Enteric Adenovirus and Coliphage as Microbial Indicators in
Singapore's Kallang Basin
by
Tina Y. Liu
B.S. Civil Engineering
University of Maryland, College Park, 2011
Submitted to the Department of Civil and Environmental Engineering
in Partial Fulfillment of the Requirements for the Degree of
Master of Engineering
in Civil and Environmental Engineering
at the
MASSACHUSETTS INSifiTf"
OF TECH
cNOGY
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
JUN 13 201
June 2014
PSRAR
© 2014 Tina Y. Liu
All rights reserved.
The author hereby grants to MIT permission to reproduce and to distribute publicly paper and
electronic copies of this thesis document in whole or in part in any medium now known or
hereafter created.
Signature redacted
Signature of Author
Tina Y. Liu
Department of Civil and Environmental Engineering
May 9, 2014
Certified byignature
redacted
Peter Shanahan
Senior Lecturer of Civil and Environmental En ineering
II
Accepted by
A
Thesis
pervisor
Signature redacted_
Heidi M. Nepf
Chair, Departmental Committee for Graduate Students
I
9
Enteric Adenovirus and Coliphage as Microbial Indicators in
Singapore's Kallang Basin
By
Tina Y. Liu
Submitted to the Department of Civil and Environmental Engineering on May 9, 2014 in Partial
Fulfillment of the Requirements for the Degree of Master of Engineering in Civil and Environmental
Engineering
ABSTRACT
E. coli, Enterococci, and other fecal indicator bacteria have been the gold standard for assessing and
regulating water quality. However, the presence of these water quality indicators often do not reflect
the presence of viral pathogens, such as human enteric viruses, posing significant health risks to the
general population. Furthermore, high concentrations of E. coli are often found in tropical environments
with no apparent source of fecal contamination. In order to gain comprehensive insight on the
recreational water quality of Kallang Basin in Singapore, it is important to establish an understanding of
the interactions between pathogens and other microorganisms within the environment. This study
focuses on enteric adenovirus and coliphage (F' male-specific and somatic) as potential alternative
indicators of fecal contamination. Adenovirus and coliphage concentrations from water samples
collected over a 48-hour period were quantified using qPCR assay and cell culture methods, respectively,
and analyzed for trends. The presence of viruses was compared to that of E. coli and Enterococci from
the same samples.
The results from this study suggest significant fecal contamination originating from the tributaries that
flow into the Kallang Basin. E. coli and Enterococci concentrations at each station exceeded U.S. EPA
regulation standards, however, neither correlated with the presence of adenovirus. Additionally, there
was an overall trend of higher concentrations of microorganisms during the first 24-hours of sampling
than the second, potentially due to rainfall prior to sampling. The findings from this study emphasize the
need for further investigation of pathogenic microorganism to establish effective indices for recreational
water quality monitoring in the Kallang Basin.
Thesis Supervisor: Peter Shanahan
Title: Senior Lecturer of Civil and Environmental Engineering
2
ACKNOWLEDGEMENTS
While my name is on the cover of this thesis, none of this would have been possible without the support
and dedication of numerous others.
First, I would like to express the deepest appreciation to Pete for going above and beyond as a thesis
supervisor. You have been an amazing mentor and great friend this year.
To Justin, Allison, Riana, and Jia for all the adventures, some fun and some not-so-fun, we shared this
year in Singapore and at MIT.
To Ginger, Prof. Gin, and everyone at NUS for their warmth and hospitality during our time in Singapore.
To the M.Eng program and fellow students for creating an atmosphere of friendship and camaraderie
even during our short stay here at MIT.
To my family for their unwavering love and support from miles away.
To Andrew for being my cheerleader, therapist, chef, comedian, and everything in between.
And finally, these acknowledgements would not be complete without special recognition to the cast of
Disney's Frozen. Thank you for keeping my spirits up on those long days of writing and being the
soundtrack to my thesis.
3
TABLE OF CONTENTS
A b stra ct .........................................................................................................................................................
2
Acknowledgem ents.......................................................................................................................................3
L ist of F igu res ................................................................................................................................................
6
List o f Ta b le s .................................................................................................................................................
6
List of Appendix Figures................................................................................................................................7
List of Appendix Tables .................................................................................................................................
7
1 Intro du ctio n ...............................................................................................................................................
8
1.1 Singapore's W ater...............................................................................................................................
8
1.2 M arina Reservoir and Kallang Basin..............................................................................................
11
1.3 Scope of Study...................................................................................................................................12
2 Review of Pathogen Detection ................................................................................................................
13
2.1 Traditional M icrobial Indicators of W ater Quality ........................................................................
13
2.1.1 Total Coliform, Fecal Coliform, and E. coli ..............................................................................
13
2.1.2 Fecal Streptococci and Enterococci .......................................................................................
13
2.2 Choosing a M icrobial Indicator.........................................................................................................
13
2.3 Coliphage as a M icrobial Indicator................................................................................................
14
2.4 Enteric Virus as a M icrobial Indicator: Adenovirus........................................................................
15
3 M ethodology............................................................................................................................................17
3.1 Field Sampling...................................................................................................................................
17
3.2 Primary Concentration......................................................................................................................
20
3.3 Detection of Coliphage .....................................................................................................................
20
3.4 Detection of Adenovirus ...................................................................................................................
20
3.4.1 Secondary Concentration...........................................................................................................
21
3.4.2 Viral DNA Extraction...................................................................................................................
21
3.4.3 qPCR Detection ..........................................................................................................................
21
4 Results a nd Discussion .............................................................................................................................
24
4.1 Coliphage Results ..............................................................................................................................
25
4.2 Adenovirus Results............................................................................................................................
26
4.2.1 Calculating Genome Copies per Liter from Raw
4
CT
Value .....................................................
26
4.2.2 Adenovirus Detection ................................................................................................................
4.3 Comparison with Fecal Bacteria ................................................
27
28
5 Conclusions and Recom m endations....................................................................................................34
References ...
et.......................................................................................................................
36
Appendices ..................................................................................................................................................
39
Appendices ..................................................................................................................................................
39
Appendix I: Raw Data ..............................................................................................................................
39
Appendix II: Concentration and Dilution Factor Calculations..............................................................
42
5
LIST OF FIGURES
Figure 1-M ap of Singapore.........................................................................................................................8
Figure 2
-
Singapore's W ater M anagem ent.................................................................................................
9
Figure 3 - M ap of Singapore's Reservoirs and Rivers ..............................................................................
10
Figure 4 - M arina Reservoir Catchm ent ..................................................................................................
11
Figure 5 - Sam pling Stations in the Kallang Basin ..................................................................................
17
Figure 6 - Sam pling Station 2, Jalan Benaan Kapal.................................................................................
18
Figure 7 - Sam pling Station 3, Kallang Riverside Park ............................................................................
18
Figure 8 - Sam pling Station 4, Upper Boon Keng Road ..........................................................................
19
Figure 9 - Sam pling Station 5, Crawford Street.......................................................................................
19
Figure 10 - Hollow-fiber Filtration Setup................................................................................................
20
Figure 11 - Overview of TaqM an® Probe qPCR Assay............................................................................
22
Figure 12 - Sam ple Log Plot of Am plification Curves ..............................................................................
23
Figure 13 - Norm alized Results for Coliphage .........................................................................................
