Discovery of a novel fungal Tc toxin complex and a functional myco- serpin via a unique two-by-two comparative genomics pipeline

Discovery of a novel fungal Tc toxin complex and a functional myco- serpin via a unique two-by-two comparative genomics pipeline | 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 Research Article Discovery of a novel fungal Tc toxin complex and a functional myco- serpin via a unique two-by-two comparative genomics pipeline Zack Saud, Yujuan Luo, Martyn J. Wood, Ian Boostrom, Bruce J. MacLachlan, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6005389/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 Background Fungi have been a rich source of pharmaceuticals such as antibiotics, immunosuppressants, and cholesterol-lowering drugs; however, their therapeutic potential remains largely untapped due to difficulties in culturing and elucidating the genetic basis of beneficial traits. Fungi contain 'cryptic' genes that are expressed under certain, and often obscure, growth conditions and can produce complex compounds that are difficult to synthesize economically. Developments in genome sequencing and DNA-synthesis technologies offer new opportunities to produce such compounds using biotechnological techniques, however, accurately identifying useful and novel genes, a prerequisite for such approaches, remains challenging. Results We present a novel ‘two-by-two’ comparative genomics pipeline for comprehensive gene analysis of selected fungal groups, enabling more confident identification of unique genes across the analyzed species. The approach compares gene sets from two strains of the same species with those from two strains of different species or families within a fungal order. Self-clustering orthologs that are unique to strains from the same species provide higher confidence in identifying species-specific proteins and help reduce noise from low-quality genome assemblies and gene prediction errors. We validated our method on a well-studied group of fungi, discovering the first functional myco-serpin and an undescribed fungal Tc toxin complex. Using a gene knockout approach, we have implicated both proteins’ roles in the insect host infection process of this entomopathogenic fungal species. Conclusions Elucidating the genes underlying beneficial traits in fungi presents significant challenges, largely due to the unique and relatively complex aspects of their lifestyles. Our two-by-two approach offers broad potential for applications in fungal genome mining and bioprospecting as exemplified in this study by the discovery of the first fungal Tc toxin complex and a functional myco-serpin. We identified genes with high sequence identity to this serpin in other pathogenic fungal strains, including those known to infect humans. Furthermore, the two-by-two approach can be adapted to other organisms with genome architectures similar to fungi. Bioinformatics Fungi Hypocreales Infection Serpin Tc toxin Biosynthetic Gene Cluster Comparative Genomics Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Fungi have played crucial roles in human industrial activities for millennia [ 1 ]. The discovery of Penicillin marked the beginning of extensive exploration into fungal metabolites [ 2 , 3 ] that led to the development of further classes of fungal-derived pharmaceuticals such as; cyclosporine [ 4 ], an immunosuppressive agent, lovastatin [ 5 ], a cholesterol-lowering drug, and various other antibiotics with differing modes of action, such as fusidic acid and cephalosporin [ 6 , 7 ]. Despite these achievements, the development of fungal therapeutics has lagged in comparison to other organisms for several reasons. Fungi exhibit intricate life cycles, encompassing the production of spores, mycelia, and fruiting bodies. Notably, the biosynthesis of bioactive compounds in fungi often occurs at specific developmental stages, with some metabolites being structurally complex and large. This inherent complexity can render their extraction and purification more cost-effective than chemical synthesis, as exemplified by the production of cyclosporine. Cultivating fungi and extracting metabolites often necessitates specialized techniques, with fewer than 5% of species having been successfully cultured to date [ 8 ]. Additionally, large-scale extraction of useful compounds demands substantial investment in tailored bioreactors and monitoring systems for each species, making plant-based natural product discovery more financially attractive to pharmaceutical companies. Fungi generally harbor more "cryptic" genes compared to other organisms, such as plants [ 9 ], that only activate in response to specific, often obscure, environmental cues or stressors, rendering them undetectable to transcriptomic, proteomic, and gene-knockout screening. This presents a significant opportunity for fungal natural product discovery through advanced comparative genomic approaches, as the presence of cryptic genes indicates that the biosynthetic potential of many cultivable fungi is likely much greater than currently recognized [ 10 ]. With the advent of NGS and improved DNA synthesis technologies, novel approaches have been developed such as the "HEx" synthetic biology platform, wherein gene clusters are cloned from hard-to-culture fungi, refactored, and optimized to express in Saccharomyces cerevisiae , a traditional 'cell factory' for pharmaceutical production due to its simple growth requirements and rapid proliferation [ 11 ]. The compact genomes of Ascomycota fungi (30–40 Mb) [ 12 ] make full genome sequencing and assembly both affordable and feasible, as highlighted by the recent surge of fungal genome submissions to databases like GenBank, and we have completed telomere-to-telomere assemblies, including mitochondrial genomes, for two Ascomycota fungi for under $ 1000 each. [13, and this study]. While some fungal genome sequences are high-quality, telomere-to-telomere assemblies or contain some complete chromosomes – a likely requirement for effective genome mining - many rely solely on short-read technology and are thus more fragmented. The impact of this fragmentation on gene and biosynthetic gene cluster prediction accuracy remains unclear. Despite the opportunities that have arose from technological advancements, there remains challenges as the bioinformatics analyses employed to identify functionally relevant fungal genes lack standardization and entail inherent complexity, often utilizing homology-based searches of biosynthetic gene cluster databases, likely biasing against discovery of completely novel clusters [ 10 ]. Fungi boast higher gene densities relative to plants and animals [ 14 ], with variation of gene sets being observed, even between closely related strains. This exacerbates the likelihood of false positive and negative discovery rates at the bioinformatics stage, especially given the intrinsic variance that can occur from differing genome assembly pipelines (sequencing technologies, read pre-processing strategies, assembler algorithm usage, polishing methods) and gene prediction approaches (e.g. ab-initio , homology-based, or RNA-seq guided). Given the costs and low throughput of designing, cloning, and expressing genes in heterologous hosts [ 11 ], bioinformatics tools that confidently prioritize candidate genes are essential. There is a need for simple methods that can accurately identify strain-specific, species-wide, or genus-wide genes across diverse fungal genomes, achieving high confidence despite inherent genomic error rates. To address this need, we present the "two-by-two" approach, which compares gene sets from two strains of the same species with those from two strains of different species or families within a fungal order. Self-clustering orthologs between strains of the same species provide higher confidence in identifying species-specific proteins and help reduce noise from low-quality genome assemblies and gene prediction errors in comparison to comparing species using only a single representative strain. We conducted a proof-of-concept study on Hypocreales fungi, an order with several well-studied species and multiple genomes of varying quality, including some telomere-length assemblies, available in GenBank. Notable members of Hypocreales include Trichoderma spp., widely used in agriculture as biocontrol agents against plant pathogens [ 15 ]; Cordyceps spp., entomopathogens valued in traditional medicine, with compounds under study for immunomodulatory and anticancer effects [ 16 ]; Beauveria bassiana , a common pest management agent [ 17 ]; and Metarhizium spp., also used in pest control, with conidia that have been demonstrated to be larvicidal against disease-vectoring mosquitoes [ 19 ] and shown to produce compounds with immunomodulatory [ 20 ] and anticancer [ 21 ] potential. Many genes involved in producing bioactive compounds in these fungi are well-characterized, allowing effective benchmarking of our approach. Additionally, the diverse ecological niches occupied by these closely related fungi enable assessment of the hits by plausibility. The test group includes five closely related species from Cordycipitaceae , two distantly related species from Clavicipitaceae , and one from Hypocreaceae , allowing evaluation of the approach in distinguishing unique genes across varying levels of relatedness. As only one genome was available for the most widely used entomopathogen Cordyceps javanica , we assembled a full telomere length genome, marking the third entomopathogenic fungus with a complete chromosome assembly. Using our two-by-two approach, we identified two novel proteins in Metarhizium brunneum : a functional serpin-like protein with homology to Drosophila melanogaster serpin 42Dd, an immune modulating protein, and a fungal Tc toxin complex with structural homology to bacterial Tc toxin complexes. This is the first report of a Tc toxin in fungi and we describe the first functional myco-serpin. Our findings provide a valuable reference for genome mining within the Hypocreales order and demonstrate that this analysis method can be applied to other fungal orders or organisms with high gene densities and significant interspecies gene variation, where potentially useful but under-characterized gene products are present. Results Cordyceps javanica genome assembly and genome attributes of species used in analyses A commercial strain of C. javanica was subjected to genome sequencing and assembly. Seven chromosomes were assembled telomere to telomere (Fig. 1 a), consistent with the chromosome counts of the entomopathogens Cordyceps militaris and Metarhizium brunneum , the genomes of which have previously been assembled to full telomere length [ 13 , 22 ]. In all three species, chromosome 1 was markedly larger than the other chromosomes. In addition, a circular mitogenome 34,146 bp in size was also assembled (Fig. 1 b). Identified mitochondrial genes include; cox 1–3, nad 1–6 and nad 4L, cob , atp 6, atp 8, atp 9, rnl and rns , mirroring the mitochondrial gene composition found in M. brunneum ARSEF 4556 [ 13 ]. A total of 27 tRNA genes were detected in the mitogenome sequence in contrast to the 25 tRNA genes detected in the M. brunneum genome [ 13 ]. The mitochondrial genome was also found to contain four GIY-YIG and two LAGLIDADG intronic homing endonuclease genes, endonucleases commonly found in fungal mitochondrial DNA [ 23 ]. Genomes were chosen from the Hypocreales families Cordycipitaceae , Clavicipitaceae , and Hypocreaceae , utilizing criteria such as genome quality as assessed by BUSCO score and assembly N50, giving preference to assemblies that were telomere length (if available). Including the assembled C.javanica genome, a total of 16 genomes comprising two strains from each species within three families in the order Hypocreales were subjected to orthologous protein and biosynthetic gene cluster analyses (table 1). Two-by-two biosynthetic gene cluster analysis of Hypocreales The two-by-two approach used two strains from each species to perform gene cluster and orthogonal protein analyses against other species in the group (Fig. 2 ). Biosynthetic gene cluster analyses of these strains revealed various gene clusters that were common between the three families analyzed. M. brunneum exhibited the highest number of predicted biosynthetic gene clusters (BGCs), followed by B. bassiana , Cordyceps cateniannulata , and C. javanica (Fig. 3 .a). Approximately one-third to one-quarter of the predicted gene clusters for each species demonstrated matches to known BGCs. Out of the 64 BGCs that had hits to known BGC clusters, 43 (67.2%) were unique to a single species within the Hypocreales fungi analyzed. The most prevalent known BGC cluster across all species of Hypocreales was associated with choline biosynthesis (Fig. 3 .b), a metabolite essential for fungal growth [ 24 ]. The siderophore metachelin C and antimicrobial poly-amino acid ε-poly-L-lysine were also present in most fungal species analyzed (Fig. 3 .b.), and are known to be compounds commonly produced by fungi [ 25 – 28 ]. Interestingly, a lower scoring hit was observed for the gene cluster associated with the synthesis of the squalene-synthesis inhibiting compound squalestatin S1 within the Cordycipitaceae and Hypocreaceae families, which was absent from the genomes of Clavicipitaceae species [ 29 – 30 ]. The pathway synthesizing the