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On the hydrodynamic nature of DNA acoustic sensing Achilleas Tsortos, George Papadakis, and Electra Gizeli Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b01165 • Publication Date (Web): 27 May 2016 Downloaded from http://pubs.acs.org on May 30, 2016

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Analytical Chemistry

On the hydrodynamic nature of DNA acoustic sensing Achilleas Tsortos,1,* George Papadakis,1 Electra Gizeli1,2 1

Institute of Molecular Biology & Biotechnology, FO.R.T.H, Vassilika Vouton, 70013, Heraklion, Greece 2 Department of Biology, University of Crete, Vassilika Vouton, 71409, Heraklion, Greece

Keywords: DNA conformation, QCM-D, Love wave device, intrinsic viscosity, radius of gyration, surface effects * Corresponding Author: Dr. Achilleas Tsortos, tel: +30 2810 394093, [email protected] In memory of the late Dr. Yiannis Papanikolaou ABSTRACT In this work we provide strong experimental evidence on the hydrodynamic nature of the acoustic wave/biomolecule interaction at a solid/liquid interface. By using a wide range of DNAs of various sizes and by assuming DNA attachment as discrete particles through a neutravidin/biotin link, we prove experimentally that the acoustic ratio (dissipation/frequency) is directly related to the molecules’ intrinsic viscosity [η]. The relationship of [η] to the size and shape of biomolecules is described in general and more specifically for linear dsDNA; equations are derived linking the measured acoustic ratio to the number of dsDNA base pairs for two acoustic sensors, the QCM and Love wave devices operating at a frequency of 35 and 155 MHz, respectively. Single stranded DNAs were also tested and shown to fit well to the equation derived for the double stranded molecules while new insight is provided on their conformation on a surface. Other types of DNA are also shown to fit the proposed model. The current work establishes a new way of viewing acoustic sensor data and lays down the groundwork for a surface technique where quantitative information can be obtained at the nanometer scale regarding the shape and size, i.e., conformation of biomolecules at an interface. INTRODUCTION The measurement of the conformation of biomolecules on a solid surface has been a constant quest in fields such as molecular biophysics, analytical chemistry and materials science. Numerous surface techniques are currently in use. Besides the classical methodologies much progress has been made in the field of biosensors too. Optical ones like surface plasmon resonance1, dual photon interferometry2 and fluorescence3 have been shown to be able to detect structural changes. Electrochemical biosensors have exploited the distance of a probe, as it moves closer or away from an electrode surface, as an indicator for conformational change in the molecule 4,5. “Off-on” hairpin and other design DNA and RNA genosensors have been constructed for use in diagnostics and not only 6. Bulge-containing DNA duplexes have increased bending elasticity and this can be exploited to study mutations and insertion/deletion polymorphisms using square wave voltammetry 7. Finally, an ion-sensitive field-effect-transistor sensor has been recently used to study protein conformation changes following ligand binding 8.

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Despite the above efforts, still, no single biosensing technique exists that allows the user to know what specific signal to expect for a certain molecular geometry on a device surface; e.g. the signal that corresponds to the conformation of an anchored or physisorbed linear 100 base pair (bp) double stranded dsDNA or a globular protein. Acoustic wave devices have the potential to provide such information based on their ability to measure two signal changes; the wave’s frequency (F), related to mass and the wave’s energy (D) related to viscoelasticity. Indeed, up to now many studies have focused on monitoring a conformational change per se, e.g. ligand-induced transition in a glycoprotein 9, plasminogen 10, calmodulin 11,12, intrinsically disordered peptides 13 as well as RNA 14 and a DNA aptamer for the detection of ATP in serum 15 or estrogen 16. In addition, considerable efforts have been directed towards the development of models for acoustic data interpretation. Except for the two marginal cases of purely elastic/rigid films17 and purely viscous solutions 18,19, the biological layer is most often described by the model of a continuous viscoelastic film existing at the surface of the sensor 20,21 which comprises the macromolecules plus the solvent molecules (water). Such modeling is quite elaborate mathematically and relies on simplifications such as the homogeneity of the film; it typically derives information on the film thickness (df), effective density (ρf), absolute viscosity (ηf), elastic modulus (µf) or compliance (J 'f) 21-24, albeit without any kind of clear reference to the particular macromolecule characteristics. An alternative approach to the homogeneous film refers to the hydrodynamic nature of acoustic sensing. Within this concept, two-dimensional simulations employing the finite element method (FEM) 21,25 have been used to analyze the hydrodynamic interactions at the sensor surface obtaining descriptions of/information on the immobilized particles. Moreover, the quartz crystal microbalance QCM-D has been used to determine the size of a 30 nm mosaic virus26, adsorbed nm-size liposomes25,26 and metallic and polymer nanoparticles27 deposited on surfaces. One quantity frequently employed in acoustic analysis is the ratio ∆D/∆F i.e., the change in measured energy dissipation per surface-coupled unit mass, obtained with a QCM device. Since its first use in physics 28, this expression has independently received a lot of attention in biophysics and analytical chemistry as a qualitative fingerprint of the studied bio-layer producing information related to the layer’s structure (i.e., relative rigidity etc.). We recently proposed a new model which suggested that instead of using this ratio as a qualitative descriptor of film properties, it is possible to use it as a quantitative measure of the intrinsic viscosity [η] of the attached molecules, where [η] is a hydrodynamic property directly related to the hydrodynamic volume/shape of the biomolecule in solution. This approach relies on the assumption that attached biomolecules behave as discrete particles instead of a film. The analytical significance of this description can be realized if one considers the fact that [η] can be mathematically related to the geometrical features of the biomolecule under study, i.e., its shape and size, by using well known equations derived for polymers 29,30. Based on this approach it was shown that acoustic ratio measurements were able to discriminate surface attached double stranded (ds) DNA molecules of various sizes but same shape or DNAs of same size but various shapes (rod, bent, triangle) 29,30. Following these initial publications, several follow-up works from our group provided additional evidence on the validity of the approach; hybridized DNA structures of similar size but with a different geometry were resolved acoustically 31,32 as well as a DNA nanomachine switching between two distinct structures 33. However, with the exception of one case study 33, up to now the connection of acoustic ratio to [η] was made by use of theoretical modeling and semi-empirical approximations 29,30,32,34. In this work we take the concept further by determining the intrinsic viscosity [η] of a large structural variety of dsDNAs experimentally and deriving a mathematical relationship between ∆D/∆F and [η] for two of the most widely used types of acoustic systems, i.e., the QCM and Love wave. In addition, we measured and correlated for the first time the acoustic ratio and [η] of a whole range of single stranded (ss) DNAs and showed an excellent correlation of the two parameters, also in good agreement with the mathematical relationship obtained for the 2


