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Modern diets contain diverse macro- and micronutrients that are differentially digested and absorbed throughout the gastrointestinal tract. The objective of this study was to determine how nutrient receptor expression varies across intestinal regions in neuropod cells, specialized sensory epithelial cells that directly relay nutritive information to the brain to regulate feeding behavior. We hypothesized that neuropod cells in distinct gut regions exhibit unique transcriptional profiles of nutrient receptors, and that these spatial patterns could be effectively conveyed through data sonification. Neuropod cells were collected from the small intestine and colon, and RNA-sequencing was performed to generate a spatial map of nutrient receptor expression. Receptor expression levels (counts per cell) served as the primary dataset. To transform these high-dimensional data into an auditory format, we applied data sonification, mapping gene expression values onto musical parameters including pitch, rhythm, timbre, and loudness. Receptors for proteins, fats, sugars, vitamins, and minerals were assigned distinct musical motifs and instrument classes, producing the composition A Nutrient Symphony. Analysis of these data revealed region-specific transcriptional signatures. As one moves from the proximal small intestine to the distal colon, neuropod cells demonstrated a marked shift in fat receptor expression, transitioning from enriched to depleted levels, which is rendered musically as a shift from violin to cello timbres. Similar auditory transitions corresponded to spatial changes in receptors for sugars, amino acids, and micronutrients, enabling listeners to perceive gene expression dynamics across gut regions. These findings demonstrate that data sonification can encode biologically meaningful spatial patterns in neuropod cell transcriptomics and provides an accessible, immersive modality for exploring complex datasets. As biological datasets expand in scale and dimensionality, sonification offers a complementary analytical and communicative tool for pattern recognition, hypothesis generation, and public engagement. Funding: This work was supported by the Arizona Biological and Biomedical Sciences graduate program (N.C.F.), and DK131403-01A1 (M.M.K.) This abstract was presented at the American Physiology Summit 2026 and is only available in HTML format. There is no downloadable file or PDF version. The Physiology editorial board was not involved in the peer review process.
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Ferguson et al. (2026) studied this question.
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