Accurate multiplexing and filtering for high-throughput amplicon-sequencing

Multifaceted DNA metabarcoding: Validation of a noninvasive, next-generation approach to studying bat populations

As multiple species of bats are currently experiencing dramatic declines in populations due to white-nose syndrome (WNS) and other factors, conservation managers have an urgent need for data on the ecology and overall status of populations of once-common bat species. Standard approaches to obtain data on bat populations often involve capture and handling, requiring extensive expertise and unavoidably resulting in stress to the bats. New methods to rapidly obtain critical data are needed that minimize both the stress on bats and the spread of WNS. Guano provides a noninvasive source of DNA that includes information from the bat, but also dietary items, parasites, and pathogens. DNA metabarcoding is a high-throughput, DNA-based identification technique to assess the biodiversity of environmental or fecal samples. We investigated the use of multifaceted DNA metabarcoding (MDM), a technique combining next-generation DNA sequencing (NGS), DNA barcodes, and bioinformatic analysis, to simultaneously collect data on multiple parameters of interest (bat species composition, individual genotype, sex ratios, diet, parasites, and presence of WNS) from fecal samples using a single NGS run. We tested the accuracy of each MDM assay using samples in which these parameters were previously determined using conventional approaches. We found that assays for bat species identification, insect diet, parasite diversity, and genotype were both sensitive and accurate, the assay to detect WNS was highly sensitive but requires careful sample processing steps to ensure the reliability of results, while assays for nectivorous diet and sex showed lower sensitivity. MDM was able to quantify multiple data classes from fecal samples simultaneously, and results were consistent whether we included assays for a single data class or multiple data classes. Overall, MDM is a useful approach that employs noninvasive sampling and a customizable suite of assays to gain important and largely accurate information on bat ecology and population dynamics.

Dynamics of Gut Microbiota Diversity During the Early Development of an Avian Host: Evidence From a Cross-Foster Experiment

Despite the increasing knowledge on the processes involved in the acquisition and development of the gut microbiota in model organisms, the factors influencing early microbiota successions in natural populations remain poorly understood. In particular, little is known on the role of the rearing environment in the establishment of the gut microbiota in wild birds. Here, we examined the influence of the nesting environment on the gut microbiota of Great tits (Parus major) by performing a partial cross-fostering experiment during the intermediate stage of nestling development. We found that the cloacal microbiota of great tit nestlings underwent substantial changes between 8 and 15 days of age, with a strong decrease in diversity, an increase in the relative abundance of Firmicutes and a shift in the functional features of the community. Second, the nesting environment significantly influenced community composition, with a divergence among separated true siblings and a convergence among foster siblings. Third, larger shifts in both microbiota diversity and composition correlated with lower nestling body condition. Our results shed new light on the dynamics of microbial diversity during the ontogeny of avian hosts, indicating that the nest environment continues to shape the gut microbiota during the later stages of nestling development and that the increase in gut diversity between hatching and adulthood may not be as linear as previously suspected. Lastly, the microbiota changes incurred during this period may have implications for nestling body condition which can lead to long-term consequences for host fitness.

EukRef-Ciliophora: a manually curated, phylogeny-based database of small subunit rRNA gene sequences of ciliates

High-throughput sequencing (HTS) surveys, among the most common approaches currently used in environmental microbiology, require reliable reference databases to be correctly interpreted. The EukRef Initiative (eukref.org) is a community effort to manually screen available small subunit (SSU) rRNA gene sequences and produce a public, high-quality and informative framework of phylogeny-based taxonomic annotations. In the context of EukRef, we present a database for the monophyletic phylum Ciliophora, one of the most complex, diverse and ubiquitous protist groups. We retrieved more than 11 500 sequences of ciliates present in GenBank (28% from identified isolates and 72% from environmental surveys). Our approach included the inference of phylogenetic trees for every ciliate lineage and produced the largest SSU rRNA tree of the phylum Ciliophora to date. We flagged approximately 750 chimeric or low-quality sequences, improved the classification of 70% of GenBank entries and enriched environmental and literature metadata by 30%. The performance of EukRef-Ciliophora is superior to the current SILVA database in classifying HTS reads from a global marine survey. Comprehensive outputs are publicly available to make the new tool a useful guide for non-specialists and a quick reference for experts.

Non-biological synthetic spike-in controls and the AMPtk software pipeline improve mycobiome data

High-throughput amplicon sequencing (HTAS) of conserved DNA regions is a powerful technique to characterize microbial communities. Recently, spike-in mock communities have been used to measure accuracy of sequencing platforms and data analysis pipelines. To assess the ability of sequencing platforms and data processing pipelines using fungal internal transcribed spacer (ITS) amplicons, we created two ITS spike-in control mock communities composed of cloned DNA in plasmids: a biological mock community, consisting of ITS sequences from fungal taxa, and a synthetic mock community (SynMock), consisting of non-biological ITS-like sequences. Using these spike-in controls we show that: (1) a non-biological synthetic control (e.g., SynMock) is the best solution for parameterizing bioinformatics pipelines, (2) pre-clustering steps for variable length amplicons are critically important, (3) a major source of bias is attributed to the initial polymerase chain reaction (PCR) and thus HTAS read abundances are typically not representative of starting values. We developed AMPtk, a versatile software solution equipped to deal with variable length amplicons and quality filter HTAS data based on spike-in controls. While we describe herein a non-biological SynMock community for ITS sequences, the concept and AMPtk software can be widely applied to any HTAS dataset to improve data quality.

Characterising planktonic dinoflagellate diversity in Singapore using DNA metabarcoding

Dinoflagellates are traditionally identified morphologically using microscopy, which is a time-consuming and labour-intensive process. Hence, we explored DNA metabarcoding using high-throughput sequencing as a more efficient way to study planktonic dinoflagellate diversity in Singapore’s waters. From 29 minimally pre-sorted water samples collected at four locations in western Singapore, DNA was extracted, amplified and sequenced for a 313-bp fragment of the V4–V5 region in the 18S ribosomal RNA gene. Two sequencing runs generated 2,847,170 assembled paired-end reads, corresponding to 573,176 unique sequences. Sequences were clustered at 97% similarity and analysed with stringent thresholds (≥150 bp, ≥20 reads, ≥95% match to dinoflagellates), recovering 28 dinoflagellate taxa. Dinoflagellate diversity captured includes parasitic and symbiotic groups which are difficult to identify morphologically. Richness is similar between the inner and outer West Johor Strait, but variations in community structure are apparent, likely driven by environmental differences. None of the taxa detected in a recent phytoplankton bloom along the West Johor Strait have been recovered in our samples, suggesting that background communities are distinct from bloom communities. The voluminous data obtained in this study contribute baseline information for Singapore’s phytoplankton communities and prompt future research and monitoring to adopt the approach established here.

