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. 2018 Sep;136(3):405-423.
doi: 10.1007/s00401-018-1870-7. Epub 2018 Jun 7.

Transcriptome-pathology correlation identifies interplay between TDP-43 and the expression of its kinase CK1E in sporadic ALS

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Transcriptome-pathology correlation identifies interplay between TDP-43 and the expression of its kinase CK1E in sporadic ALS

Florian Krach et al. Acta Neuropathol. 2018 Sep.

Abstract

Sporadic amyotrophic lateral sclerosis (sALS) is the most common form of ALS, however, the molecular mechanisms underlying cellular damage and motor neuron degeneration remain elusive. To identify molecular signatures of sALS we performed genome-wide expression profiling in laser capture microdissection-enriched surviving motor neurons (MNs) from lumbar spinal cords of sALS patients with rostral onset and caudal progression. After correcting for immunological background, we discover a highly specific gene expression signature for sALS that is associated with phosphorylated TDP-43 (pTDP-43) pathology. Transcriptome-pathology correlation identified casein kinase 1ε (CSNK1E) mRNA as tightly correlated to levels of pTDP-43 in sALS patients. Enhanced crosslinking and immunoprecipitation in human sALS patient- and healthy control-derived frontal cortex, revealed that TDP-43 binds directly to and regulates the expression of CSNK1E mRNA. Additionally, we were able to show that pTDP-43 itself binds RNA. CK1E, the protein product of CSNK1E, in turn interacts with TDP-43 and promotes cytoplasmic accumulation of pTDP-43 in human stem-cell-derived MNs. Pathological TDP-43 phosphorylation is therefore, reciprocally regulated by CK1E activity and TDP-43 RNA binding. Our framework of transcriptome-pathology correlations identifies candidate genes with relevance to novel mechanisms of neurodegeneration.

Keywords: ALS; Casein kinase; Gene-expression; Laser capture microdissection; Motor neuron; Neurodegeneration; RNA; RNA-seq; Sporadic disease; TDP-43.

