A comparison of DNA profiling techniques for monitoring...
Transcript of A comparison of DNA profiling techniques for monitoring...
A comparison of DNA profiling techniques for monitoring nutrient
impact on microbial community composition during
bioremediation of petroleum-contaminated soils
DeEtta K. Millsa,*, Kristin Fitzgeralda, Carol D. Litchfielda, Patrick M. Gillevetb
aDepartment of Biology, 4400 University Drive, George Mason University, Fairfax, VA 22030, USAbDepartment of Environmental Sciences and Public Policy, 10900 University Boulevard, George Mason University, Manassas, VA 20110, USA
Received 31 July 2002; received in revised form 16 October 2002; accepted 19 December 2002
Abstract
Amplicon length heterogeneity PCR (LH-PCR) and terminal restriction fragment length polymorphisms (TRFLP) were
used to monitor the impact that nutrient amendments had on microbial community dynamics and structural diversity during
bioremediation of petroleum-contaminated soils. Slurried soils contaminated with petroleum hydrocarbons were treated in
airlift bench-scale bioreactors and were either amended with optimal inorganic nutrients or left unamended. Direct DNA
extraction and PCR amplification of whole eubacterial community DNAwere performed with universal primers that bracketed
the first two or three hypervariable regions of the 16S rDNA gene sequences. The LH-PCR method profiled a more diverse
microbial community than did the TRFLP method. The LH-PCR method also tracked differences between the communities
due to nutrient amendments. An in silico database search for bacterial genera with amplicon lengths represented in the
community fingerprints was performed. It was possible to qualitatively identify different groups in the microbial community
based on the amplicon length variations. A similar ‘‘virtual’’ search was performed for the TRFLP fragments using the web-
based TAP-TRFLP program. Cloning and sequencing of the PCR products confirmed the in silico database matches. The
application of the LH-PCR method as a monitoring tool for bioremediation could greatly enhance and extend the current
understanding of the microbial community dynamics during the biodegradation of environmental contaminants.
D 2003 Elsevier Science B.V. All rights reserved.
Keywords: Amplicon length heterogeneity; Terminal restriction fragment length polymorphisms; Bioremediation; Microbial dynamics;
Monitoring tool
1. Introduction
Given that microbial communities are metabol-
ically both diverse and highly tuned to their
specific habitats, monitoring microbial population
dynamics in an environmental system can be a
sensitive method to track changes. To successfully
accomplish this, however, requires robust and
0167-7012/03/$ - see front matter D 2003 Elsevier Science B.V. All rights reserved.
doi:10.1016/S0167-7012(03)00007-1
* Corresponding author. Present address: Department of Bio-
logical Sciences, OE 167, University Park Campus, Florida
International University, 11200 SW 8th Street, Miami, FL 33199,
USA. Tel.: +1-305-348-2913; fax: +1-305-348-1986.
E-mail address: [email protected] (D.K. Mills).
www.elsevier.com/locate/jmicmeth
Journal of Microbiological Methods 54 (2003) 57–74
reproducible methods of detection that can detect
relatively small changes in a complex background.
Fortunately, with the application of molecular
techniques (i.e., culture independent) to the study
of microbial ecology, a more thorough understand-
ing of the microbial community composition and
the fundamental roles they play in all of the
major biogeochemical and degradation cycles are
possible (Colwell, 1997; Pace, 1997; Torsvik et
al., 1996).
DNA profiling techniques that use 16S riboso-
mal (16S rRNA) genes as phylogenetic markers
have proven to be rapid and economical methods
to assess microbial diversity albeit at somewhat
lower resolution than nucleic acid sequencing
(Torsvik et al., 1996). Some common profiling
methods are based on the enzymatic digestion of
16S rRNA genes: restriction fragment length poly-
morphisms (RFLP) (Pukall et al., 1998) and fluo-
rescent terminal restriction fragment length
polymorphisms (TRFLP) (Dunbar et al., 2000).
The distribution of restriction site sequences within
the 16S rRNA genes has been found to reflect
phylogeny at some taxonomic level. Therefore,
inferences as to community composition and diver-
sity are possible using only the terminal fragments
(Marsh et al., 2000). The disadvantage of these
types of methods is that many taxonomically unre-
lated organisms could produce the same length
fragments and, thus, can underestimate the true
diversity of the whole community (Liu et al.,
1997; Marsh et al., 2000). In spite of some of
the technical limitations associated with the techni-
que, the TRFLP method has become one of the
techniques of choice for many monitoring schemes.
It has been successfully used to monitor microbial
community dynamics, diversity and richness in
agricultural and natural soils (Dunbar et al., 2000;
Lukow et al., 2000), marine waters (Moeseneder et
al., 1999), and contaminated aquifer samples (Liu
et al., 1997).
Amplicon length heterogeneity PCR (LH-PCR)
profile analyses are based on the inherent variation
in sequence lengths of specific regions of DNA.
Suzuki et al. (1998) used LH-PCR to estimate the
diversity present in bacterioplankton communities in
samples collected off the Oregon coast. Ritchie et
al. (2000) compared the LH-PCR technique with
fatty acid methyl ester (FAME) profiles in an effort
to see which method could better assess the diver-
sity present in agricultural soil communities. They
found that both FAME and LH-PCR were able to
characterize the microbial communities but the LH-
PCR method was better able to assess the com-
munity diversity and differences associated with
tillage practices. Other investigators have used
LH-PCR to distinguish between human and rumi-
nant fecal anaerobes using species-specific primers
(Bernhard and Field, 2000). Because of the sensi-
tivity and resolution of the LH-PCR technique, they
were able to identify whether the nonpoint source
water contamination was human or bovine in ori-
gin.
