Assessment of Microbial Diversity in Four Southwestern United States Soils by 16S rRNA Gene Terminal Restriction Fragment Analysis

Abstract

The ability of terminal restriction fragment (T-RFLP or TRF) profiles of 16S rRNA genes to provide useful information about the relative diversity of complex microbial communities was investigated by comparison with other methods. Four soil communities representing two pinyon rhizosphere and two between-tree (interspace) soil environments were compared by analysis of 16S rRNA gene clone libraries and culture collections (Dunbar et al., Appl. Environ. Microbiol. 65:1662-1669, 1998) and by analysis of 16S rDNA TRF profiles of community DNA. The TRF method was able to differentiate the four communities in a manner consistent with previous comparisons of the communities by analysis of 16S rDNA clone libraries. TRF profiles were not useful for calculating and comparing traditional community richness or evenness values among the four soil environments. Statistics calculated from RsaI, HhaI, HaeIII, and MspI profiles of each community were inconsistent, and the combined data were not significantly different between samples. The detection sensitivity of the method was tested. In standard PCRs, a seeded population comprising 0.1 to 1% of the total community could be detected. The combined results demonstrate that TRF analysis is an excellent method for rapidly comparing the relationships between bacterial communities in environmental samples. However, for highly complex communities, the method appears unable to provide classical measures of relative community diversity.

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APPLIED AND ENVIRONMENTAL MICROBIOLOGY,
0099-2240/00/$04.00⫹0
July 2000, p. 2943–2950 Vol. 66, No. 7
Assessment of Microbial Diversity in Four Southwestern United States
Soils by 16S rRNA Gene Terminal Restriction Fragment Analysis
JOHN DUNBAR,
1
LAWRENCE O. TICKNOR,
2
AND CHERYL R. KUSKE
1
*
Biosciences Division
1
and Technology and Safety Assessment Division,
2
Los Alamos National Laboratory, Los Alamos, New Mexico 87545
Received 21 December 1999/Accepted 8 May 2000
The ability of terminal restriction fragment (T-RFLP or TRF) profiles of 16S rRNA genes to provide useful
information about the relative diversity of complex microbial communities was investigated by comparison
with other methods. Four soil communities representing two pinyon rhizosphere and two between-tree (in-
terspace) soil environments were compared by analysis of 16S rRNA gene clone libraries and culture collec-
tions (Dunbar et al., Appl. Environ. Microbiol. 65:1662–1669, 1998) and by analysis of 16S rDNA TRF profiles
of community DNA. The TRF method was able to differentiate the four communities in a manner consistent
with previous comparisons of the communities by analysis of 16S rDNA clone libraries. TRF profiles were not
useful for calculating and comparing traditional community richness or evenness values among the four soil
environments. Statistics calculated from RsaI, HhaI, HaeIII, and MspI profiles of each community were
inconsistent, and the combined data were not significantly different between samples. The detection sensitivity
of the method was tested. In standard PCRs, a seeded population comprising 0.1 to 1% of the total community
could be detected. The combined results demonstrate that TRF analysis is an excellent method for rapidly com-
paring the relationships between bacterial communities in environmental samples. However, for highly com-
plex communities, the method appears unable to provide classical measures of relative community diversity.
Rapid analysis of diversity in complex microbial communi-
ties has remained an elusive but important goal in microbial
ecology. Community diversity can be examined at several lev-
els. The most simple analyses use DNA profiles (generated by
PCR and sometimes followed by restriction digestion of am-
plification mixtures) to identify differences in the composition
of communities. More refined approaches describe differences
not only in community composition but also in community
organization by measuring the number (richness) and relative
abundance (structure or evenness) of species or phylotypes.
The richness and evenness of biological communities reflect
selective pressures that shape diversity within communities.
Measuring these parameters is most useful when assessing
treatment effects (e.g., physical disturbance, pollution, nutrient
addition, predation, climate change, etc.) on community diver-
sity. Diversity statistics can also indicate the ability of a com-
munity to recover from disturbance and utilize resources effi-
ciently (4). An ideal method for analysis of diversity in complex
microbial communities would enable the simultaneous mea-
surement of composition, phylotype richness, and community
structure. The method would be rapid and reproducible and
would permit flexible sampling of the entire microbial commu-
nity.
Direct amplification of bacterial 16S rRNA genes from ex-
tracted soil DNA provides the most comprehensive and flexi-
ble means of sampling bacterial communities. Analysis of clone
libraries of 16S rRNA genes amplified from different environ-
ments can provide relative measures of diversity that are, in
general, consistent with qualitative relationships determined
from traditional culture collections (9). However, analysis of
individual 16S rRNA gene clones in multiple libraries is an
expensive and extremely inefficient approach for comparison
of numerous bacterial communities in replicated field experi-
ments. Other methods, such as thermal or denaturing gradient
gel electrophoresis (DGGE) (12, 14, 16, 21, 23, 28), heterodu-
plex analysis (8, 11), or terminal restriction fragment (T-RFLP
or TRF) analysis (3, 6, 18, 20), assess the diversity of 16S rRNA
gene mixtures more crudely than cloning and sequencing but
are far more rapid and therefore more amenable to field-scale
experiments in which replication is important. DGGE and the
TRF method were recently shown to identify similar relation-
ships among marine communities (20). DGGE has also been
shown to provide estimates of cyanobacterial richness consis-
tent with estimates based on direct observation of cell mor-
phological types in cyanobacterial mat communities (22).
