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Appl Environ Microbiol, February 1998, p. 405-410, Vol. 64, No. 2
0099-2240/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
Delineating the Specific Influence of Virus Isoelectric Point and
Size on Virus Adsorption and Transport through Sandy
Soils
Scot E.
Dowd,1,
Suresh D.
Pillai,1,*
Sookyun
Wang,2 and
M. Yavuz
Corapcioglu2
Environmental Science Program, Texas A&M
University Research Center, El Paso, Texas
79927,1 and
Department of Civil
Engineering, Texas A&M University, College Station, Texas
778432
Received 5 May 1997/Accepted 16 October 1997
 |
ABSTRACT |
Many of the factors controlling viral transport and survival within
the subsurface are still poorly understood. In order to identify the
precise influence of viral isoelectric point on viral adsorption onto
aquifer sediment material, we employed five different spherical
bacteriophages (MS2, PRD1, Q
, 
X174, and PM2) having differing
isoelectric points (pI 3.9, 4.2, 5.3, 6.6, and 7.3 respectively) in
laboratory viral transport studies. We employed conventional batch
flowthrough columns, as well as a novel continuously recirculating column, in these studies. In a 0.78-m batch flowthrough column, the
smaller phages (MS2, X174, and Q), which had similar diameters, exhibited maximum effluent concentration/initial concentration values
that correlated exactly with their isoelectric points. In the
continuously recirculating column, viral adsorption was negatively
correlated with the isoelectric points of the viruses. A model of virus
migration in the soil columns was created by using a one-dimensional
transport model in which kinetic sorption was used. The data suggest
that the isoelectric point of a virus is the predetermining factor
controlling viral adsorption within aquifers. The data also suggest
that when virus particles are more than 60 nm in diameter, viral
dimensions become the overriding factor.
| |
INTRODUCTION |
Numerous urban centers in the United
States and around the world rely on groundwater as their only source of
drinking water. Every year, almost one-half of the disease outbreaks in
the United States can be attributed to contaminated groundwater
(7). Wastewater effluents, sewage sludges, and leaking
septic tanks have commonly been identified as the sources of bacterial
and viral pathogens in contaminated groundwater. The primary factors
relied on to prevent contamination of drinking water wells with viral
pathogens from contaminating septic sources include natural viral
inactivation within aquifers and viral adsorption to soil particles
(10, 11, 19, 20, 27).
Virus survival within aquifers has been shown to be highly site
specific and virus specific (8, 12, 14, 17, 29). The
physical nature and chemical nature of aquifers have also been shown to
influence viral adsorption (9, 13). Sobsey et al.
(25) studied various soil materials to determine their ability to remove and retain viruses that were introduced via sewage
effluent. These authors concluded that clayey materials having
different pHs and organic contents efficiently adsorbed the viruses,
especially at low pHs. They also reported that sandy soils were poor
adsorbers except under intermittent unsaturated conditions. However,
Sobsey et al. reported that even under unsaturated conditions the
viruses could still be washed from sandy soils under rainfall
conditions. Other investigators (14, 15) have placed viruses
into two broad groups, groups I and II. Group I includes the phages and
viruses which have been found to be influenced by soil factors, such as
pH, organic matter, and exchangeable iron, while group II includes the
viruses which are not influenced by any specific soil factor. Although
there have been a number of studies which have correlated an aquifer's
physicochemical characteristics with viral survival, adsorption, and
transport within aquifers, unfortunately many of the factors
controlling viral transport are still poorly understood (16,
24).
The primary objective of this study was to identify the role(s) of
specific virus characteristics, such as isoelectric point and
dimensions, on the adsorption and transport of viruses in sandy soils.
To do this, we employed five different bacteriophages (differing in
size and isoelectric point) in conventional laboratory batch
(flowthrough) columns and in a novel recirculating column. Our
underlying hypothesis was that the viral isoelectric point is a
critical parameter which influences viral transport in the subsurface.
The null hypothesis was that no virus-associated factor or
characteristic would correlate with viral transport.
| |
MATERIALS AND METHODS |
Bacteriophages.
