m a
Anal. Chem. 1995, 66,3700-3712
TECHNICAL NOTES
Automated Veioclty Programming for Increased Detection Zone Residence Times in Capillary Electrophoresis Jason B. Shear, Luis A. ColbnJ and Richard N. Zare' Department of Chemistry, Stanford University, Stanford, California 94305
INTRODUCTION Frequently in chemical separations an analyte band yields a detectable signal that is too small to measure accurately. The lowest quantifiable analyte concentration is generally three to five times greater than the lowest detectable concentration.'r2 Although the difference between the limit of quantitation (LOQ) and the limit of detection (LOD) is sometimes unavoidable-particularly when a large fraction of the analyte is chemically altered in the measurement process-it often results from an insufficient detection period. In these instances, all detectable species can be quantified without any modification of the detection hardware. We report the implementationof an "intelligent" detection system for capillary electrophoresis that responds rapidly to the detection of an analyte by directing a decrease in the separation field-and, hence, an increase in the measurement time-and demonstrate its ability to improve the LOQ almost to the LOD. For a wide range of column separation techniques (e.g., HPLC, capillary chromatography, and capillary electrophoresis), analyte molecules commonly are probed briefly as they traverse either an on-line or a postcolumn flow cell and thus generate peaks in a chromatogram or an electropherogram. This procedureis important for rapid and reproducible analyses, but it can severely limit the signal-noiseratio (SNR) of bands. In shot-noise-limited detection procedures, an increase in the detection period can enhance the SNR, provided that a large fraction of analyte molecules continues to generate signal during the additional measurement period. The most widely employed detection method with capillary electrophoresis (CE),UV absorbancedetection, is commonly shot-noise-limited and uses excitation intensities far below those necessary to effect significant analyte degradati~n.~,~ Similar problems are encountered in radioactivity detection, in which nuclide half-lives typically exceed the available measurement time by many orders of magnitude: and in fluorescence detection systems that employ low-intensity lasera incapable of supplying the optimal excitation intensity.=P7 + Present address: Department of Chemistry, SUNY-Buffalo,Buffalo, NY 14214. (1) MacDougall, D.; et al. Anal. Chem. 1980,52, 2242-2249. (2) Ingle, J. D., Jr.; Crouch, S. R. Spectrochemical Analysis; Prentice Halk Englewood Cliffs, NJ, 1988; pp 174-176. (3) Xue, Y.; Yeung, E. S.On-Column Double Beam Laser Absorption Detection for Capillary Electrophoresis. Anal. Chem. 1993, 65, 19881993. (4)Xue, Y.; Yeung, E. S. Double-Beam Laser Indirect Absorption Detection in Capillary Electrophoresis. Anal. Chem. 1993,65,2923-2927. (5) Pentoney, S. L., Jr.; Zare, R. N.; Quint, J. F. J . Chromatogr. 1989, 480,259-270. (6) Soper, S. A.; Shera, E. B.; Martin, J. C.; Jett, J. H.; Hahn,J. H.; Nutter, H.L.; Keller, R. A. Anal. Chem. 1991,63,432-437. (7) Shear, J. B.; Dadoo, R.; Fishman, H.A.; Scheller, R. H.;Zare, R. N. Anal. Chem. 1993,65, 2977-2982. 0003-2700/93/0365-3708$04.00/0
Several techniques exist for increasing the measurement time of analytes in CE. Manual velocity programming for CE was demonstrated by Pentoney, h e , and Quints in a radioisotope detection system. The observationtime for 32Plabeled nucleotides was increased substantially by manually reducing the separation field at the time that an analyta band was expected to arrive at the detection zone. Thii system could improve both the LOQ and the LOD by nearly 1order of magnitude but was critically dependent on the user. Sweedler et al.8 developed an automated approach for increasing the measurement time of analytes in which residence times in the detection zone could be extended by more than a fador of 100. In this procedure, the accumulating analyte signal on a two-dimensional multichannel detedor was shifted from one column to the next at the same rate that the fluorescence image of an analyte band moved across the detector. Optimized fluorescence detection was possible for fast-migrating species even when the excitation intensity was limited to very low levels. The method we describe for quantifying analytes at the detection limit has advantages over the alternative methods for increasing measurement time. An algorithm is developed for automatingvelocity programming that receives input from the detector, assesses the likelihood that an anal* band is in the detection zone, and reduces the rate of analyta transit when the likelihood is high. Rapid analysis time is achieved by maintaining a fast rate of analyte transit when no analyte is present in the detection zone. Although the LOD cannot be improved by using this technique, no advance knowledge is required of the migration time of analytes, and unlike the band-tracking technique, the existing algorithm can be applied to any detection method that can benefit from longer detection periods, including W absorbance detection.
