Effects of Genetic Variation on the E. coli Host-Circuit Interface

GenoMine: a CRISPR-Cas9-based kill switch for biocontainment of Pseudomonas putida

Synthetic genetic circuits have revolutionised our capacity to control cell viability by conferring microorganisms with programmable functionalities to limit survival to specific environmental conditions. Here, we present the GenoMine safeguard, a CRISPR-Cas9-based kill switch for the biotechnological workhorse Pseudomonas putida that employs repetitive genomic elements as cleavage targets to unleash a highly genotoxic response. To regulate the system's activation, we tested various circuit-based mechanisms including the digitalised version of an inducible expression system that operates at the transcriptional level and different options of post-transcriptional riboregulators. All of them were applied not only to directly control Cas9 and its lethal effects, but also to modulate the expression of two of its inhibitors: the AcrIIA4 anti-CRISPR protein and the transcriptional repressor TetR. Either upon direct induction of the endonuclease or under non-induced conditions of its inhibitors, the presence of Cas9 suppressed cell survival which could be exploited beyond biocontainment in situations where further CRISPR genome editing is undesirable.

Transfer learning for cross-context prediction of protein expression from 5'UTR sequence

Model-guided DNA sequence design can accelerate the reprogramming of living cells. It allows us to engineer more complex biological systems by removing the need to physically assemble and test each potential design. While mechanistic models of gene expression have seen some success in supporting this goal, data-centric, deep learning-based approaches often provide more accurate predictions. This accuracy, however, comes at a cost - a lack of generalization across genetic and experimental contexts that has limited their wider use outside the context in which they were trained. Here, we address this issue by demonstrating how a simple transfer learning procedure can effectively tune a pre-trained deep learning model to predict protein translation rate from 5' untranslated region (5'UTR) sequence for diverse contexts in Escherichia coli using a small number of new measurements. This allows for important model features learnt from expensive massively parallel reporter assays to be easily transferred to new settings. By releasing our trained deep learning model and complementary calibration procedure, this study acts as a starting point for continually refined model-based sequence design that builds on previous knowledge and future experimental efforts.

Context-dependent redesign of robust synthetic gene circuits

Cells provide dynamic platforms for executing exogenous genetic programs in synthetic biology, resulting in highly context-dependent circuit performance. Recent years have seen an increasing interest in understanding the intricacies of circuit-host relationships, their influence on the synthetic bioengineering workflow, and in devising strategies to alleviate undesired effects. We provide an overview of how emerging circuit-host interactions, such as growth feedback and resource competition, impact both deterministic and stochastic circuit behaviors. We also emphasize control strategies for mitigating these unwanted effects. This review summarizes the latest advances and the current state of host-aware and resource-aware design of synthetic gene circuits.

Unveiling distinct genetic features in multidrug-resistant Escherichia coli isolated from mammary tissue and gut of mastitis induced mice

Escherichia coli is one of the major pathogens causing mastitis in lactating mammals. We hypothesized that E. coli from the gut and mammary glands may have similar genomic characteristics in the causation of mastitis. To test this hypothesis, we used whole genome sequencing to analyze two multidrug resistant E. coli strains isolated from mammary tissue (G2M6U) and fecal sample (G6M1F) of experimentally induced mastitis mice. Both strains showed resistance to multiple (>7) antibiotics such as oxacillin, aztreonam, nalidixic acid, streptomycin, gentamicin, cefoxitin, ampicillin, tetracycline, azithromycin and nitrofurantoin. The genome of E. coli G2M6U had 59 antimicrobial resistance genes (ARGs) and 159 virulence factor genes (VFGs), while the E. coli G6M1F genome possessed 77 ARGs and 178 VFGs. Both strains were found to be genetically related to many E. coli strains causing mastitis and enteric diseases originating from different hosts and regions. The G6M1F had several unique ARGs (e.g., QnrS1, sul2, tetA, tetR, emrK, blaTEM-1/105, and aph(6)-Id, aph(3″)-Ib) conferring resistance to certain antibiotics, whereas G2M6U had a unique heat-stable enterotoxin gene (astA) and 7192 single nucleotide polymorphisms. Furthermore, there were 43 and 111 unique genes identified in G2M6U and G6M1F genomes, respectively. These results indicate distinct differences in the genomic characteristics of E. coli strain G2M6U and G6M1F that might have important implications in the pathophysiology of mammalian mastitis, and treatment strategies for mastitis in dairy animals.

Design principles for synthetic control systems to engineer plants

KEY MESSAGE

Synthetic control systems have led to significant advancement in the study and engineering of unicellular organisms, but it has been challenging to apply these tools to multicellular organisms like plants. The ability to predictably engineer plants will enable the development of novel traits capable of alleviating global problems, such as climate change and food insecurity. Engineering predictable multicellular phenotypes will require the development of synthetic control systems that can precisely regulate how the information encoded in genomes is translated into phenotypes. Many efficient control systems have been developed for unicellular organisms. However, it remains challenging to use such tools to study or engineer multicellular organisms. Plants are a good chassis within which to develop strategies to overcome these challenges, thanks to their capacity to withstand large-scale reprogramming without lethality. Additionally, engineered plants have great potential for solving major societal problems. Here we briefly review the progress of control system development in unicellular organisms, and how that information can be leveraged to characterize control systems in plants. Further, we discuss strategies for developing control systems designed to regulate the expression of transgenes or endogenous loci and generate dosage-dependent or discrete traits. Finally, we discuss the utility that mathematical models of biological processes have for control system deployment.

