Microbial surface thermodynamics and applications

Research in Microbiology 154 (2003) 329–335 www.elsevier.com/locate/resmic

Mini-review

Microbial surface thermodynamics and applications Keith A. Strevett a,∗ , Gang Chen b a Bioenvironmental Engineering and Environmental Science Laboratory, School of Civil Engineering and Environmental Science,

University of Oklahoma, Norman, OK 73019, USA b Department of Crop and Soil Science, Washington State University, Pullman, WA 99164, USA

Received 12 November 2002; accepted 5 February 2003 First published online 5 February 2003

Abstract Microbial surface thermodynamics is the reflection of microbial physicochemical and biological characteristics and it bridges micro-scale structures with macro-scale biological functions. Microbial surface thermodynamics is theoretically based on colloid surface thermodynamics using the classical theory of colloidal stability, Derjauin–Landau–Verwey–Overbeek (DLVO) theory. An extended DLVO theory is applied to for the hydration forces not considered in the classical DLVO theory. Herein, a review of current application of microbial surface thermodynamic theory is presented. Microbial surface thermodynamic theory is the fundamental theory in interpreting microbial hydrophilicity or hydrophobicity, microbial attachment, and microbial biofilm development.  2003 Éditions scientifiques et médicales Elsevier SAS. All rights reserved. Keywords: Microbial surface thermodynamics; DLVO; XDLVO; Biofilm; Microbial transport; Microbial adhesion

1. Introduction Liquid and solid surface thermodynamics can be well described by the surface tension that is defined as half of the free energy change due to cohesion of the material in vacuo [10]. The surface tension of a material is contributed by a number of relatively independent forces such as dispersion, dipolar, induction, hydrogen-bonding, and metallic interactions [9]. According to the traditional and extended Derjaguin, Landau, Verwey, and Overbeek (DLVO) theory, the surface tension of colloid-size particles is mainly composed of apolar, or Lifshitz–van der Waals (LW) component; polar, or Lewis acid–base (AB) component; and electrostatic (EL) component [5,15–17,21,26]. Lifshitz–van der Waals component surface tension is initiated by the unevenness of the electron cloud surrounding the molecules or particles. Lewis acid–base component surface tension is owing to the potential formation of coordinate covalent bonds by Lewis acids, or electron pair acceptors and Lewis bases, or electron pair donors [18]. Electrostatic component sur* Corresponding author.

E-mail address: [email protected] (K.A. Strevett).

face tension is more commonly described using the term of ζ potential, which is a measurement of electrical surface charge. The capability of colloid-size particle based traditional and extended DLVO theory has been previously discussed [14] and successfully introduced in describing microbial surface thermodynamics [6,11,12,22]. Impacts of nutrient conditions, exopolymer production, growth rates and physiological states on microbial surface thermodynamics have been extensively investigated [2,7,8]. Microbial surface thermodynamic theory is the fundamental theory in interpreting microbial hydrophilicity or hydrophobicity, microbial attachment to porous media, and microbial biofilm development. Owing to increasing interest in predicting the fate and transport of bacteria in the subsurface, which is motivated by the fact that some microorganisms can contaminate drinking water supplies, while others can be utilized for bioremediation, the successful application of microbial surface thermodynamic theory is becoming more prevalent [2,17,22,28]. This review addresses the recent development and achievement in the microbial surface thermodynamic theory and its applications.

0923-2508/03/$ – see front matter  2003 Éditions scientifiques et médicales Elsevier SAS. All rights reserved. doi:10.1016/S0923-2508(03)00038-X

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K.A. Strevett, G. Chen / Research in Microbiology 154 (2003) 329–335

2. Microbial surface thermodynamics 2.1. Microbial surface thermodynamic measurement Microbial surface thermodynamic properties can be obtained through contact angle measurements using the van Oss–Chaundhury–Good equation [26]:  
  + − LW LW (1 + cos θ )γL = 2 γS γL + γS γL + γS− γL+ , (1) where γL is the surface tension of the liquid that is used for the measurement (mJ/m2 ); γ LW Lifshitz–van der Waals component of surface tension (subscript S for solid and L for liquid) (mJ/m2); γ + electron-acceptor parameter and γ − electron-donor parameter of Lewis acid–base component of surface tension (subscript S for solid and L for liquid) (mJ/m2). In addition, liquid surface tension γL can be expressed in terms of Lifshitz–van der Waals and Lewis acid–base components of surface tension γLLW , γL+ and γL− :  γL = γLLW + 2 γL− γL+ . (2)

Fig. 1. Microbial total interaction free energy as a function of lawn moisture content.

