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STEMCELL Technologies develops cell culture media, cell separation systems, instruments and other reagents for use in life sciences research in the fields of immunology, hematology, neuroscience, mesenchymal cell, stem cell and epithelial cell biology.
STEMCELL Technologies Patents
STEMCELL Technologies has filed 42 patents.
Transcription factors, Clusters of differentiation, Molecular biology, Cell biology, Proteins
Transcription factors, Clusters of differentiation, Molecular biology, Cell biology, Proteins
Latest STEMCELL Technologies News
Sep 21, 2023
Abstract Tauopathies are a heterogenous group of neurodegenerative disorders characterized by tau aggregation in the brain. In a subset of tauopathies, rare mutations in the MAPT gene, which encodes the tau protein, are sufficient to cause disease; however, the events downstream of MAPT mutations are poorly understood. Here, we investigate the role of long non-coding RNAs (lncRNAs), transcripts >200 nucleotides with low/no coding potential that regulate transcription and translation, and their role in tauopathy. Using stem cell derived neurons from patients carrying a MAPT p.P301L, IVS10 + 16, or p.R406W mutation and CRISPR-corrected isogenic controls, we identified transcriptomic changes that occur as a function of the MAPT mutant allele. We identified 15 lncRNAs that were commonly differentially expressed across the three MAPT mutations. The commonly differentially expressed lncRNAs interact with RNA-binding proteins that regulate stress granule formation. Among these lncRNAs, SNHG8 was significantly reduced in a mouse model of tauopathy and in FTLD-tau, progressive supranuclear palsy, and Alzheimer’s disease brains. We show that SNHG8 interacts with tau and stress granule-associated RNA-binding protein TIA1. Overexpression of mutant tau in vitro is sufficient to reduce SNHG8 expression and induce stress granule formation. Rescuing SNHG8 expression leads to reduced stress granule formation and reduced TIA1 levels in immortalized cells and in MAPT mutant neurons, suggesting that dysregulation of this non-coding RNA is a causal factor driving stress granule formation via TIA1 in tauopathies. Introduction Tauopathies are a class of neurodegenerative diseases that manifest as cognitive decline and are neuropathologically characterized by the accumulation of intracellular hyperphosphorylated tau protein [ 1 ]. Dominantly inherited mutations in the MAPT gene, which encodes the tau protein, are sufficient to cause disease in a subset of tauopathies termed frontotemporal lobar degeneration with tau pathology (FTLD-tau) [ 2 ]. However, the underlying mechanisms by which MAPT mutations cause disease remain unclear. Several mechanisms contributing to FTLD-tau have been proposed. MAPT mutations have been reported to affect molecular and structural properties of tau. As a consequence, microtubule binding efficiency, post-translational modification status, and isoform balance of tau in the central nervous system (CNS) may be altered [ 3 ]. MAPT mutations also lead to tau accumulation, impaired neuronal function, cell death, mitochondrial stress, autophagic and lysosomal dysregulation, and nuclear-cytosolic transport defects [ 4 , 5 , 6 , 7 , 8 , 9 ]. Whether there are mechanisms upstream of these molecular events remains poorly understood. Disruption of non-coding regulatory elements in the genome may have broad downstream effects that have yet to be fully explored in FTLD-tau [ 10 , 11 ]. Stem cell modeling along with genome editing have revealed that MAPT mutations are sufficient to elicit a number of molecular events associated with synaptic function and proteostasis [ 5 , 12 , 13 , 14 , 15 ]. These studies have focused on understanding the effects of MAPT mutations on coding genes. Yet, coding genes represent only 2% of the human genome. Non-coding regions, such as long non-coding RNAs (lncRNAs), represent 31.79% of the genome. LncRNAs play crucial regulatory roles in many cellular processes [ 16 ], including the regulation of transcriptional modulation, post-transcriptional control, nuclear-cytoplasmic transport, translational inhibition, mRNA stability, RNA decoys, and regulation of protein activity [ 17 ]. LncRNAs also interact with a wide range of RNA-binding proteins, including those involved in stress granule formation [ 18 , 19 ]. With non-coding RNAs making up a significant portion of the human genome, the impact of MAPT mutations on lncRNAs is an unexplored area that may hold key insights