Article pubs.acs.org/Langmuir
Nanoscale Roughness Affects the Activity of Enzymes Adsorbed on Cluster-Assembled Titania Films Lasma Gailite,†,‡ Pasquale E. Scopelliti,§ Vimal K. Sharma,†,§ Marco Indrieri,‡,§ Alessandro Podestà,‡ Gabriella Tedeschi,§,∥ and Paolo Milani*,‡,§ †
European School of Molecular Medicine (SEMM), IFOM-IEO, Via Adamello 16, 20139 Milano, Italy Interdisciplinary Centre for Nanostructured Materials and Interfaces (CIMaINa) and Department of Physics, Università degli Studi di Milano, via Celoria 16, 20133 Milano, Italy § Fondazione Filarete, v.le Ortles 22/4, 20139 Milano, Italy ∥ Department of Veterinary Science and Public Health (DIVET), Università degli Studi di Milano, via Celoria 10, 20133 Milano, Italy ‡
S Supporting Information *
ABSTRACT: In this study, we investigated how the adsorption properties governed by the nanometer-scale surface morphology of cluster-assembled titanium oxide films influence the catalytic activity of immobilized serine-protease trypsin. We developed an activity assay for the parallel detection of physisorbed enzyme activity and mass density of the adsorbed proteins in microarray format. The method combines a microarray-based technique and advanced quantitative confocal microscopy approaches based on fluorescent labeling of enzymes and covalent labeling of active sites of surface-bound enzymes. The observed diminishing trypsin binding affinity with increasing roughness, as opposed to the steep rise in its saturation uptake, was interpreted as heterogeneous nucleation-driven adsorption of trypsin at the rough nanoporous titania surface. The increase in relative activity of adsorbed trypsin is proportional to the fractional saturation of titania surfaces, expressed as percentage of saturation uptake. In turn, the specific activity, that is, the ratio of active proteins to the absolute number of adsorbed proteins, drops with growing saturation uptake and surface roughness, witnessing a reduction in the accessibility of enzyme active sites. Both geometrical constraints of titania nanopores and the clusterwise adsorption of trypsin were identified as the key factors underpinning the steric hindrance of the immobilized enzyme. These findings are relevant for the optimization of rough nanoporous surfaces as carriers of immobilized enzymes. The proposed activity assay is particularly advantageous in the screening of candidate materials for enzyme immobilization.
1. INTRODUCTION
immobilization strategy on nanoparticles or micro- to nanoporous solid matrices as enzyme carriers.6,9 The understanding of the role of surface nanostructure in the adsorption, desorption, activity, and stability of enzymes is of outmost importance in the view of applications such as biosensors,9,10 fine-chemical synthesis, and biocatalysis.11 A considerable number of studies have been dedicated to the optimization of enzyme immobilization in order to enhance the catalysis in terms of the turnover rate, the specificity or the stability of the immobilized enzymes, as well as the reusability of the immobilized catalyst.6−8 It is therefore of particular interest to quantitatively uncover the role of nanoscale roughness in determining enzyme adsorption, as well as the functionality and activity. Here we report a systematic and quantitative characterization of the influence of nanoscale roughness on adsorption and
Topographical features of material surfaces at the nanoscale have a strong influence on protein adsorption in terms of the amount of adsorbed species, the density and the structure of adsorbed layers,1,2 and the selective localization and patterning.3 Nanostructured thin films have been extensively studied as platforms for protein adsorption for their topographical resemblance with the extracellular matrix.4,5 In the case of enzymes, it has been recognized that nanometer-scale topography favors the use of immobilization techniques alternative to covalent attachment, including entrapment and physical adsorption that allow enzyme immobilization under mild conditions and often also the simplification of immobilization procedures. Entrapment has been demonstrated as an effective approach for enzyme immobilization within porous or layered carrier matrices, such as organic polymers or silica sol−gels.6−8 Physical adsorption of enzyme molecules is facilitated by the large surface area of nanostructured materials and hence has been employed as the © 2014 American Chemical Society
Received: February 24, 2014 Revised: May 2, 2014 Published: May 2, 2014 5973
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and condense to form clusters.22,23 The mixture of clusters and inert gas is then extracted into the vacuum through a nozzle to form a seeded supersonic beam, which is collected on a set of round borosilicate glass coverslips (diameter 15 mm, thickness 0.13−0.17 mm) intercepting the beam in a deposition chamber. The clusters kinetic energy is low enough to avoid fragmentation and hence a nanostructured film is grown, leading to granular, highly porous, highspecific area material. Ns-TiOx films with different nominal thicknesses in the range 25−300 nm were simultaneously deposited onto standard round microscopy glass coverslips (thickness number 1.5, diameter 13 mm) and onto standard microarray slides (250 mm × 750 mm) (see Supporting Information for details) to apply them either for microscopy-based methods, atomic force microscopy (AFM), fluorescence recovery after photobleaching (FRAP), fluorescence photobleaching quantification (FPQ), or for microarray-based methods such as PSIM. 2.2. AFM Characterization of Surface Morphology. Surface morphology of the deposited films was probed by a Multimode atomic force microscope equipped with a Nanoscope IV controller (Veeco Instruments). AFM was operated in air in tapping mode, using single crystal silicon tips with nominal radius of curvature 5−10 nm and cantilever resonance frequency of about 300 kHz. Scan rate was 1.5−2 Hz, and scan areas 2 μm × 1 μm sampled at 2048 × 512 points. The root-mean-square roughness was calculated from flattened AFM topographs as the root-mean-square deviation of surface heights from their average value. The specific area was determined from AFM topography as the ratio of the surface area versus the projected area. Specific area is always greater than one for rough surfaces, although the finite size of the tip determines a systematic underestimation of the value of this parameter. Proteins however are as large as the AFM tip (several nm), and therefore, it can be argued that the specific area measured by AFM is the same seen by the proteins interacting with the rough ns-TiOx surfaces. According to this working hypothesis, we have normalized adsorption data by the specific area in order to take into account the “geometrical” contribution of surface morphology and highlight other more subtle morphology-related mechanisms. 