Sensory neurons face extraordinary challenges: they have to reliably detect and amplify weakest stimuli but also remain functional up to highest intensities. To accomplish these tasks, they combine a polarized cell structure with sophisticated biophysical signaling cascades and ion dynamics. A central question in sensory physiology is how the stimulus, cellular geometry, ionic environment and the signal transduction pathway determine the neuronal response. A major impediment to a quantitative understanding of such neurons is the inherent complexity with which these determinants synergize at the cellular level. Furthermore, due to experimental limitations, it is difficult to observe and quantify molecular processes that occur in tiny compartments, e.g. the outer segment of photoreceptors or the cilia of olfactory receptor neurons.
To progress in this field, I pursue an interdisciplinary approach involving electrophysiology to record responses, biophysical modeling to understand molecular processes, mathematics for analysis and quantification, and computer simulations that incorporate the complexity and predict the neuronal response. I study how the interplay between geometry, signaling cascades and ionic environment determine the response of olfactory receptor neurons and photoreceptors. I pursue a bottom up approach where the neuronal response is derived from underlying biological models. Based on the models, I develop computer tools to simulate neurons in normal and pathological conditions.
Cellular responses require the fast activation or repression of specific genes, which depends on Transcription Factors (TFs) that have to quickly find the promoters of these genes within a large genome. TFs search for their DNA promoter target by alternating between bulk diffusion and sliding along the DNA, a mechanism known as facilitated diffusion. I use mean first passage time (MFPT) analysis to study a facilitated diffusion framework with switching between several search modes: a bulk mode and two sliding modes triggered by conformational changes between two protein conformations. In one conformation (search mode) the TF interacts unspecifically with the DNA backbone resulting in fast sliding. In the other conformation (recognition mode) it interacts specifically and strongly with DNA base pairs leading to slow displacement. From the bulk, a TF associates with the DNA at a random position that is correlated with the previous dissociation point, which implicitly is a function of the DNA structure. The target affinity depends on the conformation. Using a MFPT analysis we derived exact expressions for the MFPT to bind to the promoter, and the conditional probability to bind to the promoter before detaching when arriving at the promoter site.
Diffusion is a key regulator of the forward rate of chemical interactions. Numerous cellular processes rely on the rate at which diffusing molecules interact with each other or encounter a small target site. If the number of diffusing molecules is limited, the time to reach a small target in a confined micro-environment is often a limiting step that determines the cellular response. Furthermore, this time depends strongly on the geometry and structure of the microdomain. The narrow escape theory pioneered by D. Holcman determines how the geometry adn other diffusional properties affect the encounter rate between a diffusing ligand and its target site.
The course takes place every Wednesday from 17.15h-19.30h in room 319 at ENS, 46 rue d'Ulm, 75005 Paris. Here you can find the poster and the detailed program. For registered students there is Moodle website where they can find additional information. This is the permanent link for the online streaming .