Proteomics Insights into the Biomass Hydrolysis Potentials of a

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PROTEOMICS INSIGHTS INTO THE BIOMASS HYDROLYSIS POTENTIALS OF A HYPERCELLULOLYTIC FUNGUS Penicillium funiculosum Funso Emmanuel Ogunmolu, Inderjeet Kaur, Mayank Gupta, Zeenat Bashir, Nandita Pasari, and Syed Shams Yazdani J. Proteome Res., Just Accepted Manuscript • DOI: 10.1021/acs.jproteome.5b00542 • Publication Date (Web): 20 Aug 2015 Downloaded from http://pubs.acs.org on August 21, 2015

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Journal of Proteome Research

PROTEOMICS INSIGHTS INTO THE BIOMASS HYDROLYSIS POTENTIALS OF A HYPERCELLULOLYTIC FUNGUS Penicillium funiculosum

Funso Emmanuel Ogunmolu1, Inderjeet Kaur2, Mayank Gupta1, Zeenat Bashir1, Nandita Pasari1, Syed Shams Yazdani1,3*

1

Synthetic Biology and Biofuels Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India

2

Malaria Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India

3

DBT-ICGEB Centre for Advanced Bioenergy Research, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India

* Corresponding author Address: Synthetic Biology and Biofuels Group, International Centre for Genetic Engineering and Biotechnology, Aruna Asaf Ali Marg, New Delhi, India. Email: [email protected]. Tel: +91-11-26742357.

1 ACS Paragon Plus Environment


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ABSTRACT

The quest for cheaper and better enzymes needed for the efficient hydrolysis of lignocellulosic biomass has placed filamentous fungi in the limelight for bioprospecting research. In our search for efficient biomass degraders, we identified a strain of Penicillium funiculosum whose secretome demonstrates high saccharification capabilities. Our probe into the secretome of the fungus through qualitative and label free quantitative mass spectrometry based proteomics studies revealed a high abundance of inducible CAZymes and several non-hydrolytic accessory proteins. The preferential association of these proteins and the attending differential biomass hydrolysis gives an insight into their interactions and clues about possible roles of novel hydrolytic and non- hydrolytic proteins in the synergistic deconstruction of lignocellulosic biomass. Our study thus provides the first comprehensive insight into the repertoire of proteins present in a high performing secretome of a hypercellulolytic Penicillium funiculosum, their relative abundance in the secretome and the interaction dynamics of the various protein groups in the secretome. The gleanings from the stoichiometry of these interactions hold a prospect as templates in the design of cost effective synthetic cocktails for the optimal hydrolysis of biomass.

KEYWORDS lignocellulosic biomass, saccharification, Penicillium funiculosum, secretome, quantitative mass spectrometry, CAZymes, non-hydrolytic accessory proteins


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INTRODUCTION The efficiency of filamentous fungi as key players in carbon recycling in nature has placed them in the spotlight as potential sources of enzymes for converting recalcitrant lignocellulosic materials into precursors for industrial purposes.1-4 With an estimated 5.1 million species5 they represent an unending pool for potential sources of cellulase producers with novel applications. The recent upward trend in the commercial launch of biorefineries that use lignocellulosic biomass as a source of sugars for ‘advanced biofuel’ production is a testament.6, 7 Several fungi have been reported with proven abilities to produce lignocellulosic enzymes1, 3, 4, 6, 8-17; with the mutant strains of the fungus Trichoderma reesei dominating the industrial arena as the workhorse for the production of cellulases.3, 9, 10, 13, 17-19 Recent insights about its genome however, have revealed an unexpectedly poor collection of genes and enzymes associated with biomass degradation when compared with other fungi having the ability to degrade biomass; underscoring the need to explore nature’s repository for alternatives and/or complements.3, 19-21 In addition, there are several reports of enzymes cocktails from different fungi outperforming enzyme preparations from T. reesei in the hydrolysis of biomass when applied at equal enzyme loadings, while some other reports complementary performance (synergism). An overview is presented in earlier reports.6, 8, 9, 13, 15

However, the main obstacle in designing cost effective lignocellulolytic enzyme cocktail is the lack of knowledge on total enzyme inventory and exact molar concentration of individual cellulolytic protein secreted by lignocellulose degrading microbial species.22 An understanding of the qualitative and quantitative composition of fungal secretome, the complex interactions of the various enzyme types and kinetic expression profiles will allow for the establishment of efficient in vitro lignocellulose utilization processes.23 Comprehending the 3 ACS Paragon Plus Environment


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enzymatic apparatus of cellulolytic strains, with a focus on achieving better efficiency thus, is a key biotechnological bottleneck to be overcome before the production of liquid biofuels from lignocellulosic biomass becomes a commercial reality.24, 25 In this regards, the mass spectrometric-based proteomic analysis of the secretome serves as a valuable tool in the discovery of new enzymes or interesting enzyme complexes associated with improved lignocellulose deconstruction.23,

26

While the advances in mass

spectrometry based proteomics machines and methods continually aids in elucidating the biological roles of protein players in several biological process,22 it focuses more on the description of carbohydrate active proteins

and accessory components involved in the

degradation of plant cell wall polysaccharides in cellulolytic fungi.24 24, 25 To this end, we conducted a search for efficient biomass hydrolyzing fungi from both natural environments as well as an Indian culture repository. Most of the fungi from the culture collection had been previously identified and designated as having potentials for the production of cellulases. However their classification had been based on the enzyme profiling and activities using cellulase monocomponents, but the performances on active biomass were hardly evaluated for majority of them. We thus evolved a strategy to incorporate the respective fungi performance on model substrates with observed activity on heterogeneous substrates and rank them accordingly using the weighted sum model (WSM). The WSM has been described as the best known and simplest multi-criteria decision making method for evaluating a number of alternatives in terms of a number of decision criteria.27, 28 Using shotgun proteomic strategy, we analyzed the secretome obtained from the most performing fungus to get an in depth understanding of the enzymes sets secreted by the fungus, their abundance as well as how they interact with each other to bring about effective biomass deconstruction.


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MATERIALS AND METHODS Collection and Identification of Potential Cellulolytic Fungi Potential cellulase degraders were sourced from actively decaying plant materials within the forested areas of the International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi – India campus. The respective fungi were isolated from the decaying plant materials using potato dextrose agar (Himedia, India) plates to which 0.5% Avicel (Sigma Aldrich, USA), 0.01% Trypan blue (Himedia, India) and chloramphenicol (Sigma Aldrich, USA) 100µg/mL were incorporated. The plates were buried within the actively decaying plant materials and retrieved after 4 days. Actively growing fungi were isolated from the retrieved plates in pure forms and subcultured on carboxymethyl cellulose (CMC)-Trypan blue agar plates containing soya peptone (24 g/L), KH2PO4 (5.9 g/L), (NH4)2SO4 (3.12 g/L), CaCl2.2H2O (0.05 g/L), yeast extract (0.05 g/L), Agar (15 g/L), Triton X-100 (0.01% v/v), Trypan blue (0.01% w/v) and CMC (0.5% w/v) at pH 5.5. The biomass degrading potentials of the strains were evaluated after 5 days incubation at 28 C based on the enzymatic index (EI) of the respective fungi. The enzymatic Index was calculated as a function of the fungus growth (diameter) in relation to the diameter of the observed clear zones (halos) on CMC-Trypan blue agar plate. Fungi exhibiting an enzymatic Index (EI) greater than or equal to one were noted as potential biomass degraders. In addition, filamentous fungi previously designated as potential cellulase producers were obtained from the culture repository of the National Collection of Industrial Microorganisms (NCIM), Pune – India. The classification of these fungal isolates as cellulase producers had been mostly based on the enzyme profiling and activity using cellulase monocomponents, but their performances on active biomass were hardly evaluated. A total of 26 fungi were obtained from NCIM, maintained on potato dextrose agar (PDA) and evaluated for its biomass degrading potentials.



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Culture Conditions and Supernatant Preparation On the basis of preliminary experiments in our laboratory, fungi obtained from the different sources were further cultivated in a cellulase inducing medium containing soya peptone (24 g/L), KH2PO4 (5.9 g/L), (NH4)2SO4 (3.12 g/L), CaCl2.2H2O (0.05 g/L), yeast extract (0.05 g/L), wheat bran (24 g/L) and Avicel (21.4 g/L); the final pH was adjusted to 5.5. The cellulase inducing medium in Erlenmeyer flasks were inoculated with four plugs (1 mm diameter) from the edge of the actively growing fungi respectively. The flasks were kept at 30 C for 6 days (optimal cellulase induction had been previously observed at this period of incubation) with orbital shaking at 150 rpm (Innova 44, Eppendorf AG – Germany).3 Induced cultures were centrifuged at 7,000 rpm for 10 min at 4 °C, and the supernatants were filtered using syringe filters with a 0.45-μm PVDF membrane (Millipore, Germany). For screening experiments, the filtered secretome were used for saccharification and enzyme assays. However, for subsequent evaluation of most performing secretome and proteomics experiments, the obtained secretome were concentrated using Vivaspin columns with a 5 kDa MWCO (GE Healthcare Life Sciences, India); then, culture media were replaced by citrate-phosphate buffer 50 mM, pH 5.20 The protein concentrations of the obtained secretome were determined by the Bicinchoninic acid (BCA) method using bovine serum albumin as a standard.29, 30

Evaluating Enzyme Activity Unless otherwise indicated, all enzymatic activities were measured in citrate–phosphate buffer (50 mM, pH 5.0) at 50 C. The activities of enzymes towards CMC, microcrystalline cellulose (Avicel PH-101) and Birchwood xylan, were measured by using the dinitrosalicylic acid 6 ACS Paragon Plus Environment

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(DNSA) method, as described before.21 Briefly, 30 µL of crude secretome were mixed with 100 µL of substrates at 1% concentration and incubated for 30 minutes. The reaction was terminated by the addition of DNSA reagent31, 32 and boiled for 10 min. The absorbance at 540 nm was measured relative to a glucose standard curve. One unit of enzyme activity was defined as the amount of protein that released 1 µmol of reducing sugar per min. β-glucosidase and βxylosidase, activities were assayed by monitoring the release of p-nitrophenol from pnitrophenyl-β-D-glucopyranoside (pNPG) and p-nitrophenyl-β-D-xylopyranoside (pNPX) respectively, as described by Ravalason et al.21 Briefly, 30 µL of enzymes were mixed with 100 µL of substrate (1 mM) and incubated for 20 min. The reaction was stopped by adding 130 µL of 1 M sodium carbonate (pH 11.5), and the release of 4-nitrophenol was quantified at 410 nm using a 4-nitrophenol standard curve. One unit of enzyme activity was defined as the amount of protein that released 1 µmol of p-nitrophenol per min. Lytic polysaccharide monooxygenases (LPMOs) activity were assayed using the method described by Kittl et al.33 Briefly, the reactions were performed in 100 mM sodium phosphate buffer, pH 6.0 at 22 °C. The reaction mixture comprised of 20 μL dilutions of LPMO source (enzyme) and 180μL assay solution which comprised 18 μL of 300 μM ascorbate (Sigma Aldrich), 18 μL of 500 μM Amplex Red (Sigma Aldrich), 18 μL of 71.4 units/ml HRP (Sigma Aldrich), 18 μL of 1 M sodium phosphate buffer pH 6.0 and 108 μL HPLC grade water. Resorufin fluorescence was taken at excitation wavelength of 530 nm and emission wavelength 580 nm after 10 minutes incubation using a multimode plate reader (Spectra Max M3, USA). In reference experiments without LPMO the background signal was measured and subtracted from the assays. A standard curve obtained with various dilutions of H2O2 was used for the calculation of an enzyme factor to convert the fluorimeter readout (counts min-1), into enzyme activity. LPMO activity is defined as one µmol H2O2 generated per minute under the defined assay conditions. Overall cellulase activity was determined using filter paper (FP) as described before.34, 35



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Rolled Whatman No. 1 filter paper strip (1.0 x 6.0 cm) was incubated with the appropriate enzyme solutions for 1 hour at 50 C. The reducing sugars released were measured using the dinitrosalicylic acid method31, 32 with glucose as the standard. One unit of filter paper activity was defined as the amount of protein that released 1 µmol of reducing sugar per min.

