Optical Tracking of Surfactant-Tuned Bacterial Adhesion: a Single-Cell Imaging Study

ABSTRACT

Probing the interfacial dynamics of single bacterial cells in complex environments is crucial for understanding the microbial biofilm formation process and developing antifouling materials, but it remains a challenge. Here, we studied single bacterial interfacial behaviors modulated by surfactants via a plasmonic imaging technique. We quantified the adhesion strength of single bacterial cells by plasmonic measurement of potential energy profiles and dissected the mechanism of surfactant-tuned single bacterial adhesion. The presence of surfactant tuned single bacterial adhesion by increasing the thickness of extracellular polymeric substances (EPS) and reducing the degree of EPS cross-linking. The adhesion kinetics and equilibrium state of bacteria attached to the surface confirmed the decrease in adhesion strength tuned by surfactants. The information obtained is valuable for understanding the interaction mechanism between a single bacterial cell and surface, developing new biofilm control strategies, and designing anticontamination materials.

IMPORTANCE Studying the interfacial dynamic of single bacteria in complex environments is crucial for understanding the microbial biofilm formation process and developing antifouling materials. However, quantifying the interactions between microorganisms and surfaces in the presence of pollution at the single-cell level remains a great challenge. This paper presents the analysis of single bacterial interfacial behaviors modulated by surfactants and quantification of the adhesion strength via a plasmonic imaging technique. Our study provided insights into the mechanism of initial bacterial adhesion, facilitating our understanding of the adhesion process at the microscopic scale, and is of great value for controlling membrane fouling biofilm formation.

INTRODUCTION

Ubiquitous biofilms play a vital role in the natural environment, industrial applications, and medical settings (1–3). The initial bacterial adhesion to solid surfaces is the most crucial step in biofilm formation, controlled by the extracellular polymeric substances (EPS) of bacteria (4). The properties and components of EPS are influenced by a series of conditions such as flow shear stress, ionic strength, metal concentration and toxic substances through hydrodynamic shear force, ion bridging, electrostatic-hydrophobic interactions, and hydrogen bond force (5, 6). Many attempts have been made to study the effect of hydrochemical conditions on bacteria-surface interactions. For example, column experiments have been used to reveal the influence of ionic strength and persistent organic pollutants in the natural aquatic environment on the transport of bacteria (7, 8). Quartz crystal microbalance with dissipation (QCM-D) can analyze the viscoelastic properties of the bacterium-surface bond affected by hydrophobic interactions (9, 10). Most technologies analyze ensemble interactions with vast populations of cells, which washes out heterogeneity information from single bacterial cells and cannot measure the adhesion force of single bacteria. The exact role of complex hydrochemical conditions (such as the presence of pollutants or surfactants in nature water) in the initial bacterial adhesion to the solid surface is still unclear due to the lack of analytical tools for single bacterial cells.

Surfactants, as amphiphilic molecules, can adsorb to bacterial cells and affect biofilm formation. Since surfactants are increasingly used as detergents, wetting agents, emulsifiers, and foaming agents, especially after the outbreak of COVID-19 (4.1 million tons in 2017, with forecast growth of 18% by 2022) (11, 12), the presence of surfactants in subsurface or groundwater systems significantly influences the adhesion of bacteria. Initial bacterial adhesion is generally predicted by the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, with the estimation of the energy from the electric double-layer force and the van der Waals energy in terms of interparticle distance. The Lewis acid-base interactions are also considered in the extended DLVO theory (13, 14). However, the DLVO theory is often inaccurate for the complex biological regime (15, 16). Complex hydrochemical conditions bring challenges to the DLVO theory, as it assumes that microbial cells behave as inert particles and ignores the effect of surfactants on the bacterial surface (15). Meanwhile, DLVO theory lacks information from single bacterial cells. Therefore, it is challenging to unveil the surfactant-tuned bacterial adhesion at the single-cell level from a thermodynamic perspective.

