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Ni-rich Li(Ni x Co y Mn z )O 2 (x ≥ 0.8)-layered oxide materials are highly promising as cathode materials for high-energy-density lithium-ion batteries in electric and hybrid vehicles. However, their tendency to undergo side reactions with electrolytes and their structural instability during cyclic lithiation/delithiation impairs their electrochemical cycling performance, posing challenges for large-scale applications. This paper explores the application of an Al 2 O 3 coating using an atomic layer deposition (ALD) system on Ni-enriched Li(Ni 0.8 Co 0.1 Mn 0.1 )O 2 (NCM811) cathode material. Characterization techniques, including X-ray diffraction, scanning electron microscopy, and transmission electron microscopy, were used to assess the impact of alumina coating on the morphology and crystal structure of NCM811. The results confirmed that an ultrathin Al 2 O 3 coating was achieved without altering the microstructure and lattice structure of NCM811. The alumina-coated NCM811 exhibited improved cycling stability and capacity retention in the voltage range of 2.8-4.5 V at a 1 C rate. Specifically, the capacity retention of the modified NCM811 was 5%, 9.11%, and 11.28% higher than the pristine material at operating voltages of 4.3, 4.4, and 4.5 V, respectively. This enhanced performance is attributed to reduced electrode-electrolyte interaction, leading to fewer side reactions and improved structural stability. Thus, NCM811@Al 2 O 3 with this coating process emerges as a highly attractive candidate for high-capacity lithium-ion battery cathode materials.

The stabilization of different active conformations of G protein-coupled receptors is thought to underlie the varying efficacies of biased and balanced agonists. Here, profiling the activation of signal transducers by angiotensin II type 1 receptor (AT 1 R) agonists revealed that the extent and kinetics of β-arrestin binding exhibited substantial ligand-dependent differences, which were lost when receptor internalization was inhibited. When AT 1 R endocytosis was prevented, even weak partial agonists of the β-arrestin pathway acted as full or near-full agonists, suggesting that receptor conformation did not exclusively determine β-arrestin recruitment. The ligand-dependent variance in β-arrestin translocation was much larger at endosomes than at the plasma membrane, showing that ligand efficacy in the β-arrestin pathway was spatiotemporally determined. Experimental investigations and mathematical modeling demonstrated how multiple factors concurrently shaped the effects of agonists on endosomal receptor-β-arrestin binding and thus determined the extent of functional selectivity. Ligand dissociation rate and G protein activity had particularly strong, internalization-dependent effects on the receptor-β-arrestin interaction. We also showed that endocytosis regulated the agonist efficacies of two other receptors with sustained β-arrestin binding: the V 2 vasopressin receptor and a mutant β 2 -adrenergic receptor. In the absence of endocytosis, the agonist-dependent variance in β-arrestin2 binding was markedly diminished. Our results suggest that endocytosis determines the spatiotemporal bias in GPCR signaling and can aid in the development of more efficacious, functionally selective compounds.

Nowadays, lithium-ion batteries are undoubtedly known as the most promising rechargeable batteries. However, these batteries face some big challenges, like not having enough energy and not lasting long enough, that should be addressed. Ternary Ni-rich Li[Ni x Co y Mn z ]O 2 and Li[Ni x Co y Al z ]O 2 cathode materials stand as the ideal candidate for a cathode active material to achieve high capacity and energy density, low manufacturing cost, and high operating voltage. However, capacity gain from Ni enrichment is nullified by the concurrent fast capacity fading because of issues such as gas evolution, microcracks propagation and pulverization, phase transition, electrolyte decomposition, cation mixing, and dissolution of transition metals at high operating voltage, which hinders their commercialization. In order to tackle these problems, researchers conducted many strategies, including elemental doping, surface coating, and particle engineering. This review paper mainly talks about origins of problems and their mechanisms leading to electrochemical performance deterioration for Ni-rich cathode materials and modification approaches to address the problems.

