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Langmuir 2006, 22, 7296-7301
Specific and Nonspecific Interaction Forces Between Escherichia coli and Silicon Nitride, Determined by Poisson Statistical Analysis Nehal I. Abu-Lail† and Terri A. Camesano* Department of Chemical Engineering, Worcester Polytechnic Institute, Worcester, Massachusetts 01609 ReceiVed December 9, 2005. In Final Form: March 31, 2006 The nature of the physical interactions between Escherichia coli JM109 and a model surface (silicon nitride) was investigated in water via atomic force microscopy (AFM). AFM force measurements on bacteria can represent the combined effects of van der Waals and electrostatic forces, hydrogen bonding, steric interactions, and perhaps ligandreceptor type bonds. It can be difficult to decouple these forces into their individual components since both specific (chemical or short-range forces such as hydrogen bonding) and nonspecific (long-range colloidal) forces may be present in the overall profiles. An analysis is presented based on the application of Poisson statistics to AFM adhesion data, to decouple the specific and nonspecific interactions. Comparisons with classical DLVO theory and a modified form of a van der Waals expression for rough surfaces were made in order to help explain the nature of the interactions. The only specific forces in the system were due to hydrogen bonding, which from the Poisson analysis were found to be -0.125 nN. The nonspecific forces of 0.155 nN represent an overall repulsive interaction. These nonspecific forces are comparable to the forces calculated from DLVO theory, in which electrostatic-double layer interactions are added to van der Waals attractions calculated at the distance of closest approach, as long as the van der Waals model for “rough” spherical surfaces is used. Calculated electrostatic-double layer and van der Waals interactions summed to 0.116 nN. In contrast, if the classic (i.e., smooth) sphere-sphere model was used to predict the van der Waals forces, the sum of electrostatic and van der Waals forces was -7.11 nN, which appears to be a large overprediction. The Poisson statistical analysis of adhesion forces may be very useful in applications of bacterial adhesion, because it represents an easy way to determine the magnitude of hydrogen bonding in a given system and it allows the fundamental forces to be easily broken into their components.
Introduction The use of atomic force microscopy (AFM) to probe the physical properties of microbial surfaces has been in continuous evolution since the first AFM studies on microbes were performed. Quantitative information is now easily obtained as the AFM can detect nano- or picoNewton microbial interaction forces under physiological conditions.1 Such force measurements are used to gain insight on microbial adhesion forces and on the physicochemical nature of microbial surface macromolecules.2-5 For a sample that is heterogeneous and somewhat poorly defined, i.e., a microbe, it can be difficult to relate the measured forces to their fundamental components. In one study on Enterococcus faecalis, AFM force profiles were integrated, and the resulting energy profiles were compared with classical DLVO (Derjaguin-Landau-Verwey-Overbeek) predictions of such profiles.5 When bacterial sticking efficiencies were calculated based on AFM data or DLVO predictions, the DLVO-predicted values were many orders of magnitude smaller than those predicted from AFM force data. The discrepancy could be due to the fact that AFM force profiles on most bacterial species will display forces in addition to van der Waals and electrostatic forces, which are not accounted for in the DLVO theory. There also may be discrepancies due to the assumptions needed to * To whom correspondence should be addressed. Ph: 508.831.5380. Fax: 508.831.5853. E-mail:
[email protected]. † Current address: Center for Biologically-Inspired Materials and Material Systems, Duke University, Durham, NC. (1) Dufreˆne, Y. F. Micron 2001, 32, 153-165. (2) Van der Aa, B. C.; Michel, R. M.; Asther, M.; Zamora, M. T.; Rouxhet, P. G.; Dufreˆne, Y. F. Langmuir 2001, 17, 3116-3119. (3) Abu-Lail, N. I.; Camesano, T. A. Langmuir 2002, 18, 4071-4081. (4) Lower, B. H.; Yongsunthon, R.; Vellano, F. P.; Lower, S. K. J. Bacteriol. 2005, 187, 2127-2137. (5) Cail, T. L.; Hochella, M. F. Geochim. Cosmochim. Acta 2005, 69, 29592969.
