Journal of Microbiological Methods 55 (2003) 155 – 164
www.elsevier.com/locate/jmicmeth
Assessment of bacterial community structure in the deep
sub-seafloor biosphere by 16S rDNA-based techniques:
a cautionary tale
Gordon Webster, Carole J. Newberry, John C. Fry, Andrew J. Weightman *
Cardiff School of Biosciences, Cardiff University, Main Building, Park Place, P.O. Box 915, Cardiff, CF10 3TL, S. Wales, UK
Received 6 December 2002; received in revised form 9 April 2003; accepted 9 April 2003
Abstract
Investigations into the deep marine environment have demonstrated the presence of a significant microbial biomass buried
deep within sediments on a global scale. It is now believed that this deep biosphere plays a major role in the global cycling
of elements and contains a large reservoir of organic carbon. This paper reports the development of a DNA extraction
protocol that addresses the particular problems faced in applying molecular ecological techniques to samples containing very
low biomass. Sediment samples were collected from different geographical locations within the Pacific Ocean and include the
Ocean Drilling Program (ODP) Leg 190, Nankai Trough Accretionary Prism. Seven DNA extraction protocols were tested
and a commercially available DNA extraction kit with modifications was shown to produce higher yields of polymerase
chain reaction (PCR)-amplifiable DNA than standard laboratory methods. Denaturing gradient gel electrophoresis (DGGE)
analysis of 16S rRNA gene diversity revealed that template DNA from these extremely low biomass sediment samples was
susceptible to PCR bias and random amplification. We propose that it is essential to screen 16S rRNA gene products for
bacterial diversity by DGGE or other rapid fingerprinting methods, prior to their use in establishing a representative clone
library of deep sub-seafloor bacteria. This represents a cautionary approach to analysis of microbial diversity in such subseafloor ecosystems.
D 2003 Elsevier Science B.V. All rights reserved.
Keywords: Anaerobic sediments; Deep biosphere; DNA extraction; DGGE; 16S rRNA; PCR bias
1. Introduction
Recent studies on the deep sub-seafloor biosphere
(Parkes et al., 1994, 2000) have shown that microbial
populations can be found buried within sediments as
* Corresponding author. Tel.: +44-292087-5877; fax: +44292087-4305.
E-mail address: [email protected] (A.J. Weightman).
deep as 800 mbsf (metres below the seafloor) and as
old as 15 million years (Wellesbury et al., 2002). Deep
marine sediments have also been estimated to contain
a bacterial mass z 10% of the total surface biosphere
(Parkes et al., 1994; Whitman et al., 1998). Microbial
ecology studies over the last decade have revealed low
culturability (Cragg et al., 1990), activity, cell density
and productivity (Parkes et al., 2000) in these deep
sediments. So culture independent molecular methods
are needed to investigate the diversity of prokaryotes
0167-7012/03/$ - see front matter D 2003 Elsevier Science B.V. All rights reserved.
doi:10.1016/S0167-7012(03)00140-4
156
G. Webster et al. / Journal of Microbiological Methods 55 (2003) 155–164
that are likely to be important in biogeochemical
cycles in this habitat.
Molecular analyses of microbial diversity in complex environmental samples such as marine sediments
require efficient and unbiased DNA extraction procedures (for review, see Roose-Amsaleg et al., 2001).
Direct DNA extraction from environmental samples
by either mechanical or chemical methods yields more
DNA, and is more representative, than methods that
employ cell removal from the environmental matrix
before DNA extraction (von Wintzingerode et al.,
1997; Li et al., 1999b). In addition, direct DNA
extraction methods facilitate rapid processing and
allow higher sample throughput. Detergent lysis and
freeze – thaw procedures (Rochelle et al., 1992a; Marchesi et al., 1998; Juniper et al., 2001) have been used
for direct DNA extraction from subsurface sediments.
