DGGE Analysis
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•Amplify 200 base pairs of highly conserved bacterial DNA (16S rDNA) from each sample
•DNA “unzips” during DGGE as the denaturant (urea) becomes increasingly concentrated in the gel
•Each rung of the DNA “ladder” is composed of one base pair (AT or GC)
•AT base pairs have fewer hydrogen bonds than GC base pairs
•AT base pairs are more vulnerable in denaturing situations
•Species with the most AT base pairs will unravel earlier in the DGGE process, traveling less distance than species with more GC pairs
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•DGGE can detect differences of only 1 or 2 base pairs in 16S rDNA
•Different species of bacteria are distinguished in this way
•The relative dominance of a species within a community is reflected in the width and intensity of the band on the gel (Figure 9)
•Population changes can be monitored for each microcosm over time
•Microbial populations in different environments can be compared
Example of large, dark bands, indicating dominant species
Example of less prominent bands, indicating a less-dominant species
Results
Stage 1: Lake of the Woods near South Bend, Indiana
•DGGE does not provide evidence for population change under the experimental parameters
•Tests conducted using a representative selection of samples 
•Changes may have occurred that are undetectable by DGGE
•Results indicate a stable microbial community in Lake of the Woods wetland sediments under the salinity ranges and environmental conditions tested
•Techniques involving DNA isolation, polymerase chain reaction (PCR), agarose gel electrophoresis, and denaturing gradient gel electrophoresis (DGGE) were acquired
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Stage 2: Phuket and Khao Lak, Thailand
•unable to transport sediment samples into the United States
•Sediment collected in Washington due to the necessary shift in the primary focus of study
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Stage 3: Rooks Park near Walla Walla, Washington
•Experimental process from Stage 1 repeated
•Microbial populations serve as a comparison for resilient microbial populations in Indiana
•Analysis of the DGGE product consistent with Stage 1 results
•Populations in each simulated microhabitat maintain a high level of diversity throughout time in each of the post-tsunami conditions
•Stagnant and flowing freshwater systems
•Seawater of various ionic strengths 
•Freshwater wetlands in Walla Walla, Washington appear to have a stable microbial population after saltwater intrusion (Figure 10) 
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Analytical Process
The Effect of Tsunamis on Wetlands:
Monitoring Microbial Populations
Tamara L. Carley, Whitman College.  Jennifer R. Woertz and Susan E.H. Sakimoto, University of Notre Dame.
Interdisciplinary Studies in Tsunami Impacts and Mitigation. Research Experience for Undergraduates.  University of Notre Dame, Department of Civil Engineering and Geological Sciences. Summer 2006.
Special thanks to the National Science Foundation and the Department of Defense for making this research possible through the funding of NSF Grant #EEC-0552432.
With gratitude to Stefen J. Green, Robert Nerenberg, Margaret Dudley, and Tina Mitchell at the University of Notre Dame.
Objective
The objective of this research is to better understand the impact of tsunamis upon microbial communities in coastal freshwater wetlands.
Introduction
Tsunamis can generate major disruptions in water quality and ecosystem health within coastal surface and near-surface freshwater systems as a result of rapid salinity changes.  Bacteria are important indicators of overall ecosystem health, as environmental stress can be reflected in their genetic diversity and abundance.  To date, little is known of the particular impact of rapid seawater inundation as an environmental stress upon microbial populations in wetlands.
Approach
This study simulates the impact of seawater rapidly inundating freshwater wetlands, specifically the impact rapid saline influx upon bacterial communities.  Sediment samples from freshwater wetlands in Lake of the Woods near South Bend, Indiana and Rooks Park near Walla Walla, Washington are used to establish baseline communities of microbes. These study cases act as an analogue for sediment and microbes found in freshwater wetlands in the southern province of Thailand that were flooded by the tsunami resulting from the M9.0 Sumatra-Andaman Islands earthquake of December 2004 (Figure 1).
Figure 1
Khao Lak in the province of Phang-nga, approximately 100 km north of Phuket.
More than 1000 people died and 80 percent of the area suffered damage as a result of the December 26, 2004 Sumatra-Andaman tsunami.  Circled areas are wetlands that were inundated by the tsunami event.  Images are approximately 8 km in length. 