Five bacteriophages having various sizes and
various isoelectric points were employed in this study (Table
1). Two of these phages (MS2 and X174)
have been reported to belong to group I as described by Gerba and Goyal
(14). These different phages (phages having different
isoelectric points and dimensions) were chosen in order to observe
their adsorption and transport under uniform saturated soil conditions.
The appropriate host bacteria were used to enumerate the phages. The
double agar overlay procedure was used to prepare high-titer lysates
(2).
Aquifer material.
Sediment and groundwater were obtained
from a previously well-studied sandy aquifer (95% sand, 7% silt, 2%
clay) underlying the Brazos Alluvium (Burleson County, Tex.) (21,
28). The aquifer sediment had a pH of 7.1.
Column studies.
The following two types of columns were
employed in this study: conventional batch (flowthrough) columns and a
novel continuously recirculating column.
(i) Batch columns.
The batch columns were constructed by
using clear rigid polyvinyl chloride tubing that was 0.05 m in
diameter and 0.76 m long (Fig. 1A).
Each column was sanded around the inner surface 90° to the flow path
to prevent preferential flow along the walls of the column and was
packed with aquifer sediment in 0.05-m increments. The sediment
material was stirred and tapped with a rubber mallet to remove possible
channels and to create a homogeneous soil matrix throughout the column.
A peristaltic pump (Spenser Veristaltic pump; Manostat Corp.,
Barrington, Ill.) was used to create saturated conditions within the
column. Saturated conditions were achieved by pumping 3 pore volumes of
groundwater up through the bottom of the vertically oriented column,
which forced gases trapped in pore spaces out and replaced them with
groundwater. We did not attempt to pump carbon dioxide through the
column to displace the oxygen (23) since we felt that this
procedure might acidify the column. The transparency of the polyvinyl
chloride permitted us to visually confirm that major preferential flow
paths were not occurring and that the soil column appeared to be
completely saturated.
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FIG. 1.
Schematic diagram of the batch flowthrough column used
in the viral batch transport studies. (B) Schematic diagram of the
continuous column used in the viral transport studies.
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Once the column was completely saturated, Tygon tubing was used to pump
2.1 pore volumes of virus-seeded groundwater (from
a separate
reservoir) into the column. Up to 10 pore volumes of
virus-free
groundwater was added after the viruses were introduced.
Due to
logistical considerations, MS2 and PRD1 were introduced
together, while
the other phages were introduced separately. The
effluent was sampled
as soon as the viruses were introduced into
the columns. Multiple
samples were also taken from the virus injectate
to determine the
injected or initial virus concentration (
C0).
Effluent samples (calibrated as pore volumes or fractions of pore
volumes) were collected from the columns for phage enumeration.
Samples
were collected in sterilized flasks, and one 1-ml aliquot
for every 50 ml of effluent sample was plated for phage analysis
(e.g., if 200 ml of
effluent sample was collected, then four 1-ml
aliquots were used for
the phage analysis). The detection limits
of the assay were 0.1 PFU/ml
for the first 2 pore volumes and
1.0 PFU/ml for subsequent samples.
(ii) Continuously recirculating column.
The continuously
recirculating column was used to simulate an aquifer in a laboratory
setting so that we could monitor the movement of virus particles over
time and space. To our knowledge, this type of column approach for
studying virus transport is novel. The recirculating column was
designed to replace the conventional shaking microcosms that are
normally used to study virus adsorption in the laboratory. Unlike batch
columns, which can be used to study movement over a discrete distance
only, a continuous column can be used to study movement over very long
distances and over longer periods of time. The recirculating column
adsorption studies were performed by using the basic column design
described above, but the column was modified to make it recirculating
(Fig. 1B). Clinical intravenous tube connections (Continu-flo; Travenol
Laboratories, Inc., Deerfield, Ill.) were used to create ports at the
top and bottom of the column; the needle ports were inserted into the peristaltic pump line, which created an injection port at the bottom of
the column and a sampling port at the top. The column was saturated by
passing 3 pore volumes through the system, after which the circuit was
closed and the column was allowed to stabilize until it maintained a
constant pressure (7.5 lb/in2) at the injection port. Virus
particles (diluted in groundwater) were then injected by using a
syringe and a 20-gauge needle. As in the batch column experiments, most
of the phages were introduced separately; the exceptions were MS2 and
PRD1, which were introduced together. Samples were obtained by
injecting 1 ml of inoculum into the sampling port (to maintain constant
groundwater volume within the column), waiting for several seconds, and
then withdrawing a 1-ml aliquot. Samples for analysis were obtained
2.5, 5, 10, 20, 40, 60, 120, and 240 min after injection.
