FEMS Microbiology Ecology 45 (2003) 105^114
www.fems-microbiology.org
Soil fungal community structure in a temperate upland grassland soil
Eoin Brodie, Suzanne Edwards, Nicholas Clipson
Department of Industrial Microbiology, University College Dublin, Bel¢eld, Dublin 4, Ireland
Received 13 June 2002; received in revised form 24 January 2003; accepted 8 April 2003
First published online 24 May 2003
Abstract
Alterations in soil microfungal community structure across a transect between a semi-natural upland grassland and an agriculturally
improved enclosure were assessed using an indirect measurement of active fungal biomass (ergosterol), together with a nucleic acid
approach, terminal restriction fragment length polymorphism (TRFLP), which was compared to a commonly used but less sensitive
community fingerprinting technique, denaturing gradient gel electrophoresis (DGGE). These techniques indicated that there was no
reduction in numbers of fungal ribotypes across the floristic transect, despite decreased floristic diversity and a reduction of more than
two-fold in ergosterol concentration. Although there were no differences in ribotype number, there was a decrease in diversity and an
increase in dominance in only one of the transitional areas. The highest degree of variability within fungal communities was also found in
this transitional area, with 84% of ribotypes only being detected in one of three replicates. Comparison of the two fungal community
fingerprinting approaches indicated that TRFLP (26^33 ribotypes) was more sensitive for monitoring alterations in fungal community
structure than DGGE (13^18 ribotypes). Using a measurement of the relative percentage of each ribotype within communities, a decrease
in abundance of prominent ribotypes of the natural grassland soil fungal community was indicated together with an emergence of
previously undetected ribotypes towards the improved area. This may have important implications for ecosystem stability or productivity,
particularly if agricultural inputs to managed grasslands are suspended.
7 2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.
Keywords : Upland grassland; Fungus; Terminal restriction fragment length polymorphism; Denaturing gradient gel electrophoresis ; Polymerase chain
reaction; DNA; Ergosterol
1. Introduction
Acidic upland grasslands have become increasingly
managed in recent years to improve the productivity of
areas previously considered rough grazings (low yielding
permanent pasture), leading to signi¢cant £oristic change
[1,2]. The practices of liming, fertilisation, increased grazing and reseeding lead to diminished £oristic diversity,
with a shift from semi-natural species-rich grasslands to
species-poor plant communities dominated principally by
perennial ryegrass (Lolium perenne) and white clover (Trifolium repens). These practices are also known to a¡ect the
microbial component of soil communities, with fertiliser or
lime applications typically resulting in increased bacterial
numbers, decreased fungal biomass, and changes in micro-
* Corresponding author. Tel. : +353 (1) 716-1365;
Fax : +353 (1) 716-1183.
E-mail address : [email protected] (N. Clipson).
bial functional properties [3^6]. In acidic upland grasslands, fungi have been shown to be major components
of soil microbial biomass [4], contributing signi¢cantly to
nutrient and organic turnover processes including proteolysis, phosphorus mobilisation and translocation [7^9].
Although a considerable amount is known about broadscale in£uences on microbial communities, much less is
understood about the structure of individual soil fungal
populations in acidic grasslands and the e¡ects of environmental parameters. A number of techniques have been
used to assess soil fungal communities including culturebased approaches, direct microscopy of soil hyphae
[10,11], fatty acid analysis [12,13] and membrane sterol
quanti¢cation [14,15]. Such methods provide an overview
of fungal community structure but have inherent limitations. Culture-based analyses, such as plate counts, selective enrichment, or baiting (for in situ isolation of fungi),
only pro¢le the limited culturable proportion of the fungal
community, whereas the other techniques provide little
insight into fungal community structure.
Molecular techniques based upon the analysis of rRNA
0168-6496 / 03 / $22.00 7 2003 Federation of European Microbiological Societies. Published by Elsevier Science B.V. All rights reserved.
doi:10.1016/S0168-6496(03)00126-0
FEMSEC 1523 11-7-03
106
E. Brodie et al. / FEMS Microbiology Ecology 45 (2003) 105^114
genes are now widely used for the assessment of bacterial
and fungal community structure in soils (e.g. [16^20]), but
have not yet been applied to the fungal communities of
upland grasslands. These approaches are dependent upon
the successful extraction and puri¢cation of environmental
nucleic acids from soil, together with PCR ampli¢cation linked either to a clone sequence-based analysis or a
community ¢ngerprinting technique. Cloning-based approaches are costly, laborious and generally less suited
to the analysis of multiple samples. For this reason, cloning approaches have largely been superseded by community ¢ngerprinting when alterations in microbial community structure are being monitored. Such approaches are
much more developed for the analysis of bacterial rRNA
genes, where techniques such as denaturing/temperature
gradient gel electrophoresis (DGGE/TGGE), ampli¢ed ribosomal DNA restriction analysis, ribosomal internal
transcribed spacer analysis, and terminal restriction fragment length polymorphism (TRFLP) are now widely used
[21^24].
For complex microbial communities, such as those typically found in soils, a ¢ngerprinting technique must possess a level of sensitivity capable of detecting and discriminating between large numbers of ribotypes occurring at
di¡erent abundances. In this paper, fungal community
structure is assessed using community ¢ngerprinting approaches to pro¢le soil taken from a zone of £oristic transition (transect), which re£ects a change in grassland £oral
communities from a typical upland acidic system to an
agriculturally improved ley community. The aim of this
work was to assess whether reductions in fungal biomass
reported as a consequence of agricultural improvement correspond to alterations in fungal community structure.
and Festuca ovina at 80% in the Nardo-Galion (U4a) grassland, with L. perenne, Poa trivialis and T. repens all occurring at 100% frequency in the Lolio-Plantaginion (MG7b)
grassland. A zone of £oristic transition was evident between the two grassland types based on increased frequency and abundance of Lolio-Plantaginion plant species.
