Mass spectrometry
(MS) is widely used in science and industry.
It allows accurate, specific, sensitive, and reproducible detection
and quantification of a huge range of analytes. Across MS applications,
quantification by MS has grown most dramatically, with >50 million
experiments/year in the USA alone. However, quantification performance
varies between instruments, compounds, different samples, and within-
and across runs, necessitating normalization with analyte-similar
internal standards (IS) and use of IS-corrected multipoint external
calibration curves for each analyte, a complicated and resource-intensive
approach, which is particularly ill-suited for multi-analyte measurements.
We have developed an internal calibration method that utilizes the
natural isotope distribution of an IS for a given analyte to provide
internal multipoint calibration. Multiple isotope distribution calibrators
for different targets in the same sample facilitate multiplex quantification,
while the emerging random-access automated MS platforms should also
greatly benefit from this approach. Finally, isotope distribution
calibration allows mathematical correction for suboptimal experimental
conditions. This might also enable quantification of hitherto difficult,
or impossible to quantify, targets, if the distribution is adjusted in silico to mimic the analyte. The approach works well
for high resolution, accurate mass MS for analytes with at least a
modest-sized isotopic envelope. As shown herein, the approach can
also be applied to lower molecular weight analytes, but the reduction
in calibration points does reduce quantification performance.