THE CHARACTERIZATION AND QUANTIFICATION OF METHANOGENIC AND

METHANOTROPHIC BACTERIAL COMMUNITIES ASSOCIATED WITH

PETROLEUM DEGRADATION

A thesis presented to the

Faculty of the Biological Sciences Department

California Polytechnic State University, San Luis Obispo

In Partial Fulfillment

of the Requirements for the Degree

Master of Science in Biological Sciences

by

Wendy Anjanette Phillips

October 2006

© 2006

Wendy Anjanette Phillips

All Rights Reserved

ABSTRACT

The Characterization and Quantification of Methanogenic and Methanotrophic Bacterial

Communities Associated With Petroleum Degradation

By

Wendy A. Phillips

Natural attenuation is contributing to the reduction of contaminant concentrations

in the environment through natural biological mechanisms at the former Guadalupe Dunes

Oil Field near Guadalupe, CA. While a large variety of microorganisms contribute to

natural attenuation processes, this study focused only on methanogenic and

methanotrophic bacterial communities associated with the Guadalupe Dunes aquifer.

Methane is commonly detected in petroleum-affected groundwater at Guadalupe,

but not above ground or in surface samples. This suggests that methanogens produce

methane under anaerobic conditions at this site and methanotrophs rapidly degrade it

before it reaches the surface. Therefore, the methanogenic and methanotrophic

communities at Guadalupe work together to complete the conversion of total petroleum

hydrocarbons (TPH) to CO2 in a combination of anaerobic and aerobic processes. This

study characterized the methanogenic and methanotrophic populations in groundwater

samples collected from the Guadalupe Dunes site. Soil samples were also collected from

the CP plume at this site to quantify the methanogenic and methanotrophic bacterial

communities associated with petroleum degradation.

Twenty-eight groundwater samples were collected from ten different dissolved

phase petroleum plumes which were analyzed for TPH and nutrients. Bacterial DNA from

these samples was analyzed by Terminal Restriction Fragment Length Polymorphism

(TRFLP) to characterize methanogenic and methanotrophic populations.

Methanogenic bacteria were only detected in groundwater samples with high TPH

concentrations. Two to three genera of methanogenic bacteria dominated methanogen

communities, but the distribution of these genera was not correlated with any physical or

chemical gradient in groundwater chemistry. Thus, the type of methanogen present in the

groundwater plumes is independent of groundwater chemistry.

In contrast, the distribution of methanotrophic bacteria was correlated with a redox

gradient in groundwater chemistry. Thus, the type of methanotroph varied with indications

of a redox gradient such as increasing methane and TPH, and decreasing oxygen

concentrations. As with methanogens two to three genera of methanotrophs dominated the

community.

Based on these results it appears that methanogens are actively producing methane

in the central, high TPH portions of groundwater plumes, while methanotrophs survive in

the oxygen rich peripheries metabolizing the dissolved methane before it diffuses to the

surface. Some populations of methanotrophs prefer lower methane and higher oxygen,

while others prefer higher methane and lower oxygen.

Quantitative PCR (qPCR) was used to measure the size of the methanogenic and

methanotrophic populations. Groundwater samples were not useful for qPCR due to

inherent sampling irregularities such as different amounts of suspended solids and different

filtration volumes. Soil samples, however, were appropriate for qPCR because sample

processing was easily standardized. Soil samples were collected from a vertical profile

above a large source of petroleum at the Guadalupe Dunes site. Samples were collected at

half foot intervals from 30.5 to 128.5 ft with the water table at 118 feet.

Methanogenic bacteria were detected in soil samples from 118 to 128.5 ft, with

maximum population numbers near 118 ft, at the groundwater/air interface. Shallower soil

samples collected above this depth showed a sudden and significant drop in methanogen

numbers, indicating that soils above the groundwater interface are too oxygen rich to

support methanogenic populations. Methanotrophic bacteria were detected from 30.5 to

120 ft., with maximum population numbers near 95 ft, which correlated with intermediate

levels of methane.

Results from this study suggest that the Guadalupe Dunes site supports a complex

population of both methanogenic and methanotrophic bacteria. Their presence actively

contributes to the natural attenuation processes occurring at the Guadalupe Dunes site.

ACKNOWLEDGEMENTS

I would like to thank Dr. Chris Kitts for all of his encouragement, technical expertise,

availability, and patience. I am always amazed at the amount of time he invests with each

of his students, and I am more grateful to him than I could ever possibly express. I would

also like to thank Drs. Raul Cano and Yarrow Nelson for their support and assistance with

the completion of my thesis. I am very grateful to them and all of the faculty in the

Biological Sciences Department who helped me mature from an undergraduate student into

an independent graduate researcher. I would also like to thank Unocal for providing the

financial support that made this and many other educational projects possible.

In addition to the above I would like to thank Andre Hsiung for his constant and

unwavering support. I am forever grateful for all of the opportunities he has provided me

with in the advancement of my professional career. Andre is a truly wonderful mentor and

a dear friend. I am also thankful to my fellow graduate students Anna Engelbrektson and

Kelly Wrighton for their support and friendship, and to my two dear friends Beckie

Hellwig and Darin Gabler for their amazing friendship and shared love of coffee breaks.

Lastly I’d like to thank the two people who have most impacted my life. My mother, who

has been an unwavering source of constant support and love, and my brother with whom I

share a very special and treasured bond. I would never have made it this far without either

of them in my life, and words cannot adequately express the depth of my love and

gratitude for them. Thank you David and Mom for all of your unwavering support, advice,

laughter, and love. I hope you both know how fortunate I feel to have you in my life.

