RESEARCH ARTICLE
Metal oxides, clay minerals and charcoal determine the
composition of microbial communities in matured artificial soils
and their response to phenanthrene
€ gel-Knabner2,3
Doreen Babin1, Guo-Chun Ding1, Geertje Johanna Pronk2,3, Katja Heister2, Ingrid Ko
1
& Kornelia Smalla
1
€hn-Institut, Federal Research Centre for Cultivated Plants, Institute for Epidemiology and Pathogen Diagnostics, Braunschweig,
Julius Ku
€r Bodenkunde, Technische Universit€at Mu
€nchen, Freising-Weihenstephan, Germany; and 3Institute for Advanced Study,
Germany; 2Lehrstuhl fu
€nchen, Garching, Germany
Technische Universit€
at Mu
Correspondence: Kornelia Smalla, Julius
€hn-Institut, Messeweg 11-12, 38104
Ku
Braunschweig, Germany. Tel.:
+49 531 2993814; fax: +49 531 2993006;
e-mail: [email protected]
Received 26 September 2012; revised 6
December 2012; accepted 9 December 2012.
Final version published online 21 January
2013.
MICROBIOLOGY ECOLOGY
DOI: 10.1111/1574-6941.12058
Editor: Angela Sessitsch
Keywords
artificial soils; RHDa genes; 16S rRNA genes;
ITS; DGGE.
Abstract
Microbial communities in soil reside in a highly heterogeneous habitat where
diverse mineral surfaces, complex organic matter and microorganisms interact
with each other. This study aimed to elucidate the long-term effect of the soil
mineral composition and charcoal on the microbial community composition
established in matured artificial soils and their response to phenanthrene. One
year after adding sterile manure to different artificial soils and inoculating
microorganisms from a Cambisol, the matured soils were spiked with phenanthrene or not and incubated for another 70 days. 16S rRNA gene and internal
transcribed spacer fragments amplified from total community DNA were analyzed by denaturing gradient gel electrophoresis. Metal oxides and clay minerals
and to a lesser extent charcoal influenced the microbial community composition. Changes in the bacterial community composition in response to phenanthrene differed depending on the mineral composition and presence of
charcoal, while no shifts in the fungal community composition were observed.
The abundance of ring-hydroxylating dioxygenase genes was increased in phenanthrene-spiked soils except for charcoal-containing soils. Here we show that
the formation of biogeochemical interfaces in soil is an ongoing process and
that different properties present in artificial soils influenced the bacterial
response to the phenanthrene spike.
Introduction
Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous
pollutants of great environmental concern due to their
persistence and ecotoxicological effects (Habe & Omori,
2003). To efficiently and economically remediate polluted
sites, the ability of microorganisms to degrade PAHs is
often exploited. Many efforts have been made to unravel
underlying biological mechanisms involved in microbial
PAH degradation (Habe & Omori, 2003; Peng et al.,
2008). It is known that the first step in the bacterial
degradation pathway of PAHs under aerobic conditions is
catalyzed by ring-hydroxylating dioxygenases (RHD;
Cerniglia, 1993), whose genes are often located on IncP-7 and
IncP-9 plasmids (Izmalkova et al., 2005; Sevastsyanovich
FEMS Microbiol Ecol 86 (2013) 3–14
et al., 2008). By employing a novel primer system targeting PAH-RHDa genes of Gram-positive and Gram-negative bacteria, Ding et al. (2010) recently showed an
increased abundance and soil type-dependent diversity of
PAH-RHDa genes in response to the PAH model compound phenanthrene spiked to a Cambisol and a Luvisol
soil. The environmental factors that influence PAH degradation in different habitats such as soils, sediments, or
surface water are manifold and far from being understood.
Among those, soils belong to the most complex habitats
on earth. Compounds of different structure, characteristics, and origin contact each other, aggregate, and form
so-called biogeochemical interfaces (K€
ogel-Knabner et al.,
2008). This highly heterogeneous structure creates a multitude of microhabitats colonized by diverse microbial
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
4
communities and is a prerequisite for a plethora of
interactions and processes (Young & Crawford, 2004;
K€
ogel-Knabner et al., 2008; Totsche et al., 2010). This soil
interaction network has to be considered for predictions
on the fate of PAHs and on the microbial response to
PAHs (Totsche et al., 2010). Several abiotic factors were
shown to limit the interaction of microbial communities
with PAHs (reviewed by Johnsen et al., 2005). For
instance, the spatial distribution of bacteria as well as
oxygen availability in soil restrict the PAH degradation by
microorganisms (Manilal & Alexander, 1991; Harms &
Bosma, 1997). The bioavailability can be strikingly
decreased by sorption and entrapment of phenanthrene in
nanopores (Nam & Alexander, 1998), which was used in
many studies as model compound for PAHs. Karickhoff
et al. (1979) reported first about a relation between sorption behavior of hydrophobic compounds and the organic
carbon content in natural sediments. Nowadays, it is
widely assumed that the fate of organic pollutants is controlled mainly by soil organic matter including charcoal
(Cornelissen et al., 2005), but it can also be affected by
clay minerals and iron hydroxides (Hundal et al., 2001;
Celis et al., 2006; M€
uller et al., 2007). Minerals and charcoal in turn were also shown to influence the establishment of the bacterial communities in soil (Carson et al.,
2007; Ding et al., 2013). However, still little is known
about their influence on the interplay between microorganisms and PAHs. To unravel this biogeochemical interaction, it is necessary to reduce the complexity of the soil
matrix and to exclude unpredictable influences from the
environment. Pronk et al. (2012) recently described an
artificial soil incubation experiment that was set up to
study the formation of biogeochemical interfaces over
time depending only on the soil mineral composition and
the presence of charcoal. Using this approach, Ding et al.
(2013) linked the establishment of microbial communities
with the soil mineral composition and showed that after
90 days of incubation, charcoal, to a lesser extent clay
minerals and metal oxides determined the composition of
the bacterial communities established in different artificial
soils with identical texture. Regarding the maturation of
biogeochemical interfaces in soil, we analyzed in this study
whether the soil mineral composition and charcoal will
determine the bacterial community structure also after a
longer incubation time and affect fungal communities as
well. Furthermore, due to differences in the established
microbiota that may again influence the characteristics of
the biogeochemical interfaces formed in the different artificial soils, we hypothesized that the response of microorganisms to the PAH model compound phenanthrene will
vary.
To test these hypotheses, artificial soils matured for
1 year were spiked with phenanthrene and respective
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
D. Babin et al.
control samples were left unspiked. After 70 days of
incubation, total community (TC-) DNA was extracted,
and PCR-amplified bacterial 16S rRNA gene or fungal
internal transcribed spacer (ITS) fragments, respectively,
were analyzed by denaturing gradient gel electrophoresis
(DGGE). In addition, the abundance of PAH-RHDa
genes and of plasmids belonging to different IncP
groups was studied by PCR and Southern blot hybridization.
