Insight into Enzymatic Degradation of Corn, Wheat, and

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Article

Insight into enzymatic degradation of corn, wheat, and soybean cell wall cellulose using quantitative secretome analysis of Aspergillus fumigatus Prakriti Sharma Ghimire, Haomiao Ouyang, Qian Wang, Yuanming Luo, Bo Shi, Jinghua Yang, Yang Lu, and Cheng Jin J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.6b00465 • Publication Date (Web): 13 Sep 2016 Downloaded from http://pubs.acs.org on September 13, 2016

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Insight into enzymatic degradation of corn, wheat, and soybean cell wall cellulose using quantitative secretome analysis of Aspergillus fumigatus Prakriti Sharma Ghimire1,2,5, Haomiao Ouyang1, Qian Wang3, Yuanming Luo3, Bo Shi4, Jinghua Yang1, Yang Lü1, Cheng Jin1,2* 1

State Key Laboratory of Mycology, Institute of Microbiology, Chinese Academy of Sciences, Beijing

100101, China; 2University of Chinese Academy of Sciences, Beijing 100101, China;

3

State Key

Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China;4 Feed Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China;5 Himalayan Environment Research Institute (HERI), Bouddha-6, Kathmandu, Nepal.

* To whom corresponding should be addressed: 1-3 West Beichen Road, Chaoyang District, Beijing 100101, China; Tel: +86-10-64807425; Fax: +86-10-64807429; e-mail: [email protected].

Author details Prakriti SharmaGhimire: [email protected]. Haomiao Ouyang: [email protected]. Qian Wang: [email protected]. Yuanming Luo: [email protected]. Bo Shi: [email protected]. Jinghua Yang: [email protected] Yang Lü: [email protected] 1 ACS Paragon Plus Environment

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Abstract

Lignocelluloses contained in animal forage cannot be digested by pigs or poultry with 100% efficiency. On the other hand, Aspergillus fumigatus, a saprophytic filamentous fungus, is known to harbor 263 glycoside hydrolase (GH) encoding genes, suggesting that A. fumigatus is an efficient lignocellulose degrader. Hence the present study uses corn, wheat or soybean as a sole carbon source to culture A. fumigatus under animal physiological condition as to understand how cellulolytic enzymes work together to achieve an efficient degradation of lignocellulose. Our results showed that A. fumigatus produced different sets of enzymes to degrade lignocelluloses derived from corn, wheat, or soybean cell wall. In addition, the cellulolytic enzymes produced by A. fumigatus were stable under acidic condition or at higher temperatures. Using isobaric tags for relative and absolute quantification (iTRAQ) approach, total of ~600 extracellular proteins were identified and quantified, in which ~50 proteins were involved in lignocellulolysis, including cellulases, hemicellulases, lignin-degrading enzymes and some hypothetical proteins. Data are available via ProteomeXchange with identifier PXD004670. Based on quantitative iTRAQ results, 14 genes were selected for further confirmation by RT-PCR. Taken together, our results indicated that the expression and regulation of lignocellulolytic proteins in the secretome of A. fumigatus were dependent on both nature and complexity of cellulose, thus suggesting that different enzyme system is required for degradation of different lignocelluloses derived from plant cells. Although, A. fumigatus is pathogenic fungus and cannot be directly used as an enzyme source, as an efficient lignocellulose degrader its strategy to synergistically degrade various lignocelluloses with different enzymes can be used to design enzyme combination for optimal digestion and absorption of corn, wheat, or soybean that are used as forage of pig and poultry.

Keywords: Aspergillus fumigatus, iTRAQ, lignocelluloses, secretome, lignocellulolytic proteins, forage

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Introduction The complexity of plant cell wall is primarily due to the existence of polysaccharides organized together with different sugar residues, and linked with an array of structures1-2. These polysaccharides can be rationally assembled into cellulose, hemicellulose and pectin. Cellulose is the most bounteous and least intricate polysaccharide (20 to 30% of the dry weight primary cell walls) formed from linear chains of β1,4-linked glucose units. Hemicellulose is composed of sugars, such as xylan (β-1,4-linked D-xylose), mannan (β-1,4-linked D-mannose), or xyloglucan (β-1,4-linked D-glucose) as a backbone and may attach with sugars such as D-galactose, D-xylose, L-arabinose, and D-glucuronic acid. Pectin is the least abundant polysaccharide of all which is primarily composed of α-1,4-linked D-galacturonic acid backbone 1, 3-4

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When plant seeds, such as wheat, corn, and soybean are used as animal forage, the cell wall complexities complicate the digestion and absorption process in animals or hinder their digestive system that restrict them from maximum energy conversion. This is because of inability of the animal to produce necessary enzymes for degradation of plant seed cell wall cellulose and thus unable to release starch from intact plant seed cells. In recent years, feeding enzymes to poultry and pigs has turned out to be one of the key alarms in animal science

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. Although mono-gastric animals can naturally produce some enzymes to aid

feed digestion but lack enzymes to break down cellulose fiber completely. It undergoes fermentation to produce short-chain fatty acid providing 15% and 8% energy in pigs and chickens, respectively 4, 6. Corn, wheat, or soybean is one of the main forage in pigs and poultry diets where exogenous dietary enzymes supplement may serve as a good choice to aid digestion. Indeed, β-glucanase and xylanase have been used in poultry and piglets diet to improve digestion and absorption and to reduce intestinal viscosity3, 7-9; however, the improvement is still poor and uneconomical. Therefore, a special enzyme cocktail should be designed for a better degradation of corn, wheat, or soybean cell wall.

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Various bacterial and fungal species that produce cellulase and transport them out of the cell membrane have been studied10-13. Previous studies have shown that a group of filamentous fungi, for example, A. niger, A. nidulans, or T. reesei (Hypocrea jecorina), produces an extensive set of industrial cellulases using wide range of carbon source14-15. Based on proteomics and transcriptomics analyses of several fungi on different lignocelluloses, various groups of enzymes like cellulases, glycoside hydrolases, hemicellulases, and lignin degrading enzymes, peroxidases, esterases, lipases, chitinases, peptidases, and protein translocating transporter are synergistic enzymes for optimal lignocelluloses degradation16-21. It is conceivable that filamentous fungi have a robust ability to obtain nutrition and energy from various celluloses during their long-term evolution and may produce some special enzyme combinations to degrade various celluloses. Thus, knowledge of appropriate enzyme combination produced by filamentous fungi for plant cellulose degradation might be used to design the enzyme cocktail for a better degradation of corn, wheat, or soybean cell wall. As one of the most ubiquitous saprophytic fungi, A. fumigatus is highly thermotolerant, comfortably grows at 30-50°C, and produces a number of stable enzymes, such as cellulase11 and phytase22. In addition, A. fumigatus contains 263 glycoside hydrolase (GH) encoding genes, which is higher than that in T. reesei (200 GH) and P. chrysosporium, a white rot fungus that is known for the complete degradation of major components of the plant cell wall including lignin, cellulose, and hemicellulose23-24, suggesting that A. fumigatus is an efficient producer of cellulases for the complete degradation of lignocellulose. Previously, by using LC-MS/MS and iTRAQ-based quantitative proteomics, proteins secreted by A. fumigatus in presence of different carbon sources, such as avicel, rice straw, cellulose, xylan and starch, were identified and quantified, which demonstrated that A. fumigatus could produce specific cellulose-, hemicellulose-, pectin- and lignin-degrading enzymes that are valuable for the lignocellulosic bioenergy industry24. Although enzymes including endoglucanases, cellobiohydrolases, glucosidases, hemicellulases, and lignin degrading enzymes are found to be modified by deamidation, its biological function is unclear25. These

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previous researches demonstrate that A. fumigatus can produce different enzyme sets for an efficient cellulose degradation of various lignocelluloses20, 24-28. As wheat, corn, or soybean are commonly used as animal forage and their cell wall is a barrier for the digestion and absorption of intracellular starch, the present study is aimed to reveal how the A. fumigatus cellulolytic enzymes synergistically degrade various cell wall celluloses derived from forage. To achieve this goal, the ability of A. fumigatus to degrade lignocellulose derived from corn, wheat, or soybean cell wall was evaluated first. Then quantitative expression of lignocellulolytic proteins produced by A. fumigatus were profiled using isobaric tags for relative and absolute quantification (iTRAQ) and further confirmed by RT-PCR at the gene expression levels.

