The DOI matches its Crossref record; 77 of the 77 references it cites were found in a registry or an index.
Imaging proteins inside cells with fluorescent tags
Open accessAbstract
Watching biological molecules provides clues to their function and regulation. Some of the most powerful methods of labeling proteins for imaging use genetically encoded fluorescent fusion tags. There are four standard genetic methods of covalently tagging a protein with a fluorescent probe for cellular imaging. These use I) auto-fluorescent proteins, II) self-labeling enzymes, III) enzymes that catalyze the attachment of a probe to a target sequence, and IV) biarsenical dyes that target tetracysteine motifs. Each of these techniques has advantages and disadvantages. In this review, we cover new developments in these methods and discuss practical considerations for their use in imaging proteins inside living cells.
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Shaner, N. C., Campbell, R. E., Steinbach, P. A., Giepmans, B. N. G., Palmer, A. E., & Tsien, R. Y. (2004) · Nature Biotechnology · doi:10.1038/nbt1037 · Cited by 4,619
A guide to choosing fluorescent proteins
Shaner, N. C., Steinbach, P. A., & Tsien, R. Y. (2005) · Nature Methods · doi:10.1038/nmeth819 · Cited by 2,840
Nagai, T., Ibata, K., Park, E. S., Kubota, M., Mikoshiba, K., & Miyawaki, A. (2002) · Nature Biotechnology · doi:10.1038/nbt0102-87 · Cited by 2,753
A monomeric red fluorescent protein
Campbell, R. E., Tour, O., Palmer, A. E., Steinbach, P. A., Baird, G. S., Zacharias, D. A., & Tsien, R. Y. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.082243699 · Cited by 2,365
Engineering and characterization of a superfolder green fluorescent protein
Pédelacq, J.-D., Cabantous, S., Tran, T., Terwilliger, T. C., & Waldo, G. S. (2006) · Nature Biotechnology · doi:10.1038/nbt1172 · Cited by 2,291
Crystal Structure of the Aequorea victoria Green Fluorescent Protein
Ormö, M., Cubitt, A. B., Kallio, K., Gross, L. A., Tsien, R. Y., & Remington, S. J. (1996) · Science · doi:10.1126/science.273.5280.1392 · Cited by 2,242
Partitioning of Lipid-Modified Monomeric GFPs into Membrane Microdomains of Live Cells
Zacharias, D. A., Violin, J. D., Newton, A. C., & Tsien, R. Y. (2002) · Science · doi:10.1126/science.1068539 · Cited by 2,235
A general method for the covalent labeling of fusion proteins with small molecules in vivo
Keppler, A., Gendreizig, S., Gronemeyer, T., Pick, H., Vogel, H., & Johnsson, K. (2003) · Nature Biotechnology · doi:10.1038/nbt765 · Cited by 1,956
Huston, J. S., Levinson, D., Mudgett-Hunter, M., Tai, M. S., Novotný, J., Margolies, M. N., Ridge, R. J., Bruccoleri, R. E., Haber, E., & Crea, R. (1988) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.85.16.5879 · Cited by 1,593
Nanoscale architecture of integrin-based cell adhesions
Kanchanawong, P., Shtengel, G., Pasapera, A. M., Ramko, E. B., Davidson, M. W., Hess, H. F., & Waterman, C. M. (2010) · Nature · doi:10.1038/nature09621 · Cited by 1,567
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Recent progresses in small-molecule enzymatic fluorescent probes for cancer imaging
Liu, H.-W., Chen, L., Xu, C., Li, Z., Zhang, H., Zhang, X.-B., & Tan, W. (2018) · Chemical Society Reviews · doi:10.1039/c7cs00862g · Cited by 948
Crozet, P., Navarro, F. J., Willmund, F., Mehrshahi, P., Bakowski, K., Lauersen, K. J., Pérez-Pérez, M.-E., Auroy, P., Gorchs Rovira, A., Sauret-Gueto, S., et al. (2018) · ACS Synthetic Biology · doi:10.1021/acssynbio.8b00251 · Cited by 297
Gradient light interference microscopy for 3D imaging of unlabeled specimens
Nguyen, T. H., Kandel, M. E., Rubessa, M., Wheeler, M. B., & Popescu, G. (2017) · Nature Communications · doi:10.1038/s41467-017-00190-7 · Cited by 259
Metadata
- Authors
- Crivat, G., & Taraska, J. W.
- Venue
- Trends in Biotechnology
- Publisher
- Elsevier BV
- Published
- 2012-01
- Volume
- 30
- Issue
- 1
- Pages
- 8-16
- ISSN
- 0167-7799 (ISSN-L)
- OpenAlex
- W1985283191
- Cited by
- 291
- References
- 77
- FWCI
- 1.48
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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