Exploiting plug-and-play synthetic biology for drug discovery and production in microorganisms

Novel 15N Metabolic Labeling-Based Large-Scale Absolute Quantitative Proteomics Method for Corynebacterium glutamicum

With fast growth, synthetic biology powers us with the capability to produce high commercial value products in an efficient resource/energy-consuming manner. Comprehensive knowledge of the protein regulatory network of a bacterial host chassis, e.g., the actual amount of the given proteins, is the key to building cell factories for certain target hyperproduction. Many talent methods have been introduced for absolute quantitative proteomics. However, for most cases, a set of reference peptides with isotopic labeling (e.g., SIL, AQUA, QconCAT) or a set of reference proteins (e.g., commercial UPS2 kit) needs to be prepared. The higher cost hinders these methods for large sample research. In this work, we proposed a novel metabolic labeling-based absolute quantification approach (termed nMAQ). The reference Corynebacterium glutamicum strain is metabolically labeled with ¹⁵N, and a set of endogenous anchor proteins of the reference proteome is quantified by chemically synthesized light (¹⁴N) peptides. The prequantified reference proteome was then utilized as an internal standard (IS) and spiked into the target (¹⁴N) samples. SWATH-MS analysis is performed to obtain the absolute expression levels of the proteins from the target cells. The cost for nMAQ is estimated to be less than 10 dollars per sample. We have benchmarked the quantitative performance of the novel method. We believe this method will help with the deep understanding of the intrinsic regulatory mechanism of C. glutamicum during bioengineering and will promote the process of building cell factories for synthetic biology.

A scalable platform to discover antimicrobials of ribosomal origin

Ribosomally synthesized and post-translationally modified peptides (RiPPs) are a promising source of new antimicrobials in the face of rising antibiotic resistance. Here, we report a scalable platform that combines high-throughput bioinformatics with automated biosynthetic gene cluster refactoring for rapid evaluation of uncharacterized gene clusters. As a proof of concept, 96 RiPP gene clusters that originate from diverse bacterial phyla involving 383 biosynthetic genes are refactored in a high-throughput manner using a biological foundry with a success rate of 86%. Heterologous expression of all successfully refactored gene clusters in Escherichia coli enables the discovery of 30 compounds covering six RiPP classes: lanthipeptides, lasso peptides, graspetides, glycocins, linear azol(in)e-containing peptides, and thioamitides. A subset of the discovered lanthipeptides exhibit antibiotic activity, with one class II lanthipeptide showing low µM activity against Klebsiella pneumoniae, an ESKAPE pathogen. Overall, this work provides a robust platform for rapidly discovering RiPPs.

Bacterial degrons in synthetic circuits

Bacterial proteases are a promising post-translational regulation strategy in synthetic circuits because they recognize specific amino acid degradation tags (degrons) that can be fine-tuned to modulate the degradation levels of tagged proteins. For this reason, recent efforts have been made in the search for new degrons. Here we review the up-to-date applications of degradation tags for circuit engineering in bacteria. In particular, we pay special attention to the effects of degradation bottlenecks in synthetic oscillators and introduce mathematical approaches to study queueing that enable the quantitative modelling of proteolytic queues.

Multiplexed Promoter Engineering for Improving Thaxtomin A Production in Heterologous Streptomyces Hosts

Thaxtomin A is a potent bioherbicide in both organic and conventional agriculture; however, its low yield hinders its wide application. Here, we report the direct cloning and heterologous expression of the thaxtomin A gene cluster in three well-characterized Streptomyces hosts. Then, we present an efficient, markerless and multiplex large gene cluster editing method based on in vitro CRISPR/Cas9 digestion and yeast homologous recombination. With this method, we successfully engineered the thaxtomin A cluster by simultaneously replacing the native promoters of the txtED operon, txtABH operon and txtC gene with strong constitutive promoters, and the yield of thaxtomin A improved to 289.5 µg/mL in heterologous Streptomyces coelicolor M1154. To further optimize the biosynthetic pathway, we used constraint-based combinatorial design to build 27 refactored gene clusters by varying the promoter strength of every operon, and the highest titer of thaxtomin A production reached 504.6 μg/mL. Taken altogether, this work puts forward a multiplexed promoter engineering strategy to engineer secondary metabolism gene clusters for efficiently improving fermentation titers.

