Multicellular Models Bridging Intracellular Signaling and Gene Transcription to Population Dynamics

Cell signaling and gene transcription occur at faster time scales compared to cellular death, division, and evolution. Bridging these multiscale events in a model is computationally challenging. We introduce a framework for the systematic development of multiscale cell population models. Using message passing interface (MPI) parallelism, the framework creates a population model from a single-cell biochemical network model. It launches parallel simulations on a single-cell model and treats each stand-alone parallel process as a cell object. MPI mediates cell-to-cell and cell-to-environment communications in a server-client fashion. In the framework, model-specific higher level rules link the intracellular molecular events to cellular functions, such as death, division, or phenotype change. Cell death is implemented by terminating a parallel process, while cell division is carried out by creating a new process (daughter cell) from an existing one (mother cell). We first demonstrate these capabilities by creating two simple example models. In one model, we consider a relatively simple scenario where cells can evolve independently. In the other model, we consider interdependency among the cells, where cellular communication determines their collective behavior and evolution under a temporally evolving growth condition. We then demonstrate the framework\u27s capability by simulating a full-scale model of bacterial quorum sensing, where the dynamics of a population of bacterial cells is dictated by the intercellular communications in a time-evolving growth environment

Engineering Responsive Yeast Systems Using Fungal G-Protein-Coupled Receptors

Communication is a ubiquitous component of life. While complexity and sophistication vary, both unicellular and multicellular organisms constantly interact with their environment. Unicellular organisms, once thought to be asocial, have since been demonstrated to display a multitude of social interactions and hierarchies. For example, quorum sensing enables a bacterial population to modulate gene expression in response to cell-population density, initiating social behavior and the exchange of resources. In eukaryotes, unicellular ascomycete fungi use mating GPCRs to detect secreted peptide pheromones, initiating changes in gene expression required for mating. An overview of communication in unicellular organisms is presented in Chapter 1. In general, these communication systems are characterized by a high degree of fidelity, and as such have been harvested by synthetic biologists to organize communication in synthetic systems. Quorum sensing modules have been employed for pattern formation and to coordinate biosynthesis processes across a community. However, fungal mating remains underutilized as a source of synthetic biology tools. In this dissertation, we leverage fungal mating G-protein-coupled receptors (GPCRs) and their peptide ligands to build responsive yeast systems. We use genome-mining to identify additional fungal peptide-GPCR pairs, which are then characterized in the yeast Saccharomyces cerevisiae. In Chapter 2, we exploit the high specificity and sensitivity of fungal mating GPCRs to design a yeast whole-cell biosensor that produces a visible output in response to detection of peptide biomarkers. In Chapter 3, we genome-mine additional peptide-GPCR pairs and use them as orthogonal signaling channels to build synthetic yeast communities. Finally, in Chapter 4, we use these synthetic yeast communities to provide sense-and-respond capabilities to an Engineered Living Material (ELM)

Agent-based modelling in synthetic biology

Biological systems exhibit complex behaviours that emerge at many different levels of organization. These span the regulation of gene expression within single cells to the use of quorum sensing to co-ordinate the action of entire bacterial colonies. Synthetic biology aims to make the engineering of biology easier, offering an opportunity to control natural systems and develop new synthetic systems with useful prescribed behaviours. However, in many cases, it is not understood how individual cells should be programmed to ensure the emergence of a required collective behaviour. Agent-based modelling aims to tackle this problem, offering a framework in which to simulate such systems and explore cellular design rules. In this article, I review the use of agent-based models in synthetic biology, outline the available computational tools, and provide details on recently engineered biological systems that are amenable to this approach. I further highlight the challenges facing this methodology and some of the potential future directions

