Photobiont diversity in lichens from metal-rich substrata based on ITS rDNA sequences.

Abstract

The photobiont is considered as the more sensitive partner of lichen symbiosis in metal pollution. For this reason the presence of a metal tolerant photobiont in lichens may be a key factor of ecological success of lichens growing on metal polluted substrata. The photobiont inventory was examined for terricolous lichen community growing in Cu mine-spoil heaps derived by historical mining. Sequences of internal transcribed spacer (ITS) were phylogenetically analyzed using maximum likelihood analyses. A total of 50 ITS algal sequences were obtained from 22 selected lichen taxa collected at three Cu mine-spoil heaps and two control localities. Algae associated with Cladonia and Stereocaulon were identified as members of several Asterochloris lineages, photobionts of cetrarioid lichens clustered with Trebouxia hypogymniae ined. We did not find close relationship between heavy metal content (in localities as well as lichen thalli) and photobiont diversity. Presence of multiple algal genotypes in single lichen thallus has been confirmed.

Full text

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Photobiont diversity in lichens from metal-rich substrata based
on ITS rDNA sequences
Martin Bac ˇkora,n, Ondˇ rej Peksab,c, PavelˇSkaloudc, Miriam Bac ˇkorova ´d
aInstitute of Biology and Ecology, Department of Botany,ˇSafa ´rik University, Ma ´nesova 23, SK-041 67 Koˇ sice, Slovak Republic
bThe West Bohemian Museum in Pilsen, Kopecke ´ho sady 2, CZ-301 00 Plzeˇ n, Czech Republic
cDepartment of Botany, Charles University, Bena ´tska ´ 2, CZ-128 01 Praha 2, Czech Republic
dInstitute of Biology and Ecology, Department of Cellular and Molecular Biology,ˇSafa ´rik University, Moyzesova 11, SK-040 01 Koˇ sice, Slovak Republic
a r t i c l e i n f o
Article history:
Received 2 March 2009
Received in revised form
11 November 2009
Accepted 17 November 2009
Available online 23 December 2009
Keywords:
Algae
Asterochloris
Cu
Heavy metals
Metal toxicity
Metal tolerance
Trebouxia
a b s t r a c t
The photobiont is considered as the more sensitive partner of lichen symbiosis in metal pollution. For
this reason the presence of a metal tolerant photobiont in lichens may be a key factor of ecological
success of lichens growing on metal polluted substrata. The photobiont inventory was examined for
terricolous lichen community growing in Cu mine-spoil heaps derived by historical mining.
Sequences of internal transcribed spacer (ITS) were phylogenetically analyzed using maximum
likelihood analyses. A total of 50 ITS algal sequences were obtained from 22 selected lichen taxa
collected at three Cu mine-spoil heaps and two control localities. Algae associated with Cladonia and
Stereocaulon were identified as members of several Asterochloris lineages, photobionts of cetrarioid
lichens clustered with Trebouxia hypogymniae ined.
We did not find close relationship between heavy metal content (in localities as well as lichen thalli)
and photobiont diversity. Presence of multiple algal genotypes in single lichen thallus has been
confirmed.
& 2009 Elsevier Inc. All rights reserved.
1. Introduction
Through the world, there are many metal-polluted areas,
including rocks and soils derived from metal mining. Specific
lichen communities occurring on these substrata have been found
(Nash, 1989; Purvis and Halls, 1996; Bac ˇkor and Fahselt, 2004a;
Bana ´sova ´ et al., 2006). Some lichens associated with heavy metal-
rich substrata are common species able to tolerate metals. These
lichens are frequent in both metal polluted as well as unpolluted
areas. However, some lichen species are restricted to heavy-
metal-rich substrata and their distribution reflects the presence of
these substrata (Purvis and Halls, 1996).
Lichens growing in metal-rich environments are known to
accumulate considerable amounts of heavy metals by their thalli.
In the case of copper (Cu), lichen Acarospora rugulosa K¨ orb.
accumulates up to 16% on a dry weight basis (Chisholm et al.,
1987). Lichens Lecidea lactea and A. rugulosa from cupriferous
pyritic rocks in Central Scandinavia contained up to 5% of Cu on a
dry weight basis (Purvis, 1984).