Bead beating with and without detergent lysis (Kuske
et al., 1998; Teske et al., 2002), and in the presence of
phenol (Webster et al., 2002; Griffiths et al., 2000;
Stephen et al., 1996), have been used effectively to
extract good quality DNA from sediments and soil.
Recently, commercially available bead-beating-based
DNA extraction kits, developed for soil, have also
been used on samples from the deep biosphere
(Orphan et al., 2001; Reed et al., 2002; Takai et al.,
2001).
In addition to DNA extraction, other steps in
nucleic acid-based community analyses are also subject to bias and error. For example, sample handling
and/or storage (Rochelle et al., 1994), DNA template
concentration (Chandler et al., 1997), DNA purity
(Roose-Amsaleg et al., 2001; Juniper et al., 2001)
and PCR conditions (Chandler et al., 1997) can result
in the selective amplification of marker genes.
In this report, we describe the empirical development of a protocol which aims to overcome the major
potential problems faced when analysing bacterial
16S rRNA gene diversity in the deep sub-seafloor
biosphere. The paper will detail a method of DNA
extraction suitable for samples with extremely low
biomass, organic matter and DNA template followed
by a series of steps to produce representative clone
libraries of deep sediment samples. We also recommend the use of denaturing gradient gel electrophoresis (DGGE) as a time saving step to screen PCR
products for 16S rRNA sequence diversity prior to
cloning.
2. Materials and methods
2.1. Sample description and handling
Sediment samples were collected as whole round
cores (WRC) from locations in the Pacific Ocean,
South East of Shikoku Island, Japan by the Ocean
Drilling Program (ODP) Leg 190 (Nankai Trough) and
along the Chilean Continental Margin by the German
research vessel SONNE during cruise SO156, Peru
und Chile Kontinentalhang (PUCK). Nankai Trough,
Site 1173 (32j 14.663VN 135j 1.509VE) at 4790.7 mbsl
(metres below sea level), sample depths 4.15, 98.3 and
193.3 mbsf (metres below seafloor); Site 1174 (32j
20.540VN 134j 57.386VE) at 4751 mbsl, sample depths
306.7, 412.6, 499.55, 598.85 and 656.45 mbsf. Chilean Continental Margin, Gravity core GeoB 7112-3
(24j 02.00VS 70j 49.41VW) at 2507 mbsl, sample
depth 2.2 mbsf; Gravity core GeoB 7132-5 (29j
28.00VS 71j 53.49VW) at 3248 mbsl, sample depth
1.0 mbsf; Gravity core GeoB 7190-3 (44j 16.99VS 75j
51.93VW) at 3285 mbsl, sample depth 3.1 mbsf. All
ODP samples used in this study were collected with an
advanced hydraulic piston corer and bacteria sized
fluorescent beads within the drilling fluid as a contamination check. No fluorescent beads were found
within the inner core samples (Moore et al., 2001).
To further minimise the risk of contamination,
intact Nankai Trough WRCs were aseptically subsampled (Parkes et al., 1995) and stored at 80 jC.
The WRC samples from the Chile Continental Margin
were stored intact, anaerobically at 80 jC prior to
being aseptically sub-sampled in a laminar air flow
cabinet with a sterile 2-cm diameter stainless steel
corer. All sub-samples were stored at 80 jC until
required for molecular analysis.
