# Discrepancies between prokaryotes and eukaryotes need to be considered in soil DNA -based studies

Enrique Lara, David Singer, Stefan Geisen

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Enrique Lara, David Singer, Stefan Geisen. Discrepancies between prokaryotes and eukaryotes need to be considered in soil DNA -based studies. Environmental Microbiology, 2022, 24 (9), pp.3829-3839. 10.1111/1462-2920.16019 . hal-04342516

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Discrepancies between prokaryotes and eukaryotes
need to be considered in soil DNA-based studies

Enrique Lara ID, <fnref n="1" />* David Singer ID<fnref n="2" /> and
Stefan Geisen ID<fnref n="3" />

Summary

Metabarcoding approaches are exponentially increas-
ing our understanding of soil biodiversity, with a
major focus on the bacterial part of the microbiome.
Part of the soil diversity are also eukaryotes that
include fungi, algae, protists and Metazoa. Nowa-
days, soil eukaryotes are targeted with the same
approaches developed for bacteria and archaea (pro-
karyotes). However, fundamental differences exist
between domains. After providing a short historical
overview of the developments of metabarcoding
applied to environmental microbiology, we compile
the most important differences between domains that
prevent direct method transfers between prokaryotic
and eukaryotic soil metabarcoding approaches, cur-
rently dominated by short-read sequencing. These
include the existence of divergent diversity concepts
and the variations in eukaryotic morphology that
affect sampling and DNA extraction. Furthermore,
eukaryotes experienced much more variable evolu-
tionary rates than prokaryotes, which prevent captur-
ing the entire eukaryotic diversity in a soil with a
single amplification protocol fit for short-read
sequencing. In the final part we focus on future
potentials for optimization of eukaryotic
metabarcoding that include superior possibility of
functionally characterizing eukaryotes and to extend

the current information obtained, such as by adding
a real quantitative component. This review should
optimize future metabarcoding approaches targeting
soil eukaryotes and kickstart this promising research
direction.

**Introduction**

The use of molecular approaches to study soil microorganisms catalysed the immense development of microbial ecology. While soil bacterial diversity has received attention since the late 80s, studies on microbial eukaryotes (fungi, protists and micro-algae, but also soil microfauna) have been lagging behind. Yet, they are currently gaining momentum, as large/global-wide studies (Bates et al., 2013; Tedersoo et al., 2014; Mahé et al., 2017; Oliverio et al., 2020; Aslani et al., 2022) are generating immense amounts of data. The global understanding of diversity distribution and community assemblage rules (Aslani et al., 2022), as well as the discovery of novel environmental clades with high relevance for deep eukaryotic phylogeny (Burki et al., 2020), has considerably increased our understanding of soil eukaryotic diversity. Major breakthroughs were made, such as showing that eukaryotes in soils are more diverse than in aquatic systems (Singer et al., 2021), the most dominant eukaryotes are phagotrophs with small protists dominating (Oliverio et al., 2020) and that phototrophs are major contributors of the global carbon cycle (Jassey et al., 2022).

The precursory nature of ecological environmental
studies focusing on prokaryotes has led to the fact that
eukaryote-focused environmental diversity studies use
largely the same methodology. Nevertheless, the last
10 years saw the development of new curated genetic
databases dedicated to eukaryotes (Guillou et al., 2012)
and the expansion of existing ones (Quast et al., 2013).
However, sampling designs, laboratory protocols, data
analyses tools and concepts that are used by most soil
ecologists interested in eukaryotes are still mostly based
on – or even are identical to – the approaches used to
study prokaryotes.

<footnote n="1">¹Real Jardin Botánico-CSIC, Plaza de Murillo 2, Madrid, 28014, Spain.</footnote>

<footnote n="2">²UMR CNRS 6112 LPG-BIAF, Angers University,
2 Boulevard Lavoisier, Angers, 49045, France.</footnote>

<footnote n="3">³Laboratory of Nematology, Wageningen University,
Wageningen, 6700 AA, The Netherlands.</footnote>
Our aim in this perspective is to highlight fundamental
differences between prokaryotes and eukaryotes, and
the resulting consequences for environmental
metabarcoding studies. Indeed, the immense morphologi-
cal diversity of eukaryotes as well as their fast and inho-
mogeneous evolutionary rates prevent the application of
protocols for eukaryotic metabarcoding that were devel-
oped to study prokaryotes. Indeed, unified protocols for
all eukaryotes can only provide partial images of the
domain's diversity in soils. In addition to this comparative
list of warnings, we highlight avenues to take to optimize
the methodology to study soil eukaryotes.