2.2. Factors that impact microbial surface thermodynamics 2.2.1. Growth conditions Microbial anabolism depends upon a stoichiometric ratio of carbon and nitrogen, two essential components, to synthesize new cellular materials [23]. Different carbon and nitrogen conditions yield different cell growth rates and surface thermodynamic properties. Table 1 shows the surface thermodynamics of some microorganisms cultured under different carbon and nitrogen conditions. For the same carbon source, ammonia yields greater electron donor parameter of Lewis acid–base component of surface tension, γ − ; while nitrate yields greater van der Waals component of surface

For the determination of microbial surface thermodynamics, i.e., γSLW , γS+ and γS− , three contact angle measurements (with three different liquids) are needed. Microbial contact angles are usually measured by depositing cells on a flat surface, growth of cells on a flat solid (nutrient) medium, or suction-filtrating cell suspensions onto a flat filter. As a certain amount of moisture is required during contact angle measurements to maintain a smooth and measurable surface, the thus measured microbial surface thermodynamic properties depend on the lawn moisture contents (Fig. 1). Table 1 Microbial surface thermodynamic properties under different growth conditions Bacteria

Medium formation

E. coli1

Glu +

E. coli1

Glu +

E. coli1

Glu +

E. coli1

Glu +

E. coli1

Glu +

E. coli1

Glu +

E. coli1

Lac +

E. coli1

Lac +

E. coli1

Lac +

E. coli1

Lac +

E. coli1

Lac +

E. coli1

Lac +

P. aeruginosa2

Suc +

A. calcoaceticus RAG-13 A. actinomycetemcomitans HG10993 S. mitis BA3

NH+ 4 NH+ 4 NH+ 4 NO− 3 NO− 3 NO− 3 NH+ 4 NH+ 4 NH+ 4 NO− 3 NO− 3 NO− 3 NO− 3

BHI BHI THB

C:N

γ+

γ−

γ LW

(g g−1 )

(mJ m−2 )

(mJ m−2 )

(mJ m−2 )

(mJ m−2 )

5:1

0.438

53.16

44.23

31.49

30:1

0.294

57.23

42.04

38.76

1:1.5

0.597

50.22

45.03

26.52

5:1

0.668

48.08

47.17

22.23

30:1

0.406

53.23

45.03

31.30

1:1.5

0.458

47.29

48.35

21.53

5:1

0.198

56.40

42.49

38.47

30:1

0.214

58.28

41.09

41.36

1:1.5

0.146

55.52

44.23

36.99

5:1

0.348

53.24

44.64

31.99

30:1

0.322

56.36

42.49

37.22

1:1.5

0.356

52.16

45.03

30.36

1:5

0.381

53.70

32.54

– – –

0 3.2 5.8

41.4 0.2 3.8

36.8 33.5 35.8

GTOT 131

38.26 20.2 −65.1 −39.7

1 From Chen and Strevett [7]; 2 from Grasso et al. [12]; 3 from van der Mei et al. [24]. Glu, glucose; Lac, sodium lactate; Suc, succinic acid; BHI, brain heart infusion broth; THB, Todd Hewitt broth.

K.A. Strevett, G. Chen / Research in Microbiology 154 (2003) 329–335

tension γ LW . When carbon is limited, microorganisms have smaller γ − , but greater γ LW than that of no nutrient limitation. When nitrogen is the limiting factor, bacteria have smaller γ LW , but greater γ − . Whereas, there is no reporting germane ζ potential changes with regarding to growth conditions. 2.2.2. Physiological states Van Oss [26] has suggested that the γ LW values for a considerable number of biological and many other organic materials are typically equal to 40 mJ/m2 with minor variability. Chen and Strevett [6] demonstrated that γ LW did not change significantly for E. coli, P. fluorescens and B. subtilis from logarithmic state to stationary state and decay state and Grasso et al. [12] made the same observations (Table 2). As bacteria exhibit a monopolar surface (γ1− at least one order of magnitude greater than γ1+ ), γ − plays a more important role among other surface thermodynamic parameters. This is demonstrated in Fig. 2,