Saccharification Assays The crude secretome obtained from the fungi were evaluated for their biomass hydrolyzing capabilities. The biomass hydrolyzing potentials were measured in citrate–phosphate buffer (50 mM, pH 5.0) and at 50 C with orbital shaking at 150 rpm (Innova 44, Eppendorf AG – Germany). Wheat straw that had been subjected to sodium hydroxide and ammonium pretreatment (kindly provided by Prof. Arvid Lali [Lali AM, Varavadekar JS, Wadekar PC. Process for fractionation of biomass. 2010;PCT/IN2010/000634]) were used as substrates for the hydrolysis experiments respectively. The pre-treated straws were graded through a 0.5 mm mesh and stored at 4 C. Enzymatic hydrolysis were carried out in 1.2 mL capacity 96-wells deep ell plates (Tarson, India) sealed with adhesive PCR Plate Seals (Genetix, India) to prevent evaporation. The reaction mixture included the pre-treated wheat straws at 5% dry weight loading in a 250 µL final reaction volume containing the appropriate enzyme dilutions of the enzymes. The hydrolysis was carried out for 6 hours. Control experiments were carried out under the same conditions using substrates without enzymes (enzyme blank) and enzymes without substrates (substrate blank) - a substrate-free negative control was set up by filling wells with 50 mM citrate-phosphate buffer, pH 4.8, and the background of soluble sugars present in the wheat straw sample was determined by incubating wheat straw in the absence of enzyme.3 All assays were carried out in triplicate. The concentration of reducing sugars in the hydrolysates was analyzed with the dinitrosalicylic acid method3, 32 using glucose as a standard. 8 ACS Paragon Plus Environment

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In the initial screening experiments, the addition of fungal secretomes were not normalized on the basis of the protein loading since differences in the amount of total protein secreted by fungal strains from natural sources had been previously observed and reported.3 Moreover, since our objective was to identify fungi strains that secretes active biomass hydrolyzing cocktails in copious amounts. The biomass hydrolyzing potential of the most performing fungal strain was evaluated with respect to a commercial enzyme - Advanced enzyme formulation (AETL) (India). The conditions were as described above except that enzyme loading was normalized based on filter paper units (FPU) and the hydrolysis allowed for 36 hours with the concentration of reducing sugar in the hydrolysate determined at the interval of every 6 hour. Ranking of Fungi Strains for Biomass Hydrolysis To rank our fungi strains on their suitability as potential sources for biomass hydrolyzing enzymes, we employed the weighted sum model (WSM) algorithm. The WSM, being a multicriteria decision analysis tool, considers a set of alternatives M and relevant criteria N and identifies the best alternative using the following expression:

Where (AiWSM-score) = the WSM score of the best alternative, N = the number of criteria, aij = the actual value of the ith alternative in terms of the jth criterion, wj = the weight of the importance of the jth criterion.28, 36-38 To implement the WSM in our experiment, we used the performance of the different fungal crude enzymes on different model substrates-CMC, Avicel PH-101 and pNPG as the base criteria (N) for arriving at the weighted sums for the different pre-treated wheat straw tested. A relative weight (w) was assigned to the respective criterion based on the Pearson Correlation coefficients between the criteria.37 The performance of



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different fungal crude enzymes on pre-treated wheat straw was assigned a maximum score of one. The obtained scores for each criterion (including model substrates and pre-treated biomass) were summed up as the weighted sum for each fungus.

Molecular Identification of Cellulase Positive Strains Genomic DNA was extracted from 5-7 day old fungal colony grown on PDA plates using the Nucleopore gDNA isolation kit and stored at −20°C. PCR was performed using standard procedures.3, 39, 40 In brief, amplification of the ITS regions of nuclear ribosomal RNA gene was achieved using primers ITS1 (5′-TCCGTAGGTGAACCTTGCGG-3′) and ITS4 (5′TCCTCCGCTTATTGATATGC-3′) with the genomic DNA as template.41 The corresponding ITS region was amplified from approximately 50 ng genomic DNA in 50µL PCR reaction containing 200 nM primers, 200 nM dNTPs and 1 U Phusion® High-Fidelity (Thermo Scientific®, USA). The PCR reaction was carried out in a Biorad PCR system (Biorad, USA), using 30 cycles of denaturation at 98 °C for 15 seconds, annealing at 57 °C for 30 seconds, and extension at 72 °C for 25 seconds, with a final extension step at 72 °C for 2 minutes. PCR products were analysed by electrophoresis in 1% (w/v) agarose (Sigma Aldrich) gels at 80V. The PCR products were purified using the NucleoSpin® Gel and PCR Clean-up kit (Clontech Inc). The sequencing of the purified products were carried out with a high throughput Applied Biosystems 3730XL Sequencers (Macrogen Inc, Seoul, Korea). The nucleotide sequences obtained were curated manually and final consensus sequence was subjected to pairwise similarity search against multiple fungi databases through the BioloMICS software42,

43

accessible from “The CBS Fungal Biodiversity Centre” web resources for fungal taxonomy http://www.cbs.knaw.nl/Collections/BioloMICSSequences.aspx.


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SDS-PAGE Analysis Sodium dodecyl sulfate (SDS)-polyacrylamide gels (12 %) were prepared and proteins obtained following the culture supernatant preparation were separated via SDSpolyacrylamide gel electrophoresis (PAGE) as described before 44. Mini-PROTEAN Tetra Cell (Bio-Rad) with gel size of 8.6 x 6.7 cm was used for protein separation under denaturing condition. Proteins of the gel were stained with Coomassie blue R-250 (Sigma Aldrich, USA).45 The molecular mass under denaturing conditions was determined with reference standard proteins (Thermo Scientific, USA).

Protein Preparation for LC-MS/MS Analysis One hundred micrograms of total protein from the most performing strain was separated by one dimensional (1D) electrophoresis prepared and stained as described above. The 1D electrophoresis lane was cut into 15 pieces based on the protein banding pattern ( Supporting Information Figure S-1). Each fraction was further diced into 1 mm by 1 mm cubes and transferred into 1.5 mL microfuge tubes. In-gel digestion was carried out according to Shevchenko et al.46 Gel pieces were first destained with 100 mM ammonium bicarbonate/acetonitrile (1:1 vol/vol), followed by addition of 50 μl of 10mM dithiothréitol (Sigma Aldrich, USA) and incubation at 56 °C for 45 minutes. After cooling, the supernatant was removed, and the samples were alkylated in the presence of 50 μl of 55 mM iodoacetamide at room temperature in the dark for 30 minutes. Gel pieces were washed with 100 mM ammonium bicarbonate/acetonitrile (1:1, vol/vol) for 15minutes after which enough acetonitrile was added to cover the gel particles. The gels were then dried in a vacuum speed concentrator (Thermo fisher, USA). In-gel digestion was performed overnight with 200ng of trypsin gold – mass spectrometry grade (Promega, USA). The resulting peptides were extracted 11 ACS Paragon Plus Environment


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twice with 50% acetonitrile in 0.1% formic acid for 20 minutes followed by 70% acetonitrile in 0.1% formic acid for 20 minutes. These two peptide extracts were pooled, dried in a vacuum speed concentrator. Dried peptides from each fraction were dissolved in 0.1% formic acid.

Data Acquisition All experiments were performed on an Orbitrap Velos Pro equipped with nano-LC Easy nLC1000 (Thermo Fischer Scientific, USA). For liquid chromatography, separation was performed with a flow rate of 300 nl/min on a C-18 pre-column (Acclaim PepMap, 75 μm x 2 cm, 3μm, 100A0, Thermofisher Scientific Incorporation) followed by analytical column (Acclaim PepMap, 50 μm x 15 cm, 2μm, 100A0). The peptides were separated using a gradient of 5% solvent B to 35% B in 25 min followed by sharp increase to 90%, then retention of 90% for 3 min followed by 5 % aqueous phase for 5 min. Solvent A was aqueous solution in 0.1% formic acid, and solvent B was 100% acetonitrile in 0.1% formic acid. The eluted peptides were injected into the mass spectrometer and the MS1 data were acquired in full scan mode at 60000 resolution with mass range from 350-2000Da. Data were acquired using the Xcalibur software package. Top 20 precursors were allowed to fragment using CID (collision induced dissociation) in Ion trap with collision energy of 35 in a data dependent acquisition. Chargestate screening of precursor ions and monoisotopic precursor selection was enabled. The unassigned charge and single charged precursors were rejected (not allowed to fragment). The parent ions once fragmented were excluded for 40 secs with exclusion mass width of ± 10ppm. The lock mass option (polydimethylcyclosiloxane; m/z 445.120025) enabled accurate mass measurement in the MS mode.40


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Evaluating Protein Interaction Dynamics in Penicillium funiculosum by Non-denaturing Size Exclusion Chromatography and Mass Spectrometry Based Quantitative Proteomics (SEC-MS) To separate the crude Penicillium funiculosum into its natural associating partners, crude secretome (20 mg) prepared as described above was loaded in a HiLoad 16/600 Superdex 200pg pre-packed XK columns (GE Healthcare Life Sciences, India) using a NGC™ MediumPressure Chromatography System (BioRad, USA). Absorbance was monitored at 280 nm. Elution was performed with 50mM sodium acetate buffer PH 5.0 containing 150 mM NaCl at an optimal flow rate of 0.5 ml/min. Protein from the individual fractions were subjected to SDS-PAGE as described above but were silver stained. Based on the observed protein banding pattern sub fractions were pooled into five groups (pools A to E). Protein from pooled fractions were concentrated using Vivaspin columns with a 5 kDa MWCO (GE Healthcare Life Sciences, India) and were subsequently run on12% Laemmli SDS-PAGE and stained with coomassie Blue R-250. The relative concentration of proteins in the pooled fractions was also determined using the BCA method.29, 30 About 20 µg of protein from each pool were reduced and alkylated followed by a subsequent acetone precipitation. The obtained pellets were resuspended in 50 mM NH4HCO3 and trypsin digested in-solution. 47 The resulting peptides were extracted and treated as described above for MS/MS analysis. The other portions of the protein pools were used for biomass hydrolysis/saccharification. The apparent molecular mass of the fractions was estimated by gel filtration on the same column as described above calibrated with a GE Healthcare high-molecular-weight (HMW) gel filtration calibration kit (GE Healthcare). The molecular mass of standards used were ovalbumin (44 kDa), conalbumin (75 kDa), aldolase (158 kDa), ferritin (440 kDa) and blue dextran (2,000 kDa). Other portion of the pools were evaluated for their biomass saccharification potential with respect to the saccharification potential of the crude secretome The total reducing sugar concentration were determined as 13 ACS Paragon Plus Environment


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described in the biomass saccharification section above. The biomass hydrolysis efficiency of the pools was expressed as a percentage of total hydrolysis by the crude P. funiculosum secretome.

