Conductometric Monitoring of ProteinâProtein Interactions - American

Article pubs.acs.org/jpr

Conductometric Monitoring of Protein−Protein Interactions Rosanna Spera,‡ Fernanda Festa,§ Nicola L. Bragazzi,‡ Eugenia Pechkova,†,‡ Joshua LaBaer,§ and Claudio Nicolini*,†,‡,§ †

Nanoworld Institute, Fondazione EL.B.A. Nicolini, Largo Redaelli 7, 24020, Pradalunga, Bergamo, Italy Laboratories of Biophysics and Nanobiotechnology, Department of Experimental Medicine, University of Genova, Via Pastore 3, 16132, Genova, Italy § Virginia G. Piper Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, Arizona 85287, United States ‡

ABSTRACT: Conductometric monitoring of protein−protein and protein−sterol interactions is here proved feasible by coupling quartz crystal microbalance with dissipation monitoring (QCM_D) to nucleic acid programmable protein arrays (NAPPA). The conductance curves measured in NAPPA microarrays printed on quartz surface allowed the identification of binding events between the immobilized proteins and the query. NAPPA allows the immobilization on the quartz surface of a wide range of proteins and can be easily adapted to generate innumerous types of biosensors. Indeed multiple proteins on the same quartz crystal have been tested and envisaged proving the possibility of analyzing the same array for several distinct interactions. Two examples of NAPPA-based conductometer applications with clinical relevance are presented herein, the interaction between the transcription factors Jun and ATF2 and the interaction between Cytochrome P540scc and cholesterol. KEYWORDS: conductometer, nucleic acid programmable protein array, quartz crystal microbalance with dissipation monitoring, cell free expression system

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INTRODUCTION Protein arrays are rapidly becoming established as a powerful platform to investigate protein interactions and functions. They made possible the parallel multiplex screening of thousands of interactions, encompassing protein-antibody, protein−protein, protein−ligand or protein−small molecules, enzyme−substrate screening and multianalyte diagnostic assays.1 Moreover, protein arrays are increasingly generating interest at the biotechnology levels, especially when coupled to label-free detecting techniques that do not require the use of reporter elements (fluorescent, luminescent, radiometric, or colorimetric) to facilitate measurements. Label-free techniques can provide direct and straightforward information on analyte binding to query molecules typically in the form of mass change (addition or depletion) from the surface of a sensor substrate2,3 or via changes in a physical bulk property of a sample.4,5 We created a new conductometric biosensor in which the sensitive biological elements are engineered proteins expressed in vitro in a self-assembling protein microarray, using NAPPA technology.6 NAPPA technique relies on the production of © XXXX American Chemical Society

proteins directly on the microarray surface using a cell-free in vitro transcription/translation (IVTT) system7,8 (Figure 1a). The use of a human-based IVTT system has proven particularly advantageous since it allows the expression of human proteins using human machinery and chaperones, increasing the likelihood of proper folding and post-translational modifications. NAPPA, successfully coupled with the human IVTT system, became the first high-density protein microarray to display human proteins expressed in human milieu.9 Typically, more than 2000 unique features can be spotted in a single glass slides,7 or more than 8000 features in nanowells.10 The design of NAPPA has been directed to overcome the limitations of traditional protein microarray technologies. Among the advantages of NAPPA it is possible to include the following: minimal manipulation of the proteins; protein repertoire (cDNA is used as a template for the protein expression, and the availability of comprehensive cDNA Received: May 10, 2013

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dx.doi.org/10.1021/pr400445v | J. Proteome Res. XXXX, XXX, XXX−XXX

Journal of Proteome Research

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Figure 1. Quartz crystal microbalance with dissipation monitoring (QCM_D) coupled to nucleic acid programmable protein arrays (NAPPA). (a) Schematic representation of NAPPA technology. In each spot a mixture of plasmid DNA, BSA and anti-GST antibodies is printed and immobilized on cysteamine coated surface. The antibody is responsible for the capture of the freshly expressed proteins that are tagged, at one of their ends, with a GST tail. The proteins are translated using an in vitro transcription−translation system (IVTT).2 (b) Nanogravimetric biosensor prototype scheme. The quartz is positioned in a flow chamber that guarantees the temperature control. Temperature and flux rate are settable trough the controllers and D factor and frequency values are visible on two displays. It is also possible to record the conductance curves (the frequency and D factor shifts) in real time (example shown on the right).6

libraries makes it possible to use virtually any cDNA sequence on the array); protein integrity; and protein stability (proteins are produced just in time for the assay). Proteins displayed on NAPPA arrays are properly folded and active. NAPPA microarray has, in fact, been successfully used for the study of protein−protein interaction;7 more than 85% of the interactions that had been demonstrated biochemically with purified proteins were detected on the array. Those interactions occur only between properly folded and active proteins, demonstrating that the proteins on the array are properly folded and active. Moreover, it is possible to measure kinase activity on the array (data not published). Our previous data shows that proteins displayed on the array can be used for functional assays up to 24 h after the protein expression. However it is important to emphasize that NAPPA arrays printed with the cDNAs of interest can be stored for more than six months. The expression of the proteins is performed just when the microarray is needed, and for this reason it is not necessary to worry about protein stability above the 24 h window. NAPPA method, naturally, has also some drawbacks, which include the following: the potential diffusion across spots; the use of tags for the protein capture, which may impair the folding and/or activity of the proteins; the presence of plasmid DNA and the capture antibody in the final protein microarray, which may increase the background; and the fact that each DNA array produces a single protein array.11 Nonetheless, NAPPA microarrays were employed in several distinct applications including functional assays to detect protein−protein interactions7 and biomarker discovery for breast cancer, 12 arthritis 13 and Pseudomonas aeruginosa infection.14 Since the proteins on the array are in principle in a native state, these arrays should allow the parallel detection of protein activity15−17 toward personalized medicine.2 These are the reasons why we pointed our attentions to NAPPA as sensing system of our recently developed biosensor.6