Although presence of Cu is essential for living organisms, like
all other metals it is toxic at high concentrations. Lichen as a
symbiotic unit possesses several mechanisms that detoxify
harmful effects of metal excess in thalli. Exclusion of heavy
metals is one of the most studied and effective processes related
to heavy metal detoxification mechanisms in lichen thalli (Collins
and Farrar, 1978). Cell walls of both bionts are included in metal
exclusion; however, lichens, as a whole symbiotic unit, produce
organic acids and lichen secondary metabolites, which can chelate
metals. However, the extent of all these detoxification mechan-
isms is limited and excess metal can reach plasmalemma and
enter the cells of lichen symbionts, where it is potentially toxic.
When grown aposymbiotically, axenic cultures of lichen algae
(photobionts) seem to be more sensitive to excess heavy metals,
e.g. Cu, than lichen fungi – mycobionts (Bac ˇkor et al., 2006; 2007).
For this reason, photobiont can be a likely key element of lichen
sensitivity/tolerance as a symbiotic unit.
Physiological basis of metal detoxification in lichen is still
poorly known; however photobiont cell walls, free amino acids,
non-protein thiols and proteins (e.g. hsp70) have all been
included in this process (see for review Bac ˇkor and Fahselt,
2008). So far, many physiological and biochemical parameters
were employed as markers for assessment of metal stress in
lichen photobionts, including growth inhibition (Bac ˇkor and
ARTICLE IN PRESS
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journal homepage: www.elsevier.com/locate/ecoenv
Ecotoxicology and Environmental Safety
0147-6513/$-see front matter & 2009 Elsevier Inc. All rights reserved.
doi:10.1016/j.ecoenv.2009.11.002
nCorresponding author. Fax: +421 55 6337353.
E-mail address: martin.backor@upjs.sk (M. Bac ˇkor).
Ecotoxicology and Environmental Safety 73 (2010) 603–612

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Va ´czi, 2002), cytological effects (Tarhanen, 1998; Sanit? a di Toppi
et al., 2005), enzymatic activities (Sanit? a di Toppi et al., 2004),
assimilation pigment composition (Garty et al. 1992; Chettri et al.,
1998), chlorophyll a fluorescence (Branquinho et al., 1997) and
non-protein thiols (Pawlik-Skowron ´ska et al., 2002).
However, it has been found that even photobionts are
differentially sensitive to presence of heavy metals in the
environment. Photosynthesis of lichens containing cyanobacteria
was more sensitive to the presence of Zn, Cd and Cu than that of
lichens with eukaryotic photobionts (Brown and Beckett, 1983)
and cyanobacterial Nostoc photobiont has been found to be more
sensitive to Mn than eukaryotic Dictyochloropsis photobiont
(Paul and Hauck, 2006). The sensitivity of eukaryotic photobionts
also varies. For example, lipid metabolism has been found to be
more affected by Cu and Pb in Coccomyxa, than in Trebouxia
(Gushina and Harwood, 2006).
Photobiont involvement in lichen tolerance to heavy metals
was suggested by Beck (1999), who found that all nine lichen
species of the community Acarosporetum sinopicae on iron-rich
rocks at ‘‘Schwarze Wand’’ (Austria) contained the same photo-
biont, Trebouxia simplex (reported as Trebouxia jamesii in Beck,
1999). However, further taxonomic study of metal tolerant
photobionts is required, related to different chemical types of
substrata, as well as their age and degree of ecological succession.
Existence of metal-tolerant populations of lichen photobionts has
been discovered within other taxa of Trebouxia photobionts.
Evidence that this observed metal tolerance occurs in nature is
supported by successful production of tolerance under laboratory
conditions by gradually increasing, over a 3-year period, the Cu
concentration of the medium. By this way a Cu-tolerant photo-
biont strain was obtained from wild-type Trebouxia erici (UTEX
911) (Bac ˇkor and Va ´czi, 2002). When exposed to excess Cu the
tolerant genotype exhibited uptake, growth rates, pigment
content, membrane integrity, dehydrogenase activity, photosys-
tem II activity, synthesis of free proline and non-protein thiols
that were not significantly different from control photobionts
growing on nutritional media (Bac ˇkor and Fahselt, 2008).
In the present case, DNA sequence data provide us with the
capability to evaluate photobionts in field-collected lichens. Diver-
sity of lichen photobionts in situ has been studied using molecular
markers, including internal transcribed spacer (ITS) region (e.g. Beck
et al., 1998; 2002; Yahr et al., 2004; Hauck et al., 2007).
