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Applied and Environmental Microbiology, April 1999, p. 1721-1730, Vol. 65, No. 4
0099-2240/99/$04.00+0
Copyright © 1999, American Society for Microbiology. All rights reserved.
Molecular Analysis of Bacterial Community Structure and
Diversity in Unimproved and Improved Upland Grass
Pastures
Allison E.
McCaig,
L. Anne
Glover, and
James I.
Prosser*
Department of Molecular and Cell Biology,
Institute of Medical Sciences, University of Aberdeen,
Foresterhill, Aberdeen AB25 2ZD, Scotland, United Kingdom
Received 21 October 1998/Accepted 25 January 1999
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ABSTRACT |
Bacterial community structure and diversity in rhizospheres in two
types of grassland, distinguished by both plant species and
fertilization regimen, were assessed by performing a 16S ribosomal DNA
(rDNA) sequence analysis of DNAs extracted from triplicate soil plots.
PCR products were cloned, and 45 to 48 clones from each of the six
libraries were partially sequenced. Phylogenetic analysis of the
resultant 275 clone sequences indicated that there was considerable
variation in abundance in replicate unfertilized, unimproved soil
samples and fertilized, improved soil samples but that there were no
significant differences in the abundance of any phylogenetic group.
Several clone sequences were identical in the 16S rDNA region analyzed,
and the clones comprised eight pairs of duplicate clones and two sets
of triplicate clones. Many clones were found to be most closely related
to environmental clones obtained in other studies, although three
clones were found to be identical to culturable species in databases.
The clones were clustered into operational taxonomic units at a level
of sequence similarity of >97% in order to quantify diversity. In all, 34 clusters containing two or more sequences were identified, and
the largest group contained nine clones. A number of diversity, dominance, and evenness indices were calculated, and they all indicated
that diversity was high, reflecting the low coverage of rDNA libraries
achieved. Differences in diversity between sample types were not
observed. Collector's curves, however, indicated that there were
differences in the underlying community structures; in particular,
there was reduced diversity of organisms of the
subdivision of the
class Proteobacteria (
-proteobacteria) in improved soils.
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INTRODUCTION |
Land use in the United Kingdom has
undergone considerable change over the last decade due to both economic
and political pressure and increasing public concern regarding the
quality of the environment. This has led to more extensive
grazing regimens in the uplands of Britain and reductions in
fertilizer applications. While considerable information concerning
the effect of this extensification on the vascular plant community is
available, the effect on soil bacteria is not understood. Plant and
bacterial activities are closely linked through microbial
utilization of root exudates, dead cells, and litter, and soil
bacterial diversity may therefore be influenced by plant diversity and
community structure.
The traditional approach to analysis of bacterial diversity involves
identification of pure cultures isolated on laboratory media. There is
strong evidence that this approach detects only a small proportion
(estimated to be less than 1% [38]) of the bacteria
present due to the selectivity of growth media and conditions. Analysis
of respiration in individual cells extracted from soil, however, has
indicated that virtually all bacteria in soil are metabolically active
(38). Analysis of DNA extracted from environmental samples
has allowed workers to investigate bacterial communities without cell
extraction and laboratory cultivation. Broad-scale techniques, such as
DNA reassociation and reannealing, provide a measure of total microbial
diversity and have revealed the influence of environmental parameters,
such as pollution (1) and agricultural exploitation, on
microbial diversity (38).
More detailed analyses can be performed by using 16S ribosomal DNA
(rDNA)-based techniques, and a range of methods targeting both rRNA
and rDNA are now used routinely in microbial ecology (reviewed in
references 8, 14, and 40). These
methods include detection by PCR, in situ hybridization, sequence
analysis, and denaturing gradient gel electrophoresis. Primers and
probes having different specificities, ranging from universal to
species specific, can be used with combinations of these techniques to
provide a comprehensive understanding of bacterial community structure. 16S rDNA-based analyses of terrestrial samples from a range of geographical locations (3, 4, 10, 16, 17, 27, 29, 45) have
demonstrated that there is considerable bacterial diversity in natural
environments. Sequences cloned from environmental samples are rarely
identical to sequences of cultured bacteria represented in gene
databases, and all investigations have recovered clones belonging to a
