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Published online 31 May 2006
Published in J Environ Qual 35:1018-1025 (2006)
DOI: 10.2134/jeq2005.0224
© 2006 American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America
677 S. Segoe Rd., Madison, WI 53711 USA
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TECHNICAL REPORTS

Ground Water Quality

Comparison of Escherichia coli and Campylobacter jejuni Transport in Saturated Porous Media

Carl H. Bolstera,*, Sharon L. Walkerb and Kimberly L. Cooka

a USDA-ARS, 230 Bennett Lane, Bowling Green, KY 42104
b Department of Chemical and Environmental Engineering, University of California, Riverside, B355 Bourns Hall, Riverside, CA 92521

* Corresponding author (cbolster{at}ars.usda.gov)

Received for publication June 4, 2005.

   ABSTRACT
TOP
 NOTES
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Due to the difficulties in testing for specific pathogens, water samples are tested for the presence of nonpathogenic indicator organisms to determine whether a water supply has been contaminated by fecal material. An implicit assumption in this approach is that where pathogenic microorganisms are present fecal indicator organisms are present as well; yet surprisingly few studies have been conducted that directly compare the transport of indicator organisms with pathogenic organisms in ground water environments. In this study we compared the cell properties and transport of Escherichia coli, a commonly used indicator organism, and Campylobacter jejuni, an important enteropathogen commonly found in agricultural wastes, through saturated porous media. Differences in cell properties were determined by measuring cell geometry, hydrophobicity, and electrophoretic mobility. Transport differences were determined by conducting miscible displacement experiments in laboratory columns. Under the experimental conditions tested, C. jejuni was much more negatively charged and more hydrophobic than E. coli. In addition, C. jejuni cells were slightly longer, narrower, and less spherical than E. coli. The variations in cell properties, primarily surface charge, resulted in significant differences in transport between these two microorganisms, with the transport of C. jejuni exceeding that of E. coli when conditions favored low attachment rates, thus calling into question the usefulness of using E. coli as an indicator organism for this important pathogen.


   INTRODUCTION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
INFILTRATION of fecal material into the subsurface can result in contamination of soils and ground water by enteropathogenic microorganisms such as bacteria, viruses, and protozoa. Recent studies have shown that fecal contamination has been detected in nearly half of all the drinking water wells tested in the United States (Macler and Merkle, 2002). Some of the most cited sources of fecal contamination of ground water supplies are agricultural activities (USEPA, 1994) including use of manure for crop fertilization (Gagliardi and Karns, 2002), pasturing of livestock, animal feeding operations (Gerba and Smith, 2005), wash water from animal housing (Mawdsley et al., 1995), and leaky manure storage lagoons (USEPA, 1993). Several recent studies have found a strong link between human illness and land application of agricultural waste (Clark et al., 2003; Stanley and Jones, 2003; Valcour et al., 2002).

Although the presence of pathogenic microorganisms in drinking water supplies is a threat to public health, rarely are concentrations of these particular organisms measured. Rather, water samples are tested for the presence of nonpathogenic microorganisms commonly found in fecal material, referred to as indicator organisms. The presence of these indicator organisms does not mean necessarily that the water is unsafe for consumption; rather it indicates that the water has likely been contaminated by fecal material and thus potentially contains pathogens (Leclerc and Mosel, 2001). Commonly used indicator organisms include total coliforms, fecal coliforms, E. coli, and enterococci. To be effective, an indicator organism must occur in a sample when fecal pathogens are present, but in far greater numbers than the pathogen(s) of interest. Additionally, the indicator should respond to natural environmental conditions and water treatment processes in a manner similar to the pathogen(s) of concern. In ground water environments this requires that the indicator organism have similar or greater transport and survival characteristics than the pathogenic microorganisms of concern to ensure detectable quantities of the indicator organism in fecally contaminated waters.