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dsDNAs. The idea of the hydrodynamic nature of acoustic sensing was further supported by calculating theoretically the radius of gyration Rg of the ssDNAs and showing the expected good correlation to [η]. Last, we used a whole range of structures of DNAs to show the universal validity of the assumption that ∆D/∆F is a direct measure of [η], at least for DNA molecules anchored at the surface through a single point. In what follows, we first present briefly the theory behind our proposed acoustic wave sensing hypothesis followed by experimental results and a thorough in-depth analysis of the science underpinning acoustic hydrodynamic sensing at an interface. THEORY Theoretically, even the presence of a single molecule at the surface of a sensor would produce a signal. Given that current technology allows the control of surface coverage down to a few single molecules 35, we arguably cannot interpret acoustic data on the basis of film models. In our earlier work we suggested that the value of ∆D/∆F is dictated by the structural features of the attached molecules through a simple and, importantly, predictive model 29,30. The link between structure and acoustic wave properties was made through the intrinsic viscosity [η] of the molecule, a hydrodynamic quantity that is directly related to shape and is independent of concentration 36. The approach acknowledges the fact that biomolecules (such as DNA) anchored to the device surface can be viewed as discrete molecules (instead of forming a homogeneous viscoelastic film) and can thus be modeled using bulk solution viscosity theory equations η = η 0 (1 + [η ]C + K H [η ] 2 C 2 + O ( C ))

and

N  [η ] = ν  A V h  M 

(1) (2)

where η is the solution absolute viscosity at a particular solute concentration C, ηο the viscosity of the solvent; KH is the Huggins parameter and v, Vh and M are the shape factor, hydrated volume and molecular weight of the solute and NA the Avogadro number. The viscosity of a fluid reflects its resistance to flow; addition of large molecules increases viscosity in a manner dependent on three parameters: concentration, size and structure, i.e., molecular weight and shape, of these molecules. Associated with this resistance is a certain amount of energy being dissipated in the particular system. In dilute solutions (non-interacting molecules) and with the assumptions that D ~ η (the viscosity at the surface) and that F ~ C surf (the macromolecule surface concentration), we obtained the fundamental prediction of the model 29,30

D ~ [η ] F

(3)

For polymers the Mark-Houwink relation may be used, correlating the intrinsic viscosity with the molecular weight M of a macromolecule in a particular solvent

[η ] = KM

α

~ Lα

(4)

where α is a factor indicative of the shape and L is the contour length of the (linear) chain; in theory, α ranges from ~zero for globular molecules to 0.50 for random coils and approaches 1.8 for long stiff rods. In addition to the above general equations regarding polymer molecules, we experimentally determined [η] for linear dsDNA of length shorter than ~3,000 base pairs (bp) and found it to be 37 3



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[η ] = 3 . 5 ⋅ 10 − 4 M

1 . 05

( ml / g )

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(5)

EXPERIMENTAL MATERIALS & METHODS Figure 1 shows a cartoon of the sensor surface. A Quartz Crystal Microbalance (QCM, Q-Sense D300 or E4, Sweden) acoustic device was used with a fundamental frequency of 5 MHz (thickness shear mode, TSM) and a working range of 5-65 MHz. The results reported here are energy dissipation changes (∆D) and frequency shifts (∆F) for the 7th harmonic (i.e., 35 MHz) with the frequency data not divided by the harmonic. The other sensor used was a Love-wave device, a waveguide configuration based on a shear horizontal surface acoustic wave sensor (SH-SAW) operating at 155 MHz; the corresponding recorded quantities are wave amplitude ∆A (in dB) and phase ∆Ph (in deg) changes. For the QCM sensor the acoustic ratio ∆D/∆F (or ∆A/ ∆Ph for the SH-SAW) is obtained from the slope in the ‘D vs. F’ (or ‘A vs. Ph’) plot of the raw data.

