的同位素标记标准,因此其含量和同位素富集分析仍然是一个重大挑战。本研究采用6-氨基喹啉- n -羟基辛咪酰氨基甲酸酯(AQC)衍生化法和超高高效液相色谱-高分辨率Orbitrap质谱(UPLC-Orbitrap MS),分别用13c标记和未标记的氨基酸混合物建立了16种氨基化合物的同位素校准曲线。所有标准氨基化合物的aqc衍生物的分子离子均按各自同位素的预期m/z值进行了鉴定。同位素校准曲线在整个13C富集范围内表现出良好的线性拟合,在低13C富集范围内表现出良好的多项式拟合(R2 >;0.990)。然而,多项式拟合项在单个氨基酸之间是不同的。随后,我们建立了方程,将校准的回归项与各自氨基酸的物理化学性质联系起来,这里主要是aqc -氨基化合物衍生物中氨基化合物C原子与总C原子的比率。基于这些回归,我们最终可以预测那些无法作为13C标记标准的氨基化合物的同位素校准曲线,例如,氨基酸、羟脯氨酸和二氨基苯甲酸。为了测试模型的准确性,我们将测量校准的结果与同位素富集标准氨基酸的预测校准结果进行了比较。实测数据与预测数据之间的线性回归结果非常好,R2为>;0.97,平均绝对(百分比)偏差MAD和MAPD分别为0.334和15.8%。最后,我们将标准和预测校准曲线应用于低13C修正的土壤样品和未标记的对照,以测试我们模型的适用性。不同氨基化合物的检出限(LOD)在0.0003 ~ 0.14原子%之间。该通用预测模型可用于全面量化整个土壤氨基化合物剖面的同位素富集,包括氨基糖、蛋白质和非蛋白质氨基酸,为更好地了解土壤和其他复杂环境系统中不同氨基化合物的总体命运提供了有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Comprehensive and Ultrasensitive Isotope Calibration Method for Soil Amino Compounds Using Orbitrap Mass Spectrometry

A Comprehensive and Ultrasensitive Isotope Calibration Method for Soil Amino Compounds Using Orbitrap Mass Spectrometry
Bound amino compounds (amino acid and amino sugar polymers) comprise a significant proportion (∼40%) of soil organic nitrogen and therefore represent an essential source of nitrogen for plant and microbial nutrition. The analysis of their content and isotope enrichment still represents a significant challenge due to the low isotope enrichment levels reached under near-native soil conditions and the lack of isotopically labeled standards for some key amino compounds. In this study, we used both a 13C-labeled and an unlabeled amino acid mixture to establish isotope calibration curves for 16 amino compounds, using the 6-aminoquinolyl-N-hydroxysccinimidyl carbamate (AQC) derivatization method and ultrahigh-performance liquid chromatography with high-resolution Orbitrap mass spectrometry (UPLC-Orbitrap MS). Molecular ions of AQC-derivatives for all standard amino compounds were identified at the expected m/z values of the respective isotopologues. The isotope calibration curves exhibited excellent linear fits across the whole 13C enrichment range and polynomial fits in the low 13C enrichment range (R2 > 0.990). However, the polynomial fitting terms differed between individual amino acids. Subsequently, we developed equations to relate the calibrated regression terms to the physicochemical properties of the respective amino acids, here mainly the ratio of amino compound-C atoms to total C atoms in AQC-amino compound derivatives. Based on these regressions, we could ultimately predict isotope calibration curves for those amino compounds unavailable as 13C labeled standards, for example, muramic acid, hydroxyproline, and diaminopimelic acid. To test the model accuracy, we compared the outcomes of measured calibrations with predicted calibrations for amino acids where we had isotopically enriched standards. The results of linear regression between measured and predicted data were excellent, where R2 was >0.97, and mean absolute (percentage) deviations, MAD and MAPD, were 0.334 and 15.8%. Finally, we applied both standard and predicted calibration curves to low 13C amended soil samples and unlabeled controls to test the applicability of our model. The limit of detection (LOD) as the minimum detectable atom % 13C incorporation of amino compounds ranged from 0.0003 to 0.14 atom % among different amino compounds. This general predictive model can be used to comprehensively quantify isotope enrichments across the entire soil amino compound profile, including amino sugars and proteinogenic and nonproteinogenic amino acids, providing valuable insights for a better understanding of the overall fate of different amino compounds in soils and other complex environmental systems.
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来源期刊
Analytical Chemistry
Analytical Chemistry 化学-分析化学
CiteScore
12.10
自引率
12.20%
发文量
1949
审稿时长
1.4 months
期刊介绍: Analytical Chemistry, a peer-reviewed research journal, focuses on disseminating new and original knowledge across all branches of analytical chemistry. Fundamental articles may explore general principles of chemical measurement science and need not directly address existing or potential analytical methodology. They can be entirely theoretical or report experimental results. Contributions may cover various phases of analytical operations, including sampling, bioanalysis, electrochemistry, mass spectrometry, microscale and nanoscale systems, environmental analysis, separations, spectroscopy, chemical reactions and selectivity, instrumentation, imaging, surface analysis, and data processing. Papers discussing known analytical methods should present a significant, original application of the method, a notable improvement, or results on an important analyte.
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