ASSESSING THE BIODEGRADATION OF TOLUENE, ETHYLBENZENE AND RDX
AND THE IDENTIFICATION OF THE MICROORGANISMS INVOLVED USING
STABLE ISOTOPE PROBING AND HIGH THROUGHPUT AMPLICON
SEQUENCING
By
Indumathy Jayamani

A DISSERTATION
Submitted to
Michigan State University
In partial fulfillment of the requirements
for the degree of
Environmental Engineering – Doctor of Philosophy
2015

ABSTRACT
ASSESSING THE BIODEGRADATION OF TOLUENE, ETHYLBENZENE AND RDX AND
THE IDENTIFICATION OF THE MICROORGANISMS INVOLVED USING STABLE
ISOTOPE PROBING AND HIGH THROUGHPUT AMPLICON SEQUENCING
BY
Indumathy Jayamani
Contamination of groundwater by organic pollutants is a worldwide environmental problem.
Bioremediation is a viable option for cleaning and reclaiming sites contaminated with pollutants
amenable to microbial transformation. However, our understanding of microorganisms playing
key roles in bioremediation is still developing. In this study, specific aspects of biodegradation of
three organic pollutants namely toluene, ethylbenzene and the nitramine explosive hexahydro1,3,5-trinitro-1,3,5-triazine (RDX) were investigated. The overall objectives of this research
were to 1) assess the biodegradation potential of toluene, ethylbenzene and RDX using soils
from various sources, 2) identify the major groups of microorganisms responsible for the
degradation of ethylbenzene and RDX in these samples and 3) assess the effect of a potential cocontaminant, isobutanol, on toluene biodegradation.
The first study examined the effect of isobutanol on the biodegradation of toluene under
sulfate amended, nitrate amended or methanogenic conditions. The results indicated that toluene
biodegradation was not greatly affected by isobutanol in five of the six experimental set-ups.
However, toluene biodegradation was completely inhibited in one set of microcosms amended
with sulfate and inocula from wastewater treatment plant activated sludge. This suggests that if
co-contamination occurs, in some cases toluene degradation may be inhibited. In the second
study, stable isotope probing (SIP) and high throughput sequencing were used with ethylbenzene
degrading consortia to identify microorganisms benefiting from 13C label uptake from

ethylbenzene (or metabolites). Several phylotypes were relatively more abundant in the heavy
fractions from the labeled ethylbenzene amended soil microcosms compared to the controls
indicating 13C label uptake. This included phylotypes within the families Oxalobacteraceae,
Rhodospirillaceae, Xanthomonadaceae and Rhodocyclaceae (Proteobacteria) as well as the
genus Gemmatimonas. This work indicates microorganisms not previously linked to
ethylbenzene degradation could have significant roles in the carbon uptake from this pollutant.
The third and fourth studies involved applying SIP and high throughput sequencing to
investigate RDX degrading microbial communities. In the third study, microbial communities
obtained from four soils previously unexposed to explosives were investigated. Sequences from
the total DNA extracts of all soils illustrated an increase in abundance of Brevundimonas and/or
unclassified Bacillaceae 1 compared to the microbial communities in the initial soil or no RDX
treatments. The fourth study investigated a RDX degrading community obtained from a Navy
Base previously contaminated with explosives with and without glucose. The microbial
communities in the total DNA samples indicated phylotypes classing as Pseudomonadaceae and
Acinetobacter was more abundant in the presence and absence of glucose respectively. The SIP
study also found that unclassified Pseudomonadaceae were primarily responsible for label
uptake in both treatments. When glucose was present, Comamonas also increased in abundance
following RDX degradation and was enriched in the heavy fractions, suggesting, for the first
time, that this phylotype is also important for RDX removal. Overall, these data suggest both
novel RDX degraders and previously reported RDX degraders were associated with RDX
removal in these soils.

Dedicated to all the great people in my life

iv

ACKNOWLEDGEMENTS

This journey was a life changing experience and was made possible by many kind hearts. While
the space here might not allow me to list all, I will do my best to list most. First of all, I am very
grateful for this opportunity to conduct doctoral research in this field and sincerely thank my
research advisor and mentor Dr. Alison M. Cupples for that. She has been nothing less of
supportive, encouraging and patient throughout the course of my studies. She has seen me
through my ups and downs and I am grateful for her trust in my work. I also would like to thank
my dissertation committee members Dr. Syed Hashsham, Dr. Irene Xagoraraki and Dr.Terrence
Marsh, whose guidance, support and comments makes this work complete. I would also like to
extend my thanks to my mentors from Dr. Cupples group, Dr. Weimin Sun, Dr. Chunlin Luo and
Dr. Shuguang Xie, who helped me learn the basics of the work that I present here. I am also
indebted to Dr. Weimin Sun for providing me enrichment culture samples for the work presented
in chapter 2. I am grateful to Yanlyang Pan for his assistance with the analytical instruments.
Special thanks to my friend and colleague Fernanda Paes for the numerous discussions and
evenings of bouncing ideas off each other and for her constant support through my studies. I am
also thankful to Hanna Miller, Alyse Way, Kathyleen Haynes and Jordyn Davis who helped me
as part of their undergraduate research work. I owe my gratitude to members of Dr.Hashsham’s,
Dr. Xagoraraki’s and Dr. Voice’s laboratory - Dr. Robert D. Stedfeld, Tiffany L. Stedtfeld, Dr.
Amanda Herzog, Maggie Kronlein, Mariya Munir, Amira Oun and Chaiyanun Tangtong for
letting me share their instruments and for the countless research discussions. I am also grateful to
my teaching mentor Dr. Masten for her tremendous support. I would also like to extend my
thanks to my colleagues Yang Song, Liang Ding, Jean Rene Thelusmond and Yogendra

v

Kanitkar. Thanks to Lori Larner, Margaret Connor, Mary Morz and Laura Taylor for their
support during my studies.
The research work presented here was funded by two different research grants funded to Dr.
Cupples and I am grateful for that (National Science Foundation grant number 0853249 and
Strategic Environmental Research and Development Program, Project ER1606). My sincere
thanks to members of Dr. Patrick Schloss laboratory at University of Michigan, particularly Ms.
Sarah Wescott for her advice during the Mothur analysis. Also thanks to Dr. Mark E. Fuller and
Dr. Paul Hatzinger (CB&I Federal Services) for providing samples from the Navy Base Site for
the work presented in chapter 5. Thanks also to all my friends and family in Michigan providing
me a home away from home. Last but not least, I am grateful to my husband Purushotham
Pakala for his love and support through my endeavors.

vi

TABLE OF CONTENTS
LIST OF TABLES…………………………………………………………………………………..ix
LIST OF FIGURES………………………………………………………………………………….x
KEY TO ABBREVIATIONS………………………………………………………………………..xiii
CHAPTER 1 INTRODUCTION ............................................................................................................ 1
GROUNDWATER POLLUTION BY BTEX AND RDX ....................................................................... 1
BIODEGRADATION OF TOLUENE, ETHYLBENZENE AND RDX ....................................................... 1
STABLE ISOTOPE PROBING AND HIGH THROUGHPUT SEQUENCING .............................................. 3
OBJECTIVES .................................................................................................................................. 3
REFERENCES ................................................................................................................................ 7
CHAPTER 2 EFFECT OF ISOBUTANOL ON TOLUENE BIODEGRADATION IN NITRATE AMENDED,
SULFATE AMENDED AND METHONOGENIC ENRICHMENT MICROCOSMS.................................. 13
ABSTRACT .................................................................................................................................. 13
INTRODUCTION ........................................................................................................................... 14
METHODS ................................................................................................................................... 16

Microcosm preparation .......................................................................................................... 17
Analytical methods ................................................................................................................ 17
RESULTS AND DISCUSSION ......................................................................................................... 18
CONCLUSIONS ............................................................................................................................ 21
APPENDIX ................................................................................................................................... 23
REFERENCES .............................................................................................................................. 31
CHAPTER 3 STABLE ISOTOPE PROBING AND HIGH THROUGHPUT SEQUENCING IMPLICATES
OXALOBACTERACEAE, RHODOSPIRILLACEAE, XANTHOMONADACEAE AND RHODOCYCLACEAE IN
ETHYLBENZENE DEGRADATION .................................................................................................. 35
ABSTRACT .................................................................................................................................. 35
INTRODUCTION ........................................................................................................................... 36
METHODS ................................................................................................................................... 39

Chemicals .............................................................................................................................. 39
Development of Ethylbenzene Degrading Microcosms ........................................................ 39
Analytical Techniques ........................................................................................................... 40
DNA Extraction and Isopycnic Centrifugation ..................................................................... 41
High Throughput Amplicon Sequencing (Illumina MiSeq) .................................................. 42
Cloning and Sanger Sequencing ............................................................................................ 43
RESULTS ..................................................................................................................................... 44
Ethylbenzene Biodegradation ................................................................................................ 44
High Throughput Amplicon Sequencing Analysis................................................................ 44
Microbial Community in Ethylbenzene Degrading Microcosms .......................................... 45
16S rRNA Gene Clone Library ............................................................................................. 47
Phylotype Relative Abundance Across SIP Fractions........................................................... 48
DISCUSSION ................................................................................................................................ 49

vii

APPENDIX ................................................................................................................................... 52
REFERENCES .............................................................................................................................. 61
CHAPTER 4 COMPARATIVE STUDY OF RDX DEGRADING MICROBIAL COMMUNITIES IN FOUR
SOILS ............................................................................................................................................. 68
ABSTRACT .................................................................................................................................. 68
INTRODUCTION ........................................................................................................................... 69
METHODS ................................................................................................................................... 72

Chemicals .............................................................................................................................. 72
Experimental Design ............................................................................................................. 72
RDX Extraction and Analysis ............................................................................................... 73
DNA Extraction and Isopycnic Centrifugation ..................................................................... 74
Amplicon Sequencing and Data Analysis ............................................................................. 75
RESULTS AND DISCUSSION ......................................................................................................... 76
RDX Degradation .................................................................................................................. 76
Comparison at Phyla Level ................................................................................................... 76
Microbial Community Analysis ............................................................................................ 78
Phylotypes Increasing in Abundance Following RDX Degradation ..................................... 80
Phylotypes Indicated In Label Uptake .................................................................................. 82
APPENDIX ................................................................................................................................... 85
REFERENCES .............................................................................................................................. 97
CHAPTER 5 STABLE ISOTOPE PROBING REVEALS THE IMPORTANCE OF COMAMONAS AND
PSEUDOMONADACEAE IN RDX DEGRADATION IN SAMPLES FROM A NAVY DETONATION SITE

..................................................................................................................................................... 105
ABSTRACT ................................................................................................................................ 105
INTRODUCTION ......................................................................................................................... 106
METHODS ................................................................................................................................. 109
Chemicals ............................................................................................................................ 109
Experimental Setup and DNA Extraction ........................................................................... 109
Analytical Methods ............................................................................................................. 110
Isopycnic Centrifugation ..................................................................................................... 111
Illumina MiSeq™ High Throughput Amplicon Sequencing .............................................. 112
Data Analysis....................................................................................................................... 113
RESULTS ................................................................................................................................... 114
DISCUSSION .............................................................................................................................. 117
APPENDIX ................................................................................................................................. 122
REFERENCES ............................................................................................................................ 129

viii

LIST OF TABLES

Table 2.1. Experimental setup for nitrate amended, sulfate amended and methanogenic toluene
degrading samples. ........................................................................................................................ 24
Table 3.1. Buoyant density of heavy fractions from the labeled and unlabeled samples submitted
for amplicon sequencing. .............................................................................................................. 53
Table 3.2. Summary MiSEQ Illumina data generated from the fractions as well as total DNA
extracted from labeled and unlabeled ethylbenzene amended microcosms ................................. 53
Table 3.3. Classification of 16S rRNA gene clones in the clone library. .................................... 54
Table 4.1. The properties of the four agricultural soils used in this study. .................................. 86
Table 4.2. A summary of MiSEQ Illumina data generated from all genomic total DNA samples
and fractions for Soil 9 and Soil 10. ............................................................................................. 86
Table 4.3. The classification of anaerobic RDX degrading isolates from previous studies. ....... 87
Table 5.1. Chao1 and Shannon and lower and upper confidence intervals (CI) values for all
microbial communities................................................................................................................ 123

ix

LIST OF FIGURES

Figure 2.1. Toluene concentrations in nitrate amended microcosms derived from enrichments
constructed from agricultural soil 1(a), agricultural soil 2 (b) and agricultural soil 3 (c). ........... 25
Figure 2.2. Toluene concentrations in sulfate amended microcosms derived from enrichments
constructed from agricultural soil 1(a) wastewater treatment plant digester sludge with 2.5 ppm
isobutanol (b), or with 5 ppm isobutanol (c)................................................................................. 26
Figure 2.3. Toluene concentrations in methanogenic microcosms derived from enrichments
constructed from wastewater treatment plant digester sludge. ..................................................... 27
Figure 2.4. Isobutanol concentrations in nitrate amended toluene degrading microcosms derived
from enrichments constructed from agricultural soil 1 (a), agricultural soil 2 (b) and agricultural
soil 3 (c). ....................................................................................................................................... 28
Figure 2.5. Isobutanol concentrations in sulfate amended toluene degrading microcosms derived
from enrichments constructed with agricultural soil 1 (a), and wastewater treatment plant
digester sludge 2.5 ppm isobutanol (b) or 5 ppm isobutanol (c). ................................................. 29
Figure 2.6. Isobutanol concentrations in methanogenic toluene degrading microcosms derived
from enrichments constructed with wastewater treatment plant digester sludge. ........................ 30
Figure 3.1. Concentration of ethylbenzene in microcosms over time ( × - abiotic controls, open
triangles - amended with 12C6 ethylbenzene, closed circles - amended with 13C6 ethylbenzene). 55
Figure 3.2. DNA concentration over the ultracentrifugation gradient in fractions from replicate
microcosms amended with labeled or unlabeled ethylbenzene. The dashed arrows indicate the
fractions that were sequenced from the unlabeled EB amended samples and solid arrows indicate
the fractions that were sequenced from the labeled EB amended samples................................... 56
Figure 3.3. Rarefaction curves generated from sequencing data from total DNA extracts for all
six microcosms.............................................................................................................................. 57
Figure 3.4. Comparison of relative abundance of sequences in total genomic DNA extracted
from six microcosms amended with 13C6 labeled or unlabeled ethylbenzene at phylum level
classification ................................................................................................................................. 58
Figure 3.5. Relative abundance (%) of the most common phylotypes (>1%, at the lowest
classification level) in all six microcosms (from total DNA extracts). The phylotypes are at the
genus level, unless unclassified. ................................................................................................... 59
Figure 3.6. Relative abundance of the most common phylotypes in heavy fractions from 13C
ethylbenzene amended microcosms compared to those from 12C ethylbenzene amended
microcosms (SIP Label EB1 and SIP Unlabel EB1 on left, SIP Label EB2 and SIP Unlabel EB2
on right). ........................................................................................................................................ 60
x

Figure 4.1. RDX in microcosms amended with labeled RDX (13C3, 15N3), unlabeled RDX (12C3,
14
N3), and killed abiotic controls for Soil 9 (A), Soil 10 (B), Soil 11 (C), Soil 12 (D). Error bars
denote standard deviation from triplicate micrososms. Arrows indicate hypothetical RDX
concentrations on the day of respike. ............................................................................................ 88
Figure 4.2. Phyla level comparison between the four soils of the communities in 1) the initial
soils (No RDX, Time 0), 2) replicates of the labeled and unlabeled RDX amended microcosms
(Labeled 1 & 2, Unlabeled 1 & 2, Time t) and 3) microcosms without RDX addition (No RDX,
Time t)........................................................................................................................................... 89
Figure 4.3. MLTree Map (A) and heatmap analysis (B) of the phylotypes within the initial soils
and in samples with and without RDX. To simplify the presentation, only one replicate was used
for the RDX amended samples. .................................................................................................... 90
Figure 4.4. Rarefaction curves (A) and Principal Component Analysis (B) of sequencing data
generated from all four soils, including total DNA extracts of the labeled RDX (Labeled 1 & 2,
Time t), unlabeled RDX (Unlabeled 1 & 2, Time t), no RDX (No RDX, Time t) microcosms and
the initial soils (No RDX, Time 0)................................................................................................ 92
Figure 4 5. A comparison of the relative abundance (%) of the most common phylotypes (>1% ,
at the lowest classification level) in all four soils in the no RDX samples, including the initial
soils (No RDX, Time 0) (A) and the microcosms without RDX (No RDX, Time t) (B). ............ 93
Figure 4.6. A comparison of the relative abundance (%) of the most common phylotypes (>1% ,
at the lowest classification level) in all four soils (A-D) following RDX degradation. ............... 94
Figure 4.7. The relative abundance (%) of the eight most abundant phylotypes in the four RDX
amended agricultural soils (Labeled 1 &2, Unlabeled 1 &2, Time t) compared to the RDX
controls (initial soil and no RDX microcosms). Boxed phylotypes illustrate a greater abundance
in RDX amended samples compared to the RDX controls for at least three soils. The phylotypes
are at genus level, unless unclassified........................................................................................... 95
Figure 4.8. Relative abundance of the most common phylotypes in heavy fractions from the
labeled RDX amended microcosms compared to those from the unlabeled RDX amended
microcosms in Soil 9 (A) and Soil 10 (B). Bars illustrate standard deviations from triplicate
sequencing data. ............................................................................................................................ 96
Figure 5.1. Relative abundance of the most common phylotypes in RDX amended microcosms
(with and without glucose) compared to their abundance in the initial soil community and no
RDX microcosms. ....................................................................................................................... 124
Figure 5.2. Rarefaction curves for the total microbial communities in the initial soil, RDX
amended microcosms and the no RDX controls for both the no glucose amended (A) and glucose
amended (B) microcosms. .......................................................................................................... 125
Figure 5.3. Relative abundance of phylotypes illustrating a difference in relative abundance
between the RDX amended microcosms and the no RDX controls (initial soil and no RDX

xi

microcosm) in the glucose amended microcosms (A) and in the microcosms that were not
amended with glucose (B). ......................................................................................................... 126
Figure 5.4. DNA concentration (ng/µL) in fractions across buoyant density gradients obtained
from samples amended with labeled and unlabeled RDX, with (A) or without (B) the addition of
glucose. Replicate lines represent duplicate DNA measurements. The shaded area represents the
fractions analyzed with Illumina sequencing. ............................................................................. 127
Figure 5.5. The three most abundant phylotypes in the heavy fractions from the labeled RDX
amended microcosms compared to their abundance in fractions of similar buoyant density from
the unlabeled RDX amended microcosms. Data are shown from those amended with glucose (A,
top three graphs) and those not amended with glucose (B, bottom three graphs). The y-axis
represents relative abundance in each fraction normalized by the DNA mass in each fraction
(relative abundance times the DNA mass (ng)). Error bars represent standard deviations from
three replicates and may be too small to be seen. ....................................................................... 128

xii

KEY TO ABBREVIATIONS

BTEX - benzene, toluene, ethylbenzene and o-, p-, and m-xylenes
CFR – Code of Federal Regulations
DGGE – Denaturing gradient gel electrophoresis
DNA - deoxyribonucleic acid
LUST – leaking underground storage tanks
OTU - operational taxonomic unit
PCR - polymerase chain reaction
RDX – royal demolition explosive (hexahydro-1,3,5-trintro-1,3,5-triazine)
rRNA - ribosomal RNA
SIP – stable isotope probing
TRFLP - terminal restriction fragment length polymorphism

xiii

CHAPTER 1 INTRODUCTION

GROUNDWATER POLLUTION BY BTEX AND RDX
The chemicals benzene, toluene, ethylbenzene and the xylenes, collectively known as BTEX
compounds, are a major source of groundwater contamination from leaking gasoline tanks.
According the USEPA, as of March 2014, over half of a million releases have been confirmed in
the United States from underground storage tanks (UST) containing gasoline (1). Groundwater
contamination near military sites with the nitroamine explosive hexahydro-1,3,5-trinitro-1,3,5triazine (RDX) is widespread due to the explosives manufacturing and handling particularly
after World War II (2). Groundwater contamination by such organic pollutants threatens drinking
water sources due to their toxic health effects. Bioremediation is a viable remedy option for these
contaminants as they are amenable to bacterial degradation. In situ biodegradation of organic
pollutants can depend on numerous factors including the microbial community, nutrient
availability, physical and chemical factors and co-contaminant effects. It is also more appropriate
to consider degradation of such pollutants under anaerobic conditions (as groundwater is often
depleted in oxygen). The research presented in this thesis relates to the microorganisms involved
in the biodegradation of the organic contaminants toluene, ethylbenzene and RDX.

