PROEFSCHRIFT
ter verkrijging van de graad van doctor aan de Technische Universiteit Delft,
op gezag van de Rector Magnificus prof. dr. ir. J.T. Fokkema, voorzitter van het College voor Promoties
in het openbaar te verdedigen op maandag 27 maart 2006 om 13.00 uur
door
Yulia Mikhailovna EFIMOVA Magister van de Natuurkunde,
Toegevoegd promotor: Dr. ir. A. A. van Well
Samenstelling promotiecommissie: Rector Magnificus voorzitter
Prof. dr. G. J. Kearley Technische Universiteit Delft, promotor
Dr. ir. A. A. van Well Technische Universiteit Delft, toegevoegd promotor Prof. dr. S.J. Picken Technische Universiteit Delft
Prof. dr. J. Penfold Oxford Universiteit Prof. dr. ir. W. Norde Universiteit Wageningen
Dr. B. Wierczinski Technische Universiteit M¨uenchen Dr. H. Th. Wolterbeek Technische Universiteit Delft
Published by IOS Press under the imprint Delft University Press
IOS Press Nieuwe Hemweg 6b 1013 BG Amsterdam The Netherlands Telephone: +31 20 6883355 Telefax: +31 20 6870039 E-mail: order@iospress.nl ISBN 1-58603-***-*
Keywords: Proteins, adsorption, neutron scattering, FTIR spectroscopy, thin gap c
°2006 Y.Efimova and IOS Press
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1 General Introduction 1
1.1 Introduction . . . 1
1.2 Proteins, structures and functions . . . 2
1.2.1 Lysozyme . . . 2
1.2.2 Bovine Serum Albumin . . . 3
1.2.3 Fibrinogen . . . 6
1.3 General aspects of protein adsorption . . . 8
1.3.1 Driving forces for protein adsorption . . . 8
1.3.2 Kinetics . . . 9
1.3.3 Exchangeability . . . 11
1.4 Motivation . . . 12
I Techniques, methods and materials 13 2 Techniques 15 2.1 Introduction . . . 15
2.2 Matching sample environments . . . 16
2.3 Neutron reflectometry . . . 18
2.3.1 Theoretical background . . . 18
2.3.2 Laminar flow cell construction . . . 21
2.3.3 Neutron scattering length density of proteins . . . 23
2.4 ATR-FTIR spectroscopy . . . 31
2.4.1 Introduction . . . 31
2.4.2 Quantitative analysis of the adsorbed amount . . . 34
2.4.3 Secondary structure and fitting procedure . . . 35
2.4.4 Solving the water vapour problem . . . 35
2.5 Thin gap radiotracer instrument . . . 39
2.5.1 Principle . . . 39
2.5.2 Theory . . . 41
2.5.3 Construction and materials . . . 42
3 Materials and methods 45 3.1 Introduction . . . 45
3.2 Buffer solutions . . . 45
3.3 Preparation and cleaning of SiO2 and TiO2 surfaces . . . 47
3.3.1 SiO2 surfaces . . . 47
3.3.2 TiO2 surfaces . . . 48
3.4 Proteins . . . 49
3.4.1 Protein solutions . . . 49
3.4.2 Stability of proteins determined by Differential Scanning Calorime-try (DSC) . . . 49
3.4.3 Protein aggregation examined by Dynamic Light Scattering . . . 59
3.5 Radiotracers production . . . 60
3.5.1 Labelling methods . . . 61
3.5.2 Enzymatic activity of labelled LSZ . . . 64
3.5.3 Influence of labelling on the protein secondary structure . . . 65
3.5.4 Concluding remarks . . . 66
II Experimental results, discussions and conclusions 67 4 Changes in the protein secondary structure upon adsorption determined by FTIR spectroscopy 69 4.1 Introduction . . . 69
4.2 Method to determine time-dependent changes in the protein’s secondary structure upon adsorption . . . 71
4.3 Structural analysis of proteins adsorbed on hydrophilic surfaces . . . 72
4.3.1 LSZ structural changes . . . 73
4.3.2 BSA structural changes . . . 77
4.3.3 FIB structural changes . . . 82
4.4 Conclusions . . . 84
5 Protein density profile by neutron reflectometry 87 5.1 Introduction . . . 87
5.2 Experimental section and fitting procedure . . . 87
5.3 Results . . . 90
5.3.1 LSZ adsorption onto TiO2 . . . 90
5.3.2 BSA adsorption onto TiO2 . . . 93
5.3.3 FIB adsorption onto TiO2 . . . 95
5.4 Conclusions . . . 97
6 Protein adsorption kinetics by FTIR spectroscopy 103 6.1 Introduction . . . 103
6.2 FTIR data normalization . . . 104
6.3 Modelling of the kinetics of protein adsorption . . . 105
6.4 Charges and history effect . . . 107
6.4.1 LSZ . . . 107
6.4.2 BSA . . . 110
6.4.3 FIB . . . 114
7 Desorption and exchange of proteins measured by thin-gap instrument 121
7.1 Introduction . . . 121
7.2 Experimental . . . 122
7.3 Protein exchangeability results and discussion . . . 122
7.4 Conclusion . . . 126
Summary 137
Samenvatting 141
Acknowledgements 145
General Introduction
1.1
Introduction
Protein adsorption at solid-liquid interfaces is a widespread phenomenon in both nat-ural and man-made systems and it plays an important role in many disciplines including biomedical engineering, biotechnology and environmental science. Therefore, the under-standing of protein adsorption was and is of great interest for scientist for many years and much progress has been made as shown in a number of review articles [1, 2, 3]. From these reviews it is clear that although most studies use the same protein (usually lysozyme, albumin or fibrinogen) many experimental results are contradictory. This is mainly due to the use of different measurement techniques, surface preparation, hydrodynamic con-ditions, etc. For this reason, in this study we try to control the parameters which may influence the protein adsorption process and choose a set of experimental techniques for a combined study of the protein adsorption process on solid surfaces.
The choice of techniques was inspired by the idea of looking at different aspects of the protein adsorption process for a fixed set of parameters. Neutron reflectometry (NR) is used to determine the density profile of the adsorbed protein layer. By attenuated to-tal reflection Fourier-transform infra-red spectroscopy (ATR-FTIR) the changes in the protein’s secondary structure upon adsorption are followed and the adsorbed amount is also measured as a function of time to obtain the protein adsorption kinetics. Fur-thermore, a new thin gap (TG) instrument was developed and tested to study protein adsorption/desorption and exchange processes using radiolabelled proteins.
We especially focus on the influence of electrostatic interactions on the protein adsorp-tion onto hydrophilic surfaces. The interacadsorp-tion between proteins and between proteins and surfaces is controlled by the pH, salt concentration and the properties of the surfaces. Also important to notice is that, during the protein adsorption, after initial attachment, a protein rearrangement often takes place. In case of similar rates of rearrangements and attachment the structure of protein adsorbed layer and adsorbed amount may be deter-mined by the interplay between these two rates. So, the history is important and the protein supply rate towards the surface has to be controlled. This can be achieved by the construction of a laminar flow cell with well defined hydrodynamic parameters.
