Journal of Contaminant Hydrology 92 (2007) 255 – 273
www.elsevier.com/locate/jconhyd

Bacteria transport and deposition under unsaturated
conditions: The role of the matrix grain size
and the bacteria surface protein
G. Gargiulo a,⁎, S. Bradford b , J. Šimůnek c , P. Ustohal a ,H. Vereecken a , E. Klumpp aaAgrosphere (ICG-IV), Institute of Chemistry and Dynamics of the Geosphere (ICG), Forschungszentrum,
Jülich GmbH D-52425, Jülich, Germanyb
USDA-ARS, George E. Brown, Jr. Salinity Laboratory, 450 W. Big Springs Road, Riverside,
CA 92507–4617, United Statesc
Department of Environmental Sciences, University of California, Riverside, CA 92521, United States
Received 28 April 2006; received in revised form 31 October 2006; accepted 3 January 2007
Available online 24 January 2007

Abstract
Unsaturated (80% water saturated) packed column experiments were conducted to investigate theinfluence of grain size distribution and bacteria surface macromolecules on bacteria (Rhodococcus
rhodochrous) transport and deposition mechanisms. Three sizes of silica sands were used in thesetransport experiments, and their median grain sizes were 607, 567, and 330 μm. The amount of retained
bacteria increased with decreasing sand size, and most of the deposited bacteria were found adjacent tothe column inlet. The deposition profiles were not consistent with predictions based on classical filtration
theory. The experimental data could be accurately characterized using a mathematical model that
accounted for first-order attachment, detachment, and time and depth-dependent straining processes.
Visual observations of the bacteria deposition as well as mathematical modelling indicated that straining
was the dominant mechanism of deposition in these sands (78–99.6% of the deposited bacteria), which
may have been enhanced due to the tendency of this bacterium to form aggregates. An additional
unsaturated experiment was conducted to better deduce the role of bacteria surface macromolecules on
attachment and straining processes. In this case, the bacteria surface was treated using a proteolitic
enzyme. This technique was assessed by examining the Fourier-transform infrared spectrum and hydrophobicity of untreated and enzyme treated cells. Both of these analytical procedures demonstrated that
this enzymatic treatment removed the surface proteins and/or associated macromolecules. Transport and⁎ Corresponding author.
E-mail address: grazgar@yahoo.it (G. Gargiulo).
0169-7722/$ - see front matter © 2007 Elsevier B.V. All rights reserved.
doi:10.1016/j.jconhyd.2007.01.009

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modelling studies conducted with the enzyme treated bacteria, revealed a decrease in attachment, but thatstraining was not significantly affected by this treatment.
© 2007 Elsevier B.V. All rights reserved.
Keywords: Bacteria transport; Classical filtration theory; Unsaturated flow; Rhodococcus rhodochrous

1. Introduction
Microbial contamination of groundwater is a serious problem that can result in large outbreaksof waterborne disease (Fontes et al., 1991; Scandura and Sobsey, 1997; Ginn et al., 2002;
Reynolds et al., 2004). Most waterborne pathogens (viruses, bacteria, and protozoan parasites) areof faecal origin, and come from either human and/or animal wastes. These solid wastes (biosolids
and manure) and contaminated effluents from wastewater treatment plants and concentrated
animal feeding operations are frequently land applied as a means of treatment and/or disposal. An
ability to accurately predict the transport and fate of pathogenic microorganisms in unsaturated
soil environments is therefore needed to protect surface and groundwater resources from contamination. On the other hand, many bacteria can beneficially degrade or immobilize environmental contaminants (Grasso et al., 1996; Schaefer et al., 1998; Bolster et al., 2001; Ginn et al.,2002). Bioremediation and/or bio-augmentation strategies to clean up recalcitrant chemicals insubsurface environments could be greatly enhanced by efficient delivery of specialized bacteria totargeted locations in the subsurface.
In comparison to saturated systems, relatively few studies have examined the transport anddeposition behaviour of bacteria under unsaturated condition (Wan et al., 1994; Powelson andMills, 1996; Schafer et al., 1998; Jewett et al., 1998; Gargiulo et al., submitted for publication).
Mechanisms of microbe deposition in unsaturated porous media include attachment, interfacial
attachment, straining, and film straining. Attachment and interfacial attachment refers to deposition on the solid–water and air–water interface, respectively. Conversely, microbe deposition bystraining and film straining occurs due to physical restrictions of the pore geometry and the water
film thickness, respectively. Both attachment and straining processes are expected to be functionsof colloid–colloid, colloid–solvent, colloid–interface interactions and system hydrodynamics
that will influence mass transfer and fixation at locations of deposition. It should be noted,
however, that the bulk of the research on colloid transport have focused on attachment, and havenot considered the potential influence of pore geometry on deposition.
In contrast to abiotic colloids, bacteria surfaces have a more complicated chemical structure. The bacteria surface layers (S-layers) are the outer components of the cell wall andconsist primarily of proteins. The rate and the extent of bacteria attachment to soil surfaces andair–water interfaces are governed by molecular-scale interactions between the bacteria outerlayer and a particular interface. Since the surface macromolecular structure is not well known,these interactions are poorly understood, in particular the role of cell surface polymers(Caccavo, 1999). These macromolecules can inhibit or promote attachment in accordance with
their affinities for the interface and depending on the aqueous solution chemistry (Salerno
et al., 2004).
Classical filtration theory (CFT) predicts that the deposition profile of attached colloids will
decrease exponentially with increasing transport depth. Recent experimental studies, however,
have reported that CFT is frequently inadequate to describe colloid and bacteria deposition
profiles when a energy barrier exists (unfavourable deposition conditions), and for larger sizedG. Gargiulo et al. / Journal of Contaminant Hydrology 92 (2007) 255–273