β

Figure 1. Schematic drawing of straight and bent, double and triple-stranded DNA molecules, an open and closed Holliday junction and a single stranded DNA on an acoustic sensor surface (yellow). The single-point attachment is obtained via a biotin-neutravidin (black-red) interaction. Binding of each molecule on the sensor results in dissipation and frequency changes which are used to express ∆D/∆F at any particular frequency. All molecules were added by use of a flow-through system.

The buffers used here were PBS (pH 7.5, 150 mM NaCl) or Tris (50 mM, pH 7.5, 10 mM KCl) for the dsDNA; for the ssDNA PBS was used. The results are not influenced by the buffer choice for dsDNA, not even by the addition of 10 mM MgCl2; for ssDNA salt content is very important. The flow rate in the flow-through system used for passing the samples over the devices was 20 µl/min (shear rate ~1.9 sec-1). Neutravidin from Pierce (Germany) was used for the immobilization of all the biotin end-functionalized DNA molecules at the protein-saturated sensor surface. Details are given in previous publications 29,30,32. The acoustic data used in this study are either obtained here i.e., for the (30, 60, 75, 110, 157, 249, 297, 361, 422, 524, 689, 852, 1011, 1294, 1724) bp dsDNA chains or were previously reported30 by our group i.e., the (20, 50, 90, 132, 167, 198, 270, 395) bp chains, a total of 23 molecules for the QCM sensor. For the Love-wave sensor the here measured molecules were of (30, 50, 110, 157, 270, 297, 422, 524, 689, 852, 1011, 1294, 1724) basepairs in addition to the those reported previously with (20, 75, 90, 132, 167, 198) bp 29, a total of 19 molecules. The ssDNA measured here acoustically had (2, 5, 10, 21, 50, 60) bases in addition to the data of (75, 110) bases already reported32, all of random sequence. Primers and oligos were from Metabion (Germany) or IDT (USA) and Microchemistry (Heraklion). The experimental 4


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intrinsic viscosity of the (5, 21, 86) base ssDNA was measured here in PBS with a microviscometer (AMVn, Anton Paar) at 30 or 50 degrees angle as described before 37. The [η] experimental data for dsDNA are from Ref.37. The temperature was 25 ºC in all types of experiments. For details see the supporting information (SI-A). RESULTS Verification of acoustic ratio-[η] relationship for linear dsDNA In this study, linear dsDNAs were bound to a neutravidin-modified surface through a biotin linker attached to the 5’-end of the molecule; DNA was employed both for its value as a model hydrodynamic system and existing interest in nano-biotechnology applications. DNA molecules can be prepared at controlled lengths and attached at known points, thus providing well-regulated modified surfaces in order to facilitate data interpretation and assess validity of models developed to explain the sensor response. Figure 2 shows the relation between experimental ∆D/∆F values and the corresponding intrinsic viscosities for linear dsDNA in the range of 20-1,724 bp. In this figure we observe a linear relationship between [η] and ∆D/∆F up to a certain length, as predicted by theory (Eq. 3), and then a plateau is reached. Here this plateau value is ~ 0.11 (10-6/Hz) (at 35 MHz, QCM). 0.12

689

0.08

524

Δ Δ

D/ F

-6

(10 / Hz)

0.10

0.06 0.04 0.02 20 bp

0.00 0

200

η

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400

600

[ ] (ml/g)

Figure 2. The acoustic ratio/intrinsic viscosity relationship for linear dsDNA for the 35 MHz frequency of the QCM device. The [η] values are from the experimentally obtained Eq. 5. The numbers adjacent to the line indicate number of base pairs giving an approximate value of 600 bp at the ‘break’ point. Using data shown in Fig. 2, we derived the equation describing the first part of the graph resulting from the linear fit valid up to ~ 600 bp; this equation is  ∆D  3   ∗ 10 = 11.2 ± 0.3 + 0.340 ± 0.005 ∗ [η ]  ∆F 35

(6)

Based on Eq. 5 and the correlation of M to the number of base pairs (bp), the above is equivalent to  ∆D  3   * 10 = 10 . 5 ± 0 . 3 + 0 .137 ± 0 .002 ∗ ( bp )  ∆ F  35 ACS Paragon Plus Environment

(7) 5


Note that Eq.7 given for the QCM sensor here is an improved version of approximations given in Refs. 30,38 . To exclude the possibility that this result may depend on the particular acoustic wave device used, we repeated the same work employing another frequently used device, the Love wave sensor operating at 155 MHz. Following the same analysis Fig. 3 was produced.

Δ Δ

A / Ph ( dB / deg )

0.6 0.5 0.4 0.3 0.2 0.1 0.0 0

200

η

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400

600

[ ] (ml/g)

Figure 3. The acoustic ratio/intrinsic viscosity relationship for linear dsDNA for the 155 MHz frequency of the Love-wave sensor. The [η] values are from the experimentally obtained Eq. 5.

