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As the scope of plant eDNA metabarcoding diversifies, so do the primers, markers and methods. A wealth of primers exists today, but their comparative evaluation is lacking behind. Similarly, multi‐marker approaches are recommended but debates persist regarding barcode complementarity and optimal combinations. After a literature compilation of used primers, we compared in silico 102 primer pairs based on amplicon size, coverage and specificity, followed by an experimental evaluation of 15 primer pairs on a mock community sample covering 268 plant species and genera, and about 100 families. The analysis was done for the four most common plant metabarcoding markers, rbcL, trnL, ITS1 and ITS2 and their complementarity was assessed based on retrieved species. By focusing on existing primers, we identify common designs, promote alternatives and enhance prior‐supported primers for immediate applications. The ITS2 was the best‐performing marker for flowering vascular plants and was congruent to ITS1. However, the combined taxonomic breadth of ITS2 and rbcL surpassed any other combination, highlighting their high complementarity across Streptophyta. Overall, our study underscores the significance of comprehensive primer and barcode evaluations tailored to metabarcoding applications. [ABSTRACT FROM AUTHOR]

The small subunit (SSU) ribosomal RNA (rRNA) is the most commonly used marker for the identification of microbial taxa, but its full‐length reconstruction from high‐throughput sequencing (HTS) data remains challenging. Metagenomics and total RNA sequencing (total RNA‐Seq) are target‐PCR‐free HTS methods that are used to characterize microbial communities and simultaneously reconstruct SSU rRNA sequences. However, more testing is required to determine and improve their effectiveness.We processed metagenomics and total RNA‐Seq data retrieved from a commercially available mock microbial community and an aquarium sample using 112 combinations of data processing tools. We determined the SSU rRNA reconstruction completeness of both sequencing methods for both samples and analysed the impact of data processing tools on SSU rRNA completeness.In contrast to metagenomics, total RNA‐Seq allowed for the complete or near‐complete reconstruction of all mock community SSU rRNA sequences and generated up to 438 SSU rRNA sequences with ≥80% completeness from the aquarium sample using only 1/5 of an Illumina MiSeq run. SSU rRNA completeness of metagenomics significantly correlated with the genome size of mock community species. Data processing tools impacted SSU rRNA completeness, in particular the utilized assemblers.These results are promising for the high‐throughput reconstruction of novel full‐length SSU rRNA sequences and could advance the simultaneous application of multiple ‐omics approaches in routine environmental assessments to allow for more holistic assessments of ecosystems. [ABSTRACT FROM AUTHOR]

Fish eDNA metabarcoding is usually performed from filtered water samples. The volume of filtered water depends on the study scope and can rapidly become time consuming according to the number of samples that have to be processed. To avoid time allocated to filtration, passive DNA samplers have been used to recover fish eDNA from marine environments faster. In freshwater ecosystems, aquatic biofilms were used to catch eDNA from macroinvertebrates. Here, we test the capacity of aquatic biofilms to entrap fish eDNA in a large lake and, therefore, the possibility to perform fish eDNA metabarcoding from this matrix compared to the traditional fish eDNA approach from filtered water samples. Methodological aspects of the use of aquatic biofilms for fish eDNA metabarcoding (e.g. PCR replicates, biological replicates, bioinformatics pipeline, reference database and taxonomic assignment) were validated against a mock community. When using biofilms from habitats sheltered from wind and waves, biofilm and water approach provided similar inventories. Richness and diversity were comparable between both approaches. Approaches differed only for rare taxa. Our results illustrate the capacity of aquatic biofilms to act as passive eDNA samplers of fish eDNA and, therefore, the possibility to use biofilms to monitor fish communities efficiently from biofilms. Furthermore, our results open up avenues of research to study a diversity of biological groups (among which bioindicators as diatoms, macroinvertebrates and fish) from eDNA isolated from a single environmental matrix reducing sampling efforts, analysis time and costs. [ABSTRACT FROM AUTHOR]