Data Analysis Raw MS data files obtained from the mass spectrometer were processed in parallel with two different

data

processing

pipelines

viz:

SearchGUI/PeptideShaker48,

49

and

Maxquant/Andromeda.50 The SearchGUI/PeptideShaker was used for processing the 1DLCMS/MS samples because of the ease of downstream processing of obtained results. The Maxquant/Andromeda was employed in the quantitation of relative protein abundance across SEC fraction pools since this pipeline is an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. In the SearchGUI/PeptideShaker, Peak lists obtained from MS/MS spectra were identified using, X!Tandem version X! Tandem Sledgehammer (2013.09.01.1),51 MS Amanda version 1.0.0.325352 and MS-GF+ version Beta (v10024).53 The search was conducted using SearchGUI version 1.23.2.48 Protein identification was conducted against a concatenated target/decoy54 version of the in house predicted proteins (11213 target sequences) obtained from the draft genome sequence of Penicillium funiculosum (unpublished work), together with contaminant database from ftp://ftp.thegpm.org/fasta/cRAP. The decoy sequences were created by reversing the target sequences in SearchGUI. The identification settings were as follows: trypsin with a maximum of 2 missed cleavages; 20 ppm as MS1 and 0.6 Da as MS2 tolerances; fixed modifications: carbamidomethyl c (+57.021464Da), variable modifications: oxidation of m (+15.994915Da), acetylation of protein n-term (+42.010565Da), pyro-cmc (+17.026549Da), pyro-glu from n-term e (+18.010565Da) and pyro-glu from n-term q 14 ACS Paragon Plus Environment

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(+17.026549Da). Peptides and proteins were inferred from the spectrum identification results using PeptideShaker version 0.36.2.49 Peptide Spectrum Matches (PSMs), peptides and proteins were validated at a 1.0% False Discovery Rate (FDR) estimated using the decoy hit distribution. Post-translational modification localizations were scored using the D-score55 as implemented in the compomics-utilities package.56 Spectrum counting abundance indexes were estimated using the Normalized Spectrum Abundance Factor adapted for better handling of protein inference issues and peptide detectability. For the Maxquant workflow, raw MS data files were processed by MaxQuant 1.5.2.8 for peak detection and quantification. MS/MS spectra were searched against the same set of target and decoy databases as described for SearchGUI/PeptideShaker using the Andromeda search engine.50 Proteases, variable and fixed modifications were specified as above. Mass accuracy of the precursor ions was determined by the time-dependent recalibration algorithm of Maxquant, and fragment ion mass tolerance was set to of 0.6 Da and 20 ppm. Peptide Spectrum Matches (PSMs), peptides and proteins were validated at a 1.0% False Discovery Rate (FDR). Protein abundance was estimated and normalised using the iBAQ approach (intensity based absolute protein quantification) as described earlier.57 The displayed protein abundance values were log10 transformed.57 The relative protein abundance estimation including normalization, hierarchical cluster analysis, scatter plots were performed using Perseus version 1.5.1.6 available with MaxQuant. Venn representation of protein pools was done using http://bioinformatics.psb.ugent.be/webtools/Venn/ Function

assignment

and

annotation

by

gene

ontology

terms

(GO;

www.geneontology.org), InterPro terms (InterProScan, EBI), enzyme classification codes (EC), and metabolic pathways (KEGG, Kyoto Encyclopedia of Genes and Genomes) were determined using the Blast2GO software suite.58 For each query sequence the software first detects up to 20 homolog sequences in the nrNCBI database accessed in December 2014 with 15 ACS Paragon Plus Environment


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a minimum expectation value of 1×10−25 and a high scoring segment pair cut-off of 33. The search was restricted to the fungi taxonomy (taxid 4751). Annotations were made with default parameters and were augmented by using the Annotation Expander (ANNEX) and by addition of the GO terms associated with functional domains derived from scanning the InterPro database.59 For sequences retuned without any significant hits, putative functions were inferred using protein similarity through transitivity clustering.60, 61 Protein networks were visualized in Cytoscape.62 Carbohydrate and auxiliary-active enzyme families were assigned using the CAZy database (http://ww.cazy.org).63

RESULTS AND DISCUSSION Identification of Penicillium funiculosum (NCIM1228) as a fungus with promising potentials for biomass hydrolysis The quest for cheaper and better enzymes needed for the efficient hydrolysis of lignocellulosic biomass has placed fungi in the limelight for bioprospecting research, either for the discovery of novel fungi and/or fungal enzymes. 8, 64 In our bid to identify fungi with promising potentials for industrial production of biomass hydrolyzing enzymes, we evaluated some previously unexplored natural fungal isolates as well fungi designated as cellulase producers from National Collection of Industrial Microorganisms (NCIM – India) (Supporting Information Table S-1). With our screening strategy that incorporated their respective performance on model substrates, i.e., CMC, pNPG and Avicel, as well as heterogeneous substrates, i.e., ammonium and sodium hydroxide pre-treated wheat straw (Supporting Information Figure S2), we observed a positive correlation between enzyme performance on model substrates and biomass (Table 1). The crude enzyme activities on amorphous/soluble substrates (CMC/pNPG) 16 ACS Paragon Plus Environment

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however, were weakly correlated in comparison to crystalline substrate (Avicel) (Supporting Information Figure S-2; Table 1). This is consistent with previous reports,65-67 indicating the insufficiency of using “amorphous model” substrates in predicting hydrolytic performance on heterogeneous lignocellulosic materials. While cellobiohydrolase as well as β-glucosidase activities were reported16 to be correlated to overall saccharification of AFEX-SG (Ammonia Fiber Exploded Switch Grass), IL-SG (Ionic Liquid pre-treated Switch Grass), and dilute-acid pre-treated switch grass; we only observed the confirmation of the former from our data on pre-treated biomass (Table 1) . Our data instead conformed to earlier report by Gao et al68 in which the order of importance of core cellulases with respect to overall biomass saccharification can be surmised to be cellobiohydrolase>endoglucanase> β-glucosidase. We thus suggest that higher priority be assigned to the role of cellobiohydrolases in the bioprospecting for better biomass hydrolyzing enzymes from cellulase producing fungi. Using the various performances as inputs, a weighted sum score (AiWSM-score) was generated for the respective fungi to model their performances on both ammonia and sodium hydroxide treated wheat straw (Table 2). The weighted sum model (WSM) has been described as the best known and simplest multi-criteria decision making method for evaluating a number of alternatives in terms of a number of decision criteria.27,

28

From Table 2, the fungus

Penicillium funiculosum ranked highest with an average weighted sum score of 59.80. Our reevaluation of the strain’s identity through its internal transcribed spacer (ITS1-5.8S-ITS2) region sequences revealed 100% similarity to ITS1-5.8S-ITS2 sequences from Penicillium pinophilum, P. allahabadense, Acremonium cellulolyticus, Talaromyces pinophilus, T. cellulolyticus and T. verruculosus (Supporting Information Table S-2). This is not surprising as P. funiculosum had earlier been described as a complex encompassing many sub taxa including P. pinophilum and P. allahabadense,69 and the genus Talaromyces is reported to be a sexual state of the genus Penicillium.39, 70 While the internal transcribed spacer (ITS) region 17 ACS Paragon Plus Environment


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has been said to have the highest probability of successful identification for the broadest range of fungi and proposed as the standard barcode for fungi,71 many reports however proposed the incorporation of β-tubulin (BenA) region as a secondary molecular marker to the accepted ITS barcode for fungi.39, 70, 72 We thus upheld the culture collection centre designation of the strain till in depth taxonomic studies and re-classification is done.

Evaluation of Biomass Saccharification and the Lignocellulolytic Enzyme Activities of Penicillium funiculosum Secretome Produced during Submerged Cultivation To further ascertain the biomass hydrolyzing capability of the strain, we compared the efficiency of the crude enzyme obtained under our cellulase inducing conditions with that of a commercial cellulase preparation both at low enzyme and high enzyme loading. Our protein loading was normalized based on the filter paper units of the respective enzyme. P. funiculosum secretome saccharification activities out performs that of the commercial enzymatic mixture both on sodium hydroxide and ammonium pre-treated wheat straws at 50 °C (Figure 1). Previously reported works on this strain73-75 as well as some other closely related species from the same genus9, 10, 76-90 confirmed our observation describing it as an excellent source of biomass degrading enzymes; with capabilities exceeding that of Trichoderma reesei which has been the hub for most commercial cellulase preparation.3, 8-11, 14, 64 A closer look at the cellulase (endoglucanase, cellobiohydrolase, β-glucosidase), hemicellulase (xylanase, β-xylosidase) and polysaccharide monoxygenase (AA9) activities of the fungus’ secretome in relation to the commercial enzyme (Table 3) revealed a significantly higher cellobiohydrolase, β-glucosidase and LPMO activities per mg of protein produced by the fungus; while the commercial enzyme cocktail showed a significantly higher endoglucanase, β-xylosidase and endoxylanase activities per mg of protein. Reports of exo-acting cellulases, β-glucosidase and LPMO being critical for 18 ACS Paragon Plus Environment

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efficient saccharification of biomass are well documented.6, 9, 10, 14, 16, 68 In the review articles,9, 10

author(s) also associated the superiority of cellulase preparations from Penicillium sp with a

higher level of β-glucosidase, higher specific activity of family 7 cellobiohydrolases (CBHI), less inhibition of Penicillium CBHI activity to inhibitors and reduced affinity of Penicillium cellulases for lignin thus making them less susceptible to inhibition by lignin-derived compounds. This tends to explain the observed performance of the fungus’ secretome on sodium hydroxide and ammonium pre-treated biomass.

Overview of Penicillium funiculosum (NCIM 1228) secretome Secretome analysis, apart from being an excellent method to understand the biological mechanisms of lignocellulose degradation, is a valuable tool in the search for new enzymes or interesting enzyme complexes in the biofuels field.26 In our quest to understand the repertoire of proteins in the “most performing” secretome of the fungus Penicillium funiculosum NCIM1228 and their relative abundance, we undertook a proteomic study comparing the obtained mass spectrometry spectra against an in house predicted proteins (11213 target sequences) obtained from the draft genome sequence of the fungus available in our laboratory. These analyses led to the identification of 195 proteins, validated at 1% FDR (Supporting Information Table S-3). When we compared the numbers of proteins validated in the secretome of P. funiculosum with those reported in the literature for other cellulolytic fungi of the genera Podospora20, Fusarium21, Aspergillus91, Trichoderma22, 40, 92, 93 among others; we observed the moderate induction of proteins in the secretome of P. funiculosum. However, cellulase preparations from the genus Penicillium have been reported to outperform preparations from Trichoderma and other fungi9, 10. It is also noteworthy to mention that the numbers of proteins we identified were significantly higher than the number reported in the previous report79 where 19 ACS Paragon Plus Environment


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only 50 proteins were unambiguously identified in Rovabio™ (a commercial cocktail from Penicillium funiculosum). We were able to confidently identify more proteins from our secretome experiments because our acquired mass spectra were queried against predicted proteins from the draft genome sequence of the strain available in our laboratory, while previous report79 inferred the protein identity through homology search with public fungi database. The high number of detected proteins could be also attributable to the possibly higher induction of a large subset of enzymes during cultivation as well as the sensitivity of the mass spectrometer used.40 We used Blast2GO suite to assign functions to our identified protein.58 Most of the functions were assigned from the genus Talaromyces (Figure 2, Supporting Information Table S-3) which is the sexual state of Penicillium.39 However in instances where certain proteins were described as hypothetical protein, putative functions were assigned through pairwise similarity function between identified proteins. This was done through a method developed earlier to partition biological data into groups of similar objects through Transitivity Clustering.60, 61 Utilizing the tool, we were able to assign putative functions to twelve hypothetical proteins (Table 4). Our results showed that the molecular weights of all the identified proteins were in the range of 11–150 kDa, with the exception of a putative histone acetylase complex subunit Paf400 showing a molecular weight of 439 kDa, while most of the carbohydrate active proteins were with pI within the acidic range (Supporting Information Table S-3, Figure 3). Of the validated proteins, only 38% were confirmed to have N-terminal Sec-dependent secretion secretory signals in silico. In their work with Trichoderma reesei RUTC30 and Trichoderma asperellum, Marx et al40 observed a similar trend with only 39% of total proteins detected having N-terminal Sec-dependent secretory signals. The authors suggested that this could be as a result of cell lysis, cell death or protein having non-classic secretory mechanisms. Functional categorization of the validated proteins based on CAZy database63 however indicated that 58% of the total proteins (113 proteins) can be described as


