A Quantitative Criterion to Predict Cell Adhesion by Identifying the

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Biological and Environmental Phenomena at the Interface

A Quantitative Criterion to Predict Cell Adhesion by Identifying the Dominant Interaction between Microorganism and Abiotic Surface Hao Yuan, Xinru Zhang, Zeyi Jiang, Xuehui Chen, and Xinxin Zhang Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.8b03465 • Publication Date (Web): 23 Dec 2018 Downloaded from http://pubs.acs.org on December 27, 2018

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A Quantitative Criterion to Predict Cell Adhesion by Identifying the Dominant Interaction between Microorganism and Abiotic Surface

Hao Yuan, a Xinru Zhang, a,b * Zeyi Jiang, a, c Xuehui Chen,d Xinxin Zhang a, c a School

of Energy and Environmental Engineering, University of Science and Technology

Beijing, Beijing, 100083, China b

Beijing Engineering Research Center of Energy Saving and Environmental Protection,

University of Science and Technology Beijing, Beijing, 100083, China c

Beijing Key Laboratory for Energy Saving and Emission Reduction of Metallurgical

Industry, University of Science and Technology Beijing, Beijing, 100083, China d

School of Mathematics and Physics, University of Science and Technology Beijing,

Beijing, 100083, China

Corresponding Author *Xinru Zhang Ph. D

Mailing Address: School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China Phone: 86-10-62334971; E-mail: [email protected]

1

ACS Paragon Plus Environment

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Abstract Cell adhesion is ubiquitous and plays an important role in various scientific and engineering problems. Herein, a quantitative criterion to predict cell adhesion was proposed by identifying the dominant interaction between microorganisms and abiotic surfaces. According to the criterion, the dominant interaction in cell adhesion could be identified as a Lewis Acid-Base (AB) interaction or electrostatic (EL) interaction via comparison of two expressions containing the electron donor characteristics of the － microorganism (  mv ) and abiotic surface (  sv－ ) and their ζ potentials (ζm, ζs). The results

revealed that when dominated by the AB interaction, adhesion would decrease with increasing

   mv

  sv

. Whereas, when the EL interaction was dominant, adhesion would

decrease with increasing ( m   s )2 . We have verified the criterion based on the adhesion of microalgae, bacteria and fungi onto various surfaces obtained via our experiments and available in literatures. The results demonstrated that the criterion had important implications in prediction of cell adhesion in various applications.

Keywords: Microbial adhesion, dominant interaction, Lewis Acid-Base interaction, electrostatic interaction, surface energy, zeta potential.

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Introduction Microorganisms are capable of adhering onto surfaces and forming highly productive biofilms, which plays an important role in various scientific and engineering problems,1-3 including biofouling and biocorrosion in environmental engineering, bioremediation of wastewater, bioadhesion in microbial fuel cells, the mineral beneficiation process, the production of biosensors, and so forth.4-10 Generally, biofilm formation and development consists of transportation of microbial cells from liquid medium to the surface, followed by adhesion of cells onto surfaces by physicochemical interactions, and then biofilm development and maturation.11-13 During this process, microbial adhesion onto surface is essential to biofilm formation14 and directly influences biofilm development. Therefore, it is important to understand the behavior of cell adhesion. To date, many previous studies have shown that microbial adhesion onto abiotic surfaces can be influenced by multiple factors, such as the surface properties of microorganism and abiotic surfaces, including their surface free energy (SFE),15 ζ potential,16 hydrophobicity,17 roughness,18 and morphology,19-20 the characteristics of the cultivating liquid medium, including its surface tension,21 pH,22 ionic strength,23 temperature24 and hydrodynamics25-26, as well as some biotic factors, including the properties of cell membrane, production of extracellular polymeric substances,27 the chemotaxis of cells and the presence of pili and flagella28-29. Overall, it has been established that these factors can influence cell adhesion mainly by affecting the physicochemical interactions between cells 3


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and surfaces. To understand the physicochemical interactions between cells and surfaces, several theoretical methods have been proposed based on the thermodynamic theory or the DLVO (Derjaguin-Landau-Verwey-Overbeek) theory. In the thermodynamic approach, the thermodynamic adhesion energy (ΔGadh) between cell and surface is evaluated to predict cell adhesion by determining the SFE or the components of SFE,30 and a negative ΔGadh leads to adhesion, whereas a positive ΔGadh does not. In addition, adhesion has also been studied within the scope of the classical DLVO or the extended DLVO (xDLVO) theories by analyzing the total interaction energy (Gtot) between cells and surfaces as a function of separation distance via consideration of the Lifshitz-van der Waals (LW) interaction, electrostatic (EL) interaction and Lewis acid-base (AB) interaction.31 Undoubtedly, these theoretical methods have provided many valuable points regarding interpretation and prediction of cell adhesion. Recently, some researchers proposed several criteria to quantitatively predict cell adhesion. Based on the thermodynamic approach, Zhang et al.15 found that bacterial adhesion was mediated by the SFE difference between cells and surfaces, with a lower SFE difference indicating a higher degree of adhesion. Furthermore, by considering the components of SFE, Cui et al.32 reported that, for microalgae that have a dispersive component of SFE higher than that of water and a polar component of SFE lower than that of water, adhesion would be more favorable on surfaces with a higher dispersive 4


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component of SFE but a lower polar component of SFE. Moreover, some researchers 33-36 showed that cell adhesion would decrease with increasing electron-donor characters. Overall, these criteria have important implications in predicting the cell adhesion. Meanwhile, these criteria indicated that the physicochemical interactions between cells and surfaces, including EL, LW and AB interactions, might play different roles in cell adhesion under different conditions. However, to date, few studies have been conducted to understand and quantify the dominant physicochemical interactions in various cell adhesions. Herein, based on a theoretical analysis, we hypothesized that the dominant interaction can be identified as a Lewis Acid-Base (AB) interaction or electrostatic (EL) interaction via comparison of

   mv

  sv

and

( m   s ) 2 ,

where

－  mv

and

－  sv

are electron donor

characteristics of the microorganism and abiotic surface, respectively, ζm and ζs are their ζ potentials. When the AB interaction was dominant, cell adhesion would decrease with increasing

   mv   sv

, whereas cell adhesion would decrease with increasing

( m   s ) 2

when the EL interaction was dominant. To verify this hypothesis, the adhesion of microalgae, bacteria and fungi onto various abiotic surfaces was analyzed based on our experiments and the data published in literature. The proposed criterion may have important implications for the prediction of cell adhesion in various applications. Theoretical section Identification of the dominant interactions in cell adhesion by theoretical analysis 5