Algorithmic Programming of Sequential Logic and Genetic Circuits for Recording Biochemical Concentration in a Probiotic Bacterium

Through the implementation of designable genetic circuits, engineered probiotic microorganisms could be used as noninvasive diagnostic tools for the gastrointestinal tract. For these living cells to report detected biomarkers or signals after exiting the gut, the genetic circuits must be able to record these signals by using genetically encoded memory. Complex memory register circuits could enable multiplex interrogation of biomarkers and signals. A theory-based approach to create genetic circuits containing memory, known as sequential logic circuits, was previously established for a model laboratory strain of Escherichia coli, yet how circuit component performance varies for nonmodel and clinically relevant bacterial strains is poorly understood. Here, we develop a scalable computational approach to design robust sequential logic circuits in probiotic strain Escherichia coli Nissle 1917 (EcN). In this work, we used TetR-family transcriptional repressors to build genetic logic gates that can be composed into sequential logic circuits, along with a set of engineered sensors relevant for use in the gut environment. Using standard methods, 16 genetic NOT gates and nine sensors were experimentally characterized in EcN. These data were used to design and predict the performance of circuit designs. We present a set of genetic circuits encoding both combinational logic and sequential logic and show that the circuit outputs are in close agreement with our quantitative predictions from the design algorithm. Furthermore, we demonstrate an analog-like concentration recording circuit that detects and reports three input concentration ranges of a biochemical signal using sequential logic.

Low concentration quaternary ammonium compounds promoted antibiotic resistance gene transfer via plasmid conjugation

During the pandemic of COVID-19, the amounts of quaternary ammonium compounds (QACs) used to inactivate the virus in public facilities, hospitals and households increased, which raised concerns about the evolution and transmission of antimicrobial resistance (AMR). Although QACs may play an important role in the propagation of antibiotic resistance gene (ARGs), the potential contribution and mechanism remains unclear. Here, the results showed that benzyl dodecyl dimethyl ammonium chloride (DDBAC) and didecyl dimethyl ammonium chloride (DDAC) significantly promoted plasmid RP4-mediated ARGs transfer within and across genera at environmental relevant concentrations (0.0004-0.4 mg/L). Low concentrations of QACs did not contribute to the permeability of the cell plasma membrane, but significantly increased the permeability of the cell outer membrane due to the decrease in content of lipopolysaccharides. QACs altered the composition and content of extracellular polymeric substances (EPS) and were positively correlated with the conjugation frequency. Furthermore, transcriptional expression levels of genes encode for mating pairing formation (trbB), DNA replication and translocation (trfA), and global regulators (korA, korB, trbA) are regulated by QACs. And we demonstrate for the first time that QACs decreased the concentration of extracellular AI-2 signals, which was verified to be involved in regulating conjugative transfer genes (trbB, trfA). Collectively, our findings underscore the risk of increased disinfectant concentrations of QACs on the ARGs transfer and provide new mechanisms of plasmid conjugation.

Modelling genetic stability in engineered cell populations

Predicting the evolution of engineered cell populations is a highly sought-after goal in biotechnology. While models of evolutionary dynamics are far from new, their application to synthetic systems is scarce where the vast combination of genetic parts and regulatory elements creates a unique challenge. To address this gap, we here-in present a framework that allows one to connect the DNA design of varied genetic devices with mutation spread in a growing cell population. Users can specify the functional parts of their system and the degree of mutation heterogeneity to explore, after which our model generates host-aware transition dynamics between different mutation phenotypes over time. We show how our framework can be used to generate insightful hypotheses across broad applications, from how a device's components can be tweaked to optimise long-term protein yield and genetic shelf life, to generating new design paradigms for gene regulatory networks that improve their functionality.

Parallel engineering of environmental bacteria and performance over years under jungle-simulated conditions

Engineered bacteria could perform many functions in the environment, for example, to remediate pollutants, deliver nutrients to crops or act as in-field biosensors. Model organisms can be unreliable in the field, but selecting an isolate from the thousands that naturally live there and genetically manipulating them to carry the desired function is a slow and uninformed process. Here, we demonstrate the parallel engineering of isolates from environmental samples by using the broad-host-range XPORT conjugation system (Bacillus subtilis mini-ICEBs1) to transfer a genetic payload to many isolates in parallel. Bacillus and Lysinibacillus species were obtained from seven soil and water samples from different locations in Israel. XPORT successfully transferred a genetic function (reporter expression) into 25 of these isolates. They were then screened to identify the best-performing chassis based on the expression level, doubling time, functional stability in soil, and environmentally-relevant traits of its closest annotated reference species, such as the ability to sporulate and temperature tolerance. From this library, we selected Bacillus frigoritolerans A3E1, re-introduced it to soil, and measured function and genetic stability in a contained environment that replicates jungle conditions. After 21 months of storage, the engineered bacteria were viable, could perform their function, and did not accumulate disruptive mutations.

