YAP/TAZ-CDC42 signaling regulates vascular tip cell migration

Angiogenesis and vascular remodeling are essential for the establishment of vascular networks during organogenesis. Here we show that the Hippo signaling pathway effectors YAP and TAZ are required, in a gene dosage-dependent manner, for the proliferation and migration of vascular endothelial cells (ECs) during retinal angiogenesis. Intriguingly, nuclear translocation of YAP and TAZ induced by Lats1/2-deletion blocked endothelial migration and phenocopied Yap/Taz-deficient mutants. Furthermore, overexpression of a cytoplasmic form of YAP (YAPS127D) partially rescued the migration defects caused by loss of YAP and TAZ function. Finally, we found that cytoplasmic YAP positively regulated the activity of the small GTPase CDC42, deletion of which caused severe defects in endothelial migration. These findings uncover a previously unrecognized role of cytoplasmic YAP/TAZ in promoting cell migration by activating CDC42 and provide insight into how Hippo signaling in ECs regulates angiogenesis

Self-Association of an Activating Natural Killer Cell Receptor, KIR2DS1

As a major component of the innate immune system, natural killer cells are responsible for activating the cytolytic killing of certain pathogen-infected or tumor cells. The self-recognition of natural killer cells is achieved in part by the killer cell immunoglobulin-like receptors (KIRs) protein family. In the current study, using a suite of biophysical methods, we investigate the self-association of an activating KIR, KIR2DS1. This KIR is of particular interest because when in the presence of the HLA-Cw6 protein, KIR2DS1 becomes a major risk factor for psoriasis, an autoimmune chronic skin disease. Using circular dichroism spectroscopy, dynamic light scattering, and atomic force microscopy, we reveal that KIR2DS1 self-associates in a well-defined fashion. Our novel results on an activating KIR allow us to suggest a working model for the KIR2DS1- HLA class I molecular mechanism

Matched sizes of activating and inhibitory receptor/ligand pairs are required for optimal signal integration by human Natural Killer cells

It has been suggested that receptor-ligand complexes segregate or co-localise within immune synapses according to their size, and this is important for receptor signaling. Here, we set out to test the importance of receptor-ligand complex dimensions for immune surveillance of target cells by human Natural Killer (NK) cells. NK cell activation is regulated by integrating signals from activating receptors, such as NKG2D, and inhibitory receptors, such as KIR2DL1. Elongating the NKG2D ligand MICA reduced its ability to trigger NK cell activation. Conversely, elongation of KIR2DL1 ligand HLA-C reduced its ability to inhibit NK cells. Whereas normal-sized HLA-C was most effective at inhibiting activation by normal-length MICA, only elongated HLA-C could inhibit activation by elongated MICA. Moreover, HLA-C and MICA that were matched in size co-localised, whereas HLA-C and MICA that were different in size were segregated. These results demonstrate that receptor-ligand dimensions are important in NK cell recognition, and suggest that optimal integration of activating and inhibitory receptor signals requires the receptor-ligand complexes to have similar dimensions

Measuring our universe from galaxy redshift surveys

Galaxy redshift surveys have achieved significant progress over the last couple of decades. Those surveys tell us in the most straightforward way what our local universe looks like. While the galaxy distribution traces the bright side of the universe, detailed quantitative analyses of the data have even revealed the dark side of the universe dominated by non-baryonic dark matter as well as more mysterious dark energy (or Einstein's cosmological constant). We describe several methodologies of using galaxy redshift surveys as cosmological probes, and then summarize the recent results from the existing surveys. Finally we present our views on the future of redshift surveys in the era of Precision Cosmology.Comment: 82 pages, 31 figures, invited review article published in Living Reviews in Relativity, http://www.livingreviews.org/lrr-2004-

Novel Information on the Epitope of an Inverse Agonist Monoclonal Antibody Provides Insight into the Structure of the TSH Receptor

The TSH receptor (TSHR) comprises an extracellular leucine-rich domain (LRD) linked by a hinge region to the transmembrane domain (TMD). Insight into the orientation of these components to each other is required for understanding how ligands activate the receptor. We previously identified residue E251 at the LRD-hinge junction as contributing to coupling TSH binding with receptor activation. However, a single residue cannot stabilize the LRD-hinge unit. Therefore, based on the LRD crystal structure we selected for study four other potential LRD-hinge interface charged residues. Alanine substitutions of individual residues K244, E247, K250 and R255 (as well as previously known E251A) did not affect TSH binding or function. However, the cumulative mutation of these residues in varying permutations, primarily K250A and R255A when associated with E251A, partially uncoupled TSH binding and function. These data suggest that these three residues, spatially very close to each other at the LRD base, interact with the hinge region. Unexpectedly and most important, monoclonal antibody CS-17, a TSHR inverse agonist whose epitope straddles the LRD-hinge, was found to interact with residues K244 and E247 at the base of the convex LRD surface. These observations, together with the functional data, exclude residues K244 and E247 from the TSHR LRD-hinge interface. Further, for CS-17 accessibility to K244 and E247, the concave surface of the TSHR LRD must be tilted forwards towards the hinge region and plasma membrane. Overall, these data provide insight into the mechanism by which ligands either activate the TSHR or suppress its constitutive activity