257

colloids and finer textured media (DeFlaun et al., 1997; Bolster et al., 2001; Bradford et al.,2002, 2003; Tufenkji et al., 2004; Tufenkji and Elimelech, 2004; Johnson et al., 2005;
Bradford and Bettahar, 2005, 2006; Gargiulo et al., submitted for publication). For
unfavourable conditions, the deposition profile has frequently been reported to follow a
hyper-exponential (power law) distribution, implying a decreasing rate of deposition withtransport distance (Bradford et al., 2006). Different hypotheses have been formulated andreported in the literature to account for these experimental observations. Chemical explanations that have been proposed include: porous media charge variability (Johnson and Elimelech, 1995), heterogeneity in the surface charge of the colloids (Bolster et al., 2001); andcolloid deposition in the secondary energy minimum of the Derjaguin-Landau-Verwey-Overbeek (DLVO) potential energy distribution (Li et al., 2004; Tufenkji and Elimelech, 2005a,b).
Other authors have presented an explanation based on pore structure. For example, Bradford
et al. (2002, 2003), Tufenkji et al. (2003), and Foppen et al. (2004) related the deviations from
CFT predictions to straining.
The aim of this work is to improve our understanding of bacteria deposition mechanisms in
unsaturated conditions. Specifically, we attempt to better quantify the roles of attachment andstraining processes. A set of unsaturated column experiments was performed using various sized
sands. Straining has previously been reported to increase with decreasing sand size in saturated
porous media McDowell-Boyer et al., 1986; Bradford et al., 2002, 2003) and decreasing water
saturation in unsaturated systems (Gargiulo et al., submitted for publication). The coupled role ofwater saturation and grain size on straining deposition, however, has not yet been systematicallystudied. A proteolitic enzymatic treatment was employed to investigate the role of surface
proteins on bacteria attachment. This technique also proved to be a useful tool to discriminate
straining and attachment deposition processes. Data analysis of the breakthrough curves anddeposition profiles was further aided by using fitted model parameters that accounts for timedependent attachment and/or straining processes.
2. Materials and methods
2.1. Bacteria
The bacterial strain Rhodococcus rhodochrous (DSMZ 11097) was used in the unsaturated
transport experiments. R. rhodochrous is a gram-positive spherical bacterium of 1 μm that isable to form big three-dimensional aggregates as large as 10–15 μm. This strain was isolated
from soil contaminated with alkenes by Kästner (1989). Rhodococci are aerobic actinomycetes
that exhibit a diverse range of metabolic activities. Rhodococci have the ability to degradehydrocarbon chains and a variety of organic compounds, including xenobiotic compounds like
PCB and benzothiophene.
R. rhodochrous was grown on agar plates consisting of ATCC Medium 220: CASO AGAR
(Merck 105458), peptone from casein (15.0 g), peptone from soy meal (5.0 g), NaCl (5.0 g), agar
(15.0 g), and distilled water (1000 ml). For column experiments, this bacterial strain was
cultivated at 30 °C in a nutrient broth that was agitated at 130 rpm using a thermo stated shaker(Certomax HK BRAUN®). The nutrient broth consisted of mineral medium (Brunner) Na2HPO4(2.44 g), KH2PO4 (1.52 g), (NH4)2SO4 (0.50 g), MgSO4 × 7 H2O (0.20 g), CaCl2 × 2 H2O(0.05 g), trace element sol. (10 ml), glucose (5.0 g), and distilled water (1000 ml). The bacteria
cells were harvested from the nutrient broth in the late stationary phase by gentle centrifugation(10 min, 8000 rpm, 25 °C) and re-suspended in phosphate buffer saline 10− 4 M, pH = 7. In this258