Estimating intraspecific genetic diversity from community DNA metabarcoding data

Background

DNA metabarcoding is used to generate species composition data for entire communities. However, sequencing errors in high-throughput sequencing instruments are fairly common, usually requiring reads to be clustered into operational taxonomic units (OTUs), losing information on intraspecific diversity in the process. While Cytochrome c oxidase subunit I (COI) haplotype information is limited in resolving intraspecific diversity it is nevertheless often useful e.g. in a phylogeographic context, helping to formulate hypotheses on taxon distribution and dispersal.

Methods

This study combines sequence denoising strategies, normally applied in microbial research, with additional abundance-based filtering to extract haplotype information from freshwater macroinvertebrate metabarcoding datasets. This novel approach was added to the R package "JAMP" and can be applied to COI amplicon datasets. We tested our haplotyping method by sequencing (i) a single-species mock community composed of 31 individuals with 15 different haplotypes spanning three orders of magnitude in biomass and (ii) 18 monitoring samples each amplified with four different primer sets and two PCR replicates.

Results

We detected all 15 haplotypes of the single specimens in the mock community with relaxed filtering and denoising settings. However, up to 480 additional unexpected haplotypes remained in both replicates. Rigorous filtering removes most unexpected haplotypes, but also can discard expected haplotypes mainly from the small specimens. In the monitoring samples, the different primer sets detected 177-200 OTUs, each containing an average of 2.40-3.30 haplotypes per OTU. The derived intraspecific diversity data showed population structures that were consistent between replicates and similar between primer pairs but resolution depended on the primer length. A closer look at abundant taxa in the dataset revealed various population genetic patterns, e.g. the stonefly Taeniopteryx nebulosa and the caddisfly Hydropsyche pellucidula showed a distinct north-south cline with respect to haplotype distribution, while the beetle Oulimnius tuberculatus and the isopod Asellus aquaticus displayed no clear population pattern but differed in genetic diversity.

Discussion

We developed a strategy to infer intraspecific genetic diversity from bulk invertebrate metabarcoding data. It needs to be stressed that at this point this metabarcoding-informed haplotyping is not capable of capturing the full diversity present in such samples, due to variation in specimen size, primer bias and loss of sequence variants with low abundance. Nevertheless, for a high number of species intraspecific diversity was recovered, identifying potentially isolated populations and taxa for further more detailed phylogeographic investigation. While we are currently lacking large-scale metabarcoding datasets to fully take advantage of our new approach, metabarcoding-informed haplotyping holds great promise for biomonitoring efforts that not only seek information about species diversity but also underlying genetic diversity.

Assessing the effect of mercury pollution on cultured benthic foraminifera community using morphological and eDNA metabarcoding approaches

Mercury (Hg) is a highly toxic element for living organisms and is known to bioaccumulate and biomagnify. Here, we analyze the response of benthic foraminifera communities cultured in mesocosm and exposed to different concentrations of Hg. Standard morphological analyses and environmental DNA metabarcoding show evidence that Hg pollution has detrimental effects on benthic foraminifera. The molecular analysis provides a more complete view of foraminiferal communities including the soft-walled single-chambered monothalamiids and small-sized hard-shelled rotaliids and textulariids than the morphological one. Among these taxa that are typically overlooked in morphological studies we found potential bioindicators of Hg pollution. The mesocosm approach proves to be an effective method to study benthic foraminiferal responses to various types and concentrations of pollutants over time. This study further supports foraminiferal metabarcoding as a complementary and/or alternative method to standard biomonitoring program based on the morphological identification of species communities.

Predatory flying squids are detritivores during their early planktonic life

Cephalopods are primarily active predators throughout life. Flying squids (family Ommastrephidae) represents the most widely distributed and ecologically important family of cephalopods. While the diets of adult flying squids have been extensively studied, the first feeding diet of early paralarvae remains a mystery. The morphology of this ontogenetic stage notably differs from other cephalopod paralarvae, suggesting a different feeding strategy. Here, a combination of Laser Capture Microdissection (LCM) and DNA metabarcoding of wild-collected paralarvae gut contents for eukaryotic 18S v9 and prokaryotic 16S rRNA was applied, covering almost every life domain. The gut contents were mainly composed by fungus, plants, algae and animals of marine and terrestrial origin, as well as eukaryotic and prokaryotic microorganisms commonly found in fecal pellets and particulate organic matter. This assemblage of gut contents is consistent with a diet based on detritus. The ontogenetic shift of diet from detritivore suspension feeding to active predation represents a unique life strategy among cephalopods and allows ommastrephid squids to take advantage of an almost ubiquitous and accessible food resource during their early stages. LCM was successfully applied for the first time to tiny, wild-collected marine organisms, proving its utility in combination with DNA metabarcoding for dietary studies.

Surface ocean metabarcoding confirms limited diversity in planktonic foraminifera but reveals unknown hyper-abundant lineages

Since the advent of DNA metabarcoding surveys, the planktonic realm is considered a treasure trove of diversity, inhabited by a small number of abundant taxa, and a hugely diverse and taxonomically uncharacterized consortium of rare species. Here we assess if the apparent underestimation of plankton diversity applies universally. We target planktonic foraminifera, a group of protists whose known morphological diversity is limited, taxonomically resolved and linked to ribosomal DNA barcodes. We generated a pyrosequencing dataset of ~100,000 partial 18S rRNA foraminiferal sequences from 32 size fractioned photic-zone plankton samples collected at 8 stations in the Indian and Atlantic Oceans during the Tara Oceans expedition (2009–2012). We identified 69 genetic types belonging to 41 morphotaxa in our metabarcoding dataset. The diversity saturated at local and regional scale as well as in the three size fractions and the two depths sampled indicating that the diversity of foraminifera is modest and finite. The large majority of the newly discovered lineages occur in the small size fraction, neglected by classical taxonomy. These unknown lineages dominate the bulk [>0.8 µm] size fraction, implying that a considerable part of the planktonic foraminifera community biomass has its origin in unknown lineages.

Metabarcoding for the parallel identification of several hundred predators and their prey: Application to bat species diet analysis

Assessing diet variability is of main importance to better understand the biology of bats and design conservation strategies. Although the advent of metabarcoding has facilitated such analyses, this approach does not come without challenges. Biases may occur throughout the whole experiment, from fieldwork to biostatistics, resulting in the detection of false negatives, false positives or low taxonomic resolution. We detail a rigorous metabarcoding approach based on a short COI minibarcode and two-step PCR protocol enabling the "all at once" taxonomic identification of bats and their arthropod prey for several hundreds of samples. Our study includes faecal pellets collected in France from 357 bats representing 16 species, as well as insect mock communities that mimic bat meals of known composition, negative and positive controls. All samples were analysed using three replicates. We compare the efficiency of DNA extraction methods, and we evaluate the effectiveness of our protocol using identification success, taxonomic resolution, sensitivity and amplification biases. Our parallel identification strategy of predators and prey reduces the risk of mis-assigning prey to wrong predators and decreases the number of molecular steps. Controls and replicates enable to filter the data and limit the risk of false positives, hence guaranteeing high confidence results for both prey occurrence and bat species identification. We validate 551 COI variants from arthropod including 18 orders, 117 family, 282 genus and 290 species. Our method therefore provides a rapid, resolutive and cost-effective screening tool for addressing evolutionary ecological issues or developing "chirosurveillance" and conservation strategies.

