Bison
& B~~~i~
7 (1992) 91-101
Effects of temperature and analyte application technique on neuronbased chemical sensing Rodney S. Skeen & Bernard J. Van Wie Department
of Chemical
Engineering,
Washington
State University,
Pullman,
WA 99164-2710, USA
Simon J. Fung & Charles D. Barnes Department
ofVeterinary
and Comparative
(Received 11 February
Anatomy, Pharmacology and Physiology, Washington Pullman, WA 99164-6520, USA
State University,
1991; revised version received 16 Iv&y 1991; accepted 20 May 1991)
Abstract: Results are presented which enhance the field of neuron-based sensing by providing insight on the effects of operating temperature and analyte application technique (pulse versus back-mixed) on sensing properties. In these studies, serotonin sensing attributes of giant visceral neurons VVl and W2 from the pond snail Lymneu sfugnaliswere measured. Experiments using a rapid fluid-exchange system reveal a concentration-dependent increase in maximum firing frequency similar to that reported earlier for a slow well-mixed application. With a rapid application, however, the maximum firing frequency is reached more quickly, and there is less cell-to-cell variability in both the maximum response and sensitivity. Given an application technique, an increase in temperature causes an increase in sensitivity and maximum firing frequency, as well as a decrease in the time required for the response to return to baseline following removal of the analyte. To provide insights on the kinetics of the serotonin-induced response, the effects of temperature and concentration on the rates of activation, recovery and desensitization were examined in detail. In general, it was found that an increase in temperature increases the rates of activation and desensitization, while the effects on recovery were not apparent. In addition, both the rates of activation and desensitization have a direct dependence on concentration while the rate of recovery has an inverse dependence. Keywords: biosensom, neuron, s~n~neous snail, serotonin, activation, desensitization,
supidus (Belli & Rechnitz, 1986, 1988; Buch & Rechnitz, 1989a, 1989b), as well as with identified neurons from the pond snail Lymnea stagnalis (Skeen et al., 1990). These authors have demonstrated that excitable tissues possess many
INTRODUCTION In recent years, the concept tissue for chemical
isolated
antennae
~~~3/9~05,~
sensing
from
of using excitable
has been proven
the
crab
with
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firing frequency, Lymnea sfa~~~~s, recovery.
Ltd.
91
R. S. Skeen et al. desirable sensing characteristics such as a concentration-dependent response, digital output, a fast response time, repeatability, reversibility, selectivity, and a sensitivity range which spans several orders of magnitude. Recent work by the group of G. A. Rechnitz has also demonstrated a new method of analyzing multineuron activity which utilizes pattern reposition (Baker et al., 1990). Applying pattern recognition to decipher concentration information from the response of many different types of neurons has the potential to allow simultaneous detection of many analytes. The digital output of excitable tissue is generated because as the analyte interacts with the tissue it triggers changes in the transmembrane potential, either directly or through secondary messengers, which are then amplified by voltage-dependent ionic channels to produce discrete, all-or-none voltage spikes or action potential events. A typical action potential lasts only a few milliseconds and is tens of millivolts in amplitude. The large amplitude of action potentials makes them easy to monitor. In addition, it has been shown that the concen~ation of the detected chemical is encoded in the frequency at which action potential events occur. Besides demonstrating the sensing characteristics mentioned above, work with Lymneu has focused on systematically chara~te~zing a simplistic system which provides good experimental repeatability to further understand neuron-based sensing as it will relate to a practical biosensor. Previous studies have shown that there is cell-to-cell variability in the firing frequency response to the model analyte serotonin (Skeen a al., 1990). This suggests the need for individual calibration of each neuron, or averaging of the response of several cells to provide a reliable signal. Also, these authors have shown that extended exposure of the neurons to serotonin causes a desensitizing phenomenon which means an individual neuron will give a repeatable response to serotonin only if a long enough rinse time is given between applications. Furthermore, the length of the required rinse increases with the concentration of the previous application. From these results it was suggested that a sensor based on the Lymnea preparation will operate best if test solutions are introduced to the sensor in short pulses, with the time between applications varied according to the concentration in the sample. 92
Biosensors& Bioelectronics Although much work has been done to understand the concent~tion-de~ndent info~ation generated by neural preparations, little has been done to optimize responses as a function of temperature, or to understand the temperature range over which reliable responses can be expected. In addition, a systematic study of the effects of mixing en~ronment on sensing is needed since sensors of this type may be used in situations where mixing may not be easily controlled. It is the goal of this paper to expand the current understanding of neuron-based sensing by examining the effects of temperature, as well as the effects of the mixing profile in the surrounding medium on the sensing properties of neurons.
METHODS Ganglia preparation The methods for preparing the ganglion have been described in detail by Skeen et al. (1990). In brief, the visceral ganglion of an adult Lymnea stagnaiis snail was isolated and pinned to a Sylgard 184 (Dow Coming, Midland, MI) surface in the recording chamber described below. The orientation of the ganglion after pinning allowed the visual identi~cation of the giant visceral neurons Wl and W2 winlow & Benjamin, 1976). To soften the protective fibrous sheath, the ganglion was soaked in a 0.2% trypsin solution (Sigma type III) for 30 min. All solutions were made in Lymnea saline which was buffered to a pH of 7.4 with HEPES buffer. Experimental apparatus The recording chamber, shown in Fig. l(a), consisted of a trough cut in a polycarbonate block to which inlet and outlet flow lines were attached. The trough was shaped so that when inlet and outlet tubing with an i.d. of $ inches and an o.d. of & inches was slipped snugly into the block the inner walls of the trough matched identically with the inner walls of the tubing. This configuration minimized possible dead zones and back-mixing due to expansions or restrictions in the flow lines. By minimizing these flow patterns a more plugflow-like protile could be achieved. This was desirable for these experiments since rapid changes in fluid composition at the ganglion were
R S. Skeen et al.
Neuron-based chemical sensing
(b) Fig. 1. (a) Schematic of the plug-flow recording chamber Shown are a complete view of the chamber. afront view, and a cmsssectional view which highlights the Syrganipad and tempemture-contra1 water jacket. (b) Schematic of the flow system. Test mlutions areplaced in separate aspimtor bottles and intmduced to the recoding chamber by opening the correspondingpinch valves while directing the outlet of the three-way valve to thechamber. Each aspimtor bottle inmaintained at 2 psig toprovide a constant head to drive flow.
needed. As shown in Fig. l(a), a groove was cut in the bottom of the trough and filled with Sylgard to serve as the pad for pinning the ganglion. In addition, a water jacket surrounded the trough so that water from a constant-temperature bath (VWR Scientific, San Francisco, CA) could be passed around the trough to control the temperature of the fluid in the chamber. The recording chamber temperatures reported in this paper were measured by a silicon rubber-coated thermocouple situated in the recording chamber. Before each experiment, a solution of serotonin at the highest concentration to be used was freshly pre-mixed in Lymnea saline using serotonin creatinine sulfate complex (Research Biochemicals Inc., Natick, MA). The stock solution was next diluted in the appropriate increments to concentrations ranging from lo+ to 10e3 M. For each experiment, the solutions to be tested were then placed in separate aspirator bottles. As shown in Fig. l(b), which is a schematic diagram of the fluid perfusion system used in these experiments, each aspirator bottle was connected to a pressurized nitrogen source to maintain the internal pressure of each bottle at 2 psig. This provided a constant pressure head to drive flow. A flow rate of 2.4 ml s-’ was used for all serotonin experiments. The outlet lines of each aspirator bottle were fitted with a check valve to
prevent contamination due to back flow. Sections of 4 inch i.d. tubing led from each check valve to the flow manifold shown in Fig. l(b). A portion of each line with a volume of 30 ml was bundled around a $ inch copper tube and insulated to form the heat exchanger shown in Fig. l(b). The single outlet of the flow manifold led to the recording chamber. Each of the six individual lines leading into the manifold had a pinch valve just before the manifold. A three-way valve was placed in the line between the manifold and the recording chamber. Using this system, a solution of interest was made ready by opening the corresponding pinch valve while the outlet of the three-way valve was directed to the waste bottle. This allowed the fluid in the tubing up to the valve to be replaced with the desired solution. Once this line was tilled, the outlet of the three-way valve was directed toward the recording chamber. A volume of approximately 25 ml was then allowed to pass through the chamber. Flow was stopped by closing the pinch valve and diverting the outlet of the three-way valve back to the waste container. The volume of fluid in the recording chamber was 1 ml. Temperature control was achieved with the pulse application by controlling the temperature of the fluid in the recording chamber via the water jacket, and pre-adjusting the temperature of the 93
R S. Skeen et al.
