Local climatic conditions constrain soil yeast

FEMS Yeast Research, 16, 2016, fov103
doi: 10.1093/femsyr/fov103
Advance Access Publication Date: 13 November 2015
Research Article
RESEARCH ARTICLE
Local climatic conditions constrain soil yeast diversity
patterns in Mediterranean forests, woodlands and
scrub biome
Andrey M. Yurkov1,∗ , Oliver Röhl2,†,‡ , Ana Pontes2,‡ , Cláudia Carvalho2 ,
Cristina Maldonado2 and José Paulo Sampaio2
1
Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Inhoffenstraße 7B, 38124
Brunswick, Germany and 2 UCIBIO-REQUIMTE, Departamento de Ciências da Vida, Faculdade de Ciências e
Tecnologia, Universidade Nova de Lisboa, 2829-516 Caparica, Portugal
∗
Corresponding author: Leibniz Institute DSMZ-German Collection of Microorganisms and Cell Cultures, Inhoffenstraße 7B, 38124 Brunswick, Germany.
Tel: +493512616239; Fax: +493512616418; E-mail: [email protected]
†
Present address: Geobotany, Faculty for Biology and Biotechnology, Ruhr-Universität Bochum, 44780 Bochum, Germany.
‡
These authors contributed equally to this work.
One sentence summary: The authors provide the first comprehensive inventory of soil yeasts in a Mediterranean ecosystem and evaluate the effect of
microclimate factors on yeast community in a transect from humid broadleaf forests to dry maquis.
Editor: Cletus Kurtzman
ABSTRACT
Soil yeasts represent a poorly known fraction of the soil microbiome due to limited ecological surveys. Here, we provide
the first comprehensive inventory of cultivable soil yeasts in a Mediterranean ecosystem, which is the leading biodiversity
hotspot for vascular plants and vertebrates in Europe. We isolated and identified soil yeasts from forested sites of Serra
da Arrábida Natural Park (Portugal), representing the Mediterranean forests, woodlands and scrub biome. Both cultivation
experiments and the subsequent species richness estimations suggest the highest species richness values reported to
date, resulting in a total of 57 and 80 yeast taxa, respectively. These values far exceed those reported for other forest soils in
Europe. Furthermore, we assessed the response of yeast diversity to microclimatic environmental factors in biotopes
composed of the same plant species but showing a gradual change from humid broadleaf forests to dry maquis. We
observed that forest properties constrained by precipitation level had strong impact on yeast diversity and on community
structure and lower precipitation resulted in an increased number of rare species and decreased evenness values.
In conclusion, the structure of soil yeast communities mirrors the environmental factors that affect aboveground
phytocenoses, aboveground biomass and plant projective cover.
Keywords: yeasts; soils; Mediterranean basin; biodiversity hotspot; Basidiomycetes; microclimate
INTRODUCTION
Yeasts inhabit soils worldwide (Botha 2011; Yurkov, Kemler
and Begerow 2012). Even though first isolations of yeasts from
soils have been made more than a century ago (reviewed by
Guilliermond 1920), our knowledge of the determinants of soil
yeast diversity and density is restricted to a limited number of
studies focused on biotopes like arable fields (e.g. Starkey and
Henrici 1927; Bouthilet 1951; Sláviková and Vadkertiová 2003;
Lynch and Thorn 2006) and a few major forest types (e.g. di
Received: 27 September 2015; Accepted: 10 November 2015
C FEMS 2015. All rights reserved. For permissions, please e-mail: [email protected]
1
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FEMS Yeast Research, 2016, Vol. 16, No. 1
Menna 1965; Sláviková and Vadkertiová 2000; Maksimova and
Chernov 2004; Mestre et al. 2011; Yurkov, Kemler and Begerow
2012). As a consequence, many biotopes and soil types still lack
an inventory of the correspondent yeast community, a situation
that is further complicated by the difficulty in tracing species
in older publications due to changing species concepts and different nomenclatures. In the last few decades, the use of ribosomal DNA sequences greatly improved yeast identification
and increased the depth of ecological studies. Moreover, species
recognitions and comparisons across different studies become
possible through sequence data deposited in public repositories
such as NCBI GenBank and MycoBank.
In addition to their contribution to biodiversity, soil yeasts
are gaining increasing importance in biotechnology as enzyme
producers and as sources of oils (e.g. Buzzini and Margesin 2014;
Schulze et al. 2014; Tanimura et al. 2014). However, undersampling strongly limits the discovery of new soil yeast species
(e.g. Yurkov, Kemler and Begerow 2011) and consequently yeast
diversity in most soil types remains largely unknown.
Forest biotopes harbour diverse above- and belowground cultivable yeast populations predominantly consisting of basidiomycetous yeasts (Sláviková and Vadkertiová 2000; Maksimova
and Chernov 2004; Fonseca and Inácio 2006; Yurkov, Kemler and
Begerow 2012; Yurkov et al. 2015a). According to current knowledge, the type of forest determines the size, diversity and structure of the yeast community (reviewed in Yurkov et al. 2015a).
However, different types of forests occur in distinct climatic
zones and this makes the assessment of yeast biodiversity biased by the effects of local climatic parameters, both aboveground and in soils or soil litter. Chernov (2005) and Vishniac
(2006) investigated the structure of the community of soil yeasts
along vast latitudinal gradients and reported that species composition changed significantly with rainfall values. However, it
is important to document that the most pronounced differences
were observed between sampling sites in regions that were distantly separated, i.e. in a different natural zone and under a different type of vegetation. To our knowledge, there was no study
designed to specifically evaluate the effects of either vegetation
properties or climatic conditions on soil yeasts. However, there
is some indirect evidence that the two factors are indeed important constraints of the yeast community. Yeast communities isolated in a spruce forest (zonal vegetation type) for example differed from those observed in birch and alder forests (intrazonal
vegetation type) (Maksimova and Chernov 2004). Similarly, the
yeast community of Sphagnum mosses present in forest ground
cover showed a gradual change along the temperature-moisture
ecocline between boreal spruce forest (zonal) and swamp (intrazonal) biotopes (Kachalkin and Yurkov 2012). In agreement with
those observations, soil yeast communities isolated from clear-
cut planted spruce forests differed substantially from the yeast
populations found in near-natural unmanaged beech forests
(Yurkov, Kemler and Begerow 2012). It was also observed that
total yeast numbers and diversity did not depend on basic soil
properties (Birkhofer et al. 2012), thus suggesting the importance
of aboveground biotope properties for the yeast community.