A confidence interval analysis of sampling effort, sequencing depth, and taxonomic resolution of fungal community ecology in the era of high-throughput sequencing

High-throughput sequencing technology has helped microbial community ecologists explore ecological and evolutionary patterns at unprecedented scales. The benefits of a large sample size still typically outweigh that of greater sequencing depths per sample for accurate estimations of ecological inferences. However, excluding or not sequencing rare taxa may mislead the answers to the questions ‘how and why are communities different?’ This study evaluates the confidence intervals of ecological inferences from high-throughput sequencing data of foliar fungal endophytes as case studies through a range of sampling efforts, sequencing depths, and taxonomic resolutions to understand how technical and analytical practices may affect our interpretations. Increasing sampling size reliably decreased confidence intervals across multiple community comparisons. However, the effects of sequencing depths on confidence intervals depended on how rare taxa influenced the dissimilarity estimates among communities and did not significantly decrease confidence intervals for all community comparisons. A comparison of simulated communities under random drift suggests that sequencing depths are important in estimating dissimilarities between microbial communities under neutral selective processes. Confidence interval analyses reveal important biases as well as biological trends in microbial community studies that otherwise may be ignored when communities are only compared for statistically significant differences.

New barcoded primers for efficient retrieval of cercozoan sequences in high-throughput environmental diversity surveys, with emphasis on worldwide biological soil crusts

We describe the performance of a new metabarcoding approach to investigate the environmental diversity of a prominent group of widespread unicellular organisms, the Cercozoa. Cercozoa is an immensely large group of protists, and although it may dominate in soil and aquatic ecosystems, its environmental diversity remains undersampled. We designed PCR primers targeting the hypervariable region V4 of the small subunit ribosomal RNA (SSU or 18S) gene, which is the recommended barcode marker for Cercozoa. The length of the amplified fragment (c. 350 bp) is suitable for Illumina MiSeq, the most cost-effective platform for molecular environmental surveys. We provide barcoded primers, an economical alternative to multiple libraries for multiplex sequencing of over a hundred samples. In silico, our primers matched 68% of the cercozoan sequences of the reference database and performed better than previously proposed new-generation sequencing primers. In mountain grassland soils and in biological soil crusts from a variety of climatic regions, we were able to detect cercozoan sequences encompassing nearly the whole range of the phylum. We obtained 901 operational taxonomic units (OTUs) at 97% similarity threshold from 26 samples, with c. 50,000 sequences per site, and only 8% of noncercozoan sequences. We could report a further increase in the diversity of Cercozoa, as only 43% of the OTUs were 97%-100% similar to any known sequence. Our study thus provides an advanced tool for cercozoan metabarcoding and to investigate their diversity and distribution in the environment.

High-throughput sequencing of kDNA amplicons for the analysis of Leishmania minicircles and identification of Neotropical species

Leishmania kinetoplast DNA contains thousands of small circular molecules referred to as kinetoplast DNA (kDNA) minicercles. kDNA minicircles are the preferred targets for sensitive Leishmania detection, because they are present in high copy number and contain conserved sequence blocks in which polymerase chain reaction (PCR) primers can be designed. On the other hand, the heterogenic nature of minicircle networks has hampered the use of this peculiar genomic region for strain typing. The characterization of Leishmania minicirculomes used to require isolation and cloning steps prior to sequencing. Here, we show that high-throughput sequencing of single minicircle PCR products allows bypassing these laborious laboratory tasks. The 120 bp long minicircle conserved region was amplified by PCR from 18 Leishmania strains representative of the major species complexes found in the Neotropics. High-throughput sequencing of PCR products enabled recovering significant numbers of distinct minicircle sequences from each strain, reflecting minicircle class diversity. Minicircle sequence analysis revealed patterns that are congruent with current hypothesis of Leishmania relationships. Then, we show that a barcoding-like approach based on minicircle sequence comparisons may allow reliable identifications of Leishmania spp. This work opens up promising perspectives for the study of kDNA minicercles and a variety of applications in Leishmania research.

Development of amplicon deep sequencing markers and data analysis pipeline for genotyping multi-clonal malaria infections

Background

Amplicon deep sequencing permits sensitive detection of minority clones and improves discriminatory power for genotyping multi-clone Plasmodium falciparum infections. New amplicon sequencing and data analysis protocols are needed for genotyping in epidemiological studies and drug efficacy trials of P. falciparum.

Methods

Targeted sequencing of molecular marker csp and novel marker cpmp was conducted in duplicate on mixtures of parasite culture strains and 37 field samples. A protocol allowing to multiplex up to 384 samples in a single sequencing run was applied. Software “HaplotypR” was developed for data analysis.

Results

Cpmp was highly diverse (H_e = 0.96) in contrast to csp (H_e = 0.57). Minority clones were robustly detected if their frequency was >1%. False haplotype calls owing to sequencing errors were observed below that threshold.

Conclusions

To reliably detect haplotypes at very low frequencies, experiments are best performed in duplicate and should aim for coverage of >10′000 reads/amplicon. When compared to length polymorphic marker msp2, highly multiplexed amplicon sequencing displayed greater sensitivity in detecting minority clones.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4260-y) contains supplementary material, which is available to authorized users.

Algorithm for post-clustering curation of DNA amplicon data yields reliable biodiversity estimates

DNA metabarcoding is promising for cost-effective biodiversity monitoring, but reliable diversity estimates are difficult to achieve and validate. Here we present and validate a method, called LULU, for removing erroneous molecular operational taxonomic units (OTUs) from community data derived by high-throughput sequencing of amplified marker genes. LULU identifies errors by combining sequence similarity and co-occurrence patterns. To validate the LULU method, we use a unique data set of high quality survey data of vascular plants paired with plant ITS2 metabarcoding data of DNA extracted from soil from 130 sites in Denmark spanning major environmental gradients. OTU tables are produced with several different OTU definition algorithms and subsequently curated with LULU, and validated against field survey data. LULU curation consistently improves α-diversity estimates and other biodiversity metrics, and does not require a sequence reference database; thus, it represents a promising method for reliable biodiversity estimation.

