THE APPLICATION OF MOLECULAR METHODS INCLUDING STABLE ISOTOPE
PROBING TO IDENTIFY THE MICROORGANISMS INVOLVED IN TOLUENE AND
MTBE DEGRADATION IN MIXED MICROBIAL SYSTEMS
By
Weimin Sun

A DISSERTATION
Submitted to
Michigan State University
In partial fulfillment of the requirements
for the degree of
DOCTORAL OF PHILOSOPHY
Environmental Engineering
2012

ABSTRACT
THE APPLICATION OF MOLECULAR METHODS INCLUDING STABLE ISOTOPE
PROBING TO IDENTIFY THE MICROORGANISMS INVOLVED IN TOLUENE AND
MTBE DEGRADATION IN MIXED MICROBIAL SYSTEMS
BY
Weimin Sun
Sites containing leaking underground storage tanks (LUST sites) are a national problem, with
over 443 568 releases confirmed as of 2003, resulting in BTEX (benzene, toluene, ethylbenzene,
xylenes) or oxygenate (e.g. MTBE or TBA) contamination. These chemicals are a threat to
drinking water supplies because of their human health effects and relatively high aqueous
solubilities. Bioremediation can be a cost-effective method to remove such groundwater
contaminants either through natural attenuation or by advanced engineering methods.
Understanding the microbial processes involved in the biodegradation of BTEX and MTBE has
the potential to improve the efficiency of LUST site remediation. The overall aims of this project
were to: 1) characterize the microorganisms able to degrade toluene under a range of redox
conditions from a variety of soil and sediment sources using stable isotope probing (SIP); 2)
investigate the diversity of the bssA and bamA genes in a wide range of anaerobic
toluene-degrading consortia; and 3) identify the microorganisms able to transform MTBE
anaerobically using SIP.
The first study in this research involved using SIP to identify the active members in an aerobic
toluene degrading consortium. Specifically, SIP was used with terminal restriction fragment
length polymorphism (TRFLP) and the results indicated that a 313 bp terminal restriction
fragment (T-RF) incorporated the majority of the

13

C from

13

C labeled toluene. Sequencing of

16S rRNA genes from these communities indicated the organism represented by this T-RF was a

Polaromonas spp. Real-time PCR was also utilized to provide quantitative patterns in gradient
fractions and document increases in Polaromonas populations as toluene was degraded. In the
second study, SIP was applied to five toluene-degrading consortia under sulfate and nitrate
amended conditions. In all, five different phylotypes were found to be responsible for toluene
degradation and these included previously identified toluene degraders as well as novel toluene
degrading microorganisms. In nitrate amended microcosms, inoculated from granular sludge,
microorganisms classifying within the genus Thauera were the primary toluene degraders.
Whereas in nitrate amended microcosms, inoculated from a different source (agricultural soil),
microorganisms in the family Comamonadaceae (genus unclassified) were the key degraders. In
one set of sulfate amended microcosms (agricultural soil), the primary degrader affiliated within
the class Clostridia (genus Desulfosporosinus), while in other sulfate amended microcosms, the
primary degraders affiliated with the class Deltaproteobacteria, classifying within the families
Syntrophobacteraceae (digester sludge) or Desulfobulbaceae (contaminated soil) (genus
unclassified for both). The third study involved an investigation into the diversity of anaerobic
toluene-degrading functional genes (bssA and bamA genes) in a number of inocula sources. The
results suggest that targeting the bamA and bssA genes in a quantitative or non-quantitative
manner could be a productive approach for investigating toluene biodegradation potential over a
range of samples and redox conditions. The final study involved using SIP to investigate the
dominant degraders in an anaerobic MTBE degrading microcosms. These experiments indicated
bacteria in the phyla Firmicutes (family Ruminococcaceae) and Alphaproteobacteria (genus
Sphingopyxis) were the dominant MTBE degraders in a methanogenic MTBE-degrading
consortium seeded from activated sludge.

ACKNOWLEDGEMENTS
There are many people who have made my research possible, by giving me guidance and
lending me their time and moral support. I would like to thank and acknowledge these people
who have made my research experience an opportunity for personal growth, while allowing me
to contribute to the field. First and foremost, I would like to extend my appreciation to my
advisor, Dr. Alison Cupples for her encouragement, patience, research ideas, manuscript
revisions, personal guidance and giving me the opportunity to explore different areas of interest
in these five years of my PhD study. I would also like to thank my other committee members, Dr.
Thomas Voice, Dr. Syed Hashsham and Dr. Terence Marsh, for taking the time to review my
work and suggest areas of improvement. Also, I would like to express my appreciation to Dr.
Marsh for the use of his laboratory and software. I am very thankful for the help from the
members in Dr. Cupples' lab, Shuguang Xie, Chunlin Luo, Indumathy Jayamani, Fernanda Paes
and Xiaoxu Sun. This work would not have been possible without such support. I would also like
to express my appreciation to Alla Alpatova and Kelvin Wong for their help in my dissertation
completion. I owe debt and gratitude to all of the group members of Dr. Hashsham and Dr.
Xagoraraki, for the use of their equipment and for sharing great research ideas. I would like to
give special thanks to Xiaoxu Sun, who has helped me tremendously and was willing to stay
with me doing bench work late at night. I want to thank my good friends Jie Niu, Pin Gao, Biao
Chang, Tan Zhao, Liyan Song, Fulin Wang and Xufeng Xu for their kind help and valuable
research ideas. Finally, I would like to thank my parents and my girlfriend for their support and
encouragement during the past years.

iv

TABLE OF CONTENTS

LIST OF TABLES........................................................................................................................ vii
LIST OF FIGURES ....................................................................................................................... ix
ABBREVIATIONS ..................................................................................................................... xiii
CHAPTER 1 ................................................................................................................................... 1
INTRODUCTION .......................................................................................................................... 1
MTBE and BTEX contamination ............................................................................................ 1
Stable isotope probing (SIP) .................................................................................................... 1
The functional gene responsible for anaerobic toluene biodegradation .................................. 2
Objectives ................................................................................................................................ 3
References:............................................................................................................................... 7
CHAPTER 2 ................................................................................................................................. 11
TOLUENE DEGRADATION IN CONTAMINATED SITE MICROCOSMS IS DIRECTLY
LINKED TO A POLAROMONAS STRAIN............................................................................... 11
Introduction............................................................................................................................ 11
MATERIALS AND METHODS........................................................................................... 13
Experimental design, microcosm setup and chemical analyses...................................... 13
DNA extraction ............................................................................................................... 14
DNA ultracentrifugation ................................................................................................. 15
PCR and TRFLP ............................................................................................................. 15
16S rRNA gene sequencing ............................................................................................ 16
Real-time PCR ................................................................................................................ 17
RESULTS AND DISCUSSION ............................................................................................ 18
References.............................................................................................................................. 31
CHAPTER 3 ................................................................................................................................. 33
DIVERSITY OF TOLUENE DEGRADING MICROORGANIMS AND THE BSSA GENE IN
FIVE NITRATE OR SULFATE AMENDED MICROBIAL COMMUNITIES INVESTIGATED
USING STABLE ISOTOPE PROBING (SIP)............................................................................. 33
Introduction............................................................................................................................ 33
Materials and Methods........................................................................................................... 35
Development of Toluene Degrading Microcosms .......................................................... 35
Analytical Techniques..................................................................................................... 37
DNA Extraction and Ultracentrifugation ........................................................................ 37
PCR and TRFLP ............................................................................................................. 38
Presence of bssA in Microcosms and Enumeration in SIP Fractions ............................. 38
Sequencing of Partial bssA and 16S rRNA Genes.......................................................... 39
Results.................................................................................................................................... 40
Frequency of Toluene Degradation................................................................................. 40

v

SIP on Agricultural Soil Nitrate Amended Microcosms (AgN) ..................................... 41
SIP on the Granular Sludge Nitrate Amended Microcosms (GNS)................................ 42
SIP on the Agricultural Soil Sulfate Amended Microcosms (AgS) ................................ 43
SIP on the Digester Sludge Sulfate Amended Microcosms (DSS)................................. 43
SIP on Gas Compressor Site Soil Sulfate Amended Microcosms (CSS) ....................... 44
Partial Sequencing of the bssA Gene .............................................................................. 45
Quantification of bssA Genes in SIP Fractions............................................................... 46
Discussion .............................................................................................................................. 46
Acknowledgements................................................................................................................ 52
References.............................................................................................................................. 79
CHAPTER 4 ................................................................................................................................. 85
PRESENCE,DIVERSITY AND THE ENUMERATION OF TOLUENE DEGRADING
FUNCTIONAL GENES (BSSA AND BAMA) ACROSS A RANGE OF REDOX CONDITIONS
AND INOCULUM SOURCES .................................................................................................... 85
Introduction............................................................................................................................ 85
Materials and Methods........................................................................................................... 87
Screening of Toluene Degrading Microcosms................................................................ 87
DNA Extraction and PCR ............................................................................................... 88
Quantitative PCR ............................................................................................................ 89
Sequencing of Partial bssA and bamA Genes ................................................................. 90
Results.................................................................................................................................... 90
bssA and bamA Gene Amplification ............................................................................... 91
bssA and bamA Gene Quantification .............................................................................. 92
Discussion .............................................................................................................................. 94
References............................................................................................................................ 109
CHPATER 5 ................................................................................................................................111
ANAEROBIC MTBE DEGRADING MICROORGANISMS IDENTIFIED IN WASTEWATER
TREATMENT PLANT SAMPLES USING STABLE ISOTOPE PROBING ...........................111
Introduction...........................................................................................................................111
Methods................................................................................................................................ 113
Microcosm Construction and Analytical Techniques ................................................... 113
DNA Extraction and Ultracentrifugation ...................................................................... 114
PCR, TRFLP and Sequencing of 16S rRNA Genes...................................................... 115
Results and Discussion ........................................................................................................ 116
References............................................................................................................................ 130

vi

LIST OF TABLES

Table 2.1. Average percent toluene remaining in control and sample microcosms (error bars
represent standard deviations represent from triplicates). ..................................................... 24
Table 2.2. Comparison of dominant fragments in heavy fraction TRFLP to clone restriction
enzyme cut sites predicted from sequence analyses. .............................................................. 25
Table 3.1. Primers used in this study to investigate the presence of the bssA gene ...................... 53
Table 3.2. Phylogenetic affiliation of each 16S rRNA clone in nitrate amended toluene degrading
microcosms as determined with the RDP analysis tool “classifier” ....................................... 54
Table 3.3. Comparison of fragment length of dominant T-RF in heavy fractions to predicted
fragment length from in silico sequence analyses (nitrate amended agricultural soil
microcosms)............................................................................................................................ 56
Table 3.4. Comparison of fragment length of dominant T-RFs in heavy fractions to predicted
fragment lengths from in silico sequence analyses (nitrate amended granular sludge
microcosms)............................................................................................................................ 57
Table 3.5. Phylogenetic affiliation of each 16S rRNA clone in sulfate amended toluene degrading
microcosms as determined with the RDP analysis tool “classifier” ....................................... 58
Table 3.6. Comparison of fragment length of dominant T-RF in heavy fractions to predicted
fragment lengths from in silico sequence analyses (sulfate amended agricultural soil
microcosms)............................................................................................................................ 60
Table 3.7. Comparison of fragment length of dominant T-RF in heavy fractions to predicted
fragment lengths from in silico sequence analyses (digester sludge sulfate amended
microcosms)............................................................................................................................ 61
Table 3.8. Comparison of fragment length of dominant T-RF in heavy fractions to predicted
fragment lengths from in silico sequence analyses (sulfate amended contaminated site soil
microcosms)............................................................................................................................ 62
Table 3.9. Success (+) or failure (-) of primers sets for bssA gene amplification. ........................ 63
Table 4.1. Success of bssA and bamA primers, amplicons cloned and the consortia targeted for
qPCR. .................................................................................................................................... 101
Table 5.1. Summary of the investigations conducted on the anaerobic degradation of MTBE in
different inoculum types ....................................................................................................... 122
Table 5.2. Phylogenetic affiliation of bacterial 16S rRNA clone in methanogenic MTBE

vii

degrading microcosms as determined with the RDP analysis tool “classifier” .................... 123
Table 5.3. Phylogenetic affiliation of Archaeal 16S rRNA clone in methanogenic MTBE
degrading microcosms as determined with the RDP analysis tool “classifier” .................... 124
Table 5.4. Comparison of fragment length of dominant T-RF in heavy fractions to predicted
fragment length from in silico sequence analyses ................................................................ 125

viii

LIST OF FIGURES
-1

Figure 2.1. Comparison of TRFLP electropherograms of heavier fractions (>1.736 g mL )
between DNA obtained from labeled and unlabeled toluene amended microcosms,
illustrating the dominance of TFRLP fragment 313 bp in fractions from the labeled
toluene amended microcosms. A similar pattern was observed in the soil 1 replicate and
in replicates of soil 2...................................................................................................... 26
Figure 2.2. Difference between abundance of Polaromonas sp. rRNA gene copies in
13
ultracentrifugation fractions from labeled ( C toluene) and unlabeled toluene amended
microcosms from soil 2 as determined via qPCR. Fractions obtained from soil 1
illustrated a similar trend. ............................................................................................... 27
Figure 2.3. Correlation between Polaromonas sp. 16S rRNA gene copies (determined by qPCR)
and toluene removal over time in live samples and no-toluene controls (microcosms
constructed ...................................................................................................................... 28
Figure 2.4. Benzene, m-xylene and cis-dichloroethene (cDCE) concentrations over time in
supernatant of microcosms samples and in autoclaved controls (error bars represent
standard deviations). ....................................................................................................... 29
Figure 3.1. Percent relative abundance of fragments (digested by Hae III) assigned to
Comamonadaceae within buoyant density gradients of DNA extracted from the nitrate
13
amended agricultural soil microcosms. Figure symbols: ▲ C-toluene (~33% toluene
13

13

degraded); ♦ C-toluene (~75% toluene degraded); ■ C-toluene (~100% toluene
12

degraded); □ C-toluene (~100% toluene degraded). ................................................... 64
Figure 3.2. Percent relative abundance of fragments (digested by Hae III) assigned to Azoarcus
within buoyant density gradients of DNA extracted from the nitrate amended agricultural
13
soil microcosms. Figure symbols: ▲ C-toluene (~33% toluene degraded);
13

13

♦ C-toluene (~75% toluene degraded); ■ C-toluene (~100% toluene degraded);
12

□ C-toluene (~100% toluene degraded). ....................................................................... 65
Figure 3.3. Percent relative abundance of fragments (digested by Hae III) assigned to Thauera,
within buoyant density gradients of DNA extracted from the nitrate amended granular
13
sludge microcosms. Figure symbols: ▲ C-toluene (~33% toluene degraded);
13

13

♦ C-toluene (~75% toluene degraded); ■ C-toluene (~100% toluene degraded);
12

□ C-toluene (~100% toluene degraded). ....................................................................... 66
Figure 3.4. Percent relative abundance of fragments (digested by Hae III) assigned to
Desulfosporosinus with T-RF 77 bp within buoyant density gradients of DNA extracted
13
from the agricultural soil sulfate amended microcosms. Figure symbols: ▲ C-toluene
13

13

(~33% toluene degraded); ♦ C-toluene (~75% toluene degraded); ■ C-toluene
ix

12

(~100% toluene degraded); □ C-toluene (~100% toluene degraded). .......................... 67
Figure 3.5. Percent relative abundance of fragments (digested by Hae III) assigned to
Desulfosporosinus with T-RF 213 bp within buoyant density gradients of DNA extracted
13
from the agricultural soil sulfate amended microcosms. Figure symbols: ▲ C-toluene
13

13

(~33% toluene degraded); ♦ C-toluene (~75% toluene degraded); ■ C-toluene
12

(~100% toluene degraded); □ C-toluene (~100% toluene degraded). ........................... 68
Figure 3.6. Percent relative abundance of fragments (digested by Hae III) assigned to
Syntrophobacteraceae within buoyant density gradients of DNA extracted from the
13
digester sludge sulfate amended microcosms. Figure symbols: ▲ C-toluene (~33%
13

13

toluene degraded); ♦ C-toluene (~75% toluene degraded); ■ C-toluene (~100%
12

toluene degraded); □ C-toluene (~100% toluene degraded). ........................................ 69
Figure 3.7. Percent relative abundance of fragments (digested by Hae III) assigned to
Desulfobulbaceae within buoyant density gradients of DNA extracted from the
13
contaminated site, sulfate amended microcosms. Figure symbols: ▲ C-toluene (~33%
13

13

toluene degraded); ♦ C-toluene (~75% toluene degraded); ■ C-toluene (~100%
12

toluene degraded); □ C-toluene (~100% toluene degraded). ........................................ 70
Figure 3.8. Phylogenetic tree of bssA partial sequences (722 bp) from nitrate amended
agricultural soil microcosms (using the primer set 7772f/8546r) along with the closest
matches in GenBank, constructed with MEGA 4.1 software using the neighbor-joining
method. ............................................................................................................................ 71
Figure 3.9. Phylogenetic tree of bssA partial sequences (722 bp) from nitrate amended granular
sludge microcosms (using the primer set 7772f/8546r) along with the closest matches in
GenBank, constructed with MEGA 4.1 software using the neighbor-joining method. ... 72
Figure 3. 10. Phylogenetic trees of bssA partial sequences (97 bp) from sulfate amended digester
sludge microcosms (using the primer set SRBf/SRBr) along with the closest matches in
GenBank, constructed with MEGA 4.1 software using the neighbor-joining method. ... 73
Figure 3.11. Phylogenetic trees of bssA partial sequences (637 bp) from sulfate amended
contaminated soil microcosms (using the primer set 7772f/8828r) along with the closest
matches in GenBank, constructed with MEGA 4.1 software using the neighbor-joining
method. ............................................................................................................................ 74
Figure 3.12. Difference between abundance of bssA gene copies in ultracentrifugation fractions
13
from labeled ( C toluene) and unlabeled toluene amended microcosms from the
granular sludge nitrate amended microcosms as determined via qPCR. Figure symbols:
13
12
■ C-toluene (~100% toluene degraded); □ C-toluene (~100% toluene degraded)..... 75
Figure 3.13. Difference between abundance of bssA gene copies in ultracentrifugation fractions
x

13

from labeled ( C toluene) and unlabeled toluene amended microcosms from the
agricultural soil nitrate amended microcosms as determined via qPCR. Figure symbols:
13
12
■ C-toluene (~100% toluene degraded); □ C-toluene (~100% toluene degraded)..... 76
Figure 3.14. Difference between abundance of bssA gene copies in ultracentrifugation fractions
13
from labeled ( C toluene) and unlabeled toluene amended microcosms from the
digester sludge sulfate amended microcosms as determined via qPCR. Figure symbols:
13
12
■ C-toluene (~100% toluene degraded); □ C-toluene (~100% toluene degraded)..... 77
Figure 4. 1. Gene numbers of bssA and bamA during toluene degradation in nitrate amended
microcosms AgN. The error bars represent standard deviations form triplicate qPCR
samples......................................................................................................................... 102
Figure 4.2. Gene numbers of bssA and bamA during toluene degradation in nitrate amended
microcosms BoN1. The error bars represent standard deviations form triplicate qPCR
samples. ......................................................................................................................... 103
Figure 4.3. Gene numbers of bssA and bamA during toluene degradation in nitrate amended
microcosms GSN. The error bars represent standard deviations form triplicate qPCR
samples. ......................................................................................................................... 104
Figure 4.4. Gene numbers of bssA and bamA during toluene degradation in a sulfate amended
microcosm, DUKE.The error bars represent standard deviations form triplicate qPCR
samples. ......................................................................................................................... 105
Figure 4.5. Gene numbers of bssA and bamA during toluene degradation in a methaongeic
microcosm, ASM. The error bars represent standard deviations form triplicate qPCR
samples. ......................................................................................................................... 106
Figure 4.6. Gene numbers of bssA and bamA during toluene degradation in a methaongeic
microcosm, HM. The error bars represent standard deviations form triplicate qPCR
samples. ......................................................................................................................... 107
12

Figure 5.1. MTBE concentration over time in C-MTBE amended abiotic controls (♦),
13

12

C-MTBE (■) and C-MTBE (□) amended samples. The arrows indicate when DNA
was extracted. The error bars represent standard deviations from triplicate microcosms.
..................................................................................................................................... 126

Figure 5.2. Percent relative abundance of fragments (digested by Hae III) assigned to
Clostridiales within buoyant density gradients of Bacterial DNA extracted from the
13
methanogenic activated sludge microcosms. Figure symbols: ♦ C-MTBE (~30%
13

12

toluene degraded); ■ C-MTBE (~70% toluene degraded); □ C-MTBE (~70% toluene
degraded). ...................................................................................................................... 127
Figure 5.3. Percent relative abundance of fragments (digested by Hae III) assigned to
xi

Sphingomonadales within buoyant density gradients of Bacterial DNA extracted from
13
the methanogenic activated sludge microcosms. Figure symbols: ♦ C-MTBE (~30%
13

12

toluene degraded); ■ C-MTBE (~70% toluene degraded); □ C-MTBE (~70% toluene
degraded). ...................................................................................................................... 128
Figure 5.4. Percent relative abundance of fragments (digested by Hae III) assigned to
Methanosarcina within buoyant density gradients of Archaeal DNA extracted from the
13
methanogenic activated sludge microcosms. Figure symbols:■ C-MTBE (~70%
12

toluene degraded); □ C-MTBE (~70% toluene degraded). ......................................... 129
Figure 5.5. Percent relative abundance of fragments (digested by Hae III) assigned to
Methanocorpusculum within buoyant density gradients of Archaeal DNA extracted from
13
the methanogenic activated sludge microcosms. Figure symbols:■ C-MTBE (~70%
12

toluene degraded); □ C-MTBE (~70% toluene degraded). ......................................... 130

xii

ABBREVIATIONS
bamA- the gene encoding 6-oxocyclohex-1-ene-1-carBoN1yl-CoA hydrolase
BSS - benzylsuccinate synthase, a glycyl radical enzyme catalyzing the first step in anaerobic
toluene degradation
BssA- α-subunit of benzyl succinate synthase
bssA - the gene encoding BssA
BTEX - benzene, toluene, ethylbenzene and o-, p-, and m-xylenes
DNA - deoxyribonucleic acid
MTBE - methyl tertiary butyl ether
OTU - operational taxonomic unit
PCR - polymerase chain reaction
qPCR- quantitative PCR
rDNA - ribosomal DNA
TBA - tertiary butyl alcohol
TRFLP - terminal restriction fragment length polymorphism

xiii

CHAPTER 1
INTRODUCTION

MTBE and BTEX Contamination
The chemicals benzene, toluene, ethylbenzene and xylene (BTEX) and MTBE (a fuel oxygenate)
are frequently the major pollutants at gasoline contaminated sites (leaking underground storage
tank sites or LUST sites) (24). In the United states, 50 states have reported MTBE in
groundwater, surface water and drinking water (29). Bioremediation can be a cost-effective
method to remove groundwater contaminants either through natural attenuation or by advanced
engineering methods. Understanding the microbial processes involved in the biodegradation of
BTEX and MTBE has the potential to improve the efficiency of LUST site remediation.