This figure shows that the response obtained with the Love wave device is similar to that obtained with the QCM. The correlation between ∆A/∆Ph and [η] or (bp) obtained for the linear part of the graph is described by the corresponding equations  ∆Α  3  * 10 = 57 ± 5 + 1.86 ± 0.13 ∗ [η ]   ∆Ph 155

(8)

 ∆A  3   * 10 = 53 ± 5 + 0 .75 ± 0 .05 ∗ ( bp )  ∆ Ph 155

(9)

Study of ssDNA at a QCM surface Besides double stranded DNA we extended the work to single stranded DNA molecules. We applied to the device surface ssDNAs of various numbers of bases and measured the change in D and F signals upon reaching equilibrium. Figure 4 shows the results; a remarkable feature is observed here: the ssDNA ratio rises fast at first reaching above the ds-curve and then it nearly flattens out, intersecting the ds-curve at ~ 55±10 bases.

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-6

(10 / Hz)

0.03

Δ

D/ F

0.02

Δ

0.01

0

20

40

60

80

100

120

140

# bases OR bp

Figure 4. The acoustic ratio (∆D/∆F) versus number of bases or base pairs; the black line represents Eq. 7 (with error margins) for dsDNA and in red are the experimental data for ssDNA.

This observation has never been made before and an explanation (let alone prediction) is beyond the reach of available theories, as ssDNA is assumed to be softer than dsDNA for all lengths. If the theory presented here predicts correctly, then [η] should follow the exact same trend as ∆D/∆F in Fig.4. The intrinsic viscosity of ssDNAs, measured as described in SI-B (Eq. S1), is plotted in Fig. 5 as a function of the number of bases. According to this figure, indeed, [η]ss follows the same trend to ssDNA bases as the acoustic ratio presented in Fig. 4, i.e., [η]ss rises fast and then it slows down intercepting the [η]ds curve at ~ 57 bases. 10

30

η

[ ] (ml/g)

8 20

6 4

Rg (nm)

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10 2 0

0 0

20

40

60

80

100

# bases OR bp

Figure 5. The intrinsic viscosity [n] (left Y-axis) versus the number of bases for ss (dot lines) and dsDNA (solid lines). The [η] lines are from the experimentally obtained Eq. 5 and Eq. S1. The radius of gyration Rg (right axis) is also shown as a function of the number of bases for ssDNA; Rg values were calculated from Eq. 10. 7



Having made the case for the intrinsic viscosity and in order to further test the idea of a hydrodynamic basis of the acoustic wave/particle interaction at the interface, we examined the behaviour of another hydrodynamics related parameter the radius of gyration Rg. This gives an equivalent-sphere radius for a chain in solution and depends on size and shape. Here we employed the worm-like-chain (WLC) model which has been extensively used, and shown to be accurate enough, for the evaluation of hydrodynamics related quantities of polymers, ss- and dsDNA39-41. The Benoit-Doty equation 42 is used here

1 P P2 P3 R = 2 PL { − + 2 − 3 (1 − e 6 2L L L 2 g

−L P

(10)

)}

with L = lN, N being the number of chain segments and l the rise/turn and P the persistence length. For dsDNA we use the typical values of P ~ 50 nm and l ~ 0.34 nm; these values do not depend on the ionic strength 37. For ssDNA we calculated P ~ 2 nm for our buffer conditions 43 and l ~ 0.6 nm. Figure 5 then shows the calculation for both ds and ssDNA using the values of (P, l ) (50, 0.34) and (2, 0.6) nm respectively; these values give an excellent fit of available experimental data (see SI-C). As can be seen the Rg data also follow closely the behaviour of the acoustic ratio of ssDNA in Fig. 4 and [η] in Fig. 5; all curves rise fast and then tend to a flatter area. Verification of acoustic ratio-[η] relationship for a variety of DNA shapes In an attempt to further check the general applicability of Eq. 6 we tested, in addition to the dsDNAs, single and triple stranded molecules as well as synthetic DNAs possessing specific structural features, such as the open and closed form of a Holliday junction molecule. Figure 6 shows that the relationship of acoustic ratio to [η] described by Eq. 6 holds for all surface-suspended molecules and not just the linear dsDNA i.e., for coil-like ssDNA, stiff-rod triple stranded tsDNA and the cross-like Holliday Junction. It, therefore, appears that the mathematical expression produced for dsDNA describes a ‘universal’ line at least for DNA molecules with [η] up to 50 ml/g end-tethered at a non-adsorbing surface through the neutravidin/biotin linker.