Here we report on a study designed to assess the effects of
local microclimatic conditions on basic parameters of soil yeast
communities. The goal of this investigation was to study abundance, diversity (observed and estimated), composition and
structure (evenness, number of singletons, proportion of rare
species) of the yeast communities in soils characterized by a
highly similar vegetation cover but strong differences in precipitation levels. The study was performed in Serra da Arrábida Natural Park (Portugal) on sites previously studied for phylloplane
yeasts (Inácio et al. 2002). This study also provides the first comprehensive inventory of cultivable soil yeasts in a Mediterranean
ecosystem and includes in the same sampling strategy the three
most relevant Mediterranean biomes—forests, woodlands and
scrubland vegetation. According to the classification of World
Wide Fund for Nature, the Mediterranean forests, woodlands and
scrub biome (PA1214 ecoregion), together with four other scrubland types, support more than 25 000 species of plants, of which
more than half are endemic. Similarly to other countries, in Portugal this Eco-region is threatened by urbanization, agriculture,
frequent fires and invasive species (Olson and Dinerstein 1998).
This is the first study providing a comprehensive analysis of soil
biodiversity in this type of ecosystem.
MATERIALS AND METHODS
Study sites and sampling
The Serra da Arrábida is a small chain of limestone outcrops with a maximum elevation of 500 m running in an
east-west direction, parallel to the Southern edge of the
Setúbal peninsula (Fig. 1) and falling off as steep cliffs into
the sea. It encompasses different areas with specific formations of typical Mediterranean vegetation of great interest,
which has led to the creation of the Arrábida Natural Park
in 1976 (http://www.icnf.pt/portal/ap/p-nat/pnar). The region is
generally characterized by an Atlantic-Mediterranean climate
and consists of different microclimatic areas determined by
the varying orientation of the landscape and orography. The
area is characterized by a Mediterranean climate with 14–16◦ C
average temperatures and 600–700 mm annual precipitation
(Guerreiro 2008). Two rather contrasting habitats can be found
on the northern and southern slopes of the Arrábida mountain
range, a humid site with more pronounced Atlantic influence
Palmela
Lisbon
Setúbal
Arrábida Natural Park
Azeitao
10 km
rea
da
mi
Hu
y
Dr
to
id
um
50 km
bh
Su
Sesimbra
1 km
N1: Humid, forest
Figure 1. Location of study sites in the Serra da Arrábida Natural Park.
S1: Subhumid, forest
S2: Dry, shrubland
Yurkov et al.
located on the northern slope and a subhumid to semiarid
site on the southern slope. Soils are red Mediterranean soils
on calcareous or dolomitic bedrock, specifically Rendzic Leptosols associated with Rendzic Cambisols on the northern slope,
and Calcic Cambisols with rock outcrops on the southern slope
(Schrittenlocher 1997). According to the information available
(Schrittenlocher 1997; Guerreiro 2008), topsoils under humid and
semihumid forest are moist (Topographic Wetness Index (Beven
and Kirkby 1979), TWI = 13–17) and are characterized by high
values of available water capacity (140–200 mm) at root depth.
In contrast, soils under scrubland vegetation are dry (TWI 3–5)
and have poor available water capacity of 50–100 mm (Schrittenlocher 1997; Guerreiro 2008). Soils in the areas studied are
slightly acid to neutral, pH = 6–7 (Schrittenlocher 1997). Other
climatic parameters and basic soil properties of the study area
have been published elsewhere (Schrittenlocher 1997; Guerreiro
2008).
Differences in precipitation have a strong effect on vegetation cover resulting in a gradual change of vegetation from
humid forest (northern slope) to semihumid chaparral forest (southern slope, valleys) and dry patchy maquis scrubland
(southern slope, open areas). The predominant plant cover consists of forests and shrub formations largely composed of the
same plant species, namely oaks (Quercus coccifera, Q. faginea,
Q. ilex, Q. suber), Montpellier maple (Acer monspessulanum), juniper (Juniperus navicularis), wild olive (Olea europaea), turpentine tree (Pistacia lentiscus), tree heath (Erica arborea), strawberry tree (Arbutus unedo), cistus (Cystus albidus) and phillyrea
(Phillyrea latifolia). These plant species provide a good representation of the ancient Mediterranean vegetation and may
probably represent remnants of the primordial forest formations that developed under the specific bioclimatic conditions of
Arrábida.
In September 2013, soils were collected from three different
areas of the Serra da Arrábida, in humid forest (northern slope,
plot N1), in semihumid chaparral forest (Mata do Solitário, plot
S1) and in maquis scrubland (Alto do Jaspe, plot S2) (Fig. 1). On
each 20 × 20 m plot, four 10-m long transects were made from
the centre of the plot to the four cardinal directions (north, east,
south and west). Soils were collected in equal proportions every
2 m along a transect resulting in five soil samples combined in a
composite sample (100–200 g in total) and making a total of four
composite soil samples per plot. Coarse woody debris, roots and
stones (>5 mm) were aseptically removed in the field.
Soil samples were placed in sterile paper bags, transferred
to the laboratory and kept at –80◦ C before analysis. Prior to the
analysis, soils were slowly thawed at 4◦ C and sieved sequentially
through 5, 2 and 1 mm meshes. Roots, stones and woody particles were thereby removed in every step. Five subsamples were
randomly taken (20 subsamples per plot), from the four composite samples collected on a single plot, suspended in sterile water
and plated on three plates each, 180 plates in total. The use of
composite soil samples gave reliable results in previous surveys
(e.g. Yurkov, Kemler and Begerow 2011) and was also tested on
a few samples for Serra da Arrábida soils in the present study
(data not shown).
