extfieldsofstudy: Chemistry Medicine

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Platymonas subcordiformis Channelrhodopsin-2 (PsChR2) Function

Background: Channelrhodopsins (ChRs) are light-gated cation channels widely used in optogenetics. Results: The photocycle obtained from time-resolved absorption spectroscopy of PsChR2 is shown to explain photocurrent kinetics observed in HEK293 cells. Conclusion: The photochemical reactions involving two parallel photocycles result in the complex photocurrent behavior. Significance: The parallel-cycle model opens new perspectives in understanding photocurrents from channelrhodopsins. Channelrhodopsins, such as the algal phototaxis receptor Platymonas subcordiformis channelrhodopsin-2 (PsChR2), are light-gated cation channels used as optogenetic tools for photocontrol of membrane potential in living cells. Channelrhodopsin (ChR)-mediated photocurrent responses are complex and poorly understood, exhibiting alterations in peak current amplitude, extents and kinetics of inactivation, and kinetics of the recovery of the prestimulus dark current that are sensitive to duration and frequency of photostimuli. From the analysis of time-resolved optical absorption data, presented in the accompanying article, we derived a two-cycle model that describes the photocycles of PsChR2. Here, we applied the model to evaluate the transient currents produced by PsChR2 expressed in HEK293 cells under both fast laser excitation and step-like continuous illumination. Interpretation of the photocurrents in terms of the photocycle kinetics indicates that the O states in both cycles are responsible for the channel current and fit the current transients under the different illumination regimes. The peak and plateau currents in response to a single light step, a train of light pulses, and a light step superimposed on a continuous light background observed for ChR2 proteins are explained in terms of contributions from the two parallel photocycles. The analysis shows that the peak current desensitization and recovery phenomena are inherent properties of the photocycles. The light dependence of desensitization is reproduced and explained by the time evolution of the concentration transients in response to step-like illumination. Our data show that photocycle kinetic parameters are sufficient to explain the complex dependence of photocurrent responses to photostimuli.

Channelrhodopsins (ChRs) 2 are phototaxis receptors in unicellular algae (1) that function as light-gated ion channels when expressed in animal cells (2)(3)(4)(5). Upon illumination, channelrhodopsins transiently increase the membrane conductance for protons and mono-and divalent cations, causing depolarization of the membrane on a fast, millisecond time scale. Their light-gated channel activity makes them a valuable optogenetic tool (4 -8). To better understand the channel functions on the molecular level, the connections between the current transients and the light-induced intermediates need to be established. Kinetic intermediates are generally derived from light-induced opticalabsorptionchangesrecordedinphotochemicalmeasurements. At the levels of expression obtainable for channelrhodopsins, such measurements cannot be performed with sufficient accuracy in intact cells or membrane preparations due to high light scattering in those preparations. Photoreaction kinetics for channelrhodopsins have therefore been obtained from measurements carried out on solubilized protein samples. The properties of proteins in the solubilized and membraneembedded states may or may not be identical, and local ion concentrations at the membrane surface may influence the kinetics. However, in general, it is assumed that the kinetics of the solubilized protein are similar enough to those in the membrane that the conclusions drawn from measurements on the solubilized protein can explain the protein functions in the membrane environment. This is the ultimate goal of kinetic studies and is a testable assumption. Previous work on channelrhodopsins CrChR2 and PsChR2 indicated that laser-induced current transients roughly correlate with late photocycle intermediate(s) observed in independent photochemical studies (9,10). The complex time dependence of the current response to step or continuous illumination, however, is difficult to reconcile with the reaction sequence derived from photochemical measurements (9,(11)(12)(13)(14). The desire to explain the unusual * This work was supported by National Institutes of Health Grant R01EY000983 from the NEI (to D. S. K.). The authors declare that they have no conflicts of interest with the contents of this article. 1 To whom correspondence should be addressed. E-mail: kliger@ucsc. edu.
features displayed by the current profile prompted the development of hypothetical models, called four-state models (15)(16)(17). Support for these sophisticated models from photochemical experiments is still lacking. The current response shown by PsChR2 to a step-like illumination (10) is typical of responses reported for other ChR proteins (12), a fast peak followed by a plateau current. However, the extent of peak current inactivation or desensitization is less and the recovery to repetitive illumination steps is faster than those of CrChR2 (10). The time course of the current induced by a laser flash lacks the ultrafast transient signals seen in rhodopsin proton pumps and CrChR1 associated with proton transfer from the retinylidene Schiff base (18,19) and follows the time dependence of the absorption transient assigned to an unidentified red-shifted intermediate (10). These properties of PsChR2, mentioned above briefly, make this protein a desirable subject for studies aimed at connecting the channel current kinetics to light-induced intermediates. Here we report on the relationship between the published channel currents produced by PsChR2 expressed in HEK293 cells, as well as current transients reported for other ChR2 proteins, and the photocycle derived from time-dependent absorption experiments on the solubilized PsChR2 protein presented in the accompanying article (21). We suggest that similar relationships may exist for ChR proteins in general.

Materials and Methods
Transient Photocurrent-Transient photocurrent in response to a short laser pulse, courtesy of Professor J. L. Spudich, was measured in HEK293 cells expressing PsChR2 as described (19). All other current transients discussed in this work have been previously published as referenced in the text.
Model Calculations-The time dependence of intermediate concentrations was calculated based on the microscopic rate constants of the kinetic scheme corresponding to the reaction scheme involved. The rate constants were arranged in a kinetic matrix, and the eigenvalues and eigenvectors of the matrix were obtained. The eigenvectors were scaled according to the initial conditions, i.e. the relative concentrations of the intermediates of the scheme at zero time. The product of the scaled eigenvectors and the time-dependent exponential functions based on the eigenvalues yielded the time dependence of the intermediate concentrations. Responses to switching on and off the light pulses were calculated separately and merged to give continuity according to the profile of the light pulse regime involved. The calculations were performed using programs written in MATLAB (MathWorks).

Results and Discussion
The PsChR2 Photocycle-The analysis of PsChR2 kinetics reported in the accompanying article (21) revealed the simultaneous presence of two photocycles in PsChR2. Cycle 1 accounted for 30% of the reacting molecules and included the reversible decay of the K state to the M state, followed by conversion to the O state, which decayed to the P state before returning to the recovered, R, state. Cycle 2 represented 70% of the reacting molecules and showed the decay of the first intermediate state, K, forming coupled equilibria with the L and M states, followed by buildup of the O state, which decayed directly to the recovered state. The microscopic rate constants, in units of s Ϫ1 , of the reaction steps obtained from fitting the two-cycle model (shown below) to the experimental data are placed next to the arrows in the schemes.
Based on these rate constants, the time-dependent concentrations of the intermediate states were calculated. The states likely to be involved in channel function can be evaluated by comparing the time evolution of the intermediate states with the transient cell current produced by the channel opening of PsChR2 in response to a laser pulse.
Identifying the Conductive States-In response to a short laser pulse, HEK293 cells expressing PsChR2 exhibit a transient photocurrent that reaches its maximal value between 1 and 2 ms. Fig. 1, a and b, show the concentration profiles of Cycle 1 and Cycle 2, respectively, and Fig. 1c compares the sum of the contributions by the two cycles with the transient photocurrent (black curve) reported earlier (19). It is clear that the concentration profiles of the O states in both cycles overlap with the current transient. An approximate match in the current to redshifted intermediate accumulation has been noted previously for CrChR2 (9) and for PsChR2 (10).
The match between the O intermediate lifetimes and the photocurrent is not exact. Although quantitative differences might be expected due to uncertainties in both the current measurements and the kinetic analysis, the qualitative agreement in times for the channel opening and O state population is striking. Nevertheless, the O state in Cycle 1 starts earlier than the current, and the two cycles do not contribute to the current shape equally. To account mathematically for the lag period between the current and the O state in Cycle 1, we split the O state into two states, a nonconductive and a conductive one, by introducing a step with a 200-s lifetime (rate constant kЈ 2 in xCycle 1 below) to connect the two. Thus, the O state responsible for the channel opening would appear 30 s later than the detection of absorbance of the O form. To distinguish it from the conductive O state, the nonconductive early state we call O n . A possible explanation for the delayed current is that protonation of the Schiff base in Cycle 1 occurs rapidly because a proton is readily available at a nearby group. The pore formation, however, needs more time, although it may also require the initial protonation step. Also, the color change and the flow of ions are two different responses produced by the protein and detected by two different techniques. Because the protonation of the Schiff base in Cycle 2 is a relatively slow process, with a