Employing NAPPA as sensing system, we are able to develop a large number of biosensors, simply changing the cDNAs immobilized on the sensor, without interfering with the sensing technology.3 One of the main limitations in the development of a biosensor is, in fact, that the sensing technology is still strictly dependent to the unique signal transduction properties of the sensing element and need to be suited to it. The detection technology we identified as one of the most promising is the quartz crystal microbalance with dissipation monitoring (QCM_D) is a useful analytical tool for label-free and real-time analysis of biological molecule.18 To this aim NAPPAs was spotted on standard nanogravimetry quartz crystals (NAPPA-QC). The interaction between immobilized protein and analyte was monitored by the shift in the resonance frequency, which is directly proportional to the amount of molecule immobilized according to the well-known Sauerbrey equation,18 and the contemporary variations in conductance and bandwidth, which provides fundamental information about the viscoelastic properties of the solution and, moreover, the proper biosensor response.4,18−23 The dissipation factor, D, of the crystal’s oscillation reveals the film’s viscoelasticity, and its measurement can be deduced from the bandwidth of the conductance curve, 2Γ. It was demonstrated,19 in fact, that the dissipation factor of the quartz could be calculated by the following simple equation: D = 2Γ/f

(1) 19

where f is the peak frequency value. In the analysis of our results we introduced a further parameter, the “normalized D factor”, DN, defined as follows:3,6

D N = 2Γ/Gmax

(2)

where Gmax is the maximum conductance of the conductance curve. DN is more strictly related to the curve shape, respect D, and takes into account the conductance variation. Our previous results3,6 demonstrated that the use of QCM_D as a conductometric device gives reliable results and allows further B



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oscillation. The QCM_D software, QCMAgic-Q5.3.256 (Elbatech srl, Marciana − LI, Italy) works in two different modes (not simultaneously): the first allows to acquire the conductance curve, and the second allows to acquire simultaneously the frequency and dissipation factor variation versus time. Moreover, the software measured also the normalized D factor. In order to have a stable control of the temperature, the experiments were conduced in a temperature chamber. During protein−protein interaction analysis the QC was positioned in a miniature flow-cell produced in house. The flow-cell chamber volume is 100 μL, and it is connected to a BioRad Econo Gradient Pump, able to pump solution in a flux range of 0.02−6 mL/min. Microarrays were produced on standard nanogravimetry quartz used as highly sensitive transducers. The QC expressing proteins consisted of 9.5 MHz, AT-cut quartz crystal of 14 mm blank diameter and 7.5 mm electrode diameter, produced by ICM (Oklahoma City, OK, USA). The electrode material was 100 Å Cr and 1000 Å Au, and the quartz was embedded into glass-like structures for easy handling.

information about the interactions between antibody−protein and protein−protein, as well as enzyme−small molecules. In most cases conductometer have been strongly associated with enzymatic studies, where the ionic strength, and consequently the conductivity, of a solution between two electrodes changes as a result of an enzymatic reaction.24−26 Although conductometric sensing has not been as extensively implemented as it could be,27 there are examples of successful development of these devices for practical application, such as drug detection in human urine and pollutant detection in environmental testing.25,28 Even though QCM_D appears to be a promising tool to study protein−protein interactions as well as protein− membrane29 and nanoparticle−membrane dynamics,30 relatively few efforts have been made to adapt QCM_D to the study of protein−protein interactions.20,31−36 To the best of our knowledge, we coupled for the first time QCM_D with NAPPA technology for biomedical applications6 and for personalized medicine.2 To highlight the extreme versatility of our conductometric biosensor, we analyzed not only protein−protein interactions but also protein−small molecule interactions with potentially useful clinical applications. Moreover multiple proteins on the same QC have been tested, proving the possibility of analyzing multiprotein interactions. As proof of principle, applications with clinical relevance are presented herein, the interaction between the transcription factors Jun and ATF2 and the interaction between Cytochrome P540scc and cholesterol. Jun−ATF2 heterodimers are important for many cellular and neoplastic processes.37,38 Cytochrome P450scc is a mitochondrial enzyme that catalyzes the cholesterol side chain cleavage reaction after the hydroxilations at C22 and at C20, the initial and key step in the regulation of steroid hormone biosynthesis and steroidogenesis.39−42 Cholesterol sensing and monitoring has a great clinical value and importance, since the association between elevated plasma levels of cholesterol and cardiovascular diseases is well-known. The response to cholesterol was measured and compared against traditional technologies,40,43 which employes potentiometric and/or amperometric biosensor (signal is measured as the potential difference, or the current intensity, between two electrodes; the signal depends on the concentration of the analyte in solution).

