Temperature dependence of ssrA-tag mediated protein degradation

Toxin-based screening of C-terminal tags in Escherichia coli reveals the exceptional potency of ssrA-like degrons

All bacteria possess ATP-dependent proteases that destroy cytosolic proteins. These enzymes help cells mitigate proteotoxic stress, adapt to changing nutrient availability, regulate virulence phenotypes, and transition to pathogenic lifestyles. Moreover, ATP-dependent proteases have emerged as promising antibacterial and antivirulence targets in a variety of pathogens. The physiological roles of these proteases are largely defined by the complement of proteins that they degrade. Substrates are typically recognized in a highly selective manner, often via short unstructured sequences termed degrons. While a few degrons have been identified and rigorously characterized, we lack a systematic understanding of how proteases select valid degrons from the vast complexity of protein sequence space. Here, we describe a novel high-throughput screening approach in Escherichia coli that couples proteolysis of a protein toxin to cell survival. We used this method to screen a combinatorial library of C-terminal pentapeptide sequences for functionality as proteolytic degrons in wild type E. coli, and in strains lacking components of the ClpXP and ClpAP proteases. By examining the competitive enrichment of sequences over time, we found that about one percent of pentapeptide tags lead to toxin proteolysis. Interestingly, the most enriched degrons were ClpXP-dependent and highly similar to the ssrA tag, one of the most extensively characterized degrons in bacteria. Among ssrA-like sequences, we observed that specific upstream residues correlate with successful recognition. The lack of diversity among strongly enriched sequences suggests that ssrA-like tags comprise a uniquely potent class of short C-terminal degron in E. coli. Efficient proteolysis of substrates lacking such degrons likely requires adaptors or multivalent interactions. These findings broaden our understanding of the constraints that shape the bacterial proteolytic landscape. Our screening approach may be broadly applicable to probing aspects of proteolytic substrate selection in other bacterial systems.

Toehold switch based biosensors for sensing the highly trafficked rosewood Dalbergia maritima

Nucleic acid sensing is a 3 decades old but still challenging area of application for different biological sub-domains, from pathogen detection to single cell transcriptomics analysis. The many applications of nucleic acid detection and identification are mostly carried out by PCR techniques, sequencing, and their derivatives used at large scale. However, these methods’ limitations on speed, cost, complexity and specificity have motivated the development of innovative detection methods among which nucleic acid biosensing technologies seem promising. Toehold switches are a particular class of RNA sensing devices relying on a conformational switch of secondary structure induced by the pairing of the detected trigger RNA with a de novo designed synthetic sensing mRNA molecule. Here we describe a streamlined methodology enabling the development of such a sensor for the RNA-mediated detection of an endangered plant species in a cell-free reaction system. We applied this methodology to help identify the rosewood Dalbergia maritima, a highly trafficked wood, whose protection is limited by the capacity of the authorities to distinguish protected logs from other unprotected but related species. The streamlined pipeline presented in this work is a versatile framework enabling cheap and rapid development of new sensors for custom RNA detection.

Measuring and modeling energy and power consumption in living microbial cells with a synthetic ATP reporter

Background

Adenosine triphosphate (ATP) is the main energy carrier in living organisms, critical for metabolism and essential physiological processes. In humans, abnormal regulation of energy levels (ATP concentration) and power consumption (ATP consumption flux) in cells is associated with numerous diseases from cancer, to viral infection and immune dysfunction, while in microbes it influences their responses to drugs and other stresses. The measurement and modeling of ATP dynamics in cells is therefore a critical component in understanding fundamental physiology and its role in pathology. Despite the importance of ATP, our current understanding of energy dynamics and homeostasis in living cells has been limited by the lack of easy-to-use ATP sensors and the lack of models that enable accurate estimates of energy and power consumption related to these ATP dynamics. Here we describe a dynamic model and an ATP reporter that tracks ATP in E. coli over different growth phases.

