Microbial production of the plant flavanone hesperetin from caffeic acid

OBJECTIVE

Hesperetin is an important O-methylated flavonoid produced by citrus fruits and of potential pharmaceutical relevance. The microbial biosynthesis of hesperetin could be a viable alternative to plant extraction, as plant extracts often yield complex mixtures of different flavonoids making it challenging to isolate pure compounds. In this study, hesperetin was produced from caffeic acid in the microbial host Escherichia coli. We combined a previously optimised pathway for the biosynthesis of the intermediate flavanone eriodictyol with a combinatorial library of plasmids expressing three candidate flavonoid O-methyltransferases. Moreover, we endeavoured to improve the position specificity of CCoAOMT7, a flavonoid O-methyltransferase from Arabidopsis thaliana that has been demonstrated to O-methylate eriodictyol in both the para- and meta-position, thus leading to a mixture of hesperetin and homoeriodictyol.

RESULTS

The best performing flavonoid O-methyltransferase in our screen was found to be CCoAOMT7, which could produce up to 14.6 mg/L hesperetin and 3.8 mg/L homoeriodictyol from 3 mM caffeic acid in E. coli 5-alpha. Using a platform for enzyme engineering that scans the mutational space of selected key positions, predicting their structures using homology modelling and inferring their potential catalytic improvement using docking simulations, we were able to identify a CCoAOMT7 mutant with a two-fold higher position specificity for hesperetin. The mutant's catalytic activity, however, was considerably diminished. Our findings suggest that hesperetin can be created from central carbon metabolism in E. coli following the introduction of a caffeic acid biosynthesis pathway.

Carboxylic acid reductase-dependent biosynthesis of eugenol and related allylphenols

BACKGROUND

(Hydroxy)cinnamyl alcohols and allylphenols, including coniferyl alcohol and eugenol, are naturally occurring aromatic compounds widely utilised in pharmaceuticals, flavours, and fragrances. Traditionally, the heterologous biosynthesis of (hydroxy)cinnamyl alcohols from (hydroxy)cinnamic acids involved CoA-dependent activation of the substrate. However, a recently explored alternative pathway involving carboxylic acid reductase (CAR) has proven efficient in generating the (hydroxy)cinnamyl aldehyde intermediate without the need for CoA activation. In this study, we investigated the application of the CAR pathway for whole-cell bioconversion of a range of (hydroxy)cinnamic acids into their corresponding (hydroxy)cinnamyl alcohols. Furthermore, we sought to extend the pathway to enable the production of a variety of allylphenols and allylbenzene.

RESULTS

By screening the activity of several heterologously expressed enzymes in crude cell lysates, we identified the combination of Segniliparus rugosus CAR (SrCAR) and Medicago sativa cinnamyl alcohol dehydrogenase (MsCAD2) as the most efficient enzymatic cascade for the two-step reduction of ferulic acid to coniferyl alcohol. To optimise the whole-cell bioconversion in Escherichia coli, we implemented a combinatorial approach to balance the gene expression levels of SrCAR and MsCAD2. This optimisation resulted in a coniferyl alcohol yield of almost 100%. Furthermore, we extended the pathway by incorporating coniferyl alcohol acyltransferase and eugenol synthase, which allowed for the production of eugenol with a titre of up to 1.61 mM (264 mg/L) from 3 mM ferulic acid. This improvement in titre surpasses previous achievements in the field employing a CoA-dependent coniferyl alcohol biosynthesis pathway. Our study not only demonstrated the successful utilisation of the CAR pathway for the biosynthesis of diverse (hydroxy)cinnamyl alcohols, such as p-coumaryl alcohol, caffeyl alcohol, cinnamyl alcohol, and sinapyl alcohol, from their corresponding (hydroxy)cinnamic acid precursors but also extended the pathway to produce allylphenols, including chavicol, hydroxychavicol, and methoxyeugenol. Notably, the microbial production of methoxyeugenol from sinapic acid represents a novel achievement.

CONCLUSION

The combination of SrCAR and MsCAD2 enzymes offers an efficient enzymatic cascade for the production of a wide array of (hydroxy)cinnamyl alcohols and, ultimately, allylphenols from their respective (hydroxy)cinnamic acids. This expands the range of value-added molecules that can be generated using microbial cell factories and creates new possibilities for applications in industries such as pharmaceuticals, flavours, and fragrances. These findings underscore the versatility of the CAR pathway, emphasising its potential in various biotechnological applications.

Expanding flavone and flavonol production capabilities in Escherichia coli

Flavones and flavonols are important classes of flavonoids with nutraceutical and pharmacological value, and their production by fermentation with recombinant microorganisms promises to be a scalable and economically favorable alternative to extraction from plant sources. Flavones and flavonols have been produced recombinantly in a number of microorganisms, with Saccharomyces cerevisiae typically being a preferred production host for these compounds due to higher yields and titers of precursor compounds, as well as generally improved ability to functionally express cytochrome P450 enzymes without requiring modification to improve their solubility. Recently, a rapid prototyping platform has been developed for high-value compounds in E. coli, and a number of gatekeeper (2S)-flavanones, from which flavones and flavonols can be derived, have been produced to high titers in E. coli using this platform. In this study, we extended these metabolic pathways using the previously reported platform to produce apigenin, chrysin, luteolin and kaempferol from the gatekeeper flavonoids naringenin, pinocembrin and eriodictyol by the expression of either type-I flavone synthases (FNS-I) or type-II flavone synthases (FNS-II) for flavone biosynthesis, and by the expression of flavanone 3-dioxygenases (F3H) and flavonol synthases (FLS) for the production of the flavonol kaempferol. In our best-performing strains, titers of apigenin and kaempferol reached 128 mg L-1 and 151 mg L-1 in 96-DeepWell plates in cultures supplemented with an additional 3 mM tyrosine, though titers for chrysin (6.8 mg L-1) from phenylalanine, and luteolin (5.0 mg L-1) from caffeic acid were considerably lower. In strains with upregulated tyrosine production, apigenin and kaempferol titers reached 80.2 mg L-1 and 42.4 mg L-1 respectively, without the further supplementation of tyrosine beyond the amount present in the rich medium. Notably, the highest apigenin, chrysin and luteolin titers were achieved with FNS-II enzymes, suggesting that cytochrome P450s can show competitive performance compared with non-cytochrome P450 enzymes in prokaryotes for the production of flavones.

