Abstract
We investigated the kinetics and sensitivity of photocurrent responses of salamander rods, both in darkness and during adaptation to steady backgrounds producing 20–3,000 photoisomerizations per second, using suction pipet recordings. The most intense backgrounds suppressed 80% of the circulating dark current and decreased the flash sensitivity ∼30fold. To investigate the underlying transduction mechanism, we expressed the responses as a fraction of the steady level of cGMPactivated current recorded in the background. The fractional responses to flashes of any fixed intensity began rising along a common trajectory, regardless of background intensity. We interpret these invariant initial trajectories to indicate that, at these background intensities, light adaptation does not alter the gain of any of the amplifying steps of phototransduction. For subsaturating flashes of fixed intensity, the fractional responses obtained on backgrounds of different intensity were found to “peel off” from their common initial trajectory in a backgrounddependent manner: the more intense the background, the earlier the time of peeling off. This behavior is consistent with a backgroundinduced reduction in the effective lifetime of at least one of the three major integrating steps in phototransduction; i.e., an acceleration of one or more of the following: (1) the inactivation of activated rhodopsin (R*); (2) the inactivation of activated phosphodiesterase (E*, representing the complex G_{α}–PDE of phosphodiesterase with the transducin αsubunit); or (3) the hydrolysis of cGMP, with rate constant β. Our measurements show that, over the range of background intensities we used, β increased on average to ∼20 times its darkadapted value; and our theoretical analysis indicates that this increase in β is the primary mechanism underlying the measured shortening of timetopeak of the dimflash response and the decrease in sensitivity of the fractional response.
Introduction
In the presence of background illumination, rod photoreceptors adjust their sensitivity and response kinetics over an intensity range of several decades, and cone photoreceptors do so over an even greater range of intensities. Over the years, a number of investigators have studied the dependence of the rod's steady photocurrent and flash sensitivity on the intensity of background illumination. Other investigators have measured a shortening of the effective lifetime of cGMP (using an “IBMXjump” protocol), and a shortening of the apparent lifetime of activated rhodopsin (monitored with bright flashes) during steady illumination. In other studies, it has been reported that the amplification of phototransduction is reduced during light adaptation.
In the present work the aim of our experiments has been to investigate all of these properties in the same population of rod photoreceptors. Thus, in an ideal experiment we have attempted: (1) to measure the steady state response versus intensity relation; (2) to measure families of flash responses on a range of backgrounds, from very dim flashes (to determine flash sensitivity) up to very bright flashes (to determine the dominant time constant of recovery); (3) to measure responses to steps of isobutyl methylxanthine (IBMX), both in darkness and on backgrounds (to determine the steadystate rate constant of cGMP hydrolysis); and (4) to measure “step/flash” behavior, which permits estimation of the lifetime of activated rhodopsin. In practice, it has not been feasible to perform all these experiments on an individual rod, but, in a population of about a dozen rods recorded for up to 4 h, we were able to perform several of the procedures on each.
In a recent quantitative study of light adaptation using truncated salamander rods, Koutalos et al. 1995a,Koutalos et al. 1995b investigated the contributions of guanylyl cyclase activity and phosphodiesterase activity to the overall light adaptation behavior of the cells. One of our goals has been to extend their analysis of the steady state by focusing on the role of the phosphodiesterase activity, which we have measured using the “IBMXjump” method. Another goal has been to characterize the effects of adaptationdependent changes in the principal integrating steps of phototransduction, which include the following: the lifetime of R*; the lifetime of the active phosphodiesterase complex (PDE*); and the lifetime of cGMP, which is the reciprocal of the instantaneous rate constant of cGMP hydrolysis. As an aid to achieving these goals, we developed a molecular model of the complete set of reactions mediating transduction and adaptation, and solved the equations to obtain the steady state response versus intensity relation. In addition, we have integrated the equations numerically, so as to predict the kinetic responses and to examine the dependence of the solutions on the time constants of the principal integrating steps.
Our main conclusions are, first, that the gain of the activation steps in transduction is unaltered during light adaptation; and, second, that much of the acceleration in kinetics and desensitization of the biochemical cascade arises from the increased rate constant of cGMP hydrolysis resulting from lightstimulated PDE activity. The negative feedback loop mediated by Ca^{2+} concentration acts to prevent the suppression of circulating current that would otherwise occur and, in this way, the drop in Ca^{2+} concentration rescues the cell from the saturation that would occur in the absence of adaptational mechanisms. A preliminary and qualitative description of some of these results has been presented by Pugh et al. 1999.
Materials And Methods
Suction Pipet Recordings
Our methods for preparing isolated salamander rods and for recording and analyzing their electrical responses have been reported previously (Lyubarsky et al. 1996; Nikonov et al. 1998). The photocurrents were low pass–filtered at 150 Hz (4pole Butterworth) and sampled at 300 Hz; the delay introduced by this filtering was measured as 5.5 ms at the 50% response to a step input, and as 5.4 ms for a ramp input. All records were analyzed at full bandwidth, and are presented in the figures at full bandwidth, unless otherwise specified.
For all the experiments reported here, the rod's inner segment was drawn into a suction pipet, which recorded the circulating current, while the protruding outer segment was continually superfused with a standard amphibian Ringer's solution (Lyubarsky et al. 1996). In “IBMXjump” experiments, the outer segment was briefly exposed to a test solution containing 500 μM IBMX (a competitive inhibitor of phosphodiesterase), by rapid translation of a laminarflow boundary across the cell. This procedure was used to estimate the activity of guanylyl cyclase (and, thereby, the phosphodiesterase activity in the steady state before the jump) in the manner developed by Hodgkin and Nunn 1988.
To obtain enough information to make the required quantitative calculations for an individual rod, we found it necessary to hold the cell for at least an hour, and in the best experiments, we achieved stable recordings for >4 h. A summary of the stability of our recordings is presented in Fig. 1, which plots the amplitudes of saturating responses obtained under darkadapted conditions over the entire recording duration, for each of the nine rods that provided the core observations presented in this paper. (Data from five additional rods recorded for ∼1 h are also included in some summary figures.)
Light Stimuli
Light stimuli were monochromatic (500 nm, bandwidth 8 nm), circularly polarized, and generated via one of two optical channels: (1) a tungsten halogen lamp illuminating a grating monochromator, followed by a shutter; and (2) a xenon flash lamp (flash duration, 20 μs) filtered by an interference filter. In all experiments using backgrounds, the steady illumination was provided by the shuttered incandescent beam, and the flashes came from the xenon flash lamp. For some experiments in darkadapted conditions, the flashes were delivered using the shuttered beam, and the flash duration was 22 ms. Flash intensities (Φ) are given in estimated numbers of photoisomerizations per outer segment, calculated by multiplying the measured flux density of the flash at the image plane (in photons per square micrometer) by the estimated outer segment collecting area of 18 μm^{2} for salamander rods (Baylor et al. 1979; Lyubarsky et al. 1996). Steady intensities (I) are similarly given in photoisomerizations per second. For results taken from other investigations, we have adopted a collecting area of 20 μm^{2} for circularly polarized (or unpolarized) light, and 40 μm^{2} for linearly polarized light, as was generally used in those studies.
Light Adaptation Protocol
Darkadapted rods were exposed to steps of light of calibrated intensity for periods of ∼2 min. Beginning at least 20 s after the onset of the background, a number of test flashes were delivered at separations sufficient to allow full recovery. These were followed by a saturating flash, to determine the circulating current remaining in the presence of the background, and after recovery from this bright flash, the background was extinguished. The cycle was repeated for a series of test flash intensities, and the entire procedure was repeated for a range of background intensities. Control experiments established that the time course of the response to the saturating flash was unchanged over the epoch of the background from 20 s to 2 min. In some experiments (the step/flash protocol), a saturating flash was delivered at the instant the background was extinguished, as in Fain et al. 1989.
Numerical Integration of Equations
A complete set of equations describing transduction in the Gprotein cascade is set out in the . To solve these equations numerically, we coded the equations independently in our two laboratories, using Matlab (The Mathworks), and the programs are available at http://www.physiol.cam.ac.uk/staff/Lamb/RodSim and upon request. The solutions to both steady state and timevarying equations obtained with the two programs agreed very closely.
Simulated Responses to Steps of IBMX
To simulate responses to steps of IBMX in darkness or during steady backgrounds (for the analysis in Fig. 7), we adopted the following procedures. The value of β was reduced according to the competitive inhibition factor given in Formula A15, which specifies a time constant (τ_{I}) for equilibration of the concentration of IBMX in the outer segment with that in the perfusate. Previous experiments had shown that the time for completion of the movement of the laminar boundary across the rod is ∼100 ms (Lyubarsky et al. 1996). Therefore, we initially set τ_{I} to this value, and varied it to obtain the best fit to the earliest onset of increased current over the family of background intensities; we found that the best fit was obtained with τ_{I} = 100 ms, and so we maintained this value throughout.
To begin with, the values of all parameters were set to those of the standard rod (see ). The value of β_{Dark} for the particular rod was determined as that which provided the best fitting simulation to the IBMX step in darkness; this value invariably agreed to within 10% of that obtained using the Hodgkin and Nunn 1988 method of analysis (which is described in results). The amplification constant (A) of the rod was extracted by analysis of the rising phase of the flash response family obtained in the darkadapted state; this analysis differed from that of Lamb and Pugh 1992, in that the activation model incorporating the membrane time constant (Smith and Lamb 1997) was used. Finally, for each IBMX step in lightadapted conditions, the value of I was found that minimized the sumofsquares error between experiment and prediction over the first 200 ms of the response. From this value of I, the value of β(I) was found by substitution in Eq. B7. From the steepness of the variation in the sumofsquares error with variation in β (see Fig. 8 E), we think that our extracted estimates of β are reliable to within about ±10%.
Theory
In this section, we examine ways of quantifying the PDE activity that underlies the rod's electrical response. We show that a fundamentally important parameter that must be extracted is the fractional opening of cGMPactivated channels, which we denote as F. To estimate this parameter, we need to express the rod's response (and/or circulating current) in fractional terms. Similarly, we have found it important to express the rod's sensitivity in terms of the fractional response; as we shall show, we thereby avoid the effects of “response compression” and obtain a measure of the intrinsic biochemical adaptation.
