What makes a mycoparasite? Similarities between fungi that attack other fungi and fungal and oomycete plant pathogens based on structural homology of their candidate effectors

What makes a mycoparasite? Similarities between fungi that attack other fungi and fungal and oomycete plant pathogens based on structural homology of their candidate effectors | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article What makes a mycoparasite? Similarities between fungi that attack other fungi and fungal and oomycete plant pathogens based on structural homology of their candidate effectors Alexandros Sotiropoulos, Matthias Heuberger, Thomas Wicker, Levente Kiss This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7759314/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Fungi that feed and thrive on other living fungi and damage those through specific adaptations to this lifestyle are known as mycoparasites. Despite its ecological significance and practical applications in crop protection, this type of parasitism is still poorly understood. Here, we hypothesize that aggressive fungal-fungal parasitic interactions are similar to those between plants and their fungal pathogens. We tested this hypothesis in two ways. First, we analyzed the genetic signatures of the mycoparasitic nutrition mode through the Carbohydrate-Active enZYme (CAZyme) profiles of more than 50 fungi with high-quality reference genomes across the Fungal Kingdom, including mycoparasites and their close relatives. Two CAZyme families, AA3-2 and AA9, appeared to be associated with mycoparasitism. Second, we searched for candidate effectors in protein datasets of three specialist mycoparasites and closely related fungi. Based on the tertiary structures of selected proteins predicted by AlphaFold, we identified protein clusters. Surprisingly, several tertiary structures predicted in all three, phylogenetically diverse mycoparasites were homologous to well-studied candidate effectors in a model plant pathogen, Blumeria graminis . One of these protein clusters belonged to the AA9 CAZyme family. These results supported our hypothesis and revealed a new approach to understand mycoparasitism at molecular level. Biological sciences/Microbiology/Fungi/Fungal genomics Biological sciences/Microbiology/Fungi/Fungal pathogenesis Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Some fungi, from yeasts to mushrooms, are often attacked and damaged by other fungi. Aggressive antagonistic interactions between fungal species may take diverse forms that are sometimes loosely defined in the literature 1 – 3 . The terms ‘parasitism’, usually with the ‘myco-‘ prefix, and also ‘predation’, and ‘pathogenicity’, have been used to describe such interactions when one fungus feeds and thrives on or inside another living fungus, the mycohost, and damages it through specific adaptations to this lifestyle 1 – 4 . Here we apply the term ‘mycoparasitism’ to this type of relationship between fungal species that has evolved in diverse groups of fungi through specific genetic, physiological and/or structural adaptations 1 – 7 . Mycoparasites can also be considered as pathogens, i.e., disease-causing agents of their mycohosts, and the visual symptoms they may cause can be called as ‘disease’. The latter terminology is mostly used in relation to the aggressive antagonistic interactions between some microscopic fungi, such as Trichoderma spp., and mushrooms as their mycohosts 8 , 9 . Those mycoparasites cause economic damage in mushroom production 8 , 9 ; others were commercialised as biocontrol agents in crop protection 10 – 13 . Ecological studies have revealed the significance of mycoparasitism in natural ecosystems 14 , 15 . Current knowledge on mycoparasitic nutrition mode is largely based on empirical evidence 1 – 5 , 16 . Similar to the interactions between plant pathogenic microbes and their photosynthesizing hosts, there is a wide range of mycoparasitic relationships that are categorized as biotrophic and necrotrophic at the two extremes, and intermediate types 1 . Necrotrophic mycoparasites usually have a broader mycohost range as the interactions, from the initial steps of attack to the final nutrient uptake process, are less specific compared to biotrophic and hemibiotrophic relationships 6 , 17 – 19 . Some fungi, e.g., Trichoderma spp. and Clonostachys rosea , may act as necrotrophic mycoparasites opportunistically, and acquire nutrients from diverse other sources, as well 1 , 6 , 7 , 19 . For other fungi, necrotrophic or biotrophic mycoparasitism appears to be the major or only way of nutrition 12 , 20 – 25 . Examples include Paraphaeosphaeria minitans 20 , Ampelomyces quisqualis 21 , 22 , Syncephalis spp. 23 and Sphaerellopsis spp. 24 , 25 . Empirical evidence 1 – 5 , 16 , genome organization 26 , and phylogenetic relationships between some fungal plant pathogens and mycoparasites 26 , 27 may indicate that aggressive fungal-fungal interactions are similar to those between plant pathogenic fungi and their hosts. Molecular signatures of the mycoparasitic lifestyle may reveal such similarities but are still largely unknown 6 , 7 , 18 . Carbohydrate-Active enZYme (CAZyme) profiles could be useful in understanding mycoparasitism as a special nutrition mode because CAZymes are vital in formation and breakdown of complex carbohydrates and glycoconjugates during diverse ways of nutrition 28 . Many CAZymes are known as effectors in plant pathogens and are used to acquire nutrients from their hosts without being recognised by plant resistance proteins 29 – 30 . The sequences of effector genes are highly diversified between and within fungal species as revealed in well-studied crop pathogens including Blumeria graminis 31 , Zymoseptoria tritici 32 and Parastagonospora nodorum 33 . Interestingly, the tertiary structures of effector proteins exhibit sequence-unrelated similarities through specific folds that were recently identified in diverse, phylogenetically unrelated plant pathogenic fungi 34 . Here, we test the hypothesis that aggressive fungal-fungal parasitic relationships are similar to interactions between plants and their fungal pathogens; and aim to better understand mycoparasitism at molecular level. To achieve this goal, we first selected fungal species that are known as mycoparasites and possess high-quality reference genomes. We added some of their close relatives and/or mycohosts to our initial dataset when possible and compared the CAZyme profiles of mycoparasites to non-mycoparasitic fungi. Second, we selected three, phylogenetically diverse mycoparasites, namely A. quisqualis, P. minitans , and Escovopsis weberi , and their close relatives and/or mycohosts, and searched for candidate effectors in their protein datasets. We applied AlphaFold to predict tertiary structures of selected proteins in these three selected mycoparasites and their relatives. Finally, we used searches in the GenBank database of the National Center for Biotechnology Information (NCBI) to verify that the major or only nutrition mode of these three selected mycoparasites is indeed mycoparasitism as indicated by previous empirical works. Results Phylogeny of selected mycoparasites and their plant pathogenic and other relatives indicates several mycoparasitic lineages across the Fungal Kingdom We first selected mycoparasites with high-quality genome annotations available in public repositories. Whenever possible, we included their protein datasets and also the protein datasets of their closely related plant pathogenic, saprobic, and other relatives in our dataset established for comparative analyses. For example, we included the genome of Parastagonospora nodorum in our database, because it is a close phytopathogenic relative of A. quisqualis , common mycoparasite of powdery mildews 11 , 14 , 15 , 22 , 26 ; and Paraphaeosphaeria sporulosa as a close saprobic relative of the well-known mycoparasite P. minitans 12 , 20 , 35 – 37 . Following quality checks of our initial dataset based on Benchmarking Universal Single-Copy Orthologs (BUSCO) values (Supplementary Table S1 and Supplementary Figs. S1, S2), a phylogenetic analysis was conducted based on 627 orthogroups from 89 selected fungal strains with high-quality genomes, and two oomycetes used as outgroups. The consensus tree is shown in Fig. 1 . Twenty nine out of those 89 fungal strains represent species that are known as mycoparasites and belong to Basidiomycota, Zoopagomycota, Mucoromycota, and all the orders of the Ascomycota, i.e., Orbiliales, Hypocreales, Glomerellales, Cladosporiales, and Pleosporales (Supplementary Table S1 ). For more informed phylogenetic topologies, we subsequently used a subset of 44 ascomycetes that included mycoparasites of interest. This analysis of 2,589 orthogroups with all species present, including 993 single-copy orthologs resulted in topologies a tree with stronger support (Supplementary Fig. S3). This cohort of 44 fungi, including 16 mycoparasites that represent two classes, was included in analyses of their protein profiles. These included analyses of (a) CAZyme patterns of all 44 fungi (i.e. number of genes in a fungus per CAZyme family/subfamily); and (b) candidate effector tertiary structure patterns of selected ascomycete strains that had data suitable for analysis, i.e. high-quality annotations for the mycoparasite and the closely related non-mycoparasitic species or mycohosts (Supplementary Fig. S4). CAZyme analyses group phylogenetically diverse mycoparasites together and point to protein families associated with mycoparasitism To identify patterns associated with the mycoparasitic nutrition mode as opposed to other feeding strategies of diverse fungi, the CAZyme profiles of the 29 selected mycoparasites were first analysed together with a total of 209 representatives of Animalia, Viridiplantae, Oomycota, Archaea and Bacteria (Fig. 2 a). Twenty out of the 29 selected mycoparasites were defined as ‘specialists’ because all their mycohosts belong to a single fungal family or order based on empirical evidence. The other nine mycoparasites were considered as ‘generalists’ (Supplementary Table S3). Principal Component (PC) 1 grouped fungi and oomycetes in clusters that corresponded to their grouping that were reported earlier, when CAZyme analyses were performed in the absence of species outside Fungi and Oomycota 28 . Mycoparasites clustered together with other fungi (Fig. 2 a); however, when fungi were analysed separately, PC1 produced a cluster that included most species known as mycoparasites, e.g., A. quisqualis, P. minitans , E. weberi , and also Trichoderma spp. which includes some generalist mycoparasitic species, but also species that thrive as saprobes or/and plant endophytes instead 8 , 9 , 17 , 38 (Fig. 2 b). There, A. quisqualis grouped close to two fungi that have a symbiotic relationship with plants, i.e. Sebacina vermifera , a mycorrhizal fungus 39 , and Piriformospora indica (synonym Serendipita indica ), a mycorrhiza-like endophytic fungus that colonises diverse plant species by direct manipulation of plant hormone signalling pathways and inducing both local and systemic resistance to several plant diseases through signal transduction 40 . PC3 separated S. vermifera and Pi. indica from mycoparasites (Fig. 2 c). The relatives of the mycoparasites clustered together with A. quisqualis , P. minitans , E. weberi , and Trichoderma spp., despite being known as plant pathogens or saprobes (Fig. 2 c). By default, feeding on fungi does not require cellulases as part of the CAZyme profile as cellulose and hemicellulose are not found in fungi. When we performed blast searches of six well-defined cellulases from plant pathogenic and saprobic fungi against the gene sets of two specialist mycoparasites, A. quisqualis and P. minitans , homologs of cellulases were found in these mycoparasites (Supplementary Table 2). This was somewhat surprising but may point to the close phylogenetic relationship between A. quisqualis and cellulase-using crop pathogens such as Pa. nodorum 41 ; and between P. minitans and the saprobic P. sporulosa that uses cellulases during its life cycle 42 . The analysis of specific CAZyme gene families other than cellulases indicated that gene/protein numbers vary considerably across them. We identified trends in four CAZyme protein families (Supplementary Table 3), i.e. three from the Auxiliary Activities class: AA3-2, AA9 (formerly GH61), AA11, and one from the GlycosylTransferase class: GT2 Chitin Synthase 2 43 . For the families AA3-2 and AA9, we observed that the specialist mycoparasites in the Pleosporales, i.e., A. quisqualis, S. filum and P. minitans have statistically more CAZymes counted in these families compared to the other fungal and oomycete groups (Fig. 2 d, Supplementary Fig. S5) with the exception of their relatives in the Pleosporales and a few Sordariomycetes, indicating identity by descent. Some of our more detailed analyses presented below focused on proteins in the AA9 family. For the CAZyme family AA11, we noticed that there were statistically more genes of that family for some species in the Zoopagomycota mycoparasites compared to all the other fungi and non-fungi (Supplementary Fig. S5). Finally, the GT2 Chitin Synthase 2 stood out for the increased number of genes (25) in the mycoparasite Parasitella parasitica and a few other non-mycoparasitic Mucoromycota (Supplementary Fig. S5). Amongst these four CAZyme families, we studied AA9 further in the analyses presented below. Various proteins of mycoparasites are structurally homologous with candidate effectors of the model plant pathogen Blumeria graminis To identify potential effectors in mycoparasites, we selected the protein datasets of three specialists ( A. quisqualis , P. minitans and E. weberi; Fig. 3 ) and their close relatives: Plenodomus lingam (synonym Leptosphaeria maculans ), a plant pathogen; P. sporulosa , known as an endophyte; and Trichoderma harzianum , a metabolically versatile fungus that is known as an endophyte and also a generalist mycoparasite. These fungi were selected for further analyses based on their available protein profiles in our original dataset (Supplementary Table 1). We added the proteins of Blumeria graminis , a mycohost of A. quisqualis , in these analyses because its effector repertoire has been thoroughly studied (Supplementary Table 1) and we wanted to find any similarities. In these fungi, about 6–12% of the proteins contained a predicted signal peptide (Supplementary Fig. S6). Out of these proteins, approximately 27–73% were identified as candidate effectors using EffectorP. Not surprisingly, the well-studied B. graminis had the highest ratio of candidate effectors. When comparing the number of all candidate effector proteins, we observed that B. graminis has ~ 850, about double the candidate effectors compared to its mycoparasite, A. quisqualis (~ 340), even though B. graminis has a smaller number of predicted proteins compared to its mycoparasite (Supplementary Fig. S6). Regarding another mycohost-mycoparasite pair, P. minitans had more proteins (13,677) and candidate effectors (526) than its mycohost S. sclerotiorum with 11,130 proteins and 347 candidate effectors. Furthermore, E. weberi had about half the proteins and less than half candidate effectors compared to its close relative T. harzianum . To study these candidate effector proteins, we selected A. quisqualis as a mycoparasite of a single fungal family, the Erysiphaceae, that includes economically important and well-studied mycohosts. Two approaches were applied: (a) a de novo approach, focusing on the largest candidate effector clusters identified within A. quisqualis ; and (b) a reference-based approach, where the well-defined B. graminis effectors were used to identify similarities and differences with the A. quisqualis clusters.the three selected mycoparasites The protein sets of the other two selected mycoparasites, P. minitans and