High‐throughput sequencing outperforms traditional morphological methods in Blue Catfish diet analysis and reveals novel insights into diet ecology

Blue Catfish Ictalurus furcatus are an invasive, yet economically important species in the Chesapeake Bay. However, their impact on the trophic ecology of this system is not well understood. In order to provide in‐depth analysis of predation by Blue Catfish, we identified prey items using high‐throughput DNA sequencing (HTS) of entire gastrointestinal tracts from 134 samples using two genetic markers, mitochondrial cytochrome c oxidase I (COI) and the nuclear 18S ribosomal RNA gene. We compared our HTS results to a more traditional “hybrid” approach that coupled morphological identification with DNA barcoding. The hybrid study was conducted on additional Blue Catfish samples (n = 617 stomachs) collected from the same location and season in the previous year. Taxonomic representation with HTS vastly surpassed that achieved with the hybrid methodology in Blue Catfish. Significantly, our HTS study identified several instances of at‐risk and invasive species consumption not identified using the hybrid method, supporting the hypothesis that previous studies using morphological methods may greatly underestimate consumption of critical species. Finally, we report the novel finding that Blue Catfish diet diversity inversely correlates to daily flow rates, perhaps due to higher mobility and prey‐seeking behaviors exhibited during lower flow.     

Impact of a resistance gene against a fungal pathogen on the plant host residue microbiome: The case of the Leptosphaeria maculans–Brassica napus pathosystem

Oilseed rape residues are a crucial determinant of stem canker epidemiology as they support the sexual reproduction of the fungal pathogen Leptosphaeria maculans. The aim of this study was to characterize the impact of a resistance gene against L. maculans infection on residue microbial communities and to identify microorganisms interacting with this pathogen during residue degradation. We used near-isogenic lines to obtain healthy and infected host plants. The microbiome associated with the two types of plant residues was characterized by metabarcoding. A combination of linear discriminant analysis and ecological network analysis was used to compare the microbial communities and to identify microorganisms interacting with L. maculans. Fungal community structure differed between the two lines at harvest, but not subsequently, suggesting that the presence/absence of the resistance gene influences the microbiome at the base of the stem whilst the plant is alive, but that this does not necessarily lead to differential colonization of the residues by fungi. Direct interactions with other members of the community involved many fungal and bacterial amplicon sequence variants (ASVs). L. maculans appeared to play a minor role in networks, whereas one ASV affiliated to Plenodomus biglobosus (synonym Leptosphaeria biglobosa) from the Leptosphaeria species complex may be considered a keystone taxon in the networks at harvest. This approach could be used to identify and promote microorganisms with beneficial effects against residue-borne pathogens and, more broadly, to decipher the complex interactions between multispecies pathosystems and other microbial components in crop residues.     

Identifying error and accurately interpreting environmental DNA metabarcoding results: A case study to detect vertebrates at arid zone waterholes

Environmental DNA (eDNA) metabarcoding surveys enable rapid, noninvasive identification of taxa from trace samples with wide‐ranging applications from characterizing local biodiversity to identifying food‐web interactions. However, the technique is prone to error from two major sources: (a) contamination through foreign DNA entering the workflow, and (b) misidentification of DNA within the workflow. Both types of error have the potential to obscure true taxon presence or to increase taxonomic richness by incorrectly identifying taxa as present at sample sites, but multiple error sources can remain unaccounted for in metabarcoding studies. Here, we use data from an eDNA metabarcoding study designed to detect vertebrate species at waterholes in Australia's arid zone to illustrate where and how in the workflow errors can arise, and how to mitigate those errors. We detected the DNA of 36 taxa spanning 34 families, 19 orders and five vertebrate classes in water samples from waterholes, demonstrating the potential for eDNA metabarcoding surveys to provide rapid, noninvasive detection in remote locations, and to widely sample taxonomic diversity from aquatic through to terrestrial taxa. However, we initially identified 152 taxa in the samples, meaning there were many false positive detections. We identified the sources of these errors, allowing us to design a stepwise process to detect and remove error, and provide a template to minimize similar errors that are likely to arise in other metabarcoding studies. Our findings suggest eDNA metabarcoding surveys need to be carefully conducted and screened for errors to ensure their accuracy.     

Latent Dirichlet Allocation reveals spatial and taxonomic structure in a DNA‐based census of soil biodiversity from a tropical forest

High‐throughput sequencing of amplicons from environmental DNA samples permits rapid, standardized and comprehensive biodiversity assessments. However, retrieving and interpreting the structure of such data sets requires efficient methods for dimensionality reduction. Latent Dirichlet Allocation (LDA) can be used to decompose environmental DNA samples into overlapping assemblages of co‐occurring taxa. It is a flexible model‐based method adapted to uneven sample sizes and to large and sparse data sets. Here, we compare LDA performance on abundance and occurrence data, and we quantify the robustness of the LDA decomposition by measuring its stability with respect to the algorithm's initialization. We then apply LDA to a survey of 1,131 soil DNA samples that were collected in a 12‐ha plot of primary tropical forest and amplified using standard primers for bacteria, protists, fungi and metazoans. The analysis reveals that bacteria, protists and fungi exhibit a strong spatial structure, which matches the topographical features of the plot, while metazoans do not, confirming that microbial diversity is primarily controlled by environmental variation at the studied scale. We conclude that LDA is a sensitive, robust and computationally efficient method to detect and interpret the structure of large DNA‐based biodiversity data sets. We finally discuss the possible future applications of this approach for the study of biodiversity.     