Symbols and Terminology
The three independent variables of our analysis are t, Φ, and I, where t is the time after a stimulus delivering Φ photoisomerizations to the rod, in the presence of a steady background intensity of I photoisomerizations per second. Four important dependent variables that we will use in this section are as follows: f(t), the proportion of cGMPactivated channels open; j(t), the circulating current; r(t), the response expressed as the change in this current; and s, the sensitivity. Note that we use lowercase symbols to denote the absolute values of these dependent variables. We will now distinguish two ways of normalizing these variables, and in an effort to avoid ambiguity, we will adopt two different terms to refer to these different types of normalization, which are summarized in Table 1.
First, we will use the term “fractional” to indicate that the circulating current has been divided by its steady state value, and that the response and sensitivity have been calculated from this fractional current. We will denote these fractional parameters using the corresponding uppercase symbols J(t), R(t), and S. Furthermore, we will denote steady state values obtained on a background of intensity (I) by writing them in the form j(I), β(I), etc. Thus, the fractional circulating current is defined as J(t) = j(t)/j(I), and the fractional response as R(t) = r(t)/j(I), where r(t) = j(I) − j(t). Hence, R(t) is the complement of J(t); i.e., R(t) = 1 − J(t). The absolute sensitivity is defined as s = r(t_{peak})/Φ, in the limit of dim flashes (where, by convention, r is measured at the peak); hence, the fractional sensitivity is defined as S = R(t_{peak})/Φ.
To distinguish our second way of normalizing, we will use the term “relative” to indicate that a steady value is expressed relative to its value in darkness. Thus, the relative circulating current is J_{rel}(I) = j(I)/j_{Dark}, whereas the relative sensitivity is s_{rel} = s/s_{Dark}, and the relative fractional sensitivity is S_{rel} = S/S_{Dark}.
Fractional cGMPactivated Current and Response
The importance of expressing the circulating current (and/or the response) in fractional terms is that this immediately provides us with an estimate of the fractional level of channel opening, which in turn gives us the cGMP concentration, and (as we will show) thereby provides information about the underlying PDE activity.
The cGMPactivated opening of channels is described by the Hill relation, Formula A6, as 1 where f(t) is the absolute proportion of cGMPactivated channels open, cG(t) is the free concentration of cGMP, n_{cG} is the Hill coefficient, and K_{cG}(t) is the halfactivation concentration. The approximation on the right applies because the cGMP concentration is always much smaller than the halfactivation concentration. Hence, the fractional opening of cGMPgated channels (i.e., expressed as a fraction of the steadystate level) is defined as 2
We have adopted the symbol F for this variable for consistency with our previous notation (Lamb and Pugh 1992).
At sufficiently early times in the response to any stimulus, the Ca^{2+} concentration Ca(t) will have changed negligibly from the steadystate level Ca(I), and, therefore, it will be acceptable to regard K_{cG}(t) in Formula 2 as unchanged from the steady value K_{cG}(I), even though K_{cG}(t) will change at later times through modulation of the channels by Ca^{2+}calmodulin (see Formula A11). Accordingly, at early times in any response, the fractional opening of channels F(t) will approximate to 3
Now, provided that the cGMPactivated current j_{cG} is directly proportional to the number of channels open (i.e., independent of membrane voltage) then J_{cG}(t) = F(t), and we can write 4 where the subscript “_{cG}” has been introduced to denote the cGMPactivated component of J or R.
Formula 4 shows that, even in the presence of steady background illumination, and in the face of changes in the steady magnitude of K_{cG}(I) in different adaptational states, the fractional cGMP concentration at early times can be extracted simply by measuring the fractional cGMPactivated current; i.e., we can use R_{cG}(t) to provide a measure of cG(t)/cG(I).
In practice, a complication arises in calculating the cGMPactivated component of current j_{cG} because we can only measure the total outer segment current j_{tot}, which is the sum of j_{cG} and the electrogenic exchange current j_{ex.} Unfortunately, we do not have a direct measure of the time course of the latter (small) component, except for the special case of a strongly saturating flash. However numerical simulations (not presented) indicate that over the early rising phase of the flash response, it is adequate to ignore the time dependence of j_{ex}(t), and simply approximate it as constant; i.e., j_{ex}(t) ≈ j_{ex}(I). Thus, at early times, we can approximate the fractional response R_{cG}(t) required in Formula 4 as 5
A graphical illustration of this normalization is shown in Fig. 2 B, where a scale for R_{cG} is plotted at the right, running from zero at the steadystate level of measured current to a value of unity at the level of current reached shortly after an extremely bright flash (i.e., at the initial level of the exchange current). One needs to be aware that the approximation in Formula 5 breaks down at later times, when j_{ex}(t) changes. In view of this limitation, we will use Formula 5 to evaluate the response R(t) in Formula 4 only when we are examining the early phase of light responses. In other cases, on a slower time base, when j_{ex}(t) is expected to change substantially, we will simply determine R(t) with respect to the total current by calculating R_{tot}(t) = r_{tot}(t)/j_{tot}(I).
Relation between PDE Activity and Circulating Current
By considering the differential equation for the synthesis and hydrolysis of cGMP, Lamb and Pugh 1992 derived an expression for the flashinduced increase, Δβ(t), in the rate constant of cGMP hydrolysis, from its darkadapted level β_{Dark}, in terms of the current scaled to the dark level. Since we have now shown that a comparable scaling is applicable for steady backgrounds, rather than just in darkness, Lamb and Pugh's Equation 6.18 can be extended to the general form 6
At sufficiently early times, when F(t) ≈ 1, the final term in this expression approaches zero, so that Δβ(t) is given by the first term, in which the only variable is the fractional opening of cGMPactivated channels, F(t), which we have shown is given by 1− R_{cG}(t) (Formula 4).
The important conclusion from this equation is that, if, at sufficiently early times, it can be shown experimentally that the fractional response R_{cG}(t) has a common initial phase in the presence of different backgrounds then the initial time course of PDE activation underlying the responses must also be the same on the different backgrounds.
Relative Steadystate Current
Since F(t) expresses the channel activation as a fraction of its steadystate level, it must always start from unity. But another parameter of considerable interest is the steadystate level of channel activation in a steady background, relative to its darkadapted level, which we denote as F_{rel}(I) = f(I)/f_{Dark}. If we again assume that the circulating current j(I) is directly proportional to channel opening f(I), then we have 7
Koutalos et al. 1995b have shown that, in the steady state, the exchange current j_{ex}(I) is directly proportional to the cGMPactivated current j_{cG}(I) (see Formula A4), so that the relative steadystate current F_{rel}(I) will be the same whether Formula 7 is evaluated using j_{cG} or using j_{tot}.
Fractional Sensitivity of the Flash Response
According to our analysis above, the transduction process may be probed at the level of PDE activity by first converting the absolute response (r) to fractional response (R), and in the same way the rod's sensitivity may be corrected for “response compression” by measuring the fractional sensitivity, S = R/Φ. The sensitivity parameter that is conventionally plotted is the relative sensitivity s_{rel} = s/s_{Dark} (in the past, this has often been denoted as S_{F}/S_{F}^{D}, but we avoid that terminology here since F denotes fractional opening of channels). This measure of raw sensitivity may be converted to the fractional form S_{rel} = S/S_{Dark} simply by dividing it by the relative circulating current J_{rel}(I), because of the following relations: 8
The crucial insight is that use of the relative fractional sensitivity (S_{rel}) in Formula 8 removes the response compression that results from a reduced steadystate level of circulating current. The application of this concept will be illustrated in Fig. 5.
Results
Flash Response Families in Darkadapted and Lightadapted Conditions
Fig. 2 presents families of flash responses from one rod under four adaptation conditions: darkness, and in the presence of steady illumination estimated to produce I = 260, 810, and 2,600 photoisomerizations per second. An identical series of seven flashes was delivered in each panel, and the traces of raw response r(t) clearly show the hallmarks of light adaptation: progressive reduction in sensitivity; a decrease in time to peak of the dimflash response; and earlier recovery from a bright flash, in the presence of successively brighter backgrounds. For example, under the four conditions of adaptation, the dimmest flash suppressed 20, 4.7, 3, and 1.1 pA of circulating current, and the peak response occurred at 0.6, 0.38, 0.34, and 0.30 s, respectively. For the most intense flash, the time taken to reach 50% recovery was 12.3, 9.1, 7.8, and 6.6 s in the four conditions.
There are conflicting reports in the literature as to whether part of photoreceptor desensitization during light adaptation is brought about by a reduction in the gain of any of the “amplification” steps underlying activation of the Gprotein cascade. This has been investigated through examination of the early rising phase of lightadapted responses. On the one hand, Torre et al. 1986 and Fain et al. 1989 have reported that this early rising phase is unaltered by adaptation to weak backgrounds, even though the recovery phase occurs earlier. On the other hand, both GrayKeller and Detwiler 1994 and Jones 1995 have reported that the early rising phase of the response is attenuated, and that their results indicate a reduction in the amplification constant of transduction. Likewise, Lagnado and Baylor 1994 have reported that, in the presence of lowered intracellular Ca^{2+} concentration, the gain of activation is reduced. In view of these differences, one of the principal aims of our experiments has been to test thoroughly whether the gain of transduction is altered during light adaptation.
Invariance of the Initial Activation Phase of Phototransduction
To examine this question, it is essential (as explained in theory) to express the cGMPactivated currents (and/or responses) in fractional form. Accordingly, Fig. 3 presents results similar to those in Fig. 2, from a rod tested under six different states of adaptation, after transformation in three ways. First, we plotted the fractional cGMPactivated response, R_{cG}(t) = j_{cG}(t)/j_{cG}(I); second, we expanded the time scale by factors of ∼10 and 20fold; and third, we grouped the responses according to flash intensity rather than background. The individual panels in Fig. 3 (A–I) paint a highly consistent picture: for every flash intensity the fractional response R(t) began rising along a common trajectory independent of the state of adaptation.
