Review Article | Open Access
Ulysses Amancio de Frias, Greicy Kelly Bonifacio Pereira, María-Eugenia Guazzaroni, Rafael Silva-Rocha, "Boosting Secondary Metabolite Production and Discovery through the Engineering of Novel Microbial Biosensors", BioMed Research International, vol. 2018, Article ID 7021826, 11 pages, 2018. https://doi.org/10.1155/2018/7021826
Boosting Secondary Metabolite Production and Discovery through the Engineering of Novel Microbial Biosensors
Bacteria are a source of a large number of secondary metabolites with several biomedical and biotechnological applications. In recent years, there has been tremendous progress in the development of novel synthetic biology approaches both to increase the production rate of secondary metabolites of interest in native producers and to mine and reconstruct novel biosynthetic gene clusters in heterologous hosts. Here, we present the recent advances toward the engineering of novel microbial biosensors to detect the synthesis of secondary metabolites in bacteria and in the development of synthetic promoters and expression systems aiming at the construction of microbial cell factories for the production of these compounds. We place special focus on the potential of Gram-negative bacteria as a source of biosynthetic gene clusters and hosts for pathway assembly, on the construction and characterization of novel promoters for native hosts, and on the use of computer-aided design of novel pathways and expression systems for secondary metabolite production. Finally, we discuss some of the potentials and limitations of the approaches that are currently being developed and we highlight new directions that could be addressed in the field.
Microorganisms have provided a variety of natural products (NPs) or secondary metabolites (SMs) with interesting chemical structures and bioactivities . Typically, bacteria biosynthesize a range of distinct molecules, and many of them present remarkable biological activities acting as bioregulators, quorum-sensing/signaling molecules, and antimicrobial drugs . However, the preponderance of NP molecules with clinical relevance was derived from Gram-positive bacteria, highlighting the Streptomyces genus . Although many hundred thousand different NPs have been described (Dictionary of Natural Products 19.2, Copyright © 2011 Taylor & Francis Group), those molecules arising from four generic classes of biosynthetic systems have been reported most frequently. These are the (i) polyketides (PK), (ii) nonribosomal peptides (NRPs), (iii) isoprenoids, and (iv) shikimate derivatives [4–6]. The core structures biosynthesized by these four systems are generally defined as superimposed “scaffolds” whose “tailoring” modifications are implemented. These tailoring reactions modify the final structures of NPs by multiple mechanisms, including oxidation/reduction, macrocyclization, halogenation, glycosylation, acylation, phosphorylation, sulfation, methylation, and other chemical transformations .
While Gram-positive bacteria are without a doubt the most preeminent group for the isolation of SMs, it is important to notice that Gram-negative bacteria also represent an exciting group for biotechnological prospection. For instance, many clinically relevant NPs molecules produced by Gram-negative bacteria can be found in the Minimum Information about a Biosynthetic Gene cluster (MIBiG) database . MIBiG implements robust and standard annotations for biosynthetic gene clusters (BGCs) and their molecules. NRPs and PKs are the most studied group of NPs in bacteria [9, 10]. Both form complex and diverse families of compounds with therapeutic applicability, such as molecules presenting cytotoxic/antitumor, antibacterial, antifungal, antimicrobial, cholesterol-lowering, immunosuppressant, and other activities. Briefly, NRPs and PKs are biosynthesized in modules by enzymes known as nonribosomal peptide synthetases and polyketide synthases, respectively . Below, we present recent advances in synthetic biology approaches toward SMs production in bacteria.
2. Synthetic Biology Application for the Design of Novel Biosensors
Recent years have been particularly productive for the generation of tools and approaches to enhance SM synthesis in bacteria. Under the umbrella of synthetic biology, many works have focused on the reconstruction of biosynthetic gene clusters in native or heterologous hosts or on the engineering of the regulatory network of the host itself, allowing an increasing expression of the genes of interest. These approaches have been extensively used for both Gram-positive and Gram-negative bacteria and have been expanded to nonmodel organisms through the generation of new genetic tools, as presented below. In terms of engineering or rewiring of the regulatory networks controlling biosynthetic gene clusters, there has been a tremendous effort to engineer new inducible systems in bacteria to use these elements either as control systems for gene pathway expression or as biosensors to monitor the production rate of the compounds of interest . In this sense, Figure 1 represents schematically some of the main approaches developed recently, many of which are discussed below. The classical approach to enhance the production of a biosynthetic gene cluster is to place these elements under the control of a strong regulatory element such as the T7 RNA polymerase/T7 promoter system , which is highly used for large-scale protein production in Escherichia coli. Using this approach, Ross and coworkers captured a 34 kb gene cluster encoding the synthesis of an alterochromide lipopeptide from Pseudoalteromonas piscicida and expressed it under the control of a T7 expression system in E. coli . This approach is particularly useful since the T7-based expression system allows an orthogonal expression device that can be introduced into a number of host strains , eliminating the necessity of redesigning native regulatory elements from the original host. Also, T7-based systems can be easily adapted for cell-free setups , such as the one generated for in vitro production of SM in Streptomyces . Additionally, the use of strategies aiming at the assembly of artificial gene clusters could enhance even more the production of compounds of interest. This is the case of the AGOS (Artificial Gene Operon assembly System) presented by Basitta and coworkers (2017). This strategy allows not only the optimization of the pathway of interest, but also the introduction of gene diversity that could lead to the production of SM with different chemical modifications .
When the engineering of a particular host is intended, a frequent limitation is the lack of efficient genetic tools and induction systems essential for the success of the circuit of interest. In this sense, Phelan and coworkers (2017) have recently reported a set of new vectors for use in Streptomyces venezuelae aiming at the enhanced production of SMs . By the same token, DeLorenzo and colleagues (2017) performed an extensive characterization of genetic parts related to fluorescent reporter systems, inducible systems, and biosensors for utilization in Rhodococcus opacus . In that work, the authors were able to optimize inducible systems responsive to arabinose (Pbad), anhydrotetracycline (Ptet), and acetamide (Pacet), while also combining genome mining and transcriptomic analysis to identify endogenous expression systems responsible for compounds such as phenol . In fact, genome mining combined with transcriptomic analysis seems to be a very interesting way to find novel expression devices for use in synthetic biology projects in nonmodel organisms, and similar attempts have been reported for Streptomyces [20, 21]. In a very elegant report, Li and coworkers (2017) applied a statistical analysis to investigate the optimal condition for SM production in Streptomyces coelicolor. After finding the optimal conductions, the authors combined genome mining and transcriptomic profiles to identify native promoters with expression dynamics similar to those required to obtain the optimal SM production. By replacing the inducible system for the nearly identified native promoters, the authors generated stable strains producing enhanced amounts of the metabolites of interest . Another example is presented by Khalid and collaborators (2017), who used a reassembled terpenoid-production pathway from Streptomyces initially placed under the control of the native regulator Fur22 and lately redesigned with native promoters from the primary metabolism of the bacterium, resulting in an optimized production strain . These works thus demonstrate the power of combining approaches (statistical, induction, and mining) to enhance SM production in nonmodel organisms.