steroid clavaric acid was also absent from Clavicipitaceae as well as not being detected in the genome of C. javanica [ 31 ]. Hits to the gene cluster for fumosorinone synthesis, a compound found to inhibit protein tyrosine phosphatase 1B, a major negative regulator of the insulin signaling pathway, were detected in both species of Cordyceps fumosorosea from which the compound was first identified. Interestingly, we also detected a high homology hit in both C. cateniannulata genomes analyzed, to our knowledge, the first time this gene cluster has been reported in the species. The gene cluster for beauvericin, a cyclic hexadepsipeptide mycotoxin that has insecticidal, antimicrobial, antiviral and cytotoxic activities [ 32 ], was detected in all genomes of species within Cordycipitaceae (with a high percent score in Beauveria species and lower percentage hit to Cordyceps species), but was absent from the genomes of C.javanica . The BGC for the iron-binding siderophore epichloenin A [ 33 ] was detectable in both genomes of C.javania and C.cateniannulata , but only present in one genome of Epichloe festucae . Gene clusters with incomplete homology to the neuritogenic polyketide Shimalactone A/B gene cluster [ 34 ] were present in all Cordyceps species except C.militaris . The beauveriolide compounds were present in Cordyceps and Beauveria as previously documented [ 35 ]. Gene clusters that were uniquely found in two strains of a single species and were known to be unique from that species (or at least absent from the other species analyzed) include; clusters for swainsonine, destruxin A and helvolic acid in M. brunneum , clusters for oosporein and tenellin in B. bassiana , clusters for melinacidin IV in Trichoderma reesei , and ergovaline in Epichloe festucae . This demonstrates the ability of the two-by-two approach to better and more confidently predict true unique BGCs amongst a group of closely related fungi. Some predicted clusters had high percentage identity hits to known clusters, but were detected in only one of the two strains analyzed. These include clusters for; (2 Z ,4 E ,6 E ,10 E )-9-hydroxydodeca-2,4,6,10-tetraenoic acid/(2 E ,4 E ,6 E ,10 E )-9-hydroxydodeca-2,4,6,10-tetraenoic acid (BAA/BAB), serinocyclin A/serinocyclin B and fusarin only detected in M. brunneum 4556, epichloenin A only present in E. festucae Fl1, and clavaric acid only present in T. reesei QM6a. It is not clear whether these differences are due to a genuine gene variation between the two strains, or whether they are present in the genome of the second strain but not predicted due to sequencing and/or assembly issues. It is worth noting that in the case of M. brunneum , the genome of 4556 is telomere length and was assembled using hybrid sequencing technology, whilst the 3297 genome was assembled as part of pioneering efforts to utilize massively parallel sequencing technologies on fungi for the first time (see dates, BUSCO scores and contig information in table 1). Two-by-two analyses of orthogonal proteins To identify unique proteins in each species, orthologous protein analysis was performed with OrthoVenn3 using the OrthoFinder algorithm and using the two-by-two approach to identify strain self-clusters that were absent from other species (Fig. 4 ). A total of 3891 clusters were seen to contain orthologous proteins from the 16 strains comprising 8 species that were analyzed, and this represents the core genes for the group shared across all the species. The highest number of species self-clusters was observed between the two strains of M. brunneum analyzed (1269 clusters), followed by the two strains of T. reesei (847 clusters). B. bassiana formed 559 clusters, C. militaris 383 clusters, C. cateniannulata 330 clusters, E. festucae 273 clusters, C. javanica 236 clusters and C. fumosorosea 198 clusters (supplementary file 1). Singlet proteins that did not form a cluster with any other proteins ranged in number for each species from 1411 for C. javanica strain IJ2G to 56 for M. brunneum ARSEF 3297 with an average of around 250 proteins across all 16 strains analyzed (supplementary file 2). Clusters that were found to form uniquely within a single strain included; 21 clusters for B. bassiana JEF350, 17 clusters for C. javanica Apopka97, 11 clusters for C. cateniannulata MBC234, 9 clusters for M. brunneum ARSEF4556, 7 clusters for C. cateniannulata FRD24, 6 clusters for C. javanica IJ2G, 5 clusters for both C. fumosorosea grCorFumo1 and B. bassiana ERL836, 4 clusters for E. festucae Fl1, 3 clusters for E. festucae RoseCity, 2 clusters for C. fumosorosea ARSEF2679, 1 cluster for both C. militaris CM01 and T. reesei QM6a and no unique strain self-clusters were observed for C. militaris ATCC34164, M. brunneum ARSEF3296 or T. Reesei CBS999 (supplementary file 3). Of the species unique strain self-clusters, 18 clusters were found to contain genes that produce 10 previously characterized natural products that have been demonstrated to be unique to the species (table 2). These included: proteins responsible for synthesizing oosporein in B. bassiana , a metabolite required for fungal virulence that acts by evading host immunity to facilitate fungal multiplication in insects [ 36 ]; proteins that produce the compound cordycepin in C. militaris , an adenosine derivative shown to have antibiotic, anti-inflammatory, and anticancer activities [ 37 ]; the Metarhizium proteins Cuticle-degrading protease PR1 [ 38 ] and various subtilisin-like proteins known to be involved in cuticle and collagen degradation [ 39 , 40 ], a known protein involved in the formation of appressoria [ 41 ], and various proteins involved in the production of swainsonine [ 42 ], a cytotoxic fungal alkaloid and a potential cancer therapy drug. In the non-entomopathogenic fungal species, a protein known to take part in synthesis of sorbicillinoids was detected in T. reesei - an anti-fungal metabolite known to be produced by this species [ 43 ]. Two proteins known to be involved in the synthesis of the antifungal verlamelin were detected in E. festucae [ 44 ]. Genes for oosporein, sorbicillin, and swainsonine were also detected in the BGC analyses (Fig. 2 .c), however, it was encouraging to see that multiple proteins in this pathway were also detected as unique species self-clusters in the orthogonal protein analysis pipeline, validating the approach. BGC algorithms such as antiSMASH have previously been shown to be unable to detect the cordycepin Cns cluster [ 45 ], and we were also unable to detect it using the latest version of this tool but were able to detect 3 of the 4 genes in the cluster using the two-by-two orthologous protein analysis (table 2). Given that the two-by-two approach was able to detect this gene cluster that could not be detected by BGC identification algorithms, we mapped all the species self-cluster proteins for fungi with telomere length genome assemblies back to their respective genomes, and then compiled a list of potential gene clusters by mapping genes unique to each species that were within 5kb of each other in the genome (supplementary file 4). We present this list as a resource to the community that likely contains other novel BGCs for these species that could not be detected by antiSMASH. Overall, the two-by-two approach when used for individual proteome analysis effectively identified known distinct proteins for each species within the group, unaffected by the degree of relatedness or genetic distance among the species analyzed and, compared to the BGC analysis, was seemingly less affected by the quality of the genomes utilized. Identification of a fungal Tc toxin complex and functional myco-serpin Next, we assessed self-cluster hits that were found to contain proteins with high homology to previously characterized proteins that are involved in pathogenesis, antibiotic production, or interesting catabolic processes, and these have been listed in (table 3) Interestingly, we observed a previously undescribed protein in M. brunneum with homology to serpin 42Dd of the fruit fly, Drosophila melanogaster (cluster 13612, ORF G6M90_00g004700 of M. brunneum 4556). The protein was predicted to have a classical serpin structural domain (IPR023796) spanning from amino acids 13–365 of the 365 amino acid sequence. This protein was not present in any of the other entomopathogenic fungi, but a blast search revealed it to be present in multiple species of Trichophyton , a mammalian pathogen, as well as being present in multiple species of Aspergillus and Fusarium , which contain species that are opportunistic mammalian pathogens. A structural alignment revealed close structural homology between the two proteins (Fig. 5 . a). To determine the potential function of this gene in fungal virulence, a gene knockout line of this serpin, designated MBR_07878, was made. Topical infection of D. melanogaster revealed that the virulence of null mutants was significantly impaired (log-rank test, P < 0.01) compared to the wild-type strain (Fig. 5 . b), thus implicating the protein in the infection process. Another hit in the M. brunneum species self-cluster showed a hit to subunit C1 of the Tc toxin complex of Yersinia entomophaga (cluster 10481, ORF G6M90_00g045720 of M. brunneum 4556). Tc toxins complexes are virulence factors of many infectious and entomopathogenic bacteria [ 84 ]. The toxins are composed of three subunits that assemble to perforate a host membrane and translocate a toxic enzyme into the cell [ 84 ]. To date, no such toxin complex has been described in a fungal species. The Y. entomophaga Tc toxin subunit C1 ortholog found in Metarhizium mapped to chromosome 2 ( M. brunneum strain 45556- regions 5382531–5386727). This 1258 amino acid protein was found to contain an Insecticide toxin TcdB middle/C-terminal region domain (IPR022044). Interestingly, a downstream neighboring ( M. brunneum strain 45556- regions 5387051–5388929) gene was found to have homology to Y. entomophaga Tc toxin subunit B (ORF G6M90_00g045730 of M. brunneum 4556). Using AlphaFold3, we computationally docked the M. brunneum toxin subunits B and C (Fig. 3 .c). The predicted multimer showed good structural homology to a crystal structure of TcdB2-TcdC3 subunits of Photorhabdus luminsecens [PDB:4O9X, 85], with and RMSD of 2.247 Å. We then conducted a protein blast of the M. brunneum proteome using the sequence for Yersinia Entomophaga Tc toxin subunits A1 and A2. A hit was located for subunit A2 that mapped to chromosome 4 of M. brunneum 4556 (regions 1096054–1104757). This protein was found to be 2882 amino acids long and contained a Tc toxin complex TcA C-terminal TcB-binding domain (IPR040840) at positions 2440–2726, a Neuraminidase-like domain (IPR041079) at positions 1495–1655, and an ABC toxin N-terminal region domain (IPR046839) at positions 1344–1465 (ORF G6M90_00g069900 of M. brunneum 4556). A blast search of this protein revealed it to be present in multiple other Metarhizium species including; M. robertsii , M. anisopliae , M. humberi , M. guizhouense , and M. album . Previous studies in bacteria have demonstrated the A subunit alone is readily toxic but its effect is enhanced with the other two subunits docked [ 86 ]. We used AlphaFold3 to predict structures of the various subunits of the M. brunneum Tc toxin complex and input these smaller subunits into CombFold to generate the 16,253 amino acid toxin complex and compared it to the a Cryo-EM structure of Photorhabdus luminescens ABC holotoxin assembly embedded in a lipid nanodisc (Fig. 3 .d). Both toxin complexes have the distinct common architecture of Tc toxins. An A2 subunit Tc toxin gene knockout M. brunneum strain (MBR_09287) was made, which showed an increased survival rate for the null mutants when compared to wild-type when after topical challenge of D. melanogaster (Fig. 3 . e), thus implicating the protein in the infection process. Discussion We put forward a simple, novel, validated approach to determine the unique genes more accurately within a pre-selected group of fungi and is capable of distinguishing genes that are unique to a strain. We validated the method by selecting a group of fungi that have been subjected to decades of wet-lab experimentation, and confirmed that the approach could successfully detect genes and gene clusters that have previously been demonstrated to be unique to certain species within the group. We have compiled a list of orthologous proteins that uniquely self-cluster between two strains of the same species that can be used for bioprospecting useful novel genes and gene clusters from these species, and may also be used to subtract common fungal genes/gene clusters from analyses of species other than those included in our group. Given the gene richness of fungal genomes, declining sequencing costs, and improving genome assembly algorithms, we anticipate that comparative genomics, including our two-by-two approach, will continue to enhance fungal gene discovery. This method complements RNA-Seq by simplifying differential gene expression analysis and identifying species-specific genes regardless of expression. In this study, we have limited our search to truly unique genes between species by looking at strain self-clusters, however, the approach would also allow one to determine interesting genes shared by two very closely related species but potentially not the rest of the species within a test group (e.g. by