25
Figure 14 - Standard Curve for Adenovirus...........................................................................................
26
Figure 15 - Norm alized Results for Adenovirus.......................................................................................
27
Figure 16 - Norm alized Results for E. coli and Enterococci....................................................................
28
Figure 17 - Heat M ap of M icroorganism Concentrations .....................................................................
29
Figure 18 - Box Plot for Coliphage..............................................................................................................
30
Figure 19 - Box Plot for E. coli and Enterococci.......................................................................................
31
Figure 20 - Box Plot for Adenovirus ...........................................................................................................
32
LIST OF TABLES
Table 1 - PCR Techniques ...........................................................................................................................
15
Table 2 - Prim er Inform ation for Adenovirus qPCR.................................................................................
23
Table 3 - Adenovirus Detection in Kallang Basin.....................................................................................
27
6
LIST OF APPENDIX FIGURES
Figure A-1 - Raw Data Plot for Coliphage ...............................................................................................
39
Figure A-2 - Raw Data Plot for Adenovirus..............................................................................................
40
Figure A-3 - Raw Data Plot for E. coli and Enterococci..........................................................................
41
Figure A-4 - Flow Chart for Concentration and Dilution of Raw Water Sample ...................................
42
LIST OF APPENDIX TABLES
Table A -1
-
Coliphage Raw D ata .................................................................................................................
39
Table A -2 - A denovirus Raw D ata...............................................................................................................
40
Table A-3 - E. coli and Enterococci Raw Data.........................................................................................
41
7
1
INTRODUCTION
Singapore is a tropical island nation located on the southern tip of the Malay Peninsula in Southeast
Asia. Spanning over 700 square kilometers (kM 2 ), Singapore is comprised of many islands, including the
main island known as Singapore Island, or Palau Ujong (Figure 1). The city-state has a population of
approximately 5.4 million as of June 2013, making it one of the most population-dense countries in the
world (Government of Singapore 2013). With a thriving economy and high standard of living, Singapore
is one of the wealthiest nations in the world.
IyIqA
Figure 1 - Map of Singapore (University of Alabama Cartographic Research Lab 2014; Wikipedia 2014)
1.1 Singapore's Water
The rapid population and economic growth in recent decades has put pressure on Singapore's limited
natural water resources. The current demand of 400 million gallons a day (MGD) is expected to double
by 2060 (PUB 2013). In view of inevitable deficits down the road, Singapore's Public Utilities Board (PUB)
has spent the past 50 years developing and diversifying the national water sources to secure a
sustainable water supply. Coined the "Four National Taps," the four sources consist of imported water,
reclaimed NEWater, desalinated seawater, and local catchment water (Figure 2) (PUB 2013).
8
A
I
7
/
~
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Treatment of
Used Water
Desalination
NEWater
Collection of
Used Water
1/
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U
S
Treatment of
Raw to Potable
Water
-*
+
'A=
Supply of
Water to the
Uopu
latone
Industries
Indirect Potable Use
Direct Non-Potable Use
Figure 2 - Singapore's Water Management (NCCS 2012)
Singapore signed two water agreements with Malaysia's Johor State Government in the 1960s. The first
agreement in 1961 allowed Singapore to draw water from designated lands until 2011. In 1962, a new
agreement gave Singapore rights to draw a maximum of 250 million gallons a day (MGD) from the Johor
River until 2061 (National Library Board Singapore 2014). Relying on Malaysia has created political
tension between the two countries. This, coupled with exponential water use projections, has spurred
PUB's strong determination to have complete water self-sufficiency before the expiration of the 1962
agreement. As research and development for the other three "taps" has progressed, PUB has started to
shift away from using imported water.
9
In 2003, PUB introduced NEWater, a highly-treated, reclaimed water source that exceeds World Health
Organization (WHO) and the United States Environmental Protection Agency (U.S. EPA) drinking water
standards. Using purification techniques such as microfiltration, reverse osmosis, and ultraviolet
disinfection to treat wastewater, the NEWater plants currently meet 30% of the water demand;
however, PUB hopes to expand capacity and eventually have the NEWater plants producing 55 percent
of the nation's water by 2060 (PUB 2013).
Desalination, the removal of salts and other minerals from seawater to produce freshwater, has been
another promising alternative water source in Singapore. With the recent opening of Tuaspring
Desalination plant, the largest of its kind in Asia, PUB moves forward with the plan to have desalinated
water meet 25 percent of the water demand (Boon 2013).
The final "tap" in Singapore's water supply, which will be the focus of this study, comes from the local
catchments that span two-thirds of the land surface. Rainwater and surface water runoff are collected in
17 reservoirs on the island and then treated before use in the water supply (Figure 3). Continuing with
their catchment master plan, PUB plans to dam the remaining streams and canals to reach a water
catchment area of 90 percent by 2060 (PUB 2013).
Figure 3 - Map of Singapore's Reservoirs and Rivers (PUB 2012)
As part of their Active, Beautiful, Clean Waters (ABC Waters) Programme, PUB wants to open these
reservoirs for recreational activities such as kayaking, windsurfing, and dragon boating. They hope that
having pristine parks for the community to enjoy will not only enhance public awareness and
appreciation of a vital and valuable resource, but also conserve water and reduce pollution in the
waterways. One reservoir of particular importance is the Marina Reservoir. Located in the most denselyurbanized areas of the city, Marina Reservoir has been the most challenging reservoir project due to its
susceptibility to pollution and visibility in the public's eye (PUB n.d.).
10
1.2 Marina Reservoir and Kallang Basin
The Marina Barrage was unveiled in 2008, changing the once saline Marina Bay and Kallang Bay into a
freshwater reservoir known as the Marina Reservoir. Situated in the heart of downtown Singapore,
Marina Reservoir is the island's 1 5th reservoir and has the largest catchment area of 10,000 hectares
(ha). Five main tributaries flow into Marina Reservoir: Singapore River, Stanford Canal, Rochor Canal,
Kallang River, and Geylang River (Figure 4).
Figure 4 - Marina Reservoir Catchment (dark green) (Nauta et al. 2008)
With five historically polluted rivers feeding into the reservoir, the industrial background of the area
raises questions about the current water quality. In the 1800s, the Marina Bay area was home to an
economic boom which prompted the development of financial institutions and commercial industries
along its banks. The flourishing commercial activity and growing population exacerbated existing
pollution problems and by the mid-1970s, the waterways had become an open sewer. Finally, in 1977,
the government began a 10-year river cleanup program for the Singapore River and Kallang Basin, the
two most polluted water bodies in the city (Hon 1991). This extensive program relocated the
commercial industries, developed new infrastructure to house those affected by the relocation, and
11
cleaned the waterways. The Marina area saw much improvement through these efforts, and Kallang
Basin was eventually transformed into a riverside park (Nauta et al. 2008).
Despite the rehabilitation, there are concerns that the historical pollution in the area may undermine
the water quality of Marina Reservoir. To deal with this issue, PUB has imposed guidelines to control
pollution, establish mitigation strategies, develop a water quality modeling and monitoring system, and
educate the public about pollution through their ABC Waters Programme (Nauta et al. 2008). PUB has
additional concerns that bacterial and viral pathogen levels in storm water runoff are high and may pose
risks to people using the reservoir for water-contact activities. Because of these reasons, routine
monitoring for pathogens is necessary to determine water quality.
