Stochastic simulations of the tetracycline operon

Direct visualisation of drug-efflux in liveEscherichia colicells

Drug-efflux by pump proteins is one of the major mechanisms of antibiotic resistance in bacteria. Here, we use quantitative fluorescence microscopy to investigate the real-time dynamics of drug accumulation and efflux in live E. coli cells. We visualize simultaneously the intrinsically fluorescent protein-synthesis inhibitor tetracycline (Tc) and the fluorescently labelled Tc-specific efflux pump, TetA. We show that Tc penetrates the cells within minutes and accumulates to stable intracellular concentration after ∼20 min. The final level of drug accumulation reflects the balance between Tc-uptake by the cells and Tc-efflux by pump proteins. In wild-type Tc-sensitive cells, drug accumulation is significantly limited by the activity of the multidrug efflux pump, AcrAB-TolC. Tc-resistance wild-type cells carrying a plasmid-borne Tn10 transposon contain variable amounts of TetA protein, produced under steady-state repression by the TetR repressor. TetA content heterogeneity determines the cells’ initial ability to efflux Tc. Yet, efflux remains partial until the synthesis of additional TetA pumps allows for Tc-efflux activity to surpass Tc-uptake. Cells overproducing TetA no longer accumulate Tc and become resistant to high concentrations of the drug. This work uncovers the dynamic balance between drug entry, protein-synthesis inhibition, efflux-pump production, drug-efflux activity and drug-resistance levels.

Role of AcrAB-TolC multidrug efflux pump in drug-resistance acquisition by plasmid transfer

Drug-resistance dissemination by horizontal gene transfer remains poorly understood at the cellular scale. Using live-cell microscopy, we reveal the dynamics of resistance acquisition by transfer of the Escherichia coli fertility factor-conjugation plasmid encoding the tetracycline-efflux pump TetA. The entry of the single-stranded DNA plasmid into the recipient cell is rapidly followed by complementary-strand synthesis, plasmid-gene expression, and production of TetA. In the presence of translation-inhibiting antibiotics, resistance acquisition depends on the AcrAB-TolC multidrug efflux pump, because it reduces tetracycline concentrations in the cell. Protein synthesis can thus persist and TetA expression can be initiated immediately after plasmid acquisition. AcrAB-TolC efflux activity can also preserve resistance acquisition by plasmid transfer in the presence of antibiotics with other modes of action.

Continuous Culture Adaptation of Methylobacterium extorquens AM1 and TK 0001 to Very High Methanol Concentrations

The bio-economy relies on microbial strains optimized for efficient large scale production of chemicals and fuels from inexpensive and renewable feedstocks under industrial conditions. The reduced one carbon compound methanol, whose production does not involve carbohydrates needed for the feed and food sector, can be used as sole carbon and energy source by methylotrophic bacteria like Methylobacterium extorquens AM1. This strain has already been engineered to produce various commodity and high value chemicals from methanol. The toxic effect of methanol limits its concentration as feedstock to 1% v/v. We obtained M. extorquens chassis strains tolerant to high methanol via adaptive directed evolution using the GM3 technology of automated continuous culture. Turbidostat and conditional medium swap regimes were employed for the parallel evolution of the recently characterized strain TK 0001 and the reference strain AM1 and enabled the isolation of derivatives of both strains capable of stable growth with 10% methanol. The isolates produced more biomass at 1% methanol than the ancestor strains. Genome sequencing identified the gene metY coding for an O-acetyl-L-homoserine sulfhydrylase as common target of mutation. We showed that the wildtype enzyme uses methanol as substrate at elevated concentrations. This side reaction produces methoxine, a toxic homolog of methionine incorporated in polypeptides during translation. All mutated metY alleles isolated from the evolved populations coded for inactive enzymes, designating O-acetyl-L-homoserine sulfhydrylase as a major vector of methanol toxicity. A whole cell transcriptomic analysis revealed that genes coding for chaperones and proteases were upregulated in the evolved cells as compared with the wildtype, suggesting that the cells had to cope with aberrant proteins formed during the adaptation to increasing methanol exposure. In addition, the expression of ribosomal proteins and enzymes related to energy production from methanol like formate dehydrogenases and ATP synthases was boosted in the evolved cells upon a short-term methanol stress. D-lactate production from methanol by adapted cells overexpressing the native D-lactate dehydrogenase was quantified. A significant higher lactate yield was obtained compared with control cells, indicating an enhanced capacity of the cells resistant to high methanol to assimilate this one carbon feedstock more efficiently.

