Evaluating amplified rDNA restriction analysis assay for identification of bacterial communities.

Abstract

Amplified ribosomal DNA restriction analysis (ARDRA) and restriction fragment length polymorphism were originally used for strain typing and for screening clone libraries to identify phylogenetic clusters within a microbial community. Here we used ARDRA as a model to examine the capacity of restriction-based techniques for clone identification, and the possibility of deriving phylogenetic information from ARDRA-based dendrograms. ARDRA was performed in silico on 48,759 sequences from the Ribosomal Database Project, and it was found that the fragmentation profiles were not necessarily unique for each sequence in the database, resulting in different species sharing fragmentation profiles. Although ARDRA-based clusters separated clones into different genera, these phylogenetic clusters did not overlap with trees constructed according to sequence alignment,calling into question the intra-genus ARDRA based phylogeny. It is thus suggested that the prediction power of ARDRA clusters in identifying clone phylogeny be regarded with caution.

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SHORT COMMUNICATION
Evaluating amplified rDNA restriction analysis assay
for identification of bacterial communities
Menachem Y. Sklarz Æ Æ Roey Angel Æ Æ Osnat Gillor Æ Æ
M. Ines M. Soares
Received: 14 July 2009/Accepted: 15 September 2009/Published online: 24 September 2009
? The Author(s) 2009. This article is published with open access at Springerlink.com
Abstract
analysis (ARDRA) and restriction fragment length
polymorphism were originally used for strain typing
and for screening clone libraries to identify phyloge-
netic clusters within a microbial community. Here we
used ARDRA as a model to examine the capacity of
restriction-based techniques for clone identification,
and the possibility of deriving phylogenetic informa-
Amplified ribosomal DNA restriction
tion from ARDRA-based dendrograms. ARDRA was
performed in silico on 48,759 sequences from the
Ribosomal Database Project, and it was found that the
fragmentation profiles were not necessarily unique for
each sequence in the database, resulting in different
species sharing fragmentation profiles. Although
ARDRA-based clusters separated clones into different
genera, these phylogenetic clusters did not overlap
with trees constructed according to sequence align-
ment, calling into question the intra-genus ARDRA-
based phylogeny. It is thus suggested that the
prediction power of ARDRA clusters in identifying
clone phylogeny be regarded with caution.
Keywords
16S subunit ribosomal DNA ?
Ribosomal database project
ARDRA ? In-silico fragmentation ?
Abbreviations
ARDRAAmplified ribosomal DNA restriction
analysis
Restriction endonucleaseRE
Amplified ribosomal DNA restriction analysis (AR-
DRA) is a commonly used tool to study microbial
diversity that relies on DNA polymorphism (Deng
et al. 2008). Clones containing 16S rDNA gene
fragments, obtained by applying either universal or
genus-specific primer sets, are amplified and digested
Electronic supplementary material
this article (doi:10.1007/s10482-009-9380-1) contains
supplementary material, which is available to authorized users.
The online version of
M. Y. Sklarz (&) ? R. Angel ? O. Gillor ? M. I. M. Soares
Environmental Hydrology and Microbiology,
Zuckerberg Institute for Water Research,
Blaustein Institutes for Desert Research,
Ben-Gurion University of the Negev,
Sede Boqer Campus, 84990 Midreshet Ben Gurion, Israel
e-mail: Sklarz@bgu.ac.il
R. Angel
e-mail: angel@mpi-marburg.mpg.de
O. Gillor
e-mail: gilloro@bgu.ac.il
M. I. M. Soares
e-mail: soares@bgu.ac.il
Present Address:
R. Angel
Max Planck Institute for Terrestrial Microbiology,
Karl-von-Frisch-Strasse 8, 35043 Marburg, Germany
123
Antonie van Leeuwenhoek (2009) 96:659–664
DOI 10.1007/s10482-009-9380-1

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by restriction endonucleases (REs), followed by
separation of the resulting fragments on high-density
agarose or acrylamide gels. The emerging profiles are
then used either to cluster the community into
genotypic groups or for strain typing (Tiedje et al.
1999).
Attempts to use ARDRA to identify species within
particular genera have only been partially successful.
Mycoplasma species isolated from cats (Criado-
Fornelio et al. 2003) and humans (Stakenborg et al.