2.3. Preparation of Labeled Trypsin. For adsorption and activity studies, we used methods based on the detection of fluorescently labeled proteins. Alexa-Fluor-647−trypsin conjugate was used to obtain the adsorption signal through the Cy5 channel (red). Labeling was performed in amine-free buffer according to producers’ instructions; the detailed labeling procedure is reported in the Supporting Information. 2.4. Protein−Surface Interaction Microarrays. Adsorption and activity of surface-bound enzymes were evaluated in parallel using PSIM. Slides coated with ns-TiOx gradients were prepared as described in the previous sections. Slides with four-step ns-TiOx gradients were used for the adsorbed enzyme activity detection in order to match the geometry of the 16-well slide chamber in which the incubation with the activity probe was performed. Alexa-647−trypsin was arrayed on ns-TiOx according to the protocol presented in the Supporting Information. After blocking, washing and drying, slides were mounted in the 16-well slide chamber in such a manner that each well enclosed a single 10 × 10 array. Carboxytetramethylrhodamine (TAMRA) labeled activity probe (cat #88318 ActivX TAMRA-FP Serine Hydrolase Probe from Pierce/Thermo Scientific) was then applied to each slide mounted in the 16-well chamber (details in the Supporting Information) to obtain the adsorption signal through the Cy3 channel (green). Fluorescence was detected simultaneously in Cy3 and Cy5 channels, using the excitation of 532 nm and 635 diode laser lines combined with the corresponding emission filter sets (579 and 676 nm central wavelengths with 30 nm bandwidth) of the Power Scanner (Tecan). Images were analyzed with ScanArray Express software (PerkinElmer). 2.5. Fluorescence Photobleaching Quantification. In order to calibrate the semiquantitative microarray data, PSIMs were used in combination with the fluorescence photobleaching quantification (FPQ) method. Briefly, the principle of the FPQ method relies on the use of the protein solution at known nominal protein concentration above the layer, as the calibration standard for the
functionality of enzyme adsorbed on nanostructured titania thin films (ns-TiOx, where x ≈ 2) produced by supersonic cluster beam deposition (SCBD).12 SCBD ensures a predictable and reproducible variation of nanostructured film morphology without altering the chemical composition of their surfaces.13 Cluster-assembled titania films were selected as the supports for enzyme adsorption, owing to their high protein loading capacity, and biocompatibility.14 We have demonstrated in previous works that several proteins, including streptavidin and immunoglobulin G, retain their functionality upon adsorption on ns-TiOx films; moreover, stable binding is achieved by simple physical adsorption.14 In this case, we used trypsin as model enzyme, owing to its well-studied structure and properties, its widespread application, as well as the ability to target trypsin with activity-based probes.15,16 A major drawback affecting the study of enzyme physical adsorption is the occurrence of leakage that limits the applicability of this technique on one hand, and the capability of precise estimation of the enzymatic activity, on the other hand. Standard spectrophotometric or fluorescence- and luminescence-based activity assays that rely on the detection of enzymatic reaction products fail to discriminate between the activity originating from the adsorbed enzyme and the leached enzyme.17,18 In order to estimate the contribution of leakage to the total activity signal, additional methods are necessary to accompany the standard activity assay, such as the Bradford assay or absorbance measurements aimed at the quantitative assessment of the immobilized amount of enzyme.17,18 These methods are however unsuitable to support high-throughput screening approaches thus limiting the range of enzyme concentration and different nanoscale roughness that can be explored in a single experiment. To circumvent this problem, we used an approach based on protein−surface-interaction-microarrays (PSIM) technology,19 combining the principles of material screening with the tools of activity-based protein profiling, commonly used in functional proteomics. In order to target trypsin arrayed on slide surfaces, we took the advantage of activity-based small-molecule probes for serine hydrolases, recently available on the market (further shortened to “activity probe”).20 These probes are fluorophosphonate derivatives that covalently bind to the active site serine residue of serine hydrolases in an activity-dependent manner, thus rendering the bound enzymes inactive and at the same time detectable by virtue of a fluorescent tag.15,16,21 Thanks to the covalent binding of the activity labels, PSIM is not affected by the issue of leakage. Furthermore it enables the simultaneous assessment of the surface density and the activity of immobilized enzymes with respect to a range of surface parameters of the solid substrate in a high-throughput manner. Taking benefit of the fully parallel detection method, the adsorption and the catalytic activity of physisorbed trypsin were studied in a 2 orders of magnitude wide concentration range on nanostructured titania films with six different nanotopographies.