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Based on xDLVO theory, cell adhesion can be regarded as a sphere opposed to a semiinfinite flat plate with a balance between EL, LW and AB interactions, and the total interaction energy between the cell and abiotic surface, i.e., Gtot, can be determined by: 14 G tot  d   G EL  d   G LW  d   G AB  d 

(1)

where d is the distance between the cell and surface, GEL, GLW and GAB denote the EL, LW and AB interaction between the cell and surface, respectively. In the xDLVO theory, a positive Gtot denotes repulsion energy, while a negative Gtot represents attraction. GEL can be calculated by: G EL  d    a ( m2   s2 )[

2 m s 1  exp(  d ) ln( )  ln(1  exp( 2 d ))]  m2   s2 1  exp(  d )

(2)

where ε is the permittivity of media, a is the cell radius and κ is the Debye constant. GLW can be expressed as: G LW  d   

A a a d [   ln( )] 6 d d  2a d  2a

LW A  12 d 0 2 Gadh

(3) (4)

LW LW Gadh  -2(  mv   lvLW ) (  svLW   lvLW )

(5)

where d0 is the minimum separation distance between cells and abiotic surfaces, A is the Hamaker constant of the interacting media,  lvLW

and

 svLW

LW Gadh

is the change of LW interaction and

LW  mv ,

are the LW components of SFE for microorganismvapor, liquidvapor and

abiotic surfacevapor interactions, respectively. GAB relates to the electron-donating and electron-accepting interactions between the cells and surfaces14, and can be expressed as: 6


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AB G AB (d )  2 aGadh exp  d 0  d   



AB Gadh  2  mv   sv

 

 mv

 

  sv - 2  mv   lv

 

 mv

 

(6)

  lv - 2  sv   lv

 

 sv

  lv



(7)

where λ is the correlation length of molecules in liquid medium. In the study, because the culture medium is water, λ is set to be 6×10-10 and 1.5×10-9 m for hydrophilic and hydrophobic interactions, respectively, based on the gyration radius of water molecules.14, 35

AB Gadh

+  mv ,  lv+

is the change in AB interaction,

and

 sv+

are the electron acceptor

components of SFEs for microorganismvapor, liquidvapor and abiotic surfacevapor interactions, respectively, and

－  mv ,  lv－

and

－  sv

are the electron donor components of

SFEs for these interactions. By comparing the EL, LW and AB interactions between cells and surfaces, we found that the LW interaction was generally much lower than the EL and AB interaction in the near-surface area, since LW is a long-range interaction, the working distance is greater than that of the AB or the EL interaction (see Table S1 and Figure S1-6 in the Supporting Information (SI)). These findings indicated that the EL and AB interactions played more important roles than the LW interaction in the near-surface area. Therefore, we focused on the EL and AB interactions in this study. Furthermore, because the EL interaction is generally repulsive, whereas the AB interaction is attractive, the following cases were considered. When the EL interaction was much higher than the AB interaction (as shown by case 1 in Figure 1a), an energy barrier would occur, because the dominant EL interaction was repulsive. However, when the EL interaction was much lower than the AB interaction 7


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(as shown by case 3 in Figure 1a), the Gtot would be dominated by the attractive AB interaction. Evidently, as the EL interaction decreased, the Gtot curves would change from case 1 to case 3. Furthermore, when the maximum Gtot equaled zero in the near-surface area, as shown by case 2 in Figure 1a, Gtot would change from repulsion to attraction. Herein, the maximum Gtot that equaled zero in the near-surface area was expressed as the Max G

tot

(d ) 

.

The pairs of surface characteristics (including the components of SFE and ζ potential for the cell and surface) leading to the zero Max G

tot

( d ) 

were determined as the [SC]0 points.

Afterward, a [SC]0 curve can be obtained by fitting the [SC]0 points, on which the EL interaction and AB interaction were balanced. Moreover, as shown in Figure 1b, the AB interaction and EL interaction were set as the horizontal and vertical axis, respectively. It was found that when the surface characteristics for the adhesion pair of the cellsurface were located in the upper left zone (blue), GEL would be higher than G AB, i.e., the EL interaction would be dominant in adhesion. While, when the surface characteristics for the adhesion pair of the cellsurface were located in the lower right zone (green), GAB would be higher than GEL, i.e., the AB interaction would be dominant. Based on the above analysis, the dominant interaction involved in adhesion can be identified after determining the [SC]0 curve and surface characteristics for a cellsurface adhesion pair. Analysis and simplification of the AB and EL interactions To predict the adhesion behavior under different dominant interactions, the AB and EL 8


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interactions were further analyzed. Based on a mathematical derivation (see SI for detailed information), Equation 2 can be rewritten as: G EL（d）  a ( m   s )2 [ Ln(1  exp(  d ))]  ( m   s )2 [ Ln(1  exp(  d ))]

(8)

Considering that ζm and ζs generally had the same magnitude in various adhesions,35 the value of

( m   s ) 2

would be much higher than that of

( m   s ) 2 . Therefore, the second term

in Equation 8 was negligible and the EL interaction can be simplified as: （d）  a ( m   s ) 2 [ Ln (1  exp(  d ))] G EL

(9)

Equation 9 indicates that the repulsive EL interaction would increase with increasing ( m   s ) 2 .

Moreover, based on Equation 5,

AB Gadh

can be derived as follows (see SI for detailed

information regarding the derivation process): AB Gadh 2



 lv   sv



 +2  mv



  lv   mv



 sv +2



 +  sv  2  lv  mv



 lv

(10)

Previous studies reported that, when compared with the culture media, microbial cells and surfaces were generally weak electron acceptors,37 i.e., lower than

 lv

(see Table S2). Therefore,

simplification. Accordingly,

AB Gadh

and

 sv

and

 sv

were much

were neglected in this

and G AB can be simplified as:

AB Gadh  2  lv

G AB (d)  4 a   lv 

  mv

  mv





 mv



 +  sv  4  lv  lv  mv



+  sv  2  lv  lv  exp  d0  d    

(11) (12)

It should be noted that the AB interaction is generally attractive; therefore, G AB should be negative. Accordingly, based on Equation 11 and 12, the AB interaction should decrease 9


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with increasing

   mv   sv

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.

