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, 11 (2), 552-564

Recapitulation of Human Neural Microenvironment Signatures in iPSC-Derived NPC 3D Differentiation

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Recapitulation of Human Neural Microenvironment Signatures in iPSC-Derived NPC 3D Differentiation

Daniel Simão et al. Stem Cell Reports.

Abstract

Brain microenvironment plays an important role in neurodevelopment and pathology, where the extracellular matrix (ECM) and soluble factors modulate multiple cellular processes. Neural cell culture typically relies on heterologous matrices poorly resembling brain ECM. Here, we employed neurospheroids to address microenvironment remodeling during neural differentiation of human stem cells, without the confounding effects of exogenous matrices. Proteome and transcriptome dynamics revealed significant changes at cell membrane and ECM during 3D differentiation, diverging significantly from the 2D differentiation. Structural proteoglycans typical of brain ECM were enriched during 3D differentiation, in contrast to basement membrane constituents in 2D. Moreover, higher expression of synaptic and ion transport machinery was observed in 3D cultures, suggesting higher neuronal maturation in neurospheroids. This work demonstrates that 3D neural differentiation as neurospheroids promotes the expression of cellular and extracellular features found in neural tissue, highlighting its value to address molecular defects in cell-ECM interactions associated with neurological disorders.

Keywords: 3D culture; ECM; hiPSC; microenvironment; neural cell models; neural differentiation; neural progenitors; neurospheroids; proteomics; transcriptomics.