new bacterial group, which is represented by the cultured species
Acidobacterium capsulatum and Holophaga foetida (16, 22). Several other clusters of sequences have been
identified, and these sequences appear to be widespread in soils with
very diverse physicochemical properties (3, 4, 17, 29).
The aim of this project was to apply quantitative measures of
diversity to 16S rDNA data and to use the information obtained to
determine the effects of grass species and other influences associated with improvement (namely, fertilization and grazing) on the
diversity and community structure of rhizobacteria by using samples
from the same geographical location.
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MATERIALS AND METHODS |
Sample collection and DNA extraction.
Rhizosphere samples
from two characteristic vegetation types, designated unimproved and
improved (U4a and MG6 of the National Vegetation Classification,
respectively) (31), were collected from Sourhope Research
Station (map reference NT 850 205) in the Borders Region of Scotland.
The unimproved plots (brown forest soil; pH 5.5 to 6.9; 0.33 to 0.37 µg of C g [dry weight]
1) represented natural
grassland dominated by the grass species Agrostis capillaris
and Festuca ovina. They had never received fertilizer
treatment but were grazed by sheep during the summer months. The
improved plots (brown forest soil; pH 6.1 to 6.8; 0.21 to 0.26 µg of
C g [dry weight]
1) were reseeded with Lolium
perenne (perennial ryegrass) and Trifolium repens
(clover) approximately 25 years ago. These plots received dressings
consisting of 50 kg of N ha
1 in March and August and
fertilizer containing N, P, and K (40:20:20) in May. They were also
grazed by sheep from spring to mid-November (weather permitting) at a
sward height of 4 cm. At each sampling site, three 5- by 5-m quadrats
were randomly located, and 50 cores (diameter, 3.5 cm; depth, 5 cm)
were collected, combined, and sieved (mesh size, <2 mm) to remove
plant material. Due to the density of the grass root systems, all soil
was assumed to be in contact with plant roots and was considered
rhizosphere. Subsamples of soil used for molecular analyses were stored
at
70°C.
DNA was extracted by C. D. Clegg (Scottish Crop Research
Institute, Invergowrie, United Kingdom), who used the protocol of Clegg
et al. (6). This method involved incubation of 1-g samples of soil in the presence of polyvinylpolypyrrolidone and lysozyme, followed by three rounds of freezing and thawing to facilitate cell
disruption. Crude DNA was purified by two rounds of cesium chloride
centrifugation, which produced DNA of high purity (6).
PCR amplification, cloning, and sequencing.
PCR
amplification of bacterial rDNA was carried out by using the
primers Bf (20) and 1390r (7). Amplification was
performed in a 50-µl (total volume) reaction mixture containing ~10
ng of soil DNA, 1 U of Taq DNA polymerase (Promega UK Ltd.,
Southampton, United Kingdom), an appropriate dilution of the
manufacturer's buffer, each deoxynucleoside triphosphate at a
concentration of 250 µM, each primer at a concentration of 0.4 µM,
and 1 µl of a bovine serum albumin solution (20 mg ml
1;
Boehringer Mannheim Diagnostics and Biochemicals Ltd., Lewes, United
Kingdom). Thirty cycles of amplification were carried out with a model
Omn-E thermal cycler (Hybaid Ltd., Teddington, United Kingdom) as
follows: one cycle consisting of 95°C for 10 min, 50°C for 1 min,
and 72°C for 2 min; nine cycles consisting of 94°C for 30 s,
50°C for 30 s, and 72°C for 2 min; and 20 cycles consisting of
92°C for 30 s, 50°C for 30 s, and 72°C for 2.5 min. This was followed by a final step consisting of incubation at 72°C
for 30 min. Products were visualized on an agarose gel stained with
ethidium bromide (1%, wt/vol), bands were excised, and DNA was
purified from gel slices by using a QIAEX II gel extraction kit (Qiagen
Ltd., Crawley, United Kingdom).
Purified amplification products were cloned into the vector pCR 2.1 from an Original TA Cloning kit (Invitrogen BV, Groningen,
The
Netherlands) by using a vector/insert ratio of 1:1. Ligations
were
transformed into supercompetent
Escherichia coli XL1-Blue
MRF' Kan (Stratagene Ltd., Cambridge, United Kingdom). White colonies
were screened directly for inserts by performing colony PCR with
T7 and
M13 reverse primers. The amplification conditions were
the same as
those described above except that bovine serum albumin
was not included
in the mixture and the final step consisted of
incubation for 10 min at
72°C. The PCR products were visualized
by agarose gel
electrophoresis, and the products obtained from
randomly selected
positive clones were purified by adding an equal
volume of
chloroform-isoamyl alcohol (24:1), followed by vortexing
and
centrifugation for 5 min at 10,000 ×
g. Radiolabeled
primer
cycle sequencing was carried out by using a Thermo Sequenase
cycle
sequencing kit (Amersham International plc., Slough, United
Kingdom)
and primer 537r (
7) according to the
manufacturer's instructions.
Reaction products were analyzed by
standard polyacrylamide gel
