Towards high-value chemicals production harnessing synthetic biology

We aim to design and construct organisms with new functionalities of unprecedented scope, by exploiting synthetic biology for metabolic engineering; e.g. by harnessing our ability to readily sequence complete genomes and to rewrite/re-design pathways on a large scale. We explore these possibilities in the context of high-value chemical production, utilising the Design/Build/Test/Learn cycle at the Parts, Devices and Systems level. Many microorganisms already have the machinery to produce diverse bioactive molecules that can be used in health, agriculture and food (Cimermancic et al., Cell 2014). As a first step towards re-engineering these high-value chemical biosynthesis pathways for enhanced productivity and diversity, we aim to understand the interchangeability of biosynthetic parts (Diez et al., ACS Synth Biol 2015) and created a minimal information database for natural products with the support from the natural products community (Medema et al., Nature Chem. Biol. 2015). We have designed and assembled pathways using the identified parts (Leferink et al., ChemistrySELECT 2016) and will engineer orthogonal transcription mechanisms (based on signalling molecule circuits (Biarnes-Carrera et al., Curr. Opin. Chem. Biol. 2015) and bacterial microcompartments (Chessher et al., ACS Biomater. Sci. Eng. 2015). In addition, we are expanding our collection of computational tools for the detection and analysis of secondary metabolite biosynthesis gene clusters, to enrich our library of parts and building blocks for pathway engineering (Weber et al., Nucl. Acids Res. 2015). We also use computational modelling (constraint-based descriptions of bacterial metabolism) to identify suitable overproduction hosts and pinpoint biosynthetic bottlenecks to target for further cellular engineering in a synthetic biology strategy (Breitling et al., ACS Synth. Biol. 2013). And finally, we combine this analysis with high-resolution mass spectrometry analysis, which we also employ for the debugging of the engineered systems (Jankevics et al., Metabolomics 2012). We have these tools in the Design/Build/Test/Learn cycle of the recently established BBSRC/EPSRC-funded Manchester Synthetic Biology Research Centre, SYNBIOCHEM, where they provide a platform for the high-throughput engineering of fine and speciality chemicals production in microbial systems

Metabolic modeling and analysis of the metabolic switch in Streptomyces coelicolor

Background The transition from exponential to stationary phase in Streptomyces coelicolor is accompanied by a major metabolic switch and results in a strong activation of secondary metabolism. Here we have explored the underlying reorganization of the metabolome by combining computational predictions based on constraint-based modeling and detailed transcriptomics time course observations. Results We reconstructed the stoichiometric matrix of S. coelicolor, including the major antibiotic biosynthesis pathways, and performed flux balance analysis to predict flux changes that occur when the cell switches from biomass to antibiotic production. We defined the model input based on observed fermenter culture data and used a dynamically varying objective function to represent the metabolic switch. The predicted fluxes of many genes show highly significant correlation to the time series of the corresponding gene expression data. Individual mispredictions identify novel links between antibiotic production and primary metabolism. Conclusion Our results show the usefulness of constraint-based modeling for providing a detailed interpretation of time course gene expression data

The effect of terminal globular domains on the response of recombinant mini-spidroins to fiber spinning triggers

From Springer Nature via Jisc Publications RouterHistory: received 2020-02-04, accepted 2020-06-11, registration 2020-06-15, pub-electronic 2020-06-30, online 2020-06-30, collection 2020-12Publication status: PublishedFunder: Defence Science and Technology Laboratory; doi: http://dx.doi.org/10.13039/100010418; Grant(s): DSTLX1000101893, DSTLX1000101893, DSTLX1000101893, DSTLX1000101893, DSTLX1000101893Funder: Engineering and Physical Sciences Research Council; doi: http://dx.doi.org/10.13039/501100000266; Grant(s): EP/L014904/1Funder: Biotechnology and Biological Sciences Research Council; doi: http://dx.doi.org/10.13039/501100000268; Grant(s): BB/M017702/1, BB/M017702/1, BB/M017702/1Abstract: Spider silk spidroins consist of long repetitive protein strands, flanked by globular terminal domains. The globular domains are often omitted in recombinant spidroins, but are thought to be essential for the spiders’ natural spinning process. Mimicking this spinning process could be an essential step towards producing strong synthetic spider silk. Here we describe the production of a range of mini-spidroins with both terminal domains, and characterize their response to a number of biomimetic spinning triggers. Our results suggest that mini-spidroins which are able to form protein micelles due to the addition of both terminal domains exhibit shear-thinning, a property which native spidroins also show. Furthermore, our data also suggest that a pH drop alone is insufficient to trigger assembly in a wet-spinning process, and must be combined with salting-out for effective fiber formation. With these insights, we applied these assembly triggers for relatively biomimetic wet spinning. This work adds to the foundation of literature for developing improved biomimetic spinning techniques, which ought to result in synthetic silk that more closely approximates the unique properties of native spider silk

