Fungal extrolites as a new source for therapeutic compounds and as building blocks for applications in synthetic biology.

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ARTICLE IN PRESS Microbiological Research xxx (2014) xxx–xxx

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Microbiological Research journal homepage: www.elsevier.com/locate/micres

Review

Fungal extrolites as a new source for therapeutic compounds and as building blocks for applications in synthetic biology Ana Lúcia Leitão a,∗ , Francisco J. Enguita b,∗∗ a Departamento de Ciências e Tecnologia da Biomassa, Faculdade de Ciências e Tecnologia, Universidade Nova de Lisboa, Campus da Caparica, Caparica 2829-516, Portugal b Instituto de Medicina Molecular, Faculdade de Medicina, Universidade de Lisboa, Av. Prof. Egas Moniz, Lisboa 1649-028, Portugal

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Article history: Received 26 June 2013 Received in revised form 15 February 2014 Accepted 16 February 2014 Available online xxx Keywords: Secondary metabolism Genome editing Hybrid metabolite Gene cluster

a b s t r a c t Secondary metabolic pathways of fungal origin provide an almost unlimited resource of new compounds for medical applications, which can fulfill some of the, currently unmet, needs for therapeutic alternatives for the treatment of a number of diseases. Secondary metabolites secreted to the extracellular medium (extrolites) belong to diverse chemical and structural families, but the majority of them are synthesized by the condensation of a limited number of precursor building blocks including amino acids, sugars, lipids and low molecular weight compounds also employed in anabolic processes. In fungi, genes related to secondary metabolic pathways are frequently clustered together and show a modular organization within fungal genomes. The majority of fungal gene clusters responsible for the biosynthesis of secondary metabolites contain genes encoding a high molecular weight condensing enzyme which is responsible for the assembly of the precursor units of the metabolite. They also contain other auxiliary genes which encode enzymes involved in subsequent chemical modification of the metabolite core. Synthetic biology is a branch of molecular biology whose main objective is the manipulation of cellular components and processes in order to perform logically connected metabolic functions. In synthetic biology applications, biosynthetic modules from secondary metabolic processes can be rationally engineered and combined to produce either new compounds, or to improve the activities and/or the bioavailability of the already known ones. Recently, advanced genome editing techniques based on guided DNA endonucleases have shown potential for the manipulation of eukaryotic and bacterial genomes. This review discusses the potential application of genetic engineering and genome editing tools in the rational design of fungal secondary metabolite pathways by taking advantage of the increasing availability of genomic and biochemical data. © 2014 Elsevier GmbH. All rights reserved.

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Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Secondary metabolites: opportunities for synthetic biology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1. Combining genes from different biosynthetic pathways . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2. Substrate channeling and metabolic flux control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3. Selective combination of enzymatic “modules” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Diverse scenarios for the production of new lead compounds of fungal origin . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.1. Control of metabolic flux by genetic engineering of enzyme-encoding genes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.2. Selective transcriptional activation of whole gene clusters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.3. Activation by low-molecular weight inducers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.4. Enzymatic transformation of metabolite scaffolds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3.5. Custom engineering of protein domains in multi-modular enzymes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

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∗ Corresponding author. Tel.: +351 212948543; fax: +351 212948543. ∗∗ Corresponding author. Tel.: +351 217999503; fax: +351 217999412. E-mail addresses: [email protected] (A.L. Leitão), [email protected] (F.J. Enguita). http://dx.doi.org/10.1016/j.micres.2014.02.007 0944-5013/© 2014 Elsevier GmbH. All rights reserved.

Please cite this article in press as: Leitão AL, Enguita FJ. Fungal extrolites as a new source for therapeutic compounds and as building blocks for applications in synthetic biology. Microbiol Res (2014), http://dx.doi.org/10.1016/j.micres.2014.02.007


ARTICLE IN PRESS A.L. Leitão, F.J. Enguita / Microbiological Research xxx (2014) xxx–xxx

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Genome editing platforms for synthetic biology and their potential applications in fungal genome engineering . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Final remarks and future trends . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

1. Introduction Evolution has yielded an enormous variety of life forms on Earth, enmeshed in a complex network of relationships and driven by interspecies competition for limited natural resources. From the chemical point of view, these relationships are frequently mediated by dispensable biomolecules, namely secondary metabolites, which are a reflection of extant and extinct interactions across evolution. Secondary metabolites, which are an important resource for the design and development of new drugs, consist of a heterogeneous class of low-molecular weight compounds that, unlike primary metabolites, are not essential or directly required for the growth of the organisms that produce them (Fox and Howlett, 2008). Among microorganisms, fungi are remarkable in their ability to produce a great variety of metabolites. Biosynthetic genes for the production of secondary metabolites either in fungi or in other microorganisms such as filamentous bacteria are typically located in clusters spanning gene segments of more than 10 kb. Most of the biosynthetic gene clusters contain one or more multidomain high molecular weight condensing enzymes that build the skeleton of the majority of secondary metabolites (Fisch et al., 2011; Gao et al., 2012). Additional enzymes such as oxidases, transferases, and regulatory proteins can be also found within these biosynthetic gene clusters. These enzymes act upon the chemical skeleton of the secondary metabolite introducing chemical modifications and regulating its production and secretion to the extracellular medium (Coque et al., 1995; Enguita et al., 1996; Santamarta et al., 2011). The existence of hitherto unknown genes and gene clusters for the biosynthesis of secondary metabolites has been predicted by bioinformatics analysis of deep-sequencing data of fungal genomes. However, the majority of newly identified fungal secondary metabolite gene clusters are referred to as “cryptic” or “orphan”, as they are not expressed under controlled laboratory conditions and consequently the end product has not yet been characterized (Bergmann et al., 2010; Zabala et al., 2012). Several in vitro strategies for targeted expression of these clusters have been recently discussed and reviewed (Brakhage and Schroeckh, 2011). Given the increasing number of cryptic clusters being characterized in fungal genomes and the fact that only a small proportion of existing fungi have been cultivated in the laboratory, it is evident that there is a profusion of natural compounds awaiting discovery. These natural compounds constitute a reservoir of chemical diversity with the potential to feed drug discovery pipelines for the foreseeable future. Synthetic biology is a relatively new discipline of biology which has its foundations in classical biochemistry, bioengineering and molecular genetics. The basic principles of synthetic biology rely on the modular and hierarchical nature of the biochemical reactions within a cell, that allow us to create new biological systems based on selected combinations of metabolic “blocks” or “modules” (Esvelt and Wang, 2013). Considering the direct analogy with electronic systems (circuits, switches, processors), synthetic biology is a very promising discipline, especially for the creation of new microbial cell factories for the production of novel metabolites (Medema et al., 2011). Selective combination of biological modules using genetic engineering techniques has an almost unlimited power for the construction of new metabolic machines, only constrained by the knowledge of the function and working principles

