MIRELLA: a mathematical model explains the effect of microRNA-mediated synthetic genes regulation on intracellular resource allocation.

Competition for intracellular resources, also known as gene expression burden, induces coupling between independently co-expressed genes, a detrimental effect on predictability and reliability of gene circuits in mammalian cells. We recently showed that microRNA (miRNA)-mediated target downregulation correlates with the upregulation of a co-expressed gene, and by exploiting miRNAs-based incoherent-feed-forward loops (iFFLs) we stabilise a gene of interest against burden. Considering these findings, we speculate that miRNA-mediated gene downregulation causes cellular resource redistribution. Despite the extensive use of miRNA in synthetic circuits regulation, this indirect effect was never reported before. Here we developed a synthetic genetic system that embeds miRNA regulation, and a mathematical model, MIRELLA, to unravel the miRNA (MI) RolE on intracellular resource aLLocAtion. We report that the link between miRNA-gene downregulation and independent genes upregulation is a result of the concerted action of ribosome redistribution and 'queueing-effect' on the RNA degradation pathway. Taken together, our results provide for the first time insights into the hidden regulatory interaction of miRNA-based synthetic networks, potentially relevant also in endogenous gene regulation. Our observations allow to define rules for complexity- and context-aware design of genetic circuits, in which transgenes co-expression can be modulated by tuning resource availability via number and location of miRNA target sites.

Engineering Protein-Based Parts for Genetic Devices in Mammalian Cells.

Synthetic biology has been advancing cellular and molecular biology studies through the design of synthetic circuits capable to examine diverse endogenously or exogenously driven regulatory pathways. While early genetic devices were engineered to be insulated from intracellular crosstalk, more recently the need of achieving dynamic control of cellular behavior has led to the development of smart interfaces that connect signal information (sensor) to desired output activation (actuator). Sensor-actuator circuits can respond to diverse inputs, including small molecules, exogenous and endogenous mRNA, noncoding RNA (i.e., miRNA), and proteins to regulate downstream events, transcriptionally, posttranscriptionally, and translationally. These devices require attentive engineering to either create complex chimeric proteins or modify protein structures to be amenable to the specific circuits' architecture and/or purpose.In this chapter, we describe how to implement two different protein-based devices in mammalian cells: (1) a modular platform that sense and respond to disease-associated proteins and (2) a protein-based system that allows simultaneous regulation of RNA translation and protein activity, via RNA-protein and newly engineered protein-protein interactions.

Characterization and mitigation of gene expression burden in mammalian cells.

Despite recent advances in circuit engineering, the design of genetic networks in mammalian cells is still painstakingly slow and fraught with inexplicable failures. Here, we demonstrate that transiently expressed genes in mammalian cells compete for limited transcriptional and translational resources. This competition results in the coupling of otherwise independent exogenous and endogenous genes, creating a divergence between intended and actual function. Guided by a resource-aware mathematical model, we identify and engineer natural and synthetic miRNA-based incoherent feedforward loop (iFFL) circuits that mitigate gene expression burden. The implementation of these circuits features the use of endogenous miRNAs as elementary components of the engineered iFFL device, a versatile hybrid design that allows burden mitigation to be achieved across different cell-lines with minimal resource requirements. This study establishes the foundations for context-aware prediction and improvement of in vivo synthetic circuit performance, paving the way towards more rational synthetic construct design in mammalian cells.

Protein-based parts and devices that respond to intracellular and extracellular signals in mammalian cells.

Synthetic biology aims to rewire cellular activities and functionality by implementing genetic circuits with high biocomputing capabilities. Recent efforts led to the development of smart sensing interfaces which integrate multiple inputs to activate desired outputs in a highly specific and sensitive manner. In this review, we highlight protein-based interfaces that sense intracellular or extracellular cues providing information about dynamic environmental changes and cellular state. We will also discuss different mechanisms of regulation of gene expression connected to the sensors to develop diagnostic and therapeutic devices. We conclude discussing challenges and opportunities for biomedical applications of synthetic mammalian protein-based devices.

Engineering protein-protein devices for multilayered regulation of mRNA translation using orthogonal proteases in mammalian cells.

The development of RNA-encoded regulatory circuits relying on RNA-binding proteins (RBPs) has enhanced the applicability and prospects of post-transcriptional synthetic network for reprogramming cellular functions. However, the construction of RNA-encoded multilayer networks is still limited by the availability of composable and orthogonal regulatory devices. Here, we report on control of mRNA translation with newly engineered RBPs regulated by viral proteases in mammalian cells. By combining post-transcriptional and post-translational control, we expand the operational landscape of RNA-encoded genetic circuits with a set of regulatory devices including: i) RBP-protease, ii) protease-RBP, iii) protease-protease, iv) protein sensor protease-RBP, and v) miRNA-protease/RBP interactions. The rational design of protease-regulated proteins provides a diverse toolbox for synthetic circuit regulation that enhances multi-input information processing-actuation of cellular responses. Our approach enables design of artificial circuits that can reprogram cellular function with potential benefits as research tools and for future in vivo therapeutics and biotechnological applications.