apply these models to AFM data. In other studies where it has not been possible to decouple AFM force curves into fundamental components of the interaction, correlations have been developed to help explain the origin of the various forces. For example, the adhesion force from AFM retraction profiles on nine different strains of Streptococcus mitis, each interacting with silicon nitride, could be correlated with the water contact angle on bacterial lawns and with the nitrogen-to-carbon ratio on the bacterial surface, the latter parameter quantified by X-ray photoelectron spectroscopy (XPS).6 Despite some success with such correlations, it is generally not possible to quantitatively describe AFM force data on bacteria in terms of the underlying fundamental components. One approach to quantifying information from AFM force data is to concentrate on statistical analysis from many adhesion force measurements. Several approaches that rely either on a quantized distribution of discrete single-bond contact forces or on the histogram of the distribution of rupture forces have been used to determine individual bond forces between ligand-receptor interactions and self-assembled monolayers (SAMs) of carboxylic groups 7-9 or amino-terminated SAMs.10 This analysis has the most obvious physical meaning for well-defined samplesubstrate interactions, such as ligand-receptor pairs,8 but some success has been found in applying these approaches in bacterial adhesion studies.3,11 Limitations of this approach are that sev(6) Vadillo-Rodriguez, V.; Busscher, H. J.; Norde, W.; de Vries, J.; van der Mei, H. C. Langmuir 2003, 19, 2372-2377. (7) Hoh, J. H.; Cleveland, J. P.; Prater, C. B.; Revel, J.-P.; Hansma, P. K. J. Am. Chem. Soc. 1992, 114, 4917-4918. (8) Lee, G. U.; Kidwell, D. A.; Colton, R. J. Langmuir 1994, 10, 354-357. (9) Moy, V., T.; Florin, E.-L.; Gaub, H. E. Science 1994, 266, 257-259. (10) Wei, Z. Q.; Wang, C.; Zhu, C. F.; Zhou, C. Q.; Xu, B.; Bai, C. L. Surf. Sci. 2000, 459, 401-412. (11) Abu-Lail, N. I.; Camesano, T. A. EnViron. Sci. Technol. 2003, 37, 21732183.
10.1021/la0533415 CCC: $33.50 © 2006 American Chemical Society Published on Web 07/18/2006
Interaction Forces between E. coli and Silicon Nitride
eral hundreds to thousands of force measurements must be performed, requiring a long measurement time that could damage the sample,12 and for bacterial adhesion studies, it still can be difficult to relate the force distributions to their fundamental components. Another approach, which does not require as many measurements and can be used to quantify the individual strength of bond forces, is derived based on Poisson statistics.12,13 Applying a Poisson distribution to AFM pull-off data can allow an accurate estimation of the individual bond strengths and provide detailed information on the magnitude of the forces involved in the adhesion between the sample and tip.13 This method represents one of the only available ways to quantify hydrogen bonding between bacteria and surfaces from AFM data. The current study provides a detailed investigation of the interaction forces that affect the adhesion of E. coli JM109 to a model surface, a silicon nitride AFM tip. Poisson statistical analysis was used to decouple the specific and nonspecific forces that make up bacterial force profiles. Materials and Methods Cultures. Escherichia coli JM109 (K-12) was provided by Professor Kristin N. Wobbe of the Department of Chemistry and Biochemistry at Worcester Polytechnic Institute (Worcester, MA). Cells were grown in Luria broth [5 g of NaCl, 5 g of tryptone, 2.5 g of yeast extract in 1 L of milli-Q water (Millipore)] at 37 °C and 200 rpm and harvested when the OD600 reached 0.9. After being harvested, cells were centrifuged and washed with ultrapure water (Milli-Q water, Millipore Corp.) to remove excessive salts. The cells were then resuspended in ultrapure water until they were ready to be used. Atomic Force Microscopy Experiments. All AFM experiments were performed with a Dimension 3100 Nanoscope IIIa (Digital Instruments/Veeco) and silicon nitride tips (Digital Instruments/ Veeco). As a pretreatment, silicon nitride cantilevers were irradiated with ultraviolet light in air for 15 min to remove any organic contaminates prior to use.14 The spring constants of the tips were measured to be 0.13 ( 0.02 N/m.15 