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Evidence for Conformational Mechanism on the Binding of TgMIC4 with β‑Galactose-Containing Carbohydrate Ligand Adriano Santos,† Fernanda C. Carvalho,† Maria-Cristina Roque-Barreira,‡ André Luiz Zorzetto-Fernandes,‡ David Gimenez-Romero,§ Isidro Monzó,§ and Paulo R. Bueno*,† †

Institute of Chemistry, Physical Chemistry Department, Nanobionics Laboratory, Universidade Estadual Paulista (São Paulo State University), CP 355, 14800-060 Araraquara, São Paulo, Brazil ‡ Departamento de Biologia Celular e Molecular e Bioagentes Patogênicos, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo (USP), Av. dos Bandeirantes, 3900, Ribeirão Preto, 14049-900 São Paulo, Brazil § Departamento de Química Física, Facultad de Química, Universitat de València, Avda. Dr. Moliner 50, 46100 Burjassot, Valencia, Spain S Supporting Information *

ABSTRACT: A deeper understanding of the role of sialic/desialylated groups during TgMIC4− glycoproteins interactions has importance to better clarify the odd process of host cell invasion by members of the apicomplexan phylum. Within this context, we evaluated the interaction established by recombinant TgMIC4 (the whole molecule) with sialylated (bovine fetuin) and desialylated (asialofetuin) glycoproteins by using functionalized quartz crystal microbalance with dissipation monitoring (QCM-D). A suitable receptive surface containing recombinant TgMIC4 for monitoring β-galactose-containing carbohydrate ligand (limit of quantification ∼ 40 μM) was designed and used as biomolecular recognition platform to study the binding and conformational mechanisms of TgMIC4 during the interaction with glycoprotein containing (fetuin), or not, terminal sialic group (asialofetuin). It was inferred that the binding/interaction monitoring depends on the presence/absence of sialic groups in target protein and is possible to be differentiated through a slower binding kinetic step using QCM-D approach (which we are inferring to be thus associated with β-galactose ligand). This slower binding/interaction step is likely supposed (from mechanical energetic analysis obtained in QCM-D measurements) to be involved with Toxoplasma gondii (the causative agent of toxoplasmosis) parasitic invasion accompanied by ligand (galactose) induced binding conformational change (i.e., cell internalization process can be additionally dependent on structural conformational changes, controlled by the absence of sialic groups and to the specific binding with galactose), in addition to TgMIC4-glycoprotein solely recognition binding process.

1. INTRODUCTION It is largely known that the adsorption of proteins in functionalized surfaces is very important in a multitude of applications that include, for instance, biosensors1−9 as the most obvious, that is when the protein binding/adsorption event can be translated to a measurable (generally optical or electric) signal. Furthermore, adsorption of large biomolecules such as proteins is of high physiological relevance, mainly because the adsorption mechanisms are different due to the intrinsic complexity of biomolecules, indeed very much different from those even analogous chemical action lower weight molecules or atoms because of the multitude of molecular species present on the protein surface (that depends also on the size and conformational shape of the protein). The differences are additionally associated with the fact that proteins are driven by different intermolecular forces, hydrophobicity, and ionic or electrostatic interaction that affect protein adsorption and consequently physiological action. In terms of molecular or biomolecular adsorption models on crystalline surfaces, one of the most used, simpler models is the Langmuir physical chemistry model which assumes that molecular adsorbate behaves as an ideal gas at isothermal © 2015 American Chemical Society

conditions, meaning that the adsorptions sites are equivalent (in energy and size) and have unit occupancy. Furthermore, the model assumes that adsorbates do not interact between their neighbors on the receptive surface and so are usually used under dilute conditions where the previously mentioned presumption is generally obeyed, but it can fail in many cases where dilute conditions are not applicable and where the rough inhomogeneous characteristic due to multiple site-types available for adsorptions becomes preponderant as well as the adsorbate/adsorbate interactions. The latter is highly preponderant on high-coverage conditions where adsorbing one near other adsorbate molecules turns to be favorable or unfavorable relative to preceding bindings. Recently, we have demonstrate how such kind of more realistic physical chemistry problems can be investigated by using quartz crystal microbalance (QCM) technique, additionally using its potentiality/applicability associated with the use of dissipation factor (D) of the quartz crystals on this subject.10 Indeed, by using the D factor, Received: September 1, 2015 Revised: October 11, 2015 Published: October 21, 2015 12111