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of these blocks. Despite its media impact and controversy, synthetic biology tools and principles will probably drive the design and production of new chemicals with important therapeutic applications in the following years (Takano et al., 2012). 2. Secondary metabolites: opportunities for synthetic biology The use of genetically modified microorganisms is an important resource for the industrial production of enzymes and proteins for human and animal health. However, applications using genetically manipulated microbes for the production of small molecules are comparatively less widespread. Classical techniques for improvement of microbial strains are exemplified by the development of antibiotic-producing strains of Penicillium based on protocols such as random mutagenesis or protoplast fusion (Adrio and Demain, 2006). In the 1980s and 1990s, molecular biology techniques were used to elucidate the biosynthetic pathways of many other secondary metabolites (Hutchinson, 1988; Epp et al., 1989; Martin and Liras, 1989; Zuber, 1991). Some preliminary strategies based on synthetic biology principles were also born in those years, such as the development of “hybrid metabolites”, proposed by Hopwood early in the 1980 as compounds with a chemical structure resulting from the action of enzymes encoded by genes isolated from two or more different organisms (Hopwood et al., 1985). This idea, plus the detailed knowledge of the biosynthetic pathways for complex metabolites and the location of the genes involved, allowed the design of new compounds with enhanced or altered pharmacological/biological properties. It even became possible to combine enzymes and genes belonging to secondary and primary metabolic pathways to generate new lead compounds (Epp et al., 1989; Bedford et al., 1995; Stachelhaus et al., 1995). Despite the enormous diversity of secondary metabolites with therapeutic applications, their synthesis is typically based on the condensation of a limited number of primary metabolites that act as subunits or building-blocks. Among these precursors we can find amino acids, short-chain fatty acids, hexoses and pentoses, isoprenyl-derivatives, and others (Lewis, 2013). The genes encoding enzymes related to secondary metabolic pathways are typically conserved among the microorganisms that produce the same family of metabolites. This may be related to the inherent specialization of secondary metabolism, which requires families of enzymes devoted to the production of very specific compounds (Brakhage, 2013). Metabolic flux exerts a strong selective pressure over the enzymes of primary metabolic pathways. Indeed, promiscuous substrate recognition and catalysis would negatively affect the efficiency of a biochemical reaction, and can be considered as the main driving force for negative selection of promiscuous enzymes throughout the evolution of primary metabolic pathways (Bar-Even et al., 2011). In consequence, catalytic efficiency and conserved core metabolic functions are typical of primary metabolic pathways. On the other hand, the more specialized secondary metabolism has been molded by a different set of evolutionary constraints (Busch and Hertweck, 2009; Zucko et al., 2011). The enzymes involved in secondary metabolic pathways do not need to provide high catalytic efficiency in order to produce metabolites to fulfill the different environmental and physiological conditions that change with time. Fluctuating environmental variables are essential to




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Fig. 1. Combination of genes from biosynthetic pathways of different organisms to generate a hybrid compound. This strategy requires molecular knowledge of both of the pathways and of substrate compatibility between the encoded enzymes of the endogenous and introduced genes. Selective gene engineering is a useful strategy to introduce further modifications into a basic chemical nucleus.

understand the advantage of the catalytic promiscuity of secondary metabolic enzymes (Weng and Noel, 2012). The selection for catalytic efficiency and precision observed in primary metabolic processes has been altered in specialized metabolism due to the need to respond to spatially and temporally fluctuating selective pressures (Nam et al., 2012). Catalytic promiscuity observed in secondary metabolism can be more precisely described as substrate permissiveness and mechanistic elasticity, resulting in increased product diversity (Weng and Noel, 2012). Many of the enzymes involved in secondary metabolism show a certain substrate permissiveness, which allows them to accept chemically related substrates, thus generating different products dependent on substrate availability (Brakhage and Schroeckh, 2011). This apparent biological contradiction arises from the uniqueness of secondary metabolites, and facilitates the rational design and production of different compounds from the same chemical skeleton (Blazeck and Alper, 2010). Moreover, the biological diversity of secondary metabolites can also be a consequence of additional events such as gene duplication and parallel evolution (Haarmann et al., 2005), or the control of the precursor pool by the cell (Gruschow et al., 2009). Following the principles of synthetic biology, several strategies can be used to manipulate biosynthetic pathways with the main objective of producing new metabolites with different or enhanced biological activities:

chemical modification of the natural cephalosporin to produce the precursor compound. 2.2. Substrate channeling and metabolic flux control As discussed previously, enzymes involved in the biosynthesis of secondary metabolites are prone to show increased substrate permissiveness when compared with those involved in primary metabolism. Supplementation of culture media with different precursors, that are able to compete with naturally occurring substrates, can generate new compounds (Fig. 2). This precursorguided biosynthesis in which the natural and the induced pathways co-exist is referred to as co-synthesis (Xu et al., 2011; Go et al., 2012). However, the main disadvantage of this strategy is the possible generation of many more secondary metabolites which will

2.1. Combining genes from different biosynthetic pathways This strategy arises not only from the idea of a “hybrid metabolite”, but also from the concept of modularity inherent in synthetic biology principles; namely that the combination of genes from different biosynthetic pathways can lead to the production of novel metabolites (Fig. 1). Selected chemical modifications of the original metabolite may enhance its pharmacological properties or bioavailability. An example of an application of this strategy is the production of recombinant strains of Acremonium chrysogenum expressing a bacterial cephalosporin C acylase (Sonawane, 2006). Natural occurring cephalosporin antibiotics, such as cephalosporin C, contain an alpha-aminoadipate chain fused to the beta-lactam ring (Martin and Liras, 1989). Heterologous expression of the bacterial enzyme catalyzed the conversion of cephalosporin C into 6-aminocephalosporanic acid (6-APA), which is a precursor for the production of semisynthetic cephalosporins (Honda et al., 1997). This innovation resulted in the direct intracellular bioconversion of cephalosporin C into 6-APA, avoiding the costs derived from the

Fig. 2. Strategies for substrate channeling in metabolic pathways. Novel compounds can be synthesized from natural pathways by manipulating the metabolic flow, either by adding new intermediates or precursors (co-synthesis), or by selective mutational blocking of rate-limiting steps and subsequent addition of intermediates (muta-synthesis). When precursors or intermediates are unable to diffuse across cell membranes, the use of purified recombinant enzymes is required.


