New cell cycle-regulated genes in the yeast Saccharomyces cerevisiae

Topology of transcriptional regulatory networks: testing and improving

With the increasing amount and complexity of data generated in biological experiments it is becoming necessary to enhance the performance and applicability of existing statistical data analysis methods. This enhancement is needed for the hidden biological information to be better resolved and better interpreted. Towards that aim, systematic incorporation of prior information in biological data analysis has been a challenging problem for systems biology. Several methods have been proposed to integrate data from different levels of information most notably from metabolomics, transcriptomics and proteomics and thus enhance biological interpretation. However, in order not to be misled by the dominance of incorrect prior information in the analysis, being able to discriminate between competing prior information is required. In this study, we show that discrimination between topological information in competing transcriptional regulatory network models is possible solely based on experimental data. We use network topology dependent decomposition of synthetic gene expression data to introduce both local and global discriminating measures. The measures indicate how well the gene expression data can be explained under the constraints of the model network topology and how much each regulatory connection in the model refuses to be constrained. Application of the method to the cell cycle regulatory network of Saccharomyces cerevisiae leads to the prediction of novel regulatory interactions, improving the information content of the hypothesized network model.

The Pyst2-L phosphatase is involved in cell-crowding

The dual-specificity phosphatase Pyst2-L was found to be over expressed in leukocytes derived from AML and ALL patients as well as in certain other solid tumors and lymphoblastoid cell lines. Pyst2-L, binds and dephosphorylates both pERKs and pJNKs proteins, and thus, plays a role in regulating the MAP kinase signaling pathway. In the present study, a comparative genomic application was used and sequence analysis of multi-organisms databases were searched in order to identify genes homologous to Pyst2-L. The Xenopus laevis MAP kinase phosphatase X17c gene and the Yeast nitrogen starvation-induced protein phosphatase Yvh1p gene were revealed to be highly homologous with Pyst2-L. Both X17c and Yvh1p genes play a role in cell cycle regulation. A down regulated expression of the Yvh1p gene occurred in Saccharomyces cerevisiae that were synchronized to the G2-phase of the cell cycle by alpha-factor. In conformity with this result, a reduction in Pyst2-L expression levels was observed in G2-phase-synchronized Human K562 cells. Finally, we were able to show that cells in highly crowded cultures express high levels of the Pyst2-L phosphatase. These observations may indicate that low levels of the Pyst2-L phosphatase are essential for the G2-phase of the cell cycle and that this phosphatase might play a role in signaling cascades induced by cellular crowding.