effects of autochthonous microbial community on the die-off of fecal indicators in tropical beach...

R E S E A R C H A R T I C L E

E¡ects ofautochthonousmicrobial communityon thedie-o¡offecal indicators in tropical beach sandFan Feng, Dustin Goto & Tao Yan

Department of Civil and Environmental Engineering, University of Hawaii at Manoa, Honolulu, HI, USA

Correspondence: Tao Yan, Department of

Civil and Environmental Engineering,

University of Hawaii at Manoa, 2540 Dole

Street, 383 Holmes Hall, Honolulu, HI 96822,

USA. Tel.: 11 808 956 6024; fax: 11 808 956

5014; e-mail: [email protected]

Received 13 January 2010; revised 12 May

2010; accepted 25 May 2010.

Final version published online 12 July 2010.

DOI:10.1111/j.1574-6941.2010.00921.x

Editor: Riks Laanbroek

Keywords

beach sand; bacterial antagonism; Escherichia

coli; Enterococcus faecalis; protozoan

predation; biotic stresses.

Abstract

The recently observed high levels of fecal indicators in beach sand confound beach

water monitoring efforts. The high levels of fecal indicators may be caused by the

loss or the reduced activities of common environmental stresses controlling die-off

in the sand. Microcosm experiments were conducted to compare the effects of

biotic stresses from autochthonous sand bacteria, protozoa, and viruses on

Escherichia coli and Enterococcus faecalis in two tropical beach sands. The

inhibition of protozoan activities by cycloheximide did not significantly affect the

die-off of E. coli, indicating that protozoan predation played a limited role in beach

sand. The contribution from phage infection to E. coli die-off was also negligible.

Consequently, autochthonous bacteria were identified as the predominant biotic

stress to the die-off of E. coli in beach sand. Subsequent experiments demonstrated

that the beach sand had a very low protozoan concentration and low protozoan

growth potential when compared with various environmental samples. Co-

culturing of E. coli with autochthonous sand bacterial isolates significantly

enhanced E. coli die-off. PCR-denaturing gradient gel electrophoresis analysis

revealed a complex sand bacterial community, suggesting that bacterial antagonis-

tic effects may be widespread. The study also found that E. faecalis exhibited a

much longer survival in beach sand compared with E. coli.

Introduction

The presence of high levels of fecal indicator organisms in

beach sand may have significant implications for the mon-

itoring and regulation of beach water quality. Reports

showing the presence of Escherichia coli and enterococci in

beach sand were initially presented in the early 1990s

(Ghinsberg et al., 1994; Oshiro & Fujioka, 1995). Recent

comparative studies at beaches in the Great Lakes region

reported the presence of significantly higher levels of E. coli

and enterococci in beach foreshore sand than in beach water

(Wheeler-Alm et al., 2003; Whitman & Nevers, 2003).

Similar observations were subsequently made at different

geographic regions and at both freshwater and seawater

beaches (Beversdorf et al., 2007; Bonilla et al., 2007; Edge &

Hill, 2007; Ishii et al., 2007; Kon et al., 2007; Yamahara et al.,

2007; Hartz et al., 2008). Because beach sand and water have

a continuous interaction, the fecal indicators harbored in

sand will inevitably enter the beach water at various rates

subject to hydrometeorological control (Wheeler-Alm et al.,

2003; Whitman & Nevers, 2003; Yamahara et al., 2007;

Nevers & Whitman, 2008). Since little is known about the

correlation between fecal indicators and pathogens in sand,

the sand-sourced fecal indicators may undermine the funda-

mental assumption of the indicator-based water monitoring

approach (Cabelli et al., 1979, 1982) and therefore compli-

cate the interpretation of water bacteriological data.

Fecal indicators in beach sand may originate from human

and other warm-blooded animal feces (Oshiro & Fujioka,

1995; Ishii et al., 2007) or may exist as members of the

autochthonous sand microbial community (Kon et al.,

2007). Regardless of their original sources, the widely

observed high abundance of fecal indicators in beach sand

can be attributed, at least partially, to their prolonged

survival, or slow die-off, in beach sand (Hartz et al., 2008).

Given the presence of various abiotic and biotic environ-

mental stresses that collectively determine the die-off of fecal

indicators, it is reasonable to suspect that the accumulation

FEMS Microbiol Ecol 74 (2010) 214–225c� 2010 Federation of European Microbiological SocietiesPublished by Blackwell Publishing Ltd. All rights reserved

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of fecal indicators in beach sand may be due to the absence

or the reduced activities of certain common environmental

stresses.

Previous studies on the die-off of fecal indicators have

identified numerous important abiotic and biotic environ-

mental stresses. The abiotic stresses, which include tempera-

ture variation (Vasconcelos & Swartz, 1976), sunlight

inactivation (Fujioka et al., 1981; Sinton et al., 1999), carbon

starvation (Terzieva & McFeters, 1991), pH fluctuation

(Carlucci & Pramer, 1960b), and osmotic stress from salinity

changes (Carlucci & Pramer, 1960b; Anderson et al., 1979),

have been studied extensively and their effects on fecal

indicator die-off are well understood. The biotic environ-

mental stresses, on the other hand, have received consider-

ably less attention, mainly due to the dynamic nature of

biological interactions and the technical difficulties involved

in studying them. Nevertheless, studies have shown that

biotic stresses may play just as important roles as abiotic

stresses in the die-off of fecal indicators (Barcina et al., 1997;

Rozen & Belkin, 2001; Hartz et al., 2008).