Mycobacterium vaccae as Adjuvant Therapy to Anti-Tuberculosis Chemotherapy in Never-Treated Tuberculosis Patients: A Meta-Analysis

OBJECTIVE: To evaluate the effectiveness and safety of heat-killed M. vaccae added to chemotherapy of never-treated tuberculosis (TB) patients. METHODS: The databases of Medline, Embase, Biosis, Cochrane Central Register of Controlled Trials, SCI, CBM, VIP and CNKI were searched. Randomized controlled trials (RCT) and Controlled clinical trials (CCT) comparing M. vaccae with or without a placebo-control injection as adjuvant therapy in the chemotherapy of never-treated TB patients were included. Two reviewers independently performed data extraction and quality assessment. Data were analyzed using RevMan 5.0 software by The Cochrane Collaboration. RESULTS: Fifty four studies were included. At the end of the follow-up period, Pooled RR (Risk Ratio) and its 95% CI of sputum smear conversion rate were 1.07 (1.04, 1.10) in TB patients without complications, 1.17 (0.92, 1.49) in TB patients with diabetes mellitus, 1.02 (0.94, 1.10) in TB patients with hepatitis B, and 1.46 (0.21, 10.06) in TB patients with pneumosilicosis. In elderly TB patients the RR was 1.22 (1.13, 1.32). Analysis of each time point during the follow-up period showed that M. vaccae could help to improve the removal of acid-fast bacilli from the sputum, and promote improvement of radiological focal lesions and cavity closure. Compared with the control group, the differences in levels of immunological indicators of Th1 such as IL-2 and TNF-α were not statistical significant (P = 0.65 and 0.31 respectively), and neither was that of IL-6 produced by Th2 (P = 0.52). An effect of M. vaccae of prevention of liver damage was found in TB patients with hepatitis B (RR 0.20 and 95% CI (0.12, 0.33). No systemic adverse events were reported. CONCLUSION: Added to chemotherapy, M. vaccae is helpful in the treatment of never-treated TB patients in terms of improving both sputum conversion and X-ray appearances

Can Survival Prediction Be Improved By Merging Gene Expression Data Sets?

BACKGROUND:High-throughput gene expression profiling technologies generating a wealth of data, are increasingly used for characterization of tumor biopsies for clinical trials. By applying machine learning algorithms to such clinically documented data sets, one hopes to improve tumor diagnosis, prognosis, as well as prediction of treatment response. However, the limited number of patients enrolled in a single trial study limits the power of machine learning approaches due to over-fitting. One could partially overcome this limitation by merging data from different studies. Nevertheless, such data sets differ from each other with regard to technical biases, patient selection criteria and follow-up treatment. It is therefore not clear at all whether the advantage of increased sample size outweighs the disadvantage of higher heterogeneity of merged data sets. Here, we present a systematic study to answer this question specifically for breast cancer data sets. We use survival prediction based on Cox regression as an assay to measure the added value of merged data sets. RESULTS:Using time-dependent Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) and hazard ratio as performance measures, we see in overall no significant improvement or deterioration of survival prediction with merged data sets as compared to individual data sets. This apparently was due to the fact that a few genes with strong prognostic power were not available on all microarray platforms and thus were not retained in the merged data sets. Surprisingly, we found that the overall best performance was achieved with a single-gene predictor consisting of CYB5D1. CONCLUSIONS:Merging did not deteriorate performance on average despite (a) The diversity of microarray platforms used. (b) The heterogeneity of patients cohorts. (c) The heterogeneity of breast cancer disease. (d) Substantial variation of time to death or relapse. (e) The reduced number of genes in the merged data sets. Predictors derived from the merged data sets were more robust, consistent and reproducible across microarray platforms. Moreover, merging data sets from different studies helps to better understand the biases of individual studies and can lead to the identification of strong survival factors like CYB5D1 expression

KIR Polymorphisms Modulate Peptide-Dependent Binding to an MHC Class I Ligand with a Bw6 Motif