Materials and methods
Experimental design
Seven artificial soil compositions (three replicates per treatment) were made as recently described in detail by Pronk
et al. (2012). Briefly, each of these soils contained the same
texture provided by quartz (Q) of different sizes, namely a
sand (> 63 lm, c. 42%), silt (6.3–63 lm, 52%), and clay
(< 6.3 lm, c. 5.6%) fraction, but differed in their content
of clay minerals [montmorillonite (M), illite (I)], metal
oxides [ferrihydrite (F), aluminum hydroxide (A)], and
presence of charcoal (C) (e.g. artificial soil QM consists of
quartz and montmorillonite; Table 1). Three days after
adding sterile manure as microbial nutrient source, each
soil was inoculated with an aliquot of the microbial
fraction from a natural Cambisol, Ultuna (60 °N, 17 °E in
Sweden). The microbial fraction was obtained after shaking
the soil resuspended in water with gravel for 2 h. The
incubation took place under constant environmental conditions (20 °C, 60% of maximum water-holding capacity,
in the dark). After 1-year incubation, samples were taken
and a seeding soil was mixed thoroughly with acetone-dissolved phenanthrene (Merck Schuchhardt, Hohenbrunn,
Germany). After evaporation of acetone, the seeding soil
was added to the total soil at a final concentration of
2 mg g 1 as described by Ding et al. (2010; treatments
labeled with +P). Controls were generated accordingly but
without adding phenanthrene. The treatments, consisting
each of three replicates, were incubated for 70 days at
22 °C, in the dark and under constant water content.
Samples were stored at 20 °C before extracting TC-DNA.
TC-DNA extraction
TC-DNA was extracted from 0.4 g soil (wet weight) using
FastPrep FP24 bead-beating system (MP Biomedicals,
Santa Ana, CA) twice for 30 s at a speed of 5.5 m s 1 to
harshly lyse cells and FastDNA spin kit for soil (MP Biomedicals) following the manufacturer’s protocol. The
DNA yield was checked by agarose gel electrophoresis,
and a cleaning step of DNA solution was followed using
GeneClean spin kit (Qbiogene, Inc., Carlsbad, CA)
FEMS Microbiol Ecol 86 (2013) 3–14
5
Microbes in matured artificial soils
Table 1. Artificial soil compositions used in this study (in mass %)
Component
Quartz (Q)
Montmorillonite (M)
Illite (I)
Ferrihydrite (F)
Aluminum hydroxide (A)
Charcoal (C)
Artificial soil
QM
QI
QMI
QMC
QIF
QIA
QIFC
94
94
94
94
94
94
94
6
0
3
4
0
0
0
0
6
3
0
5
5
3
0
0
0
0
1
0
1
0
0
0
0
0
1
0
0
0
0
2
0
0
2
according to the manufacturer’s recommendations. DNA
was stored at 20 °C.
PCR amplification of bacterial 16S rRNA gene
and fungal ITS fragments
The microbial community composition in soil samples was
studied based on purified TC-DNA. Primers F984GC/
R1378 (N€
ubel et al., 1996; Heuer et al., 1997; Supporting
Information, Table S1) were used to amplify bacterial 16S
rRNA gene fragments for DGGE analysis according to
Heuer et al. (1997) and Gomes et al. (2001) but using
0.2 lM primer and 0.1 U lL 1 AmpliTaq DNA Polymerase (Stoffel Fragment; Applied Biosystems). Additionally,
16S rRNA gene fragments of specific bacterial groups were
studied by DGGE for all artificial soil compositions except
for QIFC, for which only the alphaproteobacterial fingerprint was generated because the number of lanes that could
be evaluated without distortion of the gel run was limited
to 38 lanes. A nested PCR approach was used as described
by Milling et al. (2004) but only with acetamide (4%)
instead of DMSO, using 0.2 lM primer and 0.025 U lL 1
Taq Polymerase (TrueStart; Fermentas) in the first groupspecific amplification (25 cycles) with primer pair F311Ps/
R1459Ps for Pseudomonas (Milling et al., 2004) or forward
primer F203 for Alphaproteobacteria, F948 for Betaproteobacteria (Gomes et al., 2001), F243HGC for Actinobacteria
(Heuer et al., 1997) combined with the reverse primer
R1494 (Weisburg et al., 1991), respectively (Table S1).
This was followed by amplification of 1 : 10 diluted
PCR products with primer pair F984GC/R1378 (Table S1).
To study the fungal communities by DGGE, the ITS
fragments were also amplified in a nested approach using
primer pairs ITS1F/ITS4 and ITS1FGC/ITS2 (Anderson &
Cairney, 2004; Table S1) according to the PCR conditions
described by Weinert et al. (2009).
Detection of RHDa genes
PAH-RHDa genes were amplified from purified TC-DNA
with the PAH-RHDa primer 396F/696R as described by
FEMS Microbiol Ecol 86 (2013) 3–14
Ding et al. (2010; Table S1). To increase the specificity
and sensitivity of detection, PCR products were Southern
blotted to a nylon membrane (Amersham Hybond-N; GE
Healthcare, Freiburg, Germany) as described by Sambrook & Russell (2001). Hybridization was performed following the standard procedure of Roche Diagnostics for
filter hybridization under conditions of middle stringency
(Fulthorpe et al., 1995). A specific probe was generated
from purified PCR products from cloned PAH-RHDa
genes or reference plasmid pNF142 and digoxigeninlabeled with the DIG DNA labeling kit (Roche Applied
Science, Mannheim, Germany). Primers and probes are
listed in Tables S1 and S2.
PCR amplification of IncP plasmids
The presence of IncP-1, IncP-7, and IncP-9 plasmids was
analyzed in purified TC-DNA. For IncP-1 a, b, c, d, e a 25lL PCR with 0.6 lM of each Primer trfA 733f/trfA 1013r/
trfA c-F/trfA c-R/trfA d-F/trfA d-R (Bahl et al., 2009; Table
S1), TrueStart Buffer (Fermentas), 0.2 mM dNTPs, 2.5 mM
MgCl2, 0.1 mg mL 1 bovine serum albumin (BSA), and
0.025 U lL 1 Taq Polymerase (TrueStart; Fermentas) was
performed with the following thermal program: 5 min
94 °C, 35 cycles of 30 s 94 °C, 20 s 60 °C, 20 s 72 °C, and
5 min at 72 °C. The presence of IncP-7 was tested with
0.1 lM of primers P7repA/P7repB (Table S1) described by
Izmalkova et al. (2005) in a PCR of 25 lL containing Stoffel
Buffer, 0.2 mM dNTPs, 3.75 mM MgCl2, 0.1 mg mL 1
BSA, and 0.1 U lL 1 Stoffel Fragment (Applied Biosystems). Thermocycles were 3 min at 94 °C, 30 cycles of 30 s
at 94 °C, 30 s at 54 °C, and 1 min at 72 °C with a final step
of 5 min at 72 °C. IncP-9 plasmids were studied using
primers IncP-9 ori 69f/IncP-9 rep 679r (Table S1) in a PCR
with same volumes as described for IncP-1 but using
Stoffel Fragment (Applied Biosystems). PCR conditions were
5 min at 94 °C, 35 cycles of 1 min at 94 °C, 1 min at 53 °C,
2 min at 72 °C, and a final step of 10 min at 72 °C. IncP-1,
IncP-7, and IncP-9 PCR products were subjected to a Southern blot hybridization as described above for PAH-RHDa
genes but using probes listed in Table S2.