The main aim of this study was assessment of algal genotype
preference by lichen fungi due to the presence of increased levels
of heavy metals (mostly Cu) in specific, metal-rich copper mine-
spoil heaps derived from the historical mining. Common lichen
species, including members of genus Cladonia, Cetraria and
Stereocaulon, were selected for this study as they grow in both
heavy-metal-polluted as well as unpolluted habitats. In addition
to Cu mine-spoil heaps, we chose for comparison two localities:
first non-polluted by heavy metals and situated near the Cu-
mining area in central Slovakia, and the second, rich in heavy
metals (Cu content is however low here) but extrapolated from
the Slovak localities and thus separated from the local pool of
photobionts.
2.Material and methods
2.1. Collection of material
Specimens of lichens were collected during the years 2006 and 2007 at five
different sites, three Cu mine-spoil heaps in central and eastern Slovakia, rocky
slope in ‘‘Harmanec’’ in Slovakia (control) and former ore-sedimentation basin
near ‘‘Chvaletice’’ in the Czech Republic (Table 1). All the lichen specimens are
deposited in PL (Pilsen, Czech Republic). The present work did not involve humans
or experimental animals.
2.2.Gelnica-Cechy, L’ubietova ´-Podlipa andˇSpania dolina
Three localities represent the Cu mine-spoil heaps derived from the
historical mining activity situated in the mountain areas of central and eastern
Slovakia: Volovske ´ vrchy Mts. (Gelnica-Cechy, 500 m a.s.l, 481500N, 201560E),
Slovenske ´ Stredohorie Mts. (L’ubietova ´-Podlipa, 570–700 m a.s.l., 481450N,
191220E) and Low Tatra Mts. (ˇSpania dolina, 780 m a.s.l., 481490N, 191080E).
The area around L’ubietova ´ andˇSpania dolina especially belonged to the most
important mining centers of Slovakia and Europe. All the localities are strongly
polluted by heavy metals, especially by Cu (concentrations of Cd, Co, Hg, Sb and
other metals are also above the limit values). All the Cu mine-spoil heaps are
more than 200 years old; recent human activity at this places is low; thus the
substrate attributable to historical mining is the main source of metal pollution
in the area. The mine heaps habitats are mostly colonized by a specific small
group of vascular and non-vascular plants, including approximately 30 taxa of
terricolous lichens, creating distinctive plant communities tolerant to heavy
metals (Bana ´sova ´ et al., 2006).
2.3. Harmanec
Lichens were collected from soil and rocks at the rocky slope in Harmanec
(481490N, 191030E), Vel’ka ´ Fatra Mountains, central Slovakia, at approximately
500 m a.s.l.. This area belongs to Vel’ka ´ Fatra National Park, and there is no known
rock mineralization by Cu or other toxic metals.
2.4. Chvaletice
Lichens were collected in two parts of former industrial sedimentation basin
near Chvaletice (250 m a.s.l.; 5012028.57700N, 15126039.361*E), East Bohemia: on
clayey soil along the access road to the sedimentation basin and on dry soil
directly in the sludge bed. Both of these sublocalities are strongly polluted by
heavy metals; excess concentrations were measured especially for Fe, Mn, Zn, Al
and Cd (Kova ´ˇ r, 2004). Except the heavy metal content, the soil in the sludge bed is
characterized by very high salinity and extremely low pH (reaching as low as 3 in
extreme cases). The ore-sedimentation basin was erected in 1952 for deposition of
wastes from the factory producing sulfuric acid from pyrite ore. The basin was
abandoned in 1979 and the ore deposit was colonized by pioneer, heavy metal
resistant species of vascular plants, mosses and lichens (unsuccessful attempts to
reforest the locality were conducted); 38 taxa of terricolous lichens were noted
here by Palice and Solda ´n (2004) and Peksa (2009).
Lichens were identified using standard
chromatography (TLC) on Merck silica gel 60 F254 pre-coated glass plates in
solvent systems A, B and C according to Orange et al. (2001).
methods, including thin-layer
2.5.Analysis of Cu content in soils and lichen thalli
Flame atomic absorption spectrometry (FAAS) was used to determine back-
ground Cu content in thalli of selected lichen species (Cetraria islandica, Cladonia
arbuscula, Cladonia mitis, Cladonia cf. novochlorophaea, Cladonia pyxidata and
Cladonia rei) growing on five selected localities.
