Improving eDNA-based protist diversity assessments using networks of amplicon sequence variants

Intragenomic diversity of the V9 hypervariable domain in eukaryotes has little effect on metabarcoding

Metabarcoding revolutionized our understanding of diversity and ecology of microorganisms in different habitats. However, it is also associated with several inherent biases, one of which is associated with intragenomic diversity of a molecular barcode. Here, we compare intragenomic variability of the V9 region of the 18S rRNA gene in 19 eukaryotic phyla abundant in marine plankton. The level of intragenomic variability is comparable across all the phyla, and in most genomes and transcriptomes one V9 sequence and one OTU is predominant. However, most of the variability observed at the barcode level is probably caused by sequencing errors and is mitigated by using a denoising tool, DADA2. The SWARM algorithm commonly used in metabarcoding studies is not optimal for collapsing genuine and erroneous sequences into a single OTU, leading to an overestimation of diversity in metabarcoding data. For an unknown reason, SWARM inflates diversity of eupelagonemids more than that of other eukaryotes.

Maximising signal-to-noise ratios in environmental DNA-based monitoring

Man's impacts on global ecosystems are increasing and there is a growing demand that these activities be appropriately monitored. Monitoring requires measurement of a response metric ('signal') that changes maximally and consistently in response to the monitored activity irrespective of other factors ('noise'), thus maximising the signal-to-noise ratio. Indices derived from time-consuming morphology-based taxonomic identification of organisms are a core part of many monitoring programmes. Metabarcoding is an alternative to morphology-based identification and involves the sequencing of short fragments of DNA ('markers') from multiple taxa simultaneously. DNA suitable for metabarcoding includes that extracted from environmental samples (eDNA). Metabarcoding outputs DNA sequences that can be identified (annotated) by matching them against archived annotated sequences. However, sequences from most organisms are not archived - preventing annotation and potentially limiting metabarcoding in monitoring applications. Consequently, there is growing interest in using unannotated sequences as response metrics in monitoring programmes. We compared the sequences from three commonly used markers (16S (V3/V4 regions), 18S (V1/V2 regions) and COI) and, sampling along steep impact gradients, showed that the 16S and COI sequences were associated with the largest and smallest signal-to-noise ratio respectively. We trialled four separate, intuitive, noise-reduction approaches and demonstrated that removing less frequent sequences improved the signal-to-noise ratio, partitioning an additional 25 % from noise to explanatory factors in non-parametric ANOVA (NPA) and reducing dispersion in the data. For the 16S marker, retaining only the most frequently observed sequence, per sample, resulting in nine sequences across 150 samples, generated a near-maximal signal-to-noise ratio (95 % of the variance explained in NPA). We recommend that NPA, combined with rigorous elimination of less frequent sequences, be used to pre-filter sequences/taxa being used in monitoring applications. Our approach will simplify downstream analysis, for example the identification of key taxa and functional associations.

Metabarcoding Approaches for Soil Eukaryotes, Protists, and Microfauna

There have been major developments in the molecular characterization of soil protist and micrometazoan diversity, leading to a better understanding of these minute soil eukaryotes. Like in all newly developing research fields, several approaches are currently used in parallel to study these organisms. Here, we synthesize these various approaches and propose a best practice manual that should help researchers to efficiently target soil eukaryotic diversity as a whole. We cover the whole working pipeline, ranging from sampling to nucleic acids extraction to bioinformatic processing and sequence identification. Synchronous approaches to molecularly survey microbial-sized eukaryotes and other soil biodiversity groups are needed in order to provide a cumulative knowledge of soil biodiversity, as here shown for the soil eukaryome. This will be crucial in understanding the important ecosystem functions provided by soil biodiversity.

