Kinetic transcriptome analysis reveals an essentially intact induction system in a cellulase hyper-producer Trichoderma reesei strain

Biotechnology for Biofuels

Dante Poggi-Parodi²  Frédérique Bidard⁵  Aurélie Pirayre⁵  Thomas Portnoy⁴  Corinne Blugeon⁴  Bernhard Seiboth³  Christian P Kubicek¹  Stéphane Le Crom⁴  Antoine Margeot⁵ 

[1] Austrian Center of Industrial Biotechnology, Graz, 8010, Austria

[2] Sorbonne Universités, UPMC Univ Paris 06, Institut de Biologie Paris-Seine (IBPS), Paris, F-75005, France

[3] Research Division Biotechnology and Microbiology, Institute of Chemical Engineering, Technische Universität Wien, Getreidemarkt 9/166, Vienna, A- 1060, Austria

[4] Ecole Normale Supérieure, Institut de Biologie de l’ENS, IBENS, CNRS, UMR 8197, Paris F-75005, France

[5] IFP Energies nouvelles, 1-4 avenue de Bois-Préau, Rueil-Malmaison, 92852, France

关键词: Systems biology;    Transcriptome;    Trichoderma reesei;    Fed-batch;    Cellulase;    Biofuels;   

Others  :  1084197
DOI  :  10.1186/s13068-014-0173-z

 received in 2014-07-07, accepted in 2014-11-18,  发布年份 2014

【 摘 要 】

Background

The filamentous fungus Trichoderma reesei is the main industrial cellulolytic enzyme producer. Several strains have been developed in the past using random mutagenesis, and despite impressive performance enhancements, the pressure for low-cost cellulases has stimulated continuous research in the field. In this context, comparative study of the lower and higher producer strains obtained through random mutagenesis using systems biology tools (genome and transcriptome sequencing) can shed light on the mechanisms of cellulase production and help identify genes linked to performance. Previously, our group published comparative genome sequencing of the lower and higher producer strains NG 14 and RUT C30. In this follow-up work, we examine how these mutations affect phenotype as regards the transcriptome and cultivation behaviour.

Results

We performed kinetic transcriptome analysis of the NG 14 and RUT C30 strains of early enzyme production induced by lactose using bioreactor cultivations close to an industrial cultivation regime. RUT C30 exhibited both earlier onset of protein production (3 h) and higher steady-state productivity. A rather small number of genes compared to previous studies were regulated (568), most of them being specific to the NG 14 strain (319). Clustering analysis highlighted similar behaviour for some functional categories and allowed us to distinguish between induction-related genes and productivity-related genes. Cross-comparison of our transcriptome data with previously identified mutations revealed that most genes from our dataset have not been mutated. Interestingly, the few mutated genes belong to the same clusters, suggesting that these clusters contain genes playing a role in strain performance.

Conclusions

This is the first kinetic analysis of a transcriptomic study carried out under conditions approaching industrial ones with two related strains of T. reesei showing distinctive cultivation behaviour. Our study sheds some light on some of the events occurring in these strains following induction by lactose. The fact that few regulated genes have been affected by mutagenesis suggests that the induction mechanism is essentially intact compared to that for the wild-type isolate QM6a and might be engineered for further improvement of T. reesei. Genes from two specific clusters might be potential targets for such genetic engineering.