Criterion to predict cell adhesion Based on the above simplification,

   mv   sv

and

( m   s ) 2

were set as the horizontal

and vertical axis, respectively (Figure 2). The pairs of surface characteristics (including ζm, ζs,

－  mv

and

－  sv )

leading to the zero Max G tot (d )  , i.e., [SC]0 points, were determined using

an exhaustive method by assigning a large amount of values to the surface characteristics (see SI for the detailed information). The [SC]0 curve can then be obtained by fitting the [SC]0 points. Note that the slope of the [SC]0 curve was negative in Figure 2 because the attractive AB interaction decreased with increasing

   mv   sv

interaction in adhesion can be identified by comparing

. Afterward, the dominant

   mv   sv

with

( m   s ) 2

for the

cellsurface adhesion pairs. As shown in Figure 2, when the surface characteristics for the cellsurface adhesion pair were located in the upper right zone (blue), the EL interaction would be dominant. It should be noted that, although the EL interaction is generally repulsive, previous studies14,

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indicated that the cell could overcome the energy barrier and adhere onto the surface, due to the Brownian motion or the hydrodynamic forces. Therefore, when the EL interaction is dominant, adhesion would decrease with increasing

( m   s ) 2 . Moreover, when the surface

characteristics of the adhesion pairs were located in the lower left zone (green), the AB interaction would be dominant and cell adhesion would decrease with increasing

   mv   sv

We will verify this hypothesis in a subsequent study based on the adhesion of microalgae, 10


.

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bacteria and fungi onto various abiotic surfaces obtained in our experiments and the data published in literatures. Experimental section Cultivation and characterization of microbial cells To verify the hypothesis, the adhesion behavior of four widely-used microalgae species and two bacteria species onto five abiotic surfaces was experimentally observed. The microalgae species used in this study were two marine microalgae, i.e., marine Chlorella sp. (CCMA-309) and Nannochloris oculata (CCMA-325), two freshwater microalgae, i.e., freshwater Chlorella sp. (USTB-A01) and Scenedesmus obliquus (FACHB-276), and two bacteria species, i.e., Enterococcus faecalis (ATCC-29212) and Staphylococcus epidermidis (ATCC-12228). The detailed information on cultivating cells can be found in SI. Note that all these cells had no pili and flagella on their surfaces, and the biotic factors were not considered in the study. Following harvest, the microalgal and bacterial suspensions were centrifuged at 1770 g and 3600 g, respectively, for 4 min at room temperature to remove cell debris. After three rounds of centrifugation and washing, the marine Chlorella sp., N. oculata, E. faecalis and S. epidermidis were resuspended in 0.9% NaCl solution to form homogeneous cell suspensions at a concentration of 106 cells/mL (for microalgae) or 108 cells/mL (for bacteria), while the freshwater Chlorella sp. and S. obliquus were resuspended in 0.1% NaCl solution at a concentration of 106 cells/mL. Note that, before the experiments, all cell suspensions were vibrated for 1 min by vortexing, and 11


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then sonicated for 15 seconds to form homogeneous cell suspensions. After preparation of the microbial cells, the cell morphology, ζ potential and SFE components were determined. Specifically, the cell shape and size were determined by microscopy (BX61, Olympus, Japan). The ζ potentials of cells in liquid media with pH values of 5–10 were determined by electrophoresis method using a commercial ζ potential meter (Microtrac, Nanotrac Wave, USA). The SFEs components of cells, including γtot (the total SFE),

LW  mv ,  mv+

and

 mv ,

were quantified by a low-rate dynamic contact angle

measurement (LDCAM) on the cell lawn using pure water, formamide and methylene iodide as the probe liquids in conjunction with the Lifshitz-van der Waals/acid-base (LWAB) approach (see SI for the details).37 Preparation and characterization of material surfaces Five abiotic surfaces, polymethyl methacrylate (PMMA), polyvinyl chloride (PVC), poly carbonate (PC), glass and 1,1,1,3,3,3-hexamethyldisilazane (HMDS) coated glass, were prepared. Briefly, surfaces were thoroughly cleaned in a solution (Decon Neutracon solution, Decon Laboratories Limited, UK) for 12 hours, then rinsed three times with deionized water and dried under nitrogen flow. The surface properties of these abiotic surfaces, including roughness, ζ potential and SFE components, were then characterized. Specifically, ζ potentials of abiotic surfaces with 0.1% NaCl solution and 0.9% NaCl solution between pH 5 and 10 were measured by the streaming current method using a commercial ζ potential meter (Surpass, Anton Paar, Austria). The SFEs of the abiotic 12


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surfaces, including

 svtot ,  svLW ,  sv+

and

 sv- , were also determined by the LDCAM using pure

water, formamide and methylene iodide as the probe liquids in conjunction with the LWAB approach (see SI).37, 39 Cell adhesion onto abiotic surface The adhesion of microalgae and bacteria onto abiotic surfaces were studied using a parallel plate flow chamber (#31-011, Glyco-Tech, MD, USA). As shown in Figure S10, the abiotic surface was connected to the flow chamber by a vacuum pump. The cell suspensions were delivered into the flow chamber by a microinjection pump (PHD 2000, Harvard Apparatus, USA) at a rate of 0.0216 mL min-1. The Reynolds number and wall shear rate over the test section were 0.035 and 3.35 s-1, respectively. It should be noted that the culture medium was flowing in the chamber during the experiments; therefore, the unadhered cells can be washed off because of the hydrodynamic forces (see SI for the analysis of hydrodynamics forces in the flow chamber). To demonstrate a stable adhesion result, the images of the cells adhered onto the surfaces were obtained at around 3000 s using an inverted microscope equipped with a high-speed camera (IX73, Olympus, Japan). Subsequently, all images were processed using the ImageJ (NIH) software to quantify the adhesion density of cells onto surface. All measurements were performed three times and the results shown are the means ± SD. Results and discussion Properties of cells and abiotic surfaces 13