1.3 Scope of Study
As part of the plan to open Kallang Basin for recreational purposes, PUB requested a water sampling
program to monitor microbial water quality, specifically viral pathogens and microbial water quality
indicators.
Traditionally, microbial water quality indicators are bacteria that reflect the presence of fecal
contamination in water. Testing water for all pathogens would be extremely expensive and timeconsuming, so having a comprehensive selection of indicators can be invaluable to water quality control.
Some common examples of indicator bacteria are Escherichia coli (E. coli), Enterococci, and other fecal
coliform. However, it has been found that these indicators can be unreliable in tropical environments,
like Singapore's, due to their natural growth in soils and waters (Lopez-Torres et al. 1987). In addition,
they do not always reflect the risk from viral pathogens such as human enteric viruses, which cause
gastrointestinal infections even at low concentrations (Fong and Lipp 2005). Because of these
limitations, it is important to consider potential alternatives to supplement traditional indicators. One
possible alternative is coliphages, which are bacteriophages that infect E. coli. Coliphages are naturally
present in human feces and sewage and are more resistant to environmental stresses than E. coli
(Borrego et al. 1990). They may also be used to determine risk from enteric viruses (Simkovs and
Cervenka 1981; Stetler 1984). Another alternative is to look at enteric viruses themselves and use direct
detection methods to assess risk.
This study focuses on the detection of coliphages and adenovirus because of their potential to be better
human viral contamination indices in the Kallang Basin. These results were compared to those of
traditional bacterial indicators. The field study was completed in collaboration with Justin Angeles and
Allison Park from the Massachusetts Institute of Technology (MIT) and with Professor Karina Gin's
students at the National University of Singapore (NUS). The laboratory analysis of this study was
completed in collaboration with Genevieve Vergara of NUS.
12
2 REVIEW OF PATHOGEN DETECTION
The concept of using bacteria as indicators of water quality can be traced back to 1891 when Percy and
Grace Frankland first identified the importance of characterizing microorganisms that consistently
appear in sewage and correlating them with potential water pollution (Ashbolt et al. 2001). Since then,
indicator technology has progressed considerably to accommodate the range of pathogens present in
water bodies.
2.1 Traditional Microbial Indicators of Water Quality
Among the types of microbial indicators used for determining water quality, bacterial indicators have
been considered the standard. While they do not cause illness themselves, the presence of these
bacteria in water often correlates with that of other pathogens. Because these pathogens typically
originate from feces of humans or animals, occurrence of bacterial indicator species can be a sign of
poor water conditions.
2.1.1 Total Coliform, Fecal Coliform, and E. coli
Coliform bacteria can be found in environmental soil and water as well as feces of animals and humans.
They are relatively simple to culture in the laboratory which makes them the standard indicator for
many regulatory agencies. Total coliform consist of all coliform bacteria and can imply possible water
contamination. While total coliform is no longer used as an indicator in recreational waters, its presence
in drinking water can be a sign of contamination from an outside source (U.S. EPA 2012a). Fecal
coliform, a subgroup of total coliform bacteria, are only found in animal and human feces and often
indicate recent fecal contamination. E. coli is a single species of fecal coliform. Existing naturally in the
intestine, E. coli is considered a suitable indicator for fecal contamination and possible pathogen
presence since it is the only coliform that solely originates from fecal sources (Lin and Ganesh 2013). The
U.S. EPA (2012) recommends using E. coli as the indicator in recreational waters. Total coliform and E.
coli can be detected and quantified using the Colilert* test (IDEXX Laboratories, Westbrook, Maine,
USA).
2.1.2 Fecal Streptococciand Enterococci
Like coliform bacteria, fecal streptococci are bacteria found in the intestine of warm-blooded animals.
Yet, unlike coliform, they do not generally proliferate in the environment and tend to survive for longer
(Lin and Ganesh 2013). Enterococci are a subgroup of fecal streptococci that are particularly resilient in
salt water and specific to humans. The U.S. EPA (2012) recommends using Enterococci as the indicator in
recreational salt waters. Enterococci can be detected and quantified using the Enterolert* test (IDEXX
Laboratories, Westbrook, Maine, USA).
2.2 Choosing a Microbial Indicator
There are several criteria that need to be considered when choosing a microbial indicator for pathogens
in water (Borrego et al. 1990; Goyal 1983; Stetler 1984).
(a) The indicator should be present when the pathogen is present and absent when the
pathogen is absent.
13
(b) The indicator should have similar growth patterns and qualities as the pathogen.
(c) The indicator and pathogen should occur at a constant ratio.
(d) The indicator should be present in higher concentrations than the pathogen.
(e) The indicator should have similar resistance to environmental factors and disinfectants.
(f) The indicator should be nonpathogenic and easy to quantify.
(g) The indicator test should be applicable to all types of water.
(h) The indicator test should only detect the indicator.
Indicators organisms such as E. coli and Enterococci have been the norm for examining water quality;
however, these traditional indicator systems may not be the ideal system, especially in tropical
environments. Fecal coliform bacteria are often found naturally in soils. Lopez-Torres et al. (1987)
determined that fecal coliforms such as E. coli can survive for long periods of time in tropical freshwater
environments. They were able to isolate two genera of bacteria without any source of fecal pollution
indicating that it is possible for E. colito become a natural part of tropical freshwater environments,
raising further questions about the efficacy of using fecal coliform water quality indicators in tropical
environments.
In addition, bacterial indicators do not always reflect the risk associated with viral pathogens such as
enteric viruses (Fong and Lipp 2005). There have been cases where enteric viruses have been isolated
from environments that had been deemed safe by bacterial indicators. Enteric viruses are often the
culprit behind outbreaks from contaminated drinking water, recreational waters, urban rivers, and
shellfish harvested from contaminated waters. They do not occur in normal fecal microbiota; instead,
enteric viruses are only excreted by infected individuals, contributing to the host of pathogens
circulating in the sewage system (Ashbolt et al. 2001). Because of incomplete removal of viral pathogens
in treated wastewater, these viruses often enter the drinking water system through sewage and
wastewater discharge (Bosch 1998).
2.3 Coliphage as a Microbial Indicator
Due to the challenges of using traditional indicators in tropical waters, researchers have been searching
for better indicators to determine water quality and quantify risk from bacteria and enteric viruses. One
potential alternative that has been proposed is coliphages, viruses that infect E. coli. Two main groups of
coliphages are male-specific (F+) coliphage and somatic coliphage which are found in human and animal
feces (Scott et al. 2002; U.S. EPA 2001a). Male-specific (F+) coliphages are viruses that infect through the
F-pilus of male strain E. coli and somatic coliphages are viruses that infect the outer cell membrane of E.
coli host cells (U.S. EPA 2001b). These two coliphage types can easily be detected in the laboratory using
culture methods determined by the U.S. EPA.
Male-specific (F') coliphages are divided into four main groups: group I, group II, group Ill, and group IV.
Groups I and Ill are often associated with human fecal contamination and domestic sewage, while
group IV indicate incidence of animal and livestock waste. Group I coliphages are present in both human
14
and animal feces and sewage. Genotyping of male-specific (F+) coliphages can be used for tracking the
source of fecal pollution (Scott et al. 2002).