This zone was characterised by four main areas, the climax
grasslands (U4a and MG7b) and the transitional areas
(1 and 2). A notable component of this zone was a progressive reduction in grassland species number in the order
U4a s Transitional 1 s Transitional 2 s MG7b. Soil physico-chemical properties also changed across this transect
with notable increases in soil pH, nitrate, calcium, phosphorus and potassium towards MG7b, while organic matter content and ammonium levels declined (see [25] for full
description).
2.2. Sampling procedure
The zone of £oristic transition (transect) between the
two grasslands was sampled across three transects 10 m
in length, 12 m apart. Transects extended over the ¢eld
boundary, 7 m into the Nardo-Galion grassland, and 3 m
into the Lolio-Plantaginion grassland. Quadrats (1U1 m)
were placed at each end of the transect, at the ¢eld boundary, and 2.15^2.50 m into the Nardo-Galion grassland. In
each quadrat three randomly selected cores (10 cm diameter) were taken to a depth of 15 cm in September 1998.
Cores were placed in Ziploc1 plastic bags and transported
back to the laboratory where all plant and root material
was removed by sieving ( 6 2 mm). Ergosterol assays were
performed immediately and the sieved soil was then stored
at 380‡C prior to nucleic acid analysis.
2.3. Soil ergosterol content
2. Materials and methods
2.1. Study area
An area of Nardo-Galion grassland (U4a type within the
UK National Vegetation Classi¢cation [1]) was selected at
Longhill, Kilmacanogue, Co., Wicklow, Ireland (Nat.
Grid Ref. O 218 124) at an altitude of 300 m above sea
level on a peaty podzolic soil formed over granite/quartzite
bedrock, with an annual rainfall between 2000 and 2800
mm, and is described in detail elsewhere [25]. Brie£y, at
one part of the site an area of Lolio-Plantaginion grassland
(MG7b type within the UK National Vegetation Classi¢cation [1]) had been enclosed, this was a product of
ploughing and reseeding in 1993. This area has been limed
at approximately 5 t ha31 and fertilised at a rate of approximately 150 kg N, 25 kg P and 50 kg K ha31 , annually. Floristic analysis of the climax grasslands indicated
Agrostis capillaris, Galium saxatile, Potentilla erecta and
Rhytidiadelphus squarrosus occurring at 100% frequency
Soil ergosterol concentration was measured using a
method modi¢ed from the approaches of Grant and
West [26] and Eash et al. [27]. Sieved soil (5 g fresh weight)
was placed into a 50-ml centrifuge tube, and 15 ml of
methanol (0‡C) was added followed by 5 ml of potassium
hydroxide solution (40 g KOH l31 of 95% ethanol). This
mixture was then vortexed for 30 s and sonicated (U200S
Sonicator, IKA Labortechnik, Germany) for 2 min at
100% amplitude. Tubes were placed in a water bath at
85‡C, removed after 15 min and mixed manually for
1 min and replaced for a further 15 min. Following this,
the samples were cooled to 4‡C in a refrigerator for 20
min. 10 ml of high-performance liquid chromatography
(HPLC) grade pentane (BDH Ltd., UK) was added to
the tubes which were hand-shaken for 1 min. The samples
were then centrifuged at 3000Ug for 3 min to separate the
pentane layer from the soil. The pentane layer was removed and transferred to a new tube. This procedure
was carried out three times for each sample and the pentane extracts were combined. Extracts were dried under N2
FEMSEC 1523 11-7-03
E. Brodie et al. / FEMS Microbiology Ecology 45 (2003) 105^114
to minimise oxidation of extracted ergosterol before being
redissolved in HPLC grade methanol and ¢ltered through
0.2-Wm Te£on ¢lters into glass HPLC vials. HPLC analysis was carried out using a Waters Sugar-Analyser I HPLC
system with a Partisil ODS 10 HPLC column (22 cm in
length, 4.6 mm in diameter ^ Hichrom, Reading, UK)
with a methanol mobile phase at 1 ml min31 . Ergosterol
was detected with a UV detector set at 282 nm. Concentrations of ergosterol in samples were quanti¢ed by comparison with standard ergosterol solutions. The e⁄ciency
of ergosterol extraction from soil samples was determined
by the incorporation of 25 Wg ergosterol (Fluka Ltd., UK)
as an internal standard along with soil. Extraction e⁄ciency of ergosterol from soil in these experiments was
estimated at 85 S 3.5%.
2.4. Fungal community ¢ngerprinting by TRFLP analysis
Total soil DNA was extracted as described previously
[25]. Brie£y this involved extraction from 0.5-g aliquots of
soil with a combination of heat, chemical lysis and bead
beating. After extraction and puri¢cation of total DNA
from soil, a portion of the eukaryotic 18S small subunit
rRNA gene speci¢c to fungi was ampli¢ed using primer set
nu-SSU-0817-5P (5P-TTAGCATGGAATAATRRAATAGGA-3P) and nu-SSU-1536-3P (5P-ATTAGCAATGCYCTATCCCCA-3P) [19]. The forward primer nu-SSU0817-5P was labelled with £uorescent dye D4 (Beckman
Coulter Inc., CA, USA). PCR reactions were performed
in 50-Wl volumes containing 5 Wl of 10UMg free PCR
bu¡er (Promega, WI, USA), 1.25 mM MgCl2 , 15 pmol
of each primer, 200 WM of each dNTP, 25 Wg bovine
serum albumin, V10 ng extracted total soil DNA and
2.5 U Taq DNA polymerase (Promega, WI, USA).
The thermocycling conditions were as follows : a hot
start at 94‡C for 2 min (one cycle) ; 94‡C for 1 min,
56‡C for 2 min, 72‡C for 1.5 min (45 cycles) ; 72‡C for
5 min (one cycle). PCR products of the correct size were
con¢rmed by agarose gel electrophoresis and subsequently
puri¢ed using a High Pure1 PCR product puri¢cation kit
(Roche Diagnostics GmbH, Mannheim, Germany) according to manufacturer’s instructions (50 Wl ¢nal volume). The puri¢ed PCR product was then digested enzymatically and analysed using an automated sequencer as
described previously [25]. Of the enzymes assessed (CfoI,
Sau3aI and MspI) the restriction enzyme MspI provided
the best discrimination between samples (data not shown).
