A synthetic Escherichia coli predator–prey ecosystem

Bioresources and Bioprocessing, 2014

Synthetic biology is a newly emerged research discipline that focuses on the engineering of novel cellular behaviors and functionalities through the creation of artificial gene circuits. One important class of synthetic circuits currently under active development concerns the programming of bacterial cellular communication and collective population-scale behaviors. Because of the ubiquity of cell-cell interactions within bacterial communities, having an ability of engineering these circuits is vital to programming robust cellular behaviors. Here, we highlight recent advances in communication-based synthetic gene circuits by first discussing natural communication systems and then surveying various functional engineered circuits, including those for population density control, temporal synchronization, spatial organization, and ecosystem formation. We conclude by summarizing recent advances, outlining existing challenges, and discussing potential applications and future opportunities.

PLOS One, 2010

Synthetic biology seeks to enable programmed control of cellular behavior though engineered biological systems. These systems typically consist of synthetic circuits that function inside, and interact with, complex host cells possessing preexisting metabolic and regulatory networks. Nevertheless, while designing systems, a simple well-defined interface between the synthetic gene circuit and the host is frequently assumed. We describe the generation of robust but unexpected oscillations in the densities of bacterium Escherichia coli populations by simple synthetic suicide circuits containing quorum components and a lysis gene. Contrary to design expectations, oscillations required neither the quorum sensing genes (luxR and luxI) nor known regulatory elements in the P luxI promoter. Instead, oscillations were likely due to density-dependent plasmid amplification that established a population-level negative feedback. A mathematical model based on this mechanism captures the key characteristics of oscillations, and model predictions regarding perturbations to plasmid amplification were experimentally validated. Our results underscore the importance of plasmid copy number and potential impact of ''hidden interactions'' on the behavior of engineered gene circuits -a major challenge for standardizing biological parts. As synthetic biology grows as a discipline, increasing value may be derived from tools that enable the assessment of parts in their final context.

PROCEEDINGS 29th INTERNATIONAL CONFERENCE ON MICROELECTRONICS (MIEL 2014), BELGRADE, SERBIA, 12-15 MAY, 2014, 2014

To coordinate their behavior and virulence and to synchronize attacks against their hosts, bacteria communicate by producing and detecting signaling molecules (autoinducers). This communication is controlled by biological circuits called quorum sensing circuits. Recently quorum sensing circuits have been recognized as an alternative target for controlling bacterial virulence and infections without the use of antibiotics. Here we model the quorum sensing process as a state transition graph. Based on this model we develop a simulation tool for the quorum sensing process in open and confined spaces. We perform a number of numerical experiments with various strategies of quorum sensing circuit regulation and we study the effectiveness of quorum sensing inhibitors. We also use network graph theory to model the complete quorum sensing system of Pseudomonas aeruginosa and construct its state space, which turned out to be very large, hierarchical, modular and scale-free.

Biotechnology Journal, 2011

Early studies in synthetic biology primarily focused on the construction of simple genetic devices, such as logic gates, bistable switches, and oscillators. These genetic circuits generally operated intracellularly to program single-cell behavior. Yokoba-A major aim of synthetic biology is to program novel cellular behavior using engineered gene circuits. Early endeavors focused on building simple circuits that fulfill simple functions, such as logic gates, bistable toggle switches, and oscillators. These gene circuits have primarily focused on single-cell behaviors since they operate intracellularly. Thus, they are often susceptible to cell-cell variations due to stochastic gene expression. Cell-cell communication offers an efficient strategy to coordinate cellular behavior at the population level. To this end, we review recent advances in engineering cell-cell communication to achieve reliable population dynamics, spanning from communication within single species to multispecies, from one-way sender-receiver communication to two-way communication in synthetic microbial ecosystems. These engineered systems serve as well-defined model systems to better understand design principles of their naturally occurring counterparts and to facilitate novel biotechnology applications. Abbreviations: 3OC6HSL, N-3-(oxohexanoyl)homoserine lactone; AHL, acylated homoserine lactone; ECFP, enhanced cyan fluorescent protein; IPTG, isopropyl β-D-1-thiogalactopyranoside; QS, quorum sensing; RTC, riboregulated transcriptional cascade

Journal of The Royal Society Interface, 2012

Population-level measurements of phenotypic behaviour in biological systems may not necessarily reflect individual cell behaviour. To assess qualitative changes in the behaviour of a single cell, when alone and when part of a community, we developed an agent-based model describing the metabolic states of a population of quorum-coupled cells. The modelling is motivated by published experimental work of a synthetic genetic regulatory network (GRN) used in Escherichia coli cells that exhibit oscillatory behaviour across the population. To decipher the mechanisms underlying oscillations in the system, we investigate the behaviour of the model via numerical simulation and bifurcation analysis. In particular, we study the effect of an increase in population size as well as the spatio-temporal behaviour of the model. Our results demonstrate that oscillations are possible only in the presence of a high concentration of the coupling chemical and are due to a time scale separation in key regulatory components of the system. The model suggests that the population establishes oscillatory behaviour as the system's preferred stable state. This is achieved via an effective increase in coupling across the population. We conclude that population effects in GRN design need to be taken into consideration and be part of the design process. This is important in planning intervention strategies or designing specific cell behaviours.