Stable Isotope Probing (SIP)
Although many BTEX degraders have been identified through enrichment and isolation
procedures, a question arises that culturing microorganisms may not fully reflect the microbial
diversity (2, 3, 30). Stable isotope probing (SIP) is a novel molecular method which can link the
function to active microbial members in environmental samples or directly in field studies. The
application of SIP has the potential to increase our understanding of function in mixed microbial
systems and its use has increased remarkably in recent years (9, 11, 20, 22, 23). The method
consists of sample exposure to labeled substrates (e.g.
1

13

15

18

C, N, O), separation of labeled and

unlabeled nucleic acids (DNA or RNA) and analysis of separated heavy (labeled) or unlabeled
(background) nucleic acids. Nucleic acids can be separated by needle extraction (25, 26) or by
fractionation (9, 16, 21).

Functional Genes for Anaerobic Toluene Degradation
The gene encoding for the enzyme benzylsuccinate synthase has been linked to anaerobic
toluene degradation under nitrate reducing (1, 15), sulfate reducing (32-34), ferric iron reducing
(7, 10), and methanogenic enrichment cultures or environmental samples (31, 32). The enzyme
benzylsuccinate synthase catalyzes the first step of anaerobic toluene degradation and involves
the addition of toluene across the double bond of fumarate to produce (R)-benzylsuccinate.
Benzylsuccinate is then oxidized to benzoyl-CoA and succinate via β-oxidation pathway. The
final step is the recycling of the fumarate cosubstrate of benzylsuccinate synthase from succinate
by succinate dehydrogenase. The overall result is an oxygen-independent reaction (6).
Benzylsuccinate synthase, which has been identified in denitrifying bacteria, was characterized
as a novel glycyl radical enzyme (19). The enzyme contains a big subunit, α-subunit (98 kDA)
and two small subunits β (8.6 kDa) and γ (6.6 kDa); bssA encodes the large α subunits while
bssB and bssC encode the other two small subunits, β and γ (13). A limited number of bssA
sequences from pure cultures are available to date (1, 8, 10, 14, 19, 27, 28). Previous studies
have developed PCR methodologies to target the bssA gene (5, 12) and the current work
involved using these methods to amplify the functional gene.

The other functional gene investigated in this research was previously reported to be important
for the degradation of aromatics. Anaerobic aromatic biodegradation typically involves the
2

channeling of aromatic growth substrates to the central intermediate benzoyl-coenzyme A (CoA)
prior to dearomatization and ring cleavage (17). In Thauera aromatica, the metabolism of
benzoyl-CoA

comprises

of

several

steps

with

ring

cleavage

action

by

6-oxocylcohex-1-ene-1-carbonyl-CoA (6-OCH-CoA) hydrolase, which likely catalyzes the
transformation of 6-OCH-CoA to 6-hydroxypimelyl-CoA (17, 18). The ring-cleaving hydrolase
of the benzoyl-CoA pathway is encoded by the bamA gene. Recently, this pathway was studied
in obligate anaerobes that use aromatic growth substrates (17).

Objectives
The overall objectives of this project were:

1) To characterize the microorganisms able to degrade toluene under a range of redox conditions
(aerobic, nitrate and sulfate reducing and methanogenic) from a variety of soil and sediment
sources using stable isotope probing (SIP) (Chapters 2 and 3).

2) To investigate the diversity of the bssA gene (encodes for benzylsuccinate synthase α unit)
and bamA genes (encodes for the ring-cleaving hydrolase of the benzoyl-CoA pathway) in a wide
range of anaerobic toluene-degrading consortia (Chapter 4);

3) To identify the organisms able to transform MTBE anaerobically using SIP (Chapter 5).

Chapter 2 describes the work targeting aerobic toluene degradation and also describes the SIP
methodology used throughout the thesis. In summary, the work identified members of
3

Polaromonas as the key aerobic toluene-degrading bacteria. This conclusion was also supported
by quantitative PCR (qPCR) results. A modified version of Chapter 2 was published in Applied
and Environmental Microbiology.

The same SIP methodology was used in Chapter 3 to investigate diversity of microorganisms
able to uptake carbon from toluene in a diverse number of samples under sulfate and nitrate
amended conditions. In these studies, different microorganisms were identified as toluene
degraders. Microorganisms classifying within the family Comamonadaeae and the genus
Thauera were pinpointed in nitrate amended microcosms seeded from agricultural soil and
granular sludge, respectively. Members of Desulfosporosinus, Syntrophaceae, Desulfobulbaceae
were identified from agricultural soil, digester sludge and contaminated aquifer sediment as
toluene degraders under sulfate amended conditions. A modified version of Chapter 3 was
published in Applied and Environmental Microbiology.

The work described in Chapter 4 focuses on previously designed primer pairs to amplify the
bssA and bamA genes. The bssA phylogenetic information was also related to the toluene
degraders identified via SIP in Chapter 3. In Chapter 4, I tested a range of bssA- and bamAprimers on 16 toluene-degrading consortia. Two primer pairs, 7772f/8546r and SRBr/SRBf,
exhibited good coverage for nitrate amended samples and sulfate amended samples, respectively.
The bamA primer set (bam-sp9 and bam-asp1) produced a strong amplicon in DNA extracted
from all except one microcosm. Partial bssA and bamA sequences were obtained for a number of
samples (four bssA and six bamA sequences) and compared to those available in GenBank. The
partial bssA sequences (from nitrate amended and methanogenic microcosms) were most similar

4

to Thauera sp. DNT-1, Thauera aromatica, Aromatoleum aromaticum EbN1 and bssA clones
from a study involving sulfate reducing toluene degradation. The bamA sequences obtained
could be placed into five clades.

In Chapter 5, SIP was utilized on a methanogenic MTBE-degrading consortium. The SIP
experiments indicated bacteria in the phyla Firmicutes (family Ruminococcaceae) and
Alphaproteobacteria (genus Sphingopyxis) were the dominant MTBE degraders. Previous
studies on have suggested a role for Firmicutes in anaerobic MTBE degradation, however the
Alphaproteobacteria phylotype represents a novel MTBE degrader. Two archaeal phylotypes
(genera Methanosarcina and Methanocorpusculum) were also enriched in the heavy fractions
and these organisms may be responsible for minor amounts of MTBE degradation or for the
uptake of metabolites released from the primary MTBE degraders. The work described in
Chapters 5 was published in Applied and Environmental Microbiology.

5

REFERENCES

6

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Leuthner, B., C. Leutwein, H. Schulz, P. Horth, W. Haehnel, E. Schiltz, H. Schagger,
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9

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Winderl, C., H. Penning, F. von Netzer, R. U. Meckenstock, and T. Lueders. 2010.
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10

CHAPTER 2
TOLUENE DEGRADATION IN CONTAMINATED SITE MICROCOSMS IS
DIRECTLY LINKED TO A POLAROMONAS STRAIN

Introduction
Sites containing leaking underground storage tanks (LUST sites) are a national problem,
resulting in BTEX (benzene, toluene, ethylbenzene, xylenes) or oxygenate (e.g. MTBE or TBA)
contamination and risk to sensitive receptors such as drinking water supplies. A common
remediation method for such sites involves in situ biological degradation of these contaminants.
Aerobic bioremediation has been favored over other electron acceptors, such as nitrate, sulfate
and ferric iron, because BTEX degradation is typically faster when oxygen is available. Although
many aerobic BTEX isolates have been obtained in pure culture, less is known about the
organisms responsible for in situ contaminant transformation. For example, toluene
transformation has been particularly well studied in a number of isolates (e.g. Pseudomonas
putida F1, P. putida mt-2, P. mendocina KR1, P. stutzeri OX1, Burkholderia vietnamiensis G4,
Burkholderia sp. strain JS150 and Ralstonia pickettii PK01, for review see (14)), however,
information on the organisms responsible for toluene degradation in a mixed community sample
is lacking. In this study, we attempt to address this knowledge gap, focusing on toluene as a
model BTEX contaminant. Identification of microorganisms responsible for BTEX degradation
in mixed community environmental samples should result in a better understanding of
microorganisms responsible for degradation in situ. It is hoped that such information can aid in
the design of remediation approaches as well as in the prediction of contaminant removal rates.

11

To identify the dominant organism responsible for toluene transformation within a mixed
community sample, an approach was adopted to result in less culture bias than would be produced
using repeated enrichments or isolation. Therefore, the data produced should more accurately
reflect the organisms responsible for in situ toluene transformation. To do this, stable isotope
probing (SIP), a method that links in situ function with identity for mixed microbial systems (15),
was adopted. The method involves sample exposure to labeled compounds, separation of heavy
(label incorporated) and light (background) nucleic acids using ultracentrifugation, then gene
sequencing (16S rRNA) to identify the label-consuming microorganisms. For this purpose, SIP
has two key advantages over traditional microbiological methods for investigating contaminant
removal, as follows, (1) identification of organisms able to assimilate carbon from the
contaminant, therefore selectively pinpoints efficient degraders and (2) studies can be conducted
on environmental samples, thus results are much more applicable to the field environment than
traditional approaches.

The objective here was to identify the organisms responsible for aerobic carbon uptake from the
environmental contaminant toluene in two soils obtained from a BTEX contaminated site. DNA
based SIP was utilized to identify the active toluene degrader and following this, a real time PCR
assay was designed to confirm these results. The results were also compared with those from
previous m-xylene and benzene SIP studies on this soil (5). The research offers new insight into
contaminant transformation in mixed communities.

12

MATERIALS AND METHODS
Experimental design, microcosm setup and chemical analyses
The gasoline-contaminated soil used in this study was collected from a gasoline-contaminated
site located in Michigan. Two soil samples, obtained at different depths (3 - 4 ft and 5 - 6 ft deep)
at the same site were used and are further referred to as soil 1 and soil 2. Microcosms were
constructed with 6 g soil along with 20 mL phosphate-buffered mineral media (12) in a 150 mL
serum bottle sealed with rubber stoppers and aluminum seals. Three sets of experiments were
conducted, experiment 1 involved SIP to identify the dominant toluene degraders in both soils,
experiment 2 focused on real-time PCR to confirm SIP results and investigate microorganism
growth on toluene and experiment 3 involved simple biodegradation studies with other
environmental contaminants (benzene, m-xylene and cis-dichloroethene).

The SIP study (experiment 1) was conducted on both soils 1 and 2 and involved triplicate abiotic
controls, triplicate unlabeled toluene (1 μL, 99 %, Chem Service, West Chester, PA) and
13

triplicate labeled toluene (1 μL ring- C6 toluene, 99%, Cambridge Isotope Laboratories, Inc.
Andover, MA) amended samples. Experiment 2 involved sixteen sample microcosms, each with
6 g soil 2 and 20 mL media (as above). Toluene (1 μL, 99 %, Chem Service, West Chester, PA)
was added to eight of these and the other eight served as no-toluene controls (to determine if
toluene was needed to cause an increase in Polaromonas sp. cell numbers). At each sampling
time, two samples and two controls were sacrificed for DNA extraction and qPCR.

In experiment 3, for each contaminant investigated (benzene, m-xylene and cis-dichloroethene),

13

three sample microcosms and two autoclaved control microcosms were constructed using the
supernatant of toluene degrading soil microcosms from soil 2. Specifically, following the
depletion of toluene, 5 mL supernatant was transferred to a 150 mL serum bottle with 20 mL
media (as above). Following this, either benzene (99.8%, Sigma Aldrich), cis-dichloroethene
(purity not provided, Supelco) or m-xylene (99%, Sigma Aldrich) were added to a final solution
-1

concentration of approximately 45 mg L . All microcosms were incubated at room temperature
(~20

°C)

with

reciprocal

shaking.

Contaminant

(toluene,

benzene,

m-xylene

and

cis-dichloroethene) concentrations in headspace gas samples (200 μL) were typically determined
daily with a gas chromatograph (Perkin Elmer) equipped with flame ionization detector and a
capillary column (J&W Scientific, DB-624, diameter 0.53mm). Injector and detector temperature
were set at 200 oC and the column temperature was 120oC.

DNA extraction
The powersoil DNA extraction kit (MO BIO Laboratories, Inc. Carlsbad, CA) was used for soil
DNA extraction in experiments 1 and 2 according to the manufacturer’s recommended procedure.
Extraction times, number of samples and mass of soil extracted varied depending on the
experiment. In experiment 1, DNA was extracted from the entire microcosm, whereas in
experiment 2, DNA was extracted from 0.3 g soil. In experiment 1 (SIP study), for both soil 1
and soil 2, two labeled and two unlabeled microcosms were sacrificed for DNA extraction at day
7 (at this time, all toluene had been depleted). In experiment 2 (qPCR study), DNA was extracted
from samples sacrificed at successive time points for the unlabeled toluene sample microcosms
and no-toluene-amended control microcosms. Specifically, two sample and two control

14

microcosms were scarified at day 3, 4, 5, 6 when approximately 20 %, 50 %, 80 % and 100 % of
the added toluene was transformed.
DNA ultracentrifugation
Approximately 10 μg DNA (quantified with Nanodrop, ND-1000) was added to Quick-Seal
polyallomer tubes (13×51 mm, 5.1 ml, Beckman Coulter) along with a Tris-EDTA (TE, pH 8.0)
/CsCl solution. Prior to sealing (cordless quick-seal tube topper, Beckman), the buoyant density
(BD) was determined with a model AR200 digital refractometer (Leica Microsystems Inc.) and
adjusted by adding small volumes of CsCl solution or Tris-EDTA buffer. The tubes were
centrifuged at 178,000 g (20 ºC) for 48 h in a Stepsaver 70 V6 Vertical Titanium Rotor (8 x 5.1
ml capacity) within a Sorvall WX 80 Ultra Series Centrifuge (Thermo Scientific). Following
centrifugation, the tubes was placed onto a fraction recovery system (Beckman) and fractions
(150 l) were collected. The BD of each fraction was measured, and CsCl was removed by
glycogen-assisted ethanol precipitation.

PCR and TRFLP
The ultracentrifugation fractions from replicates of labeled and unlabeled microcosms for both
soils were PCR-amplified using 27F-FAM (5’-AGAGTTTGATCMTGGCTCAG, 5’ end-labeled
with

carboxyfluorescine)

and

1492R

(5’-GGTTACCTTGTTACGACTT)

(Operon

Biotechnologies) as previously described (4). The presence of PCR products was confirmed by
1.5% agarose gel electrophoresis and the subsequent staining of the gels with ethidium bromide.
PCR products were purified with QIAquick PCR purification kit (Qiagen Inc.), following the
manufacturer’s instructions and approximately 150 ng purified PCR products were digested with

15

Hae III (New England Biolabs) with a 6-hour incubation period. Additional digests (Hha I, Mse I,
Bsp1286I, BsrB I) for TRFLP analyses in a number of heavy labeled fractions were included to
correlate the TRFLP fragment lengths to the in silico cut sites of the cloned 16S rRNA gene
sequences. DNA fragments were separated by capillary electrophoresis (ABI Prism 3100 Genetic
Analyzer, Applied Biosystems) at the Research Technology Support Facility (RTSF) at Michigan
State University. Data were analyzed with GeneScan software (Applied Biosystems) and the
percent abundance of each fragment was determined.

16S rRNA gene sequencing
Heavy fraction

13

-1

C-DNA (BD value of 1.744 g mL ) was amplified as above except the forward

primer was unlabeled and the final extension time was extended to 15 minutes. The PCR
products were purified with QIAquick PCR purification kit (Qiagen Inc.) and cloned into
Escherichia coli TOP10 vector supplied with a TOPO TA cloning kit (Invitrogen Corporation). E.
-1

coli clones were grown on Luria-Bertani (LB) medium solidified with 15 g agar L

with 50 g

ampicillin L-1 for 16 h at 37 ºC. Colonies with inserts were verified by PCR with primers M13 F
(5’-TGTAAAACGACGGCCAGT-3’) and M13 R (5’-AACAGCTATGACCATG-3’), plasmids
were extracted from the positive clones with a QIAprep miniprep system (Qiagen, Inc.) and the
insertions were sequenced at RTSF. The Ribosomal Database Project (RDP) (Center for
Microbial Ecology, Michigan State University) analysis tool “classifier” was utilized to assign
taxonomic identity.

16

Real-time PCR
A quantitative real-time PCR assay (qPCR) was developed targeting the 16S rRNA gene of the
dominant toluene degrader identified above. The assay was developed to quantify the increase in
the DNA BD resulting from label incorporation. In addition, the assay provided a rapid method
to investigate cell numbers under mixed culture conditions as toluene was depleted. The assay
was conducted in a Chromo 4 real-time PCR cycler (Bio-Rad) using the primer set PO313F (5’AATGGATGGTACAGAGGGTC-3’)

and

PO313R

(5’-ATTACTAGCGATTCCGACTT-3’)

(Operon Biotechnologies), and produced a 114 bp PCR product. Primers were designed with
NCBI primer-BLAST (National Center for Biotechnology Information, Bethesda, MD) and
checked for specificity using the Ribosomal Database Project (RDP) probe match tool. The
forward primer matched 64 16S rRNA gene sequences (out of a total of 856,341) and of this, 32
belonged to the genus Polaromonas. The reverse primer matched 105,600 16S rRNA gene
sequences and from this, 252 belonged to the genus Polaromonas. For the purposes of this study,
this level of specificity was considered adequate. Both nucleic acid samples from density
gradient fractions (experiment 1, SIP fractions) and total DNA extractions at successive time
points (experiment 2, real-time PCR) were quantified with primers PO313F and PO313R using a
SYBR green real-time PCR kit (Applied Biosystems) following the manufacturer’s
recommended recipe. Each 20 μL PCR reaction mixture containing 10 μL ABI real-time PCR kit ,
0.25 μM of each primer, and 1 μL DNA template. The thermal protocol consisted of an initial
denaturation (95 ºC, 15 s), 40 cycles of amplification (95 ºC, 15 s; 60 ºC, 20 s; 72 ºC 20 s) and a
terminal extension step (72 ºC, 2 min). Melting curves were constructed from 55.0ºC to 95.0ºC,
read every 0.6ºC for 2 s. For each gradient fraction, 1 μL was diluted with 3 μL water as template
(to conserve the sample). For experiment 2, 1 μL total DNA was used directly as the template.

17

For both, samples were measured in triplicate. Cloned plasmid DNA was utilized as a standard
for quantification and gene copies were determined as shown in the equation below, as
previously described (16) (plasmid size was 5441 bp, including 1485 bp of insert).

  1 mol bp DNA   6.023  10 23 bp 

ng   1g




gene copies   DNA concentration,

 

3 ng   660g DNA  
mol bp
L  1000

 

 



1 copy

 plasmid size [bp]   volume, L 




RESULTS AND DISCUSSION
Toluene removal (both labeled and unlabeled) occurred rapidly (~100 % removal in seven days)
in triplicates of soil 1 and soil 2 microcosms, but was limited in the autoclaved controls (~20%
decrease, likely due to sorption), confirming a biological removal mechanism (Table 2.1).
Several molecular methods (SIP and qPCR) were employed to identify the dominant
microorganism responsible for aerobic toluene removal in these microcosms. Following toluene
depletion, DNA was extracted from replicate soil 1 and soil 2 microcosms (labeled and unlabeled
toluene amended) and subjected to ultracentrifugation, followed by fractionation of the
ultracentrifugation samples. TRFLP was then conducted on all fractions so that heavy fractions
from the labeled and unlabeled samples could be compared and thus account for false positives
(from contamination or high GC content microorganisms) in the sample heavy fractions. TRFLP
profiles indicated one fragment (313 bp) was more dominant in the heavy fractions (> ~ 1.74 g
-1

mL ) of labeled toluene amended microcosms compared to the controls (unlabeled toluene)
(Figure 2.1). This trend was observed in the replicates of both soils. Other TRFLP fragments
were found in the heavy fractions from the labeled toluene amended samples, however, as these

18

were also found at similar levels in the heavy fractions of the controls, they were excluded from
further analyses.

The identity of the organism producing the TRFLP 313 bp fragment was determined using two
-1

methods. Firstly, the fraction (BD value of 1.744 g mL ) with highest relative abundance of the
313 bp fragment was subject to cloning and sequencing. Sequences with a Hae III cut site of 313
bp were identified from this. Additionally, fractions with dominant 313 bp fragments were
chosen for additional TRFLP analyses with four other enzyme (Hha I, Mse I, Bsp1286I, BsrB I).
The dominant fragments obtained from these additional TRFLP digests were then compared to
the clone library sequences to correlate actual cut sites with predicted cuts sites, thus determine
the identity of the organism producing the Hae III 313 bp peak (Table 2.2). Only slight
differences (1 to 2) between the predicted and actual lengths were seen, such differences have
been noted by others (1, 13) and may be a result of variability within the TRFLP method. The
clone sequence obtaining the five appropriate cut sites classified as a Polaromonas strain within
the class β Proteobacteria. To our knowledge, this is the first report directly linking toluene
degradation to the Polaromonas genus.

