Search bioRxiv⌕ Search

bioRxiv · 10.1101/2021.08.22.457278

An isogenic panel of single App knock-in mouse models of Alzheimer's disease confers differential profiles of β-secretase inhibition and endosomal abnormalities

Abstract

We previously developed single App knock-in mouse models of Alzheimers disease (AD) that harbor the Swedish and Beyreuther/Iberian mutations with or without the Arctic mutation (AppNL- G-F and AppNL-F mice). These models showed the development of amyloid {beta} peptide (A{beta}) pathology, neuroinflammation and cognitive impairment with aging. We have now generated App knock-in mice devoid of the Swedish mutations (AppG-F mice) and some additional mutants to address the following two questions: [1] Do the Swedish mutations influence the mode of {beta}-secretase inhibitor action in vivo? [2] Does the quantity of C-terminal fragment of amyloid precursor protein (APP) generated by {beta}-secretase (CTF-{beta}) affect endosomal properties as previously reported as well as other pathological events? A{beta} pathology was exhibited by AppG-F mice from 6 to 8 months of age, and was accompanied by microglial and astrocyte activation. We found that a {beta}-secretase inhibitor, verubecestat, inhibited A{beta} production in AppG-F mice, but not in AppNL-G-F mice, indicating that the AppG-F mice are more suitable for preclinical studies of {beta}-secretase inhibition given that most AD patients do not carry Swedish mutations. We also found that the quantity of CTF-{beta} generated by various App knock-in mutants failed to correlate with endosomal alterations or enlargement, implying that CTF-{beta}, endosomal abnormalities, or both are unlikely to play a major role in AD pathogenesis. This is the first AD mouse model ever described that recapitulates amyloid pathology in the brain without the presence of Swedish mutations and without relying on the overexpression paradigm. Thus, experimental comparisons between different App knock-in mouse lines will potentially provide new insights into our understanding of the etiology of AD.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Watamura, N., Sato, K., Shiihashi, G., Iwasaki, A., Kamano, N., Takahashi, M., Sekiguchi, M., Yamazaki, N., Fujioka, R., Nagata, K., Ohshima, T., Saito, T., Saido, T. C., Sasaguri, H.. 2021-08-24. An isogenic panel of single App knock-in mouse models of Alzheimer's disease confers differential profiles of β-secretase inhibition and endosomal abnormalities. https://doi.org/10.1101/2021.08.22.457278

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↗