bioRxivNeurosciencePreprint
Sweet taste receptor cells may participate in mucosal immune surveillance
Yumei QiniD, Xin Min ZhengiD, Shiyi TianiD, Robert F. MargolskeeiD, Sunil Kumar SukumaraniD
Abstract
The oral microbiome is second only to its intestinal counterpart in diversity and abundance, but its effects on taste cells remains largely unexplored. Using single cell RNASeq, we found that mouse taste receptor cells (STRCs) have a gene expression signature reminiscent of Microfold (M) cells, a central player in immune surveillance in the mucosa associated lymphoid tissue (MALT) such as those in the Peyers patch and tonsils. Administration of Tumor Necrosis Factor Ligand Superfamily Member 11 (TNFSF11, also known as RANKL), a growth factor required for differentiation of M cells dramatically increased M cell proliferation and marker gene expression in the taste papillae and in cultured taste organoids from wild type (WT) mice. Taste papillae and organoids from knockout mice lacking Spib (SpibKO), a RANKL-regulated transcription factor required for M cell development and regeneration on the other hand, failed to respond to RANKL. Taste papillae from SpibKO mice also showed reduced expression of NF-{kappa}B signaling pathway components and proinflammatory cytokines and attracted fewer immune cells. However, lipopolysaccharide-induced expression of cytokines was strongly upregulated in SpibKO mice compared to their WT counterparts. Like M cells, STRCs from WT but not SpibKO mice readily took up fluorescently labeled microbeads, a proxy for microbial transcytosis. The proportion of STRCs and other taste cell subtypes are unaltered in SpibKO mice; however, they displayed increased attraction to sweet and umami taste stimuli. We propose that STRCs are involved in immune surveillance at the taste papillae and tune their taste responses to microbial signaling and infection.
- organism: mouse
- assay: scRNA-seq
- research focus: cell type annotation
- research focus: differential expression
- research focus: cell-cell communication
- approach: statistical model
- Citations
- 0
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