Results

The reporter is made by fusing an ATP-sensing rrnB P1 promoter with a fast-folding and fast-degrading GFP. Good correlations between reporter GFP and cellular ATP were obtained in E. coli growing in both minimal and rich media and in various strains. The ATP reporter can reliably monitor bacterial ATP dynamics in response to nutrient availability. Fitting the dynamics of experimental data corresponding to cell growth, glucose, acetate, dissolved oxygen, and ATP yielded a mathematical and circuit model. This model can accurately predict cellular energy and power consumption under various conditions. We found that cellular power consumption varies significantly from approximately 0.8 and 0.2 million ATP/s for a tested strain during lag and stationary phases to 6.4 million ATP/s during exponential phase, indicating ~ 8–30-fold changes of metabolic rates among different growth phases. Bacteria turn over their cellular ATP pool a few times per second during the exponential phase and slow this rate by ~ 2–5-fold in lag and stationary phases.

Conclusion

Our rrnB P1-GFP reporter and kinetic circuit model provide a fast and simple way to monitor and predict energy and power consumption dynamics in bacterial cells, which can impact fundamental scientific studies and applied medical treatments in the future.

Novel Tunable Spatio-Temporal Patterns From a Simple Genetic Oscillator Circuit

Multicellularity, the coordinated collective behavior of cell populations, gives rise to the emergence of self-organized phenomena at many different spatio-temporal scales. At the genetic scale, oscillators are ubiquitous in regulation of multicellular systems, including during their development and regeneration. Synthetic biologists have successfully created simple synthetic genetic circuits that produce oscillations in single cells. Studying and engineering synthetic oscillators in a multicellular chassis can therefore give us valuable insights into how simple genetic circuits can encode complex multicellular behaviors at different scales. Here we develop a study of the coupling between the repressilator synthetic genetic ring oscillator and constraints on cell growth in colonies. We show in silico how mechanical constraints generate characteristic patterns of growth rate inhomogeneity in growing cell colonies. Next, we develop a simple one-dimensional model which predicts that coupling the repressilator to this pattern of growth rate via protein dilution generates traveling waves of gene expression. We show that the dynamics of these spatio-temporal patterns are determined by two parameters; the protein degradation and maximum expression rates of the repressors. We derive simple relations between these parameters and the key characteristics of the traveling wave patterns: firstly, wave speed is determined by protein degradation and secondly, wavelength is determined by maximum gene expression rate. Our analytical predictions and numerical results were in close quantitative agreement with detailed individual based simulations of growing cell colonies. Confirming published experimental results we also found that static ring patterns occur when protein stability is high. Our results show that this pattern can be induced simply by growth rate dilution and does not require transition to stationary phase as previously suggested. Our method generalizes easily to other genetic circuit architectures thus providing a framework for multi-scale rational design of spatio-temporal patterns from genetic circuits. We use this method to generate testable predictions for the synthetic biology design-build-test-learn cycle.

An Open-Source Plate Reader

Microplate readers are foundational instruments in experimental biology and bioengineering that enable multiplexed spectrophotometric measurements. To enhance their accessibility, we here report the design, construction, validation, and benchmarking of an open-source microplate reader. The system features full-spectrum absorbance and fluorescence emission detection, in situ optogenetic stimulation, and stand-alone touch screen programming of automated assay protocols. The total system costs less than $3500, a fraction of the cost of commercial plate readers, and can detect the fluorescence of common dyes at concentrations as low as ∼10 nM. Functional capabilities were demonstrated in the context of synthetic biology, optogenetics, and photosensory biology: by steady-state measurements of ligand-induced reporter gene expression in a model of bacterial quorum sensing and by flavin photocycling kinetic measurements of a LOV (light-oxygen-voltage) domain photoreceptor used for optogenetic transcriptional activation. Fully detailed guides for assembling the device and automating it using the custom Python-based API (Application Program Interface) are provided. This work contributes a key technology to the growing community-wide infrastructure of open-source biology-focused hardware, whose creation is facilitated by rapid prototyping capabilities and low-cost electronics, optoelectronics, and microcomputers.

