Mary J. Dunlop

Regulatory activity revealed by dynamic correlations in gene expression noise.

Gene regulatory interactions are context dependent, active in some cellular states but not in others. Stochastic fluctuations, or noise, in gene expression propagate through active, but not inactive, regulatory links. Thus, correlations in gene expression noise could provide a noninvasive means to probe the activity states of regulatory links. However, global, extrinsic, noise sources generate correlations even without direct regulatory links. Here we show that single-cell time-lapse microscopy, by revealing time lags due to regulation, can discriminate between active regulatory connections and extrinsic noise. We demonstrate this principle mathematically, using stochastic modeling, and experimentally, using simple synthetic gene circuits. We then use this approach to analyze dynamic noise correlations in the galactose metabolism genes of Escherichia coli. We find that the CRP-GalS-GalE feed-forward loop is inactive in standard conditions but can become active in a GalR mutant. These results show how noise can help analyze the context dependence of regulatory interactions in endogenous gene circuits.

A synthetic three-color scaffold for monitoring genetic regulation and noise

BackgroundCurrent methods for analyzing the dynamics of natural regulatory networks, and quantifying synthetic circuit function, are limited by the lack of well-characterized genetic measurement tools. Fluorescent reporters have been used to measure dynamic gene expression, but recent attempts to monitor multiple genes simultaneously in single cells have not focused on independent, isolated measurements. Multiple reporters can be used to observe interactions between natural genes, or to facilitate the debugging of biologically engineered genetic networks. Using three distinguishable reporter genes in a single cell can reveal information not obtainable from only one or two reporters. One application of multiple reporters is the use of genetic noise to reveal regulatory connections between genes. Experiments in both natural and synthetic systems would benefit from a well-characterized platform for expressing multiple reporter genes and synthetic network components.ResultsWe describe such a plasmid-based platform for the design and optimization of synthetic gene networks, and for analysis of endogenous gene networks. This network scaffold consists of three distinguishable fluorescent reporter genes controlled by inducible promoters, with conveniently placed restriction sites to make modifications straightforward. We quantitatively characterize the scaffold in Escherichia coli with single-cell fluorescence imaging and time-lapse microscopy. The three spectrally distinct reporters allow independent monitoring of genetic regulation and analysis of genetic noise. As a novel application of this tool we show that the presence of genetic noise can reveal transcriptional co-regulation due to a hidden factor, and can distinguish constitutive from regulated gene expression.ConclusionWe have constructed a general chassis where three promoters from natural genes or components of synthetic networks can be easily inserted and independently monitored on a single construct using optimized fluorescent protein reporters. We have quantitatively characterized the baseline behavior of the chassis so that it can be used to measure dynamic gene regulation and noise. Overall, the system will be useful both for analyzing natural genetic networks and assembling synthetic ones.

Trade-Offs in Improving Biofuel Tolerance Using Combinations of Efflux Pumps

Microbes can be engineered to produce next-generation biofuels; however, the accumulation of toxic biofuels can limit yields. Previous studies have shown that efflux pumps can increase biofuel tolerance and improve production. Here, we asked whether expressing multiple pumps in combination could further increase biofuel tolerance. Pump overexpression inhibits cell growth, suggesting a trade-off between biofuel and pump toxicity. With multiple pumps, it is unclear how the fitness landscape is impacted. To address this, we measured tolerance of Escherichia coli to the biojet fuel precursor α-pinene in one-pump and two-pump strains. To support our experiments, we developed a mathematical model describing toxicity due to biofuel and overexpression of pumps. We found that data from one-pump strains can accurately predict the performance of two-pump strains. This result suggests that it may be possible to dramatically reduce the number of experiments required for characterizing the effects of combined biofuel tolerance mechanisms.

A Multi-Model Approach to Identification of Biosynthetic Pathways

We present an identification framework for biochemical systems that allows multiple candidate models to be compared. This framework is designed to select a model that fits the data while maintaining model simplicity. The model identification task is divided into a parameter estimation stage and a model comparison stage. Model selection is based on calculating Akaikes information criterion, which is a systematic method for determining the model that best represents a set of experimental data. Two case studies are presented: a simulated transcriptional control circuit and a system of oscillators that has been built and characterized in vitro. In both examples the multi-model framework is able to discriminate between model candidates to select the one that best describes the data.

Design and Selection of a Synthetic Feedback Loop for Optimizing Biofuel Tolerance

Feedback control allows cells to dynamically sense and respond to environmental changes. However, synthetic controller designs can be challenging because of implementation issues, such as determining optimal expression levels for circuit components within a feedback loop. Here, we addressed this by coupling rational design with selection to engineer a synthetic feedback circuit to optimize tolerance of Escherichia coli to the biojet fuel pinene. E.xa0coli can be engineered to produce pinene, but it is toxic to cells. Efflux pumps, such as the AcrAB-TolC pump, can improve tolerance, but pump expression impacts growth. To address this, we used feedback to dynamically regulate pump expression in response to stress. We developed a library with thousands of synthetic circuit variants and subjected it to three types of pinene treatment (none, constant, and varying pinene). We were able to select for strains that were biofuel tolerant without a significant growth cost in the absence of biofuel. Using next-generation sequencing, we found common characteristics in the designs and identified controllers that dramatically improved biofuel tolerance.