MATERIALS AND METHODS Strains and culture conditions A. fumigatus strain YJ407 (China General Microbiological Culture Collection Center, CGMCC0386) was maintained on CM medium29-30 and the spore suspension containing 106-107 spores/ml was inoculated in SHMM media14. Starch-free corn cell wall cellulose (CCC), wheat cell wall cellulose (WCC), and soybean cell wall cellulose (SCC) were made by grounding corn, wheat, and soybean respectively into powder and suspended in water to remove starch. The insoluble materials were autoclave at 121 lb for 30 min, removed the soluble starch and confirmed by iodine test. Control sample was applied in each experiment containing galactose (CT) as a sole carbon source. 5% (w/v) CCC, WCC, SCC, and CT were added to the SHMM medium (as mentioned above) as a sole carbon source and incubated at 37 °C. The secreted proteins from each of the sole carbon source were used for further study. Scanning electron microscopy (SEM) was performed according to Li et al. 31. Culture samples were fixed with 2.5 % glutaraldehyde in phosphate buffer (pH 7.2) and then examined with FESEM SU8010 (HITACHI) scanning electron microscope. 5 ACS Paragon Plus Environment

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Protein precipitation and zymogram analysis Extracellular proteins were precipitated using freshly prepared 2% (w/v) sodium deoxycholate to the culture supernatant (1:100) for 30 min on ice followed by addition of 100% trichloroacetic acid (1:10) for 30 min on ice, and collected by centrifugation (12,000 × g at 4 °C for 10 min). The precipitate was washed 3 times with ice-cold acetone (once with 100% [v/v] and twice with 90% [v/v]) and dried by exposure to air

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. Zymogram study for cellulase and xylanase was performed according to Sun et al. with some

modifications 33. 10-12% SDS-PAGE gel was incorporated with 0.2% CMC and 0.2% xylan and the active proteins band after run was washed once with 50mM NaAc containing 25% isopropanol and twice with 50mM NaAc at room temperature to remove remaining sodium dodecyl sulfate. Protein renaturation was done by 50 mM acetate buffer (pH 4.8) containing 5mM β-mercaptoethanol and incubated overnight at 4 °C by stirring. Again, the gel was washed with 50 mM acetate buffer (pH 4.8) for 2 h at room temperature and at 50 °C for another 2 h. After that, the gel was stained in 0.2% Congo red for 30 min and de-stained using 1 M NaCl solution and finally hydrolysis of substrate by enzyme present in gel can be observed with a dark red background.

SDS-PAGE and in-gel digestion Precipitated secreted proteins were separated by 10-12% SDS-PAGE, stained with R-250, and then cut out from gel bands. In-gel digestion of secretory protein in SDS-PAGE obtained from A. fumigatus was performed according to Liu et al. with slight modification 24. Briefly, each sliced band was completely destained by using 50% (v/v) acetonitrile in 40 mM NH4HCO3, dehydrated using 100% acetonitrile and dried using SpeedVac. Proteins were then reduced with 10mM DTT / 40 mM NH4HCO3 (Sigma-Aldrich Co.) at 56 °C for 20 min, alkylated with 55 mM iodoacetamide / 40 mM NH4HCO3 in the dark for 25 min at room temperature followed by subsequent wash and dry. Peptides were then produced by trypsin 6 ACS Paragon Plus Environment

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digestion (50 ng trypsin, Promega Sequence Grade, Modified)24. For MALDI-MS analysis, 0.4 µL aliquot of the reconstituted tryptic peptide mixture in 0.1% TFA was mixed with 0.4 µL of CHCA matrix solution (5 mg/mL CHCA in 50% ACN/0.1% TFA) and spotted onto a freshly cleaned target plate. After air drying, the crystallized spots were analyzed on the MALDI-TOF/TOF 5800 (AB SCIEX, Framingham, MA). MS calibration was automatically performed by a peptide standard Kit (Applied Biosystems) containing des-Arg1-bradykinin (m/z 904), Angiotensin I (m/z 1296.6851), Glu1-fibrinopeptide B(m/z 1570.6774), ACTH (1-17, m/z 2903.0867), ACTH (18-39,m/z 2465.1989), and ACTH (7-38, m/z 3657.9294) and MS/MS calibration was performed by the MS/MS fragment peaks of Glu1-fibrinopeptide B. Peptide mass maps were acquired in positive reflection mode, averaging 1500 laser shots per MALDITOF spectrum and 3000 shots per TOF/TOF spectrum. Parent mass peaks with a mass range of 800–3500 Da and the ten most abundant ions from MS analysis were chosen for tandem TOF/TOF analysis. MS and MS/MS data were analyzed using MASCOT 2.0 search engine (Matrix Science, London, U.K.) to search against the A. fumigatus database downloaded from NCBI database on March 20 2013. Searching parameters were conducted using the following setting: one missed cleavage sites by trypsin, 0.2 Da peptide mass tolerance, 0.5 Da MS/MS ion tolerance, carbamidomethylation of cysteine as a fixed modification, and methionine oxidation as a variable modification. The Mascot result including all the information such as peptide expect, peptide sequence with ion score and Mascot score are presented in supporting information Table S3.

Enzyme activity assays The efficacy of cellulase and hemicellulase secreted by A. fumigatus was compared by determining the enzyme activity using their respective substrate. Cellulase, xylanase, and pectinase activity was determined using 1% (w/v) carboxymethyl cellulose (CMC), 1% (w/v) xylan, and 1% (w/v) pectin respectively (Sigma-Aldrich Co.) (Table S1) and the reducing sugar was measured by DNS method with slight modification on reduction of reaction volume34-35. An aliquot of the substrate stock solution was 7 ACS Paragon Plus Environment

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mixed with the secreted protein followed by the addition of DNS reagent and incubated in a boiling water bath for 15 min, cooled and measured at 540 nm. The reducing sugars were calculated by reading the absorbance at 540 nm against a standard curve of glucose, xylose, and galacturonic acid for cellulase, xylanase, and pectinase respectively. All activities were expressed in International Unit (IU), corresponding to the quantity of enzyme hydrolyzing 1ߤmoL of reducing sugar from the appropriate substrate per minute under the assay conditions. Triplicates of each sample were analyzed and mean values were calculated.

iTRAQ labeling The iTRAQ labeling of peptide samples derived from harvested secretome of A. fumigatus grown with CCC, WCC, SCC, and control (CT) were carried out using iTRAQ reagent Multiplex kit (Applied Biosystems, Foster City, CA)38-40. The secreted and precipitated protein from each of the four samples were lysed in iTRAQ lysis buffer containing 25 mM Triethylammonium bicarbonate (TEAB), 8 M urea, 50 µg/ml DNase I, 50 µg/ml RNase A, 0.1% SDS, 2% Triton X-100, and 1×Halt protease inhibitor cocktail (Pierce, Rockford, IL), and centrifuged at 18,000 × g for 1 h at 15 °C. The supernatant was collected and quantified by Bradford protein assay method (BIO-RAD, USA) using bovine serum albumin (BSA) as a standard. The concentration of each sample was adjusted to the same concentration and used for protein digestion and iTRAQ labeling. 200 µg of each lysate were reduced with 4 µl of reducing agent [Tris (2-carboxyethyl) phosphine (TCEP)] for 1 h at 37 °C and then alkylated with cysteine blocking reagent (AB SCIEX) for 20 min at room temperature. The samples were digested with sequencing grade trypsin (Roche) (1:40) overnight at 37 °C and peptides were collected in a new microfuge tube, dried and then labeled with iTRAQ reagents (8-plex) (AB SCIEX, Foster City, CA) according to the manufacturer’s instruction. iTRAQ reagents were resuspended in 150µl isopropanol, transferred to the samples and incubated at room temperature for 2 h. The reaction was quenched by adding deionised water. The samples were individually labeled by the following replicate reporters: CT: 113 and 117; CCC: 114 and 8 ACS Paragon Plus Environment

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118; WCC: 115 and 119 and SCC: 116 and 121. Based on experimental design, the reporter designated as CT is selected as reference ion channel. The labeled peptides were pooled together for the first dimensional fractionation by high pH reversed phase liquid chromatography.

High pH reversed phase fractionation To get a better resolution, a two-dimensional liquid chromatography method comprising high pH reversed-phase separation and low pH reversed-phase separation was used. For peptide fractionation, 8 Plex iTRAQ reagent labeled peptide mixtures were separated with a Gemini 3µm-C18 column (4.6 x 250 mm; Phenomenex) on a LC-20A HPLC system (Shimadzu, Japan). Briefly, the dried peptides were reconstituted in Buffer A (0.1% (w/v) ammonium hydroxide), injected onto the column and washed for 10 min at a flow rate of 0.5 mL/min with 2% Buffer B (Acetonitrile, 0.1% (w/v) ammonium hydroxide). Peptides were eluted using a non-linear gradient (5-25 % B over 45 minutes, 25-40% B over 15 minutes, 80% B for additional 10 minute) at a flow rate of 0.5 mL/min. Fractions were collected from the beginning of the gradient at 1 tube /min for 60 minute, dried in a SpeedVac and stored at -20°C. In this approach, 60 fractions were collected from the first dimensional reversed-phase separation at high pH (approximately pH 10). And then these fractions were pooled and 23 combined peptide samples were obtained for the second separation at low pH (approximately pH 3) reversed-phase liquid chromatography. The schematic representation of pooling strategy is presented in supporting information Figure S3.