Inducible plasmid copy number control for synthetic biology in commonly used E. coli strains

The ability to externally control gene expression has been paradigm shifting for all areas of biological research, especially for synthetic biology. Such control typically occurs at the transcriptional and translational level, while technologies enabling control at the DNA copy level are limited by either (i) relying on a handful of plasmids with fixed and arbitrary copy numbers; or (ii) require multiple plasmids for replication control; or (iii) are restricted to specialized strains. To overcome these limitations, we present TULIP (TUnable Ligand Inducible Plasmid): a self-contained plasmid with inducible copy number control, designed for portability across various Escherichia coli strains commonly used for cloning, protein expression, and metabolic engineering. Using TULIP, we demonstrate through multiple application examples that flexible plasmid copy number control accelerates the design and optimization of gene circuits, enables efficient probing of metabolic burden, and facilitates the prototyping and recycling of modules in different genetic contexts.

A Plasmid-Based Fluorescence Reporter System for Monitoring Oxidative Damage in E. coli

Quantitating intracellular oxidative damage caused by reactive oxygen species (ROS) is of interest in many fields of biological research. The current systems primarily rely on supplemented oxygen-sensitive substrates that penetrate the target cells, and react with ROS to produce signals that can be monitored with spectroscopic or imaging techniques. The objective here was to design a new non-invasive analytical strategy for measuring ROS-induced damage inside living cells by taking advantage of the native redox sensor system of E. coli. The developed plasmid-based sensor relies on an oxygen-sensitive transcriptional repressor IscR that controls the expression of a fluorescent marker in vivo. The system was shown to quantitatively respond to oxidative stress induced by supplemented H₂O₂ and lowered cultivation temperatures. Comparative analysis with fluorescence microscopy further demonstrated that the specificity of the reporter system was equivalent to the commercial chemical probe (CellROX). The strategy introduced here is not dependent on chemical probes, but instead uses a fluorescent expression system to detect enzyme-level oxidative damage in microbial cells. This provides a cheap and simple means for analysing enzyme-level oxidative damage in a biological context in E. coli.

Mitigating Host Burden of Genetic Circuits by Engineering Autonegatively Regulated Parts and Improving Functional Prediction

Mitigating unintended interferences between circuits and host cells is key to realize applications of synthetic regulatory systems both for bacteria and mammalian cells. Here, we demonstrated that growth burden and circuit dysregulation occurred in a concentration-dependent manner for specific transcription factors (CymR*/CymR) in E.coli, and direct negative feedback modules were able to control the concentration of CymR*/CymR, mitigate growth burden, and restore circuit functions. A quantitative design scheme was developed for circuits embedded with autorepression modules. Four key parameters were theoretically identified to determine the performance of autoregulated switches and were experimentally modified by fine-tuning promoter architectures and cooperativity. Using this strategy, we synthesized a number of switches and demonstrated its improvement of product titers and host growth controlling the complex deoxyviolacein biosynthesis pathway. Furthermore, we restored functions of a dysregulated multilayer NOR gate by integrating autorepression modules. Our work provides a blueprint for engineering host-adaptable synthetic systems.

Genomics Characterization of an Engineered Corynebacterium glutamicum in Bioreactor Cultivation Under Ionic Liquid Stress

Corynebacterium glutamicum is an ideal microbial chassis for production of valuable bioproducts including amino acids and next generation biofuels. Here we resequence engineered isopentenol (IP) producing C. glutamicum BRC-JBEI 1.1.2 strain and assess differential transcriptional profiles using RNA sequencing under industrially relevant conditions including scale transition and compare the presence vs absence of an ionic liquid, cholinium lysinate ([Ch][Lys]). Analysis of the scale transition from shake flask to bioreactor with transcriptomics identified a distinct pattern of metabolic and regulatory responses needed for growth in this industrial format. These differential changes in gene expression corroborate altered accumulation of organic acids and bioproducts, including succinate, acetate, and acetoin that occur when cells are grown in the presence of 50 mM [Ch][Lys] in the stirred-tank reactor. This new genome assembly and differential expression analysis of cells grown in a stirred tank bioreactor clarify the cell response of an C. glutamicum strain engineered to produce IP.

Algorithms for ribosome traffic engineering and their potential in improving host cells' titer and growth rate

mRNA translation is a fundamental cellular process consuming most of the intracellular energy; thus, it is under extensive evolutionary selection for optimization, and its efficiency can affect the host's growth rate. We describe a generic approach for improving the growth rate (fitness) of any organism by introducing synonymous mutations based on comprehensive computational models. The algorithms introduce silent mutations that may improve the allocation of ribosomes in the cells via the decreasing of their traffic jams during translation respectively. As a result, resources availability in the cell changes leading to improved growth-rate. We demonstrate experimentally the implementation of the method on Saccharomyces cerevisiae: we show that by introducing a few mutations in two computationally selected genes the mutant's titer increased. Our approach can be employed for improving the growth rate of any organism providing the existence of data for inferring models, and with the relevant genomic engineering tools; thus, it is expected to be extremely useful in biotechnology, medicine, and agriculture.

A novel knock out strategy to enhance recombinant protein expression in Escherichia coli

Background

The expression of recombinant proteins triggers a stress response which downregulates key metabolic pathway genes leading to a decline in cellular health and feedback inhibition of both growth and protein expression. Instead of individually upregulating these downregulated genes or improving transcription rates by better vector design, an innovative strategy would be to block this stress response thereby ensuring a sustained level of protein expression.