fluid to be perfused through contact with the copper tube of the heat exchanger. Water from the same constant temperature bath fed both the water jacket and the copper tube. To ensure the fluid to be introduced into the chamber was at equilibrium with the water in the heat exchanger, the fluid in each inlet line was left in contact with the heat exchanger for a minimum of 10 min. In this way, the temperature in the chamber was maintained to within 0.5, 05, and 1.5 K for operating temperatures of 290, 297, and 306 K, These three temperatures respectively. correspond to the levels used when obtaining the data presented in this paper. Data collection and analysis To perform intracellular recordings, the giant neurons Wl and W2 were visually identified and impaled with a glass microelectrode filled with 3 M KCl. The resistance of the electrodes ranged from 15 to 35 Ma. On impalement, if a cell could not generate repetitive action potentials greater than 50 mV it was assumed damaged and the impalement abandoned. The frequency at action potentials were which spontaneous generated was determined on-line using a microcomputer equipped with an analog-to-digital converter. Each frequency point was calculated as the inverse of the time between an action potential and the previous action potential. A detailed description of the data collection and analysis system is given by Skeen et al. (1990). Recording chamber turnover studies Recording chamber turnover studies were performed by step introduction of 10T3 M acetylcholine solutions while monitoring Wl and W2 neurons under constant membrane conditions. (i.e. voltage-clamp) potential Acetylcholine solutions were made fresh before each experiment by dissolving acetylcholine chloride (Sigma, St Louis, MO) in Lymnea saline to make a 10v3 M solution. A holding potential between -95 mV and -90 mV was used for all neurons. The membrane potential was controlled by the single-electrode voltage-clamp system in a Dagan 8100 electrophysiological recording unit. Clamp currents were monitored on the oscilloscope and stored on a modified video cassette recorder for off-line analysis. Off-line 94
Biosensors & Bioelectronics
analysis of the time course of the clamping current was using accomplished the microcomputer equipped with the A/D board and in-house developed software. A Sage Instruments model 335 constant-head syringe pump (Orion Research Inc., Cambridge, MA) equipped with a 60 cm3 syringe was used to apply acetylcholine solutions. The outlet of the syringe was connected to the three-way valve located before the chamber. A solution was introduced to the ganglion by starting the pump with the outlet of the valve directed toward the waste container. Once enough fluid had been drained through the waste outlet to ensure that the flow line contained the solution in the syringe, the outlet was directed toward the chamber. A constant flow rate of l-4 ml/s was used in all acetylcholine experiments.
RESULTS AND DISCUSSION Recording chamber turnover rate To estimate the turnover rate of the plug-flow chamber, the time course of current shifts induced by 10m3M acetylcholine in four Wl and W2 neurons was monitored under voltageclamp conditions. The time required for the acetylcholine response to reach a steady level provides a maximum estimate for the chamber turnover time. This is because acetylcholine is known to cause an increasing inward current in many Lymnea neurons which is more rapid than the serotonin-induced tiring frequency change observed in these experiments (Andreev eral., 1984). The average time for the acetylcholine response to reach a maximum in the four neurons tested was 900 ms while the minimum value of the four was 600 ms. It should be noted that the flow rate used in the acetylcholine studies was 42% below that of the serotonin applications, which indicates that this turnover time estimate is conservative. However, even this conservative estimate suggests that serotonin concentration can be assumed to be constant throughout a response since the neurons exposed to serotonin showed a much slower time course for the increase in firing frequency. For example, the average time to reach a maximum tiring frequency for each condition reported in this paper was between 11 s and 21 s.
Neuron-basedchemical sensing
Biosensors& Bioelectronics Effects of temperature and application technique on sensing total of 12 Wl and W2 neurons were studied at three operating temperatures to accumulate information on the effects of temperature and application method on serotonin sensing properties. Eleven of 12 cells were exposed to three brief, 30-70 s, applications of serotonin, each followed by a 10 min rinse, and a fourth application with a duration of 30 min. The concentrations for the four serotonin applications were lo-‘, 5 X 10m5, 10m4, and 10m3M, respectively. The remaining cell was exposed to brief applications of 5 X 10m6 and 10m4M, and a long application of lob3 M. The three operating temperatures which were used when recording from the 12 neurons were 290, 297, and 306 K. These temperature levels were chosen since they span the range in which Wl and W2 neurons give a tiring frequency response to serotonin. The minimum operating temperature which could be used for this study was determined by exposing three neurons to various concentrations of serotonin between lo-’ and 10m3M at low temperatures. One cell was exposed to 1 min applications of 10s5, 5 X 10e5, and 10m4M, followed by a 5 min application of 10m3M at an operating temperature that fluctuated between 281 and 283 K. For another cell, temperatures of 285, 288, and 289 K were A
0
1000 Seconds
tested. For each condition, the cell was exposed to short applications of serotonin between low5 and 10m4M followed by a long application of 10T3 M. The third cell was tested at an operating temperature which fluctuated between 290 and 291 K. For this cell, short applications of 10m5, 5 X 10e5, and 10m4M serotonin, followed by a long application of 10V3M serotonin were applied. It was found that the neurons tested below 290 K had very little spontaneous activity and showed no change in the activity with serotonin. However, the cell exposed at a temperature which varied between 290 and 291 K exhibited spontaneous firing frequency behavior that was serotonin dependent. The maximum temperature for this study, 306 K, corresponds to the upper limit in which Wl and W2 neurons will still tire spontaneous action potentials on exposure to serotonin. The data reported in this paper for application of analyte under constant perfusion in a backmixed recording chamber is from Fig. 3 of Skeen ec al. (1990). As reported, the chamber used by these authors had a flow protile which could be approximated by an ideal stirred vessel with constant volume and flow rate, and a residence time of O-88 min-‘. Concentration-dependent response Consistent with previous work (Belli & Rechnitz, 1986; Skeen et al., 1990), when the data for each
2000 From
Start
3000
4000
of Experiment
Fig. 2. Typical results obtained jkom experiments where ident@ed neurons VVI and VW are exposed to three short applications of increasing levels of serotonin followed by an extended application of a more concentrated solution. The temperature was 297 K in the expen’ment represented. 95
R S. Skeen et al.
