Organization of β-adrenoceptor signaling compartments by sympathetic innervation of cardiac myocytes

The sympathetic nervous system regulates cardiac function through the activation of adrenergic receptors (ARs). β1 and β2ARs are the primary sympathetic receptors in the heart and play different roles in regulating cardiac contractile function and remodeling in response to injury. In this study, we examine the targeting and trafficking of β1 and β2ARs at cardiac sympathetic synapses in vitro. Sympathetic neurons form functional synapses with neonatal cardiac myocytes in culture. The myocyte membrane develops into specialized zones that surround contacting axons and contain accumulations of the scaffold proteins SAP97 and AKAP79/150 but are deficient in caveolin-3. The β1ARs are enriched within these zones, whereas β2ARs are excluded from them after stimulation of neuronal activity. The results indicate that specialized signaling domains are organized in cardiac myocytes at sites of contact with sympathetic neurons and that these domains are likely to play a role in the subtype-specific regulation of cardiac function by β1 and β2ARs in vivo

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

REEPs Are Membrane Shaping Adapter Proteins That Modulate Specific G Protein-Coupled Receptor Trafficking by Affecting ER Cargo Capacity

<div><p>Receptor expression enhancing proteins (REEPs) were identified by their ability to enhance cell surface expression of a subset of G protein-coupled receptors (GPCRs), specifically GPCRs that have proven difficult to express in heterologous cell systems. Further analysis revealed that they belong to the Yip (Ypt-interacting protein) family and that some REEP subtypes affect ER structure. Yip family comparisons have established other potential roles for REEPs, including regulation of ER-Golgi transport and processing/neuronal localization of cargo proteins. However, these other potential REEP functions and the mechanism by which they selectively enhance GPCR cell surface expression have not been clarified. By utilizing several REEP family members (REEP1, REEP2, and REEP6) and model GPCRs (α2A and α2C adrenergic receptors), we examined REEP regulation of GPCR plasma membrane expression, intracellular processing, and trafficking. Using a combination of immunolocalization and biochemical methods, we demonstrated that this REEP subset is localized primarily to ER, but not plasma membranes. Single cell analysis demonstrated that these REEPs do not specifically enhance surface expression of all GPCRs, but affect ER cargo capacity of specific GPCRs and thus their surface expression. REEP co-expression with α2 adrenergic receptors (ARs) revealed that this REEP subset interacts with and alter glycosidic processing of α2C, but not α2A ARs, demonstrating selective interaction with cargo proteins. Specifically, these REEPs enhanced expression of and interacted with minimally/non-glycosylated forms of α2C ARs. Most importantly, expression of a mutant REEP1 allele (hereditary spastic paraplegia SPG31) lacking the carboxyl terminus led to loss of this interaction. Thus specific REEP isoforms have additional intracellular functions besides altering ER structure, such as enhancing ER cargo capacity, regulating ER-Golgi processing, and interacting with select cargo proteins. Therefore, some REEPs can be further described as ER membrane shaping adapter proteins.</p> </div

Confocal ER localization of REEPs with ER Tracker™ dye.

<p>HEK293A cells were transfected with Flag-REEP1, -REEP2, or -REEP6. Forty-eight hrs post-transfection, cells were fixed with 4% PFA, permeabilized, and examined by confocal microscopy. The ER was identified by staining with the ER-specific dye ER Tracker™ Blue/White DPX, which is retained within the ER lumen, thus labeling the ER tubular network (29). REEPs were stained with M2-Alexa 488 antibody (anti-Flag). REEP1/2/6 staining (Left) delineated an intracellular reticular pattern that showed extensive overlap with the ER luminal network (Middle), as seen in merged images (Right). Areas of punctate REEP expression likely represent areas of focal accumulation within the ER and confocal cross-sections of ER tubules. REEP1 demonstrated focal accumulation near the nucleus (arrow), whereas REEP2 was not found in all ER Tracker™-labeled ER regions (arrow), suggesting the existence of possible REEP/ER subdomains. Representative of three separate transfections. Scale bars: 25 µm.</p

Immunoprecipitation of α2 ARs by REEPs.

