Adsorption of a Water Treatment Protein from Moringa oleifera Seeds

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Adsorption of a Water Treatment Protein from Moringa oleifera Seeds to a Silicon Oxide Surface Studied by Neutron Reflection Habauka M. Kwaambwa,*,†,‡ Maja Hellsing,‡ and Adrian R. Rennie‡ † ‡

University of Botswana, Department of Chemistry, Private Bag UB 00704, Gaborone, Botswana, and Department of Physics, A˚ngstr€ om Laboratory, Uppsala University, Box 530, 751 21 Uppsala, Sweden Received August 20, 2009. Revised Manuscript Received February 2, 2010

An extract from the seeds of the Moringa oleifera tree that is principally a low molecular mass protein is known to be efficient as a coagulating agent for water treatment. The present paper investigates the adsorption of the purified protein to silica interfaces in order to elucidate the mechanism of its function as a flocculent. Neutron reflection permits the determination of the structure and composition of interfacial layers at the solid/solution interface. Dense layers of protein with about 5.5 mg m-2 were found at concentrations above 0.025% wt. The overall thickness with a dense layer in excess of 60 A˚ at 0.05 wt % suggests strong co-operative binding rather than single isolated molecules. An ionic surfactant, sodium dodecyl sulfate, was also seen to coadsorb. This strong adsorption of protein in combination with the tendency for the protein to associate suggests a mechanism for destabilizing particulate dispersions to provide filterable water. This can occur even for the protein that has previously been identified as being of low mass (about 7 kDaltons) and thus is unlikely to be efficient in bridging or depletion flocculation.

Background and Introduction The treatment of water to render it fit for human consumption has been a problem of immense challenges, in both developing and developed countries. In developing countries, the quality of drinking water is often hazardous to human health. Aluminum salts, iron salts, and synthetic polymers are commonly used coagulants in water treatment.1 The cost and environmental side effects of these compounds are their main disadvantages. For instance, aluminum salts have been associated with Alzheimer’s disease.2,3 As a result, it is desirable to develop other cost-effective coagulants that are more environmentally acceptable. Naturally occurring alternatives to currently used coagulants are being considered including cultivated plants. The seeds of a tropical tree, Moringa oleifera (MO), have attracted particular interest since they treat water on two levels, acting as both a coagulant and an antimicrobial agent.3 MO seeds, therefore, present a viable alternative coagulant not only in developing countries but worldwide. The tree grows rapidly even in marginal soils, demands little or no horticultural attention, and possesses a hardiness that enables it to survive prolonged periods of drought. It is native of northern India but is widely cultivated throughout the tropics and is found in many countries of Africa. It is a multipurpose tree with most of its parts being useful for medicinal and commercial applications, in addition to its value in nutrition and water treatment. Previous studies in this area have focused mainly on the extraction and purification, efficiency, and evaluation of the *Author to whom correspondence should be addressed. Permanent address, Department of Chemistry, University of Botswana. (1) Letterman, R. D.; Pero, R. W. Am. Water Works Assoc. J. 1990, 82, 87–89. (2) Martyn, C. N.; Barker, D. J. P.; Osmond, C.; Harris, E. C.; Edwardson, J. A.; Lacey, R. F. The Lancet 1989, 59–62. (3) Broin, M.; Santaella, C.; Cuine, S.; Kokou, K.; Pelteir, G.; Jo€et, T. Appl. Microbiol. Biotechnol. 2002, 60, 114–119. (4) Grabow, W. O. K.; Slabert, J. L.; Morgan, W. S. G.; Jahn, S. A. Water SA 1985, 11, 9–14. (5) Madsen, M.; Schlundt, J.; Omer, E. E. J. Trop. Med. Hygiene 1987, 90, 101– 109. (6) Muyibi, S. A.; Evison, L. M. Water Res. 1995, 29, 2689–2695.

3902 DOI: 10.1021/la9031046

quality of the treated water.4-11 Some of the benefits reported in the literature about treatment with extracts from MO seeds include 92-99% reduction in turbidity, decrease in clay and bacteria content of raw water, efficiency as good as aluminum salts, and production of lower sludge volumes.12 It is now generally accepted from numerous studies that the MO seeds possess effective coagulation properties, although the nature and properties of the active component seem to differ depending on the method of extraction and purification used. For instance, the molecular masses for the extracted protein varying between 6 and 13 kDa. Ndabigengesere et al. (1995) described the seeds from this plant as containing active coagulating agents that were characterized as dimeric cationic proteins having a molecular weight of 13 kDa and an isoelectric pH between 10 and 11.13 On the other hand, Okuda et al. (2001) reported that flocculation of clays could occur from an extract of MO seeds that was not protein.9,10 More recent studies by Kwaambwa and Maikokera14-16 have shown that the active component is a protein but the mechanism of coagulation and flocculation caused by a short protein chain at low concentration is not well understood, and so, fundamental studies based on colloid science are useful. The present paper describes the amount of adsorbate and the structure of interfacial (7) Gassenschmidt, U.; Jany, J. D.; Tauscher, B.; Niebergall, H. Biochim. Biophys. Acta 1995, 1243, 477–481. (8) Folkard, G. K.; Sutherland, J. P.; Shaw, R. In Running Water, Shaw, R., Ed.; Intermediate Technology Publications: London; pp 1109-1112. (9) Okuda, T.; Baes, A. U.; Nishijima, W.; Okada, M. Water Res. 2001, 35, 405– 410. (10) Okuda, T.; Baes, A. U.; Nishijima, W.; Okada, M. Waer Res. 2001, 35, 830– 834. (11) Ghebremichael, K. A.; Gunarutna, K. R.; Henrikson, H.; Brumer, H.; Dalhammor, G. Water Res. 2005, 39, 2338–2344. (12) Ndabigengesere, A.; Narasiah, K. S. Water Res. 1998, 32, 781–791. (13) Ndabigengesere, A.; Narasiah, K. S.; Talbot, B. G. Water Res. 1995, 29, 703–710. (14) Maikokera, R.; Kwaambwa, H. M. Colloids Surf. B: Biointerfaces 2007, 55, 173–178. (15) Kwaambwa, H. M.; Maikokera, R. Colloids Surf. B: Biointerfaces 2007, 60, 213–220. (16) Kwaambwa, H. M.; Maikokera, R. Colloids Surf. B: Biointerfaces 2008, 64, 118–125.

