Data from: Membrane phase separation drives responsive assembly of receptor signaling domains Article Swipe
Sarah A. Shelby
,
Ivan Castello-Serrano
,
Kathleen Wisser
,
Ilya Levental
,
Sarah L. Veatch
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.7508426
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.5281/zenodo.7508426
Plasma membrane heterogeneity has been tied to a litany of cellular functions and is often explained by analogy to membrane phase separation, yet models based on phase separation alone fall short of describing the rich organization available within cell membranes. We present comprehensive experimental evidence motivating an updated model of plasma membrane heterogeneity in which membrane domains assemble in response to protein scaffolds. Quantitative super-resolution nanoscopy measurements in live B lymphocytes detect membrane domains that emerge upon clustering B cell receptors (BCR). These domains enrich and retain membrane proteins based on their preference for the liquid-ordered phase. Unlike phase separated membranes that consist of binary phases with defined compositions, membrane composition at BCR clusters is modulated through the protein constituents in clusters or the composition of the membrane overall. This tunable domain structure is detected through the variable sorting of membrane probes and impacts the magnitude of BCR activation.
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https://doi.org/10.5281/zenodo.7508426Digital Object Identifier
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Data from: Membrane phase separation drives responsive assembly of receptor signaling domainsWork title
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datasetOpenAlex work type
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2023Year of publication
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2023-01-05Full publication date if available
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Sarah A. Shelby, Ivan Castello-Serrano, Kathleen Wisser, Ilya Levental, Sarah L. VeatchList of authors in order
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https://zenodo.org/record/7508426Publisher landing page
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://zenodo.org/record/7508426Direct OA link when available
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Separation (statistics), Membrane, Chemistry, Phase (matter), Cell biology, Biophysics, Biology, Computer science, Biochemistry, Machine learning, Organic chemistryTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.measurements | 66 |
| abstract_inverted_index.organization | 35 |
| abstract_inverted_index.compositions, | 108 |
| abstract_inverted_index.comprehensive | 42 |
| abstract_inverted_index.heterogeneity | 2, 52 |
| abstract_inverted_index.liquid-ordered | 95 |
| abstract_inverted_index.super-resolution | 64 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| citation_normalized_percentile |