Search bioRxiv⌕ Search

bioRxiv · 10.1101/2024.05.29.596266

D-Serine inhibits non-ionotropic NMDA receptor signaling

Abstract

NMDA-type glutamate receptors (NMDARs) are widely recognized as master regulators of synaptic plasticity, most notably for driving long-term changes in synapse size and strength that support learning. NMDARs are unique among neurotransmitter receptors in that they require binding of both neurotransmitter (glutamate) and co-agonist (e.g. O_SCPLOWDC_SCPLOW-serine) to open the receptor channel, which leads to the influx of calcium ions that drive synaptic plasticity. Over the past decade, evidence has accumulated that NMDARs also support synaptic plasticity via ion flux-independent (non-ionotropic) signaling upon the binding of glutamate in the absence of co-agonist, although conflicting results have led to significant controversy. Here, we hypothesized that a major source of contradictory results can be attributed to variable occupancy of the co-agonist binding site under different experimental conditions. To test this hypothesis, we manipulated co-agonist availability in acute hippocampal slices from mice of both sexes. We found that enzymatic scavenging of endogenous co-agonists enhanced the magnitude of LTD induced by non-ionotropic NMDAR signaling in the presence of the NMDAR pore blocker, MK801. Conversely, a saturating concentration of O_SCPLOWDC_SCPLOW-serine completely inhibited both LTD and spine shrinkage induced by glutamate binding in the presence of MK801. Using a FRET-based assay in cultured neurons, we further found that O_SCPLOWDC_SCPLOW-serine completely blocked NMDA-induced conformational movements of the GluN1 cytoplasmic domains in the presence of MK801. Our results support a model in which O_SCPLOWDC_SCPLOW-serine inhibits ion flux-independent NMDAR signaling and plasticity, and thus O_SCPLOWDC_SCPLOW-serine availability could serve to modulate NMDAR signaling even when the NMDAR is blocked by magnesium. Significance StatementNMDARs are glutamate-gated cation channels that are key regulators of neurodevelopment and synaptic plasticity and unique in their requirement for binding of a co-agonist (e.g. O_SCPLOWDC_SCPLOW-serine) in order for the channel to open. NMDARs have been found to drive synaptic plasticity via non-ionotropic (ion flux-independent) signaling upon the binding of glutamate in the absence of co-agonist, though conflicting results have led to controversy. Here, we found that O_SCPLOWDC_SCPLOW-serine inhibits non-ionotropic NMDAR-mediated LTD and LTD-associated spine shrinkage. Thus, a major source of the contradictory findings might be attributed to experimental variability in O_SCPLOWDC_SCPLOW-serine availability. In addition, the developmental regulation of O_SCPLOWDC_SCPLOW-serine levels suggests a role for non-ionotropic NMDAR plasticity during critical periods of plasticity.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Barragan, E. V., Anisimova, M., Vijayakumar, V., Coblentz, A. C., Park, D. K., Salaka, R. J., Nisan, A. F. K., Petshow, S., Dore, K., Zito, K., Gray, J. A.. 2024-06-01. D-Serine inhibits non-ionotropic NMDA receptor signaling. https://doi.org/10.1101/2024.05.29.596266

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↗