1.2
Proteins, structures and functions
Proteins, from the Greek proteios, meaning first, are a class of organic compounds, which are present in and vital to every living cell. In the form of enzymes, hormones, antibodies, and globulins, they catalyze, regulate, and protect the body chemistry. In the form of hemoglobin, myoglobin and various lipoproteins, they effect the transport of oxygen and other substances within an organism. Proteins differ not only in their functions, but also in structures and molecular masses. Humans and animals consist of an estimated 30 thousand different proteins, ranging in molecular mass from a few thousand Da (g/mol) to more than a million Da. When we speak about protein structure, we recognize several levels of structural complexity. The basic level of protein structure is its primary structure, which is determined by the sequence of amino-acid residues. Each protein has its own unique amino-acid composition. Due to the forces between these amino acids and amino acids and medium (solvent), such as hydrogen bonds, disulfide bridges and electrostatic interactions, the protein molecule folds into the secondary structure. The main elements of secondary structure are: α-helix, β-sheet, β-turn and random coil. Interactions between these secondary structure elements form the protein’s tertiary structure, and its final macroscopic dimension. For our study, we choose three different types of proteins and their properties being discussed in next sections.
1.2.1 Lysozyme
Lysozyme (LSZ) was discovered in 1922 by Alexander Fleming and the first X-ray structure of LSZ, made by David Phillips in 1965 [4], revealed its ellipsoidal shape as well as the prominent cleft, see Figure 1.1. In general, LSZ is considered as a globular protein with dimensions 4.5×3.0 nm.
Figure 1.1: Structure of LSZ [5].
The primary structure of egg white LSZ is a single polypeptide chain of 129 amino acids [7]. It has a mass of 14.3 kDa and contains four disulfide bonds [8]. LSZ is known as a ”hard” globular protein in the sense of having a strong internal structure and con-formational stability. From the comparison of different methods for secondary structure analysis (i.e. circular dichroism or infra red spectroscopy) we deduce that LSZ has ∼34% of α-helix and ∼35% of β-sheet component [9]. The main physico-chemical properties of LSZ are presented in Table 1.1.
Table 1.1: Lysozyme data sheet.
Property Value Reference
Molecular weight Mw 14307 Da [7]
Isoelectric point (pI) 11.35 [10]
Diffusion coefficient 1.13·10−10 m2/s [11]
Optical absorbance A1g/l
279nm 2.36 UV measurements
Volume
(from protein crystal structure), vc 18.0 nm3 calculated using ref.[12]
Consensus volume
(average of six sets), vp 17.1 nm3 calculated using ref.[12] Specific enzymatic activity 15 [1000units/mg] measurements of lysis of
Micrococcus lysodecticus
Number of charges per LSZ molecule
at pH=4.0 +11 LSZ titration curve [1]
at pH=7.5 +7.5 LSZ titration curve [1]
Refractive index increment (dn/dc) 0.185 ml/g [13]
1.2.2 Bovine Serum Albumin
of a cigar, see Figure 1.2.
Figure 1.2: General perception of the structure of serum albumin.
However, studies using 1H NMR indicated that an ellipsoid structure of albumin is unlikely; rather a heart-shaped structure was proposed [24, 25] (Figure 1.3). This is in agreement with X-ray crystallographic data [26].
Figure 1.3: Space filling model of serum albumin molecule in the N form (A) Front view,
(B) back view, (C) left side, and (D) right side [25].
Moreover, crystallographic studies showed that the BSA molecule is made up of three homologous domains (I, II, III) (Figure 1.2) and undergoes a reversible conformational isomerization by changing pH [27, 28] (Figure 1.4).
Figure 1.4: Ribbon diagram of serum albumin in its N form, and in its proposed F and E
forms [25].
characterized by loss of the intra-domain helices of domains I and II. At pH>8 BSA has the less well characterized isomeric basic form, B. If a solution of albumin is maintained at pH 9 and low ionic strength at 30 C for 3 to 4 days, another isomerization occurs. This
is the A form, see Figure 1.4 and Figure 1.5.
Figure 1.5: Relationships of isomeric forms of Bovine Serum Albumin [27].
In order to complete the description of the BSA molecule, selected physico-chemical data of BSA used in our study are listed in Table 1.2.
Table 1.2: Bovine Serum Albumin data sheet.
Property Value Reference
Molecular weight Mw 66430 Da [29]
Isoelectric point (pI) 4.8 [30]
Diffusion coefficient 5.9·10−11 m2/s [31]
Optical absorbance A1g/l279nm 0.63 UV measurements
Volume
(from protein crystal structure), vc 84.5 nm3 calculated using ref.[12] Consensus volume
(average of six sets), vp 80.8 nm3 calculated using ref.[12] Number of charges per BSA molecule
pH=4.0 +25 BSA titration curve [32]
pH=5.0 ∼0 BSA titration curve [32]
pH=7.5 -7.5 BSA titration curve [32]
1.2.3 Fibrinogen
Fibrinogen (FIB) is an important protein in blood plasma. This is because the transfor-mation of fibrinogen to fibrin is the end result of a complex process of blood coagulation. If an injury occurs FIB coagulates to fibrin in the presence of thrombin. Fibrin forms a fibrous three dimensional network, preventing further blood loss (Figure 1.6). The FIB concentration in blood plasma is 20-45 g/l [33].
Figure 1.6: Main steps for the transformation from Fibrinogen to fibrin, producing blood
clots (cross-linked fibrin polymer).
Determination of the molecular structure of FIB was completed in the late 1970s [33, 34] and was established as two sets of three nonidentical polypeptide chains named
α, β, and γ, composed of 610, 461, and 411 amino acids, respectively, and held together
by 29 disulphide bonds, see Figure 1.7.
free-Figure 1.7: Schematic structure of FIB, consisting of three pairs of polypeptide chains α,
β, and γ. † Disulfide rings. ? Carbohydrate clusters [35].
Figure 1.8: Schematic view of a complex model of the FIB structure [37].
Table 1.3: Fibrinogen data sheet.
Property Value Reference
Molecular weight Mw 340000 Da [33]
Isoelectric point (pI) 5.5 [39]
Diffusion coefficient 1.98·10−11 m2/s [31]
Optical absorbance A1g/l
279nm 1.55 UV measurements
Volume
(from protein crystal structure), vc 433 nm3 calculated using ref.[12] Consensus volume
(average of six sets), vp 412 nm3 calculated using ref.[12] Number of charges per FIB molecule
pH=4.0 + [32]
pH=7.5 -7 [40]
Refractive index increment (dn/dc) 0.185 (ml/g) [13]
1.3
General aspects of protein adsorption
Protein adsorption plays a central role in many biological processes and it is a very chal-lenging fundamental problem since the energy scales involved are in general large com-pared to thermal energy. Proteins have colloidal type of interactions due to their large size. Furthermore, they have additional complexity due to the fact that they are largely inhomogeneous in size, shape and interaction. They can be charged and they can change their conformations upon adsorption. A good perspective for protein adsorption studies is that most of the proteins adsorb to almost all surfaces. It is rarely a problem to achieve the adsorption of a protein, but rather how to prevent it.
1.3.1 Driving forces for protein adsorption
The interactions between proteins, and between proteins and solid surfaces are mostly non-covalent, such as hydrogen-bonding, hydrophobic, Coulomb and Van der Waals inter-actions.
Hydrogen bonds.
Most of the H-bonds in proteins are between amide and carbonyl groups of the polypep-tide backbone. They are short ranged (∼0.1 nm) and have an effect on the stability of protein structure [41]. Formation of H-bonds appears not to be the main driving force for protein adsorption.
Hydrophobic interaction.
hydrophobic dehydration is considered to be the primary driving force for the folding process.
Coulomb interaction.