Results

We postulated that the genes which are commonly up-regulated post induction may play the role of signalling messengers in mounting the cellular stress response. We identified those genes which have no known downstream regulatees and created knock outs which were then tested for GFP expression. Many of these knock outs showed significantly higher expression levels which was also sustained for longer periods. The highest product yield (Y_p/x) was observed in a BW25113ΔcysJ knock out (Y_p/x 0.57) and BW25113ΔelaA (Y_p/x 0.49), whereas the Y_p/x of the control W3110 strain was 0.08 and BW25113 was 0.16. Double knock out combinations were then created from the ten best performing single knock outs leading to a further enhancement in expression levels. Out of 45 double knock outs created, BW25113ΔelaAΔyhbC (Y_p/x 0.7) and BW25113ΔcysJΔyhbC (Y_p/x 0.64) showed the highest increase in product yield compared to the single gene mutant strains. We confirmed the improved performance of these knock outs by testing and obtaining higher levels of recombinant asparaginase expression, a system better suited for analysing sustained expression since it gets exported to the extracellular medium.

Conclusion

Creating key knock outs to block the CSR and enhance expression is a radically different strategy that can be synergistically combined with traditional methods of improving protein yields thus helping in the design of superior host platforms for protein expression.

Cultivation at high osmotic pressure confers ubiquinone 8-independent protection of respiration on Escherichia coli

Ubiquinone 8 (coenzyme Q8 or Q8) mediates electron transfer within the aerobic respiratory chain, mitigates oxidative stress, and contributes to gene expression in Escherichia coli In addition, Q8 was proposed to confer bacterial osmotolerance by accumulating during growth at high osmotic pressure and altering membrane stability. The osmolyte trehalose and membrane lipid cardiolipin accumulate in E. coli cells cultivated at high osmotic pressure. Here, Q8 deficiency impaired E. coli growth at low osmotic pressure and rendered growth osmotically sensitive. The Q8 deficiency impeded cellular O₂ uptake and also inhibited the activities of two proton symporters, the osmosensing transporter ProP and the lactose transporter LacY. Q8 supplementation decreased membrane fluidity in liposomes, but did not affect ProP activity in proteoliposomes, which is respiration-independent. Liposomes and proteoliposomes prepared with E. coli lipids were used for these experiments. Similar oxygen uptake rates were observed for bacteria cultivated at low and high osmotic pressures. In contrast, respiration was dramatically inhibited when bacteria grown at the same low osmotic pressure were shifted to high osmotic pressure. Thus, respiration was restored during prolonged growth of E. coli at high osmotic pressure. Of note, bacteria cultivated at low and high osmotic pressures had similar Q8 concentrations. The protection of respiration was neither diminished by cardiolipin deficiency nor conferred by trehalose overproduction during growth at low osmotic pressure, but rather might be achieved by Q8-independent respiratory chain remodeling. We conclude that osmotolerance is conferred through Q8-independent protection of respiration, not by altering physical properties of the membrane.

Construction of Two-Input Logic Gates Using Transcriptional Interference

Transcriptional interference (TI) has been shown to regulate gene expression at the DNA level via different molecular mechanisms. The obstacles present on the DNA that a transcribing RNA polymerase might encounter, for example, a DNA-bound protein or another RNA polymerase, can result in TI causing termination of transcription, thus reducing gene expression. However, the potential of TI as a new strategy to engineer complex gene expression modules has not been fully explored yet. Here we created a series of two-input genetic devices that use the presence of a roadblocking protein to control gene expression and analyzed their behaviors using both experimental and mathematical modeling approaches. We explored how multiple characteristics affect the response of genetic devices engineered to act like either AND, OR, or single input logic gates. We show that the dissociation constant of the roadblocking protein, inducer activation of promoter and operator sites, and distance between tandem promoters tune gate behavior. This work highlights the potential of rationally creating different types of genetic responses using the same transcription factors in subtly different genetic architectures.

Trade-offs between gene expression, growth and phenotypic diversity in microbial populations

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Limitations in molecular resources for gene expression influence bacterial physiology.

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Bacteria optimise trade-offs between resource allocation and growth.

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Resource allocation plays a role in the emergence of phenotypic heterogeneity.

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Trade-offs between bet-hedging and growth can be harnessed in biotechnology.

Bacterial cells have a limited number of resources that can be allocated for gene expression. The intracellular competition for these resources has an impact on the cell physiology. Bacteria have evolved mechanisms to optimize resource allocation in a variety of scenarios, showing a trade-off between the resources used to maximise growth (e.g. ribosome synthesis) and the rest of cellular functions. Limitations in gene expression also play a role in generating phenotypic diversity, which is advantageous in fluctuating environments, at the expenses of decreasing growth rates. Our current understanding of these trade-offs can be exploited for biotechnological applications benefiting from the selective manipulation of the allocation of resources.

Construction and characterization of broad-host-range reporter plasmid suitable for on-line analysis of bacterial host responses related to recombinant protein production

BACKGROUND

Bacteria are widely used as hosts for recombinant protein production due to their rapid growth, simple media requirement and ability to produce high yields of correctly folded proteins. Overproduction of recombinant proteins may impose metabolic burden to host cells, triggering various stress responses, and the ability of the cells to cope with such stresses is an important factor affecting both cell growth and product yield.

RESULTS

Here, we present a versatile plasmid-based reporter system for efficient analysis of metabolic responses associated with availability of cellular resources utilized for recombinant protein production and host capacity to synthesize correctly folded proteins. The reporter plasmid is based on the broad-host range RK2 minimal replicon and harbors the strong and inducible XylS/Pm regulator/promoter system, the ppGpp-regulated ribosomal protein promoter PrpsJ, and the σ32-dependent synthetic tandem promoter Pibpfxs, each controlling expression of one distinguishable fluorescent protein. We characterized the responsiveness of all three reporters in Escherichia coli by quantitative fluorescence measurements in cell cultures cultivated under different growth and stress conditions. We also validated the broad-host range application potential of the reporter plasmid by using Pseudomonas putida and Azotobacter vinelandii as hosts.