TABLE OF CONTENTS

Page

List of Figures………………………………………………………………………....x

List of Tables…………………………………………………………………………xi

Introduction……………………………………………………………………………1

Methods and Materials………………………………………………………………...7

Principal Component Analysis of Hydrogeochemical Data….……………….7

DNA Extraction and PCR Amplification……………………………………..7

TRFLP Generation…………………………………………………..………...9

TRFLP Analysis……………………………………..………………………10

TRFLP Database Matching…………………………………………………..11

qPCR of Soil Samples……………………………………………………..…11

Results………………………………………………………………………………..14

Site Sampling – Groundwater Collection……………………...…………….14

Groundwater Chemical Analysis.…………….……………………………...16

Groundwater Chemical Analysis of DT Plume……………………………...17

PCR Amplification of the mcrA gene………………………………………..19

PCR Amplification of the pmoA gene……………………………...………..20

Methanogen mcrA TRFLP Patterns..……...…………………………………21

Methanotroph pmoA TRFLP Patterns...…...…………………………...……21

Effect of Groundwater Chemistry on Microbial Community Structure……..22

Influence of Groundwater Chemistry on Methanogens in the DT Plume…...23

Influence of Groundwater Chemistry on Methanotrophs in the DT Plume….23

Quantification of mcrA and pmoA in Soil Samples from the CP Site………26

Vertical Distribution of Methanogenic and Methanotrophic Bacteria…........27

Discussion……………………………………………………………………………29

References……………………………………………………………………………34

List of Figures

Figure Page

1. Guadalupe Dunes Regional Map………………………………………………...15

2. PCA Analysis of the Hydrogeochemical Data of the 10 Plumes………………...17

3. PCA Analysis of the Hydrogeochemical Data of DT Plume…………………….18

4. Gel Electrophoresis of Methanogenic DNA…………………………………..…19

5. Gel Electrophoresis of Methanotrophic DNA…………………………………...20

6. Example of mcrA TRFLP Pattern………….………..………………………..….21

7. Example of pmoA TRFLP Pattern…………….…………………………………22

8. PCA of mcrA TRFLP data from the DT Plume Samples………………………..24

9. Regression Analysis of mcrA PC1 and DT Chem PC1……………………….....24

10. PCA of pmoA TRFLP data from the DT Plume Samples…………………...…..25

11. Regression Analysis of pmoA PC1 and DT Chem PC1……………………...….25

12. qPCR Standard Curves for mcrA and pmoA…………………………………….26

13. Vertical Profile of Soil Gases and Populations of Methanogens and Methantrophs

……………………………………………………………………………………….28

List of Tables

Tables Page

1. Hydrogeochemical Data from Zymax Envirotechnology of DT Plume………..16

Chapter 1

INTRODUCTION

Environmental contamination can be tied to practices such as improper waste

disposal, storage, and transfer (2). When environmental contamination occurs, efforts are

usually made to remediate the affected area as soon as possible to prevent contaminants

from adversely affecting nearby wildlife and human populations. Unfortunately the

removal of environmental contaminants can be very labor intensive and expensive, and can

often result in its own set of environmental impact problems. Because of this, natural

attenuation has become a popular bioremediation option since it often offers an effective

and inexpensive alternative for pollutant removal at contaminated sites (1). Natural

attenuation relies on biological, chemical, and physical processes to contain and eliminate

the spread of contamination from its original source (3). This study focuses on the natural

attenuation processes occurring within petroleum affected soils and groundwater at the

Former Guadalupe Oil Field in California.

Recovery of oil from the Guadalupe Dunes site began in 1949 and continued until

the 1990s. Unfortunately the crude oil at this site was found to be extremely viscous with a

density comparable to that of asphalt at room temperature. The physical properties of

Guadalupe’s petroleum made it very hard to extract, so a petroleum thinner, referred to as

diluent, was pumped into the site to dilute the crude oil and make recovery easier (12).

This diluent was derived from the distillation of crude oil, whose specific chemical

composition varied, but was consistently similar to a mixture of kerosene and diesel (21).

As time progressed, the network of pipes that delivered diluent within the Guadalupe Oil

Field began to develop many substantial leaks. It has been estimated that approximately 8-

20 million gallons of diluent accidentally spilled out and contaminated 250 acres of this

site before the oil field was abandoned in the 1990s.

The Guadalupe Dune site is located in a unique and delicate environmental setting.

It is bordered on the south by the Santa Maria River, on the west by the Pacific Ocean, on

the north by Nature Conservancy-managed land, and on the east by agricultural land (12).

A total of three aquifers are located beneath the Guadalupe Dunes and dissolved petroleum

has been found in the uppermost dune sand aquifer. Groundwater in this aquifer is

estimated to flow at a rate of 0.3 m/day in an east to west direction resulting in dissolved

total petroleum hydrocarbons (TPH) flowing directly towards the Pacific Ocean and the

Santa Maria River. The rapid groundwater flow rate and permeable sand matrix has

resulted in groundwater contamination at the site, impacting numerous fragile land and

water ecosystems and threatening the welfare of many endangered species occupying this

area. Because of the depth of the groundwater, the fragile ecosystems involved, and the

presence of endangered species, natural attenuation was investigated as a remediation

solution for this site (13).

In order for natural attenuation to be considered as an acceptable remediation

method, regulatory agencies require evidence that clearly demonstrates sustainable

biodegradation (28). This evidence can include the detection of hydrocarbon degradation

intermediates, depletion of electron acceptors, microcosm studies, and a description of the

microbial community associated with hydrocarbon degradation (6, 28). At the Guadalupe

Dunes site subsurface methane has been detected which indicates the presence of an active

community of methanogenic bacteria. While these bacteria cannot utilize petroleum

hydrocarbons directly, they can utilize petroleum degradation products such as carbon

dioxide, hydrogen, and acetate for methane production (19). Therefore, methanogens

provide evidence that sustainable petroleum degradation is actively occurring at the

Guadalupe site. In addition to this, methane has not been detected above ground, which

indicates the presence of an active methanotrophic community. Methanotrophs degrade

methane into carbon dioxide and water, and must have a steady supply of methane

available for their survival (9). Therefore, methanotrophs provide additional evidence that

sustainable methanogenesis is occurring at the Guadalupe site, which in turn offers

evidence for sustainable natural attenuation.

Methanogenesis is commonly associated with organic material dissolved in

groundwater, since water acts as a physical barrier to rapid oxygen diffusion allowing for

the creation of anaerobic conditions (19). Since methanogenesis is the least energetically

favorable anaerobic process, all other electron acceptors such as oxygen, nitrate and

sulfate, must be completely depleted before this process occurs (20). Methanogenesis in

some bacteria can be driven by the oxidation of acetate, methanol, or formate. However,

Archaea derive energy from methanogenesis from the oxidation of molecular hydrogen

using carbon dioxide as a terminal electron acceptor. Archaea have a suite of unique

enzymes for the reduction of CO2 to methane that can serve as molecular markers for this

important group of methanogens. For the purpose of this study we’re focusing on the alpha

subunit of the methyl-coenzyme M reductase gene (mcrA). This functional gene is housed

in the methyl coenzyme-M reductase (MCR) complex where the reduction of a methyl

group occurs, resulting in the release of methane (19). This enzyme complex is both

unique and ubiquitous in all methanogenic Archaea (20).

In the absence of oxygen methane is very stable, but under aerobic conditions this

gas can be readily oxidized. Methane oxidation occurs through metabolic processes that

are unique to methanotrophic bacteria (9). The methanotrophs oxidize methane to CO2

through methanol, formaldehyde and formate intermediaries. For the purpose of this study

we focused on the methane mono-oxygenase gene (pmoA). This gene is associated with

the membrane bound pMMO complex unique to methanotrophic bacteria (9). The pMMO

enzyme oxidizes methane to methanol utilizing molecular oxygen (O2). This enzyme

complex is both unique and ubiquitous in all methanotrophic bacteria (9).

For this study culture-dependent methods were deemed too inaccurate and

unreliable. For the most part culture-dependent methods are time-consuming, use large

amount of materials, and are biased towards organisms that can survive in a laboratory

setting. In fact, approximately 0.1% of microorganisms present in soil or groundwater

samples can be successfully cultivated under laboratory conditions (15). Due to the

limitations associated with culture-dependent methodology, DNA based methods were

used exclusively in this study.

Terminal Restriction Fragment Length Polymorphism (TRFLP) was used to

characterize methanogenic and methanotrophic communities in Guadalupe groundwater

samples. This technique is based on the amplification of DNA with a primer set that

contains one fluorescently end labeled primer (15). The resulting amplified DNA is

digested with an appropriate restriction enzyme specific for the amplified gene target. Due

to variations in the target gene sequence, restriction sites for each species in the community

are usually different, resulting in different sized end labeled, “terminal restriction

fragments” (TRF) (21). These fragments are separated by size and detected in a DNA

sequencing machine resulting in a pattern of peaks that represent each TRF. The area under

each peak can be used to determine relative species abundance, and the location of each

peak can help indicate dominant genera in the community (20). The methanogenic

community was characterized using TRFLP of the mcrA gene, while the methanotrophic

community was characterized using TRFLP of the pmoA gene. Principal Components

Analysis (PCA) was used with the generated TRFLP data to evaluate trends in community

structure and hydrogeochemistry.