EXPERIMENTAL SECTION We employ laser-induced fluorescence (LIF)detection with CE to demonstrate the effects of velocity programming on the SNR for analyte bands. In brief, the 514.6-nml i e from an argon ion laser (Model 2017,Spectra Physics, Mountain View, CA) is focused onto the channel of a 66-pm-i.d., 370-pm 0.d. capillary using a 50-mm f.1. plano-convex lens. Fluorescence is collected by placing the illumination spot of the capillary at the focus of a 2-cm-diameterparabolic mirror and focusingthe reflected light onto the photocathode of a photomultiplier tube (PMT) using a ah-diameter plano-convex lens. The capillary is affiied to an immobile mount on either side of the parabolic mirror to prevent voltage-dependent flexing at the detection zone. Three narrow-band interference fiiters (centered at 546-660 nm, +lonm baseline width) are positioned between the mirror and the collection lens to discriminate analyte fluorescence from background. The PMT is operated at 600 V, and the output current is sent to a picoammeter (Model 485, Keithley Instrumenta, (8) Sweedier, J. V.; Shear, J. B.; Fishman, H.A.; h e , R. N.; Scheller,
R. H.Anal. Chem. 1991,63,496-502. Q 19Q3Amerlcan Chemlcal Soclety
ANALYTICAL CHEMISTRY. VOL. 85. NO. 24. DECEMBER 15. 1999
Cleveland, OH)via a
1-8
RC fiiter. The ampliried signal from
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thepicoammeterisconnectedtotheinputofananalog-bdigital converter (board Model NB-MIO-16XL42, National Instruments, Austin, TX) in an Apple Macintosh nci computer. AprogramwritteninLabView2(panno.320244-01.Nationd Instruments) employs this input signal as the basis for control
of theseparation field. The algorithmcalculatestheappropriate output signal to be sent as an instruction from the 1/0 board (a possible -10 to +IO V) to a high-voltage power supply (Model 20 20, Trek. Inc., Medina, NY). The uutput voltage from the powersupplyscalesas2000X theinstructionsignaland therefore provides a possible -20 to +20 kV voltage drop across the separation capillary. In t h e e experimentn. the power supply is directed to generate either a "high" voltage of 17 kV when no band is detected traversing the excitation spot or a 'low' voltage of 1.7 kV when a band is detected. The values of both the high and low voltage are adjustable. The distance from the capillary inlet to the detection zone is 50 cm. and the total capillary length is 92 cm. Thus. the poesible values for the separation field are 185 and 18.5 V/cm. A 5 mM sodium borate buffer (pH 8.9)is the separation electrolyte, and samplesareintroduced by placing thecapillary inlet inasample vial rained -S cm ahove the outlet for 20 8. Arginine and glutamate are tagged with the fluorescentprobe, (carboxytetramethylkhodaminesuccinimidylester (CTMR-SE) (Molecular Prohes.Eugene.OR). Approrimately30mMarginine or 15 mM glutamate in a sodium horate buffer (pH 8)is mixed at a 5 1 volume ratio with a 0.6 mM solution of the labeling reagent in dimethyl sulfoxide. The tcarboxytetramethylJrhodaminearginine (CTMR-Arg) and (carboxytetramethylJrhodamineglutamate (CTVR-Clu)productsarediluted in water before separation.
