Bradykinin receptors: towards new pathophysiological roles

In addition to being a pro-inflammatory mediator, bradykinin is now recognized as a neuromediator and regulator of several vascular and renal functions. New breakthroughs point to unusual and atypical signalling pathways for a G-protein coupled receptor that could explain the anti-proliferative and anti-fibrogenic effects of bradykinin. The availability of transgenic and knock out animal models for bradykinin receptors or bradykinin-synthesizing or -catabolic enzymes confirms these cardiac and renal protective roles for this peptide system. Bradykinin receptors are involved in the therapeutic action of angiotensin-1 converting enzyme inhibitors that are used in the treatment of arterial hypertension, heart failure and diabetes. Nevertheless, recent evidence highlights dissimilar mechanisms in the regulation and function of these receptors between the central nervous system and peripheral tissues. Therefore, the development of more specific bradykinin receptor agonists or antagonists devoid of central actions seems to evolve as a new therapeutic approach.     

Exploring the conformational space of membrane protein folds matching distance constraints

Herein we present a computational technique for generating helix-membrane protein folds matching a predefined set of distance constraints, such as those obtained from NMR NOE, chemical cross-linking, dipolar EPR, and FRET experiments. The purpose of the technique is to provide initial structures for local conformational searches based on either energetic considerations or ad-hoc scoring criteria. In order to properly screen the conformational space, the technique generates an exhaustive list of conformations within a specified root-mean-square deviation (RMSD) where the helices are positioned in order to match the provided distances. Our results indicate that the number of structures decreases exponentially as the number of distances increases, and increases exponentially as the errors associated with the distances increases. We also found the number of solutions to be smaller when all the distances share one helix in common, compared to the case where the distances connect helices in a daisy-chain manner. We found that for 7 helices, at least 15 distances with errors up to 8 A are needed to produce a number of solutions that is not too large to be processed by local search refinement procedures. Finally, without energetic considerations, our enumeration technique retrieved the transmembrane domains of Bacteriorhodopsin (PDB entry1c3w), Halorhodopsin (1e12), Rhodopsin (1f88), Aquaporin-1 (1fqy), Glycerol uptake facilitator protein (1fx8), Sensory Rhodopsin (1jgj), and a subunit of Fumarate reductase flavoprotein (1qlaC) with Calpha level RMSDs of 3.0 A, 2.3 A, 3.2 A, 4.6 A, 6.0 A, 3.7 A, and 4.4 A, respectively.     

Optimal bundling of transmembrane helices using sparse distance constraints

We present a two-step approach to modeling the transmembrane spanning helical bundles of integral membrane proteins using only sparse distance constraints, such as those derived from chemical cross-linking, dipolar EPR and FRET experiments. In Step 1, using an algorithm, we developed, the conformational space of membrane protein folds matching a set of distance constraints is explored to provide initial structures for local conformational searches. In Step 2, these structures refined against a custom penalty function that incorporates both measures derived from statistical analysis of solved membrane protein structures and distance constraints obtained from experiments. We begin by describing the statistical analysis of the solved membrane protein structures from which the theoretical portion of the penalty function was derived. We then describe the penalty function, and, using a set of six test cases, demonstrate that it is capable of distinguishing helical bundles that are close to the native bundle from those that are far from the native bundle. Finally, using a set of only 27 distance constraints extracted from the literature, we show that our method successfully recovers the structure of dark-adapted rhodopsin to within 3.2 A of the crystal structure.     

Oligocene sivaladapid primate from the Bugti Hills (Balochistan, Pakistan) bridges the gap between Eocene and Miocene adapiform communities in Southern Asia

A new species of Guangxilemur (Sivaladapidae, Adapiformes) is described from the early Oligocene Chitarwata Formation (Bugti Member) of the Bugti Hills, Sulaiman geological Province, Balochistan, Pakistan. Guangxilemur singsilai n. sp. provides further diagnostic morphological characters from its newly described upper and lower dentitions, confirming its intermediate phylogenetic position between Eocene and Miocene Asian sivaladapid adapiforms. G. singsilai possesses moderately developed shearing and puncturing molar features and maintains lingual cusps on upper molars as in Eocene hoanghoniines; in contrast, it possesses a typical molariform P(4) as in Miocene sivaladapines. The important paleogeographic changes that have affected South Asia during the Tertiary (related to the collision between the Indian and Eurasian Plates) have played a critical role in reforming circulation and climatic differentiation. The presence in Pakistan of an unique and well-diversified Oligocene primate fauna, clearly demonstrates that South Asia maintained favourable environmental conditions during the middle Caenozoic global climatic deterioration that coincides with drastic changes in faunal structure on the whole Holarctic Province, including the extinction of adapiform primates.     

