Title |
High-efficacy subcellular micropatterning of proteins using fibrinogen anchors
|
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Published in |
Journal of Cell Biology, January 2021
|
DOI | 10.1083/jcb.202009063 |
Pubmed ID | |
Authors |
Joseph L. Watson, Samya Aich, Benjamí Oller-Salvia, Andrew A. Drabek, Stephen C. Blacklow, Jason Chin, Emmanuel Derivery |
Abstract |
Protein micropatterning allows proteins to be precisely deposited onto a substrate of choice and is now routinely used in cell biology and in vitro reconstitution. However, drawbacks of current technology are that micropatterning efficiency can be variable between proteins and that proteins may lose activity on the micropatterns. Here, we describe a general method to enable micropatterning of virtually any protein at high specificity and homogeneity while maintaining its activity. Our method is based on an anchor that micropatterns well, fibrinogen, which we functionalized to bind to common purification tags. This enhances micropatterning on various substrates, facilitates multiplexed micropatterning, and dramatically improves the on-pattern activity of fragile proteins like molecular motors. Furthermore, it enhances the micropatterning of hard-to-micropattern cells. Last, this method enables subcellular micropatterning, whereby complex micropatterns simultaneously control cell shape and the distribution of transmembrane receptors within that cell. Altogether, these results open new avenues for cell biology. |
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Geographical breakdown
Country | Count | As % |
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United Kingdom | 7 | 18% |
United States | 4 | 10% |
Germany | 3 | 8% |
Canada | 2 | 5% |
France | 2 | 5% |
Italy | 1 | 3% |
Japan | 1 | 3% |
Denmark | 1 | 3% |
Austria | 1 | 3% |
Other | 2 | 5% |
Unknown | 15 | 38% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 19 | 49% |
Scientists | 18 | 46% |
Practitioners (doctors, other healthcare professionals) | 1 | 3% |
Science communicators (journalists, bloggers, editors) | 1 | 3% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 58 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 10 | 17% |
Student > Master | 9 | 16% |
Student > Bachelor | 6 | 10% |
Researcher | 5 | 9% |
Other | 3 | 5% |
Other | 8 | 14% |
Unknown | 17 | 29% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 22 | 38% |
Agricultural and Biological Sciences | 6 | 10% |
Physics and Astronomy | 2 | 3% |
Chemistry | 2 | 3% |
Engineering | 2 | 3% |
Other | 5 | 9% |
Unknown | 19 | 33% |