The ability to rationally manipulate the transcriptional states of cells would be of great use in medicine and bioengineering. We have developed an algorithm, NetSurgeon, which uses genomewide gene-regulatory networks to identify interventions that force a cell toward a desired expression state. We first validated NetSurgeon extensively on existing datasets. Next, we used NetSurgeon to select transcription factor deletions aimed at improving ethanol production in Saccharomyces cerevisiae cultures that are catabolizing xylose. We reasoned that interventions that move the transcriptional state of cells using xylose toward that of cells producing large amounts of ethanol from glucose might improve xylose fermentation. Some of the interventions selected by NetSurgeon successfully promoted a fermentative transcriptional state in the absence of glucose, resulting in strains with a 2.7-fold increase in xylose import rates, a 4-fold improvement in xylose integration into central carbon metabolism, or a 1.3-fold increase in ethanol production rate. We conclude by presenting an integrated model of transcriptional regulation and metabolic flux that will enable future efforts aimed at improving xylose fermentation to prioritize functional regulators of central carbon metabolism.gene-regulatory networks | regulatory systems biology | transcriptome | engineering | Saccharomyces cerevisiae T he central premise of regulatory systems biology is that a systematic map of a cell's regulatory machinery will enable us to understand, predict, and rationally manipulate the cell's state or behavior. Manipulation of cellular state has many promising applications, including stem cell biology and regenerative medicine, biofuel production, and gene therapy. Progress toward cellular state control has been driven by both the systems biology and the synthetic biology research communities. Systems biology has produced whole-genome regulatory network maps (1), but relatively little research has focused on using these maps for predicting and manipulating cellular behavior (2). Regulatory synthetic biology has focused on creating molecular circuits that can be placed into a cell to control the transcription of a small number of transgenes, but genome-scale engineering of the cell's native regulatory apparatus is still rare, with most systems restricted to a limited set of controlled targets (3). Here, we demonstrate that transcription factor (TF) network mapping, gene expression profiling, and computational modeling can be integrated to rationally engineer transcriptional state. We call this activity, which bridges the gap between systems biology and synthetic biology, "transcriptome engineering