MINIREVIEW

Transcription factors in fungi Ekaterina Shelest ¨ Institute (HKI), Department of Molecular and Applied Microbiology, Leibniz Institute for Natural Product Research and Infection Biology, Hans Knoll Jena, Germany

Correspondence: Ekaterina Shelest, Department of Molecular and Applied Microbiology, Leibniz Institute for Natural Product Research and Infection Biology, Hans ¨ Institute (HKI), Beutenbergstrasse 11a, Knoll 07745, Jena, Germany. Tel.: 149 3641 5321114; fax: 149 3641 5320808; e-mail: [email protected] Received 3 June 2008; accepted 30 June 2008. First published online August 2008. DOI:10.1111/j.1574-6968.2008.01293.x Editor: Derek Sullivan Keywords transcription factor; DNA-binding domain; fungal-specific; horizontal gene transfer.

Abstract Transcription factors (TFs) orchestrate gene expression control of a cell and, in many respects, their repertoire determines the life and functionality of the cell. For a better understanding of their regulatory mechanisms, it is essential to know the entire repertoire of TFs of a species. The increasing number of sequenced genomes together with the development of computational methods allow us not only to predict whole sets of TFs but also to analyse and compare them. Such an analysis is required in particular for fungal species, as our knowledge of the potential set of TFs in fungi is very limited. In fact, at present we do not know which TFs can in general be found in fungi, and which of them are strictly fungal specific. Other interesting questions regard the evolutionary relationships of fungal TFs with other kingdoms and the functions of fungal-specific TFs. This minireview addresses these issues. The analysis of predicted occurrences of DNA-binding domains in 62 fungal genomes reveals a set of 37 potential ‘fungal’ TF families. Six families are fungal-specific, i.e. they do not appear in other kingdoms. Interestingly, the fungal-specific TFs are not restricted to strictly fungal-specific functions. Consideration of fungal TF distributions in different kingdoms provides a platform to discuss the evolution of domains and TFs.

Introduction Transcription factors (TFs) are essential players in the signal transduction pathways, being the last link between signal flow and target genes expression. The functionality of TFs depends on many parameters, and their involvement in a particular signalling pathway is sometimes difficult to predict. Nonetheless, the mere occurrence of a specific TF type can already provide some information about the possible existence of particular signalling pathways, or, in the opposite case, the absence of a certain TF can be taken to indicate that the corresponding pathway is absent. Therefore, it would be beneficial to know the whole repertoire of TFs in different species and in higher taxa. There are some taxonspecific TFs, for instance those that are found only in bacteria or in plants, or in animals, but little is known about fungal TFs and their relatedness to TFs in other eukaryotes. The number of experimentally verified TFs in fungi is significantly lower than in higher eukaryotes, as reflected in databases such as TRANSFAC (Wingender et al., 2000) and MycoPath (both: http://www.biobase-international.com/ pages/). This can have two possible explanations: either they FEMS Microbiol Lett 286 (2008) 145–151

are really less abundant (which would conform to the view that organisms require additional TFs as their complexity increases; Amoutzias et al., 2007) or they have not yet been identified. However, we can estimate the number of potential TFs computationally, by pairwise comparisons (alignments, BLAST searches) or by hidden Markov models (HMMs) and other models based on multiple alignments of domains (Wilson et al., 2008). Large evolutionary distances, which characterize the fungal kingdom (Dujon et al., 2004), make the application of usual (pairwise) comparative approaches unreliable; thus, HMMs are the better choice. By considering the HMM-based predictions from corresponding databases we can estimate the possible number of fungal TFs and list those TF families (TFfs) that can potentially occur in fungi. Thus far, we do not have functional verification of each and every TF of a particular species (including those that are very well annotated, such as human, mouse or Saccharomyces cerevisiae). Thus, the analysis of an entire set of TFs cannot be based totally on experimental data. Here, I analyse only the predictions, intentionally considering from the start all known DNA-binding domains, independently of
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their initial taxonomic assignment. The underlying idea is that as we do not know which TFs occur in fungi, it is reasonable simply to check them all. This gives information not only about potential fungal TFs, but also about the sharing of TFs between kingdoms. At present, we lack an overview of TFs in fungi, and in fact we do not have answers to several simple questions: which TFs can be found in fungi, and which cannot? How many TFs (or TFfs) are strictly fungal-specific? With which other species do fungi share their TFs? Here I address these questions and also discuss some evolutionary insights that arise from the consideration of TF taxon distributions.