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NAPPA-QC

In Spera et al.,3 we presented our preliminary results concerning an earlier version of our NAPPA based biosensor; 16 NAPPA spots of 300 μm diameter were spotted on the QC surface, and the functional proteins were synthesized in situ using a T7-coupled rabbit reticulocyte lysate as an in vitro transcription−translation (IVTT) system. In Nicolini et al.,6 as proof of principle of biosensor response to protein−protein interaction, we tested the interaction between p53 proteins immobilized on the NAPPA (after its expression) with a MDM2 solution.44 The preliminary results presented3,6 had demonstrated how our prototype of NAPPA based biosensor gave a valid response to the protein−protein and drug enzyme interaction. Moreover we verified the high selectivity and sensitivity of our biosensor. Here we present the results obtained employing a further improved version of the biosensor for the analysis of protein−protein and protein−small molecule interactions. The NAPPA-QC arrays were printed with 100 spots per QC, to enhance the sensitivity. As IVTT system we used a human lysate, which guaranteed a higher protein yield with respect to the rabbit reticulocyte lysate employed in the preliminary experiments.9 Moreover, the QCM_D software has been updated and improved, allowing the acquisition of the conductance curves at higher resolution (namely, the frequency acquisition interval has been shortened from 120 down to 1 Hz). Quartzes’ gold surfaces were coated with cysteamine to allow the immobilization of the NAPPA printing mix. Briefly, quartzes were washed three times with ethanol, dried with Argon and incubated overnight at 4 °C with 2 mM cysteamine. Quartzes were then washed three times with ethanol to remove any unbound cysteamine and dried with argon. Plasmid DNA coding for GST tagged proteins were transformed into Escherichia coli, and DNA were purified using the NucleoPrepII anion exchange resin (Macherey Nagel). NAPPA printing mix was prepared with 1.4 μg/μL of DNA, 3.75 μg/μL of BSA (Sigma-Aldrich), 5 mM BS3 (Pierce, Rockford, IL, USA) and 66.5 μg of polyclonal capture GST antibody (GE Healthcares). Negative controls, named master mix (hereinafter abbreviated as “MM”), were obtained replacing DNA for water in the printing mix. Samples were incubated at room temperature for

MATERIALS AND METHODS

QCM_D Conductometer

The QCM_D instrument was developed from a basic patent on QCM biosensor (world patent WO9602830A1 published in 2004 by Nicolini Claudio, Sartore Marco, Troitzky Vladimir and Adami Manuela) and resulted on a pending application (patent UIBMGE2012A000080) specific for protein−protein interaction study based on QCM_D, Anodic Pourus Allumina and NAPPA (deposited in 7 October 2012 by Nicolini Claudio, Bragazzi Nicola, Spera Rosanna and Pechkova Eugenia). The quartz was connected to an RF gain-phase detector (Analog Devices, Inc., Norwood, MA, USA) and was driven by a precision DDS (Analog Devices, Inc., Norwood, MA, USA) around its resonance frequency, thus acquiring a conductance versus frequency curve (“conductance curve”) which shows a typical Gaussian behavior. The conductance curve peak was at the actual resonance frequency, while the shape of the curve indicated how damped the oscillation was, i.e., how the viscoelastic effects of the surrounding layers affected the C



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Figure 2. NAPPA expression for the individual CDK2 (left), P53 (middle) and combined P53 and CDK2 genes (right) on each individual quartz. The blue curves were acquired before the expression of NAPPA, while the red curves were acquired after the protein expression/capture and washing process. The curves have been centered to their maximum frequency to better visualize the changing in bandwidths and maximum of conductance.

response to ATF2 on both NAPPA-expressed QCs. It is wellknown that the proto-oncoprotein c-Jun is a major dimerization partner of ATF2, and c-Jun−ATF2 heterodimers are important for many cellular and neoplastic processes.37,38 On the contrary, no interactions are known between ATF2 and CDK2 or p53.

1 h with agitation and then printed on the cysteamine-coated gold quartz using the Qarray II from Genetix. In order to enhance the sensitivity, each quartz was printed with 100 identical features of 300 μm diameter each, spaced by 350 μm center-to-center. The human cDNAs immobilized on the NAPPA-QC were CDK2 (Cyclin-Dependent Kinase 2), CYP11A1 (Cytochrome P450, Family 11, Subfamily A, Polypeptide 1), Jun, MLH1 (mutL homologue 1), p53, and polD1 (Polymerase (DNA Directed), Delta 1, Catalytic Subunit). The size of those proteins ranged from 61 to 150 kDa, including the 27 kDa GST tag. Gene expression was performed immediately before the assay, following the protocol described as modified from Festa et al.9 Briefly, in vitro transcription and translation were performed using HeLa lysate mix (1-Step Human Coupled IVTT Kit, Thermo Fisher Scientific, Inc.), prepared according to the manufacturers’ instructions. The quartz, connected to the nanogravimeter inside the incubator, was incubated for 1.5 h at 30 °C with 40 μL of HeLa lysate mix for proteins synthesis, and then the temperature was decreased to 15 °C for a period of 30 min to facilitate the proteins binding on the capture antibody (anti-GST). After the protein expression and capture, the quartz was removed from the instrument and washed at room temperature, in PBS for 3 times. The quartz was then placed in the flux chamber for protein−protein interaction analysis. The protocol described above was followed identically for both negative control QC (the one with only MM, i.e, all the NAPPA chemistry except the cDNA) and protein displaying QC.

