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

Reingold, Victoria; Faigenboim, Adi; Matveev, Sabina; Haviv, Sabrina; Belausov, Eduard; Vilcinskas, Andreas; Ment, Dana

doi:10.1186/s12864-024-10824-y

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

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Published: 02 October 2024

Volume 25, article number 917, (2024)
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Transcriptional reprogramming in the entomopathogenic fungus Metarhizium brunneum and its aphid host Myzus persicae during the switch between saprophytic and parasitic lifestyles

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Victoria Reingold^1,2,
Adi Faigenboim³,
Sabina Matveev^1,2,
Sabrina Haviv¹,
Eduard Belausov³,
Andreas Vilcinskas^4,5 &
…
Dana Ment¹

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 the course of 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 course of the 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.

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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 [1]. This created a wide range of lifestyles, including fungi that function 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. One of the most adaptable 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 (Fig. 1). These fungi are beneficial to plants at multiple levels including pest and disease reduction, plant induced resistance and growth stimulation and are therefore interesting both as model organisms and for their potential applications in agriculture.

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 [2], reflecting the ease of mass production as saprophytic cultures [3,4,5,6,7]. In nature, the fungal saprophytic lifestyle is characterized by growth on organic matter in the soil [8] until a suitable arthropod host is encountered [9]. 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 [10]. Depending on the environmental conditions, the new propagules may remain dormant or may switch back to the saprophytic lifestyle [11,12,13].

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 [10, 14, 15], as well as proteins that enable the evasion of innate immunity [16]. In contrast, cultivation in rich media enables the fungus to divert its resources to nutrient metabolism [8, 17]. Metarhizium can grow as a saprophyte or an endophyte in different plant roots in the rhizosphere [18, 19]. It can acquire nutrients from the plant and, in turn, promote plant growth and systemic immunity to a broad range of pests and pathogens [20, 21]. 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 [9]. 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 [22].

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.

Results

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 in-vitro development (Fig. 2A, top) and M. persicae adults to initiate pathogenic development (Fig. 2A, bottom), allowing the comparative analysis of the saprophytic in-vitro and parasitic fungal transcriptomes and the host response during pathogenesis.

Differential gene expression during fungal in-vitro saprophytic development

Fungal RNA-Seq data representing different stages of in-vitro saprophytic development were evaluated by principal component analysis (PCA), revealing distinct variation along the axis of principal component (PC) 2 (Fig. 2B). We identified 2,925 differentially expressed genes (DEGs) differing at least in a single comparison, based on the fold change (FC) criteria log₂FC >|2| and p_adj < 0.001. Given a total M. brunneum gene number of 11,595 [23], the DEGs comparing to the 0 h conidia accounted for 25% of all genes. Variation was observed between conidia (0 h) and germinated conidia (9 h, 912 DEGs), hyphae 24 h (1,790 DEGs) and hyphae 72 h (1,406 DEGs) (Fig. 2C, 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 in-vitro saprophytic development (Fig. 3A). Two groups of clusters showed highly similar expression profiles. The first group comprised clusters F, G and H, though represented different hierarchical clustering also represented genes upregulated during development (mainly expressed in the hyphae 24 h and hyphae 72 h, Fig. 3A). The second group comprised clusters I and J, and represented genes downregulated during development (i.e., upregulated in the conidia control, Fig. 3A).

Differential gene expression during fungal pathogenic development

Given that the rate of disease progression varies widely in different aphids following simultaneous infection [24], 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. 2A, bottom). PCA showed a clear separation between the in-vitro saprophytic and parasitic lifestyles, with directional differences correlated to fungal development in each lifestyle (Fig. 2B). Due to low variation between the penetration and germination stages, and between early hemocoel colonization and late colonization, these pairs of stages were combined for further analysis and are described as early infection and late infection, respectively (Fig. 2A, B).

