Perilipin 2 (PLIN2)-Deficiency Does Not Increase Cholesterol-Induced Toxicity in Macrophages

Interventions on macrophages/foam cells to redirect intracellular cholesterol towards efflux pathways could become a very valuable addition to our therapeutic arsenal against atherosclerosis. However, certain manipulations of the cholesteryl ester cycle, such as the inhibition of ACAT1, an ER-resident enzyme that re-esterifies cholesterol, are not well tolerated. Previously we showed that targeting perilipin-2 (PLIN2), a major lipid droplet (LD)-associated protein in macrophages, prevents foam cell formation and protects against atherosclerosis. Here we have assessed the tolerance of PLIN2-deficient bone marrow derived macrophages (BMM) to several lipid loading conditions similar to the found during atherosclerosis development, including exposure to modified low-density lipoprotein (mLDL) and 7-ketocholesterol (7-KC), a free cholesterol (FC) metabolite, in media with or without cholesterol acceptors. BMM isolated from mice that do or do not express PLIN2 were tested for apoptosis (TUNEL and cleaved caspase-3), ER stress (CHOP induction and XBP-1 splicing), and inflammation (TNF-α and IL-6 mRNA levels). Like in other cell types, PLIN2 deficiency impairs LD buildup in BMM. However, while most stress parameters were elevated in macrophages under ACAT inhibition and 7-KC loading, PLIN2 inactivation was well tolerated. The data support the safety of targeting PLIN2 to prevent foam cell formation and atherosclerosis

Personalized Drug Dosage – Closing the Loop

A brief account is given of various approaches to the individualization of drug dosage, including the use of pharmacodynamic markers, therapeutic monitoring of plasma drug concentrations, genotyping, computer-guided dosage using ‘dashboards’, and automatic closed-loop control of pharmacological action. The potential for linking the real patient to his or her ‘virtual twin’ through the application of physiologically-based pharmacokinetic modeling is also discussed

Functional Analysis of Conserved Non-Coding Regions Around the Short Stature hox Gene (shox) in Whole Zebrafish Embryos

Background: Mutations in the SHOX gene are responsible for Leri-Weill Dyschondrosteosis, a disorder characterised by mesomelic limb shortening. Recent investigations into regulatory elements surrounding SHOX have shown that deletions of conserved non-coding elements (CNEs) downstream of the SHOX gene produce a phenotype indistinguishable from Leri-Weill Dyschondrosteosis. As this gene is not found in rodents, we used zebrafish as a model to characterise the expression pattern of the shox gene across the whole embryo and characterise the enhancer domains of different CNEs associated with this gene. Methodology/Principal Findings: Expression of the shox gene in zebrafish was identified using in situ hybridization, with embryos showing expression in the blood, putative heart, hatching gland, brain pharyngeal arch, olfactory epithelium, and fin bud apical ectodermal ridge. By identifying sequences showing 65% identity over at least 40 nucleotides between Fugu, human, dog and opossum we uncovered 35 CNEs around the shox gene. These CNEs were compared with CNEs previously discovered by Sabherwal et al. ,resulting in the identification of smaller more deeply conserved sub-sequence. Sabherwal et al.’s CNEs were assayed for regulatory function in whole zebrafish embryos resulting in the identification of additional tissues under the regulatory control of these CNEs. Conclusion/Significance: Our results using whole zebrafish embryos have provided a more comprehensive picture of the expression pattern of the shox gene, and a better understanding of its regulation via deeply conserved noncoding elements. In particular, we identify additional tissues under the regulatory control of previously identified SHOX CNEs. We also demonstrate the importance of these CNEs in evolution by identifying duplicated shox CNEs and more deeply conserved sub-sequences within already identified CNEs

Computational Models of Classical Conditioning guest editors’ introduction

In the present special issue, the performance of current computational models of classical conditioning was evaluated under three requirements: (1) Models were to be tested against a list of previously agreed-upon phenomena; (2) the parameters were fixed across simulations; and (3) the simulations used to test the models had to be made available. These requirements resulted in three major products: (a) a list of fundamental classical-conditioning results for which there is a consensus about their reliability; (b) the necessary information to evaluate each of the models on the basis of its ordinal successes in accounting for the experimental data; and (c) a repository of computational models ready to generate simulations. We believe that the contents of this issue represent the 2012 state of the art in computational modeling of classical conditioning and provide a way to find promising avenues for future model development

Zoledronic acid renders human M1 and M2 macrophages susceptible to Vδ2(+) γδ T cell cytotoxicity in a perforin-dependent manner.

Vδ2(+) T cells are a subpopulation of γδ T cells in humans that are cytotoxic towards cells which accumulate isopentenyl pyrophosphate. The nitrogen-containing bisphosphonate, zoledronic acid (ZA), can induce tumour cell lines to accumulate isopentenyl pyrophosphate, thus rendering them more susceptible to Vδ2(+) T cell cytotoxicity. However, little is known about whether ZA renders other, non-malignant cell types susceptible. In this study we focussed on macrophages (Mϕs), as these cells have been shown to take up ZA. We differentiated peripheral blood monocytes from healthy donors into Mϕs and then treated them with IFN-γ or IL-4 to generate M1 and M2 Mϕs, respectively. We characterised these Mϕs based on their phenotype and cytokine production and then tested whether ZA rendered them susceptible to Vδ2(+) T cell cytotoxicity. Consistent with the literature, IFN-γ-treated Mϕs expressed higher levels of the M1 markers CD64 and IL-12p70, whereas IL-4-treated Mϕs expressed higher levels of the M2 markers CD206 and chemokine (C-C motif) ligand 18. When treated with ZA, both M1 and M2 Mϕs became susceptible to Vδ2(+) T cell cytotoxicity. Vδ2(+) T cells expressed perforin and degranulated in response to ZA-treated Mϕs as shown by mobilisation of CD107a and CD107b to the cell surface. Furthermore, cytotoxicity towards ZA-treated Mϕs was sensitive-at least in part-to the perforin inhibitor concanamycin A. These findings suggest that ZA can render M1 and M2 Mϕs susceptible to Vδ2(+) T cell cytotoxicity in a perforin-dependent manner, which has important implications regarding the use of ZA in cancer immunotherapy