Once native promoters can be identified by a series of approaches, achieving the optimal production usually requires fine-tuning of the expression system used. This scenario makes the availability of sets of promoters with varying strengths imperative, allowing thus the construction of the circuits of interest. With this aim in mind, Yang and colleagues (2017) used promoter design together with random mutagenesis and selection to construct novel broad-host range promoters able to trigger gene expression in E. coli, Bacillus subtilis, and Saccharomyces cerevisiae . This elegant work opened a new venue of possibilities to construct universal synthetic clusters that could be tested in several Gram-negative and Gram-positive hosts, and even across life kingdoms. While the work of Yang et al. provided a limited number of promoter variants analyzed by classical approaches, Rohlhill et al. (2017) used Fluorescence Activated Cell Sorting (FACS) coupled to next-generation sequencing (NGS) technologies to identify enhanced promoter variants generated by random mutagenesis of the formaldehyde-inducible promoter of E. coli . This Sort-Seq technology could expand the existing capabilities to experimentally address novel promoters for SM-production engineering. Alternatively, novel computational approaches have been developed recently that allow in silico design of regulated promoters in E. coli [25, 26]. In combination with novel experimental approaches for the construction of combinatorial promoters with complex behaviors  and with models of transcriptional-factor/promoter interaction , these technologies could drastically simplify the way novel expression systems are engineered. However, a very drastic alternative for single-input promoter induction in bacteria has been the use of a mutated version of the CRISPR/Cas9 system not able to cleave DNA. In these systems, a nuclease-deficient Cas9 variant is used to block promoter activity by expressing a guide-RNA targeting RNAP binding site into the promoter, or by activating gene expression through the fusion of an RNAP subunit to Cas9 . In fact, this strategy has been used to enhance the production of the lipodepsipeptide WAP-8294A in Lysobacter enzymogenes OH11 .
While tremendous progress in the identification/optimization of promoters has been achieved in the past years, there has also been an intensive search for novel transcriptional factors able to recognize new molecules of interest. As represented in Figure 1, these approaches have been based on (i) the design of biosensors by simply implementing an endogenous/heterologous regulator into a host of interest, (ii) the random or rational engineering of regulator variants to change the inducer specificity, or (iii) the reconstruction of novel transcriptional factors by fusing unrelated protein modules, generating new-to-nature, fully synthetic inducible systems. In the first case, Liu and coworkers (2017) used a Lys-type regulator named ShiR from Corynebacterium glutamicum to develop a shikimic acid biosensor in this organism. The use of this new biosensor in combination with FACS allowed optimizing the expression of the tktA gene, encoding a transketolase . But while Liu et al. used a regulator able to recognize the compound of interest, there is currently a deficiency in the availability of regulators responsible for compounds of interest. In these cases, an alternative is to engineer by random mutagenesis or rational design novel regulators with improved response to a particular compound, and several examples have been reported over the years . Of particular interest, Kasey and colleagues (2017) used the crystal structure of the TetR-type MphR regulator to select five candidate residues for saturation mutagenesis. Upon selection based on FACS, the authors were able to identify several regulator variants including a new pikromycin responsive transcriptional factor . Again, while this approach allows the improvement in sensitivity toward suboptimal inducers, it still is restricted to compounds structurally similar to those recognized by the transcriptional factor of interest. In light of all the improvement on the engineering of synthetic regulators with specific ligand of DNA-binding selectivity, it is important to notice that the final sensitivity of the circuit is dependent not only on the sensitivity of the ligand-domain engineered, but also on the arrangement of DNA-binding sites existing in the target promoter . Another radical approach is to construct novel transcriptional factors from the assembly of protein modules of interest. In this context, Younger and collaborators (2017) fused several zinc-finger DNA-binding modules to a maltose binding protein (MBP) domain to create novel synthetic regulators responsive to maltose . In this context, this approach could be extended to other ligands of interest and would strongly facilitate the generation of novel inducible regulatory systems with different DNA- and ligand-binding specificities. In an even more drastic approach, Chang and colleagues (2017) fused the well-known DNA-binding domains (from LexA and CadC) to single-domain VHH (variable domains of camelid heavy chain only) antibodies to construct both cytosolic and transmembrane receptors for caffeine . Once more, the potential of such technologies is tremendous as it allows the coupling of VHH domains (selected either naturally or from techniques such as phage display) to construct functional biosensors for molecules that could be internalized by the cell or that could be present only on the extracellular medium. While the progress on the engineering of novel transcriptional factors has been remarkable, it is important to notice that the single-cell behavior of the resultant expression system is often neglected. This is particularly important since many natural responsive systems can display a graded or bimodal expression behavior in single cells depending on the arrangement of the genetic circuit used .
Finally, another potential approach to construct tailored biosensors is to use natural or engineered trans-acting regulatory RNAs. In this sense, Jang et al. (2017) used SELEX (Systematic Evolution of Ligands by EXponential Enrichment) to construct novel riboswitches responsible for the flavonoid naringenin. This work is particularly important since the authors provided a defined aptamer design for optimal arrangement of the regulatory elements . Using a different approach, Sen and coworkers (2017) used computational models of base pairing to construct temperature responsive trans-regulatory RNAs . This type of regulatory element is particularly useful since many industrial conditions are prone to changes in temperature, and these elements could be used to provide fine-tuning for engineered pathways in bacteria. Yet, as the authors reported differences between the predicted and the experimental behaviors of the engineered structures, there is still room for improvements of the computational models used. In this sense, development of efficient in silico algorithms should permit creating functional RNA thermometers.
3. Metagenomics as a Source of Genetic Parts for SM Production in Bacteria
Metagenomics allows searching in the huge biochemical array present in the genomes of microorganisms found in environmental samples, having access to most of the genetic material of bacteria that are recalcitrant to cultivation . In this sense, novel functional gene clusters involved in the production of bioactive compounds can be identified by directly cloning or sequencing the DNA retrieved from the microbial community inhabitants of an ecosystem of interest (Figure 2) . In the activity-based metagenomic approach, the construction and subsequent screening of metagenomic libraries allow identification of the targeted genes encoding the desired activities . Thus, large-insert libraries, usually constructed in cosmids, fosmids, or BACs (bacterial artificial chromosomes), would allow the recovery of complete biosynthetic pathways or the functional expression of large multienzyme clusters (as in the case of nonribosomal peptide synthetases (NRPS), polyketide synthases (PKS), and terpene synthases, to name a few) . Normally, PKS type I and NRPS’s pathways are organized in large assembly operons going from 20 kb to 100 kb in length . Accordingly, several examples in the literature show that metagenomics has been successfully applied for the identification of novel pathways coding for bioactive compounds in diverse environments [44–49]. Although the functional-based approach allows obtaining completely original genes in an independent-sequence way, numerous studies using next-generation sequencing techniques and subsequent bioinformatic mining of the metagenomes have also achieved novel gene clusters involved in secondary metabolites production [50–53].
In this sense, metagenomics has become a proper methodological tool to improve and expand NPs discovery from natural sources, contributing with novel genetic parts (such as structural genes and regulatory sequences), acting as an important contributor to the expansion of the synthetic biology toolbox (Figure 2) [54, 55]. Secondary metabolite genes are organized in clusters or operons leading to a well-ordered biosynthesis of molecules in multiple sequential steps by a set of functionally interconnected enzymes . Novel combinations and rewiring of these enzymes performing a huge repertoire of biochemical transformations, along with proper modulation of catalytic synergy, would permit the design and generation of innovative complex bioactive molecules. For instance, Smanski and coauthors (2014) developed an approach exploiting the modularity of a refactored Klebsiella oxytoca nitrogen fixation gene cluster that led to the functional optimization of the operon by combinatorial design and assembly of 103 biological parts . Also, a study reported a plug-and-play pathway refactoring workflow using expression cassettes for high-throughput pathway construction in E. coli and S. cerevisiae . As a proof of principle, a total of 96 pathways for combinatorial carotenoid biosynthesis were built successfully . In an elegant study, Freestone and collaborators (2017) discovered a novel phosphonoacetic acid by pathway refactoring of a gene cluster from Streptomyces sp. strain NRRL F-525 using for expression the production host S. lividans . In parallel, efforts are conducted for the optimization of biosynthesis of compounds through the creation of algorithms considering a plethora of genetic and nongenetic factors [60, 61].