looking at clusters formed between two paired strains from 2 separate species). The species selected for analyses will likely affect the outputs, however, genes/gene clusters that are truly unique to only one species of fungi will likely always form strain self-clusters, regardless of what other fungi are added to the group. We envision that the approach can be used to elucidate unique genes in organisms from other kingdoms that have genome architecture and species diversity comparable to fungi. Two M. brunneum self-clusters represent novel genes that have never been described before in fungi. We have identified the first functional myco-serpin that has significant homology to a known D. melanogaster immunomodulatory serpin. A major function of serpins in Drosophila is to confine immune reactions and prevent excessive activation [ 87 , 88 ]. Serpin 42Dd is a negative regulator of the Toll and melanization cascade pathways, blocking the serine proteases ModSP and Grass, with mutations in its gene leading to spontaneous melanization and constitutive activation of the Toll pathway [ 88 ]. A recent study has shown that Metarhizium robertsii produces an immune modulating protein during infection that can aslo block the Toll pathway [ 89 ]. The Metarhizium serpin may play a role in immune evasion, as previous studies have shown that a serpin-like compound in the Microsporidia, Nosema bombycis , can suppress insect host hemolymph melanization [ 90 ]. Parasitic insects have also been shown to use serpin-like proteins to dampen the melanization response against eggs they inject into other insects [ 91 ], and poxviruses produce secreted serpin-like proteins to dampen inflammatory responses against mammals [ 92 ]. Furthermore, a serpin-like protein from a symbiotic human gut bacteria has been shown to protect against exogenous proteolysis by gut proteins [ 93 ]. Moreover, the serpin shares homology with other previously undescribed fungal serpins in Fusarium , Aspergillus , Microsporum and Trichophytan , with the two former species being opportunistic human pathogens and the latter two being parasitic mammalian pathogens. It would be of great interest to assess the impact on infection of knocking out the gene from a mammalian parasite, as mammals are also known to utilize serpins to regulate the immune system. We cannot exclude the possibility of the serpin acting on a fungal serine protease, however, we observed no detrimental effects to fungal growth in the knockout strain. Prior to this study, the only other fungi to have been reported to have a serpin-like protein is the anaerobic fungus Piromyces sp., which contains a multi-domain protein that forms part of the cellulosome and contains a smaller serpin-like domain [ 94 ]. Finally, we describe, for the first time, a fungus that contains multiple subunits of a Tc toxin complex with significant structural homology to the extensively studied bacterial Tc toxin complexes [ 95 – 101 ]. Two of these subunits were found to be neighboring one another on the same chromosome, whilst the third subunit was found on a separate chromosome. Whether the serpin and oral toxin play a role in the fungi’s entomopathogenic lifestyle remains to be determined. The fungi most likely acquired the genes for this large protein complex from bacteria, a horizontal gene transfer process that has been well-documented [ 102 , 103 ]. The fact that the two subunits are located on chromosome 2, whilst the third is located on chromosome 4 may be attributable to a peculiar form of chromosomal evolution termed mesosynteny that has only been reported in Ascomycete fungi [ 104 ]. The serpin and Tc complex are upregulated in Metarhizium brunneum during infection of Myzus persicae , as revealed by a recent transcriptomic study of differentially expressed genes [in supplementary Fig. 1 of reference 105]. Further work should assess the functional activity of the fungal toxin complex in purified form to assess its efficacy in comparison to bacterial Tc toxin complexes. Since the fungal proteins were predicted from spliced genes, investigating the potential enhancements in the fungal protein upon expression would be intriguing. It has not escaped our notice that the splicing of fungal genes that have been acquired by horizontal transfer from bacteria may, in certain circumstances, lead to an enhanced version of the protein and would thus constitute a novel form of protein evolution. Methods Growth and DNA extraction of Cordyceps javanica C. javanica strain Apopka97 was commercially sourced (PREFERRAL WG, Biobest Group, Holland). 10mg of water dispersible granules were added to 10mL of distilled water and mixed by pulse vortex. Larvae of the greater wax moth, Galleria mellonella , were immersed in 10 ml of conidial suspension for 10 seconds and were placed on moist filter paper in petri dishes to encourage sporulation and fungal growth. Plates were incubated in the dark at 25°C and were inspected daily. After fungal growth was observed, mycelia were collected and grown on sabouraud dextrose agar for DNA extraction. A total of 100 mg of conidia was scraped off the plate under a laminar flow hood, and collected into a sterile 1.5 mL DNA LoBind tube (Eppendorf, Hamburg, Germany). Liquid nitrogen was added to the tube which was subsequently ground to a fine powder with a micro pestle. 1 mL of lysis buffer (2% CTAB, 100mM Tris-HCl, 20mM EDTA, 1.4M NaCl, 1% PVP, 80uL proteinase K, 5 uL RNAse A) was added to the powder which was subsequently incubated at 55°C for 5 minutes. 1 mL of phenol/chloroform/isoamylic alcohol (PCI) 25:24:1 was added and mixed by inversion. The tube was subsequently spun at 13,000 x G for 20 minutes in a benchtop centrifuge, the aqueous layer removed and placed in a new tube, and this this step was repeated with fresh PCI. After the second spin, 1 volume of isopropanol was added to the mixture and spun at 13,000 x G for 20 minutes to precipitate the DNA. The pellet was washed once with 70% ethanol and subsequently resuspended in 10mM Tris-HCl overnight. The DNA yield was measured by Nanodrop. Cordyceps javanica genome sequencing and assembly For long read sequencing, 1ug of DNA library was prepared using the Ligation Sequencing Kit V14 (SQK-LSK114, Oxford Nanopore Technologies). Sequencing was performed on a MinION sequencer using an r10.4.1 flowcell for 72 hours. Base calling was performed offline with ONT’s Guppy software pipeline version 6.1.2 with the using the super accuracy model for the r10.4.1 flowcell, enabling the --pt_scaling flag and setting the --trim_strategy flag to DNA. Adapters were trimmed using Porechop version 0.2.4 ( www.github.com/rrwick/Porechop ), setting the --adapter_threshold to 96, and the reads were subjected to 9 iterations (until no further changes were observed) of the split_on_adapter module of duplex-tools ( https://github.com/nanoporetech/duplex-tools ). Illumina DNA library preparation and sequencing were outsourced to Eurofins Genomics GmbH, Ebersberg, Germany. Illumina paired-end reads (2 × 150 bp) were produced using the ‘INVIEW Resequencing Sequencing of Fungi 50x Coverage’ package. Illumina reads were trimmed using Trimmomatic version 0.38, setting the HEADCROP configuration to 15 and the CROP configuration to 120. Short-read qualities were assessed with FastQC [ 106 ]. Long reads were corrected using FMLRC2 [ 107 ]. The trimmed and corrected long reads were further trimmed with Canu version v2.2 [ 108 ], using the -trim option, setting the genome size to 35 Mb, and disabling the stop on low coverage and stop on low quality features. Multiple genome assemblies were made using Flye version 2.9.1 [ 109 ] and adjusting the minimum overlap and read-error parameters iteratively until the sequences of all 7 chromosomes and the mitogenome were deduced. The genome was subsequently polished with 3 rounds of Racon (long reads) [ 110 ], followed by 2 rounds of Medaka (long reads), 2 rounds of Pilon (short reads)[ 111 ], a round of POLCA (short reads)[ 112 ], a round of FMLRC2 (short reads) and the telomere-to-telomere sequencing of each chromosome was confirmed by loading the genome assembly into Bandage [ 113 ] and BLAST searching for the fungal telomere sequence ‘TTAGGG’. Gene predictions and annotations Biosynthetic gene cluster predictions were performed using the fungal version of the antiSMASH web server (v7.1) [ 114 ], setting the detection strictness to ‘relaxed’ and activating all extra features. The presence of signal peptides was predicted using SignalP 5.0 [ 115 ]. Protein domain analyses was performed using InterProScan (v5.65-97.0). FunAnnotate (v1.8.15) was used to predict and annotate genes in the C.javanica genome, as well as the Hypocreales fungal genomes used in this study that lacked gene predictions in Genbank. BUSCO analyses were performed with BUSCO version 5.5.0 [ 116 ], using the hypocreales_odb10 lineage gene set. To determine the core genes shared across the Hypocreales species analyzed, comparison of orthologous gene clusters between the protein sets for each of the Hypocreales fungi were performed with a standalone version of OrthoVenn3 using the OrthoFinder algorithm [ 117 ]. AlphaFold3 was used to predict protein structure and dock multimers [ 118 ]. Overlaps of protein structure were performed using the align tool in PyMOL Version 3.0 [ 119 ]. In-silco structural prediction of the M. brunneum 4556 was Tc toxin complex was performed using CombFold [ 120 ], using various smaller AlphaFold3 docked multimer combinations as input. Gene deletions and fly survival assays Deletion of the serpin and Tc genes were conducted in M. brunneum by homologous replacement [ 89 ]. In brief, the 5’- and 3’-flanking regions of each gene were amplified by PCR using different primer pairs (supplementary file 5), and the purified products were cloned into the binary vector pDHt-bar (conferring resistance to ammonium glufosinate) [ 89 ]. Constructs were individually transformed into the Agrobacterium tumefaciens AGL1 strain, which was used to infect the wild-type spores of M. brunneum . The drug-resistance colonies were selected and verified by PCR analysis. At least, two independent mutant isolates were selected for survival assays against the females of D. melanogaster (3 days post eclosion). Two-week-old conidia of the wild-type and mutants were harvested from the potato dextrose agar, and suspended in 0.01% Tween-20. The spore suspensions were adjusted to 5 ×10 5 conidia/ml, and used for topical infection of female flies [ 89 ]. Flies treated with Tween 20 carrier were included as a mock control. There were more than 70 flies used for each treatment, and insect survivals were recorded every 12 hours. The difference between wild-type and mutant strains was examined by Kaplan-Meier analysis utilizing the log-rank test using GraphPad Prism version 10.1 (GraphPad software Inc., San Diego, CA). Data and materials availability Genomic data generated in this study has been deposited at the NCBI under PRJNA1069981. C. javanica illumina sequencing read data can be accessed at the NCBI Sequence Reads Archive using the accession number SRR31344820. C. javanica nanopore sequencing read data can be accessed at the NCBI SRA Sequence Reads Archive using the accession number SRR31344819. Sample information can be accessed at the NCBI BioSample repository using the accession number SAMN39632599. The genome assembly generated in this study can be accessed in NCBI’s GenBank database using the accession numbers CP146854 - CP146861. Gene and protein names and functional annotations (GO terms, InterPro, PFAM) are included in GenBank entries. Output files have been deposited in the following GitHub repository - https://github.com/zacksaud/Cordyceps-javanica-Assembly-Project . The following genomes and/or information on the genome assemblies were retrieved from NCBI’s GenBank database; Beauveria bassiana ERL836 (accession number: GCA_010099065.1), Beauveria bassiana JEF-350 (accession number: GCA_021365345.1), Cordyceps javanica IJ2G (accession number: GCA_006981975.1), Cordyceps fumosorosea ARSEF 2679 (accession number: GCA_001636725.1), Cordyceps fumosorosea grCorFumo1 (accession number: GCA_963580265.1), Cordyceps militaris ATCC 34164 (accession number: GCA_008080495.1), Cordyceps militaris CM01 (accession number: GCA_000225605.1), Cordyceps cateniannulata FRD 24 (accession number: GCA_028828415.1), Cordyceps cateniannulata MBC 234 (accession number: GCA_030411495.1), Metarhizium brunneum ARSEF 4556 (accession number: GCA_013426205.1), Metarhizium brunneum ARSEF 3297 (accession number: GCF_000814965.1), Epichloe festucae Fl1 (accession number: GCA_003814445.1), Epichloe festucae RoseCity (accession number: GCA_016859245.1), Trichoderma reesei CBS999.97 (accession number: GCA_016806755.1), Trichoderma reesei QM6a (accession number: GCA_002006585.1). Abbreviations ARSEF ARS Collection of Entomopathogenic Fungal Cultures BGC Biosynthetic Gene Cluster BUSCO Benchmarking Universal Single-Copy Orthologs DNA Deoxyribonucleic acid Mb Million base pairs NCBI National center for biotechnology information ORF Open reading frame tRNA Transfer ribonucleic acid Declarations Acknowledgments We thank Professor Stephen C. Graham for guidance on in-silico protein structural modelling very large complexes. Funding ZS was supported by a Wellcome Trust grant (226615/Z/22/Z) awarded to RJS. YL was supported by grants from the National Natural Science Foundation of China (No. 32021001 and 32230087) awarded to CW. Author contributions ZS, YL, MJW, IB, RJS, BJM, CW and TMB conceived of the study and participated in its design and coordination. ZS and MJW carried out the sequencing of C. javanica. ZS, BJM and IB performed the bioinformatics analyses. YL and CW produced the M. brunneum knockout strains and conducted the Drosophila survival assays. 