FSP27 Promotes Lipid Droplet Clustering and Then Fusion to Regulate Triglyceride Accumulation

Fat Specific Protein 27 (FSP27), a lipid droplet (LD) associated protein in adipocytes, regulates triglyceride (TG) storage. In the present study we demonstrate that FSP27 plays a key role in LD morphology to accumulate TGs. We show here that FSP27 promotes clustering of the LDs which is followed by their fusion into fewer and enlarged droplets. To map the domains of FSP27 responsible for these events, we generated GFP-fusion constructs of deletion mutants of FSP27. Microscopic analysis revealed that amino acids 173–220 of FSP27 are necessary and sufficient for both the targeting of FSP27 to LDs and the initial clustering of the droplets. Amino acids 120–140 are essential but not sufficient for LD enlargement, whereas amino acids 120–210 are necessary and sufficient for both clustering and fusion of LDs to form enlarged droplets. In addition, we found that FSP27-mediated enlargement of LDs, but not their clustering, is associated with triglyceride accumulation. These results suggest a model in which FSP27 facilitates LD clustering and then promotes their fusion to form enlarged droplets in two discrete, sequential steps, and a subsequent triglyceride accumulation

18S rRNA is a reliable normalisation gene for real time PCR based on influenza virus infected cells

Background: One requisite of quantitative reverse transcription PCR (qRT-PCR) is to normalise the data with an internal reference gene that is invariant regardless of treatment, such as virus infection. Several studies have found variability in the expression of commonly used housekeeping genes, such as beta-actin (ACTB) and glyceraldehyde-3-phosphate dehydrogenase (GAPDH), under different experimental settings. However, ACTB and GAPDH remain widely used in the studies of host gene response to virus infections, including influenza viruses. To date no detailed study has been described that compares the suitability of commonly used housekeeping genes in influenza virus infections. The present study evaluated several commonly used housekeeping genes [ACTB, GAPDH, 18S ribosomal RNA (18S rRNA), ATP synthase, H+ transporting, mitochondrial F1 complex, beta polypeptide (ATP5B) and ATP synthase, H+ transporting, mitochondrial Fo complex, subunit C1 (subunit 9) (ATP5G1)] to identify the most stably expressed gene in human, pig, chicken and duck cells infected with a range of influenza A virus subtypes. Results: The relative expression stability of commonly used housekeeping genes were determined in primary human bronchial epithelial cells (HBECs), pig tracheal epithelial cells (PTECs), and chicken and duck primary lung-derived cells infected with five influenza A virus subtypes. Analysis of qRT-PCR data from virus and mock infected cells using NormFinder and BestKeeper software programmes found that 18S rRNA was the most stable gene in HBECs, PTECs and avian lung cells. Conclusions: Based on the presented data from cell culture models (HBECs, PTECs, chicken and duck lung cells) infected with a range of influenza viruses, we found that 18S rRNA is the most stable reference gene for normalising qRT-PCR data. Expression levels of the other housekeeping genes evaluated in this study (including ACTB and GPADH) were highly affected by influenza virus infection and hence are not reliable as reference genes for RNA normalisation

A multi-factorial analysis of response to warfarin in a UK prospective cohort

Background Warfarin is the most widely used oral anticoagulant worldwide, but it has a narrow therapeutic index which necessitates constant monitoring of anticoagulation response. Previous genome-wide studies have focused on identifying factors explaining variance in stable dose, but have not explored the initial patient response to warfarin, and a wider range of clinical and biochemical factors affecting both initial and stable dosing with warfarin. Methods A prospective cohort of 711 patients starting warfarin was followed up for 6 months with analyses focusing on both non-genetic and genetic factors. The outcome measures used were mean weekly warfarin dose (MWD), stable mean weekly dose (SMWD) and international normalised ratio (INR) > 4 during the first week. Samples were genotyped on the Illumina Human610-Quad chip. Statistical analyses were performed using Plink and R. Results VKORC1 and CYP2C9 were the major genetic determinants of warfarin MWD and SMWD, with CYP4F2 having a smaller effect. Age, height, weight, cigarette smoking and interacting medications accounted for less than 20 % of the variance. Our multifactorial analysis explained 57.89 % and 56.97 % of the variation for MWD and SMWD, respectively. Genotypes for VKORC1 and CYP2C9*3, age, height and weight, as well as other clinical factors such as alcohol consumption, loading dose and concomitant drugs were important for the initial INR response to warfarin. In a small subset of patients for whom data were available, levels of the coagulation factors VII and IX (highly correlated) also played a role. Conclusion Our multifactorial analysis in a prospectively recruited cohort has shown that multiple factors, genetic and clinical, are important in determining the response to warfarin. VKORC1 and CYP2C9 genetic polymorphisms are the most important determinants of warfarin dosing, and it is highly unlikely that other common variants of clinical importance influencing warfarin dosage will be found. Both VKORC1 and CYP2C9*3 are important determinants of the initial INR response to warfarin. Other novel variants, which did not reach genome-wide significance, were identified for the different outcome measures, but need replication