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
6
DGGE analysis of 16S rRNA gene and ITS
fragments
Bacterial and fungal communities were studied by DGGE
with the Ingeny PhorU system (Ingeny, Goes, the Netherlands) as previously described by Weinert et al. (2009)
and silver-stained according to Heuer et al. (2001). Gel
analysis was performed by Software GELCOMPARE II 6.5
(AppliedMaths, Belgium) using Pearson correlation for
calculating similarity coefficient values per lane and
unweighted pair group method with arithmetic mean
(UPGMA) algorithm for cluster analysis.
Cloning and sequence analysis
DGGE bands with treatment-dependent increased abundance were excised with a scalpel from silver-stained gel.
Three replicates were combined in a Lysing Matrix E tube
and rinsed three times with water to destain the gel. To
extract DNA, sterile zirconium beads and 50 lL 1X TE buffer were added and gel slices were broken in a bead-beating
process twice for 30 s at maximum speed followed by storage at 20 °C for 4 h and 4 °C overnight. Samples were
centrifuged several times for 1 min at 13 000 g to separate
gel residues and DNA-containing supernatant, which was
subsequently transferred to a new 1.5-mL tube. Two microliters of DNA were re-amplified using primer pair F984GC/
R1378 as described previously (Table S1). For cloning, PCR
products from DNA of selected samples with correct electrophoretic mobility on the DGGE control gel were generated under same PCR conditions but using F984 without
GC clamp. To increase ligation efficiency, 3′ A-overhang
was added in a 10-lL reaction step for 30 min at 70 °C
with Stoffel Buffer, 3.5 mM MgCl2, 0.2 mM dATP,
0.5 U lL 1 Taq Polymerase (Stoffel Fragment; Applied
Biosystems) using 5 lL gel-purified DNA. Ligation into
pGEM-T Vector System I (Promega, Madison, WI) and
transformation into competent cells (Escherichia coli
JM109; Promega) were carried out following supplier’s recommendations. Clones were screened as described by
Smalla et al. (2001) and sequenced in both directions with
standard primers SP6 and T7prom (Macrogen, Korea).
Sequences were tested for similarity hits in BLASTN (http://
blast.ncbi.nlm.nih.gov/Blast.cgi) and are available under
GenBank accession numbers JX524512 and JX524513.
Results
Effect of soil mineral composition and charcoal
on microbial communities
To unravel the microbial community structure depending
on the artificial soil composition after long maturation
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
D. Babin et al.
time and to analyze the response of the microbial communities to the phenanthrene spike, DGGE fingerprints
of total Bacteria, Alphaproteobacteria, Betaproteobacteria,
Actinobacteria, and Fungi were generated and analyzed by
UPGMA based on Pearson correlation indices (Figs 1 a–d
and 3).
DGGE fingerprints of the total bacterial community in
artificial soils (Fig. S1) showed a high similarity between
replicates and highly distinct patterns for each of the seven
different artificial soil compositions. Depending on the
soil composition, different bands were increased in intensity, for example, band A was detected only in soils containing charcoal (QMC, QIFC) or band B was specific for
soil QIF (Fig. S1). UPGMA analysis revealed clustering
according to the soil composition (Fig. 1a). Two main
clusters sharing c. 36% similarity were formed separating
the fingerprints of artificial soils with or without metal
oxides. Thus, one big cluster was formed for QIA, QIF,
and QIFC and the other one for QM, QMC, QI, and
QMI. Interestingly, the influence of the charcoal differed
depending on the clay mineral or metal oxide present.
Thus, the fingerprints of QMC clustered together with
those of QMI (65% similar) and were more similar to the
QI than to QM fingerprints. The charcoal-containing
QIFC fingerprints formed a separate cluster in the metal
oxide cluster (except for one replicate) and shared only
about 40% of similarity with the fingerprints of the other
metal oxide-containing soils (Fig. 1a).
To get a closer insight into the influence of soil mineral
components and charcoal on less abundant bacterial
groups that might be important for PAH degradation,
PCR–DGGE analyses for Alphaproteobacteria, Betaproteobacteria, and Actinobacteria (Figs S2, S3 and 2, respectively) were performed and also showed artificial soil
composition-dependent patterns as seen for total Bacteria.
The alphaproteobacterial fingerprints (Figs 1b and S2),
similar to Bacteria, revealed a strong influence of metal
oxides as two main clusters were formed separating the
fingerprints of artificial soils with or without metal oxides.
Populations with altered abundance in the presence of
charcoal compared with other soil compositions were
observed (e.g. band A in Fig. S2). In comparison with the
cluster analysis of total bacterial community, UPGMA
cluster analysis of alphaproteobacterial fingerprints
(Fig. 1b) showed that QMC was less similar to QI and
QMI soils (43%).
For Betaproteobacteria (Figs 1c and S3), the effect of
charcoal was more striking, as the QMC fingerprints
shared < 45% similarity with the fingerprints of the other
artificial soils. Band A (Fig. S3) was detected only in the
fingerprints of QMC indicating a betaproteobacterial
population with increased abundance in response to charcoal. Band B (Fig. S3) was detected only in the QM soil
FEMS Microbiol Ecol 86 (2013) 3–14
7
Microbes in matured artificial soils
(a)
(b)
(c)
(d)
Fig. 1. UPGMA cluster analysis of control treatments of artificial soils (QM, QI, QMI, QMC, QIF, QIA, QIFC) for total bacterial communities (a)
and specific groups (b-Alphaproteobacteria, c-Betaproteobacteria, d-Actinobacteria).
indicating a betaproteobacterial population positively
responding to montmorillonite. The fingerprints of QM
soil were clearly separated from the illite cluster and
shared c. 61% similarity. In contrast to the total bacterial
fingerprints, the effect of metal oxides was weaker for
Betaproteobacteria as cluster analysis showed high similarity (67%) between all soil variants containing illite
(QI, QIF, QMI, QIA).