DOI: 10.1021/acs.langmuir.5b03141 Langmuir 2015, 31, 12111−12119

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to measure very small masses changes on the surface4,18 in a real-time label free platform enabling additional study of protein binding affinity and kinetics when appropriate protein adsorption models are stated.19−23 The principle of QCM operation is based on the quartz crystal as a thin piezoelectric plate with metal electrodes deposited on each side. The resonant frequency can be accessed by submitting the quartz crystal to an AC-voltage perturbation and if the mass is attached or adsorbed over; and if the mass is evenly distributed or rigidly attached, with no slip or deformation due to the oscillation motion, the resonant frequency decreases proportionally to the mass of the adhered film.24 Historically following this Sauerbrey24 proposal, QCM was initially employed to measure the adsorbed mass to a quartz crystal surface in gas phase with the detectable decrease in the oscillating frequency of the quartz crystal proportionally and quantifiably associated with an increasing of the mass adsorbed on that surface.24 The subsequent development of QCM to be used in liquids allowed the measurement of interactions on the sensor-solution interface, facilitating applications into a range of fields including immunology, medicine, cell biology among others.25 Furthermore, the QCM associated with dissipation (QCM-D) is able to measure mass changes in adlayers and additionally measure viscoelastic properties of such adhered layer using the measurements of the dissipation factor D,15 which gives structural information, mainly conformational changes during a biomolecular recognition process,10,26 and overcomes problems related to the rigidity of the protein adsorbed adlayers.26−28 In the present work, the interaction of recombinant TgMIC4 (rTgMIC4) with fetuin and its diasylated form, named asialofetuin, was studied. The study was conducted by functionalizing a QCM-chip able to characterize, specially using real-time measurements, TgMIC4−glycoprotein interaction equally in dilute (low coverage) and nondilute (high coverage) conditions. Besides, to observe the practical applicability of the improved isotherm model using the D factor (and by considering kinetics of the binding/interaction besides the solely steady-state analysis) as an extra parameter of the adsorption model, the results lead to additional biological inferences. For instance, it was concluded that differentiation between proteins containing (or not) sialic groups is possible due to a slower kinetic step that is dominated by conformational changes during the protein adsorptions on the QCMchip surface and is preponderant for the asialofetuin specific binding to TgMIC4. This allowed us to infer about the preponderant conformational/structural (or molecular mechanics) role operated by TgMIC4-A5 during parasitic invasion (host adhesion) and its specificity to galactose binding.

it is possible to achieve additional information on the binding kinetics using the energy losses introduced to the oscillatory system due to adsorbed protein.10 Such energy losses are directly related to frictional losses within the proteins, between proteins and the surface, and also between protein and its environment solvent, and so forth. Our main goal on the present work is to continue and expand previous analysis introduced by the use of the D factor in monitoring protein−protein interaction,10 such as the differentiation of binding processes that are experimentally equivalent under dilute conditions but very different under high protein coverage (so that applicable in real world events),10 exploring the binding kinetics and its analysis using improved adsorption models. Presently, TgMIC4 interaction with sialylated and desialylated proteins was elected as an appropriated biomolecular model. In doing so, we demonstrated that the existing differences on TgMIC4 binding and interaction with sialylated and desialylated proteins cannot be revealed solely by the use of traditional Langmuir adsorption analysis. The focus on the binding of the elected protein, in its sialylated and desialylated forms, with TgMIC4 as our model is justified by its potential importance on biomolecular mechanisms of host cell penetration by Toxoplasma gondii. Indubitably, TgMIC1-4-6 complexes play important roles in motility, host cell attachment, moving junction formation, and invasion of Toxoplasma gondii.11 Monteiro et al.12 demonstrated that mutant mammalian cells that present few or no surface-exposed sialic acid residues were infected to a lower extent by Toxoplasma gondii. Similar results were obtained if sialic acid residues were removed by previous neuraminidase treatment. These investigators observed that the addition of sialic acid residues to surface-exposed glycoconjugates using fetuin as a sialic acid donor and the trans-sialidase of Trypanosoma cruzi rendered the cells more easily infected by Toxoplasma gondii. This observation is attributable to TgMIC1, which was later reported as a sialic-acid-binding adhesion molecule. In addition, TgMIC1 recruits TgMIC4 which also exerts adhesive function during invasion,13 through the βgalactose recognition on the host cells. Whereas TgMIC1 and TgMIC4 behave as lectins that interact with glycoconjugates on the host cells surface, TgMIC6 anchors the complex on the parasite surface via a transmembrane domain. TgMIC4 binds to diverse range of neutral and acidic sequences oligosaccharide probes terminating in βgalactose, including some glycans that are sialylated and sulfated at inner residues.14 Regarding experimental ex situ studies, commercial (bovine) fetuin, a liver glycoprotein secreted into the bloodstream, typically containing three asparagines modified with complex-type N-linked glycans and four serine or threonine residues modified with O-linked oligosaccharides, 15 is a useful protein model to infer information on binding mechanisms with TgMIC4. The fetuin N- and O-glycans are all terminated with sialic acid Ncetylneuraminic acid (Neu5Ac) and N-glycolylneuraminic acid (Neu5Gc) in either (α2−3) or (α2−6) linkages. Besides natural (sialylated) form of fetuin, desialylated forms can be generated either enzymatically or chemically, such as asyalofetuin.16 Fetuin desialylated by mild acid hydrolysis was formerly used to demonstrate characteristics of a completely desialylated glycoform.7 Among several approaches and techniques,17 in literature, QCM is very useful in studying protein−protein interaction, which consist of a piezoelectric quartz crystal that can be used