Although TRFLP can indicate dominant members of a community, it cannot be

used to quantify the absolute numbers of bacteria in a sample. To accomplish this,

methanogenic and methanotrophic bacteria were quantified by Quantitative PCR (qPCR)

of the mcrA and pmoA gene respectively. qPCR quantifies DNA by measuring the amount

of DNA produced during PCR amplification of a target gene. The method used in this

study required a fluorescent reporter molecule, SYBR Green, which intercalates into newly

synthesized double stranded DNA (dsDNA). As the amount of dsDNA product increases

so too does the fluorescence intensity. This intensity level is measured and recorded as

amplification occurs, and can later be used to calculate initial DNA concentrations in a soil

sample.

Therefore, the overall purpose of this study was to both characterize and quantify

methanogenic and methanotrophic populations at the Guadalupe Dune site. These two

groups of bacteria were selected because methanogenesis is a major contributor to

degradation and detoxification of Guadalupe’s petroleum affected soil and groundwater.

TRFLP analysis was performed on groundwater samples to provide information on

bacterial community structure and relative species abundance. qPCR was performed on

soil samples collected from the CP site to quantify the methanotrophic and methanogenic

populations. Also at the CP site a vertical profile of soil gas sampling wells nearby was

used to measure methane and oxygen levels present in the soil column.

Chapter 2

MATERIALS AND METHODS

Principal Components Analysis of Hydrogeochemical Data

Trends in the hydrogeochemical data generated by Zymax Envirotechnology were

visualized by Principal Component Analysis (PCA) using Minitab 14 (Minitab Inc., State

College PA). PCA is a rapid method for visualizing trends in multidimensional data that

serves to transform the data into new variables called the principal component scores.

These scores are constructed to represent the greatest variation in the data set. The first

principal component (PC) accounts for as much variation in the data as possible, and each

succeeding PC accounts for as much of the remaining variation as possible. PC scores are

generated by summing the total of all variables multiplied by their loading factors. A

meaningful result would be an obvious grouping or gradient of samples in a PCA plot.

The hydrogeochemical data set was adjusted prior to being imported into Minitab

14. Certain chemical variables were excluded due to a lack of data or accuracy in sampling

techniques. Half detection limit values replaced non-detect data. All variables were

normalized to Z scores to account for scaling (correlation matrix analysis). The final

chemical variable set included the following variables: TPH, BTEX, methane, oxygen,

hydrogen, carbon dioxide, nitrate, sulfate, ammonium, phosphate, dissolved iron, and pH.

DNA Extraction and PCR Amplification

Four liters of groundwater from each well of the 11 plumes were filtered through

0.2 µm nylon membrane filters. These filters were frozen until half of each filter was

removed and homogenized with liquid nitrogen. Samples were extracted using the MoBio

Ultraclean® soil DNA kit (MoBio® Laboratories Inc., Solana Beach, CA) following

manufacturer’s protocol. Success of each extraction was determined by measuring DNA

concentration in the extraction product with a Spectramax spectrophotometer (Molecular

Devices, Palo Alto CA).

Methanogenic bacteria were detected by amplifying the alpha subunit of the

methyl-coenzyme M reductase gene (mcrA) unique to all methanogens. This gene

produces the enzyme that catalyzes the reduction of methyl-coenzyme M, which leads to

the release of methane gas. The mcrA gene was amplified with the primer set MCRf and

MCRr (18). The MCRf primer was fluorescently labeled with a Cy5 phosphamide dye

(ProLigo LLC, Boulder, CO) and recognized the sequence 5′-

TAYGAYCARATHTGGYT-3′. The MCRr primer was an unlabeled reverse primer that

recognized the sequence 5′-ACRTTCATBGCRTARTT-3′. PCR was performed using the

following reagents: 10X Buffer, 10mM dNTP, 25mM MgCl2, 0.8 µg/ml BSA, PCR water,

and 5 U/ul AmpliTaq Gold (Applied Biosystems, Foster City, CA). Once a master mix was

created with these reagents, 49 µl was aliquot into a 96 well plate. Each groundwater

sample that had been previously processed was diluted to final concentration of 2 ng/µl

DNA and was then added to an individual well. The general PCR reaction protocol for the

mcrA primers involved the following temperatures and cycling: 95ºC for 10 min, 30 cycles

of 94ºC for 1 min, 45ºC for 1 min, and 72ºC for 2 min, followed by 72ºC for 10 min.

Successful PCR reactions were confirmed by gel electrophoresis with positive samples

showing a single band of approximately 470 base pairs.

Methanotrophic bacteria were detected by amplifying the methane monooxygenase

gene (pmoA) unique to all methanotrophs. This gene codes for the enzyme responsible for

the oxidation of methane to methanol, and was amplified with the primer set A189 and

A682 (11). The A189 forward primer was fluorescently labeled with a Cy5 phosphamide

dye (ProLigo LLC, Boulder, CO) and recognized the sequence 5′-

GGNGACTGGGACTTCTGG-3′. The A682 primer was an unlabeled reverse primer and

recognized the sequence 5′- GAASGCNGAGAAGAASGC-3′. PCR was performed using

the following reagents: 10X Buffer, 10mM dNTP, 25mM MgCl2, 0.8 µg/ml BSA, PCR

water, and 5 U/ul AmpliTaq Gold (Applied Biosystems, Foster City, CA). Once a master

mix was created 49 µl was aliquot into a 96 well plate. Each of the groundwater samples

that had been previously processed were diluted to 2 ng/µl DNA and were then added to an

individual well. The general PCR reaction protocol for the pmoA primers involved the

following temperatures and cycling: 95ºC for 10 min, 35 cycles of 94ºC for 1 min, 51.5ºC

for 1 min, and 72ºC for 1 min, followed by 72ºC for 10 min. Successful PCR reactions

were confirmed by gel electrophoresis with positive samples showing a single band of

approximately 525 base pairs.

TRFLP Generation

Three 50µl replicate PCR reactions were performed on each groundwater sample

with both respective primer sets. The excess primer, dNTPs, and MgCl2 were removed

using the MoBio Ultra Clean PCR cleanup kit (MoBio® Laboratories Inc., Solana Beach,

CA) following the manufacture’s protocol. Samples were washed with SpinClean solution

to remove any excess impurities before elution. The cleaned PCR product was eluted with

50µl of PCR water, and was quantified using a fluorometer (Bio-tek Instruments INC.,

Winooski, VT) tuned to the Cy5 labeling dye.

Methanogenic DNA (75 ng) was digested with 0.06µl of Sau96I enzyme (New

England Biolabs Inc., Beverly, MA), 4 µL of manufacturer recommended buffer and PCR

water to create a final volume of 40 µL. The Sau96I enzyme cut at sequences with

5′…G٧GNCC…3′. This digestion was incubated for 4 hours at 37ºC and deactivated for

20 min by incubation at 80ºC.