In contrast to the betaproteobacterial fingerprints but
consistent with total Bacteria and Alphaproteobacteria, a
strong influence of ferrihydrite and aluminum hydroxide
was seen for Actinobacteria (Figs 1d and 2), as UPGMA
analysis showed a clear separation between soils with or
without metal oxides sharing < 35% similarity with each
other. Band A (Fig. 2) was detected only in QIA soil
FEMS Microbiol Ecol 86 (2013) 3–14
indicating a population that increased in abundance in
the presence of aluminum hydroxide. The charcoal effect
on Actinobacteria was less pronounced than on Betaproteobacteria, but stronger than for the total bacterial community. Soils containing only clay minerals (QM, QI,
QMI) developed similar populations (e.g. band B in
Fig. 2) and formed a clearly separated cluster (48% of
similarity). Interestingly, illite more strongly influenced
the bacterial communities than montmorillonite as the
fingerprints of QMI clustered with QI and shared 74%
similarity.
Fungal community analysis based on ITS fragment
fingerprints showed less bands compared with the bacterial fingerprints for all soil compositions (Fig. 3). An
influence of the soil composition was also seen for
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
8
D. Babin et al.
Fig. 2. DGGE fingerprint of 16S rRNA gene
fragments of Actinobacteria for artificial soils
unspiked (QM, QI, QMI, QMC, QIF, QIA) and
spiked with phenanthrene (+P). BS, bacterial
standard of 16S rRNA gene fragments from
11 bacterial strains.
Fig. 3. DGGE fingerprint of fungal communities based on ITS and respective UPGMA cluster for artificial soils unspiked (QM, QI, QMI, QMC, QIF,
QIA) and spiked with phenanthrene (+P). FS, fungal standard of ITS gene fragments from 16 fungal strains.
fungal fingerprints. Comparing the fungal communities
among the different artificial soils, only fungal communities of QM and QMC soils showed distinct populations
compared with highly similar QI, QMI, QIF, and QIA
compositions. Bands A and B were detected in QM and
QMC, indicating that these fungal populations likely
established in response to montmorillonite (Fig. 3). But
also charcoal shaped the fungal communities as revealed
by a reduced number of bands and the appearance of
band C (Fig. 3). Accordingly, in UPGMA analysis
(Fig. 3), QM and QMC showed only low similarity with
a cluster formed by the fingerprints of all illite-containing soils that shared more than 74% similarity. As
already seen for all studied bacterial groups, the effect of
illite seemed to be stronger than that of montmorillonite
when both were present in QMI soil as its fingerprints
showed higher similarity to QI (89%) than to QM
(64%). Illite, montmorillonite, and charcoal can be
regarded as strong drivers determining the fungal community composition.
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
Effect of phenanthrene spike on microbial
communities
To investigate the effect of phenanthrene on bacterial and
fungal communities established in artificial soils, DGGE
fingerprints of control and phenanthrene treatments (+P)
of total Bacteria (Fig. S1), specific bacterial groups potentially involved in phenanthrene degradation (Figs 2 and
S2–S4), and Fungi (Fig. 3) were compared and analyzed
by UPGMA clustering. In general, no obvious change in
bacterial complexity (number of bands) between spiked
and unspiked soils was seen. However, numerous bands
with increased or decreased abundance in response to
phenanthrene spike were detected. In the total bacterial
community fingerprint (Fig. S1), band C represents a
responder with decreased abundance among all artificial
soils in the presence of phenanthrene. Additionally, soil
composition-dependent responses to phenanthrene were
seen. Band D (Fig. S1) was detected only in soils containing illite in response to the phenanthrene spike. However,
FEMS Microbiol Ecol 86 (2013) 3–14
9
Microbes in matured artificial soils
the effect of phenanthrene on the bacterial communities
was less pronounced compared with the soil composition
as UPGMA analysis revealed subclusters of phenanthrenespiked and unspiked controls for several of the soil
compositions (QM, QMC, QIF, QIFC). However, the
fingerprints of the QI+P soil were more similar to those
of QMI+P than to the fingerprints of the corresponding
control soils. Bacterial community fingerprints of QMC
soil showed a less pronounced response to phenanthrene
compared with other soil compositions (c. 80% treatment
similarity between QMC+P and QMC).
Similar observations were made for the phenanthrene
response of Alphaproteobacteria (Fig. S2) except that a
stronger response of both charcoal-containing soils to the
phenanthrene treatment was observed, which was more
pronounced for QIFC+P. The response of alphaproteobacterial populations was mainly seen in changes of the
relative abundance, for example, band B (Fig. S2) showed
an increased intensity in the fingerprints of phenanthrene-spiked soils. Only a few new bands in spiked soils
were observed.
In contrast to the total Bacteria and the Alphaproteobacteria, betaproteobacterial community of QMC showed a
strong response to phenanthrene spike (Fig. S3). The two
intense bands C and D (Fig. S3) detected in QMC+P but
not in the QMC likely contributed to similarity values of
< 50% between spiked and unspiked QMC soil. The
fingerprints of QMC and QMC+P soils formed a separate cluster and shared only c. 30% similarity with the
fingerprints of all other artificial soils. In all illitecontaining soils, band E (Fig. S3) was detected in response
to the phenanthrene spike, and thus, a separate illite cluster formed in UPGMA analysis. Interestingly, as already
seen for total Bacteria and Alphaproteobacteria, QI+P and
QMI+P were more similar to each other (c. 90%) than to
the respective control soils. The dissimilarity between the
fingerprints of the control and the corresponding phenanthrene-spiked soils was similar for QM, QIA, and QIF.
Except for the QMC soil, the strongest effects of phenanthrene on all bacterial groups analyzed in artificial soils
were seen in the actinobacterial fingerprints with several
bands displaying an increased intensity in response to the
phenanthrene treatment (Fig. 2, e.g. bands C-F, Fig. S4).
Bands with the same electrophoretic mobility were
detected in response to phenanthrene spike, for example,
band C appeared in all soil compositions except for
QMC+P soil (Fig. 2). Additionally, clear differences in
the phenanthrene response depending on the soil composition were seen for the actinobacterial fingerprints. Band
D was detected only in illite-containing artificial soils in
response to phenanthrene, while bands E and F appeared
only in QMC+P soil and seemed to be charcoal-depending responders (Fig. 2). Based on the similarities observed
FEMS Microbiol Ecol 86 (2013) 3–14
between phenanthrene-spiked and phenanthrene-unspiked
soils in the UPGMA analysis (Fig. S4), the strongest
response of the actinobacterial communities to phenanthrene occurred in QI, QMI, and QM soils followed by
QIA and QIF. The weakest response was clearly found for
QMC. For QI+P and QMI+P soils, Actinobacteria communities were again more similar to each other than to
their corresponding controls. Once again, a clear separate
cluster was observed for phenanthrene-spiked and phenanthrene-unspiked metal oxide-containing soils (QIF,
QIA), which shared only 31% similarity with all other
fingerprints.