Nano-LC-MS/MS Nano-LC separation was conducted using a Thermo Scientific™ EASY-nLC™ 1000 HPLC system. Mobile phases were composed of [A] water (0.1% formic acid) and [B] acetonitrile (0.1% formic acid). Peptides were directly loaded onto a homemade C18 column (75 µm ID x 15 cm, 2 µm, 100 Å). The analytical gradient was from 6-25% B in 55 min followed by 25-35% B in 15min, and then 80% B for 9 ACS Paragon Plus Environment

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extra 10 min. Flow rate for analytical gradients was 300 nL/min. All the separated peptide fractions were then analyzed using a Thermo Orbitrap Fusion mass spectrometer. Data were acquired on the Orbitrap Fusion MS using Data dependent mode: Top Speed, Precursor priority: Most intense, and Scan time in each cycle: 3s. Mass window for precursor ion selection is 1.6 m/z, Intensity threshold for precursor ion selection of 5.0e4, Charge state screening parameters of 2-7 and Mass resolution of 15000 for MS2 was used. MS Scan Properties select Orbitrap Detector Type, Orbitrap Resulution 120000, and Scan Range of 400-1600 m/z, RF Lens60 %, AGC Target 2.0e5 and Max Injection time: 50ms. Data-dependent MS/MS Properties select Quadrupole isolation mode followed by HCD activation type with 35% HCD collision energy, Orbitrap Detector Type, AGC Target is 5.0e4 and Max Injection time is 60ms and Dynamic Exclusion time is 60s.

Database searching All MS/MS samples were analyzed using Mascot (Matrix Science, London, UK; version 2.5.1). Mascot was set up to search the A. fumigatus Af293 database (20061 entries) download from the NCBI assuming the digestion enzyme trypsin. Mascot was searched with a fragment ion mass tolerance of 0.020 Da and a parent ion tolerance of 10.0 PPM. Methylthio of cysteine and iTRAQ 8plex of lysine and the N-terminus were specified in Mascot as fixed modifications. Oxidation of methionine and iTRAQ8plex of tyrosine were specified in Mascot as variable modifications. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE

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partner repository with the dataset identifier PXD004670 and 10.6019/PXD004670. The raw

spectrum data for representative of MS/MS spectrum of the iTRAQ-labeled peptides for the cellulolytic proteins is presented in File S1. The detail information about identified proteins obtained from Mascot analysis is presented in Table S4-S5. The variation of each reporter identified for different peptides in same proteins are presented in supporting information Table S6.

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Quantitative data analysis Scaffold Q+ (version Scaffold_4.5.3, Proteome Software Inc., Portland, OR) was used for peptide and protein identifications and statistical analysis of proteins based on iTRAQ-labeled. Peptide identifications were accepted if FDR is less than 1.0%. Peptide Probabilities from Mascot were assigned by the Peptide Prophet algorithm37 with Scaffold delta-mass correction. Peptide Probabilities from Mascot were assigned by the Scaffold Local FDR algorithm. Protein identifications were accepted with less than 1% FDR and contained at least 2 unique peptides per protein. Modified or non-tryptic peptides were subjected to separate statistical filters to limit false discovery. Protein probabilities were assigned by the Protein Prophet algorithm37-38. Proteins that contained similar peptides and could not be differentiated based on MS/MS analysis alone were grouped to satisfy the principles of parsimony. Data were Log2-transformed, and weighted by an adaptive intensity weighting algorithm. All normalization calculations were performed using medians to multiplicatively normalize data based on Oberg’s approach39. Differentially expressed proteins (p values0.84, suggesting the acceptability of experimental variation Figure 6A. Gene ontology of the identified proteins was studied using Blast2go, KAAS database, CAZy database and Agbase database based on their cellular component, biological process, and molecular function (Figure S1). The result showed that most of the proteins obtained were from extracellular component as anticipated (Figure S1A) and also found to possess the molecular function and biological process involved in cellulolytic process, carbohydrate metabolism and sugar transport (Figure S1B, and S1C). The possible reason for identification of some intracellular and cell wall proteins might be due to cell lysis, cell death or other mechanism during sample processing18, 21. Functional classification of proteins showed that 15% cellulases, 14 % glycosyl hydrolases, and 22% hemicellulases has been identified (Figure 6C). Recent report on functional classifications of protein quantified from A. fumigatus showed that out of 73 cellulase and glycoside hydrolase group of proteins 32.9% and 16.2% protein belong to cellulases and glycoside hydrolases, and hemicellulases, respectively25. Comparatively, iTRAQ analysis of T. reesei revealed 31.34% cellulases and 17.91% hemicelluloses in presence of lignocellulosic biomass18. In this study, more hemicellulases were produced as compared to other microbial source. The graph of theoretically obtained molecular weights vs. isoelectric points of identified proteins suggests that molecular weights of the proteins range between 10 - 170 kDa, while their isoelectric points range between 4.0-11.0, indicating that most of the proteins were acidic to neutral (pI 4-7) (Figure 6B). The cultivation of A. fumigatus on different forage based carbon sources induced the production of different GH family proteins, carbohydrate metabolizing proteins, polysaccharide transport and degrading 16 ACS Paragon Plus Environment

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proteins. The quantitative expression pattern of cellulolytic proteins upon induction with CCC, WCC and SCC as a sole carbon source is listed in Table 1. The identified proteins were further categorized into different families, in which more than 50% of the proteins belong to GH family protein (Figure 7), such as Endo-β-1-3-glucanase (GH 16), β-glucosidase (GH 3), and β-glucanosyltransferase (GH 72) (Table 1, Figure 7). The hierarchical cluster of protein expression using R package gplots function depicted 5 different clusters C1-C5 (Figure S2). Upon FunCat analysis, (data not shown) with Bonferroni correction < 0.05, and p-value < 0.05, cellulase encoding genes such as AFUA_7G05450, AFUA_6G06770, AFUA_4G03585 and AFUA_3G07520 were found to be involved in sugar, glucoside, polyol and carboxylate metabolism, polysaccharide metabolism and biogenesis of cellular component. In addition, several genes encoding exo-β-1,4-glucanase and glucosidase (AFUA_8G06890, AFUA_6G13270) were expressed with significant enrichment in degradation and modification of exogenous polysaccharide. On the other hand, proteins such as α-1,3 glucanase (AFUA_6G13610) and endo-β-1,4 xylanase (AFUA_2G03980) involved in polysaccharide binding and SUN domain protein (Uth1) was expressed for cell aging process. Many unspecified proteins were also identified together with other proteins involved in cellular and metabolic processes such as glycolysis and gluconeogenesis, fungal development, transport, etc. Hence, protein hierarchical cluster results indicated that the pattern and quantity of protein expression differed in A. fumigatus fed with different carbon sources.

Identification and iTRAQ quantification of cellulolytic proteins The genomic comparison shows T. reesei with 10 cellulolytic genes 18 while that of A. fumigatus support a higher cellulolytic activity with 19 cellulases genes

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. It is well known that three major enzymes,

endoglucanase, hemicellulase, and β-glucosidase, mediates the hydrolysis of complex cellulose into simple sugars. In the present study, we categorized the identified proteins into above three groups of enzymes and also enzymes such as cellulose-binding protein, glycosidase/galactosidase, and cellulose-

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hydrolyzing proteins (Table 1). With reference to the data analysed for iTRAQ of secretomic analysis of A. fumigatus , we analyzed major and important GH family proteins. The comparisons of similar identified proteins induced by different carbon source that are compared with previously identified protein from A. fumigatus have been elaborated in Table 1. This study identified 10 endoglucanases, among which three GH 16 cell wall glucanases (gi|66848373, gi|66850620, and gi|66847078) were induced by SCC, whereas GH 72 glucanosyltransferase (gi|66844618) and GH 17 β-1,3-endoglucanase (gi|66845978) were induced by CCC and WCC. Previous studies on A. fumigatus secretome reported the abundance of endoglucanase (gi|66846467, gi|66845787 and gi|66846525) and endo 1-3,β-glucosidase belonging to GH 45, GH 5, and GH 12 when grown under cellulose induction25. GH7 cellobiohydrolaseD (gi|74670999) and GH 3 βglucosidase (gi|74668742) were also found to be expressed upon cellulose induction, while that in A. nidulans GH 1, GH 3, GH 6, GH 7, GH 5, and GH 61 endoglucanase and cellulases were quantified26. Adav et. al identified GH 30 β-1,6-glucanase (gi|70983969) to be up-regulated with cellulose induction28. On the other hand the T. reesei QM6a and Rut C30 abundantly induced GH 7, GH 30 and GH 61 endoglucanases and glucosidases (gi|340518009, gi|340522464 and gi|340519892)18 . In addition, iTRAQ quantification of GH 3 Cel3b β-glucosidase (gi|340518276) in the secretome of T. reesei implies its hypercellulolytic nature that avoids the negative inhibition by cellobiose18. Most of the exoglucanases and endoglucanases such as PL3 exo-β-1,3-glucanase (gi|66852496, gi|66848836), GH 16 cell wall glucanase (gi|66848373, gi|66850837) and GH 81 endo-1,3-β-glucanase (gi|66847805) identified in the present study were similarly expressed in previous studies on A. fumigatus LF9 (Table 1) 28. Two different GH 16 cell wall glucanases (gi|66846259 and gi|66850620) and cell wall biogenesis protein (gi|66846257) were identified in this study. These proteins are required for the carbohydrate metabolic process, and linkage of chitin to β-1,3-glucose branches of β-1,6-glucan, an important step in the assembly of main structural component of cell wall, which has not been reported in the previous study of A. fumigatus secretome analysis. Numbers of cellobiose cleaving β-glucosidases were also quantified in this study. One GH 3 βglucosidase (gi|66847959) was identified in this study with the iTRAQ ratio 0.72±0.1 and 0.8±0.03 in