Methanotrophic DNA (75 ng) was digested with 0.5µl of HpaII enzyme (New

England Biolabs Inc., Beverly, MA), 4µl buffer, and PCR water to create a final volume of

40µl. The HpaII enzyme cut at sequences with 5′…C٧CGG…3′. This digestion was also

incubated for 4 hours at 37ºC and deactivated for 20 min by incubation at 80ºC.

Following digestion the methanogenic and methanotrophic DNA was purified by

ethanol precipitation. The purified DNA was dissolved in 20 µL of CEQ™ Sample

Loading Solution and 0.25 µL of CEQ™ DNA size standard-600 (Beckman Coulter Inc,

Fullerton, CA) and run on a CEQ™ 8000 (Beckman Coulter Inc, Fullerton, CA). Fragment

results were analyzed with CEQ™ 8000 Genetic Analysis System. TRF peaks were

aligned using the AFLP align function of the CEQ™ 8000 software.

TRFLP Analysis

Terminal Restriction Fragment (TRF) length in nucleotides, and TRF peak area

were exported from the CEQ8000 into Excel (Microsoft, Seattle WA). To standardize the

data for comparison between samples, the area under each TRF peak was normalized to

total amount of DNA analyzed and expressed as parts per million (ppm). Dominant peaks

were noted, and the data containing peak size and area were copied from Excel into

Minitab for subsequent statistical analysis. TRF peaks with an area of less than 10,000

ppm (<1.0% of the total for that sample) were excluded from analysis. The TRF data were

transformed by taking the square root of each TRF peak area to de-emphasize large TRF

peaks, while still taking relative abundance into account for Principle Components

analyses. Because all TRF variables are measured on the same scale, PCA was performed

without normalization (covariance matrix analysis).

TRFLP Database Matching

Tentative assignments of organism identity were made by comparison to a database

composed of TRF lengths predicted from approximately 30,000 gene sequences in the

Ribosomal Database Project and GenBank (22). In addition to these databases TRFLP

patterns were compared with published results using the same primer sets (9, 18).

Observed TRFs were matched to a database entry only if they fell within 2 base pairs of

the predicted TRF from the database (12).

qPCR of Soil Samples

Soil samples collected from the CP plume (Figure 1) were extracted using the

MoBio Ultraclean® soil DNA kit (MoBio® Laboratories Inc., Solana Beach, CA). The

extracted DNA was amplified with qPCR using a master mix of the following reagents:

SYBR Green PCR ReadyMix (Roche Laboratories), 25mM MgCl2, and PCR water. This

master mix was aliquot into individual qPCR tubes along with 2µl of DNA isolated from

one soil sample. Following qPCR amplification methanogenic and methanotrophic cells

were quantified by comparing their location to that of known quantity values on a

previously generated standard curve.

To create a methanogenic standard curve, controlled amounts of methanogenic

cells needed to be amplified with qPCR. Since cultivating methanogenic bacteria in a lab is

extremely difficult due to their anaerobic requirements, a pure sample of a methanogen

culture was ordered from the American Type Culture Collection (ATCC). Methanococcus

janneschi cells were ordered from ATCC with a known concentration of 1x107 cells/µl.

This concentration was verified with a petroff-hauser counting chamber slide. Dilutions of

this suspension were prepared using 9 ml saline blanks to reach a final dilution of 1x102

cells per milliliter. One ml aliquots were removed from each dilution and were spiked into

individual bead tubes from the MoBio Ultra Clean Soil DNA Extraction Kit (Mo Bio,

Solana Beach, CA). A gram of soil that was previously verified to be negative for

methanogenic bacteria was also added to the bead tubes to simulate normal soil sample

processing. Extractions were carried out as previously described and were quantified with

a 96-well spectrophotometer (Spectramax Plus, Molecular Devices, Sunnyvale, CA).

Following this procedure each sample was diluted to a concentration of 2ng/µl DNA to be

analyzed with the qPCR Smart Cycler® (Cepheid).

Methanogenic bacteria were quantified with the MCRf and MCRr primer set that

was were previously described (19). With qPCR however the MCRf primer was left

unlabeled so as to not interfere with SYBR green fluorescence. The mcrA primers were

amplified with the following temperatures and cycling times: 95ºC for 10 min, 30 cycles of

94ºC for 30 sec, 52ºC for 30 sec, and 72ºC for 30 sec, and 72ºC for 2 min followed by

72ºC for 10 min. Successful qPCR amplification was confirmed both visually by observing

fluorescent levels and by using a melt curve to verify true qPCR product. On a melt curve

false positives from primer-dimers were easily detected since these products have a much

lower melting point than true dsDNA product.

To prepare methanotroph qPCR standards, the methanotrophic bacterium

Methylomonas methanica was grown in the lab to a final concentration of 1x108 cells/µl

(28). This concentration level was determined by direct microscopic count utilizing a

petroff-hauser counting chamber slide. Subsequent dilutions were performed using 9 ml

saline blanks to reach a final dilution of 1x102 cells. One ml was removed from each

dilution and spiked into individual bead tubes from the MoBio Ultra Clean Soil DNA

Extraction Kit (Mo Bio, Solana Beach, CA). A gram of soil that was previously verified to

be negative for methanotrophic bacteria was also added to the bead tubes to simulate

normal soil sample processing. Extractions were carried out as previously described and

were quantified with a 96-well spectrophotometer (Spectramax Plus, Molecular Devices,

Sunnyvale, CA). Each sample was then diluted to a concentration of 2ng/µl to be analyzed

with the qPCR Smart Cycler® (Cepheid). As previously described these samples were

used to construct a standard curve to which field samples were later compared to determine

cell quantity.

Methanotrophic bacteria were quantified by amplifying the methane

monooxygenase gene (pmoA) with the primers A189 and A682 (9). This method once

again utilized SYBR green as a marker dye to fluorescently label dsDNA products. With

qPCR the A189 primer was left unlabeled so as to not interfere with DNA quantification.

The general qPCR reaction protocol for the pmoA primers was the following temperatures

and cycling: 95ºC for 10 min, 30 cycles of 94ºC for 30 sec, 58.5ºC for 30 sec, and 72ºC for

30 sec, and 72ºC for 2 min followed by 72ºC for 10 min.

Chapter 3

RESULTS

Site Sampling – Groundwater Collection

Twenty-eight groundwater wells from ten different plumes of dissolved phase

diluent were sampled from the Guadalupe Dunes restoration site (Figure 1). These

groundwater samples were collected in sterile glass bottles after approximately 4 well

volumes of standing water was removed from the well via a submersible pump. Any

headspace in the bottle was carefully removed to maintain anaerobic conditions. Ground

water samples were immediately transferred to the laboratory and stored for less than 24

hours at 4°C until further chemical and biological processing could occur.

Additional groundwater samples were sent to Zymax Envirotechnology in San Luis

Obispo, CA for chemical analysis. Chemical analysis included the following variables:

dissolved TPH, acetate, benzene, ethylbenzene, toluene, xylene, methane, hydrogen,

ammonium, dissolved iron, oxygen, carbon dioxide, nitrate, sulfate, and phosphate. The

total concentration of benzene, toluene, ethylbenzene, and xylene were summarized

together as the variable BTEX. Chemical variables with concentrations consistently below

detection limits were excluded from analysis (Table 1). The hydrogeochemical data was

analyzed to look for trends across the plume profile, and later to summarize the data for

comparison to methanogenic and methanotrophic bacterial community TRFLP patterns.