To identify some of the main bacterial responders to
phenanthrene depending on the soil composition, band D
in QIF+P and band F in QMC+P soil were excised from
Actinobacteria DGGE (Fig. 2). After checking the
electrophoretic mobility of re-amplified 16S rRNA gene
fragments by DGGE, the PCR products were cloned and
sequenced. The sequence of band D was 100% consistent
with the partial 16S rRNA gene sequence of Arthrobacter
polychromogenes DSM 20136. Bands with identical electrophoretic mobility were detected in all other soils containing illite (band D) in response to phenanthrene spike.
Sequencing of two selected clones derived from band F
revealed their identity and displayed 100% sequence identity with the partial 16S rRNA gene sequence of Pseudonocardia dioxanivorans CB1190.
In contrast to other bacterial fingerprints, Pseudomonas
(data not shown) and Fungi (Fig. 3) responded only
weakly to phenanthrene. Especially for fungal communities, a high similarity between control and spiked soil
independent of the soil composition was seen by UPGMA
analysis (> 90% similarity, Fig. 3).
Detection of PAH-RHDa genes in artificial soils
The PCR approach targeting PAH-RHDa genes in TC-DNA
of artificial soils showed several unspecific amplicon bands
additionally to the expected product size of 320 bp as
detected by ethidium bromide–stained 1% agarose gel (data
not shown). To increase the specificity and sensitivity, PCR
products were blotted and hybridized with a probe generated from different PAH-RHDa genotypes (Fig. 4). While
no amplicons were detected in unspiked QI, QMI, and
QMC soils, weak signals indicating the presence of PAHRHDa genes even in the absence of phenanthrene were seen
in blots of QM, QIF, QIA, and QIFC controls. However, in
all corresponding soils spiked with phenanthrene except for
those containing charcoal, the hybridization signals were
strongly increased indicating an enhanced abundance of
PAH-RHDa genes containing populations in response to
the phenanthrene spike. The intensity of the signal was similar between all spiked soils except for soils with charcoal.
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
10
D. Babin et al.
Fig. 4. Southern blot hybridization to PAH-RHDa genes of PCR products amplified from extracted TC-DNA of artificial soils unspiked (QM, QI,
QMI, QMC, QIF, QIA, QIFC) and spiked with phenanthrene (+P). Positive control pNF142 from Pseudomonas putida KT2442 at 320 bp. DIG VI-M,
digoxigenin-labeled DNA molecular weight marker VI (Roche Applied Science).
QMC+P soil revealed a significant lower abundance of
PAH-RHDa genes. The QIFC+P showed also a weaker signal compared with the response of the other spiked artificial
soils but not as weak as seen for QMC+P.
Detection of IncP-1, IncP-7, and IncP-9 plasmids
The detection of IncP-1, IncP-7, and IncP-9 plasmidspecific sequences in TC-DNA by PCR and Southern blot
hybridization (data not shown) revealed a heterogeneous
distribution of plasmids among replicates, artificial soils,
and treatments indicating a low abundance and no treatment-dependent selection of plasmid-containing bacterial
populations.
Discussion
Long-term effects of soil mineral composition
and charcoal on the microbial community
composition in artificial soils
In this study, the influence of the artificial soil composition on the structure of microbial communities established after a long-term maturation time and their
response to a phenanthrene spike was investigated. The
artificial soil experiment was designed as recently
described by Pronk et al. (2012). Using artificial soils,
Ding et al. (2013) reported in this thematic issue on the
initial establishment of bacterial communities depending
on the soil mineral composition and observed that
mainly charcoal and to a lesser extent the clay minerals
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
montmorillonite and illite determined the bacterial community composition. In this study, we observed a still
ongoing influence of clay minerals and charcoal on the
bacterial and fungal communities present in the artificial
soils after long-term incubation (1 year and 70 days).
High similarities of microbial communities between
independent replicates of the same artificial soil composition showed the driving force of minerals and charcoal.
In contrast to Ding et al. (2013), the effect of metal oxides remarkably increased and developed to the main driver
of
microbial
communities
except
for
Betaproteobacteria and Fungi. The metal oxides used in
this study had a high surface area and provided therefore
many sorption sites (Pronk et al., 2012). However, Heister et al. (2012) showed by secondary ion mass spectrometry at the nanoscale (NanoSIMS) that only small
amounts of organic material attached to iron oxides.
Only minor differences in the microbial community
composition of the metal oxide-containing soils QIF and
QIA indicated that these soil components influenced
biogeochemical interfaces in a similar way probably due
to their positive surface charge.
While Ding et al. (2013) reported charcoal as the
strongest factor shaping the bacterial community composition, the present study showed only a modest effect of
charcoal except for Betaproteobacteria and Fungi. The
effect of charcoal decreased probably due to the increasing occlusion of charcoal with organic matter over the
maturation time (Pronk et al., 2012).
A strong influence of illite and montmorillonite was
observed for bacterial and fungal communities. In contrast
FEMS Microbiol Ecol 86 (2013) 3–14
Microbes in matured artificial soils
to Ding et al. (2013), the influence of illite in matured
artificial soils became stronger than that of montmorillonite as QI and QMI soils always clustered separately from
QM soils possibly due to microaggregation and a decline
of available surfaces of montmorillonite. As Pronk et al.
(2012) did not report about differences in macroaggregation between soils with illite and montmorillonite, differences in microbial communities might be due to the
different physicochemical characteristics of the clay minerals (as reviewed by Stotzky, 1986).
Fungal populations were previously shown to be driven
by individual chemical elements of mineral substrates
(Gleeson et al., 2005). Differences in the fungal communities between QM and QI soil can be also explained by
different swelling behavior of montmorillonite and illite
(Stotzky, 1986). Furthermore, fungal hyphae are known
to be important in the formation of macroaggregates (Six
et al., 2004), and thus, the differences in the fungal community composition among the artificial soils might have
contributed to the decrease in macroaggregate stability
observed by Pronk et al. (2012) after 1 year for the soils
containing charcoal.
Effect of phenanthrene on the microbial
community composition in artificial soils
After maturation for 1 year and after another 70 days of
incubation with phenanthrene, a response of the bacterial
communities to the spike was seen in all artificial soils but
differing dependent on the soil composition and the taxonomic groups analyzed. The comparison of the bacterial
fingerprints of different phenanthrene-spiked artificial
soils revealed bands of same electrophoretic mobility
among different artificial soils, but also soil compositionspecific phenanthrene responses were observed. Ding et al.