【 授权许可】

   
2014 Poggi-Parodi et al.; licensee BioMed Central.

【 图 表 】

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【 参考文献 】

• [1]Vinci VA, Byng G: Strain Improvement by Nonrecombinant Methods. Volume 2. ASM, Washington, DC; 1999.
• [2]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
• [3]Peterson R, Nevalainen H: Trichoderma reesei RUT-C30 - thirty years of strain improvement.Microbiology (Reading, England) 2011:58–68
• [4]Stricker AR, Mach RL, De Graaff LH: Regulation of transcription of cellulases- and hemicellulases-encoding genes in Aspergillus niger and Hypocrea jecorina (Trichoderma reesei). Appl Microbiol Biotechnol 2008, 78:211-220.
• [5]Stricker AR, Grosstessner-Hain K, Würleitner E, Mach RL: Xyr1 (xylanase regulator 1) regulates both the hydrolytic enzyme system and D-xylose metabolism in Hypocrea jecorina. Eukaryot Cell 2006, 5:2128-2137.
• [6]Mach-Aigner AR, Pucher ME, Steiger MG, Bauer GE, Preis SJ, Mach RL: Transcriptional regulation of xyr1, encoding the main regulator of the xylanolytic and cellulolytic enzyme system in Hypocrea jecorina. Appl Environ Microbiol 2008, 74:6554-6562.
• [7]Strauss J, Mach RL, Zeilinger S, Hartler G, Stöffler G, Wolschek M, Kubicek C: Crel, the carbon catabolite repressor protein from Trichoderma reesei. FEBS Lett 1995, 376:103-107.
• [8]Seidl V, Gamauf C, Druzhinina IS, Seiboth B, Hartl L, Kubicek CP: The Hypocrea jecorina (Trichoderma reesei) hypercellulolytic mutant RUT C30 lacks a 85 kb (29 gene-encoding) region of the wild-type genome. BMC Genomics 2008, 9:327. BioMed Central Full Text
• [9]Portnoy T, Margeot A, Linke R, Atanasova L, Fekete E, Sándor E, Hartl L, Karaffa L, Druzhinina IS, Seiboth B, Le Crom S, Kubicek CP: The CRE1 carbon catabolite repressor of the fungus Trichoderma reesei: a master regulator of carbon assimilation. BMC Genomics 2011, 12:269. BioMed Central Full Text
• [10]Nakari-Setala T, Paloheimo M, Kallio J, Vehmaanpera J, Penttila M, Saloheimo M: Genetic modification of carbon catabolite repression in Trichoderma reesei for improved protein production. Appl Environ Microbiol 2009, 75:4853.
• [11]Ilmén M, Thrane C, Penttilä M: The glucose repressor gene cre1 of Trichoderma: isolation and expression of a full-length and a truncated mutant form. Mol Gen Genet 1996, 251:451-460.
• [12]Lichius A, Seidl-Seiboth V, Seiboth B, Kubicek CP: Nucleo-cytoplasmic shuttling dynamics of the transcriptional regulators XYR1 and CRE1 under conditions of cellulase and xylanase gene expression in Trichoderma reesei. Mol Microbiol 2014, 94:1162.
• [13]Saloheimo A, Aro N, Ilmén M, Penttilä M: Isolation of the ace1 gene encoding a Cys2-His2transcription factor involved in regulation of activity of the cellulase promoter cbh1 of Trichoderma reesei .J Biol Chem 2000, 275:5817–5825.
• [14]Aro N, Saloheimo A, Ilmén M, Penttilä M: ACEII, a novel transcriptional activator involved in regulation of cellulase and xylanase genes of Trichoderma reesei. J Biol Chem 2001, 276:24309-24314.
• [15]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.
• [16]Denton JA, Kelly JM: Disruption of Trichoderma reesei cre2, encoding an ubiquitin C-terminal hydrolase, results in increased cellulase activity. BMC Biotechnol 2011, 11:103. BioMed Central Full Text
• [17]Häkkinen M, Valkonen MJ, Westerholm-Parvinen A, Aro N, Arvas M, Vitikainen M, Penttilä M, Saloheimo M, Pakula TM: Screening of candidate regulators for cellulase and hemicellulase production in Trichoderma reesei and identification of a factor essential for cellulase production. Biotechnol Biofuels 2014, 7:14. BioMed Central Full Text
• [18]Pakula TM, Salonen K, Uusitalo J, Penttilä M: The effect of specific growth rate on protein synthesis and secretion in the filamentous fungus Trichoderma reesei. Microbiology 2005, 151(Pt 1):135-143.