Common biotic environmental stresses include proto-

zoan predation, phage infection, and bacterial antagonism.

Among these, protozoan predation was most frequently

identified as the predominant biotic stress causing die-off

of E. coli in aquatic environments (Enzinger & Cooper, 1976;

McCambridge & McMeekin, 1980; Gonzalez et al., 1992). In

nonaquatic soil and sediment environments, protozoan

predation stress also plays an important role. Studies have

shown that microcosms amended with E. coli prey cells often

result in the population growth of soil protozoa, indicating

the predator–prey relationship between the autochthonous

protozoa and the exogenous E. coli cells (Tate, 1978). When

protozoan activities were inhibited using the protozoan-

specific inhibitor cycloheximide, the die-off of amended E.

coli cells was significantly reduced (Davies et al., 1995;

Sørensen et al., 1999). Bacteriophages that can infect and

lyse fecal indicators are widely present in both aquatic and

soil environments (Carlucci & Pramer, 1960a; Ashelford

et al., 2003). Phage infection, however, is usually considered

a minor stress to the die-off of fecal indicators in natural

environments (Rozen & Belkin, 2001).

In contrast to the relatively simple underlying mechan-

isms in protozoan predation and phage infection, bacterial

antagonism may involve various different mechanisms, such

as direct predation, competition for nutrients, and antimi-

crobial production. Direct predation of fecal indicators by

autochthonous bacteria was previously reported in marine

environments; a number of marine bacteria were capable of

breaking the cell walls of E. coli cells (Mitchell et al., 1967),

and some marine Pseudomonas can destroy and utilize the

capsular polysaccharide of E. coli cells as the sole carbon

source (Mitchell & Nevo, 1965). Autochthonous bacterial

communities may also adversely affect the survival of fecal

indicators by competing and scavenging for limited nutri-

ents; it was shown that E. coli cells are generally poor

competitors against autochthonous bacterial populations

under low nutrient conditions (Jannasch, 1968). Further-

more, it is well known that soil bacteria, such as Streptomyces

species, are capable of producing small antimicrobial mole-

cules to inhibit the growth of competitors (Hibbing et al.,

2010).

The objective of the present study, therefore, was to

determine the effects of the various autochthonous sand

biotic stresses (i.e. protozoa, bacteria, and bacteriophages)

on the die-off of E. coli and Enterococcus faecalis in beach

sand. Autochthonous sand microbial components were

inoculated into sand microcosms to determine their respec-

tive effects on the die-off of amended E. coli and E. faecalis

cells. Subsequent experiments focused on bacterial antagon-

ism and protozoan predation. The bacterial communities in

the sand microcosms were analyzed using the 16S rRNA

gene-based PCR-denaturing gradient gel electrophoresis

(PCR-DGGE) technique to detect major indigenous sand

bacterial populations and monitor their changes over time.

Autochthonous sand bacteria were also isolated, and their

antagonistic effects were directly illustrated in one-on-one

co-culturing experiments with E. coli. In addition, the

protozoan abundances and growth potentials in beach sand

and several reference environmental samples were also

determined and compared.

Materials and methods

Bacterial strains and enumeration

The model organisms used in the study were E. coli ATCC

25922 and E. faecalis ATCC 29212. The experimental cells

were obtained by growing fresh single colonies overnight in

10 mL culture broths at 37 1C with continuous shak-

ing (200 r.p.m.), and harvesting at the stationary phase

(OD600 nmZ1.2) by centrifugation at 10 000 g for 30 s. LB

agar and broth were used for E. coli, and TSA agar and TSB

broth were used for E. faecalis. The harvested cells were

washed twice with phosphate-buffered water (PBW), and

then suspended in PBW to prepare working cell suspensions

(OD600 nm = 0.3, approximately 108 CFU mL�1). The num-

bers of E. coli and E. faecalis cells in the working cell

suspensions and the samples from microcosms were deter-

mined by plate-counting; the modified mTEC agar method

was used for E. coli (USEPA, 2002a) and the mE-EIA

method was used for E. faecalis (USEPA, 2002b).

Sample collection

Foreshore sand samples from Sand Island (SI) beach

(21118004.4000N, 157152040.4600W) and Kailua (KL) beach

(21123055.4400N, 157143043.2200W) were collected at

FEMS Microbiol Ecol 74 (2010) 214–225 c� 2010 Federation of European Microbiological SocietiesPublished by Blackwell Publishing Ltd. All rights reserved

215Biotic stresses and die-off of fecal indicators in sand

locations approximately 1.5 m away from the water line and

about 10 cm below the surface. The sand samples were

transported to the laboratory at 4 1C and processed within

48 h. Sand samples from the two beaches showed similar

physical and chemical characteristics (data not shown). In

addition, to compare the natural abundance and growth

potential of protozoa between beach sand and other envir-

onments, organic-rich soil samples, stream sediment sam-

ples, and stream water samples were collected from Manoa

Stream near the University of Hawaii Manoa campus.