It might be thought that the common initial rate of rise in Fig. 3 could be limited by the membrane time constant. However, even at the highest flash intensity (Fig. 3 I) the slope was only 12 s^{−1}, well short of the maximal slope (60 s^{−1}) previously reported for responses of nonvoltageclamped salamander rods stimulated with much more intense flashes, which has been shown to be set by the membrane time constant (Cobbs and Pugh 1987). Hence, the membrane capacitive time constant will only become limiting at even higher flash intensities than illustrated in Fig. 3.
In the theory, we drew the important conclusion from Formula 6 that the occurrence of a common rising phase for the fractional response R(t) in the presence of different backgrounds could only occur if the initial time course of the underlying PDE activation was common. Applying that insight, we conclude from the analysis of Fig. 3 that a flash of fixed intensity elicits an increment in PDE activity, Δβ(t), which initially is independent of the state of steady adaptation. We applied the same analysis to the responses of the 11 rods for which extensively averaged records were available (Table 2), and for two additional rods with less extensive data, for backgrounds suppressing up to 75% of the dark current. In all cases, behavior very similar to that in Fig. 3 was observed, with close coincidence of the early phase of the fractional response R(t) to a given flash presented on different backgrounds.
As a final point in relation to the traces in Fig. 3, it is interesting to note that the more intense the background, the earlier in time the peelingoff occurs; i.e., the earlier the deviation of the fractional response from the common initial trajectory. In a subsequent section, we show that behavior of this kind is, in fact, expected as a consequence of the increased steady rate constant of cGMP hydrolysis, β(I), whose measurement we describe shortly.
From the results for the rod in Fig. 3, we calculated the average dimflash response per photoisomerization, R(t)/Φ, in each of the six adaptational states, and we have plotted these traces in Fig. 4. For each background intensity (or darkness), we considered only those test flash intensities that elicited a fractional response R(t) of less than ∼30% at its peak, and we calculated the weighted average response per isomerization. Hence, the composite plot in Fig. 4 is broadly analogous to any of the individual panels for a fixed flash intensity in Fig. 3 (e.g., Fig. 3 D), except that it is constructed only from dimflash responses and has been scaled according to flash intensity. It is also similar to the plot in Figure 3 of Baylor and Hodgkin 1974 for turtle cones, except that the traces in that plot were not scaled according to the maximal response in each adaptation condition.
Fig. 4 extends our finding of an invariant early rise at any fixed intensity, by showing that the initial time course of the fractional response per photoisomerization R(t)/Φ is invariant. Furthermore, this figure shows that the parabolic approximation of the “activation only” model provides a remarkably accurate prediction of the response in each adaptational state, up until the time of peeling off (which is shorter in the presence of brighter backgrounds), at which point each individual experimental trace suddenly deviates from the parabola.
Absolute Sensitivity and Fractional Sensitivity during Light Adaptation
We now illustrate the method described in the theory for extracting a measure of flash sensitivity that is “corrected for response compression.” Fig. 5A and Fig. B, illustrates data from the rods of Fig. 2 and Fig. 3, respectively. The top left section of each panel (left ordinate) plots the amplitude of the rod's fractional response, R (measured at the peak), as a function of flash intensity Φ; the circles were obtained under darkadapted conditions, while the other sets of symbols correspond to different background intensities. The fractional sensitivity, S = R/Φ in the limit of dim flashes (see theory), is given by the horizontal position of the curves that have been fitted; for the darkadapted measurements in Fig. 5 A, the horizontal position gives the fractional sensitivity as S_{Dark} = 0.0036 photoisomerization^{−1}. (The fitted curves on the leftside of Fig. 5 are exponential saturation functions, but the chosen form of equation is not critical since all that is relevant to sensitivity is the horizontal positioning at dim flash intensities.) For the three backgrounds tested in Fig. 5 A, the rightward shifts of the other fitted curves from the darkadapted one give the relative fractional sensitivity S_{rel} as 0.24, 0.18, and 0.08. These rightward shifts reflect the extent of desensitization of transduction because of factors other than response compression. We shall return later to the results plotted in the lower right of each panel in Fig. 5.
Collected Measurements of Circulating Current and Sensitivity
In Fig. 6, we summarize our steadystate measurements of circulating current and sensitivity for all the rods of this study as well as for selected results from salamander rods in other investigations; in each panel, the values are given relative to the darkadapted level. Fig. 6. A presents the relative circulating current in the steady state, J_{rel}(I) = j(I)/j_{Dark}. Fig. 6 (B and C) present the relative measures of sensitivity, s/s_{Dark} and S/S_{Dark}, where s = r/Φ is the absolute sensitivity, and S = R/Φ is the fractional sensitivity, as defined in the theory. The relative sensitivity in Fig. 6 B is the parameter that usually has been plotted in previous studies, and the relative fractional sensitivity in Fig. 6 C is obtained by dividing the results in B by those in A (Formula 8). The values in Fig. 6 C are completely equivalent to the lateral shifts shown for the two illustrative cells on the left of Fig. 5, and represent the reduction in flash sensitivity after correction for response compression. Also shown in Fig. 6 are theoretical traces (continuous curves), which we will describe later.
Measurement of the Steadystate Rate Constant of cGMP Hydrolysis, β(I)
An unavoidable consequence of increasing the intensity of the steady illumination is that the steady rate constant of cGMP hydrolysis β(I) will increase, and it is our goal both to measure this increase and to show how it contributes to desensitization. To measure the steady rate constant β(I), we used the IBMXjump method of Hodgkin and Nunn 1988 with modified analysis. (We retain the conventional term rate constant to describe β, even though the value of β is not constant, but varies as a function of steady intensity and can also change dynamically during the light response.)
Fig. 7 A superimposes the fractional current recorded in response to seven repetitions of exposure of a darkadapted rod outer segment to Ringer's solution containing 500 μM IBMX. Once the current had increased appreciably, a saturating flash was delivered (with manual triggering; timing indicated by arrows), and shortly thereafter, the rod was returned to normal Ringer's solution. The responses to IBMX exposure were highly reproducible. Furthermore, no differences were observable between two traces obtained in total darkness and five traces obtained in the presence of the normal dim infrared illumination. These seven responses are shown again in Fig. 7 B on a faster time base (lowest set of traces), along with similar results collected when the rod had adapted to steady backgrounds of three intensities. In each case, the current was expressed as the fraction J(t) of the steadystate level before IBMX exposure.
Our first method of estimating β(I), which is closely similar to that of Hodgkin and Nunn 1988, is illustrated in Fig. 7 C. It is based on the assumption that a few hundred milliseconds after the solution change, the IBMX concentration within the outer segment will have risen enough to totally inhibit all the PDE activity, yet the cyclase rate α(t) will not have changed from its initial steady rate α(I). On the basis of the first of these assumptions, the term β in Formula A3 disappears, so that dcG/dt ≈ α(t), whereas on the basis of the second assumption, α(t) ≈ α(I) = β(I) cG(I), so that in conjunction with Formula 4 we can write 9
One difference between this formulation and that of Hodgkin and Nunn 1988 is that we use normalization with respect to the steady current present before the IBMX exposure, rather than with respect to the dark current.
As assumed by Hodgkin and Nunn 1988, we ignore the exchange current (i.e., we assume that j_{cG} ≈ j_{tot}), and we take the maximum value of the derivative, which occurs ∼100–200 ms after the solution change, to represent β(I). Thus, an implicit assumption of this method is that the time of occurrence of the maximal slope is late enough that the IBMX will have equilibrated, but early enough that the cyclase rate will not have changed. Accordingly, the peaks of the traces plotted in Fig. 7 C provide estimates of the steady rate constant of cGMP hydrolysis applicable in darkness and in the presence of steady adapting backgrounds. We hypothesize that the main limitation in this approach is that α is not constant after the solution change and, instead, that the increase in Ca^{2+} concentration that occurs within 200 ms can cause appreciable inhibition of guanylyl cyclase before maximal inhibition of PDE occurs, thus, leading to underestimation of the rate constant, β(I).
In an attempt to investigate this hypothesis, we numerically integrated the entire set of equations for phototransduction presented in , as described in detail in materials and methods (see Table 3 and Table 4).
Fig. 8 compares the recorded responses to IBMX steps with the predictions of the model, for two cells: the top row (Fig. 8A and Fig. B) shows the averaged traces from Fig. 7 B, whereas the bottom row (Fig. 8C and Fig. D) shows similar averaged traces from the rod of Fig. 2. The left and right columns show the predictions obtained using two assumptions for the value of the Hill coefficient of the cGMPactivated channels, n_{cG} = 2 (left) and n_{cG} = 3 (right). Inspection of Fig. 8 shows that the quality of fit of the simulated traces to the experimental traces was very good over the initial 200 ms, for each adaptational state, and this finding lends credence to the general adequacy of the theoretical framework laid out in the . Comparison of the left and right columns of Fig. 8 shows that the quality of fit was essentially unaffected by the assumed value of channel cooperativity, n_{cG}. Between the different traces, we kept all the parameters of the model (i.e., those listed in Table 4 [see ]) constant, and we varied only the intensity (I) of steady illumination to find the best fit over the initial 200 ms. Even though the fitting has been constrained only over this early phase, the theory traces generated with the model provide a reasonably good general description of the whole family of responses out to 1 s.
The estimates of β(I) obtained by the approach illustrated in Fig. 8 coincided closely with those obtained by the derivative method of Fig. 7, for IBMX jumps in darkness and in the presence of relatively dim backgrounds. However, at brighter backgrounds, the estimates from the derivative method were smaller, as would be expected if that method was compromised by a rapid change in α. Thus, for the cell illustrated in Fig. 8 A, the derivative method gave values of β(I) = 1.3, 2.0, 3.2, and 6.6 s^{−1} (in darkness and on the three backgrounds), whereas the simulation approach gave β(I) = 1.4, 1.8, 3.2, and 8.5 s^{−1} (in both cases using n_{cG} = 2). Similarly, for the rod of Fig. 8 B, the derivative method gave 0.92, 3.5, 6.6, and 11.5 s^{−1}, whereas the simulation approach gave 1.0, 3.5, 7.5, and 16.6 s^{−1}. We would emphasize that the discrepancy between the pairs of estimates of β(I) at higher intensities was not caused by failure of the theory curves to describe the experimental recordings. Indeed, the maximum slopes of the respective experimental and simulated traces agreed closely with each other. Instead, the simulations indicated that, by the time that the maximal slope was attained (150–200 ms), α(t) had declined to ∼70% of its initial steady level α(I), so that the approximation underlying Formula 9 was compromised. Hence, we conclude that the derivative method underestimates β(I) at higher intensities, and that for these backgrounds, the method of fitting simulated responses is more accurate.