temperature is viewed collectively a general increase in spontaneous firing frequency with analyte concentration is seen. Figure 2 portrays an example of the graded increase in firing frequency seen in both Wl and W2 neurons with serotonin concentration. This figure represents typical results obtained from the multiple application experiments described above. The operating temperature for the cell represented in Fig. 2 was 297 K. For serotonin sensing, it was shown by Skeen et al. (1990) with a back-mixed application that the maximum firing frequency response to serotonin can be used to indicate chemical concentration. As is evident from the frequency response represented in Fig. 2, this is also true for the plug-flow technique. In fact, all cells exposed to multiple applications of serotonin at 297 K showed a continuous increase in maximum firing frequency with serotonin concentration, while 4 out of 5 cells at 306 K showed a continuous increase. The fifth cell at 306 K showed an increase in the maximum tiring frequency between lo-’ and 5 X 10m5M, and between 10m4and 10m3M; however, there was a slight reduction in the maximum firing frequency between 5 X 10-j and 10d4 M. The 290 K data also show an increasing trend in maximum firing frequency with serotonin, but the increase is not continuous for all cells. As will be discussed later, this is probably due to the fact that at 290 K the 10 min rinse given between applications was not long enough for a neuron to recover fully from an application. This caused prior additions to affect the maximum response to subsequent applications. The maximum tiring frequency behavior for the 297 and 306 K data, along with data for the back-mixed application at 301 K, is summarized in Fig. 3. Here, a bar graph is used to summarize the average maximum tiring frequency and standard deviations for cells at the different temperatures, concentrations, and application technique (297 K, n = 3-4; 301 K, n = 6; 306 K, n = 5). From this figure, the concentrationdependent increase in maximum firing frequency for each condition can be seen by the increasing means. Also evident from Fig. 3 is that, given an application technique, the maximum firing frequency response to a concentration increases with temperature. Furthermore, the application technique does not appear significantly to affect maximums since the back-mixed data are at an intermediate temperature between the two plug96
Biosensors & Bioelectronics
0
-6
I
-I
&‘ol
297
K
306
K
PF
CST
K
-I)
Fig. 3. Summary of the maximumJiringfiequencyfor VVI and VV2 neurons with a plug-flow application at 297 and 306 K, and a back-m&d application at 301 K. The bars represent the mean of between 3 and 1I cells, and the capped lines show plus and minus one standard deviation around the means.
flow data sets, and, for lob4 and 10m3M serotonin, the means for the back-mixed data also lies between the plug-flow means. At 10m5M the backmixed mean is below both the plug-flow means; however, as seen by the larger back-mixed standard deviations, there is also a large amount of scatter in the back-mixed data. The fact that the application technique appears not to affect the maximal response significantly is important when considering possible uses for a neuronbased sensor because it will allow a device which is calibrated for one monitoring application to be applied to others with different flow characteristics. The increase in firing frequency with temperature is also significant for neuron-based sensing for two reasons. First, it shows that the temperature of the sensor must be closely controlled at the calibration conditions. Second, by operating the sensor at higher temperatures the measured response to serotonin will increase, thus providing a signal which is more easily distinguished from the background firing frequency. An advantage of using a plug-flow application rather than a back-mixed application can be seen from the sizes of the standard deviations in Fig. 3. At all concentrations the plug-flow standard deviations are smaller than the back-mixed value, which indicates a smaller cell-to-cell variability for the plug-flow responses. The cause of the smaller cell-to-cell variability is not yet clear since numerous factors may influence the observed tiring frequency response. However, the reduced cell-to-cell variability is important if a neural sensor is to rely on the average response of a
Neuron-based chemical sensing
Biosensors & Bioelectronics
population
of neurons as suggested by Skeen
etaf. (1990), since a smaller variation translates
into fewer cells required to obtain an accurate average. Reducing the number of cells reduces the device complexity.
.
0.60
2 >I
0.60
.z E z
One positive attribute of a neuron-based sensor illuminated by the back-mixed application experiments of Skeen et al. (1990)was that rinsing returned the response to the baseline, demonstrating reversibility. This was also evident when plug-flow applications were applied to cells. Figure 4 reveals that at 297 and 306 K all neurons exhibited a tiring frequency response which returned to baseline within the 10 min rinse period. In this figure the number of points represented in the averages is between 2 and 5 (29OKn = 2;297K,n = 2-4;306K,n =4-5).For cells at 290 K however, the response diminished more slowly so that it did not always return to baseline during the IO-min rinse for 5 X lo-’ and 10W4~ serotonin. This absence of a return to baseline in 10 min at 290 K is why no data are shown on Fig. 4 for this temperature at 5 X 10m5 and 10e4~. These results suggest that temperature has a significant effect on the reversibility of the response. It is also evident from Fig. 4 that, although there is cell-to-cell va~abili~, the time to return to baseline at a given increasing concentration decreases with temperature.
0
cl
290
K
297
K
306
K
Fig 4. Summary of the time required for the Jiring frequency to return to baseline after rinsing. Represented are results for plug-flow applications at 290. 297, and 306 K. The bars represent the mean of between 2 and 5 cells. while the capped lines show plus and minus one standard deviation around the means.
030
t 0.00
Fig. 5. Mean sensitivity between 10-j and 10m3Mserotonin for cells exposed using a plug-flow application at 297 and 306 K, and using a bark-mixed application at 301 K. The bars represent the mean of between 3 and 6 nouns, while the capped lines show one standard deviation above and below the means.
To determine the effects of temperature and application method on the sensitivity of a neuron-based sensor, the slope of the maximum firing frequency versus the logarithm of the serotonin concentration data for each neuron was estimated using linear regression. Figure 5 shows the average value of slope and standard deviation for cells exposed to plug-flow applications of serotonin between 10m5and 10T3M at 297 and 306 K, and for a back-mixed application at 301 K. In this tigure n = 3,4, and 6 for temperatures of 297,306, and 301 K, respectively. Comparing the mean values for the two plug-flow applications, it is clear that an increase in temperature also increases the slope, thus increasing the sensitivity of the neurons to serotonin. An increase in sensitivity is advantageous since it will provide finer concentration resolution for a neuron-based sensor. Looking at the two application techniques represented in Fig. 5, it appears that even at a lower temperature a back-mixed application provides a more sensitive response to serotonin than a plug-flow application. However, the gain in sensitivity is accompanied by considerably more cell-to-cell variation. This is indicated by the larger standard deviation for a back-mixed application. As with the reduction in the cell-toceil variability seen with a plug-flow applica~on, it is difficult to postulate why a back-mixed application appears to increase the sensitivity. This difticulty arises because of the potential complexity of the mechanism underlying the response. 97
R. S. Skeet
et al.
Application durution
Previous findings from this laboratory showed that the amount of desensitization seen in the maximum firing frequency after an application of serotonin increases with the length of preexposure to a lower concentration (cf. Fig. 9 in Skeen et al., 1990). In addition, Katz & Thesleff (1957) reported that when acetylcholine receptors in frog motor end-plates are exposed to agonists for an extended duration, recovery from desensitization is slowed or incomplete. These results suggest that the time the neurons are exposed to a sample should be minimized to keep desensitization effects low, and thus reduce the amount of rinse time required to recover from desensitization. This raises the question of how short may the application be and still stimulate a true maximum firing frequency response. It was found from these plug-flow addition studies that a maximum response to serotonin is always obtained in 30 s or less, thus setting the minimum time these neurons must be exposed to the analyte solution. A 30 s minimum is the same order of magnitude as the response time reported for Callinectes sapidus (Belli & Rechnitz, 1986). In addition, A plug-flow application is better suited for minimizing desensitization since a sample can be introduced instantaneously to the sensing interface and left in contact just long enough to record the maximum response. Once the maximum has been reached the solution can be quickly replaced with analyte-free saline. By the back-mixed application comparison, reported earlier required 5 min to reach a steady level, while rinsing required the same time to remove the serotonin.
and continues until the next application begins. The third component is the decay in firing frequency, or desensitization, which occurs during a 30 min exposure. Activation
To quantify the effects of temperature and concentration on activation, the increase in firing frequency over baseline after 9 s of exposure (AFF9) was measured. It was found that at each tern~m~~ all cells exposed to multiple additions of serotonin showed a general increase in AFF, with concentration. The trend, though, was not continuous for 1 of 4 cells at 297 K and 1 of 5 cells at 306 IS. Each of these cells showed a AFF9 at 5 X 10e5 M slightly larger than the value at 10m4M. At 290 K, where recovery was not complete after each application, AFF, for 2 of the 3 cells tested increased between 10e5 and 5 X 10e5 M, and then remained at that level for the higher concentrations. The AFF, value for the third cell at 290 K increased between 10e5 and 5 X lo-’ M, but at low4M the level dropped to below that at 10m5M. When 10m3M was applied to this cell AFFg again showed an increase. The effects of temperature and concentration on AFF, are summarized in Fig. 6, representing 2-5 cells per application condition. From Fig. 6 the general increase in AFF, with concentration at constant temperature can be seen by the increasing means. This is most evident at 297 and 306 K. By comparing the mean values at constant concentration, it is apparent that an increase in
Effects of temperature and concentration on response kinetics
Each addition in the multiple application experiments was examined in detail to gain qualitative insights into the influence of concentration and temperate on the kinetics of the firing frequency response. These findings are important since they provide a basis for a quantitative study which will be reported in a future paper. Three components of these experiments are of particular interest. The first component is the rise in firing frequency, or activation, induced by the addition of serotonin. The second component, termed recovery in this paper, begins at the time a rinse cycle is started 98
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E
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LogK?oncentrstionf
Fig. 6. Summaryof the increase in$ringfrequency ajlter9 s of exposure to various concentrations of serotonin. The mean value for neurons exposed using a plug-jlow application at 290. 297, and 306 K are represented by the bars. Each bar is the mean of between 2 and 5 cells, while the capped lines indicate plus and minus one standard deviation on the mean.
