Anal. Chem. 2000, 72, 3635-3641
Label-Free Biochemical Detection Coupled On-Line to Liquid Chromatography Hans-Martin Haake,† Leonie de Best,‡ Hubertus Irth,*,‡ Ram Abuknesha,§,| and Andreas Brecht⊥,#
Institute of Physical Chemistry, University of Tu¨bingen, Auf der Morgnestelle 8, 72076 Tu¨bingen, Germany, Division of Analytical Chemistry, Leiden/Amsterdam Center of Drug Research, University of Leiden, Leiden Institute of Chemistry, Einsteinweg 55, P.O. Box 9502 2300RA, Leiden, The Netherlands, Division of Chemistry, Department of Analytical Chemistry, Vrije Universiteit Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands, Division of Life Sciences, King's College London, University of London, 150 Stamford Street, London SE1 8WA, United Kingdom, and EPFL, Department du Chimie, LCPPM, Institute of Physical Chemistry, 1040 Lausanne, VD, Switzerland
The on-line coupling of a label-free optical biosensor to a HPLC system is described by combining the separation power of HPLC with the specificity of the biosensor system. A highly cross-reactive antibody against the pesticide isoproturon was used as model for affinity proteins. The binding strength of the antibody to the utilized pesticides was characterized with the biosensor, first. In the on-line coupling setup, the eluate of the HPLC was mixed continuously with the antibodies. The presence of antigens was detected by a reduction of the antibody binding to the transducer. This reduced binding was quantified by a differentiation of the sensor signal by applying a Savitzky-Golay algorithm. Limits of detection were found to be in the femtomole range without preconcentration, which is comparable to a study using fluorescence-based biochemical detection. Typical detectors in liquid chromatography such as UV detectors, differential refractometers, and electrochemical detectors are nonselective. An improved selectivity is achieved with hyphenated techniques such as HPLC-MS, HPLC, and NMR. While these detectors respond to structural aspects of the analyte molecule, i.e., its chemical nature, often functional aspects of the analyte are of interest. To obtain functional information, a different approach to detection is necessary. Biochemical assays as detectors in liquid chromatography can provide information about biological activity. Several methods of coupling HPLC and bioassays were developed in recent years. These techniques utilize the high selectivity and sensitivity of bioassays and the separation power and potential of automation of HPLC, as well. Thus, attractive ways are available to identify substances in mixtures, by their effect on biological receptor molecules. This is especially interesting in the area of screening for natural compounds. Several reports of coupling immunoassays (for example),1-3 receptor †
University of Tu ¨ bingen. University of Leiden. § Vrije Universiteit Amsterdam. | King's College London and EPFL, Department du Chimie. ⊥ Institute of Physical Chemistry. # Present address: Agilent Technologies, Hewlett-Packard Str. 8, D76337 Waldbronn, Germany. ‡
10.1021/ac991157g CCC: $19.00 Published on Web 06/29/2000
© 2000 American Chemical Society
assays,4 and immobilized enzyme reactors (for example)5-8 online to liquid chromatography have been published in recent years. Whereas the postcolumn immunoassays and receptor assays are based on the detection of labeled receptors or ligands, enzymatic reactions were detected electrochemically5,6,8 or by using chemiluminescence.7 An extensive review of biospecific detection in liquid chromatography was published by Emneus and MarkoVarga.9 In the past decade, affinity biosensors have been developed as analytical tools for label-free bioassays.10-13 All techniques allow the direct detection of the interaction between two species without labeling. One species is immobilized at the surface of a transducer. The binding of the other compound to the immobilized partner will lead to distinct physical effects, detected at the transducer surface. Two principal assay formats allow for the quantification of a compound. In the direct test format, the binding of the active compound to the immobilized species itself is detected. In the second type of assay, the examined substance is determined indirectly by the inhibition of a binding partner by a reduction in the binding of this partner to the transducer. While the first format is preferred for the quantification of macromolecules such as proteins, the second type is used for small molecules, which would show only minor effects in a direct binding assay. These affinity biosensors are of particular interest as tools for fundamental (1) Oosterkamp, A. J.; Irth, H.; Tjaden, U. R.; Van der Greef, J. Anal. Chem. 1994, 66, 4295-4301. (2) Oosterkamp, A. J.; Irth, H.; Beth, M.; Unger, K. K. U. R.; Van der Greef, J. J. Chromatogr. 