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Figures

Fig. 1
Fig. 1
Laser capture microdissection (LCM) isolates viable lumbar MNs from respiratory onset sALS patients. a Study paradigm: disease progresses caudally in sALS patients with respiratory onset. At the time of death, spinal MNs proximal to the site of onset (cervical) have succumbed, whereas distal MNs (lumbar) remain. These MNs are captured via LCM and subjected to RNA-seq. b Heatmap of RNA-seq derived gene expression signature of LCM MNs for controls and sALS samples showing enrichment of neuronal and glial markers. Two independent iPSC-derived MN lines and HEK293T (non neuronal) were used as controls. Color bar indicates Log2 fold change over HEK239T non-neuronal cells
Fig. 2
Fig. 2
Differential gene expression analysis in sALS reveals immune signature. a PCA plot representing genome-wide variance of control (blue) and sALS (red) LCM MN sample RNA-seq data along the first two PCs. b Unsupervised hierarchical clustering heatmap by correlation distance of differentially expressed genes determined by DEseq. Color scale represents z-scores. c Three most significant biological function (green), cellular compartment (red) and molecular function (yellow) GO-terms (DAVID) enriched within significantly dysregulated genes (left), and 1000 genes with highest PC1-eigenvalues (right). d Representative immunohistochemistry (IHC) of a control and an sALS patient exhibiting CX3CR1-positive microglia (arrow) within a 100 µm radius (circle) of a MN. e Quantification of number of CX3CR1-positive microglia within 100 µm radius of MNs, (N sALS = 10, N control = 9). Graph represents median and interquartile range, Significance was calculated with Mann–Whitney-U-test (P value = 0.0204). f Unsupervised correlation-distance based hierarchical clustering heatmap illustrating 370 differentially expressed genes (post filtering out PC1). Color scale represents z-scores. g Highly significant GO-terms of three GO categories that were not previously reported. Green = biological function, red = cellular compartment, yellow = molecular function
Fig. 3
Fig. 3
Unsupervised clustering stages sALS patients in two groups based of pTDP-43 status. a Correlation heatmap clustering sALS (red) and control (black) LCM MN samples according to 370 differentially expressed genes (left) or 10,000 × 370 random genes (right). Color scale represents correlation coefficients. Magenta arrowheads mark samples in the ‘mild’ gene expression group. Age, postmortem interval (PMI) and RNA integrity number (RIN) for individuals are represented in purple color scales. Motor neuron burden (MNB) of sALS patients indicates primarily upper MN (UMN) involvement (-2) in blue scales, lower MN (LMN) burden (+2) in red scales and equal contribution (0) of both MNs in white. b Representative IHC of pTDP-43 in sALS patients. Arrow marks morphologically normal MNs, dashed arrow marks morphologically degenerated MNs, arrowhead indicates pTDP-43 within MNs. c Quantification of TDP-43-positive and MN degeneration in each patient (3 lumbar sections per sALS patient). Samples were ranked by their percentage of pTDP-43-positive MNs. Green arrow indicates ‘low’ p TDP-43 group, while yellow marks the ‘high’ group. Magenta arrowheads indicate sALS samples clustering in ‘mild’ gene expression group
Fig. 4
Fig. 4
Neuropathology vs. gene expression correlations and TDP-43 eCLIP reveal potential candidate genes. a Histogram of Pearson correlation coefficients (log2 RPKM gene expression vs. pTDP-43 metric) for each patient sample (green) or randomized values (grey). Analysis performed with all detected transcripts before subtraction of immune genes. b TDP-43 eCLIP-seq of motor cortex from controls (n = 2) and sALS patients (n = 3). Venn diagram shows overlapping genes between control (n = 2) and sALS (n = 3) identified by TDP-43 eCLIP. Blue shows genes identified in both control samples (305), red shows genes identified in all sALS samples (62), magenta shows genes identified in all samples (351). Of the 305 genes conserved between both control samples, 293 were identified in at least one sALS sample (left pie chart). Of the 62 genes conserved between all sALS samples, 61 were identified in at least one control sample (right pie chart). c Pie chart showing genes highly correlated with TDP-43 pathology (r > |0.8|, 301 genes) with 16 genes that are also bound by TDP-43. CSNK1E shows the highest correlation (r = 0.96) and is bound by TDP-43. d Scatter plot illustrating regression of CSNK1E log2 RPKM vs. observed pTDP-43 status in respective sALS patients with fitted line and R2 value. e UCSC genome browser track shows binding of TDP-43 in the 3′ UTR of CSNK1E in the TDP-43 CLIP but not in the inputs (no IP control). f Radiolabeling of RNA pulled-down with pTDP-43- (left) and TDP-43-specific antibody in unstressed and stressed MNs
Fig. 5
Fig. 5
TDP-43 regulates CSNK1E mRNA levels. a CSNK1E RNA levels determined by qPCR. Graph represents mean +SEM, significance was calculated with t test (P value = 0.0271). b CSNK1D RNA levels determined by qPCR. Graph represents mean +SEM, significance was calculated with t test (P value = 0.4538). c Representative western blot showing reduced CK1E protein levels in TDP-43 knock down conditions
Fig. 6
Fig. 6
TDP-43 is a substrate of CK1E. a Immunohistochemistry for CK1E and pTDP-43 in lumbar spinal cord sections show co-occurrence of these signals in the same cell. β-III tubulin marks neurons. Scale bar 20 µm. b Immunoprecipitation (IP) of TDP-43 from three control and one fALS patient (TARDBP mutation) iPSC-derived MNs shows CSNK1E co-IP with TDP-43 but not IgG. c Immunofluorescence (IF) for pTDP-43 after overexpression (OE) of either CSNK1E or mock (control) in three different iPSC-derived MN lines shows increased pTDP-43 aggregates in CSNK1E OE. Scale bar 10 µm. d Quantification of pTDP-43 signal from CSNK1E or mock OE iPSC-MN lines described in c. Data represented as mean ± SEM. Mann–Whitney-U test was used to determine significance

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