Cell-specific IL-1R1 regulates the regional heterogeneity of microglial displacement of GABAergic synapses and motor learning ability.

Microglia regulate synaptic function in various ways, including the microglial displacement of the surrounding GABAergic synapses, which provides important neuroprotection from certain diseases. However, the physiological role and underlying mechanisms of microglial synaptic displacement remain unclear. In this study, we observed that microglia exhibited heterogeneity during the displacement of GABAergic synapses surrounding neuronal soma in different cortical regions under physiological conditions. Through three-dimensional reconstruction, in vitro co-culture, two-photon calcium imaging, and local field potentials recording, we found that IL-1ß negatively modulated microglial synaptic displacement to coordinate regional heterogeneity in the motor cortex, which impacted the homeostasis of the neural network and improved motor learning ability. We used the Cre-Loxp system and found that IL-1R1 on glutamatergic neurons, rather than that on microglia or GABAergic neurons, mediated the negative effect of IL-1ß on synaptic displacement. This study demonstrates that IL-1ß is critical for the regional heterogeneity of synaptic displacement by coordinating different actions of neurons and microglia via IL-1R1, which impacts both neural network homeostasis and motor learning ability. It provides a theoretical basis for elucidating the physiological role and mechanism of microglial displacement of GABAergic synapses.

Elastic network modeling of cellular networks unveils sensor and effector genes that control information flow.

The high-level organization of the cell is embedded in indirect relationships that connect distinct cellular processes. Existing computational approaches for detecting indirect relationships between genes typically consist of propagating abstract information through network representations of the cell. However, the selection of genes to serve as the source of propagation is inherently biased by prior knowledge. Here, we sought to derive an unbiased view of the high-level organization of the cell by identifying the genes that propagate and receive information most effectively in the cell, and the indirect relationships between these genes. To this aim, we adapted a perturbation-response scanning strategy initially developed for identifying allosteric interactions within proteins. We deployed this strategy onto an elastic network model of the yeast genetic interaction profile similarity network. This network revealed a superior propensity for information propagation relative to simulated networks with similar topology. Perturbation-response scanning identified the major distributors and receivers of information in the network, named effector and sensor genes, respectively. Effectors formed dense clusters centrally integrated into the network, whereas sensors formed loosely connected antenna-shaped clusters and contained genes with previously characterized involvement in signal transduction. We propose that indirect relationships between effector and sensor clusters represent major paths of information flow between distinct cellular processes. Genetic similarity networks for fission yeast and human displayed similarly strong propensities for information propagation and clusters of effector and sensor genes, suggesting that the global architecture enabling indirect relationships is evolutionarily conserved across species. Our results demonstrate that elastic network modeling of cellular networks constitutes a promising strategy to probe the high-level organization and cooperativity in the cell.

Superantigenic character of an insert unique to SARS-CoV-2 spike supported by skewed TCR repertoire in patients with hyperinflammation.

Multisystem Inflammatory Syndrome in Children (MIS-C) associated with COVID-19 is a newly recognized condition in children with recent severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. These children and adult patients with severe hyperinflammation present with a constellation of symptoms that strongly resemble toxic shock syndrome, an escalation of the cytotoxic adaptive immune response triggered upon the binding of pathogenic superantigens to T cell receptors (TCRs) and/or major histocompatibility complex class II (MHCII) molecules. Here, using structure-based computational models, we demonstrate that the SARS-CoV-2 spike (S) glycoprotein exhibits a high-affinity motif for binding TCRs, and may form a ternary complex with MHCII. The binding epitope on S harbors a sequence motif unique to SARS-CoV-2 (not present in other SARS-related coronaviruses), which is highly similar in both sequence and structure to the bacterial superantigen staphylococcal enterotoxin B. This interaction between the virus and human T cells could be strengthened by a rare mutation (D839Y/N/E) from a European strain of SARS-CoV-2. Furthermore, the interfacial region includes selected residues from an intercellular adhesion molecule (ICAM)-like motif shared between the SARS viruses from the 2003 and 2019 pandemics. A neurotoxin-like sequence motif on the receptor-binding domain also exhibits a high tendency to bind TCRs. Analysis of the TCR repertoire in adult COVID-19 patients demonstrates that those with severe hyperinflammatory disease exhibit TCR skewing consistent with superantigen activation. These data suggest that SARS-CoV-2 S may act as a superantigen to trigger the development of MIS-C as well as cytokine storm in adult COVID-19 patients, with important implications for the development of therapeutic approaches.