The Porifera microeukaryome: Addressing the neglected associations between sponges and protists

While bacterial and archaeal communities of sponges are intensively studied, given their importance to the animal's physiology as well as sources of several new bioactive molecules, the potential and roles of associated protists remain poorly known. Historically, culture-dependent approaches dominated the investigations of sponge-protist interactions. With the advances in omics techniques, these associations could be visualized at other equally important scales. Of the few existing studies, there is a strong tendency to focus on interactions with photosynthesizing taxa such as dinoflagellates and diatoms, with fewer works dissecting the interactions with other less common groups. In addition, there are bottlenecks and inherent biases in using primer pairs and bioinformatics approaches in the most commonly used metabarcoding studies. Thus, this review addresses the issues underlying this association, using the term "microeukaryome" to refer exclusively to protists associated with an animal host. We aim to highlight the diversity and community composition of protists associated with sponges and place them on the same level as other microorganisms already well studied in this context. Among other shortcomings, it could be observed that the biotechnological potential of the microeukaryome is still largely unexplored, possibly being a valuable source of new pharmacological compounds, enzymes and metabolic processes.

Diversity Patterns of Protists Are Highly Affected by Methods Disentangling Biological Variants: A Case Study in Oligotrich (s.l.) Ciliates

Protists are a dominant group in marine microplankton communities and play important roles in energy flux and nutrient cycling in marine ecosystems. Environmental sequences produced by high-throughput sequencing (HTS) methods are increasingly used for inferring the diversity and distribution patterns of protists. However, studies testing whether methods disentangling biological variants affect the diversity and distribution patterns of protists using field samples are insufficient. Oligotrich (s.l.) ciliates are one group of the abundant and dominant planktonic protists in coastal waters and open oceans. Using oligotrich (s.l.) ciliates in field samples as an example, the present study indicates that DADA2 performs better than SWARM, UNOISE, UPARSE, and UCLUST for inferring diversity patterns of oligotrich (s.l.) ciliates in the Pearl River Estuary and surrounding regions. UPARSE and UNOISE might underestimate species richness. SWARM might not be suitable for the resolution of alpha diversity owing to its rigorous clustering and sensitivity to sequence variations. UCLUST with 99% clustering threshold overestimates species richness, and the beta diversity pattern inferred by DADA2 is more reasonable than that of the other methods. Additionally, salinity is shown to be one of the key factors responsible for variations in the community distribution of ciliates, but infrequent marine-freshwater transitions occurred during evolutionary terms of this group.

Phylogenetic and functional diversity of Chrysophyceae in inland waters

Chrysophyceae are a diverse group of planktonic protists widely distributed in freshwater. They encompass a variety of orders, whereby heterotrophy has evolved independently in several phylogenetic lineages. Therefore, closely related taxa evolved that developed different feeding strategies (photo-, mixo-, heterotrophy). In high-throughput sequencing studies, the Chrysophyceae were usually addressed as a group rather than split in individual phylogenetic orders. Also because of the close relationship of the distinct nutritional strategies, no functional statements were made about nutritional patterns. Based on an extensive phylogenetic tree and phylogenetic placement, we link OTU diversity of Chrysophyceae from 218 freshwater lakes with phylogenetic affiliations. This provides information on the relative importance of lineages affiliated with different nutrition modes. Our study demonstrates that Chrysophyceae are one of the most common groups in freshwaters. We found Chrysophyceae in 213 out of 218 sample sites across Europe and in several sites they belong to the most commonly retrieved taxa. Ochromonadales and a Chrysosacca-Apoikiida clade (including Apoikiida, Chrysosaccales, Chrysastrella) are the most widespread Chrysophyceae groups and show a high degree of OTU diversity. Most detected and assignable OTUs were affiliated with mixotrophic Chrysophyceae. Niche width differs only slightly between members of different clades and between the different trophic modes. We found several OTUs within the Ochromonadales, Synurales, and Chrysosacca-Apoikiida clade, that show a wide distribution and large tolerance ranges concerning ecophysiological factors.