This corresponded to our previous study of bacterial community dynamics, and a TRFLP analysis of micro-eukaryotes in activated sludge [28]. Phylogenetic ribotypes were
assigned to some terminal restriction fragments (TRFs) by
analysing a subset of complete ( s 1700 bp) 18S rRNA sequences from the ribosomal database [29] using a pattern
matching program PatScan (http://www-unix.mcs.anl.
gov/compbio/PatScan/HTML/getting_scan_for_matches.
html).
107
2.5. Diversity of fungal TRFLP pro¢les
The Shannon^Weaver diversity index [30] was used to
estimate fungal diversity based on the size and number of
TRFs using Eq. 1 :
^Þ ¼
Shannon Weaver index ðH
C=N ðN log10 N3
P
ni log10 ni Þ
ð1Þ
Where C = 2.3, N = sum of peak heights in a given
TRFLP pro¢le, ni = height of TRF i and i = number of
TRFs in each TRFLP pro¢le.
Dominance within communities was estimated using the
equitability index [30] based upon the size and number of
TRFs present using Eq. 2 :
^ =H max
Equitability ðJÞ ¼ H
ð2Þ
Where H = Shannon^Weaver diversity index and
Hmax = theoretical maximal Shannon^Weaver diversity index assuming all peaks are equal in height. Hmax was calculated according to Eq. 3:
P
H max ¼ C=N ðN log10 N3 ni log10 ni Þ
ð3Þ
Where C = 2.3, N = sum of peak heights in a given
TRFLP pro¢le assuming that each peak has a height of
1, and ni = height of TRF i (1), i = number of TRFs in
each TRFLP pro¢le.
2.6. Phylogenetic association of individual TRFs
A subset of near complete sequences ( s 1700 bp) was
extracted from the eukaryotic small subunit ribosomal database (courtesy of Terry Marsh, Center for Microbial
Ecology at Michigan State University) for simulated restriction digestion (in silico). Using the PatScan program
(http ://www-unix.mcs.anl.gov/compbio/PatScan/HTML/
getting_scan_for_matches.html), this database was scanned
in order to determine the relative positions of primer and
restriction enzyme recognition sites.
2.7. Fungal community ¢ngerprinting by DGGE analysis
For this approach a slightly di¡erent bead beatingbased DNA extraction procedure was employed. DNA
was extracted from identical soil samples (0.25 g in this
case) as for TRFLP analyses using an UltraClean Soil
DNA isolation kit1 (Mo Bio Laboratories Inc., CA,
USA), using a bead beater. Bead beating was performed
at 4500 rpm using a Minibeadbeater (BioSpec Products
Inc., OK, USA) twice for 30 s with cooling on ice for
1 min between beating cycles. The remainder of the extraction process was as per the manufacturer’s instructions. A further soil DNA puri¢cation step was found to
be necessary in most cases and therefore was performed on
all samples. This step involved adding 0.1 g of polyvinylpolypyrillidone (PVPP) to each 50-Wl DNA extract and
FEMSEC 1523 11-7-03
108
E. Brodie et al. / FEMS Microbiology Ecology 45 (2003) 105^114
incubating at 4‡C for 1 h followed by centrifugation at
14 000 rpm for 2 min. All soil DNA samples were then
subjected to a ¢nal ¢ltration puri¢cation step using a High
Pure1 PCR product clean up kit. DNA was ampli¢ed by
a nested PCR procedure [17]. The ¢rst round involved
ampli¢cation of an approximately 1400-bp portion of
the 18S rDNA gene using primers EF4 (5P-GGAAGGGRTGTATTTATTAG-3P) and EF3 (5P-TCCTCTAAATGACCAAGTTTG-3P). The product of this reaction
was then diluted 1:500 with sterile water and used as a
template for a subsequent round of PCR with primers
EF4 and NS3-GC (NS3-GC 5P-CGCCCGCCGCGCC
CCGCGCCCGGCCCGC CGCCCCCGCCCCGGCTGCTGGCACCAGACTTGC-3P, GC clamp underlined) resulting in a PCR product of approximately 500 bp which
was suitable for DGGE. PCR reactions were performed in
50-Wl volumes containing 5 Wl of 10UMg free PCR bu¡er
(Promega, WI, USA), 1.25 mM MgCl2 , 15 pmol of each
primer, 200 WM of each dNTP, V10 ng extracted total
soil DNA or 2 Wl of diluted PCR product, and 2.5 U Taq
DNA polymerase (Promega, WI, USA). The following
thermocycling patterns were used: for initial PCR with
EF4-EF3: 94‡C for 3 min (one cycle); 94‡C for 1 min,
50‡C for 1 min, 72‡C for 2 min (40 cycles) ; and 72‡C for
10 min (one cycle). For nested PCR with EF4-NS3-GC :
94‡C for 3 min (one cycle); 94‡C for 1 min, 60‡C for 1 min
(with reduction of 1‡C every cycle), 72‡C for 1 min
(10 cycles) ; 94‡C for 1 min, 50‡C for 1 min, 72‡C for
2 min (15 cycles); 72‡C for 5 min (one cycle). PCR products of correct size were con¢rmed by agarose gel electrophoresis and puri¢ed as before. Triplicate samples were
pooled for each position across the transect and 15 Wl of
this mixture was analysed by DGGE using a polyacrylamide gel (10%) with a gradient of 30^45% denaturants
(100% denaturant is equivalent to 7 M urea and 40%
v/v of de-ionised formamide). Polymerisation was achieved
by addition of ammonium persulphate (0.10% v/v)
and TEMED (N,N,NP,NP-tetra-methyl-ethylene diamine,
0.05% v/v). Gradients were formed using a Model 475
gradient delivery system (Bio-Rad Inc., CA, USA). Before
polymerisation was complete a 3-ml top loading gel containing 0% denaturants was dispensed and the gel comb
carefully placed into this. This was to ensure that wells
to which the DNA samples were to be added would be
su⁄ciently polymerised so no leakage would occur. Gels
were electrophoresed for 17 h at 85 V in 1UTAE bu¡er
at a constant temperature of 60‡C using a Bio-Rad
DGENE0 system. Gels were stained in SYBR1 Green I
(Molecular Probes Inc., OR, USA) using the manufacturer’s recommended dilution (1:10 000) for 30 min. The
number of bands on gels was quanti¢ed using Quantity
One software (Bio-Rad Inc., CA, USA) and images captured using a FlourS-Max1 MultiImager (Bio-Rad Inc.,
CA, USA).
