Lingchong You

Programmed population control by cell–cell communication and regulated killing

De novo engineering of gene circuits inside cells is extremely difficult, and efforts to realize predictable and robust performance must deal with noise in gene expression and variation in phenotypes between cells. Here we demonstrate that by coupling gene expression to cell survival and death using cell–cell communication, we can programme the dynamics of a population despite variability in the behaviour of individual cells. Specifically, we have built and characterized a ‘population control’ circuit that autonomously regulates the density of an Escherichia coli population. The cell density is broadcasted and detected by elements from a bacterial quorum-sensing system, which in turn regulate the death rate. As predicted by a simple mathematical model, the circuit can set a stable steady state in terms of cell density and gene expression that is easily tunable by varying the stability of the cell–cell communication signal. This circuit incorporates a mechanism for programmed death in response to changes in the environment, and allows us to probe the design principles of its more complex natural counterparts.

Engineering microbial consortia: a new frontier in synthetic biology

Microbial consortia are ubiquitous in nature and are implicated in processes of great importance to humans, from environmental remediation and wastewater treatment to assistance in food digestion. Synthetic biologists are honing their ability to program the behavior of individual microbial populations, forcing the microbes to focus on specific applications, such as the production of drugs and fuels. Given that microbial consortia can perform even more complicated tasks and endure more changeable environments than monocultures can, they represent an important new frontier for synthetic biology. Here, we review recent efforts to engineer synthetic microbial consortia, and we suggest future applications.

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 others 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.

A bistable Rb–E2F switch underlies the restriction point

The restriction point (R-point) marks the critical event when a mammalian cell commits to proliferation and becomes independent of growth stimulation. It is fundamental for normal differentiation and tissue homeostasis, and seems to be dysregulated in virtually all cancers. Although the R-point has been linked to various activities involved in the regulation of G1–S transition of the mammalian cell cycle, the underlying mechanism remains unclear. Using single-cell measurements, we show here that the Rb–E2F pathway functions as a bistable switch to convert graded serum inputs into all-or-none E2F responses. Once turned ON by sufficient serum stimulation, E2F can memorize and maintain this ON state independently of continuous serum stimulation. We further show that, at critical concentrations and duration of serum stimulation, bistable E2F activation correlates directly with the ability of a cell to traverse the R-point.

Origin of bistability underlying mammalian cell cycle entry

Precise control of cell proliferation is fundamental to tissue homeostasis and differentiation. Mammalian cells commit to proliferation at the restriction point (R‐point). It has long been recognized that the R‐point is tightly regulated by the Rb–E2F signaling pathway. Our recent work has further demonstrated that this regulation is mediated by a bistable switch mechanism. Nevertheless, the essential regulatory features in the Rb–E2F pathway that create this switching property have not been defined. Here we analyzed a library of gene circuits comprising all possible link combinations in a simplified Rb–E2F network. We identified a minimal circuit that is able to generate robust, resettable bistability. This minimal circuit contains a feed‐forward loop coupled with a mutual‐inhibition feedback loop, which forms an AND‐gate control of the E2F activation. Underscoring its importance, experimental disruption of this circuit abolishes maintenance of the activated E2F state, supporting its importance for the bistability of the Rb–E2F system. Our findings suggested basic design principles for the robust control of the bistable cell cycle entry at the R‐point.

Effects of Escherichia coli Physiology on Growth of Phage T7 In Vivo and In Silico

Phage development depends not only upon phage functions but also on the physiological state of the host, characterized by levels and activities of host cellular functions. We established Escherichia coli at different physiological states by continuous culture under different dilution rates and then measured its production of phage T7 during a single cycle of infection. We found that the intracellular eclipse time decreased and the rise rate increased as the growth rate of the host increased. To develop mechanistic insight, we extended a computer simulation for the growth of phage T7 to account for the physiology of its host. Literature data were used to establish mathematical correlations between host resources and the host growth rate; host resources included the amount of genomic DNA, pool sizes and elongation rates of RNA polymerases and ribosomes, pool sizes of amino acids and nucleoside triphosphates, and the cell volume. The in silico (simulated) dependence of the phage intracellular rise rate on the host growth rate gave quantitatively good agreement with our in vivo results, increasing fivefold for a 2.4-fold increase in host doublings per hour, and the simulated dependence of eclipse time on growth rate agreed qualitatively, deviating by a fixed delay. When the simulation was used to numerically uncouple host resources from the host growth rate, phage growth was found to be most sensitive to the host translation machinery, specifically, the level and elongation rate of the ribosomes. Finally, the simulation was used to follow how bottlenecks to phage growth shift in response to variations in host or phage functions.

