YY1 is involved in homologous recombination inhibition at guanine quadruplex sites in human cells.

Homologous recombination (HR) is a key process for repairing DNA double strand breaks and for promoting genetic diversity. However, HR occurs unevenly across the genome, and certain genomic features can influence its activity. One such feature is the presence of guanine quadruplexes (G4s), stable secondary structures widely distributed throughout the genome. These G4s play essential roles in gene transcription and genome stability regulation. Especially, elevated G4 levels in cells deficient in the Bloom syndrome helicase (BLM) significantly enhance HR at G4 sites, potentially threatening genome stability. Here, we investigated the role of G4-binding protein Yin Yang-1 (YY1) in modulating HR at G4 sites in human cells. Our results show that YY1's binding to G4 structures suppresses sister chromatid exchange after BLM knockdown, and YY1's chromatin occupancy negatively correlates with the overall HR rate observed across the genome. By limiting RAD51 homolog 1 (RAD51) access, YY1 preferentially binds to essential genomic regions, shielding them from excessive HR. Our findings unveil a novel role of YY1-G4 interaction, revealing novel insights into cellular mechanisms involved in HR regulation.

Which Coverages of Arc-Shaped Proteins Are Required for Membrane Tubulation?

Arc-shaped BIN/Amphiphysin/Rvs (BAR) domain proteins generate curvature by binding to membranes and induce membrane tubulation at sufficiently large protein coverages. For the amphiphysin N-BAR domain, Le Roux et al., Nat. Commun. 2021, 12, 6550, measured a threshold coverage of 0.44 ± 0.097 for nanotubules emerging from the supported lipid bilayer. In this article, we systematically investigate membrane tubulation induced by arc-shaped protein-like particles with coarse-grained modeling and simulations and determine the threshold coverages at different particle-particle interaction strengths and membrane spontaneous curvatures. In our simulations, the binding of arc-shaped particles induces a membrane shape transition from spherical vesicles to tubules at a particle threshold coverage of about 0.5, which is rather robust to variations of the direct attractive particle interactions or spontaneous membrane curvature in the coarse-grained model. Our study suggests that threshold coverages of around or slightly below 0.5 are a general requirement for membrane tubulation by arc-shaped BAR domain proteins.

Membrane-Mediated Cooperative Interactions of CD47 and SIRPα.

The specific binding of the ubiquitous 'marker of self' protein CD47 to the SIRPα protein anchored in the macrophage plasma membrane results in the inhibition of the engulfment of 'self' cells by macrophages and thus constitutes a key checkpoint of our innate immune system. Consequently, the CD47-SIRPα protein complex has been recognized as a potential therapeutic target in cancer and inflammation. Here, we introduce a lattice-based mesoscale model for the biomimetic system studied recently in fluorescence microscopy experiments where GFP-tagged CD47 proteins on giant plasma membrane vesicles bind to SIRPα proteins immobilized on a surface. Computer simulations of the lattice-based mesoscale model allow us to study the biomimetic system on multiple length scales, ranging from single nanometers to several micrometers and simultaneously keep track of single CD47-SIRPα binding and unbinding events. Our simulations not only reproduce data from the fluorescence microscopy experiments but also are consistent with results of several other experiments, which validates our numerical approach. In addition, our simulations yield quantitative predictions on the magnitude and range of effective, membrane-mediated attraction between CD47-SIRPα complexes. Such detailed information on CD47-SIRPα interactions cannot be obtained currently from experiments alone. Our simulation results thus extend the present understanding of cooperative effects in CD47-SIRPα interactions and may have an influence on the advancement of new cancer treatments.

Structural and functional insights into the chloroplast division site regulators PARC6 and PDV1 in the intermembrane space.

