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MICROBIAL COMMUNITY STRUCTURE IN A
TRICHLOROETHYLENE CONTAMINATED AQUIFER
DURING TOLUENE STIMULATED BIOREMEDIATION

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ELICA MONIQUE MOSS

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Doctoral Crop and Soil
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8/01 cJCIFlCIDaIeDuepas-sz

Microbial Community Structure in a Trichloroethylene Contaminated
Aquifer During Toluene Stimulated Bioremediation

By

Elica Monique Moss

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of requirements
for the Degree of

DOCTOR OF PHILOSOPHY

Department of Crop and Soil Sciences

2004

ABSTRACT

Microbial Community Structure in a Trichloroethylene Contaminated
Aquifer During Toluene Stimulated Bioremediation

By

Elica Monique Moss

Trichloroethylene (TCE), a common groundwater pollutant, is a major problem
facing communities throughout the world. This widespread occurrence has created
public demand for technologies to remediate aquifers contaminated with TCE. One
such in situ technique is the phenol or toluene stimulated co-oxidation of TCE and its
dechlorination products. This technique is dependent on the capability of the intrinsic
microbial population to produce oxygenases that degrade these chlorinated solvents
given the appropriate stimulating conditions. In this work, I evaluated microbial
community response to a ﬁeld test of toluene-stimulated TCE degradation implemented
by a Stanford research team at Edwards Air Force Base (AFB). High-throughput
sequencing and analysis of 168 rRNA gene libraries from ﬁltered monitoring well water
showed that populations taken 1 month and 3 months after toluene additions were
statistically different from those found before toluene addition. Furthermore,
communities near and down-gradient from the bio-treatment well were different from
those up-gradient to the bio-treatment wells. The major trends noted were a decline in
the Pseudomonas populations and an increase in Sphingomonas and eventually

Legionella populations after toluene feeding. In order to determine the presence of

toluene-degrading populations and to determine whether they co-oxidized TCE, I
isolated and characterized dominant populations from the site. While some showed a
low level of toluene consumption, none produced rapid growth on toluene and none
oxidized TCE. Since both toluene and TCE were removed in the ﬁeld test, the lack of
toluene-degraders in the monitoring wells must be due to the fact that the toluene
degraders had not yet reached these wells or the bacteria found there were not the ones
oxidizing toluene.

Because of the Bio-Enhanced In-Well Vapor Stripping (BEHIVS) System used
at Edwards AFB, I determined if bacteria in the Burkholderia cepacia complex (Bcc),
were present. This group of opportunistic human pathogens, especially in cystic ﬁbrosis
(CF) patients, lives in soil and some grow on toluene. High-throughput 16S rRNA
sequencing, isolation and characterization of colonies, and screening larger populations
by hybridization with a Bee speciﬁc probe revealed no such populations. But since
members of the Bcc can be agents for bioremediation and because the clinical and
environmental strains cannot be distinguished, I explored the different patterns of
aromatic substrate use between clinical and environmental strains. Cluster analysis
indicated that aromatic use by isolates from the environment was much higher than
from the clinic, but that no set of one or a few substrates could reliably distinguish an

environmental strain from a CF-lung colonizing strain.

To my mother and friend

Yvonne

who is always an inspiration to me.
I Love You!

iv

ACKNOWLEDGEMENTS

The author wishes to express her sincere thanks to:

Dr. James M. Tiedje who has assisted me on my path to academic success with
continued patience and words of encouragement. It meant so much to have you as an
adviser.

Dr. Stephen A. Boyd, Dr. Michael J. Klug, and Dr. Syed A. Hashsham,
members of my guidance committee.

My mother Yvonne, Father Ellis, Grandmother Corine and all members of my
family who have been there for me on this long journey. Thank you so much for all
your prayers, words of encouragement, and love.

Tomeka, Kerri, Mr. and Mrs. Scott and all my friends who were always there
cheering me on.

Dr. James E. Jay and Dr. Eunice Foster for your guidance and kindness.

Dr. Hector Ayala del Rio, Dr. Joonhong Park, and Dr. Alban Ramette for your
knowledge and support throughout my program.

My fellow lab colleagues, Claribel Cruz-Garcia, Benjamin Grifﬁn, Monica
Ponder, Xiaoyun Qiu, Veronica Gruntzig, Joel Klappenbach, John Urbance, John Davis,
Tamara Tsoi, Jorge Rodriguez Stephan Gantner, Mary Beth Leigh, Jacob Parnell, Peter
Bergholz, Vincent Denef, Kostas Konstantinidis, Debra Rodrigues, Carlos Rodriguez,
and Baolin Sun, thank you for your friendship.

Center for Microbial Ecology (CME) staff, Lisa Pline, Pat Englehart, Nicole

Mulvaney, and Joyce Wildenthal for all your help.

I Dr. Perry L. McCarty, Gary Hopkins and the Stanford University team for the

Edwards Air Force Base components of this work.

Dr. John LiPuma, University of Michigan Medical School, for providing the
strains for the Burkholderia cepacia complex analysis.

The Ribosomal Database Project 11 staff (RDP) James Cole, Benli Chai, and
Qiong Wang.

The Genomics Technology Support Facility (GTSF), Annette Thelen, PhD, and
Shari Tjugum-Holland.

Darlene Johnson and Rita House for their support since my admission into the
graduate program.

The author is indebted to CME, Crop and Soil Science and the Graduate School

for providing the opportunity and ﬁnancial aid during the course of this doctoral work.

vi

Table of Contents

LIST OF TABLES ................................................................................. x
LIST OF FIGURES ................................................................................ xi
Chapter I ................................................................................................. 1
Overview ............................................................................................. 1
Introduction ................................................................................. 1
Background ................................................................................. 5

What is TCE? ............................................................................................ 5

What is Toluene? ....................................................................................... 7
Rationale of Research ...................................................................... 9
Potential for bioremediation ................................................... .9

Aerobic transformation processes ..................................... 9

Anaerobic biotransformation processes ............................. 13

Field evaluation of toluene-driven cometabolic remediation of TCE.... 15
Moffett Field pilot study ............................................... 15
Edwards AFB study ..................................................... 16

References ................................................................................. 19
Chapter II .......................................................................................... 24
Microbial community response during a ﬁeld evaluation of toluene as the primary

substrate for TCE co-oxidation ...................................................................... 24
Introduction ............................................................................... 24
Materials and Methods ................................................................... 26

Site Description .................................................................. 26

Previous ﬁeld test design ........................................................ 27

Design for full-scale test with vapor-stripping system... .. .... .. . ...........28

Collection of Microbes from Groundwater Samples ........................ 31

Biomass collection ............................................................... 31

Terminal Restriction Fragment Length Polymorphism (TRFLP).. . ......31

Community similarity ........................................................... 33

. Burkholderia analysis ........................................................... 34
High-Throughput Sequencing of Clone Libraries ........................... 35

Cloning .................................................................... 37

Sequencing .............................................................. 38

Determination of signiﬁcant differences within communities. . . . . . . . . ....39

Results ..................................................................................... 40
Community composition ....................................................... 4O

Temporal Analysis of populations ............................................. 44

Spatial Analysis of populations ................................................ 46

Detection of Burkholderia cepacia complex (Bcc) ......................... 48

vii

Clone Library results of all six (6) wells and their signiﬁcance to each

other ................................................................................ 49
Burkholderia cepacia complex selection using recA primers... ... .........58
16S rRNA Clone Library results of all six (6) well samples taken at the
end of the experiment that were selected for analysis of Bcc using the

recA gene primers ................................................................. 60
Discussion ................................................................................. 63
References ................................................................................. 68
Chapter III ........................................................................................ 74
Isolation, characterization, and distribution of toluene degraders ﬁ'om soil and aquifer
habitats ............................................................................................... 74
Introduction ............................................................................... 74
Materials and Methods ................................................................... 76
Isolation of dominant populations ........................................... .76
Characterization of isolates .................................................... 77
Identiﬁcation of toluene degraders ........................................... .79
Determining substrates consumed ............................................. 79
Soil Samples ..................................................................... 80
Isolation of dominant soil populations ....................................... 80
Determination of Burkholderia cepacia complex (Bcc) .................... 80
Results ............................................... , ....................................... 83
Identiﬁcation of isolates ........................................................ 84
Colony hybridization ............................................................ 86
Discussion ........................................................................ 88
References ........................................................................ 90
Chapter IV ........................................................................................ 96

Determination of different patterns of aromatic substrate use between clinical and
environmental Burkholderia cepacia complex (Bcc) stra1ns96

Introduction .............................................................................. 96
Lignin Biosynthesis and Associated Aromatic Compounds... ... .........98

Materials and Methods ................................................................ 103
Collection of strains .......................................................... 103
Chemicals used ............................................................... 103
Preparation for aromatic growth analysis ................................. 105
Analysis of environmental vs. clinical strains ............................. 105
Determination of phenol hydroxylase genes .............................. 105

Results ................................................................................... 106
Growth of clinical compared to environmental strains on aromatic
compounds ..................................................................... 107
Phenol Hydroxylase analysis ................................................ 118

viii

Discussion .............................................................................. l 19
References .............................................................................. 122

ix

List of Tables

Table Page
Chapter II

Table 2.1. Morisita community similarity indices for the six well communities, N-l -L,

N-S-L, MW23-L, N-l l-L, N-l6-L, and N—l8-L .............................................. 42

Table 2.2 Taxonomy of well samples showing their hierarchical structure to show the

presence or lack there of for members of the genus Burkholderia ......................... 59
Chapter 111

Table 3.1 Results of toluene degradation and TCE co-oxidation of isolates from
Edwards AFB and three positive control. strains. Data are means of triplicate samples

...................................................................................................... 83

Table 3.2 Closest phylogenetic relative of sequenced isolates and their toluene and TCE

degrading abilities ................................................................................ 85

Table 3.3 ClustalW analysis of isolates against different Bacillus species ............... 86
Chapter IV

Table 4.1. Strains of the Bcc, the genomovar to which they belong, from where the
strains were isolated and the people who supplied them. Strains Corn 4, 5, 6,& 7 did
not have a high similarity to the known genomovars when analyzed with restriction
enzyme HaeIII as determined by Dr. Alban Ramette, Michigan State University. . .. .104

Table 4.2. Growth of environmental Bcc strains and Burkholderia Vietnamiensis G4
(positive control) on toluene and the total percentage of toluene degraded. Data are the
mean results oftriplicate samples. 106

Table 4.3. Growth of clinical Bcc strains on toluene and the total percentage of toluene
degraded. Data are the mean results oftriplicate samplele7

Table 4.4. Growth of environmental Bcc strains on different aromatic compounds
measured in triplicates. (+) represents at least two. out of the three replicates exhibiting
turbidity). (-) represents one or none of the isolates being turbid ................................ 109

Table 4.5. Growth of clinical Bcc strains (isolated from patients), on different aromatic
compounds measured in triplicates. (+) represents at least two out of the three
replicates exhibiting turbidity). (-) represents one or none of the isolates being
turbid .............................................................................................. 110

List of Figures

Figures Page
Chapter I

Figure 1.1 Chemical structure of TCE ......................................................... 5

Figure-1.2 Chemical structure of Toluene. . . . .. .............................................. 7

Figure 1.3 TCE Degradation Pathway with Psuedomonas putida F1 .................. 11

Figure 1.4 Anaerobic Tetrachloroethene Pathway ......................................... 14
Chapter 11

Figure 2.1. A cross-sectional view of a two-well cometabolic TCE biodegradation
treatment system spanning two separate aquifers. Also illustrates wells screened in both
shallow upper aquifer and deeper lower aquifer. This was the ﬁrst test implemented at
Edwards AFB (McCarty et a1, 1998)....' ................................................................... 27

Figure 2.2. Schematic of treatment system showing the physical characteristics
(Gandhi et a1, 2000) ............................................................................... 29

Figure 2.3a. Aerial view of the site locations within the BEHIV S system. The
BEHIVES system includes the vapor stripping well (D04) and the biotretment wells
(Bio). The other wells are monitoring wells (MW) and (T) and nested wells (N). The
remaining wells were not examined characteristics (Gandhi et al, 2000) .................. 30

Figure 2.3b. Simulated Flow Field at Edwards AFB created by one up-ﬂow well and
two down-ﬂow biotreatmentwells .............................................................. 30

Figure 2.4. Well diagram of only the samples that were analyzed. - represents the
biotreatm'ent wells (B101 and B102) amended with toluene, [:1 represents samples
upstream of B101 and 3102, Q represents samples nearest B101 and B102, and A
represents samples downstream of B101 and B102 ........................................... 36

Figure 2.5 PCR Results for the samples using 16S rRNA primers.
Positive control=E.coli; Negative control=blank ﬁlter ................................................ 41

xi

Figure 2.6. Puriﬁed DNA concentrations for the various wells taken before the toluene
treatment began .................................................................................... 42

Figure 2.7. TRF LP analysis of background communities taken from 24 different wells.
Sizes of colored bars reﬂect peak heights of different T-RFs (terminal restriction

ﬁagment). CI N-l-L and N-5-L, 9 N-l l-L and MW23L, and A N-16-L and N-18-L all
reﬂect wells that will be further analyzed ...................................................... 43

Figures 2.8-2.9. Composite analysis of samples taken before toluene injection and
samples taken one month after toluene injection. . . . . . . . .. ................................... 50

Figure 2.10. Log signiﬁcance of samples taken before toluene injection and samples
taken one month after toluene injection ........................................................ 50

Figures 2.11-2.12. Composite analysis of samples taken before toluene injection and
samples taken three months after injection ..................................................... 51

Figure 2.13. Log signiﬁcance of samples taken before toluene injection and samples
taken three months after injection ............................................................... 51

Figures 2.14-2.15. Composite analysis of samples taken one month after toluene
injection and samples taken three months after injection .................................... 52

Figure 2.16. Log signiﬁcance between samples taken one month alter toluene injection
and samples taken three months after injection ................................................ 52

Figure 2.17. Proﬁles of samples taken before toluene injection (background), one
month after injection (initial), and samples taken at the end of the experiment (end)
samples ........................................................... 53

Figures 2.18-2.19. Composite analysis from all three sampling periods of samples
upstream and nearest the BIO .................................................................... 54

Figure 2.20. Log signiﬁcance of the composite analysis from all three sampling
periods of , samples upstream and nearest the BIO ........................................... 54

Figures 2.21-2.22. Composite analysis from all three sampling periods of samples
upstream and downstream of B10 ............................................................. 55

Figure 2.23. Log signiﬁcance of the composite analysis from all three sampling
periods of samples upstream and downstream of BIO ...................................... 55

Figures 2.24-2.25. Composite analysis from all three sampling periods of samples
downstream and nearest of B10 ................................................................ 56

xii

Figure 2.26. Log signiﬁcance of the composite analysis from all three sampling
periods of samples downstream and nearest of B10 .......................................... 56

Figure 2.27. Proﬁles of thecomposite analysis from all three sampling periods of
samples upstream, nearest, and downstream of BIO .......................................... 57

Figure 2.27a. Analysis of samples using recA gene primers. Samples positive for recA

are bold ............................................................................................... 58
Figure 2.27b. Additional analysis of samples using recA gene primers. Samples

positive for recA are bold .......................................................................... 58
Figure 2.28.: Composite analysis of well N-8-L.. ........................................... 61
Figure 2.29. Composite analysis of well N-9- ................................................ 61
Figure 2.30. Composite analysis of well N-12-L. ............................................ 61
Figure 2.31. Composite analysis of well N-16-L. ............................................ 62
Figure 2.32. Composite analysis of well N-I 7-L. ............................................ 62
Figure 2.33. Composite analysis of well N-18-L. ............................................ 62

Chapter 111

Figure 3.1. Experimental protocol for the determination of toluene degraders, TCE co-
oxidizers, and for isolation of the most dominant populations from the
aquifer ............................................................................................... 78

Figures 3.2a and 3.2b. Detection of bacteria of the Burkholderia cepacia complex
(Bee), as determined by colony hybridization. 3.2a is the positive control. 3.2b is the
Bearlake sample and is representative of all soil samples tested ........................... 87

Chapter IV

Figure 4.1. Simple and modiﬁed version (from Lewis et al 1998) of lignin biosynthesis
involving aromatics used in this experiment .................................................. 102

Figure 4.2. Probability of environmental/clinical strain growth on a variety of
aromatics .......................................................................................... 111

xiii

Figure 4.3. Growth of clinical vs. environmental strains of the Bee on a variety of
aromatics .......................................................................................... 111

Figure 4.4. Dendrogram showing both clinical and environmental strains With similar
aromatic substrate use. Symbols used represent the following: @ Corn,

I Prairie, ‘Patients w/Cystic Fibrosis, A Patients w/Chronic Granulomatous
Disease, V Soil, Panama Palm Plant, 0 Onion, Water, Ubiquitous
environmental strains The eight major clusters of strains with sirm ar substrate use are
identiﬁed. Genomovars, when known, are indicated by the Roman nmneral before the
strain number ..................................................................................... 1 14

Figure 4.5. Dendrogram showing similar aromatic substrate use by strains from corn
( ® ) and prairie (- )rhizospheres .......................................................... 117

Figure 4.6. Electrophoresis gel of PCR products of Bcc strains that were ampliﬁed
using phenol hydroxylase primers, PheUf and PheUr. Only 1111112485, Corn 3, and G4
(positive control) had bands at the expected 600bp site ...................................... 118

xiv

Chapter I

Overview

Introduction

Trichloroethene (TCE), a well-known groundwater pollutant, is of great concern
throughout the United States, because it and especially its vinyl chloride product are
hazardous to humans. Cometabolism of TCE and its dechlorination products 1,2-cis-
dichloroethene (c-DCE) 1,2-rrans-dichloroethene (t-DCE), 1,1-dichloroethene (1,1,
DCE), and vinyl chloride, stimulated by primary substrates such as phenol and toluene,
has become a successful approach for in situ bioremediation of TCE. A pilot-scale
study at Moffett Field, CA (Mch et al., 1998), demonstrated the aerobic
cometabolic biodegradation of TCE and evaluated the microbial community
composition and succession in the aquifer amended with phenol, toluene, and
chlorinated aliphatic hydrocarbons such as TCE and 1,1-dichloroethene (1,1-DCE)
(Fries et al., 1997). Following this pilot-scale study, this technology was tested at a
TCE contaminated site, Edwards Air Force Base, CA. Prior microcosm studies using
Edwards AFB soil mimicked the cometabolic biodegradation observed at Moffett Field
and indicated that 87-99% TCE removal could be expected at Edwards AFB (McCarty
et al., 1998). Because of the success of the pilot study at Moffett Field and the
microcosm studies at Edwards AFB, the opportunity for implementing a full-scale test
of TCE remediation by cometabolism was undertaken at Edwards AFB led by Stanford
University engineers.