2.8. Statistical analyses
All statistical analyses were carried out using the computer package SPSS v.11.0 (SPSS Inc., IL, USA). One-way
analysis of variance (ANOVA) was used to determine signi¢cance of di¡erences between ergosterol concentrations,
Shannon^Weaver diversity estimates, and equitability of
communities in soil at positions across the transect. Multivariate ANOVA followed by Bonferroni’s t-test (P 9 0.05
probability level) was used to determine signi¢cant di¡erences in the presence of individual TRFs between positions across the transect.
DGGE data and pooled TRFLP data were converted to
binary format and compared using the Jaccard coe⁄cient
(Sj ) [31]. This describes the similarity of each sample pair
based only on DGGE bands or TRFs present in one or
both communities. As such, DGGE bands or TRFs that
are not present in either of two communities being compared do not contribute to the similarity of the two communities. The results of Jaccard similarity measurements
are presented as a proximity matrix.
3. Results
3.1. Soil ergosterol concentrations
There was a marked decrease in ergosterol concentration across the transect from the U4a area towards MG7b
(Fig. 1). Soil from the U4a area had signi¢cantly
(P 6 0.05) higher concentrations of ergosterol than all other positions across the transect with more than twice that
of MG7b soil. Soil from the Transitional 1 area also contained signi¢cantly (P 6 0.05) higher ergosterol concentrations than MG7b.
Fig. 1. Concentrations of ergosterol in soil at positions across a transect
between U4a and MG7b grasslands. Same letter denotes no signi¢cant
di¡erence (P s 0.05). Bars indicate mean S S.E.M. (n = 9).
FEMSEC 1523 11-7-03
E. Brodie et al. / FEMS Microbiology Ecology 45 (2003) 105^114
109
3.2. TRFLP
There were no signi¢cant (P s 0.05) di¡erences in mean
numbers of TRFs between sample sites across the transect
between U4a and MG7b soils (Table 1), with mean ribotype numbers detected ranging between 13 and 17.
Fungal community diversity (Shannon^Weaver index)
as estimated from TRFLP pro¢les was signi¢cantly
(P 6 0.05) lower in soil from the Transitional 2 area
than in any other position across the transect (Table 1).
Soil from the Transitional 2 area also exhibited a greater
degree of dominance within the fungal community as indicated by the equitability index, although this was only
signi¢cantly di¡erent (P 6 0.05) from U4a and Transitional 1 fungal communities (Table 1). Visual inspection of the
list of unique TRFs detected (Table 2) supports this ¢nding. For example, U4a soil produced six TRFs which accounted for more than 10% of the relative abundance,
Transitional 1 produced three TRFs accounting for 10%
each while Transitional 2 and MG7b only produced one
or two TRFs respectively which accounted for 10% or
more of the relative abundance. In fact a single TRF
(568) from Transitional 2 soil accounted for almost 40%
of the relative abundance in those pro¢les (mean of three
replicates). Although TRF568 showed a trend of increasing
abundance across the transect this increase was not statistically signi¢cant (P s 0.05). Of the 56 TRFs detected only
¢ve (TRF 274, 275, 562, 563 and 634) were signi¢cantly
(P 6 0.05) di¡erent between positions across the transect.
The number of ribotypes detected was most variable in
Transitional area 2 with over 84% of TRFs only detected
in one of three replicate samples.
3.3. Phylogenetic association of individual TRFs by
simulated restriction digestion
The primer sequence and the MspI recognition sequence
were successfully pattern-matched to 1477 sequences in the
database. The simulated restriction digestion of the eukaryotic small subunit rDNA database was compared
with the seven most abundant TRFs from U4a soil. This
revealed that three TRFs (578, 130 and 634) did not correspond to any sequences present in the database; TRF568
matched to two species of Kionochaeta (Sordariales) ;
TRF573 matched to Kluyveromyces lactis; TRF565 matched
to 23 members of the Basidiomycota (6% Ceratobasidiales/Cantharellales, 20% Stereales, 27% Hymenomyceti-
Fig. 2. DGGE pro¢les of fungal communities in soil at positions across
a transect between U4a and MG7b grasslands. Horizontal bars in columns to the left of gel lanes indicate positions of individual bands.
dae and 47% Agaricales); and TRF563 also matched 23
species, mostly members of the Basidiomycota (6% Hymenomycetidae, 6% Agaricales, 78% Tremellales) but also
matching 10% Taphrinales (Ascomycota).
3.4. Comparison of pooled TRFLP and DGGE samples
Fig. 2 shows a DGGE pro¢le of pooled soil fungal
communities at positions across the transect and demonstrates discernible banding patterns. Numbers of DGGE
bands were found to increase across the transect with a
total number of identi¢able bands ranging from 13 detected from the U4a community and 14, 18 and 15 detected in soil from the Transitional 1, Transitional 2 and
Table 1
Numbers of TRFs and diversity measurements of fungal ribotypes in soil at positions across a transect between U4a and MG7b grasslands
Position across transect
TRF numbers
Shannon^Weaver diversity index of TRFLP patterns
Equitability index of TRFLP patterns
U4a
Transitional 1
Transitional 2
MG7b
13.0 S 1.53
12.7 S 1.45
13.3 S 3.38
17.3 S 1.20
2.11 S 0.08
2.13 S 0.15
1.30 S 0.16
2.17 S 0.11
0.83 S 0.04
0.84 S 0.02
0.53 S 0.09
0.77 S 0.06
a
a
a
a
a
a
b
a
a
a
b
ab
Mean S S.E.M. of three replicates are shown. Di¡erent letters denote signi¢cant di¡erence (ANOVA followed by Bonferroni’s t-test, P 6 0.05).