Given the diversity of potentially pathogenic microorganisms found in animal manures, it is reasonable to expect diversity in the cell surface properties of these microorganisms. For instance, Lytle et al. (2002) have shown that several important microorganisms to public health such as E. coli O157:H7, Cryptosporidium parvum oocysts, and Vibrio cholorae all have significantly different charges (zeta potential) on their outer surface. Given that the movement of bacteria through the subsurface is governed, in part, by cell properties such as surface charge (Busscher et al., 1984; van Loosdrecht et al., 1987a), cell geometry (Fontes et al., 1991; Gannon et al., 1991; Weiss et al., 1995), and hydrophobicity (Stenstrom, 1989; van Loosdrecht et al., 1987a, 1990), it is likely that there exists a range of transport characteristics for the variety of microorganisms commonly found in fecal material. Therefore, it seems unlikely that a single organism, for example E. coli, can adequately serve as a surrogate for the subsurface transport of all pathogenic microorganisms. Indeed, the effectiveness of E. coli as an indicator of enteric virus transport in ground water has already been questioned (Borchardt et al., 2003; Meschke and Sobsey, 2003).

The objective of our study was to compare key cell properties and transport characteristics of C. jejuni, an important pathogen commonly found in agricultural wastes (Wesley et al., 2000) and a leading cause of gastroenteritis in the United States (Allos, 2001), and E. coli, a commonly used indicator of fecal contamination. Although Campylobacter spp. has been detected in ground water samples (Stanley et al., 1998), we are unaware of any studies that have looked specifically at the transport of C. jejuni in porous media and compared its transport to that of an indicator organism. The results of our research will provide much needed information for determining whether E. coli is a useful indicator for assessing potential ground water contamination by C. jejuni.


   MATERIALS AND METHODS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Bacteria Preparation
Cultures of E. coli O157:H7 strain L-2 were maintained at –80°C in Luria broth (LB) with 50 µg ampicillin mL–1 and 15% glycerol. The L-2 strain is derived from E. coli O157:H7 strain B6-914 (ATCC 43888), which does not produce Shiga-like toxins I or II and does not possess the genes for these toxins (Siragusa et al., 1999). One week before the experiments the culture was resuscitated by two successive passages on LB agar with 50 µg ampicillin mL–1 and incubated for 24 h at 37°C. One isolated colony from a fresh LB agar plate was inoculated into 50 mL of LB broth and the culture was incubated at 37°C for 24 h to achieve stationary phase. Cultures of C. jejuni (ATCC 49943) were maintained on Campylobacter Selective Agar (CSA) prepared as recommended by the manufacturer and transferred weekly. Briefly, campylobacter agar base (Oxoid, Basingstoke, England) was autoclaved for 15 min and cooled, and modified Preston campylobacter selective supplement (Oxoid) and 5% lysed horse blood (Hemostat Labs, Dixon, CA) were added. Inoculated plates were incubated at 37°C for 48 h under microaerophilic conditions using anaerobic gas jars equipped with the CampyPak Plus microaerophilic system (BBL, Cockeysville, MD). Before the experiments, one C. jejuni colony from a CSA plate was used to inoculate 500 mL of tryptic soy agar (BD, Sparks, MD). To achieve stationary phase C. jejuni cultures were incubated at 37°C for 48 h in anaerobic gas jars under microaerophilic conditions. Bacterial cells were pelleted and washed three times in KCl solution by centrifugation at 9000 x g for 10 min and resuspended in the appropriate KCl solution for approximately 18 h to ensure that the bacteria were in a resting state before conducting column experiments and characterization of surface properties.

Cell culturability was evaluated following 18-h incubation in KCl solution. Culturability of E. coli was determined by plating onto LB agar with no antibiotic. Plates were incubated at 37°C for 24 h. Final culturable cell numbers for E. coli were 1.0 x 108 cells mL–1. Culturability of C. jejuni was determined by plating onto TSA with 5% sheep's blood (Hemostat Labs). Plates were incubated microaerophilically at 37°C for 48 h. Final culturable cell numbers for C. jejuni were 2.9 x 108 cells mL–1.