The full-scale study focused only on evaluating the effectiveness of the

cometabolic process in removing TCE but with no measures of the microbial population

response during the course of the ﬁeld trail. I took advantage of this ﬁeld experiment to
study the microbial community succession at three sampling periods: before toluene
injection; one month after the initial injection of toluene: and 3 months after toluene
injection (at the end of the experiment). This study was done to complement their
research. Therefore, the objectives of this study were to:
Objective 1: Determine which microbial populations are stimulated in the ﬁeld in
this full-scale remediation test. This is important since populations differ in their
ability to degrade TCE and hence could explain success or failure. Using this

approach, the following questions were addressed:

0 What is the population density of the subset of populations?

Using the results from the three (3) sampling periods, i.e.,
before toluene was added (background samples); one month after
the initial injection of toluene; and three (3) months after the
initial injection of toluene (the end of the experiment), the
samples were analyzed to determine what organisms are present

and their portion of the population.

0 What are the similarities in community structures among the diﬂerent
wells?

Communities were compared to each other in relation to

location of treatment wells and between similar sampling wells.

o What are the similarities in phylotypes at diﬂerent wells?
The 168 rRNA gene sequences of the different organisms
were analyzed to compare how similar they are, especially

between replicate wells.

Objective 2: Determine whether this process selects Burkholderia cepacia, a potential

human pathogen, but good TCE degrader.
The identiﬁcation of Burkholderia cepacia complex (Bcc) is of signiﬁcance
because this group of opportunistic human pathogens, which causes serious
infection in patients with Cystic Fibrosis (CF), lives in soil and grows on toluene
or phenol (Mahenthiralingam et al., 2000). Therefore, stimulating their growth
in the environment may be of concern at sites practicing aerobic TCE
cometabolism, such as Edwards AFB. In fact the best-known TCE
cometabolizing strain, G4, is a member of the Bee. The Bio-enhanced In-Well
Vapor Stripping (BEHIV S) system used at Edwards AFB, which employs a
vapor stripping well, could aerosolize B. cepacia cells if they are enriched in the
aquifer. If this is the case, this form of bioremediation would most likely be

shutdown by public health authorities.

Objective 3: Isolate dominant microorganisms from two wells and determine their
toluene and TCE-degrading ability and the type and the diversity of their aromatic

oxygenase genes.

Objective 4: Determine ability of various members of the B. cepacia complex, both

from clinical and environmental isolates to grow on a range of aromatic compounds.
Because Bee in the soil and lung would be expected to grow on very different
resources, for example a variety of aromatics in soil, these substrates might be

useful for differentiating between soil and CF -pathogenic strains.

These objectives were addressed by using molecular methods such as 168 rRNA
gene analysis, which avoid the limitations of culturability by providing more complete
information on community composition. Terminal restriction fragment polymorphism
(TRFLP) analysis of ampliﬁed total community 16S rRNA genes was used to explore
community structure and diversity (Braker et al., 2001). TAP-TRFLP was used; it is a
software tool that guides the microbial community analysis as it allows in silico
restriction digests of the entire 16S rRNA gene sequence database to ﬁnd fragment sizes
of bacterial species that can then be compared to T-RFs of the ﬁeld data (Osborn et al.,
2000). Secondly, clone libraries of 16S rRNA genes were collected from aquifer
bacteria using PCR with 16S rRNA gene primers to analyze bacterial diversity among

the active microbial communities in the Edwards AFB samples. Finally, I isolated

representative toluene degrading populations present after toluene additions to the site
and determined their growth rate on toluene, and their TCE degradation rate. These
results contributed to our understanding of the organizational structure of communities
within Edwards AFB, thereby conveying to researchers what organisms are stimulated
in the ﬁeld when the primary substrate, toluene, is added. Consequently, this research
aided in further understanding the natural populations of microorganisms that
metabolize toxic agents such as TCE, and whether there is likely any associated public

health risk, especially for CF patients.

Background

What‘is TCE?

.,>'——x

Figure 1.1 Chemical structure of TCE

Cl

TCE is a volatile, colorless liquid at room temperature that has been widely used
as a solvent to remove oil and grease from metal parts. TCE is an ingredient in
adhesives and paint removers and the textile industry uses it as a solvent in dying and

ﬁnishing operations with cotton, wool, and other fabrics (ATSDR, 1997). It is a

convenient solvent to use because of its low ﬂammability. TCE has a solubility in
water of ~1100 ppm, hence, it is mobile in soils and often found as a groundwater
contaminant. According to the EPAs Contract Laboratory Program Statistical Database,
TCE is reported to occur in 19% of groundwater samples at a geometric mean
concentration of 27.3 ppb (individually ranging from 0.1 to 27,300 ppb). It can also
migrate through soils and sub-soils and because its density is >1 g/cm3 i.e., it moves to
the bottom of aquifers. The presence of such a dense non-aqueous phase liquid
(DNAPL) usually serves as a long-term source of groundwater contamination.

One may become exposed to TCE by breathing TCE vapors from the
contaminated water (e. g. showers), or drinking the contaminated water. Breathing
small amounts of TCE can cause headaches, lung irritation, dizziness, poor
coordination, and difﬁculty concentrating (ATSDR, 1997). Breathing large amounts for
short periods may cause impaired heart function, unconsciousness, and death, whereas
breathing the TCE for long periods may cause nerve, kidney, and liver damage
(ATSDR, 1997). Drinking large amounts of TCE for short periods may cause problems
such as nausea, liver damage, unconsciousness, impaired heart function, and death.
Additionally, drinking small amounts of TCE for long periods may cause liver and
kidney damage, impaired immune system function, and impaired fetal development in
pregnant women (ATSDR, 1997). Workers involved in the manufacture or use of TCE
degreasers may constitute a group at risk because of the potential for occupational
exposure (ATSDR, 1997). The National Occupational Exposure Survey for 1981 to
1983 (NIOSH, 1990) reported that 401,373 employees in the US were exposed to TCE.

People located near or downwind of factories involved in vapor degreasing operations,

as well as hazardous waste disposal sites, or landﬁlls, have experienced effects from
breathing TCE vapors or drinking TCE contaminated water (ATSDR, 1997).

The Environmental Protection Agency (EPA) has limited the TCE concentration
‘ in drinking water to 0.005 ppm (Sppb), and the National Institute for Occupational
Safety and Health Administration (OSHA), has set an exposure limit of 100 ppm of air
for an 8-hour workday, 40—hr workweek. Evidence of carcinogenicity of TCE in
humans suggests that occupational exposure was associated with excess incidences of
liver cancer, kidney cancer, and non-Hodgkin’s lymphoma (W artenberg et al, 2000).
The results in humans are veriﬁed by the presence of tumors at the same sites in
experimental animals. The metabolism of TCE in mice, rats, and humans is similar,
thus, producing the same primary metabolites such as trichloroacetic acid (NTP, 1990).
Consequently, TCE is reasonably anticipated to be a human carcinogen based on

limited evidence of carcinogenicity from studies in humans and sufﬁcient studies in

animals (NTP, 1990).

What is Toluene?

@ms

Figure 1.2 Chemical Structure of Toluene

Toluene is a clear, colorless liquid with a distinctive smell. It is produced during
the gasoline making process from crude oil. It is also used in making paints, ﬁngernail

polish, and in some printing and leather tanning processes. Toluene enters surface water

and groundwater from spills of solvents and petroleum products as well as from leaking
underground storage tanks at gasoline stations and other facilities (ATSDR, 2000). And
when toluene-containing products are placed in landﬁlls or waste disposal sites, the
toluene can enter the soil or water near the waste site. However, toluene does not

usually stay in the environment long.

One can become exposed to toluene by breathing contaminated air, which includes
automobile exhaust, drinking contaminated well water, or living near hazardous waste
sites containing toluene products (ATSDR, 2000). Drinking low to moderate levels can
cause tiredness, confusion, drunken-type actions, memory loss, and nausea. The
inhalation of high levels for short periods causes dizziness, unconsciousness, and
sometimes death (ATSDR, 2000). These symptoms usually disappear when exposure is

stopped.

Toxicological data suggests that a maximum contamination level (MCL) for
toluene in drinking water be 14.3 mg/l (14.3 ppm) (Lederer, 1985). The maximtun
contamination level goal (MCLG) set by EPA for toluene in drinking water is 1 mg/L (1
ppm), while OSHA has set a limit of 200 ppm of workplace air. Previous studies
indicate that toluene does not cause cancer in humans or animals. Therefore, the EPA

has determined that the carcinogenicity of toluene cannot be classiﬁed (ATSDR, 2000).

Rationale of Research
1. Potential for bioremediation

TCE persists in polluted groundwater because conditions are oﬁen not favorable
for biodegradation in aerobic subsurface environments (Agency for Toxic Substances,
1997 and Wilson et al., 1985). Biostimulation is a technology used to create subsurface
conditions in which naturally occurring TCE-degrading bacteria thrive and grow,
resulting in the rapid degradation of the compound.

The widespread occurrence of TCE in groundwater has created public demand
for techniques to remediate aquifers contaminated with TCE. In situ bioremediation
using aerobic cometabolic or anaerobic reductive dechlorination processes is an
attractive approach for TCE contaminated aquifers (Semprini, 1995). Potential
advantages of in situ biological technologies are that TCE is destroyed during the
process rather than being transferred to another place for disposal, and there is no above
ground treatment system required (Mch et al., 1998). In situ treatment also avoids
transporting contaminants to the surface, thereby reducing potential risk exposure to
humans. Pilot-scale studies for in situ bioremediation have shown that certain.
substrates such as toluene or phenol injected into aquifer material stimulated indigenous

TCE-degrading organisms (Jenal-Wanner et al., 1997).

Aerobic transformation processes
There is potential for the restoration of aquifers to be widely successful due to
the in situ aerobic bioremediation of contaminated sites with TCE and its anaerobic

dechlorination products, 1, 2-cis-dichloroethylene (c-DCE), 1, 2-trans-dichloroethylene

(t-DCE), and vinyl chloride (V C) (Hopkins et al., 1993). The likelihood of successful
in situ bioremediation is dependent on the capability of the intrinsic microbial
population to degrade the compounds of interest given the appropriate stimulating
conditions (Jenel-Wanner et al., 1997). Previously, Wilson and Wilson (1985) have
described successful cometabolism of TCE in soil communities fed with natural gas. In
chlorinated aliphatic hydrocarbon (CAH) cometabolism, an oxgenase normally used by
the microorganisms for initiating primary substrate oxidation, transforms the pollutant
(Hopkins et al., 1995). For example, three soil bacterial cultures that catabolize toluene,
Burkholderia vietnamensis strain G4, Pseudomonas putida F1 , and P. putida BS, have
been demonstrated to cometabolize TCE (Wackett et al., 1988). P. putida Fl
metabolizes TCE using toluene dioxygenase (Nelson et al., 1987), as seen in Figure 1.3.
Other toluene degraders use a monooxygenase to degrade TCE, but by the same
pathway. Nelson et al. (1987) used a chloride-speciﬁc electrode to show that all three
chlorine atoms of TCE are converted to inorganic chloride by strain G4. The initial
carbon product of TCE cometabolism, TCE epoxide, (F ig.1.3) further decomposes to
form non-chlorinated compounds, which could then be converted to C02 by enzymatic

or chemical oxidations, or be assimilated into cellular carbon (Nelson et al., 1987).

10

Cl H

\_/
c1 Aer

Trichloroethylene

C‘\/ O \
Cl/'I‘C epoxide\ C1

Toluene dioxygenase

0
0 0
\ + + Cl'
0' 0'
Glyoxylate Formate
F orrnate dehydrogenase
CO2 C02

Figure 1.3: TCE Degradation Pathway with Pseudomonas putida F1.

11

McCarty et al. (1998) have completed several small-scale ﬁeld experiments at
Moffett Field, CA to determine how effective phenol and toluene are in stimulating in
situ bioremediation. Toluene and phenol may stimulate very similar if not the same
monooxygenases active in TCE co-oxidation. It is unknown, however, how similar the
populations are that are stimulated by these substrates or whether they are equivalent in
their TCE-co-oxidizing ability (Fries et al., 1997). The challenge in managing phenol-
or toluene-induced cometabolism of TCE in situ is to selectively stimulate and maintain
active TCE degraders, since in nature many other bacteria grow on the same substrates,
but do not cometabolize TCE (Fries et al., 1997). The previous laboratory and ﬁeld
studies, have not established whether phenol or toluene is a better substrate for
stimulating TCE bioremediation. Hence, a number of factors are signiﬁcant in the
decision to use toluene as the primary substrate.

Toluene, a naturally produced chemical, is a common groundwater pollutant that
is already present at Edwards AFB (Mch et al., 1998). Even though toluene may
already be present, its concentrations are insufﬁcient to induce cometabolic degradation.
Laboratory and ﬁeld studies reveal that toluene concentrations well below lug/L result
from toluene biodegradation by indigenous aquifer microbes in the Moffett ﬁeld
treatment system (Hopkins et al., 1995). The observed concentrations are several orders
of magnitude below the MCLG for drinking water (1mg/L) and an order of magnitude
below the taste threshold (120-160 ug/L) (Mch et al., 1998). Thus, the use of

toluene has become the favored substrate for in situ cometabolic remediation of TCE

(Mch et al., 1998).

12

Anaerobic biotransformation processes

Tetrachloroethene (PCB), another potentially toxic chlorinated ethylene can be
transformed anaerobically to TCE (Fig. 1.4), then to a series of sequentially lesser
chlorinated products, and ﬁnally to ethene and C1' by anaerobic reductive
dehalogenation (V ogel et a1. 1987). Tetrachloroethene and trichloroethene are
transformed to less chlorinated ethenes by slow, anaerobic, cometabolic processes by
methanogenic, homoacetogenic, and sulfate reducing microorganisms or by a faster,
anaerobic, halorespiring process (Loefﬂer et al., 2000). In the latter case, microbes can
gain energy for growth by using the chlorinated ethenes as electron acceptors and
coupling this exergonic reaction to ATP formation. This process results in a much faster
rate of dechlorination. Members of the genera Desulfuromonas, Dehalospirillum,
Dehalobacter, Desulﬁtobacterium and Dehalococcoides reductively dechlorinate PCB
and TCE, and some Dehalococcoides can complete the reduction of cis-DCE and VC
(vinyl chloride) to ethene and chloride (Loefﬂer et al., 2003). The restoration of some
anaerobic polluted environments can be credited to the natural activities of these
anaerobic dechlorinating populations in aquifers where this anaerobic process is active
(Gerritse et al., 1999). When PCE is present in the contaminating solvent mix, the
anaerobic chlororespiring approach is the only feasible bioremediation process since
PCE cannot be co-oxidized by natural populations. But if only TCE is present, and the

aquifer is primarily aerobic, then the cometabolic approach is feasible and likely faster.

13

 

 

 

Cl \ / Cl
C C Tetrachloroethene
/ \ Cl
Cl 211* + 2c'
Tetrachloroethene reductive
dehalogenase HCI
Cl CI
\ / Trichloroethene
/ C C \
H
Cl
2H+ +2e'
Trichloroethene reductive
dehalogenase HCI .
C] 1-1

\ /C| Cl\

C

C + C C/
Cl / \ H/ \

 

 

 

 

I

- Cl
ctr-Dichloroethene trans-Dichloroethene
2H+ + 2e'
Dichloroethene reductive
dehalogenase
HCl
c1 \ H
C — C Vinyl Chloride
Cl / \ H
2H+ + 2e'
Vinyl Chloride reductive
dehalogenase
HCI
C — C Ethylene

/
H/ \

H

Figure 1.4: Anaerobic Tetrachloroethene Pathway.

14

Dechlorination may result in the build-up of toxic products that are formed
biologically from the primary pollutants. This is particularly a concern for the
reductive dechlorination of PCB and TCE since cis-dichloroethene (cis-DCE) and vinyl
chloride (V C) both tend to accumulate. Both are toxic and the later is a human
carcinogen (Wackett et al., 1988). In this regard, the use of an aerobic cometabolic
approach carries less risk for TCE remediation because of its potential to produce C02
and Cl' as end products, and it does not accumulate toxic intermediates.

The need for remediation at Edwards AFB centers on the potential contact of
TCE with soil where it is less easily evaporated than in surface water. Thus, this study
will largely focus on understanding how effective the selected indigenous populations
are at TCE degradation and how their TCE oxidizing capacity compares to that of well-
studied strains, i.e., Burkholderia vietnamiensis G4. This study will also enable us to
examine the dynamics of the communities in response to toluene injection, such as the
extent of diversity among the selected toluene degrading strains and the dominance

maintained in the ﬁeld over time.