• [19]Herpoël-Gimbert I, Margeot A, Dolla A, Jan G, Mollé D, Lignon S, Mathis H, Sigoillot J-C, 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
• [20]Martinez D, Berka RM, Henrissat B, Saloheimo M, Arvas M, Baker SE, Chapman J, Chertkov O, Coutinho PM, Cullen D, Danchin EGJ, 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.
• [21]Le Crom S, Schackwitz W, Pennacchio L, Magnuson JK, Culley DE, Collett JR, Martin J, Druzhinina IS, Mathis H, Monot F, Seiboth B, Cherry B, Rey M, Berka R, Kubicek CP, Baker SE, Margeot A: Tracking the roots of cellulase hyperproduction by the fungus Trichoderma reesei using massively parallel DNA sequencing. Proc Natl Acad Sci U S A 2009, 106:16151-16156.
• [22]Koike H, Aerts A, LaButti K, Grigoriev IV, Baker SE: Comparative genomics analysis of Trichoderma reesei strains. Ind Biotechnol 2013, 9:352-367.
• [23]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 β-glucosidase expression in Trichoderma reesei. Fungal Genet Biol 2012, 49:388-397.
• [24]Porciuncula JDO, Furukawa T, Shida Y, Mori K, Kuhara S, Morikawa Y, Ogasawara W: Identification of major facilitator transporters involved in cellulase production during lactose culture of Trichoderma reesei PC-3-7. Biosci Biotechnol Biochem 2013, 77:1014.
• [25]Vitikainen M, Arvas M, Pakula T, Oja M, Penttilä M, Saloheimo M: Array comparative genomic hybridization analysis of Trichoderma reesei strains with enhanced cellulase production properties. BMC Genomics 2010, 11:441. BioMed Central Full Text
• [26]Ivanova C, Bååth 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.
• [27]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
• [28]Dos Santos CL, Pedersoli WR, Antoniêto ACC, Steindorff AS, Silva-Rocha R, Martinez-Rossi NM, Rossi A, Brown NA, Goldman GH, Faça VM: Comparative metabolism of cellulose, sophorose and glucose in Trichoderma reesei using high-throughput genomic and proteomic analyses. Biotechnol Biofuels 2014, 7:1-18.
• [29]Jourdier E, Poughon L, Larroche C, Monot F, Ben Chaabane F: A new stoichiometric miniaturization strategy for screening of industrial microbial strains: application to cellulase hyper-producing Trichoderma reesei strains. Microb Cell Fact 2012, 11:70. BioMed Central Full Text
• [30]Jourdier E, Cohen C, Poughon L, Larroche C, Monot F, Ben Chaabane F: Cellulase activity mapping of Trichoderma reesei cultivated in sugar mixtures under fed-batch conditions. Biotechnol Biofuels 2013, 6:79. BioMed Central Full Text
• [31]Bradford MM: A rapid and sensitive method for the quantitation of microgram quantities of protein utilizing the principle of protein-dye binding. Anal Biochem 1976, 72:248-254.
• [32]Gusakov AV, Shulga TN, Chekushina AV, Sinitsyn AP: Comparison of three protein assays for purified cellulases and hemicellulases from fungi. Open J Anal Chem Res 2013, 1:1-4.
• [33]Lowry OH, Rosebrough NJ, Farr AL, Randall RJ: Protein measurement with the Folin phenol reagent. J Biol Chem 1951, 193:265-275.
• [34]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.
• [35]Hemsworth GR, Davies GJ, Walton PH: Recent insights into copper-containing lytic polysaccharide mono-oxygenases. Curr Opin Struct Biol 2013, 23:660-668.
• [36]Seiboth B, Hartl L, Salovuori N, Lanthaler K, Robson GD, Vehmaanperä J, Penttilä ME, Kubicek CP: Role of the bga1-encoded extracellular β-galactosidase of Hypocrea jecorina in cellulase induction by lactose. Appl Environ Microbiol 2005, 71:851-857.
• [37]Arvas M, Haiminen N, Smit B, Rautio J, Vitikainen M, Wiebe M, Martinez D, Chee C, Kunkel J, Sanchez C, Nelson MA, Pakula T, Saloheimo M, Penttilä M, Kivioja T: Detecting novel genes with sparse arrays. Gene 2010, 467:41-51.
• [38]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 PJM, Yao J, Ward M: Transcriptional regulation of biomass-degrading enzymes in the filamentous fungus Trichoderma reesei. J Biol Chem 2003, 278:31988-31997.
