Intracellular Calcium Responses Encode Action Potential Firing in Spinal Cord Lamina I Neurons.

Maladaptive plasticity of neurons in lamina I of the spinal cord is a lynchpin for the development of chronic pain, and is critically dependent on intracellular calcium signaling. However, the relationship between neuronal activity and intracellular calcium in these neurons is unknown. Here we combined two-photon calcium imaging with whole-cell electrophysiology to determine how action potential firing drives calcium responses within subcellular compartments of male rat spinal cord lamina I neurons. We found that single action potentials generated at the soma increase calcium concentration in the somatic cytosol and nucleus, and these calcium responses invade dendrites and dendritic spines by active backpropagation. Calcium responses in each compartment were dependent on voltage-gated calcium channels, and somatic and nuclear calcium responses were amplified by release of calcium from ryanodine-sensitive intracellular stores. Grouping single action potential-evoked calcium responses by neuron type demonstrated their presence in all defined types, as well as a high degree of similarity in calcium responses between neuron types. With bursts of action potentials, we found that calcium responses have the capacity to encode action potential frequency and number in all compartments, with action potential number being preferentially encoded. Together, these findings indicate that intracellular calcium serves as a readout of neuronal activity within lamina I neurons, providing a unifying mechanism through which activity may regulate plasticity, including that seen in chronic pain.SIGNIFICANCE STATEMENT Despite their critical role in both acute pain sensation and chronic pain, little is known of the fundamental physiology of spinal cord lamina I neurons. This is especially the case with respect to calcium dynamics within these neurons, which could regulate maladaptive plasticity observed in chronic pain. By combining two-photon calcium imaging and patch-clamp electrophysiological recordings from lamina I neurons, we found that action potential firing induces calcium responses within the somatic cytosol, nucleus, dendrites, and dendritic spines of lamina I neurons. Our findings demonstrate the presence of actively backpropagating action potentials, shifting our understanding of how these neurons process information, such that calcium provides a mechanism for lamina I neurons to track their own activity.

Quantification of stimulus-evoked tactile allodynia in free moving mice by the chainmail sensitivity test.

Chronic pain occurs at epidemic levels throughout the population. Hypersensitivity to touch, is a cardinal symptom of chronic pain. Despite dedicated research for over a century, quantifying this hypersensitivity has remained impossible at scale. To address these issues, we developed the Chainmail Sensitivity Test (CST). Our results show that control mice spend significantly more time on the chainmail portion of the device than mice subject to neuropathy. Treatment with gabapentin abolishes this difference. CST-derived data correlate well with von Frey measurements and quantify hypersensitivity due to inflammation. Our study demonstrates the potential of the CST as a standardized tool for assessing mechanical hypersensitivity in mice with minimal operator input.

Downregulation of the silent potassium channel Kv8.1 increases motor neuron vulnerability in amyotrophic lateral sclerosis.

While voltage-gated potassium channels have critical roles in controlling neuronal excitability, they also have non-ion-conducting functions. Kv8.1, encoded by the KCNV1 gene, is a 'silent' ion channel subunit whose biological role is complex since Kv8.1 subunits do not form functional homotetramers but assemble with Kv2 to modify its ion channel properties. We profiled changes in ion channel expression in amyotrophic lateral sclerosis patient-derived motor neurons carrying a superoxide dismutase 1(A4V) mutation to identify what drives their hyperexcitability. A major change identified was a substantial reduction of KCNV1/Kv8.1 expression, which was also observed in patient-derived neurons with C9orf72 expansion. We then studied the effect of reducing KCNV1/Kv8.1 expression in healthy motor neurons and found it did not change neuronal firing but increased vulnerability to cell death. A transcriptomic analysis revealed dysregulated metabolism and lipid/protein transport pathways in KCNV1/Kv8.1-deficient motor neurons. The increased neuronal vulnerability produced by the loss of KCNV1/Kv8.1 was rescued by knocking down Kv2.2, suggesting a potential Kv2.2-dependent downstream mechanism in cell death. Our study reveals, therefore, unsuspected and distinct roles of Kv8.1 and Kv2.2 in amyotrophic lateral sclerosis-related neurodegeneration.

A multiparametric activity profiling platform for neuron disease phenotyping and drug screening.

Patient stem cell-derived models enable imaging of complex disease phenotypes and the development of scalable drug discovery platforms. Current preclinical methods for assessing cellular activity do not, however, capture the full intricacies of disease-induced disturbances and instead typically focus on a single parameter, which impairs both the understanding of disease and the discovery of effective therapeutics. Here, we describe a cloud-based image processing and analysis platform that captures the intricate activity profile revealed by GCaMP fluorescence recordings of intracellular calcium changes and enables the discovery of molecules that correct 153 parameters that define the amyotrophic lateral sclerosis motor neuron disease phenotype. In a high-throughput screen, we identified compounds that revert the multiparametric disease profile to that found in healthy cells, a novel and robust measure of therapeutic potential quite distinct from unidimensional screening. This platform can guide the development of therapeutics that counteract the multifaceted pathological features of diseased cellular activity.

Automated preclinical detection of mechanical pain hypersensitivity and analgesia.

ABSTRACT: The lack of sensitive and robust behavioral assessments of pain in preclinical models has been a major limitation for both pain research and the development of novel analgesics. Here, we demonstrate a novel data acquisition and analysis platform that provides automated, quantitative, and objective measures of naturalistic rodent behavior in an observer-independent and unbiased fashion. The technology records freely behaving mice, in the dark, over extended periods for continuous acquisition of 2 parallel video data streams: (1) near-infrared frustrated total internal reflection for detecting the degree, force, and timing of surface contact and (2) simultaneous ongoing video graphing of whole-body pose. Using machine vision and machine learning, we automatically extract and quantify behavioral features from these data to reveal moment-by-moment changes that capture the internal pain state of rodents in multiple pain models. We show that these voluntary pain-related behaviors are reversible by analgesics and that analgesia can be automatically and objectively differentiated from sedation. Finally, we used this approach to generate a paw luminance ratio measure that is sensitive in capturing dynamic mechanical hypersensitivity over a period and scalable for high-throughput preclinical analgesic efficacy assessment.

Up-Down Reader: An Open Source Program for Efficiently Processing 50% von Frey Thresholds.

Most pathological pain conditions in patients and rodent pain models result in marked alterations in mechanosensation and the gold standard way to measure this is by use of von Frey fibers. These graded monofilaments are used to gauge the level of stimulus-evoked sensitivity present in the affected dermal region. One of the most popular methods used to determine von Frey thresholds is the up-down testing paradigm introduced by Dixon for patients in 1980 and by Chapman and colleagues for rodents in 1994. Although the up-down method is very accurate, leading to its widespread use, defining the 50% threshold from primary data is complex and requires a relatively time-consuming analysis step. We developed a computer program, the Up-Down Reader (UDReader), that can locate and recognize handwritten von Frey assessments from a scanned PDF document and translate these measurements into 50% pain thresholds. Automating the process of obtaining the 50% threshold values negates the need for reference tables or Microsoft Excel formulae and eliminates the chance of a manual calculation error. Our simple and straightforward method is designed to save research time while improving data collection accuracy and is freely available at https://sourceforge.net/projects/updownreader/ or in supplementary files attached to this manuscript.