2338
Anal. Chem. l W l , 63, 2338-2345
(18) Oeborne, B. G.; Feam, T. J . Fwd Techno/. 1983, 18, 453. (17) She&, J. S.; Westehus, M. 0.;Templeton, W. C., Jr. Crop Scl. 1985, 25, 158. (18) chase, D. B. Appl. Spectrosc. 1984. 38(4),491, (18) Carter, R. O.,111: Lindsay, N. E.; Beduhn. D. Appl. Spectrosc. 1990, 44 (7),1147. (20) Fuller, M. P.; Rltter, 0. L.; Draper, C. S. Appl. Spectrosc. 1988, 42 (3).217 and 228. (21) Llndberg, W.; Persson. J. A.; Wold, S. Anal. Chem. 1983, 55, 643. (22) Cahn. F.; Compton. s. Appl. Spectrosc. 1988, 42. 865. (23) Frederlcks, P. M.; Lee, J. B.; Osborn, P. R.; Swinkels, D. A. Appl. Spectrosc. 1985, 39,303 and 311.
(24)Thomas, E. V.; kaland, D. M. Anal. Chem. 1990, 62 (lo),1091.
RECEIVED for review April 2, 1991. Accepted July 19, 1991. This work was performed in part at Sandia National Laboratories supported by the U. S. Dept. of Energy under Contract No. DE-AC04-76-DP00789 and by Semiconductor Research Corp*/SEMATECH through the University of New Mexico SEMATECH Center of Excellence.
Integrated Fluid Handling System for Biomolecular Interaction AnaIysis Stefan Sjolander a n d Csaba Urbaniczky*
Pharmacia Biosensor AB, Building F 61-1,S-751 82 Uppsala, Sweden
injection analysis might provide problems when conventional An Integrated fluid handling system used for muitlchannei bulk detectors are used (5). But with a surface-sensitive biomolecular interaction analysis is d e r c r W . Reactions detection method the sensitivity and detection limit are imbetween blologkai molecules are monltored In real time by proved by miniaturization, as will be shown in this paper. measuring changes In the angular porltlon where surface In the system described here, the biomolecular interaction plasmon resonance occurs at a biospectflc active surface. takes place on the biospecific active surface, which serves as The adsorptbn dfklency of the analyte onto the M o ~ c l f l c one of the walls in a thin-layer cell. This surface has such actlve surface Is up to =3%, due to the low channel height, properties that the adsorbed mass on it can be probed with 50 pm, In the flow cell. When a large part of the total blothe SPR technique when a part of it is illuminated from the rpedlic~emfaceformf~plermon~probln(l opposite side (2).For direct immunological sensing with SPR, (=0.15 m")b used, the sensttlvlty Ir hlgh. Sample dres In the thin-layer cell is used to transfer the analyte in the sample the order of 1-50 pL can be injected. The sample zone onto the sensing surface with a known mass-transfer rate and dkpembn b mhdmked by the low dead volume in the system efficiency. The mass-transfer characteristics for a thin-layer (=0.4 pL) a c w q H W d by udng lntwated sample bops and cell are well-known since that behavior is as for an electrothin conduits. An asset of thls integration is the low reagent chemical thin-layer cell when the active surface behaves as consumption. The sensor chlp wlth the blospeclflc actlve an infinite drain and the reaction proceeds with infinite resurface Is reusable and easily exchanged. Experimental reaction rate (6-8). An analytical solution for the mass-transfer suits obtalned with a theophyllh monoclonal antibody as the equation was given by Matauda. It is valid when the diffusion analyte are compared wtlh a theoretical model. The standard layer thickness next to the biospecific active surface is sufdeviation for the repeatablltty k =5 % typkaHy wlth 50 pL of ficiently thin relative to the channel height in the thin-layer 250 pM analyte, and the a m y t h e Is 10 mln. The detectlon cell (9). Some of the constrains in the boundary conditions were relaxed in a mathematical solution given by Weber and limit Is 4 0 pg of the analyte on the probed spot of the surPurdy (10)by using semiempirical constants. A mathematical face. P d b k hprovements of the sensitivity and detectlon solution consisting of power series was later given by Mollimit are dlscusmd.
INTRODUCTION With surface plasmon resonance (SPR) the kinetics for biomolecular interactions between, for instance, an antigen and an antibody can be followed directly without labeling (I). The SPR response is sensitive to changes in refractive index in the probed volume. The change in refractive index is proportional to changes in mass concentration. Since many biochemically active molecules have high molecular weight, samles with low concentrations of such analytes can be detected in situ with SPR (2). The penetration depth is so thin that the probed volume will be referred to as a probed area when it can not be misunderstood. The flow injection analysis technique (3) is suitable for reproducing qualitative and quantitative measurements with rapid response time. Sample and reagent volumes can be minimized by integrating and miniaturizing sample loops, valves, and conduits in a system. In addition, enhanced repeatability is achieved (4).Miniaturization as such with flow 0003-2700/91/0363-2338$02.50/0
doveanu and Anderson (1l) as well as by Roosendaal and Poppe (12).Some controversy about the validity of the formulas has been settled (6, 13). If low detection limit is the primary goal, the thin-layer cell should be designed to enable transfer of the analyte in the sample onto the sensing surface with (ultimately) 100% adsorption efficiency. Low detection limit is also easier achieved by using low flow rate. However, for kinetic studies a high mass-transfer rate is advantageous. If the mass-transfer rate is much higher than the heterogeneous reaction rate, then diffusion/convection terms in the mathematical model can be neglected. The reaction model is then simplified to include an ordinary differential equation instead of a partial differential equation. When the reaction rate of the antigen-antibody has a finite rate (in the same order as the mass-transfer constant) only numerical simulation methods are available (14, 15). Flow simulation is more common in electrochemistry (1617)and that approach is also valid for adsorption studies. Higher maas transfer of the analyte to the surface (by for instance higher flow rate) leads to a thinner diffusion layer, and thus, a lower relative amount of the analyte in the sample is adsorbed onto 0 1991 American Chemical Soclety
ANALYTICAL CHEMISTRY, VOL. 83, NO. 20, OCTOBER 15, 1991
