Comparative acetylome analysis reveals the potential roles of lysine acetylation for DON biosynthesis in Fusarium graminearum

Difference of the acetylated proteins between the wild type and Fggcn5 deletion mutant

The predicted gene in the F. graminearum genome, FGRAMPH1_01T00753, is orthologous to yeast GCN5 and its lysine acetyltransferase activity was confirmed in a previous study [23]. To gain insights into the possible acetylome regulated by FgGCN5 in F. graminearum, we generated the gene deletion construct by the split-marker approach [24] and transformed it into the wild-type strain PH-1. As shown in Fig. 1, the Fggcn5 deletion mutant significantly reduced hyphae growth (growth rate is 53.45% of PH-1), and failed to produce DON.

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To identify proteins acetylated by FgGCN5, total proteins were isolated from PH-1 and Fggcn5 mutant. After digestion with trypsin, lysine-acetylated peptides were enriched with the anti-acetyl-lysine antibody and analyzed with LC-MS/MS as described [25]. A total of 2626 lysine acetylation sites (Additional file 1: Table S1) were identified in 1875 proteins from PH-1 and Fggcn5 mutant (Additional file 2: Table S2). Among them, 95 proteins were differentially acetylated at a significant level of Ratio > + /− 2 (p < 0.05) in the Fggcn5 deletion mutant in comparison with PH-1. 43 proteins were up-regulated, 52 were down-regulated in the mutant (Additional file 3: Table S3). It is possible that the acetylation down-regulated proteins in the Fggcn5 mutant function in a positive slight role in the DON biosynthesis, while the up-regulated proteins play the opposite role.

The abundance of acetylated proteins detected in this study indicated that lysine acetylation is a common protein modification in F. graminearum similar to the observations in other living organisms [12, 13, 14, 15]. Approximately 14.24% of the acetylated proteins identified in this study were only detected in the wild type strain and are potential targets of FgGCN5 lysine acetyltransferase.

Functional annotation and enrichment analysis of the proteins differentially acetylated in PH-1 and the Fggcn5 mutant

To determine the functions of acetylated proteins, we analyzed GO annotation and classified the identified proteins according to their biological processes, molecular functions and cellular compartments. In the GO biological processes, 59 proteins were involved in metabolic processes, 59 in cellular processes, 15 in biological regulation, and 14 in the regulation of biological processes and cellular compartment organization or biogenesis. According to GO molecular function category, 42 proteins were involved in catalytic activities, 45 in binding activities, and 17 in structural molecular activity. With respect to the cellular compartments on level 2, 59 proteins were cell proteins, 58 were cell part proteins, 49 were organelle proteins, 30 were macromolecular-complex proteins, 24 were organelle part proteins, and 10 were membrane-enclosed lumen proteins (Fig. 2a).

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Furthermore, the GO enrichment analysis was performed to identify the biological processes and molecular functions of the acetylated proteins (Fig. 2b, Additional file 5: Table S5). The results showed that the acetylated proteins identified in this study were significantly enriched in several GO biological processes, including monocarboxylic acid metabolism, pyridine nucleotide metabolism, nicotinamide nucleotide metabolism, pyruvate metabolic process, glucose 6-phosphate metabolic process, glyceraldehyde-3- phosphate metabolic process, and NADP metabolic process. In the GO molecular functions, most of the acetylated proteins were significantly enriched in structural molecular activity, structural constituent of ribosome, oxidoreductase activity. From the GO cellular compartment categories, we found that a great proportion of the identified acetylated proteins were in intracellular non-membrane-bounded organelles, ribonucleoprotein complexes, and ribosome.

The KEGG-pathways in which the acetylated proteins involved were analyzed (Fig. 3a). The results revealed that proteins were enriched in several conserved pathways such as ribosomes, glycolysis/gluconeogenesis and citrate cycle (TCA cycle) (Fig. 3b, Additional file 6: Table S6). Moreover, the KEGG-pathways enriched in fatty acid biosynthesis, pyruvate metabolism suggested that the acetylation play important roles in cell metabolic processes. It is in agreement with the well-established conclusion that lysine acetylation plays key roles in regulation of the metabolic pathways [8, 17, 40]. Further, the acetylate form of the enzymes involved in the acetyl-CoA synthesis, such as pyruvate dehydrogenase E2 (FG04171.1) and long-chain acyl-CoA synthetase (FG08543.1) were detected only in PH-1 but not in the Fggcn5 mutant. It should be noted that the acetyl-CoA is essential for the DON synthesis. Therefore, the GO and KEGG enrichment provided powerful evidence for the role of acetylation in DON synthesis.

