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Background: The interconnection of quantitatively characterized biological devices may lead to composite systems with apparently unpredictable behaviour. Context-dependent variability of biological parts has been investigated in several studies, measuring its entity and identifying the factors contributing to variability. Such studies rely on the experimental analysis of model systems, by quantifying reporter genes via population or single-cell approaches. However, cell-to-cell variability is not commonly included in predictability analyses, thus relying on predictive models trained and tested on central tendency values. This work aims to study in silico the effects of cell-to-cell variability on the population-averaged output of interconnected biological circuits., Methods: The steady-state deterministic transfer function of individual devices was described by Hill equations and lognormal synthetic noise was applied to their output. Two- and three-module networks were studied, where individual devices implemented inducible/repressible functions. The single-cell output of such networks was simulated as a function of noise entity; their population-averaged output was computed and used to investigate the expected variability in transfer function identification. The study was extended by testing different noise models, module logic, intrinsic/extrinsic noise proportions and network configurations., Results: First, the transfer function of an individual module was identified from simulated data of a two-module network. The estimated parameter variability among different noise entities was limited (14%), while a larger difference was observed (up to 62%) when estimated and true parameters were compared. Thus, low-variability parameter estimates can be obtained for different noise entities, although deviating from the true parameters, whose measurement requires noise knowledge. Second, the black-box input-output function of a two/three-module network was predicted from the knowledge of the transfer function of individual modules, identified in the presence of noise. Estimates variability was low (16%); however, differences up to 68% were observed by simulating a typical experimental study where the predictions obtained above were compared to network outputs generated in the presence of noise. Network predictions can, thus, deviate from real outputs when modules are characterized and re-used in different noise contexts., Conclusions: The adopted approach can support predictability studies in synthetic biology by distinguishing between actual unpredictability and contribution of noise and by guiding researchers in the design of suitable experimental measurement for gene networks.

Building biological devices to perform computational and signal processing tasks is one of the main research issues in synthetic biology. Herein, two modular biological systems that could mimic multiplexing and demultiplexing logic functions are proposed and discussed. These devices, called multiplexer (mux) and demultiplexer (demux), respectively, have a remarkable importance in electronic, telecommunication, and signal processing systems and, similarly, they could play a crucial role if implemented in a living organism, such as Escherichia coli. BioBrick standard parts were used to design mux and demux and to construct two genetic circuits that could carry out the desired tasks. A modular approach, mimicking basic logic gates (AND, OR, and NOT) with protein/autoinducer or protein/DNA interactions and interconnecting them to create the final circuits, was adopted. A mathematical model of the designed gene networks was been defined and simulations performed to validate the expected behavior of the systems. In addition, circuit subparts were tested in vivo and the results used to determine some of the parameters of the mathematical model. According to both the experimental and simulated results, guidelines for future finalization of mux and demux are provided., (Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Feedback control is ubiquitous in biological systems. It can also play a crucial role in the design of synthetic circuits implementing novel functions in living systems, to achieve self-regulation of gene expression, noise reduction, rise time decrease, or adaptive pathway control. Despite in vitro, in vivo, and ex vivo implementations have been successfully reported, the design of biological close-loop systems with quantitatively predictable behavior is still a major challenge. In this work, we tested a model-based bottom-up design of a synthetic close-loop controller in engineered Escherichia coli, aimed to automatically regulate the concentration of an extracellular molecule, N-(3-oxohexanoyl)-L-homoserine lactone (HSL), by rewiring the elements of heterologous quorum sensing/quenching networks. The synthetic controller was successfully constructed and experimentally validated. Relying on mathematical model and experimental characterization of individual regulatory parts and enzymes, we evaluated the predictability of the interconnected system behavior in vivo. The culture was able to reach an HSL steady-state level of 72 nM, accurately predicted by the model, and showed superior capabilities in terms of robustness against cell density variation and disturbance rejection, compared with a corresponding open-loop circuit. This engineering-inspired design approach may be adopted for the implementation of other close-loop circuits for different applications and contribute to decreasing trial-and-error steps. [ABSTRACT FROM AUTHOR]