Genomic Comparisons and Phenotypic Diversity of Dickeya zeae Strains Causing Bacterial Soft Rot of Banana in China

Bacterial soft rot of banana, caused by Dickeya zeae, is spreading rapidly in important banana growing areas in China and seriously threatens banana production. In this study, we sequenced the high-quality complete genomes of three typical banana strains, MS1 (size: 4,831,702-bp; genome coverages: 538x), MS_2014 (size: 4,740,000-bp; genome coverages: 586x) and MS_2018 (size: 4,787,201-bp; genome coverages: 583x), isolated in 2009, 2014, and 2018, respectively. To determine their genomic and phenotypic diversity with respect to their hosts of origin, they were compared with other D. zeae strains, including another representative banana strain MS2 from China. The sequenced strains were similar in utilization of carbon source and chemical substrates, and general genomic features of GC content, and tRNA and rRNA regions. They were also conserved in most virulence determinants, including gene-encoding secretion systems, plant cell wall degrading enzymes, and exopolysaccharides. We further explored their genomic diversity in the predicted genomic islands (GIs). These GIs were rich in integrases and transposases, where some genomic dissimilarity was observed in the flagellar gene cluster and several secondary metabolite gene clusters. Different constituents of core biosynthetic modules were found within the bacteriocin and aryl polyene (APE) pigment gene clusters, and the strains from banana showed different phenotypes with respect to antibiosis effects and colony pigmentation. Additionally, clustered regularly interspaced short palindromic repeat (CRISPR) and prophage elements, such as type I-F and III-A CRISPR arrays and an intact prophage of MS1-P5, contributed to bacterial diversity. Phylogenetic tree analysis and genome-genome nucleotide comparison confirmed the genomic divergence among the strains isolated from banana. Considering these characteristics, MS2 and MS_2014 probably diverged later than MS1, while MS_2018 was different and more similar to foreign strains isolated from other hosts in several characteristics. Strain MS_2018 caused severe symptoms on banana varieties previously considered moderately resistant or moderately susceptible, including varieties of Cavendish (Musa AAA) and Plantain (Musa ABB). Our study of genomic and phenotypic diversity raises public attention to the risk of spreading new pathogenic variants within banana growing regions and supports development of predictive strategies for disease control.

Overproduction of medicinal ergot alkaloids based on a fungal platform

Privileged ergot alkaloids (EAs) produced by the fungal genus Claviceps are used to treat a wide range of diseases. However, their use and research have been hampered by the challenging genetic engineering of Claviceps. Here we systematically refactored and rationally engineered the EA biosynthetic pathway in heterologous host Aspergillus nidulans by using a Fungal-Yeast-Shuttle-Vector protocol. The obtained strains allowed the production of diverse EAs and related intermediates, including prechanoclavine (PCC, 333.8 mg/L), chanoclavine (CC, 241.0 mg/L), agroclavine (AC, 78.7 mg/L), and festuclavine (FC, 99.2 mg/L), etc. This fungal platform also enabled the access to the methyl-oxidized EAs (MOEAs), including elymoclavine (EC), lysergic acid (LA), dihydroelysergol (DHLG), and dihydrolysergic acid (DHLA), by overexpressing a P450 enzyme CloA. Furthermore, by optimizing the P450 electron transfer (ET) pathway and using multi-copy of cloA, the titers of EC and DHLG have been improved by 17.3- and 9.4-fold, respectively. Beyond our demonstration of A. nidulans as a robust platform for EA overproduction, our study offers a proof of concept for engineering the eukaryotic P450s-contained biosynthetic pathways in a filamentous fungal host.

Exploring presentations of sustainability by US synthetic biology companies

The field of synthetic biology is increasingly being positioned as a key driver of a more sustainable, bio-based economy, and has seen rapid industry growth over the past 15 years. In this paper we undertake an exploratory investigation of the relationship between sustainability and synthetic biology, identifying and analyzing sustainability-related language on the public websites of 24, US-based synthetic biology companies. We observe that sustainability is a visible part of the self-presentation of the nascent synthetic biology industry, explicitly mentioned by 18 of the 24 companies. The dominant framing of sustainability on these company websites emphasizes environmental gains and "free-market" approaches to sustainability, with little explicit mention of social dimensions of sustainability such as access, justice or intergenerational equity. Furthermore, the model of sustainability presented focuses on incremental transition towards environmental sustainability through direct substitution of products and processes using bioengineered alternatives (n = 16 companies), with no change in societal consumption or policy frameworks required in order to see sustainability gains. One-third of the companies analyzed (n = 8) mention "nature" on their websites, variously framing it as a resource to be managed or as a source of inspiration; whether the latter signals a potentially more complex relationship with nature than advanced free-market models of sustainability remains to be seen. As the synthetic biology industry begins to grow in size and visibility, we suggest this is an opportune time for the community to engage in explicit deliberation about its approach to sustainability.

Streptomyces: host for refactoring of diverse bioactive secondary metabolites

Microbial secondary metabolites are intensively explored due to their demands in pharmaceutical, agricultural and food industries. Streptomyces are one of the largest sources of secondary metabolites having diverse applications. In particular, the abundance of secondary metabolites encoding biosynthetic gene clusters and presence of wobble position in Streptomyces strains make it potential candidate as a native or heterologous host for secondary metabolite production including several cryptic gene clusters expression. Here, we have discussed the developments in Streptomyces strains genome mining, its exploration as a suitable host and application of synthetic biology for refactoring genetic systems for developing chassis for enhanced as well as novel secondary metabolites with reduced genome and cleaned background.