Neuron-based chemical sensing
Biosensors t Bioelectmnics
.25
5
10
15
Time From Start of Rinse (Seconds) Fig. 7. Example of the e&cts of serotonin concentration on thefiringfequency decay seen in WI and vv2 neurons during a rinse afkr a short application. The difkrent line types represent the response aJserd@erent levels of serotonin.
temperature increases the rate of rise in the serotonin-induced firing frequency. Recovery
It was observed at all temperatures that following a rinse the rate of decay in tiring frequency was inversely related to the concentration of serotonin that had been applied. An example of the relationship between the decay in firing frequency and concentration is shown in Fig. 7. Figure 7 represents the decay of a WI neuron’s firing frequency after application of three concentrations of serotonin at 306 K. In this figure the tiring frequency for each concentration has been subtracted from the firing frequency when the rinse began so that each concentration could be more easily compared. To quantify the decay behavior, the drop in firing frequency after 40 s of rinsing was measured (AFF,). It was found that at 290 K 2 of 3 cells showed a consistent decrease in AFF, with increasing concentration. For the third cell at 290 K, the inverse relationship between the drop in firing concentration was not frequency and distinguishable after 40 s, but appeared after 100 s. At 297 K, 4 of 4 cells showed a consistent decrease in AFF, with increasing concentration, while at 306 K 1 of 5 cells showed this trend. Of the remaining 4 cells at 306 K, one cell had already reached a minimum firing frequency by 40 s after the lo-’ M application. For this cell, if the drop in
tiring frequency was measured at 18 s, which corresponds to the time when the firing frequency had just reached a minimum, the inverse relationship was apparent. Two other cells at 306 K showed AFF, decreasing between 10m5 and 5 X IO-’ M and then increasing slightly between 5 X lob5 and 10e4~. The final cell showed a continual increase in AFF, with increasing concentration. The effects of temperature on AFF, could not be distinguished from these data because of cell-to-cell variability. Desensitization
Desensitization was examined at 10m3M for the 12 cells exposed to multiple applications, and for 3 additional Wl and W2 neurons with a 10V4M application. The operating temperature for the 3 cells exposed to extended applications of 10m4M was 297 K. It was found that the amount of desensitization increases with increasing temperature and concentration. This is summarized in Fig. 8, which shows the drop in tiring frequency after 15 min of exposure plotted against the operating temperature. Each point represents the mean of between 2 and 4 cells. The direct relationship between temperature and the amount of desensitization is similar to the results reported by Andreev et al. (1984) for desensitization of acetylcholine currents in Lymnea neurons. Extreme temperatures were found to produce a 99
R. S. Skeen et al.
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’
00001
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290
225
300
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310
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Fig. 8. Average drop in firing frequency after 15 min of exposure to serotonin as a finction of temperature and application concentration.
tendency for cells suddenly to stop firing action potentials. This occurred in 4 of 5 cells at 306 K; however, the time of onset of this sudden loss of activity was dramatically different for each cell. Activity was lost after 40, 74, 362, and 1490 s, respectively. For the 3 cells exposed to an extended application of 10d3M serotonin at 290 K, 1 cell stopped tiring after 921 s of exposure. The reason for this loss of activity is not known; however, a similar type of behavior was described by Skeen et al. (1990) with a lo-* M back-mixed application of serotonin at 301 K. CONCLUSIONS A plug-flow technique for applying analytes to an isolated Lymneu s~ag~u~is ganglion preparation has been developed and tested. This system was used to advance the field of neural sensing by providing insight on the effects of temperature and mixing environment on sensing properties. A total of 15 Wl and W2 neurons at three operating temperatures of 290, 297, and 306 K were used in this study. These three temperatures were used since outside this temperature range Wl and W2 neurons lost their concentrationdependent response. To determine the effects of mixing on sensing characte~stics the plug-flow application data were compared to the slow backmixed application data of Skeen et al. (1990). Results show a concentration-dependent increase in the frequency of spontaneous action potentials with a plug-flow application. The increase is seen at all temperatures tested. An increase in temperature results in an increase in the maximal firing frequency caused by a given 100
concentration, as well as in an increase in the sensitivity of these neurons to serotonin. In addition, the time required for the firing frequency to return to baseline decreases with an increase in temperature. Comparing the two application techniques suggests that the maximal frequency response to a concentration is not affected by application technique. Furthermore, by using a plug-flow application, a maximal response is achieved at all conditions tested in 30 s or less which is several times faster than the response reported earlier for the back-mixed application. This is advantageous since it means the neurons may be exposed to serotonin for a shorter period of time, which should reduce the amount of desensitization, thus reducing the rinse time required for the cell to recover completely and give a repeatable response. Also, the data indicate that a plug-flow application reduces cell-to-cell variability in the maximum firing frequency. These results suggest that a neural sensor based on this preparation will operate best at higher temperatures while utilizing a rapid application to expose the cells to analyte. ACKNO’WLEDGEMENTS The authors thank Clark Maxwell for his assistance in designing the rapid application system. This project was supported under the Microsensor Technology program of the Washin~on Technology Center. An equipment donation for the oscilloscope was received from Tektronix Corporation. Initiation of the neuronal biosensor program at Washington State University was aided by an NSF grant, ECE8609910.Graduate training support was provided by the National Institute of Health Biotechnology Training Grant, T32GM08336. REFERENCES Andreev, A. A., Veprintsev,B. N. & Vulfius, C. A. (1984). Two component desensitization of nicotinic receptors induced by acetylcholine agonists in Lymnaeastagnalis neurons.1 Physiol., 353,3X-91.
Baker, T. Q., Buch, R. M. & Rechnitz, G. A. (1990). Intact chemoreceptor-basedbiosensors.Biotechnol. Prog., 6, 498-503. Belli, S. L. & Rechnitz, G. A. (1986). Prototype potentiometric biosensor using intact chemoreceptor structures. Anal. Lett..,19,403-16.
Biosensors& Bioelectronics Belli, S. L. & Rechnitz, G. A. (1988). Biosensors based on chemoreceptors. Fnwnius Z Anal. Chem.. 331, 439-41. Buch, R. M. & Rechnitz. G. A. (1989a). Intact chemoreceptor-based biosensors: responses and analytical limits. Biosensors,4, 215-30. Buch, R M. & Rechnitz, G. A (1989b). Intact chemoreceptor-based biosensors: extreme sensitivity to some excitatory amino acids. Anal. L&t..,25 2685-702. Katz, B. & Thesleff, S. (1957). A study of the desensitiz-
Neuron-based chemical sensing ation produced by acetylcholine at the motor endplate. 1 Physiol., 138, 63-80. Skeen, R. S., Van Wie, B. J., Fung, S. J. & Barnes, C. D. (1990). Evaluation of neuron-based sensing with the neurotransmitter serotonin. Biosensors and Bioelectronics,5, 491-S 10. Winlow, W. & Benjamin, P. R (1976). Neuronal mapping of the brain of the pond snail Limnea stagnalis. In Neurobiology of Invertibrates, ed. J. Salanki, Akademiai Riado, Budapest, Hungary, pp. 41-59.
