Physical biology of GPCR signalling dynamics inferred from fluorescence spectroscopy and imaging

A Reliable System for Quantitative G-Protein Activation Imaging in Cancer Cells

Fluorescence resonance energy transfer (FRET) biosensors have proven to be an indispensable tool in cell biology and, more specifically, in the study of G-protein signalling. The best method of measuring the activation status or FRET state of a biosensor is often fluorescence lifetime imaging microscopy (FLIM), as it does away with many disadvantages inherent to fluorescence intensity-based methods and is easily quantitated. Despite the significant potential, there is a lack of reliable FLIM-FRET biosensors, and the data processing and analysis workflows reported previously face reproducibility challenges. Here, we established a system in live primary mouse pancreatic ductal adenocarcinoma cells, where we can detect the activation of an mNeonGreen-Gαi3-mCherry-Gγ2 biosensor through the lysophosphatidic acid receptor (LPAR) with 2-photon time-correlated single-photon counting (TCSPC) FLIM. This combination gave a superior signal to the commonly used mTurquoise2-mVenus G-protein biosensor. This system has potential as a platform for drug screening, or to answer basic cell biology questions in the field of G-protein signalling.

Dynamic in Situ Confinement Triggers Ligand-Free Neuropeptide Receptor Signaling

Membrane receptor clustering is fundamental to cell-cell communication; however, the physiological function of receptor clustering in cell signaling remains enigmatic. Here, we developed a dynamic platform to induce cluster formation of neuropeptide Y₂ hormone receptors (Y₂R) in situ by a chelator nanotool. The multivalent interaction enabled a dynamic exchange of histidine-tagged Y₂R within the clusters. Fast Y₂R enrichment in clustered areas triggered ligand-independent signaling as determined by an increase in cytosolic calcium and cell migration. Notably, the calcium and motility response to ligand-induced activation was amplified in preclustered cells, suggesting a key role of receptor clustering in sensitizing the dose response to lower ligand concentrations. Ligand-independent versus ligand-induced signaling differed in the binding of arrestin-3 as a downstream effector, which was recruited to the clusters only in the presence of the ligand. This approach allows in situ receptor clustering, raising the possibility to explore different receptor activation modalities.

Unraveling the hidden temporal range of fast β2-adrenergic receptor mobility by time-resolved fluorescence

G-protein-coupled receptors (GPCRs) are hypothesized to possess molecular mobility over a wide temporal range. Until now the temporal range has not been fully accessible due to the crucially limited temporal range of available methods. This in turn, may lead relevant dynamic constants to remain masked. Here, we expand this dynamic range by combining fluorescent techniques using a spot confocal setup. We decipher mobility constants of β2-adrenergic receptor over a wide time range (nanosecond to second). Particularly, a translational mobility (10 µm²/s), one order of magnitude faster than membrane associated lateral mobility that explains membrane protein turnover and suggests a wider picture of the GPCR availability on the plasma membrane. And a so far elusive rotational mobility (1-200 µs) which depicts a previously overlooked dynamic component that, despite all complexity, behaves largely as predicted by the Saffman-Delbrück model.

Allosteric Activation of SARS-CoV-2 RNA-Dependent RNA Polymerase by Remdesivir Triphosphate and Other Phosphorylated Nucleotides

The catalytic subunit of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA-dependent RNA polymerase (RdRp) Nsp12 has a unique nidovirus RdRp-associated nucleotidyltransferase (NiRAN) domain that transfers nucleoside monophosphates to the Nsp9 protein and the nascent RNA. The NiRAN and RdRp modules form a dynamic interface distant from their catalytic sites, and both activities are essential for viral replication. We report that codon-optimized (for the pause-free translation in bacterial cells) Nsp12 exists in an inactive state in which NiRAN-RdRp interactions are broken, whereas translation by slow ribosomes and incubation with accessory Nsp7/8 subunits or nucleoside triphosphates (NTPs) partially rescue RdRp activity. Our data show that adenosine and remdesivir triphosphates promote the synthesis of A-less RNAs, as does ppGpp, while amino acid substitutions at the NiRAN-RdRp interface augment activation, suggesting that ligand binding to the NiRAN catalytic site modulates RdRp activity. The existence of allosterically linked nucleotidyl transferase sites that utilize the same substrates has important implications for understanding the mechanism of SARS-CoV-2 replication and the design of its inhibitors.

Allosteric activation of SARS-CoV-2 RdRp by remdesivir triphosphate and other phosphorylated nucleotides

The catalytic subunit of SARS-CoV-2 RNA-dependent RNA polymerase (RdRp), Nsp12, has a unique NiRAN domain that transfers nucleoside monophosphates to the Nsp9 protein. The NiRAN and RdRp modules form a dynamic interface distant from their catalytic sites and both activities are essential for viral replication. We report that codon-optimized (for the pause-free translation) Nsp12 exists in inactive state in which NiRAN/RdRp interactions are broken, whereas translation by slow ribosomes and incubation with accessory Nsp7/8 subunits or NTPs partially rescue RdRp activity. Our data show that adenosine and remdesivir triphosphates promote synthesis of A-less RNAs, as does ppGpp, while amino acid substitutions at the NiRAN/RdRp interface augment activation, suggesting that ligand binding to the NiRAN catalytic site modulates RdRp activity. The existence of allosterically-linked nucleotidyl transferase sites that utilize the same substrates has important implications for understanding the mechanism of SARS-CoV-2 replication and design of its inhibitors.

HIGHLIGHTS

Codon-optimization of Nsp12 triggers misfolding and activity lossSlow translation, accessory Nsp7 and Nsp8 subunits, and NTPs rescue Nsp12Non-substrate nucleotides activate RNA chain synthesis, likely via NiRAN domainCrosstalk between two Nsp12 active sites that bind the same ligands.

Imaging of Genetically Encoded FRET-Based Biosensors to Detect GPCR Activity

A wealth of assays for screening GPCR activity have been developed. Biosensors that employ Förster Resonance Energy transfer (FRET) are specific and enable dynamic measurements. Moreover, FRET biosensors are ideally suited for the analysis of single living cells. The FRET biosensors described in this manuscript are entirely genetically encoded by plasmids. Here, protocols for employing FRET-based biosensors to detect G protein activity upon GPCR activation are reported. The protocols include details on the isolation of plasmids, transfection, generation of stable cell lines with the FRET biosensors, FRET ratio imaging, and data analysis.

VolcaNoseR is a web app for creating, exploring, labeling and sharing volcano plots

Comparative genome- and proteome-wide screens yield large amounts of data. To efficiently present such datasets and to simplify the identification of hits, the results are often presented in a type of scatterplot known as a volcano plot, which shows a measure of effect size versus a measure of significance. The data points with the largest effect size and a statistical significance beyond a user-defined threshold are considered as hits. Such hits are usually annotated in the plot by a label with their name. Volcano plots can represent ten thousands of data points, of which typically only a handful is annotated. The information of data that is not annotated is hardly or not accessible. To simplify access to the data and enable its re-use, we have developed an open source and online web tool with R/Shiny. The web app is named VolcaNoseR and it can be used to create, explore, label and share volcano plots (https://huygens.science.uva.nl/VolcaNoseR). When the data is stored in an online data repository, the web app can retrieve that data together with user-defined settings to generate a customized, interactive volcano plot. Users can interact with the data, adjust the plot and share their modified plot together with the underlying data. Therefore, VolcaNoseR increases the transparency and re-use of large comparative genome- and proteome-wide datasets.