Fibrillar Î²-Lactoglobulin Gels: Part 3. Dynamic ... - ACS Publications

Biomacromolecules 2004, 5, 2430-2438

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Fibrillar β-Lactoglobulin Gels: Part 3. Dynamic Mechanical Characterization of Solvent-Induced Systems Walraj S. Gosal,†,§ Allan H. Clark,*,‡,| and Simon B Ross-Murphy† Department of Life Sciences, King’s College London, Franklin-Wilkins Building, 150 Stamford Street, London SE1 9NN, United Kingdom, and Unilever Research, Colworth House, Sharnbrook, Bedford MK44 1LQ, United Kingdom Received June 9, 2004; Revised Manuscript Received August 3, 2004

Oscillatory shear rheometry has been used to study the gelation of β-lactoglobulin at ambient in 50% v/v trifluoroethanol (TFE)/pH 7 aqueous buffer and in 50% v/v ethanol (EtOH)/water at pH 2. In contrast to what was found on heating aqueous solutions at pH 2 (Part 2 of this series), a more expected “chemical gelation”-like profile was found with modulus components G′ and G′′ crossing over as the gels formed and then with G′′ passing through a maximum. In addition, for the EtOH system, there was a significant modulus increase at long time, suggestive of a more complex two-step aggregation scheme. Modulus-concentration relationships were obtained for both systems by extrapolating cure data to infinite time. For the TFE gels, this data was accurately described by classical branching theory, although it could also be approximated by a constant power-law relationship. Only the latter described the modulus-concentration data for the gels in ethanol, but there were problems here of greater frequency dependence of the modulus values and much less certain extrapolation. Gel times for the TFE systems showed higher power laws in the concentration than could be explained by the branching theory in its simplest form being similar, in this respect, to the heat-set systems at pH 2. Such power laws were harder to establish for the EtOH gels as for these there was evidence of gel time divergence close to a critical concentration. Reduced G′/G′inf versus t/tgel data were difficult to interpret for the gels in ethanol, but for the TFE system they were consistent with previous results for the heat-set gels and approximated master curve superposition. The frequency and temperature dependences of the final gel moduli were also studied. In general, the networks induced by alcohols appeared more flexible than those obtained by heating. Introduction The self-assembly of proteins and peptides can be induced by a variety of treatments most of which initiate partial unfolding of the native monomer. Hence, methods such as thermal, mutagen, solvent, enzyme degradation, or chemically induced unfolding of the protein are possible. The denaturation of proteins in alcohol-water mixtures, in particular, is a well-documented feature of protein chemistry, leading to the formation (in most cases, and at appropriate molar concentrations of solvent) of an expanded helical conformation often referred to as the “H-state”.1-5 For β-lactoglobulin, numerous studies (for example by ORD6 and CD7 spectroscopy) have shown that the largely β-sheeted secondary structure of this protein can be converted to a mainly R-helical form upon addition of various alcohols, and at the same time, the protein expands (as shown by SAXS * To whom correspondence should be addressed. Phone: +44 (0) 20 7848 4081. Thermal Fax: +44 (0) 20 7848 4082. Plain Paper Fax: +44 (0) 20 7848 4500. E-mail: [email protected]. † King’s College London. ‡ Unilever Research. § Present Address: Astbury Centre for Structural Molecular Biology, University of Leeds, Leeds LS2 9JT, United Kingdom. | Present Address: Department of Life Sciences, King’s College London, Franklin-Wilkins Building, 150 Stamford Street, London SE1 9NN, United Kingdom.

experiments5). In addition, a partially folded intermediate (the so-called “molten globule”) is formed prior to such transformation to the “H” state.8 The “H-state” itself, however, seems to be unstable and prone to aggregation. Hence, in some cases, fibrillar aggregates have been shown to occur in alcohol-water mixtures: for example lysozyme in high molar concentrations of ethanol.9 The aggregation of the β-lactoglobulin “Hstate” has been investigated extensively by Renard and coworkers, mostly at neutral pH, and in ethanol-water mixtures.10-12 Here, a “cloudy” gel was reported in 50% v/v ethanol and shown, using confocal laser microscopy, to be composed of “fractal” clusters.10 The authors suggest that this structure probably forms through demixing of primary linear aggregates followed by the aggregation and trapping of these to form a heterogeneous gel network. However, this observation is contrary to what has been reported when a wider range of alcohols (including the use of fluorinated alcohols) are used, as well as a buffer to control the pH.13 Here, clear gels have been reported, indicating more uniform structures for the underlying networks. A clear gel is also observed as the pH is lowered to ∼2, in 50% v/v ethanolwater, and scattering techniques have shown that aggregates have a fractal dimension close to unity.10 This suggests that essentially linear fibrils are formed which interact to produce a uniform gel network (no demixing).