II. Field evaluation of toluene-driven cometabolic remediation of T CE

Moﬂett Field pilot study

A pilot-scale study at Moffett Field demonstrated the aerobic cometabolic
biodegradation of TCE and other chlorinated alkenes would be successfully stimulated
in the ﬁeld (Mch et al., 1998). At Moffett Field, microbial community composition
and succession were evaluated in an aquifer amended with phenol, toluene, and

chlorinated aliphatic hydrocarbons such as TCE and 1,1-dichloroethene (1,1-DCE)

15

(Fries et al., 1997). The populations in the aquifer were isolated, identiﬁed, and their
TCE degrading abilities determined (Fries et al., 1997). Fries et a1. (1997) used
genomic ﬁngerprints determined by repetitive extragenic palindromic (REP)-PCR as a
measure of genetic diversity of the phenol and toluene degrading community. The
results indicated that only a few gram-positive isolates were obtained after treatment
with phenol +l,1-DCE (~2 rep-PCR groups), compared to the initial isolates with no
treatment (~14 rep-PCR groups) (Fries et al., 1997). Although microbial densities
increased following phenol-TCE treatment (~5 rep-PCR groups), the original species
richness was restored, following toxic 1, l —DCE, only after the toluene-TCE treatment
(~13 rep-PCR groups). Also, TCE removal efficiency was much greater with either
phenol or toluene than with methane (>85% versus 15%). In essence, this study
concluded that taxonomically diverse communities of indigenous aquifer phenol and
toluene degraders with moderate but satisfactory TCE-degrading ability were stimulated
by the addition of the primary substrates. Both gram negative and positive bacteria
were found: the former included members of the genera Burkholderia, Variovorax, and
Azoarcus, all from the phylum Proteobacteria and the later included members of the
genera Rhodococcus and Nocardia, all from the phylum Actinobacteria of high G+C

content (Fries et al., 1997).

Edwards AFB study
Following the pilot-scale study at Moffett Field, this technology was tested at
full-scale at Edwards AFB, CA, a TCE contaminated site. From 1958 until 1967

engines for the X-15 rocket plane were stored in facilities at the Edwards AFB

16

(Mch et al., 1998). One 55-gallon drum of trichloroethylene (TCE) was used each
month to clean the engines, and afterwards, was dumped in the nearby desert creating a
large groundwater contaminant plume (Mch et al., 1998). This resulted in TCE
contamination of both the upper and lower aquifers at Edwards AFB.

Edwards Air Force Base (AFB) was originally established in 1933 and occupies
470 square miles in the Mojave Desert. It is the home of the Air Force Flight Test
Center (AF F TC), the Air Force Research Laboratory (AF RL), and National Aeronautics
and Space Administration (NASA), and involved in aircraft research, development, and
testing. It was placed on the National Priorities List (NFL) in 1990. In December 1999,
over 460 sites and Areas of Concern (AOC) have been identiﬁed on the Base (The
Edwards Air Base Installation Restoration Program: An Investment Report, 2000). The
Edwards AFB is unique to other Air Force Bases because of the large size of the Base
(470 sq. miles), the large number of sites, the extreme temperatures, and rocket engine
research missions.

The cometabolic degradation of TCE was tested at site 19 as a cooperative effort
among the US. Air Force, USEPA, Stanford University, and Oregon State University.
The indigenous bacteria use oxygen as “air” and toluene as “food” and produce the
toluene monoxygenase enzyme (TMO) which degrades the TCE in the groundwater
(The Edwards Air Base Installation Restoration Program: An Investment Report,
2000)

A microcosm study was carried out using Edwards AFB soil to predict
treatment performance. The results, which differed with location and varied between 87

and 99% TCE removal, mimicked the cometabolic biodegradation at Moffett Field and

17

indicated that TCE removal by cometabolism should also work here (J enal-Wanner al.,
1997). Hence, a full-scale remediation experiment involving cometabolism of TCE in
the Edwards AFB plume was then attempted by Stanford University engineers. The
research focused only on evaluating the effectiveness of the cometabolic process in
removing TCE with no measures of the microbial population response. My study

focused on the microbial community and was done to complement their research.

18

10.

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30. Munakata-Marr, Junko, V. Grace Matheson, Larry J. Forney, James M.
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38. Taylor, R.T.1993. In situ bioremediation of trichloroethylene-contaminated
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39. The Edwards Air Force Base Installation Restoration Program. 2000.
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22

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23

Chapter II

Microbial community response during a ﬁeld evaluation of toluene as the primary
substrate for TCE co-oxidation.

Introduction
Trichloroethene (TCE), a well-known groundwater pollutant, is of great concern

throughout the United States. It has been widely used as a solvent to remove oil and
grease from metal parts. TCE has moderate water solubility (~1100 ppm), hence, it is
mobile in soils and often found as a groundwater contaminant. It is denser than water
and hence can also migrate through soils and sub-soils as a DNAPL. According to the
EPAs Contract Laboratory Program Statistical Database, TCE is reported to occur in
19% of groundwater samples at a geometric mean concentration of 27.3 ppb

(individually ranging from 0.1 to 27,300 ppb).

Pilot-scale studies for in situ bioremediation have shown that certain substrates
such as toluene or phenol injected into aquifer material stimulated co-oxidation of
indigenous TCE-degrading organisms (Jenal-Wanner et al., 1997). McCarty et a1.
(1998) completed several small-scale ﬁeld experiments at Moffett Field, CA which
showed that phenol and toluene stimulated in situ TCE bioremediation. The microbial
community composition and succession were also evaluated in response to the phenol,
toluene, and chlorinated aliphatic hydrocarbon treatments (Fries et al., 1997). The TCE
removal efﬁciency was much greater with either phenol or toluene than with methane
(>85% versus 15%) and taxonomically diverse communities of indigenous phenol and

toluene degraders with TCE-degrading ability were stimulated. Both gram negative and

24

positive bacteria were found: the former included members of the genera Burkholderia,
Variovorax, and Azoarcus, all from the phylum Proteobaeteria and the later included
members of the genera Rhodococcus and Nocardia, all from the phylum Actinobacteria
of high G+C content (Fries et al., 1997).

A microcosm and full-scale study done at Edwards AFB, a site contaminated
with TCE and amended with toluene, concluded that TCE removal between 87%-99%
and 83%-87%, respectively, occurred by cometabolic degradation. Because of the
success of their studies at Edwards AFB, another full scale test of TCE remediation by
cometabolism was undertaken to test the combination of bioremediation coupled with a
vapor stripping system. The Stanford engineering team evaluated the effectiveness of
the cometabolic process in removing TCE and 1 evaluated the microbial community
response by measurements at three sampling periods: before toluene injection (June
2000); one month after the initial injection of toluene (November 2001); and 3 months

after toluene injection (late January 2002, at the end of the experiment).

25

Materials and Methods
Site Description. Edwards AFB, located about 60 miles north of Los Angeles, was
selected by a team of Stanford University scientist and engineers because it presented
ideal conditions for the study. The groundwater plume was aerobic and contaminated
with approximately 500-1500 rig/L of TCE and no PCE. At the site are two bio-
treatrnent wells, each with two aquifers, upper and lower, separated by a silty clay
aquitard of low permeability. The upper aquifer is unconﬁned while the lower aquifer
is conﬁned and lies above weathered bedrock (Fig. 2.1). The sediments are of alluvial
origin and lacustrine deposits (Mch et al., 1998). The aquifer material consists of
ﬁne to medium size sand with some silt. Sieve analysis of aquifer material from
borings at the evaluation site at four depths indicated that the lower aquifer material is
somewhat larger {suter mean diameter dsm=0.4 mm} and better degraded {coefficient of
uniformity Cu=7; coefficient of gradient Cg=l} than upper aquifer material {d,m=0.2
mm; Cu=4; Cg=1) (Mch et al., 1998). The permeability should allow the

groundwater to be mixed effectively by pumping.

26

  
   

 

T

7 Meters 1'0“!quPe’foxlde,,,0xy9en

 

Treatment

 

 

 

 

 

 

 

Figure 2.1. A cross-sectional view of a two-well cometabolic TCE biodegradation treatment system
spanning two separate aquifers. Also illustrates wells screened in both shallow upper aquifer and deeper
lower aquifer. This was the ﬁrst full-scale test implemented at Edwards AFB (McCarty et al, 1998).

Previous ﬁeld test design. The Stanford engineering team implemented the following
full scale remediation design to treat the groundwater contaminated with 500-1200ug/L
TCE in situ over a 410-day period by co-metabolic biodegradation. A submersible
pump capable of delivering a ﬂow rate of 10 gallons per minute (gpm) was installed
between the two screens of each bio-treatrnent well located 10 m apart to induce the
ﬂow ﬁeld shown in Fig. 2.1 (Mch et al., 1998). Well 1 withdrew groundwater from
the upper aquifer and discharged it into the lower aquifer and well 2 did the reverse.
This caused the water to circulate between the two aquifers (Fig. 2.1) (Mch et al.,

1998). Toluene and oxygen, added in pulses for a timed concentration of 7-13.4 mg/L,

27

were introduced into the two wells through feed lines and mixed with the TCE-
contaminated water (Mch et al., 1998). Following 18 days of periodic toluene
injection to develop an active biological population, continuous pulses were added.
Oxygen was added because of the potential bactericidal properties of hydrogen
peroxide. However, hydrogen peroxide was later used to prevent the clogging of pores
near the injection wells (Mch et al., 1998).

This full-scale test indicated that 87% TCE removal was achieved in the upper
aquifer with each pass through the treatment well and 83% in the lower aquifer,
consistent with the predicted results of 87-99% removal in the Edwards AFB soil
(Mch et al., 1998). In addition, 99% toluene was removed through biodegradation
and biomass distribution throughout the treatment zone was contingent on where
toluene consumption was the greatest, which was usually within the ﬁrst couple of

meters from the treatment wells (Mch et al., 1998).

Design for full-scale test with a vapor-stripping system. This full-scale TCE treatment
system, also designed by the Stanford team included a TCE vapor stripping system
since preliminary studies suggested it was necessary to reduce TCE to non-toxic levels
for the bioremediation. Hence, the Bio-Enhanced In-Well Vapor Stripping (BEHIVS)
system was implemented in a different location on the same TCE plume, but much
closer to the source of TCE contamination where TCE concentrations were much
higher. The system consists of one vapor stripping well (up-ﬂow) pumping at 8 gpm
and two bio-treatrnent wells (down-ﬂow) pumping at 4 gpm each (Fig. 2.2). Each well

has two aquifers, upper and lower, separated a clay aquitard of low-permeability. The

28

ﬁgure below (Fig. 2.2) shows that the vapor stripping well creates a raised water
gradient that aids the water cycling in the upper aquifer. TCE-contaminated water is
pumped up through the lower aquifer to the upper aquifer of the vapor-stripping well
and then dispersed out to the upper aquifer of the bio-treatrnent wells pumping down-
ﬂow to the lower aquifer where toluene, 02 and less TCE-contaminated water ﬂowed.
The vapor stripping well (D04) and bio-treatrnent wells (Bio 1, Bio 2) (Fig. 2.3a),
created the groundwater ﬂow shown in Fig. 2.3b. Also included in this BEHIVS
system are 20 nested (deep and shallow) monitoring wells in the test zone (Fig. 2.3a and
2.3b). The monitoring wells could be easily installed because the groundwater surface

lies about 9 m below the ground surface.

BEHIV S System

'Vapor stripping well Biotreatment “well!

 

 

Alluvium
(sand, silt,
gravel)

Weathered
bedrock

   
 

NAPL- ,
containing V i ' I "' i V Aquitard

fractures

 

Bioactive
zone

 

 

Figu're'2:2.‘ Schematic of treatment system showing the physical characteristics
(Gandhi, et al, 2000).

29

 

BEHIVS Site Well Locations

(meters)

Y

N13

I 201113) 2011140

 

Figure 2.38. Aerial View of the site locations within the BEHIVS system. The BEHIVES system includes the vapor stripping well (D04)
bio-treatment wells (Bio). The other wells are monitoring wells (MW) and (T) and nested wells (N). The remaining wells were not

mmined.(Gsndhi,, et al, 2000).

sndthe

 

 

658810 '

658790

658780

658770

658760

  

2.01108E+06 2.0111E+06 X 2.01112E+06 2.01114E+06

 

 

Figure 2.3b. Simulated Flow Field at Edwards AFB created by one up-ﬂow well and two down-ﬂow bio—treatment wells.

(Gandhi, ct al, 2000).

30

 

 

Collection of microbes from groundwater samples. High throughput ﬁlters, which had
50 gallons of monitoring well water run through them, were used to collect the
microbial biomass from the site. The commercial ﬁlters (Parker Process Filtration,
Lebanon, IN) were made of thick layers of yarn raveled together to create a hollow
cylinder. The yarn cores were removed from their holder, placed in plastic bags along
with some of the water contained in the ﬁlter housing, and transported on dry ice in
coolers overnight to Michigan State University (MSU). On arrival, unfrozen samples
were kept at 4°C until analysis, which was within 7 to 10 days.
Biomass collection. The ﬁlters were unraveled with the aid of a sterile scalpel and
forceps, and all contents placed in a sterile 2 L beaker. Sterile 1M sodium phosphate
buffer (pH 7) was then added to cover the ﬁlter parts and the beaker was covered with
aluminum foil. Each beaker was placed on a rotary shaker in a 4°C room and operated
at medium speed overnight. The buffer was then poured off into 4L sterile ﬂasks. The
beakers were ﬁlled again with sterile buffer and placed on the shaker for 2h. When that
buffer was poured off, additional buffer was used to rinse the parts. The combined
collection solution was centrifuged at 5000 rpm in sterile centrifuge bottles to collect
cell pellets. A pellet was noticeable in some of the samples. A ﬁlter control sample
was processed in the same way except no water was passed through the ﬁlter.
Terminal Restriction Fragment Length Polymorphism (TRFLP)

In order to determine the initial community structure of the site at Edwards
AFB, 16S rRNA TRFLP was done on water samples taken before toluene injection
(background). A 1 mL solution of the cell pellet was resuspended in 50 mL of sodium

phosphate buffer. DNA was extracted using the M0 BIO Ultra-Clean Soil DNA

31

Isolation Kit (MO BIO Laboratories Inc., Carlsbad, CA). DNA recovery was
assessed on a 0.8% agarose electrophoresis gel, and quantiﬁed at 260 nm by UV
spectrophotometry. Total DNA was ampliﬁed using the Polymerase Chain Reaction
(PCR) with the ﬂuorescently labeled primer, 8F, (E. coli numbering) {8 forward --5’
AGAGTITGATCMTGGCTCAG 3’} and the reverse primer 1392{1392 reverse --5’
ACGGGCGGTGTGTACA 3’}(Amann, et al, 1995). The primers along with the DNA
were added to a master mix containing ReadyMixTM RedTaqTM PCR Reaction Mix with
MgClz (Sigma, St. Louis, MO). This PCR generated a mixture of amplicons of the same
size and with a ﬂuorescent label at the 5’ end. The PCR cycle used for ampliﬁcation
was: 95°C 3 min-Hot Start/Denaturation, 30 cycles of {94°C 30 sec denaturation, 55°C
45 sec annealing, 72°C 1 min elongation} followed by 72°C at 7 min-ﬁnal extension
held at 4°C.

After three (3) replications of PCR, the amplicons were combined and puriﬁed
using the QIAquick PCR Puriﬁcation Kit (Qiagen, Valencia, CA). The puriﬁed DNA
product was quantiﬁed by UV spectrophotometry and by gel visualization. The
samples were then digested with restriction enzyme HpaI 1 . The master mix consisted
of 1 pl 10X buffer, 1 pl BSA, 0.5 pl restriction enzyme (10 U/pl), and 2.5 pl water.
Digestion occurred for 2-3 h at 37°C using 5 p1 of PCR product. The enzyme was
inactivated by heating the digest to 65°C for 15 min.

Two micro liters of TAMRA GS 2500 marker (Perkin Elmer) was added to 2 pl
of the digested PCR products. The combination was separated in a 6% polyacrylamide
gel in a DNA sequencer (373 ABI Stretch) for 14 h at 168 volts. The data was viewed

using Gene Scan software version 3.1.

32

Community similarity. Community similarity before toluene injection (TRF LP) was
calculated using the Morisita index, as described by Dollhopf et al (2001). The Morisita
index of community similarity, which is based on Simpson’s dominance index, was
calculated using the formula
1M=2_Zﬂﬂﬂzt
(11+12)N 1N2
where n] is the number of individuals of species i, N is the total number of individuals
sampled and l is Simpson’s dominance index for each community. The formula for
Simpson’s index is
l= 2?(ni(ni-I))
n=1
N(N-1 )
where s is the total number of species in the community. The index ranges from 0 to 1,
with 0 designating that no species are shared between the two communities and 1
meaning there is complete identity. Because the index takes species abundance into
account, communities that contain the same species but have different species
abundance will have an n index value less than 1. The data will be reﬂective of
recognizing each terminal restriction fragment as a separate species and peak height as a

measure of species abundance.

33

Burkholderia cepacia analysis. Samples were analyzed for Burkholderia cepacia
complex (Bee) by using Bee-speciﬁc recA primers. Edwards’ samples taken three
months after toluene was added to the wells (end of the experiment) were analyzed for
the presence of the recA gene. DNA was extracted using the MO BIO UltraClean Soil
DNA Isolation Kit (MO BIO Laboratories Inc., Carlsbad, CA). DNA recovery was
assessed on a 0.8% agarose electrophoresis gel, and quantiﬁed at 260 nm by UV
spectrophotometry. The RFLP pattern or the nucleotide sequence is a rapid and
reproducible means of identifying the genomovars within the B. cepacia complex.
BCRl (5’- TGACCGCCGAGAAGAGCA-3’) and BCR2 (5’-
CTCTTCTTCGTCCATCGCCTC-3’) were designed by Mahenthiralingam et. a1 (2000)
from homologous sequences at the 5’ and 3’ end of the recA open reading frame and
amplify a single l-kb amplicon from all strains representative of the Bee.

