Chapter title |
Comprehensive Analysis of Immunological Synapse Phenotypes Using Supported Lipid Bilayers
|
---|---|
Chapter number | 26 |
Book title |
The Immune Synapse
|
Published in |
Methods in molecular biology, March 2017
|
DOI | 10.1007/978-1-4939-6881-7_26 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6879-4, 978-1-4939-6881-7
|
Authors |
Salvatore Valvo, Viveka Mayya, Elena Seraia, Jehan Afrose, Hila Novak-Kotzer, Daniel Ebner, Michael L. Dustin, Valvo, Salvatore, Mayya, Viveka, Seraia, Elena, Afrose, Jehan, Novak-Kotzer, Hila, Ebner, Daniel, Dustin, Michael L. |
Editors |
Cosima T. Baldari, Michael L. Dustin |
Abstract |
Supported lipid bilayers (SLB) formed on glass substrates have been a useful tool for study of immune cell signaling since the early 1980s. The mobility of lipid-anchored proteins in the system, first described for antibodies binding to synthetic phospholipid head groups, allows for the measurement of two-dimensional binding reactions and signaling processes in a single imaging plane over time or for fixed samples. The fragility of SLB and the challenges of building and validating individual substrates limit most experimenters to ~10 samples per day, perhaps increasing this few-fold when examining fixed samples. Successful experiments might then require further days to fully analyze. We present methods for automation of many steps in SLB formation, imaging in 96-well glass bottom plates, and analysis that enables >100-fold increase in throughput for fixed samples and wide-field fluorescence. This increased throughput will allow better coverage of relevant parameters and more comprehensive analysis of aspects of the immunological synapse that are well reconstituted by SLB. |
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Mendeley readers
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Demographic breakdown
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Researcher | 7 | 29% |
Student > Ph. D. Student | 6 | 25% |
Student > Master | 5 | 21% |
Professor > Associate Professor | 3 | 13% |
Student > Postgraduate | 1 | 4% |
Other | 0 | 0% |
Unknown | 2 | 8% |
Readers by discipline | Count | As % |
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Agricultural and Biological Sciences | 4 | 17% |
Immunology and Microbiology | 3 | 13% |
Medicine and Dentistry | 2 | 8% |
Materials Science | 2 | 8% |
Other | 6 | 25% |
Unknown | 3 | 13% |