Isolation of cultures
Frozen soil samples were thawed at 4◦ C overnight and placed
in 50 ml plastic tubes, suspended 1:5, 1:10 and 1:20 (w/v) in
sterile water and shaken on an orbital shaker at 200 rpm for
1 hour. An aliquot of 0.15 ml was distributed on the surface
of glucose-yeast extract-peptone agar acidified with lactate to
3
pH 4.5 (Yurkov, Kemler and Begerow 2011). Plates were incubated at room temperature for 2 days and then at lower temperature (4◦ C) to prevent fast development of moulds. Plates were
checked after 7, 14 and 21 days of incubation. Colonies were differentiated into macromorphological types using dissection microscopy, counted and one to two representatives of every colony
type per plate were purified.
Identification of cultures
Detailed protocols describing DNA extraction, amplification, purification and sequencing are given by Yurkov, Kemler and
Begerow (2011) and Yurkov, Kemler and Begerow (2012). In short,
PCR fingerprinting with minisatellite-specific oligonucleotides
derived from the core sequence of bacteriophage M13 with the
sequence given by Sampaio et al. (2001) or microsatellite-specific
oligonucleotides (GTG)5 , (ATG)5 and (GAC)5 as single PCR primer
(Gadanho and Sampaio 2002) were used to group pure cultures.
Strains showing identical electrophoretic profiles were considered as conspecific and only one to two representatives of them
were chosen for further identification by sequencing of rRNA
gene regions.
Yeast cultures were identified using nucleotide sequences of
the D1/D2 domains of the large subunit (26S/28S or LSU) rRNA
gene and in a few cases the internal transcribed spacer (ITS) region was also used. The nucleotide sequences were compared
with sequences deposited in the NCBI (www.ncbi.nih.gov) and
CBS (www.cbs.knaw.nl) databases, respectively. Nucleotide sequences were deposited in GenBank under the accession numbers given in Table 1.
Statistical data analyses
Yeast quantity and community structure were determined for
each subsample. Yeast quantity was calculated as colony forming units (CFU) per gram of soil at natural humidity. Frequency
of occurrence was calculated as the number of samples where
a species was observed as a proportion of the total number of
samples. Relative abundance was calculated as proportion of a
particular species in the sample and is based on colony counts.
Species diversity was assessed using Shannon diversity index
and species evenness was assessed using Pielou community
evenness index. Additional details on these methods are given
by Yurkov, Kemler and Begerow (2012).
Cultivation results from a total of 428 plates were included
in the final analysis. Results from other subsamples and culture
plates were not included in the final dataset, as they yielded no
yeast cultures either due to low fungal quantity in a particular
replicate or due to fast development of moulds, which made isolation and appropriate quantification of yeasts difficult.
Species accumulation curves were calculated with EstimateS
9.1.0 using 100 randomizations and sampling without replacement, and the upper limit for infrequent species was set to five
samples (Colwell et al. 2012). As distinct yeast species could form
colonies with similar morphology and thus make the separation
into different types doubtful, we used only presence/absence
(incidence data) in our community matrix. The latter did not
depend on the morphological differentiation and relied solely
on molecular species identification. Four estimators of species
richness were used: Chao 2 richness estimator, ICE incidencebased coverage estimator, first-order Jackknife richness estimator (Jackknife 1) and Bootstrap richness estimator. Other details
on the use of species richness estimators are given by Yurkov,
Kemler and Begerow (2011).
Cryptococcus aerius
Cryptococcus aerius 2
Cryptococcus terreus
Cryptococcus sp. 8
Cryptococcus uzbekistanensis
Cryptococcus sp. 8
Cryptococcus arrabidensis
Cryptococcus sp. 1
Cryptococcus sp. 2
Cryptococcus sp. 9
Cryptococcus magnus
Cryptococcus oeirensis
Cryptococcus sp. 7
Cryptococcus laurentii
Cryptococcus terrestris
Cryptococcus carnescens
Cryptococcus heimaeyensis
Cryptococcus sp. 3
Cryptococcus sp. 4
Cryptococcus cuniculi
Cryptococcus podzolicus
Cryptotrichosporon sp. 1
Trichosporon moniliiforme
Lineage
Filobasidiales
Filobasidiales
Filobasidiales
Filobasidiales
Filobasidiales
Filobasidiales
Filobasidiales
Filobasidiales
Filobasidiales
Filobasidiales
Filobasidiales
Filobasidiales
Tremellales
Tremellales
Tremellales
Tremellales
Tremellales
Tremellales
Tremellales
Tremellales
Tremellales
Trichosporonales
Trichosporonales
Pezizomycotina
Pezizomycotina
Pezizomycotina
Saccharomycotina
Saccharomycotina
Saccharomycotina
Saccharomycotina
Saccharomycotina
Saccharomycotina
Saccharomycotina
Saccharomycotina
Saccharomycotina
Saccharomycotina
Saccharomycotina
Basidiomycota, Agaricomycotina
Aureobasidium namibiae
Aureobasidium pullulans
Dothidea sp.