BIODEGRADATION OF TOLUENE, ETHYLBENZENE AND RDX
Microorganisms that are able to metabolize or mineralize toluene under nitrate reducing (3-6),
iron reducing (7, 8) and sulfate reducing (9) conditions have been isolated thus far. However,

1

very little is known about the effects of a potential co-contaminant (isobutanol) on toluene
degradation. To date, only three studies have investigated the effect of isobutanol on BTEX, two
under aerobic conditions (10, 11) and one under anaerobic conditions(12). In this study, we
extend on knowledge by investigating the effect of isobutanol on toluene (a model BTEX
compound) in six different toluene degrading communities.

In contrast to toluene, only five anaerobic ethylbenzene degrading isolates exist. Among these,
four can degrade ethylbenzene under nitrate reducing conditions (13). These include two
Azoarcus sp. strains (Aromatoleum aromaticum EbN1 and EB1) (14-16) , Dechloromonas
aromatica RCB (6, 17), Georgfuchsia toluolica (18) and Desulfobacteraceae Strain EbS7 (19).
Interestingly, all except Strain EbS7 (Deltaproteobacteria) belong to the family Rhodocyclaceae
(Betaproteobacteria).

Compared to the BTEX chemicals, many microorganisms have been associated with RDX
degradation. Many anaerobic RDX degraders have been isolated from the phyla Proteobacteria
(20-32) and Firmicutes (21, 29, 33-38) with one in the phylum Fusobacteria (28). Although
contaminant degradation has been confirmed with pure cultures, it is still uncertain if these
isolates can degrade ethylbenzene or RDX when present in a mixed culture. To address this
unknown, stable isotope probing (SIP) was used in this research to link function to identity in
mixed communities.

2

STABLE ISOTOPE PROBING AND HIGH THROUGHPUT SEQUENCING
SIP involves amending a stable isotope labeled (e.g. 13C, 15N) compound to a mixed microbial
community, such as a soil or water sample (39). Isopycnic centrifugation of the extracted DNA
in cesium chloride gradients allows the DNA to band based on it’s buoyant density. Thus, this
technique allows the separation of DNA that has incorporated the label (heavy DNA) from the
background community DNA (unlabeled or light DNA). SIP studies have been used to identify
microorganisms involved in biogeochemical cycles (40, 41) and environmental pollutant
remediation (42-45). These studies employed finger printing techniques such as denaturing
gradient gel electrophoresis (DGGE), terminal restriction fragment length polymorphism
(TRFLP) and cloning and sequencing methods. Recently, researchers have combined SIP with
high throughput sequencing to obtain a greater depth of information than that achievable with
fingerprinting techniques or Sanger sequencing. (46-48). In this study, we combined SIP with
high throughput amplicon sequencing (MiSeq Illumina) to identify the microorganisms in mixed
communities involved in ethylbenzene/RDX biodegradation.

OBJECTIVES
The overall objectives were,
i)

To assess toluene, ethylbenzene and RDX biodegradation potential in soils from
various sources.

ii)

To identify the major groups of microorganisms responsible for degradation of
ethylbenzene and RDX.

iii)

To assess the effect of a potential co-contaminant, isobutanol, on toluene
biodegradation.

3

Specific objectives addressed in each chapter are as follows:
1. To assess the effect of a potential co-contaminant (isobutanol) on a model gasoline
compound (toluene) under various electron acceptor conditions in laboratory microcosms
(Chapter 2).
2. To identify the microorganisms responsible for carbon uptake from ethylbenzene under
oxygen depleted conditions (Chapter 3).
3. To determine and compare the dominant RDX degraders in four uncontaminated soils
and in a soil from a contaminated site (Chapters 4 and 5).

The research work presented under Chapters 2 and 3 were funded by an NSF grant awarded to
Dr. Cupples entitled “Stable isotope probing to assess bioremediation of LUST contaminants:
addressing existing MTBE/BTEX and probably future ethanol/BTEX contamination”. Chapter 2
addresses specific objective 1 and involved the investigation of isobutanol on toluene
degradation in six toluene degrading communities. The results indicated that isobutanol had
varying effects on toluene biodegradation. A modified version of the work in Chapter 2 was
published (Jayamani, I and A. M. Cupples. 2013. Effect of isobutanol on toluene biodegradation
in nitrate amended, sulfate amended and methanogenic enrichment microcosms. Biodegradation,
24: 657-663).

The study on ethylbenzene degradation under oxygen depleted conditions in agricultural soils is
presented in Chapter 3. This study involved the investigation of ethylbenzene degradation in ~30
different experimental set-ups (different soils and redox conditions). From these, ethylbenzene
degradation was noted only once. For this condition (nitrate reducing conditions in an

4

agricultural soil), SIP and amplicon sequencing were used to identify the dominant ethylbenzene
degrading microorganisms. . Bacteria belonging to the families Oxalobacteraceae,
Rhodospirillaceae, Xanthomonadaceae and Rhodocyclaceae and the genus Gemmatimonas were
linked to the assimilation of the ring labeled carbon from ethylbenzene. The sequencing data
from the total DNA extracts from the ethylbenzene degrading microcosms showed that
phylotypes belonging to the genus Rhodanobacter were the most dominant microorganisms. The
work presented under Chapter 3 has been submitted for publication to a peer reviewed journal.

The research work presented in Chapters 4 and 5 were funded by a Strategic Environmental
Research and Development Program (SERDP) grant entitled “Development of biomarkers for
assessing in situ RDX biodegradation potential” awarded to Dr. Cupples. In Chapter 4, a
comparative study of RDX degrading microbial communities obtained from four different
uncontaminated soil sources is presented. Illumina sequencing revealed that phylotypes
classifying either within the family Bacillaceae 1 (contains RDX isolates) or the genus
Brevundimonas (no known RDX degrading isolates) were the most abundant phylotypes in all
four soils. In addition, a SIP study was conducted with samples for two of the soils (soil 9 and
soil 10). In soil 9, sequences classifying as Bacillaceae, Clostridiales and Tisserella were the
most abundant in the heavy labeled fractions compared to the control unlabeled fractions. In soil
10, phylotypes belonging to Pusillimonas, Rhodococcus, Sedimentibacter were enriched in the
heavy labeled fractions in comparison to the fractions obtained from the unlabeled samples. The
work presented under this chapter is being prepared for publication.

5

Chapter 5 involves the use of SIP and high throughput sequencing to identify the
microorganisms responsible for RDX degradation in soils obtained from an area used to test
denotations (a Navy Base in Virginia, US). This work also explores the use of glucose as an
amendment to promote RDX degradation. Members of the Pseudomonadaceae, Comamonas
(with glucose samples) and Acinetobacter (no glucose samples) were observed as the most
abundant phylotypes in the total DNA extracts. Members of the Pseudomonadaceae family were
also linked to label uptake from RDX, both in the presences and absence of glucose. The work in
Chapter 5 has been submitted for publication to a peer reviewed journal.

6

REFERENCES

7

REFERENCES

1.

EPA 2014, posting date. Underground Storage Tanks. [Online.]

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Pennington JC, Brannon JM. 2002. Environmental fate of explosives. Thermochimica
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Dolfing J, Zeyer J, Bindereicher P, Schwarzenbach RP. 1990. Isolation and
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4.

Schocher RJ, Seyfried B, Vazquez F, Zeyer J. 1991. Anaerobic degradation of toluene
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Evans P, Mang D, Kim KS, Young L. 1991. Anaerobic degradation of toluene by a
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Chakraborty R, O'Connor SM, Chan E, Coates JD. 2005. Anaerobic degradation of
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Lovley DR, Lonergan DJ. 1990. Anaerobic oxidation of toluene, phenol, and paracresol by the dissimilatory iron-reducing organism, GS-15. Applied and Environmental
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Kunapuli U, Jahn MK, Lueders T, Geyer R, Heipieper HJ, Meckenstock RU. 2010.
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Beller HR, Spormann AM, Sharma PK, Cole JR, Reinhard M. 1996. Isolation and
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10.

Schaefer CE, Yang XM, Pelz O, Tsao DT, Streger SH, Steffan RJ. 2010. Aerobic
biodegradation of iso-butanol and ethanol and their relative effects on BTEX
biodegradation in aquifer materials. Chemosphere 81:1104-1110.

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Ding L, Cupples AM. 2014. The effect of the potential fuel additive isobutanol on
benzene, toluene, ethylbenzene, and p-xylene degradation in aerobic soil microcosms.
Environmental Technology:1-8.

12.

Schaefer CE, Yang XM, Pelz O, Tsaob DT, Streger SH, Steffan RJ. 2010. Anaerobic
biodegradation of iso-butanol and ethanol and their relative effects on BTEX
biodegradation in aquifer materials. Chemosphere 81:1111-1117.

8

13.

Weelink SAB, van Eekert MHA, Stams AJM. 2010. Degradation of BTEX by
anaerobic bacteria: physiology and application. Rev Environ Sci Bio 9:359-385.

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45.

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46.

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11

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Pyro-SIP. Fems Microbiology Ecology 78:165-175.

12

CHAPTER 2 EFFECT OF ISOBUTANOL ON TOLUENE BIODEGRADATION IN
NITRATE AMENDED, SULFATE AMENDED AND METHONOGENIC
ENRICHMENT MICROCOSMS

ABSTRACT
Isobutanol is an alternate fuel additive that is being considered because of economic and lower
emission benefits. However, future gasoline spills could result in co-contamination of isobutanol
with gasoline components such as benzene, toluene, ethyl-benzene and xylene (BTEX). Hence,
isobutanol could affect the degradability of gasoline components thereby having an effect on
contaminant plume length and half-life. In this study, the effect of isobutanol on the
biodegradation of a model gasoline component (toluene) was examined in laboratory
microcosms. For this, toluene and isobutanol were added to six different toluene degrading
laboratory microcosms under sulfate amended, nitrate amended or methanogenic conditions.
While toluene biodegradation was not greatly affected in the presence of isobutanol in five out of
the six different experimental sets, toluene degradation was completely inhibited in one set of
microcosms. This inhibition occurred in sulfate amended microcosms constructed with inocula
from wastewater treatment plant activated sludge. Our data suggest that toluene degrading
consortia are affected differently by isobutanol addition. These results indicate that, if cocontamination occurs, in some cases the in situ half-life of toluene could be significantly
extended.

13

INTRODUCTION
Various additives have been added to gasoline in an effort to minimize the emissions and to
reduce non-renewable fuel dependency. Approximately 77% of all gasoline in the US contained
alcohol up to 10% v/vol as of the year 2009 (1). Currently, biologically produced isobutanol is
being considered as an alternative gasoline additive as it convenient to use with existing car
engines and pipelines, can be used pure or at any blend ratio and also can be mixed offsite (2). A
recent success in obtaining microbially produced isobutanol from cellulosic material such as
corn stove waste by genetically engineered bacterium (3) adds to the benefits of switching to
isobutanol as a gasoline additive. However, assuming that future spills are inevitable, it would be
wise to have an understanding of the fate of isobutanol in the environment as well as any effect it
might have on the biodegradation of other gasoline components.

Previous research has revealed ethanol affects the fate of gasoline components in the
environment. For example, due to its high hygroscopic nature, ethanol was found to produce a
co-solvency effect resulting in increased BTEX aqueous concentrations (4, 5) and plume lengths
(6). Ethanol is also preferentially degraded, causing depletion of oxygen, resulting in the
inhibition of benzene degradation (7, 8). Further, ethanol biodegradation can consume subsurface
nutrients and electron acceptors that would otherwise have been available for BTEX degradation
(9). This in turn alters the composition of the local microbial population which could further
result in reduced BTEX degradation (10). The concentration of ethanol also appears to affect
BTEX degradation. At low ethanol concentrations, it was found to enhance BTEX
biodegradation, in particular both aerobic and anaerobic benzene biodegradation (11, 12). In

14

contrast, at higher concentrations, ethanol decreased the degradation rates BTEX compounds (9,
11, 13).

As ethanol exerts a high biochemical oxygen demand on the system, it is more relevant to
discuss the effect of ethanol on BTEX biodegradation under anaerobic conditions (7). Corseiul et
al.(1998) reported ethanol’s detrimental effect on toluene degradation under iron and
methanogenic conditions, but enhanced toluene degradation under sulfate reducing conditions
(14). Others have reported only slight toluene degradation under denitrifying conditions (15). In
contrast, Da Silva et al. (2005) reported that though ethanol was inhibitory under methanogenic
conditions, it enhanced BTEX biodegradation with the addition of electron acceptors (12). At
higher ethanol concentrations most studies report slow or no BTEX biodegradation (9, 11, 12,
15-17). Similar contradicting results were obtained in biodegradation studies with n-butanol, an
isomer of isobutanol. N-butanol while enhancing biodegradation of gasoline (18), was also found
to be toxic to cell growth even at a concentration of 1% v/v (19).

To date, only three studies (three aerobic and one anaerobic) have investigated the impact of
isobutanol on BTEX biodegradation (20-22). Two of the studies used soil and groundwater
samples collected from the same contaminated site in CA (20, 21) and found isobutanol had
varying effects on BTEX degradation. The third study (22) used several agricultural soils
degrading one or more of the BTEX compounds under aerobic conditions and concluded that
isobutanol does not affect aerobic BTEX degradation. Here, we expand on this research by
investigating the effect of isobutanol in six microbial communities derived from four different
sources. The objective was to determine if the effect of isobutanol varied between samples from

15

different sources (i.e. different microbial communities). More specifically, the effect of
isobutanol on toluene degradation was investigated under nitrate amended, sulfate amended and
methanogenic conditions, using samples from different sources. Toluene was selected as the
representative BTEX compound because previous work in our laboratory identified the toluene
degrading species in a number of these communities using stable isotope probing (SIP) (23).
Thus, this enabled us to link the effect of isobutanol of specific toluene degrading species.

METHODS
The effect of isobutanol on toluene degradation was investigated in seven different experiments
prepared using inocula from enrichment cultures previously developed in our laboratory. Of
these, toluene was degraded under either methanogenic (one experiment), sulfate amended (three
experiments), or nitrate amended (three experiments) conditions (Table 2.1). Each experiment
consisted of 12 sample (live) microcosms and 2 control (killed) microcosms.

The microcosms for the methanogenic experiment were prepared using wastewater treatment
plant digester sludge. The microcosms for the three nitrate amended experiments were prepared
using either one of the three agricultural soils (corn crop) obtained from three different sources,
two with low organic matter (agricultural soil 1 and 2) and one with high organic matter
(agricultural soil 3). The microcosms for two of the sulfate amended experiments were prepared
using wastewater treatment plant digester sludge and the microcosm for the third sulfate
amended experiment was prepared using agricultural soil 1. A low concentration of isobutanol (5
mg/L) was chosen for six out of the seven experiments, following previous research (21). For the

16

seventh set (sulfate amended experiment prepared with agricultural soil 1) the isobutanol
concentration was still lower (~2.5 mg/L).

Microcosm preparation
All microcosms were prepared under strictly anaerobic conditions in an anaerobic chamber (Coy
Laboratory Products, Grass Lake, MI). The microcosms were prepared in 60 mL clear wheaton
serum bottles (Fisher scientific, Pittsburgh, PA) by adding 0.5 to 1 mL of enrichment culture to
40 mL of basal minimal media (24). When appropriate, sterile potassium nitrate or magnesium
sulfate solution were added (final concentration of 1 g/L) as electron acceptors. The microcosms
were sealed tight with a butyl rubber stopper with PTFE coating and an aluminum seal to
maintain anaerobic conditions. Seven experiments were performed to investigate the effect of
isobutanol on toluene degradation (one methanogenic, three sulfate amended and three nitrate
amended). For each experiment, 14 microcosms were prepared, including 2 abiotic controls (heat
sterilized), 6 no isobutanol replicate microcosms and 6 replicate microcosms with isobutanol.
The concentration of isobutanol in the isobutanol containing replicate microcosms, was ~5 mg/L
in all experiments except one sulfate amended experiment prepared with wastewater sludge
enrichment, which was prepared with lower isobutanol concentration(~ 2.5 mg/L). The rationale
for this extra experiment is discussed later. The microcosms were stored at room temperature
without shaking.

Analytical methods
Toluene and isobutanol concentrations were investigated over time in all microcosms. The
timing of sample removal varied depending on preliminary data collected on toluene

17

degradation. Headspace toluene concentrations were measured using a Perkin Elmer gas
chromatography equipped with a flame ionization detector (GC-FID). 200 µL headspace samples
were sampled using a gas-tight syringe and injected through a DB-624 (Agilent) capillary
column (length 30m, internal diameter 0.53mm and a film thickness of 0.5 um). Helium was
used as the carrier and at 14 psi head pressure the elution time for ethylbenzene was 1.8 minutes.
The aqueous phase toluene concentrations were calculated by applying Henry’s law. Aqueous
isobutanol concentrations were estimated using headspace isobutanol concentrations and mass
balance, using the same GC protocol.

RESULTS AND DISCUSSION
The effect of isobutanol on toluene degradation was examined in seven experiments involving
microbial communities from four different sources. As expected, toluene was degraded in all live
samples but was not significantly depleted in the controls, indicating a biological removal
mechanism. The time for toluene depletion varied, primarily depending on the electron accepting
process. While the varying levels of organic matter in the different soils could affect sorption of
toluene and thereby its bioavailability and biodegradation rates, previous studies show that it also
desorbs rapidly when biodegradation occurs (25). In microcosms amended with nitrate and
constructed with the agricultural soil 1 enrichment, toluene degraded in just over 20 days in all
12 live samples (Figure 2.1a). There was no significant difference in the time for toluene
degradation between the samples amended and those unamended with isobutanol. Toluene was
degraded more rapidly (under 5 days) in the microcosms derived from agricultural soil 2 and soil
3 enrichments (Figures 2.1b and 2.1c). Again, no effect of isobutanol on toluene degradation was
noted for these samples.

18

Toluene degraded at a much slower rate in sulfate amended experiments compared to the nitrate
amended experiments. In sulfate amended microcosms constructed from agricultural soil 1
enrichments, (Figure 2.2a), toluene degradation was completed in all live samples after
approximately 90 days. In these samples, toluene degradation rates varied between replicates
and between the treatments, with no clear trend being apparent. In contrast, in the sulfate
amended microcosms constructed from the digester sludge enrichments (Figure 2.2b and 2.2c),
toluene degradation was completely inhibited in the presence of isobutanol. Also, among the two
different sulfate amended experiments constructed from digester sludge enrichments, the time for
toluene degradation was slower in those amended with a lower concentration of isobutanol
(Figure 2.2b), which was likely because these were prepared at a later date and the enrichment
culture was less active. Toluene degradation was also slow in the methanogenic microcosms
constructed from wastewater digester sludge enrichments. In these microcosms, toluene
degradation occurred between day 60 and 137. As no measurements were taken between these
timepoints, it is difficult to conclude if isobutanol had an effect on toluene degradation during
this time (Figure 2.3). Also in these microcosms, isobutanol was in fact completely degraded by
day 34 (see below).

Isobutanol degradation varied between the different experiments. Among the nitrate amended
samples, it was slightly depleted in two of the three experiments to ~2-3 ppm (Figure 2.4a and
2.4c). In the third set of nitrate amended samples, the isobutanol concentration did not
significantly change (Figure 2.4b). In the sulfate amended samples, isobutanol degradation was
varied, taking between 21 and 118 days to degrade to ~1 ppm in the samples constructed with
agricultural soil 1 enrichments (Figure 2.5a). In contrast, in the two experiments with the

19

activated sludge samples, isobutanol degradation was rapid at both the lower (Figure 2.5b) and
higher (Figure 2.5c) isobutanol concentrations. In these samples, isobutanol was degraded by
approximately day 15. In the methanogenic toluene degrading microcosms, isobutanol degraded
rapidly and was completely depleted by day 34 (Figure 2.6). Our results show that isobutanol is
completely biodegradable in both the sulfate and nitrate amended microcosms and in the
methanogenic microcosms. Isobutanol degraded much faster and along with toluene in the nitrate
amended microcosms compared to the sulfate amended microcosms.