Soil samples for qPCR analysis were collected from a vertical profile above a large

source of petroleum at the CP site in the Guadalupe Dunes (Figure 1). A vertical profile of

soil gas sampling wells nearby was used to measure methane and oxygen in the soil

column. Soil gases were measured by gas chromatography at an external lab (Inland

Empire Laboratories). Forty-five soil samples were collected at half-foot intervals from

30.5 to 32.5 feet and from 80.5 to 128.5 feet. Aliquots of each sample were given to

Yarrow Nelson at the EBI to assess methanogenic and methanotrophic activities in

microcosm experiments (24).

Figure 1: Guadalupe Dunes Regional Map

Geographical location of the ten dissolved phase groundwater plumes (colored

symbols) and wells (black triangles) that were sampled and analyzed. This map

also shows the natural flow of groundwater at this site in relation to the Pacific

Ocean and Santa Maria River (blue lines). The red circle indicates the DT plume

that was used for statistical analysis with methanotrophic and methanogenic

TRFLP patterns. The orange triangle indicates the CP plume where soil samples

were collected along a vertical profile for qPCR analysis.

Table 1. Hydrogeochemical Data from Zymax Envirotechnology of DT Plume.

Well Number

Distance to

Source

Screen Length TPH BTEX CH

4 NH4 Fe

2+ CO

2 O

2 SO

4 NO

3

EPA Method - -

EPA 8015

DIESEL

EPA 8260

EPA RSK SOP-175

EPA 350.1

EPA 6020

EPA RSK SOP-175

EPA RSK SOP-175

EPA 300.0

EPA 300.0

Units m m mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L mg/L 204-A 140 6.1 2.3 ND 0.18 0.5 8.4 16.37 0.46 23 ND 206-C 51 6.1 4.25 ND 0.23 1.7 15 15.07 0.15 43 ND 207-B 744 6.1 0.46 ND 0.003 ND 0.39 5.52 6.41 59 7.52 209-C 44 6.1 14.5 28.15 7.83 3.7 38 17.72 0.28 2.8 ND 209-D 324 6.1 7.95 24.65 0.08 0.04 93 19.08 2.95 11 0.71 F4-1 343 4.6 1.35 ND ND 0.25 1.3 6.99 7.01 38 0.65 G3-1 134 4.6 10.5 22.4 5.88 0.83 16 13.46 1.5 20 ND G3-2 211 4.6 12.5 17.9 6.09 0.49 12 24 0.66 7.4 ND G4-3 131 4.6 7.05 134 2.85 0.31 2.7 16.31 2.1 4.4 ND H11-1 124 4.6 3 ND ND ND 0.38 11.8 1.5 24 0.33 H1-3 41 4.6 10.4 23.2 0.82 0.42 11 14.98 0.2 21 ND

ND, Non Detect -, Not Measured

Groundwater Chemical Analysis

Trends in the hydrogeochemical data generated by Zymax Envirotechnology were

visualized by Principal Component Analysis (PCA). This analysis created a new variable,

Chem. PC1, which consolidated 13 physical and chemical variables in the final data set.

Chem PC1 represented a parameter associated with TPH degradation that accounted for

48% of the variation in the physical and chemical data, while PC2 explained another 11%

of the variation left in the data set (Figure 2).

Figure 2: PCA Analysis of the Hydrogeochemical Data of the 10 Plumes

Wells are indicated in black, and hydrogeochemical variables are in blue. A

high negative Chem. PC1 value (e.g. wells H5-6, G3-2, 209-C) represents

anaerobic, lower redox, higher TPH environments. A high positive Chem. PC1

value (e.g. wells A8-8, F4-1, and 207-B) represents more aerobic, higher redox,

and lower TPH environments.

Different plumes may have been formed from source materials with differing

compositions. A separate analysis of the DT plume was performed below because it was

associated with the largest contaminant source at the Guadalupe Dune site and contained

the largest number of individual samples.

Groundwater Chemical Analysis of the DT Plume

When only the DT plume was analyzed the new variable, DT Chem. PC1,

accounted for 58% of the variation in hydrogeochemical data (Figure 3), as opposed to

48% for PC1 when all of the plumes were included (Figure 2). This indicates that plume-

to-plume variation of groundwater chemistry was significant. However, DT Chem. PC1

represented the same parameter associated with TPH degradation, a gradient from

anaerobic, lower redox, higher TPH environments to more aerobic, higher redox, and

lower TPH environments.

Figure 3: PCA Analysis of the Hydrogeochemical Data of DT Plume

Sample wells are in black and groundwater variables are in blue. A high

negative Chem. PC1 value (e.g. wells 209C, G3-2, 206-C) represents anaerobic,

lower redox, higher TPH environments. A high positive Chem. PC1 value (e.g.

wells 207-B, F4-1, and H11-1) represents more aerobic, higher redox, and

lower TPH environments.

PCR Amplification of the Methanogen mcrA Gene

Methanogenic bacteria were detected by PCR of the mcrA gene down to a

detection limit of 2 pg of DNA from a standard organism, Methanococcus janneschi

(Figure 4). All 28 groundwater samples were analyzed for the mcrA gene, but only wells

associated with anaerobic, low redox, and high TPH concentrations were positive.

Figure 4: Gel Electrophoresis of Methanogenic DNA

Serial ten fold dilutions of M. janneschi DNA in E. coli DNA to a total of 2

ng/µl. Detection limit was 2 pg of M. janneschi DNA

1KB 20 ng 2 ng 0.2 ng 20 pg 2 pg 0.2 pg 0.02 pg

PCR Amplification of the Methanotroph pmoA Gene

Methanotrophic bacteria were detected by PCR of the pmoA gene down to a

detection limit of 20 pg of DNA from a standard organism, Methylomonas methanica

(Figure 5). All 28 groundwater samples were positive for the pmoA gene.

Figure 5: Gel Electrophoresis of Methanotrophic DNA

Serial ten-fold dilutions of M. methanica DNA in E. coli DNA to a total of 2

ng/µl. Detection limit was 20 pg of M. methanica DNA

1KB 20 ng 2 ng 0.2 ng 20 pg 2 pg 0.2 pg 0.02 pg

Methanogen mcrA TRFLP Patterns

Two to three genera dominated the methanogenic community in groundwater

samples positive for mcrA. Data base matching of the dominant TRF peaks indicated that

Methanococcus and Methanobacteracea spp. were the most commonly detected

methanogens (Figure 6).

Figure 6: Example mcrA TRFLP Pattern

McrA PCR product digested with the Sau96I enzyme. This sample is from well

G3-1 found in the DT plume and shows two pairs of dominant peaks

corresponding to Methanococcus and Methanobacteracea spp.

Methanotroph pmoA TRFLP Data

Similarly, two to three genera dominated the methanotrophic community in

groundwater samples positive for pmoA. Database matching of the dominant TRF peaks

indicated that Methylococcus and Methylosinus spp. were the most commonly detected

methanotrophic genera (Figure 7).