This work aims to probe surfactant-tuned bacterial adhesion using a plasmonic single-cell interferometric imaging technique. We have recently developed a method to measure bacterial adhesion strength via plasmonic imaging of the intrinsic fluctuations of bacteria attached to the surface (17). To probe the tiny vertical fluctuations, we imaged the interferometric pattern of bacterial cells scattering the planar plasmonic wave propagating on the surface. The plasmonic scattering intensity was extremely sensitive to the vertical distance, allowing precise tracking of the fluctuations. From the fluctuation analyses, we obtained the interfacial energy profiles and elasticity of microbial binding. How surfactants affect bacterial adhesion, especially the binding thermodynamics, at the single-cell level remains unexplored. In this study, we used sodium dodecyl sulfate (SDS) and hexadecyl trimethyl ammonium bromide (CTAB) as model anionic and cationic surfactants, and we employed Pseudomonas aeruginosa PAO1, a ubiquitous environmental Gram-negative pathogen, as a model strain (18). The knowledge obtained can help better understand bacterial adhesion and be beneficial for pathogen control in aquatic environments and biofilm management in engineered systems.

RESULTS

Tracking the interface dynamics of single bacteria using plasmonic interferometric scattering imaging.

A plasmonic interferometric scattering imaging technique was used to visualize single bacterial cells (Fig. 1), which has been introduced in detail in our previous work (19). The bacterial suspension was placed onto gold chips coated with a C₁₁-NH₂ self-assembled monolayer (SAM). The adhered bacterial cells on the surface scattered the plasmonic waves, generating a parabola-shaped plasmonic interferometric scattering image for each bacterium (Fig. 2A). Since the surface plasmons decay exponentially from the gold film into the solution, the vertical position (z position) can be tracked with a resolution of 0.1 nm by extracting the plasmonic intensity of bacteria (Fig. 2B and C) (20). Three distinct behaviors of bacteria near the surface were identified, (i) adhesion to the solid surface, (ii) vibration on the surface, and (iii) repulsion after reaching the surface (Fig. 2D). These three behaviors depend on hydrochemical conditions of the solution. In a solution without surfactants, the plasmonic intensity of bacteria remains stable, meaning the adhesion of bacteria on the surface (Fig. 2A). In contrast, an unstable plasmonic intensity profile with sharp peaks was visualized for surfactant-containing solutions. These features were attributed to the behaviors of vibration or repulsion of bacteria (Fig. 2B and C). Our work shows the ability of plasmonic imaging techniques to track different interfacial behaviors of bacteria. Since the sampling times were limited for repulsive bacteria, we further analyzed and compared the time series of the plasmonic intensity from adhesive and vibrative bacteria.

FIG 1.

Schematic of bacteria dynamic interfacial behaviors imaged by surface plasmon resonance microscope. (A) Setup of the plasmonic imaging system. (B) Distinct adhesion behaviors with surfactant and without surfactant. (C) Workflow for data processing, including z position obtained from plasmonic images, potential energy profiles derived from z position fluctuations of bacterial cells, and extraction of parameters for characterizing extracellular polymeric substance properties.

FIG 2.

Distinguishing different interfacial behaviors of bacteria using a plasmonic imaging system. (A) Several snapshots of single bacteria dynamics at different times. Scale bar, 4 μm. (B) Plasmonic intensity profile of single bacteria. (C) The corresponding vertical displacement was calculated from the plasmonic intensity of the orange area in panel B. (D) Distinct bacterial interfacial behaviors, adhesion (left), vibration (middle), and repulsion (right).

Quantification of surfactant-tuned single bacterial adhesion strength.

To examine the effects of surfactants on the adhesion of bacteria, we quantified the standard deviations of vibration amplitude profiles of adhesion bacteria (Fig. 3A and B). The vibration amplitude increased correspondingly with the increase in surfactant concentration. For example, the average amplitude rose from 1.9 to 12.0 and 19.6 nm in 10-mg/L SDS and 150-mg/L CTAB solutions, respectively (Fig. 3C), indicating that bacteria are prone to change from strong adhesion to weak adhesion with the addition of surfactants.

FIG 3.

