Design of stability at extreme alkaline pH in streptococcal protein G

Available online at www.sciencedirect.com

Journal of Biotechnology 134 (2008) 222–230

Design of stability at extreme alkaline pH in streptococcal protein G Benjamin Palmer a , Katy Angus b , Linda Taylor b , Jim Warwicker a , Jeremy P. Derrick a,∗ a

Faculty of Life Sciences, University of Manchester, 131 Princess Street, Manchester M1 7DN, United Kingdom b Millipore UK Ltd., Medomsley Road, Consett, Co Durham DH8 6SZ, United Kingdom Received 13 April 2007; received in revised form 14 November 2007; accepted 5 December 2007

Abstract Protein G (PrtG) is widely used as an affinity-based ligand for the purification of IgG. It would be desirable to improve the resistance of affinity chromatography ligands, such as PrtG, to commercial cleaning-in-place procedures using caustic alkali (0.5 M NaOH). It has been shown that Asn residues are the most susceptible at extreme alkaline pH: here, we show that replacement of all three Asn residues within the IgG-binding domain of PrtG only improves stability towards caustic alkali by about 8-fold. Study of the effects of increasing pH on PrtG by fluorescence and CD shows that the protein unfolds progressively between pH 11.5 and 13.0. Calculation of the variation in electrostatic free energy with pH indicated that deprotonation of Tyr, Lys and Arg side-chains at high pH would destabilize PrtG. Introduction of the triple mutation Y3F/T16I/T18I into PrtG stabilized it by an extra 6.8 kcal/mol and the unfolding of the protein occurred at a pH of about 13, or 1.5 pH units higher than wild type. The results show that strategies for the stabilization of proteins at extreme alkaline pH should consider thermodynamic stabilization that will retain the tertiary structure of the protein and modification of surface electrostatics, as well as mutation of alkali-susceptible residues. © 2007 Elsevier B.V. All rights reserved. Keywords: Protein G; Alkaline stability; Thermodynamic stability

1. Introduction The most extensively used clean-in-place (CIP) and sanitization agent is sodium hydroxide. It is known to be an effective CIP agent, achieving multilog reduction of contaminants such as microbes, proteins, lipids and nucleic acids. Affinity chromatography ligands that are stable to treatment by caustic alkali, at concentrations of 0.5 M NaOH, for several hours would therefore be advantageous. This stringent requirement limits the use of many proteins which would otherwise be extremely valuable affinity ligands. It is well established that certain residues, such as asparagines and glutamines, deamidate upon exposure to alkali (Robinson, 2002). The rate of deamidation is dependent on a number of factors, including temperature, pH and the identity of the residues immediately adjacent in the polypeptide chain (Geiger and Clarke, 1987; Song et al., 2000; Athmer et al., 2002; Robinson, 2002). Deamidation is known to destabilize protein structure, causing most proteins to unfold and their function to be impaired (Kim et al., 2002; Carvalho et al., 2003).

∗

Corresponding author. E-mail address: [email protected] (J.P. Derrick).

0168-1656/$ – see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.jbiotec.2007.12.009

Protein G (PrtG) is a cell-surface protein from Streptococcus: it contains multiple copies of two different small domains which ˚ can independently bind albumin and IgG antibody (Akerstr¨ om et al., 1987). It is widely used as an affinity ligand for the purification of IgG antibody. G¨ulich et al. (2000) demonstrated that mutation of all four Asn residues within the PrtG albuminbinding domain resulted in a protein with enhanced stability towards 0.5 M NaOH. In a later study, the effect of mutation of two out of the three Asn residues within the IgG-binding domain of PrtG was reported (G¨ulich et al., 2002): again, an enhancement of alkaline stability was observed in the double mutant. A more commonly employed affinity protein for the purification of IgG is Staphylococcal protein A (SPA): a small domain from this protein, which adopts a three helix bundle structure, is able to bind to the Fc and Fab portions of IgG (Deisenhofer, 1981; Graille et al., 2000). SPA has a much higher intrinsic stability towards alkali than PrtG: for example, wild-type SPA has a halflife of approximately 16 h in 0.5 M NaOH (Linhult et al., 2004), whereas the equivalent for PrtG is less than 10 min (G¨ulich et al., 2002). Given that SPA and PrtG both contain Asn residues which are susceptible to deamidation, what is the origin of the much higher intrinsic stability of SPA in alkali? Circular dichroism (CD) spectra demonstrated that SPA retained its helical

