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Analysis of Surface Protein Expression Reveals the Growth Pattern of the Gram-Negative Outer Membrane

Overview of attention for article published in PLoS Computational Biology, September 2012
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Title
Analysis of Surface Protein Expression Reveals the Growth Pattern of the Gram-Negative Outer Membrane
Published in
PLoS Computational Biology, September 2012
DOI 10.1371/journal.pcbi.1002680
Pubmed ID
Authors

Tristan S. Ursell, Eliane H. Trepagnier, Kerwyn Casey Huang, Julie A. Theriot

Abstract

The outer membrane (OM) of Gram-negative bacteria is a complex bilayer composed of proteins, phospholipids, lipoproteins, and lipopolysaccharides. Despite recent advances revealing the molecular pathways underlying protein and lipopolysaccharide incorporation into the OM, the spatial distribution and dynamic regulation of these processes remain poorly understood. Here, we used sequence-specific fluorescent labeling to map the incorporation patterns of an OM-porin protein, LamB, by labeling proteins only after epitope exposure on the cell surface. Newly synthesized LamB appeared in discrete puncta, rather than evenly distributed over the cell surface. Further growth of bacteria after labeling resulted in divergence of labeled LamB puncta, consistent with a spatial pattern of OM growth in which new, unlabeled material was also inserted in patches. At the poles, puncta remained relatively stationary through several rounds of division, a salient characteristic of the OM protein population as a whole. We propose a biophysical model of growth in which patches of new OM material are added in discrete bursts that evolve in time according to Stokes flow and are randomly distributed over the cell surface. Simulations based on this model demonstrate that our experimental observations are consistent with a bursty insertion pattern without spatial bias across the cylindrical cell surface, with approximately one burst of ≈ 10(-2) µm(2) of OM material per two minutes per µm(2). Growth by insertion of discrete patches suggests that stochasticity plays a major role in patterning and material organization in the OM.

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Geographical breakdown

Country Count As %
United States 1 1%
India 1 1%
Lithuania 1 1%
Unknown 90 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 32 34%
Researcher 18 19%
Student > Bachelor 9 10%
Student > Master 6 6%
Student > Doctoral Student 5 5%
Other 10 11%
Unknown 13 14%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 30 32%
Agricultural and Biological Sciences 29 31%
Chemistry 7 8%
Engineering 4 4%
Immunology and Microbiology 2 2%
Other 5 5%
Unknown 16 17%