Surfactant concentration-dependent amplitudes of Pseudomonas aeruginosa PAO1. (A) Schematic diagrams of surfactant concentration-dependent amplitudes. (B) Typical fluctuation profile of vertical z positions for single bacteria corresponding to 0, 0.1, 1, and 10 mg/L SDS. The corresponding amplitude is marked in the top right corner. (C) Amplitude of Pseudomonas aeruginosa PAO1 in different concentrations of SDS and CTAB solutions.

To quantify the binding strength of single bacterial cells perturbed by surfactants, we used an elastomer model for analyzing fluctuations of bacteria (17). The fluctuation amplitudes of individual bacterial cells were related to binding energy, which determined the binding strength of bacterial cells to the surface (21, 22). The vibration amplitudes of bacteria in unfavorable adhesion conditions were much larger than that of those in favorable adhesion conditions. We determined the single-cell adhesion potential energy profiles, Φ, using the Maxwell-Boltzmann equation (17)

$$\Phi \left(h\right)=-\mathit{kT}\left\{\ln \left[P\left(h\right)\right]+C\right\}$$

where h is the distance of a bacterial cell from the surface, k is the Boltzmann constant, T is temperature, and C is an unknown constant. P(h) is the probability density function and can be obtained by kernel density estimation of the bacterial vertical position. The inclination of single-cell adhesion potential energy profiles corresponded to the fluctuation activity with various surfactant concentrations (Fig. 4A and B). The gentle profile indicates that the bacteria were active during the fluctuation, and the sharp indicates that the bacteria were inactive (17). The potential energy profiles change from sharp to gentle with the increase of surfactant concentration, implying that the addition of surfactants causes an adhesion-resistant condition.

FIG 4.

Energy profile calculation and elastic parameter fitting. (A, B) Calculated potential energy profiles between bacterium and surface at various surfactant concentrations. The potential energies taken from z position fluctuations of bacteria are shown as circles. The polymer elasticity fittings are shown as lines. (C to F) Elastic parameters were derived from potential energy profiles in different surfactant solutions. (C, E) Binding constant; (D, F) elastomer length.

In addition, the vertical fluctuation profile is asymmetric on the left and right sides, indicating that the potential energy distribution is not an ideal harmonic but a nonlinear deformation-force relationship (23). This asymmetry may arise from the viscoelastic properties of bacterial EPS, which were responsible for the adhesion of bacteria to surfaces (24). The confinement constant of the EPS network is proportional to the elastic modulus of the network. Given the viscoelastic nature of EPS, we introduced a stress-strain relationship of polymer and obtained the elastic potential energy equation of the elastomer as follows:

$$\Delta \varphi \left(h\right)=\underset{l_0}{\overset{h}{{\displaystyle \int }}}{S}_{\mathit{cell}}\text{σ}\mathit{dh}=K\left(\frac{h^2}{2l_0^2}+\frac{l_0}{h}-\frac{3}{2}\right)$$

$$K=G{S}_{\text{cell}}{l}_0$$

where S_cell is the contact area of bacteria binding to the surface. The binding constant, K, is defined as the product of the elastic modulus, the initial elastomer length, and contact area. Elastomer length, l₀, is the initial length of the elastomer.

With the elastomer model, two elastic parameters were extracted from the potential energy profiles, (i) binding constant (Fig. 4C and E), which is related to the elastic modulus and the contact area; and (ii) elastomer length (Fig. 4D and F), which is the initial thickness of the polymer. These two parameters are related to the properties of bacterial EPS and can be used to quantify the binding strength between bacteria and surface at different surfactant concentrations. The bacteria have a high binding constant (475 kT) and low elastomer length region (29 nm) without surfactant, indicating a high binding strength. The binding constant decreased, respectively, to 376, 207, and 148 kT as the concentration of anionic surfactant SDS increased to 0.1, 1, and 10 mg/L (Fig. 4C), with the elastomer length increased to 59, 71, and 148 nm (Fig. 4D). The same result was observed for CTAB (Fig. 4E and F). Surfactants adsorbed to microbial surfaces induced changes in bacterial surface hydrophobicity and zeta potential (see Tables S1 and S2 in the supplemental material), which affected the viscoelasticity of bacterial EPS. The increase in surfactant concentration disrupted the balance of interfacial energy and weakened the interactions between the bacteria and the surface, which could be read out from the binding constant and the elastomer length of single cells.