As in the TRFLP method, the disadvantage of LH-
PCR method is that multiple, phylogenetically unre-
lated organisms could produce the same length frag-
ment and be indistinguishable from each other in the
profile. However, the purpose of any profiling method
is to produce an overall pattern of the community, not
to identify absolutely each individual species or genus
in that community. The individual peaks displayed
become the units, or phylotypes, used in the monitor-
ing process.
In the present study, an airlift bioreactor model
system was used to assess the ability of the two
profiling techniques, TRFLP and LH-PCR, to mon-
itor nutrient effects on microbial community struc-
tural dynamics during bioremediation. In most
bioremediation studies, the focus is on monitoring
contaminant degradation and disappearance. How-
ever, without an understanding of the link between
the contaminant degradation and basic nutritional
needs of the microbial community, the biotic com-
ponent of the bioremediation process often remains
in the proverbial ‘‘black box’’. Therefore, the
objective of this study was to evaluate the micro-
bial communities under two different nutrient
regimes during biodegradation of oil-contaminated
soil by comparing two different fluorescent-based
DNA profiling techniques: LH-PCR and TRFLP.
These two methods used the same DNA extraction
method, the same PCR conditions (with the excep-
tion of the primer sets), and were run and analyzed
by the same instrument. Therefore, any extraction
or instrument-related differences between the two
methods would be minimized. Additionally, the
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–7458
PCR products were cloned and sequenced to aid in
evaluating the microbial community profiles.
2. Materials and methods
2.1. Soil samples and bioreactors
Petroleum-contaminated soils were collected from
a leaking underground storage tank site in Capitol
Heights, MD. Samples were taken from highly weath-
ered soils that had been stockpiled for 5 years from a
previously excavated contaminated tank site and from
a newly excavated tank site. The level of contamina-
tion in the two soils when mixed was approximately
1000 ppm of mixed petroleum products. Soil samples
were transported on ice to the laboratory and were then
mixed together in equal proportions and homogenized.
One liter of distilled deionized (ddI) water was added
to 1 kg of the soil mixture. Four 200-g aliquots of
slurry were placed into the four airlift bioreactors
(Kontes, Vineland, NJ), continuously mixed and aer-
ated during the 31-day experiment. Three amended
bioreactors continuously received supplemental inor-
ganic nutrients (N/P, 16:1) at the rate of 20 Al min� 1
via a Hamilton syringe pump. The unamended control
reactor was supplemented only with ddI water deliv-
ered at the same rate. Homogenized samples were
taken at time zero (T0) before placing the slurry in
the bioreactors, and then 10 additional times through-
out the experiment. Data for five time points are
reported and are representative of all the samples
taken. All samples for DNA analysis were immedi-
ately frozen at � 80 jC. Other assays were also
performed on the soils and reported elsewhere (Fitz-
gerald, 1999). To monitor the response of the previ-
ously petroleum-adapted microbial community to
petroleum shock, an additional 85 g of the original
highly weathered soil, freshly contaminated with 4000
ppm Arabian light crude oil, were added to each
bioreactor on day 17, and the experiment continued
for an additional 14 days. Petroleum data were gath-
ered using standard gravimetric and qualitative GC/
MS methods and reported elsewhere (Fitzgerald,
1999). The primary focus of this paper is to compare
two similar molecular techniques that are used to track
community structural dynamics during bioremediation
and under different nutrient regimes.
2.2. DNA extraction and PCR conditions
Whole-community genomic DNA was extracted
from the frozen bioreactor slurry samples using
slight modifications to the FastDNARSPIN kit for
soil (QBiogene, Vista, CA) (Mills, 2000). Briefly, to
aid in cell lysis and increase DNA yield, samples
were incubated for 45 min at 70 jC after the initial
20 s of bead beating, placed back into the FastPrepRinstrument, and processed for an additional 10 s at
the same speed setting of 5.5. This kit efficiently
removed most of the inhibitory humic and fulvic
acids that can sometimes interfere with subsequent
amplification steps. The kit was also tested on pure
cultures of Gram-positive bacteria (e.g., Bacillus
macerans, ATCC #7068) and proved to efficiently
and reproducibly lyse the cells. High-molecular-
weight (HMW) DNA was quantified using a Bio-
Rad fluorometer (Bio-Rad, Richmond, CA), and 10
ng of HMW DNA were consistently used in each
PCR reaction.
The PCR reaction mixture and concentrations
were the same for the TRFLP and LH-PCR studies
except different primers were used. The TRFLP
method used universal 16S rDNA fluorescently
labeled primers (Escherichia coli numbering) 63F-
NED (5V-NED-CAG GCC TAA CAC ATG CAA
GTC-3V) and 1387R-6-FAM (5V-6-FAM-GGG CGG
WGT GTA CAA GGC-3V) (GIBCO BRL, Life Tech-
nologies, Gaithersburg, MD) (Marchesi et al., 1998).
