Comparative metabolism of cellulose, sophorose and glucose in Trichoderma reesei using high-throughput genomic and proteomic analyses

Biotechnology for Biofuels

Lilian dos Santos Castro⁴  Wellington Ramos Pedersoli⁴  Amanda Cristina Campos Antoniêto⁴  Andrei Stecca Steindorff²  Rafael Silva-Rocha⁴  Nilce M Martinez-Rossi¹  Antonio Rossi⁴  Neil Andrew Brown³  Gustavo H Goldman³  Vitor M Faça⁴  Gabriela F Persinoti¹  Roberto Nascimento Silva⁴ 

[1] Department of Genetics, Ribeirão Preto Medical School, University of São Paulo, 14049-900 Ribeirão Preto, SP, Brazil

[2] Departamento de Biologia Celular, Universidade de Brasília, Asa Norte, 70910-900 Brasília, DF, Brazil

[3] Faculdade de Ciências Farmacêuticas de Ribeirão Preto, Universidade de São Paulo, São Paulo, and Laboratório Nacional de Ciência e Tecnologia do Bioetanol, Campinas, Brazil

[4] Department of Biochemistry and Immunology, Ribeirão Preto Medical School, University of São Paulo, 14049-900 Ribeirão Preto, SP, Brazil

关键词: Bioethanol;    Cellulases;    DIGE;    RNA-seq;    Trichoderma reesei;   

Others  :  793034
DOI  :  10.1186/1754-6834-7-41

 received in 2014-01-14, accepted in 2014-02-26,  发布年份 2014

【 摘 要 】

Background

The filamentous fungus Trichoderma reesei is a major producer of lignocellulolytic enzymes utilized by bioethanol industries. However, to achieve low cost second generation bioethanol production on an industrial scale an efficient mix of hydrolytic enzymes is required for the deconstruction of plant biomass. In this study, we investigated the molecular basis for lignocellulose-degrading enzyme production T. reesei during growth in cellulose, sophorose, and glucose.

Results

We examined and compared the transcriptome and differential secretome (2D-DIGE) of T. reesei grown in cellulose, sophorose, or glucose as the sole carbon sources. By applying a stringent cut-off threshold 2,060 genes were identified as being differentially expressed in at least one of the respective carbon source comparisons. Hierarchical clustering of the differentially expressed genes identified three possible regulons, representing 123 genes controlled by cellulose, 154 genes controlled by sophorose and 402 genes controlled by glucose. Gene regulatory network analyses of the 692 genes differentially expressed between cellulose and sophorose, identified only 75 and 107 genes as being specific to growth in sophorose and cellulose, respectively. 2D-DIGE analyses identified 30 proteins exclusive to sophorose and 37 exclusive to cellulose. A correlation of 70.17% was obtained between transcription and secreted protein profiles.

Conclusions

Our data revealed new players in cellulose degradation such as accessory proteins with non-catalytic functions secreted in different carbon sources, transporters, transcription factors, and CAZymes, that specifically respond in response to either cellulose or sophorose.