FEMSEC 1523 11-7-03
110
E. Brodie et al. / FEMS Microbiology Ecology 45 (2003) 105^114
Table 2
Relative abundance (%) of fungal TRFs in soil at positions across a transect between U4a and MG7b grasslands
TRF length
57
62
68
73
74
75
76
92
93
129
130
131
268
269
270
271
272
274
275
312
314
316
318
404
454
469
497
498
499
560
562
563
564
565
566
568
569
570
571
572
573
574
575
577
578
581
582
583
584
585
586
587
607
634
637
638
U4a
0.19 (1)
Transitional 1
0.13 (1)
0.31 (1)
0.39 (1)
Transitional 2
0.45
0.17
0.11
0.21
(1)
(1)
(1)
(1)
0.24 (1)
0.12 (1)
13.23 (3)
1.65 (3)
0.66 (1)
6.74 (2)
0.68 (1)
1.29 (1)
0.97 (1)
0.26 (1)
0.30 (1)
0.86 (1)
1.79 (3)
0.91 (1)
1.54 (1)
MG7b
0.19 (1)
0.52 (2)
0.33 (1)
0.26 (1)
0.34 (1)
0.24 (1)
0.39 (1)
0.1 (1)
3.14 (3)
0.18
0.32
0.55
0.37
0.25
1.28
0.16
(1)
(1)
(1)
(1)
(1)
(3)
(1)
0.19 (1)
0.34 (1)
0.19 (1)
0.84 (1)
9.91 (2)
4.47 (1)
10.54 (2)
6.70 (1)
12.51 (3)
0.66
1.52
0.27
0.15
1.09
0.16
(1)
(1)
(1)
(1)
(1)
(1)
5.97 (3)
6.17 (2)
1.44
1.41
2.65
5.77
(1)
(1)
(1)
(2)
11.85 (3)
28.46 (2)
2.12 (2)
39.91 (3)
0.78 (2)
0.1 (1)
0.34 (1)
1.39 (2)
5.96 (3)
4.56 (1)
4.36 (2)
11.12 (1)
28.84 (3)
1.35 (1)
0.61 (1)
0.68 (1)
12.09 (1)
2.68 (1)
1.85 (2)
19.59 (2)
2.49 (1)
7.40 (2)
2.82 (1)
7.40 (2)
0.82 (2)
1.39 (1)
0.31 (1)
10.11 (3)
0.31 (1)
0.55 (1)
0.65 (1)
0.28 (1)
6.44 (2)
4.90 (3)
3.50 (1)
3.71 (1)
0.13 (1)
1.23 (1)
1.58 (1)
1.36 (1)
12.73 (2)
3.61 (1)
0.79 (1)
5.97 (1)
9.39 (3)
3.52 (1)
8.22 (1)
2.98 (1)
4.48 (3)
8.43 (2)
7.42 (3)
8.88 (3)
1.21 (1)
0.7 (1)
Data represent combined values from three subsamples at each position. Values in parentheses indicate frequency of TRF detection within subsamples
(n = 3).
FEMSEC 1523 11-7-03
E. Brodie et al. / FEMS Microbiology Ecology 45 (2003) 105^114
111
Table 3
Proximity matrix based on Jaccard measurements of fungal ribotype similarity in soil at positions across a transect between U4a and MG7b grasslands
as measured from 18S rDNA TRFs and DGGE bands (1.0 indicates complete similarity)
Position across transect
U4a
Transitional 1
Transitional 2
MG7b
a
U4a
Transitional 1
Transitional 2
MG7b
TRFLP
DGGEa
TRFLP
DGGE
TRFLP
DGGE
TRFLP
DGGE
1.0
0.32
0.29
0.28
1.0
0.42
0.48
0.33
1.0
0.34
0.47
1.0
0.78
0.71
1.0
0.41
1.0
0.65
1.0
1.0
Based on pooled samples (n = 3) for DGGE.
MG7b areas respectively. As these values represent the
contribution of pooled DNA from three samples it was
not possible to test whether di¡erences were signi¢cant
statistically.
Jaccard analysis indicated substantial di¡erences in ribotypes between fungal communities across the transect,
with the TRFLP-based approach showing the lower similarity values (Table 3) compared to DGGE. The U4a and
MG7b soil fungal communities were the least similar, with
most similarity between the transitional and MG7b communities.
4. Discussion
Changes in soil ergosterol concentrations across the
transect between U4a and MG7b grassland types indicated that levels of active fungal biomass in improved soils
were reduced by around 50%. Similar reductions in fungal
biomass have been found in other studies. In upland
brown podzolic soils, Neale et al. [32] found that liming
reduced total fungal hyphal length, and Bardgett et al. [4]
demonstrated that fertilisation reduced the ratio of fungal
to bacterial phospholipid fatty acids (PLFAs) in a permanent pasture. Bardgett and McAlister [33] found that unimproved upland pastures had higher levels of fungal
PLFAs than improved upland pastures.
In this study, the decline in active fungal biomass was
coincident with changes in both £oristic diversity and in
soil physico-chemical factors. Bardgett et al. [5], using a
microcosm approach, proposed that the abundance and
activity of soil microorganisms is mainly regulated by
plant species traits. Conversely, Brodie et al. [25] suggested
that soil physico-chemical factors such as pH or available
nitrogen were the principal determinants controlling bacterial community structure in a ¢eld situation. However, it
is likely that reductions in active fungal biomass are due to
a number of factors attributable to agricultural improvement. Increased soil pH has been shown to in£uence levels
of fungal biomass although varied responses have been
reported [34,35] ; likewise nitrogen applications have been
implicated in both increased and decreased fungal biomass
[5,36,37]. It is possible that di¡erences in the initial fungal
community compositions of soils contribute to these contrasting ¢ndings. As such it would be bene¢cial to have
some information regarding the components of a soil fungal community in the absence of agricultural treatments
and subsequently monitor the impact of treatments on
individual community members. In e¡ect the transect or
gradient at this site permitted us to follow community
alterations on a spatial scale without the confounding environmental parameters associated with temporal studies.
