Investigating variability in microbial community composition in replicate environmental DNA samples down lake sediment cores

Lake sediments are natural archives that accumulate information on biological communities and their surrounding catchments. Paleolimnology has traditionally focussed on identifying fossilized organisms to reconstruct past environments. In the last decade, the application of molecular methodologies has increased in paleolimnological studies, but further research investigating factors such as sample heterogeneity and DNA degradation are required. In the present study we investigated bacterial community heterogeneity (16S rRNA metabarcoding) within depth slices (1-cm width). Sediment cores were collected from three lakes with differing sediment compositions. Samples were collected from a variety of depths which represent a period of time of approximately 1,200 years. Triplicate samples were collected from each depth slice and bacterial 16S rRNA metabarcoding was undertaken on each sample. Accumulation curves demonstrated that except for the deepest (oldest) slices, the combination of three replicate samples were insufficient to characterise the entire bacterial diversity. However, shared Amplicon Sequence Variants (ASVs) accounted for the majority of the reads in each depth slice (max. shared proportional read abundance 96%, 86%, 65% in the three lakes). Replicates within a depth slice generally clustered together in the Non-metric multidimensional scaling analysis. There was high community dissimilarity in older sediment in one of the cores, which was likely due to the laminae in the sediment core not being horizontal. Given that most paleolimnology studies explore broad scale shifts in community structure rather than seeking to identify rare species, this study demonstrates that a single sample is adequate to characterise shifts in dominant bacterial ASVs.

Environmental DNA variability in lake sediment cores

Lake sediments are natural archives that accumulate information about biological communities and their surrounding catchments. Paleolimnology has traditionally focussed on identifying fossilized organisms to reconstruct past environments. In the last decade, the application of molecular methodologies has increased in paleolimnological studies, but further studies investigating factors such as sample heterogeneity and DNA degradation are required. Here we investigated bacterial community heterogeneity (16S rRNA metabarcoding) within depth slices. Sediment cores were collected from three lakes with differing sediment compositions. Samples were collected from a variety of depths (1-cm width) which represent a period of time of approximately 1,200 years. Triplicate samples were collected from each slice and bacterial 16S rRNA metabarcoding was undertaken on each sample. Rarefaction curves showed that except for the deepest (oldest) slices, the combination of three replicate samples were insufficient to characterise the entire bacterial diversity. However, shared Amplicon Sequence Variants (ASVs) accounted for the majority of the reads in each slice (max. shared proportional read abundance 96%, 86%, 65% in the three lakes). Within slice similarity was higher than between slice similarity. No general trend was observed in variability among replicates with depth amongst the lakes. In one core. there was a higher community dissimilarity in older sediment, which may be due to laminae not being horizontal. These results highlight the fact that microbial communities can be differentiated with depth however it is critical to interpret these results in the context of the stratigraphic data of the core.

Optimization and Application of direct PCR in community metabarcoding

Direct PCR allows the amplification of DNA from animal or plant tissue samples without the need for DNA extraction and purification steps. For this procedure, dry tissue is homogenized, dissolved in water and subsequently amplified, thus, its successful application largely depends on the absence of PCR inhibitors. Although this method has been successfully applied in barcoding approaches of invertebrates, it has not yet been attempted in metabarcoding approaches. We used nonbiting midges (Diptera: Chironomidae) to test if amplicons produced by direct PCR could be used for next-generation sequencing. To access whether direct PCR is applicable for a variety of chironomid species, we tested 236 adult specimens randomly selected from emergence traps of an artificial pond mesocosm. We used ground tissue, corresponding to 0.1% of the specimens’ biomass, and a direct PCR protocol following Wong et al. (2014) for amplification. In total, 98 % of the samples were successfully amplified and we found a diverse community comprised of 20 different genera. In order to compare direct PCR and ´traditional´ DNA isolation-PCR, we created mock communities (14 species) and used both approaches for the amplification of a 421 bp COI fragment. After a second PCR for indexing and adapter ligation, samples were sequenced on an Illumina sequencer. We found only slightly lower recovery rates for mock communities with the direct PCR approach compared to traditional protocols. These recovery rates were further improved for both methods when an equal biomass (ca. 0.006 mg) of chironomid specimens was used. With our approach, it was possible to detect species which constituted only 1% of the entire biomass of a sample. Generally, direct PCR did not have a large effect on sequence read abundance. However, read abundance varied strongly between species. We are currently investigating whether this was caused by primer bias or an artifact of differently degraded tissue. This study is a proof of principle that the amplicons produced by direct PCR can be used for next-generation sequencing, with possible applications for future biomonitoring projects and portable laboratory technologies. We are currently using this technique to monitor a large-scale chironomid community experiment (artificial pond mesocosm facility) covering weekly samples taken over two summer half-years.