iDNA screening: Disease vectors as vertebrate samplers

In the current context of global change and human-induced biodiversity decline, there is an urgent need for developing sampling approaches able to accurately describe the state of biodiversity. Traditional surveys of vertebrate fauna involve time-consuming and skill-demanding field methods. Recently, the use of DNA derived from invertebrate parasites (leeches and blowflies) was suggested as a new tool for vertebrate diversity assessment. Bloodmeal analyses of arthropod disease vectors have long been performed to describe their feeding behaviour, for epidemiological purposes. On the other hand, this existing expertise has not yet been applied to investigate vertebrate fauna per se. Here, we evaluate the usefulness of hematophagous dipterans as vertebrate samplers. Blood-fed sand flies and mosquitoes were collected in Amazonian forest sites and analysed using high-throughput sequencing of short mitochondrial markers. Bloodmeal identifications highlighted contrasting ecological features and feeding behaviour among dipteran species, which allowed unveiling arboreal and terrestrial mammals of various body size, as well as birds, lizards and amphibians. Additionally, lower vertebrate diversity was found in sites undergoing higher levels of human-induced perturbation. These results suggest that, in addition to providing precious information on disease vector host use, dipteran bloodmeal analyses may represent a useful tool in the study of vertebrate communities. Although further effort is required to validate the approach and consider its application to large-scale studies, this first work opens up promising perspectives for biodiversity monitoring and eco-epidemiology.

Indigenous species barcode database improves the identification of zooplankton

Incompleteness and inaccuracy of DNA barcode databases is considered an important hindrance to the use of metabarcoding in biodiversity analysis of zooplankton at the species-level. Species barcoding by Sanger sequencing is inefficient for organisms with small body sizes, such as zooplankton. Here mitochondrial cytochrome c oxidase I (COI) fragment barcodes from 910 freshwater zooplankton specimens (87 morphospecies) were recovered by a high-throughput sequencing platform, Ion Torrent PGM. Intraspecific divergence of most zooplanktons was < 5%, except Branchionus leydign (Rotifer, 14.3%), Trichocerca elongate (Rotifer, 11.5%), Lecane bulla (Rotifer, 15.9%), Synchaeta oblonga (Rotifer, 5.95%) and Schmackeria forbesi (Copepod, 6.5%). Metabarcoding data of 28 environmental samples from Lake Tai were annotated by both an indigenous database and NCBI Genbank database. The indigenous database improved the taxonomic assignment of metabarcoding of zooplankton. Most zooplankton (81%) with barcode sequences in the indigenous database were identified by metabarcoding monitoring. Furthermore, the frequency and distribution of zooplankton were also consistent between metabarcoding and morphology identification. Overall, the indigenous database improved the taxonomic assignment of zooplankton.

Ecosystem biomonitoring with eDNA: metabarcoding across the tree of life in a tropical marine environment

Effective marine management requires comprehensive data on the status of marine biodiversity. However, efficient methods that can document biodiversity in our oceans are currently lacking. Environmental DNA (eDNA) sourced from seawater offers a new avenue for investigating the biota in marine ecosystems. Here, we investigated the potential of eDNA to inform on the breadth of biodiversity present in a tropical marine environment. Directly sequencing eDNA from seawater using a shotgun approach resulted in only 0.34% of 22.3 million reads assigning to eukaryotes, highlighting the inefficiency of this method for assessing eukaryotic diversity. In contrast, using 'tree of life' (ToL) metabarcoding and 20-fold fewer sequencing reads, we could detect 287 families across the major divisions of eukaryotes. Our data also show that the best performing 'universal' PCR assay recovered only 44% of the eukaryotes identified across all assays, highlighting the need for multiple metabarcoding assays to catalogue biodiversity. Lastly, focusing on the fish genus Lethrinus, we recovered intra- and inter-specific haplotypes from seawater samples, illustrating that eDNA can be used to explore diversity beyond taxon identifications. Given the sensitivity and low cost of eDNA metabarcoding we advocate this approach be rapidly integrated into biomonitoring programs.

A from-benchtop-to-desktop workflow for validating HTS data and for taxonomic identification in diet metabarcoding studies

The main objective of this work was to develop and validate a robust and reliable "from-benchtop-to-desktop" metabarcoding workflow to investigate the diet of invertebrate-eaters. We applied our workflow to faecal DNA samples of an invertebrate-eating fish species. A fragment of the cytochrome c oxidase I (COI) gene was amplified by combining two minibarcoding primer sets to maximize the taxonomic coverage. Amplicons were sequenced by an Illumina MiSeq platform. We developed a filtering approach based on a series of nonarbitrary thresholds established from control samples and from molecular replicates to address the elimination of cross-contamination, PCR/sequencing errors and mistagging artefacts. This resulted in a conservative and informative metabarcoding data set. We developed a taxonomic assignment procedure that combines different approaches and that allowed the identification of ~75% of invertebrate COI variants to the species level. Moreover, based on the diversity of the variants, we introduced a semiquantitative statistic in our diet study, the minimum number of individuals, which is based on the number of distinct variants in each sample. The metabarcoding approach described in this article may guide future diet studies that aim to produce robust data sets associated with a fine and accurate identification of prey items.

Predicting the Ecological Quality Status of Marine Environments from eDNA Metabarcoding Data Using Supervised Machine Learning

Monitoring biodiversity is essential to assess the impacts of increasing anthropogenic activities in marine environments. Traditionally, marine biomonitoring involves the sorting and morphological identification of benthic macro-invertebrates, which is time-consuming and taxonomic-expertise demanding. High-throughput amplicon sequencing of environmental DNA (eDNA metabarcoding) represents a promising alternative for benthic monitoring. However, an important fraction of eDNA sequences remains unassigned or belong to taxa of unknown ecology, which prevent their use for assessing the ecological quality status. Here, we show that supervised machine learning (SML) can be used to build robust predictive models for benthic monitoring, regardless of the taxonomic assignment of eDNA sequences. We tested three SML approaches to assess the environmental impact of marine aquaculture using benthic foraminifera eDNA, a group of unicellular eukaryotes known to be good bioindicators, as features to infer macro-invertebrates based biotic indices. We found similar ecological status as obtained from macro-invertebrates inventories. We argue that SML approaches could overcome and even bypass the cost and time-demanding morpho-taxonomic approaches in future biomonitoring.

PCR cycles above routine numbers do not compromise high-throughput DNA barcoding results

High-throughput DNA barcoding has become essential in ecology and evolution, but some technical questions still remain. Increasing the number of PCR cycles above the routine 20-30 cycles is a common practice when working with old-type specimens, which provide little amounts of DNA, or when facing annealing issues with the primers. However, increasing the number of cycles can raise the number of artificial mutations due to polymerase errors. In this work, we sequenced 20 COI libraries in the Illumina MiSeq platform. Libraries were prepared with 40, 45, 50, 55, and 60 PCR cycles from four individuals belonging to four species of four genera of cephalopods. We found no relationship between the number of PCR cycles and the number of mutations despite using a nonproofreading polymerase. Moreover, even when using a high number of PCR cycles, the resulting number of mutations was low enough not to be an issue in the context of high-throughput DNA barcoding (but may still remain an issue in DNA metabarcoding due to chimera formation). We conclude that the common practice of increasing the number of PCR cycles should not negatively impact the outcome of a high-throughput DNA barcoding study in terms of the occurrence of point mutations.

