pubs.acs.org/Langmuir © 2011 American Chemical Society
Kinetics and Mechanism of Single-Stranded DNA Adsorption onto Citrate-Stabilized Gold Nanoparticles in Colloidal Solution Edward M. Nelson† and Lewis J. Rothberg*,‡ †
Department of Physics and ‡Department of Chemistry, University of Rochester, Rochester, New York 14627, United States Received June 30, 2010. Revised Manuscript Received December 16, 2010
A variety of rapid biomolecular assays under development rely on the selective adsorption of single-stranded DNA onto unfunctionalized, negatively charged, citrate-stabilized gold nanoparticles. We investigate the adsorption mechanism with a study of the binding kinetics and find strong evidence for the dominance of hydrophobic effects including linear compensation between the activation energy and the natural log of the Arrhenius prefactor and the correlation of the adsorption rate in the presence of various salts with the Hofmeister series. These results explain the selectivity for single-stranded over double-stranded DNA adsorption and contradict previous work citing an electrostatic DLVO-like mechanism. Our understanding should facilitate improvements to the selective-adsorption-based assays and, more generally, contribute to the understanding of interactions between like-charged species in aqueous solution.
Introduction There has been a flurry of interest in nanoparticles for the purpose of biomolecular sensing.1 Noble metal nanoparticles in particular have a number of chemical and optical properties that make them extremely attractive for use in biotechnology. These properties include a large surface/volume ratio, flexible shape-controlled synthesis,2 chemically active surfaces that bind to amine3-5 and thiol6 groups, and biocompatibility in that they are generally nontoxic.7 In addition, these nanoparticles have useful optical properties such as a strong, tunable visible extinction that depends on the shape and size8,9 and can also result in the plasmonic enhancement of Raman scattering10-12 or fluorescence.13 Given these characteristics, *To whom correspondence should be addressed. E-mail: rothberg@chem. rochester.edu. (1) Caruthers, S. D.; Wickline, S. A.; Lanza, G. M. Curr. Opin. Biotechnol. 2007, 18, 26–30. (2) Wiley, B.; Sun, Y.; Chen, J.; Cang, H.; Li, Z.-Y.; Li, X.; Xia, Y. MRS Bull. 2005, 30, 356–361. (3) Leff, D.; Brandt, L.; Heath, J. Langmuir 1996, 12, 4723–4730. (4) Sastry, M.; Kumar, A.; Mukherjee, P. Colloids Surf., A 2001, 181, 255–259. (5) Selvakannan, P.; Mandal, S.; Phadtare, S.; Pasricha, R.; Sastry, M. Langmuir 2003, 19, 3545–3549. (6) Templeton, A. C.; Wuelfing, W. P.; Murray, R. W. Acc. Chem. Res. 2000, 33, 27–36. (7) Shukla, R.; Bansal, V.; Chaudhary, M.; Basu, A.; Bhonde, R.; Sastry, M. Langmuir 2005, 21, 10644–10654. (8) Liz-Marzan, L. M. Langmuir 2006, 22, 32–41. (9) Hurst, S. J.; Lytton-Jean, A. K. R.; Mirkin, C. A. Anal. Chem. 2006, 78, 8313–8318. (10) Aravind, P.; Nitzan, A.; Metiu, H. Surf. Sci. 1981, 110, 189–204. (11) Kneipp, K.; Wang, Y.; Kneipp, H.; Perelman, L.; Itzkan, I.; Dasari, R.; Feld, M. Phys. Rev. Lett. 1997, 78, 1667–1670. (12) Felidj, N.; Aubard, J.; Levi, G.; Krenn, J.; Salerno, M.; Schider, G.; Lamprecht, B.; Leitner, A.; Aussenegg, F. Phys. Rev. B: Condens. Matter 2002, 65, 075419–075427. (13) Thomas, K.; Kamat, P. J. Am. Chem. Soc. 2000, 122, 2655–2656. (14) (a) Mirkin, C. A.; Letsinger, R. L.; Mucic, R. C.; Storhoff, J. J. Nature 1996, 382, 607–609. (b) Elghanian, R.; Storhoff, J. J.; Mucic, R. C.; Letsinger, R. L.; Mirkin, C. A. Science 1997, 227, 1078–1081. (c) Taton, T. A.; Mirkin, C. A.; Letsinger, R. L. Science 2000, 289, 1757–1760. (d) Weizmann, Y.; Patolsky, F.; Willner, I. Analyst 2001, 126, 1502–1504. (e) Cao, Y.; Wei, C.; Jin, R.; Mirkin, C. A. Science 2002, 297, 1536–1540. (f) Park, S.-J.; Taton, T. A.; Mirkin, C. A. Science 2002, 295, 1503–1506. (g) Zhao, X.; Tapec-Dytioco, R.; Tan, W. J. Am. Chem. Soc. 2003, 125, 11474–11475. (h) Foultier, B.; Moreno-Hagelsieb, L.; Flandre, D.; Remacle, J. IEE Proc. Nanobiotechnol. 2005, 152, 3–12.