Background: The study of simplified, ad-hoc constructed model systems can help to elucidate if quantitatively characterized biological parts can be effectively re-used in composite circuits to yield predictable functions. Synthetic systems designed from the bottom-up can enable the building of complex interconnected devices via rational approach, supported by mathematical modelling. However, such process is affected by different, usually non-modelled, unpredictability sources, like cell burden. Methods: Here, we analyzed a set of synthetic transcriptional cascades in . We aimed to test the predictive power of a simple Hill function activation/repression model (no-burden model, NBM) and of a recently proposed model, including Hill functions and the modulation of proteins expression by cell load (burden model, BM). To test the bottom-up approach, the circuit collection was divided into training and test sets, used to learn individual component functions and test the predicted output of interconnected circuits, respectively. Results: Among the constructed configurations, two test set circuits showed unexpected logic behaviour. Both NBM and BM were able to predict the quantitative output of interconnected devices with expected behaviour, but only the BM was also able to predict the output of one circuit with unexpected behaviour. Moreover, considering training and test set data together, the BM captures circuits output with higher accuracy than the NBM, which is unable to capture the experimental output exhibited by some of the circuits even qualitatively. Finally, resource usage parameters, estimated via BM, guided the successful construction of new corrected variants of the two circuits showing unexpected behaviour. Conclusions: Superior descriptive and predictive capabilities were achieved considering resource limitation modelling, but further efforts are needed to improve the accuracy of models for biological engineering. [ABSTRACT FROM AUTHOR]

The genetic elements regulating the natural quorum sensing (QS) networks of several microorganisms are widely used in synthetic biology to control the behaviour of single cells and engineered bacterial populations via ad-hoc constructed synthetic circuits. A number of novel engineering-inspired biological functions have been implemented and model systems have also been constructed to improve the knowledge on natural QS systems. Synthetic QS-based parts, such as promoters, have been reported in literature, to provide biological components with functions that are not present in nature, like modified induction logic or activation/repression by additional molecules. In this work, a library of promoters that can be repressed by the LuxR protein in presence of the QS autoinducer N-3-oxohexanoyl-L-homoserine lactone (AHL) was reported for Escherichia coli, to expand the toolkit of genetic parts that can be used to engineer novel synthetic QS-based systems. The library was constructed via polymerase chain reaction with highly constrained degenerate oligonucleotides, designed according to the consensus -35 and -10 sequences of a previously reported constitutive promoter library of graded strength, to maximize the probability of obtaining functional clones. All the promoters have a lux box between the -35 and -10 regions, to implement a LuxR-repressible behaviour. Twelve unique library members of graded strength (about 100-fold activity range) were selected to form the final library and they were characterized in several genetic contexts, such as in different plasmids, via different reporter genes, in presence of a LuxR expression cassette in different positions and in response to different AHL concentrations. The new obtained regulatory parts and corresponding data can be exploited by synthetic biologists to implement an artificial AHL-dependent repression of transcription in genetic circuits. The target transcriptional activity can be selected among the available library members to meet the design specifications of the biological system. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: The bottom-up programming of living organisms to implement novel user-defined biological capabilities is one of the main goals of synthetic biology. Currently, a predominant problem connected with the construction of even simple synthetic biological systems is the unpredictability of the genetic circuitry when assembled and incorporated in living cells. Copy number, transcriptional/translational demand and toxicity of the DNA-encoded functions are some of the major factors which may lead to cell overburdening and thus to nonlinear effects on system output. It is important to disclose the linearity working boundaries of engineered biological systems when dealing with such phenomena. Results: The output of an N-3-oxohexanoyl-L-homoserine lactone (HSL)-inducible RFP-expressing device was studied in Escherichia coli in different copy number contexts, ranging from 1 copy per cell (integrated in the genome) to hundreds (via multicopy plasmids). The system is composed by a luxR constitutive expression cassette and a RFP gene regulated by the luxI promoter, which is activated by the HSL-LuxR complex. System output, in terms of promoter activity as a function of HSL concentration, was assessed relative to the one of a reference promoter in identical conditions by using the Relative Promoter Units (RPU) approach. Nonlinear effects were observed in the maximum activity, which is identical in single and low copy conditions, while it decreases for higher copy number conditions. In order to properly compare the luxI promoter strength among all the conditions, a mathematical modeling approach was used to relate the promoter activity to the estimated HSL-LuxR complex concentration, which is the actual activator of transcription. During model fitting, a correlation between the copy number and the dissociation constant of HSL-LuxR complex and luxI promoter was observed. Conclusions: Even in a simple inducible system, nonlinear effects are observed and non-trivial data processing is necessary to fully characterize its operation. The in-depth analysis of model systems like this can contribute to the advances in the synthetic biology field, since increasing the knowledge about linearity and working boundaries of biological phenomena could lead to a more rational design of artificial systems, also through mathematical models, which, for example, have been used here to study hard-to-predict interactions. [ABSTRACT FROM AUTHOR]

