Abstract
This work describes the development and characterization
of a modular synthetic expression system that provides a
broad range of adjustable and predictable expression
levels in S. cerevisiae. The system works as a fixed-gain
transcription amplifier, where the input signal is
transferred via a synthetic transcription factor (sTF)
onto a synthetic promoter, containing a defined core
promoter, generating a transcription output signal. The
system activation is based on the bacterial
LexA-DNA-binding domain, a set of modified, modular
LexA-binding sites and a selection of transcription
activation domains. We show both experimentally and
computationally that the tuning of the system is achieved
through the selection of three separate modules, each of
which enables an adjustable output signal: 1) the
transcription-activation domain of the sTF, 2) the
binding-site modules in the output promoter, and 3) the
core promoter modules which define the transcription
initiation site in the output promoter. The system has a
novel bidirectional architecture that enables generation
of compact, yet versatile expression modules for multiple
genes with highly diversified expression levels ranging
from negligible to very strong using one synthetic
transcription factor. In contrast to most existing
modular gene expression regulation systems, the present
system is independent from externally added compounds.
Furthermore, the established system was minimally
affected by the several tested growth conditions. These
features suggest that it can be highly useful in large
scale biotechnology applications. © 2016 Rantasalo et al.
This is an open access article distributed under the
terms of the Creative Commons Attribution License, which
permits unrestricted use, distribution, and reproduction
in any medium, provided the original author and source
are credited.
| Original language | English |
|---|---|
| Article number | e0148320 |
| Journal | PLoS ONE |
| Volume | 11 |
| Issue number | 2 |
| DOIs | |
| Publication status | Published - 2016 |
| MoE publication type | A1 Journal article-refereed |
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