the surface. So there is an inherent contradiction between the high mass-transfer rate of the analyte to the surface and high relative adsorption efficiency of the analyte. Literature reviews on antigen-antibody binding (18) and protein adsorption on solid-fluid interface (19,20) with reaction models and rates are available. There is also an interest in the study of kinetics in affinity chromatography; see for instance ref 21. Most of the results concerning chemical reactions obtained with affinity chromatographyare applicable on experiments as performed here, where a flow passes over a plane surface coated with a thin layer of adsorbate, and detected with the SPR technique. Many methods are used to study protein adsorption. The most common method is to measure the amount of radiolabeled protein adsorbed onto surfaces. The advantage of this method is the possibility to use any kind of surface, however it is not a real-time method. The major disadvantage is that radioactive material must be handled. Measurement with ellipsometry gives the same kind of information as with the SPR detection technique (22). Direct measurement of adsorption kinetics of proteins onto surfaces in continuous well-defined flow systems is not common, for which the herein described system is well suited. Gendreau used internal reflectance infrared spectrometry to study protein interaction in real-time with germanium surfaces in a flow cell (23). Van Wagenen et al. used internal reflectance fluorometry to study albumin adsorption onto quartz (24). Also, Beissinger and Leonard used internal reflectance fluorometry for study of adsorption of y-globulin onto quartz (14). They found that the kinetic step was rate determining in the adsorption process. Cheng et al. studied adsorption of albumin on six polymers by using internal reflectance fluorometry (25). They found that the heterogeneous adsorption rate constants for albumin reacting with three polymers are greater than 5.0 pm s-l while the rates are 1.5 pm s-l and 73 nm s-l for the two kinetic limited reactions. The desorption rate constants are small in all these cases. Eddowes has in general terms discussed the fundamental chemical limitations for a direct immunochemical sensing detector (26,27). The aim of this study is to determine how the detection limit for the analyte depends on the described micro fluid handling system as well as to identify important factors that influence the performance of the SPR instrument. Further, ways to optimize assay time and sensitivity are shown. The repeatability for assays are determined with a model system: anti-theophylline monoclonal antibody is the analyte in the sample and interacts with a theophylline-modifiedbiospecific active surface. In addition, the range in which the heterogeneous and homogenous rate constants can be determined will be characterized.
THEORY First we introduce a very useful time-related parameter for the thin-layer cell. The time taken for a given analyte in a sample volume to pass along the biospecific active surface is l / u , while the time for it to diffuse across the channel is -h2/D. (See Table I for a list of variables). Hence, the time for the analyte to travel along the channel related to the time to diffuse across it is the unitless time relation:
= Dl/uh2 (1) This reduced time, T,, was introduced by Weber and Purdy and defined in a slightly different way (10). The variables in eq 1 are macroscopic and can be determined independently. As will be shown, T~ is a very important constant describing the behavior of a thin-layer cell. It is helpful to make a classification of adsorption kinetics in a fluid system depending on the magnitude of the rate constants. Mathematically the convective diffusion system T,
2399
Table I. List of Variables Used area for the biospecific active surface (m2) channel width (m) concentration (mol m-3) diffusion coefficient (m*s) f volumetric flow rate (m3s-l) h channel height (m) j , flux of the analyte to the unit area for the biospecific active surface (mol m-2 s-l) J flux of the analyte to the biospecific active surface (mol 8-l) relative flux of the analyte to the biospecific active surface Jr homogeneous association rate constant (mol-' m3 9-l) ka kad heterogeneous adsorption rate constant (m 8-l) homogeneous dissociation rate constant (8-l) kd kde heterogeneous desorption rate constant (s-l) 1 length for the biospecific active surface (m) ml mass transfer coefficient (m 8-l) total mass of the analyte in the sample (kg) m0 n refractive index for the probed volume na specific refractive index for the analyte n b specific refractive index for the bulk solution time (s) t U linear flow rate (m 8-l) va volume of the analyte adsorbed onto the probed volume at the biospecific active surface (m3) volume of the bulk solution probed at the biospecific active ub surface (m3) distance across the channel (m) Y r surface concentration (mol m") r m maximum surface concentration (mol m-2) a beginning of the probed spot on the biospecific active surface (m) P end of the probed spot on the biospecific active surface (m) density for the analyte (kg m-3) Pn reduced time T. A b C D
is described by a partial differential equation, as shown in depth by Levich (28). In this case, the boundary condition at the biospecific active surface is
This boundary condition states that the rate for surface concentration change is proportional to the diffusion rate. Also, that the diffusion rate is proportional to the heterogeneous reaction rate. At equilibrium (aI'/at = 0) this heterogeneous reaction rate expression can be rearranged to give the Langmuir isotherm. The relation between the heterogeneous and the homogeneous rate constants for an ordinary homogeneous bimolecular reaction is kad = k , r , and kde = k d , respectively. It is assumed that no adsorption occurs on the other surfaces than on the biospecific active one. If the mass-transfer rate is much less than the heterogeneous reaction rate, then the overall adsorption rate is mass transfer limited. In the case when the surface behaves like an infinite sink and the reaction rate is infinite, the surface concentration is always zero from a mathematical point of view. If we also assume that it is a steady-state condition, aC/at = 0, and the flow rate is linear (instead of parabolic), then there is an analytical solution to this problem. This case was solved by Matsuda for a similar electrochemicalproblem (9). He showed that the total flux, J , of the analyte to the active surface is
J = 1.47(DA/h)2/3Cp/3= 1.47C(Dlb/h)2/3(ubh)1/3 = 1.47Cb(DZ)2/3(u/h)1/3 (3) If this relation is normalized with the amount of the analyte flowing into the channel (Cf = Cbhu) then a relative flux, J,, or adsorption efficiency is obtained:
J , = J / ( C b h u ) = 1 . 4 7 ( 0 1 / ~ h ~=) ~1 ./ 4~7 ~ > / ~(4)
& 4 can be larger than unity, and thus obviously it is not valid
2840
ANALYTICAL CHEMISTRY, VOL.