10.1021/bm0496615 CCC: $27.50 © 2004 American Chemical Society Published on Web 10/14/2004

Characterization of Solvent-Induced Systems

The formation of fibrillar aggregates at lower sub-critical concentrations of β-lactoglobulin in the presence of alcohols such as methanol, ethanol, propan-2-ol and trifluoroethanol (TFE) has been discussed in Part 1 of this series.14 There, evidence was presented based on studies using transmission electron microscopy (TEM), atomic force microscopy (AFM), infrared (IR) and Raman spectroscopy, and X-ray diffraction (XRD). At pH 2, well-defined fibrillar aggregates formed in all four alcohols, whereas at pH 7, only trifluoroethanol generated obviously linear species, more random clusters forming otherwise. In the present paper, this study is extended to include gel formation at higher concentrations and the preferred technique is oscillatory shear rheometry (dynamic mechanical spectroscopy) to follow shear modulus cure data. Attention is mainly focused on two of the fibril-forming systems, i.e., β-lactoglobulin in a trifluoroethanol/pH 7 buffer mixture, and the same protein in ethanol-water mixtures at pH 2. This choice was based on protein solubility in the solvents used, and the ability of the systems to form gels over convenient time scales at the concentrations possible. The results will be treated much as described in Part 2 of this series15 which described the heat-setting of β-lactoglobulin at pH 2 and analogous cure measurement. However, a particular aim will be to compare solvent-induced gelation of this protein with gelling by heat treatment. Issues such as long time limiting moduli, gel times, the mathematical forms of cure data, and the frequency and temperature dependences of moduli will all receive attention. Some preliminary experimental data have already been reported16 but without any such detailed analysis. The study of the fibrillar aggregation and gelation of β-lactoglobulin is important for two reasons. First, the solgel transition is of practical industrial importance as a means of structuring fluids (e.g., in the food industry), and second, the filamentous aggregation of proteins is of general interest, as this phenomenon seems to be an important element in the generation of disease states (e.g., amyloid disorders) through the malfunction of protein components. Of course neither practical aspect is directly relevant to the present nonaqueous solvent systems, but the latter are aids to understanding the underlying mechanisms of fibrillar selfassembly. This is currently an area of major interest in its own right. Materials and Methods In contrast to thermally induced systems, only a very few rheological studies of solvent-induced gels have been reported for β-lactoglobulin.10-12 The investigation presented here is both an extension of work described in Part 2 of this series,15 and a demonstration of the contrasting systems obtained by the two approaches. The two systems investigated using in situ oscillatory shear techniques were TFEinduced pH 7 and ethanol-induced pH 2 gels. Both of these are, on the basis of, for example, the microscopy work of Part 1 of this series,14 considered to be fibrillar. The alcohol content in each case was fixed at 50% v/v. (A systematic investigation of the consequences of varying this parameter was not undertaken and remains for future work.)

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Sample Preparation. Lyophilised β-lactoglobulin AB (Sigma Chemicals, Dorset, UK) from bovine milk (product code L-0130, lot number 21K7079) was left to dissolve in de-ionized water (Milli-Q purification system, Millipore Limited, Watford, UK) for 1 h on a vibrating platform (Vibrax-VXR, IKA-Werke GmbH & Co., Staufen, Germany). The pH was monitored with the use of a combination microelectrode (Radiometer Limited, Crawley, UK) and the pH of native solutions was found to be 7.1 ( 0.05. Where required, the pH was adjusted from 7.1 to pH 2 ( 0.05, with the use of 1M HCl (BDH, UK). For pH 7 alcohol-water samples, β-lactoglobulin was dissolved in a 20 mM phosphate buffer, pH 7, to control the pH. The resulting β-lactoglobulin solution was filtered with the use of a 0.2 µm syringe filter (Acrodisc PF 0.8/0.2 µm, Gelman Sciences, UK) to yield an optically clear liquid. Samples for solventinduced gel-formation experiments were diluted with the appropriate amount of alcohol and gently agitated for a few seconds whereupon homogeneous solutions were obtained. The alcohols used were 2,2,2, trifluoroethanol (Fluka Chemika), ethanol and methanol (AnalaR, BDH, Poole, UK), and propan-2-ol (HPLC Grade, May & Baker, Dagenham, UK). The protein solutions were then immediately loaded onto the rheometer, and the “delay-time” was noted. These delay times were usually ∼5 min and were added to the experimental time coordinate in all cases. The importance of correctly establishing the true time origin of cure data has been discussed and illustrated in Part 2 of this series.15 Dynamic Oscillatory Measurements. β-lactoglobulin gelformation induced by alcohols was monitored in situ using servo-controlled strain-controlled measurements on a constant stress rheometer. (The advantages and limitations of this approach are detailed in Part 2 of this series.15) For the present experiments, 1.4 mL of solution were pipetted onto the instrument (CSL 100, T.A Instruments, UK) and oscillatory measurements (ω ) 1 rad/s, nominal strain γ ) 1%) made at 20 °C. The geometry used was a 40 mm 4° metallic cone, with a nominal truncation length 100 µm, quoted value 99 µm supplied by T.A Instruments. Modifications were made to the instrument in order to handle very low viscosity sols using accessories designed and constructed at the King’s College Instrument Development Unit. This was necessary since solvent-containing samples tended to flow across the bottom plate, before the top plate could be lowered and measurements could be made. To avoid this, a split ring was used (stainless steel, inner diameter ∼41 mm). The advantage here was that once the top plate was lowered the split-ring could be removed, since the surface tension of the sample was sufficient to retain it centrally between cone and bottom plate. Any excess sample was blotted away with filter paper, and paraffin oil (GPR grade, BDH, UK) was layered around exposed regions. A solvent-trap cover-slip was also used to prevent evaporation and a water-solvent mixture was added to the solvent-trap well. A false bottom plate (stainless steel, thickness ∼2 mm) was used to prevent damage to the original bottom plate from harsh solvents such as TFE. These precautions are the best that can be taken, but cannot guarantee that long-time solvent