It is possible to investigate this conclusion, and the underlying basis of the effect, by considering the predicted behavior of our model rod to a step of IBMX when changes in Ca^{2+} concentration are prevented. These simulations gave predicted responses (dotted traces in Fig. 8) that followed purely accelerating trajectories. When we compared the maximal slope predicted by the full model with the slope at the corresponding time predicted by the calciumclamped model, we found only a slight difference in darkness or with a dim background, but a considerable discrepancy when the background was bright. On the assumption that such differences in the model calculations genuinely reflect the behavior of real rods, we conclude that the primary shortcoming in the derivative approach stems from the dynamic change in Ca^{2+} concentration that accompanies exposure to IBMX.
A more intuitive (and less modeldependent) way to arrive at the same conclusion can be obtained by considering a straightforward approximation. If we take the cyclase activity under calciumclamped conditions to be constant at the steadystate level determined by the background, and then integrate both sides of Formula 9, we obtain an analytical prediction for the IBMXjump response as t≈1+It^{ncG}. This is a continually accelerating function of time that closely approximates each of the dotted traces in Fig. 8. Importantly, it is the trajectory that the response of the real rod would need to follow, if the derivative method of Formula 9 were to give the correct value for β(I). And since the slope of the real rod's response is considerably smaller than the slope of this trajectory for brighter backgrounds, we again conclude that the derivative method underestimates β(I).
Collected Measurements of the Rate Constant of cGMP Hydrolysis, β(I)
We now summarize in Fig. 9 the estimates of β(I) obtained with the derivative method (Formula 9), both from this study (closed symbols) and from previous investigations (open symbols). All estimates were obtained with an assumed Hill coefficient of n_{cG} = 2, and to a good approximation the equivalent values for n_{cG} = 3 can be obtained simply by scaling all the points down to two thirds of their plotted values. In addition, at the higher intensities, we have also shown the estimates of β(I) determined by the fitting method of Fig. 8. Each of these estimates is shown at the upper end of a vertical arrow from the corresponding point obtained with the derivative method, which, as explained above, is expected to provide an underestimate of the true value of β(I). The results in Fig. 9 show that, for an assumed channel cooperativity of n_{cG} = 2, the estimate of β(I) increases from ∼1 s^{−1} in darkness to 10–20 s^{−1} for steady illumination of 1,000–2,000 photoisomerizations per second, which (as shown by Fig. 6) suppresses 60–70% of the circulating current. We have intentionally not normalized β(I) to its dark level, for reasons that will become apparent later.
In subsequent sections, we will investigate the contribution of this increase in β(I) to the desensitization of the flash response observed during light adaptation, and we will also investigate the role that it plays in the earlier “peeling away” of the flash responses from the common initial trajectory, which is observed with more intense backgrounds. But before doing so, we need to quantify any adaptational changes that occur in the other two major recovery processes: the mean lifetime of activated rhodopsin (τ_{R}) and the mean lifetime of activated PDE (τ_{E}).
The Mean Effective Lifetime of Activated PDE during Light Adaptation
Previous investigations have shown that the “dominant” time constant in recovery of the brightflash response (i.e., the slowest time constant) is virtually unaffected by light adaptation or by cytoplasmic Ca^{2+} concentration (Pepperberg et al. 1992, Pepperberg et al. 1996; Lyubarsky et al. 1996; Murnick and Lamb 1996; Nikonov et al. 1998). Nikonov et al. 1998 have reviewed the evidence and concluded that this time constant corresponds to the mean lifetime of activated PDE, denoted as τ_{E}.
The method for estimating the magnitude of the dominant time constant is illustrated by the points in the bottom right section of the two panels in Fig. 5. The measurements plot the time taken for recovery to a criterion level of circulating current (of 50% in Fig. 5) after saturating flashes of different intensity, which were presented either in dark or lightadapted conditions. When the flash intensity is plotted on a logarithmic scale, as in Fig. 5, then a straight line relationship is consistent with firstorder removal of a substance that is produced in proportion to light, and the slope of this line is directly proportional to the time constant of removal. Hence, the straight, and broadly parallel, results in Fig. 5 A are consistent with firstorder removal, with a time constant that appears independent of adapting intensity (1.6 ± 0.2 s, mean ± SD). In Fig. 5 B, the points at each background fall along a straight line, but the slope of the line appears to decline as the background intensity increases, indicating a reduction in the size of the dominant time constant at higher levels of adaptation. Our collected measurements are presented in Fig. 11, and will be described shortly.
Measurement of the Effective R* Lifetime during Light Adaptation
Fig. 10 illustrates an experiment of a type introduced by Fain et al. 1989 that has been hypothesized to measure the change in effective lifetime of R* elicited by adaptation to backgrounds (Matthews 1996, Matthews 1997; Murnick and Lamb 1996). The protocol, which we refer to as a “step/flash” experiment, is illustrated in Fig. 10 A. The rod was exposed to a saturating flash, either in darkness (top set), or synchronously with the extinction of a background that had been applied for 20 s (bottom sets). In this particular experiment, three different intensities of saturating flash were used (indicated by a, b, and c), in conjunction with backgrounds delivering I = 0, 370, 1,200, or 3,700 photoisomerizations per second.
As reported by Fain et al. 1989, recovery of the saturating response to any criterion level is accelerated when the flash is preceded by background illumination. For the brightest flash (c) in Fig. 10 A, the extent of this step/flash acceleration is illustrated graphically by the horizontal arrows that have been drawn from the vertical line that marks the time to 50% recovery in the absence of any preceding exposure to a background. In this case, the shifts for the three backgrounds were measured as ΔT_{50} = 2.3, 2.9, and 3.7 s, where the symbol ΔT_{50} denotes the shortening of recovery time measured at the 50% criterion level.
By examining the other test flash intensities, and other criterion levels of recovery, we found that the measurements of step/flash acceleration were quite robust. For the intermediate flash intensity (b), the corresponding shifts for the three levels of adaptation were ΔT_{50} = 2.1, 2.5, and 3.0 s, broadly comparable to (but 10–18% shorter than) the values obtained with the strongest flash. Similarly, at a criterion level of 20% recovery, the shifts were ΔT_{20} = 2.0, 2.6, and 3.1 s for flash b, and 2.3, 3.0 and 4.0 s for flash c. The relatively small size of the variations indicates that the shape of the recovery phase is similar at different intensities of saturating flash, but simply shifted in time, and that the dominant time constant of recovery is at most only weakly affected by background illumination. In the following analysis we will neglect such variations. Fig. 10 B presents the shift ΔT_{50} as a function of adapting intensity, for six rods from this study and for the rod in Fain et al. 1989 Figure 8. The theory traces in Fig. 10 B will be described shortly.
By making several assumptions, it is possible to convert the shifts obtained in the step/flash experiments into changes in the effective lifetime of R*. The first two assumptions are expressed in Formula A1 and Formula A2 of A, which specify that the activities of R* and E* each decline as firstorder processes, with time constants τ_{R} and τ_{E} at a given level of adaptation. The third assumption is that τ_{E} is independent of background intensity, a matter that we examine in Fig. 11. The final assumption is that τ_{E} > τ_{R}. This last assumption restates our view, set out in the previous section, that τ_{E} represents the dominant time constant of recovery, and can therefore be estimated from the slope of the plot of recovery time versus logarithm of flash intensity, of the kind illustrated in Fig. 5.
The practical meaning of these assumptions is that, when measured at times much greater than τ_{R}, the state of activation underlying the saturating flash response declines as an exponential with time constant τ_{E}, from an initial level that is directly proportional to the time constant τ_{R}. Hence, if τ_{R} changes from its darkadapted value of τ_{R, Dark} then the induced shift in recovery time ΔT is given to a good approximation by the exponential relation 10
Analysis of the exact form of the solution to Formula A1 and Formula A2, given by Nikonov et al. 1998, shows that the approximation involved in Formula 10 is very accurate when τ_{E} is much greater than τ_{R, Dark}, as is the case in the salamander rod, where τ_{E} = 1.5–2.7 s and τ_{R, Dark} ≈ 0.4 s, and we therefore adopt Formula 10 in the estimation of τ_{R}. The extracted values are presented in the next section along with those of the other two time constants of recovery.
It is worth mentioning that, even if the assumption of firstorder decline in R* activity is not correct, the ratio calculated in Formula 10 (and plotted in Fig. 11 A) remains useful. Provided that the R* activity declines much more rapidly than the PDE time constant τ_{E}, the factor exp(−ΔT/τ_{E}) will represent the light to darkadapted ratio of the integrated R* activity, ∫R*(t) dt.
To compare the shifts measured in the step/flash experiments with theory, we include in Fig. 10 B two traces generated with our model of recoverin's interaction with RK. The traces were generated by solving the steady state, including the equations of C, and then substituting the values of τ_{R}(I)/τ_{R,Dark} from Formula A12 into Formula 10 above to obtain ΔT. We used two values of τ_{E} corresponding roughly to the upper and lower range of estimates obtained in Table 2: τ_{E} = 2.4 s (Fig. 10 A, top trace) and 1.6 s (Fig. 10 A, bottom trace). Comparison of these traces with the symbols in Fig. 10 B shows a general correspondence between the predicted shifts and the estimates of τ_{E} (Table 2). Thus, rod f (▾, τ_{E} = 2.7 s) exhibited the largest shifts, whereas rod b (▪, τ_{E} = 1.5 s) exhibited the smallest.
Dependence of the Three Principal Time Constants of Recovery on Adaptation Level
In Fig. 11, we present our collected measurements of the three principal time constants governing the recovery phase of salamander rod phototransduction as functions of the intensity I of steady background illumination. The estimated lifetimes of R* and E* have been plotted relative to their darkadapted levels, as τ_{R}/τ_{R, Dark} (A) and τ_{E}/τ_{E, Dark} (B). But, for the lifetime of cGMP (C), we plotted 1/β without normalization to the darkadapted level. Our reason for not doing so is that β_{Dark} appeared to vary from cell to cell in a manner unrelated to the lightactivated PDE activity. Thus, in Fig. 9, β_{Dark} exhibited a range of nearly fourfold, whereas at backgrounds in the neighborhood of I = 1,000 photoisomerizations per second, the range of β(I) was only slightly greater than twofold.
