Signal transduction in vertebrate photoreceptors

Fig. 1: Scanning micrograph of rod (green) and cone (blue) photoreceptors in the retina.

Vision is initiated by the absorption of light photons in rod and cone photoreceptors in the retina. Phototransduction is the multistep process by which a photoreceptor converts light into an electrical signal (for reviews see [1-3]). There are two different types of photoreceptors in the human retina: rods and cones (Fig. 1). Rods sustain the monochrome vision under dim light conditions (scotopic vision), whereas cones are responsible for the colored daylight vision (photopic vision). Rods have a remarkable property: They are so sensitive that they can reliably detect even the absorption of a single photon in darkness [4]. However, the drawback of such a high fidelity is that rods quickly saturate and become dysfunctional at daylight. Contrary to rods, cones cannot detect single photons and their light sensitivity is much reduced. Under daylight conditions vision is sustained entirely by cones. But contrary to rods, cones adapt to light and never saturate which ensures vision even under brightest light conditions.

Phototransduction still moves at the forefront of signal transduction research, and despite of intense efforts, the exact mechanisms governing the light response in rods and cones are still not fully understood. To elucidate photoreceptor functioning and to understand the impact of the biochemical pathway and the complex photoreceptor structure, our group pursues a modeling approach in combination with experimental groups (A.P. Sampath and G. Fain, UCLA ). Based on the analysis of electrophysiological data, we develop models and computer tools to simulate the photon response starting from a fundamental molecular level. Such tools are important e.g. to test molecular mechanisms responsible for pathologies involving photoreceptor degeneration (e.g. retinitis pigmentosa, loss of night vision), or to develop artificial retinas.

Modeling rod photoreceptors

Fig. 2: Polarized structure of rod and cone: Outer segment, inner segment and synaptic terminal.

The outer segment (OS) is the sensory unit of a photoreceptor where photons are absorbed and a photocurrent is generated (Fig. 2). The current is injected into the inner segment where it generates a voltage response that finally modulates vesicular release at the ribbon synapse. The rod OS has a special structure and is segmented by around 103 internal disks into narrow and almost separated compartments. The absorption of a photon activates of a rhodopsin protein located on the surface of the internal disks leading to the activation of many phosphodiesterase (PDE) molecules via a G-protein coupled amplification cascade. Activated PDE hydrolyzes cyclic GMP (cGMP), a second messenger that diffuses between the internal disks gating the opening of ion channels in the membrane. A declining cGMP concentration leads to channel closure and photoreceptor hyperpolarization. PDE fulfills two essential functions: First, the PDE that becomes activated through the G-protein cascade after a photon absorption (light-activated PDE signals the light response (Fig. 3 A-B); second, spontaneously activated PDE is necessary to maintain in darkness a steady-state cGMP concentration and to set the cGMP turnover rate (Fig. 3 C-D). Fluctuations in the number of spontaneously activated PDEs generate a background noise known as the dark noise [5]. The main source of variability of the single-photon response is due to variability in the number of light and spontaneously activated PDEs.

Mean and variance of the number of light-activated PDE

We investigated the PDE amplification gain and noise using a Markov model based on the biochemical reactions including rhodopsin deactivation via multiple phosphorylations [6]. In a mouse rod, the absorption of a photon leads in average to the activation of only around 8 PDE molecules due to fast rhodopsin deactivation within ~40 milliseconds (Fig. 3B). In contrast, a much larger rhodopsin lifetime ~2 seconds in a toad rod leads to the activation of around 100-150 PDE molecules (Fig. 3A). Contrary to common belief, a low variability of activated rhodopsin lifetime is neither necessary nor sufficient for a low variance in the number of activate PDE activation. The PDE noise depends significantly on whether PDE or rhodopsin deactivation is rate limiting [6].

Hydrolytic activity of light activated PDE

Fig. 3: PDE activation. (A) Simulations of light activated PDE after a photon absorption (black) for a toad rod together with their mean (red) and the analytic result for the mean. (B) Same as (A) but for mouse rod. (C) Simulation of the number of spontaneously activated PDE in a toad rod compartment. (D) Same as (C) but for mouse rod. (from [9])

Light-activated PDE is a highly efficient enzyme that hydrolyses cGMP with a diffusion limited rate constant. In this case the geometry of the OS strongly the cGMP hydrolysis rate. We estimated the hydrolysis rate by calculating the encounter rate between diffusing cGMP molecules in the cytosol and activated PDE molecules located in the surface of the internal disks in the confined rod geometry [7,8]. We computed a rate around 2.9s−1 for a toad rod, and much higher rate around 60s−1 for a mouse rod due to the smaller diameter of a mouse rod. Because the rate constant is so much higher in a mouse, only few light-activated PDEs per photon absorption are needed to produce a response amplitude that overcomes background noise. As a consequence, the lifetime of activated rhodopsin in a mammalian rod can be much shorter than in an amphibian rod, allowing for much faster temporal resolution in mammalian rod vision [9].