1994, 653, 55-61. (3) Irth, H.; Oosterkamp, A. J.; van der Welle, W.; Tjaden, U. R.; Van der Greef, J. J. Chromatogr. 1993, 633, 65-72. (4) Oosterkamp, A. J.; Villaverde Herraiz, M. T.; Irth, H.; Tjaden, U. R.; Van der Greef, J. Anal. Chem. 1996, 68, 1201-6. (5) Kiba, N.; Shitara, K.; Furusawa, M. J. Chromatogr. 1990, 537, 443-48. (6) Yao, T.; Wasa, T. Anal. Chim. Acta 1988, 209, 259-64. (7) Ikegawa, S.; Hirabayashi, N.; Yoshimura, T.; Tohma, M.; Maeda, M.; Tsuji, A. J. Chromatogr. 1992, 577, 229-38. (8) Ortega, F.; Dominguez, E.; Burestedt, E.; Emneus, E.; Gorton, L.; MarkoVarga, G. J. Chromatogr. 1994, 675, 65-78. (9) Emneus, J.; Marko-Varga, G. J. Chromatogr. 1995, 703, 191-243. (10) Liedberg, B.; Nylander, C.; Lundstro ¨m, I. Sens. Actuators 1983 4, 299304. (11) Cush, R.; Cronin, J.; Steward; W.; Maule, C.; Molloy; J.; Goddard, N. Biosens. Bioelectron. 1993, 8, 347-54. (12) Nellen, P.; Tiefenthaler, K.; Lukosz, W. Sens. Actuators 1988, 15, 285-95. (13) Gauglitz, G., Brecht, A., Nahm, W. Sens. Actuators B 1993, 11, 21-7.
Analytical Chemistry, Vol. 72, No. 15, August 1, 2000 3635
detecting free antibodies by their binding to the sensor surface. The presence of an analyte in the eluate decreases the concentration of free antibodies temporarily. A partial mass transport limited binding was used to determine the concentration of these unoccupied antibodies. Signals depending on the concentrations of antigens and on their affinities to the antibodies were measured.
Figure 1. Structures of the examined pesticides and of the derivative used as hapten.
research where interaction monitoring without a label avoids potential interference from a labeling step. The transducer employed in this work was based on reflectometric interference spectroscopy (RIfS) introduced by Gauglitz et al.13 RIfS proved to be a robust system for immunosensing of pesticides,14 determination of affinity constants,15 and examination of DNA intercalating substances.16 A compact, cost-effective system for RIfS measurements was set up based on a commercial cuvette spectrometer, allowing the label-free detection of changes below 1‰ of a protein monolayer.17 The coupling of label-free detection techniques to liquid chromatography applying a direct assay format is described in the literature for the quantification of specific proteins. Tom-Moy et al.18 demonstrated the use of a surface transverse wave (STW) device as HPLC detector for human IgG. Recently, Bracewell et al.19 coupled an optical biosensor to affinity chromatography to detect the breakthrough of antibody fragments through a column. In this paper, we report a novel approach to the label-free biospecific detection of small molecules separated by HPLC. An indirect assay format was applied using antibodies against the pesticide isoproturon as model affinity protein. The antiserum was generated by immunizing a rabbit with a bovine serum conjugate of the hapten [3-(4-carboxymethylphenyl)]-1,1-dimethylurea to yield a highly cross-reactive polyclonal antibody to the 1,1dimethylphenylurea group. Figure 1 shows the structure of the four examined pesticides and the structure of the hapten. The eluate of the HPLC column was mixed with the antibody solution continuously and passed through a reaction coil to the biosensor (14) Brecht A.; Piehler J.; Lang, G.; Gauglitz G. Anal. Chim. Acta 1995, 311, 289-99. (15) Piehler J.; Brecht A.; Giersch, T.; Hock, B.; Gauglitz G. J. Immunol. Methods 1997, 201, 189-206. (16) Piehler, J.; Brecht A.; Gauglitz G.; Zerlin, M.; Maul, C.; Thiericke, R.; Grabley, S. Anal. Biochem. 1997, 294, 94-102. (17) Schmitt, H.-M.; Brecht, A.; Piehler, J.; Gauglitz, G. Biosens. Bioelectron. 1997, 12, 809-16. (18) Tom-Moy, M.; Doherty, T. P.; Baer, L. R.; Spira-Solomon, D. ACS Symp. Ser. 1995, No. 613, Chapter 2. (19) Bracewell, D. G.; Gill, A.; Hoare, M.; Lowe, P. A.; Maule, C. H. Biosens. Bioelectron. 1998, 13, 847-53.