(2012) reported about soil type-dependent responses of
bacterial communities in phenanthrene-spiked Luvisol
and Cambisol soils and that the bacterial community
composition of phenanthrene-spiked soils became more
similar to each other than to their respective controls as
seen in the present study for spiked QI and QMI. The fingerprints of the other artificial soils (QM, QMC, QIF,
QIFC, QIA) showed that the soil mineral composition
and charcoal and to a lesser extent phenanthrene shaped
the composition of the microbial communities. The
changes observed in the bacterial community composition
of artificial soils due to the phenanthrene spike showed
that organic carbon was not limited in the soil mixtures
up to an incubation time of 1 year and that the microbiota was still able to respond to the newly added compound. This finding is in agreement with the constant
CO2 respiration rates in artificial soils over a maturation
FEMS Microbiol Ecol 86 (2013) 3–14
11
period up to 18 months reported by Pronk et al. (2012).
The strongest response of bacterial communities in artificial soils to phenanthrene was observed by DGGE for
Actinobacteria. Members of this phylum, for example,
Arthrobacter, Mycobacterium, and Rhodococcus, were
already frequently described as PAH-degrading organisms
(Seo et al., 2006; Uyttebroek et al., 2006; DeBruyn et al.,
2007). Cloning of 16S rRNA gene fragments re-amplified
from differentiating bands appearing in the fingerprints of
phenanthrene-treated soils showed that P. dioxanivorans
was a typical responder of QMC and A. polychromogenes
in illite-containing soils. Previously, both species were
reported as degraders of organic compounds (Keuth &
Rehm, 1991; Mahendra & Alvarez-Cohen, 2005). RHDa
genes affiliated to Mycobacterium were found enriched
63 days after spiking natural Cambisol with phenanthrene
(Ding et al., 2010). However, the main bacterial responders of this soil to phenanthrene were identified by
amplicon sequencing as Sphingomonas (Alphaproteobacteria; Ding et al., 2012) and Polaromonas (Betaproteobacteria; Ding et al., 2012). The bands with increased intensity
in the alpha- and betaproteobacterial fingerprints of the
phenanthrene-treated soils observed in the present study
might be also attributed to selected degraders. However, it
can be assumed that enhanced bands could also represent
surfactant producing populations that have advantages in
contaminated sites (Willumsen & Karlson, 1997) or bacteria, which can use metabolites of the phenanthrene degradation pathway as nutrients. Bands that appeared weaker
or disappeared completely in DGGE patterns of soils
spiked with phenanthrene possibly represent populations
that were outcompeted by enriched populations or negatively affected by the bioavailable phenanthrene concentration present in the soils. Regarding Betaproteobacteria, we
observed a stronger influence of phenanthrene in QMC
compared with the other artificial soils. Probably, preselection of organic compound degraders belonging to Betaproteobacteria around charcoal particles (Kolton et al., 2011)
might have provided an advantage for a few populations that
also utilize phenanthrene. However, Betaproteobacteria represented only a small proportion of the total Bacteria present
in artificial soils as the fingerprints differed clearly from
the total bacterial fingerprints. We assume that the major
part of Bacteria did not have access to phenanthrene in
QMC soil as the DGGE fingerprints and also the PAHRHDa gene detection showed a weaker response compared with the other artificial soils. Charcoal exhibits a
strong sorption ability (Cornelissen et al., 2005), and
probably, sorption sites for phenanthrene were still present even after 1-year maturation time and lowered the
bioavailability. This is also supported by G.J. Pronk, K.
Heister & I. Kögel-Knabner (unpublished data) showing a
higher sorption of phenanthrene to QIFC soil compared
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
12
with QI and QIF. The strongest effects of phenanthrene
were clearly seen for the artificial soils QI, QMI, and QM.
Different smectites were previously reported to have an
influence on the fate of phenanthrene (Hundal et al.,
2001; M€
uller et al., 2007). We found differences in the
microbial response to phenanthrene depending on the
presence of illite or montmorillonite, respectively. However, we also observed that fingerprints of QI+P and
QMI+P became more similar to each other than to their
respective control soils.
In accordance with Ding et al. (2012), DGGE fingerprints showed no effect of phenanthrene on Pseudomonas
communities in artificial soils 70 days after spiking (data
not shown). PCR–Southern blot detection of IncP-1-,
IncP-7-, and IncP-9-specific sequences indicated a heterogeneous distribution and low abundance of bacterial populations carrying these plasmids, and no increased
abundance in response to the phenanthrene spike was
observed (data not shown). As the preferred host of plasmids belonging to the IncP-7 and IncP-9 group are Pseudomonas species (Krasowiak et al., 2002; Izmalkova et al.,
2006), these data indicate that Pseudomonas populations
might not be involved in the degradation of phenanthrene at this time point. Thus, the strongly increased
abundance of PAH-RHDa genes detected in phenanthrene-spiked soils (except for charcoal-containing soils)
was likely not carried on IncP-1, IncP-7, and IncP-9 plasmids. Hickey et al. (2012) reported about a PAH-RHD
genotype located on genomic islands and proposed
another opportunity for horizontal transfer of these genes,
which might be important in contaminated sites.
The degrading potential of fungi and the fungal impact
on the bioavailability of pollutants were recently reviewed
by Harms et al. (2011). In the present study, we observed
only weak shifts in the fungal community composition in
the different artificial soils in response to the phenanthrene spike. Similarly, Ding et al. (2012) reported that
the fungal community composition in Luvisol and Cambisol was not, or only weakly, affected 63 days after a
phenanthrene spike. Therefore, it can be assumed that
fungi established in artificial soils did not act as phenanthrene degraders, but it still has to be tested whether fungal hyphae played a passive role in transporting
phenanthrene or degrading bacteria (Kohlmeier et al.,
2005; Furuno et al., 2012).
Although artificial soils might only partially simulate
the conditions in natural soils, the present study demonstrates the usefulness of artificial soils to link the influence of soil minerals and charcoal on the microbial
composition and their response to spiked phenanthrene
and sheds light on the complex biogeochemical network
in soil. We could show that the formation of biogeochemical interfaces in soil is an ongoing developing
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
D. Babin et al.
process. Furthermore, by different responses to phenanthrene of established bacterial communities depending on
minerals or charcoal present in soil, we demonstrated that
each artificial soil composition developed its own microbiota and likely exhibited specific biogeochemical interface properties, which influenced the fate and effects of
phenanthrene.
Acknowledgements
We thank Ilse-Marie Jungkurth for carefully reading the
manuscript. This work was funded by the research pro€
jects DFG-SPP1315 (SM59/8-1, 8-2) and BMBF MAQNU
03MS642H.
References
Anderson IC & Cairney JWG (2004) Diversity and ecology of
soil fungal communities: increased understanding through
the application of molecular techniques. Environ Microbiol
6: 769–779.
Bahl MI, Burmølle M, Meisner A, Hansen LH & Sørensen SJ
(2009) All IncP-1 plasmid subgroups, including the novel e
subgroup, are prevalent in the influent of a Danish
wastewater treatment plant. Plasmid 62: 134–139.