The pure electrostatic forces between charges. Since most of the charged amino-acid residues in a protein molecule are located at the aqueous periphery, this leads to a strong electrostatic interaction with charged surfaces. Usually, the protein surface is not ho-mogeneously charged. Close to the protein isoelectric point (pI) the interaction between proteins is attractive and repulsive when remote from pI [41]. By varying the pH of the solution the charges of the surface and protein can be changed. The electrostatic inter-action is an important driving force for the protein adsorption process, as indicated by many studies [2].
Lifshitz-Van der Waals interaction.
The Lifshitz-Van der Waals (LW) interaction is a result of interactions between induced dipoles [42]. The Van der Waals force for macrobodies is long range attractive, and relatively weak. Experimentally, the LW interaction energy between proteins and surface materials can be determined from contact angle measurements on a flat piece of surface material [43].
One of the most widely used models, often applied to calculate the non-covalent inter-action between biological colloids in terms of Gibbs energy, is Derjaguin-Landau-Verwey-Overbeek (DLVO) theory [44, 45]. This theory has been applied to the study of protein adsorption based on the assumptions that the particles are rigid, spherical, charged objects and their interactions with each other and with the surface (electrostatic, Van der Waals and solvation forces) are pairwise and additive. The assumption of rigidity is justified if the native structure of the protein is not significantly changed upon protein-surface inter-action. It is not surprising that the interaction of ”hard” globular protein such LSZ with solid surfaces can be reasonable well described by the DLVO model [46, 47], which is far less suitable for ”soft” nonspherical proteins like BSA and FIB.
1.3.2 Kinetics
Modelling of adsorption in single protein systems is of considerable interest and includes many different theoretical approaches.
The most common model for many years to fit proteins adsorption data is the Langmuir model:
dΘ
dt = kac0(1 − Θ) − kdΘ, (1.1)
where ka, kd are adsorption and desorption rate constants, respectively, c0 represents the
rate of adsorption) as (1-Θ), where Θ is the fractional surface site coverage. This is a consequence of the Langmuir model that one molecule occupies only one site. Obviously, proteins that are generally big enough can cover several sites. A possible way to get around this argument is redefining a site as protein footprint for physical adsorption, that is not associated with any chemical identity at the surface.
In general, the change in the density with time of adsorbed proteins on the surface can be written in generalized Langmuir form:
dΘ
dt = kac0φ(Θ) − kdΘ, (1.2)
where ka, kd, c0 have the same meaning as in the original Langmuir equation and the main
question is to determine the surface coverage function φ(Θ) which denotes the fraction of the surface available for adsorption.
One of the approaches, applied to the protein adsorption process, is the Random Sequential Adsorption model (RSA). This model does not allow for desorption or diffusion of the protein over the surface, and is derived for hard spheres. RSA represents the opposite to the fully reversible equilibrium Langmuir model. An important aspect of the RSA theory is the jamming limit of surface coverage, beyond which no additional molecules can be accommodated in the adsorbed layer. The main impact to the RSA model investigation in relation to protein adsorption has come from the studies of Schaaf and Talbot [48]. For circular discs they calculated the jamming limit Θ∞ of surface coverage to be 0.547.
The surface coverage function, φ(θ), determined from the RSA model has the form:
φ = (1 − x)3
1 − 0.812x + 0.2336x2+ 0.0845x3, (1.3)
where x = Θ/Θ∞.
The fact that coverage in protein adsorption is known to reach higher values (close to 1) suggests that some desorption and/or surface diffusion can occur as was demonstrated by a number of studies [49, 50]. However, the RSA model seems to work for modelling the protein adsorption process with some changes to the way of writing the adsorption rate [51]. On the basis of experimental observations two possible modes of adsorption, reversible and irreversible were postulated. In order to apply the RSA theory in fitting the experimental results it is convenient to write all equations in terms of rates of adsorption masses, Γ, defined by Equation 1.4. Then the reversible and irreversible components of adsorption masses are given by Equations 1.5- 1.6:
Γ = Θ · Γmax, (1.4)
where Γmax is maximum adsorption mass
dΓr dt = kac0φ − kdΓr p φ, (1.5) dΓi dt = kic0φ (1.6)
and the total mass of adsorption is
Recently, [52] a kinetic model was proposed that can take into account some of the key features of the reorientation mechanism. It was called a mass action kinetic model and includes bulk protein adsorption into either a ”nonoptimized configuration” (B) or an ”optimized configuration”(C), and transitions between the two configurations.
Figure 1.9: Schematic view of the mass action kinetic model.
A schematic illustration of this model is given in Figure 1.9 and described by:
dcA dt = 0, (1.8) dΓB dt = kacA(Γmax− ΓB− α · ΓC) − k2fΓBcA− kd1ΓB+ k2rα · ΓCcA, (1.9) dΓC dt = kacA(Γmax− ΓB/α − ΓC) + k2fΓB/α · cA− kd2ΓC− k2rΓCcA, (1.10)
where cA is the bulk concentration; α is the ratio of the occupied area between state C
and B, ka, kd1, kd2, k2f and k2r are rate constants for adsorption, desorption of species B, C and the transition from the B to C and the transition from the C to B, respectively.
1.3.3
Exchangeability
far, only a few simple models have been proposed that assume the existence of different adsorbed populations, each having its own characteristic exchange rate [55]. It is clear that there are still many remaining questions about the exchange process.
1.4
Motivation
Many studies have been performed with the aim of understanding the process of protein adsorption onto various interfaces (water/solid, water/oil). There are several applications of this adsorption phenomenon, such as solid-phase immunoassay for medical diagnostic tests, prediction and preventing unfavourable consequences of blood coagulation caused by artificial implants, or biofilms used on contact lenses, and oil-in-water emulsions in food industry stabilized by sodium caseinate.
However, in spite of the huge number of articles available on protein adsorption it is clear that a proper understanding of this process is still missing. In most of these studies the same types of proteins (usually LSZ, BSA, FIB) have been used but deviation of results and conclusions makes it difficult to obtain a clear understanding. The differences in results are mainly due to differences in:
• the measurement technique
• the solution properties (such as ionic strength, pH, presence of different ions) • the surface characteristic (type of surface, surface properties, way of preparation,
cleaning procedure)
• the formation of the adsorbed protein layer (hydrodynamic conditions of the
experi-ment) because the behavior of proteins at solid-liquid interfaces is often characterized by a strong history dependence caused by long relaxation times or irreversible transitions [56]. All these facts formed the aim of our study, which is to obtain a comprehensive picture of the protein adsorption process for a fixed number of protein-solution-surface systems applying different techniques with the same experimental conditions.
Therefore, the main objective of this thesis was to develop new, and improve existing instruments for protein adsorption at planar solid surfaces, and obtain a better insight into the problem of protein adsorption.
This thesis is divided into two parts. In the first part we described the main techniques used in our study. The materials and methods are also included in this part. Proteins are very delicate systems so checking and control of the sample quality is important because this determines the validity of the experimental results.
In the second part the experimental results of three proteins (LSZ, BSA, FIB) ad-sorption onto two planar solid surfaces (SiO2 and TiO2) are presented. Possible changes
Techniques
2.1
Introduction
In general, protein interaction with solid surfaces and further formation of adsorbed layers can be described via the rate constants of different processes as shown in Figure 2.1. The kinetics of some of these processes are described in Chapter 1.3.2. Figure 2.1 shows that different structures of the adsorbed layer can be formed and therefore, a large number of techniques, based on different principles have been, and are, used to study protein-surface interactions and adsorbed layer formation. In order to get complete information about the protein adsorption process a multi-technique approach is required. In our study we chose three experimental techniques: neutron reflectometry (NR), attenuated total internal reflection Fourier transform infrared spectroscopy (ATR-FTIR) and the thin gap (TG) radiotracer technique.
