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

TL;DR

This study introduces a new method to accurately measure isotope enrichment in soil amino compounds using high-resolution mass spectrometry, enabling better understanding of nitrogen cycling in soils.

Contribution

A predictive model for isotope calibration of soil amino compounds, even without labeled standards, using physicochemical properties.

Findings

Isotope calibration curves showed excellent linear and polynomial fits across 13C enrichment ranges.

The model accurately predicted calibration curves for amino compounds without labeled standards, with high R² values.

The method achieved detection limits as low as 0.0003 atom % 13C incorporation for some amino compounds.

Abstract

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 (R
2 > 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 R
2 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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