PsChR2 Photocycle Explains Photocurrent Kinetic Behavior
1.4-ms lifetime, no delay between the current and color change is expected. We emphasize that it is entirely possible that electrical potential present across the HEK293 plasma membrane in photocurrent measurements, or other differences in the PsChR2 preparation, are responsible for the kinetic mismatch between the O lifetime and the photocurrent, and that the assumption of two physically different O states or, equivalently, one with a delayed conductance response, is consistent with, but not demonstrated by the data.
The concentration profiles of the nonconductive O n , the conductive O state of Cycle 1, and the open channel O state of Cycle 2 are shown in Fig. 2 (blue, green, and red curves, respectively). When the concentrations of the conductive O form of Cycle 1 and the O form of Cycle 2 are summed in a 1:1 ratio, the resulting curve has its peak value almost a millisecond later than the current peak (Fig. 2, cyan and black curves, respectively). An acceptable match can be found only when the concentrations of the O states of Cycle 1 and Cycle 2 are summed in a 3.6:1 ratio (Fig. 2, pink curve). Thus, the channel created by the O state in Cycle 1 appears to be 3.6 times more conductive than the channel produced by the O state in Cycle 2. This is an unexpected observation based on the almost identical absorption spectra of the O states in the two cycles. However, it is consistent with the decoupling between pore and O state formation in Cycle 1 suggested above. The absorption spectra report only the structure around the retinal chromophore and may not be sensitive to distant changes in the protein conformation. The differences in structure of the O states in Cycle 1 and Cycle 2, which lead to the differences in conductivity, may also be responsible for the different recovery routes observed in the two cycles. The more open channel structure of the O state in Cycle 1 recovers in two steps, whereas the less open O state in Cycle 2 recovers in a fast single transition.
The laser-induced transient current is of primary importance in identifying the states responsible for channel opening. However, the laser technique is not the most frequently used technique in electrophysiological studies aimed at possible application of channelrhodopsins in optogenetics. In practical applications, the light source is likely to be less intense than a laser pulse, and thus the delivery of the needed number of photons would take a longer time. Recording the current in response to step-like light pulses of several seconds duration is the standard method of channelrhodopsin studies. The time dependences of photocurrent responses for channelrhodopsins, mainly for CrChR2, are described in detail in a number of publications (for review see Ref. 12), which allows us to compare the predictions by the two-cycle model with the experimental observations and to test whether the model fits the basic properties not only of PsChR2 but of ChR2 proteins in general.
Modeling the Channel Current Induced by Long Light Pulses-Channel currents evoked by light pulses of moderate intensity and a few seconds duration show a number of interesting kinetic features that are quite different from the transient current seen following a short and intense laser pulse. The current response to a light step starts with a fast rise, reaching an  initial peak value, called the peak current, and then the current decays to a lower, but steady level and stays at this plateau until the light pulse ends. This current profile is characteristic not only of PsChR2 (10) but also ChR proteins in general (12). The decay of the peak current is called desensitization or inactivation, and this unusual phenomenon described in earlier studies on ChR proteins initiated a number of hypothetical models, the most complex being called the four-state model, having two light-induced and interconnected open-channel states, which decay to two closed-channel dark states (15). The rate of conversion between the two open states was later proposed to depend on the intensity of the light step applied (16). These models, aimed at explaining the current transients under continuous illumination, or long-lasting light pulses, have little connection to the actual photocycle intermediates deduced from time-resolved spectroscopy measurements (12,13). The photocycle kinetics, interpreted in terms of a sequential mechanism, show relatively simple time dependences of intermediate concentrations (13), which are difficult to reconcile with the far more complex time course of the current response to a light step. It has been suggested that the protein, responding to a longer but less intense continuous illumination, may have a cycle that is more complex than the photocycle derived from laser experiments that use very intense pulses (12).
We deduced the two-cycle model from laser-induced absorption changes. Thus, if the protein has different cycles when it responds to an intense laser or moderate continuous illumination, the model we deduced should fail when attempting to reproduce the experimental current response obtained in light step experiments. To test the model, we modified Cycle 1 and Cycle 2 by adding a light-driven step connecting the recovered state, R, to the K state in each of the cycles, and thus turning the schemes into true cycles. Also, a step connecting O n to O is included in xCycle 1.
We call these extended schemes xCycle 1 and xCycle 2, and we refer to the model as the extended model. The rate constant, k 5 , of the new step we call the light rate constant, which is assumed to be a function of light intensity. The concentration time dependence for all the molecular states in the two cycles was calculated, and the light-on and light-off responses were merged.
The results of the calculation for a light pulse of 1-s duration having a 20 s Ϫ1 light rate constant are shown in Fig. 3 for the conductive O states. The xCycle 1 produces a concentration spike of the O state that decays to a low steady level (blue curve), whereas the concentration of the O state in xCycle 2 rises fast to a plateau (green curve). The 1:1 sum of the two curves, shown as the red trace, produces a shape similar to the current response observed experimentally for PsChR2 (15), but does not have the proper ratio between the peak current and the plateau current. Summing up the contributions by the xCycle 1 and xCycle 2 in a 3.6:1 ratio (cyan curve) matches both the published (15) experimental current shape and the peak-to-plateau ratio reasonably well, thus supporting the assumption of the higher conductivity of the O state in Cycle 1 relative to that in Cycle 2, as discussed above in connection with the laser-induced current response. Note that the sum of the two contributions contains all the exponential functions involved in the two cycles. Therefore, the time course of the desensitization may not always yield a single exponential "desensitization rate." The shapes of the current responses to an intense laser pulse, shown in Fig. 2, and to a light pulse of moderate intensity, as modeled and shown in Fig. 3, are readily explained by their origins. The current transient seen in a laser experiment reflects molecular events, the rise and decay of the channelforming intermediates that follow the synchronous and instant excitation of molecules in their ground state. Because of the asynchronous and prolonged excitation of the molecules in the ground state, the current profile being produced by a light step reflects the onset of a steady state. As discussed later in more detail, the intermediates in a reaction sequence display a transient response to a light step before relaxing to a steady state level. The relative steady state concentration, c, of an intermediate is proportional to the fraction its lifetime represents in the total lifetime of the cycle, c ϳ /⌺. In xCycle 1, the decay of the P state, with 0.71 s Ϫ1 rate constant, is much slower than the decay of all other states, including the R state, with a 20 s Ϫ1 decay rate constant used in the modeling. Thus, the P state builds up at the expense of all the other states. The O state, which is responsible for the open channel, starts with a higher initial concentration as the light-induced flow is the highest at the beginning of the light pulse, and later relaxes to a relatively low steady state level as shown in Fig. 3. The details of the concentration profiles for all of the intermediate states will be discussed later. In xCycle 2, the O state has the lowest decay constant in the chain leading to the recovered R state. It thus will have a relatively high steady state level. Even so, it does not accumulate to the same extent as the P state in xCycle 1 because in xCycle 2, the decay of the O state is not the slowest step; rather the light-induced decay of the R state is the slowest one for low and moderate light intensities. In the case of the 20 s Ϫ1 light rate constant used in the modeling, the O state accounts for roughly 10% of the total concentration in the steady state. Because the O state corresponds to the open channel protein state, it is responsible for most of the plateau current seen in the step response in Fig. 3. Note that the concentration of the O state in xCycle 2 and that of the P state in xCycle 1, which precede the recovered state in the chains, do not display transient peaks; rather they build up steadily.
The characteristic current response, a peak followed by a plateau, to a light step stimulus is a general feature of all twocycle models that have The Recovery of the Peak Current in Multistep Experiments-Characterization of ion channels often involves measuring the current response to a train of alternating light and dark steps. It is frequently observed that the peak current produced by a second light step is lower in amplitude than the peak invoked by the first light pulse, whereas the plateau regions are reproduced reasonably well (12,15). This phenomenon is called the peak current recovery and observed also for PsChR2 (10).
In the two-cycle extended model, the peak current is the response of xCycle 1. To produce a full size peak current, xCycle 1 has to recover completely. At the end of the light pulse, most of the molecules are in the nonconductive P state and must convert into the R state before responding to the second light pulse. The smaller peak amplitude during the second light pulse means that xCycle 1 has not fully completed its course in the dark period between the two pulses because the decay of the P state is slow. Only that fraction of the molecules that had already recovered into the R state during the dark period is ready to respond. The peak current recovery phenomenon in our two-cycle model is the result of the open-closed state sequence, -O-P-R, in Cycle 1, which produces a peak current due to the transient O state and delays the recovery due to the nonconductive long-lived P state. The -O-R sequence in Cycle 2, which produces most of the plateau current, recovers much faster.
To demonstrate the recovery process outlined above, the time-dependent concentrations of the molecular states in the extended cycles were calculated for two 1-s light pulses with a 1-s dark period between them. Fig. 4a, blue curve, shows the sum of O state concentrations from the two photocycles, using the 3.6:1 ratio in the summation as above. Fig. 4b shows the current contribution by the O state (blue curve) and the concentration of the recovered R state in xCycle 1 (green curve). In xCycle 1, only a fraction, about 50%, of the molecules recovered in the dark period because the P state has a 1.4-s lifetime, whereas in xCycle 2, the recovery is very fast as the O state decays to the R state with a 7-ms lifetime (not shown).
The reduction of the peak current amplitude in the second pulse, predicted by the extended model, is more pronounced than observed experimentally for PsChR2 (10). To produce less reduction, the decay rate constant of the P state would need to be increased. An increase by a factor of two is sufficient to reproduce the peak-to-plateau ratio seen in the experimental traces. Because the currents are recorded on proteins embedded in membrane, and the photochemical experiments are carried out on solubilized protein samples, such differences in rates are not unusual.
The Light-dependent Rate of Desensitization-Desensitization or inactivation, the decay of the peak current to the steady state level in light step experiments, is an important and interesting channel property, the origin of which has been obscure (12). It has also been found that the rate of the transition responsible for the inactivation of the channel is light-dependent. Exponential fits to the falling part of the peak current revealed that the channel desensitizes faster at higher light pulse intensities. No such light-dependent rates have been reported in absorption studies. In the first four-state channel model (15), two conductive states, connected via a reversible step, were proposed to account for the peak current deactivation. However, for better reproduction of the light-dependent deactivation rates, the idea of a light-assisted transition between the conductive states was introduced and added to the improved four-state model (16). Note that light-dependent kinetics and complications arising from secondary photoreactions (9), which are more prominent at high light intensities, are not part of our discussion. A comparison of the reported action spectra of channel currents generated in HEK293 cells (10) with the absorption spectra of solubilized PsChR2 shows no noticeable contributions from secondary photoreactions at normal light intensities. This is also likely to apply to CrChR2.
In our two-cycle model, there is no connection between the two cycles and no light-assisted transition between the conducting O states to facilitate the peak current decay in a lightsensitive manner. To test the light dependence of desensitization, we modeled the current response to light steps of different intensity by varying the value of the light rate constant in the extended cycles from 10 s Ϫ1 to 80 s Ϫ1 . The results, the concentrations of the conductive O states, are shown in Fig. 5. Fig. 5, a and b, display the current response produced by xCycle 1 and xCycle 2, respectively, for 10, 20, 40, and 80 s Ϫ1 light rate constants. As expected, the reproduced channel currents increase with light intensity as more molecules of the R state are driven into the cycles. The rise in current level deviates from linearity at higher light intensities as the pool of molecules in the R state becomes exhausted. For a better comparison with the current signals measured in experiments, Fig. 5c shows the sum of currents reproduced by the two extended cycles (colors as in panel a), normalized to the plateau level. The desensitization rate produced by the two-cycle model is clearly light-dependent. The similarity between these curves and the ones published earlier (15,16) on ChR2 proteins is striking.
The light dependence of the desensitization can also be tested by applying a second light step on top of a weaker first one. Experiments on ChR2 reported on this type of light dependence (15). We modeled the experiment by applying a first pulse with 4 s Ϫ1 light rate and a second pulse of higher intensity, with 20 s Ϫ1 light rate, at 1 s after the start of the first pulse. Because xCycle 1 is responsible for the peak current, the results for this cycle only are shown in Fig. 6. The blue curve in Fig. 6a is the concentration transient for the O state, and the green curve is the response observed when the second pulse is applied to a relaxed dark state. Because of depletion of the R state by the first pulse, the amplitude of the O concentration transient produced by the second pulse is very small, roughly the size produced by the much weaker first pulse. In Fig. 6b, the concentration time dependences for the P state (broken curve) and for the recovered R state (solid curve) are plotted for the two-pulse sequence (blue curves) and for the single pulse applied to the dark state (green curves) to show the accumulation of the molecules in the nonconductive P state and the simultaneous depletion of the recovered R state. The first pulse of lower intensity drives a large fraction of molecules from the R state into the cycle, and little is left for the larger second pulse. In Fig.  6c, the transient of the superimposed second pulse (blue curve) is compared with the transient of the pulse applied to the relaxed state (green curve) after normalizing their amplitudes. Before normalization, the steady state levels were subtracted. The comparison shows that the rate of desensitization becomes higher when a pulse is superimposed on a weaker background light. Thus, the channel senses the total light intensity and displays a rate of desensitization as if the second pulse had a higher intensity.
The Origin of the Light-dependent Desensitization Rate-Using the two-cycle model derived from time-dependent absorption, data we were able to reproduce all the basic observations regarding the experimental channel currents and, more importantly, the light-dependent desensitization of the current. What is the origin of the light dependence? Analyzing the time evolution of intermediates and their concentration transients in multistep photoreactions following short laser and step-like long pulse excitations provides the key to answer this question.
Analysis of the Concentration Transients-To understand the relationship between the rate constants in xCycle 1 and the kinetics of desensitization, the concentration transient displayed by the O conductive state, we have to solve the differen- tial equations that describe the concentration changes in the cycle. The cycle, however, is too complex to solve analytically; therefore, we are going to use a simplified version of xCycle 1 that serves our purpose equally well. We skip the equilibration between K and M states and replace it with a single intermediate, KM, and combine the O n and O states into one. For simplicity, we call them KM, O, P, and R intermediates. The simplified sequential scheme is arranged in a linear chain for convenience.
This simple xCycle 1 scheme, sxCycle 1, is a sequential scheme without back reactions, one that has a relatively easy analytical solution. We will recite some of the equations, or their approximations, to describe the time dependence of intermediate concentrations in laser studies as well as in light-step experiments. In the description, we refer to the "rise" and "fall" of the transient concentrations and restrict the term "decay" to the rate constants of transitions between molecular states in the schemes.
In the description, we will analyze cycles with four intermediates. Therefore, we start with the general formulas for this type of reaction sequence. The concentration time dependence of intermediates A, B, C, and D in a linear sequential scheme without back reactions is described by the following reaction and equations (20).
Laser Experiments-First we apply these equations to describe the concentration time dependence of intermediates in the sxCycle 1 scheme as it occurs in laser experiments. Because of the short duration and high light intensity in a laser experiment, the first transition, R to KM, is too fast for the common absorption studies. It is observed only in ultrafast laser photochemistry. In nanosecond spectroscopy, as used in this study, the kinetics starts with the KM intermediate, and the scheme can be shortened by omitting the first step.
The rate constants in this scheme follow a descending order, k 2 Ͼ Ͼ k 3 Ͼ Ͼ k 4 . Replacing k A , k B , and k C by k 2 , k 3 , and k 4 , respectively, the integrated forms of the intermediate concentrations, to a good approximation, are as follows.
KM ϭ KM 0 exp͑Ϫk 2 t͒ . Reproduction of the current transients produced by two superimposed light pulses using the two-cycle model. In a, the current transient at zero time is produced by a weak first pulse of 4 s Ϫ1 light rate constant, and the second transient is produced by a more intense second pulse of 20 s Ϫ1 light rate constant, superimposed on the first one at 1 s (blue curve). The current transient produced by a light pulse of 20 s Ϫ1 light rate constant applied to a relaxed sample at 1 s is shown for comparison (green curve). In b, the evolution of the P and R states (broken and solid lines, respectively) of Cycle 1 during the illumination period is shown for the superimposed pulses and the single pulse (blue and green lines, respectively). c compares the rates of desensitization for the superimposed and single pulses after subtracting the plateau levels and normalizing the single pulse signal to the amplitude of the multistep signal. The concentration of KM falls with the k 2 rate constant to zero, and the concentration of O rises with the same k 2 and falls with the k 3 rate constant. The concentration of P rises with the k 3 and falls with the k 4 rate constants. The R form recovers, approximately, with a rising exponential function, 1 Ϫ exp(Ϫk 4 t). When the experimental data produced by the shortened scheme are fit to a sum of exponentials, it is found that the apparent rates in the fit are the same as the k 2 , k 3 , and k 4 microscopic rates. The transient concentrations of the intermediates rise and fall with the rate constants as seen in the shortened scheme above. If the intermediates in the scheme are all single molecular states, as in Cycle 1 and Cycle 2, the experimental apparent rates or decay constants can be regarded as molecular characteristics associated with the probabilities of converting one molecular state into another one. This seemingly trivial argument is the key to understanding and interpreting the peculiarities of the kinetics under continuous illumination.