Chloroplast division involves the coordination of protein complexes from the stroma to the cytosol. The Min system of chloroplasts includes multiple stromal proteins that regulate the positioning of the division site. The outer envelope protein PLASTID DIVISION1 (PDV1) was previously reported to recruit the cytosolic chloroplast division protein ACCUMULATION AND REPLICATION OF CHLOROPLAST5 (ARC5). However, we show here that PDV1 is also important for the stability of the inner envelope chloroplast division protein PARALOG OF ARC6 (PARC6), a component of the Min system. We solved the structure of both the C-terminal domain of PARC6 and its complex with the C terminus of PDV1. The formation of an intramolecular disulfide bond within PARC6 under oxidized conditions prevents its interaction with PDV1. Interestingly, this disulfide bond can be reduced by light in planta, thus promoting PDV1-PARC6 interaction and chloroplast division. Interaction with PDV1 can induce the dimerization of PARC6, which is important for chloroplast division. Magnesium ions, whose concentration in chloroplasts increases upon light exposure, also promote the PARC6 dimerization. This study highlights the multilayer regulation of the PDV1-PARC6 interaction as well as chloroplast division.

Application of Nanotechnology in Thrombus Therapy.

A thrombus is a blood clot that forms in the lumen of an artery or vein, restricting blood flow and causing clinical symptoms. Thrombosis is associated with many life-threatening cardiovascular diseases. However, current clinical therapeutic technologies still have many problems in targeting, enrichment, penetration, and safety to meet the thrombosis treatment needs. Therefore, researchers devote themselves to developing nanosystems loaded with antithrombotic drugs to address this paradox in recent years. Herein, the existing thrombosis treatment technologies are first reviewed; and then, their advantages and disadvantages are outlined based on a brief discussion of thrombosis's definition and formation mechanism. Furthermore, the need and application cases for introducing nanotechnology are discussed, focusing on thrombus-specific targeted ligand modification technology and microenvironment-triggered responsive drug release technology. Then, nanomaterials that can be used to design antithrombotic nanotherapeutic systems are summarized. Moreover, a variety of drug delivery technologies driven by nanomotors in thrombosis therapy is also introduced. Last of all, a prospective discussion on the future development of nanotechnology for thrombosis therapy is highlighted.

Intercellular Receptor-ligand Binding: Effect of Protein-membrane Interaction.

Gaining insights into the intercellular receptor-ligand binding is of great importance for understanding numerous physiological and pathological processes, and stimulating new strategies in drug design and discovery. In contrast to the in vitro protein interaction in solution, the anchored receptor and ligand molecules interact with membrane in situ, which affects the intercellular receptor-ligand binding. Here, we review theoretical, simulation and experimental works regarding the regulatory effects of protein-membrane interactions on intercellular receptor-ligand binding mainly from the following aspects: membrane fluctuations, membrane curvature, glycocalyx, and lipid raft. In addition, we discuss biomedical significances and possible research directions to advance the field and highlight the importance of understanding of coupling effects of these factors in pharmaceutical development.

Interplay of receptor-ligand binding and lipid domain formation during cell adhesion.

Cell adhesion involved in biological processes such as cell migration, immune responses, and cancer metastasis, is mediated by the specific binding of receptor and ligand proteins. Some of these proteins exhibit affinity for nanoscale lipid clusters in cell membranes. A key question is how these nanoscale lipid clusters influence and react to the receptor-ligand binding during cell adhesion. In this article, we review recent computational studies that shed new light on the interplay of the receptor-ligand binding and the formation of lipid domains in adhering membranes. These studies indicate that the receptor-ligand binding promotes coalescence of lipid clusters into mesoscale domains, which, in turn, enhances both the affinity and cooperativity of the receptor-ligand binding in cell-cell adhesion with mobile ligands. In contrast, in the case of cell-extracellular matrix adhesion with immobile ligands, the receptor-ligand binding and the lipid cluster coalescence can be correlated or anti-correlated, depending strongly on the ligand distribution. These findings deepen our understanding of correlations between cell adhesion and membrane heterogeneities.

A Universal Chemotactic Targeted Delivery Strategy for Inflammatory Diseases.

Above 50% of deaths can be attributed to chronic inflammatory diseases; thus, the construction of drug delivery systems based on effective interaction of inflammatory factors with chemotactic nanoparticles is meaningful. Herein, a zwitterion-based artificial chemotactic nanomotor is proposed for universal precise targeting strategy in vivo, where the high level of reactive oxygen species (ROS) and inducible nitric oxide synthase (iNOS) in inflammatory sites are used as a chemoattractant. Multidimensional static models, dynamic models, and in vivo models are established to evaluate chemotactic performance. The results show that the upregulated ROS and iNOS can induce the chemotaxis of nanomotors to diseased tissues in inflammation-related disease models. Further, mesoscale hydrodynamics simulations are performed to explain the chemotactic behavior of the nanomotors. Such a chemotactic delivery strategy is expected to improve delivery efficiency and may be applicable to a variety of inflammatory diseases.

