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Foo, M.

Publications and source records attributed to Foo, M..

5 recordsLinked to original sources

Multi-Level Regulation in RNA-Protein Hybrid Incoherent Feedforward Loop Circuits for Tunable Pulse Dynamics in Escherichia coli

Regulating gene expression with precision is essential for cellular engineering and biosensing applications, where rapid, programmable, and sensitive control is desired. Current approaches to regulatory circuit design often rely on control at a single regulatory level, primarily the transcriptional level, thereby limiting the capability of fine-tuning the regulatory dynamics in response to complex stimuli. To address this challenge, we developed four novel RNA-protein hybrid type-1 incoherent feed-forward loop (I1-FFL) circuits in Escherichia coli that integrate transcriptional and translational regulators to achieve multi-level control of gene expression. These hybrid circuits leverage the modularity and rapid dynamics of RNA-based activators alongside the versatile inhibition capabilities of the protein-based repressors, to endow tunable pulse dynamics through engineered delays that act as transient repressor decoys. By repurposing synthetic RNA regulators at multiple regulatory levels together with aptamer and RNA-binding proteins, we demonstrate previously unexplored circuits with tunable dynamics. Complementary simulation results highlighted the importance of the engineered delays in achieving tunable pulse dynamics in these circuits. Integrating modeling insights with experimental validation, we demonstrated the flexibility of designing the RNA-protein hybrid I1-FFL circuits, as well as the tunability of their dynamics, highlighting their suitability for applications in environmental monitoring, metabolic engineering, and other engineered biological systems, where precise temporal control and adaptable gene regulation are desired.

synthetic biology↗

Mining Yeast Diversity Unveils Novel Targets for Improved Heterologous Laccase Production in Saccharomyces cerevisiae

The budding yeast Saccharomyces cerevisiae is a widely utilized host cell for recombinant protein production due to its well studied and annotated genome, its ability to secrete large and post-translationally modified proteins, fast growth and cost-effective culturing. However, recombinant protein yields from S. cerevisiae often fall behind that of other host systems. To address this, we developed a high throughput screen of wild, industrial and laboratory S. cerevisiae isolates to identify strains with a natural propensity for greater recombinant protein production, specifically focussing on laccase multicopper oxidases from the fungi Trametes trogii and Myceliophthora thermophila. Using this method, we identified 20 non-laboratory strains with higher capacity to produce active laccase. Interestingly, lower levels of laccase mRNA were measured in most cases, indicating that the drivers of elevated protein production capacity lie beyond the regulation of recombinant gene expression. We characterized the identified strains using complementary genomic and proteomic approaches to reveal several potential pathways driving the improved expression phenotype. Gene ontology analysis suggests broad changes in cellular metabolism, specifically in genes/proteins involved in carbohydrate catabolism, thiamine biosynthesis, transmembrane transport and vacuolar degradation. Targeted deletions of the hexose transporter HXT11 and the Coat protein complex II interacting paralogs PRM8 and 9, involved in ER to Golgi transport, resulted in significantly improved laccase production from the S288C laboratory strain. Whereas the deletion of the Hsp110 SSE1 gene, guided by our proteomic analysis, also led to higher laccase activity, we did not observe major changes of the protein homeostasis network within the strains with higher laccase activity. This study opens new avenues to leverage the vast diversity of Saccharomyces cerevisiae for recombinant protein production, as well as offers new strategies and insights to enhance recombinant protein yields of current strains.

molecular biology↗

Data-driven dynamical modelling of a pathogen-infected plant gene regulatory network: a comparative analysis

Recent advances in synthetic biology have enabled the design of genetic feedback control circuits that could be implemented to build resilient plants against pathogen attacks. To facilitate the proper design of these genetic feedback control circuits, an accurate model that is able to capture the vital dynamical behaviour of the pathogen-infected plant is required. In this study, using a data-driven modelling approach, we develop and compare four dynamical models (i.e. linear, Michaelis-Menten, standard S-System and extended S-System) of a pathogen-infected plant gene regulatory network (GRN). These models are then assessed across several criteria, i.e. ease of identifying the type of gene regulation, the predictive capability, Akaike Information Criterion (AIC) and the robustness to parameter uncertainty to determine its viability of modelling the pathogen-infected plant GRN. Using our defined ranking score, our analyses show that while the extended S-System model ranks highest in the overall comparison, the performance of the linear model is more consistent throughout the comparison, making it the preferred model for this pathogen-infected plant GRN.

systems biology↗

Mangroves are an overlooked hotspot of insect diversity despite low plant diversity

We here compare the tropical arthropod fauna across a freshwater swamp and six different forest types (rain-, swamp, dry-coastal, urban, freshwater swamp, mangroves) based on 140,000 barcoded specimens belonging to ca. 8,500 species. Surprisingly, we find that mangroves, a globally imperiled habitat that had been expected to be species-poor for insects, are an overlooked hotspot for insect diversity despite having low plant diversity. Our study reveals a species-rich mangrove insect fauna (>3,000 species) that is distinct (>50% of species are mangrove-specific), and has high species turnover across Southeast and East Asia. For most habitats, plant diversity is a good predictor for insect diversity, but mangroves are an exception and compensate for a comparatively low number of phytophagous and fungivorous insect species by supporting an unusually rich community of predators whose larvae feed in the productive mudflats. For the remaining tropical habitats, the insect communities have diversity patterns that are largely congruent across guilds. The discovery of such a sizeable and distinct insect fauna in a globally threatened habitat underlines how little is known about global insect biodiversity.

ecology↗

Minimally Complex Nucleic Acid Feedback Control Systems for First Experimental Implementations

Chemical reaction networks based on catalysis, degradation, and annihilation may be used as building blocks to construct a variety of dynamical and feedback control systems in Synthetic Biology. DNA strand-displacement, which is based on DNA hybridisation programmed using Watson-Crick base pairing, is an effective primitive to implement such reactions experimentally. However, experimental construction, validation and scale-up of nucleic acid control systems is still significantly lagging theoretical developments, due to several technical challenges, such as leakage, crosstalk, and toehold sequence design. To help the progress towards experimental implementation, we provide here designs representing two fundamental classes of reference tracking control circuits (integral and state-feedback control), for which the complexity of the chemical reactions required for implementation has been minimised. The supplied minimally complex control circuits should be ideal candidates for first experimental validations of nucleic acid controllers.

synthetic biology↗