Large Magnetoelectric Coupling in the Thin Film of Multiferroic CuO

We report observation of large magnetoelectric coupling in an epitaxial thin film of multiferroic CuO grown on the (100)MgO substrate by the pulsed laser deposition technique. The film is characterized by X-ray diffraction, transmission electron microscopy, and Raman spectrometry. The crystallographic structure of the film turns out to be monoclinic (space group C2/c) with 111]CuO parallel to100]MgO ``out-of-plane'' epitaxy and ``in-plane'' domain structure. The lattice misfit strain is found to vary within +/- 1-3%. The dc resistivity, magnetization, dielectric spectroscopy, and remanent ferroeletric polarization have been measured across 80-300 K. The dielectric constant is found to decrease by >20% under a moderate magnetic field of similar to 18 kOe while the remanent ferroelectric polarization, emerging at the onset of magnetic transition (T-N similar to 175 K), decreases by nearly 50% under similar to 18 kOe field. These results could assume importance as the strain-free bulk CuO does not exhibit magnetoelectric coupling within such magnetic field regime. The strain-induced large magnetoelectric coupling in the CuO thin film would generate new possibility of further strain tuning to observe room-temperature magnetoelectric multiferroicity suitable for scores of applications such as memories, sensors, energy-harvesting devices, generators, amplifiers, and so forth

Structure and dynamics of a constitutively active neurotensin receptor

Many G protein-coupled receptors show constitutive activity, resulting in the production of a second messenger in the absence of an agonist; and naturally occurring constitutively active mutations in receptors have been implicated in diseases. To gain insight into mechanistic aspects of constitutive activity, we report here the 3.3 Å crystal structure of a constitutively active, agonist-bound neurotensin receptor (NTSR1) and molecular dynamics simulations of agonist-occupied and ligand-free receptor. Comparison with the structure of a NTSR1 variant that has little constitutive activity reveals uncoupling of the ligand-binding domain from conserved connector residues, that effect conformational changes during GPCR activation. Furthermore, molecular dynamics simulations show strong contacts between connector residue side chains and increased flexibility at the intracellular receptor face as features that coincide with robust signalling in cells. The loss of correlation between the binding pocket and conserved connector residues, combined with altered receptor dynamics, possibly explains the reduced neurotensin efficacy in the constitutively active NTSR1 and a facilitated initial engagement with G protein in the absence of agonist

N-linked glycosylation of protease-activated receptor-1 at extracellular loop 2 regulates G-protein signaling bias

G-protein-coupled receptors (GPCRs) are the largest class of mammalian signaling receptors and mediate vast physiological responses. The capacity to modulate GPCR signaling therapeutically is important for treatment of various diseases, and discovering new aspects of receptor signaling is critical for drug development. Protease-activated receptor-1 (PAR1) is GPCR for thrombin. Similar to other GPCRs, PAR1 is promiscuous and couples to multiple heterotrimeric G-protein subtypes in the same cell. How a single GPCR can couple to multiple G-protein subtypes concurrently has remained an enigma. We demonstrate that N-linked glycosylation of PAR1 regulates G-protein coupling specificity and differentially controls cellular responses. Thus, the status of GPCR glycosylation is a critical determinant for specifying coupling to distinct G-protein subtypes

Dynamic Phenotypic Switching and Group Behavior Help Non-Small Cell Lung Cancer Cells Evade Chemotherapy

Drug resistance, a major challenge in cancer therapy, is typically attributed to mutations and genetic heterogeneity. Emerging evidence suggests that dynamic cellular interactions and group behavior also contribute to drug resistance. However, the underlying mechanisms remain poorly understood. Here, we present a new mathematical approach with game theoretical underpinnings that we developed to model real-time growth data of non-small cell lung cancer (NSCLC) cells and discern patterns in response to treatment with cisplatin. We show that the cisplatin-sensitive and cisplatin-tolerant NSCLC cells, when co-cultured in the absence or presence of the drug, display dynamic group behavior strategies. Tolerant cells exhibit a \u27persister-like\u27 behavior and are attenuated by sensitive cells; they also appear to \u27educate\u27 sensitive cells to evade chemotherapy. Further, tolerant cells can switch phenotypes to become sensitive, especially at low cisplatin concentrations. Finally, switching treatment from continuous to an intermittent regimen can attenuate the emergence of tolerant cells, suggesting that intermittent chemotherapy may improve outcomes in lung cancer