Bacterial cells from suspension were attached to cleaned, silanized glass slides by covalent bonding between bacterial carboxylic groups and amino groups of the aminosilane compound.3,16 Cells remained hydrated with water prior to AFM measurements, and AFM imaging was performed in tapping mode using ultrapure water. Force measurements were made on a bacterium-free area of the glass slide before and after making the measurement on the bacterium, to ensure that the tip’s properties had not been altered by contact with the sample.11 Although we have performed our force measurements in ultrapure water, we know that cells retained their structure and did not lyse over the time scale of these experiments, because this was verified with AFM imaging. Imaging of each cell was always performed prior to the force measurement, and revealed that E. coli JM109 cells retained their ellipsoid shapes and had dimensions within those reported in the literature.17 All force measurements were performed using a 2.39 µm/s pulling rate and with applied loads that varied between 3.7 and 8 nN. A typical AFM experiment lasted 2-3 h. A total of 11 bacterial cells from cultures prepared on 3 days were examined. For each bacterium, 3 force profiles were captured, always over the center of the cell. Bacterial Surface Roughness. From AFM images in tapping mode, we analyzed the roughness of the bacterial surfaces, quantified (12) Williams, J. M.; Han, T.; Beebe, J. T. P. Langmuir 1996, 12, 1291-1295. (13) Han, T.; Williams, J. M.; Beebe, J. T. P. Anal. Chim. Acta 1995, 307, 365-376. (14) Tomitori, M.; Arai, T. Appl. Surf. Sci. 1999, 140, 432-438. (15) Cleveland, J. P.; Manne, S.; Bocek, D.; Hansma, P. K. ReV. Sci. Instrum. 1993, 64, 403-405. (16) Camesano, T. A.; Logan, B. E. Langmuir 2000, 16, 4563-4572. (17) Amro, N. A.; Kotra, L. P.; Wadu-Mesthridge, K.; Bulychev, A.; Mobashery, S.; Liu, G. Langmuir 2000, 16, 2789-2796.
Langmuir, Vol. 22, No. 17, 2006 7297 in terms of the root-mean-square roughness (rms) parameter. Images of five bacterial cells were captured (scan size ) 15 µm, scan speed ) 1.01 Hz, 512 samples/line). The rms was measured on five replicate 200 nm × 200 nm areas. Contact Angle Measurements. Contact angles of ultrapure water (polar), formamide (polar), and diiodomethane (apolar) were measured on E. coli JM109 lawns, using a Rame´-Hart NRL Contact Angle Goniometer (model #100, Mountain Lakes, NJ). A 2 mL sample of ∼108 cells/ml was filtered onto a 0.45-µm silver membrane filter (Osmonics Inc.). At least 20 separate measurements with each liquid (2 µL droplets) were taken on both sides of each droplet. Poisson Analysis of the Adhesion Force Data from AFM Retraction Curves. Retraction curves were analyzed to quantify and characterize the adhesion events. In each cycle, at least one, but often multiple, adhesion events were observed, which represent an attachment between the AFM silicon nitride tip and a bacterial surface biopolymer (or biopolymers; Figure 1). Each adhesion event is characterized by a pull-off distance and a pull-off force as represented by the circles in panels A and B in Figure 1. The pull-off force is equivalent to the adhesion force and represents the sum of all interaction forces (specific and nonspecific) between the bacterial surface biopolymers and the silicon nitride cantilever. Beebe et al. developed a method for characterizing AFM pull-off force data using a Poisson statistical distribution function,12,13,18 which allows for the detection of the strength of individual chemical bond forces. The main assumptions underlying the application of the Poisson analysis to force data are (1) the total adhesive force (F) develops as the sum of discrete bonds, both chemical and noncovalent bond interactions, such as hydrogen bonding and van der Waals forces10 and (2) these bonds form randomly with a small probability and all have similar force values (Fi). This methodology was shown to be valid for characterizing single bond forces between carboxylic-functionalized surfaces,19 between silicon nitride and either gold or mica,20 for surfaces functionalized with organosilanes,21 and between biotin and avidin or streptavidin.22 The probability function that is used to describe the Poisson distribution of the forces formed at the pull-off point can be expressed as23 exp(-Fav) P(F) ) (Fav)n n!