E. weberi , were also analysed as part of the reference-based approach. The first approach identified four clusters within the candidate effector protein dataset of A. quisqualis , defined as Clusters A, B, C, and X. These were revealed by studying structure homologies of all the candidate effector proteins with each other (Fig. 4 a). Most proteins in these clusters contained multiple beta sheets and a range of cysteine bridges structurally (Fig. 4 b,c, Supplementary Fig. S7, Supplementary Table 4). We then compared these proteins with B. graminis candidate effectors looking for any structural homology as per our second approach. Proteins in Cluster A were similar to the B. graminis effector family E139 (via its protein Bgt-3979), which is a monogenic family (sharing some homology with two previously unidentified proteins within B. graminis , Bgt-3809 and Bgt-4300) 44 . There was structural homology (> 0.5, both sides) of the A. quisqualis protein mc_14_sg_13_40, belonging to this cluster with 20 other A quisqualis proteins (Fig. 4 b). Protein mc_14_sg_13_40 was then used as the new reference for Cluster A, finding structural homology with 19 P. minitans proteins (Fig. 4 a, Supplementary Table 5). Furthermore, three E. weberi proteins were identified with homology. In comparison, for P. lingam , which is a close relative of Ampelomyces , there were only 11 corresponding proteins. All these proteins were also identified by dbCAN3 as belonging to the CAZyme group AA9 (Supplementary Table S6). Most of these proteins across species had conserved cysteine residues, creating a cysteine bridge, with a few regions on the protein alignment that were conserved (Fig. 4 b,c). Similar patterns were observed for Cluster B (Fig. 4 a), where proteins (with a structure of about ten beta sheets and mostly one or more cysteine bridges) were homologous to the monogenic family E064 (via protein Bgt-55126) with less proteins being homologous in this Cluster (Supplementary Table S7). More specifically, there were six candidate effectors for A. quisqualis , 10 for P. minitans , and 7 for E. weberi , while only three in P. lingam . There was no homology to any CAZyme proteins from dbCAN3, no similarity to other defined proteins on NCBI, and few amino acids were conserved, with potential cysteine bridges conserved in 28 out of these 33 proteins (Supplementary Figs. S7a,b, Supplementary Table S7). In Cluster C (Fig. 4 a), proteins had homology to the ones of the monogenic effector family E156 (via proteins Bgt-178), with fewer proteins than in the previous clusters. In this case, there were three candidate effectors for A. quisqualis , six for P. minitans and two for E. weberi , plus one with slightly less structural homology from one side ~ 0.4. In contrast, P. lingam had only two proteins of homologous structure to the B. graminis candidate effector Bgt-178. Despite having no homology to any CAZyme protein from dbCAN3 and mostly no similarity to other defined proteins on NCBI (apart from > 75% similarity with cupredoxin that may indicate electron transfer activity), many amino acids were conserved across all the seven species included in these analyses, with cysteine bridges fully conserved for all these proteins (Supplementary Fig. S7c, Supplementary Table S8). Cluster X in the A. quisqualis protein set (Fig. 4 a) included 15 proteins with structural homology to each other that had no homology to any known Blumeria effectors. Most of these proteins belonged to the CAZyme groups of polysaccharide lyase (PL) and glycoside hydrolase (GH) (Supplementary Table S9). Finally, there were other effector families in B. graminis that were structurally homologous to mycoparasite proteins, as shown in Supplementary Table S10. Most of these candidate effectors belong to B. graminis families that have only one or a few effectors included, with the exceptions highlighted. All these proteins were placed into three groups. First, we identified proteins that have homologous structure with an equivalent number of proteins with P. lingam , implying an importance in all fungi (E098, E105, E129, E176, and the families E004 and E024 with many effectors in B. graminis ) (Group A in Supplementary Table S10). Then, we have effector families were A. quisqualis has slightly more effector proteins than P. lingam (E070 and E156) (Group B in Supplementary Table S10). Lastly, we have families that do not seem to have an equivalent in P. lingam , even though they do not appear to expand compared to B. graminis (E090, E099, E159, E217, and the multiple effector families E016, E017 and E028) (Group C in Supplementary Table S10). The protein families identified above during in silico analyses represent the first candidate effectors revealed in fungi known as specialist mycoparasites based on microscopy and other empirical evidence 1 – 4 , 16 . Our next step was to verify the observations regarding the way of life of these fungi. Specialised mycoparasitic lifestyle tested with environmental genetic data in NCBI To test whether mycoparasitism is indeed the major nutrition mode of the three fungi included in the candidate effector study, i.e., A. quisqualis, P. minitans and E. weberi , we used their ITS sequences to search for potential matches in any environmental samples across NCBI. We wanted to test if the ITS sequences of these three species have been detected in random samples of environments other than the ecological niches that they occupy as specialised mycoparasites, i.e., powdery mildew colonies for A. quisqualis ; sclerotia in soils for P. minitans ; and ant colonies for E. weberi . Detection of these three fungi outside those niches may indicate that their nutrition mode is more diverse than described in the literature. For A. quisqualis , the only hits in environmental samples were samples of beech ( Fagus sp.) litter; those could potentially contain beech powdery mildew that would explain the hits. For P. minitans we found only two hits: one coming from sclerotia (its mycohost) and another one from tomato potentially infected with Sclerotinia spp. Escovopsis weberi was revealed in a single environmental hit that came from an ant colony sample (Supplementary Table S11). Therefore, environmental samples in NCBI did not reveal data that are in contradiction with the known specialised mycoparasitic nutrition mode of A. quisqualis, P. minitans and E. weberi . This method was also tested with Sphaerellopsis filum , known as a common mycoparasite specialised to rust fungi (Pucciniales) 24 , 25 and no hits were found in environmental samples without their mycohosts. When an ITS sequence of Trichoderma was the query, multiple environmental samples including air, soil, plant material, and water, were positive, which is in accordance with the versatile nutrition mode of this fungus. The ITS sequence of Penicillium brevicompactum , a saprobic fungus that is commonly found in soil 45 – 47 was also used as a query, to test the method, and returned over 30 hits including soil, plant material, air filter and water samples. Discussion Mycoparasitism is a multi-faceted interaction between fungi Fungi have largely evolved as decomposers of organic matter, dead or alive. Some are versatile and take up nutrients in diverse ways, in purely saprobic ways or after killing their live food sources, including plants, animals, and other fungi. Others are more adapted to specific nutrition modes and have developed special mechanisms to feed on organisms that are still alive while being consumed. The genomic signatures of these diverse fungal nutrition modes are necessarily complex especially in versatile species. The mycoparasitic lifestyle is one of the less researched nutrition modes of the fungi despite applications in crop disease biocontrol 10 – 13 and implications in mushroom production 8 , 9 . To our knowledge, this is the first comprehensive analysis that aimed at deciphering some of the general molecular patterns associated with mycoparasitism across the Fungal Kingdom. Our study was severely limited by the low number of high-quality genome annotations of fungi classified as mycoparasites; and also by the lack of detailed structural and functional studies on many fungal-fungal interactions that are described as mycoparasitism in the literature. An example of these limitations is provided by the genus Sphaerellopsis that includes common mycoparasites of many rust fungi (Pucciniales), with a global distribution 25 . Still, the first genome of a Sphaerellopsis mycoparasite was only recently reported 48 and further studies are needed to reveal some of the fine details of the structural interactions between rust colonies and these mycoparasites 24 . CAZymes play an important role in mycoparasitism Fungi secrete a wide spectrum of CAZymes, echoing their specialized habitat-related substrate utilization 49 . Those associated with mycoparasitism are largely unknown. A pioneering genomic and transcriptomic study has identified multiple CAZyme genes present in P. minitans and up-regulation of some of them 37 . In Calcarisporium cordycipiticola , a mycoparasite of Cordyceps spp., the number of CAZymes was reduced compared to other mycoparasites, which was hypothesized to be because of its host specificity 50 . However, some CAZymes were upregulated in this mycoparasite, including the AA9 family 51 that was also revealed in this study as being somewhat expanded in A. quisqualis, P. minitans and E. weberi . Furthermore, the AA9 CAZyme family was identified in two oomycetes, Pythium oligandrum and Pythium periplocum that are known as parasites of oomycete plant pathogens and are also mycoparasites because attack ascomycete and basidiomycete fungi, as well 52 . Therefore, this CAZyme family appears to be associated with the mycoparasitic nutrition mode even beyond the Fungal Kingdom, in the Oomycota, and may also be linked to parasitic interactions between oomycete species. Candidate effectors as tools to understand mycoparasitism Using known effector proteins from the well-studied fungal plant pathogen B. graminis , has provided us with tools to identify candidate effectors that may be involved in mycoparasitism. As revealed in B. graminis , effector families can expand through duplication e.g. AvrPm3 d3 , AvrPm17 , etc 53 , 54 . This results in the formation of large effector families with possibly redundant function, allowing the deletion of some of these effectors, which could prevent recognition by the plant host 44 , 55 . This work identified clusters of candidate effectors where the number of proteins is higher in mycoparasitic species compared to their close non-mycoparasitic relatives depending on the group of proteins. Some of these proteins, above all those in the AA9 family, exhibit clear structural homology in phylogenetically diverse specialist mycoparasites. Proteins in other clusters identified in this work are different, while still exhibiting effector-like structures. Previous studies have identified diverse effector-like proteins associated with some specific interfungal parasitic relationships 6 , 7 , 56 – 59 , and other aggressive fungal-fungal interactions 60 , as well. Our work appears to be the first attempt to reveal effector families that may play a role in mycoparasitism across diverse groups of specialised mycoparasites. Environmental genetic data strengthens the identification of the specialised mycoparasitic nutrition mode All fungi that are currently known as mycoparasites in the literature were defined as such based on direct observations of their interactions with other fungi using light and electron microscopy and other visualisation techniques 4 , 22 , 24 , 25 ,61–63 . Those observations were sometimes based on a limited number of samples, and some studies applied the term ‘mycoparasitism’ loosely to diverse interactions amongst fungi 1 – 5 . Our simple NCBI searches with ITS sequences provided indirect support of the specialized mycoparasitic lifestyle of the target fungi by confirming that these species were not detected at random in environmental genetic samples that had no traces of their mycohosts. This approach could be useful in a variety of other studies. Mycoparasitic relationships may be similar to plant-pathogen interactions This study was driven by the hypothesis that the molecular interplay between specialist mycoparasites and their mycohosts is similar to the interactions between plant pathogenic fungi and their hosts. We showed that CAZyme profiles grouped phylogenetically diverse mycoparasites together and pointed to protein families associated with mycoparasitism. One of these, AA9, has been revealed earlier in an economically important mycoparasite 50, 51 ; and, surprisingly, also in two mycoparasitic oomycete species that parasitise fungi as well as other oomycetes 52 . The discovery that key proteins in the AA9 family of diverse specialist mycoparasites, including oomycetes, are structurally homologous to an effector known in the model plant pathogen B. graminis , may indicate a link between the nutrition mode of this obligate biotrophic plant pathogen and the mycoparasites studied in detail here and in earlier works 50–52 . These results are in line with the hypothesis and shed new light on the molecular mechanisms of mycoparasitism. Methods Data collection and initial analyses First, based on searches in the NCBI GenBank genomic database (as of October 2024), a list of 98 mycoparasitic and non-mycoparasitic fungi and two oomycetes was made, and their protein datasets were collected. The fungal strains represented 29 mycoparasitic and 69 non-mycoparasitic species based on data in the literature (Supplementary Table 1). Whenever possible, we selected mycoparasitic and non-mycoparasitic species within the same genera (e.g., P. minitans and P. sporulosa , or Clonostachys rosea and C. solani ) for comparative analyses. Two oomycete strains were used as outgroups in phylogenomic analyses. The quality of these sequence sets was tested using Benchmarking Universal Single-Copy Orthologs (BUSCO) (v5.4.4) 64,65 , and protein sets that had completeness lower than 80% were removed from the list (Supplementary Figs. S1,S2), except for the Oomycetes and a few fungal species (i.e. Lecanicillium spp., Piptocephalis spp.). Some known mycoparasitic species did not have a representative gene/protein set and had to be excluded (Supplementary Table 1). We ended up with 89 selected strains with their gene/protein sets to use. We grouped these using the Orthofinder software to keep and compare orthologous conserved genes 66 . With the use of the oomycete outgroups and some fungi with lower BUSCO score, we ended up with 627 orthologous genes found in all these 89 strains. Creating phylogenies In order to infer phylogenomic trees we used the filtered dataset on Orthofinder (v2.5.5) 66,67 . The output consensus tree was then visualised using FigTree (v1.4.4, http://tree.bio.ed.ac.uk/software/figtree/ ). CAZymes and cellulases In order to analysze CAZyme protein profiles of all the species, we used the CATAStrophy pipeline (v0.1.0) 28 to search for any differences between mycoparasite and non-mycoparasites on their CAZyme make-up. To make an even more informative grouping we used a bigger dataset by including animals, bacteria, archaea and plants, where we followed the same pipeline as with the original fungal-oomycete dataset (Supplementary Table S1 ). We further analysed specific families of interest studying the counts of genes per species and per group. Since cellulases play an important role on plant pathogenic fungi, we studied the genetic make-up of cellulases on mycoparasites. We collected five cellulase genes from species of specific genera in ( Parastagonospora , Paraphaeosphaeria and Alternaria ) and out ( Trichoderma and Aspergillus ) of the Pleosporales order. We used this dataset to blast against our Ampelomyces gene dataset to find homologous genes (NCBI, September 2024). Discovering