Data sources and methodological background Besides literature sources, here I analyse data from the DBD database (Wilson et al., 2008), a database of predicted sequence-specific DNA-binding TFs for all publicly available proteomes. The method behind DBD uses profile HMMs of DNA-binding domains [taken from the PFAM (protein family) and Superfamily databases] to predict transcription factors by homology. The advantage of this method is that it can accurately identify both known and previously uncharacterized TFs that bind specifically to DNA; even TFs without obvious sequence homology to known factors can be identified. Therefore, DBD provides far more information than manually curated literature-based databases such as TRANSFAC, although with the drawback of possible false predictions. The Superfamily database (Madera et al., 2004) is based on the structural classification of proteins (SCOP) (Murzin et al., 1995). SCOP is a structural domain-based hierarchical classification with several levels, including the ‘superfamily’. Proteins grouped together at the superfamily level are defined as displaying structural, functional and sequence evidence of common evolutionary ancestry. The ‘family’ level lies below this and groups more closely related domains. This level is described by PFAM, a well-known collection of protein families and domains (Bateman et al., 2004). To collect fungal TFfs, I screened all DNA-binding domains from DBD (‘Browse Families’) for the entry ‘Fungi’ in the ‘Taxonomic distribution’. Ultimately, the ‘Taxonomic distribution’ links to the corresponding PFAM and Superfamily taxonomic tables, which can be downloaded and are easy to examine. A family was considered as ‘fungal’ if it occurred in more than three species, as single occurrences are more likely to be false predictions. The latter statement has been checked: every protein of a TFf, represented in fewer than three fungal species, was examined for the level of similarity with its counterparts from other kingdoms (by BLAST). There were seven TFfs with low occurrence, each represented in fungi by one to three proteins. In all cases the
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percentage of identity was low (c. 30%), so they were considered as false predictions. Analysis of the cross-kingdom distributions was made only on the family level. For each fungal TFf the corresponding ‘Species distribution’ table of PFAM was examined, noting only the presence (‘yes’ or ‘no’) in animals, plants, bacteria and viruses. Here, again, the single occurrences (in fewer than three species) were considered as nonreliable. There are 62 fungal genomes in the DBD database, the majority of which belong to the Ascomycetes. Nonetheless, there are about 10 species of Basidiomycetes and several genomes of other fungi. Thus, the representativeness of the set is satisfactory for the current purposes.

Which transcription factors can be expected in fungi? The ‘fungal’ TFfs were collected as described in the previous section and are detailed in Table 1. There is some redundancy between the Superfamily and PFAM lists, when the names of a family and a superfamily are the same (SRF, HLH, etc.). Families are normally subdivisions of the superfamilies, so the appearance of the same term on either level is justified. If a family and a superfamily completely coincide, I consider only one of them further. For fungal TFfs, superfamilies are essentially equal to families (coincide in 4 90% of instances) for helix–loop–helix (HLH), SRF-like and Zn2/Cys6 (zinc cluster).

Superfamilies of DNA-binding domains present in fungi The total number of superfamilies of DNA-binding domains is 37 (http://supfam.org/SUPERFAMILY), of which only 12 are predicted in fungi (Table 1). From these 12 superfamilies, three are not found in other kingdoms: ‘Zn-cluster’, ‘Zinc domain conserved in yeast copper-regulated transcription factors’ and ‘DNA-binding domain of Mlu1-box-binding protein MBP1’.

PFAM families PFAM contains 296 entries for the term ‘DNA-binding’. After text-mining-based filtering for sequence-specific binding, i.e. excluding general TFs, nonspecific binding and domains involved in other processes (reparation, recombination, etc.), 145 domains remain. Of these, 37 (about onequarter) domains are found in fungal species. Thus, the proportion of ‘fungal’ TFfs in PFAM families and ‘Superfamilies’ is roughly the same.

