I thank Xiaowei Du, Hadeel El-Malaki, Camille English, Richard Hung, Arati Inamdar, Samantha Lee, Prakash Masurekar, Shannon Morath, Sally Padhi, Kayla Pennerman, Craig Pritch, David Pu, Melanie Yap, Guohua (Karen) Yin, and Guozhu Zhao for their research contributions, intellectual insights, and lively discussions. Special thanks to Guohua Yin for help with the images.

## References

**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Copyright © 2015 Bennett. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

## *Jens C. Frisvad\**

Section of Eukaryotic Biotechnology, Department of Systems Biology, Technical University of Denmark, Kongens Lyngby, Denmark

#### *Edited by:*

Jonathan Palmer, United States Department of Agriculture Forest Service, USA

#### *Reviewed by:*

Antonello Santini, University of Naples Federico II, Italy Rob Samson, CBS Fungal Biodiversity Centre, Netherlands

#### *\*Correspondence:*

Jens C. Frisvad, Section for Eukaryotic Biotechnology, Department of Systems Biology, Technical University of Denmark, Søltofts Plads B. 221, 2800 Kongens Lyngby, Denmark e-mail<EMAIL_ADDRESS>
Aspergillus, Penicillium, and Talaromyces are among the most chemically inventive of all fungi, producing a wide array of secondary metabolites (exometabolites). The three genera are holophyletic in a cladistic sense and polythetic classes in an anagenetic or functional sense, and contain 344, 354, and 88 species, respectively. New developments in classification, cladification, and nomenclature have meant that the species, series, and sections suggested are natural groups that share many extrolites, including exometabolites, exoproteins, exocarbohydrates, and exolipids in addition to morphological features. The number of exometabolites reported from these species is very large, and genome sequencing projects have shown that a large number of additional exometabolites may be expressed, given the right conditions ("cryptic" gene clusters for exometabolites). The exometabolites are biosynthesized via shikimic acid, tricarboxylic acid cycle members, nucleotides, carbohydrates or as polyketides, non-ribosomal peptides, terpenes, or mixtures of those. The gene clusters coding for these compounds contain genes for the biosynthetic building blocks, the linking of these building blocks, tailoring enzymes, resistance for own products, and exporters. Species within a series or section in Aspergillus, Penicillium, and Talaromyces have many exometabolites in common, seemingly acquired by cladogenesis, but some the gene clusters for autapomorphic exometabolites may have been acquired by horizontal gene transfer. Despite genome sequencing efforts, and the many breakthroughs these will give, it is obvious that epigenetic factors play a large role in evolution and function of chemodiversity, and better methods for characterizing the epigenome are needed. Most of the individual species of the three genera produce a consistent and characteristic profile of exometabolites, but growth medium variations, stimulation by exometabolites from other species, and variations in abiotic intrinsic and extrinsic environmental factors such as pH, temperature, redox potential, and water activity will add significantly to the number of biosynthetic families expressed in anyone species. An example of the shared exometabolites in a natural group such as Aspergillus section Circumdati series Circumdati is that most, but not all species produce penicillic acids, aspyrones, neoaspergillic acids, xanthomegnins, melleins, aspergamides, circumdatins, and ochratoxins, in different combinations.

**Keywords:** *Aspergillus***,** *Penicillium***,***Talaromyces***, secondary metabolites, chemodiversity, chemoconsistency**

## **INTRODUCTION**

The genera *Aspergillus sensu lato* and *Penicillium sensu lato* contain a high number of very diverse species. These species produce a large number of exometabolites, also known as secondary metabolites. Exometabolites are small molecules produced during morphological and chemical differentiation that are outward directed, i.e., secreted or deposited in or on the cell wall, and accumulated in contrast to endometabolites (primary metabolites), that are fluctuating in concentration (the fluxome), and either transformed into other endometabolites or feeding into exometabolites, exoproteins, exopolysaccharides, and morphological structures. While endometabolites can be found in almost all species of fungi (and most other kinds of organisms), exometabolites, exoproteins, and exopolysaccharides are taxonomically restricted, being produced in species-specific profiles. Some metabolites can occur

both as endo- and exometabolites, for example citric acid. When citric acid is part of the mitochondrial fluxome, it should be regarded as an endometabolite, but when citric acid is secreted and accumulated (Goldberg et al., 2006; Andersen et al., 2011; Poulsen et al., 2012), as in *Aspergillus niger*, it must be regarded as an exometabolite. Accumulation of citric acid requires that there is a reductive pathway for it in the cytosol and that it can be secreted to the surroundings via an exporter. Thus the transport from the mitochondria to the cytosol, the cytosolic reduction, and the secretion requires a dedicated gene cluster. Such a gene cluster has been found in for example *A. terreus* that is coding for accumulating and secreting itaconic acid (van der Straat et al., 2014), but the gene cluster for citric acid accumulation has not been described yet. Some species related to *Aspergillus* and *Penicillium*, such as *Xeromyces bisporus*, are predominantly

stress-selected (S-selected) and the lack of any competitors at very low water activities will have the consequence that *X. bisporus* produces no exometabolites (Leong et al., 2014). In *Aspergillus* most species produce a large number of exometabolites, but some stress selected species, such as *A. penicillioides* and *A. restrictus*, have only been reported to produce asperglaucide and cristatin A, and the related arestrictin A and B (Itabashi et al., 2006). However, the closely related xerotolerant/xerophilic species in the *Aspergillus* subgenus *Aspergillus* (formerly *Eurotium*) produce a high number of exometabolites in the ascomata, making them chemically very diverse (Slack et al., 2009).

## *Aspergillus* **AND** *Penicillium* **TAXONOMY AND NOMENCLATURE**

Because of their importance, species of *Aspergillus* and *Penicillium* have been taxonomically treated several times, but the monographs by Raper and Thom (1949) for *Penicillium* and Raper and Fennell (1965) for *Aspergillus* are still regarded as cornerstones in the taxonomy of these fungi. In the period between these two monographs, however, several authors (Benjamin, 1955; Malloch and Cain, 1971) suggested to use names for the sexual state of the Aspergilli and Penicillia, whenever possible, to adhere to the Botanical Code in a nomenclatural sense. The use of *Penicillium* and *Aspergillus* for species that had not yet been found to produce a sexual state could keep their *Penicillium* and *Aspergillus* names, because of a special nomenclatural "exception" in the Botanical Code (Art. 59) that allowed to use two names for a specific fungal species, one for the asexual states (the "anamorph") and one for the sexual state (the "teleomorph"). Despite this it was recommended to use the sexual name for the whole fungus (the "holomorph"), whenever a sexual state had been found. For this reason many species in *Penicillium* were renamed *Eupenicillium* or *Talaromyces* (Pitt, 1980) and many *Aspergillus* species were renamed *Chaetosartorya*, *Emericella*, *Eurotium, Fennellia, Hemicarpenteles*, *Hemisartorya*, *Neocarpenteles*, *Neopetromyces*, *Neosartorya*, *Petromyces, Saitoa*, *Sclerocleista*, or *Warcupiella* (Rai and Chowdhery, 1975; Rajendran and Muthappa, 1980; Gams and Samson, 1986). To give one example of the name changes one can mention a fungus that was originally described as *A. fischeri*. Since this fungus was described including the sexual state, it could not be used for the asexual state anymore, so the correct name for the fungus according the nomenclatural rules before 2011 was *Neosartorya fischeri*, while *A. fischeri* had to be renamed *A. fischerianus* if one wanted only to refer to the asexual state. A full monographic revision of *Aspergillus* according to the Botanical Code has not been written, but lists of accepted *Aspergillus* and *Penicillium* species have been made (Pitt et al., 2000) and several revisions of the individual genera have been published.

In 2010 it was suggested to introduce a new nomenclatural system in which one fungus had only one name (Hawksworth et al., 2011; Hawksworth, 2012). This suggestion was adopted by the Botanical Congress in Melbourne (McNeill et al., 2012), and thus hereafter any species in fungi will only have one official name. The selection of those names is encouraged to take place by consensus among international experts in the group of fungi under consideration. The International Commission of *Penicillium* and

*Aspergillus* (ICPA) has decided to use *Penicillium* for the monophyletic clade that includes *Penicillium* subgenera *Aspergilloides*, *Furcatum,* and *Penicillium sensu* Pitt (1980), *Eupenicillium*, *Chromocleista*, *Thysanophora* and *Eladia,* and *Talaromyces* for the monophyletic clade that includes *Talaromyces* itself and *Penicillium* subgenus *Biverticillium sensu* Pitt (1980). For *Aspergillus sensu lato,* a cladistic study using DNA sequence data, showed that most known *Aspergillus* species were included in a monophyletic clade (Houbraken and Samson, 2011), while a few rare species, such as *A. zonatus* and *A. clavatoflavus* were more closely related to other genera in the *Eurotiomycetes*. The nomenclatural consequence of this is to call all the species in the monophyletic clade *Aspergillus* (Houbraken et al., 2014; Samson et al., 2014) or retypify the genus *Aspergillus* with for example *A. niger*, and then subdivide *Aspergillus* into the genera *Aspergillus*, *Neosartorya*, *Emericella*, *Eurotium,* and *Chaetosartorya* (Pitt and Taylor, 2014). This would have the consequence that the name *Aspergillus* would only be used for a paraphyletic weakly supported clade representing subgenus *Aspergillus* and that the genus *Neosartorya* would be polyphyletic as it includes *Dichotomomyces*. Even though a majority of ICPA members voted for the *Aspergillus* solution, which includes mentioning the sexual state informally, for example *A. fischeri* (neosartorya-morph present), general consensus has not yet been reached. In this review *Aspergillus* names will be used, as suggested by Samson et al. (2014), as the name *Aspergillus* can be confidently used for the monophyletic clade that includes the genera listed above (Houbraken et al., 2014). All species formerly included in *Dichotomomyces*, *Cristaspora, Phialosimplex*, *Polypaecilum*, in addition to *Penicillium inflatum*, have been formally combined into *Aspergillus* (Samson et al., 2014), while *A. crystallinus*,*A. malororatus,* and*A. paradoxus*(*Hemicarpenteles paradoxus*) have been combined into *Penicillium*, as *P. crystallinum*, *P. malodoratum,* and *P. paradoxum* (Visagie et al., 2014b). This means that the presence of aspergilla in an isolate does not necessarily mean that the isolate belongs to *Aspergillus sensu stricto*, and the presence of penicilli in an isolates does not necessarily mean the species belong in *Penicillium sensu stricto*. However, in the majority of cases aspergilla or penicilli indicates that the species belong to *Aspergillus* and *Penicillium*, respectively.

Pitt and Taylor (2014) suggested to use *Aspergillus* for the paraphyletic subgenus *Circumdati* only (after potential re-typification of *Aspergillus* with *A. niger*), stating that this restricted use of the genus *Aspergillus* would make this genus phenotypically different from the closely related *Aspergillus* subgenus *Nidulantes* and therefore suggested the name *Emericella* for the latter monophyletic clade. However, there are many phenotypic traits in common between section *Circumdati* and *Nidulantes*, including the presence of hülle cells and the exometabolites kojic acid, aflatoxins, and sterigmatocystins in both subgenera (Raper and Fennell, 1965; Wiley and Simmons, 1973; Frisvad and Samson, 2004a; Frisvad et al., 2005; Zalar et al., 2008). Subgenus *Circumdati* includes species with both multiple cleistothecia in sclerotia (*Petromyces, Neopetromyces, Saitoa*; Udagawa et al., 1994; Yaguchi et al., 1994; Frisvad and Samson, 2000; Horn et al., 2013) and pseudoparenchymatous multiple ascomata in hyphal masses with or without hülle cells (*Fennellia* and the perfect state of *A. terreus*; Wiley and Simmons, 1973; Locquin-Linard, 1990; Yaguchi

et al., 1994; Samson et al., 2011a; Arabatsis and Velegraki, 2013), while several species in *Aspergillus* section *Nidulantes* produce pseudoparenchymatous single ascomata and hülle cells.

Assistance in choosing between *Aspergillus* (Samson et al., 2014) versus the genera *Eurotium, Emericella, Neosarotrya* and *Chaetosartorya, Phialosimplex, Polypaecilum*, *Dichotomomyces,* and *Cristaspora* (Pitt and Taylor, 2014) can be sought from scientific databases. It is very clear that while *Aspergillus* has been used in 56178 publications the other genera, when all added, have only been used in 1093 publications (approximately 2%; **Table 1**).

A classification of isolates into sections and series in *Penicillium*, *Talaromyces,* and *Aspergillus* based on phenotypic characters will show that these supraspecific taxa are natural polythetic classes (Beckner, 1959) in exometabolite, ecophysiological, and morphological characters. For example in *Aspergillus* subgenus *Circumdati* section *Circumdati* (the former *A. ochraceus* group) most species, but not all, produce aspyrones, penicillic acids, xanthomegnins, ochratoxins, melleins, circumdatins, neoaspergillic acids, and aspergamides/stephacidins (Frisvad et al., 2004a,b; Finefield et al., 2012;Visagie et al., 2014a). In addition individual species produces exometabolites that are only accumulated by few species in the

**Table 1 | References to** *Aspergillus, Penicillium,Talaromyces,* **and associated genera (Web of Science, as of 18 October, 2014).**

section. *A. westerdijkiae* and *A. ochraceus* can both produce all the exometabolites listed above, but in addition *A. westerdijkiae* produces preussin and mellamide, not produced by *A. ochraceus*.

At present *Aspergillus* comprises 344 species (Samson et al., 2014), *Penicillium* 354 species (Visagie et al., 2014b), and *Talaromyces* 88 species (Yilmaz et al., 2014). These genera include species that have been reported to produce large numbers of exometabolites (**Table 2**).