Microbial composition, diversity, and activity varies across different types of basal ice

ABSTRACTBasal ice often contains entrained subglacial debris and sediment which can serve as a source of nutrients and organic matter and provide habitat for microorganisms adapted to frozen conditions. However, basal ice comes in many different forms and comparatively little is known about how microbial composition, diversity, and activity vary across different types of basal ice. Here, we investigated these parameters in four different types of basal ice from two different glaciers and then used a meta-analysis to compare our findings with microbiome studies of other permanently frozen environments. We found microbiome composition varies substantially between basal ice types, even within the same glacier. Further, the microbiomes of sediment-rich basal ices were distinct from those found in glacial ice and instead were most like those found in permafrost. Consistent with this, microbial diversity was also comparable to that found in permafrost and was much higher relative to glacial ice. Patterns of 16S rRNA read abundance from RNA relative to DNA implicated certain taxa as potentially active in basal ice with ice temperature appearing to be an important predictor for the diversity of taxa inferred to be active. Our results improve our understanding of the microbial ecology of different basal ice types and provide insight into which types are likely habitats for metabolizing microbial communities.

Sediment-associated microbial community profiling: sample pre-processing through sequential membrane filtration for 16s rDNA amplicon sequencing

ABSTRACTSequential membrane filtration as a pre-processing step for the isolation of microorganisms could provide good quality and integrity DNA that can be preserved and kept at ambient temperatures before community profiling through culture-independent molecular techniques, e.g., 16s rDNA amplicon sequencing. Here, we assessed the impact of pre-processing sediment samples by sequential membrane filtration (from 10, 5 to 0.22 μm pore size membrane filters) for 16s rDNA-based community profiling of sediment-associated microorganisms. Specifically, we examined if there would be method-driven differences between non- and pre-processed sediment samples regarding the quality and quantity of extracted DNA, PCR amplicon, resulting high-throughput sequencing reads, microbial diversity, and community composition. We found no significant difference in the quality and quantity of extracted DNA and PCR amplicons between the two methods. Although we found a significant difference in raw and quality-filtered reads, read abundance after bioinformatics processing (i.e., denoising and the chimeric-read filtering steps) were not significantly different. These results suggest that read abundance after these read processing steps were not influenced by sediment processing or lack thereof. Although the non- and pre-processed sediment samples had more unique than shared amplicon sequence variants (ASVs), we report that their shared ASVs accounted for 74% of both methods’ absolute read abundance. More so at the genus level, the final collection filter identified most of the genera (95% of the reads) captured from the non-processed samples, with a total of 51 false-negative (2%) and 59 false-positive genera (3%). Accordingly, the diversity estimates and community composition were not significantly different between the non- and pre-processed samples. We demonstrate that while there were differences in shared and unique taxa, both methods revealed comparable microbial diversity and community composition. We also suggest the inclusion of sequential filters (i.e., pre- and mid-filters) in the community profiling, given the additional taxa not detected from the non-processed and the final collection filter. Our observations highlight the feasibility of pre-processing sediment samples for community analysis and the need to further assess sampling strategies to help conceptualize appropriate study designs for sediment-associated microbial community profiling.

Validated removal of nuclear pseudogenes and sequencing artefacts from mitochondrial metabarcode data