The presence of isobutanol had varying effects on toluene degradation in the six different
microbial communities. In all three nitrate amended toluene degrading microbial consortia, the
presence of isobutanol did not significantly alter the rate of toluene degradation. Schaefer et al
(2010b) (21) reported that isobutanol actually increased the rate of BTEX biodegradation. They
reported that isobutanol enhanced TEX biodegradation under nitrate reducing conditions and
both ethanol and isobutanol enhanced benzene biodegradation under sulfate reducing conditions.
Whereas, in the current study, in the sulfate amended samples derived from wastewater digester
sludge, isobutanol actually inhibited toluene degradation. As previously mentioned, such mixed
effects have been noted before for ethanol, where ethanol inhibited toluene degradation under
methanogenic, iron reducing and nitrate reducing conditions, yet enhanced toluene degradation
under sulfate reducing conditions (14). Schaefer et al (2010b) (21) also found that isobutanol
could have a mixed effect on toluene degradation particularly under the presence of excess
sulfate. Other studies have reported ethanol slowed TEX biodegradation rate in the absence of
any electron acceptors (12, 21). These results show that the effect of isobutanol on BTEX
biodegradation is likely not electron acceptor specific.

20

The current study found that the effect of isobutanol on toluene degradation varied between
different toluene degrading communities. The major toluene degraders in three of the six inocula
tested have been previously identified (23). The key degraders in agricultural soil 1 were
identified as members of the family Comamonadaceae. In the microcosms derived from
agricultural soil 1 enrichments, where isobutanol did not affect toluene biodegradation in sulfate
amended microcosms, the major toluene degrader was identified as a member of the genus
Desulfosporosinus. In the sulfate amended microcosms derived from digester sludge enrichments
in which toluene degradation was inhibited in the presence of isobutanol the major toluene
degrading organism was identified as a member of the family Syntrophobacteraceae. Site
specific active microbial communities are often not considered as a input parameter in numerical
models used to predict BTEX plume length (7). However, different microbial communities might
be affected differently by isobutanol as seen here, and such numerical models may provide only
partial information. Thus like ethanol the effect of isobutanol could be specific to the system in
which contamination occurs (26). To our knowledge, this is the first study that has studied the
effect of isobutanol on more than one toluene degrading consortia under different electron
acceptor conditions.

CONCLUSIONS
Isobutanol illustrated a varying effect on toluene biodegradation in the different toluene
degrading microbial communities. While the presence of isobutanol did not affect toluene
degradation in five of the six experiments under nitrate reducing, sulfate reducing or
methanogenic conditions, toluene degradation was inhibited in the digester sludge amended
sulfate reducing microcosms. Also, in the experiments in which isobutanol did not affect toluene

21

degradation, there was no apparent difference in the rate of degradation, suggesting it neither
enhanced nor inhibited toluene degradation in these microcosms. Our results suggest that the
effect of isobutanol on BTEX biodegradation could differ based on the site specific conditions,
particularly the microbial consortia and their assimilative capacity. Thus, this study supports the
need for further site specific studies on the effect of isobutanol on BTEX contaminants to further
understand the overall impact of switching to isobutanol as a gasoline additive.

22

APPENDIX

23

Table 2.1. Experimental setup for nitrate amended, sulfate amended and methanogenic toluene
degrading samples.

1

2
3
4
5
6

7

Electron
acceptor
Methanogenic

Nitrate amended

Sulfate amended

Enrichment culture
source
Wastewater
treatment plant
activated sludge
Agricultural soil 1
Agricultural soil 2
Agricultural soil 3
Agricultural soil 1
Wastewater
treatment plant
activated sludge
Wastewater
treatment plant
activated sludge

No. of microcosms
Abiotic
Live (no
isobutanol)
2
6

Live (with
isobutanol)
6

Isobutanol
concentration
(mg/L)
5

2
2
2
2
2

6
6
6
6
6

6
6
6
6
6

5
5
5
5
5

2

6

6

2.5

24

25

(a)

20
15

Toluene concentration in solution (mg/L)

10

5
0
25
(b)

20
15
10

5
0
25
20

(c)

15

10
5
0

0

5

10

15

20

25

Time (Days)
Figure 2.1. Toluene concentrations in nitrate amended microcosms derived from enrichments
constructed from agricultural soil 1(a), agricultural soil 2 (b) and agricultural soil 3 (c).
The symbols represent abiotic control [ ♦ ], toluene only [ ] and toluene and isobutanol [
amended microcosms.

25

]

30

25

(a)

20
15

10

Toluene concentration in solution (mg/L)

5
0
30

25
20

(b)

15

10
5

0
30
25

20

(c)

15
10
5

0
0

20

40

60
80
Time (Days)

100

120

140

Figure 2.2. Toluene concentrations in sulfate amended microcosms derived from enrichments
constructed from agricultural soil 1(a) wastewater treatment plant digester sludge with 2.5 ppm
isobutanol (b), or with 5 ppm isobutanol (c).
The symbols represent abiotic control [ ], toluene only [ ] and toluene and isobutanol [
amended microcosms.

26

]

Toluene concentration in
solution (mg/L)

35
30

25
20
15

10
5
0
0

25

50

75
100
Time (Days)

125

150

Figure 2.3. Toluene concentrations in methanogenic microcosms derived from enrichments
constructed from wastewater treatment plant digester sludge.
The symbols represent abiotic control [ ], toluene only [ ] and toluene and isobutanol [
amended microcosms.

27

]

Isobutanol concentration in solution (mg/L)

16
14
12
10
8
6
4
2
0
16
14
12
10
8
6
4
2
0
16

(a)

(b)

(c)

14

12
10
8
6
4

2
0

0

5

10
15
20
25
Time (Days)
Figure 2.4. Isobutanol concentrations in nitrate amended toluene degrading microcosms derived
from enrichments constructed from agricultural soil 1 (a), agricultural soil 2 (b) and agricultural
soil 3 (c).

28

12
10

8

(a)

6

Isobutanol concentration in solution (mg/L)

4

2
0
12
10
8

(b)

6

4
2
0
12
10
8

(c)

6
4

2
0
0

20

40

60
80
Time (Days)

100

120

140

Figure 2.5. Isobutanol concentrations in sulfate amended toluene degrading microcosms derived
from enrichments constructed with agricultural soil 1 (a), and wastewater treatment plant
digester sludge 2.5 ppm isobutanol (b) or 5 ppm isobutanol (c).

29

Isobutanol concentration in
solution (mg/L)

8
7

6
5

4
3

2
1

0
0

25

50

75

100

125

150

Time (Days)
Figure 2.6. Isobutanol concentrations in methanogenic toluene degrading microcosms derived
from enrichments constructed with wastewater treatment plant digester sludge.

30

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31

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Microbial and modeling studies. Journal of Environmental Engineering-Asce 128:868875.

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Powers SE, Rice D, Dooher B, Alvarez PJJ. 2001. Will ethanol-blended gasoline affect
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less harmful to the environment. Environmental Science & Technology 35:24A-30A.

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Ruiz-Aguilar GML, O'Reilly K, Alvarez PJJ. 2003. A comparison of benzene and
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Feris K, Mackay D, de Sieyes N, Chakraborty I, Einarson M, Hristova K, Scow K.
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Osterreicher-Cunha P, Guimaraes JRD, Vargas ED, da Silva MIP. 2007. Study of
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Wu YG, Li YF, Hui L, Tan Y, Jin S. 2009. Effects of Ethanol on Benzene Degradation
Under Denitrifying Conditions. Bulletin of Environmental Contamination and
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Mariano AP, Tomasella RC, Di Martino C, Maciel Filho R, Regali Seleghim MH,
Contiero J, de Angelis DdF. 2009. Aerobic biodegradation of butanol and gasoline
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34

CHAPTER 3 STABLE ISOTOPE PROBING AND HIGH THROUGHPUT
SEQUENCING IMPLICATES OXALOBACTERACEAE, RHODOSPIRILLACEAE,
XANTHOMONADACEAE AND RHODOCYCLACEAE IN ETHYLBENZENE
DEGRADATION

ABSTRACT
The overall aim was to identify the microorganisms responsible for carbon uptake from
ethylbenzene (or ethylbenzene breakdown products) in soil microcosms using culture
independent methods. Ethylbenzene degradation was observed in only one (nitrate amended
agricultural soil) of the thirty-one different experimental setups (different amendments and
inocula sources) tested. To determine which microorganisms were responsible for 13C uptake,
stable isotope probing (SIP) was combined with high throughput sequencing Illumina amplicon
sequencing. For this, total genomic DNA and heavy fraction samples (following
ultracentrifugation to separate light from heavy DNA) from the live control microcosms
(amended with 12C6 ethylbenzene) and sample microcosms (amended with 13C6 ethylbenzene)
were subject to Illumina amplicon sequencing. Several phylotypes were relatively more abundant
in the heavy fractions from the 13C6-labeled ethylbenzene amended soil microcosms compared to
the heavy fractions from the live controls (from unlabeled ethylbenzene amended microcosms).
This included unclassified phylotypes within the families Oxalobacteraceae, Rhodospirillaceae,
Xanthomonadaceae and Rhodocyclaceae (Proteobacteria) as well as the genus Gemmatimonas
(phylum Gemmatimonadetes). In addition, the total microbial community was characterized in
six ethylbenzene degrading microcosms and was dominated by the genus Rhodanobacter

35

(relative abundance 11.7 – 15.6%) (family Xanthomonadaceae), although this phylotype did not
illustrate 13C uptake. Azoarcus (family Rhodocyclaceae), a known ethylbenzene degrader, was
dominant in only two of the six microcosms (relative abundance 14.6 and 24.1%) and it also did
not illustrate label uptake. The work indicates microorganisms not previously linked to
ethylbenzene degradation have significant roles in the carbon uptake from this contaminant.

INTRODUCTION
Hydrocarbons such as benzene, toluene, ethylbenzene and xylene (BTEX) contained in gasoline
have been released into the environment by accidental spillage or from leaking underground
storage tanks. These compounds cause groundwater and sediment pollution posing an
environmental and health threat due to their toxicity and mobility. BTEX remediation using
microorganisms that can utilize these compounds as a carbon or an energy source is a feasible
solution. However, under anaerobic conditions, BTEX biological removal is typically slow.

From the BTEX chemicals, toluene is the most studied and perhaps the most readily amenable to
anaerobic biodegradation (1). Several microorganisms have been isolated that are able to
metabolize or mineralize toluene under nitrate reducing (2, 3), iron reducing (4) and sulfate
reducing (5) conditions (the majority belong to the phylum Proteobacteria and a few to
Firmicutes). Isolates have also been shown to degrade m- or o-xylene under nitrate reducing (2),
sulfate reducing (6) and iron reducing (7) conditions. In contrast, there have been reports of only
three nitrate reducing, benzene degrading isolates (8, 9). After benzene, ethylbenzene is perhaps
the next most difficult to degrade among the BTEX compounds. To date, anaerobic ethylbenzene
degradation has been shown in several nitrate reducing or sulfate reducing bacteria (1). These

36

include two Azoarcus sp. strains (Aromatoleum aromaticum EbN1 and EB1) (10-12) ,
Dechloromonas aromatica RCB (8, 13), Georgfuchsia toluolica (14) and Desulfobacteraceae
Strain EbS7 (15). Interestingly, all except Strain EbS7 (Deltaproteobacteria) belong to the
family Rhodocyclaceae (Betaproteobacteria). More information concerning the diversity of
microorganisms involved in ethylbenzene degradation would contribute to our understanding of
the biodegradation potential of this chemical at contaminated sites.

The current limited information on ethylbenzene degraders can, in part, be attributed to the
limitations associated with traditional microbiological methods (only a minor % of existing
bacteria can be cultured in the laboratory). Culture independent methods, such as stable isotope
probing (SIP), can often circumvent these limitations. For example, SIP studies have identified
novel microorganisms involved in geochemical cycles (16, 17) and in remediation of
environmental pollutants (18-21) that were not previously identified using culture based
techniques. SIP involves the addition of a labeled substrate (e.g. 13C labeled toluene) to a mixed
community, ultracentrifugation of the extracted DNA, then the analysis of the heavy fractions of
the SIP gradient to identify the phylotypes responsible for label uptake. Previously, we have used
terminal restriction fragment length polymorphism (TRFLP) and clone libraries (with traditional
Sanger sequencing) to identify the organisms enriched in the labeled treatments during SIP
experiments (22-27). However, extensive 16S rRNA gene clone libraries are needed to identify
the enriched TRFLP fragments. In fact, researchers have previously reported they were unable to
identify 25% (two out of eight) TRFLP fragments thought to be responsible for label uptake (28).
Replacing TRFLP and clone libraries with next generation sequencing has the potential to
provide a greater depth of information on the occurrence of specific phylotypes in SIP gradients.

37

For example, in 2011, researchers have used pyrosequencing on total DNA extracts in an SIP
study to investigate the microorganisms involved in toluene degradation at a tar-oil-contaminated
aquifer (29). Others have integrated pyrosequencing libraries with SIP identified sequences to
determine the abundance of microorganisms in samples from the Deepwater Horizon soil spill
(30) or to investigate ammonia oxidizers (31). Further, researchers have also used
pyrosequencing on the SIP fractions (rather than on total DNA extracts) to, for example,
investigate nitrogen-incorporating bacteria in petroleum contaminated artic soils (32), to study
organic carbon uptake by bacterioplankton (33), to investigate ammonia and nitrite oxidation
(31, 34-36), to study nonylphenol degraders in activated sludge (37), to study the gut microbiota
of cotton leafworm (Spodoptera littoralis) (38) to investigate toluene degradation (39) and to
study biological soil crusts (40).

In the current study, the overall aim was to identify microorganisms able to uptake 13C from
ethylbenzene (or ethylbenzene degradation products) in soil based microcosms, using culture
independent methods (SIP and high throughput sequencing). For this, the relative abundance of
phylotypes present in the heavy fractions of two labeled and two unlabeled ethylbenzene
amended microcosms from one soil were compared. The phylotypes with a high relative
abundance in the heavy fractions of the labeled ethylbenzene amended microcosm (compared to
similar fractions in the unlabeled amended microcosms) were deemed responsible for
incorporating the labeled carbon from ethylbenzene (or ethylbenzene degradation products). An
underlying hypothesis of this work was that these techniques would produce a more diverse
group of ethylbenzene degraders than those previously reported.

38

METHODS
Chemicals
Unlabeled and labeled ethylbenzene (Phenyl -13C6 , 99% ) were purchased from Sigma-Aldrich
(St. Louis, MO, USA). Other reagents were purchased from one or more of the following
vendors: Fisher Bioreagent (Thermo Fisher Scientific, NJ, USA), Invitrogen (Life Technologies,
Grand Island, NY, USA) and Sigma-Aldrich (St.Louis, MO, USA), unless stated otherwise.

Development of Ethylbenzene Degrading Microcosms
A wide variety of inocula and electron acceptor conditions were tested for ethylbenzene
degradation using microcosms prepared under strict anaerobic conditions in an anaerobic
chamber (Coy Laboratory Products, Grass Lake, MI). The inocula sources consisted of 12
different agricultural soil samples (collected from Michigan), activated sludge samples (from two
wastewater treatment plants) and digested manure samples (from an anaerobic digester at
Michigan State University). These sources were selected because previous research indicated
BTEX degradation potential (23-27). The inocula sources were tested under nitrate amended,
sulfate amended, iron amended and/or methanogenic conditions in the presence of an anaerobic
minimal basal media (41). For this, triplicate microcosms were prepared with 6 to 10 g (wet
weight) of the inocula source, 30 mL of the anaerobic basal media and 20 mg L-1 of unlabeled
ethylbenzene in a 160 mL serum bottle. Electron acceptors were amended (1 g L-1 of SO42- or
NO3- or Fe3+) as required. Microcosms were sealed using rubber stoppers and aluminum seals in
the anaerobic chamber. All incubations were monitored for ethylbenzene removal for up to 8
weeks (data not shown). Among the 31 different incubations, only the triplicate microcosms
prepared with an agricultural soil inocula amended with nitrate showed ethylbenzene

39

degradation. This soil was used to inoculate the microcosms for the SIP study (prepared as
above). For the SIP study, triplicate killed controls and four microcosms were prepared with 20
mg L-1 of unlabeled ethylbenzene (hereafter, called Unlabel EB 1, Unlabel EB 2, SIP Unlabel EB
1 and SIP Unlabel EB 2) and two live sample microcosms were prepared with 20 mg L-1 of
labeled ethylbenzene (phenyl -13C6 , 99% ) (hereafter, called SIP Label EB 1 and SIP Label EB
2). From these, DNA extracted from SIP Unlabel EB 1, SIP Unlabel EB 2, SIP Label EB 1 and
SIP Label EB 2 was used for SIP analysis (ultracentrifugation and fractionation) and total
microbial community analysis. Whereas, DNA extracted Unlabel EB 1 and Unlabel EB 2 was
only used for microbial community analysis. This allowed the comparison of the microbial
community across six microcosms. All microcosms were incubated at room temperature (~20
°C), without shaking.

Analytical Techniques
Ethylbenzene biodegradation was monitored over time by measuring headspace ethylbenzene
concentrations in the microcosms. Sampling days for the SIP microcosms were determined based
on the results of the initial screening microcosms. For this, 200 µL of headspace samples were
injected into a gas chromatograph (Perkin Elmer) attached to a flame ionization detector and an
AT-624 capillary column (J & W Scientific; 30 m, 0.53 mm ID, 3.0 µm) with helium as carrier
gas. The oven temperature was set to 150 °C while the injector port and detector temperature
were set to 200 °C with an ethylbenzene elution time of 2.3 minutes. Nitrite and nitrate
measurements were made only on day 1 and 22 using ion chromatography.

40

DNA Extraction and Isopycnic Centrifugation
Total genomic DNA was extracted from the six microcosms (two labeled and four unlabeled
ethylbenzene amended) using the Power Soil DNA extraction kit following the manufacturer’s
instruction (MO BIO Laboratories, Inc. Carlsbad, CA) following the degradation of
ethylbenzene. The extracted DNA from SIP Unlabel EB 1, SIP Unlabel EB 2, SIP Label EB 1
and SIP Label EB 2 was ultracentrifuged in cesium chloride gradients separately to obtain
density-resolved gradients and fractions. Approximately 10 µg of total genomic DNA was mixed
with a Tris-EDTA (pH 8.0) buffer and CsCl solution (no glycogen was added to the gradient).
This mixture was added to a 5.1 mL Quick-Seal polyallomer tubes (1.3 x 5.1 cm, Beckman
Coulter) the buoyant density (BD) of this mixture was adjusted to ~1.72 g mL-1 using a model
AR200 digital refractometer (Leica Microsystems Inc.) and then sealed using a tube topper
(Cordless quick-seal tube topper, Beckman). The tubes were then centrifuged at 178,000 x g for
46 hours at 20 °C in a Wx Sorvall Ultra 80 ultracentrifuge fitted with a Stepsaver 70 V6 Vertical
Titanium Rotor (Thermo Scientific).

The samples were separated into 20 fractions (each 250 µL) by displacing the samples with
molecular grade water. A syringe pump attached to a needle (BD, 23G and 1 inch) was used to
displace samples from the top of the tube, as fractions were collected from the bottom by gravity,
from heavy to light fractions. The BD of each fraction was calculated from the refractive index
obtained using a refractometer. DNA from each of the fraction was recovered using a glycogen
and ethanol precipitation. Precipitated DNA was then re-suspended in 30 µL PCR grade water
and stored at -20 °C for further analysis. The DNA concentration in was quantified in these
fractions using replicate measurements with the Qubit assay.

41

High Throughput Amplicon Sequencing (Illumina MiSeq)
Samples were subject to amplicon sequencing, following the protocol described elsewhere (42,
43) (Research Technology Support Facility or RTSF at Michigan State University). The fractions
were analyzed to determine which microorganisms were enriched in the heavy fractions and
were therefore responsible for carbon uptake from ethylbenzene (or ethylbenzene degradation
products). Also, the total DNA samples were analyzed with high throughput sequencing to
characterize the total microbial community present. The analysis included four heavy fractions
from SIP Unlabel EB 1, SIP Unlabel EB 2, SIP Label EB 1 and SIP Label EB 2. To enable a
comparison between fractions, the BD of the selected fractions from the labeled and unlabeled
amended microcosms were similar (maximum difference ±0.01 g mL-1) (Table 3.1). These
fractions were selected because their BD values were similar to those previously reported by our
group for SIP label enrichment (22-27). In addition, the fractions were selected based on the
concentration of DNA in each fraction. Illumina specific fusion primers were used to amplify the
V4 region of the 16S rRNA (42) and to add unique barcodes to samples in each well to enable
pooling and sequencing. After the amplicons were checked on 1% agarose gel, equimolar
amounts of the sample were pooled to normalize results, purified and then sequenced on the
Illumina MiSeq™ Personal Sequencing System.

