Polyclonal sensory neuron derivation from iPSCs as an efficient alternative to single clone strategies for pain-relevant in vitro models
Year: 2026
Type: preprint
Abstract: Induced pluripotent stem cell (iPSC) workflows typically rely on monoclonal cultures, requiring multiple independent cell lines to compensate for clonal variability. This increases workload, cost, and limits scalability for translational applications. Here, we establish polyclonal reprogramming strategies using Sendai virus to generate clonally diverse iPSC cultures already during reprogramming through FACS, MACS, manual selection, or prolonged culture. Both monoclonal and FACS-derived polyclonal cultures reached pluripotency. Reprogramming transgenes were silenced, whereas Sendai virus (SeV) mRNA persisted across passages in both culture types; heat treatment at 38.5 °C markedly reduced SeV levels. Monoclonal and polyclonal cultures differentiated efficiently into neural crest-like cells and sensory neurons. As a second polyclonal strategy, monoclonal cultures were pooled at day-5 of sensory neuron differentiation to generate percentage-controlled progenitor mixtures. TRPA1 protein expression has not been shown reliably in iPS-derived sensory neurons. We hypothesized that increased clonal diversity might facilitate detection of TRPA1 protein expression. Despite rigorous antibody validation, TRPA1 protein expression was detectable only diffusely across the whole cell area. Together, our results show that polyclonal iPSC strategies enable clonally inclusive generation of patient-specific sensory neurons. These workflows reduce early workload and provide a robust foundation for scalable drug-screening and patient-in-a-dish applications.
Institutions: Universitätsklinikum Aachen, RWTH Aachen University
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: green
Awards: G1019523665, G1589237255, G1696875972, Verbundprojekt: BIOmetrische und BIOlogische Daten für die Diagnose und Therapie bei Schmerzpatienten (Bio2Treat) - Teilvorhaben: Stammzellmodell chronischer Schmerzen, Gewinnung biometrischer Daten und Integration mittels machine Learning, G2199443702, G2409365229, G3315347718, G3384819866, G5347424008, GRK 2416: MultiSensesMultiScales: Neue Ansätze zur Aufklärung neuronaler multisensorischer Integration, G5790310174, G7020358615, G7040511491, GRK 2415: Mechanobiology in Epithelial 3D Tissue Constructs
OpenAlex ID: W7212750759
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