2.2. DNA extraction, purification and quantification
The DNA extraction optimisation, development and
methodological comparison were undertaken on sediment samples from the Nankai Trough site 1173 at 4.15
mbsf and a control surface sediment collected from
Cardiff Bay, Cardiff, UK. A total of seven DNA
extraction protocols were investigated for suitability
on these sediments, based on previously published
techniques (Marchesi et al., 1998; Griffiths et al.,
2000; Webster et al., 2002) and commercial DNA
G. Webster et al. / Journal of Microbiological Methods 55 (2003) 155–164
extraction kits, designated JRM, GW, RIG, ANC, MB,
FAST and FAST+ (Table 1). Extraction procedures
were undertaken as described (Marchesi et al., 1998;
Griffiths et al., 2000; Webster et al., 2002) or as
recommended in the manufacturer’s instructions. The
exception was FAST+, which was the same as FAST
but with the following modifications: addition of 200
Ag of poly-adenylic acid (poly A) to the lysis mixture
(Hugenholtz et al., 1998), extended spin and matrix
binding times, the use of Hi-Yield Nucleic Acid Recovery Tubes (Robbins Scientific, Sunnyvale, CA,
USA), and eluting the crude DNA extract in 100 Al
of sterile distilled water (SDW). DNA extractions were
carried out on 5 1 g replicate samples except JRM
and MB which employed a 1 10 g sample. Replicate
crude DNA fractions (5 1 g samples) were pooled,
purified and concentrated in a YM-100 Microcon
(Millipore, Bedford, MA, USA) centrifugal device by
washing three times with 200 Al SDW and eluting in 40
Al SDW. Crude extracts obtained by JRM and MB
methods were also washed and concentrated in YM100 Microcon filters and resuspended in 40 Al SDW.
To quantify DNA yield, extracts were examined by
agarose (1.2% w/v) gel electrophoresis, stained with
0.5 Ag ml 1 ethidium bromide and compared to
HyperLadder I DNA quantification marker (Bioline,
London, UK). DNA purity was assessed by its ability
to amplify with bacterial 16S rRNA gene primers in
the polymerase chain reaction (PCR).
157
2.3. PCR amplification of 16S rRNA gene sequences
Amplification of 16S rRNA genes from Bacteria
was performed using the following primer combinations in a nested PCR with 27F-1492R (DeLong,
1992) and 357F-GC-518R (Muyzer et al., 1993).
Primary amplification reactions (27F-1492R) were
performed with 0.4 pmol Al 1 of primers, 1 Al of
DNA template, 1 reaction buffer (Bioline), 1.5 mM
MgCl2, 1.5 U Biotaq DNA polymerase (Bioline), 0.25
mM each dNTP, 10 Ag bovine serum albumin (BSA)
in a 50-Al PCR reaction mixture with molecular grade
water. Negative controls, with 1 Al of molecular grade
water as template, were included in all sets of PCR
reactions to provide a contamination check. Reaction
mixtures were held at 95 jC for 2 min followed by 30
cycles of 94 jC for 30 s, 52 jC for 30 s and 72 jC for
90 s plus 1 s per cycle, with a final extension step of 5
min at 72 jC. The secondary (nested) PCR amplification step (357F-GC-518R) was carried out as above
without BSA in a 50-Al reaction mix. A re-amplified
negative control from the first round PCR plus a fresh
negative control were also included. PCR conditions
were as previously described (Muyzer et al., 1993).
All amplifications were carried out in a DNA Engine
Dyad Thermal Cycler (MJ Research, Boston, MA,
USA). PCR operations were carried out under sterile
conditions and all disposable plasticware was autoclaved and UV treated prior to use. Primers used in
Table 1
A comparison of different DNA extraction procedures on sediment from the Nankai Trough Accretionary Prism (ODP Leg 190) site 1173 at
4.15 mbsf
DNA extraction method
Code
Preparation DNA yield
timea (h)
(ng DNA g 1 fresh
weight sediment)
Suitability for Reference or
PCRmanufacturer
amplifiableb automation
Lysozyme/proteinaseK,
phenol-chloroform
Bead beating, phenol-chloroform
Bead beating, phenol-chloroform
GENECLEAN kit for ancient DNA
UltraClean soil DNA kit mega prep
JRM*
10
10
F
No
Marchesi et al. (1998)
GW
RIG
ANC
MB*
5
5
5+
2.5
0c
0c
0c
1–5
–
–
–
F
Yes
Yes
No
Yes
FAST
FAST +
3
3
8
15
+
+
Yes
Yes
Webster et al. (2002)
Griffiths et al. (2000)
Bio101, Vista, CA, USA
MoBio, Solana Beach,
CA, USA
Bio101
Bio101
FastDNA Spin Kit for Soil
FastDNA Spin Kit for Soil with
modifications
a
Preparation time based on the time required to process 5 1 g replicate samples, except *1 10 g sample.