Measurements based upon the assessment of microbial
biomass through quanti¢cation of signal molecules such as
fatty acids or sterols give a broad-scale view of microbial
population structure, but may be limited by the in£uence
of microbial physiological status [15,38] and can only give
very super¢cial diversity estimates. For this study we developed a sensitive approach to monitor soil fungal community structure based on soil nucleic acid extraction and
TRFLP analysis, which to our knowledge is one of the
¢rst reported uses of this approach in grassland fungal
ecology.
The value of a TRFLP approach is that it may be interpreted on a number of levels. Firstly, the number of
TRFs or ribotypes found in each soil gives information
regarding fungal diversity at a quantitative level (numbers
of ribotypes present). Secondly, fragment lengths can potentially be compared with known sequences in a database
or clone library (identi¢cation of ribotypes); while fragment peak height provides information about the relative
abundance of a ribotype within a particular soil sample. In
principle, combining these parameters builds a view of
fungal community structure.
Although mean ribotype number as determined from
TRFLP data (Table 1) was not signi¢cantly di¡erent
across the transect between U4a and MG7b, Jaccard analysis of both fragment length and DGGE data (Table 3)
indicated that the composition of soil fungal communities
across the transect was quite di¡erent. Low similarity values applied to all pairwise comparisons. The Shannon^
Weaver diversity index also indicated a change in community diversity based on TRFLP data, although fungal diversity did not decrease with decreasing £oristic diversity.
The Transitional 2 area appeared to have a variable soil
fungal community exhibiting some degree of dominance.
With total peak height values converted into percentage
abundances (Table 2) it was possible to monitor the potential dominance or co-dominance of individual ribotypes
within fungal communities. For this purpose we consid-
FEMSEC 1523 11-7-03
112
E. Brodie et al. / FEMS Microbiology Ecology 45 (2003) 105^114
ered ribotypes with percentage abundances above or
around 10% as dominant. The U4a soil community appeared to have many more co-dominant members than the
improved soil communities. It was also noticeable that
certain dominant ribotypes were location speci¢c across
the transect. For example, the ribotype with a TRF length
of 578 (TRF578 ) was the most abundant in U4a soil, but
declined very markedly in Transitional 1 and was not detectable thereafter. TRF568 was present in high abundance
in all positions across the transect, whilst TRF586 increased across the transect. Overall, a great number of
trends concerning individual TRFs were traced, demonstrating that the use of TRFLP can be used to explore
complex changes in fungal diversity in ecological situations.
To provide supporting evidence for TRFLP analysis of
fungal communities across the transect, a comparison was
made using DGGE performed on the same soil samples,
albeit with a nucleic acid extraction procedure that differed slightly. Detectable ribotype numbers determined
by DGGE (13^18) were approximately half those detected
by TRFLP (23^33). DGGE is relatively insensitive with
less abundant ribotypes tending not to form distinct bands
but contributing to a di¡use background, or structurally
di¡erent DNA molecules coincidentally co-migrating to
the same place on a gel [39]. TRFLP has been shown to
typically distinguish a greater proportion of ribotypes
from environmental samples [40]. This is borne out from
comparing proximity matrices generated from TRFLP and
DGGE data (Table 3), with similarities between transect
positions being much greater for DGGE ribotypes than
those for TRFLP. This re£ects the more limited resolution
of DGGE in detecting less abundant ribotypes.
TRFs can potentially be used to indicate phylogenetic
associations, which can be used to propose putative species identity. This is dependent upon the availability of a
well developed fungal sequence database which, with the
necessary software, could generate a restriction fragment
list speci¢c to primers and restriction enzymes used. This
approach is routinely available for prokaryotes (http://
rdp.cme.msu.edu/html/TAP-tr£p.html), although it is still
somewhat limited by insu⁄cient database coverage of environmentally relevant organisms. While this web-based
program is not currently linked to eukaryotic databases
the authors were able to use a subset of near complete
sequences extracted from the eukaryotic small subunit ribosomal database and perform simulated digestions.
When the seven most abundant TRFs from U4a soil
were compared to the database three TRFs (578, 130
and 634) did not correspond to any sequences present.
This may re£ect the dominance of culturable industrial
and medically important species in such databases. While
matches were found for the other TRFs analysed it appeared that at least from the limited data presented here,
the resolution of phylogenetic inference is limited to broad
fungal groups. It is also clear from this work that many
identi¢cations are not speci¢c, probably re£ecting that a
single TRF may represent a number of species. This could
be improved through the use of more than one restriction
enzyme for the analyses, or through identi¢cation of TRFs
within clone libraries generated from rDNA sequences
predigestion. The purpose of TRFLP analysis in this
work was primarily to discriminate between communities,
and preliminary analyses showed the enzyme MspI to be
the most successful in this regard. As always with PCRbased community analyses some caution must be exercised
in the interpretation of such data, particularly quantitative
aspects, due to di¡ering PCR ampli¢cation e⁄ciencies of
templates within heterogeneous community DNA extracts
[41].
