We have taken the first steps towards a complete reconstruction of the Mycobacterium tuberculosis regulatory network based on ChIP-Seq and combined this reconstruction with system-wide profiling of messenger RNAs, proteins, metabolites and lipids during hypoxia and re-aeration. Adaptations to hypoxia are thought to have a prominent role in M. tuberculosis pathogenesis. Using ChIP-Seq combined with expression data from the induction of the same factors, we have reconstructed a draft regulatory network based on 50 transcription factors. This network model revealed a direct interconnection between the hypoxic response, lipid catabolism, lipid anabolism and the production of cell wall lipids. As a validation of this model, in response to oxygen availability we observe substantial alterations in lipid content and changes in gene expression and metabolites in corresponding metabolic pathways. The regulatory network reveals transcription factors underlying these changes, allows us to computationally predict expression changes, and indicates that Rv0081 is a regulatory hub. Mycobacterium tuberculosis has the ability to survive within the host for months to decades in an asymptomatic state, and adaptations to hypoxia are thought to have an important role in pathogenesis; here a systems-wide reconstruction of the regulatory network provides a framework for understanding mycobacterial persistence in the host. Tuberculosis is a particularly debilitating disease, in part because of the ability of the Mycobacterium tuberculosis pathogen to persist asymptomatically in the host for many months or even decades. A ChIP-Seq genomic mapping analysis of more than 45 M. tuberculosis transcription factors, combined with expression data from the systematic overexpression of the same factors, has been used to develop a systems-wide reconstruction of the regulatory network underlying mycobacterial persistence. The network reveals links between hypoxia adaptation and lipid metabolism, both considered critical for tuberculosis pathogenesis, and the study identifies the previously unstudied transcription factor Rv0081 as a regulatory hub of the network.