All together now: Limitations and recommendations for the simultaneous analysis of all eukaryotic soil sequences

In silico assessment of 18S rDNA metabarcoding markers for the characterization of nematode communities

Nematodes are keystone actors of soil, freshwater and marine ecosystems, but the complexity of morphological identification has limited broad-scale monitoring of nematode biodiversity. DNA metabarcoding is increasingly used to assess nematode diversity but requires universal primers with high taxonomic coverage and high taxonomic resolution. Several primers have been proposed for the metabarcoding of nematode diversity, many of which target the 18S rRNA gene. In silico analyses have a great potential to assess key parameters of primers, including taxonomic coverage, resolution and specificity. Based on a recently-available reference database, we tested in silico the performance of fourteen commonly used and one newly optimized primer for nematode metabarcoding. Most primers showed very good coverage, amplifying most of the sequences in the reference database, while four markers showed limited coverage. All primers showed good taxonomic resolution. Resolution was particularly good if the aim was the identification of higher-level taxa, such as genera or families. Overall, species-level resolution was higher for primers amplifying long fragments. None of the primers was highly specific for nematodes as, despite some variation, they all amplified a large number of other eukaryotes. Differences in performance across primers highlight the complexity of the choice of markers appropriate for the metabarcoding of nematodes, which depends on a trade-off between taxonomic resolution and the length of amplified fragments. Our in silico analyses provide new insights for the identification of the most appropriate primers, depending on the study goals and the origin of DNA samples. This represents an essential step to design and optimize metabarcoding studies assessing nematode diversity.

Community metabarcoding reveals the relative role of environmental filtering and spatial processes in metacommunity dynamics of soil microarthropods across a mosaic of montane forests

Disentangling the relative role of environmental filtering and spatial processes in driving metacommunity structure across mountainous regions remains challenging, as the way we quantify spatial connectivity in topographically and environmentally heterogeneous landscapes can influence our perception of which process predominates. More empirical data sets are required to account for taxon- and context-dependency, but relevant research in understudied areas is often compromised by the taxonomic impediment. Here we used haplotype-level community DNA metabarcoding, enabled by stringent filtering of amplicon sequence variants (ASVs), to characterize metacommunity structure of soil microarthropod assemblages across a mosaic of five forest habitats on the Troodos mountain range in Cyprus. We found similar β diversity patterns at ASV and species (OTU, operational taxonomic unit) levels, which pointed to a primary role of habitat filtering resulting in the existence of largely distinct metacommunities linked to different forest types. Within-habitat turnover was correlated to topoclimatic heterogeneity, again emphasizing the role of environmental filtering. However, when integrating landscape matrix information for the highly fragmented Quercus alnifolia habitat, we also detected a major role of spatial isolation determined by patch connectivity, indicating that stochastic and niche-based processes synergistically govern community assembly. Alpha diversity patterns varied between ASV and OTU levels, with OTU richness decreasing with elevation and ASV richness following a longitudinal gradient, potentially reflecting a decline of genetic diversity eastwards due to historical pressures. Our study demonstrates the utility of haplotype-level community metabarcoding for characterizing metacommunity structure of complex assemblages and improving our understanding of biodiversity dynamics across mountainous landscapes worldwide.

Degree of urbanization and vegetation type shape soil biodiversity in city parks

Urbanization negatively impacts aboveground biodiversity, such as bird and insect communities. City parks can reduce these negative impacts by providing important habitat. However, it remains poorly understood how the degree of urbanization and vegetation types within city parks (e.g., lawns, woodland) impact soil biodiversity. Here we investigated the impact of the degree of urbanization (urban vs. suburban) and vegetation type (lawn, shrub-lawn, tree-lawn and tree-shrub mixtures) on soil biodiversity in parkland systems. We used eDNA metabarcoding to characterize soil biodiversity of bacteria, fungi, protists, nematodes, meso- and macrofauna across park vegetation types in urban and suburban regions in Xiamen, China. We observed a strong effect of the degree of urbanization on the richness of different soil biota groups, with higher species richness of protists and meso/macrofauna in urban compared to suburban areas, while the richness of bacteria and fungi did not differ, and the difference of nematode richness depended on vegetation type. At the functional level, increased degree of urbanization associated with greater species richness of bacterivores, plant pathogens and animal parasites. These urbanization effects were at least partly modulated by higher soil phosphorous levels in urban compared to suburban sites. Also, the vegetation type impacted soil biodiversity, particularly fungal richness, with the richness of pathogenic and saprotrophic fungi increasing from lawn to tree-shrub mixtures. Tree-shrub mixtures also had the highest connectedness between biotas and lowest variation in the soil community structure. Overall, we show that soil biodiversity is strongly linked to the degree of urbanization, with overall richness increasing with urbanization, especially in bacterivores, plant pathogens and animal parasites. Targeted management of vegetation types in urban areas should provide a useful way to help mitigate the negative effect of urbanization on soil biodiversity.