Historical context; why did the study of eukaryotes
lag behind prokaryotic studies?

Environmental microbiology with a focus on an *in toto*
nucleic acid extraction, the current standard to assess
microbial biodiversity, has started to reveal the immense
diversity of planktonic bacteria in the Sargasso Sea
(Lane *et al.*, 1985; Giovannoni *et al.*, 1990). Similar
approaches followed shortly afterwards for Archaea
(DeLong, 1992). Protocols were developed at that time to
extract environmental DNA from soil (Tsai and
Olson, 1992). These approaches led to the discovery of
many major lineages composed exclusively of uncultured
organisms, called ‘environmental clades’ (for a review
encompassing all domains of life, see López-García and
Moreira (2008)). While prokaryotic microbiology devel-
oped considerably, microbial eukaryotic environmental
diversity remained unstudied for more than a decade.
Casually, the first study aimed at characterizing changes
in communities in artificial systems after virus-induced
lysis in filamentous cyanobacteria (van Hannen
et al., 1999). Eukaryotes gained more attention in aquatic
systems, and studies revealed novel eukaryotic clades in
marine (López-García et al., 2001; Moon-van der Staay
et al., 2001) and freshwater hyperacidic systems
(Amaral-Zettler et al., 2002). Early environmental molecu-
lar explorations of soil eukaryotic diversity were still ham-
pered by the low sequencing depth provided by amplicon
cloning/Sanger sequencing approaches used by then,
which did not allow seeing beyond the over-dominance of
a few plant and fungal operational taxonomic units
(OTUs). Most sequences of protists, fungi and animals
could not be retrieved (Lesaulnier et al., 2008), thus over-
looking most eukaryotic diversity. Taxon-specific primers
circumvented this problem and were applied to investi-
gate certain eukaryotic groups such as among protists
(Bass and Cavalier-Smith, 2004; Lara et al., 2007). In the
meanwhile, soil bacteria studies were flourishing
(Borneman et al., 1996; Chelius and Triplett, 2001; Ses-
sitsch et al., 2001; Zhou et al., 2002). Later, the

development and application of high-throughput sequenc-
ing (HTS) technologies allowed comprehensive insights
into microbial diversity in soils, such as of bacteria
(Roesch *et al.*, 2007), leading eventually to a better
understanding of the distribution of bacterial diversity
across global ecosystems (Delgado-Baquerizo
et al., 2018).

These methodological developments also benefited
eukaryotic diversity surveys, as they allow overcoming
the obstacle represented by the few over-dominant OTUs
and make possible the retrieval of a more complete pic-
ture of the eukaryotic biodiversity in soils. Eventually, the
development of HTS in the last decade saw the consider-
able development of large soil metabarcoding initiatives,
including global diversity surveys (Bates et al., 2013;
Oliverio et al., 2020; Aslani et al., 2022). All these
eukaryote-focused approaches are mainly transferred
from prokaryotic examples, often even using the same
samples taken for prokaryotes for which the sampling
has been optimized. The question remains how well
transferable these approaches are and how accurately
these data reflect the true eukaryotic diversity found in
soils.