Although cyanobacteria comprise a small phylogenetic group,
these findings support the idea that rapid fingerprinting tech-
niques might be capable of assessing the richness and evenness
of microbial communities in general.
We calibrated the TRF method by comparing the composi-
tion, relative species richness, and evenness of four soil micro-
bial communities that had been analyzed previously by culti-
vation and by 16S rDNA cloning (9). The four soils were from
pinyon rhizosphere and between-tree (interspace) environ-
ments at two sites 19 km apart in northern Arizona (17). Both
sites are pinyon-juniper woodlands but differ dramatically in
soil type (7, 17). Here we show that the TRF method success-
fully demonstrated relationships between the four samples
consistent with previous comparisons of 801 16S rRNA gene
clones from the samples. However, calculations from TRF
profiles provided variable values for comparison of phylotype
richness and community evenness and depended on the restric-
tion enzyme used to derive the profile. The data demonstrate
both the strengths and limitations of the TRF method for
analysis of natural communities that are highly complex.
MATERIALS AND METHODS
Field sites and soil samples. Soil samples were collected from a site in the
Coconino National Forest near the town of Cosnino and another site 19 km due
* Corresponding author. Mailing address: Environmental Molecular
Biology Group, M888, Biosciences Division, Los Alamos National
Laboratory, Los Alamos, NM 87545. Phone: (505) 665-4800. Fax:
(505) 665-6894. E-mail: kuske@lanl.gov.
2943

north at Sunset Crater National Monument (17). The sites differ dramatically in
soil type, but have similar dominant plant communities (pinyon-juniper wood-
lands), elevation, and general weather patterns (7, 13, 17). At Cosnino, the soil
is a light sandy loam (13), and the areas between widely spaced trees (inter-
spaces) are sparsely covered with grass and forb species. In contrast, Sunset
Crater soil consists largely of black, coarse-textured, well-drained cinders, and
the interspace regions between trees are typically barren (7). Composite soil
samples were collected from interspace areas unassociated with plant roots (C0
and S0 samples) and the rhizospheres of pinyon trees (Pinus edulis Englm.) that
were matched for age (C1 and S1 samples) at Cosnino and Sunset Crater,
respectively, as previously described (17).
16S rDNA clone libraries. A 200-member 16S rDNA clone library was con-
structed for each of the four Arizona soil samples as previously described (17).
Briefly, DNA was extracted using a four-step procedure including three cycles of
freezing-thawing, a 70°C heat incubation with sodium dodecyl sulfate, bead mill
homogenization, and ethanol precipitation. The concentration of PCR-inhibiting
materials was found to be too high in the precipitated DNA. Therefore, the DNA
was cleaned further by phenol-chloroform extraction, passage through Sephadex
G-200 spin columns, and then precipitated again with ethanol. The resulting
high-molecular-weight DNA was stored at ⫺20°C and was used as a template in
PCR with 16S rRNA gene primers 8-27f (pA; 5⬘-AGAGTTTGATCCTGGCTC
AG) (10) and 1507-1492r (5⬘-TACCTTGTTACGACTT) (29). For each soil
DNA, 16S rDNA amplicons from 10 independent PCRs were pooled, ligated
into the pGEM-T plasmid vector (Promega, Madison, Wis.), and transformed
into Escherichia coli DH10␤Electromax cells (Gibco BRL, Gaithersburg, Md.).
For each soil, at least 200 clones containing inserts of the correct size (approx-
imately 1,500 bp) were stored in 20% glycerol at ⫺70°C.
TRF analysis of C0 and S0 16S rDNA clones. Cloned 16S rDNA sequences
from the C0 and S0 clone libraries (representing the interspace areas at Cosnino
and Sunset Crater, respectively) were amplified using the primers M13-20 (5⬘-
GTAAAACGACGGCCAGT) and M13-24 (5⬘-AACAGCTATGACCATG).
Each 25-␮l reaction mixture contained 30 mM Tris (pH 8.4), 50 mM KCl, 1.5
mM MgCl
2
(24), 50 ␮M concentrations of each deoxynucleoside triphosphate, 25
pmol of each primer, and 0.75 U of Taq polymerase (AmpliTaq; Perkin-Elmer,
Foster City, Calif.). Frozen cells (1 ␮l) from 20% glycerol stocks were added as
template in each PCR. PCRs were performed in a Perkin-Elmer 9600 thermal
cycler with the following cycling conditions: 2 min of denaturation at 94°C, 25
cycles of 30 s at 50°C, 1 min at 72°C, 10 s at 94°C, and a final cycle of annealing
at 55°C for 1 min and extension at 72°C for 5 min. One microliter of each
reaction mixture was used as template in a second PCR containing forward
primer 8-27f fluorescently labeled with TET (4,7,2⬘,7⬘-tetrachloro-6-carboxyfluo-
rescein; ABI, Perkin-Elmer) and reverse primer 1507-1492r. Reaction conditions
were the same as those described above except that only 10 cycles of PCR were
used instead of 25. Fluorescent amplification products were ethanol precipitated
and resuspended in 25 ␮l of sterile, distilled water, and 8 ␮l was digested with 5
UofRsaI (New England Biolabs, Beverly, Mass.) in 12-␮l reaction mixtures.