50-ts 86-ss

-6

(10 / Hz)

0.03

Δ

Hopen

D/ F

Δ

0.02 21-ss Hclosed 5-ss

0.01

0

10

20

η

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30

40

50

[ ] (ml/g)

Figure 6. The acoustic ratio/[η] relationship obeyed by all types and shapes of DNA. The ss, dsDNA and Holliday data are from our previous publications, Refs. 30,33,34 and this work; the tsDNA point’s ratio was measured before 34 and its [η] is obtained from Ref. 44

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DISCUSSION All the above data provide strong experimental evidence and drive to the conclusion that the underlying mechanism of acoustic sensing is of hydrodynamic nature. Below, we give a more detailed view of the analysed system and address some implicit assumptions and concerns regarding our model, mainly focusing on the effects that surface immobilization might have on the molecules and the molecule’s characteristic hydrodynamics related parameters. Surface orientation, molecular packing & flow effects The importance of hydrodynamics at a sensor surface has been stressed before 45. When a polymer chain is one-end tethered at a non-adsorbing and impenetrable surface, the surface sterically blocks end-overend tumbling, reducing the degrees of freedom relatively to the free molecule. For very long chains ( > µm scale, e.g. λ-phage DNA) extensive work with simulation 46-49 and fluorescence video microscopy techniques 50-52 has shown that there is hydrodynamic coupling within the chain i.e., the molecules drag along the surrounding solvent 47,50 and the chain stretches and fluctuates in size, exhibiting a rather complex dynamic behaviour with its orientation dictated by the interplay of shear flow and thermal fluctuations; the tilt angle approaches the surface as the shear flow increases. On the other hand, for shortstiff and intermediate length chains (e.g. up to a few hundred basepairs) the expected position is nearly an upright one 46 while bending and approaching of the surface is only expected for very high shear. For example, the hydrodynamic force is negligible compared to thermal fluctuations if one studies the orientation of a 21 bp DNA 47 in shear less than ~ 109 sec-1. The orientation of grafted molecules per se has also been studied 53-57; in the absence of flow, short ss- or ds-DNAs (< 24 bp) are found to be oriented away from the surface, tilted towards the normal 54,55. Regarding shape, for dsDNA no changes are expected; even long brushes at high surface coverage do not exhibit significant excluded volume effect 41,58. For ssDNA the shape is expected to be brush or mushroom-like depending on length and surface coverage 53,55. In our experiments we calculated the area per single-stranded molecule for 5, 21 and 86 bases to be ~ 1.5, 18 and 96 nm2 40; comparison to a (max) grafting density of one chain per neutravidin molecule of area ~ 42 nm2, suggests that these chains are in the mushroom regime (no strong overlap) 58. It must be noted that we also found no dependence of ∆D/∆F on surface coverage (for up to ~ 1,000 bp), also suggesting that chain-chain interaction is minimal at least in the sense that chain shape is not affected 29,30. In addition it has been shown that tethering of dsDNA on neutravidin via biotin does not affect its overall flexibility even if the anchoring point is not at the end 59. Under our experimental conditions then - non-adsorbing and negatively charged surface, Debye-Huckel screening length ≈1 nm and low flow rate (~ 1.9 sec-1) - it is expected that our (negatively charged) molecules protrude away from the surface, show no significant effect neither on tilt and stretch nor on [η]37 and are fully interacting with the solvent, a prerequisite for application of the model. Attachment effects on [η] and Rg There exists a question as to how well dimensionality is preserved when going from bulk to surface. In many studies it has been shown by simulation that for both Rg and Ree (chain end-to-end distance) when expressed in the form R = kM b the scale factor (exponent b) remains the same for the free and the oneend tethered (on a non-interacting surface) polymer chain 60-63. Nevertheless, the possibility of a direct relationship between polymer [η] and its dimensions/conformation when the chain is attached/adsorbed at a surface has been discussed only in a few publications 64,65. It was found that the hydrodynamically effective dimensions of molecular coils do not change greatly upon adsorption and especially [η] follows closely the thickness of the adsorbed layer both when (short)train-loops are involved and for end-on 9



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adsorption. This relationship is linear when adsorption is weak; in such cases, the dependence of the layer effective hydrodynamic thickness LH to [η] was also found to be linear, a result also corroborated by ellipsometry data 66. In many cases it is found that LH ≈ 2Rg 67,68. Although the situation is far from clear, these and other works on polymers and proteins69,70 point to bulk size preservation upon immobilization provided there is minimal interaction with the surface and among the chains. This is the case, for both ss- and ds-DNA on the neutravidin-covered sensor surface where non-specific binding was not observed in our experiments. The only direct measurement published 71 regarding end-tethered DNA is for (long) dsDNA chains and indeed shows that Rgbulk = Rgsurface . Confinement effects on [η] and Rg The shape and dynamics of individual DNA molecules when confined in a channel/slit of height h where flow exists (as is the situation inside an acoustic sensor chamber) is rather well studied. The deGennes and Odijk regimes where both Rg and relaxation times are affected (Rgsurface < Rgbulk) are reached only for very small heights, comparable to the chain dimensions i.e., h < 2Rgbulk 72-74. With respect to [η] of a chain flowing in a channel it is theoretically calculated that [η]conf. < [η]bulk only when h/Rg < 1.5 75. In our experimental setup h ~ 1 mm (for either sensor) while the longest DNA chain (1,724 bp) has a contour length of ~ 586 nm and so no confinement effect is expected. Acoustics Three experimental observations have not been answered within the presented model. The first one is that the linear part (for both sensors) reaches a plateau at some point; this is ~ 1,000 bp (∆D/∆F ~ 0.11) in the case of QCM. This plateau was reached at ∆D/∆F ~ 0.060 in previous work 30 and it was suggested that it coincides with the purely-viscous limiting-value (glycerol gives 0.055 10-6/Hz) 18,19,30; with the addition of more data points and corrections in the present work, this explanation is no longer valid. The second is the non-zero intercept in Fig. 2 (Eq. 7) and Fig. 3 (Eq. 9). Such non-zero intercepts in biosensor measurements have been reported before and although some attempts to identify plausible causes have been made a true explanation is lacking 30,76,77. The third observation is that the linear parts in Figs. 2, 3 appear to stop at different chain lengths. Assuming that this small difference is significant we can only attribute it to the difference in the acoustic mode and/or operating frequency. The Love-wave sensor operates at 155 MHz while the QCM one at 35 MHz. One possible explanation could come from the fact that at 35 MHz the penetration depth29 of the decaying wave is δ35 ≈ 95 nm while δ155 ≈ 45 nm. All of these questions certainly merit deeper theoretical investigation. Finally, of interest is the interpretation of data from Fig. 4, regarding the conformation of ssDNA at a surface. The fact that [η] changes little in the range of 20-110 bases, suggests that the molecules under the specific experimental conditions of applied buffer and attachment mode adopt a conformation which keeps the hydrodynamic interaction nearly the same. This graph comes to explain previous observations in our laboratory, regarding the similar acoustic ratio obtained for branched DNA molecules, where the branch consisted of ssDNA chains of different length 31.

