Do Macromolecular Crowding Agents Exert Only an Excluded Volume

Article pubs.acs.org/JPCB

Do Macromolecular Crowding Agents Exert Only an Excluded Volume Effect? A Protein Solvation Study Sanjib K. Mukherjee, Saurabh Gautam, Saikat Biswas, Jayanta Kundu, and Pramit K. Chowdhury* Department of Chemistry, Indian Institute of Technology Delhi, Hauz Khas, New Delhi 110016, India S Supporting Information *

ABSTRACT: The effect of macromolecular crowding on protein structure and dynamics has mostly been explained on the basis of the excluded volume effect, its origin being entropic. In recent times a progressive shift in this view has been taking place with increasing emphasis on soft interactions that are enthalpic by nature. Using very low concentrations (1−10 g/L) of both synthetic (dextran- and poly(ethylene glycol) (PEG)-based) and protein (αsynuclein and myoglobin)-based crowders, we have shown that the solvation of probe molecule ANS (1-anilinonapthalene-8-sulfonate) bound to serum proteins bovine serum albumin (BSA) and human serum albumin (HSA) is significantly modulated in both a protein- and crowder-dependent fashion. Since under such conditions the effect of excluded volume is appreciably low, we propose that our observations are direct evidence of soft interactions between the macromolecular crowding agents used and the serum proteins. Moreover, our data reveal, that since at these low crowder concentrations major perturbations to the protein structure are unlikely to take place while minor perturbations might not be readily visible, protein solvation provides a unique spectral signature for capturing such local dynamics, thereby allowing one to decouple hardsphere interactions from soft sphere ones. Furthermore, since fast fluctuations are known to play a major role in determining the functional characteristics of proteins and enzymes, our results suggest that such motions are prone to be modulated even when the cellular crowding conditions are quite relaxed. In other words, by the time the excluded volume effects come into the picture in the physiological milieu, modulations of functionally important protein motions that need a relatively lower activation energy have already taken place as a result of the aforementioned enthalpic (soft) interactions.

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INTRODUCTION Macromolecular crowding at the physiological level is well appreciated in the scientific community. This has resulted in a recent surge in studies of biomolecular conformations and dynamics in the presence of synthetic and protein-based macromolecular crowding agents. Investigations with regard to macromolecular congestion both in vitro and in vivo have revealed significant modulations in protein structure and function, protein−protein association, protein aggregation, and intracellular diffusion, to name a few.1−11 One of the most common ways of studying the phenomenon of crowding in vitro has involved the use of some synthetic (mostly sugaror PEG-based) and protein-based crowding agents. While the general consensus is that crowders influence the test biomolecules primarily via the excluded volume effect with the underlying assumption of the crowding agents behaving like hard spheres,12 recent reports have suggested otherwise. For example, Pielak’s group using extensive NMR studies have shown that BSA, lysozyme, and proteins in the E. coli extract exert an appreciable influence through soft interactions on the protein CI2.13,14 This is expected as the proteins have a noticeable distribution of surface-charged residues and/or hydrophobic patches that can potentially show significant interactions with the probe molecule,15 which itself has its own © 2015 American Chemical Society

share of charged amino acid side chains. Though the same has been hinted at to some extent for the Ficoll-, PEG-, and dextran-based synthetic crowders that are uncharged and are often used to mimic the intracellular milieu,16−18 strong evidence of such interactions is still hard to come by. The latter arises in part because a majority of studies dealing with modulations in protein conformations in the presence of these synthetic crowders are performed at quite high concentrations of these crowding agents. Under such conditions the excluded volume phenomenon predominates and might either mask the other crowder-induced effects that can also influence the proteins or remain intricately intertwined such that its exact influence is difficult to decipher. Moreover, even for the protein-based crowders, the concentrations used have been on the higher side, that is, ∼50 g/L or higher. In other words, at low-enough crowder concentrations, hardly does one expect any major perturbation of the protein structure being brought about, and hence such a dilute regime has been left relatively unexplored. Received: September 28, 2015 Revised: October 8, 2015 Published: October 9, 2015 14145

DOI: 10.1021/acs.jpcb.5b09446 J. Phys. Chem. B 2015, 119, 14145−14156

Article

The Journal of Physical Chemistry B

concentration was checked against an extinction coefficient of 5000 M−1 cm−1 at 350 nm. All absorbance measurements were performed using a Shimadzu UV−Vis (model UV-2450) spectrophotometer. One centimeter path length cells were used for all the measurements. Fluorescence Measurements. Steady-state fluorescence measurements were carried out on an Edinburgh FLS900 fluorescence spectrometer. The fluorescence spectra were measured using fluorescence quartz cuvettes having a 1 cm path length, and the samples were excited at 375 nm corresponding to the ANS absorption maximum. The excitation and emission slits were both set at 5 nm. In the presence of myoglobin (Mb) as the crowder, we used a 3 mm path length cuvette and excited the samples (BSA-ANS and HSA-ANS) at 325 nm to eliminate complications due to the inner filter effect. Measurements of the excited-state lifetime decays of ANS were performed using a time-correlated singlephoton-counting (TCSPC) spectrometer (Edinburgh FLS900). A picosecond diode laser (EPL375) was used to excite the samples at 375 nm. Time-resolved emission decays of the samples were collected from 410 to 600 at 10 nm intervals through a single monochromator with a 2 nm emission bandpass, and for each experiment the TAC was set to 50 ns. The emission decays were collected at the magic angle of 54.7° to avoid complications due to rotation. Emission decays were fit with the instrument response function (IRF) collected with a scattering Ludox solution using reconvolution least-squares algorithm software. The fwhm (full width at half-maximum) of IRFs were typically in the range of 220 ps. The peak counts were kept at 5000 (3000 at the red edge) for the lifetime decay measurements. The time-dependent emission spectra (see the text) obtained were fit to a log-normal function to ascertain the peak frequency ν(t).21 The average lifetimes of the decays collected at the ANS emission maximum (475 nm) were calculated by using the following equation