Following restriction digestion, 1 ␮l of each digest was dried, suspended in 1.75
␮l of loading buffer containing 0.25 ␮l of Genescan 2500 TAMRA size standard
(ABI), a 5:1 mixture of deionized formamide-blue dextran, and 25 mM EDTA,
and then denatured at 94°C for 2 min. Fragments were separated by electro-
phoresis in denaturing 4% polyacrylamide gels with an ABI 377 DNA sequencer.
Reagents for polyacrylamide gel electrophoresis were purchased from Bio-Rad
(Hercules, Calif.). TRF sizes were determined using Genescan version 2.02
analytical software (ABI).
TRF profiles for C0, C1, S0, and S1 soil DNA samples. The four soil DNA
templates used for TRF analysis were the same DNA preparations from which
16S rDNA was amplified in 1994 for construction of clone libraries (17). These
DNA preparations were stored frozen between construction of the clone librar-
ies and the TRF analyses (approximately 4 years). 16S rDNA for TRF analysis
was amplified with primer 8-27f fluorescently labeled with TET and with primer
1507-1492r. Each 50-␮l reaction mixture contained 30 mM Tris (pH 8.4), 50 mM
KCl, 1.5 mM MgCl
2
(24), 50 ␮M concentrations of each deoxynucleoside tri-
phosphate, 50 pmol of each primer, and 0.75 U of LD Taq polymerase (Ampli-
Taq; Perkin-Elmer). Cycling conditions were as follows: 2 min of denaturation at
94°C, 35 cycles of 30 s at 50°C, 1 min at 72°C, 10 s at 94°C, and a final cycle of
annealing at 55°C for 1 min and extension at 72°C for 5 min. Three independent
PCRs were performed for each sample and combined. PCR products were
separated by electrophoresis in 1% Nusieve agarose (FMC, Rockland, Maine),
and the DNA band approximately 1,500 bp in size was excised and purified as
had been done previously for the construction of clone libraries (17).
16S rDNA from the four soil DNA samples was also amplified with a FAM
(5-carboxyfluorescein; ABI)-labeled forward primer (YOGA31F, 5⬘-GATCCT
GGCTCAGAATC, E. coli positions 15 to 31) that is specific for members of the
Acidobacterium division (2) and with reverse primer 1507-1492r. Amplification
conditions were the same as above except that a 42°C annealing temperature was
used. Three independent PCRs were performed for each sample, and PCR
products were combined and purified with a Qiaquick PCR cleanup kit (Qiagen,
Inc., Chatsworth, Calif.). Purified amplicons were digested with the enzymes
HaeIII, HhaI, RsaI, and MspI, and fragments were separated by electrophoresis
in polyacrylamide gels as described above. For each sample, two or three aliquots
of each digest were applied to separate gels to obtain replicate profiles.
Analysis of TRF profiles. TRF profiles were analyzed as follows, using S-PLUS
version 3.2 (MathSoft, Inc., Seattle, Wash.). First, replicate profiles of each sam-
ple were compared to identify the subset of reproducible fragment sizes (i.e.,
peaks that appeared in every replicate profile of a sample). The average height
of each reproducible peak of a sample was calculated, and the set of reproducible
peaks with newly calculated average heights was assigned as the average profile
of the sample for use in all subsequent analyses. Second, the DNA quantity an-
alyzed for each of the four samples was compared and standardized to the lowest
quantity. To standardize the DNA quantities, the sum of peak heights in each
average profile of a sample was calculated as a representation of the total DNA
quantity. The sum-of-peak-height values were standardized between samples by
proportionally decreasing the height of each peak in the average profiles until the
sum of peak heights (total fluorescence) for each profile equaled the lowest value
represented among the samples. This procedure was performed to allow com-
parisons between samples of equal size (equal amounts of DNA). Adjustment of
larger sample sizes usually resulted in the elimination of one or more peaks from
a profile as some adjusted peak heights dropped below the noise threshold
(height, 25).
Community composition comparison. For comparison of community similarity
between the four different soil environments, peak heights from TRF profiles
were converted to binary data (presence or absence of a peak). Profiles gener-
ated from different enzymes were combined in a tandem array, and a Jaccard
similarity matrix was calculated for the set of samples.