ClustENMD: efficient sampling of biomolecular conformational space at atomic resolution.

SUMMARY: Efficient sampling of conformational space is essential for elucidating functional/allosteric mechanisms of proteins and generating ensembles of conformers for docking applications. However, unbiased sampling is still a challenge especially for highly flexible and/or large systems. To address this challenge, we describe a new implementation of our computationally efficient algorithm ClustENMD that is integrated with ProDy and OpenMM softwares. This hybrid method performs iterative cycles of conformer generation using elastic network model for deformations along global modes, followed by clustering and short molecular dynamics simulations. ProDy framework enables full automation and analysis of generated conformers and visualization of their distributions in the essential subspace. AVAILABILITY AND IMPLEMENTATION: ClustENMD is open-source and freely available under MIT License from https://github.com/prody/ProDy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

ProDy 2.0: increased scale and scope after 10 years of protein dynamics modelling with Python.

SUMMARY: ProDy, an integrated application programming interface developed for modelling and analysing protein dynamics, has significantly evolved in recent years in response to the growing data and needs of the computational biology community. We present major developments that led to ProDy 2.0: (i) improved interfacing with databases and parsing new file formats, (ii) SignDy for signature dynamics of protein families, (iii) CryoDy for collective dynamics of supramolecular systems using cryo-EM density maps and (iv) essential site scanning analysis for identifying sites essential to modulating global dynamics. AVAILABILITY AND IMPLEMENTATION: ProDy is open-source and freely available under MIT License from https://github.com/prody/ProDy. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Mechanistic Insights into Passive Membrane Permeability of Drug-like Molecules from a Weighted Ensemble of Trajectories.

Passive permeability of a drug-like molecule is a critical property assayed early in a drug discovery campaign that informs a medicinal chemist how well a compound can traverse biological membranes, such as gastrointestinal epithelial or restrictive organ barriers, so it can perform a specific therapeutic function. However, the challenge that remains is the development of a method, experimental or computational, which can both determine the permeation rate and provide mechanistic insights into the transport process to help with the rational design of any given molecule. Typically, one of the following three methods are used to measure the membrane permeability: (1) experimental permeation assays acting on either artificial or natural membranes; (2) quantitative structure-permeability relationship models that rely on experimental values of permeability or related pharmacokinetic properties of a range of molecules to infer those for new molecules; and (3) estimation of permeability from the Smoluchowski equation, where free energy and diffusion profiles along the membrane normal are taken as input from large-scale molecular dynamics simulations. While all these methods provide estimates of permeation coefficients, they provide very little information for guiding rational drug design. In this study, we employ a highly parallelizable weighted ensemble (WE) path sampling strategy, empowered by cloud computing techniques, to generate unbiased permeation pathways and permeability coefficients for a set of drug-like molecules across a neat 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine membrane bilayer. Our WE method predicts permeability coefficients that compare well to experimental values from an MDCK-LE cell line and PAMPA assays for a set of drug-like amines of varying size, shape, and flexibility. Our method also yields a series of continuous permeation pathways weighted and ranked by their associated probabilities. Taken together, the ensemble of reactive permeation pathways, along with the estimate of the permeability coefficient, provides a clearer picture of the microscopic underpinnings of small-molecule membrane permeation.

Differences in the intrinsic spatial dynamics of the chromatin contribute to cell differentiation.

Advances in chromosome conformation capture techniques as well as computational characterization of genomic loci structural dynamics open new opportunities for exploring the mechanistic aspects of genome-scale differences across different cell types. We examined here the dynamic basis of variabilities between different cell types by investigating their chromatin mobility profiles inferred from Hi-C data using an elastic network model representation of the chromatin. Our comparative analysis of sixteen cell lines reveals close similarities between chromosomal dynamics across different cell lines on a global scale, but notable cell-specific variations emerge in the detailed spatial mobilities of genomic loci. Closer examination reveals that the differences in spatial dynamics mainly originate from the difference in the frequencies of their intrinsically accessible modes of motion. Thus, even though the chromosomes of different types of cells have access to similar modes of collective movements, not all modes are deployed by all cells, such that the effective mobilities and cross-correlations of genomic loci are cell-type-specific. Comparison with RNA-seq expression data reveals a strong overlap between highly expressed genes and those distinguished by high mobilities in the present study, in support of the role of the intrinsic spatial dynamics of chromatin as a determinant of cell differentiation.