Beach sand microcosm setup

Beach sand microcosms were set up to investigate the effects

of different sand biotic stresses on the die-off of fecal

indicators. The biotic stresses were simulated by inoculating

sand microcosms with different microbial components in

sand extracts. Sand extracts from the SI and KL sands were

prepared separately by shaking 50 g of fresh sand samples in

50 mL of 0.05 M ammonium phosphate buffer (APB, pH

6.88) (Kingsley & Bohlool, 1981) in 12 plastic bottles on a

wrist-action shaker (250 r.p.m., 1 h) at room temperature.

After settling for 30 s, 40 mL sand extract supernatants were

collected and pooled for subsequent characterization and

inoculation. A preliminary test indicated that sand extracts

from the SI and KL sands contained 5–30 CFU 100 mL�1

E. coli and 50–113 CFU 100 mL�1 E. faecalis.

Four experimental treatments, each containing triplicate

microcosms, were established in Mason jars by combining

200 g (dry weight) of sterile beach sand, approximately

106 CFU g�1 sand of E. coli or E. faecalis cells, and 50 mL of

treated sand extracts that contained different autochtho-

nous sand microbial components. The sterile sand was

prepared by autoclaving at 121 1C for 20 min on two

consecutive days to remove autochthonous organisms in-

cluding the resilient spore-forming bacteria. Fecal indicator

cells were amended in numerical dominance over the

existing populations of autochthonous fecal indicators,

whose presence therefore can be neglected in data analysis.

Sand extracts were processed to obtain inoculums for four

experimental treatments: (1) the negative control (NC)

treatment with sterilized sand extracts, (2) the live control

(LC) treatment with whole sand extracts including auto-

chthonous sand protozoa, bacteria, and viruses, (3) the

protozoan-inhibited (PI) treatment with cycloheximide-

treated whole sand extracts, and (4) the phage-only (PO)

treatment with membrane-filtered sand extracts. For the PI

treatment, 12 mg of cycloheximide was added to each

microcosm, which resulted in final concentrations of 150

and 218 mg L�1 in the SI microcosms and KL microcosms,

respectively, due to the slightly different moisture levels at

saturation. The effectiveness of cycloheximide at the two

concentrations in killing autochthonous protozoa was

experimentally verified in the laboratory (data not shown).

For the PO treatment, sand extracts were filtered using a

0.2-mm pore size membrane (Millipore, Billerica, MA) to

remove both protozoa and bacteria, leaving only phage

particles in the inoculums. The sand microcosms were then

adjusted to full water saturation by adding additional PBW

to just submerge the sand to mimic beach swash zone

conditions (Kon et al., 2007) and also to minimize variations

in the moisture level (Solo-Gabriele et al., 2000). The

experimental moisture levels in the microcosms using SI

sand and KL sand were 28.5� 1.3% and 21.7� 1.2%,

respectively. The microcosms were completely mixed, in-

cubated in the dark at room temperature (25 1C), and then

repeatedly sampled over time. During sampling, approxi-

mately 10 g of sand samples were collected from the fully

mixed sand microcosms. The samples were extracted using

20 mL of APB, and the culturable cell numbers of E. coli and

E. faecalis in the resulting extracts were enumerated.

PCR-DGGE

Bacterial communities in the sand extracts and their changes

over time in the microcosms were analyzed using a 16S

rRNA gene-based PCR-DGGE procedure (Yan et al., 2006).

Briefly, total genomic DNA was extracted from the sand

extracts using the Powersoils DNA isolation kit (MO-BIO,

Carlsbad, CA) following the manufacturer’s instructions. A

short fragment of the 16S rRNA gene was amplified using

the bacterial universal primers 338F and 518R with a GC

clamp, and the PCR amplicons were separated by electro-

phoresis on 8% w/v polyacrylamide gels with a 30–55%

denaturing gradient using a D-Code apparatus (Bio-Rad;

Hercules, CA). Gels were stained with SYBR Green I

(Molecular Probes; diluted 1 : 5000 in 0.5�TAE), visualized

on a UV transilluminator, and photographed using a digital

CCD camera (Bio-Rad). Gel image analysis was performed

using the GELCOMPAR software package (Applied Maths, Sint-

Martens-Latem, Belgium). Briefly, gel images were digita-

lized and processed with background subtraction and least

squared filtering, normalized with reference positions, and

then auto-searched to identify the bands. DGGE bands were

subsequently excised and sequenced to determine the phy-

logenetic affiliation of bacterial populations. The excised gel

bands were first frozen and thawed in 20 mL of nuclease-free

water to release DNA. After centrifugation at 10 000 g for

4 min, supernatants (1 mL) were used as DNA templates in

additional rounds of PCR amplification, which only used 30

thermal cycles to minimize the amplification of contami-

nant DNAs. The PCR amplicons were further purified by

electrophoresis to achieve a single DGGE band in each PCR

reaction. The final PCR products were cleaned using the

PinkClean DNA kit (G-Biosciences, Maryland Heights,

MO) before sequencing. The DNA sequences were


216 F. Feng et al.

compared with the GenBank database to determine their

closest phylogenic relatives.