Two different diversity concepts

Species (i.e. independent evolutionary units) are the
basic unit of biological diversity. While this concept has
largely been developed based on macroscopic and sex-
ual eukaryotes such as plants and animals, species are
more challenging to delimit in the asexual prokaryotes.
Some researchers even doubt the meaningfulness of the
notion of species in prokaryotes, where genes are com-
monly exchanged between organisms (Doolittle and
Zhaxybayeva, 2009). Indeed, bacterial and archaeal
genomes possess a relatively restricted number of spe-
cific genes ('core genome'), while many functional genes
related to adaptations to the environment are freely trans-
ferred horizontally through plasmid exchanges and conju-
gation (Paquola et al., 2018; Kloub et al., 2021) (Fig. 1).
Diversity units are therefore constituted by these core
genomes (Bobay, 2020) which also include relatively var-
iable genes that can be used to differentiate between
close related clinical strains (Bourdin et al., 2021) or to
observe geographical isolation (Qin et al., 2022). Yet,
prokaryotic environmental studies aim at a more com-
plete overview of the prokaryotic diversity than the few
taxa for which genomes can be compiled as
metagenome-assembled genomes (Howe et al., 2014).
These studies still need to apply metabarcoding based
on arbitrary criteria such as genetic distances between
strains to delimit species, such as the 97% 16S rRNA
gene identity 'rule' (Stackebrandt et al., 2002) or
amplicon sequence variants (Callahan et al., 2017). The
A Prokaryotes

<figure><img src="image_3.png" /></figure>

B Eukaryotes

<figure><img src="image_4.png" /><figcaption>**Fig. 1.** Differences between prokaryotic and eukaryotic diversity. While the first exchange functional genes frequently between taxa (A), eukaryotic genomes are much more stable and functions can be related to taxonomic affiliation (B).</figcaption></figure>

delimitation of independent evolutionary units still
remains unclear in bacteria, therefore the link between
OTUs and bacterial biological species is not obvious. An
example is provided by the human pathogen *Salmonella*
*flexneri*, which shares 99.9% similarity with *Escherichia*
*coli* on the 16S rRNA gene (Fukushima *et al.*, 2002), with
even *E.coli* variants ranging from pathogenic to mutualis-
tic (Dethlefsen *et al.*, 2007). A recent study showed that
more than hundred thousand *E. coli* and *Shigella*
genomes varied in their pathogenicity depending on
genomic features which are invisible at the 16S rRNA
gene level (Abram *et al.*, 2021).

In eukaryotes, biodiversity has been studied first on
organisms that are easy to observe, that is, plants and
animals, where genetic cohesion can essentially be char-
acterized by sexual compatibility and population struc-
ture. These rules can also be applied to eukaryotic
microbes, as most are considered sexual (Hofstatter and
Lahr, 2019). Therefore, scientists interested in soil
eukaryotes mostly benefit from the concept of species
and all its developments (De Queiroz, 2007) as a bench-
mark for diversity. Genomes are much more stable in the
eukaryotic world, and even if horizontal gene transfers
have played a role in evolutionary histories, they remain
extremely rare and would not bias diversity estimations
(Van Etten and Bhattacharya, 2020) (Fig. 1). The term
‘core genome’ previously mentioned for bacteria does
not apply here, as all genes are transmitted mostly within
species, therefore, the OTUs obtained in environmental
diversity studies are representative of the diversity. It

must be noted that in microbial eukaryotes, organisms
form temporal to permanent associations, most often
composed by a consumer and a phototrophic organism
(the consumer is then called ‘mixotroph’ by
protistologists). Metabarcoding studies will retrieve
sequences of both organisms, which we also consider as
separate, like bacteria in a consortium.

Also in eukaryotes, the identity of species is not directly
translatable from the commonly used 18S rRNA gene
focused on in metabarcoding approaches. The reason is
that this gene is simply not variable enough in most taxa.
We illustrate this caveat in Fig. 2, showing that humans
share exactly the same full 18S rRNA gene sequence
with hominid primates (Fig. 2). Eukaryotic environmental
metabarcoding targets even shorter parts of this gene,
mostly the ‘hypervariable’ regions v4 and v9 of the 18S
(Vaulot et al., 2022). Therefore, the reduced amount of
phylogenetic information retrieved in current
metabarcoding approaches would classify humans within
the same taxonomic unit as elephants (Fig. 2). This
vision would obfuscate a tremendous amount of diversity
as the genetic information would be systematically
pooled. This could lead to the fact that rare and poten-
tially endangered species could be considered abundant
if classified the same as some common species. For this
reason, while 18S rRNA gene metabarcoding may pro-
vide a general overview of eukaryotic diversity in a soil,
OTUs cannot be considered as equivalent to species, the
basic unit of diversity. In order to allow species delimita-
tion in eukaryotic metabarcoding studies by gaining taxo-
nomic resolution, several variable genetic markers have
been developed for the different groups and tested for
specific resolution. The nuclear internal transcribed
spacer (ITS), the mitochondrial cytochrome oxidase
(COI) and the chloroplastic 23S rRNA in photosynthetic
organisms are more variable than the 18S rRNA gene
(Pawlowski et al., 2012) and are (or could be) used in
group-specific metabarcoding (see Section Potential for
species-level resolution in eukaryotic metabarcoding).

