In a given bacterial population, antibiotic treatment will kill a large portion of the population, while a small, tolerant subpopulation will survive. Tolerant cells disrupt the efficacy of antibiotic treatment and increase the likelihood that a population gains antibiotic resistance. When a population becomes resistant, antibiotic treatment fails, which is a major health concern. Since antibiotic tolerance often leads to resistance, we have taken a systems biology approach to examine how transcriptional networks respond to antibiotic stress so that cells can survive and recover after antibiotic treatment. We have compared gene expression with and without ampicillin in E. coli. While many previous studies have identified aspects of the antibiotic stress response at either the protein or transcriptional level, our work leverages existing knowledge of transcriptional regulation to link the dynamics of the two allowing for a more holistic approach. Here, we are the first to develop a whole-cell, transcriptional regulatory network (TRN) of antibiotic tolerant subpopulations and examine how cells respond at the transcriptional level to bactericidal concentrations of an antibiotic. Using TRN analysis, we show how certain sigma and transcription factors are affecting transcriptional regulation under antibiotic stress, and that changes in gene expression specific to ampicillin treatment can be directly linked to cell survival and recovery. The resulting network demonstrates that cells are mounting an active and coordinated response to the antibiotic that spans multiple systems and pathways. The redundancy and interconnectivity of the networks suggest that accounting for whole-cell dynamics may be crucial when modeling and studying antibiotic tolerance in the future.