COMPUTER ALGORITHM The LabView program for controlling the separation field operatea at 1 Hz (an approximate match to the 1-8 RC filter) andhastwomainfunctions: (I)tocalculateadetenrsignal threshold used to determine whether an analyte band is traversing the detection zone and (2) to instruct the power supply to generate either a 'high" or 'low" separation field, depending on whether an analyte band is in the detection zone. When the separation starts. the field is maintained at the highsettinguntil30datapointacanbetaken. Beginning at this time, a calculation is made for the values of the mean and standard deviation of the baseline values using a sliding data set of the previous 30 measurements. The threshold (TH) for concluding that a band is in the detection zone is calculated as T H = AV + nu (1) where AV is the data set mean, u is the standard deviation of the data set, and n is a positive number that will vary, depending on the relative importance of false positives (incorrectly concluding that a band is in the detection zone) to false negatives (incorrectly concluding that a hand is not in the detection zone). Although the value of TH changes a8 each new data point iscollected, asinglevalueofn is employed for an entire separation. In our studies, we require that a data point exceed the mean by more than 30 before the controlling program concludes that a band occupies the detection zone. Assuming that the distribution of baseline datapointaisCaussian (agoodapproximationtothePoisson distribution when n is large), only 0.13% of all data points should randomly exceed the threshold value when n = 3. Figure 1 demonstrates the sequence of events as a band approaches, passes through, and leaves the detection zone. In the first diagram (Figure la), the band travels toward the detection zone under the influence ofa high separation field (Eblh, denoted by the large arrow). As the band enters the detection zone and generatea fluorescence (Figure Ib), the LabView program acknowledges that a data point has
Sequenceof eventsasananalytebandapproaches,~ and leavesthe deteclh zone (DZ) in capnlary elecbophamSa. (a) An analyte band rapidly approaches DZ under the influem of a hlgheparatlon Reld (denoted by the large arrow). The mreshold for -the separa~fieldiscakulateduslngtheaverageandstandsrd devlalbn of a sllding 30-point data set. (b) The band enters DZ and Is detected. causing the computer program lo wnd an insku& to the separalbn field power supply to redthe Reld (shown by the small arrow). (c) The band continues to lravene at the detection zone at a slow velochy. lhereby increasing the total amunt of measured signal. To lessen the llkellhcud lhat a data palm randomly drops below the threshold durlng lhis period. summed blocks of 10 data points ara cmpared to a modif!& lhreshold value. (d) The band has p a d through DZ. but not enough time has elapsed to Wnerate a new data set of 30 baseline values. Consequently. ltmmntshold is set to the last threshdd value before the peak arrived at DZ unHl a complete data s e t c a n beaccumulated.(e)ThebandhasbeenpastDZfwmanydata points andltmlhreshddvaluelsagain calculated intheorlginal manner. -1.