A synthetic Escherichia coli predator–prey ecosystem

We have constructed a synthetic ecosystem consisting of two Escherichia coli populations, which communicate bi-directionally through quorum sensing and regulate each other's gene expression and survival via engineered gene circuits. Our synthetic ecosystem resembles canonical predator–prey systems in terms of logic and dynamics. The predator cells kill the prey by inducing expression of a killer protein in the prey, while the prey rescue the predators by eliciting expression of an antidote protein in the predator. Extinction, coexistence and oscillatory dynamics of the predator and prey populations are possible depending on the operating conditions as experimentally validated by long-term culturing of the system in microchemostats. A simple mathematical model is developed to capture these system dynamics. Coherent interplay between experiments and mathematical analysis enables exploration of the dynamics of interacting populations in a predictable manner

Bioengineered conduits for directing digitized molecular-based information

Molecular recognition is a prevalent quality in natural biological environments: molecules- small as well as macro- enable dynamic response by instilling functionality and communicating information about the system. The accession and interpretation of this rich molecular information leads to context about the system. Moreover, molecular complexity, both in terms of chemical structure and diversity, permits information to be represented with high capacity. Thus, an opportunity exists to assign molecules as chemical portrayals of natural, non-natural, and even non-biological data. Further, their associated upstream, downstream, and regulatory pathways could be commandeered for the purpose of data processing and transmission. This thesis emphasizes molecules that serve as units of information, the processing of which elucidates context. The project first strategizes a biocompatible assembly process that integrates biological componentry in an organized configuration for molecular transfer (e.g. from a cell to a receptor). Next, we have explored the use of DNA for its potential to store data in richer, digital forms. Binary data is embedded within a gene for storage inside a cell carrier and is selectively conveyed. Successively, a catalytic relay is developed to transduce similar data from sequence-based DNA storage to a delineated chemical cue that programs cellular phenotype. Finally, these cell populations are used as mobile information processing units that independently seek and collectively categorize the information, which is fed back as fluorescently ‘binned’ output. Every development demonstrates a transduction process of molecular data that involves input acquisition, refinement, and output interpretation. Overall, by equipping biomimetic networks with molecular-driven performance, their interactions serve as conduits of information flow

DNA-based communication in populations of synthetic protocells

Developing molecular communication platforms based on orthogonal communication channels is a crucial step towards engineering artificial multicellular systems. Here, we present a general and scalable platform entitled ‘biomolecular implementation of protocellular communication’ (BIO-PC) to engineer distributed multichannel molecular communication between populations of non-lipid semipermeable microcapsules. Our method leverages the modularity and scalability of enzyme-free DNA strand-displacement circuits to develop protocellular consortia that can sense, process and respond to DNA-based messages. We engineer a rich variety of biochemical communication devices capable of cascaded amplification, bidirectional communication and distributed computational operations. Encapsulating DNA strand-displacement circuits further allows their use in concentrated serum where non-compartmentalized DNA circuits cannot operate. BIO-PC enables reliable execution of distributed DNA-based molecular programs in biologically relevant environments and opens new directions in DNA computing and minimal cell technology

Infobiotics : computer-aided synthetic systems biology

Until very recently Systems Biology has, despite its stated goals, been too reductive in terms of the models being constructed and the methods used have been, on the one hand, unsuited for large scale adoption or integration of knowledge across scales, and on the other hand, too fragmented. The thesis of this dissertation is that better computational languages and seamlessly integrated tools are required by systems and synthetic biologists to enable them to meet the significant challenges involved in understanding life as it is, and by designing, modelling and manufacturing novel organisms, to understand life as it could be. We call this goal, where everything necessary to conduct model-driven investigations of cellular circuitry and emergent effects in populations of cells is available without significant context-switching, “one-pot” in silico synthetic systems biology in analogy to “one-pot” chemistry and “one-pot” biology. Our strategy is to increase the understandability and reusability of models and experiments, thereby avoiding unnecessary duplication of effort, with practical gains in the efficiency of delivering usable prototype models and systems. Key to this endeavour are graphical interfaces that assists novice users by hiding complexity of the underlying tools and limiting choices to only what is appropriate and useful, thus ensuring that the results of in silico experiments are consistent, comparable and reproducible. This dissertation describes the conception, software engineering and use of two novel software platforms for systems and synthetic biology: the Infobiotics Workbench for modelling, in silico experimentation and analysis of multi-cellular biological systems; and DNA Library Designer with the DNALD language for the compact programmatic specification of combinatorial DNA libraries, as the first stage of a DNA synthesis pipeline, enabling methodical exploration biological problem spaces. Infobiotics models are formalised as Lattice Population P systems, a novel framework for the specification of spatially-discrete and multi-compartmental rule-based models, imbued with a stochastic execution semantics. This framework was developed to meet the needs of real systems biology problems: hormone transport and signalling in the root of Arabidopsis thaliana, and quorum sensing in the pathogenic bacterium Pseudomonas aeruginosa. Our tools have also been used to prototype a novel synthetic biological system for pattern formation, that has been successfully implemented in vitro. Taken together these novel software platforms provide a complete toolchain, from design to wet-lab implementation, of synthetic biological circuits, enabling a step change in the scale of biological investigations that is orders of magnitude greater than could previously be performed in one in silico “pot”