Compared to the conidial control, pathogenic development showed an even distribution of upregulated and downregulated genes. We identified 4,818 DEGs differing at least in a single comparison (~ 41% of all genes) when using permissive criteria (log₂FC >|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), we used only genes which were expressed in both stages. This resulted in 563 DEGs, most of which were upregulated during adhesion. We also identified 1,864 and 4,294 DEGs when comparing the conidial control to the early and late infection, respectively (Fig. 2D). We also compared pathogenic development to the conidial control and germinated in-vitro saprophytic conidia 9 h in order to identify genes involved in conidial dormancy breaking regardless of the subsequent lifestyle. The resulting 3,889 DEGs (~ 33% of all genes) were used to construct a Venn diagram (p_adj < 0.05, log₂FC >|1| for adhesion compared to the conidial control and log₂FC >|2| for all other comparisons) (Fig. 3B, C). The comparison revealed 1,907 upregulated and 1,982 downregulated genes in the parasitic germination and in-vitro saprophytic 9 h germination samples, respectively, compared to the conidial control (Fig. 3B,C). We detected 1,009 DEGs upregulated at all pathogenic stages (Fig. 3B) and 989 that were downregulated (Fig. 3C). Also 1,549 genes were upregulated in proliferating fungi (in-vitro saprophytic and pathogenic germination, hyphae and mycelia, penetration and host colonization) (Fig. 3B) and 1,779 were downregulated (Fig. 3C) compared to the conidial stages. Validation of gene expression by real-time PCR was carried out on selected DEGs (Fig. S1A-B).

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. 2E). 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 (Liu et al. 2021), yet the proportion of upregulated genes was still significantly higher in the NC aphids (Fig. 2F). Using this analysis, we found 617, 639 and 1215 DEGs when comparing the NC to the adhesion, early infection and late infection stages, respectively (log₂FC >|0.4|, FDR < 0.05; Fig. 2F). 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. 3D,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. 3D). Similarly, only 5% of the downregulated genes were uniquely downregulated during early infection (Fig. 3E). Validation of gene expression by real-time PCR was carried out on selected DEGs (Fig. S1C-G).

Enriched pathways and ontologies in the fungus and host

Significant pathways and ontologies in fungal in-vitro saprophytic development

Significant conidial metabolic activity pathways were observed in clusters B and IJ (combined based on pattern similarity), representing log₂FC > 2 expressed genes 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).

Significant pathways and ontologies in fungal pathogenic development

The gene groups identified by Venn analysis (Fig. 3B, C; Table S8) were used to find enriched pathways required for pathogenesis.By the addition of upregulated genes during in-vitro saprophytic germination (9 h), we were able to observe germination related genes during pathogenesis. 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. 5A; 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 in-vitro saprophytic germination (Table S8). Pathways enriched during in-vitro saprophytic germination included secondary metabolism, riboflavin synthesis (spo00740) and sugar metabolism.

GO terms enriched during in-vitro saprophytic germination included cytoplasmic translation (also found in all proliferating fungi) and aerobic respiration related to energy gain (GO:0009060) (Fig. 5B; Table S8). On the other hand, early and late infection involved the enrichment of peptidase and oxidation–reduction activities (GO:0004252, GO:0055114) (Fig. 5D, 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. 5C, G; Table S8). The early and late infection stages featured unique enriched metabolic pathways compared to the in-vitro 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. 5E,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. 5F; Table S8).

Expression of enzymes during fungal pathogenic development

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. 6A). Some of the identified enzymes were constantly expressed in both lifestyles, such as chitinase 18 (QLI68859.1) and a lipase (QLI66658.1), suggesting a general role in fungal development and hyphal elongation, (Fig. 6A). 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. 6A).

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. 6B). 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. 6B). 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. 6B). 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 in-vitro saprophytic and parasitic contexts. Few proteases were overexpressed during in-vitro saprophytic growth, but exceptions included Pr1G (QLI71439.1) and an aspartic protease (QLI65683.1) (Fig. 6B).