The data obtained from amplicon sequencing in the fastq file format was analyzed using Mothur
(version 1.32.1) developed by Schloss (44) and the MiSeq standard operating procedure (SOP)
developed by the same laboratory(45, 46). Briefly, barcodes were removed from the sequence
data and contigs were made using the forward and reverse reads. Samples from one labeled and
one unlabeled replica each containing 4 fractions and one total genomic DNA sample (thus a

42

total of 10 samples) were analyzed together. The paired-end reads were used to make contigs,
were analyzed for errors and then classified. Sequences that did not assemble well were removed
from further analysis. Reads were checked for ambiguous bases and homopolymer length greater
than 8 (following the Mothur SOP) to remove sequencing errors. These sequences were then
aligned with the SILVA bacteria database (47) for the V4 region. Chimeras, mitochondrial and
chloroplast lineage sequences were removed and then the sequences were classified into OTU’s.
The OTUs were then grouped into taxonomical levels with corresponding confidence levels.
Rarefaction curves were generated using Mothur.

Cloning and Sanger Sequencing
A 16S rRNA gene clone library was constructed by amplifying, cloning and sequencing the total
genomic DNA. The 16S rRNA gene was amplified using the universal primers: 27F 5’AGAGTTTGATCMTGGCTCAG) and 1492R (5’-GGTTACCTTGTTACGACTT) (Operon
Biotechnologies) using the following cycle program: initial denaturation step (94 °C for 5 min),
30 cycles of amplification (94 °C for 30 sec, 55 °C for 30 sec, 72 °C for 1.5 min) and final
extension step (72 °C for 5 min). The amplicons were run on a 1% agarose gel and were then cut
and purified using a gel purification kit (Qiagen). The purified amplicons were then cloned using
the TOPO TA kit as per manufacturer’s instruction. The cloned Escherichia coli cells were then
plated on agar plates with 50 µg mL-1 ampicillin and grown over night. The colonies were
screened for inserts using blue-white screening and PCR (M13F 5’TGTAAAACGACGGCCAGT-3’ and M13R 5’-AACAGCTATGACCATG-3’). The positive
cells were submitted to RTSF for Sanger sequencing. The sequences obtained were then
classified using the Ribosomal Database Project (RDP) “Classifier” (48) .

43

RESULTS
Ethylbenzene Biodegradation
Ethylbenzene degradation was observed in only one of the 31 different incubations over an 8
week period. The lack of ethylbenzene degradation may be a result of the rare occurrence of
ethylbenzene degrading microorganisms (however, no molecular analysis of those samples not
illustrating ethylbenzene degradation was performed). In the microcosms amended with
agricultural soil and nitrate, >90% of the added ethylbenzene was degraded in 29 days in the
sample microcosms, with no significant degradation in the killed abiotic controls (data not
shown). There was an initial decrease of approximately 5 mg L-1 in all of the microcosms (live
and killed) between day 1 and day 7. This was possibly due to sorption as no further decrease
was noted in the killed control microcosms. Similar degradation rates were observed in the SIP
microcosms prepared with this inoculum (Figure 3.1). However, replicate microcosms exhibited
slightly different rates of ethylbenzene degradation.

No significant reductions in ethylbenzene concentrations were observed in the abiotic killed
controls (after the initial sorption decrease in all microcosms). An initial lag in degradation was
observed in all microcosms and following this, most degradation occurred in 7 to 10 days. There
was also an 80% decrease in the nitrate concentration between day 1 and day 22 in the labeled
and unlabeled samples with no significant decrease in the abiotic controls (data not shown).

High Throughput Amplicon Sequencing Analysis
Samples from fractions (Table 3.1) as well as total DNA were submitted for high throughput
amplicon sequencing. The fractions selected were at the heavy end of the ultracentrifugation

44

gradient (Figure 3.2). Approximately 90,000 final sequences were obtained per sample.
Sequencing data were obtained for both the fractions as well as total DNA. The number of
sequences obtained per run and the final number of sequences used for the OTU and phylotypes
classification are listed (Table 3.2). Sequences that did not assemble well (>275 bp) were
dropped from further analysis. Further, an average of approximately 3.3 % of the remaining
sequences were also removed as they were either marked as chimeric by the Uchime algorithm
(49) or as belonging to mitochondria or chloroplast lineage by the Bayesian classifier. The
remaining sequences were used for analysis. These sequences were classified into OTU’s and
taxons by splitting them into bins and clustering them at the order level within each bin at 97%
similarity cutoff level. Sequences of clones from this study were submitted to Genbank under
accession number KM362736-KM362822. The high throughput sequence data was submitted to
SRA under Bioproject number PRJNA257333.

Microbial Community in Ethylbenzene Degrading Microcosms
Rarefaction curves indicated an adequate level of sequence coverage for the total community
analysis of the six microcosms (Figure 3.3). As expected, no differences were noted between the
coverage in the labeled compared to the unlabeled ethylbenzene amended microcosms. The OTU
classification data of the total DNA samples into phylotypes was used to determine the
community composition in each of the six microcosms. Figure 3.4 shows the phyla level
classification of the sequences in the total genomic DNA samples from the six microcosms. A
small percentage (4.3-8%) of the sequences were unclassified Bacteria. Proteobacteria was the
most abundant phyla in all six microcosms (relative abundance of 58.7-79.1%). The remaining
dominant phyla included Firmicutes (6.3-13.17%), Actinobacteria (2.9-8.4 %), Acidobacteria

45

(2.0-13.3%), and Bacteroidetes (0.8-4.6%). Microorganisms from both phyla
Gemmatimonadetes and Verrucomicrobia were present in all six microcosms at levels between
0.9 and 1.9 %. Microorganisms in the phyla TM7, Planctomycetes, Chloroflexi, DeinococcusThermus, Armatimonadetes, Chlamydiae and Nitrospira were present on all six microcosms, but
only at lower levels (0.007-0.3%). Whereas, microorganisms classifying within BRC1, OD1,
WS3, Chlorobi, Lentisphaerae were present in some microcosms, but not in others (when
present, <0.006%).

The relative abundance of all phylotypes with a relative abundance of > 1 % were compared
across all six microcosms (Figure 3.5). This resulted in a comparison of fifteen phylotypes. In
four of the six microcosms, Rhodanobacter (Gammaproteobacteria) was the most abundant
phylotype (14.1-15.6%) and in the other two microcosms it was the second (14.2%) or third
(11.7%) most abundant phylotype. In two microcosms, Azoarcus was the most abundant
phylotype (24.1 and 14.6%), however, in the other four microcosms it was present at very low
levels (<0.006 %). In four microcosms, unclassified Rhodospirillaceae was the second most
dominant phylotype (10.7-14.1%) a family within the Alphaproteobacteria. In the other two
microcosms, it was present at lower levels (2.7 and 5.1%). In all six microcosms, unclassified
Oxalobacteraceae (Betaproteobacteria) was present at high levels (5.5-14.1%). Unclassified
Xanthomonadaceae (the family containing Rhodanobacter) was also present in all six
microcosms, but at lower levels (1.9-6.3%). Other unclassified families occurring in all six
microcosms at lower levels include Bacillaceae 1 (Firmicutes), Chitinophagaceae
(Bacteroidetes) and Comamonadaceae (Betaproteobacteria). Three unclassified orders
(Bacillales, Rhodospirillales and Rhizobiales), unclassified Bacteria and unclassified

46

Betaproteobacteria were also present in all six microcosms. In addition, two phylotypes
classifying as Thiobacillus (Betaproteobacteria) and Gemmatimonas (phylum
Gemmatimonadetes) were found in all six microcosms.

16S rRNA Gene Clone Library
A clone library was generated so that a comparison could be performed between traditional
Sanger sequencing and high throughput sequencing data. The clone library consisted of a 120
clones (Table 3.3) belonging to eight different phyla: Proteobacteria (73.1%), Firmicutes
(10.9%), Bacteriodetes (8.4%), Acidobacteria (5.0%), Armatimonadetes (0.8%),
Gemmatimonadetes (0.8%), TM7 (0.8%), and Verrucomicrobia (0.8%). Among the
Proteobacteria, the majority belonged to Betaproteobacteria (45.8% of the total). The major
phyla present in the clone library were relatively consistent with the high throughput sequencing
results. That is, the Illumina results indicated the communities in the six microcosms were also
dominated by Proteobacteria (58.7-79.1%), followed by Firmicutes (6.3-13.17%), Acidobacteria
(2.0-13.3%), and Bacteroidetes (0.8-4.6%). Notably, no clones belonging to Actinobacteria were
present in the clone library, however, this phylum exhibited a relative abundance of between 2.9
and 8.4 % in high throughput sequencing results. Further, the clone library did not contain
representatives from 11 additional phyla that were found in the high throughput sequencing data.
Consistent with the high throughput sequencing data, the clone library did contain a high number
of Rhodanobacter (relative abundance of 10.0%) and unclassified Oxalobacteraceae sequences
(25.0%). In contrast, the number of sequences of unclassified Rhodospirillaceae was much lower
in the library (3.3%) compared to the Illumina data. Azoarcus was not present in the clone
library, however, Gemmatimonas was present (0.83%). As expected, the Illumina results

47

provided a more in depth representation of the microorganisms present in these ethylbenzene
degrading communities.

Phylotype Relative Abundance Across SIP Fractions
The relative abundance of phylotypes in heavy fractions were compared between the labelled
and unlabeled ethylbenzene amended microcosms to determine which phylotypes could be
linked to label uptake. For this, the analysis focused on the most abundant phylotypes in
fractions from the labeled ethylbenzene amended microcosms. The relative abundance of these
phylotypes was then compared to their relative abundance in fractions from the unlabeled
ethylbenzene amended microcosms. Overall, seven phylotypes were dominant in the heavy
fractions from both of the labeled ethylbenzene amended microcosms (Figure 3.6).
Rhodanobacter was the most abundant in these fractions, however, the relative abundance was
similar in fractions from the labeled and unlabeled ethylbenzene amended samples, indicating no
label uptake. Following this, unclassified Oxalobacteraceae and Rhodospirillaceae were also
dominant. A comparison of the relative abundance of these phylotypes indicates label uptake
likely occurred in one labeled ethylbenzene amended microcosm (SIP Label EB 2), but not the
other (SIP Label EB 1). Unclassified Xanthomonadaceae and Rhodocyclaceae both illustrated a
higher relative abundance in the fractions from the labeled ethylbenzene amended microcosms
compared to the unlabeled amended microcosms. No difference in relative abundance was noted
for unclassified Bacillales between treatments. Finally, the phylotype Gemmatimonas was more
abundant in fractions from one labeled ethylbenzene amended microcosm (SIP Label EB 1).
Azoarcus was not dominant in the heavy fractions of either labeled ethylbenzene amended
microcosm.

48

DISCUSSION
Biodegradation studies using SIP aim to identify active organisms involved in chemical
transformations that are typically not identified using culture based techniques (21, 50, 51).
Combining SIP with high throughput sequencing has the added advantage of a greater depth of
analysis (compared to Sanger sequencing). Although Illumina amplicon sequencing produces
shorter reads even with paired reads (250 bp) compared to Sanger sequencing (up to ~1000 bp)
(52, 53), previous studies have shown the method can still resolve the differences between
microbial communities (42). The data generated in the current study indicated that one clone
library (120 clones) with Sanger sequencing provided a weaker representation of the microbial
community compared to the Illumina data. For example, Actinobacteria, a major phylum in the
Illumina data, was absent from the clone library, as were 11 other phyla (that were present in the
Illumina data). The contrasting results from these two sequencing methods are consistent with
previous studies that used both techniques. The large amount of sequencing information from
amplicon sequencing is an improved predictor of phylotype relative abundance (29, 32, 35) and
thus has great potential for SIP studies.

Although Rhodanobacter was the most abundant phylotype in the majority of the six
microcosms, it’s relative abundance was similar in the fractions obtained from the labelled and
unlabeled ethylbenzene amended microcosms, indicating it was not responsible for label uptake.
Phylotypes from the families Oxalobacteraceae and Rhodospirillaceae appeared to be involved
in carbon uptake from ethylbenzene in one microcosm (SIP Label EB 2). According to the
Ribosomal Database Project (http://rdp.cme.msu.edu/index.jsp), Oxalobacteraceae (order
Burkholderiales, class Betaproteobacteria) contains 11 genera and Rhodospirillaceae (order

49

Rhodospirillales, class Alphaproteobacteria) contains 27 genera. Any of these genera could be
responsible for label uptake in this microcosm. The phylotype Gemmatimonas was more
abundant in the fractions from one labeled ethylbenzene amended microcosm (SIP Label EB 1).
This microorganism belongs to the phylum Gemmatimonadetes, which only contains one genus
(with 15 known isolates), with the first isolate being obtained only relatively recently (2003)
(54). The family Xanthomonadaceae (order Xanthomonadales, class Gammaproteobacteria)
contains 21 genera and phylotypes within this family appeared to responsible for label uptake in
both label amended microcosms. Again, any of these genera could be responsible for label
uptake.

Phylotypes within the family Rhodocyclaceae were also more abundant in the fractions from
both the labeled ethylbenzene amended microcosms compared to similar fractions from the
unlabeled ethylbenzene amended microcosms. This pattern indicates phylotypes classifying as
Rhodocyclaceae were involved in carbon uptake from ethylbenzene (or ethylbenzene
degradation products). These results are consistent with pure culture studies, as the majority of
anaerobic ethylbenzene degrading isolates belong to this family. Previous research has indicated
phylotypes classifying as Rhodocyclaceae (Azoarcus, Dechloromonas, Georgfuchsia spp.) are
capable of ethylbenzene degradation (8, 10, 11, 14). Also, previous studies have linked
organisms from this family to transformation of several organic and inorganic substances such as
phenantharene (55-57), naphthalene (58), other petroleum products (32), arsenic (59), uranium
(60), chromium (61) and alkanes (62). Members of this family are also shown to degrade almost
all of the BTEX compounds, particularly under nitrate reducing conditions (8-11, 15, 29, 63, 64).
These findings indicate these microorganisms play an important role in monoaromatic

50

hydrocarbon degradation in isolation as well as in mixed communities. Also, two ethylbenzene
degrading strains, Aromatoleum aromaticum EbN1 and Dechloromonas aromatica RCB, were
isolated from uncontaminated fresh water sediments. The other sulfate reducing ethylbenzene
degrading bacterium was isolated from uncontaminated marine sediment, emphasizing the
importance of ethylbenzene degrading bacteria in communities not previously exposed to
monoaromatic or polyaromatic hydrocarbons (as in the current study).

In summary, combining the culture independent technique SIP with high throughput amplicon
sequencing can be a useful approach for investigating the biodegradation of xenobiotics by
minority organisms or by a community of organisms. The current work illustrates the utility of
these methods for examining carbon pathways in soil communities. Although it was not possible
to identify enriched phylotypes at the genus level, important families involved in carbon
assimilation were identified. Interestingly, all classified within the Proteobacteria.

51

APPENDIX

52

Table 3.1. Buoyant density of heavy fractions from the labeled and unlabeled samples submitted
for amplicon sequencing.
Microcosm name
SIP Label EB 1
SIP Label EB 2
SIP Unlabel EB 1
SIP Unlabel EB 2

1.780
1.778
1.778
1.780

Buoyant Density of Fractions (g mL-1)
1.755
1.745
1.768
1.756
1.759
1.747
1.765
1.755

1.742
1.748
1.740
1.744

Table 3.2. Summary MiSEQ Illumina data generated from the fractions as well as total DNA
extracted from labeled and unlabeled ethylbenzene amended microcosms.

SIP Label EB 1 and
SIP unlabeled EB 1
with 4 fractions from
each and total DNA
samples from both
SIP Label EB 2 and
SIP unlabeled EB 2
with 4 fractions from
each and total DNA
samples from both
Unlabel EB 1 and
Unlabel EB 2 total
DNA

# of
Sequences
Following
Make Contigs
command
1758568

Final # of
Unique
Sequences

Final # of
Sequences

%
Chimeric

68926

869977

3.09

OTUs Per
Fraction or
Sample
(Average ± Std
dev)
2622 ± 719

2181584

81557

1075361

3.20

2758 ± 743

829470

26696

409141

3.13

1495±254

53

Table 3.3. Classification of 16S rRNA gene clones in the clone library.
Phyla

Class

Acidobacteria
Acidobacteria
Acidobacteria
Acidobacteria
Armatimonadetes
Bacteriodetes
Bacteriodetes
Bacteriodetes
Firmicutes
Firmicutes
Firmicutes
Firmicutes
Gemmatimonadetes
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria
Proteobacteria

Acidobacteria GP1
Acidobacteria GP3
Acidobacteria GP4

Proteobacteria
Proteobacteria
TM7
Verrucomicrobia

Order

Family

Flavobacteria
Sphingobacteria

Flavobacteriales
Sphingobacteriales

Flavobacteriaceae
Chitinophagaceae

Bacilli
Bacilli
Bacilli
Bacilli
Gemmatimonadetes
Alphaproteobacteria
Alphaproteobacteria
Alphaproteobacteria
Alphaproteobacteria
Alphaproteobacteria
Alphaproteobacteria
Betaproteobacteria
Betaproteobacteria
Betaproteobacteria
Betaproteobacteria
Betaproteobacteria
Betaproteobacteria
Betaproteobacteria
Betaproteobacteria
Gammaproteobacteria
Gammaproteobacteria

Bacilllales
Bacilllales
Bacilllales
Bacilllales
Gemmatimonadales
Rhizobiales
Rhizobiales
Rhizobiales
Rhizobiales
Rhizobiales
Rhodospirillales
Burkholderiales
Burkholderiales
Burkholderiales
Burkholderiales
Burkholderiales
Burkholderiales
Rhododcyclales

Alicyclobacillaceae
Bacillaceae
Paenibacillaceae 1

Xanthomonadales
Xanthomonadales

Xanthomonadaceae
Xanthomonadaceae

Gammaproteobacteria

Xanthomonadales

Xanthomonadaceae

Spartobacteria

Gemmatimonadaceae
Brucellaceae
Methylobacteriaceae
Phyllobacteriaceae
Xanthobateraceae
Rhodospirillaceae
Alcaligenaceae
Comamonadaceae
Oxalobacteraceae
Oxalobacteraceae
Oxalobacteraceae
Rhodocyclaceae

Unclassified TM7
Unclassified Spartobacteria

54

Full name

No. of
Clones

Gp1
Gp3
Gp4
Gp6
Armatimonadetes_Gp4
Flavobacterium
Ferruginibacter
Unclassified Bacteriodetes
Tumebacilus
Bacillus
Unclassified Bacillales
Unclassified Bacillales
Gemmatimonas
Unclassified Brucellaceae
Microvirga
Aminobacter
Unclassified Rhizobiales
Pseudolabrys
Unclassified Rhodospirillaceae
Pusilimonas
Ramlibacter
Herbaspirillum
Massilia
Unclassified Oxalobacteraceae
Unclassified Burkholderiales
Unclassified Rhodocyclaceae
Unclassified Betaproteobacteria
Rhodanobacter
Unclassified
Xanthomonadaceae
Luteimonas
Unclassified Proteobacteria
TM7 genera incertae sedis
Spartobacteria genera incertae

3
1
1
1
1
3
6
1
1
5
1
6
1
1
1
1
2
1
4
1
1
4
1
30
10
4
4
12
1
1
8
1
1

Ethylbenzene concencentration mg/L

25

20
Abiotic controls

15
Unlabel EB 2

10

SIP Unlabel EB 2
Unlabel EB 1

5

SIP Label EB 2
SIP Unlabel EB 1

SIP Label EB 1

0
0

5

10

15

20

25

30

Time (days after ethylbenzene addition)

Figure 3.1. Concentration of ethylbenzene in microcosms over time ( × - abiotic controls, open
triangles - amended with 12C6 ethylbenzene, closed circles - amended with 13C6 ethylbenzene).