Molecular interactions between killer immunoglobulin-like receptors (KIRs) and their MHC class I ligands play a central role in the regulation of natural killer (NK) cell responses to viral pathogens and tumors. Here we identify Mamu-A1*00201 (Mamu-A*02), a common MHC class I molecule in the rhesus macaque with a canonical Bw6 motif, as a ligand for Mamu-KIR3DL05. Mamu-A1*00201 tetramers folded with certain SIV peptides, but not others, directly stained primary NK cells and Jurkat cells expressing multiple allotypes of Mamu-KIR3DL05. Differences in binding avidity were associated with polymorphisms in the D0 and D1 domains of Mamu-KIR3DL05, whereas differences in peptide-selectivity mapped to the D1 domain. The reciprocal exchange of the third predicted MHC class I-contact loop of the D1 domain switched the specificity of two Mamu-KIR3DL05 allotypes for different Mamu-A1*00201-peptide complexes. Consistent with the function of an inhibitory KIR, incubation of lymphocytes from Mamu-KIR3DL05+ macaques with target cells expressing Mamu-A1*00201 suppressed the degranulation of tetramer-positive NK cells. These observations reveal a previously unappreciated role for D1 polymorphisms in determining the selectivity of KIRs for MHC class I-bound peptides, and identify the first functional KIR-MHC class I interaction in the rhesus macaque. The modulation of KIR-MHC class I interactions by viral peptides has important implications to pathogenesis, since it suggests that the immunodeficiency viruses, and potentially other types of viruses and tumors, may acquire changes in epitopes that increase the affinity of certain MHC class I ligands for inhibitory KIRs to prevent the activation of specific NK cell subsets

Differentiating Protein-Coding and Noncoding RNA: Challenges and Ambiguities

The assumption that RNA can be readily classified into either protein-coding or non-protein–coding categories has pervaded biology for close to 50 years. Until recently, discrimination between these two categories was relatively straightforward: most transcripts were clearly identifiable as protein-coding messenger RNAs (mRNAs), and readily distinguished from the small number of well-characterized non-protein–coding RNAs (ncRNAs), such as transfer, ribosomal, and spliceosomal RNAs. Recent genome-wide studies have revealed the existence of thousands of noncoding transcripts, whose function and significance are unclear. The discovery of this hidden transcriptome and the implicit challenge it presents to our understanding of the expression and regulation of genetic information has made the need to distinguish between mRNAs and ncRNAs both more pressing and more complicated. In this Review, we consider the diverse strategies employed to discriminate between protein-coding and noncoding transcripts and the fundamental difficulties that are inherent in what may superficially appear to be a simple problem. Misannotations can also run in both directions: some ncRNAs may actually encode peptides, and some of those currently thought to do so may not. Moreover, recent studies have shown that some RNAs can function both as mRNAs and intrinsically as functional ncRNAs, which may be a relatively widespread phenomenon. We conclude that it is difficult to annotate an RNA unequivocally as protein-coding or noncoding, with overlapping protein-coding and noncoding transcripts further confounding this distinction. In addition, the finding that some transcripts can function both intrinsically at the RNA level and to encode proteins suggests a false dichotomy between mRNAs and ncRNAs. Therefore, the functionality of any transcript at the RNA level should not be discounted

Human-Specific Evolution and Adaptation Led to Major Qualitative Differences in the Variable Receptors of Human and Chimpanzee Natural Killer Cells

Natural killer (NK) cells serve essential functions in immunity and reproduction. Diversifying these functions within individuals and populations are rapidly-evolving interactions between highly polymorphic major histocompatibility complex (MHC) class I ligands and variable NK cell receptors. Specific to simian primates is the family of Killer cell Immunoglobulin-like Receptors (KIR), which recognize MHC class I and associate with a range of human diseases. Because KIR have considerable species-specificity and are lacking from common animal models, we performed extensive comparison of the systems of KIR and MHC class I interaction in humans and chimpanzees. Although of similar complexity, they differ in genomic organization, gene content, and diversification mechanisms, mainly because of human-specific specialization in the KIR that recognizes the C1 and C2 epitopes of MHC-B and -C. Humans uniquely focused KIR recognition on MHC-C, while losing C1-bearing MHC-B. Reversing this trend, C1-bearing HLA-B46 was recently driven to unprecedented high frequency in Southeast Asia. Chimpanzees have a variety of ancient, avid, and predominantly inhibitory receptors, whereas human receptors are fewer, recently evolved, and combine avid inhibitory receptors with attenuated activating receptors. These differences accompany human-specific evolution of the A and B haplotypes that are under balancing selection and differentially function in defense and reproduction. Our study shows how the qualitative differences that distinguish the human and chimpanzee systems of KIR and MHC class I predominantly derive from adaptations on the human line in response to selective pressures placed on human NK cells by the competing needs of defense and reproduction