Somatic coliphages may be suitable enteric virus indicators since they exhibit similar behavioral patterns
and resistances to environmental stresses as viruses (Borrego et al. 1987; Lin and Ganesh 2013; Simkovd
and Cervenka 1981). When coliphages were monitored with enteroviruses and indicator bacteria, it was
found that the presence of enterovirus was better correlated with the presence of somatic coliphage
than with indicator bacteria such as total coliforms, fecal coliforms, and other standard bacterial
indicators (Stetler 1984). The presence of somatic coliphage followed similar patterns as the presence of
enterovirus, and the two were removed at a similar rate during water treatment processes such as
chlorination. Additionally, the somatic coliphage concentrations were in excess of enterovirus
concentrations, allowing for better sensitivity during testing. Somatic coliphage also appear five times
more frequently in the environment than male-specific (F+) coliphages making them easier to detect (Lin
and Ganesh 2013).
Some researchers have reservations about the validity of using somatic coliphages as water quality
indicators because they can replicate and originate in the environment and thus may not correctly
reflect fecal contamination (Borrego et al. 1990; Jofre 2009). However, in his review, Jofre (2009)
concluded that any replication of somatic coliphages outside the gut and in the environment has
negligible influence on the number detected in the environment with standard methods and should not
be a limitation in using somatic coliphages as water quality indicators.
2.4 Enteric Virus as a Microbial Indicator: Adenovirus
Another potential alternative for pathogen detection is using direct detection of enteric viruses to
determine water quality. There are over 100 different enteric viruses that are associated with
gastrointestinal infection in humans (Scott et al. 2002). Some commonly studied enteric viruses in water
quality analysis are poliovirus, enterovirus, hepatitis A, norovirus, rotavirus, and adenovirus. By
monitoring enteric viruses directly, uncertainties and issues of using bacterial fecal indicators can be
avoided. Molecular methods such as polymerase chain reaction (PCR) can be used to detect viruses that
do not replicate well in cell cultures (Pina et al. 1998). Specific PCR techniques are shown in Table 1.
Table 1- PCR Techniques
PCR
RT-PCR
(reverse transcription)
qPCR
(quantitative)
qRT-PCR
(quantitative reverse
transcription)
Determine presence
of DNA virus
Determine presence
of RNA virus
Quantify DNA virus
Quantify RNA virus
15
Amplify nucleic acid of
DNA virus
Amplify nucleic acid of
RNA virus
Amplify nucleic acid of
DNA virus and detect
fluorescence emission
Amplify nucleic acid of
RNA virus and detect
fluorescence emission
Of the common enteric viruses, adenovirus (a DNA virus) has been suggested as a promising index of
fecal pollution because of its persistence and prevalence in sewage and contaminated waters (Fong and
Lipp 2005; Hamza et al. 2009; Pina et al. 1998). There are currently 51 known serotypes of adenovirus
which are classified into six species, A-F (Lin and Ganesh 2013). Adenovirus species F has been found to
be more resistant to ultraviolet irradiation and other water treatment processes than other enteric
viruses (Hewitt et al. 2013; Meng and Gerba 1996; Pina et al. 1998). Pina et al. (1998) found that
presence of adenovirus in sewage samples significantly correlated with the presence of hepatitis A and
other human-specific bacteriophages, and wastewater treatment processes do not completely remove
it. Furthermore, adenoviruses can be detected throughout the year whereas other enteric viruses, such
as enterovirus and rotavirus, show seasonal fluctuations (Lin and Ganesh 2013; Pina et al. 1998).
16
3 METHODOLOGY
3.1 Field Sampling
Field work for this study was completed during a 48-hour sampling program on January 7-9, 2014. As
part of the field study, a MIT team participated in the joint sampling program with Prof. Karina Gin's
students from NUS. Water samples of 20 L were taken from the Kallang Basin from four different
sampling stations: (2) Jalan Benaan Kapal, (3) Kallang Riverside Park, (4) Upper Boon Keng Road, and (5)
Crawford Street (Figure 5 to Figure 9). The (1) Tanjong Rhu View sampling station was only used for algal
analysis. These 48 samples were taken at four-hour intervals over the course of the two days starting at
11:00 AM on January 7. The water samples were collected using the grab-sampling method and
processed in the laboratory. The laboratory analysis was completed in collaboration with the Gin
laboratory at NUS.
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Figure 5 - Sampling Stations in the Kallang Basin (Google Maps 2014)
17
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Figure 6 - Sampling Station 2, Jalan Benaan Kapal (Vergara 2014)
Figure 7 - Sampling Station 3, Kallang Riverside Park (Vergara 2014)
18
Figure 8 -Sampling Station 4, Upper Boon Keng Road (Vergara 2014)
Figure 9 - Sampling Station 5, Crawford Street (Vergara 2014)
19
3.2 Primary Concentration
In the laboratory, the 20-L water samples were filtered and concentrated using hollow-fiber filtration
(Figure 10). The recommended hollow-fiber filter is a Fresenius Polysulfone* Hemoflow F80A (Fresenius
Medical Care Deutschland GmbH, Germany), however due to its unavailability in Singapore, the
Hemoflow HF80S was used instead. The filter was connected to a peristaltic pump and equilibrated for
10 min with deionized H20 prior to loading each sample. The experimental sample was pumped through
the machine and filter; the permeate passed through the filter fibers and was collected in a waste
container, while the retentate was retained and recirculated until the sample volume was reduced to
100 mL. Remaining sample was eluted through a 10-min recirculation cycle of 300-mL glycine (0.05 M),
which was added to the initial permeate.
Peristaltic pump
Fresenius
0 Polysulfone*
Hemoflow HF80S
Permeate
Retentate
20 L
sample
Waste
Figure 10- Hollow-fiber Filtration Setup
3.3 Detection of Coliphage
After the primary concentration, the samples were immediately tested for presence of male-specific (F')
and somatic coliphage using U.S. EPA Method 1602. Method 1602 is a quantitative single agar layer
(SAL) procedure used for enumerating male-specific (F') and somatic coliphages.
Water samples were collected for each of the two coliphage types in plastic bottles and stored at 40 C
prior to the procedure. MgCI 2, log-phase host bacteria (E. coli Famp for the male-specific coliphage and E.
coli CN-13 for the somatic coliphage), and tryptic soy agar were added to the sample and thoroughly
mixed as described in Method 1602. The total volume was then poured into five to ten plates and
incubated overnight. Circular lysis zones, or plaques, indicated the presence of coliphages and were
quantified per plate and expressed as plaque-forming units (PFU) per 100 mL. Coliphage-positive and
negative reagent water served as positive and negative controls, respectively, and were analyzed for
each type of coliphage (U.S. EPA 2001c).
3.4 Detection of Adenovirus
To detect and quantify adenovirus, the water samples were further concentrated and purified. The 200mL samples from the primary concentration underwent a secondary concentration process to prepare
20
for DNA extraction. The extracted DNA was then used in a quantitative PCR procedure to determine
adenovirus quantity.