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need to be identified and further separated in downstream applications. More efficient strategies to control substrate channeling in secondary metabolite generation are those based on the mutation of key precursor biosynthesis genes, thus generating mutants of the producer organisms which are unable to form the natural product without external supplementation of the key intermediates (Fig. 2). Subsequently analogs of biosynthetic intermediates can be fed to the mutants, thus probing the biosynthetic machinery for its flexibility, and ideally producing novel secondary metabolites with structural alterations dictated by the supplemented intermediate. This concept is termed mutational biosynthesis or muta-synthesis, and has the advantage of totally blocking the natural biosynthetic pathway, facilitating the downstream processing of the new metabolites (Yonemoto et al., 2012; Almabruk et al., 2013). These strategies have been applied with success in the production of several derivatives of the antibiotic lincomycin (Ulanova et al., 2010), proteasome inhibitors as fluorosalinosporamide and secondary flavonoid-derivatives from plants (Chemler et al., 2007). However a limitation of both strategies, co-synthesis and mutasynthesis, is that they require the diffusion of the supplemented non-physiological substrates through the barrier of the live cell membrane. In some cases this has been overcome by feeding different substrates to recombinantly-expressed and purified enzymes in vitro. This approach has been used successfully to produce different penicillins by recombinant isopenicillin N synthase from Penicillium chrysogenum (Huffman et al., 1992). 2.3. Selective combination of enzymatic “modules” The inherent possibilities and potential applications of combining different enzymatic modules to create novel metabolites have been most extensively explored for modification of peptide and macrolide antibiotics. These compounds are synthesized by multidomain enzymes that are able to activate and condense a discrete number of precursors. In addition, other auxiliary proteins further modify the basic framework of the antibiotic. Macrolide antibiotics are synthesized by polyketide synthases (PKS), a group of enzymes that condense acetyl-CoA or malonyl-CoA building blocks. In the case of polypeptide antibiotics, the multidomain condensing enzymes are called peptide-synthetases or non-ribosomal peptide synthetases (NRPS), and each domain can activate specifically one amino acid (Fig. 3). Engineering PKS or NRPS genes by combining different activation domains from diverse organisms has allowed the production of a great range of compounds from various building blocks, which can exhibit diverse biological activities such as antibiotic, antitumoral and enzymatic inhibition (Silakowski et al., 2001; Xu et al., 2010; Zhou et al., 2011). 3. Diverse scenarios for the production of new lead compounds of fungal origin 3.1. Control of metabolic flux by genetic engineering of enzyme-encoding genes Metabolic pathways can be engineered by selective expression of enzymes that have novel catalytic activities and are thus able to act upon an already synthesized chemical nucleus (Maharjan et al., 2012). Other strategies include the use of incremental gene dosage to overcome constraints caused by rate-limiting enzymes in pathways. In P. chrysogenum, where industrial strains contain several copies of the penicillin biosynthetic gene cluster, there is a rate limiting step controlled by a phenylacetic acid coenzyme A (CoA) ligase (PCL) responsible for the activation of phenylacetate, a precursor of benzyl-penicillin biosynthesis. This enzyme is encoded by a single gene, located at a different locus from the

penicillin cluster in the P. chrysogenum genome (Lamas-Maceiras et al., 2006). In industrial P. chrysogenum strains, availability of PCL is strongly correlated with the accumulation of the intermedi˜ et al., 1996). ate compound, 6-aminopenicillanic acid (Minambres Limited availability of PCL, and thus production of benzyl-penicillin, has been successfully overcome by controlled overexpressing the PCL-encoding gene in industrial strains (Weber et al., 2012a,b). In addition to the complete cloning of biosynthetic pathways in heterologous hosts (Gidijala et al., 2009), penicillin biosynthesis has been redesigned using genes belonging to other microorganisms. For instance, the expression of the expandase/hydroxylase gene from A. chrysogenum in industrial strains of P. chrysogenum produced stable transformants that were able to synthesize antibiotics containing a 6-membered cephem ring (Robin et al., 2001, 2003). Moreover, P. chrysogenum has also been successfully engineered to produce a new carbamoylated cephem-based antibiotic by simultaneous expression of the expandase/hydroxylase from the cephalosporin producer A. chrysogenum, and the cephem carbamoyl-transferase from the filamentous bacterium and cephamycin producer Streptomyces clavuligerus (Harris et al., 2009) (Fig. 4). In A. chrysogenum, several strategies have been devised to produce the cephalosporin precursor 7-aminocephalosporanic (7-ACA) acid without the use of enzymatic bioconversions. This molecule is the direct precursor for all the semisynthetic cephalosporins, and its industrial manufacture is based on the enzymatic hydrolysis of cephalosporin C, the natural beta-lactam antibiotic produced by A. chrysogenum, using an immobilized bacterial cephalosporin acylase (Yamada et al., 1996; Wang et al., 2012). As an alternative, the heterologous expression of a cephalosporin acylase gene from Pseudomonas sp. in A. chrysogenum was enough for the accumulation of 7-aminocephalosporanic acid in the fungal culture, avoiding the immobilized enzymatic step for its biosynthesis (Li et al., 1999) (Fig. 4) 3.2. Selective transcriptional activation of whole gene clusters Overexpression of either global or specific transcription factors to control the transcription of all secondary metabolite genes in a cluster is an efficient method to increase metabolite yields and also to trigger the activation of silent gene clusters, thus inducing the production of normally cryptic metabolites (Brakhage et al., 2008; Bergmann et al., 2010). The importance of genome-wide studies applied to microbial genomes as a powerful tool for understanding their functions when compared to other organisms has already been discussed in depth (Crawford and Clardy, 2012). In fact, genome-wide studies powered by the next generation sequencing technologies have shown that the clusters of genes responsible for biosynthesis of secondary metabolites in fungi are frequently distributed preferentially in sub-telomeric chromosomal locations (Yin and Keller, 2011). The probable reason controlling this location is related to the presence in these regions of facultative heterochromatin, which can be silenced or activated by chromatin remodeling complexes (Palmer and Keller, 2010). These clusters typically include genes encoding a central multidomain condensing enzyme (PKSs or NRPSs), genes for auxiliary modifying enzymes responsible for the final chemical shape of the secondary metabolite, as well as regulatory genes frequently associated with transcriptional activation and transport mechanisms (Coque et al., 1993a). Genomic mining in the search for gene clusters relating to secondary metabolites has revealed that many fungi contain a large number of these clusters (Eisendle et al., 2003; Wei et al., 2005; Mukherjee et al., 2012; Sanchez et al., 2012). Bioinformatics strategies and specific computer applications for cluster-mining have recently been developed, taking advantage of the availability of increasing numbers




