Abstract

BackgroundSpinal 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.MethodsWe 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.ResultsWe 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.ConclusionsThis 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

Highlights

  • Spinal cord motor neurons (MNs) from human iPS cells have wide applications in disease modeling and therapeutic development for amyotrophic lateral sclerosis (ALS) and other MN-associated neurodegenerative diseases

  • We show that edaravone and GDNF combined treatment more effectively protects mRNA-induced motor neuron (miMN) from H2O2-induced neurotoxicity than single treatment, suggesting a potential combination strategy for ALS treatment

  • Synthetic mRNAs coding Olig2 and Ngn2 with phosphosite modification induce efficient MN differentiation from induced pluripotent stem cell (iPSC) Ngn2 and Olig2 are two transcription factor (TF) co-expressing in motor neuron progenitor cells, and their ectopic expression in combination induces MNs in the chick neural tube [17]

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Summary

Introduction

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. An important application of these models is to understand molecular mechanisms of action of FDA-approved ALS drugs that only show modest clinical efficacy. Human motor neurons (MNs) derived from iPSCs provide a unique and efficient platform for modeling various MN disorders and developing effective therapies. To improve clinical efficacy of current ALS drugs, it is critical to understand their molecular mechanisms of action in disease models that closely recapitulate the genetic and phenotypic complexity of ALS, and further rationally design single or possibly combination therapies together with predictive biomarkers to achieve better clinical efficacy

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