63,NO. 20, OCTOBER 15, 1991
for all 7rsince J , must be an unitless number between 0 and 1. Elbicke et al. (6) showed that eq 4 is valid when 7 , < 0.2 (corresponding to a relative flux efficiency of 50% ). The flux, j , to the surface at a given position, 1, measured from the front end of the biospecific active surface is obtained by differentiating eq 3 with respect to the active surface area:
j l = dJ/dA = (2/3)1.47CD2/3(u/hl)1/3
A
d
(5)
The mass-transfer coefficient, m,, is the flux to the surface a t a given position, 1, along the biospecific active surface: ml = j r / C = (2/3)1.47D2/3(u/hl)1/3 = 0.98D2/3(u/h1)1/3
(6) This mass-transfer coefficient has the same units as the heterogeneous adsorption reaction rate constant, and their magnitudes can be directly compared. When 7, > 2 the relative adsorption efficiency is almost 100% (IO). The equation describing the relative adsorption efficiency in the transit region from 50% to almost 100% was derived by Moldoveanu and Anderson (11). An alternative expression was derived by Rossendaal and Poppe (12). So far we have only discussed the mass transfer of the analyte to the biospecific active surface and reaction rates that result in a certain surface concentration of the analyte on the biospecific active surface. We shall now consider the refractive index change that the protein adsorption causes, which is observed as a measurable SPR response. Here, the SPR response is defined as the angular position where the reflectance intensity curve is a t a minimum. Stenberg et al. have quantified the correlation between surface concentration of protein on the biospecific active surface and SPR response with radiolabeled proteins (2). Here a method will be derived to simply estimate the refractive index change that the adsorbed protein causes. It is based on the fact that for an ideal solution the refractive index is an additative relationship that depends on the specific refractivity and the partial specific volume. The biospecific active surface is actually three-dimensional, i.e. a volume (2). In the model derived here it is assumed that the adsorbate is evenly distributed within this volume probed by the evanescent wave (which is caused by the illumination from the opposite side). Thus, the probed bulk volume, Ub, that influences the refractive index is given by the indirectly illuminated part of the biospecific active surface area and the penetration depth for the evanescent wave. The probed analyte volume, u,, is the volume of the analyte (from the sample volume) that is adsorbed onto (or absorbed into) the same surface area. Then the refractive index for the entire probed volume is
n = nb[l
- u,/(u, + Ub)] + naua/(ua + ub)
(7)
If we are only interested in small responses, we can simplify eq 7 by assuming that u, is much less than Ub. Then we obtain
n = nb(1 - ua/ub)
+ naU,/Ub
(8)
and the refractive index change (measured as the change in SPR response) in thus
An = n - nb = (n,- flb)u,/Ub
(9)
But only a part of the biospecific active surface is probed. Measured from the beginning of the biospecific active surface, a is the beginning and 6 is the end of the indirectly illuminated part of it and (Y < /3 < 1. If the mass transfer is the rate-limiting step, then the volume of the analyte adsorbed on this probed spot is ua
=
(Jr,8
- Jr,a)ms/Pa
(10)
B
Fbm 1.
Outlet Inlet
--
Schematic view of the optical system. (A) Side view where the attenuated light is shown as a dark band. (8)Top view, which schematically shows the three channels of the flow cell projected onto the detector. The other components are described in the text.
where pa is the density for the analyte. The change in refractive index response a t the probed spot is thus (11) An = (J,,a - Jr,a)(na - nb)ms/(P&b) This equation will be correlated with experimental data for the change in SPR response.
EXPERIMENTAL SECTION Apparatus. The SPR instrumentation consists of a pump (pLC-500, ISCO Inc., Lincoln, NB), an autoinjector (Gilson 231-401, Villiers le Bel, France), an optical measuring unit, 16 pneumatic valves (SBX, Parker Pneutronics, Papperell, MA) in an external box, a measuring computer (Motorola Inc., Phoenix AZ), and a computer on which the user application program is run (HP310, Hewlett Packard Corp., Fort Collins, CO). A schematic diagram of the optical measuring unit is shown in Figure 1A. It consists of a light source with corresponding optics, a glass prism and a detector array with imaging optics. The light source (a) is a high-output light-emittingdiode (Hitachi HPIAORA, Hitachi Ltd., Tokyo, Japan),with wavelength 760 nm and bandwidth 15 nm. A divergent beam from the light-emitting diode is collimated and focused (b) on the glass-gold interface through the prism (e, glass quality BK 7, Hoya Corp., Tokyo, Japan). The measurable angular range is from 65 to 71'. The reflected beams of light from the prism are collimated and projected onto the photodetector array (g, Reticon RA 1662N, EG&G Reticon, Sunnyvale,CA). This detector has 16 rows with 62 pixels per row. Polarization is achieved by a film polarizer (f, HN32, Polaroid, Norwood, MA). The optical layout produces a wedge-shaped beam of light hitting the glass-gold interface, which enables the use of multichannel monitoring (Figure 1B). The optical unit together with a sensor chip (c) and an integrated micro fluidic cartridge (d) forms the integrated fluid handling system; see details below. The measuring computer is a VME card cage with a Motorola MVME 101card computer. The VME card cage is also equipped with a detector interface card made in house. The detector reading is performed as follows: the microprocessor in the measuring computer is interrupted every 82 ps and the next pixel in a row is clocked out and fed to an analog to digital converter (Crystal CS 5016-JN32,Crystal Semiconductor Corp., Austin, TX) that has 16-bits resolution. The converted digital value is stored in the memory. When all pixels in a row have been converted, the next row is selected and the pixels are clocked out in order and converted. This is a repetitive process, and all pixels in the photodetector are converted in 82 ms. Eight separate values for each pixel in the photodetector are stored in the measuring computer memory, and the rolling mean value of these is calculated. The time taken to convert all pixels in the detector eight
ANALYTICAL CHEMISTRY, VOL. 63, NO. 20, OCTOBER 15, 1991
A
2341
B 35000
I
30000 ? 225000-
2
H 20000
c
d 0
MembraneValve
o Inlet or Outlet 0
15000
-
10000
-
Connecting pipe
Figure 2. Schematic view of the fluid-handling system with integrated channels. (A) Side view demonstrating the function of the layers with pressurized air inlet (a), flow inlet (b), plate 1 (c), pneumatic connection layer (d), plate 2 (e), membrane layer (f), fluid connection layer (g), plate 3 (h), flow channel layer (i), and a sensor chip (j). (B) Top view with waste outlet (a), pump inlet (b), sample inlet (c), sample waste (d), three sample channels (e), 45-pL loop extension (f), and 5-pL loop (9).