PsChR2 Photocycle Explains Photocurrent Kinetic Behavior
Light Step Experiments-Under constant light illumination of moderate intensities, the R to KM transition is no longer the fastest one; in fact it is often one of the slowest rates in the cycle. At moderate light intensities, such as the 20 s Ϫ1 light rate constant used in the modeling, among the rate constants in the sxCycle 1 scheme, only k 4 , having a 0.7 s Ϫ1 value, is smaller than k 5 . Because the P to R transition is so slow, 0.7 s Ϫ1 , there is a negligible recovery of the R state from the P state in the time window where all the other transitions occur. Thus, to describe the main characteristics of the kinetics under continuous illumination, the simplified xCycle 1 can be shortened by omitting the last step.
As was done above for the laser experiment, the rate constants k A , k B , and k C in the general equations are replaced by k 5 , k 2 , and k 3 , respectively. Because k 2 Ͼ Ͼ k 3 , k 5 , the concentration time dependence of the intermediates in this scheme, is described, with good approximation, by the following equations.
The KM concentration transient does not rise with k 5 , the rate constant of the step pointing to KM in the scheme. Instead it rises with k 2 , which belongs to the decay step of KM in the scheme. The light rate constant, k 5 , describes the decrease of the KM concentration transient. The concentration transient for the O intermediate also falls with the k 5 rate constant, and rises with k 3 , which belongs to its decay step in the cycle. Note that the concentration transient has very small amplitude for KM because k 5 is small when compared with k 2 , whose value is 5 ϫ 10 3 s Ϫ1 . The transient is much larger, and therefore detectable, for the O intermediate because the ratio of k 3 to k 5 is around seven at the light intensity used in the modeling. For moderate light intensities, the concentration transient for the P intermediate rises with k 5 , and this is true even for the scheme that has the P to R step. The analysis above shows that the transient concentrations of most of the intermediates do not rise and fall with the rate constants as seen in the scheme. The "odd" behavior of the concentration transients, when compared with the "normal" behavior observed in the laser experiment, reflects the order of rates of the consecutive steps in the mechanism. If the supply rate constant for an intermediate is larger than its decay rate constant, the transition follows the normal, fast-to-slow step order and the concentration transient for the intermediate rises with the supply rate constant and falls with the decay rate constant, as in the laser experiment. If the supply is slower than the decay, the transition follows the odd slow-to-fast step order and the concentration transient for the intermediate rises with the decay rate constant and falls with the supply rate constant, as in the light pulse experiment. For light pulses of high intensity, the light rate constant, k 5 , becomes larger than k 3 . In that case, the equation for the O concentration shows that the O intermediate displays a normal behavior; its concentration transient rises and falls the way it is observed in laser experiments. The desensitization rate constant thus increases with the light intensity until it reaches the value of the true decay rate constant of the O state. The increase is linear at low light intensities and shows saturation behavior at high intensities as it approaches the true decay rate limit, in accord with experimental observations (16). Having these guidelines, we can examine the concentration transients reproduced by xCycle 1 under continuous illumination.

The Concentration Transients in Light
Step Responses Produced by xCycle 1-The current response to a light pulse as predicted by the two extended cycles was shown in Fig. 3 for a 20 s Ϫ1 light rate constant. There we depicted only the time-dependent concentrations of the conductive O states. In Fig. 7, we show the concentration transients to a light step for all of the states involved in the extended Cycle 1. The blue, green, red, cyan, pink, and orange lines represent the concentration transients for the K, M, O n , O, P, and R states, respectively. Because the concentration transients are very different in amplitude for the different molecular states, we normalized the K, M, O n , and O states, according to their steady state level, bringing their plateau regions to the steady state level of the R state. All the characteristics of the rise and fall of the intermediate concentrations, briefly outlined above, can be seen in this figure.
The concentration transient of the K state (blue curve) rises with the true, microscopic decay rate constants obtained in the laser experiment. In xCycle 1, the K state decays in two steps: first to the M state, forming an equilibrium mixture between the two, which then decays to the O n state. The decay constant of the latter transition controls the rise of the M concentration transient. The rise of the O n and O state transients occurs with their molecular decay rate constants found in Cycle 1 (red and cyan curves, respectively). All these early states have molecular decay constants higher than the light rate constant, k 5 , in the extended scheme, and because of that, their transients follow the slow-fast rate combination pattern. The light rate constant, k 5 , has a value of 20 s Ϫ1 in the model, and thus all the early transients fall with a rate constant that is very close to k 5 (see below), together with the concentration of R for which k 5 is the true, microscopic decay rate constant. The same rate constant also describes the rise of the P concentration transient. Examination of the eigenvalues and eigenvectors of the kinetic matrix for the extended Cycle 1 also reveals that none of the apparent rates corresponds to k 4 or k 5 . Instead, an apparent rate of ϳk 4 ϩ k 5 is found. The formation and decay pattern of the molecular states in the transients, depicted in Fig. 7 and explained above, can also be read directly from the compositions of the eigenvectors.
From the results of the transient shape analysis, we can draw an important conclusion: the rates obtained from fitting exponential functions to the rising and falling parts of the experimental concentration transients do not necessarily represent the true microscopic formation and decay rates of the particular states to which the transients belong. This statement applies not only to the light step experiments discussed here, but to any other experimental kinetic transient. The light dependence of the rate constant of desensitization in our model is not connected to any channel property, or to any adjustment in the open state configuration via modification of the O state, which is responsible for the open channel. The rate constant itself does not belong to the molecular state responsible for opening of the channel. It is the rate constant of the R state depletion, driven by the continuous light. Thus, it not only is, but must be, light-dependent according to our model.
Having found the source of light dependence, it is now easy to understand the current response, shown in Fig. 6, caused by a second light pulse of 20 s Ϫ1 rate constant superimposed on the first one having a 4 s Ϫ1 rate constant. The signal is small because the pool of molecules in the R state is nearly depleted with the first light pulse of lower intensity. The transient produced by the second light pulse falls with a light rate constant that is the sum of the light rate constants of the two light pulses present simultaneously, 24 s Ϫ1 in the model calculations. It is this moderate increase in the rate that is seen in Fig. 6b.
Conclusion-We have shown that the photoreactions and the channel currents of PsChR2, a member of the ChR2 group, can be adequately described on the molecular level by two independent parallel photocycles. Cycle 1 contains the K, M, O, and P states and is responsible for 30% of the converted molecules. The transitions in Cycle 2 involve the K, L, M, and O states and account for 70% of the reacting molecules. The O states in the cycles are responsible for the open channel. The O state in Cycle 1 appears 30 s earlier than the current response and shows a 3.6 times higher conductivity than that of the O state in Cycle 2. The two cycles reproduce the current transients under the different illumination regimes, including single and multiple light pulses of different intensities. The desensitization phenomenon is linked to the transient current prior to the establishment of steady state kinetics in Cycle 1. The recovery of the peak current is explained by the presence of the nonconductive P state with a slow decay rate in Cycle 1. The analysis of the light-induced concentration transients revealed the source of the light dependence of the desensitization rate constant reported for ChR2 proteins. It was found that the desensitization rate is a characteristic of the transients leading to the steady state and is identical to the rate of the light-induced depletion of the recovered state. Our results show that a single molecular mechanism with a single set of microscopic rate constants describes both the kinetics of the photochemistry and the light-induced currents of PsChR2. Differences in photocycle kinetics may exist between the solubilized and membrane embedded protein. However, they do not seem to be critical in the evaluation of channel current properties.