ipaPy2: Integrated Probabilistic Annotation (IPA) 2.0 - an improved Bayesian-based method for the annotation of LC-MS/MS untargeted metabolomics data

SUMMARY

The Integrated Probabilistic Annotation (IPA) is an automated annotation method for LC-MS-based untargeted metabolomics experiments, that provides statistically rigorous estimates of the probabilities associated with each annotation. Here we introduce ipaPy2, a substantially improved and completely refactored Python implementation of the IPA method. The revised method is now able to integrate tandem MS fragmentation data, which increases the accuracy of the identifications. Moreover, ipaPy2 provides a much more user-friendly interface, and isotope peaks are no longer treated as individual features, but integrated into isotope fingerprints, greatly speeding up the calculations. The method has also been fully integrated with the mzMatch pipeline, so that the results of the annotation can be explored through the newly developed PeakMLViewerPy tool available at https://github.com/UoMMIB/PeakMLViewerPy.

AVAILABILITY AND IMPLEMENTATION

The source code, extensive documentation and tutorials are freely available on GitHub at https://github.com/francescodc87/ipaPy2.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

TFBMiner: A User-Friendly Command Line Tool for the Rapid Mining of Transcription Factor-Based Biosensors

Transcription factors responsive to small molecules are essential elements in synthetic biology designs. They are often used as genetically encoded biosensors with applications ranging from the detection of environmental contaminants and biomarkers to microbial strain engineering. Despite our efforts to expand the space of compounds that can be detected using biosensors, the identification and characterization of transcription factors and their corresponding inducer molecules remain labor- and time-intensive tasks. Here, we introduce TFBMiner, a new data mining and analysis pipeline that enables the automated and rapid identification of putative metabolite-responsive transcription factor-based biosensors (TFBs). This user-friendly command line tool harnesses a heuristic rule-based model of gene organization to identify both gene clusters involved in the catabolism of user-defined molecules and their associated transcriptional regulators. Ultimately, biosensors are scored based on how well they fit the model, providing wet-lab scientists with a ranked list of candidates that can be experimentally tested. We validated the pipeline using a set of molecules for which TFBs have been reported previously, including sensors responding to sugars, amino acids, and aromatic compounds, among others. We further demonstrated the utility of TFBMiner by identifying a biosensor for S-mandelic acid, an aromatic compound for which a responsive transcription factor had not been found previously. Using a combinatorial library of mandelate-producing microbial strains, the newly identified biosensor was able to distinguish between low- and high-producing strain candidates. This work will aid in the unraveling of metabolite-responsive microbial gene regulatory networks and expand the synthetic biology toolbox to allow for the construction of more sophisticated self-regulating biosynthetic pathways.

Biotechnological application of Streptomyces for the production of clinical drugs and other bioactive molecules

Streptomyces is one of the most relevant genera in biotechnology, and its rich secondary metabolism is responsible for the biosynthesis of a plethora of bioactive compounds, including several clinically relevant drugs. The use of Streptomyces species for the manufacture of natural products has been established for more than half a century; however, the tremendous advances observed in recent years in genetic engineering and molecular biology have revolutionised the optimisation of Streptomyces as cell factories and drastically expanded the biotechnological potential of these bacteria. Here, we illustrate the most exciting advances reported in the past few years, with a particular focus on the approaches significantly improving the biotechnological capacity of Streptomyces to produce clinical drugs and other valuable secondary metabolites.

Data integration and mechanistic modelling for breast cancer biology: Current state and future directions

Breast cancer is one of the most common cancers threatening women worldwide. A limited number of available treatment options, frequent recurrence, and drug resistance exacerbate the prognosis of breast cancer patients. Thus, there is an urgent need for methods to investigate novel treatment options, while taking into account the vast molecular heterogeneity of breast cancer. Recent advances in molecular profiling technologies, including genomics, epigenomics, transcriptomics, proteomics and metabolomics data, enable approaching breast cancer biology at multiple levels of omics interaction networks. Systems biology approaches, including computational inference of ‘big data’ and mechanistic modelling of specific pathways, are emerging to identify potential novel combinations of breast cancer subtype signatures and more diverse targeted therapies.

Harnessing intercellular signals to engineer the soil microbiome

Covering: Focus on 2015 to 2020Plant and soil microbiomes consist of diverse communities of organisms from across kingdoms and can profoundly affect plant growth and health. Natural product-based intercellular signals govern important interactions between microbiome members that ultimately regulate their beneficial or harmful impacts on the plant. Exploiting these evolved signalling circuits to engineer microbiomes towards beneficial interactions with crops is an attractive goal. There are few reports thus far of engineering the intercellular signalling of microbiomes, but this article argues that it represents a tremendous opportunity for advancing the field of microbiome engineering. This could be achieved through the selection of synergistic consortia in combination with genetic engineering of signal pathways to realise an optimised microbiome.

A completely resolved phylogenetic tree of British spiders (Arachnida: Araneae)

The recent accumulation of increasingly densely sampled phylogenetic analyses of spiders has greatly advanced our understanding of evolutionary relationships within this group. Here, this diverse literature is reviewed and combined with earlier morphological analyses in an attempt to reconstruct the first fully resolved phylogeny for the spider fauna of the British Isles. The resulting tree highlights parts of the group where data are still too limited for a confident assessment of relationships, proposes a number of deviations from previously suggested phylogenetic hypotheses, and can serve as a framework for evolutionary and ecological interpretations of the biology of British spiders, as well as a starting point for future studies on a larger geographical scale.

The evolving art of creating genetic diversity: From directed evolution to synthetic biology

The ability to engineer biological systems, whether to introduce novel functionality or improved performance, is a cornerstone of biotechnology and synthetic biology. Typically, this requires the generation of genetic diversity to explore variations in phenotype, a process that can be performed at many levels, from single molecule targets (i.e., in directed evolution of enzymes) to whole organisms (e.g., in chassis engineering). Recent advances in DNA synthesis technology and automation have enhanced our ability to create variant libraries with greater control and throughput. This review highlights the latest developments in approaches to create such a hierarchy of diversity from the enzyme level to entire pathways in vitro, with a focus on the creation of combinatorial libraries that are required to navigate a target's vast design space successfully to uncover significant improvements in function.