Although fungal biomass was reduced towards MG7b,
both TRFLP and DGGE data indicated that position
within the transect (and hence the environmental parameters operating at that position) did not reduce fungal ribotype number (diversity). One interesting result of soil
improvement was a reduction in co-dominant fungal ribotypes, with communities in transitional areas (particularly
Transitional area 2) and MG7b being dominated by fewer
ribotypes. Across the transect (towards MG7b) there was
a substantial reduction in plant diversity (25 species reducing to six), together with a marked increase in pH (pH 3.9
to 6.3), phosphorus and nitrate; conversely there was a
substantial decline in soil ammonium levels [25]. Clearly
these factors will in£uence the composition and abundance
of fungal community members, although it is not possible
to single out any one factor as a dominant one from this
data. It is often perceived that high plant diversity should
promote a richly diverse microbial community due to the
formation of intimate relationships between speci¢c plant
species and microorganisms, and conversely low plant diversity should be associated with reduced microbial diversity. Clearly this was not the case in this grassland, with
reductions in plant diversity having no signi¢cant e¡ect on
fungal ribotype number. It is more likely that fungal diversity is determined by complex interactions between the
aforementioned environmental parameters. Nevertheless,
while having no e¡ect on total ribotype number, there
were obvious changes in ribotype composition, with the
appearance and disappearance of ribotypes across the
transect. The composition of fungal species present in a
grassland soil may have important implications for plant
biodiversity and ecosystem variability [42], while ecosystem stability may be particularly a¡ected if application of
inputs to managed pastures is suspended.
Acknowledgements
We thank the Roche family at Longhill for kind permission to carry out ¢eld work on their land, Terry Marsh
for providing the 18S rRNA database subset, Martin
Moelho¡ for assistance with PatScan. We are grateful to
FEMSEC 1523 11-7-03
E. Brodie et al. / FEMS Microbiology Ecology 45 (2003) 105^114
Nabla Kennedy, Deirdre Gleeson, Sue Lynch and three
anonymous reviewers for helpful comments on the manuscript. Part of this work was supported by the Enterprise
Ireland Basic Research Grant Programme.
[20]
[21]
References
[1] Rodwell, J.S. (1992) British Plant Communities. Cambridge University Press, Cambridge.
[2] Fothergill, M., Davies, D.A. and Morgan, C.T. (1994) Extensi¢cation
of upland pasture in Britain. Proc. N.Z. Grassl. Assoc. 56, 219^222.
[3] Lovell, R.D., Jarvis, S.C. and Bardgett, R.D. (1995) Soil microbial
biomass and activity in long-term grassland: E¡ects of management
change. Soil Biol. Biochem. 27, 969^975.
[4] Bardgett, R.D., Lovell, R.D., Hobbs, P.J. and Jarvis, S.C. (1999)
Seasonal changes in soil microbial communities along a fertility gradient of temperate grasslands. Soil Biol. Biochem. 31, 1021^1030.
[5] Bardgett, R.D., Mawdsley, J.L., Edwards, S., Hobbs, P.J., Rodwell,
J.S. and Davies, W.J. (1999) Plant species and nitrogen e¡ects on soil
biological properties of temperate upland grasslands. Funct. Ecol. 13,
650^660.
[6] Watson, C.J. and Mills, C.L. (1998) Gross nitrogen transformations
in grassland soils as a¡ected by previous management intensity. Soil
Biol. Biochem. 30, 743^753.
[7] Bafiafith, E. and So«derstro«m, B. (1980) Degradation of macromolecules
by soil fungi isolated from di¡erent podzolic soil horizons. Can. J.
Bot. 58, 422^425.
[8] Bolan, N.S. (1991) A critical review on the role of mycorrhizal fungi
in the uptake of phosphorus by plants. Plant Soil 134, 189^207.
[9] Cromack, K. and Caldwell, B.A. (1992) The role of fungi in litter
decomposition and nutrient cycling. In: The Fungal Community, its
Organisation and Role in the Ecosystem (Carroll, G.C. and Wicklow,
D.T., Eds.), pp. 601^618. Marcel Dekker, New York.
[10] Frankland, J.C., Dighton, J. and Boddy, L. (1990) Methods for
studying fungi in soil and forest litter. Methods Microbiol. 22, 343^
404.
[11] Miller, M., Palojarvi, A., Rangger, A., Reeslev, M. and Kjoller, A.
(1998) The use of £uorogenic substrates to measure fungal presence
and activity in soil. Appl. Environ. Microbiol. 64, 613^617.
[12] Olsson, P.A., Thingstrup, I., Jakobsen, I. and Baath, E. (1999) Estimation of the biomass of arbuscular mycorrhizal fungi in a linseed
¢eld. Soil Biol. Biochem. 31, 1879^1887.
[13] Grayston, S.J., Gri⁄th, G.S., Mawdsley, J.L., Campbell, C.D. and
Bardgett, R.D. (2001) Accounting for variability in soil microbial
communities of temperate upland grassland ecosystems. Soil Biol.
Biochem. 33, 533^551.
[14] West, A.W., Grant, W.D. and Sparling, G.P. (1987) Use of ergosterol, diaminopimelic acid and glucosamine contents of soils to monitor
changes in microbial populations. Soil Biol. Biochem. 19, 607^612.
[15] Ruzicka, S., Edgerton, D., Norman, M. and Hill, T. (2000) The
utility of ergosterol as a bioindicator of fungi in temperate soils.
Soil Biol. Biochem. 32, 989^1005.
[16] Felske, A. and Akkermans, A.D.L. (1998) Spatial homogeneity of
abundant bacterial 16S rRNA molecules in grassland soils. Microb.
Ecol. 36, 31^36.
[17] Smit, E., Lee£ang, P., Glandorf, B., van Elsas, J.D. and Wernars, K.
(1999) Analysis of fungal diversity in the wheat rhizosphere by sequencing of cloned PCR-ampli¢ed genes encoding 18S rRNA and
temperature gradient gel electrophoresis. Appl. Environ. Microbiol.
65, 2614^2621.
[18] Borneman, J. and Hartin, R.J. (2000) PCR primers that amplify
fungal rRNA genes from environmental samples. Appl. Environ.
Microbiol. 66, 4356^4360.