Statistical analysis.
A statistical analysis was performed
by using Sigmastat software (Jandel Corporation, San Rafael, Calif.).
(The applicability of this analysis was verified by using the
software's Wizard function.) The maximum viral adsorption percentage
was calculated by dividing the C0 in the
supernatant in the system at time zero (prior to adsorption) by the
resultant (effluent) virus concentration (C) in the
supernatant after 2 h. A Spearman rank order correlation analysis
was used to determine the viral characteristics which correlated to the
maximum adsorption characteristics. The Spearman rank order correlation
analysis was used to measure the strength of association between pairs
of variables without specifying which variable was dependent or
independent. A Pearson product moment correlation analysis was used to
determine the association between the isoelectric points of the phages
and experimental data. The Pearson product moment correlation analysis
was used to measure the strength of association between pairs of
variables without regard to which was dependent or independent.
Mathematical modeling.
The virus migration in the soil
columns was described by using two separate one-dimensional
mathematical models which took into account factors such as advection,
diffusion, dispersion, adsorption, and decay. Modeling of microbial
transport in saturated porous medium has been described by Corapcioglu
and Haridas (5, 6). In this study, two models which
represent bacteriophage sorption as equilibrium and as a kinetic
sorption process were used.
Model A was developed with one-dimensional mass balance equations for
bacteriophages exhibiting advective-dispersive transport,
kinetic
sorption, and first-order decay in a saturated medium.
The governing
equations used for model A are:
|
(1)
|
|
(2)
|
where
C is the mass concentration of bacteriophage in
the aqueous phase (in PFU per liter),
D is the hydrodynamic
dispersion
coefficient (in [units of length]
2 per unit of
time),
is the porosity,
q is the specific discharge
of
water (in units of length per unit of time),
is the decay
rate
(expressed as 1/unit of time),
k1 is the rate
coefficient
for bacteriophage capture to the solid matrix (expressed as
1/unit
of time),
k2 is the rate coefficient for
bacteriophage release
from the solid matrix (expressed as 1/unit of
time),
S is the
mass concentration of captured bacteriophage
in the solid phase
(in units of mass per unit of length
3),
t is time, and
x is the distance from the source
(in units
of length). In the case of the 0.78-m column, the decay rate
was
neglected because of the relatively short travel time (11.3 min).
Therefore, in model A, parameters
k1 and
k2 were determined by
fitting the model results
to the experimental data, and these
optimized values were used in the
analysis.
Numerical solutions to the bacteriophage mass balance equations were
obtained by using a fully implicit finite difference
method. This
one-dimensional numerical solution was limited in
application to simple
geometry and to homogeneous media. Basic
hydrogeologic parameters like
dispersivity were obtained by applying
the curve-fitting method to the
experimental data for
X174, which
had the highest
C/C0 value. The optimized value for dispersivity
obtained by this method was 9.94 cm. The parameters used for model
A
are as follows: pore velocity, 0.176 cm/s; porosity, 0.3; column
length, 0.78 m; injection duration, 824 s; decay rate, 0;
hydrodynamic
dispersion coefficient, 1.75 cm
2/s.
Model B was used for one-dimensional advective-dispersive transport
with a linear adsorption isotherm and first-order decay
in saturated
flow. The governing equation is
|
(3)
|
and its analytical solution as described by van Genuchten and
Alves (
26) is
|
(5)
|
where
|
(6)
|
and
|
(7)
|
where
C0 is the bacteriophage source
concentration (in PFU per liter),
Ci is the
background bacteriophage concentration (in
PFU per liter),
erfc
is the complementary error function,
R is
the
retardation factor,
t is the time (in seconds), and
v is the
pore velocity (in units of length per unit of
time).