Macroscopic foreign material adhering to lichen surfaces (e.g. soil particles)
was removed with forceps and lichens were rinsed by deionized water. Lichens
were dried at 80oC for 24 h and 100 mg of dry material was digested for 48 h in
3 ml of concentrated HNO3(Suprapur, Merck, Darmstadt, Germany) and H2O2(2:1,
v/v) with the volume brought to 10 ml with deionized water, n=3 (Bac ˇkor et al.,
2007). Analysis of the trace elements was performed using a Perkin-Elmer 3030B
spectrometer (Perkin-Elmer Corp., Norwalk, CT, USA). Each sample was analyzed
at least three times and mean values were used as one observation.
Soil samples for determination of Cu content were collected from places where
lichen thalli were collected. Three replicates were taken from each place. After
removal of visible organic material and stones, soils were dried for 48 h at 80 1C
and sieved through mesh with 0.8 mm pores. Total Cu was measured after
digestion of 0.5 g DW in aqua regia (50 ml) for 24 h; solutions were then
evaporated to dryness in a water bath and dissolved in 5% HNO3 prior to
measurement on FAAS. Detection was at Cu lmax=324.8 nm.
2.6.DNA extraction, PCR amplification and DNA sequencing
Total genomic DNA was extracted from apical parts of lichen thalli following
the standard CTAB protocol (Doyle and Doyle, 1987) with minor modifications, or
with the DNeasy Plant Mini Kit (Qiagen, Venlo, The Netherlands) with extraction
buffers as recommended by the manufacturer. Algal DNA was resuspended in
sterile dH2O and amplified by the polymerase chain reaction (PCR). The ITS1, ITS2
and 5.8S regions were amplified using the algal-specific primer nr-SSU-1780-50
(50-CTG CGG AAG GAT CAT TGA TTC-30; Piercey-Normore and DePriest, 2001) and
a universal primer ITS4-30(50-TCC TCC GCT TAT TGA TAT GC-30; White et al., 1990).
All PCRs were performed in 20 ml reaction volumes (15.1 ml sterile Milli-Q Water,
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2 ml 100PCR buffer (Sigma), 0.4 ml dNTP (10 mM), 0.25 ml of primers (25 pmol/ml),
0.5 ml Red Taq DNA Polymerase (Sigma) (1U/ml), 0.5 ml of MgCl2and 1 ml of DNA
(not quantified)).
PCR and cycle-sequencing reactions were performed in either an XP thermal
cycler (Bioer) or a Touchgene gradient cycler (Techne). PCR amplification of the
algal ITS began with an initial denaturation of 95 1C for 5 min, and was followed by
35 cycles of denaturing at 95 1C for 1 min, annealing at 54 1C for 1 min and
elongation at 72 1C for 1 min, with a final extension at 72 1C for 7 min. Identical
conditions were used for the amplification of the actin I locus, except that an
annealing temperature of 60–62 1C was used. The PCR products were quantified on
1% agarose gel stained with ethidium bromide and cleaned either with the
JetQuick PCR Purification Kit (Genomed) or with QIAquick Gel Extraction Kit
(Qiagen) following the manufacturer’s protocols. The purified amplification
products were sequenced from both directions with the PCR primers at Macrogen,
Inc. (Seoul, Korea, http://dna.macrogen.com) and submitted to GenBank (accession
numbers in Table 1). Each polymorphic position was checked manually in all
electropherograms. Sequences of ITS variants were reconstructed from the
sequences containing ambiguities following Clark (1990) and Beszteri et al.
(2005). The method of manual checking of polymorphic sites (Clark, 1990) has
been recently utilized by Beszteri et al. (2005), who used the polymerase in PCR
reactions. Contrary to Clark (1990) we do not identify haplotypes in diploid
population, but distinguish particular species co-occurring in the lichen thallus.
