High-Throughput Calcium Imaging Screen of Toxins' Function in Dissociated Sensory Neurons

Fluorescence-Based HTS Assays for Ion Channel Modulation in Drug Discovery Pipelines

Ion channels represent a druggable family of transmembrane pore-forming proteins with important (patho)physiological functions. While electrophysiological measurement (manual patch clamp) remains the only direct method for detection of ion currents, it is a labor-intensive technique. Although automated patch clamp instruments have become available to date, their high costs limit their use to large pharma companies or commercial screening facilities. Therefore, fluorescence-based assays are particularly important for initial screening of compound libraries. Despite their numerous disadvantages, they are highly amenable to high-throughput screening and in many cases, no sophisticated instrumentation or materials are required. These features predispose them for implementation in early phases of drug discovery pipelines (hit identification), even in an academic environment. This review summarizes the advantages and pitfalls of individual methodological approaches for identification of ion channel modulators employing fluorescent probes (i. e., membrane potential and ion flux assays) with emphasis on practical aspects of their adaptation to high-throughput format.

Elucidation of Medusozoan (Jellyfish) Venom Constituent Activities Using Constellation Pharmacology

Within the phylum Cnidaria, sea anemones (class Anthozoa) express a rich diversity of ion-channel peptide modulators with biomedical applications, but corollary discoveries from jellyfish (subphylum Medusozoa) are lacking. To bridge this gap, bioactivities of previously unexplored proteinaceous and small molecular weight (~15 kDa to 5 kDa) venom components were assessed in a mouse dorsal root ganglia (DRG) high-content calcium-imaging assay, known as constellation pharmacology. While the addition of crude venom led to nonspecific cell death and Fura-2 signal leakage due to pore-forming activity, purified small molecular weight fractions of venom demonstrated three main, concentration-dependent and reversible effects on defined heterogeneous cell types found in the primary cultures of mouse DRG. These three phenotypic responses are herein referred to as phenotype A, B and C: excitatory amplification (A) or inhibition (B) of KCl-induced calcium signals, and test compound-induced disturbances to baseline calcium levels (C). Most notably, certain Alatina alata venom fractions showed phenotype A effects in all DRG neurons; Physalia physalis and Chironex fleckeri fractions predominantly showed phenotype B effects in small- and medium-diameter neurons. Finally, specific Physalia physalis and Alatina alata venom components induced direct excitatory responses (phenotype C) in glial cells. These findings demonstrate a diversity of neuroactive compounds in jellyfish venom potentially targeting a constellation of ion channels and ligand-gated receptors with broad physiological implications.

NeuriteNet: A convolutional neural network for assessing morphological parameters of neurite growth

BACKGROUND

During development or regeneration, neurons extend processes (i.e., neurites) via mechanisms that can be readily analyzed in culture. However, defining the impact of a drug or genetic manipulation on such mechanisms can be challenging due to the complex arborization and heterogeneous patterns of neurite growth in vitro. New Method: NeuriteNet is a Convolutional Neural Network (CNN) sorting model that uses a novel adaptation of the XRAI saliency map overlay, which is a region-based attribution method. NeuriteNet compares neuronal populations based on differences in neurite growth patterns, sorts them into respective groups, and overlays a saliency map indicating which areas differentiated the image for the sorting procedure.

RESULTS

In this study, we demonstrate that NeuriteNet effectively sorts images corresponding to dissociated neurons into control and treatment groups according to known morphological differences. Furthermore, the saliency map overlay highlights the distinguishing features of the neuron when sorting the images into treatment groups. NeuriteNet also identifies novel morphological differences in neurons cultured from control and genetically modified mouse strains. Comparison with Existing Methods: Unlike other neurite analysis platforms, NeuriteNet does not require manual manipulations, such as segmentation of neurites prior to analysis, and is more accurate than experienced researchers for categorizing neurons according to their pattern of neurite growth.

CONCLUSIONS

NeuriteNet can be used to effectively screen for morphological differences in a heterogeneous group of neurons and to provide feedback on the key features distinguishing those groups via the saliency map overlay.