Environment-Specific Gene Regulatory Networks for MTB

The MTB Network Portal also contains an interactive BioTapestry network viewer that nicely demonstrates the regulation of specific genes in a selection of environmental conditions we investigated. BioTapestry is an interactive tool for building, visualizing, and simulating genetic regulatory networks.

The architecture of the BioTapestry network is based on the validated bicluster genes and their regulatory influences (TFs and environmental). The network is condensed to only contain genes with annotated functions that are grouped into broad categories of ‘cholesterol processes’, ‘fatty acid processes’, ‘growth’ and ‘growth of symbiont in host cell’. Due to the complexity of transcriptional regulation, a single overview network is not sufficient and this visualization method allows for an easy comparison between environmental contexts. By just comparing the regulatory interactions that are regulated during wild-type growth to those that are regulated during growth on cholesterol, it is possible to glean some interesting biological insights.

Transcription Factors (TFs) are grouped together and represented by bent arrows, which extend to horizontal and vertical lines that connect to their regulatory gene targets. The gene targets that are shown were predicted by the EGRIN model to be co-regulated in biclusters and were validated for regulation by their linking TF through ChIP-Seq binding and differential expression from TF overexpression experiments (see text). Inclusion in these models required significant correlation of expression of TF and validated bicluster genes under wild-type growth (A) or growth in cholesterol (B). The arrows and barred lines indicate the direction of correlation (activation or repression).

References: Longabaugh WJ, Davidson EH, Bolouri H. (2009). Visualization, documentation, analysis, and communication of large-scale gene regulatory networks. Biochim Biophys Acta. 1789(4):363-74

References: Peterson, E. J. R., Reiss D. J., Turkarslan S., Minch K. J., Rustad T., Plaisier C. L., et al. (2014). A high-resolution network model for global gene regulation in Mycobacterium tuberculosis.. Nucleic acids research. 42(18), 11291-303