ABSTRACT
Advancements in the field of synthetic biology have been possible due to the development of genetic tools that are able to regulate gene expression. However, the current toolbox of gene regulatory tools for eukaryotic systems have been outpaced by those developed for simple, single-celled systems. Here, we engineered a set of gene regulatory tools by combining self-cleaving ribozymes with various upstream competing sequences that were designed to disrupt ribozyme self-cleavage. As a proof-of-concept, we were able to modulate GFP expression in mammalian cells, and then showed the feasibility of these tools in Drosophila embryos. For each system, the fold-reduction of gene expression was influenced by the location of the self-cleaving ribozyme/upstream competing sequence (i.e. 5' vs. 3' untranslated region) and the competing sequence used. Together, this work provides a set of genetic tools that can be used to tune gene expression across various eukaryotic systems.
Subject(s)
Genetic Engineering/methods , RNA, Catalytic/physiology , Synthetic Biology/methods , Animals , Drosophila/genetics , Eukaryota/genetics , Eukaryota/metabolism , Eukaryotic Cells/metabolism , Gene Expression/genetics , Gene Expression/physiology , Gene Expression Regulation/genetics , Gene Expression Regulation/physiology , Nucleic Acid Conformation , Proof of Concept Study , RNA, Catalytic/genetics , RNA, Messenger/metabolismABSTRACT
BACKGROUND: A complex network of gene interactions controls gene regulation throughout development and the life of the organisms. Insights can be made into these processes by studying the functional interactions (or "motifs") which make up these networks. RESULTS: We sought to understand the functionality of one of these network motifs, negative feedback, in a multi-cellular system. This was accomplished using a synthetic network expressed in the Drosophila melanogaster embryo using the yeast proteins Gal4 (a transcriptional activator) and Gal80 (an inhibitor of Gal4 activity). This network is able to produce an attenuation or shuttling phenotype depending on the Gal80/Gal4 ratio. This shuttling behavior was validated by expressing Gal3, which inhibits Gal80, to produce a localized increase in free Gal4 and therefore signaling. Mathematical modeling was used to demonstrate the capacity for negative feedback to produce these varying outputs. CONCLUSIONS: The capacity of a network motif to exhibit different phenotypes due to minor changes to the network in multi-cellular systems was shown. This work demonstrates the importance of studying network motifs in multi-cellular systems.