candidate effectors in silico In order to find further similarities/differences between mycoparasites and non-mycoparasites, we tried to identify potential candidate effector proteins like in the plant pathogenic fungi that are infected by mycoparasites. Even though effector proteins are routinely identified in plant pathogenic fungi, mycoparasites have not been studied for this purpose. We first checked the protein datasets for signal peptides using SingalP (v6.0g) 68 for A. quisqualis , P. minitans , E. weberi and Trichoderma spp. datasets, along with their close non-mycoparasite, but plant pathogenic relatives P. lingam , P. sporulosa and other Trichoderma spp. respectively and some of their host species (e.g. Sclerotinia sclerotiorum ) were used for comparison of quality statistics in gene numbers (Supplementary Fig. S6). Secondly, we used the EffectorP (v3.0) software to identify candidate effector proteins 69 . The candidate effector proteins had their tertiary structure modelled using the AlphaFold software (v.2) 70 . The results were compared using the software TMalign (v.20190822) 71 and the structures were visualised on the protein data bank ( https://www.rcsb.org/3d-view ). Candidate effector proteins were then blasted on NCBI and aligned with Clustalw (v. 1.83) 72 to check for homology between the used species datasets. Alignments were visualised using Jalview v2.11.3.3 73 . Phylogenetic networks were constructed to depict the relationships of these proteins with Splitstree (v4.19.1) 74 . We used dbCAN3 (26/06/2024) in order to check if any of our candidate effectors belonged to any CAZyme family 75 . Identifying mycoparasites in environmental genomic samples In order to find a new way to improve the identification of mycoparasitic species, we blasted the ITS sequence of some mycoparasites and non-mycoparasitic relatives using NCBI (v2.5.0+). We kept the results that had over 98.5% similarity 76–78 , and 85% query coverage to the input sequence. We removed the sequences that were directly matching the target species/genera classification in order to keep only the environmental and uncultured samples. After getting the accession numbers for 5000 hits each, we retrieved the host, collection site data from NCBI wherever possible and sorted them. Declarations Data Availability Benefits from this research accrue from the sharing of our data and results on public databases as described above.The datasets used in this study are available on NCBI. Acknowledgements We are grateful to Prof. Beat Keller for his insightful comments on a previous version of the manuscript. We are also grateful to Dimitrios Sotiropoulos for his bioinformatics support. Author Contributions L.K. and A.G.S. developed the study conception and design. A.G.S., M.H., T.W. and L.K. performed the data analyses. A.G.S. and L.K. wrote the manuscript. L.K. acquired the funding for the project. L.K., A.G.S., T.W., and M.H. revised the manuscript and discussed the results. All authors read and approved the final manuscript. Funding This work was funded by the Australian Research Council Discovery Project no. DP210103869, and supported by the University of Southern Queensland and the the Swiss National Science Foundation grant 310030_212428. Competing Interests / Conflict of Interest Statement The authors declare no competing interests. References Boddy, L. in The fungi 337–360 (Elsevier, 2016). Sun, J.-Z. et al. Fungicolous fungi: terminology, diversity, distribution, evolution, and species checklist. Fungal Divers. 95, 337–430 (2019). Bermúdez-Cova, M. A. et al. Hyperparasitic fungi—definitions, diversity, ecology, and research. Authorea Prepr. (2023). Jeffries, P. & Young, T. W. K. Interfungal parasitic relationships. (1994). Barnett, H. L. The nature of mycoparasitism by fungi. Annu. Rev. Microbiol. 17, 1–14 (1963). Karlsson, M., Atanasova, L., Jensen, D. F. & Zeilinger, S. Necrotrophic mycoparasites and their genomes. Microbiol. Spectr. 5, 10–1128 (2017). Piombo, E., Guaschino, M., Jensen, D. F., Karlsson, M. & Dubey, M. Insights into the ecological generalist lifestyle of Clonostachys fungi through analysis of their predicted secretomes. Front. Microbiol. 14, 1112673 (2023). Allaga, H. et al. Members of the Trichoderma harzianum species complex with mushroom pathogenic potential. Agronomy 11, 2434 (2021). Kredics, L. et al. in Advances in Trichoderma Biology for Agricultural Applications 559–606 (Springer, 2022). Meher, J., Rajput, R. S., Bajpai, R., Teli, B. & Sarma, B. K. Trichoderma: A globally dominant commercial biofungicide. Trichoderma Agric. Appl. beyond 195–208 (2020). Németh, M. Z., Seress, D. & Nonomura, T. Fungi parasitizing powdery mildew fungi: Ampelomyces strains as biocontrol agents against powdery mildews. Agronomy 13, 1991 (2023). Nicot, P. C. et al. Differential susceptibility to the mycoparasite Paraphaeosphaeria minitans among Sclerotinia sclerotiorum isolates. Trop. Plant Pathol. 44, 82–93 (2019). Funck Jensen, D., Dubey, M., Jensen, B. & Karlsson, M. Clonostachys rosea to control plant diseases. (2022). Tollenaere, C. et al. A hyperparasite affects the population dynamics of a wild plant pathogen. Mol. Ecol. 23, 5877–5887 (2014). Parratt, S. R. & Laine, A.-L. The role of hyperparasitism in microbial pathogen ecology and evolution. ISME J. 10, 1815–1822 (2016). Kiss, L. in Biotic interactions in plant-pathogen associations 227-236 (CABI Publishing International, 2001). Mukherjee, P. K., Mendoza-Mendoza, A., Zeilinger, S. & Horwitz, B. A. Mycoparasitism as a mechanism of Trichoderma-mediated suppression of plant diseases. Fungal Biol. Rev. 39, 15–33 (2022). Singh, S. et al. Harnessing Trichoderma Mycoparasitism as a Tool in the Management of Soil Dwelling Plant Pathogens. Microb. Ecol. 87, 1–14 (2024). Broberg, M. et al. Comparative genomics highlights the importance of drug efflux transporters during evolution of mycoparasitism in Clonostachys subgenus Bionectria (Fungi, Ascomycota, Hypocreales). Evol. Appl. 14, 476–497 (2021). Patel, D. et al. Genome sequence of the biocontrol agent Coniothyrium minitans conio (IMI 134523). Mol. Plant-Microbe Interact. 34, 222–225 (2021). Kiss, L., Russell, J. C., Szentiványi, O., Xu, X. & Jeffries, P. Biology and biocontrol potential of Ampelomyces mycoparasites, natural antagonists of powdery mildew fungi. Biocontrol Sci. Technol. 14, 635–651 (2004). Németh, M. Z. et al. Green fluorescent protein transformation sheds more light on a widespread mycoparasitic interaction. Phytopathology 109, 1404–1416 (2019). Benny, G. L., Ho, H.-M., Lazarus, K. L. & Smith, M. E. Five new species of the obligate mycoparasite Syncephalis (Zoopagales, Zoopagomycotina) from soil. Mycologia 108, 1114–1129 (2016). Gomez-Zapata, P.A., Diaz-Valderrama, J.R., Fatemi, S., Ruiz-Castro, C.O. & Aime, M.C. Characterization of the fungal genus Sphaerellopsis associated with rust fungi: species diversity, host-specificity, biogeography, and in-vitro mycoparasitic events of S. macroconidialis on the southern corn rust, Puccinia polysora. IMA Fungus 15, 18 (2024). Risteski, J., Kiss, L., Idnurm, A., Shivas, R.G., Tan, Y.P., Sun, J. & Vaghefi, N. First molecular phylogeny of mycoparasitic species of Sphaerellopsis isolated from rust fungi in Australia. Mycol. Progress 24, 57 (2025). Huth, L., Ash, G. J., Idnurm, A., Kiss, L. & Vaghefi, N. The “bipartite” structure of the first genome of Ampelomyces quisqualis, a common hyperparasite and biocontrol agent of powdery mildews, may point to its evolutionary origin from plant pathogenic fungi. Genome Biol. Evol. 13, evab182 (2021). Haridas, S. et al. 101 Dothideomycetes genomes: a test case for predicting lifestyles and emergence of pathogens. Stud. Mycol. 96, 141–153 (2020). Hane, J. K., Paxman, J., Jones, D. A. B., Oliver, R. P. & De Wit, P. “CATAStrophy,” a genome-informed trophic classification of filamentous plant pathogens–how many different types of filamentous plant pathogens are there? Front. Microbiol. 10, 3088 (2020). Stukenbrock, E. H. & McDonald, B. A. Population genetics of fungal and oomycete effectors involved in gene-for-gene interactions. Mol. Plant-Microbe Interact. 22, 371–380 (2009). Bourras, S., McNally, K. E., Müller, M. C., Wicker, T. & Keller, B. Avirulence genes in cereal powdery mildews: the gene-for-gene hypothesis 2.0. Front. Plant Sci. 7, 241 (2016). Menardo, F., Praz, C. R., Wicker, T. & Keller, B. Rapid turnover of effectors in grass powdery mildew ( Blumeria graminis ). 1–14 (2017). Gohari, A. M. et al. Effector discovery in the fungal wheat pathogen Zymoseptoria tritici. Mol. Plant Pathol. 16, 931 (2015). Richards, J. K. et al. A triple threat: the Parastagonospora nodorum SnTox267 effector exploits three distinct host genetic factors to cause disease in wheat. New Phytol. 233, 427–442 (2022). Seong, K. & Krasileva, K. V. Prediction of effector protein structures from fungal phytopathogens enables evolutionary analyses. Nat. Microbiol. 8, 174–187 (2023). Verkley, G. J. M., da Silva, M., Wicklow, D. T. & Crous, P. W. Paraconiothyrium, a new genus to accommodate the mycoparasite Coniothyrium minitans, anamorphs of Paraphaeosphaeria, and four new species. Stud. Mycol. 50, 323–336 (2004). Verkley, G. J. M., Dukik, K., Renfurm, R., Göker, M. & Stielow, J. B. Novel genera and species of coniothyrium-like fungi in Montagnulaceae (Ascomycota). Persoonia-Molecular Phylogeny Evol. Fungi 32, 25–51 (2014). Zhao, H. et al. Mycoparasitism illuminated by genome and transcriptome sequencing of Coniothyrium minitans, an important biocontrol fungus of the plant pathogen Sclerotinia sclerotiorum. Microb. genomics 6, e000345 (2020). Zheng, H. et al. New species of Trichoderma isolated as endophytes and saprobes from Southwest China. J. fungi 7, 467 (2021). Ray, P. et al. Genome sequence of the plant growth promoting fungus Serendipita vermifera subsp. bescii: the first native strain from North America. Phytobiomes 2, 62–63 (2018). Gill, S. S. et al. Piriformospora indica: potential and significance in plant stress tolerance. Front. Microbiol. 7, 332 (2016). Hane J.K. et al. Dothideomycete–plant interactions illuminated by genome sequencing and EST analysis of the wheat pathogen Stagonospora nodorum. The Plant Cell 19, 3347–3368 (2007). Zeiner C.A. et al. Quantitative iTRAQ-based secretome analysis reveals species-specific and temporal shifts in carbon utilization strategies among manganese(II)- oxidizing Ascomycete fungi. Fungal Genet. Biol. 106, 61-75 (2017). Drula, E. et al. The carbohydrate-active enzyme database: functions and literature. Nucleic Acids Res. 50, D571–D577 (2022). Müller, M. C. et al. A chromosome-scale genome assembly reveals a highly dynamic effector repertoire of wheat powdery mildew. New Phytol. 221, 2176–2189 (2019). Scott, J. A., Wong, B., Summerbell, R. C. & Untereiner, W. A. A survey of Penicillium brevicompactum and P. bialowiezense from indoor environments, with commentary on the taxonomy of the P. brevicompactum group. Botany 86, 732–741 (2008). Tian, F. H., Li, C. T. & Li, Y. First report of Penicillium brevicompactum causing blue mold disease of Grifola frondosa in China. Plant Dis. 101, 1549 (2017). Ferreira-Filipe, D. A. et al. Biodegradation of e-waste microplastics by Penicillium brevicompactum. Sci. Total Environ. 173334 (2024). D’Angelo D. et al. IMA GENOME-F20 A draft genome assembly of Agroathelia rolfsii, Ceratobasidium papillatum, Pyrenopeziza brassicae, Neopestalotiopsis macadamiae, Sphaerellopsis filum and genomic resources for Colletotrichum spaethianum and Colletotrichum fructicola. IMA Fungus 16, e141732 (2025). Barrett, K., Jensen, K., Meyer, A. S., Frisvad, J. C. & Lange, L. Fungal secretome profile categorization of CAZymes by function and family corresponds to fungal phylogeny and taxonomy: Example Aspergillus and Penicillium. Sci. Rep. 10, 5158 (2020). Liu, Q. et al. Infection process and genome assembly provide insights into the pathogenic mechanism of destructive mycoparasite Calcarisporium cordycipiticola with host specificity. J. Fungi 7, 918 (2021). Liu, Q. & Dong, C. Dual transcriptomics reveals interspecific interactions between the mycoparasite Calcarisporium cordycipiticola and its host Cordyceps militaris. Microbiol. Spectr. 11, e04800-22 (2023). Liang, D., Andersen, C. B., Vetukuri, R. R., Dou, D. & Grenville-Briggs, L. J. Horizontal gene transfer and tandem duplication shape the unique CAZyme complement of the mycoparasitic oomycetes Pythium oligandrum and Pythium periplocum. Front. Microbiol. 11, 581698 (2020). Bourras, S. et al. The AvrPm3-Pm3 effector-NLR interactions control both race-specific resistance and host-specificity of cereal mildews on wheat. Nat. Commun. 10, 2292 (2019). Müller, M. C. et al. Ancient variation of the AvrPm17 gene in powdery mildew limits the effectiveness of the introgressed rye Pm17 resistance gene in wheat. Proc. Natl. Acad. Sci. 119, e2108808119 (2022). Praz, C. R. et al. AvrPm2 encodes an RN ase-like avirulence effector which is conserved in the two different specialized forms of wheat and rye powdery mildew fungus. New Phytol. 213, 1301–1314 (2017). Guzmán-Guzmán, P. et al. Identification of effector-like proteins in Trichoderma spp. and role of a hydrophobin in the plant-fungus interaction and mycoparasitism. BMC Genet. 18, 16 (2017). Dubey, M., Vélëz, H., Broberg, M., Jensen, D.F. and Karlsson, M. LysM proteins regulate fungal development and contribute to hyphal protection and biocontrol traits in Clonostachys rosea. Front. Microbiol. 11, 679 (2020). Zhao, H. et al. Mycoparasitism illuminated by genome and transcriptome sequencing of Coniothyrium minitans, an important biocontrol fungus of the plant pathogen Sclerotinia sclerotiorum. Microb. Genom. 6, e000345 (2020). Liu, Q. et al. Infection process and genome assembly provide insights into the pathogenic mechanism of destructive mycoparasite Calcarisporium cordycipiticola with host specificity. J. Fungi 7, 918 (2021). Laur, J., Ramakrishnan, G.B., LabbÚ, C., Lefebvre, F., Spanu, P.D. and BÚlanger, R.R., 2018. Effectors involved in fungal–fungal interaction lead to a rare phenomenon of hyperbiotrophy in the tritrophic system biocontrol agent–powdery mildew–plant. New Phytologist , 217 (2), pp.713-725. Kiss, L. Natural occurrence of Ampelomyces intracellular mycoparasites in mycelia of powdery mildew fungi. New Phytol. 140, 709–714 (1998). Trakunyingcharoen, T. et al. Mycoparasitic species of Sphaerellopsis, and allied lichenicolous and other genera. IMA Fungus 5, 391–414 (2014). Tsapikounis, F. A., Ipsilandis, C. G. & Greveniotis, V. Studies on the infection and parasitism course of sclerotia of Sclerotinia sclerotiorum by three different mycoparasites. J. Plant Dis. Prot. 126, 225–235 (2019). Simão, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V & Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210–3212 (2015). Manni, M., Berkeley, M. R., Seppey, M., Simão, F. A. & Zdobnov, E. M. BUSCO update: novel and streamlined workflows along with broader and deeper phylogenetic coverage for scoring of eukaryotic, prokaryotic, and viral genomes. Mol. Biol. Evol. 38, 4647–4654 (2021). Emms, D. M. & Kelly, S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 20, 1–14 (2019). Emms, D. M. & Kelly, S. OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy. Genome Biol. 16, 1–14 (2015). Teufel, F. et al. SignalP 6.0 predicts all five types of signal peptides using protein language models. Nat. Biotechnol. 40, 1023–1025 (2022). Sperschneider, J. & Dodds, P. N. EffectorP 3.0: prediction of apoplastic and cytoplasmic effectors in fungi and oomycetes. Mol. plant-microbe Interact. 