electrophoresis and
autoradiography.
Sequence analysis.
A total of 281 partial clone sequences
were compared with sequences in the Ribosomal Database Project (RDP)
database (18) by using the SEQUENCE_SIMILARITY function and
with sequences in the GenBank database by performing FastA searches
with Genetics Computer Group software (12) installed in the
Seqnet node of the BBSRC Daresbury Laboratory (Warrington, United
Kingdom). Sequences were also checked for chimeric properties by using
CHIMERA_CHECK of the RDP. On the basis of the results of database
searches, sequences were aligned with representative bacterial
sequences from the RDP and GenBank databases by using the Genetic Data
Environment running in ARB (37). Phylogenetic trees were
constructed by using the Jukes-Cantor model (15) and
neighbor joining (32) with PHYLIP, version 3.5 (9). Data sets were bootstrapped by using SEQBOOT (PHYLIP,
version 3.5). The levels of similarity of clones were assessed by using
the GAP algorithm of the Genetics Computer Group, the clones were
clustered into operational taxonomic units (OTUs) at a level of
sequence similarity of >97%, and a number of diversity indices were
calculated. These indices included (i) library coverage, the portion of
a clone library of infinite size that is sampled (13, 25);
(ii) species richness, the total number of OTUs (5); (iii)
the Shannon diversity index, a general diversity index which considers
both species richness and evenness (28); (iv) evenness,
which describes the distribution of abundance of clone types
(28); and (v) dominance, which describes the extent of
dominance by individual OTUs (28). For comparisons of
library coverage, the Shannon diversity index, dominance, and evenness,
libraries with sample sizes of more than 45 were artificially reduced
to a sample size of 45 by randomly removing clone sequences. For
species richness, normalization of library size to 45 was achieved by
rarefaction (5). Diversity indices for unimproved and
improved sites were also calculated by using the pooled data from
triplicate libraries whose combined data set sizes were reduced to 135 as described above. The maximum and minimum values for each index were
also determined. Similarity coefficients, which reflected the
proportions of shared OTUs, were calculated by performing pairwise
comparisons of libraries (28). Finally, collector's curves
or species abundance curves (28) (the number of species detected plotted versus the number of clones analyzed) were constructed to compare the diversities of major phylogenetic groups. Pooled data
for unimproved and improved grasslands used as the data sets obtained
from individual libraries were too small to allow meaningful comparisons.
Nucleotide sequence accession numbers.
The partial clone
sequences determined in this study have been deposited in the GenBank
database under accession no. AF078179 to AF078453.
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RESULTS |
Construction of rDNA libraries.
Bacterial diversity in
triplicate soil samples from rhizospheres from unimproved and improved
grassland pastures was analyzed by PCR amplification of total DNA
extracts with bacterial primers (6). Products from three
separate amplifications were pooled prior to cloning in order to
minimize PCR drift (39). For each of the six clone libraries
obtained, 45 to 48 clones were selected randomly for sequencing of
321 to 466 bases, including variable regions V2 and V3 at the 5'
end of the rRNA gene (26). In all, 281 partial
sequences were obtained; 6 of these were considered putative chimeras
on the basis of the results of a CHIMERA_CHECK analysis and were
omitted from further analyses.
Identification and distribution of clones.
Phylogenetic
analysis of the 275 clones studied and their closest relatives in the
RDP and GenBank databases and FastA and SEQUENCE_SIMILARITY
searches were used to assign each environmental clone to a major
bacterial group, when possible. Two individual clones and six
clone clusters comprising two to seven sequences were not related to
cultured or uncultured representatives of the sequence databases,
formed distinct phylogenetic branches, and were considered novel
groups. Several clone sequences were identical in the
region analyzed. These sequences included eight pairs of
duplicate clones and two sets of triplicate clones. While seven of
these sets, including one set of triplicate clones, contained clones from a single unimproved soil library, the remaining three groups comprised clones from both unimproved and improved soil libraries. In addition, we identified three clones whose
sequences were identical, as determined by FastA searches, in the
region sequenced to the sequences of culturable species in the
databases (namely, Agrobacterium tumefaciens,
Rhizobium loti, and Staphylococcus succinus).
Table
1 lists the broad phylogenetic
distribution of clones within each library and within all of the clones
analyzed, along
with average values for each grassland type. Many
clones belonged
to major previously characterized groups, including the

