Discussion
In this study, we used a distinct transition zone in vegetation and soil
moisture, as the framework to analyze how different OTU generation
methods affect the detection of a shift in the composition of
microeukaryotic soil communites. Interestingly, the sharp transition in
plant community, with lower richness in wet compared to mesic-dry soils,
was not associated with a difference in observed richness for the
corresponding microeukaryotic soil communities. However, both above and
belowground community composition were significantly different in wet
and mesic-dry soil moisture regimes. We demonstrate that different OTU
generation methods applied to the same long amplicon eDNA dataset affect
the documented composition of soil microeukaryotic communities.
Similarly, earlier studies have reported that large scale ecological
patterns are recovered irrespective of the OTU or ASV generation method
or clustering threshold (for short read data) (Glassman & Martiny,
2018), sequencing technology (Furneaux et al., 2021) or sampling effort
(Castle et al., 2019). We conclude that large scale ecological patterns
are robustly recovered irrespective of the OTU or ASV generation method
applied. However, for studies focused on the particular members of these
contrasting communities, the OTU generation method selected
significantly affects the phylogenetic resolution and detection of taxa.
For instance, our results show that inference of ASVs with DADA2 (here
OTU_A) captures less than 30% of all reads, providing information on
intra-species genetic variation only for abundant taxa while rare taxa,
including entire phylum-level lineages, remain undetected. The over-all
estaimated OTU richness was also lower for OTU_A compared to the
cluster-based methods. When comparing OTU generation methods, others
have found contrasting patterns, with higher richness captured with
ASVs, the equvivalent to OTU_A in this study, compared to clustering
(Glassman & Martiny, 2018). Differences between our results and those
of Glassman and Martiny (2018) can be attributed to the earlier study´s
shorter amplicon (only ITS2 for fungi) and sequening depth generated by
Illumina, compared to our long amplicon sequencing with lower depth
using PacBio. In studies using short read amplicons, denoising increased
overall richness by capturing intraspecies genetic variation (Callahan
et al., 2016). However, when applied to long read amplicons from diverse
communities, intra-species variation can only be captured for the most
abundant taxa. While OTU accumulation curves saturated for all methods,
we found that increasing the number of samples would have increased the
number of detected taxa at the site. Due to soil heterogeneity and
spatial community turnover, increasing the number of samples rather than
the sequenincing depth increases the estimated alpha diversity even in
well-mixed, managed agricultural soils (Castle et al., 2019). The same
pattern was previously observed in forst soils from West Africa (Meidl
et al., 2021), highlighting the importance of optimizing sampling effort
versus sequencing depth to obtain a good representation of the alpha
diversity.
Single-linkage clustering with a distance threshold of 2%, on the other
hand, captures most reads in OTU_Ss that correspond closely to broadly
accepted fungal species-level sequence similarity across the ITS region,
suggesting that this method provides an acceptable proxy for species
richness. We anticipate that phylogenetic resolution of species and
genus-level relationships could have been improved by the generation of
a hybrid tree that included ITS2 alignments to resolve relationships
within each GH_90 lineage, in a manner similar to ghost-tree (Fouquier
et al., 2016). Such tree could have been used to generate phylogenetic
species hypotheses (ref) to analyze community composition and generate
species richness estimates for these communities. Apart from sequence
clustering approaches, extraction and amplification biases remains as a
major filtering step for analysis of total microeukaryptic soil
communites. Althought the primers we used have no known biases against
Glomeromycota, we obtained low read abundance for this group, despite
known high abundance of Gomeromycota spores at the site. This apparent
contradiction may be explained by the low copy number of around ten rDNA
operones in this phylum (Maeda et al., 2018) compared to other fungi
that may harbor hundreds to thousands of copies (Lofgren et al., 2019).
In addition to copy number variation, length difference in the rDNA,
especially ITS, can introduce bias both during PCR and sequencing
(Tedersoo et al., 2015), rendering this type of data far from
quantitative, especially when applied to broad phylogenetically groups
such as micoeukaryotes.
Our study also provides a first insight into the belowground diversity
of a meadow known for its rich plant community (Sernander, 1948; Zhang,
1983; Zhang & Hytteborn, 1985). Studies that aim to simultaneously
characterize communities of both protists and fungi have often found
that fungi dominate the sequenced microeukaryotic communities, e.g., in
tropical forest soil (Tedersoo et al., 2018) and soils from different
habitats in temperate regions (Tedersoo & Anslan, 2019). In previous
studies using the exact same primers, sequenced soil communities from
ectomycorrhizal dominated forests in Sweden and West Africa have been
almost completely dominated by reads taxonomically assigned to kingdom
Fungi (Furneaux et al., 2021; Kalsoom Khan et al., 2020; Meidl et al.,
2021). The dominance of protists in the sequenced microeukaryotic
community indicates that these soil systems are particularly suitable
for diverse communities of protists. High soil moisture may be one
explanation, but other factors like plant community, pH and total
nitrogen have also been associated with high abundance of protists in
soil (Oliverio et al., 2020). We anticipate that future studies may hold
many interesting discoveries of hitherto unknown diversity at this site.