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Combination of Suppression Subtractive Hybridization and Microarray Technologies to Enumerate Biomass-Induced Genes in the Cellulolytic Fungus Trichoderma reesei

2005; Elsevier BV; Linguagem: Inglês

10.1016/s1874-5334(05)80014-0

1874-5334

Elena V. Bashkirova, Michael W. Rey, Randy M. Berka,

Microbial Metabolic Engineering and Bioproduction

The concerted action of many enzymes is required for the hydrolysis of cellulosic biomass. However, only a few have been identified and characterized in detail. Mixtures of isolated cellulase components have been shown to be less efficient than crude culture filtrates for the conversion of biomass to fermentable sugars. This may suggest that additional components are required for complete saccharification of biomass. Trichoderma reesei is the best-studied cellulolytic fungus. To identify new T. reesei genes involved in biomass conversion, we have employed the high throughput analysis of expression of subtractive cDNA libraries by DNA microarray technology. The cDNA libraries have been generated by suppression subtractive hybridization (SSH), which allowed not only the selection of differentially expressed mRNAs, but also the enrichment for rare mRNAs and equalization of cDNA in a pool. Messenger RNA pools from T. reesei cells grown on glucose, cellulose, or acid-pretreated corn stover (PCS) was isolated and used for construction of the SSH cDNA libraries. Three SSH libraries representing cellulose-induced, PCS-induced and PCS minus cellulose-induced transcripts were constructed. Approximately 3600 cDNA clones from three SSH libraries were amplified by high throughput rolling circle amplification (RCA) to produce DNA for microarray printing. Microarray hybridization with tester and driver probes revealed728. DNA sequence analysis and bioinformatics were used to assemble these clones into approximately 90 previously unrecognized genes/proteins. Among them we have identified a number of novel enzymes/proteins with potential direct benefit for improving biomass degradation. Thus, the combination of SSH and cDNA microarray technologies has proven to be a powerful tool for discovery of new differentially expressed genes involved in biomass utilization.