Paradoxical protective effect of central obesity in patients with suspected stable coronary artery disease

Objective:

Increased body mass index (BMI) has been paradoxically inversely associated with the presence of angiographic coronary artery disease (CAD). Central obesity measures, considered to be more appropriate for assessing obesity‐related cardiovascular risk, have been little studied in relation to the presence of CAD. The aim was to investigate the association of central obesity with the presence of angiographic CAD as well as the prognostic significance of obesity measures in CAD prediction when added to other cardiovascular risk factors.

Design and Methods:

Patients with suspected stable CAD (n = 403, age 61 ± 10 years, 302 males) referred for diagnostic coronary angiography with documented anthropometric data were enrolled.

Results:

Significant angiographic CAD was found in 51% of patients. Both BMI (OR = 0.64 per 1 SD increase, P = 0.001) and waist circumference (WC) (OR = 0.54 per 1 SD increase, P < 0.001) were inversely associated with the presence of CAD even after adjustment for cardiovascular risk factors. In subgroup analysis, BMI and WC were significantly inversely associated with the presence of CAD in males, non diabetics, patients >60 years old and patients with Framingham risk score (FRS) >20% (P < 0.01 for all). The addition of BMI or WC in FRS‐based regression models improved prediction of CAD (P = 0.03 and P < 0.001 for BMI and WC respectively) without a significant difference between the two models (P = 0.08).

Conclusions:

Central and overall obesity were independently associated with a reduced prevalence of angiographic CAD, lending further credence to the existence of the ‘obesity paradox’. Obesity measures may further improve risk discrimination for the presence of CAD when added in an established risk score such as FRS.     