Die Rolle von Quorum sensing und Quorum quenching im Metaorganismus Hydra

Every metaorganism consisting of a host and its associated microbes needs to maintain its homeostasis. Bacteria are controlling their behavior by their communication system, called quorum sensing (QS). As a host is interested in suppressing processes as virulence, the interference with a QS system (quorum quenching, QQ) could be an instrument to regulate the behavior of its bacteria. In this thesis, it could be proven that bacteria colonizing Hydra vulgaris (AEP) are producing N-acyl-homoserine-lactones, a class of QS signaling molecules. By analyzing the QS system of Curvibacter sp., the main colonizer of Hydra vulgaris (AEP), it could be shown that it can detect 3-hydroxy-HSLs (3OH-HSLs) as well as 3-oxo-HSLs (3O-HSLs) and produces 3OHC12. Furthermore, a new host mechanism could be identified, which enables Hydra to modify 3O-HSLs via an oxidoreductase activity to the 3OH-HSL counterpart. Consequently, Hydra’s QQ activity promotes Curvibacter’s 3OH-HSL regulated processes. Transcriptional expression data revealed that Curvibacter sp. possesses a differential response to 3OHC12 and 3OC12. Thereby, genes involved in flagella biosynthesis were induced by 3OC12 and inhibited by 3OHC12. The AHLs have also different impacts on the metaorganism assembly. While 3OHC12 promotes, 3OC12 inhibits colonization of host tissue by Curvibacter sp., most likely by a flagellin activated innate immune response. These findings indicate that 3O-HSLs induce the production of flagella in Curvibacter sp., which cause a response in Hydra, resulting in a decreased bacterial community within the metaorganism Hydra. These insights show for the first time, that a host is manipulating QS signals and thereby maintain symbiotic function of its bacteria, which contribute to the homeostasis of the metaorganism.Jeder Metaorganismus, bestehend aus einem Wirt und seinen assoziierten Mikroben, muss seine Homöostase erhalten. Bakterien kontrollieren ihr Verhalten mit ihrem Kommunikationssystems, dem so genannten Quorum sensing (QS). Da QS gesteuerte Prozesse, wie Virulenz für den Wirtsorganismus von Nachteil sein können, könnte das Eingreifen in das QS-System (Quorum quenching, QQ) der bakteriellen Kolonisierer für den Wirt von Vorteil sein und eine Möglichkeit bieten das Verhalten seiner Bakterien zu regulieren. In dieser Arbeit konnte gezeigt werden, dass Bakterien von Hydra vulgaris (AEP) N-Acyl-Homoserinlaktone produzieren, eine Klasse von QS-Signalmolekülen. Die Analyse des QS-Systems von Curvibacter sp., der Hauptkolonisierer von Hydra vulgaris (AEP), ergab, dass es sowohl 3-hydroxy-HSLs (3OH-HSLs) als auch 3-oxo-HSLs (3O-HSLs) erkennt und 3OHC12 produziert. Außerdem wurde ein neuer Wirtsmechanismus entdeckt, wodurch Hydra in der Lage ist 3O-HSLs mit einer Oxidoreduktase-Aktivität zu ihrem 3OH-HSL Gegenstück zu modifizieren. Folglich fördert Hydras QQ-Aktivität Curvibacters 3OH-HSL regulierte Prozesse. Die Analyse von Transkriptionsdaten ergab, dass Curvibacter sp. unterschiedlich auf 3OHC12 und 3OC12 reagiert. Unter anderem werden Gene, die an der Flagellenbiosynthese beteiligt sind, durch 3OC12 induziert und durch 3OHC12 inhibiert. Die AHL-Modifizierungen haben auch einen Einfluss auf den Metaorganismus; 3OHC12 fördern die Kolonisierung durch Curvibacter sp., während 3OC12 sie inhibieren. Diese Ergebnisse zeigen, dass 3O-HSLs u.a. die Flagellenproduktion von Curvibacter sp. induzieren, wodurch möglicherweise eine Immunantwort in Hydra ausgelöst wird, die zur Reduktion der bakteriellen Gemeinschaft führt. Diese Erkenntnisse zeigen zum ersten Mal, dass ein Wirt QS-Signale manipuliert und dadurch die symbiotischen Eigenschaften seiner Bakterien fördert, und damit zur Homöostase des Metaorganismus beiträgt

