The DOI matches its Crossref record.
Quantitative Analysis of Bacterial and Mammalian Proteomes Using a Combination of Cysteine Affinity Tags and 15N-Metabolic Labeling
Abstract
We describe the combined use of 15N-metabolic labeling and a cysteine-reactive biotin affinity tag to isolate and quantitate cysteine-containing polypeptides (Cys-polypeptides) from Deinococcus radiodurans as well as from mouse B16 melanoma cells. D. radiodurans were cultured in both natural isotopic abundance and 15N-enriched media. Equal numbers of cells from both cultures were combined and the soluble proteins extracted. This mixture of isotopically distinct proteins was derivatized using a commercially available cysteine-reactive reagent that contains a biotin group. Following trypsin digestion, the resulting modified peptides were isolated using immobilized avidin. The mixture was analyzed by capillary reversed-phase liquid chromatography (LC) online with ion trap mass spectrometry (MS) as well as Fourier transform ion cyclotron resonance (FTICR) MS. The resulting spectra contain numerous pairs of Cyspolypeptides whose mass difference corresponds to the number of nitrogen atoms present in each of the peptides. Designation of Cys-polypeptide pairs is also facilitated by the distinctive isotopic distribution of the 15N-labeled peptides versus their 14N-labeled counterparts. Studies with mouse B16 cells maintained in culture allowed the observation of hundreds of isotopically distinct pairs of peptides by LC-FTICR analysis. The ratios of the areas of the pairs of isotopically distinct peptides showed the expected 1:1 labeling of the 14N and 15N versions of each peptide. An additional benefit from the present strategy is that the 15N-labeled peptides do not display significant isotope-dependent chromatographic shifts from their 14N-labeled counterparts, therefore improving the precision for quantitating peptide abundances. The methodology presented offers an alternate, cost-effective strategy for conducting global, quantitative proteomic measurements.
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
Cited by
Mass spectrometry–based proteomics turns quantitative
Ong, S.-E., & Mann, M. (2005) · Nature Chemical Biology · doi:10.1038/nchembio736 · Cited by 1,572
Protein Analysis by Shotgun/Bottom-up Proteomics
Zhang, Y., Fonslow, B. R., Shan, B., Baek, M.-C., & Yates, J. R. (2013) · Chemical Reviews · doi:10.1021/cr3003533 · Cited by 1,491
Quantitative, High-Resolution Proteomics for Data-Driven Systems Biology
Cox, J., & Mann, M. (2011) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-061308-093216 · Cited by 685
Proteomics in gram‐negative bacterial outer membrane vesicles
Lee, E., Choi, D., Kim, K., & Gho, Y. S. (2008) · Mass Spectrometry Reviews · doi:10.1002/mas.20175 · Cited by 339
Methods for samples preparation in proteomic research
Bodzon-Kulakowska, A., Bierczynska-Krzysik, A., Dylag, T., Drabik, A., Suder, P., Noga, M., Jarzebinska, J., & Silberring, J. (2007) · Journal of Chromatography B · doi:10.1016/j.jchromb.2006.10.040 · Cited by 254
Metadata
- Authors
- Conrads, T. P., Alving, K., Veenstra, T. D., Belov, M. E., Anderson, G. A., Anderson, D. J., Lipton, M. S., Paša-Tolić, L., Udseth, H. R., Chrisler, W. B., Thrall, B. D., & Smith, R. D.
- Venue
- Analytical Chemistry
- Publisher
- American Chemical Society (ACS)
- Published
- 2001-03-13
- Volume
- 73
- Issue
- 9
- Pages
- 2132-2139
- ISSN
- 0003-2700 (ISSN-L)
- 1520-6882
- OpenAlex
- W1997898173
- Cited by
- 286
- References
- 0
- FWCI
- 19.87
- Type
- journal article
- Language
- en
- Open access
- closed
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: Quantitative Analysis of Bacterial and Mammalian Proteomes Using a Combination of Cysteine Affinity Tags and 15N-Metabolic Labeling. https://app.cochat.ai/papers/10.1021/ac001487x
- The paper
- Conrads, T. P., Alving, K., Veenstra, T. D., Belov, M. E., Anderson, G. A., Anderson, D. J., Lipton, M. S., Paša-Tolić, L., Udseth, H. R., Chrisler, W. B., Thrall, B. D., & Smith, R. D. (2001). Quantitative Analysis of Bacterial and Mammalian Proteomes Using a Combination of Cysteine Affinity Tags and 15N-Metabolic Labeling. Analytical Chemistry. https://doi.org/10.1021/ac001487x
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.