Calponin and SM22 as differentiation markers of smooth muscle: spatiotemporal distribution during avian embryonic development

Abstract. Calponin and SM 22 are two proteins related in sequence that are particularly abundant in smooth muscle cells. Here, the distribution patterns of calponin and SM 22 were compared with that of other smooth muscle contractile and cytoskeletal components in the avian embryo using immunofluorescence microscopy and immunoblotting. Like myosin-light-chain kinase and heavy caldesmon, both calponin and SM 22 were more or less exclusively found in smooth muscle cells, during embryonic development and in the adult. Labelling of other cell types including striated muscle was not observed. In contrast, tropomyosin, smooth muscle α-actin, filamin and desmin could also be detected in many other cell types in addition to smooth muscles, at least during part of embryonic life. Calponin and SM 22 appeared almost synchronously during the differentiation of all smooth muscle cell populations, though with a slight time difference in the case of the aorta. The appearance of calponin, SM22 and heavy caldesmon was generally delayed in relation to desmin, tropomyosin, smooth muscle α-actin, myosin-light-chain kinase and filamin and a marked increase in abundance of these proteins was observed in the late embryo and in the adult. From these observations we can conclude that both calponin and SM 22 belong to a group of late differentiation determinants in smooth muscle and may constitute convenient and reliable markers to follow the differentiation of most, if not all, smooth muscle cell populations.     

Production of macrophage-activated killer cells for targeting of glioblastoma cells with bispecific antibody to FcγRI and the epidermal growth factor receptor

Objective: The aim was to determine the ability of macrophage-activated killer cells (MAK cells) obtained from peripheral blood of normal volunteers to kill glioblastoma multiforme (GBM) cell lines. Another goal was to investigate whether a bispecific antibody (bsAb) MDX-447, recognizing the high-affinity Fc receptor for IgG (FcγRI) and epidermal growth factor receptor (EGFR), would enhance MAK cell tumoricidal activity. Methods: Monocytes, from leukapheresis product, were isolated by countercurrent elutriation and differentiated into MAK cells by culture with granulocyte/macrophage-colony-stimulating factor, vitamin D₃ and interferon γ. Cells were checked for sterility, endotoxin and phenotypic markers. MAK cell functional activity was measured by a flow-cytometric phagocytosis assay. Target cells, a carcinoma cell line and two glioma cell lines expressing EGFR, were stained with PKH-26. MAK cells were labeled with fluorescein-conjugated anti-CD14. Combined effectors, targets and bsAb were incubated and the percentage of MAK cells with phagocytosed targets was determined by flow cytometry. Conclusion: We demonstrate that a large number of highly purified monocytes, isolated from peripheral blood, can be differentiated into MAK cells for use as an adjuvant for cancer treatment. After culture these cells are sterile, endotoxin-free and comprise more than 95% MAK cells. Increased amounts of CD14, CD64 and HLA-DR, which are characteristics of macrophage activation, were expressed. MAK cells were extremely phagocytic in comparison to monocytes, even in the absence of bsAb. Moreover, bsAb enhanced the tumoricidal activity of elutriated MAK cells targeted against GBM cell lines. Therefore, intracavity MAK cells armed with MDX-447 could be an effective adoptive immunotherapy for EGFR-positive GBM. Received: 5 April 2000 / Accepted: 12 July 2000     

Label-free Quantitative Urinary Proteomics Identifies the Arginase Pathway as a New Player in Congenital Obstructive Nephropathy