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CCC and WCC respectively while 0.5±0.01 in case of SCC-induced expression. Interestingly, it appeared that A. fumigatus share many similar GH family proteins even in different carbon source. Compared to the previous studies on A. fumigatus LF9 25, 28, GH 3 β-glucosidase (gi|66850743), GH 16 cell wall glucanase (gi|66850620) and GH 17 endo-1,3-β-glucosidase (gi|66845978) were the most commonly expressed proteins from A. fumigatus under cellulosic substrate induction. As compared with the proteins detected in A. fumigatus Z524, only few proteins identified were found to be commonly expressed in this study while the present results share more common proteins with A. fumigatus LF927, as mentioned in Table 1. However, the most common Aspergillus GH 18 and GH 45 family proteins observed in previous studies24, 27

were found to be missing in this study. The possible reason behind lacking some cellulolytic protein

expression might be due to some loss during sample preparation and also normalization during data processing. These observations suggest that A. fumigatus is able to produce different sets of enzymes to break down different cellulose structures. The important factor that enhances substrate hydrolysis is the adhesion of cells to substrates, which eliminates competitors from liberated sugars present in the culture medium, as well as degrade unmodified crystalline cellulose18, 54. Most commonly identified hemicellulase in the secretome of Aspergillus are GH 10, GH 43, GH 47, GH 62 and GH 35, while that in Trichoderma are GH 11, GH 30, GH 79, GH 47 and GH 28, but it is stated that hemicellulases such as GH 30 and GH 55 are rarely expressed by Trichoderma18-19, 24, 55. Some unique hemicellulase such as GH 38 mannosidase II (gi|57338726), GH 47 mannosidase (gi|66850460), and GH 27 α-galactosidase (gi|66850907, gi|298351562) were identified in presence of CCC, WCC, and SCCculture. In contrast, the result differs in terms of xylanase and some other hemicellulase. Although, we identified number of hemicellulases in this study, it was observed that this study lack most of the important GH such as GH 10 and GH 11 with xylosidase properties identified in the study done by Adav et. al

28

. Although the quantitative cellulase expression has been less extensively done in A. fumigatus,

some studies have characterized the mRNA expression of this species with β-mannosidase, endo-β-1,4xylanase and α/β galactosidase16, 18, 20. The present study also identified some other proteins, such as SUN 19 ACS Paragon Plus Environment

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domain protein (gi|66846594), hydrophobin (gi|66850728, gi|66851317), and fucose-specific lectin (gi|66850819) that could improve binding of sugars and polysaccharide. Cellulose binding and transport protein, such as CBM 20 glucoamylase (gi|66846839) and endo-arabinase (gi|66853445) have also been taken into consideration since these proteins play some role in cellulolytic process. One pectin methylesterase (gi|66845113) was identified in the secretome obtained from CCC, WCC and SCC-culture in the present findings. The detailed variation of these proteins on different cultivation is shown in the Table 1, Table S4-S6. Lignin (10-25 % constituent of lignocellulosic biomass) is mainly composed of aromatic compound without any sugar. It remains as a residue and hence, lignin degradation is also a demanding task for efficient degradation of lignocelluloses. Till date, P. chrysosporium has been studied as a model organism for lignin degradation since it can act on lignin efficiently when grown on lignocellulosic biomass 16, 18, 2021

. Aspergillus sp. was found to produce lignin degrading enzyme, while T. reesei can degrade cellulose

but not lignin

19, 54

. So regarding this property Aspergillus sp. could be possible model organism for

cellulose degradation. Previous study quantified lignin de-polymerizing enzymes like copper oxidase, CuZn superoxide dismutase, peroxidase, glyoxal oxidase and glutathione reductase as the major enzymes which work by catalyzing initial oxidation of phenolics and aromatic amines to diffuse oxidases and reactive radical creating an easy environment for microbes to participate in lignin de-plymerization

21

.

Table 1 shows the comparative result for lignin degrading protein expression obtained when the present data was compared with previous findings. Adav et. al. showed that most commonly expressed lignin hydrolyzing protein in A fumigatus are similar to our findings such as mycelial catalase (gi|70986104), alcohol dehydrogenase (gi|119498511), FAD/FMN-containing isoamyl alcohol oxidase (gi|70984404), FAD-dependent oxygenase (gi|70985799), and catalase-peroxidase (gi|74629205)25,28. All of these expressed proteins were shared among A. fumigatus as well as expressed in wide variety of cellulosic substrate 24. In the present study, some unique lignin depolymerizing enzymes were identified with great variation among three different forage based carbon source. Catalase B (gi|2493539), FAD-dependent

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oxidase (gi|66847480), NADH-ubiquinone oxidoreductase (gi|66853031, gi|66853461) and isoamyl alcohol oxidase (gi|66844460, gi|129556964) were identified in A. fumigatus grown on CCC, WCC and SCC. These results indicated that A. fumigatus expressed different level of lignocellulases to depolymerize lignin present in carbon sources used in this study. It further clarifies that different forages used to feed animals differ with the lignin content and the result could provide a specific enzyme required as a supplement to enhance digestion and absorption. The production of such proteins has been reported but the exact correlation of such proteins on cellulolytic and lignocellulolytic properties have not been clearly defined yet 18-19, 54-55.

Analysis of iTRAQ quantified modulated protein by RT-PCR The iTRAQ quantified data was further complemented with transcription of the genes that are involved in cellulolysis by RT-PCR. 14 genes encoding cellulolytic proteins identified by iTRAQ quantification were selected. RNA was extracted from A. fumigatus cultivated with CCC, WCC, or SCC for 12 to 96 h, followed by real time PCR analysis (Figure 8). Most of the genes such as exo-β-1,3-glucanase (gi|66850450),

endo-1,3-β-glucanase

(gi|66847805),

α-1,3-glucanase/mutanase

(gi|66847161),

endoarabinase (gi|66853445) and glucan endo-1,3-β-glucosidase (gi|66845978) showed a similar pattern of expression and regulation (Table 2). However, some of the genes did not offer correlated pattern of expression between iTRAQ and RT-PCR quantification. Previous studies also reported the correspondence between proteins and their mRNA expression patterns under different treatments and observed that RT-PCR is an important way to validate the proteomics microarray data. The weak accordance with corresponding protein expression levels could be the result of influence of some factors that alter transcription and translation mechanism20, 25, 56. Remarkably, most of the genes tested showed increased mRNA accumulation at 48 h and greatly reduced at 96 h. However, all the genes, to some extent, showed variation of expression during fungal growth in presence of different carbon sources,

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which apparently supports that the approach used in this study is capable of providing information about A. fumigatus gene expression modulation. Transcriptional study alone done in A. niger reported 18 cellulases and 21 hemicellulases encoding genes expressed during growth on SEB and emphasized the importance of transcriptional modulation degradation of lignocelluloses24. Although most of the genes were found to be highly expressed at 48 h (mycelial growth phase), the expression levels were different (Figure 8). The expression level of endo-1,3(4)-β-glucanase (gi|66847805) and exo-β-1,3-glucanase (gi|66850450) was higher when A. fumigatus was cultured with CCC (48 h), while the expression of endo1,3(4)-β-glucanase (gi|66847805) was comparatively low when A. fumigatus was cultured with WCC and SCC. These results suggested that the structure and complexity of the cell wall celluloses for different plant seeds were different and hence different groups of enzymes were required for efficient degradation. Similarly, it also provide some hints that, if these enzymes are used as a supplements in animal feed, it could be consistent with the stability of enzyme, as well as the length of the time that the food remain in digestive system, since expression of enzymes with respect to time is very crucial for any enzymatic reactions. The similar transcriptional study done in A. nidulans showed enhanced expression time for mannosidase (AN5361), GH 16 extracellular cellulase (AN0933), GH 16 endo-1,3-β-glucanase (AN6819), GH 72 β-1,3-glucanosyltransferase (AN1657) and β-1,3-exoglucanase (AN0779) showed higher expression up to day 3 ranging from day 1 to day 7. Similarly, A. nidulans PL3/PL1 pectale lyase ( AN2569, AN7646, AN8453) and GH 15 glucoamylase (AN7402) demonstrated maximum expression at day 3

26

. In the present study, hemi/cellulase encoding gene such as cellobiose dehydrogenase

(gi|71002832), endo-1,3-β-glucosidase (gi|66845978) and endo-arabinase (gi|66853445) showed high mRNA accumulation in CCC-induced culture at 48 h as compared with other genes. Likewise, in case of the

WCC-cultured

A.

fumigatus,

exo-β-1,3-glucanase

(gi|66853445),

endo-1,3-β-glucosidase

(gi|66845978), endoarabinase (gi|66853445) and α-mannosidase (gi|66852431) might play an essential role in its complex cell wall degradation at the later stage of maturity (96 h). Similarly, expression of βglucosidase in A. fumigatus cultivated with all three carbon sources was observed to be highly expressed

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as compared with other enzymes observed in this study. Hence, the overall results revealed that A. fumigatus stimulated differential expression of various enzymes at different stages of its maturity when grown on structurally and compositionally different plant seeds and thus provided with a valid understanding about different sets of enzymes required for sequential degradation of celluloses or hemicelluloses present in major animal forages.