35, 146–156 (2022). Jumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583–589 (2021). Zhang, Y. & Skolnick, J. TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res. 33, 2302–2309 (2005). Thompson, J. D., Higgins, D. G. & Gibson, T. J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22, 4673–4680 (1994). Waterhouse, A. M., Procter, J. B., Martin, D. M. A., Clamp, M. & Barton, G. J. Jalview Version 2—a multiple sequence alignment editor and analysis workbench. Bioinformatics 25, 1189–1191 (2009). Huson, D. H. SplitsTree: analyzing and visualizing evolutionary data. Bioinformatics 14, 68–73 (1998). Zheng, J. et al. dbCAN3: automated carbohydrate-active enzyme and substrate annotation. Nucleic Acids Res. 51, W115–W121 (2023). Irinyi, L., Lackner, M., De Hoog, G. S. & Meyer, W. DNA barcoding of fungi causing infections in humans and animals. Fungal Biol. 120, 125–136 (2016). Hoang, M. T. V. et al. Dual DNA barcoding for the molecular identification of the agents of invasive fungal infections. Front. Microbiol. 10, 1647 (2019). Salem-Bango, Z. et al. Fungal whole-genome sequencing for species identification: from test development to clinical utilization. J. Fungi 9, 183 (2023). Additional Declarations There is NO Competing Interest. Supplementary Files SupplementaryTablesv28092025submitted1Oct2025.xlsx Supplementary Tables S1-S11 SupplementaryFiguresv23092025submitted1Oct2025.pdf Supplementary Figures S1-S7 Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7759314","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":525297010,"identity":"1e625343-5cdf-441d-8688-105e13e768cc","order_by":0,"name":"Alexandros Sotiropoulos","email":"data:image/png;base64,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","orcid":"","institution":"Centre for Crop Health, University of Southern Queensland, Toowoomba, 4350, QLD, Australia","correspondingAuthor":true,"prefix":"","firstName":"Alexandros","middleName":"","lastName":"Sotiropoulos","suffix":""},{"id":525297011,"identity":"8dcccb61-b759-4891-8495-652cc8e819fd","order_by":1,"name":"Matthias Heuberger","email":"","orcid":"https://orcid.org/0000-0003-3283-9233","institution":"Department of Plant and Microbial Biology, University of Zurich, Zurich, 8008, Switzerland","correspondingAuthor":false,"prefix":"","firstName":"Matthias","middleName":"","lastName":"Heuberger","suffix":""},{"id":525297012,"identity":"d730eaf8-855e-4dcd-bfc8-7cad85884001","order_by":2,"name":"Thomas Wicker","email":"","orcid":"https://orcid.org/0000-0002-6777-7135","institution":"Department of Plant and Microbial Biology, University of Zurich, Zurich, 8008, Switzerland","correspondingAuthor":false,"prefix":"","firstName":"Thomas","middleName":"","lastName":"Wicker","suffix":""},{"id":525297009,"identity":"49e2a41e-b88a-4e5b-b90f-f8b641b2ccbf","order_by":3,"name":"Levente Kiss","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABEElEQVRIie3RMUvDQBTA8RcOkuW5p5x4X+FCICCk5qu8EohTB5fOSuCylM4R9Dv4EVoOdAl1dXCoBDopBLoUOugpWKRwlW4i9x/ucvB+3EEAXK4/mNx+aLN0APh1wl8JAUQlgFcfRGKzse3kXhKMo/ZinUISBO2qr56PRUXe4k2BkFMLwSaOayogZZjwoVqibBYsulUQ3dlIWBQcSX8Snw2VRhmSz48UeFYilucbpHdImHnYqSGipmBjSGa/hd0zpCnEDCT3DIEn8pkhAyvBXHMscoxKTHrjuXlY81L2buZhfm0hWTW7WmF6diIfH9puPdKZqPJZ9zpK+xML+e7njxhcmiXcP78THTTtcrlc/78P2ghSFdiloxAAAAAASUVORK5CYII=","orcid":"https://orcid.org/0000-0002-4785-4308","institution":"Centre for Crop Health, University of Southern Queensland, Toowoomba, 4350, QLD, Australia","correspondingAuthor":true,"prefix":"","firstName":"Levente","middleName":"","lastName":"Kiss","suffix":""}],"badges":[],"createdAt":"2025-10-01 12:05:34","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7759314/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7759314/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":92929297,"identity":"5c5ec725-e106-4b64-b698-5bed4a18bb44","added_by":"auto","created_at":"2025-10-07 08:39:25","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":3433720,"visible":true,"origin":"","legend":"","description":"","filename":"MYCOPARASITISMgenomicsandeffectorssubmitted1Oct2025.docx","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/d70161164d5259954962103b.docx"},{"id":92928276,"identity":"04c8121a-a8cf-4aa3-9394-180203f2e4f8","added_by":"auto","created_at":"2025-10-07 08:31:24","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":5841,"visible":true,"origin":"","legend":"","description":"","filename":"NCOMMS2578521.json","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/ead7c23f6ad3f922380afbd9.json"},{"id":92928280,"identity":"5e0abfb9-9512-40e7-82c7-0114882ee126","added_by":"auto","created_at":"2025-10-07 08:31:24","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":2177546,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFiguresv23092025submitted1Oct2025.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/e647ee4ebcb265171dc8dfa7.pdf"},{"id":92928283,"identity":"fb877e9d-be74-452d-8d18-fda7a6596d70","added_by":"auto","created_at":"2025-10-07 08:31:25","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":140759,"visible":true,"origin":"","legend":"","description":"","filename":"NCOMMS25785210enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/8f9f803df7c4880ff90ee424.xml"},{"id":92929299,"identity":"a6a996ea-72fd-4401-9a65-09d7e13a9e86","added_by":"auto","created_at":"2025-10-07 08:39:25","extension":"jpeg","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1230073,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/4b68393a46c64ee962e268c3.jpeg"},{"id":92928286,"identity":"269b412e-1ffa-485e-a537-32567a12da45","added_by":"auto","created_at":"2025-10-07 08:31:25","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":291045,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/7ff89f72634139e6e76bf2b8.png"},{"id":92928290,"identity":"48f1916d-dad7-4c6c-97b7-e966ed082b51","added_by":"auto","created_at":"2025-10-07 08:31:25","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1538813,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/fb5c6d986da9f91bf90b2b4a.png"},{"id":92929301,"identity":"2b04871c-ed93-408f-a0dd-1bf95f48f0c7","added_by":"auto","created_at":"2025-10-07 08:39:25","extension":"png","order_by":7,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":1334018,"visible":true,"origin":"","legend":"","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/09480f69be605c36611d4a0c.png"},{"id":92928293,"identity":"4e272c4a-1eed-4d7c-a68c-f4ed53aac95a","added_by":"auto","created_at":"2025-10-07 08:31:25","extension":"png","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":212312,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/35bd90b0629277095045d8d8.png"},{"id":92928294,"identity":"6a996ce8-4caf-4493-b074-881c6e410487","added_by":"auto","created_at":"2025-10-07 08:31:25","extension":"png","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":79500,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/9e7af619b849cec598867f34.png"},{"id":92928289,"identity":"e7cda8e6-a9a7-4ee8-a90f-8e21e7da3a7d","added_by":"auto","created_at":"2025-10-07 08:31:25","extension":"png","order_by":10,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":213071,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/adeb6a686e960090398ff6eb.png"},{"id":92928295,"identity":"2761ec5a-1fee-401e-bbc3-d059b6053dde","added_by":"auto","created_at":"2025-10-07 08:31:25","extension":"png","order_by":11,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":225512,"visible":true,"origin":"","legend":"","description":"","filename":"Onlinefloatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/6ca4c4a521ca5b34dc40941f.png"},{"id":92928291,"identity":"3a54ef87-475d-4f03-b837-273817b91da2","added_by":"auto","created_at":"2025-10-07 08:31:25","extension":"xml","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":138603,"visible":true,"origin":"","legend":"","description":"","filename":"NCOMMS25785210structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/50572ed6f642a2c90355cf51.xml"},{"id":92929302,"identity":"73d08534-e958-4fbe-834a-87b601b8f483","added_by":"auto","created_at":"2025-10-07 08:39:25","extension":"html","order_by":13,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":152141,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/48913c19ba62a7731c7c7629.html"},{"id":92928278,"identity":"8a733707-1080-4f3f-852f-45e877a37445","added_by":"auto","created_at":"2025-10-07 08:31:24","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":298492,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe consensus phylogenomic tree of 87 selected fungal strains, including mycoparasites, mycohosts, and related taxa, and two oomycetes as outgroups.\u003c/strong\u003e These strains were selected for this study based on the availability of high-quality genome annotations. The analysis was based on 627 orthogroup genes Lineages representing four fungal phyla (Zoopagomycota, Mucoromycota, Basidiomycota, and Ascomycota) and the Oomycota are shown with coloured background. Strains that are primarily known as mycoparasites based on empirical and other studies are indicated with red asterisks (*). Black asterisks (*) indicate strains with multiple nutrition modes that may include mycoparasitic activity. See also Supplementary Table S1.\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/d5ad2723ed6192f960a1e520.png"},{"id":92929501,"identity":"6605c15f-eff6-4d59-9362-e2be32f7ea12","added_by":"auto","created_at":"2025-10-07 08:47:24","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":343515,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eResults of the CAZyme analyses. a\u003c/strong\u003e, PCA of the two first components for the mycoparasitic fungi along with all other fungi, oomycetes, and other groups (animals, plants, bacteria and archaea) included in the analyses. Main taxonomic groups are indicated with different colours. The plants are separated from the other groups in the top right corner, while the animals are taking up the space in the centre of the PCA. The bacteria and the archaea are placed on the bottom left corner clustering with the obligate biotrophic fungi as they also have fewer CAZyme genes. The fungi and the oomycetes follow the same patterns as in Hane et al. (28). \u003cstrong\u003eb\u003c/strong\u003e, PCA of the first and second components of all fungi included in the analyses. \u003cstrong\u003ec\u003c/strong\u003e, PCA of the second and third components of all fungi. \u003cstrong\u003ed\u003c/strong\u003e, Counts of enzymes per species for CAZyme AA9 of the AA family. “Specialists” refers to mycoparasites that are known to have a restricted mycohost range. The mycoparasitic oomycete \u003cem\u003ePythium oligandrum\u003c/em\u003e is included in this group. “Generalists” refers to mycoparasites with a broad range of mycohosts, such as \u003cem\u003eTrichoderma\u003c/em\u003e spp.. “Pathogens” refers to fungi that are plant and/or animal pathogens. “Relatives” refers to the Pleosporales relatives of \u003cem\u003eAmpelomyces\u003c/em\u003e. “Other Fungi” refers to all other fungi included in the analysis, e.g., saprobes, potential pathogens, and so on. Species name abbreviations are in Supplementary Table 3.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/8b36fcc309b5cc0e828c10cd.png"},{"id":92928281,"identity":"53b51651-6fdc-4e9b-a95a-6b95858aca6a","added_by":"auto","created_at":"2025-10-07 08:31:24","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":884131,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDiagram of the interactions between three specialist mycoparasites and their mycohosts selected for the detailed candidate effector study.\u003c/strong\u003e Fungal hosts (mycohosts) in their natural habitats (left) and being attacked by their naturally occurring specialist mycoparasites (right). \u003cstrong\u003ea\u003c/strong\u003e, \u003cem\u003eBlumeria graminis\u003c/em\u003einfecting the tissues of its host plant (wheat) and causing a crop disease known as powdery mildew. \u003cstrong\u003eb\u003c/strong\u003e, Hyphae and intracellular fruiting bodies (pycnidia) of the mycoparasite \u003cem\u003eAmpelomyces quisqualis\u003c/em\u003e inside the hyphae and the conidiophores of \u003cem\u003eB. graminis\u003c/em\u003e (in red). \u003cstrong\u003ec\u003c/strong\u003e, White mycelia and black sclerotia of \u003cem\u003eSclerotinia sclerotiorum\u003c/em\u003e infecting one of its host plants (beans) and causing a crop disease known as white mould. \u003cstrong\u003ed\u003c/strong\u003e, Small pycnidia of the mycoparasite \u003cem\u003eParaphaeosphaeria minitans\u003c/em\u003e on sclerotia (in red). \u003cstrong\u003ee\u003c/strong\u003e, \u003cem\u003eLeucoagaricus gongylophorus\u003c/em\u003e, a fungus cultivated by leafcutter ants. \u003cstrong\u003ef\u003c/strong\u003e, Hyphae of the mycoparasite \u003cem\u003eEscovopsis weberi\u003c/em\u003e covering\u003cem\u003e L. gongylophorus\u003c/em\u003e (in white).\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/49ec777a22e6e49d41f7e652.png"},{"id":92928284,"identity":"f7b10462-ea2b-45c7-adf7-fb6c79875ae3","added_by":"auto","created_at":"2025-10-07 08:31:25","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1241871,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eClusters of candidate effectors in mycoparasites.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e, A heatmap of the AlphaFold-predicted structure distances between \u003cem\u003eAmpelomyces quisqualiis\u003c/em\u003e candidate effector proteins. Black boxes indicate the clusters of interest (A, C, B, and X); some of them indicate gene expansions. \u003cstrong\u003eb\u003c/strong\u003e, Tertiary structure of the key \u003cem\u003eA. quisqualis\u003c/em\u003e protein (mc_14_sg_13_40) that belongs to the CAZyme family AA9 (Cluster A) and has structural homology to the \u003cem\u003eBlumeria graminis\u003c/em\u003e effector family E139. The zoomed in region in the top right corner depicts the disulfide bridge between the two cysteine residues found in many effector proteins. \u003cstrong\u003ec\u003c/strong\u003e, A protein alignment of all the proteins of Cluster A from the selected mycoparasites and \u003cem\u003eP. lingam\u003c/em\u003e(syn. \u003cem\u003eLeptosphaeria maculans\u003c/em\u003e), a plant pathogenic relative exhibiting similar structures in the family E139. Black boxes indicate cysteine, with conserved positions in most of these proteins.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/cd4c5c0747d4a54447e21840.png"},{"id":93135999,"identity":"1f351e21-caf3-4a3b-bba1-868dcc60fa6f","added_by":"auto","created_at":"2025-10-09 12:14:02","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3859819,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/ff7fd116-93cb-4fac-98f2-e8e45c28ebdd.pdf"},{"id":92928275,"identity":"59be8bc0-d07b-4fc3-b129-32c45bb3057f","added_by":"auto","created_at":"2025-10-07 08:31:24","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":78525,"visible":true,"origin":"","legend":"Supplementary Tables S1-S11","description":"","filename":"SupplementaryTablesv28092025submitted1Oct2025.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/9512ea5e4e0055092f7d0241.xlsx"},{"id":92928279,"identity":"5ba607d2-7922-4f3f-972f-8016a20f3165","added_by":"auto","created_at":"2025-10-07 08:31:24","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":2177546,"visible":true,"origin":"","legend":"Supplementary Figures S1-S7","description":"","filename":"SupplementaryFiguresv23092025submitted1Oct2025.