Ecology and Evolution. 2020;10:11779–11786.
Received: 19 June 2020
Revised: 12 August 2020
Accepted: 24 August 2020
Jumping the green wall: The use of PNA-DNA clamps to
enhance microbiome sampling depth in wildlife microbiome
Luis Víquez-R1 | Ramona Fleischer1 | Kerstin Wilhelm1 | Marco Tschapka1,2 |
This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium,
provided the original work is properly cited.
© 2020 The Authors. Ecolog y and Evolution published by John Wiley & Sons Ltd
1Institute for Evolutionary Ecology and
Conser vation Genomic s, University of Ulm,
2Smithsonian Tropical Research Institute,
Luis Víquez-R, Institute for Evolutionar y
Ecology and Conservation Genomics,
University of Ulm, Ulm, Germany.
CONICIT-MICITT (Costa Rica), Grant/
Award Number: FI-190B-14; Columbus Zoo
and Aquarium; Ruf ford Foundation, Grant/
Award Number: 18771-1; Elisabeth Kalko
Stiftung, Grant/Award Number: 1601
As microbiome research moves away from model organisms to wildlife, new chal-
lenges for microbiome high-throughput sequencing arise caused by the variety of
wildlife diets. High levels of contamination are commonly observed emanating from
the host (mitochondria) or diet (chloroplast). Such high contamination levels affect
the overall sequencing depth of wildlife samples thus decreasing statistical power
and leading to poor performance in downstream analysis. We developed an ampli-
fication protocol utilizing PNA-DNA clamps to maximize the use of resources and
to increase the sampling depth of true microbiome sequences in samples with high
levels of plastid contamination. We chose two study organisms, a bat (Leptonyteris
yerbabuenae) and a bird (Mimus parvulus), both relying on heavy plant-based diets that
sometimes lead to traces of plant-based fecal material producing high contamination
signals from chloroplasts and mitochondria. On average, our protocol yielded a 13-
fold increase in bacterial sequence amplification compared with the standard proto-
col (Earth Microbiome Protocol) used in wildlife research. For both focal species, we
were able to increase significantly the percentage of sequences available for down-
stream analyses after the filtering of plastids and mitochondria. Our study presents
the first results obtained by using PNA-DNA clamps to block the PCR amplification
of chloroplast and mitochondrial DNA from the diet in the gut microbiome of wildlife.
The method involves a cost-effective molecular technique instead of the filtering out
of unwanted sequencing reads. As 33% and 26% of birds and bats, respectively, have
a plant-based diet, the tool that we present here will optimize the sequencing and
analysis of wild microbiomes.
16s, chloroplast, mitochondria, PCR blockers, PNAs, wildlife microbiome
VÍQUEZ-R Et al.
1 | INTRODUCTION
A new world of research opportunities has emerged with the advance-
ment of sequencing techniques. One of the fields that have benefited
most is the study of whole microbial communities, so-called microbi-
omes. This method allows the study of microbial communities, includ-
ing those closely associated with eukaryotic hos ts, without the need to
cultivate each bacterium separately (Caporaso et al., 2012). Together
with recently developed and improved bioinformatic pipelines (Mothur,
QIIME 2, etc.), we now have the means to classify and assign taxonomy
with a reasonable level of confidence (Bolyen et al., 2019).
As microbiome research moves away from model organisms and
extends into natural settings, new challenges of wildlife research and
those arising bec ause of the variety of wildlife diets need to be tac kled.
One of the challenges is the separation of bacterial from nonbacterial
sequences, that is, those from mitochondria (from the host) and chlo-
roplasts (from the diet) can sometimes be tricky (Barott et al., 2011;
Lundberg et al., 2013). According to the widely accepted endosymbi-
osis theory (Margulis [then known as Sagan (1967), Gray 2017], mi-
tochondria and chloroplasts were originally derived during evolution
from hijacked bacteria engulfed by other bacteria. Because of this bac-
terial origin, some DNA sequences of organelles are strikingly bacte-
ria-like. This is also the case with reads obtained from high-throughput
sequ encing of 16S rRNA genes, the usu al target of micr obiome st udies .
In the worst case, the resulting read coverage consists of many reads
assigned to mitochondria or chloroplasts.