The DNA samples were analyzed by PCR using a master mix of ReadyMixTM
RedTaqTM PCR Reaction Mix with MgClz (Sigma, St. Louis, MO). The positive control
was Burkholderia vietnamiensis G4. The PCR cycle used for ampliﬁcation was: 95°C 3
min-Hot Start/Denaturation, 30 cycles of {94°C 30 sec denaturation, 58°C 45 sec
annealing, 72°C 1 min elongation} followed by 72°C at 10 min-ﬁnal extension held at
4°C. The amplicons generated were then puriﬁed using the QIAquick PCR Puriﬁcation
Kit (Qiagen, Valencia, CA). The puriﬁed DNA product was quantiﬁed by UV
spectrophotometry and by gel visualization. Finally, the products were taken to GTSF
at Michigan State University to be sequenced in order to determine if the samples that
were selected using the recA primers were indeed members of the Burkholderia cepacia

complex.

34

High-Throughput Sequencing of Clone Libraries

To better determine the active microbial communities in the Edwards AFB well
samples, I prepared clone libraries of 16S rRNA genes in the aquifer water before and
after substrate addition. The wells analyzed for the subsequent analysis were chosen in
relation to their location to the Bio-treatment wells (BIO) (Fig. 2.4). I used: NlL and
NSL-wells upstream of B10; MW23L and N1 1L-wells nearest BIO; and N16L and
N18L-wells downstream of B10. The sampling times were: before toluene injection
(background); one month after toluene injection (initial); and three months after
toluene injection (end of the experiment). DNA was extracted from all samples using
the M0 BIO UltraClean Soil DNA Isolation Kit (MO BIO Laboratories Inc., Carlsbad,
CA). DNA recovery was assessed on a 0.8% agarose electrophoresis gel, and
quantiﬁed at 260 nm on an UV spectrometer. DNA was ampliﬁed using the Polymerase
Chain Reaction (PCR) with the universal primer (E. coli numbering) 8-27F {8 forward -
-5’ AGAGTTTGATCMTGGCTCAG 3’} and the reverse primer 1392-1406R {1392
reverse --5’ ACGGGCGGTGTGTACA 3’}(Amann, et al, 1995). The primers along
with the DNA were added to a master mix containing ReadyMixTM RedTaqTM PCR
Reaction Mix with MgClz (Sigma, St. Louis, MO). The PCR cycle used for
ampliﬁcation was: 95°C 3 min-Hot Start/Denaturation, 30 cycles of {94°C 30 sec

denaturation, 5 5°C 45 sec annealing, 72°C 1 min elongation} followed by 72°C at 7

min and a ﬁnal extension held at 4°C. The amplicons generated were then puriﬁed
using the QIAquick PCR Puriﬁcation Kit (Qiagen, Valencia, CA). The puriﬁed DNA

product was quantiﬁed by UV spectrophotometry and by gel visualization.

35

658840

658830

658820

658810

Y
(meters)

658800

658790

658780

658770

2011070 2011080 2011090 2011100 2011110 2011120 2011130 2011140
X(meters)

Figure 2.4: Well diagram of only the samples that were analyzed. 9 represents the

\ Gradient
\

 

 

N-5-L

 

NLl-L

0 13102

 

oN-fu-L

 

 

R»

I. MW23I

IAN-rs-L

 

 

- 16-L

 

 

 

 

 

 

 

 

 

 

biotreatment wells (B101 and BIOZ) amended with toluene, L—J represents samples
upstream of B101 and B102, 0 represents samples nearest B101 and B102, and A

represents samples downstream of B101 and B102. The images seen here as well as

several other images in this dissertation are presented in color.

36

 

Cloning. Puriﬁed PCR products were cloned using the TOPO-TA cloning kit with the
PCR 2.1 Vector according to the manufacturer’s protocol (Invitrogen, Carlsbad, CA).
To set up the reaction, the following components were needed: 2 pl of fresh PCR
product; 2 pl sterile water; 1 pl salt solution and 1 pl TOPO vector (each from the
TOPO TA Cloning Kit). The reagents were mixed gently and then incubated for 5 min
at room temperature. The reaction was immediately placed on ice or at -20°C overnight
before the One Shot Chemical Transformation. Two micro liters of the cloning reaction
was added into a vial of one shot chemically competent E. coli and mixed gently. The
cells were incubated on ice for 30 min and then heat shocked for 30 sec. at 42°C
without shaking and again transferred to ice. Then, 250 pl of the SOC medium (2%
Tryptone, 0.5% Yeast Extract, 10 mM NaCl, 2.5 mM KCl, 10 mM MgC12, 10 mM
MgSO4, and 20 mM glucose) was added and the vials were placed horizontally on a
shaker (200 rpm) at 37°C for l h. Afterwards, 10-150 pl of each transformation was
spread on a pre-warmed Luria Bertani (LB) plates containing 250 pl ampicillian, 500 pl
IPTG (4%), and 500 pl XGAL (4%), and incubated overnight at 37°.

For analysis, LB Freezing Buffer (LBFB) was used. The pH was corrected to
7.5 with NaOH and the following was added: K21-1P04 12.6 g; KH2P04 3.6 g; sodium
citrate, dehydrate 1.0 g; MgSO4'7H20 2.0 g; ammonium sulfate 1.8 g; and glycerol 88.0
ml. After the volume was adjusted to 2 L, 500 p1 was transferred to individual bottles
and autoclaved. Once cooled, 83 pl of ampicillian (300 ng /ml) was added to each

bottle.

37

Sterile toothpicks were used to pick up well-deﬁned white colonies from the LB plates
and place them into each well of a growth block containing 600 pl of the LBFB. When
completed, air pore paper was used to cover the blocks. The growth blocks were then
placed on a shaker at 37 °C overnight.

Sequencing. One hundred micro liters was taken from each well of the growth blocks
and placed in the same position in the 96-well micro-plates. Once completed,
aluminum foil was used to cover the plate to avoid contamination and the plate taken to
the Genomic Technology Support Facility (GTSF) at Michigan State University, East
Lansing, MI 48824. DNA from E. coli clones was puriﬁed at GTSF using Qiagen 3000
robots. Once the ﬂuorescent-labeled sequencing products were generated by PCR
ampliﬁcation, the products were separated by capillary electrophoresis on an ABI Prism
3700 DNA Analyzer. The sequence from GTSF was piped to a F inch-Server (copyright
2000 Geospiza, Inc., Seattle, WA. http://www.geospiza.com), a web-based interface for
retrieving sequencing data. The data were then ﬁltered for quality and classiﬁed by the
Ribosomonal Database Projects (RDP) classiﬁer according to Bergey’s Hierarchy. This

output was compared among wells and sampling times.

38

Determination of significant differences within communities. The difference in
occurrence of microbial taxa was analyzed based on the Bayesian method. Given the
usual community complexity, observing a given taxon qualiﬁes as a rare event, as the
abundance of most individuals are of the order of a few percents or less (Audie et al,
1997). The probability of a given 16S rRNA gene sequence to be picked up x times
when the sampling size was N1, and y times when the sampling size was N2 is given by

the formula:

 

Pear-E. ’ (x+y)

xly! 1+132) (“Y“)
N1

whereas signiﬁcant differences between x (from one library) and y (from the other) will
characterize different communities, i.e., the relative abundance of which is unlikely to
be the same in the two libraries, each having different sampling sizes. If the probability
(P) is less than 0.01 (102), the difference in x and y is signiﬁcant (Audie et al, 1997).

The probability was calculated by the Ribosomal Database Project (RDP) at MSU.

39

Results

Community composition. DNA was extracted ﬁ'om the cotton ﬁlters (4°C) that had
I recovered microbes from six sampled wells at Edwards AFB. A PCR ampliﬁcation
using 16S rRNA primers 8F and 1392R showed that bacteria were present in all
samples (Fig. 2.5). Once the samples were puriﬁed the DNA concentrations were
measured to ﬁnd out how much of the DNA remained in those samples (Fig. 2.6). A
blank sterile ﬁlter extracted in the same way produced no detectable DNA.

T-RFLP analysis was used to assess the similarity in community structure
among the six wells before toluene was added. The digested fragments ranged from 30
bp to 565 bp in length. Some of the communities within the different wells (Fig. 2.7)
were quite similar in that they contained several of the same fragments but not in the
same quantity. For instance, all have the presence of a dominant 207 bp fragment. The
species that represent this fragment have densities comprising more than 90% of the
community (N-l l-L), but only 40% of N-5-L. Thus, these communites had a similarity
index of 0.74 (T able 2.1). The next dominant T-RF has 93 bp. It is also prevalent in
almost all of the samples. Although it is not as dominate as 207 bp, it does constitute
almost 40% of the total proﬁle for the N-S-L well community, but as low as 10% for
others such as N-18-L. These two communities when compared to each other have a
similarity index of 0.66 (T able 2.1). Most of the remaining fragments are distributed in
lesser percentages within each community.

While most of the proﬁles contain T-RFs 143 bp, 137 bp, and 127 bp, they are
not prevalent in all the communities. The amount of DNA recovered from each well

varied considerably (Fig. 2.6). There was no apparent correlation between the puriﬁed

4o

DNA concentrations (Fig. 2.6) and the community proﬁle (Figure 2.7). The TRFLP

analyses indicated that even though the same fragments (representing different taxa)

were present in a majority of the well samples, they were not as evenly distributed in

the well communities before the toluene injection as evidenced by the average

community similarity indices of 0.77, 0.81, 0.83, 0.81, 0.72, and 0.78 among the wells

i.e., N-l-L, N-S-L, MW23-L, N-l l-L, N-16-L and N-18-L, respectively (Table 2.1).

Lane 1:
Lane 2:
Lane 3:
Lane 4:
Lane 5:

Lane 1:
Lane 2:
Lane 3:

Lane 4:
Lane 5:

Marker
N9L
MW23D
T1 1
N10L

Marker
N5L
N6L

N1 6L
N7L

 

Lane : N18L
Lane 7: N19L
Lane 8: N4L
Lane 9: N12L
Lane10:Nl7L

Lane 6: N13L
Lane 7: Blank
Lane 8:
*Positive Control
Lane 9: Blank
Lane 10:
*Negative Control

Figure 2.5. PCR Results for the samples using 16S rRNA primers.

Positive control=E. coli; Negative control=blank ﬁlter

41

Table 2.1. Morisita community similarity indices for the six well communities, N-l-L,
N-5-L, MW23-L, N-l l-L, N-16-L, and N-l8-L.

 

Sample Well Communities

 

 

N-l-L N-S-L MW23L N-ll-L N-l6-L N-18-L

N-l-L l 0.76 0.80 0.88 0.66 0.73
N-S-L 0.76 l 0.96 0.74 0.66 0.66
MW23-L 0.80 0.96 1 0.80 0.81 0.77
N-ll-L 0.88 0.74 0.80 l 0.67 0.92
N-l6-L 0.66 0.91 0.81 0.67 1 0.80
N-18-L 0.73 0.66 0.77 0.92 0.80 1

Average 0. 77 0. 81 0. 83 0. 81 0. 72 0. 78

 

 

Purified DNA Concentrations of Background Samples
for T-RFLP Analysis

 

NW 9) ’\ QNW'bb-bK‘bQK (55"0
ssfisfeffassssssssgggeee

Sample Names

 

 

 

Figure 2.6. Puriﬁed DNA concentrations for the various wells taken before the toluene treatment began.

42

 

 

 

 

 

IN I& use [181 I87 I93 I1(BD127I137I143D1&IZJ7I335I344I®IW1I416I449
D479D4Ql5133540I552ﬂﬁ

 

 

Figure 2.7. TRFLP analysis of background communities taken from 24 different wells.
Sizes of colored bars reﬂect peak heights of different T-RFs (terminal restriction
fragment). U N-l-L and N-S-L, 9 N-l l-L and MW23L, and A N-16-L and N-18-L
all reﬂect wells that will be ﬁrrther analyzed.

43

 

Temporal analysis of populations. A clone library of the 16s rRNA genes was
constructed and clones sequenced in order to indicate potential community members
with a matching TRF. Comparative analyses of the populations present in the Edwards
AFB samples before and after toluene injection were evaluated. The results are based on
RDPs classiﬁer analysis which is based on Bergey’s Taxonomy. Bergey's Manual of
Systematic Bacteriology is the authoritative descriptions of all prokaryotic species
validly described (Staley, 1989). Also, based on probability statistics, the populations
in the communities are determined to be signiﬁcantly different when the probability (P)
is less than 102. The percentages (%) identiﬁed here are representative of the total
number of populations from each commtmity. These results show that collectively, all
six (6) well samples taken before toluene injection (background) was not as evenly
represented by all populations as the samples after injection (initial and end). This was
further examined by comparing the background vs. initial (Fig. 2.8-2.10). For
example, the genus Pseudomonas occupied 65% of the total community before toluene
injection and only 24% of the total community after the initial injection. The
probability test shows that the likelihood of the Pseudomonas populations representing
the same percentage of both communities is highly unlikely and is thus signiﬁcantly
different (P=10'1°). These results further show that as you add toluene, the
Pseudomonas population was not as abundant, as other populations were stimulated. In
contrast, the Sphingomonas population was enriched (16%) as toluene was added over
its background (3%) population. The probability that Sphingomonas would occupy the

same fraction of the background and initial communities was low (P=10 ’3'5), which

44

means this particular population is signiﬁcantly different in the number of members
represented in both communities

When comparing background vs. end samples (Fig. 2.11-2.13), there was also a
signiﬁcant difference with Pseudomonas, Sphingomas, and Legionella populations.
Pseudomonas ﬁrst occupied 65% of the total background community and then only
27% of the end community resulting in a decreased probability of occurrence (P=10"3)
in both communities. Sphingomonas represented 3% of the background community
but 28% of the end community so there is a very high chance that both communities
will not be represented by the same quantity of Sphingomonas species as is evident by
the probability of occurrence (P=10'13). Legionella on the other hand was not present in
the background community, but was signiﬁcantly enriched (10%) in the end
community, and thus signiﬁcantly different (P=10’8). Whereas there was a difference in
Legionella when background samples were compared to end samples, there was no
difference when comparing background to initial samples, zero and two sequences,
respectively. Because of this uneven distribution, no signiﬁcant difference between the
two earlier samples was noted (P=10'1). This could indicate that the longer toluene is in
the system, the greater the Legionella population. These results also indicate that
Sphingomonas and Legionella had similar trends as it relates to their abundance when
toluene was added.

Comparison of the initial samples vs. end samples (Fig. 2.14-2.16) indicate that
there is no difference (P=10"'5) in the Pseudomonas population, which represents 24%
of the initial community, and 27% of the end community. These analyses also show a

trend of increasing frequency of the Sphingomonas and Legionella populations.

45

Sphingomonas was signiﬁcantly different (P=10'3) occupying 16% of the initial
community composition and then had a shiﬁ to 28% of the end community. And it is
also not likely that Legionella would occur in both communities(P=10'3'5) embodying
2% of the initial composition and 10% of the end community.

The results of the changing community proﬁles of the background, initial, and
end samples are summarized in Fig. 2.17.
Spatial analysis of populations. The same data was compared to determine any spatial
patterns of populations present in the Edwards AFB samples. The two (2) wells located
upstream of the bio-treatment wells, N—l-L and N-S-L were tested against wells nearest
the treatment wells, MW23L and N1 1L and wells downstream of the treatment wells
N16L and N18L. Data from all three sampling wells are included in this analysis. Well
samples nearest and downstream of the treatment wells show a richer composition than
the wells upstream of the treatment wells. This is demonstrated in Figures 2.18-2.20
where again Pseudomonas was not as evenly distributed in the well community nearest
the bio-treatrnent wells (26%) as it was in the upstream community (51%). Thus the
probability of Pseudomonas representing the same fraction of both communities was
low (P=10'2‘1). This spatial analysis also showed a signiﬁcant reduction in the
Sphingomonas populations for the upstream to nearest wells with Sphingomonas
representing 21% and 11%, respectively of each well community. Legionella, however,
was much more plentiful in the wells nearest the treatment wells representing 11% of
the community than it was in the upstream community where 0% of the population was

represented and thus the probability of occurring in both wells was low (P=10'7).

46

In the evaluation of the upstream well samples to the well samples downstream
of the treatment wells, again there was a signiﬁcant decline in the Pseudomonas
population from 51% to 23%, respectively. However the Sphingomonas populations in
these two systems were not signiﬁcantly different representing 21% and 24% of the two
communities. But, the Legionella population was signiﬁcantly more abundant, from not
being represented in the upstream well community and then representing 9% of the end
community.

The well communities nearest the bio-treatment wells compared to the
communities downstream of the treatment show that Pseudomonas basically
represented similar fractions of both community (26% and 23%, respectively), so the
probability of occurring was relatively high (P=10'”). Also, the Legionella
populations were not signiﬁcantly different with a slight downward shiﬂ from 11% to
9% of the communities. Sphingomonas, however, was signiﬁcantly more abundant
representing 11% of the well community nearest the bio-treatment wells and 24% of
the well community downstream of the bio-treatrnent wells.

The population proﬁles are summarized in Figure 2.27 and indicate a trend of
Pseudomonas becoming less abundant moving from upstream to nearest to
downstream of the treatment wells. Alternatively, Legionella showed a greater species
richness from the well community upstream to the community nearest the bio-treatrnent
wells, but then a reduction in number further downstream of the groundwater ﬂow.
Additionally, Sphingomonas declined from the well communities upstream of the bio-
treatment wells to the communities nearest the treatment wells, but a signiﬁcant rise in

number further downstream of the groundwater ﬂow.

47

Detection of Burkholderia cepacia complex (Bee). Several samples from Edwards
AFB that were taken three months aﬁer the injection of toluene (end of experiment)
were used in an attempt to amplify the recA gene of the Bee. About V4 of the samples
produced visible bands and those that did were not strong. Those well samples were N-
8-L, N-9-L, N—12-L, N-l6-L, N-l7-L, and N-18-L (Fig. 2.28a and 2.28b). Sequencing
those amplicons produced no results, i.e., they did not have a passing score when
analyzed by GTSF, therefore, they could not be sequenced. The result is consistent
with ﬁnding no members of the genus Burkholderia in the analysis of the 16S clones
(Fig. 2.8-2.l6). Bacteria of the order Burkholderiales and the family Burkholderace
were found, however (Table 2.2). Tire weak bands found using the recA primers that
were not sequenced could be attributed to miss priming, hence not detecting the

Burkholderia cepacia complex.