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Protein-protein interaction network analysis

To better understand the cellular processes regulated by lysine acetylation, the protein-protein interaction network was predicted as described [41]. In total, 93 acetylated proteins were mapped into the protein-protein interaction network (Additional file 7: Table S7). As shown in Fig. 4, the network overviews the physical and functional interactions of the acetylated proteins in F. graminearum. Obviously, the ribosome-associated proteins, metabolism-associated proteins, especially proteins involved in the citrate cycle were specifically enriched. These findings suggest that acetylation plays a key role in protein biosynthesis and central metabolic processes. Interestingly, the core component of nucleosome Histone H3 and Histone H2B were involved in the network. The H3-interacting protein (FGSG-08173) is predicted to be homologous to the Pim1 Ser/Thr protein kinase, which plays an important role in signal transduction related to energy metabolism and cell proliferation and survival in humans [42, 43]. Another H3-interacting protein (FGSG_10,040) is predicted to encode FACT complex subunit SPT16, which was demonstrated to participate in specific regulation on genes transcription in yeast [44]. It was well demonstrated that acetylation of histone H3 by FgGCN5 is directly related to DON biosynthesis [45]. It is possible that histone H3 was co-regulated by FgGCN5 and kinase FGSG-08173. The acetylation and phosphorylation of histone H3 contributes to the activation or inactivation of FGSG-10040 in the FACT complex, which in turn affects the re-organization of nucleosomes. As a result, the transcription of genes involved in the DON production were initiated or blocked.

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Proteins acetylated in PH-1 involved in DON biosynthesis

Since the Fggcn5 gene deletion mutant was defective in DON biosynthesis, lysine acetylation manipulated by FgGCN5 likely plays important regulatory roles in DON biosynthesis in F. graminearum. In this study, we found that some proteins involved in DON production are the potential acetylation targets of FgGCN5.

GzBrom002 (FGSG_06291) encoding a transcription factor plays essential roles in DON production, virulence, asexual and sexual reproduction. The gene deletion mutant GzBrom002 completely lost virulence on wheat, ability in DON production and asexual and sexual spores production [28]. A Homocysteine transferase gene (FGSG_10825) is also multifunctional in F. graminearum. Phenotype assays showed that the virulence and DON production were reduced in the gene deletion mutant Moreover, the mutant failed to produce perithecia and aerial mycelia [29]. Another gene FGK3 (FGSG-07329), encodes a glycogen synthase kinase orthologous to mammalian GSK3. The gene deletion mutant Δfgk3 is defective in DON production [30]. FgGCN5 might positively regulate DON biosynthesis through acetylating these proteins.

It has been well demonstrated that cAMP- dependent protein kinase (PKA) plays critical roles in DON biosynthesis in F. graminearum [46, 47]. In this study, PKR (FGSG_09908), the regulatory subunit of PKA, was found to be acetylated in PH-1 but not in the Fggcn5 mutant. The result indicates that the PKR may be one of the substrates of FgGCN5 acetyltransferase in F. graminearum. However, PKR acts as a negative factor in DON production as the DON content was increased in the gene deletion mutant of PKR [31]. This suggests that the negative effect of PRK on DON biosynthesis may be limited by FgGCN5 through lysine acetylation.

Proteins acetylated in Fggcn5 mutant are associated with DON production

Proteins acetylated specifically in Fggcn5 mutant were identified as well, suggesting that the proteins are targets of other KATs rather than FgGCN5. Interestingly, some proteins were proved to be associated with DON biosynthesis.