Several ways are available to circumvent this problem; the most
common path is to increase the sequencing depth and then filter out
the reads assigned to the organelles. However, this technique results
in an expensive price tag (due to the high percentage of reads wasted
on contamination) for sequencing and may lead to highly skewed
read numbers depending on the provenance of the samples. Another
option has recently arisen: the use of DNA-PNA clamps as PCR
blockers to prevent the amplification of the specific mitochondrial or
chloroplast sequences (Lundberg et al., 2013). PNAs (peptide nucleic
acids) are DNA-mimicking molecules with outstanding hybridization
properties (Nielsen & Egholm, 1999). The backbone of the mole-
cules is constructed of N-(2-amino-ethyl) glycyl (AEG) instead of the
sugar-phosphate backbone of DNA (Nielsen et al., 1994). The nu-
cleobases attached to this backbone are the same as those in DNA,
thereby allowing hybridization between the probe and the bacterial
DNA. PNAs are thus a powerful molecular tool in microbiome re-
search for dealing with samples with a high content of either host
or plant remnants in fecal pellets (Fitzpatrick et al., 2018; Lundberg
et al., 2013).
In thi s stu dy, we test ed th e PNA-D NA clamps as a meth od fo r im-
proving microbiome discovery rates in bats (tequila bat Leptonycteris
yerbabuenae) and Galapagos mockingbirds (Mimus parvulus). We
chose these two study organisms because they both rely on heavy
plant-based diets that sometimes can lead to masses of plant-based
fecal material producing high contamination signals from chloroplast
and mitochondria. Our study presents the first results obtained by
using PNA-DNA clamps to block the PCR amplification of chloroplast
and mitochondrial DNA from the diet during investigations of gut
microbiomes of wild animal populations. The method involves a
cost-effective molecular technique, instead of the filtering out of the
unwanted sequencing reads.
2 | MATERIALS AND METHODS
2.1 | Sample collection
In 2018, we netted tequila bats (L. yerbabuenae) while they were
returning from a night's foraging trip. A mist net was positioned at
the entrance of the roosting cave located in the Pinacate and Gran
Desierto de Altar Biosphere Reserve in Northern Sonora, Mexico.
Bats were immediately removed from the net and kept in a soft
cloth bag until processed (<60 min). Animals were handled following
guidelines from the ASM for animal care (Sikes & The animal care &
use committee of the American society of Mammalogists, 2016) and
local regulations (Permit Number: SGPA/DGVS/06361/17). A sin-
gle fecal pellet was collected from the cloth bag and preserved in a
safe-lock 1.5-ml Eppendorf tube containing 500 µl DNA/RNA shield
(Zymo Research Europe GmbH, Germany). The tube was shaken to
ensure the maximum impregnation of the sample with the buffer
and then stored in a cool place until it could be frozen at −20°C.
For the present study, we used samples from eight randomly chosen
Mockingbird (M. parvulus) individuals were captured between
2007 and 2008 at various sites across the Galapagos Islands. Birds
were trapped by using mist nets or potter traps. Fecal pellets from
the birds were collected in ethanol and stored at −20°C. Further de-
tails about the capturing procedure are given in Hoeck et al. (2010)
and Štefka et al. (2011). In the present study, we used samples from
ten randomly chosen individuals inhabiting the islands of Santiago,
Santa Cruz, and Marchena (Fleischer et al., in review).
2.2 | DNA extraction
We extracted the fecal pellets by using the NucleoSpin® Soil extrac-
tion kit (Macherey-Nagel, Düren, Germany) following the manufac-
turer's guidelines. For the tequila bat samples, we homogenized the
sample (2 × 150 s at 50 Hz) by using a Speed Mil l PLUS (A naly tik Jena,
Jena, Germany). To maximize DNA yield, we conducted consecutive
elutions (2 × 50 µl) with a preheated (ca. 45°C) SE buffer. For the
mockingbird samples, the samples were washed in 50 µl SE buffer
and then homogenized using the same procedure as with the tequila
bat samples. We stored the extracted DNA at −20°C.
