Biology subjects

Zurek, N. A.

Publications and source records attributed to Zurek, N. A..

4 recordsLinked to original sources

bioRxiv2024

Neuroimmune mechanisms of a mouse model of chronic back pain

Chronic back pain (CBP) is the leading cause of disability affecting 1 in 10 people worldwide. Symptoms are marked by persistent lower back pain, reduced mobility, and heightened cold sensitivity. Here, we utilize a mouse model of CBP induced by injecting urokinase-type plasminogen activator (uPA), a proinflammatory agent in the fibrinolytic pathway, between the L2/L3 lumbar vertebrae. We identified neuroimmune interactions contributing to uPA-induced CBP (henceforth, uPA-CBP) in mouse dorsal root ganglia (DRG), where nociceptive neurons reside. Flow cytometric data reveal that uPA-CBP increases CD45+CD11b+ cells in the DRG, a population characteristically implicated in other chronic pain models1. Blocking colony stimulating factor 1 receptor (CSF1R) signaling using PLX5622 partially reduced pain, suggesting CD45+CD11b+ macrophage involvement. Whole-cell patch-clamp electrophysiology data indicated DRG neuron hyperexcitability in CBP mice compared to controls. RNA sequencing revealed upregulation of pain- and inflammation-related genes involved in leukocyte migration. Together, these findings underscore the importance of the DRG neuroimmune axis in mediating chronic back pain. HighlightsO_LIuPA-CBP induces gait changes, mechanical and thermal sensitivity compared to shams C_LIO_LIuPA-CBP mice show increased CD45+CD11b+ cells in DRG compared to shams C_LIO_LIuPA-CBP mice show neuronal excitability in DRG neurons compared to shams C_LIO_LIPain behaviors are alleviated by pharmacologically blocking CSF1R signaling C_LIO_LIDysregulation of inflammation- and ion channel-related genes in uPA-CBP DRG C_LI

neuroscience↗

bioRxiv2024

Gabapentin's Effect on Human Dorsal Root Ganglia: Donor-Specific Electrophysiological and Transcriptomic Profiles

Neuropathic pain affects approximately 10% of the adult population and is commonly treated with gabapentin (GBP), a repurposed anticonvulsant drug. Despite its widespread clinical use, GBPs efficacy varies significantly among patients, highlighting the need to better understand its functional and molecular impacts on human pain-sensing neurons. In this study, we characterized the electrophysiological and transcriptomic effects of GBP on primary sensory neurons derived from the dorsal root ganglia (DRG) of ethically consented human donors. Using patch-clamp electrophysiology, we demonstrated that GBP treatment reduced neuronal excitability, with more pronounced effects in multi-firing vs. single-firing neuronal subtypes. Notably, significant donor-specific variability was observed in electrophysiological responsiveness to GBP treatment in vitro. RNA sequencing of DRG tissue from the GBP-responsive donor revealed differences in the transcriptome-wide expression of genes associated with ion transport, synaptic transmission, inflammation, and immune response relative to non-responsive donors. Cross-transcriptomic analyses further showed that GBP treatment counteracted these altered processes, rescuing aberrant gene expression at the pathway level and for several key genes. This study provides a comprehensive electrophysiological and transcriptomic profile of the effects of GBP on human DRG neurons. These findings enhance our understanding of GBPs mechanistic actions on peripheral sensory neurons and could help optimize its clinical use for neuropathic pain management.

neuroscience↗

bioRxiv2024

Machine learning elucidates electrophysiological properties predictive of multi- and single-firing human and mouse dorsal root ganglia neurons

Human and mouse dorsal root ganglia (hDRG and mDRG) neurons are important tools in understanding the molecular and electrophysiological mechanisms that underlie nociception and drive pain behaviors. One of the simplest differences in firing phenotypes is that neurons are single-firing (exhibit only one action potential) or multi-firing (exhibit 2 or more action potentials). To determine if single- and multi-firing hDRG exhibit differences in intrinsic properties, firing phenotypes, and AP waveform properties, and if these properties could be used to predict multi-firing, we measured 22 electrophysiological properties by whole-cell patch-clamp electrophysiology of 94 hDRG neurons from 6 male and 4 female donors. We then analyzed the data using several machine learning models to determine if these properties could be used to predict multi-firing. We used 1000 iterations of Monte Carlo Cross Validation to split the data into different train and test sets and tested the Logistic Regression, k-Nearest Neighbors, Random Forest, Supported Vector Classification, and XGBoost machine learning models. All models tested had a greater than 80% accuracy on average, with Supported Vector Classification and XGBoost performing the best. We found that several properties correlated with multi-firing hDRG neurons and together could be used to predict multi-firing neurons in hDRG including a long decay time, a low rheobase, and long first spike latency. We also found that the hDRG models were able to predict multi-firing with 90% accuracy in mDRG. Targeting the neuronal properties that lead to multi-firing could elucidate better targets for treatment of chronic pain.

neuroscience↗

bioRxiv2023

Electrophysiological analyses of human dorsal root ganglia and human induced pluripotent stem cell-derived sensory neurons from male and female donors

Human induced pluripotent stem cell-derived sensory neurons (hiPSC-SNs) and human dorsal root ganglia (hDRG) neurons are popular tools in the field of pain research; however, few groups make use of both approaches. For screening and analgesic validation purposes, important characterizations can be determined of the similarities and differences between hDRG and hiPSC-SNs. This study focuses specifically on electrophysiology properties of hDRG in comparison to hiPSC-SNs. We also compared hDRG and hiPSC-SNs from both male and female donors to evaluate potential sex differences. We recorded neuronal size, rheobase, resting membrane potential, input resistance, and action potential waveform properties from 83 hiPSCs-SNs (2 donors) and 108 hDRG neurons (9 donors). We observed several statistically significant electrophysiological differences between hDRG and hiPSC-SNs, such as size, rheobase, input resistance, and several actional potential (AP) waveform properties. Correlation analysis also revealed many properties that were positively or negatively correlated, some of which were differentially correlated between hDRG and hiPSC-SNs. This study shows several differences between hDRG and hiPSC-SNs and allows better understanding of the advantages and disadvantages of both for use in pain research. We hope this study will be a valuable resource for pain researchers considering the use of these human in vitro systems for mechanistic studies and/or drug development projects.

neuroscience↗