Beyond Plug and Pray: Context Sensitivity and in silico Design of Artificial Neomycin Riboswitches

Gene regulation in prokaryotes often depends on RNA elements such as riboswitches or RNA thermometers located in the 5' untranslated region of mRNA. Rearrangements of the RNA structure in response, e.g., to the binding of small molecules or ions control translational initiation or premature termination of transcription and thus mRNA expression. Such structural responses are amenable to computational modelling, making it possible to rationally design synthetic riboswitches for a given aptamer. Starting from an artificial aptamer, we construct the first synthetic transcriptional riboswitches that respond to the antibiotic neomycin. We show that the switching behaviour in vivo critically depends not only on the sequence of the riboswitch itself, but also on its sequence context. We therefore developed in silico methods to predict the impact of the context, making it possible to adapt the design and to rescue non-functional riboswitches. We furthermore analyse the influence of 5' hairpins with varying stability on neomycin riboswitch activity. Our data highlight the limitations of a simple plug-and-play approach in the design of complex genetic circuits and demonstrate that detailed computational models significantly simplify, improve, and automate the design of transcriptional circuits. Our design software is available under a free licence on GitHub (https://github.com/xileF1337/riboswitch_design).

Genetically Encodable Scaffolds for Optimizing Enzyme Function

Enzyme engineering is an indispensable tool in the field of synthetic biology, where enzymes are challenged to carry out novel or improved functions. Achieving these goals sometimes goes beyond modifying the primary sequence of the enzyme itself. The use of protein or nucleic acid scaffolds to enhance enzyme properties has been reported for applications such as microbial production of chemicals, biosensor development and bioremediation. Key advantages of using these assemblies include optimizing reaction conditions, improving metabolic flux and increasing enzyme stability. This review summarizes recent trends in utilizing genetically encodable scaffolds, developed in line with synthetic biology methodologies, to complement the purposeful deployment of enzymes. Current molecular tools for constructing these synthetic enzyme-scaffold systems are also highlighted.

New developments in RiPP discovery, enzymology and engineering

Covering: up to June 2020Ribosomally-synthesized and post-translationally modified peptides (RiPPs) are a large group of natural products. A community-driven review in 2013 described the emerging commonalities in the biosynthesis of RiPPs and the opportunities they offered for bioengineering and genome mining. Since then, the field has seen tremendous advances in understanding of the mechanisms by which nature assembles these compounds, in engineering their biosynthetic machinery for a wide range of applications, and in the discovery of entirely new RiPP families using bioinformatic tools developed specifically for this compound class. The First International Conference on RiPPs was held in 2019, and the meeting participants assembled the current review describing new developments since 2013. The review discusses the new classes of RiPPs that have been discovered, the advances in our understanding of the installation of both primary and secondary post-translational modifications, and the mechanisms by which the enzymes recognize the leader peptides in their substrates. In addition, genome mining tools used for RiPP discovery are discussed as well as various strategies for RiPP engineering. An outlook section presents directions for future research.

Data-driven rational biosynthesis design: from molecules to cell factories

A proliferation of chemical, reaction and enzyme databases, new computational methods and software tools for data-driven rational biosynthesis design have emerged in recent years. With the coming of the era of big data, particularly in the bio-medical field, data-driven rational biosynthesis design could potentially be useful to construct target-oriented chassis organisms. Engineering the complicated metabolic systems of chassis organisms to biosynthesize target molecules from inexpensive biomass is the main goal of cell factory design. The process of data-driven cell factory design could be divided into several parts: (1) target molecule selection; (2) metabolic reaction and pathway design; (3) prediction of novel enzymes based on protein domain and structure transformation of biosynthetic reactions; (4) construction of large-scale DNA for metabolic pathways; and (5) DNA assembly methods and visualization tools. The construction of a one-stop cell factory system could achieve automated design from the molecule level to the chassis level. In this article, we outline data-driven rational biosynthesis design steps and provide an overview of related tools in individual steps.