The Escherichia coli Peripheral Inner Membrane Proteome

Biological membranes are essential for cell viability. Their functional characteristics strongly depend on their protein content, which consists of transmembrane (integral) and peripherally associated membrane proteins. Both integral and peripheral inner membrane proteins mediate a plethora of biological processes. Whereas transmembrane proteins have characteristic hydrophobic stretches and can be predicted using bioinformatics approaches, peripheral inner membrane proteins are hydrophilic, exist in equilibria with soluble pools, and carry no discernible membrane targeting signals. We experimentally determined the cytoplasmic peripheral inner membrane proteome of the model organism Escherichia coli using a multidisciplinary approach. Initially, we extensively re-annotated the theoretical proteome regarding subcellular localization using literature searches, manual curation, and multi-combinatorial bioinformatics searches of the available databases. Next we used sequential biochemical fractionations coupled to direct identification of individual proteins and protein complexes using high resolution mass spectrometry. We determined that the proposed cytoplasmic peripheral inner membrane proteome occupies a previously unsuspected ∼19% of the basic E. coli BL21(DE3) proteome, and the detected peripheral inner membrane proteome occupies ∼25% of the estimated expressed proteome of this cell grown in LB medium to mid-log phase. This value might increase when fleeting interactions, not studied here, are taken into account. Several proteins previously regarded as exclusively cytoplasmic bind membranes avidly. Many of these proteins are organized in functional or/and structural oligomeric complexes that bind to the membrane with multiple interactions. Identified proteins cover the full spectrum of biological activities, and more than half of them are essential. Our data suggest that the cytoplasmic proteome displays remarkably dynamic and extensive communication with biological membrane surfaces that we are only beginning to decipher.An in-depth understanding of cellular proteomes requires knowledge of protein subcellular topology, assembly in macromolecular complexes, and modification and degradation of poplypeptides. Escherichia coli, a model organism for many such studies, is by far the best studied. The genomes of strain K-12 derivatives MG1655 and W3110 have been sequenced (1, 2), and >75% of their genes have been functionally assigned (3). Almost 90% of the K-12 proteome has been identified experimentally, and >73% of its proteins have known structures (4, 5). Moreover, the genomes of another 38 E. coli strains have been determined (see EcoliWiki for details).In E. coli, like in all Gram-negative bacteria, the bacterial cell envelope comprises the plasma or inner membrane and the outer membrane, which are separated by the periplasmic space. The inner membrane encloses the cytoplasm and is a dynamic substructure. It harbors a wide variety of proteins that function in vital cell processes such as the trafficking of ions, molecules, and macromolecules; cell division; environmental sensing; lipid, polysaccharide, and peptidoglycan biosynthesis; and metabolism. Inner membrane proteins either fully span the lipid bilayer using one or more hydrophobic transmembrane helices (integral) or are bound either directly to phospholipid components or via protein–protein interactions to the surface of the membrane (peripheral) (6) (Fig. 1A). Peripheral inner membrane proteins exist on either side of the membrane and may be recruited in membrane-associated complexes on demand (7). Peripheral inner membrane proteins on the cytoplasmic side constitute a sub-proteome of central importance because of their interaction with the cytoplasmic proteome, the nucleoid, and most of the cell''s metabolism. Thanks to their soluble character and the nature of their interactions with the membrane (mostly electrostatic and moderate hydrophobic interactions (7)), peripheral inner membrane proteins can be extracted using high salt concentrations, extreme pH levels, or chaotropes without disrupting the lipid bilayer (8–11). In contrast, the solubilization of integral proteins requires amphiphilic detergents in order to displace the membrane phospholipids and maintain them as soluble in aqueous solutions (12).Open in a separate windowFig. 1.Bioinformatics and experimental workflow for characterizing peripheral inner membrane proteins. A, schematic representation of the subcellular localization of the E. coli inner membrane peripherome. Protein topology assignment is based on the cellular compartment: A, cytoplasmic; B, integral inner membrane proteins; F1, peripheral inner membrane proteome; r, ribosome. B, schematic diagram for PIM protein annotation. 130 cytoplasmic and PIM E. coli K-12 proteins were downloaded from Uniprot (November 2010) (81) and EchoLOCATION (23). A set of bioinformatics tools was used to predict topologies and features of the unassigned and differently assigned proteins and to further validate existing protein annotations (see supplemental text). For the annotation of additional peripheral membrane proteins, the literature was extensively searched. Additional, other E. coli K-12 databases containing gene ontology annotations (84, 85) and protein homologies through BLAST (44) were employed. Homologues of curated E. coli K-12 proteins were identified in E. coli BL21(DE3) (supplemental Table S1A). C, preparation strategy for detecting the E. coli inner membrane peripherome via nanoLC-MS/MS. Inverted membrane vesicles (IMVs) were isolated and washed extensively with the indicated chemical agents to extract cytoplasmic and PIM proteins (“IMVs washed”), and then their surface was trypsinized (gray arrow). Following digestion, soluble peptides were analyzed via nanoLC-MS/MS. D, protein enrichment at different sample preparation conditions. Top: Relative percentage of proteins detected with the proteolysis approach. Proteins are classified here in three major categories: cytoplasmic (A), ribosomal (r), and peripheral (F1). The bar graphs indicate the percentage of proteins in each category relative to the proteins in other categories at a given sample preparation condition. Bottom: Heat maps showing relative quantities of individual proteins at different sample preparation conditions. Perseus (version 1.2.0.16), a part of the MaxQuant bioinformatics platform, was used for the construction of the heat map (86). A top-three label-free quantitative method was employed (27). Individual protein values across the various treatments are given in supplemental Table S3B.Unlike the cytoplasmic proteome of E. coli, which has been extensively characterized (13), its membrane sub-proteome is still poorly defined. Of 1133 predicted integral inner membrane proteins, only half were experimentally identified through proteomics approaches (14). These figures are constantly being re-evaluated,² but most protein identifications appear robust. In contrast to integral inner membrane proteins, bioinformatics prediction of peripheral inner membrane proteins is currently not possible because they are not known to possess any specific features. Despite the occasional designation of partner proteins identified as peripheral in studies that target inner membrane complexes (15–21), no systematic effort has been undertaken to analyze the peripheral inner membrane proteome.Here we have used a multi-pronged strategy employing bioinformatics, biochemistry, proteomics, and complexomics to systematically determine the peripheral inner membrane proteome of E. coli. We focus exclusively on the peripheral inner membrane proteome that faces the cytoplasm, referred to hereinafter as PIM,¹ and do not analyze peripheral inner membrane proteins residing on the periplasm. Manually curated and re-evaluated topology of the E. coli K-12 proteome was extrapolated to the non-K-12 strain BL21(DE3) (95% proteome homology to K-12) (22). By combining various biochemical treatments, we determined experimentally that several cytoplasmic proteins are also novel PIM proteins, and many of them participate in protein complexes associated with the membrane. Collectively, we demonstrate that a significant, previously unsuspected percentage of the expressed polypeptides constitute the PIM proteome.     