3.4.1 Secondary Concentration
After the primary concentration, the concentrated sample was subjected to secondary concentration to
eliminate contaminants and isolate the viruses for DNA extraction. Polyethylene glycol (PEG-8000) was
added to 200 mL of the primary concentrated sample for a final concentration of 8%, while sodium
chloride (NaCI) was added for a final concentration of 0.3 M. The resulting solution was incubated at 4"C
for 18 h. After incubation, the sample was split into four 50-mL tubes and then centrifuged at 14,000 g
at 4*C for 30 min. The supernatant was discarded and the pellet was re-suspended with 2.5 mL of
phosphate-buffered saline (PBS). The four fractions were consolidated into 10-mL samples. Equal
volumes (10 mL) of chloroform were added to each sample and agitated before centrifugation at 1,700 g
at 40 C for 30 min. The supernatant was collected and filtered through a 0.2-pm Minisart* High Flow
syringe filter (Sartorius Stedim Biotech, Aubagne, France). Finally, the resulting filtrate was concentrated
through centrifugation at 4,000 g at 4*C for 10 min in an Amicon* Ultra-15 Ultracel-50K centrifugal filter
unit (EMD Millipore, Billerica, Massachusetts, USA). The final volume ranged from 500-1000 pl.
3.4.2 Viral DNA Extraction
Enteric viruses can be either RNA or DNA viruses. While this study only focuses on adenoviruses, a DNA
virus, it was important to preserve RNA for other studies. Thus, the samples were prepared with the
QlAamp* Viral RNA kit (QIAGEN GmbH, Venlo, Limburg, Netherlands), which extracts both RNA and
DNA, instead of the QlAamp* Viral DNA kit, which only extracts DNA.
The buffers AVL, AW1, AW2, AVE, and carrier RNA were prepared according to the manufacturer
instructions. The viral nucleic acid was purified using the spin protocol. The samples were first lysed
using AVL to inactivate any ribonucleases (RNases), which are nucleases that catalyze nucleic acid
degradation. The AVE buffer is a RNAse-free water containing sodium azide that decreases microbial
growth and contamination with RNAses. It is used to dissolve the carrier RNA at the beginning of the
protocol and to elute the viral nucleic acid during the last step. Carrier RNA enhances nucleic acid
binding to the membrane and further reduces chances of degradation. AW1 and AW2 are two different
wash buffers used to remove impurity of the samples. The extraction yielded a 60-p solution containing
at least 90% of the viral nucleic acid (Qiagen 2010).
3.4.3 qPCR Detection
After the nucleic acid was extracted from the samples, they were prepared for qPCR using the
quantitative TaqMan* qPCR assay described by Jothikumar et al. (2005) to detect and quantify human
adenovirus serotypes 40 (AdV40) and 41 (AdV41).
The standard curves were generated using stock adenovirus. The TaqMan* probe was created using
specific forward and reverse primers for adenovirus to amplify a 96-base pair fragment of the hexon
gene region. This probe was labeled with a reporter fluorescent dye on the 5' end and a quencher on the
3' end (Life Technologies 2013). A reporter dye (FAM) is the fluorescent dye that indicates how much
DNA of a specific sequence is present while the quencher (NFQ-MGB) suppresses the fluorescence from
21
the reporter dye. The reporter dye only emits its fluorescence when it is detached from the quencher
during the elongation step when the DNA polymerase cleaves the probe (Figure 11).
Template DNA
3
5'
5'1
Denaturation
3'
.
...........
I ..
...
..
.....
...
1_.I ..
..
..
...
....
.I ......
. ...
.....
....
...
-_................
I...
.
. 3'
5
Annealing
3'
5
Forward Primer
Reverse Primer
i1-7I
YrfProbe
S
3'
5#
...
...
- .3 '0
. 1.1
I ......
'
Extension/Elongation
5,
Cleavage
Figure 11- Overview of TaqMan* Probe qPCR Assay
Real-time TaqMan* PCR assays were performed on the extracted DNA using the QuantiTect Probe PCR
kit (QIAGEN GmbH, Hilden, Germany) in a StepOnePlus Real-Time PCR System (Applied Biosystems,
Foster City, California, USA). FastStart Universal Probe Master ROX (Roche Applied Science, Indianapolis,
Indiana, USA), adenovirus forward and reverse primers (Integrated DNA Technologies, Coralville, Iowa,
USA), and the FAM/NFQ-MGB probe (Integrated DNA Technologies, Coralville, Iowa, USA) were used to
22
complete the amplification reaction. The procedure took approximately 90 min starting with a hot-start
denaturation step at 95 0 C for 15 min, and then 40 cycles with the following steps: (1) a 95 0 C
denaturation step for 10 s, (2) a 55*C annealing step for 30 s, and (3) a 72 0 C elongation step for 15 s
(Jothikumar et al. 2005). After the 40 cycles, there was a final cooling step at 400 C for 30 s.
Table 2 - Primer Information for Adenovirus qPCR
V4 u
AdV40, AdV41
ucin
F
R
Probe
eune('-'
GGACGCCTCGGAGTACCTGAG
ACIGTGGGGTTCTGAACTTGTT
FAM-CTGGTGCAGTTCGCCCGTGCCA-BHQ1
aepir
96
eeec
Jothikumar et
al. 2005
At the end of amplification, the fluorescence level of the probe was evaluated by the PCR system. The
more fluorescence present, the more viral DNA had been replicated. The final results for each sample
were represented by a threshold cycle value (C), which is the cycle number when the fluorescent signal
crosses a level that reflects a significant increase over a baseline signal (Figure 12).
10
1
i
Threshold
1004
10-1-
Baseline
10-4
10-
I
1
F
5
1
10
Ct Ct C C,
I
I
15
20
25
I
30
35
Cycle number
Figure 12 - Sample Log Plot of Amplification Curves (Invitrogen n.d.)
23
40
45
4 RESULTS AND DISCUSSION
The water samples from the Kallang Basin were tested for presence of coliphages, adenovirus, E. coli,
and Enterococci. All pathogen data were normalized using the peak concentrations for ease of
comparison. The raw data values and corresponding graphs can be found in the Appendix 1.
24
4.1 Coliphage Results
The concentrations of both male-specific (F') and somatic coliphages at the four stations were
quantified by Vergara (2014) at NUS. The concentrations of coliphage ranged from 2 to 156 PFU/100 mL
for male-specific (F+) and 30 to 640 PFU/100 mL for somatic. For both male-specific (F') and somatic
coliphages, the times of high and low concentrations correlate well among the four stations (Figure 13).
Additionally, there is a particularly strong peak for both types of coliphages during the first 24-hour
sampling period (at 1/8/2014 0:00 in Figure 13). Somatic coliphage seem to have a stronger presence in
the samples, with peak values of the somatic coliphage roughly five times those of the male-specific (F+)
coliphage. These results are consistent with the literature.
Station 2
Station 3
- ---
Station 4
-e-
Station 5
120%
Male-specific (F) Coliphage
200
100%
E
E 80%
150
'U
100
60%
40%
50
20%
0%
0
-
1/7/2014 0:00
1/7/2014 12:00
1/8/2014 0:00
1/8/2014 12:00
1/9/2014 0:00
1/9/201 4 12:00
Time
120%
-
Somatic Coliphage
100%
600
500
E
E 80%
4.
700
60%
400
\
300
40%
200
20%
100
0
0%
1/7/2014 0:00
1/7/2014 12:00
1/8/2014 0:00
1/8/2014 12:00
1/9/2014 0:00
1/9/2014 12:00
Time
Figure 13 - Normalized Results for Coliphage. Normalized concentrations of male-specific (F+) coliphage (top) and
somatic coliphage (bottom) with bar graph indicating peak concentrations (in PFU/100 mL) for each station.