into the underlying mechanisms of FTLD-tau. Our findings suggest that MAPT mutations have a significant impact on lncRNA expression in human neurons. We identified a lncRNA, SNHG8, that is reduced across three types of MAPT mutations and reduced in brains from tauopathy mouse models and human patients. In vitro studies demonstrate that MAPT mutations disrupt SNHG8 expression, which promotes stress granule formation. This represents a novel mechanism that could be targeted for therapeutic intervention in the context of tauopathies. These results highlight the importance of studying the role of lncRNAs in the regulation of stress granule formation and the effects of MAPT mutations on lncRNA expression in the development of effective treatments for tauopathies. Material and methods Patient consent To obtain fibroblasts, skin punches were performed following written informed consent from the donor. The informed consent was approved by the Washington University School of Medicine Institutional Review Board and Ethics Committee (IRB 201104178 and 201306108). The University of California San Francisco Institutional Review Board approved the operating protocols of the UCSF Neurodegenerative Disease Brain Bank (from which brain tissues were obtained). Participants or their surrogates provided consent for autopsy, in keeping with the guidelines put forth in the Declaration of Helsinki, by signing the hospital’s autopsy form. If the participant had not provided future consent before death, the DPOA or next of kin provided it after death. All data were analyzed anonymously. iPSC generation and genome engineering Human iPSCs used in this study have been previously described [ 20 ]. iPSC lines were generated using non-integrating Sendai virus carrying the Yamanaka factors: OCT3/4, SOX2, KLF4, and cMYC (Life Technologies) [ 21 , 22 ]. The following parameters were used for the characterization of each of the iPSC lines using standard methods [ 21 ]: pluripotency markers by immunocytochemistry (ICC) and quantitative PCR (qPCR); spontaneous or TriDiff differentiation into the three germ layers by ICC and qPCR; assessment of chromosomal abnormalities by karyotyping; and MAPT mutation status confirmation by Sanger sequencing (characterization data previously reported [ 15 ]). To determine the impact of the MAPT mutant allele on molecular phenotypes, we used CRISPR/Cas9-edited isogenic controls in which the mutant allele was reverted to the wild-type (WT) allele in each of the donor iPSC lines as previously described [ 15 , 20 ]. The resulting edited iPSC lines were characterized as described above in addition to on- and off-target sequencing (characterization data previously reported [ 15 ]). All iPSC lines used in this study carry the MAPT H1/H1 common haplotype. All cell lines were confirmed to be free of mycoplasma. Differentiation of iPSCs into cortical neurons iPSCs were differentiated into cortical neurons as previously described [ 5 , 20 ] ( https://doi.org/10.17504/protocols.io.p9kdr4w ). Briefly, iPSCs were plated at a density of 65,000 cells per well in neural induction media (StemCell Technologies) in a 96-well v-bottom plate to form neural aggregates. After 5 days, cells were transferred into culture plates. The resulting neural rosettes were isolated by enzymatic selection (Neural Rosette Selection Reagent; StemCell Technologies) and cultured as neural progenitor cells (NPCs). NPCs were differentiated in planar culture in neuronal maturation medium (neurobasal medium supplemented with B27, GDNF, BDNF, and cAMP). The cells were analyzed after 6 weeks in neuronal maturation medium. At this time, tau protein levels are stable and similar to protein profiles described in human brains [ 23 ]. RNA sequencing and lncRNA transcript quantification RNAseq was generated from iPSC-derived neurons as previously described [ 12 , 15 ]. Briefly, samples were sequenced by an Illumina HiSeq 4000 Systems Technology with a read length of 1 × 150 bp and an average library size of 36.5 ± 12.2 million reads per sample. Salmon (v. 0.11.3) [ 24 ] was used to quantify the expression of the genes annotated within the human reference genome (GRCh38.p13; Supplementary Table 1 ). The lncRNA genes were selected for downstream analyses. LncRNA genes that were present in at least 10% of samples with expression >0.1 TPM were included in subsequent analyses: 7,537 lncRNA genes (Supplementary Fig. 1 ). Principal component and differential expression analyses Principal component analyses (PCA) were performed with the selected 7,537 