• [39]Boase NA, Kelly JM: A role for creD, a carbon catabolite repression gene from Aspergillus nidulans, in ubiquitination. Mol Microbiol 2004, 53:929-940.
• [40]Fekete E, Seiboth B, Kubicek CP, Szentirmai A, Karaffa L: Lack of aldose 1-epimerase in Hypocrea jecorina (anamorph Trichoderma reesei): a key to cellulase gene expression on lactose. Proc Natl Acad Sci U S A 2008, 105:7141-7146.
• [41]Ivanen DR, Rongjina NL, Shishlyannikov SM, Litviakova GI, Isaeva-Ivanova LS, Shabalin KA, Kulminskaya AA: Novel precipitated fluorescent substrates for the screening of cellulolytic microorganisms. J Microbiol Methods 2009, 76:295-300.
• [42]Zhang W, Kou Y, Xu J, Cao Y, Zhao G, Shao J, Wang H, Wang Z, Bao X, Chen G: Two major facilitator superfamily sugar transporters from Trichoderma reesei and their roles in induction of cellulase biosynthesis. J Biol Chem 2013, 288:32861-32872.
• [43]Warzywoda M, Larbre E, Pourqui J: Production and characterization of cellulolytic enzymes from Trichoderma reesei grown on various carbon sources. Bioresour Technol 1992, 39:125-130.
• [44]Montenecourt BS, Eveleigh DE: Preparation of mutants of Trichoderma reesei with enhanced cellulase production. Appl Environ Microbiol 1977, 34:777-782.
• [45]Eveleigh DE, Montenecourt BS: Increasing yields of extracellular enzymes. Adv Appl Microbiol 1979, 23:74.
• [46]Ries L, Belshaw NJ, Ilmén M, Penttilä ME, Alapuranen M, Archer DB: The role of CRE1 in nucleosome positioning within the cbh1 promoter and coding regions of Trichoderma reesei. Appl Microbiol Biotechnol 2014, 98:749-762.
• [47]Mello-de-Sousa TM, Gorsche R, Rassinger A, Poças-Fonseca MJ, Mach RL, Mach-Aigner AR: A truncated form of the carbon catabolite repressor 1 increases cellulase production in Trichoderma reesei. Biotechnol Biofuels 2014, 7:129. BioMed Central Full Text
• [48]Kazi FK, Fortman JA, Anex RP, Hsu DD, Aden A, Dutta A, Kothandaraman G: Techno-economic comparison of process technologies for biochemical ethanol production from corn stover. Fuel 2010, 89:S20-S28.
• [49]Ghose TK: Measurement of cellulase activities. Pure Appl Chem 1987, 59:257-268.
• [50]Jourdren L, Duclos A, Brion C, Portnoy T: Teolenn: an efficient and customizable workflow to design high-quality probes for microarray experiments. Nucleic Acids 2010, 38:e117.
• [51]Lemoine S, Combes F, Servant N, Le Crom S: Goulphar: rapid access and expertise for standard two-color microarray normalization methods. BMC Bioinformatics 2006, 7:467. BioMed Central Full Text
• [52]Smyth GK: Linear models and empirical Bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol 2004, 3:Article3.
• [53]Jourdren L, Bernard M, Dillies M-A, Le Crom S: Eoulsan: a cloud computing-based framework facilitating high throughput sequencing analyses. Bioinformatics 2012, 28:1542-1543.
• [54]Langmead B, Trapnell C, Pop M, Salzberg SL: Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 2009, 10:R25. BioMed Central Full Text
• [55]Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R: The sequence alignment/map format and SAMtools. Bioinformatics 2009, 25:2078-2079.
• [56]Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B: Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods 2008, 5:621-628.
• [57]Vaquerizas JM, Conde L, Yankilevich P, Cabezón A, Minguez P, Díaz-Uriarte R, Al-Shahrour F, Herrero J, Dopazo J: GEPAS, an experiment-oriented pipeline for the analysis of microarray gene expression data. Nucleic Acids Res 2005, 33(suppl 2):W616-W620.
• [58]Howe E, Holton K, Nair S, Schlauch D, Sinha R, Quackenbush J: MeV: MultiExperiment Viewer. In Biomedical Informatics for Cancer Research. Springer (US); 2010:267–277
• [59]Ruepp A, Zollner A, Maier D, Albermann K, Hani J, Mokrejs M, Tetko I, Güldener U, Mannhaupt G, Münsterkötter M: The FunCat, a functional annotation scheme for systematic classification of proteins from whole genomes. Nucleic Acids Res 2004, 32:5539-5545.