25
4.2 Adenovirus Results
During PCR amplification of DNA, the number of genes present from a specific sequence double after
every cycle, resulting in exponential growth. The initial quantity of an experimental sample can
be
calculated through the use of a standard curve, developed using known quantities of end-products
and
the threshold cycle for their respective detection. As part of the quantitative PCR assay conducted for
this study, the quantity of DNA was quantified after each cycle by measuring the fluorescence
and
reporting the threshold cycle value, CT. The CT was then compared to a standard curve, generated
using
a serial dilution of stock adenovirus by Vergara (2014) at NUS, to determine the accumulation of genetic
material (Figure 14).
45
R2 =0.9995
40
35
30
25
20
15
10
5
0
L
1E+0
--
-
-
--
-
-
__
1E+4
1E+2
_
__
1E+6
_
-
1E+8
-------
1E+10
GC
Figure 14 - Standard Curve for Adenovirus (Vergara 2014)
4.2.1 Calculating Genome Copies per Liter from Raw CT Value
After the amplification, CT values were evaluated for each sample. The adenovirus threshold detection
limit was found to be 3 genomic copies (GC) per reaction at a CT of 38.41±1.59 cycles (Vergara 2014).
Following standard practice, the logarithmic equation calculated from the standard curve was used to
correlate CT with GC (Equations 1 and 2).
CT = -3.604log(GC)
GC = 10
+ 41.421
(1)
CT-41.421
(2)
-3604
To calculate genome copies per 100 milliliters of water from the Kallang Basin, the GC value must be
corrected by a concentration-dilution factor of 4.35 (Equation 3).
26
C-T-41.421
GC/100 mL = 4.35*
10
-304
)(3)
This factor accounts for the adjusted sample volumes during the DNA extraction and the 10x dilution
of
the DNA during qPCR preparation. See Appendix 11 for concentration and dilution factor calculations.
4.2.2 Adenovirus Detection
While adenovirus was detected at all four sampling stations in the Kallang Basin, it was detected more
frequently at Stations 2 and 5 (Table 3). The detection limit for the qPCR assay is 3 GC/reaction which is
equivalent to 13.1 GC/100 mL. Thus, samples indicated as undetected (-) had concentrations below this
threshold. For these undetected concentrations, a value of half the detection rate was assumed. The
detected concentrations varied from 19 to 546 GC/100 mL of water. Despite having lower detection
rates than Stations 2 and 5, Station 4 had the highest peak concentration of all the stations (Figure 15).
Station 3 had the lowest detection rate for adenovirus even though it is located directly downstream of
Station 4, which had higher detection rates. Perhaps the distance and volume of water between the two
stations allowed for degradation or dilution of adenovirus concentrations before reaching Station 3.
Table 3 - Adenovirus Detection in Kallang Basin
2
+
3
-
4
+
-
5
+
+
+
+
+
Station 2
+
-
+
+
+
+
+
-e'-
Station 3
+
+
-t+
Station 4
+
+
+
+
+
+
+
+
-+- Station 5
120%
Adenovirus
100%
600
500
E
E 80%
400
'U
60%
300
40%
200
+J
100
20%
0
0%
1/7/2014 0:00
1/7/2014 12:00
1/8/2014 0:00
1/8/2014 12:00
1/9/2014 0:00
1/9/2014 12:00
I
I
Time
Figure 15 - Normalized Results for Adenovirus. Normalized concentrations of adenovirus with bar graph indicating
peak concentrations (in GC/100 mL) for each station.
27
4.3 Comparison with Fecal Bacteria
The presence of coliphage and adenovirus was compared with the occurrence of the traditional
microbial indicators, E. coliand Enterococci. E. coli and Enterococci quantification was performed by
Angeles (2014) at NUS. E. coli concentrations spanned from 56 to 19,866 most probable number (MPN)
per 100 milliliters, while Enterococci concentrations were from 5 to 2,420 MPN/100 mL. E. co/i was
present in higher concentrations mostly at the beginning and end of the sampling period. However,
Station 2 exhibited high levels of E. coli around noon of the second sampling day. Many of the samples
indicated Enterococci concentrations of 2,420 MPN/100 mL, or the maximum possible reported value
for the Quanti-Tray*/2000 (IDEXX Laboratories, Westbrook, Maine, USA) procedure. This means that the
actual concentrations could be much higher and the three sampling points between midnight and noon
on January 8 for Station 5 may be part of a larger and wider peak (Figure 16). The Enterococci
concentration trends among the stations closely resemble each other.
Station 2
Station 3
-+-Station 4
-.-
Station 5
120%
E. coli
25000
100%
20000
E
E
80%
15000
2 60%
10000
40%
CL
5000
20%
0 L
0%
1/7/2014 0:00
1/7/2014 12:00
1/8/2014 0:00
1/8/2014 12:00
1/9/2014 0:00
1/9/2014 12:00
Time
120%
Enterococci
100%
3000
2500
E
80%
2000
2 60%
1500
40%
1000
20%
0%
1/7/2014 0:00
1/7/2014 12:00
1/8/2014 0:00
1/8/2014 12:00
1/9/2014 0:00
1/9/2014 12:00
Time
Figure 16 - Normalized Results for E. coli and Enterococci. Normalized concentrations of E. coli (top) and
Enterococci (bottom) with bar graph indicating peak concentrations (in MPN/100 mL) for each station.
28
As previously mentioned, the concentrations of each microorganism were normalized by the peak value
at each station. These normalized values were then used to generate a heat map, providing a visual
representation of the changes in concentrations overtime (Figure 17). Red and orange indicate higher
normalized values, while yellow and green represent lower normalized values. The heat map draws
attention to the higher density of reds and oranges representing higher concentrations during the first
24 hours of sampling (above the dotted horizontal line in Figure 17). The second 24 hours of sampling
(below the dotted horizontal line) yielded more yellows and greens which signify lower values. To
evaluate whether there was a significant shift in pathogen presence over time, the data were analyzed
to assess differences on either side of an arbitrary separation time ("cut-off time"). Different cut-off
times were tested for statistical significance (p<0.05) using a two-tailed t-test. The p-values were
calculated for different cut-off times and it was evident that the most significant (p=0.0000014) change
in concentration of the microorganisms was between the first 24-hour sampling period (January 7 11:00
to January 8 7:00) and the second 24-hour sampling period (January 8 11:00 to on January 9 7:00). This
is the time marked by the dotted horizontal line in Figure 17.
Station 2
F
0
S
Ec
Station 3
En
A
F
S
Station 4
Ec En
A
F
S
Ec
Station 5
En
A
F
S
Ec
En
A
p -value
1/7/2014 11:00
1.7E-04
1/7/2014 15:00
1.8E-04
1/7/2014 19:00
1/7/2014 23:00
/
4:.
1/8/2014 3:00
2.OE-03
1/8/2014 7:00
-06
1/8/2014 11:00
9.8E-03
3.4E-05
......