non-coding genes using regularized-logarithm transformation (rlog) counts. Differential gene expression was performed using the DESeq2 (v.1.22.2) R package [ 25 ]. PCA and differential gene expression analyses were performed independently for each pair of MAPT mutations and isogenic controls. Each MAPT mutation and its isogenic control were considered independent cohorts due to their shared genetic background. PCA and Volcano plots were created for each comparison using the ggplot2 R package (v3.3.6) [ 26 ]. Functional annotation of differentially expressed lncRNA genes LncSEA was used to determine the RNA-binding protein interactions of common differentially expressed lncRNAs [ 27 ]. Gene relationships of top RNA-binding proteins and MAPT, including physical interaction, co-localization, pathway, shared protein domain, and genetic interaction, were examined using the GeneMANIA Cytoscape plugin [ 28 ]. CatRAPID was applied to identify the interactions between individual lncRNAs and RNA-binding proteins [ 29 , 30 ]. The input for CatRAPID analysis was the FASTA sequence of lncRNA and protein. The output was a heat map where the axes represent the indexes of the RNA and protein sequences with interaction propensity and discriminative power. The Interaction Propensity is a measure of the interaction probability between one protein (or region) and one RNA (or region). This measure is based on the observed tendency of the components of ribonucleoprotein complexes to exhibit specific properties of their physio-chemical profiles that can be used to make a prediction. The Discriminative Power is a statistical measure introduced to evaluate the Interaction Propensity with respect to CatRAPID training. It represents confidence of the prediction. The Discriminative Power (DP) ranges from 0% (unpredictable) to 100% (predictable). DP values above 50% indicate that the interaction is likely to take place, whereas DPs above 75% represent high-confidence predictions. Plasmids Plasmids pRK5-EGFP containing 4R0N Tau WT or P301L (Addgene plasmids 46904 and 46908) were used to evaluate the impact of tau on stress granule formation and lncRNA expression [ 31 ]. To test the impact of SNHG8 on stress granule formation, a plasmid containing human SNHG8 (transcript 203) in pcDNA3.1(+)-C-eGFP was used (pcDNA3.1(+)-SNHG8-203-EGFP (transcript 203) and control pcDNA3.1(+)-EGFP; Genescript). Untagged P301L-Tau (4R2N) constructs in pcDNA3.1(+) were employed in tau interaction and SNHG8-EGFP rescue experiments [ 32 ]. Transient transfection in HEK293-T cells HEK293-T cells were grown in Dulbecco’s Modified Eagle Medium (DMEM; Life Technologies) supplemented with 10% FBS, 1% L-Glutamine, and 1% Penicillin and streptomycin solution. Plasmids were transfected using Lipofectamine 2000 (Invitrogen, San Diego, CA, USA) according to the manufacturer’s protocol. The transfected cells were evaluated after 24 or 48 h for immunocytochemistry or RNA-immunoprecipitation, respectively. RNA immunoprecipitation RNA-immunoprecipitation (RIP) was performed as previously described with minor modifications [ 33 ]. Briefly, HEK293-T cells transfected with either WT-Tau (2N4R) or control vector plasmid constructs [ 32 ]. Cells were lysed in RIP buffer containing 20 mM Tris-HCl, pH 8.0, 200 mM NaCl, 1 mM EDTA, 1 mM EGTA, 0.5% Triton X-100, 0.4U/ul RNase inhibitor and 1X protease inhibitor cocktail (Roche). The lysate was pre-cleared by centrifugation and the total protein of the supernatant was quantified by BCA protein assay kit (Pierce). Approximately 1 mg of pre-cleared lysate was incubated with 2.5 ug of Tau5 and Tau7 antibodies (generous gift from Lester Binder) or pre-immune IgG (sc-2025) overnight at 4 °C. The lncRNA-protein complexes were captured with antibody coupled protein A/G beads (Thermo Fisher Scientific, Cat#20333), washed with RIP buffer, and treated with RNase free DNase I. RNAs were isolated using the Trizol method. QPCR was performed with SNHG8 and GAPDH primer by using iTaq-one step RT-PCR kit (Bio-Rad). For western blot analyses, approximately 20% of the capture beads were washed three times with cell lysis buffer and once with 1X phosphate-buffered saline (PBS). The washed beads were mixed with 4x Laemmli sample buffer (Bio-Rad, Cat#: 161-0747) and 10% β-mercaptoethanol, heated at 95 °C for 30 min, and run on a 4%–12% Bis-Tris gel (NuPAGE). Proteins were transferred to PVDF membrane and blocked for 1 h at room temperature in 5% milk in phosphate buffered saline with 0.1% Tween 20 (PBS-T). Membranes were probed with the mouse