GSE42692
A comparative systems analysis of polysaccharide-elicited responses in Neurospora crassa reveals carbon source-specific cellular adaptations
Filamentous fungi are powerful producers of hydrolytic enzymes for the deconstruction of plant cell wall polysaccharides. However, the central question of how these sugars are perceived in the context of the complex cell wall matrix remains largely elusive. To address this question in a systematic fashion we performed an extensive comparative systems analysis of how the model filamentous fungus Neurospora crassa responds to the three main cell wall polysaccharides: pectin, hemicellulose and cellulose. We found the pectic response to be largely independent of the cellulolytic one with some overlap to hemicellulose, and in its extent surprisingly high, suggesting advantages for the fungus beyond being a mere carbon source. Our approach furthermore allowed us to identify carbon source-specific adaptations, such as the induction of the unfolded protein response on cellulose, and a commonly induced set of 29 genes likely involved in carbon scouting. Moreover, by hierarchical clustering we generated a co-expression matrix useful for the discovery of new components involved in polysaccharide utilization. This is exemplified by the identification of lat-1, which we demonstrate to encode for the physiologically relevant arabinose transporter in Neurospora. The analyses presented here are an important step towards understanding fungal degradation processes of complex biomass. Overall design: Our data are based on carbon source transfer experiments. For this, N. crassa pregrown in sucrose for 16 hrs was washed in media without carbon and then transferred to either pectin, orange peel powder (OPP), xylan, Avicel (cellulose), sucrose, or media without carbon (NoC) for another 4 hrs. Biological triplicates (pectin, Avicel, sucrose, NoC) or duplicates (OPP) were used to identify differentially expressed genes in WT. For xylan only a single library was prepared, which was found to correlate well with previously published microarray data (Sun et al. 2012; doi: 10.1128/EC.05327-11)