Model B was also fitted to the experimental data in order to provide
simulation data. The parameters used for model A were
also used for
model B with the exception of rate coefficients
k1 and
k2. In model B, the retardation
factor was used instead
of the
k1 and
k2 parameters used in model A for each
bacteriophage
based on the best fit of the simulation to the column
experimental
data. The retardation factor is expressed as
|
(8)
|
where
Kd is the partition coefficient of
the virus and
b is the bulk density of the
soil.
| |
RESULTS AND DISCUSSION |
Batch columns. (i) MS2 transport.
Two pore volumes (i.e.,
1,052 ml) of groundwater containing 2.1 × 109 PFU/ml
was introduced into the batch column. The phage initially appeared
after 0.5 pore volume had been introduced (Fig.
2A). A total of 1.23 × 1012 PFU was recovered from 12 pore volumes; this value is
54% of the total amount of MS2 virus that was introduced (2.25 × 1012 PFU). After the initial feed solution was switched to
virus-free groundwater, there was a substantial increase in viral
release for 1 pore volume, after which the concentration declined. The maximum C/C0 was 0.50 at 3 pore volumes, after
which the virus concentration slowly decreased through the 12th pore
volume.
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FIG. 2.
Breakthrough curves for bacteriophages in the
flowthrough column. (A) MS2. (B) PRD1. (C) Q. (D) X174. (E)
PM2.
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(ii) PRD1 transport.
A total of 3.09 × 1010
PFU of PRD1 was introduced into the column. More than 69% of the virus
remained in the column after 12 pore volumes. The first breakthrough of
PRD1 occurred after 0.5 pore volume, and the phage titer steadily
increased until the virus-free groundwater flow was begun (Fig. 2B). As
with MS2, the PRD1 virus level reached a peak after the beginning of
the virus-free flow and then steadily declined through the 12th pore volume. The maximum C/C0 at 3 pore volumes was
0.19.
(iii) Q transport.
A total of 6.69 × 107
PFU of Q was introduced into the column, and the
C0 was 6.36 × 104 PFU/ml (Fig.
2C). A total of 3.11 × 107 PFU was recovered over 8 pore volumes, indicating that 3.6 × 107 PFU of Q
(53% of the viruses introduced) remained in the soil column. The first
breakthrough of Q occurred within the first 0.5 pore volume, after
which the concentration climbed quickly, reaching a peak value at 2.5 pore volumes, which corresponded to a C/C0 of
0.68. After this peak, the concentration of the virus particles (in the
effluent) declined rapidly over the next 6 pore volumes. The
breakthrough characteristic of this virus was similar to that exhibited
by MS2, X174, and PRD1. The maximum C/C0 was high compared to the C/C0 values of MS2 and PRD1
in this column, although it was lower than the
C/C0 of 
X174.
(iv) X174 transport.
A total of 2.02 × 109 PFU was introduced into the column, and the
C0 was 1.92 × 106 PFU/ml. A
total of 1.98 × 109 PFU was recovered over 10 pore
volumes (Fig. 2D), suggesting that 5.0 × 107 PFU of
X174 (2.5% of the virus introduced) remained in the soil column.
The first breakthrough of X174 occurred within the first 0.25 pore
volume, after which the concentration climbed quickly and reached a
peak value at 3 pore volumes, which corresponded to a
C/C0 of 0.834. After this peak, the
concentration of the virus particles in the effluent declined rapidly
over the next 7 pore volumes. The overall curve and breakthrough
characteristics are similar to those exhibited by MS2 and PRD1. The
maximum C/C0 was much higher than the
C/C0 values of MS2 and PRD1 in this column.
(v) PM2 transport.
