Cross-cascade activation of ERKs and ternary complex factors by Rho family proteins.

Mitogens promote cell growth through integrated signal transduction networks that alter cellular metabolism, gene expression and cytoskeletal organization. Many such signals are propagated through activation of MAP kinase cascades partly regulated by upstream small GTP-binding proteins. Interactions among cascades are suspected but not defined. Here we show that Rho family small G proteins such as Rac1 and Cdc42hs, which activate the JNK/SAPK pathway, cooperate with Raf-1 to activate the ERK pathway. This causes activation of ternary complex factors (TCFs), which regulate c-fos gene expression through the serum response element. Examination of ERK pathway kinases shows that neither MEK1 nor Ras will synergize with Rho-type proteins, and that only MEK1 is fully activated, indicating that MEKs are a focal point for cross-cascade regulation. Rho family proteins utilize PAKs for this effect, as expression of an active PAK1 mutant can substitute for Rho family small G proteins, and expression of an interfering PAK1 mutant blocks Rho-type protein stimulation of ERKs. PAK1 phosphorylates MEK1 on Ser298, a site important for binding of Raf-1 to MEK1 in vivo. Expression of interfering PAK1 also reduces stimulation of TCF function by serum growth factors, while expression of active PAK1 enhances EGF-stimulated MEK1 activity. This demonstrates interaction among MAP kinase pathway elements not previously recognized and suggests an explanation for the cooperative effect of Raf-1 and Rho family proteins on cellular transformation.     

Reduced susceptibility to DDT in field populations of Anopheles quadriannulatus and Anopheles arabiensis in Malawi: evidence for larval selection

Abstract.  Bioassays for insecticide resistance in adult mosquitoes were conducted on samples of Anopheles gambiae Giles s.l . (Diptera: Culicidae) species collected as larvae from breeding sites in the lower Shire Valley, Malawi. The results indicate full susceptibility to permethrin, deltamethrin and malathion, but reduced susceptibility to DDT in one sample from Thom (LT₅₀ of 8.39 min for females and 25.09 min for males). Polymerase chain reaction-based species identification of the mosquitoes assayed revealed a mixture of Anopheles arabiensis Patton and Anopheles quadriannulatus (Theobold). The LT₅₀ did not differ significantly between species. Genotyping of the L1014F and L1014S kdr alleles showed all mosquito specimens to be homozygous wild type; thus the reduced susceptibility detected is not attributable to target site insensitivity and instead is likely to be metabolic in nature. Anopheles quadriannulatus is characteristically zoophagic and exophilic. Indeed, of 82 Anopheles collected through knockdown collections within dwellings, only one was An. quadriannulatus and the rest were An. arabiensis . They are unlikely, therefore, to have been exposed to selection pressure arising from insecticide-treated net usage or to DDT indoor residual spraying. Therefore, it is suggested that this example of reduced susceptibility to DDT in An. quadriannulatus reflects selection in the larval stages.     

Contribution of the Ly49E Natural Killer Receptor in the Immune Response to Plasmodium berghei Infection and Control of Hepatic Parasite Development

Natural killer (NK) cells have different roles in the host response against Plasmodium-induced malaria depending on the stage of infection. Liver NK cells have a protective role during the initial hepatic stage of infection by production of the T_H1-type cytokines IFN-γ and TNF-α. In the subsequent erythrocytic stage of infection, NK cells also induce protection through Th1-type cytokines but, in addition, may also promote development of cerebral malaria via CXCR3-induction on CD8⁺ T cells resulting in migration of these cells to the brain. We have recently shown that the regulatory Ly49E NK receptor is expressed on liver NK cells in particular. The main objective of this study was therefore to examine the role of Ly49E expression in the immune response upon Plasmodium berghei ANKA infection, for which we compared wild type (WT) to Ly49E knockout (KO) mice. We show that the parasitemia was higher at the early stage, i.e. at days 6–7 of Plasmodium berghei ANKA infection in Ly49E KO mice, which correlated with lower induction of CD69, IFN-γ and TNF-α in DX5⁻ liver NK cells at day 5 post-infection. At later stages, these differences faded. There was also no difference in the kinetics and the percentage of cerebral malaria development and in lymphocyte CXCR3 expression in WT versus Ly49E KO mice. Collectively, we show that the immune response against Plasmodium berghei ANKA infection is not drastically affected in Ly49E KO mice. Although NK cells play a crucial role in Plasmodium infection and Ly49E is highly expressed on liver NK cells, the Ly49E NK receptor only has a temporarily role in the immune control of this parasite.     

