Engineering microbial phenotypes through rewiring of genetic networks.

The ability to program cellular behaviour is a major goal of synthetic biology, with applications in health, agriculture and chemicals production. Despite efforts to build 'orthogonal' systems, interactions between engineered genetic circuits and the endogenous regulatory network of a host cell can have a significant impact on desired functionality. We have developed a strategy to rewire the endogenous cellular regulatory network of yeast to enhance compatibility with synthetic protein and metabolite production. We found that introducing novel connections in the cellular regulatory network enabled us to increase the production of heterologous proteins and metabolites. This strategy is demonstrated in yeast strains that show significantly enhanced heterologous protein expression and higher titers of terpenoid production. Specifically, we found that the addition of transcriptional regulation between free radical induced signalling and nitrogen regulation provided robust improvement of protein production. Assessment of rewired networks revealed the importance of key topological features such as high betweenness centrality. The generation of rewired transcriptional networks, selection for specific phenotypes, and analysis of resulting library members is a powerful tool for engineering cellular behavior and may enable improved integration of heterologous protein and metabolite pathways.

A tool for rapid, automated characterization of population epigenomics in plants.

Epigenetic variation in plant populations is an important factor in determining phenotype and adaptation to the environment. However, while advances have been made in the molecular and computational methods to analyze the methylation status of a given sample of DNA, tools to profile and compare the methylomes of multiple individual plants or groups of plants at high resolution and low cost are lacking. Here, we describe a computational approach and R package (sounDMR) that leverages the benefits of long read nanopore sequencing to enable robust identification of differential methylation from complex experimental designs, as well as assess the variability within treatment groups and identify individual plants of interest. We demonstrate the utility of this approach by profiling a population of Arabidopsis thaliana exposed to a demethylating agent and identify genomic regions of high epigenetic variability between individuals. Given the low cost of nanopore sequencing devices and the ease of sample preparation, these results show that high resolution epigenetic profiling of plant populations can be made more broadly accessible in plant breeding and biotechnology.

Grand challenge commentary: Transforming biosynthesis into an information science.

Engineering biosynthetic pathways to natural products is a challenging endeavor that promises to provide new therapeutics and tools to manipulate biology. Information-guided design strategies and tools could unlock the creativity of a wide spectrum of scientists and engineers by decoupling expertise from implementation.

Building synthetic systems to learn nature's design principles.

Evolution undoubtedly shapes the architecture of biological systems, yet it is unclear which features of regulatory, metabolic, and signalling circuits have adaptive significance and how the architecture of these circuits constrains or promotes evolutionary processes, such as adaptation to new environments. Experimentally rewiring circuits using genetic engineering and constructing novel circuits in living cells allows direct testing and validation of hypotheses in evolutionary systems biology. Building synthetic genetic systems enables researchers to explore regions of the genotype-phenotype and fitness landscapes that may be inaccessible to more traditional analysis. Here, we review the strategies that allow synthetic systems to be constructed and how evolutionary design principles have advanced these technologies. We also describe how building small genetic regulatory systems can provide insight on the trade-offs that constrain adaptation and can shape the structure of biological networks. In the future, the possibility of building biology de novo at the genome scale means that increasingly sophisticated models of the evolutionary dynamics of networks can be proposed and validated, and will allow us to recreate ancestral systems in the lab. This interplay between evolutionary systems theory and engineering design may illuminate the fundamental limits of performance, robustness, and evolvability of living systems.

Synthesis of methyl halides from biomass using engineered microbes.

Methyl halides are used as agricultural fumigants and are precursor molecules that can be catalytically converted to chemicals and fuels. Plants and microorganisms naturally produce methyl halides, but these organisms produce very low yields or are not amenable to industrial production. A single methyl halide transferase (MHT) enzyme transfers the methyl group from the ubiquitous metabolite S-adenoyl methionine (SAM) to a halide ion. Using a synthetic metagenomic approach, we chemically synthesized all 89 putative MHT genes from plants, fungi, bacteria, and unidentified organisms present in the NCBI sequence database. The set was screened in Escherichia coli to identify the rates of CH(3)Cl, CH(3)Br, and CH(3)I production, with 56% of the library active on chloride, 85% on bromide, and 69% on iodide. Expression of the highest activity MHT and subsequent engineering in Saccharomyces cerevisiae results in productivity of 190 mg/L-h from glucose and sucrose. Using a symbiotic co-culture of the engineered yeast and the cellulolytic bacterium Actinotalea fermentans, we are able to achieve methyl halide production from unprocessed switchgrass (Panicum virgatum), corn stover, sugar cane bagasse, and poplar (Populus sp.). These results demonstrate the potential of producing methyl halides from non-food agricultural resources.