Obstructive nephropathy is a frequently encountered situation in newborns. In previous studies, the urinary peptidome has been analyzed for the identification of clinically useful biomarkers of obstructive nephropathy. However, the urinary proteome has not been explored yet and should allow additional insight into the pathophysiology of the disease. We have analyzed the urinary proteome of newborns (n = 5/group) with obstructive nephropathy using label free quantitative nanoLC-MS/MS allowing the identification and quantification of 970 urinary proteins. We next focused on proteins exclusively regulated in severe obstructive nephropathy and identified Arginase 1 as a potential candidate molecule involved in the development of obstructive nephropathy, located at the crossroad of pro- and antifibrotic pathways. The reduced urinary abundance of Arginase 1 in obstructive nephropathy was verified in independent clinical samples using both Western blot and MRM analysis. These data were confirmed in situ in kidneys obtained from a mouse obstructive nephropathy model. In addition, we also observed increased expression of Arginase 2 and increased total arginase activity in obstructed mouse kidneys. mRNA expression analysis of the related arginase pathways indicated that the pro-fibrotic arginase-related pathway is activated during obstructive nephropathy. Taken together we have identified a new actor in the development of obstructive nephropathy in newborns using quantitative urinary proteomics and shown its involvement in an in vivo model of disease. The present study demonstrates the relevance of such a quantitative urinary proteomics approach with clinical samples for a better understanding of the pathophysiology and for the discovery of potential therapeutic targets.Congenital obstructive nephropathy is the main cause of end stage renal disease (ESRD) in children (1). The most frequently found cause of congenital obstructive nephropathy is ureteropelvic junction (UPJ)¹ obstruction with an estimated incidence of 1 in 1000–1500 births. Milder forms of UPJ obstruction often progress to the spontaneous resolution of the pathology over time. This has led to a watchful waiting approach with surgical intervention only if renal deterioration is detected (2). Although this medical surveillance prevents unnecessary surgery, it mostly relies on invasive follow-up. Consequently with the aim to reduce this invasive follow-up, several groups have initiated research to identify noninvasive urinary biomarkers of UPJ obstruction using both targeted and nontargeted (e.g. proteome analysis based) strategies. Targeted strategies including urinary cytokine expression analyses failed to clearly determine the need for surgery in UPJ obstruction (3, 4). On the other hand, untargeted strategies have been more successful and by using urinary proteomics, biomarkers for renal and non-renal diseases have been identified (5–9). Using urinary peptidome analysis, we identified and validated a urinary peptide panel that predicted the clinical outcome of newborns with UPJ obstruction with 97% accuracy several months in advance (3, 10). An independent small-scale study confirmed the efficiency of this biomarker panel (7). These studies indicate the potential of urinary proteomics to predict the clinical fate of patients with UPJ obstruction. Although these endogenous urinary peptide biomarkers are of great potential clinical value, sequencing of these biomarkers mainly identified collagen fragments that are less informative on the pathophysiology of the disease. In contrast, studies of the high molecular weight urinary proteome (i.e. proteins) might be more informative on the pathophysiology of disease. Different approaches have been used in the past to characterize the urinary proteome, either by 2D-gel electrophoresis coupled to mass spectrometry (11, 12) or reverse phase liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) analysis (13–16). In-depth proteome analysis using extensive fractionation of the sample and high resolution, fast sequencing mass spectrometers have reported the identification of >2000 proteins in normal human urine (13, 15, 16). Here, we applied quantitative high-resolution label free LC-MS/MS analysis for the identification of urinary proteins associated to UPJ obstruction in newborns. Among a number of proteins uniquely associated with severe UPJ obstruction, we identified Arginase 1, not previously recognized in UPJ obstruction. Using an independent larger cohort, we further verified reduced urinary abundance of Arginase 1 using both Western blot and multiple reaction monitoring (MRM). Using the mouse model of obstructive nephropathy, we observed that the expression of arginases is modulated in situ in obstructed kidneys. Further gene expression analysis of the arginase pathway allowed us to hypothesize for a role of arginases in the development of fibrotic lesions in obstructive nephropathy.     

Compound toxicity screening and structure-activity relationship modeling in Escherichia coli

Synthetic biology and metabolic engineering are used to develop new strategies for producing valuable compounds ranging from therapeutics to biofuels in engineered microorganisms. When developing methods for high-titer production cells, toxicity is an important element to consider. Indeed the production rate can be limited due to toxic intermediates or accumulation of byproducts of the heterologous biosynthetic pathway of interest. Conversely, highly toxic molecules are desired when designing antimicrobials. Compound toxicity in bacteria plays a major role in metabolic engineering as well as in the development of new antibacterial agents. Here, we screened a diversified chemical library of 166 compounds for toxicity in Escherichia coli. The dataset was built using a clustering algorithm maximizing the chemical diversity in the library. The resulting assay data was used to develop a toxicity predictor that we used to assess the toxicity of metabolites throughout the metabolome. This new tool for predicting toxicity can thus be used for fine-tuning heterologous expression and can be integrated in a computational-framework for metabolic pathway design. Many structure-activity relationship tools have been developed for toxicology studies in eukaryotes [Valerio (2009), Toxicol Appl Pharmacol, 241(3): 356-370], however, to the best of our knowledge we present here the first E. coli toxicity prediction web server based on QSAR models (EcoliTox server: http://www.issb.genopole.fr/～faulon/EcoliTox.php).