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CAZymes out of which 47% (92 proteins representing 38 families) were identified as glycoside hydrolases, 6% (11 proteins representing 5 families) as performing auxiliary activities, 4% (7 proteins representing 6 families) as carbohydrate esterases and a 1% (3 proteins representing only the PL1 family) as polysaccharide lyases (Figure 2). Other non-CAZymes identified include proteins involved in carbohydrate binding (2%), amino acid metabolism or proteolysis (15%), oxidases with other functions (6%), hypothetical or proteins with other functions (19%) (Figure 2, Supporting Information Table S-4). A comparative evaluation of all possible CAZymes from the draft genome sequence as against those we detected in the secretome of Penicillium funiculosum is presented in (Figure 4). Although only 20% of the possible CAZymes were detected through our proteomic experiment, we however noted that proteins belonging to the class copper-dependent lytic polysaccharide monooxygenases (LPMOs) AA9, cellobiohydrolase II - GH6, cellobiohydrolase I and endoglucanase GH7, xylanase GH10, β-hexosaminidase GH20, endo-β-1,4-galactanase - GH53, α-L-arabinofuranosidase GH62, α-trehalase - GH65, β-glucuronyl hydrolase - GH88 and pectin lyase - PL1 present were identified in the secretome at 100% of the possible magnitude in the genome of the fungus (Supporting Information Table S-5). Other identified proteins at an upward of 40% of the possible proteins in the genome included: lignin peroxidase - AA2, acetyl xylan esterase – CE2, β-glucosidase and β-xylosidase – GH3, β-mannosidase and endoglucanase – GH5, xylanase – GH11, endoglucanase – GH12, α-galactosidase – GH27, glucosylceramidase - GH30, βgalactosidase – GH35, α-glucuronidase – GH67, α-1,3-glucanase – GH71, β-1,3glucanosyltransglycosylase – GH72, α-mannosidase – GH92 and a hypothetical protein of the class GH79. Many of the identified glycoside hydrolases possessed additional carbohydrate binding modules (CBMs) belonging to 8 different families (Supporting Information Table S4). The identified CBMs can be grouped into Type A CBMs (predominantly CBM1 which acts on crystalline cellulose) and type B (CBMs from families 6, 18, 20, 24, 42, 43 and 46 which



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acts linear oligosaccharide chains in the less crystalline region of cellulose).15,

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63

CBMs

increase cellulase concentration on the surface of the insoluble substrate, recognize the specific site in the substrates, and induce cellulose disruption, all of which facilitate cellulase catalytic activity.15 These arrays of core cellulases, hemicelluases as well as accessory enzymes detected in our “most performing secretome” could possible explain the observed excellent biomass hydrolysis from the fungus. Interestingly, most of the detected proteins have been reported to be the major players in biomass hydrolysis.6, 9, 10, 14, 16, 68, 94, 95 Of notable point to be mentioned is the detection of LPMOs (formerly GH61) belonging to the AA9 family and the confirmation of such through enzyme assay.33 A cellobiose dehydrogenase (CDH) of the CAZy family AA3 was equally detected in the secretome. This could possibly be the possible synergistic partner (electron donor) for the AA9 protein.33, 96 We found that our strain possess 25 genes encoding proteins of the class AA3 but only one gene encoding AA9 protein. In general, the CDH/PMO system helps to improve the degradation of cellulose in combination with cellulases.14, 33, 97 The diversity of enzymes related to biomass hydrolysis detected in our “most performing secretome” gives credence to the axiom that complex substrates lead to the induction of more complex lignocellulolytic cocktails.40, 98

Quantitative analysis of Carbohydrate Active Proteins in the secretome of Penicillium funiculosum To gain an insight into the relative abundance of the respective proteins present in the “most performing” secretome, spectrum abundance indexes were estimated using the Normalized Spectrum Abundance Factor (NSAF).49 A list of 21 identified proteins representing approximately 60% of the crude secretome and ranked based on their spectrum abundance is shown in Table 5. Our result shows the preponderance of cellobiohydrolase 1 (CBH1) and


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cellobiohydrolase II (CBH II) belonging to the GH7 and GH6 families respectively. This predominance of cellobiohydrolases is similar to reports from Trichoderma reesei strains although the proportions are at lesser magnitudes.9 We however noted that while CBHs typically represent up to 90–95% of the total secreted protein in Trichoderma reesei with CBH1 making up 50–60% and CBH II approx. 20% of the total cellulases,9 we only observed a cumulative CBHs abundance totaling 15% with CBH1 approx. 10% and CBHII 5% of the identified proteins. CBH1 from Penicillium species are known to have higher specificity as well as more resistant to inhibition by cellobiose.9,

10

This could suggest why they were

produced at lesser magnitudes. There equally could be the presence of other enzymes working in tandem with the CBHs to synergistically deconstruct biomass. In our experiment, other highly abundant classes of enzymes making up the approximately 60% of total proteins include: endoglucanases (GH5, 7, 12 & 17), β-glucosidase (GH3), endoxylanases (GH10, GH11), glucoamylase (GH15), extracellular cell wall glucanase (GH16), arabinofuranosidase (GH62), lytic polysaccharide monooxygenase (AA9), ferulic acid esterase (CE1), swolleninlike proteins, hydrophobic surface binding-like protein (HsbA) and immunoglobulin E binding protein. It is worth stating that non-hydrolytic accessory proteins such as swollenin-like proteins, hydrophobic surface binding-like protein (HsbA) and immunoglobulin E binding proteins make up about 10% of the total secreted proteins. Their high abundance could point to their role in biomass hydrolysis by Penicillium funiculosum. The synergism between cellulases and/or other enzymes for complete lignocellulose hydrolysis is well documented.6, 8, 12, 14, 15, 67, 95

Swollenin shows disruptive activity toward various cellulosic substrates,

presumably through their ability to disrupt hydrogen bonds, thereby reducing cellulose crystallinity and increasing cellulase accessibility,6, 15, 99 while HsbA is involved in the sensing of, or physical association with, hydrophobic surfaces and promotion of substrate degradation.98 In Aspergillus oryzae, Ohtaki et al100 showed that HsbA gets adsorbed to



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hydrophobic surfaces such as – Polybutylene succinate-co-adipate (PBSA) in the presence of NaCl or CaCl2 and promotes its degradation via a cutin-degrading esterase (CutL1 polyesterase). We suggest it could be performing similar function(s) in Penicillium funiculosum, mediating degradation via recruiting hydrolases to the surface of lignocellulosic biomass.

Evaluating Protein Interaction Dynamics in Penicillium funiculosum Secretome by NonDenaturing Size Exclusion Chromatography and Mass Spectrometry Based Quantitative Proteomics (SEC-MS) The secretion in large quantities of varieties of carbohydrate active proteins has been one of the reasons while filamentous fungi have been in the mainstay of cellulase research.64 Having validated a total of 195 proteins of which a greater proportion have carbohydrate-related functions (Figure 2), our interest was to understand the protein interaction dynamics in the secretome of P. funiculosum. We intended to enrich for “useful vs junk proteins” that could potentiate improved biomass saccharification. To this end, we subjected the crude secretome through a non-denaturing size exclusion chromatography (Figure 5). Size-exclusion chromatography (SEC) being a well-established technique used to separate proteins and protein complexes in solution on the basis of their rotational cross section

and size; offers a

comparative advantage of understanding and characterizing soluble protein dynamics in their native conformation and on a system-wide scale when coupled with downstream mass spectrometry.101-103 In our experiments, fractions eluting after 83 mL were subjected to a reducing SDS-PAGE and silver stained (Supporting Information Figure S-3). Our results showed that the majority of proteins in the crude secretome of P. funiculosum eluted over a broad range between 90 mL to 130 mL, which literally could translate to the predominance of


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low molecular weight proteins in the secretome when compared to the elution volume of the molecular weight standards. However the protein profile/banding pattern revealed by SDSPAGE indicates the presence of multiple proteins with molecular weight ranging from approx. 10 kDa to 130 kDa. While size exclusion chromatography have been used to estimate the relative size of individual proteins and / or complexes,101, 104, 105 the molecular weights of glycoproteins or non-globular proteins may not correlate well to the calibration curves established for globular proteins by the Calibration Kit proteins. However, these standards provide a general size indication.101 When proteins interacts to form multimers, their sizes and shapes are altered and this affect their migration pattern during size exclusion chromatography.101 In addition, the possibility of protein-resin interactions cannot be ruled out as the gel filtration medium (Superdex) is made from carbohydrate, and our crude enzyme being rich in carbohydrate-binding proteins could be interacting with the resin. To this end, we pooled sub-fractions showing similar banding pattern on reducing SDS-PAGE together into five pools viz: A to E (Figure 5) for downstream quantitative proteomics investigations and biomass hydrolysis. For proteomic investigations, the resulting pools were digested with trypsin, and then the peptides analyzed via LC-MS/MS. The MS data files were analyzed and peptides associated with each fraction identified and quantitated using MaxQuant.50 The relative protein abundance in each of the sub-fraction pools were estimated and normalised using the iBAQ approach (see “Materials and Methods”). A total of 86 unique proteins were validated at 1% FDR by MaxQuant across the protein pools of which 31, 40, 29, 17 and 13 proteins were exclusively associated with protein pools A to E, respectively. The list of proteins identified and their relative abundance are shown in Supporting Information Table S-6. An overview of the protein distribution and network across the respective groups is shown in Supporting Information Table S-7, Figure 6 and 7. We observed that the different proteins present in the respective 25 ACS Paragon Plus Environment


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pools tend to differentially associate with each other with some proteins being represented in more than one contiguous protein pool. For instance, cellobiohydrolase 1 (GH7-CBM1) was found across the protein pools A to E. Swollenin was found in pools A to D, cellobiohydrolase II (GH6 –CBM1) found in pools B, C, D and E; beta-glucosidase (GH1) & glucoamylase (GH15-CBM20) present in pools A, B & C;

beta-glucosidase (GH3) & alpha-L-

arabinofuranosidase (GH54-CBM42) present in pools B, C & D and endoglucanase GH5CBM1, beta-1,4-xylanase GH10-CBM1 and endoglucanase GH45 present in pools C, D & E. A hierarchical clustering to give a visual representation of the distribution and the relative abundance of the various detected proteins across the pools is given in Figure 8. The detection of a protein across multiple pools suggests they differentially associate with multiple proteins. In evaluating the interaction dynamics of the human interactome when stimulated with epidermal growth factor (EGF) using SEC coupled with mass spectrometry, Kristensen et al102 noted that proteins frequently participate in more than one complex or in similar complexes with different stoichiometries. This is similar to what we observed with the different stoichiometries of the different proteins occurring across the multiple pools (Figure 8 and 9). While SEC is expected to give a continuum of proteins with regular molecular weight pattern in adjacent pools, we observed the exclusive co-elution of certain low molecular weight proteins less than 20 kDa in Pool B, C and D but conspicuously missing in Pool E where they should have naturally eluted based on their low molecular weight (Figure 5b, 7 and 8). This suggests certain proteins are interacting with some other proteins in the pool. Of a seemingly interest is the presence of certain low molecular weight proteins – IgE-binding like protein (18kDa) and Hydrophobic surface binding protein A (HsbA) (17kDa) exclusively co-eluting with other higher molecular weight proteins in pool C. Their relative abundance and exclusive co-elution in Pool C where we observed the highest percentage of sugar release (Figure 10) gives credence to our earlier suggestion that they could be enhancing the deconstruction of


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biomass through synergy with core cellulases. This is of great importance when the stoichiometries of proteins in the different fraction pools are put in perspective.22 It will be interesting to further characterize these proteins and identify their interacting partners.

CONCLUSION In summary, we report the discovery through an integrated screening strategy of a promising Penicillium funiculosum strain with great potentials for the production of enzymes relevant for the efficient degradation of lignocellulosic biomass. While reports on the biomass hydrolyzing efficacy of the fungus and related species abounds in the literature, there is a paucity of information on the arrays of enzymes associated with such observation. Our study thus provides the first comprehensive insight into the repertoire of proteins present in a high performing secretome of Penicillium funiculosum and their relative abundance in the secretome. The preponderance of inducible CAZymes as well non-hydrolytic accessory proteins in the fungus secretome reiterates the concept of synergism between proteins for effective hydrolysis of lignocellulosic biomass. In addition, the preferential association of certain proteins and the attending differential biomass hydrolysis gives an insight into the concept of protein-protein interaction as well as clues about non-hydrolytic proteins from the fungus with possible roles in the synergistic deconstruction of lignocellulosic biomass. The gleanings from the stoichiometry of these interactions holds a prospect as templates in the design of cost effective synthetic cocktails for the optimal hydrolysis of biomass; mimicking the natural distribution of these enzyme in the different pools.