PCR-amplifiable DNA with Bacteria-specific 16S rRNA gene primers 27F/1492R (DeLong, 1992) and 357F-GC/518R (Muyzer et al.,
1993), F: poor PCR reproducibilty.
c
No DNA detected by ethidium bromide-stained agarose gel electrophoresis.
b
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G. Webster et al. / Journal of Microbiological Methods 55 (2003) 155–164
this study were analysed using ROSE version 1.1.3
(Ashelford et al., 2002) computer software to check
the coverage of the primer within the bacterial domain
of the RDP database (release 8.1), Ribosomal Database Project-II (http://www.rdp.cme.msu.edu/).
2.4. DGGE analysis of bacterial diversity
DGGE was carried out on the nested PCR products
to check for bacterial diversity as previously described
(Schäfer and Muyzer, 2001; Webster et al., 2002). PCR
products (ca. 200 ng of each product) were separated
using 8% (w/v) polyacrylamide gels with a denaturant
gradient between 30% and 60%. One hundred percent
denaturing conditions are defined as 7 M urea and 40%
(v/v) formamide. Gels were poured with the aid of a
50-ml volume Gradient Mixer (Fisher Scientific,
Loughborough, UK) and electrophoresis done at 200
V for 5 h at 60 jC. Polyacrylamide gels were stained
with SYBRGold nucleic acid gel stain (Molecular
Probes, Leiden, The Netherlands) for 30 min and
viewed under UV. Gel images were captured with a
Gene Genius Bio Imaging System (Syngene, Cambridge, UK).
sediments (JRM), humic rich soils (GW, RIG and
MB) and ancient DNA (ANC) were not reliable for
the extraction of PCR-amplifiable DNA from sediments of the Nankai Trough site 1173 (Table 1). In
contrast, DNA was readily extracted from the control
Cardiff Bay sediment by all methods (data not shown).
The best method tested for obtaining DNA from deep
sediments was the FastDNA Spin Kit for Soil with
modifications (designated FAST+ method) which
included the addition of poly A to the lysis buffer.
Poly A is thought to block the sites on sediment
particles that DNA could bind to after cell lysis and
so increase DNA yield. Nankai site 1173 at 4.15-mbsf
sediment DNA yield increased by two-fold compared
to the FAST method. However, relatively low quantities of DNA were still obtained by the FAST+ method
(Fig. 1) which presumably reflects the low biomass in
these samples (7.23 – 5.38 107 cells ml 1 and average TOC of 0.35 wt.%; Moore et al., 2001) and since
the same DNA extraction protocol employed on surface sediments of Cardiff Bay resulted in about 50 more DNA (Fig. 1). DNA yields obtained by the
laborious JRM method, which was modified from
Rochelle et al. (1992a) and by the MB method, were
2.5. Sequencing and phylogenetic analysis of excised
DGGE bands
Excised DGGE bands were re-amplified by PCR,
confirmed by DGGE and the re-amplified products
sequenced directly with the 357F or 518R primer using
an ABI PRISM 3100-Genetic Analyzer (Applied Biosystems, Foster City, CA, USA). Partial bacterial 16S
rRNA gene sequences were subjected to a NCBI
BLASTN (http://www.ncbi.nlm.nih.gov/blast/) search
to identify sequences with highest similarity. Bacterial
16S rRNA sequences obtained during this study have
been deposited as accession numbers AJ517415 to
AJ517419.
