Proteomic analysis reflects an environmental alkalinization-coupled pH-dependent mechanism of regulating lignocellulases in Trichoderma guizhouense NJAU4742
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Filamentous fungi have the ability to efficiently decompose plant biomass, and thus are widely used in the biofuel and bioprocess industries. In process, ambient pH has been reported to strongly affect the performance of the applied functional filamentous fungi. In this study, Trichoderma guizhouense NJAU4742 was investigated under the fermentation of rice straw at different initial pH values for a detailed study.
The results showed that NJAU4742 strain could tolerate ambient pH values ranging from 3.0 to 9.0, but had significantly higher growth speed and extracellular enzyme activities under acidic conditions. At low ambient pH (< 4), NJAU4742 strain achieved rapid degradation of rice straw by elevating the ambient pH to an optimal range through environmental alkalinization. Further proteomic analysis identified a total of 1139 intracellular and extracellular proteins during the solid-state fermentation processes, including the quantified 190 carbohydrate-active enzymes (CAZymes) responsible for rice straw degradation, such as 19 cellulases, 47 hemicellulases and 11 chitinases. Meanwhile, the analysis results clearly showed that the secreted lignocellulases had a synergistic trend in distribution according to the ambient pH, and thus led to a pH-dependent classification of lignocellulases in T. guizhouense NJAU4742.
Most functional lignocellulases were found to be differently regulated by the ambient pH in T. guizhouense NJAU4742, which had the ability of speeding up biomass degradation by elevating the ambient pH through environmental alkalinization. These findings contribute to the theoretical basis for the biodegradation of plant biomass by filamentous fungi in the biofuel and bioprocess industries.
KeywordsPlant biomass Trichoderma pH Lignocellulases Environmental alkalinization
the releasing amount of carbon dioxide
the concentrations of extracellular proteins
Plant biomass, as the most abundant natural material on earth, mainly consists of cellulose (40–50%), hemicellulose (25–30%) and lignin (15–20%) . For a long time, scientists have tried their best to overcome the structural recalcitrance and time-consuming degradation process of plant biomass [2, 3, 4]. Detailed in structure, cellulose and hemicellulose are the most abundant natural polysaccharides, where the former exists mostly as a crystalline structure [5, 6], and the latter exists as a mixture of xylan, glucomannan, arabinogalactan, xyloglucan and galactoglucomannan . Hemicellulose is usually decorated with various side-chain substituents, such as acetyl, α-arabinosyl, α-glucuronyl and 4-O-methylglucuronycyl residues . As a complex phenolic polymer, lignin is composed of three monolignol monomers that can be methoxylated to various degrees: p-coumaryl alcohol, coniferyl alcohol, and sinapyl alcohol. These lignols are incorporated into lignin in the form of the phenylpropanoid p-hydroxyphenyl (H), guaiacyl (G), and syringyl (S) units, respectively . Finally, by physical and chemical forces, all three different polymers form a 3D microstructure in the plant cell wall, which is very stable and shows strong resistance to hydration .
So far, plant biomass is widely used in two areas: biofuel and bioorganic fertilizer , in which filamentous fungi are employed as the plant biomass-degraders for their highly efficient secretion of many synergistic enzymes, such as cellulases, hemicellulases, pectinases and ligninases. However, it is still a challenge to completely degrade plant biomass in an economical amount of time just with the secreted enzymes from filamentous fungi. In the biofuel industry, acid or alkaline pretreatment is used and will partly destroy and significantly loosen the entire stable structure of plant biomass, thus providing a less recalcitrant and much more accessible material for the hydrolytic enzymes . Similarly, in the field of bioorganic fertilizer, amino acids with animal origins are added into plant biomass for highly efficient fermentation by functional filamentous fungi, aiming to supply nutrients, slightly pretreat and prevent the growth of other microbes . Certainly, all of these treatments would significantly change the subsequent environmental pH of the next step regardless of biofuel or bioorganic fertilizer production. Additionally, biological organic fertilizer containing the functional filamentous fungi would be applied to different farmlands, which have fluctuant natural pH values ranging from 4.0 to 9.0 . These facts drew our attention to investigate the effect of pH on the growth of filamentous fungi, or more specifically, focus on the effect of pH on the regulation of lignocellulases in functional filamentous fungi.