Calculation of traditional diversity indices. To evaluate richness and evenness,
diversity statistics were calculated from each standardized, average enzyme pro-
file of a sample by using the number and height of peaks in each average profile
as representations of the number and relative abundance of different phylotypes
in a sample. It is understood that any given TRF fragment may represent
sequences from multiple phylogenetic groups and may therefore not represent a
true phylotype in the traditional sense. We use the term phylotype to indicate
groups for richness calculations and also for the sake of consistency during
comparisons of the TRF method with restriction fragment length polymorphism
(RFLP) analysis of 16S rRNA gene clones. Phylotype richness (S) was calculated
as the total number of distinct TRF sizes (between 94 and 827 bp) in a profile.
The Shannon-Weiner diversity index (19) was calculated as follows: H ⫽⫺⌺(p
i
)
(log
2
p
i
), where pis the proportion of an individual peak height relative to the
sum of all peak heights. Simpson’s index of diversity (27) was calculated as
follows: D ⫽1⫺⌺(p
i
)
2
. The scale for D ranges from 1 to D
max
, where D
max
⫽
1⫺1/(S). Evenness (19) was calculated from the Shannon-Weiner diversity
function: E⫽H/H
max
, where H
max
⫽log
2
(S).
Detection sensitivity. Detection assays were performed by amplification and
TRF analysis of 16S rRNA genes from a soil DNA sample that had been mixed
with different concentrations of a cloned 16S rRNA gene prior to PCR ampli-
fication. The soil DNA was extracted from a Cosnino interspace soil sample
collected in 1998. The cloned 16S gene was selected from the S0 16S rRNA gene
clone library (17) based on its unique RsaI TRF size which was not observed in
previous TRF profiles of Cosnino interspace soil DNA samples. Plasmid DNA
containing the cloned 16S rRNA gene was extracted by alkaline lysis (25). PCRs
were performed with primers 8-27f (labeled with FAM) and 1507-1492r as
described above, with 1 ng of Cosnino interspace soil DNA template and plasmid
DNA dilutions ranging from 1 to 0.001 pg. Amplification products were purified
using a Qiaquick PCR Purification Kit (Qiagen), gel quantified, digested with
RsaI, and subjected to TRF analysis as described above.
RESULTS AND DISCUSSION
TRF analysis is increasingly popular as a fingerprinting
method for analysis of microbial communities, although the
abilities of the method are still being explored. We examined
the capabilities of the TRF method by calibrating the method
with data from a previous RFLP analysis of 801 16S rDNA
clones from four soil communities.
Community composition. Figure 1 illustrates the typical ex-
tent of differences we observed in TRF profiles of the C0, C1,
S0, and S1 DNA. Profiles from the C0, C1, and S1 samples
were visually quite similar regardless of the enzyme used for
restriction digestion of amplified 16S rDNA. In contrast, the
profiles from the S0 environment were noticeably different.
The striking differences (or similarities) in the height of peaks
in profiles from different environments have not yet been in-
corporated into our comparison of the composition of samples.
Although we are developing analytical procedures that will
include peak height information, at present only the presence
or absence of TRFs in community profiles is used to compare
community composition.
The similarity of the four environments (C0, C1, S0, and S1),
2944 DUNBAR ET AL. APPL.ENVIRON.MICROBIOL.

based on a distance matrix analysis of community TRF profiles,
is illustrated in Fig. 2. The analysis indicated that the sandy
loam rhizosphere (C1) and interspace (C0) soil communities at
Cosnino were the most similar in composition, whereas the
cinders interspace (S0) community was the most different.
These results were consistent with expectations based on the
physical conditions of the four environments. The soil condi-
tions (texture, moisture, and nutrient capacity) in the two
sandy loam environments at Cosnino are very similar but differ
substantially from the conditions in the cinders soil environ-
ments at Sunset Crater (7). The cinders interspace (S0) envi-
ronment is primarily gravel in texture and is very hot, dry, and
nutrient-poor (7), and the bacterial community in the extreme
S0 environment was expected to be the most divergent. On the
cinder field, nutrient levels are higher in the pinyon rhizo-
spheres than in the interspaces. The cinders rhizosphere (S1)
FIG. 1. RsaI TRF profiles of 16S rDNA amplified directly from S0, S1, C0, and C1 soil DNA samples.
VOL. 66, 2000 TRF ANALYSIS OF SOIL BACTERIAL COMMUNITIES 2945

environment exhibits conditions intermediate between the
Cosnino sandy loam soil and the cinders interspace (S0) envi-
ronment. The pinyon pine roots in the cinders probably mod-
ulate but do not entirely eliminate the effects of the cinders soil
type.
The TRF dendrograms in Fig. 2 illustrate the same relation-
ship between the four bacterial communities that had previ-
ously been identified by comparison of the four communities
by using RsaI plus BstUI RFLP patterns of approximately 200
individual 16S rDNA clones from each environment (9). RFLP
analysis (or sequence analysis) of clones from 16S rDNA clone
libraries provides the most detailed, reliable information about
the composition of microbial communities but is the most
time-consuming and expensive method of community analysis.
