Background: Isotopic Ratio Outlier Analysis (IROA) is an untargeted metabolomics
method that uses stable isotopic labeling and LC-HRMS for identification
and relative quantification of metabolites in a biological sample under varying experimental
Objective: We demonstrate a method using high-sensitivity 13C NMR to identify an
unknown metabolite isolated from fractionated material from an IROA LC-HRMS
Methods: IROA samples from the nematode Caenorhabditis elegans were fractionated
using LC-HRMS using 5 repeated injections and collecting 30 sec fractions.
These were concentrated and analyzed by 13C NMR.
Results: We isotopically labeled samples of C. elegans and collected 2 adjacent LC fractions. By HRMS,
one contained at least 2 known metabolites, phenylalanine and inosine, and the other contained tryptophan
and an unknown feature with a monoisotopic mass of m/z 380.0742 [M+H]+. With NMR, we were
able to easily verify the known compounds, and we then identified the spin system networks responsible
for the unknown resonances. After searching the BMRB database and comparing the molecular formula
from LC-HRMS, we determined that the fragments were a modified anthranilate and a glucose modified
by a phosphate. We then performed quantum chemical NMR chemical shift calculations to determine the
most likely isomer, which was 3’-O-phospho-β-D-glucopyranosyl-anthranilate. This compound had previously
been found in the same organism, validating our approach.
Conclusion: We were able to dereplicate previously known metabolites and identify a metabolite that was
not in databases by matching resonances to NMR databases and using chemical shift calculations to determine
the correct isomer. This approach is efficient and can be used to identify unknown compounds of interest
using the same material used for IROA.