Transcriptional reprogramming in the entomopathogenic fungus Metarhizium brunneum and its aphid host Myzus persicae during the switch between saprophytic and parasitic lifestyles 

Transcriptional reprogramming in the entomopathogenic fungus Metarhizium brunneum and its aphid host Myzus persicae during the switch between saprophytic and parasitic lifestyles | 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 Transcriptional reprogramming in the entomopathogenic fungus Metarhizium brunneum and its aphid host Myzus persicae during the switch between saprophytic and parasitic lifestyles Victoria Reingold, Adi Faigenboim, Sabina Matveev, Sabrina Haviv, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4587553/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Oct, 2024 Read the published version in BMC Genomics → Version 1 posted 11 You are reading this latest preprint version Abstract Background The fungus Metarhizium brunneum has evolved a remarkable ability to switch between different lifestyles. It develops as a saprophyte, an endophyte establishing mutualistic relationships with plants, or a parasite, enabling its use for the control of insect pests such as the aphid Myzus persicae . We tested our hypothesis that switches between lifestyles must be accompanied by fundamental transcriptional reprogramming, reflecting adaptations to different environmental settings. Results We combined high throughput RNA sequencing of M. brunneum in vitro and at different stages of pathogenesis to validate the modulation of genes in the fungus and its host during early infection. In agreement with our hypothesis, we observed transcriptional reprogramming in M. brunneum following conidial attachment, germination on the cuticle, and early-stage growth within the host. This involved the upregulation of genes encoding degrading enzymes and gene clusters involved in synthesis of secondary metabolites that act as virulence factors. The transcriptional response of the aphid host included the upregulation of genes potentially involved in antifungal activity, but antifungal peptides were not induced. We also observed the induction of a host flightin gene, which may be involved in wing formation and flight muscle development. Conclusions The switch from saprophytic to parasitic development in M. brunneum is accompanied by fundamental transcriptional reprogramming during the early phases of infection. The aphid host responds to fungal infection with its own transcriptional reprogramming, reflecting its inability to express antifungal peptides but featuring the induction of genes involved in winged morphs that may enable offspring to avoid the contaminated environment. Mycopathogen Host-pathogen interaction Transcriptomic Live imaging Fungal infection Early infection Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 1. Background Fungi evolved more than 900 million years ago, but unprecedented radiation and diversification occurred ~ 480 million years ago due to interactions between fungi and terrestrial plants (Lutzoni et al., 2018 ). This created a wide range of lifestyles, including fungi that functional primarily as saprophytes and saprobes in the soil (necessary for nutrient recycling and soil health) as well as pathogens and parasites that leech nutrients from other organisms. The most fascinating are the widespread entomopathogenic fungi, which can proliferate as independent saprophytes, plant-associated endophytes, or pathogens infecting arthropod hosts, switching between lifestyles according to need (Vilcinskas 2019). These fungi are beneficial to plants and are therefore interesting both as model organisms and for their potential applications in agriculture (Fig. 1 ). Most entomopathogenic fungi represent the divisions Entomophthoromycota or Ascomycota, the latter including the widely-studied genus Metarhizium (Hypocreales: Clavicipitaceae). Furthermore, Metarhizium and Beauveria spp. are the most common fungi used as commercial microbial biopesticides (Um et al., 2018 ), reflecting the ease of mass production as saprophytic cultures (Jaronski, 2023 ; Loskutova and Fedotova, 2015 ; Mechnikov, 1879 ; Shah and Pell, 2003 ; Zimmermann et al., 1995 ). In nature, the fungal saprophytic lifestyle is characterized by growth on organic matter in the soil (St Leger and Wang, 2020 ) until a suitable host is encountered (Stone and Bidochka, 2020 ). This triggers a switch to parasitism, in which fungal conidia adhere to the host cuticle and germinate. The germ tube differentiates into an appressorium that penetrates the host integument, reaching the hemocoel and allowing proliferation within the host. When the host nutrient supply is exhausted, the fungus breaks through the cuticle, producing new propagules as conidia, which are passively disseminated and reach new environments and potential hosts (Gillespie et al., 2000 ). Depending on the environmental conditions, the new propagules may remain dormant or may switch back to the saprophytic lifestyle (Ment et al., 2010 ; Small and Bidochka, 2005 ; St. Leger, 2008 ). The lifestyle switches require the fungus to adapt and acquire different competences. As a pathogen, the fungus must produce enzymes that digest the host cuticle and allow the utilization of nutrients in the hemolymph (Gillespie et al., 2000 ; Lu and St. Leger, 2016 ; Vilcinskas, 2010 ), as well as proteins that enable the evasion of innate immunity (Chen et al., 2016 ). In contrast, cultivation in rich media enables the fungus to divert its resources to nutrient metabolism (Li et al., 2021 ; St Leger and Wang, 2020 ). Metarhizium can grow as a saprophyte or an endophyte in different plant roots in the rhizosphere (Ment et al., 2020a , 2020b ). It can acquire nutrients from the plant and, in turn, promote plant growth and systemic immunity to a broad range of pests and pathogens (Gupta et al., 2022 ; Vega et al., 2008 ). Indeed, Metarhizium may have evolved from a plant endophyte into an insect pathogen to gain new sources of nitrogen that can be traded with plants for carbohydrates (Stone and Bidochka, 2020 ). This adaptation necessitated genomic diversification to support the new physiological and metabolic functions, as well as the evolution of regulatory systems to control the switch between lifestyles in different environments (Barelli et al., 2016 ). We have previously reported intraspecific variation in terms of pathogenicity and secreted active metabolites in M. brunneum isolates and proposed epigenetic regulation as a means to control the switch between lifestyles (Reingold et al., 2022 , 2021 ). Here, we hypothesize that lifestyle switches require early gene expression to enable a rapid response to changing growth conditions. We therefore investigated transcriptome reprogramming during lifestyle shifting in M. brunneum , specifically the change from in vitro growth on complete medium (mimicking saprophytic nutrient acquisition) to parasitism in the model aphid host Myzus persicae . We used a combination of live imaging and host–fungus dual RNA sequencing (RNA-Seq) to analyze the rapid and flexible transcriptional response in conidia during lifestyle shifting and dormancy breaking, leading to early host responses with the potential for transgenerational priming. 2. Results 2.1 Patterns of fungal and host gene expression To understand the molecular basis of lifestyle shifts in M. brunneum isolate K (MbK), we collected conidia from a culture growing in complete medium (CM) and sequenced the transcriptome as a control. We also inoculated fresh CM to initiate saprophytic development (Fig. 2 A, top) and M. persicae adults to initiate pathogenic development (Fig. 2 A, bottom), allowing the comparative analysis of the saprophytic and parasitic fungal transcriptomes and the host response during pathogenesis. 2.1.1 Differential gene expression during fungal saprophytic development Fungal RNA-Seq data representing different stages of saprophytic development were evaluated by principal component analysis (PCA), revealing distinct variation along the axis of principal component (PC) 2 (Fig. 2 B). We identified 2925 differentially expressed genes (DEGs) differing at least in a single comparison, based on the fold change (FC) criteria log 2 FC > |2| and p adj < 0.001. Given a total M. brunneum gene number of 11,595, the DEGs accounted for 25% of all genes (Saud et al., 2021 ). Variation was observed between conidia (0 h) and germinated conidia (9 h, 912 DEGs), hyphae (24 h, 1790 DEGs) and mycelia (72 h, 1406 DEGs) (Fig. 2 C, top; DEGs summarized in Tables S1–S3). The entire set of DEGs formed 10 clusters (assigned letters A to J) based on expression patterns during saprophytic development (Fig. 3 A). Two groups of clusters showed highly similar expression profiles. The first group comprised clusters F, G and H, and represented genes upregulated during development (mainly expressed in the hyphae and mycelia, Fig. 3 A). The second group comprised clusters I and J, and represented genes downregulated during development (i.e., upregulated in the conidia control, Fig. 3 A). 2.1.2 Differential gene expression during fungal pathogenic development Given that the rate of disease progression varies widely in different aphids following simultaneous infection (Reingold et al., 2021 ), we monitored individual aphids by confocal microscopy and pooled those at similar stages of disease progression rather than specific times post-inoculation for the RNA-Seq samples (Fig. 2 A, bottom). PCA showed a clear separation between the saprophytic and parasitic lifestyles, with directional differences correlated to fungal development in each lifestyle (Fig. 2 B). Due to low variation between the penetration and germination stages, and between initial hemocoel colonization and massive colonization, these pairs of stages were combined for further analysis and are described as early infection and late infection, respectively (Fig. 2 B). Compared to the conidial control, pathogenic development showed a similar distribution of upregulated and downregulated genes. We identified 4818 DEGs differing at least in a single comparison (~ 41% of all genes) when using permissive criteria (log 2 FC > |1|, p adj < 0.05) because these samples contained only a small proportion of fungal reads. To address the bias caused by scarce fungal reads in the conidial adhesion samples compared to the conidial control (0 h), the threshold was set to > 0 FPKM. This resulted in 563 DEGs, most of which were upregulated during adhesion. We also identified 1864 and 4294 DEGs when comparing the conidial control to the early and late infection stages, respectively (Fig. 2 D). We also compared pathogenic development to the conidial control and germinated saprophytic conidia in order to identify genes involved in conidial dormancy breaking regardless of the subsequent lifestyle. The resulting 3889 DEGs (~ 33% of all genes) were used to construct a Venn diagram (p adj |1| for adhesion compared to the conidial control and log 2 FC > |2| for all other comparisons) (Fig. 3 B,C). The comparison revealed 1907 upregulated and 1982 downregulated genes in the parasitic and saprophytic germination (9 h) samples, respectively, compared to the conidial control (Fig. 3 B,C). We detected 1009 DEGs upregulated at all pathogenic stages (Fig. 3 B) and 989 that were downregulated (Fig. 3 C). Also 1549 genes were upregulated in proliferating fungi (Fig. 3 B) and 1779 were downregulated (Fig. 3 C) compared to the conidial stages. Validation of gene expression by real-time PCR was carried out on selected DEGs (Fig. S1A-B) 2.1.3 Differential gene expression in aphids during fungal developmental The aphid samples were classified as the uninfected negative control (NC), early infection (a combination of adhesion, germination and penetration), and late infection comprising initial and massive hemocoel colonization (Fig. 2 E). Among the 17,052 genes in the M. persicae genome, we detected only 154, 232 and 454 DEGs at the adhesion, early infection and late infection stages, respectively, compared to the NC (log2FC > |1|, p adj < 0.05). However, no genes were significantly upregulated in the infected aphids during the early infection stage and only 12 were upregulated during the adhesion stage. Reducing the statistical threshold did not yield significantly different results. We therefore analyzed our data using edgeR to obtain more uniform transcriptome results, yet the proportion of upregulated genes was still significantly higher in the NC aphids (Fig. 2 F). Using this analysis, we found 617, 639 and 1215 DEGs when comparing the NC to the adhesion, early infection and late infection stages, respectively (log 2 FC > |0.4|, FDR < 0.05; Fig. 2 F). For further analysis we combined all the early and late disease stages, and also conducted a separate comparison between the adhesion stage and NC aphids. The top-ranking DEGs at each disease stage compared to the NC are summarized in Tables S4–S6. Many common DEGs were observed during the early and late infection stages (Fig. 3 D,E). However, more than 80% of the genes upregulated during infection were uniquely expressed during late infection, whereas only a small fraction was upregulated uniquely during early infection (Fig. 3 D). Similarly, only 5% of the downregulated genes were uniquely downregulated during early infection (Fig. 3 E). Validation of gene expression by real-time PCR was carried out on selected DEGs (Fig. S1C-G). 2.2 Enriched pathways and ontologies in the fungus and host 2.2.1 Significant pathways and ontologies in fungal saprophytic development Significant conidial metabolic activity was observed in clusters B and IJ (combined based on pattern similarity), representing strongly expressed gene at the conidial stage (0 h) (Fig. 4A,B; Table S7). The enriched metabolic pathways included glycolysis and gluconeogenesis (spo00010) based on the upregulation of several alcohol dehydrogenases, galactose catabolism, oxidoreductase activity (GO:0055114) and fatty acid degradation (spo00071) (Fig. 4A,B). In these clusters, we observed the enrichment of RNA and DNA binding, together with regulatory elements of transcription (Fig. 4A,B; Table S7). Similar enrichment was also observed in cluster E, indicating upregulation in the conidia and mycelia (Table S7). On the other hand, enrichment in clusters C and FGH (combined based on pattern similarity) included ergosterol and fatty acid biosynthesis (Fig. 4C,D; Table S7). In these clusters, we observed significant enrichment of translation and ribosome biogenesis instead of transcription and transcriptional regulation. The biosynthesis of secondary metabolites was significantly enriched in all clusters with more than 50 genes (Table S7). 2.2.2 Significant pathways and ontologies in fungal pathogenic development The gene groups identified by Venn analysis (Fig. 3 B,C; Table S8) were used to find enriched pathways required for pathogenesis, and to eliminate genes related to saprophytic growth, by the exclusion of germinated conidia during saprophytic development. Similarly, we were able to recognize the common genes and pathways related to fungal proliferation regardless of the developmental lifestyle by excluding the adhesion stage. As expected, among the genes common to proliferating fungi, we observed the enrichment of cell cycle and mitosis pathways (spo04111, GO:0044732, GO:0031028), as well as secondary metabolism (spo01110), glycolysis (spo00010) and sugar metabolism (spo00520, spo00051) (Fig. 5 A; Table S8). RNA regulation was enriched in the conidial control compared to all pathogenic stages (GO: 0000981) (Table S8). Similarly, ribosome biogenesis and cytoplasmic translation were enriched at pathogenic stages and during saprophytic germination (Table S8). Pathways enriched during saprophytic germination included secondary metabolism, riboflavin synthesis (spo00740) and sugar metabolism. GO terms enriched during saprophytic germination included cytoplasmic translation (also found in all proliferating fungi) and aerobic respiration related to energy gain (GO:0009060) (Fig. 5 B; Table S8). On the other hand, early and late infection involved the enrichment of peptidase and oxidation-reduction activities (GO:0004252, GO:0055114) (Fig. 5 D-E, H-I; Table S8). These were not enriched during the adhesion stage, which included chromatin remodeling and ribosome biogenesis (GO:0031011, GO:0060303), as well as tryptophan and fatty acid metabolism (Fig. 5 C,G; Table S8). The early and late infection stages featured unique enriched metabolic pathways compared to the saprophytic stages. This included pentose and glucoronate metabolism (spo00040) at both stages and glyoxylate and dicarboxylate metabolism (spo00630) strongly enriched only at the late infection stage (Fig. 5 E,I; Table S8). DEGs common to all pathogenic stages were associated with GO terms such as peptidase activity (GO:0004252, GO:0008233) and catabolic processes (GO:0007039, GO:0009251), whereas the analysis of KEGG pathways revealed the weak enrichment of autophagy (spo04138) (Fig. 5 F; Table S8). 2.2.3 Enzymatic gene expression during fungal pathogenic development The transcriptomic response of the fungus largely depends on its environment. We found a large set of genes activated upon first encounter with the host, as early as the adhesion stage in the case of one unique chitinase (QLI73536.1) and two phospholipases (QLI71879.1, QLI74668.1) (Fig. 6 A). Some of the identified enzymes were constantly expressed, such as chitinase 18 (QLI68859.1) and a lipase (QLI66658.1), suggesting a general role in fungal development and hyphal elongation, whereas others were silenced (QLI74656.1) in comparison to dormant conidia (Fig. 6 A). A single lipase (QLI68060.1) was expressed only in the conidia during both dormancy and adhesion. The well-studied hydrophobin gene Mad1 (QLI72677.1) was constitutively expressed compared to dormant conidia (Fig. 6 A). Further analysis of all predicted proteases in the fungal genome resulted in three main phylogenetic groups: subtilisin Pr1 proteases (10 genes), trypsin Pr2 proteases (11 genes), and subtilisin PR1C proteases (6 genes) (Fig. 6 B). A single gene predicted to encode Pr1H (QLI67847.1) was separated from the Pr1 group and was constitutively expressed during pathogenic development together with the cuticle-degrading protease (QLI69644.1) and an extracellular subtilisin-like Pr1F (QLI66763.1) (Fig. 6 B). The earliest proteases induced by infection also included a trypsin-like serine protease (QLI70195.1, presumably Pr2) and a single Pr1 subtilisin (QLI172563.1) expressed only during the adhesion stage (Fig. 6 B). Another putative Pr1H (QLI65301.1) was constitutively expressed during fungal growth, with the highest expression during the conidial stages (0 h and adhesion). The well-known subtilisin Pr1A (QLI64437.1) was detected only during late pathogenic growth. The trypsin-like protease gene PnmB (QLI69436.1) was expressed during late fungal development in both the saprophytic and parasitic contexts. Few proteases were overexpressed during saprophytic growth, but exceptions included Pr1G (QLI71439.1) and an aspartic protease (QLI65683.1) (Fig. 6 B). 