2.1E-05
1/8/2014 15:00
9.6E-04
-a 1/8/2014 19:00
0
1/8/2014 23:00
6.9E-04
2.7E-02
0-
1/9/2014 3:00
6.2E-01
1/9/2014 7:00
F = Male-specific (F+) coliphage, S Somatic coliphage, Ec = E.col, En
= Enterococci,
A = Adenovirus
Figure 17 - Heat Map of Microorganism Concentrations
To further emphasize the concentration variation over the first and second 24-hour sampling periods,
"box-and-whisker" plots for each microorganism were generated (Figure 18 to Figure 20). As previously
discussed, the first period was selected to include times between the beginning of sampling and the
most significant cut-off time (which was 24 hours into the sampling program), while the second period
was from the significant cut-off time to the end of sampling. The top and bottom bars on the whiskers
indicate the maximum and minimum values of the period. The three demarcations within each box
indicate the 7 5 th, 5 0 th, and 2 5 th percentiles, from top to bottom. The decrease in levels of
microorganisms between Periods 1 and 2 is readily apparent at almost all stations. Furthermore, it is
clear that coliphages vary more markedly than others, though E. coli and Enterococci follow the same
29
trends. In contrast, the adenovirus levels do not decrease significantly from Period 1 to Period 2. In
some cases, they even appear to increase slightly, though not to a statistically significant level. This
difference in behavior may indicate that adenovirus concentrations follow a separate kinetic profile that
could be attributed to any number of confounding factors, including temperature fluctuations, growth
kinetics, host presence, and environmental stability. The biological basis for this difference in trends is
an interesting question that remains outside the scope of this project. Nevertheless, it is clear that
microbial pathogen levels can vary widely on a day-to-day basis. Thus, understanding the sources behind
this variation is imperative to making the Kallang Basin safe for recreational users.
1E+3
Male-specific (F+) Coliphage
I
1E+2
0J
0
_r
f
T
Day 2
Day 1
T
L
in
I
1E+1
1E+O
Day 1
Day 2
Station 2
Day I
Station 3
Day 2
Station 4
Day 1
Day 2
Station 5
1E+3
Somatic Coliphage
T
0
V 1E+2
I
U-
1E+1
I
F
Day 1
Day 2
Station 2
Day 1
J
Day 2
Day 1
Day 2
Station 4
Station 3
Day 1
Day 2
Station 5
Figure 18 - Box Plot for Coliphage. Concentrations of male-specific (F*) coliphage (top) and somatic coliphage
(bottom) from the first and second 24 hours of sampling for each station.
30
1E+5
E. coil
I
1E+4
E
z
T
1E+3
T
4-
1E+2
i
1E+1
--Day 1
Day 2
Day I
Station 2
Day 2
Day 1
Station 3
Day 2
Day I
Station 4
Day 2
Station 5
1E+4
Enterococci
1E+3
0
0
z
T
I
I
1E+2
T
I
I
1E+1
1E+O
Day 1
Day 2
Station 2
Day
1
Day 2
Station 3
Day 1
Day 2
Station 4
Day I
j
Day 2
Station 5
Figure 19 - Box Plot for E. coli and Enterococci. Concentrations of E. coli (top) and Enterococci (bottom) from the
first and second 24 hours of sampling for each station.
31
1E+3
Adenovirus
1E+2
1E+1
1E+0
--------T
Day I
Day 2
Station 2
Day 1
Day 2
Station 3
Day
1
Day 2
Station 4
Day I
Day 2
Station 5
Figure 20 - Box Plot for Adenovirus. Concentrations of adenovirus from the first and second 24 hours of sampling
for each station.
To further characterize the basis of this fluctuation in microorganism levels, measured rainfall depths
prior to and during sampling periods were evaluated. The high concentrations during the first 24 hours
of sampling could potentially be caused by rainstorms in the area on the two days prior to sampling.
Rainfall data collected by Wang (2014) at the Balam Estate Rain Garden, located just north of the Kallang
Basin and within its drainage basin, showed rainfall of 14.6 mm and 17.8 mm on January 5 and 6,
respectively.
Rainstorms tend to have an effect on water quality. Increased flow from rainfall runoff and increased
winds during storms enhance turbulence in water bodies which can contribute to the mixing and
resuspension of sediments into the water column. Storm water runoff often contains high levels of
pathogenic bacteria and viruses (Novotny and Olem 1994). While most fecal bacteria and viruses are
free-floating individuals, a significant quantity of pathogens may adsorb to sediment particles. Studies
have shown that these fecal bacteria can often survive in the sediment beds of water bodies for up to six
weeks (Jamieson et al. 2005).
There are some general conclusions that can be reached about the four sampling stations from the
above data. Because Station 3 is directly downstream of Station 4, it can be assumed that water flowing
from Station 4 should pass by Station 3. Interestingly, almost all the microorganisms showed a decrease
in concentration from Station 4 to 3. This decrease may be due to possible dilution or degradation as the
Kallang River widens into the Kallang Basin. Of the four stations, Station 5 generally has lesser variation
between Period 1 and Period 2, as is visible in Figure 17. This deviation at Station 5 from the time
pattern observed otherwise may be due to an increase in the Period 2 concentrations caused by passing
rain showers (0.2 mm) while collecting the last sample at 7:00 AM. Additionally, Station 5 is located in
Rochor Canal, the most stagnant of the three tributaries. Average river flow rates determined by
32
Angeles (2014) indicate that the Rochor Canal has a flow rate of 0.35 m3 /s, while the Kallang River
(Stations 3 and 4) and Geylang River (Station 2) flow at 3.63 m 3 /s and 0.53 m3 /s, respectively. Stagnant
waters tend to harbor more pathogens which could account for the higher concentrations of fecal
bacteria.
33
5 CONCLUSIONS AND RECOMMENDATIONS
Water samples from four stations in the Kallang Basin were evaluated over a 48-hour sampling period
and tested for various microorganisms. Male-specific (F') coliphage, somatic coliphage, and adenovirus
were quantified and detected using standard procedures in the laboratory. Coliphages were plated and
enumerated using U.S. EPA Method 1602, while adenovirus concentrations were determined using a
Taqman* qPCR assay. The resulting concentrations were then compared to corresponding
concentrations of E. coli and Enterococci, the standard indicators for bacteriological water quality.
Laboratory analysis of the samples from the four stations indicated that there was substantial pathogen
contamination in the water over the course of the 48 hours. Coliphages were detected in all 48 samples;
adenovirus was detected in half. Despite presenting at high concentrations, somatic coliphages followed
similar trends over the sampling periods as male-specific (F') coliphages. Adenovirus had higher
detection rates at Station 2 and 5. However, there were no distinct correlations between presence of
adenovirus and occurrence of coliphages. As for the E. coli and Enterococci, the geometric mean of each
of their concentrations were above the U.S. EPA regulation standards of 126 colony forming units (CFU 1 )
per 100 milliliters and 35 CFU/100 mL, respectively (U.S. EPA 2012b).
The data for the different microorganisms were also normalized according to the highest concentration
for each station and then used to generate a heat map (Figure 17). From the distributions in the heat
map, it can be seen that the first 24 hours of sampling corresponded with higher concentration values,
while the second 24 hours mostly exhibited lower concentrations. This trend may have resulted from
rainfall in the area days immediately prior to sampling. Rainstorms can increase runoff and turbulence,
inducing sediment mixing in the Basin. Pathogens that had previously adsorbed to sediments may
resuspend after a rain event. Further studies are necessary to confirm and strengthen this finding.