Which TF families are fungal-specific? Three superfamilies and three families of TFs are fungalspecific, i.e. they are present only in fungi and are not found FEMS Microbiol Lett 286 (2008) 145–151

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Table 1. Twelve superfamilies and 37 PFAM families of TF DNA-binding domains, predicted to occur in fungal species Family name

Database ID

PFAM family APSES domain bZIP TF 1 Basic region leucine zipper 2 TFIIH C1-like domain CCAAT-binding TF (CBF-B/NF-YA) subunit B CP2 TF DDT domain Putative FMN-binding domain Fork head domain Fungal-specific TF domain Fungal Zn(2)-Cys(6) binuclear cluster domain GATA zinc finger GRF zinc finger Helix–loop–helix DNA-binding domain Homeobox domain HSF-type DNA-binding Helix–turn–helix Bacterial regulatory HTH proteins, AraC family Helix–turn–helix, Psq domain Mating-type protein MAT a1 MIZ zinc finger Myb-like DNA-binding domain NDT80/PhoG-like DNA-binding family NF-X1-type zinc finger CCR4-Not complex component, Not1 PAS fold RFX DNA-binding domain SART-1 family SGT1 protein SRF-type TF (DNA-binding and dimerization domain) STE-like TF TEA/ATTS domain family YL1 nuclear protein BED zinc finger Zinc finger, C2H2 type Zinc finger, C5HC2 type Zinc knuckle

PFAM ID PF02292 PF00170 PF07716 PF07975 PF02045 PF04516 PF02791 PF04299 PF00250 PF04082 PF00172 PF00320 PF06839 PF00010 PF00046 PF00447 PF01381 PF00165 PF05225 PF04769 PF02891 PF00249 PF05224 PF01422 PF04054 PF00989 PF02257 PF03343 PF07093 PF00319 PF02200 PF01285 PF05764 PF02892 PF00096 PF02928 PF00098

Superfamily

Superfamily ID 57667 54616

C2H2 and C2HC zinc fingers DNA-binding domain of Mlu1-box-binding protein MBP1 Glucocorticoid receptor-like (DNA-binding domain) Helix–loop–helix DNA-binding domain Homeodomain-like Lambda repressor-like NA-binding domains Nucleic acid-binding proteins p53-like transcription factors SRF-like Winged helix DNA-binding domain Zinc domain conserved in yeast copper-regulated TFs Zn2/Cys6 DNA-binding domain

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57716 47459 46689 47413 50249 49417 55455 46785 57879 57701

in other kingdoms (Table 2). Here I consider them and their functions in more detail. The largest class of fungal-specific domains is the zinccluster superfamily [this can also be found in PFAM as a family (PF00172)]. The DNA-binding domain consists of six cysteine residues that, unlike the other zinc-finger proteins, bind two zinc atoms; thus, this domain can also be found under the names Zn(II)2Cys6, or zinc binuclear cluster. The zinc clusters can interact with DNA as monomers or as homo- or heterodimers. It is a multifunctional class of factors that regulate a plethora of cellular processes, including the most crucial for survival and prospering of the fungus: sugar and amino acid metabolism, gluconeogenesis and respiration, vitamin synthesis, cell cycle, chromatin remodelling, nitrogen utilization, peroxisome proliferation, pleiotropic drug response and stress response (reviewed in MacPherson et al., 2006). Many zinc cluster TFs have more than one distinct role, and can also have overlapping functions. Several dozens of zinc cluster proteins have been experimentally proven in S. cerevisiae, Candida albicans, Schizosaccharomyces pombe, as well as in several Aspergillus species and other filamentous fungi. Unlike the multifunctional zinc cluster, the representatives of the two other fungal-specific superfamilies (‘DNAbinding domain of MBP1’ and ‘copper-regulated Zinc domain’) are more restricted in their functions. Factors with the ‘DNA-binding domain of MBP1’ are involved in cellcycle regulation (Ayt´e et al., 1997, Machado et al., 1997). MBP1, together with Swi6, comprises a complex MCBbinding factor (MBF), a TF from budding yeast that binds to the so-called MCB (MluI cell-cycle box) elements found in the promoters of many DNA synthesis genes and activates their transcription at the G1 ! S phase transition (Xu et al., 1997). The MBP1 DNA-binding domain has some topological similarity to the ‘winged helix’ DNA-binding domain (SCOP, http://scop.mrc-lmb.cam.ac.uk/scop/index.html). The ‘Zinc domain of yeast copper-regulated factors’ regulate transcription of a set of yeast genes, many of which encode membrane proteins (Keller et al., 2001) and mediate copper utilization and stress response (Jungmann et al., 1993). The functions of different zinc copper-regulated TFs can be independent and complementary: for instance, Ace1 and Mac1 undergo reciprocal copper metalloregulation in yeast cells (Keller et al., 2005). As indicated by its name, this family is often referred to as yeast-specific; nonetheless, it is possible to predict its representatives in all fungal species considered. The second largest TF class after the zinc cluster is the ‘fungal-specific transcription factor domain’ (Fungal_trans, PF04082). Interestingly, in all experimentally proven factors listed in the TRANSFAC database, the Fungal_trans domain is always located downstream of the zinc cluster domain (the zinc cluster tends to locate near the N-terminus). The
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Table 2. Fungal-specific TFfs and their functions Name