Host Systems for the Production of Recombinant Spider Silk

Spider silk is renowned for its impressive mechanical properties. It is one of the strongest known biomaterials, possessing mechanical properties that outmatch both steel and Kevlar. However, the farming of spiders for their silk is unfeasible. Consequently, production of recombinant spider silk proteins (spidroins) in more amenable hosts is an exciting field of research. For large-scale production to be viable, a heterologous silk production system that is both highly efficient and cost effective is essential. Genes encoding recombinant spidroin have been expressed in bacterial, yeast, insect, and mammalian cells, in addition to many other platforms. This review discusses the recent advances in exploiting an increasingly diverse range of host platforms in the heterologous production of recombinant spidroins.

Synthetic biology approaches to actinomycete strain improvement

Their biochemical versatility and biotechnological importance make actinomycete bacteria attractive targets for ambitious genetic engineering using the toolkit of synthetic biology. But their complex biology also poses unique challenges. This mini review discusses some of the recent advances in synthetic biology approaches from an actinomycete perspective and presents examples of their application to the rational improvement of industrially relevant strains.

Investigation of the effects of actinorhodin biosynthetic gene cluster expression and a rpoB point mutation on the metabolome of Streptomyces coelicolor M1146

The previously reported Streptomyces coelicolor M1146 is commonly used as a host strain for engineering of secondary metabolite production. In this study, absolute quantification of intracellular and extracellular metabolites of M1146 was performed in mid-log phase and stationary phase to observe major metabolites and the changes that occurred during growth. Decreased levels of central carbon metabolites (glycolysis, TCA cycle, and pentose phosphate pathway) and increased levels of amino acids were observed in stationary phase compared to mid-log phase. Furthermore, comparative metabolome analyses of M1146 upon expression of the actinorhodin biosynthetic gene cluster (M1146+ACT), a point mutation on the rpoB gene encoding RNA polymerase beta-subunit (M1152), and both expression of actinorhodin biosynthetic gene cluster and a rpoB point mutation (M1152+ACT) were performed. M1146+ACT showed higher levels of important cofactors, such as ATP, NADPH, and FMN while M1152 led to higher levels of intracellular S-adenosyl-methionine, acyl-CoAs, and extracellular nucleosides compared to M1146. M1152+ACT exhibited the highest levels of actinorhodin with elevated bases, nucleosides, and nucleotides, such as intracellular PRPP (phosphoribosyl phosphate), ATP, along with extracellular inosine, uridine, and guanine compared to the other three strains, which were considered to be combined effects of actinorhodin gene cluster expression and a rpoB point mutation. Metabolites analysis by means of absolute quantification demonstrated changes in precursors of secondary metabolites before and after phosphate depletion in M1146. Comparative metabolome analysis provided further insights into the effects of actinorhodin gene cluster expression along with a rpoB point mutation on the metabolome of S. coelicolor.

Multi-Omics Analysis of the Effect of cAMP on Actinorhodin Production in Streptomyces coelicolor

Cyclic adenosine monophosphate (cAMP) has been known to play an important role in regulating morphological development and antibiotic production in Streptomyces coelicolor. However, the functional connection between cAMP levels and antibiotic production and the mechanism by which cAMP regulates antibiotic production remain unclear. In this study, metabolomics- and transcriptomics-based multi-omics analysis was applied to S. coelicolor strains that either produce the secondary metabolite actinorhodin (Act) or lack most secondary metabolite biosynthesis pathways including Act. Comparative multi-omics analysis of the two strains revealed that intracellular and extracellular cAMP abundance was strongly correlated with actinorhodin production. Notably, supplementation of cAMP improved cell growth and antibiotic production. Further multi-omics analysis of cAMP-supplemented S. coelicolor cultures showed an increase of guanine and the expression level of purine metabolism genes. Based on this phenomenon, supplementation with 7-methylguanine, a competitive inhibitor of reactions utilizing guanine, with or without additional cAMP supplementation, was performed. This experiment revealed that the reactions inhibited by 7-methylguanine are mediating the positive effect on growth and antibiotic production, which may occur downstream of cAMP supplementation.

Engineering Escherichia coli towards de novo production of gatekeeper (2S)-flavanones: naringenin, pinocembrin, eriodictyol and homoeriodictyol

Natural plant-based flavonoids have drawn significant attention as dietary supplements due to their potential health benefits, including anti-cancer, anti-oxidant and anti-asthmatic activities. Naringenin, pinocembrin, eriodictyol and homoeriodictyol are classified as (2S)-flavanones, an important sub-group of naturally occurring flavonoids, with wide-reaching applications in human health and nutrition. These four compounds occupy a central position as branch point intermediates towards a broad spectrum of naturally occurring flavonoids. Here, we report the development of Escherichia coli production chassis for each of these key gatekeeper flavonoids. Selection of key enzymes, genetic construct design and the optimization of process conditions resulted in the highest reported titers for naringenin (484 mg/l), improved production of pinocembrin (198 mg/l) and eriodictyol (55 mg/l from caffeic acid), and provided the first example of in vivo production of homoeriodictyol directly from glycerol (17 mg/l). This work provides a springboard for future production of diverse downstream natural and non-natural flavonoid targets.

Unravelling the γ-butyrolactone network in Streptomyces coelicolor by computational ensemble modelling

Antibiotic production is coordinated in the Streptomyces coelicolor population through the use of diffusible signaling molecules of the γ-butyrolactone (GBL) family. The GBL regulatory system involves a small, and not completely defined two-gene network which governs a potentially bi-stable switch between the “on” and “off” states of antibiotic production. The use of this circuit as a tool for synthetic biology has been hampered by a lack of mechanistic understanding of its functionality. We here present the creation and analysis of a versatile and adaptable ensemble model of the Streptomyces GBL system (detailed information on all model mechanisms and parameters is documented in http://www.systemsbiology.ls.manchester.ac.uk/wiki/index.php/Main_Page). We use the model to explore a range of previously proposed mechanistic hypotheses, including transcriptional interference, antisense RNA interactions between the mRNAs of the two genes, and various alternative regulatory activities. Our results suggest that transcriptional interference alone is not sufficient to explain the system’s behavior. Instead, antisense RNA interactions seem to be the system's driving force, combined with an aggressive scbR promoter. The computational model can be used to further challenge and refine our understanding of the system’s activity and guide future experimentation.