Metabarcoding of Metazoa using mitochondrial genes may be confounded by both the accumulation of PCR and sequencing artefacts and the co-amplification of nuclear mitochondrial pseudogenes (NUMTs). The application of read abundance thresholds and denoising methods is efficient in reducing noise accompanying authentic mitochondrial amplicon sequence variants (ASVs). However, these procedures do not fully account for the complex nature of concomitant sequences and the highly variable DNA contribution of individuals in a metabarcoding sample. We propose, as a complement to denoising, the metabarcoding Multidimensional Abundance Threshold Evaluation (metaMATE) framework, a novel approach that allows comprehensive examination of multiple dimensions of abundance filtering and the evaluation of the prevalence of unwanted concomitant sequences in denoised metabarcoding datasets. metaMATE requires a denoised set of ASVs as input, and designates a subset of ASVs as being either authentic (mtDNA haplotypes) or non-authentic ASVs (NUMTs and erroneous sequences) by comparison to external reference data and by analysing nucleotide substitution patterns. metaMATE (i) facilitates the application of read abundance filtering strategies, which are structured with regard to sequence library and phylogeny and applied for a range of increasing abundance threshold values, and (ii) evaluates their performance by quantifying the prevalence of non-authentic ASVs and the collateral effects on the removal of authentic ASVs. The output from metaMATE facilitates decision-making about required filtering stringency and can be used to improve the reliability of intraspecific genetic information derived from metabarcode data. The framework is implemented in the metaMATE software, available at https://github.com/tjcreedy/metamate).

Quantification of past arctic herbivore populations from ancient sedimentary DNA by hybridization capture enrichment, metabarcoding, and droplet digital PCR

<p>The Arctic is currently experiencing dramatic ecosystem changes with immediate effects on biodiversity. Sedimentary ancient DNA is a unique and valuable source of information on ecosystem changes over a long temporal scale. Understanding these past changes may help predict the relative impacts of climate change, herbivory, and anthropogenic effects on present ecosystems. In the BiodivERsA project “Future ArcTic Ecosystems” (FATE), we aim to assess changes in past herbivore abundance over large spatial (circumarctic) and temporal (Last Glacial Maximum until today) scales using three (semi-)quantitative methods on sedimentary ancient DNA of plants, herbivores, and herbivore proxies (i.e. coprophilous fungi and parasites) – metabarcoding, hybridization capture enrichment, and droplet digital PCR (ddPCR).</p><p>Metabarcoding was applied to DNA of plants and also of coprophilous fungi as proxies of herbivore abundance. This approach is an established and important tool for assessing biodiversity from recent environmental DNA; however, quantification of specific taxa may be complicated due to inherent methodological biases (e.g. amplification efficiency due to primer bias), and our current understanding of the factors affecting potential quantification by metabarcoding is still limited. Moreover, ancient DNA is highly fragmented, which may prevent PCR amplification altogether. As an alternative, target enrichment by hybridization capture is a method that does not depend on target PCR amplification and is typically not affected by DNA fragmentation. Furthermore, hybridization capture can be used to target numerous genetic markers of a vast range of highly diverse taxa. We are using hybridization capture to enrich DNA of a range of herbivore species and numerous proxy organisms. Metabarcoding and hybridization capture can be applied to a vast taxonomic range and may be used quantitatively based on relative sequencing read abundance; however, the respective read abundance may be confounded by random and systematic errors and other biases. We are therefore using an additional quantification method – ddPCR – on several selected taxa, which is taxon-specific but facilitates highly accurate quantification of template DNA molecules in a given sample. The combined taxonomic and quantitative results of these three approaches are used to generate highly resolved datasets on past vegetation and herbivores, which allows us to reconstruct past vegetation changes over large spatial (circumarctic) and temporal (Last Glacial Maximum until today) scales.</p><p>Detailed inferences on herbivore abundance and reconstructing past ecological conditions may be important for ecosystem management and conservation in the face of accelerating changes in Arctic ecosystems due to global climate change.</p>

A highly diverse fungal community associated with leaves of the mangrove plant Acanthus ilicifolius var. xiamenensis revealed by isolation and metabarcoding analyses