Insights into intercellular receptor-ligand binding kinetics in cell communication.

Cell-cell communication is crucial for cells to sense, respond and adapt to environmental cues and stimuli. The intercellular communication process, which involves multiple length scales, is mediated by the specific binding of membrane-anchored receptors and ligands. Gaining insight into two-dimensional receptor-ligand binding kinetics is of great significance for understanding numerous physiological and pathological processes, and stimulating new strategies in drug design and discovery. To this end, extensive studies have been performed to illuminate the underlying mechanisms that control intercellular receptor-ligand binding kinetics via experiment, theoretical analysis and numerical simulation. It has been well established that the cellular microenvironment where the receptor-ligand interaction occurs plays a vital role. In this review, we focus on the advances regarding the regulatory effects of three factors including 1) protein-membrane interaction, 2) biomechanical force, and 3) bioelectric microenvironment to summarize the relevant experimental observations, underlying mechanisms, as well as their biomedical significances and applications. Meanwhile, we introduce modeling methods together with experiment technologies developed for dealing with issues at different scales. We also outline future directions to advance the field and highlight that building up systematic understandings for the coupling effects of these regulatory factors can greatly help pharmaceutical development.

Effects of Capsaicin on the Hypoglycemic Regulation of Metformin and Gut Microbiota Profiles in Type 2 Diabetic Rats.

Dietary capsaicin (CAP), the main irritant component in pepper, can reduce the incidence of diabetes, while metformin (MET) is a first-line oral hypoglycemic drug. The purpose of this study was to investigate whether CAP on the hypoglycemic effect of MET is pertinent to gut microbiota. The glucose and insulin tolerance of diabetic rats were monitored. The glycolipid metabolism was analyzed by detecting blood biochemical parameters. Liver pathological changes were observed by Hematoxylin eosin (HE) staining. The inflammatory cytokines and intestinal tight junction proteins were detected by RT-qPCR and Western blot. 16S rRNA sequencing was employed to analyze gut microbiota profiles. The results showed that CAP and MET co-treatment could significantly reduce fasting blood glucose, improve glucose tolerance, lessen liver injury and inflammatory infiltration, down-regulate inflammatory cytokines and up-regulate intestinal tight junction proteins in diabetic rats by comparing it with MET monotherapy. Moreover, CAP and MET co-treatment altered gut microbiota profiles by regulating microbials' abundances such as Akkermansia. In conclusion, CAP showed the significant hypoglycemic effect of MET and remodulated gut microbiota profiles in diabetic rats.

Stability and Deformation of Vesicles in a Cylindrical Flow.

In this work, we used dissipative particle dynamics to study the stability, deformation, and rupture of polymer vesicles confined in cylindrical channels under the flow field. The morphological evolution, elongation, and rupture of vesicles and the corresponding mechanisms were intensively investigated. Bullet-like vesicles, leaking vesicles, spherical micelles, hamburger-like micelles, and bilayers were observed by changing the degree of confinement and dimensionless shear rate. We found that increasing the dimensionless shear rate and the degree of confinement can cause the deformation or rupture of polymeric vesicles. The asphericity parameter was utilized to describe the degree of elongation of vesicles deviating from the sphere in the direction of the flow. The results show that the aggregates are more likely to be spherical when the confinement is weak, while they become elongated bullet-like shapes when the confinement is strong. The investigation of dynamics reveals that the degree of confinement and the dimensionless shear rate can affect the chain stretching and reorganization during the process of vesicle elongation. Furthermore, the rupture time of the vesicle shows a nonlinear decrease with an increase in the dimensionless shear rate, and the confinement also contributes to the rupture. The results are very useful for guiding the application of vesicles in a flow environment.

Tuning cell adhesion on supported lipid bilayers via nanoscale geometry.