2. MATERIALS AND METHODS 2.1. Reagents and Solutions. The recombinant micronemal protein MIC4 from Toxoplasma gondii (rTgMIC4) was kindly provided by Dra. Maria Cristina Roque-Barreira, Faculdade de Medicina de Ribeirão Preto − University of São Paulo.14 The thiols 11-mercapthundecanoic acid (11-MUA) and the 6-mercaphexanol (C6OH), anhydrous ethanol, gelatin, fetuin, asialofetuin, bovine serum albumin (BSA), hydrochloric acid (HCl), tris(hydroxymethyl)aminomethane (Tris), N-(3-(dimethylamino)propyl)-N′-ethylcarbodiimide (EDC), N-hydroxysuccinimide (NHS), and sodium chloride (NaCl) were purchased from Sigma Chemical Co. (St. Louis, MO). All the solutions used in the analytical procedures were prepared with Milli-Q purified water (Millipore, Simplicity System, Bedford, 12112


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Figure 1. Step by step schematic description of TgMIC4 recognition surface preparation before the evaluation of the binding/interaction processes of the TgMIC4 modified surface with fetuin and asialofetuin. (a) Functionalization of gold surface with a mixed solution containing MUA and C6OH in ethanol. (b) Activation of carboxylic groups with EDC/NHS protocol, forming NHS ester, able to react with amine groups present in rTgMIC4 protein, as shown in (c). (d) Blocking nonspecific sites with gelatin 0.1% to avoid interference.

Figure 2. (a) Schematic diagram of TgMIC1−4 sub complex. The interaction studied here is that encircled with host cell binding part, i.e. those involved with TgMIC4 binding to the host cell involving mainly the apple-5 part of the MIC4 protein. (b) The result of sugar binding activity as described in section 2.4. The study confirms that TgMIC4 is specific to β-galactose-containing carbohydrate ligand such as asialofetuin (a desialylated glycoprotein). MA) with 18.2 MΩ cm at 25 °C. The rTgMIC4 solution was prepared and used in Tris-HCl buffered solution, pH 8.0, with 200 mM NaCl. 2.2. Functionalization of Piezoelectric Sensor with rTgMIC4. The strategy used to immobilize rTgMIC4 was the self-assembled monolayers approach (SAM). Figure 1 shows step by step how the SAM was obtained by immersion of the cleaned crystal chip in an ethanoic solution of 11-mercaptoundecanoic acid and 6-mercaptohexanol, in the proportion of 1:3 (2.5 mM/7.5 mM), respectively, overnight at room temperature (25 °C). After the SAM formation, the crystal was washed with anhydrous ethanol and dried with nitrogen gas. To activate the SAM surface, it was used an aqueous solution with 1-ethyl-3-[3-(dimethylamino)propyl]carbodiimide (EDC) and Nhydroxysuccinimide (NHS), 10 and 20 mM, respectively, for 2 h at room temperature. The protein immobilization proceeded by immersion of the activated crystal in a rTgMIC4 (0.15 mg mL−1) solution buffered with Tris-HCl (pH 8.0) for 2 h at room temperature. The surface concentration of immobilized protein is equal to 860 ± 60 ng cm−2. To block residual carboxylic groups, the lectin-modified

crystal surface was exposed to a gelatin solution at 0.1% (w/v) for 2 h. After washing the crystal with Milli-Q water and carefully drying in air, the sensor was ready for immediate use in the affinity studies. In order to confirm the rTgMIC4 binding specificity to fetuin and asialofetuin, BSA was immobilized in the quartz transducer in replacement of rTgMIC4 followed by addition of the maximum glycoprotein concentration. The measurements were done in triplicate. The mass change of the quartz crystal was small, 21 ± 6 and 36 ± 9 ng cm−2 for asialofetuin and fetuin, respectively, meaning that BSA interaction with these glycoproteins is irrelevant compared with rTgMIC4 binding. 2.3. Apparatus. The quartz used was 14 mm in diameter, AT-cut and with a fundamental frequency of 5 MHz (polished quartz crystals provided by Q-Sense company with gold electrodes, QSX-301, with a Sauerbrey constant for the third overtone about 5.9 ng cm−2 Hz−1). Prior to the experiments, the quartz electrode gold surface was cleaned with freshly prepared hot piranha solution (3:1 H2SO4 (conc)/H2O2 30% (v/v). Caution! It is a powerf ul oxidant solution and must be used 12113