Molecular interactions between anorexigenic leptin and orexigenic endocannabinoids, although of great metabolic significance, are not well understood. We report here that hypothalamic STAT3 signaling in mice, initiated by physiological elevations of leptin, is diminished by agonists of the cannabinoid receptor 1 (CB 1 R). Measurement of STAT3 activation by semi-automated confocal microscopy in cultured neurons revealed that this CB 1 R-mediated inhibition requires both T cell protein tyrosine phosphatase (TC-PTP) and β-arrestin1 but is independent of changes in cAMP. Moreover, β-arrestin1 translocates to the nucleus upon CB 1 R activation and binds both STAT3 and TC-PTP. Consistently, CB 1 R activation failed to suppress leptin signaling in β-arrestin1 knockout mice in vivo, and in neural cells deficient in CB 1 R, β-arrestin1 or TC-PTP. Altogether, CB 1 R activation engages β-arrestin1 to coordinate the TC-PTP-mediated inhibition of the leptin-evoked neuronal STAT3 response. This mechanism may restrict the anorexigenic effects of leptin when hypothalamic endocannabinoid levels rise, as during fasting or in diet-induced obesity., Competing Interests: The authors declare no competing interest., (© 2023 The Author(s).)

Angiotensin II (AngII) is a vasoactive peptide hormone, which, under pathological conditions, contributes to the development of cardiovascular diseases. Oxysterols, including 25-hydroxycholesterol (25-HC), the product of cholesterol-25-hydroxylase (CH25H), also have detrimental effects on vascular health by affecting vascular smooth muscle cells (VSMCs). We investigated AngII-induced gene expression changes in VSMCs to explore whether AngII stimulus and 25-HC production have a connection in the vasculature. RNA-sequencing revealed that Ch25h is significantly upregulated in response to AngII stimulus. The Ch25h mRNA levels were elevated robustly (~50-fold) 1 h after AngII (100 nM) stimulation compared to baseline levels. Using inhibitors, we specified that the AngII-induced Ch25h upregulation is type 1 angiotensin II receptor- and G q/11 activity-dependent. Furthermore, p38 MAPK has a crucial role in the upregulation of Ch25h . We performed LC-MS/MS to identify 25-HC in the supernatant of AngII-stimulated VSMCs. In the supernatants, 25-HC concentration peaked 4 h after AngII stimulation. Our findings provide insight into the pathways mediating AngII-induced Ch25h upregulation. Our study elucidates a connection between AngII stimulus and 25-HC production in primary rat VSMCs. These results potentially lead to the identification and understanding of new mechanisms in the pathogenesis of vascular impairments.

Poor bioavailability of eye drops is a well-known issue, which can be improved by increasing the residence time on the eye surface and the penetration of the active pharmaceutical ingredient (API). This study aims to formulate in situ gelling mucoadhesive ophthalmic preparations. To increase the residence time, the formulations were based on a thermosensitive polymer (Poloxamer 407 (P407)) and were combined with two types of mucoadhesive polymers. Dexamethasone (DXM) was solubilized by complexation with cyclodextrins (CD). The effect of the composition on the gel structure, mucoadhesion, dissolution, and permeability was investigated with 3 3 full factorial design. These parameters of the gels were measured by rheological studies, tensile test, dialysis membrane diffusion, and in vitro permeability assay. The dissolution and permeability of the gels were also compared with DXM suspension and CD-DXM solution. The gelation is strongly determined by P407; however, the mucoadhesive polymers also influenced it. Mucoadhesion increased with the polymer concentration. The first phase of drug release was similar to that of the CD-DXM solution, then it became prolonged. The permeability of DXM was significantly improved. The factorial design helped to identify the most important factors, thereby facilitating the formulation of a suitable carrier for the CD-DXM complex., Competing Interests: The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

