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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.