In this study, using the time-dependent Stokes shift analyses of ANS (1-anilinonapthalene-8-sulfonate) bound to the proteins bovine serum albumin (BSA) and human serum albumin (HSA), we have shown that synthetic crowders, dextran (6, 40 and 70)- and PEG (200, 8000)-based, at low concentrations can have an appreciable effect on the extent of protein solvation, thereby implying the presence of soft interactions that were initially very hard to detect. In addition we have also used the disordered protein α-synuclein as a crowder, with the latter inducing considerable changes in solvation, in and around the binding sites occupied by ANS. Our results reveal that protein solvation/hydration is a sensitive probe of the presence of soft interactions at low crowder concentrations, wherein the excluded volume effect is operational at a much reduced level, thereby opening new directions in analyzing and decoupling soft interactions from hard-sphere ones. In addition, since protein hydration plays an important role in many aspects of biomolecular structure and function, it is essential to realize that such perturbations might come into the picture much before the excluded volume exerts its influence. In other words, our data reveal negligible changes at the equilibrium level but dramatic modulations in dynamics, therefore implying that the crowders show substantial transient/weak nonspecific interactions with the proteins, thereby providing insights that will significantly contribute to the overall importance and understanding of the phenomenon of macromolecular crowding.

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MATERIALS AND METHODS Chemicals Used. Essentially fatty acid-free human serum albumin (HSA), bovine serum albumin (BSA), myoglobin (Mb), dextran 70, dextran 40, dextran 6, PEG8000, PEG200, and the fluorescent probe ANS (1-anilinonapthalene-8sulfonate) were purchased from Sigma Chemical Co. (USA) and were used as received without further purification. αSynuclein was expressed in E. coli and purified on the basis of a previously published protocol.19,20 Sodium phosphate dibasic anhydrous (Na2HPO4) and sodium phosphate monobasic anhydrous (NaH2PO4) were purchased from Merck Specialties Private Limited (Mumbai, India). Millipore water was obtained from a Millipore Milli-Q Academic water purification system. Preparation of Solutions. Phosphate buffer solution (pH 7) was prepared by mixing definite weighed amounts of monobasic and dibasic phosphate salts in Millipore water. The pH of the resultant buffer was measured by using an HI3220 (HANNA) pH meter. All weighings were performed using a Precisa XB 120A (Sweden) analytical balance. Stock solutions of HSA and BSA in 50 mM phosphate buffer (pH 7) were prepared by dissolving a weighed amount of the protein in 0.5 mL of the buffer solution. In the case of experiments involving the crowders (dextran series and PEG series), solutions were prepared by dissolving a definite amount of the crowding agents in the phosphate buffer. The concentrations of the serum proteins, BSA and HSA, and that of ANS were kept at 15 μM throughout. Absorbance Measurements. The concentration of the protein solutions was determined spectrophotometrically using molar absorption coefficients of 36 500 and 43 800 M−1 cm−1 at 280 nm for HSA and BSA, respectively. Subsequently, 3 mL of a protein solution was prepared by a dilution of the stock solution, and the concentration was again determined spectrophotometrically before each measurement. The ANS stock solutions were prepared in Millipore water, and the

⟨τ ⟩ =

∑i aiτi ∑i ai

(1)

where ai represents the amplitude of the respective decay component τi. For all samples, the ANS lifetime was typically fit to a three-exponential function (individual values have not been shown here). Measurements of the rotational anisotropy of ANS were performed using the above-mentioned time-correlated singlephoton-counting (TCSPC) spectrometer. For every measurement we calculated the G factor and then fitted the anisotropy decay to find the rotational time constant. The time-dependent anisotropy function, r(t), was expressed using the following formula r (t ) =

III − GI⊥ III + 2GI⊥

(2)

where G is the instrument- and wavelength-dependent correction factor produced by the optical system that corrects for any depolarization of the detection system. The anisotropy decays were fitted to the following double-exponential function r(t ) = r0⎡⎣a1e(−t / τr1) + a 2e(−t / τr 2)⎤⎦ 14146

(3)


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Figure 1. Normalized time-resolved fluorescence decays of ANS (15 μM) bound to (A) HSA (15 μM) and (B) BSA (15 μM) as a function of the emission wavelength. In panels (C) and (D) are displayed the time-resolved emission spectra (TRES) for ANS bound to HSA in buffer and in PEG8000 (2 g/L), respectively. (λexc = 375 nm).

where r0 is the limiting anisotropy, τr1 and τr2 represent the local and global (with the protein) motions of ANS, and a1 and a2 are the corresponding amplitudes. FRET Analyses. The efficiency of energy transfer between ANS (bound to BSA or HSA) as the donor and the heme cofactor as the acceptor was determined by steady-state fluorescence measurements using the following equation