Figures

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Figure 1
Figure 1
Schematic Workflow for hiPSC-Derived NPC 3D Differentiation (A) NPCs were derived from two hiPSC lines, expanded as monolayer, and differentiated as neurospheroids. Cells harvested at days 0, 12, and 30 were processed for transcriptomic or proteomic analysis. (B) The coverage and overlap between total identified transcripts and proteins are represented in the Venn diagram. (C) Cellular localization of the identified transcripts and proteins according to Ingenuity Pathway Analysis (IPA) knowledge base. (D) Density scatterplot describes the transcriptome-proteome correlation, where each dot indicates the fold change (logarithmized) of an individual transcript/protein (total of 3,667). The Pearson correlation coefficient (PCC) is indicated in the scatterplot. The color code represents the density of dots included in a region of the scatterplot. Data shown represent four pooled independent biological experiments (two independent experiments of two cell lines). See also Figures S1 and S2.
Figure 2
Figure 2
Transcriptome Dynamics during hiPSC-NPC 3D Differentiation (A) Heatmap of significantly modulated transcripts between days 0 (D0), 12 (D12), and 30 (D30) (total of 12,116). Hierarchical clustering performed for the biological replicates of each time point and cell line (in columns; A and B refer to R1-hiPSC1-NPC and R1-hiPSC4-NPC, respectively), and for transcripts (in rows). Significantly modulated transcripts identified by multi-sample ANOVA test with a permutation-based false discovery rate (FDR) cutoff of 0.05 applied on the logarithmized intensities. Z-score values were color coded from blue (downregulation) to red (upregulation). (B) Heatmaps of gene expression profiles of neuronal and astrocytic specific markers at day D0, D12, and D30. Z score values were color coded from blue (downregulation) to red (upregulation). (C) (Left) Immunocytochemistry of hiPSC-NPC at D0, with the expression of nestin, vimentin, and Sox-2. Scale bars, 50 μm. (Right) Confocal imaging of neurospheroids at D30, with staining of βIII-tubulin or dendritic MAP2 and presynaptic markers of GABAergic (GAD65/67-positive) and glutamatergic (VGlut1-positive) neurons (3D-rendering insets of regions indicated by the asterisks highlight co-localization), βIII-tubulin, and glial fibrillary acidic protein (GFAP). Scale bars, 10 μm. (D) Top ten canonical pathways identified by IPA to describe the transcriptome modulation between D0 and D30. (E) Two-dimensional annotation enrichment analysis, correlating the pathways significantly modulated during 3D differentiation at the transcriptome and proteome level (Benjamini-Hochberg FDR < 0.05). Negative score values describe downregulation and positive scores indicate upregulation. Each dot represents a GO-Biological Process (GO-BP) term. Related GO-BP terms are presented with the same color. (F) Proposed regulatory network responsible for the transcriptome remodeling during differentiation. Different factors were color labeled according to the fold change between D0 and D30, ranging from green (downregulation) to red (upregulation). Predicted activation Z score is indicated by the number bellow each of the three transcription factors (REST, ASCL1, and TLX3), where negative and positive values indicate repression and activation, respectively. (G) Transcript levels of the different players represented in the regulatory network. Data are presented as mean ± SEM of the log2 of the fold change between D0 and D12 (green bars) or D0 and D30 (orange bars). Data shown in all panels represent four pooled independent biological experiments (two independent experiments of two cell lines). See also Figures S1 and S3; Table S1.
Figure 3
Figure 3
Extracellular Space and Plasma Membrane Proteome Remodeling during hiPSC-NPC 3D Differentiation (A) Heatmap of proteins significantly modulated at the extracellular or plasma membrane level, during 3D and 2D differentiation (total of 294 proteins). Hierarchical clustering performed for the biological replicates of each time point and cell line (in columns) and for proteins (in rows). Significantly modulated proteins identified by multi-sample ANOVA test with a permutation-based FDR cutoff of 0.05 applied on the logarithmized intensities. Z score values were color coded from blue (downregulation) to red (upregulation). (B) Volcano plot of proteins identified after 2D or 3D differentiation of hiPSC-NPCs. Significantly enriched proteins after 2D (orange) or 3D (green) differentiation are color labeled. Significantly modulated proteins identified by permutation-based FDR t test applied on the logarithmized intensities, with a threshold value of 0.05 and S0 of 0.1. (C) GO-BP terms significantly over-represented (Benjamini-Hochberg FDR < 0.02) in 2D (negative score) or 3D (positive score) differentiated cells. The y axis presents the corresponding p values (in negative log scale). Related GO-BP terms are presented with the same color, where some specific terms are highlighted by arrowheads. (D) Selected functional categories significantly over-represented during 3D differentiation (Benjamini-Hochberg FDR < 0.05) for proteins annotated as extracellular space or plasma membrane components. p values and number of proteins are graphically represented by different colors and sphere sizes, respectively. (E) Heatmaps of protein abundance profile at day 0 (D0), 2D at day 30, and 3D at day 30 of selected categories. Z score values were color coded from blue (downregulation) to red (upregulation). Data shown in all panels represent four (two independent experiments of two cell lines) or two pooled independent biological experiments, for neurospheroids or 2D cultures, respectively. See also Figure S4 and Table S2.
Figure 4
Figure 4
Transcriptomic Remodeling during Neural Differentiation in Different 2D and 3D Culture Systems (A) Principal component analysis of different in vitro culture systems. (B) Main GO-BP terms significantly over-represented in genes with top 1,000 positive (red) or negative (blue) loadings for principal component 1 (PC1) or PC2. The y axis corresponds to the negative log10 of the p values (FDR corrected). (C) Heatmap of the genes included in the GO-BP terms of cell division (87 genes), chemical synaptic transmission (68 genes), ECM organization (59 genes), regulation of ion transmembrane transport (22 genes), and CNS development (19 genes). Hierarchical clustering was performed for different genes (columns). Rows represent the different samples. Z score values were color coded from blue (downregulation) to red (upregulation). See also Table S3.
Figure 5
Figure 5
Upstream Regulator Analysis of Neurospheroids and 2D Differentiation (A) Venn diagram of differentially expressed genes associated with extracellular space and plasma membrane in neurospheroids and 2D differentiation (Srikanth et al., 2015). (B) Top five upstream regulators predicted in IPA to be responsible for the differential gene expression of exclusively modulated genes (extracellular space and plasma membrane genes only) in 3D (665 genes) and 2D (755 genes). The activation scores and p values are graphically represented by different colors and sphere sizes, respectively. (C) Regulatory networks derived for 3D and 2D data based on IPA predictions for the top five upstream regulators. See also Figure S5.

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