bioRxiv ScienceSearch

bioRxiv · 10.1101/574434

Colocalization of MOR1 and GAD67 in Mouse Nucleus Accumbens

Abstract

Current understanding of the rewarding and addictive effects of opioids involves mu-opioid receptor (MOR) binding within the nucleus accumbens (NAcc), a region of the ventral striatum. GABAergic neurotransmission in the NAcc potentiates the rewarding response to opioids, and in fact, drugs that stimulate GABAergic activity are also addictive, a phenomenon mediated in part by endogenous opioids. However, the neuroanatomical relationship between opioid and GABA systems is still unclear, and further study of the interaction between these neurotransmitter systems in the reward pathway is warranted. We report evidence supporting the direct interaction between GABAergic and opioidergic neurotransmitter systems within the mouse NAcc. Male and female FVB/NJ mice (12-16 months of age) were euthanized via carbon dioxide inhalation and brains processed for histology and immunohistochemistry (IHC). Coronal cryosections (10-12 um in thickness) were taken through the NAcc at the level of the anterior commissure. A mouse monoclonal antibody against GAD67, an enzyme catalyzing GABA production, was used in conjunction with an anti-mouse rhodamine red-X-labeled secondary antibody to identify GABAergic neurons in the NAcc. Alternating sections were stained for MOR using a fluorescein isothiocyanate (FITC)-conjugated rabbit polyclonal anti-MOR1 antibody. DAPI (4',6-diamidino-2-phenylindole) was used to counterstain the nuclei. As expected, fluorescence microscopy results show that GAD67 staining is localized predominately in the neuronal cytoplasm, with approximately 40% of the population staining. The MOR1-FITC stain showed localization within the cytoplasm and plasma membrane as expected, however, there was also significant staining in the nuclear membrane and neuronal nucleus. MOR1-FITC was present in approximately 35% of the neuronal population. In separate experiments, we used double-immunostaining to study the co-expression of MOR1 and GAD67 within the same NAcc neurons. A similar localization pattern was detected with a small subset, approximately 2%, of neurons expressing both labels. There are few published reports of GAD67 and MOR1 co-expression within neurons of the NAcc. Previous studies of MOR expression show the receptor to be localized to the plasma membrane and, to a smaller degree, intracellularly. Here we found the MOR1 staining to be predominantly in the nucleus and nuclear membrane, with minimal expression on the plasma membrane. Further studies are in progress to validate the nuclear expression of MOR in GABAergic NAcc neurons. Results of the study suggest that a subset of mouse NAcc neurons express both MOR1 and GAD67, providing a direct intracellular link between opioid and GABAergic systems in the reward pathway. Preliminary intranuclear localization of MOR suggests a novel signaling pathway that may be important in fully elucidating neurobiological mechanisms underlying behaviors related to reward and addiction.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Hinkle, C. F., Dedkov, E. I., Buono, R. J., Ferraro, T. N.. 2019-03-12. Colocalization of MOR1 and GAD67 in Mouse Nucleus Accumbens. https://doi.org/10.1101/574434

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

The Unreasonable Effectiveness of Cell Types in Describing Neuronal Physiological Features

Single-cell RNA sequencing (scRNA-seq) captures detailed gene expression profiles at scale, while patch-clamp recordings measure intrinsic neuronal electrophysiological properties. Modeling the relations between these two modalities remains a challenge. Here, we compare how well electrophysiological features can be predicted by traditional transcriptomic cell type classification, representations derived from a foundational model (scGPT) pretrained on large-scale scRNA-seq datasets, ion channel-coding genes, and highly variable genes. Using paired transcriptomic and electrophysiological patch-sequencing data from 495 human neurons from neurosurgical tissue, we find that cluster-level cell type representations consistently outperform highly variable gene selection, ion channel gene selection, and context-enriched scGPT embeddings. Notably, performance varies across model architectures and initializations, and the best results are obtained by combining the outputs of separate cell type and scGPT-based models. Together, these findings suggest that traditional discrete cellular classification is highly effective in predicting physiological features. For maximum performance it can be complemented by pretrained transformer models.

neuroscience

A nonlinear inhibition pathway underlying cortical responses to tuned holographic optogenetic perturbations

Optogenetics enables causal manipulation of cortical activity. Perturbation responses can be counterintuitive due to network interactions, making theory essential for predicting them. Existing approaches often rely on linear approximations, which fail for many biologically relevant perturbations. Here we develop a nonlinear theory of responses to holographic perturbations in cell-type-specific recurrent networks with structured connectivity. We fit a nonlinear model to mouse V1 data, which shows cotuned-ensemble suppression: perturbing spatially clustered neurons with similar preferred orientations yields markedly stronger short-range suppression than perturbing untuned ensembles. We show that cotuned-ensemble suppression arises from a feature-tuned, nonlinear inhibition pathway implicating somatostatin-positive (SST) interneurons. The theory predicts that cotuned ensembles suppress parvalbumin-positive (PV) neurons but facilitate SST neurons, and links the degree of cotuned-ensemble suppression or facilitation to the variance of the SST response. This framework identifies mechanisms by which nonlinear inhibition sculpts cortical dynamics and establishes a predictive basis for targeted optogenetic interventions.

neuroscience

Proteomic signatures of APOE ε4 across human tissues and cell types in Alzheimers disease

The apolipoprotein E {varepsilon}4 (APOE {varepsilon}4) allele is the strongest genetic risk factor for late-onset Alzheimers disease (AD). However, the underlying molecular mechanisms remain unclear. This study included 1691 participants from the Religious Orders Study and Rush Memory and Aging Project (ROSMAP), 1226 participants from the Accelerating Medicines Partnership - Alzheimers Disease (AMP-AD) Diverse Cohorts Study, and 735 participants from the Alzheimers Disease Neuroimaging Initiative (ADNI). To characterise APOE {varepsilon}4 molecular effects, we analysed proteomic data from plasma, cerebrospinal fluid (CSF), and induced pluripotent stem cell (iPSC)-derived astrocytes and neurons, as well as transcriptomic and proteomic data from multiple brain regions. The association of APOE {varepsilon}4 with AD neuropathology was also examined. APOE {varepsilon}4 carriers shared a plasma proteomic signature enriched for immune processes, irrespective of AD diagnosis. A machine learning classifier trained on this signature discriminated APOE {varepsilon}4 carriers from non-carriers in an independent cohort using CSF proteomics. APOE {varepsilon}4 carriage was associated with higher Braak stages and Consortium to Establish a Registry for Alzheimers Disease (CERAD) score. However, only limited APOE {varepsilon}4-associated transcriptomic and proteomic changes were observed in bulk brain tissue, with poor cross-layer concordance. Proteomic analyses of iPSC-derived astrocytes and neurons further revealed cell-type-specific APOE {varepsilon}4-associated changes. APOE {varepsilon}4 is associated with a consistent proteomic signature across plasma and CSF. Its molecular effects in the brain differ across cell types, brain regions and molecular layers. These findings support the need for cell-type-resolved multi-omic studies to elucidate how APOE {varepsilon}4 confers AD risk.

neuroscience