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which depicts the potential energy of interaction between P. aeruginosa and dolomite as a function of distance [12]. Chen and Strevett [6] also reported γ − increase by 1.5–4% for E. coli, P. fluorescens and B. subtilis and Grasso et al. [12] reported γ − increase by 2.6% for P. aeruginosa from logarithmic state to stationary state. Conversely, there was no significant change from logarithmic state to decay state (change of γ − <1.2%). 2.2.3. Microbial surface structures Using infrared spectroscopy (IR), microbial surfaces are found to be characterized by a variety of different functional groups of aldehydes (RCOH) (peaks shown at wavenumber of 1700 cm−1 ), ketones (RCOR) (1680 cm−1 ), carboxylic acids (RCOOH, RCOO− ) (1690 cm−1 , 1600 cm−1 ), carbonyl groups (CH3 CO–) (1320 cm−1 ), peptide bond (–CO– NH–) (1500 cm−1 ), ethers (–CH2 –O–, CH3 –O–, –C–O– C–) (1000 cm−1 , 980 cm−1 , 1060 cm−1 ), ethenyl groups (–CH=CH–, >C=CH2 , –CH=CH2 ) (700 cm−1 , 830 cm−1 ,

Table 2 Microbial surface thermodynamic properties in different physiological states Strain E. coli L1 E. coli S1 E. coli D1 P. fluorescens L1 P. fluorescens S1 P. fluorescens D1 B. subtilis L1 B. subtilis S1 B. subtilis D1 P. aeruginosa L2 P. aeruginosa S2 P. aeruginosa D2

ζ potential (mV)

γ1LW (mJ m−2 )

γ1+ (mJ m−2 )

γ1− (mJ m−2 )

−2 GTOT 131 (mJ m )

−16.4 −16.3 −16.5 −19.5 −18.9 −19.0 −22.9 −22.8 −22.8 −17.59 −26.17 −18.50

39.62 39.11 39.62 36.49 36.49 37.02 45.03 44.64 44.64 32.54 30.66 32.83

0.72 0.59 0.56 1.32 1.29 1.29 0.07 0.08 0.09 0.381 0.211 0.035

57.19 58.98 57.87 56.00 56.83 55.82 57.59 59.88 57.55 53.70 39.49 55.18

48.95 41.19 48.48 55.49 50.77 56.17 43.85 38.84 43.96 38.26 21.16 44.02

1 From Chen and Strevett [7]; 2 from Grasso et al. [12]. L, logarithmic state; S, stationary state; D, decay state.

Fig. 2. Total interaction energy, GTOT 132 , for dolomite–P. aeruginosa. Insert panel is an expanded view of the secondary minumum ca. 20 nm: – – –, logarithmic; · · ·, stationary; —, decay (adapted from Grasso et al. [12]).

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Table 3 Relevant transmissions of different functional groups on microbial surface RCOH RCOR RCOOH RCOO− CH3 CO– –CO–NH– –CH2 –O– CH3 –O– –C–O–C– –CH=CH– >C=CH2 –CH=CH2 E. coli L 35.5 42.1 N/A 49.2 58.2 45.1 62.8 N/A 60.1 60.1 76.5 77.6 E. coli S 20.3 21.2 N/A 32.3 55.1 44.2 60.9 N/A 62.2 62.5 78.3 76.4 E. coli D 30.4 35.4 N/A 39.1 56.7 50.1 68.2 N/A 72.4 62.4 78.1 76.1 P. fluorescens L 39.6 N/A N/A 55.5 74.4 75.2 54.4 N/A 57.8 72.3 72.8 66.4 P. fluorescens S 30.5 N/A N/A 50.4 62.2 58.4 50.0 N/A 61.9 82.8 82.2 78.2 P. fluorescens D 38.1 N/A N/A 52.3 62.5 58.2 52.1 N/A 60.5 82.2 78.4 76.5 B. subtilis L 21.7 27.5 N/A 32.0 30.2 39.3 40.5 N/A 40.7 40.1 45.5 40.4 B. subtilis S 8.8 18.4 N/A 10.8 30.0 19.8 35.7 N/A 36.5 46.7 48.2 42.2 B. subtilis D 19.8 29.2 N/A 30.2 32.5 30.1 37.4 N/A 36.2 46.1 44.8 38.7 Strain*

∗ From Chen and Strevett [6]. L, logarithmic state; S, stationary state; D, decay state.