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it is not surprising that gold nanoparticles have been incorporated into a number of novel biomolecular sensors.14 In early implementations, the gold nanoparticles were covalently functionalized with specific molecular receptors to implement molecular recognition assays. More recently, however, it has been shown that similar assays can be designed using the fact that different biomolecules adsorb selectively onto unfunctionalized gold nanoparticles.15 The assays using unfunctionalized gold nanoparticles have substantial advantages in their simplicity and generality because the detection step can be effectively decoupled from the binding step so that molecular recognition can be tested under optimized conditions independent of the assay conditions. Of particular interest for the present study is a gold-nanoparticle-based DNA hybridization assay based on the surprising observation that single-stranded (ss) DNA adsorbs onto unmodified gold nanoparticles (Au-np) whereas double-stranded (ds) DNA does not.15 This discovery has led to a number of oligonucleotide, enzyme, small ion, and protein detectors16,17 that work without the need to functionalize the nanoparticles specifically, enabling much more general and practical assay development. Nevertheless, it remains poorly understood why there is a tendency for ssDNA to adsorb onto Au-np whereas dsDNA does not. In this article, we report studies of the adsorption kinetics of ssDNA on Au-np and its dependence on salt type, salt concentration, and temperature to reach a better understanding of the thermodynamics driving the process. (15) Li, H.; Rothberg, L. J. Proc. Natl. Acad. Sci. U.S.A. 2004, 101, 14036– 14039. (16) Li, H.; Rothberg, L. J. Anal. Chem. 2004, 76, 5414–5417. (17) (a) Li, M.; Lin, Y.-C.; Wu, C.-C.; Liu, H.-S. Nucleic Acids Res. 2005, 33, e184. (b) Wang, L.; Liu, X.; Hu, X.; Song, S.; Fan, C. Chem. Commun. 2006, 3780– 3782. (c) Wei, H.; Li, B.; Li, J.; Wang, E.; Dong, S. Chem. Commun. (Cambridge, U. K.) 2007, 3735–3737. (d) Zhao, W.; Chiuman, W.; Lam, J. C. F.; Brook, M. A.; Li, Y. Chem. Commun. (Cambridge, U.K.) 2007, 3729–3731. (e) Wang, W.; Chen, C.; Qian, M.; Zhao, X. S. Anal. Biochem. 2008, 373, 213–219. (f) Wang, Z.; Lee, J. H.; Lu, Y. Adv. Mater. 2008, 20, 3263–3267. (g) Zhang, J.; Wang, L.; Pan, D.; Song, S.; Boey, F. Y. C.; Zhang, H.; Fan, C. Small 2008, 4, 1196–1200. (h) Li, L.; Li, B.; Qi, Y.; Jin, Y. Anal. Bioanal. Chem. 2009, 393, 2051–2057. (i) Li, B.; Du, Y.; Dong, S. Anal. Chim. Acta 2009, 644, 78–82. (j) Shen, Q.; Nie, Z.; Guo, M.; Zhong, C.-J.; Lin, B.; Li, W.; Yao, S. Chem. Commun. 2009, 929–931. (k) Xu, X.; Wang, J.; Jiao, K.; Yang, X. Biosens. Bioelectron. 2009, 24, 3153–3158.
Published on Web 01/10/2011
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Both ssDNA and the citrate-stabilized gold nanoparticles used here are negatively charged, so an electrostatic description of adsorption within the context of Derjaguin-LandauVerwey-Overbeek (DLVO) theory18 as originally proposed by Li and Rothberg19 appeared to be a possible explanation. However, straightforward calculations of the Debye screening20 established that the linear charge density alone was not sufficient to account for the disparity in adsorption between ssDNA and dsDNA above monovalent salt concentrations of ∼20 mM. Moreover, as we show below, DLVO theory cannot account for either the observed base-sequence-dependent adsorption or the salt-type-dependent adsorption. These facts have motivated us to propose an alternative description of the interaction from the perspective of solvation effects. Specifically, we believe that the hydrophobic effect21 plays a dominant role in the interaction and can explain the phenomenology we observe. This insight into the adsorption thermodynamics should enable practitioners to broaden the applicability of the assay technology and to improve its sensitivity and specificity.