Key Challenges in Designing CHO Chassis Platforms

Following the success of and the high demand for recombinant protein-based therapeutics during the last 25 years, the pharmaceutical industry has invested significantly in the development of novel treatments based on biologics. Mammalian cells are the major production systems for these complex biopharmaceuticals, with Chinese hamster ovary (CHO) cell lines as the most important players. Over the years, various engineering strategies and modeling approaches have been used to improve microbial production platforms, such as bacteria and yeasts, as well as to create pre-optimized chassis host strains. However, the complexity of mammalian cells curtailed the optimization of these host cells by metabolic engineering. Most of the improvements of titer and productivity were achieved by media optimization and large-scale screening of producer clones. The advances made in recent years now open the door to again consider the potential application of systems biology approaches and metabolic engineering also to CHO. The availability of a reference genome sequence, genome-scale metabolic models and the growing number of various “omics” datasets can help overcome the complexity of CHO cells and support design strategies to boost their production performance. Modular design approaches applied to engineer industrially relevant cell lines have evolved to reduce the time and effort needed for the generation of new producer cells and to allow the achievement of desired product titers and quality. Nevertheless, important steps to enable the design of a chassis platform similar to those in use in the microbial world are still missing. In this review, we highlight the importance of mammalian cellular platforms for the production of biopharmaceuticals and compare them to microbial platforms, with an emphasis on describing novel approaches and discussing still open questions that need to be resolved to reach the objective of designing enhanced modular chassis CHO cell lines.

Genome Mining as New Challenge in Natural Products Discovery

Drug discovery is based on bioactivity screening of natural sources, traditionally represented by bacteria fungi and plants. Bioactive natural products and their secondary metabolites have represented the main source for new therapeutic agents, used as drug leads for new antibiotics and anticancer agents. After the discovery of the first biosynthetic genes in the last decades, the researchers had in their hands the tool to understand the biosynthetic logic and genetic basis leading to the production of these compounds. Furthermore, in the genomic era, in which the number of available genomes is increasing, genome mining joined to synthetic biology are offering a significant help in drug discovery. In the present review we discuss the importance of genome mining and synthetic biology approaches to identify new natural products, also underlining considering the possible advantages and disadvantages of this technique. Moreover, we debate the associated techniques that can be applied following to genome mining for validation of data. Finally, we review on the literature describing all novel natural drugs isolated from bacteria, fungi, and other living organisms, not only from the marine environment, by a genome-mining approach, focusing on the literature available in the last ten years.

SBOLExplorer: Data Infrastructure and Data Mining for Genetic Design Repositories

This paper describes SBOLExplorer, a system that is used to provide intuitive searching within the SynBioHub genetic design repository. SynBioHub stores genetic constructs encoded in the SBOL data format. These constructs can represent genetic parts, circuits, and sequences. These constructs are often numerous, exist in various states of completeness and documentation, and do not lend themselves to simple searching and discovery. In particular, this paper focuses on improving the search capabilities of SynBioHub. Inspiration is drawn from the techniques used to organize and search over the World Wide Web, a linked data set with many of the same properties of the SBOL data in SynBioHub. SBOLExplorer integrates these methods into SynBioHub's data representation and search, providing significant improvement over the previous search implementation based on pattern-matching.

Novel bioactive natural products from bacteria via bioprospecting, genome mining and metabolic engineering

For over seven decades, bacteria served as a valuable source of bioactive natural products some of which were eventually developed into drugs to treat infections, cancer and immune system-related diseases. Traditionally, novel compounds produced by bacteria were discovered via conventional bioprospecting based on isolation of potential producers and screening their extracts in a variety of bioassays. Over time, most of the natural products identifiable by this approach were discovered, and the pipeline for new drugs based on bacterially produced metabolites started to run dry. This mini-review highlights recent developments in bacterial bioprospecting for novel compounds that are based on several out-of-the-box approaches, including the following: (i) targeting bacterial species previously unknown to produce any bioactive natural products, (ii) exploring non-traditional environmental niches and methods for isolation of bacteria and (iii) various types of 'genome mining' aimed at unravelling genetic potential of bacteria to produce secondary metabolites. All these approaches have already yielded a number of novel bioactive compounds and, if used wisely, will soon revitalize drug discovery pipeline based on bacterial natural products.

Gut Microbiota: Small Molecules Modulate Host Cellular Functions

The human gut metagenome was recently discovered to encode vast collections of biosynthetic gene clusters with diverse chemical potential, almost none of which are yet functionally validated. Recent work elucidates common microbiome-derived biosynthetic gene clusters encoding peptide aldehydes that inhibit human proteases.

Regulation of antibiotic production in Actinobacteria: new perspectives from the post-genomic era

Covering: 2000 to 2018 The antimicrobial activity of many of their natural products has brought prominence to the Streptomycetaceae, a family of Gram-positive bacteria that inhabit both soil and aquatic sediments. In the natural environment, antimicrobial compounds are likely to limit the growth of competitors, thereby offering a selective advantage to the producer, in particular when nutrients become limited and the developmental programme leading to spores commences. The study of the control of this secondary metabolism continues to offer insights into its integration with a complex lifecycle that takes multiple cues from the environment and primary metabolism. Such information can then be harnessed to devise laboratory screening conditions to discover compounds with new or improved clinical value. Here we provide an update of the review we published in NPR in 2011. Besides providing the essential background, we focus on recent developments in our understanding of the underlying regulatory networks, ecological triggers of natural product biosynthesis, contributions from comparative genomics and approaches to awaken the biosynthesis of otherwise silent or cryptic natural products. In addition, we highlight recent discoveries on the control of antibiotic production in other Actinobacteria, which have gained considerable attention since the start of the genomics revolution. New technologies that have the potential to produce a step change in our understanding of the regulation of secondary metabolism are also described.