Discussion In recent years, enzymatic degradation of lignocellulosic biomass into fermentable sugars has drawn significant interest due to its varieties of beneficial use as alternate bioenergy source as well as in animal feeding19. In the present study, we mainly focused on cellulases that are important for animal feeding so as to progress the energy conversion and efficient degradation of forages for better assimilation of feed, as well as animal health. Filamentous fungi, such as T. reesei, A. niger, and A. nidulans, have been widely used for the production of the wide range of cellulolytic enzymes, which show transcriptional regulation and carbon source dependency14, 18, 41. Many industrially focused researches have been done in T. reesei to identify the best possible lignocellulose-degrading enzymes. Moreover, early studies used agriculture crop residues like sugarcane baggase, wheat bran, corn stover etc for microbial enzyme induction56-57. As A. fumigatus is known to harbor more GH genes and produce many stable enzymes such as phytase, chitinase, and cellulase as compared to well-known lignocellulolytic enzyme producer T. reesei and P. chrysosporium22, 24, 30, 58, it should be an successful lignocellulose degrader and an ideal model organism to investigate the synergistic degradation of lignocelluloses by enzymes. The comparative analysis reveals that A. fumigatus possesses a higher cellulolytic activity as compared with T. reesei and P. chrysosporium, where the expression pattern depends on carbon source and various other factors27. In this study, for the first time, we used major forage of pigs and poultry feeding i.e. corn, wheat or soybean cell wall as sole carbon source to cultivate A. fumigatus. The main hypothesis of this research is that A. fumigatus could

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produce different sets of cellulose degrading enzymes to efficiently degrade the lignocellulose present in corn, wheat and soybean cell wall, which would be an efficient strategy that is obtained by A. fumigatus during long-term evolution. Although A. fumigatus is an opportunistic fungal pathogen, the strategy adopted by A. fumigatus could be applied to design a enzyme cocktail to improve animal feeding. In addition, A. fumigatus is an ideal source to obtain the genes encoding stable cellulose degrading enzymes. Expression of these genes in non-pathogenic microorganism will provide promising enzymes for enzyme cocktail. This work combined enzyme activity assay, extracellular protein expression and transcriptional modulation in order to find efficient enzyme combination for degradation of plant seed cell wall. More importantly, by taking the advantage that A. fumigatus produces a number of stable enzymes, the present work mimics the digestive physiology of pigs in order to accomplish major goal of enhancing feed degradation. The body temperature of pig is slightly higher than human which vary from 38-39°C. The pH in the stomach of fully fed pigs rarely go above pH 3.0 and the distal digestive tract (duodenum, jejunum, ileum, and caecum) shows pH ranging 5.5-7. There are variable degrees of food break down and absorption in each part of digestive tract which influences the activity of enzymes47, 59-60. By using SEM analysis and activity assay, we showed that A. fumigatus was able to efficiently degrade the lignocelluloses derived from corn, wheat, and soybean. As expected, our data showed that the A. fumigatus lignocellulolytic enzymes were stable and active under the mimicry conditions of pig digestive tract, which enable us to completely evaluate how enzymes synergistically degrade lignocellulose under animal physiological condition. Our results demonstrated that the enzyme activity differs with carbon source complexities and also with time required for fungi to degrade and break down the complex structure of lignocelluloses, which is consistent with earlier reports that explained the variable expression of cellulases when cultured with different carbon sources24. To understand how A. fumigatus degrades lignocelluloses with different component and structure, comprehensive iTRAQ based proteomic analysis of secretome was carried out with A. fumigatus 24 ACS Paragon Plus Environment

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cultivated in lignocellulosic biomass derived from animal forage. iTRAQ result differentiates the level of expression of different proteins depending on carbon source61-62. Our study revealed that endoglucanases, exoglucanases and β-glucosidases belonging to GH 2, GH 16, GH 72, GH 43, GH 17 and GH 3 were found to be up-regulated and two different PL-3 family protein were found to be abundant, while GH 30, GH 45, GH 55, GH 61, GH 81, GH 5 were found to be abundant and differentially regulated in P. chrysosporium and T. reesei

16, 18

. Previous study reported that A. fumigatus produced significantly up-

regulated enzyme such as endoglucanases (GH 12, GH 5, and GH 45), cellobiohydrolase (GH 7), and βglucosidase (GH 3)27. In comparison to these previous findings, our results spotted some potential enzymes giving more importance to GH 16, GH 17, GH 16, GH 43, GH 38, GH 81, GH 72, GH 76 and GH 47. Most of the proteins that were identified in this study are predominantly present in most of the fungi including A. fumigatus. To our knowledge, some most common cellulolytic proteins identified, such as GH 27, GH 16, and GH 17, are multifunctional. For example, GH 16 may act as endo 1,3 β-glucanase as well as xyloglucosyltransferase and GH 17 acts as endo 1,3 β-glucanase and transglycosidase. These properties may also have some role in the variation in the degree of lignocellulolysis. The structural studies have opened up the idea that all endocellulases have open active sites and are able to bind at any point along with cellulose molecule, while some enzymes’ active sites remain in a tunnel with multiple subsites for binding glucose residues63. Some other unique family protein such as CBM family, CHD family protein, and SUN domain protein have also found to be actively regulated in the present study. This clearly suggests that specific set of enzymes are required for efficient degradation of the CCC, WCC, and SCC. Many different cellulases, β-glucosidases, hemicellulases, and lignin degrading proteins were also identified mostly belonging to GH family and some belonging to pectate lyase family, hydrophobin and CBM family. The effect of carbon source in variability of iTRAQ ratios of expressed proteins focusing on greater involvement of high expressions potential in lignocellulose degradation has been documented18. Recently, the studies are more focused on the impact of post translational modification and deamidation on enzyme production and expression also12, 27, which is however not dealt with detail in the present study.

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Our results successfully validated that the expression pattern of proteins and mRNAs of A. fumigatus to greater extent. Out of 14 different genes selected form the iTRAQ result, some of the genes such as cellobiose dehydrogenase, endo-1,3-β-glucosidase, and endo-arabinase were found to be expressed in CCC-cultivated A. fumigatus while most of the β-glucosidase and glucanases were abundantly expressed in all three carbon source used. The expression of genes in A. fumigatus was found to be varied with time, which could somehow be attributed to the feeding and digestion process in animals. RT-PCR data showed activation and expression of different enzymes with respect to time. In addition, our results demonstrated that not all A. fumigatus enzymes were induced at the same time but rather induced sequentially depending upon the structure of lignocelluloses. This observation is similar with the previous studies, which proposed that some degrading enzymes are induced parallel while some in sequential manner depending on substrate as well as their transcriptional and translational regulation24,

26, 64

. The overall result also

provides the insinuation for the continuation of research to attain a major goal of finding proper enzyme combination. So the use of A. fumigatus expression pattern at different time could be another most important factor for finding best possible enzyme cocktails which is lined up for our future work.

Conclusion Through these findings, it is suggested that different forages used for animal feeding possess different cell wall structure and composition, hence requires different sets of enzymes to break their complexities. This study unfolds the fact that A. fumigatus can offer an excellent microbial system for cellulose degradation. Moreover, the degradation also depends on the gut physiology which restricts the efficient digestion and absorption of starch present in plant seed. The approach of highly sensitive quantitative analysis of proteome and transcriptome respond to the probable enzyme combination required in agro industries and animal feeding purpose towards more efficient cellulose degradation and therefore better digestion of intracellular starch. Furthermore, out of 46 expressed proteins, number of important GH family protein,

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some CBM and polysaccharide lyase family proteins have been identified, which could attribute towards better degradation of lignocelluloses to release starch. Associated Content

Supporting Information Table S1 Substrates used in the study Table S2 Primer pairs used for RT-PCR Table S3 List of cellulose degrading proteins separated by SDS-PAGE and identified by LC-MS/MS spectrometry Table S4 List of details of identifications and relative quantifications for proteins Table S5 List of LC MS/MS proteomic results of identified proteins obtained from iTRAQ analysis Table S6 List of Quantitative Peptide report of variation of different reporters in different peptides of same protein Figure S1 Distribution of iTRAQ identified proteins Figure S2 Hierarchical cluster and classification based on expression pattern Figure S3 Scheme of fractionation and pooling strategy applied to the RPLC File S1 MS/MS spectrum of identified protein involved in cellulolytic process when A. fumigatus was grown with corn, wheat and soybean cell wall cellulose as a sole carbon source. MS/MS Raw data: The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD004670 and 10.6019/PXD004670.