Barnettozyma californica
Candida magnoliae
Candida parapsilosis
Candida quercitrusa
Candida railenensis
Debaryomyces hansenii
Kuraishia molischiana
Lachancea thermotolerans
Meyerozyma guilliermondii
Schwanniomyces polymorphus
Torulaspora delbrueckii
Ascomycota
Indentification results
Aerius
Aerius
Aerius
Aerius
Albidus
Albidus
Arrabidensis
Arrabidensis
Arrabidensis
Arrabidensis
Floriforme
Floriforme
Amylolyticus
Bulleromyces
Bulleromyces
Dimennae
Dimennae
Filobasidiella
Filobasidiella
Kwoniella
Podzolicus
Cryptotrichosporon
Cutaneum
Barnettozyma
Starmerella
Lodderomyces
Kurtzmaniella
Kurtzmaniella
Debaryomyces
Kurashia
Lachancea
Meyerozyma
Schwanniomyces
Torulaspora
Clade
OR 177
OR 727
OR 263
OR 721
OR 812
OR 67
OR 255
OR 78
OR 402
OR 262
OR 759
OR 826
OR 975
OR 333
OR 780
OR 129
OR 313
OR 918
OR 849
OR 338
OR 981
OR 395
OR 562
OR 431
OR 756
OR 1009
OR 575
OR 46
OR 435
OR 191
OR 687
OR 547
OR 554
OR 967
OR 506
OR 363
OR 446
Strain ID
PYCC 6815
PYCC 6809
PYCC 6483
PYCC 6814
PYCC 6805
PYCC 6816
PYCC 6486
PYCC 6482
PYCC 6481
PYCC 6817
PYCC 6806
PYCC 6810
PYCC 6480
PYCC 6919
PYCC 6812
PYCC 6477
PYCC 6813
PYCC 6811
Collection ID
Taxon example
KT225566
KT225567
KT304207
KT314198
KT253546
KT253545
KT253538
KT314191
KT314192
KT253539
KT304206
KT253541
KT314197
KT304205
KT253546
KT253540
KT304204
KT314193
KT314194
KT304202
KT253542
KT314199
KT304216
KT304200
LN906592
KT314203
KT225561
KT304199
KT225562
KT225563
KT225565
KT304211
KT253550
KT253551
KT261409
KT253548
KT261411
GenBank
KC433824
FR716531
HF558655
HF558655
JX188136
JX188127
AF181535
EU002810
FN428974
FN428974
JX188126
AM160646
KM555196
AY315663
FN428902
HG421433
HG421432
JN939462
JN939461
EU002791
FN428938
KP020115
FN868265
FN824492
FJ150942
GQ153222
FR772338
KJ630501
HF545671
KF830174
JX188108
HF545662
DQ128167
CU928180
JX188191
FN545820
HE799671
Closest match
99%, AF075486
99%, AF075486
99%, AF075479
99%, AF075479
99%, AF181508
97%, FJ473376
100%, AF181535
97%, AF181535
98%, AF181535
98%, AF181535
99%, AF181851
100%, AF181519
94%, AB261011
99%, FN689393
100%, LK023756
100%, AB035054
100%, DQ000317
96%, AF075484
99%, AF105391
99%, DQ333885
99%, AF075481
97%, AY550002
100%, HE616749
99%, FJ150937
100%, FJ150942
97%, AY930108
100%, U75957
99%, U45722
100%, U45754
99%, U45831
99%, U45800
100%, JN940504
100%, U70178
99%, JQ689022
99%, U45709
100%, AB054994
100%, AF105391
Closest type
GenBank accession numbers
1.04
–
18.57
1.56
1.56
s.i.
–
2.08
–
–
–
–
–
1.04
s.i.
–
1.04
–
–
s.i.
1.56
–
s.i.
5.73
–
–
1.04
–
s.i.
4.69
–
1.56
s.i.
3.65
18.23
1.56
s.i.
Plot N1
4.85
1.21
24.24
1.21
–
–
2.42
–
–
s.i.
–
–
–
–
–
–
–
–
–
–
–
–
–
1.21
–
–
–
–
–
6.06
1.21
–
–
s.i.
13.33
s.i.
–
Plot S1
Frequency, %
s.i.
–
26.27
4.31
8.24
–
1.57
s.i.
–
1.96
s.i.
–
s.i.
s.i.
s.i.
–
3.92
s.i.
–
s.i.
s.i.
–
1.57
3.14
s.i.
–
0.78
s.i.
–
–
–
–
3.14
s.i.
–
–
Plot S2
Table 1. Yeast species inventory and frequency of occurrence of soil yeasts isolated three forest types. Total quantity, species richness, diversity and community evenness indices are provided
below.
4
FEMS Yeast Research, 2016, Vol. 16, No. 1
Rhodotorula slooffiae
Curvibasidium cygneicollum
Curvibasidium pallidicorallinum
Curvibasidium sp.1
Leucosporidium scottii
Rhodosporidium babjevae
Rhodotorula mucilaginosa
Sporobolomyces roseus
Rhodotorula sp. 1
Rhodotorula sp. 2
Species richness, N
Shannon diversity index, H
Pielou evenness index, J
Frequent species (>10%), %
Rare species (<1%), %
Singletons, N
Basidiomycota, Pucciniomycotina
Cryptococcus ramirezgomezianus
Cryptococcus sp. 5
Cryptococcus sp. 6
Holtermanniella takashimae
Cystofilobasidium capitatum
Cystofilobasidium sp. 1
Cystofilobasidium sp. 2
Cystofilobasidium sp. 3
Cystofilobasidium sp. 4
Guehomyces pullulans
Cryptococcus huempii
Indentification results
Table 1. (Continued).
Cystobasidiomycetes
Mycrobotryomycetes
Mycrobotryomycetes
Mycrobotryomycetes
Mycrobotryomycetes
Mycrobotryomycetes
Mycrobotryomycetes
Mycrobotryomycetes
Mycrobotryomycetes
Mycrobotryomycetes
Trichosporonales
Trichosporonales
Trichosporonales
Holtermanniales
Cystofilobasidiales
Cystofilobasidiales
Cystofilobasidiales
Cystofilobasidiales
Cystofilobasidiales
Cystofilobasidiales
Cystofilobasidiales
Lineage
Sporidiobolales
Cystobasidiales
Curvibasidium
Curvibasidium
Curvibasidium
Leucosporidiales
Sporidiobolales
Sporidiobolales
Sporidiobolales
Cystofilobasidium
Cystofilobasidium
Cystofilobasidium
Cystofilobasidium
Cystofilobasidium
Guehomyces
Huempii
Humicola
Humicola
Humicola
Clade
OR 1010
OR 442
OR 860
OR 28
OR 548
OR 337
OR 228
OR 157
OR 209
OR 742
OR 335
OR 1016
OR 701
OR 241
OR 124
OR 392
OR 240
OR 238
OR 878
OR 523
OR 30
Strain ID
PYCC 6808
PYCC 6818
PYCC 6807
PYCC 6856
PYCC 6804
PYCC 6484
Collection ID
Taxon example
KT261410
KT304209
KT304210
KT314200
KT261408
KT304213
KT304214
KT304215
KT314204
KT261412
KT253543
KT314195
KT314196
KT304212
KT253547
KM409623
KM409621
KT314201
KT314202
KT253549
KT304217
GenBank
AB052212
JX188149
JX188150
JX188149
AF070419
JX188219
KF411535
AM160644
KC006703
KF411559
HF558654
KP020115
FN824491
JX188168
JF501392
FN667853
EU002815
KC006882
KC006882
FN868259
AF189844
Closest match
99%, AF189965
99%, AF189928
100%, AF444736
99%, AF189950
100%, AF070419
99%, AF070420
100%, AF070432
100%, AF070441
91%, AY212993
95%, AF070432
100%, AB126584
97%, AY550002
97%, AB126586
100%, FM242574
99%, AF075465
98%, AF075465
98%, EU085532
91%, EU085532
91%, AF075465
100%, AF105394
99%, AF189844
Closest type
GenBank accession numbers
–
2.6
7.81
1.56
1.56
s.i.