Cytokine effects on cell survival and death of A549 lung carcinoma cells

PurposeIL-13, TNF-α and IL-1β have various effects on lung cancer growth and death, but the signaling pathways mediating these effects have not been extensively analyzed. Therefore, the effects of IL-13, TNF-α and IL-1β alone, and in combination with Fas, on cell viability and death as well as major signaling pathways involved in these effects were investigated in A549 lung carcinoma cells.ResultsUsing MTT and flow cytometry, IL-13, TNF-α and IL-1β pretreatment decreased Fas-induced cell death. These anti-cell death effects were attenuated by pretreatment with inhibitors of Nuclear factor-κB [NF-κB], Phoshatidylinositole-3 kinase [PI3-K], JNK, p38 and ERK1/2 pathways.Using Western blot, IL-13, TNF-α and IL-1β treated cells showed time-dependent expression of p-ERK1/2, p-p38, p-JNK, p-Akt and p-IκBα proteins, decreased IκBα protein expression, no cleavage of Caspase-3 and PARP1 proteins and no notable alterations of Fas protein. IL-13 and TNF-α treated cells showed time-dependent increase of FLIP_L expression.ConclusionIL-13, TNF-α and IL-1β attenuate the pro-cell death effects of Fas on A549 cells, at least partially, by pathways involving the NF-κB, PI3-K and MAP kinases, but not by alterations of Fas protein expression. The IL-13 and TNF-α cell survival effects may also be due to increased expression of FLIP_L protein.     

A versatile strategy for gene trapping and trap conversion in emerging model organisms

Genetic model organisms such as Drosophila, C. elegans and the mouse provide formidable tools for studying mechanisms of development, physiology and behaviour. Established models alone, however, allow us to survey only a tiny fraction of the morphological and functional diversity present in the animal kingdom. Here, we present iTRAC, a versatile gene-trapping approach that combines the implementation of unbiased genetic screens with the generation of sophisticated genetic tools both in established and emerging model organisms. The approach utilises an exon-trapping transposon vector that carries an integrase docking site, allowing the targeted integration of new constructs into trapped loci. We provide proof of principle for iTRAC in the emerging model crustacean Parhyale hawaiensis: we generate traps that allow specific developmental and physiological processes to be visualised in unparalleled detail, we show that trapped genes can be easily cloned from an unsequenced genome, and we demonstrate targeting of new constructs into a trapped locus. Using this approach, gene traps can serve as platforms for generating diverse reporters, drivers for tissue-specific expression, gene knockdown and other genetic tools not yet imagined.     

The Complementary Effects of Atorvastatin and Exercise Treatment on the Composition and Stability of the Atherosclerotic Plaques in ApoE Knockout Mice

Aim

This study aimed to investigate the effects of combined atorvastatin and exercise treatment on the composition and stability of the atherosclerotic plaques in apolipoproteinE (apoE) knockout mice.

Methods

Forty male, apoE^−/− mice were fed a high-fat diet for 16 weeks. Thereafter, while maintained on high-fat diet, they were randomized into four (n = 10) groups for 8 additional weeks: Group CO: Control. Group AT: Atorvastatin treatment (10 mg/Kg/day). Group EX: Exercise-training on treadmill. Group AT+EX: Atorvastatin and simultaneous exercise training. At the study’s end, plasma cholesterol levels, lipids and triglycerides were measured, along with the circulating concentrations of matrix-metalloproteinases (MMP-2,3,8,9) and their inhibitors (TIMP-1,2,3). Plaque area and the relative concentrations of collagen, elastin, macrophages, smooth muscle cells, MMP-2,3,8,9 and TIMP-1,2,3 within plaques were determined. Lastly, MMP activity was assessed in the aortic arch.

Results

All intervention groups showed a lower degree of lumen stenosis, with atheromatous plaques containing more collagen and elastin. AT+EX group had less stenosis and more elastin compared to single intervention groups. MMP-3,-8 -9 and macrophage intra-plaque levels were reduced in all intervention groups. EX group had increased TIMP-1 levels within the lesions, while TIMP-2 was decreased in all intervention groups. The blood levels of the above molecules increased during atherosclerosis development, but they did not change after the therapeutic interventions in accordance to their intra-plaque levels.