Secondary metabolism during in-vitro 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 in-vitro saprophytic development. In contrast, secondary metabolism was enriched during pathogenic development mainly after conidia had germinated (Fig. 5G–I), and the enrichment was more significant at later developmental stages (Fig. 5H,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 (e.g., destruxin, serinocyclin, and swainsonine biosynthesis) 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 in-vitro saprophytic and parasitic lifestyles. Two destruxin clusters were predicted on chromosomes 5 and 7 (Fig. S2A,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 in-vitro saprophytic growth (24 and 72 h) (Fig. S2). We also identified genes responsible for the synthesis of serinocyclin and swainsonine, the former upregulated during in-vitro saprophytic growth and the latter expressed at the same level in both lifestyles (Fig. S2C,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 in-vitro saprophytic growth (Fig. S2E). 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 1,000-fold higher expression level in the parasitic fungus (Fig. S2E).

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. 2F). 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. 7A). Chitin-related GO terms were also enriched during early infection, whereas the melanization defense response was significantly downregulated (Fig. 7B). 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 (Mitogen-activated protein kinase) signaling (Fig. 7C, 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 (Jun N-terminal kinase) signaling and wound healing (Fig. 7E). 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. 7F).

Discussion

Entomopathogenic fungi such as M. brunneum tend to develop as either pathogens or saprophytes, commencing at the conidial stage, depending on environmental signals. The use of a GFP-expressing strain of M. brunneum to correlate fungal gene expression with particular fungal developmental stages within the aphid host enabled the observation of gene expression during fungal-host interaction, even during adhesion. Shared and unique pathways between the in-vitro saprophytic and parasitic lifestyles were identified.

Dormancy breaking and epigenetic regulation of lifestyle shifting

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 [25]. When removed from the conidiophore, conidia are ready to break dormancy and initiate development, which includes an increase in protein synthesis [26].

Interestingly, during mycelial development on CM, we observed the upregulation of transcription, including genes encoding transcription factors. Conidia (0 h) and mycelia (72 h) show similarities in gene expression, presumably because during 72 h the mycelia is differentiating into conidiophore differentiation and conidiogenesis occur [27]. Transcriptional reprogramming may therefore be required at these two time points as the fungus further develop and differentiate. On the other hand, the enrichment of regulatory factors in mycelia may reflect environmental changes sensed by the fungus. As fungal mycelia further grow and nutrient availability decreases over time the fungus may shift to maintaining existing hyphal networks and sporulate. Also, a decrease in nutrient availability may cause the activation of stress response pathways, leading to competition.

As expected, we observed significant differences between the two lifestyles in terms of the expression of genes encoding enzymes and proteins involved in secondary metabolism. 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 [28]. During the adhesion stage, we observed the expression of a gene related to conidiation in A. flavus [29] and a cell differentiation gene encoding a member of the CCR4-NOT complex, which regulates the cell cycle during normal growth [30]. Based on our findings, we suggest the early adhesion as a decision-making point for further development of M. brunneum. 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. 8). Our data suggest that conidia prepare for the sensed environment as some pathogenicity related genes found to be expressed as early as conidia adhere to host cuticle but not in the conidia collected from complete media, is in agreement with previous studies [31,32,33]. 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 [34]. The equivalent shift from parasitic to saprophytic may shed light on the molecular basis of lifestyle shifting.

Protease gene expression varies as M. brunneum lifestyles change

Subtilisin-like (Pr1) and trypsin-like (Pr2) proteases are known to be involved in the pathogenicity of Metarhizium spp. as they are required for cuticle degradation, penetration, and nutrient acquisition [35, 36]. Conidia secrete proteases even before germination, which may facilitate the early stages of infection [37]. 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. 8). The best-studied Pr1 protease is M. anisopliae Pr1A, which facilitates cuticle penetration [35]. Even so, a Pr1A mutant caused mortality in greater wax moth (Galleria mellonella) larvae similarly to the wild-type strain [38]. 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 [39]. We found that a single trypsin-like serine protease was uniquely expressed during adhesion, whereas two Pr1 proteases (putative Pr1F and Pr1H) were expressed during adhesion through the germination stage, suggesting a further role in pathogenicity. Though, Pr1F was reported to be expressed rarely in M. anisopliae, but this may reflect the use of a less sensitive detection method [35] it also has no role in B. bassiana pathogenicity [40]. Finally, only one of the two Pr1H-like genes we detected was constitutively expressed during fungal growth, with the highest expression during the in-vitro saprophytic conidia and pathogenic adhesion stage. This may therefore be the endocellular Pr1 of the MbK isolate [35]. The second Pr1H-like protease may be a pathogenicity-related peptidase rather than an endopeptidase because it was expressed exclusively during pathogenic development.The expression of Tryp8 during late pathogenic and in-vitro saprophytic development, corresponds with a similar protease detected in Pandora neoaphidis (Entomophtorales), infecting aphids [41]. Different fungal strains and isolates may express diverse proteases as virulence factors, causing differences in performance against particular susceptible hosts [15]. In agreement with our results, a previous study showed neither Pr1a nor Pr1b were expressed when G. mellonella was infected with M. brunneum [42]. In order to more precisely understand the role of the different proteases during infection, wider host range should be considered in future studies.