2. EXPERIMENTAL SECTION 2.1. Fabrication of Nanostructured Titanium Oxide Films. Nanostructured titanium oxide films (ns-TiOx) were synthesized in a supersonic cluster beam deposition (SCBD) apparatus equipped with a pulsed microplasma cluster source (PMCS), as described in detail in ref 12. The PMCS operation principle is based on the ablation of a titanium rod by a helium or argon plasma jet, ignited by a pulsed electric discharge; the ablated species thermalize with helium or argon 5974
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fluorescence signal of the adsorbed protein layer itself. Details are provided in the Supporting Information. 2.6. Random Sequential Adsorption Approximation. The values of trypsin surface density were normalized by the specific surface area estimated by AFM, in order to account for the morphology-related enhancement of accessible surface of ns-TiOx. Trypsin surface density values, expressed in mass of adsorbed trypsin per unit area (μg/cm2), were then translated into monolayer units to define the relative coverage of ns-TiOx surface upon trypsin adsorption. The theoretical monolayer units of trypsin coverage were calculated taking into account the approximate dimensions of trypsin molecule given by crystallography (4.9 nm × 3.9 nm × 3.3 nm).24 The maximum relative coverage (the so-called jamming limit θ) was determined by the random sequential adsorption (RSA) model for unoriented hard rotation ellipsoids according to the equation obtained by Adamczyk et al.:25
θ = 0.304 − 0.123A + (0.365/A) where A is the ratio of the axis of the rotation ellipsoid. The weighted mean jamming limit for all three trypsin orientations was estimated as θ ≈ 0.69 and taken for the calculation of monolayer coverage. 2.7. Fitting Adsorption Isotherms. To extract quantitative information from adsorption isotherms, the Langmuir equation was fitted to data. The Langmuir model describes adsorption as reversible occupation of vacant adsorption sites on a flat homogeneous surface driven solely by the affinity between the adsorbates and the adsorption sites on the surface. The Langmuir model relates the equilibrium surface coverage ρ of adsorbent occupied by adsorbate molecules with the bulk concentration of the adsorbate, C:
ρ = Γm/(1 + kD/C) where the saturation uptake Γm signifies the maximum loading capacity of the adsorbent surface with the adsorbate molecules, while the equilibrium dissociation constant kD is inversely proportional to the effective affinity between the adsorbate and the adsorbent surface. Both saturation uptake and kD depend on the physiochemical properties of adsorbate and adsorbent; additionally, in our case, also the morphological properties of the nanostructured ns-TiOx surfaces play a role. Despite of inconsistencies with Langmuir adsorption theory, such as the irreversibility of protein adsorption and/or the occurrence of protein−protein interactions, the Langmuir equation has often been used for the representation of protein adsorption governed by more complex mechanisms for the sake of simplicity.26,27 The Langmuir model yielded good agreement with trypsin adsorption isotherms on all ns-TiOx samples: despite the remarkable exceeding of monolayer coverage at high surface roughness, the goodness of fit was marked by R2 values ranging from 0.86 to 0.98. The heterogeneous nanostructured ns-TiOx surface, as well as the multilayer adsorption of trypsin, is inconsistent with the Langmuir theory of adsorption. We retained the Langmuir formalism, however, since it described trypsin isotherms with sufficient accuracy to convey the meaning of the two Langmuir parameters to the adsorption process of trypsin on ns-TiOx. 2.8. Statistical Analysis. All results were reported as mean ± standard error (standard error of the mean in the case of AFM data) of at least three measurements. For fitting analysis of experimental data, Origin 7.5 (Origin Lab, MA) was used.