CONCLUSIONS

The plasmid-based reporter system can be used for analysis of the total inducible recombinant protein production, the translational capacity measured as transcription level of ribosomal protein genes and the heat shock-like response revealing aberrant protein folding in all studied Gram-negative bacterial strains.

Absolute quantification of translational regulation and burden using combined sequencing approaches

Translation of mRNAs into proteins is a key cellular process. Ribosome binding sites and stop codons provide signals to initiate and terminate translation, while stable secondary mRNA structures can induce translational recoding events. Fluorescent proteins are commonly used to characterize such elements but require the modification of a part's natural context and allow only a few parameters to be monitored concurrently. Here, we combine Ribo-seq with quantitative RNA-seq to measure at nucleotide resolution and in absolute units the performance of elements controlling transcriptional and translational processes during protein synthesis. We simultaneously measure 779 translation initiation rates and 750 translation termination efficiencies across the Escherichia coli transcriptome, in addition to translational frameshifting induced at a stable RNA pseudoknot structure. By analyzing the transcriptional and translational response, we discover that sequestered ribosomes at the pseudoknot contribute to a σ32-mediated stress response, codon-specific pausing, and a drop in translation initiation rates across the cell. Our work demonstrates the power of integrating global approaches toward a comprehensive and quantitative understanding of gene regulation and burden in living cells.

Improving Reproducibility in Synthetic Biology

Synthetic biology holds great promise to deliver transformative technologies to the world in the coming years. However, several challenges still remain to be addressed before it can deliver on its promises. One of the most important issues to address is the lack of reproducibility within research of the life sciences. This problem is beginning to be recognised by the community and solutions are being developed to tackle the problem. The recent emergence of automated facilities that are open for use by researchers (such as biofoundries and cloud labs) may be one of the ways that synthetic biologists can improve the quality and reproducibility of their work. In this perspective article, we outline these and some of the other technologies that are currently being developed which we believe may help to transform how synthetic biologists approach their research activities.

Designing Spatially Distributed Gene Regulatory Networks To Elicit Contrasting Patterns

Pattern formation and differential interactions are important for microbial consortia to divide labor and perform complex functions. To obtain further insight into such interactions, we present a computational method for simulating physically separated microbial colonies, each implementing different gene regulatory networks. We validate our theory by experimentally demonstrating control over gene expression patterns in a diffusion-mediated lateral inhibition circuit. We highlight the importance of spatial arrangement as a control knob for modulating system behavior. Our systematic approach provides a foundation for future applications that require understanding and engineering of multistrain microbial communities for sophisticated, synergistic functions.

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.

Engineered integrative and conjugative elements for efficient and inducible DNA transfer to undomesticated bacteria

Engineering microorganisms to promote human or plant health will require manipulation of robust bacteria that are capable of surviving in harsh, competitive environments. Genetic engineering of undomesticated bacteria can be limited by an inability to transfer DNA into the cell. Here we developed an approach based on the integrative and conjugative element from Bacillus subtilis (ICEBs1) to overcome this problem. A donor strain (XPORT) was built to transfer miniaturized integrative and conjugative elements (mini-ICEBs1) to undomesticated bacteria. The strain was engineered to enable inducible control over conjugation, to integrate delivered DNA into the chromosome of the recipient, to restrict spread of heterologous DNA through separation of the type IV secretion system from the transferred DNA, and to enable simple isolation of engineered bacteria through a D-alanine auxotrophy. Efficient DNA transfer (10^-1 to 10^-7 conjugation events per donor) is demonstrated using 35 Gram-positive strains isolated from humans (skin and gut) and soil. Mini-ICEBs1 was used to rapidly characterize the performance of an isopropyl-β-D-thiogalactoside (IPTG)-inducible reporter across dozens of strains and to transfer nitrogen fixation to four Bacillus species. Finally, XPORT was introduced to soil to demonstrate DNA transfer under non-ideal conditions.

Cell-free prediction of protein expression costs for growing cells

Translating heterologous proteins places significant burden on host cells, consuming expression resources leading to slower cell growth and productivity. Yet predicting the cost of protein production for any given gene is a major challenge, as multiple processes and factors combine to determine translation efficiency. To enable prediction of the cost of gene expression in bacteria, we describe here a standard cell-free lysate assay that provides a relative measure of resource consumption when a protein coding sequence is expressed. These lysate measurements can then be used with a computational model of translation to predict the in vivo burden placed on growing E. coli cells for a variety of proteins of different functions and lengths. Using this approach, we can predict the burden of expressing multigene operons of different designs and differentiate between the fraction of burden related to gene expression compared to action of a metabolic pathway.