Materials and Methods Materials. DNA sequences were synthesized by IDT (Integrated DNA Technologies, Inc., Coralville, IA) and used without further purification. The following sequences were used: 50 -AAA AAA AAA AAA AAA-30 (referred to herein as poly(A)), 50 -TTT TTT TTT TTT TTT-30 (poly(T)), and 50 -CCC CCC CCC CCC CCC-30 (poly(C)). Homonucleobase sequences were chosen because each base has a different capacity to be hydrated and hence is influenced by the hydrophobic effect a little differently. Therefore, this selection represents extreme cases from the point of view of hydrophilicity. Guanine sequences were not considered because of their tendency to self-hybridize into G-quadruplex structures under certain conditions.22 The length of 15 bases was chosen because this is a common length of probe sequences in hybridization assays. The DNA sequences were modified with a Cy5 dye molecule (ex, 645 nm; em, 665 nm) at the 50 end. Given that the dye is small compared to DNA and the phenomenon seems to be nearly independent of the choice of dye, it is assumed and it has been our experience16 that most dyes have no effect on the interaction. Nevertheless, it has been demonstrated23 that Cy5 does not interact with the gold nanoparticle unlike other dyes that may.24,25 Salts sodium chloride (NaCl), ammonium sulfate ((NH4)2SO4), ammonium chloride (NH4Cl), potassium nitrate (KNO3), sodium sulfate (Na2SO4), sodium phosphate dibasic (Na2HPO4), and sodium phosphate monobasic (NaH2PO4) were obtained from Mallinckrodt Baker (Phillipsburg, NJ). For Au-np synthesis, hydrogen tetrachloroaurate(III) trihydrate (HAuCl4 3 3H2O) and trisodium citrate dihydrate (Na3C6H5O7 3 2H2O) were obtained from Alfa Aesar (Ward Hill, MA). The Au-np’s were prepared according to the procedure used by Frens26 and Grabar et al.27 This method yields particles with an absorption maximum at 520 nm and a particle diameter of 13 nm.27 Instrumentation. Fluorescence measurements were carried out on a Horiba Yobin Jvon (Edison, NJ) FluoroLog-3 spectrofluorometer with temperature control provided through a digital (18) Israelachvili, J. N. Intermolecular and Surface Forces; Academic Press: New York, 1985. (19) Li, H.; Rothberg, L. J. J. Am. Chem. Soc. 2004, 126, 10958–10961. (20) Nelson, E. M. Ph.D. Thesis, University of Rochester: Rochester, NY, 2008. (21) Kauzmann, W. Adv. Protein Chem. 1959, 14, 1–63. (22) Simonsson, T. Biol. Chem. 2001, 382, 621–628. (23) Pellegrino, T.; Sperling, R. A.; Alivisatos, A. P.; Parak, W. J. J. Biomed. Biotechnol. 2007, 2007, 26796–26804. (24) Nie, S.; Emory, S. R. Science 1997, 275, 1102–1106. (25) Maxwell, D. J.; Taylor, J. R.; Nie, S. J. Am. Chem. Soc. 2002, 124, 9606– 9612. (26) Frens, G. Nat. Phys. Sci. 1973, 241, 20–22. (27) Grabar, K. C.; Freeman, R. G.; Hommer, M. B.; Natan, M. J. Anal. Chem. 1995, 67, 735–743.
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Article circulating water bath manufactured by VWR Scientific (West Chester, PA). The procedure for fluorescence quenching measurements was as follows: the input and output monochrometers were set to the peak emission and excitation wavelength of Cy5 dye, respectively. Then, 500 μL of a 17 nM gold colloid in a 1 cm path-length cuvette was placed in the sample holder, and 500 μL of 85 nM DNA analyte in salt solution was added. The pH of the buffer was not explicitly controlled. The use of phosphate buffer solution in the 10-20 mM range would be comparable to the salt concentrations used in this study and would therefore interfere with analysis of the binding kinetics. The concentration of the salt buffer was deliberately set lower than optimum for biomolecular assays so that the adsorption kinetics was slow enough to be measured accurately. In addition, the lower salt concentration ensures that any colloid aggregation in minimized. Data acquisition began within 2 s of mixing the reagents together and ran for 300 s. For most samples, total fluorescence quenching occurred within 180 s. The fluorescence intensity of the nonadsorbed sequences is linear with respect to the fluorophore concentration so that timedependent fluorescence quenching measurements were fit to a single-exponential decay function using least-squares fitting to determine the characteristic binding rate. This fit is consistent with a single binding event in the dilute limit where changes in surface charge density or binding coverage over the course of the experiment have little effect on the binding rate. If the adsorbed DNA somehow affects the binding kinetics of nonadsorbed sequences, then we could expect to see second-order decay in the fluorescence signal. Consequently, we used MemExp software, which uses the maximum entropy method to analyze a time-dependent signal in terms of discrete or distributed lifetimes,28,29 to confirm the quality of the fit. Methods. Binding kinetics was used to determine the activation energy of the reaction, which we believe is relevant to the mechanics of adsorption. This is justified on a physical basis by arguing that the adsorbed state depends on the ability to create an intermediate population with some activation energy. We think it is reasonable to believe that there are three distinct processes necessary to reach the intermediate state that could contribute to an activation barrier. These are the desolvation of ssDNA, the desolvation of Au-np, and the transition of the oligonucleotide from a closed helix to an open form more conducive to adsorption. The desolvation of the oligonucleotide will depend on the concentration and solubility of the electrolyte as well as the makeup of the sequences. Likewise, the desolvation of the Aunp is also dependent on the type of salt. The third process, unwinding of the DNA helix, is strongly dependent on the nucleotide makeup of the sequence.30 Therefore, we can systematically investigate the solvation contributions by varying the salt type in the Debye limit and the unwinding contributions by varying the base sequence. Accordingly, the rate constant k can be expressed by the wellknown Arrhenius equation k ¼ Ae - Ea =RT
ð1Þ
where R is the gas constant, T is the temperature, Ea is the activation energy, and A is the exponential prefactor that may have some weak temperature dependence.31 In linear form, eq 1 can be written as lnðkÞ ¼ lnðAÞ -
Ea 1 R T
ð2Þ
(28) Steinback, P. J.; Chu, K.; Frauenfelder, H.; Johnson, J. B.; Lamb, D. C.; Nienhaus, G. U.; Sauke, T. B.; Young, R. D. Biophys. J. 1992, 61, 235–245. (29) Steinback, P. J.; Ionsescu, R.; Matthews, C. R. Biophysics 2002, 82, 2244– 2255. (30) Goddard, N. L.; Bonnet, G.; Krichevsky, O.; Libchaber, A. Phys. Rev. Lett. 2000, 85, 2400–2403. (31) Levin, I. N. Physical Chemistry; McGraw-Hill: New York, 1983.