3. Results
3.1. DNA recovery from deep sub-seafloor sediments
A methodological comparison of different DNA
extraction techniques and commercially available kits
found that previous laboratory methods used on deep
Fig. 1. Gel electrophoresis of 25% of the total DNA extracted using
FAST+ method from deep-sea sediment samples. Lane 1, HyperLadder I DNA quantification marker; lane 2, Nankai Trough site
1173, 4.15 mbsf (5 g sediment); lane 3, Nankai Trough site 1173,
98.3 mbsf (5 g sediment); lane 4, Cardiff Bay (control) surface
sediment (1 g sediment).
G. Webster et al. / Journal of Microbiological Methods 55 (2003) 155–164
comparable to yields obtained by the FAST method
without modifications (Table 1). However, in our
hands, the FAST+ method was found to be the most
reliable and consistent with regard to DNA yield and
ability to generate PCR products from DNA extracted
from these sediments.
3.2. Determination of bacterial community structure
in the Nankai Trough site 1173
The DNA obtained by the FAST+ method from the
Nankai Trough site 1173 after purification was shown
to be of sufficient quality to be used as template DNA
in the PCR although, it was necessary to dilute the
purified DNA 50 before bacterial 16S rRNA gene
products could be obtained. Primary amplification
using the primer pair 27F-1492R resulted in a PCR
product of about 1.5 kb; nearly a full-length sequence
of the 16S rRNA gene. Complete or near complete 16S
rRNA sequences are the ideal when compiling 16S
rRNA gene clone libraries of bacterial diversity. However, repeated experiments demonstrated that when
these primary PCR products were re-amplified in a
159
nested PCR, using primers (357F-GC-518R) that produce a smaller-sized rDNA product (194 bp) and
analysed by DGGE analysis, they gave rise to different
DGGE patterns. Specific experiments designed to
investigate this observation further looked at the
DGGE profiles obtained from six different sets of
5 replicate PCR products obtained from Nankai
Trough site 1173 DNA. It was observed that 50% of
the batches of PCR products showed a reduced bacterial community structure with noticeably fewer bands.
Fig. 2 is an example of the DGGE results obtained
from two of the sets of 5 replicate PCR reactions
that were produced with the aim of constructing clone
libraries from Nankai Trough sediment. One set (Set
A) of PCR products (Fig. 2A) showed a low bacterial
diversity that was dominated by two sequence types
(band N2, a h-Proteobacteria and band N1, associated
with the OP9 candidate division). In comparison, the
other group of PCR products (Set B; Fig. 2B) showed a
high degree of sequence diversity but also contained
one dominant DGGE band (band N3) similar to band
N1 and near absence of band N2. Sequencing band N3
showed that it had 99% sequence similarity to the
Fig. 2. DGGE gel images showing the differences between replicate 16S rRNA gene PCR amplifications from the same template DNA of
Nankai Trough site 1173 at 4.15 mbsf. (A) Five replicate nested PCR amplifications, Set A. (B) Five replicate nested PCR amplifications, Set B.
(C) Duplicate nested PCR amplifications using pooled template DNA from the primary amplification products of Set A (Lanes 1A and 2A) and
Set B (Lanes 1B and 2B). Lanes marked M represent a DGGE marker lane consisting of 16S rRNA sequences from Pseudomonas sp.,
Staphylococcus sp., Bacillus sp. and Arthrobacter sp. Arrows represent DGGE bands that were excised for sequencing.
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G. Webster et al. / Journal of Microbiological Methods 55 (2003) 155–164
uncultured bacterium clones, MB-102-03 found in
deep sediments of the Nankai Trough forearc basin
(Reed et al., 2002) and JTB138 from the Japan Trench
(Li et al., 1999a) and associated with the candidate
division OP9 (Hugenholtz et al., 1998; Teske et al.,
2002). The differences in results are suggestive of PCR
bias caused by random amplification due to low
template concentration (Chandler et al., 1997).
