Acidic extracellular pH increases calcium influx-triggered phospholipase D activity along with acidic sphingomyelinase activation to induce matrix metalloproteinase-9 expression in mouse metastatic melanoma

Acidic extracellular pH is a common feature of tumor tissues. We have reported that culturing cells at acidic pH (5.4-6.5) induced matrix metalloproteinase-9 expression through phospholipase D, extracellular signal regulated kinase 1/2 and p38 mitogen-activated protein kinases and nuclear factor-kappaB. Here, we show that acidic extracellular pH signaling involves both pathways of phospholipase D triggered by Ca2+ influx and acidic sphingomyelinase in mouse B16 melanoma cells. We found that BAPTA-AM [1,2-bis(2-aminophenoxy)-ethane-N,N,N',N'-tetraacetic acid tetrakis (acetoxymethyl) ester], a chelator of intracellular free calcium, and the voltage dependent Ca2+ channel blockers, mibefradil (for T-type) and nimodipine (for L-type), dose-dependently inhibited acidic extracellular pH-induced matrix metalloproteinase-9 expression. Intracellular free calcium concentration ([Ca2+]i) was transiently elevated by acidic extracellular pH, and this [Ca2+]i elevation was repressed by EGTA and the voltage dependent Ca2+ channel blockers but not by phospholipase C inhibitor, suggesting that acidic extracellular pH increased [Ca2+]i through voltage dependent Ca2+ channel. In contrast, SR33557, an L-type voltage dependent Ca2+ channel blocker and acidic sphingomyelinase inhibitor, attenuated matrix metalloproteinase-9 induction but did not affect calcium influx. We found that acidic sphingomyelinase activity was induced by acidic extracellular pH and that the specific acidic sphingomyelinase inhibitors (perhexiline and desipramine) and siRNA targeting aSMase/smpd1 could inhibit acidic extracellular pH-induced matrix metalloproteinase-9 expression. BAPTA-AM reduced acidic extracellular pH-induced phospholipase D but not acidic sphingomyelinase acitivity. The acidic sphingomyelinase inhibitors did not affect the phosphorylation of extracellular signal regulated kinase 1/2 and p38, but they suppressed nuclear factor-kappaB activity. These data suggest that the calcium influx-triggered phospholipase D and acidic sphingomyelinase pathways of acidic extracellular pH induced matrix metalloproteinase-9 expression, at least in part, through nuclear factor-kappaB activation.     

Detection of terminal mismatches on DNA duplexes in homogeneous assays or with immobilized probes

We recently reported the design of new fluorescent oligo-2'-deoxyribonucleotides (FODNs) for the detection of terminal mismatches on DNA duplexes in homogeneous assays. We now report the validation of this method in homogeneous assays with other sequences and the feasibility of the detection of terminal mismatches with immobilized FODNs. In all cases studied, the mismatched duplexes were more fluorescent than the perfect ones and results confirmed that the discrimination factor is sequence-dependent.     

Stress-induced morphogenic responses: growing out of trouble?

Plants exposed to sub-lethal abiotic stress conditions exhibit a broad range of morphogenic responses. Despite the diversity of phenotypes, a generic 'stress-induced morphogenic response' can be recognized that appears to be carefully orchestrated and comprises three components: (a) inhibition of cell elongation, (b) localized stimulation of cell division and (c) alterations in cell differentiation status. It is hypothesized that the similarities in the morphogenic responses induced by distinct stresses, reflect common molecular processes such as increased ROS-production and altered phytohormone transport and/or metabolism. The stress-induced morphogenic response (SIMR) is postulated to be part of a general acclimation strategy, whereby plant growth is redirected to diminish stress exposure.     

PARP-1-induced cell death through inhibition of the MEK/ERK pathway in MNNG-treated HeLa cells

Poly(ADP-ribose) polymerase-1 (PARP-1) hyper-activation promotes cell death but the signaling events downstream of PARP-1 activation are not fully identified. To gain further information on the implication of PARP-1 activation and PAR synthesis on signaling pathways influencing cell death, we exposed HeLa cells to the DNA alkylating agent N-methyl-N′-methyl-nitro-N-nitrosoguanidine (MNNG). We found that massive PAR synthesis leads to down-regulation of ERK1/2 phosphorylation, Bax translocation to the mitochondria, release of cytochrome c and AIF and subsequently cell death. Inhibition of massive PAR synthesis following MNNG exposure with the PARP inhibitor PJ34 prevented those events leading to cell survival, whereas inhibition of ERK1/2 phosphorylation by inhibiting MEK counteracted the cytoprotective effect of PJ34. Together, our results provide evidence that PARP-1-induced cell death by MNNG exposure in HeLa cells is mediated in part through inhibition of the MEK/ERK signaling pathway and that inhibition of massive PAR synthesis by PJ34, which promotes sustained activation of ERK1/2, leads to cytoprotection.     

Query-driven module discovery in microarray data

MOTIVATION: Existing (bi)clustering methods for microarray data analysis often do not answer the specific questions of interest to a biologist. Such specific questions could be derived from other information sources, including expert prior knowledge. More specifically, given a set of seed genes which are believed to have a common function, we would like to recruit genes with similar expression profiles as the seed genes in a significant subset of experimental conditions. RESULTS: We introduce QDB, a novel Bayesian query-driven biclustering framework in which the prior distributions allow introducing knowledge from a set of seed genes (query) to guide the pattern search. In two well-known yeast compendia, we grow highly functionally enriched biclusters from small sets of seed genes using a resolution sweep approach. In addition, relevant conditions are identified and modularity of the biclusters is demonstrated, including the discovery of overlapping modules. Finally, our method deals with missing values naturally, performs well on artificial data from a recent biclustering benchmark study and has a number of conceptual advantages when compared to existing approaches for focused module search.     

Kernel-based data fusion for gene prioritization

MOTIVATION: Hunting disease genes is a problem of primary importance in biomedical research. Biologists usually approach this problem in two steps: first a set of candidate genes is identified using traditional positional cloning or high-throughput genomics techniques; second, these genes are further investigated and validated in the wet lab, one by one. To speed up discovery and limit the number of costly wet lab experiments, biologists must test the candidate genes starting with the most probable candidates. So far, biologists have relied on literature studies, extensive queries to multiple databases and hunches about expected properties of the disease gene to determine such an ordering. Recently, we have introduced the data mining tool ENDEAVOUR (Aerts et al., 2006), which performs this task automatically by relying on different genome-wide data sources, such as Gene Ontology, literature, microarray, sequence and more. RESULTS: In this article, we present a novel kernel method that operates in the same setting: based on a number of different views on a set of training genes, a prioritization of test genes is obtained. We furthermore provide a thorough learning theoretical analysis of the method's guaranteed performance. Finally, we apply the method to the disease data sets on which ENDEAVOUR (Aerts et al., 2006) has been benchmarked, and report a considerable improvement in empirical performance. AVAILABILITY: The MATLAB code used in the empirical results will be made publicly available.