On the other hand, a current significant limitation in recovery of natural products from metagenomes is the use of E. coli as a host, a Gram-negative bacterium that is distant phylogenetically from microbes that are native producers of NPs . This way, the strongest producers of diverse secondary metabolites broadly used in several therapeutic applications are the Gram-positive bacteria belonging to the phylum Actinobacteria [63–65]. Restrictions related to codon usage, transporters, regulatory signals, proper folding of proteins, and cofactor availability, as well as limited precursor availability for secondary metabolite synthesis, are some of the main constraints that restrict E. coli usage as a host for NPs discovery in metagenomic libraries . However, a considerable number of efforts involving systems and synthetic biology approaches along with metabolic engineering are already in progress to transform Actinobacteria members in sophisticated heterologous expression platforms for NP biosynthesis. For instance, different strains of S. coelicolor have been genetically engineered to enhance secondary metabolite expression, involving deletions in endogenous gene clusters , removal of transcriptional factors , or modifications of native promoters . Moreover, systematic minimization of the genome of the industrial microorganism Streptomyces avermitilis was carried out to remove nonessential genes, leading to the creation of a versatile model host for heterologous expression of NPs . In addition, different genetic tools for genetic manipulation and genome editing (i.e., the prominent CRISPR/Cas system) were already developed in Actinobacteria [69, 71–76]. In conclusion, while there are still several limitations that need to be overcome to optimize these bacteria as effective host strains for the screening of metagenome libraries, the work at present including synthetic biology approaches for chassis engineering and molecular tools development seems to be certainly promising.
4. Potential of NPs Originating from Gram-Negative Bacteria
As stated before, while Gram-positive bacteria have the highest potential for SM production, this topic has been extensively reviewed elsewhere . Additionally, one of the main advantages of using Gram-negative bacteria in comparison to Gram-positive is the abundant portfolio of genetic tools currently available, especially those for the metabolically versatile bacterium Pseudomonas putida . Therefore, we focus here on the remarkable potential of biosynthetic gene clusters found in Gram-negative bacteria and on the metabolic engineering of SM production in these organisms. In this sense, the Burkholderia genus has a powerful enzymatic machinery for the biosynthesis of many distinct natural products with clinical interest. Furthermore, after Actinobacteria, Burkholderia presents the second highest percentage of clusters related to the biosynthesis of PKS and NRPS molecules . The genus Burkholderia is cosmopolitan and has been isolated from the most diverse types of environments, from soil and water to the human lung . This genus comprises more than 90 species, according to the German Collection of Microorganisms and Cell Cultures (DSMZ) database. Considering its potential for NPs biosynthesis, several studies have demonstrated that the Burkholderia genera are able to produce important molecules such as rhizoxin , bongkrekic acid , thailanstatin , burkholdac , spliceostatin , thailandamide , bactobolin , and gladiolin  (Figure 3). Two interesting examples of NPs isolated from Burkholderia are burkholdacs and gladiolin. The isolation of the bicyclic depsipeptide burkholdacs A and B was reported by Biggins (2011) as histone deacetylase (HDAC) inhibitors. The burkholdacs were identified as a hybrid NRP/PK; these molecules were obtained through overexpression of a transcription factor associated with gene clusters in B. thailandensis E264 . Recently, Song et al. (2017)  reported the identification of gladiolin from B. gladioli, a compound molecularly comparable to the unstable antibiotic etnangien [89, 90]. Like etnangien, gladiolin inhibits RNA polymerase, providing an antibacterial activity against Mycobacterium tuberculosis. Moreover, purified gladiolin was tested against ESKAPE panel of pathogens and showed also a moderate activity against methicillin-resistant Staphylococcus aureus (MRSA) . In addition to Burkholderia, Pseudomonas is also a cosmopolitan microorganism and possesses the ability to biosynthesize a wide range of specific metabolites, emphasizing the production of NRP. Many of these NRPs showed significant biological activities; the following antimicrobials can be cited as examples: cichofactin , tolaasin [92–95], sessilin [96, 97], kalimantacin [98–100], obafluorin [101, 102], arthrofactin , xantholysin , poaeamide [105, 106], and WLIP [107–110]. In this sense, while Gram-negative bacteria have been primarily used as hosts for the assembly of novel biosynthetic pathways, still there is a tremendous potential for the screening and production of novel bioactive molecules from these organisms.
5. Metabolic Engineering of Gram-Negative Bacteria for SM Production
Over the past years, several groups have worked on the metabolic engineering of SM production in bacteria. In this sense, E. coli is one of the most characterized Gram-negative bacteria and many strategies have been developed for the genetic manipulation and engineering of this organism. Since the success of the first ever genetically modified E. coli in 1973, this bacterium became the pioneer in the field of genetic engineering . One interesting example is the use of cocultures of E. coli for the producing of flavan-3-ols, a subclass of flavonoid molecules, which have broad pharmaceutical applications. This approach produced a 970-fold improvement when compared to previous attempts, and it allowed the optimization of diverse factors such as carbon source, induction temperature, induction point, inoculation ratio, and strain choice . Also, the heterologous expression of carotenoid genes from Pantoea ananatis in E. coli produced great amounts of zeaxanthin , a carotenoid synthesized by some plants, bacteria, and fungi , used against age-related macular degeneration and also in the food industry [115, 116]. For this, the authors used the tunable intergenic regions approach to coordinate the expression of the crtY and crtZ genes . Yet, genes related to the production of myrcene, an acyclic monoterpene, are also being customized in E. coli strains . Myrcene, a monoterpene compound, has been considered as a starting material for the synthesis of more complex compounds, and it is utilized in flavors, fragrances, cosmetics, vitamins, and pharmaceuticals . Through the heterologous expression of the mevalonate (MVA) pathway, the level of myrcene increased 34 times (58.19 ± 12.13 mg/L) . Additionally, recently, the US Department of Energy has listed the glutamate derivate 2-pyrrolidone as an important C4 “Top Value-Added Chemical from Biomass” . 2-Pyrrolidone is a high-value product considering its great commercial applicability. It can be used in ring-opening polymerization to produce nylon-4, an enhanced nylon type fiber with more thermal stability and hydrophilicity than its precursors. With that in mind, a group from California has engineered a recombinant E. coli strain capable of producing 2-pyrrolidone using glutamate as a substrate . To achieve that, two ORFs of the type I PK gene clusters were first identified by in silico analysis, both predicted to be AMP-dependent synthetases. Recombinant E. coli expressing a glutamate decarboxylase and one of the synthetases showed an improvement in the 2-pyrrolidone production, with an efficiency of 25% . Still, a coexpression method to produce trans-resveratrol in E. coli was put forward by Wang et al. (2017) . Resveratrol is a secondary metabolite, member of the stilbene family found in a wide range of plant sources , aromatherapy products, and dietary supplements. Stilbenes are being used in humans for the prevention of cancer, heart diseases, and neurodegenerative diseases .
