Scalable Generation of Pseudo-Unipolar Sensory Neurons from Human Pluripotent Stem Cells Article Swipe
Tao Deng
,
Carlos A. Tristan
,
Claire Weber
,
Pei‐Hsuan Chu
,
Seungmi Ryu
,
Vukasin M. Jovanovic
,
Pinar Ormanoglu
,
Prisca Twumasi
,
Jaehoon Shim
,
Selwyn S. Jayakar
,
Han-Xiong Bear Zhang
,
Sooyeon Jo
,
Ty C. Voss
,
Anton Simeonov
,
Bruce P. Bean
,
Clifford J. Woolf
,
Ilyas Singeç
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1101/2022.03.24.485622
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.1101/2022.03.24.485622
Development of new non-addictive analgesics requires advanced strategies to differentiate human pluripotent stem cells (hPSCs) into relevant cell types amenable for translational research. Here, we developed a highly efficient and reproducible method that differentiates hPSCs into peptidergic and non-peptidergic nociceptors. By modulating specific cell signaling pathways, hPSCs were first converted into SOX10 + neural crest cells, followed by differentiation into sensory neurons with an in vivo -like pseudo-unipolar morphology. Detailed characterization confirmed that the hPSC-derived nociceptors displayed molecular and cellular features comparable to native dorsal root ganglion (DRG) neurons, and expressed high-threshold primary sensory neuron markers, transcription factors, neuropeptides, and over 150 ion channels and receptors, including critical pain-relevant drug targets (e.g., TRPV1, TAC1, CALCA, NA V 1.7, NA V 1.8). Moreover, after confirming robust functional activities and differential response to noxious stimuli and specific drugs, a robotic cell culture system was employed to produce large quantities of human sensory neurons, which can be used to develop nociceptor-selective analgesics.
Related Topics
Concepts
Nociceptor
Induced pluripotent stem cell
Dorsal root ganglion
Sensory system
Neuroscience
Neural crest
Sensory neuron
Cell type
TRPV1
Biology
Nociception
Cell
Cell biology
Embryonic stem cell
Transient receptor potential channel
Receptor
Gene
Embryo
Genetics
Biochemistry
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2022.03.24.485622
- https://www.biorxiv.org/content/biorxiv/early/2022/03/27/2022.03.24.485622.full.pdf
- OA Status
- green
- Cited By
- 4
- References
- 47
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4220906033
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4220906033Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1101/2022.03.24.485622Digital Object Identifier
- Title
-
Scalable Generation of Pseudo-Unipolar Sensory Neurons from Human Pluripotent Stem CellsWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2022Year of publication
- Publication date
-
2022-03-27Full publication date if available
- Authors
-
Tao Deng, Carlos A. Tristan, Claire Weber, Pei‐Hsuan Chu, Seungmi Ryu, Vukasin M. Jovanovic, Pinar Ormanoglu, Prisca Twumasi, Jaehoon Shim, Selwyn S. Jayakar, Han-Xiong Bear Zhang, Sooyeon Jo, Ty C. Voss, Anton Simeonov, Bruce P. Bean, Clifford J. Woolf, Ilyas SingeçList of authors in order
- Landing page
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https://doi.org/10.1101/2022.03.24.485622Publisher landing page
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https://www.biorxiv.org/content/biorxiv/early/2022/03/27/2022.03.24.485622.full.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://www.biorxiv.org/content/biorxiv/early/2022/03/27/2022.03.24.485622.full.pdfDirect OA link when available
- Concepts
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Nociceptor, Induced pluripotent stem cell, Dorsal root ganglion, Sensory system, Neuroscience, Neural crest, Sensory neuron, Cell type, TRPV1, Biology, Nociception, Cell, Cell biology, Embryonic stem cell, Transient receptor potential channel, Receptor, Gene, Embryo, Genetics, BiochemistryTop concepts (fields/topics) attached by OpenAlex
- Cited by
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4Total citation count in OpenAlex
- Citations by year (recent)
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2024: 1, 2022: 3Per-year citation counts (last 5 years)
- References (count)
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47Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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