Global gene expression mediated by Thermus thermophilus SdrP, a CRP/FNR family transcriptional regulator.

Thermus thermophilus SdrP is one of four cyclic AMP receptor protein (CRP)/fumarate and nitrate reduction regulator (FNR) family proteins from the extremely thermophilic bacterium T. thermophilus HB8. Expression of sdrP mRNA increased in the stationary phase during cultivation at 70 degrees C. Although the sdrP gene was non-essential, an sdrP-deficient strain showed growth defects, particularly when grown in a synthetic medium, and increased sensitivity to disulphide stress. The expression of several genes was altered in the sdrP disruptant. Among them, we found eight SdrP-dependent promoters using in vitro transcription assays. A predicted SdrP binding site similar to that recognized by Escherichia coli CRP was found upstream of each SdrP-dependent promoter. In the wild-type strain, expression of these eight genes tended to increase upon entry into the stationary phase. Transcriptional activation in vitro was independent of any added effector molecule. The hypothesis that apo-SdrP is the active form of the protein was supported by the observation that the three-dimensional structure of apo-SdrP is similar to that of the DNA-binding form of E. coli CRP. Based on the properties of the SdrP-regulated genes found in this study, it is speculated that SdrP is involved in nutrient and energy supply, redox control, and polyadenylation of mRNA.

Transcription activation mediated by a cyclic AMP receptor protein from Thermus thermophilus HB8.

The extremely thermophilic bacterium Thermus thermophilus HB8, which belongs to the phylum Deinococcus-Thermus, has an open reading frame encoding a protein belonging to the cyclic AMP (cAMP) receptor protein (CRP) family present in many bacteria. The protein named T. thermophilus CRP is highly homologous to the CRP family proteins from the phyla Firmicutes, Actinobacteria, and Cyanobacteria, and it forms a homodimer and interacts with cAMP. CRP mRNA and intracellular cAMP were detected in this strain, which did not drastically fluctuate during cultivation in a rich medium. The expression of several genes was altered upon disruption of the T. thermophilus CRP gene. We found six CRP-cAMP-dependent promoters in in vitro transcription assays involving DNA fragments containing the upstream regions of the genes exhibiting decreased expression in the CRP disruptant, indicating that the CRP is a transcriptional activator. The consensus T. thermophilus CRP-binding site predicted upon nucleotide sequence alignment is 5'-(C/T)NNG(G/T)(G/T)C(A/C)N(A/T)NNTCACAN(G/C)(G/C)-3'. This sequence is unique compared with the known consensus binding sequences of CRP family proteins. A putative -10 hexamer sequence resides at 18 to 19 bp downstream of the predicted T. thermophilus CRP-binding site. The CRP-regulated genes found in this study comprise clustered regularly interspaced short palindromic repeat (CRISPR)-associated (cas) ones, and the genes of a putative transcriptional regulator, a protein containing the exonuclease III-like domain of DNA polymerase, a GCN5-related acetyltransferase homolog, and T. thermophilus-specific proteins of unknown function. These results suggest a role for cAMP signal transduction in T. thermophilus and imply the T. thermophilus CRP is a cAMP-responsive regulator.

Inference of S-system models of genetic networks using a cooperative coevolutionary algorithm.

MOTIVATION: To resolve the high-dimensionality of the genetic network inference problem in the S-system model, a problem decomposition strategy has been proposed. While this strategy certainly shows promise, it cannot provide a model readily applicable to the computational simulation of the genetic network when the given time-series data contain measurement noise. This is a significant limitation of the problem decomposition, given that our analysis and understanding of the genetic network depend on the computational simulation. RESULTS: We propose a new method for inferring S-system models of large-scale genetic networks. The proposed method is based on the problem decomposition strategy and a cooperative coevolutionary algorithm. As the subproblems divided by the problem decomposition strategy are solved simultaneously using the cooperative coevolutionary algorithm, the proposed method can be used to infer any S-system model ready for computational simulation. To verify the effectiveness of the proposed method, we apply it to two artificial genetic network inference problems. Finally, the proposed method is used to analyze the actual DNA microarray data.