times is ~ 7 0 ms, 0 which is of the form of a digital time constant. When the program that runs on the HP310 computer asks for the values for a certain detector array row, the program on the measuring computer sends the mean values for that row. It takes 430 ms to transfer the 62 values belonging to a row between the computers. The SPR effect is observed as a dark band in the reflected light from the gold surface (2). The reflected light with this band is projected onto the rows in the detector and is seen as a reflected intensity curve with a minimum. The SPR angle is the position for the minimum in this reflected intensity curve. It is estimated by fitting a second degree polynomial to the values for three pixels closest to the minimum. Then the position for the minimum is calculated from the polynomial. The integrated micro fluidic cartridge is made from three molded polystyrene plastic plates (52 X 52 X 1.5 mm). The upper plastic plate with ridge patterns is ultrasonically welded to the middle plate (Figure2A). Thereby, a pneumatic connection layer is created between external pneumatic solenoid valves through multichannel tubing and the integrated valves. The middle plate has holes through it down to the molded soft silicone rubber layer beneath it, thereby forming flexible membrane valves (0.d. = 0.5 mm). The lowest plate has molded hard silicone rubber layers on both sides. The membrane layer is yulcanized with the upper layer of hard silicone rubber, hence forming the fluid connection layer. Stainless steel capillary tubing is connected directly to this fluid connection layer. The carrier stream is lead through holes in the lowest plate to the fluid channel layer, which forms the sample flow channels when facing the sensor chip. The fluid connection layer has an integrated 5-pL loop with a 45-pL extension that are used either as a 5- or as a 50-pL sample loops (Figure 2B). The fluid channel layer has three channels where channel 1 is closest to the inlet. This construction needs 11external valves to control the flow through the three channels and the two loops. Each channel is 1.6 mm long, 300 pm wide, and 50 pm high. The biospecific active area in a channel is 0.48 mm2 and the illuminated SPR probing spot is estimated to be 0.5 0.1 mm long located in the center of the channel; thus the spot area is -0.15 mm2. The geometric dead volume from the loop to the inlet of channel 1 is 0.33 pL and increases to 0.43 p L for channel 3. The sensor chip, a gold-coated glass slide (see details below), is placed onto the prism base with the chemically modified gold layer (the biospecific active surface) facing upward. Optical contact between the prism and this sensor chip is achieved by a refractive index matching fluid (bis(2-hydroxyethyl)sulfide, n = 1.520, Fluka, puriss). The flow cell is placed onto the sensor chip and tightened by a spring. Reagents. All water used was deionized and further purified with a Millipore Milli-Q filtration system. The biospecific active surface is described in detail by Loftis and Johnsson (29). In short, the sensor chips were made in the
*
-
0
5
; 0
1'5
io
Angle [A U ]
Figure 3. Reflected intensity curve for a pixel row in the detector before (---) and after (-) linear normalization. The light intensity levels used in the normalization procedure are shown by the two horizontal dotted lines. The position of the curve minimum is the SPR response.
following way. A 0.3 mm thick glass slide (glass quality BK 7, Hoya Corp., Tokyo, Japan) (12 X 12 mm) was coated with 47-nm gold in a sputtering system (MRC 903, Material Research Corp., Orangeburg,NY). The gold layer was coated spontaneouslywith a monolayer of 16-mereapto-1-hexadecanolfollowed by covalently coupling of a dextran (T500, Pharmacia, Uppsala, Sweden) hydrogel, and thereafter carboxymethyl groups were introduced. Finally, 8-(3-aminopropy1)theophylline(a theophylline analogue) was covalently bound to these groups. The theophylline monoclonal antibody was obtained from Pharmacia Diagnostics, Uppsala, Sweden (batch 459). A stock solution of 23.6 mg mL-' was prepared and stored in a refrigerator. Aliquots of this stock solution were diluted and used in the experiments. The carrier used was a saline buffer: 150 mM NaCl (Merck, pro analysi), 10 mM HEPES (Merck),pH 7.4, and 50 ppm Tween 20 (Surfact-Amps, Pierce). The pH was adjusted with NaOH (May and Baker, reagent grade). The biospecific active surface was regenerated before each sample injection (i.e. forced desorption of the adsorbate) by injecting between 5 and 50 pL of 100 mM NaOH sample solution. The refractive index calibration of the SPR monitor was performed by measuring a series of sucrose (Fluka, for microbiology) solutions with known refractive indices (30). The temperature was 22 i 2 "C.
RESULTS The response for the system was characterized by injecting samples with known refractive indices. The transport of the sample plugs through the channel were monitored by collecting the reflected intensity curves as a function of time after each injection. Delay times, dead volumes and dispersion of the sample plug in the channels of the flow cell were characterized this way. Detector and Sensor Chip Normalization. First the noise in the reflected intensity curve was determined, i.e. the intensity variation as function of time for each pixel in the detector array. The standard deviation for the noise is 4-9 levels for each pixel in a row when retrieved from the measuring computer. Therefore, at least 81 intensity curves must be collected to minimize this random noise to one level. Besides this random noise, each pixel in the detector diode array was found to have a different light intensity response. This variation in the reflected light intensity response was linearly normalized by collecting 100 intensity curves a t two different light intensities with total reflection from the sensor chip (Figure 3). These light intensities were obtained by changing the LED current and were selected so that the light intensity responses were below and above the intensity values for the reflectance minimum in a typical curve. The smoothing effect due to the normalization is demonstrated in Figure 3. Every sensor chip was normalized.
