Robustness Analysis of a Synthetic Translational Resource Allocation Controller

Recent research in Synthetic Biology has highlighted the potential of translational resource allocation controllers to improve circuit modularity by dynamically allocating finite cellular resources in response to fluctuating circuit demands. The design of such controllers is complicated by the significant levels of parametric uncertainty that arise in their biological implementations. Tools from robust control, such as µ-analysis, can be used to determine the robustness of controller designs to parametric uncertainty, but require further development to allow their application to biomolecular control systems, which are typically highly non-linear, and contain multiple uncertainties that cannot be represented using the standard linear fractional transformation formalism. Here, we show how an LFT (Linear Fractional Transformation)-free formulation of the µ-analysis problem can be used to analyse and compare the robustness of alternative potential implementations of a translational resource allocation controller that utilises orthogonal ‘circuit-specific’ ribosomes to translate circuit genes. Our results provide useful guidelines for the construction of robust resource allocation circuitry for multiple future biotechnological applications

Robust set-point regulation of gene expression using resource competition couplings in mammalian cells

Gene expression depends on the cellular con-text. One major contributor to gene expression variability is competition for limited transcriptional and translational re-sources, which may induce indirect couplings among otherwise independently-regulated genes. Here, we apply control theoretical concepts and tools to design an incoherent feedforward loop (iFFL) biomolecular controller operating in mammalian cells using translational-resource competition couplings. Harnessing a resource-aware mathematical model, we demonstrate analytically and computationally that our resource-aware design can achieve near-constant set-point regulation of gene expression whilst ensuring robustness to plasmid uptake variation. We also provide an analytical condition on the model parameters to guide the design of the resource-aware iFFL controller ensuring robustness and performance in set-point regulation. Our theoretical design based on translational-resource competition couplings represents a promising approach to build more sophisticated resource-aware control circuits operating at the host-cell level

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

Burden-driven feedback control of gene expression

Cells use feedback regulation to ensure robust growth despite fluctuating demands for resources and differing environmental conditions. However, the expression of foreign proteins from engineered constructs is an unnatural burden that cells are not adapted for. Here we combined RNA-seq with an in vivo assay to identify the major transcriptional changes that occur in Escherichia coli when inducible synthetic constructs are expressed. We observed that native promoters related to the heat-shock response activated expression rapidly in response to synthetic expression, regardless of the construct. Using these promoters, we built a dCas9-based feedback-regulation system that automatically adjusts the expression of a synthetic construct in response to burden. Cells equipped with this general-use controller maintained their capacity for native gene expression to ensure robust growth and thus outperformed unregulated cells in terms of protein yield in batch production. This engineered feedback is to our knowledge the first example of a universal, burden-based biomolecular control system and is modular, tunable and portable

Control Theory for Synthetic Biology: Recent Advances in System Characterization, Control Design, and Controller Implementation for Synthetic Biology

Living organisms are differentiated by their genetic material-millions to billions of DNA bases encoding thousands of genes. These genes are translated into a vast array of proteins, many of which have functions that are still unknown. Previously, it was believed that simply knowing the genetic sequence of an organism would be the key to unlocking all understanding. However, as DNA sequencing technology has become affordable, it has become clear that living cells are governed by complex, multilayered networks of gene regulation that cannot be deduced from sequence alone. Synthetic biology as a field might best be characterized as a learn-by-building approach, in which scientists attempt to engineer molecular pathways that do not exist in nature. In doing so, they test the limits of both natural and engineered organisms

A partially self-regenerating synthetic cell

Self-regeneration is a fundamental function of all living systems. Here we demonstrate partial molecular self-regeneration in a synthetic cell. By implementing a minimal transcription-translation system within microfluidic reactors, the system is able to regenerate essential protein components from DNA templates and sustain synthesis activity for over a day. By quantitating genotype-phenotype relationships combined with computational modeling we find that minimizing resource competition and optimizing resource allocation are both critically important for achieving robust system function. With this understanding, we achieve simultaneous regeneration of multiple proteins by determining the required DNA ratios necessary for sustained self-regeneration. This work introduces a conceptual and experimental framework for the development of a self-replicating synthetic cell. A fundamental function of living systems is regenerating essential components. Here the authors design an artificial cell using a minimal transcription-translation system in microfluidic reactors for sustained regeneration of multiple essential proteins

