Significance of the hydrophobic residues 225–230 of apoA-I for the biogenesis of HDL

We studied the significance of four hydrophobic residues within the 225–230 region of apoA-I on its structure and functions and their contribution to the biogenesis of HDL. Adenovirus-mediated gene transfer of an apoA-I[F225A/V227A/F229A/L230A] mutant in apoA-I^−/− mice decreased plasma cholesterol, HDL cholesterol, and apoA-I levels. When expressed in apoA-I^−/− × apoE^−/− mice, approximately 40% of the mutant apoA-I as well as mouse apoA-IV and apoB-48 appeared in the VLDL/IDL/LDL. In both mouse models, the apoA-I mutant generated small spherical particles of pre-β- and α4-HDL mobility. Coexpression of the apoA-I mutant and LCAT increased and shifted the-HDL cholesterol peak toward lower densities, created normal αHDL subpopulations, and generated spherical-HDL particles. Biophysical analyses suggested that the apoA-I[225–230] mutations led to a more compact folding that may limit the conformational flexibility of the protein. The mutations also reduced the ability of apoA-I to promote ABCA1-mediated cholesterol efflux and to activate LCAT to 31% and 66%, respectively, of the WT control. Overall, the apoA-I[225–230] mutations inhibited the biogenesis of-HDL and led to the accumulation of immature pre-β- and α4-HDL particles, a phenotype that could be corrected by administration of LCAT.     

Structure of an atypical periplasmic adaptor from a multidrug efflux pump of the spirochete Borrelia burgdorferi

Periplasmic adaptor proteins are essential components of bacterial tripartite multidrug efflux pumps. Here we report the 2.35 Å resolution crystal structure of the BesA adaptor from the spirochete Borrelia burgdorferi solved using selenomethionine derivatized protein. BesA shows the archetypal linear, flexible, multi-domain architecture evident among proteobacteria and retains the lipoyl, β-barrel and membrane-proximal domains that interact with the periplasmic domains of the inner membrane transporter. However, it lacks the α-hairpin domain shown to establish extensive coiled-coil interactions with the periplasmic entrance helices of the outer membrane-anchored TolC exit duct. This has implications for the modelling of assembled tripartite efflux pumps.     

Prevalence of BRCA1 Mutations in Familial and Sporadic Greek Ovarian Cancer Cases

Germline mutations in the BRCA1 and BRCA2 genes contribute to approximately 18% of hereditary ovarian cancers conferring an estimated lifetime risk from 15% to 50%. A variable incidence of mutations has been reported for these genes in ovarian cancer cases from different populations. In Greece, six mutations in BRCA1 account for 63% of all mutations detected in both BRCA1 and BRCA2 genes. This study aimed to determine the prevalence of BRCA1 mutations in a Greek cohort of 106 familial ovarian cancer patients that had strong family history or metachronous breast cancer and 592 sporadic ovarian cancer cases. All 698 patients were screened for the six recurrent Greek mutations (including founder mutations c.5266dupC, p.G1738R and the three large deletions of exon 20, exons 23–24 and exon 24). In familial cases, the BRCA1 gene was consequently screened for exons 5, 11, 12, 20, 21, 22, 23, 24. A deleterious BRCA1 mutation was found in 43/106 (40.6%) of familial cancer cases and in 27/592 (4.6%) of sporadic cases. The variant of unknown clinical significance p.V1833M was identified in 9/698 patients (1.3%). The majority of BRCA1 carriers (71.2%) presented a high-grade serous phenotype. Identifying a mutation in the BRCA1 gene among breast and/or ovarian cancer families is important, as it enables carriers to take preventive measures. All ovarian cancer patients with a serous phenotype should be considered for genetic testing. Further studies are warranted to determine the prevalence of mutations in the rest of the BRCA1 gene, in the BRCA2 gene, and other novel predisposing genes for breast and ovarian cancer.     