Engineering Translational Resource Allocation Controllers: Mechanistic Models, Design Guidelines, and Potential Biological Implementations

The use of orthogonal ribosomes in combination with dynamic resource allocation controllers is a promising approach for relieving the negative effects of cellular resource limitations on the modularity of synthetic gene circuits. Here, we develop a detailed mechanistic model of gene expression and resource allocation, which when simplified to a tractable level of complexity, allows the rational design of translational resource allocation controllers. Analysis of this model reveals a fundamental design trade-off: that reducing coupling acts to decrease gene expression. Through a sensitivity analysis of the experimentally tunable controller parameters, we identify how each controller design parameter affects the overall closed-loop behavior of the system, leading to a detailed set of design guidelines for optimally managing this trade-off. On the basis of our designs, we evaluated a number of alternative potential experimental implementations of the proposed system using commonly available biological components. Finally, we show that the controller is capable of dynamically allocating ribosomes as needed to restore modularity in a number of more complex synthetic circuits, such as the repressilator, and activation cascades composed of multiple interacting modules.

Towards an Aspect-Oriented Design and Modelling Framework for Synthetic Biology

Work on synthetic biology has largely used a component-based metaphor for system construction. While this paradigm has been successful for the construction of numerous systems, the incorporation of contextual design issues-either compositional, host or environmental-will be key to realising more complex applications. Here, we present a design framework that radically steps away from a purely parts-based paradigm by using aspect-oriented software engineering concepts. We believe that the notion of concerns is a powerful and biologically credible way of thinking about system synthesis. By adopting this approach, we can separate core concerns, which represent modular aims of the design, from cross-cutting concerns, which represent system-wide attributes. The explicit handling of cross-cutting concerns allows for contextual information to enter the design process in a modular way. As a proof-of-principle, we implemented the aspect-oriented approach in the Python tool, SynBioWeaver, which enables the combination, or weaving, of core and cross-cutting concerns. The power and flexibility of this framework is demonstrated through a number of examples covering the inclusion of part context, combining circuit designs in a context dependent manner, and the generation of rule, logic and reaction models from synthetic circuit designs.

Orthogonal Regulatory Circuits for Escherichia coli Based on the γ-Butyrolactone System of Streptomyces coelicolor

Chemically inducible transcription factors are widely used to control gene expression of synthetic devices. The bacterial quorum sensing system is a popular tool to achieve such control. However, different quorum sensing systems have been found to cross-talk, both between themselves and with the hosts of these devices, and they are leaky by nature. Here we evaluate the potential use of the γ-butyrolactone system from Streptomyces coelicolor A3(2) M145 as a complementary regulatory circuit. First, two additional genes responsible for the biosynthesis of γ-butyrolactones were identified in S. coelicolor M145 and then expressed in E. coli BL21 under various experimental conditions. Second, the γ-butyrolactone receptor ScbR was optimized for expression in E. coli BL21. Finally, signal and promoter crosstalk between the γ-butyrolactone system from S. coelicolor and quorum sensing systems from Vibrio fischeri and Pseudomonas aeruginosa was evaluated. The results show that the γ-butyrolactone system does not crosstalk with the quorum sensing systems and can be used to generate orthogonal synthetic circuits.

Re-using biological devices: a model-aided analysis of interconnected transcriptional cascades designed from the bottom-up

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 Escherichia coli. 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.

Electronic supplementary material

The online version of this article (10.1186/s13036-017-0090-3) contains supplementary material, which is available to authorized users.