BGCs related to secondary metabolism expressed during in-vitro saprophytic and pathogenic development suggest various roles in fungal lifestyles

Fungal BGCs responsible for the synthesis of secondary metabolites encode core enzymes as well as transporters and regulators [43]. The synthesis of secondary metabolites released during fungal development [44] is related to environmental adaptation, interspecific competition and virulence factors [43, 45, 46]. Metarhizium anisopliae was previously shown to secrete secondary metabolites during growth on the host cuticle [47]. Beauveria bassiana secondary metabolites are mainly expressed when the fungus proliferates in the hemocoel [48]. Using in silico prediction tool we have generated a putative list of BGCs using fungal genome. We can not exclude that some predicted clusters are present only partially in the genome and thus might be non-active BGCs. Thus, we compared the genes within the clusters to the trancriptomic data and found that most of the core enzymes and transporters are expressed in at least one of the fungal lifestyles (Fig. 8). Our study design enabled to detect secondary metabolites BGCs expression already during adhesion to aphid cuticle.

Our previous results showed that diverse secondary metabolites are secreted by the MbK isolate during stationary growth including destruxins [49]. Destruxins are of the best-studied Metarhizium secondary metabolites, which facilitates the pathogenicity of M. anisopliae by preventing the attachment of hemocytes to fungal propagules, thus inhibiting phagocytosis [45, 50, 51]. Here, we found that destruxin biosynthesis genes were expressed at only low levels in conidia samples during in-vitro saprophytic growth and not at all during pathogenesis. Along with a previous study in which M. brunneum destruxin secretion was elevated in dead tissues (Bekker et al., 2013), which was not assessed in our study, it may insinuate a role of destruxin during in-vitro saprophytic lifestyle.

Differential expression of genes linked to the production of two known Metarhizium secondary metabolites, serinocyclin [52] and swainsonine, was also observed in our study (Table S3). The swainsonine core gene was expressed during in-vitro saprophytic and pathogenic growth, whereas serinocyclin-related gene expression was only detected during in-vitro saprophytic development. This agrees with our previous results showing both metabolites present during in-vitro saprophytic growth in M. brunneum [49]. The role of these metabolites in fungal pathogenicity is unclear [53,54,55] although sublethal effects have been reported in mosquitoes [56].

Moreover, 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 [57]. In Metarhizium, similar genes were predicted in a tropolone/citrinin BGC and were upregulated during early pathogenic development (Table S3; Fig. 8), but their effect on virulence has not been assessed [55]. This cluster was also expressed during the pathogenic development of M. anisopliae, but the fold change compared to in-vitro saprophytic growth was lower than in our study [55]. We hypothesize that this BGC may have a role in parasitic lifestyle but requires future studies. A putative BGC for shearinine D was strongly expressed during pathogenic growth, with the core enzyme responsible for the synthesis of lolitrem B (Table S3). The synthesis of this compound in two endophytic fungi showed high insecticidal activity toward aphids [58]. 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 [58], was downregulated during pathogenic development in our study.