Streptomyces species are Gram-positive soil-dwelling bacteria, which are known as a prolific source of secondary metabolites, such as antibiotics. Antibiotic production is coordinated in the bacterial population through the use of diffusible signalling molecules of the γ-butyrolactone (GBL) family. The GBL regulatory system involves a small, yet complex two-gene network, the mechanism of which has not yet been completely defined. The complete elucidation of this system could potentially lead to the ability to design reliable and sensitive engineered cellular switches. We therefore designed a versatile model of the GBL system in order to investigate the feasibility of various hypothesized mechanisms. The ensemble modelling analysis that we performed revealed that antisense RNA interactions seem to be the system’s driving force, together with an aggressive scbR promoter. Transcriptional interference is also significant; however, it is not sufficient to explain the system’s behavior by itself. Finally, the model indicates key experiments, which could completely elucidate the role of the system and the interactions of its components and potentially lead to the design of reliable and sensitive systems with significant applications as orthologous regulatory circuits in synthetic biology and biotechnology.

Rapid prototyping of microbial production strains for the biomanufacture of potential materials monomers

Bio-based production of industrial chemicals using synthetic biology can provide alternative green routes from renewable resources, allowing for cleaner production processes. To efficiently produce chemicals on-demand through microbial strain engineering, biomanufacturing foundries have developed automated pipelines that are largely compound agnostic in their time to delivery. Here we benchmark the capabilities of a biomanufacturing pipeline to enable rapid prototyping of microbial cell factories for the production of chemically diverse industrially relevant material building blocks. Over 85 days the pipeline was able to produce 17 potential material monomers and key intermediates by combining 160 genetic parts into 115 unique biosynthetic pathways. To explore the scale-up potential of our prototype production strains, we optimized the enantioselective production of mandelic acid and hydroxymandelic acid, achieving gram-scale production in fed-batch fermenters. The high success rate in the rapid design and prototyping of microbially-produced material building blocks reveals the potential role of biofoundries in leading the transition to sustainable materials production.

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

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.

Bioengineering horizon scan 2020

Horizon scanning is intended to identify the opportunities and threats associated with technological, regulatory and social change. In 2017 some of the present authors conducted a horizon scan for bioengineering (Wintle et al., 2017). Here we report the results of a new horizon scan that is based on inputs from a larger and more international group of 38 participants. The final list of 20 issues includes topics spanning from the political (the regulation of genomic data, increased philanthropic funding and malicious uses of neurochemicals) to the environmental (crops for changing climates and agricultural gene drives). The early identification of such issues is relevant to researchers, policy-makers and the wider public.

Exploring novel bacterial terpene synthases

Terpenes are the largest class of natural products with extensive structural diversity and are widely used as pharmaceuticals, herbicides, flavourings, fragrances, and biofuels. While they have mostly been isolated from plants and fungi, the availability and analysis of bacterial genome sequence data indicates that bacteria also possess many putative terpene synthase genes. In this study, we further explore this potential for terpene synthase activity in bacteria. Twenty two potential class I terpene synthase genes (TSs) were selected to represent the full sequence diversity of bacterial synthase candidates and recombinantly expressed in E. coli. Terpene synthase activity was detected for 15 of these enzymes, and included mono-, sesqui- and diterpene synthase activities. A number of confirmed sesquiterpene synthases also exhibited promiscuous monoterpene synthase activity, suggesting that bacteria are potentially a richer source of monoterpene synthase activity then previously assumed. Several terpenoid products not previously detected in bacteria were identified, including aromandendrene, acora-3,7(14)-diene and longiborneol. Overall, we have identified promiscuous terpene synthases in bacteria and demonstrated that terpene synthases with substrate promiscuity are widely distributed in nature, forming a rich resource for engineering terpene biosynthetic pathways for biotechnology.

Towards engineering and production of artificial spider silk using tools of synthetic biology

Spider silk is one of the strongest biomaterials available in nature. Its mechanical properties make it a good candidate for applications in various fields ranging from protective armour to bandages for wound dressing to coatings for medical implants. Spider silk is formed by an intricate arrangement of spidroins, which are extremely large proteins containing long stretches of repeating segments rich in alanine and glycine. A large amount of research has been directed towards harnessing the spectacular potential of spider silks and using them for different applications. The interdisciplinary approach of synthetic biology is an ideal tool to study these spider silk proteins and work towards the engineering and production of synthetic spider silk. This review aims to highlight the recent progress that has been made in the study of spider silk proteins using different branches of synthetic biology. Here, the authors discuss the different computational approaches, directed evolution techniques and various expression platforms that have been tested for the successful production of spider silk. Future challenges facing the field and possible solutions offered by synthetic biology are also discussed.

Highly multiplexed, fast and accurate nanopore sequencing for verification of synthetic DNA constructs and sequence libraries

Synthetic biology utilizes the Design-Build-Test-Learn pipeline for the engineering of biological systems. Typically, this requires the construction of specifically designed, large and complex DNA assemblies. The availability of cheap DNA synthesis and automation enables high-throughput assembly approaches, which generates a heavy demand for DNA sequencing to verify correctly assembled constructs. Next-generation sequencing is ideally positioned to perform this task, however with expensive hardware costs and bespoke data analysis requirements few laboratories utilize this technology in-house. Here a workflow for highly multiplexed sequencing is presented, capable of fast and accurate sequence verification of DNA assemblies using nanopore technology. A novel sample barcoding system using polymerase chain reaction is introduced, and sequencing data are analyzed through a bespoke analysis algorithm. Crucially, this algorithm overcomes the problem of high-error rate nanopore data (which typically prevents identification of single nucleotide variants) through statistical analysis of strand bias, permitting accurate sequence analysis with single-base resolution. As an example, 576 constructs (6 × 96 well plates) were processed in a single workflow in 72 h (from Escherichia coli colonies to analyzed data). Given our procedure's low hardware costs and highly multiplexed capability, this provides cost-effective access to powerful DNA sequencing for any laboratory, with applications beyond synthetic biology including directed evolution, single nucleotide polymorphism analysis and gene synthesis.

