- Research article
- Open Access
Transcriptome sequencing of Mycosphaerella fijiensis during association with Musa acuminata reveals candidate pathogenicity genes
- Roslyn D. Noar1 and
- Margaret E. Daub2Email author
- Received: 30 June 2016
- Accepted: 20 August 2016
- Published: 30 August 2016
Abstract
Background
Mycosphaerella fijiensis, causative agent of the black Sigatoka disease of banana, is considered the most economically damaging banana disease. Despite its importance, the genetics of pathogenicity are poorly understood. Previous studies have characterized polyketide pathways with possible roles in pathogenicity. To identify additional candidate pathogenicity genes, we compared the transcriptome of this fungus during the necrotrophic phase of infection with that during saprophytic growth in medium.
Results
Transcriptome analysis was conducted, and the functions of differentially expressed genes were predicted by identifying conserved domains, Gene Ontology (GO) annotation and GO enrichment analysis, Carbohydrate-Active EnZymes (CAZy) annotation, and identification of genes encoding effector-like proteins. The analysis showed that genes commonly involved in secondary metabolism have higher expression in infected leaf tissue, including genes encoding cytochrome P450s, short-chain dehydrogenases, and oxidoreductases in the 2-oxoglutarate and Fe(II)-dependent oxygenase superfamily. Other pathogenicity-related genes with higher expression in infected leaf tissue include genes encoding salicylate hydroxylase-like proteins, hydrophobic surface binding proteins, CFEM domain-containing proteins, and genes encoding secreted cysteine-rich proteins characteristic of effectors. More genes encoding amino acid transporters, oligopeptide transporters, peptidases, proteases, proteinases, sugar transporters, and proteins containing Domain of Unknown Function (DUF) 3328 had higher expression in infected leaf tissue, while more genes encoding inhibitors of peptidases and proteinases had higher expression in medium. Sixteen gene clusters with higher expression in leaf tissue were identified including clusters for the synthesis of a non-ribosomal peptide. A cluster encoding a novel fusicoccane was also identified. Two putative dispensable scaffolds were identified with a large proportion of genes with higher expression in infected leaf tissue, suggesting that they may play a role in pathogenicity. For two other scaffolds, no transcripts were detected in either condition, and PCR assays support the hypothesis that at least one of these scaffolds corresponds to a dispensable chromosome that is not required for survival or pathogenicity.
Conclusions
Our study revealed major changes in the transcriptome of Mycosphaerella fijiensis, when associating with its host compared to during saprophytic growth in medium. This analysis identified putative pathogenicity genes and also provides support for the existence of dispensable chromosomes in this fungus.
Keywords
- Mycosphaerella fijiensis
- Black Sigatoka
- Transcriptome
- Effectors
- Secondary metabolism
- Non-ribosomal peptide synthase
- Fusicoccane
- Domain of Unknown Function 3328
- Salicylate hydroxylase
- Dispensable chromosome
Background
Banana (including common “dessert” bananas as well as cooking and plantain types) is one of the world’s most important food crops, grown in tropical and subtropical regions in over 120 countries [1]. Only about 10–15 % of bananas are grown for export, with the rest serving as an important subsistence crop in many developing countries [2, 3]. Black Sigatoka, caused by the ascomycete fungus Mycosphaerella fijiensis, is a major threat to banana production. It is found in almost all banana-growing countries, and can cause up to 50 % yield loss as well as premature ripening of fruit [3]. Control of the disease is through frequent applications of fungicides, which are estimated to account for 25–30 % of the total banana production cost [1–4]. Fungicide resistance is an ongoing problem that threatens the viability of this method of black Sigatoka control [2, 5].
M. fijiensis produces both conidia and ascospores, both of which can infect banana leaves via the stomata [1]. The fungus is a hemibiotroph. The conidia or ascospores germinate, forming mycelium that initially grows epiphytically on the leaf surface prior to penetration through the stomata and into the leaf [1]. The fungus colonizes the intercellular spaces of the leaf during its biotrophic phase [1]. The fungus then switches to a necrotrophic stage, leading to the death of leaf cells and the formation of necrotic leaf lesions [1].
As a hemibiotroph, M. fijiensis would be expected to produce both effectors to suppress host defense responses and prevent death of host cells during biotrophy [6], and toxic secondary metabolites and proteins to kill host tissue during necrotrophy [7]. However, little is known about the repertoire of effectors and toxic metabolites produced by M. fijiensis during its association with banana. Homologs of the Cladosporium fulvum effectors Ecp2, Ecp6, and Avr4 have been identified from the M. fijiensis genome [8, 9]. However, most fungal pathogens have a large repertoire of effectors, and most effectors have a restricted phylogenetic distribution, so M. fijiensis is likely to produce many other effectors [6]. In addition to effectors, several studies have been done to identify toxins secreted by M. fijiensis. Several phytotoxic metabolites have been identified from M. fijiensis including 2,4,8-trihydroxytetralone, which showed some host selectivity and was thought to be an important pathogenicity factor [10–12]. However, 2,4,8-trihydroxytetralone is a melanin shunt metabolite [13], and disruption of the melanin biosynthetic pathway was shown to have no effect on pathogenicity [1]. Phytotoxic activity has also been identified from the hydrophilic portion of culture filtrates, but the identity of these toxins is unknown [14, 15]. All of these studies were done using mycelium grown in culture conditions, which may not fully reflect what is produced during the association of M. fijiensis with its host.
In previous work we used the publicly available M. fijiensis genome sequence (NCBI Genome ID 10962) [16], obtained from isolate CIRAD86, to predict the capacity of M. fijiensis to produce polyketides [17], an important class of secondary metabolites that are used as pathogenicity factors by closely related fungi [18, 19]. In this study, seven putative polyketide synthase gene clusters and one hybrid polyketide synthase/non-ribosomal peptide synthase gene cluster were identified [17]. Among the clusters were ones with similarity to clusters producing melanin, as well as the secondary metabolites fumonisin, solanapyrone, and alternapyrone produced by Alternaria and Fusarium species [17]. Melanin has been shown to play important roles in fungal pathogenicity of plants including penetration into host tissue [20, 21]. Fumonisin promotes Fusarium spp. pathogenicity by perturbing sphingolipid biosynthesis in the host [22, 23].
The publicly available M. fijiensis genome sequence has also been used to investigate possible dispensable chromosomes. Many fungi use genes located on conditionally dispensable chromosomes to assist in pathogenicity, host specificity, and other functions that are useful but not required for survival [24]. Ohm et al. observed that the CIRAD86 M. fijiensis genome contains 14 scaffolds that are very different from the rest of the scaffolds in the genome: they are small, have a low G + C content, have the lowest gene density and the lowest proportion of genes encoding proteins with PFAM domains, have the highest proportion of repetitive DNA, and have different codon usage [25]. Though it has not been proven that these 14 scaffolds represent dispensable chromosomes, they share their unusual characteristics with dispensable chromosomes from the related species Mycosphaerella graminicola [25, 26].
Next-generation transcriptome sequencing has greatly improved our understanding of the genetic mechanisms of pathogenicity in other species [27, 28]. For M. fijiensis, it can help identify genes encoding effectors, secondary metabolite pathways, and other proteins that may be important for pathogenicity. It can also identify portions of the genome with an abundance of genes that are expressed during association with banana, and thereby suggest which putative dispensable chromosomes may be important for pathogenesis. To date, however, research on changes in gene expression during the M. fijiensis-Musa spp. (banana) interaction has largely been limited to the Musa spp. transcriptome. Portal et al. created suppression subtractive hybridization cDNA libraries from late stages of infection to identify expressed genes from banana and M. fijiensis [29]. They identified banana genes involved in biosynthesis of phenyl-propanoids, jasmonic acid and ethylene, genes encoding pathogenesis-related (PR) proteins, and genes involved in detoxification such as glutathione S-transferases [29]. Although many defense-related banana genes were identified, the inefficiency of CTAB-based RNA extraction protocols with M. fijiensis had not been reported at the time [29]. As a result, the only fungal gene identified from their libraries was a gene for UDP glucose pyrophosphorylase, which is involved in trehalose biosynthesis [29]. Another study used microarray analysis to compare genes expressed in the resistant banana variety Calcutta 4 versus the susceptible variety, Williams, when challenged with M. fijiensis [30]. Banana genes encoding peroxidase, PR-4, PR-10, phenylalanine ammonia lyase, and disease resistance response 1 showed higher expression in Calcutta 4 compared to Williams, between 6 and 24 h after inoculation [30].
Studies of M. fijiensis gene expression have been more limited. Expressed sequence tags have been identified from M. fijiensis grown in three different culture media: Potato Dextrose Agar (PDA), Fries liquid medium, and Fries liquid medium with banana leaf extract added [31]. This analysis found a homolog of the Cladosporium fulvum effector gene Avr4 in all three libraries, and a homolog of the C. fulvum effector gene Ecp2 in both the Fries liquid medium and medium supplemented with leaf extract [31]. In our study on M. fijiensis polyketide synthases, we used transcriptome sequencing to compare expression of the polyketide synthase gene clusters in infected banana leaf tissue relative to in culture medium [17]. The genes in the previously mentioned polyketide synthase clusters with similarities to fumonisin and solanapyrone clusters had increased expression in infected leaf tissue, suggesting that these gene clusters may produce polyketide products that are important for pathogenicity [17]. By contrast, the melanin cluster had lower expression in infected leaf tissue as compared to expression in culture medium [17]. This was the first study in which transcriptome sequencing was used to analyze expression of M. fijiensis during its association with banana. However, our analysis was limited to polyketide synthase gene clusters.
Other transcriptome sequencing studies have been done with banana infected with the related banana pathogens Mycosphaerella musicola and Mycosphaerella eumusae. One study compared the resistant banana variety Calcutta 4 to the susceptible Grand Nain variety during association with M. musicola [32]. A homolog of the C. fulvum effector Ecp6 gene [8] was shown to have higher expression in M. musicola during association with Calcutta 4 relative to Grand Nain, whereas genes encoding a SAP family cell cycle dependent phosphate-associated protein, two Hsp70 family proteins, an FAD binding domain protein, and a calcium channel all had higher expression in M. musicola in the association with Grand Nain compared to Calcutta 4 [32]. Another study compared the transcriptomes of resistant (Manoranjitham) and susceptible (Grand Nain) banana varieties challenged or unchallenged with M. eumusae [33]. Banana genes with higher expression in the resistant compared to susceptible banana variety included those encoding enzymes involved in the phenylpropanoid pathway, abscisic acid biosynthesis, alkaloid biosynthesis, and scavenging of reactive oxygen species [33].
The limited information on pathogenicity-related genes in M. fijiensis and other Mycosphaerella banana pathogens is a barrier to the development of new control methods for this devastating disease. Thus, the objectives of this paper were to expand beyond our focus on polyketides to use transcriptome sequencing data from symptomatic leaf tissue and mycelium growing saprophytically in medium to predict other M. fijiensis genes that may have roles in pathogenicity. In addition, we were interested to determine if putative pathogenicity-related genes are concentrated in particular regions of the genome, such as on scaffolds predicted by Ohm et al. to represent dispensable chromosomes [25].
Results
Identification of differentially expressed genes
Banana plants and Potato Dextrose Broth (PDB) medium were inoculated with M. fijiensis conidia. Tissue harvested from the fungus grown in liquid medium as well as from symptomatic leaf tissue were used for RNA isolation and transcriptome sequencing. Principal component analysis showed that the samples from the same treatment (leaf tissue, liquid medium) clustered together, separately from samples in the other treatment group (Additional file 1: Figure S1). A total of 802 differentially expressed genes were identified (Additional file 2: Figure S2, Additional file 3: Tables S1 and Additional file 4: Table S2); of these, 483 genes were more highly expressed in infected leaf tissue, and 319 genes were more highly expressed in culture medium (Additional file 4: Table S2).