Metabarcoding is an important tool for understanding fungal communities. The internal transcribed spacer (ITS) rDNA is the accepted fungal barcode but has known problems. The large subunit (LSU) rDNA has also been used to investigate fungal communities but available LSU metabarcoding primers were mostly designed to target Dikarya (Ascomycota + Basidiomycota) with little attention to early diverging fungi (EDF). However, evidence from multiple studies suggests that EDF comprise a large portion of unknown diversity in community sampling. Here, we investigate how DNA marker choice and methodological biases impact recovery of EDF from environmental samples. We focused on one EDF lineage, Zoopagomycota, as an example. We evaluated three primer sets (ITS1F/ITS2, LROR/LR3, and LR3 paired with new primer LR22F) to amplify and sequence a Zoopagomycota mock community and a set of 146 environmental samples with Illumina MiSeq. We compared two taxonomy assignment methods and created an LSU reference database compatible with AMPtk software. The two taxonomy assignment methods recovered strikingly different communities of fungi and EDF. Target fragment length variation exacerbated PCR amplification biases and influenced downstream taxonomic assignments, but this effect was greater for EDF than Dikarya. To improve identification of LSU amplicons we performed phylogenetic reconstruction and illustrate the advantages of this critical tool for investigating identified and unidentified sequences. Our results suggest much of the EDF community may be missed or misidentified with "standard" metabarcoding approaches and modified techniques are needed to understand the role of these taxa in a broader ecological context. [ABSTRACT FROM AUTHOR]

The effective use of metabarcoding in biodiversity science has brought important analytical challenges due to the need to generate accurate taxonomic assignments. The assignment of sequences to genus or species level is critical for biodiversity surveys and biomonitoring, but it is particularly challenging as researchers must select the approach that best recovers information on species composition. This study evaluates the performance and accuracy of seven methods in recovering the species composition of mock communities by using COI barcode fragments. The mock communities varied in species number and specimen abundance, while upstream molecular and bioinformatic variables were held constant, and using a set of COI fragments. We evaluated the impact of parameter optimization on the quality of the predictions. Our results indicate that BLAST top hit competes well with more complex approaches if optimized for the mock community under study. For example, the two machine learning methods that were benchmarked proved more sensitive to reference database heterogeneity and completeness than methods based on sequence similarity. The accuracy of assignments was impacted by both species and specimen counts (query compositional heterogeneity) which ultimately influence the selection of appropriate software. We urge researchers to: (i) use realistic mock communities to allow optimization of parameters, regardless of the taxonomic assignment method employed; (ii) carefully choose and curate the reference databases including completeness; and (iii) use QIIME, BLAST or LCA methods, in conjunction with parameter tuning to better assign taxonomy to diverse communities, especially when information on species diversity is lacking for the area under study. see also the Perspective by Holly M. Bik. [ABSTRACT FROM AUTHOR]

Although most predators are generalists, the majority of studies on the association between prey availability and prey consumption have focused on specialist predators. To investigate the role of highly generalist predators in a complex food web, we measured the relationships between prey consumption and prey availability in two common arthropodivorous bats. Specifically, we used high‐throughput amplicon sequencing coupled with a known mock community to characterize seasonal changes in little brown and big brown bat diets. We then linked spatiotemporal variation in prey consumption with quantitative prey availability estimated from intensive prey community sampling. We found that although quantitative prey availability fluctuated substantially over space and time, the most commonly consumed prey items were consistently detected in bat diets independently of their respective abundance. Positive relationships between prey abundance and probability of consumption were found only among prey groups that were less frequently detected in bat diets. While the probability of prey consumption was largely unrelated to abundance, the community structure of prey detected in bat diets was influenced by the local or regional abundance of prey. Observed patterns suggest that while little brown and big brown bats maintain preferences for particular prey independently of quantitative prey availability, total dietary composition may reflect some degree of opportunistic foraging. Overall, our findings suggest that generalist predators can display strong prey preferences that persist despite quantitative changes in prey availability. [ABSTRACT FROM AUTHOR]

Summary: Recent studies have questioned the use of high‐throughput sequencing of the nuclear ribosomal internal transcribed spacer (ITS) region to derive a semi‐quantitative representation of fungal community composition. However, comprehensive studies that quantify biases occurring during PCR and sequencing of ITS amplicons are still lacking.We used artificially assembled communities consisting of 10 ITS‐like fragments of varying lengths and guanine‐cytosine (GC) contents to evaluate and quantify biases during PCR and sequencing with Illumina MiSeq, PacBio RS II and PacBio Sequel I technologies.Fragment length variation was the main source of bias in observed community composition relative to the template, with longer fragments generally being under‐represented for all sequencing platforms. This bias was three times higher for Illumina MiSeq than for PacBio RS II and Sequel I. All 10 fragments in the artificial community were recovered when sequenced with PacBio technologies, whereas the three longest fragments (> 447 bases) were lost when sequenced with Illumina MiSeq. Fragment length bias also increased linearly with increasing number of PCR cycles but could be mitigated by optimization of the PCR setup. No significant biases related to GC content were observed.Despite lower sequencing output, PacBio sequencing was better able to reflect the community composition of the template than Illumina MiSeq sequencing. [ABSTRACT FROM AUTHOR]