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phase the substrate had been consumed, the cell culture stopped growing, and the cells had
reached a resting mode.
Gargiulo et al. (submitted for publication) previously reported information on the surface
characteristics and morphology of R. rhodochrous. This information is briefly summarized
below. The hydrophobicity of R. rhodochrous was quantified using the M.A.T.H. approach(microbial adhesion to hydrocarbon). Between 55 to 90% of the bacteria partitioning to thehydrocarbon-water interface, indicating that it is very hydrophobic. The zeta potential wasmeasured at 25 °C using a suspension of 7 ⁎ 108 cells per ml (phosphate buffer 10− 4 M pH = 7)
and a Lazer Zee Meter (Pen Kem, Model 501) equipped with a video system to be − 47 ± 7 mV. An
epifluorescent microscope was used to determine the morphology of R. rhodochrous. This
bacterium exhibits three-dimensional aggregates that can reach the size of 10–15 μm, while
single cells have a diameter of only 0.8–1 μm.
Some of the bacteria cells of R. rhodochrous were harvested and treated by a proteolitic
enzyme to remove the proteins and associated macromolecules on the surface of the cells that may
promote attachment to solid substrates. The harvested cells were then re-suspended in Chymotrypsin solution (100 U/ml) consisting of 350 U/mg of Chymotrypsin powder (Sigma) and asolution of 100 U/ml in Tris HCl buffer (0.1 M and pH = 7). The Tris HCl buffer was preparedusing 12.1 g of Trizma base that was diluted in 1 l of deionized and sterile water, and 4.1 ml of
30% HCl. The cells and solution were left in the dark at 37 °C for 2 h and agitated at 130 rpm
using a thermo stated shaker (Certomax HK BRAUN®). The bacteria cells were then washed twicewith a 10− 4 M (pH = 7) phosphate buffer saline solution.
The infrared (IR) spectra of the untreated and treated bacterial cell samples were recorded
using a BRUKER EQUINOX model 55/S (OPUS software version 5.5) Fourier-transform (FT)
spectrometer to quantify the effect of proteolitic enzymatic treatment on the surface properties
of R. rhodochrous. The bacteria cells were harvested during late stationary phase by centrifugation (1000 rpm for 2 min, 25 °C) and cell pellets were obtained. The bacteria were
washed twice with phosphate buffer solution (10− 4 M and pH = 7) and re-pelleted by centrifugation at 1000 rpm for 2 min. The pellets were scraped on ATR (ZnSe)-crystal for reflection(which are highly transparent to IR radiation) with a sterile bacteriological loop and air driedfor 15 min at room temperature (or for 5 min by air drying in a laminar flow hood). FT-IR
measurements were performed in the transmission mode with a liquid-nitrogen-cooled MCT
detector that was connected to the FT-IR microscope (Bruker IRScope II) and spectrometer.
The spectra were obtained over the wave number range of 600–4000 nm. Typical measurement times while recording the spectra were about 4 min (60 scan) at a resolution of 4 nm.
For each sample, the spectrum was taken as the average of five measurements. There were no
significant differences (SD) in the spectra from the various sites (SD did not exceed 0.005).
The aperture that was used in this study and that provided the best signal/noise ratio was
100 μm.
2.2. Porous media
Three different sands were used in the transport experiments. These sands consisted ofseveral sieve sizes of sterile fused silica sand (Teco-Sil, C-E Minerals Greenville, USA). The
grain size distribution of the various sands was determined by sieve analysis (Laser Particle
Sizer Fritsch analysette 22). The median grain size of the three sands was 607, 567, and 330 μm.
The coefficient of uniformity for the 607, 567, and 330 μm sand was 1.44, 1.87, and 1.81,
respectively.