Stress Introduction Rate Alters the Benefit of AcrAB-TolC Efflux Pumps

Stress tolerance studies are typically conducted in an all-or-none fashion. However, in realistic settings-such as in clinical or metabolic engineering applications-cells may encounter stresses at different rates. Therefore, how cells tolerate stress may depend on its rate of appearance. To address this, we studied how the rate of stress introduction affects bacterial stress tolerance by focusing on a key stress response mechanism. Efflux pumps, such as AcrAB-TolC of Escherichia coli, are membrane transporters well known for the ability to export a wide variety of substrates, including antibiotics, signaling molecules, and biofuels. Although efflux pumps improve stress tolerance, pump overexpression can result in a substantial fitness cost to the cells. We hypothesized that the ideal pump expression level would involve a rate-dependent trade-off between the benefit of pumps and the cost of their expression. To test this, we evaluated the benefit of the AcrAB-TolC pump under different rates of stress introduction, including a step, a fast ramp, and a gradual ramp. Using two chemically diverse stresses, the antibiotic chloramphenicol and the jet biofuel precursor pinene, we assessed the benefit provided by the pumps. A mathematical model describing these effects predicted the benefit as a function of the rate of stress introduction. Our findings demonstrate that as the rate of introduction is lowered, stress response mechanisms provide a disproportionate benefit to pump-containing strains, allowing cells to survive beyond the original inhibitory concentrations.IMPORTANCE Efflux pumps are ubiquitous in nature and provide stress tolerance in the cells of species ranging from bacteria to mammals. Understanding how pumps provide tolerance has far-reaching implications for diverse fields, from medicine to biotechnology. Here, we investigated how the rate of stressor appearance impacts tolerance. We focused on two distinct substrates of AcrAB-TolC efflux pumps, the antibiotic chloramphenicol and the biofuel precursor pinene. Interestingly, tolerance is highly dependent on the rate of stress introduction. Therefore, it is important to consider not only the total quantity of a stressor but also the rate at which it is applied. The implications of this work are significant because environments are rarely static; antibiotic concentrations change during dosing, and metabolic engineering processes change with time.

Analysis of a Digital Clock for Molecular Computing

The control of synthetic genetic regulatory networks is an emerging engineering challenge. In this study, we propose a new synthetic genetic network that behaves as a digital clock, producing square waveform oscillations. We analyze two models of the network: a deterministic model based on Michaelis-Menten kinetics, as well as a stochastic model based on the Gillespie algorithm. Both models predict regions of oscillatory behavior; the deterministic model provides insight into the conditions required to produce the oscillating clock-like behavior, while the stochastic model is truer to natural dynamics. Intracellular stochasticity is seen to contribute phase noise to the oscillator, and we propose improvements for the network and discuss the conceptual foundations of these improvements.

Customized Regulation of Diverse Stress Response Genes by the Multiple Antibiotic Resistance Activator MarA

Stress response networks frequently have a single upstream regulator that controls many downstream genes. However, the downstream targets are often diverse, therefore it remains unclear how their expression is specialized when under the command of a common regulator. To address this, we focused on a stress response network where the multiple antibiotic resistance activator MarA from Escherichia coli regulates diverse targets ranging from small RNAs to efflux pumps. Using single-cell experiments and computational modeling, we showed that each downstream gene studied has distinct activation, noise, and information transmission properties. Critically, our results demonstrate that understanding biological context is essential; we found examples where strong activation only occurs outside physiologically relevant ranges of MarA and others where noise is high at wild type MarA levels and decreases as MarA reaches its physiological limit. These results demonstrate how a single regulatory protein can maintain specificity while orchestrating the response of many downstream genes.

Expression of Heterologous Sigma Factor Expands the Searchable Space for Biofuel Tolerance Mechanisms

Microorganisms can produce hydrocarbons that can serve as replacements or additions to conventional liquid fuels for use in the transportation sector. However, a common problem in the microbial synthesis of biofuels is that these compounds often have toxic effects on the cell. In this study, we focused on mitigating the toxicity of the biojet fuel precursor pinene on Escherichia coli. We used genomic DNA from Pseudomonas putida KT2440, which has innate solvent-tolerance properties, to create transgenic libraries in an E.xa0coli host. We exposed cells containing the library to pinene, selecting for genes that improved tolerance. Importantly, we found that expressing the sigma factor RpoD from P.xa0putida greatly expanded the diversity of tolerance genes recovered. With low expression of rpoDP.putida, we isolated a single pinene tolerance gene; with increased expression of the sigma factor our selection experiments returned multiple distinct tolerance mechanisms, including some that have been previously documented and also new mechanisms. Interestingly, high levels of rpoDP.putida induction resulted in decreased diversity. We found that the tolerance levels provided by some genes are highly sensitive to the level of induction of rpoDP.putida, while others provide tolerance across a wide range of rpoDP.putida levels. This method for unlocking diversity in tolerance screening using heterologous sigma factor expression was applicable to both plasmid and fosmid-based transgenic libraries. These results suggest that by controlling the expression of appropriate heterologous sigma factors, we can greatly increase the searchable genomic space within transgenic libraries.

Robustness in gene circuits: clustering of functional responses

In contrast to engineering applications, in which the structure of control laws are designed to satisfy prescribed function requirements, in biology it is often necessary to infer gene-circuit function from incomplete data on gene-circuit structure. By using the feed-forward loop as a model system, this paper introduces a technique for classifying gene-circuit function given gene-circuit structure. In simulations performed on a comprehensive set of models that span a broad range of parameter space, some designs are robust, producing one unique type of functional response regardless of parameter selection. Other designs may exhibit a variety of functional responses, depending upon parameter values. We conclude that, although some feed-forward loop models have designs that lend themselves to unique function inference, others have designs for which the function type may be uncertain.