Published on Web 02/17/2010

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layers formed by the extracted protein. Broin et al.3 sequenced the amino acid composition of the purified recombinant MO2.1 that had similar flocculating properties to a protein that had been isolated and sequenced earlier by Gassenschmidt et al.7 The sequence of Broin et al., however, only differed by two cysteine residues. There is, therefore, a general consensus among researchers that the active component is protein. The activity of the protein MO2.1 was found to be independent of the electrostatic charge of the impurity: it caused flocculation of both grampositive and gram-negative bacteria.3 Apart from being nontoxic, it has several advantages over conventional water treatment materials, because it is entirely biodegradable, provides significantly reduced volume of sludge, and is insensitive to the pH and conductivity of the water. In previous studies of the physicochemical and conformational properties of the protein extract, techniques such as spectroscopy (i.e., intrinsic and extrinsic fluorescence, circular dichroism, infrared, and UV-vis spectroscopy), surface tension, measurements of density, and viscosity were used.14-18 Although these studies have been able to elucidate structure (primary, secondary, and tertiary), conformational states and physicochemical properties as function of microenvironment (i.e., pH, ionic strength, and added surfactant), they have not been able to answer and address certain fundamental questions about this protein such as amino acid composition, charge characteristics, microstructure of the protein-surfactant complexes, and protein adsorption on opposite charged particle surfaces to mimic dirt, and so forth. Lack of such information or data compromises the interpretation of biophysical parameters. From a fundamental point of view, it is important to determine the mechanisms that control the interactions between water impurities and the protein. The role of protein extracted from MO seeds as a flocculent in water purification is directly related to adsorption. Information about the amount of material that is adsorbed at the surface and how this relates to the concentration in solution is obviously of crucial importance in making efficient use of the material and providing water with low levels of impurities and additives. It is well-known that the conformation of a protein molecule can be distorted by adsorption to an interface, and the physicochemical properties might be important, since they depend on structural reorganization that occurs with adsorption. The degree of distortion depends on the protein-surface bonds, on modification to intramolecular binding, and on the density of the adsorbed layer. Adsorption of surfactants can modify adsorbed protein layers resulting in a change of adsorption as well as rheological characteristics. In the present study, neutron reflection is used to investigate the structure and composition of the protein from MO seeds adsorbed at a silicon oxide/water interface. The technique offers the opportunity to measure not only adsorbed amounts, but also the surface/interfacial structure of the adsorbed protein under aqueous conditions at a resolution not obtained currently by other techniques such as ellipsometry and atomic force microscopy (AFM). SiO2 layers on the surface of silicon crystals have been widely used in the neutron reflection as a flat hydrophilic model substrate to assess the adsorption characteristics of various surface active materials. These include various low molecular mass surfactants, synthetic polymers, and proteins.19 The surfaces can (17) Kwaambwa, H. M.; Maikokera, R. Water SA 2007, 3, 583–588. (18) Maikokera, R.; Kwaambwa, H. M. Research Letters in Physical Chemistry, Vol. 2009, Article ID 927329, 5 pages (doi: 10.1155/2009/927329). (19) Thomas, R. K. Annu. Rev. Phys. Chem. 2004, 55, 391–426. (20) Marsh, R. J.; Richard, Jones, R. A. L.; Sferrazza, M. Colloids Surf. B: Biointerfaces 2002, 23, 31–42. (21) Lu, J. R.; Zhao, X.; Yaseen, M. Curr. Opin. Colloid Interface Sci. 2007, 12, 9–16.

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also be modified so as to provide hydrophobic interfaces.20,21 Several other investigations have been made of other proteins such as casein, lysozyme, BSA, and antifreeze protein, to mention but a few, on either hydrophilic or hydrophobic surfaces22-25 and have also included displacement of adsorbed layers with surfactants.26 There have also been studies of proteins with specific biological or medical interest such as those in membranes27 and the components of saliva28 adsorbed to Al2O3. There are also a number of studies of surfactant proteins such as surfactin29 and latherin30 at solid/liquid or air/liquid interfaces. As the SiO2 surface is covered with hydrated water molecules and is hydrophilic, it is a good mimic of common water impurity surfaces and is suitable for experiments with neutron reflection. In these systems, there is a large contrast for neutrons between both the substrate and D2O as a solvent. Ground water often contains natural surfactants and as a proxy sodium dodecyl sulfate (SDS) will be used to compare the effects of competitive interaction at an interface. SDS was used as model anionic surfactant for several reasons. First, its binding with a range of proteins in bulk solution has been extensively studied (see ref 18 and the references therein). Second, the protein in this study is known to be positively charged at neutral pH, and therefore, it should interact with both silicon oxide and SDS. Additionally, Kwaambwa and Maikokera have studied the protein and its interaction with surfactant, particularly SDS, using other techniques as mentioned earlier.14-18 Interpretation of Neutron Reflection Data. Neutron reflectivity, R(Q), is defined as the ratio of the intensity of the reflected beam to that of the incident beam and is usually presented as a function of the momentum transfer, Q, perpendicular to the reflecting interface given as Q¼