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EXPERIMENTAL SECTION Materials. Fenuron (1,1-dimethyl-3-phenylurea), isoproturon ([3-(4-iospropylphenyl)]-1,1-dimethylurea), monuron ([3-(4-chlorphenyl)]-1,1-dimethylurea), and monolinuron ([3-(4-chlorphenyl)]1-methoxy-1-methylurea) were obtained from Riedel de Hae¨n (Seelze, Germany). The derivative [3-(4-carboxymethylphenyl)]1,1- was prepared by a reaction of N,N-dimethylcarbamyl chloride with aminophenylacetic acid ethyl ester, followed by a cleavage of the ester binding. Details will be published elsewhere.20 Methanol HPLC grade was supplied from Rathburn Chemicals (Walkerburn, U.K.). Common chemicals and biochemicals were purchased from Sigma (Deideshofen, Germany) and Fluka (NeuUlm, Germany). Transducers for RIfS were manufactured by Schott (Mainz, Germany), on float glass using an ion plating process (10 nm of Ta2O5 and 330 nm of SiO2). Amino dextran for surface modification was prepared according to ref 21 The transducer chips were modified with amino dextran as described in ref 21. The isoproturon derivative was bound to the amino dextran using 2-(1H-benzotriazol-1-yl)-1,1,3,3-tetramethyluronium tetrafluorborate (TBTU) and N-ethyldiisopropylamine (DIPEA) as coupling reagents: 2 mg of [3-(4-carboxymethylphenyl)-1,1dimethylurea and 1 mg of TBTU were dissolved in dimethylformamide; 1 µL of DIPEA was added. An amino dextran modified transducer was incubated overnight with this solution and rinsed with N,N-dimethylformamide and Millipore water. Apparatus. Titration experiments were carried out with a RIfS setup, which is described in ref 17, using a flow injection analysis system with autosampler for sample handling. A schematic drawing of the setup used for the coupling experiments is given in Figure 2. The LC system consisted of a Spectroflow 400 HPLC pump (Applied Biosystems), a 7010 Rheodyne six-port injection valve (PEEK injection loop 2 µL) and a 150 mm × 1.6 mm i.d. PEEK column packed with Lichrosorb RP-2 (Chrompack Merck, Darmstadt, Germany). For some measurements, an UV detector Jasco 875-UV (Jasco Benelux B. V., Maarsen, The Netherlands) with λ ) 254 nm, range 0.001 absorption unit (3) was used. LC separations were carried out using 37% methanol, 63% Millipore water (v/v) as mobile phase; the flow rate was 200 µL/min. The HPLC eluate was split 1:3 (2). A fraction of 50 µL/min was mixed with a 1.5 µg/mL (10 nM) antibody solution (5) at 200 µL/min pumped with a Minipuls 3 (Gilson, Villiers-le-Bel, France) using a T-type mixing union (4). The mixture was directed through a reaction coil (6) of 150 µL volume (knitted 0.25- mm-i.d. poly(tetrafluoroethylene) tubing). A second Rheodyne six-port injection valve (7) was used to switch the flow through the RIfS cell between eluate/antibody mixture and regeneration fluids (8). The RIfS measurements were perfomed using a cuvette spectrometer Spekol 1100 (Analytik Jena, Jena, Germany) modified according to ref 17 with a 1:2 fiber (20) Abuknesha, R.; et al., in preparation. (21) Piehler J.; Brecht A.; Geckeler K. E.; Gauglitz G. Biosens. Bioelectron. 1996, 11, 579-90.