subdivision
of the class
Proteobacteria
(

-proteobacteria),

-proteobacteria,

-proteobacteria,
flavobacteria, and actinomycetes, and many belonged
to relatively
recently recognized groups, such as the
Acidobacterium,
Holophaga, and
Verrucomicrobium groups. Clones related to
Deinococcus radiodurans and the green sulfur
bacteria were also obtained.
Eight clusters of sequences, accounting
for 9.3% of all of the
clones, were not related to culturable
organisms in the databases
(level of sequence similarity, <81%).
These clusters were designated
unclassified Sourhope groups 1 to
8. A novel group which clustered
with the

- and

-proteobacteria was also observed, and as the
phylogeny of this
group is uncertain, it is referred to below
as the

-/

-proteobacteria.
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TABLE 1.
Relative abundance of clones from triplicate unimproved
and improved grassland soil samples and belonging to a number of
bacterial phylogenetic groups
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Sequences belonging to members of the

-proteobacteria were most
abundant, were recovered in all libraries, and comprised
43.5 and
34.2% (grassland means) of the unimproved and improved
soil clone
sequences, respectively. Actinomycete sequences were
the next most
abundant clone sequences recovered for both the
unimproved and
improved grassland types (mean values, 8.1 and
18.2%,
respectively) and for all of the improved soil replicate
samples (13.3 to 22.2%). Considerable variability in the triplicate
libraries is
evident in Table
1. For example, while actinomycete
sequences were the
second most abundant sequence type in library
SAF2 (accounting for
17.8% of the sequences), these sequences
accounted for only 2.1 and
4.4% of the sequences in the SAF1 and
SAF3 libraries, respectively.
Similarly, sequences of flavobacteria
accounted for 0, 4.4, and 17.8%
of the sequences in the replicate
libraries from the improved
grassland soils. Analysis of the relative
abundance of each group in
unimproved and improved soil replicates
by using the
Student
t test did not reveal any statistically
significant
differences between the means for the grasslands for
any phylogenetic
group (
P 
0.05). The greatest
apparent differences between the
grassland types were the differences
for Sourhope group 1 and
the

-/

-proteobacteria, which were more
prevalent in the unimproved
soils (
P = 0.091 and
P = 0.112, respectively). In addition, there
was
some suggestion that there were slight excesses of actinomycete
sequences (
P = 0.163) and sequences of members of the
Acidobacterium group (
P = 0.189) in
improved
soils.
Phylogenetic analysis.
A phylogenetic analysis was carried out
with sequence data for four groups (Fig.
1 through
4).
The first three groups, which formed distinct lineages on the bacterial
16S rRNA tree with strong bootstrap support, were the
-proteobacteria (100% support), the
- and
-proteobacteria
(100%), and the actinomycetes (97%). The fourth group contained all
of the other Sourhope clones and included clones belonging to the
flavobacteria, to the novel lineage containing A. capsulatum
and H. foetida, and to the eight unclassified groups. Alignments consisting of 327, 373, 379, and 276 bases were analyzed for
the
-proteobacteria, the
- and
-proteobacteria, the
actinomycetes, and all other clones, respectively. Bootstrap values
were obtained for the branch topologies with >50% support in
the bootstrap analysis of 100 replicates. Clones that exhibited
>97% sequence similarity were clustered on the trees (Fig. 1 through
4, solid boxes), unless high levels of similarity to other
sequences made this impossible.