2.3 | PNA-DNA clamp design
The probes in our study were designed based on the work of
Lundberg et al. (2013) who developed PNA-DNA clamps to block
VÍQUEZ-R Et al .
mitochondrial (mPNA) and chloroplast (pPNA) DNA, these clamps
are known as universal clamps. Recently, Fitzpatrick et al. (2018)
reported that the universal pPNA showed a mismatch in six plant
lineages by means of an experimental and bioinformatic analy-
sis. Preliminary results from our study showed that the plant con-
tamination material in our bat samples belonged to one of these
lineages, namely Saguaro Columnar cacti (Cactaceae: Carnigea gi-
gantea). Therefore, following the recommendations of Fitzpatrick
et al. (2018), we developed a special clamp for the bat samples
(cpPNA: 5′GGCTCAACCCCGGACAG-3′); the sequence for the uni-
versal PNA-DNA clamps (cPNA and mPNA) can be obtained from
Lundberg et al. (2013). This is not a trivial matter, since even a single
base mismatch between the chloroplast sequence and the clamp can
increase levels of plastid contamination in the sequencing output
(Fitzpatrick et al., 2018). For the mockingbird, the universal clamps
were used to block both chloroplast and mitochondrial DNA. All
clamps were ordered from PNA Bio (Newbury Park, USA).
2.4 | DNA amplification, library
preparation, and sequencing
To investigate the gut microbiomes of bats (n = 8) and birds (n = 10),
we followed the Earth Microbiome Protocol (Caporaso et al., 2010).
Moreover, we added four samples consisting of a ZymoBIOMICS
microbial community standard D6300 (Zymo Research Europe,
Fr eiburg, Ge r m any ). These were use d as po s i t i v e co n t r o l s fo r mi crobi-
ome amplification and allowed us to examine whether the clamps had
any effect over the yield of a normal sample depleted of chloroplast
and mitochondria. The extracted DNA was amplified with the uni-
versal bacterial primers 515F (5′-GTGCCAGCMGCCGCGGTAA-3′)
and 806R (5′-GGACTACHVGGGTWTCTAAT-3′). We used a two-
step amplification process following the amplicon tagging scheme
of Fluidigm (Access Array System™ for Illumina Sequencing Systems,
©Fluidigm, San Francisco, USA). In the first step, we amplified a 291-
bp fragment of the hypervariable V4 region of the 16S rRNA gene by
using tagged (CS) target-specific (TS) primers: CS1-NNNN-TS-515F
and CS2-TS-806R. We added four random bases to our forward
primers to facilitate cluster identification during the first cycles on
the Illumina MiSeq System. In the second step, the tags (CS1 and
CS2) were used to add a sample-specific 10 bp barcode and the
Illumina system adapters.
FIGURE 1 A tequila bat (Leptonycteris yerbabuenae) visiting a
cactus flower (image for journal cover)
FIGURE 2 PCR protocol for the
implementations of the cpPNA-DNA
clamps. I. Normal workflow according to
the Earth Microbiome Protocol (Caporaso
et al., 2012); and II. our modified protocol
with the addition of one extra step for
clamp annealing (Step b)
VÍQUEZ-R Et al.
The initial 15 μl PCR volume contained 1.5 μl (5–15 ng) extracted
DNA, 7.5 μl DNA polymerase AmpliTaq Gold™ 360 Master Mix
(Applied Biosystems, Darmstadt, Germany), 1.5 μl (0.2 μM) primers,
and 4.5 μl sterile water. The PCR protocol consisted of an initial ac-
tivation step at 95°C for 10 min, followed by 35 cycles at 95°C for
30 s, 60°C for 30 s and 72°C for 45 s, and a final elongation at 72°C
for 10 min. When clamps where implemented, the water volume
was reduced to 1.5 μl; the 1.5 μl from each clamp (mPNA and either
cpPNA or pPNA) was added to this first step to give a final concen-
tration of 1 μM (Figure 1).
The modified PCR protocol included a step in order to allow the
binding of the PNA to the target sequences (Figure 2). For the sec-
ond barcoding PCR (20 μl), we used 3 μl initial PCR product, 10 μl
AmpliTaq Gold™ 360 Master Mix, 4 μl (0.4 μM) barcode primers
(Fluidigm), and 3 μl sterile water. PCR conditions were the same as
before, but only 10 cycles were performed.
TABLE 1 Summary of read counts for each sample before and after the filtering of reads assigned to chloroplasts and mitochondria. The
last column summarize the number of reads retained for the downstream microbiome analyses after the filtering.