0

1000

2000

3000

4000

5000

6000

7000

8000

9000

10000

11000

12000

13000

50 100 150 200 250 300 350 400 450 500 550Size (nt)

Methanobacteracea spp.

Methanococcus spp.

Figure 7: Example of a pmoA TRFLP Pattern

PmoA PCR product digested with the HpaII restriction enzyme. This sample is

from well G3-1 in the DT plume and shows two dominant peaks corresponding

to Methylococcus and Methylosinus spp

The Effect of Groundwater Chemistry on Microbial Community Structure

Trends in the TRFLP data indicating methanogenic and methanotrophic bacterial

community structure were visualized by PCA. Potential relationships between bacterial

community structure and groundwater chemistry were investigated by comparing PCA of

the two data sets. No correlation could be detected between Chem. PC1 and either

methanogenic or methanotrophic bacterial community structure when all 28 wells were

included in the analysis (data not shown). Consequently, this analysis was repeated with

samples from the DT plume only.

0

5000

10000

15000

20000

25000

30000

100 150 200 250 300 350 400 450 500 550Size (nt)

Methylosinus spp.

Methylococcus spp.

Influence of Groundwater Chemistry on Methanogens in the DT Plume

PCA of methanogenic bacteria based on the mcrA TRFLP data showed some

clustering of the DT plume samples based on the relative abundance of dominant genera

(Figure 8). However, a regression analysis of the mcrA PC1 (Figure 8) with DT Chem PC1

(Figure 3) did not show a correlation (Figure 9). This indicates that different types of the

mcrA gene do not dominate under different groundwater conditions along the redox

gradient represented by DT Chem PC1.

Influence of Groundwater Chemistry on Methanotrophs in the DT Plume

PCA of methanotrophic bacteria based on the pmoA TRFLP data showed a

distribution of the DT plume samples based on the relative abundance of dominant genera

(Figure 10). This time, a regression analysis of the pmoA PC1 (Figure 10) with DT Chem

PC1 (Figure 3) showed a correlation (Figure 11). This indicates that different types of the

pmoA gene dominate under different groundwater conditions along the redox gradient

represented by DT Chem PC1.

Figure 8: PCA of mcrA TRFLP Data from the DT Plume Samples

Corresponding TRF peaks from all DT wells appear in blue.

S509

S507

S505

S504

S503

S502

S470

S469

S425

S417

S409

S406

S403

S402

S359

S258

S254

S239

S196

S110

S106

S084

PC1 20%

5002500-250-500-750

750

500

250

0

-250

-500

H1-3

H11-1

G4-3

G3-2

G3-1 F4-1

209-D

209-C

207-B206-C

204-A

PC2

14%

0.40.20.0-0.2-0.4-0.6

0.5

0.4

0.3

0.2

0.1

0.0

-0.1

-0.2

-0.3

-0.4

S509

S507

S505

S504

S503

S502

S470

S469

S425

S417

S409

S406

S405

S403

S402

S359

S258

S254

S239

S196

S110

S106

S084

5002500-250-500-750

750

500

250

0

-250

-500

H1-3

H11-1

G4-3

G3-2

G3-1 F4-1

209-D

209-C

207-B206-C

204-A

0.40.20.0-0.2--0.6

0.5

0.4

0.3

0.2

0.1

0.0

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S509

S507

S505

S504

S503

S502

S470

S469

S425

S417

S409

S406

S403

S402

S359

S258

S254

S239

S196

S110

S106

S084

PC1 20%

5002500-250-500-750

750

500

250

0

-250

-500

H1-3

H11-1

G4-3

G3-2

G3-1 F4-1

209-D

209-C

207-B206-C

204-A

PC2

14%

0.40.20.0-0.2-0.4-0.6

0.5

0.4

0.3

0.2

0.1

0.0

-0.1

-0.2

-0.3

-0.4

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-0.4

S509

S507

S505

S504

S503

S502

S470

S469

S425

S417

S409

S406

S405

S403

S402

S359

S258

S254

S239

S196

S110

S106

S084

5002500-250-500-750

750

500

250

0

-250

-500

H1-3

H11-1

G4-3

G3-2

G3-1 F4-1

209-D

209-C

207-B206-C

204-A

0.40.20.0-0.2--0.6

0.5

0.4

0.3

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0.4

0.3

0.2

0.1

0.0

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-0.2

-0.3

-0.4

S417

S402

S509

S507

S505

S504

S503

S502

S470

S469

S425

S417

S409

S406

S403

S402

S359

S258

S254

S239

S196

S110

S106

S084

PC1 20%

5002500-250-500-750

750

500

250

0

-250

-500

H1-3

H11-1

G4-3

G3-2

G3-1 F4-1

209-D

209-C

207-B206-C

204-A

PC2

14%

0.40.20.0-0.2-0.4-0.6

0.5

0.4

0.3

0.2

0.1

0.0

-0.1

-0.2

-0.3

-0.4

S509

S507

S505

S504

S503

S502

S470

S469

S425

S417

S409

S406

S405

S403

S402

S359

S258

S254

S239

S196

S110

S106

S084

5002500-250-500-750

750

500

250

0

-250

-500

H1-3

H11-1

G4-3

G3-2

G3-1 F4-1

209-D

209-C

207-B206-C

204-A

0.40.20.0-0.2--0.6

0.5

0.4

0.3

0.2

0.1

0.0

-0.1

-0.2

-0.3

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0.4

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-0.2

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0.3

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-0.1

-0.2

-0.3

-0.4

S509

S507

S505

S504

S503

S502

S470

S469

S425

S417

S409

S406

S403

S402

S359

S258

S254

S239

S196

S110

S106

S084

PC1 20%

5002500-250-500-750

750

500

250

0

-250

-500

H1-3

H11-1

G4-3

G3-2

G3-1 F4-1

209-D

209-C

207-B206-C

204-A

PC2

14%

0.40.20.0-0.2-0.4-0.6

0.5

0.4

0.3

0.2

0.1

0.0

-0.1

-0.2

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S509

S507

S505

S504

S503

S502

S470

S469

S425

S417

S409

S406

S405

S403

S402

S359

S258

S254

S239

S196

S110

S106

S084

5002500-250-500-750

750

500

250

0

-250

-500

H1-3

H11-1

G4-3

G3-2

G3-1 F4-1

209-D

209-C

207-B206-C

204-A

0.40.20.0-0.2--0.6

0.5

0.4

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0.1

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-0.2

-0.3

-0.4

S417

S402

Figure 9: Regression Analysis of mcrA PC1 and DT Chem PC1

-

-

-

-

-

-

-

-

-

-

-

-

R2 = 0.15

5.02.50.0-2.5-5.0

500

250

0

-250

-500

-750

H1-3H11-1

G4-3

G3-2

G3 1

F4-1

209 D

209 C

207 B

206 C

204 A

R2 = 0.15R2 = 0.15

5.02.50.0-2.5-5.0

500

250

0

-250

-500

-750

H1-3H11-1

G4-3

G3-2

G3 1

F4

-2.5-5.0

500

250

0

-250

-500

-750

H1-3H11-1

G4-3

G3-2

G3 1

F4-1

209-D

209 C

207 B

206-C

204 A

R 2 = 0.15

-

-

-

-

-

-

-

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-

-

-

-

-

-

-

-

-

-

-

-

-

-

-

R2 = 0.15

5.02.50.0-2.5-5.0

500

250

0

-250

-500

-750

H1-3H11-1

G4-3

G3-2

G3 1

F4-1

209 D

209 C

207 B

206 C

204 A

R2 = 0.15R2 = 0.15

PC1 from Physical & Chemical Parameters of the DT Plumes (58%)

mcr

A T

RFL

P PC

1 (2

0%)