2005) were identified using the ARDRA technique,
though their identity was not confirmed by sequenc-
ing. ARDRA fingerprinting could not distinguish
between genomic species of Acinetobacter, even at a
low cut-off level (Koeleman et al. 1998), while
identification of Bdellovibrio and Bdellovibrio-like
microorganisms using ARDRA grouping mostly
reflected diversity and phylogenetic affiliation when
compared to sequencing of the 16S rDNA gene
(Davidov and Jurkevitch 2004). Rhizobia species
isolated from nodules of Vicia were identified using
16S ARDRA, restriction fragment length polymor-
phism (RFLP) of 16S–23S internally transcribed
spacer (ITS), and sequencing of the 16S rDNA. The
derived phylogenetic relationships mostly supported
the relationships estimated by the ARDRA and ITS-
RFLP, albeit some discrepancies were detected (Lei
et al. 2008). Lactobacillus strains isolated from grape
must and wine (Rodas et al. 2003), dairy products
(Giraffa et al. 1998), and faecal samples (Ventura
et al. 2000) were identified by ARDRA fingerprint-
ing. However, the tested isolates were verified by
partial sequencing and by comparing the ARDRA
patterns to predicted profiles of known strains of
lactobacilli. Attempts to apply ARDRA profiles using
a panel of six enzymes in order to discriminate
Ralstonia and Pandoraea strains isolated from the
respiratory tract of cystic fibrosis patients showed that
all the Ralstonia, but not the Pandoraea strains tested
could be differentiated (Segonds et al. 2003). Brev-
ibacillus species isolated from clinical, dairy and
industrial environments were distinguished using
ARDRA (the amplicons were digested with five
REs), but comparison of the emerging profiles to
those obtained with several phenotypic methods and
sequence analysis revealed inconsistencies (Logan
et al. 2002). However, a careful choice of REs
enabled the use of the ARDRA technique to
discriminate among Lactobacillus, Streptococcus
and Bifidobacterium at the genus, but not species,
level (Collado and Hernandez 2007).
Heyndrickx et al. (1996) studied the application of
ARDRA in the clarification of the phylogeny and
taxonomy of the genus Bacillus. They found several
inter-specific phylogenetic relationships, as well as
inter-group phylogenetic relationships, to be in
accordance with 16S rDNA sequence analysis; thus,
the ARDRA technique, based on the combination of
five selected REs, was deemed reliable and valuable
for phylogenetic and taxonomic studies of large sets
of strains. However, some apparent phylogenetic
relationships indicated by ARDRA were not sup-
ported by the sequence analysis results. It was
postulated that this stemmed from the small phylo-
genetic distance between these rDNA groups (Van-
eechoutte and Heyndrickx 2001).
A study assessing the applicability of ARDRA to
the identification of operational taxonomic units
based on their ARDRA profiles was carried out
more than a decade ago (Moyer et al. 1996), in
which a detailed analysis of the types of REs that
provide the best differentiating power was per-
formed. In addition, Moyer et al. (1996) compared
phylogenetic trees based on 16S rDNA sequences
and on ARDRA profiles, and reached the conclusion
that using ten REs will yield 76–100% success in
obtaining accurate phylogenetic affiliations. How-
ever, that study used the very narrow range of
sequences available at the time, while today the
databases have increased many-fold and the ques-
tions have once again arisen: Are ARDRA profiles
sufficient for clone identification? Are phylogenetic
relationships described by ARDRA sufficiently rep-
resentative of the ‘‘true’’ relationships determined by
the 16S rDNA sequences?
In the current study, we re-evaluated the predictive
power of ARDRA, by assessing two ways in which
ARDRA can be used to foresee the identity or
phylogeny of clones: (a) environmental clone iden-
tification via profile matching to theoretically com-
puted fragmentation profiles and (b) clustering of
ARDRA fragmentation profiles in comparison to
parallel sequence-based clustering.
A total of 48,759 sequences from the Ribosomal
Database Project (RDP) (Maidak et al. 2001) were
taken for in-silico ARDRA (see ‘‘Supplementary
material’’ for detailed methods). Profiles were found
to be unique to genera for two or more REs (Fig. 1a),
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even at a high error level of 20% in the sizing of the
restriction fragments (as might occur in agarose gels).
However, at least three enzymes were necessary to
differentiate species (Fig. 1b). Even then, while most
patterns referred to unique sequences, exceptions
were observed, e.g. species of Salmonella (one
species), Citrobacter (3), Klebsiella (3) and Entero-
bacter (7) shared patterns, as did species of Kocuria
(1), Micrococcus (3), Arthrobacter (4) and Strepto-
myces (3). When all ten REs were used, only four
patterns were shared by more than one genus:
Citrobacter (4) and Klebsiella (1); Legionella (3)
and Fluoribacter (1); Saccharothrix (1) and Actino-
synnema (1); Raoultella (1) and Citrobacter (1).
