Recent interest in the large-scale production of bioethanol for transportation fuel has intensified the search for efficient fermentative microorganisms that produce ethanol. Zymomonas mobilis ZM4 is a promising candidate due to its productivity, high level of ethanol tolerance and its ability to be genetically manipulated. However, the main drawback to using wild-type Z. mobilis is its narrow substrate utilization range, which is limited to glucose, fructose and sucrose. The efficient conversion of lignocellulosic hydrolysates to ethanol requires high-yield ethanol production from most, if not all, available sugars and resistance to industrially relevant stress and inhibitors. We have proposed to elucidate the molecular basis for important process traits using systems biology tools and the completed genome sequence. In order to optimize these studies, we have updated the Z. mobilis ZM4 genome annotation. The reannotation identifies new genes, corrects gene starts, deletes incorrect genes, detects frame shifts, updates the protein functional annotation and identifies CRISPR (Clustered regularly interspaced short palindromic repeats) sequences, which have been shown to play a role in bacteriophage resistance in other systems. The corrections were identified via a new gene prediction algorithm, Prodigal, developed at Oak Ridge National Laboratory and experimental evidence. Two additional annotation tools, one that identifies and categorizes regulatory proteins, and a second that identifies and categorizes transporters, will provide important information not included in other annotation pipelines. The updated annotation will be critical in identifying genome features that can be modified to achieve optimal ethanol production.