【 授权许可】

   
2014 dos Santos Castro et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

【 参考文献 】

• [1]Pessoa-Jr A, Roberto IC, Menossi M, dos Santos RR, Filho SO, Penna TC: Perspectives on bioenergy and biotechnology in Brazil. Appl Biochem Biotechnol 2005, 121–124:59-70.
• [2]Mosier N, Wyman C, Dale B, Elander R, Lee YY, Holtzapple M, Ladisch M: Features of promising technologies for pretreatment of lignocellulosic biomass. Bioresour Technol 2005, 96:673-686.
• [3]Ojeda K, Kafarov V: Exergy analysis of enzymatic hydrolysis reactors for transformation of lignocellulosic biomass to bioethanol. Chem Eng J 2009, 154:390-395.
• [4]Soccol CR, Vandenberghe LPD, Medeiros ABP, Karp SG, Buckeridge M, Ramos LP, Pitarelo AP, Ferreira-Leitao V, Gottschalk LMF, Ferrara MA, Bon EPD, de Moraes LMP, Araujo JD, Torres FAG: Bioethanol from lignocelluloses: Status and perspectives in Brazil. Bioresource Technology 2010, 101:4820-4825.
• [5]Kubicek CP, Herrera-Estrella A, Seidl-Seiboth V, Martinez DA, Druzhinina IS, Thon M, Zeilinger S, Casas-Flores S, Horwitz BA, Mukherjee PK, Mukherjee M, Kredics L, Alcaraz LD, Aerts A, Antal Z, Atanasova L, Cervantes-Badillo MG, Challacombe J, Chertkov O, McCluskey K, Coulpier F, Deshpande N, von Dohren H, Ebbole DJ, Esquivel-Naranjo EU, Fekete E, Flipphi M, Glaser F, Gomez-Rodriguez EY, Gruber S, et al.: Comparative genome sequence analysis underscores mycoparasitism as the ancestral life style of Trichoderma. Genome biology 2011, 12:R40. BioMed Central Full Text
• [6]Schuster A, Schmoll M: Biology and biotechnology of Trichoderma. Appl Microbiol Biotechnol 2010, 87:787-799.
• [7]Martinez D, Berka RM, Henrissat B, Saloheimo M, Arvas M, Baker SE, Chapman J, Chertkov O, Coutinho PM, Cullen D, Danchin EG, Grigoriev IV, Harris P, Jackson M, Kubicek CP, Han CS, Ho I, Larrondo LF, de Leon AL, Magnuson JK, Merino S, Misra M, Nelson B, Putnam N, Robbertse B, Salamov AA, Schmoll M, Terry A, Thayer N, Westerholm-Parvinen A, et al.: Genome sequencing and analysis of the biomass-degrading fungus Trichoderma reesei (syn. Hypocrea jecorina). Nat Biotechnol 2008, 26:553-560.
• [8]Saloheimo M, Nakari-Setala T, Tenkanen M, Penttila M: cDNA cloning of a Trichoderma reesei cellulase and demonstration of endoglucanase activity by expression in yeast. Eur J Biochem 1997, 249:584-591.
• [9]Hakkinen M, Arvas M, Oja M, Aro N, Penttila M, Saloheimo M, Pakula TM: Re-annotation of the CAZy genes of Trichoderma reesei and transcription in the presence of lignocellulosic substrates. Microb Cell Fact 2012, 11:134. BioMed Central Full Text
• [10]Verbeke J, Coutinho P, Mathis H, Quenot A, Record E, Asther M, Heiss-Blanquet S: Transcriptional profiling of cellulase and expansin-related genes in a hypercellulolytic Trichoderma reesei. Biotechnol Lett 2009, 31:1399-1405.
• [11]Mandels M, Parrish FW, Reese ET: Sophorose as an inducer of cellulase in Trichoderma viride. J Bacteriol 1962, 83:400-408.
• [12]Kubicek CP, Messner R, Gruber F, Mach RL, Kubicek-Pranz EM: The Trichoderma cellulase regulatory puzzle: from the interior life of a secretory fungus. Enzyme Microb Technol 1993, 15:90-99.
• [13]Seiboth B, Hakola S, Mach RL, Suominen PL, Kubicek CP: Role of four major cellulases in triggering of cellulase gene expression by cellulose in Trichoderma reesei. J Bacteriol 1997, 179:5318-5320.