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259

2.3. Packed column experiments
Gargiulo et al. (submitted for publication) previously reported on the setup that was used in thepacked column experiments. Only an abbreviated discussion is provided below. The experimental
column (diameter 8.0 cm and length 22.5 cm) was constructed from Plexiglas and consisted of 4
filled sections (5 cm in length) and one empty section (2.5 cm in length). The column wasprovided with pressure probes (tensiometer with PMP 4070 pressure transducers) near the top
and near the bottom to verify unit gradient conditions. The air phase in the column wasmaintained at atmospheric pressure by means of two aeration openings. At the top of the column asprinkling plate equipped with 80 stainless steel needles was used to evenly distribute the influent
over the sand surface at a rate of 165–170 ml/h. The water and the solution were supplied to thesprinkling plate using a piston pump (Ismatec Reglo CPF). The bottom was formed by a porous
stainless steel plate covered with a hydrophilic membrane (polyester fabric, mesh size 15 μm).
The suction at the bottom of the column was adjusted to achieve unit gradient by adjusting thedrip point of a hanging water column. Steady-state water flow conditions were kept constant for
the remainder of the transport experiment. The total column water content was continuously
monitored gravimetrically using a digital balance (Sartorius® CP12001S). The column bottom
was connected with PVC tubes (2 mm inner diameter) to a conductivity probe (WTW D823662
Heilheim LDM/S), spectrophometer (Tidas Spectralitic) and UV detector (Hitachi-Merck f-1050),
respectively. Both the bacteria and the tracer outflow concentration were monitored on-line.
The column was uniformly packed with dry sand. The porosity of the packing was determined
gravimetrically (Sartorius® CP12001S digital balance). Water was introduced into the column
by slowly pumping upwards at a constant rate until a water saturation of approximately 80%(containing residual entrapped air bubbles) was achieved. Unit gradient conditions were thenobtained following the protocol outlined above. Before initiating the transport experiment, thesand pack was equilibrated by flushing it with several pore volumes of phosphate buffer solution( pH = 7 and 10− 4 M).
The final spatial distribution of retained bacteria was measured following each transport
experiment according to the procedure described by Gargiulo et al. (submitted for publication).
The deposition profile of retained cells per gram of dry sand was determined from measured
values of the total organic carbon content (TOC) in the sand. Experimental mass balance wascalculated independently for the cells in the effluent and retained cells, and normalized by the total
number injected into the column.
2.4. Theory and model
The experimental data were characterized using the HYDRUS-1D code (Šimůnek et al., 2005).
Relevant aspects of the code are briefly summarized below. The code numerically solves theRichards equation for saturated–unsaturated water flow. The bacteria transport was modelledusing a modified form of the convection–dispersion equation, in which kinetic adsorption sites
were considered for both attachment (s1) and straining (s2) processes. The mass balance equation
is defined as:


∂hc
∂s
∂
∂c
∂qc
þ qb ¼
hD
ð1Þ
−
∂t
∂t ∂x
∂x
∂x
where θ is the volumetric water content, ρb is the soil bulk density [ML− 3], t is the time [T], q is
the flow rate [LT− 1], x is the spatial coordinate [L], D is the dispersion coefficient [L2T− 1], c is

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the bacteria concentration in the aqueous phase [NcL− 3], s is the solid phase concentration[NcM− 1], and NC is the number of bacteria. The classical filtration theory (CFT) assumes that themass transfer between the aqueous and solid phase can be described as:q∂s¼ hwt ka c − kd qb s∂t

ð2Þ

where ka is the first-order attachment coefficient [T− 1], kd is the first-order detachment coefficient[T− 1], and ψt is a dimensionless colloid retention function that accounts for time-dependent
deposition. To simulate reductions in the time-dependent deposition coefficient due to theblocking or filling of favourable deposition sites, ψt is sometimes assumed to decrease withincreasing colloid mass retention. A Langmuirian dynamics (Adamczyk et al., 1994) equation has
been proposed for ψ to describe this phenomenon as:
wt ¼ 1−

s
smax

ð3Þ

in which smax is the maximum solid phase concentration [NcM− 1] of colloids on sorption sites.
Several studies (e.g., Schijven and Šimůnek, 2002; Bradford et al., 2002, 2003) divided
sorption sites into two fractions (s = s1 + s2) and assumed different rates or processes occurring at
each sorption site. Eq. (2) can then be rewritten as follows (Bradford et al., 2003):
q∂s∂ð s 1 þ s 2 Þ¼q¼ hwt ka c − kd qb s1 þ hkstr wx c
∂t
∂t

ð4Þ

where kstr is the first-order straining coefficient [T− 1], and coefficients ψt and ψstr are dimensionless colloid retention functions that account for time and/or depth-dependent deposition. Notethat the detachment process occurs only from the first sorption sites. In this analysis, attachment tothe solid phase and the air–water interface can be lumped in the ka term. Similarly, straining inpores and water films are also considered to be lumped using the kstr term.
Bradford et al. (2003) hypothesized that the influence of depth-dependent straining processeson colloid retention can be described using the following coefficient:
wx ¼



dc þ x−x0 −bdc

ð5Þwhere dc is the median diameter of the sand grains [L], x0 is the coordinate [L] of the location
where the straining process starts (in this case the surface of the soil profile), and β is an empiricalfactor controlling the shape of the spatial distribution. In this work, when we consider both timeand depth-dependent straining, the value of colloid retention function in the straining term ofEq. (4) is equal to the product of ψt and ψx.
In the Results and discussion section below, we will refer to model fits based on Eqs. (1) and(2) with ψ = 1 (i.e., without blocking) as the CFT model and with ψ ≤ 1 (i.e., with blocking of
favourable deposition sites) as the Langmuirian blocking model. Model fits based on Eqs. (1) and(4) will be referred to as the Straining model. The code allowed us to fit simultaneously theparameters ka, kd, kstr, smax and β, while considering both the breakthrough curve and theretention profile in the parameter optimisation. The mean pore water velocity and dispersivity
were obtained by fitting the solution of the convective dispersion equation for the tracer
breakthrough curve.