Cell Properties
Hydrophobicity was measured using the microbial adhesion to hydrocarbons (MATH) assay (Rosenberg et al., 1980). Four milliliters of a bacterial solution containing approximately 108 cells mL–1 was added to 13-mL test tubes containing 1 mL n-dodecane (Fisher Scientific, Hampton, NH). The test tubes were vortexed for 2 min and allowed to stand for 45 min to allow the complete separation of the hydrocarbon and water phases. Afterward, 1 mL of the water phase was removed from each test tube and the bacterial concentration in the aqueous phase was measured. Concentrations of E. coli and C. jejuni were determined by measuring the optical density of the samples at a wavelength of 546 nm with a UV–visible spectrophotometer (BioSpec-mini; Shimadzu, Kyoto, Japan). Hydrophobicity was determined by:

Formula 1[1]
where C0 is the initial concentration (cells mL–1) and C45 is the concentration in the aqueous phase following mixing and a 45-min separation period (cells mL–1).

Electrophoretic mobility of the bacterial cells was determined using a ZetaPALS analyzer (Brookhaven Instruments, Holtsville, NY). The bacteria were prepared by the same methods as used for transport experiments and diluted to a final concentration between 105 and 106 cells mL–1 in a 10 mM KCl electrolyte solution. Electrophoretic mobility measurements were conducted at 25°C and were repeated five times for each microorganism.

Average cell diameter, cell width, and cell shape were measured using Image Pro Plus software (Media Cybernetics, 2004). Cell shape, defined as the ratio between cell width and length, was used as a way to assess each cell's departure from sphericity. The closer the shape value is to 1 the more spherical it is. Three hundred cells were measured for each microorganism.

Sand Preparation
Quartz sand (Unimin, New Caanan, CT) was sifted through 350- and 250-µm sieves (U.S.A. Standard Testing Sieves; ATM, New Berlin, WI). The fraction of sand between 250 and 350 µm in size was collected and utilized for the experiments. To remove metal oxide coatings and organic matter associated with the quartz, the sand was boiled in a 2-L flask containing 1 M hydrochloric acid (Fisher Scientific) for 2 h and then rinsed with deionized water until the rinse water pH was equal to the pH of the deionized water. The sand was then dried overnight at 105°C, re-rinsed in deionized water the following day, and dried again overnight.

Portions of the acid-washed sand were coated with metal oxides by the method of Bolster et al. (2001). Sand was placed in a concentrated solution containing either FeCl3 or AlCl3 (Fisher Scientific). The solution pH was adjusted so that it exceeded 9 by the addition of 10 M NaOH (Fisher Scientific). Sand was equilibrated in the solution for 36 to 48 h. One molar NaOH was added to the solution when the pH dropped below 9. Following equilibration of the sand with the solution, the sand was rinsed in deionized water until the water was clear and baked again at 105°C for 24 h. The final step of rinsing and drying was repeated. Before column experiments, the sand was sterilized by autoclaving at 121°C and 103 kPa (15 psi) for 20 min.

Column Preparation
Columns were wet packed by slowly pouring autoclaved sand into 2.5-cm-diameter Chromaflex Chromatography Columns (Kontes Glass Co., Vineland, NJ) filled with electrolyte solution (10 or 1 mM KCl; Fisher Scientific). Columns were repeatedly tapped during the addition of sand to prevent any entrapment of air bubbles within pore spaces. Column lengths ranged from 9.8 to 10.2 cm. After packing was completed, columns were operated in a downflow direction using a peristaltic pump, and approximately 10 pore volumes (where a pore volume represents the volume of water contained within the sand pack) of the appropriate electrolyte solution were passed through each column to equilibrate the sand pack. Darcian velocity was approximately 3 m d–1. All column experiments were run in duplicate.