Figure 2. Scheme of the setup: 1, eluate of the HPLC column; 2, split; 3, UV detector (only for some measurements), 4, mixing union; 5, reagent flow of the antibody solution; 6, reaction coil; 7, injection valve; 8, reagent flow of regeneration solution; 9, measurement cell with transducer; 10, 1:2 fiber coupler; 11, diode array; 12, halogen lamp; 13, waste. Straight curves, flow line run mode; dotted curves, flow line regeneration mode; dashed curves, light pass.
coupler (Microparts, Dortmund, Germany) and a 5-V/10-W halogen lamp with integrated reflector (Welch Allyn, New York). Transducer chips were mounted to a flow cell with a flow channel 50 µm × 2 mm × 5 mm (Perspex, varnished outside with black paint,). The gap (∼100 µm) between transducer chip and the fiber was filled with glycerol (80%) for refractive index matching. Data acquisition and evaluation of the interference spectra was performed with self-written software running under Windows95 on a personal computer. During a HPLC run, the transducer surface binds several nanograms of antibodies per square millimeter. These have to be removed after each run to reset the system for the next chromatogram. Regeneration of the transducer surface was performed by injection of first a pepsin solution, pH 1.75, followed by acetonitrile/water/propionic acid (49:49:2, v:v:v). After recording longer chromatograms, it was necessary to repeat this procedure once. Regeneration fluids were pumped at 320 µL/min with a Skalar tubing pump using an acid flex pump tubing, i.d. 0.76 mm. The regeneration fluids were selected with an 1-8 solvent select valve (actuator 817, Gilson). Methods. Affinity Titration. An important parameter for biochemical detection is the affinity of the antibodies to the analytes. The affinities of the antibodies used were determined with a titration assay: Purified antibody solutions of 300 ng/mL were incubated with increasing concentrations of analyte. The relative concentrations of free antibodies under equilibrium conditions were determined with a RIfS transducer under mass transport limited conditions as described in ref 15 using the RIfS setup with FIA outlined in ref 17. A transducer with a high binding capacity for the antibody leads to a fast binding reaction at the surface, and hence the diffusion of antibodies to the surface becomes rate limiting. Thus, linear binding curves are obtained, the slopes being proportional to the concentration of free antibodies in the flow (see Figure 3). Titration curves were plotted with relative slopes as measure for the concentration of free antibody versus the concentration of analyte. The titration curves were fitted with a logistic function
y)
A1 - A 2 1 + (x/x0)p
+ A2
Figure 3. Binding curves for the injection of 280 ng/mL antibody with 0/1/10/100/1000 ng/L (from top to bottom) fenuron. A, prerun baseline; B, binding; C, regeneration; D, postrun baseline.
by a Marquart-Levenberg nonlinear least-squares fit (software Origin 5.0 from Microcal, Northampton, MA). For the fit, the value of A1 was fixed to 100% whereas the offset A2, the test midpoint x0, and the exponent p were varied. The mixing of the eluate with antibody solution introduces a certain amount of methanol, which affects the affinities of the antibodies. This influence was quantified to determine a tolerable content of methanol. Titrations were performed with PBS buffer containing 5 and 10% methanol; the titration curves were fitted in the same way as for the titration in pure PBS. Evaluation of the HPLC-RIfS Binding Curves. The signals measured in the coupled HPLC-RIfS setup were also obtained under mass transport limited conditions. Thus, the slope of the signal was proportional to the concentration of unblocked antibodies. Therefore, quantification was performed by differentiation of the binding curves with Origin 5.0 using the Savitzky-Golay method to reduce the influence of noise in the RIfS signal. - Nine points, corresponding to 45 s, were chosen for the local polynomial regression around each point since the half-width of the peaks of the first eluted substance fenuron was found to be in the range of 40-50 s, depending on the concentration. The result of this operation is a reasonably constant baseline with any substance peak occurring as a negative excursion from the baseline level. For the quantitative evaluation of the RIfS chromatograms, the first derivatives were normalized to the baseline calculated with a fit of a second-order polynomial to all parts of the curve that do not contain a peak. Then the curves were subtracted from 1.0 and the peaks were integrated numerically with Origin 5.0. RESULTS AND DISCUSSION Determination of the Affinities and the Influence of Organic Solvent. The use of mass transport limited binding of affinity proteins to ligands immobilized at the transducer surface for the determination of the concentration of unbound protein has been shown previously.14,15 Five binding curves for the antiisoproturon antibody with various concentrations of fenuron are given in Figure 3 as an example. At 120 s, a mixture of antibody and antigen is injected. An increased amount of antigen decreases the concentration of free antibodies and thus decreases the slope of the curve. These curves Analytical Chemistry, Vol. 72, No. 15, August 1, 2000
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Table 1. Test Midpoints and Standard Deviation from the Fit of the Titration Curves for the Four Analytes with Different Amounts of Methanola
isoproturon monuron fenuron monolinuron a
pure PBS
5% methanol
10% methanol
0.7 ( 0.1 2.1 ( 0.2 5.4 ( 0.4 72.9 ( 7.5
1.6 ( 0.2 5.8 ( 0.7 13.1 ( 1.3 181.5 ( 30.6
4.0 ( 0.7 13.1 ( 1.3 30.7 ( 2.3 410.0 ( 49.9
Values are given in nanograms per milliliter.