Co-culturing of sand bacterial isolates and E. coli

Sand bacterial isolates were obtained and co-cultured with

E. coli cells to illustrate their antagonistic effects on E. coli

die-off. Sand extracts containing autochthonous bacteria

from SI beach sand microcosms were spread onto both LB

agar plates and sand extract agar (SEA) plates to isolate

autochthonous sand bacteria. The low-nutrient SEA agar

was used to isolate bacterial species that may not grow well

on the nutrient-rich LB agar (Bogosian et al., 1996). The LB

plates were incubated at 37 1C overnight, while the SEA

plates were incubated at room temperature for at least 3

days. A total of five visually different bacterial isolates, four

from the LB plates and one from the SEA plates, were

obtained. The phylogenetic information of the bacterial

isolates was determined by sequencing their 16S rRNA

genes. Bacterial colonies were boiled in 50mL of 50 mM

NaOH for 10 min to release total genomic DNA. After

centrifugation at 10 000 g for 10 min, the supernatants

(1mL) were used as DNA templates to amplify the 16S rRNA

gene using bacterial universal primers 27F and 1522R (Yan

et al., 2006).

Co-culturing of the autochthonous sand bacterial isolates

with E. coli was conducted in beach sand microcosms

containing sterile SI beach sand. A total of six different

treatments (i.e. 18 microcosms) were established, including

one negative control treatment that contained only E. coli

cells and five experimental treatments that contained both E.

coli cells and cells from each of the five autochthonous sand

bacterial isolates. Each microcosm contained 100 g of SI

beach sand (dry weight), and the moisture content was

adjusted to a full saturation of 27% by adding sterile

artificial seawater. Equal numbers (108) of E. coli and

individual bacterial isolate cells were added to each micro-

cosm. The sand microcosms were fully mixed, incubated at

room temperature in the dark, and sampled periodically.

Protozoan enumeration

Protozoa were enumerated with a microscope-based most

probable number (MPN) method (Rønn et al., 1995) using

either 20-mL glass culture tubes or 96-well microtiter plates.

Glass culture tubes were used to enumerate protozoa in

environmental samples where large sample sizes were

needed to compensate for the low protozoa concentration.

The environmental samples (5 g of soil, 5 g of beach sand,

5 mL of water, and 5 g of sediment) were completely mixed

in 10 mL of Page’s amoeba saline (PAS) (Page, 1988). The

mixtures were then used to prepare threefold MPN serial

dilutions in glass culture tubes. The microtiter plate-based

MPN was used to quantify protozoa in microcosms where

active protozoan growth was stimulated by the addition of

E. coli cells as prey. For microcosms containing sand, soil,

and sediment, 5 g samples were collected from the fully

mixed microcosms and extracted using 10 mL PAS with

vigorous shaking on a wrist-action shaker (250 r.p.m.,

10 min). The extract supernatants (100mL) were used to

inoculate the microtiter plates to establish threefold serial

dilutions for MPN tests. For water samples, 100 mL of water

from the microcosms was directly used to inoculate the

microtiter plates for MPN tests. The culture tubes or

microtiter plates were incubated in the dark at 10 1C for

1–3 weeks, and were periodically examined for the presence

or absence of protozoa.

Protozoan growth microcosm setup

The growth potentials of protozoa in the SI beach sand and

the soil, sediment, and stream water samples were compared

using microcosms. Beach sand (100 g), soil (100 g), sedi-

ment (100 g), and water samples (100 mL) were added

separately to 12 Mason jars to establish four treatments.

For the sand, soil, and sediment microcosms, moisture levels

were adjusted to 30% by using autoclaved artificial seawater

for sand microcosms, autoclaved DI water for soil micro-

cosms, and autoclaved stream water for sediment micro-

cosms. Stationary-phase E. coli cells (4� 109) were spiked

into the microcosms on Day 0 as prey, and a subsequent

addition (5� 1010 cells) was carried out on Day 20. The

microcosms were incubated at room temperature in the

dark and sampled periodically to determine protozoan

concentrations using the microscope-based MPN enumera-

tion method.

Data analysis and GenBank accession number

The first-order decay kinetics model (ln C = ln C0� kt;

C, indicator cell concentration at time t; C0, initial indicator

cell concentration; and k, first-order die-off coefficient) was

used to fit the die-off data of E. coli and E. faecalis in the

microcosm studies. Die-off coefficients for the different

experimental treatments were determined by linear regres-

sion of log-transformed concentration data. Statistical ana-

lyses were performed using a STATISTIXL add-in package in

MICROSOFT EXCEL. The default statistical significance was

based on a P � 0.05 level, unless stated otherwise. For the

initial beach sand microcosm experiments, the die-off

coefficients of fecal indicators in different treatments were

analyzed using ANOVA to determine whether significant

differences exist. For the co-culturing experiment between

E. coli and autochthonous bacterial isolates, an ANOVA was

performed to detect statistically significant differences

among the experimental treatments, and then post hoc

paired t-tests were performed to determine whether signifi-

cant differences exist between different experimental



treatments. DNA sequences were compared with sequences

in the GenBank database using the BLASTN program to search

for their closest phylogenetic relatives. Sequences were

deposited in the GenBank database under accession nos

GU397434–GU397445.

Results

Die-off of fecal indicators in the presence ofautochthonous microbial communities

The die-off of E. coli and E. faecalis in the presence of

different autochthonous sand microbial components was

investigated in microcosms using both SI and KL beach

sands. The concentrations of culturable E. coli cells in the

microcosms over time are shown in Fig. 1a and b, and the

first-order E. coli die-off coefficients are listed in Table 1.

