Long weekend for all the Canadians which means more time to read and certainly no post on Monday.
Knowledge of community structure within an ecosystem is essential when trying to understand the function and importance of the system and when making related management decisions. Within the larger ecosystem, microhabitats play an important role by providing inhabitants with a subset of available resources. On coral reefs, cryptobenthic fishes encompass many groups and make up an important proportion of the biodiversity. However, these fishes are relatively small, exhibit extreme visual or behavioral camouflage, and, therefore, are often overlooked. We examined the differences in fish community structure between three common reef microhabitats (live hard coral, dead coral rubble, and sand) using ichthyocide stations in the central Red Sea. Using a combination of morphological and genetic (cytochrome oxidase I (COI) barcoding) techniques, we identified 326 individuals representing 73 species spread across 17 families, from fifteen 1 m2 quadrats. Fish assemblages in the three microhabitats were significantly different from each other. Rubble microhabitats yielded the highest levels of fish abundance, richness, and diversity, followed by hard coral, and then sand. The results show that benthic composition, even at a small scale, influences cryptobenthic communities. This study also provides new COI sequence data to public databases, in order to further the research of cryptobenthic fishes in the Red Sea region.
The cytochrome c oxidase subunit I (cox1) gene is the main mitochondrial molecular marker playing a pivotal role in phylogenetic research and is a crucial barcode sequence. Folmer's "universal" primers designed to amplify this gene in metazoan invertebrates allowed quick and easy barcode and phylogenetic analysis. On the other hand, the increase in the number of studies on barcoding leads to more frequent publishing of incorrect sequences, due to amplification of non-target taxa, and insufficient analysis of the obtained sequences. Consequently, some sequences deposited in genetic databases are incorrectly described as obtained from invertebrates, while being in fact bacterial sequences. In our study, in which we used Folmer's primers to amplify COI sequences of the crustacean fairy shrimp Branchipus schaefferi (Fischer 1834), we also obtained COI sequences of microbial contaminants from Aeromonas sp. However, when we searched the GenBank database for sequences closely matching these contaminations we found entries described as representatives of Gastrotricha and Mollusca. When these entries were compared with other sequences bearing the same names in the database, the genetic distance between the incorrect and correct sequences amplified from the same species was c.a. 65%. Although the responsibility for the correct molecular identification of species rests on researchers, the errors found in already published sequences data have not been re-evaluated so far. On the basis of the standard sampling technique we have estimated with 95% probability that the chances of finding incorrectly described metazoan sequences in the GenBank depend on the systematic group, and variety from less than 1% (Mollusca and Arthropoda) up to 6.9% (Gastrotricha). Consequently, the increasing popularity of DNA barcoding and metabarcoding analysis may lead to overestimation of species diversity. Finally, the study also discusses the sources of the problems with amplification of non-target sequences.
DNA metabarcoding is increasingly used in dietary studies to estimate diversity, composition, and frequency of occurrence of prey items. However, few studies have assessed how technical and biological replication affect the accuracy of diet estimates. This study addresses these issues using the European free-tailed bat Tadarida teniotis, involving high-throughput sequencing of a small fragment of the COI gene in 15 separate faecal pellets and a 15-pellet pool per each of 20 bats. We investigated how diet descriptors were affected by variability among (i) individuals, (ii) pellets of each individual, and (iii) PCRs of each pellet. In addition, we investigated the impact of (iv) analysing separate pellets versus pellet pools. We found that diet diversity estimates increased steadily with the number of pellets analysed per individual, with seven pellets required to detect ~80% of prey species. Most variation in diet composition was associated with differences among individual bats, followed by pellets per individual, and PCRs per pellet. The accuracy of frequency of occurrence estimates increased with the number of pellets analysed per bat, with the highest error rates recorded for prey consumed infrequently by many individuals. Pools provided poor estimates of diet diversity and frequency of occurrence, which were comparable to analysing a single pellet per individual, and consistently missed the less common prey items. Overall, our results stress that maximizing biological replication is critical in dietary metabarcoding studies, and emphasize that analysing several samples per individual rather than pooled samples produce more accurate results.
