Since 1991, the NAD(P)H-aided conversion of resazurin to fluorescent resorufin has been widely used to measure viability based on the metabolic activity in mammalian cell culture and primary cells. However, different research groups have used divergent assay protocols, scarcely reporting the systematic optimization of the assay. Here, we perform extensive studies to fine-tune the experimental protocols utilizing resazurin-based viability sensing. Specifically, we focus on (A) optimization of the assay dynamic range in individual cell lines for the correct measurement of cytostatic and cytotoxic properties of the compounds; (B) dependence of the dynamic range on the physical quantity detected (fluorescence intensity versus change of absorbance spectrum); (C) calibration of the assay for the correct interpretation of data measured in hypoxic conditions; and (D) possibilities for combining the resazurin assay with other methods including measurement of necrosis and apoptosis. We also demonstrate the enhanced precision and flexibility of the resazurin-based assay regarding the readout format and kinetic measurement mode as compared to the widely used analogous assay which utilizes tetrazolium dye MTT. The discussed assay optimization guidelines provide useful instructions for the beginners in the field and for the experienced scientists exploring new ways for measurement of cellular viability using resazurin.

We implemented an assay combining fluorescence and bright‐field microscopy to measure ligand binding to dopamine D3 receptors in live mammalian cells. For fluorescence intensity quantification from microscopy images, we developed a machine learning‐based user‐friendly software membrane tools. For the experiments, a novel fluorescent ligand NAPS‐Cy3B was synthesized. The subnanomolar affinity of NAPS‐Cy3B makes it a suitable ligand for the characterization of D3 receptors and its ligands in live HEK293 cells.

The recent crystallization of the neuropeptide Y Y 1 receptor (Y 1 R) in complex with the argininamide-type Y 1 R selective antagonist UR-MK299 (2) opened up a new approach toward structure-based design of nonpeptidic Y 1 R ligands. We designed novel fluorescent probes showing excellent Y 1 R selectivity and, in contrast to previously described fluorescent Y 1 R ligands, considerably higher (∼100-fold) binding affinity. This was achieved through the attachment of different fluorescent dyes to the diphenylacetyl moiety in 2 via an amine-functionalized linker. The fluorescent ligands exhibited picomolar Y 1 R binding affinities (pK i values of 9.36−9.95) and proved to be Y 1 R antagonists, as validated in a Fura-2 calcium assay. The versatile applicability of the probes as tool compounds was demonstrated by flow cytometry-and fluorescence anisotropy-based Y 1 R binding studies (saturation and competition binding and association and dissociation kinetics) as well as by widefield and total internal reflection fluorescence (TIRF) microscopy of live tumor cells, revealing that fluorescence was mainly localized at the plasma membrane.

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Identifying nuclei is a standard first step when analysing cells in microscopy images. The traditional approach relies on signal from a DNA stain, or fluorescent transgene expression localised to the nucleus. However, imaging techniques that do not use fluorescence can also carry useful information. Here, we used brightfield and fluorescence images of fixed cells with fluorescently labelled DNA, and confirmed that three convolutional neural network architectures can be adapted to segment nuclei from the brightfield channel, relying on fluorescence signal to extract the ground truth for training. We found that U-Net achieved the best overall performance, Mask R-CNN provided an additional benefit of instance segmentation, and that DeepCell proved too slow for practical application. We trained the U-Net architecture on over 200 dataset variations, established that accurate segmentation is possible using as few as 16 training images, and that models trained on images from similar cell lines can extrapolate well. Acquiring data from multiple focal planes further helps distinguish nuclei in the samples. Overall, our work helps to liberate a fluorescence channel reserved for nuclear staining, thus providing more information from the specimen, and reducing reagents and time required for preparing imaging experiments.