2.2.4 Secondary metabolism during saprophytic and pathogenic development Secondary metabolic processes were enriched in clusters representing both increasing (Fig. 4D) and decreasing (Fig. 4A,B) gene expression levels throughout saprophytic development. In contrast, secondary metabolism was enriched during pathogenic development mainly after conidia had germinated (Fig. 5 G–I), and the enrichment was more significant at later developmental stages (Fig. 5 H,I). Specifically, we observed differences in gene expression levels between developmental stages in the context of terpenoid and steroid biosynthesis as well as specific amino acids (e.g., arginine biosynthesis) and toxins (e.g., aflatoxin biosynthesis). We did not detect the unique enrichment of virulence-related metabolites in the parasitic lifestyle. AntiSMASH analysis of the M. brunneum genome revealed 55 known and unknown biosynthetic gene clusters (BGCs) dispersed across seven chromosomes (Table S9). The predicted BGCs were combined with the transcriptomic data to compare gene expression levels between the saprophytic and parasitic lifestyles. Two destruxin clusters were predicted on chromosomes 5 and 7 (Fig. 7 A,B). The first was divided into two sub-clusters, each containing a non-ribosomal polyketide (NRPK) as the core gene. The first sub-cluster also included the aclP gene (QLI72085.1), and BLAST analysis using the remaining coding sequences as queries indicated a similarity to gliP , which is required for glitoxin production in Aspergillus spp. The second subcluster contained the gene dtxS1 (QLI74679.1), which is required for destruxin synthesis. Interestingly, the first subcluster was strongly upregulated during pathogenesis, but the second was upregulated only during saprophytic growth (Fig. 7 A). We also identified genes responsible for the synthesis of serinocyclin and swainsonine, the former upregulated during saprophytic growth and the latter expressed at the same level in both lifestyles (Fig. 7 C,D). A single BGC on chromosome 1, predicted to synthesize eupenifeldin (27% of genes show similarity) or stipitatic acid (28% of genes show similarity), was strongly upregulated during pathogenic development, with individual genes showing 100-fold to more than 30,000-fold increases in expression compared to saprophytic growth (Fig. 7 E). These genes were predicted to synthesize citrinin/tropolone, given the presence of a citrinin biosynthesis transcriptional activator gene ( ctnR , QLI63578.1) 3.8 kb away from the core gene, with a 1000-fold higher expression level in the parasitic fungus (Fig. 7 E). 2.3 Significant pathways and ontologies in M. persicae during infection Significant differences in gene expression were observed between infected and uninfected aphids at all disease stages, with more genes significantly upregulated in the uninfected aphids. A significant response to fungal infection was observed during fungal adhesion to the aphid cuticle. Only 96 genes were significantly upregulated at this stage but 521 were significantly downregulated (Fig. 2 F). Chitin-related terms were significantly enriched among the upregulated genes during conidial adhesion, whereas hydrolase and oxidoreductase activities were more strongly enriched among the downregulated genes (Fig. 8 A). Chitin-related GO terms were also enriched during early infection, whereas the melanization defense response was significantly downregulated (Fig. 8 B). The analysis of DEGs revealed that two genes related to flight were upregulated more than 30-fold at the adhesion stage in the alate aphids: flightin (LOC111036448) and troponin C-like (LOC111036236). Genes encoding esterase FE4 (LOC111030482) and esterase E4 (LOC111030391) were significantly downregulated during the early infection stages, including fungal adhesion and fungal development on the cuticle (Tables S4, S5). The early and late stages of infection differed substantially in terms of fungal growth. In the early stages, fungi develop on the outer surface of the aphid and start to penetrate through the outer integument. In the late stages, fungi develop within the aphid body cavity, reproducing as blastospores in direct contact with the host immune system. The first significant enrichment related to the immune response was observed only in aphids where fungi had already colonized the hemocoel, including GO terms related to heat shock proteins (HSPs) and starvation responses, and KEGG pathways associated with endocytosis, longevity, autophagy and MAPK signaling (Fig. 8 C,D). More specific immune response enrichment was observed in aphids during late infection compared to early infection. Whereas early infection was enriched for terms related to chitin, late infection also included enrichment for JNK signaling and wound healing (Fig. 8 E). Early infection was associated mainly with proteasome-related and metabolic pathways in KEGG, whereas immune response pathways were dominant at the late infection stages (Fig. 8 F). 3. Discussion 3.1 Dormancy breaking and epigenetic regulation of lifestyle shifting Entomopathogenic fungi such as M. brunneum tend to develop as either pathogens or saprophytes, commencing at the conidial stage, depending on environmental signals. Our results demonstrated the initial process of environmental adaptation and dormancy breaking, starting with the transcription of specific genes in the dormant conidia in response to environmental cues (in this case, the different carbon sources available in the CM or on the insect cuticle) and ultimately leading to protein synthesis and fungal growth. These results support the hypothesis that conidia prepare for environmental conditions by transcription while delaying translation (Teertstra et al., 2017 ). When removed from the conidiophore, conidia are ready to break dormancy and initiate development, which includes an increase in protein synthesis (Hagiwara et al., 2016 ). Interestingly, during mycelial development on CM, we observed the upregulation of transcription, including genes encoding transcription factors. Conidia (0h) and mycelia (72h) show similarities in gene expression because conidiophore differentiation or conidiogenesis occur already after 72 h (Jenkins and Prior, 1993 ). Transcriptional reprogramming may therefore be required at these two time points. On the other hand, the enrichment of regulatory factors in mycelia reflect environmental changes sensed by the fungus, such as density and nutrient availability. As expected, we observed significant differences between the two lifestyles in terms of enzymes and secondary metabolites. We collected conidia from CM with no previous adaptation to a parasitic lifestyle, thus pathogenicity-related genes were not expressed during the conidial stage. RNA synthesis in the conidia did not reinforce a specific lifestyle, but instead facilitated general fungal growth. However, when the fungi sense a host, gene expression must switch to the parasitic setting (Mukherjee and Vilcinskas, 2018 ). We propose that epigenetic regulation based on chromatin remodeling plays a significant role during this lifestyle shift, as previously shown in yeast lifestyle shifting (Bao and Shen, 2011 ). The Ino80, NuA4 and SWR1 complexes were previously shown to regulate lifestyle shifting in yeast, such as the shift to hyphal growth (Wang et al., 2018 ). During the adhesion stage, we observed the expression of a gene related to conidiation in A. flavus (Chang et al., 2017 ) and a cell differentiation gene encoding a member of the CCR4-NOT complex, which regulates the cell cycle during normal growth (Cotobal et al., 2015 ). Although M. brunneum does not have a sexual reproduction mode (St Leger and Wang, 2020 ), early adhesion is a decision-making point for further development. Dormancy breaking and the shift from saprophytic to pathogenic development may therefore be regulated to some extent by this essential complex, although this must be confirmed in further experiments (Fig. 9 ). Our data suggest that conidia prepare for the sensed environment, in agreement with previous studies (Earl Kang et al., 2021 ; Hagiwara et al., 2017 ; Krach et al., 2022 ). Interestingly, conidia begin to express genes and store mRNA needed for subsequent growth in the sensed environment even before detachment from the conidiophore or dormancy (Wang et al., 2021 ). The equivalent shift from parasitic to saprophytic may shed light on the molecular basis of lifestyle shifting. 3.2. Protease gene expression may explain the plasticity of M. brunneum lifestyles Subtilisin-like (Pr1) and trypsin-like (Pr2) proteases are known to be involved in the pathogenicity of Metarhizium spp. because they are required for cuticle penetration and nutrient acquisition (Bagga et al., 2004 ; St Leger et al., 1996 ). Conidia secrete proteases even before germination, which may facilitate the early stages of infection (Leger et al., 1991 ). We have demonstrated that M. brunneum encodes a large number of trypsin-like Pr2, subtilisin Pr1, and subtilisin Pr1C proteases that are modulated in an orchestrated manner throughout development (Fig. 9 ). We found that a single trypsin-like serine protease was expressed solely during adhesion, whereas two Pr1 proteases (putative Pr1F and Pr1H) were expressed during adhesion but did not shut down at the start of germination, suggesting a further role in pathogenicity. However, Pr1F proteases in B. bassiana have no role in pathogenicity and are assumed to be evolutionary remnants (Gao et al., 2020 ). Pr1F was reported to be expressed rarely in M. anisopliae , but this may reflect the use of an less sensitive detection method (Bagga et al., 2004 ). We observed the expression of Tryp8 during late pathogenic and saprophytic development, similar to the trypsin-like serine-protease identified in the entomopathogenic fungus Zoophthora radicans (order Entomophtorales), which plays a role in pathogenesis but not host specificity (Xu et al., 2006 ). A similar protease was also detected in Pandora neoaphidis (Entomophtorales), which infects aphids (Grell et al., 2011 ). The best-studied Pr1 protease is M. anisopliae Pr1A, which facilitates cuticle penetration (Bagga et al., 2004 ). Even so, a Pr1A mutant caused mortality in greater wax moth ( Galleria mellonella ) larvae similarly to the wild-type strain (Wang et al., 2002 ). We did not identify Pr1A among the abundant proteases expressed during M. brunneum pathogenic development. Moreover, M. anisopliae strains differing in Pr1 and Pr2 activity did not show correlation between protease activity and mortality (Rosas-García et al., 2014 ). Different fungal strains and isolates may express diverse proteases as virulence factors, causing differences in performance against particular susceptible hosts (Vilcinskas, 2010 ). In agreement with our results, a previous study showed neither Pr1 a nor Pr1 b were expressed when G. mellonella was infected with M. brunneum (Grizanova et al., 2019 ). Finally, only one of the two Pr1H -like genes we detected was constitutively expressed during fungal growth, with the highest expression during the saprophytic conidia and pathogenic adhesion stage. This may therefore be the endocellular Pr1 of the MbK isolate (Bagga et al., 2004 ). The second Pr1H-like protease may be a pathogenicity-related peptidase rather than an endopeptidase because it was expressed exclusively during pathogenic development. We used a GFP-expressing strain of M. brunneum to correlate fungal gene expression with particular fungal developmental stages within the host. For the first time, we observed gene expression during fungal adhesion in vivo before any germination. We also identified shared and unique pathways between the saprophytic and parasitic lifestyles. We conclude that conidia produced during saprophytic growth in CM have no advantage in pathogenic development and require subsequent adaptation. Further experiments should focus on the conidia produced during pathogenesis to determine which adaptations mediate virulence. 3.3. BGCs related to secondary metabolism expressed during saprophytic and pathogenic development suggest active biofeedback processes Fungal BGCs responsible for the synthesis of secondary metabolites encode core enzymes as well as transporters and regulators (Molnár et al., 2010 ). The synthesis of secondary metabolites released during fungal development (Iwanicki et al., 2020 ) is related to environmental adaptation, interspecific competition and virulence factors (Chatterjee et al., 2016 ; Molnár et al., 2010 ; Vilcinskas et al., 1997 ). M. anisopliae was previously shown to secrete secondary metabolites during growth on the host cuticle (Wang et al., 2005 ), but secondary metabolites produced during adhesion have not been assessed before. B. bassiana secondary metabolites are mainly expressed when the fungus proliferates in the hemocoel (Lobo et al., 2015 ). We found that most of the predicted BGCs expressed core enzymes and transporters in at least one of the fungal lifestyles (Fig. 9 ). Our previous results showed that diverse secondary metabolites are secreted by the MbK isolate (Reingold et al., 2022 ). One of the best-known Metarhizium secondary metabolites is destruxin, which facilitates the pathogenicity of M. anisopliae by preventing the attachment of hemocytes to fungal propagules, thus inhibiting phagocytosis (Pal et al., 2007 ; Sowjanya Sree et al., 2008 ; Vilcinskas et al., 1997 ). Fascinatingly, we found that destruxin was expressed at only low levels in conidia samples during saprophytic growth and not at all during pathogenesis. In agreement, M. brunneum destruxin activity was elevated in cadavers (Bekker et al., 2013 ), which were not assessed in our study. Two other known Metarhizium secondary metabolites, namely serinocyclin (Gibson et al., 2014 ) and swainsonine, were also identified in our study. The swainsonine core gene was expressed during saprophytic and pathogenic growth, whereas serinocyclin-related gene expression was only detected during saprophytic development. This agrees with our previous results showing both metabolites present during saprophytic growth in M. brunneum (Reingold et al., 2022 ). The role of these metabolites in fungal pathogenicity is unclear (Cook et al., 2017; Moon et al., 2008; Sbaraini et al., 2016 ) although sublethal effects have been reported in mosquitoes (Krasnoff et al., 2007 ). We detected the expression of genes associated with other secondary metabolites that are not known to facilitate Metarhizium virulence. For example, Penicillium citrinum produces a mycotoxin known as citrinin, which inhibits the synthesis of aflatoxin by A. parasiticus (Ichinomiya et al., 2023 ). In Metarhizium , similar genes were predicted in a tropolone/citrinin BGC and were upregulated during early pathogenic development (Fig. 9 ), but their virulence was not assessed (Sbaraini et al., 2016 ). This cluster was also expressed during the pathogenic development of M. anisopliae , but the fold change compared to saprophytic growth was lower than in our study (Sbaraini et al., 2016 ). We hypothesize that this BGC is pathogenic or at least nonessential for saprophytic growth in rich media. Finally, a putative BGC for shearinine D was strongly expressed during pathogenic growth, with the core enzyme responsible for the synthesis of lolitrem B. The synthesis of this compound in two endophytic fungi showed high insecticidal activity toward aphids (Collinson et al., 2020 ). However, a strain without lolitrem B also caused significant mortality, indicating this compound must act with others to exert an insecticidal effect. Interestingly, peramine, which does not affect aphids (Collinson et al., 2020 ), was downregulated during pathogenic development in our study. 3.4. Fungal infection causes a cascade of responses in aphids 3.4.1. The fast and furious cuticular response does not inhibit the infection The first level of arthropod defense against fungal pathogens is the cuticle as a physical barrier, followed by humoral and cellular immune responses (Vilcinskas and Götz 1999). We observed the massive upregulation of genes encoding cuticle proteins as one of the only means to promote wound repair during fungal infection (Fig. 9 ). M. persicae has soft and rigid cuticle proteins featuring chitin-binding sites RR-1 and RR-2, respectively (Dombrovsky et al., 2007 , 2003 ). The soft cuticle is easier for fungi to penetrate (Butt et al., 1995 ). Harder cuticle proteins containing the RR-2 domain were upregulated during fungal infection in this study, possibly increasing cuticle sclerotization as a defense mechanism (Dombrovsky et al., 2007 ; Iconomidou et al., 2005 ; Koganemaru et al., 2013 ). The strongest upregulation of cuticle protein genes in this study occurred during the earliest infection stages, before fungal penetration. This is an effective defense and evasion mechanism in insects in response to fungal infection (Xing et al., 2017 ), even though it is ultimately unsuccessful (Reingold et al., 2021 ). The strong upregulation of cuticle proteins has been observed in previous studies, sometimes as the most prominent response to fungal pathogens (Dongxu et al., 2017 ; Li et al., 2016 ; Yu et al., 2016 ). Cuticle proteins are also upregulated during molting and development (Charles, 2010 ). However, these aspects were not considered in our study because we only used adult aphids. 