4π sin θ λ

ð1Þ

where θ is the incidence angle and λ the wavelength of the incident neutron beam. The scattering length density (F) that governs the neutron refractive index depends on chemical composition through the following equation X ð2Þ F¼ ni bi where ni is the number density of the element i, and bi is its scattering length. The reflectivity can be calculated from the profile of refractive index (or F) as a function of depth at the interface as described in, e.g., ref 22. Different isotopes have different bi values, and isotopic substitution is widely used to highlight specific components at the interface. It is convenient to highlight the adsorbed protein layer using D2O. The volume fraction of each component within the protein layer is related to F by ð3Þ F ¼ φp Fp þ φw Fw (22) Penfold, J.; Thomas, R. K. J. Phys.: Condens. Matter 1990, 2, 1369–1412. (23) Lu, J. R.; Thomas, R. K.; Penfold, J. Adv. Colloid Interface Sci. 2000, 84, 143–304. (24) Lu, J. R. Ann. Rep. Prog. Chem., Sect. C 1999, 95, 3–45. (25) Fragneto, G.; Thomas, R. K.; Rennie, A. R.; Penfold, J. Science 1995, 267, 657–660. (26) Green, R. J; Su, T. J.; Lu, J. R.; Penfold, J. J. Phys. Chem. B 2001, 105, 1594–1602. (27) Nylander, T.; Campbell, R. A.; Vandoolaeghe, P.; Cardenas, M.; Linse P.; Rennie A. R., Biointerphases 2008, 3, FB64-FB82; doi: 10.1116/1.2976448. (28) Cardenas, M.; Arnebrant, T.; Rennie, A. R.; Fragneto, G.; Thomas, R. K.; Lindh, L Biomacromolecules 2007, 8, 65–69. (29) Shen, H.-H.; Thomas, R. K.; Chen, C.-H.; Darton, R. C.; Baker, S. C.; Penfold, J. Langmuir 2009, 4211–4218. (30) McDonald R. E.; Fleming R. I.; Beeley J. G.; Bovell D. L.; Lu J. R.; Zhao, X.; Cooper, A.; Kennedy, M. W. 2009, PLoS ONE, 4, e5726; doi:10.1371/journal. pone.0005726.

DOI: 10.1021/la9031046

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Kwaambwa et al. Table 1. Elemental Analysis of the MO Seeds (% by Mass) sample

carbon (%)

hydrogen (%)

nitrogen (%)

sulfur (%)

Shelled MO seeds with oil Shelled MO seeds without oil Purified protein powder Protein calculated from data in Table 2

52.3 ( 0.3 44.4 ( 0.3 44.93 ( 0.05 44.0 ( 0.1

8.7 ( 0.1 7.34 ( 0.05 7.5 ( 0.2 7.6 ( 0.1

5.9 ( 0.1 7.72 ( 0.08 18.8 ( 0.1 15.5 ( 0.1

1.8 ( 0.1 2.38 ( 0.09 2.8 ( 0.5 2.0 ( 0.2

where Fp and Fw are the scattering length densities of protein and water, respectively, and φp and φw their respective volume fractions. As the protein layer is fully immersed in water at the solid/ solution interface, φp þ φw = 1. Equations 1, 2, and 3 indicate the relationship between structural models and F. Direct Fourier transformation of reflectivity measured as a function of Q to obtain density as a function of depth is constrained by the narrow Q range with which the neutron reflectivity profiles are measured. In practice, reflectivity profiles are usually analyzed by means of an optical matrix formalism to calculate R(Q) for a series of layers that has been described in detail, for example, by Penfold and Thomas.22 The structural parameters used in data analysis are the number of layers, layer thickness (τ), and the corresponding scattering length density (F) for each layer (related to layer composition as in eq 3). The area per molecule (A) for the protein adsorbed in a uniform layer can be calculated from P A¼

mp bp þ nbw Fτ

ð4Þ

P where mpbp is the total scattering length for the protein and n is the number of water molecules associated with each protein molecule. The surface excess (Γ) can be obtained from Γ¼

MW AN A

ð5Þ

where MW is the molecular weight and NA is the Avogadro’s number. If two or more sublayers are required to describe the nonuniform distribution of the adsorbed protein layer, eqs 3, 4, and 5 are applicable to each sublayer, and the total adsorbed amount is obtained by summing over the sublayers used in the fitting procedure. As stated previously, the choice of the number of layers is dependent upon the extent of inhomogeneity at the interface. The minimum number of layers that will successfully fit the data is often chosen, but if there is a smooth profile, it is useful to define with a few parameters the composition of a sequence of layers.

Materials and Methods Materials. Sodium dodecyl sulfate (Sigma Ultra grade) was purchased from Sigma-Aldrich and was used without further purification. For the neutron experiments, water was obtained from a Millipore System and D2O was supplied by EURISOTOP, CEA, Saclay. The MO seeds were obtained from a local farmer in Gaborone, Botswana and were stored at room temperature. Extraction and Purification of Protein. The MO seeds were shelled manually just before the extraction, and the kernel was ground to a powder using mortar and pestle and sieved. The extraction and purification of protein powder was made using the method of Ndabigengesere and Narasiah12 and has been described in detail previously by Kwaambwa and Maikokera.14,15 Basically, the procedure involves the following steps: (i) extraction of oil using petroleum ether (40-60 °C); (ii) filtration and retention of the solids; (iii) extraction of the water-soluble proteins with water and filtration; (iv) precipitation of the protein from 3904 DOI: 10.1021/la9031046

Table 2. Amino Acid Composition of the Extracted and Purified MO Seeds Protein componenta

mole fraction

aspartic acid 0.029 threonine 0.022 serine 0.043 glutamic acid 0.232 proline 0.070 glycine 0.124 alanine 0.056 half-cystine 0.061 valine 0.041 methionine 0.018 isoleucine 0.031 leucine 0.054 tyrosine 0.012 phenylalanine 0.030 histidine 0.019 lysine 0.009 tryptophan 0.004 arginine 0.144 a Ammonia amounted to 0.222 of the amino acid molar composition.

