Mouse RAGE Variant 4 Is a Dominant Membrane Receptor that Does Not Shed to Generate Soluble RAGE

<div><p>The receptor for advanced glycation end products (RAGE) is a multi-ligand, immunoglobulin-like receptor that has been implicated in aging-associated diseases. Recent studies have demonstrated that both human and murine <i>Ager</i> genes undergo extensive alternative splicing that generates multiple putative transcripts encoding different receptor isoforms. Except for the soluble isoform (esRAGE), the majority of putative RAGE isoforms remain unstudied. Profiling of murine <i>Ager</i> transcripts showed that variant transcript 4 (mRAGE_v4), the second most abundant transcript in lungs and multiple other tissues, encodes a receptor that lacks nine residues located within the C2 extracellular section close to the trans-membrane domain. We therefore characterized mRAGEV4 isoreceptor in comparison with the full-length mRAGE (mRAGEFL). Although differing in only nine residues, mRAGEFL and mRAGEV4 display very different cellular behaviors. While mRAGEFL undergoes constitutive, extensive shedding in the cell to generate sRAGE, mRAGEV4 hardly sheds. In addition, we found that while mRAGEFL can localize to both the plasma membrane and the endosome, mRAGEV4 is exclusively localized to the plasma membrane. These very different cellular localization patterns suggest that, in addition to their roles in sRAGE production, mRAGEFL and mRAGEV4 may play distinct, spatiotemporal roles in signaling and innate immune responses. Compared to mice, humans do not have the v4 transcript. Although hRAGE, like mRAGEFL, also localizes to the plasma membrane and the endosome, its rate of constitutive shedding is significantly lower. These observations provide valuable information regarding RAGE biology, and serve as a reference by which to create mouse models relating to human diseases.</p></div

Examination of constitutive RAGE shedding using cycloheximide chase and ELISA analyses.

<p>A549 cells transfected with FLAG-tagged mRAGEFL and mRAGEV4 were pre-treated with cycloheximide and then incubated in medium supplemented with cycloheximide. At each time point, cell culture medium (1 ml) was collected for ELISA analyses and cells were lysed for western blotting, using anti-FLAG-antibodies. (A) mRAGEFL; (B) mRAGEV4. For (A) and (B), the left panel is the western blot; the right panel is the densitometry semi-quantification of the western blot. C. ELISA analyses of sRAGE in cell culture medium from mRAGEFL- and mRAGEV4-transfected cells. The ELISA was performed in triplicate, and Student <i>t</i>-test was performed to compare sRAGE production between mRAGEFL and mRAGEV4 at each time point. *** <i>p</i> < 0.001.</p

Examination of cellular localization of mRAGEFL and mRAGEV4 in serum-starved A549 cells.

<p>A549 cells were serum-starved for 6 h prior to transfection. (A) plasma membrane localization; (B) lysosomal localization. Blue: DAPI (nucleus); red: mcherry (mRAGEFL and mRAGEV4); green: Alexa Fluor 488-conjugated plasma membrane marker cholera toxin B (A), and GFP-tagged lysosome marker LAMP-1(B). The scale bar represents 10 μm.</p

Examination of RAGE shedding using immunoprecipitation.

<p>A549 cells were transfected with FLAG-tagged hRAGE, mRAGEFL, and mRAGEV4 expression vectors. Cell culture medium was collected 16 h post-transfection and immunoprcipitated with anti-FLAG antibodies. The cell lysates (A) and immunoprecipitants (B) were resolved with SDS gel and western blotted with anti-FLAG antibodies conjugated with HRP. * marks the resolved mRAGEFL and mRAGEV4, and β-actin level in the cell lysates was used as the loading control for cell lysates.</p

Examination of cellular localizations of mRAGEFL and mRAGEV4.

<p>(A) Plasma membrane localization; (B) early endosome localization; (C) late endosome localization. Blue: DAPI (nucleus); red: mcherry (mRAGEFL and mRAGEV4); green: Alexa Fluor 488-conjugated plasma membrane marker cholera toxin B (A), and GFP tagged early endosome marker Rab11 (B) and late endosome marker Rab 9 (C). The scale bar represents 10 μm.</p

Discovering Brain Mechanisms Using Network Analysis and Causal Modeling

Mechanist philosophers have examined several strategies scientists use for discovering causal mechanisms in neuroscience. Findings about the anatomical organization of the brain play a central role in several such strategies. Little attention has been paid, however, to the use of network analysis and causal modeling techniques for mechanism discovery. In particular, mechanist philosophers have not explored whether and how these strategies incorporate information about the anatomical organization of the brain. This paper clarifies these issues in the light of the distinction between structural, functional and effective connectivity. Specifically, we examine two quantitative strategies currently used for causal discovery from functional neuroimaging data: dynamic causal modeling and probabilistic graphical modeling. We show that dynamic causal modeling uses findings about the brain’s anatomical organization to improve the statistical estimation of parameters in an already specified causal model of the target brain mechanism. Probabilistic graphical modeling, in contrast, makes no appeal to the brain’s anatomical organization, but lays bare the conditions under which correlational data suffice to license reliable inferences about the causal organization of a target brain mechanism. The question of whether findings about the anatomical organization of the brain can and should constrain the inference of causal networks remains open, but we show how the tools supplied by graphical modeling methods help in addressing it