Identifying modules of coexpressed transcript units and their organization of Saccharopolyspora erythraea from time series gene expression profiles.
BACKGROUND
The Saccharopolyspora erythraea genome sequence was released in 2007. In order to look at the gene regulations at whole transcriptome level, an expression microarray was specifically designed on the S. erythraea strain NRRL 2338 genome sequence. Based on these data, we set out to investigate the potential transcriptional regulatory networks and their organization.


RESULTS
In view of the hierarchical structure of bacterial transcriptional regulation, we constructed a hierarchical coexpression network at whole transcriptome level. A total of 27 modules were identified from 1255 differentially expressed transcript units (TUs) across time course, which were further classified in to four groups. Functional enrichment analysis indicated the biological significance of our hierarchical network. It was indicated that primary metabolism is activated in the first rapid growth phase (phase A), and secondary metabolism is induced when the growth is slowed down (phase B). Among the 27 modules, two are highly correlated to erythromycin production. One contains all genes in the erythromycin-biosynthetic (ery) gene cluster and the other seems to be associated with erythromycin production by sharing common intermediate metabolites. Non-concomitant correlation between production and expression regulation was observed. Especially, by calculating the partial correlation coefficients and building the network based on Gaussian graphical model, intrinsic associations between modules were found, and the association between those two erythromycin production-correlated modules was included as expected.


CONCLUSIONS
This work created a hierarchical model clustering transcriptome data into coordinated modules, and modules into groups across the time course, giving insight into the concerted transcriptional regulations especially the regulation corresponding to erythromycin production of S. erythraea. This strategy may be extendable to studies on other prokaryotic microorganisms.
Chang
Xiao
X
Key Lab of Systems Biology, Bioinformatics Center, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, China.
Liu
Shuai
S
Yu
Yong-Tao
YT
Li
Yi-Xue
YX
Li
Yuan-Yuan
YY
D049109:Cell Proliferation; D016000:Cluster Analysis; D004917:Erythromycin / Q000096:biosynthesis; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks; D009876:Operon / Q000235:genetics; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D016930:Saccharopolyspora / Q000166:cytology / Q000235:genetics* / Q000378:metabolism; D014158:Transcription, Genetic
D012333:RNA, Messenger; D004917:Erythromycin