Figure 4. Titration curves for the four analytes: 9, isoproturon; b, monuron; [, fenuron; *, monolinuron; n ) 2. Data were fitted with a logistic function.
can be used to determine the affinity between the antibody and an antigen by plotting the slopes normalized to the slope of a blank (pure antibody solution) versus the concentration of antigen in a titration curve (see Figure 4). After injection of the antibodies, the transducer surface is regenerated with a 150-s pulse of HCl followed by a 10-s pulse of acetonitrile/water/propionic acid and washed for 3 min. Polyclonal antibodies consist of a distribution of species with different affinities for a given hapten. Therefore, it is not possible to determine a certain affinity for these antibodies. But the affinity distribution to a certain antigen can be seen from the titration curve. Figure 4 shows the titration of the policonal anti-isoproturon antibodies with the four analytes used for the coupling experiments. For the same concentration of antibodies, the test midpoints of the titration curves can be used as a measure for the affinities of the antibodies to the different antigens. As can be seen in the titration curves, the dynamic range covers up to 2 orders of magnitude, indicating that the antibodies exhibit a broad distribution of affinities. Such an extended dynamic range is desired for analytical purposes since it allows detection of compounds in a larger range of concentrations. Another fact can be seen in Figure 4. The binding curves show a residual slope for monuron, fenuron, and monolinuron even for high concentrations of antigen and consequently there is an offset in the titration curve, in Figure 4. The organic modifier of the mobile phase in the liquid chromatography affects the affinities of the antibodies. Effects depend on the biological system as well as on the modifier. Polyclonal anti-digoxigenin antibody Fab fragments were found be tolerate up to 30% of methanol and 10% of acetonitrile.3 Normally acetonitrile has a higher impact on affinity than methanol. The effect of methanol on the affinities of the anti-isoproturon antibodies was determined using a titration assay with 5 and 10% methanol in the buffer. The results are summarized in Table 1 using the test midpoints calculated by the fit. It can be stated that an amount of 10% methanol shifts the test midpoint ∼1/2 order of magnitude to higher concentrations. The influence of methanol on the affinity of the antibodyantigen system can also be seen from the offsets in the titration curves, indicating especially for monolinuron a significant reduc3638 Analytical Chemistry, Vol. 72, No. 15, August 1, 2000
Figure 5. RIfS binding curve of the injection of 3 µg/mL on the column,. Dotted line: UV chromatogram at 254 nm, arbitrary ordinate units.
tion in analyte binding under assay conditions, while surface binding of the antibodies still can be observed. Coupling HPLC-RIfS. Figure 2 shows the setup for the coupling experiments. A concentration of 37% methanol and a flow rate of 200 µL/min was found to be suitable for the separation of all four pesticides. The eluate was split and then mixed with the antibody solution via a T-shaped mixing union. Thus, the concentration of modifier in the antibody/eluate mixture could be adjusted by the ratio of the flow rates. The eluate was split 1:3, and the 50 µL/min flow was mixed with 200 µL/min antibody solution to reduce the amount of methanol in the mixture to 7.4%. This mixture was passed through a reaction coil to allow the reaction of the antibodies with antigens available in the eluate. After passing the reaction coil, the mixture was directed through the RIfS cell. An injection valve set directly before the cell allowed switching between antibody/eluate and fluids for a regeneration of the transducer surface. Figure 5 shows the RIfS binding curve of a coupled HPLCRIfS run. a 2-µL sample of a fenuron solution with 3 µg/mL in 37% methanol was injected on the HPLC column. In the binding curve, the time of the injection was set to zero. As can be seen from Figure 5, the optical thickness increases linear due to the mass transport limited binding of the anti-isoproturon antibodies. At ∼190 s, the binding rate decreases because of the presence of the fenuron in the column effluent which binds to and in consequence inhibits surface binding of a fraction of the antibodies. The slope of the curve returns to the initial value at ∼280, when all antigen has passed the detection cell. This can be seen from the linear extension of the initial part of the binding curve (dashed line), which runs essentially parallel to the second part
Figure 6. First derivative of the binding curve in Figure 5.