55

30
SIP Unlabel EB 1

SIP Label EB 1

25

20

-1

DNA Concentration (ng µL )

15
10

5
0
1.70
30

1.72

1.74

1.76

1.78

1.80

SIP Unlabel EB 2
SIP Label EB 2

25
20
15
10
5
0
1.70

1.72

1.74

1.76

1.78

1.80

-1

Buoyant Density (g mL )
Figure 3.2. DNA concentration over the ultracentrifugation gradient in fractions from replicate
microcosms amended with labeled or unlabeled ethylbenzene. The dashed arrows indicate the
fractions that were sequenced from the unlabeled EB amended samples and solid arrows indicate
the fractions that were sequenced from the labeled EB amended samples.

56

4000
3500

Number of OTUs

3000
Unlabel EB 1

2500

Unlabel EB 2
SIP Label EB 1

2000

SIP Label EB 2
1500

SIP Unlabel EB 1
SIP Unlabel EB 2

1000
500
0
0

20000

40000

60000

80000

100000 120000 140000

Number of sequences

Figure 3.3. Rarefaction curves generated from sequencing data from total DNA extracts for all
six microcosms.

57

100

Lentisphaerae
Chlorobi
WS3
OD1

80

BRC1

Relative Abundance (%)

Nitrospira
Chlamydiae
60

Armatimonadetes
Deinococcus-Thermus
Chloroflexi
Planctomycetes

40

TM7
Verrucomicrobia
Gemmatimonadetes

Bacteroidetes

20

Acidobacteria
Actinobacteria
unclassified
0

Firmicutes
Unlabel EB 1

Unlabel EB 2

SIP Label EB 1 SIP Label EB 2 SIP Unlabel EB SIP Unlabel EB
1
2

Proteobacteria

Figure 3.4. Comparison of relative abundance of sequences in total genomic DNA extracted
from six microcosms amended with 13C6 labeled or unlabeled ethylbenzene at phylum level
classification.

58

Unlabel EB 1

SIP Label EB 1

Unlabel EB 2

Rhodanobacter
Azoarcus
unclassified Rhodospirillaceae
unclassified Oxalobacteraceae
Thiobacillus
unclassified Bacteria
unclassified Xanthomonadaceae
unclassified Bacillales
unclassified Rhodospirillales
unclassified Bacillaceae 1
unclassified Betaproteobacteria
unclassified Chitinophagaceae
unclassified Comamonadaceae
unclassified Rhizobiales
Gemmatimonas

SIP Unlabel EB 1

SIP Unlabel EB 2

SIP Label EB 2

Figure 3.5. Relative abundance (%) of the most common phylotypes (>1%, at the lowest
classification level) in all six microcosms (from total DNA extracts). The phylotypes are at the
genus level, unless unclassified.

59

Abundance in SIP Label EB 1, SIP Unlabel

25

20

20

15

15

10

10

5

5

0
1.74

1.75

1.76

1.77

1.78

0
1.74

1.79

15

15

10

10

5

5

0
1.74

1.75

1.76

1.77

1.78

0
1.74

1.79

25

20

20

15

15

10

10

5

5
1.75

1.76

1.77

1.78

0
1.74

1.79

6

1.78

1.79

1.75

1.76

1.77

1.78

1.79

Unclassified Rhodospirillaceae

1.75

1.76

1.77

1.78

1.79

Unclassified Xanthomonadaceae

4
2

1.75

1.76

1.77

1.78

1.79

0
1.74

6

6

4

4

2

2

1.75

1.76

1.77

1.78

1.79

0
1.74

10

10

8

8

6

6

4

4

2

2
1.75

1.76

1.77

1.78

1.79

0
1.74

4

4

3

3

2

2

1

1

0
1.74

1.77

12C EB

2

0
1.74

1.76

6
13C EB

4

0
1.74

1.75

8

8

0
1.74

Rhodanobacter

Unclassified Oxalobacteraceae

25

0
1.74

Relative Abundance (%)

Abundance in SIP Label EB 2, SIP Unlabel EB 2

25

1.75

1.76

1.77

1.78

1.79

0
1.74

1.75

1.76

1.77

1.78

1.79

Unclassified Rhodocyclaceae

1.75

1.76

1.77

1.78

1.79

Unclassified Bacillales

1.75

1.76

1.77

1.78

1.79

Gemmatimonas

1.75

1.76

1.77

1.78

1.79

Buoyant density (g mL-1)

Figure 3.6. Relative abundance of the most common phylotypes in heavy fractions from 13C
ethylbenzene amended microcosms compared to those from 12C ethylbenzene amended
microcosms (SIP Label EB1 and SIP Unlabel EB1 on left, SIP Label EB2 and SIP Unlabel EB2
on right).
60

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Martin F, Torelli S, Le Paslier D, Barbance A, Martin-Laurent F, Bru D, Geremia
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67

CHAPTER 4 COMPARATIVE STUDY OF RDX DEGRADING MICROBIAL
COMMUNITIES IN FOUR SOILS

ABSTRACT
The explosive hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) has contaminated many military
sites. Recently, attempts to remediate these sites have focused on biostimulation to promote in
situ RDX biodegradation. Although many RDX degrading isolates have been obtained in the
laboratory, little is known about the potential of microorganisms to degrade this chemical in
mixed microbial communities. The current study compared four soils to elucidate the
microorganisms linked to RDX degradation. These soils were selected as they had no previous
exposure to RDX, therefore their microbial communities offered an excellent baseline to
determine changes following exposure to RDX. The work involved the collection of two sets of
molecular data. First, high throughput sequencing was used to determine which phylotypes
experienced an increase in relative abundance following RDX degradation. For this, DNA was
sequenced from 1) the initial soil, 2) microcosms following RDX degradation and 3) control
microcosms without RDX. Second, to ascertain which phylotypes were responsible for label
(ring 15N or 13C) uptake from RDX, stable isotope probing (SIP) was performed on two soils.

The sequencing data provided valuable information on which phylotypes increased in abundance
in RDX degrading microcosms compared to control microcosms. The most notable trend was the
increase in abundance of Brevundimonas and/or unclassified Bacillaceae 1 in the four soils

68

studied. These data indicate these two phylotypes are benefiting from RDX degradation under
these conditions. Although members of the family Bacillaceae 1 have previously been linked to
RDX degradation, the genus Brevundimonas has not been previously associated with RDX
degradation. SIP data indicated that phylotypes classifying within the Firmicutes and
Actinobacteria (Rhodococcus) were involved in label uptake from RDX. Overall, these data
suggest both novel RDX degraders and previously reported RDX degraders were associated with
RDX removal in these soils.

INTRODUCTION
The manufacturing, transport and use of the nitramine explosive hexahydro-1,3,5-trinitro-1,3,5triazine (RDX) has resulted in groundwater and sediment contamination at many military sites.
RDX has moderate solubility, low sorption and low vapor pressure resulting in significant
mobility in groundwater and sediments. Due to neurotoxic effects, the potential carcinogenic
nature of RDX and widespread RDX contamination, the US EPA has issued a life-time drinking
water health advisory level of 2 µg/L RDX. Although RDX was initially thought to be
recalcitrant, the chemical has been shown amenable to biodegradation under both aerobic and
anaerobic conditions. Thus, bioremediation has been considered a viable option to treat RDX
contaminated sites. As many of these sites are oxygen depleted, it is more suitable to consider
RDX biodegradation under anaerobic conditions.

Several bacteria have been isolated with the ability to degrade RDX under anaerobic conditions.
These microorganisms classify within the phyla Firmicutes, Fusobacteria and Proteobacteria.
The first anaerobic RDX degrading isolate obtained, Clostridia bifermentans, classified with the

69

Firmicutes (1). Other Clostridia isolates have also been reported with RDX degrading abilities,
including, for example, Clostridia sp. EDB2 and Clostridia acetobutylicum (2-5). Other RDX
degrading bacteria belonging to the Firmicutes include two Acetobacterium spp. (6, 7), two
Bacillus spp. (8) and a Desulfitobacterium strain (9). Fusobacteria sp. HAQ-EB21 (10, 11) is the
only anaerobic RDX degrading isolate from the phylum Fusobacteria.

The Proteobacteria, particularly the classes Gamma and Deltaproteobacteria, contain diverse
anaerobic RDX degrading isolates. In the Gammaproteobacteria, RDX degrading bacteria have
been isolated from the families Enterobacteriaceae (12-16), Pseudomonadaceae (8, 17),
Shewanellaceae (10, 18, 19) and Xanthomonadaceae (20). Isolates belonging to
Cystobacteraceae (9), Geobacteraceae (21) or Desulfovibrionaceae (11, 22, 23) within the
Deltaproteobacteria are also able to degrade RDX.

Although much is known about pure cultures able to degrade RDX in the laboratory, very little is
known about the microorganisms responsible for RDX degradation in mixed communities or at
contaminated sites. Researchers have reported the microorganisms detected in field samples
actively degrading RDX were generally not closely related to previously reported RDX
degrading isolates (24). It is now widely recognized that only a small fraction of microorganisms
can be isolated and cultivated in the laboratory (25), therefore, it is likely that many RDX
degraders have yet to be identified. This information is important because if several key species
were consistently linked to effective RDX degradation in mixed communities, their presence
could provide strong evidence of RDX natural attenuation.

70

Recently, a small number of studies have used stable isotope probing (SIP) to determine which
microorganisms were involved in carbon and/or nitrogen uptake from RDX (26-29). One report
revealed the important of Sphingobacteriales (Bacteroidetes) in RDX degradation (28). A SIP
(15N labeled RDX) study by another group using samples from the Picatinny Arsenal Site,
identified five phylotypes similar to known RDX degraders and ten phylotypes not previously
linked to RDX degradation (29). A 13C labeled RDX SIP study again using samples from one
site, also revealed that novel phylotypes and phylotypes similar to known RDX degraders were
responsible for label uptake (27). A recent SIP investigation (15N labeled RDX) using material
from the Eglin Air Force Base bombing range, reported that RDX degradation was spatially
heterogeneous and dependent on carbon source addition (26). These researchers reported that
Rhodococcus (a known RDX degrader) as well as several Proteobacteria were highly labeled
with 15N. These studies have led to the conclusion that RDX degrading microorganisms are
phylogenetically more diverse than was previously thought.

In the past few years, SIP has been combined with high throughput sequencing. For example,
researchers have examined the biodegradation of toluene (30), the thermophilic anaerobic
conversion of microcrystalline cellulose (31), nitrogen incorporation from monoammonium
phosphate in arctic soils (32) and carbon uptake in microbial fuel cells (33) using this technique.
In the current study, SIP was combined with high throughput sequencing to compare the RDX
degrading communities in four soils without prior exposure to RDX. This is the first
investigation of RDX degrading communities in uncontaminated soils using the combined
approaches. Further, is it is first study to use high throughput sequencing to compare the
microbial communities between RDX degrading soils.

71

METHODS
Chemicals
Unlabeled and ring-labeled RDX (13C3, 99%; 15N3, 98%) dissolved in acetonitrile were
purchased from Cambridge Isotope Laboratories, Inc. (Tewksbury, MA). HPLC grade
acetonitrile (≥99.8 % purity) was purchased from EMD Chemicals Inc. (New Jersey, USA).
Other reagents were purchased from Sigma-Aldrich (St. Louis, MO, USA), Fisher BioReagent
(New Jersey, USA), or Invitrogen (Carlsbad, CA, USA) unless otherwise stated.

Experimental Design
Four agricultural soils were utilized in these experiments and, to our knowledge, these soils have
not previously been exposed to RDX (Table 1). The soil microcosms for screening RDX
degradation were established as previously described, with only slight modifications (28, 34).
Briefly, for each soil, 60 mL serum bottles contained 1 g soil (wet weight), 20 mg L-1 unlabeled
RDX dissolved in acetonitrile (as the sole nitrogen source), 201.6 mg L-1 glucose, and 4 mL of a
minimal salts media (MSM) (28, 34).

For the high throughput sequencing and SIP studies, the microcosms were prepared with 1 g soil
(wet weight), 1 mL of inocula from the corresponding RDX screening microcosm, 20 mg L-1
unlabeled or ring-labeled RDX dissolved in acetonitrile (as the sole nitrogen source), 201.6 mg
L-1 glucose, and 4 mL of a minimal salts media (MSM). Triplicate live sample microcosms were
amended with ring-labeled RDX (13C3, 15N3), triplicate live and killed abiotic controls
(autoclaved) microcosms were amended with unlabeled RDX (12C3, 14N3). Two successive
amendments of 20 mg L-1 of RDX were added to the live labeled and unlabeled RDX

72

microcosms. The triplicate abiotic killed controls were prepared in a similar manner to the live
microcosms except that they received only one amendment of unlabeled RDX. All microcosms
were sealed with rubber stoppers and aluminum seals and were covered with aluminum foil to
prevent photodegradation. The microcosms were incubated between 3 to 7 weeks in the dark at
room temperature (~20 °C) without shaking while being monitored for RDX degradation.
Due to time constraints, only DNA extracted from soils 9 and 10 were ultracentrifuged for
fraction analysis. However, total DNA extracts from all four soils, extracted from both replicates
of the labeled RDX (hereafter called Labeled 1, Time t and Labeled 2, Time t) and unlabeled
RDX microcosms (hereafter called Unlabeled 1, Time t and Unlabeled 2, Time t) were
sequenced.

Additional live control microcosms, without RDX addition, were also prepared with all four soils
and these were maintained under the same conditions as the live sample microcosms. Nucleic
acids were extracted from these control microcosms (hereafter called No RDX, Time t) at the
same time as those extracted from the RDX amended microcosms. Further, DNA was extracted
from each soil prior to any manipulation (hereafter called No RDX, Time 0). These two sets of
DNA extracts were sequenced to determine how the communities changed followed RDX
degradation compared to the initial soil and the no RDX controls.

RDX Extraction and Analysis
RDX concentrations were determined using high performance liquid chromatography (HPLC) as
previously described (34) with modifications. For this, 0.5 mL (extracted using a 1 mL BD
syringe with a 21 gauge needle) was placed in a 1.7 mL sterile microcentrifuge tube. An equal

73

volume of acetonitrile was added and the microcentrifuge tubes were shaken for 2 hours at room
temperature to extract RDX. The samples were then centrifuged for 5 minutes at 10,000 x g and
the supernatant was filtered using acetonitrile wetted filters (PVDF, 0.22 µm, Whatman) into
HPLC amber vials (Sigma-Aldrich, St. Louis, MO, USA). External standards for the calibration
curve were prepared with a dilution factor of 2 to account for the sample dilution at the liquidliquid extraction step. HPLC analysis involved a Perkin Elmer (PE) series 200 autosampler; PE
binary LC Pump 250; PE diode array detector 235C, at wavelength 255nm; Supelco C18 (25 cm
X 4.6 mm, 5 µm) column; and isocratic conditions (40% acetonitrile and 60% 0.1% H3PO4
acidified deionized water) at a flow rate of 1 mL min-1.

DNA Extraction and Isopycnic Centrifugation
As stated above, total genomic DNA from all four soils was extracted to establish the baseline
microbial community (No RDX, Time 0). Total genomic DNA was also extracted from all
sixteen microcosms (four soils, Labeled 1 & 2, Unlabeled 1 & 2, Time t) after the complete
degradation of the second amendment of RDX. In addition, DNA was extracted from the
corresponding live control microcosms at the same time (No RDX, Time t). All DNA extractions
used the Power Soil DNA extraction kit (MO BIO Laboratories, Inc. Carlsbad, CA).

Isopycnic centrifugation was conducted for soils 9 and 10, following previously described
procedures (35-40). DNA extracted from one labeled and one unlabeled microcosm for these
soils was ultracentrifuged separately in Tris EDTA - Cesium Chloride (CsCl) gradients to obtain
density gradient fractions. Approximately 3 to 5 µg of the total genomic DNA was added to a
CsCl and TrisEDTA solution with an initial buoyant density (BD) of ~1.72 g mL-1 in a 5.1 mL

74

Beckmann Coulter Quick-Seal polyallomer tubes. Tubes were then sealed (Cordless quick-seal
tube topper, Beckman) and centrifuged at 178,000 x g for 46 hours at 20 oC in a Wx Sorvall
Ultra 80 ultracentrifuge fitted with a Stepsaver 70 V6 Vertical Titanium Rotor (Thermo
Scientific). Each sample was then divided into 20 fractions (each 250 µL) by displacement with
molecular grade water using a syringe pump system. The BD of all samples was measured using
a model AR200 digital refractometer (Leica Microsystems Inc.) and the DNA from each fraction
was precipitated using ethanol and glycogen. Precipitated DNA was then re-suspended in 30 µL
PCR grade water and stored at -20 °C for further analysis.

Amplicon Sequencing and Data Analysis
Total genomic DNA extracted from four microcosms (Labeled 1, Labeled 2, Unlabeled 1,
Unlabeled 2, Time t) for all four soils (soil 9, 10 , 11 and 12) and from the microcosms without
RDX (No RDX, Time t) for all four soils were submitted for amplicon sequencing at Michigan
State University’s Research Technology and Support Facility (RTSF). Total genomic DNA
extracted from all four of the initial soils (no RDX, Time 0) were also amplicon sequenced.
Additionally, the first ultracentrifugation eight fractions with high BD values from soils 9 and 10
were also submitted for amplicon sequencing, in triplicate. Amplification of the V4 region and
paired-end high throughput amplicon sequencing on the Illumina MiSeq platform at RTSF was
conducted using a procedure previously described (41, 42).

Sequencing data obtained from the MiSeq platform Laboratory Information Management System
(LIMS) was analyzed using Mothur v.1.33.2 (43) using the MiSeq standard operating procedure
(44). The sequences data in the fastq format were processed using Mothur to remove the

75

barcodes and these were then aligned to form contiguous sequences. The data was checked for
sequencing errors and read length. The sequences were then aligned and checked for chimeras
using UCHIME in Mothur (45). Following which, the sequences were classified into OTU’s and
phylotypes using the Ribosomal Database Project dataset within Mothur. The sequence data was
then imported into Microsoft Excel for further analysis. High throughput sequences were also
processed using the default pipeline option on MG-RAST (46) to create the MLTreeMap and the
Heatmap with the following parameters, annotation source: RDP; maximum e-value cutoff :1e-5;
minimum % identity cutoff: 60%; minimum alignment length cutoff: 15. Illumina sequencing
data were deposited to the NCBI Sequence Read Archive under Bioproject Number
PRJNA263419.

RESULTS AND DISCUSSION
RDX Degradation
All four agricultural soils illustrated RDX degradation (Figure 4.1). The first amendment of
RDX was degraded in 15 to 31 days and the second amendment was degraded in 7 to 12 days.
No significant degradation of RDX was observed in the killed control microcosms. Among the
four soils, RDX degradation was the fastest in the microcosms with soil 10 and was the slowest
in the microcosms with soil 9.

Comparison at Phyla Level
Total genomic DNA from all treatments and live controls (all four soils) as well as DNA from
the ultracentrifugation fractions (soils 9 and 10) were submitted for amplicon sequencing (116
samples in total). An average of >120,000 reads was obtained per sample (Table 2). On average,

76

27% of the sequences did not align properly into contiguous sequences resulting in read lengths
>275 bp and these were dropped from the analysis. Another 2.3% (average) of the sequences
were identified as chimeric or as non-bacterial (mitochondrial/chloroplast) by the Bayesian
classifier within Mothur.

Phylotype classification and sequence abundance data were used to assess the microbial
communities in each of the four soils (Figure 4.2). The relative abundance of each phyla for all
four initial soils (No RDX, Time 0) were remarkably similar. That is, the phylotypes classified
into Firmicutes, Proteobacteria, Actinobacteria (the three most dominant), Bacteroidetes,
Acidobacteria, Verrucomicrobia, Chloroflexi and Gemmatimonadetes. In contrast, for all four
soils, in both the RDX amended microcosms (Labeled, Unlabeled 1 & 2, Time t) and in the
microcosms not amended with RDX (No RDX, Time t), the communities were primarily
composed of Proteobacteria (particularly soils 10 and 11) and Firmicutes (particularly soils 9
and 12). This increase in Firmicutes is likely a result of oxygen depletion in these samples (the
microcosms were sealed for more than 20 days). For the RDX amended samples, these results
are somewhat expected, as the majority of anaerobic RDX degrading isolates belong to the
Firmicutes and Proteobacteria (Table 1).