anti-Tau5 antibody (1:2000; Abcam, Cat# ab3931, RRID: AB_304171) and GAPDH (1:5000, Thermo Fisher Scientific, Cat# MA5-15738, RRID: AB_10977387) overnight at 4 °C. Membranes were subsequently washed and incubated in affiniPure Goat anti-mouse HRP (1:3000, Jackson Immuno Research Labs, Cat# 115-035-174, RRID: AB_2338512) for 1 h at room temperature, washed, and developed using SuperSignal West Pico PLUS Chemiluminescent Substrate (Thermo Fisher Scientific). Mouse model of tauopathy To evaluate whether the genes differentially expressed in iPSC-derived neurons from MAPT mutation carriers were altered in animal models of tauopathy, we analyzed transcriptomic data from a Tau-P301L mouse model of tauopathy and non-transgenic controls [ 34 , 35 ]. Differential gene expression of lncRNAs was performed in mice at 2, 4, and 8 months of age using unpaired t-tests to assess significance. Gene expression analysis in PSP and AD brains To determine whether the differentially expressed lncRNAs in the MAPT mutant iPSC-derived neurons capture molecular processes that occur in human brains with primary tauopathy, we analyzed gene expression in a publicly available dataset: the temporal cortex of 76 control, 82 PSP, and 84 AD brains (syn6090813) [ 36 ]. Differential gene expression analyses comparing controls with PSP and AD brains were performed using a “Simple Model” that employs multi-variable linear regression analyses using normalized gene expression measures and corrected by sex, age-at-death, RNA integrity number (RIN), brain tissue source, and flowcell as covariates [ 36 ]. Transcriptomic data from the middle temporal gyrus of FTLD-tau patients with MAPT IVS10 + 16 and p.P301L mutation (MAPT IVS10 + 16 n = 2 and MAPT p.P301L n = 1) and neuropathology free controls (n = 3) were also analyzed [ 15 ]. Differential expression analyses comparing FTLD-tau mutation carrier brains with controls were performed using DESeq2 (v.1.22.2) R package [ 25 ] as previously described [ 15 ]. qPCR validation of lncRNA-SNHG8 and TIA1 SNHG8 expression was validated using qPCR by SYBR green chemistry. Specific primers probes (Supplementary Table 2 ) were used to study the expression of lncRNAs in neurons expressing the MAPT IVS10 + 16, p.R406W, or p.P301L mutation along with their isogenic controls. Transcript quantification of TIA1 from HEK293-T cells under stress or basal conditions was performed using specific primers to TIA1 (Supplementary Table 2 ). LncRNA expression was measured by qPCR on a Quantstudio 3 qPCR machine (Applied Biosystems by Thermo Fisher Scientific) using specific primers. Melt curve was analyzed to study the specificity of the primers. Induction and quantification of stress granules TIA1, G3BP2, or PABP were used to monitor stress granule formation [ 37 ]. Stress granule formation was induced by culturing HEK293-T cells in a nutrient poor buffer (Hank’s buffer) or 0.5 mM sodium arsenite, which induces oxidative stress, as previously described [ 38 , 39 , 40 , 41 ]. HEK293-T or iPSC-derived neurons were immunostained with TIA1 (Sigma Aldrich-SAB4301803, 1:250 dilution), G3BP2 (Cell Signaling Technology- 31799S, 1:500 dilution), or PABP (Sant Cruz-sc-32318, 1:50 dilution) antibodies. Briefly, to perform immunocytochemistry, cells were grown on chamber slides. Culture media was aspirated, and cells were washed with PBS and fixed with 4% paraformaldehyde (Sigma) for 20 min at room temperature. Cells were washed with PBS and incubated with permeabilization buffer (0.1% Triton X-100 in PBS). Cells were then blocked in 0.1% bovine serum albumin (BSA; Sigma) and treated with primary and secondary antibodies diluted in 0.1% BSA. Immunostained cells were imaged (BZ-X800 series, Keyence fluorescent microscope, Keyence, IL, USA and Zeiss LSM 980 with Airyscan 2, Zeiss, Germany). At least six random images were captured per replicate, per condition. To calculate the percentage of cells positive for stress granules, the number of cells with stress granules in GFP-positive cells were divided by total number of GFP-positive cells. To determine the number of stress granules/cell and total stress granules in all GFP-positive cells, TIA1-, G3BP2-, and PABP-positive inclusions were manually counted and corrected for the GFP-positive cells. RNAscope RNAscope (Advanced Cell Diagnostics, ACD; Hayward, CA) was performed using BaseScope Reagent Kit v2 – RED (323900) kit by using specific probes targeting human SNHG8 (NC_000004.12) according to the manufacturer’s protocol. 