High-Content Screening for Protein-Protein Interaction Modulators Using Proximity Ligation Assay in Primary Neurons

High-Content Screening of Synaptic Density Modulators in Primary Neuronal Cultures

The synapse, which represents the structural and functional basis of neuronal communication, is one of the first elements affected in several neurodegenerative diseases. To better understand the potential role of gene expression in synapse loss, we developed an original high-content screening (HCS) model capable of quantitatively assessing the impact of gene silencing on synaptic density. Our approach is based on a model of primary neuronal cultures (PNCs) from the neonatal rat hippocampus, whose mature synapses are visualized by the relative localization of the presynaptic protein Synaptophysin with the postsynaptic protein Homer1. The heterogeneity of PNCs and the small sizes of the synaptic structures pose technical challenges associated with the level of automation necessary for HCS studies. We overcame these technical challenges, automated the processes of image analysis and data analysis, and carried out tests under real-world conditions to demonstrate the robustness of the model developed. In this article, we describe the screening of a custom library of 198 shRNAs in PNCs in the 384-well plate format. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Culture of primary hippocampal rat neurons in 384-well plates Basic Protocol 2: Lentiviral shRNA transduction of primary neuronal culture in 384-well plates Basic Protocol 3: Immunostaining of the neuronal network and synaptic markers in 384-well plates Basic Protocol 4: Image acquisition using a high-throughput reader Basic Protocol 5: Image segmentation and analysis Basic Protocol 6: Synaptic density analysis.

Elucidating the Interactome of G Protein-Coupled Receptors and Receptor Activity-Modifying Proteins

G protein-coupled receptors (GPCRs) are known to interact with several other classes of integral membrane proteins that modulate their biology and pharmacology. However, the extent of these interactions and the mechanisms of their effects are not well understood. For example, one class of GPCR-interacting proteins, receptor activity-modifying proteins (RAMPs), comprise three related and ubiquitously expressed single-transmembrane span proteins. The RAMP family was discovered more than two decades ago, and since then GPCR-RAMP interactions and their functional consequences on receptor trafficking and ligand selectivity have been documented for several secretin (class B) GPCRs, most notably the calcitonin receptor-like receptor. Recent bioinformatics and multiplexed experimental studies suggest that GPCR-RAMP interactions might be much more widespread than previously anticipated. Recently, cryo-electron microscopy has provided high-resolution structures of GPCR-RAMP-ligand complexes, and drugs have been developed that target GPCR-RAMP complexes. In this review, we provide a summary of recent advances in techniques that allow the discovery of GPCR-RAMP interactions and their functional consequences and highlight prospects for future advances. We also provide an up-to-date list of reported GPCR-RAMP interactions based on a review of the current literature. SIGNIFICANCE STATEMENT: Receptor activity-modifying proteins (RAMPs) have emerged as modulators of many aspects of G protein-coupled receptor (GPCR)biology and pharmacology. The application of new methodologies to study membrane protein-protein interactions suggests that RAMPs interact with many more GPCRs than had been previously known. These findings, especially when combined with structural studies of membrane protein complexes, have significant implications for advancing GPCR-targeted drug discovery and the understanding of GPCR pharmacology, biology, and regulation.

Establishment of a High Content Image Platform to Measure NF-κB Nuclear Translocation in LPS-Induced RAW264.7 Macrophages for Screening Anti-inflammatory Drug Candidates

BACKGROUND

High content image (HCI), an automatic imaging and analysis system, provides a fast drug screening method by detecting the subcellular distribution of protein in intact cells.

OBJECTIVE

This study established the first standardized HCI platform for lipopolysaccharide (LPS)-induced RAW264.7 macrophages to screen anti-inflammatory compounds by measuring nuclear factor-κB (NF-κB) nuclear translocation.

METHOD

The influence of the cell passages, cell density, LPS induction time and concentration, antibody dilution, serum, dimethyl sulfoxide and analysis parameters on NF-κB nuclear translocation and HCI data quality was optimized. The BAY-11-7085, the positive control for inhibiting NF-κB and Western blot assay were separately employed to verify the stability and reliability of the platform. Lastly, the effect of BHA on NO release, iNOS expression, IL-1β, IL-6, and TNF-α mRNA in LPS-induced RAW264.7 cells was detected.

RESULTS

The optimal conditions for measuring NF-κB translocation in LPS-induced RAW264.7 cells by HCI were established. Cells that do not exceed 22 passages were seeded at a density of 10 k cells/well and pretreated with compounds following 200 ng/mL LPS for 40 min. Parameters including nuclear area of 65 μm2, cell area of 80 μm2, collar of 0.9 μm and sensitivity of 25% were recommended for image segmentation algorithms in the analysis workstation. Benzoylhypaconine from aconite was screened for the first time as an anti-inflammatory candidate by the established HCI platform. The inhibitory effect of benzoylhypaconine on NF-κB translocation was verified by Western blot. Furthermore, benzoylhypaconine reduced the release of NO, inhibited the expression of iNOS, decreased the mRNA levels of IL-1β, IL-6, and TNF-α.

CONCLUSION

The established HCI platform could be applied to screen anti-inflammatory compounds by measuring the NF-κB nuclear translocation in LPS-induced RAW264.7 cells.