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261

3. Results and discussion
3.1. Role of grain size
Fig. 1A presents the breakthrough curves for R. rhodochrous using 330, 567 and 607 μm
sands when the water saturation was 80%. Here the relative effluent concentration, c/c0, is plotted
as a function of pore volume. The bacteria breakthrough curves always coincide with the arrivalof a conservative tracer (data not shown). The comparison of the effluent concentrations in
Fig. 1A indicates that the sand size plays a significant role in the bacteria transport and deposition
under unsaturated conditions. The effluent concentration of cells decreased with decreasing grain
size. The peak effluent concentration was 0.92, 0.7, and 0.02 for the 607, 567, and 330 μm sands,
respectively. Effluent mass balance information provided in Table 1 also supports this finding.
Fontes et al. (1991) also found a similar effect of sand size on bacteria transport under saturated
condition. These authors attributed this behaviour to the larger average pore diameter in coarser
sands.
Fig. 1B shows the corresponding bacteria deposition profiles for the variously sized sands
when the water saturation was 80%. The amount of bacteria that was retained in the sandFig. 1. Rhodococcus rhodochrous transport experiment under unsaturated conditions (80%) with different sand grain sizes.
(A) Breakthrough curves. (B) Retention profiles expressed using relative numbers, i.e., the number of bacteria found ineach soil layer divided by the total number of bacteria injected.

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Table 1
Experimental and modelled mass balances for Rhodococcus rhodochrous cells in the column outflow and retained in thecolumnGrain size

Coarse sandMedium sand untreated cells
Medium sand treated cells
Fine sandExperimental

Modeled% Outflow% Retained% Attached% Strained

Total % retained

95
63
72
5

7
33
17
98

0.9
7.8
3.4
0.4

9.7
27.6
17.6
96.7

10.6
35.4
20.9
97.1

The straining model was used in calculations.

increased with decreasing sand size. All of the deposition profiles were hyper-exponential andtended to decrease monotonically with distance from the injection point. Retained concentrations
were highest near the column inlet, especially for decreasing sand sizes. In the finest grain size
sand (330 μm) nearly all the bacteria (97%) were retained adjacent to the column inlet.

Fig. 2. Measured and fitted breakthrough curves (A) and retention profiles (B) for untreated Rhodococcus rhodochrous at
80% saturation and grain size of 607 μm. Fitted curves were obtained using the classical filtration theory (CFT) (red),Langmuirian blocking (blue), and straining (black) models.

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263

The effluent and spatial distribution data presented in Fig. 1A and B, respectively, were
simulated using the CFT and Langmuirian blocking models to better deduce mechanism ofdeposition. Simulation results are shown in Figs. 2, 3 and 4 for the 607, 567, and 330 μm
sands, respectively. Table 2 summarizes fitted model parameters as well as statistical parameters for the goodness of fit. Note in Figs. 2–4 and Table 2 that the CFT and the Langmuirian
blocking provide an adequate description of the breakthrough curves, but a much poorer
characterization of the deposition profiles. The sticking efficiency for the CFT model was
calculated from the fitted values of ka and predicted values of the collector efficiency (Tufenkji
and Elimelech, 2004). Values of the sticking efficiency (α) are theoretically independent of thegrain size of the sand and should only dependent on the chemistry of the colloids, aqueous
phase, and porous media. Calculated values of the sticking efficiency, however, systematicallyincreased with decreasing sand size, with α equal to 0.018, 0.05, and 0.568 for 607, 567, and330 μm sand, respectively. All of these observations suggest considerable deviations from CFT
predictions.

Fig. 3. Measured and fitted breakthrough curves (A) and retention profiles (B) for untreated Rhodococcus rhodochrous at
80% saturation and grain size of 567 μm. Fitted curves were obtained using the classical filtration theory (CFT) (red),Langmuirian blocking (blue), and straining (black) models.

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Fig. 4. Measured and fitted breakthrough curves (A) and retention profiles (B) for untreated Rhodococcus rhodochrous at
80% saturation and grain size of 330 μm. Fitted curves were obtained using the classical filtration theory (CFT) (red),Langmuirian blocking (blue), and straining (black) models.

Figs. 2–4 also present simulated bacteria transport behaviour in the 607, 567, and 330 μm
sands, respectively, using the straining model (Eqs. (1) and (4)). Table 3 summarized fitted model
parameters and statistical parameters for the goodness of fit. Table 1 includes the percentage ofbacteria mass retained by attachment and straining processes as predicted by the straining model.
Note in Figs. 2–4 and Table 3 that the straining model provide a good description of bothbreakthrough curves and deposition profiles. Table 1 indicates that straining was the dominantmechanism of bacteria deposition in all the sands, and that the percent mass retained by straining
dramatically increases with decreasing sand size (9.7, 27.6, and 96.7% for the 607, 567, and330 μm sands, respectively). This observation suggests that decreasing the pore size in theunsaturated systems significantly enhanced the straining. Bradford et al. (2002, 2003), Bradford
and Bettahar (2006) similarly found that straining increased with decreasing sand size in saturated
systems.
Fig. 5 shows a transverse slice of the packed column near the inlet for the transport experimentin the finest (330 μm) textured sand. The bacteria accumulation on the sand surface is visible, andthe biomass appears to be filtered-out in the first sand centimetres after the injection point. In
agreement with the modelling results, this is attributed to bacteria straining in the small pores andG. Gargiulo et al. / Journal of Contaminant Hydrology 92 (2007) 255–273