aqueous filtrate by addition of solid ammonium sulfate, (NH4)2SO4; (v) filtration, resuspension of protein in water followed by filtration to remove any insoluble materials; (vi) dialysis of the solution using cellulose membrane (Sigma Aldrich) with a molecular weight cutoff of 12 to 14 kDa, (vii) adsorption of the protein to a carboxymethyl cellulose column; and subsequent elution of the protein using 1 M sodium chloride solution; (viii) dialysis of the saline protein solution using again a cellulose membrane molecular weight cutoff of 12-14 kDa; and (ix) finally freeze-drying. The lyophilized protein powder was kept at ambient temperature in glass containers. To check reproducibility of the extraction and purification, elemental analysis using a Vario El Elemental Analyzer on deshelled MO seeds with and without oil and the purified protein powder. The elemental analysis data presented in Table 1 are simple averages of at least three analyses to check if the was any batch dependence. The purified protein powder was found contain 44.93% carbon, 7.5% hydrogen, 18.8% nitrogen, and 2.8% sulfur. The results for shelled seeds with oil contained 52.3% carbon, 8.7% hydrogen, 5.9% nitrogen, and 1.8% sulfur, which are not very different from the values reported by Ndabigengesere et al. (55% carbon, 8.5% hydrogen, and 6% nitrogen).13 The amino acid composition analysis for a sample of purified protein powder was done by the Department of Biochemistry and Organic Chemistry of the Uppsala University. Amino acid analysis allowed the average composition of the extracted protein to be determined. The results are shown in Table 2. The extraction procedure provides all water-soluble proteins rather than a single protein as isolated in some previous studies3,7 and thus is more typical of a water treatment process.

Experimental Section The neutron reflectivity experiment was performed on the reflectometer D17 at the Institut Laue Langevin, Grenoble (France). The time-of-flight (TOF) mode uses wavelengths from 2 to 20 A˚ to provide data over a wide range of Q simultaneously. The resolution was chosen to be on the order of 5% in the current measurements. Data were recorded at two incident angles of 0.8° and 3.5° for each sample, and the resulting reflectivity profiles Langmuir 2010, 26(6), 3902–3910

Kwaambwa et al. combined to cover a momentum transfer (Q) range between 0.01 and 0.2 A˚-1. Few samples showed significant measurable signal beyond 0.2 A˚-1, although data could be recorded up to 0.3 A˚-1. The substrate for adsorption was the oxide layer on a silicon crystal cut to expose the (111) face. Before use, the silicon crystal was cleaned with dilute Piranha solution as described by Turner31 with a concentration 5:4:1 of water, concentrated sulfuric acid, and 30% H2O2 at a temperature of between 70 and 80 °C for 15 min. Note that although this reagent is less aggressive than the common “Piranha solution”, protective clothing is essential. The surface was then rinsed extensively with Millipore pure water. The back glass surface of the cell was cleaned in the same way and then further cleaned by UV-ozone oxidation for 10 min and further rinsed with Millipore pure water. The other parts of the cell and connecting tubing were cleaned with Decon90 and then rinsed copiously with water. A PTFE gasket with inlet and outlet ports was clamped between the freshly cleaned surface of a polished silicon block and a borosilicate glass backing plate. The area of polished surface was 50  50 mm2. The cell normally required about 2 mL solution to fill. The neutron beam illuminated an area that was about 3.5 cm  3 cm; its exact size was defined by the horizontal and vertical slits placed before the sample setup. Data were reduced by integrating the counts in the region of the specular peak for each wavelength and normalizing this with the intensity of the direct beam at the corresponding wavelength that was determined from a separate measurement of transmission through the silicon crystal. The background was estimated from the observed counts on the two-dimensional detector at higher and lower angles than the specular reflection. These were normalized for the area of integration and subtracted so as to provide reflectivity curves that could be modeled without any subsequent specific inclusion of the background. The measurements were made at 25 °C according to the following protocol. The sample solutions were obtained by directly dissolving the protein powder in pure D2O. Stock solutions of 0.05 wt % of protein in D2O and 12 mM SDS in D2O were used to make samples for all measurements. The mixtures and final concentrations were obtained by directly mixing the desired ratios of solutions using a Knauer Smartline HPLC pump with a four-channel input and degasser with an output from the mixing chamber that was connected directly to the filling port of the cell. The concentrations of adsorbate and isotopic mixtures of H2O and D2O could thus be programmed directly from the instrument control computer. Changes of sample solution were made by flushing a minimum of 15 mL of solution through the cell at a rate of 2.0 mL min-1. The protein concentrations used were 0.001%, 0.005%, 0.01%, 0.025%, and 0.05%. Binding of surfactant to the adsorbed layer was studied by exposing preadsorbed layer of protein to solutions of SDS with concentrations of 0.12, 0.24, 0.48, 0.96, 2, and 12 mM. Note that the highest SDS concentration used is above the critical micelle concentration (cmc) of the surfactant (i.e., about 8.2 mM at room temperature32). For the present study, adequate fits of models to the experimental data could be obtained by including just two layers at the interface with a smooth exponential decay in composition from that of the outer layer to that of the bulk solution. The inner layer was used to model the oxide at the surface of the silicon crystal. Modeling of reflectivity data were made using the special software programs DRYDOC, LPROF, and CPROF for polymers at interfaces by Rennie.33 (31) Turner, S. F. PhD Thesis, Cambridge University, United Kingdom, 1998. (32) Holmberg, K., Ed. Handbook of Applied Surface and Colloid Chemistry; John Wiley & Sons Ltd.: New York, 2001. (33) Rennie, A. R. http://material.fysik.uu.se/Group_members/adrian/cprof. htm. & http://material.fysik.uu.se/Group_members/adrian/drydoc.htm