A single-input binary counting module based on serine integrase site-specific recombination

A device that counts and records the number of events experienced by an individual cell could have many uses in experimental biology and biotechnology. Here, we report a DNA-based 'latch' that switches between two states upon each exposure to a repeated stimulus. The key component of the latch is a DNA segment whose orientation is inverted by the actions of ϕC31 integrase and its recombination directionality factor (RDF). Integrase expression is regulated by an external input, while RDF expression is controlled by the state of the latch, such that the orientation of the invertible segment switches efficiently each time the device receives an input pulse. Recombination occurs over a time scale of minutes after initiation of integrase expression. The latch requires a delay circuit, implemented with a transcriptional repressor expressed in only one state, to ensure that each input pulse results in only one inversion of the DNA segment. Development and optimization of the latch in living cells was driven by mathematical modelling of the recombination reactions and gene expression regulated by the switch. We discuss how N latches built with orthogonal site-specific recombination systems could be chained together to form a binary ripple counter that could count to 2N - 1.

Mathematical model of a serine integrase-controlled toggle switch with a single input

Dual-state genetic switches that can change their state in response to input signals can be used in synthetic biology to encode memory and control gene expression. A transcriptional toggle switch (TTS), with two mutually repressing transcription regulators, was previously used for switching between two expression states. In other studies, serine integrases have been used to control DNA inversion switches that can alternate between two different states. Both of these switches use two different inputs to switch ON or OFF. Here, we use mathematical modelling to design a robust one-input binary switch, which combines a TTS with a DNA inversion switch. This combined circuit switches between the two states every time it receives a pulse of a single-input signal. The robustness of the switch is based on the bistability of its TTS, while integrase recombination allows single-input control. Unidirectional integrase-RDF-mediated recombination is provided by a recently developed integrase-RDF fusion protein. We show that the switch is stable against parameter variations and molecular noise, making it a promising candidate for further use as a basic element of binary counting devices.

Pulse Detecting Genetic Circuit - A New Design Approach

A robust cellular counter could enable synthetic biologists to design complex circuits with diverse behaviors. The existing synthetic-biological counters, responsive to the beginning of the pulse, are sensitive to the pulse duration. Here we present a pulse detecting circuit that responds only at the falling edge of a pulse-analogous to negative edge triggered electric circuits. As biological events do not follow precise timing, use of such a pulse detector would enable the design of robust asynchronous counters which can count the completion of events. This transcription-based pulse detecting circuit depends on the interaction of two co-expressed lambdoid phage-derived proteins: the first is unstable and inhibits the regulatory activity of the second, stable protein. At the end of the pulse the unstable inhibitor protein disappears from the cell and the second protein triggers the recording of the event completion. Using stochastic simulation we showed that the proposed design can detect the completion of the pulse irrespective to the pulse duration. In our simulation we also showed that fusing the pulse detector with a phage lambda memory element we can construct a counter which can be extended to count larger numbers. The proposed design principle is a new control mechanism for synthetic biology which can be integrated in different circuits for identifying the completion of an event.

Half-life measurements of chemical inducers for recombinant gene expression

Background

Inducible promoters are widely spread genetic tools for triggering, tuning and optimizing the expression of recombinant genes in engineered biological systems. Most of them are controlled by the addition of a specific exogenous chemical inducer that indirectly regulates the promoter transcription rate in a concentration-dependent fashion. In order to have a robust and predictable degree of control on promoter activity, the degradation rate of such chemicals should be considered in many applications like recombinant protein production.

Results

In this work, we use whole-cell biosensors to assess the half-life of three commonly used chemical inducers for recombinant Escherichia coli: Isopropyl β-D-1-thiogalactopyranoside (IPTG), anhydrotetracycline (ATc) and N-(3-oxohexanoyl)-L-homoserine lactone (HSL). A factorial study was conducted to investigate the conditions that significantly contribute to the decay rate of these inducers. Temperature has been found to be the major factor affecting ATc, while medium and pH have been found to highly affect HSL. Finally, no significant degradation was observed for IPTG among the tested conditions.