R 2 = 0.15R 2 = 0.15

H1-3H11-1

G4-3

G3-2

G3-1

F4-1

209-D

209-C

207-B

206-C

204-A

R 2 = 0.15

-

-

-

-

-

-

-

-

-

-

-

-

R2 = 0.15

5.02.50.0-2.5-5.0

500

250

0

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-500

-750

H1-3H11-1

G4-3

G3-2

G3 1

F4-1

209 D

209 C

207 B

206 C

204 A

R2 = 0.15R2 = 0.15

5.02.50.0-2.5-5.0

500

250

0

-250

-500

-750

H1-3H11-1

G4-3

G3-2

G3 1

F4

-2.5-5.0

500

250

0

-250

-500

-750

H1-3H11-1

G4-3

G3-2

G3 1

F4-1

209-D

209 C

207 B

206-C

204 A

R 2 = 0.15

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R2 = 0.15

5.02.50.0-2.5-5.0

500

250

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-500

-750

H1-3H11-1

G4-

-2.5-5.0

500

250

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-500

-750

H1-3H11-1

G4-3

G3-2

G3 1

F4-1

209-D

209 C

207 B

206-C

204 A

R 2 = 0.15

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R2 = 0.15

5.02.50.0-2.5-5.0

500

250

0

-250

-500

-750

H1-3H11-1

G4-3

G3-2

G3 1

F4-1

209 D

209 C

207 B

206 C

204 A

R2 = 0.15R2 = 0.15

PC1 from Physical & Chemical Parameters of the DT Plumes (58%)

mcr

A T

RFL

P PC

1 (2

0%)

R 2 = 0.15R 2 = 0.15

H1-3H11-1

G4-3

G3-2

G3-1

F4-1

209-D

209-C

207-B

206-C

204-A

R 2 = 0.15

Figure 10: PCA of pmoA TRFLP Data from the DT Plume Samples

Corresponding TRF peaks from all DT wells appear in blue.

PC1 16%5002500-250-500-750

500

250

0

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H11-1

G4-3

G3-2

G3-1

209-D 209-CPC2

13%

0.40.30.20.10.0-0.1-0.2-0.30.4

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0.2

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H538H537

H536

H324

H291

H258

H244

H243

H234

H228

H208

H207

H142

H134

H125

H122

H114

H107

H105

H092

H089H088

H078

H073

H070

H069

H068

H066

H057

0---

500

0

-250

H11-1

G4-3

G3-2

G3-1

209-D 209-C

0.40.30.0--0.2-0.3

0.3

0.1

0.0

-

-0.2

-

-

H536

H291

H258 H208

H207

H134

H125

H122

H114

H089

H078 H069

H068

PC1 16%5002500-250-500-750

500

250

0

-250

-500

H1-3

H11-1

G4-3

G3-2

G3-1

F4-1

209-D 209-C

207-B

206-C

PC2

13%

0.40.30.20.10.0--0.2-0.30.4

0.3

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H538H537

H536

H324

H291

H258

H244

H243

H234

H228

H208

H207

H134

H125

H122

H114

H107

H092

H089

H078H069

H068

H057

0---

500

0

-250 G4-3

G3-2

G3-1

209-D209-D

0.40.30.0-0.2-0.3

0.3

0.1

0.0

-

-0.2

-

-

H536

H291

H258 H208

H207

H134

H125

H122

H121H114

H089

H078 H069

H068H075

H11-1

PC1 16%5002500-250-500-750

500

250

0

-250

-500

H11-1

G4-3

G3-2

G3-1

209-D 209-CPC2

13%

0.40.30.20.10.0-0.1-0.2-0.30.4

0.3

0.2

0.1

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H538H537

H536

H324

H291

H258

H244

H243

H234

H228

H208

H207

H142

H134

H125

H122

H114

H107

H105

H092

H089H088

H078

H073

H070

H069

H068

H066

H057

0---

500

0

-250

H11-1

G4-3

G3-2

G3-1

209-D 209-C

0.40.30.0--0.2-0.3

0.3

0.1

0.0

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-0.2

-

-

H536

H291

H258 H208

H207

H134

H125

H122

H114

H089

H078 H069

H068

PC1 16%5002500-250-500-750

500

250

0

-250

-500

H1-3

H11-1

G4-3

G3-2

G3-1

F4-1

209-D 209-C

207-B

206-C

PC2

13%

0.40.30.20.10.0--0.2-0.30.4

0.3

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H538H537

H536

H324

H291

H258

H244

H243

H234

H228

H208

H207

H134

H125

H122

H114

H107

H092

H089

H078H069

H068

H057

0---

500

0

-250 G4-3

G3-2

G3-1

209-D209-D

0.40.30.0-0.2-0.3

0.3

0.1

0.0

-

-0.2

-

-

H536

H291

H258 H208

H207

H134

H125

H122

H121H114

H089

H078 H069

H068H075

H11-1

Figure 11: Regression Analysis of pmoA PC1 and DT Chem PC1

5.02.50.0-2.55.0

500

250

0

-250

-500

-750

209-C

PC1 from Physical & Chemical Parameters of the DT Plume (58%)

-

-

R2 = 0.561

H1-3

G4-3

G3-2

G3-1

F4-1

209-D

207-B

206-C

-

R2 = 0.561H11-1

pmoA

TR

FLP

PC1

(16%

)

Quantification of mcrA and pmoA in Soil Samples from the CP Site

Forty-five soil samples collected from the CP site were evaluated with qPCR to

determine methanogenic and methanotrophic populations along a vertical profile.

Methanogenic cells could be detected from 107 down to 102 cells/g of soil, and

methanotrophic cells could be detected from 108 down to 102 cells/g of soil (Figure 12).

Figure 12: qPCR Standard Curves for mcrA (Methanogens) and pmoA

(Methanotrophs)

Soil samples were spiked with cells of Methanococcus janneschi

(methanogen) and Methylomonas methanica (methanotroph) and amplified to

create individual standard curves utilizing the same primers as the TRFLP

analysis. The methanogen standard curve appears as red squares, while the

methanotroph standard curve appears as black circles.

(

qPCR Cycles for Detection of DNA Amplification

Log

(cel

ls/g

)

2826 2422201816 14 12

8

7

6

5

4

3

2

Methanotrophs Methanogens

R2 = 0.98 R2 = 0.98

Vertical Distribution of Methanogenic and Methanotrophic Bacteria

Methanogenic bacteria were detected at depths of 118 ft to128.5 feet (Figure 13).

Methanogen populations at 118 ft were several orders of magnitude greater than those

detected at depths of 120 ft and greater. This finding corresponded with increased levels of

detectable methane and the presence of groundwater at this depth (Figure 13). Soil samples

deeper than 118 ft. showed a gradual decrease in methanogen numbers.