Surfactant concentration-dependent adhesion process.

To verify the binding strength extracted from the elastomer model, the numbers of adherent Pseudomonas aeruginosa PAO1 cells under various concentrations of SDS and CTAB were analyzed (Fig. 5A and B). Theoretically, less bacteria adhesion occurs with weaker binding strengths. Our results confirmed that the bacteria adhesion rate was 6.7 × 10⁴ μm⁻² s⁻¹ without surfactant. For anionic surfactant SDS, the adhesion rate at a concentration of 10 mg/L was 2.9 times lower than that without surfactant (Fig. 5C), while the adhesion rates in 150-mg/L CTAB solutions were reduced by 5.2 times (Fig. 5D; Table S3). The reduced amounts of adherent bacteria under surfactant solutions confirmed that surfactants influenced the binding strength between bacteria and the surface.

FIG 5.

Surfactant concentration-dependent adhesion curve of Pseudomonas aeruginosa PAO1. (A, B) Typical plasmonic images of bacteria with/without surfactant taken after a 60-s adhesion. The bacterium in panel B was treated with 10 mg/L SDS. Scale bar, 5 μm. (C, D) Adhesion curves of Pseudomonas aeruginosa PAO1 in different SDS and CTAB solution concentrations.

Surfactant concentration-dependent postcollision behavior and equilibrium positions.

To further reveal the surfactant concentration-dependent interaction process between bacteria and the surface, we analyzed the equilibrium positions and the ratio of different behaviors, i.e., adhesion, vibration, and repulsion of individual bacterial cells. All bacteria adhered to the surface stably without surfactants. As the surfactant concentration increased, bacteria were more likely to be detached and had a negligible probability of adhering to high surfactant concentration (Fig. 6A and B). Specifically, for anionic surfactant SDS, the probability of adhesion events at 10 mg/L (6.2 ± 0.6%) was decreased much more than that at 0.1 mg/L (95.4 ± 5.3%). Meanwhile, bacteria began to exhibit vibration and repulsion behavior with 30 mg/L CTAB, and the adhesion rate at high concentrations was also significantly reduced. The fraction of bacteria with vibration and repulsion behaviors increased gradually with surfactant concentration, which further confirmed that the surfactants weaken the interaction process between bacteria and the surface.

FIG 6.

Surfactant concentration-dependent final behaviors and equilibrium positions of Pseudomonas aeruginosa PAO1. (A) Schematic diagrams of different postcollision behaviors. (B) Ratios of different bacteria interfacial behaviors at various surfactant concentrations. (C) Schematic diagrams of different equilibrium z positions. (D) Equilibrium z positions of adhesion bacteria at various surfactant concentrations.

By analyzing the plasmonic intensity variations of many single adhered bacterial cells (Fig. S1), we found that the equilibrium z position also strongly correlated with surfactant concentration (Fig. 6C). Compared with bacteria in the absence of surfactants, those in SDS and CTAB solutions had a higher equilibrium z position. The equilibrium z position of bacteria was 23.5 nm without surfactants, while for SDS at the concentration of 0.1 mg/L, the equilibrium z position increased to 48.7 nm, and for CTAB at the concentration of 30 mg/L, the equilibrium z position was 59.5 nm (Fig. 6D).

Correlation between microelastic parameters and macroadhesion behaviors of EPS.

We compared the binding constants and elastomer lengths with adhesion behaviors obtained from plasmonic single-cell imaging. The binding constant was positively correlated with the rate of adherent bacteria (Fig. 7A), while the elastomer length was positively correlated with the equilibrium z position of the bacteria (Fig. 7B). This result suggested that surfactant affects EPS viscoelasticity, which was responsible for the bacteria binding to the surface, leading to different bacterial adhesion behaviors (Fig. 7C and D).

FIG 7.