Plug-and-play metabolic transducers expand the chemical detection space of cell-free biosensors

Cell-free transcription–translation systems have great potential for biosensing, yet the range of detectable chemicals is limited. Here we provide a workflow to expand the range of molecules detectable by cell-free biosensors through combining synthetic metabolic cascades with transcription factor-based networks. These hybrid cell-free biosensors have a fast response time, strong signal response, and a high dynamic range. In addition, they are capable of functioning in a variety of complex media, including commercial beverages and human urine, in which they can be used to detect clinically relevant concentrations of small molecules. This work provides a foundation to engineer modular cell-free biosensors tailored for many applications.

The range of chemicals detectable by cell-free systems is still limited. Here the authors combine metabolic cascades with transcription factor networks to detect small molecules in complex environments.

Computational identification of co-evolving multi-gene modules in microbial biosynthetic gene clusters

The biosynthetic machinery responsible for the production of bacterial specialised metabolites is encoded by physically clustered group of genes called biosynthetic gene clusters (BGCs). The experimental characterisation of numerous BGCs has led to the elucidation of subclusters of genes within BGCs, jointly responsible for the same biosynthetic function in different genetic contexts. We developed an unsupervised statistical method able to successfully detect a large number of modules (putative functional subclusters) within an extensive set of predicted BGCs in a systematic and automated manner. Multiple already known subclusters were confirmed by our method, proving its efficiency and sensitivity. In addition, the resulting large collection of newly defined modules provides new insights into the prevalence and putative biosynthetic role of these modular genetic entities. The automated and unbiased identification of hundreds of co-evolving group of genes is an essential breakthrough for the discovery and biosynthetic engineering of high-value compounds.

BioBits™ Explorer: A modular synthetic biology education kit

Hands-on demonstrations greatly enhance the teaching of science, technology, engineering, and mathematics (STEM) concepts and foster engagement and exploration in the sciences. While numerous chemistry and physics classroom demonstrations exist, few biology demonstrations are practical and accessible due to the challenges and concerns of growing living cells in classrooms. We introduce BioBits™ Explorer, a synthetic biology educational kit based on shelf-stable, freeze-dried, cell-free (FD-CF) reactions, which are activated by simply adding water. The FD-CF reactions engage the senses of sight, smell, and touch with outputs that produce fluorescence, fragrances, and hydrogels, respectively. We introduce components that can teach tunable protein expression, enzymatic reactions, biomaterial formation, and biosensors using RNA switches, some of which represent original FD-CF outputs that expand the toolbox of cell-free synthetic biology. The BioBits™ Explorer kit enables hands-on demonstrations of cutting-edge science that are inexpensive and easy to use, circumventing many current barriers for implementing exploratory biology experiments in classrooms.

Extending the "One Strain Many Compounds" (OSMAC) Principle to Marine Microorganisms

Genomic data often highlights an inconsistency between the number of gene clusters identified using bioinformatic approaches as potentially producing secondary metabolites and the actual number of chemically characterized secondary metabolites produced by any given microorganism. Such gene clusters are generally considered as “silent”, meaning that they are not expressed under laboratory conditions. Triggering expression of these “silent” clusters could result in unlocking the chemical diversity they control, allowing the discovery of novel molecules of both medical and biotechnological interest. Therefore, both genetic and cultivation-based techniques have been developed aimed at stimulating expression of these “silent” genes. The principles behind the cultivation based approaches have been conceptualized in the “one strain many compounds” (OSMAC) framework, which underlines how a single strain can produce different molecules when grown under different environmental conditions. Parameters such as, nutrient content, temperature, and rate of aeration can be easily changed, altering the global physiology of a microbial strain and in turn significantly affecting its secondary metabolism. As a direct extension of such approaches, co-cultivation strategies and the addition of chemical elicitors have also been used as cues to activate “silent” clusters. In this review, we aim to provide a focused and comprehensive overview of these strategies as they pertain to marine microbes. Moreover, we underline how changes in some parameters which have provided important results in terrestrial microbes, but which have rarely been considered in marine microorganisms, may represent additional strategies to awaken “silent” gene clusters in marine microbes. Unfortunately, the empirical nature of the OSMAC approach forces scientists to perform extensive laboratory experiments. Nevertheless, we believe that some computation and experimental based techniques which are used in other disciplines, and which we discuss; could be effectively employed to help streamline the OSMAC based approaches. We believe that natural products discovery in marine microorganisms would be greatly aided through the integration of basic microbiological approaches, computational methods, and technological innovations, thereby helping unearth much of the as yet untapped potential of these microorganisms.

