The Tuberculosis Systems Biology Program has experimentally mapped and computationally modeled the molecular pathways of M. tuberculosis under conditions relevant to TB pathogenesis. To do so, we established a network that performed systematic profiling using ChIP-Seq, transcriptomics, proteomics, metabolomics, and lipidomics during both in vitro and in vivo growth and integrated these data into predictive computational models of the M. tuberculosis regulatory and metabolic networks.
The results of mapping the regulatory nework for 50 transcription factors and integrating these data with systematic profiling in vitro have been published:
Galagan, J.E., Minch, K., Peterson, M., Lyubetskaya, A., Azizi, E., Sweet, L., Gomes, A., Rustad, T., Dolganov, G., Glotova, I., Abeel, T., Mahwinney, C., Kennedy, A.D., Allard, R., Brabant, W., Krueger, A., Jaini, S., Honda, B., Yu, W.H., Hickey, M.J., Zucker, J., Garay, C., Weiner, B., Sisk, P., Stolte, C., Winkler, J.K., Van de Peer, Y., Iazzetti, P., Camacho, D., Dreyfuss, J., Liu, Y., Dorhoi, A., Mollenkopf, H.J., Drogaris, P., Lamontagne, J., Zhou, Y., Piquenot, J., Park, S.T., Raman, S., Kaufmann, S.H., Mohney, R.P., Chelsky, D., Moody, D.B., Sherman, D.R., Schoolnik, G.K. (2013) The Mycobacterium tuberculosis regulatory network and hypoxia. Nature.499(7457):178-83
This project was funded by a contract from the National Institute of Allergy and Infectious Diseases (NIAID). For the benefit of the TB scientific community, all ChIP-Seq data have been made publicly available. They can be accessed using the tools from this site, or from the Patric BRC.
regulatory network map has been generated using ChIP-Seq data combined with transcriptomic data following transcription factor induced expression. From this site you can search or browse the regulatory network inferred from all data generated by the project.
Download available data files and other resources.