E=1−

FDA FD

R 0 = 9.78 × 103[J(λ)n−4κ 2ϕD]1/6

where J(λ) is the overlap integral, n is the refractive index of the medium, and κ2 (assumed to be 2/3) is the orientation factor. Size-Exclusion Chromatography (SEC). SEC analysis was carried out on a Superdex 200 Increase 10/300 GL column (i.d. 1.0 cm × 30 cm) using an AKTA purifier FPLC system (GE Healthcare). The elution was carried out using a 10 mM sodium phosphate buffer (pH 7.4) with 0.1 M NaCl with a flow rate of 0.50 mL/min. All of the samples were injected after centrifugation at 10 000g for 20 min and filtration through a 0.22 μm membrane filter. The size-exclusion column was calibrated using a standard globular set of proteins of known molecular weights (data not shown). Job’s Plot. The binding stoichiometry of the serum proteins (P)−ANS (L) complex was determined by Job’s method of continuous variation in different crowded media. This method is based on the principle that the analytical signal due to the complex PLn arising from the interaction of the protein with a ligand according to the equilibrium P + nL ⇔ PLn will attain a maximum value when

(4)

where FD is the fluorescence intensity of the donor only and FDA is the fluorescence intensity of the donor in the presence of the acceptor (myoglobin). Here we have used the absolute fluorescence intensity of ANS (bound to BSA/HSA) at 475 nm to calculate the efficiency. Subsequent to this the distance between the FRET pair, rDA was calculated using the following expression: E=

R 06 R 0 6 + rDA 6

(6)

(5)

The value of R0 (Å) was obtained from the following equation 14147


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Table 1. Time-Resolved Stokes Shift and Solvation Response Time (τs) for ANS (15 μM) in (A) BSA (15 μM) and (B) HSA (15 μM) in the Presence of Different Concentrations of Crowding Agents 1 g/L crowder

Δν (cm−1)

2 g/L τs (ps)

dextran 6 dextran 40 dextran 70 PEG8000 PEG200 buffer

a

a

438

2569

a

a

438 564

2069 1998

dextran 6 dextran 40 dextran 70 PEG8000 PEG200 buffer

501 313 501 313

2075 1885 2250 2207

a

a

Δν (cm−1) 395 330 260 560 395

3 g/L

τs (ps)

Δν (cm−1)

1700 2750 2630 1460 1240

a

438 263 a a

4 g/L

τs (ps)

Δν (cm−1)

τs (ps)

(A) In BSA a 330 a 1750 2019 263 a 627 a

5 g/L

1465 a

1830 1243

a

a

8 g/L

Δν (cm−1)

τs (ps)

330 130 130 313 263

10 g/L

Δν (cm−1)

τs (ps)

1400 1240 1490 940 990

330 NDb 130

1283 NDb 1290

a

a

a

a

1670 660 800 1050 1750

329 NDb NDb 313 220

1600 NDb NDb 1120 807

Δν (cm−1)

τs (ps)

220 NDb NDb 130 263

720 NDb NDb 700 540

329 NDb NDb 197 260

1700 NDb NDb 1070 650

−1

501 260 330 461 263

2150 1230 1650 1200 2500

a a

438 a

263

Δν = 697 cm , τs = 2660 ps (B) In HSA a 329 1765 376 a 313 1014 220 1524 438 1660 263 a a a 313 1870 263 1709 330 Δν = 877 cm−1, τs = 2550 ps

a

At this particular concentration, experiments were not performed because for the respective crowder concentration before and after this, the changes in τs were quite small. bAt this particular concentration of crowding agents, solvation was too fast to be detected by the resolution of ∼200 ps of our current setup. All of the C(t) decays were fit to a single-exponential function.

L n = P+L 1+n

by a sudden increase in the dipole moment and hence charge distribution, to which the protein matrix responds in a timedependent fashion, the latter typifying the protein response time, that is, protein solvation. ANS (1-anilinonapthalene-8sulfonate) is known to bind with appreciable affinity to bovine serum albumin (BSA) and human serum albumin (HSA).28 In addition, once bound to the proteins, ANS undergoes a significant blue shift in its emission maximum (as compared to that in buffer only) with a concomitant dramatic increase in the fluorescence quantum yield, an aspect that has made ANS a very popular probe for reporting changes in binding pockets and hydrophobic patches in biomolecules.29 In addition, ANS has already been used to probe protein solvation reliably.27 Job’s plot analysis reveals that ANS binds to both BSA and HSA with a 1:4 binding stoichiometry, that is, for every protein molecule, on average four ANS molecules are bound (SI Figure 1). Time-resolved emission spectra of ANS bound to BSA and HSA were constructed from ANS lifetimes obtained at different wavelengths (Figure 1 and SI Figures 2−4). In brief, for the construction of the time-resolved emission spectra (TRES), at first a series of decays (excited at 375 nm) were collected from 410 to 560 in 10 nm intervals. The decays were fit to a sum of exponentials, subsequent to which TRES were reconstructed from these fitted decay curves by normalizing to the steadystate emission spectra of ANS bound to the protein (eq 9)30

(7)

The variation of the protein and ligand concentration was carried out such that the total concentration (P + L) was fixed for the equation to be valid. Benesi−Hildebrand Method. The dissociation constants were determined using the Benesi−Hildebrand method. When assuming a 1:1 association between serum proteins and the ANS, the Benesi−Hildebrand equation is given as follows 1 1 1 = + F − F0 K (Fmax − F0)[ANS]0 Fmax − F0