thr-
exceeded the threshold level and consequently sends a signal to reduce the separation field to E,, (shown by the small arrow). The band velocity decreases; consequently, analyta molecules have a longer period to generate signal as they pasa through the detection zone. The controlling program must analyze the incoming data at a relatively rapid frequency (-10 times per hand-usually 1 Hz) to ensure that the separation field can be reduced before the peak maximum crossesthedetectionmne. Totakeadvantageof thedecreaee in relative noise that accompanies longer detection periods, electropherogram data points are produced by binning the rapidly acquired data points. Because the velocity of an analyte band is slow while it is being measured, the number of binned data pointa, B, used to generate the new data block can be set to
B = Ew/Eh
(2)
without sacrificing resolution. Hence, when Em = 17 kV a n d E h = 1.7kV,B= 10. Ifanalytasigdincreaseslinearly with measurement time, the mean integrated signalof a data block is a factor of B greater than the mean signal from an individualdatapoint. Theuncertaintyin thedata blockalso is larger, hut becausetheaccuracyof measurementsis limited hy Poisson statistica, it d e s only as the square root of B. Thus, the signal and error in a data block are related to the same quantities in a data point by (signal),,,
f (error)blwk= B(signal)&, f B'/2(error)w
(3)
The error in the baseline (background) also s d e s as El'* and often is the primary uncertainty in the measured signal (i.e.,
>> error,^). If the concentration of an anal@ is close to the LOD, a datapoint value may fallbelow the m o l d during theperiod shown in Figure ICbecause of random fluctuations in the baseline or signal. Should such a fall occur,the separation field would increase and the band could rapidly migrate from ERO-
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ANALYTICAL CHEMISTRY, VOL. 65, NO. 24, DECEMBER 15, 1993
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Threshold Calculation
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Seoaration Field Determination
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7 1 Flgure 2. Fbw cherts of the algorithms for (a) the thredrold value calculation and (b) the separation field determination. TH is the measurement threshold for concluding that an analyte band is being detected,AVm and AVm are the mean value8 of the data sets containing the last 30 and 29 measurements, respecUvely, 630 and um are the standard deviations of these data sets, and 8 is the number of rapid data points binned to generate a data block.
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the detection zone. To avoid this problem, a threshold that takes advantage of the decrease in the relative error of a data block value is used when the separation field is low:
+
TH,, = B(AV) B 1 ’ 2 ( ~ ~ )
(4)
Here, THLFis the threshold when the field is low, AV is the mean data-point value from the data set containing the last 29 data points taken under the high-field setting, and u is the standard deviation of this data set. A data block of 10 data points is summed once every 10 s and is compared with this threshold value until the sum of a data block drops below the threshold. Because the relative error for a long measurement is less than that for a short one, the likelihood that a summed block of data points will randomly dip below the threshold is significantly reduced. In Figure Id the analyte band has exited the detection zone, the signal has fallen below the threshold value, and the separation field has increased to the high setting. Data points again must be compared with the threshold every second. Until the band has been past the detection zone for at least 30 s, the threshold cannot be calculated using new data. Consequently, during this period, the threshold is set to the value of the last threshold before the band arrived at the detection zone. Finally, in Figure le, the band has been past the detection zone for many data points, and the threshold is once again calculated in the original manner. Flow charta that describe the logical progression of the threshold calculation and the separation field determination are shown in Figure 2.
RESULTS AND DISCUSSION Successful application of velocity programming requires that the rate of signal generation exceeds the rate of increase in noise for increased detection times. The laser intensity employed in the flow experiments is 4 mW, a relatively low
2 min Figure 8. Demonstratbn of the degree of photoalteratbn during three w - ! P ~ t h e - = n - f ( - ~ glutamate (CTM-Glu). Approximate~ly25 mW of the 514.5-nm line of an argon b n laser is focused onto the Separation channel, and CTMRgiu m&ates through the excitation spot under the Inof 185 V/cm (peak 1). The Reid is then reversed, and CTMI-QIuis datectd a thne (peak 2). Finally, the fk# is rmtoredto b original dkectkn,and CTMRQlu is detected a thkd time (peak 3). Even at W relethrely high excttatbn Intendty,the w e eof photoelkwatknle small.
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F l g m 4. Three coneecutlvo separations at 185 Vlcm of CTMR-Arg (nominally 15 nM, peak A) and a reafpntspeck18(peak B) using 4-mW exoftatkn intensity. No vekclty programming is employed in separatbns. Note the varlabmty in the ratb of the helghl of peek A to peak B in the three separatbm due to the b w slgnal-to-ndso ratb. The apparent peak at -2.5 min is the result of a spike In the detectbn SyStStTl.
