Figure 1.
The paraquat-induced transcriptional and metabolic cascade.
Paraquat generates superoxide inside the cell by NADPH-mediated reduction of oxygen. Superoxide is sensed by SoxR, which enhances the expression of the transcription factor SoxS, which in turn stimulates other downstream targets. One of the SoxS-regulated genes, sodA (superoxide dismutase), converts superoxide into hydrogen peroxide, which acts as a signal to enhance transcription of genes through OxyR. katG (catalase), a hydrogen peroxide scavenger is an OxyR-regulated gene. Superoxide and hydrogen peroxide also directly affect IscR modulation of a set of genes involved in iron sulfur cluster biogenesis.
Figure 2.
Expression analysis work flow.
Figure 3.
Major paraquat response clusters.
Each graph shows average log2 expression values as a function of time of all genes in a cluster relative to time zero. The groups are derived from K-means clustering on all three time-series experiments.
Figure 4.
Each graph shows changes in the expression values of each individual gene in cluster 14.
Figure 5.
A model of the superoxide transcriptional response.
This model summarizes the transcriptional response to paraquat, and consists of protein-coding genes and sRNAs present in the clusters 1–3 and 5–8 shown in Figure 3, along with their regulators and putative targets. It is a synthesis of our microarray results, interactions in RegulonDB, genome annotation and the primary literature related to the regulation of these primary paraquat responsive genes. Thus, it does not show other genes regulated by these transcription factors, nor does it include all regulatory factors that may govern these genes. Regulatory proteins are represented by ovals, sRNAs are represented by rounded rectangles and mRNAs are represented by boxes. SoxR-dependent transcripts that increase are shaded magenta, SoxR-independent transcripts are shaded blue, transcripts that are SoxR-dependent, but still have some residual paraquat response are shaded green, transcripts that decrease are shaded red. Regulatory proteins and sRNAs that appear on the right side of the figure are derived from transcripts present in the boxes. Boxes that are directly attached to each other represent chromosomally adjacent genes. Many of the transcripts are also connected as part of common protein complexes, metabolic pathways and in other biological processes. However, this level of biological detail could not be represented clearly in this model.
Figure 6.
Expression levels of soxS mRNA.
soxS mRNA levels as are shown as a function of time in the wild type and the ΔsoxR strain.
Figure 7.
Effect of paraquat on strains carrying deletions in SoxR-modulated genes relative to the wild type.
The values represent the percent difference in final optical density and exponential growth rate in 94 precise deletion strains relative to the wild type in presence of paraquat normalized by the change in the deletion strains relative to the wild type in absence of paraquat. Therefore, a strain having wild type final optical density levels and exponential growth levels in the presence and absence of paraquat would have a value of 100 on both the x and y-axis. A minimum of six replicate growth curves were run for each deletion strain. The results for the ΔsoxR and ΔsoxS strains are circled. The following strains were not included because the corresponding genes are essential or are not part of the Keio collection: b1052, fldA, hemB, ligA, lpxC, map, mdl, ribA, rpoH, yadR, ygiA, yhbN, yraL, and yrbK.
Figure 8.
Significant two-block motifs in SoxR-dependent clusters.
The two block algorithm implemented in Bioprospector finds a motif with two blocks separated by a variable length gap. The median gap for cluster 1 is 7 with a range of 5 to 9. The median gap for cluster 2 is 6 with a range of 4 to 8. The median gap for cluster 3 is 6 with a range of 5 to 8.
Table 1.
Partial summary of Biological Relationship Analysis results for transcription factors which regulate genes in the clusters shown in Fig. 3.