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Table 1 shows the contact angles of water, formamide and methylene iodide on the cell lawns and abiotic surfaces (θW, θF, θM), as well as the components of SFEs for the cells and tot + surfaces determined by the LW-AB approach, i.e.,  mv ,  mvLW ,  mv ,  mv ,  svtot ,  svLW ,  sv+

and  sv- . It was found that γtot of these cells ranged from 41.2 to 53.9 mJ/m2, while the γtot of PMMA, PVC, PC, HMDS coated glass and glass ranged from 30.7 to 56.0 mJ/m2. These results agreed well with those of previously conducted studies.40,41 In addition, the results demonstrated that the contact angle of water on the glass was 19.4 ± 1.8°, indicating that glass was a completely hydrophilic surface. Additionally, the contact angles of water on the other four surfaces (PMMA, PVC, PC, and HMDS coated glass) were 84.2 ± 2.3°, 96.6 ± 2.2°, 96.4 ± 1.5° and 81.0 ± 1.8°, respectively, which indicated that these four surfaces were all hydrophobic. Furthermore, the results indicated that the γ+ values of the marine Chlorella sp., N. oculata, freshwater Chlorella sp., S. obliquus, E. faecalis, S. epidermidis, PMMA, PVC, PC, HMDS coated glass and glass were 3.9, 2.7, 5.7, 6.3, 7.5, 8.3, 0.1, 0.01, 0.01, 1.9, and 2.9 mJ/m2, respectively, while the respective γ− values were 4.6, 14.7, 31.5, 42.1, 5.38, 2.69, 4.14, 0.03, 0.28, 5.9, and 50.18 mJ/m2. These results indicated that the cells and abiotic surfaces all had weak electron acceptors (γ+) ranging from ~0.01 mJ/m2 to ~8 mJ/m2, which agreed well with the literatures.42-43 Moreover, because the cells were cultivated in water-based culture media, it should be noted that the γ+ of water is approximately 25 mJ/m2. Clearly, the

 lv+

values were much higher than the

values. Therefore, these measurements can also verify the omission of 14


+  mv

+  mv

and

and

 sv+

 sv+

in the

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simplification of the AB interaction. Moreover, the ζ potentials for the cells and abiotic surfaces are also shown in Table 1. The results indicated that the ζ potentials of the cells and surfaces interacting with 0.1% NaCl solutions ranged from −22.5 to −43.8 mV, while those of the cells and abiotic surfaces interacting with 0.9% NaCl solutions ranged from −4.18 to −21.8 mV. Evidently, because of the decrease in NaCl concentrations, the cells and abiotic surfaces interacting with 0.1% NaCl solutions were more electronegative than those interacting with 0.9% NaCl solutions.44 In addition, it was found that ζm and ζs had the same magnitude (Table 1). Thus, the values of

( m   s ) 2

would be much higher than those of

( m   s ) 2 .

Therefore,

these measurements can verify the simplification of the EL interaction. Predicting cell adhesion using the criterion by identifying the dominant interactions based on the measured surface characteristics Based on the surface characteristics of cell and abiotic surface, the dominant interaction between cell and surface was analyzed, and then the cell adhesion was predicted using the proposed criterion. Firstly, the surface characteristics leading to the zero Max G

tot

(d ) 

, i.e.,

[SC]0 points, were determined for the microalgae and bacteria, which were shown by the hollow squares in Figure 3, where

   mv   sv

and

( m   s ) 2

were set as the horizontal axis

and vertical axis, respectively. The [SC]0 curves were then obtained by fitting these [SC]0 points. It should be noted that the [SC]0 curve shown in Figure 3a appeared to be linear, whereas the [SC]0 curve in Figure 3b seemed nonlinear. A detailed reason for this 15


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phenomenon can be found in SI. Briefly, as shown in Figure S9 and Table S5, when the zero Max G tot (d )  occurred at a distance between the cell and surface ranging from 3 to 7 nm, the AB interaction was comparable to the EL interaction; therefore, the [SC]0 curve would be linear. However, in the near-surface area (the distance was lower than 3 nm), the variation in the AB interaction was much greater than that in the EL interaction because the AB interaction was a short range interaction.14, 35 Thus, when the zero Max G tot (d )  occurred at a distance between cell and surface lower than 3 nm, a higher ( m   s )2 should be provided to compensate for the higher variation in

  mv   sv

to obtain a balance

between EL and AB interaction, thereby, the [SC]0 curve would be nonlinear. After determining the [SC]0 curve, the values of

   mv   sv

and

( m   s ) 2

for the

adhesion pairs of microorganism−abiotic surfaces used in the experiments were determined based on the parameters shown in Table 1 (see Table S8 and Table S9), as shown by the solid circles in Figure 3. According to the criterion, Figure 3a indicates that, for the marine Chlorella sp., N. oculata, E. faecalis and S. epidermidis, their adhesions onto five abiotic surfaces were located in the lower left area, indicating that these adhesions would be dominated by the AB interaction and may decrease with increasing

   mv   sv

. Meanwhile,

Figure 3b shows that, for the freshwater Chlorella sp. and S. obliquus, their adhesions onto five surfaces were located in the upper right area, indicating that these adhesions would be dominated by the EL interaction, and may decrease with increasing

( m   s ) 2 .

Validating the criterion using the adhesion data obtained in experiment 16


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Figure 4 shows the adhesion density and adhesion rate for the microalgae and bacteria cells onto the five abiotic surfaces. Overall, the results indicated that the marine Chlorella sp. and N. oculata both preferred to adhere onto PVC surface, and their adhesions onto glass were the lowest. Whereas, E. faecalis and S. epidermidis preferred to adhere onto PC and PVC, and their adhesions onto glass and HMDS coated glass were much lower than that onto PC and PVC. In addition, the freshwater Chlorella sp. and S. obliquus preferred to adhere onto HMDS coated glass, PC and PMMA. Evidently, the adhesion behaviors of different microbial cells onto surfaces were different. We will analyze and predict these complicated adhesion results using the proposed criterion. Based on the criterion, the adhesions of marine Chlorella sp., N. oculata, E. faecalis and S. epidermidis were dominated by the AB interaction and would decrease with increasing    mv   sv

. While, the adhesions of freshwater Chlorella sp. and S. obliquus were dominated

by the EL interaction and would decrease with increasing

( m   s ) 2 .

Figure 5a and 5b

shows the adhesion density of the marine Chlorella sp. and N. oculata, as well as E. faecalis and S. epidermidis as a function of

   mv   sv

. It should be noted that, although the

adhesions of marine Chlorella sp., N. oculata, E. faecalis and S. epidermidi were all dominated by the AB interaction, due to the different concentrations of cell suspensions (microalgae: 1 × 106 cells/mL, bacteria: 1 × 108 cells/mL), their adhesions as a function of    mv   sv

can not be shown in the same figure. Clearly, Figure 5a and 5b demonstrated

that the adhesion density of marine Chlorella sp., N. oculata, E. faecalis and S. epidermidi 17


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all decreased as

   mv   sv

Page 18 of 38

increased. Furthermore, Figure 5c shows the adhesion density

of the freshwater Chlorella sp. and S. obliquus as a function of

( m   s ) 2 .