It is well known on the functions of some TRI genes in DON biosynthesis. In this study, the acetylated TRI15 (FGSG_11205) was detected only in the Fggcn5 mutant. TRI15, encoding a Cys2-His2 zinc finger protein, acts as a negative regulator of the trichothecene biosynthetic genes [39, 48]. It is likely that TRI15 is activated by other KATs and thereby plays a negative role in DON production in Fggcn5 mutant.

Additionally, FgHXK1(FGSG_00500) encodes a rate-limiting enzyme in DON biosynthesis. DON production was severely inhibited in the gene deletion mutant. Moreover, the ΔFgHXK1 mutant is nonpathogenic on wheat, defective in hyphae growth and conidiation [33]. Some transcription factors identified in this study were also characterized to play key roles in DON production and pathogen virulence including GzHMG002 (FGSG_00385), GzCCHC011 (FGSG_10716) and GzZC230 (FGSG_07133) [28]. Recently, a ATP-binding cassette (ABC) transporte FgArb1 (FGSG_04181) was proved to function in pathogenesis and DON production in F. graminearum, as the virulence and DON production were dramatically reduced in the gene deletion mutant [36]. It is likely that acetylation of these proteins by other KATs in the absence of FgGCN5 leads to the inactivation of the genes, and finally leads to the inhibition of the DON production in Fggcn5 mutant.

Generation of Fggcn5 mutant

DON content measurement assay

DON content in LTB cultures [50, 51] was assayed with a competitive enzyme-linked immunosorbent assay (ELISA) based DON detection plate kit (Beacon Analytical Systems, Inc., USA) after incubation at 25 °C for 5 days, as described by Gardiner et al. [1]. In the assay, the Tri5 deletion mutant was used as a negative control.

Strains culture conditions

The wild-type strain PH-1 and the gene deletion mutant Fggcn5 of F. graminearum were cultured on potato dextrose agar (PDA) at 25 °C for 4 d. The mycelia were harvested and ground with MiniBead Beater-16 (Biospec, USA) at 30 Hz for 30 s. The ground mycelium were then cultured in 100 mL liquid YEPD medium with shaking at 25 °C for 24 h. Subsequently, the mycelium was collected by filtration with sterile macrocloth and was then incubated in DON inducing medium in the dark with shaking at 25 °C for 4 d. The DON inducing medium was prepared as described by Gardiner et al. [1].

Protein extraction and trypsin digestion

The procedures of protein extraction and peptide digestion were modified from a previous report [15]. In brief, the mycelia samples were harvested and ground into cell powder in liquid nitrogen. The resulting cell powder was then transferred into 5 × volume of TCA/acetone (1:9, containing 65 mM DTT) and mixed by vortex. After placed at − 20 °C overnight, the mixture was centrifuged at 7000×g for 20 min at 4 °C. The precipitate was washed with ice-cold acetone for three times and was air-dried at 4 °C. The dried precipitate was then resolved in UA buffer (8 M urea, 150 mM Tris-HCl, Ph8.0) and sonicated 10 times (10 s burst with a 15 s interval for each time) on ice using a high intensity ultrasonic processor (Scientz, Ningbo, China). After centrifuged at 14,000 g for 40 min, the supernatant was filtered with 0.45 μm filters. The filtrate was quantified with the BCA Protein Assay Kit (Bio-Rad, USA).

The resulting protein solution was reduced with 10 mM DTT for 1 h at 37 °C and alkylated with 20 mM iodoacetamide for 45 min at room temperature in darkness. For trypsin digestion, 100 mM (NH₄)₂CO₃ was added to urea concentration less than 2 M. Finally, trypsin was added at an enzyme-to-substrate mass ratio of 1:50 overnight and additional trypsin was added at an enzyme-to-substrate mass ratio of 1:100 for 4 h to ensure complete digestion.

Immunoaffinity enrichment

The sample was separated into fractions by high pH reverse-phase HPLC followed Zhou et al. [15]. As a result, the tryptic peptides were separated into 6 fractions which were then dried by vacuum centrifuging.