of the binding curve. An UV detector was placed before the mixing union for referencing the measurement. The UV chromatogram recorded at 254 nm is drawn as a dotted line in Figure 5. Here the fenuron peak appears from 145 to 220 s. The reduced binding rate due to the presence of antigen in the mixture can be seen more distinctly from the first derivative of the RIfS binding curve (Figure 5). The derivative was taken by applying the Savitzky-Golay method22 to reduce the influence of the signal noise on the differentiation. The first derivative starts at ∼7.3 pm/s, the initial slope of the RIfS curve in Figure 5. At 165 s, the first derivative decreases; the minimum value of 4.95 pm/s is reached at 200 s. At this point, the maximum concentration of fenuron has arrived at the measurement cell. The amount of antibodies with at least one free binding site in the peak maximum can be calculated from the ratio of the slope in the peak maximum to the slope of the pure antibody solution (the “baseline”) to be 4.95/7.3 ) 67.8%. Postcolumn reaction detection systems introduce an additional peak broadening to the HPLC peaks. The peak broadening for the described detection technique depends also on the degree of smoothing. A differentiation without smoothing leads to a peak with a full width at half-height of 34.3 s compared to 29.4 s for the UV peak. The Savitzky-Golay differentiation with a smoothing window (local polynomial regression) of nine points corresponding to 45 s increases this value to 41.3 s but decreases at the same time the rms noise in the first derivative from 0.7 to 0.05 pm/s. The additional peak broadening of the mixing union, reaction coil, and RIfS cell in terms of σ2 is 56 and 152 s2 for the direct and the smoothed derivative, respectively. The first derivative in Figure 6 shows a slight negative drift at longer retention times due to a decreasing binding rate of the RIfS curve. The reason for the decreased binding rate is the reduction of free binding sites on the transducer surface and thus an increasing influence of reaction kinetics on the binding. This corresponds to a continuous deviation from a pure to partial mass transport limited binding. The effect is a slight, but clear continuous baseline drift in the “RIfS chromatogram“. A HPLC separation of all four examined pesticides coupled to RIfS is given in Figure 7, which contains the RIfS binding curve, its first derivative, and the signals from the UV detector. In the (22) Savitzky, G.; Golay; M. J. E. Anal. Chem. 1964, 36, 1627-38.
Figure 7. Binding curve (dashed line, left ordinate) and binding chromatogram (first derivative, solid line, right ordinate) for a separation of four pesticides: (1) fenuron 2 µg/mL; (2) monuron 2 µg/mL; (3) monolinuron 10 µg/mL; and (4) isoproturon 2 µg/mL (from left to the right). Dotted line: UV chromatogram at 254 nm, arbitrary ordinate units.
Figure 8. Binding curve (dashed line, left ordinate) and binding chromatogram (first derivative, solid line, right ordinate) for a separation of four pesticides. Peaks from left to the right: (1) DMF, (2) fenuron 1 µg/mL; (3) simazine 10 µg/mL; (4) atrazine 10 µg/mL; and (5) isoproturon 0.5 µg/mL (not separated). Dotted line: UV chromatogram at 254 nm, arbitrary ordinate units.