Conclusions

We have quantified the decay rate of IPTG, ATc and HSL in many conditions, some of which were not previously tested in the literature, and the main effects affecting their degradation were identified via a statistics-based framework. Whole-cell biosensors were successfully used to conduct this study, yielding reproducible measurements via simple multiwell-compatible assays. The knowledge of inducer degradation rate in several contexts has to be considered in the rational design of synthetic biological systems for improving the predictability of induction effects, especially for prolonged experiments.

Analysis and design of a genetic circuit for dynamic metabolic engineering

Recent advances in synthetic biology have equipped us with new tools for bioprocess optimization at the genetic level. Previously, we have presented an integrated in silico design for the dynamic control of gene expression based on a density-sensing unit and a genetic toggle switch. In the present paper, analysis of a serine-producing Escherichia coli mutant shows that an instantaneous ON-OFF switch leads to a maximum theoretical productivity improvement of 29.6% compared to the mutant. To further the design, global sensitivity analysis is applied here to a mathematical model of serine production in E. coli coupled with a genetic circuit. The model of the quorum sensing and the toggle switch involves 13 parameters of which 3 are identified as having a significant effect on serine concentration. Simulations conducted in this reduced parameter space further identified the optimal ranges for these 3 key parameters to achieve productivity values close to the maximum theoretical values. This analysis can now be used to guide the experimental implementation of a dynamic metabolic engineering strategy and reduce the time required to design the genetic circuit components.

Stochastic model reduction using a modified Hill-type kinetic rate law

In the present work, we address a major challenge facing the modeling of biochemical reaction networks: when using stochastic simulations, the computational load and number of unknown parameters may dramatically increase with system size and complexity. A proposed solution to this challenge is the reduction of models by utilizing nonlinear reaction rate laws in place of a complex multi-reaction mechanism. This type of model reduction in stochastic systems often fails when applied outside of the context in which it was initially conceived. We hypothesize that the use of nonlinear rate laws fails because a single reaction is inherently Poisson distributed and cannot match higher order statistics. In this study we explore the use of Hill-type rate laws as an approximation for gene regulation, specifically transcription repression. We matched output data for several simple gene networks to determine Hill-type parameters. We show that the models exhibit inaccuracies when placed into a simple feedback repression model. By adding an additional abstract reaction to the models we account for second-order statistics. This split Hill rate law matches higher order statistics and demonstrates that the new model is able to more accurately describe the mean protein output. Finally, the modified Hill model is shown to be modular and models retain accuracy when placed into a larger multi-gene network. The work as presented may be used in gene regulatory or cell-signaling networks, where multiple binding events can be captured by Hill kinetics. The added benefit of the proposed split-Hill kinetics is the improved accuracy in modeling stochastic effects. We demonstrate these benefits with a few specific reaction network examples.

Dynamics of transcription driven by the tetA promoter, one event at a time, in live Escherichia coli cells

In Escherichia coli, tetracycline prevents translation. When subject to tetracycline, E. coli express TetA to pump it out by a mechanism that is sensitive, while fairly independent of cellular metabolism. We constructed a target gene, P_tetA-mRFP1-96BS, with a 96 MS2-GFP binding site array in a single-copy BAC vector, whose expression is controlled by the tetA promoter. We measured the in vivo kinetics of production of individual RNA molecules of the target gene as a function of inducer concentration and temperature. From the distributions of intervals between transcription events, we find that RNA production by P_tetA is a sub-Poissonian process. Next, we infer the number and duration of the prominent sequential steps in transcription initiation by maximum likelihood estimation. Under full induction and at optimal temperature, we observe three major steps. We find that the kinetics of RNA production under the control of P_tetA, including number and duration of the steps, varies with induction strength and temperature. The results are supported by a set of logical pairwise Kolmogorov-Smirnov tests. We conclude that the expression of TetA is controlled by a sequential mechanism that is robust, whereas sensitive to external signals.