2342
5 -10
ANALYTICAL CHEMISTRY, VOL. 83, NO. 20, OCTOBER 15, 1991
0
10
20
Time [SI
30
40
I
50
Flgure 4. Difference in SPR response as a function of time with different sample injection techniques. First a 5-pL sample volume was injected from the large loop by opening the injection valves for 33.3 s using the cutoff technique for the sample injection (- -). The same volume was injected by using the internal small loop (-). The sample was 9% sucrose in the HEPES buffer used as carrier, and the linear low rate was 10 mm s-'.
-
Valve Switching. The valve-switching time depends on the air pressure and the flow rate. The valves can withstand a maximum air pressure of ~ 3 0 kPa. 0 But the air pressure must be above ~ 2 0 0kPa to avoid leakage so a pressure of 250-260 kPa was used throughout this investigation. The valve switches faster with increasing air pressure. With the air pressure used here, the total valve-switching time (including mechanical switch delay) is ~ 3 0 ms 0 when the flow rate is 7.5 pL s-l. The uncertainty in time when the valve opens is less than 80 ms when the linear flow rate is 7.5 p L 5-l. This uncertainty increases to -500 ms when the flow rate decreases to 0.15 pL s-l. This time variation influences the assay repeatibility as will be discussed below. The uncertainty when the valve is closing is much less. System Dead Volume. Like all other flow systems, this fluid handling system has also a dead volume. It was estimated by measuring the delay from when an injection occurs until a noticeable SPR response is observed. Duplicate injections were made for each channel at six different flow rates. From the lowest flow rates used, the dead volume was estimated to be =0.21,0.24, and 0.26 p L for the channels. These values are smaller than the expected geometrical ones: 0.33, 0.38, and 0.43 pL, respectively. Tailing of the Sample Injection. Large tailing of the sample plug occurs when a loop is emptied. It is possible to inject a sample volume in two ways. Samples are either injected from the 5-pL loop or the same volume is injected from the larger loop by closing the injection loop after a selected time, a cutoff technique (Figure 4). The loop influences the degree of tailing, which increases with flow rate. So, sample injections with the cutoff technique have the following advantages. First, a shorter analysis time is achieved since it takes a longer time to wash out the last traces of the sample in the loop. Second, a more well-defined sample injection plug is obtained since the tailing of the plug, which is less reproducible, is avoided. This improves the reproducibility of quantitative determinations as well as the determination of desorption rate constants. Finally, it is not necessary to calibrate the loop volume since it is known from the flow rate and by accurate timing of the sample injection duration. Throughout these experiments, 150 r L of the sample solution was used to flush and fill the sample loops with the autoinjector. Repeatability of the Refractive Index Response. The SPR response difference (Ap, in unitless interpolated distance between pixels) was calibrated by measuring the SPR response for the sucrose samples with known refractive index (An,
unitless or with refractive index units, RIU). The response for this instrument is linear when Ap < 1,and the relation between refractive index response and pixel distance is An Ap. This factor is used when the results are = 8.3 X presented as refractive index responses. During a single sweep up to lo00 data points are collected. A sweep time of 80 s was used in the following experiments, and the sample was injected after an initial delay of 35 s. The background SPR response is the mean response during the fmt 35 s prior to the injection, while the sample SPR response is the mean response during the last 35 s, and the change in response, ASPR, is the difference between the sample and the background SPR response. The standard deviation for the noise level is in the range from 2 to 5 pRIU for the background SPR response. The uncertainty increases slightly with the magnitude of the response for the sample; however the relative error decreases. With five repetitive injections, the relative standard deviation is less than 1% when the response is larger than 150 pRIU. These experiments where repeated in the three channels and with two sensor chips. The total error increases when channels and sensor chips are varied; however, there is no significant difference. In these cases, a sucrose sample with a response to 19.3 mRIU has a relative standard deviation of 1.2%. The flow rate was also varied in separate experiments: no influence on the refractive index response was found with the investigated flow rate range from 10 to 500 mm s-l. The theoretical reflected light intensity as a function of the incident angle is known, and thus the systematic error in estimating the position of the angle minimum by using the algorithm used can be calculated. This error is less than ~ 2 % of the distance between two adjacent pixels or -16 pRIU when expressed as refractive index error. Detection Limit as Mass on the Probed Spot for the Refractive Index Samples. The standard deviation for the response for injections of the buffer solution (blank experiments) between channels and sensor chips is 12 pRIU. So the detection limit is -40 pRIU for samples with a refractive index response. However, the standard deviation for repetitive injections with a solution with refractive index difference lower than 1 mRIU is typically 2-3 pRIU when a single channel is used. The penetration depth is calculated to be -300 nm (2). With an illuminated spot area of 0.15 mm2,this corresponds to a probed volume, ub, of 45 pL. The refractive index for pure protein is ~ 1 . 6 RIU, 0 and thus An 0.27 RIU relative to the buffer solution. By use of eq 9 and with the refractive index response set to 40 pRIU, a minimum detectable analyte volume, u., of =7 fL is obtained. Calculated from the partial molar volume (31),the density for protein in solution is 1.36 kg L-l. Hence the estimated minimum detectable analyte mass on the probed spot is -10 pg, as determined from these refractive index response measurements. Characterization with Theophylline Antibody. The 0 molecular weight for theophylline antibody is ~ 1 6000. Therefrom the diffusion coefficient is estimated to be -4 X lo-" m2s-l; and this f w e is used in the following calculations. The lowest flow rate used in this investigation is 10 mm 5-l. With this flow rate, the relative flux is 3% onto the biospecific active surface. To apply a 50-pL sample takes more than 5 min. Flow rates lower than this would increase the relative flux further; however, the assay time then becomes impractically long. Due to the adsorption of the analyte, the SPR response increases until the sample plug has passed the probed spot (Figure 51, and this recording is called a sensorgram. The difference between an adsorption process and a plain refractive index response as seen in a sensorgram is obvious by comparing Figures 4 and 5.