Patterns of eukaryotic diversity from the surface to the deep-ocean sediment

Remote deep-ocean sediment (DOS) ecosystems are among the least explored biomes on Earth. Genomic assessments of their biodiversity have failed to separate indigenous benthic organisms from sinking plankton. Here, we compare global-scale eukaryotic DNA metabarcoding datasets (18S-V9) from abyssal and lower bathyal surficial sediments and euphotic and aphotic ocean pelagic layers to distinguish plankton from benthic diversity in sediment material. Based on 1685 samples collected throughout the world ocean, we show that DOS diversity is at least threefold that in pelagic realms, with nearly two-thirds represented by abundant yet unknown eukaryotes. These benthic communities are spatially structured by ocean basins and particulate organic carbon (POC) flux from the upper ocean. Plankton DNA reaching the DOS originates from abundant species, with maximal deposition at high latitudes. Its seafloor DNA signature predicts variations in POC export from the surface and reveals previously overlooked taxa that may drive the biological carbon pump.

Antibiotics as a silent driver of climate change? A case study investigating methane production in freshwater sediments

Methane (CH4) is the second most important greenhouse gas after carbon dioxide (CO2) and is inter alia produced in natural freshwater ecosystems. Given the rise in CH4 emissions from natural sources, researchers are investigating environmental factors and climate change feedbacks to explain this increment. Despite being omnipresent in freshwaters, knowledge on the influence of chemical stressors of anthropogenic origin (e.g., antibiotics) on methanogenesis is lacking. To address this knowledge gap, we incubated freshwater sediment under anaerobic conditions with a mixture of five antibiotics at four levels (from 0 to 5000 µg/L) for 42 days. Weekly measurements of CH4 and CO2 in the headspace, as well as their compound-specific δ13C, showed that the CH4 production rate was increased by up to 94% at 5000 µg/L and up to 29% at field-relevant concentrations (i.e., 50 µg/L). Metabarcoding of the archaeal and eubacterial 16S rRNA gene showed that effects of antibiotics on bacterial community level (i.e., species composition) may partially explain the observed differences in CH4 production rates. Despite the complications of transferring experimental CH4 production rates to realistic field conditions, the study indicated that chemical stressors contribute to the emissions of greenhouse gases by affecting the methanogenesis in freshwaters.

Using metatranscriptomics to estimate the diversity and composition of zooplankton communities

DNA metabarcoding is a rapid, high‐resolution tool used for biomonitoring complex zooplankton communities. However, diversity estimates derived with this approach can be biased by the co‐detection of sequences from environmental DNA (eDNA), nuclear‐encoded mitochondrial (NUMT) pseudogene contamination, and taxon‐specific PCR primer affinity differences. To avoid these methodological uncertainties, we tested the use of metatranscriptomics as an alternative approach for characterizing zooplankton communities. Specifically, we compared metatranscriptomics with PCR‐based methods using genomic (gDNA) and complementary DNA (cDNA) amplicons, and morphology‐based data for estimating species diversity and composition for both mock communities and field‐collected samples. Mock community analyses showed that the use of gDNA mitochondrial cytochrome c oxidase I (mtCO1) amplicons inflates species richness due to the co‐detection of extra‐organismal eDNA. Significantly more amplicon sequence variants, nucleotide diversity, and indels were observed with gDNA amplicons than with cDNA, indicating the presence of putative NUMT pseudogenes. Moreover, PCR‐based methods failed to detect the most abundant species in mock communities due to priming site mismatch. Overall, metatranscriptomics provided estimates of species richness and composition that closely resembled those derived from morphological data. The use of metatranscriptomics was further tested using field‐collected samples, with the results showing consistent species diversity estimates among biological and technical replicates. Additionally, temporal zooplankton species composition changes could be monitored using different mitochondrial markers. These findings demonstrate the advantages of metatranscriptomics as an effective tool for monitoring diversity in zooplankton research.

To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography

BACKGROUND

The recent blooming of metabarcoding applications to biodiversity studies comes with some relevant methodological debates. One such issue concerns the treatment of reads by denoising or by clustering methods, which have been wrongly presented as alternatives. It has also been suggested that denoised sequence variants should replace clusters as the basic unit of metabarcoding analyses, missing the fact that sequence clusters are a proxy for species-level entities, the basic unit in biodiversity studies. We argue here that methods developed and tested for ribosomal markers have been uncritically applied to highly variable markers such as cytochrome oxidase I (COI) without conceptual or operational (e.g., parameter setting) adjustment. COI has a naturally high intraspecies variability that should be assessed and reported, as it is a source of highly valuable information. We contend that denoising and clustering are not alternatives. Rather, they are complementary and both should be used together in COI metabarcoding pipelines.