B. Palmer et al. / Journal of Biotechnology 134 (2008) 222–230

structure at pH 13.7, indicating that its secondary structure was maintained at high pH (Linhult et al., 2004). A plausible working hypothesis is therefore that retention of secondary structure, and possibly tertiary structure, will assist in protecting a protein against deamidation at extreme alkaline pH. Here, we have examined the evidence for this hypothesis and show that optimization of non-covalent interactions and surface electrostatics could provide an alternative approach to the development of alkali-stable protein affinity ligands.

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2. Materials and methods

wavelength 350 nm. The slits were set at 5 nm. The temperature was 20 ◦ C and spectra were recorded in a 1 cm path length, 3 ml quartz cell. The solution was stirred throughout the titration and measurement. Three different sets of buffer conditions over a range of pH values were used to monitor alkali-induced unfolding and refolding of PrtG. Fixed pH solutions were prepared using methods given in the CRC handbook (Weast, 1977). Coverage of pH ranges was as follows: pH 9.4–10.8, 25 mM B4 O7 /NaOH; 10.7–11.9, 50 mM Na2 HPO4 /NaOH; pH 12.0–13.0, 200 mM KCl/NaOH. The final protein concentration was 1 ␮g/ml.

2.1. Production and purification of PrtG and mutants

2.3. Stopped flow analysis

For convenience for isolation of the IgG-binding domain of PrtG, the coding sequence for domain II (C2) of PrtG (Derrick and Wigley, 1992; Lian et al., 1992) was recloned into an expression vector, to incorporate a polyhistidine sequence at the C-terminus. The coding sequence for domain II (C2) of PrtG (Derrick and Wigley, 1992) was amplified by PCR using the following oligonucleotides: GAGATCCGCATATGACACCAGCCGTGACAACT; GCGGATCTAAGCTTTTCTGGTTTTTCAGTAACTGT (italics denote NdeI and HindIII sites). The fragment was digested with NdeI and HindIII, and inserted into pET22b (Novagen). Insertion was carried out in-frame to give a recombinant domain which started with MTPAV. . .. . . and concluded with KPE, with the following additional sequence at the C-terminal from the pET22b vector: KLAAALEHHHHHHH. Protein expression was carried out by transformation of the pET22b/protein G expression vector into E. coli BL21/DE3 (Invitrogen) and growth in batch culture on 2YT medium. Protein expression was induced by IPTG and cells were harvested by centrifugation. Cell paste was resuspended in 20 mM Na2 HPO4 /NaOH (pH7.4), 0.5 M NaCl. The suspended cells were disrupted using a probe sonicator and the debris sedimented by centrifugation at 13,000 rpm for 10 min. The sample was then subjected to a heat treatment at 70 ◦ C for 10 min, before cooling and centrifugation at 13,000 rpm for 10 min to remove denatured, contaminant proteins. The supernatant was filtered through a 0.22 ␮m filter, and applied to Ni NTA-Agarose column (Qiagen). The column was washed with five volumes of column buffer (20 mM Na2 HPO4 /NaOH (pH 7.4), 0.5 M NaCl; 10 mM imidazole) and protein G was eluted with 20 mM Na2 HPO4 /NaOH (pH 7.4), 0.5 M NaCl, 500 mM imidazole. Peak fractions were pooled, dialysed against water and freeze dried before storage at −20 ◦ C. Protein concentration was estimated by absorbance at 280 nm assuming an extinction coefficient of 11,000 M−1 cm−1 . Site-directed mutagenesis was carried out using a QuickChangeTM site-directed mutagenesis kit (Stratagene, La Jolla, CA) according to the protocol recommended by the manufacturer.

