Metabolite Spectral Accuracy on Orbitraps

Xiaoyang Su, Wenyun Lu, Joshua D. Rabinowitz

Research output: Contribution to journalArticlepeer-review

157 Scopus citations


Orbitraps are high-resolution ion-trap mass spectrometers that are widely used in metabolomics. While the mass accuracy and resolving power of orbitraps have been extensively documented, their spectral accuracy, i.e., accuracy in measuring the abundances of isotopic peaks, remains less studied. In analyzing spectra of unlabeled metabolites, we discovered a systematic under representation of heavier natural isotopic species, especially for high molecular weight metabolites (∼20% under-measurement of [M + 1]/[M + 0] ratio at m/z 600). We hypothesize that these discrepancies arise for metabolites far from the lower limit of the mass scan range, due to the weaker containment in the C-trap that results in suboptimal trajectories inside the Orbitrap analyzer. Consistent with this, spectral fidelity was restored by dividing the mass scan range (initially 75 m/z to 1000 m/z) into two scan events, one for lower molecular weight and the other for higher molecular weight metabolites. Having thus obtained accurate mass spectra at high resolution, we found that natural isotope correction for high-resolution labeling data requires more sophisticated algorithms than typically employed: the correction algorithm must take into account whether isotopologues with the same nominal mass are resolved. We present an algorithm and associated open-source code, named AccuCor, for this purpose. Together, these improvements in instrument parameters and natural isotope correction enable more accurate measurement of metabolite labeling and thus metabolic flux.

Original languageEnglish (US)
Pages (from-to)5940-5948
Number of pages9
JournalAnalytical Chemistry
Issue number11
StatePublished - Jun 6 2017

All Science Journal Classification (ASJC) codes

  • Analytical Chemistry


Dive into the research topics of 'Metabolite Spectral Accuracy on Orbitraps'. Together they form a unique fingerprint.

Cite this