48

Clone Library results of all six (6) wells and their signiﬁcance to each other

Figures 2829: Composite analysis of samples taken before toluene injection and
samples taken one month after toluene injection.

Figure 2.10: Signiﬁcant difference of samples taken before toluene injection and
samples taken one month after toluene injection.

Figures 2.11-2.12: Composite analysis of samples taken before toluene injection and
samples taken three months after injection.

Figure 2.13: Signiﬁcant difference of samples taken before toluene injection and
samples taken three months after injection.

Figures 2.14-2.15: Composite analysis of samples taken one month after toluene
injection and samples taken three months after injection.

Figure 2.16: Signiﬁcant difference of samples taken one month after toluene injection
and samples taken three months after injection.

Figure 2.17: Proﬁles of samples taken before toluene injection (background), one
month after injection (initial), and samples taken at the end of the experiment (end)
samples.

Figures 2.18-2.19: Composite analysis from all three sampling periods of samples
upstream and nearest the BIO.

Figure 2.20: Signiﬁcant difference of the composite analysis from all three sampling
periods of samples upstream and nearest the B10.

Figures 2.21-2.22: Composite analysis from all three sampling periods of samples
upstream and downstream of B10.

Figure 2.23: Signiﬁcant difference of the composite analysis from all three sampling
periods of samples upstream and downstream of B10.

Figures 2.24-2.25: Composite analysis from all three sampling periods of samples
downstream and nearest of B10.

Figure 2.26: Signiﬁcant difference of the composite analysis from all three Sampling
periods of samples downstream and nearest of B10.

Figure 2.27: Proﬁles of the composite analysis from all three sampling periods of
samples upstream, nearest, and downstream of B10.

49

 

Samples taken before toluene Injection (background)

 

85%

 

 

I ACINETOBACTERU)
I AUSHEWANELLA(24)

a FLAVOBACTERIUM(1)

I FLEXIBACTER(15)

I PROPIONIBACTERIUMQ)
I Pseuoomomsma)

I RHIZDBIUM(1)
SPHINGOMONASU)

I comma BACTERIUM(4)

I FINEGOLD|A(1)

u JANTHINOBACTERIUMQ4)
I METHYLOBAC‘iERIUM(1)
I SHIGELLA(1)

I THIOCAPSA(1)

 

 

 

Samples taken one month after toluene injection (Initial)
5%

 

I smoamzoeium (1)
I AUSHEWANELLA(14)
n FLAVOBACTE RlUM(1 a)
I FLEXIBACTER(5)
I ARENIBACTERU)
I PSEUDOMONAS(29)
I RHIZDBIUM (2)
I SPHINGOMONASUQ)
I BREVUNDIMONAS (1)
I DYADOBACTER(9)
n GELIDIBACTER(6)
I HYDROGENOPHAGMZ)
I LEGIONELLMZ)
I DEVOSIA (1)
I MAGNETOSPIRILLUM (1)
I opmnuse)

 

 

 

 

log_sign of (background vs. intlal)

“Q

—0- PSEUDOMONAS

 

/ .
P: ,) Anything below 10‘2 is

 

f'

l

 

Genus

3 *BREVUNDIMONAS

+ FLAVOBACTERIUM
JANTHINOBACTERIU

—><—- EYADOBACTER

+ SPHINGOMONAS

+ OPITUTUS

—l—- GELIDIBACTER

—— RHODOBACTER

 

 

FLEXIBACTER

 

 

50

 

 

 

 

2_11 Samples taken before toluene Injection (background)

 

I ACINETOBACTERU)
I ALISHEWANELLM24)

1:1 FLAVOBACTERIUM(1)
FLEXIBACTER(15)

I PROPIONIBACTERIUMQ)
I PSEUDOMONAS(148)

I RHIZDBIUM(1)
SPHINGOMONASU)

I CORYNEBACTE RIUM(4)

I FINEGOLDIA(1)

u JANTHINOBACTE RIUM(24)
I ME'iHYLOBACTERIUM(1)
I SHIGELLAU)

I THIOCAPSAU)

 

 

65%

 

 

 

 

2.12 Samples taken three months after toluene injection (end)

HMCRQIC'IER M (321)

. Igsvcnmrégém
HWTE

I 'gIJODOCOCCUS 23)
I SPHNGmIC IUMZ)

 

 

 

 

 

 

 

 

signiﬁcantly different

 

 

 

51

 

 

 

2_14 Samples taken one month after toluene Injection (initial)
5%

I SINORHIZOBIUM (1)
I AUSHEWANELLA(14)
c1 FLAVOBACTERIUM(18)
u FLEXIBACTER(5)
I ARENIBAC‘iE R(1)
I PSEUDOMONAS(29)
I RHIZOBIUM (2)
a SPHINGOMONAS(19)
I BREVUNDIMONAS (1)
I DYADOBACTER(9)
1:1 GELIDIBACTER(6)
I HYDROGENOPHAGA(2)
I LEGIONELLA(2)
, I DEVOSIA (1)

24% I MAGNETOSPIRILLUM (1)

I oprnnusw)

 

 

 

 

Samples taken three months after toluene injection (end)
I ACINETOBACTE:g5 3)

2.15

 

OBAC RJ
MCROBPCTER M(3
gOVOSSE-IgilEEOgIUM 1)
PSYCH ROBIé'I‘ERU )

RHODOBACTERéZ
EIRHODOCOCCU 3)
ISHEVIMEL 1

ISP HINGOBPC RIUMZ)

13
D
D
I
I
I

 

 

 

 

 

 

2.16 Ioaémariﬁal mm) 1mm

 

 

 

 

 

52

 

 

 

Temporal Analysis 1-background 2-initial 3-end

 

 

 

 

 

0%

20%

40%

60% 80% 100%

 

W

I El'H
IMICROBACTERIU M
EgOVOSPHINGOBIUM

I PARACOCCU CS

I PROPIONIBABCRTERIUM
I PROPIONI RIO

I P EUDOMONAS

I PSYCHROBACTER

= RHIZOB

IS IGE U.A
I SINORH IZOBIUM

IPS HINGOBACTERIUM
ISPHIN GOMON AS
IT OCAI‘IIPSA

 

 

53

 

 

 

 

Samples upstream of biotreatment wells
8%

 

I ALISHEWANAELLA 28

I ACINETOBACTE11§

D 00A
DMICROBACTERIACEAE £2)
IJANTHINOBACTERIUM(

 

 

 

Samples nearest biotreatment wells“:

 

ETOBACTER ”$323)
”ZOBACTERW)
parser-gilt”:

Iggoﬁlosmmcokgﬁiiu
Wilgﬁig'ﬁ‘ <15
I -BIREWNDIWN';S (3:6)
= arrest. (.1)

D SINORHIZOBIUls 11))

as;

IIIIIIII IIIIDII

HIZOBm14

woo

GELIDIBACTERQ)

 

 

 

 

log_sign

Anything below

is

 

 

 

 

54

 

 

 

Samples upstream of biotreatment wells
8%

 

 

IA ALISHEWANELLA 23
nPSYCHROBACTE 1
IDYAooaA
IFLAVOBACTERI ( a)
:EELEXIBA c 4)

UDOMO )S(176)

I ACINETOBACTE11§

IHYD REOG P( HA)GA(3)
I LIMNOVL’BACTEOm)
IBREvu NDM 3(5)

I SHIGE LLA 1
I METHYLO CCRTE:(:l)EAUM(1)

1:1 MICRoRraDIA CEAEé)
IJANTHINOBAC'iERIUM( )

 

 

 

 

Samples downstream of biotreatment wells

 

9%

 

 

I RHODOCOCCUS(1)
I ALISHEWANELLA(26)

El CAULOBACTER(1)

1:1 DYADOBACTERU)

I FLAVOBACTERIUIVK4)

I FLEXIBACTER (25)

I LEGIONELLA (13)

n PSEUDOMONAS(33)

I SPHINGOMONAS(34)

I SPHINGOBACTERIUIVKZ)
c1 THIOCAPSA(1)

 

 

 

 

 

-1o —

signiﬁcantly different

Genus

 

-2- x ms

 

 

 

 

55

 

 

Samples nearest biotreatment wells

 

IPCIIgHETOBPCTER W991
ICINJL l111(9)

= D YADOBI‘ICTEFEI-égi2 O)
ELEGIONELLA LG)

I

I

enemagaw

NOWSPH

moﬁﬂRlLLJUMd)
I RHOD

erases Aggie)
=mﬁWNDImN (3)

ﬂ ARENI 1
ESINORI-llAgOBILU's 611))
I D

I RHIZOBI

 

I gGELIDIBﬁCTERﬁé)

 

 

Samples downstream of biotreatment wells

 

 

 

I RHODOCOCCUS(1)
I ALISHEWANELLNZS)

1:1 CAULOBACTERU)

1:1 DYADOBACTER(1)

I FLAVOBACTERIUM(4)

I FLEXIBACTER (25)

I LEGIONELLA (13)

1:1 PSEUDOIVONAS(33)

I SPHINGONDNAS(34)

I SPHINGOBACTERIUM(2)
1:1 THIOCAPSA(1)

 

 

 

 

Iog_sign

 

Genus

 

+SPHWONAS
+AUSI'EWA'ELLA
FLENBACTER
> PSELWONAS
x GELIUBACTER
+UMmBACTER
+ LEGIOIELLA

 

 

 

56

 

 

 

2.27
3-downstream

 

 

 

 

 

0% 50% 100%

SpatialAnaiysis 1-upstream 2-nearest

I
E13
(02

IETVOIBALETER
ACTER

as;
095:
am":
0
.1
ITI
1‘10

E°Eg¥
ggE; 5§:m

1AA
BACTER
LAVOBACTERIU M

I GLELIDIBACTER

IH JAN YDTgﬁOBBCTE/E‘IGM
l LE

'OBACTE
MAGN ETOSPIRILLUM
B RIAC|

FY

IIIIE—IEE-
O-l
(D
'2
II
F
r-
C
:—

Er;
g
88
C);
.1
Th
Ii
E
Z

OPIT
ARAJTCOJCCUS
PROPIIDONIVIBRIO

R

S

SHGE LELA
SINORHIZOBIUM
EBH HINGOBACTERIUM

 

 

IIIII-II-IIIIII l I: I

HINGO MONAS
OCAPSA

 

 

57

 

Burkholderia cepacia complex selection using recA primers

Lane 1: Ladder
Lane 2: N-l-L '
Lane 3: N-2—L r m " "‘“ """ " '

Lane 4: N-3-L
Lane 5: N—4-L
Lane 6: N-S-L
Lane 7: N-6-L
Lane 8: N-7-L

‘: as”: ‘u-.' can; :
Lane 1: Ladder !
Lane 2: N-8-L

Lane 3: N-9-L " T
Lane 4: N-lO-L
Lane 5: N-l 1-L
Lane 6: N-12-L
Lane 7: Pos. control

_ ‘

 

Figure 2.28a: Analysis of samples using recA gene primers. Samples positive for recA
are bold. Positive control=B. vietnamensis G4.

Lane 1: Ladder
Lane 2: N-13-L ' ‘ .

Lane 3IN-14-L - - - . ’tui ‘I: draw...“ “I “~-
Lane 4: N-lS-L
Lane 5: N-l6-L
Lane 6: N-l7-L
Lane 7: N-18-L
Lane 8: N-19-L
Lane 9: N-20-L
Lane 10: MW21L

Lane 1: Ladder
Lane 2: MW22L
Lane 3: MW23L
Lane 4: D4L
Lane 5: Pos. control
Lane 6: Empty
Lane 7: Neg. control

 

Figure 2.28b: Additional analysis of samples using recA gene primers. Samples
positive for recA are bold. Positive control=B. vietnamensis G4.

58

Table 2.2. Taxonomy of well samples showing their hierarchical structure to show the
presence or lack there of for members of the genus Burkholderia.

 

 

 

 

 

We” Phylum Class Family Order Genus
sample
name
N-8-L Comamonadaceae Burkholderiales Acidovorax
Proteo Beta
bacteria proteobacteria Comamonadaceae Burkholderiales Hydro
genophaga
Burkholderiaceae Burkholderiales Limnobacter
N-9-L Proteo Beta Comamonadaceae Burkholderiales Hydro
bacteria proteobacteria genophaga
N-17L Proteo Beta Comamonadaceae Burkholderiales Acidovorax
bacteria proteobacteria

 

 

 

 

 

 

59

 

168 rRNA Clone Library results of all six (6) well samples taken at the end of the
experiment that were selected for analysis of Bee using the recA gene primers

Figures 2.29: Composite analysis of well N-8-L
Figures 2.30: Composite analysis of well N-9-L
Figures 2.31: Composite analysis of well N-12-L
Figures 2.32: Composite analysis of well N-16-L
Figures 2.33: Composite analysis of well N-l 7-L

Figures 2.34: Composite analysis of well N-18-L

6O

 

2.29

N-8i that was selected using recA gene primers

 

   

I FLAVOBACTERIUM(B)
IFLEXIBACTER(1)
DSPHINGOMONAS(42)
I'.‘lAC|DOVORAX(1)

I HYDROGENOPHAGA(G)
I LIMNOBACTER(2)
ILEGIONELLA(1)

 

68%

 

 

N-9-L that was selected using recA gene primers

 

I FLAVOBACTERIUM(1)
I BREVUNDIMONAS(6)
U CAULOBACTER(1)

El SPHINGOMONAS(71)
I HYDROGENOPHAGA(1)
I PSEUDOMONAS(28)

 

 

 

 

 

N-12-L that was selected using recA gene primers

1%
1%

  

22%

 

IFLEXIBACTER(1)
IBREVUNDIMONAS(1)
USPHINGOMONAS(15)
6% ElALISHEWANELLA(4)
ILEGIONELLA(14)

I PSEUDOMONAS(33)

49%

 

 

 

21%

 

 

61

 

 

 

 

2.32

N-16-L that was selected using recA gene primers

1%

 

 

 

I RHODOCOCCUS(1)
I FLEXIBACTER(24)

u SPHINGOBACTERIUM(2)
:1 SPHINGOMONAS (3)

I ALISHEWANELLA(3)

I LEGIONELLA(13)

I PSEUDOMONAS(29)

 

 

 

 

2.33

N-17L that was selected by recA primers

 

 

 

 

I FLEXIBACTER“)

I BREVUNDIMONAS(Z)
u NOVOSPHINGOBIUM(1)
n RHIZOBIUM(1)

I SPHINGOBIUM(1)

I SPHINGOMONAS(45)
I ACIDOVORAXU )

a ACINETOBACTE R(1)
I ALISHEWANELLA(1)
I LEGIONELLA(10)

n PSEUDOMONAS(SO)

 

 

 

 

 

 

71%

 

 

I DYADOBACTER(1)
I FLAVOBACTERIUM(4)
u CAULOBACTER(1)

n SPHINGOMONAS(28)
I PSELDOMONAS(4)
I ALlSl-EWABELLAU)

 

 

 

 

62

 

Discussion

The detection, identiﬁcation, and characterization of microbial populationsand
their activities in environments are quite challenging because of their diversity and
difﬁculty in culturing (Qiu et al., 2001). PCR targeting the 168 rRNA gene has become
an important culture-independent means of characterizing microbial communities and
has advanced our understanding of microbial diversity and evolutionary relationships
(Speksnijder et al., 2001). Several 16S rRNA approaches have been used, including
TRFLP and the construction of clone libraries to be analyzed by high-throughput
sequencing.

One of the best methods to analyze bacterial diversity is the use of clone
libraries of 16S rRNA genes collected from bacteria using PCR with 16S rRNA gene
primers (Cottrell et al., 2000). In the past, bacterial communities have normally been
compared by analyzing isolates cultivated on plates (Dunbar et al., 1999). Methods of
analysis and direct ampliﬁcation of 16S rRNA genes are replacing the cultivation of
isolates when a more comprehensive sampling of the community is desired (Dunbar et
al., 1999). There have been several studies that reﬂect the advantages and signiﬁcance
of constructing these clone libraries (Cottrell et al., 2000, Nogales et al., 2001, and
Dunbar et al., 1999). Hence, to better determine the active microbial communities in
the Edwards AFB samples taken from the full-scale BEHIVS site, I prepared clone
libraries of 16S rRNA genes before and after substrate addition. These results indicated ‘
that there is greater overall species richness once toluene is added to the samples. The
well samples taken one month after injection (initial) and those three months after

injection (end) have less difference from each other because both of these groups had

63

new substrate whereas the background had only very low levels of indigenous
substrate. Temporal proﬁle analysis of the Edwards samples indicate populations such
as Pseudomonas declined as. toluene was added and Sphingomonas and Legionella were
much more abundant.

Spatial analysis was also done on the well samples in relation to their location to
the treatment wells. The TRFLP analysis prior to treatment showed that several well
communities regardless of location are similar in the fragments (representative of
different taxa) they contain, but have an uneven distribution of those fragments as was
evidenced by the similarity indices. Upstream samples should not have been affected
because the ﬂow of the groundwater with toluene injection was down gradient. Hence,
the well samples nearest and downstream of the treatment wells are the ones expected
to be affected by substrate addition. The clone libraries show that the upstream wells
are somewhat reﬂective of the background samples. This could suggest that the
population shift seen between the background vs. initial and end communities is due to
the samples nearest and downstream of the bio-treatment wells.

Further evaluation of the spatial proﬁles show that populations of Pseudomonas
were reduced with the groundwater/toluene ﬂow and the Sphingomonas population was
larger with the groundwater /toluene ﬂow. Populations of Legionella, however, were
greater initially with the groundwater/toluene ﬂow, but smaller at the downstream
wells. This suggests that the further the ﬂow of groundwater, the more evidence there
is of a population shift in the communities.