First, sequences without any ambiguities were selected, as these undoubtedly
represent sequence variants occurring in the sample. Then those containing a
single ambiguous position were resolved as two variants differing at the single
position concerned and the resulting variants were added to the list of resolved
variants. For each variant thus identified, the remaining sequences containing
more than one ambiguities were screened. If the known variant could be made
from some combination of the ambiguous sites, the complement of the variant
was recovered as another potential variant. If only a single variant or a single
variant and its complement were found for a sequence containing multiple
ambiguities in this way, the variants were resolved unambiguously, and the
complementary variant was added to the list of resolved variants. This was
repeated as long as all ambiguities were resolved.
2.7. Sequence alignment and phylogenetic analyses
Asterochloris and Trebouxia ITS sequences (comprising ITS1, 5.8S and ITS2
regions) were aligned on the basis of their rRNA secondary structure information
(Beiggi and Piercey-Normore, 2007) with MEGA 3 (Kumar et al., 2004). Using RNA
secondary structure as a guide in aligning rRNA sequences is widely used. The
advantage of this approach is in apparent improvement of hardly alignable
regions. There are no conflicts between the primary and secondary structure
alignment. With the aid of secondary structure information, we are able to align
undoubtedly even highly variable parts of the alignment. Positions with deletions
in a majority of sequences were removed from the alignment, resulting in an
alignment comprising 523 (Asterochloris) and 607 (Trebouxia) base positions,
respectively. The phylogenetic trees were inferred by maximum likelihood (ML)
and weighted parsimony (wMP) criteria using PAUPn, version 4.0b10 (Swofford,
2003), and by Bayesian inference (BI) using MrBayes version 3.1 (Ronquist and
Huelsenbeck, 2003). A substitution model was estimated using the Akaike
Information Criterion (AIC) with PAUP/MrModeltest 1.0b (Nylander, 2004).
Accordingly, the HKY+I+G model was chosen for Asterochloris alignment, whereas
Table 1
List of lichen taxa used in this study with collection informations and GenBank accession numbers of algal symbionts.
Fungal taxaCode of sample Collection no.Locality GenBank
Cetraria aculeata
Backor 19 Peksa 800
ˇSpania dolina
ˇSpania dolina
Harmanec
L’ubietova ´
Gelnica
Chvaletice
Chvaletice
Harmanec
Chvaletice
Chvaletice
ˇSpania dolina
Harmanec
ˇSpania dolina
Gelnica
L’ubietova ´
Chvaletice
Chvaletice
Chvaletice
Chvaletice
L’ubietova ´
ˇSpania dolina
ˇSpania dolina
Harmanec
Harmanec
L’ubietova ´
Gelnica
Harmanec
Harmanec
Gelnica
Chvaletice
Chvaletice
Gelnica
ˇSpania dolina
L’ubietova ´
Chvaletice
Chvaletice
Chvaletice
Chvaletice
Chvaletice
Chvaletice
ˇSpania dolina
Gelnica
FM945343
Cetraria islandica
Backor 07Peksa 799FM945344
Cetraria islandica
Cetraria islandica
Cladonia arbuscula
Cladonia coccifera
Cladonia coccifera
Cladonia coccifera
Cladonia coniocraea
Cladonia deformis
Cladonia fimbriata
Backor 20
Backor 21
Backor 13
Clad 06
Clad 07
Backor 03
Clad 02
Clad 08
Backor 04
Peksa 813
Peksa 812
Peksa 789
Peksa 588
Peksa 589
Peksa 818
Peksa 576
Peksa 918
Peksa 796
FM945345
FM945346
FM945347
FM945351
FM945352
FM945353
FM945354
FM945357
FM945358
Cladonia fimbriata
Cladonia furcata
Backor 27
Backor 08
Peksa 815
Peksa 797
FM945359
FM945360
Cladonia furcata
Cladonia furcata
Cladonia humilis
Cladonia humilis
Cladonia macilenta
Cladonia macilenta
Cladonia mitis
Cladonia mitis
Backor 12
Backor 24
Clad 11 A, B
Clad 12
Clad 04
Clad 05 A, B, C
Backor 01
Backor 05
Peksa 792
Peksa 811
Peksa 919
Peksa 925
Peksa 917
Peksa 922
Peksa 808
Peksa 807
FM945361
FM945362
FM945348, FM945349
FM945350
FM945363
FM945364, FM945365, FM945366
FM945367
FM945368
Cladonia cf. novochlorophaea
Backor 06Peksa 798
FM945372
Cladonia ochrochlora
Cladonia pleurota
Cladonia pleurota
Cladonia pyxidata
Cladonia pyxidata
Cladonia rangiferina
Cladonia rangiformis
Cladonia rei
Cladonia rei
Cladonia rei
Cladonia rei
Backor 02
Backor 18
Backor 28
Backor 16 A, B
Backor 26
Backor 29
Backor 15
Clad 16 A, B
Clad 09
Backor 14
Backor 23 A, B
Peksa 816
Peksa 820
Peksa 810
Peksa 791
Peksa 814
Peksa 819
Peksa 790
Peksa 927
Peksa 921
Peksa 787
Peksa 794
FM945369
FM945370
FM945371
FM945373, FM945374
FM945375
FM945376
FM945377
FM945355, FM945356
FM945378
FM945380
FM945381, FM945382
Cladonia rei
Cladonia subulata
Cladonia subulata
Cladonia subulata
Cladonia sp.