Fungal infection causes a cascade of responses in aphids

The cuticular responses does not inhibit fungal infection

The first level of arthropod defense against fungal pathogens is the cuticle as a physical barrier, followed by humoral and cellular immune responses [45]. We observed upregulation of genes encoding cuticle proteins as one of the only means to promote wound repair during fungal infection (Fig. 8). M. persicae has soft and rigid cuticle proteins featuring chitin-binding sites RR-1 and RR-2, respectively [59, 60]. The soft cuticle is easier for fungi to penetrate [61]. Harder cuticle proteins containing the RR-2 domain were upregulated during fungal infection in this study, possibly increasing cuticle sclerotization as a defense mechanism [59, 62, 63]. The strongest upregulation of cuticle protein genes in this study occurred during the earliest infection stages, before fungal penetration. This is a well-studied defense and evasion mechanism in insects in response to fungal infection [64], even though it is ultimately unsuccessful [24]. The strong upregulation of cuticle proteins has been observed in previous studies, sometimes as the most prominent response to fungal pathogens [64,65,66].

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 [67]. However only two GNBP genes are present in aphids (named GNBP1 and GNBP2 in Acyrthosiphon pisum) [68]. The GNBP3 gene, which detects fungi in D. melanogaster [67], is not present in aphids, which also lack a PGRP gene, suggesting that fungi are detected by GNBP1 [68, 69]. A recent publication demonstated the role of M. robertsii effector in the suppression of GNBP3 resulting in attenuated antifungal response through Toll pathway [70]. 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 upregulation 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. 8). Autophagy was observed in G. mellonella during fungal infection as part of the hemocyte response [71]. Autophagy was initially thought to remove endogenous waste materials, but was later shown to also eliminate cell-borne pathogens [72]. 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. 8).

Host immune response upon fungal infection is weak and insufficient to overcome infection

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 [73,74,75]. Conversely, two cathepsin B genes were upregulated in correlation with fungal infection in our study, as previously reported [41], and these may indeed act as detoxifying enzymes [76] (Fig. 8).

Oxidative stress in the insect host during fungal infection induces an immune response [77]. 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 [78] and the receptor was downregulated in cockroaches during oxidative stress [79]. Phenoloxidases were also downregulated during our infection experiments, in contrast to A. pisum infected with B. bassiana [80]. Interestingly, phenoloxidase gene expression in aphids infected with Pandora spp. was induced 48 h post-inoculation, with no significant expression before or after [81]. 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 [82]. The humoral immune system is based mainly on the Toll and IMD signaling pathways [83]. The Toll pathway is the main mediator of antifungal responses, activating the production of antimicrobial peptides (AMPs) during hemocoel invasion [14, 68]. However, aphids lack key components of the Toll and IMD pathways as found in Drosophila spp. [68, 84]. 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 [85]. Interestingly, aphid genomes are almost completely devoid of AMP genes suggesting that the defense mechanisms activated by Toll are probably enzyme based [68, 86].

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. [87]. 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 [88]. 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 [41] accompanied by costly effects on life-history traits [24, 89].

Fungal infection leads to expression of wing formation genes

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 [90]. Similar impairments were observed when the flightin gene was silenced in the aphid A. pisum [91]. In planthoppers, the flightin gene cooperates with troponin C and others to control wing dimorphism and is essential in long-winged forms [92]. Interestingly, aphids infected with entomopathogenic fungi produce a higher proportion of winged offspring [93]. 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. 8).

The transgenerational effects of chemicals that cause wing defects in D. melanogaster were recently shown to be regulated by histone methylation [94]. Transgenerational inheritance in insects may involve a vast array of epigenetic marks [95]. More importantly, exposure to pathogens may lead to resistance in the offspring, also mediated by epigenetic marks [96]. Immune priming can involve the direct maternal translocation of the pathogen or pathogenic elements [97, 98]. Interestingly, genes correlated with transgenerational wing formation in aphids [99] exhibited an upward trend in expression 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.

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 in-vitro saprophytic to a parasitic life style must be accompanied by fundamental transcriptomic reprogramming. By using a GFP-expressing fungal strain and live imaging of disease progression, we collected accurate information about the disease stages on M. persicae by combining high-throughput RNA-Seq analysis of M. brunneum grown in vitro. We identified a comprehensive set of genes that are modulated during the switch from in-vitro 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 pathogenin 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. We conclude that conidia produced during in-vitro 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.