Sample ID Species Clamp use Total read count
Number of reads assigned to
chloroplasts and mitochondria
140 L. yerbabuenae No 33,128 21,347 11,781
140 L. yerbabuenae Ye s 44,350 319 44,031
141 L. yerbabuenae No 31,707 28,320 3,387
141 L. yerbabuenae Yes 36,719 1,986 34,733
142 L. yerbabuenae No 37,85 6 13,891 23,965
142 L. yerbabuenae Yes 31,372 44 31,328
143 L. yerbabuenae No 32,777 31, 243 1,534
143 L. yerbabuenae Ye s 31,063 1,072 29,9 91
144 L. yerbabuenae No 31,564 29, 4 88 2, 076
144 L. yerbabuenae Ye s 30,579 3,102 27,47 7
145 L. yerbabuenae No 38,329 22,6 45 15,684
145 L. yerbabuenae Yes 37,232 173 37, 0 59
181 L. yerbabuenae No 33 ,516 21,996 11,520
181 L. yerbabuenae Yes 32,589 70 32 , 519
195 L. yerbabuenae No 30,738 30, 295 443
195 L. yerbabuenae Yes 3 0,421 4,533 25,888
143114 M. parvulus No 76,954 31,062 45,892
143114 M. parvulus Yes 56,890 511 56,379
143120 M. parvulus No 92,269 39, 606 52,663
143120 M. parvulus Ye s 50,596 196 50,400
143124 M. parvulus No 94,728 36,449 58,279
143124 M. parvulus Yes 39,96 3 413 3 9, 55 0
143170 M. parvulus No 121,709 3 8,511 83,198
143170 M. parvulus Yes 51,766 113 51, 65 3
143185 M. parvulus No 72, 513 65,422 7, 0 9 1
143185 M. parvulus Yes 35,253 7, 2 01 28,052
143193 M. parvulus No 67, 6 47 60,026 7,621
143193 M. parvulus Yes 37, 6 3 9 10,665 26,974
143195 M. parvulus No 53,607 53,396 211
143195 M. parvulus Yes 34,516 5,108 29, 4 0 8
143199 M. parvulus No 99,402 84,424 14,978
143199 M. parvulus Yes 41,528 1,585 39,94 3
143356 M. parvulus No 55,739 52,807 2,932
143356 M. parvulus Ye s 31,529 6,966 24, 563
143358 M. parvulus No 43,320 42,879 441
143358 M. parvulus Yes 39,65 8 5,114 34,544
VÍQUEZ-R Et al .
We used the NucleoMag® NGS Clean-Up and Size Select Kit
(Macherey-Nagel, Düren, Germany) on a GeneTheatre® (Analytik
Jena, Jena, Germany) to clean the PCR products according to the
manufacturer's guidelines. We assessed the quality of the ampl-
icons by using the QIAxcel Advanced System® (QIAGEN, Hilden,
Germany) and then proceeded to quantify the DNA concentration
by using the PicoGreen QuantiFluor® dsDNA System (Promega,
Madison, USA) on a TECAN Infinite F200 PRO® plate reader (Tecan,
Männedorf, Switzerland). We normalized the library to include 20 ng
DNA from each sample. Finally, we diluted the library to 3 nM for
sequencing. The library was spiked with 5% PhiX sequencing control
V3 (Illumina, San Diego, USA). Paired-end sequencing of the ampli-
cons was performed as recommended by Illumina (MiSeq Reagent
Kit v2—Reagent Preparation Guide) and loaded at a final library
concentration of 6 pM. Paired-end sequencing was performed over
2 × 250 cycles.
2.5 | Bioinformatics analysis
We conducted the demultiplexing and denoising of the samples in
the QIIME2 (version 2019.10) pipeline (Bolyen et al., 2019) and used
the DADA 2 method (Callahan et al., 2016) to get rid of artefacts and
chimeras. We trimmed the reads at 200 bp using a mean quality score
of 37 in both directions. Only amplicon sequence variants (ASVs)
that survived the filtering step were kept for subsequent analyses.
We trained a new SILVA V4 Classifier (SSU release 132 515-806) by
using QIIME2 tutorials as a reference (Quast et al., 2012). ASVs were
then assigned a taxonomy using the “qiime feature-classifier clas-
sify-sklearn” function) with the highest resolution possible (level 7).