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Fig. 3. Multidomain enzyme engineering. Condensation products generated from multidomain enzymes can be designed by selective combination of catalytic domains. The different precursors (prc) activated by each domain will be condensed in the order dictated by the domain sequence. The use of this strategy has been hindered by its dependency on the genomic recombination required to substitute the DNA fragments encoding the catalytic domains. Recently-developed genome editing platforms will open new possibilities for the application of multidomain engineering in the discovery and production of new metabolites.

of complete fungal genomes (Khaldi et al., 2010). General purpose databases of different biosynthetic clusters for secondary metabolites have also become available (Ichikawa et al., 2013). As we have already pointed out, the majority of these clusters produce unknown metabolites or remain silent under regulatory pressure due to epigenetic factors, or by direct transcriptional repression (Metsa-Ketela et al., 2004; Zabala et al., 2012). The physical linkage of genes which are involved in the same pathway minimizes the number of regulatory mechanisms necessary for their control (Gacek and Strauss, 2012). These clusters, however, are controlled by an intricate regulatory network which responds to several environmental stimuli (carbon and nitrogen source starvation, pH, redox status, light intensity, etc.) and can act at different levels (Roze et al., 2011; Hong et al., 2013a,b). Fungal clusters for the biosynthesis of antibiotics and other secondary metabolites often contain one or more transcription factors required for the expression of the genes encoding biosynthetic enzymes (Yin and Keller, 2011). From current sequencing data it appears that the majority of the transcription factors within biosynthetic clusters belong to a specific protein family characterized by the presence of a bi-nuclear Zn cluster (Zn2 -Cys6 binuclear cluster domain family). Several intra-cluster transcription factors have also been characterized in different clusters, for example the AflR and AflS proteins required for aflatoxin biosynthesis in Aspergillus flavus and Aspergillus nidulans (Kusumoto et al., 1998; Price et al., 2006). Constitutive overexpression of the AflR transcription factor leads to accumulation of aflatoxin cluster gene mRNAs and increases aflatoxin production by A. flavus (Flaherty and Payne, 1997). Conversely, mutational inactivation of the aflR gene reduces aflatoxin production in Aspergillus sojae (Matsushima et al., 2001). Other transcription factors required for secondary metabolite production also include GliZ, a regulator of gliotoxin biosynthesis and

virulence controller of Aspergillus fumigatus (Bok et al., 2006), and ScpR, a transcriptional regulator for aspyridone biosynthesis identified in A. nidulans (Bromann et al., 2012). Interestingly, the gene cluster for aspyridone remains silent under most physiological conditions, and is only activated under controlled overexpression of ScpR (Bergmann et al., 2007, 2010). In those fungal strains able to produce more than one secondary metabolite, the biosynthesis of multiple compounds is often controlled by global regulators of secondary metabolism which constitute an additional layer of control. One such global regulator, LaeA, was characterized in Aspergillus as a nuclear protein with transcriptional activity able to control the production of at least three different secondary metabolites: penicillin, lovastatin and sterigmatocystin. LaeA deletion decreased levels of all three metabolites (Bok et al., 2004). The importance of LaeA in other fungal species and secondary metabolites has also been described in the last five years. In fact, LaeA is not only a global regulatory effector for the production of penicillin and pigments in P. chrysogenum (Kosalkova et al., 2009), but also a virulence factor in pathogenic fungi such as A. fumigatus (Perrin et al., 2007; Dagenais et al., 2010). Overexpression of LaeA in selected strains always results in an increase of the metabolic activities associated with secondary metabolic pathways, indicating its global regulatory effect (Xing et al., 2010; Lee et al., 2013). The LaeA protein is a part of the so called “velvet complex” composed by VelB/VeA/LaeA. The presence of the auxiliary proteins VelB and VeA is required for the regulatory activity of the complex (Bayram et al., 2008). Interestingly a new group of global regulators of secondary metabolism is emerging. This group is represented by the fungalspecific sirtuin HstD, a member of the NAD-dependent histone deacetylases. This family of proteins regulates chromatin structure by facilitating its degree of compactness, and has been shown




Fig. 4. Biosynthetic pathways of beta-lactam antibiotics (penicillins, cephalosporins and cephamycins) and engineered compounds resulting from the heterologous expression of bacterial genes in fungi. Penicillin biosynthesis starts from the condensation of three precursor amino acids, alpha-aminoadipate, cysteine and valine to produce the tripeptide ACV, which is further cyclized by an isopenicillin N epimerase encoded by the gene pcbC. An acyltransferase (encoded by penDE) produces benzyl-penicillin (penicillin G). The production of semysinthetic penicillins requires the hydrolysis of the benzyl group to generate 6-aminopenicillanic acid (6-APA). On the other hand, in fungi such as A. chrysogenum, and in streptomycetes, isopenicillin N is further converted into cephalosporin C through the action of an acetyltransferase. This compound needs to be converted into 7-aminocephalosporanic acid (7-ACA) by a cephalosporin acylase which serves as a lead compound for semisynthetic cephalosporins. Bacterial genes encoding cephalosporin acylases can be overexpressed in A. chrysogenum to generate 7-ACA in fermentation broths (Honda et al., 1997). In streptomycetes such as S. clavuligerus, the final product of the beta-lactam antibiotic biosynthesis is cephamycin C, a modified cephalosporin with increased resistance to microbial beta-lactamases. The expression of cephalosporin (cefE and cefF) and cephamycin biosynthetic genes (cmcH) in the penicillin producer P. chrysogenum has also been used to generate modified cephalosporins in an engineered beta-lactam pathway (Harris et al., 2009).