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.

Omics and multi-omics approaches to study the biosynthesis of secondary metabolites in microorganisms

Natural products produced by microorganisms represent the main source of bioactive molecules. The development of high-throughput (omics) techniques have importantly contributed to the renaissance of new antibiotic discovery increasing our understanding of complex mechanisms controlling the expression of biosynthetic gene clusters (BGCs) encoding secondary metabolites. In this context this review highlights recent progress in the use and integration of 'omics' approaches with focuses on genomics, transcriptomics, proteomics metabolomics meta-omics and combined omics as powerful strategy to discover new antibiotics.

An Autoregulated Fine-Tuning Strategy for Titer Improvement of Secondary Metabolites Using Native Promoters in Streptomyces

Streptomycetes are well-known producers of biologically active secondary metabolites. Various efforts have been made to increase productions of these metabolites, while few approaches could well coordinate the biosynthesis of secondary metabolites and other physiological events of their hosts. Here we develop a universal autoregulated strategy for fine-tuning the expression of secondary metabolites biosynthetic gene clusters (BGCs) in Streptomyces species. First, inducible promoters were used to control the expression of secondary metabolites BGCs. Then, the optimal induction condition was determined by response surface model in both dimensions of time and strength. Finally, native promoters with similar transcription profile to the inducible promoter under the optimal condition were identified based on time-course transcriptome analyses, and used to replace the inducible promoter following an elaborate replacement approach. The expression of actinorhodin (Act) and heterogeneous oxytetracycline (OTC) BGCs were optimized in Streptomyces coelicolor using this strategy. Compared to modulating the expression via constitutive promoters, our strategy could dramatically improve the titers of Act and OTC by 1.3- and 9.1-fold, respectively. The autoregulated fine-tuning strategy developed here opens a novel route for titer improvement of desired secondary metabolites in Streptomyces.

Mining prokaryotes for antimicrobial compounds: from diversity to function

The bacterial kingdom provides a major source of antimicrobials that can either be directly applied or used as scaffolds to further improve their functionality in the host. The rapidly increasing amount of bacterial genomic, metabolomic and transcriptomic data offers unique opportunities to apply a variety of approaches to mine for existing and novel antimicrobials. Here, we discuss several powerful mining approaches to identify novel molecules with antimicrobial activity across structurally diverse natural products, including ribosomally synthesized and posttranslationally modified peptides, nonribosomal peptides and polyketides. We not only discuss the direct mining of genomes based on identification of biosynthetic gene clusters, but also describe more advanced and integrative approaches in ecology-based mining, functionality-based mining and mode-of-action-based mining. These efforts are likely to accelerate the discovery and development of novel antimicrobial drugs.

Output ordering and prioritisation system (OOPS): ranking biosynthetic gene clusters to enhance bioactive metabolite discovery

The rapid increase of publicly available microbial genome sequences has highlighted the presence of hundreds of thousands of biosynthetic gene clusters (BGCs) encoding valuable secondary metabolites. The experimental characterization of new BGCs is extremely laborious and struggles to keep pace with the in silico identification of potential BGCs. Therefore, the prioritisation of promising candidates among computationally predicted BGCs represents a pressing need. Here, we propose an output ordering and prioritisation system (OOPS) which helps sorting identified BGCs by a wide variety of custom-weighted biological and biochemical criteria in a flexible and user-friendly interface. OOPS facilitates a judicious prioritisation of BGCs using G+C content, coding sequence length, gene number, cluster self-similarity and codon bias parameters, as well as enabling the user to rank BGCs based upon BGC type, novelty, and taxonomic distribution. Effective prioritisation of BGCs will help to reduce experimental attrition rates and improve the breadth of bioactive metabolites characterized.

Omics-based natural product discovery and the lexicon of genome mining

Genome sequencing and the application of omic techniques are driving many important advances in the field of microbial natural products research. Despite these gains, there remain aspects of the natural product discovery pipeline where our knowledge remains poor. These include the extent to which biosynthetic gene clusters are transcriptionally active in native microbes, the temporal dynamics of transcription, translation, and natural product assembly, as well as the relationships between small molecule production and detection. Here we touch on a number of these concepts in the context of continuing efforts to unlock the natural product potential revealed in genome sequence data and discuss nomenclatural issues that warrant consideration as the field moves forward.