3.4.2. Recognition of fungi breaching the cuticular barrier In Drosophila melanogaster , the Gram-negative binding protein (GNBP) detects both Gram-positive and fungal invaders by interacting with the peptidoglycan receptor protein (PGRP) to activate the Toll and IMD pathways (Gottar et al., 2006 ). However only two GNBP genes are present in aphids (named GNBP1 and GNBP2 in Acyrthosiphon pisum ) (Gerardo et al., 2010 ). The GNBP3 gene, which detects fungi in D. melanogaster (Gottar et al., 2006 ), is not present in aphids, which also lack a PGRP gene, suggesting that fungi are detected by GNBP1 (Gerardo et al., 2010 ; Ye et al., 2022 ). In M. persicae , BLAST analysis revealed two GNBP genes, both similar to GNBP2 (LOC111036217 and LOC111031217). We found that LOC111036217 was significantly downregulated in aphids during late infection, whereas LOC111031217 was not differentially expressed. The Toll pathway was also upregulated in infected aphids but the phenoloxidase pathway was significantly downregulated during infection. A comparison between early and late infection enabled us to detect the shift in the aphid response. The main early response involved cuticle proteins accompanied by lysosome, phagosome and proteasome activities, whereas hemocoel colonization during late infection triggered the overexpression of immune response pathways. The main enriched pathway was longevity (mediated by FoxO and HSPs) together with the JNK signaling, endocytosis and wound healing pathways, meaning that cuticle protein expression was ultimately replaced by other defense strategies (Fig. 9 ). Autophagy was observed in G. mellonella during fungal infection as part of the hemocyte response (Kazek et al., 2020 ). Autophagy was initially thought to remove endogenous waste materials, but was later shown to also eliminate cell-borne pathogens (Kuo et al., 2018 ). The enrichment of autophagy in our study may reflect the fungal degradation of host organelles targeted for destruction or a role in the direct elimination of fungal propagules by phagocytosis (Fig. 9 ). 3.4.3. Fight not flight? The activation or suppression of early-response genes is essential for host–pathogen interactions. We found that the early response was insufficient to overcome infection, which may reflect the suppression of genes known to participate in detoxification and fungal resistance encoding E4 and FE4 esterases, glutathione S-transferase, and UDP-glucuronosyltransferase (Bilal et al., 2018 ; Field and Devonshire, 1998 ; Xia et al., 2013 ). Conversely, two cathepsin B genes were upregulated in correlation with fungal infection in our study, as previously reported (Grell et al., 2011 ), and these may indeed act as detoxifying enzymes (Lan et al., 2021 ) (Fig. 9 ). Oxidative stress in the insect host during fungal infection induces an immune response (Butt et al., 2016 ). The gonadotropin-releasing hormone receptor, which is known to activate immune responses, was significantly downregulated in the infected aphids. However, the hormone (not the receptor) was upregulated in A. pisum in response to stress (Jedlička et al., 2015 ) and the receptor was downregulated in cockroaches during oxidative stress (Huang et al., 2012 ). Phenoloxidases were also downregulated during our infection experiments, in contrast to A. pisum infected with B. bassiana (Xu et al., 2019 ). Interestingly, phenoloxidase gene expression in aphids infected with Pandora spp. was induced 48 h post-inoculation, with no significant expression before or after (Parker et al., 2017 ). Although our sample collection was based on fungal developmental stages rather than time post-inoculation (to ensure accuracy), no such expression was detected at any disease stage in our study. The cellular immune response in insects includes phagocytosis and encapsulation by hemocytes when pathogens are recognized (Strand, 2008 ). The humoral immune system is based mainly on the Toll and IMD signaling pathways (Ali Mohammadie Kojour et al., 2020 ). The Toll pathway is the main mediator of antifungal responses, activating the production of antimicrobial peptides (AMPs) during hemocoel invasion (Gerardo et al., 2010 ; Lu and St. Leger, 2016 ). However, aphids lack key components of the Toll and IMD pathways as found in Drosophila spp. (Gerardo et al., 2010 ; Vilcinskas, 2016 ). As expected, the Toll and IMD pathways (KEGG api04624) were induced only when fungal propagules were present in the hemocoel and not during penetration. Interestingly, there are four genes in the aphid genome encoding Spätzel (Spz), the Toll ligand and activator, but only two of them were annotated as part of the Toll pathway in KEGG. The spz3 gene was not annotated as part of the Toll pathway, and was the only spz gene significantly upregulated during the fungal colonization of the hemocoel. We therefore propose that Spz3 activates the Toll receptor during the infection of M. persicae by M. brunneum . The multiple duplications of Toll pathway genes in the aphid genome may interfere with computational predictions, especially those based on comparisons in different organisms (Lima et al., 2021 ). Interestingly, aphid genomes are almost completely devoid of AMP genes suggesting that the defense mechanisms activated by Toll are probably enzyme based (Altincicek et al., 2008 ; Gerardo et al., 2010 ). The IMD pathway was also upregulated, specifically the AP-1 transcription factor that binds to the promoters of genes needed for wound repair in Drosophila spp. (Mace et al., 2005 ). However, the known target gene of this pathway – grainyhead-like ( grh ) – was not differentially expressed in our system. Moreover, the phenoloxidase genes responsible for the melanization response were strongly downregulated in the infected aphids. This weak response may reflect the presence of endosymbiont activity in the aphids, which is known to modify the immune response (Nichols et al., 2021 ). In this regard, no Regiella spp. were found in our aphid colony, but Rickettsia spp. and other unspecified Enterobacteriaceae were identified by 16S rRNA sequencing (data not shown). This is not the first report of a weak aphid response to entomopathogenic fungi (Grell et al., 2011 ) accompanied by costly effects on life-history traits (Barribeau et al., 2014 ; Reingold et al., 2021 ). 3.4.4. Flight not fight? The flightin gene appears to be involved in wing formation and flight muscle development in insects given that D. melanogaster null mutants feature ultrastructural defects in the flight muscles and impaired flight (Vigoreaux et al., 1998 ). Similar impairments were observed when the flightin gene was silenced in the aphid A. pisum (Chang et al., 2022 ). In planthoppers, the flightin gene cooperates with troponin C and others to control wing dimorphism and is essential in long-winged forms (Xue et al., 2013 ). Interestingly, aphids infected with entomopathogenic fungi produce a higher proportion of winged offspring (Hatano et al., 2012 ). The high expression levels of flightin and troponin C genes in our study were in correlation to early fungal infection in aphids, this might suggest a transgenerational evasion strategy (Fig. 9 ). The transgenerational effects of chemicals that cause wing defects in D. melanogaster were recently shown to be regulated by histone methylation (Sun et al., 2023 ). Transgenerational inheritance in insects may involve a vast array of epigenetic marks (Mukherjee and Dobrindt, 2022 ). More importantly, exposure to pathogens may lead to resistance in the offspring, also mediated by epigenetic marks (Gegner et al., 2019 ). Immune priming can involve the direct maternal translocation of the pathogen or pathogenic elements (Freitak et al., 2014 ; Vilcinskas, 2021 ). Interestingly, genes correlated with transgenerational wing formation in aphids (Vellichirammal et al., 2017 ) were also upregulated in our infected aphids, but the fold change was not significant. This lack of significance may reflect the pooling of mothers and offspring, which would obscure significant changes that occur in the embryos during wing formation. 3.5. Conclusions Entomopathogenic fungi such as M. brunneum have evolved the ability to survive as saprophytes (which can therefore be cultured in artificial media), as endophytes in plants, and as parasites that infect insects directly via their cuticle. We proposed that the switch from a saprophytic to a parasitic life style must be accompanied by fundamental transcriptomic reprogramming. Using a GFP-expressing fungal strain and live imaging of disease progression we collected accurate disease stages on Myzuys persicae and combined high-throughput RNA-Seq analysis of M. brunneum grown also in vitro . we identified a comprehensive set of genes that are modulated during the switch from saprophytic to pathogenic development. We observed highly orchestrated transcriptomic reprogramming involving genes encoding proteases and BGCs producing secondary metabolites operating as virulence factors during adhesion and germination of conidia on the insect cuticle and during cuticle penetration and pathogenesis within the host insect. Our experimental setup also allowed us to analyze transcriptomic reprogramming in aphid hosts in response to fungal infection. This is the first report to examine the specific disease stages of the fungal pathogen in vivo , and to investigate the shift in gene expression at the stage of fungal adhesion, as determined by live imaging. We demonstrated that the aphid responds to the fungal pathogen at the earliest stage of their encounter: conidial adhesion. The significant changes provide insight into the aphid defense strategy, which ultimately fails. We propose an evasion strategy, based on increasing the proportion of alate offspring, which is mediated by flight-related gene expression. 4. Materials and methods 4.1 Fungal culture conditions Metarhizium brunneum isolate MbK constitutively expressing the GFP reporter gene was cultured on Sabouraud dextrose agar (SDA, Difco) plates at 28 ± 0.5°C in the dark (defined as complete medium, CM). For saprophytic growth in vitro , conidia were harvested from three replica plates (14 days old) into 0.01% Triton X-100. Conidial suspensions were transferred through two layers of gauze pads to exclude hyphae. The concentration was measured using a hemocytometer and adjusted to 10 8 /ml. A 100-µl sample of each conidial suspension was flash-frozen in liquid nitrogen with TRIzol reagent (Thermo Fisher Scientific, USA) and stored at − 80°C (0 h conidial control; Fig. 2 A). 4.2 Media inoculation for transcriptomic profiling during saprophytic growth Conidial suspensions were plated on CM (10 6 conidia/plate) and samples were harvested from four plates after 9 h (almost all conidia germinated), 24 h (long hyphae) and 72 h (dense hyphae, white mycelial layer) (Fig. 2 A, top) and pooled in 1% Triton X-100. Samples were precipitated at 8000 × g for 5 min, suspended in TRIzol reagent, and flash-frozen in liquid nitrogen for storage at − 80°C. Three sets of conidial samples were collected from different maternal plates at each time point. A single sample at 9 h (germination) yielded RNA of insufficient quality and was excluded from further analysis (Fig. 2 B). 4.3 Aphid inoculation for transcriptomic profiling during pathogenesis Organic pepper plants ( Capsicum annuum cv Maor) were used to rear M. persicae in insect-proof cages maintained at 25 ± 2°C and 60% relative humidity with a 12-h photoperiod (Reingold et al., 2021 ). Adult aphids were inoculated with M. brunneum MbK in a fine sieve by soaking in a solution of 1×10 8 conidia/ml for 8 s, before drying on a paper towel and careful transfer to pepper leaves embedded in 2% agarose. Inoculated aphids were incubated in controlled chambers at 28 ± 0.5°C and 70% relative humidity with a 12-h photoperiod (Reingold et al., 2021 ). 4.4 Live imaging during pathogenic development Disease progression was monitored in live aphids by confocal microscopy (Reingold et al., 2021 ). Live aphids were placed on a cover slip in a water drop and were then separated into tubes based on the latest disease stage: adhesion (no germinated conidia detected), germination (no penetration detected), penetration (including only appressorium formation and penetration peg, without hemocoel colonization), hemocoel colonization (approximately half of the body cavity), and fully colonized hemocoel (Fig. 1 A, bottom). All aphids were live and motile. Collected aphids were flash-frozen in liquid nitrogen with TRIzol reagent, and stored at − 80°C. We prepared four samples of 25 non-infected aphids, two samples (50 aphids each) demonstrating conidial adhesion to the cuticle, 66 and 67 aphids with germinated conidia, 24 aphids demonstrating penetration, 25 and 24 aphids demonstrating initial hemocoel colonization, and two samples of 24 aphids each with massive hemocoel colonization. Conidial adhesion samples were prepared in which the conidia showed no germination on the aphid cuticle. Two separate pools were sequenced in aphids with various quantities of adhered conidia. Two “germination” samples consisted of aphids with mainly germinated conidia and fungal growth on the outer cuticle without appressorium formation or penetration, but also non-germinated conidia to some extent. A single penetration sample included aphids exhibiting fungal appressorium formation and penetration pegs, without development within the hemocoel. The later fungal developmental stages included aphids with fungal hemocoel colonization. These were categorically separated into two arbitrary groups of less than or more than half of the aphid body colonized by fungi as visualized by confocal microscopy, termed initial hemocoel colonization and full hemocoel colonization (Fig. 2 A, bottom). 4.5 RNA extraction and high-throughput sequencing Total RNA was extracted from harvested conidia, germinated conidia and hyphae (designated saprophytic growth), and infected aphids (designated pathogenic growth, parasitic lifestyle) using TRIzol reagent. Briefly, samples were thawed on ice, then homogenized using metal beads in a Geno/Grinder at 6500 oscillations/min for 3 min. Samples were then phase separated at 8000 × g for 15 min at 4°C, and the aqueous phase was transferred to an RNA Clean & Concentration Column (Zymo, USA) followed by in-column DNase I treatment. Eluted RNA was measured using a Nanodrop spectrophotometer, and its integrity was assessed by 1% agarose gel electrophoresis. RNA samples were qualified using a Bioanalyzer 2100 (Agilent Technologies, USA) at BGI Genomics (China). Libraries were constructed using poly-A capture, and paired-end 150-bp reads were sequenced on DNA nanoball (DNB) platform at BGI Genomics. 4.6 Bioinformatic analysis 4.6.1 Fungal transcriptome . We mapped ~ 2.1 Gb of paired-end reads (average 88.8 million per sample) to the reference genome of Metarhizium brunneum 4556 ( https://www.ncbi.nlm.nih.gov/assembly/GCA_013426205.1/ ) using STAR v2.7.1a (Dobin et al., 2013 ). Gene abundance was estimated using Cufflinks v2.2 (Trapnell et al., 2010 ) combined with gene annotations from the NCBI nr database ( https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/013/426/205/GCA_013426205.1_ASM1342620v1/GCA_013426205.1_ASM1342620v1_genomic.gff.gz ). PCA plots and heat maps were prepared and visualized using R Bioconductor, accessed on 15 May 2022 (Gentleman et al., 2004 ). Gene expression values were computed as fragments per feature kilobase per million reads mapped (FPKM). Differential expression was analyzed using the DESeq2 R package (Love et al., 2014 ) with a two-fold-change cutoff and a statistical significance of ≤ 0.05 after false discovery correction (Benjamini and Hochberg, 1995 ). Genes were hierarchically clustered based on FPKM values and the clusters were extracted using R scripts. Venn diagrams were constructed using Venny 2.0 online ( http://bioinfogp.cnb.csic.es/tools/venny/ ) (Oliveros, 2007 ). We used KOBAS 3.0 ( http://kobas.cbi.pku.edu.cn/kobas3/?t=1 ) to find statistically significant enrichment of differentially expressed genes in the KEGG pathway database and Gene Ontology (GO) categories (Xie et al., 2011 ). Phylogenetic analysis of protease genes within the M. brunneum genome was conducted using PhyML online (Guindon et al., 2010 ). BGCs were predicted using fungal antiSMASH v6.1.1 ( https://fungismash.secondarymetabolites.org/#!/start ) (Blin et al., 2021 ). 4.6.2 Aphid transcriptome The paired-end reads were mapped to the reference genome of Myzus persicae ( https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_001856785.1/ ) using STAR software (v2.7.1a) (Dobin et al., 2013 ). Gene abundance was estimated using Cufflinks (v. 2.2) (Trapnell et al., 2010 ) combined with gene annotations from the NCBI database ( https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/001/856/785/GCF_001856785.1_MPER_G0061.0/GCF_001856785.1_MPER_G0061.0_genomic.gff.gz ). Gene expression values were computed as fragments per feature kilobase per million reads mapped (FPKM). Differential expression analysis was performed with the edgeR R package (Robinson et al. 2010 ). Genes ≥ 2-fold differentially expressed with a false discovery-corrected statistical significance of at most 0.05 were considered differentially expressed (Benjamini and Hochberg, 1995 ). 4.7 cDNA synthesis and real-time PCR validation RNA samples (500 µl) were reverse transcribed using the qPCRBIO cDNA Synthesis Kit and oligo dT primers (PCRBIOSYSTEMS, UK). The cDNA was used for real-time PCR analysis with Fast SYBR Green Master Mix (Thermo Fisher Scientific) and gpd as a reference gene (Fang and Bidochka, 2006 ). Relative expression levels were calculated using the 2 −ΔΔCt method (Livak and Schmittgen, 2001 ). Statistical significance was determined using a standard least squares restricted maximum likelihood (REML) test, followed by post hoc comparison with Student’s ttest or Tukey’s test in JMP Pro v16.0.0 (SAS Institute, USA). Primers were designed using Primer3 (Table S10) and efficiency was determined by constructing standard curves. Declarations Ethics approval and consent to participate All co-authors have approved to participate. Consent for publication Not applicable. Funding This research was funded by the German-Israeli Foundation (GIF) Young Scientists’ Program, Project No. I-1541-500.15/2021 to DM and AV. Authors' contributions VR, AV and DM wrote the manuscript. VR, SM and EB collected the fungal and aphid materials for transcriptomics. SH did the Real-time qPCR of gene expression validation. VR and AF analysed the data by bioinformatics. Acknowledgment The authors thank Dr. Richard M Twyman for the professional editing of the manuscript. Data Availability statement All data of the study is fully accessible in the public repository NCBI under bioprojects: PRJNA1106639; PRJNA1106641. References Ali Mohammadie Kojour, M., Han, Y.S., Jo, Y.H., 2020. An overview of insect innate immunity. 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Molecular characterization of the flightin gene in the wing-dimorphic planthopper, Nilaparvata lugens, and its evolution in Pancrustacea. Insect Biochemistry and Molecular Biology 43, 433–443. https://doi.org/10.1016/j.ibmb.2013.02.006 Ye, C., Wang, Z.-W., Sheng, Y.-L., Wang, Z.-G., Smagghe, G., Christiaens, O., Niu, J., Wang, J.