RESULTS

Using a COI dataset from benthic marine communities, we compared two denoising procedures (based on the UNOISE3 and the DADA2 algorithms), set suitable parameters for denoising and clustering, and applied these steps in different orders. Our results indicated that the UNOISE3 algorithm preserved a higher intra-cluster variability. We introduce the program DnoisE to implement the UNOISE3 algorithm taking into account the natural variability (measured as entropy) of each codon position in protein-coding genes.  This correction increased the number of sequences retained by 88%. The order of the steps (denoising and clustering) had little influence on the final outcome.

CONCLUSIONS

We highlight the need for combining denoising and clustering, with adequate choice of stringency parameters, in COI metabarcoding. We present a program that uses the coding properties of this marker to improve the denoising step. We recommend researchers to report their results in terms of both denoised sequences (a proxy for haplotypes) and clusters formed (a proxy for species), and to avoid collapsing the sequences of the latter into a single representative. This will allow studies at the cluster (ideally equating species-level diversity) and at the intra-cluster level, and will ease additivity and comparability between studies.

An integrative approach sheds new light onto the systematics and ecology of the widespread ciliate genus Coleps (Ciliophora, Prostomatea)

Species of the genus Coleps are one of the most common planktonic ciliates in lake ecosystems. The study aimed to identify the phenotypic plasticity and genetic variability of different Coleps isolates from various water bodies and from culture collections. We used an integrative approach to study the strains by (i) cultivation in a suitable culture medium, (ii) screening of the morphological variability including the presence/absence of algal endosymbionts of living cells by light microscopy, (iii) sequencing of the SSU and ITS rDNA including secondary structures, (iv) assessment of their seasonal and spatial occurrence in two lakes over a one-year cycle both from morphospecies counts and high-throughput sequencing (HTS), and, (v) proof of the co-occurrence of Coleps and their endosymbiotic algae from HTS-based network analyses in the two lakes. The Coleps strains showed a high phenotypic plasticity and low genetic variability. The algal endosymbiont in all studied strains was Micractinium conductrix and the mutualistic relationship turned out as facultative. Coleps is common in both lakes over the whole year in different depths and HTS has revealed that only one genotype respectively one species, C. viridis, was present in both lakes despite the different lifestyles (mixotrophic with green algal endosymbionts or heterotrophic without algae). Our results suggest a future revision of the species concept of the genus Coleps.

Lake Ecosystem Robustness and Resilience Inferred from a Climate-Stressed Protistan Plankton Network

Network analyses of biological communities allow for identifying potential consequences of climate change on the resilience of ecosystems and their robustness to resist stressors. Using DNA metabarcoding datasets from a three-year-sampling (73 samples), we constructed the protistan plankton co-occurrence network of Lake Zurich, a model lake ecosystem subjected to climate change. Despite several documentations of dramatic lake warming in Lake Zurich, our study provides an unprecedented perspective by linking changes in biotic association patterns to climate stress. Water temperature belonged to the strongest environmental parameters splitting the data into two distinct seasonal networks (October–April; May–September). The expected ecological niche of phytoplankton, weakened through nutrient depletion because of permanent thermal stratification and through parasitic fungi, was occupied by the cyanobacterium Planktothrix rubescens and mixotrophic nanoflagellates. Instead of phytoplankton, bacteria and nanoflagellates were the main prey organisms associated with key predators (ciliates), which contrasts traditional views of biological associations in lake plankton. In a species extinction scenario, the warm season network emerged as more vulnerable than the cold season network, indicating a time-lagged effect of warmer winter temperatures on the communities. We conclude that climate stressors compromise lake ecosystem robustness and resilience through species replacement, richness differences, and succession as indicated by key network properties.