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

Multi-Scale Host-Aware Modeling for Analysis and Tuning of Synthetic Gene Circuits for Bioproduction

[ES] Esta Tesis ha sido dedicada al modelado multiescala considerando al anfitrión celular para el análisis y ajuste de circuitos genéticos sintéticos para bioproducción. Los objetivos principales fueron: 1. El desarrollo de un modelo que considere el anfitrión celular de tamaño reducido enfocado para simulación y análisis. 2. El desarrollo de herramientas de programación para el modelado y la simulación, orientada a la biología sintética. 3. La implementación de un modelo multiescala que considere las escalas relevantes para la bioproducción (biorreactor, célula y circuito sintético). 4. El análisis del controlador antitético considerando las interacciones célula-circuito, como ejemplo de aplicación de las herramientas desarrolladas. 5. El desarrollo y la validación experimental de leyes de control robusto para biorreactores continuos. El trabajo presentado en esta Tesis cubre las tres escalas del proceso de bioproducción. La primera escala es el biorreactor: esta escala considera la dinámica macroscópica del sustrato y la biomasa, y como estas dinámica se conecta con el estado interno de las células. La segunda escala es la célula anfitriona: esta escala considera la dinámica interna de la célula y la competencia por los recursos limitados compartidos para la expresión de proteínas. La tercera escala es el circuito genético sintético: esta escala considera la dinámica de expresión de los circuitos sintéticos exógenos y la carga que inducen en la célula anfitriona. Por último, como > escala, parte de la Tesis se ha dedicado a desarrollar herramientas de software para el modelado y la simulación. Este documento se divide en siete capítulos. El Capítulo 1 es una introducción general al trabajo de la Tesis y su justificación; también presenta un mapa visual de la Tesis y enumera las principales contribuciones. El Capítulo 2 muestra el desarrollo del modelo del anfitrión celular (los Capítulos 4 y 5 hacen uso de este modelo para sus simulaciones). El Capítulo 3 presenta OneModel: una herramienta de software desarrollada en la Tesis que facilita el modelado y la simulación en biología sintética, en particular, facilita el uso del modelo del anfitrión celular. El Capítulo 4 utiliza el modelo del anfitrión celular para montar el modelo multiescala que considera el biorreactor y analiza el título, la productividad y el rendimiento en la expresión de una proteína exógena. El Capítulo 5 analiza un circuito más complejo, el recientemente propuesto y muy citado controlador biomolecular antitético, utilizando el modelo del anfitrión celular. El Capítulo 6 muestra el diseño de estrategias de control no lineal que permiten controlar la concentración de biomasa en un biorreactor continuo de forma robusta. El Capítulo 7 resume y presenta las principales conclusiones de la Tesis. En el Apéndice A se muestra el desarrollo teórico del modelo del anfitrión celular. Esta Tesis destaca la importancia de estudiar la carga celular en los sistemas biológicos, ya que estos efectos son muy notables y generan interacciones entre circuitos aparentemente independientes. La Tesis proporciona herramientas para modelar, simular y diseñar circuitos genéticos sintéticos teniendo en cuenta estos efectos de carga y permite el desarrollo de modelos que conecten estos fenómenos en los circuitos genéticos sintéticos, que van desde la dinámica intracelular de la expresión génica hasta la dinámica macroscópica de la población de células dentro del biorreactor.[CA] Aquesta Tesi tracta del modelat multiescala considerant l'amfitrió ce\lgem ular per a l'anàlisi i ajust de circuits genètics sintètics per a bioproducció. Els objectius principals van ser: 1. El desenvolupament d'un model de grandària reduïda que considere l'amfitrió ce\lgem ular, enfocat al seu ús en simulació i anàlisi. 2. El desenvolupament d'eines de programari per al modelatge i la simulació, orientada a la biologia sintètica. 3. La implementació d'un model multiescala que considere les escales rellevants per a la bioproducció (bioreactor, cè\lgem ula i circuit sintètic). 4. L'anàlisi del controlador antitètic considerant les interacciones cè\lgem ula-circuit, com a exemple d'aplicació de les eines desenvolupades. 5. El desenvolupament i la validació experimental de lleis de control robust per a bioreactors continus. El treball presentat en aquesta Tesi cobreix les tres escales del procés de bioproducció. La primera escala és el bioreactor: aquesta escala considera la dinàmica macroscòpica del substrat i la biomassa, i com aquestes dinàmiques es connecten amb l'estat intern de les cè\lgem ules. La segona escala és la cè\lgem ula amfitriona: aquesta escala considera la dinàmica interna de la cè\lgem ula i la competència pels recursos limitats compartits per a l'expressió de proteïnes. La tercera escala és la del circuit genètic sintètic: aquesta escala considera la dinàmica d'expressió de circuits sintètics exógens i la càrrega que indueixen en la cè\lgem ula amfitriona. Finalment, com a > escala, part de la Tesi s'ha dedicat a desenvolupar eines de programari per al modelatge i la simulació. Aquest document es divideix en set capítols. El Capítol 1 és una introducció general al treball de la Tesi i la seua justificació; també presenta un mapa visual de la Tesi i enumera les principals contribucions. El Capítol 2 mostra el desenvolupament del model de l'amfitrió ce\lgem ular (els