High‐throughput sequencing has the potential to describe biological communities with high efficiency yet comprehensive assessment of diversity with species‐level resolution remains one of the most challenging aspects of metabarcoding studies. We investigated the utility of curated ribosomal and mitochondrial nematode reference sequence databases for determining phylum‐specific species‐level clustering thresholds. We compiled 438 ribosomal and 290 mitochondrial sequences which identified 99% and 94% as the species delineation clustering threshold, respectively. These thresholds were evaluated in HTS data from mock communities containing 39 nematode species as well as environmental samples from Vietnam. We compared the taxonomic description of the mocks generated by two read‐merging and two clustering algorithms and the cluster‐free Dada2 pipeline. Taxonomic assignment with the RDP classifier was assessed under different training sets. Our results showed that 36/39 mock nematode species were identified across the molecular markers (18S: 32, JB2: 19, JB3: 21) in UClust_ref OTUs at their respective clustering thresholds, outperforming UParse_denovo and the commonly used 97% similarity. Dada2 generated the most realistic number of ASVs (18S: 83, JB2: 75, JB3: 82), collectively identifying 30/39 mock species. The ribosomal marker outperformed the mitochondrial markers in terms of species and genus‐level detections for both OTUs and ASVs. The number of taxonomic assignments of OTUs/ASVs was highest when the smallest reference database containing only nematode sequences was used and when sequences were truncated to the respective amplicon length. Overall, OTUs generated more species‐level detections, which were, however, associated with higher error rates compared to ASVs. Genus‐level assignments using ASVs exhibited higher accuracy and lower error rates compared to species‐level assignments, suggesting that this is the most reliable pipeline for rapid assessment of alpha diversity from environmental samples. Curated DNA barcode data were used to delineate nematode‐specific inter‐specific operational taxonomic unit (OTUs) clustering thresholds, which were subsequently tested on a artificial nematode community and environmental samples. Open‐reference clustering (UClust_ref) at these empirically derived thresholds outperformed denovo (UParse) as well as cluster‐free approaches (DADA2), resulting in the most accurate description of the nematode community. [ABSTRACT FROM AUTHOR]

Receiving the same results from repeated analysis of the same sample is a basic principle in science. The inability to reproduce previously published results has led to discussions of a reproducibility crisis within science. For studies of microbial communities, the problem of reproducibility is more pronounced and has, in some fields, led to a discussion on the very existence of a constantly present microbiota. In this study, DNA from 44 bovine milk samples were extracted twice and the V3-V4 region of the 16S rRNA gene was sequenced in two separate runs. The FASTQ files from the two data sets were run through the same bioinformatics pipeline using the same settings and results from the two data sets were compared. Milk samples collected maximally 2 h apart were used as replicates and permitted comparisons to be made within the same run. Results show a significant difference in species richness between the two sequencing runs although Shannon and Simpson's diversity was the same. Multivariate analyses of all samples demonstrate that the sequencing run was a driver for variation. Direct comparison of similarity between samples and sequencing run showed an average similarity of 42%-45% depending on whether binary or abundance-based similarity indices were used. Within-run comparisons of milk samples collected maximally 2 h apart showed an average similarity of 39%-47% depending on the similarity index used and that similarity differed significantly between runs. We conclude that repeated DNA extraction and sequencing significantly can affect the results of a low microbial biomass microbiota study., (© 2023 The Authors. MicrobiologyOpen published by John Wiley & Sons Ltd.)

DNA metabarcoding is widely used to study prokaryotic and eukaryotic microbial diversity. Technological constraints limit most studies to marker lengths below 600 base pairs (bp). Longer sequencing reads of several thousand bp are now possible with third‐generation sequencing. Increased marker lengths provide greater taxonomic resolution and allow for phylogenetic methods of classification, but longer reads may be subject to higher rates of sequencing error and chimera formation. In addition, most bioinformatics tools for DNA metabarcoding were designed for short reads and are therefore unsuitable. Here, we used Pacific Biosciences circular consensus sequencing (CCS) to DNA‐metabarcode environmental samples using a ca. 4,500 bp marker that included most of the eukaryote SSU and LSU rRNA genes and the complete ITS region. We developed an analysis pipeline that reduced error rates to levels comparable to short‐read platforms. Validation using a mock community indicated that our pipeline detected 98% of chimeras de novo. We recovered 947 OTUs from water and sediment samples from a natural lake, 848 of which could be classified to phylum, 397 to genus and 330 to species. By allowing for the simultaneous use of three databases (Unite, SILVA and RDP LSU), long‐read DNA metabarcoding provided better taxonomic resolution than any single marker. We foresee the use of long reads enabling the cross‐validation of reference sequences and the synthesis of ribosomal rRNA gene databases. The universal nature of the rRNA operon and our recovery of >100 nonfungal OTUs indicate that long‐read DNA metabarcoding holds promise for studies of eukaryotic diversity more broadly. [ABSTRACT FROM AUTHOR]