The community ecology perspective of omics data

The measurement of uncharacterized pools of biological molecules through techniques such as metabarcoding, metagenomics, metatranscriptomics, metabolomics, and metaproteomics produces large, multivariate datasets. Analyses of these datasets have successfully been borrowed from community ecology to characterize the molecular diversity of samples (ɑ-diversity) and to assess how these profiles change in response to experimental treatments or across gradients (β-diversity). However, sample preparation and data collection methods generate biases and noise which confound molecular diversity estimates and require special attention. Here, we examine how technical biases and noise that are introduced into multivariate molecular data affect the estimation of the components of diversity (i.e., total number of different molecular species, or entities; total number of molecules; and the abundance distribution of molecular entities). We then explore under which conditions these biases affect the measurement of ɑ- and β-diversity and highlight how novel methods commonly used in community ecology can be adopted to improve the interpretation and integration of multivariate molecular data. Video Abstract.

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

Metabarcoding approaches are exponentially increasing 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. Nowadays, soil eukaryotes are targeted with the same approaches developed for bacteria and archaea (prokaryotes). 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, currently 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 evolutionary rates than prokaryotes, which prevent capturing 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.

Depth-structuring of multi-kingdom soil communities in agricultural pastures

The biodiversity and structure of deep agricultural soil communities are poorly understood, especially for eukaryotes. Using DNA metabarcoding and co-occurrence networks, we tested whether prokaryote, fungal, protist, and nematode biodiversity declines with increasing depth (0-0.1,  0.3-0.5,  and 1.1-1.7m) in pastoral soil; whether deep soil organisms are subsets of those at the surface; and whether multi-kingdom networks become more interconnected with increasing depth. Depth-related richness declines were observed for almost all detected fungal classes, protist phyla, and nematode orders, but only 13 of 25 prokaryote phyla, of which nine had increasing richness with depth. Deep soil communities were not simply subsets of surface communities, with 3.8%-12.2% of eukaryotes and 13.2% of prokaryotes detected only in the deepest samples. Eukaryotes mainly occurred in the upper soil layers whereas prokaryotes were more evenly distributed across depths. Plant-feeding nematodes were most abundant in top soil, whereas bacteria feeders were more abundant in deep soil. Co-occurrence network structure differences suggested that deep soil communities are concentrated around scarce niches of resource availability, in contrast to more spatially homogenous and abundant resources at the surface. Together, these results demonstrate effects of depth on the composition, distribution, and structure of prokaryote and eukaryote soil communities.

Improved high throughput protocol for targeting eukaryotic symbionts in metazoan and eDNA samples

Eukaryote symbionts of animals are major drivers of ecosystems not only because of their diversity and host interactions from variable pathogenicity but also through different key roles such as commensalism and to different types of interdependence. However, molecular investigations of metazoan eukaryomes require minimising coamplification of homologous host genes. In this study we (1) identified a previously published “antimetazoan” reverse primer to theoretically enable amplification of a wider range of microeukaryotic symbionts, including more evolutionarily divergent sequence types, (2) evaluated in silico several antimetazoan primer combinations, and (3) optimised the application of the best performing primer pair for high throughput sequencing (HTS) by comparing one‐step and two‐step PCR amplification approaches, testing different annealing temperatures and evaluating the taxonomic profiles produced by HTS and data analysis. The primer combination 574*F – UNonMet_DB tested in silico showed the largest diversity of nonmetazoan sequence types in the SILVA database and was also the shortest available primer combination for broadly‐targeting antimetazoan amplification across the 18S rRNA gene V4 region. We demonstrate that the one‐step PCR approach used for library preparation produces significantly lower proportions of metazoan reads, and a more comprehensive coverage of host‐associated microeukaryote reads than the two‐step approach. Using higher PCR annealing temperatures further increased the proportion of nonmetazoan reads in all sample types tested. The resulting V4 region amplicons were taxonomically informative even when only the forward read is analysed. This region also revealed a diversity of known and putatively parasitic lineages and a wider diversity of host‐associated eukaryotes.