## **CHEMODIVERSITY**

Species of *Aspergillus*, *Penicillium,* and *Talaromyces* are extraordinarily productive concerning exometabolites. A comparison with other genera shows that most exometabolites have been

**Table 2 | Individual exometabolites produced by important genera of filamentous fungi ranked according to highest number of exometabolites reported (according to AntiBase).**

Species of Penicillium listed were revised to Talaromyces if they belonged there (Yilmaz et al., 2014).

reported from *Aspergillus* (1984), next-most from Penicillium (1338), and fifth-most by *Talaromyces*, (316), with only *Fusarium* (507) and *Trichoderma* (438) producing more exometabolites *in toto* (**Table 1**). The number of exometabolites pr species is 5.77 for *Aspergillus*, 3.77 for *Penicillium,* and 3.58 for *Talaromyces*. These number per species are clearly underestimates as some exometabolites are produced by more than one species in a genus, in addition to the fact that many species have not been examined and that some exometabolites are only expressed under unique circumstances and thus may remain undetected (Sanchez et al., 2012; Brakhage, 2013; Scherlach et al., 2013; Takahashi et al., 2013; Bertrand et al., 2014; Marmann et al., 2014). Light, pH, redox potential, temperature, water activity, carbon sources, nitrogen sources, iron starvation, and exometabolites from other species can all have a regulatory effect on the regulatory proteins for exometabolite expression in a fungus (Brakhage, 2013). A majority of the exometabolites produced by *Penicillium* and *Aspergillus* are only found sporadically in other genera, but a large number of exometabolites are in common between *Aspergillus* and *Penicillium*. On the other hand exometabolites from *Talaromyces* are nearly all unique to that genus (Samson et al., 2011b), or only shared with few other species.

The same exometabolite may be produced by widely different species. For example aflatoxin is produced by the species listed in *Aspergillus* section *Flavi* (15 spp.), *Aspergillus* section *Nidulantes* (3 spp.), *Aspergillus* section *Ochraceorosei* (2 spp.), and *Aschersonia* (2 spp.; Frisvad and Samson, 2004a; Frisvad et al., 2005; Zalar et al., 2008; Varga et al., 2009, 2011; Kornsakulkarn et al., 2012, 2013; Massi et al., 2014). Three species in *Aspergillus* section *Flavi* and all the seven species outside section *Flavi* listed above only produce aflatoxins of the B type. It is surprising that aflatoxins have never been found in *Penicillium*, but they have been found in the unrelated scale insect fungi *Aschersonia coffea* and *Aschersonia marginata* (Kornsakulkarn et al., 2012, 2013). However, the precursor sterigmatocystin, although end-product for some species, has been found in a large number of unrelated genera (Rank et al., 2011), suggesting that this complicated gene cluster has been horizontally transfered between species in widely different genera, as shown by Slot and Rokas (2011) for *Podospora anserina* and *A. nidulans*. Fungal species are specifically associated to certain habitats or few plant, animal, or other kind of organisms (Filtenborg et al., 1996), and will therefore produce exometabolites in reponse to the challenges in the particular habitat. For example *P. herquei* was thought to be a soil fungus saprophyte (Kwa´sna, 2004), but recent studies have shown tha the leaf-rolling weevil (*Euops chinensis*) have developed mycangia to inoculates leaves with *P. herquei* conidia to protect the weevil eggs (Li et al., 2012). *P. herquei* produce a species specific profile of exometabolites, of which several are antibiotically active (Petit et al., 2009; Tansakul et al., 2014). Thus the specificity in both association of fungal species to other species and the profile of exometabolites are factors that have boosted the evolution of so many exometabolites.

*Dichotomomyces cejpii* was transferred to *A. cejpii* by Samson et al. (2014), and this new combination is supported by chemotaxonomic evidence. *D. cejpii* was reported to produce gliotoxin, xanthocillin X monomethylether, tryptoquivalones, JBIR-03, emindole SB, emindole SB beta-mannoside, and 27-*O*methylasporyzin (Varga et al., 2007; Harms et al., 2014). While gliotoxin, tryptoquivalones, and xanthocillins (Frisvad et al., 2009; Zuck et al., 2011) indicates a relationship to *A. fumigatus* and tryptoquivalones a close relationship to *A. clavatus*, as supported by DNA sequences (Varga et al., 2007), production of emindole SB indicates a relationship to *Aspergillus* section *Nidulantes*. The report of emindole SB, emeniveol, asporyzin A-C, and JBIR-03 from a marine-derived *A. oryzae* (Qiao et al., 2010), indicates what they identified as "*A. oryzae*" is a fungus related to *A. cejpii* or a species in *Nidulantes* rather than *A. oryzae*, however.

### **CHEMOCONSISTENCY AND OSMAC**

The abbreviation OSMAC (one strain many compounds) was introduced by Bode et al. (2002)where the authors showed, among several examples, that a strain of *A. westerdijkiae* produced a series of exometabolites that could be ordered into different biosynthetic families. Furthermore, by using several media a more full profile of these exometabolites could be revealed. The idea that one strain can produce several exometabolites was already introduced by Frisvad (1981) and Frisvad and Filtenborg (1983, 1989). These authors showed that terverticillate penicillia produced a unique profile of different exometabolites and also that certain media, such as Czapek yeast autolysate (CYA) agar and yeast extract sucrose (YES) agar were very efficient for production of a large number of different exometabolites, while further media may increase the number of exometabolites expressed (Bills et al., 2008; Nielsen et al., 2011; Frisvad, 2012). Furthermore they showed that these profiles of exometabolites were species specific and consistent from isolate to isolate, i.e., the isolates in anyone fungal species were chemo consistent (Larsen et al., 2005). One of the original terms for exometabolites or secondary metabolites was idiolites, the latter indicating that production of exometabolites was strain specific, however, exometabolite profiles are clearly species specific (Frisvad et al., 2008). However, a single mutation in a gene in an exometabolite gene-cluster will often be sufficient for loss of phenotypic expression (Susca et al., 2014), and this may be the reason some authors call the production of certain exometabolites "strain-specific" (i.e., Engel et al., 1982). The ability to produce mycophenolic acid in *P. roqueforti* is retained in most strains, however, (Frisvad and Filtenborg, 1989; Geisen et al., 2001; Frisvad and Samson, 2004b), but is not as consistent as in *P. brevicompactum*, where a non-producing strain has never been found (Frisvad and Filtenborg, 1989; Frisvad and Samson, 2004b). Reasons for observing "unusual " or "unexpected" exometabolites in a species may be horizontal gene transfer of a gene cluster in only one or few strains, hybridization (which is not common in filamentous fungi), or epigenetic priming. Raper and Thom (1949) mentioned a strain of *P. citrinum* (NRRL 822, their group III in a subdivision of *P. citrinum* "transitional toward *P. chrysogenum* series") produced both citrinin, known from this species, and penicillin, known from *P. chrysogenum*. They also mentioned that their strain had the cultural appearance of both *P. citrinum* and *P. chrysogenum*. We have re-examined this strain, and indeed it had characters of both species, and appeared to be a (rare) hybrid. However, exometabolites from co-occurring species from the same habitat may stimulate the epigenome by acting as inhibitors of histone

acetylation or methylation, and this exometabolite stimulation will be one of many ways of having silent exometabolite gene clusters in filamentous fungi expressed (Bertrand et al., 2014). It was recently shown that*A. niger* could produce sclerotia with many hitherto not expressed aflavinins in them (Frisvad et al., 2014) simply by stimulating *A. niger* with whole fruits or rice. Whether this stimulation is caused by extrolites from those whole fruits or rice or from a physical stimulation is not yet known. Furthermore variations in the growth medium and ecophysiological factors such as pH, temperature, and water activity will obviously also stimulate expression of gene clusters of exometabolites that were initially thought to be silent.

In conclusion *Aspergillus, Penicillium,* and *Talaromyces* contain species that produce a very large number of species-specific exometabolites with a high degree of chemoconsistency. The chemodiversity of the many species in these three genera is extremely high and many more bioactive compounds from the species will be found in the future. Both ecological and genetic/molecular approaches are needed to fully explore this treasure-trove of natural products.

#### **REFERENCES**

taxa accommodated in *Penicillium* subgenus *Biverticillium*. *Stud. Mycol.* 70, 159– 184. doi: 10.3114/sim.2011.70.04

Zuck, K. M., Shipley, S., and Newman, D. J. (2011). Induced production of N-formyl alkaloids from *Aspergillus fumigatus* by co-culture with *Streptomyces peucetius*. *J. Nat. Prod.* 74, 1653–1657. doi: 10.1021/ np200255f

**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 09 November 2014; paper pending published: 05 December 2014; accepted: 17 December 2014; published online: 12 January 2015.*

*Citation: Frisvad JC (2015) Taxonomy, chemodiversity, and chemoconsistency of Aspergillus, Penicillium, and Talaromyces species. Front. Microbiol. 5:773. doi: 10.3389/fmicb.2014.00773*

*This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology.*

*Copyright © 2015 Frisvad. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

## *Chun-Jun Guo1 and Clay C. C. Wang1,2\**

*<sup>1</sup> Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, Los Angeles, CA, USA <sup>2</sup> Department of Chemistry, College of Letters, Arts, and Sciences, University of Southern California, Los Angeles, CA, USA*

#### *Edited by:*

*Ozgur Bayram, National University of Ireland Maynooth, Ireland*

#### *Reviewed by:*

*Axel A. Brakhage, Friedrich Schiller University Jena, Germany Sean Doyle, National University of Ireland Maynooth, Ireland*

#### *\*Correspondence:*

*Clay C. C. Wang, Department of Pharmacology and Pharmaceutical Sciences, School of Pharmacy, University of Southern California, 1985 Zonal Ave PSC 406A, Los Angeles, CA, USA e-mail<EMAIL_ADDRESS>
Filamentous fungi are rich resources of secondary metabolites (SMs) with a variety of interesting biological activities. Recent advances in genome sequencing and techniques in genetic manipulation have enabled researchers to study the biosynthetic genes of these SMs. *Aspergillus terreus* is the well-known producer of lovastatin, a cholesterol-lowering drug. This fungus also produces other SMs, including acetylaranotin, butyrolactones, and territram, with interesting bioactivities. This review will cover recent progress in genome mining of SMs identified in this fungus. The identification and characterization of the gene cluster for these SMs, as well as the proposed biosynthetic pathways, will be discussed in depth.

**Keywords: genome mining,** *Aspergillus terreus***, secondary metabolites, natural products**

## **INTRODUCTION**

Filamentous fungi, such as species found within the genus *Aspergillus*, are known to produce a wide variety of natural products displaying a broad spectrum of biological activities. Genome sequencing of members in the genus *Aspergillus* revealed that the number of secondary metabolite (SM) genes or gene clusters greatly exceeds the number of SMs identified so far. This suggests that more types of SMs still remain to be discovered. Efficient and high-throughput genome sequencing techniques have now greatly facilitated the genome mining of SMs identified in *Aspergillus* species. More and more studies have shown that most fungal SM genes are clustered, often separated from each other by less than 2 kb within the chromosome (Keller et al., 2005). Striking examples of fungal SM clusters include those responsible for the biosynthesis of fumonisin (Proctor et al., 2003) and sterigmatocystin (Brown et al., 1996). The clustering of these SM genes is fortuitous for researchers since upon discovering one responsible gene within a cluster, other genes that are within close proximity of the identified genes may be involved in the biosynthesis of the same natural product.

Analysis of the fungal genome makes it feasible to characterize these SM gene clusters via genetic manipulations. Verification of function of the relevant genes can be achieved via several approaches. These approaches include targeted deletion or over-expression of the relevant genes in the native organism, heterologous expression in an alternative host, or *in vitro* biochemical characterization. Recent advances in the genome editing of *Aspergillus nidulans* have greatly expedited the SM genome mining of this fungal species (Sanchez et al., 2012). One advance is the development of a fusion PCR technique that allows quick synthesis of linear PCR fragments that are used in the transformation of filamentous fungi (Yu et al., 2004; Szewczyk et al., 2006). Another advance concerns the establishment of an efficient gene targeting system in the fungus *A. nidulans*. This is accomplished via targeted deletion of the *A. nidulans* homolog (*nkuA*) of the human KU70 gene which is essential for nonhomologous end joining of DNA in DNA double-strand breaks (Nayak et al., 2006; Szewczyk et al., 2006). Later, this *ku70* deletion toolbox was expanded to other *Aspergillus* species and boosted the gene targeting efficiency in these species (Kuck and Hoff, 2010).

The fungus *Aspergillus terreus* is known to produce lovastatin, which became the first cholesterol-lowering drug of its class approved for human use in the United States. Besides lovastatin, *A. terreus* produces a number of biologically relevant compounds such as sulochrin, terretonin, asterriquinone, and butyrolactone. The strain *A. terreus* NIH 2624, a patient isolate, was sequenced by the Broad Institute as part of the Broad Fungal Genome Initiative. A 10 × coverage genome sequence has been completed, and the data are publicly available through the Broad Institute website. Analysis by Secondary Metabolite Unique Regions Finder (SMURF) showed that *A. terreus* NIH2624 contains 28 polyketide synthase (PKS) genes, 22 non-ribosomal peptide synthetase (NRPS) genes, one hybrid PKS/NRPS gene, two PKS-like genes, and 15 NRPS-like genes (Khaldi et al., 2010). This review will cover the most current knowledge of the genome mining of SMs produced by *A. terreus*. The review consists of three major sections: genome mining of PKS-derived natural products, genome mining of NRPS-derived natural products, and genome mining of hybrid PKS-NRPS derived natural products by *A. terreus*.

## **GENOME MINING OF PKS-DERIVED NATURAL PRODUCTS IN** *A. TERREUS*

## **BIOSYNTHESIS OF LOVASTATIN IN** *A. TERREUS*

Perhaps the most well-known molecule produced by *A. terreus* is lovastatin. Lovastatin is an inhibitor of the enzyme (3*S*)-hydroxymethylglutaryl-coenzyme A (HMG-CoA) reductase which reduces HMG-CoA to mevalonate. The biosynthesis of lovastain has been extensively reviewed in literature reports (Hill, 2006; Cox, 2007; Campbell and Vederas, 2010; Chiang et al., 2010; Chooi and Tang, 2012). Two highly reducing PKSs (HR-PKSs), LovB (lovastatin nonaketide synthase) and LovF, play critical roles in the formation of the lovastatin core structure (**Figure 1**). In the pathway, the HR-PKS LovB, together with the trans-acting enoyl reductase (ER) protein LovC, are responsible for the production of dihydromonacolin L acid (**1**). The release of **1** from LovB is catalyzed by a thioesterase LovG (Xu et al., 2013a). The oxidative conversion of **1** to monacolin J acid (**2**) involves LovA. The other HR-PKS LovF synthesizes the 2-methylbutyrate moiety of lovastatin (**3**) and the covalent attachment of this moiety to **2** is catalyzed by a transesterase, LovD (**Figure 2**). Recent efforts

in engineering LovD using a directed evolution strategy generated a mutant LovD containing 29 point mutations that greatly improves (∼1000 fold) the protein's efficiency in the synthesis of the drug simvastatin (Jimenez-Oses et al., 2014), representing an excellent example of how the combination of synthetic biology and protein chemistry may facilitate drug discovery and production.