The growing availability of single-cell data, especially transcriptomics, has sparked an increased interest in the inference of cell-cell communication. Many computational tools were developed for this purpose. Each of them consists of a resource of intercellular interactions prior knowledge and a method to predict potential cell-cell communication events. Yet the impact of the choice of resource and method on the resulting predictions is largely unknown. To shed light on this, we systematically compare 16 cell-cell communication inference resources and 7 methods, plus the consensus between the methods' predictions. Among the resources, we find few unique interactions, a varying degree of overlap, and an uneven coverage of specific pathways and tissue-enriched proteins. We then examine all possible combinations of methods and resources and show that both strongly influence the predicted intercellular interactions. Finally, we assess the agreement of cell-cell communication methods with spatial colocalisation, cytokine activities, and receptor protein abundance and find that predictions are generally coherent with those data modalities. To facilitate the use of the methods and resources described in this work, we provide LIANA, a LIgand-receptor ANalysis frAmework as an open-source interface to all the resources and methods., (© 2022. The Author(s).)

Comparing SARS-CoV-2 infection-induced gene expression signatures to drug treatment-induced gene expression signatures is a promising bioinformatic tool to repurpose existing drugs against SARS-CoV-2. The general hypothesis of signature-based drug repurposing is that drugs with inverse similarity to a disease signature can reverse disease phenotype and thus be effective against it. However, in the case of viral infection diseases, like SARS-CoV-2, infected cells also activate adaptive, antiviral pathways, so that the relationship between effective drug and disease signature can be more ambiguous. To address this question, we analysed gene expression data from in vitro SARS-CoV-2 infected cell lines, and gene expression signatures of drugs showing anti-SARS-CoV-2 activity. Our extensive functional genomic analysis showed that both infection and treatment with in vitro effective drugs leads to activation of antiviral pathways like NFkB and JAK-STAT. Based on the similarity-and not inverse similarity-between drug and infection-induced gene expression signatures, we were able to predict the in vitro antiviral activity of drugs. We also identified SREBF1/2, key regulators of lipid metabolising enzymes, as the most activated transcription factors by several in vitro effective antiviral drugs. Using a fluorescently labeled cholesterol sensor, we showed that these drugs decrease the cholesterol levels of plasma-membrane. Supplementing drug-treated cells with cholesterol reversed the in vitro antiviral effect, suggesting the depleting plasma-membrane cholesterol plays a key role in virus inhibitory mechanism. Our results can help to more effectively repurpose approved drugs against SARS-CoV-2, and also highlights key mechanisms behind their antiviral effect., Competing Interests: I have read the journal’s policy and the authors of this manuscript have the following competing interests: JSR reports funding from GSK and Sanofi and fees from Travere Therapeutics and Astex. BS is a full time employee of Turbine Ltd., Budapest, Hungary.

Prostate cancer is the second most occurring cancer in men worldwide. To better understand the mechanisms of tumorigenesis and possible treatment responses, we developed a mathematical model of prostate cancer which considers the major signalling pathways known to be deregulated. We personalised this Boolean model to molecular data to reflect the heterogeneity and specific response to perturbations of cancer patients. A total of 488 prostate samples were used to build patient-specific models and compared to available clinical data. Additionally, eight prostate cell line-specific models were built to validate our approach with dose-response data of several drugs. The effects of single and combined drugs were tested in these models under different growth conditions. We identified 15 actionable points of interventions in one cell line-specific model whose inactivation hinders tumorigenesis. To validate these results, we tested nine small molecule inhibitors of five of those putative targets and found a dose-dependent effect on four of them, notably those targeting HSP90 and PI3K. These results highlight the predictive power of our personalised Boolean models and illustrate how they can be used for precision oncology., Competing Interests: AM, JB, PT, BS, EB, LC No competing interests declared, LT is a full-time employee and shareholder of AstraZeneca, VS is a full-time employee of AstraZeneca, RA is CEO of Astridbio Technologies Ltd, LP is a scientific advisor of Astridbio Technologies Ltd, AV Reviewing editor, eLife, JS reports funding from GSK and Sanofi and fees from Travere Therapeutics and Astex, (© 2022, Montagud et al.)