Antitumor immunization of mothers delays tumor development in cancer-prone offspring

Maternal immunization is successfully applied against some life-threatening infectious diseases as it can protect the mother and her offspring through the passive transfer of maternal antibodies. Here, we sought to evaluate whether the concept of maternal immunization could also be applied to cancer immune-prevention. We have previously shown that antibodies induced by DNA vaccination against rat Her2 (neu) protect heterozygous neu-transgenic female (BALB-neuT) mice from autochthonous mammary tumor development. We, herein, seek to evaluate whether a similar maternal immunization can confer antitumor protection to BALB-neuT offspring. Significantly extended tumor-free survival was observed in BALB-neuT offspring born and fed by mothers vaccinated against neu, as compared to controls. Maternally derived anti-neu immunoglobulin G (IgG) was successfully transferred from mothers to newborns and was responsible for the protective effect. Vaccinated mothers and offspring also developed active immunity against neu as revealed by the presence of T–cell-mediated cytotoxicity against the neu immunodominant peptide. This active response was due to the milk transfer of immune complexes that were formed between the neu extracellular domain, shed from vaccine-transfected muscle cells, and the anti-neu IgG induced by the vaccine. These findings show that maternal immunization has the potential to hamper mammary cancer in genetically predestinated offspring and to develop into applications against lethal neonatal cancer diseases for which therapeutic options are currently unavailable.

Introduction
Vaccination is the most powerful and versatile tool in preventive medicine and has recently extended its reach beyond infectious diseases to other life-threatening illnesses, such as cancer. Examples can be found in vaccines that have been designed to prevent infection-associated tumors 1 and in those targeting noninfection-related cancer diseases now in preclinical phases or in clinical trials. 2 Maternal immunization against life-threatening diseaseinducing pathogens has been shown to be a viable approach against many childhood pathologies. The induction of high antibody levels following vaccination is fundamental to maternal immunization success. It has long been known that maternally derived IgG is the only antibody class that causes short-term passive immunity to be transferred from mother to fetus across the placenta and via the proximal small intestine during breastfeeding. 3,4 This passive protection slowly declines over the first year of life while the infant's immune system become more mature. 5 The vaccination of pregnant women against tetanus and the influenza virus has recently been proven to be safe and highly effective in providing newborn children with maternally transferred antibodies and, thus, protection from pathogens. [6][7][8] Several antenatal vaccines are now available and recommended for pregnant women whereas others are in development. 9,10 Maternal immunization against tumor-associated antigens, instead, is not a currently rated field and very few preclinical attempts have been made to prevent neonatal congenital tumors by maternal vaccination. 11,12 Most of our recent studies have focused on DNA vaccination against what we have defined as oncoantigens: tumor-associated antigens that have a causal role in the promotion of tumor progression. 13,14 Membrane tyrosine kinase Her2, of the epidermal growth factor receptor family, is expressed by many human carcinomas in association with poor prognosis 15 and fulfills the definition of an oncoantigen. We have demonstrated that vaccination with a plasmid that codes for the extracellular and transmembrane (ECTM) domains of rat Her2 (neu) effectively inhibits mammary carcinogenesis [16][17][18] in female BALB/c mice heterozygous for the transforming form of the neu transgene under the transcriptional control of the mouse mammary tumor virus promoter (BALB-neuT mice). 19,20 Vaccine-elicited tumor inhibition in these mice is driven by anti-neu antibody generation, 16,17 whereas the T-cell cytotoxic response is marginal as T cells that react against neu with high affinity are wiped out by central tolerance. 21,22 The induction of high levels of antibodies following vaccination is also the mainstay of the success of maternal immunization strategy against infectious diseases. In the present study, we seek to evaluate whether maternal immunization can also induce an anti-neu immune response capable of hampering spontaneous tumor progression in BALB-neuT offspring.

Results
Vaccine-induced antitumor antibodies are transferred from mothers to their offspring and delay tumor development Virgin BALB/c female mice were twice vaccinated via electroporation of ECTM plasmid (ECTM mothers) or its empty control vector (control mothers) and mated with a BALB-neuT male soon after their last immunization. No fertility impairment, reduction in litter number, newborn size, or in the percentage of BALB-neuT mice was evident in the comparison between offspring of ECTM mothers, those of control mothers, and those of  mothers (data not shown). The presence of anti-neu antibodies in sera and milk of ECTM mothers was confirmed 2 weeks after the last immunization and 3 weeks after delivery, respectively (Fig. 1A). As expected, passively transferred anti-neu antibodies were found in the sera of offspring born from and fed by ECTM mothers (ECTM offspring), but not in the sera of offspring born from and fed by control mothers (control offspring) ( Fig. 1A and B). The highest anti-neu antibody amount was found at 1 week of age, probably due to colostrum ingestion, and remained high until the fifth weeks. The anti-neu antibody titer dropped from week 6, probably because of offspring weaning at 4 weeks (Fig. 1B).
We have previously shown that the anti-neu antibodies induced by ECTM vaccination of BALB-neuT females halt autochthonous mammary carcinogenesis. 16,17,23 Having found specific anti-neu antibodies in ECTM offspring, we investigated whether these antibodies were able to inhibit mammary carcinogenesis in female BALB-neuT pups (neu C offspring). Indeed, neu C ECTM offspring showed significantly extended tumor-free ( Fig. 1C) and overall ( Fig. 1D) survival over neu C control offspring. At week 23, approximately 35% of neu C ECTM offspring were free from palpable lesions, whereas all neu C control offspring displayed at least one palpable tumor. At week 30, 27% of ECTM offspring were still alive when all control offspring were dead.
The passage of antitumor immunity from mother to offspring was further confirmed by the ability of non-transgenic pups (neuoffspring) from ECTM mothers to hamper the growth of a transplantable tumor induced by a neu C cancer cell line challenge (TUBO cells). 24 Although 100% neucontrol offspring developed TUBO tumors, 2 of the 22 neu -ECTM offspring did not develop a palpable tumor ( Table 1). Moreover, the time required for the TUBO cells to give rise to 2, 4, 6, or 8-mm mean diameter tumors was significantly longer in neu -ECTM offspring than in neucontrol offspring. The 10-mm mean diameter threshold (survival time) was reached in an average time of 34.8 § 1.4 d in neu -ECTM offspring and in 26.8 § 1.3 d in neucontrol offspring ( Table 1).
To determine whether these results obtained with antenatal vaccination can be generalized, BALB/c females were vaccinated against Angiomotin p80 (Amot), an oncoantigen expressed on tumor vasculature, 25 using a plasmid coding for this protein (pAmot). Vaccinated females were then mated with a BALB-neuT male and neu C offspring was evaluated for mammary tumor development. We have previously shown that vaccinationinduced anti-Amot antibodies impair tumor vascularization 26 and significantly delay autochthonous tumor progression 27 in female BALB-neuT mice. Post-vaccination anti-Amot antibody induction was confirmed in pAmot-vaccinated mother sera and milk as well as in the sera of their offspring (pAmot offspring) ( Fig. 2A). Mammary carcinoma onset in neu C female offspring born from and fed by pAmot-vaccinated mothers was significantly delayed compared to female offspring born from and fed by control vaccinated mothers (Fig. 2B).
Finally, to demonstrate that the observed antitumor protection was due to the choice of an oncoantigen as the DNA vaccination target, we vaccinated BALB/c females with a plasmid coding for Escherichia coli b-galactosidase (LacZ plasmid), a tumor-unrelated protein. Vaccinated females were soon mated with a BALB-neuT male and carcinogenesis progression was evaluated in neu C female offspring. Although anti-b-galactosidase antibodies were found in the sera of both LacZ-vaccinated mothers and their offspring, no statistically significant difference in tumor incidence was observed between neu C female offspring born from and fed by LacZ-vaccinated mothers and those born from and fed by control mothers (Fig. 2C and D).