Two additional lines of inquiry provided further evidence that the Polaromonas strain was indeed
responsible for toluene transformation within the mixed community sample. Firstly, the relative
distribution of Polaromonas 16S rRNA genes, as determined via the developed qPCR assay,
indicated an increase in DNA BD between the labeled and unlabeled toluene amended
microcosms (Figure 2.2, soil 1). Maximum 16S rRNA gene abundance levels from labeled
-1

-1

toluene amended microcosms were found at 1.742 g mL (soil 1) and1.744 g mL (soil 2), a

19

clear increase over the maximum abundance values in the unlabeled toluene amended samples
-1

-1

(1.719 g mL for soil 1 and 1.726 g mL for soil 2). Thus, the BD differences between the peak
-1

abundance in unlabeled compared to the labeled were 0.023 g mL

(soil 1) and 0.018 g mL

-1

(soil 2), respectively. The slight difference between the two soils is likely a result of analytical
variability. As expected, the increase is less than has been seen with pure cultures exposed to
-1

higher concentrations of labeled substrates (e.g. an increase of 0.038 g mL was noted in E. coli
-1 13

following exposure to 1.3 g L

C lactate (3)), yet it is a large enough signal to indicate label

uptake from toluene by the Polaromonas population.

The second line of evidence indicating the Polaromonas sp. was responsible for toluene
degradation is provided by Polaromonas specific qPCR analyses of toluene degrading
microcosms. Specifically, qPCR was utilized to monitor the total number of Polaromonas
species at successive time points of toluene removal. The data collected indicated a clear increase
in Polaromonas sp. cell numbers as toluene was depleted in the replicate live samples but not in
the replicate no-toluene controls, indicating toluene was required for growth of these organisms
(Figure 2.3). The qPCR assay provided a rapid investigative tool enabling cell populations to be
determined and correlated with toluene removal in mixed culture, without the need for isolation.
Again, to our knowledge, these data represent the first report of growth on toluene of by an
organism in the Polaromonas genus.

Supernatant samples transferred from toluene degrading microcosms (following complete
removal of toluene) were tested for their ability to transform other contaminants. Previous SIP

20

research indicated the same (based on 16S rRNA gene sequences) Polaromonas sp. was
responsible for benzene transformation within a mixed community microcosm sample
constructed from the same soil (5), therefore benzene degradation was tested to confirm this
result. Another SIP study on m-xylene degradation with the same soil found that a
microorganism other than the Polaromonas sp., was responsible for m-xylene degradation (5),
therefore m-xylene was also added to the supernatant to further investigate this finding. Finally,
given the importance of cis-dichloroethene (cDCE) as an environmental contaminant, and
previous reports of Polaromonas sp. strain JS666 using cDCE as a sole energy and carbon source
(2, 11), the supernatant was also tested for cDCE removal. As expected, benzene transformation
occurred rapidly in the samples but not in the autoclaved controls, whereas neither m-xylene nor
cDCE concentrations declined in either the samples or controls (Figure 2.4).

This research provides evidence that that a Polaromonas species survives and grows in the
presence of toluene while in a mixed community sample. Research to date on both aerobic and
anaerobic toluene degradation has typically focused on pure cultures, due to the technical
difficulties associated with examining particular species while existing in mixed culture. The
primary method of inquiry used here, SIP, allows function to be linked with identity in a mixed
community sample, more realistically reflecting a real-world scenario. The method has been
utilized once before to investigate toluene degradation in mixed community samples. In that
study, another novel organism, belonging to the “candidate” phylum TM7 was responsible for
toluene transformation in mixed community samples (10). Clearly, SIP provides a unique ability
to open up the “black box” of the microbial world providing interesting contrasts to previous
reports based on isolations. Stable isotope probing, in theory, avoids the biases involved in

21

conventional isolation procedures. In other words, microorganisms that do not grow well under
typical isolation conditions can still be studied and identified if SIP is used. The results presented
here confirm this, as others have indicated Polaromonas species have traits (e.g. oligotrophic and
slow growing) that are likely to impede their isolation and characterization by standard methods
(11).

Since the genus was first reported in 1996 (6), only a small number of other Polaromonas strains
have been obtained. The type stain, P. vacuolata, was isolated in 1996 from Antarctic marine
waters (6). Others, also obtained from interesting sources, were isolated more recently, including
P. aquatica obtained from tap water in 2006 (9) and P. hydrogenivorans, a psychrotolerant

hydrogen oxidizing bacterium isolated from soil over permafrost in Alaska in 2007 (17). More
relevant to the research presented here are the remaining two Polaromonas strains previously
reported, as both have been linked to the degradation of important environmental contaminants.
The first, isolated in 2002 from granular activated carbon from a chlorinated solvent
pump-and-treat plant in Germany, Polaromonas sp. strain JS666, is the only known
microorganism able to grow using the environmental contaminant cDCE as a sole carbon and
energy source (2, 11). The other, isolated in 2003 from coal-tar contaminated sediment, P.
naphthalenivorans strain CJ2 uses naphthalene as a sole carbon and energy source (7).

Interestingly, P. naphthalenivorans strain CJ2 was also first identified with the SIP method (8).
The 16S rRNA gene of the toluene degrading Polaromonas strain described here was 96.6 %
(1447/1498) and 97.6 % (1459/1495) similar to P. naphthalenivorans strain CJ2 and
Polaromonas sp. strain JS666, respectively.

22

In conclusion, several lines of evidence indicated a Polaromonas species was responsible for
toluene removal in mixed culture samples. Firstly, SIP illustrated that a 313 bp TRFLP fragment
was more dominant in heavy fractions obtained from labeled microcosms compared to the heavy
fractions of the unlabeled controls. This pattern suggests the microorganism represented by
fragment 313 bp was responsible for

13

C uptake from toluene. The identity of this organism was

determined by 16S rRNA gene sequencing as well as TRFLP with additional enzymes on heavy
fractions. Additionally, qPCR targeted to the identified Polaromonas species indicated an
increase in DNA BD over the gradient fractions between the labeled and unlabeled samples,
further confirming label uptake occurred. A second line of evidence indicating the Polaromonas
strain was responsible for growth on toluene in mixed culture was provided by qPCR, which
illustrated an increase in cell numbers only when toluene was present. In addition, samples
highly enriched with Polaromonas cells rapidly depleted benzene. These results contribute to the
growing body of knowledge on the abilities of Polaromonas species to degrade and grow on key
environmental organic pollutants and thus indicate these may be key species for use in situ
contaminant removal. Further, we provided evidence that this particulate Polaromonas strain can
thrive in mixed culture suggesting they will likely compete well at a contaminated site.

23

Tables and figures
Table 2.1. Average percent toluene remaining in control and sample microcosms (error bars

represent standard deviations represent from triplicates).
-1

Soil 1

Soil 2

Time
(days)
0
4
5
7
0
4
5
7

Toluene concentration (mg L )
Unlabeled toluene Labeled toluene (13C)
12
( C) samples
samples
Sterile controls
37.2 ± 1.9
38.0 ± 0.5
34.7 ± 4.8
33.5 ± 2.4
23.8 ± 7.7
25.6 ± 7.6
29.4 ± 3.3
9.0 ± 4.6
6.5 ± 7.1
29.3 ± 0.5
0.1 ± 0.2
0.3 ± 0.2
31.3 ± 1.9
28.3 ± 0.8
28.3 ± 0.8
25.6 ± 1.6

34.2 ±2.7
22.6 ± 4.3
10.8 ± 3.4
0.1 ± 0.1

24

30.2 ± 4.1
17.2 ± 4.8
9.0 ± 3.6
0.1 ± 0.1

Table 2.2. Comparison of dominant fragments in heavy fraction TRFLP to clone restriction

enzyme cut sites predicted from sequence analyses.
Restriction enzyme
Hha I
Bsp 1286 I
BsrB I
Mse II

TRFLP
204
119
214
535

25

Clones
203
117
212
534

From

13

C

From

toluene amended
313 bp

50 100 150 200 250 300 350 400 450

12

50 100 150 200 250 300 350 400 450 500

1.751 g/mL

1.753 g/mL

1.749 g/mL

1.748 g/mL

1.747 g/mL

1.745 g/mL

1.744 g/mL

1.740 g/mL

1.739 g/mL

Fluorescence intensity

C toluene amended
313 bp

1.736 g/mL
Fragment length (bp)
-1

Figure 2.1. Comparison of TRFLP electropherograms of heavier fractions (>1.736 g mL )
between DNA obtained from labeled and unlabeled toluene amended microcosms, illustrating the
dominance of TFRLP fragment 313 bp in fractions from the labeled toluene amended
microcosms. A similar pattern was observed in the soil 1 replicate and in replicates of soil 2.

26

Polaromonas rRNA gene abundance (normalized)

1.2
1
0.8
0.6
0.4
0.2
0
1.7

1.72

1.74

1.76

1.78

DNA Buoyant Density (g/mL)

Figure 2.2. Difference between abundance of Polaromonas sp. rRNA gene copies in
13
ultracentrifugation fractions from labeled ( C toluene) and unlabeled toluene amended
microcosms from soil 2 as determined via qPCR. Fractions obtained from soil 1 illustrated a
similar trend.

27

3
2.5
2

120
100
80
60

1.5
40

1

Toluene removal rate (%)

16S rRNA gene copies per ul template
per gram soil

Gene copies (rep.1)
Gene copies (rep.2)
Control (rep.1)
Control (rep.2)
Toluene removed (rep.1)
Toluene removed (rep.2)

3.5

20

0.5

0

0
0

2

4

6

8

Time (days)

Figure 2.3. Correlation between Polaromonas sp. 16S rRNA gene copies (determined by qPCR)
and toluene removal over time in live samples and no-toluene controls (microcosms constructed
from soil 2).

28

Benzene, m-xulene or cDCE
concentration (mg/L)

60

40

Benzene (sample)
cDCE (sample)
m-xylene (sample)
m-xylene (sample)

20

Benzene (control)
cDCE (control)
m-xylene (control)
m-xylene (control)

0
0

10

20

30
Time (days)

40

50

60

Figure 2.4. Benzene, m-xylene and cis-dichloroethene (cDCE) concentrations over time in
supernatant of microcosms samples and in autoclaved controls (error bars represent standard
deviations).

29

REFERENCES

30

References

1.

Clement, B. G., L. E. Kehl, K. L. DeBord, and C. L. Kitts. 1998. Terminal restriction
fragment patterns (TRFPs), a rapid, PCR-based method for the comparison of complex
bacterial communities. Journal of Microbiological Methods 31:135-142.

2.

Coleman, N. V., T. E. Mattes, J. M. Gossett, and J. C. Spain. 2002. Biodegradation of
cis-dichloroethene as the sole carbon source by a beta-proteobacterium. Applied and
Environmental Microbiology 68:2726-2730.

3.

Cupples, A. M., E. A. Shaffer, J. C. Chee-Sanford, and G. K. Sims. 2007. DNA
buoyant density shifts during N-15-DNA stable isotope probing. Microbiological
Research 162:328-334.

4.

Cupples, A. M., and G. K. Sims. 2007. Identification of in situ
2,4-dichlorophenoxyacetic acid-degrading soil microorganisms using DNA-stable isotope
probing. Soil Biology & Biochemistry 39:232-238.

5.

Cupples, A. M., S. Xie, C. Luo, and W. Sun. 2009. Novel toluene, m-xylene and
benzene degraders at contaminated and uncontaminated sites identified by SIP. 109th
General Meeting, American Society for Microbiology, Philadelphia, PA.

6.

Irgens, R. L., J. J. Gosink, and J. T. Staley. 1996. Polaromonas vacuolata gen nov, sp
nov, a psychrophilic, marine, gas vacuolate bacterium from Antarctica. International
Journal of Systematic Bacteriology 46:822-826.

7.

Jeon, C. O., W. Park, W. C. Ghiorse, and E. L. Madsen. 2004. Polaromonas
naphthalenivorans
sp
nov.,
a
naphthalene-degrading
bacterium
from
naphthalene-contaminated sediment. International Journal of Systematic and
Evolutionary Microbiology 54:93-97.

8.

Jeon, C. O., W. Park, P. Padmanabhan, C. DeRito, J. R. Snape, and E. L. Madsen.
2003. Discovery of a bacterium, with distinctive dioxygenase, that is responsible for in
situ biodegradation in contaminated sediment. Proceedings of the National Academy of
Sciences of the United States of America 100:13591-13596.

9.

Kampfer, P., H. J. Busse, and E. Falsen. 2006. Polaromonas aquatica sp nov., isolated
from tap water. International Journal of Systematic and Evolutionary Microbiology
56:605-608.

10.

Luo, C., S. Xie, W. Sun, X. Li, and A. M. Cupples. 2009. Identification of a novel
toluene-degrading bacterium from the candidate phylum TM7 determined by DNA stable
isotope probing. Applied and Environmental Microbiology In press.

11.

Mattes, T. E., A. K. Alexander, P. M. Richardson, A. C. Munk, C. S. Han, P. Stothard,
and N. V. Coleman. 2008. The genome of Polaromonas sp. strain JS666: Insights into

31

the evolution of a hydrocarbon- and xenobiotic-degrading bacterium, and features of
relevance to biotechnology. Applied and Environmental Microbiology 74:6405-6416.
12.

Mu, D. Y., and K. M. Scow. 1994. Effect of trichloroethylene (TCE) and toluene
concentrations on TCE and toluene biodegradation and the population density of TCE
and toluene degraders in soil. Applied and Environmental Microbiology 60:2661-2665.

13.

Osborn, A. M., E. R. B. Moore, and K. N. Timmis. 2000. An evaluation of
terminal-restriction fragment length polymorphism (T-RFLP) analysis for the study of
microbial community structure and dynamics. Environmental Microbiology 2:39-50.

14.

Parales, R. E., J. V. Parales, D. A. Pelletier, and J. L. Ditty. 2008. Diversity of
microbial toluene degradation pathways. Advances in Applied Microbiology, Vol 64
64:1-+.

15.

Radajewski, S., P. Ineson, N. R. Parekh, and J. C. Murrell. 2000. Stable-isotope
probing as a tool in microbial ecology. Nature 403:646-649.

16.

Ritalahti, K. M., B. K. Amos, Y. Sung, Q. Z. Wu, S. S. Koenigsberg, and F. E. Loffler.
2006. Quantitative PCR targeting 16S rRNA and reductive dehalogenase genes
simultaneously monitors multiple Dehalococcoides strains. Applied and Environmental
Microbiology 72:2765-2774.

17.

Sizova, M., and N. Panikov. 2007. Polaromonas hydrogenivorans sp nov., a
psychrotolerant hydrogen-oxidizing bacterium from Alaskan soil. International Journal of
Systematic and Evolutionary Microbiology 57:616-619.

32

CHAPTER 3
DIVERSITY OF TOLUENE DEGRADING MICROORGANIMS AND THE BSSA GENE
IN FIVE NITRATE OR SULFATE AMENDED MICROBIAL COMMUNITIES
INVESTIGATED USING STABLE ISOTOPE PROBING (SIP)

Introduction

Among the petroleum-related environmental contaminants, benzene, toluene, ethylbenzene and
xylene (BTEX) are of particular concern because of their toxicity and easy migration in
groundwater. Aerobic degradation of these chemicals is generally rapid (37, 53, 59, 60), however,
because anaerobic conditions typically exist at contaminated sites, understanding anaerobic
biodegradation is more relevant to site cleanup. Unfortunately, the fate of BTEX under anaerobic
conditions is still difficult to predict because removal is slow (or non-existent), and therefore
difficult to study, and the microorganisms responsible are still being identified. In addition, many
factors, such as electron acceptor availability, substrate competition between potential indigenous
biodegraders and co-contamination (e.g. ethanol), can affect anaerobic BTEX degradation. More
knowledge on the diversity of degrading species in complex samples and the effect of electron
acceptor availability on these species has the potential to enhance our understanding of the
variability associated with anaerobic degradation.

From the BTEX contaminants, toluene degradation has been of great interest to many, with
information available on pure and mixed cultures (based on the 16S rRNA gene) as well as the
functional genes and enzymes involved. Toluene degradation has been observed over a range of
electron accepting conditions with nitrate and sulfate being two important electron acceptors for

33

toluene degradation. Nitrate reduction may be an important mechanism for aromatic
biodegradation because agricultural activity may result in high groundwater nitrate
concentrations. In addition, relatively high levels of sulfate may occur naturally in some
groundwater systems or may be added to enhance anaerobic degradation. A number of key
toluene denitrifiers have been identified, affiliating within the genera of Azoarcus, Aromatoleum,
Magnetospirillum Pseudomonas, Dechloromonas and Thaurea (5, 15, 23, 45, 48, 49, 54, 62).

Similarly, microorganisms have also been linked to toluene degradation under sulfate reducing
conditions, including, for example, microorganisms in the genera Desulfobacula (10),
Desulfocapsa (39, 58), Desulfotomaculum (40), Desulfotignum (42), Desulfovibrio (3) and
Desulfosporosinus (31, 57) (34).

Although numerous organisms have been linked to anaerobic toluene degradation in pure or
mixed cultures, it is challenging to determine if these organisms are actually responsible for
toluene degradation in complex samples. To address this, molecular methods have been
developed to link function with identity in complex samples enabling a greater understanding of
microbial communities involved in contaminant removal or other biological processes. A key
molecular method for this has been stable isotope probing (SIP). This method has been used only
recently to study anaerobic toluene degradation. To date, SIP has been applied in three different
studies under sulfate reducing conditions. In 2010, SIP was used to identify the active toluene
degraders in aquifer sediment from a former gasworks site in Germany (12, 41, 57), and also in a
sulfate reducing consortium developed from a BTEX contaminated aquifer also in Germany (12,
41, 57). In 2011, SIP was also applied to contaminated sediment samples from Germany to
identify active toluene degrading species (44).

34

In the current study, we expand on this knowledge by applying SIP to samples from a wider
range of sources, including uncontaminated sites. SIP was applied over two electron accepting
conditions (nitrate or sulfate amended) and time-series SIP (DNA extraction over time) was used
to enable label cross-feeding between species to be investigated. SIP was applied to the
ribosomal gene as well as the functional gene (bssA encoding for benzylsuccinate synthase)
previously correlated to anaerobic toluene degradation. Benzylsuccinate synthase has been
recognized as a key enzyme for anaerobic toluene biodegradation under nitrate reducing (2, 29),
sulfate reducing (56-58), ferric iron reducing (13, 25), and methanogenic enrichment cultures or
environmental samples (55, 56).

Here, the overall aim was to determine the diversity of active anaerobic toluene degraders and
bssA genes across different habitats, both contaminated and uncontaminated samples, and

compare these results to the current knowledge on pure cultures as well as previous SIP studies
involving only contaminated site samples. This work represents the first study to use SIP to
examine the diversity of active anaerobic toluene degraders across diverse sample sources.

Materials and Methods
Development of Toluene Degrading Microcosms

A wide range of inocula sources were investigated for toluene degrading potential. These sources
included agricultural soils (MI), subsurface soil from BTEX-contaminated sites (MI), sediments
from a former gas-compressor site (24) (OK), digester sludges from wastewater treatment plants

35

(MI) and anaerobic granular sludge (WA). Triplicates of ~10g (wet weight) were incubated in
sterile 160 mL serum bottles containing 50 mL anaerobic basal media (61), sealed with rubber
stoppers and aluminum seals. Microcosms were prepared under strictly anaerobic conditions in
an anaerobic chamber (Coy Laboratory Products INC, Grass Lake, MI). Potassium nitrate and
magnesium sulfate were amended as electron acceptors. From approximately 38 incubations,
only two nitrate-amended and three sulfate-amended microcosms exhibited toluene degradation
and these were selected for the SIP experiments. The two active nitrate-amended microcosms
were seeded from an agricultural soil (hereafter AgN) and anaerobic granular sludge from an
UASB reactor in Washington (hereafter GSN). The three sulfate-amended toluene-degrading
microcosms were inoculated from the same agricultural soil (hereafter AgS), contaminated
sediments from a previous BTEX contaminated aquifer (hereafter CSS) (24) and digester sludge
from a wastewater treatment plant in St. Clair, Michigan (hereafter DSS). For each microcosm, 3
g biomass (wet weight: enrichment cultures obtained in screening stage were inoculated for AgN,
AgS and CSS; freshly sampled sludges were seeded for GSN and DSS) were anoxically
incubated in 60 mL serum bottles containing 25 mL of anaerobic basal media as described above.
-1

-

Potassium nitrate and magnesium sulfate were added to a final concentration of 1 g L NO3 and
2-

SO4

. Each treatment involved triplicate abiotic controls, triplicate unlabeled toluene (1 μL,

99 %, Chem Service, West Chester, PA) and three triplicate labeled toluene (1 μL ring

-13

C6

toluene, 99%, Cambridge Isotope Laboratories, Inc. Andover, MA) amended samples. These
microcosms were incubated at room temperature (~20 °C) with reciprocal shaking.

36

Analytical Techniques

Toluene concentrations in headspace gas samples (200 μL) were typically determined weekly
with a gas chromatograph (Perkin Elmer) equipped with flame ionization detector and a capillary
column (J&W Scientific, DB-624, diameter 0.53mm). Injector and detector temperature were set
at 200 oC and the column temperature was 120oC.

DNA Extraction and Ultracentrifugation

Microcosms were sacrificed for DNA extraction at various time points during toluene depletion
for AgN, GSN, AgS and DSS to further understand the flow of carbon through these microbial
communities. For CSS, an early time stage (50% toluene removal) was investigated due to limited
availability of active microcosms. The powersoil DNA extraction kit (MO BIO Laboratories, Inc.
Carlsbad, CA) was used for total nucleic acids extraction from entire microcosms in each
treatment according to the manufacturer’s recommended procedure. Quantified DNA extracts
(~10 μg) were loaded into Quick-Seal polyallomer tubes (13×51 mm, 5.1 ml, Beckman Coulter)
along with a Tris-EDTA (TE, pH 8.0) /CsCl solution. Prior to sealing (cordless quick-seal tube
topper, Beckman), the buoyant density (BD) was determined with a model AR200 digital
refractometer (Leica Microsystems Inc) and adjusted by adding small volumes of CsCl solution or
-1

Tris-EDTA buffer with a final BD of 1.7300 mgL . The tubes were centrifuged at 178,000 g (20
ºC) for 48 h in a Stepsaver 70 V6 Vertical Titanium Rotor (8 x 5.1 ml capacity) within a Sorvall
WX 80 Ultra Series Centrifuge (Thermo Scientific). Following centrifugation, the tubes was
placed onto a fraction recovery system (Beckman) and fractions (150 l) were collected. The BD
of each fraction was measured, and CsCl was removed by glycogen-assisted ethanol precipitation.