#### **BIOSYNTHESIS OF TERRETONIN IN** *A. TERREUS*

Terretonin is one type of meroterpenoids with mixed origins (**Figure 3**). Previous studies by Simpson and Vederas in the 1980's using isotopic labeled precursors have shown that terretonin originates from both polyketide and terpenoid pathways (McIntyre et al., 1982, 1989). Recent genome mining studies revealed that the terretonin cluster contains a total of 10 genes (Guo et al., 2012). The cluster includes a non-reducing PKS (NR-PKS) gene, *trt4* (ATEG\_10080.1), and a prenyltransferase gene, *trt2* (**Figure 1**). Trt4 is responsible for the biosynthesis of 3,5 dimethylorsellinic acid (**4**) and Trt2 catalyzes the alkylation of compound **4** to give **5** (**Figures 1**, **3**) (Guo et al., 2012; Itoh et al., 2012). The following methylation (**5** to **6**), epoxidation (**6** to **7**) and cyclization (**7** to **8**) are proposed to be catalyzed by proteins encoded by *trt5*, *trt8*, and *trt1*, respectively (Guo et al., 2012; Matsuda et al., 2012). Interestingly, the Abe group discovered that the methylation step catalyzed by Trt5 is an essential step for cyclization (Matsuda et al., 2012). Upon formation of the tetracyclic precursor, Trt9 is proposed to oxidize compound **9** to **10** and Trt3 hydroxylases **10** to give **11** (**Figure 3**). Next, the putative protein Trt6 catalyzes the intra-lactonization reaction to give **12**, while the conversion of **12** to terretonin (**13**) might involve other enzymes that are not identified by Guo et al. (2012).

#### **BIOSYNTHESIS OF 10,11-DEHYDROCURVULARIN IN** *A. TERREUS*

The polyketide origin of the compound 10,11-dehydrocurvularin (**14**) was established by incorporation of stable isotope labeled precursors (Arai et al., 1989). The biosynthetic cluster for 10,11-dehydrocurvularin was identified in *A. terreus* AH-02- 30-F7. The cluster is proposed to contain four genes, an HR-PKS gene (*Atcurs1*), an NR-PKS gene (*Atcurs2*), a GAL4-like transcription regulatory gene (*AtcursR*) and a major facilitator superfamily gene (*AtcursE*) (**Figure 1**) (Xu et al., 2013b). The biosynthesis of 10,11-dehydrocurvularin in *A. terreus* was characterized by heterologous expressing the HR-PKS and NR-PKS pair in *Saccharomyces cerevisiae* (Xu et al., 2013b). In the pathway, the HR-PKS AtCURS1 is proposed to synthesize the tetraketide 7(*S*)-hydroxyotc-2(*E*)-enoic acid (**Figure 4**). This tetraketide is then loaded onto the starter unit ACP transacylase domain (SAT) of AtCURS2, followed by four chain extension cycles to release the final product **14**. In the cluster, the gene *AtcursR* is predicted to encode for a fungal transcription regulator and *AtcursE* may code for an exporter involved in the transporting of 10,11 dehydrocurvularin (**14**) (Xu et al., 2013b). Further investigation of the product template (PT) domain of AtCURS2, which catalyzes the ring cyclization and aromatization, revealed that the cyclization mode of this domain could be reshaped from the bacterial folding mode, as shown in the biosynthesis of compound **14**, to the fungal mode by three selected point mutations (Xu et al., 2013c). Such rational control of fungal polyketide ring cyclization should facilitate the engineering of natural products with novel chemical scaffolds.

#### **BIOSYNTHESIS OF ASPERFURANONE IN** *A. TERREUS*

The azaphilone asperfuranone (**20**) was first isolated from *A. nidulans* after activating two PKSs encoded by *afoE* and *afoG* (Chiang et al., 2009). Later a highly homologous cluster was identified in the *A. terreus* genome (**Figure 1**) (Chiang et al., 2013). In this case, the individual genes from *A. terreus* were heterologously expressed in *A. nidulans* and the whole asperfuranone pathway was reconstituted. The asperfuranone cluster in *A. terreus* contains a total of seven genes including two PKS genes

*ateafoE* and *ateafoG* (**Figure 1**). In the pathway, the gene *AteafoG* encodes the HR-PKS that is responsible for the production of the PK intermediate **15**. The enzyme AteafoC might facilitate the transfer of the side chain **15** from AteafoG to AteafoE. Next, AteafoD catalyzes the dearomatization of the precursor **16** to give intermediate **17**, followed by hydroxylation by AteafoF to **18**. Last, the authors proposed the existence of an endogenous reductase in *A. nidulans* that catalyzes the conversion of **19** to asperfuranone (**20**) (**Figure 5**).

### **BIOSYNTHESIS OF TERREIN IN** *A. TERREUS*

The terrein (**25**) cluster was serendipitously identified while the Brock group were initially looking for secondary metabolites that are involved in the biosynthesis of conidia pigment in *A. terreus* (Zaehle et al., 2014). Previous isotope-labeling studies revealed that the biosynthesis of terrein originates from a polyketide-based pathway (Birch et al., 1965) and involves the contraction of a six-membered ring precursor to give the five-membered ring terrein (**25**) (Hill et al., 1981). The terrein cluster contains a total of 11 genes, including an NR-PKS gene *terA* (ATEG\_00145.1) and a transcription factor gene, *terR* (**Figure 1**). In the terrein biosynthetic pathway as shown in **Figure 6**, the NR-PKS encoded by *terA* condensates one acetyl-CoA and four malonyl-CoA to synthesize the precursor 2,3-dehydro-6-hydroxymellein (**23**). Heterologous expression of *terA* in *A. niger* revealed that the NR-PKS TerA is also capable of producing compounds **21** and **22** by incorporating different number of malonyl-CoAs as substrates. The reduction of compound **23** to 6-hydroxymellein (6-HM) (**24**) is probably catalyzed by TerB, but it is also possible that other unspecific ketoreductases may perform this reduction. The authors proposed that the conversion of 6-HM (**24**) to the final product terrein (**25**) might involve four genes, *terC*, *terD*, *terE*, and *terF* while the specific roles of these genes await further verification. Interestingly, the study also revealed that

terrein (**25**) has phytotoxic activity. In the two experiments, terrein (**25**), rather than the intermediates or shunt products, inhibited root elongation and caused lesions on fruit surface (Zaehle et al., 2014), representing a prime example of how fungal secondary metabolites might play a role in fungus-plant interactions.

### **BIOSYNTHESIS OF TERREIC ACID IN** *A. TERREUS*

Terreic acid (**30**) is a natural product isolated from *A. terreus* with anti-bacterial activity (Yamamoto et al., 1980). A later study recognized its inhibitory effect against Bruton's tyrosine kinase (Btk), and this compound has been used as a chemical probe to examine the function of Btk (Kawakami et al., 1999). Previous research using isotope-labeled precursors has shown that the biosynthesis of terreic acid originated from one polyketide, 6 methylsalicylic acid (6-MSA, **26**) (Read and Vining, 1968; Read et al., 1969). The PKS gene *atX* was cloned and identified as a 6-MSA (**26**) synthase (Fujii et al., 1996). A recent bioinformatic analysis study predicts that the PKS gene *atX* and its surrounding genes encodes the biosynthetic cluster which is responsible for terreic acid biosynthesis (Boruta and Bizukojc, 2014). The cluster was experimentally characterized using a targeted gene deletion method (Guo et al., 2014). The cluster contains a total of eight genes, including a partially reducing PKS (PRPKS) gene, *atX*, and a transcription factor gene *atF* (**Figure 1**). The pathway starts with the formation of 6-MSA (**26**) by AtX using one acetyl-CoA and three malonyl-CoA units as its substrates, followed by a decarboxylative hydroxylation catalyzed by AtA to give **27**. Compound **27** could be degraded to a shunt product, (2*Z*,4*E*)- 2-methyl-2,4-hexadienedioic acid. The degradation of **27** may be catalyzed by a putative catechol 1,2-dioxygenase in *A. terreus*, but the coding gene for this enzyme is not identified in the terreic acid cluster (Guo et al., 2014). The hydroxylation of **27** to give **28** is possibly catalyzed by AtE. The oxidative conversion of **28** to **29** might involve AtG, but this proposal is not confirmed in the study. Last, AtC catalyzes the oxidation of compound **29** to give the final product terreic acid (**30**) (**Figure 7**).

## **IDENTIFICATION OF THE PRODUCTS OF SIX NR-PKS GENES IN** *A. TERREUS*

The previous studies successfully linked several PKS-derived SMs with their biosynthetic clusters in *A. terreus*. Using a heterologous expression strategy, researchers also identified the products of six NR-PKS genes in *A. terreus* (Chiang et al., 2013). The products of these NR-PKSs are shown in **Table 1**. The NR-PKS encoded by ATEG\_00145.1 synthesizes a mixture of compounds, **21**, **22**, **23**, and **31**. The plasticity of ATEG\_00145.1 is also demonstrated in the study of terrein biosynthesis (Zaehle et al., 2014). The products of the NR-PKS, encoded by ATEG\_03432.1, are compounds **32** and **33**, and the product of the ATEG\_03629.1 encoded NR-PKS is **34**. The NR-PKS atrochrysone carboxylic acid synthase (ACAS) encoded by ATEG\_08451.1 produces atrochrysone **35** and its derivative emodin **36** with the aid of a β-lactamase encoded by ATEG\_08450.1. This result matches the previous finding reported by Awakawa et al. (2009) As expected, ATEG\_10080.1 (*trt4*) synthesizes and releases the PKS product 3,5-dimethylorsellinic acid (**4**), which is presumed to be the first precursor in the biosynthesis of terretonin (**Figure 3**) (Guo et al., 2012; Itoh et al., 2012). As aforementioned, the products of the NR-PKS AteafoE and its adjacent HR-PKS AteafoG incorporate into the asperfuranone pathway as shown in **Figure 5** (**Table 1**).

## **BIOSYNTHESIS OF NRPS-DERIVED NATURAL PRODUCTS IN** *A. TERREUS*

#### **BIOSYNTHESIS OF ACETYLARANOTIN IN** *A. TERREUS*

Acetylaranotin belongs to one group of SM toxins named epipolythiodioxopiperizine (ETP). This type of natural products is usually featured by the presence of unique di- or poly-sulfide bridges. The di- or poly-sulfide bridges are presumed to mediate the molecule's cytotoxicity, either by cross-linking vital proteins via cysteine bonds, or by generating reactive oxygen species via redox cycling (Scharf et al., 2011a). An early study using stable isotope-labeled precursors showed that the diketopiperazine (DKP) precursor, compound **37**, could be incorporated intact into acetylaranotin (**44**) (Boente et al., 1981). This indicates that the acetylaranotin pathway may include an NRPS that catalyzes the condensation of two L-phenylalanines to give **37**. Bioinformatic analysis of the ETP clusters dispersed in filamentous ascomycetes uncovered two putative clusters in *A. terreus* that might encode the biosynthetic pathway for acetylaranotin (Patron et al., 2007).

Using the gene targeted deletion strategy, one of the two clusters, named *ata* cluster, was found to be responsible for acetylaranotin production in *A. terreus* (Guo et al., 2013b). The *ata* cluster contains a total of nine genes, including one NRPS gene, *ataP* (**Figure 1**). In the pathway, the NRPS AtaP catalyzes the condensation of two phenylalanines to give compound **37**. Next, the C domain of the protein AtaTC is proposed to catalyze the dual hydroxylation of compound **37** to **38**. A series of studies have fully elucidated the functions of the enzymes that are involved in the installation of the disulfide moiety in gliotoxin (Scharf et al., 2010, 2011b, 2012, 2013; Schrettl et al., 2010; Davis et al., 2011; Gallagher et al., 2012). Similar to their homologs in the gliotoxin cluster, AtaG, AtaJ, AtaI are involved in the conversion of the dual hydroxyl groups in **38** to thiol groups in **39**, followed by the AtaT-mediated

#### **Table 1 | The core synthesis genes and their products identified in** *A. terreus***.**

*(Continued)*

#### **Table 1 | Continued**

#### **Table 1 | Continued**

*Domains shown in bracket are supposed to be non-functional.*

oxidation to form the transannular disulfide bridge as shown in intermediate **40**. Next, AtaF catalyzes the dual epoxidation of **40** followed by the spontaneous nucleophilic attack of the amide nitrogens to yield intermediate **41**. The acetylation of **41** to **42** is catalyzed by AtaH, and the oxepine ring formation involves the protein AtaY to yield acetylaranotin **44** (**Figure 8**). The proteins AtaH and AtaY can function independently, but the detailed catalytic mechanism of AtaY still awaits further investigation. Two recent studies unveiled that the *S*-alkylation of gliotoxin was catalyzed by a SAM dependent methyltransferase encoded by a gene *tmtA/gtmA* outside the gliotoxin cluster (Dolan et al., 2014; Scharf et al., 2014). These studies suggest that the *S*-methylation of acetylaranotin to give bisdethiobis(methylthio)acetylaranotin is likely to be catalyzed by a methyltransferase encoded by a gene outside the acetylaranotin cluster.