Genes with highest expression in infected leaf tissue compared to culture medium as determined by log2FC
Gene ID | Protein ID | Predicted function of encoded protein | Log2FC |
|---|---|---|---|
fgenesh1_kg.9_#_12_#_4417424:1 | 183842 | Hypothetical; 44 % identity to WI-1 adhesin from Blastomyces dermatitidis | 13.3 |
estExt_Genewise1Plus.C_90054 | 157089 | Hypothetical with Domain of Unknown Function (DUF) 3328 | 11.4 |
Mycfi1.estExt_fgenesh1_pg.C_120010 | 87989 | Hypothetical, no conserved domains | 11.3 |
Mycfi1.fgenesh1_pg.C_scaffold_29000110 | 84397 | Hypothetical, no conserved domains | 11.2 |
Mycfi1.e_gw1.43.35.1 | 46458 | FAD-dependent oxidoreductase | 11.1 |
e_gw1.2.477.1 | 132918 | 2-oxoglutarate and Fe(II)-dependent oxygenase superfamily | 10.9 |
fgenesh1_pm.1_#_1217 | 185508 | MFS multidrug transporter-like protein | 10.8 |
fgenesh1_pg.3_#_601 | 195588 | Hypothetical, no conserved domains | 10.6 |
Genemark.4551_g | 173539 | Hypothetical, no conserved domains | 10.6 |
Mycfi1.gw1.34.54.1 | 20039 | PKS7-1 | 10.5 |
fgenesh1_pm.4_#_231 | 188143 | Zinc peptidase | 10.5 |
estExt_Genemark.C_30183 | 207097 | Hypothetical, no conserved domains | 10.3 |
fgenesh1_pm.7_#_421 | 190048 | Monooxygenase in PKS7-1 cluster | 10.2 |
fgenesh1_pg.7_#_244 | 198484 | Hypothetical, no conserved domains | 10.0 |
Genemark.2108_g | 171096 | Hypothetical, no conserved domains | 9.96 |
Genemark.4552_g | 173540 | Hypothetical, no conserved domains | 9.82 |
fgenesh1_pg.9_#_17 | 199506 | Hypothetical with DUF3328 | 9.76 |
Mycfi1.fgenesh1_pm.C_scaffold_23000030 | 65382 | Hypothetical protein in cupin superfamily | 9.69 |
Mycfi1.e_gw1.22.234.1 | 43729 | Transcription factor | 9.55 |
Mycfi1.fgenesh1_pg.C_scaffold_1001762 | 76887 | Hypothetical, no conserved domains | 9.37 |
Genes with lowest expression in infected leaf tissue compared to culture medium as determined by log2FC
Gene ID | Protein ID | Predicted function | Log2FC |
|---|---|---|---|
fgenesh1_pm.2_#_327 | 186279 | Hypothetical, no conserved domains | −7.1 |
estExt_Genewise1Plus.C_90903 | 157466 | Cysteine synthase | −6.8 |
estExt_fgenesh1_kg.C_20418 | 210593 | Hypothetical, no conserved domains | −6.8 |
gw1.2.3679.1 | 120453 | Heme peroxidase | −6.7 |
estExt_fgenesh1_pm.C_60071 | 204084 | Hypothetical, no conserved domains | −6.7 |
fgenesh1_kg.1_#_500_#_4410656:1 | 181367 | Hypothetical, with some homology to phosphate carrier protein | −6.7 |
fgenesh1_pg.1_#_1546 | 193207 | Hypothetical, no conserved domains | −6.4 |
fgenesh1_pm.2_#_99 | 186051 | α/β-hydroxylase | −6.4 |
estExt_fgenesh1_pg.C_80340 | 216449 | Hypothetical, with CFEM domain | −6.3 |
Mycfi1.e_gw1.1.178.1 | 26018 | Cytochrome P450 | −6.2 |
Mycfi1.estExt_fgenesh1_pg.C_160286 | 88531 | Hypothetical, no conserved domains | −6.2 |
Mycfi1.e_gw1.3.802.1 | 31919 | FAD dependent oxidoreductase | −6.1 |
Genemark.2479_g | 171467 | Hypothetical, no conserved domains | −6.1 |
estExt_Genemark.C_80180 | 208708 | 2-oxoglutarate and Fe(II)-dependent oxygenase superfamily | −6.1 |
estExt_fgenesh1_kg.C_80203 | 212291 | Glutamine amidotransferase | −6.0 |
estExt_fgenesh1_kg.C_30187 | 210875 | Copper transporter | −5.9 |
estExt_fgenesh1_kg.C_50238 | 211639 | Hypothetical, no conserved domains | −5.8 |
estExt_fgenesh1_kg.C_20200 | 210380 | Hypothetical, no conserved domains | −5.8 |
estExt_fgenesh1_kg.C_20513 | 210685 | Hypothetical, no conserved domains | −5.8 |
Mycfi1.estExt_Genewise1.C_12242 | 48579 | Cupredoxin | −5.8 |
Validation of RNA-Seq results by RT-qPCR
Validation of RNA-Seq results using RT-qPCR assays. The cytochrome P450 and oligopeptide transporter were normalized against ubiquitin-conjugating enzyme E2 6, and the proteinase and ferric-chelate reductase were normalized against transcription initiation factor TFIID subunit 10. Fold change was calculated using the 2-ΔΔC T method, relative to the Flask #3 sample. Green bars represent expression in infected leaf tissue; blue bars represent expression in mycelial culture. Error bars represent standard error from mean of technical replicates for each sample. Results confirmed the RNA-Seq data that showed higher expression of the cytochrome P450, proteinase, and oligopeptide transporter in infected leaf tissue, whereas the ferric-chelate reductase had lower expression
Prediction of differentially expressed gene functions
Blast and conserved domain analysis
Differentially-regulated genes identified through domain analysis with homology to secondary metabolite genes. For each of the 802 differentially expressed genes identified from RNA-Seq, a blastp search was done, and conserved protein domains were identified. The figure shows genes with homology to genes commonly involved in secondary metabolism [36]. Green bars = genes more highly expressed in infected leaf tissue relative to mycelium grown in medium; Blue bars = genes with lower expression in infected leaf tissue
Differentially-regulated genes identified through domain analysis with homology to genes with roles in pathogenesis. For each of the 802 differentially expressed genes identified from RNA-Seq, a blastp search was done, and conserved protein domains were identified. The number of genes with higher expression in the infected leaf tissue or in culture medium from each category of genes with roles in pathogenesis in other species was determined and is indicated in the bar chart. Green bars = genes more highly expressed in infected leaf tissue relative to mycelium grown in culture medium; Blue bars = genes with lower expression in infected leaf tissue
Differentially-regulated genes identified through domain analysis with homology to genes with roles in nutrition. For each of the 802 differentially expressed genes identified from RNA-Seq, a blastp search was done, and conserved protein domains were identified. The number of genes with higher expression in the infected leaf vs. in culture medium from each category of genes with putative roles in response to nutrient levels in the environment was determined and is indicated in the bar chart [112–123]. Green bars = genes with higher expression in infected leaf tissue relative to mycelium grown in medium; Blue bars = genes with lower expression in infected leaf tissue
Differentially-regulated genes identified through domain analysis with homology to genes with miscellaneous biological roles. For each of the 802 differentially expressed genes identified from RNA-Seq, a blastp search was done, and conserved protein domains were identified. The number of genes with higher expression in the infected leaf or in culture medium from each category of genes with miscellaneous biological roles was determined and is indicated in the bar chart. Green bars = genes with higher expression in infected leaf tissue relative to mycelium grown in medium; Blue bars = genes with lower expression in infected leaf tissue
GO annotation of differentially expressed genes
Blast2GO is a tool for associating Gene Ontology (GO) [48] terms with sequences of interest [49, 50]. This program uses blast to find homologs of the input sequences. InterProScan searches against all the European Bioinformatics Institute databases to find protein signatures [51, 52]. GO terms associated with the blast hits are mapped using annotation files from the GO Consortium. Depending on the similarity of the input sequence with the blast hit, as well as the quality of the evidence code, the input sequences are finally annotated with these GO terms [49, 50].
Over-represented GO terms in sequences having higher expression in infected leaf tissue
GO-ID | Term | Category | FDR | P-Value |
|---|---|---|---|---|
GO:0016491 | oxidoreductase activity | Molecular Function | 1.31E-16 | 1.69E-20 |
GO:0055114 | oxidation-reduction process | Molecular Process | 1.49E-14 | 3.85E-18 |
GO:0004497 | monooxygenase activity | Molecular Function | 1.11E-13 | 4.29E-17 |
GO:0016705 | oxidoreductase activity, acting on paired donors, with incorporation or reduction of molecular oxygen | Molecular Function | 1.84E-12 | 9.51E-16 |
GO:0005506 | iron ion binding | Molecular Function | 2.61E-12 | 1.68E-15 |
GO:0020037 | heme binding | Molecular Function | 2.35E-08 | 2.12E-11 |
GO:0046906 | tetrapyrrole binding | Molecular Function | 2.35E-08 | 2.12E-11 |
GO:0055085 | transmembrane transport | Molecular Process | 1.38E-04 | 1.42E-07 |
GO:0016021 | integral component of membrane | Cellular Component | 1.83E-04 | 2.12E-07 |
GO:0031224 | intrinsic component of membrane | Cellular Component | 2.71E-04 | 3.49E-07 |
GO:0003824 | catalytic activity | Molecular Function | 3.62E-03 | 5.12E-06 |
GO:0046914 | transition metal ion binding | Molecular Function | 1.29E-02 | 2.00E-05 |
GO:0051213 | dioxygenase activity | Molecular Function | 1.54E-02 | 2.58E-05 |
GO:0008643 | carbohydrate transport | Molecular Process | 4.86E-02 | 9.18E-05 |
GO:0008171 | O-methyltransferase activity | Molecular Function | 4.86E-02 | 9.38E-05 |
CAZy annotation of differentially expressed genes
Number of genes with CAZy annotations. Indicated are the number of genes with each CAZy annotation within: Gray = All M. fijiensis genes; Green = List of genes having higher expression in infected leaf tissue; Blue = List of genes having higher expression during growth in medium
Effector protein predictions
Pathogenic fungi secrete effector proteins into the plant apoplast that modulate host physiology and suppress or otherwise protect the pathogen from host defenses [54]. Secreted proteins can be predicted by the presence of a signal peptide, which are N-terminal peptides that target proteins for translocation across the endoplasmic reticulum membrane and that are cleaved off during the translocation process [55]. The overwhelming majority of known fungal effectors are less than 300 amino acids in length after the signal peptide is cleaved [54]. Further, most avirulence effectors are cysteine-rich [56], because the disulfide bonds from the cysteines provide stability against plant proteases in the apoplast [57].
To identify small, cysteine-rich, secreted proteins, the program SignalP 4.1 [58] was first used to predict M. fijiensis protein sequences that contain a signal peptide. From this analysis, 863 protein sequences (7 % of total sequences) were predicted to contain a signal peptide. SignalP 4.1 was also used to generate predictions of the mature protein sequences once the signal peptides are cleaved. Of the 863 mature protein sequences, 394 were less than 300 amino acids in length, and 231 of these sequences were considered cysteine-rich, containing four or more cysteine residues.