Following the taxonomic assignment, we split the analysis into two
parts: we kept the original output of the taxonomy assignment (un-
filtered) and then we filtered the chloroplast and mitochondria as-
signed reads (filtered). This step was necessary to evaluate the effect
of the clamps on the percentage of reads that were allocated to the
chloroplasts and mitochondria before and after application of the
clamps. The script for our analysis is deposited in GitHub (https://
github.com/luisv qz/V4_pna_clamps_4_wildlife). Further analyses
were performed in R [version 3.4.4 (2018)] by using the phyloseq
package (McMurdie & Holmes, 2013) in a Linux environment. Plots
were generated in R (R Core Team, 2018) by using the package gg-
plot2 (Wickham, 2016).
3 | RESULTS
In bats, we obtained on average 40,278 (±3 ,719, n = 8) reads per
individual and in birds 71,367 (±26,981, n = 10; Table 1). From early
on, we were able to detect that a large percentage of the reads in
the unclamped samples were allocated to a few ASVs and, after per-
forming the taxonomic assignment, we were certain that those reads
matched known sequences of chloroplasts and mitochondria from
publicly available databases. The chloroplast sequences obtained
from the bat fecal samples matched 100% with a chloroplast se-
quence published from the Saguaro Columnar cacti (GenBank
Accession Number: KT164771).
After filtering out the chloroplast and mitochondria assigned
reads from the data set, we found that, by using the PNA-DNA
clamps, we were able to retain a significantly larger portion of the
reads after the filtering step (Figure 3a). Although the effectivity
varied between individual samples, we always detected an improve-
ment of read coverage available for downstream analyses while
using the clamps compared with the unclamped results in pairwise
comparisons. On average, the percentage of reads kept improved
by 13-fold for the bat (with the clamps cpPNA and mPNA) and by
34-fold for the bird (cPNA and mPNA) (Table 1). The two extreme
cases were the bat sample Lepto-195 with a 65-fold improvement
and the bird sample MM-143195 with a 216-fold improvement. The
control samples, that is, the bacterial mock community without chlo-
roplasts and mitochondria, showed no fold change indicating that
the use of the clamps did not affect the Zymo Mock community in
any way (Figure 3). We also tested for differences in alpha diversity
in clamped and unclamped samples and controls. We detected no ef-
fect of the clamps on the overall alpha diversity (p = .192; Figure 4).
Thus, the use of the clamps increased the percentage of reads kept
after the subsequent filtering step but did not affect the alpha diver-
sity of the samples.
4 | DISCUSSION
Challenges associated with plastid contamination represent a
major concern in microbiome analyses (Beckers et al., 2016; Gaona
et al., 2020; Jackrel et al., 2017). Our results indicate that the use of
DNA-PNA clamps significantly improves the microbiome sequenc-
ing output of fecal samples obtained from species with a diet har-
boring a large amount of chloroplast and mitochondrial DNA. This
effect has also been shown by Fitzpatrick et al. (2018) in plant sur-
face microbiomes; however, our study is the first to test the use-
fulness of clamps in wildlife microbiome studies relying on fecal
pellets. Microbiome studies have recently been growing at an ac-
celerated pace. As we move away from model organisms, the diets
of the animals under study become more and more diverse. As a
rough estimate, 26% of bats and 33% of birds (Ko et al., 2014) follow
a plant-based diet. Therefore, techniques that allow us to bypass the
remnant plant material in fecal samples are becoming more and more
important for microbiome studies.
One important factor to keep in mind when using PNA-DNA
clamps is the need to have some information about the diet of the
study species. PNA-DNA clamp specificity varies between groups.
In our case, we had previous knowledge that, in our study area, the
diet of tequila bats consists of almost 100% columnar cacti, par-
ticularly from one species, namely Carnigea gigantea (LV and MT,
personal observation and unpublished data). In the bat case, visual
inspection of the fecal pellets also revealed that a large percentage
of the pellets was undigested pollen grain clusters. This facilitated
VÍQUEZ-R Et al.
the development of the cpPNA clamp thanks to the information
available from other studies (Fitzpatrick et al., 2018).
Our technique allows the more cost-effective use of sequenc-
ing capacity. By employing PNA-DNA clamps, we have been able to
target the “true microbiome” more directly and waste fewer reads
related to by-products from the diet of the animal. Having higher
read num ber s enables better st atist ical power in the analysis an d de-
creases data losses in the subsequent steps in downstream process-
ing. Other authors have suggested to circumvent this problem by
targeting a different region of the 16S rRNA (Copeland et al., 2015).