The Columbia Cancer Target Discovery and Development (CTD2) Center is developing PANACEA, a resource comprising dose-responses and RNA sequencing (RNA-seq) profiles of 25 cell lines perturbed with ∼400 clinical oncology drugs, to study a tumor-specific drug mechanism of action. Here, this resource serves as the basis for a DREAM Challenge assessing the accuracy and sensitivity of computational algorithms for de novo drug polypharmacology predictions. Dose-response and perturbational profiles for 32 kinase inhibitors are provided to 21 teams who are blind to the identity of the compounds. The teams are asked to predict high-affinity binding targets of each compound among ∼1,300 targets cataloged in DrugBank. The best performing methods leverage gene expression profile similarity analysis as well as deep-learning methodologies trained on individual datasets. This study lays the foundation for future integrative analyses of pharmacogenomic data, reconciliation of polypharmacology effects in different tumor contexts, and insights into network-based assessments of drug mechanisms of action., Competing Interests: A.C. is founder, equity holder, and consultant of DarwinHealth, Inc., a company that has licensed the PANACEA database used in this manuscript from Columbia University. Columbia University is also an equity holder in DarwinHealth, Inc. J.S.-R. has received funding from GSK and Sanofi and personal fees from Travere Therapeutics. B.S. received consultation fees from Turbine, Ltd. All other authors declare no competing interests., (© 2021.)

Activation of the type I angiotensin receptor (AT1-R) in vascular smooth muscle cells (VSMCs) plays a crucial role in the regulation of blood pressure; however, it is also responsible for the development of pathological conditions such as vascular remodeling, hypertension and atherosclerosis. Stimulation of the VSMC by angiotensin II (AngII) promotes a broad variety of biological effects, including gene expression changes. In this paper, we have taken an integrated approach in which an analysis of AngII-induced gene expression changes has been combined with the use of small-molecule inhibitors and lentiviral-based gene silencing, to characterize the mechanism of signal transduction in response to AngII stimulation in primary rat VSMCs. We carried out Affymetrix GeneChip experiments to analyze the effects of AngII stimulation on gene expression; several genes, including DUSP5 , DUSP6 , and DUSP10 , were identified as upregulated genes in response to stimulation. Since various dual-specificity MAPK phosphatase (DUSP) enzymes are important in the regulation of mitogen-activated protein kinase (MAPK) signaling pathways, these genes have been selected for further analysis. We investigated the kinetics of gene-expression changes and the possible signal transduction processes that lead to altered expression changes after AngII stimulation. Our data shows that the upregulated genes can be stimulated through multiple and synergistic signal transduction pathways. We have also found in our gene-silencing experiments that epidermal growth factor receptor (EGFR) transactivation is not critical in the AngII-induced expression changes of the investigated genes. Our data can help us understand the details of AngII-induced long-term effects and the pathophysiology of AT1-R. Moreover, it can help to develop potential interventions for those symptoms that are induced by the over-functioning of this receptor, such as vascular remodeling, cardiac hypertrophy or atherosclerosis.

Pathway analysis methods are frequently applied to cancer gene expression data to identify dysregulated pathways. These methods often infer pathway activity based on the expression of genes belonging to a given pathway, even though the proteins ultimately determine the activity of a given pathway. Furthermore, the association between gene expression levels and protein activities is not well-characterized. Here, we posit that pathway-based methods are effective not because of the correlation between expression and activity of members of a given pathway, but because pathway gene sets overlap with the genes regulated by transcription factors (TFs). Thus, pathway-based methods do not inform about the activity of the pathway of interest but rather reflect changes in TF activities., (© 2020 The Authors. FEBS Letters published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