Combining a Toggle Switch and a Repressilator within the AC-DC Circuit Generates Distinct Dynamical Behaviors

Although the structure of a genetically encoded regulatory circuit is an important determinant of its function, the relationship between circuit topology and the dynamical behaviors it can exhibit is not well understood. Here, we explore the range of behaviors available to the AC-DC circuit. This circuit consists of three genes connected as a combination of a toggle switch and a repressilator. Using dynamical systems theory, we show that the AC-DC circuit exhibits both oscillations and bistability within the same region of parameter space; this generates emergent behaviors not available to either the toggle switch or the repressilator alone. The AC-DC circuit can switch on oscillations via two distinct mechanisms, one of which induces coherence into ensembles of oscillators. In addition, we show that in the presence of noise, the AC-DC circuit can behave as an excitable system capable of spatial signal propagation or coherence resonance. Together, these results demonstrate how combinations of simple motifs can exhibit multiple complex behaviors.

Orthogonality and Burdens of Heterologous AND Gate Gene Circuits in E. coli

Synthetic biology approaches commonly introduce heterologous gene networks into a host to predictably program cells, with the expectation of the synthetic network being orthogonal to the host background. However, introduced circuits may interfere with the host’s physiology, either indirectly by posing a metabolic burden and/or through unintended direct interactions between parts of the circuit with those of the host, affecting functionality. Here we used RNA-Seq transcriptome analysis to quantify the interactions between a representative heterologous AND gate circuit and the host Escherichia coli under various conditions including circuit designs and plasmid copy numbers. We show that the circuit plasmid copy number outweighs circuit composition for their effect on host gene expression with medium-copy number plasmid showing more prominent interference than its low-copy number counterpart. In contrast, the circuits have a stronger influence on the host growth with a metabolic load increasing with the copy number of the circuits. Notably, we show that variation of copy number, an increase from low to medium copy, caused different types of change observed in the behavior of components in the AND gate circuit leading to the unbalance of the two gate-inputs and thus counterintuitive output attenuation. The study demonstrates the circuit plasmid copy number is a key factor that can dramatically affect the orthogonality, burden and functionality of the heterologous circuits in the host chassis. The results provide important guidance for future efforts to design orthogonal and robust gene circuits with minimal unwanted interaction and burden to their host.

Genome-wide analysis of E. coli cell-gene interactions

BACKGROUND

The pursuit of standardization and reliability in synthetic biology has achieved, in recent years, a number of advances in the design of more predictable genetic parts for biological circuits. However, even with the development of high-throughput screening methods and whole-cell models, it is still not possible to predict reliably how a synthetic genetic construct interacts with all cellular endogenous systems. This study presents a genome-wide analysis of how the expression of synthetic genes is affected by systematic perturbations of cellular functions. We found that most perturbations modulate expression indirectly through an effect on cell size, putting forward the existence of a generic Size-Expression interaction in the model prokaryote Escherichia coli.

RESULTS

The Size-Expression interaction was quantified by inserting a dual fluorescent reporter gene construct into each of the 3822 single-gene deletion strains comprised in the KEIO collection. Cellular size was measured for single cells via flow cytometry. Regression analyses were used to discriminate between expression-specific and gene-specific effects. Functions of the deleted genes broadly mapped onto three systems with distinct primary influence on the Size-Expression map. Perturbations in the Division and Biosynthesis (DB) system led to a large-cell and high-expression phenotype. In contrast, disruptions of the Membrane and Motility (MM) system caused small-cell and low-expression phenotypes. The Energy, Protein synthesis and Ribosome (EPR) system was predominantly associated with smaller cells and positive feedback on ribosome function.

CONCLUSIONS

Feedback between cell growth and gene expression is widespread across cell systems. Even though most gene disruptions proximally affect one component of the Size-Expression interaction, the effect therefore ultimately propagates to both. More specifically, we describe the dual impact of growth on cell size and gene expression through cell division and ribosomal content. Finally, we elucidate aspects of the tight control between swarming, gene expression and cell growth. This work provides foundations for a systematic understanding of feedbacks between genetic and physiological systems.

Genetic circuit characterization and debugging using RNA-seq

Genetic circuits implement computational operations within a cell. Debugging them is difficult because their function is defined by multiple states (e.g., combinations of inputs) that vary in time. Here, we develop RNA‐seq methods that enable the simultaneous measurement of: (i) the states of internal gates, (ii) part performance (promoters, insulators, terminators), and (iii) impact on host gene expression. This is applied to a three‐input one‐output circuit consisting of three sensors, five NOR/NOT gates, and 46 genetic parts. Transcription profiles are obtained for all eight combinations of inputs, from which biophysical models can extract part activities and the response functions of sensors and gates. Various unexpected failure modes are identified, including cryptic antisense promoters, terminator failure, and a sensor malfunction due to media‐induced changes in host gene expression. This can guide the selection of new parts to fix these problems, which we demonstrate by using a bidirectional terminator to disrupt observed antisense transcription. This work introduces RNA‐seq as a powerful method for circuit characterization and debugging that overcomes the limitations of fluorescent reporters and scales to large systems composed of many parts.

Synthetic Gene Expression Circuits for Designing Precision Tools in Oncology

Precision medicine in oncology needs to enhance its capabilities to match diagnostic and therapeutic technologies to individual patients. Synthetic biology streamlines the design and construction of functionalized devices through standardization and rational engineering of basic biological elements decoupled from their natural context. Remarkable improvements have opened the prospects for the availability of synthetic devices of enhanced mechanism clarity, robustness, sensitivity, as well as scalability and portability, which might bring new capabilities in precision cancer medicine implementations. In this review, we begin by presenting a brief overview of some of the major advances in the engineering of synthetic genetic circuits aimed to the control of gene expression and operating at the transcriptional, post-transcriptional/translational, and post-translational levels. We then focus on engineering synthetic circuits as an enabling methodology for the successful establishment of precision technologies in oncology. We describe significant advancements in our capabilities to tailor synthetic genetic circuits to specific applications in tumor diagnosis, tumor cell- and gene-based therapy, and drug delivery.