ANALYTICAL CHEMISTRY, VOL. 63, NO. 20, OCTOBER 15, 1991
2343
3.
E 2.
1,
-.
-100
Time Is]
Dlfference in SPR response as a function of time with a 130 nM theophyllhreantibody sample. The cutoff technique for the sample injection was used and the injection valves were open for 33.3 s, corresponding to a volume of 5 pL. The linear flow rate was 10 mm Flgm 5.
S-1.
I
0.04
C I m
loo
200
300 400 Linear Flow Rate [mm s '1
500
I
600
Flgun 6. Difference in SPR response as a function of sweep rate with a 13 nM theophylline antlbody sample. The sample volume was 20 pL. Duplicate injections were made at each sweep rate in channel 1 (o),2 (A), and 3 (0)when the first sensor chip was used and in channel 1 (O), 2 (V),and 3 (0)when the second sensor chip, was used. The solid line is the theoretical response according to eq 11.
The maximum linear flow rate used here, 500 mm s-l, was set by the fastest possible sampling time, 80 ms, for the computer program. I t corresponds to a mass-transfer rate of 220 pm s-l and a t this flow rate the relative flux decreases to 0.2%. The biospecific active surface was regenerated before each sample injection. Preliminary tests showed that the regeneration of the surface is fast, even 1 pL of 100 mM NaOH seemed to be sufficient. In these experiments, a fixed time of 30 s was used to regenerate the surface. Depending on the flow rate, between 5 and 50 pL of 100 mM NaOH was in contact with the surface. Studies of the refractive index responses of sucrose samples suggested that sample injection with the cutoff technique is superior to using a loop with a fixed volume. This was checked by applying 10 injections with 5 p L of 13 nM theophylline antibody. The results confirmed that the sample injection with the cutoff technique has better repeatability 1.2% versus 2.0% for the fixed loop technique. The capacity of the biospecific active surface did not change due to the regeneration. By variation of the flow rate the validity of eq 11 for a mass-transfer-limited reaction was checked. Duplicate injections were made at six different flow rates between 10 and 500 mm s-l, repeated in each channel and by using two different sensor chips. The results are shown in Figure 6, which reveals that the major difference in the results is due to
0
roo
zoo
Time [SI
360
460
560
m e 7. Dlfference In SPR response as a function of t h e with a 250 pM theophylline antibody sample demonstrating the detection limit. The sample volume was 50 pL, and the cutoff technique was not used for
the sample injection. The linear flow rate was 10 mm s-'.
differences between channels. The ASPR response is highest in channel 3,and it is close to the theoretically expected one. Thus the heterogeneous adsorption rate constant is much larger than 20 pm s-l, the maximum mass-transfer rate. These results show that the responses can be predicted with eq 11. To verify the conclusions above concerning the detection limit, 10 repetitive injections of 50 p L of 250 pM anti-theophylline antibody were performed. The total assay time was less then 10 min, including the time required for the regeneration of the biospecific active surface between the sample injections. One of the sensorgrams is shown in Figure 7. The step response noticed directly as the sample is injected varied between the injections. It is probably due to a temperature difference between the sample and the carrier stream. Theoretically, the sample injection duration is 333 s and the sample tailing is noticed as the sample bulk solution is replaced with the carrier stream, compare with Figure 4. The mean ASPR response obtained was 103 pRIU with a relative standard deviation of 5%. This corresponds to 14 pg of the analyte on the probed spot. The theoretical expected ASPR response was 62 pRIU. In this case the experimental ASPR response was higher than the theoretically expected one. These results also show that the nonspecific adsorption is not large in this case (due to the presence of Tween 20). DISCUSSION The normalization of the reflectance intensity curve is necessary mainly due to the response differences for the pixels in the detector array. This normalization procedure decreases the overall error significantly. I t also compensates for imhomogeneities and thickness variations in the different layers of the sensor chip. The injection of samples with known refractive index is useful for identification of system malfunction. The reproducibility of the valve switching time can also be checked in this way. Although the repeatability of the valve switching time is better a t higher flow rate, the relative precision diminishes. When the flow rate is 0.15 p L s-', a 0.5s uncertainty corresponds to a volume variation of 75 nL. Thus, if the volume repeatibility has to be better than 1 % , then sample volumes larger than 7.5 pL must be used. At the highest flow rate used in this investigation, the relative error due to the uncertainty in the valve switching time is 2.4% when the sample volume is 25 pL. The observed dead volume is always less than the calculated geometrical one. This might be due to the fact that the flow velocity in the channel center is higher than the mean one and a response is earlier noticed. Tight tolerances for the silicone rubber layers are necessary in the manufacturing of the integrated micro fluidic cartridge.
2344
ANALYTICAL CHEMISTRY, VOL.