Lysoglycerophospholipids in chronic inflammatory disorders: The PLA2/LPC and ATX/LPA axes

Lysophosphatidylcholine (LPC) and lysophosphatidic acid (LPA), the most prominent lysoglycerophospholipids, are emerging as a novel class of inflammatory lipids, joining thromboxanes, leukotrienes and prostaglandins with which they share metabolic pathways and regulatory mechanisms. Enzymes that participate in LPC and LPA metabolism, such as the phospholipase A₂ superfamily (PLA₂) and autotaxin (ATX, ENPP2), play central roles in regulating LPC and LPA levels and consequently their actions. LPC/LPA biosynthetic pathways will be briefly presented and LPC/LPA signaling properties and their possible functions in the regulation of the immune system and chronic inflammation will be reviewed. Furthermore, implications of exacerbated LPC and/or LPA signaling in the context of chronic inflammatory diseases, namely rheumatoid arthritis, multiple sclerosis, pulmonary fibrosis and hepatitis, will be discussed. This article is part of a Special Issue entitled Advances in Lysophospholipid Research.     

Proteasome dysfunction in Drosophila signals to an Nrf2‐dependent regulatory circuit aiming to restore proteostasis and prevent premature aging

The ubiquitin–proteasome system is central to the regulation of cellular proteostasis. Nevertheless, the impact of in vivo proteasome dysfunction on the proteostasis networks and the aging processes remains poorly understood. We found that RNAi‐mediated knockdown of 20S proteasome subunits in Drosophila melanogaster resulted in larval lethality. We therefore studied the molecular effects of proteasome dysfunction in adult flies by developing a model of dose‐dependent pharmacological proteasome inhibition. Impaired proteasome function promoted several ‘old‐age’ phenotypes and markedly reduced flies' lifespan. In young somatic tissues and in gonads of all ages, loss of proteasome activity induced higher expression levels and assembly rates of proteasome subunits. Proteasome dysfunction was signaled to the proteostasis network by reactive oxygen species that originated from malfunctioning mitochondria and triggered an Nrf2‐dependent upregulation of the proteasome subunits. RNAi‐mediated Nrf2 knockdown reduced proteasome activities, flies' resistance to stress, as well as longevity. Conversely, inducible activation of Nrf2 in transgenic flies upregulated basal proteasome expression and activity independently of age and conferred resistance to proteotoxic stress. Interestingly, prolonged Nrf2 overexpression reduced longevity, indicating that excessive activation of the proteostasis pathways can be detrimental. Our in vivo studies add new knowledge on the proteotoxic stress‐related regulation of the proteostasis networks in higher metazoans. Proteasome dysfunction triggers the activation of an Nrf2‐dependent tissue‐ and age‐specific regulatory circuit aiming to adjust the cellular proteasome activity according to temporal and/or spatial proteolytic demands. Prolonged deregulation of this proteostasis circuit accelerates aging.     

Using dynamic relative climate impact curves to quantify the climate impact of bioenergy production systems over time

The climate impact of bioenergy is commonly quantified in terms of CO₂ equivalents, using a fixed 100‐year global warming potential as an equivalency metric. This method has been criticized for the inability to appropriately address emissions timing and the focus on a single impact metric, which may lead to inaccurate or incomplete quantification of the climate impact of bioenergy production. In this study, we introduce Dynamic Relative Climate Impact (DRCI) curves, a novel approach to visualize and quantify the climate impact of bioenergy systems over time. The DRCI approach offers the flexibility to analyze system performance for different value judgments regarding the impact category (e.g., emissions, radiative forcing, and temperature change), equivalency metric, and analytical time horizon. The DRCI curves constructed for fourteen bioenergy systems illustrate how value judgments affect the merit order of bioenergy systems, because they alter the importance of one‐time (associated with land use change emissions) versus sustained (associated with carbon debt or foregone sequestration) emission fluxes and short‐ versus long‐lived climate forcers. Best practices for bioenergy production (irrespective of value judgments) include high feedstock yields, high conversion efficiencies, and the application of carbon capture and storage. Furthermore, this study provides examples of production contexts in which the risk of land use change emissions, carbon debt, or foregone sequestration can be mitigated. For example, the risk of indirect land use change emissions can be mitigated by accompanying bioenergy production with increasing agricultural yields. Moreover, production contexts in which the counterfactual scenario yields immediate or additional climate impacts can provide significant climate benefits. This paper is accompanied by an Excel‐based calculation tool to reproduce the calculation steps outlined in this paper and construct DRCI curves for bioenergy systems of choice.     