Determination of Protein−Small Molecules Interactions

We analyzed the interaction between CYP11A1 and cholesterol, both in solution and in blood, to acquire information on the binding kinetics.6 After protein expression and capture CYP11A1 expressing QC was positioned in the flow chamber and exposed to a flow of a 50 μM cholesterol (Sigma-Aldrich) solution in 30% sodium cholate (Sigma-Aldrich), at 0.02 mL/ min flow rate, for 10 min at 22 °C. We used cytochrome P450scc (CYP11A1) for the detection of cholesterol (SigmaAldrich) because of its specificity. As negative control we analyzed the interaction between Clompiramine and polD1 and MLH1. MLH1 is a protein involved in DNA mismatches repair, and polD1 is a DNA polymerase. None of these proteins should interact with Clomipramine. Mathematical Model

Various kinetic models have been developed to describe protein−protein and protein−small molecules interactions. For our data, on the basis of the results of Turon and co-worker,45 we performed mathematical modeling of the protein−protein interaction, assuming saturation-like kinetics, that is to say, a quasi-steady-state condition model. For this purpose, we used the following experimental equation45 based on an exponential decay function instead of using deterministic models, focusing on frequency variation:

Determination of Protein−Protein Interactions

After protein expression and capture, the QCs were washed and used for the interaction studies as follows: QC displaying Jun was exposed to a flow of a 33 μM ATF2 (Sigma-Aldrich) solution in PBS (for flow interaction at 0.02 mL/min flow rate) for 10 min at 22 °C; alternatively 60 μL of 33 μM ATF2 solution in PBS was added on the QC surface (for static interaction) for 10 min at 22 °C. We also tested the possibility to analyze protein−protein interactions in QC displaying multiple proteins. For this aim, we coprinted cDNA for Jun&CDK2 and Jun&CDK2&p53 on a single QC, and after the expression, a mixture of these proteins was displayed on the QC surface. We analyzed the interaction

Δf = M max (1 − e−τ / t )

(3)

where Δf is the frequency variation (in Hz), Mmax is the maximum binding value in hertz (corresponding to the minimum frequency measured, or plateau value), τ is the relaxation time (expressed in reciprocal minutes), that is, the reciprocal of the enzyme protein adsorption/interaction rate, and t is the time (in minutes). The sensitivity of our NAPPA based biosensor was determined by the QC characteristics and the sensitivity of the nanogravimeter. At the moment, the minimum frequency D



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Figure 3. Matching of conductance curves of Jun expressing QC, CDK2 expressing QC and p53 expressing QC after lysate addition.

Figure 4. Conductance curves of MM QC (upper) and of CYP11A1 QC (lower). The curves were collected in different steps of NAPPA protocol, as reported in the legend, and after the addition of cholesterol. In the box the MM+CYP11A1+cholesterol conductance curves acquired with frequency acquisition steps of 1 Hz.

E



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Table 1. Main Parameters of QC-NAPPA Displaying No Proteins (MM) or CYP11A1a MM Conductance Curves baseline IVTT addition 90 min IVTT addition postcapture (30 min) postwash CYP11A1 Conductance Curves baseline IVTT addition 90 min IVTT addition postcapture (30 min) postwash MM+CYP11A1+cholesterol

f (Hz)b

Γ (Hz)b

Gmax (mS)b

D × 103 c

DN (Hz/mS)c

9497485 9493570 9493495 9493120 9489085

2422 4562 4500 4875 6255

0.432 0.370 0.390 0.378 0.046

0.51 0.96 0.95 1.03 1.32

11218 24653 23071 25814 273144

9487615 9481540 9479935 9479790 9475975 9478300

2265 4198 3984 3980 5625 6410

0.440 0.399 0.401 0.400 0.150 0.268

0.48 0.87 0.84 0.84 1.19 1.35

10286 21069 19895 19895 75050 47782

Conductance curves were collected in different steps of NAPPA protocol. bf is peak frequency, Γ is the half-width half-maximum, and Gmax is the max conductance. cD factor and DN = 2Γ/Gmax normalized D factor. a

Table 2. Shift of the Main Parameters of MM and CYP11A1 Conductance Curves after Lysate Addition and the Corresponding Mass of Immobilized Protein on the QC Surface MM Conductance Curves IVTT addition 90 min IVTT addition postcapture (30 min) CYP11A1 Conductance Curves IVTT addition 90 min IVTT addition postcapture (30 min) MM+CYP11A1+cholesterol

CV (%)a

ΔDb

ΔDN (Hz/mS)b

Δf (Hz)c

Δf ′ (Hz)c

m (μg)c

m′ (μg)c

3.3 4.1 4.0

− −0.01 0.07

− −1582 1161

−3915 −3990 −4365

− −75 −450

17.0 17.3 18.9

− 0.4 2.0

4.8 4.8 4.6 6.9

− −0.03 −0.03 0.48

− −1174 −1174 26713

−6075 −7680 −7825 −9315

− −1605 −1750 −3240

26.3 33.3 33.9 40.3

− 7.0 7.6 14

Coefficient of variation of three independent experiments. bD factor and normalized D factor shifts (ΔD and ΔDN) respect the values immediately after lysate addition cFrequency shifts respect the initial frequency (Δf) and respect the frequency immediately after lysate addition (Δf ′) and corresponding molecular masses (m and m′).

