Simple derivation of skeletal muscle from human pluripotent stem cells using temperature‐sensitive Sendai virus vector

温度感受性センダイウイルスベクターを用いて ヒトES細胞／iPS細胞から骨格筋細胞を簡便に作製する技術開発 --神経筋疾患病態モデル構築と創薬研究への利用--. 京都大学プレスリリース. 2021-09-13.Human pluripotent stem cells have the potential to differentiate into various cell types including skeletal muscles (SkM), and they are applied to regenerative medicine or in vitro modelling for intractable diseases. A simple differentiation method is required for SkM cells to accelerate neuromuscular disease studies. Here, we established a simple method to convert human pluripotent stem cells into SkM cells by using temperature-sensitive Sendai virus (SeV) vector encoding myoblast determination protein 1 (SeV-Myod1), a myogenic master transcription factor. SeV-Myod1 treatment converted human embryonic stem cells (ESCs) into SkM cells, which expressed SkM markers including myosin heavy chain (MHC). We then removed the SeV vector by temporal treatment at a high temperature of 38℃, which also accelerated mesodermal differentiation, and found that SkM cells exhibited fibre-like morphology. Finally, after removal of the residual human ESCs by pluripotent stem cell-targeting delivery of cytotoxic compound, we generated SkM cells with 80% MHC positivity and responsiveness to electrical stimulation. This simple method for myogenic differentiation was applicable to human-induced pluripotent stem cells and will be beneficial for investigations of disease mechanisms and drug discovery in the future

Establishment of induced pluripotent stem cells from schizophrenia discordant fraternal twins

Schizophrenia (SCZ) is one of the major psychiatric disorders. The genetic factor is certainly influential in the onset of the disease but is not decisive. There is no identified molecular/cellular marker of the disease, and the pathomechanism is still unknown. In this study, we generated human induced pluripotent stem cells (iPSCs) derived from SCZ-discordant fraternal twins, and they could contribute to elucidation of the pathomechanism of SCZ

Prediction Model of Amyotrophic Lateral Sclerosis by Deep Learning with Patient Induced Pluripotent Stem Cells

Deep LearningとALS iPS細胞を用いた疾患予測テクノロジー --人工知能のALS検知・診断への応用--. 京都大学プレスリリース. 2021-02-24.Deep learning amyotrophic lateral sclerosis by taking pictures. 京都大学プレスリリース. 2021-02-24.In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the diagnosis, we constructed an artificial intelligence‐based prediction model of ALS using induced pluripotent stem cells (iPSCs). Images of spinal motor neurons derived from healthy control subject and ALS patient iPSCs were analyzed by a convolutional neural network, and the algorithm achieved an area under the curve of 0.97 for classifying healthy control and ALS. This prediction model by deep learning algorithm with iPSC technology could support the diagnosis and may provide proactive treatment of ALS through future prospective research. ANN NEUROL 202

Deep Learning and ALS

In amyotrophic lateral sclerosis (ALS), early diagnosis is essential for both current and potential treatments. To find a supportive approach for the diagnosis, we constructed an artificial intelligence-based prediction model of ALS using induced pluripotent stem cells (iPSCs). Images of spinal motor neurons derived from healthy control subject and ALS patient iPSCs were analyzed by a convolutional neural network, and the algorithm achieved an area under the curve of 0.97 for classifying healthy control and ALS. This prediction model by deep learning algorithm with iPSC technology could support the diagnosis and may provide proactive treatment of ALS through future prospective research

iPSC-Based Compound Screening and In Vitro Trials Identify a Synergistic Anti-amyloid β Combination for Alzheimer’s Disease

In the process of drug development, in vitro studies do not always adequately predict human-specific drug responsiveness in clinical trials. Here, we applied the advantage of human iPSC-derived neurons, which offer human-specific drug responsiveness, to screen and evaluate therapeutic candidates for Alzheimer’s disease (AD). Using AD patient neurons with nearly 100% purity from iPSCs, we established a robust and reproducible assay for amyloid β peptide (Aβ), a pathogenic molecule in AD, and screened a pharmaceutical compound library. We acquired 27 Aβ-lowering screen hits, prioritized hits by chemical structure-based clustering, and selected 6 leading compounds. Next, to maximize the anti-Aβ effect, we selected a synergistic combination of bromocriptine, cromolyn, and topiramate as an anti-Aβ cocktail. Finally, using neurons from familial and sporadic AD patients, we found that the cocktail showed a significant and potent anti-Aβ effect on patient cells. This human iPSC-based platform promises to be useful for AD drug development

TDP-43 regulates cholesterol biosynthesis by inhibiting sterol regulatory element-binding protein 2

Dyslipidemia is considered an essential component of the pathological process of amyotrophic lateral sclerosis (ALS), a fatal motor neuron disease. Although TAR DNA Binding Protein 43 kDa (TDP-43) links both familial and sporadic forms of ALS and cytoplasmic aggregates are a hallmark of most cases of ALS, the molecular mechanism and the in vivo relation of ALS dyslipidemia with TDP-43 have been unclear. To analyze the dyslipidemia-related gene expression by TDP-43, we performed expression microarray and RNA deep sequencing (RNA-Seq) using cell lines expressing high levels of TDP-43 and identified 434 significantly altered genes including sterol regulatory element-binding protein 2 (SREBP2), a master regulator of cholesterol homeostasis and its downstream genes. Elevated TDP-43 impaired SREBP2 transcriptional activity, leading to inhibition of cholesterol biosynthesis. The amount of cholesterol was significantly decreased in the spinal cords of TDP-43-overexpressed ALS model mice and in the cerebrospinal fluids of ALS patients. These results suggested that TDP-43 could play an essential role in cholesterol biosynthesis in relation to ALS dyslipidemia

Generation of a human induced pluripotent stem cell line, BRCi009-A, derived from a patient with glycogen storage disease type 1a

Glycogen storage disease type 1a (GSD1a) is an autosomal recessive disorder caused by mutations of the glucose-6-phosphatase (G6PC) gene. Mutations of the G6PC gene lead to excessive accumulation of glycogen in the liver, kidney, and intestinal mucosa due to the deficiency of microsomal glucose-6-phosphatase.Human induced pluripotent stem cells (iPSCs) enable the production of patient-derived hepatocytes in culture and are therefore a promising tool for modeling GSD1a. Here, we report the establishment of human iPSCs from a GSD1a patient carrying a G6PC mutation (c.648G > T; p.Leu216 = )