860 cm−1 ), etc., as well as hydrogen (H–) (2900 cm−1 ) and (hydroxyl) (OH–) (3600 cm−1 ), which are contributed by water [3]. At stationary state, bacteria have more functional groups that favor γ − , or hydrogen-binding groups such as RCOH and RCOO− which show peaks at wavenumber between 1400 and 1700 cm−1 than at logarithmic and decay states, but less functional groups such as –CH=CH– and >C=CH2 that weaken γ − . Microbial surface thermodynamics are a reflection of physico-chemistry of bacterial surfaces, which is controlled by macromolecular components, e.g., lipo-polysaccharide, protein and exopolymers, varying in quantity with growth conditions and from strains to strains. The amount of the macromolecular components can be represented by a variety of different functional groups. Recently, Chen and Strevett [6] demonstrated that microbial surface characteristics contribute to surface thermodynamics. Table 3 summarizes the relevant transmissions of functional groups on E. coli, P. fluorescens and B. subtilis surfaces at different physiological states [6]. In addition, surface characteristics are related directly to microbial surface thermodynamics, i.e., functional groups such as RCOH and RCOO− favor γ − ; functional groups such as –H=CH– and >C=CH2 weaken γ − [6].

3. Microbial surface thermodynamic theory application 3.1. Hydrophilicity and hydrophobicity Microbial surface hydrophilicity or hydrophobicity can be evaluated using GTOT 131 , the total free energy of interactions between microbial cells (1), immersed in water (3), which is the sum of GLW 131 , Lifshitz–van der Waals interaction free energy and GAB 131 , Lewis acid–base interaction free energy [26]: LW AB GTOT 131 = G131 + G131 , 
 2 LW − γ LW = −2 γ , GLW 131 3 1

GAB 131 = −4




γ1+ −



γ3+




γ1− −

(3) (4) 

 γ3− .

(5)

G131 describes the interaction of two microbial cells immersed in water, as a model solvent. These interactions are assumed as a semi-infinite flat parallel slab configuration and are evaluated at the equilibrium distance or closest approach, y0 (assumed to be 1.57 Å by [26]) where physical “contact” can occur. At this distance, the electrostatic interactions can be neglected compared with Lifshitz–van der Waals and Lewis acid–base interactions [25]. Based on van Oss [26], a microbial surface is classified hydrophilic when GTOT 131 is greater than zero or hydrophobic when GTOT is smaller than zero. The hydrophilicity or 131 hydrophobicity increases with the increase of the absolute GTOT 131 value. Thus microbial surface thermodynamics can be used in evaluating microbial surface hydrophilicity and hydrophobicity. E. coli cultured with previously mentioned medium formulations and P. aeruginosa thus exhibits a predominant hydrophilic surface (Table 1). The predominant hydrophilicity of bacteria results in a mono-dispersed microbial suspension in water rather than aggregation. Also, E. coli has a more hydrophilic surface when nitrogen is limited, and a less hydrophilic surface when carbon is limited than that of no carbon or nitrogen limitation. A. actinomycetemcomitans HG1099 and S. mitis BA exhibit a predominant hydrophobic surface (Table 1). E. coli, P. fluorescens, B. subtilis and P. aeruginosa have a less hydrophilic surface in stationary states than logarithmic and decay states (Table 2). Microbial surface thermodynamics is mainly determined by the outer surface of the bacterial membrane [26]. As the outer surface of the membrane in Gram-negative bacteria is high in lipid contents and low in peptidoglycan contents, Gram-negative bacterial surface thermodynamic properties are easily influenced by moisture contents of the surrounding environment [13,19]. While Gram-positive bacteria are high in peptidoglycan, which makes them resistive to the surrounding environment and their surface thermodynamic properties relatively stable with regarding to changes of surrounding environmental moisture contents. Thus the hydrophilicity of Gram-negative bacteria increases significantly with the decrease of surrounding moisture contents; however, the hydrophilicity of Gram-positive bacteria is relatively stable.