Introduction: In Hungary, SARS-CoV-2 was first detected in the swab samples of two Iranian patients on March 4, 2020. After finding the first positive cases, the question arose whether the virus had entered Hungary and caused infections before this date. Before March 4, 2020, except for the two above-mentioned samples, none of the 224 swab samples received specifically for SARS-CoV-2 tested positive., Aim: The National Reference Laboratory for Respiratory Viruses of the National Public Health Center aimed to carry out a retrospective study of the swab and other samples taken for testing respiratory virus infections between January 1, and April 19, 2020 sent by sentinel physicians within the influenza surveillance for diagnostic purposes., Method: For the study, we used swab samples taken weekly by sentinel physicians of the influenza surveillance service, and other samples received for diagnostic purposes. Tests were performed using real-time PCR., Results: All the 465 swab samples sent by sentinel physicians were found to be SARS-CoV-2 negative. Also, of the 551 samples collected for diagnostic reasons of other respiratory viruses, no SARS-CoV-2 positive was found among those taken before March 4., Conclusion: Based on our data, it is very likely that prior to the first cases diagnosed on March 4, 2020, SARS-CoV-2 did not cause clinically symptomatic infections in Hungary. Orv Hetil. 2020; 161(38): 1619-1622.

Knowledge about the clonal evolution of a tumor can help to interpret the function of its genetic alterations by identifying initiating events and events that contribute to the selective advantage of proliferative, metastatic, and drug-resistant subclones. Clonal evolution can be reconstructed from estimates of the relative abundance (frequency) of subclone-specific alterations in tumor biopsies, which, in turn, inform on its composition. However, estimating these frequencies is complicated by the high genetic instability that characterizes many cancers. Models for genetic instability suggest that copy number alterations (CNAs) can influence mutation-frequency estimates and thus impede efforts to reconstruct tumor phylogenies. Our analysis suggested that accurate mutation frequency estimates require accounting for CNAs-a challenging endeavour using the genetic profile of a single tumor biopsy. Instead, we propose an optimization algorithm, Chimæra, to account for the effects of CNAs using profiles of multiple biopsies per tumor. Analyses of simulated data and tumor profiles suggested that Chimæra estimates are consistently more accurate than those of previously proposed methods and resulted in improved phylogeny reconstructions and subclone characterizations. Our analyses inferred recurrent initiating mutations in hepatocellular carcinomas, resolved the clonal composition of Wilms' tumors, and characterized the acquisition of mutations in drug-resistant prostate cancers.

Transcriptome profiling followed by differential gene expression analysis often leads to lists of genes that are hard to analyze and interpret. Functional genomics tools are powerful approaches for downstream analysis, as they summarize the large and noisy gene expression space into a smaller number of biological meaningful features. In particular, methods that estimate the activity of processes by mapping transcripts level to process members are popular. However, footprints of either a pathway or transcription factor (TF) on gene expression show superior performance over mapping-based gene sets. These footprints are largely developed for humans and their usability in the broadly-used model organism Mus musculus is uncertain. Evolutionary conservation of the gene regulatory system suggests that footprints of human pathways and TFs can functionally characterize mice data. In this paper we analyze this hypothesis. We perform a comprehensive benchmark study exploiting two state-of-the-art footprint methods, DoRothEA and an extended version of PROGENy. These methods infer TF and pathway activity, respectively. Our results show that both can recover mouse perturbations, confirming our hypothesis that footprints are conserved between mice and humans. Subsequently, we illustrate the usability of PROGENy and DoRothEA by recovering pathway/TF-disease associations from newly generated disease sets. Additionally, we provide pathway and TF activity scores for a large collection of human and mouse perturbation and disease experiments (2374). We believe that this resource, available for interactive exploration and download (https://saezlab.shinyapps.io/footprint_scores/), can have broad applications including the study of diseases and therapeutics., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Background: Many functional analysis tools have been developed to extract functional and mechanistic insight from bulk transcriptome data. With the advent of single-cell RNA sequencing (scRNA-seq), it is in principle possible to do such an analysis for single cells. However, scRNA-seq data has characteristics such as drop-out events and low library sizes. It is thus not clear if functional TF and pathway analysis tools established for bulk sequencing can be applied to scRNA-seq in a meaningful way., Results: To address this question, we perform benchmark studies on simulated and real scRNA-seq data. We include the bulk-RNA tools PROGENy, GO enrichment, and DoRothEA that estimate pathway and transcription factor (TF) activities, respectively, and compare them against the tools SCENIC/AUCell and metaVIPER, designed for scRNA-seq. For the in silico study, we simulate single cells from TF/pathway perturbation bulk RNA-seq experiments. We complement the simulated data with real scRNA-seq data upon CRISPR-mediated knock-out. Our benchmarks on simulated and real data reveal comparable performance to the original bulk data. Additionally, we show that the TF and pathway activities preserve cell type-specific variability by analyzing a mixture sample sequenced with 13 scRNA-seq protocols. We also provide the benchmark data for further use by the community., Conclusions: Our analyses suggest that bulk-based functional analysis tools that use manually curated footprint gene sets can be applied to scRNA-seq data, partially outperforming dedicated single-cell tools. Furthermore, we find that the performance of functional analysis tools is more sensitive to the gene sets than to the statistic used.