In bacterial diversity studies, a number of PCR
products from the same template DNA are often
pooled prior to cloning (e.g. Chandler et al., 1997;
Marchesi et al., 2001; Reed et al., 2002). This is to
ensure a representative sample and sufficient DNA to
achieve optimum cloning efficiency. Therefore, primary PCR products from the two sets of PCRs shown
in Fig. 2A and B were pooled prior to being reamplified for DGGE analysis. Pooling of PCR products did not change the diversity of 16S rRNA genes
in the template DNA as assessed by DGGE (Fig. 2C).
Clone libraries that were produced from the two sets
of primary PCR products shown in Fig. 2 confirmed
that the diversity of 16S rRNA sequences in PCR
product Set A was completely dominated by two clone
types, a h-Proteobacteria clone sequence similar to
band N2 and a clone associated with the OP9 candidate division. Whereas, the clone library from PCR
product Set B showed a higher degree of sequence
diversity (4% Planctomycetes, 8% Cyanobacteria and
chloroplasts, 11% h-Proteobacteria, 14% g-Proteobacteria and 53% associated with the OP9 candidate
division; C.J. Newberry, G. Webster, A.J. Weightman
and J.C. Fry, unpublished data).
Sequences of Escherichia coli found in some
DGGE samples and in PCR negative controls during
this study (data not shown) were attributed to a batch
of Taq DNA polymerase. Previously, it has been
shown that sequences of E. coli can be linked to
contaminating crude DNA in commercial preparations
of Taq DNA polymerases (Rochelle et al., 1992b).
However, this type of contamination was readily
identified during this study by DGGE analysis and
contaminated samples were discarded.
samples obtained from the Nankai Trough and the
Chilean Continental Margin. DNA could be readily
extracted using the FAST+ from all samples obtained
from the Chilean Continental Margin and from the
two other sediment depths (98.3 and 193.3 mbsf) of
the Nankai Trough site 1173 (Fig. 1). Lower concentrations of DNA were extracted with increasing sample depth at site 1173, which almost certainly reflected
the lower cell counts (3.04 107 – 1.85 106 cells
ml 1; Moore et al., 2001) and similar to observations
by Rochelle et al. (1992a) on Japan Sea sediment.
However, DNA could not be recovered from any
samples obtained from the Nankai Trough site 1174,
a result that may be attributed to the very low biomass
(6.11 106 – 1.59 104 cells ml 1) and organic matter (average TOC = 0.37 wt.%) observed in these deep
samples (Moore et al., 2001).
DNA extracted from the Chilean Contentinal Margin sediment samples GeoB 7112-3, GeoB 7132-5 and
GeoB 7190-3 readily amplified with 16S rRNA primers and PCR products could be analysed by DGGE
3.3. Application of optimal protocol to other deep
biosphere sediments
Fig. 3. DGGE gel showing the bacterial 16S rRNA gene diversity
within duplicate sub-seafloor sediment samples of the Chilean
Continental Margin. Lane M, DGGE marker (see Fig. 2); Lanes 1
and 2, sediment sample GeoB 7112-3; Lanes 3 and 4, sediment
sample GeoB 7132-5; Lanes 5 and 6, sediment sample GeoB 7190-3.
Arrows represent DGGE bands that were excised for sequencing.
The above DNA extraction procedure and analysis
of microbial diversity was applied to other sediment
G. Webster et al. / Journal of Microbiological Methods 55 (2003) 155–164
(Fig. 3). The DGGE banding patterns obtained for these
samples were similar to each other suggesting that
these sediments have similar bacterial populations.
All samples were observed to have one brightly stained
dominant band (Fig. 3) which when excised and
sequenced (bands C1 and C2) showed 98% sequence
identity to clones MB-B2-103 (Reed et al., 2002) and
JTB138 (Li et al., 1999a) and 97% identity to clone C1
B023 from hydrothermally heated sediment from the
Guaymas Basin (Teske et al., 2002) associated with the
candidate division OP9 (Hugenholtz et al., 1998; Teske
et al., 2002).