8.33
–
–
–
31
3.08
0.87
6
26
9
5.73
–
–
–
–
–
–
–
–
2.6
s.i.
Plot N1
–
1.82
3.03
s.i.
–
–
9.09
s.i.
s.i.
–
25
2.81
0.86
8
32
8
–
–
4.24
s.i.
1.21
6.67
5.45
s.i.
–
7.88
–
Plot S1
Frequency, %
s.i.
–
9.02
9.8
–
s.i.
13.33
s.i.
–
0.78
34
2.92
0.8
6
59
17
s.i.
s.i.
–
–
1.57
2.35
–
–
1.18
–
0.78
Plot S2
Yurkov et al.
5
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FEMS Yeast Research, 2016, Vol. 16, No. 1
Candida parapsilosis
Cryptococcus uzbekistanensis
Curvibasidium cygneicollum
Cryptococcus terrestris
Schwanniomyces polymorphus
Cryptococcus ramirezgomezianus
Guehomyces pullulans
Cryptococcus huempii
N1
Rhodosporidium babjevae
Cryptococcus sp. 1
Candida quercitrusa
Cryptococcus sp. 8
31 species
Aureobasidium namibiae
Cryptococcus aerius
Cryptococcus terreus
S2
Curvibasidium pallidocorallinum
S1
Curvibasidium sp. 1
Lachancea thermotolerans
Meyerozyma guilliermondii
Rhodotorula mucilaginosa
34 species
25 species
Incidence
15 - 11 %
Cystofilobasidium capitatum
10 - 5 %
Cystofilobasidium sp. 1
4-2%
Sporobolomyces roseus
1-0%
Figure 2. Total species richness, dominating and shared yeasts species isolated from the three plots. Grey shades show average frequency of occurrence of common
yeast species. Colour codes follow those of Fig. 1.
RESULTS
All analysed soils yielded yeasts. Highest total yeast counts values varied from 1.3 × 105 (plot S1) to 1.3 × 106 (plot S2) CFU per
gram of soil at natural humidity. A total of 613 cultures were
isolated and identified to 57 yeast species, 13 belonging to the
Ascomycetes and 44 to the Basidiomycetes (Table 1). Only eight
species (14%) occurred in all three sampling sites. The highest
number of species recovered in a single plot was 34 (59% of the
total number of species found). These values appear to reflect
contrasting environmental conditions in the study area.
The most species-rich community (34 species) was that of
soil under dry maquis scrubland (plot S2) followed by humid forest community (31 species, plot N1) and that of semihumid chaparral forest (25 species, plot S1). In all three plots, basidiomycetous yeasts prevailed over ascomycetous species (Fig. 2). The
most frequent basidiomycetous species were Cryptococcus terreus
(plot N1 and S1), Rhodotorula mucilaginosa (plot S1) and Cr. aerius
(plot S2). Among ascomycetous yeasts, Candida quercitrusa (plots
N1 and S1), Meyerozyma guilliermondii (plots N1 and S1), Aureobasidium namibiae (plots N1 and S2) and Lachancea thermotolerans
(plots N1 and S2) were the most frequent species (Fig. 2).
The Pielou evenness index that compares the proportion of
the different species in the community ranged between 0.87 and
0.80, which indicates that structure of the yeast communities in
the three plots was not even (Table 1). The class of most frequent
species (those with >10% of isolates) had the same number of
representatives in all three plots: two species or 6–8% of the total
richness. While the majority of species in forested sites (N1 and
S1) were found at frequencies ranging from 1% to 10%, 21 species
(68% of species) in plot N1 and 15 species (60% of species) in plot
S1, the majority of species (20 species, 59%) isolated from dry
scrubland (plot S2) were rare (often singletons) and were found
with a frequency of less than 1%. Shannon diversity index reflects both species richness and community structure. The highest diversity value was recorded for humid forest soil (H = 3.08,
plot N1) followed by dry maquis scrubland (H = 2.92, plot S2) and
semihumid chaparral forest (H = 2.81, plot S1). Despite the substantial difference in the observed species richness values between the two plots located on the southern slope (25 and 35
species in plots S1 and S2, respectively), the Shannon diversity
indices calculated for these plots were very close and reflected
little contribution of rare species to soil yeast communities.
Diversity estimations using Chao 2, ICE, first-order Jackknife
and Bootstrap estimators predict up to 80 yeast species to be
present from all three investigated plots (Fig. 3). Species richness curves obtained with Chao 2 and ICE estimators were
close to saturation after the given sampling effort. Chao 2 estimator resulted in the highest diversity values. The observed
value of 60 species laid within 75%–90% of the predicted species
richness values (depending on the estimator used) showing
that our study provides a reliable basis for yeast species richness assessment in the studied soils. Estimations performed for
each sampling site suggest that the cultivation approach used
s results in species rarefaction curves that are close to saturation
for soils in the two forested areas (plots N1 and S1) but not for soil
Yurkov et al.