Transcriptional perturbation signatures are valuable data sources for functional genomics. Linking perturbation signatures to screenings opens the possibility to model cellular phenotypes from expression data and to identify efficacious drugs. We linked perturbation transcriptomics data from the LINCS-L1000 project with cell viability information upon genetic (Achilles project) and chemical (CTRP screen) perturbations yielding more than 90 000 signature-viability pairs. An integrated analysis showed that the cell viability signature is a major factor underlying perturbation signatures. The signature is linked to transcription factors regulating cell death, proliferation and division time. We used the cell viability-signature relationship to predict viability from transcriptomics signatures, and identified and validated compounds that induce cell death in tumor cell lines. We showed that cellular toxicity can lead to unexpected similarity of signatures, confounding mechanism of action discovery. Consensus compound signatures predicted cell-specific drug sensitivity, even if the signature is not measured in the same cell line, and outperformed conventional drug-specific features. Our results can help in understanding mechanisms behind cell death and removing confounding factors of transcriptomic perturbation screens. To interactively browse our results and predict cell viability in new gene expression samples, we developed CEVIChE (CEll VIability Calculator from gene Expression; https://saezlab.shinyapps.io/ceviche/)., (© The Author(s) 2019. Published by Oxford University Press on behalf of Nucleic Acids Research.)

In 2013-2016, West Africa experienced the largest and longest Ebola virus disease outbreak ever documented. The wide geographic spread and magnitude of the outbreak often limited the timely and rapid testing of diagnostic samples from patients with suspected Ebola virus disease, raising questions regarding the optimal storage and shipping conditions of clinically relevant specimens, including EDTA-whole blood, plasma, capillary blood, urine and seminal fluid (associated with sexual transmission of the Ebola virus after recovery from the disease). Therefore, the aim of our study was to identify the extent to which storage temperature and clinical specimen type influence Ebola virus viability. Virus infectivity was determined using a fluorescent focus-forming assay. In our study, we show that Ebola virus was the most stable in EDTA-whole blood and plasma samples, whereas rapid decay of infectivity was observed in simulated capillary blood, urine and semen samples, especially when these samples were stored at higher temperatures. The analysis of variance results demonstrated that both temperature and clinical specimen type have significant effects on virus viability, whereas donor differences were not observed. Repeated freeze and thaw cycles of the samples also had a notable impact on virus viability in EDTA-whole blood and urine. Due to the rapid temperature- and specimen-dependent degradation of the virus observed here, our study highlights the importance of proper clinical sample storage at low temperatures during transportation and laboratory analysis.