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evaporation does not occur; for this, a sealed and pressurized assembly would be needed. Results and Discussion Preliminary Observations. Essentially transparent gels were formed in all of the solvents tested, although the precise degree of transparency varied both with the alcohol used and the pH. Often, apparently high viscosity fluids (“pre-gel” state) were formed after many months. As always with such systems it was difficult to establish whether a gel had formed without recourse to rheological analysis. At pH 7, the propensity of a sample for gel-formation in the different solvents (concentration ∼8% w/v β-lactoglobulin), was propan-2-ol > ethanol > TFE ∼ methanol. However, gels with a much lower critical concentration were formed in TFE. Also, at concentrations above ∼8% w/v, the solubility of β-lactoglobulin in 50% v/v propan-2-ol was very low, and white precipitates were formed immediately upon addition of this alcohol, in agreement with previous observations in the literature.17 As this insolubility behavior was also exhibited to some extent in ethanol and methanol solutions, pH 7 studies focused on gelling in the presence of TFE. At pH 2, the pattern was altered, and here the gelation tendency was methanol > ethanol > propan-2-ol > TFE. It was interesting to note that the observed critical concentration (C0) of gels formed in TFE was now as high as 10% w/v, and at concentrations below this, solutions seemed to form very small amounts of precipitate over many months, rather than high viscosity fluids. Because of these disadvantages, studies at pH 2 focused on gels induced in the ethanolwater mixture. The effects of the various alcohol-water solvents on gelling clearly show a complex pattern, but the results are reasonably consistent with those obtained on aggregate morphology and discussed in Part 1 of this series.14 For example, TFE-mediated self-assembly at pH 7 led to the observation of long fibrils (∼500 nm), whereas for the other solvents at this pH, random clustering seemed to predominate (suggesting an altered aggregation mechanism). Fibrils formed in all four solvents at pH 2. Thus, in keeping with the previous rheological study15 of heat-set gels at pH 2 (Part 2), the current rheological measurements were directed at gels whose underlying networks were likely to be based on the uniform cross-linking of well-defined preformed linear aggregates (fibrils). Cure Curves. Cure data (G′ versus time) obtained for the two systems studied here are presented in Figures 1 and 2 in the usual log-log display. In practice, significance in the data is not seen for G′ < ∼0.2 Pa, but lower values are shown for interest. Concentrations range from 7% w/v to 14% w/v for β-lactoglobulin in TFE/pH 7 buffer and from 5% w/v to 8% w/v for the protein in ethanol (EtOH)/water at pH 2. In both cases, the data show the form characteristic of gelling biopolymer solutions.15 In a later section, superposition of such data will be discussed. One thing that is immediately clear, in most of the ethanol data, is the presence of a second phase of gelation beginning after several thousand seconds and involving a secondary

Figure 1. G′ versus time, cure data, for β-lactoglobulin gelled at ambient in a 50% v/v trifluoroethanol (TFE)/aqueous pH 7 buffer solvent. For experimental details see text.

Figure 2. G′ versus time, cure data, for β-lactoglobulin gelled at ambient in a 50% v/v ethanol (EtOH)/aqueous pH 2 solvent. For experimental details see text.

increase in the modulus. This is much less evident in the TFE results though there may be a similar effect at the highest two concentrations (see later). In the ethanol case, the modulus achieved during the first stage of gelation is significantly smaller than is found for TFE at pH 7 and, in consequence, the details of initial modulus growth during this period have been measured less extensively and less accurately. Some further insights may be obtained by selecting two examples of comparable gel time from the two sets of cure data and comparing them directly, including values for the loss component of the modulus (G′′ versus time). This is done in Figure 3 for the 14% w/v TFE and 7% w/v EtOH data. A first observation is that, in contrast to the heat-set systems,15 G′′ is initially greater than G′, and then the order is reversed at, or just after, the gel point. Subsequently, G′ becomes significantly greater than G′′ as gelation proceeds. Such a crossover in the modulus components was absent from the corresponding data15 for heat-setting β-lactoglobulin at pH 2, where starting solutions showed initial “solid” character (G′ greater than G′′) a fact that was ascribed to “structuring” through protein repulsion. This structuring effect is evidently absent for both the pH 7 and pH 2 solventinduced gelling solutions studied here. To our knowledge, the behavior seen here for the solvent gels has never been observed for heat-set systems and is a clear signature of a difference in the mechanism and/or kinetics of self-assembly.


Figure 3. Comparison of G′, G′′ versus time cure data for 14% w/v TFE pH 7 and 7% w/v EtOH pH 2 solutions. For experimental details see text.