Abbreviations

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GH: Glycoside hydrolase; iTRAQ: isobaric tags for relative and absolute quantification; RT-PCR: reverse transcriptase polymerase chain reaction; CCC: Corn cell wall cellulose; WCC: Wheat cell wall cellulose; SCC: Soybean cell wall cellulose; CT: Control; SEM: Scanning electron microscopy; SDS-PAGE: Sodium dodecyl sulfate-polyacrylamide gel electrophoresis; LC-MS/MS: Liquid chromatography-tandem mass spectroscopy; CBM: Carbohydrate binding module; SHMM: Spent hydrolysate model medium; CMC: Carboxymethyl cellulose; CAZy families: Carbohydrate active enzyme families; CDH: Cellobiose dehydrogenase; DNS: Dinitrosalicylic acid; TEAB: Triethylammonium bicarbonate; DTT: Dithiothreitol; BSA: Bovine serum albumin; GO:Gene ontology; BP: Biological process; CC: cellular component; MF: Molecular function.

Acknowledgments This project was supported by the State ‘‘863’’ High-tech Project of China (2014AA093511).

Authors’ contributions PS carried out the scretome analysis, iTRAQ, RT-PCR analysis, and drafted the manuscript. HO partially designed the experiments and participated in the sequence alignment. QW and YL carried out the iTRAQ analysis and data analysis. BS and JY participated in the design of the study. CJ conceived of the study, and participated in its design and coordination and helped to draft the manuscript. All authors read and approved the final manuscript.

Competing interests The authors declare that they have no competing interests.

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36. Vizcaíno, J. A.; Côté, R. G.; Csordas, A.; Dianes, J. A.; Fabregat, A.; Foster, J. M.; Griss, J.; Alpi, E.; Birim, M.; Contell, J., The PRoteomics IDEntifications (PRIDE) database and associated tools: status in 2013. Nucleic acids research 2013, 41 (D1), D1063-D1069. 37. Keller, A.; Nesvizhskii, A. I.; Kolker, E.; Aebersold, R., Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Analytical chemistry 2002, 74 (20), 5383-5392. 38. Nesvizhskii, A. I.; Keller, A.; Kolker, E.; Aebersold, R., A statistical model for identifying proteins by tandem mass spectrometry. Analytical chemistry 2003, 75 (17), 4646-4658. 39. Oberg, A. L.; Mahoney, D. W.; Eckel-Passow, J. E.; Malone, C. J.; Wolfinger, R. D.; Hill, E. G.; Cooper, L. T.; Onuma, O. K.; Spiro, C.; Therneau, T. M., Statistical analysis of relative labeled mass spectrometry data from complex samples using ANOVA. J Proteome Res 2008, 7 (1), 225-233. 40. Wang, J.; Zhou, H.; Lu, H.; Du, T.; Luo, Y.; Wilson, I. B.; Jin, C., Kexin-like endoprotease KexB is required for N-glycan processing, morphogenesis and virulence in Aspergillus fumigatus. Fungal Genet Biol 2015, 76, 57-69. 41. Semighini, C. P.; Marins, M.; Goldman, M. H. S.; Goldman, G. H., Quantitative Analysis of the Relative Transcript Levels of ABC Transporter Atr Genes in Aspergillus nidulans by Real-Time Reverse Transcription-PCR Assay. Appl Environ Microbiol 2002, 68 (3), 1351-1357. 42. Ma, Q.; Wu, M.; Pei, W.; Li, H.; Li, X.; Zhang, J.; Yu, J.; Yu, S., Quantitative phosphoproteomic profiling of fiber differentiation and initiation in a fiberless mutant of cotton. BMC genomics 2014, 15 (1), 466. 43. ZHANG, J.-z.; Yang, G.; LU, Q.-p.; SA, R.-n.; ZHANG, H.-f., iTRAQ-based quantitative proteomic analysis of longissimus muscle from growing pigs with dietary supplementation of non-starch polysaccharide enzymes. Journal of Zhejiang University Science B 2015, 1. 44. Xiong, Y.; Coradetti, S. T.; Li, X.; Gritsenko, M. A.; Clauss, T.; Petyuk, V.; Camp, D.; Smith, R.; Cate, J. H.; Yang, F.; Glass, N. L., The proteome and phosphoproteome of Neurospora crassa in response to cellulose, sucrose and carbon starvation. Fungal Genet Biol 2014, 72, 21-33. 45. Qin, J.; Gu, F.; Liu, D.; Yin, C.; Zhao, S.; Chen, H.; Zhang, J.; Yang, C.; Zhan, X.; Zhang, M., Proteomic analysis of elite soybean Jidou17 and its parents using iTRAQ-based quantitative approaches. Proteome Sci 2013, 11 (1), 12. 46. Wang, S.; Chen, W.; Xiao, W.; Yang, C.; Xin, Y.; Qiu, J.; Hu, W.; Ying, W.; Fu, Y.; Tong, J.; Hu, G.; Chen, Z.; Fang, X.; Yu, H.; Lai, W.; Ruan, S.; Ma, H., Differential Proteomic Analysis Using iTRAQ Reveals Alterations in Hull Development in Rice (Oryza sativa L.). PLoS One 2015, 10 (7), e0133696. 47. Ingram, D. L.; Legge, K. F., Variation in deep body temperature in the young unrestrained pig over the 24 hour period. J. Physiol. 1970, 210, 989-998. 48. Kararli, T. T., Comparison of the gastrointestinal anatomy, physiology, and biochemistry of humans and commonly used laboratory animals. Biopharmaceutics & Drug Disposition 1995, 16 (5), 351380. 49. Kosugi, A.; Murashima, K.; Doi, R. H., Characterization of xylanolytic enzymes in Clostridium cellulovorans: expression of xylanase activity dependent on growth substrates. J Bacteriol 2001, 183 (24), 7037-43. 50. Mawadza, C.; Hatti-Kaul, R.; Zvauya, R.; Mattiasson, B., Purification and characterization of cellulases produced by two Bacillus strains. J Biotechnol 2000, 83 (3), 177-87. 51. Charita Devi, M.; Sunil Kumar, M., Production, optimization and partial purification of cellulase by Aspergillus niger fermented with paper and timber sawmill industrial wastes. J. Microbiol. Biotech. Res 2012, 2 (1), 120-128. 52. Jahangeer, S.; Khan, N.; Saman, J.; Sohail, M.; Ahmed, A.; Khan, S. A., Screening and characterisation of fungal cellulase isolated from native environmental source. Pak. J. Bot. 2005, 37 (3), 739-748. 31 ACS Paragon Plus Environment

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53. Hideno, A.; Inoue, H.; Tsukahara, K.; Yano, S.; Fang, X.; Endo, T.; Sawayama, S., Production and characterization of cellulases and hemicellulases by Acremonium cellulolyticus using rice straw subjected to various pretreatments as the carbon source. Enzyme MicrobTechnol 2011, 48 (2), 162-8. 54. Wilson, D. B., Microbial diversity of cellulose hydrolysis. Curr Opin Microbiol 2011, 14 (3), 259-63. 55. Adav, S. S.; Ng, C. S.; Sze, S. K., iTRAQ-based quantitative proteomic analysis of Thermobifida fusca reveals metabolic pathways of cellulose utilization. J Proteomics 2011, 74 (10), 2112-22. 56. Andrade, J. P.; Bispo, A. S.; Marbach, P. A.; do Nascimento, R. P., Production and Partial Characterization of Cellulases from Trichoderma sp. IS-05 Isolated from Sandy Coastal Plains of Northeast Brazil. Enzyme Res 2011, 2011, 167248. 57. Manavalan, T.; Manavalan, A.; Thangavelu, K. P.; Heese, K., Secretome analysis of Ganoderma lucidum cultivated in sugarcane bagasse. J Proteomics 2012, 77, 298-309. 58. Grigorevski-Lima, A.; Da Vinha, F.; Souza, D.; Bispo, A.; Bon, E.; Coelho, R.; Nascimento, R., Aspergillus fumigatus thermophilic and acidophilic endoglucanases. Appl Biochem Biotechnol 2009, 155 (1-3), 18-26. 59. Thacker, P. A.; Baas, T. C., Effects of gastric pH on the activity of exogenous pentosanase and the effect of pentosanase supplementation of the diet on the performance of growing-finishing pigs. Animal Feed Science Technology 1996, 63, 187-200. 60. Mussatto, S. I.; Fernandes, M.; Milagres, A. M. F.; Roberto, I. C., Effect of hemicellulose and lignin on enzymatic hydrolysis of cellulose from brewer's spent grain. Enzyme and Microbial Technology 2008, 43 (2), 124-129. 61. Wu, W. W.; Wang, G.; Baek, S. J.; Shen, R.-F., Comparative study of three proteomic quantitative methods, DIGE, cICAT, and iTRAQ, using 2D gel-or LC-MALDI TOF/TOF. J Proteome Res 2006, 5 (3), 651658. 62. Hou, Q.; Tan, H. T.; Lim, K. H.; Lim, T. K.; Khoo, A.; Tan, I. B.; Yeoh, K. G.; Chung, M. C., Identification and functional validation of caldesmon as a potential gastric cancer metastasis-associated protein. J Proteome Res 2013, 12 (2), 980-90. 63. Wilson, D. B., Processive and nonprocessive cellulases for biofuel production--lessons from bacterial genomes and structural analysis. Appl Microbiol Biotechnol 2012, 93 (2), 497-502. 64. Gautam, P.; Shankar, J.; Madan, T.; Sirdeshmukh, R.; Sundaram, C. S.; Gade, W. N.; Basir, S. F.; Sarma, P. U., Proteomic and transcriptomic analysis of Aspergillus fumigatus on exposure to amphotericin B. Antimicrob Agents Chemother 2008, 52 (12), 4220-7.