Genes encoding 40 of the 231 short, cysteine-rich, secreted proteins were differentially expressed in our RNA-Seq analysis (Additional file 9: Table S6). Thirty were more highly expressed in infected leaf tissue, whereas only 10 were more highly expressed in culture (Additional file 9: Table S6). Of the protein sequences encoded by the 30 transcripts that were more highly expressed in infected leaf tissue, six had conserved domains: one had a PR-1-like protein domain, two were predicted to be cutinases, one had a CFEM domain, one had a DUF3328 domain, and one had a globin-like domain (Additional file 9: Table S6). Two identified as hypothetical were among those with the highest expression in infected leaf tissue compared to culture medium (Table 1, Additional file 9: Table S6). For the 10 short, cysteine-rich, secreted proteins whose transcripts were more highly expressed in culture, two had conserved domains: one had a CFEM domain, and the other had a serine/threonine phosphatase domain (Additional file 9: Table S6). The CFEM domain-encoding transcript was also identified in the list of genes with highest expression in culture medium compared to infected leaf tissue (Table 2, Additional file 9: Table S6). For the remaining 32 differentially expressed genes encoding short, cysteine-rich, secreted proteins, no significant homology to characterized protein sequences and no predicted conserved domains could be identified (Additional file 9: Table S6). Overall, 16 of the 30 differentially expressed putative effector genes with higher expression in the infected leaf tissue had homologs restricted to species within the Mycosphaerellaceae (Additional file 9: Table S6); others had homologs outside this family. This result is consistent with the observation that many fungal effectors have a restricted phylogenetic distribution [6].
Homologs of the Ecp2, Ecp6 and Avr4 effectors of the tomato pathogen Cladosporium fulvum have been identified in M. fijiensis, and the M. fijiensis Ecp2 and Avr4 effectors are recognized by tomato R proteins that normally recognize the C. fulvum Ecp2 and Avr4 effectors [8, 9]. In C. fulvum, Avr4 and Ecp6 bind chitin and protect fungal cell walls from plant chitinases [59]. The function of Ecp2 is not known [9]. In our dataset, none of the genes were strongly differentially expressed: MfAvr4 had a log2FC of -0.8 with an adjusted p-value of 0.05, and the expression of MfEcp2 and MfEcp6 was unchanged between the two conditions (Additional file 3: Table S1). This result may be due to our focus on the necrotrophic phase in our transcriptome analysis.
Identification of differentially expressed gene clusters
To identify potential gene clusters, we searched for loci in the genome with at least three adjacent genes that were similarly differentially expressed. Using this method, 16 gene clusters were identified with higher expression in infected leaf tissue, and 5 clusters were identified with lower expression in infected leaf tissue. Three of the putative clusters with higher expression in infected leaf tissue encode polyketide pathways, and have been previously described [17]. The remaining 18 clusters are detailed in Additional file 10: Table S7.
Non-ribosomal peptide synthase (NRPS), NRPS-like, and fusicoccane clusters with higher expression in infected leaf tissue. The NRPS or NRPS-like gene is shown along with its neighboring genes in the M. fijiensis genome. The description of each gene as determined by blastp of the corresponding protein is shown along with its log2FC value of expression in infected leaf tissue versus expression in liquid medium. Blue boxes indicate genes in putative cluster; gray boxes indicate genes flanking the cluster. Black bars are proportional to the log2FC value. Gene expression differences that are significant at p < 0.01 are shown with two asterisks above the corresponding bar, and those significant at p < 0.05 are shown with a single asterisk. NE = no expression detected. a NRPS gene cluster on scaffold 7; b NRPS-like gene cluster on scaffold 4; c Fusicoccane gene cluster on scaffold 2
Comparison of M. fijiensis and Alternaria brassicicola fusicoccane biosynthetic clusters. Genes in the M. fijiensis fusicoccane biosynthetic cluster are shown compared to those in the A. brassicicola cluster. Orientation of each gene is indicated by the direction of each arrow. Genes encoding proteins with similar functions are indicated by the same color, and genes not shared between the two clusters are shown in gray
Gene clusters encoding Domain of Unknown Function (DUF) 3328-containing proteins. Gene clusters with higher expression in infected tissue are shown, which contain genes encoding DUF3328 proteins. The description of each gene as determined by blastp of the corresponding protein is shown along with its log2FC value of expression in infected leaf tissue versus expression in liquid medium. Blue boxes indicate genes in putative cluster; gray boxes indicate genes flanking the cluster. Black bars are proportional to the log2FC value. Gene expression differences that are significant at p < 0.01 are shown with two asterisks above the corresponding bar, and those significant at p < 0.05 are shown with a single asterisk. NE = no expression detected. a Gene cluster on scaffold 12; b Gene cluster on scaffold 2; c Gene cluster on scaffold 9; d Gene cluster on scaffold 3
Two gene clusters with higher expression in infected leaf tissue, on scaffolds 7 and 21, consist almost entirely of genes encoding hypothetical proteins (Additional file 10: Table S7H-I and Additional file 13: Figure S5A-B). The other clusters contain genes with putative functions, but their roles as gene clusters are unclear (Additional file 10: Table S7J-M and Additional file 13: Figure S5C-F). For example, one cluster contains several genes commonly found in secondary metabolite gene clusters [36] including one encoding a 2-oxoglutarate and Fe(II)-dependent oxygenase superfamily enzyme, two methyltransferases, an oxidoreductase, and a transporter (Additional file 10: Table S7J and Additional file 13: Figure S5C). Another cluster contains genes encoding two hydrophobic surface binding proteins with homology to HsbA and a pyridine nucleotide-disulfide oxidoreductase (Additional file 10: Table S7K and Additional file 13: Figure S5D). HsbA domains are found in proteins implicated in recruitment of cutinases [37, 38], but the role of the oxidoreductase in this gene cluster is unclear.
The five gene clusters with lower expression in infected leaf tissue contain genes encoding proteins with putative functions, but the role of the genes together as a cluster is unclear (Additional file 10: Table S7N-R and Additional file 14: Figure S6). For example, one cluster contains genes encoding a putative cerato-platanin, two hypothetical proteins, and a C2 domain-containing protein (Additional file 10: Table S7N and Additional file 14: Figure S6B). Cerato-platanin was first described as a small, secreted fungal toxin from Ceratocystis fimbriata [70]. However, cerato-platanins are produced by both pathogenic and non-pathogenic fungi [71, 72], and they are believed to play multiple roles in fungal biology including promotion of cell wall expansion and hyphal elongation [73, 74]. Though the putative cerato-platanin encoded by this gene cluster may play a role in hyphal elongation in the culture medium, it is unclear whether cerato-platanin would interact with any of the other gene products in this cluster. Another example of a gene cluster with lower expression in the infected leaf tissue contains genes encoding an oxidoreductase, a short-chain dehydrogenase, a choline dehydrogenase, an MFS transporter, an aminoacyl-tRNA ligase, a protein containing ankyrin repeats, two hypothetical proteins, and a sequence with homology to pyoverdine/dityrosine biosynthesis protein (Additional file 10: Table S7O and Additional file 14: Figure S6C). Dityrosine is a cross-linking agent that is present in the cell walls of some fungi and protects against adverse environmental conditions [75, 76]. Dityrosine is present in the outermost wall layer of ascospores in many members of the family Saccharomycetaceae [77]. In Candida albicans, dityrosine is also produced along the surface of yeast bud scars and germinated cells [78]. Pyoverdine is a siderophore produced by Pseudomonas spp. which consists of a fluorescent chromophore, a peptide chain, and an acyl side chain [79]. While putative functions for many genes in this cluster can be predicted, it is unclear how proteins encoded by this cluster may work together to produce a product.
Distribution of differentially expressed genes on M. fijiensis genome scaffolds
Many fungi have one or more dispensable chromosomes that assist pathogenicity on a particular host, or have other functions that are useful but not strictly necessary for survival [24]. The related species Mycosphaerella graminicola has eight dispensable chromosomes which are readily lost when the fungus undergoes meiosis [80]. These dispensable chromosomes from M. graminicola have characteristics that distinguish them from the core chromosomes: they are the smallest chromosomes, have the lowest G + C content, have the lowest gene density, have the lowest proportion of genes encoding proteins with PFAM domains, have the highest proportion of repetitive DNA, and have different codon usage [26, 81]. There are 14 scaffolds from the M. fijiensis genome that were predicted to also be dispensable, since they have the same characteristics as the dispensable chromosomes from M. graminicola: small scaffolds, low G + C content, low gene density, low proportion of genes encoding proteins with PFAM domains, a high proportion of repetitive DNA, and different codon usage [25, 26]. If these scaffolds do correspond to dispensable chromosomes, some may play important roles in pathogenicity as is the case for some other pathogenic fungi [24, 82–86].
Percent of genes on each M. fijiensis scaffold that are differentially expressed. For each M. fijiensis genome scaffold with at least 25 predicted genes, the number of genes with higher expression in the infected leaf or in culture is expressed as a percentage of the total number of genes on that scaffold. Predictions of whether the scaffold may represent a core or dispensable scaffold [25, 26] are indicated underneath the scaffold number. Scaffolds were predicted to be dispensable based on the following characteristics: small scaffolds, low G + C content, low gene density, low proportion of genes encoding proteins with PFAM domains, high proportion of repetitive DNA, and different codon usage [25, 26]. Green = Genes more highly expressed in infected leaf tissue; Blue = Genes with lower expression in infected leaf tissue
While the other putative dispensable scaffolds did not have as large a proportion of differentially expressed genes as were found on scaffolds 15 and 21, they did have very different patterns of differential expression compared to the core scaffolds (Fig. 10). Each of the core scaffolds had some genes that were more highly expressed in the infected leaf tissue and other genes that were more highly expressed in culture medium (Fig. 10). By contrast, the scaffolds predicted to be dispensable had only genes that were more highly expressed in infected leaf tissue (scaffolds 11, 14, 15, and 21), more highly expressed in culture (scaffold 18), or no differentially expressed genes (scaffolds 13, 17, 20, and 22) (Additional file 3: Tables S1 and Additional file 4: Table S2).
PCR amplification of genes from scaffolds 13 and 20 in isolates 14H1-11A and CIRAD86. PCR amplification was done for three genes encoding hypothetical proteins on scaffolds 13 and 20, as well as β-tubulin as a positive control. Genomic DNA from isolates 14H1-11A (used in this RNA-Seq analysis) and CIRAD86 (genome sequence publicly available) was used as a template for PCR assays, with water used as a negative control. Quick-Load 100 bp DNA ladder (NEB) was used as a molecular weight marker. Red rectangles mark the expected product size for each assay
Blast hits of scaffold 20 gene amplified from both isolates CIRAD86 and 14H1-11A (gene 2 in Fig. 11)
Isolate of query sequence | Description of hit | Hit Accession | Bit score | E-value | Percent identity | Gaps |
|---|---|---|---|---|---|---|
CIRAD86 | Pseudocercospora fijiensis CIRAD86 hypothetical protein partial mRNA | XM_007934411.1 | 1129 | 0 | 611/611 (100 %) | 0/629 (0 %) |
14H1-11A | Pseudocercospora fijiensis CIRAD86 hypothetical protein partial mRNA | XM_007934411.1 | 538 | 5.00E-149 | 505/609 (83 %) | 12/609 (1 %) |
Discussion
Although several studies have investigated banana genes involved in defense against M. fijiensis and other Mycosphaerella pathogens [29, 30, 32, 33], our work is the first to identify candidate pathogenicity genes based on analysis of the M. fijiensis transcriptome during its association with banana. Our analysis identified 802 genes that were differentially expressed in infected leaf tissue compared to culture medium. Of these, 483 genes had higher expression in infected leaf tissue, and 319 genes had higher expression in medium.