265

Table 2Fitted parameters of the CFT and Langmuirian blocking models for untreated Rhodococcus rhodochrous
Grain size

CoarseValue

Medium
S.E. coeff. Value

Fine
S.E. coeff. Value

Medium treated
S.E. coeff. Value

S.E. coeff.

Classical filtration theoryka (min− 1)
1.29E− 03 22.7
R2
0.98
0.98
R2 (btc⁎)
R2 (rp+)0.36

2.96E−03 8.80E−09
0.96
0.97
0.41

2.20E + 03 7.28E + 04
0.7
0.82
0.69

2.20E− 03 1.00E + 03
0.98
0.96
0.29

Langmuirian blockingka (min− 1)
2.40E− 03 0.16
kd (min− 1)
9.10E− 04 2.48E− 03
smax(Nn/Ni)/gr sand 0.159
9.12E− 04
0.98
R2
R2 (btc⁎)
0.98
R2 (rp+)0.37

2.99E−03 2.01E−04
2.55E−05 6.77E−05
5.23E + 03 1.03E + 07
0.97
0.96
0.11

0.032
2.2
1.88E−04 8.13E− 04
1.90E + 01 3.85E− 05
0.7
0.84
0.05

0.3E− 2
0.47E− 5
0.25
0.98
0.80
0.80

0.21E− 3
0.79E− 4
0.047⁎ Breakthrough curve, + retention profile.

at grain–grain junctions. In the finest sand, the straining was enhanced due to the higher ratio of
the bacteria to pore diameter and by the aggregation behaviour of Rhodococcus due to its
hydrophobic cell surface characteristics (Gargiulo et al., submitted for publication). Crist et al.
(2005) visualized colloid transport processes in porous media. These authors found greater
deposition of the hydrophobic colloids due to attractive hydrophobic forces between colloids that
produced aggregates that were subsequently retained in the narrow passages between grains.
Once deposited, these aggregates served as preferred sites for subsequent deposition of otherhydrophobic colloids.
Table 1 indicates that straining accounted for more than 78% of the total deposited bacteria inthe various sands, reaching 99.6% in the finest 330 μm sand. The influence of bacteria attachment
in the experimental sands was confounded by straining which significantly lowers the aqueous
bacteria concentration with transport depth that can subsequently attach to solid–water or air–water interfaces. Hence, a systematic trend in the measured attachment coefficients and thepercent mass attached is not apparent in Table 1.
3.2. Role of surface macromolecules
To investigate the role of surface macromolecules on bacteria surface characteristics anddeposition mechanisms in unsaturated systems, Rhodococcus was treated with α-Chymotrypsin
enzyme to degrade the peptides bond of cell surface macromolecules. The MATH test results
indicate that this treatment had a significant effect on the bacteria surface hydrophobicity. The
percent hydrophobicity of treated cells was measured to be 21%. In contrast, untreated cells werepreviously reported by Gargiulo et al. (submitted for publication) to have a hydrophobicity of
between 55–90%. A close relationship between bacteria surface hydrophobicity and protein
content was established in other studies (Neu, 1996; Sanin et al., 2003). It has been reported thatbacteria cell surface hydrophobicity is caused by nitrogen-rich groups, most notably protein(Yang et al., 1999; Ginn et al., 2002).
In the last decade, several papers have been published on the use of Fourier- transform
infrared (FT-IR) spectroscopy as a means of rapidly identifying microorganisms (Naumann et al.,

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Table 3
Attachment, detachment, and straining coefficients of the straining model fitted to the column experimental data fordifferent grain sizes and treated and untreated Rhodococcus rhodochrous cells
Variable

Value

S.E. coeff.