37

PCR and TRFLP

The density-resolved fractions from

12

C and

13

C microcosms for each treatment were

PCR-amplified using 27F-FAM (5’-AGAGTTTGATCMTGGCTCAG, 5’ end-labeled with
carboxyfluorescine) and 1492R (5’-GGTTACCTTGTTACGACTT) (Operon Biotechnologies) as
previously described (16). The presence of PCR products was confirmed by 1.5% agarose gel
electrophoresis and the subsequent staining of the gels with ethidium bromide. PCR products
were purified with QIAquick PCR purification kit (Qiagen Inc.), following the manufacturer’s
instructions and approximately 150 ng was digested with HaeIII (New England Biolabs) with a
6-hour incubation period. Additional digests (HhaI, MseI, Bsp1286I, BsrBI etc.) for TRFLP
analyses in a number of heavy labeled fractions were included to correlate the TRFLP fragment
lengths to the in silico cut sites of the cloned 16S rRNA gene sequences. DNA fragments were
separated by capillary electrophoresis (ABI Prism 3100 Genetic Analyzer, Applied Biosystems) at
the Research Technology Support Facility (RTSF) at Michigan State University. Data were
analyzed with GeneScan software (Applied Biosystems) and the percent abundance of each
fragment was determined.

Presence of bssA in Microcosms and Enumeration in SIP Fractions

The presence of the benzylsuccinate synthase alpha-subunit gene (bssA) was investigated using
different primers pairs (Table 3.1) on DNA extracted from each of the five treatments. A gradient
PCR was performed with annealing temperature ranging from 45ºC to 58 ºC. Positive bssA
amplicons were selected for cloning and sequencing (see below). Four treatments illustrated the
38

presence of partial bssA genes (AgN, GSN, DSS and CSS). For three of these (except CSS due to
lack of sample), quantitative PCR (qPCR) was used to enumerate bssA gene copy numbers in
gradient fractions. The assay was conducted in a Chromo 4 real-time PCR cycler (Bio-Rad) using
the primer set 7772f/8546r for AgN and GSN, and SRBf/SRBr for DSS. Both 12C and 13C nucleic
acid samples from density gradient fractions were subject to quantification. Each 20 μL PCR
reaction mixture containing 10 μL SYBR green real-time PCR solution (Applied Biosystems),
0.25 μM of each primer, and 1 μL DNA template. The thermal protocol consisted of an initial
denaturation (95 ºC, 15 min), 40 cycles of amplification (95 ºC, 15 s; 55 ºC, 20 s; 72 ºC 20 s) and
a terminal extension step (72 ºC, 2 min). Melting curves were constructed from 55 ºC to 95 ºC,
read every 0.6ºC for 2 s. For each gradient fraction, 1 μL solution was diluted with 3 μL water as
template (to conserve the sample). Cloned plasmid DNA was utilized as a standard for
quantification and gene copies were determined as shown below (plasmid size was 4730 bp,
including 774 bp(7772f/8546r amplicons) and 97 bp(SRBf/SRBr amplicons) of insert).
  1 mol bp DNA   6.023  10 23 bp 

ng  
1g




gene copies   DNA concentration,

 

3 ng   660g DNA  
L  1,000
mol bp

 

 



1 copy

 plasmid size [bp]   volume, L 




Sequencing of Partial bssA and 16S rRNA Genes

Clone libraries of the 16S rRNA genes were constructed for each treatment using DNA extracted
following toluene depletion. The DNA was amplified with 27F/1492R as above except the
forward primer was unlabeled and the final extension time was extended to 15 minutes. To
reduce sequencing redundancy, restriction fragment length polymorphism (RFLP) analyses was
performed and specific operational taxonomic units (OTU) were selected for sequencing. In
39

addition to 16S rRNA sequencing, amplicons generated with bssA primer pairs were also
prepared for cloning and sequencing. The PCR products were purified with QIAquick PCR
purification kit (Qiagen Inc.) and cloned into Escherichia coli TOP10 vector supplied with a
TOPO TA cloning kit (Invitrogen Corporation). E. coli clones were grown on Luria-Bertani (LB)
-1

medium solidified with 15 g agar L

-1

with 50 g ampicillin L for 16 h at 37 ºC. Colonies with

inserts were verified by PCR with primers M13 F (5’-TGTAAAACGACGGCCAGT-3’) and
M13 R (5’-AACAGCTATGACCATG-3’), plasmids were extracted from the positive clones with
a QIAprep miniprep system (Qiagen, Inc.) and the insertions were sequenced at RTSF. The
Ribosomal Database Project (RDP) (Center for Microbial Ecology, Michigan State University)
analysis tool “classifier” was utilized to assign taxonomic identity. Phylogenetic trees for the
partial bssA sequences along with the closest matches in Genbank were obtained by the
neighbor-joining method using MEGA 4.1 software.

Results
Frequency of Toluene Degradation

Toluene degradation using various inocula sources, including agricultural soil, digester sludge,
anaerobic granular sludge and contaminated soils and sediments, was examined under nitrate and
sulfate amended conditions. Toluene biodegradation was observed in 2 from 18 and in 3 from 20
experiments set-ups, involving nitrate amendment and sulfate amendments, respectively. Active
toluene microcosms were also tested for their benzene biodegradation, however, no
biodegradation was found in any consortia. SIP was performed on the two nitrate amended (an
agricultural soil and granular sludge) and on the three sulfate amended microcosms (an

40

agricultural soil, digester sludge and contaminated site soil). At various time points, DNA was
extracted from the labeled and unlabeled toluene-amended microcosms, and was subject to
ultracentrifugation, fractionation and TRFLP (on each fraction). The organisms responsible for
13

C assimilation were identified by the comparison of relative abundances of specific T-RFs

between the control (unlabeled toluene amended) and the sample (labeled toluene amended) at
selective time points for each fraction. The identities of each enriched T-RFs for each microcosm
type were then determined using additional restriction enzyme digests and by comparison to
predicted cut sites in each 16S rRNA gene clone library, as described below.

SIP on Agricultural Soil Nitrate Amended Microcosms (AgN)

In AgN, a 214 bp HaeIII T-RF fragment became the only dominant T-RF fragment (>80%) among
-1

labeled ‘heavy’ fractions (banding between 1.7523 to 1.7448 g ml ) in all three sampling points
(33%, 75% and 100% toluene removal) (Figure 3.1 a). To identify the toluene-degrading bacteria
based on the TRFLP results and to assign phylogenetic affiliation to distinct T-RFs, the16S rRNA
clone library (Table 3.2) derived from total DNA was inspected. Three different
Burkholderiales-related microorganisms classifying within the families Alcaligenaceae,
Comamonadaceae and Oxalobacteraceae all exhibited a predicted HaeIII T-RF close to 214 bp.

Specifically, from the analysis of the clone sequences, each had a predicted Hae III cut site of 219
bp (Table 3.2). Multiple digestions were then applied to determine which of these three sequences
were actually responsible for the 214 bp HaeIII T-RF in the heavy fractions. From these digests
(Table 3.3), the phylotype within the family Comamonadaceae were found to be directly
correlated with carbon uptake from toluene and hence toluene degradation. Interestingly, the AgN

41

clone library (Table 3.2) contained a partial sequence related to the genus Azoarcus, which has
previously been linked to toluene degradation under nitrate amended conditions (2, 8, 23, 63).
However, no enrichment of the appropriate Azoarcus T-RF (77 bp) was noted in the heavy labeled
fractions (Figure 3.1 b), indicated these organisms were likely not the major toluene degraders.

SIP on the Granular Sludge Nitrate Amended Microcosms (GSN)

Compared to AgN, the nitrate amended microcosms inoculated from anaerobic granular sludge
exhibited a more diverse microbial community (Table 3.2). TRFLP revealed significant

13

C

uptake for three T-RF (Figure 3.2), a fragment sized 72 bp dominated in labeled heavy fractions
-1

(BD> 1.7448 g ml ). Additional enzyme digestions (Table 3.4) in combination with the 16S
rRNA clone library (Table 3.2) were utilized to further distinguish this Hae III T-RF. The putative
toluene degrader classified within the genus Thauera (72 bp). Thauera-related phylotypes were
strongly enriched in the heavy fractions in all three time points with relative abundances > 70% at
first two sampling points and >34% at the last time point. The peak of relative abundance
decreased over time, suggesting the

13

C-label assimilation by other microorganisms may have

diluted the fraction of Thauera-related phylotypes in heavy fractions.
Thauera-related bssA genes and the enrichment of these genes in

The presence of

13

C heavy fractions (see below)

as quantified by qPCR strengthens the hypothesis that the Thauera phylotype was responsible for
toluene degradation in this complex microbial community.

42

SIP on the Agricultural Soil Sulfate Amended Microcosms (AgS)

In the sulfate amended agricultural soil microcosms (AgS), the majority (22 from 29 clones) of
the microbial community classified within the class Clostridia (Table 3.5). Slight label
assimilation was noted in two T-RFs in the DNA extracted from microcosms which consumed
~33% toluene, however, in the later two DNA extraction points, (~75% and ~100% toluene
removal) label assimilation was more pronounced (Figure 3.3 a & b). Two TRFLP fragments, 77
bp and 213 bp, were enriched in the heavy

13

C-fractions during the course of biodegradation and

no PCR products were found in the corresponding heavy

12

C-fractions. It is likely that both

phylotypes were responsible for carbon uptake from toluene over the course of the incubations.
The 16S rRNA clone library data (Table 3.5) in combination with additional restriction digests
(Table 3.6) indicated that the two TRFLP fragments both affiliated with genus Desulfosporosinus
(>98% sequence identity).

SIP on the Digester Sludge Sulfate Amended Microcosms (DSS)

In DSS, a significant proportion (20 from 59 clones) of the microbial community classified
within the class Deltaproteobacteria (Table 3.5). The most abundant TRFLP fragment in
C-heavy fractions was a 204 bp T-RF. This fragment was highly enriched in heavy fractions at

13

the three extraction times and the effect was most obvious for the last two time points (~75 %
and ~100 % toluene depleted) (Figure 3.4). The maximum relative abundances of the 204 bp
-1

-1

fragment was 27 % (at BD of 1.7360 g ml ), 43 % (at BD of 1.7480 g ml ) and 50 % (at BD of
-1

1.7502 g ml ) for the three extraction points, indicating an increase in label uptake with time. In

43

contrast, the relative abundance of this fragment was less than 5 % in each unlabeled control
gradient fraction (Figure 3.4). The BD values of these “heavy” peaks are very close to that of
fully

13

-1

C labeled M. extorquens (1.757 g ml )(36), indicating a high degree of label assimilation.

The bacterial clone library generated (Table 3.5) indicated the 204 bp T-RF was assigned with
family Syntrophobacteraceae. As described above, additional digestion on the heavy fractions
were performed to confirm this correlation between 204 bp T-RF and the associated 16S rRNA
sequence (Table 3.7).

SIP on Gas Compressor Site Soil Sulfate Amended Microcosms (CSS)

The third sulfate amended sample involved microcosms inoculated with sediment from a former
gas compressor site (24). Previous research indicated sulfate was the major terminal electron
acceptor at this site. The clone library for this treatment indicated the dominance (91 from 106
clones) of microorganisms classifying within the Deltaproteobacteria (orders Desulfobacterales
and Desulfuromonadales). Unfortunately, because of sample limitations, SIP was performed only
on an early toluene-degrading stage (~50% toluene removal). A 202 bp T-RF was enriched in the
-1

heavy 13C- fractions (relative abundance as ~70% with a BD of 1.7469 g ml ). The clone library
for this microbial community (Table 3.5) illustrated a dominance of Desulfobulbaceae-affiliated
organisms (80 from 106 clones) which correlated with the 203 bp T-RF. Multiple enzyme
digestions (Table 3.8) confirmed that the Desulfobulbaceae-affiliated 16S rRNA gene sequence
was responsible for the enriched Hae III 203 bp T-RF. These data indicate the Desulfobulbaceae
affiliated microorganisms were responsible for toluene degradation.

44

Partial Sequencing of the bssA Gene

A number of primers successfully amplified partial bssA genes from four of the five treatments
(Table 3.9). Amplicons from AgN, GSN, DSS and CSS were selected for sequencing and
phylogenetic trees were generated for each enrichment culture along with their closest matches
in Genbank (Figure 3.6-3.9). Primer set 7772f/8546r, produced expected-size PCR products
(~774 bp) within the two nitrate amended consortia (Figures 3.6 & 3.7). A total of 32 clones
from agricultural soil and granular sludge nitrate amended enrichment cultures were digested and
representative clones (as indicated by restriction digests) were selected for sequencing. All 64
clones showed the same OTU indicating sequence similarity, belonging to Thauera-related bssA
genes (Figures 3.6 & 3.7). Primer pairs SRBf/SRBr displayed good coverage for the sulfate
amended enrichment cultures (Table 3.9). Representative OTUs from the DSS and CSS were
sequenced and three amplicons of each sample showed ~92% (90 bp out of 97 bp) similarity to
partial sulfate-reducing bacterium PRTOL1 bssA gene (EU780921.1), which was congruent with
the template sequences of the primer set. In addition, for CSS, longer partial bssA genes were
obtained using primer pair 7772f/8828r and the sequences obtained were found to branch into
two distinct lineages (Figure 3.9). Of these, 19 were closely related to bssA gene of strain TRM1
(99% sequence similarity)(58). Two clones were affiliated with uncultured bacterium clone
Zz-ox_12 bssA gene, showing only 73% sequence similarity with the sulfate-reducing bacterium
TRM1 bssA gene (22). Three clones could not be classified with any known bssA sequences.
Unfortunately, unspecific PCR products or no PCR products were produced from the sulfate
amended agricultural soil (AgS) from the primers tested (Table 3.1).

45

Quantification of bssA Genes in SIP Fractions

To further confirm anaerobic toluene degradation in the nitrate and sulfate amended samples, the
bssA genes were quantified from

12

C and

13

C gradient fractions at the last time point using

primer sets 7772f/8546r and SRBf/SRBr. Quantitative PCR analysis of gradient fractions
detected separation of bssA genes in labeled and unlabeled samples (Figure 3.10, a-c). In GSN,
13

quantitative label assimilation was very evident in the

C-fractions where bulk bssA gene

-1,

moved to a heavier fraction with a BD of 1.7513 g mL
-1

compared to that of the

12

C-fractions

13

(1.7208 g mL ) (Figure 3.10 a). In AgN, highly

C-labeled bssA genes was present at a BD of

-1

1.7415 g mL , while such ‘heavy’ bssA genes were not found in the

12

C-fractions but the peak

-1

occurred at a lighter fraction with a BD of 1.7099 g mL . Also a tail of bssA gene formed in
13

-1

C-lighter fractions with a BD of 1.7046 g mL

and

(Figure 3.10 b). In DSS, a separation of

12

C

13

C peak was also seen (Figure 3.10 c). Quantitative PCR was not performed on the AgS

fractions (no bssA primers were suitable for these microcosms) or the CSS fractions (limitation
on sample available).
Discussion

Previous SIP studies on BTEX biodegradation have focused primarily on samples or biomass
from former contaminated sites (20, 30, 57). To expand on this work and to discover novel
toluene-degrading bacteria, the current study applied SIP to a wide range of inocula sources
including agricultural soil, contaminated aquifer sediment and anaerobic granular and digester
sludge. Noteably, the selection of inocula sources covers both uncontaminated and contaminated
46

sources, as well as natural and engineered microbial communities. These experiments involved
the characterization of five toluene-degrading microbial consortia (through 16S rRNA clone
libraries) and the identification of the active toluene degraders in each sample using time series
DNA based SIP. For some of these samples, bssA gene sequences were also obtained and label
uptake into the bssA gene was also documented.

Toluene biodegradation under nitrate reducing conditions has been studied extensively (4, 11, 14,
46). To the authors’ knowledge, no detailed SIP study has not been conducted on nitrate-reducing,
toluene-degrading mixed consortia. For the current study, a natural microbiota (agricultural soil)
and an engineered microbial community (granular sludge) were investigated. These communities
were targeted, in part, because it was likely that both had high levels of denitrifying
microorganisms.

In the nitrate amended agricultural soil (AgN), microorganisms classifying within family
Comamonadaceae were found to be responsible for toluene biodegradation. Although
Comamonadaceae-related bacteria are often characterized as aerobic bacteria, others have

reported

members

of

the

Comamonadaceae

as

denitrifying

bacteria

(17,

26).

Comamonadaceae-related microorganisms have been correlated with cyclohexanol (38) and

poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) (26) biodegradation under nitrate
reducing conditions. Depletion of nitrate was not measured in the current study, however, the
following lines of evidence suggest the Comamonadaceae-related bacteria were degradating
toluene under nitrate reducing conditions: 1) strict anaerobic methods were followed, 2) partial
bssA genes were obtained from the micrososms and 3) the bssA genes were enriched in the heavy

47

fractions (qPCR data, Figure 10) indicating the Comamonadaceae-related bacteria (also enriched
in the heavy fractions) were anaerobic (benzylsuccinate synthase is irreversibly inactivated in the
presence of molecular oxygen (28)). These results are novel because the most commonly
reported

nitrate-reducing,

toluene-degrading

species (genera

Azoarcus,

Thauera

and

Dechloromonas) classify within another Betaproteobacteria family, the Rhodocyclaceae.

The AgN clone library (Table 3.2) also contained a 77 bp fragment belonging to genus Azoarcus,
a common toluene degrader under nitrate reducing conditions (2, 8, 23, 63), however, no
enrichment of this T-RF was noted in the heavy fractions, indicating these organisms were not
responsible for

13

C-substrate assimilation. The enrichment of bssA and Comamonadaceae 16S

rRNA genes in the heavy

13

C–fractions along with the presence of Azoarcus sp. in the clone

library could indicate the Comamonadaceae-related biodegraders may have obtained the
Azoarcus bssA gene by horizontal gene transfer. Horizontal gene transfer of such catabolic genes

has been suggested or found previously (13, 48, 56, 58). These finding illustrates the importance
of culture independent approaches, compared to culture dependent approaches, for understanding
functions in mixed cultures.

In the nitrate amended, granular sludge treatments (GSN), a 72 bp T-RF associated with genus
Thauera was enriched in all three time points. This is a reasonable conclusion because Thauera

spp. have been reported by others to be an important toluene-degrading species under nitrate
reducing conditions (6, 11, 32, 50). The toluene metabolic pathway in Thauera is known to be
initiated by the formation of benzylsuccinate from toluene and fumarate(10). Sequencing of the

48

partial bssA genes revealed that all 32 clones were closely related with Thauera spp. bssA gene.
The presence of Thauera-related bssA genes and the enrichment of these genes in

13

C heavy

fractions as quantified by qPCR strengthen the hypothesis that the Thauera phylotype was
responsible for toluene degradation in this complex microbial community.

In the sulfate amended agricultural soil (AgS), two T-RFs (77 bp and 213 bp), both belonging to
the genus Desulfosporosinus exhibited strong label assimilation at the last two sampling points
(Figures 3.3 a & b). The genus Desulfosporosinus has previously been linked to toluene
degradation (31, 47). It was also identified as being able to assimilate

13

C-toluene in a recent SIP

project (57). Since no other T-RFs are significantly enriched in the labeled heavy fractions over
the three time points, it is likely that the Desulfosporosinus spp. were responsible for toluene
degradation in the AgS microcosms.

In the sulfate-amended, digester sludge treatment (DSS), a 204 bp T-RF, representing a
phylotype within the family Syntrophobacteraceae, was the only T-RF dominated in the
13

C-heavy fractions. The label assimilation of this T-RF intensified over time (Figure 3.4). This

effect was most prominent at the last sampling point with more than 50 % relative abundance in
the

13

C-heavy fractions. Notably, a 77-bp T-RF affiliated within the genus Desulfovibrio, was

slightly enriched in the

13

C-heavy fractions (abundance around or less than 10%). The

Desulfovibrio spp. may have been able to scavenge labelled metabolic by-products from the
Syntrophobacteraceae related microorganisms. Members of Syntrophobacteraceae have

previously been identified as sulfate reducing bacteria (18, 35) and can degrade long chain fatty

49

acids (51, 52) and propionate (7) under sulfate-reducing conditions. The closest relatives of the
204 bp T-RF with a validly published name is Syntrophobacter wolinii (19), sharing 91%
sequence similarity. S. wolinii has been reported as a sulfate-reducing bacterium and its closest
relatives are Desulfomonile tiedjei and Desulfoarculus baarsii. The 204 bp T-RF also shared a
more distant similarity (88% 16S rRNA similarity) with sulfate reducing strain PRTOL1, a
toluene

sulfate

reducer

isolated

from

fuel-contaminated

subsurface

soil

(9,

10).

Syntrophobacteraceae were identified in a toluene-degrading sulfate-reducing bacterial

consortium, but in that study, the Desulfobulbaceae were identified as key organisms of toluene
degradation within the consortium (41). In another study, carbon stable isotope analysis in
combination with whole-cell hybridization linked toluene degradation to the Desulfobacter-like
populations, while Synthrophobacter was present in the microbiota but not responsible for
toluene

biodegradation

(43).

The

Syntrophobacteraceae

was

also

observed

in

a

benzene-degrading in situ microcosm but was not linked with benzene biodegradation (21). To
date, to the authors’ knowledge, there has been no direct evidence to correlate members of the
family of Syntrophobacteraceae with anaerobic toluene biodegradation. The presence of bssA
genes similar to sulfate reducing strain PRTOL1-related bssA genes (Figure 3.8) in DNA
extracted from the digester sludge treatment also confirmed the hypothesis that the novel
Syntrophobacteraceae clade played an active role in toluene biodegradation in these sulfate

amended samples.