A total of 1.72 × 1010
PFU of PM2 was introduced into the column, and the
C0 was 1.64 × 107 PFU/ml. A
total of 5.26 × 109 PFU (Fig. 2E) was recovered over
12 pore volumes, which left 1.19 × 1010 PFU of PM2
(30.6% of the virus introduced) in the soil column. The first
breakthrough of PM2 occurred within the first 0.25 pore volume, after
which the concentration climbed quickly and reached a peak value at 2 pore volumes, which corresponded to a C/C0 of 0.44. After this peak, the concentration of the virus particles (in the
effluent) dropped drastically (2 logs) within the next 0.5 pore volume.
After this drop, which corresponded to the addition of virus-free
influent, the concentration in the effluent declined slowly over the
next 10 pore volumes.
Continuously recirculating column studies.
The recirculating
column was essentially a closed reactor which simulated transport and
adsorption of phage through a soil matrix over time. We felt that this
column provided a more realistic scenario of adsorption kinetics than
the batch flowthrough columns used in conventional studies.
Based on preliminary studies, we found that 2 h of recirculation
was sufficient for maximal adsorption to take place in the
recirculating columns, while decay due to viral inactivation was
limited (data not shown). At the end of 2 h, MS2 showed 99.4%
adsorption, PRD1 showed 99% adsorption, Q
showed 97% adsorption,
X174 showed 85% adsorption, and PM2 showed 80% adsorption. Plots
of viral adsorption over time in the continuous columns are shown
in
Fig.
3. A Spearman rank order correlation
analysis was used
to determine if a specific viral characteristic, such
as isoelectric
point, molecular weight, buoyant density, or diameter,
correlated
with maximum level of adsorption. The only significant
relationship
that was found was the relationship between the level of
adsorption
and the isoelectric point of the phage. The correlation
analysis
showed that as the isoelectric point increased, adsorption
decreased
(
r =
0.9, with 92% confidence) (data not
shown). The results
of flask adsorption studies also indicated that the
degree of
adsorption was negatively correlated with the isoelectric
point
of the viruses (
r =
0.9, with 82% confidence)
(data not shown).
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FIG. 3.
Adsorption of bacteriophages in the continuous column.
(A) MS2. (B) PRD1. (C) Q. (D) X174. (E) PM2.
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A Pearson product moment correlation analysis was performed to
determine the correlation between the maximum flowthrough
concentrations
(
C/C0 values) of the smaller
phages, MS2, Q
, and
X174, and their
isoelectric points. There was
an exact correlation, with a coefficient
of 1.0 at a 99.7% confidence
level. This suggests that as the
isoelectric point of the phage
increases, the maximum
C/C0 also
increases. The
larger phages also exhibited the same type of effect
in relation to
their isoelectric points. Phage PM2, which had
the highest pI, had a
much higher
C/C0 than PRD1. When the larger
phages were included in the analysis with the smaller phages,
however,
the correlation coefficient decreased (
r < 0.7). This
could be related to the lipid contents of the two larger phages
(PRD1
and PM2) compared to the lipid contents of the other phages,
which were
devoid of any lipids (Table
1). This suggests that
the larger phages
have transport characteristics which are influenced
by factors other
than their isoelectric points.
Simulation results.