a

Figure 2 shows the conductance curves for three NAPPAQCs expressing p53, CDK2 and a mixture of p53 and CDK2 (both cDNAs were coimmobilized in each feature). The blue curves were acquired before the expression of NAPPA, while the red curves were acquired after the protein expression/ capture and washing process. The curves have been centered to their maximum frequency to better visualize the changing in bandwidths and conductance. These data pointed to a unique conductance curve shape for each protein and suggested the possibility to identify the expressed proteins by QCM-D even when combined on the same expressing QC (Figure 3). To test the possibility to acquire information on the kinetic constant of a protein−small molecule interaction, we realized a NAPPA-QC expressing CYP11A1 to be tested for cholesterol interaction as proof of principle. The P450scc-cholesterol interaction, in fact, is well characterized, and the results obtained have been satisfactorily compared with those in literature.39,46−48 In Figure 4 are reported the conductance curves for the negative control (MM) or CYP11A1 expressing NAPPA-QC arrays. The conductance curves were acquired in different steps of NAPPA expression process. In particular: before the beginning of the gene expression process (“baseline”, the QC is dry); after the addition of human IVTT lysate at 30 °C (“IVTT addition”), i.e., prior protein expression; after 90 min from the addition of human IVTT lysate, i.e., after protein expression (“90 min IVTT addition”); after 120 min from the addition of human IVTT lysate, i.e., at the end of QC

shift detectable is of 0.05 Hz that corresponds to about 0.3 ng of detected molecules.3

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RESULTS AND DISCUSSION QCM_D measures were calibrated for frequency and for D factor shifts. The frequency calibration was performed using different amounts of thaumatin. The calibration curve equation (obtained with Ordinary Least Squares methods, OLS) is Δf = −7.16 − 231.18m

(4)

with r2 = 0.9986. The D factor calibration in function of the viscosity was obtained using fructose samples at different concentrations. The calibration curve equation (obtained with OLS methods) is D = 0.831 + 0.286η

(5)

with r2 = 0.9990. For both the curves, a good correlation with the linear slope was found.3,6 We analyzed the conductance curves acquired in NAPPAQCs in different steps of the expressing and capturing process. Coefficients of variation (CV) have been computed for each conductance curve, according to the following equation:

C V = σ /μ

(6)

where σ is the standard deviation and μ the mean. F



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Figure 5. FLOW interaction CYP11A1 with HDL cholesterol in blood (upper panel) and in solution (lower panel).

incubation at 15 °C, which is the capture step (“postcapture (30 min)”); after the final washing process with PBS (“postwash”). At the end of the whole expression process, the CYP11A1 expressing QC was positioned in the flow chamber and exposed to a flow of a 50 μM cholesterol solution in 30% sodium cholate. The conductance curve “MM+CYP11A1+cholesterol” (see Figure 4b) was recorded in this condition. In Table 1 are reported the main parameters of the conductance curves of Figure 4. It is evident that the decrease in the frequency (f) is due to the human IVTT lysate addition. There is also a change in viscoelastic properties of the quartzes after the human IVTT lysate addition, leading to a measurable increase of the bandwidth (Γ). During the incubation, on the contrary, the frequency and bandwidth variations were minimal. This effect could be related to two main effects: first, merely because of the IVTT lysate addition on the QC surface, when the QC comes

in contact with a solution the frequency decreases depending upon the viscosity and the density of the solution, and there is a decrement in damping the resonant oscillation;47 and second, because of the change of the composition of both QC surface and IVTT lysate after the gene expression and the protein synthesis and immobilization. The conductance curves acquired after PBS washing evidenced the further changes of solution in contact with the QC. In Table 2 is reported the shift of the main parameters normalized against the “baseline” conductance curve and the conductance curve acquired after human IVTT lysate (“IVTT addition”). It is also reported the mass of molecules immobilized on the QC surface at the end of immobilization protocol and after the interaction with cholesterol (m), estimated through the calibration coefficients (eq 5). To estimate the amount of proteins anchored on the QC surface after the NAPPA expression, we had to account for the human IVTT lysate molecules aspecifically adsorbed on the G



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Figure 6. Conductance curves of Jun and CDK2 expressing QC (upper panel). Conductance curves of Jun, CDK2 and p53 expressing QC (lower panel). The curves were collected in different steps of NAPPA process, as reported in the legends, and after the addition of ATF2 solution.

obtained by subtracting 2 μg of molecules aspecifically adsorbed to the 7.6 μg of molecules adsorbed in correspondence of “postcapture (30 min)” curve (see Table 2), while the amount of cholesterol was 6.4 μg, obtained subtracting 5.6 μg of CYP11A1 proteins captured on the array and 2 μg of molecules aspecifically adsorbed from the 14 μg of molecules adsorbed in correspondence of “MM+CYP11A1+ cholesterol” curve. We verified (data not reported) that the exposure of the QC to sodium cholate solution affected only the bandwidth of the curve, considerably increasing the D factor, leaving the

quartz surface.3,22,48 Assuming that on each QC surface there was the same aspecific adsorption,48 we could estimate it from reference quartz conductance curves. In particular we considered the frequency shift between the reference QC conductance curves acquired immediately after the human IVTT lysate addition (“IVTT addition”) and that acquired at the end of the protein anchorage (“90 min IVTT addition”); this value is 450 Hz (see Table 1), which corresponds to 2 μg of molecules aspecifically adsorbed (see Table 2). The values of immobilized CYP11A1 molecules, therefore, was 5.6 μg, H



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Table 3. Main Parameters of QC-NAPPA Displaying Jun&CDK2a Jun&CDK2 conductance curves

f (Hz)b

Γ (Hz)b

Gmax (mS)b

D × 103 c

DN (Hz/mS)c

IVTT addition 5 min IVTT addition 15 min IVTT addition postcapture (5 min) postwash PBS-flux MM+Jun&CDK2+ATF2