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Table 1. Jones-Dole B Coefficient for Each Electrolyte Organized from Most Chaotropic to Most Kosmotropica salt
B (cm3 mol-1)
Bþ (cm3 mol-1)
B(cm3 mol-1)
KNO3 -47 -9 -38 -20 -11 -9 NH4Cl NaCl 70 79 -9 172 -22 171b (NH4)2SO4 NaH2PO4 288 79 209 305 158 171b Na2SO4 Na2HPO4 570 158 412 a In addition, ionic B coefficients in terms of their molar contribution to the electrolyte are also computed as described in the Materials and Methods section, assuming that Kþ and Cl- have similar Jones-Dole coefficients.34 Different cations resulted in two different results for SO42-: 194 cm3 mol-1 using NH4þ and 147 cm3 mol-1 using Naþ. b Midpoint value.
stating that when ln(k) is plotted against 1/T the resulting line of negative slope yields the activation energy Ea. The prefactor A is calculated from the intercept y0 = ln(A). The Jones-Dole viscosity parameter B was derived for each salt from data in ref 32 for aqueous solutions of electrolytes at T = 293 K. The viscosity of the electrolytes was fit to the equation η=ðη0 - 1Þ ¼ Γ þ Bc1=2 þ Dc3=2 c1=2
ð3Þ
where η is the viscosity, η0 is the viscosity of pure water taken to be η0 = 1.002 mPa s-1 at T = 293 K, c is the salt concentration, Γ is related to long-range interionic electrostatic forces and can be ignored for low salt concentrations,33 B is a direct measure of the interaction between the ions and the solvent, and D is a correction term that is included to make the expression valid at higher salt concentrations.34 The results are given in Table 1 and are organized by their rank in the Hofmeister series from the most chaotropic to the most kosmotropic electrolyte. The ionic contributions to the electrolyte B coefficient were calculated on the basis of their additivity. Adopting the premise that the ionic B coefficients of KCl (B = -18 cm3 mol-1) are nearly equal,34 all of the other ions in Table 1 could be determined.
Results and Discussion Evidence of the Role of Hydrophobic Effects. Figure 1 presents a series of adsorption kinetics data that show strong sequence and salt dependences that are inconsistent with a purely electrostatic explanation of ssDNA/gold nanoparticle interactions such as DLVO theory. These experiments used fluorescently tagged ssDNA in an electrolyte solution. When these sequences adsorb onto colloidal gold nanoparticles, the fluorescence of the associated tag is quenched by the interactions with the metal. Figure 1A depicts a cartoon of this process. In Figure 1B, we show that the binding kinetics depends considerably on the DNA base content of the sequence. The interaction between single DNA bases and the gold substrate is known to vary among the bases.35 It is speculated that the amine group in adenine and cytosine strengthens the interaction between the base and the substrate compared to that for thymine.36 Our study investigates barriers to adsorption as relevant to the assay and not the thermodynamics of the adsorbed state, so we are more concerned with DNA/ (32) CRC Handbook of Chemistry and Physics, 88th ed.; Lide, D. R., Ed.; CRC Press: Boca Raton, FL, 2008. (33) Collins, K. D. Methods 2004, 34, 300–311. (34) Jenkins, H. D. B.; Marcus, Y. Chem. Rev. 1995, 95, 2695–2724. € (35) Demers, L. M.; Ostblom, M.; Zhang, H.; Jang, N.-H.; Liedberg, B.; Mirkin, C. A. J. Am. Chem. Soc. 2002, 124, 11248–11249. (36) Kimura-Suda, H.; Petrovykh, D. Y.; Tarlov, M. J.; Whitman, L. J. J. Am. Chem. Soc. 2003, 125, 9014–9015.