50
All Plots
Chao 2
Jack 1
ICE
80
Bootstrap
60
40
Number of species, N
Number of species, N
100
20
0
Plot N1
Jack 1
ICE
Chao 2
Bootstrap
40
30
20
10
0
50
100
150
200
0
250
Number of sub-samples
40
0
70
Plot S1
25
50
75
Number of sub-samples
100
Plot S2
Chao 2
Jack 1
ICE
Chao 2
Bootstrap
30
20
10
Number of species, N
Number of species, N
7
60
ICE
Jack 1
50
Bootstrap
40
30
20
10
0
0
25
50
75
Number of sub-samples
100
0
0
25
50
75
Number of sub-samples
100
Figure 3. Randomized species accumulation curves for the total soil yeast community of the Serra da Arrábida soils and for each of the three plots (N1, S1 and S2)
obtained with incidence-based coverage (ICE), Chao 2, first-order Jackknife (Jack 1) and bootstrap richness estimators. Shadowed areas correspond to the 75% expected
diversity cut-off. Colour codes follow those of Fig. 1.
associated with scrubland vegetation (plot S2) (Fig. 3). Species
richness estimators calculated similar values for both forest
types (Fig. 3), i.e. 40–43 species in plot N1 and 29–34 species
in plot S1, respectively. In soils under scrubland vegetation, estimated species richness values varied largely from 45 to 64
species reflecting a contradictory contribution of rare species
to the total diversity. Overall, species richness estimators performed differently depending on the soil yeast community
structure. Increasing number of rare species resulted in higher
species richness values predicted by Chao 2 and ICE estimators,
which distinguish between rare and frequent species.
A total of 57 yeast species were isolated and identified during
this study. They belong to four lineages of Fungi, Pezizomycotina
(2 species), Saccharomycotina (11 species), Agaricomycotina (34
species) and Pucciniomycotina (10 species). According to the
genetic distances obtained with sequences deposited in NCBI
GenBank and MycoBank databases, 20 yeast taxa represented
potential new species (Table 1). Detailed analysis and formal description of these new species will be the aim of future studies.
While many putative new species were isolated in low frequencies, a few species (e.g. Cystofilobasidium sp. 1 in S1 and S2 plots,
and Cystofilobasidium sp. 2 in S1 plot, respectively) were rather
frequent and were isolated from different plots.
DISCUSSION
Current estimations suggest that there are 1.5–5.1 million fungal species, from which only a small part (about 100 000 species)
has been described (Blackwell 2011; Taylor et al. 2014). Furthermore, in some substrates such as plants and soils the
number of expected fungi may exceed the number of plants
by 10:1 (Blackwell 2011). Presently, culture-independent surveys of soil fungi receive much attention as the availability of
high-throughput sequencing techniques is constantly increasing. Similarly to other groups of soil microorganisms, diversity values of fungal taxa (expressed as molecular OTUs) are
high (e.g. Bueé et al. 2009; Wubet et al. 2012; Vořı́šková et al.
2014). Phylogenetic lineages represented by fungi with yeast
stages are regularly present in sequence (or clone) libraries but
despite their high occurrence they are rarely identified to the
species level and instead are assigned to large polyphyletic genera such as Cryptococcus and Rhodotorula. In other cases, environmental sequences matching those of the tremellomycetous
yeasts Cr. aerius, Cr. terreus, Cr. terricola, Cr. podzolicus, Trichosporon
dulcitum, T. porosum and Guehomyces pullulans are among the
most frequent soil OTUs revealed in culture-independent surveys (e.g. Lynch and Thorn 2006; Bueé et al. 2009; Taylor et al.
2014; Vořı́šková et al. 2014). All these widespread pedobionts
were also isolated during numerous culture-dependent studies (e.g. Wuczkowski and Prillinger 2004; Vishniac 2006; Mestre
et al. 2011; Yurkov, Kemler and Begerow 2011, 2012; Yurkov et
al. 2012). Therefore, in spite of the growing number of soil biodiversity assessments using high-throughput sequencing techniques, none of them has yet reported a substantial uncultured
diversity within the different phylogenetic lineages that include
yeasts.
8
FEMS Yeast Research, 2016, Vol. 16, No. 1
This study provides the first soil yeast species inventory in
the Mediterranean forests, woodlands and scrub biome, which is one
of the major Mediterranean biomes. Our study yielded yeasts
that are frequently reported from soils worldwide, namely
Cr. aerius, Cr. terreus, Cr. podzolicus, G. pullulans and T. moniliiforme,
all members of the Basidiomycota, and Barnettozyma californica,
Debaryomyces hansenii, M. guilliermondii and Schwanniomyces polymorphus from the Ascomycota (e.g. Botha 2006; Vishniac 2006;
Yurkov, Chernov and Tiunov 2008; Mestre et al. 2011; Yurkov,
Kemler and Begerow 2012).
A few species isolated in the present study provide a link
between above- and belowground communities. The following
yeasts were previously found on plant material collected in
Serra da Arrábida: Cr. carnescens, Cr. flavescens, Cr. magnus, Cr.
oierensis, Curvibasidium cygneicollum, Cystobasidium slooffiae, Rhodosporidium babjevae, R. mucilaginosa and Sporobolomyces roseus
(Inácio 2003; Sampaio et al. 2004). These yeasts were isolated
from aboveground in high numbers and represent in our opinion typical transient species that are introduced in the soil habitat with falling leafs or other dying plant material. The two ascomycetous yeasts C. quercitrusa and C. railenensis can reflect the
type of forest as they were previously reported in association
with oaks (e.g. Isaeva et al. 2009; Lachance et al. 2011), and L. thermotolerans was repeatedly recovered from oak bark using a selective medium (Sampaio and Gonçalves 2008). A few yeasts found
in Serra da Arrábida soils were previously isolated by other scientists in Portugal and are deposited in PYCC, e.g. Cr. aerius,
Cr. podzolicus, Cr. terreus, Cu. cygneicollum, L. thermotolerans, M. guilliermondii and S. occidentalis.
Analysis of nucleotide sequences demonstrated that out of
the 57 yeast species that we found, 20 (35%) showed low identity to any known species and may thus represent novel taxa.
These results are in agreement with the previous observation
by Yurkov, Kemler and Begerow (2012) who showed beech forest
soil in Germany to harbour many undescribed species. Similarly
to other studies, yeasts of the genus Cryptococcus accounted for
the highest diversity and were members of the following clades
and lineages: Albidus, Magnus (Floriforme), Aerius, Arrabidensis in Filobasidiales, and Aureus, Filobasidiella, Kwoniella and
Victoriae in Tremellales (Table 1). Remarkably, this study yielded
two new species, represented by strains OR849 and OR918, showing close affinity to Cr. sensu stricto, i.e., the Filobasidiella clade,
the group comprising the human pathogens Cr. neoformans and
Cr. gattii.