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7759314/v1/d6b3f8327c0d7a0ac5cbf698.pdf"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"What makes a mycoparasite? Similarities between fungi that attack other fungi and fungal and oomycete plant pathogens based on structural homology of their candidate effectors","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSome fungi, from yeasts to mushrooms, are often attacked and damaged by other fungi. Aggressive antagonistic interactions between fungal species may take diverse forms that are sometimes loosely defined in the literature\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. The terms \u0026lsquo;parasitism\u0026rsquo;, usually with the \u0026lsquo;myco-\u0026lsquo; prefix, and also \u0026lsquo;predation\u0026rsquo;, and \u0026lsquo;pathogenicity\u0026rsquo;, have been used to describe such interactions when one fungus feeds and thrives on or inside another living fungus, the mycohost, and damages it through specific adaptations to this lifestyle\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Here we apply the term \u0026lsquo;mycoparasitism\u0026rsquo; to this type of relationship between fungal species that has evolved in diverse groups of fungi through specific genetic, physiological and/or structural adaptations\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4 CR5 CR6\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Mycoparasites can also be considered as pathogens, i.e., disease-causing agents of their mycohosts, and the visual symptoms they may cause can be called as \u0026lsquo;disease\u0026rsquo;. The latter terminology is mostly used in relation to the aggressive antagonistic interactions between some microscopic fungi, such as \u003cem\u003eTrichoderma\u003c/em\u003e spp., and mushrooms as their mycohosts\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Those mycoparasites cause economic damage in mushroom production\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e; others were commercialised as biocontrol agents in crop protection\u003csup\u003e\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e. Ecological studies have revealed the significance of mycoparasitism in natural ecosystems\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eCurrent knowledge on mycoparasitic nutrition mode is largely based on empirical evidence\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Similar to the interactions between plant pathogenic microbes and their photosynthesizing hosts, there is a wide range of mycoparasitic relationships that are categorized as biotrophic and necrotrophic at the two extremes, and intermediate types\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. Necrotrophic mycoparasites usually have a broader mycohost range as the interactions, from the initial steps of attack to the final nutrient uptake process, are less specific compared to biotrophic and hemibiotrophic relationships\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan additionalcitationids=\"CR18\" citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Some fungi, e.g., \u003cem\u003eTrichoderma\u003c/em\u003e spp. and \u003cem\u003eClonostachys rosea\u003c/em\u003e, may act as necrotrophic mycoparasites opportunistically, and acquire nutrients from diverse other sources, as well\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. For other fungi, necrotrophic or biotrophic mycoparasitism appears to be the major or only way of nutrition\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan additionalcitationids=\"CR21 CR22 CR23 CR24\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Examples include \u003cem\u003eParaphaeosphaeria minitans\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eAmpelomyces quisqualis\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eSyncephalis\u003c/em\u003e spp.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e and \u003cem\u003eSphaerellopsis\u003c/em\u003e spp.\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eEmpirical evidence\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, genome organization\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e, and phylogenetic relationships between some fungal plant pathogens and mycoparasites\u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e may indicate that aggressive fungal-fungal interactions are similar to those between plant pathogenic fungi and their hosts. Molecular signatures of the mycoparasitic lifestyle may reveal such similarities but are still largely unknown\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Carbohydrate-Active enZYme (CAZyme) profiles could be useful in understanding mycoparasitism as a special nutrition mode because CAZymes are vital in formation and breakdown of complex carbohydrates and glycoconjugates during diverse ways of nutrition\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Many CAZymes are known as effectors in plant pathogens and are used to acquire nutrients from their hosts without being recognised by plant resistance proteins\u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. The sequences of effector genes are highly diversified between and within fungal species as revealed in well-studied crop pathogens including \u003cem\u003eBlumeria graminis\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e, \u003cem\u003eZymoseptoria tritici\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e and \u003cem\u003eParastagonospora nodorum\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Interestingly, the tertiary structures of effector proteins exhibit sequence-unrelated similarities through specific folds that were recently identified in diverse, phylogenetically unrelated plant pathogenic fungi\u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eHere, we test the hypothesis that aggressive fungal-fungal parasitic relationships are similar to interactions between plants and their fungal pathogens; and aim to better understand mycoparasitism at molecular level. To achieve this goal, we first selected fungal species that are known as mycoparasites and possess high-quality reference genomes. We added some of their close relatives and/or mycohosts to our initial dataset when possible and compared the CAZyme profiles of mycoparasites to non-mycoparasitic fungi. Second, we selected three, phylogenetically diverse mycoparasites, namely \u003cem\u003eA. quisqualis, P. minitans\u003c/em\u003e, and \u003cem\u003eEscovopsis weberi\u003c/em\u003e, and their close relatives and/or mycohosts, and searched for candidate effectors in their protein datasets. We applied AlphaFold to predict tertiary structures of selected proteins in these three selected mycoparasites and their relatives. Finally, we used searches in the GenBank database of the National Center for Biotechnology Information (NCBI) to verify that the major or only nutrition mode of these three selected mycoparasites is indeed mycoparasitism as indicated by previous empirical works.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003ePhylogeny of selected mycoparasites and their plant pathogenic and other relatives indicates several mycoparasitic lineages across the Fungal Kingdom\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWe first selected mycoparasites with high-quality genome annotations available in public repositories. Whenever possible, we included their protein datasets and also the protein datasets of their closely related plant pathogenic, saprobic, and other relatives in our dataset established for comparative analyses. For example, we included the genome of \u003cem\u003eParastagonospora nodorum\u003c/em\u003e in our database, because it is a close phytopathogenic relative of \u003cem\u003eA. quisqualis\u003c/em\u003e, common mycoparasite of powdery mildews\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e; and \u003cem\u003eParaphaeosphaeria sporulosa\u003c/em\u003e as a close saprobic relative of the well-known mycoparasite \u003cem\u003eP. minitans\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan additionalcitationids=\"CR36\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Following quality checks of our initial dataset based on Benchmarking Universal Single-Copy Orthologs (BUSCO) values (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e and Supplementary Figs. S1, S2), a phylogenetic analysis was conducted based on 627 orthogroups from 89 selected fungal strains with high-quality genomes, and two oomycetes used as outgroups. The consensus tree is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Twenty nine out of those 89 fungal strains represent species that are known as mycoparasites and belong to Basidiomycota, Zoopagomycota, Mucoromycota, and all the orders of the Ascomycota, i.e., Orbiliales, Hypocreales, Glomerellales, Cladosporiales, and Pleosporales (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). For more informed phylogenetic topologies, we subsequently used a subset of 44 ascomycetes that included mycoparasites of interest. This analysis of 2,589 orthogroups with all species present, including 993 single-copy orthologs resulted in topologies a tree with stronger support (Supplementary Fig. S3). This cohort of 44 fungi, including 16 mycoparasites that represent two classes, was included in analyses of their protein profiles. These included analyses of (a) CAZyme patterns of all 44 fungi (i.e. number of genes in a fungus per CAZyme family/subfamily); and (b) candidate effector tertiary structure patterns of selected ascomycete strains that had data suitable for analysis, i.e. high-quality annotations for the mycoparasite and the closely related non-mycoparasitic species or mycohosts (Supplementary Fig. S4).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003cp\u003e\u003cb\u003eCAZyme analyses group phylogenetically diverse mycoparasites together and point to protein families associated with mycoparasitism\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo identify patterns associated with the mycoparasitic nutrition mode as opposed to other feeding strategies of diverse fungi, the CAZyme profiles of the 29 selected mycoparasites were first analysed together with a total of 209 representatives of Animalia, Viridiplantae, Oomycota, Archaea and Bacteria (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea). Twenty out of the 29 selected mycoparasites were defined as \u0026lsquo;specialists\u0026rsquo; because all their mycohosts belong to a single fungal family or order based on empirical evidence. The other nine mycoparasites were considered as \u0026lsquo;generalists\u0026rsquo; (Supplementary Table S3). Principal Component (PC) 1 grouped fungi and oomycetes in clusters that corresponded to their grouping that were reported earlier, when CAZyme analyses were performed in the absence of species outside Fungi and Oomycota\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Mycoparasites clustered together with other fungi (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea); however, when fungi were analysed separately, PC1 produced a cluster that included most species known as mycoparasites, e.g., \u003cem\u003eA. quisqualis, P. minitans\u003c/em\u003e, \u003cem\u003eE. weberi\u003c/em\u003e, and also \u003cem\u003eTrichoderma\u003c/em\u003e spp. which includes some generalist mycoparasitic species, but also species that thrive as saprobes or/and plant endophytes instead\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). There, \u003cem\u003eA. quisqualis\u003c/em\u003e grouped close to two fungi that have a symbiotic relationship with plants, i.e. \u003cem\u003eSebacina vermifera\u003c/em\u003e, a mycorrhizal fungus\u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, and \u003cem\u003ePiriformospora indica\u003c/em\u003e (synonym \u003cem\u003eSerendipita indica\u003c/em\u003e), a mycorrhiza-like endophytic fungus that colonises diverse plant species by direct manipulation of plant hormone signalling pathways and inducing both local and systemic resistance to several plant diseases through signal transduction\u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. PC3 separated \u003cem\u003eS. vermifera\u003c/em\u003e and \u003cem\u003ePi. indica\u003c/em\u003e from mycoparasites (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). The relatives of the mycoparasites clustered together with \u003cem\u003eA. quisqualis\u003c/em\u003e, \u003cem\u003eP. minitans\u003c/em\u003e, \u003cem\u003eE. weberi\u003c/em\u003e, and \u003cem\u003eTrichoderma\u003c/em\u003e spp., despite being known as plant pathogens or saprobes (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eBy default, feeding on fungi does not require cellulases as part of the CAZyme profile as cellulose and hemicellulose are not found in fungi. When we performed blast searches of six well-defined cellulases from plant pathogenic and saprobic fungi against the gene sets of two specialist mycoparasites, \u003cem\u003eA. quisqualis\u003c/em\u003e and \u003cem\u003eP. minitans\u003c/em\u003e, homologs of cellulases were found in these mycoparasites (Supplementary Table\u0026nbsp;2). This was somewhat surprising but may point to the close phylogenetic relationship between \u003cem\u003eA. quisqualis\u003c/em\u003e and cellulase-using crop pathogens such as \u003cem\u003ePa. nodorum\u003c/em\u003e\u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e; and between \u003cem\u003eP. minitans\u003c/em\u003e and the saprobic \u003cem\u003eP. sporulosa\u003c/em\u003e that uses cellulases during its life cycle\u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eThe analysis of specific CAZyme gene families other than cellulases indicated that gene/protein numbers vary considerably across them. We identified trends in four CAZyme protein families (Supplementary Table\u0026nbsp;3), i.e. three from the Auxiliary Activities class: AA3-2, AA9 (formerly GH61), AA11, and one from the GlycosylTransferase class: GT2 Chitin Synthase 2\u003csup\u003e43\u003c/sup\u003e. For the families AA3-2 and AA9, we observed that the specialist mycoparasites in the Pleosporales, i.e., \u003cem\u003eA. quisqualis, S. filum\u003c/em\u003e and \u003cem\u003eP. minitans\u003c/em\u003e have statistically more CAZymes counted in these families compared to the other fungal and oomycete groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed, Supplementary Fig. S5) with the exception of their relatives in the Pleosporales and a few Sordariomycetes, indicating identity by descent. Some of our more detailed analyses presented below focused on proteins in the AA9 family. For the CAZyme family AA11, we noticed that there were statistically more genes of that family for some species in the Zoopagomycota mycoparasites compared to all the other fungi and non-fungi (Supplementary Fig. S5). Finally, the GT2 Chitin Synthase 2 stood out for the increased number of genes (25) in the mycoparasite \u003cem\u003eParasitella parasitica\u003c/em\u003e and a few other non-mycoparasitic Mucoromycota (Supplementary Fig. S5). Amongst these four CAZyme families, we studied AA9 further in the analyses presented below.\u003c/p\u003e\u003cp\u003e\u003cb\u003eVarious proteins of mycoparasites are structurally homologous with candidate effectors of the model plant pathogen\u003c/b\u003e \u003cb\u003eBlumeria graminis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eTo identify potential effectors in mycoparasites, we selected the protein datasets of three specialists (\u003cem\u003eA. quisqualis\u003c/em\u003e, \u003cem\u003eP. minitans\u003c/em\u003e and \u003cem\u003eE. weberi;\u003c/em\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) and their close relatives: \u003cem\u003ePlenodomus lingam\u003c/em\u003e (synonym \u003cem\u003eLeptosphaeria maculans\u003c/em\u003e), a plant pathogen; \u003cem\u003eP. sporulosa\u003c/em\u003e, known as an endophyte; and \u003cem\u003eTrichoderma harzianum\u003c/em\u003e, a metabolically versatile fungus that is known as an endophyte and also a generalist mycoparasite. These fungi were selected for further analyses based on their available protein profiles in our original dataset (Supplementary Table\u0026nbsp;1). We added the proteins of \u003cem\u003eBlumeria graminis\u003c/em\u003e, a mycohost of \u003cem\u003eA. quisqualis\u003c/em\u003e, in these analyses because its effector repertoire has been thoroughly studied (Supplementary Table\u0026nbsp;1) and we wanted to find any similarities.