A high diversity of culturable foliar endophytic fungi is known from various mangrove plants, and the core taxa include species from Colletotrichum, Pestalotiopsis, Phoma, Phomopsis, Sporomiella, among others. Since a small fraction of fungi is able to grow in culture, this study investigated the diversity of fungi associated with leaves of Acanthus ilicifolius var. xiamenensis using both isolation and metabarcoding approaches. A total of 203 isolates were cultured from surface-sterilized leaves, representing 47 different fungal species: 30 species from the winter samples (104 isolates), and 26 species from the summer samples (99 isolates). Ascomycota was dominant in both types of leaf samples, while Basidiomycota was isolated only from the summer samples. Drechslera dematioidea (10.58%, percentage of occurrence), Colletotrichum sp. 3 (7.69%) and Alternaria sp. (7.69%) were dominant in the winter samples; Fusarium oxysporum (13.13%), Diaporthe endophytica (10.10%) and Colletotrichum sp. 1 (9.09%) in the summer samples. Overall, Corynespora cassiicola (6.90%), F. oxysporum (6.40%) and Guignardia sp. (6.40%) had the highest overall percentage of occurrence. In the metabarcoding analysis, a total of 111 operational taxonomic units (OTUs) were identified from 17 leaf samples: 96 OTUs from the winter and 70 OTUs from the summer samples. Sequences belonging to Ascomycota and Basidiomycota were detected in both samples but the former phylum was dominant over the latter. Based on read abundance, taxa having the highest percentage of occurrence included Alternaria sp. (3.46%), Cladosporium delicatulum (2.56%) and Pyrenochaetopsis leptospora (1.41%) in the winter leaves, and Aureobasidium sp. (10.72%), Cladosporium sp. (7.90%), C. delicatulum (3.45%) and Hortaea werneckii (3.21%) in the summer leaves. These latter four species also had the highest overall percentage of occurrence. Combining the results from both methods, a high diversity of fungi (at least 110 species) was found associated with leaves of A. ilicifolius var. xiamenensis. Many of the fungi identified were plant pathogens and may eventually cause diseases in the host.

A validated workflow for rapid taxonomic assignment and monitoring of a national fauna of bees (Apiformes) using high throughput barcoding

ABSTRACTImproved taxonomic methods are needed to quantify declining populations of insect pollinators. This study devises a high-throughput DNA barcoding protocol for a regional fauna (United Kingdom) of bees (Apiformes), consisting of reference library construction, a proof-of-concept monitoring scheme, and the deep barcoding of individuals to assess potential artefacts and organismal associations. A reference database of Cytochrome Oxidase subunit 1 (cox1) sequences including 92.4% of 278 bee species known from the UK showed high congruence with morphological taxon concepts, but molecular species delimitations resulted in numerous split and (fewer) lumped entities within the Linnaean species. Double tagging permitted deep illumina sequencing of 762 separate individuals of bees from a UK-wide survey. Extracting the target barcode from the amplicon mix required a new protocol employing read abundance and phylogenetic position, which revealed 180 molecular entities of Apiformes identifiable to species. An additional 72 entities were ascribed to mitochondrial pseudogenes based on patterns of read abundance and phylogenetic relatedness to the reference set. Clustering of reads revealed a range of secondary Operational Taxonomic Units (OTUs) in almost all samples, resulting from traces of insect species caught in the same traps, organisms associated with the insects including a known mite parasite of bees, and the common detection of human DNA, besides evidence for low-level cross-contamination in pan traps and laboratory steps. Custom scripts were generated to conduct critical steps of the bioinformatics protocol. The resources built here will greatly aid DNA-based monitoring to inform management and conservation policies for the protection of pollinators.

Revealing the Complexities of Metabarcoding with a Diverse Arthropod Mock Community

DNA metabarcoding is an attractive approach for monitoring biodiversity. However, it is subject to biases that often impede detection of all species in a sample. In particular, the proportion of sequences recovered from each species depends on its biomass, mitome copy number, and primer set employed for PCR. To examine these variables, we constructed a mock community of terrestrial arthropods comprised of 374 BINs, a species proxy. We used this community to examine how species recovery was impacted when amplicon pools were constructed in four ways. The first two protocols involved the construction of bulk DNA extracts from different body partitions (Bulk Abdomen, Bulk Leg). The other protocols involved the production of DNA extracts from single legs which were then merged prior to PCR (Composite Leg) or PCR-amplified separately (Single Leg) and then pooled. The amplicon generated by these four treatments were then sequenced on three platforms (Illumina MiSeq, Ion Torrent PGM and Ion Torrent S5). The choice of sequencing platform did not substantially influence species recovery, other variables did. As expected, the best recovery was obtained from the Single Leg treatment, but the Bulk Abdomen produced a more uniform read abundance than the Bulk Leg or Composite Leg samples. Primer choice also influenced species recovery. Our results reveal how variation in protocols can have substantive impacts on perceived diversity unless sequencing coverage is sufficient to reach an asymptote. Although metabarcoding is a powerful approach, further optimization of analytical protocols is crucial to obtain reproducible results and increase its cost-effectiveness.