pH regulation of lignocellulases in filamentous fungi has already been investigated previously. For example, in Aspergillus nidulans, XlnB (xylanase) and AbfB (α-l-arabinofuranosidase) were acid-expressed, while XlnA (xylanase) was alkaline-expressed . In Botrytis cinerea, protein gel identification showed that three hydrolases (α-1,2-mannosidase, α-l-arabinofuranosidase and β-1,3-glucosidase) were up or specifically accumulated at pH 4.0, while four other hydrolases (exocellulase, arabinogalactan endo-1,4-β-galactosidase, rhamnogalacturonan acetyl esterase and exoarabinanase) were up or specifically accumulated at pH 6.0 . Transcriptome analysis of Trichoderma reesei also indicated that a series of genes encoding cellulases and hemicellulases were selectively induced under various pH values . Furthermore, deeper studies revealed that a pH regulatory system could be mediated by the transcription factor of PacC, which was responsible for differential protein expression at different pH values [14, 17]. It was reported that knocking out the pacC gene could significantly affect both cellulase and xylanase activities in two model filamentous fungi, Trichoderma reesei and Neurospora crassa [18, 19]. These previous results showed that a PacC-mediated mechanism likely exists as a general way of regulating lignocellulases in filamentous fungi. However, only portions of enzymes or sporadic indirect pieces of evidence (transcriptome sequencing) were provided in those previous studies, and very few studies have tried to entirely investigate the change in all proteins in response to pH in a filamentous fungus.
Trichoderma guizhouense NJAU4742 strain, which was isolated from compost, was widely used as a functional active component of biological organic fertilizer. In this study, NJAU4742 strain was fermented at different initial pH values to investigate the effects on degradation of the sole carbon source (rice straw). In the whole process, the growth conditions and extracellular lignocellulose activities were analyzed in detail. Simultaneously, the proteomic analysis using the Sequential Window Acquisition of all Theoretical fragment ions (SWATH) technique provided a specific description of how pH affected the intracellular and extracellular proteins synthesized by NJAU4742 strain.
Pre-evaluating the ability of T. guizhouense NJAU4742 to degrade rice straw at different pH values in the submerged fermentation
The performance of NJAU4742 strain under solid-state fermentations of rice straw at different pH values
Solid-state fermentation is an important method for cultivating filamentous fungi when used in agriculture or industry. Based on the data obtained from the submerged fermentations, pH values of 2.0, 3.0, 6.0, 8.0 and 9.0 were chosen as the initial ambient pH values for the solid-state fermentations of NJAU4742 strain using rice straw as the sole carbon source. During the fermentation course of 7 days, the spores germinated and grew until large amounts of green mature spores were produced (a complete growth cycle, Additional file 1: Figure S1). In solid-state fermentation, an initial pH of 6.0 could significantly accelerate the growth of NJAU4742 strain compared to other pH values, and initial pH values of 3.0 and 8.0 could also normally incubate this strain, but with some delay in the growth when compared to the former treatment. Similar to the submerged fermentation, an initial pH of 2.0 completely inhibited the spore germination of NJAU4742 strain, and a relatively small amount of mycelia were observed in the treatment with the initial pH value of 9.0.
Proteomic analysis for solid-state fermentations of NJAU4742 strain at pH 3.0, 6.0 and 9.0
The different growth conditions and enzymatic properties above showed that diverse regulations must exist in the solid-state fermentations of NJAU4742 strain at different initial pH values, thus proteomic analysis was used to investigate the details of responding to ambient pH by NJAU4742 strain. After protein extraction, the mycelial proteins and extracellular proteins were mixed based on the protein concentration (mg g−1 dw, protein/substrates), meaning that both were extracted from the same amount of the fermented materials (see “Methods”). SDS-PAGE analysis showed that the mixed total proteins were repeatable in each treatment and that significant differences existed among SSF3.0, SSF6.0 and SSF9.0 (Additional file 1: Figure S2). Consistent with the highest enzyme activities, total proteins of SSF6.0 had the most abundant protein bonds, as shown in Additional file 1: Figure S2. After quality control, total proteins from SSF3.0, SSF6.0 and SSF 9.0 were separately detected and analyzed using the SWATH technique, which resulted in a total number of 1139 proteins when using the whole protein sequences of NJAU4742 strain as the database.