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solvent and Au-np/solvent interactions. Therefore, we believe that the amine group affects only the activation energy and the kinetics we measure through solvent interactions, not through DNA/surface interactions. In this regard, the adsorption rate is correlated with the average number of water molecules hydrating each of the bases. Adenine binds, on average, to four water molecules:37 one at each of the aromatic nitrogens N3 and N7, one at the amine group (NH2), and the fourth shared between the amine group and the N1 nitrogen. (Atomic numbering and the hydration diagram are available in the Supporting Information.) Cytosine also binds to four water molecules: one at the carbonyl oxygen (CdO), one at the amine group, and two shared between the N3 aromatic nitrogen of the amine group and the carbonyl group. Last, thymine binds to only three water molecules: one at each of the two carbonyl oxygens and a third shared between the imine site (NH) and the C4 carbonyl site. At the other end of the nucleotide, up to four water molecules bind to the phosphate groups. The correlation between the hydration number and the binding rate may be a consequence of the DNA’s secondary structure. To reduce its solvent-exposed surface area, ssDNA undergoes small conformational changes such as increasing long-axis helical coiling. Before this can happen, the bases must dehydrate,38,39 and on the basis of the number of hydrating water molecules, adenine is less likely to dehydrate than thymine, hence adenine has a greater probability of being in an uncoiled state and subject to solvation forces. Figure 1C,D presents data demonstrating how the binding rate responds to systematic changes in the electrolyte. When only the cation in the experiment was changed from an ion that is relatively low in the Hofmeister series such as Naþ to an ion that is high in the series (e.g., Mg2þ), the binding rate increased (Figure 1C). This is consistent with the idea that kosmotropes near hydrophobic surfaces are quite effective at aggregating hydrophobic particles because of hydrogen bond competition with hydrating water molecules that causes the hydrophobic surface to minimize its solvent-accessible surface area.33 When the anion in the electrolyte was changed from Cl- to an ion higher in the Hofmeister series (HPO42-), the binding rate decreased (Figure 1D). This is a surprising result because, according to the Hofmeister series, kosmotropic anions are more likely to increase the hydrophobic effect by forming strong hydration networks in the bulk.40 We will revisit this observation later in the article. These results demonstrate a systematic adsorption rate dependence on ion type and are a convincing reason to investigate the role of solvation effects in driving ssDNA to adsorb on unfunctionalized gold nanoparticles. The observations documented in Figure 1 strongly point to the important role of hydrophobic forces in mediating the ssDNA/gold nanoparticle interactions. Compensation Effect. Most first-order, thermally activated interactions follow an Arrhenius law that is described by eq 1. The activation energy Ea is the minimum energy required for a reaction to take place at a given temperature, and the prefactor A is a measure of the total interparticle interaction frequency within the system. In most cases, changing the activation energy within a process would not have an effect on the prefactor. In other words, the activation energy and the prefactor are independent of one another. Nevertheless, some systems demonstrate a (37) Liu, D.; Wyttenbach, T.; Bowers, M. T. J. Am. Chem. Soc. 2006, 128, 15155–15163. (38) Baldwin, R. L. Biophys. J. 1996, 71, 2056–2063. (39) Lund, M.; Jungwirth, P. J. Phys.: Condens. Matter 2008, 20, 494218– 494221. (40) Zangi, R.; Hagen, M.; Berne, B. J. J. Am. Chem. Soc. 2007, 129, 4678–86.
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Figure 1. (A) Cartoon of the interaction between ssDNA and citrate-coated Au-np. Dye-modified ssDNA in an electrolyte adsorbs onto unfunctionalized gold nanoparticles where the fluorescence is quenched. Not shown are the negative charges located on the phosphate groups of DNA and the anions that form part of the electrolyte. The diagram is not to scale. (B) Fluorescence quenching of poly(A), poly(T), and poly(C) by adsorption onto Au-np in 10 mM NaCl at 293 K. (C) Fluorescence quenching of poly(A) in electrolytes that differed only by the cation whereas the anion was always Cl-. NaCl and NH4Cl were at 10 mM concentration, and MgCl2 was at 1 mM concentration. The temperature in these experiments was 293 K. (D) Fluorescence quenching of poly(A) in electrolytes that differed only in the choice of anion. The cation in these experiments was always Naþ. The monovalent electrolytes were at 10 mM concentration, and the divalent electrolytes were at 5 mM concentration. The temperature in these experiments was also 293 K.
compensation effect by which changing the activation energy also changes the prefactor. In these systems, the compensation is often linear and is described by the equation lnðAÞ ¼ REa þ β
ð4Þ
where R and β are constants. The compensation temperature, which is the theoretical temperature when all interactions within the system have the same binding rate,41 is Tc = (RR)-1 where R is the gas constant. Compensation of this type has been observed in a wide range of phenomena such as micelle formation42 and in interactions involving proteins,43 lipids,44 and nucleic acids.45 Because the transfer of small particles in aqueous solutions is often characterized by the linear compensation between Ea and (41) Liu, L.; Guo, Q. X. Chem. Rev. 2001, 101, 673–695. (42) Chen, L.-J.; Lin, S.-Y.; Huang, C.-C. J. Phys. Chem. B 1998, 102, 4350– 4356. (43) Helms, V.; Deprez, E.; Gill, E.; Barret, C.; Hui Bon Hoa, G.; Wade, R. C. Biochemistry 1996, 35, 1485–1499. (44) Jonanovich, G.; A~non, M. Biopolymers 1999, 49, 81–89. (45) Breslauer, K. J.; Remeta, D. P.; Chou, W. Y.; Ferrante, R.; Curry, J.; Zaunczkowski, D.; Snyder, J. G.; Marky, L. A. Proc. Natl. Acad. Sci. U.S.A. 1987, 84, 8922–8926.
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ln(A), the compensation effect has been historically associated with the hydrophobic effect.46-49 The activation energy Ea and the Arrhenius prefactor A for the interaction between ssDNA and Au-np were determined by fitting eq 2 to plots of ln(k) versus 1/T as shown in Figure 2. The coefficient of determination r2, a measure of the linear association between ln(k) and 1/T, varies between r2 = 0.904 and 0.999 for both poly(A) and poly(T), indicating that between 90.4 and 99.9% of the total variance in ln(k) can be explained by eq 4. For poly(C), four out of the seven salts investigated demonstrated linear Arrhenius plots with r2 values above 0.799. Three of the salts (NH4Cl, KNO3, and NaH2PO4) showed a weak linear correlation. These salts had r2 values of 0.561, 0.536, and 0.222, respectively, which leads to large uncertainties in the estimate of Ea and the prefactor A. The calculated values of ln(A) and Ea are plotted against each other in Figure 3 where the data are classified by electrolyte, with (46) (47) (48) 7113. (49)
Lumry, R.; Rajender, S. Biopolymers 1970, 9, 1125–1227. Lee, B. Biopolymers 1991, 31, 993–1008. Baldwin, R. L.; Muller, N. Proc. Natl. Acad. Sci. U.S.A. 1992, 89, 7110– Fu, L.; Freire, E. Proc. Natl. Acad. Sci. U.S.A. 1992, 89, 9335–9338.