Plant species identity drives soil microbial community structures that persist under a following crop

Compared to monocultures, multi‐species swards have demonstrated numerous positive diversity effects on aboveground plant performance, such as yield, N concentration, and even legacy effects on a following crop. Whether such diversity effects are seen in the soil microbiome is currently unclear. In a field experiment, we analyzed the effect that three plant species (a grass, forb, and legume), and mixtures of these, had on soil fungal and bacterial community structures, as well as their associated legacy effects under a following crop, the grass Lolium multiflorum. We utilized six sward types, three monocultures (Lolium perenne, Cichorium intybus and Trifolium pratense), two bi‐species mixtures, and a mixture of the three species. Soil samples were taken from these swards in March (at the end of a three year conditioning phase) and in June, August, and September after L. multiflorum was established, that is, the legacy samplings. When present, the differing monocultures had a significant effect on various aspects of the fungal community: structure, OTU richness, the relative abundance of the phylum Glomeromycota, and indicator OTUs. The effect on bacterial community structure was not as strong. In the multi‐species swards, a blending of individual plant species monoculture effects (identity effect) was seen in (a) fungal and bacterial community structure and (b) fungal OTU richness and the relative abundance of the Glomeromycota. This would indicate that plant species identity, rather than diversity effects (i.e., the interactions among the plant species), was the stronger determinant. During the legacy samplings, structural patterns in the fungal and bacterial communities associated with the previous swards were retained, but the effect faded with time. These results highlight that plant species identity can be a strong driver of soil microbial community structures. They also suggest that their legacy effect on the soil microbiome may play a crucial role in following crop performance.     

Efficacy of metabarcoding for identification of fish eggs evaluated with mock communities

There is urgent need for effective and efficient monitoring of marine fish populations. Monitoring eggs and larval fish may be more informative than that traditional fish surveys since ichthyoplankton surveys reveal the reproductive activities of fish populations, which directly impact their population trajectories. Ichthyoplankton surveys have turned to molecular methods (DNA barcoding & metabarcoding) for identification of eggs and larval fish due to challenges of morphological identification. In this study, we examine the effectiveness of using metabarcoding methods on mock communities of known fish egg DNA. We constructed six mock communities with known ratios of species. In addition, we analyzed two samples from a large field collection of fish eggs and compared metabarcoding results with traditional DNA barcoding results. We examine the ability of our metabarcoding methods to detect species and relative proportion of species identified in each mock community. We found that our metabarcoding methods were able to detect species at very low input proportions; however, levels of successful detection depended on the markers used in amplification, suggesting that the use of multiple markers is desirable. Variability in our quantitative results may result from amplification bias as well as interspecific variation in mitochondrial DNA copy number. Our results demonstrate that there remain significant challenges to using metabarcoding for estimating proportional species composition; however, the results provide important insights into understanding how to interpret metabarcoding data. This study will aid in the continuing development of efficient molecular methods of biological monitoring for fisheries management.     

Toward a standardized quantitative and qualitative insect monitoring scheme

The number of insect species and insect abundances decreased severely during the past decades over major parts of Central Europe. Previous studies documented declines of species richness, abundances, shifts in species composition, and decreasing biomass of flying insects. In this study, we present a standardized approach to quantitatively and qualitatively assess insect diversity, biomass, and the abundance of taxa, in parallel. We applied two methods: Malaise traps, and automated and active light trapping. Sampling was conducted from April to October 2018 in southern Germany, at four sites representing conventional and organic farming. Bulk samples obtained from Malaise traps were further analyzed using DNA metabarcoding. Larger moths (Macroheterocera) collected with light trapping were further classified according to their degree of endangerment. Our methods provide valuable quantitative and qualitative data. Our results indicate more biomass and higher species richness, as well as twice the number of Red List lepidopterans in organic farmland than in conventional farmland. This combination of sampling methods with subsequent DNA metabarcoding and assignments of individuals according depending on ecological characteristics and the degree of endangerment allows to evaluate the status of landscapes and represents a suitable setup for large‐scale long‐term insect monitoring across Central Europe, and elsewhere.     

Biochar alters the soil microbiome and soil function: results of next‐generation amplicon sequencing across Europe

Wide‐scale application of biochar to soil has been suggested as a mechanism to offset increases in CO₂ emissions through the long‐term sequestration of a carbon rich and inert substance to the soil, but the implications of this for soil diversity and function remain to be determined. Biochar is capable of inducing changes in soil bacterial communities, but the exact impacts of its application are poorly understood. Using three European sites [UK SRC, short rotation coppice, French grassland (FR) and Italian SRF, short rotation forestry (IT)] treated with identical biochar applications, we undertook 16S and ITS amplicon DNA sequencing. In addition, we carried out assessments of community change over time and N and P mobilization in the UK. Significant changes in bacterial and community structure occurred due to treatment, although the nature of the changes varied by site. STAMP differential abundance analysis showed enrichment of Gemmatimonadete and Acidobacteria in UK biochar plots 1 year after application, whilst control plots exhibited enriched Gemmataceae, Isosphaeraceae and Koribacteraceae. Increased mobility of ammonium and phosphates was also detected after 1 year, coupled with a shift from acid to alkaline phosphomonoesterase activity, which may suggest an ecological and functional shift towards a more copiotrophic ecology. Italy also exhibited enrichments, in both the Proteobacteria (driven by an increase in the order Rhizobiales) and the Gemmatimonadetes. No significant change in the abundance of individual taxa was noted in FR, although a small significant change in unweighted UNIFRAC occurred, indicating variation in the identities of taxa present due to treatment. Fungal β diversity was affected by treatment in IT and FR, but was unaffected in UK samples. The effects of time and site were greater than that of biochar application in UK samples. Overall, this report gives a tantalizing view of the soil microbiome at several sites across Europe and suggests that although application of biochar has significant effects on microbial communities, these may be small compared with the highly variable soil microbiome that is found in different soils and changes with time.