Schematic of the possible mechanism of surfactant-tuned single bacterial adhesion. (A) Correlation of the binding constant and adhesion rate of bacteria. (B) Correlation of the elastomer length and equilibrium z position of bacteria. Pentagon, without surfactant; circle, SDS; square, CTAB. (C) Schematic diagrams of bacteria with high degrees of EPS cross-linking and tightly binding without surfactant. (D) Schematic diagrams of bacteria with low degrees of EPS cross-linking and loosely binding with surfactant.

DISCUSSION

Most conventional studies focused on bacterial adhesion in pure salt or phosphate-buffered saline (PBS) buffer solution (17, 25–27). However, pollutants in the environment, such as antibiotics, heavy metals, and various detergents, influenced the hydrochemical properties in natural and engineered systems. Surfactants, one of the significant challenges facing wastewater treatment, account for a large portion of water pollution. Although some studies have focused on the effect of surfactants on bacterial adhesion or transport, most of them only obtained a macroscopic result at the population level, which cannot track the behavior at the single-cell level (7, 28–30). Taking advantage of the high temporal-spatial resolution and vertical distance sensitivity of the plasmonic scattering interferometric imaging technique, high-throughput analysis of single bacterial adhesion was achieved. This approach enabled us to quantify the adhesion strength of single cells by analyzing the potential energy of bacteria attached to the surface. The results indicated that the bacterial adhesion strength exhibited a surfactant concentration dependence, which improved our understanding of complex interactions between bacteria and the surface in the presence of surfactants at a single-cell level.

The presence of surfactants alters EPS viscoelasticity (decreased binding constant and increased elastomer length) (5, 31). Surface hydrophobicity and zeta potential of microorganisms were measured to verify the change of EPS (see Tables S1 and S2 in the supplemental material). The water contact angles of cells treated with surfactants were lower than that of untreated cells, indicating that the cell surfaces were more hydrophilic with surfactants (Table S1) (32), which is not conducive to the adhesion of bacteria to the surface. This result was consistent with previous reports that SDS or rhamnolipid decreased cell surface hydrophobicity of Alcaligenes paradoxus or Pseudomonas aeruginosa ATCC 9027 (33–35). As for the surface charge of bacteria, it is often negatively charged due to the presence of anionic surface groups such as carboxyl and phosphate (1). It is therefore difficult for SDS (the hydrophilic end negatively charged with −SO₄) to pass through the negative ion cloud around the cell (36) and change the bacterial zeta potential (from −36.2 to −37.4 mV in 10 mg/L SDS). However, electrostatic attraction dominated the driving force for the interaction between positively charged CTAB ions and the cell surface, which neutralizes the charge of bacteria (from −36.2 to 18.3 mV in 150 mg/L CTAB) (Table S2). Surfactant adsorbs to bacteria via hydrophobic forces and electrostatic forces (or both), binds to various bioactive macromolecules such as proteins and peptides, and removes lipopolysaccharide molecules or inserts into phospholipid membranes. These processes change the physical structure of the cell membrane or disrupt the protein conformation (37–42). Finally, surfactants alter the viscoelasticity of bacterial EPS, leading to different fluctuation amplitudes (Fig. 3), which are associated with the binding energy of bacteria (Fig. 4). It is worth noting that the individual bacterial cells in response to the surfactant treatment have a considerable heterogeneity, which is reflected by the error bars (Fig. 3C, Fig. 4C, and Fig. 6D). The heterogeneity of the bacterial surface structure contributes to the different behaviors of bacteria in the presence of surfactants, which makes the interaction between bacteria and surface deviate from the ideal colloid behavior at equilibrium. The inhomogeneous distribution of EPS leads to different fluctuation amplitudes of individual bacterial cells, which are associated with the binding energy of bacteria. The addition of surfactant could affect the binding energy. Due to the heterogeneity of bacterial cells, the response of bacteria to thermodynamic changes is different; some of the bacterial cells were more resistant to changes in the mechanics, and others were irresistant.