For all the determined proteins, their coverage rate of peptides was calculated and seemed to fit a noncentral F-distribution (Additional file 1: Figure S3A), with approximately 90% of identified proteins having a coverage rate of peptides lower than 37%. The protein abundances in all samples (SSF3.0, SSF6.0 and SSF9.0) conformed to a normal distribution with a range of 103–108 (Additional file 1: Figure S3B). Together with the considerable repeatability of each sample (Additional file 1: Figure S3C) and objective statistical information produced with SWATH analysis (data not shown), these data of the identified proteins allowed the deep analysis of the responses to different ambient pH values by NJAU4742 strain.
Protein location analysis
In solid-state fermentation, NJAU4742 strain had adapted to a wide environmental pH condition, ranging from 3.0 to 9.0, and showed a distinct preference for the specific pH of 6.0. Beyond adaptation, NJAU4742 strain could also significantly reconstruct the environmental pH condition by alkalinization, in which the pH value was elevated from 3.0 to 6.0 in 5 days. Therefore, it is very interesting to discuss NJAU4742’s alkalinization, which is hence hypothesized to be the result of three possible mechanisms: (I) the released components from the degradation of rice straw neutralized the acidic environmental pH; (II) NJAU4742 strain absorbed extracellular H+ and (III) the secretions of NJAU4742 strain elevated the environmental pH. For hypothesis I, the main components of rice straw contained polysaccharides (cellulose, xylan and mannan) and lignin, however, the released basic units, such as oligosaccharides, glucose, xylose, mannose and aromatic alcohols, actually had little influence on the ambient pH. The components that could alter the ambient pH were pectin and those substituent groups of hemicellulose, of which the complete hydrolysis would release various organic acids, including galacturonic acid, glucuronic acid, ferulic acid, p-coumalic acid, and acetic acid . Meanwhile, protein degradation by extracellular proteases could also release various amino acids from the substrate. Apparently, these produced organic acids will function as a reverse to the environmental alkalinization by NJAU4742 strain, and were probably absorbed and utilized rapidly by NJAU4742 strain, much like the produced sugars, and this behavior functioned in regulating ambient pH, which belonged to part of hypothesis II (absorbing extracellular acids). Additionally, the original high concentration of H+ in SSF3.0 strongly drew attention to an enzyme called the H+-ATPase, which was identified and significantly regulated by pH in this study (OPB40853, p < 0.05, Additional file 2). This enzyme was generally located on the plasma membrane of plants and fungi, and belonged to the P-type cation-translocating ATPase family. Many previous studies showed that H+-ATPases were always regulated by glucose, an acidic pH and weak organic acids , which existed in solid-state fermentations of NJAU4742 strain and resulted in the highest expression level of the H+-ATPase in SSF6.0. The complex regulation of the H+-ATPase in the SSF of NJAU4742 strain suggested its relationship with NJAU4742 strain alkalinization, but may also work as a counter for its reported function of pumping H+ out of the cell to create a transmembrane electrochemical proton gradient for nutrient uptake and stabilizing intracellular pH [24, 25]. Actually, under such a low pH of 3.0 condition (high natural potential across plasma membrane), it was hard to know whether the H+-ATPase was still needed to work or if there were any possible patterns of the H+-ATPase helping NJAU4742 strain absorb H+ in some way, which still required a more in-depth study. For hypothesis III, many studies have proposed that fungi could modify the pH of their environment by secreting acids or alkalis. For example, Sclerotinia sclerotiorum and Botrytis sp. could produce oxalic acid , while Penicillium sp. and Aspergillus sp. can secrete mainly gluconic and citric acids [27, 28]. Although pH was slightly dropped in SSF9.0, it was still difficult to judge whether NJAU4742 strain secreted acids in this study, but at least this was not the main determinant for the acidic environment. Some other fungi, such as Colletotrichum gloeosporioides , Dictyostelium discoideum  and Debaryomyces hansenii , and especially for Candida albicans , could alkalinize their environment by secreting ammonia, a byproduct during the amino acid metabolic process. By a BLAST search, the homologs of an ammonium transporter of MEPB and three ammonia transporters (ATOs) in this process were found in strain NJAU4742, but no homologs were detected for the critical regulator (Stp2p) and amino acid catabolic enzyme (Ach1p). Among the four detected homologs, only one ATO protein (OPB44235) was identified by SWATH, but its highest expression level in SSF6.0 could not be explained logically. These previous reports of other fungi’s alkalinization supported that NJAU4742 strain in this study might elevate the ambient pH by secreting another kind of alkali (not ammonia), which was entirely possible because C. albicans also shared multiple mechanisms of environmental alkalinization not only ammonia secretion [32, 33, 34]. Certainly, H2O2 and secondary metabolites were also considered as the possible functional parts of the complex environmental alkalinization of NJAU4742 strain.