### **IDENTIFICATION OF THE PRODUCTS OF FOUR NRPS OR NRPS-LIKE GENES IN** *A. TERREUS*

Screening of the genome-sequenced strain *A. terreus* NIH 2624 showed that this fungus is able to biosynthesize four main types of secondary metabolites including aspulvinones, butyrolactones, asterriquinones, and aszonalenins (Guo et al., 2013a). The NRPSorigin of these four types of natural products was revealed in previous studies (Kiriyama et al., 1977; Nitta et al., 1983; Balibar et al., 2007; Yin et al., 2009). To link these molecules to their core synthesis NRPS genes, a mutant library was created by individually deleting a total of 21 NRPS or NRPS-like genes in *A. terreus*. Screening of the mutants' SM profiles, in comparison with that of the wild type, showed that three NRPS-like genes *atqA* (ATEG\_00700.1), *apvA* (ATEG\_02004.1), and *btyA* (ATEG\_02815.1), are responsible for the synthesis of the core structures of asterriquinones, aspulvinones, and butyrolactones, respectively (**Table 1**) (Balibar et al., 2007; Guo et al., 2013a). The NRPS gene *anaPS* encoded by ATEG\_10305.1 is proposed to biosynthesize the (R)-benzodiazepinedione core (**Table 1**) (Yin et al., 2009; Guo et al., 2013a). Serendipitously, deletion of one NRPS-like gene *atmelA* (ATEG\_03563.1) generates an albino mutant that abolishes the brown conidia melanin in *A. terreus*. It is possible that AtmelA synthesizes the first precursor that incorporates into the conidia pigment produced by *A. terreus*. Since all the identified conidial melanins in other *Aspergillus* species are derived from a PKS pathway, another possibility is that this NRPS-like gene might be involved, but not directly related in the melanin biosynthesis of *A. terreus* (Guo et al., 2013a).

## **AN NRPS-LIKE GENE IS INVOLVED IN ACTIVATING AND REDUCING OF AN ARYL ACID RELEASED FROM AN NR-PKS**

Zhao group recently reported that an NRPS-like protein encoded by ATEG\_03630.1 could catalyze the reduction of compound **34** to an aryl aldehyde (Wang et al., 2014). Compound **34** is released by its adjacent NR-PKS ATEG\_03629.1, The putative domain architecture of the NRPS-like protein is A-T-R. The aryl acid product **34**, upon its release from the TE domain of the NRPKS, is then loaded onto the A domain. And the R domain is responsible for the reduction of the aryl acid **34** to its aldehyde form (Wang et al., 2014). Interestingly, a subsequent study revealed that the substrate of the A domain of this NRPS-like enzyme could be engineered to anthranilate via bioinformatic analysis and mutagenesis (Wang and Zhao, 2014).

## **BIOSYNTHESIS OF HYBRID PKS-NRPS NATURAL PRODUCTS IN** *A. TERREUS*

### **BIOSYNTHESIS OF ISOFLAVIPUCINE IN** *A. TERREUS*

Only one hybrid PKS-NRPS gene, ATEG\_00325.1, can be identified in the genome of *A. terreus* NIH 2624. The Brock group identified that the PKS-NRPS encoded by this hybrid gene is responsible for the core synthesis of isoflavipucine and dihydroisoflavipucine (Gressler et al., 2011). RT–PCR analysis of expression of the hybrid gene and its surrounding genes, under isoflavipucine producing condition, suggested that the cluster for isoflavipucine biosynthesis might contain five genes, ATEG\_00325.1, ATEG\_00326.1 (transcription factor gene), ATEG\_00329.1, ATEG\_00330.1, and ATEG\_00331.1 (**Figure 1**) (Gressler et al., 2011). In the pathway, the hybrid PKS-NRS synthesizes and releases the linear precursor (**49**). The conversion of the precursor **49** to final product includes heterocyclization (**49** to **50**), oxidation (**50** to **51**), transamination and ring arrangement (**51** to **52**), and epoxidation to give flavipucine (**53**) (**Figure 9**). However, the enzymes that are responsible for the conversion of the linear precursor **45** to isoflavipucine (**54**) are not identified in this study and needs further investigation.

#### **CONCLUSION**

In the fungus *A. terreus*, most of the genome mining experiments are carried out in the strain NIH 2624 because it is the only *A. terreus* strain in which the genome sequence is publicly available. A combination of bioinformatic analysis and experimental verification have enabled researchers to elucidate the functions of genes and proteins that are involved in the biosynthesis of several SMs produced in *A. terreus*. However, as shown in **Table 1**, there are still many other SM genes or gene clusters in *A. terreus* whose products still remain elusive. With the advance of genome sequencing and manipulation techniques, an increasing amount of effort will focus on deciphering the products of these silent or cryptic genes or gene clusters, as well as engineering the characterized pathways to produce second generation molecules with improved bioactivities.

## **ACKNOWLEDGMENTS**

Chun-Jun Guo was supported by the National Science Foundation—Emerging Frontiers in Research and Innovation-MIKS (Grant 1136903). Research conducted in the lab of Clay C. C. Wang is supported by the National Institute of General Medical Sciences GM084077, the National Science Foundation— Emerging Frontiers in Research and Innovation-MIKS (Grant 1136903), the Department of Energy, Bioenergy Technologies office, the Department of Defense Strategic Environmental Research and Development program (SERDP), and the National Aeronautics and Space Administration Space Biology program.

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bis-thiomethylation attenuates gliotoxin biosynthesis in *Aspergillus fumigatus*. *Chem. Biol.* 21, 999–1012. doi: 10.1016/j.chembiol.2014.07.006

nonaketide synthase turnover in lovastatin biosynthesis. *Angew. Chem. Int. Ed. Engl.* 52, 6472–6475. doi: 10.1002/anie.201302406

Zaehle, C., Gressler, M., Shelest, E., Geib, E., Hertweck, C., and Brock, M. (2014). Terrein biosynthesis in *Aspergillus terreus* and its impact on phytotoxicity. *Chem. Biol.* 21, 719–731. doi: 10.1016/j.chembiol.2014.03.010

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 29 October 2014; paper pending published: 15 November 2014; accepted: 01 December 2014; published online: 23 December 2014.*

*Citation: Guo C-J and Wang CCC (2014) Recent advances in genome mining of secondary metabolites in Aspergillus terreus. Front. Microbiol. 5:717. doi: 10.3389/fmicb. 2014.00717*

*This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology.*

*Copyright © 2014 Guo and Wang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

## Fungal secondary metabolite dynamics in fungus–grazer interactions: novel insights and unanswered questions

## *Marko Rohlfs\**

Johann-Friedrich-Blumenbach Institute of Zoology and Anthropology, Georg-August-University Göttingen, Göttingen, Germany

#### *Edited by:*

Ozgur Bayram, National University of Ireland Maynooth, Ireland

#### *Reviewed by:*

Jeffrey William Cary, United States Department of Agriculture – Agricultural Research Service, USA Frank Kempken, Christian-Albrecht Kiel University, Germany

#### *\*Correspondence:*

Marko Rohlfs, Johann-Friedrich-Blumenbach Institute of Zoology and Anthropology, Georg-August-University Göttingen, Berliner Strasse 28, 37073 Göttingen, Germany e-mail<EMAIL_ADDRESS>
In response to fungivore grazing fungi are assumed to have evolved secondary metabolitebased defense mechanisms that harm and repel grazers, and hence provide a benefit to the metabolite producer. However, since research into the ecological meaning of highly diverse fungal secondary metabolites is still in its infancy, many central questions still remain. Which components of the enormous metabolite diversity of fungi act as direct chemical defense mechanisms against grazers? Is the proposed chemical defense of fungi induced by grazer attack? Which role do volatile compounds play in communicating noxiousness to grazers? What is the relative impact of grazers and that of interactions with competing microbes on the evolution of fungal secondary metabolism? Here, I briefly summarize and discuss the results of the very few studies that have tried to tackle some of these questions by (i) using secondary metabolite mutant fungi in controlled experiments with grazers, and by (ii) investigating fungal secondary metabolism as a flexible means to adapt to grazer-rich niches.

**Keywords:** *Aspergillus***, chemical defense regulation, fungivory, inducible resistance, secondary metabolites**

## **INTRODUCTION**

Fungal metabolism is an important source of an apparently endless diversity of organic compounds which are not obviously required for the producer's normal growth and metabolism – one reason why they are called secondary metabolites (SMs). This chemical diversity raises a pertinent yet hardly addressed basic research question in fungal biology: why are SMs produced in such variety, especially since the SM biosynthesis is encoded in clusters of genes whose transcriptional activation is embedded in a tightly regulated network comprising the activity of signaling pathways, epigenetic regulators, fungal hormones, and cellular secretion processes (Tsitsigiannis and Keller, 2007; Roze et al., 2011; Brakhage, 2013)?

Because many fungal SMs are toxic to other organisms, in particular animals, one line of arguments follows the idea that fungi produce specific SMs as direct defense compounds to achieve protection from grazers foraging for nutrient-rich food sources (e.g., Janzen, 1977; Martin, 1979; Camazine et al., 1983; Vining, 1990; Gloer, 1995; Spiteller, 2008). Putative direct defense compounds have emerged primarily due to pharmacological evidence for their deleterious effects on grazers. This evidence stems from studies that report relationships between fungivore mortality, decreased fecundity, and feeding on purified compounds mixed into artificial diets or on fungi expressing the proposed chemical defense trait constitutively (e.g., Wright et al., 1980; Paterson et al., 1987; Panigrahi, 1993; Gloer, 1995; Rohlfs and Obmann, 2009). Such studies provide at best weak correlative evidence as they do not evaluate whether these compounds increase fungal fitness under grazing pressure, which is the defining criterion of a chemical compounds-based defense.

In a series of recent studies (see below), the use of genetically modified fungi manipulated in the expression of candidate defense gene products has corroborated the relationship between SM regulatory mechanisms and resistance against grazers, yet manipulation of pathway-specific defense products have revealed conflicting results. Moreover, first studies have demonstrated complex chemical changes in fungi after fungivore attack, which could in part be related to changes in the capacity to resist grazing. The present review intends to provide a critical discussion of these recent findings and stimulate more research into the ecological causes and consequences of fungal chemical diversity.

## **INVESTIGATING FUNGAL RESISTANCE WITH GENETICALLY MANIPULATED FUNGI**

Since more than a decade, functional genetic approaches have provided unparalleled insights into how fungi regulate their chemical diversity. Despite the availability of an increasing number of well– controlled mutant fungi, functional evaluations have largely been restricted to biochemical and medical aspects of fungal biology. Very few studies have used genetically modified fungi to conduct functional analyses of SM genes in the context of interactions with grazers.

### **GLOBAL SM REGULATION**

Six of these studies focused on *Aspergillus* spp. *laeA* loss-offunction mutants in interactions with different soil arthropods, Collembola, (Rohlfs et al., 2007; Janssens et al., 2010; Staaden et al., 2011; Stötefeld et al., 2012) or facultative fungivorous *Drosophila melanogaster* larvae (Trienens et al., 2010; Caballero Ortiz et al., 2013). The methyltransferase-domain protein LaeA is essential for both appropriate developmental processes coupled with the biosynthesis of various SMs, including mycotoxins, such as

sterigmatocystin (Bok and Keller, 2004; Sarikaya Bayram et al., 2010). Chemical deficient *laeA Aspergillus* sp. mutants generally are less detrimental to grazer fitness than wild type fungi (reduced mortality, enhanced reproductive output) and, when given the choice, fungivores prefer grazing on the *laeA* mutants. The latter appears to be mediated by a combined effect of differences in both the non-volatile SM and the volatile chemical profile (Staaden et al., 2011; Stötefeld et al., 2012). The LaeA-dependent capacity to harm insect grazers seems to be fungal species-specific though: while *laeA Aspergillus nidulans* almost entirely lost the potential to kill fruit fly *D. melanogaster* larvae, *laeA A. flavus* and *laeA A. fumigatus* were still fatal to the insects, yet the onset of larval mortality was significantly delayed (Trienens et al., 2010). Importantly, compared to wild type, the lack of expression of *laeA* in all fungi tested increased their susceptibility to grazer damage (Rohlfs et al., 2007; Trienens et al., 2010; Stötefeld et al., 2012).

Loss of the capacity to kill fruit fly larvae was also evident for *A. nidulans* impaired in the expression of VeA (Trienens and Rohlfs, 2012), which indicates that an intact velvet (VelB-VeA-LaeA) complex (Bayram et al., 2008) is required for building resistance against grazers. Therefore, global regulatory mechanisms controlling both SM diversity and development have a distinct function in mediating protection from fungivore attack, and I would predict a similar role of these mechanisms in fungi beyond *Aspergillus*.

## **PATHWAY-SPECIFIC SM REGULATION**

A review of the literature indicates that there are only five published studies that have used pathway-specific mutant strains to test for the influence of single SMs on the outcome of interactions with fungivores (Scheu and Simmerling, 2004; Staaden et al., 2010; Trienens and Rohlfs, 2012; Yin et al., 2012; Cary et al., 2014). As demonstrated by the use of knock-out mutants in feeding assays with Collembola, *Folsomia candida* and *Protaphorura armata*, and the nitidulid beetle *Carpophilus freemani*, polyketide synthase-driven formation of pigments dihydroxynaphthalene melanin in *A. fumigatus* conidia and asparasone A in sclerotia of *A. flavus* proved to impair or deter grazers, respectively, (Scheu and Simmerling, 2004; Cary et al., 2014). The latter is of particular interest because it is the first demonstration of a grazer-deterring compound whose biosynthesis is confined to fungal tissue that has a special function in ensuring survival under unfavorable conditions. However, how such pigments contribute to directly repelling grazers is unknown.