Secondary metabolic pathways have long been suspected as important during the interaction between this fungus and banana [1, 11, 12, 87–90], and we found that two of the genes with the highest expression in infected leaf tissue compared to culture medium (Table 1) were from the previously described PKS7-1 polyketide gene cluster [17], whose product and function are currently unknown. Many types of genes commonly involved in secondary metabolism were also found to have higher expression in infected leaf tissue compared to growth in medium. These genes include ones encoding cytochrome P450s, short-chain dehydrogenases, and oxidoreductases in the 2-oxoglutarate and Fe(II)-dependent oxygenase superfamily (Figs. 2 and 7) [36]. In addition to the three polyketide synthase gene clusters recently described [17], we showed that an NRPS, an NRPS-like, and a fusicoccane gene cluster had higher expression in infected leaf tissue compared to medium (Fig. 7). The closest characterized homolog to the M. fijiensis NRPS protein sequence was a destruxin synthase. Some fungal pathogens produce destruxins which are toxic to their insect or plant hosts and are thought to be involved in virulence [60–66]. Further research is needed to identify the product of the NRPS and its possible role in virulence.
Another gene cluster identified with higher expression in the infected leaf tissue is predicted to encode a fusicoccane. Fusicoccanes are diterpenoids produced by a variety of organisms including fungi, plants, and liverworts. They share a common C20 core, but vary on stereochemistry, degree of saturation, and substitutions, which all affect their physiological activity [68]. Some fusicoccanes cause stomatal opening and wilting, affect seed germination and cell elongation, have antibacterial and antifungal activities, and cause inhibition of biological nitrification and of lysophospholipase [91]. The predicted fusicoccane gene cluster in M. fijiensis is very similar to a cluster producing brassicicene C from Alternaria brassicicola, though it lacks a cytochrome P450, a short-chain dehydrogenase, and an acetyltransferase that the A. brassicicola cluster contains (Fig. 8). These differences suggest that the fusicoccane side groups may slightly differ, thus we hypothesize that the cluster encodes a novel fusicoccane. No significant antimicrobial activity has been detected from brassicicene, and its phytotoxicity and effect on the pathogenicity of A. brassicicola are unknown [92].
Other types of genes previously implicated in pathogenicity in other fungi also had higher expression in the infected leaf tissue. These include genes predicted to encode salicylate hydroxylase-like proteins, hydrophobic surface binding proteins, and CFEM domain-containing proteins (Fig. 3). We showed that the M. fijiensis homolog with highest similarity to the E. festucae salicylate hydroxylase is among the genes with higher expression in infected leaf tissue (Additional file 5: Table S3). Since salicylic acid is important for plant defense responses [43], and salicylate hydroxylase converts salicylate to catechol [44], production of salicylate hydroxylase by M. fijiensis could be a strategy to dampen the salicylic acid defense pathway. In Aspergillus oryzae, the hydrophobic surface binding protein HsbA is secreted from fungal tissue and promotes degradation of the hydrophobic compound polybutylene succinate-co-adipate (PBSA) by recruiting cutinase [37]. PBSA is structurally similar to waxes in the plant cuticle [38, 93]; therefore, it is thought that HsbA and related proteins may recruit cutinases important for plant pathogenicity [38]. CFEM domains are cysteine-rich domains that have been identified in proteins important for pathogenicity [34].
We observed that more genes encoding amino acid transporters, oligopeptide transporters, peptidases, proteases and proteinases had higher expression in infected leaf tissue compared to culture medium (Fig. 4). One proteinase gene was among the list of 20 genes with highest expression in infected leaf tissue compared to culture medium (Table 1). Conversely, more peptidase or proteinase inhibitor genes had lower expression in infected leaf tissue (Fig. 4). These results may be expected if the in planta environment is lower in nitrogen than the PDB culture medium. In other plant pathogenic fungi and bacteria, low nitrogen conditions are known to induce expression of virulence genes, and it is thought that this reflects nitrogen limitation for the pathogen during its interaction with the plant host [94, 95]. Likewise, more sugar transporters had higher expression in infected leaf tissue compared to medium (Fig. 4). This may reflect a higher sugar concentration in the PDB medium due to added dextrose, and thus a need for higher expression of sugar transporters in the plant environment compared to a relatively sugar-rich medium.
We identified four gene clusters with higher expression in the infected leaf tissue that encode one or more hypothetical proteins with Domain of Unknown Function (DUF) 3328 (Fig. 9). Two DUF3328-encoding genes were among the list of genes with highest expression in the infected leaf tissue compared to medium (Table 1). Although the function of this domain is not known, some studies have associated changes in DUF3328 gene expression with the fungal sexual cycle. In Sordaria macrospora, a DUF3328 gene cluster was identified as up-regulated in wild-type protoperithecia compared to protoperithecia of a mutant for sexual reproduction [46]. In Podospora anserina, genes encoding DUF3328 proteins were identified as having higher expression in mat- compared to mat + strains [47]. In natural infections where both mating types of M. fijiensis are present, pseudothecia develop in infected banana tissue, and ascospores are considered the primary means of pathogen spread [1]. Therefore, although the role of DUF3328 proteins remains unclear, one hypothesis is that they may be important for pseudothecia development in this fungus.
We identified genes predicted to encode small, cysteine-rich, secreted proteins, since these are features common in fungal effectors [54, 56]. We found 30 such genes with higher expression in infected leaf tissue, and 10 with higher expression in medium (Additional file 9: Table S6). Two of these were among the list of genes with highest expression in infected leaf tissue compared to culture medium (Table 1), and one was among the list of genes with highest expression in culture medium compared to infected leaf tissue (Table 2). Among the proteins encoded by the 30 genes with higher expression in infected leaf tissue were proteins implicated in other species as being important for pathogenicity, including cutinases and proteins with PR-1-like and CFEM domains [34, 41, 42, 96]. For 16 of the putative effector genes with higher expression in the infected leaf tissue, all homologs were restricted to species within the Mycosphaerellaceae. This result is consistent with the observation that many fungal effectors have a restricted phylogenetic distribution [6]. Although it has previously been shown that the M. fijiensis genome encodes homologs of the C. fulvum effectors Avr4, Ecp2 and Ecp6 [8, 9], none of these genes had higher expression in infected leaf tissue compared to culture medium (Additional file 3: Table S1). It is possible that these effectors are important for pathogenicity at different time points, such as the biotrophic phase, than for the necrotrophic phase assayed in this experiment.
Finally, we were able to provide support for the hypothesis that M. fijiensis may have dispensable chromosomes, and that some of these may be important for pathogenicity [25, 26]. Ohm et al. showed that the M. fijiensis genome has 14 scaffolds with similar characteristics to the dispensable chromosomes from M. graminicola [25]. Compared to the rest of the genome, these 14 scaffolds are small, have a lower G + C content, different codon usage, a high proportion of repetitive DNA, a low gene density, and a lower proportion of genes encoding proteins with PFAM domains [25]. We identified two of these putative dispensable scaffolds (15 and 21) for which 31 % and 52 % of the genes, respectively, on the scaffolds had higher expression in infected leaf tissue, and no genes on these scaffolds had higher expression in culture medium. It is still unknown whether these scaffolds correspond to dispensable chromosomes, but our data suggest that they may play a role in pathogenicity. We also identified two more scaffolds (13 and 20) for which no transcripts were detected. PCR assays were unable to amplify the three genes tested on scaffold 13, and two of three genes on scaffold 20 in our isolate 14H1-11A, whereas amplification was possible for all of these genes in isolate CIRAD86, for which the genome sequence is publicly available (NCBI Genome ID 10962) [16] (Fig. 11). Considering our transcriptome and PCR data, we have no evidence that scaffold 13 is present in our isolate, though PCR data show that at least part of scaffold 20 remains. Our data support the hypothesis that scaffold 13 corresponds to a dispensable chromosome that is not required for survival or pathogenicity.
Conclusions
This study is the first to identify candidate pathogenicity genes of the fungus Mycosphaerella fijiensis, based on transcriptome data from this fungus during its necrotrophic phase of infection of banana, compared to during saprophytic growth in culture medium. We showed that gene clusters predicted to synthesize a non-ribosomal peptide and a fusicoccane, as well as many types of genes encoding proteins commonly involved in secondary metabolism, such as cytochrome P450s and short-chain dehydrogenases, have higher expression in infected leaf tissue. We identified several other types of genes with higher expression in infected leaf tissue, including genes predicted to encode salicylate hydroxylase-like proteins, hydrophobic surface binding proteins, CFEM domain-containing proteins, amino acid and sugar transporters, and proteins with DUF3328 domains. Furthermore, we identified two putative dispensable scaffolds with a large proportion of genes with higher expression in infected leaf tissue, suggesting that these scaffolds may play a role in pathogenicity. We also identified two other scaffolds for which no transcripts were detected in either condition, and PCR assays support the hypothesis that at least one of these scaffolds corresponds to a dispensable chromosome that is not required for survival or pathogenicity. Together, these results suggest exciting avenues of further research for an important and understudied pathogen.
Methods
Fungal cultures
M. fijiensis isolate 14H1-11A, isolated from the FHIA research station in La Lima, Honduras, was kindly provided by Dr. Jean Ristaino (North Carolina State University) and was routinely cultured on Potato Dextrose Agar (PDA) (Difco). Conidial production was induced as described [17, 97].
Banana tissue culture
‘Grand Nain’ banana tissue culture plants were obtained from Miguel Muñoz (Dole Food Company) and were maintained on modified Murashige and Skoog medium as described [17].
Inoculation of plants and flasks
Rooted banana plants grown in modified Murashige and Skoog medium were transferred to potting mix under greenhouse conditions. When they were approximately 20 cm in height, plants were transferred to an incubator at 25 °C under cool-white fluorescent light on a 18 h light/6 h dark photoperiod. Plants were inoculated by atomizing with 5.2 × 104/mL conidia in 0.5 % Tween 20 as described [17]. Plants were covered with clear plastic bags to maintain high humidity conditions for 1 week. Symptomatic banana leaf tissue was harvested at 6 weeks post-inoculation by flash-freezing in liquid nitrogen.
For growth in culture, 50 mL flasks of Potato Dextrose Broth (PDB) (Difco) were inoculated with 10 μL of 1.3 × 106/mL conidia and incubated in a rotary shaker at 150 rpm in the dark at 25–30 °C. After one week, mycelium was harvested by filtering through Miracloth, blotting dry, and flash freezing in liquid nitrogen.
cDNA library construction and Illumina HiSeq sequencing
RNA was isolated using the Spectrum Plant Total RNA kit (Sigma). Samples were DNase treated with DNase I (Roche). Total RNA sequencing was conducted at the Genomic Sciences Laboratory, North Carolina State University. RNA quality was confirmed by gel electrophoresis and an Agilent Bioanalyzer. Strand-specific libraries were created using the NEBNext Ultra Directional library prep kit (New England BioLabs). Single-end 125-base reads were generated using an Illumina HiSeq 2500 platform. Average sequencing yield was 32 million reads per sample.
Identification of differentially expressed genes
FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/) was used to verify the quality of RNA-Seq reads. Illumina Truseq adapter sequences and low-quality bases were trimmed using CutAdapt v1.7 with a quality cutoff of 20 and a minimum sequence length of 36 [98].
Sequences were mapped from each sample to both the banana genome, Musa acuminata subsp. malaccensis double-haploid Pahang [99, 100], and to the M. fijiensis genome [16, 26] using Tophatv2.0.9 [101]. Gene expression levels were determined using HTSeqv0.6.0 [102] and the gene annotations available from the Joint Genome Institute (JGI). Differentially expressed genes were identified with an adjusted p-value < 0.01, a log2FC value > 3, and a basemean (mean of normalized read counts) > 10, using the program DESeq2 v1.4.5 (Additional file 3: Tables S1 and Additional file 4: Table S2) [103]. Principal component analysis and a volcano plot were done to verify that biological replicates were similar in expression pattern to each other (Additional file 1: Figure S1) and to visualize the distribution of differentially expressed transcripts (Additional file 2: Figure S2).