At the phyla level, for soils 9 and 12, the classifications were similar between the microcosms
amended with RDX and those not amended with RDX. For soils 10 and 11, the abundance of
Proteobacteria increased when RDX was amended. Although phyla level classifications provide
a useful baseline to compare these communities, comparisons at the phylotype level are more
informative and will be discussed below.

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Microbial Community Analysis
The microbial communities were also compared using MLTreeMap (Figure 4.3a). Again, the
phyla with the greatest representation and the most diversity included the Proteobacteria and
Firmicutes. However, no clear trends between the treatments could be ascertained from this
analysis. A heatmap was also generated with the sequencing data for all four soils and for the
microcosms with and without RDX (Figure 4.3b). The image illustrates distinct trends between
the four initial soils and the other treatments. As expected, the microbial communities from the
four initial soils clustered together. Clear differences can be seen between the initial soils and the
other treatments for the Clostridia, Cloroflexi, Gammatimonadetes, Spirochaetia and
unclassified Acidobacteria. The heatmap did not provide any strong trends for the differences in
community structure between the RDX amended microcosms and those not amended with RDX.

Rarefaction curves were also generated for the initial soils (No RDX, Time 0), for the
microcosms amended with RDX (Labeled, Unlabeled 1 & 2, Time t) and for the microcosms
without RDX (No RDX, Time t) (Figure 4.4a). The curves are all similar except for three (soils
10, 11 and 12) of the four initial soils, which illustrated a much steeper gradient, indicating
incomplete sequence coverage for these samples. The curves for the other samples started to
plateau, suggesting more complete sequence coverage.

Principal component analysis was also performed on the sequencing data (Figure 4.4b).
Clustering occurred for each soil in the four samples amended with RDX (Labeled 1 & 2,
Unlabeled 1 & 2). The clusters for soils 10 and 11 were close together, as were the clusters for

78

soils 9 and 12. Separate clusters were also formed for each of the four initial soils (No RDX,
Time 0) and for the four soil microcosms without RDX addition (No RDX, Time t).

To more precisely compare the relative abundance of phylotypes across treatments, the most
abundant phylotypes (>1% relative abundance) for each microbial community were determined.
The most abundant phylotypes were similar across all four initial soils (No RDX, Time 0)
(Figure 4.5a). The majority of the abundant phylotypes classified within the Firmicutes,
Proteobacteria, Actinobacteria and Acidobacteria, with only one in each of the Chloroflexi,
Verrucomicrobia, Gemmatimonadetes and Bacteroidetes. Each of the four soils contained a large
relative abundance of unclassified Bacteria. In general, the most abundant phylotypes in all four
soils, included unclassified Bacillales, unclassified Sphingomonadaceae, Arthrobacter,
unclassified Actinomycetales, unclassified Actinobacteria, Acidobacteria Gp1 and Gp 3 and
unclassified Chitinophagaceae. The most abundant phylotypes in the microcosms not amended
with RDX (No RDX, Time t) were different (Figure 4.5b). These phylotypes only classified
within the Firmicutes, Proteobacteria, Actinobacteria and Bacteroidetes. The most abundant
phylotypes were primarily Firmicutes, including Clostridium XIVa, Tissierella, Sedimentibacter
and unclassified Clostridiaceae 1. In addition, the phylotypes Rhodococcus and unclassified
Chitinophagaceae were abundant in three of the four soils. Not surprisingly, these data clearly
indicate that the incubation conditions (sealed bottles with glucose and a minimal salts media)
completely changed the microbial community structure. Interestingly, the microbial community
that developed following incubation was similar between soils.

79

The most abundant phylotypes were also determined for the microcosms amended with RDX
(Figure 4.6). Similar to the data discussed above (No RDX, Time t), the abundant phylotypes
classified only within the phyla Firmicutes, Proteobacteria, Actinobacteria and Bacteroidetes
(only for soils 10 and 11). Again, the majority of abundant phylotypes classified within the
Firmicutes. Similar phylotypes were enriched across all four soils. For the Firmicutes this
included Sedimentibacter, Tissierella, unclassified Clostridiaceae 1, unclassified Bacillaceae 1.
Other common phylotypes included Brevundimonas (soils 10, 11 and 12), Rhodococcus and
unclassified Bacteria (all four soils). In general, the relative abundance values were similar
between replicates and between the labeled and unlabeled RDX amended samples.

Phylotypes Increasing in Abundance Following RDX Degradation
The communities were further examined to ascertain which microorganisms increased in
abundance following RDX degradation compared to the initial soils and the microcosms without
RDX. These data indicate which microorganisms are gaining a benefit from RDX degradation
(perhaps as an energy, carbon or nitrogen source). For each soil, this involved the selection of the
eight most abundant phylotypes in the microbial communities following RDX degradation.
Following this, for each soil, the relative abundance of these eight phylotypes was determined in
the initial soils and in the microcosms not amended with RDX. The comparison of these data for
each soil has been summarized (Figure 4.7).

The data analysis produced two interesting common trends between the four soils. The
phylotypes Brevundimonas (Proteobacteria, Alphaproteobacateria, Caulobacterales,
Caulobateraceae) and unclassified Bacillaceae 1 (Firmicutes, Bacilli, Bacillales) were both

80

dominant following RDX degradation compared to the controls (initial soil and no RDX
microcosms) in at least three of the four soils. For example, Brevundimonas illustrated a clear
increase in relative abundance following RDX degradation in all four replicates for soils 10, 11
and 12, compared to the controls. The same trend can be seen for unclassified Bacillaceae 1 for
soils 9, 11 and 12.

The family Bacillaceae 1 contains 36 genera, any of which could have been involved in RDX
degradation in the current study. Bacillus is the only genus within the family previously linked to
RDX degradation (8). Members of this family were also dominant among the RDX degrading
microbial community from a saturated contaminated surface soil (47) and have previously been
reported to be involved in PCB (48) and PAH (49) degradation.

The phylotype Brevundimonas classifies within the Alphaproteobacteria. Although many known
anaerobic RDX degraders belong to the phylum Proteobacteria, only one RDX isolate
(Methylobacterium sp.) belongs to the Alphaproteobacteria (50). Therefore, the current study has
provided new insights into the importance of this phylotype for RDX degradation. In other
research, Brevundimonas was involved in degradation of an organophosphorus insecticide (51)
and cellulose (52). They have also been associated with direct petroleum hydrocarbons
degradation (53, 54) and with the root-associated bacterial communities of plants involved in
phytoremediation (55).

The phylotypes Rhodococcus, Tisserella (soil 9), unclassified Erysipelotrichaceae (soil 10),
unclassified Alcaligenaceae (soil 11) and Flavobacterium (soil 12) were also more abundant in

81

the RDX treated samples in comparison to the no RDX controls, however, their relative
abundance values were lower than Brevundimonas or unclassified Bacillaceae 1 (Figure 4.7).

Phylotypes Indicated In Label Uptake
Eight heavy fractions generated from the labeled and unlabeled RDX amended microcosms were
sequenced for soils 9 and 10. The most abundant phylotypes in the heavy fractions from the
labeled RDX amended samples were the focus of additional analysis, as these have previously
been linked to label uptake (35-38). The relative abundance of these phylotypes were compared
to their relative abundance values in the unlabeled fractions (Figure 4.8).

In soil 9, no clear enrichment of phylotypes was observed in the fractions from the labeled RDX
amended microcosm compared to the unlabeled RDX amended microcosm (Figure 4.8a).
Although the average relative abundance values were higher for unclassified Bacillaceae 1,
unclassified Clostridiales and Tissierella from the labeled RDX amended microcosm, the
standard deviations for each point were large. This trend could be attributed to any of three
factors. One, the data was not normalized to DNA concentration or the number of 16S rRNA
genes in each fraction (based on current studies in our laboratory, it is likely that the DNA
concentration was considerably less in the unlabeled RDX amended fractions). Unfortunately,
not enough fraction samples remained for this analysis. The second factor could be a dilution of
the label between several phylotypes, resulting in no clear trend for any particular phylotype.
Third, only the ring carbon and nitrogen was labeled, therefore uptake of any other nitrogen
would not have been noted with this experimental design. As discussed above, for soil 9,
unclassified Bacilliaceae 1 was enriched following RDX degradation. Unfortunately, the SIP

82

results (Figure 4.8a) are not strong enough to indicate this phylotypes was also responsible for
ring label uptake.

The standard deviations were smaller for the fractions generated from soil 10 (Figure 4.8b). In
this soil, phylotypes belonging to Pusillimonas, Rhodococcus and Sedimentibacter were more
abundant in the fractions from the labeled amended samples compared to the fractions from the
unlabeled RDX amended samples. These data indicate these phylotypes were likely involved in
carbon or nitrogen uptake from RDX. All three phylotypes were among the most abundant
microorganisms in the RDX degrading microbial communities. Unexpectedly, Brevundimonas
was not enriched in the heavy fractions of soil 10 and this may be attributed by the inability of
this microorganism to uptake the ring nitrogen or carbon.

Consistent with the fracion data for soil 10, many RDX degrading Rhodococcus isolates have
been identified, including Rhodococcus rhodochrous 11Y (56), Rhodococcus sp. strain DN22
(57-60), Rhodococcus strain YH1 (61), and others (62-64). A recent SIP study also found
Rhodococcus sp. to be associated with RDX degradation in explosive contaminated soils (26).
Although previous research has reported RDX degradation by Rhodococcus under aerobic
conditions, one report indicated RDX degradation under oxygen depleted or anaerobic conditions
(63).

The other genera associated with label uptake in soil 10, Sedimentibacter and Pusillimonas, have
not previously been associated with RDX biodegradation. Members of the genus
Sedimentibacter were found to play a role in DDT transformation under iron reducing conditions

83

(65) and were one of the dominant microorganisms in a hydrocarbon contaminated aquifer (66).
Members of the genus Pusillimonas, (Proteobacteria, Betaproteobacteria, Burkholderiales,
Alcaligenaceae) were dominant members of microbial community capable of concurrently
degrading both phenanthrene and arsenite (67). They were also associated to degradation of
synthetic and natural estrogen (68) and high molecular weight PAHs (69).

In summary, the high throughput sequencing data provided valuable information on which
phylotypes increased in abundance following RDX degradation compared to the initial soil and
microcosms not amended with RDX. The most notable trend was the common increase in
abundance of Brevundimonas and/or unclassified Bacillaceae 1 in the four soils studied. The
data indicate these two phylotypes are benefiting from RDX degradation under these conditions.
Future research is needed to determine the important of these phylotypes at RDX contaminated
sites.

84

APPENDIX

85

Table 4.1. The properties of the four agricultural soils used in this study.

Soil
9
10
11
12

Crop
Corn
Corn
Alfalfa
Corn

Organic
Matter %
1.2
1
1.5
2.2

Sand
%
70
76
80
86

Silt
%
24
22
20
14

Clay
%
6
2
0
0

Textural
Classification
Sandy Loam
Loamy Sand
Loamy Sand
Sand

Soil
pH
4.9
5.5
6.4
6.1

Calcium
mg/kg
489
787
811
1312

Magnesium
mg/kg
68
42
74
242

Potassium
mg/kg
151
108
173
139

Phosphorus
mg/kg
46
79
106
268

CEC
meq/10
0g
5
5
4.6
8.6

Table 4.2. A summary of MiSEQ Illumina data generated from all genomic total DNA samples
and fractions for Soil 9 and Soil 10.

Total DNA samples for four soils (No RDX
Time 0 and t, Labeled 1 & 2, Unlabeled 1
&2 ) (24 samples)
Triplicates, 8 fractions, Soil 9, Labeled 1 (23
samples)
Triplicates, 8 fractions, Soil 9, Unlabeled 1
(23 samples)
Triplicates, 8 fractions, Soil 10, Labeled 1
(23 samples)
Triplicates, 8 fractions, Soil 10, Unlabeled 1
(23 samples)

# of
Final # of Final # of
%
Sequences
Unique
Sequences Chimeric
Following Sequences
Make
Contigs
Command
2,845,956
75,964
1,570,985
10.00

2,304,194

27,609

1,640,354

1.20

2,275,419

27,118

1,646,062

1.20

4,098,173

35,706

3,123,322

0.63

3,286,585

25,614

2,516,050

0.33

86

OM
Level
High
Low
Low
Low

Table 4.3. The classification of anaerobic RDX degrading isolates from previous studies.
Class
Phylum Firmicutes

Order

Family

Full name

Reference(s)

Clostridia

Clostridiales

Clostridiaceae

Clostridium bifermentans

(1)

Clostridia

Clostridiales

Clostridiaceae

(4, 5)

Clostridia
Clostridia
Clostridia

Clostridiales
Clostridiales
Clostridiales

Clostridiaceae
Clostridiaceae
Clostridiaceae

Clostridia
Clostridia
Bacilli
Phylum Fusobacteria

Clostridiales
Clostridiales
Bacillales

Clostridiaceae
Peptococcaceae
Bacillaceae

Clostridium bifermentans
(HAW-1, HAW-G3, HAW-G4,
HAW- E3 and, HAW-EC1)
Clostrdium sp. HAW-EB17
Clostridium sp. EDB2
Clostridium acetobutylicum
Acetobacterium malicum sp.
HAAP-1
Acetobacterium paludosum
Desulfitobacterium sp.
Bacillus sp. HPB2 and HPB3

Fusobacteria

Fusobacteriales

Fusobacteriaceae

Fusobacteria HAW-21

(11)

Enteriobacteriales
Enteriobacteriales
Enteriobacteriales
Enteriobacteriales
Enteriobacteriales
Enteriobacteriales
Pseudomonadales
Alteromonadales
Xanthomonadales
Desulfovibrionales
Desulfuromonadales
Myxococcales

Enteriobacteriaceae
Enteriobacteriaceae
Enteriobacteriaceae
Enteriobacteriaceae
Enteriobacteriaceae
Enteriobacteriaceae
Pseudomonadaceae
Shewanellaaceae
Xanthomonadaceae
Desulfovibrionaceae
Geobacteraceae
Cystobacteraceae

Serratia sp.
Enterobacter sp.
Citrobacter sp.
Morganella sp.
Klebsiella sp.
Providencia sp.
Pseudomonas sp.
Shewenella sp.
Strenophomonas sp.
Desulfovibrio sp.
Geobacter sp.
Anaeromxyobacter sp.

(15)
(12, 14)
(13)
(13, 14)
(16)
(13)
(8)
(11, 18, 19)
(20)
(11, 22, 23)
(21)
(9)

(11)
(2)
(3)
(3, 7)
(6)
(9)
(8)

Phylum
Proteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Gammaproteobacteria
Deltaproteobacteria
Deltaproteobacteria
Deltaproteobacteria

87

25

25

RDX Concentration (mg/L)

Aa
20

20

15

15

10

10

5

5

bB
CONTROL
LABELED
UNLABELED

0

0

1

31

32

1

43

25

c
C

20

20

15

15

10

10

5

5

0

15

16

23

25

dD

0
1

26

27

39

1

19

20

28

Time since RDX was ammended (days)

Figure 4.1. RDX in microcosms amended with labeled RDX (13C3, 15N3), unlabeled RDX (12C3,
14
N3), and killed abiotic controls for Soil 9 (A), Soil 10 (B), Soil 11 (C), Soil 12 (D). Error bars
denote standard deviation from triplicate micrososms. Arrows indicate hypothetical RDX
concentrations on the day of respike.

88

100%
90%
80%
70%
60%

50%
40%
30%
20%
10%

Soil 9

Soil 10

Soil 11

Unlabeled 2 Time(t)

Labeled 2 Time(t)

Unlabeled 1 Time(t)

Labeled 1 Time(t)

No RDX Time(t)

No RDX Time(0)

Unlabeled 2 Time(t)

Labeled 2 Time(t)

Unlabeled 1 Time(t)

Labeled 1 Time(t)

No RDX Time(t)

No RDX Time(0)

Unlabeled 2 Time(t)

Labeled 2 Time(t)

Unlabeled 1 Time(t)

Labeled 1 Time(t)

No RDX Time(t)

No RDX Time(0)

Unlabeled 2 Time(t)

Labeled 2 Time(t)

Unlabeled 1 Time(t)

Labeled 1 Time(t)

No RDX Time(t)

No RDX Time(0)

0%

Soil 12

Firmicutes

Proteobacteria

Actinobacteria

unclassified

Bacteroidetes

Acidobacteria

Verrucomicrobia

Chloroflexi

Gemmatimonadetes

Others

Figure 4.2. Phyla level comparison between the four soils of the communities in 1) the initial
soils (No RDX, Time 0), 2) replicates of the labeled and unlabeled RDX amended microcosms
(Labeled 1 & 2, Unlabeled 1 & 2, Time t) and 3) microcosms without RDX addition (No RDX,
Time t).

89

A

Figure 4.3. MLTree Map (A) and heatmap analysis (B) of the phylotypes within the initial soils
and in samples with and without RDX. To simplify the presentation, only one replicate was used
for the RDX amended samples.

90

Figure 4.3.(cont’d)

B

91

A

6000

Soil 9
5000

Number of OTUs

4000

Soil 10

3000

Soil 11
2000

1000

Soil 12

No RDX Time(0)

No RDX Time(t)

Labeled 1 Time(t)

Unlabeled 1 Time(t)

Labeled 2 Time(t)

Unlabeled 2 Time(t)

No RDX Time(0)

No RDX Time(t)

Labeled 1 Time(t)

Unlabeled 1 Time(t)

Labeled 2 Time(t)

Unlabeled 2 Time(t)

No RDX Time(0)

No RDX Time(t)

Labeled 1 Time(t)

Unlabeled 1 Time(t)

Labeled 2 Time(t)

Unlabeled 2 Time(t)

No RDX Time(0)

No RDX Time(t)

Labeled 1 Time(t)

Unlabeled 1 Time(t)

Labeled 2 Time(t)

Unlabeled 2 Time(t)

0
0

50000

100000

150000

200000

Number of sequences

B

0.4

S9RDXTDNA

PC2 percent variation explained 20.9 %

0.3

Soil 9
S12RDXTDNA

0.2

NoRDXt
0.1

Soil 10
0
-0.8

-0.6

-0.4

-0.2

0

0.2

-0.1

0.4

S11RDXTD

NoRDXt0

Soil 11

NA

-0.2

S10RDXTD
NA

No RDX Time(0)

No RDX Time(t)

Labeled 1 Time(t)

Unlabeled 1 Time(t)

Labeled 2 Time(t)

Unlabeled 2 Time(t)

No RDX Time(0)

No RDX Time(t)

Labeled 1 Time(t)

Unlabeled 1 Time(t)

Labeled 2 Time(t)

Unlabeled 2 Time(t)

No RDX Time(0)

No RDX Time(t)

Labeled 1 Time(t)

Unlabeled 1 Time(t)

Labeled 2 Time(t)

Unlabeled 2 Time(t)

No RDX Time(0)

No RDX Time(t)

Labeled 1 Time(t)

Unlabeled 1 Time(t)

Labeled 2 Time(t)

Unlabeled 2 Time(t)

-0.3

Soil 12
-0.4
PC1 percent variation explained 30.3 %

Figure 4.4. Rarefaction curves (A) and Principal Component Analysis (B) of sequencing data
generated from all four soils, including total DNA extracts of the labeled RDX (Labeled 1 & 2,
Time t), unlabeled RDX (Unlabeled 1 & 2, Time t), no RDX (No RDX, Time t) microcosms and
the initial soils (No RDX, Time 0).