Legionella, the genus that causes Legionnaires disease, was enriched once

toluene was added to the bio-treatment wells at Edwards AF B. The bacterium easily

64

breeds in warm, moist conditions and thus most sources of outbreaks come from water
or air conditioning systems in large public buildings. The presence of Legionella via
the RDP classiﬁer does not necessarily constitute the detection of a pathogenic species
because the RDP hierarchy includes all bacteria with very similar 16S rRNA gene
sequences but is not further classiﬁed to the species level. More work is needed to
evaluate the occurrence of pathogenic Legionella in the Edwards samples.

Evaluation of both spatial and temporal analysis of samples from Edwards AFB
however, rendered no evidence that species of the genus Burkholderia were present.
The identiﬁcation of this group of opportunistic human pathogens, which causes
infection in patients with Cystic Fibrosis (CF), has become increasingly important in the
past few years. Cystic Fibrosis (CF) is the most common inherited lethal disorder of
Caucasian populations, with more than 500,000 individuals worldwide (30,000 in US)
affected and many others carrying the gene that causes CF (Govan et al., 1996).
Mortality in CF patients is often caused by long-term microbial colonization of the
airways that result in crippling pulmonary infections (Govan etal., 1996). In the 1980s,
concern over the emergence of these opportunistic human pathogens developed in the
CF community (Govan et al., 1996). Thus, the source of Burkholderia in strains
infecting patients with CF became a focal point of CF research.

Patients with CF are often infected with a group of diverse opportunistic human
pathogens, but Pseudomonas aeruginosa and the Burkholderia cepacia complex (Bcc)
are the most problematic (Mahenthiralingam et al., 2000). The Bee are a culmination of
nine species-like groups, i.e., genomovars I through IX. All are now described as

species (in numerical order): Burkholderia cepacia, B. multivorans, B. cenocepacia, B.

65

stabilis, B. vietnamiensis, B. dolosa, B. ambifaria, B. anthina, and B. pyrrocinia.
Strains of all nine are responsible for infection in humans with CF. The original
Burkholderia cepacia (genomovar 1) strain is a plant pathogen and nonpathogenic for
healthy humans (Li Puma et al., 1999). The outcome of Bcc infected CF patients range
from fatal pneumonia “the cepacia syndrome”, to an unmodiﬁed respiratory status
(Segonds et al., 1999). By better identifying some of the bacteria of the B. cepacia
complex and understanding their source, we may be able to improve the poor outcome
associated with these infections (Mahenthiralingam et al., 2000).

Because some of the B. cepacia complex bacteria live in soil and grow on
toluene or phenol (Mahenthiralingam et al., 2000), stimulating their growth in the
environment may be of concern at sites practicing aerobic TCE cometabolism, such as
Edwards AFB. In fact the best-known TCE co-metabolizing strain, G4, is a member of
the complex. By identifying the organisms that are selected by the treatment at the site,
I would be able to determine if any are from the Bcc. I used the Bcc recA gene primers
to determine if there were any Bcc genomovars present in the extracted DNA. A single
copy of the recA gene resides on each of the two large chromosomes of B. cepacia
(Mahenthiralingam et al., 2000). Bee A is a protein necessary for repair and
recombination of DNA (Mahenthiralingam et al., 2000). Use of Bcc speciﬁc recA
typing by RFLP, and conﬁrmation by sequencing is currently the standard in the
medical ﬁeld for rapid classiﬁcation of infectious strains. I found only weak
ampliﬁcation products that did not produce useable sequences and I did not ﬁnd any
clones of the Burkholderia genus in the 16S rRNA gene clone library. Hence, members

of the Bcc did not appear to be present or selected by toluene feeding at the Edwards

66

site as was observed by the methods used. The BEHIVS system, with the vapor
stripping well, could aerosolize Bcc cells if they were enriched in the aquifer. But since
this appeared not to be the case, there is no evidence for a public health concern for

using the BEHIVES system at Edwards AFB.

67

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23. Holliger, Christof, Gert Wohlfarth, and Gabriele Diekert. 1999. Reductive
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24. Hopkins, G.D., L. Semprini, and P.L. McCarty. 1993. Microcosm and in
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29. Lﬁffler, Frank E. Qing Sun, Jieran Li, and James M. Tiedje. 2000. 16S
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39. Munakata-Marr, Junko, V. Grace Matheson, Larry J. Forney, James M.
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73

Chapter III

Isolation, characterization, and distribution of toluene degraders from soil and
aquifer habitats.
Introduction

Trichloroethene (TCE), a common groundwater pollutant is of signiﬁcant
importance throughout the world, and speciﬁcally at Edwards AFB, where TCE was
used to clean the engines of the X-15 planes housed there in the late 50’s and 60’s.
Workers at the Air Force Base used 55 gallons of TCE each month to clean the engines
and afterwards dumped the remainder into a nearby desert creating a large groundwater
plume. A more detailed explanation of the site and its history is in Chapter 2.

The widespread occurrence of TCE in groundwater has created public demand
for techniques to remediate aquifers contaminated with TCE. While aerobic
microorganisms cannot use TCE as a carbon and energy source for growth, some can
co-metabolize TCE making this an attractive approach for cleanup of TCE
contaminated aquifers (Semprini, 1995). Pilot-scale studies for in situ bioremediation
have shown that certain substrates such as toluene or phenol injected into aquifer
material stimulated indigenous TCE- degrading organisms (J enal-Wanner etal., 1997).
Previously, Wilson and Wilson (1985) described successful cometabolism of TCE in
soil communities fed with natural gas. Certain oxgenases normally used by the
microorganisms for initiating primary substrate oxidation can transform chlorinated
ethenes (Hopkins et al., 1995). For example, three soil bacterial cultures that catabolize
toluene, Burkholderia vietnamensis strain G4, Pseudomonas putida F1, and P. putida

BS, have been demonstrated to cometabolize TCE (Wackett et al., 1988).

74

A microcosm study demonstrated that indigenous microbes in the Edwards
aquifer would co-metabolize TCE when fed toluene as the primary substrate. This
exercise resulted in 87% and 99% TCE removal. Following this, a full-scale test was
implemented which resulted in between 83-87% TCE removal (Mch et al, 1998).
The full-scale showed a similarity between predicted results and hence the opportunity
for another full-scale test using a vapor stripping system to measure the microbial
population response was initiated. My previous work based on DNA analysis indicated
that there was a shift in community structure following toluene treatment and that wells
nearby and down-gradient from the bio-treatment well had different communities than
the upstream wells (Chapter 2).

In this study I wanted to determine which culturable toluene-degrading
populations were present, whether they co-oxidized TCE, and to further explore
whether any isolates from Edwards AFB and other sites were Burkholderia cepacia

complex.

75

 

Materials and Methods

Isolation of dominant populations. The isolates were obtained ﬁ'om the resuspended
cells extracted from the ﬁlters from 4L of Edwards AFB well water. The ﬁlters
analyzed were N-l 1-L and MW-23-L taken three months after toluene injection and
both representing communities nearest the bio-treatment wells (Chapter 2). Isolations
were performed by a 10X fold dilution of 1 ml of the sample into 9 ml of phosphate-
buffered saline (PBS) at pH 7.3 (Fig. 3.1). PBS was made of 80 g NaCl; 2 g KC]; 11.5
g NazHPO4-7H20; and 2g KHzPO4. Next, 100 pl of the solution was spread on
modiﬁed-RZA agar (Fries, 1995). Modiﬁed R2A (M-RZA) is based on the original
carbon composition provided by Difco (Detroit, MI), combined with a low phosphate
plus trace salts mixture (Fries, 1995). The plates were incubated under aerobic
conditions. After initial growth on M-R2A, one colony of each morphology, color, and
size were taken from each plate and streaked onto another M-R2A plate for puriﬁcation
(this was done for a total of three times). Once the isolates were puriﬁed, they were
streaked on a low salt media, Basal Salt Media (BSM), and placed in a desiccators with
a small vial of toluene vapors to determine their relative growth on the aromatic
substrate. The amount of toluene added was calculated based on the total volume of the
desiccators to provide a ﬁnal concentration of 50 ppm. The toluene concentration was
kept low since Fries et a1 (1995) had found higher concentrations were inhibitory to
much of the toluene-degrading aquifer communities. Basal Salt Media consisted of 40
ml/L Na/KPO4 buffer; 5 ml/L MgSO4; 5 ml/L CaClz; 5m1/L FeSO4; 5 ml/L NaMoO4; 1
ml/L Metal 44 (MMO); 10 ml/L 10% (NH4)2 804; and 10 g Nobel Agar (used to

solidify medium).

76

Burkholderia vietnamiensis strain G4 , Pseudomonas putida Fl, Burkholderia
pickettii PKOl, all of which are toluene and TCE degraders were used as positive
controls.

Characterization of isolates. After the DNA analysis, the isolates were measured for
toluene degradation and TCE co-oxidation. Each colony that grew on toluene. vapors
was inoculated into 160 ml bottles with 12 ml of liquid BSM. Then 2 ml was
distributed into 20 ml bottles, spiked with 25 ppm toluene and 1 ppm TCE, and sealed
with teﬂon-lined stoppers. Those bottles were incubated at 25°C on a shaker until they
were measured for growth at days 1 and 5. Each isolate was incubated in triplicates.
Controls from the same batch of medium without cells were incubated at the same time
to determine any non-biological loss. After determining the growth by optical density,
cultures were sacriﬁced by adding 0.2 ml of 5 N HCl and stored at 4°C until analyzed
by gas chromatography. A vial was assumed to be positive for biodegradation of the
primary substrate and TCE co-oxidation when more than 50 and 95% of the TCE and
toluene, respectively, had disappeared (Fries, 1995). The amounts of toluene and TCE
remaining in the bottles were then measured by ﬂame ionization gas chromatography

(V arian model 3700) using an auto-sampler (Hewlett Packard).

77

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Identification of toluene degraders. To determine which isolates successfully
consumed toluene and co-oxidized TCE, their 16S rRNA genes were sequenced.
Puriﬁed colonies were taken from the plates of those isolates which showed the most
substrate consumed, and added to 100 pl 0.05 NaOH. The solution was incubated at
99°C for 20 min to break the cells. A PCR was then run by taking lul of that lysate and
adding it to a master mix containing ReadyMixTM RedTaqTM PCR Reaction Mix with
MgClz (Sigma, St. Louis, MO) and using the primers 8F and 1392R (Amann, et al,
1995). The PCR product was puriﬁed using the QIAquick PCR Puriﬁcation Kit
(Qiagen, Valencia, CA), and separated by electrophoresis to determine the size of the
PCR product. The concentration of cDNA was measured by UV spectrophotometry
and custom sequencing was performed by MSU’s Genomics Technology Support
Facility (GTSF). The sequences were analyzed using Sequence Match on the RDP
website to determine to which group they had the greatest similarity.

Determining substrates consumed. To determine the amount of toluene degraded
and TCE co-oxidized, the results obtained from the GC were calculated by subtracting
the area of the peak of the sample from Day 5 from the area of the peak ﬁom the control
of Day 5, dividing by the control of Day 1 and then multiplying by 100. An example of
the percent of toluene degraded in a vial containing the G4 strain is shown:

Control (Day 5)-G412ay 5) *100: 44066056-81405.§ *100 = 100%
Control (Day 1) 43584282

Of my 65 isolates, only 48 grew on plates on toluene vapors and were ﬁirther tested for

growth in liquid BSM with 25 ppm toluene and 1 ppm TCE. None of these isolates co-

79

oxidized TCE, and only a few minimally degraded toluene (Table 3.1). The most active
isolates showed only 14.4 to 17.6 % toluene removed. Irnportantly, known strains, G4,
PKOl , F1, did show essentially complete toluene degradation and TCE co-oxidation
with 100% & 98.4%; 93.8% & 100%; and 93.7% & 30.7% removal, respectively.
Soil Samples. Soil samples used in this experiment were from a variety of locations
including Schoolcratt PW—l 63-64’- a Michigan site contaminated with TCE; Wexford I
43-48’ and BearLake 10 83-88’-both sites contaminated with petroleum form oil
production wells; Merredin-a soil of Southwestern Australia; Lago Penuelas-a soil of
Central Chile; and Brittem- a soil from Saskatchewan (F ulthorpe et al., 1996). These
samples were kept at 4°C until analysis.
Isolation of dominant soil populations. Five grams of each soil was placed in bottles
with 160 ml of Basal Salt Medium (BSM) and 200 ppm of toluene. The bottles were
incubated at 25°C. After 4 days, another 200 ppm of toluene was added to each of the
sample bottles. Aliquots of each sample was then spread on BSM plates and placed in a
desiccators with toluene vapors to provide a ﬁnal concentration of 50 ppm.
Determination of Burkholderia cepacia complex (Bcc). In order to determine if the
colonies were of the Bcc, we performed colony hybridization using a Bee speciﬁc probe
provided by Dr. Alban Ramette @ Michigan State University. This probe targets the
V3 variable region of 16S gene. I followed the following protocol for colony
hybridization provided by Dr. Alban Ramette:

A. Labeling of the probe:
1) Adjust the probe concentration to 10 ng /ul
2) Denature for 5 minutes in boiling water
3) Cool on ice for 5 minutes

4) Prepare 1:4 (v:v, cross-linkerzwater) dilution of the cross-linker solution
[Alkphos labeling and detection kit (RPN3691, Amersham)]

80

5) Add to the tube containing the probe the following reaction(mix gently by
pipetting each time): [All from Alkphos labeling and detection kit
(RPN3691, Amersham]

-Probe 7ul; Reaction buffer 7ul; Labeling reagent 1.4ul; and Cross-
Linker 7ul
6) Incubate at 37°C for at least 2 hours

B. Fixation of the DNA to the membranes
Colony lift- Place a sterile precut membrane on the surface of a dry micro
liter plate. Press the membrane (Hybond N+ membranes (RPN303B,
Amersham) using the lid of the plate, to ensure a homogenous contact for all
colonies
0) Prepare 9 sheets of ﬁlter paper (Whatrnan #1). Use them as pads (2
sheets/pad). One pad is soaked with denaturing solution, two pads
with neutralizing and one with 2 x SSC. The 9th sheet is to carry the
membranes in the drying step in the oven
1) Denaturing solution: 7 min
2) Neutralizing solution: 3 min (x2) '
3) 2x SSC: 2 min
4) Cross-link (UV autocross linker, Biorad)

C. Prehybridization
1) Prehybridize the membrane at 40°C in 10 ml of Hybridization buffer
(Provided in Alkphos labeling and detection kit (RPN3691,
Amersham) for lhour in a shaking water bath.

D. Hybridization
1) Discard the prehybridization buffer
2) Add 20 pl of labeled probe to 10 ml of fresh hybridization buffer in a
separate tube. Mix well and add the hybridization buffer containing
the probe to the bag containing the membrane
3) Seal and hybridize overnight

E. Washes

1) Primary (stringent) wash. Wash with pre-warmed (40°C) Wash

Buffer I: 40 ml/membrane for 10 minutes by shaking. Repeat once with

fresh Buffer I
Wash Buffer I (500 ml): Urea 60 g; 10% SDS 5 ml; 0.5 M
Sodium Phosphate Buffer pH 7.0 50 ml; NaCl 4.35 g; l M
MgClz 0.5 ml; blocking agent (provided in Alkphos labeling and
detection kit [RPN3691, Amersham])

81

2) Secondary wash (to get rid of urea) by shaking at room temperature,
twice at 5 minutes
Wash Buffer II (250 ml): 20x stock 12.5 ml; 1 M MgClz 0.5
m1; and water to 250 ml. 20x stock (1L)-Tris base 121 g; NaCl
112 g pH 10

F. Detection

1) Place the membrane on a Saran wrap and cover with CDP-Star
reagent (Alkphos labeling and detection kit (RPN3691, Amersham)

2) Wrap in Saran wrap avoiding any leaking form the bag or any drop
on the outside of the wrap

3) Tape the wrapped membranes in a detection cassette by using the
frame of an already-exposed ﬁlm

4) In a dark room, under a safe light, place a ﬁlm on the membrane and
expose for 20 min to an hour.