Fungi associated with mesophotic macroalgae from the 'Au'au Channel, west Maui are differentiated by host and overlap terrestrial communities

Mesophotic coral ecosystems are an almost entirely unexplored and undocumented environment that likely contains vast reservoirs of undescribed biodiversity. Twenty-four macroalgae samples, representing four genera, were collected from a Hawaiian mesophotic reef at water depths between 65 and 86 m in the 'Au'au Channel, Maui, Hawai'i. Algal tissues were surveyed for the presence and diversity of fungi by sequencing the ITS1 gene using Illumina technology. Fungi from these algae were then compared to previous fungal surveys conducted in Hawaiian terrestrial ecosystems. Twenty-seven percent of the OTUs present on the mesophotic coral ecosystem samples were shared between the marine and terrestrial environment. Subsequent analyses indicated that host species of algae significantly differentiate fungal community composition. This work demonstrates yet another understudied habitat with a moderate diversity of fungi that should be considered when estimating global fungal diversity.

Dated tribe-wide whole chloroplast genome phylogeny indicates recurrent hybridizations within Triticeae

BACKGROUND

Triticeae, the tribe of wheat grasses, harbours the cereals barley, rye and wheat and their wild relatives. Although economically important, relationships within the tribe are still not understood. We analysed the phylogeny of chloroplast lineages among nearly all monogenomic Triticeae taxa and polyploid wheat species aiming at a deeper understanding of the tribe's evolution. We used on- and off-target reads of a target-enrichment experiment followed by Illumina sequencing.

RESULTS

The read data was used to assemble the plastid locus ndhF for 194 individuals and the whole chloroplast genome for 183 individuals, representing 53 Triticeae species and 15 genera. We conducted Bayesian and multispecies coalescent analyses to infer relationships and estimate divergence times of the taxa. We present the most comprehensive dated Triticeae chloroplast phylogeny and review previous hypotheses in the framework of our results. Monophyly of Triticeae chloroplasts could not be confirmed, as either Bromus or Psathyrostachys captured a chloroplast from a lineage closely related to a Bromus-Triticeae ancestor. The most recent common ancestor of Triticeae occurred approximately between ten and 19 million years ago.

CONCLUSIONS

The comparison of the chloroplast phylogeny with available nuclear data in several cases revealed incongruences indicating past hybridizations. Recent events of chloroplast capture were detected as individuals grouped apart from con-specific accessions in otherwise monopyhletic groups.

Social odours covary with bacterial community in the anal secretions of wild meerkats

The fermentation hypothesis for animal signalling posits that bacteria dwelling in an animal’s scent glands metabolize the glands’ primary products into odorous compounds used by the host to communicate with conspecifics. There is, however, little evidence of the predicted covariation between an animal’s olfactory cues and its glandular bacterial communities. Using gas chromatography-mass spectrometry, we first identified the volatile compounds present in ‘pure’ versus ‘mixed’ anal-gland secretions (‘paste’) of adult meerkats (Suricata suricatta) living in the wild. Low-molecular-weight chemicals that likely derive from bacterial metabolism were more prominent in mixed than pure secretions. Focusing thereafter on mixed secretions, we showed that chemical composition varied by sex and was more similar between members of the same group than between members of different groups. Subsequently, using next-generation sequencing, we identified the bacterial assemblages present in meerkat paste and documented relationships between these assemblages and the host’s sex, social status and group membership. Lastly, we found significant covariation between the volatile compounds and bacterial assemblages in meerkat paste, particularly in males. Together, these results are consistent with a role for bacteria in the production of sex- and group-specific scents, and with the evolution of mutualism between meerkats and their glandular microbiota.

Zooplankton Community Profiling in a Eutrophic Freshwater Ecosystem-Lake Tai Basin by DNA Metabarcoding

Communities of zooplankton, a critical portion of aquatic ecosystems, can be adversely affected by contamination resulting from human activities. Understanding the influence of environmental change on zooplankton communities under field-conditions is hindered by traditional labor-intensive approaches that are prone to taxonomic and enumeration mistakes. Here, metabarcoding of cytochrome c oxidase I (COI) region of mitochondrial DNA was used to characterize the genetic diversity of zooplankton. The species composition of zooplankton communities determined by metabarcoding was consistent with the results based on the traditional morphological approach. The spatial distribution of common species (frequency of occurrence >10 samples) by metabarcoding exhibited good agreement with morphological data. Furthermore, metabarcoding can clearly distinguish the composition of the zooplankton community between lake and river ecosystems. In general, rotifers were more abundant in riverine environments than lakes and reservoirs. Finally, the sequence read number of different taxonomic groups using metabarcoding was positively correlated with the zooplankton biomass inferred by density and body length of zooplankton. Overall, the utility of metabarcoding for taxonomic profiling of zooplankton communities was validated by the morphology-based method on a large ecological scale. Metabarcoding of COI could be a powerful and efficient biomonitoring tool to protect local aquatic ecosystems.

Strengths and Biases of High-Throughput Sequencing Data in the Characterization of Freshwater Ciliate Microbiomes

Molecular surveys of eukaryotic microbial communities employing high-throughput sequencing (HTS) techniques are rapidly supplanting traditional morphological approaches due to their larger data output and reduced bench work time. Here, we directly compare morphological and Illumina data obtained from the same samples, in an effort to characterize ciliate faunas from sediments in freshwater environments. We show how in silico processing affects the final outcome of our HTS analysis, providing evidence that quality filtering protocols strongly impact the number of predicted taxa, but not downstream conclusions such as biogeography patterns. We determine the abundance distribution of ciliates, showing that a small fraction of abundant taxa dominates read counts. At the same time, we advance reasons to believe that biases affecting HTS abundances may be significant enough to blur part of the underlying biological picture. We confirmed that the HTS approach detects many more taxa than morphological inspections, and highlight how the difference varies among taxonomic groups. Finally, we hypothesize that the two datasets actually correspond to different conceptions of "diversity," and consequently that neither is entirely superior to the other when investigating environmental protists.

