A transcriptomic analysis of Neurospora crassa using five major crop residues and the novel role of the sporulation regulator rca-1 in lignocellulase production

Biotechnology for Biofuels

Yanhe Ma¹  Chaoguang Tian¹  Jingen Li²  Wenliang Sun¹  Pengli Cai²  Bang Wang² 

[1]Key Laboratory of Systems Microbial Biotechnology, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, China

[2]University of Chinese Academy of Sciences, Beijing 100049, China

关键词: rca-1;    Biomass regulon;    Transcriptional profiling;    Crop residues;    Neurospora crassa;   

Others  :  1128579
DOI  :  10.1186/s13068-015-0208-0

 received in 2014-09-10, accepted in 2015-01-20,  发布年份 2015

【 摘 要 】

Background

Crop residue is an abundant, low-cost plant biomass material available worldwide for use in the microbial production of enzymes, biofuels, and valuable chemicals. However, the diverse chemical composition and complex structure of crop residues are more challenging for efficient degradation by microbes than are homogeneous polysaccharides. In this study, the transcriptional responses of Neurospora crassa to various plant straws were analyzed using RNA-Seq, and novel beneficial factors for biomass-induced enzyme production were evaluated.

Results

Comparative transcriptional profiling of N. crassa grown on five major crop straws of China (barley, corn, rice, soybean, and wheat straws) revealed a highly overlapping group of 430 genes, the biomass commonly induced core set (BICS). A large proportion of induced carbohydrate-active enzyme (CAZy) genes (82 out of 113) were also conserved across the five plant straws. Excluding 178 genes within the BICS that were also upregulated under no-carbon conditions, the remaining 252 genes were defined as the biomass regulon (BR). Interestingly, 88 genes were only induced by plant biomass and not by three individual polysaccharides (Avicel, xylan, and pectin); these were denoted as the biomass unique set (BUS). Deletion of one BUS gene, the transcriptional regulator rca-1, significantly improved lignocellulase production using plant biomass as the sole carbon source, possibly functioning via de-repression of the regulator clr-2. Thus, this result suggests that rca-1 is a potential engineering target for biorefineries, especially for plant biomass direct microbial conversion processes.

Conclusions

Transcriptional profiling revealed a large core response to different sources of plant biomass in N. crassa. The sporulation regulator rca-1 was identified as beneficial for biomass-based enzyme production.

【 授权许可】

   
2015 Wang et al.; licensee BioMed Central.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

Figure 5.

Figure 6.

Figure 7.

Figure 8.

Figure 9.