NR is commonly applied to determine the structural parameters of the adsorbed layer such as thickness and volume fraction of adsorbed material, but is not suitable for kinetic studies. In the case of non-spherical, rod-like, proteins we can recognize end-on or side-on adsorption using NR.
ATR-FTIR spectroscopy allows the study of both the secondary structure of the ad-sorbed proteins and the adad-sorbed mass as a function of time. By ATR-FTIR the kinetics of adsorption can be followed with time resolution of a few minutes.
TG is an instrument specially developed for work with radiotracers. By introducing a radioactive isotope into a protein (the labelling procedure) we can measure the protein adsorption process on a time scale of tens of seconds. It is also possible to detect an exchange rate of adsorbed proteins by replacing the solution of labelled proteins by non-labelled ones and measuring the decrease of activity on the surface.
Figure 2.1: Schematic illustration of possible protein interactions from aqueous solution
with a solid surface. The structure of the protein layer is characterized by its thickness, d, and protein volume fraction, φ. Different rate constants represent different processes: ka adsorption (determined by both protein transport and attachment), kd desorption, ks
spreading, k1, k2, k3 formation of different types of layer.
2.2
Matching sample environments
In order to compare the experimental results from different techniques, the same experi-mental conditions such as protein concentration, ionic strength and the pH of the buffer, surface type and structure are required. Experimentally it is rarely a problem to use the same samples in the different technique so we will not focus on this problem in the current chapter.
During the adsorption process, after initial adsorption, often a rearrangement of the molecule takes place, see Figure 2.1. If the rearrangement rate is similar to the adsorption rate of the molecules, the interplay between these two rates may affect the structure and the adsorbed amount [57]. For proteins this effect of history on the layer properties can be profound [56, 58, 59]. This means that, even when determining the structure of adsorbed protein layers in stationary experiments, information on the history of these layers is indispensable. Consequently, it is important to control this time scale of adsorption, which can be achieved by designing a measuring cell for each technique with a well-defined laminar liquid flow in a parallel plate geometry, see Figure 2.2.
Then in this geometry the protein flux toward the surface can be determined by the Leveque expression assuming a perfect sink [60]:
J = 0.538(˙γ L)
1
3D23c, (2.1)
Figure 2.2: Schematic illustration of the parallel-plate flow.
solution concentration, D is the protein diffusion coefficient and ˙γ is the wall shear rate. In all of our techniques a large probe area is used, so we have to replace the point of observation by its average along the probe area ranging from L = a to L = c and then we can write: ˆ L−13 = 1 c − a Z c a L−13dL. (2.2)
It is convenient to transfer the wall shear rate to volumetric flow Q because for the experiment we have to adjust the pump speed to produce the desired wall shear rate. For this reason the velocity profile has to be determined within the approximation that the flow is between two parallel plates with height h, width b and infinite length, see Figure 2.2, assuming that the flow is fully developed and laminar [61]:
uy = c1y + c2y2+ c3, (2.3)
with boundary conditions u(h)=0 u(0)=0 and so c3=0. Then an analytical solution of
Equation 2.3 is as follows:
uy = (6uh2)(yh − y2), (2.4)
where u is the average velocity between the plates. Then the shear rate ˙γ is defined as: ˙γ = duy
dy |y=0=
6u
h. (2.5)
The average velocity, u, can be translated to volumetric flow Q by dividing Q by the cross section A = bh, yielding
˙γ = 6Q
h2b. (2.6)
Note that laminar flow means: Reynolds number, Re, as defined by Equation 2.7, is less than 2000.
Re = 2Auρ
(h + b)µ, (2.7)
2.3
Neutron reflectometry
2.3.1 Theoretical background
The phenomenon of critical reflection of neutrons was first demonstrated by Fermi and coworkers [62]. Early applications included the determination of scattering lengths, the production of neutron guides and neutron spin polarizers. Later on, interest focused on the application of the reflection of neutrons to the study of surface and interfacial phenomena, since neutron experiments give information about the neutron refractive-index profile normal to an interface [63, 64].
Neutrons manifest wave-corpuscle dualism and so allow the description of neutron reflectometry completely analogous to light reflection. Consequently, neutron reflection is governed by the 3-dimensional Schr¨odinger equation:
− ~ 2 2mn d2Ψ(r) dr2 + V (r)Ψ(r) = ~2 2mnk0Ψ(r), (2.8)
where V (r) is the interaction potential of the neutrons with matter, mn is the neutron mass and k0 is the incoming neutron wave vector, see Figure 2.3.
Figure 2.3: Reflection geometry.
If we consider a system that is isotropic in the x, y plane (i.e. V (r) only depends on z), then we can derive the one-dimensional stationary Schr¨odinger equation for the neutron wave amplitude: − ~2 2mn d2Ψ(z) dz2 + V (z)Ψ(z) = ~2 2mnq 2 0Ψ(z), (2.9)
where q0 is the z-component of the incoming neutron wave vector k0, see Fig. 2.3, defined
as:
q0 = 2π sin(θ0)
λ . (2.10)
The position-dependent interaction with the matter can be described by the optical potential V (z) and is in absence of magnetic interaction, defined as:
V (z) = 2π~ 2
with ρ(z) the scattering length density:
ρ(z) =X
i
Ni(z)bi, (2.12)
where Ni(z) is the atom number density, bi is the coherent scattering length of species
i and the neutron absorption is taking into account by the imaginary part of scattering
length b:
b = bc+ iba. (2.13)
The perpendicular z-component of the neutron wave as a function of depth is:
q(z) = r q2 0− 2mnV (z) ~2 = q q2 0− 4πρ(z). (2.14)
In general, Equation 2.9 does not have an analytical solution for a specific ρ(z). Nev-ertheless, we can consider our system as a system of discrete homogeneous layers with a constant potential in each layer. Then the solution of the Schr¨odinger equation is:
Ψj(z) = Ajeiqjz+ B
je−iqjz, (2.15)
with boundary conditions at each interface: Ψj(z)|z=zj = Ψj+1(z)|z=zj and
dΨj(z)
dz |z=zj =
dΨj+1(z)
dz |z=zj, (2.16) where zj is the interface between layer j and j + 1 and qj =
p
q2
0− 4πρj. Then the set of equations can be solved using the optical matrix method.
In the neutron reflection experiment the square of the amplitude of the reflected wave is measured and this is called the reflectivity R = |r|2, with the reflectance r = B0/A0. The
most simple reflection case is that from a perfect interface between two media, incoming medium: j=0 and reflecting medium: j=1, which results in Fresnel’s law:
R = ¯ ¯ ¯ ¯qq11− q+ q00 ¯ ¯ ¯ ¯ 2 . (2.17)
The reflectivity decreases with increasing q0. In Figure 2.4, the solid line represents Fres-nel’s law as calculated for quartz. Either the angle, θ0, or the wavelength can be varied
to measure R as a function of q0 (Equation 2.10). The critical q0 value is determined by
the substrate, ρsub. Below the critical value, qc=p4π(ρsub− ρ0), total reflection occurs. In the case when ρsub< ρ0 no total reflection takes place.