In addition to E. coli, P. putida has also been quite used in metabolic engineering. P. putida is a Gram-negative bacterium that metabolizes a wide range of natural and synthetic organic compounds, and this competence prompted many studies to use P. putida as a biocatalytic agent in the industrial and environmental area [124, 125]. Considering that, Simm et al. (2016) published a study in which they transformed P. putida with two genes from E. coli, encoding active GGDEF and EAL domains, which are related to c-di-GMP production and degradation, respectively . The P. putida mutants were able to control biofilm formation according to specific catalytic needs, for example, for biodegradation of the environmental pollutant 1-chlorobutane. The authors showed that, by adding cyclohexanone to the culture medium, the secondary metabolite derived from haloalkane increased twice in the P. putida biofilm forming cells when compared to the planktonic cells forms .
6. Future Perspectives
As presented here, bacteria from several groups have the gene clusters for the production of secondary metabolites with potential applications in biomedicine. With the advance of postgenomic tools, there has been tremendous progress in the development of novel technologies (i) to engineer natural produces of bioactive compounds to increase productivity, (ii) to reassemble novel biosynthetic pathways into native or heterologous hosts, (iii) to mine novel clusters from metagenomes, and (iv) to monitor/discover novel metabolites using biosensors. It is important to notice that, with the advent of synthetic biology, a number of computational tools and approaches have emerged, which allowed the design of novel regulatory elements and pathways for SM production. It is reasonable to think that using strong computational tools more and more should become routine in the field, and this should have a remarkable impact in the area by allowing a more accurate design or novel pathways, speeding up the process of SM discovery. Additionally, novel genetic tools are continually being produced, and their utilization in bacterial species lacking an efficient genetic toolbox should allow the exploitation of novel microorganisms and develop their full potential. By the same token, metagenomic approaches hold potential to provide novel genetic parts either for the reprogramming of bacteria for SM production or as modules for the assembly of synthetic gene clusters, and these methodologies should be further addressed in the future. Finally, all the aforementioned improvements once coupled with high-throughput screening and engineering protocols should permit a strong increase in the SM discovery rate, allowing the identification of novel bioactive molecules.
Conflicts of Interest
The authors declare that there are no conflicts of interest regarding the publication of this paper.
R. Silva-Rocha and M.-E. Guazzaroni were supported by the Young Investigator Award of the São Paulo Research Foundation (FAPESP, Awards nos. 2012/22921-8 and 2015/04309-1, resp.). The authors would like to thank the lab members for their insightful discussions on this work.
- B. Ruiz, A. Chávez, A. Forero et al., “Production of microbial secondary metabolites: Regulation by the carbon source,” Critical Reviews in Microbiology, vol. 36, no. 2, pp. 146–167, 2010.
- V. L. Challinor and H. B. Bode, “Bioactive natural products from novel microbial sources,” Annals of the New York Academy of Sciences, vol. 1354, no. 1, pp. 82–97, 2015.
- D. J. Newman and G. M. Cragg, “Natural products as sources of new drugs from 1981 to 2014,” Journal of Natural Products, vol. 79, no. 3, pp. 629–661, 2016.
- D. Schwarzer, R. Finking, and M. A. Marahiel, “Nonribosomal peptides: from genes to products,” Natural Product Reports, vol. 20, no. 3, pp. 275–287, 2003.
- B. S. Moore and C. Hertweck, “Biosynthesis and attachment of novel bacterial polyketide synthase starter units,” Natural Product Reports, vol. 19, no. 1, pp. 70–99, 2002.
- B. M. Lange, T. Rujan, W. Martin, and R. Croteau, “Isoprenoid biosynthesis: The evolution of two ancient and distinct pathways across genomes,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 97, no. 24, pp. 13172–13177, 2000.
- C. K. Savile, J. M. Janey, E. C. Mundorff et al., “Biocatalytic asymmetric synthesis of chiral amines from ketones applied to sitagliptin manufacture,” Science, vol. 329, no. 5989, pp. 305–309, 2010.
- MH. Medema, R. Kottmann, P. Yilmaz, M. Cummings, JB. Biggins, and K. Blin, “Minimum Information about a Biosynthetic Gene cluster,” Nat Chem Biol, vol. 11, no. 9, pp. 625–31, 2015.
- J. A. Payne, M. Schoppet, M. H. Hansen, and M. J. Cryle, “Diversity of nature's assembly lines-recent discoveries in non-ribosomal peptide synthesis,” Molecular BioSystems, vol. 13, no. 1, pp. 9–22, 2016.
- L. Du and L. Lou, “PKS and NRPS release mechanisms,” Natural Product Reports, vol. 27, no. 2, pp. 255–278, 2010.
- C. Liu, B. Zhang, Y. Liu, K. Q. Yang, and S. J. Liu, “New Intracellular Shikimic Acid Biosensor for Monitoring Shikimate Synthesis in Corynebacterium glutamicum,” ACS Synth Biol, vol. 7, no. 2, pp. 591–601, 2017.
- S. Tabor and C. C. Richardson, “A bacteriophage T7 RNA polymerase/promoter system for controlled exclusive expression of specific genes.,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 82, no. 4, pp. 1074–1078, 1985.
- A. C. Ross, L. E. S. Gulland, P. C. Dorrestein, and B. S. Moore, “Targeted capture and heterologous expression of the pseudoalteromonas alterochromide gene cluster in escherichia coli represents a promising natural product exploratory platform,” ACS Synthetic Biology, vol. 4, no. 4, pp. 414–420, 2015.
- K. Terpe, “Overview of bacterial expression systems for heterologous protein production: from molecular and biochemical fundamentals to commercial systems,” Applied Microbiology and Biotechnology, vol. 72, no. 2, pp. 211–222, 2006.
- D. Schwarz, F. Junge, F. Durst et al., “Preparative scale expression of membrane proteins in Escherichia coli-based continuous exchange cell-free systems.,” Nature Protocols, vol. 2, no. 11, pp. 2945–2957, 2007.
- S. J. Moore, H.-E. Lai, H. Needham, K. M. Polizzi, and P. S. Freemont, “Streptomyces venezuelae TX-TL – a next generation cell-free synthetic biology tool,” Biotechnology Journal, vol. 12, no. 4, Article ID 1600678, 2017.
- P. Basitta, L. Westrich, M. Rösch, A. Kulik, B. Gust, and A. K. Apel, “AGOS: A Plug-and-Play Method for the Assembly of Artificial Gene Operons into Functional Biosynthetic Gene Clusters,” ACS Synthetic Biology, vol. 6, no. 5, pp. 817–825, 2017.
- R. M. Phelan, D. Sachs, S. J. Petkiewicz et al., “Development of Next Generation Synthetic Biology Tools for Use in Streptomyces venezuelae,” ACS Synthetic Biology, vol. 6, no. 1, pp. 159–166, 2017.
- D. M. DeLorenzo, W. R. Henson, and T. S. Moon, “Development of Chemical and Metabolite Sensors for,” ACS Synthetic Biology, vol. 6, no. 10, pp. 1973–1978, 2017.