Abstract: Microbial ecology has been profoundly advanced by the ability to profile complex microbial communities by sequencing of marker genes amplified from environmental samples. However, inclusion of appropriate controls is vital to revealing the limitations and biases of this technique. “Mock community” samples, in which the composition and relative abundances of community members are known, are particularly valuable for guiding library preparation and data processing decisions. I generated a set of three mock communities using 19 different fungal taxa and demonstrate their utility by contrasting amplicon sequencing data obtained for the same communities under modifications to PCR conditions during library preparation. Increasing the number of PCR cycles elevated rates of chimera formation, and of errors in the final data set. Extension time during PCR had little impact on chimera formation, error rate or observed community structure. Polymerase fidelity impacted error rates significantly. Despite a high error rate, a master mix optimized to minimize amplification bias yielded profiles that were most similar to the true community structure. Bias against particular taxa differed among ITS1 vs. ITS2 loci. Preclustering nearly identical reads substantially reduced error rates, but did not improve similarity to the expected community structure. Inaccuracies in amplicon sequence‐based estimates of fungal community structure were associated with amplification bias and size selection processes, as well as variable culling rates among reads from different taxa. In some cases, the numerically dominant taxon was completely absent from final data sets, highlighting the need for further methodological improvements to avoid biased observations of community profiles. [ABSTRACT FROM AUTHOR]

With the increasing democratization of high-throughput sequencing ( HTS) technologies, along with the concomitant increase in sequence yield per dollar, many researchers are exploring HTS for microbial community ecology. Many elements of experimental design can drastically affect the final observed community structure, notably the choice of primers for amplification prior to sequencing. Some targeted microbes can fail to amplify due to primer-targeted sequence divergence and be omitted from obtained sequences, leading to differences among primer pairs in the sequenced organisms even when targeting the same community. This potential source of taxonomic bias in HTS makes it prudent to investigate how primer choice will affect the sequenced community prior to investing in a costly community-wide sequencing effort. Here, we use Fluidigm's microfluidic Access Arrays ( IFC) followed by Illumina® MiSeq Nano sequencing on a culture-derived local mock community to demonstrate how this approach allows for a low-cost combinatorial investigation of primer pairs and experimental samples (up to 48 primer pairs and 48 samples) to determine the most effective primers that maximize obtained communities whilst minimizing taxonomic biases. [ABSTRACT FROM AUTHOR]

DNA metabarcoding is a promising method for describing communities and estimating biodiversity. This approach uses high-throughput sequencing of targeted markers to identify species in a complex sample. By convention, sequences are clustered at a predefined sequence divergence threshold (often 3%) into operational taxonomic units ( OTUs) that serve as a proxy for species. However, variable levels of interspecific marker variation across taxonomic groups make clustering sequences from a phylogenetically diverse dataset into OTUs at a uniform threshold problematic. In this study, we use mock zooplankton communities to evaluate the accuracy of species richness estimates when following conventional protocols to cluster hypervariable sequences of the V4 region of the small subunit ribosomal RNA gene (18S) into OTUs. By including individually tagged single specimens and 'populations' of various species in our communities, we examine the impact of intra- and interspecific diversity on OTU clustering. Communities consisting of single individuals per species generated a correspondence of 59-84% between OTU number and species richness at a 3% divergence threshold. However, when multiple individuals per species were included, the correspondence between OTU number and species richness dropped to 31-63%. Our results suggest that intraspecific variation in this marker can often exceed 3%, such that a single species does not always correspond to one OTU. We advocate the need to apply group-specific divergence thresholds when analyzing complex and taxonomically diverse communities, but also encourage the development of additional filtering steps that allow identification of artifactual rRNA gene sequences or pseudogenes that may generate spurious OTUs. [ABSTRACT FROM AUTHOR]

The author discusses the formation of symbiosis with mycorrhizal fungi in plant species. He states the mutualism and parasitism balnce in arbuscular mycorrhizas (AM), the key role of mycorrhizal fungi in the carbon cycle, and the acquisition of bacterial genes coding for enzyme decomposition. The author also discusses the mycorrhizal symbiosis which with basal nonvascular land plants such as liverworts.