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Figure 2. Arrhenius plots of ln(k) vs 1/T for the binding kinetics interaction of ssDNA and Au-np. The activation energy Ea and the exponential prefactor A are calculated from best-fit lines indicated by dashed lines.
Figure 3. Compensation plot for the interaction of ssDNA and Au-np. Each data point is a separate experiment using the labeled salt and either poly(A) (red), poly(T) (blue), or poly(C) (green). The dashed line represents the best-fit line through all of the data points.
each salt being marked by its own symbol and each DNA sequence being marked by a different color. A visual inspection of the linear correlation in Figure 3 indicates compensation consistent with a hydrophobic process. The best-fit line (dashed line) by linear regression of all of the data points reveals a compensation 1774 DOI: 10.1021/la102613f
temperature of Tc=314 ( 5 K. The linear correlation coefficient F between ln(A) and Ea is F = 0.987, indicating a strong compensation effect. We should point out that the compensation effect remains controversial.50,51 Often times, the range of temperature that is experimentally available in aqueous reactions is small relative to the entire temperature scale.51 Even if it were possible to derive a meaningful estimate of Ea, which is determined from the slope of a linear Arrhenius plot, it would be of limited use in estimating the prefactor A given that it is determined from the y intercept and it is often many times outside the range of experimental temperatures. Data derived directly from calorimetric experiments would not be constrained by this limitation. When calorimetric data are not available, however, it is necessary to pay close attention to the errors in both Ea and ln(A) to ensure that any observed compensation is not a statistical artifact. If there is a high correlation between the errors in Ea and ln(A), then this can also lead to linear compensation plots.50 Krug et al.52 determined that experimental errors cause the parameters to be distributed in elongated elliptical probability regions that can be misinterpreted as lines. If the range of values of Ea and ln(A) is not as large as the range of the errors in Ea and ln(A), then the observed compensation can be merely a manifestation of the (50) Sharp, K. Protein Sci. 2001, 10, 661–667. (51) Cornish-Bowden, A. J. Biosci. 2002, 27, 121–126. (52) Krug, R.; Hunter, W.; Grieger, R. Nature 1976, 261, 566–567.
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experimental error.41 Therefore, drawing the error bars in a compensation plot is a test of the existence of genuine compensation. When deciding if the compensation effect is significant or merely a statistical artifact, it is necessary to compare the uncertainty in the data to the overall range in Ea and ln(A).41 The data in Figure 3 show roughly 3 times the range of the error, indicating that there is a good chance that eq 4 describes the compensation for this interaction. Considering only the compensation within a specific DNA sequence (data of a single color in Figure 3), the range in the data compared to the error seems to be insufficient to establish if compensation exists. Finally, if we look at the compensation between different sequences under a single electrolyte, the range between data points is significantly greater than the error. This demonstrates that compensation is strongly dependent on the properties of DNA. This seems to confirm the binding kinetics results from Figure 1B that show differences in the binding rate among the three sequences. In the context of the hydrophobic effect, the binding rate difference confirms that large changes in the activation energy are a result of structural hydrophobic changes in the DNA. It is inconclusive from these results whether differences between the electrolytes cause changes in the activation energy or in the exponential prefactor. Quantification of Salt Effects on Hydrophobicity Using Solvent Viscosity. The influence of salt ions on hydrophobic processes can be traced back to experiments by Hofmeister,53 who ranked salt ions by their ability to precipitate protein in aqueous electrolyte solutions, a process referred to as salting out. The rank of each salt ion relative to one another came to be known as the Hofmeister series, and empirical evidence pointed to the ion surface charge density as the important parameter distinguishing the salts from one another in the series. The partial series among cations for a given anion is54,55 Mg2þ > Ca2þ > NH4þ > Liþ > Kþ ¼ Naþ
ð5Þ
from most effective to least effective at precipitating proteins. Among the anions for a given cation, the series is SO4 2 - > H2 PO4 - > Cl - > NO3 - > ClO4
-
ð6Þ
from most effective to least effective at precipitating proteins. The order of the ions is strongly dependent on the system, on the pH, on the temperature, and on the salt concentration, so it is not uncommon to see some of the ions switch positions54-56 or even a reversal of the entire series.57 There are two ways to understand the order of the ions in eqs 5 and 6. First, proteins are stabilized when they are surrounded by water molecules with large entropy. This signifies that weakly hydrated (chaotropic) ions will accumulate near the protein surface where weak interactions between the ion and the water molecule ensure that excess hydrogen-bonding capacity exists close to the protein surface. Therefore, weakly hydrated ions encourage protein stability and are low in the Hofmeister series. Second, the protein stability is also affected by changes in its wateraccessible surface area. To minimize hydrophobic residue exposure to solution, the protein undergoes minor conformational (53) Hofmeister, F. Arch. Exp. Path. Pharmakol. 1888, 24, 247–260. (54) Pegram, L. M.; M. Thomas Record, J. J. Phys. Chem. B 2007, 111, 5411– 5417. (55) Marcus, Y. Chem. Rev. 2009, 109, 1346–1370. (56) Cacace, M. G.; Landau, E. M.; Ramsden, J. J. Q. Rev. Biophys. 1997, 30, 241–277. (57) Bostr€om, M.; Tavares, F.; Finet, S.; Skouri-Panet, F.; Tardieu, A.; Ninham, B. Biophys. Chem. 2005, 117, 217–224.
