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Corrao, M.

Publications and source records attributed to Corrao, M..

2 recordsLinked to original sources

Quantitative Engineering and Investigation of Synthetic Sponge RNAs in E. coli

Sponge RNAs (spRNAs) play an important regulatory role in bacterial small RNA (sRNA) networks, but their engineering and quantitative systems-level properties are unexplored. Here, we design, build, and quantitatively characterise synthetic spRNA-based gene circuits in E. coli. We establish multiple design strategies for synthetic spRNAs, engineering the first synthetic spRNAs. We show that these synthetic spRNAs can reversibly de-repress sRNA-regulated gene expression, demonstrate tuneable control of gene expression, and extend these designs to multi-target regulation. Through the use of time-resolved continuous-culture characterisation in Chi.Bio together with absolute fluorescent protein quantification, we generated a quantitative dynamical dataset for model fitting and mechanistic analysis. Sequential model development showed that recapitulating the observed circuit dynamics required incorporation of Hfq-mediated resource competition, often overlooked in models of sRNA-based synthetic gene circuits. The extended model captured promoter, sRNA, and sponge circuit behaviour and was used to investigate quantitative properties of spRNA-mediated regulation, the first such quantitative investigation of spRNA-based regulation. Model-based quantitative investigations further suggest that spRNAs can tune response functions, modulate thresholds and leakiness, alter response times, improve disturbance rejection in some regimes, increase effective specificity, and buffer regulatory output against sRNA mutation. Together, these results establish synthetic spRNAs as a new post-transcriptional tool for bacterial synthetic biology and provide a quantitative framework for understanding natural and engineered spRNA-mediated regulation.

synthetic biology↗

Optimised control of adaptive evolution with competing selective pressures

The development of methods to understand and control the population dynamics of microbial evolution remains an outstanding question in synthetic biology and biotechnology more broadly. Due to the stochastic nature of evolution, its limited observability, and complex intra-population dynamics, this presents a significant challenge. In this paper, we explore techniques to control the evolutionary dynamics of a population, based on manipulation of one or two orthogonal selective pressures, which may in turn be coupled to mutagenesis. Our approach builds on past research in evolutionary biology that developed frameworks to study intra-population variant competition during asexual adaptive processes (i.e. clonal interference). Extending this theory, we design optimal control strategies for one (or more) selective pressures that can be used to maximise the rate of adaptation across a population as a whole. We introduce a theoretical modelling framework for this process, which we support with both simulations and preliminary experimental data, providing a concrete basis for emerging control approaches to directed evolution and evolution-aware design.

evolutionary biology↗