A 0.5-pore-volume pulse of either E. coli or C. jejuni at a concentration of approximately 108 cells mL–1 was injected at the top of each column followed by bacteria-free electrolyte solution. Effluent was collected in bulk (i.e., effluent was collected for each column as a single sample) for approximately 3.5 pore volumes to ensure the main pulse of bacteria had exited the column. Enumeration of effluent after the 3.5-pore-volume collection time yielded negligible numbers of bacteria indicating minimal tailing. Column influent and effluent was enumerated for total cell concentrations by staining the appropriate dilutions with a 0.1% solution of Acridine Orange (AO) (Sigma, St. Louis, MO) and filtering onto 0.22-µm black polycarbonate filters, using a modification of the AO direct count method (Hobbie et al., 1977). Stained cells were observed using a BX-41 microscope (Olympus, Melville, NY) equipped with the appropriate lamp and filter set (100-W mercury lamp, a 460–490-nm excitation filter, and a 590-nm cut-off filter). A minimum of 10 fields were counted to ensure the enumeration of a statistically significant number of cells.

Data Analysis
Assuming low surface coverage and negligible entrainment the one-dimensional transport of bacteria through laboratory columns can be described by (Harvey and Garabedian, 1991; Hornberger et al., 1992):

Formula 2[2]
where c is the aqueous concentration of bacteria (cells mL–1), x is the distance from the column inlet (cm), D is the hydrodynamic dispersion coefficient (cm2 h–1), v is the interstitial pore water velocity (cm h–1), and k is the bacterial attachment rate (h–1) which controls the rate at which bacteria are removed from the aqueous phase. High rates of attachment result in reduced transport in ground water environments.

Integrating the analytical solution to Eq. [2] over time yields an expression for the relative recovery of bacteria eluted at the column outlet (Bolster et al., 1998; Harvey and Garabedian, 1991). The bacterial attachment (or removal) rate, k, can then be calculated from the relative recovery by (Bolster et al., 1998):

Formula 3[3]
where Rr is the relative recovery defined as the number of bacteria recovered in the column effluent normalized by the total number of bacteria introduced into the system, L is column length, and Pe is the Peclet number (dimensionless), which represents the ratio of advective to dispersive forces. We estimated the Peclet number in our columns to be 110 based on bromide tracer tests conducted on larger diameter columns that contained the same sand and were of the same length as the columns used in this study.

The attachment rate, k, is a function of the physical, chemical, and biological factors which affect a cell's ability to collide with, and remain attached to, a collector surface; in our case a quartz sand grain. Based on theoretical considerations we can define the attachment rate as (Tien et al., 1979):

Formula 4[4]
where dc is the collector (sand grain) diameter (0.3 mm); {theta} is porosity (ranging from 0.36 to 0.39 in our study); {eta}0 is the single-collector contact efficiency, which is a measure of the physical mechanisms that bring a bacterial cell to the surface of the grain; and {alpha} is the attachment or "sticking" efficiency, which is a measure of the successful attachment of bacterial cells to the sediment surface (Yao et al., 1971). Although equations exist for calculating the single-collector contact efficiency, {eta}0, the derivation of these equations is based on spherical particles (Logan et al., 1995; Rajagopalan and Tien, 1976; Tufenkji and Elimelech, 2004). Because our bacteria are not spherical in shape and deviations from sphericity have been observed to affect bacterial transport in porous media (Weiss et al., 1995), we do not follow the common approach of calculating {alpha} from estimates of {eta}0. Rather, we calculated the combination of {eta}0 and {alpha}, hereafter referred to as the removal efficiency (Tufenkji and Elimelech, 2004), because we believe that the biological differences between these two microorganisms will affect both the single-collector efficiency, {eta}0, and the sticking efficiency, {alpha}. Combining and rearranging Eq. [3] and [4] allows us to calculate the removal efficiency ({eta}0{alpha}) from the relative recovery (Rr) in the column effluent by:

Formula 5[5]

Because our experiments were all conducted under similar physicochemical conditions (e.g., flow rate, porosity, ionic strength, grain size) we assume that any observed differences in our removal efficiency can be attributed to differences in cell properties such as size and shape, surface charge, and hydrophobicity.

Hydrophobicity, surface charge, relative recovery (Rr), and removal efficiency ({eta}0{alpha}) values were statistically analyzed using one-sided t tests assuming equal variances whereas differences in cell geometry (length, width, and shape) were analyzed using one-sided t tests assuming unequal variances. All statistical analyses were performed using SAS Version 9.1 (SAS Institute, 2003).