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Results and Discussion Extraction and Purification of Protein. As pointed out earlier, numerous studies have reported that the active components in MO seeds are soluble cationic proteins and peptides with molecular weight ranging from 6 to 16 kDa.7,13 One of these peptides named MO2.1 was purified and sequenced and was shown to have flocculent activity on a glass powder suspension7 and toward bacteria and clay.3 A nonprotein component of 3 kDa from MO seeds tested also showed to have flocculation activity when tested against kaolin suspension.9,10 Recently, Sharma et al. reported the isolation of even larger molecular weight protein of about 66 kDa having coagulation activity comparable to that of cationic peptides and aluminum salt on soil suspension.34 The method of extraction and purification seems to have a played a crucial role in the molecular weight of the resulting protein or peptide extract. As indicated by previous work discussed above, there are likely to be several distinct proteins obtained from the seeds of MO trees depending on the method of extraction and purification protocol used. The present study has been made with an extract that is likely to correspond to the material used in the practical application of water purification. The amino acid analysis suggests that it cannot be a single protein with molecular mass in the range of 7 kDa. A range of other studies have indicated that the proteins aggregate in solution, although at very low concentrations, they may be just dimers. For instance, determination of the molecular weight of the proteins extracted from MO seeds by molecular sieving done by Ndabigengesere et al.13 showed molecular weight of 6.5 kDa under reducing conditions and 13 kDa under nonreducing conditions. Their results further showed that the native protein was dimeric of 13 kDa with subunits of about 6.5 kDa linked by S-S bonds. In reducing conditions, the results confirmed the suggestion by Gassen et al.35 that the active proteins have a molecular weight of 6.5 kDa. Both monomers and dimers retain their coagulant properties. Characterization of the Substrate. The neutron reflection experiments were used to measure the adsorption of MO seed protein to hydrophilic silicon oxide surface. A summary of the densities and scattering lengths of the materials used is provided in Table 3. Si (111) surfaces were chosen, because they are known not to form thick native oxide layers in contrast to the behavior of Si (100) surfaces. Care was taken in the cleaning to use the minimum necessary oxidation; in particular, these surfaces were cleaned in a dilute piranha solution and were only subject to short exposure to UV-ozone in order to clean the substrate. This is desirable, as a thin oxide layer increases the sensitivity of the experiment to small amounts of adsorption. To characterize the silicon oxide layer, reflectivity profiles were first measured in pure water with different isotopic contrasts D2O, H2O, and refractive index (or contrast) matched to Si (cmSi) in this order. Plots of the neutron reflection curves for these three liquids against the clean substrate are shown in Figure 1. D2O was used to highlight the oxide layer so that its thickness and composition were well-determined. The data were fitted in a combined fit of three contrasts to a model which included 8 A˚ of SiO2 on the surface of the Si crystal as illustrated in Figure 1. The observed thickness of oxide of 8 ( 3 A˚ with 5 A˚ roughness and scattering length density (F) equal to 3.41  10-6 A˚ correspond well with previous work of one of the present authors25 for native SiO2 and (34) Sharma, A. K.; Agrawal, H.; Shee, C. Res. J. Agric. Biol. Sci. 2007, 3, 418– 421. (35) Gassen, H. G.; Gassenschmidt, U; Jany, K. D.; Tauscher, B.; Wolf, S. Biol. Chem. Hoppe-Seyler 1990, 371, 768–769.

DOI: 10.1021/la9031046

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Kwaambwa et al. Table 3. Materials Used in the Study;Neutron Scattering Lengths and Scattering Length Densities name

formula

RMM

density/g cm-3

molecular volume/A˚3

scattering length Σ b/fm

F/10-6 A˚-2

water H2O 18 0.9975 30 -1.7 -0.56 20 1.105 30 19.1 6.35 heavy water D2O silicon Si 28 2.33 20 4.15 2.07 60 1.88 46 15.8 3.41 silicon oxide SiO2 288.4 1.01 474 15.6 0.33 sodium dodecyl sulfate CH3(CH2)11OSO-3 Naþ 7307a 1.35b 9.12  103 1312 1.46 Moringa protein in H2O c a b 3 7385 1.36 9.12  10 2337 2.60 Moringa protein in D2O a Molecular mass estimated using the Protein Calculator45 using the amino acid sequence by Gassenschmidt et al.7 The composition data is taken from Table 2. b Density value from Maikokera.46 c These values make allowance for exchangeable protons and assume the same molecular volume as in H2O.

Figure 1. Reflectivity curves for the oxide layer characterization using D2O (dark cycles), H2O (squares), and cmSi (triangles). The solid lines show a fit for a model that corresponds to 8 A˚ of oxide with a roughness of 5 A˚.

are in the range that is observed by other authors in recent studies36-39of similar substrates. The value of F indicates a smooth oxide surface without any penetration of the D2O; the mixing of D2O would indicate the presence of defects over the interface.40 As with other figures, the line showing the fit is drawn over the region of Q included in the minimization. This was selected so as to exclude possible systematic errors from background subtraction. The general aspects of reliability of model fits are discussed further below. Effect of Protein Concentration. After characterization of the oxide layer, the protein adsorbed scans were taken. To provide increased scattering length density contrast for the adsorbed protein layers, all neutron solutions were prepared in D2O instead of H2O. Figure 2 shows the reflectivity profiles of the adsorbed layer at different protein concentrations. The data were fitted to models which included 8 A˚ of SiO2 on the surface of the Si crystal and a simple model for the adsorbed protein that consisted of a uniform layer near the surface and an exponential decay in the density of protein to that in the bulk solution as illustrated in Figure 3a for 0.005% protein and Figure 3b 0.05% protein. It can be seen clearly from the data in Figure 2 that an increase in protein concentration causes a marked deviation of the reflectivity from that obtained from the solid/D2O interface that increases with concentration. The reflectivity profiles become close to each other, which is an indication that the adsorption is (36) Talbot, J. P.; Barlow, D. J.; Lawrence, M. J.; Timmins, P. A.; G. Fragneto, G. Langmuir 2009, 25, 4168–4180. (37) Dabkowska, A. P.; Fragneto, G.; Hughes, A. V.; Quinn, P. J.; Lawrence, M. J. Langmuir 2009, 25, 4203–4210. (38) Mueller-Buschbaum, P.; Schulz, L.; Metwalli, E.; Moulin, J.-F.; Cubitt, R. Langmuir 2009, 25, 4235–4242. (39) Vandoolaeghe, P.; Rennie, A. R.; Campbell, R. A.; Nylander, T. Langmuir 2009, 25, 4009–4020. (40) Lu, J. R.; Pan, F.; Zhao, X.; Waigh, T. A. Biointerphases 2008, 3, FB36-FB43; doi: 10.1116/1.2965135.