to be involved in the coordination of fungal development with secondary metabolism (Kawauchi et al., 2013). Deletion mutants for the hstD gene in Aspergillus oryzae showed increased levels of LaeA protein and a consequent activation of secondary metabolic pathways (Kawauchi et al., 2013). Regulation of gene expression by chromatin accessibility is a powerful molecular mechanism in

all eukaryotic cells, and has recently been described as a possible molecular signature for fungal secondary metabolism (Gacek and Strauss, 2012). Indeed, fungi use chromatin-based mechanisms to control the expression of genes related to secondary metabolic pathways by heterochromatin formation during the active growth phase (Gacek and Strauss, 2012).




3.3. Activation by low-molecular weight inducers Fungal secondary metabolic pathways can be triggered by external low-molecular weight inducers. It is already known that in the filamentous bacterium Amycolatopsis lactamdurans (formerly Nocardia lactamdurans), the external supplementation of diamines such as putrescine, cadaverine and diaminopropane can transcriptionally activate genes involved in cephamycin C biosynthesis by a yet unknown mechanism (Leitao et al., 1999). Recently, a similar phenomenon has been observed in the production of penicillin by P. chrysogenum, in a process that involves, to some extent, the LaeA activator. Diamines not only directly activate the expression of penicillin biosynthetic genes but also activate the expression of the general activator LaeA (Martin et al., 2011). Intriguingly, diaminopropane and spermidine were also able to completely restore the phenotype of a laeA knock-down mutant indicating that the activation mechanism can also progress independently of the presence of the laeA gene (Martin et al., 2011, 2012). However, the activation mechanism involving these low-molecular weight compounds is not completely understood. Low-molecular weight compounds acting as inducers are therefore suitable candidates in strategies designed not only to activate silent clusters for the production of secondary metabolites, specifically those for which expression is dependent on chromatin structure, but also to increase the transcriptional activity of genes belonging to constitutively-expressed clusters. Such inducers could be used alone or combined with other genetic strategies such as the overexpression of specific transcription factors. Furthermore, recent studies have shown that, in some cases, the activation of fungal secondary metabolite gene clusters can be mediated by chromatin remodeling induced by interactions with other microorganisms such as bacteria (Nutzmann et al., 2011). In A. nidulans the interaction of fungal hyphae with the soil bacterium Streptomyces rapamycinicus activates the fungal ors gene cluster which encodes enzymes responsible for the production of orsellinic acid and its derivatives (Schroeckh et al., 2009; Nutzmann et al., 2011). In A. nidulans, the Saga/Ada chromatin-remodeling complex is involved in the regulation of the biosynthesis of secondary metabolites such as sterigmatocystin, terrequinone, and penicillin. This complex predominantly acetylates lysines K9 and K14 of histone 3 (H3), and it is also responsible for chromatin decondensation with a concomitant increase in gene expression. Interaction of S. rapamycinicus with A. nidulans specifically recruits the Saga/Ada complex to the chromosomal regions containing the ors gene cluster and thus induces the production of orsellinic acid, while the production of other secondary metabolites is unaffected (Schroeckh et al., 2009; Nutzmann et al., 2011). The mediators of this interaction are not yet known, but are probably low-molecular weight compounds secreted by the bacterium that behave in the same way as the diamines mentioned above, increasing the expression of genes related to secondary metabolic processes. 3.4. Enzymatic transformation of metabolite scaffolds Molecules with pharmacological activity consist of a main skeleton or scaffold, responsible for their biological action, which is chemically modified to modulate their effects and control their bioavailability. For instance, in penicillins and cephalosporins the pharmacologically active scaffold is the beta-lactam ring, which can be modulated by specific chemical modifications to improve its stability, solubility, or bioavailability (Coque et al., 1991, 1993b). Naturally occurring secondary metabolites with pharmacological activities are not usually suitable for administration to humans due to sub-optimal chemical properties. Consequently, they are frequently chemically modified either by semisynthesis or by the use of enzymes or whole cells (Sonawane, 2006; Jiang et al., 2008).