Statistically significant differences in die-off rates were

observed in the four treatments in both sands. In both

experiments, after 4 3 weeks of incubation, E. coli sus-

tained limited loss of cultivability in the NC microcosms

that received autoclaved sand extract. In the LC microcosms

that were inoculated with whole sand extracts containing

bacteria, protozoa, and phages, E. coli exhibited similar

levels of rapid loss in cultivability (approximately 107-fold)

in o 22 days in either SI sand microcosms or KL sand

microcosms (Fig. 1), and the first-order die-off coefficients

were � 0.361 and � 0.381 day�1, respectively (Table 1). The

differences in the E. coli die-off rates between the NC and the

LC microcosms can only be attributed to the presence of

autochthonous beach sand microbial components. In the PI

microcosms where the activities of protozoa were inhibited

by cycloheximide, the die-off of E. coli in both SI and

KL sand microcosms was comparable to the LC treatments

(Fig. 1, Table 1), with a small lag observed in the protozoan-

inhibited KL sand microcosms (Fig. 1b). This indicates that

the removal of protozoa activities by chemical inhibition

only slightly slowed down the die-off of E. coli in the beach

sand microcosms, suggesting that protozoa played a minor

role in the die-off of E. coli in the beach sands.

Interestingly, in the PO treatment where both protozoa

and bacteria were removed by membrane filtration, the die-

off of E. coli was very slow (Fig. 1). In the microcosms with

KL sand, the PO treatment exhibited an E. coli die-off

coefficient similar to that of the NC treatment. In the

microcosms with SI sand, the PO treatment exhibited a

trend similar to that of the KL microcosms, with a smaller

E. coli die-off coefficient than the NC treatment. On

comparing the PI treatment (i.e. bacteria plus phages) and

the PO (i.e. phages only) treatment, it is clear that the

autochthonous bacteria in beach sand played the most

important role in the die-off of E. coli in the beach sand

microcosms. The same conclusion can be drawn by compar-

ing the first-order die-off coefficients of E. coli in the two

treatments (Table 2). For example, in the KL sand experi-

ment, the E. coli die-off coefficients for the NC, PO, PI,

and LC treatments are � 0.063, � 0.066, � 0.0327, and

� 0.381 day�1, respectively. Assuming a linear system and

that the principle of superposition applies, the contributions

can be calculated as � 0.003 day�1 for phage infection,

� 0.261 day�1 for bacteria antagonism, and 0.054 day�1 for

protozoan predation. The contribution from bacteria to the

die-off of E. coli is 4.8 times the contribution from protozoa

and 87 times the contribution from phages.

Enterococcus faecalis in beach sand microcosms exhibited

a much more prolonged survival than E. coli. The number of

cultivable E. faecalis cells in microcosms with SI sand and KL

sand is plotted over time in Fig. 2a and b, respectively, and

the first-order E. faecalis die-off coefficients are listed in

Table 1. ANOVA analysis of the die-off coefficients in different

treatments indicated no significant difference. During the

experimental course of 28 days, essentially no reduction in

(a)

(b)

Fig. 1. Reduction of the number of cultivable Escherichia coli cells in

sand microcosms with sand from SI beach (a) and KL beach (b). Symbols

for different treatments are as follows: �, autoclave-sterilized sand

extract (NC); B, untreated whole-sand extract (LC); ., sand extract plus

cycloheximide (PI); and ’, 0.2-mm membrane-filtered sand extract (PO).

Error bars represent SDs of the log means of triplicates.


218 F. Feng et al.

the cultivability of E. faecalis was observed in any of the

experimental treatments. The first-order die-off coefficients

are extremely low, in the range of � 0.004 to � 0.028 day�1.

For example, when the die-off of E. coli and E. faecalis in the

SI beach sand microcosms was compared, the die-off

coefficient of E. faecalis was 25.9 times lower than that of E.

coli. Because E. faecalis cells were much more resistant than

E. coli cells, no differences in survival between the experi-

mental treatments could be observed in the beach sand

microcosms, and therefore the respective effects of the

different microbial components on the die-off of E. faecalis

could not be determined in this study.

Bacterial diversity in beach sand microcosms

Because no significant difference in how the biotic factors

affected E. coli survival was observed between the SI and the

KL sands, subsequent experiments that further investigated

bacterial antagonistic effects and protozoan predation were

conducted exclusively using the SI sand. To illustrate the

bacterial diversities in the LC and PI treatments, two

microcosms were randomly selected and analyzed using

16S rRNA gene-based PCR-DGGE. The bacterial commu-

nity in the SI beach sand is fairly complex, as indicated by

the presence of numerous distinct DGGE bands (Fig. 3). On

Day 2, 15 DGGE bands, representing 15 possible different

populations, were present in both microcosms. During the

course of the experiment, the bacterial communities in both

microcosms underwent discernable changes. For example,

on Day 20, a total of 19 DGGE bands were identified in the

PI microcosm, eight of which were not present in the

starting bacterial community. The bacterial communities

were notably similar to each other, despite the addition of

cycloheximide to the PI microcosm. The similarity in

bacterial community structures also corresponded to the

similarity in E. coli die-off rates observed. DGGE bands were

exercised and sequenced to determine their phylogenetic

identity (Table 2). Among the eight DGGE bands that were

successfully isolated and sequenced, four belong to the

phylum of Gammaproteobacteria and the other four belong

to the phylum of Bacterioides. The bacterial diversity in the

beach sand was considerable; a majority of the bacterial

Table 1. Beach sand microcosm setup and first-order die-off kinetic coefficients of Escherichia coli and Enterococcus faecalis in the microcosms