5) Develop the ﬁlm, allowing 20 min to warm up machine (Xomat,
Kodak) prior to developing the ﬁlm

82

Results

Table 3.1 Results of toluene degradation and TCE co-oxidation by isolates from
Edwards AFB and three positive control strains. Data are means of triplicate samples.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Isolates %Toluene %TCE Isolates %Toluene %TCE
MW23-L Degradation Degradation N1 l-L Degradation Degradation
EAFB-A-l 0 0.46 EAFB-B-l 8.87 7.69
EAFB-A-2 0 0.43 EAFB-B-Z - -
EAFB-A-3 1.95 0.46 EAFB-B-3 - -
EAFB-A-4 7.63 0.47 EAFB-B-4 13.8 6.45
EAFB-A-S 8.15 0.40 EAFB-B-S 1.59 4.31
EAFB-A-6 2.19 0 EAFB-B-6 - -
EAFB-A-7 12.5 1.99 EAFB-B-7 7.09 0
EAFB-A-8 0 0.50 EAFB-B-8 0.22 3.83
EAFB-A-9 6.30 0.46 EAFB-B-9 - -
EAFB-A-10 4.47 0.44 EAFB-B-lo - -
EAFB-A-ll 9.47 0.49 EAFB-B-ll 8.39 25.9
EAFB-A-lz - - EAFB-B-12 - -
EAFB-A-13 - - EAFB-B-13 17.6 7.41
EAFB-A-l4 6.92 2.21 EAFB-B-14 7.27 14.2
EAFB-A-15 3.59 2.33 EAFB-B-ls 6.93 17.87
EAFB-A-16 8.24 0 EAFB-B-16 - -
EAFB-A-17 9.26 4.05 EAFB-B-17 - -
EAFB-A-18 8.72 5.07 EAFB-B-18 4.86 0
EAFB-A-19 4.94 0 EAFB-B-l9 4.37 8.05
EAFB-A-20 1.23 0 EAFB-B-20 - -
EAFB-A-21 0 11.0 EAFB-B-Zl 0 0
EAFB-A-22 6.78 4.03 EAFB-B-22 4.70 0
EAFB-A-23 0 0 EAFB-B-23 0.82 0
EAFB-A-24 13.3 8.04 EAFB-B-24 6.57 0
EAFB-A-25 - - EAFB-B-ZS 4.98 0.47
EAFB-A-26 - - EAFB-B-26 4.81 0
EAFB-A-27 10.2 0 EAFB-B-27 7.48 1.56
EAFB-A-28 13.6 0 EAFB-B-28 2.38 3.84
EAFB-A-29 14.4 0.66 EAFB-B-29 11.2 0.08
EAFB-A—30 12.7 1.75 EAFB-B-30 11.5 1.22
EAFB-A-31 17.2 1.03 EAFB-B-31 - -
EAFB-B-32 - -
EAFB-B-33 - -
EAFB-B-34 - -
G4 100 98.4
Fl 93.7 30.7
PKOl 93.8 100

 

83

 

Identiﬁcation of isolates. Because none of the isolates effectively degraded toluene or
co-oxidized TCE, I chose only a few of the isolates that were in the median range of
toluene oxidation to determine their identity. Four of the isolates (EAFB-A-24; EAFB-
A-29; EAFB-A-3 l; and EAFB-B-4) were highly similar to Brevibacillus parabrevis and
two (EAFB-A-27; EAFB-B-29) were highly similar to Bacillus anthracis (Table 3.2).
Because these two isolates had a high similarity to Bacillus anthracis, we needed to
further resolve their identity. I performed ClustalW analysis

(hgm://clustalw. genome. adm’ /l) to determine how similar those isolates were to
Bacillus cereus, Bacillus thuringenis, and both reference and outbreak strains of

Bacillus anthracis, since it is often quite difficult to distinguish one speCies from the

other (Table 3.3).

84

Table 3.2. Closest phylogenetic relative of sequenced isolates and their toluene and
TCE degrading abilities.

 

Strain Number Closet Relatives % Similarity Consumption of Aromatics%
Toluene 19E
EAFB-A-7 Bacillus sp. No.61 0.985 12.5 1.99
Bacillus sp. No.49 0.985
EAFB-A-24 Brevibacillus parabrevis 0.769 1 3 .3 8 .04

Brevibacillus sp. Riau 0.818

EAFB-A-27 Bacillus anthracis 0.982 10.2 0
Bacillus anthracis 0.982
EAFB-A-29 Brevibacillus parabrevis <.750 14.4 0.66

Brevibacillus sp. Riau <.750

EAFB-A-3 l Brevibacillus parabrevis 0.745 17.3 1.03
Brevibacillus sp. Riau 0.809
EAFB-B -4 Brevibacillus parabrevis <.750 13.8 6.45

Brevibacillus sp. R iau <.750

EAFB-B- l 3 Bacillus thuringiensis 0.895 17.6 7.41
Bacillus anthracis 0.893

EAFB-B-29 Bacillus anthracis 0.985 1 1.2 0.08
Bacillus anthracis 0.985

EAFB-B-3O unidentiﬁed bacterium 0.895 1 1.5 1.22

Bacillus thuringiensis 0.906

85

Table 3.3. ClustalW analysis of isolates against different Bacillus species.

 

 

 

 

 

 

 

 

Isolates Bacillus Bacillus Bacillus cereus Bacillus
anthracis- anthracis- thuringiensis
outbreak strain reference

strain
MW #27 99.7 99.7 99.7 99.1
N11 #29 99.6 99.6 99.6 99.5

 

Colony hybridization. The soil samples incubated in the desiccators with the toluene

vapors produced only small white colonies, not the distinctive type of colonies of the

Burkholderia cepacia complex (Bcc). After performing colony hybridization with the

Bcc speciﬁc probes, none of the colonies from any of the six soil samples were Bcc

(Fig. 3.2 a & b). The distinction between the positive control and the colonies ﬁom the

samples, as illustrated for the Bear Lake samples, is clear cut. Approximately 50

colonies were screened but none were positive, thus indicating Bcc is rare in these

environments.

86

 

      

Figures 3i2a and 3.2b. Detection o bacteria of the Burkholderia cepacia
complex(Bcc) as determined by colony hybridization. 3.2a is the positive control 3.2b
is the Bearlakesample and is representative of all soil samples tested.

87

Discussion

1 analyzed toluene degradation, TCE co-oxidation, and the diversity of semi-
dominant toluene-degrading bacteria isolated from an aquifer at Edwards AFB. I used
conventional microbiological techniques to quantify speciﬁc toluene degraders and
TCE co-oxidizers. For this evaluation, the amount of the primary substrate used was
important. I used 25 ppm of toluene because previous studies have shown that samples
enriched with 25 ppm are the lowest concentration feasible for evaluation of TCE co-

oxidizers (Fries, 1995).

By using toluene at 25 ppm, 1 was unable to recover some toluene degraders.
Fries (1995) used the criteria that a strain was positive for biodegradation of the primary
substrate and TCE co-oxidation when more than 50 and 95% of the TCE and toluene,
respectively, had disappeared (Fries, 1995). I had no isolates that met these criteria but
I did have a few isolates that achieved more than 10% toluene degradation, excluding
G4, PKOl , and F1 , which had 100%, 93%, and 93% toluene biodegradation and 98%,
30%, and 100% TCE co-oxidation. Of the few that were over 10% toluene
biodegradation, all were Gram-positives whereas Gram-negatives dominated the results
via high-throughput sequencing (Chapter 2). Surprisingly, of those Gram-positive
samples sequenced, two showed Bacillus anthracis as the closest relative. The 16S
rRNA gene sequences of B. anthracis, B. thuringiensis and B. cereus have high levels
of sequence similarity (>99%), which hampers their identiﬁcation and differentiation
(Sacchi, et al, 2002). After alignment in CLUSTALW, my isolates were found to have
approximately 99% similarity to each of the reference species. Sacchi et al, reported

that all true B. anthracis were identical only to each other (Sacchi, et al, 2002). Hence,

88

my isolates are not B. anthracis. Since these isolates have no further value, I autoclaved
all of them.

Colony hybridization was performed on a variety of soil samples from around
the world to see how often isolates from toluene enrichments from Bcc are found. B.
cepacia was examined because it is a common and widely distributed species with
tremendous intraspecies diversity (Leff et al., 1995). Many species of bacteria which
can be cultivated cannot be easily identiﬁed by conventional methods, thus colony
hybridization was used to detect diagnostic DNA sequences. I found no bacteria of the
Bcc present in any of the six soil samples examined in this work. This conﬁrms the
colony observations since only small white colonies were noted when incubated with
the toluene vapors, which was not indicative of colonies of the Bcc. Bcc colonies, as
illustrated by the growth of G4, are larger, milky, pale colored colonies. Hence,
toluene-degrading Bcc do not seem to be widespread in the environments as was
evident with this colony hybridization protocol.

The absence of readily growing, toluene-degrading strains in the Edwards AFB
full-scale BEHIV S water samples after toluene treatment in the ﬁeld is surprising. The
positive control strains indicate the method should be reliable. The most likely
explanation is that toluene degraders, which obviously grew in the ﬁeld since both
toluene and TCE were consumed, had not yet reached the sampling wells or just could
not be detected in the analysis of the data collected. Changes in community structure
seen via high-throughput sequencing (Chapter 2) may be due to products from toluene

degraders selecting new populations

89

10.

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95

Chapter IV
Determination of different patterns of aromatic substrate use between clinical and

environmental Burkholderia cepacia complex (Bee) strains.

Introduction

Burkholderia cepacia, ﬁrst described in 1950 as the cause of soft rot in onions,
has since been recognized as an opportunistic human pathogen that causes disease in
compromised patients and especially among cystic ﬁbrosis (CF) patients (Bevivino, et
al., 2001). This is especially important because of the patient-to-patient spread of the
organism due to respiratory infections and the fact that this organism is resistant to
many anti-microbial agents (Gavan et al., 1996, Bevivino, et al., 2001), which limits
many therapeutic options (LiPuma, 1999). The clinical outcome in B. cepacia-infected
CF patients is variable and ranges from a fatal pneumonia, ”the cepacia syndrome”, that
has caused epidemics as well as small disease clusters in CF patients to an unmodiﬁed I
respiratory status (Pitt et al., 1996, Segonds etal., 1997 and 1999). However, the Bcc is
generally nonpathogenic for healthy humans (LiPuma et al., 1999).

The Bee consists of nine speciﬁc genomovars, now described as species:

B. cepacia (genomovar I), B. multivorans (II), B. cenocepacia (III), B. stabilis (IV), B.
vietnamiensis (V), B. dolosa (VI), B. ambifaria (VII), B. anthina (VIII), and B.
pyrrocinia (1A9 (Coenye, et al., 2001). B. cenocepacia and B. multivarans constitute
the majority of isolates from CF patients (LiPuma et al, 2001). Bee strains are also of
great interest in agriculture and biotechnology because of their potential as bio-control
agents for root disease, Nz-ﬁxing ability, and as bioremediation agents. This is

important because of some Bcc’s ability as a rhizosphere colonizing, plant-growth

96

promoting agent of several economic craps which subsequently increases crop yield
(Coenye, et a1 2001, Bowers and Parke, 1993). The Bee is also important because
some can degrade hydrocarbons and co-oxidize TCE and thus aid with the
bioremediation of contaminated soil and water (Folsom et al., 1990, Holmes et al.,
1998, and Bevivino et al, 2001). Whether or not there are distinguishing differences
between Bee strains isolated from the environment and those isolated from clinical
patients is unclear (Gavan et al., 1996, and Bevivino et al., 2001). What is clear,
however, is that B. cenocepacia and B. multivorans constitute the majority of isolates
from CF patients (LiPuma et al, 2001), while B. cepacia, B. cenocepacia and B.
ambifaria are the most widespread in the rhizosphere of maize (F iore et al., 2001).
More speciﬁcally, it has been stated that the observation that clinical strains lack the
ability to act as phytopathogens, and environmental isolates are unlikely to be
responsible for human infections, may be because the strains have not been fully
analyzed (Bevivino, et a1 2002). Additionally, Coenye has noted that the taxonomic
complexity of B. cepacia-like organisms and the lack of widespread and generally
accepted identiﬁcation schemes have hindered sound studies that could establish the
roles played by and the pathogenic signiﬁcance of the different B. cepacia-like
organisms (Coenye et al., 2001).

Because members of the Bcc are thought to be potential agents for
bioremediation and because they have not been well analyzed for this application, I
sought to explore the relationship between clinical and environmental strains. Since
Burkholderia have many aromatic oxygenases and the soil and lung are very different in

their supply of these substrates, I evaluated whether there were any differences in

97

species and habitat source of strains using a variety of aromatic compounds. For
example, aromatic compounds involved in lignin metabolism are a major carbon
resource in soil, but not in the lung.
Lignin Biosynthesis and Associated Aromatic Compounds

Lignin and lignans are the major metabolic products of phenylpropanaid
metabolism in vascular plants (Lewis et a1, 1998). A complex aromatic polymer, lignin
comprises about 25% of the land-based biomass on Earth, and the recycling of this and
other plant-derived aromatic compounds is vital for maintaining the Earth’s carbon
cycle (Diaz, et al., 2001). These phenolic substances account for ~30-40% of all the
organic carbon. Phenol is an industrial product although it is also produced naturally.
It is a colorless aromatic alcohol to which individuals may be exposed to through
breathing contaminated air or through skin contact in the workplace. It is considered to
be very toxic to humans through oral exposure. The primary use of phenol is in the
production of phenolic resins, used in plywood construction and automotive industries
(Agency for Toxic Substances and Disease Registry (ATSDR), 1989).

The biosynthesis of lignin, which originates from carbohydrates that are formed
from atmospheric carbon dioxide by photosynthesis, is usually described as:
C02 —>Carbohydrates aPhenylpropanoid amino acids—>Cinnamic acid
derivatives—>Cinnamyl alcohol derivatives-alignins (F reudenberg et al., 1968). The
ﬁrst major step in lignin biosynthesis is the formation of phenylpropanaid amino acids
(C6-C3) such as phenylalanine, an essential amino acid. Upon conversion of
phenylalanine to lignin is the removal of ammonia by action of L-phenylalanine

ammonia-lyase to a number of cinnamic acid derivatives which upon reduction give

98

corresponding cinnamyl alcohol derivatives from which lignin is formed (Weiss et al.,
1980). The ring- substituted cinnamic acids are distributed as p-eoumerie and ferulie
acids, which are precursors of lignin since they have the required phenylpropane carbon
structure [C6-C3 units](Schubert, 1965). Additionally, syringen is produced via the
coniferyl-alcohol pathway that ultimately gives syringie acid, which along with ferulie
acid is an intermediate product of the fungal degradation of lignin (Schubert, 1965).
Microorganisms are almost entirely responsible for the degradation of such
chemicals. In recent years there has been considerable interest in exploring the
diversity and extent of microorganisms’ ability to degrade or detoxify the increasing
amounts of aromatic compounds that enter the environment as by-products of many
industrial processes (Diaz, et al., 2001, Harayama, S, and K. N. Tirnmis, 1992, and
Pieper, D. H., and W. Reineke. 2000). In higher plants, salicylic acid, a colorless
crystalline organic carboxylic acid from willow bark, is formed by the hydroxylation of
benzoie acid, the simplest aromatic carboxylic acid that may be obtained from resins,
notably gum benzoin. 3-Chlorobenzoie acid, which is also used in this experiment, is
a product of bacterial transformations of polychlorinated biphenyls that is used as a
model for study of the evolution of chloroaromatic degradative pathways (F ulthorpe et
a1, 1996). Catechol, a dihydric phenol that accounts for a small percent of lignin in
wood, is the central intermediate in microbial catabolism of aromatic compounds
(Crawford, 1981). We chose this range of aromatic compounds to examine the range of
aromatic degrading abilities of different environmental and clinical strains of the Bcc.
Additionally because phenol and its derivatives are some of the major hazardous

compounds in industrial wastewater their biodegradation has attracted great attention.

99

In this study, selected isolates that grow an phenol were screened for phenol
hydroxylase genes using PCR primers that target conserved regions of the alpha subunit
of the multicomponent phenol hydroxylase gene family (F utamata et. al., 2001, Ayala-
del-Rio, 2002). Rapid methods for speciﬁcally detecting and quantifying toluene-
degrading bacteria in the environment would aid the evaluation of site suitability for the
implementation of toluene and phenol-stimulated TCE bioremediation.

Hence the objective of this study was to determine if there are different patterns of

aromatic substrate use between clinical and environmental Bcc strains.

100

Figure 4.1. Simple and modiﬁed version (from Lewis et al 1998) of lignin biosynthesis
involving aromatics used in this experiment.

101

 

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102

Materials and Methods
Strains used. Clinical Bce strains isolated from patients and from the environment (no
speciﬁc description of the origin for several strains) were provided by Dr. John LiPuma,
Department of Pediatrics, University of Michigan, Ann Arbor, Michigan. Also strains
isolated from rhizospheres of earn from a tall grass Iowa prairie were obtained from
Dr. Alban Ramette, Michigan State University, East Lasing, Michigan. The strains were

already identiﬁed as to which genomovar they belonged (Table 4.1).

Chemicals used Benzoic acid, catechol, 3-chlorobenzoic acid, p-coumeric acid, ferulie
acid, phenylalanine, and syringic acid were all purchased from Sigma-Aldrich
(St.Louis, MO). Salicylic acid was obtained from Matheson Coleman and Bell
(Cincinnati, OH); phenol from Fisher Scientiﬁc Company (Fair Lawn, NJ); and toluene

from Mallinckrodt Chemical Company (Paris, KY).

103

Table 4.1. Strains of the Bcc, the genomovar to which they belong, from where the
strains were isolated, and the people who supplied them. Strains Corn 4, 5, 6, & 7 did
not have a high similarity to the known genomovars when analyzed with restriction
enzyme HaelII as determined by Dr. Alban Ramette, Michigan State University.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Environmental Genomovar Origin Source
Strains
1080-1 VII Iowa Prairie Dr. Alban Ramette
[080-2 I Iowa Prairie Dr. Alban Ramette
[080-3 VII Iowa Prairie Dr. Alban Ramette
[080-4 I Iowa Prairie Dr. Alban Ramette
[080-10 VII Iowa Prairie Dr. Alban Ramette
1080-13 I Iowa Prairie Dr. Alban Ramette
[080-21 I Iowa Prairie Dr. Alban Ramette
Corn 1 I Corn Rhizosphere Dr. Alban Ramette
Corn 2 I Corn Rhizosphere Dr. Alban Ramette
Corn 3 I Corn Rhizosphere Dr. Alban Ramette
Corn 4 B Corn Rhizosphere Dr. Alban Ramette
Corn 5 C Corn Rhizoghere Dr. Alban Ramette
Corn 6 D Corn Rhizosphere Dr. Alban Ramette
Corn 7 D Corn Rhizosphere Dr. Alban Ramette
H12557 I - Dr.John LiPuma
PC783 I onion Dr.John LiPuma
H12140 I - Dr.John LiPuma
11 Soil enriched Dr.John LiPuma
H12229 w/anthranilate
E81500 III - Dr.John LiPuma
H12485 III - Dr.John LiPuma
H12468 VII - Dr.John LiPuma
H12474 VII Corn roots Dr.John LiPuma
E80034 VII - Dr.John LiPuma
E80609 VII - Dr.John LiPuma
E80193 VII - Dr.John LiPuma
' H12725 VIII Panama Palm Plant Dr.John LiPuma
BCll IX Water Dr.John LiPuma
H12710 IX - Dr.John LiPuma
E80196 IX - Dr.John LiPuma
E80219 IX - Dr.John LiPuma
E80164 IX - Dr.John LiPuma

 

104

 

Preparation for aromatic growth analysis. Aﬁer growth on Plate Count Agar (PCA),
each strain was inoculated with 2 ml Basal Salt Medium (BSM) into triplicate 20 ml
bottles. Basal Salt Media consisted of 40 m1/L Na/KP04 buffer W0); 5 ml/L
Mg804; 5 ml/L CaClz; 5 ml/L FeSO4; 5 ml/L NaMoO4; 1 ml/L Metal 44 (MMO); 10
ml/L 10% (NI-1.02 804. These three bottles of each inoculated strain were then spiked
separately with 10 ppm of benzoic acid, catechol, 3-chlorobenzoic acid, p-coumeric
acid, ferulie acid, phenol, phenylalanine, salicylic acid, syringic acid, and toluene. All
bottles inoculated were sealed with Teﬂon stoppers capped with an aluminum top,
placed on a shaker and incubated for 1 week at 25°C before analysis by visible turbidity
except for toluene where optical density (V arian CaryWinUV) was measured.

