Deletion of either the regulatory gene or metabolic gene in leads to increased CAZyme gene expression on crude plant biomass.

Background: is one of the major producers of enzymes for the conversion of plant biomass to sustainable fuels and chemicals. Crude plant biomass can induce the production of CAZymes in , but there is limited understanding of how the transcriptional response to crude plant biomass is regulated. In addition, it is unknown whether induction on untreated recalcitrant crude plant biomass (with a large diversity of inducers) can be sustained for longer. We investigated the transcriptomic response of to the two industrial feedstocks, corn stover (CS) and soybean hulls (SBH), over time (4 h, 24 h and 48 h), and its regulatory basis using transcription factor deletion mutants (Δ and Δ). We also investigated whether deletion of a xylulokinase gene (Δ) from the pentose catabolic pathway that converts potential inducers could lead to increased CAZyme gene expression.

Results: By analyzing the transcriptomic responses using clustering as well as differential and cumulative expression of plant biomass degrading CAZymes, we found that corn stover induced a broader range and higher expression of CAZymes in , while SBH induced more pectinolytic and mannanolytic transcripts. XYR1 was the major TF regulating CS utilization, likely due to the significant amount of d-xylose in this substrate. In contrast, ARA1 had a stronger effect on SBH utilization, which correlates with a higher abundance of l-arabinose in SBH that activates ARA1. Blocking pentose catabolism by deletion of led to higher expression of CAZyme encoding genes on both substrates at later time points. Surprisingly, this was also observed for Δ at later time points. Many of these genes were XYR1 regulated, suggesting that inducers for this regulator accumulated over time on both substrates.

Conclusion: Our data demonstrates the complexity of the regulatory system related to plant biomass degradation in and the effect the feedstock composition has on this. Furthermore, this dataset provides leads to improve the efficiency of a enzyme cocktail, such as by the choice of substrate or by deleting to obtain higher production of plant biomass degrading CAZymes.