92

0

93
unclassified Bacteria

Gemmatimonas

unclassified Bacteria

unclassified Chitinophagaceae

5

unclassified Chitinophagaceae

10

Chloroflexi
Verrucomicrobia
Gemmatimonadetes
Bacteroidetes

Acidobacteria

Spartobacteria

Soil 12

Ktedonobacter

Acidobacteria Gp16

Acidobacteria Gp6

Acidobacteria Gp4

Acidobacteria Gp3

Acidobacteria Gp1

unclassified Actinobacteria

20

Pedobacter

unclassified Actinomycetales
unclassified Solirubrobacterales

A. No RDX, Time 0 (initial soil)

Chryseobacterium

Arthrobacter

Rhodococcus

Proteobacteria

unclassified Xanthomonadaceae

unclassified Microbacteriaceae
unclassified Intrasporangiaceae

Actinobacteria

Rhodanobacter

unclassified Cystobacteraceae

unclassified Alcaligenaceae

unclassified Burkholderiales

unclassified Nocardioidaceae
unclassified Micromonosporaceae

Soil 11

Methylophilus

Firmicute

Pusillimonas

Arthrobacter
Pseudonocardia

Soil 10

Massilia

unclassified Sphingomonadaceae

Aeromicrobium

Solirubrobacter

Conexibacter

unclassified Proteobacteria

Proteobacteria

Brevundimonas

Methylophilus
unclassified Betaproteobacteria

Soil 9

unclassified Firmicutes

unclassified Bacillales

unclassified Rhizobiales
unclassified Alphaproteobacteria

25

unclassified Lachnospiraceae

unclassified Bacillaceae 1

unclassified Erysipelotrichaceae

Soil 11

unclassified Clostridiaceae 1

unclassified Sphingomonadaceae

Sphingomonas

Hyphomicrobium

unclassified Bacillales

unclassified Bacillaceae 1

Paenibacillus

Lysinibacillus

Firmicute

unclassified Ruminococcaceae

Soil 10

unclassified Lachnospiraceae

30

Sporomusa

Proteiniborus

Soil 9

Clostridium III

Lysinibacillus

15
Bacillus

Tumebacillus

15

Sedimentibacter

20

Tissierella

Clostridium sensu stricto

0

Clostridium XlVa

Relative Abundance (%)
30

B. No RDX, Time T

25
Actinobacteria Bacteroidetes

Soil 12

10

5

Figure 4 5. A comparison of the relative abundance (%) of the most common phylotypes (>1% ,
at the lowest classification level) in all four soils in the no RDX samples, including the initial
soils (No RDX, Time 0) (A) and the microcosms without RDX (No RDX, Time t) (B).

0

94
Unlabeled Rep 1

20
Proteobacteria

Labeled Rep 2

unclassified Bacteria

Proteobacteria

unclassified Bacteria

Arthrobacter

Rhodococcus

Labeled Rep 2

unclassified Bacteria

Proteobacteria

unclassified
Bacteria

Firmicutes
Chryseobacterium

Proteobacteria

Pedobacter

Rhodococcus

unclassified
Oxalobacteraceae

unclassified
Cystobacteraceae

Dokdonella

unclassified
Firmicutes

unclassified Bacillales

unclassified
Lachnospiraceae

unclassified
Ruminococcaceae

unclassified
Erysipelotrichaceae

unclassified
Bacillaceae 1

unclassified
Clostridiaceae 1

Unlabeled Rep 1

Flavobacterium

Labeled Rep 1

Rhodococcus

Rhodanobacter

Brevundimonas

Firmicutes

Rhodococcus

unclassified
Alcaligenaceae

Brevundimonas

unclassified Firmicutes

unclassified Bacillales

unclassified
Lachnospiraceae

unclassified
Erysipelotrichaceae

unclassified
Bacillaceae 1

Clostridium III

Clostridium XlVa

Tissierella

Lysinibacillus

Labeled Rep 1

Pseudomonas

40

unclassified
Sphingobacteriaceae

Firmicutes

Brevundimonas

unclassified Firmicutes

unclassified Bacillales

unclassified
Firmicutes

unclassified
Planococcaceae

C. Soil 11, RDX Time T

unclassified
Planococcaceae

unclassified
Clostridiaceae 1

D. Soil 12, RDX Time T

unclassified
Lachnospiraceae

Labeled Rep 2

unclassified
Bacillaceae 1

40
Labeled Rep 2

unclassified
Clostridiaceae 1

Unlabeled Rep 1

unclassified
Clostridiaceae 1

Unlabeled Rep 1

unclassified Bacillaceae
1

unclassified
Clostridiaceae 1

B. Soil 10, RDX Time T

unclassified
Erysipelotrichaceae

Tissierella

Pusillimonas

60
Sedimentibacter

A. Soil 9, RDX Time T

Lysinibacillus

0
Tissierella

Labeled Rep 1

Pusillimonas

60
Labeled Rep 1

Clostridium XlVa

60

Tissierella

80
Sedimentibacter

0

Sedimentibacter

40

Sedimentibacter

Relative Abundance (%)
40
30
20
10
0
Firmicutes
Unlabeled Rep 2

Actinobacteria

Unlabeled Rep 2

20
Actinobacteria Bacteroidetes

Unlabeled Rep 2

20
Actinobacteria

80

Actinobacteria
Bacteroidetes

Unlabeled Rep 2

Figure 4.6. A comparison of the relative abundance (%) of the most common phylotypes (>1% ,
at the lowest classification level) in all four soils (A-D) following RDX degradation.

30

Soil 9

Initial

No RDX

Labeled Rep 1

Unlabeled Rep 1

Labeled Rep 2

Unlabeled Rep 2

20
10
0
unclassified
Bacillaceae 1
60

unclassified
Clostridiaceae 1

unclassified
Cystobacteraceae

Rhodococcus

Lysinibacillus

Tissierella

unclassified
Erysipelotrichaceae

Soil 10
Initial

40

Relative Abundance (%)

Sedimentibacter

No RDX

Labeled Rep 1

Unlabeled Rep 1

Labeled Rep 2

Unlabeled Rep 2

20

0
Brevundimonas

unclassified
Erysipelotrichaceae

Tissierella

Pusillimonas

Sedimentibacter

Rhodococcus

unclassified
Clostridiaceae 1

unclassified
Lachnospiraceae

80
60

Soil 11
Initial

No RDX

Labeled Rep 1

Unlabeled Rep 1

Labeled Rep 2

Unlabeled Rep 2

40
20
0
Brevundimonas

unclassified
Bacillaceae 1

unclassified
Alcaligenaceae

Tissierella

unclassified
Clostridiaceae 1

Rhodococcus

unclassified
Planococcaceae

Sedimentibacter

60
40

Initial

No RDX

Labeled Rep 1

Unlabeled Rep 1

Labeled Rep 2

Unlabeled Rep 2

20

0
unclassified
Bacillaceae 1

Brevundimonas

unclassified
Sedimentibacter
Erysipelotrichaceae

unclassified
Firmicutes

unclassified
Clostridiaceae 1

Flavobacterium

Rhodococcus

Figure 4.7. The relative abundance (%) of the eight most abundant phylotypes in the four RDX
amended agricultural soils (Labeled 1 &2, Unlabeled 1 &2, Time t) compared to the RDX
controls (initial soil and no RDX microcosms). Boxed phylotypes illustrate a greater abundance
in RDX amended samples compared to the RDX controls for at least three soils. The phylotypes
are at genus level, unless unclassified.

95

A. Soil 9
20

B. Soil 10

unclassified Bacillaceae 1

15

Pusillimonas

15
10
Unlabeled

10

Labeled

5
5

Relative Abundance (%)

0
1.73

12

1.74

1.75

1.76

1.77

0
1.73 1.74 1.75 1.76 1.77 1.78 1.79

1.78

unclassified Clostridiales

15

8

10

4

5

0
1.73
10

1.74

1.75

1.76

1.77

Rhodococcus

0
1.73 1.74 1.75 1.76 1.77 1.78 1.79

1.78

Tissierella

10

Sedimentibacter

8
6
5

4
2
0
1.73

1.74

1.75

1.76

1.77

0
1.73 1.74 1.75 1.76 1.77 1.78 1.79

1.78

Buoyant Density (g mL-1)

Figure 4.8. Relative abundance of the most common phylotypes in heavy fractions from the
labeled RDX amended microcosms compared to those from the unlabeled RDX amended
microcosms in Soil 9 (A) and Soil 10 (B). Bars illustrate standard deviations from triplicate
sequencing data.

96

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CHAPTER 5 STABLE ISOTOPE PROBING REVEALS THE IMPORTANCE OF
COMAMONAS AND PSEUDOMONADACEAE IN RDX DEGRADATION IN SAMPLES
FROM A NAVY DETONATION SITE

ABSTRACT
This study investigated the microorganisms involved in RDX degradation from a detonation area
at a Navy Base. Using Illumina sequencing, microbial communities were compared between the
initial sample, samples following RDX degradation and controls not amended with RDX to
determine which phylotypes increased in abundance following RDX degradation. The effect of
glucose on these communities was also examined. In addition, stable isotope probing (SIP) using
labeled (13C3, 15N3) RDX was performed.

Illumina sequencing revealed several phylotypes were more abundant following RDX
degradation compared to the initial soil and the no RDX controls. For the glucose amended
samples, this trend was strong for an unclassified Pseudomonadeae phylotype and for
Comamonas. Without glucose, Acinetobacter illustrated the greatest increase following RDX
degradation compared to the initial soil and no RDX controls. Rhodococcus, a known RDX
degrader, also increased in abundance following RDX degradation.

For the SIP study, unclassified Pseudomonadaceae was the most abundant phylotype in the
heavy fractions in both the presence and absence of glucose. In the glucose amended heavy

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fractions, Comamonas and Anaeromxyobacter were also present. Without glucose, the heavy
fractions also contained Azohydromonas and Rhodococcus. However, all four phylotypes were
present at a much lower level compared to unclassified Pseudomonadaceae. Overall, these data
indicate unclassified Pseudomonadaceae were primarily responsible for label uptake in both
treatments. When glucose was present, Comamonas increased in abundance following RDX
degradation and was enriched in the heavy fractions, suggesting, for the first time, that this
phylotype is also important for RDX removal.

INTRODUCTION
RDX (hexahydro-1,3,5-trinitro-1,3,5-triazine) is an explosive that has caused widespread soil
and water contamination at many military sites in the US and worldwide. Such contamination
has been associated with manufacturing and load-assemble-package processes performed during
or after World War II and the Korean Conflict. Remediation of these sites has been initiated
since the early 1980s, however many still have groundwater contaminated with nitroaromatics.
The U.S. EPA has established a health advisory level in drinking water for RDX (2 μg/L),
indicating the potential threat to humans. RDX is susceptible to aerobic or anaerobic
biodegradation (1-10), therefore bioremediation offers a plausible approach for site clean-up.
Anaerobic RDX degradation can occur via hexahydro-1-nitroso-3,5-dinitro-1,3,5-triazine
(MNX), hexahydro-1,3-dinitroso-5-nitro-1,3,5-triazine (DNX), and hexahydro-1,3,5-trinitroso1,3,5-triazine (TNX) (11), forming methanol and formaldehyde. Denitration has also been
reported under anaerobic conditions, involving ring cleavage and methylene denitramine
(MEDINA) formation (5, 9). Under aerobic conditions, denitration appears to be a common
pathway (12). RDX denitration has been coupled with ring cleavage generating 4-nitro-2,4-

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diazabutanal (NDAB) as a ring cleavage product (13). MEDINA has also been observed as a ring
cleavage product (14, 15). In all, known RDX degrading aerobic or anaerobic isolates classify
within the phyla Firmicutes, Actinobacteria, Proteobacteria (Alpha-, Gamma- and
Deltaproteobacteria) and Fusobacteria (12). However, researchers have reported the
microorganisms detected in field samples actively degrading RDX were generally not closely
related to previously reported RDX degrading bacterial strains (16). The identification of RDX
degraders at these sites is important for 1) determining if natural attenuation is a feasible
approach across sites and 2) monitoring the populations of the microorganisms involved.

Although much is known about the pure cultures able to degrade RDX in the laboratory, very
little is known about the microorganisms responsible for RDX degradation at contaminated sites.
One group concluded that previously reported RDX degrading bacteria did not capture the
microbial diversity associated with RDX bioremediation in groundwater, especially under typical
biostimulation approaches (17). Indeed, it is now widely recognized that only a small percentage
of microorganisms can be isolated and cultivated in the laboratory (18), therefore, it is likely that
in situ RDX degraders have yet to be identified. However, recent advances in molecular biology
have enabled a wealth of information concerning a range of microbial processes. A number of
molecular approaches have been used to investigate RDX degraders in mixed communities, such
as terminal restriction fragment length polymorphism (TRFLP), Sanger sequencing (17, 19-21)
and stable isotope probing (SIP) (22-25). SIP is a culture independent method that targets only
active organisms and involves sample exposure to a labeled substrate, incubation, nucleic acid
extraction, ultracentrifugation to separate the labeled nucleic acid from the unlabeled background
nucleic acid, and finally molecular analysis to identify the organism(s) responsible for label

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uptake. The method is advantageous because there is no requirement to work with pure cultures
and so SIP can identify the microorganisms involved in label uptake in mixed cultures, e.g. soil
samples. The method has been particularly valuable for detecting microorganisms involved in
contaminant degradation (26-30).

To date, for RDX degradation studies, SIP has only been combined with TRFLP and/or Sanger
sequencing. These approaches have their limitations because it is not always possible to
sequence enough clones to identify the phylotypes involved in label uptake. In this study, we
advance this methodology by combining SIP with high throughput sequencing to investigate the
microorganisms responsible for label uptake from RDX. This is the first report of using both
methods to examine RDX degraders.

Here, the objective was to identify the microorganisms involved in RDX degradation in soils
from a detonation area at a Navy Base. The research also explores the effect of glucose on RDX
degradation and the microorganisms involved. RDX biodegradation and bioremediation often
involves the addition of a carbon source(31). Glucose was added in this study, based on previous
research indicating enhanced RDX degradation in other soil samples when this substrate was
added (24). The microbial communities were investigated both in the presence and in the
absence of glucose. The research combined SIP and high throughput sequencing to provide two
layers of data. Firstly, phylotypes illustrating an increase in relative abundance following RDX
degradation compared to controls (initial soil and samples with no RDX added) were determined
with Illumina sequencing. Secondly, DNA based SIP (15N and 13C RDX) was used to identify
which microorganisms were involved in label uptake from RDX. The wealth of information

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provided by coupling high throughput sequencing with SIP has enabled the identification of
novel RDX degraders and has provided data that can be used to design primers for the detection
of these microorganisms at other RDX contaminated sites.

METHODS
Chemicals
Unlabeled and ring- labeled RDX (13C3, 99%; 15N3, 98%) in acetonitrile (1,000 mg/L) were
purchased from Cambridge Isotope Laboratories (Andover, MA). Other reagents were purchased
from Sigma Aldrich® Corp. (St. Louis, MO) or Thermo Fisher Scientific Inc. (Waltham, MA),
unless otherwise stated. HPLC grade acetonitrile was purchased from EMD Millipore
(Chemicals), a division of Merck KGaA (Darmstadt, Germany).

Experimental Setup and DNA Extraction
The soil was collected from a Navy Installation in Virginia. Soil samples were first screened for
their ability to degrade RDX. For this, duplicate killed controls (autoclaved) and live microcosms
were prepared using 4 mL of a mineral salts media (MSM) (Thompson et al 2005), 1 mL of
glucose (1 g L-1), 1.5 g of soil (dry weight) and 10 mg L-1 of unlabeled RDX in amber serum
bottles. Microcosms were sealed with rubber stoppers and aluminum seals and stored in the dark
(~20 °C) without shaking. For the SIP study, microcosms were prepared with or without glucose.
The serum bottles (30 mL) included 2 g of soil with either 4 mL of mineral media and 1 mL of
glucose (1 g L-1 stock solution) or 5 mL of MSM. Then, 10 mg L-1 of labeled (13C3, 15N3-RDX)
or unlabeled RDX was added. A total of 2 killed controls (sterilized by autoclaving), 4 unlabeled
controls (10 mg L-1 unlabeled RDX) and 2 labeled sample microcosms (10 mg L-1 of labeled

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13

C3, 15N3-RDX) were prepared for each of the two treatments (with or without glucose). Two

additional controls (no RDX controls) were also included, both were not amended with RDX and
only one was amended with glucose. These controls were incubated under the same conditions as
the above samples.

Following the degradation of the first addition of RDX (30 days), eight microcosms (replicate
microcosms with labeled RDX and glucose, unlabeled RDX and glucose, labeled RDX and no
glucose and unlabeled RDX and no glucose) and the two no RDX controls (with and without
glucose) were sacrificed and the total genomic DNA was extracted. DNA was extracted using
the Power Soil DNA extraction kit (MO BIO Laboratories, Inc. Carlsbad, CA) as per
manufacturer’s instructions. In the remaining replicate microcosms initially amended with
unlabeled RDX (with and without glucose), a second amendment of 10 mg L-1 of RDX
(unlabeled) was added. This was degraded under 20 days and the total genomic DNA was
extracted from these samples. DNA was also extracted from the initial soil. In all, fifteen total
genomic DNA extracts were submitted for Illumina sequencing (a list is provided below).

Analytical Methods
RDX extraction and analysis methods were modified from those previously described
(Thompson et al 2005). Briefly, 200 µL from each microcosm was removed into 1.7 mL
microcentrifuge tubes. RDX was extracted by adding equal volumes of acetonitrile and shaking
the tubes at room temperature for 30 minutes. Following this, the tubes were centrifuged at
10,000 rpm for 5 minutes. The supernatant (350 µL) was filtered using 0.22 µm sterile filters
into HPLC amber vials (Sigma). The HPLC parameters were as follows: injector volume, 20 µL;

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isocratic conditions (40% acetonitrile and 60% 0.01% H3PO4-acidified water, 1 mL/min);
Perkin Elmers (PE) Series 200 autosampler; PE binary LC Pump 250; Waters UV detector;
wavelength 255 nm (detection limit was 500 µg/L).

Isopycnic Centrifugation
Total genomic DNA extracted from four microcosms with one amendment of RDX was subject
to ultracentrifugation and fractioning. This involved two microcosms amended with glucose
(labeled and unlabeled RDX amended) and two not amended with glucose (labeled and
unlabeled RDX amended). The extracted DNA was ultracentrifuged with cesium chloride and
tris-EDTA buffer solution. Specifically, 3 to 5 µg of DNA was added to a Tris-EDTA (pH 8.0)
buffer and cesium chloride solution. The initial buoyant density (BD) of this mixture was
adjusted to ~1.72 g mL-1 using a model AR200 digital refractometer (Leica Microsystems Inc.).
This mixture was then loaded to a 5.1 mL Quick-Seal polyallomer tubes (1.3 x 5.1 cm, Beckman
Coulter) and sealed using a tube topper (Cordless quick-seal tube topper, Beckman). The tubes
were balanced in a Stepsaver 70 V6 Vertical Titanium Rotor (Thermo Scientific) and centrifuged
at 178,000 x g for 46 hours at 20 °C in a Wx Sorvall Ultracentrifuge to obtain density gradients.
The density gradients were separated into 20 fractions (each 250 µL) using gravity by displacing
the samples by molecular grade water pumped by a syringe pump. Each fraction was mixed and
sampled to measure their refractive index to calculate the buoyant density. The fractions were
cleaned using a glycogen and ethanol precipitation to remove the cesium chloride and precipitate
the DNA. They were then re-suspended in 30 µL PCR grade molecular water and stored at -20
°C until further analysis. The concentration of DNA in each fraction was quantified with the
Quant-iT™ dsDNA High-Sensitivity Assay Kit using the Qubit® 2.0 Fluorometer.

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Illumina MiSeq™ High Throughput Amplicon Sequencing
Both total genomic DNA extracts and selected fractions were submitted for high throughput
amplicon sequencing following the protocol described elsewhere (32, 33) at the Research
Technology Support Facility (RTSF) at Michigan State University. Fractions were selected based
on the comparison of DNA concentrations over the buoyant density range in the fractions
obtained from the unlabeled and labeled RDX amended microcosms. Those fractions from the
labeled RDX amended microcosms illustrating a higher DNA concentration at the higher
buoyant density values were selected for sequencing. This resulted in six fractions being
sequenced for each of the four samples ultracentrifuged. Further, each fraction was sequenced
with three replicates. In addition, fifteen total DNA samples were submitted for sequencing,
including DNA extracted from 1) the soil prior to any incubation (called initial soil), 2) the two
no RDX controls (one with glucose and the other without glucose), 3) replicate microcosms
amended with labeled RDX and no glucose, 4) replicate microcosms amended with unlabeled
RDX and no glucose, 5) replicate microcosms amended with labeled RDX and glucose, 6)
replicate microcosms amended with unlabeled RDX and glucose, 7) replicate microcosms
amended with two additions of unlabeled RDX and no glucose and 8) replicate microcosms
amended with two additions of unlabeled RDX and one addition of glucose.