Analysis of environmental vs. clinical strains. Data on substrates for each set of

. strains was analyzed via molecular statistical programs Systat 8.0 and Molecular
Evolutionary Genetics Analysis Version, 2.1(MEGA) to construct dendrograms of the
strains to and determine similarities or differences between them.

Determination of phenol h ydroxylase genes. All Bcc strains that grew on PCA were
ﬁrst lysed and then PCR ampliﬁed with primers for the multi-component phenol
hydroxylases, PheUf and PheUr (F utamata et a1. 2001). PCR products were detected by
electrophoresis gel and products that were ampliﬁed were puriﬁed and sequenced by the
Genomics Technology Support Facility (GTSF) at Michigan State University.
Sequences were aligned using BLAST 2.0 (Basic Local Alignment Search Tool)

against known phenol hydroxylases in the GenBank database.

105

Results

Table 4.2. Growth of environmental Bcc strains and Burkholderia vietnamiensis G4
(positive control) on toluene and the total percentage of toluene degraded. Data are the
means of triplicate samples.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Environmental Growth on Day 1 Growth on Day 5 % Toluene
Strains (ODsoo) (OD600) Degraded
1080-1 0.04 0.04 59.7
1080-2 0.06 0.06 35.9
1080-3 0.07 0.08 54.0
1080-4 0.05 0.05 54.5

1080-10 0.04 0.05 74.5
1080-13 0.06 0.06 57.1
1080-21 0.06 0.07 15.5
Corn 1 0.02 0.03 13.8
Corn 2 0.04 0.08 69.1
Corn 3 0.05 0.05 23.4
Corn 4 0.06 0.06 21.7
Corn 5 0.10 0.19 40.8
Corn 6 0.03 0.03 82.2
Corn 7 0.07 0.12 57.4
1H12557 0.01 0.01 0
IPC783 0.01 0.01 0
11112140 0 0.01 0
111112229 0 0.01 0
IIIESISOO 0.01 0.01 16.7
IIIH12485 ' 0.01 0.01 34.2
VIIH12468 0 0.01 0
VIIH12474 0.04 0.04 63.6
V11E80034 0.07 0.08 28.9
V11E80609 0 0.01 15.0
VlIESOl93 0.03 0.03 32.6
VIIIH12725 0.03 0.04 0
IXBCll 0.02 0.05 0
IXH12710 0.02 0.02 0
1XE80196 0.01 0.01 22.9
IXE80219 0.01 0.01 28.1
IXES0164 0.02 0.02 12.9

 

 

 

 

 

106

Table 4.3. Growth of clinical Bcc strains on toluene and the total percentage of toluene
degraded. Data are the means of triplicate samples.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Clinical Bcc Growth on Day 1 Growth on Day 5 % Toluene
strains (ODsoo) (ODm) Degr_aded
1H12284C 0.02 0.02 0
111112 132C 0.02 0.03 0
IIH12240C 0.02 0.03 50.0
111H12711C 0.02 0.14 100.0
IIIHI3240C 0.02 0.03 62.8
IIIH13248C 0.01 0.02 44.8
IVH12210C 0.02 0.04 0
IVAU0244C 0.01 0.04 0
VPC259C 0.02 0.03 8.07
VAU1344C 0.03 0.03 30.0
VH12238C 0.02 0.04 58.7
VIAU0645C 0.02 0.05 19.4
VIAU0158C 0.03 0.04 33.1
VIH12238C 0.02 0.04 29.8
VIIAU0212C 0.02 0.03 39.9
VIIIAU1293C 0.01 0.02 44.2

 

 

 

 

 

Growth of clinical compared to environmental strains on aromatic compounds.

More environmental strains than clinical grew on all substrates except p-coumeric acid
(environmental 39%, clinical 44%), syringic acid (environmental 23%, clinical 31%),
and toluene (environmental 74%, clinical 75%) (Tables 4.2, 4.3, 4.4 and Fig. 4.2). I
compared the prairie and corn isolates to see whether host plants affected their aromatic
substrate range. The corn isolates grew better than the prairie ones on all aromatics
except toluene, where all strains grew, catechol, where about one-half of each set grew,
and syringic acid, where none of the strains grew. When all substrates are grouped
together, the differences in grth between the environmental and clinical are clearly
seen (Figure 4.3). To better observe these differences, dendrograms were constructed to

cluster strains that had similar aromatic degrading ability.

107

Table 4.4. Growth of environmental Bcc strains on different aromatic compounds
measured in triplicate. (+) represents at least two out of the three replicates exhibiting
turbidity. (-) represents one or none of the isolates being turbid.

108

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

  

 

 

 

 

 

 

 

 

 

 

 

 

- - - mg + + + + - + 3835

- - - fwm + + + + + + Snowman

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- - - - - - + - + + 35:59

. - - - u - + + + + _ Ryan

- - - - + - + - - + magi—F»

- + - mNn + + + + + + magma

+ + - Qm v + - - - - + 883:?»

+ + - mdm + + + + - + vmocmm—E

+ - - 9m... + - - - - + 35%;

+ + + - + + - - - + nova;

+ + - «.3 - + + - + + 335—:

+ + - N. .3 - - - - - - cam—mm:—

- + - - - - - - - - «nun—E—

- - - n + - + u + + av — ”a

+ + + - + - + - + + many:

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- - . va + + + + + + 5.7200

- - + «Na - + + + - + c-7350

- - + mdv - + - + - + wig—DU

- - + N. rm + + - + - + YZMOU

- - + vdw - + + - + + WZMOU

- - - F .3 + + - - - + «-7200

- + u w . m _. + + + + - + TZMOU

- + + m.m_. - - - + - - 3-80—

- - + F Km - - - + - - 2.30—

- - - Q: - + - + - + 3.30—

- - - m .3 + - - + - - v-30—

- - - o .3 + + - - - - mémo—

- - + aha + - - - - - «.30—

- - + 5mm + + + - + - 730—
Eom Eon. Eon 05:52» coca 35cm Eon Eon Eon 52%.

955.3% o..o~§8o£?m 20:35 Simian 236k otoﬁzooh £35m

 

 

109

Table 4.5. Grth of clinical Bcc strains (isolated from patients), on different aromatic
compounds measured in triplicates (+) represents at least two out of the three replicates
exhibiting turbidity. (-) represents one or none of the isolates being turbid.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

3-
.p- Cbloro
Benzoic coumeric Ferulic henylap Salicylic Toluene: benzoie Syringic
Strain Acid Acid Acid Phenol lanine Acid Catechol acid acid
|1H12284C + + - + - - - - + +
132 + -
+ - - + - - - -
11112240 + -
+ + - - 50.0 - + +
111112711 - 100
+ - - - - - - -
1111132401 - 62.8
- - - - - - + +
13248I 44.8
- .. + - + - .. - -
12210
.. .. .. , + - - .. - - -
lIVAU024
4C + - - - - - - - - -
VPC259C - + + - - - 8.10 - - -
VAU1344 + + 30.0
C + - - - - - -
mum + + 58.7
C + - - - - + -
V1AU064 + + 19.4
FSC + - - - - - -
VIAU015 33.1
C + - - - - - - - -
V11112238 - 29.8
c + - - - - - - +
VIIAU02 - 39.9
12c + - - + + - - +
V111AU12
I93C + - - + - - 44.2 - - -

 

 

 

 

 

 

 

 

 

 

 

110

 

 

Svrhob acid
3-Ollorobenzolc acid

Toluene
Salcylc Acid

3
i

I environmental
I clinical

ForuIic Acid
p-Oom'eric Acid
Benzoic Acid

 

0 20 40 60 80 100 120 140 160
Probability of strain growth (%)

 

 

Figure 4.2. Probability of environmental/clinical strain growth on a variety of
aromatics.

 

 

 

I Benzoic Acid
I p-Coumeric Acid
El Ferulic Acid
I:I Phenol
I Phenylalanine
_ I. ' I Salicylic Acid
envuronmenlal - Toluene
, ,. I Catech
0 15 30 45 60 75 90 105120135150165 I3-Chlorobenzolcacid

Number of strains that grew on aromatice - Syringic acid

clinical

Type of strains

    

 

 

 

 

 

Figure 4.3. Growth of clinical vs. environmental strains of the Bee on a variety of
aromatics.

111

~ The strains are divided into eight clusters of aromatic substrates used (Fig. 4.4).
The ﬁrst cluster, A, is strictly environmental strains, including those from both the
prairie and corn. The strains in this cluster grew on practically all aromatic compounds
with only a few differences among them (Tables 4.4 and 4.5). Cluster B was similar to
A except these strains did not grow on p-coumeric acid. Within this cluster is the
prairie strain 1080-10 and the clinical strain 1111113248. These strains are included in
this cluster probably because they are the only prairie and clinical strains that grew on
both ferulie acid and phenylalanine. Cluster C (75% similarity to the previous clusters)
includes prairie strains 1080-1 and Corn 3 and are two of the few strains that grew on p-
coumeric acid and catechol, but not ferulic acid, which further shows why other prairie
and corn strains were not clustered with them. The strains in cluster D only grew on
three aromatics: phenylalanine, salicylic acid, and toluene, and thus had only a 72%
similarity to other environmental strains.

Cluster B contained only clinical strains and had a 70% similarity to the other
clusters because all these strains grew only on p—coumeric acid, ferulie acid and toluene
and hardly anything else. A strictly prairie cluster (F) had only a 68% similarity to
cluster E because these were the only prairie strains that did not grow on benzoic acid,
phenylalanine or syringic acid, and also the only prairie strains that belonged to
genomovar 1. The large cluster, G, contains both clinicaland environmental strains; the
majority of these strains grew on benzoic acid and syringic acid and not ferulic acid
whereas the strains in the previous cluster did not consume benzoic acid nor syringic

acid.

112

Figure 4.4. Dendrogram showing both clinical and environmental strains with similar
aromatic substrate use. X-axis represents the variable differences between each cluster.
Symbols used represent the following:

0 Corn

I Prairie
Patients w/Cystic Fibrosis

Patients w/Chronic Granulomatous
Disease

Soil

Panama Palm Plant
Onion

Water

Ubiquitous environmental strains

ODOI{ [>>

The eight major clusters of strains with similar substrate use are identiﬁed.
Genomovars, when known, are indicated by the Roman nmneral before the strain
number.

113

 

 

 

 

 

 

 

 

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114

Cluster H had two sub-clusters, 1 and 2. Sub-cluster 1 had a 65% similarity to
sub-cluster 2 and was limited in their degrading ability to consuming only benzoic acid
and toluene, whereas sub-cluster 2, which had both environmental and clinical strains,
consumed four aromatics: benzoic acid, p-coumeric acid, phenol, and salicylic acid.
Thus, cluster H had only a 63% similarity to previous clusters. The ﬁnal two strains did
not cluster with any other because they each grew on only one aromatic each. The
clinical strain (IVH12210C) grew on phenol, and the environmental strain (11112229) on
3-chlorobenzoic acid. The results indicate that as a collective group, there are
differences between environmental and clinical strains. However, the percentages that
grew on toluene were similar as well as the percentage of strains that consumed 50% or
more of the toluene (Tables 4.2 and 4.3), indicating that there is no signiﬁcant
difference on the growth of toluene between the clinical and environmental strains.

We examined the corn and prairie strains because we knew the exact origin of
all of these environmental strains (Fig. 4.5). Cluster A consisted of four sub-clusters (1 ,
2, 3, 4) that had both corn and prairie strains. Sub-cluster 1 and 2 which had only 78%
similarity are different from one another because although they grew on some of the
same aromatics, benzoic acid and phenylalanine, for example, and they did not all share
the property of utilizing salicylic acid and catechol (Fig. 4.4). These clusters also
included strains that could not be placed into one of the nine known genomovars, based
on recA RFLP-typing, i.e., C Corn 5, D Corn 6, B Corn 4, and 1) Corn 7. Sub-cluster
3, which consisted of 1080-1 and Corn 3, was not included in the previous cluster and
had only a 75% similarity to the two previous sub-clusters because they did not

consume ferulic acid. Sub-cluster (4) was also included in the larger cluster A, because

115

of these strains’ growth on phenylalanine, toluene and salicylic acid. The prairie strains
that were incorporated in cluster A did not group With cluster B because the strains in A
had speciﬁc differences in that they grew on benzoic acid and phenylalanine and the
strains in cluster B did not. Those strains included in cluster A also were members of
genomovar VII, whereas the prairie strains in B were in genomovar I. These results
reiterate the fact that even though strains are from the same location they are not

siblings since they exhibit different growth phenotypes.

116

 

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0.30 0.25 0.20 0.15 0.10 0.05 0.00

Figure 4.5. Dendrogram showing similar aromatic substrate use by strains from
corn 0) and prairie ( - rhizospheres. X—axis represents the variable
differences between each cluster.

117

Phenol h ydroxylase analysis Of the 16 strains that grew on phenol only two produced
ampliﬁed products using the phenol hydroxylase primers. Those strains were 111
HI2485 and 1 Corn 3 (Fig. 4.6). Only one of the two ampliﬁcation products could be
sequenced. When the amplicons from the corn strain was sequenced, its nucleotide
amino acid sequence was 95% similar to a Burkholderia cepacia strain E1 ’s gene for

the alpha subunit of phenol hydroxylase.

n—I
o... p— i—i
-- <
ggééigagéééé z
D—t
ENEEcZ’ENEEEEHEOQQQQ a
screw ea°°°°°agaa 9"
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600 bp

 

Figure 4.6. Electrophoresis gel of PCR products of Bcc strains that were ampliﬁed
using phenol hydroxylase primers, PheUf and PheUr. Only IIIH12485, Corn 3, and G4
(positive control) had bands at the expected 600bp site.

118

Discussion

Lignin is the second most abundant organic compound on Earth. It originates
from the carbohydrates that are formed from atmospheric carbon dioxide by the process
of photosynthesis. Li gnins constitute a very widespread group of phenylpropanoid
natural products found in plant parts including stems, rhizomes, roots, seeds, and oils
(Lewis and Sarkanen, 1998). Ligniﬁcation in the plant cell wall is initiated by the
enzymatic formation of phenoxy radicals from cinnamyl alcohol precursors (Lewis and
Sarkanen, 1998). Thus lignin biosynthesis is the charting of the macromolecule in the
cell wall.

These phenolic substances account for ~30-40% of all organic carbon in vascular
plants, of which the lignins are the predominant members. A few bacteria and some
fungi are able to decompose lignin and to assimilate lignin degradation products as a
carbon source eventually oxidizing it to C02 (Crawford, 1981). Lignins are relatively
resistant to complete mineralization, with the greatest conversion to C02 occurring
during the earlier stages of decomposition (Crawford, 1981). In this analysis, we
studied the degradation of several aromatics including ones that are precursors for lignin
biosynthesis to determine whether Burkholderia cepacia complex (Bcc) strains from
clinical versus environmental sources had any differences in aromatic degrading
abilities.

Overall, I found that the environmental strains did grow on more aromatic
substrates than the clinical isolates. Within the environmental strains, the corn isolates
grew on more substrates than the prairie isolates. The results from clustering indicated

the relative growth or non-growth on the variety of aromatics has a profound effect on

119

how the strains are clustered together. There appeared to be ecological effects because
even though some of the strains were taken from the same locations they are grouped
with other strains from totally different areas. Importantly, most environmental and
clinical strains clustered with strains from like habitats. Finally, there were differences
between the environmental strains ﬁom the corn and prairie rhizospheres. The clear
difference was in the prairie strains because all strains that were in a speciﬁc genomovar
were clustered together signifying the disparity within one particular set of strains based
on genomovar distinctions.

Contamination of the subsurface environment with chlorinated hydrocarbons,
TCE for example, is a potentially serious threat to water sources. Laboratory studies
have demonstrated that toluene and phenol-degrading bacteria co-metabolically
transform these compounds to readily degradable oxygenated compounds.
Implementation of phenol-stimulated TCE bioremediation would be aided by rapid
methods for speciﬁcally detecting and quantifying groups of phenol-degrading bacteria
in the environment. For this purpose, several strains of the Burkholderia icepacia
complex were analyzed for the presence of genes for the largest subunit of multi-
component phenol hydroxylases (LmPHs) that could predict the TCE degradation
potential of bacterial populations (F utamata, 2001). I found that only 12% of the strains
that grew on phenol produced an ampliﬁcation product using the published phenol
hydoxylase primers. As described by Futarnata (2001), the primers used should amplify
products at the 600 bp region when analyzed by electrophoresis gel. However, of the
two research strains that produced bands, only Corn 3 produced a sequence similar to

known phenol hydroxylase genes. The most likely explanation for this discrepancy is

120

that there is greater sequence diversity in phenol hydroxylase genes than recognized by
the current primers.

In essence, the degradative properties of the strains from two sources were
found to be quite different. Growth on the different aromatics such as those involved in
lignin biosynthesis greatly affects how the strains clustered. While the strains can be
separated, more work is needed to know whether one could safely distinguish a

potential pathogen from a harmless strain by growth on aromatic substrates.

121

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