Cell Reports (May 2019)

A Single-Cell Model for Synaptic Transmission and Plasticity in Human iPSC-Derived Neurons

  • Marieke Meijer,
  • Kristina Rehbach,
  • Jessie W. Brunner,
  • Jessica A. Classen,
  • Hanna C.A. Lammertse,
  • Lola A. van Linge,
  • Desiree Schut,
  • Tamara Krutenko,
  • Matthias Hebisch,
  • L. Niels Cornelisse,
  • Patrick F. Sullivan,
  • Michael Peitz,
  • Ruud F. Toonen,
  • Oliver Brüstle,
  • Matthijs Verhage

Journal volume & issue
Vol. 27, no. 7
pp. 2199 – 2211.e6

Abstract

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Summary: Synaptic dysfunction is associated with many brain disorders, but robust human cell models to study synaptic transmission and plasticity are lacking. Instead, current in vitro studies on human neurons typically rely on spontaneous synaptic events as a proxy for synapse function. Here, we describe a standardized in vitro approach using human neurons cultured individually on glia microdot arrays that allow single-cell analysis of synapse formation and function. We show that single glutamatergic or GABAergic forebrain neurons differentiated from human induced pluripotent stem cells form mature synapses that exhibit robust evoked synaptic transmission. These neurons show plasticity features such as synaptic facilitation, depression, and recovery. Finally, we show that spontaneous events are a poor predictor of synaptic maturity and do not correlate with the robustness of evoked responses. This methodology can be deployed directly to evaluate disease models for synaptic dysfunction and can be leveraged for drug development and precision medicine. : This multisite study by Meijer et al. establishes a standardized in vitro approach to study synapse formation and function in single iPSC-derived human neurons. They validate this approach for GABA and glutamatergic human neurons. The methodology is scalable and suitable for compound screening and disease modeling. Keywords: synapse, synaptic transmission, synaptic plasticity, NGN2, synaptopathy, iPSC, human neuron, single-cell model, synaptic dysfunction, forward programming