An image-based Abplex method for high-throughput GPCRs antibody discovery.

As the field of antibody therapeutics advances rapidly, membrane proteins, particularly G protein-coupled receptors (GPCRs), have emerged as highly sought-after drug targets. However, the challenges associated with extracting membrane proteins have created a demand for effective antibody screening systems targeting these proteins. In this study, we propose developing an innovative antibody screening strategy (Abplex) based on high-content imaging. This approach leverages intact cells that express target membrane proteins, facilitating the presentation of proteins in their native conformation. Furthermore, it acquires both specific and non-specific binding signals in a single well, thereby bolstering the robustness of the outcomes. The technique involves just one step and can be completed within 50 min, enabling the analysis of a single sample in just one second. The amalgamation of dependable experimental findings, a simplified workflow, reduced hands-on time, and a swift analytical pace positions our method for superior throughput and precision when juxtaposed with traditional techniques such as CbELISA and FACS. Moreover, we introduce the concept of cell barcoding, wherein cells are labeled with different fluorescence spatial patterns. This feature allows for multiplexed detection to meet the needs of various experiments. The characteristics of Abplex promise to expedite GPCR-targeting antibody discovery, advance therapeutics and enable new disease treatments.

Association of fine particulate matter with glucose and lipid metabolism: a longitudinal study in young adults.

OBJECTIVES: This study aimed to evaluate whether PM2.5 exposure in a highly polluted area (>100 µg/m3) affects glucose and lipid metabolism in healthy adults. METHODS: We recruited 110 healthy adults in Baoding city, Hebei, China, and followed them up between 2017 and 2018. Personal air samplers were used to monitor personal PM2.5 levels. Eight glucose and lipid metabolism parameters were quantified. We performed the linear mixed-effect models to investigate the relationships between PM2.5 and glucose and lipid metabolism parameters. Stratified analyses were further performed according to sex and body mass index (BMI). RESULTS: The concentration of PM2.5 was the highest in spring, with a median of 232 µg/m3 and the lowest in autumn (139 µg/m3). After adjusting for potential confounders, we found that for each twofold increase in PM2.5, the median of insulin concentration decreased by 5.89% (95% CI -10.91% to -0.58%; p<0.05), and ox-LDL increased by 6.43% (95% CI 2.21% to 10.82%; p<0.05). Stratified analyses indicated that the associations were more pronounced in females, overweight and obese participants. CONCLUSIONS: Exposure to high PM2.5 may have deleterious effects on glucose and lipid metabolism. Females, overweight and obese participants are more vulnerable.

p16 deficiency attenuates intervertebral disc degeneration by adjusting oxidative stress and nucleus pulposus cell cycle.

The cell cycle regulator p16 is known as a biomarker and an effector of aging. However, its function in intervertebral disc degeneration (IVDD) is unclear. In this study, p16 expression levels were found to be positively correlated with the severity of human IVDD. In a mouse tail suspension (TS)-induced IVDD model, lumbar intervertebral disc height index and matrix protein expression levels were reduced significantly were largely rescued by p16 deletion. In TS mouse discs, reactive oxygen species levels, proportions of senescent cells, and the senescence-associated secretory phenotype (SASP) were all increased, cell cycling was delayed, and expression was downregulated for Sirt1, superoxide dismutase 1/2, cyclin-dependent kinases 4/6, phosphorylated retinoblastoma protein, and transcription factor E2F1/2. However, these effects were rescued by p16 deletion. Our results demonstrate that p16 plays an important role in IVDD pathogenesis and that its deletion attenuates IVDD by promoting cell cycle and inhibiting SASP, cell senescence, and oxidative stress.

Neck and shoulder pain, lower back pain and leg numbness are conditions that many people will encounter as years go by. This is because intervertebral discs, the padding structures that fit between the bones in the spine, degenerate with age: their cells enter a 'senescent', inactive state, and stop multiplying. A protein known as p16, an important regulator of cell growth and division, is known to accumulate in senescent cells. In fact, in mouse fat tissue, muscles or eyes, removing the cells that contain high levels of p16 delays aging-associated disorders. However, it was still unknown whether deactivating the gene that codes p16 in senescent cells could delay disc degeneration. Here, Che, Li et al. discovered that p16 is highly present in the senescent cells of severely degenerated human intervertebral discs. The cells in the nucleus pulposus, the jelly-like and most critical tissue in the intervertebral discs, were extracted and grown in the lab under conditions that replicate the early stages of damage to the spine. Drugs and genetic manipulations were then used to decrease the amount of p16 in these cells. The experiments showed that reducing the levels of p16 results in the senescent cells multiplying more and showing fewer signs of damage and aging. In addition, the discs of mice in which the gene that codes for p16 had been deleted were less prone to degeneration compared to 'normal' mice in similar conditions. Overall, the work by Che, Li et al. shows that inhibiting p16 in disc cells delays the aging process and reduces the degeneration of intervertebral discs. These findings may one day be applicable to people with intervertebral disc diseases who, for example, could potentially benefit from a gene therapy targeting the cells which produce p16.

