Identification of chemical compounds

Compound identification using mass spectrometry across different mass spectral protocols is difficult.  it is unlikely to be successful without careful calibrations and authentic standards.  Multiple biological compounds may be confused because they are isobaric, i.e. have the same formula or mass.  Even more problematic are unknown artifactual or fragmentary compounds that are structurally and chemically different from their biological isobaric equivalents, but may share the same mass, or even formulae.  These artifacts typically outnumber the known metabolites in metabolomics studies.

Compound Identification and Mass Spectrometry: The LTRS

In addition to authentic standards, we use the IROA Long-Term Reference Standard (IROA LTRS or LTRS).  LTRS is an isotopically-labeled complex standard, universally labeled at both 5% and 95% U-13C and mixed 1:1  It has been economically produced in bulk and has been characterized to measure hundreds of primary and secondary metabolites.

When analyzed by LC-MS, the LTRS exhibits unique labeling patterns for all biological compounds. These peak pairs provide many useful benefits:

  • They are computationally easy to find and characterize using ClusterFinder software.
  • Unique isotopic patterns discriminate peaks of biological origin allowing removal of false data.
  • The number of carbon in a biological molecule can be determined by the distance between the two monoisotopic peaks, C12 and C13. The relative height of the M+1 and M-1 provides confirmation of this fact, resulting in a triply redundant quality control check point.
  • For masses below 500 amu, the C12 or C13 monoisotopic mass plus the number of carbons almost always uniquely identifies the molecular formula.
  • Isobaric formulae are distinguished using secondary MS scans either by collecting Collisional Cross Section (CSS), or fragmentation.
  • Fragments and adducts of the M+H, e.g. [M+Na]+, [2M+H]+, [M+H -CH2O2]+, etc.,  are most commonly considered “unknowns”.  As peak pairs with artifacts excluded, the isotopic pattern of fragments derived from their parent peaks may be analyzed, correlated, and named.

The IROA LTRS is stable.  The exact same compounds that you can measure today you can measure 5 years from now.

Accurate compound identification and mass spectrometry with LTRS

  1. Analyze IROA MSMLS authentic compounds standards to get physical data for 600+ compounds. This data is stored in ClusterFinder’s internal databases.
  2. Analyze the LTRS every 10 injections. The LTRS is used to build a database of compounds or library for identification and also serves as a Quality Control sample.
  3. Perform a search for IROA peaks using ClusterFinder which will apply the MSMLS library to the search results.  Hits here become the preferred name for “identified” peaks.
  4. The well-formed IROA LTRS peaks (triply redundant and mathematically calculable) will have the correct formulae assigned.  The next step is to examine all “identified” peaks for adducts and fragments among the unidentified peaks (these are clearly identified as they will have the same IROA shape as parent peaks).  This step picks up a large percentage of the “unidentified” peaks and defines these “identified as related”.   These are entered into the database to ensure they will be identified in future analyses (Note: the database automatically annotates the source and all modifications to all records).
  5. For peaks not either identified by comparison to a standard or determined to be derived from a standard, the correct formula is assured, and the program will list all isobaric compound names. For this purpose, copies of Pubchem, ChEBI, Lipidmaps, and a peptide database are embedded in the ClusterFinder database (with links to the original source).
  6. At any point, when the identity of an unidentified peak is determined, add it into the ClusterFinder database so it will be correctly named in the future (the database will carry the date/time annotation for the new addition).

Listen to the video IROA TruQuant Workflow