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changes or, at the other extreme, much more disruptive processes such as crystallization or precipitation of the protein.54 Strongly hydrated ions found high in the Hofmeister series force proteins to adopt a more compact structure by dehydrating hydrophobic residues, thus leading to a destabilization of the protein. In later experiments, Jones and Dole58 demonstrated that the viscosity of water was affected by the strength of the interaction between the ions in the electrolyte and the water molecules. For dilute electrolytes of concentration c, the viscosity η is given by eq 3. The coefficient B is positive for strongly hydrated ions, referred to as kosmotropes, and negative for weakly hydrated ions or chaotropes. A strongly hydrated ion forms tight hydration shells around the water molecule, which decreases the overall mobility of adjacent water molecules and thereby increases the viscosity of the solution. Because hydrogen bonding between water molecules drives hydrophobic processes, it is common practice to rank the capacity of salt ions to drive hydrophobic adsorption by their B coefficient. The Jones-Dole B coefficient is a useful way to rank salt ions in that it offers a convenient approach to rank salts quantitatively in the Hofmeister series. In the next section, we show that the B coefficient also has a quantitative predictive value in determining the binding rate. Jones-Dole B Coefficient and the Binding Rate. Because the B coefficients are indicative of the effectiveness of each salt to stabilize or destabilize the system, they should also be related to the activation energy and therefore the binding rate. This is demonstrated in Figure 4 where the Jones-Dole B coefficient is plotted against k on a semilog axis for each DNA sequence as labeled. The numbered data points represent each salt. The temperature for each plot was 293 K. The best-fit lines are represented by dashed lines. The results of Figure 4 indicate that salt effects strongly influence the binding rate of ssDNA on Au-np. Of course, the Hofmeister series, as it is commonly expressed in the literature,54-56,59 ranks the cation and the anion independently of one another. However, the B coefficients have typically been determined for the electrolyte as a whole and not for each ion independently. Our data show, however, that one must consider the roles of the constituent ions to understand the adsorption fully. Surprisingly, salts containing a strongly hydrated anion, such as Na2SO4 or Na2HPO4 (the B coefficients of SO42- and HPO42are 215.5 and 590.1 cm3 mol-1, respectively), are the salts with the slowest binding rates, indicating a reversal of the Hofmeister series for anions. There are times when the Hofmeister series reverses direction, for example, when the solution pH is below the isoelectric point of the protein and anions are counterions rather than co-ions.57 The classic example is the precipitation of lysozyme (isoelectric point ∼11), which follows a reversed Hofmeister series at low pH. In this system, we make the following conclusions regarding the ions in the Hofmeister series. It is known that small, well hydrated, kosmotropic ions bind to polar groups via ion pairing.39 This leads to dehydration of the surfaces, a decrease in the solubility of the particles, and eventually to destabilization and aggregation. For cations, this justifies the direct Hofmeister series. For the anions, the reversed Hofmeister series is observed. Often times, biomolecules such as proteins, minimize their hydrophobic residue exposure by making small conformational changes. If anions are preferentially driven onto apolar residues by nonionic solvent effects,39 then these anions may dehydrate (58) Jones, G.; Dole, M. J. Am. Chem. Soc. 1929, 51, 2950–2964. (59) Zhang, Y.; Cremer, P. S. Curr. Opin. Chem. Biol. 2006, 10, 658–663.
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Figure 4. Jones-Dole B coefficient vs the binding rate k at 293 K on a semilog axis. The numbered points represent the various salts. The dashed lines are best-fit lines using a “robust’’ method that gives low weight to the outliers. The significance of outliers is discussed in the text.
Figure 5. Electrolyte effect on hydrophobic particle stability in solution based on component ion hydration. Dashed lines represent when the magnitude of the B coefficient for each ion pair is equal (positive slope) or counteracting (negative slope).
hydrophobic residues and lead to increased stability. Presumably, because kosmotropic anions have a stronger interaction with water than do chaotropic anions, the former would lead to greater conformational changes and thus to greater stability in solution thereby justifying a reversed Hofmeister series. At higher salt concentrations, conformational effects give way to much more disruptive effects such as crystallization and phase separation, so the reversed Hofmeister series may disappear at higher salt concentration. Regardless, it is unclear if the same argument can be made for DNA, whose conformational stability at low salt concentration is dominated by electrostatic effects.60 This is an aspect of the system that we do not yet fully understand and warrants further investigation. When the salts are decomposed into their ions, as shown in Figure 5, discernible differences between the salts exhibiting “fast’’ or “slow’’ characteristics are apparent. Here, fast refers to ions that increase the DNA adsorption rate compared to other more stabilizing ions and are either low in eq 5 or high in eq 6. Figure 5 is a way of illustrating what happens if we consider the Jones-Dole coefficients for the anion and cation separately. The border between fast and slow electrolytes occurs when the (60) Tinland, B.; Pluen, A.; Sturm, J.; Weill, G. Macromolecules 1997, 30, 5763– 5765.