In addition, a concentration-dependent effect on EPS was observed for both anionic and cationic surfactants, but the concentration range in which the response occurred was different. CTAB has little impact on bacterial EPS at low concentrations (less than 10 mg/L), while SDS significantly changes the thickness and viscoelasticity of EPS at the same concentration (Fig. S2). The corresponding adhesion behaviors at low concentrations of 0.1, 1, and 10 mg/L CTAB observed are shown in Fig. S3. These differences may be due to the different mechanisms of EPS damaged by cationic and anionic surfactants. CTAB adsorbs on bacteria by electrostatic attraction, hydrogen bond force, and hydrophobic interactions, and it damages EPS by the synergistic effect of solubilization property, replacement of metal cation, and release of intracellular materials (43). As a strong protein denaturant, SDS adsorbs bacteria mainly through hydrophobic interactions, and it damages EPS by its solubilization property (44, 45). SDS could lead to irreversible conformational changes and denaturation of proteins (46), causing cell lysis and diminishing biofilm cohesiveness (47). This strong destructive effect of SDS results in a great change in EPS properties even at lower concentrations of SDS (Fig. 4). Our results demonstrate that the EPS of Pseudomonas aeruginosa PAO1 is more tolerant to CTAB than SDS (Fig. S2).

Since the sensing surface with surfactant adsorption might affect hydrophilic surfaces and change surface charge (48), we compared the surfaces with different modifications (Table S4). We previously used amino-modified gold chips, which were positively charged and employed as an easy adhesion surface to explore the effect of surfactants on bacterial EPS. When shifting to carboxyl-modified gold chips with a negative charge, we obtained similar results to that of the amino-modified surface (Fig. S4 and Fig. 6). Electrostatic attraction between the surfactant head group and the oppositely charged surface could drive monomer adsorption (49, 50), while electrostatic repulsion could only lead to weak interactions between the hydrophobic tail of surfactant and the hydrophobic carbon chain on the surface (51, 52), with the zeta potential and water contact angle of the surface changed. Our results ruled out the possibility that the sensing surface coated with surfactant interred the interactions between bacteria and surface.

Taken together, we can explain the mechanisms involved in the surfactant-tuned single bacterial adhesion. In an aquatic environment without surfactants, bacterial EPS has a high binding constant and short elastomer length, resulting in strong interactions between bacteria and the surface (Fig. 7C). The surfactants in solution changes the viscoelasticity of bacterial EPS since the adsorption of surfactants to EPS or the structure and composition disruption of bacterial EPS by surfactants. This change in viscoelasticity of bacterial EPS weakens the binding strength of bacteria to the surface (low binding constant and large elastomer length) (Fig. 7D). This concentration-dependent effect on bacterial adhesion is accompanied by both anionic and cationic surfactants.

MATERIALS AND METHODS

Chemicals.

Sodium dodecyl sulfate (≥99%) and hexadecyl trimethyl ammonium bromide (≥99%) were purchased from Macklin and used without further purification. Reagents used for culture media and potassium chloride were purchased from Sinopharm.

Bacterial strain and growth conditions.

A Gram-negative bacteria Pseudomonas aeruginosa PAO1 was used as a model strain in this study. Pseudomonas aeruginosa PAO1 cells were grown from an LB agar plate and incubated overnight at 30°C. Then, a single colony of bacteria was picked and suspended in FAB medium the FAB medium contains following compositions per liter: (NH4)₂SO₄, 2 g; Na₂HPO₄·12H₂O, 12.02 g; KH₂PO₄, 3 g; NaCl, 3 g; MgCl₂, 93 mg; CaCl₂·2H₂O, 14 mg; FeCl₃, 1 μmol; and trace metals solution (CaSO₄·2H₂O, 200 mg L−1; MnSO₄·7H₂O, 200 mg L−1; CuSO₄·5H₂O, 20 mg L−1; ZnSO₄·7H₂O, 20 mg L−1; CoSO₄·7H₂O, 10 mg L−1; NaMoO₄·H₂O, 10 mg L−1; H₃BO₃, 5 mg L−1), 1 mL. The bacterial suspension was placed in a constant temperature shaker at 30°C overnight and harvested at an optical density at 600 nm (OD₆₀₀) of ~0.8 by centrifugation at 6,000 × g for 5 min. Afterward, the bacterial suspension was washed three times with KCl solution and resuspended in 10 mL of KCl solution.