Capítols 4 i 5 fan ús d'aquest model per a les seues simulacions). El Capítol 3 presenta OneModel: una eina de programari desenvolupada en la Tesi que facilita el modelatge i la simulació en biologia sintètica, en particular, facilita l'ús del model de l'amfitrió ce\lgem ular. El Capítol 4 utilitza el model de l'amfitrió ce\lgem ular per a muntar el model multiescala que considera el bioreactor i analitza el títol, la productivitat i el rendiment en l'expressió d'una proteïna exògena. El Capítol 5 analitza un circuit més complex, el recentment proposat i molt citat controlador biomolecular antitètic, utilitzant el model de l'amfitrió ce\lgem ular. El Capítol 6 mostra el disseny d'estratègies de control no lineal que permeten controlar la concentració de biomassa en un bioreactor continu de manera robusta. El Capítol 7 resumeix i presenta les principals conclusions de la Tesi. En l'Apèndix A es mostra el desenvolupament teòric del model de l'amfitrió ce\lgem ular. Aquesta Tesi destaca la importància d'estudiar la càrrega ce\lgem ular en els sistemes biològics, ja que aquests efectes són molt notables i generen interaccions entre circuits aparentment independents. La Tesi proporciona eines per a modelar, simular i dissenyar circuits genètics sintètics tenint en compte aquests efectes de càrrega i permet el desenvolupament de models que connecten aquests fenòmens en els circuits genètics sintètics, que van des de la dinàmica intrace\lgem ular de l'expressió gènica fins a la dinàmica macroscòpica de la població de cè\lgem ules dins del bioreactor.[EN] This Thesis was devoted to the multi-scale host-aware analysis and tuning of synthetic gene circuits for bioproduction. The main objectives were: 1. The development of a reduced-size host-aware model for simulation and analysis purposes. 2. The development of a software toolbox for modeling and simulation, oriented to synthetic biology. 3. The implementation of a multi-scale model that considers the scales relevant to bioproduction (bioreactor, cell, and synthetic circuit). 4. The host-aware analysis of the antithetic controller, as an example of the application of the developed tools. 5. The development and experimental validation of robust control laws for continuous bioreactors. The work presented in this Thesis covers the three scales of the bioproduction process. The first scale is the bioreactor: this scale considers the macroscopic substrate and biomass dynamics and how these dynamics connect to the internal state of the cells. The second scale is the host cell: this scale considers the internal dynamics of the cell and the competition for limited shared resources for protein expression. The third scale is the synthetic genetic circuit: this scale considers the dynamics of expressing exogenous synthetic circuits and the burden they induce on the host cell. Finally, as a > scale, part of the Thesis was devoted to developing software tools for modeling and simulation. This document is divided into seven chapters. Chapter 1 is an overall introduction to the Thesis work and its justification; it also presents a visual map of the Thesis and lists the main contributions. Chapter 2 shows the development of the host-aware model (Chapters 4 and 5 make use of this model for their simulations). Chapter 3 presents OneModel: a software tool developed in the Thesis that facilitates modeling and simulation for synthetic biology---in particular, it facilitates the use of the host-aware model---. Chapter 4 uses the host-aware model to assemble the multi-scale model considering the bioreactor and analyzes the titer, productivity (rate), and yield in expressing an exogenous protein. Chapter 5 analyzes a more complex circuit, the recently proposed and highly cited antithetic biomolecular controller, using the host-aware model. Chapter 6 shows the design of nonlinear control strategies that allow controlling the concentration of biomass in a continuous bioreactor in a robust way. Chapter 7 summarizes and presents the main conclusions of the Thesis. Appendix A shows the theoretical development of the host-aware model. This Thesis emphasizes the importance of studying cell burden in biological systems since these effects are very noticeable and generate interactions between seemingly unconnected circuits. The Thesis provides tools to model, simulate and design synthetic genetic circuits taking into account these burden effects and allowing the development of models that connect phenomena in synthetic genetic circuits, ranging from the intracelullar dynamics of gene expression to the macroscopic dynamics of the population of cells inside the bioreactor.This research was funded by MCIN/AEI/10.13039/501100011033 grant number PID2020-117271RB-C21, and MINECO/AEI, EU grant number DPI2017-82896- C2-1-R. The author was recipient of the grant “Programa para la Formación de Personal Investigador (FPI) de la Universitat Politècnica de València — Subprograma 1 (PAID-01-2017)”. The author was also a grantee of the predoctoral stay “Ayudas para Movilidad de Estudiantes de Doctorado de la Universitat Politècnica de València 2019”. The Control Theory and Systems Biology Lab of the ETH Zürich is acknowledged for accepting the author in their facilities as predoctoral stay and their valuable collaboration sharing knowledge.Santos Navarro, FN. (2022). Multi-Scale Host-Aware Modeling for Analysis and Tuning of Synthetic Gene Circuits for Bioproduction [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/183473Premios Extraordinarios de tesis doctorale