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Figure 3. Langmuir steady-state plots (obtained according to eq 2) for rTgMC4 binding/interactions with fetuin (a) and asialofetuin (b) under different protein concentrations. Statistics for linear fitting were R2 = 0.99 and 0.98 for fetuin and asialofetuin, respectively. with care.), rinsed with Milli-Q water and dried with nitrogen gas. After the rTgMIC4 immobilization onto the crystal surface, it was placed in a Q-Sense flow module with one face in contact with the solution and the other exposed to the air. The measurements were performed in a Q-Sense E4 quartz crystal microbalance (QCM system), using an ISMATEC IPC peristaltic pump with a controlled constant flow of 100 μL min−1 to pump different concentrations of glycoproteins in TrisHCL buffered solution (pH 8.0). It was used the third overtone to determine the affinity and kinetic constants. 2.4. Sugar Binding Activity. To evaluate MIC1 and MIC4 binding to fetuin and asialofetuin (as shown in Figure 2), the wells of a flat bottom microplate were coated overnight at 4 °C with 50 μL of 20 μg/mL fetuin or asialofetuin solution in carbonate buffer. The wells were washed with PBST (PBS containing 0.05% Tween-20) and blocked with 100 μL of 3% BSA in PBST (blocking buffer) for 1 h at room temperature. Afterward, 50 μL of 20 μg/mL MIC1 or MIC4 protein solution in blocking buffer was added to the wells. After 2 h incubation, unbound proteins were discarded, whereas the bound protein reacted with anti-Toxoplasma gondii mice serum for 2 h at room temperature, using a previously optimal dilution determined through a titration curve. After washing, protein−antibody complex was detected by using reaction with anti-mouse IgG conjugated with HRPO (Sigma-Aldrich). The reaction was visualized using 3,3′,5,5′tetramethylbenzidine (TMB) substrate solution and quantified by measuring optical density at 570 nm.

Δfmax = Δfsat

K ′C 1 + K ′C

(1)

in which Δf max is the maximum resonance frequency change reached at each glycoprotein concentration, Δfsat is the frequency shift upon saturation (steady-state conditions), C is the concentration of ligand (fetuin or asialofetuin) in solution, and K′ is the apparent affinity constant. Indeed, the real-time binding is monitored by following resonance frequency response of the rTgMIC4 functionalized quartz crystal as a function of time for different glycoprotein concentration in solution (and proportionally adsorbed in the surface) similarly to the methodology previously stated.10 However, as shown in Figure 3, we first only analyzed the data at steady-state, following eq 2. We observe that all measurements, in Figure 3, were performed in three independent rTgMIC4 functionalized quartz crystals and errors bars for these different measurements are also indicated. Furthermore, eq 1 can be rewritten in a more useful form, known as reciprocal Scatchard plot, which is a simpler linear form of eq 1 as C C 1 1 = + Δfmax Δfsat Δfsat K ′

3. RESULTS AND DISCUSSION

(2)

The linearity (R2 ∼ 0.98−0.99) obtained according to eq 2 can be observed experimentally in Figure 3 in which a limit of quantification, LOQ, of 40 μM is obtained for the ligand binding to rTgMIC4 functionalized surface, from which the carbohydrate-binding specificity to β-galactose-containing carbohydrate ligand is quantified. Additionally, following eq 2, it is possible to obtain resonance frequency shifts upon saturation (Δfsat) and apparent affinity constant (K′). The Δfsat obtained values are 21.7 ± 0.8 and 16.6 ± 0.8 Hz for fetuin and asialofetuin, respectively. It is important to note that the ratio asialofetuin between Δfsat for both glycoproteins is Δffetuin ∼ sat /Δfsat 21.7/16.6 = 1.3, similar to the observed ratio for molecular weights, MWfetuin/MWasialofetuin ∼ 44.4/40 = 1.1. As frequency changes are directly related to the surface protein coverage, the binding similitude of both proteins with MIC complexes is indicated by the equivalent amount of the adsorbed of fetuin and asialofetuin on the QCM chip surface. Consequently, it is possible to infer that the protein coverage during binding/ adsorption on the surface is equivalent for fetuin and asialofetuin but with a different weight loading due to the mass differences of both proteins.

3.1. Simple Protein Adsorption Model. Fetuin and asialofetuin binding/interaction properties with rTgMIC4 were investigated through the uses of rTgMIC4 functionalized quartz crystal surface, used as transducer of the molecular binding event into a measurable frequency change. The sugar binding activity and specificity was confirmed by alternative assays described in section 2.4 and summarized in Figure 2b, where the specificity of TgMIC4 to asialofetuin is confirmed. Regarding a more precise and quantitative assays using QCM approach, where the frequency change is used as transducer signal to the biological chemistry protein interactive event, the interpretation of the results depends on the election of an appropriate physical adsorption model. First the affinity event between rTgMIC4 surface and the elected glycoproteins was investigated by using the largely known simple Langmuir adsorption isothermal model20,29 under steady-state approach, where the sweeping of the glycoprotein concentration in solution is needed but only steady-state (equilibrium concentration) is evaluated and then follows eq 1 12114


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Figure 4. ΔD−Δf plots for the binding/interaction of rTgMIC4−fetuin (a) and rTgMIC4−asialofetuin (b) in glycoprotein concentration of 0.1 mM (Tris-HCl buffer, pH 8.0). Note the existence of two regions where the binding/interaction can be differentiated between these proteins according to what is discussed in the main text and attributed to be due to the influence of sialic groups on the binding/interaction process. Also note that in (a) the slower step cannot be easily identified/differentiated as it can be in (b).