3ZZ probe named BA-Hs-SNHG8-O1-3zz-st targeting 2-133 of NC_000004.12:118278708-118279137 was used. BaseScope is a chromogenic assay: red chromogen was used for SNHG8 detection which can be seen under a fluorescent microscope in the Texas Red spectrum. HEK293-T cells were fixed with paraformaldehyde and washed with PBS. Slides were then hybridized with target probes and incubated in a HybEZ oven (ACD) for 2 h at 40 °C. Next, signals were amplified and generated with a BaseScope Detection Reagent Kit v2 – RED. Cells were then counterstained with DAPI. SNHG8 expression was scored as positive if staining was present in HEK293-T cells. For visualizing the slides stained with SNHG8, a Keyence microscope (BZ-X800 series, Keyence fluorescent microscope, Keyence, IL, USA) and confocal microscope (Zeiss LSM 980 with Airyscan 2, Zeiss, Germany) were used. Images were captured at 40X and 60X magnification. ImageJ ( https://imagej.nih.gov/ ) was used to quantify the mean intensity of SNHG8. The freehand selections tool was used to mark the transfected cells in green channel and the measure tool was used to quantify the SNHG8 signal in the red channel. Overexpression of SNHG8 in iPSC-derived neurons NPCs expressing the MAPT p.P301L mutation were nucleofected with GFP vector or SNHG8-GFP containing vector using the manufacturer’s instructions. Briefly 3ug of plasmid was nucleofected in 1 × 106 NPCs using the Lonza DC-104 program and cells were plated onto PLO/Lamin-coated plate in Neural Induction Media (StemCell Technologies) with 10% FBS. After cells recovered from nucleofection, cells were differentiated into neurons as described above. At day 20 of neural differentiation, cells were plated on the coated 8 well chamber slides at density of 50,000/well. At day 42, cells were fixed and processed for immunocytochemistry. Statistical analysis Statistical analyses of biochemical and immunocytochemistry experiments were performed using GraphPad Prism version 9.2.0 (332) software. Each experiment was performed at least three times to determine statistical significance. Data distribution was assumed to be normal. Comparison between experimental and control group was analyzed using Student’s t test, a level of p < 0.05 was considered statistically significant. Details of the sample sizes and statistical tests used are indicated in the figure legends. Results MAPT mutations are sufficient to drive changes in lncRNAs in human neurons To explore the contribution of lncRNAs to tauopathy, we examined whether there were a common set of lncRNAs that are downstream of MAPT mutations. The more than 50 MAPT mutations fall into three major classes: (1) intronic mutations that alter splicing, leading to an imbalance in tau isoforms; (2) missense mutations within exon 10, leading to mutations in only a subset of tau isoforms; (3) missense mutations occurring in all tau isoforms. To begin to define the common non-coding mechanisms driving FTLD-tau, we have studied MAPT mutations that fall into each of the three major classes: MAPT IVS10 + 16, p.P301L, and p.R406W, respectively. Transcriptomic data from iPSC-derived neurons carrying MAPT IVS10 + 16, p.P301L, or p.R406W together with their CRISPR/Cas9-generated isogenic controls were analyzed (Fig. 1A ). We have previously demonstrated that these MAPT mutant neurons produce elevated phosphorylated tau, endolysosomal defects, and molecular signatures consistent with those identified in human FTLD-tau brains [ 12 , 15 , 20 , 42 , 43 ]. Fig. 1: Mutations in MAPT are sufficient to drive changes in long non-coding RNA (lncRNA) profiles in iPSC-derived neurons. A Diagram of experimental design. B–D Principal component analysis (PCA) of MAPT IVS10 + 16, p.P301L, and p.R406W carriers and their respective isogenic controls using only lncRNAs. Red dots, CRISPR-corrected isogenic controls. Black dots, MAPT mutation carriers. E–G Volcano plots representing the differential expression of lncRNAs in MAPT IVS10 + 16, p.P301L, and p.R406W carriers compared to their respective isogenic controls. Red dots, differentially expressed genes (FDR < 0.05). Blue dots, differentially expressed genes (p < 0.05). Gray dots, not significant. H Venn diagram showing lncRNA overlap among all three MAPT mutations. I Bar graph representing mean log2 foldchange of common differentially expressed lncRNAs. J Heat map of correlation between differentially expressed lncRNAs and differentially expressed protein coding RNA. Correlation coefficient >0.6. K GO terms from the analysis of highly correlated protein coding RNAs.
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