Stopped flow kinetic measurements were carried out in a similar manner to those reported previously (Park et al., 1997), but using pH changes rather than chaotrope to induce folding/unfolding. An SX.18 MV stopped flow instrument (Applied Photophysics) was used to monitor time-recorded measurements of fluorescence from the single Trp residue within the core of the PrtG domain. PrtG unfolding and refolding was carried out using the same buffers as employed for the fluorescence pH titration. Asymmetric mixing was used to give a 1:11 dilution of PrtG to the required pH. The final protein concentration was 37.5 ␮g/ml and the temperature was maintained at 20 ◦ C. The excitation wavelength was set at 295 nm and the emission wavelength was set at 350 nm; the slits were set at 5 nm. Typically, the results from five independent experiments were averaged. A nonlinear least squares method was used for fitting kinetic data. A single exponential expression is defined as:

2.2. Fluorescence pH titration Fluorescence measurements were made using a Cary Eclipse fluorimeter: the excitation wavelength was 295 nm and emission

Aexp (−kt) + B and a double exponential defined as: Aexp(−k1 t) + Bexp(−k2 t) + C 2.4. Circular dichroism Circular dichroism (CD) spectra were recorded in a JASCO J-810 instrument at 20 ◦ C using a 1 cm pathlength, 3 ml quartz cell. PrtG was added to various buffers at fixed pH values, as described for the fluorescence pH titration (above). The final concentration of PrtG in the cuvette was 75 ␮g/ml. CD spectra were averaged over four independent measurements and converted to mean residue weight molar ellipticity. 2.5. Measurement of the free energy for unfolding (Go N − U ) The free energy for unfolding (i.e. thermodynamic stability) of PrtG, Go N − U , can be determined by measurement of the response of the fluorescence of the single Trp residue (Trp43) to guanidinium HCl (GuHCl) concentration (Park et al., 1997). Parameters for fluorescence measurements were the same as stated above for the pH titration experiments, except that the buffer used was 50 mM Na2 HPO4 /NaOH (pH 7.0), with varying concentrations of GuHCl. The final protein concentration was

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50 ␮g/ml. The data were fitted by a non-linear least squares procedure to the following expression, adapted from Santoro and Bolen (1988): ΔF = [(ΔFN + mN [D]) + (ΔFU + mU [D]) exp −(ΔG◦N−U /RT + mG [D]/RT )]/[1 + exp −(ΔG◦N−U /RT + mG [D]/RT )] where F is the change in fluorescence, Fn and FU represent the fluorescence at zero (GuHCl) of the native and unfolded forms of PrtG respectively, (D) is the concentration of GuHCl, T is temperature, R is the gas constant, mN and mU describe the variation in fluorescence of the native and unfolded forms of PrtG as a function of GuHCl concentration and mg describes the variation in Gobs with [GuHCl] (Santoro and Bolen, 1988). 2.6. Surface plasmon resonance IgG binding studies Surface plasmon resonance was used to monitor changes in the binding capacity of PrtG for human IgG following exposure to NaOH at various concentrations, employing a BIAcore® instrument, essentially following the protocol adopted by G¨ulich et al. (2002). The principle behind the method is the measurement of the percentage of residual binding capability of PrtG after incubation in NaOH for a fixed period of time. Briefly, 100 ␮1 of the protein sample, at 1 mg ml−1 , was added to 100 ␮1 of NaOH at the appropriate concentration and mixed. Aliquots of 20 ␮1 were then withdrawn at timed intervals, (0, 10, 20, 30, 40, 60 min), and neutralized by addition to 180 ␮1 of 1 M Tris/HCl (pH 7.5). Human IgG was immobilized onto the surface of a CM5 sensor chip (BIAcore®) by performing an amine-coupling procedure, as recommended by the manufacturer. The interaction of the alkali exposed PrtG with human IgG was determined by passing 60 ␮1 of alkali-exposed PrtG over the chip surface at a flow rate of 60 ␮min−1 , and the change in refractive index units recorded. Between each sample load the sensor chip was regenerated by injecting 10 ␮1 of 10 mM glycine buffer at pH 2.0. 2.7. Computational methods Predictions of the pH-dependence of stability for PrtG and SPA were made with the FD/DH method for continuum electrostatics calculation (Warwicker, 2004). This refers to a combination of finite difference Poisson–Boltzmann (FDPB) and Debye–H¨uckel (DH) interaction schemes. The DH model, with a uniform relative dielectric of 78.4, corresponds to charge interactions in water, and incorporates ionic screening at 0.15 M. Relative dielectric values of 4 (protein) and 78.4 (water) are used for FDPB calculations, again with 0.15 M ionic strength. Ionisable groups that are substantially buried, with restricted conformational freedom, are allowed to interact only in the FDPB scheme since the water-dominated DH scheme is not appropriate in these cases. The resulting model incorporates the relatively small pKa shifts of the DH model with the capacity for higher pKa s that can accompany charge burial of ionis-