The polyketide sterigmatocystin is a characteristic mycotoxin of *A. nidulans*, which has insecticidal properties (Chinnici et al., 1983; Rohlfs and Obmann, 2009). In accordance with the proposed role of sterigmatocystin in mediating resistance against grazers, Collembola avoided feeding on a mutant *A. nidulans* strain over-expressing the bZIP transcription factor gene, *rsmA*, which results in a great increase of sterigmatocystin (Yin et al., 2012). RsmA activates the C6 transcription factor AflR, the ST pathway-specific regulatory factor required for transcriptional activation of ST biosynthetic genes. One would expect a benefit to grazers when exposed to *A. nidulans* deficient in the formation of sterigmatocystin. Interestingly, this hypothesis was not

supported by Trienens and Rohlfs (2012). Compared with mortality in the presence of sterigmatocystin-producing wild type *A. nidulans*, *Drosophila* larvae did not demonstrate increased survival when confronted with 1-day old *A. nidulans* mutants (*aflR*, *stcJ*, *stcE*, *stcU*) incapable of producing sterigmatocystin. To our surprise, when the insects were exposed to initially 2-days old colonies, larvae suffered even higher mortality on substrate infested with the sterigmatocystin deficient mutant strains (Trienens and Rohlfs, 2012). A similar grazer response was observed when *F. candida* was offered a sterigmatocystin deficient *aflR A. nidulans* mutant: relative to the wild type strains (Rohlfs et al., 2007), the Collembola suffered unusually high mortality and did not reproduce whatsoever (Albert, 2007). Thus, even though an artificial increase in sterigmatocystin biosynthesis enhances the capacity of *A. nidulans* to resist grazing, the loss of this compound does not reduce resistance as one would expect.

In conclusion, sterigmatocystin does not seem to be the major anti-grazer compound in wild type *A. nidulans*. In contrast, sterigmatocystin biosynthesis appears to hamper the ability of *A. nidulans* to develop even better protection against grazers. In search for an explanation of this phenomenon, one could argue that there are only a few key intermediates of the basic metabolic pathways that provide the starting points for the SM pathways. For example, acetyl-CoA is the precursor molecule for compound biosynthesis from the polyketide and the isoprenoid pathway. Possibly, artificial inactivation of the sterigmatocystin pathway leads to higher amounts of acetyl-CoA available for shunting into other pathways which produce more efficient anti-grazer compounds. If this turns out to be an adequate explanation for sterigmatocystin deficient *A. nidulans* being more detrimental to grazers than the wild type, fungi may suffer ecological costs of (high) SM diversity. And perhaps global, e.g., LaeA-dependent, regulatory mechanisms might prove to constrain fungi in activating the optimal combination of pathways for conquering grazers with a less diverse but more effective blend of SMs.

## **RESPONSES OF FUNGI TO GRAZERS**

It has been well appreciated that fungal chemical phenotypes can vary with abiotic conditions such as light, water, temperature or the availability of nutrients (Schmidt-Heydt et al., 2008; Atoui et al., 2010; Schmidt-Heydt et al., 2010; Nielsen et al., 2011). Also, interactions with bacteria have been established as critical determinants of fungal SM composition (Brakhage and Schroeckh, 2011). Some recent analyses of the chemical responses to animal grazers provide first evidence of an inducible chemical compound-based defense response in fungi, which comprises the biosynthesis of so-called cryptic metabolites.

### **EVIDENCE FROM** *Aspergillus nidulans*

Grazing by Collembola, *F. candida*, was found to induce an increase in the formation of sterigmatocystin, some meroterpenoids (mixed polyketide/terpenoid orign) and emericellamides (mixed polyketide/peptide origin) in*A. nidulans*(Döll et al.,2013). In choice experiments, Collembola preferred un-grazed colonies to grazed, probably due to changes in the volatiles released by damaged colonies (Staaden et al., 2011), and when forced to feed

**FIGURE 1 | Images depicting the localized formation of guttation droplets on the sexual fruiting bodies (cleistothecia) of** *A. nidulans***, which are possibly involved in mediating protection from grazing by Collembola (see Döll et al., 2013). (A)** To the left of the initial stage (primodium) of a cleistothecium (asterisk) a strikingly large droplet (arrow) is formed in addition to some smaller ones. The whitish appearance of the primordium is due to layers of so-called Hülle cells which are assumed to nurse and protect the developing ascospores within the cleistothecium. It is not obvious whether the guttation droplets are produced by the Hülle cells or aerial hyphae surrounding the fruiting bodies. **(B)** A cluster of larger cleistothecia (asterisk), surrounded by a dark mat of conidia-producing tissue. The cluster is covered by voluminous droplets of light-brown color (arrow). Numerous smaller and apparently colorless droplets attached to single aerial hyphae are also visible.

on un-grazed or grazed mold the animals grew slower on previously attacked colonies. Moreover, grazer-challenged *A. nidulans* colonies intensified significantly the formation of sexual fruiting bodies (cleistothecia), which appeared to be the only fungal tissue that was not consumed after prolonged grazing (Döll et al., 2013). Possibly, the positive correlation of the appearance of cleistothecia and the intensive formation of guttation droplets on the sexual fruiting bodies (**Figure 1**) is a means of protecting this valuable tissue from grazers. For example, guttation droplets produced by *Penicillium* and *Stachybotrys* are known to contain high amounts of toxic SMs (Gareis and Gareis, 2007; Gareis and Gottschalk, 2014), yet, no report exists on the SM content in *A. nidulans* guttation droplets exists (and whether it changes under grazer pressure). Nonetheless, at least for *A. nidulans*, combined investment in SM formation and sexual development seems to be a strategy to maintain high fitness in grazer-rich niches (**Figure 2**).

These findings are supported by an experiment that examined the effect of larval *Drosophila* grazing on the expression of *A. nidulans* genes. In the presence of the insect larvae, *A. nidulans* exhibited shifts in the transcriptional activity of many genes, including those involved in signal transduction, hormonal signaling, and SM biosynthesis (Caballero Ortiz et al., 2013); interestingly, *laeA* ranked highest among those genes that were found up-regulated in response to the insects. Comparable with the results of the Collembola-*A. nidulans* experiment described above, grazed wild type colonies were found to kill *Drosophila* fly larvae more rapidly than unchallenged ones. An intriguing finding here was that, in a subsequent experiment, *D. melanogaster* larvae were able to use a *laeA* mutant of otherwisefatal*A. nidulans* as the only available food source that promoted development into adult flies (Caballero Ortiz et al., 2013). That is LaeA-mediated activation of

SM formation in response to grazing to a large extent prevents the fungus from being consumed and used as a suitable diet by these facultative fungivores.

Finally, terpenoid compounds that function as hormones in arthropods, the so-called juvenile hormones (JH), have recently been found to be synthesized by *A. nidulans*, in particular under larval fruit fly grazing pressure (Nielsen et al., 2013). And when confronted with a JH over-expression mutant, fly larvae were significantly smaller. Possibly, the anti-grazer defense mechanisms of *A. nidulans* comprise the activity of insect hormone analogs that derange grazer endocrine processes.

Taken together, these findings illustrate the extent to which fungal morphological and chemical properties are affected by dynamic interactions with grazers and thereby reveal a number of new candidate defense pathways that may mediate direct resistance. Considering this chemical diversity of compounds we still lack convincing evidence for the identity of SMs used by fungi to repel and/or harm grazers. Even in this single *A. nidulans* system, it seems possible that more than one master defense compound exists, which are likely to interact with grazers via an array of perhaps equally diverse (patho-) physiological and behavioral mechanisms in the animals.

#### **EVIDENCE FROM OTHER FUNGI**

Using model fungal systems has many obvious advantages, yet there is a strong need to investigate the idea of inducible chemical compound-based resistance in other fungi. Outside the *A. nidulans* system, to the best of my knowledge, there is no good evidence of inducible chemical compound-based resistance in fungi. The study by Bleuler-Martínez et al. (2011) shows the induction of fruiting body lectins (carbohydrate-binding proteins) by nematode worms piercing hyphae and sucking in the cytoplasmatic content of *Coprinopsis cinerea*. In spite of this clear demonstration of an induced fungal response, it remains to be tested whether lectins provide an effective protection against the nematode or other grazers, since lectin toxicity has only been tested against nonfungivores (Bleuler-Martínez et al., 2011; Schubert et al., 2012; Žurga et al., 2014). Relevant to this discussion is the finding by Balogh et al. (2003), who did not find a positive influence of a lectin-deficient *Arthrobotrys oligospora* mutant on grazing by *F. candida*.

These very first studies illustrate the significance of grazing in determining the chemical profile of fungi but also the complexities and ambiguities involved in establishing a conceptually sound and direct connection between SM formation and fungal fitness. Therefore, separating functionally relevant from irrelevant chemical responses of fungi to grazing will be of utmost importance for the correct annotation of putative fungal defense traits that mediate protection from grazers. For example, genome-wide gene expression analyses should follow to reveal fungal responses to grazing the abovementioned studies may have overlooked.

### **CONCLUSION**

We are only beginning to appreciate fungal chemical dynamics under varying ecological conditions, and we should investigate deeper the full repertoire, kinetics, and sites of secondary metabolite biosynthesis in response to grazers to be able to update and rearrange the lists of putative defense compounds (in *A. nidulans* and other fungi) on the basis of inducible reactions. Carefully conducted experiments with model grazers (e.g., Collembola, *Drosophila* larvae, nematodes, etc.) exposed to purified compounds will shed light on the mode of action in fungivores, e.g., whether fungal chemicals decrease or suppress the feeding response, act as acute toxins that interfere with intermediary metabolism or cellularfunctions, or cause chronic tissue and organ malfunctions which ultimately lead to impaired development and reduced fecundity. Finally, a large fraction of fungal SMs likely have evolved to allow effective control of and/or communication with other microbes in their environment, and we should thus think about the possibility that it is not the grazer itself that is directly affected by specific metabolites, but the endogenous microorganisms fungivores require for the control of their immune system, food breakdown, and detoxification. Thus, in order to fully appreciate the complete anti-grazer potential of SM biosynthesis in fungi, we need to combine their inducible dynamics with the influence of these compounds on grazer behavior, physiology, and multi-species interactions in their environment.

## **ACKNOWLEDGMENT**

The author is funded by the German Research Foundation (Deutsche Forschungsgemeinschaft grant number: RO3523/3-2).

#### **REFERENCES**

asparasone, a sclerotium-specific pigment. *Fungal Genet. Biol.* 64, 25–35. doi: 10.1016/j.fgb.2014.01.001

**Conflict of Interest Statement:** The author declares that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 07 November 2014; accepted: 22 December 2014; published online: 13 January 2015.*

*Citation: Rohlfs M (2015) Fungal secondary metabolite dynamics in fungus–grazer interactions: novel insights and unanswered questions. Front. Microbiol. 5:788. doi: 10.3389/fmicb.2014.00788*

*This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology.*

*Copyright © 2015 Rohlfs. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

## Heterologous production of fungal secondary metabolites in Aspergilli

## *Diana Chinyere Anyaogu and Uffe Hasbro Mortensen\**

Section for Eukaryotic Biotechnology, Department of Systems Biology, Technical University of Denmark, Kongens Lyngby, Denmark

#### *Edited by:*

Nancy Keller, University of Wisconsin–Madison, USA

#### *Reviewed by:*

Clay Chia Chun Wang, University of Southern California, USA Wei Xu, University of California, Los Angeles, USA

#### *\*Correspondence:*

Uffe Hasbro Mortensen, Section for Eukaryotic Biotechnology, Department of Systems Biology, Technical University of Denmark, Soltofts Plads, Building 223, 2800 Kongens Lyngby, Denmark e-mail<EMAIL_ADDRESS>
Fungal natural products comprise a wide range of compounds. Some are medically attractive as drugs and drug leads, some are used as food additives, while others are harmful mycotoxins. In recent years the genome sequence of several fungi has become available providing genetic information of a large number of putative biosynthetic pathways. However, compound discovery is difficult as the genes required for the production of the compounds often are silent or barely expressed under laboratory conditions. Furthermore, the lack of available tools for genetic manipulation of most fungal species hinders pathway discovery. Heterologous expression of the biosynthetic pathway in model systems or cell factories facilitates product discovery, elucidation, and production.This review summarizes the recent strategies for heterologous expression of fungal biosynthetic pathways in Aspergilli.

**Keywords: secondary metabolite,** *Aspergillus***, gene clusters, fungi, heterologous expression, polyketide synthase**

### **INTRODUCTION**

Filamentous fungi produce a plethora of secondary metabolites, SMs, like polyketides (PK), terpenes, and non-ribosomal peptides (NRP). Several fungal SMs dramatically impact human life either because they are harmful mycotoxins, like carcinogenic aflatoxin (Eaton and Gallagher, 1994) and fumonisin (Voss and Riley, 2013), or because they are used to efficiently combat human disease, e.g., penicillin and lovastatin (Campbell and Vederas, 2010). Importantly, analyses of fully sequenced fungi show that the number of SMs known to be produced by these fungi is too low to account for the number of genes and gene clusters that potentially may lead to production of SMs (Szewczyk et al., 2008). This strongly suggests that the chemical diversity of the metabolomes produced by filamentous fungi is much larger than what is currently known, and it is therefore very likely that new harmful mycotoxins and new blockbuster drugs await discovery.

The rapid accumulation of fully sequenced genomes has accelerated the discovery of novel SMs dramatically. However, this sequence resource cannot be directly translated into chemical structures of new compounds despite that genes and gene clusters are often readily identified by bioinformatics tools (Khaldi et al., 2010; Andersen et al., 2013; Blin et al., 2013). For example, the exact structures of products released by fungal type I polyketide synthases are difficult to predict due to the iterative use of the different catalytic domains in these enzymes. Similarly, subsequent decorations performed by tailoring enzymes encoded by other genes in the cluster toward formation of the mature end product(s) are complex and not easy to predict. Another challenge is that many SMs are not readily produced under laboratory conditions although several approaches have been successfully employed to activate silent clusters (for reviews, see Brakhage and Schroeckh, 2011; Chiang et al., 2011; Klejnstrup

et al., 2012; Wiemann and Keller, 2014; Yaegashi et al., 2014). To link novel SMs to genes, and to map novel biosynthetic pathways, extensive genetic manipulations of the strains are typically required. Since, most new gene clusters uncovered by sequencing projects will be situated in fungi with no available genetic tools, this type of analysis may not be straight forward. Moreover, it may be difficult to purify sufficient amounts of a desired compound from these fungi to allow for thorough characterization of its bioactivity. An alternative approach is to transfer genes and gene clusters to hosts with strong genetic toolboxes thereby facilitating product discovery, production, and characterization. Here we review SM production in Aspergilli based cell factories. Considerations and strategies concerning central steps toward fungal SM production are presented for inspiration: choice of host, how to produce the first intermediate in the pathway, and how to establish the remaining part of the pathway.

