bioRxiv Science⌕ Search

bioRxiv · 10.1101/2022.07.21.501004

A 3D bioengineered neural tissue model generated from patient-derived iPSCs develops Alzheimer's disease-related phenotypes

Abstract

BackgroundCurrent models to study Alzheimers disease (AD) include cell cultures and animal models. Human diseases, however, are often poorly reproduced in animal models. Developing techniques to differentiate human brain cells from induced pluripotent stem cells (iPSCs) provides a novel approach to studying AD. Three-dimensional (3D) cultures to model AD are represented by organoids, neurospheroids, and scaffold-based cultures. Some AD-related phenotypes have been identified across 3D models [1]. However, to our knowledge, none of these studies could recapitulate several AD-related hallmarks in one single model and establish a temporal relation among them. Furthermore, to date, the transcriptomic features of these 3D models have not been compared with those of human AD brains. These data are, in our opinion, key to understanding the pertinency of these models for studying AD-related pathomechanisms over time. MethodsWe developed a 3D bioengineered model of iPSC-derived neural tissue that combines a porous scaffold composed of silk fibroin protein with an intercalated collagen hydrogel to support the growth of neurons and glial cells into complex and functional networks. This biomaterial scaffold, designed to match the mechanical properties of brain tissue, can support 3D neural cultures for an extended time without necrosis, a fundamental requisite for aging studies. We have optimized our protocol by seeding neural precursor cells (NPCs) into these scaffolds. NPC-derived cultures were generated from iPSC lines obtained from two subjects carrying the familial AD (FAD) APP London mutation, two well-studied control lines, and an isogenic control. Cultures were analyzed at 2 and 4.5 months. ResultsAn elevated A{beta}42/40 ratio was detected in conditioned media from FAD cultures at both time points, as previously reported in 2D cultures derived from the same FAD lines. However, extracellular A{beta}42 deposition and enhanced neuronal excitability were observed in FAD culture only at 4.5 months. The increased excitability of FAD cultures correlated with extracellular A{beta}42 deposition but not with soluble A{beta}42/40 ratio levels, as they were similar at both time points. These data suggest that extracellular A{beta} deposition may trigger enhanced network activity. Notably, neuronal hyperexcitability has been described in AD patients early in the disease. Transcriptomic analysis revealed the deregulation of multiple gene sets in FAD samples. Notably, such alterations were similar to those observed in human AD brains in a large study that performed a co-expression meta-analysis of harmonized data from Accelerating Medicines Partnership for Alzheimers Disease (AMP-AD) across three independent cohorts. ConclusionsOur 3D tissue model supports the differentiation of healthy iPSC-derived cultures in a porous silk-collagen composite sponge with an optically clear central region. This design facilitates nutrient delivery to meet the metabolic demand of long-term cultures. These data provide evidence that our bioengineered model from patient-derived FAD iPSCs develops time-dependent AD-related phenotypes and establishes a temporal relation among them. Furthermore, FAD iPSC-derived neuronal tissue recapitulates transcriptomic features of AD patients. Thus, our bioengineered neural tissue represents a unique tool to model AD-related pathomechanisms over time, with several advantages compared to the existing models.

Source connections

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Lomoio, S., PANDEY, R., Rouleau, N., Menicacci, B., Kim, W., Cantley, W., Haydon, P., Bennett, D., Young-Pearse, T., Carter, G., Kaplan, D., Tesco, G.. 2022-07-22. A 3D bioengineered neural tissue model generated from patient-derived iPSCs develops Alzheimer's disease-related phenotypes. https://doi.org/10.1101/2022.07.21.501004

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↗