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Background Spinal cord motor neurons (MNs) from human iPS cells (iPSCs) have wide applications in disease modeling and therapeutic development for amyotrophic lateral sclerosis (ALS) and other MN-associated neurodegenerative diseases. We need highly efficient MN differentiation strategies for generating iPSC-derived disease models that closely recapitulate the genetic and phenotypic complexity of ALS. An important application of these models is to understand molecular mechanisms of action of FDA-approved ALS drugs that only show modest clinical efficacy. Novel mechanistic insights will help us design optimal therapeutic strategies together with predictive biomarkers to achieve better efficacy. Methods We induce efficient MN differentiation from iPSCs in 4 days using synthetic mRNAs coding two transcription factors (Ngn2 and Olig2) with phosphosite modification. These MNs after extensive characterization were applied in electrophysiological and neurotoxicity assays as well as transcriptomic analysis, to study the neuroprotective effect and molecular mechanisms of edaravone, an FDA-approved drug for ALS, for improving its clinical efficacy. Results We generate highly pure and functional mRNA-induced MNs (miMNs) from control and ALS iPSCs, as well as embryonic stem cells. Edaravone alleviates H2O2-induced neurotoxicity and electrophysiological dysfunction in miMNs, demonstrating its neuroprotective effect that was also found in the glutamate-induced miMN neurotoxicity model. Guided by the transcriptomic analysis, we show a previously unrecognized effect of edaravone to induce the GDNF receptor RET and the GDNF/RET neurotrophic signaling in vitro and in vivo, suggesting a clinically translatable strategy to activate this key neuroprotective signaling. Notably, edaravone can replace required neurotrophic factors (BDNF and GDNF) to support long-term miMN survival and maturation, further supporting the neurotrophic function of edaravone-activated signaling. Furthermore, we show that edaravone and GDNF combined treatment more effectively protects miMNs from H2O2-induced neurotoxicity than single treatment, suggesting a potential combination strategy for ALS treatment. Conclusions This study provides methodology to facilitate iPSC differentiation and disease modeling. Our discoveries will facilitate the development of optimal edaravone-based therapies for ALS and potentially other neurodegenerative diseases. Graphical abstract

Proneural transcription factors (TFs) drive highly efficient differentiation of pluripotent stem cells to lineage-specific neurons. However, current strategies mainly rely on genome-integrating viruses. Here, we used synthetic mRNAs coding two proneural TFs (Atoh1 and Ngn2) to differentiate induced pluripotent stem cells (iPSCs) into midbrain dopaminergic (mDA) neurons. mRNAs coding Atoh1 and Ngn2 with defined phosphosite modifications led to higher and more stable protein expression, and induced more efficient neuron conversion, as compared to mRNAs coding wild-type proteins. Using these two modified mRNAs with morphogens, we established a 5-day protocol that can rapidly generate mDA neurons with >90% purity from normal and Parkinson’s disease iPSCs. After in vitro maturation, these mRNA-induced mDA (miDA) neurons recapitulate key biochemical and electrophysiological features of primary mDA neurons and can provide high-content neuron cultures for drug discovery. Proteomic analysis of Atoh1-binding proteins identified the nonmuscle myosin II (NM-II) complex as a new binding partner of nuclear Atoh1. The NM-II complex, commonly known as an ATP-dependent molecular motor, binds more strongly to phosphosite-modified Atoh1 than the wild type. Blebbistatin, an NM-II complex antagonist, and bradykinin, an NM-II complex agonist, inhibited and promoted, respectively, the transcriptional activity of Atoh1 and the efficiency of miDA neuron generation. These findings established the first mRNA-driven strategy for efficient iPSC differentiation to mDA neurons. We further identified the NM-II complex as a positive modulator of Atoh1-driven neuron differentiation. The methodology described here will facilitate the development of mRNA-driven differentiation strategies for generating iPSC-derived progenies widely applicable to disease modeling and cell replacement therapy. Stem Cells Translational Medicine 2019;8:112&12

Quinine is an antimalarial drug that is toxic to the auditory system by commonly inducing hearing loss and tinnitus, presumably due to its ototoxic effects on disruption of cochlear hair cells and blockade of ion channels of neurons in the auditory system. To a lesser extent, quinine also causes ataxia, tremor, and dystonic reactions. As dopaminergic neurons are implicated to play a role in all of these diseases, we tested the toxicity of quinine on induced dopaminergic (iDA) neurons derived from human pluripotent stem cells (iPSCs) and primary dopaminergic (DA) neurons of substantia nigra from mice brain slices. Patch clamp recordings and combined drug treatments were performed to examine key physiological properties of the DA neurons. We found that quinine (12.5-200 μM) depolarized the resting membrane potential and attenuated the amplitudes of rebound spikes induced by hyperpolarization. Action potentials were also broadened in spontaneously spiking neurons. In addition to quinine attenuating hyperpolarization-dependent conductance, the tail currents following withdrawal of hyperpolarizing currents were also attenuated. Taken together, we found that iPSC-derived DA neurons recapitulated all the tested physiological properties of human DA neurons, and quinine had distinct effects on the physiology of both iDA and primary DA neurons. This toxicity of quinine may be the underlying mechanism for the movement disorders of cinchonism or quinism and may play a role in tinnitus modulation.

We evaluate the feasibility of using a biological sample’s transcriptome to predict its genome-wide regulatory element activities measured by DNase I hypersensitivity (DH). We develop BIRD, Big Data Regression for predicting DH, to handle this high-dimensional problem. Applying BIRD to the Encyclopedia of DNA Elements (ENCODE) data, we found that to a large extent gene expression predicts DH, and information useful for prediction is contained in the whole transcriptome rather than limited to a regulatory element’s neighboring genes. We show applications of BIRD-predicted DH in predicting transcription factor-binding sites (TFBSs), turning publicly available gene expression samples in Gene Expression Omnibus (GEO) into a regulome database, predicting differential regulatory element activities, and facilitating regulome data analyses by serving as pseudo-replicates. Besides improving our understanding of the regulome–transcriptome relationship, this study suggests that transcriptome-based prediction can provide a useful new approach for regulome mapping., A map of the activities of all genomic regulatory elements across cell types and conditions would be a tremendous resource. The computational method introduced here predicts genome-wide accessible sites from gene expression data and allows the authors to build a database of regulatory element activities using publicly available transcriptome data.