The finding that rapid comparison of microbial community
similarity by TRF analysis provides results consistent with the
much slower procedure of comparing clone libraries validates
use of the TRF method. Moeseneder et al. (20) demonstrated
that the TRF method and DGGE provided consistent results
in differentiating marine communities. The combined data
demonstrate that TRF profiles can be used to effectively in-
vestigate natural communities in field-scale experiments and
that the TRF method is interchangeable with other molecular
techniques.
A second TRF analysis of the four soil environments was
performed to compare the composition of the Acidobacterium
division in each environment. For the TRF analysis of total
bacteria (using primer set 8-27f and 1507-1492r), the soil DNA
templates, PCR conditions, and amplicon purification proce-
dures were the same as those used to create the 16S rDNA
clone libraries. TRF analysis performed using a primer set
specific for members of the Acidobacterium division (2) was
conducted using somewhat different PCR amplification and
amplicon purification procedures. Nonetheless, the Acidobac-
terium TRF results demonstrated the same relationships be-
tween the four environments as the TRF analysis for total
bacteria, indicating that the C0 and C1 environments were the
most similar and the S0 environment was the most distinct
(Fig. 2). The topology of the Acidobacterium TRF dendrogram
was also consistent with the topology of a dendrogram based
on comparison of RFLP patterns of Acidobacterium division
clones from the four 16S rDNA clone libraries (division-level
affiliation of the clones was determined by sequence analysis)
(9, 17; J. Dunbar, S. M. Barns, J. Davis, G. Fisher, and C. R.
Kuske, unpublished data). The agreement between results
from RFLP analysis of 16S rDNA clone libraries and two
different TRF analyses of the original soil DNA templates
indicates that the TRF method is robust in identifying rela-
tionships (based on composition) among natural communities.
This illustrates the capacity of the TRF method to explore
differences in community composition between environments
without the need to separately examine individual members of
the community (by 16S rDNA gene cloning).
Method resolution. Although the overall relationships be-
tween the four soil environments were consistent between the
TRF analysis and the combined results from RFLP analysis of
individual 16S rDNA clones, the resolution (i.e., the extent of
discrimination between the four communities) differed be-
tween the two methods. The degree of similarity among the
four soil environments (C0, C1, S0, and S1) was higher accord-
ing to TRF profiles than according to RFLP data from the 16S
rDNA clone libraries. The similarity values from TRF analysis
ranged from 15 to 21% (Fig. 2). In contrast, the communities
appeared to be only 7 to 12% similar based on RsaI plus BstUI
RFLP data from clone libraries (9).
To better evaluate the resolution provided by the TRF
method, we determined the ability of the method to measure
diversity in the C0 and S0 16S rDNA clone libraries (Table 1;
Fig. 3). The 16S rDNA clone libraries are a subset of the total
bacterial diversity in the C0 and S0 soil environments. The
clone libraries have a known number of members and can be
considered two defined communities since the diversity of
these two communities was characterized previously by RFLP
analysis of each individual clone (9). A total of 154 and 134
RsaI plus BstUI RFLP patterns (i.e., patterns from RsaI digests
that were further differentiated by comparison of patterns from
separate BstUI digests) were previously identified in the C0
and S0 clone libraries, respectively (9). Only a fraction of this
diversity was detected by obtaining an RsaI TRF profile for
each of the clones in the C0 or S0 libraries. A total of 73 and
75 distinct RsaI TRF sizes were observed, respectively, from
190 C0 clones and 182 S0 clones (Table 1; Fig. 3). The lower
resolution of the TRF method does not appear to result from
examining only the length variation of one restriction fragment
(the 5⬘TRF) instead of all the restriction fragments that are
produced by digestion of the 16S rDNA (as in a standard
RFLP). As shown in Fig. 3, for example, the number of RsaI
TRFs and RsaI RFLP patterns observed among the clones was
similarly low. Only 66 distinct RsaI RFLP patterns were iden-
tified for each set of clones. The number of RsaI TRFs was
slightly larger (73 and 75) than the number of RsaI RFLP
patterns (66 and 66) due to the higher resolution (⫾0.5 bp) of
the TRF method in fragment size determination compared to
the conventional agarose gel RFLP method. Based on these
data, the lower resolution of the TRF method when compared
to sequentially digested (RsaI plus BstUI) individual clones
FIG. 2. Dendrograms based on Jaccard similarity comparisons of the C0, C1,
S0, and S1 soil communities. (A) Dendrograms based on all RsaI plus BstUI
RFLP data from 16S rDNA clone libraries or only RsaI plus BstUI RFLP
patterns representing members of the Acidobacterium division. (B) Dendrograms
based on TRF profiles of 16S rDNAs amplified from soil DNA with conserved
bacterial primers 8-27f and 1507-1492r or with specific Acidobacterium division
primers YOGA31f and 1507-1492r.
2946 DUNBAR ET AL. APPL.ENVIRON.MICROBIOL.

appears to result from measuring the diversity of 16S rRNA
gene sequences with only a single enzyme.