Figure 1. Surface morphology of nanostructured titania films. (A−C) Representative AFM images of ns-TiOx films with different nominal film thickness in the range from 25 to 300 nm and root-mean-square roughness from 15 to 34.0 nm. Scan size is 2000 nm × 1000 nm, vertical range is 160 nm for all images. (D) Log−log plot of the key morphological parameters of ns-TiOx versus the nominal thickness of films. A power law evolution is observed.
3. RESULTS AND DISCUSSION 3.1. Characterization of Surface Morphology. The overall film morphology of nanostructured titanium oxide films is characterized by nanometer-scale porosity and granularity, dominated by grains of size 5−50 nm, which represent the coalesced aggregates of primeval titanium clusters produced in the cluster source (Figure 1A−C).13 AFM images show that by increasing the nominal thickness of the films, their morphology changes from smooth to coarser, with distinguishable increase
of height and lateral extension of morphological features. The key morphological parameters of the produced samples are listed in Table 1. Roughness and specific area of ns-TiOx films are plotted in Figure 1D as functions of film thickness; their evolution obeys simple scaling laws typical of the evolving interface of materials resulting from the ballistic assembling of nanometre-sized building blocks.28,29 In order to analyze the 5975
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dyes, respectively. The amount of enzyme molecules immobilized along the concentration gradients is provided by the Cy5 channel readout, whereas the Cy3 channel fluorescence reflects the relative amount of catalytically active enzyme molecules that were covalently tagged by the fluorescent activity probe. Concentration gradients of Alexa-647-trypsin conjugate were spotted as arrays of ten serial concentrations on ns-TiOx-coated glass slides divided in four zones (corresponding to four different values of thickness/roughness). TAMRA-labeled activity probe was applied to a half of the identical trypsin arrays on each ns-TiOx zone, while the other half served as control fields. Fluorescence maps obtained by scanning a single slide through both fluorescence channels are shown in Figure 2B. Fluorescence intensity values must be extracted from maps such as those shown in Figure 2, in order to build the adsorption isotherms and quantify enzyme activity as well as adsorption on nanostructured substrates. Due to occurrence of nonspecific probe binding a careful consideration must be given to the origin of the Cy3 signal. Moreover, the effect of cross talk between Cy3 and Cy5 channels must be accounted for. These tasks require in turn the implementation of practical procedures to get rid of the above-mentioned issues; the respective procedures are described in the Supporting Information. To characterize trypsin adsorption quantitatively, the relative fluorescence units of Cy5 channel were transformed into absolute units of trypsin equilibrium surface density using FPQ as described in the Experimental Section as well as in the Supporting Information. Briefly, the FPQ method of quantification of the surface density of fluorescently labeled proteins relies on the detection of the fluorescence signal of the adsorbed protein layer using a confocal microscopy setup. The fluorescence signal of protein layer is calibrated by the fluorescence signal of the bulk protein solution at known molar concentration; this provides the absolute units for mass density of adsorbed proteins on the surface in micrograms per square centimeters. Thus, the calibration of the whole series of adsorption data on multiple ns-TiOx samples in the wide protein concentration range requires solely a few confocal microscopy (FPQ) measurements. Activity of the adsorbed trypsin, on the other hand, was expressed in relative fluorescence units per time. The relative fluorescence intensity units of the detected activity probe could be, in principle, similarly calibrated by the FPQ method to provide useful information on the absolute amount of the detected catalytic sites. The FPQ calibration of the Cy3 channel units was however not performed during this study; instead, the activity of the surface-bound trypsin was expressed in terms of relative activity as well as of specific activity (the latter normalized by the absolute units of mass of the immobilized trypsin). To validate the newly developed PSIM activity assay, we performed a standard colorimetric (BAPNA) amidase assay of trypsin adsorbed on three different ns-TiOx samples by incubating the equilibrated samples in vials of reaction solution and estimating the product-versus-time curves from the absorbance change (data not shown). Direct comparison of the PSIM assay and the colorimetric assay was not possible due to the semiquantitative readout given by PSIM method (i.e., fluorescence units per minute); both activity assays showed however a similar trend of activity increase with sample roughness..