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ACKNOWLEDGEMENTS Authors would like to thank NCIM culture collection for providing the fungal strains for study and Dr. Arvind Lali for providing pre-treated wheat straw. Technical help from Dr. Nidhi Adlakha during initial experiments is greatly acknowledged. The research was funded by the grants

from

the

Department

of

Biotechnology,

Govt

of

India

(Grant

no.

BT/PB/Center/03/2011) and Biotechnology Industry Research Assistance Council, Govt of India (Grant no. BT/BIPP0713/27/13).

SUPPORTING INFORMATION AVAILABLE Supplementary tables and figures are available as supporting information. Table S-1: List of the fungal strains used in the study. Table S-2: Pairwise sequence similarity of P. funiculosum. Table S-3: List and functional annotations of proteins identified in the secretome of P. funiculosum. Table S-4: Summary of CAZYmes identified in the secretome of P. funiculosum and their relative abundance. Table S-5: Number and distribution of predicted CAZymes from P. funiculosum. Table S-6: List of proteins validated at 1% FDR in the different SEC pools and their corresponding normalised iBAQ values. Table S-7: The distribution of validated proteins across the different SEC pools. Figure S-1: SDS-PAGE gel showing band position excised for LC-MS/MS. Figure S-2: Lignocellulolytic activity screening of studied fungi. Figure S-3: Banding pattern of SEC fractions from P. funiculosum.


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REFERENCES (1)

Lange, L.; Bech, L.; Busk, P. K.; Grell, M. N.; Huang, Y.; Lange, M.; Linde, T.;

Pilgaard, B.; Roth, D.; Tong, X. The importance of fungi and of mycology for a global development of the bioeconomy. IMA Fungus 2012, 3, 87-92. (2)

Zinoviev, S.; Muller-Langer, F.; Das, P.; Bertero, N.; Fornasiero, P.; Kaltschmitt, M.;

Centi, G.; Miertus, S. Next-generation biofuels: Survey of emerging technologies and sustainability issues. ChemSusChem. 2010, 3, 1106-1133. (3)

Berrin, J. G.; Navarro, D.; Couturier, M.; Olive, C.; Grisel, S.; Haon, M.; Taussac, S.;

Lechat, C.; Courtecuisse, R.; Favel, A.; Coutinho, P. M.; Lesage-Meessen, L. Exploring the natural fungal biodiversity of tropical and temperate forests toward improvement of biomass conversion. Appl. Environ. Microbiol. 2012, 78, 6483-6490. (4)

Doolotkeldieva, T.; Bobusheva, S. T. Screening of Wild-Type Fungal Isolates for

Cellulolytic Activity. Microbiol. Insights 2011, 1-10. (5)

Grigoriev, I. V.; Nikitin, R.; Haridas, S.; Kuo, A.; Ohm, R.; Otillar, R.; Riley, R.;

Salamov, A.; Zhao, X.; Korzeniewski, F.; Smirnova, T.; Nordberg, H.; Dubchak, I.; Shabalov, I. MycoCosm portal: gearing up for 1000 fungal genomes. Nucleic Acids Res. 2014, 42, 699704. (6)

Harris, P. V.; Xu, F.; Kreel, N. E.; Kang, C.; Fukuyama, S. New enzyme insights drive

advances in commercial ethanol production. Curr. Opin. Chem. Biol. 2014, 19, 162-170. (7)

Dale, B. E. A New Industry Has Been Launched: The Cellulosic Biofuels Ship (Finally)

Sails. Biofuels, Bioprod. Biorefin. 2015, 9, 1-3. (8)

Zhang, Z.; Donaldson, A. A.; Ma, X. Advancements and future directions in enzyme

technology for biomass conversion. Biotechnol. Adv. 2012, 30, 913-919. (9)

Gusakov, A. V. Alternatives to Trichoderma reesei in biofuel production. Trends

Biotechnol. 2011, 29, 419-425. 29 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(10)

Page 30 of 60

Gusakov, A. V.; Sinitsyn, A. P. Cellulases from Penicillium species for producing fuels

from biomass. Biofuels 2012, 3, 463-477. (11)

Zhang, X.-Z.; Zhang, Y.-H. P. Cellulases: Characteristics, Sources, Production, and

Applications. In Bioprocessing Technologies in Biorefinery for Sustainable Production of Fuels, Chemicals, and Polymers, John Wiley & Sons, Inc.: 2013; pp 131-146. (12)

Hu, J.; Arantes, V.; Saddler, J. N. The enhancement of enzymatic hydrolysis of

lignocellulosic substrates by the addition of accessory enzymes such as xylanase: is it an additive or synergistic effect? Biotechnol. Biofuels 2011, 4, 36. (13)

Payne, C. M.; Knott, B. C.; Mayes, H. B.; Hansson, H.; Himmel, M. E.; Sandgren, M.;

Stahlberg, J.; Beckham, G. T. Fungal cellulases. Chem. Rev. 2015, 115, 1308-1448. (14)

Horn, S. J.; Vaaje-Kolstad, G.; Westereng, B.; Eijsink, V. G. Novel enzymes for the

degradation of cellulose. Biotechnol. Biofuels 2012, 5, 45. (15)

Kim, I. J.; Lee, H. J.; Choi, I. G.; Kim, K. H. Synergistic proteins for the enhanced

enzymatic hydrolysis of cellulose by cellulase. Appl. Microbiol. Biotechnol. 2014, 98, 84698480. (16)

McClendon, S. D.; Batth, T.; Petzold, C. J.; Adams, P. D.; Simmons, B. A.; Singer, S.

W. Thermoascus aurantiacus is a promising source of enzymes for biomass deconstruction under thermophilic conditions. Biotechnol. Biofuels 2012, 5, 54. (17)

Peterson, R.; Nevalainen, H. Trichoderma reesei RUT-C30--thirty years of strain

improvement. Microbiology 2012, 158, 58-68. (18)

Marjamaa, K.; Toth, K.; Bromann, P. A.; Szakacs, G.; Kruus, K. Novel Penicillium

cellulases for total hydrolysis of lignocellulosics. Enzyme Microb.Technol. 2013, 52, 358-69. (19)

Martinez, D.; Berka, R. M.; Henrissat, B.; Saloheimo, M.; Arvas, M.; Baker, S. E.;

Chapman, J.; Chertkov, O.; Coutinho, P. M.; Cullen, D.; Danchin, E. G.; Grigoriev, I. V.; Harris, P.; Jackson, M.; Kubicek, C. P.; Han, C. S.; Ho, I.; Larrondo, L. F.; de Leon, A. L.;


Page 31 of 60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Magnuson, J. K.; Merino, S.; Misra, M.; Nelson, B.; Putnam, N.; Robbertse, B.; Salamov, A. A.; Schmoll, M.; Terry, A.; Thayer, N.; Westerholm-Parvinen, A.; Schoch, C. L.; Yao, J.; Barabote, R.; Nelson, M. A.; Detter, C.; Bruce, D.; Kuske, C. R.; Xie, G.; Richardson, P.; Rokhsar, D. S.; Lucas, S. M.; Rubin, E. M.; Dunn-Coleman, N.; Ward, M.; Brettin, T. S. Genome sequencing and analysis of the biomass-degrading fungus Trichoderma reesei (syn. Hypocrea jecorina). Nat. Biotechnol. 2008, 26, 553-560. (20)

Poidevin, L.; Berrin, J. G.; Bennati-Granier, C.; Levasseur, A.; Herpoel-Gimbert, I.;

Chevret, D.; Coutinho, P. M.; Henrissat, B.; Heiss-Blanquet, S.; Record, E. Comparative analyses of Podospora anserina secretomes reveal a large array of lignocellulose-active enzymes. Appl. Microbiol. Biotechnol. 2014, 98, 7457-7469. (21)

Ravalason, H.; Grisel, S.; Chevret, D.; Favel, A.; Berrin, J. G.; Sigoillot, J. C.; Herpoel-

Gimbert, I. Fusarium verticillioides secretome as a source of auxiliary enzymes to enhance saccharification of wheat straw. Bioresour. Technol. 2012, 114, 589-596. (22)

Adav, S. S.; Chao, L. T.; Sze, S. K. Protein abundance in multiplexed samples

(PAMUS) for quantitation of Trichoderma reesei secretome. J. Proteomics 2013, 83, 180-196. (23)

Bouws, H.; Wattenberg, A.; Zorn, H. Fungal secretomes--nature's toolbox for white

biotechnology. Appl. Microbiol. Biotechnol. 2008, 80, 381-388. (24)

Ribeiro, D. A.; Cota, J.; Alvarez, T. M.; Bruchli, F.; Bragato, J.; Pereira, B. M.; Pauletti,

B. A.; Jackson, G.; Pimenta, M. T.; Murakami, M. T.; Camassola, M.; Ruller, R.; Dillon, A. J.; Pradella, J. G.; Paes Leme, A. F.; Squina, F. M. The Penicillium echinulatum secretome on sugar cane bagasse. PLoS One 2012, 7, e50571. (25)

Ribeiro, D. A.; Cota, J.; Alvarez, T. M.; Brüchli, F.; Bragato, J.; Pereira, B. M. P.;

Pauletti, B. A.; Jackson, G.; Pimenta, M. T. B.; Murakami, M. T.; Camassola, M.; Ruller, R.; Dillon, A. J. P.; Pradella, J. G. C.; Paes Leme, A. F.; Squina, F. M. The Penicillium echinulatum Secretome on Sugar Cane Bagasse. PLoS ONE 2012, 7, e50571.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(26)

Page 32 of 60

Salvachua, D.; Martinez, A. T.; Tien, M.; Lopez-Lucendo, M. F.; Garcia, F.; de Los

Rios, V.; Martinez, M. J.; Prieto, A. Differential proteomic analysis of the secretome of Irpex lacteus and other white-rot fungi during wheat straw pretreatment. Biotechnol. Biofuels 2013, 6, 115. (27)

Hamdan O. A.; Abdul H. A.; L., M. Dynamic Weighted Sum Multi-Criteria Decision

Making: Mathematical Model. International Journal of Mathematics and Statistics Invention 2013, 1, 16-18. (28)

Triantaphyllou, E.; Mann, S. H. An Examination of the Effectiveness of Multi-

Dimensional Decision-Making Methods: A Decision-Making Paradox. Decision Support Systems 1989, 5, 303-312. (29)

Hill, H. D.; Straka, J. G. Protein determination using bicinchoninic acid in the presence

of sulfhydryl reagents. Anal. Biochem. 1988, 170, 203-208. (30)

Smith, P. K.; Krohn, R. I.; Hermanson, G. T.; Mallia, A. K.; Gartner, F. H.; Provenzano,

M. D.; Fujimoto, E. K.; Goeke, N. M.; Olson, B. J.; Klenk, D. C. Measurement of protein using bicinchoninic acid. Anal. Biochem. 1985, 150, 76-85. (31)

Adney, B.; Baker, J. Measurement of Cellulase Activities; NREL/TP-510-42628;

National Renewable Energy Laboratory: Colorado, USA, 2008; p 11. (32)

Miller, G. L. Use of Dinitrosalicylic Acid Reagent for Determination of Reducing

Sugar. Anal. Chem. 1959, 31, 426-428. (33)

Kittl, R.; Kracher, D.; Burgstaller, D.; Haltrich, D.; Ludwig, R. Production of four

Neurospora crassa lytic polysaccharide monooxygenases in Pichia pastoris monitored by a fluorimetric assay. Biotechnol. Biofuels 2012, 5, 79. (34)

Ghose, T. K. Measurement of cellulase activities. Pure Appl. Chem. 1987, 59, 257-268.

(35)

Eveleigh, D. E.; Mandels, M.; Andreotti, R.; Roche, C. Measurement of saccharifying

cellulase. Biotechnol. Biofuels 2009, 2, 21.


Page 33 of 60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(36)

Triantaphyllou, E. Multi-criteria Decision Making Methods: A Comparative Study.