It was found that

the adhesion density of freshwater Chlorella sp. and S. obliquus both decreased as ( m   s ) 2

increased. Taken together, these experimental results can unambiguously verify

the proposed criterion. Moreover, the above adhesion data were also analyzed using other criteria published in literatures. According to the criterion proposed by Cui et al.,32 for the marine Chlorella sp., N. oculate, E. faecalis and S. epidermidis, more adhesion would occur on surfaces with a higher dispersive component of SFE but a lower polar component of SFE, i.e., the PMMA, PVC and PC surfaces. In addition, based on the criterion proposed by Zhang et al., cell adhesion was correlated with the SFE difference between γmv and γsv, i.e., | γmv  γsv |, and a lower | γmv  γsv | was associated with a higher degree of adhesion. Therefore, it was predicted that the adhesion of the marine Chlorella sp., N. oculate, E. faecalis and S. epidermidis onto PMMA, PVC and PC would be much higher than that on HMDS coated glass and glass. Clearly, the experimental results can verify the criteria proposed by Cui 32 and Zhang.15 This may be because both Cui and Zhang’s criteria considered the effects of SFE on cell adhesion, and the adhesions of these four microorganisms onto surfaces were dominated by the AB interaction, which was a component of the SFE. However, for the two freshwater microalgae, their adhesions onto HMDS coated glass were much higher than those adhesions onto PMMA, PVC and PC surfaces, which cannot be predicted by 18


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Cui or Zhang’s criteria. This may be because the adhesion of freshwater microalgae onto these abiotic surfaces was dominated by the EL interaction, which was not considered in both the Cui and Zhang’s criteria. Revalidating the criterion using the adhesion results published in previous studies. We further revalidated the proposed criterion based on many cell adhesion results published in previous studies, including the adhesion pairs of bacteriaabiotic surface, yeastabiotic surface, and microalgaeabiotic surface pairs (the detailed surface characteristics for these adhesion pairs can be found in SI). Figure 6a shows that the surface characteristics for the adhesion of the bacteria C. jejuni C977a (CJ1), C. jejuni ATCC 33650 (CJ2), C. jejuni C939a (CJ3), Salmonella Sofia S1296a (SS) and Salmonella Infantis S1677 (SaI) onto stainless steel34 were located in the lower left area, indicating their adhesions were dominated by the AB interaction. Whereas, the surface characteristics for the adhesions of the yeast Saccharomyces cerevisiae (Sc) onto four modified surfaces by poly random copolymers were located in the upper right area, indicating their adhesions were dominated by the EL interaction.33 Furthermore, Figure 6(a1) shows the relationship between the adhesion density of CJ1, CJ2, CJ3, SS and SaI onto stainless steel and

   mv   sv

.

While, Figure 6(a2) shows the relationship between the adhesion density of Sc onto four modified surfaces and

( m   s ) 2 .

Evidently, as predicted by the proposed criterion, the

adhesion of CJ1, CJ2, CJ3, SS and SaI decreased with increasing adhesion of Sc decreased as

( m   s ) 2

increased. 19


   mv   sv

, while, the

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Furthermore, Figure 6b shows that the surface characteristics for the adhesion of Chlorella vulgaris UTEX 2714 (CV1) and Botryococcus sudeticus UTEX B 2629 (BS) onto the glass and indium-tin oxide (ITO) ,35 as well as the adhesion of Chlorella vulgaris Beijerinck CCALA 924 (CV2) under different nutrient deprivation treatments onto glass slides with/without surface modifications40 were all located in the upper right area, indicating their adhesions were dominated by the EL interaction. In addition, Figure 6(b1) and Figure 6(b2) show the adhesion of CV1 and BS onto the glass and ITO and the adhesion of CV2 onto surfaces as a function of

( m   s ) 2 ,

respectively. Evidently, it was found that

the adhesion of CV1, BS and CV2 all decreased as

( m   s ) 2

increased. It should be noted

that, although the modified surface (3-aminopropyltriethoxysilane) used in CV2 adhesion was positively charged, the criterion proposed in the study could be effectively used to predict its adhesion. This may be because when the ζs was positively charged, the EL interaction would be attractive, and would decrease with the decrease in the positive ζs, that is to say, cell adhesion would decrease with the decrease in the positive ζs. Under this circumstance,

( m   s ) 2

would increase with the decrease in the positive ζs. Evidently,

when the ζs was positive, cell adhesion would also decrease with the increase in ( m   s )2 , which agreed well with the criterion proposed in the study. Taken together, these results clearly demonstrated that the criterion could be easily used to quantitatively predict microbial adhesions in various applications. Moreover, it should be noted that although the adhesions of SC, CV1, BS, and CV2 onto 20


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various abiotic surfaces were all dominated by EL interaction, their adhesion behaviors should not be compared directly. This is because these adhesions were obtained from three separate references, and the methods to observe the adhesion behavior (including the parallel-plate flow chamber approach and placing a glass slide in cell suspension without agitation), as well as the experiment parameters (including the concentration of cell suspensions, flow rate, shear rate, and adhesion time), were completely different.33, 35, 40 Nevertheless, we found that the adhesion of CV1 and BS onto glass and ITO obtained using the same adhesion method under the same experiment parameters, would unambiguously decrease with increasing ( m   s )2 , indicating their adhesions can be effectively predicted using the proposed criterion. Implications and limitations of the proposed criterion in biofilm prediction The study demonstrated that the proposed criterion could predict microbial adhesion by identifying the dominant interactions via comparison of

   mv   sv

with

( m   s ) 2

after

determining the surface characteristics of cells and abiotic surfaces. When the AB interaction was dominant, cell adhesion would decrease with increasing

   mv   sv

, whereas,

when the EL interaction was dominant, cell adhesion would decrease with increasing ( m   s ) 2 .