Validation by RT-qPCR
Four differentially expressed genes were chosen for validation of RNA-Seq results. Genes were chosen with a basemean value of >150 in both conditions, a log2FC value >3, and an adjusted p-value of < 0.01, to select differentially expressed genes that were well-expressed in both conditions.
cDNA was synthesized with iScript Select reverse transcriptase (BioRad). qPCR reactions were performed with iQ SYBR Green SuperMix, in a CFX Connect Real-Time System machine. The program was done with an initial denaturation at 95 °C for 2 min, followed by 50 cycles of 95 °C for 10 s, 57 °C for 30 s, 72 °C for 30 s with a plate read, and then 78 °C for 30 s with a plate read. A melt curve was also done to verify that a single product was formed for each reaction.
Each gene of interest was normalized against two M. fijiensis-specific reference genes having the same reaction efficiency as the gene of interest, and fold-change in infected leaf tissue was calculated compared to when grown in liquid medium, using the 2−ΔΔC T method [104]. Primer sequences are indicated in Additional file 18: Table S10.
Prediction of differentially expressed gene functions
Blast and conserved domain analysis
For each of the 802 differentially expressed genes, a blastp search was performed using the non-redundant protein sequence database from NCBI (July 2015). NCBI’s Conserved Domain Database [35] was used to predict domains from each protein sequence (Additional file 4: Table S2). To identify the closest M. fijiensis homolog of salicylate hydroxylase, a blastp search was done with the Epichloë festucae salicylate hydroxylase sequence (Accession = AIY25489.1) [45] against all the M. fijiensis isolate CIRAD86 predicted protein sequences in NCBI’s non-redundant protein sequence database (6/1/2016) (Additional file 5: Table S3).
CAZy and GO annotations and enrichment analysis
Blast2GO Basic v3.1.3 was used to do blastx v2.2.32+ searches of M. fijiensis gene catalog coding sequences from JGI against the NCBI non-redundant protein sequences (nr database), using the default parameters. InterProScan, mapping, and annotation steps were all done with the default parameters. Using the resulting annotation data, Fisher’s Exact Test was used to identify GO terms that were over-represented from sequences having higher expression in infected leaf tissue or in medium, compared to their representation in the total set of genes from the M. fijiensis genome.
Genome annotations, including those based on the CAZy database, were downloaded from NCBI for M. fijiensis (Genome ID: 10962). Genes with CAZy annotations were compared with the list of differentially expressed genes.
Effector protein predictions
M. fijiensis Gene Catalog protein models were downloaded from the published genome sequence from JGI, in FASTA format. Signal peptides were predicted from these sequences using SignalP 4.1 [58], with the organism group set to Eukaryotes, and the D-cutoff value set to the default. SignalP 4.1 was also used to make predictions of the mature protein sequences once signal peptides are cleaved. Mature protein sequences were then sorted by length to identify sequences less than 300 amino acids in length. These short, secreted mature peptides were then sorted by cysteine content to identify sequences containing at least four cysteine residues. Differentially expressed genes predicted to be short, secreted, and cysteine rich were noted in Additional file 9: Table S6. Since M. fijiensis homologs of the C. fulvum effectors Avr4, Ecp2, and Ecp6 have previously been described [8, 9], the expression of the corresponding genes was also reported. JGI gene IDs for MfAvr4, MfEcp2 and Ecp6 are Mycfi1.estExt_fgenesh1_pg.C_60009, gw1.3.823.1, and estExt_fgenesh1_kg.C_70127, respectively.
Phylogenetic tree of fusicoccadiene synthases
Once homologs were identified of the M. fijiensis fusicoccadiene synthase using blastp, the M. fijiensis sequence and its top 49 homologs (Additional file 11: Table S8) were aligned using MUSCLE v3.8.31 [105] in Mesquite v3.04 [106]. ModelGenerator v0.85 [107] was used to select the best substitution model using the Aikaike and and Bayesian Information Criteria. RaxmlGUI v1.3.1 [108] was used to create a maximum likelihood tree using the JTT + I + G substitution model [109] with slow bootstrap, the autoMRE function, and no outgroup.
Identification of gene clusters
To identify clusters of differentially expressed genes and to analyze how differentially expressed genes are distributed across the M. fijiensis genome scaffolds, scaffold number and position on the scaffold was downloaded from JGI, and matched to each gene ID. To identify clusters of differentially expressed genes, loci were identified that contain at least three adjacent, similarly differentially expressed genes (Figs. 7 and 9, Additional file 10: Table S7, Additional file 13: Figures S5 and Additional file 14: Figure S6).
Distribution of differentially expressed genes across genome scaffolds
To analyze the distribution of differentially expressed genes across scaffolds, differentially expressed genes were sorted according to scaffold number, and the number of differentially expressed genes on a scaffold was compared to the total number of genes on the scaffold (Fig. 10). For proteins encoded by genes on scaffolds 15 and 21, blastp searches were done using NCBI’s non-redundant protein database (4/26/2016) to identify conserved domains and the top 10 homologs by bitscore of each sequence of interest (maximum E-value = 1 × 10−5) (Additional file 15: Table S9 and Additional file 16: Figure S7).
To determine whether scaffolds 13 and 20 are present in isolate 14H1-11A, three genes were chosen on scaffold 13 and scaffold 20 for PCR assays. Genomic DNA was extracted from isolate 14H1-11A and CIRAD86 using DNeasy Plant Mini Kit (Qiagen), according to manufacturer’s instructions. PCR amplifications were done using OneTaq 2X Master Mix with Standard Buffer (NEB), according to manufacturer’s instructions with 35 cycles, with primer sequences, annealing temperatures, extension times, and expected product sizes indicated in Additional file 19: Table S11. To obtain the sequence of the gene on scaffold 20 which amplified for both isolates (accession XM_007934411.1), the high fidelity DNA polymerase iProof (Bio-Rad) was used to amplify this gene from both isolates, according to manufacturer’s instructions with an annealing temperature of 60 °C, an extension time of 20 s, and 35 cycles. The band was gel purified from both isolates using a QIAquick gel extraction kit (Qiagen), and Sanger sequencing was done by Eton Bioscience using the forward primer (Additional file 19: Table S11). A blastn search was done using NCBI’s nucleotide collection database for each sequence against the M. fijiensis genome to verify amplification of the correct gene (Table 4). A blastx search was also done with the sequence from isolate 14H1-11A to determine how changes in nucleotide sequence in this isolate affect the sequence of the predicted protein. The program Chimera v1.10.2 [110] was used to display the sequence alignment and the degree of conservation for each residue in the alignment.
Abbreviations
- ABC:
-
ATP-binding cassette
- BAP:
-
6-benzylaminopurine
- CAZy:
-
Carbohydrate-active enzymes
- CFEM:
-
Common in fungal extracellular membrane
- DUF3328:
-
Domain of unknown function 3328
- FDR:
-
False discovery rate
- GO:
-
Gene ontology
- HsbA:
-
Hydrophobic surface binding protein A
- JGI:
-
Joint Genome Institute
- log2FC:
-
log2 fold change
- MFS:
-
Major facilitator superfamily
- NCBI:
-
National Center for Biotechnology Information
- NRPS:
-
Non-ribosomal peptide synthase
- PBSA:
-
Polybutylene succinate-co-adipate
- PDB:
-
Potato dextrose broth
- PR-1:
-
Pathogenesis-related protein 1
Declarations
Acknowledgements
We thank Gert Kema, Wageningen University and Research Centre, The Netherlands for providing the M. fijiensis isolate CIRAD86, and Jean Ristaino, North Carolina State University for isolate 14H1-11A. We also thank Elizabeth Thomas from North Carolina State University for consultation with qPCR assays.
Funding
Funding for this study was provided by Dole Food Company (to MED), a National Science Foundation Graduate Research Fellowship (to RDN), and a Molecular Biotechnology training grant traineeship to RDN from the National Institutes of Health. The funding bodies played no role in the design of the study, the collection, analysis, or interpretation of data, or in the writing of the manuscript.
Availability of data and material
The transcriptome dataset supporting the conclusions of this article is available in the NCBI database, with the Sequence Read Archive accession SRP075820, at http://www.ncbi.nlm.nih.gov/sra/SRP075820. All other datasets supporting the conclusions of this article are included within the article and its additional files.
Authors’ contributions
RDN conceived the study. RDN and MED planned the experiments. RDN did the laboratory work. RDN and MED analyzed the data. RDN and MED wrote the manuscript. Both authors read and approved the final manuscript.
Competing interests
The authors declare that they have no competing interests.
Consent for publication
Not applicable
Ethics approval and consent to participate
Not applicable.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
Authors’ Affiliations
References
- Churchill ACL. Mycosphaerella fijiensis, the black leaf streak pathogen of banana: progress towards understanding pathogen biology and detection, disease development, and the challenges of control. Mol Plant Pathol. 2011;12:307–28. Available from: http://dx.doi.org/10.1111/j.1364-3703.2010.00672.x.PubMedView ArticleGoogle Scholar
- Marín DH, Romero RA, Guzmán M, Sutton TB. Black Sigatoka: an increasing threat to banana cultivation. Plant Dis. 2003;87:208–22. Available from: http://dx.doi.org/10.1094/PDIS.2003.87.3.208.View ArticleGoogle Scholar
- Ploetz RC. Black Sigatoka of Banana. APSnet Feature Artic. [Internet]. 2001. Available from: http://www.apsnet.org/publications/apsnetfeatures/Pages/BlackSigatoka.aspx. Accessed 24 Aug 2016.
- Abadie C, Chilin-Charles Y, Huat J, Salmon F, Pignolet L, Carlier J, et al. New approaches to select cultivars of banana with durable resistance to Mycosphaerella leaf spot diseases. Acta Hortic. 2009;828:171–8. Available from: http://dx.doi.org/10.17660/ActaHortic.2009.828.17.
- de Lapeyre de Bellaire L, Essoh Ngando J, Abadie C, Chabrier C, Blanco R, Lescot T, et al. Is chemical control of Mycosphaerella foliar diseases of banana sustainable? Acta Hortic. 2009;818:161–70. Available from: http://dx.doi.org/10.17660/ActaHortic.2009.828.16.
- Giraldo MC, Valent B. Filamentous plant pathogen effectors in action. Nat Rev Micro. 2013;11:800–14. Available from: http://dx.doi.org/10.1038/nrmicro3119.View ArticleGoogle Scholar
- Stergiopoulos I, Collemare J, Mehrabi R, De Wit PJGM. Phytotoxic secondary metabolites and peptides produced by plant pathogenic Dothideomycete fungi. Fems Microbiol Rev. 2013;37:67–93. Available from: http://dx.doi.org/10.1111/j.1574-6976.2012.00349.x.PubMedView ArticleGoogle Scholar
- Bolton MD, van Esse HP, Vossen JH, de Jonge R, Stergiopoulos I, Stulemeijer IJE, et al. The novel Cladosporium fulvum lysin motif effector Ecp6 is a virulence factor with orthologues in other fungal species. Mol Microbiol. 2008;69:119–36. Available from: http://dx.doi.org/10.1111/j.1365-2958.2008.06270.x.PubMedView ArticleGoogle Scholar
- Stergiopoulos I, van den Burg HA, Okmen B, Beenen HG, van Liere S, Kema GHJ, et al. Tomato Cf resistance proteins mediate recognition of cognate homologous effectors from fungi pathogenic on dicots and monocots. Proc Natl Acad Sci U S A. 2010;107:7610–5. Available from: http://dx.doi.org/10.1073/pnas.1002910107.PubMedPubMed CentralView ArticleGoogle Scholar
- Upadhyay RK, Strobel GA, Coval SJ, Clardy J. Fijiensin, the 1st phytotoxin from Mycosphaerella fijiensis, the causative agent of black Sigatoka disease. Experientia. 1990;46:982–4. Available from: http://dx.doi.org/10.1007/BF01939396.View ArticleGoogle Scholar
- Stierle AA, Upadhyay R, Hershenhorn J, Strobel GA, Molina G. The phytotoxins of Mycosphaerella fijiensis, the causative agent of black Sigatoka disease of bananas and plantains. Experientia. 1991;47:853–9. Available from: http://dx.doi.org/10.1007/BF01922472.