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3.2. Microbial attachment in porous media One of the primary processes affecting microbial transport is the propensity of bacteria to adhere to the surfaces of porous media. This tendency determines the fate of bacteria in aquifer material [25]. Both deposition and retardation are related to bacterial adhesion, which is due to the interfacial forces between the bacteria and the media [8,13,15]. Winget et al. [27] demonstrated that the partition coefficient was related the difference between the standard-state free energies of transfer of the solute into the phases. Further research has presented the relationship between the equilibrium, portioning constant and surface interaction free energy. Chen and Strevett [6] illustrated that bacterial deposition on the porous media was related to the interfacial interaction energy between the bacteria and aquifer media (evaluated at closest approach). Microbial deposition on porous media can be evaluated using GTOT 132 , the total free energy of interactions between bacterial cells (1), and porous media (2), immersed in water (3), which is the sum of GLW 132 , Lifshitz–van der Waals , interaction free energy, GAB 132 Lewis acid–base interaction , electrostatic interaction free energy free energy, and GEL 132 (van Oss, 1994): LW AB EL GTOT 132 = G132 + G132 + G132 ,  
 GLW γ3LW − γ2LW 132 = −4πRy0 
  × γ3LW − γ1LW , 
    AB γ3+ γ1− + γ2− − γ3− G132 = 4πRy0 
    + 2 γ3− γ1+ + γ2+ − γ3+    − 2 γ1+ γ2− − 2 γ1− γ2+ , −κy ), GEL 132 = πεε0 Rψ01 ψ02 ln(1 + e

(6)

(7)

(8) (9)

where ε and ε0 are the relative dielectric permittivity of water and permittivity under vacuum respectively; ψ01 , ψ02 potentials at the surfaces of bacteria and the medium matrix; 1/κ Debye–Hückel length and also an estimation of the effective thickness of the electrical double layer [16]; λ decay length of water. ψ01 , ψ02 can be calculated using the following equation: ψ0 = ζ (1 + z/a) exp(κz),

(10)

where ζ is the ζ potential measured at the slipping plate; z distance from microbial surfaces to the slipping plate that is generally on the order of 5 [26]; and a radius of bacteria. These interactions are evaluated at the equilibrium distance, y0 at a contact area of 2πRy0 , where R is the miAB crobial hydrodynamic radius. GLW 132 and G132 are usually negative, which contribute attractions between bacteria and porous media. GEL 132 is usually positive because both bacteria and porous media are commonly negatively charged. If

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GTOT 132 is negative, attractive forces play a significant role and microbial attachment occurs when bacteria pass through porous media. If GTOT 132 is positive, repulsive forces are predominant, which result in microbial dispersion and passing through. 3.3. Microbial transport Microbial transport can be described using the DeepBed Filtration Model and the Convection–Dispersion Model [20]. The Deep-Bed Filtration Model describes the microbial deposition and the Convection–Dispersion Model describes microbial movement and spreading during transport in porous media. Deposition coefficient and retardation factor, which describe irreversible adsorption (i.e., deposition) and reversible adsorption (i.e., retardation), are the key parameters in these two models. Deposition coefficient and retardation factor are related to interaction free energies between bacteria and porous media at different distances. Total interaction free energies between microorganisms and porous media at the closest and secondary approach are usually found to be negative, i.e., attractive; while in between are positive, i.e., repulsive if both microorganisms and porous media are negatively charged. Microbial deposition on a clean medium particle during transport is achieved in five steps: (1) Due to hydrodynamic dispersion or molecular diffusion, microorganisms approach the medium particle within the range of the secondary approach and the onset of attractive van der Waals interactions. It should be noted that secondary approach could either be a secondary minimum value or a secondary maximum value. (2) Van der Waals interactions balance hydrodynamic dispersion or molecular diffusion and microorganisms are adsorbed to the medium particle (initial adsorption). (3) Surface shear forces break the balance and result in desorption [1]. (4) Microorganisms having enough energy overcome the repulsive electrostatic interactions and get closer to the medium surface. (5) Microorganisms are dragged onto the medium surface to reach the closest approach due to dramatic increase of attractive Lewis acid–base interactions with distance decreasing, which results in the final deposition. Chen and Strevett [6] revealed that deposition coefficient was related to GTOT 132 , total interaction free energies at the closest approach. At stationary state, B. subtilis had −18 J) on silica gel a lower GTOT 132 value (−11.88 × 10 than E. coli (−6.71 × 10−18 J) and P. fluorescens (−3.91 × 10−18 J), which corresponded to a higher deposition coefficient (8.19 hr−1 ) than that of E. coli (−3.87 hr−1 ) and P. fluorescens (1.44 hr−1 ). Chen and Strevett [7] demonstrated that the deposition coefficient, a reflection of final deposition, is thus a function of total interaction free ener-