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Accurate structure prediction of biomolecular interactions with AlphaFold 3. Nature. 2024 May 8. 10.1038/s41586-024-07487-w . Epub ahead of print. PMID: 38718835. The PyMOL Molecular. Graphics System, Version 3.0 Schrödinger, LLC. Shor B, Schneidman-Duhovny D. CombFold: predicting structures of large protein assemblies using a combinatorial assembly algorithm and AlphaFold2. Nat Methods. 2024;21:477–87. https://doi.org/10.1038/s41592-024-02174-0 . Tables Tables 1 to 3 are available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1.xlsx Table 1.Assembly and annotation statistics for Hypocreales fungi used in this study. Bold isolate names indicates that the assembly is the reference genome sequence for that species. An asterisk in front of the predicted proteins number indicates that the gene prediction was performed in this study. Table2.xlsx Table 2.Unique species self-clusters that were detected using the two-by-two approach and that have functions unique to the species that have previously been characterized. Table3.xlsx Table 3.Unique species self-clusters contained proteins with high homology to previously characterized proteins that are involved in pathogenesis, antibiotic production, or interesting catabolic processes. SupplementaryFile1.rar SupplementaryFile2.xlsx SupplementaryFile3.ods SupplementaryFile4.xlsx SupplementaryFile5.docx 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. 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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-6005389","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":431452990,"identity":"350cabd1-5ae5-487a-a429-72aabd432134","order_by":0,"name":"Zack Saud","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA0klEQVRIiWNgGAWjYJACCYYKEJXY8AFMM7ARo+UMWEvjjDNEa2FsA1EJjMRpkW8/Y3jz5zw7efP25MaGAwx28gwSaQl4tRicyTG2kNyWbDjnzEOQlmTDBom0A/i1MOSYSRhuO8A4QyKx/fEHBuYEBon0BvwO639jJpE454A9UAvIlnrCWhhuAG052HAgEarlMFALIYfdeFZs2XAsOXkGD8gvBscN23ieJRBwWPLGmz9q7GxnsKc/bDhQUS3Pz55mgN9haJYSFZGjYBSMglEwCggBAO4VSER8l8hRAAAAAElFTkSuQmCC","orcid":"","institution":"Cardiff University","correspondingAuthor":true,"prefix":"","firstName":"Zack","middleName":"","lastName":"Saud","suffix":""},{"id":431452991,"identity":"ec5e363a-91ff-4de7-ae99-c87327e7cd5e","order_by":1,"name":"Yujuan Luo","email":"","orcid":"","institution":"Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yujuan","middleName":"","lastName":"Luo","suffix":""},{"id":431452992,"identity":"d4b989ad-12bd-4e34-a569-04c55d0b52e9","order_by":2,"name":"Martyn J. 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Butt","email":"","orcid":"","institution":"Swansea University","correspondingAuthor":false,"prefix":"","firstName":"Tariq","middleName":"M.","lastName":"Butt","suffix":""}],"badges":[],"createdAt":"2025-02-11 08:38:42","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6005389/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6005389/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":78940983,"identity":"bc48388b-0561-42a9-ba0b-7541bb9bb72e","added_by":"auto","created_at":"2025-03-21 06:45:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":36314,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eCordyceps javanica \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003etelomere length genome assembly.\u003c/strong\u003e \u003cstrong\u003ea\u003c/strong\u003e. Chromosome size and gene density, color-coded as per the top-right legend. \u003cstrong\u003eb\u003c/strong\u003e. \u003cem\u003eC. javanica\u003c/em\u003e mitogenome map with mitochondrial gene families color-coded per the legend. The inner ring depicts GC content with respect to the 50% threshold ring.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/f81f0768172e203b9b69fbab.png"},{"id":78940987,"identity":"91b6dc47-688f-4c6c-bde5-f1aab9f953da","added_by":"auto","created_at":"2025-03-21 06:45:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":102363,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eOverview of the two-by-two approach.\u003c/strong\u003eInstruments, bioinformatics tools, and databases utilized in the two-by-two pipeline.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/2fa34f0056fb43e4c8918338.png"},{"id":78941003,"identity":"4fbae9ae-5c5d-43ac-b581-c70b2e93846f","added_by":"auto","created_at":"2025-03-21 06:45:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":48833,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTwo-by-two biosynthetic gene cluster analyses. a.\u003c/strong\u003e Biosynthetic gene clusters identified by AntiSMASH, showing the proportion of hits with homology to known gene clusters in the MIBiG database. \u003cstrong\u003eb.\u003c/strong\u003e Distribution of gene clusters across fungal species and strains, showing binned percentage identity scores to known clusters in the MIBiG database.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/4f80accbb8a67a63b4daf9b8.png"},{"id":78941418,"identity":"4e11a268-9fcc-489a-a566-ed29d338932e","added_by":"auto","created_at":"2025-03-21 06:53:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":25949,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTwo-by-two orthologous protein analysis of Hypocreales species.\u003c/strong\u003e Vertical bars represent the counts of unique self-clusters between single species strains (two-by-two approach) and clusters containing proteins from all analyzed strains representing pan-Hypocreales genes. Horizontal bars represent the total number of clusters for formed for each species.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/75937dc0121fff00551e8984.png"},{"id":78942074,"identity":"d4f4a812-106c-411c-8a7d-def1b2d0c561","added_by":"auto","created_at":"2025-03-21 07:01:21","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":306406,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of a novel fungal myco-serpin. a.\u003c/strong\u003e Structural homology between the \u003cem\u003eMetarhizium brunneum\u003c/em\u003e serpin and Spn44Dd (UniProt: Q7YTY6) of \u003cem\u003eDrosophila melanogaster\u003c/em\u003e, a negative regulator of the melanization and Toll pathways. \u003cstrong\u003eb.\u003c/strong\u003e Survival plot of \u003cem\u003eDrosophila\u003c/em\u003efemales infected with the \u003cem\u003eM. brummeum\u003c/em\u003e wild-type (WT) and serpin gene-knockout mutants. Panel b. mock control flies were treated with Tween 20. Survival differences between WT and individual mutants were determined by log-rank test: **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/9c0f93cf10a46d10e9f3a44c.png"},{"id":78941008,"identity":"cbbd841e-3780-4251-814c-ee23a45aaa8b","added_by":"auto","created_at":"2025-03-21 06:45:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":490335,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of a fungal Tc toxin complex. a.\u003c/strong\u003eStructural overlap of the \u003cem\u003eMetarhizium brunneum\u003c/em\u003e 4556 Alphafold3 docked YenC1 and YenB proteins with the TcdB2 and TccC3 toxin subunits of \u003cem\u003ePhotorhabdus luminescens\u003c/em\u003e (PDB:4O9X). \u003cstrong\u003eb.\u003c/strong\u003e Structure of \u003cem\u003ein-silico\u003c/em\u003e assembled \u003cem\u003eMetarhizium brunneum\u003c/em\u003e 4556 Tc toxin complex and a Cryo-EM structure of \u003cem\u003ePhotorhabdus luminescens\u003c/em\u003e ABC holotoxin assembly embedded in a lipid nanodisc (PDB:6SUF). The pentameric TcdA subunits are colored magenta, the TcdB subunit is colored yellow and the TcdC subunit is colored light blue. \u003cstrong\u003ec.\u003c/strong\u003e Survival plot of \u003cem\u003eDrosophila\u003c/em\u003efemales infected with the \u003cem\u003eM. brunneum\u003c/em\u003e wild-type and Tc toxin gene mutants. Panel c. mock control flies were treated with Tween 20. Survival differences between WT and individual mutants were determined by log-rank test: *\u003cem\u003eP \u003c/em\u003e\u0026lt; 0.05; **\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/f2fc3a93da8c1cdd8e76a4ef.png"},{"id":100370456,"identity":"1ebe6d22-9b66-4e4d-8385-e57663143ff0","added_by":"auto","created_at":"2026-01-16 08:05:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2000721,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/6243dea7-afe7-4efc-9a57-c2febcb762ec.pdf"},{"id":78940982,"identity":"822fb365-3990-427c-9845-7c6aa95dc1f0","added_by":"auto","created_at":"2025-03-21 06:45:19","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":14040,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003eAssembly and annotation statistics for Hypocreales fungi used in this study. Bold isolate names indicates that the assembly is the reference genome sequence for that species. An asterisk in front of the predicted proteins number indicates that the gene prediction was performed in this study.\u003c/p\u003e","description":"","filename":"Table1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/de7598768e38cad657e9ad1c.xlsx"},{"id":78940990,"identity":"04571e8f-55ce-4845-ab52-1a3af86b89bd","added_by":"auto","created_at":"2025-03-21 06:45:21","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":16757,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003eUnique species self-clusters that were detected using the two-by-two approach and that have functions unique to the species that have previously been characterized.\u003c/p\u003e","description":"","filename":"Table2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/c3e97b052aa4aca5f82f044f.xlsx"},{"id":78941014,"identity":"d5d1a128-7122-40d1-b496-ae3adf03b2f7","added_by":"auto","created_at":"2025-03-21 06:45:23","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":28672,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTable 3.\u003c/strong\u003eUnique species self-clusters contained proteins with high homology to previously characterized proteins that are involved in pathogenesis, antibiotic production, or interesting catabolic processes.\u003c/p\u003e","description":"","filename":"Table3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/52bafadbc6271a8811d76e6c.xlsx"},{"id":78940998,"identity":"89ab8808-080d-4c14-ba2d-0164b91c2a30","added_by":"auto","created_at":"2025-03-21 06:45:22","extension":"rar","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":2018048,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile1.rar","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/e38457bcc5d2f980bc576268.rar"},{"id":78940999,"identity":"427dfee7-43d3-4034-a149-d426eba3e740","added_by":"auto","created_at":"2025-03-21 06:45:22","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":479326,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/57635f0cb29dbfec934cf17c.xlsx"},{"id":78941421,"identity":"44f4b91e-3c83-40d2-8044-cd4e174a3c19","added_by":"auto","created_at":"2025-03-21 06:53:23","extension":"ods","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":10869,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile3.ods","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/b21729048723bd29a8b8f6fc.ods"},{"id":78940984,"identity":"9adddcba-0026-4279-a428-c1d74206513a","added_by":"auto","created_at":"2025-03-21 06:45:20","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":190101,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/2736327d9e5bb62e87a11761.xlsx"},{"id":78941404,"identity":"a39bad24-15b0-4f85-b42c-2276887db4bc","added_by":"auto","created_at":"2025-03-21 06:53:21","extension":"docx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":16494,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFile5.docx","url":"https://assets-eu.researchsquare.com/files/rs-6005389/v1/d320639296e735901d590513.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Discovery of a novel fungal Tc toxin complex and a functional myco- serpin via a unique two-by-two comparative genomics pipeline","fulltext":[{"header":"Background","content":"\u003cp\u003eFungi have played crucial roles in human industrial activities for millennia [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The discovery of Penicillin marked the beginning of extensive exploration into fungal metabolites [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] that led to the development of further classes of fungal-derived pharmaceuticals such as; cyclosporine [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], an immunosuppressive agent, lovastatin [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], a cholesterol-lowering drug, and various other antibiotics with differing modes of action, such as fusidic acid and cephalosporin [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Despite these achievements, the development of fungal therapeutics has lagged in comparison to other organisms for several reasons. Fungi exhibit intricate life cycles, encompassing the production of spores, mycelia, and fruiting bodies. Notably, the biosynthesis of bioactive compounds in fungi often occurs at specific developmental stages, with some metabolites being structurally complex and large. This inherent complexity can render their extraction and purification more cost-effective than chemical synthesis, as exemplified by the production of cyclosporine. Cultivating fungi and extracting metabolites often necessitates specialized techniques, with fewer than 5% of species having been successfully cultured to date [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Additionally, large-scale extraction of useful compounds demands substantial investment in tailored bioreactors and monitoring systems for each species, making plant-based natural product discovery more financially attractive to pharmaceutical companies.