It is still not possible to predict whether a given molecule will have a perceived odor or what olfactory percept it will produce. We therefore organized the crowd-sourced DREAM Olfaction Prediction Challenge. Using a large olfactory psychophysical data set, teams developed machine-learning algorithms to predict sensory attributes of molecules based on their chemoinformatic features. The resulting models accurately predicted odor intensity and pleasantness and also successfully predicted 8 among 19 rated semantic descriptors ("garlic," "fish," "sweet," "fruit," "burnt," "spices," "flower," and "sour"). Regularized linear models performed nearly as well as random forest-based ones, with a predictive accuracy that closely approaches a key theoretical limit. These models help to predict the perceptual qualities of virtually any molecule with high accuracy and also reverse-engineer the smell of a molecule., (Copyright © 2017, American Association for the Advancement of Science.)

Heterodimerization between angiotensin type 1A receptor (AT 1 R) and β 2 -adrenergic receptor (β 2 AR) has been shown to modulate G protein-mediated effects of these receptors. Activation of G protein-coupled receptors (GPCRs) leads to β-arrestin binding, desensitization, internalization and G protein-independent signaling of GPCRs. Our aim was to study the effect of heterodimerization on β-arrestin coupling. We found that β-arrestin binding of β 2 AR is affected by activation of AT 1 Rs. Costimulation with angiotensin II and isoproterenol markedly enhanced the interaction between β 2 AR and β-arrestins, by prolonging the lifespan of β 2 AR-induced β-arrestin2 clusters at the plasma membrane. While candesartan, a conventional AT 1 R antagonist, had no effect on the β-arrestin2 binding to β 2 AR, TRV120023, a β-arrestin biased agonist, enhanced the interaction. These findings reveal a new crosstalk mechanism between AT 1 R and β 2 AR, and suggest that enhanced β-arrestin2 binding to β 2 AR can contribute to the pharmacological effects of biased AT 1 R agonists., (Copyright © 2016. Published by Elsevier B.V.)

G Protein Coupled Receptors (GPCR) can form dimers or higher ordered oligomers, the process of which can remarkably influence the physiological and pharmacological function of these receptors. Quantitative Bioluminescence Resonance Energy Transfer (qBRET) measurements are the gold standards to prove the direct physical interaction between the protomers of presumed GPCR dimers. For the correct interpretation of these experiments, the expression of the energy donor Renilla luciferase labeled receptor has to be maintained constant, which is hard to achieve in expression systems. To analyze the effects of non-constant donor expression on qBRET curves, we performed Monte Carlo simulations. Our results show that the decrease of donor expression can lead to saturation qBRET curves even if the interaction between donor and acceptor labeled receptors is non-specific leading to false interpretation of the dimerization state. We suggest here a new approach to the analysis of qBRET data, when the BRET ratio is plotted as a function of the acceptor labeled receptor expression at various donor receptor expression levels. With this method, we were able to distinguish between dimerization and non-specific interaction when the results of classical qBRET experiments were ambiguous. The simulation results were confirmed experimentally using rapamycin inducible heterodimerization system. We used this new method to investigate the dimerization of various GPCRs, and our data have confirmed the homodimerization of V2 vasopressin and CaSR calcium sensing receptors, whereas our data argue against the heterodimerization of these receptors with other studied GPCRs, including type I and II angiotensin, β2 adrenergic and CB1 cannabinoid receptors.

