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,


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.


Fig. 2.


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.


Fig. 3.


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.


(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


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.


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.


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.


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


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


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


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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