Database and accession no.

Zn2/Cys6 (Zn cluster)

Superfamily, 57701

DNA-binding domain of Mlu1-box-binding protein MBP1 Zinc domain conserved in yeast copperregulated TFs Fungal-specific transcription factor domain APSES

Superfamily, 54616

MAT a 1

Function

Reference(s)

Mean occurrence

Sugar and amino acid metabolism, gluconeogenesis, respiration, vitamin synthesis, cell cycle, chromatin remodelling, nitrogen utilization, peroxisome proliferation, drug resistance, stress response Cell cycle

MacPherson et al. (2006)

11

Ayte´ et al. (1997), Machado et al. (1997)

0.6

Superfamily, 57879

Copper utilization and stress response

Jungmann et al. (1993), Keller et al. (2001, 2005)

0.2

PFAM, PF04082

Sugar metabolism, amino acid metabolism, TRANSFAC, PFAM gluconeogenesis, respiration, fatty acid catabolism, nitrate assimilation, etc. Morphogenesis and metabolism, developmental Dutton et al. (1997), Whitehall et al. complexity, yeast–hyphal transitions, cell cycle (1999), Doedt et al. (2004), Wang & Szaniszlo (2007) Activation of mating-type a-specific genes Tatchell et al. (1981), Sengupta & Cochran (1991)

4.2

PFAM, PF02292

PFAM, PF04769

0.5

0.06

Thirty-five species were considered for the calculation of mean occurrences. MAT a 1 was found in 21 species, DNA-binding domain of MBP1 in 32 species, and the remainder were present in all 35 species. Mean occurrences are given per species per 103 proteins.