• [14]Foreman PK, Brown D, Dankmeyer L, Dean R, Diener S, Dunn-Coleman NS, Goedegebuur F, Houfek TD, England GJ, Kelley AS, Meerman HJ, Mitchell T, Mitchinson C, Olivares HA, Teunissen PJ, Yao J, Ward M: Transcriptional regulation of biomass-degrading enzymes in the filamentous fungus Trichoderma reesei. The Journal of biological chemistry 2003, 278:31988-31997.
• [15]Schmoll M, Kubicek CP: Regulation of trichoderma cellulase formation: lessons in molecular biology from an industrial fungus.A review. Acta Microbiol Immunol Hung 2003, 50:125-145.
• [16]El-Gogary S, Leite A, Crivellaro O, Eveleigh DE, El-Dorry H: Mechanism by which cellulose triggers cellobiohydrolase I gene expression in Trichoderma reesei. Proc Natl Acad Sci USA 1989, 86:6138-6141.
• [17]Nogawa M, Goto M, Okada H, Morikawa Y: L-Sorbose induces cellulase gene transcription in the cellulolytic fungus Trichoderma reesei. Curr Genet 2001, 38:329-334.
• [18]Chambergo FS, Bonaccorsi ED, Ferreira AJ, Ramos AS, Ferreira Junior JR, Abrahao-Neto J, Farah JP, Farah JP, El-Dorry H: Elucidation of the metabolic fate of glucose in the filamentous fungus Trichoderma reesei using expressed sequence tag (EST) analysis and cDNA microarrays. J Biol Chem 2002, 277:13983-13988.
• [19]Kubicek CP: Systems biological approaches towards understanding cellulase production by Trichoderma reesei. J Biotechnol 2013, 163:133-142.
• [20]Kubicek CP, Mikus M, Schuster A, Schmoll M, Seiboth B: Metabolic engineering strategies for the improvement of cellulase production by Hypocrea jecorina. Biotechnol Biofuels 2009, 2:19. BioMed Central Full Text
• [21]Castro LD, Antonieto AC, Pedersoli WR, Silva-Rocha R, Persinoti GF, Silva RN: Expression pattern of cellulolytic and xylanolytic genes regulated by transcriptional factors XYR1 and CRE1 are affected by carbon source in Trichoderma reesei. Gene Expr Patterns 2014, 14:88-95.
• [22]Bischof R, Fourtis L, Limbeck A, Gamauf C, Seiboth B, Kubicek CP: Comparative analysis of the Trichoderma reesei transcriptome during growth on the cellulase inducing substrates wheat straw and lactose. Biotechnol Biofuels 2013, 6:127. BioMed Central Full Text
• [23]Pao SS, Paulsen IT, Saier MH: Major facilitator superfamily. Microbiol Mol Biol R 1998, 62:1-34.
• [24]Boyce KJ, Andrianopoulos A: Morphogenetic circuitry regulating growth and development in the dimorphic pathogen Penicillium marneffei. Eukaryot Cell 2013, 12:154-160.
• [25]Yao J, Bajjalieh SM: SVOP is a nucleotide binding protein. PLoS One 2009, 4:e5315.
• [26]Wieczorke R, Krampe S, Weierstall T, Freidel K, Hollenberg CP, Boles E: Concurrent knock-out of at least 20 transporter genes is required to block uptake of hexoses in Saccharomyces cerevisiae. FEBS Lett 1999, 464:123-128.
• [27]Zhang W, Kou Y, Xu J, Cao Y, Zhao G, Shao J, Wang H, Wang Z, Bao X, Chen G, Liu W: Two major facilitator superfamily sugar transporters from trichoderma reesei and their roles in induction of cellulase biosynthesis. J Biol Chem 2013, 288:32861-32872.
• [28]Ries L, Pullan ST, Delmas S, Malla S, Blythe MJ, Archer DB: Genome-wide transcriptional response of Trichoderma reesei to lignocellulose using RNA sequencing and comparison with Aspergillus niger. BMC Genomics 2013, 14:541. BioMed Central Full Text
• [29]Ivanova C, Baath JA, Seiboth B, Kubicek CP: Systems analysis of lactose metabolism in Trichoderma reesei identifies a lactose permease that is essential for cellulase induction. PLoS One 2013, 8:e62631.
• [30]Du J, Li S, Zhao H: Discovery and characterization of novel d-xylose-specific transporters from Neurospora crassa and Pichia stipitis. Mol Biosyst 2010, 6:2150-2156.