CONCLUSIONS In this work we prove experimentally that the predicted relationship between the acoustic ratio of a surface attached biomolecule and its intrinsic viscosity [η] in solution is valid. The reported experiments provide a solid proof of the hydrodynamic nature of acoustic sensing. The validity is shown for such a large range of natural and synthetic DNAs of various shapes (rod, coil, cross-shape, etc.) and sizes (20 600 base pairs and 2-110 bases) that there is little doubt on the general nature of the proposed model, at least for DNAs attached through a single point on the device surface. The generality of the model is also exemplified by the use of the two different acoustic devices (QCM and Love wave), both of which 10


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provide the same relationship for the acoustic ratio and [η]. This may well be an important finding for acoustic biophysics and nano-biotechnology. First, given the direct relationship of the intrinsic viscosity to molecular size and shape, this is the only quantitative methodology available for characterizing molecular conformation using a label-free biosensor; for example, derived equations can be applied directly to determine the number of base pairs of an unknown DNA molecule or structurally characterize novel materials at surfaces something of great interest to nano-biotechnology 78. In addition, the proposed approach provides a new way of measuring the [η] of DNA especially in micro-environments 79. Regarding the detection capability of the method, with current sensor technology the resolution for ∆D/∆F is in the order of ~ 10% i.e., allowing discrimination of ~10 bases for short DNAs. In the case of bent DNAs we were able to detect a ~ 3% change in the Ree distance of two chains (see SI-D ). For the Holliday junction33 we detected a movement of no more than ~ 1-2 nm something challenging even for an AFM. Nevertheless, there is space for improvement; recently, usage of steadier temperature controllers and novel chamber design in the acoustic holder has made it possible to discriminate ~one DNA base 80,81 ; changing the entire experimental setup of QCM may also be a promising approach 82. Overall, our approach comes as complimentary to the ‘film view’ pointing to new directions in acoustic research and holds promise for future developments in molecular biophysics and interface studies. Supporting Information. Includes materials, DNA preparation, acoustic instrumentation, intrinsic viscosity measurements, radius of gyration and end-to-end distance calculations. Acknowledgements AT acknowledges the European Commission FP7-REGPOT-InnovCrete Program (Contract No. 316223), EG and GP the European Commission FP7-ICT program (Grant No. 317742, LOVE FOOD) and EG the European Commission & Greek Ministry of Education KRIPIS program (BIOSYS, No. MIS-448301) for financially supporting this work.

REFERENCES (1) Hall, W. P.; Modica, J.; Anker, J.; Lin, Y.; Mrksich, M.; Van Duynet, R. P. Nano Lett. 2011, 11, 1098. (2) Escorihuela, J.; Gonzalez-Martinez, M. A.; Lopez-Paz, J. L.; Puchades, R.; Maquieira, A.; Gimenez-Romero, D. Chem. Rev. 2015, 115, 265. (3) Moiseev, L.; Unlu, M. S.; Swan, A. K.; Goldberg, B. B.; Cantor, C. R. Proc. Natl. Acad. Sci. USA. 2006, 103, 2623. (4) Drummond, T. G.; Hill, M. G.; Barton, J. K. Nat. Biotechnol. 2003, 21, 1192. (5) Lubin, A. A.; Plaxco, K. W. Accounts Chem. Res. 2010, 43, 496. (6) Farjami, E.; Clima, L.; Gothelf, K.; Ferapontova, E. E. Anal. Chem. 2011, 83, 1594. (7) Chiba, J.; Akaishi, A.; Ikeda, R.; Inouye, M. Chem. Commun. 2010, 46, 7563. (8) Park, H. J.; Kim, S. K.; Park, K.; Lyu, H. K.; Lee, C. S.; Chung, S. J.; Yun, W. S.; Kim, M.; Chung, B. H. Febs Letters 2009, 583, 157. (9) Lee, H. S.; Contarino, M.; Umashankara, M.; Schon, A.; Freire, E.; Smith, A. B.; Chaiken, I. M.; Penn, L. S. Anal. Bioanal. Chem. 2010, 396, 1143. (10) Nileback, E.; Westberg, F.; Deinum, J.; Svedhem, S. Anal. Chem. 2010, 82, 8374. (11) Wang, X. M.; Ellis, J. S.; Lyle, E. L.; Sundaram, P.; Thompson, M. Mol. Biosyst. 2006, 2, 184. 11