Normal mode analysis of membrane protein dynamics using the vibrational subsystem analysis.

The vibrational subsystem analysis is a useful approach that allows for evaluating the spectrum of modes of a given system by integrating out the degrees of freedom accessible to the environment. The approach could be utilized for exploring the collective dynamics of a membrane protein (system) coupled to the lipid bilayer (environment). However, the application to membrane proteins is limited due to high computational costs of modeling a sufficiently large membrane environment unbiased by end effects, which drastically increases the size of the investigated system. We derived a recursive formula for calculating the reduced Hessian of a membrane protein embedded in a lipid bilayer by decomposing the membrane into concentric cylindrical domains with the protein located at the center. The approach allows for the design of a time- and memory-efficient algorithm and a mathematical understanding of the convergence of the reduced Hessian with respect to increasing membrane sizes. The application to the archaeal aspartate transporter GltPh illustrates its utility and efficiency in capturing the transporter's elevator-like movement during its transition between outward-facing and inward-facing states.

Rutaecarpine enhances the anti-diabetic activity and hepatic distribution of metformin via up-regulation of Oct1 in diabetic rats.

Diabetes mellitus is a chronic metabolic disorder with multiple complications, patients who receive metformin may have a simultaneous intake of herbal medicine containing rutaecarpine due to cardiovascular protection and hypolipidemic effects of rutaecarpine. There might be drug interactions between metformin and rutaecarpine. This study aimed to investigate the effects of rutaecarpine on the pharmacodynamics and pharmacokinetics of metformin in diabetic rats.The diabetic rat model was induced with high-fat diet and low dose streptozotocin. Metformin with or without rutaecarpine was administered by oral gavage for 42 days. Pharmacodynamics and pharmacokinetics parameters were evaluated.The pharmacodynamics results revealed that co-administration of rutaecarpine with metformin resulted in a remarkable reduction of serum glucose and lipid profiles in diabetic rats compared to metformin treated alone. The pharmacokinetics results showed that co-treatments of rutaecarpine with metformin did not affect the systemic exposure and renal distribution of metformin, but increased metformin concentration in liver. Furthermore, rutaecarpine increased Oct1-mediated metformin uptake into hepatocytes by upregulation of Oct1 expression in the liver.The above data indicate that rutaecarpine enhanced the anti-diabetic effect of metformin, which may be associated with the increased hepatic distribution of metformin through up-regulation of Oct1 in response to rutaecarpine.

Shared Signature Dynamics Tempered by Local Fluctuations Enables Fold Adaptability and Specificity.

Recent studies have drawn attention to the evolution of protein dynamics, in addition to sequence and structure, based on the premise structure-encodes-dynamics-encodes-function. Of interest is to understand how functional differentiation is accomplished while maintaining the fold, or how intrinsic dynamics plays out in the evolution of structural variations and functional specificity. We performed a systematic computational analysis of 26,899 proteins belonging to 116 CATH superfamilies. Characterizing cooperative mechanisms and convergent/divergent features that underlie the shared/differentiated dynamics of family members required a methodology that lends itself to efficient analyses of large ensembles of proteins. We therefore introduced, SignDy, an integrated pipeline for evaluating the signature dynamics of families based on elastic network models. Our analysis confirmed that family members share conserved, highly cooperative (global) modes of motion. Importantly, our analysis discloses a subset of motions that sharply distinguishes subfamilies, which lie in a low-to-intermediate frequency regime of the mode spectrum. This regime has maximal impact on functional differentiation of families into subfamilies, while being evolutionarily conserved among subfamily members. Notably, the high-frequency end of the spectrum also reveals evolutionary conserved features across and within subfamilies; but in sharp contrast to global motions, high-frequency modes are minimally collective. Modulation of robust/conserved global dynamics by low-to-intermediate frequency fluctuations thus emerges as a versatile mechanism ensuring the adaptability of selected folds and the specificity of their subfamilies. SignDy further allows for dynamics-based categorization as a new layer of information relevant to distinctive mechanisms of action of subfamilies, beyond sequence or structural classifications.

