Automated preclinical detection of mechanical pain hypersensitivity and analgesia

Lipid nanoparticle delivery of siRNA to dorsal root ganglion neurons to treat pain

Sensory neurons within the dorsal root ganglion (DRG) are the primary trigger of pain, relaying activity about noxious stimuli from the periphery to the central nervous system; however, targeting DRG neurons for pain management has remained a clinical challenge. Here, we demonstrate the use of lipid nanoparticles (LNPs) for effective intrathecal delivery of small interfering RNA (siRNA) to DRG neurons, achieving potent silencing of the transient receptor potential vanilloid 1 (TRPV1) ion channel that is predominantly expressed in nociceptor sensory neurons. This leads to a reversible interruption of heat-, capsaicin-, and inflammation-induced nociceptive conduction, as observed by behavioral outputs. Our work provides a proof-of-concept for intrathecal siRNA therapy as a novel and selective analgesic modality.

Harnessing the potential of human induced pluripotent stem cells, functional assays and machine learning for neurodevelopmental disorders

Neurodevelopmental disorders (NDDs) affect 4.7% of the global population and are associated with delays in brain development and a spectrum of impairments that can lead to lifelong disability and even mortality. Identification of biomarkers for accurate diagnosis and medications for effective treatment are lacking, in part due to the historical use of preclinical model systems that do not translate well to the clinic for neurological disorders, such as rodents and heterologous cell lines. Human-induced pluripotent stem cells (hiPSCs) are a promising in vitro system for modeling NDDs, providing opportunities to understand mechanisms driving NDDs in human neurons. Functional assays, including patch clamping, multielectrode array, and imaging-based assays, are popular tools employed with hiPSC disease models for disease investigation. Recent progress in machine learning (ML) algorithms also presents unprecedented opportunities to advance the NDD research process. In this review, we compare two-dimensional and three-dimensional hiPSC formats for disease modeling, discuss the applications of functional assays, and offer insights on incorporating ML into hiPSC-based NDD research and drug screening.

ARBEL: A Machine Learning Tool with Light-Based Image Analysis for Automatic Classification of 3D Pain Behaviors

A detailed analysis of pain-related behaviors in rodents is essential for exploring both the mechanisms of pain and evaluating analgesic efficacy. With the advancement of pose-estimation tools, automatic single-camera video animal behavior pipelines are growing and integrating rapidly into quantitative behavioral research. However, current existing algorithms do not consider an animal's body-part contact intensity with- and distance from- the surface, a critical nuance for measuring certain pain-related responses like paw withdrawals ('flinching') with high accuracy and interpretability. Quantifying these bouts demands a high degree of attention to body part movement and currently relies on laborious and subjective human visual assessment. Here, we introduce a supervised machine learning algorithm, ARBEL: Automated Recognition of Behavior Enhanced with Light, that utilizes a combination of pose estimation together with a novel light-based analysis of body part pressure and distance from the surface, to automatically score pain-related behaviors in freely moving mice in three dimensions. We show the utility and accuracy of this algorithm for capturing a range of pain-related behavioral bouts using a bottom-up animal behavior platform, and its application for robust drug-screening. It allows for rapid objective pain behavior scoring over extended periods with high precision. This open-source algorithm is adaptable for detecting diverse behaviors across species and experimental platforms.

It all began in Issaquah 50 years ago

ABSTRACT

"Somehow scientists still pursue the same questions, if now on higher levels of theoretical abstraction rooted in deeper layers of empirical evidence… To paraphrase an old philosophy joke, science is more like it is today than it has ever been. In other words, science remains as challenging as ever to human inquiry. And the need to communicate its progress… remains as essential now as then." - Tom Siegfried, Science News 2021In fact, essential questions about pain have not changed since IASP's creation in Issaquah: what causes it and how can we treat it? Are we any closer to answering these questions, or have we just widened the gap between bench and bedside? The technology used to answer questions about pain mechanisms has certainly changed, whether the focus is on sensory neurons, spinal cord circuitry, descending controls or cortical pain processing. In this paper, we will describe how transgenics, transcriptomics, optogenetics, calcium imaging, fMRI, neuroimmunology and in silico drug development have transformed the way we examine the complexity of pain processing. But does it all, as our founders hoped, help people with pain? Are voltage-gated Na channels the new holy grail for analgesic development, is there a pain biomarker, can we completely replace opioids, will proteomic analyses identify novel targets, is there a "pain matrix," and can it be targeted? Do the answers lie in our tangible discoveries, or in the seemingly intangible? Our founders could barely imagine what we know now, yet their questions remain.