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Jones-Dole coefficient for the constituent ions, Bþ and B-, are equal. In other words, the dashed lines represent borderline salts whose hydrophobic-particle-stabilizing properties are not dominated by the characteristics of either the cation or the anion. Interestingly, Figure 5 highlights the significance of the KNO3 outlier in Figure 4. According to Table 1 and its net B coefficient, the KNO3 salt should behave similarly to NH4Cl. In fact, the binding rate associated with KNO3 is closer to that of (NH4)2SO4, a stabilizing salt. Figure 5 shows how it is possible that a salt such as KNO3 with a low B coefficient can in fact be stabilizing. Because the anionic B- coefficient is greater in magnitude than the cationic Bþ coefficient, the properties of the salt are influenced by the anion in this ionic pair. In addition, because the anion is chaotropic and we have already seen that chaotropic anions lead to a stabilization of the particles, this signifies that KNO3 is in fact not destabilizing like NH4Cl but stabilizing like (NH4)2SO4. This further demonstrates why it is important to compare the characteristics of the individual ions and not just the salt. In negatively charged systems such as DNA under typical pH (8), one expects the cations to play a large role in the stability because of ion pairing that directly influences the hydration of the surfaces. What is interesting is how sensitive the binding rate is to the properties of the anion. Taking into consideration doublelayer effects18 and the ionic concentrations used in this study, we find that the anionic concentrations should be negligible near the hydrophobic residues. Therefore, it is interesting to observe in Figure 1D that there is large variability in the binding rate with salts of the same cation. First, this demonstrates the importance of nonionic solvation effects in interactions between hydrophobic particles. Second, the anionic B- coefficients in Table 1 are all, for the most part, greater in magnitude than their cationic counterparts, so the importance of the individual ions in this system should not be understated.
Conclusions The central motivation of our studies was to understand the binding of ssDNA onto citrate-coated gold nanoparticles in colloid solution. This is an interaction that forms the basis of a simple DNA-hybridization assay based on salt-induced nanoparticle aggregation and many follow-up biomolecular recognition assays that exploit unfunctionalized gold nanoparticles for their optical properties. A deeper understanding may help us to control the adsorption kinetics and thermodynamics so as to optimize this class of assay. In addition, because this is an interaction between like-charged particles, the results of this study may be sufficiently general to be of importance for biological physics Langmuir 2011, 27(5), 1770–1777
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and nanoscience where oligonucleotides and other highly charged particles such as proteins and nanoparticles interact with one another in ionic, aqueous environments. Some previous literature suggested that the primary forces in this interaction were electrostatic in origin. Despite its simplicity, DLVO theory fails to account for three very critical observations: (1) the DNA adsorption rate is nucleotide-dependent and (2) it systematically depends on the salt type, and (3) dsDNA, whose linear charge density is only twice that of ssDNA, does not adsorb even at high salt concentration.15 However, each of these observations can be justified in the context of solvation forces, specifically, the hydrophobic effect. Some classes of thermally activated processes demonstrate a linear compensation between the activation energy and the prefactor. Systems that are dominated by hydrophobic processes often display this type of compensation. The plot between the natural log of the Arrhenius prefactor and the activation energy Ea exhibits a linear correlation consistent with compensation and is strong evidence of a hydrophobically driven effect. We also found a correlation between the ssDNA adsorption rate on Au-np and the Hofmeister series. Moreover, the correlation of the adsorption rate with the Jones-Dole B coefficient relevant to ionic effects on water viscosity is quantitative. Unexpectedly, however, chaotropic anions resulted in faster binding whereas strongly hydrated kosmotropic anions slowed the reaction down. We speculate that strongly hydrated anions bind to hydrophobic residues on the DNA, increasing the coiling of the helix and consequently the solubility. Well-hydrated DNA is
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unaffected by hydrophobic-like effects, so the stability of the entire system improves. We believe that an important part of the reason that Au-np’s work so well in solution-based hybridization assays is that so much of their surface is not covered by citrate ions and is, in fact, quite hydrophobic. An important conjecture arising from our work is that this class of biomolecular recognition assay is not limited to gold nanoparticles but can be developed from any suitable hydrophobic surface. In summary, the interaction between ssDNA and Au-np for salt concentrations typical of assay (or physiological) conditions is dominated by hydrophobic effects. The speed of the interaction can be predicted quantitatively and regulated by insightful control of the electrolyte; salts with strongly hydrated cations and weakly hydrated anions driving the adsorption faster than do salts that are low in the Hofmeister series. Acknowledgment. This work was supported by a GAANN grant from the Department of Education (P200A040206) and a grant from the NSF (DMR-0804960). We thank the anonymous referees of this article for their constructive comments from which improvements were made to the analysis of the compensation effect. Supporting Information Available: The Jones-Dole B coefficient viscosity plot for each salt and a molecular numbering and hydration diagram of the bases. This material is available free of charge via the Internet at http://pubs. acs.org.
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