Evaluation of the reproducibility of amplicon sequencing with Illumina MiSeq platform

Illumina’s MiSeq has become the dominant platform for gene amplicon sequencing in microbial ecology studies; however, various technical concerns, such as reproducibility, still exist. To assess reproducibility, 16S rRNA gene amplicons from 18 soil samples of a reciprocal transplantation experiment were sequenced on an Illumina MiSeq. The V4 region of 16S rRNA gene from each sample was sequenced in triplicate with each replicate having a unique barcode. The average OTU overlap, without considering sequence abundance, at a rarefaction level of 10,323 sequences was 33.4±2.1% and 20.2±1.7% between two and among three technical replicates, respectively. When OTU sequence abundance was considered, the average sequence abundance weighted OTU overlap was 85.6±1.6% and 81.2±2.1% for two and three replicates, respectively. Removing singletons significantly increased the overlap for both (~1–3%, p<0.001). Increasing the sequencing depth to 160,000 reads by deep sequencing increased OTU overlap both when sequence abundance was considered (95%) and when not (44%). However, if singletons were not removed the overlap between two technical replicates (not considering sequence abundance) plateaus at 39% with 30,000 sequences. Diversity measures were not affected by the low overlap as α-diversities were similar among technical replicates while β-diversities (Bray-Curtis) were much smaller among technical replicates than among treatment replicates (e.g., 0.269 vs. 0.374). Higher diversity coverage, but lower OTU overlap, was observed when replicates were sequenced in separate runs. Detrended correspondence analysis indicated that while there was considerable variation among technical replicates, the reproducibility was sufficient for detecting treatment effects for the samples examined. These results suggest that although there is variation among technical replicates, amplicon sequencing on MiSeq is useful for analyzing microbial community structure if used appropriately and with caution. For example, including technical replicates, removing spurious sequences and unrepresentative OTUs, using a clustering method with a high stringency for OTU generation, estimating treatment effects at higher taxonomic levels, and adapting the unique molecular identifier (UMI) and other newly developed methods to lower PCR and sequencing error and to identify true low abundance rare species all can increase reproducibility.

Metagenomics: Probing pollutant fate in natural and engineered ecosystems

Polluted environments are a reservoir of microbial species able to degrade or to convert pollutants to harmless compounds. The proper management of microbial resources requires a comprehensive characterization of their genetic pool to assess the fate of contaminants and increase the efficiency of bioremediation processes. Metagenomics offers appropriate tools to describe microbial communities in their whole complexity without lab-based cultivation of individual strains. After a decade of use of metagenomics to study microbiomes, the scientific community has made significant progress in this field. In this review, we survey the main steps of metagenomics applied to environments contaminated with organic compounds or heavy metals. We emphasize technical solutions proposed to overcome encountered obstacles. We then compare two metagenomic approaches, i.e. library-based targeted metagenomics and direct sequencing of metagenomes. In the former, environmental DNA is cloned inside a host, and then clones of interest are selected based on (i) their expression of biodegradative functions or (ii) sequence homology with probes and primers designed from relevant, already known sequences. The highest score for the discovery of novel genes and degradation pathways has been achieved so far by functional screening of large clone libraries. On the other hand, direct sequencing of metagenomes without a cloning step has been more often applied to polluted environments for characterization of the taxonomic and functional composition of microbial communities and their dynamics. In this case, the analysis has focused on 16S rRNA genes and marker genes of biodegradation. Advances in next generation sequencing and in bioinformatic analysis of sequencing data have opened up new opportunities for assessing the potential of biodegradation by microbes, but annotation of collected genes is still hampered by a limited number of available reference sequences in databases. Although metagenomics is still facing technical and computational challenges, our review of the recent literature highlights its value as an aid to efficiently monitor the clean-up of contaminated environments and develop successful strategies to mitigate the impact of pollutants on ecosystems.

Foliar fungal communities strongly differ between habitat patches in a landscape mosaic

Background

Dispersal events between habitat patches in a landscape mosaic can structure ecological communities and influence the functioning of agrosystems. Here we investigated whether short-distance dispersal events between vineyard and forest patches shape foliar fungal communities. We hypothesized that these communities homogenize between habitats over the course of the growing season, particularly along habitat edges, because of aerial dispersal of spores.

Methods

We monitored the richness and composition of foliar and airborne fungal communities over the season, along transects perpendicular to edges between vineyard and forest patches, using Illumina sequencing of the Internal Transcribed Spacer 2 (ITS2) region.

Results

In contrast to our expectation, foliar fungal communities in vineyards and forest patches increasingly differentiate over the growing season, even along habitat edges. Moreover, the richness of foliar fungal communities in grapevine drastically decreased over the growing season, in contrast to that of forest trees. The composition of airborne communities did not differ between habitats. The composition of oak foliar fungal communities change between forest edge and centre.

Discussion

These results suggest that dispersal events between habitat patches are not major drivers of foliar fungal communities at the landscape scale. Selective pressures exerted in each habitat by the host plant, the microclimate and the agricultural practices play a greater role, and might account for the differentiation of foliar fugal communities between habitats.

Studying the Human Microbiota

There are a range of methodologies available to study the human microbiota, ranging from traditional approaches such as culturing through to state-of-the-art developments in next generation DNA sequencing technologies. The advent of molecular techniques in particular has opened up tremendous new avenues for research, and has galvanised interest in the study of our microbial inhabitants. Given the dazzling array of available options, however, it is important to understand the inherent advantages and limitations of each technique so that the best approach can be employed to address the particular research objective. In this chapter we cover some of the most widely used current techniques in human microbiota research and highlight the particular strengths and caveats associated with each approach.

Vector soup: high-throughput identification of Neotropical phlebotomine sand flies using metabarcoding

Phlebotomine sand flies are haematophagous dipterans of primary medical importance. They represent the only proven vectors of leishmaniasis worldwide and are involved in the transmission of various other pathogens. Studying the ecology of sand flies is crucial to understand the epidemiology of leishmaniasis and further control this disease. A major limitation in this regard is that traditional morphological-based methods for sand fly species identifications are time-consuming and require taxonomic expertise. DNA metabarcoding holds great promise in overcoming this issue by allowing the identification of multiple species from a single bulk sample. Here, we assessed the reliability of a short insect metabarcode located in the mitochondrial 16S rRNA for the identification of Neotropical sand flies, and constructed a reference database for 40 species found in French Guiana. Then, we conducted a metabarcoding experiment on sand flies mixtures of known content and showed that the method allows an accurate identification of specimens in pools. Finally, we applied metabarcoding to field samples caught in a 1-ha forest plot in French Guiana. Besides providing reliable molecular data for species-level assignations of phlebotomine sand flies, our study proves the efficiency of metabarcoding based on the mitochondrial 16S rRNA for studying sand fly diversity from bulk samples. The application of this high-throughput identification procedure to field samples can provide great opportunities for vector monitoring and eco-epidemiological studies.