Network Reconstruction Based on Proteomic Data and Prior Knowledge of Protein Connectivity Using Graph Theory

Modeling of signal transduction pathways is instrumental for understanding cells’ function. People have been tackling modeling of signaling pathways in order to accurately represent the signaling events inside cells’ biochemical microenvironment in a way meaningful for scientists in a biological field. In this article, we propose a method to interrogate such pathways in order to produce cell-specific signaling models. We integrate available prior knowledge of protein connectivity, in a form of a Prior Knowledge Network (PKN) with phosphoproteomic data to construct predictive models of the protein connectivity of the interrogated cell type. Several computational methodologies focusing on pathways’ logic modeling using optimization formulations or machine learning algorithms have been published on this front over the past few years. Here, we introduce a light and fast approach that uses a breadth-first traversal of the graph to identify the shortest pathways and score proteins in the PKN, fitting the dependencies extracted from the experimental design. The pathways are then combined through a heuristic formulation to produce a final topology handling inconsistencies between the PKN and the experimental scenarios. Our results show that the algorithm we developed is efficient and accurate for the construction of medium and large scale signaling networks. We demonstrate the applicability of the proposed approach by interrogating a manually curated interaction graph model of EGF/TNFA stimulation against made up experimental data. To avoid the possibility of erroneous predictions, we performed a cross-validation analysis. Finally, we validate that the introduced approach generates predictive topologies, comparable to the ILP formulation. Overall, an efficient approach based on graph theory is presented herein to interrogate protein–protein interaction networks and to provide meaningful biological insights.     

Efficacy of Lapatinib in Therapy-Resistant HER2-Positive Circulating Tumor Cells in Metastatic Breast Cancer

Background

To evaluate the efficacy of lapatinib, a dual EGFR and HER2 tyrosine kinase inhibitor, in therapy-resistant HER2-positive CTCs in metastatic breast cancer (MBC).

Patients and Methods

Patients with MBC and HER2-positive CTCs despite disease stabilization or response to prior therapy, received lapatinib 1500 mg daily in monthly cycles, till disease progression or CTC increase. CTC monitoring was performed by immunofluorescent microscopy using cytospins of peripheral blood mononuclear cells (PBMCs) double stained for HER2 or EGFR and cytokeratin.

Results

A total of 120 cycles were administered in 22 patients; median age was 62.5 years, 15 (68.2%) patients were post-menopausal and 20 (90.1%) had HER2-negative primary tumors. At the end of the second course, HER2-positive CTC counts decreased in 76.2% of patients; the median number of HER2-positive CTCs/patient also declined significantly (p = 0.013), however the decrease was significant only among patients presenting disease stabilization (p = 0.018) but not among those with disease progression during lapatinib treatment. No objective responses were observed. All CTC-positive patients harbored EGFR-positive CTCs on progression compared to 62.5% at baseline (p = 0.054). The ratio of EGFR-positive CTCs/total CTCs detected in all patients increased from 17.1% at baseline to 37.6% on progression, whereas the mean percentage of HER2-negative CTCs/patient increased from 2.4% to 30.6% (p = 0.03).

Conclusions

The above results indicate that lapatinib is effective in decreasing HER2-positive CTCs in patients with MBC irrespectively of the HER2 status of the primary tumor and imply the feasibility of monitoring the molecular changes on CTCs during treatment with targeted agents.

Trial Registration

Clinical trial.gov NCT00694252