(8)

where F0 is the fluorescence of serum proteins in the absence of fluorescence probe ANS, F is the fluorescence intensity obtained with the addition of ANS, Fmax is the fluorescence intensity obtained with an excess amount of ANS, K is the association constant (M−1), and [ANS]0 is the concentration of free ANS. The plot of 1/(F − F0) against 1/[ANS]0 shows a linear relationship, indicating that the serum proteins associate with ANS in 1:1 stoichiometry. The association constant K between proteins and ANS is determined by the slope, and from this the dissociation constant is obtained as it is the inverse of the former one. In the case of our system exhibiting 1:4 stoichiometry, the equation used was

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1 1 1 = + 4 F − F0 Fmax − F0 K (Fmax − F0)[ANS]0

S(λ , t ) =

(9)

D(λ , t ) S0(λ) ∞

∫0 D(λ , t )

(10)

where D(λ, t) is the fluorescence decay at a particular wavelength and S0(λ) is the steady-state emission intensity at a given wavelength. The solvent correlation function was then plotted according to the following equation30

RESULTS The dielectric relaxation of proteins has often been studied by measuring the solvent response time around a suitable probe chromophore that is either intrinsic to the protein (such as the amino acid tryptophan22,23) or an external fluorescent dye that is covalently incorporated into the biomolecule24,25 or a fluorescent molecule that shows moderate to appreciable binding affinity for a protein cavity.26,27 Excitation of the chromophore creates a nonequilibrium situation brought about

C(t ) =

ν(t ) − ν(∞) ν(0) − ν(∞)

(11)

where v(t), v(0), and v(∞) are the corresponding peak frequencies at times t, 0, and ∞, respectively, with ∞ ideally 14148


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Figure 2. Comparison of the decays of the solvent response function C(t) of ANS (15 μM) bound to HSA (15 μM) in varying concentrations of crowders. (A) Dextran of different molecular weights and (B) PEG of different molecular weights.

Figure 3. C(t) decays of ANS (15 μM) in varying concentrations of α-synuclein for (A) BSA (15 μM) and (B) HSA (15 μM).

dextran 40 and dextran 70 (the dextran-based crowding agents having higher average molecular weights) at the lowest concentration of 2 g/L, almost no change is seen in the manner in which ANS is solvated. However, for 5 g/L a significant drop in the C(t) decay time can be observed while on using 10 g/L crowder the solvent response becomes too fast to be reliably analyzed by the resolution offered by the ∼200 ps fwhm instrument response function of our TCSPC setup. That the solvation of ANS is a sensitive probe for detecting crowder-induced changes was further supported by the C(t) decays obtained for the HSA−ANS samples. In the presence of 2 g/L dextran 6, the solvent correlation decay time constant was ∼2100 ps, which decreased to ∼1650 ps for both 5 and 10 g/L concentrations of the crowding agent (Figure 2, Table 2, and SI Figure 6). Surprisingly, as opposed to that observed for BSA, no change in the C(t) decay was observed for the two higher concentrations of dextran 6. Evidence for the difference in the responses of the two serum proteins could be further observed in the manner that HSA solvated ANS in the presence of dextran 40 and dextran 70. At 2 g/L the solvation response was much faster than that of BSA, giving rise to fitted decays of ∼1200 ps (dextran 40) and ∼1700 ps (dextran 70), with the same trend being maintained even at a 5 g/L concentration of the crowders. However, similar to that of BSA, the solvation at 10 g/L was again too fast to be resolved by our current setup. While the aforementioned macromolecular crowders have been considered to be inert in nature, the PEG-based crowders are known to show definite interactions with proteins. Hence it was not surprising to see that both PEG8000 and PEG200 also

referring to that time at which the system has reached equilibrium. For both BSA and HSA the C(t) decay could be well fit by a single-exponential time constant of ∼2600 ps (Table 1 and Figures 2 and 3). Given that the two proteins are homologous with ∼76% identity in sequence, the similarity of the time constant is not surprising and hence further reinforces the overall similarity in the nature of ANS binding to the respective subdomain cavities of the proteins. Bulk water is known to respond to changes in solvation on an ultrafast time scale, that is, on the order of a few hundred femtoseconds, with the response becoming slower in organized assemblies.31,32 Thus, the slow solvation response seen for BSA and HSA can be well ascribed to the following: (i) biological water, that is, the hydration layer that remains intimately associated with the protein surface lining the binding cavities and (ii) the rigid protein matrix comprised of amino acid side chains surrounding the bound ANS, providing a restricted solvation subspace.24 Once crowding agents are introduced, albeit at low concentrations, distinct changes in the solvation response could be observed in both a crowder- and protein-dependent fashion. In the presence of 2 g/L dextran 6 the observed C(t) decay time, that is, the solvation time (τs), for BSA was ∼1700 ps, which is significantly faster than that observed in buffer. An increase in dextran 6 concentration to 5 and 10 g/L resulted in even faster solvation times (Table 1 and SI Figure 5). At 10 g/L the solvation response of 700 ps implies almost a 3.5-fold increase in solvent reorientation dynamics around the bound ANS molecules as compared to that in buffer (SI Figure 5). For 14149