The purification and enrichment of lysine acetylated peptides were performed as described [15, 52]. Briefly, tryptic peptides were re-dissolved in NETN buffer (100 mM NaCl, 1 mM EDTA, 50 mM Tris-HCl, 0.5% NP-40, pH 8.0). Subsequently, the pre-washed agarose-conjugated anti-acetyllysine antibody beads (Cat. No. 104, PTM Biolabs, Hangzhou, China) were added. The tryptic peptides were incubated at 4 °C overnight with gentle shaking. The beads were then washed four times with NETN buffer and twice with pure water. Finally, the bound peptides were eluted from the beads with 0.1% trifluoroacetic acid and were then vacuum-dried. The resulting peptides were cleaned with C18 ZipTips (Millipore, Billerica, MA) according to the manufacturer’s instructions before LC-MS/MS analysis.

LC-MS/MS analysis

LC-MS/MS analysis was performed as described [53] with modification. In the assay, a Q-Exactive mass spectrometer (Thermo Scientific) coupled to Easy nLC (Proxeon Biosystems, now Thermo Fisher Scientific) was used. The mass spectrometer was operated in positive ion mode. MS data was acquired using a data-dependent top10 method dynamically choosing the most abundant precursor ions from the survey scan (300–1800 m/z) for HCD fragmentation. Automatic gain control (AGC) target was set to 3e⁶, and maximum inject time to 10 ms. Dynamic exclusion duration was 40.0 s. Survey scans were acquired at a resolution of 70,000 at m/z 200 and resolution for HCD spectra was set to 17,500 at m/z 200, and isolation width was 2 m/z. Normalized collision energy was 30 eV and the underfill ratio, which specifies the minimum percentage of the target value likely to be reached at maximum fill time, was defined as 0.1%. The instrument was run with peptide recognition mode enabled.

Database search

The resulting MS/MS data was processed using MaxQuant with integrated Andromeda search engine (v.1.4.1.2). Tandem mass spectra were searched against UniProt_F. graminearum database concatenated with reverse decoy database. Trypsin was specified as the cleavage enzyme, the maximum missing cleavage was set as 4, and up to 5 modifications and 5 charges were allowed in each peptide. Mass error was set at 10 ppm for precursor ions and 0.02 Da for fragment ions. Carbamidomethylation on cysteine was specified as fixed modification and oxidation on methionine, acetylation on lysine and acetylation on protein N-terminal were specified as variable modifications. False discovery rate (FDR) thresholds for peptide and modification site were specified at 0.01. Minimum peptide length was set as 7. All the other parameters in MaxQuant were set to default values. The site localization probability was set as 0.75.

Acetylated protein annotation

Gene Ontology (GO) annotation of identified acetylated proteins was derived from the UniProt-GOA database (http://www.ebi.ac.uk/GOA/). Firstly, the identified protein ID was converted to UniProt ID, and then mapped to GO ID by protein ID. The proteins were classified by GO annotation based on three categories: biological process, cellular component and molecular function. The subcellular localization of the protein was predicted with WoLF PSORT (http://wolfpsort.seq.cbrc.jp/). Secondary structures of proteins were predicted by NetSurfP [54]. Domain descriptions of identified protein were annotated by InterProScan5 based on protein sequence alignment, and the InterPro domain database (http://www.ebi.ac.uk/interpro/) was used. Kyoto Encyclopedia of Genes and Genomes (KEGG) database was used to annotate protein pathway [55]. Functional annotation tool of DAVID bioinformatics resources 6.7 was used to identify GO terms, KEGG pathways and protein domains [56].

GO, KEGG pathway, domain and motif enrichment analysis

A two-tailed Fisher’s exact test was performed to examine the enrichment of the protein-acetylated entries against all proteins. Correction for multiple hypothesis testing was carried out using a previously described method [57]. Any term with a corrected p < 0.05 was considered significant.

Acetylation protein–protein interaction network analysis

The protein–protein interaction was obtained from the STRING database following the methods [41, 25]. The protein–protein interaction network of the identified acetylated proteins was performed with Cytoscape software (version 3.2.1, www.cytoscape.org).

Statistical analysis

Significant differences between the mutant and wild type strain were calculated according to the peptide intensity using a one-way analysis of variance with SPSS16.05 version. The p values of 0.05 were considered to be statistically significant.