Discordance between preclinical and clinical testing of NaV1.7-selective inhibitors for pain

ABSTRACT

The voltage-gated sodium channel NaV1.7 plays an important role in pain processing according to genetic data. Those data made NaV1.7 a popular drug target, especially since its relatively selective expression in nociceptors promised pain relief without the adverse effects associated with broader sodium channel blockade. Despite encouraging preclinical data in rodents, NaV1.7-selective inhibitors have not yet proven effective in clinical trials. Discrepancies between preclinical and clinical results should raise alarms. We reviewed preclinical and clinical reports on the analgesic efficacy of NaV1.7-selective inhibitors and found critical differences in several factors. Putting aside species differences, most preclinical studies tested young male rodents with limited genetic variability, inconsistent with the clinical population. Inflammatory pain was the most common preclinical chronic pain model whereas nearly all clinical trials focused on neuropathic pain despite some evidence suggesting NaV1.7 channels are not essential for neuropathic pain. Preclinical studies almost exclusively measured evoked pain whereas most clinical trials assessed average pain intensity without distinguishing between evoked and spontaneous pain. Nearly all preclinical studies gave a single dose of drug unlike the repeat dosing used clinically, thus precluding preclinical data from demonstrating whether tolerance or other slow processes occur. In summary, preclinical testing of NaV1.7-selective inhibitors aligned poorly with clinical testing. Beyond issues that have already garnered widespread attention in the pain literature, our results highlight the treatment regimen and choice of pain model as areas for improvement.

Nociceptor-immune interactomes reveal insult-specific immune signatures of pain

Inflammatory pain results from the heightened sensitivity and reduced threshold of nociceptor sensory neurons due to exposure to inflammatory mediators. However, the cellular and transcriptional diversity of immune cell and sensory neuron types makes it challenging to decipher the immune mechanisms underlying pain. Here we used single-cell transcriptomics to determine the immune gene signatures associated with pain development in three skin inflammatory pain models in mice: zymosan injection, skin incision and ultraviolet burn. We found that macrophage and neutrophil recruitment closely mirrored the kinetics of pain development and identified cell-type-specific transcriptional programs associated with pain and its resolution. Using a comprehensive list of potential interactions mediated by receptors, ligands, ion channels and metabolites to generate injury-specific neuroimmune interactomes, we also uncovered that thrombospondin-1 upregulated by immune cells upon injury inhibited nociceptor sensitization. This study lays the groundwork for identifying the neuroimmune axes that modulate pain in diverse disease contexts.

Deep sequencing of Phox2a nuclei reveals five classes of anterolateral system neurons

The anterolateral system (ALS) is a major ascending pathway from the spinal cord that projects to multiple brain areas and underlies the perception of pain, itch, and skin temperature. Despite its importance, our understanding of this system has been hampered by the considerable functional and molecular diversity of its constituent cells. Here, we use fluorescence-activated cell sorting to isolate ALS neurons belonging to the Phox2a-lineage for single-nucleus RNA sequencing. We reveal five distinct clusters of ALS neurons (ALS1-5) and document their laminar distribution in the spinal cord using in situ hybridization. We identify three clusters of neurons located predominantly in laminae I-III of the dorsal horn (ALS1-3) and two clusters with cell bodies located in deeper laminae (ALS4 and ALS5). Our findings reveal the transcriptional logic that underlies ALS neuronal diversity in the adult mouse and uncover the molecular identity of two previously identified classes of projection neurons. We also show that these molecular signatures can be used to target groups of ALS neurons using retrograde viral tracing. Overall, our findings provide a valuable resource for studying somatosensory biology and targeting subclasses of ALS neurons.