\u003c/p\u003e \u003cp\u003eFungi generally harbor more \"cryptic\" genes compared to other organisms, such as plants [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], that only activate in response to specific, often obscure, environmental cues or stressors, rendering them undetectable to transcriptomic, proteomic, and gene-knockout screening. This presents a significant opportunity for fungal natural product discovery through advanced comparative genomic approaches, as the presence of cryptic genes indicates that the biosynthetic potential of many cultivable fungi is likely much greater than currently recognized [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. With the advent of NGS and improved DNA synthesis technologies, novel approaches have been developed such as the \"HEx\" synthetic biology platform, wherein gene clusters are cloned from hard-to-culture fungi, refactored, and optimized to express in \u003cem\u003eSaccharomyces cerevisiae\u003c/em\u003e, a traditional 'cell factory' for pharmaceutical production due to its simple growth requirements and rapid proliferation [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The compact genomes of Ascomycota fungi (30\u0026ndash;40 Mb) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e] make full genome sequencing and assembly both affordable and feasible, as highlighted by the recent surge of fungal genome submissions to databases like GenBank, and we have completed telomere-to-telomere assemblies, including mitochondrial genomes, for two Ascomycota fungi for under \u003cspan\u003e$\u003c/span\u003e1000 each. [13, and this study]. While some fungal genome sequences are high-quality, telomere-to-telomere assemblies or contain some complete chromosomes \u0026ndash; a likely requirement for effective genome mining - many rely solely on short-read technology and are thus more fragmented. The impact of this fragmentation on gene and biosynthetic gene cluster prediction accuracy remains unclear.\u003c/p\u003e \u003cp\u003eDespite the opportunities that have arose from technological advancements, there remains challenges as the bioinformatics analyses employed to identify functionally relevant fungal genes lack standardization and entail inherent complexity, often utilizing homology-based searches of biosynthetic gene cluster databases, likely biasing against discovery of completely novel clusters [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Fungi boast higher gene densities relative to plants and animals [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], with variation of gene sets being observed, even between closely related strains. This exacerbates the likelihood of false positive and negative discovery rates at the bioinformatics stage, especially given the intrinsic variance that can occur from differing genome assembly pipelines (sequencing technologies, read pre-processing strategies, assembler algorithm usage, polishing methods) and gene prediction approaches (e.g. \u003cem\u003eab-initio\u003c/em\u003e, homology-based, or RNA-seq guided). Given the costs and low throughput of designing, cloning, and expressing genes in heterologous hosts [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], bioinformatics tools that confidently prioritize candidate genes are essential. There is a need for simple methods that can accurately identify strain-specific, species-wide, or genus-wide genes across diverse fungal genomes, achieving high confidence despite inherent genomic error rates. To address this need, we present the \"two-by-two\" approach, which compares gene sets from two strains of the same species with those from two strains of different species or families within a fungal order. Self-clustering orthologs between strains of the same species provide higher confidence in identifying species-specific proteins and help reduce noise from low-quality genome assemblies and gene prediction errors in comparison to comparing species using only a single representative strain.\u003c/p\u003e \u003cp\u003eWe conducted a proof-of-concept study on Hypocreales fungi, an order with several well-studied species and multiple genomes of varying quality, including some telomere-length assemblies, available in GenBank. Notable members of Hypocreales include \u003cem\u003eTrichoderma\u003c/em\u003e spp., widely used in agriculture as biocontrol agents against plant pathogens [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]; \u003cem\u003eCordyceps\u003c/em\u003e spp., entomopathogens valued in traditional medicine, with compounds under study for immunomodulatory and anticancer effects [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]; \u003cem\u003eBeauveria bassiana\u003c/em\u003e, a common pest management agent [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]; and \u003cem\u003eMetarhizium\u003c/em\u003e spp., also used in pest control, with conidia that have been demonstrated to be larvicidal against disease-vectoring mosquitoes [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and shown to produce compounds with immunomodulatory [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] and anticancer [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] potential. Many genes involved in producing bioactive compounds in these fungi are well-characterized, allowing effective benchmarking of our approach. Additionally, the diverse ecological niches occupied by these closely related fungi enable assessment of the hits by plausibility. The test group includes five closely related species from \u003cem\u003eCordycipitaceae\u003c/em\u003e, two distantly related species from \u003cem\u003eClavicipitaceae\u003c/em\u003e, and one from \u003cem\u003eHypocreaceae\u003c/em\u003e, allowing evaluation of the approach in distinguishing unique genes across varying levels of relatedness. As only one genome was available for the most widely used entomopathogen \u003cem\u003eCordyceps javanica\u003c/em\u003e, we assembled a full telomere length genome, marking the third entomopathogenic fungus with a complete chromosome assembly.\u003c/p\u003e \u003cp\u003eUsing our two-by-two approach, we identified two novel proteins in \u003cem\u003eMetarhizium brunneum\u003c/em\u003e: a functional serpin-like protein with homology to Drosophila melanogaster serpin 42Dd, an immune modulating protein, and a fungal Tc toxin complex with structural homology to bacterial Tc toxin complexes. This is the first report of a Tc toxin in fungi and we describe the first functional myco-serpin. Our findings provide a valuable reference for genome mining within the Hypocreales order and demonstrate that this analysis method can be applied to other fungal orders or organisms with high gene densities and significant interspecies gene variation, where potentially useful but under-characterized gene products are present.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cb\u003eCordyceps javanica\u003c/b\u003e \u003cb\u003egenome assembly and genome attributes of species used in analyses\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA commercial strain of \u003cem\u003eC. javanica\u003c/em\u003e was subjected to genome sequencing and assembly. Seven chromosomes were assembled telomere to telomere (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea), consistent with the chromosome counts of the entomopathogens \u003cem\u003eCordyceps militaris\u003c/em\u003e and \u003cem\u003eMetarhizium brunneum\u003c/em\u003e, the genomes of which have previously been assembled to full telomere length [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn all three species, chromosome 1 was markedly larger than the other chromosomes. In addition, a circular mitogenome 34,146 bp in size was also assembled (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb). Identified mitochondrial genes include; \u003cem\u003ecox\u003c/em\u003e1\u0026ndash;3, \u003cem\u003enad\u003c/em\u003e1\u0026ndash;6 and \u003cem\u003enad\u003c/em\u003e4L, \u003cem\u003ecob\u003c/em\u003e, \u003cem\u003eatp\u003c/em\u003e6, \u003cem\u003eatp\u003c/em\u003e8, \u003cem\u003eatp\u003c/em\u003e9, \u003cem\u003ernl\u003c/em\u003e and \u003cem\u003erns\u003c/em\u003e, mirroring the mitochondrial gene composition found in \u003cem\u003eM. brunneum\u003c/em\u003e ARSEF 4556 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. A total of 27 tRNA genes were detected in the mitogenome sequence in contrast to the 25 tRNA genes detected in the \u003cem\u003eM. brunneum\u003c/em\u003e genome [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The mitochondrial genome was also found to contain four GIY-YIG and two LAGLIDADG intronic homing endonuclease genes, endonucleases commonly found in fungal mitochondrial DNA [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eGenomes were chosen from the Hypocreales families \u003cem\u003eCordycipitaceae\u003c/em\u003e, \u003cem\u003eClavicipitaceae\u003c/em\u003e, and \u003cem\u003eHypocreaceae\u003c/em\u003e, utilizing criteria such as genome quality as assessed by BUSCO score and assembly N50, giving preference to assemblies that were telomere length (if available).\u003c/p\u003e \u003cp\u003eIncluding the assembled \u003cem\u003eC.javanica\u003c/em\u003e genome, a total of 16 genomes comprising two strains from each species within three families in the order Hypocreales were subjected to orthologous protein and biosynthetic gene cluster analyses (table 1).\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eTwo-by-two biosynthetic gene cluster analysis of Hypocreales\u003c/h2\u003e \u003cp\u003eThe two-by-two approach used two strains from each species to perform gene cluster and orthogonal protein analyses against other species in the group (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBiosynthetic gene cluster analyses of these strains revealed various gene clusters that were common between the three families analyzed. \u003cem\u003eM. brunneum\u003c/em\u003e exhibited the highest number of predicted biosynthetic gene clusters (BGCs), followed by \u003cem\u003eB. bassiana\u003c/em\u003e, \u003cem\u003eCordyceps cateniannulata\u003c/em\u003e, and \u003cem\u003eC. javanica\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.a). Approximately one-third to one-quarter of the predicted gene clusters for each species demonstrated matches to known BGCs. Out of the 64 BGCs that had hits to known BGC clusters, 43 (67.2%) were unique to a single species within the Hypocreales fungi analyzed. The most prevalent known BGC cluster across all species of Hypocreales was associated with choline biosynthesis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.b), a metabolite essential for fungal growth [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The siderophore metachelin C and antimicrobial poly-amino acid ε-poly-L-lysine were also present in most fungal species analyzed (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.b.), and are known to be compounds commonly produced by fungi [\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eInterestingly, a lower scoring hit was observed for the gene cluster associated with the synthesis of the squalene-synthesis inhibiting compound squalestatin S1 within the \u003cem\u003eCordycipitaceae\u003c/em\u003e and \u003cem\u003eHypocreaceae\u003c/em\u003e families, which was absent from the genomes of \u003cem\u003eClavicipitaceae\u003c/em\u003e species [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The pathway synthesizing the steroid clavaric acid was also absent from \u003cem\u003eClavicipitaceae\u003c/em\u003e as well as not being detected in the genome of \u003cem\u003eC. javanica\u003c/em\u003e [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Hits to the gene cluster for fumosorinone synthesis, a compound found to inhibit protein tyrosine phosphatase 1B, a major negative regulator of the insulin signaling pathway, were detected in both species of \u003cem\u003eCordyceps fumosorosea\u003c/em\u003e from which the compound was first identified. Interestingly, we also detected a high homology hit in both \u003cem\u003eC. cateniannulata\u003c/em\u003e genomes analyzed, to our knowledge, the first time this gene cluster has been reported in the species. The gene cluster for beauvericin, a cyclic hexadepsipeptide mycotoxin that has insecticidal, antimicrobial, antiviral and cytotoxic activities [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], was detected in all genomes of species within Cordycipitaceae (with a high percent score in Beauveria species and lower percentage hit to Cordyceps species), but was absent from the genomes of \u003cem\u003eC.javanica\u003c/em\u003e. The BGC for the iron-binding siderophore