Introducing one layer between the incoming medium and the substrate results in a reflectivity: R = ¯ ¯ ¯ ¯ r0+ r1e
2iqlaydlay 1 + r0r1e2iqlaydlay
¯ ¯ ¯ ¯ 2 , (2.18)
where r0 and r1 represent the Fresnel reflectance between the incoming medium and the
layer introduces interference effects between the amplitudes reflecting from both inter-faces, which results in fringes in the reflectivity as a function of q0. As an example, the
calculated reflectivity of a 20 nm gold layer on top of a quartz substrate, is shown in Figure 2.4. In general the spatial resolution of the reflectivity depends on the maximal q at which the reflectivity is measured, roughly the minimal length scale probed is 2π/qmax. The reflectivity strongly depends on the layer thickness and all the potentials involved. There-fore, neutron reflectivity gives information about the nm scale scattering length density profile of the reflecting sample.
Figure 2.4: Calculated neutron reflection curves. The solid line represents a bare quartz
substrate, and the dashed line is the reflectivity from a gold layer of 20 nm thickness deposited on a quartz substrate.
In the case of proteins, such as LSZ, BSA, FIB, the thickness of the adsorbed protein layer is expected to be in the nm range [65, 66], which makes neutron reflectometry an appropriate experimental technique to probe the structure of this adsorbed layer.
Since according to Equation 2.12 the scattering length density is defined by the chem-ical composition of the material investigated by the neutrons the scattering length density of the adsorbed protein layers, ρ(z), is closely related to the protein volume fraction profile,
φp(z), and determined by:
ρ(z) = φp(z)ρp+ (1 − φp(z))ρs, (2.19)
where ρ(z) is the scattering length density of the adsorbed protein layer, ρpis the scattering length density of the pure protein in this layer, see Section 2.3.3, and ρs is that of the
solvent.
In order to calculate the adsorbed mass, Γp, of the adsorbed proteins on the surface
Γp = R
φp(z)dz · Mw
NAvp , (2.20)
where Mw and vp are the protein molecular weight and volume, respectively. The protein volume fraction, φp(z), profile can be calculated from Equation 2.19:
φp(z) = ρ(z) − ρρ s p− ρs
. (2.21)
The ρ(z) is determined from the experimental neutron reflection curve by a fitting procedure that is described in details in Part II, Chapter 5.
In principle, the protein experimental data can be fitted with one uniform layer of certain thickness, d, and scattering length density ρ, but if the structure of the adsorbed layer is complicated or heterogeneous then a model of multi-layer is required and total protein adsorbed mass can be calculated as:
Γ = P
jdjφpjMw
NAvp , (2.22)
wherePj is a summation over all layers. 2.3.2 Laminar flow cell construction
Based on the paper: S. Haemers, Y. M. Efimova, A. A. van Well, Physica B, 357 (2005) 208-212
As mentioned in Section 2.2, the characteristic time scales of transport and attachment to the surface have important contributions to the formation of adsorbed protein layers (a more detailed description is given in Chapter 6). Therefore, when studying the structure of protein layers using NR, despite the fact that these are static experiments, a measuring cell in which transport rates are well-defined is needed. A good method to obtain well defined transport rate is use of a homogeneous laminar flow of fresh solution over the whole footprint area of the measuring cell. The requirement of homogeneous laminar flow has to be combined with high mechanical stability during the measurements and reproducibility when mounting the cell.
In adsorption studies of macromolecules the characteristic time scale for the total adsorption process, τ , in the transport limited case, is determined by the flux of the molecules towards the surface J, see Equation 2.1, and the adsorbed amount, Γsat, at saturation. This time scale, τ , can be defined as:
τ = Γsat
J . (2.23)
Combining Equations 2.23, 2.2, 2.1 yields the characteristic time scale for adsorption:
τ = Γsat
0.538(L˙γ)13D 2 3c
. (2.24)
cell of h = 1 mm, b = 40 mm and a length of 80 mm fitting on top of a 50x100 mm quartz crystal block. The Reynolds number, Re, at maximum attainable Q of 20 (ml/min) is
Re <18, well within the laminar flow regime.
To create a homogeneous flow pattern over the area in which the adsorption is probed, triangular shaped transition chambers were positioned before and after the measuring chamber. The distance needed to form a fully developed Poiseuille flow profile depends on the Re and is approximated by l = 0.05hRe, which yields l < 1 mm [61]. This distance is negligible so it can be assumed that the profile is developed when leaving the transition chamber. All areas in contact with liquid should be inert to protein adsorption, so the cell was constructed from PTFE. This requires extra care in the construction because PTFE is a soft material, which deforms easily under sustained pressure. Figure 2.5 shows different
Figure 2.5: A) Cross-section of the laminar flow cell in parallel plate geometry as mounted
at the ROG reflectometer in Delft, locally produced at TU Delft. The upward pointing transition chambers assure an effective trapping and/or outlet for air bubbles. B) 3-D view of the same cell. For the specific functions of the different parts we refer to the text. 1) Screw bolts for clamping the cell on the base plate; 2) Fitting for feeding tubes; 3) Upper PTFE block with machined flow chamber; 4) Lower PTFE block with groove for sealing O-ring; 5) Aluminium cradle; 6) Transition chamber; 7) Base plate; 8) Quartz crystal; 9) Stainless steel pressing plate with rim; 10) Finger spring washer; 11) Measuring cell. Note that the incoming neutron beam reaches the quartz/water interface from below.
are larger than for stainless steel. Thermal expansion resulted in a loss of alignment and even observable bending of the crystal block at varying temperatures. In addition, the springs assure a reproducible clamping force when assembling the cell. This reduces the time needed for realignment when remounting the cell after, for example, cleaning. In this cell the distances between the inlet tube and the lower point of observation is the length of the transition chamber, so, a=2.0x10−2 m and c=a+8.0×10−2 m=10.0×10−2 m this yields ˆL−13=2.66 m−1/3, see Equation 2.2, corresponding with ˆL=5.3×10−2 m .
2.3.3 Neutron scattering length density of proteins
Based on the papers: Y. M. Efimova, A. A. van Well, U. Hanefeld, B. Wierczinski, W. G. Bouwman J. of Radionalytic. and Nuclear Chem., 3264 (2005) 271-275, and Y. M. Efimova, A. A. van Well, U. Hanefeld, B. Wierczinski, W. G. Bouwman, Physica B, 350 (2004) e877-e880 .
Neutron scattering length varies from isotope to isotope, so isotopic substitution can be used to produce large differences in scattering length density. For example bH =-3.739×10−6 nm and b
D=6.671×10−6 nm, so the scattering length density of water can be varied in a wide range. This means that by using a different H2O/D2O ratio we can
always highlight the adsorbed protein layer.