-J., 2022. GNBP1 as a potential RNAi target to enhance the virulence of Beauveria bassiana for aphid control. J Pest Sci 95, 87–100. https://doi.org/10.1007/s10340-021-01388-x Yu, S., Ding, L., Luo, R., Li, X., Yang, J., Liu, H., Cong, L., Ran, C., 2016. Identification of Immunity-Related Genes in Dialeurodes citri against Entomopathogenic Fungus Lecanicillium attenuatum by RNA-Seq Analysis. PLOS ONE 11, e0162659. https://doi.org/10.1371/journal.pone.0162659 Zhou, P., Zong, X., Yan, S., Zhang, J., Wang, D., Shen, J., 2023. The Wnt pathway regulates wing morph determination in Acyrthosiphon pisum. Insect Biochemistry and Molecular Biology 161, 104003. https://doi.org/10.1016/j.ibmb.2023.104003 Zimmermann, G., Papierok, B., Glare, T., 1995. Elias Metschnikoff, Elie Metchnikoff or Ilya Ilich Mechnikov (1845-1916): A Pioneer in Insect Pathology, the First Describer of the Entomopathogenic Fungus Metarhizium anisopliae and How to Translate a Russian Name. Biocontrol Science and Technology 5, 527–530. https://doi.org/10.1080/09583159550039701 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 02 Oct, 2024 Read the published version in BMC Genomics → Version 1 posted Editorial decision: Revision requested 17 Jul, 2024 Reviews received at journal 15 Jul, 2024 Reviewers agreed at journal 10 Jul, 2024 Reviewers agreed at journal 09 Jul, 2024 Reviews received at journal 08 Jul, 2024 Reviewers agreed at journal 24 Jun, 2024 Reviewers invited by journal 23 Jun, 2024 Editor invited by journal 19 Jun, 2024 Editor assigned by journal 18 Jun, 2024 Submission checks completed at journal 18 Jun, 2024 First submitted to journal 15 Jun, 2024 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-4587553","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":320261092,"identity":"391a4ce2-05e6-4b6f-822a-1d63cb06a6e0","order_by":0,"name":"Victoria Reingold","email":"","orcid":"","institution":"Rishon LeZion","correspondingAuthor":false,"prefix":"","firstName":"Victoria","middleName":"","lastName":"Reingold","suffix":""},{"id":320261094,"identity":"17d36f45-cfd3-407f-9285-617f41613d07","order_by":1,"name":"Adi Faigenboim","email":"","orcid":"","institution":"ARO, The Volcani Institute, Rishon Le Zion","correspondingAuthor":false,"prefix":"","firstName":"Adi","middleName":"","lastName":"Faigenboim","suffix":""},{"id":320261098,"identity":"340adafc-6bdd-44fb-a76d-1ceacf75bfeb","order_by":2,"name":"Sabina Matveev","email":"","orcid":"","institution":"Rishon LeZion","correspondingAuthor":false,"prefix":"","firstName":"Sabina","middleName":"","lastName":"Matveev","suffix":""},{"id":320261099,"identity":"9ac8581d-35f2-4f9a-9174-8214a413de9c","order_by":3,"name":"Sabrina Haviv","email":"","orcid":"","institution":"Rishon LeZion","correspondingAuthor":false,"prefix":"","firstName":"Sabrina","middleName":"","lastName":"Haviv","suffix":""},{"id":320261102,"identity":"8935eed8-eaef-4ba3-97d5-40d8050fa0ab","order_by":4,"name":"Eduard Belausov","email":"","orcid":"","institution":"ARO, The Volcani Institute, Rishon Le Zion","correspondingAuthor":false,"prefix":"","firstName":"Eduard","middleName":"","lastName":"Belausov","suffix":""},{"id":320261107,"identity":"fe85e83b-5589-4191-b82d-f744f1b5f584","order_by":5,"name":"Andreas Vilcinskas","email":"","orcid":"","institution":"Justus Liebig Universität Giessen","correspondingAuthor":false,"prefix":"","firstName":"Andreas","middleName":"","lastName":"Vilcinskas","suffix":""},{"id":320261108,"identity":"e3320667-b746-42cb-ac92-27f1a2bd1cd6","order_by":6,"name":"Dana Ment","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCklEQVRIiWNgGAWjYDCCAyCigoGBD0QngAhmiAQPH14tZxgY2DC0sOHTwtgG1YICcGnhO3724Keb8w7LsbEffvbgAYOd3fZ2BuYXH9sYZHBpkTyTlyydu+2wMRtPmrlBAkNy8pzDDGyWM9twO8zgQI4BUEtaYpsEg5lEAgNzsgQzA5sxzxk8Ws6/Mf6dOwekhf0bUEs9EVpu5JhJ5zbYALXwgGw5bAfUwvyYpwK3Fskbb8ysc47ZAP2SUyaRYHA8QYKZsY1xRoUETi1853OMb+fUSMjxsx/fJvmjotpegv/w4Q8fDGzs+XFoQXcnQ2IDMJokGBgkiNMAAvZAzPyBePWjYBSMglEwAgAA9apJNCR15PcAAAAASUVORK5CYII=","orcid":"","institution":"Rishon LeZion","correspondingAuthor":true,"prefix":"","firstName":"Dana","middleName":"","lastName":"Ment","suffix":""}],"badges":[],"createdAt":"2024-06-15 18:30:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4587553/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4587553/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12864-024-10824-y","type":"published","date":"2024-10-02T15:57:50+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":59642944,"identity":"953ab301-df01-4b5e-8a44-8beb1cd77aa4","added_by":"auto","created_at":"2024-07-04 08:12:18","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":377868,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eMetarhizium brunneum\u003c/em\u003elifestyles: parasitic and pathogenic in arthropods, endophytic in plants, and saprophytic in the soil or \u003cem\u003ein vitro\u003c/em\u003e. Adapted from: Ment et al. 2020a, b; Reingold et al. 2021.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4587553/v1/bc85abb802f45443bb0d6f00.png"},{"id":59642942,"identity":"c75e2362-577c-4a7c-9cfb-c9fed0304bf4","added_by":"auto","created_at":"2024-07-04 08:12:18","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":4402987,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStudy design and statistical analysis of the transcriptome\u003c/strong\u003e. \u003cstrong\u003e(A)\u003c/strong\u003e \u003cem\u003eMetarhizium brunneum\u003c/em\u003e isolate MbK conidial suspension (conidia control, 0 h) was used as the starting material for pathogenic and saprophytic development. Top shows samples of saprophytic growth \u003cem\u003ein vitro\u003c/em\u003e on complete medium (CM), from left to right: 9 h germinated conidia, 24 h hyphae, and 72 h mycelia. Bottom shows samples for dual RNA sequencing of host–pathogen interactions in \u003cem\u003eMyzus persicae \u003c/em\u003eadult aphids. Samples were selected based on live imaging by confocal laser scanning microscopy (CLSM). From left to right: conidial adhesion to the cuticle, germinated conidia, penetration, hemocoel colonization, and massive hemocoel colonization. \u003cstrong\u003e(B) \u003c/strong\u003ePCA analysis of pathogenic and saprophytic development of MbK. \u003cstrong\u003e(C)\u0026nbsp;\u003c/strong\u003eMbK differentially expressed genes\u003cstrong\u003e \u003c/strong\u003e(DEG)\u003cstrong\u003e \u003c/strong\u003ecomparing pathogenic development to the conidial control (0 h) analyzed using DEseq2 (log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; |1|, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eadj\u003c/sub\u003e \u0026lt; 0.05). \u003cstrong\u003e(D)\u003c/strong\u003e MbK DEGs comparing saprophytic development to the conidia control (log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; |2|, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eadj\u003c/sub\u003e \u0026lt; 0.001). \u003cstrong\u003e(E) PCA analysis \u003c/strong\u003eof \u003cem\u003eM. persicae \u003c/em\u003eaphid genes during fungal infection. \u003cstrong\u003e(F)\u003c/strong\u003e \u003cem\u003eM. persicae\u003c/em\u003e DEGs comparing infected and healthy aphids analyzed using edgeR (log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; |0.4|, FDR \u0026gt; 0.05).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-4587553/v1/e207b737f34670e9af747947.png"},{"id":59642946,"identity":"e98afa65-bda6-4b0a-b1e2-828bea72a985","added_by":"auto","created_at":"2024-07-04 08:12:18","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":205868,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eDifferentially expressed genes (DEGs) during saprophytic and pathogenic development of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eMetarhizium brunneum\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e and \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eMyzus persicae \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eresponse to fungal infection.\u003c/strong\u003e\u003cem\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/em\u003e(A) Hierarchical clustering of genes based on FPKM values by applying R scripts to the saprophytic development samples, grouping 2925 genes into 10 clusters differing in expression level between fungal developmental stages. Clusters were assigned letters A to J (\u003cem\u003en\u003c/em\u003e\u0026nbsp;refers to the number of genes in each cluster). Red rectangles show clusters with similar expression patterns, which were combined for further analysis. (B-E) Venn diagrams showing unique and common DEG based on DESeq2 and edgeR analysis as a function of disease progression (Venny 2.0). (B-C) \u003cem\u003eM. brunneum\u003c/em\u003e DEGs in pathogenic development and saprophytic germination (9 h) (DESeq2 log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; |1|, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eadj\u003c/sub\u003e \u0026lt; 0.05) upregulated (B) and downregulated (C) compared to the conidial control (0 h). (D-E) \u003cem\u003eM. persicae \u003c/em\u003eDEGs in response to fungal infection (edgeR analysis, log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; |0.4|, FDR \u0026gt; 0.05) upregulated (D) and downregulated (E) compared to uninfected aphids.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-4587553/v1/397ea7338df6a40389b2919e.png"},{"id":59642941,"identity":"7f4bac8c-5638-4530-aaa7-6b214a9521da","added_by":"auto","created_at":"2024-07-04 08:12:17","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":170914,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEnriched pathways within clusters of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eMetarhizium brunneum\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e genes expressed during saprophytic development. \u003c/strong\u003eGraphs on the left indicate expression patterns of the cluster, whereas those in the middle and on the right show enriched KEGG and GO pathways, respectively. (A) Enrichment within cluster B: downregulation during development. (B) Enrichment within clusters I-J: downregulation during development. (C) Enrichment within cluster C: downregulation in the conidial control. (D) Enrichment within clusters F, G and H: upregulation during fungal development.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-4587553/v1/04111e1a895a234d0916ee93.png"},{"id":59642948,"identity":"8b3145e9-74d0-461c-a986-c26968653047","added_by":"auto","created_at":"2024-07-04 08:12:18","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":235608,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKOBAS enrichment of genes expressed during the pathogenic development of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eMetarhizium brunneum\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e as separated by Venn analysis. \u003c/strong\u003e(A-F) GO enrichment of genes expressed (A) during all stages of proliferating fungi, excluding adhesion stage, (B) unique to germination as saprophyte, (C) unique to adhesion to host cuticle, (D) during early infection, excluding genes expressed during germination as a saprophyte, (E) unique to late infection, and (F) during all pathogenic stages. (G-I) KEGG enrichment of genes expressed (G) during adhesion to host cuticle, (H) during early infection, excluding genes expressed during germination as a saprophyte, and (I) unique to late infection (\u003cem\u003en\u003c/em\u003erepresents the number of genes in each group).\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-4587553/v1/0da2cabb6cf63ed9ec2c90bf.png"},{"id":59642940,"identity":"6665f6d4-ad97-4171-84d5-2208501dc748","added_by":"auto","created_at":"2024-07-04 08:12:17","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":1644584,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSelected pathogenicity-related enzymes and corresponding gene expression during fungal development. \u003c/strong\u003e(A) Heat map of selected pathogenicity-related fungal enzymes. Each column represents a corresponding gene showing the accession number. Each row shows expression at a specific developmental stage, separated into pathogenic and saprophytic development as compared to the conidial control. (B) Phylogenic tree of \u003cem\u003eMetarhizium brunneum\u003c/em\u003e proteases and relative gene expression levels during pathogenic and saprophytic development. The sequences were aligned using MUSCLE (by log-expectation), and Phylip interleaved format was applied in PhyML (Guindon et al., 2010). Accession numbers are indicated in each branch. Heat maps representing expression during saprophytic and pathogenic development are shown on the right and each row represents a single gene equivalent to the phylogenic tree. Heat map generated based on the DEseq2 values (–log\u003csub\u003e2\u003c/sub\u003eFC, \u003cem\u003ep\u003c/em\u003e\u003csub\u003eadj\u003c/sub\u003e \u0026lt; 0.05) compared to the conidial control. The values are color coded, red for upregulation, blue for downregulation, and white for no significant differential expression.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-4587553/v1/73c05ba53e4d09095a251ffe.png"},{"id":59643337,"identity":"f85aa348-93ba-4495-b87b-9bb148f040ad","added_by":"auto","created_at":"2024-07-04 08:20:19","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":249516,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSecondary metabolite clusters of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eMetarhizium brunneum\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e. \u003c/strong\u003e(A)\u003cstrong\u003e \u003c/strong\u003eCluster CP058936.1:2,211–87,262 nt, partially predicted as destruxin NRPS\u003cstrong\u003e. \u003c/strong\u003e(B) Cluster CP058938.1:2,719,929–2,819,886 nt, predicted as destruxin NRPS/T1PKS (in \u003cem\u003eM. robertsii\u003c/em\u003e). (C) Cluster CP058932.1:5,605,107–5,722,443 nt, predicted as serinocyclin A/serinocyclin B\u0026nbsp;NRPS. (D) Cluster CP058933.1:806,077–845,639 nt, predicted as swainsonine NRPS-like and PKS. (E) Cluster CP058932.1:1,671,336–1,627,762 nt, predicted as citrinin PKS. Scheme of predicted clusters was generated using antiSMASH. Core biosynthetic genes (brown) with NCBI annotations beneath, together with relative expression levels during late pathogenesis to saprophytic mycelia (DESeq2; log\u003csub\u003e2 \u003c/sub\u003eFC (pathogenic/saprophytic); \u003cem\u003ep\u003c/em\u003e\u003csub\u003eadj\u003c/sub\u003e). Red arrows indicate significant differential expression during pathogenic development.\u003c/p\u003e","description":"","filename":"floatimage7.png","url":"https://assets-eu.researchsquare.com/files/rs-4587553/v1/c08b8546b96fd4df64bee3b0.png"},{"id":59644250,"identity":"09900834-b9d6-4024-9d42-9f00c7d63b3a","added_by":"auto","created_at":"2024-07-04 08:28:18","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":286122,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eKOBAS enrichment of genes expressed during the infection of \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eMyzus persicae \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003eby \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eMetarhizium brunneum\u003c/strong\u003e\u003c/em\u003e. (A-C, E) GO enriched terms and (D, F) KEGG enriched terms of genes expressed in (A) aphids during fungal adhesion compared to uninfected aphids, (B) aphids during early infection compared to uninfected aphids, (C-D) aphids during late infection compared to uninfected aphids, and (E-F) early infected aphids compared to late infected aphids (\u003cem\u003en\u003c/em\u003eindicates the number of genes enriched within each group).\u003c/p\u003e","description":"","filename":"floatimage8.png","url":"https://assets-eu.researchsquare.com/files/rs-4587553/v1/70e27b56cd4a0f11e97489de.png"},{"id":59643335,"identity":"b310dcbc-f5b6-40fc-9f19-deaf2ba2ef77","added_by":"auto","created_at":"2024-07-04 08:20:18","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":1911283,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic summary of \u003cem\u003eMetarhizium brunneum\u003c/em\u003e development and the arms race during disease progression\u003cem\u003e \u003c/em\u003ein\u003cem\u003e Myzus persicae\u003c/em\u003e aphid.\u003c/p\u003e","description":"","filename":"floatimage9.png","url":"https://assets-eu.researchsquare.com/files/rs-4587553/v1/105860e4197fc451ba69b505.png"},{"id":66097675,"identity":"faf9da4a-fb93-47b9-ae45-a7b7feefb9ac","added_by":"auto","created_at":"2024-10-07 16:14:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":13693113,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4587553/v1/f50b3400-6831-43a2-96db-afbd708877be.