Different morphologies change sampling protocols

Eukaryotes are characterized by an immense morpholog-
ical variation (in terms of size, shape and many other
traits) that greatly exceeds that of bacteria and archaea
(Fig. 3). These variations affect how sampling for
metabarcoding experiments in soil needs to be con-
ducted. As soil eukaryotes range from few micrometres
(several flagellated and amoeboid protists) to the
centimetre or even meter scale (earthworms, burrowing
animals and fungal mycelia), sample size and distribution
need to be increased compared to studies focusing on
the purely microscopic prokaryotes (Jurburg et al., 2021;
Potapov et al., 2022). Sampling for the smallest and most
abundant eukaryotic consumers – nanoflagellates and ‘naked’ amoebae might be the same as for bacteria. These eukaryotic organisms are considered the main drivers of nutrient cycling in soils (Rønn et al., 2002). However, even larger unicells such as Arcellinida (testate amoebae) would then need further upscaling or possibly filtering for concentrating cells (Kosakyan et al., 2015). These microbial top predators can dominate microbial biomass in certain systems such as peat bogs (Jassey et al., 2013; Marcisz et al., 2014). Also, microscopic nematodes, the most abundant animals on Earth that can exceed the importance of protists for nutrient cycling in some soils (Coleman et al., 1984; Griffiths, 1990), cannot be sampled with the prokaryotic protocols as sample sizes exceeding 100 g of soil are needed for reliable diversity analyses (Wiesel et al., 2015). Due to the

functional overlap of the key microbiome predators pro-
tists and nematodes, as well as other fauna that perform
similar functions (Thakur and Geisen, 2019), a separation
between metazoans and unicellular organisms would be
artificial and provide a biased vision of eukaryotic func-
tional diversity. Like for large protists, nematodes and
certainly also rotifers are extracted from the soil matrix
before molecular work (Kawanobe et al., 2021). In order
to retrieve all microbial-sized eukaryotic diversity in
metabarcoding analyses, huge amounts of soil should be
taken. This would increase dramatically complicate and
increase costs of sampling, and setting up controlled
experiments such as mesocosms. At the same time, spa-
tial heterogeneity of smaller organisms would be shad-
owed by sampling large amounts. A solution may come
from applying different sampling strategies that target dif-
ferent organisms size classes and pooling nucleic acids
extractions together. Sampling protocols to be applied
depend therefore on the research question (and mostly
on the target taxa), but also on the type of soil
investigated.

After sampling, nucleic acids need to be extracted in order to continue the flowchain in environmental metabarcoding. Some bacterial and archaeal taxa are recalcitrant to generic extraction protocols, as for instance the highly resistant spore-forming bacteria (Dineen et al., 2010). In eukaryotes, differences between taxa exist also given their variability in morphology. In soil, most protists have the capacity to produce resistant dormant life stages or cysts (Ekelund and Rønn, 1994; Geisen et al., 2018). Some of these cysts are extremely resistant, and can withstand wet heat up to 50°C and dry heat to 120°C (Fenchel, 1987). This resistance is shown by successful resurrection of protist taxa after tenths of thousands of years from Arctic permafrost (Shmakova and Rivkina, 2015; Shmakova et al., 2016). The particularly recalcitrant cysts of *Acanthamoeba* spp. are also highly resistant to a variety of chemical agents (Turner et al., 2000). In turn, soil protist diversity includes highly