able groups. Modelling pH-dependence at high (alkaline) pH necessitates this higher pKa facility, so that buried tyrosine ionisation is incorporated. Monte Carlo sampling (Beroza et al., 1991) was used to derive pKa s from electrostatics calculations (Bashford and Karplus, 1990). The contribution of ionisable groups to folded state stability was made from integration of charge differences to the unfolded state (Antosiewicz et al., 1994), with addition of a constant of integration from calculation at an extreme pH with the reduced sites method (Bashford and Karplus, 1990). The unfolded state was modelled without interactions between ionisable groups, i.e. with standard amino acid model pKa s: Asp 4.0; Glu 4.4; Tyr 10.2; His 6.3; Lys 10.4; Arg 12.0; N-terminal 7.5; C-terminal 3.8. 3. Results 3.1. Site-directed mutagenesis of Asn residues within PrtG Previous work has indicated that, of the three Asn residues within PrtG, one (Asn37 in our numbering system) is particularly susceptible to alkali (G¨ulich et al., 2002). However, although a previous report has shown that the substitution of all Asn residues in the PrtG albumin-binding domain leads to a substantial stabilization against degradation towards alkali (G¨ulich et al., 2000), this has not been attempted for the IgG-binding domain from PrtG. Furthermore, there has not been any precise quantitation of the degree of stabilization obtained by Asn substitutions. In order to examine these questions, we constructed a range of single and multiple site mutations to the Asn residues within PrtG. Consideration was given to the environment of each residue when selecting the mutation: Asn8, for example, lies within a ␤-strand, and consequently a ␤-branched residue, such as Thr, might be expected to be a suitable substitute. The mutants made are listed in Table 1. A clear distinction needs to be made between stabilization against covalent modification in alkali (e.g. deamidation of Asn residues) and thermodynamic stability-measurement of the free energy associated with the (non-covalent) transition between the native and unfolded states. The former can be measured by determining the amount of active PrtG remaining in solution after exposure for a fixed period of time. Surface plasmon resonance (SPR) was developed as an ideal method for this purpose: using human IgG immobilized on the sensor chip, the proportion of active PrtG remaining after exposure to caustic alkali at time t could be measured by comparing responses, in refractive index units, between control (t = 0) and experimental time points. The proportion of active PrtG (G) at any time t is given by G = e(−kt) G0 where G0 is the amount of PrtG at t = 0, and k is a first order rate constant. A sample of the raw experimental data is shown in Fig. 1A and an example plot of ln(G/G0 ) versus t is shown in Fig. 1B, for different concentrations of NaOH. Plotting the values of k obtained from Fig. 1B against [NaOH] shows that k increases in a linear fashion with respect to alkali concentration (Fig. 1C). The slope of the graph in Fig. 1C gives a parameter

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Table 1 Thermodynamic and alkaline stability of wild type PrtG and mutants Stability in caustic alkali kNaOH Wild type N8G N8T N35D N8T/N35A N8T/N35A/N37A Y3F/T16I/T18I a

(M−1 s−1 )

1.7 × l0−3 4.2 × l0−4 1.1 × l0−3 1.9 × l0−3 1.0 × l0−4 2.2 × l0−4 9.4 × l0−4

Thermodynamic stability Stabilization factor

G◦ N − U (kcal mol−1 )

Ga (kcal mol−1 )

1.00 4.0 1.5 0.89 17 7.7 1.8

−5.3 −2.9 −4.8 −4.2 −4.1 −4.7 −12.1

0.0 2.4 ± 0.4 0.5 ± 0.4 1.1 ± 0.4 1.2 ± 0.4 0.6 ± 0.4 −6.8 ± 0.9

± ± ± ± ± ± ±

0.3 0.2 0.2 0.2 0.2 0.2 0.9

Represent the difference in free energy of unfolding between wild type and mutant.