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Transcriptional reprogramming in the entomopathogenic fungus Metarhizium brunneum and its aphid host Myzus persicae during the switch between saprophytic and parasitic lifestyles ","fulltext":[{"header":"1. Background","content":"\u003cp\u003eFungi evolved more than 900\u0026nbsp;million years ago, but unprecedented radiation and diversification occurred\u0026thinsp;~\u0026thinsp;480\u0026nbsp;million years ago due to interactions between fungi and terrestrial plants (Lutzoni et al., \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). This created a wide range of lifestyles, including fungi that functional primarily as saprophytes and saprobes in the soil (necessary for nutrient recycling and soil health) as well as pathogens and parasites that leech nutrients from other organisms. The most fascinating are the widespread entomopathogenic fungi, which can proliferate as independent saprophytes, plant-associated endophytes, or pathogens infecting arthropod hosts, switching between lifestyles according to need (Vilcinskas 2019). These fungi are beneficial to plants and are therefore interesting both as model organisms and for their potential applications in agriculture (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eMost entomopathogenic fungi represent the divisions Entomophthoromycota or Ascomycota, the latter including the widely-studied genus \u003cem\u003eMetarhizium\u003c/em\u003e (Hypocreales: Clavicipitaceae). Furthermore, \u003cem\u003eMetarhizium\u003c/em\u003e and \u003cem\u003eBeauveria\u003c/em\u003e spp. are the most common fungi used as commercial microbial biopesticides (Um et al., \u003cspan citationid=\"CR102\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), reflecting the ease of mass production as saprophytic cultures (Jaronski, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Loskutova and Fedotova, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Mechnikov, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e1879\u003c/span\u003e; Shah and Pell, \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Zimmermann et al., \u003cspan citationid=\"CR124\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). In nature, the fungal saprophytic lifestyle is characterized by growth on organic matter in the soil (St Leger and Wang, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) until a suitable host is encountered (Stone and Bidochka, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This triggers a switch to parasitism, in which fungal conidia adhere to the host cuticle and germinate. The germ tube differentiates into an appressorium that penetrates the host integument, reaching the hemocoel and allowing proliferation within the host. When the host nutrient supply is exhausted, the fungus breaks through the cuticle, producing new propagules as conidia, which are passively disseminated and reach new environments and potential hosts (Gillespie et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2000\u003c/span\u003e). Depending on the environmental conditions, the new propagules may remain dormant or may switch back to the saprophytic lifestyle (Ment et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Small and Bidochka, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; St. Leger, \u003cspan citationid=\"CR94\" class=\"CitationRef\"\u003e2008\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe lifestyle switches require the fungus to adapt and acquire different competences. As a pathogen, the fungus must produce enzymes that digest the host cuticle and allow the utilization of nutrients in the hemolymph (Gillespie et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2000\u003c/span\u003e; Lu and St. Leger, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Vilcinskas, \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2010\u003c/span\u003e), as well as proteins that enable the evasion of innate immunity (Chen et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). In contrast, cultivation in rich media enables the fungus to divert its resources to nutrient metabolism (Li et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; St Leger and Wang, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). \u003cem\u003eMetarhizium\u003c/em\u003e can grow as a saprophyte or an endophyte in different plant roots in the rhizosphere (Ment et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2020a\u003c/span\u003e, \u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e2020b\u003c/span\u003e). It can acquire nutrients from the plant and, in turn, promote plant growth and systemic immunity to a broad range of pests and pathogens (Gupta et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Vega et al., \u003cspan citationid=\"CR103\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Indeed, \u003cem\u003eMetarhizium\u003c/em\u003e may have evolved from a plant endophyte into an insect pathogen to gain new sources of nitrogen that can be traded with plants for carbohydrates (Stone and Bidochka, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This adaptation necessitated genomic diversification to support the new physiological and metabolic functions, as well as the evolution of regulatory systems to control the switch between lifestyles in different environments (Barelli et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe have previously reported intraspecific variation in terms of pathogenicity and secreted active metabolites in \u003cem\u003eM. brunneum\u003c/em\u003e isolates and proposed epigenetic regulation as a means to control the switch between lifestyles (Reingold et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Here, we hypothesize that lifestyle switches require early gene expression to enable a rapid response to changing growth conditions. We therefore investigated transcriptome reprogramming during lifestyle shifting in \u003cem\u003eM. brunneum\u003c/em\u003e, specifically the change from \u003cem\u003ein vitro\u003c/em\u003e growth on complete medium (mimicking saprophytic nutrient acquisition) to parasitism in the model aphid host \u003cem\u003eMyzus persicae\u003c/em\u003e. We used a combination of live imaging and host\u0026ndash;fungus dual RNA sequencing (RNA-Seq) to analyze the rapid and flexible transcriptional response in conidia during lifestyle shifting and dormancy breaking, leading to early host responses with the potential for transgenerational priming.\u003c/p\u003e"},{"header":"2. Results","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Patterns of fungal and host gene expression\u003c/h2\u003e \u003cp\u003eTo understand the molecular basis of lifestyle shifts in \u003cem\u003eM. brunneum\u003c/em\u003e isolate K (MbK), we collected conidia from a culture growing in complete medium (CM) and sequenced the transcriptome as a control. We also inoculated fresh CM to initiate saprophytic development (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, top) and \u003cem\u003eM. persicae\u003c/em\u003e adults to initiate pathogenic development (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, bottom), allowing the comparative analysis of the saprophytic and parasitic fungal transcriptomes and the host response during pathogenesis.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003e2.1.1 Differential gene expression during fungal saprophytic development\u003c/h2\u003e \u003cp\u003eFungal RNA-Seq data representing different stages of saprophytic development were evaluated by principal component analysis (PCA), revealing distinct variation along the axis of principal component (PC) 2 (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). We identified 2925 differentially expressed genes (DEGs) differing at least in a single comparison, based on the fold change (FC) criteria log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; |2| and p\u003csub\u003eadj\u003c/sub\u003e \u0026lt; 0.001. Given a total \u003cem\u003eM. brunneum\u003c/em\u003e gene number of 11,595, the DEGs accounted for 25% of all genes (Saud et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Variation was observed between conidia (0 h) and germinated conidia (9 h, 912 DEGs), hyphae (24 h, 1790 DEGs) and mycelia (72 h, 1406 DEGs) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC, top; DEGs summarized in Tables S1\u0026ndash;S3). The entire set of DEGs formed 10 clusters (assigned letters A to J) based on expression patterns during saprophytic development (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). Two groups of clusters showed highly similar expression profiles. The first group comprised clusters F, G and H, and represented genes upregulated during development (mainly expressed in the hyphae and mycelia, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). The second group comprised clusters I and J, and represented genes downregulated during development (i.e., upregulated in the conidia control, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e2.1.2 Differential gene expression during fungal pathogenic development\u003c/h2\u003e \u003cp\u003eGiven that the rate of disease progression varies widely in different aphids following simultaneous infection (Reingold et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), we monitored individual aphids by confocal microscopy and pooled those at similar stages of disease progression rather than specific times post-inoculation for the RNA-Seq samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, bottom). PCA showed a clear separation between the saprophytic and parasitic lifestyles, with directional differences correlated to fungal development in each lifestyle (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Due to low variation between the penetration and germination stages, and between initial hemocoel colonization and massive colonization, these pairs of stages were combined for further analysis and are described as early infection and late infection, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Compared to the conidial control, pathogenic development showed a similar distribution of upregulated and downregulated genes. We identified 4818 DEGs differing at least in a single comparison (~\u0026thinsp;41% of all genes) when using permissive criteria (log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; |1|, p\u003csub\u003eadj\u003c/sub\u003e \u0026lt; 0.05) because these samples contained only a small proportion of fungal reads. To address the bias caused by scarce fungal reads in the conidial adhesion samples compared to the conidial control (0 h), the threshold was set to \u0026gt;\u0026thinsp;0 FPKM. This resulted in 563 DEGs, most of which were upregulated during adhesion. We also identified 1864 and 4294 DEGs when comparing the conidial control to the early and late infection stages, respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD). We also compared pathogenic development to the conidial control and germinated saprophytic conidia in order to identify genes involved in conidial dormancy breaking regardless of the subsequent lifestyle. The resulting 3889 DEGs (~\u0026thinsp;33% of all genes) were used to construct a Venn diagram (p\u003csub\u003eadj\u003c/sub\u003e \u0026lt; 0.05, log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; |1| for adhesion compared to the conidial control and log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; |2| for all other comparisons) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB,C). The comparison revealed 1907 upregulated and 1982 downregulated genes in the parasitic and saprophytic germination (9 h) samples, respectively, compared to the conidial control (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB,C). We detected 1009 DEGs upregulated at all pathogenic stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) and 989 that were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). Also 1549 genes were upregulated in proliferating fungi (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) and 1779 were downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC) compared to the conidial stages. Validation of gene expression by real-time PCR was carried out on selected DEGs (Fig. S1A-B)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e2.1.3 Differential gene expression in aphids during fungal developmental\u003c/h2\u003e \u003cp\u003eThe aphid samples were classified as the uninfected negative control (NC), early infection (a combination of adhesion, germination and penetration), and late infection comprising initial and massive hemocoel colonization (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eE). Among the 17,052 genes in the \u003cem\u003eM. persicae\u003c/em\u003e genome, we detected only 154, 232 and 454 DEGs at the adhesion, early infection and late infection stages, respectively, compared to the NC (log2FC \u0026gt; |1|, p\u003csub\u003eadj\u003c/sub\u003e \u0026lt; 0.05). However, no genes were significantly upregulated in the infected aphids during the early infection stage and only 12 were upregulated during the adhesion stage. Reducing the statistical threshold did not yield significantly different results. We therefore analyzed our data using edgeR to obtain more uniform transcriptome results, yet the proportion of upregulated genes was still significantly higher in the NC aphids (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). Using this analysis, we found 617, 639 and 1215 DEGs when comparing the NC to the adhesion, early infection and late infection stages, respectively (log\u003csub\u003e2\u003c/sub\u003eFC \u0026gt; |0.4|, FDR\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). For further analysis we combined all the early and late disease stages, and also conducted a separate comparison between the adhesion stage and NC aphids. The top-ranking DEGs at each disease stage compared to the NC are summarized in Tables S4\u0026ndash;S6. Many common DEGs were observed during the early and late infection stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD,E). However, more than 80% of the genes upregulated during infection were uniquely expressed during late infection, whereas only a small fraction was upregulated uniquely during early infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD). Similarly, only 5% of the downregulated genes were uniquely downregulated during early infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eE). Validation of gene expression by real-time PCR was carried out on selected DEGs (Fig. S1C-G).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Enriched pathways and ontologies in the fungus and host\u003c/h2\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e2.2.1 Significant pathways and ontologies in fungal saprophytic development\u003c/h2\u003e \u003cp\u003eSignificant conidial metabolic activity was observed in clusters B and IJ (combined based on pattern similarity), representing strongly expressed gene at the conidial stage (0 h) (Fig.\u0026nbsp;4A,B; Table S7). The enriched metabolic pathways included glycolysis and gluconeogenesis (spo00010) based on the upregulation of several alcohol dehydrogenases, galactose catabolism, oxidoreductase activity (GO:0055114) and fatty acid degradation (spo00071) (Fig.\u0026nbsp;4A,B). In these clusters, we observed the enrichment of RNA and DNA binding, together with regulatory elements of transcription (Fig.\u0026nbsp;4A,B; Table S7). Similar enrichment was also observed in cluster E, indicating upregulation in the conidia and mycelia (Table S7). On the other hand, enrichment in clusters C and FGH (combined based on pattern similarity) included ergosterol and fatty acid biosynthesis (Fig.\u0026nbsp;4C,D; Table S7). In these clusters, we observed significant enrichment of translation and ribosome biogenesis instead of transcription and transcriptional regulation. The biosynthesis of secondary metabolites was significantly enriched in all clusters with more than 50 genes (Table S7).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003ch2\u003e2.2.2 Significant pathways and ontologies in fungal pathogenic development\u003c/h2\u003e \u003cp\u003eThe gene groups identified by Venn analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB,C; Table S8) were used to find enriched pathways required for pathogenesis, and to eliminate genes related to saprophytic growth, by the exclusion of germinated conidia during saprophytic development. Similarly, we were able to recognize the common genes and pathways related to fungal proliferation regardless of the developmental lifestyle by excluding the adhesion stage. As expected, among the genes common to proliferating fungi, we observed the enrichment of cell cycle and mitosis pathways (spo04111, GO:0044732, GO:0031028), as well as secondary metabolism (spo01110), glycolysis (spo00010) and sugar metabolism (spo00520, spo00051) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eA; Table S8). RNA regulation was enriched in the conidial control compared to all pathogenic stages (GO: 0000981) (Table S8). Similarly, ribosome biogenesis and cytoplasmic translation were enriched at pathogenic stages and during saprophytic germination (Table S8). Pathways enriched during saprophytic germination included secondary metabolism, riboflavin synthesis (spo00740) and sugar metabolism. GO terms enriched during saprophytic germination included cytoplasmic translation (also found in all proliferating fungi) and aerobic respiration related to energy gain (GO:0009060) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eB; Table S8). On the other hand, early and late infection involved the enrichment of peptidase and oxidation-reduction activities (GO:0004252, GO:0055114) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eD-E, H-I; Table S8). These were not enriched during the adhesion stage, which included chromatin remodeling and ribosome biogenesis (GO:0031011, GO:0060303), as well as tryptophan and fatty acid metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eC,G; Table S8). The early and late infection stages featured unique enriched metabolic pathways compared to the saprophytic stages. This included pentose and glucoronate metabolism (spo00040) at both stages and glyoxylate and dicarboxylate metabolism (spo00630) strongly enriched only at the late infection stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eE,I; Table S8). DEGs common to all pathogenic stages were associated with GO terms such as peptidase activity (GO:0004252, GO:0008233) and catabolic processes (GO:0007039, GO:0009251), whereas the analysis of KEGG pathways revealed the weak enrichment of autophagy (spo04138) (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eF; Table S8).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section3\"\u003e \u003ch2\u003e2.2.3 Enzymatic gene expression during fungal pathogenic development\u003c/h2\u003e \u003cp\u003eThe transcriptomic response of the fungus largely depends on its environment. We found a large set of genes activated upon first encounter with the host, as early as the adhesion stage in the case of one unique chitinase (QLI73536.1) and two phospholipases (QLI71879.1, QLI74668.1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Some of the identified enzymes were constantly expressed, such as chitinase 18 (QLI68859.1) and a lipase (QLI66658.1), suggesting a general role in fungal development and hyphal elongation, whereas others were silenced (QLI74656.1) in comparison to dormant conidia (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). A single lipase (QLI68060.1) was expressed only in the conidia during both dormancy and adhesion. The well-studied hydrophobin gene \u003cem\u003eMad1\u003c/em\u003e (QLI72677.1) was constitutively expressed compared to dormant conidia (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003eA). Further analysis of all predicted proteases in the fungal genome resulted in three main phylogenetic groups: subtilisin Pr1 proteases (10 genes), trypsin Pr2 proteases (11 genes), and subtilisin PR1C proteases (6 genes) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). A single gene predicted to encode Pr1H (QLI67847.1) was separated from the Pr1 group and was constitutively expressed during pathogenic development together with the cuticle-degrading protease (QLI69644.1) and an extracellular subtilisin-like Pr1F (QLI66763.1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). The earliest proteases induced by infection also included a trypsin-like serine protease (QLI70195.1, presumably Pr2) and a single Pr1 subtilisin (QLI172563.1) expressed only during the adhesion stage (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003eB). Another putative Pr1H (QLI65301.1) was constitutively expressed during fungal growth, with the highest expression during the conidial stages (0 h and adhesion). The well-known subtilisin Pr1A (QLI64437.1) was detected only during late pathogenic growth. The trypsin-like protease gene \u003cem\u003ePnmB\u003c/em\u003e (QLI69436.1) was expressed during late fungal development in both the saprophytic and parasitic contexts. Few proteases were overexpressed during saprophytic growth, but exceptions included Pr1G (QLI71439.1) and an aspartic protease (QLI65683.1) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003eB).