These results agree with those obtained by Moyer
et al. (1996); thus, we found their conclusions to be
applicable, even when a large number of sequences is
considered (48,759 vs. 106 sequences), for several
combinations of the tested REs (data not shown). It is
important to point out that the conclusions reached
above come from a global perspective; it is possible
that for specific genera, different sets of three REs
would be better for inter-genera differentiation. When
a specific genus is of interest, a specific set of REs
may produce a higher resolution even with less than
three REs. The scripts written by the authors can be
used to this end and can be obtained on request.
Dendrograms calculated from the theoretical frag-
mentation profiles (see ‘‘Supplementary material’’) of
random collections of species, both intra and inter-
genus, were found to have little relationship with the
phylogenetic clustering based on the corresponding
16S rDNA sequence. Trees based on 16S rDNA
sequences and on ARDRA fragmentation were com-
pared, and the average distance between the ARDRA-
based and sequence-based trees was 77 ± 2.6, out of a
maximum distance of 94 (see ‘‘Supplementary mate-
rial’’). In a parallel study, 20 groups of 85 sequences
each were used for comparison of ARDRA to 16S
rDNA sequence-based phylogenies (see details in
‘‘Supplementary material’’). The average similarity
between the sequence- and ARDRA-based clusters
was 2.9%, while the maximum similarity was 7.3%.
Since clustering is based on pairwise distance
or similarity between sequences, two distance
Error tolerance (%)
05 101520
40
60
80
100
Fraction of
unique profiles
Fraction of
unique profiles
40
60
80
100
a
b
6
7
8
9
1
2
3
4
5
Fig. 1 Proportion of profiles unique to a single genus (a) and to
a single species (b), defined as the number of profiles specific to
a single genus or species, respectively, divided by the total
number of profiles. Both are dependent on the error tolerance
(the x-axis) and on the number of restriction enzymes used. The
number indicates the number of restriction enzymes used
Pairwise alignment score
5060708090100110
Jaccard distance
0.0
0.2
0.4
0.6
0.8
1.0
1.2
Fig. 2 Correlation between the pairwise sequence analysis
scores and the calculated Jaccard distances for a random group
of 50 species
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parameters will result in similar trees if the two
parameterscorrelatetoacertaindegree.Whenrandom
groups of 50 species were used, a slight negative
correlation was found between the pairwise alignment
scores and the calculated Jaccard distances (for details
see ‘‘Supplementary material’’), with an average Pear-
son correlation coefficient of -0.23 ± 0.078 (Fig. 2).
Thenegativedirectionofthecorrelationwasexpected,
since pairwise alignment scores measure similarity
and the Jaccard distance measures dissimilarity; how-
ever, the low value of the Pearson correlation coeffi-
cient indicated a weak correlation. Consequently, the
phylogenetic information that could be attributed to
the ARDRA clustering, based on the Jaccard distance
between profiles, was limited.
Phylogenetic trees were constructed for 20 repre-
sentative OTUs from each of five genera with
increasing inter-genera distances (Fig. S1), based on
their 16S rDNA sequence (Fig. 3) and on the ARDRA
fragmentation profile (Fig. 4). The sequence-based
tree (Fig. 3) produced a clear division between the
genera, with inter-genera distances reflecting the
expected differences based on the taxonomic identity
of the genera. However, while the ARDRA tree
(Fig. 4) did differentiate between the OTUs (with one
exception), it did not maintain the taxonomic structure
of the genera (Fig. S1).
To conclude, ARDRA can be a suitable tool for
genus differentiation of environmental clones based
on in-silico fragmentation. Moreover, in-silico pro-
files may be used for species identification provided
caution is taken in the type and number of REs
selected. Differentiation of strains requires more
stringent measures, which are so time-consuming
that the applicability of ARDRA to that end can be
called into question. In addition, ARDRA-based
dendrograms may not mirror 16S rDNA sequence-
based phylogenetic trees.
Lysobacter
Lysobacter
Lysobacter
Lysobacter
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Lysobacter
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Lysobacter
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Lysobacter
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Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
Sphingomonas
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Nocardia
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Pseudomonas
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Acinetobacter
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Acinetobacter
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Acinetobacter
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Fig. 3 Sequence-based phylogenetic tree of 20 representatives from each of the genera listed in Fig. S1
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Lysobacter
Lysobacter
Lysobacter
Lysobacter
Lysobacter
Lysobacter
Lysobacter
Lysobacter
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