<p>HEK293A cells were co-transfected with HA-α2A or -α2C ARs and control vector, Flag-REEP1, -REEP2, or –REEP6. Eighteen hrs post-transfection, total cell lysates were isolated and analyzed by co-immunoprecipitation (co-IP) with M2 antibody (anti-Flag) and immunoblotting. Transferred proteins were probed with rabbit anti-HA Ab (A/C) or anti-M2 (B/D). Molecular weight markers (kDa) are shown to the left. Lanes representing total cell lysates (input), REEP co-IP, and α2 AR co-IP are labeled at the bottom of the blots. <b>A</b>. Note absence of α2A AR co-IP with any REEP tested (middle). <b>B</b>. Similar amounts of REEP1, REEP2, and REEP6 were present in REEP co-IP assays. <b>C</b>. REEP1, REEP2, and REEP6 could co-IP the REEP-enhanced, minimally glycosylated form of α2C AR (<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076366#pone-0076366-g009" target="_blank">Figures 9</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076366#pone-0076366-g010" target="_blank">10</a>). <b>D</b>. As seen with α2A AR/REEP co-IP assays, similar amounts of REEP1, REEP2, and REEP6 were present in REEP co-IP assays. Neither α2A nor α2C ARs could co-IP any REEP tested (B and D, right). IgG light chain artifacts are indicated by an arrow (far right).</p

Representative FACS histograms and REEP gating strategy.

<p>HEK293A cells were co-transfected with HA-α2A or -α2C ARs and control vector, Flag-REEP1, -REEP2, or –REEP6 cDNAs. Forty-eight hrs post-transfection, relative expression levels of each receptor were determined in non-permeabilized (Surface) and permeabilized (Total) cells by using a FACS assay. α2 ARs and REEPs were labeled with FITC-conjugated anti-HA and Cy3-conjugated anti-Flag (M2) antibodies respectively. <b>A</b>. Representative α2A AR FACS fluorescence distributions under non-permeabilized (Top) and permeabilized (Bottom) conditions (UT = untransfected). <b>B</b>. Representative α2C AR FACS fluorescence distributions under non-permeabilized (Top) and permeabilized (Bottom) conditions (UT = untransfected). Note the shift to higher median fluorescence upon permeabilization, which is greater for α2C vs. α2A ARs due to the larger pool of intracellular α2C ARs [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076366#B25" target="_blank">25</a>]. <b>C</b>. Representative gating strategy for FACS analysis of co-expressed α2 ARs and REEPs. Background staining of non-transfected HEK293A cells with FITC-conjugated anti-HA and Cy3-conjugated anti-Flag (M2) antibodies was determined (Top) and used to set the FACS gating thresholds for background fluorescence (Q4). Representative α2A AR and REEP1 FACS data set demonstrating co-expression of both proteins is shown (Bottom). All cells contained in quadrants Q1-3 were analyzed for calculation of REEP effects on co-expressed α2 AR surface and intracellular expression (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076366#pone-0076366-t004" target="_blank">Table <b>4A</b></a>). Data summarized from between five and eight different transfections for each combination of α2 AR and REEP with a minimum of 1000 cells analyzed for each transfection.</p

REEP co-expression enhances the presence of a minimally-glycosylated form of α2C ARs.

<p>HEK293A cells were transfected with either HA-α2A or -α2C ARs and control vector, Flag-REEP1, -REEP2, or –REEP6. Forty-eight hrs post-transfection, crude membranes were isolated and subjected to endoglycosidase digestion (<b>C</b> = No Enzyme, <b>E</b> = Endoglycosidase H (Endo H), <b>P</b> = PNGase F (PNGase)). Due to loss of signal during enzymatic digestion, 125 µg of protein was digested and loaded in each lane. Mature (<b>M</b>) and immature (<b>I</b>) glycosylated forms are indicated. Endo H cleaves only immature glycosylated forms, whereas PNGase cleaves all glycosylated forms. Molecular weight markers (kDa) are shown on the left. Note that α2A ARs exhibit mostly mature (Endo H insensitive), whereas α2C ARs show mostly immature (Endo H sensitive), glycosylation patterns, correlating with their predominant plasma membrane and intracellular localizations respectively. The presence of REEP1, REEP2, or REEP6 with either α2 AR did not alter the relative ratios of mature to immature glycosylation. However, co-expression of either REEP1, REEP2, or REEP6 with α2C ARs correlated with an increased expression of a lower molecular weight form that was minimally glycosylated (arrow), not seen following co-expression with α2A ARs. Apparent loss of the minimally glycosylated form after PNGase treatment was due to instability in PNGase enzymatic buffer conditions (data not shown). Representative of three experiments.</p