Use of multiple enzymes for either RFLP or TRF analysis of
individual clones in a 16S rDNA library increases the resolu-
tion by increasing the number of different fragments observed
and simultaneously decreasing the number of recorded simi-
larities. In contrast, use of multiple enzymes will typically not
provide substantial increases in resolution for community TRF
analysis of a mixture of 16S rDNAs amplified from a soil DNA
template. This is not a limitation of the TRF method, per se,
but is instead a limitation of analyzing mixed 16S rDNA se-
quences. For mixed 16S rDNAs amplified from two environ-
mental samples, data from an additional enzyme digest may
increase the differences observed between the two samples, but
the total number of similarities will also increase. Thus, the
resolution measured as the percent difference that can be de-
tected between the two samples may not change substantially
by use of multiple enzyme digests. The value of using multiple
enzymes for TRF analysis is to increase confidence that the
similarity relationships identified between samples are not the
result of biases in the way that a single enzyme samples diver-
sity.
Phylotype richness. The phylogenetic resolution of different
TRFs observed in TRF profiles of microbial communities is
expected to vary. Whereas one TRF size in a profile may be
derived uniquely from a small, phylogenetically coherent group
of bacteria (i.e., a true phylotype; for example, see reference
5), another TRF size may represent a broader, more distantly
related set of organisms. The lack of phylogenetic resolution in
the latter category of TRFs will contribute noise when TRF
profiles are used to measure the relative phylotype richness of
different communities. We sought to determine whether useful
measures of relative phylotype richness could be obtained from
TRF profiles despite the noise contributed by TRFs of low
phylogenetic resolution. The ability of TRF profiles to docu-
ment relative phylotype richness in the four soil bacterial com-
munities was evaluated in two ways.
First, phylotype richness values from RFLP analysis of
clones in the C0 and S0 16S rDNA libraries were compared
with the number of distinct RsaI TRFs observed among the
same clones or observed in profiles from the C0 and S0 soil
DNA samples (Table 1). RsaI plus BstUI RFLP analysis of
clones more accurately distinguishes phylotypes. Therefore, we
expected richness values calculated from TRF profiles to be
FIG. 3. Sampling curves showing diversity of the C0 and S0 clone libraries assessed by RsaI plus BstUI RFLP patterns, RsaI RFLP patterns, and RsaI TRFs. Curves
were constructed by rarefaction (15, 26). Curves marked with asterisks were reprinted from reference 9 with permission from the publisher.
TABLE 1. Comparison of phylotype richness, diversity and evenness values for the C0 (sandy loam interspace) and
S0 (cinder interspace) bacterial communities, derived from three different methods
Parameter
16S rDNA clone libraries Community TRF
C0 clone,
RsaI⫹BstUI RFLPs
S0 clone,
RsaI⫹BstUI RFLPs
C0 clone,
RsaI TRF
S0 clone,
RsaI TRF
C0 soil DNA,
RsaI TRF
S0 soil DNA,
RsaI TRF
S
a
154 134 73 75 20 (15)
b
20 (14)
H
c
7.067 6.612 5.586 5.436 3.709 3.765
H/H
max
d
0.972 0.936 0.903 0.873 0.858 0.871
a
Phylotype richness, S, was calculated as the total number of distinct TRF sizes (peaks between 94 and 827 bp) in a profile.
b
Number in parentheses indicates the number of TRF sizes in the profile from soil DNA that were also observed among 16S rDNA clones obtained from the same
soil DNA 4 years previously. The discrepancy between the number of RsaI TRFs observed among the clones (73 and 75 TRFs) and the number observed in the profiles
from soil DNA (20 TRFs in each) may have been the result of degradation of the soil DNA template during storage for 4 years.
c
Shannon-Weiner diversity index (19) was calculated as follows: H ⫽⫺⌺(p
i
)(log
2
p
i
), where pis the proportion of an individual peak height relative to the sum of
all peak heights.
d
Evenness (19) was calculated from the Shannon-Weiner diversity function as follows: E⫽H/H
max
, where H
max
⫽log
2
(S).
VOL. 66, 2000 TRF ANALYSIS OF SOIL BACTERIAL COMMUNITIES 2947

lower for the S0 community when compared to the C0 com-
munity since previous RFLP analysis of 16S rDNA clone li-
braries had indicated this relationship. However, this relation-
ship was not apparent from the number of distinct RsaI TRFs
obtained from individual C0 and S0 16S rDNA clones or from
the number of TRFs in RsaI profiles generated directly from
C0 and S0 soil DNA (Table 1). In both cases, an identical or
nearly identical number of RsaI TRFs were obtained for the
C0 and S0 communities.
Second, trends among the richness values derived from TRF
profiles of all four soil DNA samples (Table 2) were evaluated.