This set of primers was more compatible (i.e., no
recognition site within the primer sequence) with the
restriction enzymes chosen for this study than were
other universal primer sets. Only the forward primer
27F-6-FAM (5V-6-FAM-AGA GTT TGA TCM TGG
CTC AG-3V) was fluorescently labeled for the LH-
PCR study and paired with the nonfluorescent reverse
primer, 355R (5V-GCT GCC TCC CGT AGG AGT-
3V) (E. coli numbering) (PE Biosystems, Foster City,
CA) (Suzuki et al., 1998). Positive controls used
DNA from pure laboratory cultures (Pseudomonas
putida, ATCC #17472, or purified environmental
isolates from the contaminated soils. Negative con-
trols used only diethylpyrocarbonate (DEPC)-treated
water. Final concentrations of the PCR reaction
mixture were: 1� PCR buffer, 0.25 mM MgS04,
0.25 mM dNTPs (Boehringer, Mannheim), 0.5 AMforward and reverse primers, 0.25 U Tf1 DNA
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–74 59
polymerase (Promega, Madison, WI), 0.1% (w/v)
bovine serum albumin (BSA), fraction V, non-acety-
lated (ICN Biomedicals, Aurora, OH), 10 ng HMW
DNA and DEPC-treated water to make up the final
volume. The PTC-100 programmable thermal cycler
(M.J. Research, Watertown, MA) was programmed
for an initial denaturing step at 94 jC for 5 min
followed by 25 cycles of 94 jC for 1 min, 55 jC for
1 min and 72 jC for 1 min with a final extension step
at 72 jC for 10 min. Cycling parameters were tested
starting with 5 through 40 cycles at five-cycle incre-
ments to address the bias often associated with
amplification of mixed templates (Suzuki et al.,
1998; Suzuki and Giovannoni, 1996). Twenty-five
cycles were found to be optimal in order to reprodu-
cibly and consistently amplify these representative
communities without kinetic or template biases
becoming factors (data not shown). LH-PCR prod-
ucts were loaded directly onto the polyacrylamide
gels without further purification. For TRFLP the
PCR, products were further purified with the Prom-
ega WizardR PCR prep kit (Promega) using the
manufacturer’s protocol. Seventeen microliters of
purified PCR products were digested overnight at
37 jC using 10 U of HhaI endonuclease and the
appropriate 1� buffer.
2.3. Electrophoresis
All samples were denatured in a 5:1:1 mixture of
deionized formamide (98%, Sigma, St. Louis, MO),
Blue Dextran–EDTA loading dye and GeneScan ROX
internal standard (PE Biosystems), heated to 94 jC for
4 min and chilled on ice until loaded. All samples were
separated on a 48 cm, 4.25% denaturing polyacryla-
mide gels (19:1 bis/acrylamide) (Bio-Rad) using an
ABIR 377 DNA sequencing instrument. Fluorescent
LH-PCR samples used the GeneScan-500 ROX inter-
nal standard while GeneScan-1000 ROX was used
with the TRFLP products. LH-PCR gels were run for 4
h while the TRFLP gels ran for 7 h using standard
electrophoresis run parameters.
2.4. Analyses
Fingerprint profiles were collected and analyzed
using the ABI Prismk GeneScanR, ABI PrismkGenotyperR software (PE Biosystems) and Microsoft
Excel (Microsoft, Seattle, WA). In GeneScanR, anal-ysis parameters for the TRFLP profiles were set to the
local Southern size calling, left most peak method,
and the noise threshold was set at 100 fluorescent
units. LH-PCR profiles were analyzed using analysis
parameters set to the local Southern size calling, no
peak correction. The minimum noise threshold was
set at 50 fluorescent units.
Three or more replicate profiles from separate DNA
extractions and separate PCR reactions for each sam-
ple were compared to assess the reproducible frag-
ments that could be used for analyses. In order to
eliminate small peaks that may be contributed from
fluorescent background inherent to either technique,
the standardized binning criteria used to identify the
subset of reproducible peaks were: (a) the peak had to
appear in at least two-thirds of the replicates and, (b)
the relative area ratio had to be equal to or greater than
1%. The reason for setting these binning parameters
was to eliminate the error introduced by the collection
and analysis software (Dunbar et al., 2001). Partial
digests for TRFLP profiles were resolved in part by
comparisons between replicate digests as well as with
in silico, or virtual, digestions of known organisms
using the TRFLP analysis program (TAP TRFLP)
(Marsh et al., 2000) and the NCBI ribosomal database.
Relative area ratios for both fingerprint methods
were calculated by dividing each individual peak area
by the total peak area of each electropherogram.
Descriptive statistics were performed on the replicates
and the mean relative ratios were used in subsequent
analyses. The means of the peak areas were converted
to binary data (presence/absence) and similarity indi-
ces (SI) were calculated using the Sørensøn’s Index
(pairwise similarity values) (Archer and Leung, 1998).
The Shannon diversity index, phylotype richness and
evenness parameters were calculated as described in
Dunbar et al. (1999).
2.5. Cloning and sequencing
Unlike agarose- or denaturing-based gel profiling
techniques, the individual bands or amplicons cannot
be recovered from the polyacrylamide gels after run-
ning on the ABI 377 genetic analyzer. Therefore, new
PCR reactions, with the same HMW DNA that was
used for all other experiments, were cloned. PCR
products were obtained using nonfluorescent primers,
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–7460
Fig. 1. (a) Partial digests were a common technical problem with TRFLP. Asterisks (***) mark incomplete digestion (HhaI restriction enzyme)
products for T0 replicate samples. (b) The reproducibility of the LH-PCR method is demonstrated by superimposing six separate
electropherograms on top of one another. The difference in peak height is within the error margin F 3–5% for pipetting errors throughout the
protocol.
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–74 61
Fig. 2.
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–7462
27F and 536R (5V-GWA TTA CCG CGG CKG CTG-
3V) (PE Biosystems) (Suzuki et al., 1998) and cloned
using the TOPO TA, version J, cloning kit (Invitro-
gen, Carlsbad, CA) per the manufacturer’s protocol.