The third sulfate amended sample involved microcosms inoculated with material originating
from a former gas compressor site (CSS). SIP was only performed at one time point (~50%
toluene removal), however, the 16S rRNA gene and bssA gene clone libraries support the SIP

50

results. Microorganisms classifying within the Desulfobulbaceae family appeared to be
dominant in the

13

C-heavy fractions and in the clone library. Desulfobulbaceae have previously

been classified as BTEX sulfate reducers (1, 27, 30, 33, 41). They were also reported in the
DNA-SIP project described above (57) but were not identified as the primary toluene degrader.
Interestingly, Desulfosporosinus-related microorganisms (identified as primary toluene degraders
in AgS) were present in the CSS clone library (Table 5) but were not enriched in the

13

C-heavy

fractions.

In summary, five distinct phylotypes were identified as the active toluene-degrading bacteria
under either nitrate or sulfate amended conditions for five different microbial communities. For
one microcosm type, syntrophic partners were also identified. For three treatments, the
phylotypes were similar to previously identified toluene degraders (Thauera, Desulfosporosinus
and Desulfobulbaceae related phylotypes), whereas two treatments produced novel toluene
degraders (Comamonadaceae and Syntrophobacteraceae related phylotypes). The discovery of
two novel toluene degraders indicates the importance of culture independent approaches for
identifying the active microorganisms in complex samples. In addition, this study provided
information on the diversity of bssA sequences and the utility of a number of primer pairs for
detecting the bssA gene. Further, the work highlights the value of combining ribosomal and
functional gene based SIP to link function with identity for complex microbial samples and adds
to our understanding of the microbial ecology of toluene degrading communities from various
environments.

51

Acknowledgements

Funding for this work was provided by a grant awarded to A. Cupples from the National Science
Foundation (Grant 0853249). The authors thank Paul Fallgren (Western Research Institute) and
Zhenbo Yue (Michigan State University) for supplying the contaminated soil sample (CSS) and
anaerobic granular sludge (GSN) respectively.

52

Tables and figures
Table 3.1. Primers used in this study to investigate the presence of the bssA gene

Primer

Sequence(5'-3')

Reference

6888f

AATTCATCGTCGGCTACCACG

(Winderl et al. 2007)

7772f

GACATGACCGACGCSATYCT

(Winderl et al. 2007)

8546r

TCGTCGTCRTTGCCCCAYTT

(Winderl et al. 2007)

8828r

AGCAGRTTGSCCTTCTGGTT

(Winderl et al. 2007)

SRBf

(Beller et al. 2008)

SRBr

GTSCCCATGATGCGCAGC
CGACATTGAACTGCACGTGRT
CG

bssApd2f

CCTATGCGACGAGTAAGGTT

(Winderl et al. 2008)

bssApd2r

TGATAGCAACCATGGAATTG

(Winderl et al. 2008)

bssN2f

GGCTATCCGTCGATCAAGAA

(Winderl et al. 2008)

bssN2r

GTTGCTGAGCGTGATTTCAA

(Winderl et al. 2008)

bssAf

ACGACGGYGGCATTTCTC

(Beller et al. 2002)

bssAr

GCATGATSGGYACCGACA

(Beller et al. 2002)

53

(Beller et al. 2008)

Table 3.2. Phylogenetic affiliation of each 16S rRNA clone in nitrate amended toluene degrading microcosms as determined with the
RDP analysis tool “classifier”
Enriched in
Soil/Fragment (Hae III
# of
13
Class
Order
Genus
C heavy
digestion)
clones
fractions
-

Agricultural Soil, NO3
Amended
39 bp
219 bp
77 bp
219 bp
41 bp
219 bp
39 bp
250 bp
250 bp
269 bp
315 bp

No
Yes
No
No
No
No
No
No
No
No
No

20
7
8
5
4
3
1
1
1
1
1

Gammaproteobacteria Pseudomonadales
Betaproteobacteria
Burkholderiales
Betaproteobacteria
Rhodocyclales
Betaproteobacteria
Burkholderiales
Gammaproteobacteria Xanthomonadales
Betaproteobacteria
Burkholderiales
Gammaproteobacteria Xanthomonadales
Sphingobacteria
Sphingobacteriales
Clostridia
Clostridiales
Acidobacteria_Gp3
Betaproteobacteria
Burkholderiales

Pseudomonas
Unclassified
Azoarcus
Unclassified
Dokdonella
Unclassified
Luteimonas
Ferruginibacter
Sedimentibacter
Gp3
Polaromonas

Yes
Yes
Yes
No
No
No
No
No
No
No
No
No

25
14
12
8
8
7
7
5
5
4
4
4

Betaproteobacteria
Rhodocyclales
Deltaproteobacteria Syntrophobacterales
Betaproteobacteria
Burkholderiales
Deltaproteobacteria Syntrophobacterales
Bacteroidia
Bacteroidales
Flavobacteria
Flavobacteriales
Epsilonproteobacteria Campylobacterales
Nitrospira
Nitrospirales
Planctomycetia
Planctomycetales
Bacteroidia
Flavobacteria
Bacteroidia
Bacteroidales
Clostridia
Clostridiales

Thauera
Smithella
Simplicispira
Unclassified

-

Granular Sludge, NO3
Amended
77 bp
77 bp
217 bp
82 bp, 205 bp, 271 bp
260 bp
39 bp
226 bp
180 bp
180 bp, 245 bp
39 bp
260 bp
318 bp

54

Arcobacter
Magnetobacterium
Planctomyces
Unclassified
Unclassified
Fusibacter

Table 3.2 (cont’d)
951 bp
189 bp
191 bp
37 bp
202 bp
318 bp
951bp

No
No
No
No
No
No
No

4
2
2
1
1
1
1

Epsilonproteobacteria Campylobacterales
Synergistia
Synergistales
Flavobacteria
Flavobacteriales
Thermotogae
Thermotogales
Clostridia
Clostridiales
Epsilonproteobacteria Campylobacterales

55

Sulfurospirillum
Unclassified
OP3
Unclassified
Kosmotoga
Fusibacter
Sulfurospirillum

Table 3.3. Comparison of fragment length of dominant T-RF in heavy fractions to predicted
fragment length from in silico sequence analyses (nitrate amended agricultural soil microcosms)
TRFLP (bp)
Sequence Data (bp)
Restriction Enzyme
Comamonadaceae
affiliated sequence

Hae III

214

219

Msp I

485

490

Hha I

205

207

RSA I

424

429

Mse I

534

538

BsrBi

211

216

56

Table 3.4. Comparison of fragment length of dominant T-RFs in heavy fractions to predicted
fragment lengths from in silico sequence analyses (nitrate amended granular sludge
microcosms).
TRFLP (bp)
Sequence Data (bp)
Restriction Enzyme

Simplicispira
affiliated sequence

204

210

470

476

537

541

119

123

Hae III

73

77

Msp I

508

507

89

95

240

244

BSP 1286 I

Enriched fragment 3

82

RSA I

affiliated

77

Hha I

Smithella
sequence

Msp I

BSP 1286 I

Enriched fragment 2

77

Mse I

affiliated

72

RSA I

Thauera
sequence

Hae III

Hha I

Enriched fragment 1

625

623

Hae III

213

217

Msp I

489

488

Hha I

205

205

RSA I

472

471

Mse I

537

536

57

Table 3.5. Phylogenetic affiliation of each 16S rRNA clone in sulfate amended toluene degrading microcosms as determined with
the RDP analysis tool “classifier”
Enriched in
#of
13
Soil/Fragment
Class
Order
Genus
heavy C
clones
fractions
Agricultural Soil,
2SO4 Amended
2
82bp,214 bp
Yes
5
Clostridia
Clostridiales
Desulfosporosinus
252 bp
No
4
Gammaproteobacteria
Pseudomonadales
Acinetobacter
39 bp
No
1
Gammaproteobacteria
Pseudomonadales
Pseudomonas
223 bp
No
1
Bacilli
Bacillales
Paenibacillus
228 bp
No
1
Clostridia
Clostridiales
Gracilibacter
228 bp
No
1
Clostridia
Clostridiales
Gracilibacter
249 bp
No
1
Clostridia
Clostridiales
Sedimentibacter
262 bp
No
1
Sphingobacteria
Sphingobacteriales
Toxothrix
299 bp
No
1
Clostridia
Clostridiales
Proteiniborus
316 bp
No
1
Clostridia
Clostridiales
Centipeda
Digester Sludge,
2SO4 Amended
1
77bp, 209bp
Yes
0
Unclassified
Deltaproteobacteria
Syntrophobacterales
1
Unclassified
77bp, 214bp
No
0
Deltaproteobacteria
Deltaproteobacteria
258bp, 298 bp
No
9
Bacteroidia
Bacteroidales
203bp
No
8
Thermotogae
Thermotogales
Kosmotoga
238bp, 299bp
No
6
Caldisericia
Caldisericales
Caldisericum
220 bp
No
4
Unclassified
Anaerolineae
Anaerolineales
Bacterium Eub 3
914 bp
No
4
OP9
324 bp
No
3
214 bp
No
2
Unclassified
Spirochaetes
Spirochaetales
Unclassified
267 bp
No
2
Clostridia
Clostridiales

58

Table 3.5 (cont’d)
251 bp
Contaminated
2Soil, SO4
Amended

No

1

Planctomycetia

Planctomycetales

Planctomyces

205 bp
209 bp, 275 bp

Yes
No

8
0
6

Deltaproteobacteria
Deltaproteobacteria

Unclassified
Unclassified

206 bp
220 bp
206 bp
318 bp
171 bp
214 bp
220 bp

No
No
No
No
No
No
No

5
5
4
3
1
1
1

Deltaproteobacteria
Actinobacteria
Clostridia
Clostridia
Nitrospira
Clostridia
Clostridia

Desulfobacterales
Desulfobacterales
Desulfuromonadale
s
Unclassified
Clostridiales
Clostridiales
Nitrospirales
Clostridiales
Clostridiales

59

Geobacter
Fusibacter
Magnetobacterium
Desulfosporosinus
Acetivibrio

Table 3.6. Comparison of fragment length of dominant T-RF in heavy fractions to predicted
fragment lengths from in silico sequence analyses (sulfate amended agricultural soil
microcosms).

Restriction Enzyme
Desulfosporosinus affiliated sequence

Desulfosporosinus affiliated sequence

HaeIII
MspI
BsrBI
MseII

Restriction
Enzyme
HaeIII
MspI
BsrBI
MseII

60

TRFLP
(bp)
213
136
52
178

TRFLP
(bp)
77
53
N/A
223

Sequence
Data (bp)
216
140
56
180

Sequence Data
(bp)
82
62
N/A
227

Table 3.7. Comparison of fragment length of dominant T-RF in heavy fractions to predicted
fragment lengths from in silico sequence analyses (digester sludge sulfate amended microcosms).
Restriction
TRFLP
Sequence Data (bp)
Enzyme
(bp)
Syntrophobacteraceae affiliated sequence
204
209
HaeIII
160
168
MspI
626
628
MseII
238
230
RsaI
91
99
HhaI

61

Table 3.8. Comparison of fragment length of dominant T-RF in heavy fractions to predicted
fragment lengths from in silico sequence analyses (sulfate amended contaminated site soil
microcosms).

Restriction Enzyme
Desulfobulbaceae affiliated sequence

HaeIII
MspI
RsaI
HhaI

62

TRFLP (bp) Sequence Data
(bp)
202
158
222
92

205
162
226
93

Table 3.9. Success (+) or failure (-) of primers sets for bssA gene amplification.

Inocula sources
Granular sludge
(nitrate amended)
Agricultural soil
(nitrate amended)
Agricultural soil
(sulfate amended)
Digester sludge
(sulfate amended)
Contaminated soil
(sulfate amended)

Forward bssAf
Reverse bssAr

SRBf
SRBr

BssN2f
BssN2r

7772f
8546r

6888f
8546r

7772f
8828r

-

-

-

+(cloned)

+

+

-

-

-

+(cloned)

+

+

-

-

-

-

-

-

-

+(cloned)

-

-

-

-

-

+(cloned)

-

-

-

+(clone
d)

63

TRFLP Relative Abundance (%

100

80

60

40

20

0
1.69

1.71

1.73

1.75

1.77

DNA Buoyant Density (g/mL)

Figure 3. 1. Percent relative abundance of fragments (digested by Hae III) assigned to
Comamonadaceae within buoyant density gradients of DNA extracted from the nitrate amended
13
agricultural soil microcosms. Figure symbols: ▲ C-toluene (~33% toluene degraded);
13

13

12

♦ C-toluene (~75% toluene degraded); ■ C-toluene (~100% toluene degraded); □ C-toluene
(~100% toluene degraded).

64

TRFLP Relative Abundance (%

100

80

60

40

20

0
1.69

1.71

1.73

1.75

1.77

DNA Buoyant Density (g/mL)

Figure 3.2. Percent relative abundance of fragments (digested by Hae III) assigned to Azoarcus
within buoyant density gradients of DNA extracted from the nitrate amended agricultural soil
13
13
microcosms. Figure symbols: ▲ C-toluene (~33% toluene degraded); ♦ C-toluene (~75%
13

12

toluene degraded); ■ C-toluene (~100% toluene degraded); □ C-toluene (~100% toluene
degraded).

65

TRFLP Relative Abundance (%

100

80

60

40

20

0
1.69

1.71

1.73

1.75

1.77

1.79

DNA Buoyant Density (g/mL)

Figure 3.3. Percent relative abundance of fragments (digested by Hae III) assigned to Thauera,
within buoyant density gradients of DNA extracted from the nitrate amended granular sludge
13
13
microcosms. Figure symbols: ▲ C-toluene (~33% toluene degraded); ♦ C-toluene (~75%
13

12

toluene degraded); ■ C-toluene (~100% toluene degraded); □ C-toluene (~100% toluene
degraded).

66

TRFLP Relative Abundance (%

100

80

60

40

20

0
1.69

1.71

1.73

1.75

1.77

DNA Buoyant Density

Figure 3.4. Percent relative abundance of fragments (digested by Hae III) assigned to
Desulfosporosinus with T-RF 77 bp within buoyant density gradients of DNA extracted from the
13
agricultural soil sulfate amended microcosms. Figure symbols: ▲ C-toluene (~33% toluene
13

13

degraded); ♦ C-toluene (~75% toluene degraded); ■ C-toluene (~100% toluene degraded);
12

□ C-toluene (~100% toluene degraded).

67

TRFLP Relative Abundance (%

100

80

60

40

20

0
1.69

1.71

1.73

1.75

1.77

DNA Buoyant Density (g/mL)

Figure 3.5. Percent relative abundance of fragments (digested by Hae III) assigned to
Desulfosporosinus with T-RF 213 bp within buoyant density gradients of DNA extracted from
13
the agricultural soil sulfate amended microcosms. Figure symbols: ▲ C-toluene (~33% toluene
13

13

degraded); ♦ C-toluene (~75% toluene degraded); ■ C-toluene (~100% toluene degraded);
12

□ C-toluene (~100% toluene degraded).

68

TEFLP Relative Abundance (%

80

60

40

20

0
1.69

1.71

1.73

1.75

1.77

1.79

DNA Buoyant Density (g/mL)

Figure 3.6. Percent relative abundance of fragments (digested by Hae III) assigned to
Syntrophobacteraceae within buoyant density gradients of DNA extracted from the digester
13
sludge sulfate amended microcosms. Figure symbols: ▲ C-toluene (~33% toluene degraded);
13

13

12

♦ C-toluene (~75% toluene degraded); ■ C-toluene (~100% toluene degraded); □ C-toluene
(~100% toluene degraded).

69

TRFLP Relative Abundance (%

80

60

40

20

0
1.69

1.71

1.73

1.75

1.77

DNA Buoyant Density (g/mL)

Figure 3.7. Percent relative abundance of fragments (digested by Hae III) assigned to
Desulfobulbaceae within buoyant density gradients of DNA extracted from the contaminated site,
13
sulfate amended microcosms. Figure symbols: ▲ C-toluene (~33% toluene degraded);
13

13

12

♦ C-toluene (~75% toluene degraded); ■ C-toluene (~100% toluene degraded); □ C-toluene
(~100% toluene degraded).

70

Ag Soil Nitrate Amended Clone 12
Ag Soil Nitrate Reducing Clone 10
Ag Soil Nitrate Amended Clone 11
Ag Soil Nitrate Amended Clone 5
Ag Soil Nitrate Amended Clone 4
Thauera
sp.
DNT-1
Uncultured Clone LA07bs04 (GU133294.1)
Uncultured Clone LA07bs07 (GU133296.1)
Azoarcus sp. DN11 (AB285034.1)
Azoarcus sp. T (AY032676.1)
Uncultured Clone bssAC12 (FJ810633.1)
Uncultured Clone bssAC18 (FJ810639.1)
Uncultured Clone bssAC06 (FJ810627.1)
Uncultured Clone bssAC08 (FJ810629.1)
Uncultured Clone bssAC11 (FJ810632.1)
Uncultured Clone bssAD01 (FJ810643.1)
Uncultured Clone bssAD03 (FJ810645.1)
Uncultured Clone bssAC09 (FJ810630.1)
Uncultured Clone bssAC07 (FJ810628.1)
Uncultured Clone bssAC15 (FJ810636.1)
Uncultured Clone bssAD07 (FJ810647.1)
Magnetospirillum sp. TS-6 (AB167725.1)
Azoarcus aromaticum EbN1 (CR555306.1)
Thauera aromatica (AJ001848.3)
Uncultured Clone LA07bs16 (GU133304.1)
Uncultured Clone bssAC17 (FJ810638.1)
Uncultured Clone bssAC19 (FJ810640.1)
Uncultured Clone bssAD02 (FJ810644.1)
Desulfobacterium cetonicum (EF123662.1)
Bacterium Clone B1C1 (GU123599.1)
Sulfate Reduc. Bact. TRM1 (EF123667.1)
Bacterium Clone B1B6 (GU123598.1)
Uncultured Clone Zz-ox 76 (FJ889137.1)
Geobacter sp. TMJ1 (EF123666.1)
Bacterium bssA-1 (EF134966.1)
Uncultured Clone bssAC03 (FJ810624.1)
Uncultured Clone bssAC01 (FJ810622.1)

0.05
Figure 3.8. Phylogenetic tree of bssA partial sequences (722 bp) from nitrate amended
agricultural soil microcosms (using the primer set 7772f/8546r) along with the closest matches in
GenBank, constructed with MEGA 4.1 software using the neighbor-joining method.

71

Granular Sludge Nitrate Amended Clone 1
Granular Sludge Nitrate Amended Clone 3
Granular Sludge Nitrate Amended Clone 5
Granular Sludge Nitrate Amended Clone 6
Granular Sludge Nitrate Amended Clone 2
Granular Sludge Nitrate Amended Clone 4
Thauera sp. DNT-1 (AB066263.1)
Uncultured Clone LA07bs07 (GU133296.1)
Uncultured Clone LA07bs04 (GU133294.1)
Thauera aromatica (AF113168.1)
Azoarcus sp. DN11 (AB285034.1)
Azoarcus sp. T (AY032676.1)
Uncultured Clone bssAC12 (FJ810633.1)
Uncultured Clone bssAC18 (FJ810639.1)
Uncultured Clone bssAC11 (FJ810632.1)
Uncultured Clone bssAC06 (FJ810627.1)
Uncultured Clone bssAC08 (FJ810629.1)
Uncultured Clone bssAD03 (FJ810645.1)
Azoarcus aromaticum EbN1 (CR555306.1)
Magnetospirillum sp. TS-6 (AB167725.1)
Uncultured Clone bssAC17 (FJ810638.1)
Uncultured Clone bssAC19 (FJ810640.1)
Uncultured Clone bssAD02 (FJ810644.1)
Uncultured Clone LA07bs01 (GU133291.1)

0.05
Figure 3.9. Phylogenetic tree of bssA partial sequences (722 bp) from nitrate amended granular
sludge microcosms (using the primer set 7772f/8546r) along with the closest matches in
GenBank, constructed with MEGA 4.1 software using the neighbor-joining method.

72

Digester Sulfate Amended Clone 2
Digester Sulfate Amended Clone 1
Digester Sulfate Amended Clone 3
Sulf. reduc. bact. PRTOL1 (EU780921.1)
Bacterium bssA (EF134966.1)
Magnetospirillum sp. TS-6 (AB167725.1)
Aromatoleum aromaticum EbN1 (CR555306.1)
Uncultured Thauera sp. (AM887515.1)
Uncultured Thauera sp. (AM887514.1)
Uncultured Thauera sp. (AM887512.1)
Uncultured Thauera sp. (AM887517.1)
Uncultured Thauera sp. (AM887513.1)
Thauera aromatica (AJ001848.3)
Uncultured Thauera sp. (AM887516.1)
Thauera aromatica strain T1 (AF113168.1)
Thauera sp. DNT-1 (AB066263.1)
Desulfobacula toluolica (CU466268.1)
Geobacter metallireducens (AF441130.1)

0.5
Figure 3. 10. Phylogenetic trees of bssA partial sequences (97 bp) from sulfate amended digester
sludge microcosms (using the primer set SRBf/SRBr) along with the closest matches in
GenBank, constructed with MEGA 4.1 software using the neighbor-joining method.

73

Contam. Soil Sulfate Amended Clone 1
Contam. Soil Sulfate Amended Clone 5
Contam. Soil Sulfate Amended Clone 3
Enrichment Clone B1C1 (GU123599.1)
Sulfate Reduc. Bact. TRM1 (EF123667.1)
Contam. Soil Sulfate Amended Clone 7
Contam. Soil Sulfate Amended Clone 4
Enrichment Clone B2B2 (GU123600.1)
Contam. Soil Sulfate Amended Clone 2
Contam. Soil Sulfate Reducing Clone 6
Enrichment Clone B1B6 (GU123598.1)
Sulfate Reduc. Bact. PRTOL1 (EU780921.1)
Desulfobacula toluolica (CU466268.1)
Uncultured Clone LA07bs01 (GU133291.1)
Uncultured Clone bssAC14 (FJ810635.1)
Contam. Soil Sulfate Reducing Clone 8
Uncultured Clone Zz-ox 76 (FJ889137.1)
Geobacter sp. TMJ1 (EF123666.1)
Geobacter grbiciae DSM (EF123664.1)
Geobacter metallireducens (AF441130.1)
Bacterium bssA-1 (EF134966.1)
Azoarcus aromaticum EbN1 (CR555306.1)
Thauera aromatica (AJ001848.3)
Magnetospirillum sp. TS-6 (AB167725.1)
Thauera sp. DNT-1 (AB066263.1)
Uncultured Clone Zz-ox 12 (FJ889136.1)
Azoarcus sp. DN11 (AB285034.1)
Azoarcus sp. T (AY032676.1)

0.05
Figure 3.11. Phylogenetic trees of bssA partial sequences (637 bp) from sulfate amended
contaminated soil microcosms (using the primer set 7772f/8828r) along with the closest matches
in GenBank, constructed with MEGA 4.1 software using the neighbor-joining method.