Encapsulation of multiple cargo proteins within recombinant Eut nanocompartments

Spatial organization via encapsulation of enzymes within recombinant nanocompartments may increase efficiency in multienzyme cascades. Previously, we reported the encapsulation of single cargo proteins within nanocompartments in the heterologous host Escherichia coli. This was achieved by coexpression of the Salmonella enterica LT2 ethanolamine utilization bacterial microcompartment shell proteins EutS or EutSMNLK, with a signal sequence EutC1-19 cargo protein fusion. Optimization of this system, leading to the targeting of more than one cargo protein, requires an understanding of the encapsulation mechanism. In this work, we report that the signal sequence EutC1-19 targets cargo to the interior of nanocompartments via a hydrophobic interaction with a helix on shell protein EutS. We confirm that EutC1-19 does not interact with other Eut BMC shell proteins, EutMNLK. Furthermore, we show that a second signal sequence EutE1-21 interacts specifically with the same helix on EutS. Both signal sequences appear to compete for the same EutS helix to simultaneously colocalize two cargo proteins to the interior of recombinant nanocompartments. This work offers the first insights into signal sequence-shell protein interactions required for cargo sequestration within Eut BMCs. It also provides a basis for the future engineering of Eut nanocompartments as a platform for the potential colocalization of multienzyme cascades for synthetic biology applications.

Toolbox for Exploring Modular Gene Regulation in Synthetic Biology Training

We report a toolbox for exploring the modular tuning of genetic circuits, which has been specifically optimized for widespread deployment in STEM environments through a combination of bacterial strain engineering and distributable hardware development. The transfer functions of 16 genetic switches, programmed to express a GFP reporter under the regulation of the (acyl-homoserine lactone) AHL-sensitive luxR transcriptional activator, can be parametrically tuned by adjusting high/low degrees of transcriptional, translational, and post-translational processing. Strains were optimized to facilitate daily large-scale preparation and reliable performance at room temperature in order to eliminate the need for temperature controlled apparatuses, which are both cost-limiting and space-constraining. The custom-designed, automated, and web-enabled fluorescence documentation system allows time-lapse imaging of AHL-induced GFP expression on bacterial plates with real-time remote data access, thereby requiring trainees to only be present for experimental setup. When coupled with mathematical models in agreement with empirical data, this toolbox expands the scalability and scope of reliable synthetic biology experiments for STEM training.

Proteolytic crosstalk in multi-protease networks

Processive proteases, such as ClpXP in E. coli, are conserved enzyme assemblies that can recognize and rapidly degrade proteins. These proteases are used for a number of purposes, including degrading mistranslated proteins and controlling cellular stress response. However, proteolytic machinery within the cell is limited in capacity and can lead to a bottleneck in protein degradation, whereby many proteins compete ('queue') for proteolytic resources. Previous work has demonstrated that such queueing can lead to pronounced statistical relationships between different protein counts when proteins compete for a single common protease. However, real cells contain many different proteases, e.g. ClpXP, ClpAP, and Lon in E. coli, and it is not clear how competition between proteins for multiple classes of protease would influence the dynamics of cellular networks. In the present work, we theoretically demonstrate that a multi-protease proteolytic bottleneck can substantially couple the dynamics for both simple and complex (oscillatory) networks, even between substrates with substantially different affinities for protease. For these networks, queueing often leads to strong positive correlations between protein counts, and these correlations are strongest near the queueing theoretic point of balance. Furthermore, we find that the qualitative behavior of these networks depends on the relative size of the absolute affinity of substrate to protease compared to the cross affinity of substrate to protease, leading in certain regimes to priority queue statistics.

Fluorescent Reporter Libraries as Useful Tools for Optimizing Microbial Cell Factories: A Review of the Current Methods and Applications

The use of genetically encoded fluorescent reporters allows speeding up the initial optimization steps of microbial bioprocesses. These reporters can be used for determining the expression level of a particular promoter, not only the synthesis of a specific protein but also the content of intracellular metabolites. The level of protein/metabolite is thus proportional to a fluorescence signal. By this way, mean expression profiles of protein/metabolites can be determined non-invasively at a high-throughput rate, allowing the rapid identification of the best producers. Actually, different kinds of reporter systems are available, as well as specific cultivation devices allowing the on-line recording of the fluorescent signal. Cell-to-cell variability is another important phenomenon that can be integrated into the screening procedures for the selection of more efficient microbial cell factories.

Natural LacI from E. coli yields faster response and higher level of expression than the LVA-tagged LacI

The lac promoter is one of the most commonly used promoters for expression control of recombinant genes in E. coli. In the absence of galactosides, the lac promoter is repressed by its repressor protein LacI. Since the lac promoter is regulated by a repressor, overexpression of LacI is necessary for regulation when the promoter is introduced on a high-copy plasmid. For that purpose, a modified variant of LacI, a LVA-tagged LacI, was submitted to the Registry of Standard Biological Parts and has been used for more than 500 constructs since then. We have found, however, that natural LacI is superior to the LVA-tagged LacI as controller of expression.