- Strobel GA, Stierle AA, Upadhyay R, Hershenhorn J, Molina GC. The phytotoxins of Mycosphaerella fijiensis, the causative agent of black Sigatoka disease, and their potential use in screening for disease resistance. In: Wills B, Huggan RD, editors. Biotechnol. Appl. Banana Plantain Improv. Montpellier: International Network for the Improvement of Banana and Plantain; 1993. p. 93–103.Google Scholar
- Wheeler MH, Stipanovic RD. Melanin biosynthesis and the metabolism of flaviolin and 2-hydroxyjuglone in Wangiella dermatitidis. Arch Microbiol. 1985;142:234–41. Available from: http://dx.doi.org/10.1007/BF00693396.PubMedView ArticleGoogle Scholar
- Cruz-Cruz CA, Garcia-Sosa K, Escalante-Erosa F, Pena-Rodriguez LM. Production of hydrophilic phytotoxins by Mycosphaerella fijiensis. J Gen Plant Pathol. 2009;75:191–5. Available from: http://dx.doi.org/10.1007/s10327-009-0165-1.View ArticleGoogle Scholar
- Cruz-Cruz CA, Garcia-Sosa K, Escalante-Erosa F, Pena-Rodriguez LM. Physiological effects of the hydrophilic phytotoxins produced by Mycosphaerella fijiensis, the causal agent of black sigatoka in banana plants. J Gen Plant Pathol. 2011;77:93–100. Available from: http://dx.doi.org/10.1007/s10327-010-0288-4.View ArticleGoogle Scholar
- D.O.E. Joint Genome Institute. Mycosphaerella fijiensis v2.0 [Internet]. 2016. Available from: http://genomeportal.jgi-psf.org/Mycfi2/Mycfi2.home.html. Accessed 24 Aug 2016.
- Noar RD, Daub ME. Bioinformatics prediction of polyketide synthase gene clusters from Mycosphaerella fijiensis. PLoS ONE. 2016;11:e0158471. Available from: http://dx.doi.org/10.1371/journal.pone.0158471.PubMedPubMed CentralView ArticleGoogle Scholar
- Choquer M, Dekkers KL, Chen HQ, Cao LH, Ueng PP, Daub ME, et al. The CTB1 gene encoding a fungal polyketide synthase is required for cercosporin biosynthesis and fungal virulence of Cercospora nicotianae. Mol Plant Microbe Interact. 2005;18:468–76. Available from: http://dx.doi.org/10.1094/MPMI-18-0468.PubMedView ArticleGoogle Scholar
- Kabir MS, Ganley RJ, Bradshaw RE. Dothistromin toxin is a virulence factor in dothistroma needle blight of pines. Plant Pathol. 2015;64:225–34. Available from: http://dx.doi.org/10.1111/ppa.12229.View ArticleGoogle Scholar
- Howard RJ, Ferrari MA. Role of melanin in appressorium function. Exp Mycol. 1989;13:403–18. Available from: http://dx.doi.org/10.1016/0147-5975(89)90036-4.View ArticleGoogle Scholar
- Steiner U, Oerke EC. Localized melanization of appressoria is required for pathogenicity of Venturia inaequalis. Phytopathology. 2007;97:1222–30. Available from: http://dx.doi.org/10.1094/PHYTO-97-10-1222.PubMedView ArticleGoogle Scholar
- Glenn AE, Zitomer NC, Zimeri AM, Williams LD, Riley RT, Proctor RH. Transformation-mediated complementation of a FUM gene cluster deletion in Fusarium verticillioides restores both fumonisin production and pathogenicity on maize seedlings. Mol Plant Microbe Interact. 2008;21:87–97. Available from: http://dx.doi.org/10.1094/MPMI-21-1-0087.PubMedView ArticleGoogle Scholar
- Sanchez-Rangel D, Plasencia J. The role of sphinganine analog mycotoxins on the virulence of plant pathogenic fungi. Toxin Rev. 2010;29:73–86. Available from: http://dx.doi.org/10.3109/15569543.2010.515370.View ArticleGoogle Scholar
- Covert SF. Supernumerary chromosomes in filamentous fungi. Curr Genet. 1998;33:311–9.PubMedView ArticleGoogle Scholar
- Ohm RA, Feau N, Henrissat B, Schoch CL, Horwitz BA, Barry KW, et al. Diverse lifestyles and strategies of plant pathogenesis encoded in the genomes of eighteen Dothideomycetes fungi. Plos Pathog. 2012;8. Available from: http://dx.doi.org/10.1371/journal.ppat.1003037.
- Goodwin SB, Kema GHJ. The genomes of Mycosphaerella graminicola and M. fijiensis. In: Dean RA, Lichens-Park A, Kole C, editors. Genomics Plant-Assoc. Fungi Monocot Pathog. Berlin/Heidelberg: Springer; 2014.Google Scholar
- O’Connell RJ, Thon MR, Hacquard S, Amyotte SG, Kleemann J, Torres MF, et al. Lifestyle transitions in plant pathogenic Colletotrichum fungi deciphered by genome and transcriptome analyses. Nat Genet. 2012;44:1060–5. Available from: http://dx.doi.org/10.1038/ng.2372.PubMedView ArticleGoogle Scholar
- Rudd JJ, Kanyuka K, Hassani-Pak K, Derbyshire M, Andongabo A, Devonshire J, et al. Transcriptome and metabolite profiling of the infection cycle of Zymoseptoria tritici on wheat reveals a biphasic interaction with plant immunity involving differential pathogen chromosomal contributions and a variation on the hemibiotrophic lifestyle definition. Plant Physiol. 2015;167:1158–85. Available from: http://dx.doi.org/10.1104/pp.114.255927.PubMedPubMed CentralView ArticleGoogle Scholar
- Portal O, Izquierdo Y, De Vleesschauwer D, Sánchez-Rodríguez A, Mendoza-Rodríguez M, Acosta-Suárez M, et al. Analysis of expressed sequence tags derived from a compatible Mycosphaerella fijiensis–banana interaction. Plant Cell Rep. 2011;30:913–28. Available from: http://dx.doi.org/10.1007/s00299-011-1008-z.PubMedView ArticleGoogle Scholar
- Rodriguez HA, Rodriguez-Arango E, Morales JG, Kema G, Arango RE. Defense gene expression associated with biotrophic phase of Mycosphaerella fijiensis M. Morelet infection in banana. Plant Dis. 2016;100:1170-75. Available from: http://dx.doi.org/10.1094/PDIS-08-15-0950-RE.
- Cho Y, Hou S, Zhong S. Analysis of expressed sequence tags from the fungal banana pathogen Mycosphaerella fijiensis. Open Mycol J. 2008;2:61–73. Available from: http://dx.doi.org/10.2174/1874437000802010061.View ArticleGoogle Scholar
- Passos MAN, de Cruz VO, Emediato FL, de Teixeira CC, Azevedo VCR, Brasileiro ACM, et al. Analysis of the leaf transcriptome of Musa acuminata during interaction with Mycosphaerella musicola: gene assembly, annotation and marker development. Bmc Genomics [Internet]. 2013;14:78. Available from: http://dx.doi.org/10.1186/1471-2164-14-78.
- Uma S, Backiyarani S, Saravanakumar AS, Chandrasekar A, Thangavelu R, Saraswathi MS. Identification of Mycosphaerella eumusae responsive unique genes/transcripts from a resistant banana cultivar. Acta Hortic. 2016;1114:111–8. Available from: http://dx.doi.org/10.17660/ActaHortic.2016.1114.16.
- Kulkarni RD, Kelkar HS, Dean RA. An eight-cysteine-containing CFEM domain unique to a group of fungal membrane proteins. Trends Biochem Sci. 2003;28:118–21. Available from: http://dx.doi.org/10.1016/S0968-0004(03)00025-2.PubMedView ArticleGoogle Scholar
- Marchler-Bauer A, Lu S, Anderson J, Chitsaz F, Derbyshire M, DeWeese-Scott C, et al. CDD: a Conserved Domain Database for the functional annotation of proteins. Nucleic Acids Res. 2011;39:D225–9. Available from: http://dx.doi.org/10.1093/nar/gkq1189.PubMedView ArticleGoogle Scholar
- Khaldi N, Seifuddin FT, Turner G, Haft D, Nierman WC, Wolfe KH, et al. SMURF: Genomic mapping of fungal secondary metabolite clusters. Fungal Genet Biol. 2010;47:736–41. Available from: http://dx.doi.org/10.1016/j.fgb.2010.06.003.PubMedPubMed CentralView ArticleGoogle Scholar
- Ohtaki S, Maeda H, Takahashi T, Yamagata Y, Hasegawa F, Gomi K, et al. Novel hydrophobic surface binding protein, HsbA, produced by Aspergillus oryzae. Appl Environ Microbiol. 2006;72:2407–13. Available from: http://dx.doi.org/10.1128/AEM.72.4.2407-2413.2006.PubMedPubMed CentralView ArticleGoogle Scholar
- Skamnioti P, Gurr SJ. Cutinase and hydrophobin interplay: A herald for pathogenesis? Plant Signal Behav. 2008;3:248–50.PubMedPubMed CentralView ArticleGoogle Scholar
- Niderman T, Genetet I, Bruyère T, Gees R, Stintzi A, Legrand M, et al. Pathogenesis-related PR-1 proteins are antifungal. Isolation and characterization of three 14-kilodalton proteins of tomato and of a basic PR-1 of tobacco with inhibitory activity against Phytophthora infestans. Plant Physiol. 1995;108:17–27. Available from: http://dx.doi.org/10.1104/pp.108.1.17.PubMedPubMed CentralView ArticleGoogle Scholar
- Van Loon LC, Van Strien EA. The families of pathogenesis-related proteins, their activities, and comparative analysis of PR-1 type proteins. Physiol Mol Plant Pathol. 1999;55:85–97. Available from: http://dx.doi.org/10.1006/pmpp.1999.0213.View ArticleGoogle Scholar
- Prados-Rosales RC, Roldán-Rodríguez R, Serena C, López-Berges MS, Guarro J, Martínez-del-Pozo Á, et al. A PR-1-like protein of Fusarium oxysporum functions in virulence on mammalian hosts. J Biol Chem. 2012;287:21970–9. Available from: http://dx.doi.org/10.1074/jbc.M112.364034.PubMedPubMed CentralView ArticleGoogle Scholar
- Teixeira PJPL, Thomazella DPT, Vidal RO, do Prado PFV, Reis O, Baroni RM, et al. The fungal pathogen Moniliophthora perniciosa has genes similar to plant PR-1 that are highly expressed during its interaction with cacao. PLoS ONE. 2012;7:e45929. Available from: http://dx.doi.org/10.1371/journal.pone.0045929.PubMedPubMed CentralView ArticleGoogle Scholar
- Király L, Barna B, Király Z. Plant resistance to pathogen infection: forms and mechanisms of innate and acquired resistance. J Phytopathol. 2007;155:385–96. Available from: http://dx.doi.org/10.1111/j.1439-0434.2007.01264.x.View ArticleGoogle Scholar
- Yamamoto S, Katagiri M, Maeno H, Hayaishi O. Salicylate hydroxylase, a monooxygenase requiring flavin adenine dinucleotide: I. Purification and general properties. J Biol Chem. 1965;240:3408–13.PubMedGoogle Scholar
- Ambrose KV, Tian ZP, Wang YF, Smith J, Zylstra G, Huang BR, et al. Functional characterization of salicylate hydroxylase from the fungal endophyte Epichloë festucae. Sci. Rep. [Internet]. 2015;5:10939. Available from: http://dx.doi.org/10.1038/srep10939.