Involvement of organic anion-transporting polypeptides and organic cation transporter in the hepatic uptake of jatrorrhizine.

Jatrorrhizine possesses a wide spectrum of pharmacological activities. However, the mechanism underlying hepatic uptake of jatrorrhizine remains unclear.Rat liver slices, isolated rat hepatocytes and human embryonic kidney 293 (HEK293) cells stably expressing human organic anion-transporting polypeptide (OATP) and organic cation transporter (OCT) were used to evaluate the hepatic uptake of jatrorrhizine in this study.Uptake of jatrorrhizine in rat liver slices and isolated rat hepatocytes was significantly inhibited by glycyrrhizic acid (Oatp1b2 inhibitor) and prazosin (Oct1 inhibitor), but not by ibuprofen (Oatp1a1 inhibitor) or digoxin (Oatp1a4 inhibitor). Uptake of jatrorrhizine in OATP1B3 and OCT1-HEK293 cells indicated a saturable process with the Km of 8.20 ± 1.28 and 4.94 ± 0.55 µM, respectively. However, the transcellular transport of jatrorrhizine in OATP1B1-HEK293 cells was not observed. Rifampicin (OATP inhibitor) for OATP1B3-HEK293 cells and prazosin for OCT1-HEK293 cells could inhibit the uptake of jatrorrhizine with the IC50 of 5.49 ± 1.05 and 2.77 ± 0.72 µM, respectively.The above data indicate that hepatic uptake of jatrorrhizine is involved in both OATP and OCT, which may have important roles in jatrorrhizine liver disposition and potential drug-drug interactions.

Characterization of Differential Dynamics, Specificity, and Allostery of Lipoxygenase Family Members.

Accurate modeling of structural dynamics of proteins and their differentiation across different species can help us understand generic mechanisms of function shared by family members and the molecular basis of the specificity of individual members. We focused here on the family of lipoxygenases, enzymes that catalyze lipid oxidation, the mammalian and bacterial structures of which have been elucidated. We present a systematic method of approach for characterizing the sequence, structure, dynamics, and allosteric signaling properties of these enzymes using a combination of structure-based models and methods and bioinformatics tools applied to a data set of 88 structures. The analysis elucidates the signature dynamics of the lipoxygenase family and its differentiation among members, as well as key sites that enable its adaptation to specific substrate binding and allosteric activity.

Chromosomal dynamics predicted by an elastic network model explains genome-wide accessibility and long-range couplings.

Understanding the three-dimensional (3D) architecture of chromatin and its relation to gene expression and regulation is fundamental to understanding how the genome functions. Advances in Hi-C technology now permit us to study 3D genome organization, but we still lack an understanding of the structural dynamics of chromosomes. The dynamic couplings between regions separated by large genomic distances (>50 Mb) have yet to be characterized. We adapted a well-established protein-modeling framework, the Gaussian Network Model (GNM), to model chromatin dynamics using Hi-C data. We show that the GNM can identify spatial couplings at multiple scales: it can quantify the correlated fluctuations in the positions of gene loci, find large genomic compartments and smaller topologically-associating domains (TADs) that undergo en bloc movements, and identify dynamically coupled distal regions along the chromosomes. We show that the predictions of the GNM correlate well with genome-wide experimental measurements. We use the GNM to identify novel cross-correlated distal domains (CCDDs) representing pairs of regions distinguished by their long-range dynamic coupling and show that CCDDs are associated with increased gene co-expression. Together, these results show that GNM provides a mathematically well-founded unified framework for modeling chromatin dynamics and assessing the structural basis of genome-wide observations.

Chemical constituents of Bletilla striata.