Differentially Expressed microRNAs in MIA PaCa-2 and PANC-1 Pancreas Ductal Adenocarcinoma Cell Lines are Involved in Cancer Stem Cell Regulation.

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies, and thus better understanding of its molecular pathology is crucial for us to devise more effective treatment of this deadly disease. As cancer cell line remains a convenient starting point for discovery and proof-of-concept studies, here we report the miRNA expression characteristics of two cell lines, MIA PaCa-2 and PANC-1, and discovered three miRNAs (miR-7-5p, let-7d, and miR-135b-5p) that are involved in cancer stem cells (CSCs) suppression. After transfection of each miRNA's mimic into PANC-1 cells which exhibits higher stemness feature than MIA-PaCa-2 cells, partial reduction of CSC surface markers and inhibition of tumor sphere formation were observed. These results enlighten us to consider miRNAs as potential therapeutic agents for pancreatic cancer patients via specific and effective inhibition of CSCs.

The targeting mechanism of DHA ligand and its conjugate with Gemcitabine for the enhanced tumor therapy.

Docosahexaenoic acid (DHA), an omega-3 C22 natural fatty acid serving as a precursor for metabolic and biochemical pathways, was reported as a targeting ligand of anticancer drugs. However, its tumor targeting ability and mechanism has not been claimed. Here we hypothesized that the uptake of DHA by tumor cells is related to the phosphatidylethanolamine (PE) contents in cell membranes. Thus, in this manuscript, the tumor-targeting ability of DHA was initially demonstrated in vitro and in vivo on different tumor cell lines by labeling DHA with fluorescence dyes. Subsequently, the tumor targeting ability was then correlated with the contents of PE in cell membranes to study the uptake mechanism. Further, DHA was conjugated with anticancer drug gemcitabine (DHA-GEM) for targeted tumor therapy. Our results demonstrated that DHA exhibited high tumor targeting ability and PE is the main mediator, which confirmed our hypothesis. The DHA-GEM displayed enhanced therapeutic efficacy than that of GEM itself, indicating that DHA is a promising ligand for tumor targeted therapy.

Tubulin inhibitors: pharmacophore modeling, virtual screening and molecular docking.

AIM: To construct a quantitative pharmacophore model of tubulin inhibitors and to discovery new leads with potent antitumor activities. METHODS: Ligand-based pharmacophore modeling was used to identify the chemical features responsible for inhibiting tubulin polymerization. A set of 26 training compounds was used to generate hypothetical pharmacophores using the HypoGen algorithm. The structures were further validated using the test set, Fischer randomization method, leave-one-out method and a decoy set, and the best model was chosen to screen the Specs database. Hit compounds were subjected to molecular docking study using a Molecular Operating Environment (MOE) software and to biological evaluation in vitro. RESULTS: Hypo1 was demonstrated to be the best pharmacophore model that exhibited the highest correlation coefficient (0.9582), largest cost difference (70.905) and lowest RMSD value (0.6977). Hypo1 consisted of one hydrogen-bond acceptor, a hydrogen-bond donor, a hydrophobic feature, a ring aromatic feature and three excluded volumes. Hypo1 was validated with four different methods and had a goodness-of-hit score of 0.81. When Hypo1 was used in virtual screening of the Specs database, 952 drug-like compounds were revealed. After docking into the colchicine-binding site of tubulin, 5 drug-like compounds with the required interaction with the critical amino acid residues and the binding free energies < -4 kcal/mol were selected as representative leads. Compounds 1 and 3 exhibited inhibitory activity against MCF-7 human breast cancer cells in vitro. CONCLUSION: Hypo1 is a quantitative pharmacophore model for tubulin inhibitors, which not only provides a better understanding of their interaction with tubulin, but also assists in discovering new potential leads with antitumor activities.

Pharmacophore modeling and virtual screening for the discovery of new type 4 cAMP phosphodiesterase (PDE4) inhibitors.

Type 4 cAMP phosphodiesterase (PDE4) inhibitors show a broad spectrum of anti-inflammatory effects in almost all kinds of inflamed cells, by an increase in cAMP levels which is a pivotal second messenger responsible for various biological processes. These inhibitors are now considered as the potential drugs for treatment of chronic inflammatory diseases. However, some recently marketed inhibitors e.g., roflumilast, have shown adverse effects such as nausea and emesis, thus restricting its use. In order to identify novel PDE4 inhibitors with improved therapeutic indexes, a highly correlating (r = 0.963930) pharmacophore model (Hypo1) was established on the basis of known PDE4 inhibitors. Validated Hypo1 was used in database screening to identify chemical with required pharmacophoric features. These compounds are further screened by using the rule of five, ADMET and molecular docking. Finally, twelve hits which showed good results with respect to following properties such as estimated activity, calculated drug-like properties and scores were proposed as potential leads to inhibit the PDE4 activity. Therefore, this study will not only assist in the development of new potent hits for PDE4 inhibitors, but also give a better understanding of their interaction with PDE4. On a wider scope, this will be helpful for the rational design of novel potent enzyme inhibitors.