63,NO. 20, OCTOBER 15, 1991
Valve switching time depends on the air pressure and the flow rate. A too thin silicone rubber layer produces a delayed opening while a too thick layer requires too high an air pressure to avoid leakage. The responses for blank injections are zero or positive in this investigation, probably due to temperature differences between the sample and the carrier stream. In a well-thermostated system this error would decrease. Assay methods where the response is measured after the plug has passed the probed spot are less sensitive for temperature differences between the sample and the carrier stream. However, this kind of method requires a longer assay time compared with methods where the slope is measured and should therefore only be used when a low detection limit is the main concern. In these experiments, the loop was flushed and filled with 150 p L of the sample. Good results can be obtained with smaller sample volumes. Even partially filled loops can be used. A way to increase the sample turn around time is to inject the sample and reagent solutions directly into the channel instead of via a loop. Thereby, the flow cell washing time would also decrease, especially when solutions for the surface regeneration are injected, as well as when secondary reagents are used in an amplification step. The loop contamination would certainly decrease, since these reagents would never pass through the loop. Procedures where the samples with the analyte are injected directly into the detection channel without using a loop, have two advantages. The total sample volume needed would decrease as well as the nonspecific adsorption of the analyte before the biospecific active surface. It is very important to minimize nonspecific adsorption, since the surface area is so large compared with the amount of the analyte. The disadvantages with direct injection of the sample into the detection channel are also 2-fold. It is harder to thermostat the sample, and the flow rate for the sample injecting pump must be as precise as for the carrier stream pump. The integrated micro fluidic cartridge has such a low dead volume that any attempt to use segmented flows will only introduce larger dispersion; the Taylor time for this system is in the range 10*10-2 (32). The sample dispersion is mainly controlled by convection (called stage 2 by Betteridge (33)). In the calculation of the expected ASPR response, assumptions are made. Since the reduced time is much less than 0.2 in this investigation, the assumption made to derive eq 3 is valid (6, 13). The relative surface concentration is less than 2%, so the biospecific active surface behaves almost like an infinite sink. The ASPR response depends on four uncertain parameters. First, the diffusion coefficients for proteins are hard to determine and therefore uncertain due to, for instance, the amount of sugar residuals left on the protein. Second, the silicone rubber is soft, and therefore the cell height depends on the force applied by the spring. It is also hard to measure the cell height. It seems like the cell height in channel 3 is lower than in the other two channels (Figure 6). The third and probably the largest error source is in the determination of the size and the position of the probed spot. Each one of these parameters may vary &lo% or more. Considering this, the fit shown in Figure 6 between the calculated and the measured ASPR response is good. That a reaction rate is mass transfer limited is easily verified by varying the flow rate. If the slope on the sensorgram is proportional to u1I3then the reaction is mass transfer limited. On the other hand, if the slope is constant then the reaction is kinetically limited and only the surface adsorption rate process described by a ordinary differential equation must be considered, eq 2. The corresponding rule when the ASPR response is measured is as follows. If the ASPR response is proportional to d3, then the reaction is mass transfer limited
(Figure 6),while if the ASPR response is proportional to d, then the reaction is kinetically limited. In the intermediate range the rate constants must be determined numerically. The maximum reaction rate that can be determined is dependent on the maximum mass-transfer rate for the system. The ultimate hardware limitation is when turbulent flow is obtained, i.e. when the Reynolds number is more than 1500. With the channel dimensions used in this investigation, it should correspond to a linear flow rate of =15 m s-l. However, here the sampling rate of the computer is too slow to enable such a high flow rate and the highest possible linear flow rate to use is 0.5 m s-l. This corresponds to a maximum masstransfer rate of =20 pm s-l, which determines the upper limit for the measurable kinetic rate constant. With a detedor using moving parts, it is hard to obtain high sampling rates (34). Best results for quantitative assays are obtained in a masstransfer-limited region since kinetically limited reactions are less reproducible than mass-transfer-limited reactions. Possible improvements of the detection limit and the sensitivity will be discussed. The reflectance intensity curve is detector noise limited. However, the primary data acquisition from the detector diode array performed by the measurement computer can be further optimized so that 16 times more samples are collected during the same time interval. Thereby, the signal to noise ratio would be 4 times better. Also the normalization of the sensor chip could be done 16 times faster. There is a cyclic systematic error between 0 and 2% of the distance between two adjacent pixels. (But it is not the limiting factor for the results presented here. It is easy to introduce a correction for this systematic error.) By using a detector with more pixels in a row, this systematic error would decrease. The position for the minimum in the reflected intensity curve can also be estimated with functions having smaller systematic errors than the polynomial used. However, the other algorithms require more time to calculate the position of the minimum in the intensity curve. Two other error sources are due to the detector: the physical distance between the pixels in a row varies as well as the measurement center for each pixel. The adsorption efficiency of the flow cell can be optimized in the following three ways. First, the relative flux can be improved by diminishing the channel height. The lower limit is determined by the following considerations: (1)The flow cell must be practical to manufacture. (2) The cell line must be practical to use, for instance not too easily clogged by impure samples. This also means that the cell must be designed with uniform channel cross sections. We believe that a channel height below 10 gm is impractical in routine applications. Secondly, the sensitivity can be increased by illuminating the whole biospecific active surface, especially at the front of it where the mass-transfer rate is highest. This can be done for instance by sputtering gold as a thin strip, wide as the illuminated spot size and located in the channel center. Thereby eq 11 becomes Further, both J,and ub depend on the length of the biospecific active surface area. It can be shown that in theory it is advantageous to decrease the length as much as possible since the probed volume is linearly dependent on the length of the biospecific active surface area. However, imperfectionson the surface then become more significant. Therefore, we believe that biospecific active surface lengths less than 0.5 mm are impractical in routine applications. For this specific cell, by probing at the front of the biospecific active surface, the sensitivity would increase at most ~ 1 4 0 % .When the biospecific active surface is smaller than the illuminated spot size, the stray light increases due to total reflection. So, in practice
ANALYTICAL CHEMISTRY, VOL. 63, NO. 20, OCTOBER 15, 1991
it is important to match the size of the biospecific active surface with the illuminated spot size. The third way to increase the adsorption efficiency is by increasing the reduced time, T,. By decreasing the flow rate until the reduced time starta to reach unity, the relative flux efficiency increases to almost 100%. Thereafter, further decreases in flow rate have an insignificant effect on the ASPR response. Besides optimizing the adsorption efficiency, two ways remain to improve the sensitivity. The first one is to increase the m, term. This can be accomplished by injecting secondary reagents in a follow-up amplification step. The second and last way to increase the ASPR response is to increase the (n, - nb) difference by using secondary reagents with high refractive indicies. Ultimately, it is the temperature dependence for the carrier stream that determines the detection limit for an assay using the SPR detection technique. The temperature dependence for water is -100 ctRIU/OC. For example, a variation of 0.001 OC corresponds to an uncertainity of 0.1 pg of analyte on the biospecific active surface in this instrument. By thermostating the carrier stream and/or using a reference channel, some of the temperature variation can be further minimized. The instrument here was not thermostated actively. However, the optical unit was housed in a large air-filled compartment without any major heat source. CONCLUSIONS A highly efficient flow injection analysis system is obtained by incorporating the sample loop with the microconduits for biomolecular interaction analysis. The sample dispersion is mainly controlled by convection. The SPR detection technique with integrated fluid handling system as described here offers a number of advantages over conventional techniques for biomolecular interaction analysis. First, data are collected in real time with 80-ms resolution. Second, the rate constants and adsorption isotherms can be determined under wellcontrolled mass-transfer conditions. Third, it is possible to study the factors affecting biospecific interaction such as temperature, buffer properties (pH, activity) as well as other interfering species in the sample. Finally, biomolecules are not labeled and thereby their physicochemical and biochemical properties are preserved. In theory, it is possible to perform micro (pico) affinity chromatographic separation with this system since the analyte can be detected, desorbed, and collected. This can be done quantitatively when the reduced time is 1 or larger. Assuming sufficiently large equilibrium constants for the system studied, we conclude that the detection limit for a well-designed system employing the SPR detection technique is ultimately determined by temperature fluctuations. ACKNOWLEDGMENT Many at Pharmacia Biosensor AB have contributed to this work: K. Johansen has helped with fast and accurate elec-
2345
tronic design besides valuable comments. B. Ivarsson and L. Eriksson have been valuable discussion partners about detection limit improvements. The preliminary investigations on the theophylline system were performed by M. Gadnell and L. Mattson. C. Johansson and E. Stenberg have helped with the manuscript. Registry No. Theophylline, 58-55-9.