The experimental column data confirmed
that the transport of bacteriophages was retarded by the sorption
process. The sorption process characteristics for the phages used in
this study were modeled by using one-dimensional transport model A, in
which first-order kinetic sorption is used. The results of a
statistical analysis in which we used a least-squares method to
determine the capture rate coefficient
(k1) and the release rate coefficient
(k2) are given in Table
2, and the simulation results for X174
are presented in Fig. 4. This figure
shows the simulation results obtained when the kinetic (model A) and
equilibrium (model B) results were used. The model parameters were
obtained by curve fitting the model results to experimental data for
X174. MS2 and Q had similar rate coefficients for capture and
release. The capture rates of the three smaller phages are consistent
with the adsorption data, as well as the normalized transport data. The
capture rate for PRD1 is much higher than the capture rates for the
other phages, and the PRD1 release rate coefficient is much lower;
these data are not consistent with the adsorption data but are related
to the normalized transport curves. Phage PM2 (which has the highest isoelectric point) has the lowest capture rate coefficient, as well as
the lowest release rate. This is consistent with the adsorption data
(Fig. 3E) but, surprisingly, is not consistent with the normalized transport data (Fig. 5). The normalized
experimental data in Fig. 5 show the retardation effects on transport
due to sorption of phages to solids. When the experimental data were
analyzed, the removal of phage due to decay and filtration was
considered negligible because the duration of the experiment was short
and because the phage size was relatively small (<100 nm). Therefore,
the only property which could account for the differences in the
breakthrough curves for the phages was the sorption process. The
normalized data in Fig. 5 show the effects of phage sorption onto
solids. The sorption properties of each phage can be characterized by the normalized peak time and the concentration. Model B is a
one-dimensional transport model which uses equilibrium sorption along
with retardation factors to fit the data set obtained by a
least-squares treatment method. The retardation factor for each
bacteriophage obtained with model B is shown in Table 2. PRD1 had the
highest retardation factor, which conformed to the normalized transport
curve (Fig. 5). The data for X174 and Q, which had very similar
retardation factors, were not consistent with the adsorption or
transport data. The behavior of phage PM2, which had the lowest
retardation factor, was consistent with the adsorption data but not the
transport data. It is evident that low levels of viruses were
present in the effluent for extended periods of time, suggesting
that under natural conditions, low levels of
virus particles may be present in pore waters (as a result of
desorption) even after a particular point source of contamination
ceases to exist.
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FIG. 4.
Comparison of 0.78-m column data for X174 with
simulation results obtained by using model A (A) and model B (B).
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The Brazos Alluvium aquifer material that was used in these studies had
pH values that ranged between 6.9 and 7.1 (
21,
28).
This
suggests that a virus particle's net negative charge on its
surface
increases as its isoelectric point decreases from the
ambient pH. This
suggests that when a soil matrix which is essentially
negatively
charged is considered (
22), some type of charge repulsion
occurs between virus particles and soil particle surfaces. Thus,
theoretically, bacteriophage MS2, which has an isoelectric point
of
3.9, should be ionically repulsed from soil surfaces and exhibit
less
adsorption than viruses with higher pIs. The model described
by Bohn et
al. (
3) could explain the apparent discrepancy between
the
theoretical predictions and the observed experimental data.
This model
describes how a negatively charged soil particle interacts
with the
chemical makeup of its surrounding liquid phase under
saturated
conditions. According to this model, there are two layers
of cations
associated with negatively charged soil particles;
these layers are
called the Stern double layer. The layer closest
to the soil particles
is a rigid layer of associated cations,
and the layer next to this is a
diffuse region of cations. These
cation layers neutralize the negative
charge of the soil mineral
and in turn create a cation excess in a
diffuse layer which attracts
anions (such as virus particles) closer to
the soil particles,
where ion exchange with subsequent reversible and
irreversible
adsorption can theoretically occur (
18).
When phage size is considered, it is tempting to hypothesize that some
sort of straining occurs with the larger phages, such
as PRD1 and PM2.
PM2, which has the highest isoelectric point
of the phages examined (pI
7.2), should be relatively unreactive
with the soil (pH 7.1), yet it
has a lower
C/C0 than the smaller
phage
X174,
which has a lower pI (pI 6.2). Considering that the
pore spaces in the
soil matrix are many times larger than the
virus particles, straining
should be negligible theoretically.
The primary type of adsorption
which occurs in the soil matrix
has been described as adsorption due to
London (van der Waals)
forces (
4). These forces or dipole
interactions operate only
over very short distances. The energy of this
interaction varies
by a factor of 1/
r6, so that
doubling the distance between particles decreases the
energy by a
factor of 2
6 (
3). Thus, the interacting
particles (virus and soil) must
be in close proximity in order for the
forces to have any effect.
It thus follows that the probability of a
virus particle coming
under the influence of these forces should
increase with an increase
in the surface area of the particle. This
increase in reactivity
is not related to an increase in charge strength
but instead is
related to an increase in the overall number of charges
available
for interaction. Thus, the chance of adsorption may increase
with
an increase in the diameter of the phage due to an increase in
the
number of surface charges available, especially when a larger
virus
particle is compared to a smaller virus particle. Thus,
the viral
isoelectric point should still have influence by increasing
the
strength of the charges. This is illustrated by the behavior
of phages
PM2 and PRD1, which have approximately the same dimensions
but have
different isoelectric points. PM2 has a higher
C/C0 and
lower level of adsorption than PRD1.