## **HOST CHOICE FOR HETEROLOGOUS EXPRESSION OF FUNGAL SECONDARY METABOLITES**

Heterologous expression of SM genes has mainly been performed in baker's yeast *Saccharomyces cerevisiae* (Tsunematsu et al., 2013) and in the filamentous fungi *Aspergillus oryzae* and *A. nidulans*. Each of these model organisms offers specific advantages. For *S. cerevisiae* a superior genetic toolbox for strain construction has been developed and novel genes can easily be engineered into a wealth of single- and multi-copy expression plasmids or into chromosomes. For example, gene targeting and fusion of DNA fragments by homologous recombination (HR) is highly efficient in *S. cerevisiae*. Moreover, *S. cerevisiae* contains an insignificant endogenous secondary metabolism (Siddiqui et al., 2012). This fact simplifies the analysis of strains equipped with new pathways as they are not complicated by the presence of a multitude of other SMs; and the risk of undesirable side reactions due to cross chemistry between the novel and endogenous pathways is minimized. However, lack of secondary metabolism also means that yeast is not naturally geared for SM production and may contain limiting amounts of, or even lack, relevant building blocks (Kealey et al., 1998; Mutka et al., 2006). Moreover, localization of relevant enzymes for aflatoxin production into specialized vesicles in *A. parasiticus* indicate that fungi may possess specialized compartments for SM production, which yeast may not contain (Roze et al., 2011); and as introns are few in *S. cerevisiae* (Spingola et al., 1999) and differ from those in filamentous fungi (Kupfer et al., 2004), mRNA splicing could be problematic. For these reasons filamentous fungi may often be more appropriate for heterologous SM production. *A. oryzae* is often used for this purpose because it possesses a limited endogenous secondary metabolism and *A. nidulans* because a strong genetic toolbox has been developed for this fungus (for review see, Meyer, 2008; Meyer et al., 2011). Importantly, the recent development of efficient tools for gene targeting in filamentous fungi, including strains where random integration is minimized due to mutation of genes required for non-homologous end-joining (Ninomiya et al., 2004; Nayak et al., 2006; Takahashi et al., 2006), has further stimulated the use of these organisms as hosts for SM pathway reconstitution experiments.

## **HETEROLOGOUS EXPRESSION OF POLYKETIDE SYNTHASES**

The fact that the product(s) released by fungal type I PK synthases (PKSs) cannot easily be predicted from their primary sequence has sparked a major interest in expressing PKS genes in model fungi with the aim of identifying these products. In yeast, two 2 μ based multi-copy plasmids harboring the 6-methylsalicylic acid (6-MSA) synthase gene from *Penicillium patulum* and the PKS activating PPTase gene from *Bacillus subtilis* were successfully used to produce 6-MSA (Kealey et al., 1998). Similarly production of green pigment has been achieved in a *wA yA*- (white) *A. nidulans* (Holm, 2013) via co-expression of the PKS gene *wA* and laccase gene *yA* harbored on two AMA1 (Aleksenko and Clutterbuck, 1997) based plasmid. However, if multiple plasmids are needed to form a complex end-product, these vectors may have limited value since sufficient markers may not be available, and since 2 μ and AMA1 plasmids segregate unevenly during mitosis (Albertsen et al., 2011; Holm, 2013; Jensen et al., 2014).

More stable expression has been achieved by integrating PKS genes randomly into the genome of a model filamentous fungus via the non-homologous end-joining pathway. Using this concept, Fujii et al. (1996) successfully linked 6-MSA production to the PKS gene *atX* from *A. terreus* by expressing *atX* host *A. nidulans.* Considering that foreign SMs may be toxic in the new host, it is advisable to employ an expression strategy that minimizes this risk. For production of 6-MSA and enniatins in *A. nidulans* and *A. niger*, this was achieved by fusing the PKS and NRPS genes to the inducible promoters, amyB (Fujii et al., 1996) and Tet-on (Richter et al., 2014), respectively. Over the years, a number of other PKS genes have been linked to products using this strategy in *A. nidulans* and *A. oryzae* including the PKS genes for production of 1,3,6,8-tetrahydroxynaphthalene, alternapyrone, and 3-methylorcinaldehyde by (Fujii et al., 1999, 2005; Bailey et al., 2007).

Random integration may trigger unpredictable pleiotropic effects that alter the expression of neighboring genes, hence, complicating subsequent analyses (Verdoes et al., 1995; Palmer and Keller, 2010). Moreover, since multiple copies of the gene often integrate simultaneously into the same site, strains may suffer genetic instability and lose expression over time. Taking advantage of the development of strains and techniques for efficient gene targeting, these problems can be eliminated by inserting genes into a defined locus. This facilitates not only subsequent strain characterization, but also sets the stage for experiments analyzing mutant varieties of the gene where equal expression levels of the alleles are important to fairly judge the impact of individual mutations. Using this approach, Hansen et al. (2011) demonstrated that *mpaC* from *P. brevicompactum* encodes a PKS producing 5-methylorsellinic acid. In this case, *mpaC* was introduced into a defined site, *IS1*, on chromosome I of *A. nidulans*, which supports expression of non-toxic genes in a variety of tissues without affecting fitness. Moreover, to simplify the integration of genes into *IS1*, a set of vectors pre-equipped with targeting sequences, genetic markers, promoters and terminators and a USER-cloning cassette (Nour-Eldin et al.,2006) allowing for seamless ligation free insertion of relevant genes into the vector was developed. Using this technology, *ausA*, from *A. nidulans*, and *yanA*, from *A. niger*, have been shown to encode PKSs producing 3-,5-dimethyl orsellinic acid and 6-MSA, respectively (Nielsen et al., 2011; Holm et al., 2014). In a variation of this approach, Chiang et al. (2013) used fusion Polymerase chain reaction (PCR) to merge an *alcA* promoter and PKS genes followed by integration into the *wA* locus of *A. nidulans*. Correctly targeted transformants could therefore easily be identified as white colonies. The authors expressed nine non-reducing (NR) PKS genes from *A. terrreus* in this manner and identified six products. Heterologous production of PKs is complicated by the fact that not all synthases possess a domain providing a product release mechanism (Awakawa et al., 2009; Du and Lou, 2010) and by the fact that some PKSs require a starter unit different from Ac-CoA (Hoffmeister and Keller, 2007). In the study by Chiang et al. (2013), two of the nine NR-PKSs analyzed did not contain such a domain and for one, a product was achieved by co-expressing a gene encoding a thioesterase activity. In addition, two NR-PKS were predicted to employ unusual starter units. For one NR-PKS, production of this starter unit was successfully delivered by co-expressing a gene encoding a highly reducing PKS and the collaborative effort of the two enzymes resulted in production of an intermediate for production of asperfuranone (Chiang et al., 2013).

#### **TRANSFER OF GENE CLUSTERS TO HETEROLOGOUS HOSTS**

Reconstitution of most SM pathways depends on the expression of multiple genes since the SM scaffold delivered by the synthase is further decorated by tailoring enzymes. Moreover, genes providing transcriptions factors, transporters and/or a resistance mechanism may also be required. Construction of strains for heterologous end-product production is therefore a major challenge as it requires not only transfer, but also activation, of large gene clusters. Two principles are generally employed for constructing DNA fragments that allow transfer of gene clusters into another fungal host. Firstly, DNA fragments harboring entire, or a large part of, gene clusters have been identified in cosmid/fosmid libraries and transferred into vectors with a selectable fungal marker (**Figure 1A**). Secondly, PCR fragments covering the gene cluster have been stitched together using a variety of methods including USER Fusion, Gateway cloning and yeast recombination to create suitable transformation vectors (**Figure 1B**). When gene clusters have been transformed into the host, activation has been achieved by three different methods. Firstly, in cases where the native gene cluster harbors a TF gene, it has been possible to activate the genes in the cluster by equipping the TF gene with a constitutive or inducible promoter known to work in the host. Secondly, in gene clusters without a TF gene, activation has been achieved either by overexpressing the global regulator LaeA or by individually swapping cluster gene promoters for constitutive or inducible promoters. Like for integration of PKS genes, and for the same reasons, integration strategies based on random or directed integration have been used (**Figure 1C**). In many cases these strategies have been combined and successful examples are provided below.

Cosmids harboring the entire penicillin biosynthetic pathway from *P. chrysogenum* were introduced to *Neurospora crassa* and *A. niger*, resulting in the production of penicillin (Smith et al., 1990). Similary, cosmids harboring the citrinin biosynthetic pathway from *Monascus purpureus* and the monacolin K gene cluster from *Monascus pilosus* were individually integrated into random positions in the genome of *A. oryzae*. In the case of citrinin, the transformant directly produced citrinin, but in small amounts. However, as the cluster contains a TF gene, additional copies of the activator gene (*ctnA*) controlled by the *A. nidulans trpC* promoter were subsequently introduced in the strain to boost production. Impressively, this resulted in a 400 fold increase of citrinin production (Sakai et al., 2008). The monacolin K gene cluster does not contain a TF gene. In this case, the cluster was activated by overexpressing the gene encoding the global activator LaeA (Sakai et al., 2012). A limitation of this strategy may be difficulties in isolating cosmids containing a fragment that harbors the entire gene cluster, especially if clusters are large. For example, the reconstruction of the terrequinone A gene cluster in *A. oryzae* was based on a fosmid containing an incomplete gene cluster. The remaining part of the cluster was subsequently obtained by PCR, cloned into a vector and transformed into the *A. oryzae* strain harboring the partial terrequinone A gene cluster (Sakai et al., 2012).

Several PCR based strategies have been used for transferring gene clusters from the natural producer to a model fungus. For clusters harboring a TF gene, PCR fragments covering the entire gene cluster have been amplified, fused, and inserted via a single cloning step into vectors predestined for site specific integration in the genome of the host by HR. Multiple PCR fragments can be orderly assembled by different strategies. For example, PCR fragments of the geodin and neosartoricin B clusters were physically linked by *E. coli* based USER fusion and by yeast based HR, respectively (Nielsen et al., 2013; Yin et al., 2013). Importantly, in both cases the promoter controlling expression of the

TF gene was swapped for a strong constitutive promoter during the cluster re-assembly process. Large inserts (>15 kb) may not be propagated stably in a cloning vector and large clusters need to be subdivided into smaller fragment cassettes, which together represent the entire cluster. Multiple subsequent integrations depend on marker recycling, which can be achieved by using *pyrG* as a selectable/counterselectable marker. A faster method employs a two marker system for cluster transfer (Nielsen et al., 2013). During one transformation cycle, one of the markers is used to select for integration of the first cluster cassette and the other marker for the next cassette. By ensuring that integration of one cassette eliminates the marker contained by the preceding cassette, numerous cluster cassettes can be integrated sequentially by alternating the use of the two markers. Advantageously, when the gene clusters is inserted in a controlled manner it can be subjected to further genetic dissection to clarify the biochemical pathway toward end product. With the geodin cluster this was exploited to demonstrate that *gedL* encodes a halogenase using sulochrin as substrate (Nielsen et al., 2013).

Polymerase chain reaction based reconstruction of clusters that do not contain an activating TF gene requires more elaborate genetic engineering as all cluster genes need to be equipped with new promoters and terminators. In one strategy, cluster ORFs were inserted either individually or in pairs into expression cassettes in plasmids carrying different selection markers. Using this approach several small gene clusters containing four to five genes have been, fully or partially, reconstituted by randomly introducing the genes into the genome of *A.* oryzae. Several SMs have been achieved by this method including tennelin, pyripyropene, aphidicolin, terretonin, and andrastin A (Heneghan et al., 2010; Itoh et al., 2010; Fujii et al.,2011; Matsuda et al.,2012,2013). Construction of larger clusters in *A. oryzae* has been limited by the number of available markers. To bypass this problem, Tagami et al. (2013, 2014) used the high co-transformation frequency with *A. oryzae* to integrate two vectors in one round of transformation using selectionfor only one marker. This allowed for reconstituting clusters with six and seven genes for production of paxilline and aflatrem, respectively (Tagami et al., 2013, 2014). Addressing the same problem, Gateway cloning was used to construct expression vectors containing up to four genes (Pahirulzaman et al., 2012; Lazarus et al., 2014). Utilizing this approachWasil et al. (2013) expressed different combinations of the synthase and tailoring genes from the aspyridone pathway from *A. nidulans* in *A. oryzae*. An alternative approach to save markers is to generate synthetic polycistronic genes where all genes in the construct are under the control of a single promoter and where all ORFs are separated by a sequence encoding the viral 2A peptide that results in co-translational cleavage, hence, resulting in the formation of independent enzymes (Kim et al., 2011). Using this concept Unkles et al. (2014) reconstituted the penicillin gene cluster from *P. chrysogenum* as a single three ORF polystronic gene by yeast mediated HR. Random genomic integration of this construct resulted in penicillin production in *A. nidulans*.

A strategy for gene cluster activation based on promoter/terminator swapping has also been implemented in gene cluster transfer methods where genes are inserted into defined integration sites (Hansen et al., 2012; Mikkelsen et al., 2012;

Chiang et al., 2013). Specifically, expression plasmids containing one to two cluster genes were constructed by USER cloning or by fusion PCR and integrated into the expression sites in *S. cerevisiae* and *A. nidulans* to allow for production of the pigment precursor rubrofusarin in yeast (Rugbjerg et al., 2013) and for partial and fully reconstitution of the pathways for mycophenolic acid and asperfuranone production, respectively, in *A. nidulans* (Hansen et al., 2012; Chiang et al., 2013).