9482473 9482145 9481600 9481018 9479200 9480764 9481309

3073 2945 2800 2836 2400 2909 2982

0.461 0.457 0.447 0.410 0.261 0.313 0.294

0.65 0.62 0.59 0.60 0.51 0.61 0.63

13336 12885 12528 13822 18391 18577 20284

a Conductance curves were collected in different steps of NAPPA protocol. bf is peak frequency, Γ is the half-width half-maximum, and Gmax is the max conductance. cD factor and DN = 2Γ/Gmax normalized D factor.

resonance frequency unchanged. This result also served as control to verify the stability of the biosensor. Our QCM_D instrument gave us the opportunity to monitor in real-time the trend of D factor and f. In Figure 5 we reported frequency vs time during the interaction between CYP11A1 and cholesterol, both in solution (as previously reported) and in blood. Using the eq 3 to fit this experimental data in solution (Figure 5), we obtained a K of about 100 μM, a value in good agreement with the values found in the literature (see, for example, refs 49 and 50). In the first experiments, conductance curves were acquired every 5 min (data not reported), and it was noticed that 15 min after IVTT lysate addition at 30 °C the position and shape of the curves did not change until we decreased the temperature to 15 °C. After a few minutes at 15 °C, again position and shape of the curves did not change until the washing step. Deducing from these results that the protein expression took place in the first minutes and that also their capture needed only few minutes, we decided then to perform the next experiments, reducing the expression time from 90 to 15 min (at 30 °C) and the capture time from 30 to 5 min (at 15 °C). To test the possibility to analyze multiprotein interactions, we immobilized on the same QC both Jun and CDK2 cDNAs and tested the response to ATF2 interaction. c-Jun is a partner of ATF2 in many cellular processes;38 however, no interactions are known between CDK2 and ATF2. The conductance curves of NAPPA-QC expressing Jun&CDK2 acquired in different steps of NAPPA expressing process are reported in Figure 6a. After protein expression and capture, the Jun&CDK2 expressing QC was positioned in the flow chamber and exposed to a flow of 33 μM ATF2 solution in PBS. The conductance curve “MM+Jun&CDK2+ATF2” (Figure 6a) was recorded after 3 min of flux. In Table 3 are reported the main parameters of conductance curves of Figure 6a. In Table 4 is reported the shift of the main parameters normalized against the conductance curve acquired immediately after human IVTT lysate addition (“IVTT addition”). Through eq 5 we evaluated the mass of immobilized proteins on the quartz surface at the end of capture protocol and after the interaction with ATF2 (m′). The amount of molecules captured on the QC 5 min after protein capture corresponded to about 6 μg. A further frequency decrease was recorded after the washing. This decrease was not due to further molecules capture on the QC surface but rather to the change of the solution in contact with the QC surface, since the frequency is dependent upon the viscosity and the density of the solution. This effect is mostly evident considering the shift in D and normalized D factor (see Table 4). In particular, postwash ΔDN increases about 100

Table 4. Shift of the Main Parameters of Jun&CDK2 Conductance Curves after Lysate Addition and after Protein−Protein Interaction, and Relative Mass of Immobilized Proteins on the Quartz Surface Jun&CDK2 conductance curves

CV (%)a

ΔDb

ΔDN (Hz/mS)b

Δf′ (Hz)b

m′ (μg)c

5 min IVTT addition 15 min IVTT addition postcapture (5 min) postwash PBS-flux MM +Jun&CDK2+ATF2

5.5 5.7 5.3 4.8 7.3 8.0

−0.03 −0.06 −0.06 −0.28 −0.21 −0.20

−455 −660 509 45965 11182 9644

−456 −807 −1432 −3895 −2561 −2491

2.0 3.5 6.2 17.0 −5.8d −6.1d

a

Coefficient of variation. We performed three independent experiments. bD factor, normalized D factor and frequency shifts (ΔD, ΔDN, and Δf ′) with respect the values immediately after IVTT lysate addition (see Table 3). cMass of molecules immobilized on the quartz surface for each step (calculated by eq 5). dThese values were obtained considering the frequency shifts respect “postwash” curve, since the QC was in contact with PBS solution.

times. What is meaningful is the frequency shift after QC exposure to ATF2 flux. We recorded, in fact, a frequency increase, rather than a decrease as expected. Evidently the flux, even if very gentle, caused spoliation of the QC, removing some captured molecules and making it impossible to assess the interaction between Jun and ATF2. In order to overcome the spoliation problem, the interaction between Jun and AFT2 was tested in a static way, by simply adding the ATF2 solution on the QC surface. For this experiment, QC with immobilized cDNA of Jun&CDK2&p53 were expressed for a period of 90 min and captured for 30 min. After protein expression and capture, the QC was washed with PBS and incubated for 10 min with 60 μL of 33 μM ATF2 solution in PBS. In Table 5 are reported the main parameters of conductance curves of Figure 6b, and in Table 6 is reported the shift of these parameters with respect those of the conductance curve acquired immediately after lysate human IVTT lysate addition (“IVTT addition”). The unique conductance curve shape for each of the three proteins confirms the possibility to identify the three expressed proteins by QCM_D even when combined on the same expressing QC (Figure 2). The amount of molecules captured on the QC 90 min postexpression and 30 min postcapture corresponded to about 8 μg, not much different from the 6 μg obtained in the previous experiments. Again a frequency decrease was recorded after the washing (because of PBS solution). In contrast to what previously obtained, the frequency further decreased after QC I