If we dissolve proteins in an H2O/D2O mixture we should realize that some of the H atoms in proteins are not strongly bound and can easily be exchanged with D atoms from the solvent. For the correct calculation of the protein scattering length density, both the protein volume in solution and its total scattering length is needed. To calculate the total protein scattering length, the number of the H-D exchanges in proteins should be taken into account. The main contribution in literature to calculate the neutron scatter-ing length density for few proteins in H2O/D2O mixture were done by Jian Lu [3]. His
calculations were based on work of other experimental groups [67, 68] that estimated and measured the H-D exchange in some of the globular proteins. The total protein volume were estimated from the addition of all the amino acids and peptide fragments of the pro-tein. However, a complete quantitative analysis of the H-D exchanges in proteins and a method to calculate it has, to our knowledge, not been examined systematically. Moreover, the correctness of the estimated protein volume were not checked or proved experimen-tally. Regarding the problems mentioned above we present here a universal theoretical method for the calculation of the amount of labile H atoms from the primary structure, amino-acid sequence, of the protein and the knowledge of its secondary structure. The ex-perimental check were done by Positive electrospray ionization mass spectrometry (ES+ I-MS) measurements. Using ES+I- MS, the mass/charge distribution of the compound is
measured and the mass of this compound can be obtained. Differences in the masses of native ’protonated’ and ’deuterated’ proteins yield information about the H-D exchange. Theoretical calculations
The scattering length density of the protein, ρp, can be calculated by Equation 2.12 or Equation 2.25 as total scattering length of the protein bp divided by the protein volume
ρp = bp vp = P ibi P jvj, (2.25)
wherePi is a summation over all atoms, andPj a summation over all amino acids. As mentioned above, in neutron reflection experiments proteins are usually dissolved in an H2O/D2O mixture and some of the H atoms in protein exchange with D atoms from the
solution. It is important to know the number of exchanges because the scattering length density strongly depends on element composition of the specific protein, see Equation 2.25. The scattering length density of the protein in solution, with f the volume fraction of D2O
in the solvent, can be calculated as:
ρp = f ρpD+ (1 − f )ρpH, (2.26) where ρpH and ρpD are the protein scattering length densities in pure H2O and D2O,
respectively. Equation 2.25 leads to the following relation:
ρpD= ρpH+N (bD − bH)
vp
, (2.27)
where N is the maximum number of exchangeable H atoms in pure D2O. For the theoretical
calculation we need to determine N and vp. Finally, from Equations 2.25-2.27 we can write:
ρp= ( X i bi+ f N (bD − bH))( X j vj)−1. (2.28)
The amount of labile H atoms for each protein can be calculated from its amino acid sequence, the chemical structure of the amino-acid residues, and the secondary structure. The volume of the protein can be calculated as a sum of the amino-acid volumes, as presented for each protein in its data sheet in Chapter 1.
The amino-acid sequences of LSZ, BSA, and β-casein are known [14, 33, 69] and are presented in the second, third and forth column in Figure 2.7. In this type of calculation we did not look at FIB since this protein consists of more than 3000 amino-acid residues and its sequence is not easy to obtain. We consider a protein in an aqueous solution. All protein hydrogen atoms bound to O, S, or N atoms are labile and will exchange with hydrogens from the solution at a much greater rate than those bonded to C. It is important to note that the amount of labile H atoms in the side chains depends on the solution pH because the pK’ of these residue groups vary from amino acid to amino acid, see Figure 2.7. The amount of labile H atoms in the backbone of a protein is equal to the number of the peptide bonds in this protein. It is necessary to make a correction for amount of Pro residues, because the peptide bond between Pro and any other amino-acid residue does not give us a labile H atom, as illustrated in Figure 2.6.
The total amounts of exchangeable H atoms in LSZ, BSA and β-casein calculated from the primary structure of these proteins are given in the last row in Figure 2.7.
Figure 2.6: Part of the β-casein amino acid sequence.
atoms in the native state, the secondary structure has to be taken into account in the following way.
We performed circular dichroism (CD) experiments on LSZ and BSA to obtain infor-mation about its structure [70]. We had for LSZ: ∼32% of α-helixes, ∼21% of β-sheets. For BSA: ∼54% of α-helices and ∼18% of β-sheets. For β-casein: ∼10% of α-helixes and
∼13% of β-sheets [71]. This means that for the backbones for LSZ ∼69 H atoms, for BSA ∼400 and for β-casein ∼40 H are protected from exchange. Results of the calculation are
presented in Table 2.1.
Table 2.1: Amount of labile H atoms in LSZ, BSA, FIB and β-casein in the native
state, and the resulting scattering length, b, when dissolved in pure D2O. In pure H2O the scattering lengths of LSZ, BSA FIB and β-casein are: 3.41×10−3nm, 15.04×10−3 nm, 82.00×10−3nm and 5.27×10−3nm, respectively.
Protein pH<6 6<pH<7.2 7.2<pH<10 Total number of exchangeable H atoms
The number of exchanges and the scattering length of FIB were estimated based on the number of H atoms in a protein being approximately a linear function of the number of amino acid residues and the number of exchangeable H atoms is about a constant fraction of total number H in proteins. (These linear dependencies were checked for LSZ, BSA,
β-casein and extrapolated for FIB).
The calculations of the H-D exchanges were done assuming proteins in 100% D2O.
As mentioned above, the highlighting technique is used for different D2O/H2O ratios. We expect the number of exchanges to be a linear function of this ratio, see Figure 2.8, leading to Equation 2.26.
Figure 2.8: The number of exchanges in LSZ as a function of the D2O fraction in a H2O/D2O mixture: Experimental ES+I- MS points, see next section (circles). Theoretical prediction: only side chain exchanges (dotted line), all exchangeable hydrogens (dashed line), when taking into account the experimentally determined LSZ secondary structure (solid line).
From the results given in Table 2.1 we calculate the scattering-length density, ρ, as a function of the D2O fraction, f , cf. Equation 2.28. The results for LSZ and β-casein, using
the ’consensus volumes’ are illustrated in Figure 2.9. The calculated match points, using the ’consensus volumes,’ vp, and ’crystal-structure volumes’, vc, are f =0.444 and 0.422 for
LSZ, and f =0.398 and 0.380 for β-casein, respectively. The experimental match points are f =0.45 for LSZ [72] and f =0.41 for β-casein [73]. We conclude that the calculated values using ’consensus volumes’ agree well with the experimental values, this being in contrast with the conclusion of [12].
Figure 2.9: Calculated scattering length density in a H2O/D2O mixture. Dashed line: water; solid lines LSZ (top) and β-casein (bottom). Experimental match points: Right arrow: LSZ [72]; left arrow: β-casein [73].
Figure 2.10: Two-layer adsorption of LSZ on a quartz/water interface. Left panel:
Simu-lated NR data (symbols with 10% error bars, using values for the protein scattering-length density according to Figure 2.9 for water matched to quartz (68.5 vol% D2O): bottom curve and pure H2O: top curve. Results of simultaneous fit of a two-layer volume fraction profile, using the two different, correct, ρs (solid line) and using one, averaged, ρ (dashed line) Right panel: Volume-fraction profile as used in simulation (dotted line), results of ’correct’ fit (solid line) and ’averaged’ fit (dashed line).
simultaneously fitting the data to a 2-layer volume-fraction model, using the correct ρs, agree well with the original model, see Figure 2.10. Using one, fixed, ρ (2.4×10−4 nm−2) results in a good fit, see Figure 2.10 left. The layer thicknesses are reasonably reproduced, but the value of φ is approximately 20% too low.
Mass spectrometry experiments
For experimental observation of the H-D exchanges in proteins positive electrospray ion-ization mass spectrometry ES+I- MS can be applied [74, 75, 76]. Positive means that only
positive ions will be detected. In MS the ionization process is carried out at atmospheric pressure, and involves spraying a solution of the sample in a suitable solvent out of a small needle, to which a high voltage is applied. This process produces small charged droplets, and the solvent is then evaporated leaving the sample molecule ionized in the gas phase. This is then ’swept’ into a MS that is held essentially in vacuum and the ions are separated and detected using a reflectron-based time-of-flight analyzer, the principle being illustrated in Figure 2.11.