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FIG. 1.
Neighbor-joining tree showing the relationship of
grassland rhizosphere clones to reference members of the
-proteobacteria based on analysis of 327 bases of aligned 16S
rDNA sequences. Clones exhibiting >97% sequence similarity are included in numbered clusters. The
horizontal scale represents the extent of variation within each
cluster, and brackets indicate clones belonging to the same group.
Bootstrap values are shown for nodes that had >50% support in a
bootstrap analysis of 100 replicates. Sequences obtained from
unimproved and improved grassland soils are designated by the prefixes
SAF and SL, respectively, followed by replicate numbers (SAF1, SAF2,
etc.). The clones obtained during other direct analyses of
environmental samples are MHP17 (21), MC74 (36),
MC77 (36), TM69 (30), and TM28 (30).
Sequences whose designations begin with the prefix S represent
bacterial isolates (23). For convenience, the tree was
pruned from a larger tree containing additional sequences from
reference bacteria. The scale bar indicates an estimated change of
10%.
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FIG. 2.
Neighbor-joining tree showing the relationship of
grassland rhizosphere clones to reference members of the - and
-proteobacteria based on analysis of 373 bases of aligned 16S
rDNA sequences. The sequence designated PVB_3 is a clone obtained
during another direct analysis of an environmental sample
(24). Sequences whose designations begin with the prefix S
represent bacterial isolates (23). For other sequence
nomenclature and branch labeling, see the legend to Fig. 1.
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FIG. 3.
Neighbor-joining tree showing the relationship of
grassland rhizosphere clones to reference actinomycetes based on
analysis of 379 bases of aligned 16S rDNA sequences. Sequences
whose designations begin with the prefix S represent bacterial isolates
(23). For other sequence nomenclature and branch labeling
see the legend to Fig. 1.
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FIG. 4.
Neighbor-joining tree showing the relationship of
grassland rhizosphere clones to reference bacteria based on analysis of
276 bases of aligned 16S rDNA sequences. The positions of all other
clones, which are associated with the -, -, and
-proteobacteria and the actinomycetes, are shown in Fig. 1 to 3. The
clones obtained during other direct analyses of environmental samples
are MC18 (17), all other sequences whose designations begin
with the prefix MC (36), and sequences whose designations
begin with the prefixes TM (30) DA (10), and SBR
(2). Sequences whose designations begin with the prefix S
represent bacterial isolates (23). For other sequence
nomenclature and branch labeling, see the legend to Fig. 1.
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In all, 34 clusters containing two or more sequences with >97%
sequence homology were observed (Fig.
1 through
4, arrows),
and these
clusters comprised 94 of the 275 clone sequences examined.
The
clusters generally comprised only two or three sequences,
although the largest group (cluster 1), which contained nine
clones
(Fig.
1), and three clusters containing five clones (clusters
11, 13, and 19) (Fig.
1 and
2) were also observed in the
proteobacterial
region. Approximately one-half of the clusters (19 of
the 34 clusters)
comprised sequences from either unimproved or improved
soil libraries,
although no cluster contained representatives of all
three replicate
samples. In addition, 13 of these clusters consisted of
sequences
from single libraries. The 15 remaining clusters contained
sequences
from both improved and unimproved grassland
libraries.
(i)
-Proteobacterial clones.
The
-proteobacterial clones
(Fig. 1) were the most abundant clones obtained, accounting for 109 (40%) of the 275 clones with 100% support in the bootstrap
analysis and representing 17 of the 34 clusters. Three of the four
largest clusters, which contained five and nine sequences, fell in this
group. In addition, 5 of the 10 groups of identical sequences,
including both sets of triplicate clones, were found in the
-proteobacteria. Many sequences were closely associated with
culturable organisms and clustered, with strong support in the
bootstrap analysis, with a range of common rhizosphere and soil
bacteria, including Sphingomonas spp., Rhizobium spp., and A. tumefaciens. In addition, the group of clones
containing saf3_012 and cluster 9 clones and clones which occurred
close to Rhizomonas suberafaciens on Fig. 1, including
cluster 12 clones, were related to cultures obtained from paddy
field soils (23). Cluster 1 contained a range of
physiologically distinct, cultured members of the
-proteobacteria, including Afipia felis,
Nitrobacter winogradskyi, and Bradyrhizobium
japonicum, which highlighted the difficulties in inferring the
physiology of these and most other clones obtained during this study.
Within the

-proteobacteria, several clones clustered with
clones obtained in other studies. For example, saf1_121,
saf1_314,
and saf1_307 clustered with environmental clone sequences
MC77
and MC74, which originally were isolated from an Australian acid
soil (
36). In addition, a group of four clones which shared
a lineage on this tree with the methane oxidizer
Methylosinus sporium was closely related to
environmental clone MHP17, exhibiting
94% bootstrap support. This
peat clone is believed to be a member
of a novel, acidophilic
group of methane oxidizers (
21). Other
Sourhope clones which
fell in the

-proteobacteria were related
to clones TM69 and TM28
recovered from peat (
30).
(ii)
- and
-proteobacteria.
Clones falling in the
-proteobacteria formed a cluster with 76% bootstrap support (Fig.
2). All of the other clones on this tree belonged either to the
-proteobacterial group or to clusters 19 to 21, which formed a
deeply branching group (84% bootstrap support) designated the
-/
-proteobacteria (Table 1). Although the presence of these
sequences in the
- or
-proteobacteria was strongly supported
(100% of bootstrap trees), the phylogeny of this group is unclear. An
analysis of the signature nucleotides of
- and
-proteobacterial
species (43, 44) was performed by using partial sequence
data when possible. Cluster 21 sequences had a signature nucleotide
thought to be unique to the majority of
-proteobacterial
sequences (44). No other
- or
-proteobacterial signature nucleotides were detected in any of these clones, but many of
the signature nucleotides were specific to the 3' region of the rRNA
gene, which was not analyzed in this study.
Most of the clones on the

- and

-proteobacterial tree were
not closely related to culturable organisms; the exceptions were
two clones which fell in the fluorescent
Pseudomonas
group of
the