Coarse sand (607 μm)
smaxka(min− 1)
kd(min− 1)βkstr(min− 1)R2
R2 (btc⁎)
R2 (rp+)0.04
0.0008
0.032
0.648
0.017
0.99
0.99
0.69

0.00030.0003
0.08
0.004
0.002

Medium sand (567 μm)
smaxka(min− 1)
kd(min− 1)βkstr(min− 1)R2
R2 (btc⁎)
R2 (rp+)

5.5
0.003
2E− 6
1.25
0.08
0.96
0.94
0.91

5.8
4E− 4
1E− 4
0.27
0.05

Fine sand (330 μm)
smaxka(min− 1)
kd(min− 1)βkstr(min− 1)R2
R2 (btc⁎)
R2 (rp+)

19.17
0.025
0.06
0.37
0.199
0.91
0.96
0.99

5.3
0.009
0.02
1.17
1.19

Medium sand (567 μm). Treated cellssmax
ka(min− 1)
kd(min− 1)βkstr(min− 1)R2
R2 (btc⁎)
R2 (rp+)

0.02
0.001
0.0015
0.88
0.08
0.99
0.95
0.98

0.003
4E− 3
7E− 4
0.02
0.422

1991; Ngo-Thi et al., 2003; Erukhimovitch et al., 2005). IR spectrum can serve as a microorganism's fingerprint providing quantitative information about total biochemical composition of
the cell wall components (Naumann et al., 1991). Using this technique it is possible to characterize the cell surface and to obtain important information about the bacteria surface chemical
structure (Sharma et al., 2003; Flint et al., 2001). In this study, this technique was used tocharacterize the surface composition of R. rhodochrous cells before and after the treatment with
α-Chymotrypsin, a proteolitic enzyme.
Fig. 6 provides the IR transmittance spectrum for treated and untreated R. rhodochrous cells.
The bands between 3000 and 2800 nm are related to the alkyl-hydrocarbons groups, the so called

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267

Fig. 5. Photos of the sand surface close to the injection point for the column experiment under unsaturated conditions(80%) with untreated Rhodococcus rhodochrous and the sand grain size of 330 μm. (A) Surface of the first sand layer.
(B) Transverse cut of the first sand layer.

fatty acid region (Ngo-Thi et al., 2003). The bands at 2956, 2934 and 2875 nm characterize
asymmetric CH3 stretching, the asymmetric CH2 stretching, and the symmetric CH3 stretching,respectively. A protein region occurs between 1655 and 1546 nm (Dukor, 2001), and amide I andII bands can be identified. A very intense band between 1700 and 1600 nm indicates the presenceof the C = O group. The shoulder at 1750 nm has been attributed to lipid C = O. The band at
1450 nm represents asymmetric CH3 at the end of ethyl groups of proteins (Erukhimovitch et al.,2005). Fig. 6 indicates that the treatment of the bacteria surface with α-Chymotrypsin strongly
affected the spectra. In comparison to the spectra of the untreated bacteria several of the detectedpeaks were diminished. For example, at 1450 and 1245 nm the bands for the treated bacteria
completely disappeared (as mentioned above, this band was attributed to proteins), whereas theband at 1390 nm is still present. The band at 3071 nm is assigned to the symmetric stretching of
the NH2 group, and a strong decreasing was found for the treated cells. Decreases in these bands
are expected with protease treatment in the area assigned to the alkyl-hydrocarbons groups and268

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Fig. 6. Infrared analysis of Rhodococcus rhodochrous cells showing the difference between untreated cells and cells
treated with α-Chemotrypsin.

proteins. A stronger decreasing in the band intensity at 2934 and 2875 nm compared with thedecrease at 2956 nm was an indication that long alkyl chains have been removed. It is therefore
reasonable to assume that hydrocarbon chains were associated with the protein structures thatwere removed. This finding may explain the decrease in hydrophobicity observed with the MATH
test. Proteins are also hydrophobic molecules and their removal from the cell surface may havealso had a role in the decreased hydrophobicity.
Hydrophobicity is an important parameter that influences bacteria attachment to surfaces(Rosenberg and Doyle, 1980; Van Loosdrecht et al., 1987, 1989). Flint et al. (2001) reported
that a treatment with Trypsin or sodium dodecyl sulphate to remove cell surface proteins
resulted in a 100-fold reduction in the number of bacteria cells that attached to a stainless steel
surface. Caccavo (1999) demonstrated that surface proteins played a significant role in theattachment process, and that bacteria treated with proteolytic enzymes had less capability foradhesion. Consequently the presence of proteins, more than other surface macromolecules, acts
to enhance bacteria attachment. Caccavo (1999) also reported on adhesion experiments using
bacteria that were enzymatic and chemically treated to damage both the proteins and the lipopolysaccharides on the bacteria surface. In most cases the treatment to damage the protein, led
to a decrease in adhesion of bacteria. Walker et al. (2005) found a decrease in adhesion andhydrophobicity of E.coli during mid-exponential compared with the stationary phase. Theseobservations were attributed to hydrophilic (acidic) proteins on the outer membrane of E.coli
that decrease with the culture age, and consequently lead to a decrease in hydrophobicity andadhesion.
Fig. 7 shows the breakthrough curve for treated and untreated R. rhodochrous cells in 567 μm
sand at a water saturation of 80%. The mean front of treated and untreated bacteria arrived at thesame time, however, the peak effluent concentrations were different. For the untreated cells, thepeak value of c/c0 was 0.8, and for treated bacteria a lower value of 0.65 was observed. Fig. 8
shows a plot of the corresponding deposition profiles. As observed in the experiments using
different sand sizes, the retention profile for the treated bacteria did not exhibit an exponential
decrease with distance as predicted by classical filtration theory. The retention profiles for both
treated and untreated cells were hyper-exponential and the deposition was enhanced in the sandadjacent to the column inlet. The relative number of treated and untreated bacteria in the sandadjacent to the column inlet had a very similar value, suggesting that the enzyme treatment of theG. Gargiulo et al. / Journal of Contaminant Hydrology 92 (2007) 255–273