Figure 2.11: Schematic representation of the ionization process in the ES+I- MS technique.
We measured two proteins, LSZ and β-casein, with ES+I- MS. ES+I mass spectra were recorded using a Micromass Quattro LC Esp+ spectrometer (Manchester, UK). The
spray was pumped with a rate of 30 mL/min. Source temperature was 5000C, desolvation
temperature T=8000 C, cone voltage 15 V, capillary 3.2 kV. These parameters keep the
protein in its native state. The mass spectrometer was calibrated from m/z=500 to 3000, where m is the mass of the molecule to be analyzed and z its charge. Each mass spectrum was obtained at least in duplicate. The concentration of the samples was 1 mg/mL. To prevent micellization, the experiments with β-casein were performed in ice. All samples were incubated for 40 hours to allow H-D exchange to take place.
A comparison of the ES+I- MS spectra of ’protonated’ LSZ and a sample in which
H-D exchange has been taken place, ’deuterated’ LSZ, is shown in Figure 2.12 and gives in case of pH=7.5 shift in masses 188±5 Da.
For LSZ in ∼ 100 D2O we found 188±5 H-D exchanges at pH=7.5 and 187±5 at
Figure 2.12: a) ES+ mass spectra of LSZ in 10 mM buffer, pH=7.5: dotted line; LSZ in D2O, pD=7.5: solid line. b) Resulting shifts in mass.
H atoms given in Table 2.1. These experimental results show that a fraction of the exchangeable hydrogens is protected from exchange by the compact structure of the native protein under the experimental conditions used. These protected hydrogens are mostly from the backbone amide group, as we assumed and previously shown by nuclear magnetic resonance (NMR) studies of proteins [77, 68].
The ES+I- MS spectra of ’protonated’ and ’deuterated’ β-casein are presented in Figure 2.13. The shift in mass is a result of 280 ±5 H-D exchanges at pH=6.7. This result validates
the algorithm for calculating the number of exchanges in β-casein that was proposed in the previous section. The experimental results of the shift in the LSZ masses, measured for different D2O/H2O ratios, are presented in Figure 2.8. The experimental behavior of
the H-D exchanges in LSZ as a function of the D2O/H2O ratio is in good agreement with the theoretical prediction assuming that some of backbone H atoms in LSZ are protected from exchange by its secondary structure.
From Figure 2.8 we can conclude that taking into account the secondary structure of proteins plays an important role in the theoretical calculations of the number of H atoms in proteins labile for exchange.
2.4
ATR-FTIR spectroscopy
2.4.1 Introduction
When a beam of electromagnetic radiation of intensity I0 is passed through a substance, it
can be either absorbed or transmitted with intensity, It, depending upon its frequency, and the structure of the molecules it encounters, see Figure 2.14. The absorbance is defined as follows:
Abs = logI0
It = clε, (2.29)
where ε is the absorption coefficient which is specific for each molecule, c is the concentra-tion of the sample and l is the optical path length. Equaconcentra-tion 2.29 is also known as Beer’s law.
Figure 2.14: Definition of absorbance and transmittance.
Electromagnetic radiation is energy, thus when a molecule absorbs radiation it gains energy undergoing a quantum transition from one energy state, Einitial, to another, Ef inal. The frequency, ν, or the wavenumber, ˜ν=ν/c, where c is the propagation velocity, of the
absorbed radiation is related to the energy of the transition by Planck’s law: Ef inal
radiation by Planck’s constant, h, the radiation can be absorbed. If the frequency does not satisfy the Planck expression, then the radiation will be transmitted. A plot of the frequency of the incident radiation versus some measure of the percentage of radiation absorbed by the sample is the absorption spectrum of the compound.
The type of absorption spectroscopy depends upon the frequency range of the electro-magnetic radiation absorbed. Each molecular vibrational motion occurs with a frequency characteristic of the molecule and of the particular vibration. Vibrational spectroscopy measures transitions from one molecular vibrational energy level to another, and for infra-red (IR) spectroscopy requires radiation from the infrainfra-red portion of the electromagnetic spectrum in the range [4000 cm−1 - 400 cm−1]. The spectrum of the molecule appears as a series of absorption bands of variable intensity, each providing structural information. Each absorption band in the spectrum corresponds to a vibrational transition within the molecule, and gives a measure of the wavenumber at which the vibration occurs. For wa-ter, with three vibrational degrees of freedom, there are three sets of energy levels within which transitions may occur. These are found around 3500 cm−1, and 1650 cm−1 respec-tively. Application of IR Spectroscopy for structural analysis of organic molecules such as
Figure 2.15: IR spectra of FIB and part of its polypeptide chain.
proteins is usually concerned with the range between 1700 cm−1 and 1400 cm−1. In IR
FTIR-ATR spectrometer
IR spectrometers can be divided into two types: the dispersive IR spectrometer and the Fourier transform infrared spectrometer (FTIR). The FTIR spectrometer measures an infrared spectrum by Fourier-transformation of the interferogram and consists of four main parts, see Figure 2.16:
• light source (high brightness ceramic)
• interferometer (beam splitter, a fixed mirror, and a moving mirror scanning back
and forth)
• sample compartment • detector.
Figure 2.16: Schematic diagram of the FTIR spectrometer.
The FTIR spectrometer offers at least three advantages: multiplex advantage (ad-vanced accumulation and sorting of data allow to measure with one scan in one second a spectrum of all wavenumbers), aperture advantage (large aperture is used, more of the light source is available to maintain a high-throughput optical system), and wavenumber accuracy advantage.
In our study we use the FTIR type of spectrometer (Shimadzu 8300), see Figure 2.16, with a sensitive detector, L-alumine-doped deuterated triglycine sulfate (DLATGS) element. We applied FTIR in different modes: transmission, in order to look at the protein structure in solution and attenuated total reflection ATR, for investigation of protein structural changes upon adsorption and kinetics of the adsorption process.
Figure 2.17: The basics of total internal reflection. Light that is focused on one end of the
trapezoidal crystal travels through the crystal, experiencing multiple internal reflections.
With the help of an appropriate optical setup, infrared light is focused onto one of the faces of the ATR crystal. If the angle, Θ, at which the infrared light impinges upon the interface between the ATR crystal (the dense medium) and the air (or water, buffer with or without proteins - the rare medium) is greater than the critical angle then the light will totally internally reflect within the crystal. By appropriately choosing the thickness, W , and the length, L, of the crystal, we can control the total number of reflections, N . 2.4.2 Quantitative analysis of the adsorbed amount
The protein adsorbed amount, Γ, can be calculated in terms of experimentally observable quantities such as the integrated absorbance per reflection, A/N , the protein absorptivity,
², determined from transmission experiments for each protein, depth of penetration, dp, and the effective thickness, de, [78]:
Γ = A/N − cde²
²(2de/dp) . (2.30)
The magnitude of dp gives us an idea of how deep we can see into the rare medium, see Figure 2.18, and can be calculated using the following formula:
dp = λ
2n1πp(sinΘ)2− n2 21
, (2.31)
where λ is the wavelength of the light, n1 is the refractive index of the ATR crystal (for
silicon n1=3.42 and independent of wavelength), n2 is the refractive index of the rare medium that is a function of wavelength and for a protein solution of concentration c at
λ=6.45 µm, n2=nH2O+(dn/dc)·c=1.32+(dn/dc)·c ), Θ is the angle of incidence and n21
is n2/n1. A typical value for dp at 6.45 µm is 511 nm for silicon crystals. The effective thickness, de, is defined as the thickness of a material that will give the same absorbance in transmission spectra at normal incidence as that found from ATR:
de= n21E02dp
Figure 2.18: Schematic representation of attenuated total reflection.