Benthic Diatoms in River Biomonitoring—Present and Future Perspectives within the Water Framework Directive

The European Water Framework Directive 2000/60/EC (WFD) has been implemented over the past 20 years, using physicochemical, biological and hydromorphological elements to assess the ecological status of surface waters. Benthic diatoms (i.e., phytobenthos) are one of the most common biological quality elements (BQEs) used in surface water monitoring and are particularly successful in detecting eutrophication, organic pollution and acidification. Herein, we reviewed their implementation in river biomonitoring for the purposes of the WFD, highlighting their advantages and disadvantages over other BQEs, and we discuss recent advances that could be applied in future biomonitoring. Until now, phytobenthos have been intercalibrated by the vast majority (26 out of 28) of EU Member States (MS) in 54% of the total water bodies assessed and was the most commonly used BQE after benthic invertebrates (85% of water bodies), followed by fish (53%), macrophytes (27%) and phytoplankton (4%). To meet the WFD demands, numerous taxonomy-based quality indices have been developed among MS, presenting, however, uncertainties possibly related to species biogeography. Recent development of different types of quality indices (trait-based, DNA sequencing and predictive modeling) could provide more accurate results in biomonitoring, but should be validated and intercalibrated among MS before their wide application in water quality assessments.

DNA Metabarcoding for the Characterization of Terrestrial Microbiota-Pitfalls and Solutions

Soil-borne microbes are major ecological players in terrestrial environments since they cycle organic matter, channel nutrients across trophic levels and influence plant growth and health. Therefore, the identification, taxonomic characterization and determination of the ecological role of members of soil microbial communities have become major topics of interest. The development and continuous improvement of high-throughput sequencing platforms have further stimulated the study of complex microbiota in soils and plants. The most frequently used approach to study microbiota composition, diversity and dynamics is polymerase chain reaction (PCR), amplifying specific taxonomically informative gene markers with the subsequent sequencing of the amplicons. This methodological approach is called DNA metabarcoding. Over the last decade, DNA metabarcoding has rapidly emerged as a powerful and cost-effective method for the description of microbiota in environmental samples. However, this approach involves several processing steps, each of which might introduce significant biases that can considerably compromise the reliability of the metabarcoding output. The aim of this review is to provide state-of-the-art background knowledge needed to make appropriate decisions at each step of a DNA metabarcoding workflow, highlighting crucial steps that, if considered, ensures an accurate and standardized characterization of microbiota in environmental studies.

Aquatic food webs in deep temperate lakes: Key species establish through their autecological versatility

Microbial planktonic communities are the basis of food webs in aquatic ecosystems since they contribute substantially to primary production and nutrient recycling. Network analyses of DNA metabarcoding data sets emerged as a powerful tool to untangle the complex ecological relationships among the key players in food webs. In this study, we evaluated co-occurrence networks constructed from time-series metabarcoding data sets (12 months, biweekly sampling) of protistan plankton communities in surface layers (epilimnion) and bottom waters (hypolimnion) of two temperate deep lakes, Lake Mondsee (Austria) and Lake Zurich (Switzerland). Lake Zurich plankton communities were less tightly connected, more fragmented and had a higher susceptibility to a species extinction scenario compared to Lake Mondsee communities. We interpret these results as a lower robustness of Lake Zurich protistan plankton to environmental stressors, especially stressors resulting from climate change. In all networks, the phylum Ciliophora contributed the highest number of nodes, among them several in key positions of the networks. Associations in ciliate-specific subnetworks resembled autecological species-specific traits that indicate adaptions to specific environmental conditions. We demonstrate the strength of co-occurrence network analyses to deepen our understanding of plankton community dynamics in lakes and indicate biotic relationships, which resulted in new hypotheses that may guide future research in climate-stressed ecosystems.