Integrated Probabilistic Annotation: A Bayesian-Based Annotation Method for Metabolomic Profiles Integrating Biochemical Connections, Isotope Patterns, and Adduct Relationships

In a typical untargeted metabolomics experiment, the huge amount of complex data generated by mass spectrometry necessitates automated tools for the extraction of useful biological information. Each metabolite generates numerous mass spectrometry features. The association of these experimental features to the underlying metabolites still represents one of the major bottlenecks in metabolomics data processing. While certain identification (e.g., by comparison to authentic standards) is always desirable, it is usually achievable only for a limited number of compounds, and scientists often deal with a significant amount of putatively annotated metabolites. The confidence in a specific annotation is usually assessed by considering different sources of information (e.g., isotope patterns, adduct formation, chromatographic retention times, and fragmentation patterns). IPA (integrated probabilistic annotation) offers a rigorous and reproducible method to automatically annotate metabolite profiles and evaluate the resulting confidence of the putative annotations. It is able to provide a rigorous measure of our confidence in any putative annotation and is also able to update and refine our beliefs (i.e., background prior knowledge) by incorporating different sources of information in the annotation process, such as isotope patterns, adduct formation and biochemical relations. The IPA package is freely available on GitHub ( https://github.com/francescodc87/IPA ), together with the related extensive documentation.

Dynamics of the human skin mediator lipidome in response to dietary ω-3 fatty acid supplementation

Nutritional supplementation with fish oil or ω-3 (n-3) polyunsaturated fatty acids (PUFAs) has potential benefits for skin inflammation. Although the differential metabolism of the main n-3PUFA eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) could lead to distinct activities, there are no clinical studies comparing their relative efficacy in human skin. Following a 10-wk oral supplementation of healthy volunteers and using mass spectrometry-based lipidomics, we found that n-3PUFA mainly affected the epidermal mediator lipidome. EPA was more efficient than DHA in reducing production of arachidonic acid–derived lipids, and both n-3PUFA lowered N-acyl ethanolamines. In UV radiation–challenged skin (3 times the minimum erythemal dose), EPA attenuated the production of proinflammatory lipids, whereas DHA abrogated the migration of Langerhans cells, as assessed by immunohistochemistry. Interestingly, n-3PUFA increased the infiltration of CD4⁺ and CD8⁺ T cells but did not alter the erythemal response, either the sunburn threshold or the resolution of erythema, as assessed by spectrophotometric hemoglobin index readings. As EPA and DHA differentially impact cutaneous inflammation through changes in the network of epidermal lipids and dendritic and infiltrating immune cells, they should be considered separately when designing interventions for cutaneous disease.—Kendall, A. C., Pilkington, S. M., Murphy, S. A., Del Carratore, F., Sunarwidhi, A. L., Kiezel-Tsugunova, M., Urquhart, P., Watson, R. E. B., Breitling, R., Rhodes, L. E., Nicolaou, A. Dynamics of the human skin mediator lipidome in response to dietary ω-3 fatty acid supplementation.

A LITTLE LEARNING IS A DANGEROUS THING – ON THE USEFULNESS OF BARCODE DATA FOR GENUS-LEVEL TAXONOMY

The paper comments the usefulness of barcode data for genus-level taxonomy.

SelProm: A Queryable and Predictive Expression Vector Selection Tool for Escherichia coli

The rapid prototyping and optimization of plasmid-based recombinant gene expression is one of the key steps in the development of bioengineered bacterial systems. Often, multiple genes or gene modules need to be coexpressed, and for this purpose compatible, inducible plasmid systems have been developed. However, inducible expression systems are not favored in industrial processes, due to their prohibitive cost, and consequently the conversion to constitutive expression systems is often desired. Here we present a set of constitutive-expression plasmids for this purpose, which were benchmarked using fluorescent reporter genes. To further facilitate the conversion between inducible and constitutive expression systems, we developed SelProm, a design tool that serves as a parts repository of plasmid expression strength and predicts portability rules between constitutive and inducible plasmids through model comparison and machine learning. The SelProm tool is freely available at http://selprom.synbiochem.co.uk .

Synthetic biology for fibres, adhesives and active camouflage materials in protection and aerospace

Synthetic biology has huge potential to produce the next generation of advanced materials by accessing previously unreachable (bio)chemical space. In this prospective review, we take a snapshot of current activity in this rapidly developing area, focussing on prominent examples for high-performance applications such as those required for protective materials and the aerospace sector. The continued growth of this emerging field will be facilitated by the convergence of expertise from a range of diverse disciplines, including molecular biology, polymer chemistry, materials science and process engineering. This review highlights the most significant recent advances and address the cross-disciplinary challenges currently being faced.

HOW NOT TO CONDUCT A SCIENTIFIC DEBATE: A COUNTERPOINT TO THE RECENT CRITIQUE OF THE “PRAGMATIC CLASSIFICATION” OF JUMPING SPIDERS (ARTHROPODA: ARACHNIDA: ARANEAE: SALTICIDAE)

The paper gives a counterpoint to the recent critique of the “pragmatic classification” of jumping spiders (Arthropoda: Arachnida: Araneae: Salticidae).

Defining informative priors for ensemble modeling in systems biology

Ensemble modeling in molecular systems biology requires the reproducible translation of kinetic parameter data into informative probability distributions (priors), as well as approaches that sample parameters from these distributions without violating the thermodynamic consistency of the overall model. Although a number of pioneering frameworks for ensemble modeling have been published, the issue of generating informative priors has not yet been addressed. Here, we present a protocol that aims to fill this gap. This protocol discusses the collection of parameter values from a diverse range of sources (literature, databases and experiments), assessment of their plausibility, and creation of log-normal probability distributions that can be used as informative priors in ensemble modeling. Furthermore, the protocol enables sampling from the generated distributions while maintaining thermodynamic consistency. Once all parameter values have been retrieved from literature and databases, the protocol can be implemented within ~5-10 min per parameter. The aim of this protocol is to facilitate the design and use of informative distributions for ensemble modeling, especially in fields such as synthetic biology and systems medicine.