Nucleotide sequences of strains of two typical soil-related
species Cr. aerius and Cr. terreus also showed some deviation from
those of type strains. However, a reliable analysis of relationships within these two species groups is difficult as ribosomal
gene fragments show little interspecific divergence (Scorzetti
et al. 2002; Scholten 2011; A Yurkov unpublished data). According
to our results, strains of Cr. aerius and Cr. terreus show as many
as 12 and 10 nucleotide substitutions in LSU (D1/D2 domains
of 26S) rRNA, respectively. The first common DNA-Barcode for
Fungi, the ITS region, is less variable than LSU as shown by
Schoch et al. (2012) and our own results, and shows four and
three nucleotide substitutions in Cr. aerius and Cr. terreus, respectively. Thus, a combination of the two genetic markers traditionally used in yeast biodiversity assessments may be insufficient to resolve yeast species presently comprised within Cr.
aerius and Cr. terreus. This assumption is supported to some extent by results of the recent multilocus sequence analysis of
Cr. flavescens –Cr. terrestris species complex (Yurkov et al. 2015b).
Analysis of five loci including genes involved in sexual reproduction showed the limited utility of ribosomal ITS and LSU
sequences for species discrimination and resulted in the discovery of two new cryptic species. Studies by Fonseca, Scorzetti
and Fell (2000) and Scorzetti et al. (2002) made a solid basis for
sequence-based species delimitation in Filobasidiales, including
species in the Aerius clade. Our observations suggest that relationships within this group need to be resolved with a multigene
approach in the future.
Another interesting observation is the unexpected high occurrence and diversity of yeasts of the genus Cystofilobasidium.
Besides Cy. capitatum, a species frequently reported from forest litter and dried plant material (e.g. Babeva and Chernov
1995), the present study yielded several potential new species
(Fig. 4). Some of these yeasts were observed in high numbers,
thus questioning their allochtonous origin in soil, as previously
suggested for Cy. capitatum (Babeva and Chernov 1995). Specifically Cystofilobasidium sp. 1 and 2 belong to the group of frequent
species isolated from soils under S1 and S2 vegetation. Furthermore, queries in the PYCC database (http://pycc.bio-aware.com/)
yielded a strain conspecific to Cystofilobasidium sp. 2 that was
also isolated in Serra de Arrábida by Joao Inácio (PYCC database,
GenBank EU002815). This suggests that yeasts of the genus
Cystofilobasidium may be regular inhabitants of Mediterranean
forests, woodlands and scrub biome in Portugal.
The yeast community of Mediterranean soils is
hyperdiverse
The term biodiversity hotspot was introduced to distinguish biogeographic regions with a significant reservoir of biodiversity, total richness and proportion of endemic species (e.g. Myers et al.
2000). In Europe, the Mediterranean basin has been recognized
as the primary biodiversity hotspot with 45% of endemic species
of plants and vertebrates (Olson and Dinerstein 1998; Myers et
al. 2000). Unlike plants and animals, microorganisms inhabiting natural biotopes in this region received little attention. The
present study reports the first diversity values for Mediterranean
forests, woodlands and scrub biome.
Yeasts are found in soils worldwide and data available from
previous studies suggest that soil yeast communities are species
poor in a single location (low alpha-diversity) but very dissimilar
on a broader spatial scale (high beta-diversity). To date, analysis of forest soils yielded 18–26 yeast species isolated from
a single biotope, as discussed in Yurkov, Kemler and Begerow
(2011). Variation among these values can be due to the different methods used for yeast identification but cryptic species
are not considered to greatly influence these numbers (Yurkov,
Kemler and Begerow 2011; Yurkov et al. 2015a). In the present
study, a few Cryptococcus spp. members of Arrabidensis, Humicola and Kwoniella clades could be considered as cryptic
species but these yeasts were rarely observed in the same plots
(Table 1). On average, boreal forest soils are characterized by
lower yeast species richness values than broadleaf forest soils
(Maksimova and Chernov 2004; Wuczkowski and Prillinger 2004;
Yurkov, Kemler and Begerow 2012). In the present study, we
found 57 yeast species, a value that is 2- to 3-fold higher than
the values reported before, namely 20–25 species in Russia (Maksimova and Chernov 2004; Golubtsova, Glushakova and Chernov 2007; Glushakova, Kachalkin and Chernov 2015), 18 species
in Slovakia (Sláviková and Vadkertiová 2000), 19–24 species in
Austria (Wuczkowski and Prillinger 2004), 10–26 species in Germany (Yurkov, Kemler and Begerow 2011, 2012; Yurkov et al.
2012) and 22 species in Argentina (Mestre et al. 2011). Because
Yurkov et al.
9
OR158
OR273
OR242
OR185
OR392
69 OR407
Cystofilobasidium sp. 1
OR694
OR394
99
OR223
OR428
Cystofilobasidium “capitatum” MOM_884 (HG421444)
95
OR398
Cystofilobasidium capitatum CBS 6358T (AF075465)
87
97
90
99
74
OR124
OR408
OR411
Cystofilobasidium feraegula CBS 7201T (AF075487)
Cystofilobasidium lacus-mascardii CBS 10642T (AY15864)
Cystofilobasidium macerans CBS 2206T (AF189848)
Cystofilobasidium infirmo-miniatum CBS 323T (AF075505)
68
Cystofilobasidium bisporidii CBS 6346T (EU085532)
OR934
100 OR878
99
100
Cystofilobasidium sp. 4
Cystofilobasidium “capitatum” HAI-Y-699 (KC006882)
OR238
98
Cystofilobasidium sp. 3
Cystofilobasidium sp. 8C5 (KM275210)
Cystofilobasidium sp. EX-F1547 (DQ640493)
0.02
100 Cystofilobasidium sp. K146b (HF934016)
OR661
OR233
OR235
Cystofilobasidium sp. 2
OR240
OR282
Cystofilobasidium sp. PYCC 6093 (EU002815)
“Mrakia” curviuscula CBS 9136T (EF118826)
Figure 4. Maximum likelihood analysis (RAxML, GTRCAT option) of an alignment of the LSU (D1/D2 domains) rRNA gene for Cystofilobasidium spp. strains isolated
during this study. The numbers given on branches are frequencies (>50%) with which a given branch appeared in 100 bootstrap replications. The scale indicates the
number of expected substitutions accumulated per site. The tree is rooted with Mrakia curviuscula CBS 9136T .