Fig. 11 B shows that the E* lifetime τ_{E} is at most only weakly dependent on background intensity, with the estimates for most rods decreasing by 20–40% for backgrounds producing >500 photoisomerizations per second (see also Fig. 5 B). We are uncertain whether this apparent decline in τ_{E} is a true reflection of an underlying mechanism or whether it is due in some way to the limitations of the method of analysis.
In contrast to the modest and somewhat irregular decline in the estimate of τ_{E}, all rods exhibited a systematic decline in the estimate of τ_{R} beginning at the lowest backgrounds and reaching three to fivefold at the highest backgrounds. One of the assumptions underlying the calculation of τ_{R}/τ_{R, Dark} is that τ_{E} is independent of background intensity, and, as discussed above in relation to Fig. 11 B, this assumption may not be strictly correct. If the time constant τ_{E} does decrease with increasing background intensity then the values of τ_{R}/τ_{R, Dark} that we have extracted will be underestimates; i.e., the true reduction in τ_{R} will not be as pronounced as suggested by Fig. 11 A. The curve in Fig. 11 A plots the predictions of a model of recoverin's calciumdependent inhibition of rhodopsin kinase that will be considered in the discussion and C.
In comparison with the modest changes shown in Fig. 11 (A and B), the reduction in the time constant of cGMP turnover, 1/β that is plotted in Fig. 11 C is much greater, declining by ∼20fold at backgrounds of 2,000 photoisomerizations per second. Hence, for the three inactivation reactions of phototransduction, the crucial message of Fig. 11 is that, in the transition from dark to lightadapted conditions, the change in the mean lifetime is modest for R*, small for E*, and major for cGMP.
Significance of the Altered Time Constants
To assess the effects of the changes in the time constant on response kinetics and flash sensitivity, Fig. 12 presents the responses of the rod of Fig. 2 (Table 2, rod a), along with theoretical traces computed using the model set out in the . The responses have been normalized in the manner of Fig. 3. Thus, we plotted the fractional cGMPactivated current J_{cG}(t) = j_{cG}(t)/j_{cG}(I) according to Formula 5, which assumes that the component j_{ex} of Na^{+}/Ca^{2+}K^{+} exchange current does not change appreciably over this time scale (Fig. 2). To concentrate on the steadystate effects induced by the backgrounds, rather than on any dynamic changes elicited by the test flashes, we have restricted examination to the first 250 ms after the flash. And likewise, to concentrate on the steady state rather than dynamic predictions of the model, the theoretical traces have been computed under calciumclamp conditions. Thus, the steady state of the model has been computed as described in B, to generate the parameters Ca(I), τ_{R}(I), β(I), etc., and thereafter the simulated flash response has been computed with Ca(t) held at Ca(I). This is equivalent to an experiment in which the rod first adapts to a background in Ringer's, and is then exposed to a calciumclamping solution, during which period it is tested with flashes.
Comparison of the experimental and theoretical traces in Fig. 12 (A–D) shows that, on the whole, the model provides a good account of the early phase of each family of flash responses. To assist in evaluating the significance of the steadystate changes, we present two additional panels (Fig. 12E and Fig. F). Fig. 12 E superimposes all the traces presented in A–D, reconfirming that (irrespective of background intensity) the fractional responses to each flash intensity do indeed begin rising along a common trajectory; however, they peel off earlier as the background intensity increases. Likewise, Fig. 12 F superimposes the theoretical traces from A and D, emphasizing the extent of change in predicted kinetics between the two extreme states of adaptation: darkadapted (continuous traces), and on a background of 2,600 photoisomerizations per second (dashed traces). Since we have eliminated any dynamic (i.e., flashinduced) change in parameters from these simulations, and since the steadystate changes in cyclase activity are accounted for in the procedure of normalization to fractional cGMPactivated current, we conclude that the peelingoff behavior observed in the simulations on this time scale is mediated entirely by steadystate changes in β(I) and τ_{R}(I).
To further assess the effects of altered β(I) and τ_{R}(I) on response kinetics and sensitivity, we reexamined previous experimental work in which Ca^{2+}_{i} was clamped after adaptation to background illumination. The results from Figure 10 B of Fain et al. 1989 are replotted here in Fig. 13 (noisy traces) and are compared with the predictions of our equations (smooth traces). In their experiment, dim flashes were delivered during exposure to calciumclamping solution that was presented after the rod had equilibrated either to darkness (Fig. 13 A) or to a background of 96 (Fig. 13 B) or 2,100 photoisomerizations per second (Fig. 13 C). The theory traces are simulations obtained as described above, with Ca^{2+}_{i} clamped to the level determined by the steadystate solution for the three cases, i.e., darkness, 580 nM; dimmer background, 400 nM; and brighter background, 150 nM (see legend for details).
We think it impressive that the general form of agreement between simulation and experiment is so close under these conditions of calcium clamp. In considering this behavior, it is important to note that the pronounced acceleration of response kinetics in the presence of the background occurs in spite of the prevention of dynamic (i.e., responseinduced) changes in Ca^{2+}_{i}, both in experiment and simulation. Thus, the time to the peak of the experimental responses decreases from 2.4 s in darkness (Fig. 13 A) to 1.2 s on the dimmer background (Fig. 13 B) and to 0.7 s on the brighter background (Fig. 13 C), purely as a result of steadystate changes in transduction parameters. Less obvious in Fig. 13, but equally important, is the fact that the fractional sensitivity of the response also declines, despite the clamping of Ca^{2+}_{i} to its steady level. To appreciate this desensitization, it is necessary to note that the test flash intensity increased in the ratio 1:4:25 in the three panels of Fig. 13; measurement of the peak amplitudes indicates that the relative fractional sensitivity S_{rel}(I) (defined in Formula 8) declined in the ratio 1:0.23:0.027.
The effects of the decline in the time constants τ_{R}(I) and 1/β(I) on fractional sensitivity and kinetics can be approximated by the convolution of three firstorder decay reactions, where two of the time constants change with adaptation while τ_{E} remains constant. This corresponds closely to one formulation of the effects of adaptation considered by Baylor and Hodgkin 1974 for turtle cones, except that only three time constants are involved here, and each is explicitly identified with a molecular step in the phototransduction cascade. As in the analysis of Baylor and Hodgkin 1974, a backgroundinduced reduction in the time constants of inactivation reactions leads to desensitization and acceleration of recovery kinetics. We will examine this matter further in the discussion, in the context of considering all the factors contributing to desensitization.
Discussion
Photoreceptor light adaptation encompasses a complex set of molecular changes by which the cell adjusts to the ambient level of illumination. One manifestation of light adaptation is an extension of the range of intensities over which the cell is able to operate (Torre et al. 1995) beyond the restricted range that would apply as a result of the exponential saturation that occurs in the absence of adaptational changes (Matthews et al. 1988). A second manifestation is the gentle decline in flash sensitivity, according to Weber's Law, which is typically observed over the cell's operating range (Fig. 6 B). Our aim has been to account for these phenomena through a molecular model that we can express in quantitative terms, and for which most of the parameters can be measured. The primary new interpretations of our work are that light adaptation is characterized by the following: (1) an invariant gain of the amplifying steps; (2) a large reduction in the time constant of cGMP hydrolysis, which provides the dominant factor in desensitization of the biochemical cascade; and (3) a smaller reduction in the lifetime of activated rhodopsin. In addition, it is well known that guanylyl cyclase is activated, and that the K_{1/2} of the cGMPgated channels is reduced. Here, we emphasize that these two calciumdependent phenomena act to sensitize (rather than desensitize) the response, by preserving an appropriate working level of circulating current.
Koutalos et al. 1995a,Koutalos et al. 1995b undertook a similar examination of range extension and sensitivity adjustment in salamander rods during light adaptation. They identified, and quantified, the roles of three calciumdependent molecular processes: (1) the activation of guanylyl cyclase; (2) the “down regulation of PDE activity,” which they identified as including recoverindependent and nonrecoverin–dependent components; and (c) modulation of the K_{1/2} for cGMPgating of the channels. We shall compare their results and interpretations with ours as we proceed.
Light Adaptation Does Not Alter the Gain of the Amplifying Steps of Phototransduction
Our results strongly support the conclusion that there is no change in the gain of any of the amplifying steps in phototransduction at the intensities and durations of light adaptation used in our experiments. The theoretical basis for this assertion comes from the analysis underlying Formula 6, which shows that, if the fractional response is invariant at early times, then the initial time course of flashactivated PDE activity must be common. Hence, the empirical test is provided by experiments in which flash responses are scaled as the fractional change in cGMPactivated current. These experiments show that all the scaled responses to a flash of any given intensity initially follow a common trajectory, independent of background illumination (Fig. 3 and Fig. 12 E), and, more generally, that the scaled responses to all flashes begin rising along a single trajectory when they are further divided by the test flash intensity (Fig. 4). Thus, the results of Fig. 4 place on a solid foundation the suggestion made previously by Torre et al. 1986(Figure 5) and Fain et al. 1989(Figure 10) for just one or two background intensities. Therefore, our experiments show that, during light adaptation, the activation phase of transduction is unaltered at the level of the Gprotein cascade, and that what changes is instead the time of onset of recovery. This conclusion is further supported by simulation of the equations that describe the entire cascade (see ). These simulations accurately describe the observed responses over the first 250 ms, on the assumption that there is no change in the amplification constant A of phototransduction during light adaptation (Fig. 12, A–D).
Our conclusion that the amplification of phototransduction is unaltered by adaptation is at variance with conclusions drawn by several other investigators, who have reported that the early rising phase of the response is reduced by adaptation (GrayKeller and Detwiler 1994; Jones 1995) or by lowered Ca^{2+} concentration (Lagnado and Baylor 1994). We think that a major factor contributing to these previous interpretations has been a lack of appreciation of the magnitude of the reduction that occurs in the inactivation time constants, on backgrounds of moderate to high intensity. Thus, on a background that halves the circulating current of a salamander rod, we predict that two of the inactivation time constants, τ_{R} and 1/β(I), will each have declined to ∼150 ms, so that deviations from a common early rise will be expected to occur by ∼100 ms. Hence, the observation of a lowered slope of the rising phase at times later than this does not indicate a reduced amplification constant.