4. Discussion
Analysis of microbial community structure in the
deep sub-seafloor biosphere using nucleic acid techniques requires efficient and unbiased DNA extraction
procedures, and because samples are usually rare and
material is limited, it is essential that investigators
optimise DNA extraction protocols before undertaking comprehensive studies. In our study we found that
the most suitable DNA extraction protocol for sediments tested was a commercially available kit,
reported to lyse a wide range of microbes including,
Gram-positive, spore-forming and other recalcitrant
cells (Roose-Amsaleg et al., 2001). Minor modifications were, however, necessary to improve DNA
yields. The FastDNA Spin Kit for Soil plus modifications (FAST+) reliably extracted DNA from a
number of different sediments with some exceptions.
DNA yields were often low reflecting the low prokaryotic cell counts in these samples.
Extracted DNA must be representative of the total
microbial community within the sample and be of
sufficient quality for subsequent PCR. Previous studies on organic rich subsurface sediments increased
DNA yields by a 48-h gentle agitation in lysis buffer,
but DNA was unamplifiable by PCR due to the coextraction of inhibitors (Juniper et al., 2001). Humic
acids, pigments and heavy metals often co-extract
with DNA and are known to inhibit PCR amplification (Tsai and Olson, 1991; Rochelle et al., 1992a;
Juniper et al., 2001). In this study, it was necessary to
dilute DNA before bacterial 16S rRNA gene products
could be obtained by PCR amplification. Rochelle et
al. (1992a) also reported similar findings from deep
161
sediments of the Japan Sea. Recently, Reed et al.
(2002) using the MB kit found that PCR-amplifiable DNA, although at low concentrations ( < 10 ng
g 1 sediment) and comparable to this study, was
extracted from sediments of the Nankai Trough forearc
basin and used in prokaryotic diversity studies. These
workers also report problems when working with
extremely low biomass samples and found that amplification of bacterial 16S rDNA required addition of
more template DNA than for archaeal amplification.
This was thought to reflect the dominance of archaeal
cells in these samples over Bacteria (Reed et al.,
2002).
Another important consideration within the laboratory is sample preparation time, and it is clear from
Table 1 that the FastDNA Spin Kit for Soil is timeefficient. Time saving methodologies are becoming increasingly important as they present the opportunity to
use robotics for high sample throughput. The use of
commercially available kits as DNA extraction methods may also have important consequences in standardising laboratory procedures and automation that
would allow for more comparative studies between
workers. However, evidence suggests that sediments
from different geographical locations differ so greatly
in their chemical and physical properties that one
universal DNA extraction protocol may not be possible.
The most striking results in this study were the
differences observed between DGGE patterns from
different sets of PCR products obtained from the same
template DNA to construct clone libraries (Fig. 2).
There is little doubt that a clone library made from the
PCR products shown in Fig. 2A would not be representative of true diversity within these sediments.
Previously, the inability to amplify DNA at low
template concentrations in simple mammalian allelic
systems has been attributed to molecular sampling
error caused by stochastic fluctuations in the primer,
template, polymerase complex (Mutter and Boynton,
1995), termed PCR drift (Polz and Cavanaugh, 1998).
Polz and Cavanaugh (1998) recommend that to increase reproducibility between PCR replicates, amplifications should be carried out using high DNA
template concentrations. In the study by Mutter and
Boynton (1995), template concentrations of >0.5 ng
were necessary to generate consistent androgen receptor allele PCR products and as template concentrations dropped below 0.5 ng quantification of PCR
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G. Webster et al. / Journal of Microbiological Methods 55 (2003) 155–164
deteriorated. In our samples, DNA concentration
would be < 30 pg and therefore lower than those
required for quantitative amplification. In addition, the
number of different 16S rRNA genes present in our
environmental samples would be higher than the
target sequence in simple allelic systems. It is therefore possible that PCR bias due to random amplification of low concentration templates or differential
denaturation of different DNA templates during initial
rounds of PCR could have contributed to diversity
differences between the different sets of PCR products. We propose that these factors, coupled with
possible influences of residual PCR inhibitors, led to
unpredictable preferential amplification observed.