a direct comparison between studies is difficult due to different species recognition approaches and sampling effort, the
most reliable comparisons of yeast diversity can be achieved
using a restricted number of recent studies (e.g. Wuczkowski
and Prillinger 2004; Vishniac 2006; Mestre et al. 2011; Yurkov,
Kemler and Begerow 2011, 2012; Yurkov et al. 2012; Glushakova,
Kachalkin and Chernov 2015). The only study to date utilizing species richness estimators reported 14–17 yeast species to
be expected from the analysis of soil in a single beech forest
(Yurkov, Kemler and Begerow 2011). Another study that used the
same sampling approach that we used here reported the isolation of 24 species from beech forests in three regions of Germany (Yurkov, Kemler and Begerow 2012). Accordingly, species
richness estimations suggest substantially higher yeast species
richness in the Mediterranean soils that we analysed than in
soils under broadleaf vegetation in Central Europe. The present
study performed in a single biotope representing Mediterranean
forests, woodlands and scrub biome resulted in about 3-fold
higher species richness values than those reported for boreal
and temperate forests. Tropical forests are well recognized for
their extraordinary diversity of plants and animals (e.g. Myers
et al. 2000); however, our knowledge on soil yeasts in these habitats is scarce. The only recent study reporting moderate yeast
diversity values, namely up to 9–11 species isolated from soils
underneath four cloud and rain forests in Costa Rica (Vishniac
2006).
10
FEMS Yeast Research, 2016, Vol. 16, No. 1
The influence of climatic conditions on soil yeast
diversity
Near-natural and unmanaged forests are often characterized
by high heterogeneity of forest and soil cover. Forest alteration
through management activities cause substantial changes also
in belowground microbial communities of broadleaf forests and
affects both prokaryotes and fungi, including yeasts (Birkhofer
et al. 2012; Yurkov et al. 2012; Yurkov, Kemler and Begerow 2012).
Species richness estimations performed in the present study
showed strong differences between plots and suggested a total of 80 yeast species to be expected from soils in Serra da
Arrábida Natural Park. Based on species richness estimations,
maquis scrublands are expected to have the highest diversity,
followed by humid and subhumid forests. The analysis of soil
yeast community structure showed that the occurrence of rare
species accounted for higher species richness estimations for
scrubland soil. Specifically, species-rank distribution and distribution of shared species showed that the number of frequent
species (>10% of total isolates) was equal among plots and that
the frequent species corresponded to 6–8% of the total richness
(Table 1). At the same time the number of species occurring with
1–10% frequency declined from humid forest to chaparral forest
and scrubland. Rare species (<1% of total isolates) were prominent (59% of the total richness) in soils under dry maquis scrubland. Out of 20 rare species detected in scrubland soils, 17 were
singletons and this is twice the number of singletons found in
forest plots (Table 1). These differences in species occurrence
also resulted in decreasing community evenness values from
humid forest (J = 0.87) to scrubland vegetation (J = 0.8) (Table 1).
As mentioned before, the three plots were selected to depict a gradual change of environmental conditions, especially
the level of precipitation. Although the studied plots are characterized by highly similar plant communities, strong differences
in water availability shaped these phytocenoses, and so they differed substantially in properties such as aboveground biomass
and plant projective cover. The humid forest on the northern
slope (plot N1) was very dense with well-developed understory
and decaying wood logs. The semihumid chaparral forest on the
southern slope (plot S1) was located in a valley that on average
provided plants with more water than the neighbouring scrubland areas. Although large trees dominated semihumid forest, it
was more spaced with little understory. In scrublands, the plants
grew in patches and were separated by open land and rocks.
Plants were often suppressed and trees did not develop their
full size although they were still able to grow under such conditions, e.g. oaks, strawberry trees and wild olives. A few studies
have addressed the importance of forest type (dominating tree
species) and forest properties (management history, presence of
decaying wood, etc.) on soil yeast communities. In the present
study, we addressed the influence of local climatic parameters
that do not alter plant species composition but change vegetation properties such as biomass and plant projective cover. The
latter can be also considered as a measure of substrate discontinuity for microfungi as they do not form abundant hyphae and,
thus, are likely to be restricted to a local pool of nutrients in a
microhabitat. Our results suggest that the discontinuity of the
vegetation cover may affect soil microorganisms, exemplified by
yeasts, shifting the structure of the community from the dominance of frequent species to the prevalence of minor and, possibly, transient species. In the present study, we provide evidence
that supports the hypothesis that local climatic conditions can
lead to a substantial alteration of soil yeast communities even
on a small spatial scale.
CONCLUSIONS
Soil-related basidiomycetous yeasts have been recently recognized as promising candidates for biotechnological applications, e.g. as enzyme and oil producers. Despite this relevance,
limited sampling hampers a proper diversity assessment and
consequently the utilization of novel species and strains. The
sampling technique that we have optimized in previous studies
provides a solid basis for the efficient recovery of soil yeasts in
different biotopes. The analysis of cultivable soil yeasts in the
Mediterranean forest, woodland and scrub biome revealed remarkably high yeast diversity values, a finding that is in line
with the current view of the Mediterranean basin as a biodiversity hotspot. Results obtained in the present study challenge the
present knowledge of soil yeast communities as species-poor
assemblages and suggest that diversity patterns follow forest
cover properties and habitat fragmentation.
ACKNOWLEDGEMENTS
Authors are grateful to Álvaro Fonseca for his assistance in plot
selection and sampling and Brian J. Tindall for correcting the
English text.
FUNDING
This work was financially supported by the Fundação para
a Ciência e a Tecnologia, Portugal grant numbers PTDC/BIABIC/4585/2012 and UID/Multi/04378/2013.
Conflict of interest. None declared.
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