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that, being intrinsically disordered (unfolded), it is devoid of any well-formed secondary or tertiary structure and hence will have a large enough surface area to exhibit nonspecific association with BSA or HSA. Indeed, α-synuclein, as the macromolecular crowding agent, modulated the solvation dynamics of both serum proteins but in different ways. For BSA, unlike that observed for any other crowding agent before, the unfolded protein brought about a significant slow down of the solvent coordinate, with the average correlation time increasing to ∼3700 ps even at a concentration of 1 g/L. Increase in the protein-based crowder concentration led to a further delay in the solvent response, with the C(t) decay time becoming as slow as ∼4600 ps at 5 g/L α-synuclein (Figure 3A and Table 2). In case of HSA, while for 1 g/L the solvation time increased to ∼3000 ps, for 5 g/L α-synuclein there was a striking change with solvation becoming quite fast (∼1300 ps), thus bringing further to the forefront the intrinsic difference in the serum proteins belonging to the same family. Moreover, the inclusion of the protein-based crowder led to the appearance of a second solvation component which is much faster and probably signifies some local changes in the hydration structure of the water (Table 2). To extend our investigation of soft interactions we have also used the extensively studied heme protein myoglobin (Mb) as another potential crowding agent. Here, instead of probing the dynamic Stokes shifts, we have used the fact that ANS (as a donor) and heme (as an acceptor) can form an effective FRET pair with a calculated R0 value of ∼12 Å (Figure 4A). The

Table 2. Time-Resolved Stokes Shift and Solvation Response Time (τs) for ANS (15 μM) in BSA (15 μM) and HSA (15 μM) at Different Concentrations of α-Synuclein α-synuclein conc (g/L)

a1

1 2 5

0.91 0.91 0.99

1 2 5

1 0.79 0. 42

τs1 (ps)

a2

BSA 4015 0.09 4500 0.09 4668 0.01 HSA 2930 2720 0.21 3000 0. 58

τs2 (ps)

⟨τs⟩ (ps)a

Δν (cm−1)

198 525 120

3671 4140 4620

461 501 395

112 117

2930 2270 1325

460 395 376

For the double-exponential fits, the average solvation time ⟨τs⟩ was calculated by the following equation ⟨τs⟩ = a1τs1 + a2τs2, where a1 + a2 = 1. a

influenced the C(t) profiles. In the case of PEG8000 the solvent response function (C(t)) becomes much faster (1460 ps at 2 g/ L to 700 ps at 10 g/L) for BSA, while only a small change was observed in the case of HSA (1200 ps at 2 g/L to 1070 ps at 10 g/L) with increase in the crowder concentration. However, when PEG200 is used, we observed that the C(t) for HSA was much slower than that for BSA. Since the interior of the cell is crowded by many different proteins, we have also investigated how the solvation dynamics of the serum albumins is modulated by the protein α-synuclein. The choice of this protein (α-synuclein) was based on the fact

Figure 4. (A) Overlap of the absorption spectrum of myoglobin with the fluorescence spectrum of ANS of the sample BSA-ANS in buffer. (B) Emission spectra of ANS in 15 μM BSA at varying concentrations of myoglobin excited at 325 nm. (C) Efficiency of energy transfer between protein-bound ANS and Mb. (D) Variation of the donor−acceptor distance as a function of the concentration of Mb. 14150


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Figure 5. (A) Elution profiles of BSA obtained by SEC analysis with different crowding agents. (B) Elution profiles of (i) BSA with myoglobin, (ii) HSA with myoglobin, (iii) BSA with α-synuclein, and (iv) HSA with α-synuclein. Red circles (in iii and iv) show the peak(s) arising from the complexaton of α-synuclein with the individual serum proteins.

To confirm that the changes in the solvation pattern for the different crowding agents used here were not due to obvious differences in binding constants of the ANS molecule to the proteins, we constructed a Job’s plot and conducted Benesi− Hildebrand analyses to monitor the stoichiometry and the overall dissociation constants of the albumin−ANS complexes at the highest concentration of each of the crowders used. Our data (SI Table 1 and SI Figure 7) reveal that the stoichiometry remained constant throughout for all of the crowders at 1:4 (protein/ANS) and that the changes in the binding constant (except that in α-synuclein) were too small to be able to account for the changes in the solvation pattern that we observed. To further substantiate the same, we also performed time-resolved fluorescence studies that involved studying both the fluorescence lifetimes of the reporter molecule ANS and its time-dependent anisotropy in the different solvent systems in vogue. In all cases the average lifetimes of ANS bound to serum proteins are almost the same within experimental error (SI Table 2). The analysis of the anisotropy measurements also reveals a similar scenario wherein there are hardly any changes in the rotational components (SI Table 3). On the basis of the expectation that soft interactions should definitely entail the involvement of complexation/interaction between the crowders

reasons for not applying the TRES analysis in the case of Mb were twofold: (i) Because of the existence of FRET, the dynamics will be necessarily complicated as the rate of energy transfer will be an added component to be accounted for and (ii) even at the low crowder concentrations (g/L) of Mb used here, the absorption at 375 nm was quite high, thereby giving rise to the possibility of inner filter effects. Increase in the concentration of Mb resulted in a progressive decrease in the emission of bound ANS (bound to the serum proteins) arising from the energy transfer (FRET) from ANS to the heme moiety. In order to avoid complications due to the inner filter effect, the samples were excited at 325 nm, where absorption due to Mb was quite small (Figure 4B). We have also calculated the efficiency of energy transfer between ANS and Mb and observed that the efficiency increases with increase in the concentration of Mb (Figure 4C) for both BSA and HSA. This signifies an overall decrease in distance between the serum proteins and the surrounding Mb molecules, with the average FRET distance being less for BSA than for HSA. Our results reveal that even at low concentrations of Mb the crowder and test proteins are proximal enough to exhibit significant interactions by either forces that are electrostatic in origin or dispersion forces or a combination of both. 14151