Host-aware modelling of a synthetic genetic oscillator

Synthetic genetic circuits sometimes exhibit unexpected functionality or even fail entirely when implemented in vivo, due to the effects of interactions with the host cell that were not accounted for in the circuit's design. In this paper, we consider the effects that limitations in cellular resources have on the dynamics of a synthetic cellular oscillator. We show that incorporating these effects into a host-aware model of the synthetic oscillator results in significant changes in its dynamics, highlighting the need to take account of host-circuit interactions in mathematical models that are to be used as CAD tools for synthetic circuitry.

Engineering bacterial translation initiation - Do we have all the tools we need?

BACKGROUND

Reliable tools that allow precise and predictable control over gene expression are critical for the success of nearly all bioengineering applications. Translation initiation is the most regulated phase during protein biosynthesis, and is therefore a promising target for exerting control over gene expression. At the translational level, the copy number of a protein can be fine-tuned by altering the interaction between the translation initiation region of an mRNA and the ribosome. These interactions can be controlled by modulating the mRNA structure using numerous approaches, including small molecule ligands, RNAs, or RNA-binding proteins. A variety of naturally occurring regulatory elements have been repurposed, facilitating advances in synthetic gene regulation strategies. The pursuit of a comprehensive understanding of mechanisms governing translation initiation provides the framework for future engineering efforts.

SCOPE OF REVIEW

Here we outline state-of-the-art strategies used to predictably control translation initiation in bacteria. We also discuss current limitations in the field and future goals.

MAJOR CONCLUSIONS

Due to its function as the rate-determining step, initiation is the ideal point to exert effective translation regulation. Several engineering tools are currently available to rationally design the initiation characteristics of synthetic mRNAs. However, improvements are required to increase the predictability, effectiveness, and portability of these tools.

GENERAL SIGNIFICANCE

Predictable and reliable control over translation initiation will allow greater predictability when designing, constructing, and testing genetic circuits. The ability to build more complex circuits predictably will advance synthetic biology and contribute to our fundamental understanding of the underlying principles of these processes. "This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue.

Overloaded and stressed: whole-cell considerations for bacterial synthetic biology

The predictability and robustness of engineered bacteria depend on the many interactions between synthetic constructs and their host cells. Expression from synthetic constructs is an unnatural load for the host that typically reduces growth, triggers stresses and leads to decrease in performance or failure of engineered cells. Work in systems and synthetic biology has now begun to address this through new tools, methods and strategies that characterise and exploit host-construct interactions in bacteria. Focusing on work in E. coli, we review here a selection of the recent developments in this area, highlighting the emerging issues and describing the new solutions that are now making the synthetic biology community consider the cell just as much as they consider the construct.

Genetic circuit design automation

Computation can be performed in living cells by DNA-encoded circuits that process sensory information and control biological functions. Their construction is time-intensive, requiring manual part assembly and balancing of regulator expression. We describe a design environment, Cello, in which a user writes Verilog code that is automatically transformed into a DNA sequence. Algorithms build a circuit diagram, assign and connect gates, and simulate performance. Reliable circuit design requires the insulation of gates from genetic context, so that they function identically when used in different circuits. We used Cello to design 60 circuits forEscherichia coli(880,000 base pairs of DNA), for which each DNA sequence was built as predicted by the software with no additional tuning. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts), and across all circuits 92% of the output states functioned as predicted. Design automation simplifies the incorporation of genetic circuits into biotechnology projects that require decision-making, control, sensing, or spatial organization.

From noise to synthetic nucleoli: can synthetic biology achieve new insights?

Synthetic biology aims to re-organise and control biological components to make functional devices. Along the way, the iterative process of designing and testing gene circuits has the potential to yield many insights into the functioning of the underlying chassis of cells. Thus, synthetic biology is converging with disciplines such as systems biology and even classical cell biology, to give a new level of predictability to gene expression, cell metabolism and cellular signalling networks. This review gives an overview of the contributions that synthetic biology has made in understanding gene expression, in terms of cell heterogeneity (noise), the coupling of growth and energy usage to expression, and spatiotemporal considerations. We mainly compare progress in bacterial and mammalian systems, which have some of the most-developed engineering frameworks. Overall, one view of synthetic biology can be neatly summarised as "creating in order to understand."

SBOL Visual: A Graphical Language for Genetic Designs

Synthetic Biology Open Language (SBOL) Visual is a graphical standard for genetic engineering. It consists of symbols representing DNA subsequences, including regulatory elements and DNA assembly features. These symbols can be used to draw illustrations for communication and instruction, and as image assets for computer-aided design. SBOL Visual is a community standard, freely available for personal, academic, and commercial use (Creative Commons CC0 license). We provide prototypical symbol images that have been used in scientific publications and software tools. We encourage users to use and modify them freely, and to join the SBOL Visual community: http://www.sbolstandard.org/visual.