Spontaneous PDE activation and deactivation

To detect a single photon absorption, not only the amplification process has to be reliable, but also the signal has to overcome the background noise. In darkness, the major source of noise (dark noise) in a rod photoreceptor is spontaneous activations and deactivations of PDE [5]. The noise level depends on the number of spontaneously activated PDEs in a compartment. Although the PDE fluctuations increase as the mean increases, the current noise decreases because PDE hydrolyzes cGMP. More spontaneously activated PDEs reduce the dark noise level and allow for a better signal-to-noise ratio at the peak single photon response amplitude. From a power spectrum analysis of the dark noise [8], we found that in average around 0.9 PDE are spontaneously active in a single mouse compartment, which is similar to the value in toad around 1.2 [5] (Fig. 3 C-D). Such a value is indeed needed to reduce the dark noise to level where a single photon absorption with only around 5-10 % current reduction is detectable [9].

Stochastic framework to simulate a photon response with intrinsic noise

Fig. 4: Single Photon Response (A) Simulations of single photon responses in a toad rod. (B) Simulations of single photon responses in a mouse rod. (C) Recordings of single photon responses from a mouse rod. (D) Simulation of single photon response in a mouse rod with PDE density as in toad. The signal is lost in background noise. (from [9])

Next we developed a framework to simulate a single photon absorption together with the intrinsic noise [9]. Such simulations (Fig. 4 A, B) can be directly compared to experimental measurements (Fig. 4C). By assuming a transversally well-stirred OS, we reduced the full geometry to a one dimensional model where the 3D geometry is incorporated in effective parameters. In our framework, each compartment is represented by a coupled system of ordinary differential equations for cGMP and Ca2+. The compartments are coupled to each other via molecular fluxes due effective longitudinal diffusion. To simulate the intrinsic noise, we combined the system of reaction-diffusion equations with the stochastic simulations of spontaneous and light-activated PDE in each compartment (Fig. 3).

Adaption between biochemistry and rod geometry

Fig. 5: EM of toad and mouse rod.

Mammalian rods are usually much smaller compared to amphibian rods (Fig. 5) and the mammalian photon response is much faster (Fig. 4A-B). Can we generate a functional rod similar to a mammalian rod by simply shrinking the geometry of an amphibian rod. The answer is no. The biochemistry and the geometry have to adapt in order to preserve the ability of a rod photoreceptor to detect single photon absorptions [9]. Due to a higher hydrolysis rate in a smaller outer segment geometry, a mammalian rod requires fewer activated PDE molecules to produce a detectable single-photon response. Consequently, the lifetime of an activated rhodopsin molecule in a mammalian rod can be much shorter than in an amphibian rod, enabling a faster response and a shorter integration time. With an activated rhodopsin lifetime as in an amphibian rod, an abundant number of light-activated PDEs would be generated that would lead to a much prolonged single-photon response [9]. Thus, by shrinking the rod size one has also to adapt the biochemistry of rhodopsin deactivation in order to generate less light-activated PDE. However, reducing the size of the outer segment and the lifetimes of activated rhodopsin is still not sufficient to transform an amphibian into a mammalian rod. Additional adaptations in the PDE density and the catalytic activity of a spontaneously activated PDE are needed [9]. By reducing the OS size the PDE density has to be increased in order to generate sufficient spontaneously activated PDEs to maintain a low dark noise level (Fig. 4D). Indeed, the PDE density in a mouse rod is five times higher in mouse compared to toad [1]. But also the catalytic activity of spontaneously activated PDEs has to be adapted by a process that is currently unknown. If spontaneously activated PDE would have the same diffusion limited catalytic activity as light-activated PDE, the basal cGMP hydrolysis rate in a mouse would be much too high and would reduce the amplitude of the single photon response

References:

[1] E.N. Pugh Jr and T.D. Lamb. Phototransduction in vertebrate rods and cones: Molecular mechanism of amplification, recovery and light adaptation. In Handbook of Biological Physics Vol. 3, Elsevier Science B. V., Amsterdam, pages 183, (2000).
[2] F. Rieke and D. Baylor: Origin of reproducibility in the responses of retinal rods to single photons. Biophys. J., 75, 1836 (1998).
[3] M.E. Burns and V.Y. Arshavsky. Beyond counting photons: trials and trends in vertebrate visual phototransduction. Neuron, 48, 387 (2005).
[4] J. Reingruber, D. Holcman, GL. Fain: How rods respond to single photons: Key adaptations of a G-protein cascade that enable vision at the physical limit of perception, Bioessays 37(11), 1243 (2015).
[5] F. Rieke and D. Baylor. Molecular origin of continuous dark noise in rod photoreceptors. Biophys. J., 71, 2553 (1996).
[6] J. Reingruber and D. Holcman: The dynamics of phophodiesterase activation in rods and cones. Biophys. J., 94(6), 1954 (2008).
[7] J. Reingruber and D Holcman: Estimating the rate of cGMP hydrolysis by phosphodiesterase in photoreceptors. J. Chem. Phys., 129, 145192 (2008).
[8] J. Reingruber and D Holcman: Diffusion in narrow domains and application to phototransduction. Phys. Rev. E, 79(3), 030904 (2009).
[9] J. Reingruber, J. Pahlberg, ML. Woodruff, AP. Sampath, GL. Fain, D. Holcman: Detection of single photons by toad and mouse rods, PNAS 110, 19378 (2013).

Signal transduction in olfactory receptor neurons

Fig. 1: Human Olfactory Receptor Neuron scanning micrograph of a dendritic knob with olfactory cilia (from Morrison and Constanzo [1990])

The sensory domain of an olfactory receptor neuron (ORN) consists of around 15 slender cilia (less than 200 nm in diameter) embedded in a thin mucus layer on the surface of the olfactory epithelium in the nasal cavity (Fig. 1 and Fig. 2A). Odorant receptor activation in the membrane initiates a biochemical signal transduction cascade that generates a depolarizing inward current via the opening of two types of ion channels [1, 2] (Fig. 2B). The cilia terminate in the dendritic knob from where the cumulated current from all the cilia is conveyed via a dendrite to the soma where it generates action potentials. Odorant detection is challenging because it has to reliably function in a mucosal environment that is exposed to the outside world leading to ionic conditions that can vary considerably with time and can be altered by e.g. parasympathetic activity. Additional variability arises because the ORN response depends on the expressed odorant receptor (around 350 types in humans).
In addition to environmental and receptor variability, signal transduction occurs in tiny cilia where even small currents strongly affect the internal ionic concentrations and the cilia membrane potential. In such an environment currents can rapidly shift reversal potentials and thereby change electrical driving forces. Another peculiar feature of the olfactory system is the fact that signal transduction first activates CNG channels leading to Na+ and Ca2+ influx, the latter generating further excitation by gating excitatory olfactory Ca2+-activated Cl- channels, Anoctamin 2 (Ano2) [4]. Because Cl- carries up to 90% of the excitatory current in response to odors [5], it has been thought that Ano2 is the main channel responsible for amplification and odorant detection. However, this notion has been disputed recently [6] raising the puzzle what the role of the Ano2 channels and the large Cl- current might be.

Electrodiffusion model with signal transduction and ion dynamics in a cilium

Fig. 2: (A) Schematic of the olfactory epithelium, consisting of olfactory receptor neurons and supporting and basal cells. (B) A cilium with transduction components. Arrows in green and red show events for response activation and termination, respectively. R = odorant receptor, G = G-protein. (from [2])

We use modeling in collaboration with electrophysiological recordings from the group of J. Reisert (Monell Institute, Philadelphia, USA) to study the olfactory response. A key feature is to account for the complex ion dynamics (Na+, K+, Ca2+, Cl-) in the small ciliary space as a consequence of ionic fluxes between cilia, mucus and cell body. We developed a mathematical model based on electrodiffusion and Nernst potentials that accounts for the signal transduction pathway and the ion dynamics in mucus, cilia and cell body. The model takes into account the effect of CNG and Ano2 channels, and the Na+/Ca2+/K+ exchanger 4 (NCKX4) that is integral for ciliary homeostasis [7]. The simulations allow to study to what extent the ionic dynamics in the confined cilia space versus transduction pathway shape the current response.

References:

[1] Kleene, Biophys J., 33(9),839–59, 2008.
[2] Reisert, Tutorials in Mathematical Biosciences II, 1867,155–171, 2005.
[3] J. Reisert, J Gen Physiol.,136(5), 529–40, 2010.
[4] Stephan et al, PNAS, 106(28), 11776–81, 2009.
[5] Reisert et al, J Gen Physiol., 122(3), 349–63, 2003.
[6] Billig et al, Nat Neurosci., 14(6), 763–9, 2011.
[7] Reisert et al, Neuron, 45(4), 553–61, 2005.