Twenty microliters of a PCR reaction master mix [0.5
U AmpliTaq Goldk (Perkin Elmer, Foster City, CA),
1� buffer with 1.5 AM MgCl2, 250 AM dNTPs, 0.5
AM forward (27F) and reverse (536R) primers and
DEPC water to 20 Al] were placed in thin-walled PCR
reaction tubes. Positive clones (white colonies) were
picked from the LB plates using autoclaved tooth-
picks, transferred to the PCR tubes and mixed well
with the reaction mix. In order to facilitate cell lysis
and activation of AmpliTaq Goldk polymerase, the
initial heating step was held for 11 min at 94 jC. PCRcycling parameters were: 1 min at 94 jC, 1 min at 55
jC, 1 min at 72 jC for 35 cycles. The final extension
step was for 10 min at 72 jC. PCR purification of the
Fig. 2. The means of the area peak ratios ( y-axis) of replicate TRFLP digests of the bioreactor samples. Both 5V(174–177 bp) and 3V(274–302bp) terminal fragments are represented in the analysis. Solid bars represent the unamended (un) bioreactor community; hashed bars represent the
amended (am) bioreactor communities. T0 is the baseline sample taken from the contaminated soil before starting the bioreactors, T14 was
sampled on day 14, T17 on day 17, T21 on day 21 and T31 on day 31 at the conclusion of the bioreactor run. The error bars are the standard errors
of the area means. The x-axis is the terminal fragment length in base pairs.
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–74 63
Fig. 3.
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–7464
cloned product was performed using the QuickStepkPCR 96-well kit (Edge BioSystems, Gaithersburg,
MD) per the manufacturer’s protocol.
DNA sequencing reactions used 20 ng of the
cloned PCR product and 0.25 AM of the primer
added to the standard mix of ABI PrismR BigDyek
terminator cycle sequencing ready reaction mixture,
version 2 (PE Applied Biosystems). Cycle sequenc-
ing was performed using an initial heating step of 96
jC for 1 min, and then 40 cycles at 96 jC for 30 s
and 60 jC for 4 min. DNA sequencing reactions
were purified by gel filtration using Sephadex G-50
Fig. 3. The mean peak ratios ( y-axis) of replicate LH-PCR products. Solid bars represent the unamended (un) bioreactor community; hashed
bars represent the amended (am) bioreactor communities. T0 is the baseline sample, T14 was sampled on day 14, T17 on day 17, T21 on day 21
and T31 on day 31. The error bars are the standard errors of the mean area ratios. The x-axis is the amplicon lengths in base pairs.
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–74 65
(Sigma) in the 96-well microtiter Millipore Multi-
ScreenR filtration system (Millipore, Bedford, MA)
per the manufacturer’s protocol. Samples were dried
in the speed-vac (Promega) for 45 min on medium
heat, and then covered and stored at � 20 jC until
sequenced. Four percent denaturing polyacrylamide
sequencing gels (29:1 bis/acrylamide) were prepared
and run using standard protocols and run parameters
for the ABIR 377 DNA sequencer. Sequence data
were analyzed using Sequencher version 3.0 or newer
software (Gene Codes, Ann Arbor, MI). Consensus
sequences of the clones were compared to known
sequences in the NCBI ribosomal database using the
BLAST search option. Phylogenetic tree analysis
based on the partial sequences was performed with
the software program PAUP using the neighbor-join-
ing analysis function with default parameters to
determine the putative identity of each clone (Swof-
ford, 1993).
In silico or virtual analyses were done by aligning
the cloned sequences with the LH-PCR primer
sequences. This correlated the identification of the
various taxa represented by the clones to amplicon
lengths in the community profiles. Similarly, the
cloned sequences were aligned with the forward
TRFLP primer, restriction sites were identified and
the fragment lengths calculated. The TRFLP frag-
ments were ‘‘virtually’’ verified using the TRFLP
analysis program (TAP TRFLP) (Marsh et al., 2000).
3. Results
3.1. Reproducibility
Technique-related biases can dramatically influ-
ence the final data and can lead to misinterpretation
of the results if the biases are not addressed (Dunbar et
al., 2000). All methods used in this project were tested
and optimized for these samples in order to minimize
or eliminate any biases that can be introduced by
sampling, DNA extraction or template bias during
PCR (Suzuki et al., 1998; Suzuki and Giovannoni,
1996; Wintzingerode et al., 1997). For example,
Promega’s Tf1 DNA polymerase (Promega) was
found to be more efficient than AmpliTaq or Ampli-
Taq Goldk (Perkin Elmer) for amplifying the envi-
ronmental samples because of the ‘‘joyride’’ DNA
that was often amplified when using the Perkin Elmer
polymerases (Kenzelmann and Muhlemann, 1997).
BSA was added to all PCR reaction mixtures in order
to reduce any PCR inhibitory effects from any con-
taminants that may have been carried over after
extraction with the QBiogene soil kit.
In the TRFLP experiments, both the 5Vand 3Vendsof the 16S rRNA gene products were labeled with a
fluorescently tagged primer. Partial digests were the
major source of inconsistent results with the TRFLP
method (Fig. 1a). Even using three different restriction
enzymes (Mills, 2000) and optimized protocols, often
five restriction digests had to be performed on a PCR
product in order to produce three replicate samples
that could be used for further analyses. This technical
bias added to the overall sample processing time and
expense. This bias may be contributed in part to
blocking of restriction sites by either inhibitors or
the complexity of the mixed templates present in the
PCR product (Osborn et al., 2000). All data analyses,
however, were performed on at least three replicates
and included both the 5Vand 3Vterminal fragments in
the final analyses.
As in the TRFLP method, three separate DNA
extractions were performed on all samples and three
separate PCR reactions were run for the LH-PCR. The
reproducibility of the LH-PCR was not only more
consistent but the results from the LH-PCR method
allowed for confirmation of the reproducibility of both
the DNA extraction method and PCR parameters used
in this study (Fig. 1b). In addition, intra- and inter-gel
variations between LH-PCR samples were assessed.