Algorithmic co-optimization of genetic constructs and growth conditions: application to 6-ACA, a potential nylon-6 precursor

Optimizing bio-production involves strain and process improvements performed as discrete steps. However, environment impacts genotype and a strain that is optimal under one set of conditions may not be under different conditions. We present a methodology to simultaneously vary genetic and process factors, so that both can be guided by design of experiments (DOE). Advances in DNA assembly and gene insulation facilitate this approach by accelerating multi-gene pathway construction and the statistical interpretation of screening data. This is applied to a 6-aminocaproic acid (6-ACA) pathway in Escherichia coli consisting of six heterologous enzymes. A 32-member fraction factorial library is designed that simultaneously perturbs expression and media composition. This is compared to a 64-member full factorial library just varying expression (0.64 Mb of DNA assembly). Statistical analysis of the screening data from these libraries leads to different predictions as to whether the expression of enzymes needs to increase or decrease. Therefore, if genotype and media were varied separately this would lead to a suboptimal combination. This is applied to the design of a strain and media composition that increases 6-ACA from 9 to 48 mg/l in a single optimization step. This work introduces a generalizable platform to co-optimize genetic and non-genetic factors.

Emergent dynamics from quorum eavesdropping

Numerous bacterial species utilize quorum sensing to communicate, but crosstalk often complicates the dynamics of mixed populations. In this issue of Chemistry & Biology, Wu and colleagues take advantage of synthetic gene circuits to elucidate interactions between two quorum sensing systems, with potential applications to fields from infectious diseases to biosynthesis.

Layering genetic circuits to build a single cell, bacterial half adder

BACKGROUND

Gene regulation in biological systems is impacted by the cellular and genetic context-dependent effects of the biological parts which comprise the circuit. Here, we have sought to elucidate the limitations of engineering biology from an architectural point of view, with the aim of compiling a set of engineering solutions for overcoming failure modes during the development of complex, synthetic genetic circuits.

RESULTS

Using a synthetic biology approach that is supported by computational modelling and rigorous characterisation, AND, OR and NOT biological logic gates were layered in both parallel and serial arrangements to generate a repertoire of Boolean operations that include NIMPLY, XOR, half adder and half subtractor logics in a single cell. Subsequent evaluation of these near-digital biological systems revealed critical design pitfalls that triggered genetic context-dependent effects, including 5' UTR interferences and uncontrolled switch-on behaviour of the supercoiled σ54 promoter. In particular, the presence of seven consecutive hairpins immediately downstream of the promoter transcription start site severely impeded gene expression.

CONCLUSIONS

As synthetic biology moves forward with greater focus on scaling the complexity of engineered genetic circuits, studies which thoroughly evaluate failure modes and engineering solutions will serve as important references for future design and development of synthetic biological systems. This work describes a representative case study for the debugging of genetic context-dependent effects through principles elucidated herein, thereby providing a rational design framework to integrate multiple genetic circuits in a single prokaryotic cell.

Quantifying cellular capacity identifies gene expression designs with reduced burden

Heterologous gene expression can be a significant burden for cells. Here we describe an in vivo monitor that tracks changes in the capacity of Escherichia coli in real time and can be used to assay the burden imposed by synthetic constructs and their parts. We identify construct designs with reduced burden that predictably outperformed less efficient designs, despite having equivalent output.

Design and implementation of a biomolecular concentration tracker

As a field, synthetic biology strives to engineer increasingly complex artificial systems in living cells. Active feedback in closed loop systems offers a dynamic and adaptive way to ensure constant relative activity independent of intrinsic and extrinsic noise. In this work, we use synthetic protein scaffolds as a modular and tunable mechanism for concentration tracking through negative feedback. Input to the circuit initiates scaffold production, leading to colocalization of a two-component system and resulting in the production of an inhibitory antiscaffold protein. Using a combination of modeling and experimental work, we show that the biomolecular concentration tracker circuit achieves dynamic protein concentration tracking in Escherichia coli and that steady state outputs can be tuned.

How to train your microbe: methods for dynamically characterizing gene networks

Gene networks regulate biological processes dynamically. However, researchers have largely relied upon static perturbations, such as growth media variations and gene knockouts, to elucidate gene network structure and function. Thus, much of the regulation on the path from DNA to phenotype remains poorly understood. Recent studies have utilized improved genetic tools, hardware, and computational control strategies to generate precise temporal perturbations outside and inside of live cells. These experiments have, in turn, provided new insights into the organizing principles of biology. Here, we introduce the major classes of dynamical perturbations that can be used to study gene networks, and discuss technologies available for creating them in a wide range of microbial pathways.

Inducible suppression of global translation by overuse of rare codons

Recently, artificial gene networks have been developed in synthetic biology to control gene expression and make organisms as controllable as robots. Here, I present an artificial posttranslational gene-silencing system based on the codon usage bias and low tRNA content corresponding to minor codons. I engineered the green fluorescent protein (GFP) gene to inhibit translation indirectly with the lowest-usage codons to monopolize various minor tRNAs (lgfp). The expression of lgfp interfered nonspecifically with the growth of Escherichia coli, Saccharomyces cerevisiae, human HeLa cervical cancer cells, MCF7 breast cancer cells, and HEK293 kidney cells, as well as phage and adenovirus expansion. Furthermore, insertion of lgfp downstream of a phage response promoter conferred phage resistance on E. coli. Such engineered gene silencers could act as components of biological networks capable of functioning with suitable promoters in E. coli, S. cerevisiae, and human cells to control gene expression. The results presented here show general suppressor artificial genes for live cells and viruses. This robust system provides a gene expression or cell growth control device for artificially synthesized gene networks.