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The production of the main nucleus for the semisynthesis of penicillins and cephalosporins is a classic example. As discussed above, the majority of commercially available beta-lactam antibiotics are derived from the precursor compounds 6-aminopenicillanic acid (6-APA) and 7-aminocephalosporanic acid (7-ACA). These compounds are produced by enzymatic hydrolysis of the natural metabolites of fungal strains by the use of acylases or amidases (Matsumoto, 1993; Torres-Bacete et al., 2000). For instance, A. chrysogenum is used for industrial production of cephalosporin C, which can then be further hydrolyzed by a bacterial cephalosporin C acylase to generate 7-ACA (Matsumoto, 1993; Wang et al., 2012). These bacterial acylases are typically immobilized on solid supports within bioreactors to perform the conversions (Karlsen and Villadsen, 1984; Abian et al., 2003). A further example is the bioconversion of statins, which are aromatic compounds with a polyketide structure. They are produced by different genera of filamentous fungi, such as Aspergillus (Alberts et al., 1980), Penicillium (Endo et al., 1976), Monascus (Endo and Monacolin, 1979), Paecilomyces, Doratomyces, Eupenicillium, Gymnoascus, Hypomyces, Phoma, Trichoderma (Endo et al., 1986) and Pleurotus (Gunde-Cimerman et al., 1993). Statins have several biological effects, among which the reduction of cholesterol levels is one of the most studied, since it has been shown that patients treated with statin medication have a lower risk of cardiovascular disease (Barrios-González and Miranda, 2010). Pravastatin is a highly potent and specific inhibitor of HMG-CoA reductase that can selectively decrease cholesterol synthesis in the liver (Watanabe et al., 1988). Tsujita et al. (1986) initially obtained it by chemical synthesis from another statin, compactin. This process, however, was costly and produced contaminating stereoisomeric by-products. The microbial hydroxylation of compactin has since been developed as a promising alternative for pravastatin production (Shaligram et al., 2009). Compactin, also known as mevastatin, is commercially produced from cultures of Penicillium citrinum (Endo et al., 1986; Hosobuchi et al., 1993), Penicillium cyclopium (Doss et al., 1986) and Aspergillus terreus (Auclair et al., 2001) and is the first step in pravastatin production. The industrial bio-production of pravastatin was originally established in two fermentation steps: firstly the biosynthesis of compactin by P. citrinum, and secondly the bioconversion of sodium compactin to pravastatin by Streptomyces carbophilus, catalyzed by a cytochrome P-450sca monooxygenase system (Hosobuchi et al., 1993; Watanabe et al., 1995) (Fig. 5). In 1999, pravastatin biosynthesis was converted into a one-step synthesis by transforming the P. citrinum strain with an S. carbophilus hydroxylase gene that converts compactin directly to pravastatin (Ykema et al., 1999). Some of the transformants obtained, however, showed low yields of pravastatin production, possibly due to the low expression efficiency of the compactin-producing strain that was used (Barrios-González and Miranda, 2010). In fact, very few microorganisms have been reported to provide efficient biotransformation for the industrial production of pravastatin. Recently, Ba et al. (2013) reported reconstituted P450sca-2 activity (this is the enzyme that stereoselectively converts compactin into pravastatin) in Escherichia coli by co-expression with putidaredoxin reductase and putidaredoxin from the Pseudomonas putida cytochrome P450cam system (Fig. 5). According to these authors the mutant obtained was able to increase the pravastatin yield 4.1 fold with respect to the wild type (Ba et al., 2013). 3.5. Custom engineering of protein domains in multi-modular enzymes Modular enzymes are the core of many biosynthetic clusters, and are the catalysts for the biosynthesis of the main skeleton of a myriad of secondary metabolites (Evans et al., 2011; Zhou




Fig. 5. Pravastatin biosynthesis from compactin by an engineered strain of P. citrinum expressing a P450 enzyme from S. carbophilus (Ykema et al., 1999). The expression of the bacterial hydroxylase gene in the compactin producer P. citrinum circumvents the need to purify the precursor and the subsequent treatment with the S. carbophilus strain.

et al., 2011; Chooi and Tang, 2012; Brakhage, 2013). There are two main classes of multi-modular enzymes: polyketide synthases (PKS) and non-ribosomal peptide synthetases (NRPS) (Zhou et al., 2011). Another class of hybrid enzymes harboring both PKS and NRPS activities has also been characterized (Bergmann et al., 2007). NRPS are multidomain enzymes which catalyze the condensation of natural or modified amino acids to form a linear peptide that will be cyclized by the terminal domain of the NRPS enzyme (Gao et al., 2013). Each module in the enzyme is responsible for the activation and subsequent linkage of one amino acid to the growing peptide chain, which will be further cyclized by the action of an additional condensation domain of the enzyme. Modules in NRPS are composed by three basic catalytic domains: an adenylation domain (A) for amino acid selection and activation; a condensation domain (C) required for the formation of peptide bonds; and a thiolation or peptidyl carrier protein domain (T or PCP) with a phosphopantetheine side chain that will transfer the single amino acidic precursors or the growing peptide to the following catalytic site of the enzyme (Dieckmann et al., 2001; Rausch et al., 2007; Siewers et al., 2009). Structural studies show that substrate binding pockets in eukaryotic NRPS adenylation domains are typically defined by a larger number of amino acids than in their prokaryotic counterparts (Drake et al., 2006; Tooming-Klunderud et al., 2007; Lee et al., 2010). This fact is related to the different substrate specificities observed in eukaryotic and prokaryotic enzymes (Gulick, 2009; Crawford et al., 2011). In some cases, structural and genomic data allows the functional specificity in NPRS to be deduced. This relates the sequence of the adenylation domain with the activation of a particular amino acid (Challis et al., 2000; Challis and Naismith, 2004). Prediction of adenylation domain specificity based on the sequence alone can be achieved through sequence fingerprints or, more accurately, through the use of computer applications based on machine learning methods (Rottig et al., 2011). The accurate determination of NRPS domain specificity is essential for synthetic biology applications, especially in the fungal enzymes, which are more promiscuous than the bacterial ones (Crawford et al., 2011; Boettger et al., 2012). Domain exchange has been used to engineer NRPS from bacteria and streptomycetes, generating enzymes able to activate and condense different amino acids (Butz et al., 2008; Doekel et al., 2008; Pan et al., 2013). Fungal NRPS are comparatively less abundant and more complex than the bacterial enzymes and this has prevented their use in secondary metabolite engineering. However, a recent paper by Gao and coworkers has explored the enzymatic peculiarities of the cyclization domain of fungal NRPS (Gao et al., 2013). These authors reconstituted the activities of the Penicillium aethiopicum trimodular NPRS TqaA, which is involved in the biosynthesis of fumiquinazoline, in Saccharomyces