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gies at the closest approach where Lewis acid–base interactions dominate. In other words, upon approach towards a soil grain, Lewis acid–base interactions can balance electrostatic interactions (at a distance farther away from the closest approach). Therefore, the collision efficiency, which is controlled by bacterial cell-sediment/soil interactions and by the amount of previously attached bacteria, and thus the deposition coefficient should be a function of free energy of Lewis acid–base interaction at the closest approach. Retardation factor, a reflection of initial adsorption is a function of total interaction free energy values at the secondary approach where van der Waals interactions dominate. Chen and Strevett [7] showed that the retardation factor is an indicator of the “lag” of microbial transport in the porous media. By definition, it is a function of the distribution coefficient of microorganisms between aqueous and solid phases, i.e., R = ρb (1 − θ )Kp /θ , where ρb is the sediment bulk density (g/m3); θ porosity (m3/m3 ); and Kp linear equilibrium distribution coefficient of microorganisms between aqueous and solid phases (m3/g). According to van Oss [26], the distribution coefficient can be related to total interaction free energies at the secondary approach. The free energy of van der Waals interactions is the actual forcing function; thus   GLW (1 − θ ) 132 (second) = −φ ln ρb Kp , (11) kT θ where k the Boltzmann constant (1.38048 × 10−23 J/K); T absolute temperature (K); and φ correction factor [7]. Chen and Strevett [7] studied column break through curves of three different bacteria (columns were packed with the same media) and observed that the bacteria retarded in the order of their corresponding van der Waals interaction free energy values. 3.4. Biofilm development Biofilm formation is owing to interactions of deposited bacterial cells with suspended bacterial cells in the solution [25]. When suspended bacterial cells get close to deposited bacterial cells within the range of secondary approach, van der Waals interactions (attractive) begin become a contributing interaction and balance hydrodynamic dispersion or molecular diffusion. At this distance, van der Waals interactions dominate over Lewis acid–base and electrostatic interactions as Lewis acid–base interactions are a shortrange force and electrostatic interactions are weak. Due to the fact that GTOT 131 at the secondary approach where reversible adsorption occurs is one order of magnitude smaller than GTOT 132 (negatively greater), microorganisms have a more favorable adsorption tendency to deposited cells than porous media and thus biofilm is developed. As this adsorption occurs at the secondary approach, it is not thermodynamically stable [22]. When desorption occurs, the desorbed microorganisms cannot reach the closest approach to attach to the media as the majority of available spaces are occupied by deposited cells. In addition, desorbed bacteria are

also subject to repulsive interactions from deposited bacterial cells at the closest approach. As such, desorbed bacteria are usually washed away by hydrodynamic forces if not attached to deposited bacterial cells somewhere else. This explains the mechanism by which a biofilm can be removed by hydrodynamic forces [21].

4. Concluding remarks The application of natural attenuation of organic contaminants or in in situ bioremediation is severely limited by the understanding of microbial migration in the subsurface. Though discovery of viable populations of microorganisms in the subsurface at unexpected locations has been one of the major findings at the end of this century, microbial migration is still not clearly understood [4]. Biological, chemical, and hydrologic factors all impact microbial transport in the subsurface. To date, much work has been done in describing how physical and chemical variations in the subsurface result in changes in microbial migration, and yet, further insights into the subsurface as a habitat for microorganisms requires the understanding of microbial and medium interactions. Traditional and extended DLVO forces, including van der Waals, Lewis acid–base and electrostatic forces have been used in quantifying microbe–microbe and microbe– surface interactions and models that can be used for the calculation of these interactions based on independently determined microbial and medium surface thermodynamics have been developed. Because of the variable nature of microbial cell surfaces with the microorganisms’ physiological state and macro-nutrient ratio, the surface thermodynamics are highly dependent on the cell’s growth state and such dependence requires quantification. Finally, hydrodynamic forces may be significant in the kinetic process when microbes approach porous media, though they are usually ignored at the final adsorption stage. Microbial thermodynamic theory has developed a rational forecasting framework for describing microbial fate in saturated medium systems. It will be beneficial to apply the fundamental principles of this theory to facilitate studies of subsurface microbial processes and to develop engineering strategies to design and operate practical groundwater technologies such as active bioremediation and other new techniques and strategies. Microbial surface thermodynamics has potentials to work as a bridge to connect micro-scale structures with macro-scale biological functions, though it has recently been derived from traditional and extended DLVO theory. With the help of microbial surface thermodynamic theory, microbial fate and transport in the subsurface can be predicted and controlled, which is of great interests for in situ bioremediation. With its easy measurements and important functions, microbial surface thermodynamics is becoming an important microbial physical and biological parameter.

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Acknowledgements The work was support in part by National Science Foundation through Grant BES-9733969 to the University of Oklahoma.

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