value consideringthe photoalterationresistanceof rhodamine molecules and because the excitation wavelength (614.6 nm) is far from the absorption maximum (-660 nm). To assess the degree of photobleaching (Figure 3)) the excitation intensity is increased to -26 mW, and CTMR-Glu is electrophoresed under the influence of 186 V/cm. Following the detection of CTMR-Glu (peak l),the separation field is reversed and CTMR-Glu is detected again (peak 2). Finally, the field is reversed to its original direction, and CTMR-Glu is detected a thud time (peak 3). At this excitation intensity
ANALYTICAL CHEMISTRY, VOL. 65, NO. 24, DECEMBER 15, 1003 9711
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Time (minl Figure 5. Three consecuthre separations of the same sample used for Figure 4, again with 4-mW excitation intensity. For most of the separatbn, a default "high" fie# setting of 185 V/cm is empbyed. When bands are detected, automated velocity programming reduces the Re# to 18.5 V/m, thus increasing the measurement time by a factor of 10. Raw data are shown in the bwer set of electropherograms, and binned blocks of 10 l-s data points are plotted in the upper set. Note that the variability in the ratio of the peak heights seen in Figure 4 Is signiflcently reduced in the upper set of electropherograms.
almost no photoalteration of the labeled glutamate molecules occurs during a passage through the detection zone. Because the photophysical qualities of CTMR-Glu, CTMR-Arg, and CTMR-SE (native and hydrolyzed) are similar, and because the residence time for the slow-migratingCTMR-Glu is longer than for the other compounds, we can be confident that the degree of photoalteration for all the rhodamine species is minimal. Although the absolute height of a peak may vary from one separation to the next because of differences in injection quantity, the height ratio of two different peaks from a given sample solution should remain relativelyconstant for analytea at high concentrations. However, a constant ratio of peak heights cannot be expected at analyte concentrations close to the LOD. Shown in parts a-c of Figure 4 are three consecutiveseparations of CTMR-Arg (nominally15nM, peak A) and a reagent species (peak B). For these separations, no velocity programming is employed. Because the SNR is relatively poor, significant variability occurs in the height ratio of the two peaks. The relative standard deviation in the ratio of peak heights for these three separations is greater than 20% and would increase substantially for lower concentration samples. Figure 5 demonstrate that this variability can be markedly diminished by automated velocity programming. Three consecutive separations of the same sample used for Figure 4 are shown in parts a-c of Figure 5; the raw data (signalfrom the picoammeter) are provided in the lower electropherograms. For the upper traces, the LabView program takes data at 1 Hz and sums blocks of 10 consecutive data points to generate 10-8 data points. This process yields an improvement in the S N R without sacrificingresolution because of the slow migration of analytes in the detection zone. Although a small change in the absolute peak heights occurs in the three separations, the relative standard deviation in the ratio of peak heights is now between 3 and 4%, a -6-fold improvement over the separations shown in Figure 4. For these experiments, a detector measurement must exceed the average of the baseline measurements by at least 3a to effect a reduction in the separation field, and relatively few false positives are observed. In parts a and b of Figure 5 several unwanted reductions in the separation field occur in the 12-minseparation, and in Figure 5c no false reductions take place. Thus, the unproductive lengthening of the separation is, on average, less than 1min, which we consider
to be an acceptable delay. It is worthwhile noting that false positives occur -10 times in the summed period covering separations (a) and (b) (fewer than 1500 data points). If the valuea of baseline data points followed a Gaussian distribution, fewer than two false positives should occur duringthis period. The source of this discrepancy is unknown. Finally, there may be instances in which a lower threshold value is desired, but a price w i l l be paid in the length of the separation. It is also worth noting the resolution of the two peaks in the electropherograms shown in Figure 5. Although the temporal width of the peaks hae increased because of the slow velocity during detection, the resolution of the peaks does not significantly suffer (a slight lose in resolution may result from diffusional broadening that occurs during the additional analysis time). This is evidenced by fact that the baseline time separating peaks is unaffected by velocity pr~gramming.~ Figure 6 demonstrates that the results achieved by velocity programming are not artifactual but represent the consequence of integrating signal for longer periods than without velocity programming. In this separation, the rate of fluorescence (and background) is increased by raising the laser intensity by a factor of 10 to -40 mW, and no velocity programming is employed. Note the similarity in the ratio of peak heights and the SNR to the upper traces in Figure 5.