-proteobacteria (cluster 22) and a clone closely
related
to
Stenotrophomonas maltophilia (formerly
Xanthomonas maltophilia).
A group of deeply branching clones
shared a lineage on this tree
with the ammonia oxidizer
Nitrosomonas europaea, although there
was not strong support
for this
relationship.
(iii) Actinomycete clones.
The actinomycete clone types
recovered were diverse, although five clusters contained two or three
clones (clusters 23 to 27) (Fig. 3). Most clones were not closely
related to cultured representatives of the actinomycetes; the
exceptions were five clones related to Arthrobacter
oxidans (cluster 26), Nocardioides sp. strain
NCFB3005 (cluster 25), and Agromyces cerinus (sl3_606). In addition, clone sl3_621 and cluster 26 were very closely
related (>99% related) to bacterial cultures obtained from paddy
field soil (23).
(iv) Other clones.
The majority of the clones which did not
cluster with the
-,
-, or
-proteobacteria or with the
actinomycetes were most closely related to environmental clones of
uncultivated bacteria obtained in other studies (2, 10, 17, 30,
36) and belonged to groups containing only one or a few
cultured representatives (Fig. 4). Many clones fell in the
Acidobacterium and Holophaga groups, which
are believed to belong to a novel lineage on the bacterial tree
(16, 22). Other clone groups (e.g., Sourhope groups 1 and 2)
appeared to belong to this lineage, although the relationships
between the clusters were unstable and the bootstrap values were
low. Similarly, many clones were recovered in other recently described
groups, such as the Verrucomicrobium group, which may share
ancestry with members of the genus Chlamydia and the family
Planctomycetaceae (17, 41), and the
Acidimicrobium and Rubrobacter groups, which have
been described as deeply branching actinomycetes (36).
Sourhope group 7 comprises four strongly supported lineages
(
98% support in bootstrap analysis), although the clustering
of these sequences as a single group was not strongly supported
by the bootstrap analysis. Sourhope groups 4 through 6 and 8 contained only clones isolated in this study, and the phylogenetic
position of these groups is unclear. The positions of clones which are
closely related to culturable isolates belonging to the low-G+C-content
gram-positive bacterial group and the
Cytophaga-Flavobacterium group are also shown in Fig.
4. In particular, clones saf3_107 and sl3_807 exhibited >99%
sequence similarity to the cultured species Staphylococcus
equorum and Bacillus globisporus (both members of the
low-G+C-content gram-positive group), respectively, and clones sl1_105
and saf2_118 exhibited >99% sequence similarity to the cultured
species Sphingobacterium heparinum and Sporocytophaga cauliformis (both members of the
Cytophaga-Flexibacterium-Bacteroides group), respectively.
Diversity indices.
Diversity indices were calculated by using
sequence data obtained from each library and from each grassland type.
Clones which showed >97% sequence similarity, as indicated in Fig. 1
to 4, were clustered into OTUs after normalization of sample sizes
in order to directly compare individual libraries and pooled data for each grassland type. Table 2 shows
the diversity indices obtained, along with the minimum and
maximum values possible when the number of clones was 45 (n = 135 for pooled data) (i.e., when all sequences were identical
and different, respectively). The coverage within each library
(13, 25) was low, ranging from 6.7 to 15.6%, and the
Shannon diversity index and species richness values were high for
all libraries. The evenness and dominance values approximated the
maximum possible values as most sequence types were recovered only once
and the majority of sequence clusters comprised only two clones.
Differences between the diversities of the unimproved and improved soil
libraries were not evident, although the coverage, Shannon diversity
index, and evenness values were more varied for the unimproved soil
samples than for the improved soil samples. In addition, although the
values for individual libraries were similar, when the pooled data for
each grassland type were considered, all indices except the dominance
index indicated that the diversity in unimproved soil samples was
slightly greater than the diversity in improved soil samples.
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TABLE 2.
Diversity indices obtained for rDNA libraries from
triplicate unimproved and improved grassland soil samples
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The similarity coefficients, calculated by performing pairwise
comparisons of libraries (Table
3), were
generally low, ranging
from 0 to 0.132. Interestingly, the libraries
which shared the
greatest number of OTUs were obtained from different
grassland
types (e.g., the similarity coefficient for the SAF1 and SL2
libraries
was 0.132, and the similarity coefficient for the SAF3 and
SL2
libraries was 0.125), although two improved libraries, SL1 and
SL2,
also had a relatively high similarity coefficient (0.123).
Several
libraries, including replicate libraries from the same
grassland (e.g.,
SAF1 and SAF2, as well as SL1 and SL2), contained
no common species. A
comparison of pooled data from each grassland
also resulted in a low
similarity coefficient, 0.132.
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TABLE 3.
Pairwise comparisons of species compositions of
rDNA libraries from triplicate unimproved and improved
grassland soil samples
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Collector's curves.
Collector's curves were constructed for
clones belonging to the most abundant phylogenetic groups obtained
during this study by plotting the number of OTUs (level of sequence
similarity, >97%) as a function of the number of sequences sampled.
Full coverage of a library would be expected to give a plateau-shaped
curve. The collector's curves derived from pooled data for each
grassland type for clones belonging to the
-proteobacteria (Fig.
5) diverged, indicating that the recovery
of diversity was greater in the unimproved soil libraries than in the
improved soil libraries. No single library was found to be responsible
for this result, and similar curves were obtained for individual
libraries or pairs of replicate libraries (data not shown). In
addition, although considerably more
-proteobacterial sequences were
obtained from unimproved soil libraries (60 clones) than from improved
soil libraries (30 clones), the library coverage was considerably lower
in the unimproved libraries. Collector's curves were also constructed
for actinomycete and Acidimicrobium-Microthrix clones, which
were the next most abundant groups in the total sequence data set, but
no differences were observed. No other phylogenetic groups were present
in sufficient amounts in unimproved and improved soil samples to allow
informative comparisons to be made.