Springer: US.: 2000. pp 1-199 (37)

Triantaphyllou, E.; Mann, S. H. Using the Analytic Hierarchy process for decision

making in engineering applications: some challenges. International Journal of Industrial Engineering: Applications and Practice 1995, 2, 35-44. (38)

Triantaphyllou, E.; Shu, B. A.; Sanchez, S. N.; Ray, T., Multi-Criteria Decision

Making: An Operations Research Approach. In Encyclopedia of Electrical and Electronics Engineering, Webster, J. G., Ed. John Wiley & Sons: New York, 1998; pp 175-186. (39)

Yilmaz, N.; Visagie, C. M.; Houbraken, J.; Frisvad, J. C.; Samson, R. A. Polyphasic

taxonomy of the genus Talaromyces. Stud. Mycol. 2014, 78, 175-341. (40)

Marx, I. J.; van Wyk, N.; Smit, S.; Jacobson, D.; Viljoen-Bloom, M.; Volschenk, H.

Comparative secretome analysis of Trichoderma asperellum S4F8 and Trichoderma reesei Rut-C30 during solid-state fermentation on sugarcane bagasse. Biotechnol. Biofuels 2013, 6, 172. (41)

White, T. J.; Bruns, T.; Lee, S.; Taylor, J., Amplification and direct sequencing of

fungal ribosomal RNA genes for phylogenetics. Academic Press, San Diego, CA: 1990; pp 315–322. (42)

Robert, V.; Szoke, S.; Jabas, B.; Vu, D.; Chouchen, O.; Blom, E.; Cardinali, G.

BioloMICS software: Biological data management, identification, classification and statistics. Open Appl. Inf. J. 2011, 5, 87-98. (43)

Seifert, K. A. Progress towards DNA barcoding of fungi. Mol. Ecol. Resour. 2009, 9,

83-89. (44)

Laemmli, U. K. Cleavage of structural proteins during the assembly of the head of

bacteriophage T4. Nature 1970, 227, 680-685.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(45)

Page 34 of 60

Sasse, J.; Gallagher, S. R. Staining Proteins in Gels. In Curr. Protoc. Mol. Biol., John

Wiley & Sons, Inc.: 2009; pp 10.6.1-10.6.27. (46)

Shevchenko, A.; Tomas, H.; Havlis, J.; Olsen, J. V.; Mann, M. In-gel digestion for mass

spectrometric characterization of proteins and proteomes. Nat. Protoc. 2006, 1, 2856-2860. (47)

Gundry, R. L.; White, M. Y.; Murray, C. I.; Kane, L. A.; Fu, Q.; Stanley, B. A.; Van

Eyk, J. E. Preparation of proteins and peptides for mass spectrometry analysis in a bottom-up proteomics workflow. Curr. Protoc. Mol. Biol. 2009, 10, 10.25.1-10.25.23. (48)

Vaudel, M.; Barsnes, H.; Berven, F. S.; Sickmann, A.; Martens, L. SearchGUI: An

open-source graphical user interface for simultaneous OMSSA and X!Tandem searches. Proteomics 2011, 11, 996-999. (49)

Vaudel, M.; Burkhart, J. M.; Zahedi, R. P.; Oveland, E.; Berven, F. S.; Sickmann, A.;

Martens, L.; Barsnes, H. PeptideShaker enables reanalysis of MS-derived proteomics data sets. Nat. Biotechnol. 2015, 33, 22-24. (50)

Cox, J.; Mann, M. MaxQuant enables high peptide identification rates, individualized

p.p.b.-range mass accuracies and proteome-wide protein quantification. Nat. Biotechnol. 2008, 26, 1367-1372. (51)

Craig, R.; Beavis, R. C. TANDEM: matching proteins with tandem mass spectra.

Bioinformatics 2004, 20, 1466-1467. (52)

Dorfer, V.; Pichler, P.; Stranzl, T.; Stadlmann, J.; Taus, T.; Winkler, S.; Mechtler, K.

MS Amanda, a universal identification algorithm optimized for high accuracy tandem mass spectra. J. Proteome Res. 2014, 13, 3679-3684. (53)

Kim, S.; Pevzner, P. A. MS-GF+ makes progress towards a universal database search

tool for proteomics. Nat. Commun. 2014, 5, 5277. (54)

Elias, J. E.; Gygi, S. P. Target-decoy search strategy for mass spectrometry-based

proteomics. Methods Mol. Biol. 2010, 604, 55-71.


Page 35 of 60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(55)

Vaudel, M.; Barsnes, H.; Berven, F. S.; Sickmann, A.; Martens, L. SearchGUI: An

open-source graphical user interface for simultaneous OMSSA and X!Tandem searches. Proteomics 2011, 11, 996-9. (56)

Barsnes, H.; Vaudel, M.; Colaert, N.; Helsens, K.; Sickmann, A.; Berven, F. S.;

Martens, L. Compomics-utilities: an open-source Java library for computational proteomics. BMC Bioinformatics 2011, 12, 70. (57)

Wilhelm, M.; Schlegl, J.; Hahne, H.; Moghaddas Gholami, A.; Lieberenz, M.; Savitski,

M. M.; Ziegler, E.; Butzmann, L.; Gessulat, S.; Marx, H.; Mathieson, T.; Lemeer, S.; Schnatbaum, K.; Reimer, U.; Wenschuh, H.; Mollenhauer, M.; Slotta-Huspenina, J.; Boese, J. H.; Bantscheff, M.; Gerstmair, A.; Faerber, F.; Kuster, B. Mass-spectrometry-based draft of the human proteome. Nature 2014, 509, 582-587. (58)

Gotz, S.; Garcia-Gomez, J. M.; Terol, J.; Williams, T. D.; Nagaraj, S. H.; Nueda, M. J.;

Robles, M.; Talon, M.; Dopazo, J.; Conesa, A. High-throughput functional annotation and data mining with the Blast2GO suite. Nucleic Acids Res. 2008, 36, 3420-3435. (59)

Mitchell, A.; Chang, H. Y.; Daugherty, L.; Fraser, M.; Hunter, S.; Lopez, R.; McAnulla,

C.; McMenamin, C.; Nuka, G.; Pesseat, S.; Sangrador-Vegas, A.; Scheremetjew, M.; Rato, C.; Yong, S. Y.; Bateman, A.; Punta, M.; Attwood, T. K.; Sigrist, C. J.; Redaschi, N.; Rivoire, C.; Xenarios, I.; Kahn, D.; Guyot, D.; Bork, P.; Letunic, I.; Gough, J.; Oates, M.; Haft, D.; Huang, H.; Natale, D. A.; Wu, C. H.; Orengo, C.; Sillitoe, I.; Mi, H.; Thomas, P. D.; Finn, R. D. The InterPro protein families database: the classification resource after 15 years. Nucleic Acids Res. 2015, 43, 213-221. (60)

Wittkop, T.; Emig, D.; Lange, S.; Rahmann, S.; Albrecht, M.; Morris, J. H.; Bocker,

S.; Stoye, J.; Baumbach, J. Partitioning biological data with transitivity clustering. Nat. Methods 2010, 7, 419-420.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(61)

Page 36 of 60

Wittkop, T.; Emig, D.; Truss, A.; Albrecht, M.; Bocker, S.; Baumbach, J.

Comprehensive cluster analysis with Transitivity Clustering. Nat. Protoc. 2011, 6, 285-295. (62)

Smoot, M. E.; Ono, K.; Ruscheinski, J.; Wang, P. L.; Ideker, T. Cytoscape 2.8: new

features for data integration and network visualization. Bioinformatics 2011, 27, 431-432. (63)

Lombard, V.; Golaconda Ramulu, H.; Drula, E.; Coutinho, P. M.; Henrissat, B. The

carbohydrate-active enzymes database (CAZy) in 2013. Nucleic Acids Res. 2014, 42, 490-495. (64)

Znameroski, E. A.; Glass, N. L. Using a model filamentous fungus to unravel

mechanisms of lignocellulose deconstruction. Biotechnol. Biofuels 2013, 6, 6. (65)

Pryor, S. W.; Nahar, N. Deficiency of cellulase activity measurements for enzyme

evaluation. Appl. Biochem. Biotechnol. 2010, 162, 1737-1750. (66)

Arantes, V.; Saddler, J. N. Cellulose accessibility limits the effectiveness of minimum

cellulase loading on the efficient hydrolysis of pretreated lignocellulosic substrates. Biotechnol. Biofuels 2011, 4, 3. (67)

Hu, J.; Arantes, V.; Pribowo, A.; Saddler, J. N. The synergistic action of accessory

enzymes enhances the hydrolytic potential of a “cellulase mixture” but is highly substrate specific. Biotechnol. Biofuels 2013, 6, 112. (68)

Gao, D.; Chundawat, S. P.; Krishnan, C.; Balan, V.; Dale, B. E. Mixture optimization

of six core glycosyl hydrolases for maximizing saccharification of ammonia fiber expansion (AFEX) pretreated corn stover. Bioresour. Technol. 2010, 101, 2770-2781. (69)

Van Reenen-Hoekstra, E. S.; Frisvad, J. C.; Samson, R. A.; Stolk, A. C. The Penicillium

Funiculosum Complex — Well Defined Species and Problematic Taxa. In Modern Concepts in Penicillium and Aspergillus Classification, Samson, R.; Pitt, J., Eds. Springer US: 1990; Vol. 185, pp 173-192.


Page 37 of 60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(70)

Visagie, C. M.; Hirooka, Y.; Tanney, J. B.; Whitfield, E.; Mwange, K.; Meijer, M.;

Amend, A. S.; Seifert, K. A.; Samson, R. A. Aspergillus, Penicillium and Talaromyces isolated from house dust samples collected around the world. Stud. Mycol. 2014, 78, 63-139. (71)

Schoch, C. L.; Seifert, K. A.; Huhndorf, S.; Robert, V.; Spouge, J. L.; Levesque, C. A.;

Chen, W.; Fungal Barcoding, C.; Fungal Barcoding Consortium Author, L. Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi. Proc. Natl. Acad. Sci. 2012, 109, 6241-6246. (72)

Visagie, C. M.; Houbraken, J.; Frisvad, J. C.; Hong, S. B.; Klaassen, C. H.; Perrone,

G.; Seifert, K. A.; Varga, J.; Yaguchi, T.; Samson, R. A. Identification and nomenclature of the genus Penicillium. Stud. Mycol. 2014, 78, 343-371. (73)

Lachke, A. H.; Bastawde, K. B.; Powar, V. K.; Srinivasan, M. C. Isolation of a

hypercellulolytic mutant (Cu-1) of Penicillium funiculosum. Enzyme Microb.Technol. 1986, 8, 105-108. (74)

Lachke, A. H.; Srinivasan, M. C.; Deshmukh, S. S.; Deshpande, M. V. Strain selection

criteria for Penicillium funiculosum in enzymic hydrolysis of lignocellulosics. Biotechnol. Lett. 1987, 9, 147-150. (75)

Mishra, C.; Rao, M.; Seeta, R.; Srinivasan, M. C.; Deshpande, V. Hydrolysis of

lignocelluloses by Penicillium funiculosum cellulase. Biotechnol. Bioeng. 1984, 26, 370-373. (76)

A.O. Adejuwon; A. O. Oni; A. A. Ajayi; Olutiola, P. O. Cellulase activity in tomato

fruits infected with Penicillium funiculosum Thom. Afr. J. Plant Sci. 2009, 3 113-116. (77)

de Castro, A. M.; de Albuquerque de Carvalho, M. L.; Leite, S. G.; Pereira, N., Jr.