domain is also predicted in proteins without a zinc cluster domain (InterPro), but these predictions have not been confirmed experimentally. Thus, it remains questionable whether the Fungal_trans domain can act independently. There is also no single literature reference concerning the functional characterization of this domain so, although the domain is clearly present in many functionally characterized TFs, its own role remains obscure. Factors having this domain are involved in sugar metabolism, amino acid metabolism, gluconeogenesis and respiration, fatty acid catabolism, etc (TRANSFAC, PFAM). The APSES domain is a sequence-specific DNA-binding domain that can be modelled as a basic HLH (bHLH)-like structure (Dutton et al., 1997). APSES proteins (ASM-1, Phd1, StuA, EFGTF-1 and Sok2) represent a conserved class of fungal TFs regulating cellular differentiation in ascomycetes. They are involved in regulation of morphogenesis and metabolism in yeast (Doedt et al., 2004), developmental complexity in filamentous fungi (Dutton et al., 1997), regulation of the cell cycle (Whitehall et al., 1999) and reversible yeast–hyphal transitions (Wang & Szaniszlo, 2007). Moreover, some APSES proteins may be involved in determining virulence [shown for Efg1p of C. albicans (Lo et al., 1997)]. APSES proteins might act both as activators and repressors of gene expression, because they stimulate reversible transitions between spherical and filamentous cells (Doedt et al., 2004). The MAT a 1 family includes S. cerevisiae mating type protein a 1. It activates mating-type a-specific genes with
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the help of the MADS-box-containing MCM1 transcription factor. They bind cooperatively to PQ elements, common sequence motifs in the upstream regions of a-specific genes (Sengupta & Cochran, 1991). a 1 interacts in vivo with STE12, linking expression of a-specific genes to the a-pheromone response pathway; STE12 interaction is speciesspecific (no interaction with Kluyveromyces lactis STE12) (Mukai et al., 1993; Yuan et al., 1993). As it can be seen from Table 2, the number of associated functions correlates with the mean occurrence of corresponding genes (last column). This suggests that these TFs are quite function-specific. It would be logical to expect that fungal-specific TFs exert fungal-specific functions. This holds true for APSES and MAT a1 [APSES proteins apparently have general functions, which are not specific for fungi (e.g. regulation of cell cycle), but these functions are achieved through regulation of fungal-specific morphogenetic processes]. The functions of other fungal-specific TFfs remain quite ubiquitous. The question of why these functions have been delivered to highly taxon-specific genes requires further investigation.

Taxonomic distributions of fungal TFfs and some insights into domain evolution I now focus on those TFfs that occur in fungal species but are not restricted to them. For simplicity, I will refer to them as ‘fungal TFfs’. I analysed the distribution of such TFfs across the four kingdoms: animals, plants, bacteria and FEMS Microbiol Lett 286 (2008) 145–151

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Table 3. Fungal DNA-binding domains in different taxa Kingdoms

Shared domains

Fungi1animals1plants1viruses

bZIP_1 (bZIP transcription factor 1, PF00170) bZIP_2 (Basic region leucine zipper 2, PF07716) zf-GRF (GRF zinc finger, PF07716) bHLH (Helix–loop–helix DNAbinding domain, PF00010) ZF-C2H2 (Zinc finger, C2H2 type, PF00096) HTH_psq (Helix–turn–helix, Psq domain, PF05225) FMN _bind_2 (Putative FMNbinding domain, PF04299) HTH_AraC (Bacterial regulatory HTH proteins, AraC family, PF00165)

Fungi1animals1bacteria Fungi1bacteria

Four kingdoms (animals, plants, bacteria and viruses) were screened for fungal domains. Besides the purely eukaryotic TFs (not shown), three groups of fungal TFs were shared by eukaryotes either with viruses or with bacteria.

viruses. Most of the fungal TFfs are eukaryotic, and some are ubiquitous (spread over all kingdoms). The most-interesting cases from an evolutionary point of view are those where a fungal TFf is shared either with bacteria or with viruses (Table 3). I will consider these in more detail. There are five domain families that are found in eukaryotes and in viruses, but not in bacteria. The first two classes, bZIP domains, belong to one of the second largest families of dimerizing TFs, and are normally referred to as eukaryotic. The high degree of functional conservation of the bZIP proteins highlights the ancient origin of this class of TFs. These domains are also predicted in viruses, although in very few species. Remarkably, they occur only in herpesvirus and retroviruses, which might indicate that they have been recruited by the viruses from the hosts. A similar situation can be observed for HLH domain family and zinc fingers (zf), only HLH domains are predicted in more divergent virus species. The occurrence and functionality of these TFs in viruses has to be confirmed experimentally, after which it would be interesting to speculate on their origin. The evolution of bZIP, bHLH and ZF domains in eukaryotes has been investigated (e.g. Deppmann et al., 2006; Landais et al., 2006; Amoutzias et al., 2007), but the question of the viral domains has not been raised. There is only one eukaryotic TFf, HTH_psq, representatives of which are found in animals, fungi and bacteria. The distribution of the family is rather broad in animals. In fungi, it occurs in the evolutionarily divergent Ascomycota and Basidiomycota. The domain is also predicted in several distantly related bacterial species. Thus, it is difficult to FEMS Microbiol Lett 286 (2008) 145–151