74

bssA Gene Abundance

1

0.8

0.6

0.4

0.2

0
1.69

1.71

1.73

1.75

1.77

DNA Buoyant Density (g/mL)

Figure 3.12. Difference between abundance of bssA gene copies in ultracentrifugation fractions
13
from labeled ( C toluene) and unlabeled toluene amended microcosms from the granular sludge
13

nitrate amended microcosms as determined via qPCR. Figure symbols: ■ C-toluene (~100%
12

toluene degraded); □ C-toluene (~100% toluene degraded).

75

bssA Gene Abundance

1

0.8

0.6

0.4

0.2

0
1.69

1.71

1.73

1.75

1.77

DNA Buoyant Density (g/mL)

Figure 3.13. Difference between abundance of bssA gene copies in ultracentrifugation fractions
13
from labeled ( C toluene) and unlabeled toluene amended microcosms from the agricultural soil
13

nitrate amended microcosms as determined via qPCR. Figure symbols: ■ C-toluene (~100%
12

toluene degraded); □ C-toluene (~100% toluene degraded).

76

bssA Gene Abundance

1

0.8

0.6

0.4

0.2

0
1.69

1.71

1.73

1.75

1.77

DNA Buoyant Density (g/mL)

Figure 3.14. Difference between abundance of bssA gene copies in ultracentrifugation fractions
13
from labeled ( C toluene) and unlabeled toluene amended microcosms from the digester sludge
13

sulfate amended microcosms as determined via qPCR. Figure symbols: ■ C-toluene (~100%
12

toluene degraded); □ C-toluene (~100% toluene degraded).

77

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78

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Trautwein, K., S. Kuhner, L. Wohlbrand, T. Halder, K. Kuchta, A. Steinbuchel, and
R. Rabus. 2008. Solvent stress response of the denitrifying bacterium "Aromatoleum
aromaticum" strain EbN1. Applied and Environmental Microbiology 74:2267-2274.

55.

Washer, C. E., and E. A. Edwards. 2007. Identification and expression of
benzylsuccinate synthase genes in a toluene-degrading methanogenic consortium. Appl

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Environ Microb 73:1367-1369.
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Winderl, C., B. Anneser, C. Griebler, R. U. Meckenstock, and T. Lueders. 2008.
Depth-resolved quantification of anaerobic toluene degraders and aquifer microbial
community patterns in distinct redox zones of a tar oil contaminant plume. Appl Environ
Microb 74:792-801.

57.

Winderl, C., H. Penning, F. von Netzer, R. U. Meckenstock, and T. Lueders. 2010.
DNA-SIP identifies sulfate-reducing Clostridia as important toluene degraders in
tar-oil-contaminated aquifer sediment. Isme J 4:1314-1325.

58.

Winderl, C., S. Schaefer, and T. Lueders. 2007. Detection of anaerobic toluene and
hydrocarbon degraders in contaminated aquifers using benzylsuccinate synthase (bssA)
genes as a functional marker. Environ Microbiol 9:1035-1046.

59.

Xie, S. G., W. M. Sun, C. L. Luo, and A. M. Cupples. 2011. Novel aerobic benzene
degrading microorganisms identified in three soils by stable isotope probing.
Biodegradation 22:71-81.

60.

Xie, S. G., W. M. Sun, C. L. Luo, and A. M. Cupples. 2010. Stable Isotope Probing
Identifies Novel m-Xylene Degraders in Soil Microcosms from Contaminated and
Uncontaminated Sites. Water Air Soil Poll 212:113-122.

61.

Yang, Y. R., and J. Zeyer. 2003. Specific detection of Dehalococcoides species by
fluorescence in situ hybridization with 16S rRNA-targeted oligonucleotide probes. Appl
Environ Microb 69:2879-2883.

62.

Zhou, J. Z., M. R. Fries, J. C. Cheesanford, and J. M. Tiedje. 1995. Phylogenetic
Analyses of a New Group of Denitrifiers Capable of Anaerobic Growth on Toluene and
Description of Azoarcus-Tolulyticus Sp-Nov. Int J Syst Bacteriol 45:500-506.

63.

Zhou, J. Z., A. V. Palumbo, and J. M. Tiedje. 1997. Sensitive detection of a novel class
of toluene-degrading denitrifiers, Azoarcus tolulyticus, with small-subunit rRNA primers
and probes. Appl Environ Microb 63:2384-2390.

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CHAPTER 4
PRESENCE,DIVERSITY AND THE ENUMERATION OF TOLUENE DEGRADING
FUNCTIONAL GENES (BSSA AND BAMA) ACROSS A RANGE OF REDOX
CONDITIONS AND INOCULUM SOURCES

Introduction

An understanding of the biodegradation pathways for aromatic compounds is important for the
remediation of many contaminated environments. Biodegradation under anaerobic conditions is
especially critical to comprehend because under these conditions, which are typical at many
contaminated aquifers, removal rates are slow and therefore time for site closure may be
prolonged. A common approach for understanding biodegradation pathways involves an analysis
of the microbial community at the molecular level. Although an investigation into 16S rRNA
genes can provide useful indicator data, it is now well recognized that more information can be
gained by studying key functional genes. Recent research in this area involves the design and
application of molecular assays targeted to the benzoyl-CoA degradation pathway to investigate
the diversity of microorganisms involved in anaerobic aromatic biodegradation (9, 10, 14).
Anaerobic aromatic biodegradation typically involves the channeling of aromatic growth
substrates to the central intermediate benzoyl-coenzyme A (CoA) prior to dearomatization and
ring cleavage(9). In Thauera aromatica, the metabolism of benzoyl-CoA comprises of several
steps with ring cleavage action by 6-oxocylcohex-1-ene-1-carbonyl-CoA (6-OCH-CoA)
hydrolase, which likely catalyzes the transformation of 6-OCH-CoA to 6-hydroxypimelyl-CoA
(9, 11). Enzymes similar to those in the benzoyl-CoA pathway in T. aromatica are reported to be
present in most other aromatic degrading facultative anaerobes(5, 12). The ring-cleaving

85

hydrolase of the benzoyl-CoA pathway is encoded by the bamA gene. Recently, this pathway was
studied in obligate anaerobes that use aromatic growth substrates (9). The researchers expressed
genes putatively encoding for 6-OCH-CoA hydrolases from the obligately anaerobic Geobacter
metallireducens and Syntrophus aciditrophicus in Escherichia coli and identified the products as

6-OCH-CoA hydrolases and found these genes to be highly conserved in all anaerobic bacteria
using aromatic growth substrates (9). The researchers also designed primers to amplify the gene
of 6-OCH-CoA in a number or obligate and facultative anaerobes (G. metallireducens GS-15, T.
aromatic K172, Azoarcus EbN1, A. evansii KB740, Desulfococcus multivorans, S. aciditrophicus

SB, Magnetospirillum species TS-6 and CC-26) as well as from two sediment-free sulfate
reducing mixed cultures degrading toluene or m-xylene.

To date, there have only been two applications of the primers developed from this first study, the
bamA assay was modified and used to investigate bamA gene sequences in two recent field

studies(10, 14). One study investigated the diversity of bamA sequences in microcosms
incubated at benzene contaminated aquifers (10). In the other study, the authors investigated the
diversity of mono-aromate-degrading microorganisms by targeting the functional genes encoding
benzylsuccinate synthase α-subunit (bssA) as well as bamA (14). Benzylsuccinate synthase is a
key enzyme for anaerobic toluene biodegradation under nitrate reducing (1, 8), sulfate reducing
(18-20), ferric iron reducing (4, 7), and methanogenic enrichment cultures or environmental
samples (17, 18). In this second field study, the site was a leachate contaminated aquifer near the
Banisveld landfill (the Netherlands) under iron reducing conditions. The work involved analysis
of groundwater samples along a pollution plume in 1999 and 2004, which enabled the
researchers to correlate site conditions (e.g. ferrous iron concentrations and dissolved organic

86

matter) with sequence diversity.

The overall objective of the current study was to expand on the three bamA studies to further
investigate the diversity of bamA sequences across different redox conditions and inoculum
sources. For this, we studied a number of toluene-degrading mixed microbial communities
seeded from a wide range of sources, including contaminated soil from different sites,
uncontaminated soil, anaerobic granular and digester sludge and aerobic activated sludge. The
work is novel because it is the first to provide an in depth investigation of bamA diversity in
microcosms over a range of redox conditions and inoculum sources. In addition, quantitative
PCR (qPCR) assays to both bamA and bssA were developed and applied to a sub-set of these
samples. In summary, this research involved the following specific objectives 1) to determine the
diversity of bamA sequences in toluene degrading microcosms over a range of redox conditions,
2) to investigate the diversity of bamA sequences in microcosms from different sources including
contaminated and non-contaminated sites and 3) to determine if qPCR targeted to the bamA and
bssA genes could provide a reliable indicator for growth related toluene degradation.

Materials and Methods
Screening of Toluene Degrading Microcosms

A wide range of inoculum sources were examined for toluene biodegradation. The inocula were
taken from pristine agricultural soils (MI), previous gasoline contaminated soils (MI), sediments
from a former gas-compressor site (6) (OK), digester sludges from two wastewater treatment
plants (MI), activated sludge (MI) and anaerobic granular sludge (WA). Triplicates of ~10g (wet

87

weight) biomass were incubated in sterile 160 mL serum bottles containing 50 mL anaerobic
basal media (21), sealed with rubber stoppers and aluminum seals. Microcosms were prepared
under strictly anaerobic conditions in an anaerobic chamber (Coy Laboratory Products INC,
Grass Lake, MI). Potassium nitrate and magnesium sulfate were added to a final concentration of
1gL

-1

-

2-

NO3 and SO4 .From approximately fifty three incubations, six nitrate-amended, five

sulfate-amended and five methane generating (methanogenic) microcosms exhibited toluene
degradation and these were selected for DNA extraction. In addition, three nitrate amended, one
sulfate amended and two methanogenic microcosms were selected for qPCR. In this
experimental set, triplicate microcosms were set up for each treatment. For each microcosm, 3 g
biomass was anoxically incubated in 60 mL serum bottles containing 25 mL of anaerobic basal
media as described above. The microcosm inoculum sources and the experiments conducted on
each microcosm type are summarized in table 3.1. Toluene concentrations in headspace gas
samples (200 μL) were typically determined weekly with a gas chromatograph (Perkin Elmer)
equipped with flame ionization detector and a capillary column (J&W Scientific, DB-624,
diameter 0.53mm). Injector and detector temperature were set at 200 oC and the column
temperature was 120oC.

DNA Extraction and PCR

For the functional gene diversity studies (see below), microcosms exhibiting toluene
biodegradation were sacrificed for DNA extraction when toluene was depleted in each
microcosm. For the qPCR studies, DNA was extracted from samples (0.3g soil, wet weight)
sacrificed at successive time points (typically 0, 50, and 100%) to enumerate the bamA genes and

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bssA genes during the course of toluene depletion. The powersoil DNA extraction kit (MO BIO

Laboratories, Inc. Carlsbad, CA) was used for total nucleic acids extraction according to the
manufacturer’s recommended procedure. The presence of the benzylsuccinate synthase
alpha-subunit gene (bssA) and 6-oxocyclohex-1-ene-1-carBoN1yl-CoA hydrolase (bamA) was
investigated with a number of previously reported primers pairs (Table 4.1). A gradient PCR was
performed with annealing temperature ranging from 45ºC to 58 ºC. The presence of PCR
amplicons were determined using gel electrophoresis. A number of positive amplicons were
selected for cloning and sequencing (see below).

Quantitative PCR

Three nitrate amended consortia, one sulfate amended consortium and two methanogenic
consortia were selected for enumerating bssA and bamA genes during toluene biodegradation
(Table 4.1). The quantification assays were conducted in a Chromo 4 real-time PCR cycler
(Bio-Rad) using the primer sets 7772f/8546r (AgN, GSN, BoN11, HaM, ASM), 7772f/8828r
(DUKE), (bssA) or Bam-sp9 and Bam-asp1 (bamA) (Table 4.1). Each 20 μL PCR reaction mixture
containing 10 μL SYBR green real-time PCR solution (Applied Biosystems), 0.25 μM of each
primer, and 1 μL DNA template. The thermal protocol consisted of an initial denaturation (95 ºC,
15 min), 40 cycles of amplification (95 ºC, 15 s; 55 ºC, 20 s; 72 ºC 20 s) and a terminal extension
step (72 ºC, 2 min). Melting curves were constructed from 55 ºC to 95 ºC, read every 0.6ºC for 2
s. For each gradient fraction, 1 μL solution was diluted with 3 μL water as template (to conserve
the sample). Cloned plasmid DNA was utilized as a standard for quantification.

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Sequencing of Partial bssA and bamA Genes

Representative bssA and bamA amplicons were prepared for cloning and sequencing. The PCR
products were purified with QIAquick PCR purification kit (Qiagen Inc.) and cloned into
Escherichia coli TOP10 vector supplied with a TOPO TA cloning kit (Invitrogen Corporation). E.
-1

coli clones were grown on Luria-Bertani (LB) medium solidified with 15 g agar L

with 50 g

-1

ampicillin L for 16 h at 37 ºC. Colonies with inserts were verified by PCR with primers M13 F
(5’-TGTAAAACGACGGCCAGT-3’) and M13 R (5’-AACAGCTATGACCATG-3’), plasmids
were extracted from the positive clones with a QIAprep miniprep system (Qiagen, Inc.) and the
insertions were sequenced at RTSF. Phylogenetic trees for the partial bamA and bssA sequences
along with the closest matches in Genbank were obtained by the neighbor-joining method using
MEGA 4.1 software.

Results

This research builds on a previous study that involved a community analysis of five anaerobic
toluene degrading consortia. In that research, the active toluene degraders were identified using
stable isotope probing.

The putative toluene degraders were classified within the genus

Thauera (nitrate amended, GSN), the family Comamonadaceae (nitrate amended, AgN), the

genus Desulfosporosinus (sulfate amended AgS), the family Syntrophobacteraceae (sulfate
amended, DSS) and the family Desulfobulbaceae (sulfate amended, DUKE). In addition, partial
bssA sequences were obtained from four of the five consortia. The current study expands on this

research to investigate a larger number of toluene degrading samples (sixteen), includes
methanogenic microcosms, targets the presence and diversity of the bamA gene and
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quantitatively investigates the presence of the bamA and bssA genes in six of these samples.

bssA and bamA Gene Amplification

Primer sets 7772f/8546r(20) and bssAf/bssAr(2) produced strong specific amplicons for all six
and for five of the six (except DSN) of the nitrate amended microcosms, respectively. The three
other bssA primer pairs produced strong amplicons in only a small number of these microcosms
(Table 4.1). In the sulfate amended microcosms, SRBf/SRBr(3) produced strong specific
amplicons in four of the five (except BoS1) tested microcosms. Again, other primer pairs
produced specific amplicons in only a small number of the microcosms. The primer set
7772f/8828r(20) produced a strong specific amplicon for DUKE and was therefore used for the
qPCR assay on this sample. In the methanogenic microcosms, 7772f/8546f(20) performed well
in two (HaM and ASM) of the five microcosms tested and was used for the qPCR assays. Only
one other primer pair (bss1500f/bss2100r(13)) produced a strong amplicon in the methanogenic
microcosms, and this was true for only one of the five methanogenic microcosms (SM). Overall,
the success of bssA gene amplification was greatest in the nitrate amended microcosms and least
in the methanogenic microcosms. This reflects the limited bssA sequence information (and
therefore primers) on toluene degradation under methanogenic conditions compared to under
nitrate reducing conditions.

A number of the partial bssA sequences amplified were cloned and sequenced. This work is an
extension of a previous study on these samples. Previously, we obtained partial bssA sequences
from four of these samples (AgN, GSN, DSS and DUKE). The partial bssA sequences from the
nitrate amended microcosms (AgN and GSN) were found to be most similar to the bssA gene
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from Thauera sp. DNT-1. In contrast, the majority (except one) of the previously obtained bssA
sequences from the sulfate amended samples (DSS and DUKE) were most similar to the bssA
sequence from sulfate reducing bacterium PRTOL1. One sequence from the contaminated site
soil (DUKE) classified closest to an uncultured clone (Zz-ox 76) submitted to GenBank from an
unpublished study entitled characterization of anaerobic xylene biodegradation by two
dimensional isotope fractionation analysis. The current study adds to this growing database on
bssA gene diversity. Specifically, bssA sequences were determined from two additional nitrate

amended microcosms constructed from another agricultural soil (BoN11) and from digester
sludge (DSN). Also, partial bssA sequences were obtained from methanogenic microcosms
constructed from agricultural soil (HaM) or contaminated soil (SM).

The results regarding the amplification of bamA displayed a higher level of success. The primer
pair (bam-sp9 and Bam-asp1(9)) targeting the bamA gene produced strong specific amplicons in
all toluene-degrading microcosms tested except for one (contaminated soil, SM, methanogenic
microcosm). To examine the diversity of the bamA gene, amplicons were sequenced from six of
these samples (GSN, BoN1, DSS, DUKE, HaM and ASM). These samples were selected to
represent two of each redox condition. The sequences obtained were compared to the GenBank
database.

bssA and bamA Gene Quantification

Quantitative PCR was used to examine the applicability of targeting both functional genes as a
potential rapid screening method for toluene degradation potential. Microcosms from each redox
condition were selected for qPCR, three for nitrate amended samples (AgN, GSN, BoN1), one
92

for sulfate amended samples (DUKE) and two for the methanogenic samples (HaM and ASM).
In each case, the number of both genes increased over time as toluene was degraded (Figure
4.1-4.6).

In the nitrate amended samples (Figure 4.1-4.3), DNA was extracted three or three times during
the toluene degradation period.

For each experiment, a clear increase in bssA and bamA gene

numbers was seen and the raise occurred simultaneously with the course of toluene degradation.
The gene numbers of the bssA in GSN, AgN and BoN1 were approximately 145, 10200 and 400
times higher than those in the original sampling point. Similarly, the gene numbers of bamA were
3.62, 394 and 236 higher at the end compared to the beginning of the study for GSN, AgN and
BoN1, respectively. In the one sulfate amended (DUKE) and two methanogenic (ASM and HaM)
microcosms (Figure 4.4-4.6), DNA was extracted two times during the toluene degradation
period. In all three, gene numbers of bssA and bamA increased with time as toluene was
degraded. Interestingly, the final gene number for both genes differed considerably between the
range of redox conditions. In the nitrate amended samples, the final bssA gene numbers were
8

between 10 and 10

10

per gram of soil. Whereas in the sulfate amended and methanogenic
7

8

microcosms, bssA gene numbers were between 10 and 10 per gram of soil. A similar trend was
noted for the bamA gene. In the nitrate amended microcosms, final bamA gene numbers were in
8

9

the range of 10 and 10 per gram of soil. In the sulfate amended and methanogenic microcosms,
7

9

bamA gene numbers were between 10 and 10 per gram of soil. These patterns suggest the

toluene degrading population is higher under nitrate amended conditions.

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Discussion

The partial bssA and bamA sequences obtained in the current study provide an interesting picture
of the diversity of these sequences across redox conditions and different environments. Although
a significant number of partial bssA sequences are available in the literature, only three studies
have investigated the bamA gene (9, 10, 14). Here, we combine an investigation into both genes,
investigating their diversity across samples types. In addition, we provide data to indicate qPCR
targeted to these genes correlated well with toluene biodegradation. These results indicate the
qPCR assay has the potential for providing evidence of toluene degradation potential at
contaminated sites.

The study illustrated the difficulty associated with amplifying the bssA gene in sulfate amended
and methanogenic toluene degrading microcosms. As stated above, we previously obtained four
partial bssA sequences from nitrate and sulfate amended samples. In the current study, we expand
on this and identified four additional bssA gene sequences. These sequences were obtained from
two nitrate amended microcosms, one constructed from agricultural soil (BoN1) and the other
from digester sludge (DSN). In addition, two partial sequences were obtained from
methanogenic microcosms, one concentrated from agricultural soil (HaM) and the other from a
contaminated site (SM). The agricultural soil (BoN1) under nitrate amended conditions
contained two different partial bssA sequences with one being similar to Thauera sp. DNT-1
(87%). Interestingly, the other illustrated a high degree of similarity (83% identity) to bssA
clones obtained from a study involving sulfate reducing toluene degradation from a
tar-oil-contaminated aquifer at a former coal gasification plant (19). In the other nitrate amended
samples (DSN), only one clone was found and this had the highest similarity to Thauera

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aromatica (82%), a clone (clone LA07bs16) from the sulfate reducing study (81%) and
Aromatoleum aromaticum EbN1 (80%). For the methanogenic microcosms, only one dominant

sequence was obtained and these illustrated the greatest similarity to the clones described above
from the study on toluene degradation from a tar-oil-contaminated aquifer (85% and 83% for
HaM and SM, respectively). Several of these sequences were previously referred to as the
“F2”-cluster bssA (19).

In contrast to the difficultly in amplifying bssA, amplifying bamA was highly successful in all
except one toluene degrading microcosm (methanogenic SM). These results were unexpected,
because previous studies (10, 14) modified the primer pair originally proposed in 2008 (9) and
used in the current study. As discussed above, only three studies have investigated the bamA
gene in relation to aromatic degradation. The first manuscript developed the primer pair bam-sp9
and bam-asp (9) and these primers were modified for use in the two field studies (10, 14). One
study investigated the diversity of bamA sequences in microcosms incubated at benzene
contaminated aquifers (10). The other involved a landfill leachate contaminated aquifer under
iron reducing conditions (14). These two field studies are discussed below, followed by a
comparison between the bamA sequences obtained in the current study and those found in the
three previous studies.