Cellulases from Penicillium funiculosum: production, properties and application to cellulose hydrolysis. J Ind Microbiol Biotechnol 2010, 37, 151-158.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(78)

Page 38 of 60

Furniss, C. S. M.; Williamson, G.; Kroon, P. A. The substrate specificity and

susceptibility to wheat inhibitor proteins of Penicillium funiculosum xylanases from a commercial enzyme preparation. J. Sci. Food Agric 2005, 85, 574-582. (79)

Guais, O.; Borderies, G.; Pichereaux, C.; Maestracci, M.; Neugnot, V.; Rossignol, M.;

Francois, J. M. Proteomics analysis of "Rovabiot Excel", a secreted protein cocktail from the filamentous fungus Penicillium funiculosum grown under industrial process fermentation. J. Ind. Microbiol. Biotechnol. 2008, 35, 1659-1668. (80)

Joglekar, A. V.; Karanth, N. G. Studies on cellulase production by a mutant-

Penicillium funiculosum UV-49. Biotechnol. Bioeng. 1984, 26, 1079-1084. (81)

Karboune, S.; L'Hocine, L.; Anthoni, J.; Geraert, P. A.; Kermasha, S. Properties of

selected hemicellulases of a multi-enzymatic system from Penicillium funiculosum. Biosci. Biotechnol. Biochem. 2009, 73, 1286-1292. (82)

Lafond, M.; Tauzin, A.; Desseaux, V.; Bonnin, E.; Ajandouz el, H.; Giardina, T. GH10

xylanase D from Penicillium funiculosum: biochemical studies and xylooligosaccharide production. Microb. Cell Fact. 2011, 10, 20. (83)

M. Rao; A. Lachke; R. Seeta; A. Joglekar; C. Mishra; Deshpande, V. Evaluation of

Cellulase Complex of Penicillium funiculosum and Its Mutant UV-49 in Relation to Practical Saccharification. Appl. Biochem. Biotech. 1987, 16, 25-34. (84)

Maeda, R. N.; Barcelos, C. A.; Santa Anna, L. M.; Pereira, N., Jr. Cellulase production

by Penicillium funiculosum and its application in the hydrolysis of sugar cane bagasse for second generation ethanol production by fed batch operation. J. Biotechnol. 2013, 163, 38-44. (85)

Maeda, R. N.; Serpa, V. I.; Rocha, V. A. L.; Mesquita, R. A. A.; Anna, L. M. M. S.; de

Castro, A. M.; Driemeier, C. E.; Pereira, N.; Polikarpov, I. Enzymatic hydrolysis of pretreated sugar cane bagasse using Penicillium funiculosum and Trichoderma harzianum cellulases. Process Biochemistry 2011, 46, 1196-1201.


Page 39 of 60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(86)

Ramani, G.; Meera, B.; Vanitha, C.; Rao, M.; Gunasekaran, P. Production, purification,

and characterization of a beta-glucosidase of Penicillium funiculosum NCL1. Appl. Biochem. Biotechnol. 2012, 167, 959-972. (87)

Texier, H.; Dumon, C.; Neugnot-Roux, V.; Maestracci, M.; O'Donohue, M. J.

Redefining XynA from Penicillium funiculosum IMI 378536 as a GH7 cellobiohydrolase. J. Ind. Microbiol. Biotechnol. 2012, 39, 1569-1576. (88)

van Wyk, J. P. H. Paper hydrolysis by cellulase from Penicillium funiculosum and

Trichoderma viride. Bioresour. Technol. 1998, 63, 275-277. (89)

Vanitha M.C.; Meera B.; Ramani G.; Mala Rao; Seeta Laxman; Gunasekaran, P.

Molecular cloning and expression of a family 7 cellobiohydrolase gene cbh1 from Penicillium funiculosum NCL1. Int. J. Microbiol. Res. 2011, 3, 97-107. (90)

Rao, M.; Deshpande, V.; Seeta, R.; Srinivasan, M. C.; Mishra, C. Hydrolysis of

sugarcane bagasse by mycelial biomass of Penicillium funiculosum. Biotechnol. Bioeng. 1985, 27, 1070-1072. (91)

Liu, D.; Li, J.; Zhao, S.; Zhang, R.; Wang, M.; Miao, Y.; Shen, Y.; Shen, Q. Secretome

diversity and quantitative analysis of cellulolytic Aspergillus fumigatus Z5 in the presence of different carbon sources. Biotechnol. Biofuels 2013, 6, 149. (92)

Herpoel-Gimbert, I.; Margeot, A.; Dolla, A.; Jan, G.; Molle, D.; Lignon, S.; Mathis, H.;

Sigoillot, J. C.; Monot, F.; Asther, M. Comparative secretome analyses of two Trichoderma reesei RUT-C30 and CL-847 hypersecretory strains. Biotechnol. Biofuels 2008, 1, 18. (93)

Gomez-Mendoza, D. P.; Junqueira, M.; do Vale, L. H.; Domont, G. B.; Ferreira Filho,

E. X.; Sousa, M. V.; Ricart, C. A. Secretomic survey of Trichoderma harzianum grown on plant biomass substrates. J. Proteome Res. 2014, 13, 1810-1822.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(94)

Page 40 of 60

Gao, X.; Kumar, R.; Singh, S.; Simmons, B. A.; Balan, V.; Dale, B. E.; Wyman, C. E.

Comparison of enzymatic reactivity of corn stover solids prepared by dilute acid, AFEX, and ionic liquid pretreatments. Biotechnol. Biofuels 2014, 7, 71. (95)

Van Dyk, J. S.; Pletschke, B. I. A review of lignocellulose bioconversion using

enzymatic hydrolysis and synergistic cooperation between enzymes--factors affecting enzymes, conversion and synergy. Biotechnol. Adv. 2012, 30, 1458-1480. (96)

Phillips, C. M.; Beeson, W. T.; Cate, J. H.; Marletta, M. A. Cellobiose dehydrogenase

and a copper-dependent polysaccharide monooxygenase potentiate cellulose degradation by Neurospora crassa. ACS Chem. Biol. 2011, 6, 1399-1406. (97)

Quinlan, R. J.; Sweeney, M. D.; Lo Leggio, L.; Otten, H.; Poulsen, J. C.; Johansen, K.

S.; Krogh, K. B.; Jorgensen, C. I.; Tovborg, M.; Anthonsen, A.; Tryfona, T.; Walter, C. P.; Dupree, P.; Xu, F.; Davies, G. J.; Walton, P. H. Insights into the oxidative degradation of cellulose by a copper metalloenzyme that exploits biomass components. Proc. Natl. Acad. Sci. 2011, 108, 15079-15084. (98)

Pullan, S. T.; Daly, P.; Delmas, S.; Ibbett, R.; Kokolski, M.; Neiteler, A.; van Munster,

J. M.; Wilson, R.; Blythe, M. J.; Gaddipati, S.; Tucker, G. A.; Archer, D. B. RNA-sequencing reveals the complexities of the transcriptional response to lignocellulosic biofuel substrates in Aspergillus niger. Fungal Biol. Biotechnol. 2014, 1, 3. (99)

Gourlay, K.; Hu, J.; Arantes, V.; Andberg, M.; Saloheimo, M.; Penttila, M.; Saddler, J.

Swollenin aids in the amorphogenesis step during the enzymatic hydrolysis of pretreated biomass. Bioresour. Technol. 2013, 142, 498-503. (100) Ohtaki, S.; Maeda, H.; Takahashi, T.; Yamagata, Y.; Hasegawa, F.; Gomi, K.; Nakajima, T.; Abe, K. Novel hydrophobic surface binding protein, HsbA, produced by Aspergillus oryzae. Appl. Environ. Microbiol. 2006, 72, 2407-2413.


Page 41 of 60

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(101) Kirkwood, K. J.; Ahmad, Y.; Larance, M.; Lamond, A. I. Characterization of native protein complexes and protein isoform variation using size-fractionation-based quantitative proteomics. Mol. Cell Proteomics 2013, 12, 3851-3873. (102) Kristensen, A. R.; Gsponer, J.; Foster, L. J. A high-throughput approach for measuring temporal changes in the interactome. Nat. Meth. 2012, 9, 907-909. (103) da Silva, A. J.; Gomez-Mendoza, D. P.; Junqueira, M.; Domont, G. B.; Ximenes Ferreira Filho, E.; de Sousa, M. V.; Ricart, C. A. Blue native-PAGE analysis of Trichoderma harzianum secretome reveals cellulases and hemicellulases working as multienzymatic complexes. Proteomics 2012, 12, 2729-2738. (104) Olinares, P. D.; Ponnala, L.; van Wijk, K. J. Megadalton complexes in the chloroplast stroma of Arabidopsis thaliana characterized by size exclusion chromatography, mass spectrometry, and hierarchical clustering. Mol. Cell Proteomics 2010, 9, 1594-1615. (105) Inoue, H.; Decker, S. R.; Taylor, L. E., 2nd; Yano, S.; Sawayama, S. Identification and characterization of core cellulolytic enzymes from Talaromyces cellulolyticus (formerly Acremonium cellulolyticus) critical for hydrolysis of lignocellulosic biomass. Biotechnol. Biofuels 2014, 7, 151.



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Table 1. Correlations Coefficients between Core Cellulases Activities and Actual Enzyme Performance on Pre-Treated Wheat Straw

AMM ALK Note: p < 0.05

Endoglucanase (CMCase) 0.55 0.75

Exoglucanase (Avicellase) 0.92 0.90

β-glucosidase (pNPGase) 0.47 0.53

AMM= Ammonium pre-treated wheat straw ALK = sodium hydroxide pre-treated wheat straw.


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Table 2. Scoring of Strain Performance (Hydrolysis Potential) Using the Weighted Sum Model (WSM) Identity L1 L2 L3 L4 L5 L6 L7 L8 L9 L10 L11 L12 L13 L14 L15 L16 L17 L18 L19 L20 L21 L22 L23 L24 L25 L26 L27 L28 L29 L30 L31 L32 L33 L34 L35 L36 L37 L38 L39 L40 L41 L42 L43 L44 L45

Name Aspergillus niger Neurospora crassa Cladosporium sp. Aspergillus fumigatus Myrothecium verrucaria Myrothecium verrucaria Neurospora crassa Neurospora crassa Trichoderma reesei Ptychogaster sp. Fusarium sp. Coriolus versicolor Paecilomyces sp. Sclerotium rolfsii Pleurotus sajor-caju Penicillium janthinellum Penicillium janthinellum Trichoderma viride Phanerochaete chrysosporium Pleurotus ostreatus Trametes hirsuta Aspergillus terreus Aspergillus awamori (niger) Aspergillus niger Aspergillus niger Aspergillus flavus Aspergillus flavus Aspergillus flavipes Aspergillus sp. Aspergillus sp. Aspergillus sp. Penicillium sp. Aspergillus oryzae Aspergillus sp Aspergillus sp. Aspergillus niger strain Penicillium oxalicum Aspergillus sp. Penicillium citrinum strain Aspergillus sp. Trichoderma atroviride Penicilliuim funiculosum Trichoderma reesei Trichoderma reesei Aspergillus niger

Sum of weights for ALK 17.64 29.35 5.73 5.56 5.60 6.03 6.91 33.64 5.77 12.07 5.57 30.84 5.26 5.75 5.58 5.26 5.42 7.02 6.46 8.39 14.12 7.22 9.82 7.03 9.20 12.47 12.68 5.90 7.40 8.58 6.22 21.09 7.71 6.88 7.00 8.52 14.52 7.66 6.50 8.07 15.02 54.96 4.95 4.76 4.68

Sum of weights for AFEX 11.22 20.20 4.73 5.45 5.43 5.65 6.28 19.28 5.23 9.51 5.24 22.39 5.31 5.32 5.43 5.77 5.13 6.12 6.05 5.99 10.05 6.64 8.47 6.34 7.44 9.19 9.52 5.73 6.40 7.27 5.75 14.28 7.48 6.28 6.16 6.70 9.53 6.84 6.25 6.34 10.77 64.63 5.55 4.69 6.21

Average sum of weights 14.43 24.77 5.23 5.51 5.51 5.84 6.60 26.46 5.50 10.79 5.40 26.62 5.28 5.54 5.50 5.51 5.27 6.57 6.25 7.19 12.08 6.93 9.14 6.69 8.32 10.83 11.10 5.82 6.90 7.92 5.98 17.69 7.59 6.58 6.58 7.61 12.03 7.25 6.37 7.20 12.89 59.80 5.25 4.73 5.45

AMM= Ammonium pre-treated wheat straw ALK = Sodium hydroxide pre-treated wheat straw.