The cell-supported lipid bilayer (SLB) adhesion system has been widely used as the model system to study the receptor-ligand interactions that occur at the membrane interface. The ligand-functionalized SLBs are deposited either directly on solids or on polymer cushions. An important question that arises is whether the geometry of the SLB affects the binding of cell adhesion receptors to the ligands. By using a mesoscopic mechanical model and Monte Carlo simulations, we have investigated the adhesion of a fluid membrane to a corrugated or egg-carton shaped SLB. We find that the nanoscale geometry of the SLB strongly affects the receptor-ligand binding. This effect results from the fact that the adhering membrane bends according to the SLB geometry in order for the adhesion receptors to bind ligands. The membrane bending couples with spatial distribution of the receptor-ligand complexes and membrane thermal undulations. Our results demonstrate that cell adhesion to SLBs can be controlled by tuning the nanoscale geometry of the SLB, and may have profound implications for future development of tissue engineering and regenerative medicine.

Interplay between cooperativity of intercellular receptor-ligand binding and coalescence of nanoscale lipid clusters in adhering membranes.

Adhesion of biological cells is mediated by the specific binding of receptors and ligands which are typically large proteins spanning through the plasma membranes of the contacting cells. The receptors and ligands can exhibit affinity for nanoscale lipid clusters that form within the plasma membrane. A central question is how these nanoscale lipid clusters physically affect and respond to the receptor-ligand binding during cell adhesion. Within the framework of classical statistical mechanics we find that the receptor-ligand binding reduces the threshold energy for lipid clusters to coalesce into mesoscale domains by up to ∼50%, and that the formation of these domains induces significant cooperativity of the receptor-ligand binding. The interplay between the receptor-ligand binding cooperativity and the lipid domain formation manifests acute sensitivity of the membrane system to changes in control parameters. This sensitivity can be crucial in cell signaling and immune responses.

Membrane-Mediated Interactions Between Protein Inclusions.

Integral or peripheral membrane proteins, or protein oligomers often get close to each other on cell membranes and carry out biological tasks in a collective manner. In addition to electrostatic and van der Waals interactions, those proteins also experience membrane-mediated interactions, which may be necessary for their functionality. The membrane-mediated interactions originate from perturbation of lipid membranes by the presence of protein inclusions, and have been the subject of intensive research in membrane biophysics. Here we review both theoretical and numerical studies of such interactions for membrane proteins and for nanoparticles bound to lipid membranes.

An integrated prognosis model of pharmacogenomic gene signature and clinical information for diffuse large B-cell lymphoma patients following CHOP-like chemotherapy.

BACKGROUND: As the most common form of lymphoma, diffuse large B-cell lymphoma (DLBCL) is a clinical highly heterogeneous disease with variability in therapeutic outcomes and biological features. It is a challenge to identify of clinically meaningful tools for outcome prediction. In this study, we developed a prognosis model fused clinical characteristics with drug resistance pharmacogenomic signature to identify DLBCL prognostic subgroups for CHOP-based treatment. METHODS: The expression microarray data and clinical characteristics of 791 DLBCL patients from two Gene Expression Omnibus (GEO) databases were used to establish and validate this model. By using univariate Cox regression, eight clinical or genetic signatures were analyzed. The elastic net-regulated Cox regression analysis was used to select the best prognosis related factors into the predictive model. To estimate the prognostic capability of the model, Kaplan-Meier curve and the area under receiver operating characteristic (ROC) curve (AUC) were performed. RESULTS: A predictive model comprising 4 clinical factors and 2 pharmacogenomic gene signatures was established after 1000 times cross validation in the training dataset. The AUC of the comprehensive risk model was 0.78, whereas AUC value was lower for the clinical only model (0.68) or the gene only model (0.67). Compared with low-risk patients, the overall survival (OS) of DLBCL patients with high-risk scores was significantly decreased (HR = 4.55, 95% CI 3.14-6.59, log-rank p value = 1.06 × 10-15). The signature also enables to predict prognosis within different molecular subtypes of DLBCL. The reliability of the integrated model was confirmed by independent validation dataset (HR = 3.47, 95% CI 2.42-4.97, log rank p value = 1.53 × 10-11). CONCLUSIONS: This integrated model has a better predictive capability to ascertain the prognosis of DLBCL patients prior to CHOP-like treatment, which may improve the clinical management of DLBCL patients and provide theoretical basis for individualized treatment.