<figure><img src="image_5.png" /><figcaption>**Fig. 2.** Phylogenetic tree illustrating percentages of genetic similarity between humans and different mammals based on some commonly used markers. v4 and v9 correspond to variable regions of the 18S rRNA gene.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>**Fig. 3.** Schematic workflow comparison between prokaryotes and eukaryotes. Sampling and DNA extraction steps will be performed according to the targeted organisms. Fundamental differences between prokaryotes and eukaryotes (amplicon length, gene copy numbers and presence of intron in the eukaryote gene) can be observed in the PCR/Sequencing steps.</figcaption></figure>
fragile and network forming amoeboid organisms, which
are abundant and widespread, such as foraminiferans
(Holzmann *et al.*, 2021) and variosean amoebae (Berney
*et al.*, 2015). These organisms, which can reach sizes of
more than 1 mm, are disrupted when soil is ground or
sieved, and their DNA can get lost. These differences
make it impossible to assess eukaryotic diversity in an
unbiased way using a single nucleic acid extraction
approach. As it is mostly not feasible to combine many
different protocols and it is also not always the goal to
uncover the entire eukaryotic diversity, we propose to
use a single extraction approach (Santos *et al.*, 2017).
Ideally, biases in extraction should be known to reliably
discuss potential presence, absence and abundance of
eukaryotic taxa present in a sample, and although certain
trends are identifiable (Santos *et al.*, 2017), taxon
oriented-research would be needed to adapt protocols to
target eukaryotic groups.

Consequences of rRNA evolutionary rates on
eukaryotic PCR-based surveys

After sampling and extracting nucleic acids, the amplifica-
tion of DNA extractions for environmental DNA surveys is
also a source of bias that differs between prokaryotes
and eukaryotes. One of the premises of environmental
metabarcoding surveys is that taxa are equally amplified
in all clades, as the sequences of the designed primers
are highly conserved through evolution. For prokaryotes,
protocols have been developed to obtain an optimized
coverage of the whole diversity using primers flanking the
v3-v5 variable regions of the 16S rRNA gene, with a size
that is suited for short, max 550 bp targeting Illumina
sequencing. For instance, the primer pair 515f/806r 16S
SSU rRNA gene has been designed to match perfectly
with flanking regions of more than 90% of all bacterial
and archaeal 16S barcoding regions (Walters
et al., 2011), making these oligonucleotides excellent
broad-range primers to cover prokaryotes (Knight
et al., 2018). A recent test (03/2022) performed on the
SILVA database (Klindworth et al., 2012) still shows that,
despite the upload of most recent data, these primers still
accommodate over 86% of all bacterial and archaeal
sequences.

In comparison to their bacterial counterparts, eukaryotic
ribosomal 18S rRNA genes present profoundly more het-
erogeneity in the regions flanking the most variable
barcoding regions. Indeed, eukaryotes are famous for their
fast-evolving ribosomal genes that changed at different
paces between clades. As an illustration, diverging evolu-
tion paces between eukaryotic 18S rRNA genes caused
artefacts that disrupted the topology of the first eukaryotic
trees ('long branch attraction') and caused misinterpreta-
tions on the evolutionary history of the whole domain

Prokaryotes vs. eukaryotes in soil metabarcoding 3833

(Philippe and Germot, 2000). These 18S rRNA gene-
related differences still cause issues in metabarcoding
studies. The first consequence is that a universal PCR
protocol cannot be designed for the whole domain
Eukarya, because of a lack of universally conserved
regions for primer design. Therefore, eukaryotic environ-
mental molecular diversity studies based on PCRs per-
formed on the 18S rRNA gene are systematically biased
against certain organisms (Vaulot et al., 2022). Some
common and diverse soil groups, such as the protistan
Amoebozoa and Heterolobosea (Discoba) usually have
sequences that are too variable in even conserved regions
to design perfectly matching primers (Vaulot et al., 2022).
Unfortunately, primers do not only ‘eliminate’ certain large
clades from metabarcoding data. Evolutionary paces vary
within classes, orders and even families, and supergroups
tend to be partially eliminated. Often factors of these differ-
ences remain elusive, but organisms with mutualistic or
parasitic lifestyles that are also common in soil animals
and plants tend to evolve faster, as exemplified with the
intracellular rhizarian parasite *Microcytos* (Hartikainen
et al., 2014), or, living within terrestrial organisms, Micro-
sporidia (Brinkmann et al., 2005).