In SSF3.0, the growth inhibition of NJAU4742 strain by the low pH was relieved as the ambient pH increased, which indicated that environmental alkalinization determined the growth ability of NJAU4742 strain at pH 3.0. This fact reflects that a complex regulatory system exists for detecting different pH values and further, responding to the pH. The results here clearly showed that extracellular proteins, such as cellulases, hemicellulases and chitinases, were under the regulation of this possible system. Similarly, some cellulase and xylanase genes were also reported to be controlled by the ambient pH in T. reesei , Humicola grisea  and Neurospora crassa , and thus together showed the universality of pH regulation of lignocellulases in filamentous fungi. Actually, there are already some reports that the integrity of seven proteins, designated PacC, PalA, PalB, PalC, PalF, PalH and PalI, were responsible for gene regulation at different pH values . Under acidic growth conditions, PacC72 (72 kDa) is inactive without any known role in transcriptional regulation, but it is converted to PacC53 (53 kDa) and further to PacC27 (27 kDa), which is subsequently active and functions in the activation of alkaline-expressed genes and repression of acid-expressed genes. PacC orthologs were found to modulate the expression of cellulolytic genes in response to ambient pH in filamentous fungi, but the effects varied depending on the organisms. For example, deletion of the pacC gene in T. reesei significantly increased the cellulolytic enzyme activities at neutral pH , but the transcriptome analysis showed only a few cellulase- and hemicellulase-encoding genes were clearly under PacC regulation . In Aspergillus nidulans , PacC significantly upregulated the expression of cellulolytic genes at alkaline pH, but had a reverse observation in N. crassa . The homologs of the seven proteins in the whole PacC-mediated system could be detected and encoded in the genome of NJAU4742 strain, and thus suggested that those pH-regulated lignocellulases were possibly under the control of this system. Although none of the homologs appeared in the 1139 identified proteins, further study of PacC-mediated and other possible systems in regulating extracellular enzymes by the ambient pH, will be very interesting.
Obviously, filamentous fungi regulated the secretion of extracellular enzymes by the ambient pH, however, we need to understand the biological significance behind this behavior. The organisms are highly evolved, and thus the secretion adjustment of extracellular enzymes at different pH values is believed to be an adaptive mechanism to ensure better survival in that environment. That means, NJAU4742 strain possibly achieved more efficient degradation of rice straw by adjusting the differential secretion of cellulases and hemicellulases when exposed under the different pH values. Logically, the adjustment is to achieve the optimal synergy of extracellular enzymes under different pH conditions, which possibly could be explained from the different enzymatic properties of cellulases and hemicellulases. And, it is really the fact that cellulases and xylanases from the same filamentous fungus have different enzymatic properties, such as thermostability, optimal temperature, specific activity and functional domains . Just like extracellular proteases, they were distinguished as acidic, neutral and alkaline proteases and regulated by the PacC-mediated system . The secreted proteases of NJAU4742 strain also showed significant pH regulation in this study (Additional file 2). Besides, Xiong et al.  reported that xylanase I was most secreted and active at low pH value (4.0), while xylanase III was most secreted and active at high pH value (6.0) in T. reesei. Xylanase II was clearly produced at both pH values. These results and analysis clearly support such a judgment that the pH-dependent regulation of extracellular enzymes is probably for achieving higher enzymatic synergy by secreting the optimal enzymes at different pH values, so as to obtain a most efficient degradation of lignocellulose. Certainly, more detailed and in-depth researches need to be carried out to explain this pH-dependent synergy of lignocellulases.
Additionally, we also noticed the stable differential distribution of extracellular enzyme abundances, which was believed to be the result of evolution, as well as a kind of synergistic performance of multiple enzymes. For cellulose degradation, exoglucanase attacked the natural and LPMO-produced ends of crystalline cellulose, and then the products could be hydrolyzed into glucose by β-glucosidase. The high abundance of these three functional enzymes suggested the specific enhancement of the main steps in the degradation of crystalline cellulose, but not including the endoglucanases, which seemed to have difficulties when attacking the middle of the cellulose chain in the crystalline structure. In contrast, endoxylanase was the largest abundant secreted enzyme among all xylanases, corresponding to the fact that endoxylanase could easily attack the whole chain of xylan for its non-crystalline structure. Facing the complex 3D structure of lignocellulose, the differential distribution of extracellular enzymes is indeed likely to be for greater synergy efficiency, and further analyzing this synergy will be very interesting and valuable in biofuel industry.