Space Imaging: Centre for Remote Imaging, Sensing, and Processing. Singapore.
http://www.globalsecurity.org/military/world/thailand/khaolak-imagery.htm
Three Stages of Research
Stage 1: Lake of the Woods near South Bend, Indiana
•Establish and verify the experimental design
•Demonstrate that approach is feasible with our sample populations
•Prepare to repeat the experiment in a tsunami-zone environment
Stage 2: Phuket and Khao Lak, Thailand (Figures 2 and 3)
•Collect samples from 7 freshwater wetlands near the Andaman Sea
•5 sample sites were inundated by the 2004 tsunami
•2 sites were unaffected by the 2004 event
•Thailand samples have not yet arrived in America for analysis
Stage 3: Rooks Park near Walla Walla, Washington (Figure 4)
•To serve as a basis for comparison for Indiana microbial population responses to a simulated tsunami, in lieu of Thailand data
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Experimental Design
Tsunami conditions are replicated by inundating model wetlands with artificial seawater of low (10 ppt), moderate (30 ppt) and high (50 ppt) salinity (Figure 6).  Surface and substrate sediment samples are used to create microhabitats that replicate different environmental conditions (Figure 5). A stagnant system simulates standing water in the wake of a tsunami (Figure 8).  A flowing freshwater system simulates natural processes such as precipitation, percolation, and surface flow to purge intrusive saltwater from wetlands (Figure 7). In all, 22 microcosms were constructed to simulate post-tsunami scenarios.
Figure 5
Experimental design for environmental conditions in the wetland microcosms
Salinity: Theoretical and Experimental
Figure 8
Stagnant model wetland system with standing saltwater 
Figure 7
Flowing system designed to purge model wetlands of saltwater and to slowly introduce freshwater
Figure 6
Salinity of  simulated seawater used to inundate model wetlands
Figure 2
Sampling site in Khao Lak, Thailand
Figure 3
Sampling site in Phuket, Thailand
Figure 9
Examples of diversity within microbial populations. Each vertical band represents DNA from a different microcosm.
Day 1, substrate control, prior to inundation
1.1A
S
Day 1, substrate control, 2 hours after inundation
1.1B
R
Day 1, substrate control, 8 hours after inundation
1.1C
Q
Day 1, substrate sediment, stagnant system, medium salinity
1.2
P
Day 1, substrate sediment, stagnant system, high salinity
1.3
O
Day 1, substrate sediment, stagnant system, medium salinity
1.4
N
Day 1, surface sediment control
1.5
M
Day 1, surface sediment, flow-through system, high salinity
1.6
L
Day 1, surface sediment, stagnant system, high salinity
1.7
K
Day 1, surface sediment, stagnant system, medium salinity
1.8
J
Day 1, surface sediment, stagnant system, medium salinity
1.8B
I
Day 7, substrate sediment control
4.1
H
Day 7, substrate sediment, flow-through system, medium salinity
4.2
G
Day 7, substrate sediment, stagnant system, high salinity
4.3
F
Day 7, substrate sediment, substrate sediment, medium salinity
4.4
E
Day 7, surface sediment control
4.5
D
Day 7, surface sediment, flow-through system, high salinity
4.6
C
Day 7, surface sediment, stagnant system, high salinity
4.7
B
Day 7, surface sediment, stagnant system, medium salinity
4.8
A
Description—All Samples from Rooks Park
Sample
Key
Figure 10
Stage 3 DGGE Results
The DGGE gel was created using 19 samples of 16S rDNA isolated from microcosms created using sediment from Rooks Park in Washington.  Note the consistency in the location, width, and intensity of bands, each of which represents a bacterial species.  Microbial diversity is abundant in each sample, under different post-tsunami conditions.   
J
K
L
M
N
O
P
Q
R
S
B
C
E
D
F
G
H
A
I
•Collect sediment samples from microcosms on a regular schedule following the seawater inundation event
•Extract and purify DNA that is highly conserved in all bacteria, with variations of only one or two base pairs between species
•Use Mobio "powersoil" DNA extraction kits
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•Conduct Polymerase Chain Reaction (PCR)
•Amplify portions of 16S rDNA genes using primer sets targeting bacteria
•Run electrophoresis with PCR product on 2% agarose gels
•Visualize the migration of DNA across a charged field
•Determine which samples are of sufficient quality and quantity for denaturing gradient gel electrophoresis (DGGE)
•Conduct DGGE using a 20-70% denaturant gradient  for 17 hours at 60Ί C and 100 volts
•Monitor changes in bacterial community structure over time and under different environmental conditions
•Initial vulnerability
•Gradual decline
•Established dominance
•Population rebound
Figure 4
Sampling site in Washington 
Discussion
Though results are consistent for two stages of study, we are hesitant to say that microbial populations in freshwater wetlands are unaffected by tsunamis and rapid saltwater inundation. A number of significant variables such as temperature, pH, organic content, wave impact, and pollution were not factored into this study, though these would be pertinent in a natural setting. It will be worthwhile to repeat this experiment using sediment samples collected in coastal areas, as these will be better representative of microbial populations in tsunami-prone regions (which may be more or less resilient than our inland wetland sample populations).