Somatostatin inhibits dendritic cell responsiveness to Helicobacter pylori

Somatostatin is a regulatory peptide found in abundance in the stomach. We have previously shown that somatostatin is required for IL-4-mediated resolution of Helicobacter pylori gastritis. In the current study, we hypothesize that somatostatin acts directly on antigen-presenting cells in the stomach to lessen the severity of gastritis. To test this hypothesis, we first show that CD11c+ dendritic cells are present in the infected tissue of mice with H. pylori-induced gastritis. Pretreatment of bone marrow-derived dendritic cells with somatostatin results in decreased IL-12 production, and lower splenocyte proliferation induced by H. pylori-stimulated dendritic cells. Furthermore, octreotide, a somatostatin analogue, is more potent than somatostatin in suppressing IL-12 release by H. pylori-stimulated dendritic cells through an NF-kappaB-independent pathway. In addition, IL-4 stimulates somatostatin secretion from dendritic cells. In conclusion, somatostatin inhibits dendritic cell activation by H. pylori; a possible mechanism by which IL-4 mediates resolution of gastritis. We suggest that octreotide may be effective in treating immune-mediated diseases of the stomach.     

Regulation of stomatal movement by cortical microtubule organization in response to darkness and ABA signaling in <Emphasis Type="Italic">Arabidopsis</Emphasis>

Microtubule dynamics are essential for plant cell development and in producing responses to external stimuli. However, little is known about the regulation of microtubule dynamics or crosstalk between microtubule and stomatal movement. Here we identified microtubule reorganization as a crucial factor determining guard cell responses to dark and abscisic acid (ABA) signaling. As stomata opened, guard cells exhibited radially arranged cortical microtubules, which depolymerized into the cytosol when exposed to darkness and ABA. Suppression of microtubule disassembly by paclitaxel, a microtubule-stabilizing drug, significantly enhanced stomatal aperture under light, and partially blocked ABA- or darkness-induced stomatal closure. However, treatment with only the anti-microtubule drug, oryzalin, did not affect stomatal movement with or without external stimuli. Phosphatidic acid (PA) bound to a clade A type 2C protein phosphatase (PP2C), PP2CA, and deletion of PP2CA partially inhibited PA-induced microtubule depolymerization and stomatal closure. Moreover, microtubule reorganization was altered in the ABA-insensitive mutant pldα1, but not in the ABA-hypersensitive mutant pp2ca. We propose that a faithfully balanced reorganization of microtubules fulfills fundamental functions to enable the fast change of stomata in plant adaptive responses to developmental and environmental cues.     

A cluster pattern algorithm for the analysis of multiparametric cell assays.

The issue of multiparametric analysis of complex single cell assays of both static and flow cytometry (SC and FC, respectively) has become common in recent years. In such assays, the analysis of changes, applying common statistical parameters and tests, often fails to detect significant differences between the investigated samples. The cluster pattern similarity (CPS) measure between two sets of gated clusters is based on computing the difference between their density distribution functions' set points. The CPS was applied for the discrimination between two observations in a four-dimensional parameter space. The similarity coefficient (r) ranges between 0 (perfect similarity) to 1 (dissimilar). Three CPS validation tests were carried out: on the same stock samples of fluorescent beads, yielding very low r's (0, 0.066); and on two cell models: mitogenic stimulation of peripheral blood mononuclear cells (PBMC), and apoptosis induction in Jurkat T cell line by H2O2. In both latter cases, r indicated similarity (r < 0.23) within the same group, and dissimilarity (r > 0.48) otherwise. This classification and algorithm approach offers a measure of similarity between samples. It relies on the multidimensional pattern of the sample parameters. The algorithm compensates for environmental drifts in this apparatus and assay; it also may be applied to more than four dimensions.     

Heterochromatin restricts the mobility of nuclear bodies

Nuclear bodies are relatively immobile organelles. Here, we investigated the mechanisms underlying their movement using experimentally induced interphase prenucleolar bodies (iPNBs). Most iPNBs demonstrated constrained diffusion, exhibiting infrequent fusions with other iPNBs and nucleoli. Fusion events were actin-independent and appeared to be the consequence of stochastic collisions between iPNBs. Most iPNBs were surrounded by condensed chromatin, while fusing iPNBs were usually found in a single heterochromatin-delimited compartment (“cage”). The experimentally induced over-condensation of chromatin significantly decreased the frequency of iPNB fusion. Thus, the data obtained indicate that the mobility of nuclear bodies is restricted by heterochromatin.     