Separately amplified LH-PCR products that were
electrophoresed in duplicate on two separate gels
and the superimposed electropherograms showed no
variation except in amplitude of the intensity (Fig.
1b). These are representative results that were
obtained each time with the LH-PCR method but
not necessarily with the TRFLP technique.
3.2. Effect of nutrient amendments on microbial
diversity
The effect of nutrient amendments on the microbial
community was assessed using TRFLP and LH-PCR.
Both methods showed distinct differences between the
baseline sample taken at T0 and the other samples
during the course of the study (Figs. 2 and 3). The
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–7466
differences between the two treatment regimes are
clearly shown by the number of peaks and the differ-
ences in the relative abundance of the common peaks.
For the TRFLP method, terminal fragment lengths
174, 176 and 177 (5V end) were the most diagnostic
during the first phase of the experiment in that their
presence and absence as well as abundances varied
(Fig. 2). Fragment 177 base pair (bp) was only present
in the original soil (T0) while fragment 174 bp domi-
nated all of the samples. The cloning and sequencing
of the community DNA indicated several of the
members from the original T0 populations were anae-
robes. These populations would be selected against
due to the aerobic nature of the airlift reactors. The
standard error (S.E.) of the relative area ratios is
indicative of the variability in the restriction digest
products. In the case of T0 for either method, the
standard error is somewhat greater and could also be
indicative of a less uniform mixing and wetting of the
samples. These samples were taken before being
slurried and put into the airlift reactors that constantly
mixed and aerated all subsequent samples. However,
since all HMW DNAwas quantified and a standard 10
ng was used in all reactions, variation in the initial
extractions probably would not account for the
increased error. However, even considering that pos-
sibility, the relative area ratios most likely vary more
from (a) pipetting error in preparing the samples and
loading on the gel or (b) as is the most likely, a
reflection the different abundance of fragments pro-
duced during the digestion. One of the common guide-
lines used to recognize partial digests is the attenuation
of the intensity profiles as well as the disappearance
and appearance of bands in replicate experiments that
use identical protocols (Fig. 1a) (Osborn et al., 2000).
This guideline was used in this study as well.
During Phase I, the terminal fragments from the 3Vend (274 through 302 bp) varied in abundance. Frag-
ment 302 bp, however, was not present in the original
soil but did appear later in the experiment in first the
unamended control and then later in both unamended
and amended samples. Whether this fragment repre-
sents one or many different populations with common
fragment lengths that may have taken longer to adapt
Table 1
Comparison of diversity and evenness indices for TRFLP and LH-
PCR
Sample Diversity (H) Evenness (E)
TRFLP LH-PCR TRFLP LH-PCR
Phase I
T0 2.09 2.38 1.07 0.74
T14 unamend 1.63 1.70 0.84 0.71
T14 amend 0.59 2.10 0.43 0.82
T17 unamend 0.94 1.67 0.58 0.72
T17 amend 0.87 2.09 0.49 0.77
Phase II
T21 unamend 0.02 0.68 0.03 0.42
T21 amend 0.02 1.84 0.03 0.80
T31 unamend 1.37 1.32 0.77 0.60
T31 amend 1.23 1.88 0.69 0.73
S= total number of bands/profile (richness). H = Shannon diversity
index, H =�S( pi)(log2pi), where pi is the individual peak area.
Hmax = log2(S). E =H/Hmax. Phase I: days 0–17; Phase II: days
18–31.
Table 2
Similarity indices for the LH-PCR amplicon length profiles
Phase I Phase II
T0 T14 unamend T14 amend T17 unamend T17 amend T21 unamend T21 amend T31 unamend T31 amend
T0 1.00 0.47 0.51 0.42 0.44 0.36 0.42 0.38 0.41
T14 unamend 1.00 0.61 0.57 0.58 0.38 0.57 0.50 0.45
T14 amend 1.00 0.73 0.88 0.59 0.82 0.57 0.70
T17 unamend 1.00 0.70 0.53 0.60 0.84 0.67
T17 amend 1.00 0.56 0.87 0.55 0.67
T21 unamend 1.00 0.53 0.57 0.50
T21 amend 1.00 0.53 0.67
T31 unamend 1.00 0.80
T31 amend 1.00
Similarity indices were calculated using Sab = 2nab/(na + nb), where nab = the number of bands in common in both samples, na and nb = the
number of bands in lanes a and b, respectively.
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–74 67
to the bioreactor conditions cannot be ascertained
from the profiles alone. What the profiles do indicate,
however, is a change in the structural diversity of the
communities over time.
LH-PCR profiles are shown in Fig. 3. Again, the
loss of amplicon diversity from the baseline sample,
T0, is not surprising because of the aerobic nature of
the bioreactors. The presence of anaerobes with
amplicon lengths greater than 356 bp in the T0 sample
was verified with sequences from the clone library
(Mills, 2000). Interestingly, several amplicons appear
(i.e., 317, 319, 334, 335 bp) and increase in abun-
dance over time. The cloning and sequencing identi-
fied these amplicons as being associated with the
alpha-proteobacteria and the common members were
sphingomonads, known hydrocarbon degraders.
Amplicons 343 and 344 bp are dominant in most of
the communities throughout the experiment. Cloning
and sequencing verified that these amplicons are
associated with pseudomonads, a heterotrophic group
of soil bacteria known to be hydrocarbon degraders
and also known for their adaptive metabolism (Cho
and Tiedje, 2000; Foght and Westlake, 1988; Huertas
et al., 1998, 2000; Powlowski and Shingler, 1994;
Ramos et al., 1998). Optimal nutrients no doubt
affected the resilience of the community members as
seen during Phase II of the experiment (after petro-
leum shock). The diversity was higher in the amended
reactors than in the unamended reactors. The domi-
nant amplicon in the unamended reactor was again
associated with the pseudomonads (344 bp).