cerevisiae. In common with the majority of NRPS of fungal origin, the TqaA protein also contains a terminal cyclization domain which belongs to the family of the C-domains (condensation domains) (Rausch et al., 2007). C-domains catalyze the formation of a peptide bond between the growing peptidyl-NRPS and the last activated aminoacyl residue using a catalytic center containing histidine residues (Roongsawang et al., 2005; Rausch et al., 2007). Gao et al. (2013) described the macrocyclization strategy employed by fungal NRPSs and reported the ability of the C-domain from TqaA to cyclize several substrates in a heterologously expressed TqaA protein, thus opening the possibility for new applications using these domains. The PKS family are by far the most complex and diverse enzymes involved in secondary metabolism. They share some functional and structural features with fatty acid synthetases, however the number and families of precursor subunits that they are able to condense is much wider (Chooi and Tang, 2012; Gao et al., 2013). PKS generate an impressive diversity of compounds including macrolides, polyenes, and polyphenols, using simple precursors such as acetyl- and malonyl-CoA (Zhou et al., 2011). Precursors are condensed in a recursive manner using different enzymatic activities: a beta-ketoacyl-synthase (KS) which is responsible for the covalent condensation of two precursor units, an optional acyl-transferase (AT), and an acyl-carrier protein (ACP) which acts as physical support for the growing chain of the polymer. After every step of chain elongation the growing polymer chain can be modified by accessory enzymatic activities including a ketoreductase (KR), dehydratase (DH) and enoyl-reductase (ER) to generate polyphenolic compounds or partially reduced polyketides (Chooi and Tang, 2012). Depending on the mechanism of action and structure, the PKS can be classified into two main groups. Type I, composed of large multifunctional enzymes in which the modules are covalently fused in a single polypeptide chain and which are mainly found in prokaryotes, and Type II, composed of discrete dissociable monofunctional enzymes with independent catalytic activities, that frequently act in an interactive manner, and which are widespread in bacteria and actinomycetes (Zhou et al., 2011; Chooi and Tang, 2012; Mukherjee et al., 2012). In addition a Type III PKS has been described in plants and fungi, and have, as a common feature, the absence of acyl-carrier protein domains (ACP) (Katsuyama and Ohnishi, 2012). Extensive and detailed reviews about PKS have been published in recent years (Hertweck et al., 2007; Katsuyama and Ohnishi, 2012; Boettger and Hertweck, 2013; Williams, 2013). The presence of a KS, an optional AT and an ACP domain together with the additional modifying KR, DG or ER domains forms the catalytic module in a PKS. In bacterial non-interactive PKS, the number of modules is correlated with the number of the extension cycles, and the additional KR, DG or EG domains are directly




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Fig. 6. Engineering of hybrid PKS/NRPS enzymes by selective combination of domains. Directed substitution of a methyltransferase domain (CMeT) from DMBS into TENS leads to the production of a hybrid enzyme H1 able to synthesize tenellin and a new metabolite, desmethylpretenellin (Fisch et al., 2011). Engineering of keto-reductase and enoyl-reductase modules into TENS to produce hybrid enzymes H2 and H3 also leads to the biosynthesis of tenellin and to bassianin derivatives (Fisch et al., 2011). TENS: tenellin synthetase; DMBS: desmethylbassianin synthetase; KS: ketoacyl synthase domain; KR: keto-reductase domain; MAT: acetyltransferase domain; ACP: acyl carrier protein; DH: dehydration domain; ER: enoyl reduction domain; CMeT: methyltransferase domain; C: condensation domain; A: adenylation domain; T: thiolation domain; R: reductase domain.

related to the degree of modification of the polyketide (Boettger et al., 2012). Thus, it should be possible to predict the structure of a particular metabolite from the PKS organization and vice versa (Williams, 2013). Fungal interactive Type I PKS are comparatively more permissive in the use of different building blocks for polyketide biosynthesis (Vagstad et al., 2012; Gao et al., 2013). PKS can be engineered by substituting individual enzymatic domains or entire modules with those with different precursor specificity, or by deleting specific enzymatic functions to generate metabolite analogs, which is a direct application of synthetic biology principles (Ma et al., 2008; Li et al., 2010; Williams, 2013). Several recent examples show direct applications of the rational design of hybrid PKS by a selective combination of domains or catalytic activities to produce new metabolites (Yeh et al., 2013). For instance during biosynthesis of the kinase inhibitor hypothemycin by Hypomyces subiculosus, a highly reducing iterative PKS, Hpm8, cooperates with a nonreducing iterative PKS, Hpm3, to synthesize the intermediate dehydrozearalenol (DHZ). Hpm3 catalyzes the final step of the biosynthesis of hypothemycin by accepting the malonyl-CoA derivatives generated by Hpm8. However, Hpm8 is also able to accept different substrates and transfer them to Hpm3 to generate different DHZ derivatives (Gao et al., 2013). Another very recent and interesting report by Fisch and coworkers described how rational design of fungal PKS modules could be used to produce hybrid metabolites (Fisch et al., 2010, 2011). The biosynthesis of the hybrid pyridones tenellin and desmethylbassianin by the insect pathogen Beauveria bassiana involves two hybrid PKS/NRPS enzymes, tenellin synthetase (TENS) and desmethylbassianin synthetase (DMBS). Selective combination of domains between TENS and DMBS, and expression of the corresponding hybrid enzymes in A. nidulans, resulted in the synthesis of several new

metabolites differing in the length of the side chain and their chemical modifications (Fig. 6) (Fisch et al., 2011). 4. Genome editing platforms for synthetic biology and their potential applications in fungal genome engineering Genome engineering can be defined as the set of protocols designed to construct a genotype that will give rise to a desired phenotype (Esvelt and Wang, 2013). Engineering at the genomic level allows the generation of organisms that would not otherwise arise through natural selection. Conceptually, genome engineering is based on so-called genome editing technologies, a group of genetic technologies that allow either deletion or insertion of genetic information within a given genome at a specific locus. A prerequisite of genome editing technologies is the generation of genetically stable organisms and ideally the technology must be easy to perform in a wide range of organisms (Esvelt and Wang, 2013; Xu et al., 2013). Globally, genome engineering constitutes a very interesting tool for the selective combination and editing of different biosynthetic modules in fungal secondary metabolite clusters. The difficulty inherent in this approach depends directly on the scale and size of the proposed genomic alteration. Until the second half of the first decade of this century, genome editing techniques and protocols were limited to homologous recombination and virus-driven integration. However, since the discovery and characterization of many bacterial systems able to selectively cleave big DNA molecules in specific locations using only the specificity of the target sequence (Fig. 7), the game has changed. Modern technologies for genome editing are still not widely applied to the design of new drugs of biological origin, but they have an enormous potential that must, and will, be explored in the coming




Fig. 7. Classical versus advanced genome editing tools. Classical methods for genome editing are based on homologous recombination, a method in which genomic DNA is exchanged with a different sequence between similar or identical regions of DNA on an introduced DNA molecule. Although widely conserved, the efficiency of homologous recombination systems vary considerably between different organisms. More recent genome editing methods are based on specific endonucleases that are guided to the target sequence by DNA binding domains (Zn-finger nucleases and TALEN nucleases) or by trans-acting RNA molecules (CRISPR). Nuclease activity cleaves the target DNA molecule facilitating the recombination process, and increasing the overall efficiency of the system.

