Tuberculosis remains a major burden on global health infecting an estimated one-third of the world's population. A major obstacle to detecting and overcoming tuberculosis is understanding how Mycobacterium tuberculosis persists and multiplies inside host macrophages and dendritic cells and the unique roles of the two immune cells in eliminating the pathogen. Here we constructed a Physical Module Network PMN using gene expression data from in vitro experiments that simulate the reactive oxygen and nitrogen species and hypoxia encountered by M tuberculosis within host phagocytes We also used the same expression data to discover modules using Weighted Gene Correlation Network Analysis WGCNA.