A novel programmable lysozyme-based lysis system in Pseudomonas putida for biopolymer production

Cell lysis is crucial for the microbial production of industrial fatty acids, proteins, biofuels, and biopolymers. In this work, we developed a novel programmable lysis system based on the heterologous expression of lysozyme. The inducible lytic system was tested in two Gram-negative bacterial strains, namely Escherichia coli and Pseudomonas putida KT2440. Before induction, the lytic system did not significantly arrest essential physiological parameters in the recombinant E. coli (ECPi) and P. putida (JBOi) strain such as specific growth rate and biomass yield under standard growth conditions. A different scenario was observed in the recombinant JBOi strain when subjected to PHA-producing conditions, where biomass production was reduced by 25% but the mcl-PHA content was maintained at about 30% of the cell dry weight. Importantly, the genetic construct worked well under PHA-producing conditions (nitrogen-limiting phase), where more than 95% of the cell population presented membrane disruption 16 h post induction, with 75% of the total synthesized biopolymer recovered at the end of the fermentation period. In conclusion, this new lysis system circumvents traditional, costly mechanical and enzymatic cell-disrupting procedures.

AGOS: A Plug-and-Play Method for the Assembly of Artificial Gene Operons into Functional Biosynthetic Gene Clusters

The generation of novel secondary metabolites by reengineering or refactoring biochemical pathways is a rewarding but also challenging goal of synthetic biology. For this, the development of tools for the reconstruction of secondary metabolite gene clusters as well as the challenge of understanding the obstacles in this process is of great interest. The artificial gene operon assembly system (AGOS) is a plug-and-play method developed as a tool to consecutively assemble artificial gene operons into a destination vector and subsequently express them under the control of a de-repressed promoter in a Streptomyces host strain. AGOS was designed as a set of entry plasmids for the construction of artificial gene operons and a SuperCos1 based destination vector, into which the constructed operons can be assembled by Red/ET-mediated recombination. To provide a proof-of-concept of this method, we disassembled the well-known novobiocin biosynthetic gene cluster into four gene operons, encoding for the different moieties of novobiocin. We then genetically reorganized these gene operons with the help of AGOS to finally obtain the complete novobiocin gene cluster again. The production of novobiocin precursors and of novobiocin could successfully be detected by LC-MS and LC-MS/MS. Furthermore, we demonstrated that the omission of terminator sequences only had a minor impact on product formation in our system.

A Protein Interaction Map of the Kalimantacin Biosynthesis Assembly Line

The antimicrobial secondary metabolite kalimantacin (also called batumin) is produced by a hybrid polyketide/non-ribosomal peptide system in Pseudomonas fluorescens BCCM_ID9359. In this study, the kalimantacin biosynthesis gene cluster is analyzed by yeast two-hybrid analysis, creating a protein–protein interaction map of the entire assembly line. In total, 28 potential interactions were identified, of which 13 could be confirmed further. These interactions include the dimerization of ketosynthase domains, a link between assembly line modules 9 and 10, and a specific interaction between the trans-acting enoyl reductase BatK and the carrier proteins of modules 8 and 10. These interactions reveal fundamental insight into the biosynthesis of secondary metabolites. This study is the first to reveal interactions in a complete biosynthetic pathway. Similar future studies could build a strong basis for engineering strategies in such clusters.

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.

Biosynthesis of therapeutic natural products using synthetic biology

Natural products are a group of bioactive structurally diverse chemicals produced by microorganisms and plants. These molecules and their derivatives have contributed to over a third of the therapeutic drugs produced in the last century. However, over the last few decades traditional drug discovery pipelines from natural products have become far less productive and far more expensive. One recent development with promise to combat this trend is the application of synthetic biology to therapeutic natural product biosynthesis. Synthetic biology is a young discipline with roots in systems biology, genetic engineering, and metabolic engineering. In this review, we discuss the use of synthetic biology to engineer improved yields of existing therapeutic natural products. We further describe the use of synthetic biology to combine and express natural product biosynthetic genes in unprecedented ways, and how this holds promise for opening up completely new avenues for drug discovery and production.

Light-Controlled Cell Factories: Employing Photocaged Isopropyl-β-d-Thiogalactopyranoside for Light-Mediated Optimization of lac Promoter-Based Gene Expression and (+)-Valencene Biosynthesis in Corynebacterium glutamicum

Precise control of microbial gene expression resulting in a defined, fast, and homogeneous response is of utmost importance for synthetic bio(techno)logical applications. However, even broadly applied biotechnological workhorses, such as Corynebacterium glutamicum, for which induction of recombinant gene expression commonly relies on the addition of appropriate inducer molecules, perform moderately in this respect. Light offers an alternative to accurately control gene expression, as it allows for simple triggering in a noninvasive fashion with unprecedented spatiotemporal resolution. Thus, optogenetic switches are promising tools to improve the controllability of existing gene expression systems. In this regard, photocaged inducers, whose activities are initially inhibited by light-removable protection groups, represent one of the most valuable photoswitches for microbial gene expression. Here, we report on the evaluation of photocaged isopropyl-β-d-thiogalactopyranoside (IPTG) as a light-responsive control element for the frequently applied tac-based expression module in C. glutamicum In contrast to conventional IPTG, the photocaged inducer mediates a tightly controlled, strong, and homogeneous expression response upon short exposure to UV-A light. To further demonstrate the unique potential of photocaged IPTG for the optimization of production processes in C. glutamicum, the optogenetic switch was finally used to improve biosynthesis of the growth-inhibiting sesquiterpene (+)-valencene, a flavoring agent and aroma compound precursor in food industry. The variation in light intensity as well as the time point of light induction proved crucial for efficient production of this toxic compound.