A further distinction which can be made is the presence of a maximum in G′′ for the TFE pH 7 system some time after gelation. This feature has been found for other gelling systems, such as gelatin,18 poly(dimethylsiloxane), urethanes, and epoxies,19 and has been assigned tentatively as a measure of the underlying flexibility of the network.19 Bibbo and Valles,19 in particular, have studied this phenomenon by following the evolution of G′′ during the curing of vinylterminated poly(dimethylsiloxane). Here, at the gel-point, G′′ increased and reached a maximum, and then decreased to a final plateau value as the extent of curing increased. The maximum in G′′ corresponded to the maximum amount of pendant or “dangling chain ends” (one end “fixed” at a crosslink, whereas the other end is free to reptate) present within the network, the relaxations of which contribute to the loss modulus. In the present work, the maximum was less evident for the EtOH/water systems but did appear at longer times in the higher concentration cure curves (Figure 3). It seemed to arise at the point where the suggested second phase of gelation was just beginning. The explanation offered above for the maximum in G′′ implies that this can be correlated with the molecular architecture of the network. It was therefore of interest to see whether it could be observed in other situations such as when ethanol was used at pH 7 where the molecular architecture was known to be different (random clusters as opposed to more uniform fibrillar aggregation).10-12,14 In fact cure-curve data measured at the same concentration in the presence of methanol, ethanol, and propan-2-ol at pH 7, while displaying similarities to data from the TFE-induced system, showed no maximum in G′′, at least within the limited experimental time (∼18-20 h) employed. Within this time limitation, therefore, the results were consistent with our earlier microscopy data14 which showed much fewer fibrils (relative to clustered aggregation) in aggregates from these systems and with cure data obtained by Renard and coworkers for gels formed in ethanol at pH 7.10-12 They seemed also to re-enforce the assignment of a maximum in G′′ to the relaxation of pendant chains. A final observation from Figure 3 is the much more extended time region after the gel point for which G′ and G′′ have comparable values that is shown by the EtOH system. The TFE system response, on the other hand, is much


Figure 4. Data of Figure 1 re-plotted as log G′ versus 1/time. Solid lines indicate extrapolations used to estimate long-time limiting modulus values G′inf.

Figure 5. Data of Figure 2 re-plotted as log G′ versus 1/time. Solid lines indicate extrapolations used to estimate long-time limiting modulus values G′inf.

more what is expected for a strongly gelling biopolymer solution, with the divergence between G′ and G′′ becoming large, particularly after the maximum in G′′ is reached. For the EtOH system, G′ only begins to increase significantly relative to G′′ at very long times when the second cure feature is beginning to appear. It is tempting to conclude, therefore, that the more liquidlike initial response, in ethanol at pH 2, indicates entanglement of the fibrils rather than true gel formation. This may be followed by a more genuine longtime process of cross-linking (the second process), or some other form of network “ripening”, as is seen in the logarithmic phase of G′ growth for gelatin gels.18 However, caution is required, as it could also indicate an artifact such as loss of solvent occurring despite the careful precautions taken to prevent this. Concentration Dependence of the Long-Time Limiting Modulus (G′inf). As in the previous treatment of the cure data for heat-set β-lactoglobulin,15 plots of the cure data as log G′ versus 1/time were used to obtain extrapolated values for the shear modulus at long times (referred to as G′inf values). The plots are shown in Figures 4 and 5 for the TFE and EtOH systems, respectively. In neither case is the extrapolation straightforward. Even for the TFE system, there is evidence of a late increase in modulus at long times (at the highest concentrations), and for the EtOH gelling systems, this effect dominates, presumably as a result of the second network-building process referred to above.

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Figure 6. log-log displays of G′inf versus concentration data for TFE pH 7 and EtOH pH 2 gel series. Best-fitting power law (solid lines) and branching theory cascade (open circles) models are also shown together with corresponding power law indices and the predicted (cascade) critical concentration for TFE pH 7.

Meaningful extrapolation of data of this kind is usually only possible if a well-defined linear phase of modulus increase can be identified at the longest times. Curvature of the kind evident to some extent in Figure 4, and to a large extent in Figure 5, presents a real difficulty. If, however, the curvature is believed to represent either a secondary gelling event or an artifact such as drying or slippage as was discussed in the previous paper15 on heat-set systems, a second strategy can be adopted. This is to extrapolate any linear part of the plot just before the region of curvature and assume that G′inf values obtained in this way are representative of kinetic processes occurring during the initial phases of gelation. This procedure was adopted here for both systems as indicated by the straight lines in the Figures though its limitations and uncertainties are recognized. Plots of the G′inf values obtained by these forms of extrapolation, against protein concentration (w/v), appear in Figure 6. Both sets of data can be described by power-law relationships, the EtOH data fitting a straight line in loglog display extremely well. As discussed at some length for the heat-set modulus-concentration data,15 however, such power-law descriptions, which are usually based on selfsimilar fractal models for the networks,20,21 imply zero critical concentration for gelation, something which seems physically implausible. In addition, where a fractal description is applied, the power-law indices can be used to calculate corresponding fractal dimensions. In this case the very different values for the indices (n ) 2.6 and 11.4), which are found, suggest very different fractal dimensions for the gels. This again is strange from a physical perspective given the expected similarity in network form (uniform fibrillar structures) for these systems. A fit using an alternative model, the random f-functional branching (cascade) theory approach,22-25 is also indicated in Figure 6 for the TFE system. Here a percolation threshold is predicted and a corresponding critical concentration (C0) of 2.9% w/v determined. In the region of measurement, the data are evidently fitted slightly better by the branching theory than by the power law. Not surprisingly, however, given the success of the power law in describing the EtOH modulus data, a much less satisfactory cascade fit was obtained for this last (not shown), but it should be noted