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|
FIG. 5.
Collector's curves for -proteobacterial clones from
triplicate unimproved and improved soil libraries. Clones were grouped
into OTUs at a level of sequence similarity of >97%.
|
|
 |
DISCUSSION |
The aim of this study was to use 16S rDNA sequence analysis to
characterize the diversity and community structure of rhizobacteria associated with upland grass pastures, which provide the mainstay for
grazing in the United Kingdom, and to assess differences between unimproved and improved pastures. These pastures differed in grass species diversity and composition and in land management regimen, factors which may influence the genetic diversity of microbial communities. While several other rDNA or rRNA approaches are
available which may provide more rapid analysis (e.g., denaturing
gradient gel electrophoresis-temperature gradient gel electrophoresis
and amplified ribosomal restriction analysis), the great strength of
sequence analysis is the generation of additive and retrievable data
which can be used to generate phylogenetic probes and primers for use
in further studies.
The sequences amplified from extracted DNA represented a wide range of
bacterial phylogenetic groups, and sequences related to
mitochondrial or chloroplast rDNA were not detected. Phylogenetic analysis of the sequences provided no evidence that there were differences in diversity between unimproved and improved soils or
differences in the relative incidence of particular phylogenetic groups. In all of the libraries, the sequences of clones belonging to
the
-proteobacteria were the most abundant sequences (22 to 53%),
and these sequences occurred at levels similar to those found in an
acid forest soil (50%) (17), a peat sample (42%) (30), and soil from arctic tundra (21%) (45). In
contrast, in the studies of Borneman and Triplett (3) and
Kuske et al. (16),
-proteobacterial clones accounted
for only 4 and 3%, respectively, of the clones in libraries
obtained from Amazonian soils and pinyon-juniper woodland soils.
Actinomycete clones were abundant, particularly in the
improved soil libraries. Borneman and Triplett (3)
also found more high-G+C-content gram-positive sequences in soil
from an active pasture than in mature forest soil. However, a
comparison of the results of different studies was hindered by
variations both in the sample type (e.g., soil pH, location, land
use, and climate) and in the method used (e.g., DNA
extraction technique and PCR primers). Nevertheless, 16S
rDNA analyses clearly showed that terrestrial systems and
other natural environments have extremely diverse bacterial
populations. Considerable variation was also observed in replicate
samples from both the unimproved plots and the improved plots,
both in the relative distributions of different groups and in diversity
measurements, as might be expected from the low coverage of individual libraries.
Large proportions of sequences in environmental samples are only
distantly related to database sequences of cultured organisms, and many
of the major clusters of sequences obtained in this study have only
deeply branching cultured representatives. These clusters include
clones associated with the recently described prosthecate organism Verrucomicrobium spinosum,
Acidimicrobium ferroxidans, Rubrobacter
radiotolerans, and the acidophile A. capsulatum
(2, 10, 17, 30, 36). The depth of branching in these
clusters prevents inference by physiological characteristics of
the organisms from which the clones were derived. Although
representatives of these groups were first cloned from acid Australian
soils several years ago (17, 36), closely related
pure-culture representatives have not been obtained yet, and their
significance in natural environments remains unclear. Analysis of
ribosomes extracted from peat, however, has indicated that
bacteria related to clone DA079, which is affiliated with the
Acidimicrobium line of descent, are probably
physiologically active in the environment (11).
Duplicate sequences in soil libraries have rarely been recovered in
other rDNA-based studies (3, 27, 45), but we obtained several groups of identical sequences. Felske et al. (10)
proposed that the presence of duplicate sequences in libraries
derived from acid, peaty soil (10) and peat bog samples
(29) implied that the diversity was reduced due to
selection of particular microorganisms by low pH, which is a feature
of our soils, while Marilley et al. (19) observed
reduced 16S rDNA diversity in rhizosphere compared to bulk soil.
Identical 16S rDNA sequences from cultured organisms and
environmental clones are also rarely reported but three partial
sequences identical to sequences of cultured species were recovered
from Sourhope libraries. This allowed us to infer physiological