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Table 5. Main Parameters of QC-NAPPA Displaying Jun&CDK2&p53a Jun&CDK2&p53 conductance curves

f (Hz)b

Γ (Hz)b

Gmax (mS)b

D × 103 c

DN (Hz/mS)c

baseline IVTT addition 10 min IVTT addition 80 min IVTT addition postcapture (30 min) postwash MM+Jun&CDK2&p53+ATF2 MM+Jun&CDK2&p53+ATF2 (10 min)

9489250 9483250 9482625 9481750 9481250 9477250 9475125 9475625

2375 4625 4675 4625 4688 5375 6000 6063

0.436 0.347 0.339 0.342 0.300 0.111 0.188 0.187

0.50 0.98 0.99 0.98 0.99 1.13 1.27 1.28

10900 26629 27543 27038 31250 97262 63687 64894

The conductance curves were collected in different steps of NAPPA protocol. bf is peak frequency, Γ is the half-width half-maximum, and Gmax is the max conductance. cD factor and DN = 2Γ/Gmax normalized D factor. a

the same solution (PBS), and any changes in the frequency is due to the binding of ATF2. The amount of ATF2 molecules bound to the QC was 9.2 μg. As negative control, a NAPPA-QC coexpressing polD1 and MLH1 was tested for Clomipramine interaction. After protein expression and immobilization and after PBS washing, 60 μL of 110 μM Clomipramine solution in PBS was spotted on the polD1&MLH1 expressing QC. The conductance curve “MM+ polD1&MLH1+Clomipramine” (Figure 7) was recorded 1 min after Clomipramine solution addition. In Table 7 are reported the main parameters of conductance curves of Figure 7 and in Table 8 are reported the shifts of these parameters with respect to those of “IVTT addition” curve. The amount of molecules captured on the QC 15 min after the expression and 5 min after the capture corresponded to about 15 μg (Table 8). A frequency decrease was recorded after the washing (because of PBS solution). After Clomipramine addition, no significant frequency shift was recorded. This result confirms that no interaction occurs between polD1 or MLH1 and Clomipramine, as expected. As reported in the literature,51−53 CV values are usually very low, confirming the repeatability of the experiments and the validity and portability of the technique. In our hands, NAPPAbased QCM_D proved to have an intra-assay overall CV of 5% (range 3.3−8.0%).

Table 6. Shifts of the Main Parameters of Jun&CDK2&p53 Conductance Curves after Lysate Addition and Relative Mass of Immobilized Protein on the Quartz Surface Jun&CDK2&p53 conductance curves

CV (%)a

ΔDb

ΔDN (Hz/mS)b

Δf ′ (Hz)b

m′ (μg)c

10 min IVTT addition postexpression (80 min) postcapture (30 min) postwash MM +Jun&CDK2&p53+ATF2 MM +Jun&CDK2&p53+ATF2 (10 min)

5.4 6.0 5.5 5.2 6.5

0.01 0.00 0.01 0.15 0.29

914 409 4621 70633 37058

−625 −1500 −2000 −6000 −8125

2.7 6.5 8.7 26.2 9.2d

8.0

0.30

38265

−7625

7.1d

a

Coefficient of variation. We performed two different experiments. bD factor, normalized D factor, and frequency shifts (ΔD, ΔDN, and Δf ′) with respect the values immediately after IVTT lysate addition (see Table 5). cAmount of molecules immobilized on the QC surface (calculated through eq 5 respect the frequency recorded immediately after IVTT addition). dThese values were obtained considering the frequency shifts respect postwash curve, since the QC was in contact with PBS solution.

exposure to ATF2 flux, suggesting that the interaction between Jun and ATF2 was favored by the static process. To evaluate the amount of ATF2 bound to Jun, we considered the frequency shift between “postwash” and “MM+Jun&CDK2&p53+ATF2” curves, because in both conditions the QC was in

Figure 7. Conductance curves of polD1 and MLH1 expressing QC. The curves were collected in different steps of NAPPA process, as reported in the legend, and for polD1 and MLH1 expressing QC, after the addition of Clomipramine solution, as negative control. J



Article

Table 7. Main Parameters of polD1&MLH1 Conductance Curves Collected in Different Steps of NAPPA Expression Protocol

a

polD1&MLH1 conductance curves

f (Hz)a

Γ (Hz)a

Gmax (mS)a

D × 103 b

DN (Hz/mS)b

baseline IVTT addition 5 min IVTT addition 15 min IVTT addition postcapture (5 min) postwash MM+polD1&MLH1+Clomipramine

9486895 9486439 9486088 9485463 9483000 9484333 9484404

2860 2702 2596 2596 1509 1877 1895

0.450 0.441 0.431 0.393 0.051 0.157 0.170

0.60 0.57 0.55 0.55 0.32 0.40 0.40

12710 12254 12050 13219 58674 23892 22354

f is peak frequency, Γ is the half-width half-maximum, and Gmax is the max conductance. bD factor and DN = 2Γ/Gmax normalized D factor.