Table 1. Nanoscale Morphology Parameters of the ClusterAssembled Titania Samples sample ID 15 21 24 28 32 34
nm nm nm nm nm nm
ns-TiOx ns-TiOx ns-TiOx ns-TiOx ns-TiOx ns-TiOx
nominal thickness [nm] 25 50 100 150 200 300
root-mean-square roughness [nm] 14.9 20.5 24.0 27.7 31.5 34.0
± ± ± ± ± ±
0.3 0.1 0.7 0.5 0.5 0.4
specific area 1.60 1.73 1.80 1.84 1.84 1.87
± ± ± ± ± ±
0.02 0.02 0.01 0.01 0.02 0.01
dependence of trypsin adsorption and activity on the nanometer-scale properties of ns-TiOx films, roughness was chosen as the hallmark of surface nanotopography. Accordingly, ns-TiOx samples were designated by their surface roughness values as 15 nm ns-TiOx and so on. 3.2. Methodology for the Characterization of Enzyme Adsorption and Activity. The information on both trypsin adsorption and activity was obtained thanks to the doublechannel fluorescence detection setup, which allowed to simultaneously detect the fluorescence signal of the adsorbed trypsin and that of the activity probe bound to trypsin. The principles of the method are illustrated in Figure 2A. Trypsin is
Figure 2. On-slide assay for the detection of activity of physisorbed enzymes. (A) Schematics of the methodology. (B) Typical twochannels fluorescence readout of a single patterned slide. The test arrays consist of Alexa-647−trypsin proteins, visible through Cy5 channel, incubated with TAMRA-tagged activity probe, visible through the Cy3 channel; the control arrays (no probe incubation) account for desorption of physisorbed trypsin (Cy5) and channel cross-talk (Cy3).
deposited dropwise on ns-TiOx surfaces to create patterns of 10 × 10 spots arranged in concentration gradients, which are blocked, washed and subsequently incubated with the serine hydrolase activity probe. By positioning microarray slides in a multiwell chamber, each array is then subject to a different treatment, such as varying probe concentration and/or incubation time, followed by washing, drying and scanning of the slides. Fluorescence signals are detected using standard fluorescence emission filter sets established for Cy3 and Cy5 5976
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Although the PSIM activity assay was validated only with the trypsin-ns-TiOx model using the covalent activity probes specific for serine hydrolases, this methodology is applicable to a broad spectrum of enzyme-material combinations. The relevant prerequisites for the applicability of the PSIM assay to any selected enzyme-material surface system are (i) fluorescent labeling of the enzymes of interest; (ii) the presence of an enzyme fraction stably immobilized on the material surface; (iii) the availability of covalent activity labels for the enzymes of interest. Covalent activity-based probes have been synthesized for hydrolases, as well as for nucleotide-binding enzymes, such as ATPases and GTPases. Hence, the PSIM activity assay is applicable to any enzymes of interest belonging to these classes. In the next sections, we will consecutively focus on each of the two quantities that were measured simultaneously: the adsorbed density and the relative catalytic activity of trypsin immobilized on ns-TiOx surfaces of various nanometre-scale topography. 3.3. Adsorption Isotherms. According to the RSA approximation for noninteracting hard ellipsoids, the mean weighted surface density of trypsin monolayer adsorbed on a flat surface was equal to 0.21 μg/cm2; however, on nanorough surfaces, the monolayer adsorption value increased slightly according to the specific surface area characterizing each nsTiOx sample topography. Monolayer values calculated for the six ns-TiOx topographies ranged from 0.34 to 0.40 μg/cm2, on the smoothest and the roughest surfaces used in this study, respectively. Plotting the adsorbed surface density versus the bulk concentration on various ns-TiOx surfaces provided the adsorption isotherms of trypsin (Figure 3A). Within the 2 orders of magnitude wide bulk concentration range, the adsorbed amount grew rapidly and saturated at high concentrations whereby the adsorption plateau level was increasing notably with the roughness of ns-TiOx films. Taking into consideration the specific area factor of each sample, the completion of one full monolayer coincided with the isotherm plateau of the flattest surface, while on rougher surfaces monolayer coverage was greatly overstepped: plateau surface density exceeded the theoretical monolayer value by a factor of 20 at the highest ns-TiOx roughness. 3.4. Trypsin Saturation Uptake and Affinity. We followed the evolution of the two Langmuir equation parameters, the saturation uptake and the equilibrium dissociation constant kD, with ns-TiOx roughness. In the sampled roughness range, kD demonstrated a minimum region beyond which it continued to grow with ns-TiOx roughness (Figure 3B). Saturation uptake calculated from the Langmuir model was increasing with roughness according to the plateau adsorption levels of isotherms (Figure 3C). Absolute values of the adsorbed density plotted in the graphs were first normalized by the specific area factor of every ns-TiOx sample, thus taking into consideration the additional geometric area typical to nanostructured surfaces. Accordingly, a rise of the saturation uptake by a factor of 35 corresponded approximately to a 2-fold increase in roughness, while the specific area increased only 1.2 times. Hence, factors other than the simple increase in the geometric surface area associated with surface nanotopography had to be accounted for the steep rise in the saturation uptake. Nanoscale parameters of ns-TiOx films like roughness and specific area are rigorously determined by film thickness; furthermore, roughness of ns-TiOx films correlates with the average depth and aspect ratio of surface pores.19 The size distribution of surface pores is comparable to the size of
Figure 3. Trypsin adsorption on ns-TiOx surfaces with different roughness. The Langmuir model was used to extract quantitative parameters shown in panels (B) and (C). (A) Trypsin adsorption isotherms. All data were calibrated in both surface density units (μg/ cm2) and coverage (monolayers) units, and normalized by the specific area of each ns-TiOx surface. (B) Equilibrium dissociation constant kD. (C) Saturation uptake. Values of saturation uptake were calibrated and normalized by the specific area. Continuous lines in graphs (B) and (C) are drawn as guides for the eye.
