The DOI matches its Crossref record; 55 of the 55 references it cites were found in a registry or an index.
Divergent Effects of Human Cytomegalovirus and Herpes Simplex Virus-1 on Cellular Metabolism
Open accessAbstract
Viruses rely on the metabolic network of the host cell to provide energy and macromolecular precursors to fuel viral replication. Here we used mass spectrometry to examine the impact of two related herpesviruses, human cytomegalovirus (HCMV) and herpes simplex virus type-1 (HSV-1), on the metabolism of fibroblast and epithelial host cells. Each virus triggered strong metabolic changes that were conserved across different host cell types. The metabolic effects of the two viruses were, however, largely distinct. HCMV but not HSV-1 increased glycolytic flux. HCMV profoundly increased TCA compound levels and flow of two carbon units required for TCA cycle turning and fatty acid synthesis. HSV-1 increased anapleurotic influx to the TCA cycle through pyruvate carboxylase, feeding pyrimidine biosynthesis. Thus, these two related herpesviruses drive diverse host cells to execute distinct, virus-specific metabolic programs. Current drugs target nucleotide metabolism for treatment of both viruses. Although our results confirm that this is a robust target for HSV-1, therapeutic interventions at other points in metabolism might prove more effective for treatment of HCMV.
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
Metabolomics—the link between genotypes and phenotypes
Fiehn, O. (2002) · Plant Molecular Biology · doi:10.1023/a:1013713905833 · Cited by 3,445
Metabolomics — the link between genotypes and phenotypes
Fiehn, O. (2002) · Functional Genomics · doi:10.1007/978-94-010-0448-0_11 · Cited by 3,167
Singular value decomposition for genome-wide expression data processing and modeling
Alter, O., Brown, P. O., & Botstein, D. (2000) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.97.18.10101 · Cited by 1,971
Metabolomics--the link between genotypes and phenotypes.
Fiehn, O. (2002) · PubMed · Cited by 1,517
Physiology of cell volume regulation in vertebrates
Hoffmann, E. K., Lambert, I. H., & Pedersen, S. F. (2009) · Physiological Reviews · doi:10.1152/physrev.00037.2007 · Cited by 1,441
Ejercito, P. M., Kieff, E. D., & Roizman, B. (1968) · Journal of General Virology · doi:10.1099/0022-1317-2-3-357 · Cited by 875
Munger, J., Bennett, B. D., Parikh, A., Feng, X.-J., McArdle, J., Rabitz, H. A., Shenk, T., & Rabinowitz, J. D. (2008) · Nature Biotechnology · doi:10.1038/nbt.1500 · Cited by 635
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-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-citationAnalytical strategies for LC–MS-based targeted metabolomics
Lu, W., Bennett, B. D., & Rabinowitz, J. D. (2008) · Journal of Chromatography B · doi:10.1016/j.jchromb.2008.04.031 · Cited by 481
Self-citation
Cited by
NAD+ metabolism: pathophysiologic mechanisms and therapeutic potential
Xie, N., Zhang, L., Gao, W., Huang, C., Huber, P. E., Zhou, X., Li, C., Shen, G., & Zou, B. (2020) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-020-00311-7 · Cited by 1,052
Predicting Network Activity from High Throughput Metabolomics
Li, S., Park, Y., Duraisingham, S., Strobel, F. H., Khan, N., Soltow, Q. A., Jones, D. P., & Pulendran, B. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003123 · Cited by 936
Viral activation of cellular metabolism
Sanchez, E. L., & Lagunoff, M. (2015) · Virology · doi:10.1016/j.virol.2015.02.038 · Cited by 560
Viral hijacking of cellular metabolism
Thaker, S. K., Ch’ng, J., & Christofk, H. R. (2019) · BMC Biology · doi:10.1186/s12915-019-0678-9 · Cited by 526
Targeting metabolic reprogramming by influenza infection for therapeutic intervention
Smallwood, H. S., Duan, S., Morfouace, M., Rezinciuc, S., Shulkin, B. L., Shelat, A., Zink, E. E., Milasta, S., Bajracharya, R., Oluwaseum, A. J., et al. (2017) · Cell Reports · doi:10.1016/j.celrep.2017.04.039 · Cited by 171
Metadata
- Authors
- Vastag, L., Koyuncu, E., Grady, S. L., Shenk, T. E., & Rabinowitz, J. D.
- Venue
- PLoS Pathogens
- Publisher
- Public Library of Science (PLoS)
- Published
- 2011-07-14
- Volume
- 7
- Issue
- 7
- Pages
- e1002124
- ISSN
- 1553-7366 (ISSN-L)
- 1553-7374
- OpenAlex
- W2083829813
- Cited by
- 358
- References
- 55
- FWCI
- 11.02
- Type
- journal article
- Language
- en
- Open access
- gold
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: Divergent Effects of Human Cytomegalovirus and Herpes Simplex Virus-1 on Cellular Metabolism. https://app.cochat.ai/papers/10.1371/journal.ppat.1002124
- The paper
- Vastag, L., Koyuncu, E., Grady, S. L., Shenk, T. E., & Rabinowitz, J. D. (2011). Divergent Effects of Human Cytomegalovirus and Herpes Simplex Virus-1 on Cellular Metabolism. PLoS Pathogens. https://doi.org/10.1371/journal.ppat.1002124
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.