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lower than that where one would expect the excluded volume effect to be instrumental. Indeed, to work at such low concentrations and have observable effects on the protein molecule, one needs a signature, that is, a change in a certain physical parameter, which is sensitive enough to capture such alterations. In this regard the dynamic Stokes shift observed for the fluorophore ANS bound to the serum proteins proved to be an excellent way of monitoring such crowder-induced protein modulations. The variation in the manner in which the crowders affected the solvation response of the two proteins, BSA and HSA, points to the intrinsic difference based on their individual shapes, sizes, and chemical compositions (Figure 6). When

and the serum proteins, size exclusion chromatography (SEC) experiments were also performed. However, from the SEC studies there were no obvious changes observed (except in the case of α-synuclein) (Figure 5). In other words, SEC analysis showed that the addition of crowding agents to BSA/HSA even at a concentration of 10 g/L did not result in a change in the elution volume of the serum proteins (Figure 5B), implying the absence of complexes being formed, thereby further supporting the rotational anisotropy data. However, the addition of αsynuclein along with BSA/HSA resulted in the near complete disappearance of the peak arising from this uncomplexed intrinsically disordered protein and the simultaneous development of another peak at a lower elution volume. This new peak at lower volume represents a species of higher molecular weight (around 415 kDa) and is due to protein−protein complexation. Moreover, on increasing the concentration of α-synuclein, the intensity of the native BSA/HSA peak decreased marginally and at the same time the intensity of the higher-molecular-weight species increased, implying that the higher-molecular-weight cluster included both BSA/HSA and α-synuclein molecules. These results suggest the presence of soft interactions between this protein crowder and the serum proteins even at these very low concentrations. It should be pointed out here that αsynuclein has been extensively studied as a model protein with regard to protein misfolding and aggregation (the latter leading to Parkinson’s disease in the case of α-synuclein). Our SEC studies reveal the presence of monomeric α-synuclein (as can be determined from the absence of higher-molecular-weight bands), thereby implying that the effect so observed is from the monomeric disordered protein only. On the other hand, SEC studies in the presence of Mb show no such complex formation between this crowder protein and the proteins from the serum family. However, an increase in the concentration of Mb from 1 to 5 g/L brings about a distinct change in the SEC profile of Mb itself, wherein at the higher concentrations the elution peak not only becomes broader but is also accompanied by another peak at a lower elution volume (Figure 5B), suggesting the formation of higher-molecular-weight species. This we propose to be due to transient reversible oligomer formation between the Mb molecules, thereby further corroborating the FRET data wherein the efficiency of energy transfer increased with increasing concentration of the protein crowder, the latter originating from the presence of such oligomeric entities of Mb.

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Figure 6. Variation of the solvation time (τs) at varying concentrations of crowding agents.

DISCUSSION On the basis of the general approach of the phenomenon of macromolecular congestion, the so-called inert macromolecules (behaving as impenetrable solutes) are considered to reduce the conformational space available for proteins to sample and thereby affect those reactions the most that are accompanied by considerable volume changes. For such excluded volume changes to cause visible perturbations, the common strategy has been to use relatively high concentrations of these macromolecular crowders. Recent reports have shown that in contrast to the general dictum that the effects of crowders are primarily entropic in nature, enthalpy effects are also important; that is, nonspecific interactions of variable origin have to be taken into account.33 Local interactions between the protein and the crowders can also be hydrophobic in nature, and thus entropy can play an important role in such soft interactions. One of the most significant aspects of our study is the fact that considerable changes in protein motion and/or protein hydration were observed at crowder concentrations much

used at very high concentrations (50 g/L and above), as has been done in the majority of the studies until now, the observed differences in the way these macromolecules affect protein conformation and dynamics have mostly been attributed to changes in their packing nature and/or the degree of entanglement of these polymeric species. Moreover, under such conditions, the preferential interaction of these polymers (macromolecular crowders) with the biomolecule under investigation can be quite complicated because, depending on the polymer, the fraction of monomeric species left to interact will vary.34 Indeed, at relatively high concentrations, it has been shown that these individual crowders can undergo compaction because of self-crowding.35 In other words, at low enough crowder concentrations, as used in this study, one can envision that our reaction systems would be devoid of such heterogeneities and hence would provide clearer insight into the existing interactions at the molecular level. 14152


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Figure 7. Comparison of the solvation time (τs) between the two serum proteins in the presence of the different crowding agents.

be observed. On the basis of the concept of packing density (related to excluded volume), dextran 6 and PEG8000, being of lower molecular weight, should have the maximum number of molecules per unit weight of the crowder. Hence their effects on protein solvation should have been the greatest had the excluded volume been the predominating effect. Taken together, these data further confirm the presence of soft interactions, with the latter being more operative for the larger crowders. To further probe the variation of C(t), we have constructed the TRES in more intermediate ranges of crowder concentration and have plotted the solvation times (τs) of the same in Figure 6. A general feature of the profiles which is evident is that with increase in crowder concentration, the solvent response time decreases, resulting from faster solvation of the probe (ANS) molecules at higher crowder levels. Since the concentrations of the polymers used are significantly below that at which these start to interact with each other and then

