Human Sensory Neuron-like Cells and Glycated Collagen Matrix as a Model for the Screening of Analgesic Compounds
Increased collagen-derived advanced glycation end-products (AGEs) are consistently related to painful diseases, including osteoarthritis, diabetic neuropathy, and neurodegenerative disorders. We have recently developed a model combining a two-dimensional glycated extracellular matrix (ECM-GC) and pr...
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Veröffentlicht in: | Cells (Basel, Switzerland) Switzerland), 2022-01, Vol.11 (2), p.247 |
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Zusammenfassung: | Increased collagen-derived advanced glycation end-products (AGEs) are consistently related to painful diseases, including osteoarthritis, diabetic neuropathy, and neurodegenerative disorders. We have recently developed a model combining a two-dimensional glycated extracellular matrix (ECM-GC) and primary dorsal root ganglion (DRG) that mimicked a pro-nociceptive microenvironment. However, culturing primary cells is still a challenge for large-scale screening studies. Here, we characterized a new model using ECM-GC as a stimulus for human sensory-like neurons differentiated from SH-SY5Y cell lines to screen for analgesic compounds. First, we confirmed that the differentiation process induces the expression of neuron markers (MAP2,
(NeuN), and
(β-III tubulin), as well as sensory neuron markers critical for pain sensation (TRPV1,
(Nav1.7),
(Nav1.8), and
(Nav1.9). Next, we showed that ECM-GC increased c-Fos expression in human sensory-like neurons, which is suggestive of neuronal activation. In addition, ECM-GC upregulated the expression of critical genes involved in pain, including
and
. Of interest, ECM-GC induced substance P release, a neuropeptide widely involved in neuroinflammation and pain. Finally, morphine, the prototype opiate, decreased ECM-GC-induced substance P release. Together, our results suggest that we established a functional model that can be useful as a platform for screening candidates for the management of painful conditions. |
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ISSN: | 2073-4409 2073-4409 |
DOI: | 10.3390/cells11020247 |