   RESULTS AND DISCUSSION
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
CONCLUSIONS
 REFERENCES
 
Cell Properties
The electrophoretic mobility of the two bacteria tested in our study varied markedly, with C. jejuni having a significantly (p < 0.001) greater negative charge than the E. coli strain used in our study (Table 1). We measured average cell mobilities of –2.7 µm cm V–1 s–1 for C. jejuni and –0.19 µm cm V–1 s–1 for E. coli O157:H7 suspended in 10 mM KCl. Our measurements are consistent with other reported values for E. coli strains belonging to the serogroup O157, including reported mobility values ranging from –0.22 to –0.46 µm cm V–1 s–1 for seven strains of O157:H7 (Lytle et al., 1999) and –0.31 µm cm V–1 s–1 for another O157:H7 strain (Lytle et al., 2002). We are unaware of any reported zeta potential or electrophoretic mobility measurements for C. jejuni but our results are in agreement with those of Walan and Kihlstrom (1988) who reported a highly negative surface charge based on ion-exchange chromatography measurements for all C. jejuni strains tested in their study.


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  		Table 1. Average values and standard deviations (shown in parentheses) of measured biological properties of C. jejuni and E. coli O157:H7.

 
In addition to surface charge, hydrophobicity differed significantly (p < 0.001) between the two microorganisms. On average 43% of the C. jejuni cells partitioned in the hydrocarbon, whereas only 26% of the E. coli cells did the same (Table 1). Our results indicate that the more strongly charged C. jejuni cells are significantly more hydrophobic than the less negatively charged E. coli cells. Our observation that hydrophobicity and mobility are positively correlated is not uncommon (McCaulou et al., 1994; van Loosdrecht et al., 1987a). It is worth noting, however, that the microbial adhesion to hydrocarbons (MATH) assay is an indirect measure of hydrophobicity and it likely measures a combination of hydrophobic and electrostatic interactions (Geertsema-Doornbusch et al., 1993), thus our observed correlation may not hold for other organisms or test conditions.

Size and shape were also observed to vary between the two microorganisms (Table 1). Consistent with other studies, we observed E. coli to be rod-shaped and C. jejuni to have two distinct morphologies: one being a coccoid shape and the other being a slender, spirally curved rod with a characteristic "seagull-wing" shape (Smibert, 1978). The two distinct cell morphologies for C. jejuni have been hypothesized to be a result of differences in cell viability (Boucher et al., 1994). On average, C. jejuni was slightly longer (p = 0.51) and significantly narrower (p < 0.001) than E. coli with average lengths of 2.2 and 2.1 µm and average widths of 1.0 and 1.2 µm for C. jejuni and E. coli, respectively. Although the difference appears minor, C. jejuni was, on average, significantly (p < 0.01) less spherical than E. coli with average cell shapes of 0.53 for C. jejuni and 0.57 for E. coli. In looking at the size distribution, C. jejuni had a noticeably greater range in length and width than E. coli (data not shown) with the smaller C. jejuni cells representing the coccoid morphology. No attempt was made to compare cell size, shape, and distribution between the column influent and effluent.

Transport Experiments
The observed differences in cell properties between these two microorganisms resulted in significant differences (p < 0.05) in relative recovery and removal efficiency for all experimental treatments (Fig. 1 and 2). In columns packed with metal-oxide-coated sands, removal efficiencies were greater by 38 to 52% for C. jejuni as compared to E. coli (Fig. 1). Due to the nonlinear relationship between bacterial recovery and attachment rates, however, relative recovery of E. coli exceeded that of C. jejuni by over an order of magnitude, although recovery for both microorganisms was quite low (Fig. 2). In contrast, in both experiments with uncoated quartz sand, removal efficiencies for E. coli exceeded that for C. jejuni. Thus, there was greater transport of the pathogenic C. jejuni as compared to the indicator organism E. coli (Fig. 1 and 2). Given that C. jejuni and E. coli differed in size, shape, size distribution, surface charge, and hydrophobicity, all of which have been shown to affect bacterial attachment to surfaces (Gannon et al., 1991; Stenstrom, 1989; van Loosdrecht et al., 1987a; Weiss et al., 1995), it is difficult to determine which of these factors was most important in controlling these differences in transport. We can, however, make some inferences based on our results.