Our data show that all of the macromolecular crowders used exhibit significant soft interactions with the serum proteins. Changes in the solvation dynamics can also arise, in our case, from other effects such as changes in the binding stoichiometry of ANS or its dissociation constant being affected during the process. While Job’s plot analyses showed no changes in the stoichiometry for either protein, this together with the unchanged Kd values and the absence of high-molecular-weight peaks in the SEC, the constant fluorescence lifetime, and similar anisotropy results confirms that the solvation pattern changes are exclusively due to the modulations of the protein hydration layer. PEG is well regarded to have a propensity to interact with proteins, and hence it was not surprising to see its influence on the way the serum albumins solvated the bound ANS. Unexpectedly, the dextran-based crowders also induced appreciable variations in protein solvation. For example, for dextran 40 and dextran 70, the higher-molecular-weight crowders, when used at 10 g/L, the solvation was too fast to 14153


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proteins, which, in combination with the larger surface area of the longer polymers (as mentioned before), contributes to the observed variations in the solvent response. If one were to compare the two different types of crowders, one would have to take into account the fact that the number of −OH groups in the dextran-based crowding agents is greater than that in the PEG-based ones (Figure 8). Moreover, the hydrophobic backbone of dextran that includes the −CH2OCH2− groups is also higher per monomer unit, thereby providing enough factors that would give rise to a significant alteration in protein solvation. Furthermore, while PEGs are mostly linear openchain polymers, the dextrans are rodlike in shape and highly branched, thereby bringing in an additional morphological aspect that can affect their associations with the proteins under consideration. Even more interesting and relevant is that the two proteins, BSA and HSA, though having very similar structures and a high sequence identity, responded quite differently to the crowders (Figure 7). In general, the higher-molecular-weight crowding agents (dextran 70 and dextran 40) affected HSA more than they affected BSA; that is, they brought about steeper changes in the correlation times. On the other hand, BSA seemed to be more affected in the presence of the lower-molecular-weight crowding agents (dextran 6 and PEG200). Recent reports have revealed the existence of subtle structural differences between these two serum proteins.38,39 For example, an EPR-based study has shown that the structural disposition of BSA in solution is quite asymmetrical and rigid while that of HSA shows much more flexibility and also possesses a more symmetric distribution of fatty acids.38 Furthermore, a hydropathy analysis revealed that HSA is on average more hydrophobic than BSA.38 The latter finding is very much in agreement with our observed data as mentioned above. The longer-chain polymers exhibit more hydrophobic character and hence show more interaction with HSA, while BSA, being the more hydrophilic of the serum proteins, is more responsive to the shorter-chain polymers (more hydrophilic). In the case of α-synuclein as the crowding agent, again, both proteins exhibit opposite trends. For BSA, the solvation time of ANS increases as a function of the concentration of the disordered protein (α-synuclein) while the C(t) decay becomes faster for HSA under identical conditions. In other words, the rigidity of BSA is enhanced on interaction with the disordered protein while for HSA, at 2 and 5 g/L α-synuclein, the binding pockets harboring ANS show enhanced flexibility. This is further supported by the appearance of a second and much faster component of solvation in the case of HSA, with the amplitude of the same increasing with the increase in concentration of synuclein. Consistent with these observations, even at 5 g/L, in the presence of α-synuclein (Table 2), BSA shows a distinct decrease in the dissociation constant with ANS while HSA shows a slight increase in the Kd value (SI Table 1) as compared to the other crowders. However, no major changes were observed in the anisotropy decay parameters for ANS bound to BSA or HSA in the presence of 5 g/L α-synuclein (SI Table 3), again revealing that the changes are quite local in nature. The amino acid sequence of α-synuclein has been partitioned into three regions,40 namely, (i) the N-terminal region (residues 1−60), responsible for interaction with lipids, (ii) the central region (residues 61−95), showing high sequence hydrophobicity that has been implicated in the aggregation of this protein, and (iii) the C-terminal region (residues 96−140), which is predominantly hydrophilic, with

subsequently entangle, it implies that for a given protein (either BSA or HSA), the observed differences in the profiles of the solvation times arise from the intrinsic nature of these crowder molecules and their underlying mode of interaction with the protein. In other words, at these “dilute” concentrations, wherein the individual polymer molecules rarely overlap with each other, the soft interactions that are prevalent between the proteins and crowders are directly influenced by the nature of the chemical groups that these polymers possess. We hypothesize, that for dextran 40 and dextran 70, at these concentrations (2−10 g/L) wherein the polymers are not entangled enough, their larger surface area with a greater monomeric fraction of the polymers available, makes them more amenable to interacting with the serum proteins, thereby inducing the dramatic change in protein solvation at 10 g/L. PEG200, on the other hand, can be rather considered to behave as a small-molecule crowding agent having a greater probability of interactions with the protein backbone. Recent reports involving a combination of experimental and molecular docking studies have revealed that PEG polymers of higher molecular weight are more prone to interact with proteins mainly through enhanced hydrophobic effects based on the presence of more of the −CH2−CH2−O− units (Figure 8).36,37 In other words, the

Figure 8. Chemical structures of (A) dextran-based and (B) PEGbased macromolecular crowders.