Model-guided design of ligand-regulated RNAi for programmable control of gene expression.

Progress in constructing biological networks will rely on the development of more advanced components that can be predictably modified to yield optimal system performance. We have engineered an RNA-based platform, which we call an shRNA switch, that provides for integrated ligand control of RNA interference (RNAi) by modular coupling of an aptamer, competing strand, and small hairpin (sh)RNA stem into a single component that links ligand concentration and target gene expression levels. A combined experimental and mathematical modelling approach identified multiple tuning strategies and moves towards a predictable framework for the forward design of shRNA switches. The utility of our platform is highlighted by the demonstration of fine-tuning, multi-input control, and model-guided design of shRNA switches with an optimized dynamic range. Thus, shRNA switches can serve as an advanced component for the construction of complex biological systems and offer a controlled means of activating RNAi in disease therapeutics.

Programmable ligand-controlled riboregulators of eukaryotic gene expression.

Recent studies have demonstrated the importance of noncoding RNA elements in regulating gene expression networks. We describe the design of a class of small trans-acting RNAs that directly regulate gene expression in a ligand-dependent manner. These allosteric riboregulators, which we call antiswitches, are made fully tunable and modular by rational design. They offer flexible control strategies by adopting active or inactive forms in response to ligand binding, depending on their design. They can be tailor-made to regulate the expression of target transcripts in response to different cellular effectors. Coupled with in vitro selection technologies for generating nucleic acid ligand-binding species, antiswitches present a platform for programming cellular behavior and genetic networks with respect to cellular state and environmental stimuli.

Automated selection of aptamers against protein targets translated in vitro: from gene to aptamer.

Reagents for proteome research must of necessity be generated by high throughput methods. Aptamers are potentially useful as reagents to identify and quantitate individual proteins, yet are currently produced for the most part by manual selection procedures. We have developed automated selection methods, but must still individually purify protein targets. Therefore, we have attempted to select aptamers against protein targets generated by in vitro transcription and translation of individual genes. In order to specifically immobilize the protein targets for selection, they are also biotinylated in vitro. As a proof of this method, we have selected aptamers against translated human U1A, a component of the nuclear spliceosome. Selected sequences demonstrated exquisite mimicry of natural binding sequences and structures. These results not only reveal a potential path to the high throughput generation of aptamers, but also yield insights into the incredible specificity of the U1A protein for its natural RNA ligands.

Automated acquisition of aptamer sequences.

While the in vitro selection of nucleic acid binding species (aptamers) requires numerous liquid-handling steps, these steps are relatively straightforward and the overall process is therefore amenable to automation. Here we demonstrate that automated selection techniques are capable of generating aptamers against a number of diverse protein targets. Automated selection techniques can be integrated with automated analytical methods, including sequencing, determination of binding constants, and structural analysis. The methods that have so far been developed can be further multiplexed, and it should soon be possible to attempt the selection of aptamers against organismal proteomes or metabolomes.

One-Step Isothermal Assembly of DNA fragments.

The One-Step Isothermal DNA Assembly method allows for the efficient assembly of DNA constructs using fragments up to several hundred kilobases in as little as 15 min. Applications of this method range from the addition of promoters to expression constructs to the assembly of bacterial genome fragments. The production of circularized DNA using this method also enables the direct transformation of target organisms, bypassing intermediate transformations for plasmid propagation in those species where expression could lead to toxicity and cell death. Variations of the method allow for specific cloning tasks to be performed, as well as the use of microarray slides as a source of DNA. The level of precision and simplicity of this method makes it a valuable tool for most cloning efforts and all levels of proficiency in molecular biology.

Programming microbes using pulse width modulation of optical signals.

Cells transmit and receive information via signalling pathways. A number of studies have revealed that information is encoded in the temporal dynamics of these pathways and has highlighted how pathway architecture can influence the propagation of signals in time and space. The functional properties of pathway architecture can also be exploited by synthetic biologists to enable precise control of cellular physiology. Here, we characterised the response of a bacterial light-responsive, two-component system to oscillating signals of varying frequencies. We found that the system acted as a low-pass filter, able to respond to low-frequency oscillations and unable to respond to high-frequency oscillations. We then demonstrate that the low-pass filtering behavior can be exploited to enable precise control of gene expression using a strategy termed pulse width modulation (PWM). PWM is a common strategy used in electronics for information encoding that converts a series of digital input signals to an analog response. We further show how the PWM strategy extends the utility of bacterial optogenetic control, allowing the fine-tuning of expression levels, programming of temporal dynamics, and control of microbial physiology via manipulation of a metabolic enzyme.