which we will call kNaOH , and is a measure of the stability of the PrtG variant in alkali. The advantage of the use of kNaOH is that it allows the calculation of k, the first order rate constant, and hence the half-life at any particular concentration of NaOH. The values of kNaOH for the mutants studied in this paper, as well as the thermodynamic stability (Go N − U ) (Fersht, 1999), are recorded for each mutant in Table 1. All mutants were compromised in their thermodynamic stability to some extent, although in many cases the effect was minor. The largest effect was, as might be anticipated, for N8G: introduction of a Gly residue into a ␤-sheet environ-

ment would be likely to reduce Go N − U -other substitutions produced changes of around 1 kcal/mol or less. Examining the alkali stability, single site substitutions at Asn8 or Asn35 produced only marginal effects. The biggest change occurred with the N8T/N35A double mutant, which was around 17-fold more stable. The result is in contrast to the observation made by G¨ulich et al. (2002), who found that Asn37 is the most susceptible to deamidation. These authors used a rather different method for evaluating alkaline stability, however, by measuring the capacity of immobilized PrtG after repeated exposure to alkali. This could explain the difference. Most significant,

Fig. 1. Kinetics of the inactivation of PrtG in caustic alkali. Results are shown for the mutant N8T, as an example. (A) Sample raw SPR data, showing progressive inactivation of N13T PrtG in 0.1 M NaOH. Curves at selected time points are indicated. (B) Variation in the natural logarithm of fractional activity (G/G0 ) with time. Symbols are: diamonds, 50 mM NaOH; squares, 100 mM NaOH; triangles, 200 mM NaOH; circles, 400 mM NaOH. (C) Plot of rate constant k with [NaOH].

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however, is the observation from Table 1 that the triple mutant N8T/N35A/N37A is only stabilized towards alkaline treatment by around 8-fold. Even with all the Asn residues in the PrtG domain removed, stability in alkali was only improved by about an order of magnitude. G¨ulich et al. (2002) also reported attempts to improve the stability of PrtG by mutation of Asp and Glu residues, but these mutants gave no further stabilization. The predicted half-lives for wild type and the N8T/N35A/N37A triple mutant in 0.5 M NaOH, from the data in Table 1, are 7 min and 53 min, respectively. These values can be compared with a figure of around 1000 min for the half-life of wild type SPA, even before mutation of any Asn residue (Linhult et al., 2004). What is the origin of this wide disparity in stability between the two proteins? A plausible explanation lies in the maintenance of secondary and tertiary structure at high pH by SPA: Linhult et al. (2004) showed, by CD, that SPA retains its alpha helical structure at pH 13.7. As a basis for comparison, we collected the CD spectra from wild type PrtG at pH 7.0 and 13.7: the results showed a loss of about 80% of the signal from the far UV region from 230 to 220 nm, which is dominated by the single helix in PrtG (data not shown). As a result of this observation, we set out to examine the structural transition which occurs in PrtG during passage from low to high pH, and vice versa. The intrinsic fluorescence from PrtG, which arises predominantly from Trp43 under these conditions, has been used to monitor folding and unfolding transitions in the protein (Park et al., 1997, 1999). We observed that PrtG undergoes a decline in fluorescence intensity between pH 10 and pH 12 (Fig. 2A): as PrtG is denatured, the environment of W43 changes, with more exposure to solvent. The results indicate a broad unfolding profile with pH, and a hysteretic effect—the results from unfolding and refolding do not overlay (Fig. 2A). A similar experiment was carried out by CD (Fig. 2B): for unfolding, the results show a sharper transition in going from low to high pH than was the case for the fluorescence measurements. The unfolding transition also apparently occurred at a higher pH: thus, at pH 11.5, the CD signal from PrtG was largely unchanged, whereas the fluorescence signal had declined to less than half of its initial value. The failure of the refolding transition to superimpose on the unfolding transition was even more apparent in the CD data. The results in Fig. 2 indicate that unfolding of PrtG starts between pH 10 and 11, perhaps initiated by penetration of hydroxide ions into the interior of the protein. At around pH 11.5, the secondary structure within the protein starts to dissociate. Interestingly, the fact that the refolding transitions, from high to low pH, do not map onto the unfolding data indicates that the pathways for unfolding and refolding could be different. This phenomenon is not observed in chaotrope-induced unfolding/refolding of PrtG (Kuszewski et al., 1994; Park et al., 1997; Tcherkasskaya et al., 2000; Nauli et al., 2002). It should be noted that these experiments were carried out over a pH range where the rate of deamidation was negligible: the transitions in structure are therefore entirely attributable to changes in non-covalent interactions within the protein.