Daring to be differential: metabarcoding analysis of soil and plant-related microbial communities using amplicon sequence variants and operational taxonomical units

Background

Microorganisms are not only indispensable to ecosystem functioning, they are also keystones for emerging technologies. In the last 15 years, the number of studies on environmental microbial communities has increased exponentially due to advances in sequencing technologies, but the large amount of data generated remains difficult to analyze and interpret. Recently, metabarcoding analysis has shifted from clustering reads using Operational Taxonomical Units (OTUs) to Amplicon Sequence Variants (ASVs). Differences between these methods can seriously affect the biological interpretation of metabarcoding data, especially in ecosystems with high microbial diversity, as the methods are benchmarked based on low diversity datasets.

Results

In this work we have thoroughly examined the differences in community diversity, structure, and complexity between the OTU and ASV methods. We have examined culture-based mock and simulated datasets as well as soil- and plant-associated bacterial and fungal environmental communities. Four key findings were revealed. First, analysis of microbial datasets at family level guaranteed both consistency and adequate coverage when using either method. Second, the performance of both methods used are related to community diversity and sample sequencing depth. Third, differences in the method used affected sample diversity and number of detected differentially abundant families upon treatment; this may lead researchers to draw different biological conclusions. Fourth, the observed differences can mostly be attributed to low abundant (relative abundance < 0.1%) families, thus extra care is recommended when studying rare species using metabarcoding. The ASV method used outperformed the adopted OTU method concerning community diversity, especially for fungus-related sequences, but only when the sequencing depth was sufficient to capture the community complexity.

Conclusions

Investigation of metabarcoding data should be done with care. Correct biological interpretation depends on several factors, including in-depth sequencing of the samples, choice of the most appropriate filtering strategy for the specific research goal, and use of family level for data clustering.

Evaluation of Two Primer Sets for Amplification of Comammox Nitrospira amoA Genes in Wetland Soils

After the discovery of complete ammonia-oxidizing (comammox) Nitrospira, detection and assessments of the contribution of comammox Nitrospira communities to nitrogen cycling are in great demand. PCR-based approach, a common method for the detection of comammox, depends strongly on accurate amplification of the amoA genes from the original DNA samples using appropriate primers. In this study, we reported an evaluation of the performance of two commonly used primer sets, Ntsp-amoA 162F/359R and comaA/B-244f/659r, for amplifying the comammox amoA genes from three representative wetland soils in China [Sangsang (SS), Sanjiang (SJ), and Xianghai (XH)]. Our results demonstrated the two primer sets could both successfully amplify the clades with high relative abundances (RA), and further revealed a broadly similar diversity and community composition of dominant comammox operational taxonomic units (OTUs) (RA ≥ 1%) in each of the three wetland soils. However, the clades with low RA, such as the clade A (1.26%) in SJ and the clade B (11.54%) in XH that were recovered by metagenomics analysis, failed to be amplified using comaA/B-244f/659r, but were successfully amplified and sequenced using Ntsp-amoA 162F/359R. It indicated that, compared to comaA/B-244f/659r, Ntsp-amoA 162F/359R was more sensitive to the clades with low RA. However, it is worth noting that Ntsp-amoA 162F/359R would overestimate the RA of some rare clades. For example, the RAs of clade B in XH were overestimated by 32-fold. Furthermore, high levels of non-target amplification were detected via gel electrophoresis using both primer sets, especially for comammox Clade B amoA genes, implying that we should treat qPCR results based on these primers with caution. Taken together, our study comprehensively compared the performance of the two primer sets on the sensitivity and specificity of amplifying comammox amoA genes in three wetland soils, pointing out the necessity of further development of new primers for the efficient and accurate detection of comammox in various environments.

Gene Similarity Networks Unveil a Potential Novel Unicellular Group Closely Related to Animals from the Tara Oceans Expedition