16S rRNA Amplicon Sequencing for Epidemiological Surveys of Bacteria in Wildlife

The human impact on natural habitats is increasing the complexity of human-wildlife interactions and leading to the emergence of infectious diseases worldwide. Highly successful synanthropic wildlife species, such as rodents, will undoubtedly play an increasingly important role in transmitting zoonotic diseases. We investigated the potential for recent developments in 16S rRNA amplicon sequencing to facilitate the multiplexing of the large numbers of samples needed to improve our understanding of the risk of zoonotic disease transmission posed by urban rodents in West Africa. In addition to listing pathogenic bacteria in wild populations, as in other high-throughput sequencing (HTS) studies, our approach can estimate essential parameters for studies of zoonotic risk, such as prevalence and patterns of coinfection within individual hosts. However, the estimation of these parameters requires cleaning of the raw data to mitigate the biases generated by HTS methods. We present here an extensive review of these biases and of their consequences, and we propose a comprehensive trimming strategy for managing these biases. We demonstrated the application of this strategy using 711 commensal rodents, including 208 Mus musculus domesticus, 189 Rattus rattus, 93 Mastomys natalensis, and 221 Mastomys erythroleucus, collected from 24 villages in Senegal. Seven major genera of pathogenic bacteria were detected in their spleens: Borrelia, Bartonella, Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia. Mycoplasma, Ehrlichia, Rickettsia, Streptobacillus, and Orientia have never before been detected in West African rodents. Bacterial prevalence ranged from 0% to 90% of individuals per site, depending on the bacterial taxon, rodent species, and site considered, and 26% of rodents displayed coinfection. The 16S rRNA amplicon sequencing strategy presented here has the advantage over other molecular surveillance tools of dealing with a large spectrum of bacterial pathogens without requiring assumptions about their presence in the samples. This approach is therefore particularly suitable to continuous pathogen surveillance in the context of disease-monitoring programs. IMPORTANCE Several recent public health crises have shown that the surveillance of zoonotic agents in wildlife is important to prevent pandemic risks. High-throughput sequencing (HTS) technologies are potentially useful for this surveillance, but rigorous experimental processes are required for the use of these effective tools in such epidemiological contexts. In particular, HTS introduces biases into the raw data set that might lead to incorrect interpretations. We describe here a procedure for cleaning data before estimating reliable biological parameters, such as positivity, prevalence, and coinfection, using 16S rRNA amplicon sequencing on an Illumina MiSeq platform. This procedure, applied to 711 rodents collected in West Africa, detected several zoonotic bacterial species, including some at high prevalence, despite their never before having been reported for West Africa. In the future, this approach could be adapted for the monitoring of other microbes such as protists, fungi, and even viruses.

Using metabarcoding to reveal and quantify plant-pollinator interactions

Given the ongoing decline of both pollinators and plants, it is crucial to implement effective methods to describe complex pollination networks across time and space in a comprehensive and high-throughput way. Here we tested if metabarcoding may circumvent the limits of conventional methodologies in detecting and quantifying plant-pollinator interactions. Metabarcoding experiments on pollen DNA mixtures described a positive relationship between the amounts of DNA from focal species and the number of trnL and ITS1 sequences yielded. The study of pollen loads of insects captured in plant communities revealed that as compared to the observation of visits, metabarcoding revealed 2.5 times more plant species involved in plant-pollinator interactions. We further observed a tight positive relationship between the pollen-carrying capacities of insect taxa and the number of trnL and ITS1 sequences. The number of visits received per plant species also positively correlated to the number of their ITS1 and trnL sequences in insect pollen loads. By revealing interactions hard to observe otherwise, metabarcoding significantly enlarges the spatiotemporal observation window of pollination interactions. By providing new qualitative and quantitative information, metabarcoding holds great promise for investigating diverse facets of interactions and will provide a new perception of pollination networks as a whole.

DAMe: a toolkit for the initial processing of datasets with PCR replicates of double-tagged amplicons for DNA metabarcoding analyses

Background

DNA metabarcoding is an approach for identifying multiple taxa in an environmental sample using specific genetic loci and taxa-specific primers. When combined with high-throughput sequencing it enables the taxonomic characterization of large numbers of samples in a relatively time- and cost-efficient manner. One recent laboratory development is the addition of 5′-nucleotide tags to both primers producing double-tagged amplicons and the use of multiple PCR replicates to filter erroneous sequences. However, there is currently no available toolkit for the straightforward analysis of datasets produced in this way.

Results

We present DAMe, a toolkit for the processing of datasets generated by double-tagged amplicons from multiple PCR replicates derived from an unlimited number of samples. Specifically, DAMe can be used to (i) sort amplicons by tag combination, (ii) evaluate PCR replicates dissimilarity, and (iii) filter sequences derived from sequencing/PCR errors, chimeras, and contamination. This is attained by calculating the following parameters: (i) sequence content similarity between the PCR replicates from each sample, (ii) reproducibility of each unique sequence across the PCR replicates, and (iii) copy number of the unique sequences in each PCR replicate. We showcase the insights that can be obtained using DAMe prior to taxonomic assignment, by applying it to two real datasets that vary in their complexity regarding number of samples, sequencing libraries, PCR replicates, and used tag combinations. Finally, we use a third mock dataset to demonstrate the impact and importance of filtering the sequences with DAMe.

Conclusions

DAMe allows the user-friendly manipulation of amplicons derived from multiple samples with PCR replicates built in a single or multiple sequencing libraries. It allows the user to: (i) collapse amplicons into unique sequences and sort them by tag combination while retaining the sample identifier and copy number information, (ii) identify sequences carrying unused tag combinations, (iii) evaluate the comparability of PCR replicates of the same sample, and (iv) filter tagged amplicons from a number of PCR replicates using parameters of minimum length, copy number, and reproducibility across the PCR replicates. This enables an efficient analysis of complex datasets, and ultimately increases the ease of handling datasets from large-scale studies.

Electronic supplementary material

The online version of this article (doi:10.1186/s13104-016-2064-9) contains supplementary material, which is available to authorized users.

A metabarcoding framework for facilitated survey of endolithic phototrophs with tufA

Background

In spite of their ecological importance as primary producers and microbioeroders of marine calcium carbonate (CaCO₃) substrata, endolithic phototrophs spanning both prokaryotic (the cyanobacteria) and eukaryotic algae lack established molecular resources for their facilitated survey with high throughput sequencing. Here, the development of a metabarcoding framework for the elongation factor EF-Ttu (tufA) was tested on four Illumina-sequenced marine CaCO₃ microfloras for the characterization of their endolithic phototrophs, especially the abundant bioeroding Ostreobium spp. (Ulvophyceae). The framework consists of novel tufA degenerate primers and a comprehensive database enabling Operational Taxonomic Unit (OTU) identification at multiple taxonomic ranks with percent identity thresholds determined herein.