BARCODE TAXONOMY AT THE GENUS LEVEL

DNA barcode sequencing has rapidly become one of the most powerful tools for biodiversity assessments. Beyond its original uses for the identification of animal species, including the discovery of cryptic diversity in difficult taxonomic groups, the growing public sequence datasets also offer opportunities for more wide-ranging applications. This contribution shows how barcode data can provide useful complementary information to assist taxonomic decision making at the genus level. An analysis of public barcode datasets for 10 diverse spider families, covering more than 3400 species and morphospecies, reveals numerous examples where sequence similarities either strongly support or convincingly refute recent controversial genus assignments. The following nomenclatorial changes are suggested based on a combined assessment of morphological evidence and the barcode analysis: Acantholycosa = Pardosa (syn. nov.); Piratula = Pirata (syn. nov.); Pulchellodromus, Philodromimus, Tibellomimus, Artanes, and Emargidromus = subgenera of Philodromus (stat. nov.); Cryptachaea riparia = Parasteatoda riparia (comb. nov.); Ohlertidion = Heterotheridion (syn. nov.); Saaristoa = Aphileta (syn. nov.); Aphileta microtarsa = Eulaira microtarsa (comb. conf.); Centromerita and Tallusia = Centromerus (syn. conf.); Obscuriphantes, Agnyphantes, and Acanthoneta = Poeciloneta (syn. nov.); Bolyphantes bipartitus = Poeciloneta bipartita (comb. nov.); Anguliphantes, Improphantes, Piniphantes, and Mansuphantes = Oryphantes (syn. nov.), Palliduphantes antroniensis = Oryphantes antroniensis (comb. nov.), Lepthyphantes nodifer = Oryphantes nodifer (comb. nov.), Hypositticus, Sittipub, Calositticus, Sittisax, Sittiflor, and Attulus = Sitticus (syn. nov.).

Mobilising ion mobility mass spectrometry for metabolomics

Chromatography-based mass spectrometry approaches (xC-MS) are commonly used in untargeted metabolomics, providing retention time, m/z values and metabolite-specific fragments, all of which are used to identify and validate an unknown analyte. Ion mobility-mass spectrometry (IM-MS) is emerging as an enhancement to classic xC-MS strategies, by offering additional ion separation as well as collision cross section (CCS) determination. In order to apply such an approach to a metabolomics workflow, verified data from metabolite standards is necessary. In this work we present experimental DTCCSN2 values for a range of metabolites in positive and negative ionisation modes using drift tube-ion mobility-mass spectrometry (DT-IM-MS) with nitrogen as the buffer gas. The value of DTCCSN2 measurements for application in metabolite identification relies on a robust technique that acquires measurements of high reproducibility. We report that the CCS values found for 86% of metabolites measured in replicate have a relative standard deviation lower than 0.2%. Examples of metabolites with near identical mass are demonstrated to be separated by ion mobility with over 4% difference in DTCCSN2 values. We conclude that the integration of ion mobility into current LC-MS workflows can aid in small molecule identification for both targeted and untargeted metabolite screening.

A BARCODE-BASED PHYLOGENETIC SCAFFOLD FOR XYSTICUS AND ITS RELATIVES (ARANEAE: THOMISIDAE: CORIARACHNINI)

The phylogenetic relationships and taxonomy of the crab spider genus Xysticus and its closest relatives (i.e., the tribe Coriarachnini, also including, e.g., Ozyptila, Coriarachne and Bassaniana) have long been controversial, with several alternative classifications being proposed, none of which has gained universal acceptance. As Coriarachnini is largely confined to the Holarctic region, the main target area of recent DNA barcoding projects for spiders, a large amount of genetic data for the group is now publicly available. The results of a phylogenetic analysis of this sequence dataset are largely congruent with earlier morphology-based results regarding the evolutionary structure of the group. In particular, they highlight the fact that Xysticus s. lat. is a paraphyletic assembly and that several species groups need to be placed in separate genera to achieve monophyly of Xysticus s. str. Similarly, Coriarachne and Bassaniana appear as independent clades rather than a joined monophyletic Coriarachne s. lat. In contrast, further subdivision of Ozyptila is not supported by the genetic data. Importantly, the analysis also shows that anapophysate members of Xysticus s. lat. form two widely separated groups: a primarily anapophysate division, also including Coriarachne and Bassaniana, at the base of Xysticus s. lat., and a secondarily anapophysate clade deeply nested within Xysticus s. str. This might explain some of the earlier difficulties when trying to define generally accepted subgroups within Xysticus s. lat. The phylogenetic scaffold based on barcode sequences is sufficiently dense and well resolved to attempt the tentative and provisional placement of the majority of species in Xysticus s. lat. in the independent genera Xysticus s. str., Bassaniodes, Psammitis and Spiracme as a starting point for a future more formal revision of the group.

Steatoda nobilis, a false widow on the rise: a synthesis of past and current distribution trends

The Noble False Widow, Steatodanobilis (Thorell, 1875) (Araneae, Theridiidae), is, due to its relatively large size and potential medical importance, one of the most notable invasive spider species worldwide. Probably originating from the Canary Islands and Madeira, the species is well established in Western Europe and large parts of the Mediterranean area and has spread recently into California and South America, while Central European populations were not known until 2011.

We report on long-time observations that reveal that at least two flourishing populations in Germany (Cologne) have been present for over five years, while in Ecuador one population has been observed between 2014 and 2018 and several other records were made in other parts of the country. Data obtained from the British Spider Recording Scheme demonstrate that the species moved significantly northwards since the report of the first populations in the very South of England, after several decades of relative stasis. The sudden northward expansion highly correlates with a massive rise in press coverage of the species.