The fast and heterogeneously evolving eukaryotic ribo-
somal genes also incorporate often introns of many hun-
dreds of base pairs and supplementary loops that render
the retrieval of certain sequences using modern HTS tech-
nology, such as Illumina's MiSeq, impossible. The presence
of these insertions varies quickly in evolution, and closely
related taxa can gain or lose them as illustrated in Heter-
olobosea (Geisen et al., 2015a), diatoms (Han et al., 2018)
and in Arcellinid testate amoebae (Lara et al., 2008).

Among the two most commonly used variable regions of
the 18S rRNA gene (v4 and v9), v4 is particularly prone to
amplification biases (Vaulot et al., 2022). On the other
hand, v4 is longer and provides more phylogenetic informa-
tion (Fig. 2). The use of one region or the other depends of
course on the research question, and experimental designs
need to consider these limitations. In sum, there is no silver
bullet solution to track all soil eukaryotic molecular diversity
in metabarcoding studies. For eukaryotes, an homogeniza-
tion of PCR protocols as recommended in the Earth Micro-
biome Project (Thompson, 2017) would systematically bias
our vision of diversity against ‘non-standard’ taxa. These
do represent a substantial amount of the eukaryotic diver-
sity, which might be largely lost in environmental eukaryotic
DNA diversity studies.

Future perspectives on eukaryotic metabarcoding in
soils

Despite the fact that eukaryotic metabarcoding appro-
aches in soils are still in their infancy compared to pro-
karyotic studies, many methodological developments
should overcome the current shortcomings. Here we list
some potentials and recommendations to improve soil
eukaryotic metabarcoding, which we summarize in Fig. 4:

1. Different diversity concepts need to be considered. While prokaryotic 16S rRNA OTUs can be considered as diversity proxies, in eukaryotes 18S rRNA OTUs correspond to real taxa that most of the time can be annotated to genus or family level or above, but rarely to species level. The level of taxonomic definition depends on the group considered and the targeted gene.

2. Sampling needs to be optimized when larger protists and metazoa are targeted by upscaling sample sizes or possibly concentrating organisms that cover also the local heterogeneity in organismal distribution. Holistic eukaryotic analyses covering protists and at least the most abundant 'microbial sized' animals (e.g. nematodes and rotifers) could be conducted by pooling nucleic acid extractions obtained from different protocols dimensioned for different organisms size classes. Including also the larger soil eukaryotes can be of fundamental value in ecological studies through their role as major microbiome predators, which influence its composition and functioning.

3. Environmental nucleic acids extraction and PCR will invariably bias the true information on eukaryotic diversity. Consensus approaches need to be applied by using the most generalist protocols (Santos et al., 2017; Vaulot et al., 2022), which allow cross-sample comparisons. Still, it must be kept in mind that taxon-specific protocols are needed for a substantial part of all soil eukaryotic clades if the entity of eukaryotic diversity is meant to be studied.

Next, we list a series of developments that will potentially
open new research avenues in eukaryotic metabarcoding.

Functional annotations of eukaryotic metabarcoding
data are readily possible compared to bacterial
metabarcoding data

A major opportunity offered by eukaryotic environmental
DNA surveys is the possibility to infer functions from

taxonomic barcoding sequences. Eukaryotes keep to a
large extent the inherited functions, like for instance pho-
tosynthesis in diatoms or active phagocytosis in Amoe-
bozoa. This characteristic, which derives from the
stability of eukaryotic genomes, allows a relatively reli-
able functional annotation of OTUs (Singer et al., 2021).
Functions are conserved along clades at different taxo-
nomic depths. For instance, in some protist groups, like
in ciliates, function is conserved within classes to a cer-
tain extent, and a finer taxonomical resolution that can be
reached with 18S rRNA sequences may refine even
more the functional assignment (Mieczan, 2009). Thus,
annotation based on ribosomal sequences can be rela-
tively precise (Lara et al., 2007; Lara and Acosta-
Mercado, 2012). Other groups can be more challenging
to characterize, like chrysophytes, where photosynthetic
capacity was lost many times during the groups evolu-
tionary history (Boenigk et al., 2005). This characteristic
makes functional inference based on ribosomal
sequences difficult in this group known to include both
phagotrophic and phototrophic organisms. This situation
is probably going to change as more species will be func-
tionally characterized in the future. Therefore, functional
annotations based on relatively easily obtainable 18S
rRNA gene reads can be of major additional benefit to
normal taxonomic information as the ecological role of
distinct and entire communities of eukaryotes can be
studied. It is a matter of time to implement an automated
functional annotation tool for all soil eukaryotes.