Once again, we expected the S0 environment to have the low-
est richness value based on previous comparisons of the four
communities (9) and the community similarity analysis (pres-
ent study; Fig. 1). However, richness values from the TRF
profiles of community DNA failed to reveal substantial or
consistent differences in richness between the S0 community
and the other communities (Table 2). In fact, the estimates of
community richness we obtained from TRF profiles of the four
soil communities lacked any consistent trends. For example,
among the MspI profiles, the S1 sample had the highest rich-
ness value (S⫽34) while the S0 sample had the lowest value
(S⫽24). In contrast, the S1 sample had the lowest value (S⫽
14) among HaeIII profiles while the S0 sample had a higher
richness value (S⫽18). Although the average Svalues dem-
onstrated a pattern consistent with data from clone library RsaI
plus BstUI RFLP data, they were not statistically different from
one another due to the large variance that arose from averag-
ing results of multiple enzymes that measure sequence diver-
sity to different extents.
Use of TRF profiles to provide relative measures of phylo-
type richness for comparison of bacterial communities was
originally projected as a capability of the method (18). The
TRF method has previously been shown to be capable of
assessing phylotype richness in simple, artificial communities
containing only four or six members (1, 18, 20). It is possible
that use of TRF profiles to measure relative phylotype richness
is only possible for simple communities. The same variability
and inconsistency that we observed in richness values for our
soil samples are apparent in richness values reported for 20
marine samples (20). Based on these findings, the TRF method
appears ineffective in comparing the relative richness of ex-
tremely complex communities.
Community complexity can be artificially reduced by use of
group-specific PCR primers instead of universal primers. For
example, Nu¨bel et al. (22) used PCR primers specific for mem-
bers of the cyanobacteria division to amplify 16S rDNA se-
quences from eight cyanobacterial mat communities. DGGE
analysis of cyanobacterial and plastid 16S rDNA sequences
successfully provided estimates of phylotype richness congru-
ent with estimates based on the diversity of cell morphologies
observed in each sample. In the same manner, we decreased
the complexity of the C0, C1, S0, and S1 environments by using
specific primers to amplify 16S rRNA genes from members of
the Acidobacterium division only. However, diversity indices
calculated from Acidobacterium TRF profiles were as variable
as the values from bacterial TRF profiles created with the
primers 8-27f and 1507-1492r (data not shown). It is possible
that the Acidobacterium division is still too complex a subcom-
munity. Unlike the cyanobacteria division, this division is phy-
logenetically very broad (17), and Acidobacterium division se-
quences accounted for approximately 40% of the RsaI plus
BstUI RFLP patterns identified in the C0, C1, S0, and S1 clone
libraries. For broad divisions, primer sets that are specific for
smaller subgroups may be required to effectively detect differ-
ences in the richness and structure of complex communities.
Alternatively, use of the method for comparing richness in
communities should be confined to the most simple natural
communities or to experimental communities for which the
initial species composition is known.
Community evenness. In parallel with the above compari-
sons of richness, we evaluated community evenness values de-
rived from TRF profiles of C0 and S0 16S rDNA clones and
from profiles of all four soil DNA samples (Table 1). The
Shannon-Weiner diversity index (H; Table 1) and Simpson’s
diversity index (D; data not shown), both of which emphasize
phylotype richness but also measure structure, indicated that
the S0 clone library was less diverse than the C0 clone library
when calculated from TRF data from 372 individual clones.
The evenness index (H/H
max
) of TRFs from the C0 and S0
clone libraries indicated that the frequency distribution in the
S0 library was more skewed than that in the C0 library (0.873
versus 0.903). Although the numerical differences were small,
they were consistent with our previous comparison of evenness
calculated from RsaI plus BstUI RFLP data from the two clone
libraries (9). In contrast, evenness statistics calculated from the
TRF profiles of C0 and S0 total community DNA indicated the
opposite trend, suggesting that the S0 environment was more
diverse and less skewed than the C0 environment. Additional
contradictions and inconsistencies were apparent among even-
ness values from TRF profiles of all four (C0, C1, S0, and S1)
community DNA samples. The combined results suggest that
diversity indices calculated from community TRF profiles of
highly complex communities may not be adequate to accu-
rately measure relative community structure.
The inability of TRF profiles to provide reliable measures of
phylotype richness and community structure is not completely
surprising. The lower resolution of the TRF method (i.e., the
substantial probability of multiple phylotypes being repre-
sented by a single fragment size in a TRF profile) would tend
to obscure differences in phylotype richness and evenness that
might be detected by other methods with higher phylogenetic
resolution. Use of TRF profiles to measure richness and com-
munity structure is also hampered by inherent variation in the
extent to which different restriction enzymes reveal sequence
variation. Each enzyme used to create a TRF profile repre-
sents a fundamentally different sampling technique. Thus, TRF
TABLE 2. Diversity statistics calculated from TRF profiles of
16S rDNAs amplified from C0, C1, S0, and S1 soil DNA
Enzyme Index Diversity statistics
a
C0 C1 S0 S1
HaeIII S
b
21 19 18 14
d
HhaIS14 13 12 11
MspIS33 27 24 34
RsaIS20 22 20 20
Avg S22 20 19 20
HaeIII H
c
4.13 3.92 3.74 3.49
HhaIH3.68 3.52 3.51 3.32
MspIH4.78 4.48 4.19 4.72
RsaIH3.71 3.74 3.77 3.72
Avg H4.07 3.91 3.80 3.81
a
C0, Cosnino interspace; C1, Cosnino rhizosphere; S0, Sunset Crater inter-
space; S1, Sunset Crater rhizosphere.
b
Phylotype richness, S, was calculated as the total number of distinct TRF
sizes (between 94 and 827 bp) in a profile.
c
Shannon-Weiner diversity index (19) was calculated as follows: H ⫽⫺⌺(p
i
)
(log
2
p
i
), where pis the proportion of an individual peak height relative to the
sum of all peak heights.
d
Boldface type indicates the lowest value in each series.