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Figure 2. Reflectivity profiles showing the effect of protein concentration compared with D2O curve (data offset by -1 between successive concentrations for clarity of the profiles). In order not to obscure the data points, error bars are omitted, but typical errors can be taken from the data that are shown with fits in Figure 3. The solid lines show the reflectivity calculated for the models described by the parameters in Table 4.

tending to saturation. This behavior gives a plateau in the adsorption isotherm shown in Figure 4. The protein is observed to adsorb strongly to the silica layer on silicon even at very low concentrations (0.001 wt %). The surface excess is calculated by integrating over the density profile, and the plateau in adsorption is found to be about 5.5 mg m-2. This plateau is reached at a concentration of 0.025 wt %. The adsorption is irreversible. Rinsing with water did not remove any significant amount of material after exposure to 0.05 wt % protein solution. Fits to reflectivity were essentially the same in the presence of 0.05% protein and in water after rinsing. As the protein did not desorb, it was possible to replace the D2O with H2O to obtain a further independent data set that provides a different contrast. Simultaneous fits (reported in Table 4) of an identical physical model to both data sets using CPROF provide higher confidence in the structural data for this adsorbed layer. The model that best fits the adsorbed protein after rinsing consists of a hydrated layer of protein with about 50-60% water and then a decaying profile of protein density toward that of the bulk solution. For low concentrations, the structural parameters are less certain, but the surface excess is still reasonably well-defined. The protein forms a dense layer, and the diffuse region of decreasing density is small and on the order of the roughness of Langmuir 2010, 26(6), 3902–3910

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Article Table 4. Fitting Parameters for the Protein in D2Oa protein concentration/wt%

τp /A˚

F /10-6 A˚-2

L /A˚

φpb

Γ/mg m-2

0.0010 20 ( 4 4.9 ( 0.3 4. ( 3 0.39 1.3 ( 0.2 0.0025 26 ( 4 4.9 ( 0.3 5. ( 3 0.39 1.6 ( 0.2 0.0050 22 ( 4 4.9 ( 0.2 5. ( 3 0.39 1.4 ( 0.2 0.010 80 ( 15 5.5 ( 0.2 11. ( 3 0.28 3.0 ( 0.3 0.025 68 ( 12 4.7 ( 0.2 30. ( 5 0.43 5.7 ( 0.3 0.050 70 ( 9 4.8 ( 0.2 31. ( 3 0.42 5.7 ( 0.3 67 ( 5 4.7 ( 0.2 27. ( 3 0.44 5.7 ( 0.3 after rinsingc a Oxide layer, τoxide = 8 ( 3 A˚, τp = layer thickness, F = scattering length density for the adsorbed layer, L = Exponential decay length, φp = volume fraction of protein in the layer. b φ is calculated from the fitted value of F and the data in Table 3. c The constrained simultaneous fit to the same structural model for both contrasts (D2O and H2O) with CPROF gave F = 0.35  10-6 A˚-2 for the adsorbed layer in H2O.

Figure 3. Reflectivity data for protein solutions in D2O showing the model fits (continuous line) for (a) 0.005% protein and (b) 0.05% protein. The insets are the corresponding scattering length density profiles of the adsorbed layer.

the underlying substrate. For maximum adsorption, the decay length of the exponential profile was about 35 A˚, and the dense, near surface layer was typically about 60 to 70 A˚. Examples of the density profiles are shown as insets in Figure 3. The thickness of the protein layers is somewhat larger than expected for single protein molecules of about 7 kDa but not inconsistent with molecules that are observed to associate in solution (as seen by surface tension and circular dichroism).14,16 The possible effects of kinetics or time on adsorption could not be followed in these experiments. A minimum time of 7.5 min was taken to flush each new solution through the cell. The measuring time of about 1.5 h for the reflectivity profiles preclude studies of quick kinetics. Checks were made that data measured after 40 min were identical to the previous data. This experimental protocol allows time for equilibration; the low molecular mass protein can diffuse rapidly, and so it is unsurprising that kinetic effects were not observed. Effect of SDS. Measurements made after rinsing the silica surface that had been exposed to protein with water (see Figure 5) indicated that there was no significant desorption. Further experiments were then made by exposing solutions of SDS in D2O to the interface. The reflectivity data are presented in Figure 6, and model fits for 2 mM and 12 mM SDS are shown in Figure 7. In Figure 6, there is a trend with increasing concentration up to 2 mM SDS with a change in slope of the curves becoming more apparent at about 0.04 A˚-1. The substrate was rinsed with D2O after exposure to 2 mM SDS, and the measured reflectivity is substantially the same as that for the interface in the presence of the surfactant (see Figure 8). This indicates that the SDS does not remove the protein. In order to fully determine the composition and structure of a multicomponent system, it is helpful generally to use different isotopic contrasts in order to identify the different specific components. In the short measurement time available, this was not feasible, but it seems reasonable in light of the rinsing experiments to fit models to the reflectivity curves for the SDS in D2O up to 2 mM under the Langmuir 2010, 26(6), 3902–3910

Figure 4. Isotherm for the adsorption of Moringa oleifera seeds protein in D2O to SiO2 deduced from the neutron reflectivity data and fits (shown in Table 4).