Synthetic biology and microdevices : a powerful combination

Recent developments demonstrate that the combination of microbiology with micro-and nanoelectronics is a successful approach to develop new miniaturized sensing devices and other technologies. In the last decade, there has been a shift from the optimization of the abiotic components, for example, the chip, to the improvement of the processing capabilities of cells through genetic engineering. The synthetic biology approach will not only give rise to systems with new functionalities, but will also improve the robustness and speed of their response towards applied signals. To this end, the development of new genetic circuits has to be guided by computational design methods that enable to tune and optimize the circuit response. As the successful design of genetic circuits is highly dependent on the quality and reliability of its composing elements, intense characterization of standard biological parts will be crucial for an efficient rational design process in the development of new genetic circuits. Microengineered devices can thereby offer a new analytical approach for the study of complex biological parts and systems. By summarizing the recent techniques in creating new synthetic circuits and in integrating biology with microdevices, this review aims at emphasizing the power of combining synthetic biology with microfluidics and microelectronics

A synthetic gene network architecture that propagates

Thesis (Ph.D.)--Boston UniversitySynthetic biology is a field that is tending towards maturity. Synthetic gene networks are becoming increasingly more complex, and are being engineered with functional outcomes as design goals rather than just logical demonstration. As complex as circuits become, it is still a difficult process to build a functional gene network. Much work has been done to reduce DNA assembly time, but none specifically addresses the complexity ofproducing functional networks. To this end, we present a synthetic gene network assembly strategy that emphasizes characterization-driven iteration. The Plug- and-Play methodology allows for post-construction modification to circuits, which enables the simple swapping of parts. This type of modification makes it possible to tune circuits for troubleshooting, or even to repurpose networks. We used a specified set of restriction enzymes, a library of optimized parts and a compatible backbone vector system to preserve uniqueness of cloning sites and allow maintained post-construction access to the network. To demonstrate the system, we rapidly constructed a bistable genetic toggle and subsequently transformed it into two functionally distinct networks, a 3 and 4-node feed-forward loop. We also designed a synthetic gene network that can propagate signals across a population ofisogenic bacteria. We used the Plug-and-Play methodology to quickly construct an excitable system that toggles between sending and receiving states. We developed a spatial assay platform that could accommodate long-term, large-scale plating experiments so as to visualize the propagation effect on the centimeter scale. We built several iterations ofthe propagating network, probed the regulatory dynamics ofthe various nodes and identified problematic nodes. We took steps to address these nodes with both orthogonal transcription machinery as well as multiple modes of genetic regulation. We integrated the propagating networks with a DNA-damage sensitive triggering module. This opened up the gene network to potentially complex applications such as antibiotic sensing, or longer-distance communication experiments