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section3\"\u003e \u003ch2\u003e2.2.4 Secondary metabolism during saprophytic and pathogenic development\u003c/h2\u003e \u003cp\u003eSecondary metabolic processes were enriched in clusters representing both increasing (Fig.\u0026nbsp;4D) and decreasing (Fig.\u0026nbsp;4A,B) gene expression levels throughout saprophytic development. In contrast, secondary metabolism was enriched during pathogenic development mainly after conidia had germinated (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eG\u0026ndash;I), and the enrichment was more significant at later developmental stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e5\u003c/span\u003eH,I). Specifically, we observed differences in gene expression levels between developmental stages in the context of terpenoid and steroid biosynthesis as well as specific amino acids (e.g., arginine biosynthesis) and toxins (e.g., aflatoxin biosynthesis). We did not detect the unique enrichment of virulence-related metabolites in the parasitic lifestyle.\u003c/p\u003e \u003cp\u003eAntiSMASH analysis of the \u003cem\u003eM. brunneum\u003c/em\u003e genome revealed 55 known and unknown biosynthetic gene clusters (BGCs) dispersed across seven chromosomes (Table S9). The predicted BGCs were combined with the transcriptomic data to compare gene expression levels between the saprophytic and parasitic lifestyles. Two destruxin clusters were predicted on chromosomes 5 and 7 (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003eA,B). The first was divided into two sub-clusters, each containing a non-ribosomal polyketide (NRPK) as the core gene. The first sub-cluster also included the \u003cem\u003eaclP\u003c/em\u003e gene (QLI72085.1), and BLAST analysis using the remaining coding sequences as queries indicated a similarity to \u003cem\u003egliP\u003c/em\u003e, which is required for glitoxin production in \u003cem\u003eAspergillus\u003c/em\u003e spp. The second subcluster contained the gene \u003cem\u003edtxS1\u003c/em\u003e (QLI74679.1), which is required for destruxin synthesis. Interestingly, the first subcluster was strongly upregulated during pathogenesis, but the second was upregulated only during saprophytic growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003eA). We also identified genes responsible for the synthesis of serinocyclin and swainsonine, the former upregulated during saprophytic growth and the latter expressed at the same level in both lifestyles (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003eC,D). A single BGC on chromosome 1, predicted to synthesize eupenifeldin (27% of genes show similarity) or stipitatic acid (28% of genes show similarity), was strongly upregulated during pathogenic development, with individual genes showing 100-fold to more than 30,000-fold increases in expression compared to saprophytic growth (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003eE). These genes were predicted to synthesize citrinin/tropolone, given the presence of a citrinin biosynthesis transcriptional activator gene (\u003cem\u003ectnR\u003c/em\u003e, QLI63578.1) 3.8 kb away from the core gene, with a 1000-fold higher expression level in the parasitic fungus (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e7\u003c/span\u003eE).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Significant pathways and ontologies in \u003cem\u003eM. persicae\u003c/em\u003e during infection\u003c/h2\u003e \u003cp\u003eSignificant differences in gene expression were observed between infected and uninfected aphids at all disease stages, with more genes significantly upregulated in the uninfected aphids. A significant response to fungal infection was observed during fungal adhesion to the aphid cuticle. Only 96 genes were significantly upregulated at this stage but 521 were significantly downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eF). Chitin-related terms were significantly enriched among the upregulated genes during conidial adhesion, whereas hydrolase and oxidoreductase activities were more strongly enriched among the downregulated genes (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003eA). Chitin-related GO terms were also enriched during early infection, whereas the melanization defense response was significantly downregulated (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003eB). The analysis of DEGs revealed that two genes related to flight were upregulated more than 30-fold at the adhesion stage in the alate aphids: \u003cem\u003eflightin\u003c/em\u003e (LOC111036448) and \u003cem\u003etroponin C-like\u003c/em\u003e (LOC111036236). Genes encoding esterase FE4 (LOC111030482) and esterase E4 (LOC111030391) were significantly downregulated during the early infection stages, including fungal adhesion and fungal development on the cuticle (Tables S4, S5).\u003c/p\u003e \u003cp\u003eThe early and late stages of infection differed substantially in terms of fungal growth. In the early stages, fungi develop on the outer surface of the aphid and start to penetrate through the outer integument. In the late stages, fungi develop within the aphid body cavity, reproducing as blastospores in direct contact with the host immune system. The first significant enrichment related to the immune response was observed only in aphids where fungi had already colonized the hemocoel, including GO terms related to heat shock proteins (HSPs) and starvation responses, and KEGG pathways associated with endocytosis, longevity, autophagy and MAPK signaling (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003eC,D). More specific immune response enrichment was observed in aphids during late infection compared to early infection. Whereas early infection was enriched for terms related to chitin, late infection also included enrichment for JNK signaling and wound healing (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003eE). Early infection was associated mainly with proteasome-related and metabolic pathways in KEGG, whereas immune response pathways were dominant at the late infection stages (Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e8\u003c/span\u003eF).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Discussion","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Dormancy breaking and epigenetic regulation of lifestyle shifting\u003c/h2\u003e \u003cp\u003eEntomopathogenic fungi such as \u003cem\u003eM. brunneum\u003c/em\u003e tend to develop as either pathogens or saprophytes, commencing at the conidial stage, depending on environmental signals. Our results demonstrated the initial process of environmental adaptation and dormancy breaking, starting with the transcription of specific genes in the dormant conidia in response to environmental cues (in this case, the different carbon sources available in the CM or on the insect cuticle) and ultimately leading to protein synthesis and fungal growth. These results support the hypothesis that conidia prepare for environmental conditions by transcription while delaying translation (Teertstra et al., \u003cspan citationid=\"CR100\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). When removed from the conidiophore, conidia are ready to break dormancy and initiate development, which includes an increase in protein synthesis (Hagiwara et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2016\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInterestingly, during mycelial development on CM, we observed the upregulation of transcription, including genes encoding transcription factors. Conidia (0h) and mycelia (72h) show similarities in gene expression because conidiophore differentiation or conidiogenesis occur already after 72 h (Jenkins and Prior, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e1993\u003c/span\u003e). Transcriptional reprogramming may therefore be required at these two time points. On the other hand, the enrichment of regulatory factors in mycelia reflect environmental changes sensed by the fungus, such as density and nutrient availability.\u003c/p\u003e \u003cp\u003eAs expected, we observed significant differences between the two lifestyles in terms of enzymes and secondary metabolites. We collected conidia from CM with no previous adaptation to a parasitic lifestyle, thus pathogenicity-related genes were not expressed during the conidial stage. RNA synthesis in the conidia did not reinforce a specific lifestyle, but instead facilitated general fungal growth. However, when the fungi sense a host, gene expression must switch to the parasitic setting (Mukherjee and Vilcinskas, \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). We propose that epigenetic regulation based on chromatin remodeling plays a significant role during this lifestyle shift, as previously shown in yeast lifestyle shifting (Bao and Shen, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The Ino80, NuA4 and SWR1 complexes were previously shown to regulate lifestyle shifting in yeast, such as the shift to hyphal growth (Wang et al., \u003cspan citationid=\"CR113\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). During the adhesion stage, we observed the expression of a gene related to conidiation in \u003cem\u003eA. flavus\u003c/em\u003e (Chang et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and a cell differentiation gene encoding a member of the CCR4-NOT complex, which regulates the cell cycle during normal growth (Cotobal et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Although \u003cem\u003eM. brunneum\u003c/em\u003e does not have a sexual reproduction mode (St Leger and Wang, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), early adhesion is a decision-making point for further development. Dormancy breaking and the shift from saprophytic to pathogenic development may therefore be regulated to some extent by this essential complex, although this must be confirmed in further experiments (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Our data suggest that conidia prepare for the sensed environment, in agreement with previous studies (Earl Kang et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Hagiwara et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Krach et al., \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Interestingly, conidia begin to express genes and store mRNA needed for subsequent growth in the sensed environment even before detachment from the conidiophore or dormancy (Wang et al., \u003cspan citationid=\"CR112\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The equivalent shift from parasitic to saprophytic may shed light on the molecular basis of lifestyle shifting.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Protease gene expression may explain the plasticity of \u003cem\u003eM. brunneum\u003c/em\u003e lifestyles\u003c/h2\u003e \u003cp\u003eSubtilisin-like (Pr1) and trypsin-like (Pr2) proteases are known to be involved in the pathogenicity of \u003cem\u003eMetarhizium\u003c/em\u003e spp. because they are required for cuticle penetration and nutrient acquisition (Bagga et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; St Leger et al., \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e1996\u003c/span\u003e). Conidia secrete proteases even before germination, which may facilitate the early stages of infection (Leger et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e1991\u003c/span\u003e). We have demonstrated that \u003cem\u003eM. brunneum\u003c/em\u003e encodes a large number of trypsin-like Pr2, subtilisin Pr1, and subtilisin Pr1C proteases that are modulated in an orchestrated manner throughout development (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e). We found that a single trypsin-like serine protease was expressed solely during adhesion, whereas two Pr1 proteases (putative Pr1F and Pr1H) were expressed during adhesion but did not shut down at the start of germination, suggesting a further role in pathogenicity. However, Pr1F proteases in \u003cem\u003eB. bassiana\u003c/em\u003e have no role in pathogenicity and are assumed to be evolutionary remnants (Gao et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Pr1F was reported to be expressed rarely in \u003cem\u003eM. anisopliae\u003c/em\u003e, but this may reflect the use of an less sensitive detection method (Bagga et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). We observed the expression of Tryp8 during late pathogenic and saprophytic development, similar to the trypsin-like serine-protease identified in the entomopathogenic fungus \u003cem\u003eZoophthora radicans\u003c/em\u003e (order Entomophtorales), which plays a role in pathogenesis but not host specificity (Xu et al., \u003cspan citationid=\"CR118\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). A similar protease was also detected in \u003cem\u003ePandora neoaphidis\u003c/em\u003e (Entomophtorales), which infects aphids (Grell et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). The best-studied Pr1 protease is \u003cem\u003eM. anisopliae\u003c/em\u003e Pr1A, which facilitates cuticle penetration (Bagga et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Even so, a Pr1A mutant caused mortality in greater wax moth (\u003cem\u003eGalleria mellonella\u003c/em\u003e) larvae similarly to the wild-type strain (Wang et al., \u003cspan citationid=\"CR111\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). We did not identify Pr1A among the abundant proteases expressed during \u003cem\u003eM. brunneum\u003c/em\u003e pathogenic development. Moreover, \u003cem\u003eM. anisopliae\u003c/em\u003e strains differing in Pr1 and Pr2 activity did not show correlation between protease activity and mortality (Rosas-Garc\u0026iacute;a et al., \u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Different fungal strains and isolates may express diverse proteases as virulence factors, causing differences in performance against particular susceptible hosts (Vilcinskas, \u003cspan citationid=\"CR108\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). In agreement with our results, a previous study showed neither \u003cem\u003ePr1\u003c/em\u003ea nor \u003cem\u003ePr1\u003c/em\u003eb were expressed when \u003cem\u003eG. mellonella\u003c/em\u003e was infected with \u003cem\u003eM. brunneum\u003c/em\u003e (Grizanova et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Finally, only one of the two \u003cem\u003ePr1H\u003c/em\u003e-like genes we detected was constitutively expressed during fungal growth, with the highest expression during the saprophytic conidia and pathogenic adhesion stage. This may therefore be the endocellular Pr1 of the MbK isolate (Bagga et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). The second Pr1H-like protease may be a pathogenicity-related peptidase rather than an endopeptidase because it was expressed exclusively during pathogenic development.\u003c/p\u003e \u003cp\u003eWe used a GFP-expressing strain of \u003cem\u003eM. brunneum\u003c/em\u003e to correlate fungal gene expression with particular fungal developmental stages within the host. For the first time, we observed gene expression during fungal adhesion \u003cem\u003ein vivo\u003c/em\u003e before any germination. We also identified shared and unique pathways between the saprophytic and parasitic lifestyles. We conclude that conidia produced during saprophytic growth in CM have no advantage in pathogenic development and require subsequent adaptation. Further experiments should focus on the conidia produced during pathogenesis to determine which adaptations mediate virulence.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e\u003cb\u003e3.3. BGCs related to secondary metabolism expressed during saprophytic and pathogenic development suggest active biofeedback processes\u003c/b\u003e\u003c/h2\u003e \u003cp\u003eFungal BGCs responsible for the synthesis of secondary metabolites encode core enzymes as well as transporters and regulators (Moln\u0026aacute;r et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The synthesis of secondary metabolites released during fungal development (Iwanicki et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) is related to environmental adaptation, interspecific competition and virulence factors (Chatterjee et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Moln\u0026aacute;r et al., \u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Vilcinskas et al., \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). \u003cem\u003eM. anisopliae\u003c/em\u003e was previously shown to secrete secondary metabolites during growth on the host cuticle (Wang et al., \u003cspan citationid=\"CR110\" class=\"CitationRef\"\u003e2005\u003c/span\u003e), but secondary metabolites produced during adhesion have not been assessed before. \u003cem\u003eB. bassiana\u003c/em\u003e secondary metabolites are mainly expressed when the fungus proliferates in the hemocoel (Lobo et al., \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe found that most of the predicted BGCs expressed core enzymes and transporters in at least one of the fungal lifestyles (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Our previous results showed that diverse secondary metabolites are secreted by the MbK isolate (Reingold et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). One of the best-known \u003cem\u003eMetarhizium\u003c/em\u003e secondary metabolites is destruxin, which facilitates the pathogenicity of \u003cem\u003eM. anisopliae\u003c/em\u003e by preventing the attachment of hemocytes to fungal propagules, thus inhibiting phagocytosis (Pal et al., \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Sowjanya Sree et al., \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Vilcinskas et al., \u003cspan citationid=\"CR109\" class=\"CitationRef\"\u003e1997\u003c/span\u003e). Fascinatingly, we found that destruxin was expressed at only low levels in conidia samples during saprophytic growth and not at all during pathogenesis. In agreement, \u003cem\u003eM. brunneum\u003c/em\u003e destruxin activity was elevated in cadavers (Bekker et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), which were not assessed in our study.