It is recognized that each fragment or amplicon in
the profiles probably does not represent a single genus
or species or accurately reflect the intraspecific 16S
rRNA operon heterogeneity found in some microbes
(Wintzingerode et al., 1997; Klappenbach et al.,
2000). However, the fragments or amplicons (i.e.,
phylotypes) are discrete ‘‘units’’ of information that
can be used for comparative analyses (Dunbar et al.,
1999). It is also recognized that the complete micro-
bial diversity or richness of the communities is prob-
ably not represented in the profile. Therefore, only the
minimal detectable and dominant phylotypes and
those templates that were efficiently amplified by
the ‘‘universal’’ primer sets are represented. However,
as in any profiling technique, DNA fingerprinting is
not meant to identify each member of the community
but rather to produce a profile from which compar-
isons can be made.
Table 3
Similarity indices for the TRFLP profiles (HhaI digest, primers 63F-NED and 1387R-6-FAM)
Phase I Phase II
T0 T14 unamend T14 amend T17 unamend T17 amend T21 unamend T21 amend T31 unamend T31 amend
T0 1.00 0.71 0.55 0.50 0.62 0.22 0.22 0.62 0.62
T14 unamend 1.00 0.73 0.83 0.92 0.44 0.44 0.92 0.92
T14 amend 1.00 0.89 0.80 0.67 0.67 0.80 0.80
T17 unamend 1.00 0.91 0.57 0.57 0.91 0.91
T17 amend 1.00 0.50 0.50 1.00 1.00
T21 unamend 1.00 1.00 0.50 0.50
T21 amend 1.00 0.50 0.50
T31 unamend 1.00 1.00
T31 amended 1.00
Similarity indices were calculated using Sab = 2nab/(na + nb), where nab = the number of bands in common in both samples, na and nb = the
number of bands in lanes a and b, respectively.
Table 4
Taxonomic groupings of the clone libraries from the four
representative bioreactor samples
Taxonomic grouping Percent in each library
T0(n= 33)
T21unamended
(n= 11)
T21amended
(n= 14)
T31amended
(n= 32)
Actinomycetales 4.0 10.0 ND 15.0
Bacillus/Clostridium
group (low G+C)
11.0 10.0 ND ND
Bacillus/Lactobacillus
group
ND 10.0 ND 19.0
CFB group 7.0 ND ND ND
Alpha-proteobacteria 19.0 20.0 15.0 15.0
Beta-proteobacteria 37.0 ND 15.0 7.0
Gamma-proteobacteria 7.0 40.0 69.0 41.0
Delta-proteobacteria 15.0 10.0 ND 4.0
ND=none detected.
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–7468
Fig. 4. Neighbor-joining phylogenetic tree for the partial 16S rDNA sequences (c 500–550 bp) of the bioreactor clones. The bolded genera are
known representatives from the NCBI database. The name after the clone ID represents its closest match (>95%) to known genus or species in
the NCBI database.
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–74 69
Diversity and evenness indices based on the
phylotypes for the TRFLP and LH-PCR results are
shown in Table 1. These types of indices are useful
when assessing perturbations to the system (i.e.,
pollution, nutrient effect, etc.) and the response of
the community to those selective pressures (Dunbar
et al., 2000). Although not directly comparable
between the two technique data sets, all of the
indices demonstrate changing trends depicted in all
of the profiles. For example, both diversity and
evenness for the TRFLP declined dramatically in
phylotype diversity with either nutrient regime
through Phase I (T0–T17). There was a dramatic
drop at the beginning of Phase II after the addition
of Arabian light crude oil on day 17 and then an
increase in diversity during the recovering phase.
Interestingly, the unamended reactors were slightly
more diverse than the amended reactors throughout
according to the TRFLP profiles.
However, a different picture emerged with the
LH-PCR profiles. Diversity indices indicated a slight
loss of phylotype diversity as compared to the T0sample during Phase I. A large decrease was shown
for the T21 unamended sample after the additional
shock of the crude oil. Phylotype diversity levels
started to rebound during Phase II but did not return
to the Phase I levels. Since the evenness index is a
function of both diversity and richness, the same
trends as described above are reflected in these data
(Table 1). Similarity indices (SI), based on the
presence/absence and common amplicons between
samples, were calculated for both sets of data (Tables
2 and 3). The low similarity (e.g., uncommon phy-
lotypes between samples) in the LH-PCR unamended
and amended samples for each time point and
between time points was in contrast to the SI for
the TRFLP (Table 3). TRFLP SI indicated that
several of the unamended and amended samples were
identical to each other.
3.3. Cloning and sequencing
Four samples, baseline (T0), day 21 (T21) un-
amended and amended, and day 31 (T31) amended,
were selected for cloning and sequencing because
they had the most representative or unique LH-PCR
profiles. The cloned sequences were aligned with
known taxa in the ribosomal database. The taxonomic
grouping of the clones is shown in Table 4. Distinct
groups of bacteria were present at T0 that did not
appear or dominate at any other time point (e.g., beta-
proteobacteria and the CFB group) while other groups
representing known hydrocarbon degraders (e.g.,
alpha- and gamma-proteobacteria) dominated the bio-
reactors later in the experiment. The dominant clones
from either amendment regime were the alpha- (e.g.,
sphingomonads) and gamma-proteobacteria (pseudo-
monads) (Table 4). The phylogenetic tree based on the
partial sequences (Fig. 4) graphically depicts the
grouping of the clones represented in the unamended
and amended reactors as well as the baseline sample.