The bamA assays used on DNA from the benzene contaminated sites involve the primers
designed previously (9) as well as the development of two additional reverse primers (to produce
~700 and ~800-bp amplicons) to amplify the GMT (Geobacter, Magnetospirillum and Thauera)
cluster and the SA (Gram-negative/Gram positive sulfate reducing bacteria and Syntrophus,

95

Azoarcus and Aromatoleum) cluster. The PCR assays were performed on in situ microcosms

incubated at two different tar oil and BTEX contaminated anoxic aquifers (called Gneisenau and
benzene production plant or BPP). The Gneisenau site had low concentrations of organics and
previous work had demonstrated the potential for benzene and toluene degradation (15). The site
had elevated concentration of total dissolved iron, indicating Fe (III) to Fe (II) reduction (10). At
this site, one bamA clone showed the highest sequence identity to Geobacter metallireducens
(88%). Five other clones had the highest similarity to bamA from Geobacter daltonii (85-88%).
Interestingly, the authors did not obtain any appropriate amplicons using the SA cluster targeting
bamA assay. The BPP site had a high concentration of benzene and the total dissolved iron

concentrations indicated Fe (III) reduction. Again the authors used both bamA assays. Using the
SA cluster targeting bamA assay, they found 8 clones with highest similarities to bamA genes
from species of the genera Azoarcus and Aromatoleum (75-78% identity). Using the GMT cluster
targeting bamA assay, they found two sequences similar to bamA sequences from species of the
genera Magnetospirillum and Thauera (80% identity).

The other field study involved a leachate contaminated aquifer near the Banisveld landfill (the
Netherlands) under iron reducing conditions (14). In this case, both the bamA and bssA genes
were investigated. This field study produced the most extensive collection of bamA sequences to
date. The sequences obtained were placed into seven clades: bamA-clade 1, bamA-clade 2,
bamA-clade 3, Thauera/Magnetospirillum-clade, Geobacter-clade, Syntrophus-clade and a
Georgfuchsia/Azoarcus clade (9). The work involved analysis of groundwater samples along the

pollution plume in 1999 and 2004, which enabled the researchers to correlate site conditions e.g.
ferrous iron concentrations and dissolved organic matter, with sequence diversity. The

96

researchers used qPCR to obtain a ratio of functional genes to bacterial 16S rRNA genes. On
average, 1.8 bssA copies and 33.7 bamA copies were present per 10,000 16S rRNA copies in
polluted samples in 2004. They found that species containing bssA sequences closely affiliated
with Georgfuchsia toluolica. In contrast, bamA genes closely related to Geobacteraceae were
dominant and only <2% of bamA genes were related to Georgfuchsia. From 64 partial bssA
sequence variants, 57 bssA sequences clustered to the bssA gene of Georgfuchsia toluolica G5G6.
A minor number of other bssA sequences affiliated with Geobacter spp., Magnetospirillum sp.
TS-6 and Aromatoleum aromaticum sp. EbN1. In contrast, samples from 1999 illustrated a high
occurrence of Aromatoleum related bssA sequences which coincided with denitrification being a
dominant redox process. The 188 partial bamA sequence variants showed a high gene diversity
and these sequences were placed into seven clades. A small fraction (1.5%) strongly grouped
with sequences from Georgfuchsia toluolica sp. G5G6, Azoarcus sp. and Aromatoleum
aromaticum sp. EbN1. A larger percentage (43.2%) contained sequences highly related to
Geobacter spp., and these were referred to as the ‘Geobacter-clade’. A number of sequences

(13.4%) showed similarity to Syntrophus aciditrophicus sp. SB and were called the
‘Syntrophus-clade’.

A small number of sequences (5 of 188) were placed with the

‘Thauera/Magnetospirillum-clade’. Two clades (bamA-clade 1 and 2) did not contained reference
genes from isolates and one clade (bamA-clade 3) had low similarity to Azoarcus and Syntrophus
aciditrophicus sp. SB.

The bamA sequences obtained in the current study affiliated with five of these seven clades
described above. The bamA sequences from the nitrate amended samples were placed within
three clades (bamA-clade 1, Georgfuchsia/Azoarcus and Magnetospirillum/Thauera clades). In

97

contrast, the bamA sequences obtained from the sulfate amended microcosms were placed within
two different clades (Syntrophus and Geobacter clades). The bamA sequences from the
methanogenic microcosms were all placed within the Syntrophus clade. The details for each are
described below.

In the nitrate amended agricultural soil microcosms, two different bamA sequences were
obtained. Three sequences has the greatest similarity to bamA clone 0c_1999(1C) from the
landfill study (97% identity) and

the bamA sequence from Azoarcus toluvorans strain Td21

(97% identity). These three sequences could be placed in the Georgfuchsia/Azoarcus clade. The
other sequence type had the greatest similarity to landfill clone -200b_2004(1B) (92% identity)
and could be placed inside the bamA-clade 1. This was the only sequence obtained in the current
study to be placed in this clade. This clade does not contain reference genes from isolates (9).
The other nitrate amended microcosms (inoculated with digester sludge) contained a different set
of bamA genes. This time, the sequences were most similar to Magnetospirillum magneticum
(92% identity) and could be placed with the Magnetospirillum/Thauera clade. The placement of
the bamA sequences from nitrate amended samples within clades containing known nitrate
reducing toluene degrading species (Azoarcus, Georgfuchsia, Magnetospirillum and Thauera)
suggests the bamA gene is highly conserved. Interestingly, one sequence was placed in a clade
with no reference genes from isolates, indicating gene diversity under nitrate reducing conditions
cannot be not completely accounted for by known isolates.

The bamA sequences obtained from the sulfate amended samples were placed into two clades.
All clones from the digester sludge inoculated microcosms were placed into the Syntrophus clade

98

and had the greatest similarity to the landfill leachate plume clones (89% identity). In contrast,
the bamA clone from microcosm inoculated with the contaminated site sediment was placed with
the Geobacter clade and had the greatest similarity (84% identity) to bamA clones from the
Gneisenau site (10). This site is located near a former coking plant and contained iron and sulfate
as potential electron acceptors. All of the sequences obtained from the methanogenic samples
could be placed within the Syntrophus clade. The bamA clones from the methanogenic activated
sludge samples had to highest similarity to the bamA sequence from the obligately anaerobic
bacteria Syntrophus aciditrophicus (87% identity) and to bamA sequences from the landfill
leachate plume (9). The bamA sequences from the agricultural soil under methanogenic
conditions were also most similar to Syntrophus aciditrophicus (84% identity) and the landfill
leachate plumes. Again, these data indicate bamA sequence diversity to be strongly correlated
with electron accepting conditions.

In the current study, bssA and bamA gene numbers were obtained for a select number of
microcosms during toluene degradation. The only other published data quantifying these genes
together exists in the landfill leachate study (14). In that case, the authors reported on average 1.8
bssA copies and 33.7 bamA copies were present per 10,000 16S rRNA copies in polluted samples

in 2004. Although the current study did not quantify 16S rRNA gene numbers, a ratio of
bamA/bssA can be calculated to compare the new data to the field data described above. In the

nitrate amended microcosms, the bamA/bssA ratios are ~0.06, 1 and 0.25 for AgN, BoN1 and
GSN, respectively. These ratios are much lower than those described above. In the sulfate
amended sample (DUKE), the rate is ~11 and in the methanogenic microcosms the ratios are
~2.7 (HaM) and ~1.6. It is not clear why the ratios are lower in the laboratory studies. It is

99

possible that the presence of a diverse range of contaminants at the field site favors bamA,
whereas microcosms exposed to toluene only favors bssA.

In summary, this work provides the first in-depth study of the diversity of bamA gene sequences
across redox conditions and in microcosms constructed from different inoculum sources. Since
2008, to our knowledge, only three studies have investigated the bamA gene in anaerobic
aromatic degrading cultures (9, 10, 14). The research also examined the presence and diversity of
the bssA gene and documented the utility of a range of primers for bssA detection. Further, qPCR
was targeted to these two functional genes and the results provided evidence that toluene
degradation can be correlated with bamA and bssA gene numbers. Therefore, the qPCR assays
have the potential for use at field sites to document toluene degradation.

100

Tables and figures
Table 4.1. Success of bssA and bamA primers, amplicons cloned and the consortia targeted for
qPCR.
Consorti Inoculum Likely
7772f/
SRBf/
bss1500f/
Bamr/ qPCR
a
Source
TEA
8546r(20) SRBr(3) bss2100r(13) Bamf(9)
++
AgN
Ag soil
Nitrate
yes
+*
++* X
++ X
GSN
Granular
Nitrate
yes
-*
++* X
sludge
ASN
Activated Nitrate
++
++
no
sludge
BoN1
Ag soil
Nitrate
++ X
++
++ X
yes
BoN2
Ag soil
Nitrate
++
++
++
no
DSN
Digester
Nitrate
++ X
++
++
no
sludge
DSS
Digester
Sulfate
++
++ X
no
+*
++* X
sludge
#
++ X
DUKE
Contamin Sulfate
++* X
yes
+*
ated soil
++
no
AgS
Ag soil
Sulfate
++*
+*
BoS1
Ag soil
Sulfate
++
no
StS
Digester
Sulfate
+
++
++
++
no
sludge
+
+
++ X
SM
Contamin
+
no
CO2
ated soil
++ X
HaM
Ag soil
+
++ X
yes
CO2
++
+
++ X
ASM
Activated
yes
CO2
sludge
++
no
DSM
Digester
CO2
sludge
KRM
Ag soil
+
+
++
no
CO
2

++ strong specific amplicon
+ unspecific amplicon(s)
- no amplicon
X – amplicons sequenced
# - the primer set 7772f/8828r (20) was used to target bssA for qPCR
* Previous study in our group(16)

101

10

bssA
bamA

Log numbers of gene copies

9
8
7
6
5
4
3
2
1
0
33%

75%

100%

Toluene removed (%)

Figure 4. 1. Gene numbers of bssA and bamA during toluene degradation in nitrate amended
microcosms AgN. The error bars represent standard deviations form triplicate qPCR samples.

102

9

bssA
bamA

Log numbers of gene copies

8
7
6
5
4
3
2
1
0
33%

75%

100%

Toluene removed (%)

Figure 4.2. Gene numbers of bssA and bamA during toluene degradation in nitrate amended
microcosms BoN1. The error bars represent standard deviations form triplicate qPCR samples.

103

9

bssA
bamA

Log numbers of gene copies

8
7
6
5
4
3
2
1
0
50%

100%
Toluene removed (%)

Figure 4.3. Gene numbers of bssA and bamA during toluene degradation in nitrate amended
microcosms GSN. The error bars represent standard deviations form triplicate qPCR samples.

104

9

bssA
bamA

Log numbers of gene copies

8
7
6
5
4
3
2
1
0
50%

100%
Toluene removed (%)

Figure 4.4. Gene numbers of bssA and bamA during toluene degradation in a sulfate amended
microcosm, DUKE.The error bars represent standard deviations form triplicate qPCR samples.

105

Log numbers of gene copies

8

bssA

7

bamA

6
5
4
3
2
1
0
50%

100%
Toluene removed (%)

Figure 4.5. Gene numbers of bssA and bamA during toluene degradation in a methaongeic
microcosm, ASM. The error bars represent standard deviations form triplicate qPCR samples.

106

8

bssA
bamA

Log numbers of gene copies

7
6
5
4
3
2
1
0
50%

100%
Toluene removed (%)

Figure 4.6. Gene numbers of bssA and bamA during toluene degradation in a methaongeic
microcosm, HM. The error bars represent standard deviations form triplicate qPCR samples.

107

REFERENCES

108

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of Azoarcus sp strain T: Cloning, sequencing, transcriptional organization, and its role in
anaerobic toluene and m-xylene mineralization. Journal of Bacteriology 183:6763-6770.
2. Beller, H. R., S. R. Kane, T. C. Legler, and P. J. J. Alvarez. 2002. A real-time polymerase
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catabolic gene. Environmental Science & Technology 36:3977-3984.
3. Beller, H. R., S. R. Kane, T. C. Legler, J. R. McKelvie, B. S. Lollar, F. Pearson, L. Balser,
and D. M. MacKay. 2008. Comparative assessments of benzene, toluene, and xylene natural
attenuation by quantitative polymerase chain reaction analysis of a catabolic gene, signature
metabolites, and compound-specific isotope analysis. Environmental Science & Technology
42:6065-6072.
4. Botton, S., M. van Harmelen, M. Braster, J. R. Parsons, and W. F. M. Roling. 2007.
Dominance of Geobacteraceae in BTX-degrading enrichments from an iron-reducing aquifer.
Fems Microbiology Ecology 62:118-130.
5. Gibson, J., and C. S. Harwood. 2002. Metabolic diversity in aromatic compound
utilization by anaerobic microbes. Annual Review of Microbiology 56:345-369.
6. Jin, S., P. H. Fallgren, A. A. Bilgin, J. M. Morris, and P. W. Barnes. 2007.
Bioremediation of benzene, ethylbenzene, and xylenes in groundwater under iron-amended,
sulfate-reducing conditions. Environmental Toxicology and Chemistry 26:249-253.
7. Kane, S. R., H. R. Beller, T. C. Legler, and R. T. Anderson. 2002. Biochemical and
genetic evidence of benzylsuccinate synthase in toluene-degrading, ferric iron-reducing
Geobacter metallireducens. Biodegradation 13:149-154.
8. Kuhner, S., L. Wohlbrand, I. Fritz, W. Wruck, C. Hultschig, P. Hufnagel, M. Kube, R.
Reinhardt, and R. Rabus. 2005. Substrate-dependent regulation of anaerobic degradation
pathways for toluene and ethylbenzene in a denitrifying bacterium, strain EbN1. Journal of
Bacteriology 187:1493-1503.
9. Kuntze, K., Y. Shinoda, H. Moutakki, M. J. McInerney, C. Vogt, H. H. Richnow, and M.
Boll. 2008. 6-Oxocyclohex-1-ene-1-carbonyl-coenzyme A hydrolases from obligately anaerobic
bacteria: characterization and identification of its gene as a functional marker for aromatic
compounds degrading anaerobes. Environmental Microbiology 10:1547-1556.
10. Kuntze, K., C. Vogt, H. H. Richnow, and M. Boll. 2011. Combined application of
PCR-based functional assays for the detection of aromatic-compound-degrading anaerobes.
Applied and Environmental Microbiology 77:5056-5061.
11. Laempe, D., M. Jahn, and G. Fuchs. 1999. 6-hydroxycyclohex-1-ene-1-carbonyl-CoA
dehydrogenase and 6-oxocycsohex-1-ene-1-carbonyl-CoA hydrolase, enzymes of the
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benzoyl-CoA pathway of anaerobic aromatic metabolism in the denitrifying bacterium Thauera
aromatica. European Journal of Biochemistry 263:420-429.
12. Lopez Barragan, M. J., E. Diaz, J. L. Garcia, and M. Carmona. 2004. Genetic clues on
the evolution of anaerobic catabolism of aromatic compounds. Microbiology-Sgm
150:2018-2021.
13. Moore, E. 2009. Developing protocols to facilitate the enrichment and characterization of
hydrocarbon-degrading anaerobic microbial communities. Department of Chemical Engineering
and Applied Chemistry, MS Thesis, University of Toronto.
14. Staats, M., M. Braster, and W. F. M. Roling. 2011. Molecular diversity and distribution of
aromatic hydrocarbon-degrading anaerobes across a landfill leachate plume. Environmental
Microbiology 13:1216-1227.
15. Stelzer, N., C. Buning, F. Pfeifer, A. B. Dohrmann, C. C. Tebbe, I. Nijenhuis, M. Kastner,
and H. H. Richnow. 2006. In situ microcosms to evaluate natural attenuation potentials in
contaminated aquifers. Organic Geochemistry 37:1394-1410.
16. Sun, W., and A. M. Cupples. Diversity of five anaerobic toluene degrading microbial
communities investigated using stable isotope probing (SIP). Submitted.
17. Washer, C. E., and E. A. Edwards. 2007. Identification and expression of benzylsuccinate
synthase genes in a toluene-degrading methanogenic consortium. Applied and Environmental
Microbiology 73:1367-1369.
18. Winderl, C., B. Anneser, C. Griebler, R. U. Meckenstock, and T. Lueders. 2008.
Depth-resolved quantification of anaerobic toluene degraders and aquifer microbial community
patterns in distinct redox zones of a tar oil contaminant plume. Applied and Environmental
Microbiology 74:792-801.
19. Winderl, C., H. Penning, F. von Netzer, R. U. Meckenstock, and T. Lueders. 2010.
DNA-SIP identifies sulfate-reducing Clostridia as important toluene degraders in
tar-oil-contaminated aquifer sediment. Isme Journal 4:1314-1325.
20. Winderl, C., S. Schaefer, and T. Lueders. 2007. Detection of anaerobic toluene and
hydrocarbon degraders in contaminated aquifers using benzylsuccinate synthase (bssA) genes as
a functional marker. Environmental Microbiology 9:1035-1046.
21. Yang, Y. R., and J. Zeyer. 2003. Specific detection of Dehalococcoides species by
fluorescence in situ hybridization with 16S rRNA-targeted oligonucleotide probes. Applied and
Environmental Microbiology 69:2879-2883.

110

CHPATER 5
ANAEROBIC MTBE DEGRADING MICROORGANISMS IDENTIFIED IN
WASTEWATER TREATMENT PLANT SAMPLES USING STABLE ISOTOPE
PROBING

Introduction

Methyl tert-butyl ether (MTBE) is a synthetic organic compound that was added to gasoline in
the late 1970s, following the phase out of tetraethyl lead. Later, the implementation of the Clean
Air Act Amendments (1990) caused a significant increase in MTBE use. In 1970, MTBE was the
39th highest produced US organic chemical whereas by 1998 it ranked 4th. During this time the
aggregate production of MTBE was 60 million metric tons (11). The large scale use, combined
with MTBE’s physiochemical properties, has resulted in severe contamination. MTBE has a high
-1

water solubility (51 g L ), strongly partitions to water from air (dimensionless Henry’s Law
constant 0.02) (14), has a low sorption partition coefficient (Koc is 1.035-1.091(15)) and, thus, is
highly mobile in water (51). MTBE contamination has been reported in surface waters (3, 4, 9,
11, 15, 26, 46), groundwater (11, 15, 28, 29, 34, 38, 40, 53, 59, 64), and drinking water sources
(1, 6, 11, 20, 35, 42, 48, 52, 56). MTBE contamination in drinking water has been reported in 36
states, with removal estimates being $25-33.2 billion (5).

Biological degradation is becoming increasing common as a remediation method for
groundwater contaminants, either through natural attenuation or enhanced bioremediation. There
have been numerous studies on aerobic MTBE biodegradation (32, 45, 57, 58) and
microorganisms capable of degrading MTBE under aerobic conditions have been isolated (16, 39,
111

47, 49). Anaerobic MTBE biodegradation has also been documented (10, 21-23, 36, 41, 43, 54),
however, much less is known about the microorganisms involved and, to date, no MTBE
degrading isolates have been obtained. This knowledge gap is a significant limitation to in situ
MTBE bioremediation because many contaminated sites are anaerobic. More information on the
microorganisms capable of anaerobic MTBE degradation could result in the application of
molecular methods to investigate their presence and abundance, and therefore the potential for
MTBE degradation at different sites.

The microbial composition of anaerobic MTBE degrading enrichment cultures has only recently
been investigated. In 2009, the microbial communities of three anaerobic MTBE degrading
cultures derived from MTBE-contaminated aquifer material were examined using 16S rDNA
based amplified ribosomal DNA restriction analysis (ARDRA) and 16S rRNA gene sequencing
(17).

The cultures were maintained with anthroquinone-2,6-disufonate (AQDS), sulfate or

fumarate as electron acceptors and the authors found that the microbial diversity varied under
these different conditions. In another recent study, other researchers characterized the community
composition of anaerobic enrichment cultures originating from three different contaminated
sediments (63). Interestingly, terminal restriction fragment length polymorphism (TRFLP)
profiles indicated substantially different community profiles from MTBE degrading microcosms
established from different sediment sources. A third group investigated the microbial community
present (16S rRNA gene sequencing) when MTBE degradation occurred under sulfate or iron
reducing conditions or when both electron acceptors were present together and identified five to
eight microorganisms in the three consortia (43).

112

The current study expands on these investigations by applying DNA based stable isotope probing
(SIP) to determine which organisms are responsible for

13

C label uptake from MTBE in

anaerobic MTBE degrading microcosms under methanogenic conditions. The SIP method is
unique in that it can directly identify the microorganisms responsible for contaminant
degradation and therefore offers more targeted information than community analysis alone (e.g.
TRFLP, ADARA, 16S rRNA clone libraries). To date, SIP has yet to be used to investigate
MTBE degradation in anaerobic MTBE degrading microcosms. The SIP method involves
exposure of mixed cultures to the labeled compounds of interest (e.g.,

13

C MTBE) and DNA

extraction over time. The DNA is then subject to ultracentrifugation, fractionation (to separate
label incorporated DNA from the unlabeled DNA) and TRFLP on each fraction. Any TRFLP
fragment illustrating an increase in relative abundance in the heavy fraction of the samples
(exposed to labeled substrate) compared to the controls (exposed to unlabeled substrate) is
identified as the putative degrader. The method has been used to identify the microorganisms
involved in the degradation of numerous contaminants (2, 13, 27, 30, 31, 37, 55, 60, 61). In the
current study, a range of sources (contaminated site sediment, agricultural soils and wastewater
treatment samples) were examined for anaerobic MTBE degradation potential. In the active
anaerobic MTBE degrading microcosms, SIP targeted to both bacteria and archaea was applied
to identify the putative MTBE degrading microorganisms.

