Phosphoproteomics identifies microglial Siglec-F inflammatory response during neurodegeneration

Morshed, N.; Ralvenius, W. T.; Nott, A.; Watson, L. A.; Rodriguez, F. H.; Akay, L. A.; Joughin, B. A.; Pao, P.-C.; Penney, J.; LaRocque, L.; Mastroeni, D.; Tsai, L.-H.; White, F. M.

doi:10.1101/2020.05.12.090688

bioRxiv · 10.1101/2020.05.12.090688

Phosphoproteomics identifies microglial Siglec-F inflammatory response during neurodegeneration

Morshed, N.·Ralvenius, W. T.·Nott, A.·Watson, L. A.·Rodriguez, F. H.·Akay, L. A.·Joughin, B. A.·Pao, P.-C.·Penney, J.·LaRocque, L.·Mastroeni, D.·Tsai, L.-H.·White, F. M.

View original source ↗Export metadata ↓

Abstract

Alzheimers disease (AD) is characterized by the appearance of amyloid-{beta} plaques, neurofibrillary tangles, and inflammation in brain regions involved in memory. Using mass spectrometry, we have quantified the phosphoproteome of the CK-p25, 5XFAD, and Tau P301S mouse models of neurodegeneration. We identified a shared response involving Siglec-F which was upregulated on a subset of reactive microglia. The human paralog Siglec-8 was also upregulated on microglia in AD. Siglec-F and Siglec-8 were upregulated following microglial activation with interferon gamma (IFN{gamma}) in BV-2 cell line and human stem-cell derived microglia models. Siglec-F overexpression activates an endocytic and pyroptotic inflammatory response in BV-2 cells, dependent on its sialic acid substrates and immunoreceptor tyrosine-based inhibition motif (ITIM) phosphorylation sites. Related human Siglecs induced a similar response in BV-2 cells. Collectively, our results point to an important role for mouse Siglec-F and human Siglec-8 in regulating microglial activation during neurodegeneration. HighlightsO_LIPhosphoproteomics analysis of CK-p25, 5XFAD, and Tau P301S mouse models finds dysregulated signaling networks associated with Alzheimers disease pathologies. C_LIO_LIA phosphorylation site on Siglec-F is found to be upregulated across all three models of disease. C_LIO_LIExpression of Siglec-F and its human paralog Siglec-8 is increased in reactive microglia. C_LIO_LIOverexpression of Siglec-F and Siglec-8 in vitro drives an endocytic and pyroptotic inflammatory response. C_LI In BriefPhosphoproteome signaling changes associated with Alzheimers disease (AD) are poorly characterized. Here, Morshed et al. apply phosphoproteomics to mouse models of AD to uncover a novel microglial receptor, Siglec-F, that is upregulated on a subset of inflammatory microglia across models of neurodegeneration. The human paralog, Siglec-8 is also found to be upregulated in late-onset AD microglia. Overexpression of Siglec-F and related human Siglecs activates pro-inflammatory signaling responses in BV-2 cells.

Source connections

Published article ↗

Explore related subjects

neuroscience Preprint

Keep this discovery

Explore connections, maps & timelines

BibTeX RIS

Morshed, N., Ralvenius, W. T., Nott, A., Watson, L. A., Rodriguez, F. H., Akay, L. A., Joughin, B. A., Pao, P.-C., Penney, J., LaRocque, L., Mastroeni, D., Tsai, L.-H., White, F. M.. 2020-05-14. Phosphoproteomics identifies microglial Siglec-F inflammatory response during neurodegeneration. https://doi.org/10.1101/2020.05.12.090688

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

KEEP EXPLORING

Related preprints

bioRxiv2026

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↗

bioRxiv2026

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↗

bioRxiv2026

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↗