(1)
where P(F) represents the possibility that an event with an adhesive force (F) will form, Fav is the average pull-off force of all individual pull-off forces, and n is the number of pull-off forces that occur in a certain range. In our case, Fav was taken as the average value for all of the 100 points shown in Figure 1C. The adhesive force, measured as a pull-off force event in forcedistance profile, is related to the number of bonds ruptured during the pull-off event by F ) niFi
(2)
where Fi represents the average individual-bond rupture force due to specific forces and ni represents the number of individual bonds. An additional parameter, Fo, can be added to account for nonspecific interactions. Based on the relationship between the measured force and the number of bonds ruptured (eq 2), one can derive relationships (18) Wenzler, L. A.; Moyes, G. L.; Olson, L. G.; Harris, J. M.; Beebe, T. B. Anal. Chem. 1997, 69, 2855-2861. (19) Han, T.; Williams, J.; Beebe, T. P., Jr. Anal. Chim. Acta 1995, 307, 365-376. (20) Williams, J. M.; Han, T.; Beebe, T. P., Jr. Langmuir 1996, 12, 12911295. (21) Wenzler, L. A.; Moyes, G. L.; Raikar, G. N.; Hansen, R. L.; Harris, J. M.; Beebe, T. P., Jr. Langmuir 1997, 13, 3761-3768. (22) Lo, Y.-S.; Huefner, N. D.; Chan, W. C.; Stevens, F.; Harris, J. M.; Beebe, T. P., Jr. Langmuir 1999, 15, 1373-1382. (23) Barlow, R. J. Statistics. A guide to the use of statistical methods in physical sciences; Wiley: New York, 1989.
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Abu-Lail and Camesano Table 1. Summary of Adhesion Forces between E. coli JM109 and Silicon Nitride, in Water, Measured by AFM cell
avg. F, nN
variance F, nN2
set sizea
1 2 3 4 5 6 7 8 9 10 11 All
-1.01 -6.36 -0.94 -1.13 -1.22 -4.26 -0.75 -0.64 -0.44 -0.64 -0.66 -1.30
0.11 0.75 0.08 0.15 0.14 0.54 0.07 0.09 0.01 0.03 0.07
18 2 7 17 22 7 5 4 7 4 7 100
a The total number of adhesion peaks observed in three force curves measured on each bacterial cell. Bacterial cells were from different cultures and measurements were performed on different days. Individual data points are shown in Figure 1C for all cells.
Figure 2. Distribution of absolute values of pull-off forces measured during retraction portions of force cycles between E. coli JM109 surface biopolymers and silicon nitride cantilevers in water. The solid line represents the theoretical Poisson distribution of the adhesion forces.
Figure 1. Examples of AFM retraction curves measured between a silicon nitride AFM tip and E. coli JM109 bacterial surface biopolymers, in water. (A) Example of data set that shows a single adhesion event. (B) Example of data set that shows multiple adhesion events. Each adhesion event is highlighted with circles. (C) A summary of all the adhesion events measured on 11 bacterial cells. This plot shows all of the data that was used for the analysis represented in Figures 2 and 3 and is also described in Table 1. Each different type of symbol corresponds to measurements on a single cell. for the mean (µF) and variance of the distribution (σF2), which are equivalent for a Poisson distribution µ ) µ FFi + F o
(3)
σ2 ) σF2Fi2 ) µFFi - FiFo
(4)
Linear regression is used to calculate Fi and Fo for a given data set.
For our measurements, µ and σ2 were taken as the average and the variance of all of the pull-off forces measured on one cell (Table 1). A plot of σ2 versus µ is shown in Figure 3. The slope of the linear regression line that passes through the data points shown in Figure 3 was taken as the specific force, Fi, and the intercept was used to calculate the nonspecific forces, Fo. Interfacial Free Energy Calculations. For two surfaces at equilibrium and in contact, the net free energy of adhesion between the two surfaces can be described as a function of the apolar (van der Waals) and polar (Lewis acid-base) free energies. Free energies are related to the surface tension components of the two surfaces. The various surface tension components of the bacterial cell can be calculated using the Young-Dupre´ equation24 LW + - + (1 + cosθ)γL ) 2(xγLW s γL + xγs γL + xγs γL )
(5)
where θ is the contact angle, γL is the total surface tension of the liquid, γLW is the Lifshitz-van der Waals, or a polar surface tension i component of condensed material (i), γ+ i and γi are the electronacceptor and electron-donor parameters of the Lewis-acid base components of the surface tension of condensed material (i),25 and the subscripts “S” and “L” refer to the bacterial and liquid phases. (24) de Gennes, P. G. ReV. Mod. Phys. 1985, 57, 827-863. (25) van Oss, C. J. Interfacial Forces in Aqueous Media; Marcel Dekker: New York, 1994.