Materials and methods

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 1 × 10⁸/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. 2A).

Media inoculation for transcriptomic profiling during saprophytic growth in-vitro

Conidial suspensions were plated on CM (1 × 10⁶ 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. 2A, 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. 2B).

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 [24]. Adult aphids were inoculated with M. brunneum MbK in a fine sieve by soaking in a solution of 1 × 10⁸ 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 [24].

Live imaging during pathogenic development

Disease progression was monitored in live aphids by confocal laser scanning microscopy (Reingold et al. 2021). Live aphids were placed on a cover slip in a water drop for categorization of disease stage under the microscope as previously described [24]. Based on the categorization, each aphid was removed from the coverslip and 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. 1A, bottom). All aphids were live and motile during the observation and categorization. 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. 2A, bottom).

RNA extraction and high-throughput sequencing

Total RNA was extracted from harvested conidia, germinated conidia and hyphae (designated in-vitro 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 6,500 oscillations/min for 3 min. Samples were then phase separated at 8,000 × 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 a DNA nanoball (DNB) platform at BGI Genomics.

Bioinformatic analysis

Raw reads were subjected to a cleaning procedure using the FASTX Toolkit (http://hannonlab.cshl.edu/fastx_toolkit/index.html, version 0.0.13.2) which included: (i) trimming read-end nucleotides with quality scores < 30 using fastq_quality_trimmer; (ii) removing read pairs if either one had less than 70% base pairs with quality score ≤ 30 using fastq_quality_filter. Settings used for mapping the RNA-seq reads to the two reference genomes were as follow:

–readFilesCommand zcat.
–runThreadN 10.
–limitBAMsortRAM 20000000000.
–twopassMode Basic.
–quantMode TranscriptomeSAM.
–outSAMstrandField intronMotif.
–outSAMattrIHstart 0.
–alignSoftClipAtReferenceEnds No.
–outFilterIntronMotifs RemoveNoncanonical.
–outSAMtype BAM SortedByCoordinate.

Fungal transcriptome

We mapped ~ 2.1 Gb of paired-end reads (average 88.8 million per sample) to the reference genome of M. brunneum 4556 (https://www.ncbi.nlm.nih.gov/assembly/GCA_013426205.1/) using STAR V2.7.1a and –sjdbOverhang 99 [100]. Gene abundance was estimated using Cufflinks V2.2 [101] 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 [102]. Gene expression values were computed as fragments per feature kilobase per million reads mapped (FPKM). Differential expression was analyzed using the DESeq2 R package [103] with a two-fold-change cutoff and a statistical significance of ≤ 0.05 after false discovery correction [104]. Genes were hierarchically clustered based on FPKM values and the clusters were extracted using R scripts. The average FPKM values of 2,925 DEGs (fourfold & padj < 0.001; DESeq2) were hierarchical clusters after log2 transformed and center rows, mean subtracted. Hierarchical clustering of the average FPKM gene expression (using centralized and log 2 transformation) and heatmap visualization were performed using R Bioconductor (fourfold & padj < 0.001). DEGs clusters were combined based on the similarity in the expression pattern of the DEGs to enrich the dataset. Venn diagrams were constructed using Venny 2.0 online (http://bioinfogp.cnb.csic.es/tools/venny/) [105]. 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 [106]. Phylogenetic analysis of protease genes within the M. brunneum genome was conducted using PhyML online as sequences were aligned using MUSCLE (by log-expectation), and Phylip interleaved format was applied in PhyML [107]. Heat map generated based on the DEseq2 values (–log2FC, padj < 0.05) compared to the conidial control. BGCs were predicted using fungal antiSMASH V6.1.1 (https://fungismash.secondarymetabolites.org/#!/start) run with strict mode [108].

Aphid transcriptome

The paired-end reads were mapped to the reference genome of M. persicae (https://www.ncbi.nlm.nih.gov/datasets/genome/GCF_001856785.1/) using STAR software (V2.7.1a) and –sjdbOverhang 99 [100]. Gene abundance was estimated using Cufflinks V2.2 [101] 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 [109]. Genes ≥ twofold differentially expressed with a false discovery-corrected statistical significance of at most 0.05 were considered differentially expressed [104].