101
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7 (1992) 91-101
Effects of temperature and analyte application technique on neuronbased chemical sensing Rodney S. Skeen & Bernard J. Van Wie Department
of Chemical
Engineering,
Washington
State University,
Pullman,
WA 99164-2710, USA
Simon J. Fung & Charles D. Barnes Department
ofVeterinary
and Comparative
(Received 11 February
Anatomy, Pharmacology and Physiology, Washington Pullman, WA 99164-6520, USA
State University,
1991; revised version received 16 Iv&y 1991; accepted 20 May 1991)
Abstract: Results are presented which enhance the field of neuron-based sensing by providing insight on the effects of operating temperature and analyte application technique (pulse versus back-mixed) on sensing properties. In these studies, serotonin sensing attributes of giant visceral neurons VVl and W2 from the pond snail Lymneu sfugnaliswere measured. Experiments using a rapid fluid-exchange system reveal a concentration-dependent increase in maximum firing frequency similar to that reported earlier for a slow well-mixed application. With a rapid application, however, the maximum firing frequency is reached more quickly, and there is less cell-to-cell variability in both the maximum response and sensitivity. Given an application technique, an increase in temperature causes an increase in sensitivity and maximum firing frequency, as well as a decrease in the time required for the response to return to baseline following removal of the analyte. To provide insights on the kinetics of the serotonin-induced response, the effects of temperature and concentration on the rates of activation, recovery and desensitization were examined in detail. In general, it was found that an increase in temperature increases the rates of activation and desensitization, while the effects on recovery were not apparent. In addition, both the rates of activation and desensitization have a direct dependence on concentration while the rate of recovery has an inverse dependence. Keywords: biosensom, neuron, s~n~neous snail, serotonin, activation, desensitization,
supidus (Belli & Rechnitz, 1986, 1988; Buch & Rechnitz, 1989a, 1989b), as well as with identified neurons from the pond snail Lymnea stagnalis (Skeen et al., 1990). These authors have demonstrated that excitable tissues possess many
INTRODUCTION In recent years, the concept tissue for chemical
isolated
antennae
~~~3/9~05,~
sensing
from
of using excitable
has been proven
the
crab
with
Cullinectes
Q 1992 Elsevier Science Publishem
firing frequency, Lymnea sfa~~~~s, recovery.
Ltd.
91
R. S. Skeen et al. desirable sensing characteristics such as a concentration-dependent response, digital output, a fast response time, repeatability, reversibility, selectivity, and a sensitivity range which spans several orders of magnitude. Recent work by the group of G. A. Rechnitz has also demonstrated a new method of analyzing multineuron activity which utilizes pattern reposition (Baker et al., 1990). Applying pattern recognition to decipher concentration information from the response of many different types of neurons has the potential to allow simultaneous detection of many analytes. The digital output of excitable tissue is generated because as the analyte interacts with the tissue it triggers changes in the transmembrane potential, either directly or through secondary messengers, which are then amplified by voltage-dependent ionic channels to produce discrete, all-or-none voltage spikes or action potential events. A typical action potential lasts only a few milliseconds and is tens of millivolts in amplitude. The large amplitude of action potentials makes them easy to monitor. In addition, it has been shown that the concen~ation of the detected chemical is encoded in the frequency at which action potential events occur. Besides demonstrating the sensing characteristics mentioned above, work with Lymneu has focused on systematically chara~te~zing a simplistic system which provides good experimental repeatability to further understand neuron-based sensing as it will relate to a practical biosensor. Previous studies have shown that there is cell-to-cell variability in the firing frequency response to the model analyte serotonin (Skeen a al., 1990). This suggests the need for individual calibration of each neuron, or averaging of the response of several cells to provide a reliable signal. Also, these authors have shown that extended exposure of the neurons to serotonin causes a desensitizing phenomenon which means an individual neuron will give a repeatable response to serotonin only if a long enough rinse time is given between applications. Furthermore, the length of the required rinse increases with the concentration of the previous application. From these results it was suggested that a sensor based on the Lymnea preparation will operate best if test solutions are introduced to the sensor in short pulses, with the time between applications varied according to the concentration in the sample. 92
Biosensors& Bioelectronics Although much work has been done to understand the concent~tion-de~ndent info~ation generated by neural preparations, little has been done to optimize responses as a function of temperature, or to understand the temperature range over which reliable responses can be expected. In addition, a systematic study of the effects of mixing en~ronment on sensing is needed since sensors of this type may be used in situations where mixing may not be easily controlled. It is the goal of this paper to expand the current understanding of neuron-based sensing by examining the effects of temperature, as well as the effects of the mixing profile in the surrounding medium on the sensing properties of neurons.
METHODS Ganglia preparation The methods for preparing the ganglion have been described in detail by Skeen et al. (1990). In brief, the visceral ganglion of an adult Lymnea stagnaiis snail was isolated and pinned to a Sylgard 184 (Dow Coming, Midland, MI) surface in the recording chamber described below. The orientation of the ganglion after pinning allowed the visual identi~cation of the giant visceral neurons Wl and W2 winlow & Benjamin, 1976). To soften the protective fibrous sheath, the ganglion was soaked in a 0.2% trypsin solution (Sigma type III) for 30 min. All solutions were made in Lymnea saline which was buffered to a pH of 7.4 with HEPES buffer. Experimental apparatus The recording chamber, shown in Fig. l(a), consisted of a trough cut in a polycarbonate block to which inlet and outlet flow lines were attached. The trough was shaped so that when inlet and outlet tubing with an i.d. of $ inches and an o.d. of & inches was slipped snugly into the block the inner walls of the trough matched identically with the inner walls of the tubing. This configuration minimized possible dead zones and back-mixing due to expansions or restrictions in the flow lines. By minimizing these flow patterns a more plugflow-like protile could be achieved. This was desirable for these experiments since rapid changes in fluid composition at the ganglion were
R S. Skeen et al.
Neuron-based chemical sensing
(b) Fig. 1. (a) Schematic of the plug-flow recording chamber Shown are a complete view of the chamber. afront view, and a cmsssectional view which highlights the Syrganipad and tempemture-contra1 water jacket. (b) Schematic of the flow system. Test mlutions areplaced in separate aspimtor bottles and intmduced to the recoding chamber by opening the correspondingpinch valves while directing the outlet of the three-way valve to thechamber. Each aspimtor bottle inmaintained at 2 psig toprovide a constant head to drive flow.
needed. As shown in Fig. l(a), a groove was cut in the bottom of the trough and filled with Sylgard to serve as the pad for pinning the ganglion. In addition, a water jacket surrounded the trough so that water from a constant-temperature bath (VWR Scientific, San Francisco, CA) could be passed around the trough to control the temperature of the fluid in the chamber. The recording chamber temperatures reported in this paper were measured by a silicon rubber-coated thermocouple situated in the recording chamber. Before each experiment, a solution of serotonin at the highest concentration to be used was freshly pre-mixed in Lymnea saline using serotonin creatinine sulfate complex (Research Biochemicals Inc., Natick, MA). The stock solution was next diluted in the appropriate increments to concentrations ranging from lo+ to 10e3 M. For each experiment, the solutions to be tested were then placed in separate aspirator bottles. As shown in Fig. l(b), which is a schematic diagram of the fluid perfusion system used in these experiments, each aspirator bottle was connected to a pressurized nitrogen source to maintain the internal pressure of each bottle at 2 psig. This provided a constant pressure head to drive flow. A flow rate of 2.4 ml s-’ was used for all serotonin experiments. The outlet lines of each aspirator bottle were fitted with a check valve to
prevent contamination due to back flow. Sections of 4 inch i.d. tubing led from each check valve to the flow manifold shown in Fig. l(b). A portion of each line with a volume of 30 ml was bundled around a $ inch copper tube and insulated to form the heat exchanger shown in Fig. l(b). The single outlet of the flow manifold led to the recording chamber. Each of the six individual lines leading into the manifold had a pinch valve just before the manifold. A three-way valve was placed in the line between the manifold and the recording chamber. Using this system, a solution of interest was made ready by opening the corresponding pinch valve while the outlet of the three-way valve was directed to the waste bottle. This allowed the fluid in the tubing up to the valve to be replaced with the desired solution. Once this line was tilled, the outlet of the three-way valve was directed toward the recording chamber. A volume of approximately 25 ml was then allowed to pass through the chamber. Flow was stopped by closing the pinch valve and diverting the outlet of the three-way valve back to the waste container. The volume of fluid in the recording chamber was 1 ml. Temperature control was achieved with the pulse application by controlling the temperature of the fluid in the recording chamber via the water jacket, and pre-adjusting the temperature of the 93
R S. Skeen et al.