Diploschistes muscorum
Diploschistes muscorum
Stereocaulon sp.
Backor 22 A, B
Clad 10
Clad 13 A, B
Clad 14
Clad 15
Dip 08
Dip 09
Backor 09
Peksa 809
Peksa 926
Peksa 916
Peksa 924
Peksa 920
Peksa 923
Peksa 928
Peksa 801
FM945386, FM945387
FM945379
FM945383, FM945384
FM945385
FM945388
FM945389
FM945390
FM945392
Stereocaulon tomentosum
Backor 10Peksa 786FM945391
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in Trebouxia, GTR+I+G model was deemed the best. Maximum likelihood analyses
consisted of heuristic searches with 1000 random sequence addition replicates
and tree bisection reconnection swapping. Reliability of the resulting topology was
tested using bootstrap analysis (100 replications) consisting of heuristic searches
with 10 random sequence addition replicates, tree bisection reconnection
swapping and a rearrangement limit of 5000 for each replicate. The wMP
bootstrapping was performed using heuristic searches with 100 random sequence
addition replicates, tree bisection reconnection swapping, random addition of
sequences (the number limited to 10,000 for each replicate) and gap characters
treated as missing data. In BI analysis, the datasets were partitioned into stem and
loop regions, and into ITS1, ITS2 and 5.8 rRNA partitions. Different substitution
models were then selected for the six partitions. For the loop regions a 4-state,
single-nucleotide substitution model was selected, while for the paired stem
regions, the doublet model (a 16-state RNA stem substitution model) was chosen
(Verbruggen and Theriot, 2008). According to our results, the Bayesian analyses
without using the doublet model have considerable lower posterior probabilities
of internal branches. In the analysis of ITS rDNA sequences acquired from 60
Asterochloris sequences, the number of nodes receiving high/moderate PP support
decreased from 11/7 to 10/4, without using the partitioned dataset with doublet
model.
Substitutions models for rRNA partitions were estimated using the Akaike
Information Criterion (AIC) as follows: GTR+G for ITS1, K80+I+G for ITS2 and JC
for 5.8 rRNA. Two parallel MCMC runs were carried out for 2 million generations,
each with one cold and three heated chains employing the above-stated
evolutionary model. Trees and parameters were sampled every 100 generations.
Convergence of the two cold chains was checked and burn-in was determined
using the ‘‘sump’’ command.
2.8.Statistical analysis
One-way analysis of variance and Tukey’s pairwise comparisons (MINITAB
Release 11, 1996) were applied to determine the significance (Po0.05) of Cu
content in lichens and soils.
3. Results
Cu content in lichens was the highest in samples collected from
Cu mine-spoil heaps inˇSpania dolina (Table 2). Lichens collected in
Gelnica and L’ubietova ´-Podlipa also contained significantly higher
content of Cu when compared to those collected in Harmanec and
Chvaletice. Lichens C. cf. novochlorophaea and C. pyxidata collected
from Cu mine-spoil heaps inˇSpania dolina and Gelnica were the
most effective in entrapment of soil particulates from substrate and
contained the highest content of Cu when compared with the rest of
lichens analyzed for Cu content. Cu accumulation in lichens reflected
Cu availability in substrata (Table 2).
We examined the samples of 23 terricolous lichen taxa
predominantly with fruticose thalli collected at five investigated
localities. A total of 50 ITS algal sequences were obtained (Table 1).