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eIn these fungi, about 6\u0026ndash;12% of the proteins contained a predicted signal peptide (Supplementary Fig. S6). Out of these proteins, approximately 27\u0026ndash;73% were identified as candidate effectors using EffectorP. Not surprisingly, the well-studied \u003cem\u003eB. graminis\u003c/em\u003e had the highest ratio of candidate effectors. When comparing the number of all candidate effector proteins, we observed that \u003cem\u003eB. graminis\u003c/em\u003e has ~\u0026thinsp;850, about double the candidate effectors compared to its mycoparasite, \u003cem\u003eA. quisqualis\u003c/em\u003e (~\u0026thinsp;340), even though \u003cem\u003eB. graminis\u003c/em\u003e has a smaller number of predicted proteins compared to its mycoparasite (Supplementary Fig. S6). Regarding another mycohost-mycoparasite pair, \u003cem\u003eP. minitans\u003c/em\u003e had more proteins (13,677) and candidate effectors (526) than its mycohost \u003cem\u003eS. sclerotiorum\u003c/em\u003e with 11,130 proteins and 347 candidate effectors. Furthermore, \u003cem\u003eE. weberi\u003c/em\u003e had about half the proteins and less than half candidate effectors compared to its close relative \u003cem\u003eT. harzianum\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eTo study these candidate effector proteins, we selected \u003cem\u003eA. quisqualis\u003c/em\u003e as a mycoparasite of a single fungal family, the Erysiphaceae, that includes economically important and well-studied mycohosts. Two approaches were applied: (a) a \u003cem\u003ede novo\u003c/em\u003e approach, focusing on the largest candidate effector clusters identified within \u003cem\u003eA. quisqualis\u003c/em\u003e; and (b) a reference-based approach, where the well-defined \u003cem\u003eB. graminis\u003c/em\u003e effectors were used to identify similarities and differences with the \u003cem\u003eA. quisqualis\u003c/em\u003e clusters.the three selected mycoparasites The protein sets of the other two selected mycoparasites, \u003cem\u003eP. minitans\u003c/em\u003e and \u003cem\u003eE. weberi\u003c/em\u003e, were also analysed as part of the reference-based approach.\u003c/p\u003e\u003cp\u003eThe first approach identified four clusters within the candidate effector protein dataset of \u003cem\u003eA. quisqualis\u003c/em\u003e, defined as Clusters A, B, C, and X. These were revealed by studying structure homologies of all the candidate effector proteins with each other (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Most proteins in these clusters contained multiple beta sheets and a range of cysteine bridges structurally (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb,c, Supplementary Fig. S7, Supplementary Table\u0026nbsp;4). We then compared these proteins with \u003cem\u003eB. graminis\u003c/em\u003e candidate effectors looking for any structural homology as per our second approach.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eProteins in Cluster A were similar to the \u003cem\u003eB. graminis\u003c/em\u003e effector family E139 (via its protein Bgt-3979), which is a monogenic family (sharing some homology with two previously unidentified proteins within \u003cem\u003eB. graminis\u003c/em\u003e, Bgt-3809 and Bgt-4300)\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. There was structural homology (\u0026gt;\u0026thinsp;0.5, both sides) of the \u003cem\u003eA. quisqualis\u003c/em\u003e protein mc_14_sg_13_40, belonging to this cluster with 20 other \u003cem\u003eA quisqualis\u003c/em\u003e proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb). Protein mc_14_sg_13_40 was then used as the new reference for Cluster A, finding structural homology with 19 \u003cem\u003eP. minitans\u003c/em\u003e proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea, Supplementary Table\u0026nbsp;5). Furthermore, three \u003cem\u003eE. weberi\u003c/em\u003e proteins were identified with homology. In comparison, for \u003cem\u003eP. lingam\u003c/em\u003e, which is a close relative of \u003cem\u003eAmpelomyces\u003c/em\u003e, there were only 11 corresponding proteins. All these proteins were also identified by dbCAN3 as belonging to the CAZyme group AA9 (Supplementary Table S6). Most of these proteins across species had conserved cysteine residues, creating a cysteine bridge, with a few regions on the protein alignment that were conserved (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb,c).\u003c/p\u003e\u003cp\u003eSimilar patterns were observed for Cluster B (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea), where proteins (with a structure of about ten beta sheets and mostly one or more cysteine bridges) were homologous to the monogenic family E064 (via protein Bgt-55126) with less proteins being homologous in this Cluster (Supplementary Table S7). More specifically, there were six candidate effectors for \u003cem\u003eA. quisqualis\u003c/em\u003e, 10 for \u003cem\u003eP. minitans\u003c/em\u003e, and 7 for \u003cem\u003eE. weberi\u003c/em\u003e, while only three in \u003cem\u003eP. lingam\u003c/em\u003e. There was no homology to any CAZyme proteins from dbCAN3, no similarity to other defined proteins on NCBI, and few amino acids were conserved, with potential cysteine bridges conserved in 28 out of these 33 proteins (Supplementary Figs. S7a,b, Supplementary Table S7).\u003c/p\u003e\u003cp\u003eIn Cluster C (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea), proteins had homology to the ones of the monogenic effector family E156 (via proteins Bgt-178), with fewer proteins than in the previous clusters. In this case, there were three candidate effectors for \u003cem\u003eA. quisqualis\u003c/em\u003e, six for \u003cem\u003eP. minitans\u003c/em\u003e and two for \u003cem\u003eE. weberi\u003c/em\u003e, plus one with slightly less structural homology from one side\u0026thinsp;~\u0026thinsp;0.4. In contrast, \u003cem\u003eP. lingam\u003c/em\u003e had only two proteins of homologous structure to the \u003cem\u003eB. graminis\u003c/em\u003e candidate effector Bgt-178. Despite having no homology to any CAZyme protein from dbCAN3 and mostly no similarity to other defined proteins on NCBI (apart from \u0026gt;\u0026thinsp;75% similarity with cupredoxin that may indicate electron transfer activity), many amino acids were conserved across all the seven species included in these analyses, with cysteine bridges fully conserved for all these proteins (Supplementary Fig. S7c, Supplementary Table S8).\u003c/p\u003e\u003cp\u003eCluster X in the \u003cem\u003eA. quisqualis\u003c/em\u003e protein set (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea) included 15 proteins with structural homology to each other that had no homology to any known \u003cem\u003eBlumeria\u003c/em\u003e effectors. Most of these proteins belonged to the CAZyme groups of polysaccharide lyase (PL) and glycoside hydrolase (GH) (Supplementary Table S9).\u003c/p\u003e\u003cp\u003eFinally, there were other effector families in \u003cem\u003eB. graminis\u003c/em\u003e that were structurally homologous to mycoparasite proteins, as shown in Supplementary Table S10. Most of these candidate effectors belong to \u003cem\u003eB. graminis\u003c/em\u003e families that have only one or a few effectors included, with the exceptions highlighted. All these proteins were placed into three groups. First, we identified proteins that have homologous structure with an equivalent number of proteins with \u003cem\u003eP. lingam\u003c/em\u003e, implying an importance in all fungi (E098, E105, E129, E176, and the families E004 and E024 with many effectors in \u003cem\u003eB. graminis\u003c/em\u003e) (Group A in Supplementary Table S10). Then, we have effector families were \u003cem\u003eA. quisqualis\u003c/em\u003e has slightly more effector proteins than \u003cem\u003eP. lingam\u003c/em\u003e (E070 and E156) (Group B in Supplementary Table S10). Lastly, we have families that do not seem to have an equivalent in \u003cem\u003eP. lingam\u003c/em\u003e, even though they do not appear to expand compared to \u003cem\u003eB. graminis\u003c/em\u003e (E090, E099, E159, E217, and the multiple effector families E016, E017 and E028) (Group C in Supplementary Table S10).\u003c/p\u003e\u003cp\u003eThe protein families identified above during in silico analyses represent the first candidate effectors revealed in fungi known as specialist mycoparasites based on microscopy and other empirical evidence\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Our next step was to verify the observations regarding the way of life of these fungi.\u003c/p\u003e\u003c/div\u003e\n\u003cp\u003e\u003cb\u003eSpecialised mycoparasitic lifestyle tested with environmental genetic data in NCBI\u003c/b\u003e\u003c/p\u003e\n\u003cp\u003eTo test whether mycoparasitism is indeed the major nutrition mode of the three fungi included in the candidate effector study, i.e., \u003cem\u003eA. quisqualis, P. minitans\u003c/em\u003e and \u003cem\u003eE. weberi\u003c/em\u003e, we used their ITS sequences to search for potential matches in any environmental samples across NCBI. We wanted to test if the ITS sequences of these three species have been detected in random samples of environments other than the ecological niches that they occupy as specialised mycoparasites, i.e., powdery mildew colonies for \u003cem\u003eA. quisqualis\u003c/em\u003e; sclerotia in soils for \u003cem\u003eP. minitans\u003c/em\u003e; and ant colonies for \u003cem\u003eE. weberi\u003c/em\u003e. Detection of these three fungi outside those niches may indicate that their nutrition mode is more diverse than described in the literature. For \u003cem\u003eA. quisqualis\u003c/em\u003e, the only hits in environmental samples were samples of beech (\u003cem\u003eFagus\u003c/em\u003e sp.) litter; those could potentially contain beech powdery mildew that would explain the hits. For \u003cem\u003eP. minitans\u003c/em\u003e we found only two hits: one coming from sclerotia (its mycohost) and another one from tomato potentially infected with \u003cem\u003eSclerotinia\u003c/em\u003e spp. \u003cem\u003eEscovopsis weberi\u003c/em\u003e was revealed in a single environmental hit that came from an ant colony sample (Supplementary Table S11). Therefore, environmental samples in NCBI did not reveal data that are in contradiction with the known specialised mycoparasitic nutrition mode of \u003cem\u003eA. quisqualis, P. minitans\u003c/em\u003e and \u003cem\u003eE. weberi\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eThis method was also tested with \u003cem\u003eSphaerellopsis filum\u003c/em\u003e, known as a common mycoparasite specialised to rust fungi (Pucciniales)\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e and no hits were found in environmental samples without their mycohosts. When an ITS sequence of \u003cem\u003eTrichoderma\u003c/em\u003e was the query, multiple environmental samples including air, soil, plant material, and water, were positive, which is in accordance with the versatile nutrition mode of this fungus. The ITS sequence of \u003cem\u003ePenicillium brevicompactum\u003c/em\u003e, a saprobic fungus that is commonly found in soil\u003csup\u003e\u003cspan additionalcitationids=\"CR46\" citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e was also used as a query, to test the method, and returned over 30 hits including soil, plant material, air filter and water samples.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003cp\u003e\u003cb\u003eMycoparasitism is a multi-faceted interaction between fungi\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFungi have largely evolved as decomposers of organic matter, dead or alive. Some are versatile and take up nutrients in diverse ways, in purely saprobic ways or after killing their live food sources, including plants, animals, and other fungi. Others are more adapted to specific nutrition modes and have developed special mechanisms to feed on organisms that are still alive while being consumed.\u003c/p\u003e\u003cp\u003eThe genomic signatures of these diverse fungal nutrition modes are necessarily complex especially in versatile species. The mycoparasitic lifestyle is one of the less researched nutrition modes of the fungi despite applications in crop disease biocontrol\u003csup\u003e\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e and implications in mushroom production\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eTo our knowledge, this is the first comprehensive analysis that aimed at deciphering some of the general molecular patterns associated with mycoparasitism across the Fungal Kingdom. Our study was severely limited by the low number of high-quality genome annotations of fungi classified as mycoparasites; and also by the lack of detailed structural and functional studies on many fungal-fungal interactions that are described as mycoparasitism in the literature. An example of these limitations is provided by the genus \u003cem\u003eSphaerellopsis\u003c/em\u003e that includes common mycoparasites of many rust fungi (Pucciniales), with a global distribution\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Still, the first genome of a \u003cem\u003eSphaerellopsis\u003c/em\u003e mycoparasite was only recently reported\u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e and further studies are needed to reveal some of the fine details of the structural interactions between rust colonies and these mycoparasites\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\n\u003cp\u003e\u003cb\u003eCAZymes play an important role in mycoparasitism\u003c/b\u003e\u003c/p\u003e\n\u003cp\u003eFungi secrete a wide spectrum of CAZymes, echoing their specialized habitat-related substrate utilization\u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. Those associated with mycoparasitism are largely unknown. A pioneering genomic and transcriptomic study has identified multiple CAZyme genes present in \u003cem\u003eP. minitans\u003c/em\u003e and up-regulation of some of them\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. In \u003cem\u003eCalcarisporium cordycipiticola\u003c/em\u003e, a mycoparasite of \u003cem\u003eCordyceps\u003c/em\u003e spp., the number of CAZymes was reduced compared to other mycoparasites, which was hypothesized to be because of its host specificity\u003csup\u003e50\u003c/sup\u003e. However, some CAZymes were upregulated in this mycoparasite, including the AA9 family\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e that was also revealed in this study as being somewhat expanded in \u003cem\u003eA. quisqualis, P. minitans\u003c/em\u003e and \u003cem\u003eE. weberi\u003c/em\u003e.\u003c/p\u003e\u003cp\u003eFurthermore, the AA9 CAZyme family was identified in two oomycetes, \u003cem\u003ePythium oligandrum\u003c/em\u003e and \u003cem\u003ePythium periplocum\u003c/em\u003e that are known as parasites of oomycete plant pathogens and are also mycoparasites because attack ascomycete and basidiomycete fungi, as well\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. Therefore, this CAZyme family appears to be associated with the mycoparasitic nutrition mode even beyond the Fungal Kingdom, in the Oomycota, and may also be linked to parasitic interactions between oomycete species.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003cp\u003e\u003cb\u003eCandidate effectors as tools to understand mycoparasitism\u003c/b\u003e\u003c/p\u003e\u003cp\u003eUsing known effector proteins from the well-studied fungal plant pathogen \u003cem\u003eB. graminis\u003c/em\u003e, has provided us with tools to identify candidate effectors that may be involved in mycoparasitism. As revealed in \u003cem\u003eB. graminis\u003c/em\u003e, effector families can expand through duplication e.g. \u003cem\u003eAvrPm3\u003c/em\u003e\u003csup\u003e\u003cem\u003ed3\u003c/em\u003e\u003c/sup\u003e, \u003cem\u003eAvrPm17\u003c/em\u003e, etc\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e53\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e. This results in the formation of large effector families with possibly redundant function, allowing the deletion of some of these effectors, which could prevent recognition by the plant host\u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e,\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u003c/sup\u003e. This work identified clusters of candidate effectors where the number of proteins is higher in mycoparasitic species compared to their close non-mycoparasitic relatives depending on the group of proteins. Some of these proteins, above all those in the AA9 family, exhibit clear structural homology in phylogenetically diverse specialist mycoparasites. Proteins in other clusters identified in this work are different, while still exhibiting effector-like structures.