The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Development and Quantitative Evaluation of a High-Resolution Metabolomics Technology
Open accessAbstract
Recent advances in mass spectrometry have allowed for unprecedented characterization of human metabolism and its contribution to disease. Despite these advances, limitations in metabolomics technology remain. Here, we describe a metabolomics strategy that consolidates several recent improvements in mass spectrometry technology. The platform involves a high-resolution Orbitrap mass spectrometer coupled to faster scanning speeds, allowing for polarity switching and improved ion optics resulting in enhanced sensitivity. When coupled to HILIC chromatography, we are able to quantify over 339 metabolites from an extract of HCT8 cells with a linear range of over 4 orders of magnitude in a single chromatographic run. These metabolites include diverse chemical classes ranging from amino acids to polar lipids. In addition, we also detect over 3000 additional potential metabolites present in mammalian cells. We applied this platform to characterize the metabolome of eight colorectal cancer cell lines and observed both commonalities and heterogeneities across their metabolic profiles when cells are grown in identical conditions. Together these results demonstrate that simultaneous profiling and quantitation of the human metabolome is feasible.
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
Cancer-associated IDH1 mutations produce 2-hydroxyglutarate
Dang, L., White, D. W., Gross, S., Bennett, B. D., Bittinger, M. A., Driggers, E. M., Fantin, V. R., Jang, H. G., Jin, S., Keenan, M. C., et al. (2009) · Nature · doi:10.1038/nature08617 · Cited by 4,154
The M2 splice isoform of pyruvate kinase is important for cancer metabolism and tumour growth
Christofk, H. R., Vander Heiden, M. G., Harris, M. H., Ramanathan, A., Gerszten, R. E., Wei, R., Fleming, M. D., Schreiber, S. L., & Cantley, L. C. (2008) · Nature · doi:10.1038/nature06734 · Cited by 2,820
Phosphoglycerate dehydrogenase diverts glycolytic flux and contributes to oncogenesis
Locasale, J. W., Grassian, A. R., Melman, T., Lyssiotis, C. A., Mattaini, K. R., Bass, A. J., Heffron, G., Metallo, C. M., Muranen, T., Sharfi, H., et al. (2011) · Nature Genetics · doi:10.1038/ng.890 · Cited by 1,120
Self-citationA community-driven global reconstruction of human metabolism
Thiele, I., Swainston, N., Fleming, R. M. T., Hoppe, A., Sahoo, S., Aurich, M. K., Haraldsdottir, H., Mo, M. L., Rolfsson, O., Stobbe, M. D., et al. (2013) · Nature Biotechnology · doi:10.1038/nbt.2488 · Cited by 1,019
Michalski, A., Damoc, E., Hauschild, J.-P., Lange, O., Wieghaus, A., Makarov, A., Nagaraj, N., Cox, J., Mann, M., & Horning, S. (2011) · Molecular & Cellular Proteomics · doi:10.1074/mcp.m111.011015 · Cited by 832
Cited by
Cajka, T., & Fiehn, O. (2016) · Analytical Chemistry · doi:10.1021/acs.analchem.5b04491 · Cited by 830
Metabolic programming and PDHK1 control CD4+ T cell subsets and inflammation
Gerriets, V. A., Kishton, R. J., Nichols, A. G., Macintyre, A. N., Inoue, M., Ilkayeva, O., Winter, P. S., Liu, X., Priyadharshini, B., Slawinska, M. E., et al. (2015) · Journal of Clinical Investigation · doi:10.1172/jci76012 · Cited by 731
Self-citationHistone Methylation Dynamics and Gene Regulation Occur through the Sensing of One-Carbon Metabolism
Mentch, S. J., Mehrmohamadi, M., Huang, L., Liu, X., Gupta, D., Mattocks, D., Gómez Padilla, P., Ables, G., Bamman, M. M., Thalacker-Mercer, A. E., et al. (2015) · Cell Metabolism · doi:10.1016/j.cmet.2015.08.024 · Cited by 694
Self-citationA 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-citationMcDonald, O. G., Li, X., Saunders, T., Tryggvadottir, R., Mentch, S. J., Warmoes, M. O., Word, A. E., Carrer, A., Salz, T. H., Natsume, S., et al. (2017) · Nature Genetics · doi:10.1038/ng.3753 · Cited by 494
Self-citation
Metadata
- Authors
- Liu, X., Ser, Z., & Locasale, J. W.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-01-28
- Volume
- 86
- Issue
- 4
- Pages
- 2175-2184
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W2081311904
- Cited by
- 179
- References
- 5
- FWCI
- 7.79
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: Development and Quantitative Evaluation of a High-Resolution Metabolomics Technology. https://app.cochat.ai/papers/10.1021/ac403845u
- The paper
- Liu, X., Ser, Z., & Locasale, J. W. (2014). Development and Quantitative Evaluation of a High-Resolution Metabolomics Technology. Analytical Chemistry. https://doi.org/10.1021/ac403845u
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.