This study described the performances of NJAU4742 strain during the submerged and solid-state fermentation processes at different initial pH values in detail. The results showed that ambient pH dominated the growth, sporulation, extracellular enzyme activities and decomposition rate of rice straw by NJAU4742 strain. Proteomic analysis deeply revealed the intracellular and extracellular proteins during the solid-state fermentation processes and clearly quantified 190 functional enzymes for rice straw degradation especially for their extracellular synergetic distribution. More importantly, the pH-regulated lignocellulose-degrading enzymes in filamentous fungi were firstly distinguished and classified in detail. All these results contribute to the theoretical basis for the degradation of plant biomass by filamentous fungi in the biofuel and biological organic fertilizer industries.
Strains and culture conditions
Trichoderma guizhouense NJAU4742 was isolated from a mature compost sample and stored in 15% glycerol at − 80 °C in our lab, and its genome sequence was already published in the NCBI database (Accession No. LVVK00000000.1). Murashige and Skoog (MS) medium (1.36 g/L KH2PO4, 2.13 g/L Na2HPO4, 0.2 g/L MgSO4·7H2O, and trace elements) was used as the liquid medium for cultivating NJAU4742 in both submerged and solid-state fermentation, but varied in percentages of rice straw, which were 2% (w/v) or 25% (w/v), respectively. The rice straw used in this study was obtained from the local farmland (Nanjing, China) and then washed with running water for 48 h, after which it was dried entirely at 40 °C for 5 h and ball-milled into powder using a ball-miller (Retsch MM400, Germany) with ZrO2 balls (15 mm, diameter) and vessel (35 mL, volume), and the parameters were set as follows: 15 Hz, 1 min milling followed by a 30-s pause, with a total time of 5 min, after which the rice straw powder was screened by a 30 mesh sieve with the average size less than 0.6 mm. The initial pH values of the submerged or solid-state fermentations were adjusted by adding 0.5 M H2SO4 or NaOH and monitored with a pH meter (PB-10, Sartorius, Germany).
Spores of NJAU4742 strain were collected from the incubated PDA plates by washing followed by the filtration through 4 layers of gauze. After two repeated washing by the sterilized ddH2O, the spore concentration was subsequently adjusted to be 1 × 107/mL through the method of hemocytometer counting. For the submerged fermentation, a total of 5 × 106 spores were inoculated into 50 mL MS medium with 2% (w/v) rice straw in a 250-mL triangular flask and grown under the condition of 28 °C and 150 rpm. For the solid-state fermentation, a total of 1 × 107 spores were inoculated into a 500-mL triangular flask containing 75 mL MS medium and 25 g rice straw, and grown under the condition of 28 °C. All treatments were performed for total 7 days, and sampled at the incubation times of 1, 2, 3, 4, 5, 6 and 7 days. Three biological repeats existed for each sampling point.
Enzyme activity assays
Endoglucanase, exoglucanase and xylanase activities were measured using carboxymethyl cellulose sodium (CMC-Na) (Sinopharm Chemical Reagent Co., China), p-nitrophenyl-β-d-cellobiose (pNPC) (Sigma, USA), and oat spelts xylan (Sigma, USA) as the substrate, respectively, according to the methods described previously [20, 41]. One unit of enzyme activity was defined as the amount of enzyme required to release 1 μmol reducing sugars or pNP from the substrate in 1 min. Protein concentrations were determined using the Bradford protein assay kit (ThermoFisher, USA) based on the product description . All the enzyme activities were reported as the means of at least three replicates.
