Synthetic regulatory RNAs as tools for engineering biological systems: Design and applications

Establishing a Multivariate Model for Predictable Antisense RNA-Mediated Repression

Recent advances in our understanding of RNA folding and functions have facilitated the use of regulatory RNAs such as synthetic antisense RNAs (asRNAs) to modulate gene expression. However, despite the simple and universal complementarity rule, predictable asRNA-mediated repression is still challenging due to the intrinsic complexity of native asRNA-mediated gene regulation. To address this issue, we present a multivariate model, based on the change in free energy of complex formation (Δ G_CF) and percent mismatch of the target binding region, which can predict synthetic asRNA-mediated repression efficiency in diverse contexts. First, 69 asRNAs that bind to multiple target mRNAs were designed and tested to create the predictive model. Second, we showed that the same model is effective predicting repression of target genes in both plasmids and chromosomes. Third, using our model, we designed asRNAs that simultaneously modulated expression of a toxin and its antitoxin to demonstrate tunable control of cell growth. Fourth, we tested and validated the same model in two different biotechnologically important organisms: Escherichia coli Nissle 1917 and Bacillus subtilis 168. Last, multiple parameters, including target locations, the presence of an Hfq binding site, GC contents, and gene expression levels, were revisited to define the conditions under which the multivariate model should be used for accurate prediction. Together, 434 different strain-asRNA combinations were tested, validating the predictive model in a variety of contexts, including multiple target genes and organisms. The result presented in this study is an important step toward achieving predictable tunability of asRNA-mediated repression.

Engineering Human Microbiota: Influencing Cellular and Community Dynamics for Therapeutic Applications

The complex relationship between microbiota, human physiology, and environmental perturbations has become a major research focus, particularly with the arrival of culture-free and high-throughput approaches for studying the microbiome. Early enthusiasm has come from results that are largely correlative, but the correlative phase of microbiome research has assisted in defining the key questions of how these microbiota interact with their host. An emerging repertoire for engineering the microbiome places current research on a more experimentally grounded footing. We present a detailed look at the interplay between microbiota and host and how these interactions can be exploited. A particular emphasis is placed on unstable microbial communities, or dysbiosis, and strategies to reestablish stability in these microbial ecosystems. These include manipulation of intermicrobial communication, development of designer probiotics, fecal microbiota transplantation, and synthetic biology.

A universal strategy for regulating mRNA translation in prokaryotic and eukaryotic cells

We describe a simple strategy to control mRNA translation in both prokaryotic and eukaryotic cells which relies on a unique protein–RNA interaction. Specifically, we used the Pumilio/FBF (PUF) protein to repress translation by binding in between the ribosome binding site (RBS) and the start codon (in Escherichia coli), or by binding to the 5′ untranslated region of target mRNAs (in mammalian cells). The design principle is straightforward, the extent of translational repression can be tuned and the regulator is genetically encoded, enabling the construction of artificial signal cascades. We demonstrate that this approach can also be used to regulate polycistronic mRNAs; such regulation has rarely been achieved in previous reports. Since the regulator used in this study is a modular RNA-binding protein, which can be engineered to target different 8-nucleotide RNA sequences, our strategy could be used in the future to target endogenous mRNAs for regulating metabolic flows and signaling pathways in both prokaryotic and eukaryotic cells.