• [31]Sun J, Tian C, Diamond S, Glass NL: Deciphering transcriptional regulatory mechanisms associated with hemicellulose degradation in Neurospora crassa. Eukaryot Cell 2012, 11:482-493.
• [32]Glass NL, Palma-Guerrero J, Jonkers W, Leeder A, Hall C, Kowbel D, Taylor JW, Brem R: Revealing fungal communication modules by genomics, population genomics, and genome wide association studies in Neurospora crassa. Phytopathology 2013, 103:186-187.
• [33]Mukherjee PK, Horwitz BA, Herrera-Estrella A, Schmoll M, Kenerley CM: Trichoderma research in the genome era. Annu Rev Phytopathol 2013, 51:105-129.
• [34]Furukawa T, Shida Y, Kitagami N, Mori K, Kato M, Kobayashi T, Okada H, Ogasawara W, Morikawa Y: Identification of specific binding sites for XYR1, a transcriptional activator of cellulolytic and xylanolytic genes in Trichoderma reesei. Fungal Genet Biol 2009, 46:564-574.
• [35]Strauss J, Mach RL, Zeilinger S, Hartler G, Stoffler G, Wolschek M, Kubicek CP: Cre1, the carbon catabolite repressor protein from Trichoderma reesei. FEBS Lett 1995, 376:103-107.
• [36]Portnoy T, Margeot A, Seidl-Seiboth V, Le Crom S, Ben Chaabane F, Linke R, Seiboth B, Kubicek CP: Differential regulation of the cellulase transcription factors XYR1, ACE2, and ACE1 in Trichoderma reesei strains producing high and low levels of cellulase. Eukaryot Cell 2011, 10:262-271.
• [37]Nitta M, Furukawa T, Shida Y, Mori K, Kuhara S, Morikawa Y, Ogasawara W: A new Zn(II)(2)Cys(6)-type transcription factor BglR regulates beta-glucosidase expression in Trichoderma reesei. Fungal Genet Biol 2012, 49:388-397.
• [38]Martinez-Antonio A, Collado-Vides J: Identifying global regulators in transcriptional regulatory networks in bacteria. Curr Opin Microbiol 2003, 6:482-489.
• [39]Seiboth B, Karimi RA, Phatale PA, Linke R, Hartl L, Sauer DG, Smith KM, Baker SE, Freitag M, Kubicek CP: The putative protein methyltransferase LAE1 controls cellulase gene expression in Trichoderma reesei. Mol Microbiol 2012, 84:1150-1164.
• [40]Karimi-Aghcheh R, Bok JW, Phatale PA, Smith KM, Baker SE, Lichius A, Omann M, Zeilinger S, Seiboth B, Rhee C, Keller NP, Freitag M, Kubicek CP: Functional analyses of Trichoderma reesei LAE1 reveal conserved and contrasting roles of this regulator. G3 (Bethesda) 2013, 3:369-378.
• [41]Rossi A, Cruz AH, Santos RS, Silva PM, Silva EM, Mendes NS, Martinez-Rossi NM: Ambient pH sensing in filamentous fungi: pitfalls in elucidating regulatory hierarchical signaling networks. IUBMB Life 2013, 65:930-935.
• [42]Li C, Yang Z, He Can Zhang R, Zhang D, Chen S, MA L: Effect of pH on cellulase production and morphology of Trichoderma reesei and the application in cellulosic material hydrolysis. J Biotechnol 2013, 168:470-477.
• [43]Mach RL, Zeilinger S: Regulation of gene expression in industrial fungi: Trichoderma. Appl Microbiol Biotechnol 2003, 60:515-522.
• [44]Gasch AP, Spellman PT, Kao CM, Carmel-Harel O, Eisen MB, Storz G, Botstein D, Brown PO: Genomic expression programs in the response of yeast cells to environmental changes. Mol Biol Cell 2000, 11:4241-4257.
• [45]Herpoel-Gimbert I, Margeot A, Dolla A, Jan G, Molle D, Lignon S, Mathis H, Sigoillot JC, Monot F, Asther M: Comparative secretome analyses of two Trichoderma reesei RUT-C30 and CL847 hypersecretory strains. Biotechnol Biofuels 2008, 1:18. BioMed Central Full Text
• [46]Jun H, Kieselbach T, Jonsson LJ: Enzyme production by filamentous fungi: analysis of the secretome of Trichoderma reesei grown on unconventional carbon source. Microb Cell Fact 2011, 10:68. BioMed Central Full Text