where E2
o is the intensity of electrical field produced by perpendicular polarized light travelling through the ATR crystal. Using the expression for E2
o along the x, y and z directions [79] the parallel and perpendicular components of de, see Figure 2.17, are:
de⊥= 2n21dpcos Θ 1 − n2 21 , (2.33) dek = 2n21dpcos Θ(2 sin2Θ − n221) (1 − n2 21)((1 + n221) sin2Θ − n221) . (2.34)
Then, the overall effective thickness is
de=
de⊥P R + dek
1 + P R , (2.35)
where P R is the instrument polarization ratio and usually P R is close to unity. 2.4.3 Secondary structure and fitting procedure
The shape of the amide I band, see Figure 2.15, of proteins is characteristic of their secondary structure. The spectrum of single bands (each band is characteristic for a type of secondary structure) is broadened in the liquid. Therefore the bands overlap and can hardly be distinguished in the amide envelope. A curve fitting procedure can be applied to estimate quantitatively the area of each component representing a type of secondary structure [80] and by normalization each of them to the total area of the amide I peak is the percentage of secondary structure element calculated. Usually, each band is convoluted with a Lorentzian line shape function. Then the amide I can be considered as a sum of N Lorentz curves, see Figure 2.19.
In order to determine the frequency, υ0, of the band the second derivative has been
taken. The information about the width, γ, of the band and maximum absorbance, A0,
can be found from the second derivative as well. The obtained parameters (A0,υ0,γ) are
used as input parameters for a fitting procedure to fit the original infrared spectrum. To recognize the structural elements in the amide I peak we can compare the positions of frequencies, found from the second derivative, with values given in literature [81], see Table 2.2.
2.4.4 Solving the water vapour problem
Figure 2.19: Amide I band fitted with several Lorentz functions representing different
ele-ments of the protein secondary structure.
Table 2.2: Literature values for protein bands position in H2O (D2O) and positions for water vapors [81].
Structural element Protein bands (cm−1) Water vapor frequency in H2O in D2O β-sheet 1624±1 1624±4 1617 ” 1627±1 1631±4 1623 ” 1632±1 1637±3 1628 ” 1638±1 1641±2 1635.5 ” 1642±1 1645±4 1646 Random 1650±1 1653±4 1653 α-helix 1656±1 1663±4 1662 β-turn 1666±1 1671±3 1670 ” 1672±1 1675±5 1675 ” 1680±1 1683±4 1684 ” 1688±1 1689±4 1696
spectrum is measured and then after some time the blank measurement is repeated. The difference between two blank measurements represents the water vapour spectrum. After collection of the blank buffer spectra, the protein flow is started through the cell and FTIR-ATR spectra are written. A typical protein FTIR-ATR spectrum after substraction of the blank buffer spectrum, but without correction for water vapour, is presented in Figure 2.20.
Figure 2.20: The protein FTIR spectrum without substraction of water vapour spectrum.
The most common methods to get a ”clean” protein FTIR spectrum are based on subtraction of the water vapour spectrum with some normalization factor from the protein spectrum followed by a smoothing procedure [82]. This may lead to a slight modification of the protein spectrum making the protein structural analysis less accurate. A way to reduce the water vapour is the use of D2O as a solvent.
One of the solutions for the water vapour problem is to create a moisture free environ-ment. For instance, to place the FTIR spectrometer inside a sealed glovebox filled with dry air or N2 [83]. However, an experimental test of this approach shows overheating of the sample compartment. Insufficient circulation of air (N2) inside the glovebox results in
an unstable signal. Placement of the FTIR spectrometer in a larger compartment flushing with N2 first leads to a greater consumption of N2 and, second the leakages that always
take place deteriorate the FTIR protein spectra in time, see Figure 2.21.
In order to get FTIR protein spectra free from water vapours an efficient new method was developed and verified. This method enables smooth FTIR spectra of proteins in aqueous solution without water vapour subtraction from protein spectra and without using a smoothing procedure. By applying the technique of ”dynamic flushing” of N2
Figure 2.21: The protein FTIR spectra with static N2 flushing after substraction of water vapour spectra and without smoothing. a) At the beginning of experiment, b) after 3 hours running the experiment.
of N2 during the experiment the amount of water vapour is kept constant as in the blank
spectrum, which is automatically subtracted from protein spectrum by the software of the IR apparatus. Dynamic flushing offers the opportunity to correct the deterioration problem over time. The amount of nitrogen put into the system can be lowered, allowing water vapour to enter compensating for the reduced amount of water vapour. Continuous compensation gives the option to reduce the effect of water vapour even more.
It was apparent that the construction of the laminar IR flow cell plays an important role in the stability and quality of protein FTIR spectra as well. The straight base line, see Figure 2.15 of the FTIR protein spectrum in the range from 1750 to 2000 cm−1 is an important criterion for the correct water spectrum substraction from the protein+water spectrum. One of the reasons why the water substraction is done incorrectly is an accu-mulation of air bubbles inside the flow cell since the commercially available IR flow cell has a height of 1.0 mm and no chamber for trapping air bubbles at the entrance, Figure 2.22a). We modified the IR flow cell, see Figure 2.22b). The height 1.6 mm and bigger chambers at the entrance and exit of flow cell were made. This geometry yields ˆL−13=3.26 m−1/3 m, corresponding to ˆL=29 mm (Equation 2.2).
In addition, degassing of the protein solution before introducing it into the flow cell helps to prevent the formation of air bubbles.
Figure 2.22: IR flow cell. a) Commercially available, b) modified, see text.
Figure 2.23: Typical protein FTIR spectra applying dynamic flushing without substraction
of water vapour spectra and without smoothing. a) At the beginning of experiment, b) after 3 hours running the experiment.
2.5
Thin gap radiotracer instrument
2.5.1 Principle
The use of radiotracers is an attractive technique to study the exchange of proteins at solid-liquid interfaces. Substitution of atoms by radioactive isotopes, (labelling) enables isotope-tracer measurements. Various labelling methods exist, which are different in the choice of the isotopes and of labelling procedures. We developed the method to label proteins with 125I and a detailed description of this method will be presented in the
Section 3.5.
They used the fact that when adsorption is probed the substrate is pressed towards the detector surface thus removing most of the bulk solution, see Figure 2.24.
Figure 2.24: Schematic illustration of the up-down principle for the modified TG
instru-ment and its geometry.
The name ”Thin Gap” comes from the fact that this method is effective only when the gap between the detector and substrate is rather small: of order of a few micrometers. Another requirement is that the substrate effectively shields the detector from radiation originating from the bulk solution, so mostly β-emitting isotopes are used in this setup. We applied the TG instrument for 125I, which is γ-emitter with energy E
γ=35 keV.
How-ever, for 125I together with γ emitting a process of internal conversion takes place. This
process produces electrons, Auger electrons, that can be detected in the same manner as
β particles.
TG setups have been used extensively in corrosion, catalysis and electrochemistry studies. However, the TG instruments available at this moment have a large ∼100 mL batch cell, which makes changing the solutions onerous. In addition, the data analysis requires no adsorption on the surface of the detector, which is not possible in case of proteins. A lot of work has been done to make protein resistant surfaces [85, 86, 87], however no satisfactory materials were found that effectively prevent protein adsorption totally.