Methods
Microcosm Construction and Analytical Techniques

A range of sources were tested for their potential to degrade MTBE (Table 5.1), including
113

agricultural soil, contaminated site soil and wastewater treatment samples. From all samples
tested only one source (WWTP sample) demonstrated MTBE degradation and was further
investigated. Microcosms were prepared under strictly anaerobic conditions in an anaerobic
chamber (Coy Laboratory Products INC, Grass Lake, MI). For each microcosm, ~6g sample
(wet weight) was anoxically incubated in 60 mL serum bottles containing 25 mL of anaerobic
basal media (62). Each treatment involved triplicate abiotic controls, triplicate unlabeled MTBE
13

(1 μL, 99 %, Sigma Aldrich, St. Louis, MO) and three triplicate labeled MTBE ( C5-MTBE 1
μL Sigma Aldrich, St. Louis, MO) amended samples. These microcosms were incubated at room
temperature (~20 °C) with reciprocal shaking. MTBE concentrations in headspace gas samples
(200 μL) were determined with a gas chromatograph (Perkin Elmer) equipped with flame
ionization detector and a capillary column (J&W Scientific, DB-624, diameter 0.53mm). Injector
and detector temperature were set at 200 oC and the column temperature was 120oC.

DNA Extraction and Ultracentrifugation

Microcosms were sacrificed for DNA extraction at two time points (~30% and ~70% MTBE
removal) during MTBE depletion to understand the flow of carbon through these microbial
communities. The powersoil DNA extraction kit (MO BIO Laboratories, Inc. Carlsbad, CA) was
used for total nucleic acids extraction according to the manufacturer’s recommended procedure.
Quantified DNA extracts (~10 μg) were loaded into Quick-Seal polyallomer tubes (13×51 mm,
5.1 ml, Beckman Coulter) along with a Tris-EDTA (TE, pH 8.0) /CsCl solution. Prior to sealing
(cordless quick-seal tube topper, Beckman), the buoyant density (BD) was determined with a
model AR200 digital refractometer (Leica Microsystems Inc) and adjusted by adding small

114

-1

volumes of CsCl solution or Tris-EDTA buffer with a final BD of 1.7300 mgL . The tubes were
centrifuged at 178,000 g (20 ºC) for 48 h in a Stepsaver 70 V6 Vertical Titanium Rotor (8 x 5.1
ml capacity) within a Sorvall WX 80 Ultra Series Centrifuge (Thermo Scientific). Following
centrifugation, the tubes was placed onto a fraction recovery system (Beckman) and fractions
(150 l) were collected. The BD of each fraction was measured, and CsCl was removed by
glycogen-assisted ethanol precipitation.

PCR, TRFLP and Sequencing of 16S rRNA Genes

The density-resolved fractions from

12

C and

13

C microcosms for each treatment were

PCR-amplified using 27F-FAM (5’-AGAGTTTGATCMTGGCTCAG, 5’ end-labeled with
carboxyfluorescine) and 1492R (5’-GGTTACCTTGTTACGACTT) for generating bacterial
amplicons

and

A109F—FAM

(5’-

ACKGCTCAGTAACACGT)

and

A934R

(5’-

GTGCTCCCCCGCCAATTCCT ) for archaeal amplicons (Operon Biotechnologies). The
presence of PCR products was confirmed by 1.5% agarose gel electrophoresis and the
subsequent staining of the gels with ethidium bromide. PCR products were purified with
QIAquick PCR purification kit (Qiagen Inc.), following the manufacturer’s instructions and
approximately 150 ng was digested with HaeIII (New England Biolabs) with a 6-hour incubation
period. Additional digests (HhaI, MseI, Bsp1286I, BsrBI etc.) for TRFLP analyses in a number
of heavy labeled fractions were included to correlate the TRFLP fragment lengths to the in silico
cut sites of the cloned 16S rRNA gene sequences. DNA fragments were separated by capillary
electrophoresis (ABI Prism 3100 Genetic Analyzer, Applied Biosystems) at the Research
Technology Support Facility (RTSF) at Michigan State University. Data were analyzed with
115

GeneScan software (Applied Biosystems) and the percent abundance of each fragment was
determined. Clone libraries of the 16S rRNA genes were constructed using DNA amplified with
27F/1492R , A109F/A934R as above except the forward primer was unlabeled and the final
extension time was extended to 15 minutes. To reduce sequencing redundancy, restriction
fragment length polymorphism (RFLP) analyses was performed and specific operational
taxonomic units (OTU) were selected for sequencing. The PCR products were purified with
QIAquick PCR purification kit (Qiagen Inc.) and cloned into Escherichia coli TOP10 vector
supplied with a TOPO TA cloning kit (Invitrogen Corporation). E. coli clones were grown on
-1

-1

Luria-Bertani (LB) medium solidified with 15 g agar L with 50 g ampicillin L for 16 h at 37
ºC.

Colonies

with

inserts

were

verified

by

PCR

with

primers

M13

F

(5’-TGTAAAACGACGGCCAGT-3’) and M13 R (5’-AACAGCTATGACCATG-3’), plasmids
were extracted from the positive clones with a QIAprep miniprep system (Qiagen, Inc.) and the
insertions were sequenced at RTSF. The Ribosomal Database Project (RDP) (Center for
Microbial Ecology, Michigan State University) analysis tool “classifier” was utilized to assign
taxonomic identity.

Results and Discussion

From twenty-two experimental set-ups, anaerobic MTBE biodegradation was noted in
microcosms constructed from only one source and only under methanogenic conditions (Table
5.1). Microcosms for the SIP experiment were constructed using freshly sampled material from
the wastewater treatment plant (WWTP). MTBE degradation occurred in both labeled MTBE
amended and unlabeled MTBE amended samples, but not in the abiotic controls (Figure 5.1). At

116

two time points during the time period for MTBE biodegradation (~30% and 70% removal),
DNA was extracted from the labeled and unlabeled MTBE-amended microcosms, and was
subject to ultracentrifugation, fractionation and TRFLP. Bacterial microbial communities were
profiled by TRFLP when 30% and 70% MTBE was degraded, whereas archaeal communities
were only profiled when 70% was degraded. Assimilation of 13C labeled MTBE was detected by
comparing TRFLP profiles of DNA derived from labeled treatments with DNA from unlabeled
treatments. Specifically, the organisms responsible for

13

C assimilation were identified by the

comparison of relative abundances of specific terminal restriction fragments (T-RFs) between the
labeled and unlabeled gradient-fractions.

Labeled bacterial DNA was successfully amplified in the fractions with buoyant density (BD)
values of 1.7154 to 1.7719 g ml

-1

(~70% degraded) and 1.7306 to 1.7653 g ml

-1

(~30%

-1

degraded). PCR products were seen in the fractions with BDs of 1.7024 to 1.7589 g ml

in the

unlabeled treatment (~70% degraded). Two bacterial T-RFs (67 bp and 215 bp) were highly
enriched in the heavy

13

C fractions while such enrichment was not seen in the corresponding

fractions with similar buoyant density (Figure 5.2A and B). A high (>30%) relative abundance
(RA) of both T-RFs was noted in the heavier fractions and their RA increased over time, as
MTBE was degraded (30% and 70% MTBE degraded). The RA of 215 bp T-RF was > 20%
-1

among the heavy fractions (banding between 1.7545 to 1.7719 g ml ) with the maximum RA
(46.6%) in the fraction with BD of 1.7676 g ml

-1

(~70 % degraded) (Figure 5.2A). The RA of

the 67 bp T-RF was generally > 30% in labeled heavy fractions (banding between 1.7480 to

117

-1

1.7719 g ml ) under both time points with the maximum RA (48.4%) in the fraction with BD of
1.7643 g ml

-1

(~70% degraded) (Figure 5.2B). An analysis of the archaeal SIP TRFLP profiles

(from ~70% MTBE degraded) indicated two T-RFs (132 bp and 162 bp) were relatively more
dominant in the labeled fractions compared to the controls (Figure 5.3 A and B).

Clone libraries for both bacteria (Table 5.2) and archaea (Table 5.3) were generated to
investigate the diversity of the MTBE degrading microcosms and to identity the putative MTBE
degraders represented by the T-RFs discussed above. The most dominant bacterial phylum was
the Proteobacteria (59 from 122 clones or 48.4%), which contained Alphaproteobacteria (22/59),
Betaproteobacteria (21/59), Gammaproteobacteria (10/59) and Deltaproteobacteria (6/59). The

second most dominant phylum was the Firmicutes (29/122 or 23.8%), which primarily consisted
of Clostridia (26/29). Other minor phyla included Verrucomicrobia (9/122), Nitrospira (6/122),
Bacteroidetes (5/122), OP10 (5/122), Lentisphaerae (4/122), Tenericutes (3/122) and
Acidobacteria (1/122). The genera of each clone determined from the RDP are also shown, with

a significant number (13/26) from being unclassified to the genus level (Table 5.2). The archaeal
community was less diverse with only 7 different phylotypes (Table 5.3), all within the class
Methanomicrobia (phylum Euryarchaeota).

Two phylotypes could not be classified at the

genus level.

The bacterial and archaeal sequences were digested in silico to identify the T-RFs enriched in the
heavy fractions as discussed above. The two bacterial T-RFs dominant in the heavy fractions
were identified as Clostridia (215 bp) and Alphaproteobacteria (67 bp). The Clostridia-related
phylotype could be classified to the family level (Ruminococcaceae) and was most similar to an
118

uncultured Acetivibrio spp. (95% 16S rRNA gene sequence similarity: GenBank accession
number EF613411.1). The Alphaproteobacteria-related clone classified to the genus
Sphingopyxix and was most similar to an uncultured bacterium clone reservoir-30 (99% of 16S

rRNA gene sequence similarity: GenBank accession number JF697411.1). The archaeal 132 bp
and 162 bp T-RFs belonged to the genera Methanosarcina and Methanocorpusculum,
respectively. The putative identifies of the bacterial T-RFs were confirmed with additional
digests on the heavy fractions (Table 5.4).

The SIP data indicate the primary MTBE degraders in the methanogenic enrichment are bacteria
and belong to the phyla Clostridia (family Ruminococcaceae) and Alphaproteobacteria (genus
Sphingopyxis). As the label enrichment level was low in the archaeal phylotypes in the heavy

fractions, it is unlikely that these organisms (genera Methanosarcina and Methanocorpusculum)
are the dominant degraders. It is possible that the identified archaeal phylotypes are responsible
for minor amounts of MTBE degradation or they are consuming metabolites produced by the
primary bacterial degraders.

Interestingly, other researchers have identified Clostrida as

dominant organisms in their anaerobic MTBE degrading enrichments. Specifically, from the
three enrichments (AQDS, sulfate or fumarate reducing) developed from MTBE contaminated
aquifer material, the sulfate reducing enrichment contained 19.3% assigned to the order
Clostridiales and the fumarate reducing enrichment contained a dominant clone (related to
Clostridium sp. Kw12) (22.8%) also belonging to the phylum Firmicutes (17). Similarly,

following continual enrichment of an anaerobic MTBE degrading consortium, researchers
reduced the community to three dominant phylotypes belonging to Deltaproteobacteria,
Chloroflexi and Firmicutes (63). In addition, Clostridia were found in anaerobic MTBE

119

degrading consortia under sulfate and iron reducing conditions (44). These previous studies,
combined with the data in the current study indicate organisms in the phylum Firmicutes are
important for the anaerobic degradation of MTBE.

Microorganisms associated with the family of Ruminococcaceae within the phylum Firmicutes
are predominant members of mammalian gut microbial flora. The presence of these organisms in
the enrichments is therefore not surprising given the source of the inocula (WWTP sample).
Members of Ruminococcaceae isolated from human gut were correlated with biodegradation of
complex polysaccharides such as starch or xylan (19). Ruminococcaceae isolated from rumen or
human guts were proven to be able to degrade cellulose (7, 8, 18). Chassard et al. reported
Ruminococcaceae were responsible for cellulose biodegradation in the fecal samples of

methane-excreting subjects while the main cellulose-degrading bacteria belong essentially to
Bacteroidetes in non-methane-excreting subjects (7), indicating a possible link between methane

production and Ruminococcaceae-associated cellulose biodegradation. This observation is
consistent with the current study in that no MTBE biodegradation under the sulfate- and nitrateamended conditions (no methane was produced) although they were seeded from the same
inocula. Ruminococcaceae were also linked with 2,4,6-trinitrotoluene (TNT) degradation in a
recent study (12). The most similar isolate to the putative MTBE degrader (family
Ruminococcaceae) identified in the current study is uncultured Acetivibrio sp. clone ZZ-S2G3

(95% 16S rRNA similarity; Genbank accession number EF613411.1) which was found in a
sulfate reducing benzene-degrading microbial community but was not correlated with benzene
biodegradation (33).

120

In contrast to the putative MTBE degrader (Firmicutes phylotype, TR-F 215 bp) discussed above,
the other putative MTBE degrader (phylum Alphaproteobacteria, genus Sphingopyxis TR-F 67
bp), has no obvious previous links to anaerobic MTBE biodegradation. The 67-bp T-RF showed
a high level of 16S rRNA similarity (98%) to an uncultured Alphaproteobacteria bacterium
(GeneBank CU926829.1) detected in anaerobic digestion of sludge (50). The data obtained from
the current study indicate this phylotype may be a novel anaerobic MTBE degrader and should
be further investigated.

The presence of two enriched T-RFs suggests more than one microorganism may be responsible
for MTBE biodegradation. Youngster et al. (24) suggested that anaerobic MTBE biodegradation
required the interaction of a consortium. The exact mechanism of MTBE anaerobic
biodegradation in the current study has yet to be elucidated. Others have reported tert-butyl
alcohol (TBA) as a MTBE degradation metabolite (22, 25, 49), indicating the cleavage of ether
bond is the initial step of MTBE biodegradation. Interestingly, the –C–O–C– bond found in
MTBE also occurs in cellulose, therefore one might hypothesize that Ruminococcaceae which
can degrade cellulose may be responsible for the initial step of MTBE biodegradation.

121

Tables and figures
Table 5. 1. The sources and conditions investigated for anaerobic MTBE degradation potential.

Inoculum type

Electron
acceptor
sulfate

Degr

Comment

Contaminated soil 1

Incubation
time
1 year

No

Contaminated soil 1
Contaminated soil 2

1 year
1 year

nitrate
sulfate

No
No

Contaminated soil 2
Agricultural soil 1
Agricultural soil 1
Agricultural soil 1
Agricultural soil 2

1 year
1 year
1 year
1 year
1 year

nitrate
sulfate
nitrate
carbon dioxide
sulfate

No
No
No
No
No

Agricultural soil 2
Agricultural soil 2
Agricultural soil 2
Agricultural soil 3
Agricultural soil 3
Agricultural soil 3
Granular sludge
Granular sludge
Granular sludge
Activated sludge

1 year
1 year
1 year
1 year
1 year
1 year
1 year
1 year
1 year
1 year

nitrate
carbon dioxide
sulfate
sulfate
nitrate
carbon dioxide
sulfate
nitrate
carbon dioxide
sulfate

No
No
No
No
No
No
No
No
No
No

Activated sludge
Activated sludge

1 year
2 months

nitrate
carbon dioxide

No
Yes

Digester sludge
Digester sludge
Digester sludge

1 year
1 year
1 year

sulfate
nitrate
carbon dioxide

No
No
No

Samples obtained from a previously MTBE contaminated LUST
site
Same soil as above
Samples obtained from a previously MTBE contaminated LUST
site
Same soil as above
Samples obtained from a farm located at Michigan,
Same soil as above
Same soil as above
Samples obtained from a farm located at Michigan, the crop is
soybean
Same soil as above
Same soil as above
Same soil as above
Samples obtained from a farm located at Michigan, the crop is corn
Same soil as above
Same soil as above
Samples obtained from a UASB reactor in Washington
Same sludge as above
Same sludge as above
Samples obtained from East Lansing WWTP. The sludge was
taken from the aeration tank of the WWTP.
Same sludge as above
Same sludge as above,~90% MTBE removal, Significant methane
production
Samples obtained from St.Clair WWTP.
Same sludge as above
Same sludge as above
122

Table 5.2. Phylogenetic affiliation of bacterial 16S rRNA clone in methanogenic MTBE degrading microcosms as determined with the
RDP analysis tool “classifier”
Number
Soil/Fragment Enriched in
of
Phylum
Class
Order
Genus
(Hae III
heavy
digestion)
fractions
clones
39 bp
N
2
Bacteroidetes
Bacteroidia
Bacteroidales
unclassified
39 bp
N
6
Proteobacteria Gammaproteobacteria Xanthomonadales
Dokdonella
39 bp
N
3
Proteobacteria
Alphaproteobacteria
unclassified
39bp,76 bp
N
3
Proteobacteria
Deltaproteobacteria
Myxococcales
Kofleria
75,251
3
N
Bacteroidetes
Sphingobacteria
Sphingobacteriales
Haliscomenobacter
71bp,227 bp
Y
18
Proteobacteria
Alphaproteobacteria
Sphingomonadales
Sphingopyxis
190 bp
N
1
Proteobacteria
Alphaproteobacteria
unclassified
198 bp
3
N
Proteobacteria
Betaproteobacteria
unclassified
200 bp
N
4
Proteobacteria Gammaproteobacteria Xanthomonadales
Aquimonas
212bp
3
N
Firmicutes
Clostridia
Clostridiales
217 bp
16
N
Proteobacteria
Betaproteobacteria
Burkholderiales
Simplicispira
217 bp,224
bp,266
bp,349bp
Y
12
Firmicutes
Clostridia
Clostridiales
unclassified
219 bp
2
N
Proteobacteria
Betaproteobacteria
Burkholderiales
Methylibium
221 bp
N
3
Tenericutes
Mollicutes
Acholeplasmatales
Acholeplasma
224 bp
4
N
Verrucomicrobia
Subdivision5
unclassified
Subdivision5
231 bp
5
N
OP10
unclassified
OP10
240 bp,318
bp
N
2
Firmicutes
Clostridia
Clostridiales
248 bp
N
4
Lentisphaerae
Lentisphaeria
Victivallales
Victivallis
255 bp
N
3
Firmicutes
Erysipelotrichi
Erysipelotrichales
unclassified
264 bp
N
6
Nitrospira
Nitrospira
Nitrospirales
Nitrospira
265 bp
N
3
Proteobacteria
Deltaproteobacteria
Myxococcales
unclassified
268 bp
N
1
Acidobacteria
Acidobacteria_Gp3
unclassified
Gp3
290 bp
N
5
Firmicutes
Clostridia
Clostridiales
Sporacetigenium
293bp
1
N
Proteobacteria
unclassified

123

Table 5.3. Phylogenetic affiliation of Archaeal 16S rRNA clone in methanogenic MTBE degrading microcosms as determined with
the RDP analysis tool “classifier”

Soil/Fragment(Hae
III digestion)

135 bp
138 bp
135 bp
400 bp
162 bp
28 bp,135 bp
150 bp

Enriched in
13
C heavy
fractions
N
Y
Y
N
Y
N
N

Number
of

Phylum

Class

clones
4
12
15
3
18
11
9

Euryarchaeota
Euryarchaeota
Euryarchaeota
Euryarchaeota
Euryarchaeota
Euryarchaeota
Euryarchaeota

Methanomicrobia
Methanomicrobia
Methanomicrobia
Methanomicrobia
Methanomicrobia
Methanomicrobia
Methanomicrobia

124

Order

Methanomicrobiales
Methanosarcinales
Methanomicrobiales

Genus

Methanosarcina
Methanoculleus

Methanomicrobiales Methanocorpusculum
Methanomicrobiales
Methanospirillum
Methanosarcinales
Methanosaeta

Table 5.4. Comparison of fragment length of dominant T-RF in heavy fractions to predicted
fragment length from in silico sequence analyses

Microorganism

Restriction
enzyme

TRFLP

Sequence data

Ruminococcaceae

HaeIII

215

217

MspI

199

204

MSEI

588

583

RsaI

453

450

Microorganism

Restriction
enzyme

TRFLP

Sequence data

Sphingomonadaceae

HaeIII

67

71

MspI

147

150

MSEI

418

422

RsaI

507

506

125

MTBE concentration (mg/L)

30

20

10

0
-5.00

5.00

15.00
Time (days)

25.00

35.00

12

Figure 5.1. MTBE concentration over time in C-MTBE amended abiotic controls (♦),
13

12

C-MTBE (■) and C-MTBE (□) amended samples. The arrows indicate when DNA was
extracted. The error bars represent standard deviations from triplicate microcosms.

126

TRFLP Relative Abundance (%

60

40

20

0
1.69

1.71

1.73

1.75

1.77

1.79

DNA Buoyant Density (g/mL)

Figure 5.2. Percent relative abundance of fragments (digested by Hae III) assigned to
Clostridiales within buoyant density gradients of Bacterial DNA extracted from the
13
methanogenic activated sludge microcosms. Figure symbols: ♦ C-MTBE (~30% toluene
13

12

degraded); ■ C-MTBE (~70% toluene degraded); □ C-MTBE (~70% toluene degraded).

127

TRFLP Relative Abundance (%

60

40

20

0
1.69

1.71

1.73

1.75

1.77

1.79

DNA Buoyant Density (g/mL)

Figure 5.3. Percent relative abundance of fragments (digested by Hae III) assigned to
Sphingomonadales within buoyant density gradients of Bacterial DNA extracted from the
13
methanogenic activated sludge microcosms. Figure symbols: ♦ C-MTBE (~30% toluene
13

12

degraded); ■ C-MTBE (~70% toluene degraded); □ C-MTBE (~70% toluene degraded).

128

TRFLP Relative Abundance (%

40

20

0
1.69

1.71

1.73

1.75

1.77

DNA Buoyant Density (g/mL)

Figure 5.4. Percent relative abundance of fragments (digested by Hae III) assigned to
Methanosarcina within buoyant density gradients of Archaeal DNA extracted from the
13
methanogenic activated sludge microcosms. Figure symbols:■ C-MTBE (~70% toluene
12

degraded); □ C-MTBE (~70% toluene degraded).

129

TRFLP Relative Abundance (%

40

20

0
1.69

1.71

1.73

1.75

1.77

DNA Buoyant Density (g/mL)

Figure 5.5. Percent relative abundance of fragments (digested by Hae III) assigned to
Methanocorpusculum within buoyant density gradients of Archaeal DNA extracted from the
13
methanogenic activated sludge microcosms. Figure symbols:■ C-MTBE (~70% toluene
12

degraded); □ C-MTBE (~70% toluene degraded).

130

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131

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