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Table 3. Specific Activities of Selected Biomass Hydrolyzing Enzymes of Penicillium funiculosum Secretome in Comparison to Commercial Cellulase Cocktail 1, 2, 3

pNPG (U/mg)

CMC (U/mg)

avicel (U/mg)

pNPX (U/mg)

xylan (U/mg)

PMO (U/mg)

FPA (FPU/mg)

Penicillium funiculosum

3.71 (0.009)

3.14 (0.088)

0.20 (0.019)

0.21 (0.005)

3.39 (0.103)

0.05 (0.0003)

0.64

Advance Enzyme formulation (AETL)

1.77 (0.086)

8.97 (0.258)

0.02 (0.006)

0.96 (0.042)

11.09 (0.329)

NT

0.08

Enzyme

1

Specific activities based on protein concentrations obtained using the Bicinchoninic acid (BCA) method. Three replicates were performed and the standard error of mean represented in parentheses. 3 Activities represented by each substrate is described in the methods section. 2


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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47


Table 4. List of Hypothetical Proteins with Putative Functions Assigned Through Pairwise Similarity Function S/N 1 2 3 4 5 6 7 8 9 10 11 12

Protein ID maker-contig00010-exonerate_protein2genome-gene-2.14-mRNA-1 maker-contig00070-exonerate_protein2genome-gene-0.125-mRNA-1 maker-contig00025-exonerate_protein2genome-gene-0.101-mRNA-1 maker-contig00022-exonerate_protein2genome-gene-0.79-mRNA-1 maker-contig00012-exonerate_protein2genome-gene-4.76-mRNA-1 maker-contig00002-exonerate_protein2genome-gene-5.32-mRNA-1 maker-contig00009-exonerate_protein2genome-gene-0.10-mRNA-1 maker-contig00222-exonerate_protein2genome-gene-0.3-mRNA-1 maker-contig00013-exonerate_protein2genome-gene-3.69-mRNA-1 maker-contig00021-exonerate_protein2genome-gene-2.99-mRNA-1 maker-contig00005-exonerate_protein2genome-gene-2.92-mRNA-1 maker-contig00035-exonerate_protein2genome-gene-2.65-mRNA-1

Nearest neighbour ID** maker-contig00104-exonerate_protein2genome-gene-0.20-mRNA-1 maker-contig00010-exonerate_protein2genome-gene-2.36-mRNA-1 maker-contig00015-exonerate_protein2genome-gene-1.44-mRNA-1 maker-contig00048-exonerate_protein2genome-gene-1.138-mRNA-1 maker-contig00048-exonerate_protein2genome-gene-1.138-mRNA-1 maker-contig00035-exonerate_protein2genome-gene-2.46-mRNA-1 maker-contig00080-exonerate_protein2genome-gene-0.98-mRNA-1 maker-contig00037-exonerate_protein2genome-gene-0.55-mRNA-1 maker-contig00002-exonerate_protein2genome-gene-3.46-mRNA-1 maker-contig00005-exonerate_protein2genome-gene-3.32-mRNA-1 maker-contig00039-exonerate_protein2genome-gene-0.39-mRNA-1 maker-contig00035-exonerate_protein2genome-gene-1.82-mRNA-1

Putative Function endo-beta-1,4-xylanase FAD-dependent oxidase, proteasome component Pre9 xylanase xylanase endoglucanase endo-1,3-beta-glucosidase class V chitinase, xylosidase cell wall galactomannoprotein swollenin, putative catalase-peroxidase



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47

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Table 5. List of Identified Proteins Representing 60% of the Crude Secretome Based on the Normalized Spectrum Abundance Factor (NSAF) S?N

Accession

Description

Predicted CAZY Distribution

#Validated Peptides

#Validated Spectra

NSAF

1

maker-contig00012-exonerate_protein2genome-gene-4.113-mRNA-1

cellobiohydrolase I

GH7-CBM1

94

1824

1.100

2


cellobiohydrolase II

GH6-CBM1

86

1114

0.599

3


swollenin

NA

25

251

0.495

4


glucoamylase

GH15-CBM20

97

957

0.446

5


endoglucanase

GH12

16

60

0.433

6


endoglucanase

GH7-CBM1

11

71

0.352

7


endoglucanase

GH5-CBM1

43

289

0.343

8


xylanase

GH11

7

35

0.323

9


beta-glucosidase

GH3

102

758

0.319

10


hypothetical protein PMAA_045380 (HsbA -like protein)

NA

5

20

0.307

11


beta-1,4-xylanase

GH10-CBM1

39

360

0.275

12


beta-glucosidase

GH3

80

974

0.251

13


IgE-binding protein

NA

4

16

0.245

14


endoglucanase

GH5-CBM1

20

127

0.217

15


swollenin

NA

4

19

0.203

16


arabinofuranosidase

GH62-CBM1

19

83

0.166

17


CE1-CBM1

5

25

0.165

18


ferulic acid esterase A GPI-anchored cell wall beta-1,3-endoglucanase

GH17

17

126

0.163

19


xylanase

GH11-CBM1

13

39

0.159

20


extracellular cell wall glucanase Crf1

GH16

9

64

0.159

21


endoglucanase (GH61)

AA9

5

36

0.144


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FIGURE LEGENDS Figure 1. Biomass degradation kinetics of Penicillium funiculosum (NCIM 1228) in relation to commercial cellulase cocktail - advanced enzyme formulation (C1). Panel A represents the hydrolysis dynamics on sodium hydroxide pretreated wheat straw while panel B represents the hydrolysis dynamics on AMM= Ammonia pre-treated wheat straw. The amount of reducing sugar released was quantified using 3,5-Dinitrosalicylic acid (DNSA) assay. The different enzyme preparations were loaded at 0.2 filter paper unit (FPU) per gram of biomass. Biomass loading was at 5% dry weight loading. Values plotted were means ± standard error of means of three independent experiments. Figure 2. Functional classification of proteins identified in secretome of Penicillium funiculosum (NCIM 1228) Figure 3. A plot of molecular weight against the isoelectric point (pI). The molecular weights of proteins validated at 1% were profiled against their theoretical pI. Data points in circle are CAZymes with red colored indicating glycoside hydrolases (GHs); blue colored – Auxilliary Activities related enzymes (AAs); ash colored - Carbohydrate Esterases (CEs); black colored – Polysaccharide Lyases (PLs). All other non CAZYmes are represented as black colored open inverted triangles. Proteins associated with polysaccharide binding are with brown colored open inverted triangles. Figure 4. Number and distribution of predicted CAZymes obtained from the draft genome sequence versus CAZymes detected in the most performing secretome of Penicillium funiculosum NCIM 1228. Values in each category represent the actual number of CAZymes. GT = Glycosyl Transferases, AA = Auxiliary Activities, CE = Carbohydrate Esterases, PL = Polysaccharide Lyases and GH = Glycoside Hydrolases



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Figure 5. Non denaturing size exclusion fractionation of Penicillium funiculosum crude enzyme (NCIM 1228). Panel A represents a chromatogram of SEC-fractionated secretome (~ 20mg of proteins) eluted with 50mM sodium acetate buffer PH 5.0 containing 150mM NaCl. Protein standards of known molecular weights (ferritin (440kDa), aldolase (158kDa), conalbumin (75kDa) and ovalbumin (44kDa) were loaded on the same column. Fractions showing similar banding pattern on SDS-PAGE gel were pooled together as follows: pool A = F1 – F5 (83.32 -93.34 mL), pool B = F6 - F8 (93.34 -99.35 mL), pool C = F9 - F12 (99.35 – 107.36 mL), pool D = F13 - F16 (107.36 – 115.37 mL) and pool E = F17 -F25 (115.37mL – 135.36 mL). Panel B represents the banding pattern of different SEC fraction pools of P. funiculosum crude. Protein load was at 20 µg per lane. Lanes 1 and 8 represents protein marker, pooled fractions A to E represented in lanes 2 to 6; and an equal load of P. funiculosum crude protein in lane 7. Figure 6. A Venn diagram describing the relative distribution of differentially associating protein across SEC fraction pools of Penicillium funiculosum NCIM 1228. Figure 7. A Network Representation of the Protein Interaction Dynamics across SEC fraction pools. The various proteins are represented as nodes while interactions as edges. The weight of the edge represents the edge betweenness of the nodes. Details of abbreviations are in the Supporting Information Table S-6. Figure 8. Hierarchical clustering of proteins per fraction pool showing the abundance of differentially associating proteins. The hierarchical clustering was performed on log transformed iBAQ intensities using euclidean distance and complete linkage. Figure 9. Stoichiometries of major proteins in the different SEC fraction pools of Penicillium funiculosum NCIM 1228.


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Figure 10. Biomass hydrolysis potential of different pools from SEC fractions of P. funiculosum (NCIM 1228) secretome. The biomass hydrolysis potential of the different pools (differentially associating protein groups following separation under native SEC) expressed as a percentage of the total sugar released with respect to the crude protein. The amount of the total reducing sugar was estimated through the dinitrosalicylic acid (DNSA) method. Panels A and B represent the observed hydrolysis pattern on sodium hydroxide pretreated and ammonium pre-treated wheat straw, respectively. Hydrolysis was carried out at 50 C with 20 mg of protein samples per gram of dry weight biomass.



Figure 1

(A) 100

L42

C1

Percentage hydrolysis

90 80 70 60 50 40 30 20 10 0 12

24

36

Time (hrs)

(B) 100

L42

C1

90 80

Percentage hydrolysis

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 50 of 60

70 60 50 40 30 20 10 0 12

24 Time (hrs)

36


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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 2

Carbohydrate Binding 2% AAs [6%]

Other Functions 19%

Oxidases with other functions 6%

Carbohydrate active enzymes (CAZY) 58%

GHs [47%]

CEs [4%] PLs [1%]

Amino Acid Metabolism/Proteolysis 15%



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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Figure 3


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Figure 4

100% 90%

Relative abundance of CAZymes

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


80%

82

11 7 3

77

70% 60%

88 5

50% 92

40% 30%

GT AA CE PL GH

310

20% 10% 0% PREDICTED

DETECTED



Figure 5 (A)

1000 900

2000

800 700

1500

600 500

1000

400 300

500

200 100

0

Absorbance for crude enzyme euates at 280 nm (mAU)

2500

Absorbance for Protein Markers at 280 nm (mAU)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 54 of 60

0 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 Elution volume (mL)

s

(B)


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Figure 6



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 56 of 60

Figure 7


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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


Figure 8

low

high



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 58 of 60

Figure 9

extracellular cell wall glucanase Crf1 [GH16]…

Pool A

Pool B

cell wall galactomannoprotein 8%

Beta-glucosidase [GH3]…

betaglucosidase [GH1]…

beta-glucosidase [GH1], 4%

GPI-anchored cell wall beta-1,3endoglucanase EglC [GH17] 3%

cell wall galactomanno protein 76%

glucoamylase [GH15-CBM20] 44%

Beta-glucosidase [GH3] 5% betaxylosidase [GH3]…

GMF family protein 3% alpha-L-arabinofuranosidase [GH54-CBM42]…

cellobiohydrolase I [GH7-CBM1] 10% swollenin 18%

endoglucanase [AA9]…

Pool C

Pool D

endoglucanase GH45 , 2% endoglucanase [GH5-CBM1] 17%

beta-D-glucoside glucohydrolase [GH3] 2% cellobiohydrolase I [GH7-CBM1] 64%

Glycoside Hydrolase family 18 protein [GH18]…

cellobiohydrolase I [GH7-CBM1] 46%

glucoamylase [GH15-CBM20] 11% swollenin 10%

cellobiohydrolase II [GH6-CBM1] 33%

Pool E

acetyl xylan esterase [CE5-CBM1], 23% xylanase [GH11CBM1], 3%

cellobiohydrolase II [GH6-CBM1], 65%

cellobiohydrolase I [GH7-CBM1], 5% Carbohydrate esterase [CE3-CBM1], 1%


Page 59 of 60

Figure 10 (A)

Relative hydrolysis (%)

100 80 60 40 20 0 A

B

C Pools

D

E

(B) 100

Relative hydrolysis (%)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


80 60 40 20 0 A

B

C Pools

D

E



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

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For Table of Contents Only


Proteomics Insights into the Biomass Hydrolysis Potentials of a

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