Presence of antibodies and functional FcgRI/III is required to delay mammary carcinogenesis in ECTM offspring
To confirm the role of antibodies in mammary carcinogenesis delay, BALB/c female mice knockout (KO) for the mIg chain (BKO mice), 28 that are thus unable to produce antibodies, were electroporated with ECTM or the empty control vector. Females were mated with a BALB-neuT/BKO male a few days after the last immunization. No statistically significant difference in tumor incidence was observed when autochthonous mammary tumor growth was evaluated in BKO neu C ECTM and control offspring ( Fig. 3A), thus proving that maternally derived antibodies are necessary for effective antitumor protection.
Immunoglobulin G2a (IgG2a) was the most abundant IgG subclass in the milk and sera of ECTM mothers and in the sera of their pups, whereas IgG3 was the least common ( Fig. 3B). This is in line with our previous findings, which demonstrate that ECTM vaccination elicits the activation of T helper cells producing interferon gamma (IFNg), the primary switch factor  29 To further elucidate how these passively transferred antibodies induce tumor delay, BALB/c mice KO for the Fc-gamma I/ III receptors (FcgRI/III) (FcgKO mice) 30 were immunized with ECTM or its empty control vector and mated with a BALB-neuT/FcgKO male. FcgKO neu C ECTM female offspring did not display any significant tumor-onset delay over FcgKO neu C control offspring (Fig. 3C), suggesting that antibody-dependent, cell-mediated cytotoxicity is one of the mechanisms behind vaccine-induced IgG triggering of antitumor protection.
neu extracellular domain-IgG immune complexes are present in ECTM mother's milk and induce an active immune response in offspring Transfer of antigen-IgG immune complexes with breastfeeding is an important mechanism of active immunization in the offspring. We thus set up an ELISA assay to detect extracellular domain ( EC )-IgG immune complexes, showing their presence in ECTM mothers' sera and milk (Fig. 4A). We then evaluated the presence of anti-neu IgM in the offspring sera. As shown in Figure 4B, sera from ECTM offspring had a significant higher level of IgM over that of controls. Moreover, exploiting a B-cell ELISPOT analysis, a significantly higher amount of neu-specific IgM C memory B cells was found in the spleen of 5-week-old ECTM offspring as compared to age-matched control offspring (Fig. 4C).
A further confirmation of an active immune response against neu in ECTM offspring came from the evaluation of the T-cell response. We have previously shown that the ECTM vaccination of wild-type (neu -) BALB/c mice induces the expansion of a public CD8 C T-cell clone, which reacts at high avidity against the immunodominant neu nonamer peptide (p63-71). On the other hand, this high-avidity CD8 C T-cell clone is deleted in BALB-neuT mice because of neu expression in the thymus and its early overexpression in the mammary gland. 21 Indeed, our ECTM mothers displayed increased in vivo cytotoxic activity against splenic cells pulsed with p63-71 over control mothers (Fig. 5A). In a similar assay, no specific cytotoxic response was found against p63-71 in control offspring, whereas it was evident in the ECTM offspring (Fig. 5A). Surprisingly, no significant differences in lysis percentage were found in neuand neu C ECTM offspring, while a lower, if any, cytotoxic response was expected in neu C ECTM offspring. We then checked the T-cell receptor (TCR) repertoire used to react against p63-71 in these mice in order to shed light onto the origin of the cytotoxic activity found in the pups. Popliteal, inguinal, and mesenteric lymph nodes (LNs) were collected from ECTM mothers 5 weeks post delivery as well as from their 5-week-old offspring and the expansion of specific p63-71 TCR repertoires of CD8 C T cells was evaluated. We have previously identified a public TCR rearrangement, the Vb9-Jb1.2 recombination, elicited by ECTM vaccination in BALB/c mice that recognizes the p63-71 peptide with high avidity and is wiped out by central tolerance in BALB-neuT mice. 21 The expansion of this repertoire was found in all ECTM mothers as well as in 3 out of 5 neu -ECTM offspring whereas, as expected, none of the neu C ECTM offspring presented this TCR rearrangement (Fig. 5B). We then evaluated the expansion of the Vb6-Jb2.7 rearrangement. This is a low-avidity CD8 C T-cell clone that is specific for p63-71 and is induced by ECTM vaccination, but normally controlled by peripheral tolerance  mechanisms such as T-regulatory cell (Treg) expansion in adult BALB-neuT mice. 22 The Vb6-Jb2.7 rearrangement expansion was found in 5 out of 7 neu C ECTM offspring and in none of the neu C control offspring (Fig. 5B). These data rule out the possibility that the cytotoxic response found in the ECTM offspring is due to maternal CD8 C T cells being passively transferred via the milk and confirm the induction of an active immune response in the pups.
CD8 C T-cell activation in ECTM offspring was also confirmed in vitro with an IFNg-based ELISPOT assay after splenic cell stimulation using the p63-71 peptide (Fig. 5C). Again, no statistically significant difference between neuand neu C ECTM offspring was found.

Discussion
The data reported in this article show that maternal DNA immunization against neu impairs the onset of mammary tumors in cancer-prone neu C offspring. After DNA vaccination, high levels of IgG against the target oncoantigen can be detected in both, sera and milk of vaccinated mothers, although at lower levels in the milk. We observed that vaccine-induced IgG were successfully transferred to the offspring. Similar results were obtained when maternal DNA immunization was carried out against another oncoantigen, Amot, but not against the unrelated antigen b-galactosidase.
The passive transfer of maternal antibodies, in humans and other mammals, occurs via placental and milk transfer of IgG through the neonatal Fc receptor (FcRn) and via polymeric IgA milk transfer. In humans, FcRn is expressed by the syncytiotrophoblast where it antenatally transports IgG from maternal circulation to the fetal capillaries of the placental villi. 4 By contrast, in rodents the FcRn functions most efficiently in the neonatal period when it transports maternally derived IgG in ingested milk across the epithelial-cell layer of the proximal intestine. 4 Besides being the main source of passive immunity in very early life, breastfeeding is also an important route for active immunization thanks to the efficient transfer of antigen-IgG immune complexes, contained in the milk, to the breastfed pups via the FcRn and across the proximal intestine. 31 We thus hypothesized that vaccine-transfected muscle cells might be the source of the neu protein, otherwise not present in a wild-type mouse. As happens normally, EC may be shed from transfected muscle cell membranes, 32 form complexes with vaccine-induced anti-neu antibodies, and accumulate in the milk and be passed to the pups, triggering an active immune response. To confirm this hypothesis, an ELISA assay was set up to detect EC -IgG immune complexes that were found in the sera and milk of ECTM mothers.
We then sought to evaluate whether these EC -IgG immune complexes were able to induce an active immune response in the pups. An initial indication of this came from a significantly higher level of IgM against neu and of neu-specific IgM C memory B cells in ECTM offspring over control. However, the proof of active immunization in breastfed pups came from the observation of an in vivo cytotoxic response against the neu p63-71 peptide in ECTM offspring. It is known that live-activated leukocytes, including CD8 C T cells, are present in mother's milk, and that they can be transferred during breastfeeding and that they can enter pups' intestinal tract tissue and mesenteric LNs in some species. 31 It can be hypothesized, in the case of syngeneic strains, that these passively transferred cells may survive in the pups and be found in mesenteric LNs 5 weeks after birth, when the in vivo cytotoxicity assay was conducted. Nevertheless, this possibility was ruled out by the results of the Vb-Jb spectratype analysis. We observed the expansion of CD8 C T cells bearing the Vb9-Jb1.2 rearrangement in all ECTM mothers but in none of their neu C offspring; this Vb-Jb rearrangement is normally used as public in ECTM-vaccinated BALB/c mice. 21 On the other hand, in 71% of neu C ECTM offspring, there was expansion of low-avidity CD8 C T cells bearing the Vb6-Jb2.7 TCR rearrangement that is typical of ECTM-vaccinated BALB-neuT, but not BALB/c, mice. 22 Indeed, we have recently shown how a temporary Treg depletion and ECTM vaccination in BALB-neuT mice was able to induce the expansion of latent pools of lowavidity CD8 C T cells bearing TCR repertoires that react with p63-71. 22 The Vb6-Jb2.7 rearrangement, the same that expanded in neu C ECTM offspring in the present study, was among them. Preliminary data show a decrease in spleen-derived Treg percentage in neu C ECTM offspring as compared to neu C control offspring at the fifth week of age (data not shown). This may explain the presence of reactive, although low-avidity, CD8 C T-cell clones in neu C ECTM offspring.
In conclusion, taken together these findings are proof of concept of the efficacy of maternal immunization against an oncoantigen. They are of particular relevance because, in BALB-neuT mice, neu is already expressed in nascent tumors and is the driving force of mammary transformation. 20 We herein suggest that the concept of maternal immunization, being a potent weapon against pathogen-induced diseases in newborns, can be extended and used to delay cancer development in genetically predestinated offspring. The potential applications of this groundbreaking approach to neonatal cancer diseases such as neuroblastoma, rhabdomyosarcoma, Wilms' tumor, and retinoblastoma may have a substantial impact on clinical practice.

Materials and Methods
Mice BKO 28 and FcgKO mice 30 were crossed with BALB-neuT mice to generate BALB-neuT/BKO and BALB-neuT/FcgKO mice, respectively. All mice were bred under specific pathogen-free conditions at the Molecular Biotechnology Center (Torino, Italy) and treated in conformity with European Guidelines and policies, as approved by the Ethical Committee of the University of Torino.

Cells
TUBO cells, an in vitro-established neu C cell line derived from a lobular carcinoma arising in a BALB-neuT female mouse, 24 were cultured in Dulbecco's modified Eagle's Medium (DMEM) supplemented with GlutaMAX TM , D-glucose, HEPES buffer (Gibco), and 20% fetal bovine serum (FBS; Sigma-Aldrich).