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Figure captions: Figure 1. Scanning electronic microscopy (SEM) for samples grown in absence and presence of A. fumigatus. I, II, and III, SEM of samples CCC, WCC, and SCC respectively in absence of fungi shows the complex and compact nature of cellulosic carbon source. IV, V, and VI, SEM of samples for CCC, WCC, and SCC respectively cultured with fungi shows fungal growth on the surface degrading the compactness of carbon source. Bars: 20.0 µm for I, II, III, IV, V, and VI.

Figure 2. SDS–PAGE and zymogram analysis of secreted protein. A, SDS-PAGE of protein secreted upon induction with CCC, WCC, SCC, and CT;. B, SDS-PAGE of secreted protein performed in 12% gel incorporated with 0.2% CMC and 0.2% xylan: Lane 1: CCC; Lane 2: WCC; Lane 3: CT; Lane 4: SCC; M: marker.

Figure 3. Enzyme activity of secreted cellulolytic enzymes under the influence of different carbon source. The cellulolytic activity of A. fumigatus enzyme vary according to the nature of different carbon sources (CT, CCC, WCC, and SCC). The results are represented as the Mean±SD of three replicates.

Figure 4. Activities of extracellular cellulolytic enzymes in the secretome of A. fumigatus at different temperature and pH. The activity of enzyme induced by CCC, WCC and SCC estimated at two different temperature; 39 οC and 50 οC and three different pH; 2.5, 6.8 and 9 was determined by DNS spectrophotometric assays. A, B, and C represents CMCase, xylanase, and pectinase enzyme activity respectively. The results are represented as the Mean ± SD of three replicates.

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Figure 5. Time dependent profiles of cellulolytic enzyme (cellulase, xylanase, and pectinase) production by A. fumigatus on different carbon sources. A, B, C, and D, sequential induction of enzyme by different carbon source measured at different time interval for CT (A), CCC (B), WCC (C) and SCC (D) used as a sole carbon source for enzyme induction. The results are represented as the Mean±SD of three replicates.

Figure 6. Classification of iTRAQ identified proteins. A, protein expression correlation of biological replicates of CCC, WCC, and SCC induced proteins with CT (galactose) induced protein; B, distribution of proteins as a function of theoretically obtained molecular weight and isoelectric point; and C, functional classification of the iTRAQ quantified protein indicating the percentage of the protein in the category.

Figure 7. Classification of iTRAQ identified protein based on the different families of protein. A, overall classification of protein identified showing nearly half of the protein belonging to GH family; B, classification of protein belonging GH family.

Figure 8. Relative expression of genes encoding cellulase, hemicellulase and β-glucosidase. I, II, and III, relative gene expression analysis for cellulase, hemicellulase and β-glucosidase respectively, induced by A. fumigatus during growth on A (CCC), B (WCC), and C (SCC) estimated by RT-PCR.

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Table 1. iTRAQ quantified proteins expressed during growth of A. fumigatus on lignocellulosic biomass containing CCC, WCC and SCC as sole carbon source. Unique