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Figure 7. G′, G′′ cure data for the 10% w/v TFE pH7 solution showing two methods of estimating gel times adopted in the data analysis.

that, in the EtOH case, the limiting modulus values are particularly uncertain. This is partly because of the difficulties highlighted above in making convincing extrapolations but also relates to the values found for the individual G′ and G" components (Figure 3) and their ratio tanδ. The magnitude of the latter suggests a significant frequency dependence of the modulus for the gels in EtOH and this inevitably complicates any theoretical description of the modulusconcentration relationship. Concentration Dependence of the Gel Time. The existence of a well-defined crossover point for G′ and G′′ in the cure curves of nearly all of the gelling solutions studied here suggested that this feature should provide the best means of estimating the gel times. This would be consistent with current practice in biopolymer gel studies though it is emphasized that it is not what is suggested by the WinterChambon criterion26 developed for rather simpler covalently cross-linked synthetic polymer networks. There, the condition is that the tanδ ratio should be independent of frequency which is only sometimes true when this ratio is unity as the choice of G′ ) G′′ implies. Here, however, the simpler crossover criterion was accepted in the absence of such detailed frequency dependent measurements. At the same time, it was recognized that in previous studies of the heat-set systems15 gel times had been based on a socalled logarithmic divergence criterion.27 There, in the absence of a G′, G′′ crossover point, the gel time was identified as the time at which (on a log-log display) G′ began to increase rapidly. For reasons of consistency, where feasible, this point was also sought in the present work as an alternative gel time measure and compared with the estimate from the crossover. A typical situation is shown in Figures 7 and 8 for the TFE pH 7 10% w/v, and EtOH pH 2 5.5% w/v, systems, respectively. Although the G′, G′′ crossover points are readily identified in both cases, there is no doubt that noise in the data makes the logarithmic discontinuity much harder to determine accurately. Nonetheless, such a point of initial modulus rise against the solution background value appears to exist, and in both figures, the suggested gel time is significantly lower than that from the crossover. A factor of roughly two is found (independent of concentration) for the TFE system but a much larger factor (concentration dependent) for the EtOH example.


Figure 8. G′, G′′ cure data for the 5.5% w/v EtOH pH 2 solution showing two methods of estimating gel times adopted in the data analysis.

Gel times measured by both approaches are plotted against concentration in Figure 9. For the TFE pH 7 system, the results of both estimates are fitted well by power laws with indices n ) -4.1 and -4.3 which are somewhat smaller than the corresponding values (between 5 and 6) found for heat-set gelation.15 In the TFE case, the choice of gel time criterion does not seem to be of great significance. For the EtOH pH 2 system, on the other hand, there is a greater discrepancy, the crossover criterion providing relatively longer gel times at the lowest concentrations. Power law fits, if calculated for these data, would clearly give higher negative indices than found for the TFE gels and at the same time would not be particularly convincing. It is possible, however, that for these weaker EtOH gels a transition in gel time behavior24,28 is being observed from a region of logarithmic divergence (close to a critical concentration) to a fixed power law region such as is shown by the TFE pH 7 systems. Such divergent behavior at a critical concentration followed by fixed power law behavior is indeed anticipated by the branching theory24 of gelation. A power law extended indefinitely to lower concentrations is, of course, inconsistent with any form of percolation threshold. In the present EtOH case, if this interpretation is correct, the critical concentration would lie roughly around 4-5% w/v. As was discussed previously for the heat-set pH 2 gels,15 the quite large power law index estimates for the TFE system (∼-4) are inconsistent with the branching theory (cascade) description of the network-building kinetics in simplest form (index prediction -1). A similar situation may also occur for the EtOH gels, but it is impossible to verify this from the present data alone, on account of the apparent divergence of the gel time and lack of sufficient power law data at higher concentrations. For the heat-set pH 2 gels,15 the high power laws for the gel time concentration relationships were explained in terms of a cooperative nucleation and growth model which introduced fibrillar aggregates into a random cross-linking (network-building) process, this being consistent with ex situ time-lapse AFM studies.14 While it is tempting to propose a similar explanation for the power laws obtained here for the TFE/water pH 7 system (Figure 9), similar AFM experiments14 suggest a different, and apparently much less cooperative, fibril assembly. According to the microscopy,


Figure 9. log-log displays of gel time versus concentration data for the TFE pH 7 and EtOH pH 2 gel series. Best-fitting power law descriptions (solid lines) are also shown together with corresponding power law indices. Results from both methods of gel time estimation are compared.

