Fine-tuning gene networks using simple sequence repeats

Digital switching in a biosensor circuit via programmable timing of gene availability

Transient delivery of gene circuits is required in many potential applications of synthetic biology, yet pre-steady-state processes that dominate this delivery route pose significant challenges for robust circuit deployment. Here we show that site-specific recombinases can rectify undesired effects by programmable timing of gene availability in multi-gene circuits. We exemplify the concept with a proportional sensor for endogenous microRNA and show dramatic reduction in its ground state leakage thanks to desynchronization of circuit’s repressor components and their repression target. The new sensors display dynamic range of up to 1000-fold compared to 20-fold in the standard configuration. We applied the approach to classify cell types based on miRNA expression profile and measured > 200-fold output differential between positively- and negatively-identified cells. We also showed major improvement of specificity with cytotoxic output. Our study opens new venues in gene circuit design via judicious temporal control of circuits’ genetic makeup.

Improving fatty acids production by engineering dynamic pathway regulation and metabolic control

Global energy demand and environmental concerns have stimulated increasing efforts to produce carbon-neutral fuels directly from renewable resources. Microbially derived aliphatic hydrocarbons, the petroleum-replica fuels, have emerged as promising alternatives to meet this goal. However, engineering metabolic pathways with high productivity and yield requires dynamic redistribution of cellular resources and optimal control of pathway expression. Here we report a genetically encoded metabolic switch that enables dynamic regulation of fatty acids (FA) biosynthesis in Escherichia coli. The engineered strains were able to dynamically compensate the critical enzymes involved in the supply and consumption of malonyl-CoA and efficiently redirect carbon flux toward FA biosynthesis. Implementation of this metabolic control resulted in an oscillatory malonyl-CoA pattern and a balanced metabolism between cell growth and product formation, yielding 15.7- and 2.1-fold improvement in FA titer compared with the wild-type strain and the strain carrying the uncontrolled metabolic pathway. This study provides a new paradigm in metabolic engineering to control and optimize metabolic pathways facilitating the high-yield production of other malonyl-CoA-derived compounds.

Engineering modular and tunable genetic amplifiers for scaling transcriptional signals in cascaded gene networks

Synthetic biology aims to control and reprogram signal processing pathways within living cells so as to realize repurposed, beneficial applications. Here we report the design and construction of a set of modular and gain-tunable genetic amplifiers in Escherichia coli capable of amplifying a transcriptional signal with wide tunable-gain control in cascaded gene networks. The devices are engineered using orthogonal genetic components (hrpRS, hrpV and P_hrpL) from the hrp (hypersensitive response and pathogenicity) gene regulatory network in Pseudomonas syringae. The amplifiers can linearly scale up to 21-fold the transcriptional input with a large output dynamic range, yet not introducing significant time delay or significant noise during signal amplification. The set of genetic amplifiers achieves different gains and input dynamic ranges by varying the expression levels of the underlying ligand-free activator proteins in the device. As their electronic counterparts, these engineered transcriptional amplifiers can act as fundamental building blocks in the design of biological systems by predictably and dynamically modulating transcriptional signal flows to implement advanced intra- and extra-cellular control functions.

Accurate, model-based tuning of synthetic gene expression using introns in S. cerevisiae

Introns are key regulators of eukaryotic gene expression and present a potentially powerful tool for the design of synthetic eukaryotic gene expression systems. However, intronic control over gene expression is governed by a multitude of complex, incompletely understood, regulatory mechanisms. Despite this lack of detailed mechanistic understanding, here we show how a relatively simple model enables accurate and predictable tuning of synthetic gene expression system in yeast using several predictive intron features such as transcript folding and sequence motifs. Using only natural Saccharomyces cerevisiae introns as regulators, we demonstrate fine and accurate control over gene expression spanning a 100 fold expression range. These results broaden the engineering toolbox of synthetic gene expression systems and provide a framework in which precise and robust tuning of gene expression is accomplished.

Synthetic biology is gradually expanding our capability to engineer biology through rational genetic engineering of synthetic gene expression systems. These developments are already paving the way for the accelerated study of biology and applying engineered biological systems to major environmental and health problems. However, our capacity to intelligently modify and control gene expression depends on our ability to apply a broad range of genetic regulators in the engineering process. Here we show that Introns, pivotal regulators of Eukaryotic gene expression, can be rationally engineered to control a synthetic gene expression system of a Eukaryote. We developed a unique reporter-based system to evaluate the effects of engineering splicing in synthetic biology and show that the entire intron repertoire of S. cerevisiae can be accurately used to rationally engineer gene expression. Our results provide both a proof-of-concept for the integration of splicing into synthetic biology designs and a model that can be used by the scientific community for integrating splicing into their own designs. Following the extensive use of transcriptional (promoter) and translational (UTR) elements in synthetic constructs, our results introduce a new major regulatory system, splicing, that can be used to rationally engineer genetic systems.