The name after the clone ID name represents its
closest match (>95%) to known genus or species in
the NCBI database.
4. Discussion
This study investigated the microbial community
structural composition in contaminated soil and pro-
filed the dynamics of that community over time by
using two different DNA fingerprinting methods.
Since both methods used the same optimized DNA
extraction method, the same concentration of HMW
DNA, and the same PCR parameters, any technique-
related biases from these preparatory steps were
assumed to be similar. Also, the intra- and inter-gel
differences were tested and found to be minimal with
both techniques (data not shown). Therefore, the
electrophoresis and laser detection parameters were
eliminated as sources of bias. The difference in repro-
ducibility between the two techniques appeared to be
directly related to the restriction digestion step for the
TRFLP method. In this study, several separate digests
were performed on the same purified PCR products
and the inconsistencies were found to be associated
with the restriction digests (Fig. 1a). Osborn et al.
examined the effects of varying the concentration of
the restriction enzyme used in a TRFLP study on PCR-
contaminated and pristine soils. They reduced the
amount of HhaI enzyme sequentially from 20 to 5 U
and found the disappearance of smaller sized frag-
ments and an increase in larger fragments, an indica-
tion of incomplete digestions. They also found that
even without limiting the enzyme concentration, there
were often partial digestion products. They concluded
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–7470
that with the TRFLP method, as with any profiling
method, false positives are a problem that needs to be
recognized and addressed (Osborn et al., 2000).
Lukow et al. also addressed the specific need for
replicate samples to assess spatial or temporal changes
in microbial communities. They found replicate sam-
ples to be crucial for the generation of meaningful data.
There was a disparity between the terminal restriction
fragments with the largest single variance between the
seven sample means and the fragments that were
correlated to the discriminate factors used in their
analysis. Without replicate samples, they would not
have been able to determine which data accurately
reflected the spatial and temporal dynamics of the
microbial communities (Lukow et al., 2000). In this
present bioreactor study, up to five digests had to be
performed in order to have three replicates without
partial digests and that were reproducible enough to
use in TRFLP analysis, an approach that was both time
consuming and costly.
On the other hand, the high reproducibility of the
LH-PCR profiles could be attributed to the simplicity
of the method. LH-PCR products were loaded directly
onto a polyacrylamide gel without further processing,
and the amplicons were separated. This eliminated
any additional technique-related biases that could be
related to column clean up or incomplete restriction
digests that were observed with the TRFLP method.
The only visual variations that were seen in the LH-
PCR profiles were the differences in peak heights
(Fig. 1b). Those small deviations were attributed to
pipetting inaccuracies (i.e., F 3–5%) in the multiple
steps of sample preparation and gel loading (Osborn et
al., 2000).
One of the objectives of this study was to assess
the two profiling techniques for their ability to track
any impact nutrient amendments might have on the
microbial community structure. While it is recognized
that the LH-PCR and the TRFLP results cannot be
directly compared, both techniques are often used to
provide whole community information. Both methods
were able to show differences over time and between
treatment regimes. However, the two methods gave
somewhat conflicting information. The TRFLP
method showed a decline in the evenness values
throughout Phase I (Table 1). This decline could be
attributed to the aerobic condition of all the bioreac-
tors that would select against any anaerobes that were
present in the original soils. The clone library sup-
ported this hypothesis. Anaerobes such as Desulfovi-
brio spp. and Geothrix fermentans were found only in
the baseline sample. In Phase I, using the TRFLP
method, the unamended reactors appeared to be
slightly more diverse than the amended reactors. This
seemed to be counter to the idea that nutrient addition
increases diversity by removing any limitations to
growth. However, the addition of nutrients presum-
ably increased the growth potential for the entire
community. The removal of the limiting nutritional
factors then selected for populations that could utilize
the petroleum as a carbon source or utilize the
metabolic by-products produced from petroleum deg-
radation. Therefore, this may infer that the dominant
populations within the amended reactor would be the
hydrocarbon degraders that, coincidentally, produce
common terminal fragment lengths. In the unamended
community, with no selective advantage, a slightly
more diverse fragment pattern was produced, perhaps
indicative of populations not as well adapted to
metabolizing the hydrocarbons as a carbon source.
After the addition of Arabian light crude oil at day
17, the TRFLP unamended and amended communities
responded similarly with a drastic decrease in diver-
sity but then recovered in parallel to similar values by
day 31 despite the potential toxicity of the added
crude oil. This can be attributed to the selection of
only those microbes that could withstand the solvent
shock in either the unamended or amended commun-
ity. In this study, 28% of the 40 clones sequenced
from the Phase II samples were represented by pseu-
domonads and 11.1% were identified as sphingomo-
nads. These metabolically versatile bacteria are
known hydrocarbon degraders and have shown toler-
ance to solvent shock. Huertas et al. reported that
when a large dose of toluene (10% v/w) was suddenly
added to soil, only 1% of the indigenous soil bacteria
survived and subsequently, the survivors re-colonized
the soil at high densities. Several of the isolates from
that surviving fraction were subsequently identified as
pseudomonads (Huertas et al., 2000).