Identification of gene modules associated with survival of diffuse large B-cell lymphoma treated with CHOP-based chemotherapy.

Diffuse Large B-cell Lymphoma (DLBCL), a heterogeneous disease, is influenced by complex network of gene interactions. Most previous studies focused on individual genes, but ignored the importance of intergenic correlations. In current study, we aimed to explore the association between gene networks and overall survival (OS) of DLBCL patients treated with CHOP-based chemotherapy (cyclophosphamide combination with doxorubicin, vincristine and prednisone). Weighted gene co-expression network analysis was conducted to obtain insights into the molecular characteristics of DLBCL. Ten co-expression gene networks (modules) were identified in training dataset (n = 470), and their associations with patients' OS after chemotherapy were tested. The results were validated in four independent datasets (n = 802). Gene ontology (GO) biological function enrichment analysis was conducted with Metascape. Three modules (purple, brown and red), which were enriched in T-cell immune, cell-cell adhesion and extracellular matrix (ECM), respectively, were found to be related to longer OS. Higher expression of several hub genes within these three co-expression modules, for example, LCP2 (HR = 0.77, p = 5.40 × 10-2), CD2 (HR = 0.87, p = 6.31 × 10-2), CD3D (HR = 0.83, p = 6.94 × 10-3), FYB (HR = 0.82, p = 1.40 × 10-2), GZMK (HR = 0.92, p = 1.19 × 10-1), FN1 (HR = 0.88, p = 7.06 × 10-2), SPARC (HR = 0.82, p = 2.06 × 10-2), were found to be associated with favourable survival. Moreover, the associations of the modules and hub genes with OS in different molecular subtypes and different chemotherapy groups were also revealed. In general, our research revealed the key gene modules and several hub genes were upregulated correlated with good survival of DLBCL patients, which might provide potential therapeutic targets for future clinical research.

Long Non-coding RNA Expression Profiling in Biopsy to Identify Renal Allograft at Risk of Chronic Damage and Future Graft Loss.

The loss of allograft from chronic damage is still the major risk that renal transplant recipients face today. Biomarkers for early detection of chronic damage are needed to improve the long-term graft survival. This study aimed to identify long non-coding RNA (lncRNA) biomarkers associated with chronic damage and graft loss after renal transplantation. Gene Expression Omnibus (GEO) datasets including GSE57387 (n = 101), GSE21374 (n = 282), and GSE25902 (n = 24) from three high-quality studies were analyzed. By repurposing the publicly available array-based data coupled with Affymetrix Human Exon 1.0 ST and Human U133 Plus 2.0 arrays, we obtained expression profiles of 11323 and 3383 lncRNAs in biopsies after renal transplantation, respectively. The logistic regression model and Cox regression model were applied to identify lncRNAs associated with chronic damage and graft survival. High AC093673.5 expression was identified as significantly associated with the three endpoints including chronic damage, progressive chronic histological damage, and graft failure across these three datasets. A six-lncRNA signature was created to predict renal allograft at risk of chronic damage with a high predictive ability (AUC = 0.94). Gene set enrichment analysis (GSEA) indicated that our lncRNA signature was related with allograft rejection and immunity. Our study highlights the importance of lncRNAs in chronic graft damage and allograft loss, supporting their potential role as prognosis biomarkers.

Intercellular Receptor-Ligand Binding and Thermal Fluctuations Facilitate Receptor Aggregation in Adhering Membranes.

Nanoscale molecular clusters in cell membranes can serve as platforms to recruit membrane proteins for various biological functions. A central question is how these nanoclusters respond to physical contacts between cells. Using a statistical mechanics model and Monte Carlo simulations, we explore how the adhesion of cell membranes affects the stability and coalescence of clusters enriched in receptor proteins. Our results show that intercellular receptor-ligand binding and membrane shape fluctuations can lead to receptor aggregation within the adhering membranes even if large-scale clusters are thermodynamically unstable in nonadhering membranes.