Publication: Exploring the Impact of Terminators on Transgene Expression in Chlamydomonas reinhardtii with a Synthetic Biology Approach

OpenPlant PI Alison Smith and her colleagues at the University of Cambridge have recently published a new paper describing their use of synthetic biology tools to screen for improved levels of gene expression in the algae Chlamydomonas reinhardtii. Their work provides a new approach for systematic testing of genetic elements for optimal transgene design, and identifies an optimal terminator size for use in Chlamydomonas.

Exploring the Impact of Terminators on Transgene Expression in Chlamydomonas reinhardtii with a Synthetic Biology Approach

Katrin Geisler, Mark A Scaife, Paweł M Mordaka, Andre Holzer, Eleanor V Tomsett, Payam Mehrshahi, Gonzalo I Mendoza Ochoa, Alison G Smith.

Life (Basel) 2021 Sep 14;11(9):964

https://doi.org/10.3390/life11090964

ABSTRACT

Chlamydomonas reinhardtii has many attractive features for use as a model organism for both fundamental studies and as a biotechnological platform. Nonetheless, despite the many molecular tools and resources that have been developed, there are challenges for its successful engineering, in particular to obtain reproducible and high levels of transgene expression. Here we describe a synthetic biology approach to screen several hundred independent transformants using standardised parts to explore different parameters that might affect transgene expression. We focused on terminators and, using a standardised workflow and quantitative outputs, tested 9 different elements representing three different size classes of native terminators to determine their ability to support high level expression of a GFP reporter gene. We found that the optimal size reflected the median size of element found in the C. reinhardtii genome. The behaviour of the terminator parts was similar with different promoters, in different host strains and with different transgenes. This approach is applicable to the systematic testing of other genetic elements, facilitating comparison to determine optimal transgene design.