Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets. Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region. Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes

P19 H-Ras Induces G1/S Phase Delay Maintaining Cells in a Reversible Quiescence State

This is an open-access article distributed under the terms of the Creative Commons Attribution License.[Background]: Three functional c-ras genes, known as c-H-ras, c-K-ras, and c-N-ras, have been largely studied in mammalian cells with important insights into normal and tumorigenic cellular signal transduction events. Two K-Ras mRNAs are obtained from the same pre-mRNA by alternative splicing. H-Ras pre-mRNA can also be alternatively spliced in the IDX and 4A terminal exons, yielding the p19 and p21 proteins, respectively. However, despite the Ras gene family’s established role in tumorigenic cellular signal transduction events, little is known about p19 function. Previous results showed that p19 did not interact with two known p21 effectors, Raf1 and Rin1, but was shown to interact with RACK1, a scaffolding protein that promotes multi-protein complexes in different signaling pathways (Cancer Res 2003, 63 p5178). This observation suggests that p19 and p21 play differential and complementary roles in the cell.[Principal Findings]: We found that p19 regulates telomerase activity through its interaction with p73a/b proteins. We also found that p19 overexpression induces G1/S phase delay; an observation that correlates with hypophosphorylation of both Akt and p70SK6. Similarly, we also observed that FOXO1 is upregulated when p19 is overexpressed. The three observations of (1) hypophosphorylation of Akt, (2) G1/S phase delay and (3) upregulation of FOXO1 lead us to conclude that p19 induces G1/S phase delay, thereby maintaining cells in a reversible quiescence state and preventing entry into apoptosis. We then assessed the effect of p19 RNAi on HeLa cell growth and found that p19 RNAi increases cell growth, thereby having the opposite effect of arrest of the G1/S phase or producing a cellular quiescence state.[Significance]: Interestingly, p19 induces FOXO1 that in combination with the G1/S phase delay and hypophosphorylation of both Akt and p70SK6 leads to maintenance of a reversible cellular quiescence state, thereby preventing entry into apoptosis.This work was supported by Fundacion de Investigacion Medica Mutua Madrileña Automovilista (Fundacion MMA), the Plan Nacional (MEC) BFU2005-00701 and the Fundacion Eugenio Rodriguez Pascual. M.C. was a recipient of a Fmed MMA fellowship.Peer reviewe

Lemur tyrosine kinase-2 signalling regulates kinesin-1 light chain-2 phosphorylation and binding of Smad2 cargo.

A recent genome-wide association study identified the gene encoding lemur tyrosine kinase-2 (LMTK2) as a susceptibility gene for prostate cancer. The identified genetic alteration is within intron 9, but the mechanisms by which LMTK2 may impact upon prostate cancer are not clear because the functions of LMTK2 are poorly understood. Here, we show that LMTK2 regulates a known pathway that controls phosphorylation of kinesin-1 light chain-2 (KLC2) by glycogen synthase kinase-3β (GSK3β). KLC2 phosphorylation by GSK3β induces the release of cargo from KLC2. LMTK2 signals via protein phosphatase-1C (PP1C) to increase inhibitory phosphorylation of GSK3β on serine-9 that reduces KLC2 phosphorylation and promotes binding of the known KLC2 cargo Smad2. Smad2 signals to the nucleus in response to transforming growth factor-β (TGFβ) receptor stimulation and transport of Smad2 by kinesin-1 is required for this signalling. We show that small interfering RNA loss of LMTK2 not only reduces binding of Smad2 to KLC2, but also inhibits TGFβ-induced Smad2 signalling. Thus, LMTK2 may regulate the activity of kinesin-1 motor function and Smad2 signalling

Mitochondrial Alterations in PINK1 Deficient Cells Are Influenced by Calcineurin-Dependent Dephosphorylation of Dynamin-Related Protein 1

PTEN-induced novel kinase 1 (PINK1) mutations are associated with autosomal recessive parkinsonism. Previous studies have shown that PINK1 influences both mitochondrial function and morphology although it is not clearly established which of these are primary events and which are secondary. Here, we describe a novel mechanism linking mitochondrial dysfunction and alterations in mitochondrial morphology related to PINK1. Cell lines were generated by stably transducing human dopaminergic M17 cells with lentiviral constructs that increased or knocked down PINK1. As in previous studies, PINK1 deficient cells have lower mitochondrial membrane potential and are more sensitive to the toxic effects of mitochondrial complex I inhibitors. We also show that wild-type PINK1, but not recessive mutant or kinase dead versions, protects against rotenone-induced mitochondrial fragmentation whereas PINK1 deficient cells show lower mitochondrial connectivity. Expression of dynamin-related protein 1 (Drp1) exaggerates PINK1 deficiency phenotypes and Drp1 RNAi rescues them. We also show that Drp1 is dephosphorylated in PINK1 deficient cells due to activation of the calcium-dependent phosphatase calcineurin. Accordingly, the calcineurin inhibitor FK506 blocks both Drp1 dephosphorylation and loss of mitochondrial integrity in PINK1 deficient cells but does not fully rescue mitochondrial membrane potential. We propose that alterations in mitochondrial connectivity in this system are secondary to functional effects on mitochondrial membrane potential

Discovery and Scoring of Protein Interaction Subnetworks Discriminative of Late Stage Human Colon Cancer*S⃞

We used a systems biology approach to identify and score protein interaction subnetworks whose activity patterns are discriminative of late stage human colorectal cancer (CRC) versus control in colonic tissue. We conducted two gel-based proteomics experiments to identify significantly changing proteins between normal and late stage tumor tissues obtained from an adequately sized cohort of human patients. A total of 67 proteins identified by these experiments was used to seed a search for protein-protein interaction subnetworks. A scoring scheme based on mutual information, calculated using gene expression data as a proxy for subnetwork activity, was developed to score the targets in the subnetworks. Based on this scoring, the subnetwork was pruned to identify the specific protein combinations that were significantly discriminative of late stage cancer versus control. These combinations could not be discovered using only proteomics data or by merely clustering the gene expression data. We then analyzed the resultant pruned subnetwork for biological relevance to human CRC. A number of the proteins in these smaller subnetworks have been associated with the progression (CSNK2A2, PLK1, and IGFBP3) or metastatic potential (PDGFRB) of CRC. Others have been recently identified as potential markers of CRC (IFITM1), and the role of others is largely unknown in this disease (CCT3, CCT5, CCT7, and GNA12). The functional interactions represented by these signatures provide new experimental hypotheses that merit follow-on validation for biological significance in this disease. Overall the method outlines a quantitative approach for integrating proteomics data, gene expression data, and the wealth of accumulated legacy experimental data to discover significant protein subnetworks specific to disease