In the Americas, S.nobilis is currently known from four countries (USA, Chile, Ecuador, Colombia), and available DNA barcoding data obtained for specimens from this area suggest that multiple introductions occurred within each country. Using ecological niche modeling, we identified suitable climate regions for the species and discuss possible reasons for its current spread. We propose that seaside cities and villages with a temperate oceanic or Mediterranean climate are especially favourable potential habitats for S.nobilis and will face the highest colonization pressure in the future, while tropical upland regions with temperate climates are also vulnerable to invasion by S.nobilis.

Machine Learning of Designed Translational Control Allows Predictive Pathway Optimization in Escherichia coli

The field of synthetic biology aims to make the design of biological systems predictable, shrinking the huge design space to practical numbers for testing. When designing microbial cell factories, most optimization efforts have focused on enzyme and strain selection/engineering, pathway regulation, and process development. In silico tools for the predictive design of bacterial ribosome binding sites (RBSs) and RBS libraries now allow translational tuning of biochemical pathways; however, methods for predicting optimal RBS combinations in multigene pathways are desirable. Here we present the implementation of machine learning algorithms to model the RBS sequence-phenotype relationship from representative subsets of large combinatorial RBS libraries allowing the accurate prediction of optimal high-producers. Applied to a recombinant monoterpenoid production pathway in Escherichia coli, our approach was able to boost production titers by over 60% when screening under 3% of a library. To facilitate library screening, a multiwell plate fermentation procedure was developed, allowing increased screening throughput with sufficient resolution to discriminate between high and low producers. High producers from one library did not translate during scale-up, but the reduced screening requirements allowed rapid rescreening at the larger scale. This methodology is potentially compatible with any biochemical pathway and provides a powerful tool toward predictive design of bacterial production chassis.

Development and validation of an updated computational model of Streptomyces coelicolor primary and secondary metabolism

BACKGROUND

Streptomyces species produce a vast diversity of secondary metabolites of clinical and biotechnological importance, in particular antibiotics. Recent developments in metabolic engineering, synthetic and systems biology have opened new opportunities to exploit Streptomyces secondary metabolism, but achieving industry-level production without time-consuming optimization has remained challenging. Genome-scale metabolic modelling has been shown to be a powerful tool to guide metabolic engineering strategies for accelerated strain optimization, and several generations of models of Streptomyces metabolism have been developed for this purpose.

RESULTS

Here, we present the most recent update of a genome-scale stoichiometric constraint-based model of the metabolism of Streptomyces coelicolor, the major model organism for the production of antibiotics in the genus. We show that the updated model enables better metabolic flux and biomass predictions and facilitates the integrative analysis of multi-omics data such as transcriptomics, proteomics and metabolomics.

CONCLUSIONS

The updated model presented here provides an enhanced basis for the next generation of metabolic engineering attempts in Streptomyces.

Orthogonal Regulatory Circuits for Escherichia coli Based on the γ-Butyrolactone System of Streptomyces coelicolor

Chemically inducible transcription factors are widely used to control gene expression of synthetic devices. The bacterial quorum sensing system is a popular tool to achieve such control. However, different quorum sensing systems have been found to cross-talk, both between themselves and with the hosts of these devices, and they are leaky by nature. Here we evaluate the potential use of the γ-butyrolactone system from Streptomyces coelicolor A3(2) M145 as a complementary regulatory circuit. First, two additional genes responsible for the biosynthesis of γ-butyrolactones were identified in S. coelicolor M145 and then expressed in E. coli BL21 under various experimental conditions. Second, the γ-butyrolactone receptor ScbR was optimized for expression in E. coli BL21. Finally, signal and promoter crosstalk between the γ-butyrolactone system from S. coelicolor and quorum sensing systems from Vibrio fischeri and Pseudomonas aeruginosa was evaluated. The results show that the γ-butyrolactone system does not crosstalk with the quorum sensing systems and can be used to generate orthogonal synthetic circuits.

RankProd 2.0: a refactored bioconductor package for detecting differentially expressed features in molecular profiling datasets

Motivation

The Rank Product (RP) is a statistical technique widely used to detect differentially expressed features in molecular profiling experiments such as transcriptomics, metabolomics and proteomics studies. An implementation of the RP and the closely related Rank Sum (RS) statistics has been available in the RankProd Bioconductor package for several years. However, several recent advances in the understanding of the statistical foundations of the method have made a complete refactoring of the existing package desirable.

Results

We implemented a completely refactored version of the RankProd package, which provides a more principled implementation of the statistics for unpaired datasets. Moreover, the permutation-based P-value estimation methods have been replaced by exact methods, providing faster and more accurate results.

Availability and implementation

RankProd 2.0 is available at Bioconductor (https://www.bioconductor.org/packages/devel/bioc/html/RankProd.html) and as part of the mzMatch pipeline (http://www.mzmatch.sourceforge.net).

Supplementary information

Supplementary data are available at Bioinformatics online.

Rational cell culture optimization enhances experimental reproducibility in cancer cells

Optimization of experimental conditions is critical in ensuring robust experimental reproducibility. Through detailed metabolomic analysis we found that cell culture conditions significantly impacted on glutaminase (GLS1) sensitivity resulting in variable sensitivity and irreproducibility in data. Baseline metabolite profiling highlighted that untreated cells underwent significant changes in metabolic status. Both the extracellular levels of glutamine and lactate and the intracellular levels of multiple metabolites changed drastically during the assay. We show that these changes compromise the robustness of the assay and make it difficult to reproduce. We discuss the implications of the cells' metabolic environment when studying the effects of perturbations to cell function by any type of inhibitor. We then devised 'metabolically rationalized standard' assay conditions, in which glutaminase-1 inhibition reduced glutamine metabolism differently in both cell lines assayed, and decreased the proliferation of one of them. The adoption of optimized conditions such as the ones described here should lead to an improvement in reproducibility and help eliminate false negatives as well as false positives in these assays.