IEEE Congress on Evolutionary Computation, 2010

In this work, we use particle swarm optimization (PSO) to adjust the parameters of a membrane computing (MC) model of synthetic autoinducer-2 (AI-2) signalling system in genetically engineered Escherichia coli bacteria.

Journal of Theoretical Biology, 2010

Complex cellular networks regulate metabolism, environmental adaptation, and phenotypic changes in biological systems. Among the elements forming regulatory networks in bacteria are regulatory proteins such as transcription factors, which respond to exogenous and endogenous conditions. To perceive their surroundings, bacteria have evolved sensory regulatory systems of two-components. The archetype of these systems is made up of two proteins-a signal sensor and a response regulator-whose genes are usually located together in a single transcription unit. These units switch transcriptional programs in response to environmental conditions. Here, we study 14 two-component systems in Escherichia coli, which have been experimentally characterized with respect to their transcriptional regulation and their perceived signal. Given that the activity of these sensory units is connected to the rest of the transcriptional network, we first classify them as autonomous, semiautonomous or dependent, according to whether or not they use additional regulators to be transcribed. Next, we use discrete-time models to simulate their qualitative regulatory dynamics in response to their transcriptional regulation and to the activation of these systems by their cognate signals. Compared to more traditional ordinary differential equations method, ours has the advantage of being computationally simple and mathematically tractable, while keeping the ability to reproduce the phenomenology described by non-linear models. The aim of the present work is not the study of all possible behaviors of these two-component systems, but to exemplify those behaviors reported in the literature. On the other hand, most of these systems are auto-activating switches, a property that distinguishes them from the other transcription factors in the regulatory network, which are mostly auto-repressing. Based on the data, our models show dynamic behaviors that explain how most of these sensory systems convey abilities for multistationarity, and these dynamic properties could explain the phenotypic heterogeneity observed in bacterial populations. Our results are likely to have an impact in the design of synthetic signaling modules.

bioRxiv, 2021

Bacterial behavior is the outcome of both molecular mechanisms within each cell and interactions between cells in the context of their environment. Whereas whole-cell models simulate a single cell’s behavior using molecular mechanisms, agent-based models simulate many agents independently acting and interacting to generate complex collective phenomena. To synthesize agent-based and whole-cell modeling, we used a novel model integration software, called Vivarium, to construct an agent-based model of E. coli colonies where each agent is represented by a current source code snapshot from the E. coli Whole-Cell Modeling Project and interacts with other cells in a shared spatial environment. The result is the first “whole-colony” computational model that mechanistically links expression of individual proteins to a population-level phenotype. Simulated colonies exhibit heterogeneous effects on their environments, heterogeneous gene expression, and media-dependent growth. Extending the cel...

Bacterial quorum sensing (QS) has attracted much interest as the manifestation of collective behavior in prokaryotic organisms once considered strictly solitary. Significant amount of genetic, biochemical, and structural data which, has been accumulated in studies on QS in many species allows us to map properties of specific molecules and their interactions on the observed population-wide bacterial behavior. The present review attempts to give a systems biology perspective on the structure of genetic regulatory networks that control QS and considers functional implications of a variety of design principles that recur in the organization of these networks across species.

Mathematical Medicine and Biology, 2001

The regulation of density-dependent behaviour by means of quorum sensing is widespread in bacteria, the relevant phenomena including bioluminescence and population expansion by swarming, as well as virulence. The process of quorum sensing is regulated by the production and monitoring of certain molecules (referred to as QSMs); on reaching an apparent threshold concentration of QSMs (reflecting high bacterial density) the bacterial colony in concert 'switches on' the density-dependent trait. In this paper a mathematical model which describes bacterial population growth and quorum sensing in a well mixed system is proposed and studied. We view the population of bacteria as consisting of downregulated and up-regulated sub-populations, with QSMs being produced at a much faster rate by the up-regulated cells. Using curve fitting techniques for parameter estimation, solutions of the resulting system of ordinary differential equations are shown to agree well with experimental data. Asymptotic analysis in a biologically relevant limit is used to investigate the timescales for up-regulation of an exponentially growing population of bacteria, revealing the existence of bifurcation between limited and near-total upregulation. For a fixed population of cells steady-state analysis reveals that in general one physical steady-state solution exists and is linearly stable; we believe this solution to be a global attractor. A bifurcation between limited and near-total up-regulation is also discussed in the steady-state limit.