Immunization and tumor growth
The pCMV3.1 control and the ECTM, 16 the pcDNA3 and pAmot 26 plasmids were generated as previously described. The pAAV-MCS (control plasmid) and the pAAV-MCS plasmid coding for Escherichia coli b-galactosidase (LacZ plasmid), were from the AAV Helper-Free System (Agilent Technologies Inc.). Fifty micrograms of plasmids diluted in saline were injected into the quadriceps muscle of anesthetized mice. Immediately after injection, 2 25-ms transcutaneous low-voltage electric pulses (amplitude 150 V; interval 300 ms) were administered at the injection site via a multiple-needle electrode connected to a Cliniporator TM (IGEA Srl). Female mice were immunized at 10 and 12 weeks of age and mated at week 13. All pups were fed by their own mothers and weaned at 4 weeks of age. The mammary glands of BALB-neuT female offspring were inspected weekly for tumor appearance from the twelfth week of age. The 5-week-old neuoffspring were challenged subcutaneously in the inguinal region with 1 £10 5 TUBO cells. Tumor masses were measured as previously described. 35 Assessment of anti-neu and anti-Amot antibodies Sera from mothers were collected 2 weeks after the last vaccination. Pups' sera were collected from 1 to 8 weeks after birth. Mothers were separated from their litters 3 weeks after delivery for milk collection and fed with hydrated food for 24 h. Then, 2 IU of oxytocin (PitocinaIniet; Farmaceutici Gellini Srl) were injected twice intraperitoneally at an interval of 5 min between each administration. Milk was manually expressed from anesthetized mice, collected, and mixed with a protease inhibitor cocktail (Sigma-Aldrich). Defatted milk was obtained after an initial room temperature centrifugation for 10 min, at 2,000 rpm and 2 subsequent 4 C centrifugations at 12,000 rpm for 90 min. Sera and milk samples were tested by ELISA. Then, 96-well plates (Costar Ò , Sigma-Aldrich) were coated with 100 ng/well of recombinant EC neu (Genway) or recombinant human-Amot (Origene) protein, overnight at 4 C. Coated plates were then blocked with 10% Newborn Calf Serum (NCBS; Sigma-Aldrich) in phosphate-buffered saline (PBS; Invitrogen)-Tween (Sigma-Aldrich) 0.05% buffer for 2 h at 37 C. Plates were incubated with samples diluted 1:100 in 1% blocking buffer for 1 h at 37 C. Plates were washed 3 times with a PBS-Tween buffer. The horseradish peroxidase (HRP)-conjugated anti-mouse IgG antibody (Sigma-Aldrich; 1:2,000 dilution in blocking buffer) was incubated for 1 hour at 37 C. Plates were washed 6 times and chromogenic 3,3 0 ,5,5 0 -tetramethylbenzidine substrate was added (TMB; Sigma-Aldrich). The reaction was stopped by the addition of 2N hydrochloric acid and optical density was measured at 450 nm using a microplate reader (680XR, BioRad). IgG isotype titration was carried out using rat biotin-conjugated anti-mouse IgG1, IgG2a, IgG2b, IgG3, and IgM (BD PharMingen) as secondary antibodies. Plates were then incubated for 30 min at room temperature with streptavidin-HRP (R&D Systems) diluted 1:200 in a PBS-Tween buffer and reactions were carried forward as described earlier.
Memory B-cell ELISPOT Splenocytes (SPC) from 5-week-old control and ECTM offspring were collected and stimulated with a mixture of R848 (1 mg/mL, Mabtech) and rmIL-2 (10 ng/mL, Mabtech). Then, 72 h later, B cells were isolated by positive immune selection after SPC incubation with a biotin-antibody cocktail against CD43 (BD PharMingen) and CD11c (eBioscience) for 20 min at 4 C, followed by an incubation for 10 min at 4 C with Anti-Biotin MicroBeads (Miltenyi Biotec). Thereafter, 1 £10 5 B cells were plated in triplicate on polyvinylidene fluoride (PVDF) ELISPOT plates (Mabtech) pre-coated with 20 mg/mL of recombinant EC neu protein. Plates were incubated for 24 h at 37 C and developed according to manufacturer's instructions (ELISpotPLUS, Mabtech). Specific spots were enumerated using the Transtec 1300 ELI-SPOT Reader (AMI Bioline). The number of specific spots was calculated by subtracting the number of spontaneously produced spots and expressed as spot-forming unit (SFU)/10 6 cells.

Immunoblotting
A total cell lysate from mouse cardiomyocytes that express b-galactosidase protein after recombinant Adeno-associated virus 2 viral particles (kindly provided by Prof. Emilia Turco, Molecular Biotechnology Center, University of Torino) infection was separated by SDS-PAGE. Sera from vaccinated mothers and from their 3-week-old offspring were collected, pooled, diluted 1:50 in Trisbuffered saline and Tween 20 (TTBS) and incubated overnight at 4 C on the membrane, as the primary antibody. Goat anti-mouse HRP secondary antibody (Sigma-Aldrich) was used for detection. Polyclonal rabbit anti-b-galactosidase (Thermo Scientific) and anti-HSP90 antibody (Santa Cruz Biotechnology) were used as positive and loading control, respectively, and detected by goat anti-rabbit HRP (Sigma-Aldrich). Proteins were detected by enhanced chemiluminescence (ECL Ò , Amersham Biosciences).
In Vivo cytotoxicity assay For this assay, 10 7 naive SPC/mL were labeled with two different concentrations (0.5 or 5.0 mmol/L) of the fluorescent dye CFSE (Molecular Probes); 5 mmol/L labeled-SPC were also pulsed with p63-71 (TYVPANASL; InBios Srl) for 90 min at 37 C. The two SPC populations were mixed in equal amounts and injected into the tail vein of control or ECTM mothers 2 weeks after the last vaccination and into 5-week-old control or ECTM offspring. Forty-eight hours later, single-cell suspensions from the spleen of each mouse were processed to evaluate the presence of CFSE high -and CFSE low -labeled SPC on a CyAn ADP Flow Cytometer (DakoCytomation). The low peak percentage was normalized to control untreated low peaks and the specific cytolytic activity was calculated as: 100 -[(CFSE low untreated cells / CFSE low experimental cells) £ CFSE high experimental cells] £ 100 / CFSE high untreated cells.
TCR repertoire analysis Popliteal, inguinal, and mesenteric LNs were collected from 5-week-old control and ECTM offspring and cultured for 3 d with or without 15 mmol/L of p63-71. Total RNA was isolated from the recovered LNs cells using the RNeasy Mini Kit (Qiagen) according to manufacturer's instructions. cDNA was synthesized using an oligo-dT primer (dT15; Invitrogen). cDNA was subjected to PCR amplification using a common Constant (C) b primer (CACTGATGTTCTGTGTGACA) in combination with the following Vb primers: 6, CTCTCACTGTGA-CATCTGCCC; 9, TCTCTCTACATTGGCTCTGCAGGC. Using 2 mL of PCR product as a template, run-off reactions were carried out with the following internal fluorescent Jb: 1.2, AAAGCCTGGTCCCTGAGCCGAAG; 2.7, CTAAAACCGT-GAGCCTGGTGC. Run-off products were denatured in formamide and analyzed on an Applied Biosystem 3100 Prism using Gene-scan 2.0 software (Applied Biosystem). Data were reported as the rate of stimulation index (RSI): normalized peak area from stimulated cells/normalized peak area of non-stimulated cells. T cells carrying a TCR rearrangement were considered to be expanded in a vaccination-driven manner when RSI was >2. 21

EC-IgG immune complex detection
The 96-well/plates (Costar Ò , Sigma-Aldrich) were coated with 200 ng/well of the anti-CD340 monoclonal antibody (Sino Biological Inc.), saturated with 5% NCBS in PBS-Tween 0.05 % for 1 h at 37 C and, after several washes, the plates were incubated for 2 h at 37 C with a 1:50 dilution of both milk and serum followed by HRP-conjugated anti-mouse IgG antibody. The following reactions were carried forward as described for the detection of anti-neu antibodies.
IFNg ELISPOT assay For this assay, 1 £10 6 SPC from 5-week-old control and ECTM offspring were plated in triplicate into nitrocellulose 96-well HTS IP plates (Millipore, Bedford, MA) that had been pre-coated with 5 mg/mL of rat anti-mouse IFNg antibody (clone R4-6A2, BD Biosciences). SPCs were stimulated for 48 h at 37 C with 15 mg/ mL of p63-71. Plates were developed according to manufacturer's instructions (BD TM ELISPOT Set, BD Biosciences). Spots were enumerated as described earlier.

Statistical analysis
Statistical differences were evaluated using the GraphPad software 5.0 (GraphPad Inc.). The Mantel-Haenszel Log-rank test was used to analyze differences in the incidence of tumors, while the Student's t-test was used for the evaluation of all other statistical differences.

Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.


s2fieldsofstudy: Biology Medicine

text:
Drug sensitivity in cancer cell lines is not tissue-specific

Background Cancer cell lines have a prominent role in the initial stages of drug discovery, facilitating high-throughput screening of potential drugs. However, their clinical relevance remains controversial. Findings We assess whether drug sensitivity in cancer cell lines is able to discriminate tissue specificity. We find that cancer-specific drugs do not show higher efficacies in cell lines representing the respective tissues. Even when considering distinct cancer subtypes and targeted therapies, most drugs are evenly effective/ineffective throughout all cell lines. Conclusions To get the most out of cell line panels, it will be necessary to look into their molecular characteristics, and integrate them into systems biology frameworks. Electronic supplementary material The online version of this article (doi:10.1186/s12943-015-0312-6) contains supplementary material, which is available to authorized users.