- S. Li, J. Wang, W. Xiang, K. Yang, Z. Li, and W. Wang, “An Autoregulated Fine-Tuning Strategy for Titer Improvement of Secondary Metabolites Using Native Promoters in Streptomyces,” ACS Synthetic Biology, vol. 7, no. 2, pp. 522–530, 2018.
- Y. Q. Sun, T. Busche, C. Rückert et al., “Development of a Biosensor Concept to Detect the Production of Cluster-Specific Secondary Metabolites,” ACS Synthetic Biology, vol. 6, no. 6, pp. 1026–1033, 2017.
- A. Khalid, H. Takagi, S. Panthee et al., “Development of a Terpenoid-Production Platform in,” ACS Synthetic Biology, vol. 6, no. 12, pp. 2339–2349, 2017.
- S. Yang, Q. Liu, Y. Zhang, G. Du, J. Chen, and Z. Kang, “Construction and Characterization of Broad-Spectrum Promoters for Synthetic Biology,” ACS Synthetic Biology, vol. 7, no. 1, pp. 287–291, 2017.
- J. Rohlhill, N. R. Sandoval, and E. T. Papoutsakis, “Sort-Seq Approach to Engineering a Formaldehyde-Inducible Promoter for Dynamically Regulated Escherichia coli Growth on Methanol,” ACS Synthetic Biology, vol. 6, no. 8, pp. 1584–1595, 2017.
- G. R. Amores, M.-E. Guazzaroni, and R. Silva-Rocha, “Engineering Synthetic cis-Regulatory Elements for Simultaneous Recognition of Three Transcriptional Factors in Bacteria,” ACS Synthetic Biology, vol. 4, no. 12, pp. 1287–1294, 2015.
- M. E. Guazzaroni and R. Silva-Rocha, “Expanding the Logic of Bacterial Promoters Using Engineered Overlapping Operators for Global Regulators,” ACS Synthetic Biology, vol. 3, no. 9, pp. 666–675, 2014.
- L. M. O. Monteiro, L. M. Arruda, and R. Silva-Rocha, Emergent Properties in Complex Synthetic Bacterial Promoters, ACS synthetic biology, 2017.
- A. A. Mannan, D. Liu, F. Zhang, and D. A. Oyarzún, “Fundamental Design Principles for Transcription-Factor-Based Metabolite Biosensors,” ACS Synthetic Biology, vol. 6, no. 10, pp. 1851–1859, 2017.
- D. Bikard, W. Jiang, P. Samai, A. Hochschild, F. Zhang, and L. A. Marraffini, “Programmable repression and activation of bacterial gene expression using an engineered CRISPR-Cas system,” Nucleic Acids Research, vol. 41, no. 15, pp. 7429–7437, 2013.
- L. Yu, W. Su, P. D. Fey, F. Liu, and L. Du, “Yield Improvement of the Anti-MRSA Antibiotics WAP-8294A by CRISPR/dCas9 Combined with Refactoring Self-Protection Genes in,” ACS Synthetic Biology, vol. 7, no. 1, pp. 258–266, 2017.
- T. C. Galvão and V. De Lorenzo, “Transcriptional regulators à la carte: Engineering new effector specificities in bacterial regulatory proteins,” Current Opinion in Biotechnology, vol. 17, no. 1, pp. 34–42, 2006.
- C. M. Kasey, M. Zerrad, Y. Li, T. A. Cropp, and G. J. Williams, “Development of Transcription Factor-Based Designer Macrolide Biosensors for Metabolic Engineering and Synthetic Biology,” ACS Synthetic Biology, vol. 7, no. 1, pp. 227–239, 2017.
- R. Silva-Rocha and V. De Lorenzo, “Broadening the signal specificity of prokaryotic promoters by modifying cis-regulatory elements associated with a single transcription factor,” Molecular BioSystems, vol. 8, no. 7, pp. 1950–1957, 2012.
- A. K. D. Younger, N. C. Dalvie, A. G. Rottinghaus, and J. N. Leonard, “Engineering Modular Biosensors to Confer Metabolite-Responsive Regulation of Transcription,” ACS Synthetic Biology, vol. 6, no. 2, pp. 311–325, 2017.
- H. J. Chang, P. Mayonove, A. Zavala et al., “A Modular Receptor Platform To Expand the Sensing Repertoire of Bacteria,” ACS Synthetic Biology, vol. 7, no. 1, pp. 166–175, 2017.
- R. Silva-Rocha and V. de Lorenzo, “Stochasticity of TOL plasmid catabolic promoters sets a bimodal expression regime in Pseudomonas putida mt-2 exposed to m-xylene,” Molecular Microbiology, vol. 86, no. 1, pp. 199–211, 2012.
- S. Jang, S. Jang, Y. Xiu et al., “Development of Artificial Riboswitches for Monitoring of Naringenin,” ACS Synthetic Biology, vol. 6, no. 11, pp. 2077–2085, 2017.
- S. Sen, D. Apurva, R. Satija, D. Siegal, and R. M. Murray, “Design of a Toolbox of RNA Thermometers,” ACS Synthetic Biology, vol. 6, no. 8, pp. 1461–1470, 2017.
- L. Fernández-Arrojo, M. E. Guazzaroni, N. López-Cortés, A. Beloqui, and M. Ferrer, “Metagenomic era for biocatalyst identification,” Current Opinion in Biotechnology, vol. 21, no. 6, pp. 725–733, 2010.
- M. E. Guazzaroni, A. Beloqui, J. M. Vieites, and Y. Al-ramahi, “Metagenomic Mining of Enzyme Diversity,” in Handbook of Hydrocarbon and Lipid Microbiology, pp. 2911–2927, Springer, Berlin, Heidelberg, Germany, 2010.
- L. F. Alves, R. Silva-Rocha, and M. E. Guazzaroni, “Enhancing metagenomic approaches through synthetic biology,” in Functional Metagenomics: Tools and Applications, T. Charles, M. Liles, and A. Sessitsch, Eds., Springer, Cham, 2017, https://link.springer.com/chapter/10.1007/978-3-319-61510-3_5#citeas.
- C. Hertweck, “The biosynthetic logic of polyketide diversity,” Angewandte Chemie International Edition, vol. 48, no. 26, pp. 4688–4716, 2009.
- J. Fu, X. Bian, S. Hu et al., “Full-length RecE enhances linear-linear homologous recombination and facilitates direct cloning for bioprospecting,” Nature Biotechnology, vol. 30, no. 5, pp. 440–446, 2012.
- A. Felczykowska, A. Dydecka, M. Bohdanowicz et al., “The use of fosmid metagenomic libraries in preliminary screening for various biological activities,” Microbial Cell Factories, vol. 13, no. 1, article no. 105, 2014.
- H. A. Iqbal, J. W. Craig, and S. F. Brady, “Antibacterial enzymes from the functional screening of metagenomic libraries hosted in Ralstonia metallidurans,” FEMS Microbiology Letters, vol. 354, no. 1, pp. 19–26, 2014.
- S. A. Jackson, E. Borchert, F. O'Gara, and A. D. Dobson, “Metagenomics for the discovery of novel biosurfactants of environmental interest from marine ecosystems,” Current Opinion in Biotechnology, vol. 33, pp. 176–182, 2015.
- C. J. Guo, F. Y. Chang, T. P. Wyche et al., “Discovery of Reactive Microbiota-Derived Metabolites that Inhibit Host Proteases,” Cell, vol. 168, no. 3, pp. 517–526.e18, 2017.