In various scientific and engineering problems, the criterion might be used to

predict cell adhesion. For example, for microorganisms cultured in high ionic strength nutrient media, both the cells and abiotic surfaces had lower ζ potentials; thus, based on the proposed criterion, the adhesion may be dominated by the AB interaction and would 21


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decrease with increasing

   mv   sv

. Accordingly, to obtain a higher biofilm productivity in

biofilm membrane photobioreactors, an abiotic surface with a lower  sv should be used. Conversely, to prevent biofouling on ship hulls in seawater, antifouling material should be designed to have a higher  sv . While, for food preservation, containers should also have a higher  sv , which may reduce the cell adhesion. Moreover, in biofilm wastewater treatment systems,45 the substrate filters with suitable ζs and  sv can be also selected based on the criterion. Additionally, in microbial fuel cells,46-47 the criterion could be used to predict biofilm formation on the electrode to ensure the effective transfer of electrons. Fundamentally, the criterion was developed based on the sphere-plate model within the scope of xDLVO theory, in which the surfaces of the cells and substrata were considered smooth and homogeneous. However, it should be noted that, in some applications, the surface characteristics of the abiotic substrata could be affected by the roughness, heterogeneity and adsorption of molecules.13, 18, 38 While the surface characteristics of the cell could be affected by the extracellular polymeric substances pili and flagella29, 48, and might change in response to the changes in the culture conditions and different stages of cell cultivation.44 In some applications, mixed cultivation might exist, thus, the species interactions might also significantly influence the cell adhesion.49 Although these differences might affect the accuracy of the criterion, the study demonstrated that the criterion was still valuable for the prediction of adhesion in the majority of cases. Followup studies would be conducted to amend the criterion for better applicability. 22


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Conclusion In summary, a quantitative criterion to predict microbial adhesion was proposed by identifying the dominant interactions between microorganisms and abiotic surfaces. The results indicated that microbial adhesion could be dominated either by AB or EL interactions via comparing

   mv   sv

with

( m   s ) 2

after determining the surface

characteristics of cells and abiotic surfaces. When the AB interaction was dominant, cell adhesion would decrease with increasing

   mv   sv

. Whereas, cell adhesion would

decrease with increasing ( m   s )2 when the EL interaction was dominant. The criterion was verified based on the adhesions of microalgae, bacteria and fungi onto various abiotic surfaces using data generated in our experiments and available in the literatures33-35, 40. The study demonstrated that the criterion was effective and may have important implications for prediction of adhesion in various scientific and engineering problems.

Supporting Information Predicting the microalgae adhesion within the scope of xDLVO theory; simplification of the surface interactions; physicochemical properties for the microorganism and abiotic surfaces; the determination of [SC]0 curve; microbial cell cultivation; determining the surface free energy (SFE) of microbial cells and abiotic surfaces; description for the parallel flow chamber; identification of the dominant interactions in cell adhesion. 23


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Acknowledgement This work is supported by the National Science Foundation of China (No. 51706019 and No. 51406008), and the Fundamental Research Fund for the Central Universities (No. FRFAS-17-001 and No. FRF-BD-18-015).

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Predicting Bacterial Adhesion Using Surface Free Energy Determined with a Spectrophotometric Method. Environmental Science & Technology 2015, 49 (10), 61646171. 16. Poortinga, A. T.; Bos, R.; Norde, W.; Busscher, H. J., Electric Double Layer Interactions in Bacterial Adhesion to Surfaces. Surface Science Reports 2002, 47 (1), 1-32. 17. Chao, Y.; Guo, F.; Fang, H. H. P.; Zhang, T., Hydrophobicity of Diverse Bacterial Populations in Activated Sludge and Biofilm Revealed by Microbial Adhesion to Hydrocarbons Assay and High-throughput Sequencing. Colloids and Surfaces B: Biointerfaces 2014, 114 (0), 379-385. 18. Sharma, S.; Jaimes-Lizcano, Y. A.; McLay, R. B.; Cirino, P. C.; Conrad, J. C., Subnanometric roughness affects the deposition and mobile adhesion of Escherichia coli on silanized glass surfaces. Langmuir 2016, 32 (21), 5422-5433. 19. Arslan, B.; Egerton, K.; Zhang, X.; Abu-Lail, N. I., Effects of the Surface Morphology and Conformations of Lignocellulosic Biomass Biopolymers on Their Nanoscale Interactions with Hydrophobic Self-Assembled Monolayers. Langmuir 2017, 33 (27), 6857-6868. 20. Gross, M.; Zhao, X.; Mascarenhas, V.; Wen, Z., Effects of the Surface Physicochemical Properties and the Surface Textures on the Initial Colonization and the Attached Growth in Algal Biofilm. Biotechnology for biofuels 2016, 9 (1), 1. 21. Zhang, X.; Yuan, H.; Jiang, Z.; Lin, D.; Zhang, X., Impact of Surface Tension of Wastewater on Biofilm Formation of Microalgae Chlorella sp. Bioresource Technology 2018, 266, 498-506. 22. Park, B.-J.; Abu-Lail, N. I., The Role of the pH Conditions of Growth on the Bioadhesion of Individual and Lawns of Pathogenic Listeria monocytogenes cells. J Colloid Interf Sci 2011, 358 (2), 611-620. 23. Gordesli, F. P.; Abu-Lail, N. I., Impact of Ionic Strength of Growth on the Physiochemical Properties, Structure, and Adhesion of Listeria monocytogenes Polyelectrolyte Brushes to a Silicon Nitride Surface in Water. J Colloid Interf Sci 2012, 388 (1), 257-267. 24. Gordesli, F. P.; Abu-Lail, N. I., The Role of Growth Temperature in the Adhesion and Mechanics of Pathogenic L. monocytogenes: An AFM Study. Langmuir 2011, 28 (2), 1360-1373. 25. Nejadnik, M. R.; van der Mei, H. C.; Busscher, H. J.; Norde, W., Determination of the Shear Force at the Balance between Bacterial Attachment and Detachment in WeakAdherence Systems, Using a Flow Displacement Chamber. Appl Environ Microb 2008, 74 (3), 916-919. 26. Sharma, S.; Conrad, J. C., Attachment from Flow of Escherichia coli Bacteria onto Silanized Glass Substrates. Langmuir 2014, 30 (37), 11147-11155. 27. Tan, M. S.; Rahman, S.; Dykes, G. A., Pectin and Xyloglucan Influence the 26