Experimental treatment Biotic stresses

First-order die-off coefficient (day�1)�

E. coli E. faecalis

SI sand KL sand SI sand KL sand

Negative control (NC) None � 0.128 (0.81) �0.063 (0.87) � 0.004 (0.09) �0.008 (0.56)

Phage-only (PO) Phages � 0.067 (0.64) �0.066 (0.69) � 0.01 (0.03) �0.012 (0.90)

Protozoan-inhibited (PI) Bacteria and phages � 0.347 (0.99) �0.327 (0.97) � 0.028 (0.40) �0.013 (0.03)

Live control (LC) Bacteria, protozoa, and phages � 0.362 (0.98) �0.381 (0.99) � 0.014 (0.23) �0.017 (0.83)

�R2 values of linear regression are in parentheses.

Table 2. The phylogenetic affiliations of bacterial populations detected by PCR-DGGE� (Fig. 2) and bacterial isolates from SI beach sand

Band/isolatesw Sequence length (bp)

Phylogenetic affiliation

Organism (accession no.) % Identity Phylum

F1 129 Pseudomonas aeruginosa (GU263805.1) 100 Gammaproteobacteria

F2 169 Pseudomonas spp. VS-83 (FJ497695.1) 99 Gammaproteobacteria

F3 165 Arenibacter certesii (AY271622.1) 100 Bacteroidetes

F4 109 Cellulophaga fucicola (EU939693.1) 100 Bacteroidetes

F6 172 Tolumonas auensis DSM 9187 (CP001616.1) 90 Gammaproteobacteria

F7 140 Photobacterium spp. Gung47 (GQ260188.1) 94 Gammaproteobacteria

F8 166 Balneola spp. MOLA 118 (AM990892.1) 96 Bacteroidetes

F9 138 Balneola vulgaris (AY576749.1) 96 Bacteroidetes

B1 1440 Exiguobacterium homiense (DQ351341.1) 99 Firmicutes

B2 1438 Bacillus spp. (DQ643066.1) 99 Firmicutes

B3 1420 Sporosarcina saromensis (AB243864.1) 99 Firmicutes

B4 1433 Kurthia gibsonii (AM184261.1) 99 Firmicutes

B5 1341 Ochrobactrum anthropi (AM490611.1) 99 Alphaproteobacteria

�DGGE band F5 sequencing failed.wF1–9 are DGGE bands and B1–4 are sand bacterial isolates.



populations represented by DGGE bands belong to different

families, while only bands F1 and F2 share the same

Pseudomonadaceae family.

Co-culturing with bacterial isolates from beachsand

Bacterial isolates from the SI beach sand were co-cultured

with E. coli to directly demonstrate their antagonistic effects

on the die-off of E. coli. A total of five different bacterial

strains were obtained and their 16S rRNA gene-based

phylogenetic affiliations were determined (Table 2). Four of

the isolates are low-GC gram-positive Firmicutes, and the

fifth one belongs to the phylum of Alphaproteobacteria,

which differ from the major bacterial populations detected

by PCR-DGGE. The die-off patterns of E. coli in ‘E. coli only’

sand microcosms and co-cultures with the sand bacterial

isolates are shown in Fig. 4. An ANOVA analysis indicated that,

on Day 12, statistically significant differences exist between

the different treatments (P = 0.008). Post hoc paired t-tests

between the ‘E. coli only’ treatment and the co-culturing

treatments indicated that the different bacterial isolates

affected the die-off of E. coli differently. A statistically

significant enhancement in E. coli die-off was observed in

co-cultures with strains B1 (P = 0.007), B4 (P = 0.032), and

B5 (P = 0.013), while the enhancement in co-cultures with

B2 (P = 0.28) and B3 (P = 0.17) was less significant.

Abundance and growth potential of protozoa inbeach sand

To determine the causes of the observed minor role that

protozoa played in E. coli die-off in beach sand microcosms,

the population density and growth potential of autochtho-

nous protozoa in the SI sand were compared with soil,

sediment, and stream water samples. The SI beach sand

contained a very small number of autochthonous protozoa

(8.5 MPN 10 g�1), which was significantly lower than the soil

sample (1060 MPN 10 g�1) and the sediment sample

(65.5 MPN 10 g�1). The stream water sample also contained

a very low number of protozoa (1.8 CFU 10 mL�1). When

provided with E. coli cells as prey, the growth of

(a)

(b)

Fig. 2. Reduction of the number of cultivable Enterococcus faecalis cells

in sand microcosms with SI beach sand (a) and KL beach sand (b).

Symbols for different treatments are as follows: �, autoclave-sterilized

sand extract (NC); B, untreated whole-sand extract (LC); ., sand

extract plus cycloheximide (PI); and ’, 0.2-mm membrane-filtered sand

extract (PO). Error bars represent SDs of the log means of triplicates.