UV chromatogram, the monolinuron peak exceeds the dynamic range of the detector due to a high response factor and a 5-fold higher concentration. In contrast, the monolinuron “RIfS peak“ is the smallest corresponding well to the lowest affinity of the antibody to the substance. The opposite is true for isoproturon, a weak UV signal but a high response in the RIfS chromatogram. The aim of the demonstrated approach is a selective detection of substances depending on their affinity to the applied affinity protein. Substances that are not recognized by the affinity protein should not lead to a signal. This was confirmed by the injection of a mixture of two pesticides that were known to bind to the antibodies and of two pesticides with a completely different structure. Figure 8 shows the separation of fenuron, simazine, atrazine, and isoproturon. In the RIfS chromatogram, it can be seen clearly that only fenuron and isoproturon are detected by the antibodies while simazine and atrazine do not change the RIfS signal. One finds from the UV chromatogram that atrazine and isoproturon are not baseline separated. In contrast to this, the RIfS peak of isoproturon is not affected despite the 20-fold higher concentration of atrazine. Analytical Chemistry, Vol. 72, No. 15, August 1, 2000
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Table 2. Limits of Detection for the Four Pesticides
isoproturon monuron fenuron monolinuron
Figure 9. Peak heights versus concentration for (9) isoproturon and (2) monolinuron; n ) 3.
Quantitative Evaluation of the RIfS Chromatograms. As mentioned above, the slope of the binding curves shows a negative drift for higher loadings of the transducer with protein due to a deviation of the pure mass transport limited process. Therefore, for the evaluation of the RIfS chromatograms, a procedure similar to the normalization in the titrations assays was chosen. The first derivative of a binding curve was normalized to a baseline reconstructed from a second-order polynomial fit to all parts of the curve that do not contain a peak. Before integration, the resulting curves were subtracted from 1 to obtain positive peaks which could be integrated numerically by chromatography software. The obtained values reflect the fraction of inhibited antibodies in the peak maximum. A total inhibition would give a calculated peak height of 1.0. In Figure 9 , the peak heights are plotted versus the injected concentrations for isoproturon and monolinuron. The responses exhibit saturation characteristics, comparable to the shape of the titration curves. This can be explained by the limited amount of antibodies used for detection. It can be seen from Figure 9 that the response of the detection system is significantly higher for isoproturon than for monolinuron, corresponding to the binding strengths determined in the titration assays. This holds also for monuron and fenuron (data not shown in the graph); in general, the peak heights at a certain concentration are in the same succession as the test midpoints. It was shown for the titration curves that especially for solutions with organic modifier the slopes of binding curves do not reach zero even at high concentrations of antigen. This in turn means for the peak heights that the maximum values reachable are lower than 1.0. Another reason for a deviation of the maximum peak height from 1.0 is that the antibody-antigen mixture may be not in equilibrium when reaching the measurement cell. This aspect is discussed in the paragraph Parameters Determining the Performance. Finally, the smoothing algorithm leads to broader peaks with a decreased height, which also limits the maximum reachable peak height. While the peak heights are determined by the maximum concentration of antigen in the eluted peak, the total amount of antigen in the eluate is reflected by the peak area. These areas plotted versus the concentration show the same saturation curve as was found for the peak heights. In contrast to the peak heights, the peak areas are less influenced by the smoothing algorithm, 3640 Analytical Chemistry, Vol. 72, No. 15, August 1, 2000
injected concn (µg/mL)
absolute amt of substance (fmol)
0.06 0.09 0.12 0.8
75 105 165 930
because a higher degree of smoothing leads to smaller peak heights but increases at the same time the peak widths. Therefore, the difference of the peak area of a not-smoothed peak to the area of a peak smoothed in the described way is 1%. Limits of Detection. To determine the limits of detection, baseline noise levels were calculated from binding curves normalized as described above without pesticide eluting from the HPLC. The noise was calculated as the standard deviation of these baseline parts and values between 0.004 and 0.008 were found, depending on the number of measurements and regeneration procedures performed with the transducer. Limits of detection were calculated with 3σ (of the highest noise value of 0.008) using the sensitivities derived from the linear parts of the Figure 9 plot. The calculated limits of detection are given in Table 2. For the absolute amounts of substance, the split ratio of 1:3 after the HPLC column was taken into account by dividing the amount of substance present in the injection volume by the factor 4. The limits of detection are in the same order of magnitude as was found for a bioassay coupled to HPLC using labeled antidigoxigenin antibody fragments3 at a concentration of 1.3 nM. Parameters Determining the Performance. The performance of the whole system is determined by several parameters. In the following paragraph, these parameters are discussed according to their appearance in the setup as shown in Figure 2. The first component of the whole system is the