Engineering microbial consortia to enhance biomining and bioremediation.

In natural environments microorganisms commonly exist as communities of multiple species that are capable of performing more varied and complicated tasks than clonal populations. Synthetic biologists have engineered clonal populations with characteristics such as differentiation, memory, and pattern formation, which are usually associated with more complex multicellular organisms. The prospect of designing microbial communities has alluring possibilities for environmental, biomedical, and energy applications, and is likely to reveal insight into how natural microbial consortia function. Cell signaling and communication pathways between different species are likely to be key processes for designing novel functions in synthetic and natural consortia. Recent efforts to engineer synthetic microbial interactions will be reviewed here, with particular emphasis given to research with significance for industrial applications in the field of biomining and bioremediation of acid mine drainage.

Using synthetic biology to understand the evolution of gene expression.

The evolution of phenotype is often based on changes in gene expression rather than changes in protein-coding sequence. Gene expression is controlled by complex networks of interacting regulators that act through a variety of biochemical mechanisms. Perturbation of these networks can have profound effects on the fitness of organisms. This highlights an important challenge: the investigation of whether the mechanisms and network architectures we observe in Nature evolved in response to selective pressure--and, if so, what that pressure might have been--or whether the architectures are a result of non-adaptive forces. Synthetic biologists aim to construct artificial genetic and biological systems to increase our understanding of Nature as well as for a number of biotechnological applications. In this review, I will highlight how engineering 'synthetic' control of gene expression provides a way to test evolutionary hypotheses. Synthetic biology might allow us to investigate experimentally the evolutionary paths not taken by extant organisms.

Synthetic control of a fitness tradeoff in yeast nitrogen metabolism.

BACKGROUND: Microbial communities are involved in many processes relevant to industrial and medical biotechnology, such as the formation of biofilms, lignocellulosic degradation, and hydrogen production. The manipulation of synthetic and natural microbial communities and their underlying ecological parameters, such as fitness, evolvability, and variation, is an increasingly important area of research for synthetic biology. RESULTS: Here, we explored how synthetic control of an endogenous circuit can be used to regulate a tradeoff between fitness in resource abundant and resource limited environments in a population of Saccharomyces cerevisiae. We found that noise in the expression of a key enzyme in ammonia assimilation, Gdh1p, mediated a tradeoff between growth in low nitrogen environments and stress resistance in high ammonia environments. We implemented synthetic control of an endogenous Gdh1p regulatory network to construct an engineered strain in which the fitness of the population was tunable in response to an exogenously-added small molecule across a range of ammonia environments. CONCLUSION: The ability to tune fitness and biological tradeoffs will be important components of future efforts to engineer microbial communities.

Engineering stochasticity in gene expression.

Stochastic fluctuations (noise) in gene expression can cause members of otherwise genetically identical populations to display drastically different phenotypes. An understanding of the sources of noise and the strategies cells employ to function reliably despite noise is proving to be increasingly important in describing the behavior of natural organisms and will be essential for the engineering of synthetic biological systems. Here we describe the design of synthetic constructs, termed ribosome competing RNAs (rcRNAs), as a means to rationally perturb noise in cellular gene expression. We find that noise in gene expression increases in a manner proportional to the ability of an rcRNA to compete for the cellular ribosome pool. We then demonstrate that operons significantly buffer noise between coexpressed genes in a natural cellular background and can even reduce the level of rcRNA enhanced noise. These results demonstrate that synthetic genetic constructs can significantly affect the noise profile of a living cell and, importantly, that operons are a facile genetic strategy for buffering against noise.

Arginine-rich motifs present multiple interfaces for specific binding by RNA.

A number of proteins containing arginine-rich motifs (ARMs) are known to bind RNA and are involved in regulating RNA processing in viruses and cells. Using automated selection methods we have generated a number of aptamers against ARM peptides from various natural proteins. Aptamers bind tightly to their cognate ARMs, with K(d) values in the nanomolar range, and frequently show no propensity to bind to other ARMs or even to single amino acid variants of the cognate ARM. However, at least some anti-ARM aptamers can cross-recognize a limited set of other ARMs, just as natural RNA-binding sites have been shown to exhibit so-called "chameleonism." We expand upon the number of examples of cross-recognition and, using mutational and circular dichroism (CD) analyses, demonstrate that there are multiple mechanisms by which RNA ligands can cross-recognize ARMs. These studies support a model in which individual arginine residues govern binding to an RNA ligand, and the inherent flexibility of the peptide backbone may make it possible for "semi-specific" recognition of a discrete set of RNAs by a discrete set of ARM peptides and proteins.