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Attachment of Salmonella enterica and Listeria monocytogenes to Bacterial Cellulosederived Plant Cell Wall Models. Appl Environ Microb 2016, 82 (2), 680-688. 28. Friedlander, R. S.; Vogel, N.; Aizenberg, J., Role of Flagella in Adhesion of Escherichia coli to Abiotic Surfaces. Langmuir 2015, 31 (22), 6137-6144. 29. McLay, R. B.; Nguyen, H. N.; Jaimes-Lizcano, Y. A.; Dewangan, N. K.; Alexandrova, S.; Rodrigues, D. F.; Cirino, P. C.; Conrad, J. C., Level of Fimbriation Alters the Adhesion of Escherichia coli Bacteria to Interfaces. Langmuir 2018, 34 (3), 1133-1142. 30. Absolom, D. R.; Lamberti, F. V.; Policova, Z.; Zingg, W.; van Oss, C. J.; Neumann, A. W., Surface Thermodynamics of Bacterial Adhesion. Appl Environ Microb 1983, 46 (1), 90-97. 31. Van Oss, C.; Good, R.; Chaudhury, M., The Role of Van der Waals Forces and Hydrogen Bonds in “Hydrophobic Interactions” between Biopolymers and Low Energy Surfaces. J Colloid Interf Sci 1986, 111 (2), 378-390. 32. Cui, Y.; Yuan, W., Thermodynamic Modeling of Algal Cell–solid Substrate Interactions. Applied Energy 2013, 112 (0), 485-492. 33. Kang, S.; Choi, H., Effect of Surface Hydrophobicity on the Adhesion of S. cerevisiae onto Modified Surfaces by Poly(Styrene-ran-sulfonic Acid) Random Copolymers. Colloids and Surfaces B: Biointerfaces 2005, 46 (2), 70-77. 34. Nguyen, V. T.; Chia, T. W. R.; Turner, M. S.; Fegan, N.; Dykes, G. A., Quantification of Acid–base Interactions Based on Contact Angle Measurement Allows XDLVO Predictions to Attachment of Campylobacter jejuni but not Salmonella. Journal of Microbiological Methods 2011, 86 (1), 89-96. 35. Ozkan, A.; Berberoglu, H., Adhesion of Algal Cells to Surfaces. Biofouling 2013, 29 (4), 469-482. 36. Hamadi, F.; Latrache, H.; Mabrrouki, M.; Elghmari, A.; Outzourhit, A.; Ellouali, M.; Chtaini, A., Effect of pH on Distribution and Adhesion of Staphylococcus aureus to Glass. Journal of Adhesion Science and Technology 2005, 19 (1), 73-85. 37. Sharma, P. K.; Hanumantha Rao, K., Analysis of Different Approaches for Evaluation of Surface Energy of Microbial Cells by Contact Angle Goniometry. Advances in Colloid and Interface Science 2002, 98 (3), 341-463. 38. Perni, S.; Preedy, E. C.; Prokopovich, P., Success and Failure of Colloidal Approaches in Adhesion of Microorganisms to Surfaces. Advances in Colloid and Interface Science 2014, 206, 265-274. 39. Kwok, D. Y.; Neumann, A. W., Contact Angle Measurement and Contact Angle Interpretation. Advances in Colloid and Interface Science 1999, 81 (3), 167-249. 40. Sirmerova, M.; Prochazkova, G.; Siristova, L.; Kolska, Z.; Branyik, T., Adhesion of Chlorella vulgaris to Solid Surfaces, as Mediated by Physicochemical Interactions. J Appl Phycol 2013, 25 (6), 1687-1695. 41. Genin, S. N.; Stewart Aitchison, J.; Grant Allen, D., Design of Algal Film 27


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Photobioreactors: Material Surface Energy Effects on Algal Film Productivity, Colonization and Lipid Content. Bioresource Technology 2014, 155 (0), 136-143. 42. Holmes-Farley, S. R.; Bain, C. D.; Whitesides, G. M., Wetting of Functionalized Polyethylene Film Having Ionizable Organic Acids and Bases at the Polymer-water Interface: Relations Between Functional Group Polarity, Extent of Ionization, and Contact Angle with Water. Langmuir 1988, 4 (4), 921-937. 43. Nguyen, V.; Karunakaran, E.; Collins, G.; Biggs, C. A., Physicochemical analysis of initial adhesion and biofilm formation of Methanosarcina barkeri on polymer support material. Colloids and Surfaces B: Biointerfaces 2016, 143, 518-525. 44. Ozkan, A.; Berberoglu, H., Physico-chemical Surface Properties of Microalgae. Colloids and Surfaces B: Biointerfaces 2013, 112 (0), 287-293. 45. Kesaano, M.; Sims, R. C., Algal Biofilm Based Technology for Wastewater Treatment. Algal Research 2014, 5, 231-240. 46. Sun, D.; Cheng, S.; Wang, A.; Li, F.; Logan, B. E.; Cen, K., Temporal-spatial Changes in Viabilities and Electrochemical Properties of Anode Biofilms. Environmental science & technology 2015, 49 (8), 5227-5235. 47. Logan, B. E.; Hamelers, B.; Rozendal, R.; Schröder, U.; Keller, J.; Freguia, S.; Aelterman, P.; Verstraete, W.; Rabaey, K., Microbial Fuel Cells: Methodology and Technology. Environmental science & technology 2006, 40 (17), 5181-5192. 48. Wang, H.; Wilksch, J. J.; Chen, L.; Tan, J. W. H.; Strugnell, R. A.; Gee, M. L., Influence of Fimbriae on Bacterial Adhesion and Viscoelasticity and Correlations of the Two Properties with Biofilm Formation. Langmuir 2017, 33 (1), 100-106. 49. Gonçalves, A. L.; Ferreira, C.; Loureiro, J. A.; Pires, J. C.; Simões, M., Surface Physicochemical Properties of Selected Single and Mixed Cultures of Microalgae and Cyanobacteria and Their Relationship with Sedimentation Kinetics. Bioresources and Bioprocessing 2015, 2 (1), 1.

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Figure captions Figure 1. (a) The total interaction energy, Gtot, as a function of distance between cells and abiotic surfaces. Case 1: EL interaction was much higher than AB interaction. Case 2: EL interaction was comparable to AB interaction. Case 3: AB interaction was much higher than EL interaction. (b) The criterion to predict cell adhesion. The surface characteristics around the [SC]0 curve would represent the cases of which EL interaction was comparable to AB interaction (case 2). The surface characteristics of the cellabiotic surface pair located in the upper left zone (blue) represented cases of which GEL was higher than G AB (case 1). While the surface characteristics located in the lower right zone (green) represented cases of which GAB was higher than GEL (case 3). Figure 2. The criterion to predict microbial adhesion. When the surface characteristics of cellabiotic surface pairs were located in the upper right zone (blue), the cell adhesion would be dominated by the EL interaction and decrease with increase increasing ( m   s )2 . When the surface characteristics of cellabiotic surface pairs were located in the lower left zone (green), the adhesion would be dominated by the AB interaction and decrease with increasing

   mv   sv

.