%

Family

CCC:CT

WCC:CT

SCC:CT

peptides

Cov

5

15.3

Exo-β-1,3-glucanase*

gi|66852496

Y

PL3

1.25±0.11

1.46±0.23

0.72±0.06

6

9.3

Endo-1,3(4)-β-glucanase

gi|66846259

Y

GH 16

0.65±0.03

0.72±0.24

0.5±0.01

6

15.6

Cell wall glucanase*

gi|66848373

Y

GH 16

0.88±0.12

0.99±0.23

1.71±0.06

2

10.9

Exo-β-1,3-glucanase

gi|66847742

Y

GH 2

0.73±0.11

0.62±0.03

1.15±0.03

8

21

α-1,3-glucanase/mutanase+*

gi|66847161

Y

GH 17

0.76±0.02

0.77±0

0.55±0.01

10

22.9

Cell wall glucanase

gi|66850620

Y

GH 16

0.82±0.06

1.14±0.37

2.03±0.18

9

28.3

Cellulase family protein+*

gi|66850837

Y

GH 2

0.95±0.03

0.95±0

0.41±0.04

10

16.7

Exo-β-1,3-glucanase *

gi|66850450

Y

PL3

0.81±0.05

0.81±0.01

0.55±0.01

11

22

Endo-1,3-β-glucanase *

gi|66847805

N

GH 81

0.63±0.02

0.64±0.01

0.36±0

2

5.64

Cell wall glucanase *

gi|66847078

Y

GH 16

1.37±0.01

1.43±0.04

1.91±0.3

5

22

Exo-β-1,3-glucanase*

gi|66848836

Y

PL3

0.84±0.03

0.79±0.08

0.58±0.07

16

16

1,3-β-glucanosyltransferase*

gi|193806027

Y

GH 72

1.01±0.06

1.07±0.12

0.66±0.03

8

3.9

1,3-β-glucanosyltransferase

*

gi|229890273

Y

GH 72

0.87±0.03

0.85±0.06

1.52±0.34

3

15.3

Glycosyl hydrolase

gi|66846836

Y

GH 76

0.88±0.04

0.94±0.02

0.55±0

gi|66844618

Y

GH 72

1.84±0

1.88±0.08

1.06±0.01

gi|66844039

Y

GH 2

0.67±0.01

0.64±0.02

0.37±0.03

gi|66848677

Y

CBD

0.72±0.18

0.76±0.02

7.79±1.29

4

29

Description

Accession

Signal peptide

1,3-β-glucanosyltransferase

3

12.5

Glycosyl hydrolase

2

7.51

1,4-β-D-glucancellobiohydrolyase

*

*

*

10.6

α-mannosidase

gi|66852431

N

GH 38

0.68±0.01

0.64±0.02

0.51±0.02

13

22.2

α-mannosidase

#

gi|66850460

Y

GH 47

0.7±0

0.63±0.05

0.46±0.02

17

27.3

Enolase

gi|66848203

N

Enolase

1.03±0.03

0.96±0.06

2.1±0.2

8

33.1

α-galactosidase

gi|298351556

Y

GH 27/CBM 35

1.22±0.02

1.22±0.1

0.64±0.01

8

100

Glyceraldehyde 3-phosphate

gi|66845773

N

GPDHN

1.23±0.12

1.16±0.25

2.41±0.16

gi|66850626

Y

GH 31

0.62±0.12

0.59±0.13

0.49±0.01

gi|66848406

N

GH 2

0.98±0.02

0.98±0.04

0.54±0.03

gi|66845113

Y

Pectinestearase

5.81±0.06

3.65±2.78

3.32±0.12

gi|66846839

Y

CBM 20

1.41±0.03

1.35±0.08

1.84±0.06

gi|66853445

Y

GH 43

0.6±0.03

0.59±0.01

0.77±0.02

gi|66850907

Y

CBD/GH 27

0.75±0.04

0.83±0

0.52±0.03

23

dehydrogenase 8 8 3 4

7.28 14.6 3.21 18.1

α-glucosidase* β-mannosidase

+*

Pectin methylesterase α-amylase

+*

*

4

15.6

Endo-arabinase

2

7.52

α-galactosidase

11

12.2

*

β-1,3-endoglucanase

*#

gi|66845978

Y

GH 17

1.82±0.15

1.63±0.09

1.21±0.06

*#

gi|66850620

Y

GH 16

0.82±0.06

1.14±0.37

2.03±0.18

gi|66846257

Y

NA

0.91±0.01

0.92±0.02

1.88±0.03

10

22.9

Cell wall glucanase

12

11.7

Cell wall protein PhiA

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12

13.9

β-glucosidase

gi|66847959

Y

GH 3

0.72±0.1

0.8±0.03

0.5±0

7

7

β-glucosidase*#

gi|66850743

Y

GH 3

0.66±0.02

0.65±0.04

0.45±0.13

7

5.57

Isoamyl alcohol oxidase

gi|66844460

Y

FAD binding domain

1.06±0.08

0.95±0.02

0.58±0.02

6

2.8

SUN domain protein

gi|66846594

Y

SUN

0.6±0.01

1.28±0.69

5.87±0.63

3

3.97

Oxidoreductase+*

gi|66853419

Y

FAD binding domain

1.11±0.28

1.23±0.01

0.9±0.03

6

11.9

Fucose-specific lectin

gi|66850819

N

NA

1.29±0.1

1±0.09

0.62±0

4

8.54

Cell wall biogenesis protein

gi|66850142

N

RNB domain

1.5±0.07

1.57±0.2

1.05±0.02

phosphatase

4

9.31

Glutathione peroxidase+

gi|66852031

N

GSH peroxidase

0.76±0.03

0.78±0.01

2.72±0.44

4

11

NADH-ubiquinone

gi|66853031

N

NADH reductase

0.85±0

0.85±0.02

2.52±0.45

gi|71002832

Y

CDH

4.57±0.08

0.3±0.79

1.17±0.07

gi|66850728

Y

Hydrophobin

0.72±0

0.72±0.05

9.24±0.97

oxidoreductase 8

Cellobiose hydrolase*

17

Conidial hydrophobin

+

3

8.08

31

34.8

Catalase B

gi|2493539

Y

Catalase

0.59±0.01

0.52±0.04

0.45±0

11

20

Isoamyl alcohol oxidase

gi|129556964

Y

FAD/FMN containing

1.57±0.2

1.41±0.04

1±0.07

dehydrogenase 6

34.1

Conidial hydrophobin

gi|66851317

Y

Hydrophobin

1.47±0.09

1.51±0.09

1.48±0.07

5

8.04

FAD-dependent oxidase

gi|66847480

Y

FAD binding domain

1.43±0.08

1.17±0.02

0.65±0.09

8

2.11

NADH-ubiquinone

gi|66853461

N

NA

0.71±0.01

0.83±0.08

4.26±0.69

oxidoreductase #

Proteins identified in this study which has also been identified in previous study Ref 24, *Proteins identified in this study which

has also been identified in previous study Ref 25, + Proteins identified in this study which has been identified in previous study Ref 28, NA=Not Available

Table 2. Comparison between iTRAQ quantified protein expression and mRNA expression. SN

Accession

Name

Abbr.

Relative Expression

1

gi|66850450

Exo-β-1,3-glucanase

Exg0

Protein expression

2

3

gi|66847805

gi|66847161

Endo-1,3-β-glucanase

α-1,3-glucanase/mutanase

Engl1

Mut

CCC:CT

0.81±0.05

WCC:CT

SCC:CT

0.81±0.01

0.55±0.01

mRNA expression

10.93±1.02

5±0.76

0.76±0.25

Protein expression

0.63±0.02

0.64±0.01

0.36±0

mRNA expression

56.22±5.45

6.27±1.06

1.08±0.48

Protein expression

0.76±0.02

0.77±0

0.55±0.01

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5

6

7

8

9

10

11

12

Journal of Proteome Research

gi|66848677

gi|66852496

gi|2493539

gi|66848203

gi|66852431

gi|66853445

gi|298351556

gi|66845978

gi|66847959

Cellobiose dehydrogenase

Exo-β-1,3-glucanase

Catalase

Exo-glc

Cat1

Enolase

Eno

α-mannosidase

α-man

Endo-arabinase

Earb

α-gal

α-galactosidase

Endo-1,3-β-glucosidase

β-glucosidase A

Cbd

Eglc

β-glc

mRNA expression

286.43±4.86

1.89±0.02

0.1±0.06

Protein expression

4.57±0.08

0.3±0.79

1.17±0.07

mRNA expression

81.48±10.04

0.89±0.01

0.3±0.04

Protein expression

1.25±0.11

1.46±0.23

0.72±0.06

mRNA expression

264.37±3.6

223.26±10.15

92.12±4.45

Protein expression

9.78±0.08

1.63±0.21

0.24±0.01

mRNA expression

276.4±1.91

10.64±0.02

16.6±0.21

Protein expression

1.03±0.03

0.96±0.06

2.1±0.2

mRNA expression

7.51±1.09

0.88±0.28

3.87±0.35

Protein expression

0.84±0.06

1.42±0.05

1.89±0.09

mRNA expression

15.05±3.98

2.7±0.91

0.01±0.54

Protein expression

0.6±0.03

0.59±0.01

0.77±0.02

mRNA expression

2.47±0.4

0.43±0.23

3.21±0.43

Protein expression

1.22±0.02

1.22±0.1

0.64±0.01

mRNA expression

12.51±2.67

0.24±0.06

6.53±0.17

Protein expression

1.82±0.15

1.63±0.09

1.21±0.06

mRNA expression

0±2.39

1±0.14

0.01±0.11

Protein expression

0.72±0.1

0.8±0.03

0.5±0

191.55±0

3.29±0

4.63±0.02

Protein expression

0.66±0.02

0.65±0.04

0.45±0.13

mRNA expression

45.99±0.3

188.72±1.1

15.93±1.52

Protein expression

0.62±0.12

0.59±0.13

0.49±0.01

mRNA expression

45.57±0.98

68.71±0.44

13.64±1.39

mRNA expression 13

14

gi|66850743

gi|66850626

β-glucosidase M

α/β-glucosidase

β-glcM

α/β−glc

37 ACS Paragon Plus Environment

Journal of Proteome Research

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For TOC only:

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Journal of Proteome Research

Figure 1 Scanning electronic microscopy (SEM) for samples grown in absence and presence of A. fumigatus. I, II, and III, SEM of samples CCC, WCC, and SCC respectively in absence of fungi shows the complex and compact nature of cellulosic carbon source. IV, V, and VI, SEM of samples for CCC, WCC, and SCC respectively cultured with fungi shows fungal growth on the surface degrading the compactness of carbon source. Bars: 20.0 µm for I, II, III, IV, V and VI. 103x133mm (300 x 300 DPI)

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Figure 2 SDS–PAGE and zymogram analysis of secreted protein. A, SDS-PAGE of protein secreted upon induction with CCC, WCC, SCC, and CT. B, SDS-PAGE of secreted protein performed in 12% gel incorporated with 0.2% CMC and 0.2% xylan: Lane 1: CCC; Lane 2: WCC; Lane 3: CT; Lane 4: SCC; M: marker.

99x61mm (300 x 300 DPI)

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Journal of Proteome Research

Figure 3 Enzyme activity of secreted cellulolytic enzymes under the influence of different carbon source. The cellulolytic activity of A. fumigatus enzyme vary according to the nature of different carbon source; CT, CCC, WCC, and SCC. The results are represented as the Mean±SD of three replicates.

61x47mm (300 x 300 DPI)

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Journal of Proteome Research

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Figure 4 Activities of extracellular cellulolytic enzymes in the secretome of A. fumigatus at different temperature and pH. \r\nThe activity of enzyme induced by CCC, WCC and SCC estimated at two different temperature; 39 οC and 50 οC and three different pH; 2.5, 6.8 and 9 was determined by DNS spectrophotometric assays. A, B, and C represents CMCase, xylanase, and pectinase enzyme activity respectively. The results are represented as the Mean ± SD of three replicates. \r\n 61x47mm (300 x 300 DPI)

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Journal of Proteome Research

Figure 5 Time dependent profiles of cellulolytic enzyme (cellulase, xylanase, and pectinase) production by A. fumigatus on different carbon sources. A, B, C and D, sequential induction of enzyme by different carbon source measured at different time interval for CT (A), CCC (B), WCC (C) and SCC (D) used as a sole carbon source for enzyme induction. The results are represented as the Mean±SD of three replicates.

61x47mm (300 x 300 DPI)

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Figure 6 Classification of iTRAQ identified proteins. A, Protein expression correlation of biological replicates of CCC, WCC, and SCC induced proteins with CT (galactose) induced protein. B, Distribution of proteins as a function of theoretically obtained molecular weight and isoelectric point. C, Functional classification of the iTRAQ quantified protein indicating the percentage of the protein in the category.

189x118mm (300 x 300 DPI)

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Journal of Proteome Research

Figure 7 Classification of iTRAQ identified protein based on the different families of protein. A, Overall classification of protein identified showing nearly half of the protein belonging to GH family. B, Classification of protein belonging GH family.

201x140mm (300 x 300 DPI)

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Journal of Proteome Research

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Figure 8 Relative expression of genes encoding cellulase, hemicellulase and β-glucosidase. I,II, and III, Relative gene expression analysis for cellulase, hemicellulase and β-glucosidase respectively, induced by A. fumigatus during growth on A (CCC), B (WCC), and C (SCC) estimated by RT-PCR.

215x166mm (300 x 300 DPI)

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