Methodology for the Validation of Isotopic Analyses by Mass Spectrometry in Stable-Isotope Labeling Experiments

Stable-isotope labeling
experiments (ILEs) are widely used to investigate
the topology and operation of metabolic networks. The quality of isotopic
data collected in ILEs is of utmost importance to ensure reliable
biological interpretations, but current evaluation approaches are
limited due to a lack of suitable reference material and relevant
evaluation criteria. In this work, we present a complete methodology
to evaluate mass spectrometry (MS) methods used for quantitative isotopic
studies of metabolic systems. This methodology, based on a biological
sample containing metabolites with controlled labeling patterns, exploits
different quality metrics specific to isotopic analyses (accuracy
and precision of isotopologue masses, abundances, and mass shifts
and isotopic working range). We applied this methodology to evaluate
a novel LC-MS method for the analysis of amino acids, which was tested
on high resolution (Orbitrap operating in full scan mode) and low
resolution (triple quadrupole operating in multiple reaction monitoring
mode) mass spectrometers. Results show excellent accuracy and precision
over a large working range and revealed matrix-specific as well as
mode-specific characteristics. The proposed methodology can identify
reliable (and unreliable) isotopic data in an easy and straightforward
way and efficiently supports the identification of sources of systematic
biases as well as of the main factors that influence the overall accuracy
and precision of measurements. This approach is generic and can be
used to validate isotopic analyses on different matrices, analytical
platforms, labeled elements, or classes of metabolites. It is expected
to strengthen the reliability of isotopic measurements and thereby
the biological value of ILEs.