An additional factor that may explain the apparent difference between our interpretations and those of Lagnado and Baylor 1994 is that their reported K_{1/2} for the Ca dependence of the effect was 35 nM, whereas we think it likely that, in our experiments, the steady Ca^{2+} concentration remained much higher than this level. For our brightest backgrounds, of 2,000–3,000 photoisomerizations per second, the steady circulating current was reduced to roughly 20% of its darkadapted level, so that the steady Ca^{2+} concentration ought to have been reduced to a comparable fraction, i.e., to ∼120 nM. At such a concentration, the mechanism they describe would be expected to reduce the gain by only a small amount (<10%).
Elevated Phosphodiesterase Activity Evoked by Steady Light
We have made new measurements, and provided further understanding, of the lightevoked increase in steady PDE activity, which we have quantified through the steadystate rate constant β(I) of cGMP hydrolysis. First, we have been able to estimate β(I) at higher intensities than previously (up to 2,600 photoisomerizations per second) by comparing the predictions of our mathematical model with the results of experiments performed using the IBMXjump method of Hodgkin and Nunn 1988 (Fig. 8). Use of this theoretical approach provides estimates of β(I) that we think should be more accurate than those obtained using the conventional derivative method; that method yields underestimates of β(I), as a result of the rapid decrease in guanylyl cyclase activity, α, elicited by the massive rise in cytoplasmic Ca^{2+} concentration that inevitably accompanies the IBMXinduced opening of cGMPgated channels. Second, we have provided (in Eq. B7) a formulation for the dependence of β(I) on fundamental parameters of the cascade, as 11 where τ_{R}(I) is the effective lifetime of R* in the presence of the background, τ_{E} is the effective lifetime of G*E*, A is the amplification constant of transduction, n_{cG} is the Hill coefficient of channel activation, and I is the intensity of steady light. Third, we have shown that this relatively simple expression provides a good account of the experimentally measured dependence of β(I) on steady light (Fig. 9). Fourth, we have shown that the darkadapted rate constant of cGMP hydrolysis (β_{Dark}) appears to exhibit greater variability from cell to cell than does the lightstimulated increase in β(I). Therefore, we suggest that β_{Dark} is determined by factors other than, or additional to, the four that scale the intensity in Formula 11. Fifth, we have extended the analysis of Nikonov et al. 1998, which showed that in darkness 1/β_{Dark} acts as one of the time constants of recovery in the transduction cascade, to the general case, by showing that 1/β(I) plays the same role during light adaptation (Fig. 12). Finally, we have established that, of the three main time constants in the cascade, 1/β is the one that undergoes the greatest change during light adaptation (Fig. 11).
Our Formula 11 above is closely analogous to the expression for PDE activation used by Koutalos et al. 1995b in their Formula 2 and Formula 4. The difference is that their formulation used the single calciumdependent parameter β*(Ca) to express the light dependence of PDE activity, whereas we use the composite term Aτ_{R}(I)τ_{E} /n_{cG}, which comprises four parameters, each of which has a defined physical meaning and can be estimated independently. Since we have provided evidence that A is constant and that τ_{E} is, at most, weakly dependent on adaptation, and since we have no reason to suspect a change in n_{cG}, the calcium dependence of β* expressed in their (Koutalos et al. 1995b) Formula 2 should correspond to the calcium dependence of τ_{R} in our formulation; this is specified in Formula A12 and C.
Inspection of Fig. 9 shows that there is an approximately fourfold difference between our description and that of Koutalos et al. 1995b for the predicted dependence of β(I) on I. Thus, at a background of 1,000 photoisomerizations per second (∼50 photons μm^{−2} s^{1}), the Koutalos et al. 1995b description gives β(I) ≈ 2.5 s^{−1}, whereas our description gives β(I) ≈ 10 s^{−1}. In addition, there is a smaller discrepancy in the darkadapted value in the two cases: Koutalos et al. 1995b reported β_{Dark} ≈ 0.3 s^{−1}, whereas our experiments gave 0.8–1.6 s^{−1}. These differences are illustrated by the lower curves in Fig. 9: the dotted traces plot the predictions of Formula 2 from Koutalos et al. 1995b, who considered two possible levels of dark calcium concentration. These curves significantly underestimate the measurements of β(I) versus I made not only in our study, but also by Hodgkin and Nunn 1988 and Cornwall and Fain 1994.
Contribution of Individual Molecular Mechanisms to Overall Adaptational Behavior
The effect of increasing background intensity is to increase the steady rate constant of cGMP hydrolysis, β(I), thereby lowering the cGMP concentration, and driving the photoreceptor towards saturation. In our view, the primary function of “adaptation” is to prevent the rod from being driven into saturation, thereby preventing the massive reduction in sensitivity that would otherwise occur. Three molecular mechanisms are known to help the rod evade saturation, and each is calciumdependent: (1) the GCAPdependent activation of guanylyl cyclase (“GCAP mechanism”); (2) the recoverindependent increase in rhodopsin kinase activity (“Rec mechanism”); and (3) the calmodulindependent decrease in the K_{1/2} of the cGMPactivated channels (“CaM mechanism”).
In an attempt to evaluate the relative importance of these mechanisms in the maintenance of circulating current and sensitivity, we provide in Fig. 14 a series of calculations for the model rod in which the three mechanisms are either present or absent in all combinations. In considering the following analysis, it is important to bear in mind that we are not performing direct experimental manipulations, but that we are instead investigating the performance of our model when we manipulate it in ways designed to simulate alterations in the presumed molecular mechanisms. Nevertheless, we think that important lessons can be learned.
A, B, and C (Fig. 14) present the predictions for steadystate current, sensitivity, and fractional sensitivity, respectively, in the format of Fig. 6, with the following color coding. In each case, blue denotes the CaM mechanism alone; green denotes the Rec mechanism alone; and red denotes the GCAP mechanism alone. The other three colors denote paired combinations of these mechanisms: CaM + Rec (cyan); CaM + GCAP (magenta); and Rec + GCAP (yellow). Black denotes the case with none of the mechanisms enabled, whereas dark gray denotes the normal case with all three mechanisms active. In accordance with the conclusions of Koutalos et al. 1995b, and as we discuss below, the curves in Fig. 14 (A and B) are consistent with the idea that the most potent of the calciumdependent adaptational mechanisms is the activation of GC, and that the least potent is the CaMdependent shift in K_{cG} of the channels.
In Fig. 14 A, an additional ordinate scale is provided for Ca(I), since the steadystate calcium concentration is uniquely determined by the steady circulating current. At any fixed level of calcium, one can think of the rightward shift of each curve relative to the leftmost curve as the predicted effect of that mechanism (or combination of mechanisms) in extending the intensity range over which the cell can operate at that particular calcium level.
Contributions to Absolute Sensitivity and Fractional Sensitivity
Since light adaptation leads to reduced flash sensitivity, one might naively hope to determine the contribution of the individual molecular mechanisms to the overall desensitization that is observed, but such a division is fraught with difficulty. The problem arises because the feedback loop underlying photoreceptor light adaptation leads to the prevention of sensitivity loss, rather than to desensitization per se. Hence, as illustrated in Fig. 14, the role of each of the calciummodulated feedback mechanisms is to sensitize rather than desensitize the cell. To appreciate this, one needs to consider a vertical line drawn on Fig. 14B at any arbitrary intensity: the vertical spacing between the traces then gives the predicted effect of that mechanism (or those mechanisms) on sensitivity at the particular background level.
For example, imagine a steady background of 1,000 photoisomerizations per second in Fig. 14 B, and consider the predicted effect of separately disabling the three individual mechanisms. With all mechanisms functional, the relative sensitivity of the model rod is calculated as 0.032 (gray trace); with the CaM mechanism disabled, it should be indistinguishable from this, at 0.032 (yellow trace); with the Rec mechanism disabled, it should be down to 0.0136 (magenta trace); and with the GCAP mechanism disabled, it should be greatly depressed, to 0.0031 (cyan trace). Hence, the model predicts that, at this intensity, the CaM mechanism has negligible effect on sensitivity, whereas the Rec and GCAP mechanisms sensitize the rod by factors of 2.3fold and 10fold, respectively (in each case with respect to the situation where the mechanism is disabled).
In a similar manner, one can assess the predicted contributions of the different mechanisms to the fractional sensitivity plotted in Fig. 14 C. In comparing B and C in Fig. 14, perhaps the most prominent feature is the tight grouping of the traces in C compared with the wide spacing in B. For a line drawn at 1,000 photoisomerizations per second in Fig. 14 C, the solid curves are separated vertically by a factor of <2. This tight grouping means that our model predicts the “biochemical sensitivity” of the cascade at this fixed intensity to be barely affected by the presence or absence of the different molecular mechanisms. How might mechanistic insensitivity of this type come about?
Desensitization of the Biochemical Cascade: Kinetic Roles of β(I) and τ_{R}(I)
The decline in fractional sensitivity in Fig. 14 C must be caused by changes in the kinetics of inactivation of the biochemical response, i.e., by the shortening of the time constants of the signal integrating steps of the cascade (with possible contributions by dynamic feedback through the flashinduced change in Ca^{2+}_{i}). That this is so, may be seen from the fact that the rising phase of the fractional response R(t), and hence of ΔcG(t)/cG(I), is unaffected by the presence of background illumination (Fig. 3, Fig. 4, and Fig. 12). Hence, the decline in S, which is measured at the peak of the response, occurs because the time to peak becomes shorter. In the same way, the theoretical traces in Fig. 14 C reflect the reductions in biochemical sensitivity predicted to result from accelerated recovery kinetics, whereas the traces in Fig. 14 A reflect the timeinvariant reductions in sensitivity predicted to result from response compression, and the two sets of traces multiply together to yield the overall reductions in sensitivity predicted in Fig. 14 B.