Engineering reduced evolutionary potential for synthetic biology

The field of synthetic biology seeks to engineer reliable and predictable behaviors in organisms from collections of standardized genetic parts. However, unlike other types of machines, genetically encoded biological systems are prone to changes in their designed sequences due to mutations in their DNA sequences after these devices are constructed and deployed. Thus, biological engineering efforts can be confounded by undesired evolution that rapidly breaks the functions of parts and systems, particularly when they are costly to the host cell to maintain. Here, we explain the fundamental properties that determine the evolvability of biological systems. Then, we use this framework to review current efforts to engineer the DNA sequences that encode synthetic biology devices and the genomes of their microbial hosts to reduce their ability to evolve and therefore increase their genetic reliability so that they maintain their intended functions over longer timescales.

Whole-cell biocatalysis for selective and productive C-O functional group introduction and modification

During the last decades, biocatalysis became of increasing importance for chemical and pharmaceutical industries. Regarding regio- and stereospecificity, enzymes have shown to be superior compared to traditional chemical synthesis approaches, especially in C-O functional group chemistry. Catalysts established on a process level are diverse and can be classified along a functional continuum starting with single-step biotransformations using isolated enzymes or microbial strains towards fermentative processes with recombinant microorganisms containing artificial synthetic pathways. The complex organization of respective enzymes combined with aspects such as cofactor dependency and low stability in isolated form often favors the use of whole cells over that of isolated enzymes. Based on an inventory of the large spectrum of biocatalytic C-O functional group chemistry, this review focuses on highlighting the potentials, limitations, and solutions offered by the application of self-regenerating microbial cells as biocatalysts. Different cellular functionalities are discussed in the light of their (possible) contribution to catalyst efficiency. The combined achievements in the areas of protein, genetic, metabolic, and reaction engineering enable the development of whole-cell biocatalysts as powerful tools in organic synthesis.

j5 DNA assembly design automation

Modern standardized methodologies, described in detail in the previous chapters of this book, have enabled the software-automated design of optimized DNA construction protocols. This chapter describes how to design (combinatorial) scar-less DNA assembly protocols using the web-based software j5. j5 assists biomedical and biotechnological researchers construct DNA by automating the design of optimized protocols for flanking homology sequence as well as type IIS endonuclease-mediated DNA assembly methodologies. Unlike any other software tool available today, j5 designs scar-less combinatorial DNA assembly protocols, performs a cost-benefit analysis to identify which portions of an assembly process would be less expensive to outsource to a DNA synthesis service provider, and designs hierarchical DNA assembly strategies to mitigate anticipated poor assembly junction sequence performance. Software integrated with j5 add significant value to the j5 design process through graphical user-interface enhancement and downstream liquid-handling robotic laboratory automation.

A wise consistency: engineering biology for conformity, reliability, predictability

The next generation of synthetic biology applications will increasingly involve engineered organisms that exist in intimate contact with humans, animals and the rest of the environment. Examples include cellular and viral approaches for maintaining and improving health in humans and animals. The need for reliable and specific function in these environments may require more complex system designs than previously. In these cases the uncertainties in the behavior of biological building blocks, their hosts and their environments present a challenge for design of predictable and safe systems. Here, we review systematic methods for the effective characterization of these uncertainties that are lowering the barriers to predictive design of reliable complex biological systems.

Multiplex iterative plasmid engineering for combinatorial optimization of metabolic pathways and diversification of protein coding sequences

Engineering complex biological systems typically requires combinatorial optimization to achieve the desired functionality. Here, we present Multiplex Iterative Plasmid Engineering (MIPE), which is a highly efficient and customized method for combinatorial diversification of plasmid sequences. MIPE exploits ssDNA mediated λ Red recombineering for the introduction of mutations, allowing it to target several sites simultaneously and generate libraries of up to 10(7) sequences in one reaction. We also describe "restriction digestion mediated co-selection (RD CoS)", which enables MIPE to produce enhanced recombineering efficiencies with greatly simplified coselection procedures. To demonstrate this approach, we applied MIPE to fine-tune gene expression level in the 5-gene riboflavin biosynthetic pathway and successfully isolated a clone with 2.67-fold improved production in less than a week. We further demonstrated the ability of MIPE for highly multiplexed diversification of protein coding sequence by simultaneously targeting 23 codons scattered along the 750 bp sequence. We anticipate this method to benefit the optimization of diverse biological systems in synthetic biology and metabolic engineering.

Translation rate is controlled by coupled trade-offs between site accessibility, selective RNA unfolding and sliding at upstream standby sites

The ribosome's interactions with mRNA govern its translation rate and the effects of post-transcriptional regulation. Long, structured 5' untranslated regions (5' UTRs) are commonly found in bacterial mRNAs, though the physical mechanisms that determine how the ribosome binds these upstream regions remain poorly defined. Here, we systematically investigate the ribosome's interactions with structured standby sites, upstream of Shine-Dalgarno sequences, and show that these interactions can modulate translation initiation rates by over 100-fold. We find that an mRNA's translation initiation rate is controlled by the amount of single-stranded surface area, the partial unfolding of RNA structures to minimize the ribosome's binding free energy penalty, the absence of cooperative binding and the potential for ribosomal sliding. We develop a biophysical model employing thermodynamic first principles and a four-parameter free energy model to accurately predict the ribosome's translation initiation rates for 136 synthetic 5' UTRs with large structures, diverse shapes and multiple standby site modules. The model predicts and experiments confirm that the ribosome can readily bind distant standby site modules that support high translation rates, providing a physical mechanism for observed context effects and long-range post-transcriptional regulation.