fluid to be perfused through contact with the copper tube of the heat exchanger. Water from the same constant temperature bath fed both the water jacket and the copper tube. To ensure the fluid to be introduced into the chamber was at equilibrium with the water in the heat exchanger, the fluid in each inlet line was left in contact with the heat exchanger for a minimum of 10 min. In this way, the temperature in the chamber was maintained to within 0.5, 05, and 1.5 K for operating temperatures of 290, 297, and 306 K, These three temperatures respectively. correspond to the levels used when obtaining the data presented in this paper. Data collection and analysis To perform intracellular recordings, the giant neurons Wl and W2 were visually identified and impaled with a glass microelectrode filled with 3 M KCl. The resistance of the electrodes ranged from 15 to 35 Ma. On impalement, if a cell could not generate repetitive action potentials greater than 50 mV it was assumed damaged and the impalement abandoned. The frequency at action potentials were which spontaneous generated was determined on-line using a microcomputer equipped with an analog-to-digital converter. Each frequency point was calculated as the inverse of the time between an action potential and the previous action potential. A detailed description of the data collection and analysis system is given by Skeen et al. (1990). Recording chamber turnover studies Recording chamber turnover studies were performed by step introduction of 10T3 M acetylcholine solutions while monitoring Wl and W2 neurons under constant membrane conditions. (i.e. voltage-clamp) potential Acetylcholine solutions were made fresh before each experiment by dissolving acetylcholine chloride (Sigma, St Louis, MO) in Lymnea saline to make a 10v3 M solution. A holding potential between -95 mV and -90 mV was used for all neurons. The membrane potential was controlled by the single-electrode voltage-clamp system in a Dagan 8100 electrophysiological recording unit. Clamp currents were monitored on the oscilloscope and stored on a modified video cassette recorder for off-line analysis. Off-line 94
Biosensors & Bioelectronics
analysis of the time course of the clamping current was using accomplished the microcomputer equipped with the A/D board and in-house developed software. A Sage Instruments model 335 constant-head syringe pump (Orion Research Inc., Cambridge, MA) equipped with a 60 cm3 syringe was used to apply acetylcholine solutions. The outlet of the syringe was connected to the three-way valve located before the chamber. A solution was introduced to the ganglion by starting the pump with the outlet of the valve directed toward the waste container. Once enough fluid had been drained through the waste outlet to ensure that the flow line contained the solution in the syringe, the outlet was directed toward the chamber. A constant flow rate of l-4 ml/s was used in all acetylcholine experiments.
RESULTS AND DISCUSSION Recording chamber turnover rate To estimate the turnover rate of the plug-flow chamber, the time course of current shifts induced by 10m3M acetylcholine in four Wl and W2 neurons was monitored under voltageclamp conditions. The time required for the acetylcholine response to reach a steady level provides a maximum estimate for the chamber turnover time. This is because acetylcholine is known to cause an increasing inward current in many Lymnea neurons which is more rapid than the serotonin-induced tiring frequency change observed in these experiments (Andreev eral., 1984). The average time for the acetylcholine response to reach a maximum in the four neurons tested was 900 ms while the minimum value of the four was 600 ms. It should be noted that the flow rate used in the acetylcholine studies was 42% below that of the serotonin applications, which indicates that this turnover time estimate is conservative. However, even this conservative estimate suggests that serotonin concentration can be assumed to be constant throughout a response since the neurons exposed to serotonin showed a much slower time course for the increase in firing frequency. For example, the average time to reach a maximum tiring frequency for each condition reported in this paper was between 11 s and 21 s.
Neuron-basedchemical sensing
Biosensors& Bioelectronics Effects of temperature and application technique on sensing total of 12 Wl and W2 neurons were studied at three operating temperatures to accumulate information on the effects of temperature and application method on serotonin sensing properties. Eleven of 12 cells were exposed to three brief, 30-70 s, applications of serotonin, each followed by a 10 min rinse, and a fourth application with a duration of 30 min. The concentrations for the four serotonin applications were lo-‘, 5 X 10m5, 10m4, and 10m3M, respectively. The remaining cell was exposed to brief applications of 5 X 10m6 and 10m4M, and a long application of lob3 M. The three operating temperatures which were used when recording from the 12 neurons were 290, 297, and 306 K. These temperature levels were chosen since they span the range in which Wl and W2 neurons give a tiring frequency response to serotonin. The minimum operating temperature which could be used for this study was determined by exposing three neurons to various concentrations of serotonin between lo-’ and 10m3M at low temperatures. One cell was exposed to 1 min applications of 10s5, 5 X 10e5, and 10m4M, followed by a 5 min application of 10m3M at an operating temperature that fluctuated between 281 and 283 K. For another cell, temperatures of 285, 288, and 289 K were A
0
1000 Seconds
tested. For each condition, the cell was exposed to short applications of serotonin between low5 and 10m4M followed by a long application of 10T3 M. The third cell was tested at an operating temperature which fluctuated between 290 and 291 K. For this cell, short applications of 10m5, 5 X 10e5, and 10m4M serotonin, followed by a long application of 10V3M serotonin were applied. It was found that the neurons tested below 290 K had very little spontaneous activity and showed no change in the activity with serotonin. However, the cell exposed at a temperature which varied between 290 and 291 K exhibited spontaneous firing frequency behavior that was serotonin dependent. The maximum temperature for this study, 306 K, corresponds to the upper limit in which Wl and W2 neurons will still tire spontaneous action potentials on exposure to serotonin. The data reported in this paper for application of analyte under constant perfusion in a backmixed recording chamber is from Fig. 3 of Skeen ec al. (1990). As reported, the chamber used by these authors had a flow protile which could be approximated by an ideal stirred vessel with constant volume and flow rate, and a residence time of O-88 min-‘. Concentration-dependent response Consistent with previous work (Belli & Rechnitz, 1986; Skeen et al., 1990), when the data for each
2000 From
Start
3000
4000
of Experiment
Fig. 2. Typical results obtained jkom experiments where ident@ed neurons VVI and VW are exposed to three short applications of increasing levels of serotonin followed by an extended application of a more concentrated solution. The temperature was 297 K in the expen’ment represented. 95
R S. Skeen et al.
temperature is viewed collectively a general increase in spontaneous firing frequency with analyte concentration is seen. Figure 2 portrays an example of the graded increase in firing frequency seen in both Wl and W2 neurons with serotonin concentration. This figure represents typical results obtained from the multiple application experiments described above. The operating temperature for the cell represented in Fig. 2 was 297 K. For serotonin sensing, it was shown by Skeen et al. (1990) with a back-mixed application that the maximum firing frequency response to serotonin can be used to indicate chemical concentration. As is evident from the frequency response represented in Fig. 2, this is also true for the plug-flow technique. In fact, all cells exposed to multiple applications of serotonin at 297 K showed a continuous increase in maximum firing frequency with serotonin concentration, while 4 out of 5 cells at 306 K showed a continuous increase. The fifth cell at 306 K showed an increase in the maximum tiring frequency between lo-’ and 5 X 10m5M, and between 10m4and 10m3M; however, there was a slight reduction in the maximum firing frequency between 5 X 10-j and 10d4 M. The 290 K data also show an increasing trend in maximum firing frequency with serotonin, but the increase is not continuous for all cells. As will be discussed later, this is probably due to the fact that at 290 K the 10 min rinse given between applications was not long enough for a neuron to recover fully from an application. This caused prior additions to affect the maximum response to subsequent applications. The maximum tiring frequency behavior for the 297 and 306 K data, along with data for the back-mixed application at 301 K, is summarized in Fig. 3. Here, a bar graph is used to summarize the average maximum tiring frequency and standard deviations for cells at the different temperatures, concentrations, and application technique (297 K, n = 3-4; 301 K, n = 6; 306 K, n = 5). From this figure, the concentrationdependent increase in maximum firing frequency for each condition can be seen by the increasing means. Also evident from Fig. 3 is that, given an application technique, the maximum firing frequency response to a concentration increases with temperature. Furthermore, the application technique does not appear significantly to affect maximums since the back-mixed data are at an intermediate temperature between the two plug96
Biosensors & Bioelectronics
0
-6
I
-I
&‘ol
297
K
306
K
PF
CST
K
-I)
Fig. 3. Summary of the maximumJiringfiequencyfor VVI and VV2 neurons with a plug-flow application at 297 and 306 K, and a back-m&d application at 301 K. The bars represent the mean of between 3 and 1I cells, and the capped lines show plus and minus one standard deviation around the means.