In 2010, two novel porcine H1N1 influenza viruses were isolated from pigs with influenza-like illness in Hungarian swine herds. Sequence and phylogenetic analysis of these strains revealed that they shared molecular features with the pandemic H1N1 influenza virus strains, which emerged globally during 2009. The PB2, HA and NA genes contained unique amino acid changes compared to the available new H1N1 influenza virus sequences of pig origin. Furthermore, the investigated strains could be separated with respect to parallel amino acid substitutions affecting the polymerase genes (PB2, PB1 and PA) and the nucleoprotein (NP) gene, supporting the proposed complementarities between these proteins, all required for the viral fitness. Molecular characterisation of two Hungarian human pandemic H1N1 isolates was also performed, so that we could compare contemporaneous strains of different host species origins. Shared molecular motifs in various genes of animal and human influenza strains suggested that the Hungarian porcine strains could have originated from humans through direct interspecies transmission. This study is among the few that support the natural human-to-pig transmission of the pandemic H1N1 influenza virus.

G protein coupled receptor (GPCR) dimerization has a remarkable impact on the diversity of receptor signaling. Allosteric communication between the protomers of the dimer can alter ligand binding, receptor conformation and interactions with different effector proteins. In this study we investigated the allosteric interactions between wild type and mutant protomers of type 1 angiotensin receptor (AT₁R) dimers transiently expressed in CHO cells. In our experimental setup, one protomer of the dimer was selectively stimulated and the β-arrestin2 binding and conformation alteration of the other protomer was followed. The interaction between β-arrestin2 and the non-stimulated protomer was monitored through a bioluminescence resonance energy transfer (BRET) based method. To measure the conformational alterations in the non-stimulated protomer directly, we also used a BRET based intramolecular receptor biosensor, which was created by inserting yellow fluorescent protein (YFP) into the 3rd intracellular loop of AT₁R and fusing Renilla luciferase (RLuc) to its C terminal region. We have detected β-arrestin2 binding, and altered conformation of the non-stimulated protomer. The cooperative ligand binding of the receptor homodimer was also observed by radioligand dissociation experiments. Mutation of the conserved DRY sequence in the activated protomer, which is also required for G protein activation, abolished all the observed allosteric effects. These data suggest that allosteric interactions in the homodimers of AT₁R significantly affect the function of the non-stimulated protomer, and the conserved DRY motif has a crucial role in these interactions., (Copyright © 2012 Elsevier Inc. All rights reserved.)

In adrenal zona glomerulosa cells angiotensin II (Ang II) is a key regulator of steroidogenesis. Our purpose was to compare the mechanisms of Ang II-induced changes in the expression level of early transcription factors NR4A1 (NGFIB) and NR4A2 (Nurr1) genes, and the CYP11B2 gene encoding aldosterone synthase in H295R human adrenocortical tumor cells and in primary rat adrenal glomerulosa cells. Real-time PCR studies have demonstrated that Ang II increased the expression levels of NR4A1 and NR4A2 in H295R cells within 1 h after stimulation, which persisted up to 6 h; whereas in rat adrenal glomerulosa cells the kinetics of the expression of these genes were more rapid and transient. Ang II also induced prolonged nuclear translocation of Nurr1 and NGFIB proteins in both cell types. Studies using MEK inhibitor (PD98059, 20 microM), protein kinase C inhibitor (BIM1, 3 microM) and calmodulin kinase (CAMK) inhibitor (KN93, 10 microM) revealed that in rat adrenal glomerulosa cells CAMK-mediated mechanisms play a predominant role in the regulation of CYP11B2. In accordance with earlier findings, in H295R cells MEK inhibition increased the expression of NR4A1, NR4A2 and CYP11B2 genes, however, it decreased the Ang II-induced gene expression levels, suggesting that ERK activation has a role in control of expression of these genes. No such mechanism was detected in rat glomerulosa cells. Sar1-Ile4-Ile8-AngII, which can cause G protein-independent ERK activation, also stimulated the expression of CYP11B2 in H295R cells. These data suggest that the previously reported CAMK-mediated stimulation of early transcription factors NGFIB and Nurr1 has a predominant role in Ang II-induced CYP11B2 activation in rat adrenal glomerulosa cells, whereas in H295R cells ERK activation and G protein-independent mechanisms also contribute to this process.