The TRFLP and sequencing results from the clones
in this study also suggest that the dominant bacteria
that survived the crude oil addition were pseudomo-
nads. The 174 base pair (bp) terminal fragments
associated with the pseudomonads were dominant in
the TRFLP profile. However, the clone library and the
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–74 71
LH-PCR method also identified the sphingomonads
as having survived the petroleum shock. The 47-bp
terminal restriction fragment that could have been
produced by the HhaI digest for the sphingomonads
was not able to be used in this TRFLP analysis
because it was not adequately reproduced or resolved
from the fluorescent background noise produced by
the primer peaks. Because of the limited ability to
resolve small base pair terminal fragments and the
lack of reproducibility in many of the digests with the
TRFLP method, important data were lost and the
diversity of the whole community was greatly under-
estimated. Therefore, fewer fragments were used in
the analysis and this can affect the calculations and
skew interpretation of the indices. On the other hand,
most of the LH-PCR amplicons were easily resolved
and, thus, provided more data points for the analyses.
The TRFLP technique bias may be improved with
additional digestions of the PCR products with other
restriction enzymes. However, as reported in a pre-
vious pilot study using RsaI and AluII on these same
bioreactor samples (Mills et al., 1999), there were still
inherent problems with partial digests and the reso-
lution of small base pair fragments. Multiple enzy-
matic digests may help resolve the community
structure but it also increases the overall time and
costs associated with the analyses.
Greater resolution of the whole community struc-
ture was possible with the LH-PCR method. The first
two hypervariable regions of the 16S rRNA gene can
be used to discriminate between phylogenetic groups
of bacteria (Suzuki et al., 1998). The evenness values
for that domain indicated that higher overall phylotype
diversity and richness were maintained in the amended
reactors than in the unamended samples throughout the
experiment (Table 1). This was also visually obvious
when the profiles from the unamended and amended
bioreactors were compared (Fig. 3). For example,
while the 342–344-bp fragments associated with the
pseudomonads were dominant in all the bioreactor
samples, the 317–320-bp peaks appeared only in the
amended bioreactor samples. These prominent peaks
corresponded to the in silico alignment of several of
the sequenced bioreactor clones associated with the
genus Sphingomonas. Therefore, the effect of the
nutrient amendment on the community structure was
more adequately tracked with the LH-PCR method
than with the TRFLP technique.
There are certain technique-related biases inherent
to cloning. For example, the number of ribosomal
gene copies or operons can vary between taxa and
bias the overall diversity estimations (Head et al.,
1998). It is recognized that the clone libraries do not
represent the complete bacterial diversity nor the
relative proportion of populations in the whole com-
munity (Table 4). The partial sequences spanned only
the first three hypervariable regions in the 16S rRNA
genes, not the entire gene. However, the clone library
was not designed to provide definitive identification
of each clone but rather to provide confirmation of the
presence of representative bacteria that could be
associated with the amplicon lengths or terminal
fragments. The pseudomonads, sphingomonads, and
other representative genera (e.g., Rhodococcus and
Ralstonia) found in the bioreactor baseline clone
library have been previously isolated and identified
from other hydrocarbon-contaminated soils (Stapleton
and Sayler, 2000; Thomassin-Lacroix and Mohn,
2000). The presence of these various taxonomic
groups that have previously been associated with
polluted sites suggests that the original microbial
community was probably well adapted and perhaps
less diverse compared to microbial communities from
pristine or undisturbed sites.
While the TRFLP technique has proven to be a
method to evaluate many complex natural commun-
ities (Liu et al., 1997), it was shown in the present
study to be not as robust as LH-PCR in its ability to
profile the subtle changes in a previously adapted and
perhaps less complex community. A study by Lukow
et al. followed spatial and temporal changes in a
microbially diverse agricultural soil using TRFLP
method. Even in complex profiles that produced a
total of 20–40 terminal restriction fragments, the
diagnostically relevant phylotypes (i.e., those that
differed between samples) ranged from 0 to 14
(Lukow et al., 2000). If the discriminatory level was
this low in a complex healthy soil system, the TRLFP
method may have limited use in monitoring microbial
community changes or diversity in less healthy or
polluted systems.
On the other hand, even with a limited number of
studies, the LH-PCR technique has already been
shown to be a powerful tool for studying complex
natural systems (Ritchie et al., 2000; Suzuki et al.,
1998). Ritchie et al. used the LH-PCR method to
D.K. Mills et al. / Journal of Microbiological Methods 54 (2003) 57–7472
assess microbial diversity in tilled soils. The richness
(i.e., number of peaks) varied from 19 to 23 between
plots and all of those peaks were used in the analysis.
These investigators also found the LH-PCR method to
be robust, fast, and highly reproducible for assessing
differences in soil communities under different tillage
practices (Ritchie et al., 2000).
In the present study, the LH-PCR fingerprint
proved sensitive enough to provide high resolution
even in a community assumed to be low in com-
plexity. This study has shown great potential for the
use of the LH-PCR technique to monitor bioreme-
diation where the stressed community may be rep-
resented by one low in diversity. In this study, the
technique was able to track microbial community
dynamics, the impact of nutrient addition on the
communities, and could effectively monitor the
recovery phase after system perturbation. When
compared to the TRFLP method, the LH-PCR was
found, in this case, to be far more reproducible and
technically less complex. In addition to its reprodu-
cibility and lower reagent costs, the turn-around time
from field sample preparation to the output of the
final LH-PCR profile was 1.5 days compared to
2.5–3 days for TRFLP profiles. The application of
the LH-PCR method as a monitoring tool for bio-
remediation should greatly enhance and extend the
current understanding of the dynamics of microbial
communities during the biodegradation of environ-
mental contaminants.
Acknowledgements
This work was supported in part by a US EPA
Science To Achieve Results (STAR) Graduate Fellow-
ship (U915621) and the George Mason University
Dean’s Fund, both awarded to DKM, and the US–
Israel Bi-National Science Foundation grant (95-
00027) awarded to CDL and A. Oren.
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