Our simulations further support the conclusion that dynamic calcium feedback contributes little to the decline in relative fractional sensitivity. Thus, the dotted curve in Fig. 14 C computed for a rod with Ca^{2+}_{i} clamped (to the level set by a background presented in Ringer's) lies very close to the gray curve obtained for a rod operating normally in Ringer's, with Ca^{2+}_{i} free to change dynamically. Thus, we are led to the conclusion that the primary factors contributing to the decline in fractional sensitivity are the declines in the two time constants, τ_{R} and 1/β(I) (Fig. 11 and Fig. 13). The tight “bunching” in Fig. 14 C indicates that, in the presence of the normal drop in steadystate Ca^{2+}_{i}, the combined effect of the reductions in these two time constants in the model rod is computed to be roughly the same, irrespective of the combination of mechanisms enabled. Thus, in a case where a greater reduction in τ_{R} occurs, there is a smaller increase in β, and, hence, a smaller reduction in 1/β, so that the resulting time course is quite similar.
A slight exception to this trend occurs for the green trace (Rec mechanism alone), which differs significantly from the other traces at relatively dim backgrounds. This occurs because, when both the other feedback mechanisms are disabled in our model, the Rec mechanism is brought into play at relatively low intensities, and the shortening of R* lifetime causes a more pronounced reduction in biochemical sensitivity than occurs in the full model.
Relative Importance of β(I) and τ_{R}(I) in the Normal Case
To assess the relative importance of the increased PDE rate constant of cGMP hydrolysis (β) and the Recmediated shortening of R* lifetime (τ_{R}) in mediating the observed reduction in fractional sensitivity in the normal case, we now consider the effect of the altered time constants in a cascaded chain of integrating stages. Thus, we consider the dimflash approximation derived by Nikonov et al. 1998(see their Equation 19) under calciumclamped conditions that comprises a cascade of three time constants: τ_{R}(I), τ_{E}, and 1/β(I).
The two dashed traces in Fig. 14 C investigate the predicted contributions to the normal case of changes in 1/β alone and in τ_{R} alone. For these two traces, one of the time constants has been held at its darkadapted level, while the other has been varied according to the predictions of the full model. Clearly, neither of these situations can occur in reality, and we present them purely in the context of attempting to separate the contributions of the two time constants to the normal behavior. These traces show that the contribution of 1/β(I) (dashed) is predicted to significantly outweigh that of τ_{R}(I) (dotdashed), especially at higher background intensities where the decrease in R* time constant saturates.
We reiterate the proviso stated earlier, that the interpretations we have reached above have been obtained from analysis of the predictions of our model, rather than from direct experimental manipulation.
Bathtub Analogy of Reactions Governing cGMP Concentration
In an attempt to provide a more intuitive understanding of the role of the increased rate constant of cGMP hydrolysis in desensitizing the fractional response and accelerating the recovery, we now present an informal description, which we call the “bathtub analogy” of the reactions governing cGMP.
Imagine a bathtub, in which the depth of water represents the cGMP concentration. The rate at which water runs into the tub from a tap represents the activity of guanylyl cyclase (α), and the rate at which water drains out of the tub is proportional both to the depth of the water and also to the size of the drain, which represents the PDE activity, β. When a steady state is reached, the depth of water will equal the rate of influx divided by the rate constant of efflux; i.e., cG(I) = α(I)/β(I). Now imagine that the size of the drain is briefly enlarged, before returning to its previous size, causing a transient increment in the rate of efflux, Δβ(t). This will elicit a transient drop in water level, ΔcG(t), followed by eventual recovery to the original steady level. The question is: with what time course does the water level recover, once the drain has returned to its original size? The answer is that it recovers exponentially, according to a rate constant β(I), or time constant 1/β(I).
Next, imagine that the size of the drain is permanently enlarged, thus increasing β(I) and, in addition, that the tap is correspondingly opened up to increase the steady influx of water, thus increasing α(I). If the two parameters are increased in the same ratio then the steadystate depth of water, cG(I), will remain unchanged. Suppose now that the same incremental stimulus is given as previously—a transient additional opening of the drain, Δβ(t). If this stimulus is delivered instantaneously, it will cause the same initial drop in water level as previously. But, very importantly, the recovery will occur more rapidly. Thus, the water level will begin rising more rapidly than previously, because the influx of water through the tap is faster, yet it will reach the same steady level as before; therefore, it must reach that level sooner.
In general terms, the effect of enlarging the drain will be to accelerate the rate at which the water level reequilibrates whenever it is perturbed, whereas the effect of a steady openingup of the tap will simply be to scaleup the depth of water in the tub. Importantly, if one expresses the depth during the response as a fraction of its level before the stimulus, (i.e., as cG(t)/cG(I)), then the response will be independent of the rate of influx through the tap, provided that the rate is constant; i.e., that α(t) = α(I).
Flux of cGMP
The existence of the powerful Ca^{2+}mediated feedback loop results in relatively small changes in concentration of cGMP and Ca^{2+} during light adaptation, but quite large changes in the flux of cGMP, corresponding to large increases in α and β. The flux of cGMP in the model rod increases from 3.5 μM s^{−1} in darkness to ∼27 μM s^{−1} in the presence of a background producing I = 3,000 photoisomerizations per second, whereas β increases from 1.0 to 21 s^{−1}, and cG only declines from 3.5 to 1.1 μM. Experimental measurements with the ^{18}O method (applied to toad rods in the intact retina) have yielded even larger changes in the flux of cGMP (Dawis et al. 1988): from ∼2 μM s^{−1} in darkness to ∼100 μM s^{−1} during exposure to a steady light of I = 3,000 photoisomerization per second.
Some years ago, it was proposed that the lightinduced changes in cGMP flux, per se, might underlie the photoreceptor's electrical response (Goldberg et al. 1993; Dawis et al. 1988). Although that proposition is no longer tenable, in the face of overwhelming evidence that the change in concentration of cGMP is the signal that determines the electrical response, it remains conceivable that the flux of cGMP might play some role in adaptation of the photoreceptor. Certainly, the flux constitutes a significant metabolic load: in the presence of a background producing 3,000 photoisomerizations per second the calculated cGMP flux of ∼27 μM s^{−1} requires an equal rate of GTP utilization by guanylyl cyclase, and ultimately of ATP utilization. For comparison, maintenance of the 16 pA circulating current at the same intensity requires ATP utilization at a rate of ∼50 μM s^{−1}.
Relative Robustness of Conclusions
The reader may rightfully inquire as to the relative certainty (or robustness) of our conclusions, in particular, of those involving calculations with the model rod presented in the . We think that our conclusions fall into the following several categories of certainty: (a) robust, conclusions obtained through analysis of the experimental results with the “activationonly” form of the model; (b) reasonably robust, conclusions obtained by analysis using the full model under conditions of fixed Ca^{2+} concentration; and (c) less robust, conclusions dependent on the full model when the Ca^{2+} concentration is changing dynamically.
Thus, at the highest level of certainty is our conclusion that the amplification constant of phototransduction is unaltered by adaptation, since this was obtained by analysis of experimental traces simply scaled according to the steady circulating current (Fig. 3, Fig. 4, and Fig. 9). Next in degree of robustness, we consider to be the calculated dependence of β on I (Fig. 8 and Fig. 9), because this depends primarily on the Hill relation for channel activation, in conjunction with steady synthesis and hydrolysis of cGMP. Although our correction of the estimates at high background intensities, by analysis with the model rod, introduces some model dependence into the estimated values of β, this has little effect on the overall shape of the relation (Fig. 9).
We also consider the characterization of the step/flash effect as a calciumdependent shortening of a “nondominant time constant” (Fig. 10 and Fig. 11) to be a robust conclusion, especially in light of our evidence that the amplification constant is not affected by adaptation. However, our identification of this nondominant time constant as the effective lifetime of R* (and specifically our description of this lifetime as being determined by the calciumdependent inhibition of rhodopsin kinase by recoverin) clearly depends on our model and on the values adopted for the parameters of the recoverin binding reactions ( C). Although these values have been taken from the biochemical literature, they have not been obtained for salamander rod proteins, and there are substantial differences in the estimates from different laboratories and for different species.
Next in robustness are our conclusions concerning the contributions of the different calciumdependent mechanisms to the cell's operating range, i.e., its response versus intensity relation (Fig. 14 A). Although we feel confident that the relative contributions predicted for the three mechanisms are broadly correct, we acknowledge that the model utilizes a number of calciumdependent parameters whose exact values remain somewhat uncertain.
Finally, we consider our predictions of response kinetics, and of parameters derived from the response kinetics, to be the least robust aspects of our conclusions, since the underlying calculations involve dynamic changes in Ca^{2+}_{i} and, therefore, dynamic changes in all Cadependent processes in the rod. Accordingly, the predicted form of sensitivity as a function of background intensity (Fig. 6B and Fig. C, and Fig. 14B and Fig. C) cannot be considered as particularly robust; i.e., the shape of the relation is likely to be modeldependent. Despite this qualification, we think our conclusion that the increase in β(I) represents the dominant factor in desensitizing the rod's biochemical cascade remains robust, since the effect is present in calciumclamped rods (Fig. 13).
Limitations of Our Present Description of Transduction
Our present model of the salamander rod achieves a good description of the steadystate dependence of circulating current (Fig. 6 A) and sensitivity (Fig. 6B and Fig. C) on background intensity, and a good description of the kinetics of responses obtained under constant calcium conditions (Fig. 12 and Fig. 13). Where it falls down is in its prediction of the exact form of the response kinetics under conditions where Ca^{2+}_{i} is free to change; i.e., in normal Ringer's solution (traces not shown). Thus, the numerical solutions do not yet provide a satisfactory description of the overall family of flash responses in Ringer's, or even of just the dimflash response when tested over the full range of adapting intensities. We emphasize that what we seek is a model with a single set of parameters that are consistent with all relevant measurements in the literature, including measurements of Ca^{2+}_{i}, the concentrations and binding parameters of the calcium binding proteins, etc. We think that the key features remaining to be resolved relate to the dynamics of shutoff of the various proteins, and entwined with these issues are kinetic aspects of the calcium buffering provided by the various calcium binding proteins, including recoverin, guanylyl cyclase activating proteins, and calmodulin.
