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The Mycobacterium tuberculosis regulatory network and hypoxia

James E Galagan et al. Nature. .

Abstract

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.

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Figures

Figure 1
Figure 1. ChIP-Seq binding shows high sensitivity, reproducibility and sequence specificity
a, We identify all known binding sites (red bars) for KstR and DosR (Supplementary Fig. 3). Binding site heights plotted as bars and ordered by peak height. b, Binding site identification is highly reproducible. Bar plot shows the distance between corresponding sites in two KstR replicates. The majority of replicates fall within the motif (cyan line). Inset shows correlation of heights of corresponding peaks in two replicates (R2 > 0.83 for all TFs). c, Increasing TF expression increases peak height. Shown are plots of peaks identified at different levels of KstR induction. Corresponding peaks are plotted at the same position on the horizontal axis. d, KstR binding peak height correlated with motif structure. The canonical palindromic motif is identified in all strong binding sites. At weaker sites, however, we detect degraded motifs. e, Fraction of peaks assigned regulation as a function of relative peak height. f, Stacked histogram of the number of peaks assigned regulation as a function of the distance to the start codon of the predicted target gene and coloured by genomic location relative to the target gene and genic or intergenic context.
Figure 2
Figure 2. TF regulatory interaction subnet work linking hypoxia, lipid metabolism and protein degradation
The figure shows a subset of the regulatory network model for selected transcription factors. Edges are coloured by z-score (see text) with red edges indicating positive z-scores and activation, and blue indicating negative z-scores and repression. Grey edges indicate links without significant z-scores, TFs without induction expression data, or autobinding. The width of edges indicates the height of the corresponding binding site relative to the maximum binding site for the corresponding TF. Selected TFs are colour-coded by functional association and heat maps show expression data during hypoxia and re-aeration as shown in legend.
Figure 3
Figure 3. Predicting gene expression during hypoxia and re-aeration
Using the models described in text, we predict the expression pattern of 66% of genes (533) whose expression changes during hypoxia and re-aeration. Selected examples shown. Green lines, actual scaled expression with error bars from replicates; dashed black lines, model-predicted expression.
Figure 4
Figure 4. Lipid changes during hypoxia and re-aeration
HPLC-MS of total lipids from M. tuberculosis analysed in the positive-ion mode as ammoniated adducts unless otherwise indicated. Among more than 5,000 ions detected at each time point, m/z values for unnamed lipids were converted to named lipids when they matched the masses (< 10 p.p.m.) retention time (< 1 min) and collisional mass spectrometry patterns in MycoMass and MycoMap databases. Within each lipid class individual molecular species are reported by intensity and tracked by mass, converted to deduced empiric formulas and reported separately corresponding to the R group variants of mycolic acids (alpha, keto, methoxy) and as CX:Y, where X is the alkane chain length and Y is the unsaturation in the combined fatty acyl, mycolyl, phthioceranyl, pthiocerol, mycocerosyl units of one molecule. Error bars are standard deviations from four replicates.

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