【 参考文献 】

• [1]Kubicek CP: Fungi and lignocellulosic biomass. John Wiley & Sons, New York; 2012.
• [2]Carroll A, Somerville C: Cellulosic biofuels. Annu Rev Plant Biol. 2009, 60:165-82.
• [3]Sarkar N, Ghosh SK, Bannerjee S, Aikat K: Bioethanol production from agricultural wastes: an overview. Renew Energ. 2012, 37:19-27.
• [4]Menon V, Rao M: Trends in bioconversion of lignocellulose: biofuels, platform chemicals & biorefinery concept. Prog Energ Combust. 2012, 38:522-50.
• [5]Popper ZA, Michel G, Hervé C, Domozych DS, Willats WGT, Tuohy MG, et al.: Evolution and diversity of plant cell walls: from algae to flowering plants. Annu Rev Plant Biol. 2011, 62:567-90.
• [6]Alvira P, Tomás-Pejó E, Ballesteros M, Negro MJ: Pretreatment technologies for an efficient bioethanol production process based on enzymatic hydrolysis: a review. Bioresour Technol. 2010, 101:4851-61.
• [7]Parisutham V, Kim TH, Lee SK: Feasibilities of consolidated bioprocessing microbes: from pretreatment to biofuel production. Bioresour Technol. 2014, 161:431-40.
• [8]Lynd LR, Zyl WH, McBride JE, Laser M: Consolidated bioprocessing of cellulosic biomass: an update. Curr Opin Biotechnol. 2005, 16:577-83.
• [9]Roche CM, Glass NL, Blanch HW, Clark DS: Engineering the filamentous fungus Neurospora crassa for lipid production from lignocellulosic biomass. Biotechnol Bioeng. 2014, 111:1097-107.
• [10]Xu Q, Singh A, Himmel ME: Perspectives and new directions for the production of bioethanol using consolidated bioprocessing of lignocellulose. Curr Opin Biotechnol. 2009, 20:364-71.
• [11]Kolbusz MA, Di Falco M, Ishmael N, Marqueteau S, Moisan M-C, Baptista CS, et al.: Transcriptome and exoproteome analysis of utilization of plant-derived biomass by Myceliophthora thermophila. Fungal Genet Biol. 2014, 72:10-20.
• [12]Tian C, Beeson WT, Iavarone AT, Sun J, Marletta MA, Cate JHD, et al.: Systems analysis of plant cell wall degradation by the model filamentous fungus Neurospora crassa. Proc Natl Acad Sci U S A. 2009, 106:22157-62.
• [13]Delmas S, Pullan ST, Gaddipati S, Kokolski M, Malla S, Blythe MJ, et al.: Uncovering the genome-wide transcriptional responses of the filamentous fungus Aspergillus niger to lignocellulose using RNA sequencing. PLoS Genet. 2012, 8:e1002875.
• [14]Berka RM, Grigoriev IV, Otillar R, Salamov A, Grimwood J, Reid I, et al.: Comparative genomic analysis of the thermophilic biomass-degrading fungi Myceliophthora thermophila and Thielavia terrestris. Nat Biotech. 2011, 29:922-7.
• [15]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
• [16]Ries L, Pullan S, Delmas S, Malla S, Blythe M, Archer D: 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
• [17]Znameroski EA, Glass NL: Using a model filamentous fungus to unravel mechanisms of lignocellulose deconstruction. Biotechnol Biofuels. 2013, 6:6. BioMed Central Full Text
• [18]Colot HV: A high-throughput gene knockout procedure for Neurospora reveals functions for multiple transcription factors. Proc Natl Acad Sci U S A. 2006, 103:10352-7.
• [19]Dunlap JC, Borkovich KA, Henn MR, Turner GE, Sachs MS, Glass NL, et al.: Enabling a community to dissect an organism: overview of the Neurospora functional genomics project. Adv Genet. 2007, 57:49-96.
• [20]Coradetti ST, Craig JP, Xiong Y, Shock T, Tian C, Glass NL: Conserved and essential transcription factors for cellulase gene expression in ascomycete fungi. Proc Natl Acad Sci U S A. 2012, 109:7397-402.
• [21]Sun J, Tian C, Diamond S, Glass NL: Deciphering transcriptional regulatory mechanisms associated with hemicellulose degradation in Neurospora crassa. Eukaryot Cell. 2012, 11:482-93.
• [22]Benz JP, Chau BH, Zheng D, Bauer S, Glass NL, Somerville CR: A comparative systems analysis of polysaccharide-elicited responses in Neurospora crassa reveals carbon source-specific cellular adaptations. Mol Microbiol. 2014, 91:275-99.