PI LC PI PI PILC LC LC LC LC

Day 2 Day 5 Day 11 Day 16 Day 20

F1F2

F5F4F3

F6

F7

F8

Fig. 3. Bacterial community structures in two SI beach sand microcosms

(one from the PI treatment and one from the LC treatment) as revealed

by 16S rRNA gene-based PCR-DGGE analysis. Gel bands F1–F8 were

excised and sequenced.


220 F. Feng et al.

autochthonous protozoa in microcosms that contained the

different environmental samples was monitored for 42 days

(Fig. 5a). On Day 0, approximately 4� 109 E. coli cells were

amended into all experimental microcosms as prey, and

subsequent growth potentials were observed in different

environmental samples. The soil sample contained the high-

est initial number of protozoa, and produced a 0.72 log

increase in the protozoa population density after 8 days of

incubation. Although initially containing a much lower

number of protozoa than the soil sample, the stream water

and freshwater sediment samples produced higher specific

protozoan growth, resulting in 1.78 and 1.06 log increases in

protozoa population density after 5 days of incubation,

respectively. The SI sand sample generated a mere 0.24 log

peak increase on Day 5, which is consistent with its low

initial protozoa number. The second spike of E. coli prey

(approximately 5� 1010 cells) on Day 20 generated similar

protozoan growth patterns in the different environmental

samples, with the SI sand still being the least conducive

environment for protozoan growth. The second prey E. coli

addition provided about 12.5 times more prey cells, and

correspondingly higher protozoan growth responses were

observed in all treatments, which supports the presumed

E. coli–protozoa prey–predator relationship. For example, in

the stream water microcosms, the first prey amendment

resulted in an increase of 61 MPN protozoa mL�1 after 5

days, while the second prey amendment resulted in an

increase of 4431 MPN protozoa mL�1.

The numbers of cultivable E. coli cells in the microcosms

were also monitored after the second spike (i.e. from Day

20) to further illustrate the relationship between protozoan

predators and prey cells (Fig. 5b). The number of E. coli cells

in the beach sand microcosms remained significantly lower

than those in the soil and sediment microcosms (P � 0.10).

No correlation was observed between protozoa abundance

and E. coli die-off. For example, on Day 26, the protozoa

abundance in the beach sand sample was approximately 394

times lower than that in soil and five times lower than that in

sediment (Fig. 4a), while the E. coli died off faster in sand

than in the soil and sediment samples (Fig. 5b). The lack of a

correlation between protozoan abundance and E. coli die-off

further supports the conclusion that protozoa play an

insignificant role in E. coli die-off in beach sand.

Discussion

Biotic environmental stresses, albeit having received con-

siderably less attention than abiotic stresses, may play as

important a role as the abiotic stresses in the die-off of fecal

(a)

(b)

Fig. 5. Growth of protozoa in seawater beach sand, soil, freshwater

stream sediment, and stream water microcosms (a), and the die-off of

Escherichia coli prey cells (b). Symbols for different treatments are as

follows: ’, sediment; �, seawater beach sand; ., soil; and B, fresh

water. Error bars represent the SD of the log mean of triplicates.

Escherichia coli prey cells were added on day 0 and day 20, as indicated

by the arrows. In compartment A, ordinate value one corresponds to

below detection limit.

Fig. 4. The die-off of Escherichia coli over time in beach sand micro-

cosms in the presence of beach sand bacterial isolates. The symbols for

different treatments are as follows: hexagon, E. coli only; m, E. coli1

strain B1; ,, E. coli1strain B2; ’, E. coli1strain B3; B, E. coli1strain

B4; and�, E. coli1strain B5. Error bars represents the SD of the log mean

of triplicates.



indicators in the environment. Previous microcosm studies

that compared the survival of E. coli in sterile and nonsterile

soil, freshwater (Bogosian et al., 1996; Medema et al., 1997),

seawater (Carlucci & Pramer, 1961), and beach sand (Hartz

et al., 2008) often reported more than 10-fold faster die-off

rates of E. coli in the presence of the autochthonous

microbial community. Similar studies on E. faecalis also

reported that the removal of soil autochthonous microbial

communities drastically improved the survival of E. faecalis

(Medema et al., 1997; Andrews et al., 2004). Unlike the

studies on abiotic stresses where individual factors can be

easily separated and controlled experimentally, only a few

studies on biotic stresses attempted to separate the different

categories of environmental biotic stresses and determine

their relative contributions toward fecal indicator die-off.

This is mainly due to the technical difficulties associated

with separating and characterizing autochthonous environ-

mental microbial communities, which usually contain

enormous protozoan, bacterial, and phage diversities.

In this study, we utilized two commonly used experi-

mental approaches (i.e. cycloheximide inhibition and prey

addition) to examine the predator–prey interactions be-

tween protozoa and fecal indicators. Cycloheximide, as a

eukaryote-specific inhibitor, has been commonly used in

studying protozoan predation (Taylor & Pace, 1987). The

most commonly used inhibitory concentration is

100 mg L�1 (Sanders & Porter, 1986), while various concen-

tration ranges, for example 25–200 mg L�1 (Tremaine &

Mills, 1987), were reported to be effective in inhibiting

protozoa. Much higher concentrations of cycloheximide

were used previously in sediment studies (Davies et al.,

1995), presumably to counter the adsorption of cyclo-

heximide by organic matter in sediment. Owing to the low

organic content of beach sand and the low hydrophobicity

of cycloheximide (log Kow = 0.55), loss of cycloheximide

activity due to adsorption to sand particles is expected to

be minimal. The experimental results from the cyclohex-

imide inhibition experiments were supplemented and sup-

ported by prey cell addition experiments. By amending E.

coli prey cells to beach sand, it was demonstrated that

protozoa growth in beach sand was significantly hampered.