Methanotrophs were found in soil samples ranging in depth from 30.5 to 120 feet

(Figure 13). The highest numbers of methanotroph cells were detected in depths of

approximately 94.5 to 100 feet, which corresponds with intermediate levels of methane

(Figure 13). Oxygen levels in this range were near the detection limit, possibly due to

oxygen consumption by methanotrophic populations. As the soil depth increased the

methanotroph populations began to decline, possibly due to the environment becoming

more anaerobic.

Figure 13: CP Vertical Profile of Soil Gases and Populations of Methanogens and

Methanotrophs

Methane is not detected in measurable levels until soil depth increases (blue

triangles), while oxygen is detected at high levels in shallower depths and low

levels at deeper depths (green diamonds). Methanogens (red squares) and

methanotrophs (black circles) are included on this graph to show correlations

to soil gases.

Depth (ft)

L

140 120 1006040 20

9

8

7

6

5

4

3

2

1

0

20

15

10

5

0

Oxygen

MT log(cells)

Methane

MG log(cells)

80

Log

(cel

ls/g

)

Soil

Gas

(%)

Chapter 4

DISCUSSION

Analysis of Data from all 10 Groundwater Plumes

PCA was used to create new variables describing the major sources of variation in

both the hydrogeochemical data and the bacterial community data collected from all 10

groundwater plumes (Figure 2, TRFLP data not shown). Regression analysis of Chem PC1

vs. TRFLP PC1 showed no correlation for either mcrA or pmoA TRFLP data (data not

shown) indicating that hydrogeochemistry does not affect the methanogenic community

structure. One explanation for this lack of correlation may be the method used to collect

the groundwater. Samples were collected from wells with screens from 15 to 20 ft in

length. Before sampling, 4 well volumes were removed to homogenize the well water,

which resulted in disruption of any established vertical gradient. Thus, one sample could

contain bacteria from both aerobic and anaerobic groundwater zones in the surrounding

soil. Also each plume was generated by potentially different source material resulting in

additional variation (17). All of these factors may have contributed to the apparent lack of

relationship between redox gradients and bacterial community structure when data from all

10 plumes were analyzed.

Analysis of Data from the DT Plume

To decrease plume-to-plume variation, a single plume, DT, was chosen for further

analysis. Once again PCA was used to describe the major sources of variation in both the

hydrogeochemical data and the bacterial community data (Figures 3, 8, 10). Regression

analysis of DT Chem PC1 vs. TRFLP PC1 showed no correlation for mcrA data (Figure

9). Based on this finding it would appear that methanogen community structure has no

relationship to groundwater chemistry. Although methanogens do not utilize petroleum

hydrocarbons directly, the concentrations of methanogenic substrates, H2 and acetate, were

consistently non-detect and so could not contribute to analysis. As described above

because of mixing in the well before sampling it is possible that more subtle correlations to

hydrogeochemistry were missed.

Regression analysis of Chem PC1 vs. TRFLP PC1 showed a definite correlation for

pmoA data (Figure 11). This indicates that the distribution of dominant genera in the

methanotroph community is directly influenced by the area’s hydrogeochemistry. In

particular, there was a strong correlation with dissolved oxygen and methane in the

groundwater, possibly corresponding with the different types of methanotrophic bacteria.

Type I methanotrophs favor environments with limited methane and increased levels of

oxygen and nitrogen, while type II methanotrophs favor environments with high methane

levels and limited oxygen and nitrogen (7). Type I methanotrophs also prefer environments

with steady and sustained levels of methane, while type II methanotrophs can survive in

environments where methane levels are highly variable (7). Complete sequencing of the

rRNA genes from these samples is necessary though to confirm the presence and

dominance of type I and type II methanotrophs.

Tentative Identification of mcrA and pmoA Organisms in the DT Plume

The most common methanogen (mcrA) gene TRFs were 405 to 409 nucleotides in

length, and most likely represented Methanobacteracea spp. according to database

matching (19). Methanobacteracea spp. are dominant methanogens commonly isolated

from petroleum contaminated areas worldwide (18). The most common methanotroph

(pmoA) gene TRFs were 121, 134 and 207 nucleotides in length, and represented

Methylococcus spp. along with other unknown methanotroph species. Methylococcus spp.

are type I methanotrophs that are commonly isolated in areas with sustained methane

levels from either natural or pollutant sources (9). Since the dominant species in this area

are type I methanotrophs this provides evidence for constant methanogenesis at the

Guadalupe Dunes site.

qPCR of CP Soil Samples

qPCR was used to quantify methanotrophic and methanogenic bacteria because

TRFLP cannot be used to quantify the absolute numbers of bacteria in a sample. One of the

most crucial aspects of the qPCR process is constructing a standard curve for the target

populations (Figure 12). The choice of control organism used to construct a standard curve

must address the issue of gene copy number. Different species of methanogens have 1 to 4

copies of the mcrA gene in their genome, while methanotrophs can have 2 to 6 copies of

the pmoA gene. Thus, sample populations with gene copy numbers different from the

control organism may be misrepresented. Control organisms chosen for this study had an

average number of the selected target genes. Methanococcus janneschi has 2 copies of the

mcrA gene, the average number for cultured methanogenic bacteria. Methylomonas

methanica has 4 copies of the pmoA gene, the average copy number for most cultured

methanotrophic bacteria. In spite of these precautions the qPCR results from some of the

CP soil samples seemed inappropriately high. For example, 107 to 108 methanogen cells/g

were detected at depths near 120 ft. (Figure 13). Estimates of bacterial population counts in

most soils are usually less than 108 cells/g. This would seem to make nearly 100% of the

biomass methanogens. It is possible that the methanogens at Guadalupe have a higher

mcrA gene copy number than Methanococcus janneschi. Similarly, 107 methanotroph

cells/g were detected at depths near 95 ft (Figure 13), possibly due to mismatching of

pmoA gene copy number.

The largest methanogen population was found at approximately 120 ft, which

corresponds to the air/water boundary where free-phase petroleum is floating on the

groundwater. This created a highly anaerobic environment with plenty of petroleum

hydrocarbons for the indirect production of methanogenic substrates. Soil samples

shallower than 118 ft. may be too aerobic for methanogen survival, which explains why

their population numbers suddenly drop below detectable levels. At depths below 125 ft

methanogen numbers began to decline, perhaps because of a gradient in other electron

acceptors, sulfate for example. A companion study with microcosms of the CP soil found

measurable levels of methanogenesis present at approximately these same depths (24).

The largest methanotroph population was found near 95 ft., which corresponds to

intermediate methane levels in the soil. Surprisingly, this region had little to no detectable

oxygen, but the detection limit was approximately 0.5% so oxygen may still have been

available for methanotrophic growth. The microcosm study did not include methane

utilization rates by methanotrophic bacteria for soil from this depth (24).

Guadalupe Dune Site Summary

Results from this study indicate that there are active populations of methanogens

and methanotrophs contributing to the natural attenuation processes occurring at the

Guadalupe Dunes site. Together these two groups are working synergistically to complete

the conversion of TPH to CO2 in a combination of anaerobic and aerobic processes. Thus,

the presence of these communities offers strong evidence for sustainable natural

attenuation at the Guadalupe Dunes site.

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