epichloenin A [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e] was detectable in both genomes of \u003cem\u003eC.javania\u003c/em\u003e and \u003cem\u003eC.cateniannulata\u003c/em\u003e, but only present in one genome of \u003cem\u003eEpichloe festucae\u003c/em\u003e. Gene clusters with incomplete homology to the neuritogenic polyketide Shimalactone A/B gene cluster [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] were present in all Cordyceps species except \u003cem\u003eC.militaris\u003c/em\u003e. The beauveriolide compounds were present in Cordyceps and Beauveria as previously documented [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Gene clusters that were uniquely found in two strains of a single species and were known to be unique from that species (or at least absent from the other species analyzed) include; clusters for swainsonine, destruxin A and helvolic acid in \u003cem\u003eM. brunneum\u003c/em\u003e, clusters for oosporein and tenellin in \u003cem\u003eB. bassiana\u003c/em\u003e, clusters for melinacidin IV in \u003cem\u003eTrichoderma reesei\u003c/em\u003e, and ergovaline in \u003cem\u003eEpichloe festucae\u003c/em\u003e. This demonstrates the ability of the two-by-two approach to better and more confidently predict true unique BGCs amongst a group of closely related fungi. Some predicted clusters had high percentage identity hits to known clusters, but were detected in only one of the two strains analyzed. These include clusters for; (2\u003cem\u003eZ\u003c/em\u003e,4\u003cem\u003eE\u003c/em\u003e,6\u003cem\u003eE\u003c/em\u003e,10\u003cem\u003eE\u003c/em\u003e)-9-hydroxydodeca-2,4,6,10-tetraenoic acid/(2\u003cem\u003eE\u003c/em\u003e,4\u003cem\u003eE\u003c/em\u003e,6\u003cem\u003eE\u003c/em\u003e,10\u003cem\u003eE\u003c/em\u003e)-9-hydroxydodeca-2,4,6,10-tetraenoic acid (BAA/BAB), serinocyclin A/serinocyclin B and fusarin only detected in \u003cem\u003eM. brunneum\u003c/em\u003e 4556, epichloenin A only present in \u003cem\u003eE. festucae\u003c/em\u003e Fl1, and clavaric acid only present in \u003cem\u003eT. reesei\u003c/em\u003e QM6a. It is not clear whether these differences are due to a genuine gene variation between the two strains, or whether they are present in the genome of the second strain but not predicted due to sequencing and/or assembly issues. It is worth noting that in the case of \u003cem\u003eM. brunneum\u003c/em\u003e, the genome of 4556 is telomere length and was assembled using hybrid sequencing technology, whilst the 3297 genome was assembled as part of pioneering efforts to utilize massively parallel sequencing technologies on fungi for the first time (see dates, BUSCO scores and contig information in table 1).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTwo-by-two analyses of orthogonal proteins\u003c/h3\u003e\n\u003cp\u003eTo identify unique proteins in each species, orthologous protein analysis was performed with OrthoVenn3 using the OrthoFinder algorithm and using the two-by-two approach to identify strain self-clusters that were absent from other species (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA total of 3891 clusters were seen to contain orthologous proteins from the 16 strains comprising 8 species that were analyzed, and this represents the core genes for the group shared across all the species. The highest number of species self-clusters was observed between the two strains of \u003cem\u003eM. brunneum\u003c/em\u003e analyzed (1269 clusters), followed by the two strains of \u003cem\u003eT. reesei\u003c/em\u003e (847 clusters). \u003cem\u003eB. bassiana\u003c/em\u003e formed 559 clusters, \u003cem\u003eC. militaris\u003c/em\u003e 383 clusters, \u003cem\u003eC. cateniannulata\u003c/em\u003e 330 clusters, \u003cem\u003eE. festucae\u003c/em\u003e 273 clusters, \u003cem\u003eC. javanica\u003c/em\u003e 236 clusters and \u003cem\u003eC. fumosorosea\u003c/em\u003e 198 clusters (supplementary file 1). Singlet proteins that did not form a cluster with any other proteins ranged in number for each species from 1411 for C. javanica strain IJ2G to 56 for M. brunneum ARSEF 3297 with an average of around 250 proteins across all 16 strains analyzed (supplementary file 2). Clusters that were found to form uniquely within a single strain included; 21 clusters for \u003cem\u003eB. bassiana\u003c/em\u003e JEF350, 17 clusters for \u003cem\u003eC. javanica\u003c/em\u003e Apopka97, 11 clusters for \u003cem\u003eC. cateniannulata\u003c/em\u003e MBC234, 9 clusters for \u003cem\u003eM. brunneum\u003c/em\u003e ARSEF4556, 7 clusters for \u003cem\u003eC. cateniannulata\u003c/em\u003e FRD24, 6 clusters for \u003cem\u003eC. javanica\u003c/em\u003e IJ2G, 5 clusters for both \u003cem\u003eC. fumosorosea\u003c/em\u003e grCorFumo1 and \u003cem\u003eB. bassiana\u003c/em\u003e ERL836, 4 clusters for \u003cem\u003eE. festucae\u003c/em\u003e Fl1, 3 clusters for \u003cem\u003eE. festucae\u003c/em\u003e RoseCity, 2 clusters for \u003cem\u003eC. fumosorosea\u003c/em\u003e ARSEF2679, 1 cluster for both \u003cem\u003eC. militaris\u003c/em\u003e CM01 and \u003cem\u003eT. reesei\u003c/em\u003e QM6a and no unique strain self-clusters were observed for \u003cem\u003eC. militaris\u003c/em\u003e ATCC34164, \u003cem\u003eM. brunneum\u003c/em\u003e ARSEF3296 or \u003cem\u003eT. Reesei\u003c/em\u003e CBS999 (supplementary file 3).\u003c/p\u003e \u003cp\u003eOf the species unique strain self-clusters, 18 clusters were found to contain genes that produce 10 previously characterized natural products that have been demonstrated to be unique to the species (table 2). These included: proteins responsible for synthesizing oosporein in \u003cem\u003eB. bassiana\u003c/em\u003e, a metabolite required for fungal virulence that acts by evading host immunity to facilitate fungal multiplication in insects [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]; proteins that produce the compound cordycepin in \u003cem\u003eC. militaris\u003c/em\u003e, an adenosine derivative shown to have antibiotic, anti-inflammatory, and anticancer activities [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]; the Metarhizium proteins Cuticle-degrading protease PR1 [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] and various subtilisin-like proteins known to be involved in cuticle and collagen degradation [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e], a known protein involved in the formation of appressoria [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e], and various proteins involved in the production of swainsonine [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e], a cytotoxic fungal alkaloid and a potential cancer therapy drug. In the non-entomopathogenic fungal species, a protein known to take part in synthesis of sorbicillinoids was detected in \u003cem\u003eT. reesei\u003c/em\u003e- an anti-fungal metabolite known to be produced by this species [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Two proteins known to be involved in the synthesis of the antifungal verlamelin were detected in \u003cem\u003eE. festucae\u003c/em\u003e [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. Genes for oosporein, sorbicillin, and swainsonine were also detected in the BGC analyses (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.c), however, it was encouraging to see that multiple proteins in this pathway were also detected as unique species self-clusters in the orthogonal protein analysis pipeline, validating the approach.\u003c/p\u003e \u003cp\u003eBGC algorithms such as antiSMASH have previously been shown to be unable to detect the cordycepin \u003cem\u003eCns\u003c/em\u003e cluster [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e], and we were also unable to detect it using the latest version of this tool but were able to detect 3 of the 4 genes in the cluster using the two-by-two orthologous protein analysis (table 2). Given that the two-by-two approach was able to detect this gene cluster that could not be detected by BGC identification algorithms, we mapped all the species self-cluster proteins for fungi with telomere length genome assemblies back to their respective genomes, and then compiled a list of potential gene clusters by mapping genes unique to each species that were within 5kb of each other in the genome (supplementary file 4). We present this list as a resource to the community that likely contains other novel BGCs for these species that could not be detected by antiSMASH. Overall, the two-by-two approach when used for individual proteome analysis effectively identified known distinct proteins for each species within the group, unaffected by the degree of relatedness or genetic distance among the species analyzed and, compared to the BGC analysis, was seemingly less affected by the quality of the genomes utilized.\u003c/p\u003e\n\u003ch3\u003eIdentification of a fungal Tc toxin complex and functional myco-serpin\u003c/h3\u003e\n\u003cp\u003eNext, we assessed self-cluster hits that were found to contain proteins with high homology to previously characterized proteins that are involved in pathogenesis, antibiotic production, or interesting catabolic processes, and these have been listed in (table 3)\u003c/p\u003e \u003cp\u003eInterestingly, we observed a previously undescribed protein in \u003cem\u003eM. brunneum\u003c/em\u003e with homology to serpin 42Dd of the fruit fly, \u003cem\u003eDrosophila melanogaster\u003c/em\u003e (cluster 13612, ORF G6M90_00g004700 of \u003cem\u003eM. brunneum\u003c/em\u003e 4556). The protein was predicted to have a classical serpin structural domain (IPR023796) spanning from amino acids 13\u0026ndash;365 of the 365 amino acid sequence. This protein was not present in any of the other entomopathogenic fungi, but a blast search revealed it to be present in multiple species of \u003cem\u003eTrichophyton\u003c/em\u003e, a mammalian pathogen, as well as being present in multiple species of \u003cem\u003eAspergillus\u003c/em\u003e and \u003cem\u003eFusarium\u003c/em\u003e, which contain species that are opportunistic mammalian pathogens. A structural alignment revealed close structural homology between the two proteins (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. a). To determine the potential function of this gene in fungal virulence, a gene knockout line of this serpin, designated MBR_07878, was made. Topical infection of \u003cem\u003eD. melanogaster\u003c/em\u003e revealed that the virulence of null mutants was significantly impaired (log-rank test, P\u0026thinsp;\u0026lt;\u0026thinsp;0.01) compared to the wild-type strain (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. b), thus implicating the protein in the infection process.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAnother hit in the \u003cem\u003eM. brunneum\u003c/em\u003e species self-cluster showed a hit to subunit C1 of the Tc toxin complex of \u003cem\u003eYersinia entomophaga\u003c/em\u003e (cluster 10481, ORF G6M90_00g045720 of \u003cem\u003eM. brunneum\u003c/em\u003e 4556). Tc toxins complexes are virulence factors of many infectious and entomopathogenic bacteria [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. The toxins are composed of three subunits that assemble to perforate a host membrane and translocate a toxic enzyme into the cell [\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e]. To date, no such toxin complex has been described in a fungal species. The \u003cem\u003eY. entomophaga\u003c/em\u003e Tc toxin subunit C1 ortholog found in Metarhizium mapped to chromosome 2 (\u003cem\u003eM. brunneum\u003c/em\u003e strain 45556- regions 5382531\u0026ndash;5386727). This 1258 amino acid protein was found to contain an Insecticide toxin TcdB middle/C-terminal region domain (IPR022044). Interestingly, a downstream neighboring (\u003cem\u003eM. brunneum\u003c/em\u003e strain 45556- regions 5387051\u0026ndash;5388929) gene was found to have homology to \u003cem\u003eY. entomophaga\u003c/em\u003e Tc toxin subunit B (ORF G6M90_00g045730 of \u003cem\u003eM. brunneum\u003c/em\u003e 4556). Using AlphaFold3, we computationally docked the \u003cem\u003eM. brunneum\u003c/em\u003e toxin subunits B and C (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.c). The predicted multimer showed good structural homology to a crystal structure of TcdB2-TcdC3 subunits of \u003cem\u003ePhotorhabdus luminsecens\u003c/em\u003e [PDB:4O9X, 85], with and RMSD of 2.247 \u0026Aring;.