Human cancer cell lines are widely used in vitro models for studying cancer and its biology [1]. Apart from being valuable tools for identifying biomarkers and genetic variants that impact drug sensitivities [2,3], cancer cell lines play a pivotal role in the early stages of drug discovery, facilitating the screening of hundreds of potential drugs and their combinations before translating the outcomes into in vivo models and expensive clinical trials [4,5].
However, despite their fundamental role in biomedical research, the clinical relevance of cell lines remains highly controversial [6,7]. Apart from known technical and biological limitations, like contamination, missing tumor microenvironment, or lack of drug distribution and metabolism, the main concern is whether cancer cell lines are true representatives of primary tumors [8]. Prolonged culturing of immortalized cell lines may induce extensive modifications in their molecular characteristics, like secondary genomic changes [7,9], and it remains unclear how closely they still resemble the original tissue after undergoing a certain number of passages. To complement the ongoing debate from a pharmacological perspective, we analyzed the predictive power of cancer cell lines for elucidating cancer-specific drug responses. Considering the widely used NCI-60 panel [5], we assessed whether drugs for a particular cancer type display a higher efficacy in cell lines supposedly representing the respective cancer tissue. We focused on three cancer types, namely, breast, colorectal and prostate cancer, represented by five, seven and two cell lines, respectively, in the NCI-60. We analyzed all the 75 compounds, approved or experimental, associated with the treatment of these cancers that have also been tested in the NCI-60 (Additional file 1: Table S1 and Additional file 2: Table S2). We examined the sensitivity of each drug by considering its GI50 across the complete NCI-60 panel, derived from nine cancer tissues. The GI50, similar to IC50 and EC50, indicates the concentration required to inhibit cell proliferation by 50%, relative to untreated samples [5]. Note that we studied the activity of final drugs instead of the preliminary hit compounds expecting that the former remain active after preclinical optimization. Figure 1A shows the sensitivity of the corresponding cancer cell lines towards cancer-specific agents (highlighted in red) in comparison to the sensitivity measured in cell lines representing other cancer tissues. Surprisingly, cancer-specific drugs do not show a significantly higher activity in cell lines representing the respective tissue (Wilcoxon test with Bonferroni correction for multiple testing; see Additional file 1). The same trend can be observed when focusing only on approved drugs or more specific targeted agents, and after normalizing drug sensitivity values across cell lines. To avoid biases caused by drugs with multiple therapeutic indications, we also analyzed more restrictive sets containing compounds exclusively associated with breast, colorectal or prostate cancers, obtaining equivalent outcomes (Additional file 1: Figures S1, S2 and S3). Overall, our results indicate that a simple Figure 1 Tissue specificity displayed by caner-specific drugs. (A) Sensitivity of cancer-specific drugs intended for breast cancer (41), colorectal cancer (24) and prostate cancer (38) across the NCI-60 panel covering 59 cancer cell lines derived from nine cancer tissues. The GI50 represents the negative log of the concentration that is required to inhibit the growth of a cell line by 50%. Each box represents the distribution of drug activities in a given cell line. Cell lines are organized in tissue slots. In red, we highlight the cell lines representing the intended tissue of the drugs. (B) Breast cancer subtype-specific analysis. Stratification of targeted agents according to the different breast cancer subtypes. Note that agents might be used for more than one subtype. (C) Sensitivity of HR-positive and triple negative breast cancer drugs with respect to subtype-specific breast cancer cell lines. Red indicates high drug activity while green indicates inactivity for a given cell line.
selection of cell lines according to the tissue of interest does not reflect the eventual complexity in the clinics.
Given the intrinsic heterogeneity of most cancers [10], no individual cell line is likely to be a general representative for the distinct cancers derived from one tissue [11]. Hence, we do not expect a tissue-specific drug to perform equally well across the corresponding cell lines. Breast cancer, for instance, is a heterogeneous disease with at least four recognized subtypes that require a specific treatment [12,13]. Most researchers select particular cell lines based on receptor status, common genetic mutations, molecular signatures, tumor type, as well as technical or methodological limitations for their experiments [14]. Thus, mimicking this common approach, we considered the presence or absence of biomarkers that define the distinct breast cancer subtypes. Next we examined whether subtype-specific responses are reflected in cell lines representing distinct subtypes. The NCI-60 covers two subtypes, the triple-negative breast cancer (BT-549, HS-578 T and MDA-MB-231) and the HR-positive breast cancer subtype (MCF7 and T-47D). Neither the HER2overexpressing nor the normal-like subtypes are included in the panel. Among the 25 targeted breast-cancer agents, 18 are indicated for HR-positive patients, 6 for triplenegative and 4 for HER2-overexpressing breast cancer ( Figure 1B and Additional file 1: Table S3). According to this stratification, we assessed the sensitivity of the subtype-specific drugs in the corresponding cell lines. Figure 1C shows that the majority of drugs is equally active or inactive independent of the breast cancer subtype. Figitumumab, vandetanib, and gefitinib (I), for example, are evenly effective in HR-positive and triplenegative cell lines, while aromatase inhibitors like letrozole, anastrozole and aminoglutethimide are basically inactive and would not have been discovered through screening cell lines from this panel. Only four out of 18 HR-positive drugs, i.e., PD-332991, raloxifene, tamoxifen (I), and fulvestrant, exhibit a higher specificity in at least one of the HR-positive cell lines. Conversely, midostaurin, a targeted drug against HR-positive tumors, only shows activity in triple-negative cell lines. As the NCI-60 only involves five breast cancer cell lines, which only partially reflect the distinct subtypes, we performed the same analysis on the more comprehensive Cancer Cell Line Encyclopedia (CCLE) [15]. Considering 30 breast cancer cell lines and 14 targeted agents, both stratified into subtypes, we still observe a largely varying compound sensitivity rather than subtype-specific responses in the corresponding cell lines (Additional file 1: Figure S4). Thus, even when accounting for subtype-specific differences in the NCI-60, or considering a much larger cell line panel with a broader representation of breast cancer subtypes [15] (see Additional file 1: Figure S4), the previously observed tendencies regarding tissue specificity still hold.
Similarly, we investigated whether intended drug targets are expressed in the corresponding cell lines and, if so, whether the drug is active in this cell line, exploiting proteomics data of NCI-60 [16]. Again, we could not correlate target expression with drug sensitivity (Additional file 1: Figure S5). One of the few exceptions is presented by the set of EGFR modulators, Gefitinib and Erlotinib, to which cell lines are indeed more sensitive when EGFR is expressed. Yet, in the majority of instances drug activity does not depend on the presence or absence of the intended targets, which indicates that several factors, beyond target expression, determine drug sensitivity.
Although alternative models for drug screening and development are generated [9], cancer cell lines have been and will be an essential component of cancer research and drug discovery [17]. However, as we observed, relying on assays performed in a few selected cell lines may result in incorrect or misleading conclusion, and thus is unlikely to predict clinical outcomes. Cell line panels, on the other hand, may embrace the underlying complexity and variability of cancer. Yet, to fully exploit their invaluable potential, we have to move beyond 'one marker, one cell line' studies and incorporate the large amount of molecular ('omics') profiles into robust systems biology frameworks [15,16,[18][19][20]. We believe that identifying and combining the key features that each cell line is able to reproduce, beyond tissue and subtype specificity, will bring screening panels at the forefront of a more successful drug discovery.

Additional files
Additional file 1: Table S1. Summary of cancer-specific drugs assembled and mapped per cancer type. BCbreast cancer, CRCcolorectal cancer, PCprostate cancer. Note that some drugs could be mapped onto several NCI-60 tested compounds. Table S3. Classification of targeted breast cancer agents tested in the NCI-60 into distinct subtypes according to the FDA Orange Book, the NCI, ClinicalTrials.gov and the literature. Bbasal/triple negative, HRhormone receptor positive, H2 -HER2-overexpressing cancer, Usubtype indication unknown. Table S4. Classification of targeted breast cancer agents, screened in the CCLE, into distinct subtypes according to the FDA Orange Book, the NCI, ClinicalTrials.gov and the literature. Bbasal/triple negative, HRhormone receptor positive, H2 -HER2-overexpressing cancer, Usubtype indication unknown. Figure S1. Sensitivity of the breast cancer-specific drug sets considering (A) approved and (B) targeted drugs, (C) normalized drug sensitivities, as well as (D) Unique and (E) Unique* drugs. Figure S2. Sensitivity of the colorectal cancer-specific drug sets considering (A) approved and (B) targeted drugs, (C) normalized drug sensitivities, as well as (D) Unique and (E) Unique* drugs. Figure S3. Sensitivity of the prostate cancer-specific drug sets considering (A) approved and (B) targeted drugs, (C) normalized drug sensitivities, as well as the (D) Unique and (E) Unique* sets. Figure S4. Sensitivity of drugs indicated for hormone receptor positive, triple negative and HER2-overexpressing breast cancer within 30 breast cancer cell lines representing the different subtypes. Sensitivity is indicated in terms of the IC50. Red cells indicate high activity while green cells indicate inactivity. Figure S5. Contingency tables grouping target expression and discretized drug sensitivity of cell lines. Repeated instances, such as EPHA2 -Dasatinib, correspond to different NCI-60 compounds, i.e., different formulation of the same drug.


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P70S6 Kinase Phosphorylation: A New Site to Assess Pharmacodynamy of Sirolimus

Background: The phosphorylation of p70S6 kinase (p70S6K) represents an important target for sensitive detection on pharmacodynamic effects of sirolimus, but the methods of assessing p70S6K phosphorylation are still unclear. The aim of this study was to investigate p70S6K phosphorylation located down-stream of the mammalian target of rapamycin (mTOR) pathway in peripheral blood mononuclear cells (PBMCs) of liver transplant patients through different methods. Methods: Seventy-five liver transplant recipients from Beijing Chaoyang Hospital of the Capital Medical University were analyzed in this study. Patients were divided into three groups, patient treated with sirolimus (n = 22), patient treated with tacrolimus (n = 30), patient treated with cyclosporine (n = 23). The p70S6K phosphorylation of PBMCs in patients and healthy control (HC, n = 12) were analyzed by phospho-flow cytometry and Western blotting. A correlation analysis of data from phospho-flow cytometry and Western blotting was performed. Intra-assay variability of p70S6K phosphorylation in HC and different patients were measured. Results: Intra-assay variability of p70S6K phosphorylation in phospho-flow cytometry was from 4.1% to 8.4% and in Western blotting was from 8.2% to 18%. The p70S6K phosphorylation in patients receiving a sirolimus (19.5 ± 7.7) was significantly lower than in HC (50.1 ± 11.3, P < 0.001), tacrolimus (37.7 ± 15.7, P < 0.001) or cyclosporine treated patients (41.7 ± 11.7, P < 0.001). The p70S6K phosphorylation in HC (50.1 ± 11.3) was significantly higher than in tacrolimus (37.7 ± 15.7, P < 0.01) or cyclosporine-treated patients (41.7 ± 11.7, P < 0.01). There was correlation between data from phospho-flow cytometry and data from Western blotting (r = 0.88, P < 0.001). Conclusions: The degree of mTOR inhibition by assessing p70S6K phosphorylation was established by phospho-flow cytometry and Western blotting. Assessment of p70S6K phosphorylation may play an adjunct role to on pharmacodynamically guide and individualize sirolimus based on immunosuppression.

cells (PBMCs) of liver transplant patients who received different immunosuppressive drug regimens with or without sirolimus by phospho-flow cytometry and Western blotting. A correlation analysis of data from phospho-flow cytometry and Western blotting were performed.

Patients
Seventy-five liver transplantation patients were admitted to the out-and in-patient care of the Hepatobiliary Surgery Department of Beijing Chaoyang Hospital of the Capital Medical University. The study protocol was approved by the institutional review board and conducted from May 2012 to December 2013. Patient inclusion criteria: (1) Patients gave written informed consent to participate. (2) All patients were treated with immunosuppressant after liver transplantation. Patient exclusion criteria: (1) Patients with immunological diseases, hepatitis, HIV positive, hematologic malignancies. (2) Patients with acute infection chronic infection. Seventy-five liver transplantation patients were divided into three groups, 22 patients treated with sirolimus, 30 patients treated with tacrolimus, 23 patients treated with cyclosporine, respectively. Twelve healthy control (HC) were served as a control group in this study. The age and gender distribution among liver transplantation patients and HC was not significantly different from each other (P = 0.38, P = 0.61; respectively). HC did not have an acute infection or immunological diseases in medical history.