- J. J. Banik and S. F. Brady, “Recent application of metagenomic approaches toward the discovery of antimicrobials and other bioactive small molecules,” Current Opinion in Microbiology, vol. 13, no. 5, pp. 603–609, 2010.
- Z. Feng, D. Kallifidas, and S. F. Brady, “Functional analysis of environmental DNA-derived type II polyketide synthases reveals structurally diverse secondary metabolites,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 108, no. 31, pp. 12629–12634, 2011.
- F. Y. Chang and S. F. Brady, “Discovery of indolotryptoline antiproliferative agents by homology-guided metagenomic screening,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 110, no. 7, pp. 2478–2483, 2013.
- R. A. Cacho, Y. Tang, and Y.-H. Chooi, “Next-generation sequencing approach for connecting secondary metabolites to biosynthetic gene clusters in fungi,” Frontiers in Microbiology, vol. 5, article no. 774, 2014.
- T. Weber, K. Blin, S. Duddela et al., “AntiSMASH 3.0-A comprehensive resource for the genome mining of biosynthetic gene clusters,” Nucleic Acids Research, vol. 43, no. 1, pp. W237–W243, 2015.
- K. Blin, M. H. Medema, R. Kottmann, S. Y. Lee, and T. Weber, “The antiSMASH database, a comprehensive database of microbial secondary metabolite biosynthetic gene clusters,” Nucleic Acids Research, vol. 45, no. 1, pp. D555–D559, 2017.
- A. L. R. Santana-Pereira and M. R. Liles, “Challenges and opportunities in discovery of secondary metabolites using a functional metagenomic approach,” in Functional Metagenomics: Tools and Applications, T. Charles, M. Liles, and A. Sessitsch, Eds., Springer, Cham, 2017, https://link.springer.com/chapter/10.1007/978-3-319-61510-3_7.
- C. A. Westmann, L. d. F. Alves, R. Silva-Rocha, and M. E. Guazzaroni, “Assessing and characterising the repertoire of constitutive promoter elements in soil metagenomic libraries in Escherichia coli,” bioRxiv, 2017.
- P. Cimermancic, M. H. Medema, J. Claesen et al., “Insights into secondary metabolism from a global analysis of prokaryotic biosynthetic gene clusters,” Cell, vol. 158, no. 2, pp. 412–421, 2014.
- M. J. Smanski, S. Bhatia, D. Zhao et al., “Functional optimization of gene clusters by combinatorial design and assembly,” Nature Biotechnology, vol. 32, no. 12, pp. 1241–1249, 2014.
- H. Ren, P. Hu, and H. Zhao, “A plug-and-play pathway refactoring workflow for natural product research in Escherichia coli and Saccharomyces cerevisiae,” Biotechnology and Bioengineering, vol. 114, no. 8, pp. 1847–1854, 2017.
- T. S. Freestone, K.-S. Ju, B. Wang, and H. Zhao, “Discovery of a Phosphonoacetic Acid Derived Natural Product by Pathway Refactoring,” ACS Synthetic Biology, vol. 6, no. 2, pp. 217–223, 2017.
- H. Zhou, B. Vonk, J. A. Roubos, R. A. L. Bovenberg, and C. A. Voigt, “Algorithmic co-optimization of genetic constructs and growth conditions: Application to 6-ACA, a potential nylon-6 precursor,” Nucleic Acids Research, vol. 43, no. 21, pp. 10560–10570, 2015.
- S. P. Bhatia, M. J. Smanski, C. A. Voigt, and D. M. Densmore, “Genetic Design,” ACS Synthetic Biology, vol. 6, no. 11, pp. 2130–2135, 2017.
- M. E. Guazzaroni, R. Silva-Rocha, and R. J. Ward, “Synthetic biology approaches to improve biocatalyst identification in metagenomic library screening,” Microbial Biotechnology, vol. 8, no. 1, pp. 52–64, 2015.
- S. D. Bentley, K. F. Chater, A. M. Cerdeno-Tarraga, G. L. Challis, N. R. Thomson, and K. D. James, Complete genome sequence of the model actinomycete Streptomyces coelicolor A3(2, vol. 417, Nature, 2002.
- Y. Ohnishi, J. Ishikawa, H. Hara et al., “Genome sequence of the streptomycin-producing microorganism Streptomyces griseus IFO 13350,” Journal of Bacteriology, vol. 190, no. 11, pp. 4050–4060, 2008.
- E. A. Barka, P. Vatsa, L. Sanchez et al., “Taxonomy, physiology, and natural products of actinobacteria,” Microbiology and Molecular Biology Reviews, vol. 80, no. 1, pp. 1–43, 2016.
- A. Lewin, R. Lale, and A. Wentzel, Expression Platforms for Functional Metagenomics: Emerging Technology Options Beyond Escherichia coli, 2017.
- J. P. Gomez-Escribano and M. J. Bibb, “Streptomyces coelicolor as an expression host for heterologous gene clusters,” Methods in Enzymology, vol. 517, pp. 279–300, 2012.
- M. J. Smanski, J. Casper, R. M. Peterson, Z. Yu, S. R. Rajski, and B. Shen, “Expression of the platencin biosynthetic gene cluster in heterologous hosts yielding new platencin congeners,” Journal of Natural Products, vol. 75, no. 12, pp. 2158–2167, 2012.
- L. Du, R. H. Liu, L. Ying, and G. R. Zhao, “An efficient intergeneric conjugation of DNA from escherichia coli to mycelia of the lincomycin-producer streptomyces lincolnensis,” International Journal of Molecular Sciences, vol. 13, no. 4, pp. 4797–4806, 2012.
- M. Komatsu, T. Uchiyama, S. Omura, D. E. Cane, and H. Ikeda, “Genome-minimized Streptomyces host for the heterologous expression of secondary metabolism,” Proceedings of the National Acadamy of Sciences of the United States of America, vol. 107, no. 6, pp. 2646–2651, 2010.
- B. Gust, G. Chandra, D. Jakimowicz, T. Yuqing, C. J. Bruton, and K. F. Chater, “λ red-mediated genetic manipulation of antibiotic-producing Streptomyces,” Advances in Applied Microbiology, vol. 54, pp. 107–128, 2004.
- A. C. Jones, B. Gust, A. Kulik, L. Heide, M. J. Buttner, and M. J. Bibb, “Phage P1-Derived Artificial Chromosomes Facilitate Heterologous Expression of the FK506 Gene Cluster,” PLoS ONE, vol. 8, no. 7, Article ID e69319, 2013.
- R. E. Cobb, Y. Wang, and H. Zhao, “High-Efficiency Multiplex Genome Editing of Streptomyces Species Using an Engineered CRISPR/Cas System,” ACS Synthetic Biology, vol. 4, no. 6, pp. 723–728, 2015.
- H. Huang, G. Zheng, W. Jiang, H. Hu, and Y. Lu, “One-step high-efficiency CRISPR/Cas9-mediated genome editing in Streptomyces,” Acta Biochimica et Biophysica Sinica, vol. 47, no. 4, pp. 231–243, 2015.
- D. Du, L. Wang, Y. Tian, H. Liu, H. Tan, and G. Niu, “Genome engineering and direct cloning of antibiotic gene clusters via phage φbT1 integrase-mediated site-specific recombination in Streptomyces,” Scientific Reports, vol. 5, article no. 8740, 2015.