Figure 5. Reflectivity data showing the effect of rinsing of the interface after protein adsorption. Dashed line, initial measurement of interface with no protein; points, data measured in the presence of 0.05 wt % protein; continuous red line, measurement in pure D2O after rinsing. The similarity of the curves measured with the protein solution and after rinsing indicate irreversible adsorption.

assumption that there is essentially an unchanged amount of the MO protein adsorbed at the surface. The extra material observed near the suface is assumed to be SDS. There is no evidence that low concentrations of SDS displace substantially the MO protein from the silica interface. Models with a layer of uniform density adsorbed to the oxide and a uniform exponential decay were again adequate to fit the data. An example of the fit is given in Figure 7a, and the parameters for all the fits are presented in Table 5. The scattering DOI: 10.1021/la9031046

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Figure 8. Effect of rinsing with water after SDS adsorption to the protein layer. Points, measurement in the presence of 2 mM SDS solution in D2O; continuous red line, measurement in pure D2O after the interface was exposed to SDS and protein. The similarity of the curves indicates that there is a substantial amount of adsorbate in a thick layer when the interface is rinsed even after exposure to SDS. Figure 6. Reflectivity profiles showing the effect of SDS concentration compared with D2O. Successive concentrations are offset by -1 for clarity. The solid lines show the reflectivity calculated for the models described by the parameters in Table 5. In order not to obscure the data points, error bars are omitted, but typical errors can be taken from the data that are shown with fits in Figure 7.

Figure 7. Reflectivity profiles showing model fits for (a) 2 mM and (b) 12 mM SDS (insets show the corresponding scattering length density profiles for the adsorbed layer in D2O).

length density of normal, hydrogenous SDS and of the protein are not very different, and so, it is not feasible at present to make a precise distinction between these components and where they are located. However, the fractions of protein, water, and SDS in the near surface layer can be estimated on the assumption that the protein to SDS ratio is constant throughout the interfacial layer. The surface excess of SDS derived in this way is also shown in Table 5. The volume fraction of SDS increases from about 3% to 3908 DOI: 10.1021/la9031046

Table 5. Fitting Parameters for Protein/SDS in D2Oa SDS concentration/mM 0.12 0.24 0.48 0.96 2.0

τ/A˚

F /10-6A˚-2

L/A˚

12 ( 3 13 ( 3 20 ( 3 21 ( 3 46 ( 4

4. 5 4.6 4.7 4.8 4.9

50 ( 5 53 ( 5 53 ( 5 52 ( 4 25 ( 3

φSDS

Γ/mg m-2

0.03 0.2 0.05 0.4 0.07 0.5 0.09 0.6 0.10 0.75 τ3 F3 12 b 15 ( 4 4.3 17 ( 3 2.5 15 ( 3 a Oxide layer layer, τoxide = 8 ( 3 A˚, τ = layer thickness, F = scattering length density for the layer, L = Exponential decay length, φSDS = volume fraction of SDS in the layer. Γ is the surface excess of SDS. bAn extra layer described by F3 and τ3 is required to adequately model this data.

10% on increasing the surfactant concentration from 0.12 to 2 mM. The volume fraction of protein in the near surface layer is just over 50%. The composition corresponds to just over 4 SDS molecules per protein molecule. This is slightly less than that found on association in bulk solution but is not unreasonable given the dense packing of protein near the surface. It is interesting to note that the dense, near surface layer is significantly thinner in the presence of SDS than in the case of pure protein adsorption. The neutralization of some of the positive charge on the protein with the anionic surfactant may assist in forming a more tightly associated layer. A further measurement was made with a concentration of SDS of 12 mM which is above the cmc32 of about 8.2 mM. As seen in Figure 6, there is a clear, sharp minimum in the reflectivity curve, and the data could no longer be modeled adequately with a single protein/surfactant layer and a uniform decay of adsorbate density to that of the bulk solution. A fit to these data and the corresponding scattering length density profile is shown for 12 mM SDS/protein in Figure 7b. The layer of low scattering length density is not very precisely defined by the single contrast available but suggests that there is strong adsorption of SDS near the surface when the protein is present. Reasonable fits could be obtained with a layer that varied between 15 and 25 A˚. However, the density difference is inversely correlated, and so, the overall composition does not change greatly with alternative reasonable fits. As the structure is complex and we were unable to make separate measurements to verify Langmuir 2010, 26(6), 3902–3910

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the amounts of protein and/or SDS at this composition or after rinsing, it would be speculative to quote values for the excess of each component at this composition. On its own, SDS does not adsorb to a silica surface at pH 7, but cooperative adsorption to interfaces has been seen with other polyelectrolytes and proteins.41 It is interesting to note that, even above the cmc of SDS, the MO protein is still bound to the interface and is not strongly displaced by solvation into micelles. Choice of Model and Reliability of Fits. It is useful to consider carefully the reliability of the interpretation of experimental data. The choice of model that is used to fit a reflectivity profile was made on the basis of finding an adequate description of the data with a minimum number of parameters. As explained above, calculations of reflectivity are based on “optical matrix method” for a number of thin layers of defined neutron refractive index. It is advantageous to reduce the number of fitted parameters by defining a function that can relate the density in successive layers if an appropriate model is available. In practice, the detailed information about an interfacial available from a restricted amount of data is limited, and it may not be possible to distinguish between certain different structures. If there is a single uniform layer, then sharp fringes define the thickness very well. If an interface is diffuse, it is possible to add a model for roughness. A Gaussian distribution of density at the interface with a characteristic width that is small compared with an adjacent layer is easily included in a model using the method of Nevot and Croce.42 When the thickness of the diffuse region is large relative to other layers, it is necessary to introduce a specific sequence of layers as a model. Detailed discussion of the regularization of fitting and inversion of data to real space43 is outside the scope of this paper. It is helpful to consider how the results would be different under the assumption of different models and what would be the effect of systematic errors in measurements or data reduction. In particular, background subtraction algorithms may lead to systematic variations in the data both at small Q when there is little contrast (for example characterization of a clean substrate in water matched to silicon) and at large Q where scattering from the solution may be significant and, if not, linearly varying with Q subtracted incorrectly. A feature of the modeling of reflectivity data of the type presented is that the surface excess is usually better determined than individual parameters for layer thickness, as the optimal regularisation of the fit parameters does not correspond to the parameters of the optical matrix layer calculations. The experiments presented have concentrated on measurements where the solution (in D2O) and the substrate have significantly different contrast. This was necessary to give a good signal, as the protein has a scattering length density that is not very different from that of silicon. Although the very simple interpretation of data measured when only the adsorbed layer provides different contrast is not available, the surface excess which is proportional to the product of the density difference of the interfacial layers and their thickness is much better defined by the data than values of either F or τ separately. This can be seen by inspection of correlation matrices for fit parameters where F is inversely correlated with τ. For the adsorbed layer of protein, the results shown have been modeled with an exponential decay in density from a uniform (41) Turner, S. F.; Clarke, S. M.; Rennie, A. R.; Thirtle, P. N.; Cooke, D. J.; Li, Z. X.; Thomas, R. K. Langmuir 1999, 15, 1017–1023. (42) Nevot, L.; Croce, P. Rev. Phys. Appl. 1980, 15, 761–779. (43) Leeb, H. In Neutron reflectometry: a probe for materials surfaces; IAEA: Vienna, 2006; pp 177-196.