proteins; therefore, confinement of proteins within the pores can be expected according to theoretical models.30 In addition to the mean pore size, also the nano- and sub-nanoroughness of pore walls are likely to enhance the entrapment effect, since roughness has been linked to impaired self-diffusion and increased residence time of particles inside pores.31 As a result of trapping of proteins inside surface pores, a high local density 5977
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can, in turn, give rise to supersaturation spikes triggering heterogeneous protein nucleation in the form of disordered clustering at randomly rough surfaces, an effect described theoretically,32,33 and observed experimentally for a range of disordered porous materials.32,34 In our previous study of the adsorption of three model proteins (bovine serum albumin, fibrinogen, and streptavidin) on ns-TiOx films,19 we interpreted the observed adsorption behavior as heterogeneous nucleation induced by the population of high depth-to-width ratio nanopores which in the case of ns-TiOx surfaces coincide with increased roughness. According to this adsorption mechanism, nanopores with higher aspect ratio are more likely to trap proteins; moreover, as the aspect ratio of pores and the roughness increase, the number of adsorption sites and the pore volume available for nucleation increase as well, leading to higher adsorbed protein density. Yet, deeper pores, or equivalently a higher film roughness, require a higher bulk concentration of proteins, that is, higher kD, to reach the local supersaturation condition that initiates protein clustering. For trypsin, the latter two effects are witnessed by the growth of saturation uptake and kD (Figure 3B,C). The initial reduction of kD with roughness is at odd with the proposed model, suggesting that other factors may play a role, such as protein−protein interactions, which could lower the kD value. However, as revealed by the saturation uptake measuring up to multiple monolayers, trypsin adsorption can no longer be described in terms of layer-by-layer coverage of the surface. Instead, trypsin clustering inside the volume of nanopores takes place. 3.5. Relative Activity of Adsorbed Trypsin. Fluorescence intensity from both detection channels Cy5 and Cy3 was simultaneously detected on selected ns-TiOx-coated slides (roughness 21, 24, 32, and 34 nm) to reveal both, the adsorption amount and the catalytic activity of trypsin; the results of this experiment are shown in Figure 4A,B. The fluorescence of the Cy5 channel gave a direct read-out of the relative amount of adsorbed Alexa-647−trypsin, while the Cy3 channel fluorescence was expressed in relative units of the amount of bound TAMRA-activity probe after the compensation of channel cross-talk. In the setup analyzed in the graphs of Figure 4, each of the trypsin concentration gradients was incubated with 1.25 μM solution of TAMRA-activity probe. Relative activity was defined as the amount of the activity probe bound to physisorbed trypsin per given time interval that was set to 10 min for these experiments. Alexa-647−trypsin fluorescence intensity versus trypsin concentration is directly proportional to the adsorbed density and therefore is equivalent to trypsin adsorption isotherms (Figure 3A), except for the calibration and normalization by specific surface area factor. As already considered regarding trypsin adsorption isotherms, a small increase of ns-TiOx sample roughness produced a huge increase in the adsorbed trypsin density. In particular, the roughness increase from 31.5 to 34 nm resulted in a 2.6-fold jump of the maximum adsorbed density of trypsin on these surfaces (Figure 4A). In contrast to the sharp differences observed in the Cy5 channel intensity, no clear distinction is observed in the growth of Cy3 channel intensity with trypsin concentration. Instead, along the whole trypsin concentration gradient, similar levels of Cy3 channel intensity were reached within the boundaries of the standard errors on all probed nanotopographies (Figure 4B). Clearly, each trypsin concentration value arrayed on ns-TiOx films attained a different mass of the immobilized trypsin depending
Figure 4. Simultaneous double-channel detection of fluorescence intensity along trypsin concentration gradients on a panel of ns-TiOx films. Alexa-647−trypsin gradients preadsorbed on ns-TiOx were incubated for 10 min with the TAMRA-activity probe at 1.25 μM concentration. (A) Fluorescence intensity detected in the Cy5 channel, reflecting the adsorbed amount of Alexa-647−trypsin. (B) fluorescence intensity of the Cy3 channel, corrected for cross-talk and background, marking the amount of the TAMRA-activity probe bound to trypsin.
