The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Metabolite Spectral Accuracy on Orbitraps
Open accessAbstract
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.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Zubarev, R. A., & Makarov, A. (2013) · Analytical Chemistry · doi:10.1021/ac4001223 · Cited by 658
A roadmap for interpreting 13C metabolite labeling patterns from cells
Buescher, J. M., Antoniewicz, M. R., Boros, L. G., Burgess, S. C., Brunengraber, H., Clish, C. B., DeBerardinis, R. J., Feron, O., Frezza, C., Ghesquiere, B., et al. (2015) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2015.02.003 · Cited by 629
Self-citationMetabolomic Analysis and Visualization Engine for LC−MS Data
Melamud, E., Vastag, L., & Rabinowitz, J. D. (2010) · Analytical Chemistry · doi:10.1021/ac1021166 · Cited by 619
Self-citationElementary metabolite units (EMU): A novel framework for modeling isotopic distributions
Antoniewicz, M. R., Kelleher, J. K., & Stephanopoulos, G. (2007) · Metabolic Engineering · doi:10.1016/j.ymben.2006.09.001 · Cited by 538
Orbitrap mass spectrometry: Instrumentation, ion motion and applications
Perry, R. H., Cooks, R. G., & Noll, R. J. (2008) · Mass Spectrometry Reviews · doi:10.1002/mas.20186 · Cited by 514
LC‐MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine
Clasquin, M. F., Melamud, E., & Rabinowitz, J. D. (2012) · Current Protocols in Bioinformatics · doi:10.1002/0471250953.bi1411s37 · Cited by 514
Self-citationLu, W., Clasquin, M. F., Melamud, E., Amador-Noguez, D., Caudy, A. A., & Rabinowitz, J. D. (2010) · Analytical Chemistry · doi:10.1021/ac902837x · Cited by 502
Self-citationDetermination of confidence intervals of metabolic fluxes estimated from stable isotope measurements
Antoniewicz, M. R., Kelleher, J. K., & Stephanopoulos, G. (2006) · Metabolic Engineering · doi:10.1016/j.ymben.2006.01.004 · Cited by 449
ChemCalc: A building block for tomorrow’s chemical infrastructure
Patiny, L., & Borel, A. (2013) · Journal of Chemical Information and Modeling · doi:10.1021/ci300563h · Cited by 425
Defining the Metabolome: Size, Flux, and Regulation
Zamboni, N., Saghatelian, A., & Patti, G. J. (2015) · Molecular Cell · doi:10.1016/j.molcel.2015.04.021 · Cited by 300
Cited by
The Small Intestine Converts Dietary Fructose into Glucose and Organic Acids
Jang, C., Hui, S., Lu, W., Cowan, A. J., Morscher, R. J., Lee, G., Liu, W., Tesz, G. J., Birnbaum, M. J., & Rabinowitz, J. D. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2017.12.016 · Cited by 639
Self-citationQuantitative Analysis of NAD Synthesis-Breakdown Fluxes
Liu, L., Su, X., Quinn, W. J., Hui, S., Krukenberg, K., Frederick, D. W., Redpath, P., Zhan, L., Chellappa, K., White, E., et al. (2018) · Cell Metabolism · doi:10.1016/j.cmet.2018.03.018 · Cited by 564
Self-citationDietary fructose feeds hepatic lipogenesis via microbiota-derived acetate
Zhao, S., Jang, C., Liu, J., Uehara, K., Gilbert, M., Izzo, L., Zeng, X., Trefely, S., Fernandez, S., Carrer, A., et al. (2020) · Nature · doi:10.1038/s41586-020-2101-7 · Cited by 553
Self-citationDu, D., Tan, L., Wang, Y., Peng, B., Weinstein, J. N., Wondisford, F. E., Su, X., & Lorenzi, P. L. (2019) · BMC Bioinformatics · doi:10.1186/s12859-019-2669-9 · Cited by 549
Self-citationMacrophage de novo NAD+ synthesis specifies immune function in aging and inflammation
Minhas, P. S., Liu, L., Moon, P. K., Joshi, A. U., Dove, C., Mhatre, S., Contrepois, K., Wang, Q., Lee, B. A., Coronado, M., et al. (2019) · Nature Immunology · doi:10.1038/s41590-018-0255-3 · Cited by 501
Self-citation
Metadata
- Authors
- Su, X., Lu, W., & Rabinowitz, J. D.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-05-18
- Volume
- 89
- Issue
- 11
- Pages
- 5940-5948
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W2610435987
- Cited by
- 285
- References
- 21
- FWCI
- 7.18
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Metabolite Spectral Accuracy on Orbitraps. https://app.cochat.ai/papers/10.1021/acs.analchem.7b00396
- The paper
- Su, X., Lu, W., & Rabinowitz, J. D. (2017). Metabolite Spectral Accuracy on Orbitraps. Analytical Chemistry. https://doi.org/10.1021/acs.analchem.7b00396
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.