Illumina specific fusion primers were used to amplify the V4 region of the 16S rRNA (32) and to
add unique barcodes to samples in each well to enable pooling and sequencing. After the
amplicons were checked on 1% agarose gel, equimolar amounts of the sample were pooled to
normalize results, purified and then sequenced on the Illumina MiSeq™ Personal Sequencing
System. The amplicon sequencing data in the fastq file format was analyzed on Mothur version

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1.33.0 from Patrick D. Schloss Laboratory (34) using the MiSeq standard operating procedure
(35, 36). Barcode information was removed from the sequence data and contiguous sequences
were created using the forward and reverse reads, were analyzed for errors and then classified.
Samples were checked for the proper read length (<275 bp), ambiguous bases and homopolymer
length greater than 8 to eliminate such sequences. These sequences were then aligned with the
SILVA bacteria database (37) for the V4 region. Chimeras, mitochondrial and chloroplast
lineage sequences were removed and then the sequences were classified into OTU’s. The OTUs
were then grouped into taxonomical levels with corresponding confidence levels. Rarefaction
curves, Cho1 and Shannon values were determined for all DNA extracts using Mothur. Illumina
sequencing data was deposited in the NCBI Sequence Read Archive under BioProject Number
PRJNA264536.

Data Analysis
The most abundant phylotypes (>1% relative abundance) in all fifteen DNA extracts were
determined and compared to ascertain differences and similarities between the microbial
communities. The relative abundance of phylotypes was compared between the no RDX controls
(initial soil and no RDX amended microcosms) to determine which phylotypes experienced an
increase in abundance following exposure to RDX. In addition, the relative abundance (%) of the
most abundant phylotypes in the fractions of the labeled RDX amended samples were
determined. These abundance values were then compared to values from the fractions obtained
from the unlabeled RDX amended samples. The purpose of this comparison was to determine
which phylotypes had incorporated the 15N or 13C label from RDX and would thus be found in
the heavier fractions.

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RESULTS
RDX degradation occurred in all live microcosms within 30 days, whereas no removal of RDX
was noted in the abiotic controls (data not shown). In the live microcosms, additional HPLC
peaks appeared and when these were compared to analytical standards, they were identified as
the mono-, di- and tri-nitroso derivatives of RDX. By day 30, all additional peaks had
disappeared and DNA was extracted at this time. An extra amendment of RDX was added to
four microcosms and this was removed (as were the metabolites) within 20 days. Again, DNA
was extracted at this time.

High throughput sequencing was conducted on fifteen total genomic DNA extracts to investigate
the microbial communities present following each treatment. For this, the most abundant
phylotypes (>1% relative abundance) were compared between the microbial communities of
each sample (Figure 5.1). The most abundant phylotypes in the initial soil microbial community
was clearly different from the most abundant phylotypes in the other samples. For example, GP4
was the most abundant phylotype in the initial soil (12.8%), however in the other communities, it
was present only at a low level (<2.1%). In addition, the three most common phylotypes in the
other samples (unclassified Pseudomonadaceae, Acinetobacter and Gracilibacter) were present
only at low levels in the initial soil community (<0.07%). As expected, the microbial
communities were similar between the microcosms amended with labeled and unlabeled RDX.
The addition of glucose also did not greatly change the most abundant phylotypes present. The
four most abundant phylotypes in the microcosms amended with RDX in the absence of glucose
were unclassified Pseudomonadaceae, Acinetobacter, Gracilibacter and unclassified
Bacteroidetes. Whereas, in the presence of glucose and RDX, the four most abundant phylotypes

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were Pseudomonadaceae, Acinetobacter, Gracilibacter and Comamonas. Further, the
communities that received two amendments of RDX were similar to those that received only one
amendment.

Rarefaction curves (Figure 5.2) indicated that the majority of the populations were represented as
these started to plateau for all of the samples. In contrast, the curve for the initial soil microbial
community was still increasing, suggesting additional data is needed to represent the complete
diversity of this sample. The total number of OTUs or species richness was estimated using the
Chao1 estimator (Table 5.1). In general, the RDX and glucose amended microcosms appeared to
have greater species richness compared to the RDX amended microcosms that did not receive
glucose. The Chao1 value for the initial soil was notably higher than all of the other samples.
The Shannon diversity value for the initial soil was also higher than all other Shannon values
(Table 5.1). Again, the glucose amended samples illustrated higher Shannon values compared to
the samples that were not amended with glucose.

To determine which microorganisms were enriched following RDX degradation, the relative
abundance of each in RDX amended microcosms was compared to the initial soil and the no
RDX control microcosms. Phylotypes with greater relative abundance in the RDX amended
microcosms compared to the no RDX controls are shown (Figure 5.3). For the glucose amended
samples, five bacteria illustrated an increase over the controls (Figure 5.3a). From these, three
illustrated a larger increase in abundance compared to the controls, including unclassified
Pseudomonadeae, Pseudomonas and Comamonas. For the microbial communities in the absence
of glucose, Acinetobacter illustrated the greatest increase compared to the initial soil and no

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RDX controls (Figure 5.3b). In the absence of glucose, Rhodococcus (a genus containing many
known RDX degrading isolates) also increased in abundance, although it was at a much lower
level than Acinetobacter. Interestingly, both treatments resulted in a greater relative abundance
of Comamonas and Sedimentibacter in the RDX amended samples compared to the initial soil
and no RDX controls.

Total DNA samples from the labeled and unlabeled RDX amended microcosms for both the
glucose and no glucose samples were subject to ultracentrifugation and fractioning. The DNA
concentration in each fraction was then determined (Figure 5.4). The DNA concentration was
higher in the heavier fractions for the labeled RDX amended samples compared to the unlabeled
RDX amended samples, indicating an enrichment of nucleic acids with 13C and/or 15N. This
pattern occurred in both the glucose (Figure 5.4a) and the no glucose samples (Figure 5.4b). The
heavy fractions were submitted for Illumina sequencing (three replicates for each) to determine
which phylotypes were responsible for label uptake.

The three most abundant phylotypes in the heavy fractions from the labeled RDX amended
samples were determined for both treatments (Figure 5.5). The sequencing data from the three
replicates were similar, resulting in small error bars. From this analysis, only one phylotype
(unclassified Pseudomonadaceae) was similar between treatments and, in both cases, it was the
most dominant phylotype in the heavy fractions. In the glucose amended heavy fractions
Comamonas and Anaeromyxobacter were also present, but at a much lower level compared to
unclassified Pseudomonadaceae (Figure 5.5a). In the heavy fractions from the no glucose
samples, Azohydromonas and Rhodococcus were present and again this occurred at a much lower

116

level compared to the unclassified Pseudomonadaceae phylotype (Figure 5.5b). These data
indicate unclassified Pseudomonadaceae were primarily responsible for label uptake in the soil
microcosms, both in the absence and presence of glucose.

DISCUSSION
The potential for any site to biodegrade RDX is particularly difficult to predict because of the
large number of RDX degrading isolates and the lack of correlation between these isolates and
the species found at contaminated sites. To address this, the current study combined SIP and high
throughput sequencing to provide an in depth analysis of the microorganisms linked to RDX
degradation in samples from a Navy Base. The study utilized two layers of information to link
RDX degradation with microorganism identity. Firstly, phylotypes illustrating an increase in
relative abundance following RDX degradation, compared to controls (initial soil and samples
with no RDX added) were determined. This approach is similar to using quantitative PCR to
document growth on a substrate for specific phylotypes within mixed communities. It cannot be
definitely stated that these microorganisms were growing using RDX as a carbon, nitrogen or
energy source. However, because their abundance increased following RDX degradation, they
were clearly benefiting from this process. Further, in replicate samples not exposed to RDX, this
increase did not occur. Secondly, SIP was used to identify which microorganisms were involved
in label uptake from RDX. Combining the results from these two approaches has provided an
enhanced data set for documenting the microorganisms involved in RDX degradation.

To date, a range of molecular methods have been used to examine microbial communities at
RDX contaminated sites, including terminal restriction fragment length polymorphism (TRFLP),

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lipid biomarker analysis (38), denaturing gradient gel electrophoresis (17, 19, 39), amplified 16S
rDNA restriction analysis (ARDRA)(21), cloning and Sanger sequencing (17, 19-21). Only
recently (2013), has high throughput sequencing (pyrosequencing, not in combination with SIP)
been applied to examine RDX degrading microbial communities (40). Four studies have applied
SIP to investigate RDX degradation (22-25). SIP has the advantage over these methods in that
the labeled carbon or nitrogen derived from RDX can be linked to microorganism identity,
providing more robust information on the microorganisms involved in RDX degradation.
The current study is the first to combine SIP with high throughput sequencing to investigate the
microorganisms responsible for RDX degradation. Using high throughput sequencing, rather
than Sanger sequencing, with SIP provides a much greater depth of information on the
microorganisms involved. To our knowledge, SIP has been used in combination with traditional
Sanger sequencing in four studies to examine RDX degradation (22-25). One study using 15N
and 13C labeled RDX revealed the important of Sphingobacteriales in label uptake (24). Another
SIP study (15N labeled RDX) using samples from the Picatinny Arsenal Site identified five
phylotypes similar to known RDX degraders and ten phylotypes not previously linked to RDX
degradation (25). The authors reported that several of these phylotypes classified within the
genus Pseudomonas. The authors did not report any enrichment of phylotypes from the
Betaproteobacteria, indicating they did not find enrichment of the genus Comamonas. A more
recent SIP study (2013), using 13C labeled RDX, also reported the importance of Pseudomonas
phylotypes in label uptake (23). The 2013 study also found that Rhodoferax, a genus within the
same family (Comamonadaceae) as Comamonas, was responsible for label uptake. However, the
research also reported label uptake over a range of phyla, including Proteobacteria,
Spirochaetes, Bacteroidetes, Firmicutes, and Actinobacteria (23). The fourth SIP study (15N

118

labeled RDX), using material from the Eglin Air Force Base bombing range, found that
Rhodococcus illustrated the greatest amount of label uptake (22). From the other seven
phylotypes that were associated with label uptake, one classified (Variovorax) within the same
family as Comamonas and another classified within the same order (Burkholderiales). The
results obtained in the current study agree with previous SIP studies, indicating the importance of
phylotypes within the families Pseudomonadaceae and Comamonadaceae in label uptake from
RDX. In addition, similar to previous studies, the current research also found that Rhodococcus
was associated with label uptake. Taken together, these data indicate that primers designed
towards these phylotypes would be advantageous for investigating the feasibility of
bioremediation across RDX contaminated sites.

Known RDX degrading isolates classify within four phyla, the Firmicutes, Actinobacteria,
Proteobacteria and Fusobacteria. The phylum Firmicutes contains many RDX degrading
bacteria and these fall within the class Clostridia or Bacilli (9, 10, 41-47). In the current study,
unclassified Clostridiaceae 1 and Sedimentibacter were enriched following RDX degradation,
but were not linked with label uptake from RDX. The phylum Actinobacteria also contains RDX
degrading isolates including many within the genus Rhodococcus (14, 48-55). Other
Actinobacteria isolates include Williamsia sp. KTR4 (56), Gordonia sp. KTR9 (56, 57) and
Gordonia sp. YY1 (19). The data from the current study indicate Rhodococcus phylotypes
increased in abundance following RDX degradation and the SIP data suggest these phylotypes
are responsible for lower levels of label uptake.

119

RDX degrading isolates in the phylum Proteobacteria are found within the Alpha-, Gamma- and
Deltaproteobacteria classes (12). In the current study, Anaeromxyobacter was the only
Deltaproteobacteria implicated in label uptake and previous research has indicated this genus is
capable of RDX degradation (46). In the Betaproteobacteria, two phylotypes were associated
with label uptake (Comamonas was particularly enriched and Azohydromonas was enriched to a
lower level). Interestingly, no pure cultures of Betaproteobacteria have been shown to be
capable of RDX degradation. The most dominant phylotype responsible for label uptake was a
Gammaproteobacteria, unclassified Pseudomonadaceae. Any of the eight genera within this
family (Azomonas, Azorhizophilus, Azotobacter , Cellvibrio, Pseudomonas. Rhizobacter,
Rugamonas, Serpens) could have been responsible for label uptake. These results collaborate
previous research, as many Gammaproteobacteria isolates are able to degrade RDX (1, 4, 5, 58,
59). When the unclassified Pseudomonadaceae partial 16S rRNA gene sequence was compared
to those in Genbank it was found to be 100% similar to twenty uncultured bacterium sequences,
seven Pseudomonas sequences, and four Azotobacter tropicalis sequences. In the current study
Pseudomonas was also enriched following RDX degradation and again Pseudomonas isolates
have been shown to be able to metabolize RDX (47, 60).

In summary, SIP was combined with high throughput sequencing to investigate the
microorganisms involved in RDX degradation. To our knowledge, this is the first application of
this combined approach to study RDX biodegradation. The study generated two important data
sets. Firstly, high throughput sequencing data indicated several phylotypes increased in
abundance following RDX degradation compared to the initial soil and no RDX controls. These
trends suggest a growth benefit caused by the degradation of RDX as the microorganisms were

120

directly benefiting from RDX or from RDX metabolites. Secondly, using SIP, two phylotypes
were found to be primarily responsible for label uptake, indicating incorporation of the label into
their DNA. It is not possible to conclude if they were assimilating the label from RDX or from
RDX metabolites. The two phylotypes associated with label uptake included Comamonas and an
unclassified Pseudomonadaceae. The high throughput sequencing data indicated these two
phylotypes also increased in abundance following RDX degradation compared to the controls.
Taken together, the two data sets implicate these phylotypes in RDX degradation, as their
populations both increased following RDX degradation and the label was incorporated into their
DNA. Other SIP and pure culture studies have also reported the importance of phylotypes within
the Pseudomonadaceae for RDX degradation. In contrast to pure culture and SIP studies, the
current research provided evidence of the importance of Comamonas in RDX degradation. These
data suggest the presence of these microorganisms at contaminated sites should enhance natural
attenuation efforts.

121

APPENDIX

122

Table 5.1. Chao1 and Shannon and lower and upper confidence intervals (CI) values for all
microbial communities
Initial Soil
Glucose, no RDX
Glucose, lab 1
Glucose, lab 2
Glucose, unlab 1
Glucose, unlab 2
Glucose, unlab 1, time 2
Glucose, unlab 2, time 2
No glucose, no RDX
No glucose, lab 1
No glucose, lab 2
No glucose, unlab 1
No glucose, unlab 2
No glucose, unlab 1, time 2
No glucose, unlab 2, time 2

Chao1
6444
3469
4019
4404
4974
3183
4261
4718
4531
3435
3502
3628
3238
4029
3725

Lower
95% CI
6331
3379
3928
4277
4839
3086
4168
4612
4427
3347
3406
3512
3155
3929
3622

Upper
95% CI
6574
3575
4125
4552
5130
3296
4368
4840
4653
3538
3614
3764
3337
4145
3845

123

Shannon
6.6
3.4
4.3
4.3
4.2
4.1
4.4
4.5
4.3
3.8
3.3
3.3
3.6
4.3
4.1

Lower
95% CI
6.5
3.4
4.2
4.3
4.2
4.0
4.4
4.5
4.3
3.7
3.3
3.3
3.6
4.3
4.1

Upper
95% CI
6.6
3.4
4.3
4.3
4.2
4.1
4.4
4.5
4.3
3.8
3.3
3.3
3.6
4.3
4.2

100
90
80
70
60
50

Relative Abundance (%)

40
30
20
10
0
Initial
No
No
No
No
No
No
No Glucose, Glucose Glucose Glucose Glucose Glucose Glucose
Soil Glucose Glucose Glucose Glucose Glucose Glucose Glucose no RDX Lab 1 Lab 2 Unlab 1 Unlab 2 Unlab 1 Unlab 2
or RDX Lab 1 Lab 2 Unlab 1 Unlab 2 Unlab 1 Unlab 2
Time 2 Time 2
Time 2 Time 2

unclassified Pseudomonadaceae

Acinetobacter

Gracilibacter

unclassified Bacteroidetes

unclassified Bacteria

Pseudomonas

unclassified Clostridiaceae 1

Comamonas

unclassified Chitinophagaceae

unclassified Clostridiales

Gp4

unclassified Comamonadaceae

Rhodococcus

unclassified Oxalobacteraceae

Azospirillum

3 genus incertae sedis

Sedimentibacter

Flavisolibacter

unclassified Ruminococcaceae

Clostridium III

Pedobacter

Brevundimonas

Anaeromyxobacter

unclassified Rhodocyclaceae

Figure 5.1. Relative abundance of the most common phylotypes in RDX amended microcosms
(with and without glucose) compared to their abundance in the initial soil community and no
RDX microcosms.

124

Number of OTUs

No glucose, lab 1
No glucose, unlab 1
No glucose, unlab 1, time 2
Glucose, no RDX

No glucose, lab 2
No glucose, unlab 2
No glucose, unlab 2, time 2
Initial Soil

Glucose, lab 1
Glucose, unlab 1
Glucose, unlab 1, time 2
Glucose, no RDX

6000

6000

5000

5000

4000

4000

3000

3000

2000

2000

1000

1000

Glucose, lab 2
Glucose, unlab 2
Glucose, unlab 2, time 2
Initial Soil

0

0
0

20000 40000 60000 80000 100000 120000 140000

0

20000 40000 60000 80000 100000 120000 140000

Number of sequences

Figure 5.2. Rarefaction curves for the total microbial communities in the initial soil, RDX
amended microcosms and the no RDX controls for both the no glucose amended (A) and glucose
amended (B) microcosms.

125

A. Glucose Amended
40
30

Initial Soil
Glucose Lab 2
Glucose Unlab 1 Time 2

Glucose, no RDX
Glucose Unlab 1
Glucose Unlab 2 Time 2

Glucose Lab 1
Glucose Unlab 2

20

Relative Abundance (%)

10

0
unclassified
Pseudomonadaceae

Pseudomonas

Comamonas

unclassified
Rhodocyclaceae

Sedimentibacter

B. No Glucose Amended
40
30

Initial Soil
No Glucose Lab 2
No Glucose Unlab 1 Time 2

No Glucose or RDX
No Glucose Unlab 1
No Glucose Unlab 2 Time 2

No Glucose Lab 1
No Glucose Unlab 2

20
10
0
Acinetobacter

Comamonas

Sedimentibacter

unclassified
Clostridiaceae 1

Rhodococcus

Figure 5.3. Relative abundance of phylotypes illustrating a difference in relative abundance
between the RDX amended microcosms and the no RDX controls (initial soil and no RDX
microcosm) in the glucose amended microcosms (A) and in the microcosms that were not
amended with glucose (B).

126

A. Glucose Amended
Unlabeled 1
Labeled 1

10

Unlabeled 2
Labeled 2

8

DNA concentration (ng/µL)

6
4
2

0
1.700

1.720

1.740

1.760

1.780

B. No Glucose Amended
10

Labeled 1
Unlabeled 1

Labeled 2
Unlabeled 2

8
6
4
2
0
1.700

1.720

1.740

1.760

1.780

Buoyant Density (g/mL)

Figure 5.4. DNA concentration (ng/µL) in fractions across buoyant density gradients obtained
from samples amended with labeled and unlabeled RDX, with (A) or without (B) the addition of
glucose. Replicate lines represent duplicate DNA measurements. The shaded area represents the
fractions analyzed with Illumina sequencing.

127

A. Glucose Amended
unclassified Pseudomonadaceae

Abundance normalized to DNA mass in fractions

Anaeromyxobacter

Comamonas
60

60

60

Labeled

Labeled

Unlabeled

Unlabeled

Labeled

40

40

40

20

20

20

0
1.740

1.750

1.760

1.770

1.780

0
1.740

1.750

1.760

1.770

1.780

Unlabeled

0
1.740

1.750

1.760

1.770

1.780

Buoyant Density (g/mL)
B. No Glucose Amended
Azohydromonas

unclassified Pseudomonadaceae
80
Labeled
60

Unlabeled

Rhodococcus
80

80
Labeled
Unlabeled

60

Labeled
60

40

40

40

20

20

20

0
1.745 1.750 1.755 1.760 1.765 1.770

0
1.745 1.750 1.755 1.760 1.765 1.770

Unlabeled

0
1.745 1.750 1.755 1.760 1.765 1.770

Buoyant Density (g/mL)

Figure 5.5. The three most abundant phylotypes in the heavy fractions from the labeled RDX
amended microcosms compared to their abundance in fractions of similar buoyant density from
the unlabeled RDX amended microcosms. Data are shown from those amended with glucose (A,
top three graphs) and those not amended with glucose (B, bottom three graphs). The y-axis
represents relative abundance in each fraction normalized by the DNA mass in each fraction
(relative abundance times the DNA mass (ng)). Error bars represent standard deviations from
three replicates and may be too small to be seen.

128

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