However, previous attempts in our study revealed that sequencing
another location did not solve the problem since the contamina-
tion was still highly present and abundant after sequencing. Even
though the sequencing price tag is becoming cheaper every day
(Wetterstrand, 2011), without the PNA-DNA clamps, we would have
had to double or triple or even increase by 10-fold our sequencing
depth to make the latter reasonable enough to allow downstream
analyses. The cost of the clamps varies between providers but, in
general, the use of the clamps will always be more cost-effective
than aiming at larger sequencing depth. With the expansion of mi-
crobiome studies to nonmodel organisms, we believe that additional
tools like the one presented in this paper will streamline the future
advancement of the field.
LV was partly funded by Consejo Nacional de Ciencia y Tecnología,
Ministerio de Ciencia, Tecnología y Telecomunicaciones, Rufford
Small Grants, Elisabeth Kalko Stiftung, Columbus Zoo, Arizona
Game and Fish, and Whitley Fund for Nature (In collaboration with
RA Medellín, UNAM). We would like to thank the many field assis-
tants and collaborators that joined us on our numerous capturing
trips in México: RA . Medellín, A. Menchaca, D. Zamora, B. Iñarritu,
A. Vogeler, I. Barba, O. Calva, L. Torres, E. Ramírez, and many others.
We are also grateful for the technical advice provided by R. Jiménez,
FIGURE 3 Percentage of reads kept
after the filtering out the chloroplast and
mitochondrial DNA using QIIME2. Bat
samples were clamped by implementing
cpPNA/mPNA and birds by using pPNA/
mPNA. The Zymo Mock community was
treated with cpPNA/mPNA
FIGURE 4 Alpha diversity (Shannon
Index) changes in the microbiome
community before and after application
of clamps in bat, bird, and Zymo Mock
community. Bat samples were clamped
by implementing cpPNA/mPNA and birds
by using pPNA/mPNA. The Zymo Mock
community was treated with cpPNA/
VÍQUEZ-R Et al .
U. Stehle, and S. Brändel during laboratory work. Our thanks are also
due to A. Risely, R. Jiménez, A. Heni, M. Gillingham, K. Speer and
P. Santos for their comments and advice in the early stages of this
manuscript. Finally, we would like to thank the Secretaría Nacional
de Medio Ambiente y Recursos Naturales, Dirección General de
Vida Silvestre, and Consejo Nacional de Áreas Naturales Protegidas
for their help with permits and logistic support. We would also like
to thank the two anonymous reviewers for their constructive com-
ments that helped to improve the manuscript. Open access funding
enabled and organized by Projekt DEAL.
CONFLICT OF INTERESTS
The authors declare no competing interests.
Luis Viquez-R: Conceptualization (equal); Formal analysis (lead);
Funding acquisition (equal); Investigation (equal); Methodology (equal);
Project administration (equal); Writing-original draft (lead). Ramona
Fleischer: Data curation (equal); Formal analysis (equal); Investigation
(equal). Kerstin Wilhelm: Conceptualization (equal); Investigation
(equal); Methodology (equal); Writing-review & editing (equal). Marco
Tschapka: Conceptualization (equal); Funding acquisition (equal);
Supervision (equal); Writing-review & editing (equal). Simone Sommer:
Conceptualization (equal); Formal analysis (equal); Funding acquisition
(equal); Project administration (equal); Supervision (equal); Writing-
original draft (equal); Writing-review & editing (equal).
DATA AVA ILAB ILITY STATE MEN T
DNA sequences: Raw data and the necessary inputs for the
QIIME pipeline are deposited at Dryad (https://doi.org/10.5061/
dryad.4tmpg 4f7j). Mapping files, data sheets, and the scripts for
all the microbiome analysis (Qiime2 and R) are stored in GitHub
Luis Víquez-R https://orcid.org/0000-0002-5865-2461
Ramona Fleischer https://orcid.org/0000-0003-1657-9347
Kerstin Wilhelm https://orcid.org/0000-0001-5583-2777
Marco Tschapka https://orcid.org/0000-0001-9511-6775
Simone Sommer https://orcid.org/0000-0002-5148-8136
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