flow data sets, and, for lob4 and 10m3M serotonin, the means for the back-mixed data also lies between the plug-flow means. At 10m5M the backmixed mean is below both the plug-flow means; however, as seen by the larger back-mixed standard deviations, there is also a large amount of scatter in the back-mixed data. The fact that the application technique appears not to affect the maximal response significantly is important when considering possible uses for a neuronbased sensor because it will allow a device which is calibrated for one monitoring application to be applied to others with different flow characteristics. The increase in firing frequency with temperature is also significant for neuron-based sensing for two reasons. First, it shows that the temperature of the sensor must be closely controlled at the calibration conditions. Second, by operating the sensor at higher temperatures the measured response to serotonin will increase, thus providing a signal which is more easily distinguished from the background firing frequency. An advantage of using a plug-flow application rather than a back-mixed application can be seen from the sizes of the standard deviations in Fig. 3. At all concentrations the plug-flow standard deviations are smaller than the back-mixed value, which indicates a smaller cell-to-cell variability for the plug-flow responses. The cause of the smaller cell-to-cell variability is not yet clear since numerous factors may influence the observed tiring frequency response. However, the reduced cell-to-cell variability is important if a neural sensor is to rely on the average response of a
Neuron-based chemical sensing
Biosensors & Bioelectronics
population
of neurons as suggested by Skeen
etaf. (1990), since a smaller variation translates
into fewer cells required to obtain an accurate average. Reducing the number of cells reduces the device complexity.
.
0.60
2 >I
0.60
.z E z
One positive attribute of a neuron-based sensor illuminated by the back-mixed application experiments of Skeen et al. (1990)was that rinsing returned the response to the baseline, demonstrating reversibility. This was also evident when plug-flow applications were applied to cells. Figure 4 reveals that at 297 and 306 K all neurons exhibited a tiring frequency response which returned to baseline within the 10 min rinse period. In this figure the number of points represented in the averages is between 2 and 5 (29OKn = 2;297K,n = 2-4;306K,n =4-5).For cells at 290 K however, the response diminished more slowly so that it did not always return to baseline during the IO-min rinse for 5 X lo-’ and 10W4~ serotonin. This absence of a return to baseline in 10 min at 290 K is why no data are shown on Fig. 4 for this temperature at 5 X 10m5 and 10e4~. These results suggest that temperature has a significant effect on the reversibility of the response. It is also evident from Fig. 4 that, although there is cell-to-cell va~abili~, the time to return to baseline at a given increasing concentration decreases with temperature.
0
cl
290
K
297
K
306
K
Fig 4. Summary of the time required for the Jiring frequency to return to baseline after rinsing. Represented are results for plug-flow applications at 290. 297, and 306 K. The bars represent the mean of between 2 and 5 cells. while the capped lines show plus and minus one standard deviation around the means.
030
t 0.00
Fig. 5. Mean sensitivity between 10-j and 10m3Mserotonin for cells exposed using a plug-flow application at 297 and 306 K, and using a bark-mixed application at 301 K. The bars represent the mean of between 3 and 6 nouns, while the capped lines show one standard deviation above and below the means.
To determine the effects of temperature and application method on the sensitivity of a neuron-based sensor, the slope of the maximum firing frequency versus the logarithm of the serotonin concentration data for each neuron was estimated using linear regression. Figure 5 shows the average value of slope and standard deviation for cells exposed to plug-flow applications of serotonin between 10m5and 10T3M at 297 and 306 K, and for a back-mixed application at 301 K. In this tigure n = 3,4, and 6 for temperatures of 297,306, and 301 K, respectively. Comparing the mean values for the two plug-flow applications, it is clear that an increase in temperature also increases the slope, thus increasing the sensitivity of the neurons to serotonin. An increase in sensitivity is advantageous since it will provide finer concentration resolution for a neuron-based sensor. Looking at the two application techniques represented in Fig. 5, it appears that even at a lower temperature a back-mixed application provides a more sensitive response to serotonin than a plug-flow application. However, the gain in sensitivity is accompanied by considerably more cell-to-cell variation. This is indicated by the larger standard deviation for a back-mixed application. As with the reduction in the cell-toceil variability seen with a plug-flow applica~on, it is difficult to postulate why a back-mixed application appears to increase the sensitivity. This difticulty arises because of the potential complexity of the mechanism underlying the response. 97
R. S. Skeet
et al.
Application durution
Previous findings from this laboratory showed that the amount of desensitization seen in the maximum firing frequency after an application of serotonin increases with the length of preexposure to a lower concentration (cf. Fig. 9 in Skeen et al., 1990). In addition, Katz & Thesleff (1957) reported that when acetylcholine receptors in frog motor end-plates are exposed to agonists for an extended duration, recovery from desensitization is slowed or incomplete. These results suggest that the time the neurons are exposed to a sample should be minimized to keep desensitization effects low, and thus reduce the amount of rinse time required to recover from desensitization. This raises the question of how short may the application be and still stimulate a true maximum firing frequency response. It was found from these plug-flow addition studies that a maximum response to serotonin is always obtained in 30 s or less, thus setting the minimum time these neurons must be exposed to the analyte solution. A 30 s minimum is the same order of magnitude as the response time reported for Callinectes sapidus (Belli & Rechnitz, 1986). In addition, A plug-flow application is better suited for minimizing desensitization since a sample can be introduced instantaneously to the sensing interface and left in contact just long enough to record the maximum response. Once the maximum has been reached the solution can be quickly replaced with analyte-free saline. By the back-mixed application comparison, reported earlier required 5 min to reach a steady level, while rinsing required the same time to remove the serotonin.
and continues until the next application begins. The third component is the decay in firing frequency, or desensitization, which occurs during a 30 min exposure. Activation
To quantify the effects of temperature and concentration on activation, the increase in firing frequency over baseline after 9 s of exposure (AFF9) was measured. It was found that at each tern~m~~ all cells exposed to multiple additions of serotonin showed a general increase in AFF, with concentration. The trend, though, was not continuous for 1 of 4 cells at 297 K and 1 of 5 cells at 306 IS. Each of these cells showed a AFF9 at 5 X 10e5 M slightly larger than the value at 10m4M. At 290 K, where recovery was not complete after each application, AFF, for 2 of the 3 cells tested increased between 10e5 and 5 X 10e5 M, and then remained at that level for the higher concentrations. The AFF, value for the third cell at 290 K increased between 10e5 and 5 X lo-’ M, but at low4M the level dropped to below that at 10m5M. When 10m3M was applied to this cell AFFg again showed an increase. The effects of temperature and concentration on AFF, are summarized in Fig. 6, representing 2-5 cells per application condition. From Fig. 6 the general increase in AFF, with concentration at constant temperature can be seen by the increasing means. This is most evident at 297 and 306 K. By comparing the mean values at constant concentration, it is apparent that an increase in
Effects of temperature and concentration on response kinetics
Each addition in the multiple application experiments was examined in detail to gain qualitative insights into the influence of concentration and temperate on the kinetics of the firing frequency response. These findings are important since they provide a basis for a quantitative study which will be reported in a future paper. Three components of these experiments are of particular interest. The first component is the rise in firing frequency, or activation, induced by the addition of serotonin. The second component, termed recovery in this paper, begins at the time a rinse cycle is started 98
.I
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LogK?oncentrstionf
Fig. 6. Summaryof the increase in$ringfrequency ajlter9 s of exposure to various concentrations of serotonin. The mean value for neurons exposed using a plug-jlow application at 290. 297, and 306 K are represented by the bars. Each bar is the mean of between 2 and 5 cells, while the capped lines indicate plus and minus one standard deviation on the mean.