Figure 1
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  		Fig. 1. Removal efficiency for E. coli and C. jejuni in replicate 10-cm columns under the following conditions: uncoated quartz sand with 10 mM KCl, uncoated quartz sand with 1 mM KCl, Fe-coated sand with 10 mM KCl, and Al-coated sand with 10 mM KCl. Error bars represent one standard deviation of the mean.

 

Figure 2
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  		Fig. 2. Relative recovery of E. coli and C. jejuni from replicate 10-cm columns under the following conditions: uncoated quartz sand with 10 mM KCl, uncoated quartz sand with 1 mM KCl, Fe-coated sand with 10 mM KCl, and Al-coated sand with 10 mM KCl. Error bars represent one standard deviation of the mean.

 
The recovery of bacteria in the column effluent was most strongly affected by surface coatings on the quartz sand grains. For both microorganisms, the relative recovery greatly decreased for the metal-oxide-coated sands as compared to the uncoated sand (Fig. 2); however, the effect was more pronounced for C. jejuni. The average relative recovery for C. jejuni decreased from 0.35 for the uncoated sand (10 mM KCl) to 0.00034 and 0.0013 for the Fe- and Al-coated sand, respectively. For E. coli, the average relative recovery decreased from 0.11 in uncoated sand (10 mM KCl) to 0.0033 and 0.012 for the Fe- and Al-coated sand, respectively (Fig. 2). Observed reductions in relative recovery for oxide-coated sands were statistically significant at the 0.05 probability level for both C. jejuni and E. coli.

The presence of the metal-oxide coatings on the quartz sand grains resulted in an electrostatic attraction between the positively charged metal-oxide coating and the negatively charged bacteria leading to increased attachment rates; this observation is in agreement with other published studies (Bolster et al., 2001; Johnson and Logan, 1996; Mills et al., 1994; Scholl and Harvey, 1992; Scholl et al., 1990). This increase in attachment rates, leading to a decrease in bacterial transport, is evident when comparing the removal efficiency ({eta}0{alpha}) between coated and uncoated sands (Fig. 1). For both microorganisms, the removal efficiency greatly increased (p < 0.05) for the metal-oxide-coated sands as compared to the uncoated sand but the increase in removal efficiency was greatest for C. jejuni. This observation is not surprising as the C. jejuni cells were considerably more negatively charged, therefore, the presence of positively charged metal-oxide coatings would be expected to have a more pronounced influence on deposition for this organism.

Changing the ionic strength of the carrier fluid was also identified as playing a role in the extent of bacterial attachment to the uncoated quartz sand. Decreasing ionic strength of the carrier solution from 10 to 1 mM resulted in slight increases in relative recovery from columns containing uncoated sands for both types of bacteria (Fig. 2), although the increase for E. coli was not statistically significant (p = 0.28). Decreasing ionic strength resulted in a statistically significant (p = 0.049) decrease in removal efficiency (0.0033 to 0.0021) for C. jejuni but for E. coli the influence of lowered ionic strength on removal efficiency was insignificant (p = 0.22).

The impact of changing ionic strength on attachment behavior can be explained by the Derjaguin–Landau–Verwey–Overbeek (DLVO) theory of colloidal stability (Derjaguin and Landau, 1941; Verwey and Overbeek, 1948). According to this theory, bacterial deposition to like-charged surfaces is governed by a combination of electrostatic double layer repulsion (Hogg et al., 1966) and attractive van der Waals forces (Gregory, 1981). Because bacteria and uncoated quartz sand are both negatively charged particles, the electrical double layer of counter ions around their surfaces results in electrostatic repulsion. As ionic strength is lowered, the thickness of this electrical double layer increases as does the magnitude of electrostatic double layer repulsive forces. Depending on the thickness of the double layer, bacterial cells may be prohibited from approaching the surface at a sufficiently close distance that would allow for attractive van der Waals forces to overcome electrostatic repulsion. Thus, decreasing ionic strength is expected to decrease bacterial attachment to like-charged surfaces and has been confirmed in numerous studies (Fontes et al., 1991; Martin et al., 1991; Mills et al., 1994; Scholl et al., 1990). Given the stronger negative charge of C. jejuni, it is not surprising that changes in ionic strength would have a more pronounced influence on deposition of this organism as compared to the near neutrally charged E. coli.