Interaction Forces between E. coli and Silicon Nitride
Langmuir, Vol. 22, No. 17, 2006 7299 Aii ) 24πHo2γLW i
(9)
Electrostatic-Double-Layer Interactions. The electrostaticdouble-layer interactions between the bacterium and tip are calculated from the linearized version of the Poisson-Boltzmann expression, for sphere-sphere interactions.29 Ee )
2πapamNA (am + ap)κ
(φm2 + φp2)
2
{
2φmφp
φm + φ p 2
2
(
ln
)
1 + exp(-κh) 1 - exp(-κh)
ln[1 + exp(-2κh)]
Figure 3. Linear relationship between the mean and the variance of the pull-off forces, a requirement of the Poisson distribution. The error bars represent the standard errors of mean. The solid line (linear regression) was used to calculate the specific and nonspecific components of the adhesion, with resulting parameters being, the specific force, Fi ) -0.125 nN, the intercept (-FiFo) ) -0.019 nN2, and the nonspecific forces (Fo) ) 0.155 nN. R2 for the application of the Poisson distribution to these data ) 0.99.
}
(10)
where φm and φp are the normalized bacterial and tip surface potentials, respectively, κ is the inverse Debye screening length, and NA is Avogadro’s number. Surface potentials and radii for the bacterium and tip were measured by us previously.11 The values of the parameters used in our analysis were -20.2 mV, -16 mV, 500 nm, and 250 nm for the surface potentials, followed by the radii of the bacterium and the silicon nitride tip, respectively. An ionic strength of 0.0027 M was used for the ionic strength of ultrapure water, as previously estimated.30
Results
where A132 is the Hamaker constant for media 1 (bacterium) and 2 (silicon nitride) interacting across media 3 (solvent). The individual Hamaker constant for each of the interacting components can be calculated as26
Specific and Nonspecific Forces. The rupture forces between the silicon nitride tip and biopolymers were characterized by applying a Poisson distribution function to the distribution of adhesion forces (Figure 2). A summary of the mean and standard deviation of the adhesion forces per set is given in Table 1. A linear plot of mean versus variance of the force (Figure 3) was used to determine the specific and nonspecific components of the overall interaction force, which were -0.125 and +0.155 nN, respectively. Through the use of the Poisson-based analysis, the individual components of the overall interaction could be broken into their fundamental parts. Since there are no chemical bonds to be expected between silicon nitride and the bacterial surface, the specific forces can be attributed to hydrogen bonding. The measured nonspecific forces include van der Waals and electrostatic interactions, which can be compared with theoretical predictions. In calculating the theoretical van der Waals attractive force, two different models were used, both the classic model for smooth spheres, and a model accounting for the roughness of the interacting surface. To use the latter model, an estimation of the rms and the distance between asperities on the bacterial surface is necessary to calculate the van der Waals force component. AFM images on E. coli JM109 revealed that the rms value in water was 3.7 ( 0.5 nm, based on examining several 200 nm × 200 nm areas (images not shown). The asperity height was obtained from tapping-mode AFM images of a similar E. coli K-12 strain, HB101 (16.3 ( 2.8 nm;31). The Hamaker constant used in the van der Waals calculations was estimated from the liquid contact angle measurements on the bacterial lawns (Table 2) and was found to be 3.80 × 10-20 J for this bacterium in water, interacting with silicon nitride. With these parameters, van der Waals forces based on the “rough” model were -0.046 nN (Table 3). This value is much smaller than that predicted by the classical or smooth, spheresphere van der Waals model, which gives a value of -7.21 nN. Electrostatic-double layer interactions were found to be repulsive,
(26) Israelachvili, J. N. Intermolecular & Surface Forces, 2nd ed.; Academic Press: New York, 1992. (27) Rabinovich, Y. I.; Adler, J. J.; Ata, A.; Singh, R. K.; Moudgil, B. M. J. Colloid Interface Sci. 2000, 232, 10-16. (28) Rabinovich, Y. I.; Adler, J. J.; Ata, A.; Singh, R. K.; Moudgil, B. M. J. Colloid Interface Sci. 2000, 232, 17-24.