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 [110]. Relative expression levels were calculated using the 2^−ΔΔCt method [111]. Statistical significance was determined using a standard least squares restricted maximum likelihood (REML) test, followed by post hoc comparison with Student’s t-test 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.

Availability of data and materials

All data of the study is fully accessible in the public repository NCBI under bioprojects: PRJNA1106639; PRJNA1106641.

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Acknowledgements

The authors thank Dr. Richard M Twyman for the professional editing of the manuscript.

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 and partially funded by the Binational Science Foundation (BSF), Project No. 2021135 to DM.

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Authors and Affiliations

Department of Plant Pathology and Weed Research, Agricultural Research Organization, Volcani Center, Rishon LeZion, Israel
Victoria Reingold, Sabina Matveev, Sabrina Haviv & Dana Ment
The Robert H. Smith Faculty of Agriculture, The Hebrew University of Jerusalem, Food & Environment, Rehovot, Israel
Victoria Reingold & Sabina Matveev
Institute of Plant Science, ARO, The Volcani Institute, Rishon Le Zion, Israel
Adi Faigenboim & Eduard Belausov
Institute for Insect Biotechnology, Justus Liebig Universität Giessen, Giessen, 35392, Germany
Andreas Vilcinskas
Branch Bioresources of the Fraunhofer Institute for Molecular Biology and Applied Ecology, Giessen, 35392, Germany
Andreas Vilcinskas

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Victoria Reingold
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Adi Faigenboim
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Sabina Matveev
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Sabrina Haviv
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Eduard Belausov
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Andreas Vilcinskas
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Dana Ment
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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. All authors reviewed the manuscript.

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Correspondence to Dana Ment.

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Reingold, V., Faigenboim, A., Matveev, S. et al. Transcriptional reprogramming in the entomopathogenic fungus Metarhizium brunneum and its aphid host Myzus persicae during the switch between saprophytic and parasitic lifestyles. BMC Genomics 25, 917 (2024). https://doi.org/10.1186/s12864-024-10824-y

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Received: 15 June 2024
Accepted: 23 September 2024
Published: 02 October 2024
DOI: https://doi.org/10.1186/s12864-024-10824-y

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

Abstract

Background

Results

Conclusions

Background

Results

Patterns of fungal and host gene expression

Differential gene expression during fungal in-vitro saprophytic development

Differential gene expression during fungal pathogenic development

Differential gene expression in aphids during fungal developmental

Enriched pathways and ontologies in the fungus and host

Significant pathways and ontologies in fungal in-vitro saprophytic development

Significant pathways and ontologies in fungal pathogenic development

Expression of enzymes during fungal pathogenic development

Secondary metabolism during in-vitro saprophytic and pathogenic development

Significant pathways and ontologies in M. persicae during infection

Discussion

Dormancy breaking and epigenetic regulation of lifestyle shifting

Protease gene expression varies as M. brunneum lifestyles change

BGCs related to secondary metabolism expressed during in-vitro saprophytic and pathogenic development suggest various roles in fungal lifestyles

Fungal infection causes a cascade of responses in aphids

The cuticular responses does not inhibit fungal infection

Recognition of fungi breaching the cuticular barrier

Host immune response upon fungal infection is weak and insufficient to overcome infection

Fungal infection leads to expression of wing formation genes

Conclusions

Materials and methods

Fungal culture conditions

Media inoculation for transcriptomic profiling during saprophytic growth in-vitro

Aphid inoculation for transcriptomic profiling during pathogenesis

Live imaging during pathogenic development

RNA extraction and high-throughput sequencing

Bioinformatic analysis

Fungal transcriptome

Aphid transcriptome

Cdna synthesis and real-time PCR validation

Availability of data and materials

References

Acknowledgements

Funding

Author information

Authors and Affiliations

Contributions

Corresponding author

Ethics declarations

Ethics approval and consent to participate

Consent for publication

Competing interests

Additional information

Publisher's Note

Supplementary information

Supplementary Material 1.

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About this article

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