\u003c/p\u003e\u003cp\u003ePrevious studies have identified diverse effector-like proteins associated with some specific interfungal parasitic relationships\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e,\u003cspan additionalcitationids=\"CR57 CR58\" citationid=\"CR55\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e59\u003c/span\u003e\u003c/sup\u003e, and other aggressive fungal-fungal interactions\u003csup\u003e\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e60\u003c/span\u003e\u003c/sup\u003e, as well. Our work appears to be the first attempt to reveal effector families that may play a role in mycoparasitism across diverse groups of specialised mycoparasites.\u003c/p\u003e\u003c/div\u003e\n\u003cp\u003e\u003cb\u003eEnvironmental genetic data strengthens the identification of the specialised mycoparasitic nutrition mode\u003c/b\u003e\u003c/p\u003e\n\u003cp\u003eAll fungi that are currently known as mycoparasites in the literature were defined as such based on direct observations of their interactions with other fungi using light and electron microscopy and other visualisation techniques\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e,\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e,61\u0026ndash;63\u003c/sup\u003e. Those observations were sometimes based on a limited number of samples, and some studies applied the term \u0026lsquo;mycoparasitism\u0026rsquo; loosely to diverse interactions amongst fungi\u003csup\u003e\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Our simple NCBI searches with ITS sequences provided indirect support of the specialized mycoparasitic lifestyle of the target fungi by confirming that these species were not detected at random in environmental genetic samples that had no traces of their mycohosts. This approach could be useful in a variety of other studies.\u003c/p\u003e\n\u003cp\u003e\u003cb\u003eMycoparasitic relationships may be similar to plant-pathogen interactions\u003c/b\u003e\u003c/p\u003e\n\u003cp\u003eThis study was driven by the hypothesis that the molecular interplay between specialist mycoparasites and their mycohosts is similar to the interactions between plant pathogenic fungi and their hosts. We showed that CAZyme profiles grouped phylogenetically diverse mycoparasites together and pointed to protein families associated with mycoparasitism. One of these, AA9, has been revealed earlier in an economically important mycoparasite\u003csup\u003e50,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e; and, surprisingly, also in two mycoparasitic oomycete species that parasitise fungi as well as other oomycetes\u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e. The discovery that key proteins in the AA9 family of diverse specialist mycoparasites, including oomycetes, are structurally homologous to an effector known in the model plant pathogen \u003cem\u003eB. graminis\u003c/em\u003e, may indicate a link between the nutrition mode of this obligate biotrophic plant pathogen and the mycoparasites studied in detail here and in earlier works\u003csup\u003e50\u0026ndash;52\u003c/sup\u003e. These results are in line with the hypothesis and shed new light on the molecular mechanisms of mycoparasitism.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003cdiv id=\"Sec12\" class=\"Section3\"\u003e\u003cp\u003e\u003cb\u003eData collection and initial analyses\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFirst, based on searches in the NCBI GenBank genomic database (as of October 2024), a list of 98 mycoparasitic and non-mycoparasitic fungi and two oomycetes was made, and their protein datasets were collected. The fungal strains represented 29 mycoparasitic and 69 non-mycoparasitic species based on data in the literature (Supplementary Table\u0026nbsp;1). Whenever possible, we selected mycoparasitic and non-mycoparasitic species within the same genera (e.g., \u003cem\u003eP. minitans\u003c/em\u003e and \u003cem\u003eP. sporulosa\u003c/em\u003e, or \u003cem\u003eClonostachys rosea\u003c/em\u003e and \u003cem\u003eC. solani\u003c/em\u003e) for comparative analyses. Two oomycete strains were used as outgroups in phylogenomic analyses.\u003c/p\u003e\u003cp\u003eThe quality of these sequence sets was tested using Benchmarking Universal Single-Copy Orthologs (BUSCO) (v5.4.4)\u003csup\u003e64,65\u003c/sup\u003e, and protein sets that had completeness lower than 80% were removed from the list (Supplementary Figs. S1,S2), except for the Oomycetes and a few fungal species (i.e. \u003cem\u003eLecanicillium\u003c/em\u003e spp., \u003cem\u003ePiptocephalis\u003c/em\u003e spp.). Some known mycoparasitic species did not have a representative gene/protein set and had to be excluded (Supplementary Table\u0026nbsp;1). We ended up with 89 selected strains with their gene/protein sets to use. We grouped these using the Orthofinder software to keep and compare orthologous conserved genes\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u003c/sup\u003e. With the use of the oomycete outgroups and some fungi with lower BUSCO score, we ended up with 627 orthologous genes found in all these 89 strains.\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003cp\u003e\u003cb\u003eCreating phylogenies\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn order to infer phylogenomic trees we used the filtered dataset on Orthofinder (v2.5.5)\u003csup\u003e66,67\u003c/sup\u003e. The output consensus tree was then visualised using FigTree (v1.4.4, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://tree.bio.ed.ac.uk/software/figtree/\u003c/span\u003e\u003cspan address=\"http://tree.bio.ed.ac.uk/software/figtree/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003cp\u003e\u003cb\u003eCAZymes and cellulases\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn order to analysze CAZyme protein profiles of all the species, we used the CATAStrophy pipeline (v0.1.0)\u003csup\u003e28\u003c/sup\u003e to search for any differences between mycoparasite and non-mycoparasites on their CAZyme make-up. To make an even more informative grouping we used a bigger dataset by including animals, bacteria, archaea and plants, where we followed the same pipeline as with the original fungal-oomycete dataset (Supplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). We further analysed specific families of interest studying the counts of genes per species and per group.\u003c/p\u003e\u003cp\u003eSince cellulases play an important role on plant pathogenic fungi, we studied the genetic make-up of cellulases on mycoparasites. We collected five cellulase genes from species of specific genera in (\u003cem\u003eParastagonospora\u003c/em\u003e, \u003cem\u003eParaphaeosphaeria\u003c/em\u003e and \u003cem\u003eAlternaria\u003c/em\u003e) and out (\u003cem\u003eTrichoderma\u003c/em\u003e and \u003cem\u003eAspergillus\u003c/em\u003e) of the Pleosporales order. We used this dataset to blast against our \u003cem\u003eAmpelomyces\u003c/em\u003e gene dataset to find homologous genes (NCBI, September 2024).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003cp\u003e\u003cb\u003eDiscovering candidate effectors in silico\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn order to find further similarities/differences between mycoparasites and non-mycoparasites, we tried to identify potential candidate effector proteins like in the plant pathogenic fungi that are infected by mycoparasites. Even though effector proteins are routinely identified in plant pathogenic fungi, mycoparasites have not been studied for this purpose. We first checked the protein datasets for signal peptides using SingalP (v6.0g)\u003csup\u003e\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e for \u003cem\u003eA. quisqualis\u003c/em\u003e, \u003cem\u003eP. minitans\u003c/em\u003e, \u003cem\u003eE. weberi\u003c/em\u003e and \u003cem\u003eTrichoderma\u003c/em\u003e spp. datasets, along with their close non-mycoparasite, but plant pathogenic relatives \u003cem\u003eP. lingam\u003c/em\u003e, \u003cem\u003eP. sporulosa\u003c/em\u003e and other \u003cem\u003eTrichoderma\u003c/em\u003e spp. respectively and some of their host species (e.g. \u003cem\u003eSclerotinia sclerotiorum\u003c/em\u003e) were used for comparison of quality statistics in gene numbers (Supplementary Fig. S6). Secondly, we used the EffectorP (v3.0) software to identify candidate effector proteins\u003csup\u003e\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u003c/sup\u003e. The candidate effector proteins had their tertiary structure modelled using the AlphaFold software (v.2)\u003csup\u003e70\u003c/sup\u003e. The results were compared using the software TMalign (v.20190822)\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e and the structures were visualised on the protein data bank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.rcsb.org/3d-view\u003c/span\u003e\u003cspan address=\"https://www.rcsb.org/3d-view\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Candidate effector proteins were then blasted on NCBI and aligned with Clustalw (v. 1.83)\u003csup\u003e\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e72\u003c/span\u003e\u003c/sup\u003e to check for homology between the used species datasets. Alignments were visualised using Jalview v2.11.3.3\u003csup\u003e73\u003c/sup\u003e. Phylogenetic networks were constructed to depict the relationships of these proteins with Splitstree (v4.19.1)\u003csup\u003e74\u003c/sup\u003e. We used dbCAN3 (26/06/2024) in order to check if any of our candidate effectors belonged to any CAZyme family\u003csup\u003e\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e75\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003cp\u003e\u003cb\u003eIdentifying mycoparasites in environmental genomic samples\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn order to find a new way to improve the identification of mycoparasitic species, we blasted the ITS sequence of some mycoparasites and non-mycoparasitic relatives using NCBI (v2.5.0+). We kept the results that had over 98.5% similarity\u003csup\u003e76\u0026ndash;78\u003c/sup\u003e, and 85% query coverage to the input sequence. We removed the sequences that were directly matching the target species/genera classification in order to keep only the environmental and uncultured samples. After getting the accession numbers for 5000 hits each, we retrieved the host, collection site data from NCBI wherever possible and sorted them.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBenefits from this research accrue from the sharing of our data and results on public databases as described above.The datasets used in this study are available on NCBI.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe are grateful to Prof. Beat Keller for his insightful comments on a previous version of the manuscript. We are also grateful to Dimitrios Sotiropoulos for his bioinformatics support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eL.K. and A.G.S. developed the study conception and design. A.G.S., M.H., T.W. and L.K. performed the data analyses. A.G.S. and L.K. wrote the manuscript. L.K. acquired the funding for the project. L.K., A.G.S., T.W.,\u0026nbsp;and M.H. revised the manuscript and discussed the results. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was funded by the Australian Research Council Discovery Project no.\u0026nbsp;DP210103869, and supported by the University of Southern Queensland and the the Swiss National Science Foundation grant 310030_212428.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests / Conflict of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBoddy, L. in The fungi 337\u0026ndash;360 (Elsevier, 2016).\u003c/li\u003e\n\u003cli\u003eSun, J.-Z. et al. Fungicolous fungi: terminology, diversity, distribution, evolution, and species checklist. Fungal Divers. 95, 337\u0026ndash;430 (2019).\u003c/li\u003e\n\u003cli\u003eBerm\u0026uacute;dez-Cova, M. A. et al. Hyperparasitic fungi\u0026mdash;definitions, diversity, ecology, and research. Authorea Prepr. (2023).\u003c/li\u003e\n\u003cli\u003eJeffries, P. \u0026amp; Young, T. W. K. Interfungal parasitic relationships. (1994).\u003c/li\u003e\n\u003cli\u003eBarnett, H. L. The nature of mycoparasitism by fungi. Annu. Rev. Microbiol. 17, 1\u0026ndash;14 (1963).\u003c/li\u003e\n\u003cli\u003eKarlsson, M., Atanasova, L., Jensen, D. F. \u0026amp; Zeilinger, S. Necrotrophic mycoparasites and their genomes. Microbiol. Spectr. 5, 10\u0026ndash;1128 (2017).\u003c/li\u003e\n\u003cli\u003ePiombo, E., Guaschino, M., Jensen, D. F., Karlsson, M. \u0026amp; Dubey, M. Insights into the ecological generalist lifestyle of Clonostachys fungi through analysis of their predicted secretomes. Front. Microbiol. 14, 1112673 (2023).\u003c/li\u003e\n\u003cli\u003eAllaga, H. et al. Members of the Trichoderma harzianum species complex with mushroom pathogenic potential. Agronomy 11, 2434 (2021).\u003c/li\u003e\n\u003cli\u003eKredics, L. et al. in Advances in Trichoderma Biology for Agricultural Applications 559\u0026ndash;606 (Springer, 2022).\u003c/li\u003e\n\u003cli\u003eMeher, J., Rajput, R. S., Bajpai, R., Teli, B. \u0026amp; Sarma, B. K. Trichoderma: A globally dominant commercial biofungicide. Trichoderma Agric. Appl. beyond 195\u0026ndash;208 (2020).\u003c/li\u003e\n\u003cli\u003eN\u0026eacute;meth, M. Z., Seress, D. \u0026amp; Nonomura, T. Fungi parasitizing powdery mildew fungi: Ampelomyces strains as biocontrol agents against powdery mildews. Agronomy 13, 1991 (2023).\u003c/li\u003e\n\u003cli\u003eNicot, P. C. et al. Differential susceptibility to the mycoparasite Paraphaeosphaeria minitans among Sclerotinia sclerotiorum isolates. Trop. Plant Pathol. 44, 82\u0026ndash;93 (2019).\u003c/li\u003e\n\u003cli\u003eFunck Jensen, D., Dubey, M., Jensen, B. \u0026amp; Karlsson, M. Clonostachys rosea to control plant diseases. (2022).\u003c/li\u003e\n\u003cli\u003eTollenaere, C. et al. A hyperparasite affects the population dynamics of a wild plant pathogen. Mol. Ecol. 23, 5877\u0026ndash;5887 (2014).\u003c/li\u003e\n\u003cli\u003eParratt, S. R. \u0026amp; Laine, A.-L. The role of hyperparasitism in microbial pathogen ecology and evolution. ISME J. 10, 1815\u0026ndash;1822 (2016).\u003c/li\u003e\n\u003cli\u003eKiss, L. in Biotic interactions in plant-pathogen associations 227-236 (CABI Publishing International, 2001).\u003c/li\u003e\n\u003cli\u003eMukherjee, P. K., Mendoza-Mendoza, A., Zeilinger, S. \u0026amp; Horwitz, B. A. Mycoparasitism as a mechanism of Trichoderma-mediated suppression of plant diseases. Fungal Biol. Rev. 39, 15\u0026ndash;33 (2022).\u003c/li\u003e\n\u003cli\u003eSingh, S. et al. Harnessing Trichoderma Mycoparasitism as a Tool in the Management of Soil Dwelling Plant Pathogens. Microb. Ecol. 87, 1\u0026ndash;14 (2024).\u003c/li\u003e\n\u003cli\u003eBroberg, M. et al. Comparative genomics highlights the importance of drug efflux transporters during evolution of mycoparasitism in Clonostachys subgenus Bionectria (Fungi, Ascomycota, Hypocreales). Evol. Appl. 14, 476\u0026ndash;497 (2021).\u003c/li\u003e\n\u003cli\u003ePatel, D. et al. Genome sequence of the biocontrol agent Coniothyrium minitans conio (IMI 134523). Mol. Plant-Microbe Interact. 34, 222\u0026ndash;225 (2021).\u003c/li\u003e\n\u003cli\u003eKiss, L., Russell, J. C., Szentiv\u0026aacute;nyi, O., Xu, X. \u0026amp; Jeffries, P. Biology and biocontrol potential of Ampelomyces mycoparasites, natural antagonists of powdery mildew fungi. Biocontrol Sci. Technol. 