Immune drivers of physiological and pathological pain

Physiological pain serves as a warning of exposure to danger and prompts us to withdraw from noxious stimuli to prevent tissue damage. Pain can also alert us of an infection or organ dysfunction and aids in locating such malfunction. However, there are instances where pain is purely pathological, such as unresolved pain following an inflammation or injury to the nervous system, and this can be debilitating and persistent. We now appreciate that immune cells are integral to both physiological and pathological pain, and that pain, in consequence, is not strictly a neuronal phenomenon. Here, we discuss recent findings on how immune cells in the skin, nerve, dorsal root ganglia, and spinal cord interact with somatosensory neurons to mediate pain. We also discuss how both innate and adaptive immune cells, by releasing various ligands and mediators, contribute to the initiation, modulation, persistence, or resolution of various modalities of pain. Finally, we propose that the neuroimmune axis is an attractive target for pain treatment, but the challenges in objectively quantifying pain preclinically, variable sex differences in pain presentation, as well as adverse outcomes associated with immune system modulation, all need to be considered in the development of immunotherapies against pain.

Mimicking opioid analgesia in cortical pain circuits

The anterior cingulate cortex plays a pivotal role in the cognitive and affective aspects of pain perception. Both endogenous and exogenous opioid signaling within the cingulate mitigate cortical nociception, reducing pain unpleasantness. However, the specific functional and molecular identities of cells mediating opioid analgesia in the cingulate remain elusive. Given the complexity of pain as a sensory and emotional experience, and the richness of ethological pain-related behaviors, we developed a standardized, deep-learning platform for deconstructing the behavior dynamics associated with the affective component of pain in mice-LUPE (Light aUtomated Pain Evaluator). LUPE removes human bias in behavior quantification and accelerated analysis from weeks to hours, which we leveraged to discover that morphine altered attentional and motivational pain behaviors akin to affective analgesia in humans. Through activity-dependent genetics and single-nuclei RNA sequencing, we identified specific ensembles of nociceptive cingulate neuron-types expressing mu-opioid receptors. Tuning receptor expression in these cells bidirectionally modulated morphine analgesia. Moreover, we employed a synthetic opioid receptor promoter-driven approach for cell-type specific optical and chemical genetic viral therapies to mimic morphine's pain-relieving effects in the cingulate, without reinforcement. This approach offers a novel strategy for precision pain management by targeting a key nociceptive cortical circuit with on-demand, non-addictive, and effective analgesia.

Current understanding of the molecular mechanisms of chemotherapy-induced peripheral neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is the most common off-target adverse effects caused by various chemotherapeutic agents, such as cisplatin, oxaliplatin, paclitaxel, vincristine and bortezomib. CIPN is characterized by a substantial loss of primary afferent sensory axonal fibers leading to sensory disturbances in patients. An estimated of 19-85% of patients developed CIPN during the course of chemotherapy. The lack of preventive measures and limited treatment options often require a dose reduction or even early termination of life-saving chemotherapy, impacting treatment efficacy and patient survival. In this Review, we summarized the current understanding on the pathogenesis of CIPN. One prominent change induced by chemotherapeutic agents involves the disruption of neuronal cytoskeletal architecture and axonal transport dynamics largely influenced by the interference of microtubule stability in peripheral neurons. Due to an ineffective blood-nerve barrier in our peripheral nervous system, exposure to some chemotherapeutic agents causes mitochondrial swelling in peripheral nerves, which lead to the opening of mitochondrial permeability transition pore and cytochrome c release resulting in degeneration of primary afferent sensory fibers. The exacerbated nociceptive signaling and pain transmission in CIPN patients is often linked the increased neuronal excitability largely due to the elevated expression of various ion channels in the dorsal root ganglion neurons. Another important contributing factor of CIPN is the neuroinflammation caused by an increased infiltration of immune cells and production of inflammatory cytokines. In the central nervous system, chemotherapeutic agents also induce neuronal hyperexcitability in the spinal dorsal horn and anterior cingulate cortex leading to the development of central sensitization that causes CIPN. Emerging evidence suggests that the change in the composition and diversity of gut microbiota (dysbiosis) could have direct impact on the development and progression of CIPN. Collectively, all these aspects contribute to the pathogenesis of CIPN. Recent advances in RNA-sequencing offer solid platform for in silico drug screening which enable the identification of novel therapeutic agents or repurpose existing drugs to alleviate CIPN, holding immense promises for enhancing the quality of life for cancer patients who undergo chemotherapy and improve their overall treatment outcomes.