We do not underestimate the problems that remain in obtaining a complete molecular description of the rod's response to flashes on backgrounds. But at this stage, we are confident, first, that the conventional description of activation is accurate and, second, that the main factors underlying light adaptation have been described adequately in steadystate terms. However, we think that further information will be needed about dynamic changes in these inactivation steps, before a definitive molecular description of the rod's electrical response can be provided.
Acknowledgments
This work was supported by National Institutes of Health grant EY02660 and a Jules and Doris Stein Research to Prevent Blindness Professorship (to E.N. Pugh Jr.), and by Wellcome Trust grant 034792 (to T.D. Lamb).
Appendix
THE EQUATIONS OF PHOTOTRANSDUCTION
We, and other groups, have previously presented equations describing the Gprotein cascade of phototransduction that embody insights and formalisms from numerous biochemical and physiological investigations. In this we summarize those equations, and we acknowledge their first use (even when in slightly different form) using the following abbreviations: FKL (Fesenko et al. 1985), KM (Kawamura and Murakami 1986), HN (Hodgkin and Nunn 1988), FMRT (Forti et al. 1989), LCM (Lagnado et al. 1992), LP (Lamb and Pugh 1992), and NEP (Nikonov et al. 1998).
In general, each of the variables is a function both of the steady background intensity (I) and the time (t) after a flash, e.g., j(I, t), but for simplicity, we will usually drop one or both of these independent variables. Thus, we will usually denote the timedependent form as j(t), or often simply as j where this is unambiguous, whereas we will denote its steady state value j(I,∞) simply as j(I), with its darkadapted steady value denoted as j_{Dark}. Although many of the variables are calciumdependent, in general, this will not be denoted explicitly. For brevity, the definitions of all the variables and constants are given in and , respectively.
Differential Equations
The rates of supply and removal of the active species R*, E*, cG, and Ca can be expressed in terms of the four differential equations.
Activated rhodopsin: A1
Activated PDE: A2
Free cGMP concentration [KM (4)]: A3
Free Ca^{2}+ concentration [NEP (12)]: A4
In each case, the first term on the right represents generation, whereas the second term represents removal. In the first three equations, the rate constants of turnover of the active substance are the following: k_{R} (= 1/τ_{R}) for R*, k_{E} (= 1/τ_{E}) for E*, and β for cG. As a simplification in writing Formula A2, any depletion in the pools of activatable Gprotein and PDE, which may occur with intense flashes, has been ignored. In addition, a short delay t_{eff} contributed cumulatively by several of the activation steps has also been ignored, but can readily be accounted for by a simple time shift.
Equations Relevant to the Rising Phase
Two variables describing the rising phase, which do not depend explicitly on Ca^{2+} concentration, are specified by the following equations.
Rate constant of cGMP hydrolysis [LP (4.3)]: A5 cGMPactivated channel current [FKL]: A6
Nevertheless, it should, be borne in mind that K_{cG} in Formula A6 is a function of Ca; see Formula A11.
From the equations above, it is possible to solve for the rising phase of the rod's response to illumination, and the solution is characterized by an amplification constant defined as follows:
Amplification constant [LP (6.9)]: A7 where
Rate constant of cGMP hydrolysis per E* [LP (4.4)]: A8
Equations Related to Recovery and Adaptation
The remaining equations relate primarily to the recovery phase and to adaptation, and the parameters are explicitly dependent on Ca^{2+} concentration. Two of these parameters, describing the electrogenic exchange current and the guanylyl cyclase activity, are well established in the literature.
Exchange current [LCM (1)]: A9
Guanylyl cyclase [FMRT (16)]: A10
In addition, we present three new equations, the first being for the Ca^{2+}/calmodulin modulation of channel activation, and the next two characterizing the Ca^{2+}/recoverin/RK system. Whereas Koutalos et al. 1995b formulated the calmodulin effect as a change in the scaling of current (their Formula 3), we have instead specified the effect as a shift in channel activation, according to:
Channel activation constant, A11
In , we analyze the recoverin/RK system, and we develop equations specifying the free concentration of recoverin and of RK, and recoverin's Ca^{2+}buffering power, in terms of the Ca^{2+} concentration. Here, we simply take the resulting variables, RK (from Eq. C1 with C3) and B_{Ca, Rec} (from Eq. C5), and use these to specify the rate constant of R* decay, and the total Ca^{2+}buffering power of the cytoplasm.
Rate constant of R* decay: A12
Ca^{2+}buffering power: A13
Finally, the total circulating current of the outer segment is the sum of the current through the cGMPactivated channels and the electrogenic exchange current:
Total outer segment current: A14 except that, when the membrane capacitive time constant (τ_{m}) is taken into account, a filtered version of this equation must be used.
Exposure to IBMX
To deal with exposure of the outer segment to IBMX, we assume that the PDE rate constant of cGMP hydrolysis (β) that occurs in Formula A3 and is defined in Formula A5, is inhibited (divided) by the following factor.
PDE inhibition factor: A15 where IBMX is the concentration of IBMX in the perfusate, t is time after the solution change, τ_{I} ≈ 100 ms is the time constant of equilibration, and K_{I} = 10 μM is the competitive inhibition constant.
Appendix
THE STEADY STATE
The steady state of the system described in may be determined by setting the derivatives in Formula A4 equal to zero, and solving the resulting equations simultaneously with the other equations. Although it is not possible to obtain an analytical solution in terms of the steady background intensity (I), it is instead possible to adopt an inverse approach, because all the variables can be specified as functions of Ca^{2+}concentration. Hence, one may perform the following sequence of operations.
(a) Select a wide range of steady state values of Ca(I).
(b) Calculate the steadystate Ca^{2+}dependent variables: j_{ex}(I), α(I), K_{cG}(I), RK(I), and k_{R}(I).
(c) Substitute these values into Formula A4 with the derivatives set to zero, and into Formula A5 and Formula A6, to obtain respectively:
from Formula A4, B1 from Formula A6, B2 from Formula A3, B3 from Formula A5, B4 from Formula A2, B5 from Formula A1, B6
By substitution of the definition of the amplification constant (A), from Formula A7, the last three equations above may be combined to yield B7 which relates I to β(I) without the need for assumptions about the values of ν_{RE} and β_{sub}.
Any of the steady variables determined above, including Ca(I), may readily be plotted as a function of intensity, e.g., Ca(I) versus I, or as a function of any of the other steady variables.
Appendix
A QUANTITATIVE MODEL OF RECOVERIN'S INTERACTIONS
Recoverin's Interactions with Calcium and with Rhodopsin Kinase
The calcium binding protein recoverin has been reported to be present in amphibian rods at a concentration of at least 30 μM (Kawamura 1993), and more recently, as high as 140 μM (Kawamura et al. 1996). Bovine recoverin has two calcium binding sites, which bind calcium cooperatively with a Hill coefficient near 2, and an apparent K_{1/2} of 4.5 μM in frog rods (Klenchin et al. 1995) and 17 μM in bovine rods (Ames et al. 1995). From these numbers alone, it is clear that recoverin will be important in buffering calcium in the rod.
In addition to its role as a calcium buffer, recoverin with two Ca^{2+} bound (Rec · 2 Ca) has been found to inhibit the phosphorylation of rhodopsin (Kawamura 1993; Chen et al. 1995; Klenchin et al. 1995; Sato and Kawamura 1997). This most likely occurs through the binding of Rec · 2 Ca to rhodopsin kinase (RK), which is thereby prevented from interacting appropriately with R*.
We believe that these two actions of recoverin, its calcium buffering and its inhibition of RK, are critical in describing certain calciumdependent features of lightadaptation. Accordingly, we have developed a model of the binding interactions of recoverin, which is expressed in the chemical Scheme 1, which is similar to that in Erickson et al. 1998.
Analysis of the Model of Recoverin's Binding: Free Concentrations of Recoverin and RK
(Scheme 1) The experimental evidence supports the view that the binding of Rec to Ca^{2+} equilibrates very rapidly, as does the binding of myristoylated Rec · 2 Ca to disc membranes (Zozulya and Stryer 1992; Ames et al. 1995). Accordingly, we treat all the interactions in Scheme 1 as effectively instantaneous, thus, enabling the use of equilibrium binding constants.
To analyze the system in Scheme 1, one first writes the equations defining the five equilibrium constants, K_{1}–K_{5}, and then the two conservation equations specifying the total quantities of recoverin and rhodopsin kinase, Rec_{tot} and RK_{tot}, respectively. In addition, from the thermodynamic principle that there can be no net movement around the reaction loop in Scheme 1, one obtains the interrelation that K_{5} = (K_{2}/M)(K_{4}/K_{3}). The concentrations of free recoverin and rhodopsin kinase, expressed in fractional form Rec/Rec_{tot} and RK/RK_{tot} are then found to be related by the equation C1 where the parameter C_{1} is given by C2
After some tedious algebra, one obtains the following quadratic equation for the fraction of free recoverin: C3 where the parameter C_{2} is given by C4
Hence, one first evaluates the parameters C_{1} and C_{2}, then solves the quadratic in Eq. C3 to obtain the fractional recoverin concentration, and finally substitutes this into Eq. C1 to obtain the fractional rhodopsin kinase concentration. The rate constant of R* inactivation is obtained by substitution in Formula A12.
Recoverin's Calcium Buffering Power
Once the dependence of free recoverin concentration on free calcium concentration has been determined, the calcium buffering power contributed by recoverin can be calculated. Since recoverin has been assumed always to bind two Ca^{2+} ions, then its Ca^{2+}buffering power (defined in terms of the total quantity of calcium, Ca_{tot}), can be expressed as C5
The righthand side of Eq. C5 may be evaluated most simply by numerical differentiation of the relationship between Rec and Ca. Alternatively, it is possible to differentiate the quadratic expression in Eq. C3, taking care to note that C_{1} and C_{2} are not constants, but instead are functions of Ca. After some excruciating algebra, one obtains a very complicated analytical expression for B_{Ca, Rec} that will not be presented here, but which agrees exactly with the numerical solution.
Footnotes

Abbreviations used in this paper: IBMX, isobutyl methylxanthine; PDE, phosphodiesterase.
 Submitted: 8 August 2000
 Revision requested 13 September 2000
 Accepted: 15 September 2000