LITERATURE CITED
(29) (30) (31) (32) (33) (34)
Liedberg, 6.; Nylander, C.; Lundstrom, I. Sens. Actuators 1983, 4 , 299-304. Stenberg, E.; Persson, B.; Roos, H.; Llrbanlczky, C. J. CokW Interface Sci. 1991, 143, 513-526. ; New York, Rhzlcka, J.; Hansen, E. H. Flow Injection A M / J ~ sWUey: 1987; pp 247-256. Rhzicka. J.; Hansen, E. H. Anal. Chim. Acta 1984, 161, 1-25. van der Linden, W. E. Trends Anal. Chem. 1987, 6 , 37-40. Elbicki, J. M.; Morgan, D. M.; Weber, S. G. Anal. Chem. 1984, 56, 978-985. Stuik, K.; PadkovB, V. ElectmanaljlicalMeesvements In Fbwing U quids; Ellls Horwood: Chlchester, England; 1987. Compton, R. G.; Unwin, P. R. J. Electroanel. Chem. InterfacialElectrochem. 1986, 205. 1-20. Matsuda, H. J . Electroanal. Chem. Interfacial Electrochem. 1987, 15. 325-336. Weber, S. G.; Purdy, W. C. Anal. Chim. Acta 1978, 100, 531-544. Moldoveanu, S.; Anderson J. L. J . Electroanal. Chem. Interfacial Electrochem. 1984. 175, 67-77. Roosendaal, E. M. M.; Poppe, H. Anal. Chim. Acta 1984, 156, 323-333. Weber, S. G. J . Ektroanal. Chem. Interfacial Electrochem. 1983, 145, 1-7. Beissinger, R. L.; Leonard, E. F. ASAIO J . 1980, 3 , 160-175. Lok, 6. K.; Cheng, Y.I.; Robertson, C. R. J . Colbid Interface Scl. 1883. 97, 104-116. Flanagan, J. 8.; Marcoux, L. J . Phys. Chem. 1974, 78, 718-723. Anderson, J. L.: Moldoveanu, S. J . Electroanal. Chem. Interfacial Electrod”. 1984, 179, 107-117. Absolom, D. R.; van Oss, C. J. CRC Crit. Rev. Immunol. 1986, 6 , 1-46. Norde, W. A&. Colbid Interface Sci. 1988, 25, 267-340. Andrade, J. D., Ed. Proteln Adsorption; Surface and Interfacial Aspects of Blomedlcel Polymers; Plenum: New York, 1986; Vol. 2. Chalken, I . M.. Ed. Analjllaal Afflnky Chromatograph; CRC Press: Boca Raton, FL, 1987. Corsel, J. W.; Wlllems, G. M.; Kop, J. M. M.; Cuypers, P. A.; Hermens, W.Th. J . Colbid Interface Sci. 1988. 11 1 , 544-554. Gendreau, R. M.; Lelninger, R. I.; Winters, S.; Jakobsen, R. J. In Bkmretedals: Interfacialphenomenaand Applkations; Cooper, S. L., Peppas, N. A., Eds.; ACS Advances in Chemlstry Serles; Amerlcan Chemical Society: Washington, DC, 1982; Vol. 199, pp 371-394. Van Wagenen, R. A,; Zdasiuk, 6. J.; Andrade, J. D. Org. Coat. &st. Chem. 1980, 42, 749-753. Cheng, Y. L.; Seth, A. D.; Robertson, C. R. J . Colbid Interface Scl. 1987, 118, 212-223. 1889, 26, 152-154. EddOwSS, M. J. AMI. ROC. Eddowes, M. J. Biosensors 1987, 3, 1-15. ; Prentlce-Hall: En&Levich. V. 0.Physiochemical HydfWnamics .~ wood ciiffs, NJ, i g 6 z L o f k S.; Johnsson, B. J . Chem. SOC., Chem. Commun. 1990, 1526-1528. Kokhoff, 1. M.; Sandell. E. 6.; Meehan, E. J.; Bruckensteln, S. Ouenlltatlve Chemical Analysis, 4th ed.; Macmillan: New York, 1969 p 1007. handbook of Bbchemlstry;CRC-Press: Cleveland, OH, 1973; p CIO. Vandersllce, J. T.; Rosenfeld, A. G.; Beecher. G. R. Anal. Chim. Acta 1988, 179, 119-129. Betterage, D. Anal. Chem. 1978, 50, 832-845A. Kooyman, R. P. H.; Lenferink, A. T. M.; Eenink, R. G.; Greve, J. Anal. Chem. 1891, 63.83-85.
RECEIVED for review April 15, 1991. Accepted July 16,1991.