Cell cultures
Peripheral blood mononuclear cells were separated from 20-ml heparinized blood samples by standard Ficoll-Paque density gradient centrifugation. This experiment was divided into two parts. For Part 1, the p70S6K phosphorylation in PBMCs of liver transplant patients receiving different immunosuppressive drug regimens by phospho-flow cytometry and Western blotting. Data were analyzed using FlowJo Software (Version 8.7.3, Tree Star, USA) in flow cytometry. The level of phosphorylation p70S6K was quantified by the mean fluorescence intensity index (MFI index). The reactive bands were detected by chemiluminescence and signal intensity was densitometrically quantitated in Western blotting (Image J, version 2.1.4.7, National Institutes of Health, USA). The level of phosphorylation p70S6K was quantified by relative gray density values which were calculated by dividing gray density of target band by gray density of loading control. For Part 2, PBMCs were stimulated with phorbol-12-myristate-13-acetate (PMA, Sigma, Germany), ionomycin (Sigma) and rapamycin (Sigma) (0 ng/ml, 0.1 ng/ml, 1 ng/ml, 5 ng/ml and 10 ng/ml) and analyzed by flow cytometry and Western blotting after 40 h of incubation in 5% CO 2 at 37°C.

Statistics analysis
All statistical analysis was performed using SPSS version 17.0 (SPSS Inc., Chicago, IL, USA). Data were given as mean ± standard deviation (SD) and analyzed using one-way analysis of variance (ANOVA) for more than two groups. Data were compared using the two-tailed Student's t-test for normally distributed population and Mann-Whitney U-test for not normally distributed population. Correlation analysis was performed with Pearson's test after proving normal distribution of data. P < 0.05 was considered statistically significant.

Baseline characteristics, laboratory data of liver transplantation patients and healthy volunteers
Seventy-five liver transplantation patients (32 females and 43 males, mean age 56 ± 11 years, range 13-72) and 12 HC (5 females, 7 males, mean age 52 ± 13 years old, range 18-75) were served as control group in this study. The age and gender distribution between liver transplantation patients and HC was not significantly different from each other (P = 0.38, P = 0.61, respectively) [ Table 1].

Assessing intra-assay variability of phosphorylation p70S6 kinase by phospho-flow cytometry
To investigate validity and repeatability of the assay, intra-assay precision was determined in healthy subjects (n = 3) [ Table 1] and liver transplant patients receiving sirolimus, tacrolimus, or cyclosporine (n = 3 each). Isolated PBMCs were stained and assessed by phospho-flow cytometry in triplicates for each patient. The mean coefficient of variance (CV) values for intra-assay variability in different groups was from 4.1% to 8.4% [ Table 2].

Assessing intra-assay variability of phosphorylation p70S6 kinase by Western blotting
To compare and confirm the data generated in the phospho-flow cytometry assay, the phospho-flow technique was compared with Western blotting analysis of phosphorylation of p70S6K in healthy subject (n = 1) and liver transplant patients receiving sirolimus, tacrolimus or cyclosporine (n = 1 each) [ Figure 1a]. The bar graphs showed the respective analysis of triplicate Western blotting densitometric measurements expressed in pixel values (HC: 0.79 ± 0.10; cyclosporine: 0.63 ± 0.07; tacrolimus: 0.55 ± 0.06; sirolimus: 0.18 ± 0.03). The mean CV value for intra-assay variability was 8.2% for healthy individuals, 18% for patients receiving tacrolimus, 15% for cyclosporine and 16% for sirolimus, respectively. A representative Western blotting for phosphorylation of p70S6K was assessed in PBMCs of a healthy subject and a patient receiving cyclosporine, tacrolimus or sirolimus, respectively [ Figure 1b].

Assessing p70S6 kinase phosphorylation by phospho-flow cytometry is comparable to the Western blotting method
Correlation between MFI index and Western blotting values was shown in various immunosuppressive agent groups. MFI index was used to indicate the flow cytometry results while normalized mean pixel value was used to indicate the Western blotting data. The analysis of the obtained results revealed a high correlation coefficient (n = 75, r = 0.88, P < 0.001) [ Figure 3].

Incubation of peripheral blood mononuclear cells with rapamycin, phorbol-12-myristate-13-acetate, and ionomycin
To confirm the validity of the phospho-flow assay in vitro experiments, the phosphorylation status of p70S6 in mitogen-stimulated PBMCs was incubated in presence or   (a and b). b a absence of rapamycin plus PMA and ionomycin for 40 h. Phospho-flow analysis revealed that addition of rapamycin reduced the p70S6K phosphorylation in PBMCs of healthy volunteers (n = 3) in a dose-dependent manner [ Figure 4a] and this was confirmed in a representative Western blotting [ Figure 4b].
dIscussIon Transplantation rejection is an adaptive immune response caused by cell-mediated and humoral immunity. Activation of T-cell, interleukin-2 (IL-2) production and secretion play important roles in transplantation. The sirolimus bind to FKBP12, which interacts with the FKBP12 rapamycin binding domain of mTOR, leads to a decrease in messenger RNA translation and protein synthesis. This results in cell-cycle arrested in G1 phase, and it is important to suppress immunological response.
The phosphorylation of a protein correlates with its biological functions. For kinases, phosphorylation enhances their enzymatic activity and conduct signals to downstream regulations. Previous studies found there were three phosphorylation sites of p70S6K (S404, Thr389 and Thr229) to be sirolimus sensitive and showed that dephosphorylation of Thr389 most closely correlated with loss of kinase activity. [11,12] Moreover, site-directed mutational analysis has revealed that Thr389 represents the principal site of sirolimus mediated inactivation of p70S6K and most closely correlates with loss of kinase activity. [13] Inhibition of mitogen-induced p70S6K activation in vivo with either by treatment with the neutralizing antibodies or immunosuppressant sirolimus severely compromises the processing ability through the G1 phase in the cell cycle. [14] The aim of this study was to investigate Thr389 phosphorylation of p70S6K in PBMCs of liver transplant patients who received different immunosuppressive drug and HC by phospho-flow cytometry and Western blotting.
To investigate validity and repeatability of the assay, intra-assay precision was determined in healthy subject and liver transplant patients receiving sirolimus, tacrolimus, or cyclosporine. Isolated PBMCs were stained and assessed by phospho-flow cytometry and Western blotting in triplicates. The range of mean CV value of intra-assay variability assessed by phospho-flow cytometry was from 4.1% to 8.4%. Meanwhile,   b a the mean CV values for of intra-assay variability assessed by Western blotting ranged from 8.2% to 18%. Compared with Western blotting, phospho-flow cytometry showed a smaller intra-assay variability and better stability and repeatability.
Hartmann et al. [15] showed patients treated with sirolimus had a reduced phosphorylation of p70S6K in PBMCs as compared to patients treated with tacrolimus, cyclosporine by Western blotting. In this study, MFI index of PBMCs in patients treated with sirolimus was significantly lower than those with cyclosporine, tacrolimus, and HC. MFI index of patients treated with cyclosporine and tacrolimus was significantly lower than HC [ Figure 2]. Sirolimus blocks the mTORC1 and results in a decrease of p70S6K phosphorylation. Cyclosporine and tacrolimus are calcineurin inhibitors, the former binding to calcineurin, and the latter to FKBP12. In both cases the dephosphorylation of the transcription factor nuclear factor of activated T-cell is inhibited, resulting in a decrease of IL-2 production from T-cell. [16] IL-2 is a T-cell-derived-cytokine which is secreted as a soluble molecule by activated T-cell and activates dendritic cells in immune response and regulates growth and proliferation of T-cell, B-cell and natural killer cells. Interaction of IL-2 with its respective receptor leads to activation of various signaling pathways, including the PI3K-AKT pathway results in up-regulation of mTOR activity. Therefore, the activity of p70S6K in patients receiving cyclosporine or tacrolimus could be reduced by inhibition of IL-2 production and decreased in its paracrine stimulatory effects. Since tacrolimus is more potent calcineurin inhibitor, it may result in a slightly lower p70S6K phosphorylation compared to that of cyclosporine-treated patients [ Figure 2].
In order to further validate the data from the phospho-flow cytometry assay, the activity of p70S6K of PBMCs was measured by Western blotting, and the mean gray value was calculated as well. Both methods were comparable and highly correlating with each other (n = 75, r = 0.88, P < 0.001) [ Figure 3]. Analysis of the phosphorylation status of the p70S6K via phospho-flow technique provides reliable information on the extent of mTOR inhibition exerted by sirolimus, and the result is comparable to the Western blotting method.
Phorbol-12-myristate-13-acetate and ionomycin were stimulators in immunology assays, which were able to up-regulate p70S6K phosphorylation. [17] In this present study, PBMCs from HC were isolated and incubated with rapamycin in various concentrations. PMA and ionomycin in the presence of IL-2 for 40 h. The results suggested that the activity of p70S6K was up-regulated by PMA inomycin stimulation and suppressed by sirolimus in a dose-dependent manner, which was also verified by Western blotting.
The results shown above were consistent with the one of research of Leogrande et al. [18] which indicated that the decrease in p70S6K phosphorylation was caused by the PBMCs stimulated with insulin and incubated with rapamycin. The present study also indicated that sirolimus can effectively inhibit the activity of mTOR pathway in vitro and in vivo.
Sirolimus has significant inter-individual and intra-individual therapeutic range. Inhibition of mTOR pathway did not correlate with the respective sirolimus trough levels, a finding described by Hartmann et al. by Western blotting technique. These results suggest that the adjustment of sirolimus dosage in organ transplantation patients exclusively depended on trough level and needed further evaluation. Pharmacodynamic drug monitoring on immune cells represents an effort to receive more reliable information on the biological effect of mTOR inhibition in an individual transplant recipient. [19,20] In conclusion, a robust phospho-flow cytometry assay that determines the degree of mTOR inhibition by assessing p70S6K phosphorylation was established. Quantification of p70S6K phosphorylation may play an adjunct role to pharmacodynamically guide an individualized sirolimus based on immunosuppression.