Table 8. Shifts of the Main Parameters of polD1&MLH1 Conductance Curves after Lysate Addition and after Protein−Protein Interaction, and Relative Amount of Molecules Immobilized on the Quartz Surface polD1&MLH1 conductance curves

CV (%)a

ΔDb

ΔDN (Hz/mS)b

Δf ′ (Hz)b

m′ (μg)c

5 min IVTT addition 15 min IVTT addition postcapture (5 min) postwash MM+polD1&MLH1+Clomipramine

4.8 5.3 6.0 5.2 7.1

−0.02 −0.02 −0.25 −0.17 −0.17

−204 965 46420 11638 10100

−351 −976 −3439 −2106 −2035

1.5 4.3 15.0 9.2 −0.3d

Coefficient of variation. We performed two different experiments. bD factor, normalized D factor, and frequency shifts (ΔD, ΔDN, and Δf ′) with respect the values immediately after IVTT lysate addition (see Table 7). cAmount of molecules immobilized on the QC surface (calculated through eq 5 respect the frequency recorded immediately after IVTT addition). dThese values were obtained considering the frequency shifts respect postwash curve, since the QC was in contact with PBS solution. a

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CONCLUSIONS We presented the results obtained applying our innovative conductometer,2 realized by combining NAPPA technology with QCM_D, to the characterization of protein−protein and protein−sterol interactions in a multiparametric way, taking advantage of the multiple information provided by the analysis of the conductance curves (i.e., conductance, viscoelasticity and adsorbed mass). Moreover, through our conductometer we acquired information on the kinetic constant of enzymatic interaction. Results about the sensitivity and selectivity of the original prototype have been presented in previous papers.3,6,54 The data here presented have been obtained employing a further improved version both flow and static of our conductometer. The main objective of this communication was to establish two independent proofs of principle by choosing very wellknown pairs of interacting proteins and protein−steroid: CYP11A1 and cholesterol, Jun and ATF2. An interesting implication for potential clinical applications concerned the possibility to drastically reduce the time of protein expression and capture under our experimental conditions. We noticed that 15 min after IVTT lysate addition peak frequency and bandwidth of the curves did not change; the same was true, after few minutes at 15 °C, for protein capture. We deduced from these results that the protein expression took place in the first minutes and that also their capture needed only few minutes, and we performed experiments reducing the expression time and the capture time. The results presented seem to confirm our hypothesis. The conductance curves obtained showed that protein expression and capture and protein−protein interactions were successfully performed with few exceptions. To estimate the amount of molecules aspecifically captured on the QC surface after the NAPPA expression, we employed a reference QC, and we estimated an amount of 2 μg of molecules aspecifically adsorbed. For CYP11A1 quartz, we obtained 5.6 μg of CYP11A1 and 4.4 μg of cholesterol immobilized on the quartz.

The QCM_D instrument we used allowed us to monitor in real-time the trend of D factor and f during the interaction between CYP11A1 and cholesterol, both in solution and in blood. Fitting this experimental data, we obtained a K of about 100 μM, a value in good agreement with the values found in the literature.39,55 Finally to verify the possibility to analyze simultaneously more interactions in as single NAPPA-QC, we immobilized on the same QC up to three cDNAs, successfully identified all of them, and subsequently analyzed the response to multiprotein interactions. Jun&CDK2 and Jun&CDK2&p53 coexpressed in the same QCs were indeed tested for ATF2 interaction, in flow and statically. The results revealed that the flow, even if very gentle, caused a spoliation of the QC surface, removing some captured molecules and making it impossible to assess the interaction between Jun and ATF2. On the contrary, the static process favored the interaction between Jun and ATF2. We obtained an amount of ATF2 molecules immobilized on the QC of 9.2 μg. Taken all together, we demonstrated the versatility of the NAPPA-QC biosensors for the detection of protein−protein interactions and protein−sterol interaction. Because of the simplicity in which new NAPPA-QC biosensors can be generated, we envision the use of this platform for the development of biosensors for other applications, including, but not limited to, protein−small molecules, protein−lipids, and protein−DNA.

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AUTHOR INFORMATION

Corresponding Author

*Fax and Tel.: +39-035767215. E-mail: president@ fondazioneelba-nicolini.org. Notes

The authors declare no competing financial interest. K



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ACKNOWLEDGMENTS This work was supported by FIRB Nanobiosensors (ITALNANONET RBPR05JH2P_003) of MIUR (Ministero dell’Istruzione, Università e Ricerca) to Claudio Nicolini University of Genoa, and by a grant Funzionamento by MIUR (Ministero dell’Istruzione, Università e Ricerca) to Fondazione El.B.A. Nicolini.

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ABBREVIATIONS QCM_D, quartz crystal microbalance with dissipation monitoring; NAPPA, nucleic acid programmable protein arrays; NAPPA-QC, nucleic acid programmable protein arrays printed on quartz crystal; IVTT, in vitro transcription and translation; QC, quartz crystal; CDK2, cyclin-dependent kinase 2; MLH1, MutL homologue 1, colon cancer, nonpolyposis type 2; ATF2, activating transcription factor 2; CYP11A1, cytochrome P450, family 11, subfamily A, polypeptide 1; polD1, polymerase (DNA directed), delta 1, catalytic subunit; NADPH, nicotinamide adenine dinucleotide phosphate; ACTH, corticotrophin; SF-1, steroidogenic factor type 1; AP-1, activating protein type 1 α isoform; AP-2, activating protein type 2 α isoform; DAX-1, dosage-sensitive sex reversal, adrenal hypoplasia critical region, on chromosome X, gene 1; DDS, direct digital synthesizer; BSA, bovine serum albumin; BS3, Bis[sulfosuccinimidyl] suberate; MM, master mix; MDM2, mouse double minute 2 homologue; CV, coefficients of variation

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