Figure 3. Identifying the dominant interaction in cell adhesion. (a) The surface characteristics for the adhesion of marine Chlorella sp., N. oculate, E. faecalis and S. epidermidis onto five surfaces, i.e., PMMA, PVC, PC, HMDS coated glass and glass, were located in the lower left area, indicating that their adhesion were dominated by the AB 29


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Page 30 of 38

interaction. (b) The surface characteristics for the adhesion of freshwater Chlorella sp. and S. obliquus onto these five surfaces were located in the upper right area, indicating that their adhesion were dominated by the EL interaction. Figure 4. Cell adhesion density and adhesion rate of the marine Chlorella sp. (a), N. oculate (b), E. faecalis (c), S. epidermidis (d), freshwater Chlorella sp. (e), and S. obliquus (f), onto five abiotic surfaces. Figure 5. Adhesion density of the marine Chlorella sp. and N. oculate (a), as well as E. faecalis and S. epidermidis (b) as a function of

   sv  mv

. Adhesion density of freshwater

Chlorella sp. and S. obliquus as a function of ( m   s )2 (c). Figure 6. (a) (b) The criterion to determine the dominant interactions involved in microbial adhesion based on data available in the literatures. (a1) Adhesion as a function of

   mv   sv

for C. jejuni (CJ1, CJ2 and CJ3) and Salmonella (SaI and SS). (a2), (b1) and (b2) Adhesion as a function of ( m   s )2 for S. cerevisiae (Sc), C. vulgaris (CV1) and B. sudeticus (BS), as well as C. vulgaris (CV2), respectively.

30


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Langmuir

Figure 1.

31


Langmuir 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

Figure 2.

32


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Page 33 of 38 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

Langmuir

Figure 3.

33


2000

50 1500 200 100 0

Adhesion density (cell/mm2)

28000

PMMA PVC PC HMDS GLASS

(c)

24000

40 10 5 0

Adhesion density Adhesion rate

700 600

20000

500

16000

400

200

300

100

50

2400


(e)


0

90

Adhesion rate (cell/mm2·min)

0

80 70

2000

60 1600

50

200

40 10 5 0

100 0



2500

90


60

(b)

80 70 60

2000

50 1500 200 100 0

28000

PMMA PVC

(d)

24000

PC HMDS GLASS


40 10 5 0

700


70

3000

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600

20000

500

16000

400

200 100 0

300 50 0


2400

200

90 80 70 60 50 40 30

100

5

(f)

2000


1600 1200

0


Figure 4.

34


0


80


2500

90




(a)



3000


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


Langmuir

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2600

Marine Chlorella sp. N. oculate

(a)

2400 2200 2000 1800 1600

0.05 0.10 0.15 0.20 0.25 0.30 0.35 0.40    sv ( J/m 2 )  mv


28000

E.faecalis S.epidermidis

(b)

24000

20000

16000

12000 0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

   sv ( J/m 2 )  mv


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

Langmuir

2200

Freshwater Chlorella sp. S. obliquus

(c)

2000 1800 1600 1400 1200 4000

4500

5000

5500

(ζs+ζm)2 (mV2)

6000

6500

Figure 5.

35


C. jejuni (CJ1, CJ2, CJ3) Salmonella (SS,SaI)

(a1)

5

4

3

0.18

0.20

0.22

0.24

   sv ( J/m 2 )  mv

300

(a2)

Adhesion density (×103cell/mm2)

6

S.cerevisiae (Sc)

Adhesion of microalgae (%)


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

Adhesion density (log cell/cm2)

Langmuir

250

200

150

100

0

500

1000

(ζs+ζm)2 (mV2)

1500

2000

Page 36 of 38

12

C. vulgaris (Cv1) B. sudeticus (Bs)

(b1)

10 8 6 4 2 0 0

20

1000

2000

3000

(ζs+ζm)2 (mV2)

4000

C. vulgaris (Cv2)-CMM C. vulgaris (Cv2)-MLM C. vulgaris (Cv2)-SLM C. vulgaris (Cv2)-NLM

(b2)

15 10 5 0 0

1000

Figure 6.

36


2000

(ζs+ζm)2 (mV2)

3000

4000

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Langmuir

Table 1. Surface properties (ζ potential, surface free energy and its components) of the microorganisms and substrata. Microorganism and substrata Microalgae

Bacteria

Substrata

γtot θW (°)

θF (°)

γLW

γ+

γ--

θM (°) (mJ/m2)

ζ1

ζ2

(mV)

(mV)

Marine Chlorella sp.

69.8±1.3

32.7±0.9

45.8±1.2

45.0

36.5

3.9

4.6

-15.2±2.9

-

Nannochloris oculata

60.9±1.3

39.0±0.7

53.6±1.5

44.7

32.2

2.7

14.7

-14.9±3.8

-

Freshwater Chlorella sp.

42.4±1.4

29.9±1.0

67.8±0.9

50.8

24.1

5.7

31.5

-

-42.3±4.3

Scenedesmus obliquus

32.9±3.6

28.7±2.0

73.0±2.3

53.9

21.2

6.3

42.1

-

-43.8±2.9

Enterococcus faecalis

64.5±3.5

20.1±2.0

53.5±1.3

45.0

32.3

7.5

5.38

-15.9±2.9

-

Staphylococcus epidermidis

69.5±1.7

22.4±1.7

54.5±1.2

41.2

31.7

8.3

2.69

-4.18±1.6

-

PMMA

84.2±2.3

64.6±1.8

45.8±1.6

37.8

36.6

0.1

4.14

-11.8±1.0

-28.2±1.2

PC

96.6±2.2

63.2±1.7

32.1±1.9

43.4

43.3

0.01

0.03

-21.3±1.2

-27.6±1.8

PVC

96.4±1.5

66.2±2.7

39.8±1.1

39.7

39.6

0.01

0.28

-21.8±1.1

-34.9±1.3

HMDS coated glass

81.0±1.8

61.2±0.8

67.8±0.7

30.7

24.1

1.9

5.9

-9.0±2.3

-22.5±1.3

Glass

19.4±1.8

17.1±1.6

54.3±1.1

56.0

31.9

2.9

50.18

-12.0±0.6

-36.2±1.8

Note: θW, contact angle (CA) of water. θF, CA of formamide. θM, CA of methylene iodide. γtot, total surface free energy (SFE). γLW, van der Waals components of SFE. γ+, electron acceptor components of SFE. γ-, electron donor components of SFE. ζ1: Zeta potential in 0.9% NaCl solution. ζ2: Zeta potential in 0.1% NaCl solution.

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TOC

38


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A Quantitative Criterion to Predict Cell Adhesion by Identifying the

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