Carson JK, Rooney D, Gleeson DB & Clipson N (2007)
Altering the mineral composition of soil causes a shift in
microbial community structure. FEMS Microbiol Ecol 61:
414–423.
Celis R, De Jonge H, De Jonge LW, Real M, Hermosin MC &
Cornejo J (2006) The role of mineral and organic
components in phenanthrene and dibenzofuran sorption by
soil. Eur J Soil Sci 57: 308–319.
Cerniglia CE (1993) Biodegradation of polycyclic aromatic
hydrocarbons. Curr Opin Biotechnol 4: 331–338.
€ Bucheli TD, Jonker MTO,
Cornelissen G, Gustafsson O,
Koelmans AA & Van Noort PCM (2005) Extensive sorption
of organic compounds to black carbon, coal, and kerogen in
sediments and soils: mechanisms and consequences for
distribution, bioaccumulation, and biodegradation. Environ
Sci Technol 39: 6881–6895.
DeBruyn JM, Chewning CS & Sayler GS (2007) Comparative
quantitative prevalence of Mycobacteria and functionally
abundant nidA, nahAc, and nagAc dioxygenase genes in
coal tar contaminated sediments. Environ Sci Technol 41:
5426–5432.
Ding GC, Heuer H, Z€
uhlke S, Spiteller M, Pronk GJ, Heister
K, K€
ogel-Knabner I & Smalla K (2010) Soil type-dependent
responses to phenanthrene as revealed by determining
the diversity and abundance of polycyclic aromatic
hydrocarbon ring-hydroxylating dioxygenase genes by
using a novel PCR detection system. Appl Environ Microbiol
76: 4765–4771.
Ding GC, Heuer H & Smalla K (2012) Dynamics of
bacterial communities in two unpolluted soils after
FEMS Microbiol Ecol 86 (2013) 3–14
Microbes in matured artificial soils
spiking with phenanthrene: soil type specific and common
responders. Front Microbiol 3: 290.
Ding GC, Pronk GJ, Babin D, Heuer H, Heister K, K€
ogelKnabner I & Smalla K (2013) Mineral composition and
charcoal determine the bacterial community structure in
artificial soils. FEMS Microbiol Ecol, in press.
Flocco CG, Gomes NC, Mac Cormack W & Smalla K (2009)
Occurrence and diversity of naphthalene dioxygenase genes
in soil microbial communities from the Maritime Antarctic.
Environ Microbiol 11: 700–714.
Fulthorpe RR, McGowan C, Maltseva OV, Holben WE &
Tiedje JM (1995) 2,4-Dichlorophenoxyacetic acid-degrading
bacteria contain mosaics of catabolic genes. Appl Environ
Microbiol 61: 3274–3281.
Furuno S, Foss S, Wild E, Jones KC, Semple KT, Harms H &
Wick LY (2012) Mycelia promote active transport and
spatial dispersion of polycyclic aromatic hydrocarbons.
Environ Sci Technol 46: 5463–5470.
Gleeson DB, Clipson N, Melville K, Gadd GM &
McDermott FP (2005) Characterization of fungal
community structure on a weathered pegmatitic granite.
Microb Ecol 50: 360–368.
Gomes NCM, Heuer H, Sch€
onfeld J, Costa R, MendoncßaHagler L & Smalla K (2001) Bacterial diversity of the
rhizosphere of maize (Zea mays) grown in tropical soil
studied by temperature gradient gel electrophoresis. Plant
Soil 232: 167–180.
Habe H & Omori T (2003) Genetics of polycyclic aromatic
hydrocarbon metabolism in diverse aerobic bacteria. Biosci
Biotechnol Biochem 67: 225–243.
Harms H & Bosma TNP (1997) Mass transfer limitation of
microbial growth and pollutant degradation. J Ind Microbiol
Biotechnol 18: 97–105.
Harms H, Schlosser D & Wick LY (2011) Untapped potential:
exploiting fungi in bioremediation of hazardous chemicals.
Nat Rev Microbiol 9: 177–192.
Heister K, H€
oschen C, Pronk GJ, Mueller CW & K€
ogelKnabner I (2012) NanoSIMS as a tool for characterizing soil
model compounds and organomineral associations in
artificial soils. J Soils Sediments 12: 35–47.
Heuer H, Krsek M, Baker P, Smalla K & Wellington EM
(1997) Analysis of actinomycete communities by specific
amplification of genes encoding 16S rRNA and gelelectrophoretic separation in denaturing gradients. Appl
Environ Microbiol 63: 3233–3241.
onw€alder A, Gomes
Heuer H, Wieland G, Sch€
onfeld J, Sch€
NCM & Smalla K (2001) Bacterial community profiling
using DGGE or TGGE analysis. Environmental Molecular
Microbiology: Protocols and Applications (Rochelle PA, ed.),
pp. 177–190. Horizon Scientific Press, Wymondham, UK.
Hickey WJ, Chen S & Zhao J (2012) The phn island: a new
genomic island encoding catabolism of polynuclear aromatic
hydrocarbons. Front Microbiol 3: 125.
Hundal LS, Thompson ML, Laird DA & Carmo AM (2001)
Sorption of phenanthrene by reference smectites. Environ Sci
Technol 35: 3456–3461.
FEMS Microbiol Ecol 86 (2013) 3–14
13
Izmalkova TY, Sazonova OI, Sokolov SL, Kosheleva IA &
Boronin AM (2005) The P-7 incompatibility group plasmids
responsible for biodegradation of naphthalene and salicylate
in fluorescent pseudomonads. Microbiology 74: 290–295.
Izmalkova TY, Mavrodi DV, Sokolov SL, Kosheleva IA, Smalla
K, Thomas CM & Boronin AM (2006) Molecular
classification of IncP-9 naphthalene degradation plasmids.
Plasmid 56: 1–10.
Johnsen AR, Wick LY & Harms H (2005) Principles of
microbial PAH-degradation in soil. Environ Pollut 133:
71–84.
Karickhoff SW, Brown DS & Scott TA (1979) Sorption of
hydrophobic pollutants on natural sediments. Water Res 13:
241–248.
Keuth S & Rehm HJ (1991) Biodegradation of phenanthrene
by Arthrobacter polychromogenes isolated from a
contaminated soil. Appl Microbiol Biotechnol 34: 804–808.
K€
ogel-Knabner I, Guggenberger G, Kleber M, Kandeler E,
Kalbitz K, Scheu S, Eusterhues K & Leinweber P (2008)
Organo-mineral associations in temperate soils: integrating
biology, mineralogy, and organic matter chemistry. J Plant
Nutr Soil Sci 171: 61–82.
Kohlmeier S, Smits THM, Ford RM, Keel C, Harms H & Wick
LY (2005) Taking the fungal highway: mobilization of
pollutant-degrading bacteria by fungi. Environ Sci Technol
39: 4640–4646.