this appears to be more a random linear aggregation of preformed oligomers than direct nucleation and growth of fibrils. It appears that only if the oligomers, themselves, arise through rate-determining nucleation and growth can the present gel time results also be explained by cooperativity. So far, however, no direct evidence has been obtained to support this mechanism and it must remain a subject for future exploration. Reduction of Cure Curve Data. As discussed at some length in Part 2 of this series15 on heat-set β-lactoglobulin gels, it is of interest to recalculate cure data in the reduced form G′/G′inf versus t/tgel using G′inf and tgel estimates. These reduced cure curves can be plotted in log-log form for the different concentrations studied, and the results compared with the predictions of kinetic models.28 In particular, it is important to discover if the curves obtained superimpose within experimental error, and so indicate universal behavior. Recent publications29-31 on a range of gelling biopolymer systems have suggested that such superposition is to be expected, possibly on account of the fractal nature of the underlying networks. Classical theories, on the other hand suggest that over a wide enough concentration range significant dispersion of the cure curve shape will occur showing an absence of true universal character.28 Interestingly, the previous study of the heat-set β-lactoglobulin gels15 found a reasonable approximation to master curve behavior for gels at both 75 and 80 °C albeit over a restricted experimental concentration range. The present data for the TFE pH 7 system was treated in this way using the gel times and G′inf values discussed in the last two sections. The results appear in Figure 10 and do not depend significantly on the choice of gel time criterion used (i.e., discontinuity or crossover method). The only difference is an overall systematic shift of the curves along the reduced time axis depending on the method used. The data presented in Figure 10 were obtained using the discontinuity approach to the gel time, so that direct comparison could be made with the previous heat-set gel data.15 Consistent with the latter, there appears to be a good approximation to master curve form though, of course, the logarithmic display is forgiving in this respect. Again, there

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Figure 10. log-log display of G′ cure data for the TFE pH 7 gel series after reduction using G′inf and tgel values.

Figure 11. Data of Figure 10 (filled symbols) are compared with corresponding data for heat-set gels (80 °C) from ref 15 (open symbols).

is also the fact that the gel data extend over only a limited concentration range (more precisely over a limited range of C/C0). In Figure 11, the TFE results are put on the same graph as some of the reduced cure data (80 °C) for the heat-set gels.15 The appearance is of two families of quite closely overlapping curves of very similar shape, one displaced relative to the other along the log reduced time axis. The only other obvious differences are at long reduced times where aberrations appear caused by (it is assumed) gels slipping (heat-set) or drying (solvent-induced) or perhaps showing real, additional, long-time gelling events. Figure 11 can be interpreted in two ways. On one hand, it could be concluded that, whatever may be true for the individual types of gelation, these systems do not show common universal behavior and are distinguishable (either because different types of gelation are involved or because they are gelling at different ratios of concentration to critical concentration28). Another view would be that all of these data can be superimposed by a small horizontal shift along the reduced time axis. Cure data showing different modulus behavior for the starting solutions (“structured” liquid in heatset case versus G′, G′′ crossover for TFE) might make it impossible to make precisely equivalent gel time estimates even when using what was intended to be the same criterion. Systematic differences might prevail. If the latter is true, then it might be concluded that there is little fundamental

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Figure 12. log-log display of G′ cure data for the EtOH pH 2 gel series after reduction using G′inf and tgel values.

difference in kinetics between the heat-induced gels of ref 15 and the solvent-induced fibrillar gels studied here. A decision between these alternatives will need more measurement and probably extensive computer modeling of fibrillar gelation processes to better understand their properties and implications. A start to such modeling has been described in a previous publication.28 For the EtOH pH 2 system, on the other hand, the results of cure curve reduction are somewhat different. If the crossover gel times are used, the reduced cure curves are spread widely across the reduced time axis and seem to make little sense in this form. This may be a genuine result requiring an explanation, but in fact, a simpler appearance is obtained using gel times from the discontinuity method (Figure 12). The difference appears to arise from the highly concentration-dependent discrepancy between gel times from the two methods and, although the results in Figure 12 are not as well superimposed as those in Figure 10 and are subject to much more scatter in the points, curve shapes at the lower reduced times are comparable. The existence of the second longer-time gelation event is also clearly visible through the general upturn in the curves at long time. Cure data for the EtOH system, however, must be viewed with caution, since if an entangled fibrillar network is formed first, rather than a more permanent gel network, there will be a significant dependence of the shear modulus on measurement frequency, and the cure curves reported were recorded at one fixed frequency only. Some discussion of the frequency dependence of the modulus for the two systems is now given. Frequency and Temperature Dependence of the Modulus. In addition to monitoring the curing process, frequency sweeps on “fully cured” gels (both TFE and EtOH series after ∼16 h at 20 °C), were also considered. These frequency sweeps (for examples see Figure 13) gave very similar results to those obtained for the thermally induced gels,15 the modulus components generally showing low frequency dependence. Only at lower concentrations, and particularly where the low modulus EtOH gels were concerned, was there a significant frequency dependence (Figure 13A) and a lower G′/G′′ ratio. Nevertheless, on the basis of the frequency sweeps, the classification of these systems was still that of a gel, rather than an “entanglement system”.32 However, one should point out that, in the case of the EtOH pH 2 gels,



at a certain temperature threshold. Again, these findings are tentative, being subject to uncertainties relating to incomplete curing and, in the EtOH case, a greater frequency dependence of the modulus. If verified, some of these temperature effects may correlate with changes in the solvent dielectric constant with temperature. Recently, CD experiments have been employed to monitor the secondary and tertiary structure of β-lactoglobulin in polar solvents.8,33 In this case, the onset of denaturation was shown to begin at ∼ 70, leading to significant population of the “molten-globule” conformation (secondary structure mostly native, but tertiary structure “fluidlike”) and a maximum population of this species at ∼ 60 (∼30-70%). On a further decrease of polarity, the maximum helical content was induced at ∼ 50, which coincides closely with the apparent upturn in modulus found here for G′ and G′′ in ethanol (corresponding ∼ 48). Conclusion