Electron microscope analysis and respiratory rate determination
After fixation with 2.5% glutaraldehyde for 2 days, the samples from different treatments were immediately dehydrated in 10 mL of ice-cold 200 proof ethanol (Sigma-Aldrich), point-dried in a critical point dryer (HCP-2, Hitachi High-Technologies Corporation, Japan) and coated with 60% Au/Pd in a sputter coater (Sputter Coater Baltec SCD500, Bal-Tel) . The surface morphologies of different samples were observed by using an S-4800 II field emission scanning electron microscope (Hitachi, Japan). The respiratory rate of NJAU4742 strain during the solid-state fermentation process was evaluated by tracking the release of CO2. Briefly, the triangular flasks of solid-state fermentations were sealed with a parafilm 2 h before sampling. When sampling, 20 mL of gas in the triangular flask was extracted with a syringe and then injected into the gas sampling bag (E-SWITCH, China), and the contents of CO2 was determined by a gas chromatography (Agilent 7890A) equipped with Porapak Q column and a flame ionization detector (FID) according to Zhang et al.  with some modification: 500 µL of gas were injected through a septum with the temperature of 80 °C, and the carrier gas (N2) flow-rate was 30 mL min−1; meanwhile, the temperature of the methanizer and detector were set as 450 °C and 250 °C, respectively.
Protein extraction and SWATH analysis
Samples of each treatment in solid-state fermentations at the 4th day were taken and used to extract proteins for proteome analysis. Extracellular protein extraction was carried out as follows: 150 mL deionized ddH2O was added into triangular flasks, which were then shaken at 180 rpm for 1 h, and the supernatants were collected by centrifugation at 10,000 rpm for 10 min and filtration through a 0.22 µm sterile membrane. The precipitates of the former step were used to prepare the mycelial intracellular proteins, which were extracted by using the NoviPure® Soil Protein Extraction Kit (MOBIO, USA) according to the manufacturer’s protocol. After that, extracellular and intracellular proteins, both extracted from the same amount of fermentation materials samples (mg g−1 dw, protein/substrates), were directly mixed and concentrated by lyophilization and then stored at − 80 °C. Two biological repeats existed for each condition in proteomic analysis.
The whole SWATH analysis was commissioned to a specialized company (GeneCreate, Wuhan, China), and the analysis is described briefly as follows: 100 μg of proteins in each sample were digested by trypsin (Promega, USA) at 37 °C overnight, separated by the Strata-X C18 pillar and dried using a vacuum concentration meter. LC–ESI-MS/MS analysis was performed on an AB SCIEX nanoLC–MS/MS (Triple TOF 5600 plus) system in two phases: data-dependent acquisition (DDA) was followed by SWATH acquisition, where all samples were mixed and detected in DDA, and the resulting data were used as a library for analysis of each sample by SWATH. Spectral library generation and SWATH data processing were performed using skyline version 3.5 software  complying with the following rules: (i) peptides containing modifications and/or shared by different protein entries/isoforms were excluded from selection; (ii) peptides having a ProteinPilot-identified confidence less than 95% were excluded; (iii) up to five fragment ions that were ranked by intensity were chosen; (iv) fragment ions within the SWATH isolation window were excluded from selection; and (v) to control false discovery rate, a random mass shift of Q1 and Q3 m/z strategy  was used to create a decoy spectra library for targeted peak extraction, a mass-to-charge tolerance of at most 10 ppm (0.05 m/z) was allowed for both peptide precursor and fragment ion. Fragment ion areas that belonged to one peptide were added to obtain a peptide’s abundance, and the total abundance of peptides for a given protein was determined to obtain the protein’s abundance. To eliminate the random errors and sample bias, all the data among samples were normalized using the median normalization method , and the mProphet algorithm was used both for sample normalization and for assessing the data confidence .
CAZymes annotation was carried out using the hmmscan tool from HMMER software  to search the dbCAN database , and the output was processed by the script of hmmscan-parser.sh (https://github.com/carden24/Bioinformatics_scripts/blob/master/hmmscan-parser.sh). KEGG pathway annotation was performed using KEGG Orthology-Based Annotation System 2.0 (KOBAS) . Gene location was manually annotated by combining information from GO Ontology, KEGG annotation, NCBI gene descriptions and some previous articles. Signal peptide was predicted using SignalP 4.0 software . Circos  and Cytoscape  were used for data visualization. Violin plot was performed using the R package vioplot .
DL, YM and QS participated in the design of the experiments and contributed to manuscript writing. YM is responsible for the whole data analysis. XC, TL, HZ and ST performed the experiments. All authors read and approved the final manuscript.
This research was financially supported by the National Natural Science Foundation of China (31801935), the Jiangsu Provincial Natural Science Foundation (BK20180538), and Special Fund for Agro-scientific Research in the Public Interest (201503110). QS was supported by the Innovative Research Team Development Plan of the Ministry of Education of China (IRT_17R56).
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The authors declare that they have no competing interests.
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