Principles of genetic circuit design

Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform tasks or create chemicals and materials that match the complexity seen in nature. This Review describes new tools that aid the construction of genetic circuits. Circuit dynamics can be influenced by the choice of regulators and changed with expression 'tuning knobs'. We collate the failure modes encountered when assembling circuits, quantify their impact on performance and review mitigation efforts. Finally, we discuss the constraints that arise from circuits having to operate within a living cell. Collectively, better tools, well-characterized parts and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.

Screening and identification of ClpE interaction proteins in Streptococcus pneumoniae by a bacterial two-hybrid system and co-immunoprecipitation

Hsp100/Clp proteins have crucial functions in the protein quality control, stress tolerance, and virulence of many pathogenic bacteria. ClpE is an important virulence factor involved in adherence and invasion in Streptococcus pneumoniae. To explore the underlying mechanism, we screened ClpE interaction proteins using a bacterial two-hybrid system and co-immunoprecipitation. We used ClpE as bait and constructed the pBT-ClpE bait plasmid for two-hybrid screening. Then, we constructed ClpE::GFP fusion for co-immunoprecipitation screening using anti-GFP monoclonal antibody. We obtained eight potential ClpE interaction proteins, including carbamoyl-phosphate synthase, pyruvate oxidase (SpxB), phosphoenolpyruvate-protein phosphotransferase, aminopeptidase N (pepN), L-lactate dehydrogenase, ribosomal protein S4, sensor histidine kinase (SPD_2019), and FtsW (a cell division protein). FtsW, SpxB, pepN, and SPD_2019 were confirmed to interact with ClpE using Bacterial Two-hybrid or Co-immunoprecipitation. Morphologic observations found that ΔclpE strain existed in abnormal division. β-Galactosidase activity assay suggested that ClpE contributed to the degradation of FtsW. Furthermore, FtsW could be induced by heat shock. The results suggested that ClpE might affect cell division by regulating the level of FtsW. These data may provide new insights in studying the role of ClpE in S. pneumoniae.

Retroactivity controls the temporal dynamics of gene transcription

Just like in many engineering systems, impedance-like effects, called retroactivity, arise at the interconnection of biomolecular circuits, leading to unexpected changes in a circuit's behavior. In this paper, we provide a combined experimental and theoretical study to characterize the effects of retroactivity on the temporal dynamics of a gene transcription module in vivo. The response of the module to an inducer was measured both in isolation and when the module was connected to downstream clients. The connected module, when compared to the isolated module, responded selectively to the introduction of the inducer versus its withdrawal. Specifically, a "sign-sensitive delay" appeared, in which the connected module displayed a time delay in the response to induction and anticipation in the response to de-induction. The extent of these effects can be made larger by increasing the amounts of downstream clients and/or their binding affinity to the output protein of the module. Our experimental results and mathematical formulas make it possible to predict the extent of the change in the dynamic behavior of a module after interconnection. They can be employed to both recover the predictive power of a modular approach to understand systems or as an additional design tool to shape the temporal behavior of gene transcription.

Tuning the dials of Synthetic Biology

Synthetic Biology is the ‘Engineering of Biology’ – it aims to use a forward-engineering design cycle based on specifications, modelling, analysis, experimental implementation, testing and validation to modify natural or design new, synthetic biology systems so that they behave in a predictable fashion. Motivated by the need for truly plug-and-play synthetic biological components, we present a comprehensive review of ways in which the various parts of a biological system can be modified systematically. In particular, we review the list of ‘dials’ that are available to the designer and discuss how they can be modelled, tuned and implemented. The dials are categorized according to whether they operate at the global, transcriptional, translational or post-translational level and the resolution that they operate at. We end this review with a discussion on the relative advantages and disadvantages of some dials over others.