mechanism is key for the differentiation with the binding to proteins containing sialic groups, which cannot be evaluated by a simple receptor−ligand mechanism. 3.2. Dissipation Factor Shifts as Additional Information to Binding Processes. The analysis performed in section 3.1 is obviously limited to the assumptions involved with the Langmuir simple physical adsorption model (under steady-state conditions) where thermodynamic information imbedded in eqs 1 and 2 can be obtained without needs to implement any kinetic analysis. Therefore, although quantitative and more detailed than classical methods31 the “pure” QCM analyses as performed in section 3.1 has limitations that restricts the association of it to an improved protein adsorption models and consequently a deeper differentiation between protein−protein interaction mechanism is equivalently limited. In simple words, in using steady-state Langmuir model, associated with “pure” QCM approach, the adsorbing species are assumed to be rigid, to bind reversibly with homogeneous binding energies and have none interactions with each other.20 However, the protein−protein binding interactions are highly complex and it becomes obvious that for protein adsorption model none of the assumptions above is strictly valid (mainly at high coverage of the receptive protein on the surface is stablished). Once a protein molecule has reached the surface, complex dynamic processes can occurs associated with their specific structure (and ligand complexes) and a truly or improved adsorption physical models are useful specially if additional information on the binding process is needed. Therefore, in screening frequency/mass with additional conformational change information provided by the dissipation (D) factor, the adsorption process especially in real-time can be even more detailed. This is the case of using QCM-D technique, which is able not only to measure resonance frequency changes but additionally the viscoelastic properties of the adhered molecules on the surface; that is, the viscous besides elastic characteristics of adhered layer using the dissipation factor, D, can be quantified.26−28 Indeed the usefulness of QCM-D to observe complex binding kinetics was already successfully demonstrated in a previous paper16 where undiluted conditions (highly surface coverage of the QCM-chip by the target protein) are present. The specific goal of the present work (more details will be given in the next section) is to present an improved protein

On the other hand, although frequency changes (sensitivity normalized by weight) indicate that fetuin and asialofetuin are similarly recognized by rTgMIC4, the obtained K′ values (through the application of eq 2 in Figure 3) are (5 ± 2) × 104 L mol−1 and (4 ± 1) × 104 L mol−1 (or 50 ± 20 mM−1 and 40 ± 10 mM−1) for fetuin and asialofetuin, respectively, indicating that both proteins have similar affinity for rTgMIC4 complexes considering the premises of Langmuir isotherm. Nonetheless, according to a well-established microarray technique30 for this kind of investigation, the neoglycolipid (NGL)-based oligosaccharide microarray system is poised to decipher the metaglycome.30 In these cases, sialic acid is not terminal, but inside the saccharide structure. The authors postulate that the binding to GM1 probes indicates the importance of unmodified terminal Gal for the TgMIC4-A5 binding, as well as the positive contribution given by the negative charge at position three to the binding strength. To assess the carbohydratebinding properties of TgMIC4, Marchant et al.14 carried out carbohydrate microarray analyses using the recombinant proteins TgMIC4-A5, TgMIC4-A56, and TgMIC4-A12. The microarrays encompassed a panel of 400 lipid-linked oligosaccharide probes representing diverse mammalian glycan sequences and their analogues, as well as sequences derived from fungal and bacterial polysaccharides. These are arranged based on negative charge (neutral and acidic) sialyl linkages and backbone sequences. TgMIC4-A12 showed no significant binding to any of the probes in the microarray, whereas TgMIC4-A56 and TgMIC4-A5 showed good binding to a diverse range of oligosaccharide probes terminating in βgalactose (Gal) with a similar binding profile. The probes bound include a wide range of neutral sequences and several acidic sequences that are sialylated and sulfated at inner residues. This is clearly distinct from the binding specificity of TgMIC1-MARR, which bound exclusively to sialic-acidterminating sequences. On the other hand, the fetuin sialic acid is terminal as indicated by all-atom ensemble modeling as analyzed by small-angle X-ray scattering of glycosylated proteins15 and would block the TgMIC-A5 binding, as demonstrated by the glycoarray studies. As will be demonstrated further, a detailed/improved analysis by QCM (using the D factor) confirms that the fifth domain of TgMIC4 binds differently to asialofetuin (investigated by glycan microarray techniques as indicated above) where a conformational 12115