Digitalization of toxicology: improving preclinical to clinical translation

Though the portfolio of medicines that are extending and improving the lives of patients continues to grow, drug discovery and development remains a challenging business on its best day. Safety liabilities are a significant contributor to development attrition where the costliest liabilities to both drug developers and patients emerge in late development or post-marketing. Animal studies are an important and influential contributor to the current drug discovery and development paradigm intending to provide evidence that a novel drug candidate can be used safely and effectively in human volunteers and patients. However, translational gaps-such as toxicity in patients not predicted by animal studies-have prompted efforts to improve their effectiveness, especially in safety assessment. More holistic monitoring and "digitalization" of animal studies has the potential to enrich study outcomes leading to datasets that are more computationally accessible, translationally relevant, replicable, and technically efficient. Continuous monitoring of animal behavior and physiology enables longitudinal assessment of drug effects, detection of effects during the animal's sleep and wake cycles and the opportunity to detect health or welfare events earlier. Automated measures can also mitigate human biases and reduce subjectivity. Reinventing a conservative, standardized, and traditional paradigm like drug safety assessment requires the collaboration and contributions of a broad and multi-disciplinary stakeholder group. In this perspective, we review the current state of the field and discuss opportunities to improve current approaches by more fully leveraging the power of sensor technologies, artificial intelligence (AI), and animal behavior in a home cage environment.

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.

Reproducible and fully automated testing of nocifensive behavior in mice

Pain in rodents is often inferred from their withdrawal from noxious stimulation. Threshold stimulus intensity or response latency is used to quantify pain sensitivity. This usually involves applying stimuli by hand and measuring responses by eye, which limits reproducibility and throughput. We describe a device that standardizes and automates pain testing by providing computer-controlled aiming, stimulation, and response measurement. Optogenetic and thermal stimuli are applied using blue and infrared light, respectively. Precise mechanical stimulation is also demonstrated. Reflectance of red light is used to measure paw withdrawal with millisecond precision. We show that consistent stimulus delivery is crucial for resolving stimulus-dependent variations in withdrawal and for testing with sustained stimuli. Moreover, substage video reveals "spontaneous" behaviors for consideration alongside withdrawal metrics to better assess the pain experience. The entire process was automated using machine learning. RAMalgo (reproducible automated multimodal algometry) improves the standardization, comprehensiveness, and throughput of preclinical pain testing.

A novel animal model of neuropathic corneal pain-the ciliary nerve constriction model

Introduction

Neuropathic pain arises as a result of peripheral nerve injury or altered pain processing within the central nervous system. When this phenomenon affects the cornea, it is referred to as neuropathic corneal pain (NCP), resulting in pain, hyperalgesia, burning, and photoallodynia, severely affecting patients' quality of life. To date there is no suitable animal model for the study of NCP. Herein, we developed an NCP model by constriction of the long ciliary nerves innervating the eye.

Methods

Mice underwent ciliary nerve constriction (CNC) or sham procedures. Safety was determined by corneal fluorescein staining to assess ocular surface damage, whereas Cochet-Bonnet esthesiometry and confocal microscopy assessed the function and structure of corneal nerves, respectively. Efficacy was assessed by paw wipe responses within 30 seconds of applying hyperosmolar (5M) saline at Days 3, 7, 10, and 14 post-constriction. Additionally, behavior was assessed in an open field test (OFT) at Days 7, 14, and 21.

Results

CNC resulted in significantly increased response to hyperosmolar saline between groups (p < 0.0001), demonstrating hyperalgesia and induction of neuropathic pain. Further, animals that underwent CNC had increased anxiety-like behavior in an open field test compared to controls at the 14- and 21-Day time-points (p < 0.05). In contrast, CNC did not result in increased corneal fluorescein staining or decreased sensation as compared to sham controls (p > 0.05). Additionally, confocal microscopy of corneal whole-mounts revealed that constriction resulted in only a slight reduction in corneal nerve density (p < 0.05), compared to naïve and sham groups.

Discussion

The CNC model induces a pure NCP phenotype and may be a useful model for the study of NCP, recapitulating features of NCP, including hyperalgesia in the absence of ocular surface damage, and anxiety-like behavior.