Decoding the effects of synonymous variants

Synonymous single nucleotide variants (sSNVs) are common in the human genome but are often overlooked. However, sSNVs can have significant biological impact and may lead to disease. Existing computational methods for evaluating the effect of sSNVs suffer from the lack of gold-standard training/evaluation data and exhibit over-reliance on sequence conservation signals. We developed synVep (synonymous Variant effect predictor), a machine learning-based method that overcomes both of these limitations. Our training data was a combination of variants reported by gnomAD (observed) and those unreported, but possible in the human genome (generated). We used positive-unlabeled learning to purify the generated variant set of any likely unobservable variants. We then trained two sequential extreme gradient boosting models to identify subsets of the remaining variants putatively enriched and depleted in effect. Our method attained 90% precision/recall on a previously unseen set of variants. Furthermore, although synVep does not explicitly use conservation, its scores correlated with evolutionary distances between orthologs in cross-species variation analysis. synVep was also able to differentiate pathogenic vs. benign variants, as well as splice-site disrupting variants (SDV) vs. non-SDVs. Thus, synVep provides an important improvement in annotation of sSNVs, allowing users to focus on variants that most likely harbor effects.     

The p110δ subunit of PI3K regulates bone marrow-derived eosinophil trafficking and airway eosinophilia in allergen-challenged mice

Trafficking and recruitment of eosinophils during allergic airway inflammation is mediated by the phosphatidylinositol 3-kinase (PI3K) family of signaling molecules. The role played by the p110δ subunit of PI3K (PI3K p110δ) in regulating eosinophil trafficking and recruitment was investigated using a selective pharmacological inhibitor (IC87114). Treatment with the PI3K p110δ inhibitor significantly reduced murine bone marrow-derived eosinophil (BM-Eos) adhesion to VCAM-1 as well as ICAM-1 and inhibited activation-induced changes in cell morphology associated with reduced Mac-1 expression and aberrant cell surface localization/distribution of Mac-1 and α4. Infused BM-Eos demonstrated significantly decreased rolling and adhesion in inflamed cremaster muscle microvessels of mice treated with IC87114 compared with vehicle-treated mice. Furthermore, inhibition of PI3K p110δ significantly attenuated eotaxin-1-induced BM-Eos migration and prevented eotaxin-1-induced changes in the cytoskeleton and cell morphology. Knockdown of PI3K p110δ with siRNA in BM-Eos resulted in reduced rolling, adhesion, and migration, as well as inhibition of activation-induced changes in cell morphology, validating its role in regulating trafficking and migration. Finally, in a mouse model of cockroach antigen-induced allergic airway inflammation, oral administration of the PI3K p110δ inhibitor significantly inhibited airway eosinophil recruitment, resulting in attenuation of airway hyperresponsiveness in response to methacholine, reduced mucus secretion, and expression of proinflammatory molecules (found in inflammatory zone-1 and intelectin-1). Overall, these findings indicate the important role played by PI3K p110δ in mediating BM-Eos trafficking and migration by regulating adhesion molecule expression and localization/distribution as well as promoting changes in cell morphology that favor recruitment during inflammation.     

Base-Calling Algorithm with Vocabulary (BCV) Method for Analyzing Population Sequencing Chromatograms

Sanger sequencing is a common method of reading DNA sequences. It is less expensive than high-throughput methods, and it is appropriate for numerous applications including molecular diagnostics. However, sequencing mixtures of similar DNA of pathogens with this method is challenging. This is important because most clinical samples contain such mixtures, rather than pure single strains. The traditional solution is to sequence selected clones of PCR products, a complicated, time-consuming, and expensive procedure. Here, we propose the base-calling with vocabulary (BCV) method that computationally deciphers Sanger chromatograms obtained from mixed DNA samples. The inputs to the BCV algorithm are a chromatogram and a dictionary of sequences that are similar to those we expect to obtain. We apply the base-calling function on a test dataset of chromatograms without ambiguous positions, as well as one with 3–14% sequence degeneracy. Furthermore, we use BCV to assemble a consensus sequence for an HIV genome fragment in a sample containing a mixture of viral DNA variants and to determine the positions of the indels. Finally, we detect drug-resistant Mycobacterium tuberculosis strains carrying frameshift mutations mixed with wild-type bacteria in the pncA gene, and roughly characterize bacterial communities in clinical samples by direct 16S rRNA sequencing.