Susanna Zucca

Bottom-up engineering of biological systems through standard bricks: a modularity study on basic parts and devices.

Background Modularity is a crucial issue in the engineering world, as it enables engineers to achieve predictable outcomes when different components are interconnected. Synthetic Biology aims to apply key concepts of engineering to design and construct new biological systems that exhibit a predictable behaviour. Even if physical and measurement standards have been recently proposed to facilitate the assembly and characterization of biological components, real modularity is still a major research issue. The success of the bottom-up approach strictly depends on the clear definition of the limits in which biological functions can be predictable. Results The modularity of transcription-based biological components has been investigated in several conditions. First, the activity of a set of promoters was quantified in Escherichia coli via different measurement systems (i.e., different plasmids, reporter genes, ribosome binding sites) relative to an in vivo reference promoter. Second, promoter activity variation was measured when two independent gene expression cassettes were assembled in the same system. Third, the interchangeability of input modules (a set of constitutive promoters and two regulated promoters) connected to a fixed output device (a logic inverter) expressing GFP was evaluated. The three input modules provide tunable transcriptional signals that drive the output device. If modularity persists, identical transcriptional signals trigger identical GFP outputs. To verify this, all the input devices were individually characterized and then the input-output characteristic of the logic inverter was derived in the different configurations. Conclusions Promoters activities (referred to a standard promoter) can vary when they are measured via different reporter devices (up to 22%), when they are used within a two-expression-cassette system (up to 35%) and when they drive another device in a functionally interconnected circuit (up to 44%). This paper provides a significant contribution to the study of modularity limitations in building biological systems by providing useful data on context-dependent variability of biological components.

Characterization of a synthetic bacterial self-destruction device for programmed cell death and for recombinant proteins release

BackgroundBacterial cell lysis is a widely studied mechanism that can be achieved through the intracellular expression of phage native lytic proteins. This mechanism can be exploited for programmed cell death and for gentle cell disruption to release recombinant proteins when in vivo secretion is not feasible. Several genetic parts for cell lysis have been developed and their quantitative characterization is an essential step to enable the engineering of synthetic lytic systems with predictable behavior.ResultsHere, a BioBrick™ lysis device present in the Registry of Standard Biological Parts has been quantitatively characterized. Its activity has been measured in E. coli by assembling the device under the control of a well characterized N-3-oxohexanoyl-L-homoserine lactone (HSL) -inducible promoter and the transfer function, lysis dynamics, protein release capability and genotypic and phenotypic stability of the device have been evaluated. Finally, its modularity was tested by assembling the device to a different inducible promoter, which can be triggered by heat induction.ConclusionsThe studied device is suitable for recombinant protein release as 96% of the total amount of the intracellular proteins was successfully released into the medium. Furthermore, it has been shown that the device can be assembled to different input devices to trigger cell lysis in response to a user-defined signal. For this reason, this lysis device can be a useful tool for the rational design and construction of complex synthetic biological systems composed by biological parts with known and well characterized function. Conversely, the onset of mutants makes this device unsuitable for the programmed cell death of a bacterial population.

Characterization of an inducible promoter in different DNA copy number conditions

BackgroundThe 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.ResultsThe 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.ConclusionsEven 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.

A standard vector for the chromosomal integration and characterization of BioBrick™ parts in Escherichia coli

BackgroundThe chromosomal integration of biological parts in the host genome enables the engineering of plasmid-free stable strains with single-copy insertions of the desired gene networks. Although different integrative vectors were proposed, no standard pre-assembled genetic tool is available to carry out this task. Synthetic biology concepts can contribute to the development of standardized and user friendly solutions to easily produce engineered strains and to rapidly characterize the desired genetic parts in single-copy context.ResultsIn this work we report the design of a novel integrative vector that allows the genomic integration of biological parts compatible with the RFC10, RFC23 and RFC12 BioBrick™ standards in Escherichia coli. It can also be specialized by using BioBrick™ parts to target the desired integration site in the host genome. The usefulness of this vector has been demonstrated by integrating a set of BioBrick™ devices in two different loci of the E. coli chromosome and by characterizing their activity in single-copy. Construct stability has also been evaluated and compared with plasmid-borne solutions.ConclusionsPhysical modularity of biological parts has been successfully applied to construct a ready-to-engineer BioBrick™ vector, suitable for a stable chromosomal insertion of standard parts via the desired recombination method, i.e. the bacteriophage integration mechanism or homologous recombination. In contrast with previously proposed solutions, it is a pre-assembled vector containing properly-placed restriction sites for the direct transfer of various formats of BioBrick™ parts. This vector can facilitate the characterization of parts avoiding copy number artefacts and the construction of antibiotic resistance-free engineered microbes, suitable for industrial use.

Advances and Computational Tools towards Predictable Design in Biological Engineering

The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated.

Half-life measurements of chemical inducers for recombinant gene expression.

BackgroundInducible 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.ResultsIn 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.ConclusionsWe 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.

Multi-Faceted Characterization of a Novel LuxR-Repressible Promoter Library for Escherichia coli.

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.

Experimental measurements and mathematical modeling of biological noise arising from transcriptional and translational regulation of basic synthetic gene circuits

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.

Quantification of the gene silencing performances of rationally-designed synthetic small RNAs

Small RNAs (sRNAs) are genetic tools for the efficient and specific tuning of target genes expression in bacteria. Inspired by naturally occurring sRNAs, recent works proposed the use of artificial sRNAs in synthetic biology for predictable repression of the desired genes. Their potential was demonstrated in several application fields, such as metabolic engineering and bacterial physiology studies. Guidelines for the rational design of novel sRNAs have been recently proposed. According to these guidelines, in this work synthetic sRNAs were designed, constructed and quantitatively characterized in Escherichia coli. An sRNA targeting the reporter gene RFP was tested by measuring the specific gene silencing when RFP was expressed at different transcription levels, under the control of different promoters, in different strains, and in single-gene or operon architecture. The sRNA level was tuned by using plasmids maintained at different copy numbers. Results demonstrated that RFP silencing worked as expected in an sRNA and mRNA expression-dependent fashion. A mathematical model was used to support sRNA characterization and to estimate an efficiency-related parameter that can be used to compare the performance of the designed sRNA. Gene silencing was also successful when RFP was placed in a two-gene synthetic operon, while the non-target gene (GFP) in the operon was not considerably affected. Finally, silencing was evaluated for another designed sRNA targeting the endogenous lactate dehydrogenase gene. The quantitative study performed in this work elucidated interesting performance-related and context-dependent features of synthetic sRNAs that will strongly support predictable gene silencing in disparate basic or applied research studies.

Modelling the effects of cell-to-cell variability on the output of interconnected gene networks in bacterial populations

BackgroundThe 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.MethodsThe 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.ResultsFirst, 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.ConclusionsThe 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.