4.6 Article

Robust Generation of Person-Specific, Synchronously Active Neuronal Networks Using Purely Isogenic Human iPSC-3D Neural Aggregate Cultures

期刊

FRONTIERS IN NEUROSCIENCE
卷 13, 期 -, 页码 -

出版社

FRONTIERS MEDIA SA
DOI: 10.3389/fnins.2019.00351

关键词

human induced pluripotent stem cells; 3D-neural model system; neuronal networks; microelectrode array; synchronous activity

资金

  1. German Ministry of Education and Research [BMBF: FKZ 031B0010B]
  2. European Union (EuroTransBio9 project In-HEALTH)
  3. Alzheimerfonden [AF-556051/AF-744871, AF-640391]
  4. Ake Wiberg Foundation [M17-0265]
  5. Frederik and Ingrid Thuring Foundation [2016-0225]
  6. Stiftelsen Psykiatriska Forskningsfonden
  7. Ahlens stiftelse
  8. Swedish Research Council [2016-00986]
  9. Swedish State Support for Clinical Research [ALFGBG-427611]
  10. Swedish Research Council [2016-00986] Funding Source: Swedish Research Council

向作者/读者索取更多资源

Reproducibly generating human induced pluripotent stem cell-based functional neuronal circuits, solely obtained from single individuals, poses particular challenges to achieve personalized and patient specific functional neuronal in vitro models. A hallmark of functional neuronal assemblies, synchronous neuronal activity, can be non-invasively studied by microelectrode array (MEA) technology, reliably capturing physiological and pathophysiological aspects of human brain function. In our here presented manuscript, we demonstrate a procedure to generate 3D neural aggregates comprising astrocytes, oligodendroglial cells, and neurons obtained from the same human tissue sample. Moreover, we demonstrate the robust ability of those neurons to create a highly synchronously active neuronal network within 3 weeks in vitro, without additionally applied astrocytes. The fusion of MEA-technology with functional neuronal circuits solely obtained from one individual's cells represent isogenic person-specific human neuronal sensor chips that pave the way for specific personalized in vitro neuronal networks as well as neurological and neuropsychiatric disease modeling.

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