## **PERSPECTIVES**

The rapid development of molecular tools for cluster transfer and re-engineering in heterologous hosts is now at a stage where high-throughput experiments can be performed, and we therefore predict that novel SMs, genes, pathways and enzymes routinely will be discovered using this approach. For now most efforts have been proof of principle cases analyzing genes and gene clusters from genetically well-characterized organisms, but the next wave of breakthroughs will likely concern SMs originating from genetically exotic fungi. In addition, the natural reservoir of SMs will likely expand dramatically as synthetic biology based approaches using bio-bricks of promoters, terminators and SM genes are combined in intelligent or in random ways in model fungi to deliver compounds that nature never invented. Together, we envision that heterologous production will serve as a major driver for SM discovery and development delivering compounds that can be used in the food and pharma industries. Accordingly, physiologically well-characterized fungal cell factories should preferentially be employed as platforms for novel SMs discovery and development. These fungi display superior fermentation properties and extensive metabolic engineering toolboxes, hence, shortening the way toward large scale production.

## **ACKNOWLEDGMENTS**

We thank Rasmus Frandsen and Jakob Nielsen for helpful discussions; and the Danish Council for Technology and Production Sciences for financial support via grant 09-064967.

## **REFERENCES**

a hydrolase in mycophenolic acid biosynthesis. *Appl. Environ. Microbiol.* 78, 4908–4913. doi: 10.1128/AEM.07955-11

**Conflict of Interest Statement:** The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

*Received: 01 November 2014; accepted: 21 January 2015; published online: 10 February 2015.*

*Citation: Anyaogu DC and Mortensen UH (2015) Heterologous production of fungal secondary metabolites in Aspergilli. Front. Microbiol. 6:77. doi: 10.3389/fmicb.2015.00077*

*This article was submitted to Microbial Physiology and Metabolism, a section of the journal Frontiers in Microbiology.*

*Copyright © 2015 Anyaogu and Mortensen. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited andthatthe original publication inthis journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.*

## Next-generation sequencing approach for connecting secondary metabolites to biosynthetic gene clusters in fungi

## *Ralph A. Cacho1, Yi Tang1,2 and Yit-Heng Chooi <sup>3</sup> \**

<sup>1</sup> Chemical and Biomolecular Engineering Department, University of California, Los Angeles, Los Angeles, CA, USA

<sup>2</sup> Chemistry and Biochemistry Department, University of California, Los Angeles, Los Angeles, CA, USA

<sup>3</sup> Plant Sciences Division, Research School of Biology, The Australian National University, Canberra, ACT, Australia

#### *Edited by:*

Jonathan Palmer, United States Department of Agriculture – Forest Service, USA

#### *Reviewed by:*

Philipp Wiemann, University of Wisconsin–Madison, USA Liliana Losada, J. Craig Venter Institute, USA

#### *\*Correspondence:*

Yit-Heng Chooi, Plant Sciences Division, Research School of Biology, The Australian National University, Linnaeus Way, Canberra, Acton, ACT 2601, Australia e-mail<EMAIL_ADDRESS>
Genomics has revolutionized the research on fungal secondary metabolite (SM) biosynthesis.To elucidate the molecular and enzymatic mechanisms underlying the biosynthesis of a specific SM compound, the important first step is often to find the genes that responsible for its synthesis. The accessibility to fungal genome sequences allows the bypass of the cumbersome traditional library construction and screening approach. The advance in nextgeneration sequencing (NGS) technologies have further improved the speed and reduced the cost of microbial genome sequencing in the past few years, which has accelerated the research in this field. Here, we will present an example work flow for identifying the gene cluster encoding the biosynthesis of SMs of interest using an NGS approach. We will also review the different strategies that can be employed to pinpoint the targeted gene clusters rapidly by giving several examples stemming from our work.

**Keywords: filamentous fungi, secondary metabolites, gene clusters, next generation sequencing, genome mining**

## **INTRODUCTION**

Human health has been benefited from the secondary metabolites (SMs) produced by fungi. These small molecules, also known as natural products, include important clinical drugs like the antibiotic penicillins (Kardos and Demain, 2011), the cholesterol-lowering statins (Endo, 2010), the immunosuppressive cyclosporins (Britton and Palacios, 1982) and the antifungal echinocandins (Balkovec et al., 2014). Microbial SMs, including those from bacteria and fungi, continue to serve as important sources of molecules for drug discovery. For many decades, the fascinating and diverse structures of microbial SMs have inspired the organic chemists to embark on a quest to elucidate their biosynthetic pathways. Many basic insights into SM pathways were obtained by organic chemists using isotopic tracers during the 1950s (Bentley, 1999). The research shifted to the molecular biology of SM biosynthesis with the availability of tools for DNA cloning and sequencing. This is marked by several landmark papers, which described the molecular cloning of whole SM biosynthetic pathway on a contiguous stretch of DNA from actinomycete bacteria (Malpartida and Hopwood, 1984; Cortes et al., 1990; Donadio et al., 1991). Around the same period, the first fungal SM gene cluster, the penicillin biosynthetic gene cluster with the core non-ribosomal peptide synthetase (NRPS) gene encoding L-δ-(α-aminoadipoyl)-L-cysteinyl-D-valine (ACV) synthetase had been discovered in the fungus *Penicillium chrysogenum* (Díez et al., 1990). This is followed by the discovery of the terpenoid gene cluster encoding trichothecenes (Hohn et al., 1993), and polyketide gene clusters encoding aflatoxin/sterigmatocystin biosynthesis in *Aspergillus* sp. (Brown et al., 1996; Yu et al., 2004) and lovastatin biosynthesis in *A. terreus* (Kennedy et al., 1999).

This hallmark trait of gene clustering was then observed in almost all other classes of fungal SM pathways including indole alkaloids and terpenoids (Keller et al., 2005). The tendency for the biosynthetic genes in microbial SM pathways to cluster on a chromosomal locus greatly accelerated the elucidation of enzymatic steps involved in biosynthesis of individual SM compounds using molecular biology approaches. Consequently, identification of the gene cluster that encodes the production of a given SM is now becoming the common first step toward elucidating the molecular and enzymatic basis for the biosynthesis of a given SM. Subsequent verification of the predicted gene cluster is often achieved via targeted deletion and/or heterologous expression of key biosynthetic genes. Further characterization of the biosynthetic pathway can be done by deletion of the individual biosynthetic genes in the cluster or reconstruction of the whole pathway in heterologous systems.

Targeted SM gene cluster discovery in fungi in the pre-genomic era is a tedious and time-consuming process. Traditionally, this was done by either complementation of blocked mutants by cosmid libraries (e.g. Mayorga and Timberlake, 1990; Hendrickson et al., 1999), or insertional mutagenesis followed by plasmid rescue from the blocked mutant (e.g., Yang et al., 1996; Chung et al., 2003). Both of these aforementioned methods rely on screening of blocked/complementation mutants, which work well for pigment compounds but can be cumbersome if the phenotype, cannot be easily observed or assayed. For example, in the pioneering work to identify lovastatin gene cluster, 6000 mutants were screened for restored lovastatin production by HPLC/TLC after transformation of *A. terreus* with a cosmid library (Hendrickson et al., 1999). Other methods for identifying key biosynthetic gene include antibody screening of

cDNA expression library (e.g., Beck et al., 1990), differential display reverse transcriptase-PCR (e.g., Linnemannstons et al., 2002), suppression subtractive hybridization-PCR (O'Callaghan et al., 2003). However, these methods often lead to isolation of a single gene or partial gene cluster. Further cosmid library walking is required to obtain the whole gene cluster. Due to the relatively large genome size, genome scanning method, such as that demonstrated for discovery of enediyne antitumor antibiotic pathways in actinomycete bacteria (Zazopoulos et al., 2003), is less feasible for fungi.

Biosynthesis of polyketide SMs has been subjected to more intensive studies among other classes of SM pathways in fungi (Chooi and Tang, 2012). One of the earlier major advances in identification of fungal polyketide SM gene clusters is the development of degenerate primer PCR based on conserved ketosynthase (KS) domain of polyketide synthases (PKSs). The KS domain DNAfragments are then use as probes to identify the cosmid library clone carrying the whole or partial gene cluster. This method has been employed to localize the aflatoxin and fumonisin PKS genes (Feng and Leonard, 1995; Proctor et al., 1999). The subsequent primer sets developed to target KS domains of a non-reducing (NR-), partial-reducing (PR-), and highly-reducing polyketide synthases (HR-PKSs) are especially useful for localizing specific PKS gene clusters in cosmid libraries (Bingle et al., 1999; Nicholson et al., 2001). Pioneering work by Kroken et al. (2003) which performed a phylogenomic analysis of the PKS genes in the genomes of *Gibberella*, *Neurospora*,*Cochliobolus*, and *Botrytis* species revealed that fungal PKSs are likely to be derived from eight major lineages (Kroken et al., 2003). Nevertheless, despite the degeneracy of the primers and subdivision of fungal PKS genes in to different subclasses, some PKS genes in the genome can be still be missed by the degenerate primer PCR approach. Furthermore, it has to be bear in mind that, although most SM pathways are clustered on chromosome in fungi some of them can be split into two or three smaller subclusters, such as the pathways for dothistromin

in *Dothistroma septosporum* (Chettri et al., 2013), tryptoquivaline in *A. clavatus* (Gao et al., 2011), echinocandin in *Emericella rugulosa* (Cacho et al., 2012), and prenylated xanthones in *A. nidulans* (Sanchez et al., 2011). There are also instances where the gene clusters of multiple SM pathways are intertwined together, such as the fumitremorgin, fumagillin, and pseurotin supercluster (Wiemann et al., 2013a). In such cases, the absence of whole genome sequence information can complicate the identification of the complete gene set for the target SM pathway.

Whole genome sequencing (WGS) of the target SM-producing fungus bypasses the need for the cumbersome library construction, screening, and chromosome walking. More importantly, the genome sequence can reveal the inventory of all the SM gene clusters in the producing fungus. Even though each fungus can harbor 30–50 SM gene cluster, the number is still finite and one of them must encode the SM of interest. For example, WGS of *G. zeae* with the Sanger sequencing method has allowed the systematic deletion of all 15 PKS genes in the fungal genome, which lead to identification of the gene cluster for zearalenone, aurofusarin, fusarin C and an unidentified black perithecial pigment (Gaffoor et al., 2005). This opens up the opportunities for detailed characterization of these pathways for zearalenone (Kim et al., 2005; Zhou et al., 2010; Lee et al., 2011), aurofusarin (Frandsen et al., 2006; Frandsen et al., 2011), and fusarin C (Niehaus et al., 2013). The development of next-generation sequencing (NGS) technologies in the last decade has dramatically lowered the cost for DNA sequencing and put the power of microbial WGS in the hand of individual laboratories (van Dijk et al., 2014). This technology revolution has energized the natural product research field and sparked some exciting NGS-based targeted SM gene cluster discovery projects in fungi (**Table 1**). Our work that used such NGS approach includes the discovery of SM clusters encoding viridicatumtoxin and griseofulvin (Chooi et al., 2010), tryptoquialanine (Gao et al., 2011), echinocandin (Cacho et al., 2012),

**Table 1 | Examples of biosynthetic gene clusters assigned to their respective compounds using next-generation sequencing technology.**

asperlicin (Haynes et al.,2012), ardeemin (Haynes et al.,2013), and brefeldin (Zabala et al., 2014). Other studies that have taken the advantage of NGS have identified the SM clusters for fungal bicyclo[2.2.2]diazaoctane indole alkaloids (Li et al., 2012), equisetin (Kakule et al., 2013), and pneumocandin (Chen et al., 2013).

Contemporary natural product research programs are now increasingly based on the understanding of the relationship between the SM molecules and the biosynthetic genes (Walsh and Fischbach, 2010). Although such studies are primarily motivated by the desire to understand the molecular and enzymatic basis of SM biosynthesis, the potential benefits and implications derived from such work are manifold. Firstly, the new chemical insights obtained in elucidating the metabolic pathway can be used to design more efficient total synthesis routes for complex natural products. Secondly, knowledge about the gene cluster can facilitate the metabolic engineering effort to increase the yield of useful SMs for commercial production (Pickens et al., 2011). The knowledge also forms the basis for generation of new SM analogs by mutasynthesis and combinatorial biosynthesis. A recent example is the combinatorial biosynthesis of benzenediol lactones (Xu et al., 2014b), which built on previous studies (Reeves et al., 2008; Wang et al., 2008; Zhou et al., 2010; Xu et al., 2013b). Novel biocatalysts useful for green chemistry and chemoenzymatic process development may also be discovered from SM pathways. For example, the characterization of the acyltransferase LovD in lovastatin pathway led to the development of green chemistry processfor the semisynthetic cholesterol-lowering drug simvastatin (Xie et al., 2006, 2009; Gao et al., 2009; Xu et al., 2013a). Furthermore, the gene cluster information will be useful for knowledge-based genome mining for structurally-related compound in other fungi, e.g., the discovery of the immunosuppressive neosartoricin based on viridicatumtoxin biosynthesis genes (Chooi et al., 2012, 2013a). Importantly, these established links between genes and SMs are valuable knowledge that contributes to the overarching aims for (1) accurate prediction of SM structures based on DNA sequences and (2) rational design of biosynthetic pathways for synthesis of organic molecules. Finally, bridging the gaps between genes and molecules may facilitate our understanding of the natural functions of SMs using comparative genomics and transcriptomics tools (Chooi and Solomon, 2014).

It is important to note that a SM/natural product-motivated fungal genome sequencing project has different aims compared to the conventional WGS project coordinated by an international consortium of researchers associated with large sequencing centers. The major goal is to obtain the whole SM gene cluster that encode the targeted SM on a contiguous stretch of DNA sequence contig or scaffold. That means the completeness of the genome sequence coverage and whole-genome annotation is of lower priorities. The key question is how to rapidly narrow down and accurately pinpoint the correct SM cluster in the genome that encodes the production of a target SM. Getting an accurate initial prediction will significantly reduce the time spent on gene cluster verification. Below, we will provide the general work flow and guidelines for researchers who are considering adopting NGS technologies for targeted SM gene cluster discovery based on our own experience. We will also use several examples stemming from our

work, two PKS pathways and two NRPS pathways, to illustrate the concepts and strategies.