A new triphenanthrene compound named 2,2',2'',7,7',7''-hexahydroxy-4,4',4''-trimethoxy-[9,9',9'',10,10',10'']-hexahydro-1,8,1',6''-triphenanthrene (1), together with eleven known compounds (2－12), were isolated from tubers of Bletilla striata. Their structures were determined by analysis of spectroscopic data.

Both Talin-1 and Talin-2 correlate with malignancy potential of the human hepatocellular carcinoma MHCC-97 L cell.

BACKGROUND: Talin-1 (TLN-1) and TLN-2 are implicated in many cellular processes, but their roles in hepatocellular carcinoma (HCC) remain unclear. This study aimed to assess cell cycle distribution, anoikis, invasion and migration in human HCC MHCC-97 L cells. METHODS: MHCC-97 L cells, which highly express TLN-1, were transduced with TLN-1 shRNA (experimental group) or scramble shRNA (negative control group); non-transduced MHCC-97 L cells were used as blank controls. TLN-1 and TLN-2 mRNA and protein levels were detected by real-time RT-PCR and western blot, respectively. Then, cell cycle distribution and anoikis were assessed by flow cytometry. In addition, migration and invasion abilities were assessed using Transwell and cell scratch assays. Finally, a xenograft nude mouse model was established to further assess cell tumorigenicity. RESULTS: Compared with the blank and negative control groups, TLN-1/2 mRNA and protein levels were significantly reduced in the experiment group. TLN-1/2 knockdown cells showed significantly more cells in the G0/G1 phase (79.24%) in comparison with both blank (65.36%) and negative (62.69%) control groups; conversely, less cells were found in G2/M and S phases in the experimental group compared with controls. Moreover, anoikis was enhanced (P < 0.05), while invasion and migration abilities were reduced (P < 0.05) in TLN-1/2 knockdown cells compared with controls. TLN-1/2 knockdown inhibited MHCC-97 L cell migration (Percentage of wound healing area: experimental group: 32.6 ± 0.7% vs. negative controls: 50.1 ± 0.6% and blank controls: 53.6 ± 0.6%, both P < 0.01). Finally, the tumors obtained with TLN-1/2 knockdown cells were smaller (P < 0.05) compared with controls. CONCLUSION: Both TLN-1 and TLN-2 levels correlate with tumorigenicity in human HCC, indicating that these molecules constitute important molecular targets for the diagnosis and/or treatment of HCC.

Structure-Encoded Global Motions and Their Role in Mediating Protein-Substrate Interactions.

Recent structure-based computational studies suggest that, in contrast to the classical description of equilibrium fluctuations as wigglings and jigglings, proteins have access to well-defined spectra of collective motions, called intrinsic dynamics, encoded by their structure under native state conditions. In particular, the global modes of motions (at the low frequency end of the spectrum) are shown by multiple studies to be highly robust to minor differences in the structure or to detailed interactions at the atomic level. These modes, encoded by the overall fold, usually define the mechanisms of interactions with substrates. They can be estimated by low-resolution models such as the elastic network models (ENMs) exclusively based on interresidue contact topology. The ability of ENMs to efficiently assess the global motions intrinsically favored by the overall fold as well as the relevance of these predictions to the dominant changes in structure experimentally observed for a given protein in the presence of different substrates suggest that the intrinsic dynamics plays a role in mediating protein-substrate interactions. These observations underscore the functional significance of structure-encoded dynamics, or the importance of the predisposition to favor functional global modes in the evolutionary selection of structures.

Cadmium Induced Apoptosis in MG63 Cells by Increasing ROS, Activation of p38 MAPK and Inhibition of ERK 1/2 Pathways.

BACKGROUND/AIMS: Cadmium (Cd) induces apoptosis in different kinds of cells, including osteoblasts, both in vivo and in vitro. However, little is known about the mechanisms by which Cd induces apoptosis. METHODS: In the present study, we used the human osteosarcoma cell line MG63, which has characteristics similar to human osteoblasts, as an in vitro model to determine the cellular mechanisms by which Cd induces apoptosis. RESULTS: We found that short-term exposure to CdCl2 induced apoptosis in MG63 cells. Furthermore, the incubation of cells with CdCl2 significantly increased the level of phosphorylated p38MAPK and significantly decreased the phosphorylation of ERK1/2 in a concentration-dependent manner. Additionally, the inhibition of the phosphorylation of p38 MAPK by SB202190 protected MG63 cells from Cd-induced apoptosis. The incubation of MG63 cells with the ERK1/2 inhibitor PD98059 significantly increased apoptosis in MG63 cells. CdCl2 also significantly increased the intracellular levels of ROS. N-acetylcysteine (NAC) significantly reduced ROS levels and reversed the effects of CdCl2 on MAPK signaling. CONCLUSION: Our results suggested that Cd induced apoptosis in MG63 cells by increasing ROS, activation of p38 MAPK and inhibition of ERK1/2 pathways.