Optimality and robustness in quorum sensing (QS)-mediated regulation of a costly public good enzyme

Bacteria secrete a variety of public good exoproducts into their environment. These exoproducts are typically produced under the control of quorum sensing (QS), a signaling mechanism by which bacteria sense and respond to changes in their density. QS seems to provide an advantageous strategy to regulate these costly but beneficial exoproducts: it delays production until sufficiently high cell density, when the overall benefit of exoproducts outweighs cost of their production. This notion raises several fundamental questions about QS as a general control strategy adopted by bacteria. How much delay is advantageous? Under what conditions does QS-mediated regulation become advantageous? How does this advantage depend on the kinetic properties of QS? How robust is a given QS system to the stochastic events that occur over bacterial lifecycles? To quantitatively address these questions, we engineered a gene circuit in Escherichia coli to control the synthesis and secretion of a costly but beneficial exoenzyme. We show that exoenzyme production is overall advantageous only if initiated at a sufficiently high density. This property sets the potential advantage for QS-mediated regulation when the initial density is low and the growth cycle is sufficiently long compared with the exoenzyme response time. This advantage of QS-mediated regulation is robust to varying initial cell densities and growth durations, and it is particularly striking when bacteria face uncertainty, such as from stochastic dispersal during their lifecycle. We show, however, that, for QS to be optimal, its kinetic properties must be appropriately tuned; this property has implications for antibacterial treatments that target QS.

Image segmentation and dynamic lineage analysis in single-cell fluorescence microscopy

An increasingly common component of studies in synthetic and systems biology is analysis of dynamics of gene expression at the single‐cell level, a context that is heavily dependent on the use of time‐lapse movies. Extracting quantitative data on the single‐cell temporal dynamics from such movies remains a major challenge. Here, we describe novel methods for automating key steps in the analysis of single‐cell, fluorescent images—segmentation and lineage reconstruction—to recognize and track individual cells over time. The automated analysis iteratively combines a set of extended morphological methods for segmentation, and uses a neighborhood‐based scoring method for frame‐to‐frame lineage linking. Our studies with bacteria, budding yeast and human cells, demonstrate the portability and usability of these methods, whether using phase, bright field or fluorescent images. These examples also demonstrate the utility of our integrated approach in facilitating analyses of engineered and natural cellular networks in diverse settings. The automated methods are implemented in freely available, open‐source software.

Optimal tuning of bacterial sensing potential

Through production and sensing of small signal molecules, quorum sensing (QS) enables bacteria to detect changes in their density and regulate their functions accordingly. QS systems are tremendously diverse in terms of their specific sensory components, the biochemical and transport properties of signaling molecules, their target functions and the context in which QS‐mediated functions are activated. Cutting across this diversity, however, the central architecture of QS systems is universal; it comprises signal synthesis, secretion, degradation and detection. We are thus able to derive a general metric for QS ‘sensing potential’ based on this ‘core’ module. The sensing potential quantifies the ability of a single bacterium to sense the dimensions of its microenvironment. This simple metric captures the dominant activation properties of diverse QS systems, giving a concise description of the sensing characteristics. As such, it provides a convenient quantitative framework to study the phenotypic effects of QS characteristics. As an example, we show how QS characteristics uniquely determine the scenarios in which regulation of a typical QS‐controlled function, such as exoenzyme secretion, becomes advantageous.

Spatiotemporal modulation of biodiversity in a synthetic chemical-mediated ecosystem

Biodiversity, or the relative abundance of species, measures the persistence of an ecosystem. To better understand its modulation, we analyzed the spatial and temporal dynamics of a synthetic, chemical-mediated ecosystem that consisted of two engineered Escherichia coli populations. Depending on the specific experimental conditions implemented, the dominant interaction between the two populations could be competition for nutrients or predation due to engineered communication. While the two types of interactions resulted in different spatial patterns, they demonstrated a common trend in terms of the modulation of biodiversity. Specifically, biodiversity decreased with increasing cellular motility if the segregation distance between the two populations was comparable to the length scale of the chemical-mediated interaction. Otherwise, biodiversity was insensitive to cellular motility. Our results suggested a simple criterion for predicting the modulation of biodiversity by habitat partitioning and cellular motility in chemical-mediated ecosystems.