## **NEXT-GENERATION** *DE NOVO* **FUNGAL GENOME SEQUENCING AND ASSEMBLY**

The standard NGS-based targeted SM gene cluster discovery work flow used in our laboratory is presented in **Figure 1**. The fungal strain acquired from culture collections or her sources are first verified for production of the targeted compound before its genomic DNA was sent for sequencing. A variety of culture media and conditions can also be tested to optimize the production of the target compound. Gene deletion or disruption followed by the detection of loss of target compound production is still the most common method for initial gene cluster verification. Alternatively, if genetic transformation is proven to be difficult on the fungus, expression of the backbone biosynthetic enzymes [e.g., PKS, NRPS, terpene synthase, or dimethylallyltryptophan synthase (DMATS)] in the candidate SM gene cluster in a heterologous system may be another way to verify the gene cluster.

The next thing to consider will be the choice of sequencing method. The choice will be mainly based on the cost, sequence quality, sequence read length, speed and project throughput (the number of strains to be sequenced together). There are currently several NGS technologies on the market suitable for *de novo* fungal WGS, with Illumina now dominating the market

(Nowrousian, 2010; van Dijk et al., 2014). We have experience in both Roche/454 FLX Titanium and Illumina HiSeq2000, but other DNA sequencing platforms may work for this purpose as well. For an overview of the different latest NGS technologies, the readers are referred to van Dijk et al. (2014). The *de novo* sequencing of *P. aethiopicum* (synonym *P. lanosocoeruleum*) IBT5753 genome is one of the earliest examples of SM-motivated fungal WGS undertaken by individual laboratories, which used the Roche/454 FLX Titanium platform (Chooi et al., 2010).

The introduction of Illumina HiSeq2000 (now superseded by HiSeq2500) with ∼100 bp paired end (PE) reads dramatically reduced the cost of sequencing and increased the sequencing output. The shorter read length of HiSeq2000 is compensated by the deeper coverage and the paired-end nature of the Illumina reads. The Illumina PE reads allowed the assembly of longer scaffolds with gaps, which can be filled in later using routine PCR and Sanger sequencing if any of the scaffold harbor interesting SM gene cluster. Longer PE information can be obtained by generating mate pair libraries with larger insert size (e.g., 3 kbp or 5 kbp). Indeed, it has been recently demonstrated that good fungal genome assembly can be obtained on platform with shorter sequence reads (50 bp) like SOLiD using mate pair libraries (Umemura et al., 2013b).

We first used HiSeq2000 for sequencing of the brefeldinproducing *Eupenicillium brefeldianum* ATCC 58665 and the echinocandin-producing *E. rugulosa* (Cacho et al., 2012; Zabala et al., 2014). The amount of sequence data acquired for assembly of the ∼32 Mbp *E. rugulosa* genome is more than sufficient despite the shorter read length (N50 = 235 kbp). In fact, we can get equally good quality assembly using half the amount of data. Now, we routinely perform HiSeq2000 sequencing multiplexed for four fungal genomic samples per lane (∼200X depth of coverage each genome) and can routinely obtain good quality assembly for the purpose of SM gene cluster discovery. Using this arrangement, the cost of sequencing per fungal strain can be lower than the cost required for cosmid/fosmid library construction, screening, and chromosome walking, not to mention the significant time savings. With the use of mate pair libraries, more fungal genomic samples can likely be included into HiSeq2000 per lane yet still yield fine assembly. One recent study shows that the optimum sequencing depth for small bacteria to medium eukaryotic genomes with 2X 100 bp PE Illumina reads is 50-100X (Desai et al., 2013).

There is more than a dozen of software available for assembly of short reads generated by NGS, some are more memory intensive than the others, and there is differences in assembly speed as well. The popular ones including Velvet (Zerbino and Birney, 2008), SOAPdenovo (Li et al., 2010a), AllPATHS (Butler et al., 2008), and ABySS (Simpson et al., 2009). With optimization, some software may allow some small-medium size genomes to be assembled on a standalone workstation (Kleftogiannis et al., 2013). There are several studies that compare the efficiency and assembly quality of different assembly software (Lin et al.,2011; Zhang et al.,2011).We have experience mostly in using the SOAPdenovo assembler developed by BGI (Li et al., 2010a). Our SOAPdenovo assemblies were run on the UCLA Hoffman2 computer cluster. The assemblies can usually be completed with 32–128 GB memory requested from

the cluster, depending on the genome size and the amount of input data. For the standard 2X 100 bp PE reads, we often use a *k*-mer size of 63 or 79 for the SOAPdenovo assembly and were able to obtain good results. The latest version, SOAPdenovo2, promised to improve memory efficiency and assembly quality, and more optimized for the longer Illumina reads (rather than the 35–50 bp reads from older Illumina platforms; Luo et al., 2012). Many NGS providers also provide service for sequence assembly with a fee.

## **LOCATING THE TARGET SECONDARY METABOLITE GENE CLUSTER**

The first task after obtaining the scaffolds generated from the assembly is to narrow down the scaffolds containing the candidate SM gene clusters. Despite the enormous structural diversity, most fungal SMs can be divided into four major classes, polyketides, non-ribosomal peptides, terpenes, and indole alkaloids, based on the limited classes of carbon building blocks they derived from (Keller et al., 2005). Thus, an efficient way of narrowing down the scaffolds that may contain the target gene cluster is to search for genes encoding backbone biosynthetic enzymes that synthesized the specific class of compounds correspond to the target SM. This can be most easily achieved by performing a TBLASTN search against a database generated from the assembled fungal genome scaffolds using the "makeblastdb" command in the NCBI stand-alone BLAST application1. Depending on the class of SM, an arbitrary chosen conserved domain of the corresponding backbone enzymes can be used as a TBLASTN query. For example, a protein query sequence of a KS domain of PKS for polyketide SMs, an adenylation (A) domain of NRPS for non-ribosomal peptide SMs, terpene synthase for terpenoid SMs and DMATS for prenylated indole alkaloids. The TBLASTN will generate a list of scaffolds containing the SM gene clusters belongs the corresponding SM classes ranked based on homology to the query sequence. Alternatively, commercial bioinformatics software programs with intuitive graphic user interface (GUI) that support BLAST on local database are also available, e.g., CLC Genomics Workbench2 (CLC Bio) and Geneious3 (Biomatters). After locating the scaffolds containing gene clusters of the target SM classes, the number of candidate scaffolds can be further narrowed down with comparative genomics analysis (See Comparative Genomics Approach for Target SM Gene Cluster Prediction) followed by gene predictions and more in-depth knowledge-based bioinformatics analysis (see **Figure 2** and Section "Pinpointing Target SM Gene Cluster with Knowledge-Based Analysis – Retrobiosynthesis").

For fungal gene predictions (the locations and exon–intron structures of genes on individual scaffolds) we routinely use FGENESH (Softberry; Solovyev et al., 2006), which can yield relatively accurate predictions for fungi. The web server allows direct submission of FASTA nucleotide sequences with gene-finding parameters trained using datasets from several fungal species4.

<sup>1</sup>http://www.ncbi.nlm.nih.gov/guide/howto/run-blast-local/

<sup>2</sup>http://www.clcbio.com/

<sup>3</sup>http://www.geneious.com/

<sup>4</sup>http://www.softberry.com/berry.phtml?topic=index&group=programs&subgrou p=gfind

Alternatively, AUGUSTUS also provides relatively accurate fungal gene prediction<sup>5</sup> based on training sets from various fungal species (Stanke et al., 2004). Individual protein sequences predicted in a candidate scaffold are then submitted to NCBI BLASTP server for detailed conserved domain analysis (using the integrated NCBI Conserved Domain Search feature) and homologous sequence comparison. The EBI Interproscan also offers similar conserved domain prediction and protein functional analysis. As each gene cluster usually contain 3–15 genes (>20 genes in some cases), it is often not too time consuming when the number of candidate scaffolds has been narrowed down significantly. Several SM gene cluster prediction software programs have also been developed, which can aid this process considerably (see Pinpointing Target SM Gene Cluster with Knowledge-Based Analysis – Retrobiosynthesis).

## **COMPARATIVE GENOMICS APPROACH FOR TARGET SM GENE CLUSTER PREDICTION**

Comparative genomics can be a useful approach for filtering of candidate gene clusters (**Figure 2**). The increasing number of sequenced fungal genomes in public databases, due in part to the lower sequencing cost enabled by NGS technologies, allows one to find a suitable genome of related sequenced organism for comparison with the organism of interest. Since the genomes of different organisms, even those belonging to the same genus, would encode

different array of SMs, one can compare the SM backbone biosynthesis gene inventory of one organism with a closely related organism to rapidly narrow down the unique SM gene cluster. This approach is especially useful when there is pre-existing knowledge about the SM repertoire of the reference organism used for comparison. For example, in the search of SM gene clusters responsible for the biosynthesis of viridicatumtoxin and griseofulvin in *P. aethiopicum* (Chooi et al., 2010), we compared the PKS inventory of *P. aethiopicum* with that of *P. chrysogenum* based on prior knowledge from previous chemotaxonomy studies (Frisvad and Samson, 2004). Since it is known that *P. chrysogenum* produces neither viridicatumtoxin nor griseofulvin, we can first filter out the orthologous PKS genes shared between the two fungi (**Figure 3A**; Section Case Study A: Griseofulvin and Case Study B: Viridicatumtoxin). Similar the genome-wide comparison of NRPS genes in *A. nidulans* and *E. rugulosa* was used to narrow down the candidate echinocandin gene cluster (Cacho et al., 2012). It has to be bear in mind that the absence of report about the presence of a target SM compound in a specific species does not always correlate with the absence of the gene cluster in the genome as there can be strain-strain variation and many SM gene clusters could be transcriptionally silent. For example, TAN-1612, reported in another *A. niger* strain as BMS-192548 (Kodukula et al., 1995; Shu et al., 1995), is not detected in the sequenced *A. niger* ATCC 1015. However, the corresponding gene cluster can be identified and activated by transcriptional regulator overexpression (Li et al., 2011). The abilities to produce fumitremorgin by *A. fumigatus* (Kato et al., 2013), and gibberrellin and beauvericin by *G. fujikuroi* (Wiemann et al., 2013b), also vary from strain to strain. Nonetheless, such a

<sup>5</sup>http://bioinf.uni-greifswald.de/webaugustus/predictiontutorial.gsp#example data

comparative genomics approach had served as a useful first-pass filter in our hands, especially for fungal species that have been characterized chemotaxonomically, such as those species in the *Aspergillus* and *Penicillium* genera (Frisvad and Samson, 2004; Frisvad et al., 2007).

Conversely, comparative genomics can also be utilized for identifying the biosynthetic gene clusters of a target group of SMs bearing structural similarities but made by less-related fungal species (**Figure 2**). In this case, orthologous gene clusters in two organisms that are capable of synthesizing the same family of compounds are targeted. An example of the latter strategy is demonstrated in our work on tryptoquialanine/tryptoquivaline gene cluster identification in *P. aethiopicum*/*A. clavatus* (Gao et al., 2011; **Figure 3B**). The strategy is also well-demonstrated in the work by the Sherman group in investigating the biosynthesis of fungal bicyclo[2.2.2]diazaoctane indole alkaloids (−)- and (+)-notoamide A, paraherquamide A, and malbrancheamide A by *Aspergillus* sp*. MF297-2, A. versicolor* NRRL35600*, P. fellutanum* ATCC20841, and *Malbranchea aurantiaca* RRC1813, respectively (Li et al., 2012). More recently, NGS-driven comparative genomics of four *Stachybotrys*strains from two chemotypes producing either atranones or stratoxins have revealed two unique gene clusters, which possibly encode the biosynthesis of the two respective terpenoid-derived SMs (Semeiks et al., 2014). However, the identities of the two gene clusters are yet to be verified experimentally. Such comparative genomics approach is highly compatible with the high-throughput nature of Illumina sequencing as genomic samples from multiple fungal strains can be multiplexed on a single lane of an Illumina sequencer flow cell. In the case where the target SM gene cluster is split into more than one scaffold in one of the fungal genome assemblies, either due to disruption of assembly by repetitive sequence or the pathway is encoded by multiple loci, comparative genomics of the different strains can help localize the complete biosynthetic gene sets. This approach has facilitated the identification of genes for biosynthesis of tryptoquivaline in *A. clavatus*, which was separated into three genomic loci, by comparing with the tryptoquialanine-producing *P. aethiopicum* genome (Gao et al., 2011).

Lastly, one can use comparative genomics to make an educated guess on where the boundaries of the SM gene cluster are located. Oftentimes, SM gene clusters are flanked by syntenic blocks containing highly-conserved core genes (Machida et al., 2005; Tamano et al., 2008). Similarly, we have observed this trend in our studies toward the discovery of gene clusters encoding griseofulvin, viridicatumtoxin, cytochalasin, and tryptoquialanine. All four putative SM gene clusters are flanked by syntenic block of genes with high shared identity (>85%) in closely related ascomycetes species (Chooi et al., 2010; Gao et al., 2011; Qiao et al., 2011). In fact, a study reported a motif-independent bioinformatics approach for detection of SM gene cluster based on non-syntenic blocks in fungal genomes (Umemura et al., 2013a). One of the software that is useful for identifying and visualizing syntenic regions across multiple genomes is Mauve (Darling et al., 2004). While it does not guarantee that genes that are not highly conserved to a related organism are part of the cluster, this strategy is helpful toward minimizing the number of genes subjected to further functional analysis.

#### **PINPOINTING TARGET SM GENE CLUSTER WITH KNOWLEDGE-BASED ANALYSIS – RETROBIOSYNTHESIS**

As mentioned above, gene predictions of individual scaffolds can be performed using software like FGENESH or AUGUSTUS after narrowing down the number of candidate SM gene clusters to a handful of scaffolds. Further detailed bioinformatics analysis of the individual SM gene clusters is then needed to identify the target gene cluster. Some software programs have been developed to aid SM gene cluster predictions. Two of the popular software programs available for prediction of SM gene clusters are antiSMASH (Medema et al., 2011; Blin et al., 2013) and SMURF (Khaldi et al., 2010). SMURF is specific for predicting SM gene clusters in fungal genomes, while antiSMASH can be used for both bacteria and fungi. Guidelines and detailed protocols for using these two and other related SM biosynthetic gene prediction programs can be found in Fedorova et al. (2012). SMURF requires a protein FASTA file and a gene coordinate file as input data. On the other hand, antiSMASH can accepts