define the origin of the domain without detailed phylogenetic sequence analysis. A more interesting situation is seen when the domains are shared only between fungi and bacteria (FMN_bind_2 and HTH_AraC). Both domains are referred to as ‘bacterial’ in PFAM and the number of occurrences confirms this statement: HTH_AraC is found in 13 fungal (all ascomycetes) and 598 bacterial species, and FMN_bind_2 is found in 19 fungal and 130 bacterial species. Both types of domaincontaining proteins are quite conserved in fungal species (80–90% similarity), although the level of overall protein similarity to the bacterial proteins is modest (around 40–50%). The functionality of the fungal genes has not yet been proven experimentally (as is also the case for the vast majority of the bacterial FMN_bind_2 and HTH_AraCcontaining proteins). Nonetheless, the occurrence of such highly conserved genes, possessing a binding domain and exhibiting reasonable similarity to their bacterial counterparts, cannot be coincidental. It is logical to suppose that these domains have been acquired from bacteria by means of horizontal gene transfer. Whether or not they retain the regulatory function requires further investigation. The other way that fungal TFs may evolve is via capture of viral domains. An example of such a process is provided by the APSES domain, which appears to have evolved through the capture of a viral KilA-N-like precursor early in fungal evolution (Iyer et al., 2002).

Discussion and conclusions A specific repertoire of TFs is partly the result of adaptive evolution. The more signalling pathways and regulatory networks a species can exploit, the more flexible can be its reaction to disturbance. By contrast, there should be a balance between the number of pathways and the robustness of the response, which are, obviously, not in linear dependence. Finally, successful adaptation can be achieved through various evolutionary scenarios, which are now reflected by the specific sets of TFs. New TFs can be gained in different ways, including duplication with following mutations, or horizontal gene transfer. With regard to the future of the signalling pathways, gain of TFs may have two important evolutionary consequences: (1) delegation of the functions of ‘old’ TFs to new TFs, and (2) gaining new functionality together with the new TFs (probably leading to the appearance of new regulatory networks). Investigation and comparison of the TF sets can help us to reconstruct the evolutionary history of the signalling pathways. Knowing the specific repertoire of TFs has more practical consequences: for instance, it allows us to make a preselection of corresponding positional weight matrices (PWMs) for promoter analysis. Sometimes it may be even more useful to know not which TFs are present in a species but which are
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lacking. This enables a researcher to exclude some potential pathways from consideration, thus saving time. By contrast, if it is known that a particular pathway takes place and the corresponding TF does not occur in the genome, it is challenging to identify an alternative TF. The first step in identification of specific TF sets for fungal species is to confine the set of those TFs that can in general be found in fungi. This minireview lists for the first time all TFfs that are predicted to occur in fungi. There is no specific database for fungal TFs so far. Only about one-quarter of known DNA-binding domains of TFs can be predicted to occur in fungi. This observation is in agreement with the suggestion that the complexity of an organism correlates with an increase in both the absolute number of TF genes and the proportion of TFs in a genome (Levine & Tjian, 2003; Amoutzias et al., 2007). In total, fungi have 37 domains and domain families, assigned to 12 superfamilies. Three superfamilies and three families are fungal-specific. Most of the fungal-specific TFfs are not restricted to strictly fungal-specific functions, at least not on the level of domain families. This means that some of the general functions that are fulfilled in other kingdoms by other TFs have been transferred at some moment of evolution to fungal-specific TFs. The reasons, mechanisms and consequences of this transfer (which could be the result of convergent evolution of TFs in different kingdoms) are of great interest and require further investigation. Analysis of taxonomic distributions gives us some insight into the evolution of TFs in general and their evolution in fungal species in particular. There are indications that several eukaryotic domains could have been acquired by viruses (in particular retroviruses). The two bacterial domains (FMN_bind_2 and HTH_AraC) are highly conserved in fungi and could have been horizontally transferred to fungal genomes.

Acknowledgements I would like to thank Edgar Wingender, Reinhard Guthke, Daniela Albrecht and especially Anthony Pugsley for critical reading and useful comments on the manuscript.

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