- Teichert I, Wolff G, Kueck U, Nowrousian M. Combining laser microdissection and RNA-seq to chart the transcriptional landscape of fungal development. Bmc Genomics. 2012;13:511. Available from: http://dx.doi.org/10.1186/1471-2164-13-511.PubMedPubMed CentralView ArticleGoogle Scholar
- Grognet P, Bidard F, Kuchly C, Tong LCH, Coppin E, Benkhali JA, et al. Maintaining two mating types: structure of the mating type locus and its role in heterokaryosis in Podospora anserina. Genetics. 2014;197:421–32. Available from: http://dx.doi.org/10.1534/genetics.113.159988.PubMedPubMed CentralView ArticleGoogle Scholar
- Ashburner M, Ball C, Blake J, Botstein D, Butler H, Cherry J, et al. Gene ontology: tool for the unification of biology. The Gene Ontology Consortium. Nat Genet. 2000;25:25–9.PubMedPubMed CentralView ArticleGoogle Scholar
- Conesa A, Gotz S, Garcia-Gomez JM, Terol J, Talon M, Robles M. Blast2GO: a universal tool for annotation, visualization and analysis in functional genomics research. Bioinformatics. 2005;21:3674–6. Available from: http://dx.doi.org/10.1093/bioinformatics/bti610.PubMedView ArticleGoogle Scholar
- Conesa A, Götz S. Blast2GO: a comprehensive suite for functional analysis in plant genomics. Int J Plant Genomics. 2008;2008:12. Available from: http://dx.doi.org/10.1155/2008/619832.View ArticleGoogle Scholar
- Zdobnov EM, Apweiler R. InterProScan – an integration platform for the signature-recognition methods in InterPro. Bioinformatics. 2001;17:847–8. Available from: http://dx.doi.org/10.1093/bioinformatics/17.9.847.PubMedView ArticleGoogle Scholar
- Quevillon E, Silventoinen V, Pillai S, Harte N, Mulder N, Apweiler R, et al. InterProScan: protein domains identifier. Nucleic Acids Res. 2005;33:W116–20. Available from: http://dx.doi.org/10.1093/nar/gki442.PubMedPubMed CentralView ArticleGoogle Scholar
- Lombard V, Golaconda Ramulu H, Drula E, Coutinho PM, Henrissat B. The carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 2014;42:D490–5. Available from: http://dx.doi.org/10.1093/nar/gkt1178.PubMedView ArticleGoogle Scholar
- Stergiopoulos I, de Wit PJ. Fungal effector proteins. Annu Rev Phytopathol. 2009;47:233–63. Available from: http://dx.doi.org/10.1146/annurev.phyto.112408.132637.PubMedView ArticleGoogle Scholar
- Emanuelsson O, Brunak S, von Heijne G, Nielsen H. Locating proteins in the cell using TargetP, SignalP and related tools. Nat Protoc. 2007;2:953–71. Available from: http://dx.doi.org/10.1038/nprot.2007.131.PubMedView ArticleGoogle Scholar
- Tan K, Oliver RP, Solomon PS, Moffat CS. Proteinaceous necrotrophic effectors in fungal virulence. Funct Plant Biol. 2010;37:907–12. Available from: http://dx.doi.org/10.1071/FP10067.View ArticleGoogle Scholar
- van den Burg HA, Westerink N, Francoijs K-J, Roth R, Woestenenk E, Boeren S, et al. Natural disulfide bond-disrupted mutants of AVR4 of the tomato pathogen Cladosporium fulvum are sensitive to proteolysis, circumvent Cf-4-mediated resistance, but retain their chitin binding ability. J Biol Chem. 2003;278:27340–6. Available from: http://dx.doi.org/10.1074/jbc.M212196200.PubMedView ArticleGoogle Scholar
- Petersen TN, Brunak S, von Heijne G, Nielsen H. SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods. 2011;8:785–6. Available from: http://dx.doi.org/10.1038/nmeth.1701.PubMedView ArticleGoogle Scholar
- van den Burg HA, Harrison SJ, Joosten MHAJ, Vervoort J, de Wit PJGM. Cladosporium fulvum Avr4 protects fungal cell walls against hydrolysis by plant chitinases accumulating during infection. Mol Plant Microbe Interact. 2006;19:1420–30. Available from: http://dx.doi.org/10.1094/MPMI-19-1420.PubMedView ArticleGoogle Scholar
- Krasnoff SB, Gibson DM, Belofsky GN, Gloer KB, Gloer JB. New destruxins from the entomopathogenic fungus Aschersonia sp. J Nat Prod. 1996;59:485–9. Available from: http://dx.doi.org/10.1021/np9601216.View ArticleGoogle Scholar
- Lira SP, Vita-marques AM, Seleghim MHR, Bugni TS, Labarbera DV, Sette LD, et al. New destruxins from the marine-derived fungus Beauveria felina. J Antibiot. 2006;59:553–63. Available from: http://dx.doi.org/10.1038/ja.2006.76.PubMedView ArticleGoogle Scholar
- Wang B, Kang Q, Lu Y, Bai L, Wang C. Unveiling the biosynthetic puzzle of destruxins in Metarhizium species. Proc Natl Acad Sci. 2012;109:1287–92. Available from: http://dx.doi.org/10.1073/pnas.1115983109.
- Buchwaldt L, Jensen JS. HPLC purification of destruxins produced by Alternaria brassicae in culture and leaves of Brassica napus. Phytochemistry. 1991;30:2311–6. Available from: http://dx.doi.org/10.1016/0031-9422(91)83638-2.View ArticleGoogle Scholar
- Buchwaldt L, Green H. Phytotoxicity of destruxin B and its possible role in the pathogenesis of Alternaria brassicae. Plant Pathol. 1992;41:55–63. Available from: http://dx.doi.org/10.1111/j.1365-3059.1992.tb02316.x.View ArticleGoogle Scholar
- Venkatasubbaiah P, Tisserat NA, Chilton WS. Metabolites of Ophiosphaerella herpotricha, a cause of spring dead spot of bermudagrass. Mycopathologia. 1994;128:155–9. Available from: http://dx.doi.org/10.1007/BF01138477.View ArticleGoogle Scholar
- Parada RY, Oka K, Yamagishi D, Kodama M, Otani H. Destruxin B produced by Alternaria brassicae does not induce accessibility of host plants to fungal invasion. Physiol Mol Plant Pathol. 2007;71:48–54. Available from: http://dx.doi.org/10.1016/j.pmpp.2007.10.003.View ArticleGoogle Scholar
- Jenke-Kodama H, Dittmann E. Bioinformatic perspectives on NRPS/PKS megasynthases: advances and challenges. Nat Prod Rep. 2009;26:874–83. Available from: http://dx.doi.org/10.1039/b810283j.PubMedView ArticleGoogle Scholar
- de Boer AH, de Vries-van Leeuwen IJ. Fusicoccanes: diterpenes with surprising biological functions. Trends Plant Sci. 2012;17:360–8. Available from: http://dx.doi.org/10.1016/j.tplants.2012.02.007.PubMedView ArticleGoogle Scholar
- Minami A, Tajima N, Higuchi Y, Toyomasu T, Sassa T, Kato N, et al. Identification and functional analysis of brassicicene C biosynthetic gene cluster in Alternaria brassicicola. Bioorg Med Chem Lett. 2009;19:870–4. Available from: http://dx.doi.org/10.1016/j.bmcl.2008.11.108.PubMedView ArticleGoogle Scholar
- Pazzagli L, Cappugi G, Manao G, Camici G, Santini A, Scala A. Purification, characterization, and amino acid sequence of cerato-platanin, a new phytotoxic protein from Ceratocystis fimbriata f. sp. platani. J Biol Chem. 1999;274:24959–64. Available from: http://dx.doi.org/10.1074/jbc.274.35.24959.PubMedView ArticleGoogle Scholar
- Chen H, Kovalchuk A, Kerio S, Asiegbu FO. Distribution and bioinformatic analysis of the cerato-platanin protein family in Dikarya. Mycologia. 2013;105:1479–88. Available from: http://dx.doi.org/10.3852/13-115.PubMedView ArticleGoogle Scholar
- Frischmann A, Neudl S, Gaderer R, Bonazza K, Zach S, Gruber S, et al. Self-assembly at air/water interfaces and carbohydrate binding properties of the small secreted protein EPL1 from the fungus Trichoderma atroviride. J Biol Chem. 2013;288:4278–87. Available from: http://dx.doi.org/10.1074/jbc.M112.427633.PubMedView ArticleGoogle Scholar
- Baccelli I. Cerato-platanin family proteins: one function for multiple biological roles? Front Plant Sci. 2014;5:769. Available from: http://dx.doi.org/10.3389/fpls.2014.00769.PubMedGoogle Scholar
- Gaderer R, Bonazza K, Seidl-Seiboth V. Cerato-platanins: a fungal protein family with intriguing properties and application potential. Appl Microbiol Biotechnol. 2014;98:4795–803. Available from: http://dx.doi.org/10.1007/s00253-014-5690-y.PubMedPubMed CentralView ArticleGoogle Scholar
- Briza P, Winkler G, Kalchhauser H, Breitenbach M. Dityrosine is a prominent component of the yeast ascospore wall. A proof of its structure. J Biol Chem. 1986;261:4288–94.PubMedGoogle Scholar
- Briza P, Ellinger A, Winkler G, Breitenbach M. Characterization of a DL-dityrosine-containing macromolecule from yeast ascospore walls. J Biol Chem. 1990;265:15118–23.PubMedGoogle Scholar
- Prillinger H, Schweigkofler W, Breitenbach M, Briza P, Staudacher E, Lopandic K, et al. Phytopathogenic filamentous (Ashbya, Eremothecium) and dimorphic fungi (Holleya, Nematospora) with needle-shaped ascospores as new members within the Saccharomycetaceae. Yeast. 1997;13:945–60. Available from: http://dx.doi.org/10.1002/(SICI)1097-0061(199708)13:10<945::AID-YEA150>3.0.CO;2-5.PubMedView ArticleGoogle Scholar
- Smail EH, Briza P, Panagos A, Berenfeld L. Candida albicans cell walls contain the fluorescent cross-linking amino acid dityrosine. Infect Immun. 1995;63:4078–83.PubMedPubMed CentralGoogle Scholar
- Visca P, Imperi F, Lamont IL. Pyoverdine siderophores: from biogenesis to biosignificance. Trends Microbiol. 2007;15:22–30. Available from: http://dx.doi.org/10.1016/j.tim.2006.11.004.PubMedView ArticleGoogle Scholar
- Wittenberg AHJ, van der Lee TAJ, Ben M’Barek S, Ware SB, Goodwin SB, Kilian A, et al. Meiosis drives extraordinary genome plasticity in the haploid fungal plant pathogen Mycosphaerella graminicola. Plos One. 2009;4. Available from: http://dx.doi.org/10.1371/journal.pone.0005863.
