Can protein expression be "solved"?
Creators
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Baranowski, Catherine
(Researcher)1
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Martin, Hector Garcia
(Researcher)2
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Oyarzún, Diego
(Researcher)3
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Petzold, Christopher
(Researcher)4
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Nikolados, Evangelos-Marios
(Researcher)3
- Jaaks-Kraatz, Sebastian (Researcher)5
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Gaber, Aljaž
(Researcher)6
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Chalkley, Robert
(Researcher)7
- Scannell, Devin (Researcher)
- Sevey, Rachel (Project member)
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Jewett, Michael
(Researcher)8
- Kelly, Peter (Project leader)1
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DeBenedictis, Erika
(Project member)1
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Align to Innovate
(Hosting institution)
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1.
Align to Innovate
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2.
Lawrence Berkeley National Laboratory
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3.
University of Edinburgh
- 4. E O Lawrence Berkeley National Laboratory
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5.
Friedrich Miescher Institute
- 6. Univerza v Ljubljani Fakulteta za Kemijo in Kemijsko tehnologijo
-
7.
University of California, San Francisco
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8.
Stanford University
Description
Recombinant protein expression is central to biotechnology’s application in academic exploration as well as human health, climate applications and the bioeconomy in general. However, not all proteins can be expressed in all organisms, and the field lacks a predictive model of soluble protein overexpression that could replace laborious experimental trial-and-error. Here, we discuss the state of the field and identify the lack of large, high-fidelity datasets as the primary bottleneck to progress. We review possible assays that could be used for data collection to identify a path toward an extensible experimental platform for collecting soluble recombinant protein overexpression data across organisms. We suggest that the resulting dataset should be used to train increasingly generalizable predictive models of protein expression to answer the question: “How can predictive protein expression be solved?”.
Files
Can protein expression be “solved”.pdf
Files
(3.8 MB)
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