1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(12) (13) (14) (15) (16)

Page 12 of 14

Furusawa, H.; Komatsu, M.; Okahata, Y. Anal. Chem. 2009, 81, 1841. Shur, O.; Wu, J.; Cropek, D. M.; Banta, S. Protein Sci. 2011, 20, 925. Ellis, J. S.; Thompson, M. Chem. Sci. 2011, 2, 237. Ozalp, V. C. Analyst 2011, 136, 5046. Peh, W. Y. X., E. Reimhult, H. F. Teh, J. S. Thomsen, and X. Su Biophys. J. 2007, 92,

4415. (17) Sauerbrey, G. Zeitschrift Phys. 1959, 155, 206. (18) Kanazawa, K. K.; Gordon, J. G. Anal. Chim. Acta 1985, 175, 99. (19) Ricco, A. J.; Martin, S. J. Appl. Phys. Lett. 1987, 50, 1474. (20) Voinova, M. V.; Rodahl, M.; Jonson, M.; Kasemo, B. Phys. Scripta 1999, 59, 391. (21) Reviakine, I.; Johannsmann, D.; Richter, R. P. Anal. Chem. 2011, 83, 8838. (22) Johannsmann, D. Macromol. Chem. Phys. 1999, 200, 501. (23) Osypova, A.; Thakar, D.; Dejeu, J.; Bonnet, H.; Van der Heyden, A.; Dubacheva, G. V.; Richter, R. P.; Defrancq, E.; Spinelli, N.; Coche-Guerente, L.; Labbe, P. Anal. Chem. 2015, 87, 7566. (24) de-Carvalho, J.; Rodrigues, R. M. M.; Tome, B.; Henriques, S. F.; Mira, N. P.; Sa-Correia, I.; Ferreira, G. N. M. Analyst 2014, 139, 1847. (25) Tellechea, E.; Johannsmann, D.; Steinmetz, N. F.; Richter, R. P.; Reviakine, I. Langmuir 2009, 25, 5177. (26) Reviakine, I.; Gallego, M.; Johannsmann, D.; Tellechea, E. J. Chem. Phys. 2012, 136, 084702. (27) Olsson, A. L. J.; Quevedo, I. R.; He, D. Q.; Basnet, M.; Tufenkji, N. ACS Nano 2013, 7, 7833. (28) Krim, J.; Widom, A. Phys. Rev. B 1988, 38, 12184. (29) Tsortos, A.; Papadakis, G.; Mitsakakis, K.; Melzak, K. A.; Gizeli, E. Biophys. J. 2008, 94, 2706. (30) Tsortos, A.; Papadakis, G.; Gizeli, E. Biosens. Bioelectron. 2008, 24, 836. (31) Tsortos, A.; Grammoustianou, A.; Lymbouridou, R.; Papadakis, G.; Gizeli, E. Chem. Commun. 2015, 51, 11504. (32) Papadakis, G.; Tsortos, A.; Bender, F.; Ferapontova, E. E.; Gizeli, E. Anal. Chem. 2012, 84, 1854. (33) Papadakis, G.; Tsortos, A.; Gizeli, E. Nano Lett. 2010, 10, 5093. (34) Papadakis, G.; Tsortos, A.; Gizeli, E. Biosens. Bioelectron. 2009, 25, 702. (35) Kufer, S. K.; Puchner, E. M.; Gumpp, H.; Liedl, T.; Gaub, H. E. Science 2008, 319, 594. (36) Harding, S. E. Prog. Biophys. Mol. Biol. 1997, 68, 207. (37) Tsortos, A.; Papadakis, G.; Gizeli, E. Biopolymers 2011, 95, 824. (38) Papadakis, G.; Tsortos, A.; Kordas, A.; Tiniakou, I.; Morou, E.; Vontas, J.; Kardassis, D.; Gizeli, E. Sci. Rep. 2013, 3, 2033. (39) Amoros, D.; Ortega, A.; Garcia de la Torre, J. Macromolecules 2011, 44, 5788. (40) Sim, A. Y. L.; Lipfert, J.; Herschlag, D.; Doniach, S. Phys. Rev. E 2012, 86, 021901. (41) Mansfield, M. L., A. Tsortos, and J.F. Douglas J. Chem. Phys. 2015, 143, 124903. (42) Benoit, H.; Doty, P. J. Phys. Chem. 1953, 57, 958. (43) Tinland, B.; Pluen, A.; Sturm, J.; Weill, G. Macromolecules 1997, 30, 5763. (44) Ojima, N.; Fukudome, K.; Yamaoka, K. Polymer J. 1994, 26, 303. (45) Squires, T. M.; Messinger, R. J.; Manalis, S. R. Nat. Biotechnol. 2008, 26, 417. (46) Manghi, M., X. Schlagberger, Y. W. Kim, and R. R. Netz Soft Matter. 2006, 2, 653. (47) Wang, G. M.; Sandberg, A. C. Nanotechnology 2007, 18, 135702. (48) Shaqfeh, E. S. G. J. Non-Newton. Fluid Mech. 2005, 130, 1. (49) Delgado Buscalioni, R. Phys. Rev. Lett. 2006, 96, 088303. 12


