Stochastic models for regulatory networks of the genetic toggle switch

Bistability arises within a wide range of biological systems from the A phage switch in bacteria to cellular signal transduction pathways in mammalian cells. Changes in regulatory mechanisms may result in genetic switching in a bistable system. Recently, more and more experimental evidence in the form of bimodal population distributions indicates that noise plays a very important role in the switching of bistable systems. Although deterministic models have been used for studying the existence of bistability properties under various system conditions, these models cannot realize cell-to-cell fluctuations in genetic switching. However, there is a lag in the development of stochastic models for studying the impact of noise in bistable systems because of the lack of detailed knowledge of biochemical reactions, kinetic rates, and molecular numbers. in this work, we develop a previously undescribed general technique for developing quantitative stochastic models for large-scale genetic regulatory networks by introducing Poisson random variables into deterministic models described by ordinary differential equations. Two stochastic models have been proposed for the genetic toggle switch interfaced with either the SOS signaling pathway or a quorum-sensing signaling pathway, and we have successfully realized experimental results showing bimodal population distributions. Because the introduced stochastic models are based on widely used ordinary differential equation models, the success of this work suggests that this approach is a very promising one for studying noise in large-scale genetic regulatory networks.

The matricellular protein SPARC is internalized in Sertoli, Leydig, and germ cells during testis differentiation

The gene encoding the matricellular protein secreted protein, acidic and rich in cysteine (SPARC) was identified in a screen for genes expressed sex-specifically during mouse gonad development, as being strongly upregulated in the male gonad from very early in testis development. We present here a detailed analysis of SPARC gene and protein expression during testis development, from 11.5 to 15.5 days post coitum (dpc). Section in situ hybridization analysis revealed that SPARC mRNA is expressed by the Sertoli cells in the testis cords and the fetal Leydig cells, found within the interstitial space between the testis cords. Immunodetection with anti-SPARC antibody showed that the protein was located inside the testis cords, within the cytoplasm of Sertoli and germ cells. In the interstitium, SPARC was present intracellularly within the Leydig cells. The internalization of SPARC in Sertoli, Leydig, and germ cells suggests that it plays an intracellular regulatory role in these cell types during fetal testis development.

The mitogenic signaling pathway for fibroblast growth factor-2 involves the tyrosine phosphorylation of cyclin D2 in MCF-7 human breast cancer cells

Fibroblast growth factor-2 (FGF-2) is mitogenic for the human breast cancer cell line MCF-7; here we investigate some of the signaling pathways subserving this activity. FGF-2 stimulation of MCF-7 cells resulted in a global increase of intracellular tyrosine phosphorylation of proteins, particularly FGF receptor substrate-2, the protooncogene product Src and the mitogen-activated protein kinase (MAP kinase) cascade, A major increase in the tyrosine phosphorylation of a 30-kDa protein species was also found. This protein was identified as cyclin D2 by mass spectrometry after trypsin digestion. Immunoprecipitation of cyclin D2 and immunoblotting with anti-phosphotyrosine antibodies confirmed that the tyrosine phosphorylation of cyclin D2 was indeed induced by FGF-2 stimulation. In addition, pharmacological inhibition of Src (with herbimycin A and PP2), and of the MAP kinase cascade (with PD98059), confirmed that Src activity is required for the FGF-2-induced phosphorylation of cyclin D2 whereas MAP kinase activity is not, Thus, tyrosine phosphorylation of cyclin D2 may be a hey regulatory target for FGF-2 signaling. (C) 2000 Federation of European Biochemical Societies. Published by Elsevier Science B.V. All rights reserved.

Expression of apoptotic regulatory molecules in renal cell carcinoma: Elevated expression of Fas ligand

Renal cell carcinoma (RCC) is the most common renal neoplasm. Despite being infiltrated by tumour infiltrating lymphocytes (TIL), these TIL are unable to control tumour growth in vivo, suggesting that the cytotoxic capacity of TIL against RCC is impaired, or that the tumour cells are resistant to killing and therefore escape detection by the immune system. It is postulated that the expression of apoptotic regulatory molecules in RCC favours tumour cell survival. The present study has therefore determined the expression of Fas (APO- 1/CD95), Fas ligand (Fas L) and bcl-2 in these tumours. The expression of Fas, Fas L and bcl-2 mRNA transcripts was determined in RCC, normal kidney and peripheral blood by semiquantitative reverse transcriptase polymerase chain reaction (RT-PCR), following RNA extraction and cDNA synthesis from tissues and cell samples. Transcript levels were measured by densitometry after Southern blot hybridization of PCR products with internal radio-labelled oligonucleotide probes; a densitometry score was assigned to each hybridizing DNA band and expressed as a ratio of the glyceraldehyde-3-phosphate dehydrogenase content. In peripheral blood, the expression of Fas L and bcl-2 transcripts was similar between patients and normal healthy individuals; however, Fas transcript expression was significantly down-regulated in the patients' versus normal peripheral blood (P = 0.026). Most interestingly, significantly up-regulated Fas L expression was observed in RCC compared to normal kidney (P = 0.041). In contrast, bcl-2 transcripts were well represented in normal kidney but markedly decreased in RCC (P = 0.021). The expression of Fas transcripts in normal kidney and RCC was variable. These data demonstrate elevated expression of Fas L transcripts in RCC, but the functional relevance of this remains to be investigated.

Evolving noisy oscillatory dynamics in genetic regulatory networks

We introduce a genetic programming (GP) approach for evolving genetic networks that demonstrate desired dynamics when simulated as a discrete stochastic process. Our representation of genetic networks is based on a biochemical reaction model including key elements such as transcription, translation and post-translational modifications. The stochastic, reaction-based GP system is similar but not identical with algorithmic chemistries. We evolved genetic networks with noisy oscillatory dynamics. The results show the practicality of evolving particular dynamics in gene regulatory networks when modelled with intrinsic noise.