14, 635\u0026ndash;651 (2004).\u003c/li\u003e\n\u003cli\u003eN\u0026eacute;meth, M. Z. et al. Green fluorescent protein transformation sheds more light on a widespread mycoparasitic interaction. Phytopathology 109, 1404\u0026ndash;1416 (2019).\u003c/li\u003e\n\u003cli\u003eBenny, G. L., Ho, H.-M., Lazarus, K. L. \u0026amp; Smith, M. E. Five new species of the obligate mycoparasite Syncephalis (Zoopagales, Zoopagomycotina) from soil. Mycologia 108, 1114\u0026ndash;1129 (2016).\u003c/li\u003e\n\u003cli\u003eGomez-Zapata, P.A., Diaz-Valderrama, J.R., Fatemi, S., Ruiz-Castro, C.O. \u0026amp; Aime, M.C. Characterization of the fungal genus Sphaerellopsis associated with rust fungi: species diversity, host-specificity, biogeography, and in-vitro mycoparasitic events of S. macroconidialis on the southern corn rust, Puccinia polysora. IMA Fungus 15, 18 (2024). \u003c/li\u003e\n\u003cli\u003eRisteski, J., Kiss, L., Idnurm, A., Shivas, R.G., Tan, Y.P., Sun, J. \u0026amp; Vaghefi, N. First molecular phylogeny of mycoparasitic species of Sphaerellopsis isolated from rust fungi in Australia. Mycol. Progress 24, 57 (2025).\u003c/li\u003e\n\u003cli\u003eHuth, L., Ash, G. J., Idnurm, A., Kiss, L. \u0026amp; Vaghefi, N. The \u0026ldquo;bipartite\u0026rdquo; structure of the first genome of Ampelomyces quisqualis, a common hyperparasite and biocontrol agent of powdery mildews, may point to its evolutionary origin from plant pathogenic fungi. Genome Biol. Evol. 13, evab182 (2021).\u003c/li\u003e\n\u003cli\u003eHaridas, S. et al. 101 Dothideomycetes genomes: a test case for predicting lifestyles and emergence of pathogens. Stud. Mycol. 96, 141\u0026ndash;153 (2020).\u003c/li\u003e\n\u003cli\u003eHane, J. K., Paxman, J., Jones, D. A. B., Oliver, R. P. \u0026amp; De Wit, P. \u0026ldquo;CATAStrophy,\u0026rdquo; a genome-informed trophic classification of filamentous plant pathogens\u0026ndash;how many different types of filamentous plant pathogens are there? Front. Microbiol. 10, 3088 (2020).\u003c/li\u003e\n\u003cli\u003eStukenbrock, E. H. \u0026amp; McDonald, B. A. Population genetics of fungal and oomycete effectors involved in gene-for-gene interactions. Mol. Plant-Microbe Interact. 22, 371\u0026ndash;380 (2009).\u003c/li\u003e\n\u003cli\u003eBourras, S., McNally, K. E., M\u0026uuml;ller, M. C., Wicker, T. \u0026amp; Keller, B. Avirulence genes in cereal powdery mildews: the gene-for-gene hypothesis 2.0. Front. Plant Sci. 7, 241 (2016).\u003c/li\u003e\n\u003cli\u003eMenardo, F., Praz, C. R., Wicker, T. \u0026amp; Keller, B. Rapid turnover of effectors in grass powdery mildew ( Blumeria graminis ). 1\u0026ndash;14 (2017).\u003c/li\u003e\n\u003cli\u003eGohari, A. M. et al. Effector discovery in the fungal wheat pathogen Zymoseptoria tritici. Mol. Plant Pathol. 16, 931 (2015).\u003c/li\u003e\n\u003cli\u003eRichards, J. K. et al. A triple threat: the Parastagonospora nodorum SnTox267 effector exploits three distinct host genetic factors to cause disease in wheat. New Phytol. 233, 427\u0026ndash;442 (2022).\u003c/li\u003e\n\u003cli\u003eSeong, K. \u0026amp; Krasileva, K. V. Prediction of effector protein structures from fungal phytopathogens enables evolutionary analyses. Nat. Microbiol. 8, 174\u0026ndash;187 (2023).\u003c/li\u003e\n\u003cli\u003eVerkley, G. J. M., da Silva, M., Wicklow, D. T. \u0026amp; Crous, P. W. Paraconiothyrium, a new genus to accommodate the mycoparasite Coniothyrium minitans, anamorphs of Paraphaeosphaeria, and four new species. Stud. Mycol. 50, 323\u0026ndash;336 (2004).\u003c/li\u003e\n\u003cli\u003eVerkley, G. J. M., Dukik, K., Renfurm, R., G\u0026ouml;ker, M. \u0026amp; Stielow, J. B. Novel genera and species of coniothyrium-like fungi in Montagnulaceae (Ascomycota). Persoonia-Molecular Phylogeny Evol. Fungi 32, 25\u0026ndash;51 (2014).\u003c/li\u003e\n\u003cli\u003eZhao, H. et al. Mycoparasitism illuminated by genome and transcriptome sequencing of Coniothyrium minitans, an important biocontrol fungus of the plant pathogen Sclerotinia sclerotiorum. Microb. genomics 6, e000345 (2020).\u003c/li\u003e\n\u003cli\u003eZheng, H. et al. New species of Trichoderma isolated as endophytes and saprobes from Southwest China. J. fungi 7, 467 (2021).\u003c/li\u003e\n\u003cli\u003eRay, P. et al. Genome sequence of the plant growth promoting fungus Serendipita vermifera subsp. bescii: the first native strain from North America. Phytobiomes 2, 62\u0026ndash;63 (2018).\u003c/li\u003e\n\u003cli\u003eGill, S. S. et al. Piriformospora indica: potential and significance in plant stress tolerance. Front. Microbiol. 7, 332 (2016).\u003c/li\u003e\n\u003cli\u003eHane J.K. et al. Dothideomycete\u0026ndash;plant interactions illuminated by genome sequencing and EST analysis of the wheat pathogen Stagonospora nodorum. The Plant Cell 19, 3347\u0026ndash;3368 (2007).\u003c/li\u003e\n\u003cli\u003eZeiner C.A. et al. Quantitative iTRAQ-based secretome analysis reveals species-specific and temporal shifts in carbon utilization strategies among manganese(II)- oxidizing Ascomycete fungi. Fungal Genet. Biol. 106, 61-75 (2017).\u003c/li\u003e\n\u003cli\u003eDrula, E. et al. The carbohydrate-active enzyme database: functions and literature. Nucleic Acids Res. 50, D571\u0026ndash;D577 (2022).\u003c/li\u003e\n\u003cli\u003eM\u0026uuml;ller, M. C. et al. A chromosome-scale genome assembly reveals a highly dynamic effector repertoire of wheat powdery mildew. New Phytol. 221, 2176\u0026ndash;2189 (2019).\u003c/li\u003e\n\u003cli\u003eScott, J. A., Wong, B., Summerbell, R. C. \u0026amp; Untereiner, W. A. A survey of Penicillium brevicompactum and P. bialowiezense from indoor environments, with commentary on the taxonomy of the P. brevicompactum group. Botany 86, 732\u0026ndash;741 (2008).\u003c/li\u003e\n\u003cli\u003eTian, F. H., Li, C. T. \u0026amp; Li, Y. First report of Penicillium brevicompactum causing blue mold disease of Grifola frondosa in China. Plant Dis. 101, 1549 (2017).\u003c/li\u003e\n\u003cli\u003eFerreira-Filipe, D. A. et al. Biodegradation of e-waste microplastics by Penicillium brevicompactum. Sci. Total Environ. 173334 (2024).\u003c/li\u003e\n\u003cli\u003eD\u0026rsquo;Angelo D. et al. IMA GENOME-F20 A draft genome assembly of Agroathelia rolfsii, Ceratobasidium papillatum, Pyrenopeziza brassicae, Neopestalotiopsis macadamiae, Sphaerellopsis filum and genomic resources for Colletotrichum spaethianum and Colletotrichum fructicola. IMA Fungus 16, e141732 (2025). \u003c/li\u003e\n\u003cli\u003eBarrett, K., Jensen, K., Meyer, A. S., Frisvad, J. C. \u0026amp; Lange, L. Fungal secretome profile categorization of CAZymes by function and family corresponds to fungal phylogeny and taxonomy: Example Aspergillus and Penicillium. Sci. Rep. 10, 5158 (2020).\u003c/li\u003e\n\u003cli\u003eLiu, Q. et al. Infection process and genome assembly provide insights into the pathogenic mechanism of destructive mycoparasite Calcarisporium cordycipiticola with host specificity. J. Fungi 7, 918 (2021).\u003c/li\u003e\n\u003cli\u003eLiu, Q. \u0026amp; Dong, C. Dual transcriptomics reveals interspecific interactions between the mycoparasite Calcarisporium cordycipiticola and its host Cordyceps militaris. Microbiol. Spectr. 11, e04800-22 (2023).\u003c/li\u003e\n\u003cli\u003eLiang, D., Andersen, C. B., Vetukuri, R. R., Dou, D. \u0026amp; Grenville-Briggs, L. J. Horizontal gene transfer and tandem duplication shape the unique CAZyme complement of the mycoparasitic oomycetes Pythium oligandrum and Pythium periplocum. Front. Microbiol. 11, 581698 (2020).\u003c/li\u003e\n\u003cli\u003eBourras, S. et al. The AvrPm3-Pm3 effector-NLR interactions control both race-specific resistance and host-specificity of cereal mildews on wheat. Nat. Commun. 10, 2292 (2019).\u003c/li\u003e\n\u003cli\u003eM\u0026uuml;ller, M. C. et al. Ancient variation of the AvrPm17 gene in powdery mildew limits the effectiveness of the introgressed rye Pm17 resistance gene in wheat. Proc. Natl. Acad. Sci. 119, e2108808119 (2022).\u003c/li\u003e\n\u003cli\u003ePraz, C. R. et al. AvrPm2 encodes an RN ase-like avirulence effector which is conserved in the two different specialized forms of wheat and rye powdery mildew fungus. New Phytol. 213, 1301\u0026ndash;1314 (2017).\u003c/li\u003e\n\u003cli\u003eGuzm\u0026aacute;n-Guzm\u0026aacute;n, P. et al. Identification of effector-like proteins in \u003cem\u003eTrichoderma\u003c/em\u003e spp. and role of a hydrophobin in the plant-fungus interaction and mycoparasitism. BMC Genet. 18, 16 (2017).\u003c/li\u003e\n\u003cli\u003eDubey, M., V\u0026eacute;l\u0026euml;z, H., Broberg, M., Jensen, D.F. and Karlsson, M. LysM proteins regulate fungal development and contribute to hyphal protection and biocontrol traits in Clonostachys rosea. Front. Microbiol. 11, 679 (2020).\u003c/li\u003e\n\u003cli\u003eZhao, H. et al. Mycoparasitism illuminated by genome and transcriptome sequencing of Coniothyrium minitans, an important biocontrol fungus of the plant pathogen Sclerotinia sclerotiorum. Microb. Genom. 6, e000345 (2020).\u003c/li\u003e\n\u003cli\u003eLiu, Q. et al. Infection process and genome assembly provide insights into the pathogenic mechanism of destructive mycoparasite \u003cem\u003eCalcarisporium cordycipiticola\u003c/em\u003e with host specificity. J. Fungi 7, 918 (2021).\u003c/li\u003e\n\u003cli\u003eLaur, J., Ramakrishnan, G.B., Labb\u0026Uacute;, C., Lefebvre, F., Spanu, P.D. and B\u0026Uacute;langer, R.R., 2018. Effectors involved in fungal\u0026ndash;fungal interaction lead to a rare phenomenon of hyperbiotrophy in the tritrophic system biocontrol agent\u0026ndash;powdery mildew\u0026ndash;plant. \u003cem\u003eNew Phytologist\u003c/em\u003e, \u003cem\u003e217\u003c/em\u003e(2), pp.713-725.\u003c/li\u003e\n\u003cli\u003eKiss, L. Natural occurrence of Ampelomyces intracellular mycoparasites in mycelia of powdery mildew fungi. New Phytol. 140, 709\u0026ndash;714 (1998).\u003c/li\u003e\n\u003cli\u003eTrakunyingcharoen, T. et al. Mycoparasitic species of Sphaerellopsis, and allied lichenicolous and other genera. IMA Fungus 5, 391\u0026ndash;414 (2014).\u003c/li\u003e\n\u003cli\u003eTsapikounis, F. A., Ipsilandis, C. G. \u0026amp; Greveniotis, V. Studies on the infection and parasitism course of sclerotia of Sclerotinia sclerotiorum by three different mycoparasites. J. Plant Dis. Prot. 126, 225\u0026ndash;235 (2019).\u003c/li\u003e\n\u003cli\u003eSim\u0026atilde;o, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V \u0026amp; Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210\u0026ndash;3212 (2015).\u003c/li\u003e\n\u003cli\u003eManni, M., Berkeley, M. R., Seppey, M., Sim\u0026atilde;o, F. A. \u0026amp; Zdobnov, E. M. BUSCO update: novel and streamlined workflows along with broader and deeper phylogenetic coverage for scoring of eukaryotic, prokaryotic, and viral genomes. Mol. Biol. Evol. 38, 4647\u0026ndash;4654 (2021).\u003c/li\u003e\n\u003cli\u003eEmms, D. M. \u0026amp; Kelly, S. OrthoFinder: phylogenetic orthology inference for comparative genomics. Genome Biol. 20, 1\u0026ndash;14 (2019).\u003c/li\u003e\n\u003cli\u003eEmms, D. M. \u0026amp; Kelly, S. OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy. Genome Biol. 16, 1\u0026ndash;14 (2015).\u003c/li\u003e\n\u003cli\u003eTeufel, F. et al. SignalP 6.0 predicts all five types of signal peptides using protein language models. Nat. Biotechnol. 40, 1023\u0026ndash;1025 (2022).\u003c/li\u003e\n\u003cli\u003eSperschneider, J. \u0026amp; Dodds, P. N. EffectorP 3.0: prediction of apoplastic and cytoplasmic effectors in fungi and oomycetes. Mol. plant-microbe Interact. 35, 146\u0026ndash;156 (2022).\u003c/li\u003e\n\u003cli\u003eJumper, J. et al. Highly accurate protein structure prediction with AlphaFold. Nature 596, 583\u0026ndash;589 (2021).\u003c/li\u003e\n\u003cli\u003eZhang, Y. \u0026amp; Skolnick, J. TM-align: a protein structure alignment algorithm based on the TM-score. Nucleic Acids Res. 33, 2302\u0026ndash;2309 (2005).\u003c/li\u003e\n\u003cli\u003eThompson, J. D., Higgins, D. G. \u0026amp; Gibson, T. J. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 22, 4673\u0026ndash;4680 (1994).\u003c/li\u003e\n\u003cli\u003eWaterhouse, A. M., Procter, J. B., Martin, D. M. A., Clamp, M. \u0026amp; Barton, G. J. Jalview Version 2\u0026mdash;a multiple sequence alignment editor and analysis workbench. Bioinformatics 25, 1189\u0026ndash;1191 (2009).\u003c/li\u003e\n\u003cli\u003eHuson, D. H. SplitsTree: analyzing and visualizing evolutionary data. Bioinformatics 14, 68\u0026ndash;73 (1998).\u003c/li\u003e\n\u003cli\u003eZheng, J. et al. dbCAN3: automated carbohydrate-active enzyme and substrate annotation. Nucleic Acids Res. 51, W115\u0026ndash;W121 (2023).\u003c/li\u003e\n\u003cli\u003eIrinyi, L., Lackner, M., De Hoog, G. S. \u0026amp; Meyer, W. DNA barcoding of fungi causing infections in humans and animals. Fungal Biol. 120, 125\u0026ndash;136 (2016).\u003c/li\u003e\n\u003cli\u003eHoang, M. T. V. et al. Dual DNA barcoding for the molecular identification of the agents of invasive fungal infections. Front. Microbiol. 10, 1647 (2019).\u003c/li\u003e\n\u003cli\u003eSalem-Bango, Z. et al. Fungal whole-genome sequencing for species identification: from test development to clinical utilization. J. Fungi 9, 183 (2023).\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":true,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7759314/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7759314/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eFungi that feed and thrive on other living fungi and damage those through specific adaptations to this lifestyle are known as mycoparasites. Despite its ecological significance and practical applications in crop protection, this type of parasitism is still poorly understood. Here, we hypothesize that aggressive fungal-fungal parasitic interactions are similar to those between plants and their fungal pathogens. We tested this hypothesis in two ways. First, we analyzed the genetic signatures of the mycoparasitic nutrition mode through the Carbohydrate-Active enZYme (CAZyme) profiles of more than 50 fungi with high-quality reference genomes across the Fungal Kingdom, including mycoparasites and their close relatives. Two CAZyme families, AA3-2 and AA9, appeared to be associated with mycoparasitism. Second, we searched for candidate effectors in protein datasets of three specialist mycoparasites and closely related fungi. Based on the tertiary structures of selected proteins predicted by AlphaFold, we identified protein clusters. Surprisingly, several tertiary structures predicted in all three, phylogenetically diverse mycoparasites were homologous to well-studied candidate effectors in a model plant pathogen, \u003cem\u003eBlumeria graminis\u003c/em\u003e. One of these protein clusters belonged to the AA9 CAZyme family. These results supported our hypothesis and revealed a new approach to understand mycoparasitism at molecular level.\u003c/p\u003e","manuscriptTitle":"What makes a mycoparasite? Similarities between fungi that attack other fungi and fungal and oomycete plant pathogens based on structural homology of their candidate effectors","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-07 08:31:20","doi":"10.21203/rs.3.rs-7759314/v1","editorialEvents":[{"type":"communityComments","content":5}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"76420453-608d-4051-8d4f-dcbd055c7c02","owner":[],"postedDate":"October 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":55822961,"name":"Biological sciences/Microbiology/Fungi/Fungal genomics"},{"id":55822962,"name":"Biological sciences/Microbiology/Fungi/Fungal pathogenesis"}],"tags":[{"value":"featured","date":"2025-10-07 13:33:41"}],"updatedAt":"2025-10-09T12:05:54+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-07 08:31:20","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7759314","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7759314","identity":"rs-7759314","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}