Kolton M, Harel YM, Pasternak Z, Graber ER, Elad Y &
Cytryn E (2011) Impact of biochar application to soil on
the root-associated bacterial community structure of fully
developed greenhouse pepper plants. Appl Environ Microbiol
77: 4924–4930.
Krasowiak R, Smalla K, Sokolov S, Kosheleva I,
Sevastsyanovich Y, Titok M & Thomas CM (2002) PCR
primers for detection and characterisation of IncP-9
plasmids. FEMS Microbiol Ecol 42: 217–225.
Mahendra S & Alvarez-Cohen L (2005) Pseudonocardia
dioxanivorans sp. nov., a novel actinomycete that grows on
1,4-dioxane. Int J Syst Evol Microbiol 55: 593–598.
Manilal VB & Alexander M (1991) Factors affecting the
microbial-degradation of phenanthrene in soil. Appl
Microbiol Biotechnol 35: 401–405.
Milling A, Smalla K, Maidl FX, Schloter M & Munch JC
(2004) Effects of transgenic potatoes with an altered starch
composition on the diversity of soil and rhizosphere
bacteria and fungi. Plant Soil 266: 23–39.
M€
uller S, Totsche KU & K€
ogel-Knabner I (2007) Sorption of
polycyclic aromatic hydrocarbons to mineral surfaces. Eur J
Soil Sci 58: 918–931.
Nam K & Alexander M (1998) Role of nanoporosity and
hydrophobicity in sequestration and bioavailability: tests
with model solids. Environ Sci Technol 32: 71–74.
N€
ubel U, Engelen B, Felske A, Snaidr J, Wieshuber A, Amann
RI, Ludwig W & Backhaus H (1996) Sequence
heterogeneities of genes encoding 16S rRNAs in
Paenibacillus polymyxa detected by temperature gradient gel
electrophoresis. J Bacteriol 178: 5636–5643.
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
14
Peng RH, Xiong AS, Xue Y, Fu XY, Gao F, Zhao W, Tian YS
& Yao QH (2008) Microbial biodegradation of polyaromatic
hydrocarbons. FEMS Microbiol Rev 32: 927–955.
Pronk GJ, Heister K, Ding GC, Smalla K & K€
ogel-Knabner I
(2012) Development of biogeochemical interfaces in an
artificial soil incubation experiment; aggregation and
formation of organo-mineral associations. Geoderma
189–190: 585–594.
Sambrook J & Russell DW (2001) Molecular Cloning: A
Laboratory Manual, 3rd edn. Cold Spring Harbor
Laboratory Press, New York, NY, USA.
Seo JS, Keum YS, Hu YT, Lee SE & Li QX (2006)
Phenanthrene degradation in Arthrobacter sp. P1–1: initial
1,2-, 3,4- and 9,10-dioxygenation, and meta- and orthocleavages of naphthalene-1,2-diol after its formation from
naphthalene-1,2-dicarboxylic acid and hydroxyl naphthoic
acids. Chemosphere 65: 2388–2394.
Sevastsyanovich YR, Krasowiak R, Bingle LE, Haines AS,
Sokolov SL, Kosheleva IA, Leuchuk AA, Titok MA, Smalla
K & Thomas CM (2008) Diversity of IncP-9 plasmids of
Pseudomonas. Microbiology 154: 2929–2941.
Six J, Bossuyt H, Degryze S & Denef K (2004) A history of
research on the link between (micro)aggregates, soil biota,
and soil organic matter dynamics. Soil Till Res 79: 7–31.
Smalla K, Wieland G, Buchner A, Zock A, Parzy J, Kaiser S,
Roskot N, Heuer H & Berg G (2001) Bulk and rhizosphere
soil bacterial communities studied by denaturing gradient gel
electrophoresis: plant-dependent enrichment and seasonal
shifts revealed. Appl Environ Microbiol 67: 4742–4751.
Stotzky G (1986) Influence of soil mineral colloids on
metabolic processes, growth, adhesion and ecology of
microbes and viruses. Interactions of Soil Minerals with
Natural Organics and Microbes: Special Publication No 17
(Huang PM & Schmitzer M, eds), pp. 305–428. Soil Science
Society of America, Madison, WI.
Totsche KU, Rennert T, Gerzabek MH, K€
ogel-Knabner I,
Smalla K, Spiteller M & Vogel HJ (2010) Biogeochemical
interfaces in soil: the interdisciplinary challenge for soil
science. J Plant Nutr Soil Sci 173: 88–99.
Uyttebroek M, Breugelmans P, Janssen M et al. (2006)
Distribution of the Mycobacterium community and
ª 2012 Federation of European Microbiological Societies
Published by Blackwell Publishing Ltd. All rights reserved
D. Babin et al.
polycyclic aromatic hydrocarbons (PAHs) among different
size fractions of a long-term PAH-contaminated soil.
Environ Microbiol 8: 836–847.
Weinert N, Meincke R, Gottwald C, Heuer H, Gomes NC,
Schloter M, Berg G & Smalla K (2009) Rhizosphere
communities of genetically modified zeaxanthinaccumulating potato plants and their parent cultivar differ
less than those of different potato cultivars. Appl Environ
Microbiol 75: 3859–3865.
Weisburg WG, Barns SM, Pelletier DA & Lane DJ (1991) 16S
ribosomal DNA amplification for phylogenetic study. J
Bacteriol 173: 697–703.
Willumsen PA & Karlson U (1997) Screening of bacteria,
isolated from PAH-contaminated soils, for production of
biosurfactants and bioemulsifiers. Biodegradation 7: 415–423.
Young IM & Crawford JW (2004) Interactions and selforganization in the soil-microbe complex. Science 304:
1634–1637.
Supporting Information
Additional Supporting Information may be found in the
online version of this article:
Fig. S1. DGGE fingerprint of 16S rRNA gene fragments
and respective UPGMA of total bacterial community for
artificial soils unspiked (QM, QI, QMI, QMC, QIF, QIA,
QIFC) and spiked with phenanthrene (+P).
Fig. S2. DGGE fingerprint of 16S rRNA gene fragments
and respective UPGMA of alphaproteobacterial community for artificial soils unspiked (QM, QI, QMI, QMC,
QIF, QIA, QIFC) and spiked with phenanthrene (+P).
Fig. S3. DGGE fingerprint of 16S rRNA gene fragments
and respective UPGMA of Betaproteobacteria for artificial
soils unspiked (QM, QI, QMI, QMC, QIF, QIA) and
spiked with phenanthrene (+P).
Fig. S4. UPGMA cluster analysis of actinobacterial fingerprints of artificial soils unspiked (QM, QI, QMI, QMC,
QIF, QIA) and spiked with phenanthrene (+P).
FEMS Microbiol Ecol 86 (2013) 3–14