\u003c/p\u003e \u003cp\u003eWe then conducted a protein blast of the \u003cem\u003eM. brunneum\u003c/em\u003e proteome using the sequence for \u003cem\u003eYersinia Entomophaga\u003c/em\u003e Tc toxin subunits A1 and A2. A hit was located for subunit A2 that mapped to chromosome 4 of \u003cem\u003eM. brunneum\u003c/em\u003e 4556 (regions 1096054\u0026ndash;1104757). This protein was found to be 2882 amino acids long and contained a Tc toxin complex TcA C-terminal TcB-binding domain (IPR040840) at positions 2440\u0026ndash;2726, a Neuraminidase-like domain (IPR041079) at positions 1495\u0026ndash;1655, and an ABC toxin N-terminal region domain (IPR046839) at positions 1344\u0026ndash;1465 (ORF G6M90_00g069900 of \u003cem\u003eM. brunneum\u003c/em\u003e 4556). A blast search of this protein revealed it to be present in multiple other \u003cem\u003eMetarhizium\u003c/em\u003e species including; \u003cem\u003eM. robertsii\u003c/em\u003e, \u003cem\u003eM. anisopliae\u003c/em\u003e, \u003cem\u003eM. humberi\u003c/em\u003e, \u003cem\u003eM. guizhouense\u003c/em\u003e, and \u003cem\u003eM. album\u003c/em\u003e. Previous studies in bacteria have demonstrated the A subunit alone is readily toxic but its effect is enhanced with the other two subunits docked [\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e]. We used AlphaFold3 to predict structures of the various subunits of the \u003cem\u003eM. brunneum\u003c/em\u003e Tc toxin complex and input these smaller subunits into CombFold to generate the 16,253 amino acid toxin complex and compared it to the a Cryo-EM structure of \u003cem\u003ePhotorhabdus luminescens\u003c/em\u003e ABC holotoxin assembly embedded in a lipid nanodisc (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.d). Both toxin complexes have the distinct common architecture of Tc toxins. An A2 subunit Tc toxin gene knockout \u003cem\u003eM. brunneum\u003c/em\u003e strain (MBR_09287) was made, which showed an increased survival rate for the null mutants when compared to wild-type when after topical challenge of \u003cem\u003eD. melanogaster\u003c/em\u003e (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. e), thus implicating the protein in the infection process.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eWe put forward a simple, novel, validated approach to determine the unique genes more accurately within a pre-selected group of fungi and is capable of distinguishing genes that are unique to a strain. We validated the method by selecting a group of fungi that have been subjected to decades of wet-lab experimentation, and confirmed that the approach could successfully detect genes and gene clusters that have previously been demonstrated to be unique to certain species within the group. We have compiled a list of orthologous proteins that uniquely self-cluster between two strains of the same species that can be used for bioprospecting useful novel genes and gene clusters from these species, and may also be used to subtract common fungal genes/gene clusters from analyses of species other than those included in our group. Given the gene richness of fungal genomes, declining sequencing costs, and improving genome assembly algorithms, we anticipate that comparative genomics, including our two-by-two approach, will continue to enhance fungal gene discovery. This method complements RNA-Seq by simplifying differential gene expression analysis and identifying species-specific genes regardless of expression. In this study, we have limited our search to truly unique genes between species by looking at strain self-clusters, however, the approach would also allow one to determine interesting genes shared by two very closely related species but potentially not the rest of the species within a test group (e.g. by looking at clusters formed between two paired strains from 2 separate species). The species selected for analyses will likely affect the outputs, however, genes/gene clusters that are truly unique to only one species of fungi will likely always form strain self-clusters, regardless of what other fungi are added to the group. We envision that the approach can be used to elucidate unique genes in organisms from other kingdoms that have genome architecture and species diversity comparable to fungi.\u003c/p\u003e \u003cp\u003eTwo \u003cem\u003eM. brunneum\u003c/em\u003e self-clusters represent novel genes that have never been described before in fungi. We have identified the first functional myco-serpin that has significant homology to a known \u003cem\u003eD. melanogaster\u003c/em\u003e immunomodulatory serpin. A major function of serpins in \u003cem\u003eDrosophila\u003c/em\u003e is to confine immune reactions and prevent excessive activation [\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e, \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. Serpin 42Dd is a negative regulator of the Toll and melanization cascade pathways, blocking the serine proteases ModSP and Grass, with mutations in its gene leading to spontaneous melanization and constitutive activation of the Toll pathway [\u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e88\u003c/span\u003e]. A recent study has shown that \u003cem\u003eMetarhizium robertsii\u003c/em\u003e produces an immune modulating protein during infection that can aslo block the Toll pathway [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. The Metarhizium serpin may play a role in immune evasion, as previous studies have shown that a serpin-like compound in the Microsporidia, \u003cem\u003eNosema bombycis\u003c/em\u003e, can suppress insect host hemolymph melanization [\u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e90\u003c/span\u003e]. Parasitic insects have also been shown to use serpin-like proteins to dampen the melanization response against eggs they inject into other insects [\u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e91\u003c/span\u003e], and poxviruses produce secreted serpin-like proteins to dampen inflammatory responses against mammals [\u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e92\u003c/span\u003e]. Furthermore, a serpin-like protein from a symbiotic human gut bacteria has been shown to protect against exogenous proteolysis by gut proteins [\u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e93\u003c/span\u003e]. Moreover, the serpin shares homology with other previously undescribed fungal serpins in \u003cem\u003eFusarium\u003c/em\u003e, \u003cem\u003eAspergillus\u003c/em\u003e, \u003cem\u003eMicrosporum\u003c/em\u003e and \u003cem\u003eTrichophytan\u003c/em\u003e, with the two former species being opportunistic human pathogens and the latter two being parasitic mammalian pathogens. It would be of great interest to assess the impact on infection of knocking out the gene from a mammalian parasite, as mammals are also known to utilize serpins to regulate the immune system. We cannot exclude the possibility of the serpin acting on a fungal serine protease, however, we observed no detrimental effects to fungal growth in the knockout strain. Prior to this study, the only other fungi to have been reported to have a serpin-like protein is the anaerobic fungus \u003cem\u003ePiromyces\u003c/em\u003e sp., which contains a multi-domain protein that forms part of the cellulosome and contains a smaller serpin-like domain [\u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e94\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFinally, we describe, for the first time, a fungus that contains multiple subunits of a Tc toxin complex with significant structural homology to the extensively studied bacterial Tc toxin complexes [\u003cspan additionalcitationids=\"CR96 CR97 CR98 CR99 CR100\" citationid=\"CR95\" class=\"CitationRef\"\u003e95\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e101\u003c/span\u003e]. Two of these subunits were found to be neighboring one another on the same chromosome, whilst the third subunit was found on a separate chromosome. Whether the serpin and oral toxin play a role in the fungi\u0026rsquo;s entomopathogenic lifestyle remains to be determined. The fungi most likely acquired the genes for this large protein complex from bacteria, a horizontal gene transfer process that has been well-documented [\u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e102\u003c/span\u003e, \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e103\u003c/span\u003e]. The fact that the two subunits are located on chromosome 2, whilst the third is located on chromosome 4 may be attributable to a peculiar form of chromosomal evolution termed mesosynteny that has only been reported in Ascomycete fungi [\u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e104\u003c/span\u003e]. The serpin and Tc complex are upregulated in \u003cem\u003eMetarhizium brunneum\u003c/em\u003e during infection of \u003cem\u003eMyzus persicae\u003c/em\u003e, as revealed by a recent transcriptomic study of differentially expressed genes [in supplementary Fig.\u0026nbsp;1 of reference 105]. Further work should assess the functional activity of the fungal toxin complex in purified form to assess its efficacy in comparison to bacterial Tc toxin complexes. Since the fungal proteins were predicted from spliced genes, investigating the potential enhancements in the fungal protein upon expression would be intriguing. It has not escaped our notice that the splicing of fungal genes that have been acquired by horizontal transfer from bacteria may, in certain circumstances, lead to an enhanced version of the protein and would thus constitute a novel form of protein evolution.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cb\u003eGrowth and DNA extraction of\u003c/b\u003e \u003cb\u003eCordyceps javanica\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003cem\u003eC. javanica\u003c/em\u003e strain Apopka97 was commercially sourced (PREFERRAL WG, Biobest Group, Holland). 10mg of water dispersible granules were added to 10mL of distilled water and mixed by pulse vortex. Larvae of the greater wax moth, \u003cem\u003eGalleria mellonella\u003c/em\u003e, were immersed in 10 ml of conidial suspension for 10 seconds and were placed on moist filter paper in petri dishes to encourage sporulation and fungal growth. Plates were incubated in the dark at 25\u0026deg;C and were inspected daily. After fungal growth was observed, mycelia were collected and grown on sabouraud dextrose agar for DNA extraction. A total of 100 mg of conidia was scraped off the plate under a laminar flow hood, and collected into a sterile 1.5 mL DNA LoBind tube (Eppendorf, Hamburg, Germany). Liquid nitrogen was added to the tube which was subsequently ground to a fine powder with a micro pestle. 1 mL of lysis buffer (2% CTAB, 100mM Tris-HCl, 20mM EDTA, 1.4M NaCl, 1% PVP, 80uL proteinase K, 5 uL RNAse A) was added to the powder which was subsequently incubated at 55\u0026deg;C for 5 minutes. 1 mL of phenol/chloroform/isoamylic alcohol (PCI) 25:24:1 was added and mixed by inversion. The tube was subsequently spun at 13,000 x G for 20 minutes in a benchtop centrifuge, the aqueous layer removed and placed in a new tube, and this this step was repeated with fresh PCI. After the second spin, 1 volume of isopropanol was added to the mixture and spun at 13,000 x G for 20 minutes to precipitate the DNA. The pellet was washed once with 70% ethanol and subsequently resuspended in 10mM Tris-HCl overnight. The DNA yield was measured by Nanodrop.\u003c/p\u003e \u003cp\u003e \u003cb\u003eCordyceps javanica\u003c/b\u003e \u003cb\u003egenome sequencing and assembly\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFor long read sequencing, 1ug of DNA library was prepared using the Ligation Sequencing Kit V14 (SQK-LSK114, Oxford Nanopore Technologies). Sequencing was performed on a MinION sequencer using an r10.4.1 flowcell for 72 hours. Base calling was performed offline with ONT\u0026rsquo;s Guppy software pipeline version 6.1.2 with the using the super accuracy model for the r10.4.1 flowcell, enabling the --pt_scaling flag and setting the --trim_strategy flag to DNA. Adapters were trimmed using Porechop version 0.2.4 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u003ca href=\"http://www.github.com/rrwick/Porechop\" target=\"_blank\"\u003ewww.github.com/rrwick/Porechop\u003c/a\u003e\u003c/span\u003e\u003cspan address=\"http://www.github.com/rrwick/Porechop\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), setting the --adapter_threshold to 96, and the reads were subjected to 9 iterations (until no further changes were observed) of the split_on_adapter module of duplex-tools (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/nanoporetech/duplex-tools\u003c/span\u003e\u003cspan address=\"https://github.com/nanoporetech/duplex-tools\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003cspan type=\"Underline\" class=\"Underline\" name=\"Emphasis\"\u003e).\u003c/span\u003e Illumina DNA library preparation and sequencing were outsourced to Eurofins Genomics GmbH, Ebersberg, Germany. Illumina paired-end reads (2 \u0026times; 150 bp) were produced using the \u0026lsquo;INVIEW Resequencing Sequencing of Fungi 50x Coverage\u0026rsquo; package. Illumina reads were trimmed using Trimmomatic version 0.38, setting the HEADCROP configuration to 15 and the CROP configuration to 120. Short-read qualities were assessed with FastQC [\u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e106\u003c/span\u003e]. Long reads were corrected using FMLRC2 [\u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e107\u003c/span\u003e]. The trimmed and corrected long reads were further trimmed with Canu version v2.2 [\u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e108\u003c/span\u003e], using the -trim option, setting the genome size to 35 Mb, and disabling the stop on low coverage and stop on low quality features. Multiple genome assemblies were made using Flye version 2.9.1 [\u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e109\u003c/span\u003e] and adjusting the minimum overlap and read-error parameters iteratively until the sequences of all 7 chromosomes and the mitogenome were deduced. The genome was subsequently polished with 3 rounds of Racon (long reads) [\u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e110\u003c/span\u003e], followed by 2 rounds of Medaka (long reads), 2 rounds of Pilon (short reads)[\u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e111\u003c/span\u003e], a round of POLCA (short reads)[\u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e112\u003c/span\u003e], a round of FMLRC2 (short reads) and the telomere-to-telomere sequencing of each chromosome was confirmed by loading the genome assembly into Bandage [\u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e113\u003c/span\u003e] and BLAST searching for the fungal telomere sequence \u0026lsquo;TTAGGG\u0026rsquo;.