[19] Bruce, K.D. and Hughes, M.R. (2000) Terminal restriction fragment
[22]
[23]
[24]
[25]
[26]
[27]
[28]
[29]
[30]
[31]
[32]
[33]
[34]
[35]
[36]
[37]
[38]
113
length polymorphism monitoring of genes ampli¢ed directly from
bacterial communities in soils and sediments. Mol. Biotechnol. 16,
261^269.
Ranjard, L., Poly, F. and Nazaret, S. (2000) Monitoring complex
bacterial communities using culture-independent molecular techniques: application to soil environment. Res. Microbiol. 151, 167^
177.
Liu, W.T., Marsh, T.L., Cheng, H. and Forney, L.J. (1997) Characterization of microbial diversity by determining terminal restriction
fragment length polymorphisms of genes encoding 16S rRNA. Appl.
Environ. Microbiol. 63, 4516^4522.
Ovreas, L. and Torsvik, V. (1998) Microbial diversity and community
structure in two di¡erent agricultural soil communities. Microb. Ecol.
36, 303^315.
Muyzer, G. (1999) DGGE/TGGE a method for identifying genes
from natural ecosystems. Curr. Opin. Microbiol. 2, 317^322.
Ranjard, L., Poly, F., Lata, J.C., Mougel, C., Thioulouse, J. and
Nazaret, S. (2001) Characterization of bacterial and fungal soil communities by automated ribosomal intergenic spacer analysis ¢ngerprints: Biological and methodological variability. Appl. Environ. Microbiol. 67, 4479^4487.
Brodie, E., Edwards, S. and Clipson, N. (2002) Bacterial community
dynamics across a £oristic gradient in a temperate upland grassland
ecosystem. Microb. Ecol. 44, 260^270.
Grant, W.D. and West, A.W. (1986) Measurement of ergosterol,
diaminopimelic acid and glucosamine in soil: evaluation as indicators
of microbial biomass. J. Microbiol. Methods 6, 47^53.
Eash, N.S., Stahl, P.D., Parkin, T.B. and Karlen, D.L. (1996) A
simpli¢ed method for extraction of ergosterol from soil. Soil Sci.
Soc. Am. J. 60, 468^471.
Marsh, T.L., Liu, W.T., Forney, L.J. and Hans, C. (1998) Beginning
a molecular analysis of the eukaryal community in activated sludge.
Water Sci. Tech. 37, 455^460.
Maidak, B.L., Cole, J.R., Lilburn, T.G., Parker Jr., C.T., Saxman,
P.R., Farris, R.J., Garrity, G.M., Olsen, G.J., Schmidt, T.M. and
Tiedje, J.M. (2001) The RDP-II (Ribosomal database project). Nucleic Acids Res. 29, 173^174.
Atlas, R.M. and Bartha, R. (1998) Microbial Ecology: Fundamentals
and Applications, 4th edn. Benjamin/Cummings, Menlo Park, CA.
Kaufman, L. and Rousseeuw, P.J. (1990) Finding Groups in Data:
an Introduction to Cluster Analysis. John Wiley and Sons, New
York.
Neale, S.P., Shah, Z. and Adams, W.A. (1997) Changes in microbial
biomass and nitrogen turnover in acidic organic soils following liming. Soil Biol. Biochem. 29, 1463^1474.
Bardgett, R.D. and McAlister, E. (1999) The measurement of soil
fungal:bacterial biomass ratios as an indicator of ecosystem self-regulation in temperate grasslands. Biol. Fert. Soils 19, 282^290.
Fritze, H. and Ba«a«th, E. (1993) Microfungal species composition and
fungal biomass in a coniferous forest soil polluted by alkaline deposition. Microb. Ecol. 25, 83^92.
Donnison, L.M., Gri⁄th, G.S., Hedger, J., Hobbs, P.J. and Bardgett,
R.D. (2000) Management in£uences on soil microbial communities
and their function in botanically diverse haymeadows of northern
England and Wales. Soil Biol. Biochem. 32, 253^263.
Henriksen, T.M. and Breland, T.A. (1999) Nitrogen availability effects on carbon mineralization, fungal and bacterial growth, and
enzyme activities during decomposition of wheat straw in soil. Soil
Biol. Biochem. 31, 1121^1134.
Donnison, L.M., Gri⁄th, G.S. and Bardgett, R.D. (2000) Determinants of fungal growth and activity in botanically diverse haymeadows: e¡ects of litter type and fertilizer additions. Soil Biol. Biochem.
32, 289^294.
Haack, S.K., Garchow, H., Odelson, D.A., Fornet, L.J. and Klug,
M.J. (1994) Accuracy, reproducibility, and interpretation of fatty acid
methyl ester pro¢les of model bacterial communities. Appl. Environ.
Microbiol. 60, 2483^2493.
FEMSEC 1523 11-7-03
114
E. Brodie et al. / FEMS Microbiology Ecology 45 (2003) 105^114
[39] Lukow, T., Dun¢eld, P.F. and Liesack, W. (2000) Use of the TRFLP technique to assess spatial and temporal changes in the bacterial community structure within an agricultural soil planted with
transgenic and non-transgenic potato plants. FEMS Microbiol. Ecol.
32, 241^247.
[40] Moeseneder, M.M., Arrieta, J.M., Muyzer, G., Winter, C. and
Herndl, G.J. (1999) Optimization of terminal-restriction fragment
length polymorphism analysis for complex marine bacterioplankton
communities and comparison with denaturing gradient gel electrophoresis. Appl. Environ. Microbiol. 65, 3518^3525.
[41] von Wintzingerode, F., Gobel, U.B. and Stackebrandt, E. (1997)
Determination of microbial diversity in environmental samples: pitfalls of PCR-based rRNA analysis. FEMS Microbiol. Rev. 21, 213^
229.
[42] Van Der Heijden, M.G.A., Klironomos, J.N., Ursic, M., Moutoglis,
P., Streitwolf-Engel, R., Boller, T., Weimken, A. and Sanders, I.
(1998) Mycorrhizal fungal diversity determines plant biodiversity,
ecosystem variability and productivity. Nature 396, 69^72.
FEMSEC 1523 11-7-03