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Langmuir adsorption model (explored under real-time measurements) able to differentiate and to provide additional information on the binding interaction upon the adsorption of fetuin and asilofetuin into a surface containing rTgMIC4 attached over QCM chip electrodes. In so doing we were interested not only on the frequency (or Δf) but also on D (or ΔD) shifts. Indeed, as can be seen in Figure 4, ΔD values are different for fetuinrTgMIC4 (5.3 × 10−6) compared to asilofetuin−rTgMIC4 interaction (3.2 × 10−6), demonstrating that the loss of energy for rTgMIC4−fetuin (mechanical softness) is higher. Generally, Δf and ΔD shows different dependencies as a function of time and an useful way of analyzing data is by using ΔD−Δf plots (as shown in Figure 4) in which the time is an implicit parameter. This plot reveals, via slope at any linear interval, how much energy dissipation occurs per unit of frequency change, that is, the energy lost per adsorbed molecule itself can be measured. In Figure 4, it can be also noted that ΔD−Δf plots for the fetuin and asialofetuin interactions have two wellmarker linear ranges: one taking place at short and the other at long times (mainly evidenced in Figure 4b for asilofetuin− rTgMIC4 interaction). These two different linear intervals can be used to distinguish and to reveal the mechanical/viscous differences between adsorbed protein (fetuin or asialofetuin) on the appropriated engineered (here containing TgMIC4) receptive surface. Indeed the overall ratio ΔD/Δf for these processes indicates a not depreciable loss of energy per oscillation of 0.210−6 Hz−1 (reinforcing the soft and viscous characteristics of both binding processes but clearly mechanically distinguishable). In summary, the information provided by K′ (preceding section) is not elucidative as those additionally obtained from mechanical/conformational changes (observed through ΔD/Δf analysis) during TgMIC4 interaction with glycoproteins shown in the present section. The present analysis demonstrates that TgMIC4 is influenced by the presence/absence of sialic groups contained on the evaluated glycoproteins when interacting with TgMIC4-functionalized QCM-chip. In the next section, we will describe the development of an improved adsorption physical model able to consider both the differences on thermodynamics and on the conformational binding kinetics concomitantly and yet keeping the qualitative and quantitative aspects involved with literature or by using the previous (section 3.1) simple Langmuir model. 3.2. Improved Protein Adsorption Model (through Kinetics, That Is, Real-Time Measurements). The two slopes identified in ΔD−Δf plots of Figure 4 (mainly Figure 4b) indicate that the kinetic bindings of proteins containing or not sialic groups and tested against rTgMIC4 QCM functionalized surface are clearly distinguishable. They consist of two time dependent steps (one higher slope and faster and a second lower slope and slower) that are signaling for the existence of two different binding/interaction kinetic steps. The existence of these two time dependent steps (quantified in Table 1) and the

differentiation between them by the presence or absence sialic group is especially pronounced for the slower step when sialic group is absent. As will be demonstrated below, this is associated with conformational/structural changes16 during protein−protein interaction. Indeed, in terms of magnitude, differences < 28% between fast and slow steps can be observed during fetuin and rTgMIC4 interaction as visualized in Figure 4 and quantitatively confirmed in Table 1. Nonetheless, differences larger than >62% are observed between fast and slow steps during asialofetuin and rTgMIC4 interaction. It can be thus stated that the faster process is comparatively lesser influenced by sialic groups albeit the slower is preponderantly influenced by its absence. An improved physical adsorption model (represented in eqs 3 and 4) able to deal with real-time frequency and energy dissipation shifts at the same time is required. This model is then able to better differentiate the observed influence of the sialic/desialylated groups on the binding real-time processes/ steps of TgMIC4 binding to different glycoproteins. In between several kinetic step possibilities (see the Supporting Information; model selection was performed using the Bayesian and Akaike information criterions), the statistical and mathematical analyses lead to the following binding (and kinetic) mechanistic model f kon

[rTgMIC4]s + [glycoprotein]b → [glycoprotein]s s kon

[rTgMIC4]s + [glycoprotein]b → [glycoprotein]s

f

fetuin

asialofetuin −0.2638 ± 0.0010 −0.0694 ± 0.0004

s

f s Δmmax = Δmeq (1 − e−kont ) + Δmeq (1 − e−kont )

(5)

where Δmeq is the equilibrium (reached for large time limit) loaded mass on the sensor surface. Figure 5 shows the asymptotic real-time mean averaged curves for fetuin−rTgMIC4 and asialofetuin−rTgMIC4 interaction processes at different solution concentration of fetuin and asialofetuin proteins in bulk solution. It is not possible to identify any visual significant difference between these processes. The differences are only accessible by adjusting the experimental curves with the appropriate equations (see the Supporting Information for more details) associated with the kinetic model predicting the steps previously stated in the above indicated eqs 3 and 4. The robustness of the model is evaluated carefully as described in the Supporting Information, and the adjustment can be seen in Figure 5 (red line). Table 2 shows the obtained coefficients of the adjustment of the model to experimental values as a function of different concentrations of glycoproteins. The kinetic constants, as expected, are invariant when analyzed as a function of glycoprotein concentrations so that reinforcing the validity of the proposed and improved adsorption model.