- Goodwin SB, Ben M’Barek S, Dhillon B, Wittenberg AHJ, Crane CF, Hane JK, et al. Finished genome of the fungal wheat pathogen Mycosphaerella graminicola reveals dispensome structure, chromosome plasticity, and stealth pathogenesis. PLoS Genet. 2011;7:e1002070. Available from: http://dx.doi.org/10.1371/journal.pgen.1002070.PubMedPubMed CentralView ArticleGoogle Scholar
- Tsuge T, Harimoto Y, Hanada K, Akagi Y, Kodama M, Akimitsu K, et al. Evolution of pathogenicity controlled by small, dispensable chromosomes in Alternaria alternata pathogens. Physiol Mol Plant Pathol. 2016;95:27–31. Available from: http://dx.doi.org/10.1016/j.pmpp.2016.02.009.View ArticleGoogle Scholar
- Walton JD, Ahn J-H, Akimitsu K, Pitkin JW, Ransom R. Leaf-spot disease of maize: chemistry, biochemistry, and molecular biology of a host-selective cyclic peptide. In: Daniels MJ, Downie JA, Osbourn AE, editors. Adv. Mol. Genet. Plant-Microbe Interact. Vol 3 Proc. 7th Int. Symp. Mol. Plant-Microbe Interact. Edinb. UK June 1994 [Internet]. Dordrecht: Springer Netherlands; 1994. p. 231–7. Available from: http://dx.doi.org/10.1007/978-94-011-0177-6_34.Google Scholar
- Kistler HC, Meinhardt LW, Benny U. Mutants of Nectria haematococca created by a site-directed chromosome breakage are greatly reduced in virulence toward pea. Mol Plant Microbe Interact. 1996;9:804–9. Available from: http://dx.doi.org/10.1094/MPMI-9-0804.View ArticleGoogle Scholar
- Wasmann CC, VanEtten HD. Transformation-mediated chromosome loss and disruption of a gene for pisatin demethylase decrease the virulence of Nectria haematococca on pea. Mol Plant Microbe Interact. 1996;9:793–803. Available from: http://dx.doi.org/10.1094/MPMI-9-0793.View ArticleGoogle Scholar
- Enkerli J, Bhatt G, Covert SF. Maackiain detoxification contributes to the virulence of Nectria haematococca MP VI on chickpea. Mol Plant Microbe Interact. 1998;11:317–26. Available from: http://dx.doi.org/10.1094/MPMI.1998.11.4.317.View ArticleGoogle Scholar
- Molina GC, Krausz JP. Toxin production of Mycosphaerella fijiensis var. difformis. Phytopathology. 1987;77:1747.Google Scholar
- Hoss R, Helbig J, Bochow H. Function of host and fungal metabolites in resistance response of banana and plantain in the Black Sigatoka disease pathosystem (Musa spp. - Mycosphaerella fijiensis). J. Phytopathol. 2000;148:387–94. Available from: http://dx.doi.org/10.1046/j.1439-0434.2000.00530.x.View ArticleGoogle Scholar
- El Hadrami A, Kone D, Lepoivre P. Effect of juglone on active oxygen species and antioxidant enzymes in susceptible and partially resistant banana cultivars to Black Leaf Streak Disease. Eur J Plant Pathol. 2005;113:241–54. Available from: http://dx.doi.org/10.1007/s10658-005-8675-y.View ArticleGoogle Scholar
- Busogoro JP, Etame JJ, Harelimana G, Lognay G, Messiaen J, Lepoivre P, et al. Experimental evidence for the action of M. fijiensis toxins on banana photosynthetic apparatus. In: Mohan JS, Swennen R, editors. Banana Improv. Cell Mol Biol Induc Mutat. Enfield: Science Publishers. 2004;161–70.Google Scholar
- Turner NC, Graniti A. Fusicoccin - a fungal toxin that opens stomata. Nature. 1969;223:1070–1.View ArticleGoogle Scholar
- MacKinnon SL, Keifer P, Ayer WA. Components from the phytotoxic extract of Alternaria brassicicola, a black spot pathogen of canola. Phytochemistry. 1999;51:215–21. Available from: http://dx.doi.org/10.1016/S0031-9422(98)00732-8.View ArticleGoogle Scholar
- Fang X, Qiu F, Yan B, Wang H, Mort AJ, Stark RE. NMR studies of molecular structure in fruit cuticle polyesters. Phytochemistry. 2001;57:1035–42. Available from: http://dx.doi.org/10.1016/S0031-9422(01)00106-6.PubMedView ArticleGoogle Scholar
- Snoeijers SS, Perez-Garcia A, Joosten M, De Wit P. The effect of nitrogen on disease development and gene expression in bacterial and fungal plant pathogens. Eur J Plant Pathol. 2000;106:493–506. Available from: http://dx.doi.org/10.1023/A:1008720704105.View ArticleGoogle Scholar
- Talbot NJ, Ebbole DJ, Hamer JE. Identification and characterization of MPG1, a gene involved in pathogenicity from the rice blast fungus Magnaporthe grisea. Plant Cell. 1993;5:1575–90. Available from: http://dx.doi.org/10.1105/tpc.5.11.1575.PubMedPubMed CentralView ArticleGoogle Scholar
- Skamnioti P, Gurr SJ. Magnaporthe grisea cutinase2 mediates appressorium differentiation and host penetration and is required for full virulence. Plant Cell. 2007;19:2674–89. Available from: http://dx.doi.org/10.1105/tpc.107.051219.PubMedPubMed CentralView ArticleGoogle Scholar
- Peraza-Echeverría L, Rodríguez-García C, Zapata-Salazar D. A rapid, effective method for profuse in vitro conidial production of Mycosphaerella fijiensis. Austr Plant Pathol. 2008;37:460–3. Available from: http://dx.doi.org/10.1071/AP08042.View ArticleGoogle Scholar
- Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal, May. 2011;17:10–12 ISSN 2226-6089. Available at: [http://journal.embnet.org/index.php/embnetjournal/article/view/200/479]. Date accessed: 24 Aug. 2016. doi:http://dx.doi.org/10.14806/ej.17.1.200.
- Droc G, Larivière D, Guignon V, Yahiaoui N, This D, Garsmeur O, et al. The Banana Genome Hub. Database [Internet]. 2013;2013. Available from: http://database.oxfordjournals.org/content/2013/bat035.abstract.
- D’Hont A, Denoeud F, Aury J-M, Baurens F-C, Carreel F, Garsmeur O, et al. The banana (Musa acuminata) genome and the evolution of monocotyledonous plants. Nature. 2012;488:213–7. Available from: http://dx.doi.org/10.1038/nature11241.PubMedView ArticleGoogle Scholar
- Trapnell C, Pachter L, Salzberg SL. TopHat: discovering splice junctions with RNA-Seq. Bioinformatics. 2009;25:1105–11. Available from: http://dx.doi.org/10.1093/bioinformatics/btp120.PubMedPubMed CentralView ArticleGoogle Scholar
- Anders S, Pyl PT, Huber W. HTSeq-a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015;31:166–9. Available from: http://dx.doi.org/10.1093/bioinformatics/btu638.PubMedView ArticleGoogle Scholar
- Love MI, Huber W, Anders S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 2014;15. Available from: http://dx.doi.org/10.1186/s13059-014-0550-8.
- Livak KJ, Schmittgen TD. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔC T method. Methods. 2001;25:402–8. Available from: http://dx.doi.org/10.1006/meth.2001.1262.PubMedView ArticleGoogle Scholar
- Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32:1792–7. Available from: http://dx.doi.org/10.1093/nar/gkh340.PubMedPubMed CentralView ArticleGoogle Scholar
- Maddison WP, Maddison DR. Mesquite: a modular system for evolutionary analysis. 2015. Version 3.04Available from: http://mesquiteproject.org.Google Scholar
- Keane TM, Creevey CJ, Pentony MM, Naughton TJ, Mclnerney JO. Assessment of methods for amino acid matrix selection and their use on empirical data shows that ad hoc assumptions for choice of matrix are not justified. BMC Evol Biol. 2006;6:29. Available from: http://dx.doi.org/10.1186/1471-2148-6-29.PubMedPubMed CentralView ArticleGoogle Scholar
- Silvestro D, Michalak I. raxmlGUI: a graphical front-end for RAxML. Org Divers Evol. 2012;12:335–7. Available from: http://dx.doi.org/10.1007/s13127-011-0056-0.View ArticleGoogle Scholar
- Jones DT, Taylor WR, Thornton JM. The rapid generation of mutation data matrices from protein sequences. Comp Appl Biosci. 1992;8:275–82.PubMedGoogle Scholar
- Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, et al. UCSF Chimera—A visualization system for exploratory research and analysis. J Comput Chem. 2004;25:1605–12. Available from: http://dx.doi.org/10.1002/jcc.20084.PubMedView ArticleGoogle Scholar
- Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res. 1994;22:4673–80. Available from: http://dx.doi.org/10.1093/nar/22.22.4673.PubMedPubMed CentralView ArticleGoogle Scholar
- Williams RJ, Eakin RE, Snell EE. The relationship of inositol, thiamin, biotin, pantothenic acid and vitamin B6 to the growth of yeasts. J Am Chem Soc. 1940;62:1204–7. Available from: http://dx.doi.org/10.1021/ja01862a062.View ArticleGoogle Scholar
- Yamamoto LA, Segel IH. The inorganic sulfate transport system of Penicillium chrysogenum. Arch Biochem Biophys. 1966;114:523–38. Available from: http://dx.doi.org/10.1016/0003-9861(66)90376-6.PubMedView ArticleGoogle Scholar
- Rao TK, DeBusk AG. An inducible acetate transport system in Neurospora crassa conidia. Biochim. Biophys. Acta BBA - Biomembr. 1977;470:475–83. Available from: http://dx.doi.org/10.1016/0005-2736(77)90138-9.View ArticleGoogle Scholar
- Chaure PT, Connerton IF. Derepression of the glyoxylate cycle in mutants of Neurospora crassa accelerated for growth on acetate. Microbiology. 1995;141:1315–20. Available from: http://dx.doi.org/10.1099/13500872-141-6-1315.View ArticleGoogle Scholar
- Jennings DH. The physiology of fungal nutrition. Cambridge: Cambridge University Press; 1995.Google Scholar
- Marzluf GA. Molecular genetics of sulfur assimilation in filamentous fungi and yeast. Annu Rev Microbiol. 1997;51:73–96. Available from: http://dx.doi.org/10.1146/annurev.micro.51.1.73.PubMedView ArticleGoogle Scholar
- Casal M, Paiva S, Andrade RP, Gancedo C, Leão C. The lactate-proton symport of Saccharomyces cerevisiae is encoded by JEN1. J Bacteriol. 1999;181:2620–3.PubMedPubMed CentralGoogle Scholar
- Carlsen M, Nielsen J. Influence of carbon source on α-amylase production by Aspergillus oryzae. Appl Microbiol Biotechnol. 2001;57:346–9. Available from: http://dx.doi.org/10.1007/s002530100772.PubMedView ArticleGoogle Scholar
- Waters BM, Blevins DG, Eide DJ. Characterization of FRO1, a pea ferric-chelate reductase involved in root iron acquisition. Plant Physiol. 2002;129:85–94. Available from: http://dx.doi.org/10.1104/pp.010829.PubMedPubMed CentralView ArticleGoogle Scholar
- Paiva S, Devaux F, Barbosa S, Jacq C, Casal M. Ady2p is essential for the acetate permease activity in the yeast Saccharomyces cerevisiae. Yeast. 2004;21:201–10. Available from: http://dx.doi.org/10.1002/yea.1056.PubMedView ArticleGoogle Scholar
- Dumay QC, Debut AJ, Mansour NM, Saier Jr MH. The copper transporter (Ctr) family of Cu + uptake systems. J Mol Microbiol Biotechnol. 2006;11:10–9. Available from: http://dx.doi.org/10.1159/000092815.PubMedView ArticleGoogle Scholar
- Lagaert S, Pollet A, Courtin CM, Volckaert G. β-Xylosidases and α-l-arabinofuranosidases: Accessory enzymes for arabinoxylan degradation. Biotechnol. Adv. 2014;32:316–32. Available from: http://dx.doi.org/10.1016/j.biotechadv.2013.11.005.Google Scholar