Fig. 2. Denaturation and renaturation of PrtG at alkaline pH. (A) Changes in intrinsic fluorescence of PrtG with pH. Filled symbols correspond to unfolding brought about by a 1 in 50 dilution of PrtG from pH 9.2 to 12.0, and unfilled symbols represent refolding brought about by a 1 in 50 dilution of PrtG from pH 12.0 to 9.2. Squares are used to denote borate buffer and circles are used to represent phosphate buffer. Data points are the average of five readings +S.D. (B) CD (mean residue weight molar ellipticity) at 222 nm of PrtG with pH. Dilutions from low and high pH were carried out as described in (A). Filled symbols represent unfolding and unfilled data points correspond to refolding. Squares are used to denote sodium bicarbonate buffer, circles represent phosphate buffer and triangles correspond to potassium chloride buffer.

To examine the pH-induced structural transitions within PrtG in more detail, we used stopped flow measurements to examine the kinetics of unfolding and refolding (Figs. 3 and 4). Rapid dilution of PrtG from pH 10.8–12.4, for example, led to a quench of fluorescence which could be fitted to a single time-dependent exponential decay (Fig. 3A). Examination of the apparent rate constant as a function of pH revealed that it reaches a minimum at about pH 12 (Fig. 3B): this behaviour is indicative of the occurrence of a denaturant-dependent intermediate (Fersht, 2000; Sanchez and Kiefhaber, 2003; Jemth et al., 2004). Discontinuity in chevron plots of this type are frequently used as a diagnostic test for the presence of intermediates in folding pathways (Jackson, 1998; Fersht, 2000; McCallister et al., 2000; Sanchez and Kiefhaber, 2003; Jemth et al., 2004). The refolding kinetics were even more complicated: an example of the increase in fluorescence on renaturation from high to low pH is shown in Fig. 4A. The data were not consistent with a single exponential expression and required two exponential terms for fitting of the data (see insets in Fig. 4A). Both apparent rate constants increased with decreasing pH (Fig. 4B). The results provide further evidence for different unfolding and refolding

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Fig. 3. Stopped flow transient fluorescence measurements of PrtG alkaline denaturation. (A) Example data: PrtG was transferred from pH 10.8 (phosphate buffer) to pH 12.4 (KCl buffer) by rapid 11-fold dilution. A fitted curve, corresponding to a single exponential decay, is overlaid on the data, and the inset shows the deviation of the fitted line. (B) Variation in apparent rate constants with final pH after dilution. Filled squares denote phosphate and unfilled squares KCl buffers, at the indicated pH values.

pathways during alkali-induced denaturation of PrtG, behaviour that is in contrast to chaotrope-induced denaturation (Park et al., 1997). One reason for the different stabilities of PrtG and SPA in alkali could lie in the surface electrostatics of each protein. Accordingly, the variation in electrostatic free energy with pH for PrtG and SPA was computed from the 3-D structures of both of the domains. At neutral pH, charge networks/salt-bridges give overall stabilization of the folded state, which is lost at acidic pH (protonation of Asp, Glu, C-terminal) and at alkaline pH (deprotonation of Lys, Arg, His, N-terminus). Fig. 5A shows the variation in electrostatic free energy for PrtG with pH: optimal stability occurs between pH 5 and 9. The decrease in stability at alkaline pH is caused by a buried tyrosine side-chain (Tyr3), which has an up-shifted pKa and whose ionization is predicted to destabilize the folded state at high alkaline pH. The computational results in Fig. 5A therefore show a good agreement with the experimental data in Fig. 2, which also show a decrease in secondary and tertiary structure with increasing pH. The same calculation of free energy, carried out as part of a computational study of around 200 proteins, gave simi-