The effect of the isoelectric
point can also be seen in the release
rates (
k2) of the three
smaller
phages (MS2, Q
, and
X174). As the pI increases, the
k2 increases, indicating that the
adsorption which takes place
is easily reversed. We acknowledge that
the differences observed
in the adsorption of the bacteriophages could
be directly related
to the underlying taxonomic differences among the
phages (Table
1). Gerba and Goyal (
14) reported previously
that there are
adsorption differences between strains of the same
virus. However,
a direct influence of pI on virus adsorption is seen
when the
release rate coefficients of MS2 and Q
(belonging to the
same
family, the
Leviviridae) are compared. MS2, which has a
lower
isoelectric point, has a lower release rate coefficient than
Q
,
which has an isoelectric point closer to neutrality (Table
2).
Size is a significant factor and does have an obvious effect, as shown
by the extremely low release rate coefficients of the
two larger phages
(PRD1 and PM2) compared to the smaller phages.
The low release rate
coefficients indicate that once adsorption
of the larger virus
particles occurs, there is a strong binding
effect. The capture rates
tended to agree with the adsorption
data, both in the continuously
recirculating column adsorption
studies and in the flask adsorption
studies. The model A results
add strength to the hypothesis that
isoelectric point and virus
size are the major factors which influence
both the capture rates
and the release rates of the phages. Model B
provides retardation
factors for the viruses which are related to
adsorption. One of
the larger phages, PRD1, shows the greatest
retardation, followed
by MS2, which has the lowest pI, and by
X174,
Q
, and finally
PM2, which shows the least retardation and which has
the highest
pI. It is thus obvious that different viruses display a
wide variety
of adsorptive characteristics. In continuously
recirculating columns
the adsorption of phage decreases with an
increase in the pI.
This effect is evident in batch transport columns
when the maximum
C/C0 values of phages having
the same relative size are considered.
However, a size exclusion
phenomenon was evident when the two
larger phages were considered. PRD1
and PM2 showed increased retardation
in their breakthrough curves when
we compared their pIs, sizes,
and maximum
C/C0
values with those of the smaller phages. The
differences in the
isoelectric points of viruses can be attributed
to differences in the
physicochemical properties of the viruses,
which are important criteria
in virus classification. However,
our data also suggest that viral
dimensions can become an overriding
factor, especially when the virus
particles are more than 60 nm
in diameter.
Thus, this study sheds some new light on the role of a specific virus
property (isoelectric point) on the control of virus
adsorption to
soil. Our results may help in the development of
better numerical
models to predict enteric virus transport in
the subsurface or could be
used in the development of methods
(based on desorption) to selectively
concentrate specific viruses
from sediments.
| |
ACKNOWLEDGMENTS |
This project was funded by the National Water Research Institute
in cooperation with the U.S. Environmental Protection Agency. Funds
from Texas Department of Agriculture's Texas-Israel Exchange project
9275 and Texas Agricultural Experiment Station project TEX-08239 were
also used.
We appreciate the support of Ronald B. Linsky (National Water Research
Institute) and Philip Berger (U.S. Environmental Protection Agency).
| |
FOOTNOTES |
*
Corresponding author. Mailing address: Texas A&M
University Research Center, 1380 A&M Circle, El Paso, TX 79927. Phone:
(915) 859-9111. Fax: (915) 859-1078. E-mail:
s-pillai{at}tamu.edu.
Present address: Department of Soil, Water, and Environmental
Science, University of Arizona, Tucson, AZ 85721.
| |
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Appl Environ Microbiol, February 1998, p. 405-410, Vol. 64, No. 2
0099-2240/98/$04.00+0
Copyright © 1998, American Society for Microbiology. All rights reserved.
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Top
Abstract
Introduction
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