Conclusion

The two therapeutic strategies act with synergy regarding the extent of the lesions and lumen stenosis. They stabilize the plaque, increasing its content in elastin and collagen, by influencing the MMP/TIMP equilibrium, which is mainly associated with the macrophage amount. While the increased MMP-2,-3,-8 -9, as well as TIMP-1 and TIMP-2 circulating levels are markers of atherosclerosis, they are not correlated with their corresponding concentrations within the lesions after the therapeutic interventions, and cannot serve as markers for the disease development/amelioration.     

Interplay between oncogene-induced DNA damage response and heterochromatin in senescence and cancer

Two major mechanisms have been causally implicated in the establishment of cellular senescence: the activation of the DNA damage response (DDR) pathway and the formation of senescence-associated heterochromatic foci (SAHF). Here we show that in human fibroblasts resistant to premature p16(INK4a) induction, SAHF are preferentially formed following oncogene activation but are not detected during replicative cellular senescence or on exposure to a variety of senescence-inducing stimuli. Oncogene-induced SAHF formation depends on DNA replication and ATR (ataxia telangiectasia and Rad3-related). Inactivation of ATM (ataxia telangiectasia mutated) or p53 allows the proliferation of oncogene-expressing cells that retain increased heterochromatin induction. In human cancers, levels of heterochromatin markers are higher than in normal tissues, and are independent of the proliferative index or stage of the tumours. Pharmacological and genetic perturbation of heterochromatin in oncogene-expressing cells increase DDR signalling and lead to apoptosis. In vivo, a histone deacetylase inhibitor (HDACi) causes heterochromatin relaxation, increased DDR, apoptosis and tumour regression. These results indicate that heterochromatin induced by oncogenic stress restrains DDR and suggest that the use of chromatin-modifying drugs in cancer therapies may benefit from the study of chromatin and DDR status of tumours.     

The tick salivary protein sialostatin L inhibits the Th9-derived production of the asthma-promoting cytokine IL-9 and is effective in the prevention of experimental asthma

Ticks developed a multitude of different immune evasion strategies to obtain a blood meal. Sialostatin L is an immunosuppressive cysteine protease inhibitor present in the saliva of the hard tick Ixodes scapularis. In this study, we demonstrate that sialostatin L strongly inhibits the production of IL-9 by Th9 cells. Because we could show recently that Th9-derived IL-9 is essentially involved in the induction of asthma symptoms, sialostatin L was used for the treatment of experimental asthma. Application of sialostatin L in a model of experimental asthma almost completely abrogated airway hyperresponsiveness and eosinophilia. Our data suggest that sialostatin L can prevent experimental asthma, most likely by inhibiting the IL-9 production of Th9 cells. Thus, alternative to IL-9 neutralization sialostatin L provides the basis for the development of innovative therapeutic strategies to treat asthma.     

Analysis of the urine proteome via a combination of multi-dimensional approaches

Urine is a biological fluid that is non-invasively and easily harvested, and exhibits high stability from the proteomics point of view. At the downside, the overall low protein content of urine as well as the presence of low- and high-abundance proteins underscores the need for protein enrichment. As a continuation of previous efforts towards the comprehensive characterization of the urine proteome, the current study targeted the mining of urine proteins through the combined application of different protein separation methodologies, specifically, liquid chromatography and preparative electrophoresis along with 1D gel electrophoresis and protein identification by mass spectrometry. In order to enhance comparison and integration of different experimental data sets, the "standard" urine sample developed within the European Kidney and Urine Proteomics (EuroKUP) COST Action, was employed. As a contribution to the existing knowledge, we focused on maintaining and providing information about experimental mass of the identified proteins as well as information pertaining to their relative abundance--as allowed by technical limitations--thus providing an initial view of different isoforms representation and facilitating their future characterization. The difficulties in comparing proteome mining data sets become once more evident, underscoring the need for adopting standardized ways for data reporting as well as for potential new approaches for data analysis involving a thorough investigation of received information at the peptide level.