\u003c/p\u003e \u003cp\u003eTwo other known \u003cem\u003eMetarhizium\u003c/em\u003e secondary metabolites, namely serinocyclin (Gibson et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) and swainsonine, were also identified in our study. The swainsonine core gene was expressed during saprophytic and pathogenic growth, whereas serinocyclin-related gene expression was only detected during saprophytic development. This agrees with our previous results showing both metabolites present during saprophytic growth in \u003cem\u003eM. brunneum\u003c/em\u003e (Reingold et al., \u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The role of these metabolites in fungal pathogenicity is unclear (Cook et al., 2017; Moon et al., 2008; Sbaraini et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) although sublethal effects have been reported in mosquitoes (Krasnoff et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2007\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe detected the expression of genes associated with other secondary metabolites that are not known to facilitate \u003cem\u003eMetarhizium\u003c/em\u003e virulence. For example, \u003cem\u003ePenicillium citrinum\u003c/em\u003e produces a mycotoxin known as citrinin, which inhibits the synthesis of aflatoxin by \u003cem\u003eA. parasiticus\u003c/em\u003e (Ichinomiya et al., \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). In \u003cem\u003eMetarhizium\u003c/em\u003e, similar genes were predicted in a tropolone/citrinin BGC and were upregulated during early pathogenic development (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e), but their virulence was not assessed (Sbaraini et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This cluster was also expressed during the pathogenic development of \u003cem\u003eM. anisopliae\u003c/em\u003e, but the fold change compared to saprophytic growth was lower than in our study (Sbaraini et al., \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). We hypothesize that this BGC is pathogenic or at least nonessential for saprophytic growth in rich media.\u003c/p\u003e \u003cp\u003eFinally, a putative BGC for shearinine D was strongly expressed during pathogenic growth, with the core enzyme responsible for the synthesis of lolitrem B. The synthesis of this compound in two endophytic fungi showed high insecticidal activity toward aphids (Collinson et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, a strain without lolitrem B also caused significant mortality, indicating this compound must act with others to exert an insecticidal effect. Interestingly, peramine, which does not affect aphids (Collinson et al., \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), was downregulated during pathogenic development in our study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Fungal infection causes a cascade of responses in aphids\u003c/h2\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e3.4.1. The fast and furious cuticular response does not inhibit the infection\u003c/h2\u003e \u003cp\u003eThe first level of arthropod defense against fungal pathogens is the cuticle as a physical barrier, followed by humoral and cellular immune responses (Vilcinskas and G\u0026ouml;tz 1999). We observed the massive upregulation of genes encoding cuticle proteins as one of the only means to promote wound repair during fungal infection (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e). \u003cem\u003eM. persicae\u003c/em\u003e has soft and rigid cuticle proteins featuring chitin-binding sites RR-1 and RR-2, respectively (Dombrovsky et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2007\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2003\u003c/span\u003e). The soft cuticle is easier for fungi to penetrate (Butt et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Harder cuticle proteins containing the RR-2 domain were upregulated during fungal infection in this study, possibly increasing cuticle sclerotization as a defense mechanism (Dombrovsky et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Iconomidou et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Koganemaru et al., \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The strongest upregulation of cuticle protein genes in this study occurred during the earliest infection stages, before fungal penetration. This is an effective defense and evasion mechanism in insects in response to fungal infection (Xing et al., \u003cspan citationid=\"CR117\" class=\"CitationRef\"\u003e2017\u003c/span\u003e), even though it is ultimately unsuccessful (Reingold et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). The strong upregulation of cuticle proteins has been observed in previous studies, sometimes as the most prominent response to fungal pathogens (Dongxu et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Li et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Yu et al., \u003cspan citationid=\"CR122\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Cuticle proteins are also upregulated during molting and development (Charles, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). However, these aspects were not considered in our study because we only used adult aphids.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e3.4.2. Recognition of fungi breaching the cuticular barrier\u003c/h2\u003e \u003cp\u003eIn \u003cem\u003eDrosophila melanogaster\u003c/em\u003e, the Gram-negative binding protein (GNBP) detects both Gram-positive and fungal invaders by interacting with the peptidoglycan receptor protein (PGRP) to activate the Toll and IMD pathways (Gottar et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). However only two \u003cem\u003eGNBP\u003c/em\u003e genes are present in aphids (named \u003cem\u003eGNBP1\u003c/em\u003e and \u003cem\u003eGNBP2\u003c/em\u003e in \u003cem\u003eAcyrthosiphon pisum\u003c/em\u003e) (Gerardo et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The \u003cem\u003eGNBP3\u003c/em\u003e gene, which detects fungi in \u003cem\u003eD. melanogaster\u003c/em\u003e (Gottar et al., \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2006\u003c/span\u003e), is not present in aphids, which also lack a \u003cem\u003ePGRP\u003c/em\u003e gene, suggesting that fungi are detected by GNBP1 (Gerardo et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Ye et al., \u003cspan citationid=\"CR121\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In \u003cem\u003eM. persicae\u003c/em\u003e, BLAST analysis revealed two \u003cem\u003eGNBP\u003c/em\u003e genes, both similar to \u003cem\u003eGNBP2\u003c/em\u003e (LOC111036217 and LOC111031217). We found that LOC111036217 was significantly downregulated in aphids during late infection, whereas LOC111031217 was not differentially expressed. The Toll pathway was also upregulated in infected aphids but the phenoloxidase pathway was significantly downregulated during infection.\u003c/p\u003e \u003cp\u003eA comparison between early and late infection enabled us to detect the shift in the aphid response. The main early response involved cuticle proteins accompanied by lysosome, phagosome and proteasome activities, whereas hemocoel colonization during late infection triggered the overexpression of immune response pathways. The main enriched pathway was longevity (mediated by FoxO and HSPs) together with the JNK signaling, endocytosis and wound healing pathways, meaning that cuticle protein expression was ultimately replaced by other defense strategies (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e). Autophagy was observed in \u003cem\u003eG. mellonella\u003c/em\u003e during fungal infection as part of the hemocyte response (Kazek et al., \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Autophagy was initially thought to remove endogenous waste materials, but was later shown to also eliminate cell-borne pathogens (Kuo et al., \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The enrichment of autophagy in our study may reflect the fungal degradation of host organelles targeted for destruction or a role in the direct elimination of fungal propagules by phagocytosis (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section3\"\u003e \u003ch2\u003e3.4.3. Fight not flight?\u003c/h2\u003e \u003cp\u003eThe activation or suppression of early-response genes is essential for host\u0026ndash;pathogen interactions. We found that the early response was insufficient to overcome infection, which may reflect the suppression of genes known to participate in detoxification and fungal resistance encoding E4 and FE4 esterases, glutathione S-transferase, and UDP-glucuronosyltransferase (Bilal et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Field and Devonshire, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e1998\u003c/span\u003e; Xia et al., \u003cspan citationid=\"CR115\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Conversely, two cathepsin B genes were upregulated in correlation with fungal infection in our study, as previously reported (Grell et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), and these may indeed act as detoxifying enzymes (Lan et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOxidative stress in the insect host during fungal infection induces an immune response (Butt et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The gonadotropin-releasing hormone receptor, which is known to activate immune responses, was significantly downregulated in the infected aphids. However, the hormone (not the receptor) was upregulated in \u003cem\u003eA. pisum\u003c/em\u003e in response to stress (Jedlička et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) and the receptor was downregulated in cockroaches during oxidative stress (Huang et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Phenoloxidases were also downregulated during our infection experiments, in contrast to \u003cem\u003eA. pisum\u003c/em\u003e infected with \u003cem\u003eB. bassiana\u003c/em\u003e (Xu et al., \u003cspan citationid=\"CR119\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Interestingly, phenoloxidase gene expression in aphids infected with \u003cem\u003ePandora\u003c/em\u003e spp. was induced 48 h post-inoculation, with no significant expression before or after (Parker et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Although our sample collection was based on fungal developmental stages rather than time post-inoculation (to ensure accuracy), no such expression was detected at any disease stage in our study.\u003c/p\u003e \u003cp\u003eThe cellular immune response in insects includes phagocytosis and encapsulation by hemocytes when pathogens are recognized (Strand, \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). The humoral immune system is based mainly on the Toll and IMD signaling pathways (Ali Mohammadie Kojour et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The Toll pathway is the main mediator of antifungal responses, activating the production of antimicrobial peptides (AMPs) during hemocoel invasion (Gerardo et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Lu and St. Leger, \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). However, aphids lack key components of the Toll and IMD pathways as found in \u003cem\u003eDrosophila\u003c/em\u003e spp. (Gerardo et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Vilcinskas, \u003cspan citationid=\"CR107\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). As expected, the Toll and IMD pathways (KEGG api04624) were induced only when fungal propagules were present in the hemocoel and not during penetration. Interestingly, there are four genes in the aphid genome encoding Sp\u0026auml;tzel (Spz), the Toll ligand and activator, but only two of them were annotated as part of the Toll pathway in KEGG. The \u003cem\u003espz3\u003c/em\u003e gene was not annotated as part of the Toll pathway, and was the only \u003cem\u003espz\u003c/em\u003e gene significantly upregulated during the fungal colonization of the hemocoel. We therefore propose that Spz3 activates the Toll receptor during the infection of \u003cem\u003eM. persicae\u003c/em\u003e by \u003cem\u003eM. brunneum\u003c/em\u003e. The multiple duplications of Toll pathway genes in the aphid genome may interfere with computational predictions, especially those based on comparisons in different organisms (Lima et al., \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Interestingly, aphid genomes are almost completely devoid of AMP genes suggesting that the defense mechanisms activated by Toll are probably enzyme based (Altincicek et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Gerardo et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2010\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe IMD pathway was also upregulated, specifically the AP-1 transcription factor that binds to the promoters of genes needed for wound repair in \u003cem\u003eDrosophila\u003c/em\u003e spp. (Mace et al., \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). However, the known target gene of this pathway \u0026ndash; \u003cem\u003egrainyhead-like\u003c/em\u003e (\u003cem\u003egrh\u003c/em\u003e) \u0026ndash; was not differentially expressed in our system. Moreover, the phenoloxidase genes responsible for the melanization response were strongly downregulated in the infected aphids. This weak response may reflect the presence of endosymbiont activity in the aphids, which is known to modify the immune response (Nichols et al., \u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In this regard, no \u003cem\u003eRegiella\u003c/em\u003e spp. were found in our aphid colony, but \u003cem\u003eRickettsia\u003c/em\u003e spp. and other unspecified Enterobacteriaceae were identified by 16S rRNA sequencing (data not shown). This is not the first report of a weak aphid response to entomopathogenic fungi (Grell et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2011\u003c/span\u003e) accompanied by costly effects on life-history traits (Barribeau et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Reingold et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section3\"\u003e \u003ch2\u003e3.4.4. Flight not fight?\u003c/h2\u003e \u003cp\u003eThe \u003cem\u003eflightin\u003c/em\u003e gene appears to be involved in wing formation and flight muscle development in insects given that \u003cem\u003eD. melanogaster\u003c/em\u003e null mutants feature ultrastructural defects in the flight muscles and impaired flight (Vigoreaux et al., \u003cspan citationid=\"CR105\" class=\"CitationRef\"\u003e1998\u003c/span\u003e). Similar impairments were observed when the \u003cem\u003eflightin\u003c/em\u003e gene was silenced in the aphid \u003cem\u003eA. pisum\u003c/em\u003e (Chang et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In planthoppers, the \u003cem\u003eflightin\u003c/em\u003e gene cooperates with \u003cem\u003etroponin C\u003c/em\u003e and others to control wing dimorphism and is essential in long-winged forms (Xue et al., \u003cspan citationid=\"CR120\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Interestingly, aphids infected with entomopathogenic fungi produce a higher proportion of winged offspring (Hatano et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). The high expression levels of \u003cem\u003eflightin\u003c/em\u003e and \u003cem\u003etroponin C\u003c/em\u003e genes in our study were in correlation to early fungal infection in aphids, this might suggest a transgenerational evasion strategy (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe transgenerational effects of chemicals that cause wing defects in \u003cem\u003eD. melanogaster\u003c/em\u003e were recently shown to be regulated by histone methylation (Sun et al., \u003cspan citationid=\"CR99\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Transgenerational inheritance in insects may involve a vast array of epigenetic marks (Mukherjee and Dobrindt, \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). More importantly, exposure to pathogens may lead to resistance in the offspring, also mediated by epigenetic marks (Gegner et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Immune priming can involve the direct maternal translocation of the pathogen or pathogenic elements (Freitak et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Vilcinskas, \u003cspan citationid=\"CR106\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Interestingly, genes correlated with transgenerational wing formation in aphids (Vellichirammal et al., \u003cspan citationid=\"CR104\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) were also upregulated in our infected aphids, but the fold change was not significant. This lack of significance may reflect the pooling of mothers and offspring, which would obscure significant changes that occur in the embryos during wing formation.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.5. Conclusions\u003c/h2\u003e \u003cp\u003eEntomopathogenic fungi such as \u003cem\u003eM. brunneum\u003c/em\u003e have evolved the ability to survive as saprophytes (which can therefore be cultured in artificial media), as endophytes in plants, and as parasites that infect insects directly via their cuticle. We proposed that the switch from a saprophytic to a parasitic life style must be accompanied by fundamental transcriptomic reprogramming. Using a GFP-expressing fungal strain and live imaging of disease progression we collected accurate disease stages on \u003cem\u003eMyzuys persicae\u003c/em\u003e and combined high-throughput RNA-Seq analysis of \u003cem\u003eM. brunneum\u003c/em\u003e grown also \u003cem\u003ein vitro\u003c/em\u003e. we identified a comprehensive set of genes that are modulated during the switch from saprophytic to pathogenic development. We observed highly orchestrated transcriptomic reprogramming involving genes encoding proteases and BGCs producing secondary metabolites operating as virulence factors during adhesion and germination of conidia on the insect cuticle and during cuticle penetration and pathogenesis within the host insect. Our experimental setup also allowed us to analyze transcriptomic reprogramming in aphid hosts in response to fungal infection. This is the first report to examine the specific disease stages of the fungal pathogen \u003cem\u003ein vivo\u003c/em\u003e, and to investigate the shift in gene expression at the stage of fungal adhesion, as determined by live imaging. We demonstrated that the aphid responds to the fungal pathogen at the earliest stage of their encounter: conidial adhesion. The significant changes provide insight into the aphid defense strategy, which ultimately fails. We propose an evasion strategy, based on increasing the proportion of alate offspring, which is mediated by flight-related gene expression.