Bacteria can generally not be reliably assigned a func-
tion in soils. Although functions can be related to some
OTUs in bacteria and archaea (e.g. cyanobacteria, meth-
anogens, etc.), the immense often unknown diversity in
soils along with the plasticity of their genomes renders
this prediction perilous. Some bacterial functional predic-
tion pipelines like FAPROTAX have been used with some
success in soil (Sansupa et al., 2021). However, this
approach is based on the assumption that if two organ-
isms share the same 16S rRNA gene sequence, then
their genome (and thus their function) should be identical;
an assumption that does not take into account bacterial

<figure><img src="image_7.png" /><figcaption>**Fig. 4.** Illustration of the workflow followed in a eukaryotic metabarcoding experiment. Issues specific to eukaryotic metabarcoding are illustrated specifically, as well as solutions proposed to overcome these problems.</figcaption></figure>
genomic plasticity. In this sense, an approach through direct sequencing of functional genes retrieved from environmental samples has been favoured for years (see e.g. Gremion et al., 2004). In addition, recent deep-sequencing efforts that reconstitute full genomes from metagenomes, metagenome-assembled genomes (MAGs), are starting to be applied and reveal reliable potential gene functions of soil bacteria (Crits-Christoph et al., 2018). Yet, this approach is only possible for a few numerically dominant taxa as many tens of thousands of bacterial taxa constitute the immensely large metagenome of a fraction of a gram of soil. Therefore, most bacteria remain functionally unknown in soils. It must be noted that, even worse than for bacteria, MAGs of soil eukaryotes cannot be assembled. This is caused by larger genomes and eukaryotic rarity compared to bacteria and archaea (Xiong et al., 2021), which diminishes eukaryotic sequence information in metagenomic data. Furthermore, eukaryotic functional genes can often not even be assigned to known functions (Sibbald and Archibald, 2017). Yet, and until new developments of sequencing technologies allow increasing even more sequencing depth to the point that eukaryotic genomes are assembled from metagenomes, the possibility of characterizing eukaryotic functional diversity directly from metabarcodes provides great insights into terrestrial ecosystems functioning.

## The quantitative aspect of eukaryotic metabarcoding

Quantitative aspects are important information in any ecological study, and it would be desirable to include them in environmental metabarcoding surveys. Quantitative data such as abundance and especially biomass information are needed to estimate, for example, the importance of biodiversity in the global carbon, nitrogen and phosphorus cycles through food chains and across ecosystems. The question on how to interpret the number of reads obtained per OTU has been subject to a heated debate. Numbers of reads result approximately from the number of single cells times the number of copies per cell. These numbers vary between and within bacterial and archaeal taxa, spanning one order of magnitude, which prevents establishing a direct relationship between numbers of cells and numbers of reads (Stoddard et al., 2015). In eukaryotes, these numbers may vary by up to six orders of magnitude (Lavrinienko et al., 2021). As a consequence, studies show discrepancies between numbers of individuals and proportions of eukaryotic phylotypes in environmental metabarcoding studies (Gong and Marchetti, 2019). Ciliates, for instance, tend to be overrepresented, possibly due to their highly multiploid macronuclei (Geisen et al., 2015b). These numerical biases are combined with all potential flaws mentioned

above (DNA extraction, PCR and sequencing). Therefore, Jurburg et al. (2021) even suggested to handle eukaryotic metabarcoding data as presence/absence, without any quantitative interpretation. This approach, however, needs to be very carefully considered for most ecological studies as numerical comparisons can provide vastly extended information compared to presence/absence data; in this sense, numerical data are far more important than richness information.