A 'resource allocator' for transcription based on a highly fragmented T7 RNA polymerase

Synthetic genetic systems share resources with the host, including machinery for transcription and translation. Phage RNA polymerases (RNAPs) decouple transcription from the host and generate high expression. However, they can exhibit toxicity and lack accessory proteins (σ factors and activators) that enable switching between different promoters and modulation of activity. Here, we show that T7 RNAP (883 amino acids) can be divided into four fragments that have to be co‐expressed to function. The DNA‐binding loop is encoded in a C‐terminal 285‐aa ‘σ fragment’, and fragments with different specificity can direct the remaining 601‐aa ‘core fragment’ to different promoters. Using these parts, we have built a resource allocator that sets the core fragment concentration, which is then shared by multiple σ fragments. Adjusting the concentration of the core fragment sets the maximum transcriptional capacity available to a synthetic system. Further, positive and negative regulation is implemented using a 67‐aa N‐terminal ‘α fragment’ and a null (inactivated) σ fragment, respectively. The α fragment can be fused to recombinant proteins to make promoters responsive to their levels. These parts provide a toolbox to allocate transcriptional resources via different schemes, which we demonstrate by building a system which adjusts promoter activity to compensate for the difference in copy number of two plasmids.United States. Office of Naval Research (N00014‐13‐1‐0074)National Institutes of Health (U.S.) (5R01GM095765)National Science Foundation (U.S.) (Synthetic Biology Engineering Research Center (SA5284‐11210))United States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship (NDSEG) Program))Hertz Foundation (Fellowship

Control Theory for Synthetic Biology: Recent Advances in System Characterization, Control Design, and Controller Implementation for Synthetic Biology

Living organisms are differentiated by their genetic material-millions to billions of DNA bases encoding thousands of genes. These genes are translated into a vast array of proteins, many of which have functions that are still unknown. Previously, it was believed that simply knowing the genetic sequence of an organism would be the key to unlocking all understanding. However, as DNA sequencing technology has become affordable, it has become clear that living cells are governed by complex, multilayered networks of gene regulation that cannot be deduced from sequence alone. Synthetic biology as a field might best be characterized as a learn-by-building approach, in which scientists attempt to engineer molecular pathways that do not exist in nature. In doing so, they test the limits of both natural and engineered organisms