(29) Elimelech, M.; Gregory, J.; Jia, X.; Williams, R. A. Particle deposition & aggregation: Measurement, modelling and simulation; ButterworthHeinemann: Woburn, MA, 1995. (30) Abu-Lail, N. I.; Camesano, T. A. Biomacromolecules 2003, 4, 10001012. (31) Liu, Y. Personal communication.
van der Waals Forces. The nonretarded Lifshitz-van der Waals interactions between two spherical surfaces, FV, can be calculated as26 Fv ) -
A132amap
(6)
6h2(am + ap)
where the separation distance, h, is evaluated as Ho, the theoretical distance of closest approach (1.57 Å),25 A132 is the Hamaker constant of the bacterium with the tip in that media, am is the bacterial radius, and ap is the tip radius. For consideration of rough surfaces, a special form of the van der Waals expression can be used, in which the roughness of the adhering particle (E. coli JM109, in this case) is accounted for. If the roughness in the interaction is assumed to be primarily due to bacterial surface macromolecules, then the appropriate model for calculating the adhesion force has been derived as27,28 Fv,rough ) -
[
A132ap 6Ho2
1+
1 + 32apkvrms
(
λ2
)]
1 kvrms 1+ Ho
) (
2
(7)
where kv is a coefficient equal to 1.817, and the terms rms and λ refer to the root-mean-square roughness and height of asperities, respectively, on the bacterial surface. The Hamaker constant for the system is calculated as A132 ≈ (xA11 - xA33)(xA22 - xA33)
(8)
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Abu-Lail and Camesano
Table 2. Contact Angle Measurements on E. coli JM109 solvent
contact angle (θ)
Na
formamide water diiodomethane
43.0 ( 1.9 17.0 ( 3.8 50.1 ( 1.0
41 21 41
a N is the number of contact angle measurements averaged in the reported value.
Table 3. Comparison of Measured Forces, Those Predicted by Poisson Analysis, and Theoretical Calculationsa Fadh Poisson analysis, specific forces Poisson analysis, nonspecific forces theoretical van der Waals forces (rough model) theoretical van der Waals forces (classical, smooth model) theoretical electrostatic forces theoretical nonspecific: van der Waals (rough) + electrostatic theoretical nonspecific: van der Waals (smooth) + electrostatic a
-1.30 -0.125 0.155 -0.046 -7.21 0.162 0.116 -7.11
All values are in nN.
with a value of 0.162 nN. Since the nonspecific interactions are likely to be due primarily to van der Waals and electrostatic interactions, we summed those contributions. The summed contributions (when choosing the rough van der Waals model) agree fairly closely with the nonspecific interactions predicted through the use of the Poisson statistical analysis (0.116 nN compared with 0.155 nN), whereas the summed contributions based on the classical van der Waals model are very far from (and of opposite sign to) the values suggested by the Poisson analysis (total force of -7.11 nN for the smooth van der Waals model).
Discussion Breaking AFM Force Data into Components. In certain biological systems, for example, the binding forces between ligand-receptor pairs streptavidin and biotin, or between proteins and surfaces, discrete and well-defined forces govern the binding. These forces can be described using histograms to pick out discrete intervals of the binding force32 or through a thermodynamic treatment of bond energies.33 To describe the interactions between bacteria and a nonbiological surface, nonspecific interactions are always present, and in most cases, there are several types of interaction forces operating simultaneously. Repulsive forces can be observed during the approach portions of AFM force cycles, especially for bacteria which express large amounts or long polysaccharide polymers, such as Pseudomonas strains. In these cases, success has been observed with using a steric model to describe the repulsive bacterial polymer interactions with a smooth substrate.34,35 For strains that do not exhibit large steric forces due to surface polymers, such as Enterococcus faecalis, it has been possible to model the interaction forces from AFM approach curves using DLVO theory. The adhesion forces to surfaces could also be described based on the interfacial energy using the interaction force boundary layer (IFBL) theory. When both were compared, the latter model gave much more realistic (32) Sagvolden, G. Biophys. J. 1999, 77, 526-532. (33) Moy, V. T.; Florin, E.-L.; Gaub, H. E. Science 1994, 266, 257-259. (34) Camesano, T. A.; Logan, B. E. EnViron. Sci. Technol. 2000, 34, 33543362. (35) Emerson, R. J.; Camesano, T. A. Appl. EnViron. Microbiol. 2004, 70, 6012-6022.