AB designed for our experiments, automated velocity programming can improve the ability to quantify species by analysis of peak heights, not peak areas. The most fundamental reason that peak areas cannot be used is that a n a l y h at different concentrations surpass the threshold at different points in relation to the center of the band. Whereas highconcentrationanalytes trigger the reduction in the separation field as the peak begins, analytes present at the LOD do not exceed the threshold until the peak maximum is in the detection zone. Hence, the peak area is amplified more for high-concentration analytes than for low-concentration analytes. An additional problem limits the reproducibility of peak areas. Because the algorithm loop repeats at a set, finite frequency (e.g., 1Hz), significant differences can occur in the position of the band with respect to the detection zone when (9) T h e amount of time separating two adjacent peaks can increase, however, if the velocity programming algorithm falsely concludes that a band is in the detection zone. Nevertheless, this effect would not be detrimental to resolution.
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ANALYTICAL CHEMISTRY, VOL. 65, NO. 24, DECEMBER 15, 1993
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Flgwe 6. Electropherogram demonstratlng the result of employlng higher excltatbn Intensity Instead of automated velocity programming. The sample Is the same as that used In Flgures 4 and 5, and the excitation Intensity Is a factor of 10 hlgher (-40 mW). As In Flgwe 4, the separation field Is constant at 165 V/cm. The slmilarlty In the peak-t~ratbandthesigreCto-noiseretioofthis elecb.opherogam to those of the upper electropherograms of Figure 5 valldates the effects observed for veloclty programming. The splke at -4 mln Is random and does not represent detection of a band.
the command to reduce the threshold is executed. These differences may explain the variation in peak areas for the three separations shown in Figure 5. As noted earlier, this imprecision in execution time will not affect peak heights as long as the loop frequency is high enough to slow the band before the peak maximum passes through the detection zone. Automated velocity programming can be employed to increase the SNR by approximately the square root of the detection time over a limited range of times. Depending on the detection method, source flicker noise or analyte degradation becomes significant after some period. In all cases, diffusion of analyte bands is a concern. To achieve reasonably accurate measurementsfor analytes close to the LOD, a 3-fold increase in the S N R (a 10-fold increase in the detection time) is often sufficient. Capillary electrophoresisoften relies on the reproducibility of migration times to identify species. When automated
velocity programming is employed,however, the time at which an analyte is detected depends on how many bands have been detected in a separation before that analyte. Fortunately, when the migration velocities of analytes scale linearly with the separation field, identification of species based on migration times can still be accomplished by multiplying the time of detection by the average value of the separation field up to the time of detection. The product will be constant for a species, regardless of the components in the sample. A more precise identification of species can be still be accomplished, as usual, by spiking samples with standards. Although an automated velocity programming procedure hae been demonstrated to improve the LOQ for anal* close to the LOD, some samples are not amenable to this sort of analysis. One requirement for practical employment of automated velocity programming is that the detector spend a significant fraction of ita time not detecting analyte signal. For complex biological analyses, this requirement frequently will not be met. Furthermore, our algorithm relies on reestablishment of the baseline following detection of a band so that a high separation field can be reapplied. Consequently, automated velocity programming can be strongly sensitive to peak tailing. This shortcoming could be prevented by employing an algorithm that recognizes the completion of a peak by ita diminishing slope.
ACKNOWLEDGMENT We gratefully acknowledge Steve Pentoney for advice and commentsin the preparation of the manuscript. In addition, we thank Beckman Instrumenta, Inc., and the National Institute of Mental Health (Grant NIH 5R01 MH45423-03) for continued financial support. J.B.S. is a Howard Hughes Medical Institute Predodoral Fellow. RECEIVED for review July 22, 1993. Accepted September 21, 1993.