Integration Analysis of Three Omics Data Using Penalized Regression Methods: An Application to Bladder Cancer

Omics data integration is becoming necessary to investigate the genomic mechanisms involved in complex diseases. During the integration process, many challenges arise such as data heterogeneity, the smaller number of individuals in comparison to the number of parameters, multicollinearity, and interpretation and validation of results due to their complexity and lack of knowledge about biological processes. To overcome some of these issues, innovative statistical approaches are being developed. In this work, we propose a permutation-based method to concomitantly assess significance and correct by multiple testing with the MaxT algorithm. This was applied with penalized regression methods (LASSO and ENET) when exploring relationships between common genetic variants, DNA methylation and gene expression measured in bladder tumor samples. The overall analysis flow consisted of three steps: (1) SNPs/CpGs were selected per each gene probe within 1Mb window upstream and downstream the gene; (2) LASSO and ENET were applied to assess the association between each expression probe and the selected SNPs/CpGs in three multivariable models (SNP, CPG, and Global models, the latter integrating SNPs and CPGs); and (3) the significance of each model was assessed using the permutation-based MaxT method. We identified 48 genes whose expression levels were significantly associated with both SNPs and CPGs. Importantly, 36 (75%) of them were replicated in an independent data set (TCGA) and the performance of the proposed method was checked with a simulation study. We further support our results with a biological interpretation based on an enrichment analysis. The approach we propose allows reducing computational time and is flexible and easy to implement when analyzing several types of omics data. Our results highlight the importance of integrating omics data by applying appropriate statistical strategies to discover new insights into the complex genetic mechanisms involved in disease conditions.     

High Expression of KCa3.1 in Patients with Clear Cell Renal Carcinoma Predicts High Metastatic Risk and Poor Survival

Background

Ca²⁺-activated K⁺ channels have been implicated in cancer cell growth, metastasis, and tumor angiogenesis. Here we hypothesized that high mRNA and protein expression of the intermediate-conductance Ca²⁺-activated K⁺ channel, KCa3.1, is a molecular marker of clear cell Renal Cell Carcinoma (ccRCC) and metastatic potential and survival.

Methodology/Principal Findings

We analyzed channel expression by qRT-PCR, immunohistochemistry, and patch-clamp in ccRCC and benign oncocytoma specimens, in primary ccRCC and oncocytoma cell lines, as well as in two ccRCC cell lines (Caki-1 and Caki-2). CcRCC specimens contained 12-fold higher mRNA levels of KCa3.1 than oncocytoma specimens. The large-conductance channel, KCa1.1, was 3-fold more highly expressed in ccRCC than in oncocytoma. KCa3.1 mRNA expression in ccRCC was 2-fold higher than in the healthy cortex of the same kidney. Disease specific survival trended towards reduction in the subgroup of high-KCa3.1-expressing tumors (p<0.08 vs. low-KCa3.1-expressing tumors). Progression-free survival (time to metastasis/recurrence) was reduced significantly in the subgroup of high-KCa3.1-expressing tumors (p<0.02, vs. low-KCa3.1-expressing tumors). Immunohistochemistry revealed high protein expression of KCa3.1 in tumor vessels of ccRCC and oncocytoma and in a subset of ccRCC cells. Oncocytoma cells were devoid of KCa3.1 protein. In a primary ccRCC cell line and Caki-1/2-ccRCC cells, we found KCa3.1-protein as well as TRAM-34-sensitive KCa3.1-currents in a subset of cells. Furthermore, Caki-1/2-ccRCC cells displayed functional Paxilline-sensitive KCa1.1 currents. Neither KCa3.1 nor KCa1.1 were found in a primary oncocytoma cell line. Yet KCa-blockers, like TRAM-34 (KCa3.1) and Paxilline (KCa1.1), had no appreciable effects on Caki-1 proliferation in-vitro.

Conclusions/Significance

Our study demonstrated expression of KCa3.1 in ccRCC but not in benign oncocytoma. Moreover, high KCa3.1-mRNA expression levels were indicative of low disease specific survival of ccRCC patients, short progression-free survival, and a high metastatic potential. Therefore, KCa3.1 is of prognostic value in ccRCC.     

One-step sample concentration, purification, and albumin depletion method for urinary proteomics

Workflows in urinary proteomics studies are often complex and require many steps to enrich, purify, deplete, and separate the complex mixture. Many of these methods are laborious, are time-consuming, and have the potential for error. Although individual steps of these methods have been previously studied, their downstream compatibilities with fractionation technologies such as off-gel electrophoresis have not been investigated. We developed a one-step sample preparation workflow that simultaneously (i) concentrates proteins, (ii) purifies by removing salts and other low molecular weight compounds, and (iii) depletes (albumin) from urine samples. This simple and robust workflow can be multiplexed and is compatible with a diverse range of downstream multidimensional separation technologies. Additionally, because of its high reproducibility and flexibility in processing samples with different volumes and concentrations, it has the potential to be used for standardization of urinary proteomics studies, as well as for studying other body fluids of similar complexity.     

Proteomic approaches to the analysis of multiprotein signaling complexes

Signal transduction is one of the most active fields in modern biomedical research. Increasing evidence has shown that signaling proteins associate with each other in characteristic ways to form large signaling complexes. These diverse structures operate to boost signaling efficiency, ensure specificity and increase sensitivity of the biochemical circuitry. Traditional methods of protein analysis are inadequate to fully characterize and understand these structures, which are intricate, contain many components and are highly dynamic. Instead, proteomics technologies are currently being applied to investigate the nature and composition of multimeric signaling complexes. This review presents commonly used and potential proteomic methods of analyzing diverse protein complexes along with a discussion and a brief evaluation of alternative approaches. Challenges associated with proteomic analysis of signaling complexes are also discussed.