on the nanotopography features of the surface, whereas the relative amount of the activity probe bound to trypsin remained largely unaffected by the change in ns-TiOx surface roughness. To account for the differences in the adsorbed amount of trypsin at every arrayed concentration value on various ns-TiOx samples, the relative activity detected by the TAMRA-activity probe was plotted versus the relative amount of adsorbed trypsin expressed as the percentage of the saturation uptake (Figure 5). Saturation uptake is defined as the maximum adsorbed density achievable on the particular surface, that is, the asymptotic plateau of the adsorption isotherm. Consequently, the percentage of saturation uptake is equivalent to the relative coverage value on a flat surface. In case of ns-TiOx, however, this quantity can be understood as the degree of saturation of the nanorough surfaces with adsorbed trypsin or, in general terms, the relative adsorbed amount of trypsin per surface area. Following this notion, the graph in Figure 5 essentially illustrates the dependence of the relative activity 5978
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the ns-TiOx surface at distances suitable for the establishment of strong hydrogen bonds. Additionally, it was recently suggested that the nonspecific adsorption of streptavidin on ns-TiOx proceeded via formation of molecular bonds between the exposed residues of carboxylic acids (glutamic or aspartic acid), which are deprotonated at pH 8, and undercoordinated titanium atoms of the surface.38 In another report by our group, it was suggested that −OH and −NH2 functional groups can displace already adsorbed hydroxyl ions and water molecules at the TiO2 surface, forming coordinate bonds with undercoordinated titanium atoms, while the hydrogen atoms of these functional groups can be involved in hydrogen bonding with the oxygen atoms of ns-TiOx surface, further strengthening the interaction.39 Considering that trypsin consists of a single chain polypeptide of 223 amino acid residues with the hydrophilic side chains exposed on the surface, there are numerous candidates for the bonding to ns-TiOx, including 12 aspartic acids and 10 glutamic acids with −COO− groups, as well as the positively charged 6 arginine and 11 lysine residues with −NH3+ groups (NCBI Reference Sequence: XP_002687122.1). Potential binding sites are spread across the surface of trypsin molecule, and therefore, any preferential orientation of trypsin molecule upon adsorption is very unlikely. As a consequence, we can presume that the fraction of trypsin molecules with accessible active sites is comparable to the fraction of molecules with the active site blocked by the TiOx surface. As long as proteins can be accommodated on the surface, that is, as the relative saturation of the ns-TiOx surface increases, the relative activity signal is expected to grow, because for some active sites blocked by the TiOx surface there will be others accessible. The detected activity can therefore be linked to the accessibility of the active sites of adsorbed trypsin, which proved to be proportional to the degree of saturation of ns-TiOx surfaces. Figure 5 captures this trend. The weak dependence of relative activity on protein concentration, that is, on absolute amount of adsorbed protein, reported in Figure 4B, suggests that those proteins, which get clustered into the pores in excess with respect to the surface
Figure 5. Dependence of relative activity on the relative adsorbed amount of trypsin expressed as percentage of saturation uptake. Percentage of saturation uptake was defined as the adsorbed surface density divided by the saturation uptake of each ns-TiOx sample and was introduced to enable the comparison of samples with different roughness. A linear fit of data is shown as a guide for the eyes.
from the relative adsorbed amount transformed in units that enable the comparison between the various ns-TiOx samples. The relative activity of all samples followed a common trend well described by a linear function, slightly deviating only near the saturation uptake. Figure 5 shows that trypsin activity depends primarily on the fraction of the maximum loading capacity (the saturation uptake) of the surface rather than on the absolute amount of protein that is actually adsorbed. In order to understand this behavior, the interactions between trypsin molecules and titania surface have to be taken into account. At the pH 8 used in this study, the surface of ns-TiOx bears a negative charge, since it has been shown that the isoelectric point of ns-TiOx films produced by SCBD lies well below pH 5,35 while trypsin molecules acquire an overall positive charge having the isoelectric point at around pH 10.2− 10.8.36,37 The occurrence of an attractive electrostatic interaction favors the close approach of trypsin proteins to
Figure 6. Dependence of the specific activity of trypsin on (A) ns-TiOx film roughness and (B) absolute adsorbed amount per surface area (i.e., the saturation uptake). Specific activity corresponds to the adsorption plateau of trypsin. Saturation uptake is expressed as surface density, in μg/cm2 units. The continuous lines, a linear fit in (A) and an exponential fit in (B), serve as guides for the eyes. 5979
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immobilization technique, and completely eliminating the need for covalent attachment of the enzyme. PSIM allows the simultaneous measurement of activity and amount of physisorbed enzymes, as well as the exclusion of activity signal of the leached enzyme; to our knowledge, there are no other methods capable of achieving these goals with the exception of a few approaches that couple electrochemical enzyme activity detection to complementary techniques and are typically limited to redox-active enzymes.10,44,45 Our methodology represents a new strategy for biomaterial surface screening with respect to the functionality of immobilized enzymes and it can be extended beyond the trypsin-nanostructured titanium oxide model to further enzyme-material systems, particularily to any enzyme classes that can be targeted by covalent activity labels. These findings are relevant for the optimization of rough nanoporous surfaces as carriers of immobilized enzymes uncovering the limitations of nanotopography in enhancing the number of effective catalytic sites on sensor and reactor surfaces.