ΔD/Δf (10−6 Hz−1) −0.1897 ± 0.0013 −0.1743 ± 0.0004

(4)

in which []s (surface) and []b (bulk solution) represent the concentrations receptive surface of the sensor and in bulk solution, respectively. First to be observed is that (according to the fitting procedure) koff (dissociation kinetic constant) is negligible compared with kon (association kinetic constant). The s and f indexes represent those related to slower and faster processes. Therefore, in this improved adsorption kinetic model, clearly there are two dynamic processes occurring, that is, a faster and a slower one. In such model, the variation on the total loaded mass (Δmmax) has contribution of both processes and can be separated as following

Table 1. Slopes of the Lineal Intervals from the ΔD vs Δf Plot (Figure 4) Obtained during the Monitoring of the rTgMIC4−Glycoprotein Biorecognition Event

faster step slower step

(3)

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Figure 5. Real-time relaxation curves (Δm shifts as a function of time) of rTgMIC4−glycoprotein interaction for different glycoprotein concentrations in solution: (a) fetuin and (b) asialofetuin. The values were obtained in triplicate. Red lines are the fittings from the kinetic parameters shown in Table 2. All plots show only one point for every 10 points that are measured.

Table 2. Parameters Calculated from the Fittings of QCM-D Data Obtained for rTgMIC4−Glycoprotein Biorecognition Event, Figure 5a kfon (s−1)

[fetuin] (mM) 0.01 0.04 0.07 0.11 0.15 [asialofetuin] (mM)

0.0223 0.0223 0.0223 0.0223 0.0223

0.02 0.10 0.21 0.31 0.41

kson (s−1)

± 0.0003 ± 0.0003 ± 0.0003 ± 0.0003 ± 0.0003 kfon (s−1)

0.0199 0.0199 0.0199 0.0199 0.0199

± ± ± ± ±

0.0009 0.0009 0.0009 0.0009 0.0009

0.00154 0.00154 0.00154 0.00154 0.00154

Δmfeq (ng cm−2)

± 0.00006 ± 0.00006 ± 0.00006 ± 0.00006 ± 0.00006 kson (s−1)

0.00090 0.00090 0.00090 0.00090 0.00090

± ± ± ± ±

0.00007 0.00007 0.00007 0.00007 0.00007

142 ± 3 265 ± 3 363 ± 3 346 ± 3 541 ± 3 Δmfeq (ng cm−2) 82 189 376 394 592

± ± ± ± ±

3 3 3 3 3

Δmseq (ng cm−2) 97 ± 3 76 ± 3 94 ± 3 189 ± 3 54 ± 3 Δmseq (ng cm−2) 117 150 94 87 135

± ± ± ± ±

6 6 3 3 3

a Note that the differences on the mass loading for fast and slow steps are large for higher protein concentration, meaning/reinforcing that dilute (study) conditions are not appropriate for real world study of protein−protein binding process occurring during biological events.

in which Δmieq is the maximum surface mass change of the ith (faster or slower) processes, Δmisat is the surface mass shift upon saturation, and Ki its the affinity constant. In considering eq 6, it can be analyzed Δmisat and Ki for faster and slower step regimes for both fetuin−rTgMIC4 and asialofetuin−rTgMIC4 binding interactions. The mass associated with the faster (630 ± 40 ng cm−2) and slower (100 ± 30 ng cm−2) events for both binding interactions, whose sum is in good agreement and comparable to the total surface density of immobilized protein (860 ± 60 ng cm−2), corroborating the robustness of model when adjusted to the experimental data. The difference observed between the contributing mass for faster and slower steps indicates that the weight of the faster step is higher on the mass change and is dominant, also confirmed when observing that Δmfsat is higher. This corroborate with the fact that the slower step is highly controlled by conformational changes than the binding/recognition step itself. 3.3. Physical and Biological Chemistry Interpretation. As described by Marchant et al.,14 TgMIC4 comprises six apple domains that occur in intimate pairs (see Figure 2a), where interaction with β-galactose is established by the apple-5 domain of TgMIC4. In other words, the absence of sialic groups is required for the glycan recognition by the apple-5 domain, demonstrating high ligand activity with β-galactose. In the previous sections, we demonstrated that our rTgMIC4functionalized QCM-chip surface is able to differentiate

The presence of two kinetic (faster and slower) steps is evidenced by observing TgMIC4−glycoprotein association constant for fetuin and asialofetuin. They differ larger than 96% in both fetuin and asialofetuin association events. For instance, for fetuin kfon, it is 0.0223 ± 0.0003 s−1 (fast), meanwhile a much lower kson of 0.00154 ± 0.00006 s−1 (slow) is observed for the same protein. In agreement, for asilofetuin, these values are kfon of 0.0199 ± 0.0009 s−1 and kson of 0.00090 ± 0.00007 s−1, again much lower for the slower step, confirming the existence of two kinetic conformational binding processes in both fetuin and asialofetuin interactions with TgMIC4. The association kinetic constants of these two processes/steps when directly compared for TgMIC4−fetuin and TgMIC4−asialofetuin are relatively similar for the faster steps differing only by about 11%. On the other hand, these values differ by more than 58% for the slowest step. This evidence that the presence/absence of sialic group affects the binding prominently through the slower step. The thermodynamic aspects of adsorption model introduced in eqs 3 and 4 are dissociable as parallel events (in our improved model) in a way that they can be better compared with the equilibrium Langmuir isotherm presented in eq 2, and the problem can thus be equivalently treated as C C 1 1 i = i + i Δmeq Δmsat Δmsat Ki