We can also use DLVO theory to better understand the observed differences in attachment rates to the uncoated quartz sand for E. coli and C. jejuni. Using DLVO theory to calculate the total interaction energy between our bacterial cells and a quartz surface indicates that at an ionic strength of 10 mM KCl, repulsive electrostatic forces are suppressed and no energy barrier exists for E. coli attachment to negatively charged quartz sand. This suggests that irreversible attachment in the primary minimum is occurring at this ionic strength (Fig. 3). On the other hand, C. jenuni experiences a substantial repulsive energy barrier to deposition at this ionic strength due to the strong negative charge of this organism making deposition in the primary minimum unlikely; however, a shallow energy well, or secondary minimum, exists at a separation distance of approximately 17 nm between the bacterium and quartz surface (Fig. 3). This energy minimum is approximately 2.7 kT, which is sufficiently deep to allow a bacterium to be retained (Hahn and O'Melia, 2004). This provides an explanation for why experiments with uncoated quartz sand resulted in some removal of C. jejuni even though considerable repulsion was expected, as these cells likely were captured in the secondary energy minimum (Redman et al., 2004).


Figure 3
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  		Fig. 3. Total interaction energy (Vtotal) as calculated with Derjaguin–Landau–Verwey–Overbeek (DLVO) theory as a combination of electrostatic double layer (VEDL) and van der Waals (VVDW) forces between E. coli and C. jejuni and the quartz sand surface at 10 mM KCl. Calculations assume sphere–plate interactions (Gregory, 1981; Hogg et al., 1966) and a Hamaker constant of 6.5 x 10–21 J (Redman et al., 2004), and utilized a zeta potential value for quartz previously reported (Walker et al., 2002).

 
The effect of surface coatings and ionic strength on attachment rates for our two organisms demonstrates that surface charge is likely an important factor causing the observed differences in transport between E. coli and C. jejuni. To fully evaluate the relative transport of E. coli and C. jejuni, however, we must account for other surface properties and the potential coupled influence of these properties on cell transport and deposition. In columns containing metal-oxide-coated quartz, when greater hydrophobicity and more negative surface charge would suggest greater deposition for C. jejuni, removal efficiencies were greater for C. jejuni than for E. coli (Fig. 1). In this case, the combined hydrophobic and electrostatic forces resulted in anticipated trends. In experiments utilizing negatively charged uncoated quartz sand, removal efficiencies for the more hydrophilic and near neutrally charged E. coli exceeded that of C. jejuni. If hydrophobicity were the driving force in our experiments we would expect greater attachment of the more hydrophobic microorganism, C. jejuni, to the uncoated quartz sand than the hydrophilic organism, E. coli, yet we observed the opposite (Stenstrom, 1989; van Loosdrecht et al., 1987b). This suggests that electrostatic repulsion between uncoated quartz sand and C. jejuni is substantial enough to overcome the hydrophobic interactions that might otherwise control the extent of deposition. Additionally, the near neutrally charged, more hydrophilic E. coli cells deposited on the like-charged quartz, indicating that hydrophobic forces were surpassed by the forces incorporated in traditional DLVO theory. Our findings are similar to those reported by McCaulou et al. (1994) who also observed greater recovery of a hydrophilic bacterium with a low negative charge compared to a hydrophobic bacterium with a high negative surface charge in columns containing Fe-coated sands but observed greater recovery of the hydrophobic, highly negatively charged bacterium in columns containing uncoated quartz sand.