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layer. At low protein concentrations, the data can equally be described by a uniform layer with a Gaussian roughness. Alternate fits have been made with a model of a uniform linear decay for the protein adsorption data. The trend is similar to that obtained with the exponential decay model, but the surface excess that is determined is about 17% lower at the highest concentrations. The fit is not as good, but the single largest factor in changing the apparent quality of fit is determination of a possible unsubtracted component of background. A small improvement of the fit can be made by including an extra “flat” background on the order of (5-10)  10-7. At low concentration, this would give an increase in the surface excess of about 20%, but the effect is insignificant at large concentrations. The insets in Figure 3 show typical profiles of scattering length density that are linearly related to protein density for the region that consists of just protein and water. For the low concentrations, the model could simply be a uniform layer with some roughness, but this does not differ significantly from the density profile described by the parameters in the table. However, it is evident that the various different models provide broadly similar descriptions of the protein structure. The surface excess is very high. At low concentrations, the layer is thinner than at higher concentrations such as 0.01 wt % where there is a clear decaying profile. It is remarkable that both the thickness of the dense near-surface layer and the decaying profile are much larger than the dimensions of a single protein molecule. This is indicative of association of the protein molecules.

Conclusions The results of this study indicate that there is strong binding of the MO seed protein to silica surfaces even at low concentrations. The plateau in the adsorption isotherm is reached at 0.025 wt %. The adsorbed layers of protein are dense and thick. The composition of the layer near the surface consists of approximately 0.4 volume fraction protein and 0.6 water. The thickness of the dense layer was observed to be more than 60 A˚ with an additional decaying density toward the bulk solution. This is indicative of strong cooperative adsorption. The adsorbed layer of the MO protein is unusual both with regards to the relatively large surface excess and in that the thickness is much larger than the unperturbed diameter of the protein molecules in solution observed from dynamic light scattering data.44 The small size of these molecules and their tendency to associate suggest that they may continue to adsorb to an interface when a larger molecule or a material that retains a globular structure would find regions of the surface effectively blocked by other molecules or steric hindrance. Although the proteins have a net positive charge at neutral pH, the range of amino acids could allow both electrostatic and hydrophobic association. There is no particular reason to expect that the material would adsorb with similar interfacial structures to other proteins that have been investigated at silica/solution interfaces. Interfacial structures have often been explained by particular aspects of a protein sequence. For example, β-casein at the silica surface is thought to be significantly affected by the n-terminal region.25 In living systems, it is to be expected that proteins will have evolved for particular mechanisms, and these may well relate to how they bind to membranes or interfaces. (44) Kwaambwa, H. M.; Rennie, A. R. Manuscript in preparation. (45) Protein Calculator v3.3; http://www.scripps.edu/cgi-bin/cdputnam/ protcalc.html. (46) Maikokera, R. PhD Thesis, University of Botswana, Botswana, 2008.

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The presence of a biopolymer layer that tends to associate strongly at the surface of particles provides a mechanism for mutual attraction. It thus can give rise to a mechanism for flocculation in concentration and size regimes that would be susceptible to neither bridging nor depletion mechanisms. In this respect, the protein resembles a surfactant as has been observed for some other proteins such as surfactin29 and latherin.30 In order to assess whether the adsorbed protein layer is altered by other surfactants, measurements were made with SDS solutions that were found to coadsorb to the irreversibly bound MO protein layer. The SDS did not displace the protein even at a concentration above the cmc. Indeed, the adsorbed layer apparently binds SDS in to a denser layer a little above the surface. Although the protein is positively charged and thus likely to bind to a negatively charged silica surface, SDS does not simply cause desorption by neutralizing the protein. It will be interesting to explore in future experiments of the adsorption of the protein to other interfaces, as it is reported to cause flocculation in water of mineral impurities, as well as both Gram-positive and Gram-

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negative bacteria.3 The dense packing in a thick layer suggests that association of the protein molecules that may be zwitterionic could be crucial in the interfacial behavior. Understanding the mechanisms of adsorption and flocculation is crucial to the search and possible use of other natural proteins in similar applications. Acknowledgment. We acknowledge funding from the University of Botswana Office of Research and Development (Round 18) and the Royal Society of Chemistry Shared Research Fund to enable H.M.K. to carry out the extraction and purification of the protein used in this work. We are grateful to the Institut Laue Langevin for provision of neutron facilities and to Dr. Bob Cubitt for his assistance with the instrument and data reduction software. Supporting Information Available: Additional information. This material is available free of charge via the Internet at http://pubs.acs.org.

Langmuir 2010, 26(6), 3902–3910