Tuning response curves for synthetic biology

Synthetic biology may be viewed as an effort to establish, formalize, and develop an engineering discipline in the context of biological systems. The ability to tune the properties of individual components is central to the process of system design in all fields of engineering, and synthetic biology is no exception. A large and growing number of approaches have been developed for tuning the responses of cellular systems, and here we address specifically the issue of tuning the rate of response of a system: given a system where an input affects the rate of change of an output, how can the shape of the response curve be altered experimentally? This affects a system's dynamics as well as its steady-state properties, both of which are critical in the design of systems in synthetic biology, particularly those with multiple components. We begin by reviewing a mathematical formulation that captures a broad class of biological response curves and use this to define a standard set of varieties of tuning: vertical shifting, horizontal scaling, and the like. We then survey the experimental literature, classifying the results into our defined categories, and organizing them by regulatory level: transcriptional, post-transcriptional, and post-translational.

Randomized BioBrick assembly: a novel DNA assembly method for randomizing and optimizing genetic circuits and metabolic pathways

The optimization of genetic circuits and metabolic pathways often involves constructing various iterations of the same construct or using directed evolution to achieve the desired function. Alternatively, a method that randomizes individual parts in the same assembly reaction could be used for optimization by allowing for the ability to screen large numbers of individual clones expressing randomized circuits or pathways for optimal function. Here we describe a new assembly method to randomize genetic circuits and metabolic pathways from modular DNA fragments derived from PCR-amplified BioBricks. As a proof-of-principle for this method, we successfully assembled CMY (Cyan-Magenta-Yellow) three-gene circuits using Gibson Assembly that express CFP, RFP, and YFP with independently randomized promoters, ribosome binding sites, transcriptional terminators, and all parts randomized simultaneously. Sequencing results from 24 CMY circuits with various parts randomized show that 20/24 circuits are distinct and expression varies over a 200-fold range above background levels. We then adapted this method to randomize the same parts with enzyme coding sequences from the lycopene biosynthesis pathway instead of fluorescent proteins, designed to independently express each enzyme in the pathway from a different promoter. Lycopene production is improved using this randomization method by about 30% relative to the highest polycistronic-expressing pathway. These results demonstrate the potential of generating nearly 20,000 unique circuit or pathway combinations when three parts are permutated at each position in a three-gene circuit or pathway, and the methodology can likely be adapted to other circuits and pathways to maximize products of interest.

Visualization of evolutionary stability dynamics and competitive fitness of Escherichia coli engineered with randomized multigene circuits

Strain engineering for synthetic biology and metabolic engineering applications often requires the expression of foreign proteins that can reduce cellular fitness. In order to quantify and visualize the evolutionary stability dynamics in engineered populations of Escherichia coli , we constructed randomized CMY (cyan-magenta-yellow) genetic circuits with independently randomized promoters, ribosome binding sites, and transcriptional terminators that express cyan fluorescent protein (CFP), red fluorescent protein (RFP), and yellow fluorescent protein (YFP). Using a CMY color system allows for a spectrum of different colors to be produced under UV light since the relative ratio of fluorescent proteins vary between circuits, and this system can be used for the visualization of evolutionary stability dynamics. Evolutionary stability results from 192 evolved populations (24 CMY circuits with 8 replicates each) indicate that both the number of repeated sequences and overall expression levels contribute to circuit stability. The most evolutionarily robust circuit has no repeated parts, lower expression levels, and is about 3-fold more stable relative to a rationally designed circuit. Visualization results show that evolutionary dynamics are highly stochastic between replicate evolved populations and color changes over evolutionary time are consistent with quantitative data. We also measured the competitive fitness of different mutants in an evolved population and find that fitness is highest in mutants that express a lower number of genes (0 and 1 > 2 > 3). In addition, we find that individual circuits with expression levels below 10% of the maximum have significantly higher evolutionary stability, suggesting there may be a hypothetical "fitness threshold" that can be used for robust circuit design.

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.

Synthetic biology: advancing the design of diverse genetic systems

A major objective of synthetic biology is to make the process of designing genetically encoded biological systems more systematic, predictable, robust, scalable, and efficient. Examples of genetic systems in the field vary widely in terms of operating hosts, compositional approaches, and network complexity, ranging from simple genetic switches to search-and-destroy systems. While significant advances in DNA synthesis capabilities support the construction of pathway- and genome-scale programs, several design challenges currently restrict the scale of systems that can be reasonably designed and implemented. Thus, while synthetic biology offers much promise in developing systems to address challenges faced in the fields of manufacturing, environment and sustainability, and health and medicine, the realization of this potential is currently limited by the diversity of available parts and effective design frameworks. As researchers make progress in bridging this design gap, advances in the field hint at ever more diverse applications for biological systems.