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Cited by 443

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Protein Structures Forming the Shell of Primitive Bacterial Organelles

Kerfeld, Cheryl A., Sawaya, Michael R., Tanaka, Shiho, Nguyen, Chau V., Phillips, Martin, Beeby, Morgan, Yeates, Todd O.·2005·Science

Abstract

Bacterial microcompartments are primitive organelles composed entirely of protein subunits. Genomic sequence databases reveal the widespread occurrence of microcompartments across diverse microbes. The prototypical bacterial microcompartment is the carboxysome, a protein shell for sequestering carbon fixation reactions. We report three-dimensional crystal structures of multiple carboxysome shell proteins, revealing a hexameric unit as the basic microcompartment building block and showing how these hexamers assemble to form flat facets of the polyhedral shell. The structures suggest how molecular transport across the shell may be controlled and how structural variations might govern the assembly and architecture of these subcellular compartments.

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Crossref · 10.1126/science.1113397

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Metadata

Authors
Kerfeld, C. A., Sawaya, M. R., Tanaka, S., Nguyen, C. V., Phillips, M., Beeby, M., & Yeates, T. O.
Venue
Science
Published
2005-08-05
Volume
309
Issue
5736
Pages
936-938
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2103560494
Cited by
443
References
1
FWCI
10.68
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Protein Structures Forming the Shell of Primitive Bacterial Organelles. https://app.cochat.ai/papers/10.1126/science.1113397
The paper
Kerfeld, C. A., Sawaya, M. R., Tanaka, S., Nguyen, C. V., Phillips, M., Beeby, M., & Yeates, T. O. (2005). Protein Structures Forming the Shell of Primitive Bacterial Organelles. Science. https://doi.org/10.1126/science.1113397

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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.