2948 DUNBAR ET AL. APPL.ENVIRON.MICROBIOL.

profiles of a single sample can vary both in richness (total
number of TRFs in a profile) and in evenness (frequency
distribution of TRFs) depending on the enzyme used. Com-
bining data from different enzyme profiles in valid ways that
yield statistically informative results is therefore difficult.
Detection sensitivity. The detection sensitivity of the TRF
method was tested using soil DNA templates spiked with di-
lutions of a 5-kb plasmid purified from a clone (labeled S075)
from the S0 16S rRNA gene clone library (Fig. 4). In PCR
extinction dilution experiments, the detection threshold for
16S rDNA (that is, the lowest dilution of DNA from which a
visible 16S rDNA amplicon could be obtained) with soil DNA
was 1,000-fold higher than with the cloned plasmid DNA (data
not shown). Therefore, we converted DNA quantities to ge-
nome equivalents, assuming an average bacterial genome size
of 5 Mb and an average of one copy of the rRNA gene per
genome. The conversion of DNA quantities better illustrates
the ratio of target to nontarget DNA in the PCRs. As shown in
Fig. 4, 0.01 pg of the 16S rRNA gene clone spiked in 1 ng of
soil DNA was detected in an RsaI TRF profile. This repre-
sented a ratio of approximately 2,000 genomes to 200,000 ge-
nomes (1% of the total). In the absence of soil DNA, the
detection limit of the pure 16S rRNA gene clone remained at
approximately 2,000 genome equivalents per PCR. Similar re-
sults were obtained when 0.1 pg of the S0 clone was mixed with
10 ng of soil DNA in PCRs (data not shown). The S0 clone was
also detected at concentrations of 0.001 pg (200 genome equiv-
alents) in the presence of 1 ng of soil DNA per PCR (Fig. 4C).
However, at this concentration, detection of the target was
variable in contrast to the reproducible detection of 0.01 pg of
the S0 clone. The data suggest that the detection sensitivity in
these assays was determined by the target concentration alone
FIG. 4. Detection of a 16S rDNA clone (5-kb plasmid from clone S075) in a background of 1 ng of C0 soil DNA. (A) RsaI TRF profile of 16S rDNA amplified
from 0.01 pg of S075 plasmid DNA. (B) RsaI TRf profile of 16S rDNA amplified from a mixture of 0.01 pg of plasmid S075 and 1 ng of C0 soil DNA. (C) RsaI TRf
profile of 16S rDNA amplified from a mixture of 0.001 pg of plasmid S075 and 1 ng of C0 soil DNA. (D) RsaI TRF profile of 16S rDNA amplified from 1 ng of C0
soil DNA.
VOL. 66, 2000 TRF ANALYSIS OF SOIL BACTERIAL COMMUNITIES 2949

and was not substantially affected by the background concen-
tration of soil DNA. The data also suggest that populations
comprising between 0.1 and 1% of a bacterial community
could be detected in TRF profiles. The detection sensitivity of
the TRF method is comparable to other DNA-based commu-
nity analysis techniques. Using DGGE, Muyzer et al. (21)
reported the detection of a population comprising 1% of a
mixture of DNA from five organisms. Although their DNA
mixture was far less complex than the soil DNA used in our
assays, the detection sensitivities of DGGE and the TRF
method appear to be consistent.
Summary. The calibration we performed of TRF analysis of
four soil microbial communities and RFLP data from 801
clones from the same environments demonstrated strengths
and limitations of the TRF method. For the complex soil
communities compared in this study, TRF profiles were unable
to provide reliable information describing relative phylotype
richness and evenness. However, the method was very effective
in elucidating similarity relationships between communities
and has good detection sensitivity. The TRF method should be
especially useful for rapid analysis of replicate samples in field-
scale studies. Eventual incorporation of peak height data into
analyses of community similarity will further enhance the
method and its power to reveal differences between commu-
nities. While data from TRF profiles must be cautiously inter-
preted in some contexts, the method should in general prove to
be a useful new tool for microbial ecology research.
ACKNOWLEDGMENTS
We thank Tom Whitham and Catherine Gehring for their collabo-
ration at the Sunset Crater study site and Joseph Busch for help
generating the 16S rDNA clone libraries.
This work was supported in part by the Department of Energy
Program for Ecosystem Research.
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