Neuron-based chemical sensing
Biosensors t Bioelectmnics
.25
5
10
15
Time From Start of Rinse (Seconds) Fig. 7. Example of the e&cts of serotonin concentration on thefiringfequency decay seen in WI and vv2 neurons during a rinse afkr a short application. The difkrent line types represent the response aJserd@erent levels of serotonin.
temperature increases the rate of rise in the serotonin-induced firing frequency. Recovery
It was observed at all temperatures that following a rinse the rate of decay in tiring frequency was inversely related to the concentration of serotonin that had been applied. An example of the relationship between the decay in firing frequency and concentration is shown in Fig. 7. Figure 7 represents the decay of a WI neuron’s firing frequency after application of three concentrations of serotonin at 306 K. In this figure the tiring frequency for each concentration has been subtracted from the firing frequency when the rinse began so that each concentration could be more easily compared. To quantify the decay behavior, the drop in firing frequency after 40 s of rinsing was measured (AFF,). It was found that at 290 K 2 of 3 cells showed a consistent decrease in AFF, with increasing concentration. For the third cell at 290 K, the inverse relationship between the drop in firing concentration was not frequency and distinguishable after 40 s, but appeared after 100 s. At 297 K, 4 of 4 cells showed a consistent decrease in AFF, with increasing concentration, while at 306 K 1 of 5 cells showed this trend. Of the remaining 4 cells at 306 K, one cell had already reached a minimum firing frequency by 40 s after the lo-’ M application. For this cell, if the drop in
tiring frequency was measured at 18 s, which corresponds to the time when the firing frequency had just reached a minimum, the inverse relationship was apparent. Two other cells at 306 K showed AFF, decreasing between 10m5 and 5 X IO-’ M and then increasing slightly between 5 X lob5 and 10e4~. The final cell showed a continual increase in AFF, with increasing concentration. The effects of temperature on AFF, could not be distinguished from these data because of cell-to-cell variability. Desensitization
Desensitization was examined at 10m3M for the 12 cells exposed to multiple applications, and for 3 additional Wl and W2 neurons with a 10V4M application. The operating temperature for the 3 cells exposed to extended applications of 10m4M was 297 K. It was found that the amount of desensitization increases with increasing temperature and concentration. This is summarized in Fig. 8, which shows the drop in tiring frequency after 15 min of exposure plotted against the operating temperature. Each point represents the mean of between 2 and 4 cells. The direct relationship between temperature and the amount of desensitization is similar to the results reported by Andreev et al. (1984) for desensitization of acetylcholine currents in Lymnea neurons. Extreme temperatures were found to produce a 99
R. S. Skeen et al.
r(.
0001
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’
00001
M
T
T/f
,/I .-
I--_
286
290
225
300
SO6
310
% ii
Temperature
(Ki
Fig. 8. Average drop in firing frequency after 15 min of exposure to serotonin as a finction of temperature and application concentration.
tendency for cells suddenly to stop firing action potentials. This occurred in 4 of 5 cells at 306 K; however, the time of onset of this sudden loss of activity was dramatically different for each cell. Activity was lost after 40, 74, 362, and 1490 s, respectively. For the 3 cells exposed to an extended application of 10d3M serotonin at 290 K, 1 cell stopped tiring after 921 s of exposure. The reason for this loss of activity is not known; however, a similar type of behavior was described by Skeen et al. (1990) with a lo-* M back-mixed application of serotonin at 301 K. CONCLUSIONS A plug-flow technique for applying analytes to an isolated Lymneu s~ag~u~is ganglion preparation has been developed and tested. This system was used to advance the field of neural sensing by providing insight on the effects of temperature and mixing environment on sensing properties. A total of 15 Wl and W2 neurons at three operating temperatures of 290, 297, and 306 K were used in this study. These three temperatures were used since outside this temperature range Wl and W2 neurons lost their concentrationdependent response. To determine the effects of mixing on sensing characte~stics the plug-flow application data were compared to the slow backmixed application data of Skeen et al. (1990). Results show a concentration-dependent increase in the frequency of spontaneous action potentials with a plug-flow application. The increase is seen at all temperatures tested. An increase in temperature results in an increase in the maximal firing frequency caused by a given 100
concentration, as well as in an increase in the sensitivity of these neurons to serotonin. In addition, the time required for the firing frequency to return to baseline decreases with an increase in temperature. Comparing the two application techniques suggests that the maximal frequency response to a concentration is not affected by application technique. Furthermore, by using a plug-flow application, a maximal response is achieved at all conditions tested in 30 s or less which is several times faster than the response reported earlier for the back-mixed application. This is advantageous since it means the neurons may be exposed to serotonin for a shorter period of time, which should reduce the amount of desensitization, thus reducing the rinse time required for the cell to recover completely and give a repeatable response. Also, the data indicate that a plug-flow application reduces cell-to-cell variability in the maximum firing frequency. These results suggest that a neural sensor based on this preparation will operate best at higher temperatures while utilizing a rapid application to expose the cells to analyte. ACKNO’WLEDGEMENTS The authors thank Clark Maxwell for his assistance in designing the rapid application system. This project was supported under the Microsensor Technology program of the Washin~on Technology Center. An equipment donation for the oscilloscope was received from Tektronix Corporation. Initiation of the neuronal biosensor program at Washington State University was aided by an NSF grant, ECE8609910.Graduate training support was provided by the National Institute of Health Biotechnology Training Grant, T32GM08336. REFERENCES Andreev, A. A., Veprintsev,B. N. & Vulfius, C. A. (1984). Two component desensitization of nicotinic receptors induced by acetylcholine agonists in Lymnaeastagnalis neurons.1 Physiol., 353,3X-91.
Baker, T. Q., Buch, R. M. & Rechnitz, G. A. (1990). Intact chemoreceptor-basedbiosensors.Biotechnol. Prog., 6, 498-503. Belli, S. L. & Rechnitz, G. A. (1986). Prototype potentiometric biosensor using intact chemoreceptor structures. Anal. Lett..,19,403-16.
Biosensors& Bioelectronics Belli, S. L. & Rechnitz, G. A. (1988). Biosensors based on chemoreceptors. Fnwnius Z Anal. Chem.. 331, 439-41. Buch, R. M. & Rechnitz. G. A. (1989a). Intact chemoreceptor-based biosensors: responses and analytical limits. Biosensors,4, 215-30. Buch, R M. & Rechnitz, G. A (1989b). Intact chemoreceptor-based biosensors: extreme sensitivity to some excitatory amino acids. Anal. L&t..,25 2685-702. Katz, B. & Thesleff, S. (1957). A study of the desensitiz-
Neuron-based chemical sensing ation produced by acetylcholine at the motor endplate. 1 Physiol., 138, 63-80. Skeen, R. S., Van Wie, B. J., Fung, S. J. & Barnes, C. D. (1990). Evaluation of neuron-based sensing with the neurotransmitter serotonin. Biosensors and Bioelectronics,5, 491-S 10. Winlow, W. & Benjamin, P. R (1976). Neuronal mapping of the brain of the pond snail Limnea stagnalis. In Neurobiology of Invertibrates, ed. J. Salanki, Akademiai Riado, Budapest, Hungary, pp. 41-59.
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