Figure 13. Frequency sweeps conducted after 16 h curing for (A) 5% w/v β-lactoglobulin in 50% v/v ethanol (20 °C, pH 2), (B) 8% w/v β-lactoglobulin in 50% v/v ethanol (20 °C, pH 2), and (C) 10% w/v β-lactoglobulin in 50% v/v TFE (20 °C, pH 7).

these data referred to gels formed at long time after the apparent second gelling event had occurred. The cure data suggests that a less convincing gellike response would have been found at shorter times. Additional frequency sweep data were also collected over a range of temperatures (20-45 °C) by “equilibrating” the (16 h) gels at a specific temperature (for ∼20 min), obtaining measurements (experimental time ∼40 min), and then changing the temperature again. Values for G′ and G′′ at 1 rad/s and at various temperatures were recorded for gels formed in propan-2-ol at pH 7, as well as in TFE and EtOH. In terms of the temperature dependence of the modulus, the TFE-induced system was found to behave similarly to what was observed for the thermally induced gels,15 in that the storage modulus increased with temperature. However, since the curing process was probably still continuing, even after 16 h, this finding should be considered with caution. In contrast, the ethanol-induced system at pH 2 and the gels formed in propan-2-ol at pH 7 showed a more complex behavior. Here, both G′ and G′′ decreased and then increased

From the limited study described in this work, it appears that the (alcohol-water) solvent-induced gelation of β-lactoglobulin shows a number of differences in comparison with the corresponding thermally induced phenomenon. Although G′ is generally greater than G′′ in the sol-phase of the thermally induced systems, interestingly, for solvent-induced gelation, the more usual G′′ > G′ pre-gel behavior is found. Whether this is simply a dielectric effect (lower dielectric constant of the mixed solvent), or results from other more subtle factors, remains to be determined. Perhaps the most interesting difference between the two systems is the clear maximum in G′′ found here for the solvent-induced gels, particularly for those formed in TFE. Such behavior is commonly seen for synthetic polymer systems and sometimes also for gelatin gels.18 According to Bibbo and Valles,19 this is an effect that can be associated with the relaxation of pendant chains. Qualitatively, this may reflect a greater degree of chain flexibility in the underlying gel network, and if so, this is consistent with the differences found between thermally induced and solvent-induced systems in the microscopy work described in Part 1.14 It is also consistent with differences in parameters extracted by the cascade random branching theory analysis of modulusconcentration data for the two types of gel, as a much less stiff type of network is implied for the solvent-induced gels. There are also some similarities between the two gelation mechanisms (thermal- and solvent-controlled), particularly where the TFE-induced gels are concerned. Here, the forms of the storage components of the cure curves showed the same general characteristics as those measured for the thermally induced gels, and comparable high power-law descriptions of gel time-concentration relationships were obtained, which may indicate that both have rate-determining nucleation steps in their fibril-forming processes. Also, the extrapolated modulus values could be described convincingly by classical gel theories22-25 and showed the quite low concentration dependence expected for a gelling system at concentrations significantly different from critical. The reduced cure data was also consistent with similar data for

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the thermally induced gels15 and suggested at least a close approximation to master curve superposition over the limited concentration range accessed. Arguably, superposition of data from the two gelling mechanisms might also be possible, but this is not certain. The fully cured TFE gels showed the characteristic modulus-frequency response of a true gel, and a fall in modulus with falling temperature was found, as in the heat-set examples. The ethanol-induced gels at pH 2, on the other hand, were much less similar to their heat-set counterparts. Here, the cure curves were of a more complex nature, apparently involving two separate contributions to the growth in elasticity. The early rise in the modulus seemed to be different from that obtained in TFE (and for the thermally induced systems) as G′ did not increase substantially in relation to G′′ until quite long after the gel point. One possibility is that only an entanglement network of fibrils is formed at first and that this phase of structuring is then followed by “semi-permanent” cross-linking between the fibrils, or some other physical “ripening” process. Alternatively, these results may simply reflect the formation of very low modulus systems close to a critical gelling concentration. This last picture is supported both by the steep modulus concentration dependence shown by the EtOH system (Figure 6) and the possible divergence of the gel time at concentrations just below 5% w/v (Figure 9). On the other hand, more than one discrete “aggregating species” could be involved in processes involving ethanol denaturation. For example, in 50% v/v ethanol, the native β-lactoglobulin conformation is thought to be in equilibrium with both the molten globule species and the helical “Hstate”. If it is assumed that these two conformers are capable of aggregating separately, then a complex gelation mechanism could result. This might also account for the complex temperature-dependence of the modulus of the “fully cured” gels. At this stage, however, no definite explanation can be given. It is clear that more work is required to elucidate the mechanisms of gel-formation by β-lactoglobulin in alcoholwater mixtures. Studies involving other solvents and a wider range of solvent-water compositions would be valuable, as would extension to other proteins. A complete picture will not be achieved by rheological methods alone; this will require careful implementation of other physical techniques such as, for example, light scattering and the microscopical and spectroscopic approaches described earlier in Part 1.14 As was discussed in Part 2 of this series,15 the rheological approach to protein gelation, while providing unique information about the gelation phenomenon, is highly restricted in the information it provides about events at a molecular level. It is also an approach that requires great care with regard to measurement, data handling, and interpretation.