The photobionts obtained
Diploschistes and Stereocaulon (46 samples) were established to
be a member of the genus Asterochloris (Fig. 1). The phylogram
inferredfrom
Asterochloris
sequences
supported lineages (A–D) and some additional strains with
unsupported phylogenetic position (containing samples Backor
10, 23B and further related sequences). The clades A–D include 34
from specimensof
Cladonia,
contains fourwell
from a total of 46 Asterochloris sequences of photobionts
associated altogether with 16 fungal species. We found out
rather low degree of algal specificity. No clade was identified as
specific to particular fungal species; indeed, all lineages were
associated with two or more mycobionts.
In the remaining four samples representing cetrarioid lichens
(Cetraria aculeata, C. islandica), photobiont belonging to the genus
Trebouxia (s. str.) was detected. Sequences were genetically
closely related, and clustered with Trebouxia hypogymniae Hauck
and Friedl ined. (Hauck et al., 2007). The ML phylogram revealed
two well-resolved lineages within T. ‘‘hypogymniae’’, both contain-
ing photobionts of lichens growing in Cu mine-spoil heaps (Fig. 2).
Analyzing photobiont diversity in various mycobiont species
(Table 3), different degrees of selectivity toward photobiont
lineages were detected. In some fungal species, only single
photobiont clade was found, even though lichens from more
than one locality were investigated: T. hypogymniae ined. in
C. islandica; Asterochloris clade A in C. mitis and Cladonia pleurota,
clade D in Cladonia furcata. On the other hand, in the fungal
species Cladonia humilis, Cladonia macilenta, C. pyxidata, C. rei and
Cladonia subulata, two, three or four associated photobiont
lineages were recorded. Moreover, in some specimens of former
five lichen taxa, more than one photobiont was identified in a
single thallus (podetium). Usually, these photobionts were
established as members of the distantly related Asterochloris
lineages (e.g. photobionts of C. macilenta Clad 05 belong to clades
A and C; Fig. 1). To confirm the primary findings of multiple algal
genotypes, we analyzed photobiont diversity in different parts of
C. macilenta and C. subulata thalli (clump): small pieces of thalli
from the tips of one younger and one older podetia growing side
by side and from basal squamules on the base of these podetia
were selected (in previous analysis, DNA was extracted from the
whole podetium). In both fungal species, only a single photobiont
ITS variant was detected in each sample. Different photobionts
were recorded for the tips of neighboring podetia, the basal
squamules contained the same photobiont found in younger
podetium.
We did not find distinct differences in diversity of photobionts
among the localities. The number of photobiont lineages was
similar in areas with different heavy metal contents. Lineages of
Asterochloris occurring in three Cu polluted habitats (clades A–C)
were found also in Chvaletice, where the Cu content is very low
(but the amount of other metals is high). Moreover, the majority
of photobionts occurring in metal polluted localities were
detected also in natural habitat without distinct heavy metal
pollution in Harmanec (clades A–C and T. hypogymniae ined.). The
lack of particular clades in certain localities may be caused only
by incomplete sampling (we chose only part of lichen taxa
growing in studied sites for our approach). For example,
Asterochloris clade D was found only in sedimentation basin in
Chvaletice and it is missing in all four Slovak localities; however,
we found it in the thalli of Lepraria borealis collected in northeast
Table 2
Cu content (mg/g) in selected lichen species and soils collected at five localities; H=Harmanec, SD=ˇSpania dolina, L=L’ubietova ´-Podlipa, G=Gelnica, CH=Chvaletice.
HSD LGCH
Cu content – lichens
Cetraria islandica
Cladonia arbuscula
C. mitis
C. cf. novochlorophaea
C. pyxidata
C. rei
Cu content – soils
2.9871.67
–
–
–
3.9470.48
–
45.279.36
64.4718.7
–
66.5720.6
242746.3
–
–
13687161
24.378.25
–
27.6711.2
–
–
–
9247242
–
28.5711.4
–
–
163772.8
–
14867457
–
–
–
–
–
3.2870.25
1876.2
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ARTICLE IN PRESS
Low Tatra Mts. (Slovakia), not so far from the investigated sites
(unpublished results).