While there were no immediately obvious correlations between the presence of any two
microorganisms, this neither confirms nor rejects the possibility of relationships between pathogens and
indicators in the Kallang Basin. Establishing relationships between microorganisms at the same times
and stations did not result in strong or meaningful correlations, but patterns do show overall elevated
concentrations at similar times. There may be underlying factors that cause microorganism levels to
peak at distinct times. It is likely that there are many complex interactions between microorganisms,
their hosts, sources, and other environmental factors that are not readily apparent in concentration
data. Understanding factors such as growth kinetics of coliphage and adenovirus, possible flow from
non-point sources, and industrial activity of the surrounding areas may clarify the occurrence of certain
trends.
Furthermore, an in vitro study that evaluates how well the presence of coliphages and adenovirus
actually correlates with fecal contamination may prove useful in determining the efficacy of microbial
indicators. Being able to assess the direct relationship between the presence of fecal indicators and
presence of fecal matter in a controlled setting may elucidate the biological basis of their interaction,
1
For the purposes of this study, CFU and MPN are used interchangeably.
34
permitting a more comprehensive understanding of their relationship in the field. The notion that a
single microbial indicator can be the universal indicator of risks associated with poor water quality may
be an outdated ideal. While there are better indicators for specific situations or environments, generally,
it takes more than one index to paint a complete picture of the quality of a water body. Evaluating
potential indicators that may be better suited for the Kallang Basin will allow for a more effective water
quality monitoring system to protect the health and safety of the public.
35
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38
APPENDICES
Appendix I: Raw Data
The raw data from the quantification of male specific (F+) coliphage, somatic coliphage, adenovirus, E.
coli, and Enterococci used in this study are included in Figure A-1 to Figure A-3 and Table A-1 to Table A3.
Table A-1 - Coliphage Raw Data (Vergara 2014)
F+
SOM
F+
SOM
F+
SOM
40
320
F+
104
SOM
1/7/2014 11:00
200
48
160
1/7/2014 15:00
1/7/2014 19:00
52
400
140
88
16
320
36
240
44
56
480
320
21
160
16
40
76
160
480
240
36
92
120
24
200
40
156
200
128
440
56
640
56
80
20
280
12
200
12
160
36
40
1/8/2014 11:00
1/8/2014 15:00
14
94
32
62
18
78
2
172
14
68
6
42
8
60
2
120
1/8/2014 19:00
1/8/2014 23:00
8
58
18
32
40
40
2
134
50
56
72
30
30
64
64
84
38
72
14
52
72
62
30
106
8
52
4
38
8
38
2
74
1/7/2014 23:00
1/8/2014 3:00
1/8/2014 7:00
1/9/2014 3:00
1/9/2014 7:00
Station 2
200
'I
U-
a-0
Station 3
-e-Station
4
--
Station 5
I
Male-specific (F+) Coliphage
150
100
50
0
1/7/2014 0:00
1/7/2014 12:00
1/8/2014 0:00
1/8/2014 12:00
1/9/2014 0:00
1/9/2014 12:00
Time
800
E 600
Somatic Coli phage
400
200
0
1/7/2014 0:00
1/7/2014 12:00
1/8/2014 0:00
1/8/2014 12:00
1/9/2014 0:00
1/9/2014 12:00
Time
Figure A-1 - Raw Data Plot for Coliphage. Male-specific (F+), top; somatic, bottom.
39
Table A-2 - Adenovirus Raw Data 2
Will
HAdV
HAdV
HAdV
HAdV
1/7/201411:00
210
7
7
226
1/7/2014 15:00
94
7
546
7
1/7/2014 19:00
89
7
81
32
1/7/2014 23:00
7
7
7
7
1/8/2014 3:00
98
7
101
36
1/8/2014 7:00
69
7
21
15
1/8/2014 11:00
45
7
7
7
1/8/2014 15:00
91
7
7
390
1/8/2014 19:00
242
7
7
172
1/8/2014 23:00
7
7
7
1/9/2014 3:00
7
19
7
146
90
1/9/2014 7:00
7
122
7
235
Station 3
- - Station 4
Station 2
---
Station 5
600
Adenovirus
400
200
0
1/7/2014 0:00
1/7/2014 12:00
1/8/2014 0:00
1/8/2014 12:00
1/9/2014 0:00
1/9/2014 12:00
Time
Figure A-2 - Raw Data Plot for Adenovirus
For samples with undetected concentrations of adenovirus, a concentration of half of the detection limit (13.1
GC/100 mL) was assumed.
2
40
Table A-3 - E. coli and Enterococci Raw Data (Angeles 2014)
MPN10
mL
Sain
1/7/2014 11:00
1/7/2014 15:00
1/7/2014 19:00
1/7/2014 23:00
tto
3
to
4.tto
5
E. coil
Ent
E. coil
Ent
E. coil
Ent
E. coil
Ent
2098
1120
1127
281
4106
727
15531
985
22
863
30
1050
101
9804
435
106
465
54
863
61
836
132
3654
2420
2224
60
573
43
717
87
2310
263
1842
1011
281
88
906
122
1187
2420
2723
1733
372
211
1046
1733
1842
2420
1/8/2014 11:00
1/8/2014 15:00
14316
17
226
11
420
52
1354
2420
3441
5
282
18
591
50
1334
126
1/8/2014 19:00
1/8/2014 23:00
1133
7
41
139
269
403
237
1733
1726
314
22
56
103
14
12
233
134
29
36
689
128
109
1/9/2014 3:00
i/9/2014 7:00
1160
6
443
125
278
107
19866
2420
1/8/2014 3:00
1/8/2014 7:00
Station 2
2)
--
Station 3
Station 4
-.-
62
Station 5
30000
E. coi
E
o
0 20000
z 10000
0
--
1/7/2014 0:00
p
1/7/2014 12:00
1/8/2014 0:00
1/8/2014 12:00
1/9/2014 0:00
1/9/2014 12:00
Time
3000
EneIoc
Enter cocc
o 200 0
z 100 0
0
1/7/2014 0:00
1/7/2014 12:00
1/8/2014 0:00
1/8/2014 12:00
1/9/2014 0:00
1/9/2014 12:00
Time
Figure A-3 - Raw Data Plot for E. coli and Enterococci. E. coli, top; Enterococci, bottom.
41
Appendix II: Concentration and Dilution Factor Calculations
The original raw water samples from the Kallang Basin were subjected to concentration, dilution, and
division into aliquots (Figure A-4). These processes are accounted for by multiplying the genome copies
per reaction from the qPCR by a concentration and dilution factor.
EQUIVALENT
RAW WATER
Take half of the 20 L
raw sample
101
Concentrate sample to
500 p.L
10 L
Extract DNA from 140 IiL
of the concentrated sample
2.8 L
Add 5 piL extracted DNA
0.23 L
CONCENTRATION
140 pL
EXTRACTION
5 piL
DILUTION
to 45 pL DI water
qPCR
Add 15 pL qPCR Master
Mix to 5 pL diluted DNA
0.023 L
Figure A-4 - Flow Chart for Concentration and Dilution of Raw Water Sample
The quantity of DNA used for the qPCR reaction was equivalent to the quantity of DNA in 0.023 L of the
raw water sample. Thus, the GC value calculated using the standard curve actually corresponds to
GC/0.023 L. To display concentrations in GC/100 mL, the calculated GC values were multiplied by a
factor 4.35.
42