269

Fig. 7. Rhodococcus rhodochrous breakthrough curves for untreated cells and cells treated with α-Chemotrypsin in
567 μm sand and a water saturation of 80%.

bacteria did not significantly influence straining behaviour. The main difference in the deposition
profile was measured with greater transport distances. In this region, the treated bacteria wereretained to a lesser extent than untreated cells. This observation is attributed to a decrease inattachment as a result of the measured decrease in hydrophobicity.
The CFT, Langmuirian blocking, and straining models were used to characterize the transport
data presented in Fig. 9A and B for the bacteria that was subject to treatment by α-Chymotrypsin
enzyme. A summary of the fitted model and statistical parameters is provided in Tables 2 and 3.
The CFT and Langmuirian models provided only an accurate description of the breakthroughcurve, but the deposition profile was poorly characterized by these models. Conversely, thestraining model could properly fit both effluent and deposition data. The straining model
parameters for untreated and treated bacteria in 567 μm sand were subsequently compared to gain
additional insight on the deposition mechanisms. The value of ka for the treated bacteria wasinferior to the untreated bacteria. This result demonstrates the importance of the proteins on thebacteria surface to promote attachment. Other researchers have also reported that interactions
between the outer bacteria proteins and the solid surface play a dominant role in the microbial

Fig. 8. Rhodococcus rhodochrous retention profiles for untreated cells and cells treated with α-Chemotrypsin in 567 μm
sand and a water saturation of 80%.

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Fig. 9. Rhodococcus rhodochrous breakthrough curves (A) and retention profile (B) for cells treated with α-Chymotrypsin
in 567 μm sand and a water saturation of 80%. Fitted curves were obtained using the Classical filtration theory (CFT) (red),Langmuirian blocking (blue), and straining (black) models.

adsorption processes (Norde et al., 1989; Sanin et al., 2003). The value of kstr was quite similar fortreated and untreated bacteria, which demonstrated that bacteria treatment did not significantly
influence straining, presumably because the cut proteins did not affect the bacteria size; i.e., only amacromolecular layer was removed from the cell surface.
4. Summary and conclusions
The goal of this work was to investigate the influence of grain size and bacteria surface
macromolecules (in particular proteins) on unsaturated bacteria transport. A special focus was toquantify attachment and straining mechanisms of deposition. All transport experiments wereconducted at a water saturation of 80% and using R. rhodochrous, a hydrophobic bacterium thathas a tendency to form aggregates. Experimental effluent and deposition data were describedusing a mathematical model that accounts for reversible attachment, and time and depthdependent straining. This modelling approach lumped processes of deposition on the solid–water

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271

and air–water interfaces into a single attachment coefficient, and film and pore straining processes
into a single straining coefficient. Bacteria transport through different sized sands (607, 567, and330 μm) was directly related to median grain size. Decreasing the sand size resulted in a reductionin the effluent concentration and enhanced deposition close to the column inlet. For the considered sands, the deposition profile was not consistent with classical filtration theory predictions.
The deposition profile did not decrease exponentially with distance, but rather was hyperexponential. Visual observations of the deposition profiles, and mathematical modelling results
indicated that straining was the primary mechanism of deposition and accounted for 78–99.6% of
the deposited bacteria. Aggregation of this bacterium strain undoubtedly enhanced the amount ofstraining deposition in these experimental systems.
Additional studies were conducted to investigate the role of surface macromolecules onbacteria transport. In this case, a proteolitic enzyme was used to cut the macromolecules from thebacteria surface. Changes in the surface properties of R. rhodochrous were assessed by measuring
the hydrophobicity and the Fourier-transformed infrared spectrum of enzyme treated anduntreated bacteria. The percent hydrophobicity of treated and untreated cells according to the
MATH test was 21% and 55–90%, respectively. Measurement of the infrared spectrum also
revealed distinct changes in the spectrum associated with removal of macromolecules due to thisenzyme treatment. Comparison of transport data for enzyme treated and untreated bacteria in agiven sand provided interesting information on the roles of proteins on deposition. Straining
behaviour for treated and untreated bacteria was quite similar, suggesting that macromolecules do
not play a dominant role in straining deposition. Conversely, enzymatic surface treatment
significantly lowered the amount of attached cells throughout the column length and hence
produced greater mobility.
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