Genome structural dynamics: insights from Gaussian network analysis of Hi-C data.

Characterization of the spatiotemporal properties of the chromatin is essential to gaining insights into the physical bases of gene co-expression, transcriptional regulation and epigenetic modifications. The Gaussian network model (GNM) has proven in recent work to serve as a useful tool for modeling chromatin structural dynamics, using as input high-throughput chromosome conformation capture data. We focus here on the exploration of the collective dynamics of chromosomal structures at hierarchical levels of resolution, from single gene loci to topologically associating domains or entire chromosomes. The GNM permits us to identify long-range interactions between gene loci, shedding light on the role of cross-correlations between distal regions of the chromosomes in regulating gene expression. Notably, GNM analysis performed across diverse cell lines highlights the conservation of the global/cooperative movements of the chromatin across different types of cells. Variations driven by localized couplings between genomic loci, on the other hand, underlie cell differentiation, underscoring the significance of the four-dimensional properties of the genome in defining cellular identity. Finally, we demonstrate the close relation between the cell type-dependent mobility profiles of gene loci and their gene expression patterns, providing a clear demonstration of the role of chromosomal 4D features in defining cell-specific differential expression of genes.

Baicalein reduces ß-amyloid and promotes nonamyloidogenic amyloid precursor protein processing in an Alzheimer's disease transgenic mouse model.

Baicalein, a flavonoid isolated from the roots of Scutellaria baicalensis, is known to modulate γ-aminobutyric acid (GABA) type A receptors. Given prior reports demonstrating benefits of GABAA modulation for Alzheimer's disease (AD) treatment, we wished to determine whether this agent might be beneficial for AD. CHO cells engineered to overexpress wild-type amyloid precursor protein (APP), primary culture neuronal cells from AD mice (Tg2576) and AD mice were treated with baicalein. In the cell cultures, baicalein significantly reduced the production of ß-amyloid (Aß) by increasing APP α-processing. These effects were blocked by the GABAA antagonist bicuculline. Likewise, AD mice treated daily with i.p. baicalein for 8 weeks showed enhanced APP α-secretase processing, reduced Aß production, and reduced AD-like pathology together with improved cognitive performance. Our findings suggest that baicalein promotes nonamyloidogenic processing of APP, thereby reducing Aß production and improving cognitive performance, by activating GABAA receptors.

Relationship between Helicobacter pylori infection and serum interleukin-18 in patients with carotid atherosclerosis.

BACKGROUND: Helicobacter pylori (H. pylori) infection stimulates the production of proinflammatory cytokines associated with the development of atherosclerosis. Levels of circulating interleukin-18 (IL-18) have been positively correlated with carotid intima-media thickness (IMT) and coronary plaque area and have identified IL-18 levels as important predictors of coronary events and cardiovascular mortality. This study aimed to examine the relationship between serum IL-18 and H. pylori-IgG antibody as a sign of H. pylori infection in patients with carotid atherosclerosis. METHODS: The carotid IMT, traditional atherosclerotic risk factors, levels of serum H. pylori-IgG and IL-18 were measured in 573 health checkup examinees. RESULTS: Serum IL-18 and H. pylori-IgG levels were significantly increased in subjects with increased IMT in comparison with those with normal IMT. In subjects with increased IMT, serum H. pylori-IgG was positively correlated with serum IL-18 (r = .402, p = .002), and the association was independent of traditional atherosclerotic risk factors (ß = 0.310, p < .001). CONCLUSIONS: In health checkup examinees with increased IMT, serum IL-18 and H. pylori-IgG were independently correlated and were significantly higher than in subjects with normal IMT.