67 research outputs found
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The MEK2-binding tumor suppressor hDlg is recruited by E-cadherin to the midbody ring
Background: The human homologue of the Drosophila Discs-large tumor suppressor protein, hDlg, is a multi-domain cytoplasmic protein that localizes to the membrane at intercellular junction sites. At both synaptic junctions and epithelia cell-cell junctions, hDlg is known to recruit several signaling proteins into macromolecular complexes. hDlg is also found at the midbody, a small microtubule-rich structure bridging the two daughter cells during cytokinesis, but its function at this site is not clear. Results: Here we describe the interaction of hDlg with the activated form of MEK2 of the canonical RAF/MEK/ERK pathway, a protein that is found at the midbody during cytokinesis. We show that both proteins localize to a sub-structure of the midbody, the midbody ring, and that the interaction between the PDZ domains of hDlg and the C-terminal portion of MEK2 is dependent on the phosphorylation of MEK2. Finally, we found that E-cadherin also localizes to the midbody and that its expression is required for the isoform-specific recruitment of hDlg, but not activated MEK2, to that structure. Conclusion: Our results suggest that like at other cell-cell junction sites, hDlg is part of a macromolecular complex of structural and signaling proteins at the midbody.Molecular and Cellular Biolog
Lyapunov exponents and phase diagrams reveal multi-factorial control over TRAIL-induced apoptosis
Kinetic modeling, phase diagrams analysis, and quantitative single-cell experiments are combined to investigate how multiple factors, including the XIAP:caspase-3 ratio and ligand concentration, regulate receptor-mediated apoptosis
Considering Abundance, Affinity, and Binding Site Availability in the NF-κB Target Selection Puzzle
The NF-κB transcription regulation system governs a diverse set of responses to various cytokine stimuli. With tools from in vitro biochemical characterizations, to omics-based whole genome investigations, great strides have been made in understanding how NF-κB transcription factors control the expression of specific sets of genes. Nonetheless, these efforts have also revealed a very large number of potential binding sites for NF-κB in the human genome, and a puzzle emerges when trying to explain how NF-κB selects from these many binding sites to direct cell-type- and stimulus-specific gene expression patterns. In this review, we surmise that target gene transcription can broadly be thought of as a function of the nuclear abundance of the various NF-κB dimers, the affinity of NF-κB dimers for the regulatory sequence and the availability of this regulatory site. We use this framework to place quantitative information that has been gathered about the NF-κB transcription regulation system into context and thus consider questions it answers, and questions it raises. We end with a brief discussion of some of the future prospects that new approaches could bring to our understanding of how NF-κB transcription factors orchestrate diverse responses in different biological contexts
Prenatal exposure to maternal cigarette smoking, amygdala volume, and fat intake in adolescence
Context : Prenatal exposure to maternal cigarette smoking is a well-established risk factor for obesity, but the underlying mechanisms are not known. Preference for fatty foods, regulated in part by the brain reward system, may contribute to the development of obesity.
Objective : To examine whether prenatal exposure to maternal cigarette smoking is associated with enhanced fat intake and risk for obesity, and whether these associations may be related to subtle structural variations in brain regions involved in reward processing.
Design : Cross-sectional study of a population-based cohort.
Setting : The Saguenay Youth Study, Quebec, Canada.
Participants : A total of 378 adolescents (aged 13 to 19 years; Tanner stage 4 and 5 of sexual maturation), half of whom were exposed prenatally to maternal cigarette smoking (mean [SD], 11.1 [6.8] cigarettes/d).
Main Outcome Measures : Fat intake was assessed with a 24-hour food recall (percentage of energy intake consumed as fat). Body adiposity was measured with anthropometry and multifrequency bioimpedance. Volumes of key brain structures involved in reward processing, namely the amygdala, nucleus accumbens, and orbitofrontal cortex, were measured with magnetic resonance imaging.
Results : Exposed vs nonexposed subjects exhibited a higher total body fat (by approximately 1.7 kg; P = .009) and fat intake (by 2.7%; P = .001). They also exhibited a lower volume of the amygdala (by 95 mm3; P < .001) but not of the other 2 brain structures. Consistent with its possible role in limiting fat intake, amygdala volume correlated inversely with fat intake (r = −0.15; P = .006).
Conclusions : Prenatal exposure to maternal cigarette smoking may promote obesity by enhancing dietary preference for fat, and this effect may be mediated in part through subtle structural variations in the amygdala
Exploring the Contextual Sensitivity of Factors that Determine Cell-to-Cell Variability in Receptor-Mediated Apoptosis
Stochastic fluctuations in gene expression give rise to cell-to-cell variability in protein levels which can potentially cause variability in cellular phenotype. For TRAIL (TNF-related apoptosis-inducing ligand) variability manifests itself as dramatic differences in the time between ligand exposure and the sudden activation of the effector caspases that kill cells. However, the contribution of individual proteins to phenotypic variability has not been explored in detail. In this paper we use feature-based sensitivity analysis as a means to estimate the impact of variation in key apoptosis regulators on variability in the dynamics of cell death. We use Monte Carlo sampling from measured protein concentration distributions in combination with a previously validated ordinary differential equation model of apoptosis to simulate the dynamics of receptor-mediated apoptosis. We find that variation in the concentrations of some proteins matters much more than variation in others and that precisely which proteins matter depends both on the concentrations of other proteins and on whether correlations in protein levels are taken into account. A prediction from simulation that we confirm experimentally is that variability in fate is sensitive to even small increases in the levels of Bcl-2. We also show that sensitivity to Bcl-2 levels is itself sensitive to the levels of interacting proteins. The contextual dependency is implicit in the mathematical formulation of sensitivity, but our data show that it is also important for biologically relevant parameter values. Our work provides a conceptual and practical means to study and understand the impact of cell-to-cell variability in protein expression levels on cell fate using deterministic models and sampling from parameter distributions
Reproductive factors and the risk of triple-negative breast cancer in white women and African-American women: a pooled analysis
A reference map of the human binary protein interactome.
Global insights into cellular organization and genome function require comprehensive understanding of the interactome networks that mediate genotype-phenotype relationships(1,2). Here we present a human 'all-by-all' reference interactome map of human binary protein interactions, or 'HuRI'. With approximately 53,000 protein-protein interactions, HuRI has approximately four times as many such interactions as there are high-quality curated interactions from small-scale studies. The integration of HuRI with genome(3), transcriptome(4) and proteome(5) data enables cellular function to be studied within most physiological or pathological cellular contexts. We demonstrate the utility of HuRI in identifying the specific subcellular roles of protein-protein interactions. Inferred tissue-specific networks reveal general principles for the formation of cellular context-specific functions and elucidate potential molecular mechanisms that might underlie tissue-specific phenotypes of Mendelian diseases. HuRI is a systematic proteome-wide reference that links genomic variation to phenotypic outcomes
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