However, the clear demonstration, in this study, that
DGGE can be used as a tool to screen and reliably
identify predominant 16S rRNA genes within a clone
library would alleviate any misinterpretation of bacterial community structure caused by PCR drift. We
therefore stress that it is important to undertake
DGGE analysis on PCR products from low biomass
samples that are to be used in prokaryotic diversity
studies.
Other potential problems when working with low
biomass samples and DNA from unknown bacterial
populations are the introduction of artifact 16S rDNA
from contamination in the DNA extraction and PCR
reagents. Tanner et al. (1998) noted the presence of
highly similar sequences (>99%) in clone libraries
that were obtained from many physically and chemically distinct environments. They undertook a study to
clone and sequence 16S rDNA fragments obtained in
the absence of added DNA template. Common contaminant sequences found were from the genera,
Duganella, Acinetobacter, Stenotrophomonas,
Escherichia, Leptothrix and Herbaspirillum. Commercial PCR reagents and primers sometimes contain
artifact DNA and filtering through Microcon filters
can remove contaminating DNA (Willersley et al.,
1999). The presence of E. coli 16S rDNA in some
samples during this study and in others (Rochelle et
al., 1992b) could be linked to contaminating crude
DNA in particular batches of commercial Taq polymerase. Reed et al. (2002) also highlight the potential
for contamination in their study on the Nankai Trough
forearc basin and implemented rigorous negative
controls to ensure the authenticity of their clone
sequences.
Diversity of bacterial sequences within the environment can also be underestimated by the particular
methodological approach used and especially by the
choice of PCR primers employed (Marchesi et al.,
1998; Schmalenberger et al., 2001). Using the computer software ROSE (Ashelford et al., 2002) in
conjunction with the RDP database, it was possible
to determine primer coverage as a percentage of target
taxon from relevant sequence information. The primers 27F and 1492R showed 72.9% and 16.3%
coverage of Bacteria, respectively. While the primers
for DGGE analysis were considerably better and
matched with 84% (357F) and 86.7% (518R) of
bacterial 16S rDNA sequences in the database. Therefore, in further studies, different primer combinations,
or several different primer sets, should be considered
to obtain a better prokaryotic taxon coverage of the
deep sub-seafloor biosphere.
In conclusion, we recommend that workers studying prokaryotic diversity in the deep biosphere adopt
the procedure summarised in Fig. 4. It is essential,
when working with samples of low biomass that extra
care is taken during sample collection, handling and
during the extraction of nucleic acids. PCR conditions
and protocols must be efficient with rigorous contamination checks in place. For 16S rRNA clone libraries,
we also recommend that PCR products are checked
for diversity using DGGE, or other rapid fingerprint-
Fig. 4. Recommended experimental procedure for the molecular
analysis of prokaryotic diversity in the deep sub-seafloor biosphere.
G. Webster et al. / Journal of Microbiological Methods 55 (2003) 155–164
ing methods, such as T-RFLP (Lueders and Friedrich,
2003), prior to ligation.
Acknowledgements
The authors would like to thank the ODP and
Barry Cragg, University of Bristol for Leg 190
samples, Jens Kallmeyer, Tim Ferdelman and Bo
Barker Jørgenson, MPI, Bremen for supplying
samples from the PUCK SO156 Cruise. The authors
would also like to acknowledge Barry Cragg, Julian
Marchesi (University of Cork) and Laurent Toffin
(Institut Universitaire Européen de la Mer, Plouzané)
for Leg 190 WRC sub-sampling and additionally
Julian Marchesi for preliminary investigations. GW
was funded by the NERC M&FMB thematic
programme (grant NER/T/S/2000/636) and CJN by
the EU DeepBUG project (contract number EVK3CT-1999-00017).
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