Deep sequencing of Phox2a nuclei reveals five classes of anterolateral system neurons

The anterolateral system (ALS) is a major ascending pathway from the spinal cord that projects to multiple brain areas and underlies the perception of pain, itch and skin temperature. Despite its importance, our understanding of this system has been hampered by the considerable functional and molecular diversity of its constituent cells. Here we use fluorescence-activated cell sorting to isolate ALS neurons belonging to the Phox2a-lineage for single-nucleus RNA sequencing. We reveal five distinct clusters of ALS neurons (ALS1-5) and document their laminar distribution in the spinal cord using in situ hybridization. We identify 3 clusters of neurons located predominantly in laminae I-III of the dorsal horn (ALS1-3) and two clusters with cell bodies located in deeper laminae (ALS4 & ALS5). Our findings reveal the transcriptional logic that underlies ALS neuronal diversity in the adult mouse and uncover the molecular identity of two previously identified classes of projection neurons. We also show that these molecular signatures can be used to target groups of ALS neurons using retrograde viral tracing. Overall, our findings provide a valuable resource for studying somatosensory biology and targeting subclasses of ALS neurons.

The oncomodulin receptor ArmC10 enables axon regeneration in mice after nerve injury and neurite outgrowth in human iPSC-derived sensory neurons

Oncomodulin (Ocm) is a myeloid cell-derived growth factor that enables axon regeneration in mice and rats after optic nerve injury or peripheral nerve injury, yet the mechanisms underlying its activity are unknown. Using proximity biotinylation, coimmunoprecipitation, surface plasmon resonance, and ectopic expression, we have identified armadillo-repeat protein C10 (ArmC10) as a high-affinity receptor for Ocm. ArmC10 deletion suppressed inflammation-induced axon regeneration in the injured optic nerves of mice. ArmC10 deletion also suppressed the ability of lesioned sensory neurons to regenerate peripheral axons rapidly after a second injury and to regenerate their central axons after spinal cord injury in mice (the conditioning lesion effect). Conversely, Ocm acted through ArmC10 to accelerate optic nerve and peripheral nerve regeneration and to enable spinal cord axon regeneration in these mouse nerve injury models. We showed that ArmC10 is highly expressed in human-induced pluripotent stem cell-derived sensory neurons and that exposure to Ocm altered gene expression and enhanced neurite outgrowth. ArmC10 was also expressed in human monocytes, and Ocm increased the expression of immune modulatory genes in these cells. These findings suggest that Ocm acting through its receptor ArmC10 may be a useful therapeutic target for nerve repair and immune modulation.

Mouse spontaneous behavior reflects individual variation rather than estrous state

Behavior is shaped by both the internal state of an animal and its individual behavioral biases. Rhythmic variation in gonadal hormones during the estrous cycle is a defining feature of the female internal state, one that regulates many aspects of sociosexual behavior. However, it remains unclear whether estrous state influences spontaneous behavior and, if so, how these effects might relate to individual behavioral variation. Here, we address this question by longitudinally characterizing the open-field behavior of female mice across different phases of the estrous cycle, using unsupervised machine learning to decompose spontaneous behavior into its constituent elements.1,2,3,4 We find that each female mouse exhibits a characteristic pattern of exploration that uniquely identifies it as an individual across many experimental sessions; by contrast, estrous state only negligibly impacts behavior, despite its known effects on neural circuits that regulate action selection and movement. Like female mice, male mice exhibit individual-specific patterns of behavior in the open field; however, the exploratory behavior of males is significantly more variable than that expressed by females both within and across individuals. These findings suggest underlying functional stability to the circuits that support exploration in female mice, reveal a surprising degree of specificity in individual behavior, and provide empirical support for the inclusion of both sexes in experiments querying spontaneous behaviors.

Pain modulation in the spinal cord

The sensory inflow from the periphery that triggers innocuous and painful sensations is highly complex, capturing key elements of the nature of any stimulus, its location, intensity, and duration, and converting this to dynamic action potential firing across a wide population of afferents. While sensory afferents are highly specialized to detect these features, their input to the spinal cord also triggers active processing and modulation there which determines its output, to drive the sensory percept experienced and behavioral responses. Focus on such active spinal modulation was arguably first introduced by Melzack and Wall in their Spinal Cord Gate Control theory. This theory has had a profound influence on our understanding of pain, and especially its processing, as well as leading directly to the development of clinical interventions, and its historical importance certainly needs to be fully recognized. However, the enormous progress we are making in the understanding of the function of the somatosensory system, means that it is time to incorporate these newly discovered features into a more complex and accurate model of spinal sensory modulation.