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Materials and methods","content":"\u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Fungal culture conditions\u003c/h2\u003e \u003cp\u003e \u003cem\u003eMetarhizium brunneum\u003c/em\u003e isolate MbK constitutively expressing the GFP reporter gene was cultured on Sabouraud dextrose agar (SDA, Difco) plates at 28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C in the dark (defined as complete medium, CM). For saprophytic growth \u003cem\u003ein vitro\u003c/em\u003e, conidia were harvested from three replica plates (14 days old) into 0.01% Triton X-100. Conidial suspensions were transferred through two layers of gauze pads to exclude hyphae. The concentration was measured using a hemocytometer and adjusted to 10\u003csup\u003e8\u003c/sup\u003e/ml. A 100-\u0026micro;l sample of each conidial suspension was flash-frozen in liquid nitrogen with TRIzol reagent (Thermo Fisher Scientific, USA) and stored at \u0026minus;\u0026thinsp;80\u0026deg;C (0 h conidial control; Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Media inoculation for transcriptomic profiling during saprophytic growth\u003c/h2\u003e \u003cp\u003eConidial suspensions were plated on CM (10\u003csup\u003e6\u003c/sup\u003e conidia/plate) and samples were harvested from four plates after 9 h (almost all conidia germinated), 24 h (long hyphae) and 72 h (dense hyphae, white mycelial layer) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, top) and pooled in 1% Triton X-100. Samples were precipitated at 8000 \u0026times; g for 5 min, suspended in TRIzol reagent, and flash-frozen in liquid nitrogen for storage at \u0026minus;\u0026thinsp;80\u0026deg;C. Three sets of conidial samples were collected from different maternal plates at each time point. A single sample at 9 h (germination) yielded RNA of insufficient quality and was excluded from further analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Aphid inoculation for transcriptomic profiling during pathogenesis\u003c/h2\u003e \u003cp\u003eOrganic pepper plants (\u003cem\u003eCapsicum annuum\u003c/em\u003e cv Maor) were used to rear \u003cem\u003eM. persicae\u003c/em\u003e in insect-proof cages maintained at 25\u0026thinsp;\u0026plusmn;\u0026thinsp;2\u0026deg;C and 60% relative humidity with a 12-h photoperiod (Reingold et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Adult aphids were inoculated with \u003cem\u003eM. brunneum\u003c/em\u003e MbK in a fine sieve by soaking in a solution of 1\u0026times;10\u003csup\u003e8\u003c/sup\u003e conidia/ml for 8 s, before drying on a paper towel and careful transfer to pepper leaves embedded in 2% agarose. Inoculated aphids were incubated in controlled chambers at 28\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5\u0026deg;C and 70% relative humidity with a 12-h photoperiod (Reingold et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Live imaging during pathogenic development\u003c/h2\u003e \u003cp\u003eDisease progression was monitored in live aphids by confocal microscopy (Reingold et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Live aphids were placed on a cover slip in a water drop and were then separated into tubes based on the latest disease stage: adhesion (no germinated conidia detected), germination (no penetration detected), penetration (including only appressorium formation and penetration peg, without hemocoel colonization), hemocoel colonization (approximately half of the body cavity), and fully colonized hemocoel (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA, bottom). All aphids were live and motile. Collected aphids were flash-frozen in liquid nitrogen with TRIzol reagent, and stored at \u0026minus;\u0026thinsp;80\u0026deg;C. We prepared four samples of 25 non-infected aphids, two samples (50 aphids each) demonstrating conidial adhesion to the cuticle, 66 and 67 aphids with germinated conidia, 24 aphids demonstrating penetration, 25 and 24 aphids demonstrating initial hemocoel colonization, and two samples of 24 aphids each with massive hemocoel colonization.\u003c/p\u003e \u003cp\u003eConidial adhesion samples were prepared in which the conidia showed no germination on the aphid cuticle. Two separate pools were sequenced in aphids with various quantities of adhered conidia. Two \u0026ldquo;germination\u0026rdquo; samples consisted of aphids with mainly germinated conidia and fungal growth on the outer cuticle without appressorium formation or penetration, but also non-germinated conidia to some extent. A single penetration sample included aphids exhibiting fungal appressorium formation and penetration pegs, without development within the hemocoel. The later fungal developmental stages included aphids with fungal hemocoel colonization. These were categorically separated into two arbitrary groups of less than or more than half of the aphid body colonized by fungi as visualized by confocal microscopy, termed initial hemocoel colonization and full hemocoel colonization (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, bottom).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e4.5 RNA extraction and high-throughput sequencing\u003c/h2\u003e \u003cp\u003eTotal RNA was extracted from harvested conidia, germinated conidia and hyphae (designated saprophytic growth), and infected aphids (designated pathogenic growth, parasitic lifestyle) using TRIzol reagent. Briefly, samples were thawed on ice, then homogenized using metal beads in a Geno/Grinder at 6500 oscillations/min for 3 min. Samples were then phase separated at 8000 \u0026times; g for 15 min at 4\u0026deg;C, and the aqueous phase was transferred to an RNA Clean \u0026amp; Concentration Column (Zymo, USA) followed by in-column DNase I treatment. Eluted RNA was measured using a Nanodrop spectrophotometer, and its integrity was assessed by 1% agarose gel electrophoresis. RNA samples were qualified using a Bioanalyzer 2100 (Agilent Technologies, USA) at BGI Genomics (China). Libraries were constructed using poly-A capture, and paired-end 150-bp reads were sequenced on DNA nanoball (DNB) platform at BGI Genomics.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Bioinformatic analysis\u003c/h2\u003e \u003cp\u003e \u003cb\u003e4.6.1 Fungal transcriptome\u003c/b\u003e. We mapped\u0026thinsp;~\u0026thinsp;2.1 Gb of paired-end reads (average 88.8\u0026nbsp;million per sample) to the reference genome of \u003cem\u003eMetarhizium brunneum\u003c/em\u003e 4556 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/assembly/GCA_013426205.1/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/assembly/GCA_013426205.1/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) using STAR v2.7.1a (Dobin et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Gene abundance was estimated using Cufflinks v2.2 (Trapnell et al., \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) combined with gene annotations from the NCBI nr database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/013/426/205/GCA_013426205.1_ASM1342620v1/GCA_013426205.1_ASM1342620v1_genomic.gff.gz\u003c/span\u003e\u003cspan address=\"https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/013/426/205/GCA_013426205.1_ASM1342620v1/GCA_013426205.1_ASM1342620v1_genomic.gff.gz\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). PCA plots and heat maps were prepared and visualized using R Bioconductor, accessed on 15 May 2022 (Gentleman et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Gene expression values were computed as fragments per feature kilobase per million reads mapped (FPKM). Differential expression was analyzed using the DESeq2 R package (Love et al., \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2014\u003c/span\u003e) with a two-fold-change cutoff and a statistical significance of \u0026le;\u0026thinsp;0.05 after false discovery correction (Benjamini and Hochberg, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Genes were hierarchically clustered based on FPKM values and the clusters were extracted using R scripts. Venn diagrams were constructed using Venny 2.0 online (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bioinfogp.cnb.csic.es/tools/venny/\u003c/span\u003e\u003cspan address=\"http://bioinfogp.cnb.csic.es/tools/venny/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Oliveros, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). We used KOBAS 3.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://kobas.cbi.pku.edu.cn/kobas3/?t=1\u003c/span\u003e\u003cspan address=\"http://kobas.cbi.pku.edu.cn/kobas3/?t=1\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to find statistically significant enrichment of differentially expressed genes in the KEGG pathway database and Gene Ontology (GO) categories (Xie et al., \u003cspan citationid=\"CR116\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Phylogenetic analysis of protease genes within the \u003cem\u003eM. brunneum\u003c/em\u003e genome was conducted using PhyML online (Guindon et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). BGCs were predicted using fungal antiSMASH v6.1.1 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://fungismash.secondarymetabolites.org/#!/start\u003c/span\u003e\u003cspan address=\"https://fungismash.secondarymetabolites.org/#!/start\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Blin et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec30\" class=\"Section3\"\u003e \u003ch2\u003e4.6.2 Aphid transcriptome\u003c/h2\u003e \u003cp\u003eThe paired-end reads were mapped to the reference genome of Myzus persicae (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/datasets/genome/GCF_001856785.1/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_001856785.1/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) using STAR software (v2.7.1a) (Dobin et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Gene abundance was estimated using Cufflinks (v. 2.2) (Trapnell et al., \u003cspan citationid=\"CR101\" class=\"CitationRef\"\u003e2010\u003c/span\u003e) combined with gene annotations from the NCBI database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/001/856/785/GCF_001856785.1_MPER_G0061.0/GCF_001856785.1_MPER_G0061.0_genomic.gff.gz\u003c/span\u003e\u003cspan address=\"https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/001/856/785/GCF_001856785.1_MPER_G0061.0/GCF_001856785.1_MPER_G0061.0_genomic.gff.gz\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Gene expression values were computed as fragments per feature kilobase per million reads mapped (FPKM). Differential expression analysis was performed with the edgeR R package (Robinson et al. \u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Genes\u0026thinsp;\u0026ge;\u0026thinsp;2-fold differentially expressed with a false discovery-corrected statistical significance of at most 0.05 were considered differentially expressed (Benjamini and Hochberg, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e1995\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec31\" class=\"Section2\"\u003e \u003ch2\u003e4.7 cDNA synthesis and real-time PCR validation\u003c/h2\u003e \u003cp\u003eRNA samples (500 \u0026micro;l) were reverse transcribed using the qPCRBIO cDNA Synthesis Kit and oligo dT primers (PCRBIOSYSTEMS, UK). The cDNA was used for real-time PCR analysis with Fast SYBR Green Master Mix (Thermo Fisher Scientific) and \u003cem\u003egpd\u003c/em\u003e as a reference gene (Fang and Bidochka, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2006\u003c/span\u003e). Relative expression levels were calculated using the 2\u003csup\u003e\u0026minus;ΔΔCt\u003c/sup\u003e method (Livak and Schmittgen, \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2001\u003c/span\u003e). Statistical significance was determined using a standard least squares restricted maximum likelihood (REML) test, followed by \u003cem\u003epost hoc\u003c/em\u003e comparison with Student\u0026rsquo;s ttest or Tukey\u0026rsquo;s test in JMP Pro v16.0.0 (SAS Institute, USA). Primers were designed using Primer3 (Table S10) and efficiency was determined by constructing standard curves.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll co-authors have approved to participate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research was funded by the German-Israeli Foundation (GIF) Young Scientists\u0026rsquo; Program, Project No. I-1541-500.15/2021 to DM and AV.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eVR, AV and DM wrote the manuscript. VR, SM and EB collected the fungal and aphid materials for transcriptomics. SH did the Real-time qPCR of gene expression validation. VR and AF analysed the data by bioinformatics.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank Dr. Richard M Twyman for the professional editing of the manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;Data Availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data of the study is fully accessible in the public repository NCBI under bioprojects: PRJNA1106639; PRJNA1106641. \u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAli Mohammadie Kojour, M., Han, Y.S., Jo, Y.H., 2020. An overview of insect innate immunity. Entomological Research 50, 282\u0026ndash;291. https://doi.org/10.1111/1748-5967.12437\u003c/li\u003e\n\u003cli\u003eAltincicek, B., Gross, J., Vilcinskas, A., 2008. 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Insect Biochemistry and Molecular Biology 161, 104003. https://doi.org/10.1016/j.ibmb.2023.104003\u003c/li\u003e\n\u003cli\u003eZimmermann, G., Papierok, B., Glare, T., 1995. Elias Metschnikoff, Elie Metchnikoff or Ilya Ilich Mechnikov (1845-1916): A Pioneer in Insect Pathology, the First Describer of the Entomopathogenic Fungus Metarhizium anisopliae and How to Translate a Russian Name. Biocontrol Science and Technology 5, 527\u0026ndash;530. https://doi.org/10.1080/09583159550039701\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Mycopathogen, Host-pathogen interaction, Transcriptomic, Live imaging, Fungal infection, Early infection","lastPublishedDoi":"10.21203/rs.3.rs-4587553/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4587553/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThe fungus \u003cem\u003eMetarhizium brunneum\u003c/em\u003e has evolved a remarkable ability to switch between different lifestyles. It develops as a saprophyte, an endophyte establishing mutualistic relationships with plants, or a parasite, enabling its use for the control of insect pests such as the aphid \u003cem\u003eMyzus persicae\u003c/em\u003e. We tested our hypothesis that switches between lifestyles must be accompanied by fundamental transcriptional reprogramming, reflecting adaptations to different environmental settings.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWe combined high throughput RNA sequencing of \u003cem\u003eM. brunneum\u003c/em\u003e in vitro and at different stages of pathogenesis to validate the modulation of genes in the fungus and its host during early infection. In agreement with our hypothesis, we observed transcriptional reprogramming in \u003cem\u003eM. brunneum\u003c/em\u003e following conidial attachment, germination on the cuticle, and early-stage growth within the host. This involved the upregulation of genes encoding degrading enzymes and gene clusters involved in synthesis of secondary metabolites that act as virulence factors. The transcriptional response of the aphid host included the upregulation of genes potentially involved in antifungal activity, but antifungal peptides were not induced. We also observed the induction of a host flightin gene, which may be involved in wing formation and flight muscle development.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe switch from saprophytic to parasitic development in \u003cem\u003eM. brunneum\u003c/em\u003e is accompanied by fundamental transcriptional reprogramming during the early phases of infection. The aphid host responds to fungal infection with its own transcriptional reprogramming, reflecting its inability to express antifungal peptides but featuring the induction of genes involved in winged morphs that may enable offspring to avoid the contaminated environment.\u003c/p\u003e","manuscriptTitle":"Transcriptional reprogramming in the entomopathogenic fungus Metarhizium brunneum and its aphid host Myzus persicae during the switch between saprophytic and parasitic lifestyles ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-07-04 08:12:12","doi":"10.21203/rs.3.rs-4587553/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-07-17T04:40:37+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-15T13:52:07+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"121780717280810764500237977224718691326","date":"2024-07-10T16:04:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"96996171290611775562897638711583071439","date":"2024-07-09T11:26:42+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-08T17:52:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"122198277314169961434136941246925875546","date":"2024-06-24T09:33:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-23T12:56:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-06-19T07:27:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-19T00:31:43+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-06-19T00:29:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Genomics","date":"2024-06-15T18:28:41+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-genomics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"gics","sideBox":"Learn more about [BMC Genomics](http://bmcgenomics.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/gics","title":"BMC Genomics","twitterHandle":"#BMCGenomics","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"65028544-68fb-410a-ad11-dc9c48319958","owner":[],"postedDate":"July 4th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-10-07T16:11:21+00:00","versionOfRecord":{"articleIdentity":"rs-4587553","link":"https://doi.org/10.1186/s12864-024-10824-y","journal":{"identity":"bmc-genomics","isVorOnly":false,"title":"BMC Genomics"},"publishedOn":"2024-10-02 15:57:50","publishedOnDateReadable":"October 2nd, 2024"},"versionCreatedAt":"2024-07-04 08:12:12","video":"","vorDoi":"10.1186/s12864-024-10824-y","vorDoiUrl":"https://doi.org/10.1186/s12864-024-10824-y","workflowStages":[]},"version":"v1","identity":"rs-4587553","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4587553","identity":"rs-4587553","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}