SignificanceNonmodel bacteria have essential roles to play in the future development of biotechnology by providing new sources of biocatalysts, antibiotics, hosts for bioproduction, and engineered “living therapies.” The characterization of such hosts can be challenging, as many are not tractable to standard molecular biology techniques. This paper presents a rapid and automated methodology for characterizing new DNA parts from a nonmodel bacterium using cell-free transcription–translation. Data analysis was performed with Bayesian parameter inference to provide an understanding of gene-expression dynamics and resource sharing. We suggest that our integrated approach is expandable to a whole range of nonmodel bacteria for the characterization of new DNA parts within a native cell-free background for new biotechnology applications.

Cell-free transcription-translation systems were originally applied towards in vitro protein production. More recently, synthetic biology is enabling these systems to be used within a systematic design context for prototyping DNA regulatory elements, genetic logic circuits and biosynthetic pathways. The Gram-positive soil bacterium, Bacillus subtilis, is an established model organism of industrial importance. To this end, we developed several B. subtilis-based cell-free systems. Our improved B. subtilis WB800N-based system was capable of producing 0.8µM GFP, which gave a ~72x fold-improvement when compared with a B. subtilis 168 cell-free system. Our improved system was applied towards the prototyping of a B. subtilis promoter library in which we engineered several promoters, derived from the wild-type P (σA) promoter, that display a range of comparable in vitro and in vivo transcriptional activities. Additionally, we demonstrate the cell-free characterisation of an inducible expression system, and the activity of a model enzyme - renilla luciferase.

We used a protein structure prediction method to generate a variety of folds as alpha-carbon models with realistic secondary structures and good hydrophobic packing. The prediction method used only idealized constructs that are not based on known protein structures or fragments of them, producing an unbiased distribution. Model and native fold comparison used a topology-based method as superposition can only be relied on in similar structures. When all the models were compared to a nonredundant set of all known structures, only one-in-ten were found to have a match. This large excess of novel folds was associated with each protein probe and if true in general, implies that the space of possible folds is larger than the space of realized folds, in much the same way that sequence-space is larger than fold-space. The large excess of novel folds exhibited no unusual properties and has been likened to cosmological dark matter.

Overlap-directed DNA assembly methods allow multiple DNA parts to be assembled together in one reaction. These methods, which rely on sequence homology between the ends of DNA parts, have become widely adopted in synthetic biology, despite being incompatible with a key principle of engineering: modularity. To answer this, we present MODAL: a Modular Overlap-Directed Assembly with Linkers strategy that brings modularity to overlap-directed methods, allowing assembly of an initial set of DNA parts into a variety of arrangements in one-pot reactions. MODAL is accompanied by a custom software tool that designs overlap linkers to guide assembly, allowing parts to be assembled in any specified order and orientation. The in silico design of synthetic orthogonal overlapping junctions allows for much greater efficiency in DNA assembly for a variety of different methods compared with using non-designed sequence. In tests with three different assembly technologies, the MODAL strategy gives assembly of both yeast and bacterial plasmids, composed of up to five DNA parts in the kilobase range with efficiencies of between 75 and 100%. It also seamlessly allows mutagenesis to be performed on any specified DNA parts during the process, allowing the one-step creation of construct libraries valuable for synthetic biology applications.

Plants are a tremendous source of diverse chemicals, including many natural product-derived drugs. It has recently become apparent that the genes for the biosynthesis of numerous different types of plant natural products are organized as metabolic gene clusters, thereby unveiling a highly unusual form of plant genome architecture and offering novel avenues for discovery and exploitation of plant specialized metabolism. Here we show that these clustered pathways are characterized by distinct chromatin signatures of histone 3 lysine trimethylation (H3K27me3) and histone 2 variant H2A.Z, associated with cluster repression and activation, respectively, and represent discrete windows of co-regulation in the genome. We further demonstrate that knowledge of these chromatin signatures along with chromatin mutants can be used to mine genomes for cluster discovery. The roles of H3K27me3 and H2A.Z in repression and activation of single genes in plants are well known. However, our discovery of highly localized operon-like co-regulated regions of chromatin modification is unprecedented in plants. Our findings raise intriguing parallels with groups of physically linked multi-gene complexes in animals and with clustered pathways for specialized metabolism in filamentous fungi.