• [47]Adav SS, Chao LT, Sze SK: Quantitative secretomic analysis of Trichoderma reesei strains reveals enzymatic composition for lignocellulosic biomass degradation. Mol Cell Proteomics 2012, 11:M111 012419.
• [48]Tisch D, Kubicek CP, Schmoll M: New insights into the mechanism of light modulated signaling by heterotrimeric G-proteins: ENVOY acts on gna1 and gna3 and adjusts cAMP levels in Trichoderma reesei (Hypocrea jecorina). Fungal Genet Biol 2011, 48:631-640.
• [49]Druzhinina IS, Shelest E, Kubicek CP: Novel traits of Trichoderma predicted through the analysis of its secretome. FEMS Microbiol Lett 2012, 337:1-9.
• [50]Zhou QX, Xu JT, Kou YB, Lv XX, Zhang X, Zhao GL, Zhang WX, Chen GJ, Liu WF: Differential involvement of beta-glucosidases from hypocrea jecorina in rapid induction of cellulase genes by cellulose and cellobiose. Eukaryot Cell 2012, 11:1371-1381.
• [51]Znameroski EA, Coradetti ST, Roche CM, Tsai JC, Iavarone AT, Cate JHD, Glass NL: Induction of lignocellulose-degrading enzymes in Neurospora crassa by cellodextrins. Proc Natl Acad Sci USA 2012, 109:6012-6017.
• [52]Gielkens MM, Dekkers E, Visser J, de Graaff LH: Two cellobiohydrolase-encoding genes from Aspergillus niger require D-xylose and the xylanolytic transcriptional activator XlnR for their expression. Appl Environ Microbiol 1999, 65:4340-4345.
• [53]Schmoll M, Schuster A, Silva Rdo N, Kubicek CP: The G-alpha protein GNA3 of Hypocrea jecorina (Anamorph Trichoderma reesei) regulates cellulase gene expression in the presence of light. Eukaryot Cell 2009, 8:410-420.
• [54]Li H, Durbin R: Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 2009, 25:1754-1760.
• [55]Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R, Proc GPD: The sequence alignment/Map format and SAMtools. Bioinformatics 2009, 25:2078-2079.
• [56]Thorvaldsdottir H, Robinson JT, Mesirov JP: Integrative genomics viewer (IGV): high-performance genomics data visualization and exploration. Brief Bioinform 2013, 14:178-192.
• [57]Atanasova L, Jaklitsch WM, Komon-Zelazowska M, Kubicek CP, Druzhinina IS: Clonal species Trichoderma parareesei sp. nov. likely resembles the ancestor of the cellulase producer Hypocrea jecorina/T. reesei. Appl Environ Microbiol 2010, 76:7259-7267.
• [58]Anders S, Huber W: Differential expression analysis for sequence count data. Genome Biol 2010, 11:R106. BioMed Central Full Text
• [59]Vencio RZ, Koide T, Gomes SL, Pereira CA: BayGO: bayesian analysis of ontology term enrichment in microarray data. BMC Bioinformatics 2006, 7:86. BioMed Central Full Text
• [60]Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T: Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 2003, 13:2498-2504.
• [61]Steiger MG, Mach RL, Mach-Aigner AR: An accurate normalization strategy for RT-qPCR in Hypocrea jecorina (Trichoderma reesei). J Biotechnol 2010, 145:30-37.
• [62]Livak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(T)(-Delta Delta C) method. Methods 2001, 25:402-408.
• [63]MacLean B, Eng JK, Beavis RC, McIntosh M: General framework for developing and evaluating database scoring algorithms using the TANDEM search engine. Bioinformatics 2006, 22:2830-2832.
• [64]Keller A, Nesvizhskii AI, Kolker E, Aebersold R: Empirical statistical model to estimate the accuracy of peptide identifications made by MS/MS and database search. Anal Chem 2002, 74:5383-5392.
• [65]Nesvizhskii AI, Keller A, Kolker E, Aebersold R: A statistical model for identifying proteins by tandem mass spectrometry. Anal Chem 2003, 75:4646-4658.