- Y. Tong, P. Charusanti, L. Zhang, T. Weber, and S. Y. Lee, “CRISPR-Cas9 Based Engineering of Actinomycetal Genomes,” ACS Synthetic Biology, vol. 4, no. 9, pp. 1020–1029, 2015.
- P. Manivasagan, J. Venkatesan, K. Sivakumar, and S.-K. Kim, “Pharmaceutically active secondary metabolites of marine actinobacteria,” Microbiological Research, vol. 169, no. 4, pp. 262–278, 2014.
- R. Silva-Rocha, E. Martínez-García, B. Calles et al., “The Standard European Vector Architecture (SEVA): A coherent platform for the analysis and deployment of complex prokaryotic phenotypes,” Nucleic Acids Research, vol. 41, no. 1, pp. D666–D675, 2013.
- Y. Minowa, M. Araki, and M. Kanehisa, “Comprehensive Analysis of Distinctive Polyketide and Nonribosomal Peptide Structural Motifs Encoded in Microbial Genomes,” Journal of Molecular Biology, vol. 368, no. 5, pp. 1500–1517, 2007.
- T. Coenye and P. Vandamme, “Diversity and significance of Burkholderia species occupying diverse ecological niches,” Environmental Microbiology, vol. 5, no. 9, pp. 719–729, 2003.
- L. P. Partida-Martinez, I. Groth, I. Schmitt, W. Richter, M. Roth, and C. Hertweck, “Burkholderia rhizoxinica sp. nov. and Burkholderia endofungorum sp. nov., bacterial endosymbionts of the plant-pathogenic fungus Rhizopus microsporous,” International Journal of Systematic and Evolutionary Microbiology, vol. 57, no. 11, pp. 2583–2590, 2007.
- N. Moebius, C. Ross, K. Scherlach, B. Rohm, M. Roth, and C. Hertweck, “Biosynthesis of the respiratory toxin bongkrekic acid in the pathogenic bacterium burkholderia gladioli,” Chemistry & Biology, vol. 19, no. 9, pp. 1164–1174, 2012.
- X. Liu, S. Biswas, M. G. Berg et al., “Genomics-guided discovery of thailanstatins A, B, and C as pre-mRNA splicing inhibitors and antiproliferative agents from Burkholderia thailandensis MSMB43,” Journal of Natural Products, vol. 76, no. 4, pp. 685–693, 2013.
- J. B. Biggins, C. D. Gleber, and S. F. Brady, “Acyldepsipeptide HDAC inhibitor production induced in Burkholderia thailandensis,” Organic Letters, vol. 13, no. 6, pp. 1536–1539, 2011.
- A. Eustáquio, J. Janso, A. Ratnayake, L. Chang, C. O'Donnell, and F. Koehn, “Spliceostatin biosynthesis in Burkholderia spp.,” Planta Medica, vol. 81, no. 11, 2015.
- K. Ishida, T. Lincke, S. Behnken, and C. Hertweck, “Induced biosynthesis of cryptic polyketide metabolites in a Burkholderia thailandensis quorum sensing mutant,” Journal of the American Chemical Society, vol. 132, no. 40, pp. 13966–13968, 2010.
- M. R. Seyedsayamdost, J. R. Chandler, J. A. V. Blodgett et al., “Quorum-sensing-regulated bActobolin Production by burkholderia thailandensis E264,” Organic Letters, vol. 12, no. 4, pp. 716–719, 2010.
- L. Song, M. Jenner, J. Masschelein et al., “Discovery and Biosynthesis of Gladiolin: A Burkholderia gladioli Antibiotic with Promising Activity against Mycobacterium tuberculosis,” Journal of the American Chemical Society, vol. 139, no. 23, pp. 7974–7981, 2017.
- H. Irschik, D. Schummer, G. Höfle, H. Reichenbach, H. Steinmetz, and R. Jansen, “Etnangien, a macrolide-polyene antibiotic from Sorangium cellulosum that inhibits nucleic acid polymerases,” Journal of Natural Products, vol. 70, no. 6, pp. 1060–1063, 2007.
- D. Menche, F. Arikan, O. Perlova et al., “Stereochemical determination and complex biosynthetic assembly of etnangien, a highly potent RNA polymerase inhibitor from the myxobacterium Sorangium cellulosum,” Journal of the American Chemical Society, vol. 130, no. 43, pp. 14234–14243, 2008.
- V. Leclère, T. Weber, P. Jacques, and M. Pupin, “Bioinformatics tools for the discovery of new nonribosomal peptides,” Methods in Molecular Biology, vol. 1401, pp. 209–232, 2016.
- K. H. Cho and Y. K. Kim, “Two types of ion channel formation of tolaasin, a Pseudomonas peptide toxin,” FEMS Microbiology Letters, vol. 221, no. 2, pp. 221–226, 2003.
- J. C. Nutkins, R. J. Mortishire-Smith, L. C. Packman et al., “Structure determination of tolaasin, an exracellular lipodepsipeptide produced by the mushroom pathogen pseudomonas tolaasii paine,” Journal of the American Chemical Society, vol. 113, no. 7, pp. 2621–2627, 1991.
- P. B. Rainey, C. L. Brodey, and K. Johnstone, “Biological properties and spectrum of activity of tolaasin, a lipodepsipeptide toxin produced by the mushroom pathogen Pseudomonas tolaasii,” Physiological and Molecular Plant Pathology, vol. 39, no. 1, pp. 57–70, 1991.
- K. Scherlach, G. Lackner, K. Graupner, S. Pidot, T. Bretschneider, and C. Hertweck, “Biosynthesis and mass spectrometric imaging of tolaasin, the virulence factor of brown blotch mushroom disease,” ChemBioChem, vol. 14, no. 18, pp. 2439–2443, 2013.
- J. D'aes, N. P. Kieu, V. Léclère et al., “To settle or to move? The interplay between two classes of cyclic lipopeptides in the biocontrol strain Pseudomonas CMR12a,” Environmental Microbiology, vol. 16, no. 7, pp. 2282–2300, 2014.
- G. K. H. Hua and M. Höfte, “The involvement of phenazines and cyclic lipopeptide sessilin in biocontrol of Rhizoctonia root rot on bean (Phaseolus vulgaris) by Pseudomonas sp. CMR12a is influenced by substrate composition,” Plant and Soil, vol. 388, no. 1-2, pp. 243–253, 2015.
- W. Mattheus, L. J. Gao, P. Herdewijn et al., “Isolation and Purification of a New Kalimantacin/Batumin-Related Polyketide Antibiotic and Elucidation of Its Biosynthesis Gene Cluster,” Chemistry & Biology, vol. 17, no. 2, pp. 149–159, 2010.
- W. Mattheus, J. Masschelein, L.-J. Gao et al., “The kalimantacin/batumin biosynthesis operon encodes a self-resistance isoform of the FabI bacterial target,” Chemistry & Biology, vol. 17, no. 10, pp. 1067–1071, 2010.
- T. Tokunaga, K. Kamigiri, M. Orita, T. Nishikawa, M. Shimizu, and H. Kaniwa, “Kalimantacin A, B, and C, novel antibiotics produced by Alcaligenes sp. YL-02632S II. Physico-chemical properties and structure elucidation,” The Journal of Antibiotics, vol. 49, no. 2, pp. 140–144, 1996.