• [23]Glass NL, Schmoll M, Cate JH, Coradetti S: Plant cell wall deconstruction by ascomycete fungi. Annu Rev Microbiol. 2013, 67:477-98.
• [24]Gang L, Lei S: Quantitative appraisal of biomass energy and its geographical distribution in China. J Nat Resour. 2007, 22:9-19.
• [25]Kim S, Dale BE: Global potential bioethanol production from wasted crops and crop residues. Biomass Bioenerg. 2004, 26:361-75.
• [26]Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, Henrissat B: The Carbohydrate-Active EnZymes database (CAZy): an expert resource for glycogenomics. Nucleic Acids Res. 2009, 37:D233-8.
• [27]Feng J, Meyer CA, Wang Q, Liu JS, Liu XS, Zhang Y: GFOLD: a generalized fold change for ranking differentially expressed genes from RNA-seq data. Bioinformatics. 2012, 28:2782-8.
• [28]Wang L, Feng Z, Wang X, Wang X, Zhang X: DEGseq: an R package for identifying differentially expressed genes from RNA-seq data. Bioinformatics. 2010, 26:136-8.
• [29]Ruepp A, Zollner A, Maier D, Albermann K, Hani J, Mokrejs M, et al.: The FunCat, a functional annotation scheme for systematic classification of proteins from whole genomes. Nucleic Acids Res. 2004, 32:5539-45.
• [30]Seo J, Bakay M, Chen Y-W, Hilmer S, Shneiderman B, Hoffman EP: Interactively optimizing signal-to-noise ratios in expression profiling: project-specific algorithm selection and detection p-value weighting in affymetrix microarrays. Bioinformatics. 2004, 20:2534-44.
• [31]Levasseur A, Drula E, Lombard V, Coutinho PM, Henrissat B: Expansion of the enzymatic repertoire of the CAZy database to integrate auxiliary redox enzymes. Biotechnol Biofuels. 2013, 6:41. BioMed Central Full Text
• [32]Shen W-C, Wieser J, Adams TH, Ebbole DJ: The Neurospora rca-1 gene complements an aspergillus flbD sporulation mutant but has no identifiable role in Neurospora sporulation. Genetics. 1998, 148:1031-41.
• [33]Sun J, Glass NL: Identification of the CRE-1 Cellulolytic regulon in Neurospora crassa. PLoS ONE. 2011, 6:e25654.
• [34]Wieser J, Adams TH. flbD encodes a Myb-like DNA-binding protein that coordinates initiation of Aspergillus nidulans conidiophore development. Genes Dev. 1995;9:491–502.
• [35]Qin Y, Bao L, Gao M, Chen M, Lei Y, Liu G, et al.: Penicillium decumbens BrlA extensively regulates secondary metabolism and functionally associates with the expression of cellulase genes. Appl Microbiol Biotechnol. 2013, 97:10453-67.
• [36]Mathelier A, Zhao X, Zhang AW, Parcy F, Worsley-Hunt R, Arenillas DJ, et al.: JASPAR 2014: an extensively expanded and updated open-access database of transcription factor binding profiles. Nucleic Acids Res. 2014, 42:D142-7.
• [37]Thomas-Chollier M, Defrance M, Medina-Rivera A, Sand O, Herrmann C, Thieffry D, et al.: RSAT 2011: regulatory sequence analysis tools. Nucleic Acids Res. 2011, 39:W86-91.
• [38]McCluskey K: The Fungal Genetics Stock Center: from molds to molecules. Adv Appl Microbiol. 2003, 52:245-62.
• [39]Vogel HJ: A convenient growth medium for Neurospora. Microb Genet Bull. 1956, 13:42-6.
• [40]Galagan JE, Calvo SE, Borkovich KA, Selker EU, Read ND, Jaffe D, et al.: The genome sequence of the filamentous fungus Neurospora crassa. Nature. 2003, 422:859-68.
• [41]Trapnell C, Roberts A, Goff L, Pertea G, Kim D, Kelley DR, et al.: Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc. 2012, 7:562-78.
• [42]Anders S, Pyl PT, Huber W: HTSeq - a Python framework to work with high-throughput sequencing data. Bioinformatics. 2015, 31:166-9.
• [43]Mortazavi A, Williams BA, McCue K, Schaeffer L, Wold B: Mapping and quantifying mammalian transcriptomes by RNA-Seq. Nat Methods. 2008, 5:621-8.
• [44]Anders S, Huber W: Differential expression analysis for sequence count data. Genome Biol. 2010, 11:R106. BioMed Central Full Text
• [45]Bauer S, Ibáñez AB: Rapid determination of cellulose. Biotechnol Bioeng. 2014, 111:2355-7.
• [46]Updegraff DM: Semimicro determination of cellulose in biological materials. Anal Biochem. 1969, 32:420-4.