switch from a predominantly hydrophilic potential for shortlength PEG-based polymers to a more amphiphilic surface for the longer PEG chains provides increased stability to the species docked on the protein surface. However, the variation in τs as a function of the concentration of PEG200, the shortestchain-length polymer used in this study, reveal that such PEG− protein interactions do occur, contrary to what was proposed earlier; that is, short-chain PEG-based polymers show almost no tendency to associate with the proteins. 37 These observations thus further support our conclusion that the modulation of the hydration layer in and around the binding pockets of proteins is a sensitive measure of such small-scale (local) perturbations. The structure of the dextran-based crowders (Figure 8) reveals the presence of multiple −OH and −CH2OCH2− groups, signifying that these polymers also possess the ability to exhibit interactions with the protein backbone and side chains of the constituent amino acids. Indeed, the observed variations in the solvent correlation traces are apt signatures of such interactions occurring between the dextran-based crowders and the serum albumins. Moreover, for a given protein (BSA or HSA), the differences in the manner in which these crowding agents influence the correlation decays (Figure 6) arise from the intrinsic differences at the molecular level that these crowders possess. For example, among the same series of crowding agents, either dextran-based or PEG-based, increase in the chain length leads to increase in the number of functional moieties responsible for interaction with the 14154


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The Journal of Physical Chemistry B its role still not being clearly understood.41 On the basis of these we propose that α-synuclein primarily interacts with the serum proteins through its middle hydrophobic region, since it is HSA, the more hydrophobic of the serum proteins where the ANS hydration is the most affected, the latter being made even more facile by the reported flexibility of human serum albumin in solution. Adding on to these aforementioned changes, the FRET data between the bound ANS and the heme moiety of Mb reveal that on average Mb enjoys greater proximity to BSA than to HSA, a result that might be a reflection of the differences in the three-dimensional structural disposition of the two serum proteins. Taking a closer look at Tables 1 and 2, one realizes that the dynamic Stokes shift Δν for ANS is the largest for BSA and HSA in buffer only and the same undergoes a marked decrease in the presence of crowders, with the maximum change occurring at the highest concentration of the crowding agents. Moreover, for all of the collected TRES curves, the emission spectrum constructed at the longest time point almost completely overlaps with that of the steady-state spectrum, signifying the attainment of equilibrium with regard to protein solvation during the probe (ANS) lifetime. Hence for those cases where the decrease in the time-dependent Stokes shift is large enough (greater than 100 cm−1) and is accompanied by a faster solvation correlation time (as compared to that in absence of the crowders), we might be missing part of the solvent coordinate because of the limited resolution of our TCSPC setup. In other words, even at these low concentrations, the respective crowders have induced solvation on the ultrafast time scale, that is, in the subpicosecond regime. On the other hand, for those crowders wherein the aforementioned Stokes shift is accompanied by almost no change in the correlation time (dextran 40 and dextran 70 at 2 g/L for BSA and PEG200 at 2 g/L for HSA) or an increase (effect of synuclein on BSA), there is an apparent enhancement in the rigidity of the protein matrix and/or the protein hydration shell surrounding the probe molecule. Of late, long time or slow protein solvation dynamics have been attributed to solvent polarization through protein fluctuations,42−44 though another school of thought exists wherein such dynamics have alternatively been thought to arise from protein hydration.22,23,27 Whatever the inherent reason might be, the fact such changes have been observed to occur at these low concentrations of the crowding agents shows that protein structural perturbation occurs much earlier than one might imagine in the crowded cellular milieu. Moreover, since in almost all cases (except for α-synuclein) we did not see any evidence of complex formation between the crowding agents and the test proteins, we may assume that the interactions exhibited are quite transient in nature. The exception for αsynuclein can be reasoned on the basis of its disordered, extended, and flexible structure, which along with the presence of many charged amino acid side chains enhances the probability of its association with BSA and HSA. Since fast fluctuations are known to play a major role in defining the functional characteristics of proteins and enzymes,45 our results suggest that such motions are prone to modulation even when the cellular crowding conditions are quite relaxed. In other words, by the time the excluded volume effects come into play in the physiological milieu, modulations of functionally important protein motions that need relatively lower activation energy have already taken place as a result of the aforementioned enthalpic (soft) interactions. Moreover, on

the basis of the polymer concentration, four different regimes have been proposed to be present, starting from very dilute concentrations wherein the polymers do not overlap with each other to very high concentrations where the polymers are severely entangled.9 Hence, it is natural to expect that as the concentration of the polymer is increased, based on the extent of entanglement, the manner in which the polymers would interact with the test protein would definitely vary. As a result, under those conditions, the perturbation of the solvent layer would be quite different from those observed for the dilute regime. Finally, with the current possible shift in focus from entropy-dominated interactions to enthalpy-associated effects46 along with the fact that local structural perturbations occur earlier than global modulations, we feel that the area of macromolecular crowding is poised to enter a new and exciting time wherein (non)specific interactions at the molecular level are geared to take center stage. In this regard, within the domain of a bottom-up approach, the widely varying behavior of different crowding agents (both synthetic and protein-based) with respect to protein solvation should be regarded as the first step toward a comprehensive understanding of the complex behavior inside the cellular interior.

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ASSOCIATED CONTENT

S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.jpcb.5b09446. Additional TRES figures and representative solvation decays and tables showing lifetime and rotational anisotropy data for the different crowders on HSAANS and BSA-ANS (PDF)

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AUTHOR INFORMATION

Corresponding Author

*E-mail: [email protected]. Tel: +911126591521. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS S.K.M. thanks UGC, India, and S.G., S.B., and J.K. thank CSIR, India, for their fellowhips. P.K.C. thanks the Department of Science and Technology (DST), New Delhi, India, for financial support under the Fast Track Scheme for Young Scientists (SR/FT/CS-007/2010) and IIT Delhi for startup funding.

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REFERENCES

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Do Macromolecular Crowding Agents Exert Only an Excluded Volume

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