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Opioid receptors (ORs) are classified among the oldest and best investigated drug targets due to their fundamental role in the treatment of pain and related disorders. ORs are divided in three conventional subtypes (μ, κ, δ) and the non‐classical nocicepetin receptor. All ORs are family A G protein‐coupled receptors (GPCRs), and are located on the cell surface. Modern biophysical methods use light to investigate physiological processes at organismal, cellular and subcellular level. Many of these methods rely on fluorescent ligands, thus highlighting their importance. This review addresses the advancements in the development of opioid fluorescent ligands and their use in biological, pharmacological and imaging applications.
Bioimages frequently exhibit low signal-to-noise ratios due to experimental conditions, specimen characteristics, and imaging trade-offs. Reliable segmentation of such ambiguous images is difficult and laborious. Here we introduce deepflash2, a deep learning-enabled segmentation tool for bioimage analysis. The tool addresses typical challenges that may arise during the training, evaluation, and application of deep learning models on ambiguous data. The tool’s training and evaluation pipeline uses multiple expert annotations and deep model ensembles to achieve accurate results. The application pipeline supports various use-cases for expert annotations and includes a quality assurance mechanism in the form of uncertainty measures. Benchmarked against other tools, deepflash2 offers both high predictive accuracy and efficient computational resource usage. The tool is built upon established deep learning libraries and enables sharing of trained model ensembles with the research community. deepflash2 aims to simplify the integration of deep learning into bioimage analysis projects while improving accuracy and reliability.
Sphingolipids, including ceramides, are a diverse group of structurally related lipids composed of a sphingoid base backbone coupled to a fatty acid side chain and modified terminal hydroxyl group. Recently, it has been shown that sphingolipids show antimicrobial activity against a broad range of pathogenic microorganisms. The antimicrobial mechanism, however, remains so far elusive. Here, we introduce 'click-AT-CLEM', a labeling technique for correlated light and electron microscopy (CLEM) based on the super-resolution array tomography (srAT) approach and bio-orthogonal click chemistry for imaging of azido-tagged sphingolipids to directly visualize their interaction with the model Gram-negative bacterium Neisseria meningitidis at subcellular level. We observed ultrastructural damage of bacteria and disruption of the bacterial outer membrane induced by two azido-modified sphingolipids by scanning electron microscopy and transmission electron microscopy. Click-AT-CLEM imaging and mass spectrometry clearly revealed efficient incorporation of azido-tagged sphingolipids into the outer membrane of Gram-negative bacteria as underlying cause of their antimicrobial activity.
The synaptic cleft is of central importance for synaptic transmission, neuronal plasticity and memory and thus well studied in neurobiology. To target proteins of interest with high specificity and strong signal to noise conventional immunohistochemistry relies on the use of fluorescently labeled antibodies. However, investigations on synaptic receptors remain challenging due to the defined size of the synaptic cleft of ~20 nm between opposing pre- and postsynaptic membranes. At this limited space, antibodies bear unwanted side effects such as crosslinking, accessibility issues and a considerable linkage error between fluorophore and target of ~10 nm. With recent single molecule localization microscopy (SMLM) methods enabling localization precisions of a few nanometers, the demand for labeling approaches with minimal linkage error and reliable recognition of the target molecules rises.
Within the scope of this work, different labeling techniques for super-resolution fluorescence microscopy were utilized allowing site-specific labeling of a single amino acid in synaptic proteins like kainate receptors (KARs), transmembrane α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor regulatory proteins (TARPs), γ-aminobutyric acid type A receptors (GABA-ARs) and neuroligin 2 (NL2). The method exploits the incorporation of unnatural amino acids (uAAs) in the protein of interest using genetic code expansion (GCE) via amber suppression technology and subsequent labeling with tetrazine functionalized fluorophores. Implementing this technique, hard-to-target proteins such as KARs, TARPs and GABA-ARs could be labeled successfully, which could only be imaged insufficiently with conventional labeling approaches. Furthermore, functional studies involving electrophysiological characterization, as well as FRAP and FRET experiments validated that incorporation of uAAs maintains the native character of the targeted proteins. Next, the method was transferred into primary hippocampal neurons and in combination with super-resolution microscopy it was possible to resolve the nanoscale organization of γ2 and γ8 TARPs. Cluster analysis of dSTORM localization data verified synaptic accumulation of γ2, while γ8 was homogenously distributed along the neuron. Additionally, GCE and bioorthogonal labeling allowed visualization of clickable GABA-A receptors located at postsynaptic compartments in dissociated hippocampal neurons. Moreover, saturation experiments and FRET imaging of clickable multimeric receptors revealed successful binding of multiple tetrazine functionalized fluorophores to uAA-modified dimeric GABA-AR α2 subunits in close proximity (~5 nm). Further utilization of tetrazine-dyes via super-resolution microscopy methods such as dSTORM and click-ExM will provide insights to subunit arrangement in receptors in the future.
This work investigated the nanoscale organization of synaptic proteins with minimal linkage error enabling new insights into receptor assembly, trafficking and recycling, as well as protein-protein interactions at synapses. Ultimately, bioorthogonal labeling can help to understand pathologies such as the limbic encephalitis associated with GABA-AR autoantibodies and is already in application for cancer therapies.