The Holozoa clade comprises animals and several unicellular lineages (choanoflagellates, filastereans, and teretosporeans). Understanding their full diversity is essential to address the origins of animals and other evolutionary questions. However, they are poorly known. To provide more insights into the real diversity of holozoans and check for undiscovered diversity, we here analyzed 18S rDNA metabarcoding data from the global Tara Oceans expedition. To overcome the low phylogenetic information contained in the metabarcoding data set (composed of sequences from the short V9 region of the gene), we used similarity networks by combining two data sets: unknown environmental sequences from Tara Oceans and known reference sequences from GenBank. We then calculated network metrics to compare environmental sequences with reference sequences. These metrics reflected the divergence between both types of sequences and provided an effective way to search for evolutionary relevant diversity, further validated by phylogenetic placements. Our results showed that the percentage of unicellular holozoan diversity remains hidden. We found novelties in several lineages, especially in Acanthoecida choanoflagellates. We also identified a potential new holozoan group that could not be assigned to any of the described extant clades. Data on geographical distribution showed that, although ubiquitous, each unicellular holozoan lineage exhibits a different distribution pattern. We also identified a positive association between new animal hosts and the ichthyosporean symbiont Creolimax fragrantissima, as well as for other holozoans previously reported as free-living. Overall, our analyses provide a fresh perspective into the diversity and ecology of unicellular holozoans, highlighting the amount of undescribed diversity.

Perspectives from Ten Years of Protist Studies by High-Throughput Metabarcoding

During the last decade, high-throughput metabarcoding became routine for analyzing protistan diversity and distributions in nature. Amid a multitude of exciting findings, scientists have also identified and addressed technical and biological limitations, although problems still exist for inference of meaningful taxonomic and ecological knowledge based on short DNA sequences. Given the extensive use of this approach, it is critical to settle our understanding on its strengths and weaknesses and to synthesize up-to-date methodological and conceptual trends. This article summarizes key scientific and technical findings, and identifies current and future directions in protist research that uses metabarcoding.

Species detection and delineation in the marine planktonic diatoms Chaetoceros and Bacteriastrum through metabarcoding: making biological sense of haplotype diversity

High-throughput sequencing (HTS) metabarcoding is commonly applied to assess phytoplankton diversity. Usually, haplotypes are grouped into operational taxonomic units (OTUs) through clustering, whereby the resulting number of OTUs depends on chosen similarity thresholds. We applied, instead, a phylogenetic approach to infer taxa among 18S rDNA V4-metabarcode haplotypes gathered from 48 time-series samples using the marine planktonic diatoms Chaetoceros and Bacteriastrum as test case. The 73 recovered taxa comprised both solitary haplotypes and polytomies, the latter composed each of a highly abundant, dominant haplotype and one to several minor, peripheral haplotypes. The solitary and dominant haplotypes usually matched reference sequences, enabling species assignation of taxa. We hypothesise that the super-abundance of reads in dominant haplotypes results from the homogenization effect of concerted evolution. Reads of populous peripheral haplotypes and dominant haplotypes show comparable distribution patterns over the sample dates, suggesting that they are part of the same population. Many taxa revealed marked seasonality, with closely related ones generally showing distinct periodicity, whereas others occur year-round. Phylogenies inferred from metabarcode haplotypes enable delineation of biologically meaningful taxa, whereas OTUs resulting from clustering algorithms often deviate markedly from such taxa.

Gut microbiota plasticity is correlated with sustained weight loss on a low-carb or low-fat dietary intervention

While low-carbohydrate and low-fat diets can both lead to weight-loss, a substantial variability in achieved long-term outcomes exists among obese but otherwise healthy adults. We examined the hypothesis that structural differences in the gut microbiota explain a portion of variability in weight-loss using two cohorts of obese adults enrolled in the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) study. A total of 161 pre-diet fecal samples were sequenced from a discovery cohort (n = 66) and 106 from a validation cohort (n = 56). An additional 157 fecal samples were sequenced from the discovery cohort after 10 weeks of dietary intervention. We found no specific bacterial signatures associated with weight loss that were consistent across both cohorts. However, the gut microbiota plasticity (i.e. variability), was correlated with long-term (12-month) weight loss in a diet-dependent manner; on the low-fat diet subjects with higher pre-diet daily plasticity had higher sustained weight loss, whereas on the low-carbohydrate diet those with higher plasticity over 10 weeks of dieting had higher 12-month weight loss. Our findings suggest the potential importance of gut microbiota plasticity for sustained weight-loss. We highlight the advantages of evaluating kinetic trends and assessing reproducibility in studies of the gut microbiota.