years. There are two main families of genome editing techniques, driven either through proteins or RNA. They essentially differ in the molecule that controls the specificity for the target DNA sequence to be cleaved. In the protein-driven methodologies, a DNA endonuclease recognizes a specific sequence guided by the presence of protein domains that bind directly to a DNA sequence. Historically the first protein tools to be used for genome editing were the Znfinger exonucleases (Beerli et al., 1998). These enzymes contain a zinc-finger structure able to bind to DNA molecules in a specific way that is controlled by the surface-exposed amino acids (Liu et al., 1997). Their modular structure made them suitable to be re-designed for the recognition of specific DNA sequences. Based upon this concept, a group of engineered nucleases called TALEN have been developed by fusing a FokI nuclease catalytic domain to a TALE modular domain for DNA recognition (Miller et al., 2011; Bedell et al., 2012). The main advantage of TALEN nucleases is that TALE domains are able to recognize single nucleotides, increasing the flexibility of the system. Combinations of different TALE domains can be used to recognize any DNA sequence by simply exchanging the domain order (Bedell et al., 2012; Ding et al., 2013). A combinatorial library of TALEN nucleases spanning the whole human genome has already been designed (Kim et al., 2013). However, the efficacy of Zn-finger and TALEN nucleases is dependent on direct protein binding to the DNA, and binding specificity is often a problem (Wood et al., 2011; Ma et al., 2012). More recently a new family of RNA-guided genome editing tools has appeared. This editing system is based on a primitive bacterial immune system used against bacteriophages, and consists of a series of genomic sequences organized in tandem and flanked by repetitive conserved stretches (Chylinski et al., 2013). The CRISPR system (Clustered Regulatory Interspaced Short Palindromic Repeats) relies on the action of a specific trans-acting RNA that binds to the DNA forming a DNA-RNA complex, which then recruits a Cas9 nuclease to selectively cleave the DNA (Fig. 7). Trans-acting RNAs for CRISPR can easily be designed and customized for a

particular target DNA sequence using existing vectors (Burgess, 2013; Cong et al., 2013; Jiang et al., 2013). Once selectively cleaved, DNA can be edited by homologous recombination with a vector containing DNA arms which flank the induced DNA nick (Jinek et al., 2013; Richter et al., 2013). CRISPR “off-target” effects are frequent in large genomes, but are minimized when the source of genetic information is a simple eukaryote, or by inducing a double nicking in the target DNA using two trans-acting RNAs simultaneously (Ran et al., 2013). CRISPR technology has been successfully employed to edit genomes from bacteria to mammals (DiCarlo et al., 2013; Gratz et al., 2013; Hwang et al., 2013; Ramalingam et al., 2013), being particularly efficient in lower eukaryotes such as yeasts (DiCarlo et al., 2013). Genome editing by target directed nucleases is becoming a hot topic for the development of new treatments for genetic diseases (Wu et al., 2013). However, their application in biotechnology is still a developing field, with only a few described examples for selective genome modification in plants (Belhaj et al., 2013; Feng et al., 2013). Engineering of complete biosynthetic clusters, combination of enzymatic activities from different organisms or domain swapping of multimodular enzymes are some possible applications that could benefit from genome editing tools. These technologies will be applied in the next years to design improved fungal strains with new metabolic capabilities. 5. Final remarks and future trends Since the fortuitous discovery of penicillin by Fleming in 1928, filamentous fungi have been an important source of natural compounds for therapeutic use. Nowadays, clinicians are facing a need for new therapeutic alternatives with enhanced pharmacological activities which are able to circumvent the problems of the drugs currently in use (toxicity, microbial resistance, lack of bioavailability, etc.). Until the recent explosion in genomic data, new lead compounds for new drugs were almost always




obtained by screening of complex natural mixtures from microbial, animal or vegetal origin, and further optimized by chemical protocols. Furthermore, the increasing genomic information from already-sequenced microorganisms has shown that fungi, based on cryptic metabolic capabilities encoded in their genomes, hide an unexplored source of new chemicals. Exploiting these metabolic activities by taking advantage of genetic technologies is not a new idea. In fact the first concepts of genetic engineering and manipulation of secondary metabolites are originally from the early 1980s. However, application of molecular biology and genetics approaches to the optimization of lead compounds and production of new drugs from fungi has been limited by the lack of appropriate tools in the majority of organisms. In addition, the extremely successful commercial program of strain improvement by random mutagenesis took precedence over development of molecular tools, which were almost exclusively investigated in academic environments. During the last decade, genomic analysis together with advanced biochemical techniques such as structural biology has revealed basic principles that govern the production of secondary metabolites by fungi. Several enzymes and pathways have been dissected at the molecular level and, in parallel, an increasing number of biosynthetic gene clusters have been discovered in many known fungal strains. Synthetic biology rules have illustrated the modular nature of the biochemical reactions within the cells and also the apparently unlimited possibilities for manipulation of cellular metabolism from the gene to the protein. Interestingly, all these concepts have given new impetus to Hopwood’s ideas (Hopwood et al., 1985), pushing them into the 21st century. Fungal genes and enzymes involved in secondary metabolism are ideal examples of modularity. In consequence, fungi are now considered an almost unlimited source of genetic, molecular and metabolic diversity that can be exploited using modern systems and synthetic biology concepts. A note of caution is that new genomic manipulation techniques such as genome editing protocols, which will allow scientists to combine large tracts of genetic information, will be required to construct fungal strains that produce rationally-designed lead compounds for therapeutic use. The advantages of this approach, as discussed in this review, rely on two pillars. Firstly the design and combination of different building blocks to produce drug scaffolds that can be further modified either by enzymatic or chemical protocols, and secondly the use of cell factories to produce metabolites of interest which can often be more economical when compared with chemical synthesis. In summary, we predict a very promising future for the application of synthetic biology and genome editing protocols in the pursuit of new drugs from fungal origin with enhanced or novel biological activities.

Acknowledgments Authors would like to thank Francisco Enguita Jr for excellent technical assistance in manuscript design, and Dr. Paul Tucker for critical reading and suggestions to improve the text.

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