Differential CpG methylation at Nnat in the early establishment of beta cell heterogeneity

Aims/hypothesis: Beta cells within the pancreatic islet represent a heterogenous population wherein individual sub-groups of cells make distinct contributions to the overall control of insulin secretion. These include a subpopulation of highly connected ‘hub’ cells, important for the propagation of intercellular Ca2+ waves. Functional subpopulations have also been demonstrated in human beta cells, with an altered subtype distribution apparent in type 2 diabetes. At present, the molecular mechanisms through which beta cell hierarchy is established are poorly understood. Changes at the level of the epigenome provide one such possibility, which we explore here by focusing on the imprinted gene Nnat (encoding neuronatin [NNAT]), which is required for normal insulin synthesis and secretion. Methods: Single-cell RNA-seq datasets were examined using Seurat 4.0 and ClusterProfiler running under R. Transgenic mice expressing enhanced GFP under the control of the Nnat enhancer/promoter regions were generated for FACS of beta cells and downstream analysis of CpG methylation by bisulphite sequencing and RNA-seq, respectively. Animals deleted for the de novo methyltransferase DNA methyltransferase 3 alpha (DNMT3A) from the pancreatic progenitor stage were used to explore control of promoter methylation. Proteomics was performed using affinity purification mass spectrometry and Ca2+ dynamics explored by rapid confocal imaging of Cal-520 AM and Cal-590 AM. Insulin secretion was measured using homogeneous time-resolved fluorescence imaging. Results: Nnat mRNA was differentially expressed in a discrete beta cell population in a developmental stage- and DNA methylation (DNMT3A)-dependent manner. Thus, pseudo-time analysis of embryonic datasets demonstrated the early establishment of Nnat-positive and -negative subpopulations during embryogenesis. NNAT expression is also restricted to a subset of beta cells across the human islet that is maintained throughout adult life. NNAT+ beta cells also displayed a discrete transcriptome at adult stages, representing a subpopulation specialised for insulin production, and were diminished in db/db mice. ‘Hub’ cells were less abundant in the NNAT+ population, consistent with epigenetic control of this functional specialisation. Conclusions/interpretation: These findings demonstrate that differential DNA methylation at Nnat represents a novel means through which beta cell heterogeneity is established during development. We therefore hypothesise that changes in methylation at this locus may contribute to a loss of beta cell hierarchy and connectivity, potentially contributing to defective insulin secretion in some forms of diabetes. Data availability: The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD048465. Graphical Abstract

Recent Advances in Computational Protocols Addressing Intrinsically Disordered Proteins

Intrinsically disordered proteins (IDP) are abundant in the human genome and have recently emerged as major therapeutic targets for various diseases. Unlike traditional proteins that adopt a definitive structure, IDPs in free solution are disordered and exist as an ensemble of conformations. This enables the IDPs to signal through multiple signaling pathways and serve as scaffolds for multi-protein complexes. The challenge in studying IDPs experimentally stems from their disordered nature. Nuclear magnetic resonance (NMR), circular dichroism, small angle X-ray scattering, and single molecule Förster resonance energy transfer (FRET) can give the local structural information and overall dimension of IDPs, but seldom provide a unified picture of the whole protein. To understand the conformational dynamics of IDPs and how their structural ensembles recognize multiple binding partners and small molecule inhibitors, knowledge-based and physics-based sampling techniques are utilized in-silico, guided by experimental structural data. However, efficient sampling of the IDP conformational ensemble requires traversing the numerous degrees of freedom in the IDP energy landscape, as well as force-fields that accurately model the protein and solvent interactions. In this review, we have provided an overview of the current state of computational methods for studying IDP structure and dynamics and discussed the major challenges faced in this field