Journal: bioRxiv

Article Title: The LRRK2 G2019S mutation alters astrocyte-to-neuron communication via extracellular vesicles and induces neuron atrophy in a human iPSC-derived model of Parkinson’s disease

doi: 10.1101/2020.07.02.178574

Figure Lengend Snippet: (A) Astrocytes were prepared from iPSCs carrying the PD mutation LRRK2 G2019S or its isogenic control. Confocal images of immunostained iPSC-derived astrocytes show expression of astrocyte markers GFAP (green), vimentin (red), merged GFAP (green) and vimentin (red) with the nuclear marker DAPI (blue), and merged astrocyte marker CD44 (red) with DAPI (blue). (B) Heatmap representing the hierarchical clustering of significantly upregulated and downregulated genes in LRRK2 G2019S vs WT astrocytes using a 1.4-fold threshold for up-regulated genes and a 0.7-fold threshold for down-regulated genes, and a false discovery rate of 0.05. Sequencing counts were normalized using the median of ratios method and calculated by the EBseq package in R, as described in Materials and Methods, then transformed using log 10 (1+normalized sequencing counts). The genes are separated into three categories based on their log 10 (1+normalized sequencing counts) value using k-means clustering with k=3 to reveal groups of low, moderate or high expression genes. Genes encoding exosome-related components are indicated on the right (purple lines, with each indicating one gene). (C) Heatmap representing the differential expression of 20 genes encoding exosome components in WT and LRRK2 G2019S astrocytes, across three independent biological replicates (labeled 1 to 3). The values represent the log 10 (1+ normalized sequencing counts) transformation as described in Materials and Methods, log 2 FC represents LRRK2 G2019S vs WT fold change in gene expression. Genes are sorted by their log 2 FC value in order of descending fold-change. (D-H) Gene ontology analysis of non-isogenic and isogenic lines showing up-regulated components identified by RNA sequencing, and Benjamini-Hochberg adjusted P-values were obtained from the Database for Annotation, Visualization and Integrated Discovery (DAVID) tool (D,F). Gene expression validation by qPCR of two exosome components, Rab27b (E,G) and CD82 (H) in non-isogenic and isogenic lines. Data are from three (B,C, D, F) four (G,H) or five (E) independent biological replicates; error bars represent mean + standard error of the mean (SEM). Statistical analysis was performed using two-tailed unpaired Student’s t-test with equal standard deviation (s.d.) (* p≤0.05, ** p<0.01).

Article Snippet: The cells were then washed once with PBS and incubated in primary antibody overnight at 4°C with the following antibodies: anti-MAP2 (1:3000, Thermo Fisher Scientific cat. # PA1-10005), TH (1:500, PhosphoSolutions, Aurora, CO, cat. # 2025-THRAB), anti-CD63 (1:500, Thermo fisher Scientific cat. # MA1-19281), anti-LRRK2 (1:200, Abcam cat. # ab133474), anti-GFAP (1:500, BD Biosciences, cat. # 556328), anti-vimentin (1:100, R&D, Minneapolis, MN, cat. # MAB2105), and anti-CD44 (1:500, BD Biosciences, cat. # 550538) in BSA buffer (1 % BSA in PBS).

Techniques: Mutagenesis, Derivative Assay, Expressing, Marker, Sequencing, Transformation Assay, Labeling, RNA Sequencing Assay, Two Tailed Test, Standard Deviation

Journal: bioRxiv

Article Title: The LRRK2 G2019S mutation alters astrocyte-to-neuron communication via extracellular vesicles and induces neuron atrophy in a human iPSC-derived model of Parkinson’s disease

doi: 10.1101/2020.07.02.178574

Figure Lengend Snippet: (A) Histogram representing the proportion of astrocytes expressing the marker CD44 by flow cytometry in cultures prepared from human fetal midbrain astrocytes (89.55 % CD44 + cells) or iPSC-derived astrocytes (88.54 % CD44 + cells). A total of 10,000 events were recorded for each experimental condition (Ai). CD44 gene expression in iPSCs, NPCs, iPSC-derived astrocytes (iAstrocytes) or human fetal midbrain astrocytes (hMidbrain) collected by RNA-seq and expressed as CPM values (Aii). (B) Quantification of GFAP + astrocytes in cultures differentiated from WT or LRRK2 G2019S iPSCs. Data are from two independent biological replicates, and at least 260 cells were counted per experimental condition (Bi). Gene expression of astrocyte markers in astrocytes derived from isogenic and non-isogenic iPSC lines, as well as human fetal midbrain astrocytes to use as a reference. Data were collected by RNA-seq and shown as the mean log 2 (CPM) values (Bii). (C,D) To confirm the successful differentiation of iPSCs into specific cell types, we performed RNA-seq of iPSCs, NPCs, iPSC-derived astrocytes and human fetal astrocytes. RNA-seq data was analyzed by principal component analysis (PCA) (E) and a heatmap representing the unsupervised cluster analysis was generated (F); data are from two (iPSCs) or three (NPCs, iPSC-derived astrocytes and fetal astrocytes) independent biological replicates. (E,F) Representative wide-field images showing transient calcium signals using the green Fluo-4 indicator (E) and internalization of green-labeled synaptosomes (H) in WT and LRRK2 G2019S iPSC-derived astrocytes. Arrowheads in (E) show cells with transient increase in Fluo-4 signal indicative of calcium influx.

Article Snippet: The cells were then washed once with PBS and incubated in primary antibody overnight at 4°C with the following antibodies: anti-MAP2 (1:3000, Thermo Fisher Scientific cat. # PA1-10005), TH (1:500, PhosphoSolutions, Aurora, CO, cat. # 2025-THRAB), anti-CD63 (1:500, Thermo fisher Scientific cat. # MA1-19281), anti-LRRK2 (1:200, Abcam cat. # ab133474), anti-GFAP (1:500, BD Biosciences, cat. # 556328), anti-vimentin (1:100, R&D, Minneapolis, MN, cat. # MAB2105), and anti-CD44 (1:500, BD Biosciences, cat. # 550538) in BSA buffer (1 % BSA in PBS).

Techniques: Expressing, Marker, Flow Cytometry, Derivative Assay, RNA Sequencing Assay, Generated, Labeling