Accurate predictive mathematical models are urgently needed in synthetic biology to support the bottom-up design of complex biological systems, minimizing trial-and-error approaches. The majority of models used so far adopt empirical Hill functions to describe activation and repression in exogenously-controlled inducible promoter systems. However, such equations may be poorly predictive in practical situations that are typical in bottom-up design, including changes in promoter copy number, regulatory protein level, and cell load. In this work, we derived novel mechanistic steady-state models of the lux inducible system, used as case study, relying on different assumptions on regulatory protein (LuxR) and cognate promoter (Plux) concentrations, inducer-protein complex formation, and resource usage limitation. We demonstrated that a change in the considered model assumptions can significantly affect circuit output, and preliminary experimental data are in accordance with the simulated activation curves. We finally showed that the models are identifiable a priori (in the analytically tractable cases) and a posteriori, and we determined the specific experiments needed to parametrize them. Although a larger-scale experimental validation is required, in the future the reported models may support synthetic circuits output prediction in practical situations with unprecedented details. [ABSTRACT FROM AUTHOR]

• New ethanologenic E. coli strains were built by deleting 3 competing pathways. • They had superior performance in concentrated whey permeate test tube fermentation. • No superior production was detected in pH-controlled bioreactor tests. • The superior performance in test tubes was due to reduced medium acidification. • The 3 deletions led to lower KOH consumption and residual load in bioreactor tests. Whey permeate (WP) is a lactose-rich waste effluent, generated during cheese manufacturing and further valorization steps, such as protein extraction. The production of ethanol by WP fermentation has been proposed to increase cost-competitiveness of dairy waste processing. In previous work, the Escherichia coli W strain was selected for its efficient growth in dairy waste and it was engineered to convert lactose into ethanol as the main fermentation product from WP and concentrated WP (CWP). To improve its performance, here the lactate dehydrogenase, fumarate reductase and pyruvate formate lyase fermentative routes were disrupted, obtaining new deletion strains. In test tubes, growth and fermentation profiles obtained in standard laboratory media and CWP showed large differences, and were affected by oxygen, medium and ethanologenic gene expression level. Among the tested strains, the one with triple deletion was superior in both high-oxygen and low-oxygen test tube fermentations, in terms of ethanol titer, rate and yield. The improved performance was due to a lower inhibition by medium acidification rather than an improved ethanol flux. The parent and triple deletion strains showed similar performance indexes in pH-controlled bioreactor experiments. However, the deletion strain showed lower base consumption and residual waste, in terms of both dry matter and chemical oxygen demand after distillation. It thus represents a step towards sustainable dairy wastewater valorization for bioenergy production by decreasing process operation costs. [ABSTRACT FROM AUTHOR]

The small number of molecules, unevenly distributed within an isogenic cell population, makes gene expression a noisy process, and strategies have evolved to deal with this variability in protein concentration and to limit its impact on cellular behaviors. As translational efficiency has a major impact on biological noise, a possible strategy to control noise is to regulate gene expression processes at the post-transcriptional level. In this study, fluctuations in the concentration of a green fluorescent protein were compared, at the single cell level, upon transformation of an isogenic bacterial cell population with synthetic gene circuits implementing either a transcriptional or a post-transcriptional control of gene expression. Experimental measurements showed that protein variability is lower under post-transcriptional control, when the same average protein concentrations are compared. This effect is well reproduced by stochastic simulations, supporting the hypothesis that noise reduction is due to the control mechanism acting on the efficiency of translation. Similar strategies are likely to play a role in noise reduction in natural systems and to be useful for controlling noise in synthetic biology applications. [ABSTRACT FROM AUTHOR]