Design and fabrication of recombinant reflectin-based multilayer reflectors: bio-design engineering and photoisomerism induced wavelength modulation

From Springer Nature via Jisc Publications RouterHistory: received 2020-10-03, accepted 2021-06-18, registration 2021-07-07, pub-electronic 2021-07-16, online 2021-07-16, collection 2021-12Publication status: PublishedFunder: Defence Science and Technology Laboratory; doi: http://dx.doi.org/10.13039/100010418Funder: Engineering and Physical Sciences Research Council; doi: http://dx.doi.org/10.13039/501100000266; Grant(s): EP/S01778X/1, EP/S01778X/1, EP/S01778X/1Abstract: The remarkable camouflage capabilities of cephalopods have inspired many to develop dynamic optical materials which exploit certain design principles and/or material properties from cephalopod dermal cells. Here, the angle-dependent optical properties of various single-layer reflectin thin-films on Si wafers are characterized within the UV–Vis–NIR regions. Following this, initial efforts to design, fabricate, and optically characterize a bio-inspired reflectin-based multilayer reflector is described, which was found to conserve the optical properties of single layer films but exhibit reduced angle-dependent visible reflectivity. Finally, we report the integration of phytochrome visible light-induced isomerism into reflectin-based films, which was found to subtly modulate reflectin thin-film reflectivity

The Sequence of a 1.8-Mb Bacterial Linear Plasmid Reveals a Rich Evolutionary Reservoir of Secondary Metabolic Pathways

Plasmids are mobile genetic elements that play a key role in the evolution of bacteria by mediating genome plasticity and lateral transfer of useful genetic information. Although originally considered to be exclusively circular, linear plasmids have also been identified in certain bacterial phyla, notably the actinomycetes. In some cases, linear plasmids engage with chromosomes in an intricate evolutionary interplay, facilitating the emergence of new genome configurations by transfer and recombination or plasmid integration. Genome sequencing of Streptomyces clavuligerus ATCC 27064, a Gram-positive soil bacterium known for its production of a diverse array of biotechnologically important secondary metabolites, revealed a giant linear plasmid of 1.8 Mb in length. This megaplasmid (pSCL4) is one of the largest plasmids ever identified and the largest linear plasmid to be sequenced. It contains more than 20% of the putative protein-coding genes of the species, but none of these is predicted to be essential for primary metabolism. Instead, the plasmid is densely packed with an exceptionally large number of gene clusters for the potential production of secondary metabolites, including a large number of putative antibiotics, such as staurosporine, moenomycin, β-lactams, and enediynes. Interestingly, cross-regulation occurs between chromosomal and plasmid-encoded genes. Several factors suggest that the megaplasmid came into existence through recombination of a smaller plasmid with the arms of the main chromosome. Phylogenetic analysis indicates that heavy traffic of genetic information between Streptomyces plasmids and chromosomes may facilitate the rapid evolution of secondary metabolite repertoires in these bacteria

Prioritizing orphan proteins for further study using phylogenomics and gene expression profiles in Streptomyces coelicolor

BACKGROUND:Streptomyces coelicolor, a model organism of antibiotic producing bacteria, has one of the largest genomes of the bacterial kingdom, including 7825 predicted protein coding genes. A large number of these genes, nearly 34%, are functionally orphan (hypothetical proteins with unknown function). However, in gene expression time course data, many of these functionally orphan genes show interesting expression patterns.RESULTS:In this paper, we analyzed all functionally orphan genes of Streptomyces coelicolor and identified a list of "high priority" orphans by combining gene expression analysis and additional phylogenetic information (i.e. the level of evolutionary conservation of each protein).CONCLUSIONS:The prioritized orphan genes are promising candidates to be examined experimentally in the lab for further characterization of their functio

Separating the wheat from the chaff: a prioritisation pipeline for the analysis of metabolomics datasets

Liquid Chromatography Mass Spectrometry (LC-MS) is a powerful and widely applied method for the study of biological systems, biomarker discovery and pharmacological interventions. LC-MS measurements are, however, significantly complicated by several technical challenges, including: (1) ionisation suppression/enhancement, disturbing the correct quantification of analytes, and (2) the detection of large amounts of separate derivative ions, increasing the complexity of the spectra, but not their information content. Here we introduce an experimental and analytical strategy that leads to robust metabolome profiles in the face of these challenges. Our method is based on rigorous filtering of the measured signals based on a series of sample dilutions. Such data sets have the additional characteristic that they allow a more robust assessment of detection signal quality for each metabolite. Using our method, almost 80% of the recorded signals can be discarded as uninformative, while important information is retained. As a consequence, we obtain a broader understanding of the information content of our analyses and a better assessment of the metabolites detected in the analyzed data sets. We illustrate the applicability of this method using standard mixtures, as well as cell extracts from bacterial samples. It is evident that this method can be applied in many types of LC-MS analyses and more specifically in untargeted metabolomics