results than the DLVO model.5 Another study showed fairly good agreement between extended-DLVO calculations (including acid/base interactions) and AFM approach curves of three different E. coli strains with a 1 mm colloidal probe (Pyrax), although the theoretical primary energy minimum, which would extend to negative infinity, could not be demonstrated from the experiments.36 AFM retraction force portions of the cycle between bacteria and surfaces always show some degree of attraction, due to surface molecules forming weak physical attachments with the AFM tip. Histograms and statistical tests can be used to distinguish the adhesion forces among different bacterial strains or among different experimental conditions.11 It has been difficult to model the adhesion forces more explicitly, since the number and type of polymers present on a bacterial surface is generally not known, and several types of interactions are occurring simultaneously. Therefore, a key advantage of the application of the Poisson statistical analysis techniques to AFM adhesion force distributions is that one does not need to know such detailed information on the nature of the polymers present. Regardless, one is still able to decouple the overall forces into their specific and nonspecific components. Importance of Hydrogen Bonding in Bacterial Adhesion. Applying the Poisson statistical analysis to the adhesion force distribution from AFM data allowed us to decouple the components of the specific and nonspecific forces involved in the adhesion of E. coli to silicon nitride. In addition, this analysis technique represents a very simple method to estimate hydrogen bond forces from AFM data for bacteria, since, when considering bacterial adhesion to inert surfaces, we usually do not have other types of specific forces present (i.e., chemical bonds). The technique was also successfully applied to biological systems which do exhibit chemical bonding, for example, to the study of binding between biotin-avidin or biotin-streptavidin.22,37 However, such specific chemical bond forces did not exist in the system we studied. The role of hydrogen bonding in controlling bacterial adhesion to inert surfaces has been less studied than some of the other components of the interaction, such as electrostatic-double layer forces or steric repulsion, in part because there has been no simple method to measure and/or quantify these forces. One study addressed very systematically the ability to form hydrogen bonds with metal oxide surfaces (TiO2, Al2O3, and SiO2) for the isolated O-antigens of several bacterial strains, including E. coli, Citrobacter freundii, and Stenotrophomonas maltophilia.38 Infrared spectroscopy was used to demonstrate that surface hydroxyl groups from the isolated saccharides interacted with water bound to the surface of the metal oxides. Although a very interesting result, the work was not extended to whole bacteria, so it is not known how other surface molecules may form hydrogen bonds with their contacting surfaces. From our analysis, we learned that the specific forces and nonspecific forces governing the adhesion of E. coli JM109 to silicon nitride are of a very similar magnitude. Therefore, it will be important to consider forces such as hydrogen bonding in predicting the overall adhesion or attachment behavior of bacteria to inert surfaces. The hydrogen bond value we estimate for a given experiment (0.125 nN) is similar to literature values, which reportedly range from 0.094 to 0.377 nN.26 AFM analysis has not been used to quantify hydrogen bonding between bacteria (36) Morrow, J. B.; Stratton, R.; Yang, H.-H.; Smets, B. F.; Grasso, D. EnViron. Sci. Technol. 2005, 39, 6395-6404. (37) Lo, Y.-S.; Zhu, Y.-J.; Beebe, T. P., Jr. Langmuir 2001, 17, 3741-3748. (38) Jucker, B. A.; Harms, H.; Hug, S. J.; Zehnder, A. J. B. Colloids Surf. B-Biointerfaces 1997, 9, 331-343.