separation part. The influence of the organic modifier on the affinities was described above. These effects depend on the biological system as well as on the concentration and nature of the solvent. They can be estimated using the titration assay, which allows the selection of the best solvent for both the separation and the biochemical detection system. Isocratic separationsas used in this studyswill allows one to run postcolumn detection under constant conditions. If gradient techniques are required, their effect on the assay must be carefully determined. The subsequent parts in the setup are the mixing union and the reaction coil. It is clear that an efficient mixing of the flows is the basis for the reaction. The length of the reaction coil determines the reaction time but also has an effect on the peak broadening. It was shown before1 that due to the high reproducibility of the flows in the chromatographic system it is not mandatory that the mixture has reached equilibrium concentrations when it passes the detector. The optimum between extended peak broadening and higher responses at (near) equilibrium conditions depends on the kinetics of the affinity system. The next parameter to be optimized is the concentration of antibodies or affinity proteins mixed with the eluate. A higher concentration of antibodies gives higher slopes of the binding curves and thus improves the S/N ratio of the first derivative but reduces the responses of the antigens on the amount of free species. The binding rate of the antibodies to the surface is also
influenced by the flow rate in the flow cell. An increase of the flow rate decreases the dimension of the diffusion layer at the transducer surface and thus moderately (cube root of the flow rate) increases the binding rate.23 The dimension of the applied RIfS cell limits the total flow to ∼500 µL/min. The concentration of affinity proteins is also limited by the maximum binding capacity of the transducer, which depends on the surface modification. A maximum binding capacity of 15-25 ng/mm2 is typically for amino dextran surfaces, corresponding to changes of optical thickness of 15-25 nm. The heterogeneous assay format requires the regeneration of the transducer surface after measuring a binding curve. The high density of binding sites makes the regeneration more difficult since antibodies that were cleaved from the immobilized partner can bind again to the surface with a high probability. For bivalent affinity proteins like the antibodies used in the presented work, a cleavage from the surface is much harder because they will bind with two binding sites, which have both to be cleaved at the same time. For this reason, considerably more drastic regeneration conditions were necessary. We found that these regeneration conditions decreased the S/N ratio in the first derivatives for repeatedly used transducers. A FFT analysis of data calculated without smoothing found that the main part was from the pulse of the HPLC pump, which could be only slightly reduced by an additional column between pump and separation column. A major improvement of the S/N ratio was obtained by the smoothing algorithm, which on the other hand broadened the peaks as described above. The algorithm of the differentiation is the last parameter of the whole system which determines the performance of the detection system. Depending on the S/N ratios, the best amount of smoothing has to be found which decreases the noise as much as necessary and increases the width of the peaks as little as possible.
CONCLUSION We demonstrated a new approach for the label-free detection of a bioassay coupled on-line with HPLC. This method could be of particular interest in screening fields where the activity of substances may be influenced by coupling of fluorescence or enzyme labels. The limits of detection reached in this basic work are comparable to a biochemical detection method using fluorescence-labeled antibodies.2 There are several systems for label-free detection of bioassays commercially available which are based on techniques using an evanescent field to detect the binding to the transducer by changes in the refractive index in the vicinity of the transducer surface, e.g., BIACore, IASys, ASI, and IBIS. Due to this principle of detection, the signal is strongly influenced by changes in the refractive index of the solution caused by fluctuations in the temperature or flow buffer composition. In contrast to the methods detecting with an evanescent field, the signal in RIfS is less influenced by the bulk refractive index and thus less sensitive to changes of temperature and composition of flow buffer, which especially qualifies the technique for a coupling with liquid chromatography. The detection of small molecules with a label-free detection system in a direct assay format is still a challenge and demonstrated only for special systems. But the coupling of HPLC with a label-free detection using immobilized affinity protein would be very attractive. It requires the immobilization of highly purified proteins to ensure high densities of binding sites. A recent trend in separation techniques is the miniaturization of the liquid chromatography systems to reduce analysis times, analyte consumption, and amount of waste. Due to the small area necessary for detection (i.d. of optic fiber, 1 mm), the described detection method is suitable to be coupled with miniaturized chromatography systems, reducing also the consumption of affinity proteins.
(23) Glaser, R. W. Anal. Biochem.1993, 213, 152-61.
AC991157G
Received for review October 6, 1999. Accepted April 13, 2000.
Analytical Chemistry, Vol. 72, No. 15, August 1, 2000
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