Results

The newly established tufA database comprises 4057 non-redundant sequences (from 1339 eukaryotic and prokaryotic phototrophs, and 2718 prokaryotic heterotrophs) including 27 classes in 10 phyla of phototrophic diversity summarized from data mining on GenBank^®, our barcoding of >150 clones produced from coral reef microfloras, and >300 eukaryotic phototrophs (>230 Ulvophyceae including >100 ‘Ostreobium’ spp., and >70 Florideophyceae, Phaeophyceae and miscellaneous taxa). Illumina metabarcoding with the newly designed primers resulted in 802 robust OTUs including 618 phototrophs and 184 heterotrophs (77 and 23 % of OTUs, respectively). Phototrophic OTUs belonged to 14 classes of phototrophs found in seven phyla, and represented ~98 % of all reads. The phylogenetic profiles of coral reef microfloras showed few OTUs in large abundance (proportion of reads) for the Chlorophyta (Ulvophyceae, i.e. Ostreobium and Phaeophila), the Rhodophyta (Florideophyceae) and Haptophyta (Coccolithophyceae), and a large diversity (richness) of OTUs in lower abundance for the Cyanophyta (Cyanophyceae) and the Ochrophyta (the diatoms, ‘Bacillariophyta’). The bioerosive ‘Ostreobium’ spp. represented four families in a large clade of subordinal divergence, i.e. the Ostreobidineae, and a fifth, phylogenetically remote family in the suborder Halimedineae (provisionally assigned as the ‘Pseudostreobiaceae’). Together they harbor 85–95 delimited cryptic species of endolithic microsiphons.

Conclusions

The novel degenerate primers allowed for amplification of endolithic phototrophs across a wide phylogenetic breadth as well as their recovery in very large proportions of reads (overall 98 %) and diversity (overall 77 % of OTUs). The established companion tufA database and determined identity thresholds allow for OTU identification at multiple taxonomic ranks to facilitate the monitoring of phototrophic assemblages via metabarcoding, especially endolithic communities rich in bioeroding Ulvophyceae, such as those harboring ‘Ostreobium’ spp., Phaeophila spp. and associated algal diversity.

Electronic supplementary material

The online version of this article (doi:10.1186/s12898-016-0068-x) contains supplementary material, which is available to authorized users.

Network modules and hubs in plant-root fungal biomes

Terrestrial plants host phylogenetically and functionally diverse groups of below-ground microbes, whose community structure controls plant growth/survival in both natural and agricultural ecosystems. Therefore, understanding the processes by which whole root-associated microbiomes are organized is one of the major challenges in ecology and plant science. We here report that diverse root-associated fungi can form highly compartmentalized networks of coexistence within host roots and that the structure of the fungal symbiont communities can be partitioned into semi-discrete types even within a single host plant population. Illumina sequencing of root-associated fungi in a monodominant south beech forest revealed that the network representing symbiont-symbiont co-occurrence patterns was compartmentalized into clear modules, which consisted of diverse functional groups of mycorrhizal and endophytic fungi. Consequently, terminal roots of the plant were colonized by either of the two largest fungal species sets (represented by Oidiodendron or Cenococcum). Thus, species-rich root microbiomes can have alternative community structures, as recently shown in the relationships between human gut microbiome type (i.e., 'enterotype') and host individual health. This study also shows an analytical framework for pinpointing network hubs in symbiont-symbiont networks, leading to the working hypothesis that a small number of microbial species organize the overall root-microbiome dynamics.

18S rRNA V9 metabarcoding for diet characterization: a critical evaluation with two sympatric zooplanktivorous fish species

The potential of the 18S rRNA V9 metabarcoding approach for diet assessment was explored using MiSeq paired‐end (PE; 2 × 150 bp) technology. To critically evaluate the method′s performance with degraded/digested DNA, the diets of two zooplanktivorous fish species from the Bay of Biscay, European sardine (Sardina pilchardus) and European sprat (Sprattus sprattus), were analysed. The taxonomic resolution and quantitative potential of the 18S V9 metabarcoding was first assessed both in silico and with mock and field plankton samples. Our method was capable of discriminating species within the reference database in a reliable way providing there was at least one variable position in the 18S V9 region. Furthermore, it successfully discriminated diet between both fish species, including habitat and diel differences among sardines, overcoming some of the limitations of traditional visual‐based diet analysis methods. The high sensitivity and semi‐quantitative nature of the 18S V9 metabarcoding approach was supported by both visual microscopy and qPCR‐based results. This molecular approach provides an alternative cost and time effective tool for food‐web analysis.

Next-Generation Sequencing of Aquatic Oligochaetes: Comparison of Experimental Communities

Aquatic oligochaetes are a common group of freshwater benthic invertebrates known to be very sensitive to environmental changes and currently used as bioindicators in some countries. However, more extensive application of oligochaetes for assessing the ecological quality of sediments in watercourses and lakes would require overcoming the difficulties related to morphology-based identification of oligochaetes species. This study tested the Next-Generation Sequencing (NGS) of a standard cytochrome c oxydase I (COI) barcode as a tool for the rapid assessment of oligochaete diversity in environmental samples, based on mixed specimen samples. To know the composition of each sample we Sanger sequenced every specimen present in these samples. Our study showed that a large majority of OTUs (Operational Taxonomic Unit) could be detected by NGS analyses. We also observed congruence between the NGS and specimen abundance data for several but not all OTUs. Because the differences in sequence abundance data were consistent across samples, we exploited these variations to empirically design correction factors. We showed that such factors increased the congruence between the values of oligochaetes-based indices inferred from the NGS and the Sanger-sequenced specimen data. The validation of these correction factors by further experimental studies will be needed for the adaptation and use of NGS technology in biomonitoring studies based on oligochaete communities.

Diversity analysis of sulfite- and sulfate-reducing microorganisms by multiplex dsrA and dsrB amplicon sequencing using new primers and mock community-optimized bioinformatics

Genes encoding dissimilatory sulfite reductase (DsrAB) are commonly used as diagnostic markers in ecological studies of sulfite- and sulfate-reducing microorganisms. Here, we developed new high-coverage primer sets for generation of reductive bacterial-type dsrA and dsrB polymerase chain reaction (PCR) products for highly parallel amplicon sequencing and a bioinformatics workflow for processing and taxonomic classification of short dsrA and dsrB reads. We employed two diverse mock communities that consisted of 45 or 90 known dsrAB sequences derived from environmental clones to precisely evaluate the performance of individual steps of our amplicon sequencing approach on the Illumina MiSeq platform. Although PCR cycle number, gene-specific primer mismatches and stringent filtering for high-quality sequences had notable effects on the observed dsrA and dsrB community structures, recovery of most mock community sequences was generally proportional to their relative input abundances. Successful dsrA and dsrB diversity analysis in selected environmental samples further proved that the multiplex amplicon sequencing approach is adequate for monitoring spatial distribution and temporal abundance dynamics of dsrAB-containing microorganisms. Although tested for reductive bacterial-type dsrAB, this method is readily applicable for oxidative-type dsrAB of sulfur-oxidizing bacteria and also provides guidance for processing short amplicon reads of other functional genes.