In addition to surface properties, cell geometry has been shown to be a major factor affecting bacterial transport. Theoretical considerations indicate cell size should be important in attachment rates (Harvey and Garabedian, 1991; Yao et al., 1971) and this has been observed in laboratory studies. Gannon et al. (1991) observed the transport of a variety of bacterial strains through a loam soil to be correlated with cell size rather than with hydrophobicity or surface charge. Fontes et al. (1991) also observed differences in bacterial transport due to differences in cell size. Cell shape has also been shown to affect bacterial transport with more spherical cells being favored for transport (Weiss et al., 1995). If cell geometry (size, shape, and distribution) was the primary factor controlling bacterial transport in our study we would expect that the disparity in removal efficiency between the two microorganisms would remain relatively unchanged between experimental treatments. Instead, we observed that the removal efficiency for each microorganism responded differently to changes in physicochemical conditions such as surface coatings and ionic strength. Thus, it is unlikely that the measured differences in cell size and shape between our two microorganisms were substantial enough to have a noticeable impact on attachment rates.

When viewed in their entirety, our results strongly suggest that surface charge was the primary factor determining the extent of deposition and transport of these two microorganisms. This conclusion is supported by the following observations: (i) in column experiments containing positively charged metal-oxide-coated sands, attachment was greater for the more negatively charged C. jejuni; (ii) in columns packed with negatively charged uncoated quartz sand, greater attachment was observed for the near neutrally charged E. coli, due to less electrostatic repulsion as compared to the more negatively charged C. jejuni; and (iii) the sensitivity of the removal efficiency to changes in ionic strength with the negatively charged uncoated sand was greater for the more negatively charged C. jejuni. This is not to say that differences in cell geometry and hydrophobicity do not play a role in transport. Rather, our results indicate that for the experimental conditions used in this study these factors played a secondary role, if any, and are consistent with the findings of others who have reported that bacterial attachment to hydrophilic surfaces is primarily controlled by electrostatic interactions (Gross and Logan, 1995; McCaulou et al., 1994; van Loosdrecht et al., 1990).


   CONCLUSIONS
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
REFERENCES
 
Although the ability of Campylobacter spp. to move through ground water environments has been inferred from ground water sampling studies (Stanley et al., 1998), we are unaware of any studies that have looked specifically at the transport of C. jejuni through porous media. Our study suggests that the transport of C. jejuni may exceed that of the commonly used bacterial indicator, E. coli, under conditions where removal rates are expected to be low (e.g., when bacteria and collectors are similarly charged). The practical significance of this finding is that C. jejuni may be present in ground water samples in which E. coli is not detected. Admittedly, this study was developed with a simplified approach and does not address important factors such as physical, chemical, and biological heterogeneities (Bolster et al., 2000); limitations with colloid-filtration theory (Bradford et al., 2002); and recent observations that different strains of E. coli transport differently through porous media (Morrow et al., 2005). As such, the values for the removal efficiencies obtained in this study may be viewed as effective values representative for the conditions of this study. Nevertheless, our results are helpful in understanding the potential problems and limitations in using E. coli as a surrogate for the transport of C. jejuni and other pathogenic microorganisms in ground water environments. Indeed, these results bring into question the validity of using E. coli as an indicator organism for this important pathogen. Clearly, further study is needed to establish the correlation between the presence of C. jejuni and indicator organisms in environmental water samples, and to determine if the use of indicator organisms such as E. coli is a meaningful tool to assess potential ground water contamination by C. jejuni.


   ACKNOWLEDGMENTS
 
This research was part of USDA-ARS National Program 206: Manure and Byproduct Utilization. This manuscript was greatly improved by the thoughtful comments of Scott Bradford and three anonymous reviewers.


   NOTES
TOP
 NOTES
ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 
Mention of trade names or commercial products is solely for the description of experimental procedures and does not imply recommendation or endorsement by the U.S. Department of Agriculture.


   REFERENCES
TOP
 NOTES
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS AND DISCUSSION
 CONCLUSIONS
 REFERENCES
 





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