Page 13 of 14

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(50) (51) (52) (53)

Perkins, T. T.; Smith, D. E.; Larson, R. G.; Chu, S. Science 1995, 268, 83. Doyle, P. S.; Ladoux, B.; Viovy, J. L. Phys. Rev. Lett. 2000, 84, 4769. Shrewsbury, P. J.; Muller, S. J.; Liepmann, D. Biomed. Microdevices 2001, 3, 225. Levicky, R., T. M. Herne, M. J. Tarlov, and S. K. Satija J. Am. Chem. Soc. 1998, 120,

9787. (54) Erts, D.; Polyakov, B.; Olin, H.; Tuite, E. J. Phys. Chem. B 2003, 107, 3591. (55) Steel, A. B.; Levicky, R. L.; Herne, T. M.; Tarlov, M. J. Biophys. J. 2000, 79, 975. (56) Immoos, C. E.; Lee, S. J.; Grinstaff, M. W. Chembiochem 2004, 5, 1100. (57) Wong, K. Y.; Pettitt, B. M. Biopolymers 2004, 73, 570. (58) Bracha, D.; Karzbrun, E.; Shemer, G.; Pincus, P. A.; Bar-Ziv, R. H. Proc. Natl. Acad. Sci. USA. 2013, 110, 4534. (59) Vafabakhsh, R.; Ha, T. Science 2012, 337, 1097. (60) Netz, R. R.; Andelman, D. Phys. Rep.-Rev. Sec. Phys. Lett. 2003, 380, 1. (61) Huang, J. H.; Jiang, W. H.; Han, S. J. Macromol. Theory Simul. 2001, 10, 339. (62) Guttmann, A. J.; Middlemiss, K. M.; Torrie, G. M.; Whittington, S. G. J. Chem. Phys. 1978, 69, 5375. (63) Lax, M. J. Chem. Phys. 1974, 60, 2627. (64) Eirich, F. R. J. Colloid Interf. Sci. 1977, 58, 423. (65) Pefferkorn, E.; Dejardin, P.; Varoqui, R. J. Colloid Interf. Sci. 1978, 63, 353. (66) Kawaguchi, M.; Takahashi, A. Macromolecules 1983, 16, 1465. (67) Kato, T.; Nakamura, K.; Kawaguchi, M.; Takahashi, A. Polymer J. 1981, 13, 1037. (68) Cohen, Y. Macromolecules 1988, 21, 494. (69) Kawaguchi, M.; Hayashi, K.; Takahashi, A. Macromolecules 1984, 17, 2066. (70) Lopez-Montero, I.; Lopez-Navajas, P.; Mingorance, J.; Rivas, G.; Velez, M.; Vicente, M.; Monroy, F. Faseb J. 2013, 27, 3363. (71) Lehner, R., J. Koota, G. Maret, and T. Gisler Phys. Rev. Lett. 2006, 96, 107801. (72) Reisner, W.; Pedersen, J. N.; Austin, R. H. Rep. Prog. Phys. 2012, 75, 106601. (73) Bonthuis, D. J.; Meyer, C.; Stein, D.; Dekker, C. Phys. Rev. Lett. 2008, 101. (74) Strychalski, E. A.; Geist, J.; Gaitan, M.; Locascio, L. E.; Stavis, S. M. Macromolecules 2012, 45, 1602. (75) van Vliet, J. H.; ten Brinke, G. Macromolecules 1991, 24, 5351. (76) Reimhult, E.; Hook, F.; Kasemo, B. J. Chem. Phys. 2002, 117, 7401. (77) Mitsakakis, K.; Tsortos, A.; Gizeli, E. Analyst 2014, 139, 3918. (78) Yao, Y. B.; Luo, S. D.; Liu, T. Macromolecules 2014, 47, 3093. (79) Rust, P.; Cereghetti, D.; Dual, J. Lab Chip 2013, 13, 4794. (80) Yoshimine, H.; Kojima, T.; Furusawa, H.; Okahata, Y. Anal. Chem. 2011, 83, 8741. (81) Cai, H. L.; Yang, Y.; Chen, X.; Ali Mohammad, M.; Ye, T. X.; Guo, C. R.; Yi, L. T.; Zhou, C. J.; Liu, J.; Ren, T. L. Biosens. Bioelectron. 2015, 71, 261. (82) Webster, A.; Vollmer, F.; Sato, Y. Nat. Commun. 2014, 5, 5284.

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On the Hydrodynamic Nature of DNA Acoustic ... - ACS Publications

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