Preparation of plasmonic sensing chips.

BK7 glass coverslips coated with 2 nm chromium and 48 nm gold were used as sensing chips. The chips were cleaned with deionized water and ethanol three times and dried with nitrogen gas. The cleaned chips were immersed in 1 mM C₁₁-NH₂ or C₁₁-COOH solution for 24 h to form a SAM for surface functionalization. Then, the coated chips were extensively rinsed with deionized water and ethanol, dried with nitrogen, and used immediately.

Setup of plasmonic interferometric scattering imaging.

The plasmonic interferometric scattering imaging setup was built on an inverted microscope (Ti-E; Nikon, Japan) using an oil immersion objective (60×) with a high numerical aperture (NA = 1.49). A 660-nm p-polarized light from a superluminescent light-emitting diode (SLED) (SLD-26-HP; Superlum, Ireland) was used as the light source to excite surface plasmons. The reflected light was collected and recorded by a charge-coupled-device (CCD) camera (Pike-032B; Allied Vision Technologies, Germany). A coated gold chip was placed onto the object stage of the inverted microscope as a sensing platform. A polydimethylsiloxane (PDMS) sample cell was mounted on this chip and filled with 0.5 mM KCl solution. Surfactants were added and let stand for a few minutes to reach different concentrations. Then, Pseudomonas aeruginosa PAO1 was added to the cell with the final concentration of OD₆₀₀ of 0.02. The plasmonic images were captured at 6.67 frames per second (fps) for 300 s and then captured at 106.7 fps for 60 s.

Data analysis.

Data were processed using MATLAB, ImageJ, and Origin software. Raw images were converted into 16-bit TIFF files by MATLAB for further processing. The first image was subtracted to remove the background. Adhesion kinetic curves were drawn by digitally counting individual bacteria adhesion on the surface. Then, a region of interest (ROI) at the head of the particle was selected to determine the intensity of the bacteria. The plasmonic intensity of each ROI was extracted by ImageJ. The vertical positions of bacteria were obtained from plasmonic intensity using the equation

$$I_Z=I_0\exp \left(-\frac{z}{L}\right)$$

where I_Z is the plasmonic intensity of bacteria at the vertical position z, I₀ is the plasmonic intensity of bacteria at a reference point, and L is the decay length constant of the evanescent field (95.8 nm) (19). The vibration amplitudes were determined as the standard deviation of the vertical displacement in time series (typically within 2,000 frames). After bacteria reached a steady state, the ratio of different bacteria interfacial behaviors and equilibrium z position can be calculated. More than 20 bacteria were randomly analyzed in each group for all statistical analyses.

Bacterium-surface potential energy profiles and binding elastic parameters.

The data processing was performed using MATLAB and Origin software. The intensity of a single cell extracted from the recorded image sequences was converted into the vertical position of bacteria. Then, the potential energy profiles were derived from vertical position fluctuations of bacterial cells. The energy profiles extracted two elastic parameters, the binding constant and elastomer length.

Measurement of physicochemical properties of bacteria and gold film.

(i) Water contact angle measurement. Bacteria surfaces for water contact angle measurement were prepared by suction filtering the bacterial cells on 0.45-μm micropore filters. We added 2-μL water drops to the interface by using a microsyringe, and then, the contact angles of water with the bacterial surface and gold film were measured. Each reported contact angle means 10 independent measurements without maximum and minimum.

(ii) Zeta potential measurement. As for bacteria, cell suspensions were resuspended in the corresponding concentration of SDS or CTAB solutions. Zeta potentials were measured (Zetasizer Nano ZS Zen 3600; Malvern Instruments Ltd., UK) 3 times using 12 cycles per analysis (triplicate samples) and then taking the average of three tests. As for the gold film, zeta potentials were measured (SurPass 3; Malvern Instruments Ltd., Anton-Paar, Graz, Austria) based on the flow current method measurement and then taking the average of three tests.