properties of the bacteria from which the clones were derived, although
closely related organisms often have very different physiologies
(33, 35).
This is the first study to apply diversity indices to 16S rDNA
sequence abundance data obtained from environmental samples. Marilley
et al. (19) analyzed soil microbial diversity by using restriction patterns of 25 16S rDNA clones and clustering of clones into OTUs at a level of sequence similarity of >96%. A value of >97% was used in our study as this value generally discriminates between bacterial species previously defined on the basis of DNA-DNA reassociation values (34). Great diversity was detected in
improved and unimproved rhizospheres, and the Shannon indices
approximated the maximum possible values. In contrast, Marilley et al.
(19) found that diversity was considerably reduced
in the rhizospheres of monocultures of L. perenne
and T. repens compared to the diversity in bulk soil. The
greater diversity of plant species may be responsible in part
for the greater bacterial diversity in the Sourhope plots.
Low library coverage may have been responsible for the great diversity
detected in the six rDNA libraries, and in order to obtain
collector's curves which reached a plateau, considerably more
sequence data would be required, a costly and time-consuming prospect.
Despite this, the underlying differences in evenness and
dominance, as determined by clustering OTUs at >95 and 90%, suggest
that the improved soil samples may have been slightly less diverse than
the unimproved soil samples (data not shown). Similarly, indices
calculated by using pooled data indicate that the diversity was
slightly greater in the unimproved soil libraries than in the improved
soil libraries, which may have reflected greater plant diversity at
unimproved sites or selection of bacterial communities by specific
plants, fertilizer addition, and grazing in the improved soil samples.
Biases associated with the use of molecular techniques may under- or
overestimate diversity (42). For example, inclusion of
chimeric or heteroduplex sequences and divergent sequences from single
bacteria which possess multiple rRNA copy numbers could result in
overestimation of diversity. In all, 6 of 281 sequences were discarded
as chimeras in this study. Conversely, underestimation of diversity may
have occurred through lysis bias, unequal binding of PCR primers to
different bacterial groups, or PCR selection. It must be noted,
however, that all samples were treated identically to ensure, as far as
possible, that any biases occurred to the same degree throughout the
analysis. In addition, steps were taken to reduce bias; these steps
included addition of low template DNA concentrations to PCR
amplification mixtures to minimize PCR selection and pooling of
multiple PCR products prior to cloning to minimize the effect of PCR
drift (39).
Although differences in total bacterial diversity between unimproved
and improved soil libraries were not observed, variation in the
community structure of some bacterial groups was apparent. In
particular,
-proteobacterial clones were more diverse in the unimproved soil samples than in the improved soil samples. Although there were probably multiple factors resulting in this difference, it
is interesting that many
-proteobacterial clones isolated in this
study are closely related to nitrogen-fixing bacteria, particularly
Bradyrhizobium and Rhizobium spp. The improved
Sourhope plots are dominated by L. perenne and the
leguminous plant species T. repens, while the unimproved
plots are dominated by nonleguminous species, such as A. capillaris, suggesting that selection for nitrogen-fixing bacteria
may have occurred in the former plots.
In summary, our 16S rDNA sequence analysis did not detect
significant differences in bacterial diversity in agriculturally important grassland soils which differed in constituent grass species, grazing intensity, and fertilizer application but did indicate that there were underlying differences in specific components of the populations which may have been related to differences in
community function.
 |
ACKNOWLEDGMENTS |
We thank Christopher Clegg (Scottish Crop Research Institute,
Invergowrie, United Kingdom) for providing DNA samples.
This work was carried out as part of the MICRONET project funded by the
Scottish Office Agriculture, Environment and Fisheries Department (SOAEFD).
 |
FOOTNOTES |
*
Corresponding author. Mailing address: Department of
Molecular and Cell Biology, Institute of Medical Sciences, University of Aberdeen, Foresterhill, Aberdeen AB25 2ZD, Scotland, United Kingdom.
Phone: 44 1224 273148. Fax: 44 1224 273144. E-mail:
j.prosser{at}abdn.ac.uk.
 |
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