4. Discussion
4.1. Photobiont identity
Phylogram inferred from Asterochloris sequences (Fig. 1) con-
tains only one lineage including our samples (clade A), which
corresponds to a formally described morphospecies (Trebouxia
glomerata, Trebouxia irregularis and Trebouxia pyriformis – affilia-
tion of these species to the genus Asterochloris was confirmed by
several studies, e.g. Piercey-Normore and DePriest, 2001 – our
clade A corresponds well to clade I in their paper). Additional
lineages do not have any affiliation to yet described species;
however, all of them were previously reported by other authors
within phylogenetic analysis of various lichen photobionts (e.g.
Yahr et al., 2004; Beiggi and Piercey-Normore, 2007). Based on
neighbor-joining analysis (unpublished results) performed using
all known ‘‘Asterochloris’’ sequences (219 sequences obtained
from GenBank) and our 46 sequences, we tried to find out the size
(number of including sequences) and characters of particular
clades. Clade A was the most frequently occurring clade (91 algal
sequences from almost 50 lichen taxa); other well supported
clades contain fewer sequences (B – 11 sequences/10 lichen taxa,
C – 12/8 and D – 14/10).
Similar to Asterochloris clades, T. hypogymniae Hauck and Friedl
ined. is known from various lichen taxa, especially from families
Parmeliaceae and Umbiliariaceae. It is closely related to the
phenotypic species Trebouxia angustilobata (A. Beck) A. Beck ined.
(syn. T. jamesii (Hildreth and Ahmadjian) G¨ artner subsp. angusti-
lobata A. Beck; Beck, 1999; Beck et al., 2002) and an undescribed
species Trebouxia ‘‘vulpinae’’ (Kroken and Taylor, 2000). Moreover,
these sequences are related to T. simplex Tschermak–Woess
(photobiont sequence AJ51135, AJ511354 from Lecanora con-
izaeoides clustered in analysis of Hauck et al. (2007) with
sequence of the type strain of T. simplex) and another undescribed
photobiont of Letharia species T. ‘‘letharii’’ (Kroken and Taylor,
2000). All these taxa form a big clade that seems to be similar to
thevariously markedclades
‘‘T. jamesii complex’’ of Kroken and Taylor, 2000, clade A of
Opanowicz and Grube (2004), clade S3 of Blaha et al. (2006), clade
‘‘T. jamesii’’ of Piercey-Normore (2006) and clade 1 in phyloge-
netic analysis of Hauck et al. (2007).
in several publishedworks:
4.2. Photobionts and heavy metal pollution
Due to the low technology of mining operations in medieval
times, the Cu content of the mine-spoil heaps is still very high
(Bac ˇkor and Fahselt, 2004a; Bana ´sova ´ et al., 2006) – at the
localities in central Slovakia it may reach more than 3600 mg/kg,
the limit value for non-contaminated soils established by the
Slovakian Ministry of Environment is 36 mg/kg (Bana ´sova ´ et al.,
2006). Results of soil analyses in the present study (Table 2)
revealed that Cu soil content is significantly higher in samples
from Cu mine-spoil heaps inˇSpania dolina, L’ubietova ´-Podlipa
and Gelnica when compared with soil samples collected in
Harmanec and Chvaletice.
The effectiveness of lichens in intercepting atmospheric
particulates (usually up to 100 mm), as well as soil particles from
their substrate, has been shown in many studies (Loppi et al.,
1999 and references therein). These particles may be simply
deposited onto the lichen surface or trapped in the intercellular
spaces of the medulla (Garty, 2001) and can remain unaltered for
Fig. 1. ML phylogram of Asterochloris algae based on ITS rDNA sequences using a
HKY+I+G model. Values at the nodes indicate statistical support estimated by three
methods – maximum likelihood bootstrap (top left), maximum parsimony bootstrap
(top right) and MrBayes posterior node probability (lower). Thick branches represent
nodes receiving high statistical support in at least two bootstrap/posterior probability
analyses. ITS sequences determined in this study are given in bold face. Strain affiliation
to four lineages (A–D) is indicated. Localities in which algal strains were found are
illustrated by the symbols following the strain name (C – Chvaletice, G – Gelnica-Cechy,
H – Harmanec, L – L’ubietova ´-Podlipa, S –ˇSpania dolina). Different colors of symbols
indicate degree of polution (locality unpolluted by heavy metals are given in white, Cu
mine-spoil heaps in black and polluted locality with low Cu content in gray). Scale bar –
substitutions per site.
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