Selenzyme: enzyme selection tool for pathway design

Summary

Synthetic biology applies the principles of engineering to biology in order to create biological functionalities not seen before in nature. One of the most exciting applications of synthetic biology is the design of new organisms with the ability to produce valuable chemicals including pharmaceuticals and biomaterials in a greener; sustainable fashion. Selecting the right enzymes to catalyze each reaction step in order to produce a desired target compound is, however, not trivial. Here, we present Selenzyme, a free online enzyme selection tool for metabolic pathway design. The user is guided through several decision steps in order to shortlist the best candidates for a given pathway step. The tool graphically presents key information about enzymes based on existing databases and tools such as: similarity of sequences and of catalyzed reactions; phylogenetic distance between source organism and intended host species; multiple alignment highlighting conserved regions, predicted catalytic site, and active regions and relevant properties such as predicted solubility and transmembrane regions. Selenzyme provides bespoke sequence selection for automated workflows in biofoundries.

Availability and implementation

The tool is integrated as part of the pathway design stage into the design-build-test-learn SYNBIOCHEM pipeline. The Selenzyme web server is available at http://selenzyme.synbiochem.co.uk.

Supplementary information

Supplementary data are available at Bioinformatics online.

Detection and Quantification of Butyrolactones from Streptomyces

In Streptomyces, the onset of antibiotic production and sporulation is coordinated through small diffusible molecules known as γ-butyrolactones (GBLs). These are active in very low amounts, and their extraction and characterization are challenging. Here we describe a rapid, small-scale method for the extraction of GBL from Streptomyces coelicolor, from both solid and liquid cultures, which provides sufficient material for subsequent bioassays and partial characterization. We also present two different bioassay techniques for the detection and quantification of the GBL content in the extracts: the antibiotic bioassay and the kanamycin bioassay.

A transatlantic perspective on 20 emerging issues in biological engineering

Advances in biological engineering are likely to have substantial impacts on global society. To explore these potential impacts we ran a horizon scanning exercise to capture a range of perspectives on the opportunities and risks presented by biological engineering. We first identified 70 potential issues, and then used an iterative process to prioritise 20 issues that we considered to be emerging, to have potential global impact, and to be relatively unknown outside the field of biological engineering. The issues identified may be of interest to researchers, businesses and policy makers in sectors such as health, energy, agriculture and the environment.

antiSMASH 4.0-improvements in chemistry prediction and gene cluster boundary identification

Many antibiotics, chemotherapeutics, crop protection agents and food preservatives originate from molecules produced by bacteria, fungi or plants. In recent years, genome mining methodologies have been widely adopted to identify and characterize the biosynthetic gene clusters encoding the production of such compounds. Since 2011, the 'antibiotics and secondary metabolite analysis shell-antiSMASH' has assisted researchers in efficiently performing this, both as a web server and a standalone tool. Here, we present the thoroughly updated antiSMASH version 4, which adds several novel features, including prediction of gene cluster boundaries using the ClusterFinder method or the newly integrated CASSIS algorithm, improved substrate specificity prediction for non-ribosomal peptide synthetase adenylation domains based on the new SANDPUMA algorithm, improved predictions for terpene and ribosomally synthesized and post-translationally modified peptides cluster products, reporting of sequence similarity to proteins encoded in experimentally characterized gene clusters on a per-protein basis and a domain-level alignment tool for comparative analysis of trans-AT polyketide synthase assembly line architectures. Additionally, several usability features have been updated and improved. Together, these improvements make antiSMASH up-to-date with the latest developments in natural product research and will further facilitate computational genome mining for the discovery of novel bioactive molecules.

reGenotyper: Detecting mislabeled samples in genetic data

In high-throughput molecular profiling studies, genotype labels can be wrongly assigned at various experimental steps; the resulting mislabeled samples seriously reduce the power to detect the genetic basis of phenotypic variation. We have developed an approach to detect potential mislabeling, recover the “ideal” genotype and identify “best-matched” labels for mislabeled samples. On average, we identified 4% of samples as mislabeled in eight published datasets, highlighting the necessity of applying a “data cleaning” step before standard data analysis.

Respectful Modeling: Addressing Uncertainty in Dynamic System Models for Molecular Biology

Although there is still some skepticism in the biological community regarding the value and significance of quantitative computational modeling, important steps are continually being taken to enhance its accessibility and predictive power. We view these developments as essential components of an emerging 'respectful modeling' framework which has two key aims: (i) respecting the models themselves and facilitating the reproduction and update of modeling results by other scientists, and (ii) respecting the predictions of the models and rigorously quantifying the confidence associated with the modeling results. This respectful attitude will guide the design of higher-quality models and facilitate the use of models in modern applications such as engineering and manipulating microbial metabolism by synthetic biology.

Synthetic Biology of Natural Products

The diversity and natural modularity of their biosynthetic pathways has turned natural products into attractive, but challenging, targets for synthetic biology approaches. Here, we discuss the current state of the field, highlighting recent advances and remaining bottlenecks. Global genomic assessments of natural product biosynthetic capacities across large parts of microbial diversity provide a first survey of the available natural parts libraries and identify evolutionary design rules for further engineering. Methods for compound and pathway detection and characterization are developed increasingly on the basis of synthetic biology tools, contributing to an accelerated translation of genomic information into usable building blocks for pathway assembly. A wide range of methods is also becoming available for accessing ever larger parts of chemical space by rational diversification of natural products, guided by rapid progress in our understanding of the underlying biochemistry and enzymatic mechanisms. Enhanced genome assembly and editing tools, adapted to the needs of natural products research, facilitate the realization of ambitious engineering strategies, ranging from combinatorial library generation to high-throughput optimization of product titers. Together, these tools and concepts contribute to the emergence of a new generation of revitalized natural product research.

Bioinformatics for the synthetic biology of natural products: integrating across the Design-Build-Test cycle

Covering: 2000 to 2016Progress in synthetic biology is enabled by powerful bioinformatics tools allowing the integration of the design, build and test stages of the biological engineering cycle. In this review we illustrate how this integration can be achieved, with a particular focus on natural products discovery and production. Bioinformatics tools for the DESIGN and BUILD stages include tools for the selection, synthesis, assembly and optimization of parts (enzymes and regulatory elements), devices (pathways) and systems (chassis). TEST tools include those for screening, identification and quantification of metabolites for rapid prototyping. The main advantages and limitations of these tools as well as their interoperability capabilities are highlighted.