Engineering microbes with novel metabolic properties is a critical step for production of biofuels and biochemicals. Synthetic biology enables identification and engineering of metabolic pathways into microbes; however, knowledge of how to reroute cellular regulatory signals and metabolic flux remains lacking. Here we used network analysis of multi-omic data to dissect the mechanism of anaerobic xylose fermentation, a trait important for biochemical production from plant lignocellulose. We compared transcriptomic, proteomic, and phosphoproteomic differences across a series of strains evolved to ferment xylose under various conditions. Overall design: RNA-seq and transcriptome analysis of Azf1 deletion and over-expression (via MoBY 2.0 plasmid) in YPX -O2. Duplicate samples were collected on different days.