Gosal et al.

Acknowledgment. The authors would like to thank Mr. Barry Taylor (King’s College London) for construction of accessories for the CSL-100 mechanical spectrometer. W.S.G. thanks the BBSRC and Unilever Research for the award of a CASE studentship. References and Notes (1) Tanford, C.; Buckley, C. E., III; De, P. K.; Lively, E. P. J. Biol. Chem. 1962, 237, 1168-1171. (2) Tanford, C.; De, P. K. J. Biol. Chem. 1961, 236, 1711-1715. (3) Weber, R. E.; Tanford, C. J. Am. Chem. Soc. 1959, 81, 3255-3260. (4) Buck, M. Q. ReV. Biophys. 1998, 31, 297-355. (5) Kamatari, Y. O.; Ohji, S.; Konno, T.; Seki, Y.; Soda, K.; Kataoka, M.; Akasaka, K. Protein Sci. 1999, 8, 873-882. (6) Tanford, C.; De, P. K.; Taggart, V. G. J. Am. Chem. Soc. 1960, 82, 6028-6034. (7) Townend, R.; Kumosinski, T. F.; Timasheff, S. N. J. Biol. Chem. 1967, 242, 4538-4545. (8) Uversky, V. N.; Narizhneva, N. V.; Kirschstein, S. O.; Winter, S.; Lober, G. Folding Des. 1997, 2, 163-172. (9) Goda, S.; Takano, K.; Yamagata, Y.; Nagata, R.; Akutsu, H.; Maki, S.; Namba, K.; Yutani, K. Protein Sci. 2000, 9, 369-375. (10) Renard, D.; Robert, P.; Garnier, C.; Dufour, E.; Lefebvre, J. J. Biotechnol. 2000, 79, 231-244. (11) Renard, D.; Lefebvre, J.; Robert, P.; Llamas, G.; Dufour, E. Int. J. Biol. Macromol. 1999, 26, 35-44. (12) Dufour, E.; Robert, P.; Renard, D.; Llamas, G. Int. Dairy J. 1998, 8, 87-93. (13) Dong, A.; Matsuura, J.; Manning, M. C.; Carpenter, J. F. Arch. Biochem. Biophys. 1998, 355, 275-281. (14) Gosal, W. S.; Clark, A. H.; Ross-Murphy, S. B. Biomacromolecules 2004, 5, 2408. (15) Gosal, W. S.; Clark, A. H.; Ross-Murphy, S. B. Biomacromolecules 2004, 5, 2420. (16) Gosal, W. S.; Clark, A. H.; Pudney, P. D. A.; Ross-Murphy, S. B. Langmuir 2002, 18, 7174-7181. (17) Barteri, M.; Gaudiano, M. C.; Giampiero, M.; Rosato, N. J. Biochim. Biophys. Acta-Protein Struct. Mol. Enzymol. 1998, 1383, 317-326. (18) Ross-Murphy, S. B. Rheol. Acta 1991, 30, 401-411. (19) Bibbo, M. A.; Valles, E. M. Macromolecules 1984, 17, 360-365. (20) Bremer, L. G. B.; VanVliet, T.; Walstra, P. J. Chem. Soc., Faraday Trans. 1 1989, 85, 3359-3372. (21) Bremer, L. G. B.; Bijsterbosch, B. H.; Walstra, P.; Van Vliet, T. AdV. Colloid Interface Sci. 1993, 46, 117-128. (22) Gordon, M.; Ross-Murphy, S. B. Pure Appl. Chem. 1975, 43, 1-26. (23) Clark, A. H. In Food Structure and BehaViour; Lillford, P. J., Blanshard, J. M. V., Eds.; Academic Press: New York, 1987; pp 13-34. (24) Clark, A. H. Polym. Gels Networks 1993, 1, 139-158. (25) Clark, A. H.; Farrer, D. B. J. Rheol. 1995, 39, 1429-1444. (26) Winter, H. H.; Chambon, F. J. Rheol. 1986, 30, 367-382. (27) Tobitani, A.; Ross-Murphy, S. B. Macromolecules 1997, 30, 48454854. (28) Clark, A. H.; Kavanagh, G. M.; Ross-Murphy, S. B. Food Hydrocolloids 2001, 15, 383-400. (29) Meunier, V.; Nicolai, T.; Durand, D.; Parker, A. Macromolecules 1999, 32, 2610-2616. (30) Normand, V.; Lootens, D. L.; Amici, E.; Plucknett, K. P.; Biomacromolecules 2000, 1, 730-738. (31) Normand, V.; Muller, S.; Ravey, J. C.; Parker, A. Macromolecules 2000, 33, 1063-1071. (32) Clark, A. H.; Ross-Murphy, S. B. AdV. Polym. Sci. 1987, 83, 57192. (33) Dufour, E.; Bertrandharb, C.; Haertle, T. Biopolymers 1993, 33, 589-598.

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Fibrillar Î²-Lactoglobulin Gels: Part 3. Dynamic ... - ACS Publications

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