Open Access Method

A phenotypic screening platform to identify small molecule modulators of Chlamydomonas reinhardtii growth, motility and photosynthesis

Simon E Alfred1,2,3, Anuradha Surendra1,2,4, Chris Le1, Ken Lin1, Alexander Mok1, Iain M Wallace1,6, Michael Proctor5, Malene L Urbanus1,4, Guri Giaever1,3,4 and Corey Nislow1,2,3*

Author Affiliations

1 Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, 160 College Street, Toronto, Ontario M5S 3E1, Canada

2 Banting and Best Department of Medical Research, University of Toronto, 112 College Street, Toronto, Ontario M5G 1L6, Canada

3 Department of Molecular Genetics, University of Toronto, 1 King's College Circle, Toronto, Ontario, M5A 1A8, Canada

4 Department of Pharmaceutical Sciences, University of Toronto, 144 College Street, Toronto, Ontario M5S 3M2, Canada

5 Stanford Genome Technology Center, Palo Alto, CA 94304, USA

6 Novartis, 250 Massachusetts Ave., Cambridge 02139, USA

For all author emails, please log on.

Genome Biology 2012, 13:R105 doi:10.1186/gb-2012-13-11-r105

Published: 18 November 2012

Abstract

Chemical biology, the interfacial discipline of using small molecules as probes to investigate biology, is a powerful approach of developing specific, rapidly acting tools that can be applied across organisms. The single-celled alga Chlamydomonas reinhardtii is an excellent model system because of its photosynthetic ability, cilia-related motility and simple genetics. We report the results of an automated fitness screen of 5,445 small molecules and subsequent assays on motility/phototaxis and photosynthesis. Cheminformatic analysis revealed active core structures and was used to construct a naïve Bayes model that successfully predicts algal bioactive compounds.