Interaction Forces between E. coli and Silicon Nitride
Langmuir, Vol. 22, No. 17, 2006 7301
and silicon nitride previously. However, the technique has been applied to measure intramolecular hydrogen bonding in biological molecules. For example, by using an AFM force cycle to stretch the peptide cysteine3-lyseine30-cysteine from an alpha helix to a linear chain, intramolecular hydrogen bonds were broken, and such forces were quantified.39 With knowledge of the magnitude of hydrogen bonding in bacterial adhesion systems, which can easily be obtained from Poisson analysis of AFM force spectra, numerous applications can be affected. For example, one strategy to prevent bacterial adhesion to biomaterial surfaces relied on the creation of thin polymer films that lacked functional groups capable of forming hydrogen bonds, thus reducing the adhesion of bacteria (Staphylococcus aureus and Staphylococcus epidermidis) and proteins to the film surfaces.40 As another example, the resistance of bacteria to the antibiotic vancomycin has been shown to be related to the ability of certain bacteria to avoid forming a hydrogen bond with the antibiotic.41,42 These examples emphasize how important it is to consider hydrogen bonding, along with the typically considered van der Waals and electrostatic interactions, in applications that are controlled by bacterial adhesion to a surface.
Symbols Used
Acknowledgment. This publication was made possible in part by a CAREER Award to T.A.C. from the National Science Foundation (BES-0238627). We also acknowledge the donors of the Petroleum Research Fund of the American Chemical Society, for partial support of this work (PRF 38988-G2). The authors also thank Mr. Ray Emerson (WPI) for helpful discussions throughout the course of this work, and Dr. Jayne Morrow and Prof. Domenico Grasso, both formerly of Smith College, for their assistance with the contact angle measurements. (39) Lantz, M. A.; Jarvis, S. P.; Tokumoto, H.; Martynski, T.; Kusumi, T.; Nakamura, C.; Miyake, J. Chem. Phys. Lett. 1999, 315, 61-68. (40) Chapman, R. G.; Ostuni, E.; Liang, M. N.; Meluleni, G.; Kim, E.; Yan, L.; Pier, G.; Warren, H. S.; Whitesides, G. M. Langmuir 2001, 17, 1225-1233. (41) Loll, P. J.; Axelsen, P. H. Ann. ReV. Biophys. Biomol. Struct. 2000, 29, 265-289. (42) Walsh, C. T.; Fisher, S. L.; Park, I. S.; Prahalad, M.; Wu, Z. Chem. Biol. 1996, 3, 21-28.
am ) bacterial radius (nm) ap ) tip radius (nm) A132 ) Hamaker constant for interacting media (J) Aii ) individual Hamaker constant of each component (J) F ) adhesion force (nN) Fav ) average adhesion force, from AFM measurements (nN) Fe ) calculated electrostatic-double layer force (nN) Fi ) specific force component from Poisson distribution (nN) Fo ) nonspecific force component from Poisson distribution (nN) Fv ) van der Waals force for sphere-sphere interactions (nN) Fv,Rough ) van der Waals force for two spheres, accounting for surface roughness (nN) h ) separation distance between two interacting bodies (nm) Ho ) distance of closest separation (0.157 nm) kv ) dimensionless coefficient used in rough van der Waals force calculation (1.817) n ) number of occurrences of certain pull-off event ni ) number of individual bonds NA ) Avogadro’s number (#/mol) rms ) root-mean-square roughness of the bacterium (nm) φm ) Normalized surface potential of the bacterium φp ) normalized surface potential of the tip γL ) total surface tension of liquid (mJ/m2) γL+ ) electron-acceptor parameter of the Lewis acid-base surface tension component of the liquid (mJ/m2) γL- ) electron-donor parameter of the Lewis acid-base surface tension component of the liquid (mJ/m2) γLW L ) Lifshitz-van der Waals surface tension component of the liquid (mJ/m2) γs+ ) electron-acceptor parameter of the Lewis acid-base surface tension component of the bacterium (mJ/m2) γs- ) electron-donor parameter of the Lewis acid-base surface tension component of the bacterium (mJ/m2) γLW s ) Lifshitz-van der Waals surface tension component of the bacterium (mJ/m2) λ ) peak distance between asperities (nm) λc ) retardation correction (nm) θ ) contact angle µF ) mean of the adhesion forces (nN) σ2F ) variance of the adhesion force (nN2) LA0533415