Stochastic simulations of a synthetic bacteria-yeast ecosystem

BACKGROUND

The field of synthetic biology has greatly evolved and numerous functions can now be implemented by artificially engineered cells carrying the appropriate genetic information. However, in order for the cells to robustly perform complex or multiple tasks, co-operation between them may be necessary. Therefore, various synthetic biological systems whose functionality requires cell-cell communication are being designed. These systems, microbial consortia, are composed of engineered cells and exhibit a wide range of behaviors. These include yeast cells whose growth is dependent on one another, or bacteria that kill or rescue each other, synchronize, behave as predator-prey ecosystems or invade cancer cells.

RESULTS

In this paper, we study a synthetic ecosystem comprising of bacteria and yeast that communicate with and benefit from each other using small diffusible molecules. We explore the behavior of this heterogeneous microbial consortium, composed of Saccharomyces cerevisiae and Escherichia coli cells, using stochastic modeling. The stochastic model captures the relevant intra-cellular and inter-cellular interactions taking place in and between the eukaryotic and prokaryotic cells. Integration of well-characterized molecular regulatory elements into these two microbes allows for communication through quorum sensing. A gene controlling growth in yeast is induced by bacteria via chemical signals and vice versa. Interesting dynamics that are common in natural ecosystems, such as obligatory and facultative mutualism, extinction, commensalism and predator-prey like dynamics are observed. We investigate and report on the conditions under which the two species can successfully communicate and rescue each other.

CONCLUSIONS

This study explores the various behaviors exhibited by the cohabitation of engineered yeast and bacterial cells. The way that the model is built allows for studying the dynamics of any system consisting of two species communicating with one another via chemical signals. Therefore, key information acquired by our model may potentially drive the experimental design of various synthetic heterogeneous ecosystems.

An E. coli cell-free expression toolbox: application to synthetic gene circuits and artificial cells

Cell-free protein synthesis is becoming a powerful technique to construct and to study complex informational processes in vitro. Engineering synthetic gene circuits in a test tube, however, is seriously limited by the transcription repertoire of modern cell-free systems, composed of only a few bacteriophage regulatory elements. Here, we report the construction and the phenomenological characterization of synthetic gene circuits engineered with a cell-free expression toolbox that works with the seven E. coli sigma factors. The E. coli endogenous holoenzyme E(70) is used as the primary transcription machinery. Elementary circuit motifs, such as multiple stage cascades, AND gate and negative feedback loops are constructed with the six other sigma factors, two bacteriophage RNA polymerases, and a set of repressors. The circuit dynamics reveal the importance of the global mRNA turnover rate and of passive competition-induced transcriptional regulation. Cell-free reactions can be carried out over long periods of time with a small-scale dialysis reactor or in phospholipid vesicles, an artificial cell system. This toolbox is a unique platform to study complex transcription/translation-based biochemical systems in vitro.

proTeOn and proTeOff, new protein devices that inducibly activate bacterial gene expression

Using an original workflow, we have modeled, constructed, and characterized two new molecular devices that inducibly activate gene expression in Escherichia coli. The devices, prokaryotic-TetOn and prokaryotic-TetOff, were built by fusing an inducible DNA-binding protein domain to a transcription activation domain and constructing a complementary synthetic promoter sequence through which they could control downstream gene expression. In particular, the transactivators were built using variants of the tetracycline repressor, TetR, and the transactivating domain of the LuxR activator. The complementary promoter sequence included TetR's operator, tetO, and elements of the lux promoter. These specific protein domains and their operator sites were chosen as they have been thoroughly studied and well characterized. First, our methodology began with optimizing the geometry of the molecular components using molecular modeling. We did so to achieve an unprecedented combination of controllable and transactivating function in bacterial organisms. The devices were then built to activate the expression of green fluorescent protein. Their unique function was found to be robustly tight and activating many-fold increases of expressed gene levels, as measured by flow cytometry experiments. The devices were further characterized with stochastic kinetic models. The new devices presented herein may become useful additions to the molecular toolboxes used by biologists to control bacterial gene expression. The methodology used may also be a foundation for the design, development, and characterization of a library of such devices and more complex gene regulatory networks.