The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Metabolic glycoengineering: Sialic acid and beyond
Open accessAbstract
This report provides a perspective on metabolic glycoengineering methodology developed over the past two decades that allows natural sialic acids to be replaced with chemical variants in living cells and animals. Examples are given demonstrating how this technology provides the glycoscientist with chemical tools that are beginning to reproduce Mother Nature's control over complex biological systems - such as the human brain - through subtle modifications in sialic acid chemistry. Several metabolic substrates (e.g., ManNAc, Neu5Ac, and CMP-Neu5Ac analogs) can be used to feed flux into the sialic acid biosynthetic pathway resulting in numerous - and sometime quite unexpected - biological repercussions upon nonnatural sialoside display in cellular glycans. Once on the cell surface, ketone-, azide-, thiol-, or alkyne-modified glycans can be transformed with numerous ligands via bioorthogonal chemoselective ligation reactions, greatly increasing the versatility and potential application of this technology. Recently, sialic acid glycoengineering methodology has been extended to other pathways with analog incorporation now possible in surface-displayed GalNAc and fucose residues as well as nucleocytoplasmic O-GlcNAc-modified proteins. Finally, recent efforts to increase the "druggability" of sugar analogs used in metabolic glycoengineering, which have resulted in unanticipated "scaffold-dependent" activities, are summarized.
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
Influenza virus receptors in the human airway
Shinya, K., Ebina, M., Yamada, S., Ono, M., Kasai, N., & Kawaoka, Y. (2006) · Nature · doi:10.1038/440435a · Cited by 1,398
Lau, K. S., Partridge, E. A., Grigorian, A., Silvescu, C. I., Reinhold, V. N., Demetriou, M., & Dennis, J. W. (2007) · Cell · doi:10.1016/j.cell.2007.01.049 · Cited by 914
Simpson, M. A., Cross, H., Proukakis, C., Priestman, D. A., Neville, D. C. A., Reinkensmeier, G., Wang, H., Wiznitzer, M., Gurtz, K., Verganelaki, A., et al. (2004) · Nature Genetics · doi:10.1038/ng1460 · Cited by 389
Correction of leukocyte adhesion deficiency type II with oral fucose
Marquardt, T., Lühn, K., Srikrishna, G., Freeze, H. H., Harms, E., & Vestweber, D. (1999) · Blood · doi:10.1182/blood.v94.12.3976 · Cited by 280
Ladeby, R., Wirenfeldt, M., Dalmau, I., Gregersen, R., García‐Ovejero, D., Babcock, A., Owens, T., & Finsen, B. (2005) · Glia · doi:10.1002/glia.20159 · Cited by 137 · cited 2×
“To provide representative examples of each linkage, CD34 is a stem cell marker that proliferating resident microglia express in response to acute neural injury (Ladeby et al. 2005) that predominantly displays α2,3-linked sialic acid in the form of sLeX (Lanza et al. 2001).”
Background
Cited by
Agarwal, P., & Bertozzi, C. R. (2015) · Bioconjugate Chemistry · doi:10.1021/bc5004982 · Cited by 605
Wang, X., Ding, B., Sun, G., Wang, M., & Yu, J. (2013) · Progress in Materials Science · doi:10.1016/j.pmatsci.2013.05.001 · Cited by 533
Insights into the role of sialylation in cancer progression and metastasis
Dobie, C., & Skropeta, D. (2021) · British Journal of Cancer · doi:10.1038/s41416-020-01126-7 · Cited by 348
Sialic acid metabolism and sialyltransferases: natural functions and applications
Li, Y., & Chen, X. (2012) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-012-4040-1 · Cited by 281
Amano, M., Eriksson, H., Manning, J. C., Detjen, K. M., André, S., Nishimura, S., Lehtiö, J., & Gabius, H. (2012) · The FEBS Journal · doi:10.1111/febs.12001 · Cited by 111
Metadata
- Authors
- Du, J., Meledeo, M. A., Wang, Z., Khanna, H. S., Paruchuri, V. D. P., & Yarema, K. J.
- Venue
- Glycobiology
- Publisher
- Oxford University Press (OUP)
- Published
- 2009-08-12
- Volume
- 19
- Issue
- 12
- Pages
- 1382-1401
- ISSN
- 0959-6658 (ISSN-L)
- 1460-2423
- OpenAlex
- W2110731978
- Cited by
- 299
- References
- 5
- FWCI
- 5.76
- Type
- journal article
- Language
- en
- Open access
- bronze
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: Metabolic glycoengineering: Sialic acid and beyond. https://app.cochat.ai/papers/10.1093/glycob/cwp115
- The paper
- Du, J., Meledeo, M. A., Wang, Z., Khanna, H. S., Paruchuri, V. D. P., & Yarema, K. J. (2009). Metabolic glycoengineering: Sialic acid and beyond. Glycobiology. https://doi.org/10.1093/glycob/cwp115
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.