While copy numbers per genome do vary, total biovolumes of the organisms represented by different phylotypes can correlate with numbers of reads per OTU. Gonzalez-de-Salceda and Garcia-Pichel (2021) recently found an allometric relationship, where cell biovolume and ribosomal operon copy numbers in microorganisms (including bacteria and archaea) are correlated well. A similar relationship exists also for multicellular organisms, namely, nematodes (Schenk et al., 2019). Correlating eukaryote biovolumes with numbers of reads in metabarcoding studies is in our view the way to bring quantitative aspects into the currently at best semi-quantitative, qualitative metabarcoding data of soil eukaryotes. These biovolumes can be converted into C-biomass equivalents, such as done for nematodes (van den Hoogen et al., 2019), which can be instrumental in following nutrient flows in ecosystems (Gilbert et al., 1998). However, calibration studies are needed to evaluate the biases inherent to a given eukaryotic taxon. A large database of individual species biovolumes is needed for broader use in ecological studies. In the meanwhile, sequence read numbers can still be considered as semi-quantitative, but should be used with caution when applying numerically sensitive analyses as in correlation networks.

## Potential for species-level resolution in eukaryotic metabarcoding

As stated above, the 18S rRNA gene often provides a rather coarse taxonomic resolution for most eukaryotic groups. However, other molecular markers can increase taxonomic resolution. Due to the closer comparability to animals and plants, a species-level taxonomic resolution can be used to apply the ecological theoretical background developed for plants and animals during the past decades and centuries. For that purpose, several barcoding genes have been tested for their taxonomic definition in isolated organisms and on pure cultures. Primers have been designed in order to cover the largest possible range of organisms within their target groups.

While short-read metabarcoding approaches have been standard since its implementation almost a decade ago to target soil eukaryotes (Bates et al., 2013), long-read HTS approaches, such as PacBio and Nanopore,
are rapidly developing. As their error rate per base pair is decreasing, they can potentially allow the retrieval of full-length ribosomal operon, combining species or even population-resolved taxonomic information based on the ITS region with the phylogenetic information provided by 18S and 28S rRNA genes (Jamy et al., 2020; Tedersoo et al., 2021).

Another promising gene for metabarcoding is the COI. This gene is conserved across most animals (Hebert et al., 2003) and is used for rotifers, where it largely outperforms the 18S rRNA gene in terms of taxonomic resolution (Fontaneto et al., 2019). COI is also a reference for soil microarthropods (Porter et al., 2019). Although priming regions are too variable to be used to scan all nematode diversity (Ahmed et al., 2019), COI is a promising marker to delimit species within nematode families (Bai et al., 2020). In soil protist metabarcoding, this marker was applied to Arcellinida (lobose testate amoebae) revealing niche differentiation between closely related species (Singer et al., 2018). Together, metabarcoding focusing on genes other than the 18s rRNA gene and long-read sequencing provide ultra-high taxonomic resolution, which can be used for in-depth studies on taxonomic profiles, species-level biogeographic analyses or bioindication/tracking invasive species.

## Concluding remarks

We here provide an overview of how the major differences that exist between prokaryotes and eukaryotes need to be taken into consideration when performing metabarcoding studies, from the conceptualization of experiments to data interpretation. Particularly in terrestrial systems, methods have first been optimized for prokaryotes, which leads to suboptimal experimental designs and misinterpretations of results in studies aiming at studying soil eukaryotes. Furthermore, we provide perspectives on ecologically relevant data that can be obtained through eukaryotic metabarcoding approaches, like functional information on soil eukaryotes. Methodological developments, thorough calibration and optimization efforts are still needed to refine quantitative interpretation of sequence read numbers; however, it can be foreseen that many methodological gaps will be filled in the years to come. Then, the possibility of applying fast evolving markers used for barcoding opens the door to many applications in academic (phylogeography, community ecology, etc.) and applied fields (bioindication, pathogen monitoring, etc.). Taken together, all these approaches will reveal the great power of eukaryotic environmental microbiology. Still, until then, it is of crucial importance to involve experts in studies; and, furthermore to train students in all steps of a given study, from design to interpretation.

## Acknowledgements

Our research was funded by: FEDER/Ministerio de Ciencia e Innovación – Agencia Estatal de Investigación (Project PGC2018-094660-B-100) to E.L. and NWO-VENI from the Netherlands Organization for Scientific Research (016. Veni.181.078) to S.G.

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