Quantitative estimation of activity and quality for collections of functional genetic elements

Vivek K. Mutalik, Joao C. Guimaraes, Guillaume Cambray, Quynh Anh Mai, Marc Juul Christoffersen, Lance Martin, Ayumi Yu, Colin Lam, Cesar Rodriguez, Gaymon Bennett, Jay D. Keasling, Drew Endy, Adam P. Arkin

Research output: Contribution to journalArticle

122 Scopus citations

Abstract

The practice of engineering biology now depends on the ad hoc reuse of genetic elements whose precise activities vary across changing contexts. Methods are lacking for researchers to affordably coordinate the quantification and analysis of part performance across varied environments, as needed to identify, evaluate and improve problematic part types. We developed an easy-to-use analysis of variance (ANOVA) framework for quantifying the performance of genetic elements. For proof of concept, we assembled and analyzed combinations of prokaryotic transcription and translation initiation elements in Escherichia coli. We determined how estimation of part activity relates to the number of unique element combinations tested, and we show how to estimate expected ensemble-wide part activity from just one or two measurements. We propose a new statistic, biomolecular part 'quality', for tracking quantitative variation in part performance across changing contexts.

Original languageEnglish (US)
Pages (from-to)347-353
Number of pages7
JournalNature Methods
Volume10
Issue number4
DOIs
StatePublished - Apr 1 2013
Externally publishedYes

ASJC Scopus subject areas

  • Biotechnology
  • Biochemistry
  • Molecular Biology
  • Cell Biology

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    Mutalik, V. K., Guimaraes, J. C., Cambray, G., Mai, Q. A., Christoffersen, M. J., Martin, L., Yu, A., Lam, C., Rodriguez, C., Bennett, G., Keasling, J. D., Endy, D., & Arkin, A. P. (2013). Quantitative estimation of activity and quality for collections of functional genetic elements. Nature Methods, 10(4), 347-353. https://doi.org/10.1038/nmeth.2403