The insignificant protozoan predation observed in this

study contrasts with previous observations in other envir-

onments where protozoan predation plays an important

role in the die-off of E. coli (Pernthaler, 2005). Because

specific growth and die-off rates collectively determine

microbial population sizes in the environment, the absence

of any environmental stress may lead to increased popula-

tion densities. Therefore, the severely reduced protozoan

predation may provide a sound explanation for the high

numbers of fecal indicator cells observed in beach sand.

Follow-up experiments in the present study attributed the

insignificant protozoan contribution to their low abundance

level and limited growth potential in beach sand. Previous

studies have reported much smaller protozoan abundances

in sandy soils than in other types of soil (Dixon, 1936),

implicating grain sizes as a factor. The soil organic content

also controls protozoa abundance and activities (Anderson,

2005). Beach sands usually have much larger particle sizes

and lower organic contents than soils, which may be

responsible for the observed low protozoa activities.

The diminished protozoan predation stress in the beach

sand microcosms makes the antagonistic effects from the

autochthonous sand bacterial communities more promi-

nent. This phenomenon considerably differs from previous

observations in water, soil, and sediment environments,

where protozoan predation was often more important than

bacterial antagonistic effects to E. coli die-off (Enzinger &

Cooper, 1976; McCambridge & McMeekin, 1980). Cultiva-

tion-independent DGGE analyses and subsequent sequen-

cing revealed a fairly complex beach sand bacterial

community in the SI beach sand. The isolation efforts,

however, obtained bacterial isolates that did not match the

dominant populations identified by the DNA-based DGGE

analyses. This disparity between cultivation-dependent and

cultivation-independent analysis has been well documented

previously (Muyzer et al., 1993; Vladar et al., 2008). All the

bacterial isolates from the SI beach sand significantly

enhanced the die-off of E. coli in co-culturing microcosms.

Taken together, it is reasonable to conclude that the antag-

onistic effects from bacteria to E. coli die-off may be wide-

spread in autochthonous sand microbial communities.

Previous studies have identified different mechanisms of

bacterial antagonism; the present study, however, does not

provide direct evidence as to which mechanisms may be

relevant in the sand microcosms.

Bacteriophages that were separated from the other micro-

bial components by membrane filtration did not show

significant contributions to the die-off of E. coli in the beach

sand microcosms. This observation corroborates previous

studies in seawater where viruses (i.e. fraction passing 0.2-

mm filters) showed no deleterious effects while protozoa and

bacteria (i.e. fraction between 0.2 and 2.0 mm) caused rapid

die-off of E. coli (Penon et al., 1991). Previous works in

aquatic environments have shown that the effects of bacter-

iophages on E. coli survival are more pronounced under

nutrient-rich conditions (Carlucci & Pramer, 1960a). There-

fore, the observed minor contributions from bacteriophages

to E. coli die-off in beach sand may be attributable to the

oligotrophic conditions commonly found in beach sand

environments.

Because E. coli and E. faecalis are the two most commonly

used fecal indicators in water quality monitoring, their

different die-off rates in the beach sand microcosms warrant

further investigation. Previous studies have reported slightly

different, but overall comparable survival behaviors of E. coli


222 F. Feng et al.

and E. faecalis in aquatic (Gonzalez et al., 1992; Zmyslowska,

1993) and soil environments (Lau & Ingham, 2001; Andrews

et al., 2004). The present study observed that in beach sand,

the survival of E. faecalis was drastically more extended than

that of E. coli. This observation corroborates a recent study

by Yamahara et al. (2009), where intermittently wetted

seawater beach sand supported the growth of enterococci.

The extended survival of E. faecalis cells in the beach sand

microcosms may have significant implications in its role as a

common fecal indicator for beach water monitoring.

The present study used stationary-phase cells from

laboratory E. coli and E. faecalis strains in the die-off

experiments. Although cell homogeneity is essential for

laboratory testing, it should be noted that in the natural

beach sand environments, an enormous variety of different

fecal indicator strains are present and the cells may also be in

different physiological stages (Yang et al., 2004; Ishii et al.,

2006). These complicating factors need to be taken into

consideration when extrapolating results from studies using

single laboratory strains to the natural environment. The

microcosm experimental approach allows simplifying the

otherwise complex interactions between abiotic and biotic

stresses and enables the establishment of experimental

treatments under controlled laboratory conditions. How-

ever, it is worth noting that the fluctuations of abiotic

stresses in the natural environment, such as temperature

fluctuation, diurnal sunlight irradiation, etc. may also affect

the contributions from different biotic stresses. Therefore,

future work that uses environmental diffusion chambers

and large-scale field sampling efforts are necessary in order

to gain a more thorough understanding.

Acknowledgements

This work was funded in part by grants from the University

of Hawaii at Manoa and by grant 2009-35102-05212 from

USDA CSREES (to T.Y.). We thank Ms Bunnie Yoneyama

and Mr Tsu-chuan Lee for technical assistance in the

laboratory.

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