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGene predictions and annotations\u003c/h2\u003e \u003cp\u003eBiosynthetic gene cluster predictions were performed using the fungal version of the antiSMASH web server (v7.1) [\u003cspan citationid=\"CR114\" class=\"CitationRef\"\u003e114\u003c/span\u003e], setting the detection strictness to \u0026lsquo;relaxed\u0026rsquo; and activating all extra features. The presence of signal peptides was predicted using SignalP 5.0 [\u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e115\u003c/span\u003e]. Protein domain analyses was performed using InterProScan (v5.65-97.0). FunAnnotate (v1.8.15) was used to predict and annotate genes in the \u003cem\u003eC.javanica\u003c/em\u003e genome, as well as the Hypocreales fungal genomes used in this study that lacked gene predictions in Genbank. BUSCO analyses were performed with BUSCO version 5.5.0 [\u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e116\u003c/span\u003e], using the hypocreales_odb10 lineage gene set. To determine the core genes shared across the Hypocreales species analyzed, comparison of orthologous gene clusters between the protein sets for each of the Hypocreales fungi were performed with a standalone version of OrthoVenn3 using the OrthoFinder algorithm [\u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e117\u003c/span\u003e]. AlphaFold3 was used to predict protein structure and dock multimers [\u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e118\u003c/span\u003e]. Overlaps of protein structure were performed using the align tool in PyMOL Version 3.0 [\u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e119\u003c/span\u003e]. \u003cem\u003eIn-silco\u003c/em\u003e structural prediction of the \u003cem\u003eM. brunneum\u003c/em\u003e 4556 was Tc toxin complex was performed using CombFold [\u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e120\u003c/span\u003e], using various smaller AlphaFold3 docked multimer combinations as input.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eGene deletions and fly survival assays\u003c/h3\u003e\n\u003cp\u003eDeletion of the serpin and Tc genes were conducted in \u003cem\u003eM. brunneum\u003c/em\u003e by homologous replacement [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. In brief, the 5\u0026rsquo;- and 3\u0026rsquo;-flanking regions of each gene were amplified by PCR using different primer pairs (supplementary file 5), and the purified products were cloned into the binary vector pDHt-bar (conferring resistance to ammonium glufosinate) [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. Constructs were individually transformed into the \u003cem\u003eAgrobacterium tumefaciens\u003c/em\u003e AGL1 strain, which was used to infect the wild-type spores of \u003cem\u003eM. brunneum\u003c/em\u003e. The drug-resistance colonies were selected and verified by PCR analysis. At least, two independent mutant isolates were selected for survival assays against the females of \u003cem\u003eD. melanogaster\u003c/em\u003e (3 days post eclosion). Two-week-old conidia of the wild-type and mutants were harvested from the potato dextrose agar, and suspended in 0.01% Tween-20. The spore suspensions were adjusted to 5 \u0026times;10\u003csup\u003e5\u003c/sup\u003e conidia/ml, and used for topical infection of female flies [\u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e89\u003c/span\u003e]. Flies treated with Tween 20 carrier were included as a mock control. There were more than 70 flies used for each treatment, and insect survivals were recorded every 12 hours. The difference between wild-type and mutant strains was examined by Kaplan-Meier analysis utilizing the log-rank test using GraphPad Prism version 10.1 (GraphPad software Inc., San Diego, CA).\u003c/p\u003e\n\u003ch3\u003eData and materials availability\u003c/h3\u003e\n\u003cp\u003eGenomic data generated in this study has been deposited at the NCBI under PRJNA1069981. \u003cem\u003eC. javanica\u003c/em\u003e illumina sequencing read data can be accessed at the NCBI Sequence Reads Archive using the accession number SRR31344820. \u003cem\u003eC. javanica\u003c/em\u003e nanopore sequencing read data can be accessed at the NCBI SRA Sequence Reads Archive using the accession number SRR31344819. Sample information can be accessed at the NCBI BioSample repository using the accession number SAMN39632599. The genome assembly generated in this study can be accessed in NCBI\u0026rsquo;s GenBank database using the accession numbers CP146854 - CP146861. Gene and protein names and functional annotations (GO terms, InterPro, PFAM) are included in GenBank entries. Output files have been deposited in the following GitHub repository - \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://github.com/zacksaud/Cordyceps-javanica-Assembly-Project\u003c/span\u003e\u003cspan address=\"https://github.com/zacksaud/Cordyceps-javanica-Assembly-Project\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. The following genomes and/or information on the genome assemblies were retrieved from NCBI\u0026rsquo;s GenBank database; Beauveria bassiana ERL836 (accession number: GCA_010099065.1), \u003cem\u003eBeauveria bassiana\u003c/em\u003e JEF-350 (accession number: GCA_021365345.1), \u003cem\u003eCordyceps javanica\u003c/em\u003e IJ2G (accession number: GCA_006981975.1), \u003cem\u003eCordyceps fumosorosea\u003c/em\u003e ARSEF 2679 (accession number: GCA_001636725.1), \u003cem\u003eCordyceps fumosorosea\u003c/em\u003e grCorFumo1 (accession number: GCA_963580265.1), \u003cem\u003eCordyceps militaris\u003c/em\u003e ATCC 34164 (accession number: GCA_008080495.1), \u003cem\u003eCordyceps militaris\u003c/em\u003e CM01 (accession number: GCA_000225605.1), \u003cem\u003eCordyceps cateniannulata\u003c/em\u003e FRD 24 (accession number: GCA_028828415.1), \u003cem\u003eCordyceps cateniannulata\u003c/em\u003e MBC 234 (accession number: GCA_030411495.1), \u003cem\u003eMetarhizium brunneum\u003c/em\u003e ARSEF 4556 (accession number: GCA_013426205.1), \u003cem\u003eMetarhizium brunneum\u003c/em\u003e ARSEF 3297 (accession number: GCF_000814965.1), \u003cem\u003eEpichloe festucae\u003c/em\u003e Fl1 (accession number: GCA_003814445.1), \u003cem\u003eEpichloe festucae\u003c/em\u003e RoseCity (accession number: GCA_016859245.1), \u003cem\u003eTrichoderma reesei\u003c/em\u003e CBS999.97 (accession number: GCA_016806755.1), \u003cem\u003eTrichoderma reesei\u003c/em\u003e QM6a (accession number: GCA_002006585.1).\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eARSEF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eARS Collection of Entomopathogenic Fungal Cultures\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBGC\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBiosynthetic Gene Cluster\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eBUSCO\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eBenchmarking Universal Single-Copy Orthologs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eDNA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDeoxyribonucleic acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eMb\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMillion base pairs\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eNCBI\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational center for biotechnology information\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003eORF\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eOpen reading frame\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003e\u003cb\u003etRNA\u003c/b\u003e\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eTransfer ribonucleic acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Professor Stephen C. Graham for guidance on in-silico protein structural modelling very large complexes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZS was supported by a Wellcome Trust grant (226615/Z/22/Z) awarded to RJS. YL was supported by grants from the National Natural Science Foundation of China (No. 32021001 and 32230087) awarded to CW.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eZS, YL, MJW, IB, RJS, BJM, CW and TMB conceived of the study and participated in its design and coordination. ZS and MJW carried out the sequencing of C. javanica. ZS, BJM and IB performed the bioinformatics analyses. YL and CW produced the \u003cem\u003eM. brunneum\u003c/em\u003e knockout strains and conducted the Drosophila survival assays. ZS wrote the manuscript with input from all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo ethical approval was required for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare that they have no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLiu L, Wang J, Rosenberg D, Zhao H, Lengyel G, Nadel D. Fermented beverage and food storage in 13,000 y-old stone mortars at Raqefet Cave, Israel: Investigating Natufian ritual feasting. J Archaeol Science: Rep. 2018;21:783\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFleming A. On the antibacterial action of cultures of a penicillium, with special reference to their use in the isolation of B. influenzae. 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Nat Methods. 2024;21:477\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41592-024-02174-0\u003c/span\u003e\u003cspan address=\"10.1038/s41592-024-02174-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 3 are available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"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":"Bioinformatics, Fungi, Hypocreales, Infection, Serpin, Tc toxin, Biosynthetic Gene Cluster, Comparative Genomics","lastPublishedDoi":"10.21203/rs.3.rs-6005389/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6005389/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003cbr\u003e\nFungi have been a rich source of pharmaceuticals such as antibiotics, immunosuppressants, and cholesterol-lowering drugs; however, their therapeutic potential remains largely untapped due to difficulties in culturing and elucidating the genetic basis of beneficial traits. Fungi contain 'cryptic' genes that are expressed under certain, and often obscure, growth conditions and can produce complex compounds that are difficult to synthesize economically. Developments in genome sequencing and DNA-synthesis technologies offer new opportunities to produce such compounds using biotechnological techniques, however, accurately identifying useful and novel genes, a prerequisite for such approaches, remains challenging.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003cbr\u003e\nWe present a novel ‘two-by-two’ comparative genomics pipeline for comprehensive gene analysis of selected fungal groups, enabling more confident identification of unique genes across the analyzed species. The approach compares gene sets from two strains of the same species with those from two strains of different species or families within a fungal order. Self-clustering orthologs that are unique to strains from the same species provide higher confidence in identifying species-specific proteins and help reduce noise from low-quality genome assemblies and gene prediction errors. We validated our method on a well-studied group of fungi, discovering the first functional myco-serpin and an undescribed fungal Tc toxin complex. Using a gene knockout approach, we have implicated both proteins’ roles in the insect host infection process of this entomopathogenic fungal species.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eElucidating the genes underlying beneficial traits in fungi presents significant challenges, largely due to the unique and relatively complex aspects of their lifestyles. Our two-by-two approach offers broad potential for applications in fungal genome mining and bioprospecting as exemplified in this study by the discovery of the first fungal Tc toxin complex and a functional myco-serpin. We identified genes with high sequence identity to this serpin in other pathogenic fungal strains, including those known to infect humans. Furthermore, the two-by-two approach can be adapted to other organisms with genome architectures similar to fungi.\u003c/p\u003e","manuscriptTitle":"Discovery of a novel fungal Tc toxin complex and a functional myco- serpin via a unique two-by-two comparative genomics pipeline","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-03-21 06:45:13","doi":"10.21203/rs.3.rs-6005389/v1","editorialEvents":[{"type":"communityComments","content":0}],"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":"7aacc47a-4bf0-4758-97ab-392e5043aca8","owner":[],"postedDate":"March 21st, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-14T12:25:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-03-21 06:45:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6005389","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6005389","identity":"rs-6005389","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}