Nicholas Ryba, PhD

Senior Investigator

Taste & Smell Section


Building 35A, Room 3F220
35A Convent Dr. MSC 3757
Bethesda MD 20892-3757


Research Topics

The senses provide a faithful internal representation of the external world. Dr. Ryba is interested in basic questions of sensory perception and has focused on the chemical senses, particularly taste, as a powerful platform to explore how sensory signals are detected and distinguished. For the past 20 years, in a collaborative research effort with Charles Zuker (of Howard Hughes Medical Institute and Columbia University), Dr. Ryba and his colleagues have identified the taste receptors for sweet, bitter, salty, and savory stimuli and exposed the logic of coding for all five distinct taste qualities at the level of the tongue. The group also explores how taste information is represented and encoded in the brain to help explain how this hardwired chemosensory modality triggers innate responses and behaviors.


Dr. Nicholas Ryba received his degrees in biochemistry (BA and DPhil) Oxford University, UK. He completed postdoctoral training at the Max-Planck-Institut-für-biophysikalishe-Chemie in Göttingen, Germany, and the University of Leeds, UK, working on the biophysics and molecular biology of vision. In 1991, Dr. Ryba joined NIDCR to establish an independent group studying the molecular and cellular mechanisms underlying the perception of taste and smell. Dr. Ryba’s section focuses primarily on understanding the biology of taste, but has recently started to work on other aspects of sensory biology including mechanisms involved in pain.

Selected Publications

  1. von Buchholtz LJ, Ghitani N, Lam RM, Licholai JA, Chesler AT, Ryba NJP. Decoding Cellular Mechanisms for Mechanosensory Discrimination. Neuron. 2021;109(2):285-298.e5.
  2. Nguyen MQ, von Buchholtz LJ, Reker AN, Ryba NJ, Davidson S. Single-nucleus transcriptomic analysis of human dorsal root ganglion neurons. Elife. 2021;10.
  3. von Buchholtz LJ, Lam RM, Emrick JJ, Chesler AT, Ryba NJP. Assigning transcriptomic class in the trigeminal ganglion using multiplex in situ hybridization and machine learning. Pain. 2020;161(9):2212-2224.
  4. Nguyen MQ, Wu Y, Bonilla LS, von Buchholtz LJ, Ryba NJP. Diversity amongst trigeminal neurons revealed by high throughput single cell sequencing. PLoS One. 2017;12(9):e0185543.

Related Scientific Focus Areas

This page was last updated on Thursday, November 9, 2023