- R. B. Herbert and A. R. Knaggs, “The biosynthesis of the pseudomonas antibiotic obafluorin from p-aminophenylalanine and glycine (glyoxylate),” Tetrahedron Letters, vol. 31, no. 51, pp. 7517–7520, 1990.
- A. A. Tymiak, C. A. Culver, M. F. Malley, and J. Z. Gougoutas, “Structure of Obafluorin: An Antibacterial β-Lactone from Pseudomonas fluorescens,” The Journal of Organic Chemistry, vol. 50, no. 26, pp. 5491–5495, 1985.
- J. Hou, L. Robbel, and M. A. Marahiel, “Identification and characterization of the lysobactin biosynthetic gene cluster reveals mechanistic insights into an unusual termination module architecture,” Chemistry & Biology, vol. 18, no. 5, pp. 655–664, 2011.
- J. Pascual, M. García-López, C. Carmona et al., “Pseudomonas soli sp. nov., a novel producer of xantholysin congeners,” Systematic and Applied Microbiology, vol. 37, no. 6, pp. 412–416, 2014.
- D. D. Nguyen, A. V. Melnik, N. Koyama et al., “Indexing the Pseudomonas specialized metabolome enabled the discovery of poaeamide B and the bananamides,” Nature Microbiology, vol. 2, no. 1, Article ID 16197, 2017.
- C. Zachow, G. Jahanshah, I. De Bruijn et al., “The novel lipopeptide poaeamide of the endophyte Pseudomonas poae RE∗1-1-14 is involved in pathogen suppression and root colonization,” Molecular Plant-Microbe Interactions, vol. 28, no. 7, pp. 800–810, 2015.
- M. Coraiola, P. Lo Cantore, S. Lazzaroni, A. Evidente, N. S. Iacobellis, and M. Dalla Serra, “WLIP and tolaasin I, lipodepsipeptides from Pseudomonas reactans and Pseudomonas tolaasii, permeabilise model membranes,” Biochimica et Biophysica Acta (BBA) - Biomembranes, vol. 1758, no. 11, pp. 1713–1722, 2006.
- P. Lo Cantore, S. Lazzaroni, M. Coraiola et al., “Biological characterization of white line-inducing principle (WLIP) produced by Pseudomonas reactans NCPPB1311,” Molecular Plant-Microbe Interactions, vol. 19, no. 10, pp. 1113–1120, 2006.
- H. Rokni-Zadeh, A. Mangas-Losada, and R. de Mot, “PCR Detection of Novel Non-ribosomal Peptide Synthetase Genes in Lipopeptide-Producing Pseudomonas,” Microbial Ecology, vol. 62, no. 4, pp. 941–947, 2011.
- C. Soler-Rivas, N. Arpin, J. M. Olivier, and H. J. Wichers, “WLIP, a lipodepsipeptide of Pseudomonas 'reactans', as inhibitor of the symptoms of the brown blotch disease of Agaricus bisporus,” Journal of Applied Microbiology, vol. 86, no. 4, pp. 635–641, 1999.
- K. R. Choi, J. H. Shin, J. S. Cho, D. Yang, and S. Y. Lee, “Systems metabolic engineering of Escherichia coli,” EcoSal Plus, vol. 7, no. 1, pp. 1–56, 2016.
- J. A. Jones, V. R. Vernacchio, A. L. Sinkoe, S. M. Collins, M. H. A. Ibrahim, and D. M. Lachance, “Experimental and computational optimization of an Escherichia coli co-culture for the efficient production of flavonoids,” in Metabolic Engineering, vol. 35, pp. 55–63, 2016.
- Li. X-R, G-Q. Tian, H-J. Shen, and J-Z. Liu, “Metabolic engineering of Escherichia coli to produce zeaxanthin,” Journal of Industrial Microbiology Biotechnology, pp. 42–627, 2015.
- M. G. Sajilata, R. S. Singhal, and M. Y. Kamat, “The carotenoid pigment zeaxanthin - A review,” Comprehensive Reviews in Food Science and Food Safety, vol. 7, no. 1, pp. 29–49, 2008.
- W. L. Hadden, R. H. Watkins, L. W. Levy et al., “Carotenoid composition of marigold (Tagetes erecta) flower extract used as nutritional supplement,” Journal of Agricultural and Food Chemistry, vol. 47, no. 10, pp. 4189–4194, 1999.
- D. M. Snodderly, “Evidence for protection against age-related macular degeneration by carotenoids and antioxidant vitamins,” American Journal of Clinical Nutrition, vol. 62, no. 6, 1995.
- E. M. Kim, J. H. Eom, Y. Um, Y. Kim, and H. M. Woo, “Microbial synthesis of myrcene by metabolically engineered Escherichia coli,” Journal of Agricultural and Food Chemistry, vol. 63, no. 18, pp. 4606–4612, 2015.
- A. Behr and L. Johnen, “Myrcene as a natural base chemical in sustainable chemistry: A critical review,” ChemSusChem, vol. 2, no. 12, pp. 1072–1095, 2009.
- T. Werpy and G. Petersen, “Top Value Added Chemicals from Biomass: Volume I -- Results of Screening for Potential Candidates from Sugars and Synthesis Gas,” Tech. Rep. DOE/GO-102004-1992, 2004.
- S. J. Park, E. Y. Kim, W. Noh et al., “Synthesis of nylon 4 from gamma-aminobutyrate (GABA) produced by recombinant Escherichia coli,” Bioprocess and Biosystems Engineering, vol. 36, no. 7, pp. 885–892, 2013.
- J. Zhang, E. Kao, G. Wang, E. E. K. Baidoo, M. Chen, and J. D. Keasling, “Metabolic engineering of Escherichia coli for the biosynthesis of 2-pyrrolidone,” Metabolic Engineering Communications, vol. 3, pp. 1–7, 2016.
- C. Wang, S. Zhi, C. Liu et al., “Characterization of Stilbene Synthase Genes in Mulberry (Morus atropurpurea) and Metabolic Engineering for the Production of Resveratrol in Escherichia coli,” Journal of Agricultural and Food Chemistry, vol. 65, no. 8, pp. 1659–1668, 2017.
- K. A. Roupe, C. M. Remsberg, J. A. Yáñez, and N. M. Davies, “Pharmacometrics of stilbenes: seguing towards the clinic.,” Current Clinical Pharmacology, vol. 1, no. 1, pp. 81–101, 2006.
- E. Martínez-García, I. Benedetti, A. Hueso, and V. de Lorenzo, “Mining environmental plasmids for synthetic biology parts and devices,” Microbiology Spectrum, vol. 3, no. 1, Article ID PLAS-0033-2014, 2015.
- V. A. P. Martins Dos Santos, S. Heim, E. R. B. Moore, M. Strätz, and K. N. Timmis, “Insights into the genomic basis of niche specificity of Pseudomonas putida KT2440,” Environmental Microbiology, vol. 6, no. 12, pp. 1264–1286, 2004.
- R. Simm, M. Morr, A. Kader, M. Nimtz, and U. Römling, “GGDEF and EAL domains inversely regulate cyclic di-GMP levels and transition from sessibility to motility,” Molecular Microbiology, vol. 53, no. 4, pp. 1123–1134, 2004.
- I. Benedetti, V. de Lorenzo, and P. I. Nikel, “Genetic programming of catalytic Pseudomonas putida biofilms for boosting biodegradation of haloalkanes,” Metabolic Engineering, vol. 33, pp. 109–118, 2016.
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