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Fig. 4. Stopped flow transient fluorescence measurements of PrtG renaturation from high pH. (A) Example data: PrtG was transferred from pH 13.0 (KCl buffer) to pH 11.4 (phosphate buffer) by rapid 11-fold dilution. A fitted curve, corresponding to a double exponential decay, is overlaid on the data. The upper inset shows the results of an attempt to fit the data to a single exponential expression, and the lower inset a double exponential expression. (B) Variation in both apparent rate constants (k1 and k2 ) with final pH after dilution. Triangles and diamonds represent borate buffer and squares and circles correspond to phosphate buffer; triangles and squares are also used to denote k1 and diamonds and circles represent k2 .

lar results (Salaman and Warwicker, 2005), indicating that the alkaline denaturation of PrtG is likely to be a common feature of most proteins. Fig. 5B shows the results of the same calculation applied to SPA: this shows a much rarer case, in which neutral pH interactions between ionisable groups are net-destabilizing. In addition, the pH-dependence over alkaline pH is significantly less than that for PrtG, in line with the experimental observations. The difference in charged group locations that underlies this result is indicated in Fig. 5C, where salt-bridges are more numerous for PrtG, compared with fewer charge–charge interactions for SPA. This observation suggests that the disposition of titratable side-chains on the surface of a protein could play a role in dictating its alkaline stability. Attempts were made to test this theory by mutation of selected surface residues in PrtG and examination of their stability in alkali. The resulting mutants were, however, largely unchanged in their alkaline stability, possibly

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Fig. 6. The unfolding transition of Y3F/T16I/T18I and wild type PrtG as monitored by CD. Filled symbols represent wild type PrtG and unfilled symbols correspond to Y3F/T16I/T18I. Squares are used to denote sodium bicarbonate buffer, circles represent phosphate buffer, triangles correspond to potassium chloride/sodium hydroxide and the single diamond point represents borate buffer at pH 9.2.

Fig. 5. Computation of energetics of surface electrostatic charges on PrtG and SPA. (A) Computed stablizing free energy for PrtG (PDB accession 1IGD) (B) Computed stablizing free energy for SPA (PDB accession 1BDD) (C) surface charge distribution of PrtG and SPA. The calculation of potential field is colourcoded blue:positive and red:negative. (For interpretation of the references to color information in the figure or text, the reader is referred to the web version of the article.)

because a more sophisticated mutagenesis strategy is required, with multiple mutations to surface residues. Another approach to optimising the stability of PrtG in alkali would be to increase the stability of the core domain, to offset the destabilization caused by interacting charged groups at high pH. Malakauskas and Mayo (1998) reported the design of a mutated form of PrtG in order to optimize its core packing and thus increase its thermal stability. The authors used a computational approach to identify potential sites where mutation to core residues could optimise non-covalent binding, and produced a seven site mutant with an enhancement in native stability of 4.3 kcal/mol. We found that introduction of two of these mutations, Y3F/T25E, produced only a marginal improvement in thermodynamic stability of 0.2 kcal/mol. Using four of the mutations detailed by Malakauskas and Mayo, Y3F/T16I/T18I/T25E, gave an improvement of 3.5 kcal/mol, but the triple site mutant Y3F/T16I/T18I gave optimal results, stabilizing the domain by a remarkable 6.8 kcal/mol relative to wild type (Table 1). This