coverage, do not contribute active binding sites to the TAMRA activity probe. Decrease in antigen−antibody binding ratio and decrease in specific enzyme activity with adsorbed amount have both been associated with steric hindrance of the active sites of adsorbed enzymes and antibodies at high surface coverage values.40,41 3.6. Relation between the Specific Activity and Surface Nanotopography. To highlight the effect of trypsin clustering on its resulting activity, we plotted the specific activity, that is, the activity per trypsin molecule, detected near the saturation uptake, as a function of sample roughness (Figure 6A). Remarkably, the specific activity dropped almost linearly with roughness indicating that a growing fraction of the catalytic sites within trypsin clusters had become inaccessible for the binding of the activity probe. Further confirmation of this observation was obtained by examining the dependence of specific activity from the absolute adsorbed amount per surface area, that is, the saturation uptake (Figure 6B): while the adsorbed density of trypsin molecules at the plateau was growing, the specific activity was diminishing. A similar decline in the specific activity of immobilized trypsin, with the increase of its concentration, has been reported by Shtelzer et al. upon the encapsulation of trypsin in sol−gel matrices.42 This phenomenon was partially attributed to the geometric constraints of the solid matrix and partially to the aggregation of trypsin.42,43 Aggregation behavior based solely on protein− protein interactions is indeed additionally favored by the mechanism of protein adsorption on ns-TiOx surfaces, that is, heterogeneous nucleation.32−34 With respect to the multilayered aggregation of trypsin molecules inside the volume of ns-TiOx pores, steric hindrance of active sites located both, at pore walls and within trypsin clusters, could take place. Furthermore, we have shown previously that both the number and the average size of the adsorbed protein clusters increase with the roughness of titania films;19 this, in turn, implies the dependence of the steric hindrance effect on roughness, as reflected by Figure 6A.
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ASSOCIATED CONTENT
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AUTHOR INFORMATION
* Supporting Information S
Details on fabrication of nanostructured titanium oxide films; Details on the preparation of labeled trypsin; Details on Protein−Surface Interaction Microarrays (PSIM). Arraying of Alexa-647-trypsin on ns-TiOx and application of the TAMRAlabeled activity probe; Details on Fluorescence Photobleaching Quantification (FPQ); Extracting quantitative data from fluorescence arrays, background and cross-talk subtraction. This material is available free of charge via the Internet at http://pubs.acs.org.
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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4. CONCLUSIONS We quantitatively characterized the adsorption and catalytic activity of trypsin on cluster-assembled nanostructured titanium oxide surfaces with different nanoscale topographies. Saturation uptake of trypsin on ns-TiOx films remarkably exceeded the value predicted by the geometric increase in surface area, as well as the theoretical monolayer coverage. The nonlinear increase of trypsin saturation uptake and equilibrium dissociation constant with ns-TiOx roughness suggests that the adsorption mechanism of trypsin conformed with the heterogeneous nucleation model observed for several nonenzymatic proteins. Our results highlight the role of nanoscale morphology in determining the activity of adsorbed trypsin: in particular, the aggregation of trypsin inside ns-TiOx nanopores perturbs its relative catalytic activity in a roughness-dependent manner. Specific activity expressed per mass of adsorbed enzyme, decreased linearly with roughness reflecting the reciprocal increase of steric hindrance of active sites with the ns-TiOx roughness. To obtain these results we applied a recently developed method (PSIM) capable of simultaneous assessment of the activity and the amount of surface-bound enzymes in a highthroughput scheme. The primary advantage of PSIM is the direct measurement of the interaction between the surface and the enzyme under investigation, based on physisorption as the
ACKNOWLEDGMENTS The authors would like to thank Dr. Lara Pagliato and Dr. Federico Martello for their valuable assistance with the preparation of protein samples. SEMM and Fondazione Filarete are acknowledged for their support in the realization of this work.
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REFERENCES
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