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protein binding biomolecular model. In using the carbohydratebinding specificity of TgMIC4 with two variety of β-galactosecontaining carbohydrate ligand (fetuin and asialofetuin), it was possible to infer the role played by desialyated groups during binding/interaction process. In doing so, it was possible to identify the existence of two binding kinetic steps, faster and slower, where the desialyated group influences more prominently the slow, higher mechanically (viscous) dependent, kinetic binding/interaction step, during the comparative binding/interaction of TgMIC4 with fetuin and asialofetuin when using improved (and validated−details in SI document) isotherm adsorption model. Indeed, the structural dynamics (inferred through real-time D-factor analysis) involved with the binding/interaction of fetuin and asialofetuin proteins were inferred to play a prominent role in the understanding of the influence of desialyated groups on the conformational/ structural changes occurring during the TgMIC4−glycoprotein binding/interaction process. From a biological point of view, it can be inferred that the apple 5 domain of TgMIC4 depends largely on the presence of desialyated groups and so that may play an important role cell invasion through a conformational/structural slower step occurring during the binding/interaction of TgMIC4 with glycoproteins containing β-galactose. We concluded that the apple 5 domain is involved with the slower step and conformational/structural change identified in our QCM-D kinetic adsorption model and influenced by the absence of desialyated groups. The identified conformational change, mechanically viscous and flexible, may facilitate TgMIC4 binding/adhesion during parasitic invasion involving Toxoplasma gondii.

between sialylated and desialylated glycoproteins mainly due to the existence of a slower kinetic binding/interaction step that depends on the presence/absence of sialic group in the target protein. The apple 5 domains are biologically inferred13 to play an important role in Toxoplasma gondii parasitic action. In this way, the distinction (according to the presence/absence of sialic groups) is observed to be possible by using fetuin and asialofetuin. The evidence for the existence of a slower binding/ interaction steps involved with eqs 3 and 4 is thus elucidative. The faster binding/interaction step present equivalent affinity constant for the binding process independent of the presence/ absence of sialic acid groups and is also responsible for most percentage of the mass load of the QCM-chip. Consequently, such fast process does not involve conformational change so that likely is inferred to not be effective to complete/aid the parasitic invasion molecular mechanism but instead is only part of its action. On the other hand, the slower kinetic binding/ interaction steps involved with conformational and mechanical changes are inferred herein as an important and complementary step of the molecular mechanisms involved with parasitic invasion mechanism known, comprising essentially the 5 apple domain13,14 (see Figure 2a) and so that with further action susceptible to the absence of sialic acid groups and thus directly associated with β-galactose ligand. We then assume that the slower step completes the recognition/action of the parasitic invasion process inferred to be involved with the absence of sialic groups and effectively contributing as a step forward parasitic invasion besides a faster recognition/binding event. Indeed, the slower step as conformational/structural changes may contribute to an effective TgMIC4 attachment and aid the TgMIC1 further action that is preferentially made through sialic groups as shown in Figure 2a. Accordingly, we propose that the βgalactose recognition by TgMIC413,14 is a precedent step to those involving a conformational change concomitantly activating/facilitaing the cell internalization mechanism during the cell invasion, inter alia, by the apple 5 domain presented in TgMIC4. It is important to emphasize that the additional information here obtained from QCM-D studies, as a mechanically dependent technique, elucidates the role played by the absence/presence of sialic groups during the binding mechanism of TgMIC4 with sialylated (bovine fetuin) and desialylated (asialofetuin) glycoproteins thus demonstrating the contribution of the molecular mechanics characteristic involved with the binding process. Changes involved with faster binding/interaction step are virtually elastic and structurally irrelevant whereas the process involved with the slower step, a desialylated dependent event, is viscous with significant conformational/structural rearrangements. In summary, we propose that desialylated events involved with β-galactose ligand binding with TgMIC4 is mainly controlled by structural/ conformational changes rather than simply recognition process. The conformational characteristic of the binding process is a key component to be studied beyond the simplistic analysis involving the crude affinity constants interpretation of the binding events.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.langmuir.5b03141. Details on the kinetic model; additional results and information (PDF)

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AUTHOR INFORMATION

Corresponding Author

*Phone: +55 16 3301 9642. Fax: +55 16 3322 2308. E-mail: [email protected]. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors acknowledge the support of this work by the São Paulo State Research Funding Agency (FAPESP, Number Process 2009/11520-0; and 2013/04088-0) and the Brazilian National Research Council (CNPq). This research was also funded through project Feder CTQ2013-42914-R (Spanish Ministry of Economy and Competitiveness, Spain). We are also grateful to Camila F. Pinzan for providing the TgMIC used in the present study.

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4. FINAL REMARKS AND CONCLUSIONS QCM-D technique was used here to map out relevant conformational changes (taking advantage of real-time characteristics of the technique) involving rTgMIC4−glyco-

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