amounts to a doubling of the thermodynamic stability of the domain. The effect of this enhanced thermodynamic stability on denaturation at high pH is shown in Fig. 6: whereas wild type PrtG unfolds at pH 11.5, the triple mutant is starting to unfold at around pH 12.5–13. This result shows that increasing the thermodynamic stability of a protein can indeed offset denaturation at high pH. In spite of this dramatic effect on alkaline stability, however, the triple mutant only showed a limited improvement in stability towards NaOH (Table 1). This is probably because the triple mutant is still predominantly unfolded at pH 13.7—conditions where deamidation will be rapid. Nevertheless, the results show that alkaline stability can, in principle, be engineered into a protein by optimization of non-covalent interactions in core residues. 4. Discussion The results presented here have shown that there are multiple factors which can influence the stability of a protein at extreme alkaline pH. Clearly the sensitivity of asparagines, and other alkali-sensitive amino acids, to covalent modification is a primary determinant of stability. Our suggestion here is that this sensitivity is influenced indirectly, but to a substantial degree, by the tertiary structure of the protein. Broadly speaking, we can identify two reasons for the pronounced stability of SPA in alkali. First, SPA is a thermodynamically stable protein, with a Go N − U value of 4.9 kcal/mol and a Tm of 78 ◦ C for the Zdomain (Dincbas-Renqvist et al., 2004). The Go N − U value is strikingly similar to that for PrtG (Table 1), suggesting that thermodynamic stability alone is not the sole determinant of stability in caustic alkali. Critically, we have identified a second factor: the variation in electrostatic interaction energy with pH, computed from the SPA structure, is remarkably flat (Fig. 5B). This means that titration of Tyr and other residues, which appear to compromise the stability of PrtG at high pH, do not affect SPA to the same extent. We have demonstrated that PrtG, in contrast to

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SPA, undergoes complex unfolding and refolding kinetics during pH-induced transitions between folded and unfolded states. Importantly, we have shown that the denaturation of PrtG at high pH can be understood in terms of the behaviour of surface charged residues, particularly tyrosines. Computation of surface electrostatics, in combination with protein engineering strategies, could offer an alternative approach to stabilizing the tertiary structure of PrtG, and other proteins, at high alkaline pH. Supporting evidence for the role of surface residues in stabilizing protein structure at high pH has come from studies on enzymes derived from alkaliphilic bacteria. For example, Mprotease (pH 12.3) (Kobayashi et al., 1995) and AprM (pH 12–13) (Masui et al., 1994) from Bacillus sp. contain higher proportions of Arg and fewer Lys residues compared with other alkaliphilic enzymes with lower pH optima. The results in Fig. 6 suggest that improving the thermodynamic stability of PrtG could also, ultimately, lead to the engineering of a multiple site mutant with enhanced stability towards caustic alkali. It is well established that optimization of the core packing of hydrophobic residues can increase the native stability of a protein (Dill, 1990; Munson et al., 1996; Dahiyat and Mayo, 1997; Malakauskas and Mayo, 1998; Golovanov et al., 2000). We show here that this effect can also shift the denaturation profile of PrtG to the right, increasing the pH at which the protein denatures. This strategy, although successful, still has some way to go: the Y3F/T16I/T18I mutant is almost half unfolded at pH 13, and would probably be predominantly denatured at 0.5 M NaOH (pH 13.7). We presume that this is the reason why this mutant demonstrated relatively little improvement in resilience towards inactivation by NaOH. Further improvements in the thermodynamic stability of the mutant, or adjustments in the surface electrostatics, could offer a way to increase stability still further. Our conclusion is therefore that the engineering of stability against treatment with caustic alkali into PrtG, or indeed any other protein, is likely to involve optimization of thermodynamic stability, surface electrostatics and mutation of labile residues (e.g. Asn). Acknowledgements We thank the Biotechnology and Biological Sciences Research Council for studentship support for B.P. References ˚ Akerstr¨ om, B., Nielson, E., Bj¨orck, L., 1987. Definition of IgG- and albumin-binding regions of streptococcal protein G. J. Biol. Chem. 262, 13388–13391. Antosiewicz, J., McCammon, J.A., Gilson, M.K., 1994. Prediction of pHdependent properties of proteins. J. Mol. Biol. 238, 415–436. Athmer, L., Kindrachukt, J., Georges, F., Happer, S., 2002. The Influence of protein structure on the products emerging from succinimide hydrolysis. J. Biol. Chem. 277, 30502–30507. Bashford, D., Karplus, M., 1990. pKa ’s of ionizable groups in proteins: atomic detail from a continuum electrostatic model. Biochemistry 29, 10219– 10225. Beroza, P., Fredkin, D.R., Okamura, M.Y., Feher, G., 1991. Protonation of interacting residues in a protein by a Monte Carlo method: applica-

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