IMPORTANCE

Optogenetic tools are light-responsive modules that allow for a simple triggering of cellular functions with unprecedented spatiotemporal resolution and in a noninvasive fashion. Specifically, light-controlled gene expression exhibits an enormous potential for various synthetic bio(techno)logical purposes. Before our study, poor inducibility, together with phenotypic heterogeneity, was reported for the IPTG-mediated induction of lac-based gene expression in Corynebacterium glutamicum By applying photocaged IPTG as a synthetic inducer, however, these drawbacks could be almost completely abolished. Especially for increasing numbers of parallelized expression cultures, noninvasive and spatiotemporal light induction qualifies for a precise, homogeneous, and thus higher-order control to fully automatize or optimize future biotechnological applications.

Synthetic biology to access and expand nature's chemical diversity

Bacterial genomes encode the biosynthetic potential to produce hundreds of thousands of complex molecules with diverse applications, from medicine to agriculture and materials. Accessing these natural products promises to reinvigorate drug discovery pipelines and provide novel routes to synthesize complex chemicals. The pathways leading to the production of these molecules often comprise dozens of genes spanning large areas of the genome and are controlled by complex regulatory networks with some of the most interesting molecules being produced by non-model organisms. In this Review, we discuss how advances in synthetic biology--including novel DNA construction technologies, the use of genetic parts for the precise control of expression and for synthetic regulatory circuits--and multiplexed genome engineering can be used to optimize the design and synthesis of pathways that produce natural products.

Taxonomy, Physiology, and Natural Products of Actinobacteria

Actinobacteria are Gram-positive bacteria with high G+C DNA content that constitute one of the largest bacterial phyla, and they are ubiquitously distributed in both aquatic and terrestrial ecosystems. Many Actinobacteria have a mycelial lifestyle and undergo complex morphological differentiation. They also have an extensive secondary metabolism and produce about two-thirds of all naturally derived antibiotics in current clinical use, as well as many anticancer, anthelmintic, and antifungal compounds. Consequently, these bacteria are of major importance for biotechnology, medicine, and agriculture. Actinobacteria play diverse roles in their associations with various higher organisms, since their members have adopted different lifestyles, and the phylum includes pathogens (notably, species of Corynebacterium, Mycobacterium, Nocardia, Propionibacterium, and Tropheryma), soil inhabitants (e.g., Micromonospora and Streptomyces species), plant commensals (e.g., Frankia spp.), and gastrointestinal commensals (Bifidobacterium spp.). Actinobacteria also play an important role as symbionts and as pathogens in plant-associated microbial communities. This review presents an update on the biology of this important bacterial phylum.

Leucanicidin and Endophenasides Result from Methyl-Rhamnosylation by the Same Tailoring Enzymes in Kitasatospora sp. MBT66

The increasing bacterial multidrug resistance necessitates novel drug-discovery efforts. One way to obtain novel chemistry is glycosylation, which is prevalent in nature, with high diversity in both the sugar moieties and the targeted aglycones. Kitasatospora sp. MBT66 produces endophenaside antibiotics, which is a family of (methyl-)rhamnosylated phenazines. Here we show that this strain also produces the plecomacrolide leucanicidin (1), which is derived from bafilomycin A1 by glycosylation with the same methyl-rhamnosyl moiety as present in the endophenasides. Immediately adjacent to the baf genes for bafilomycin biosynthesis lie leuA and leuB, which encode a sugar-O-methyltransferase and a glycosyltransferase, respectively. LeuA and LeuB are the only enzymes encoded by the genome of Kitasatospora sp. MBT66 that are candidates for the methyl-rhamnosylation of natural products, and mutation of leuB abolished glycosylation of both families of natural products. Thus, LeuA and -B mediate the post-PKS methyl-rhamnosylation of bafilomycin A1 to leucanicidin and of phenazines to endophenasides, showing surprising promiscuity by tolerating both macrolide and phenazine skeletons as the substrates. Detailed metabolic analysis by MS/MS based molecular networking facilitated the characterization of nine novel phenazine glycosides 6-8, 16, and 22-26, whereby compounds 23 and 24 represent an unprecedented tautomeric glyceride phenazine, further enriching the structural diversity of endophenasides.