DNA metabarcoding is a technique used to survey biodiversity in many ecological settings, but there are doubts about whether it can provide quantitative results, i.e. the proportions of each species in the mixture as opposed to a species list. While there are several experimental studies that report quantitative metabarcoding results, there are a similar number that fail to do so. Here we provide the rationale to understand under what circumstances the technique can be quantitative. Basically, we simulate a mixture of DNA of S species with a defined initial abundance distribution. In the simulated PCR, each species increases its concentration following a certain amplification efficiency. The final DNA concentration will reflect the initial one when the efficiency is similar for all species; otherwise, the initial and final DNA concentrations would be poorly related. Although there are many known factors that modulate amplification efficiency, we focused on the number of primer-template mismatches, arguably the most important one. We used 15 common primers pairs targeting the mitochondrial COI region and the mitogenomes of ca. 1200 insect species. The results showed that some primers pairs produced quantitative results under most circumstances, whereas some other primers failed to do so. Many species, and a high diversity within the mixture, helped the metabarcoding to be quantitative. In conclusion, depending on the primer pair used in the PCR amplification and on the characteristics of the mixture analysed (i.e., high species richness, low evenness), DNA metabarcoding can provide a quantitative estimate of the relative abundances of different species.
Marine meiofauna comprises up to 22 phyla. Its morphological identification requires time and taxonomists' expertise, and molecular tools can make this task faster. We aim to disentangle meiofaunal diversity patterns at Araçá Bay by applying a model selection approach and estimating the effectiveness of metabarcoding (18S rDNA) and morphological methods for estimating the response of meiofauna diversity in small-scale interactions with environmental variables. A rarefaction curve indicated that ten samples were sufficient for estimating the total number of meiofauna OTUs in a tidal flat. In both approaches, richness was predicted by mean sand percentage, sediment sorting, and bacteria concentration. Nematode genera composition differed significantly between approaches, the result of taxonomic mismatch in the genetic database. The similarity between the model selected for diversity descriptors, the richness of nematode genera and meiofauna composition emphasized the utility of predictive models for metabarcoding estimates to detect small-scale interactions of these organisms.
Background: In light of the current biodiversity crisis, DNA barcoding is developing into an essential tool to quantify state shifts in global ecosystems. Current barcoding protocols often rely on short amplicon sequences, which yield accurate identification of biological entities in a community, but provide limited phylogenetic resolution across broad taxonomic scales. However, the phylogenetic structure of communities is an essential component of biodiversity. Consequently, a barcoding approach is required that unites robust taxonomic assignment power and high phylogenetic utility. A possible solution is offered by sequencing long ribosomal DNA (rDNA) amplicons on the MinION platform (Oxford Nanopore Technologies). Results: Using a dataset of various animal and plant species, with a focus on arthropods, we assemble a pipeline for long rDNA barcode analysis and introduce a new software (MiniBar) to demultiplex dual indexed nanopore reads. We find excellent phylogenetic and taxonomic resolution offered by long rDNA sequences across broad taxonomic scales. We highlight the simplicity of our approach by field barcoding with a miniaturized, mobile laboratory in a remote rainforest. We also test the utility of long rDNA amplicons for analysis of community diversity through metabarcoding and find that they recover highly skewed diversity estimates. Conclusions: Sequencing dual indexed, long rDNA amplicons on the MinION platform is a straightforward, cost effective, portable and universal approach for eukaryote DNA barcoding. Long rDNA amplicons scale up DNA barcoding by enabling the accurate recovery of taxonomic and phylogenetic diversity. However, bulk community analyses using long-read approaches may introduce biases and will require further exploration.
Background. Knowledge on the globally outstanding Amazonian biodiversity and its environmental determinants stems almost exclusively from aboveground organisms, notably plants. In contrast, the environmental factors and habitat preferences that drive diversity patterns for micro-organisms in the ground remain elusive, despite the fact that micro-organisms constitute the overwhelming majority of life forms in any given location, in terms of both diversity and abundance. Here we address how the diversity and community turnover of operational taxonomic units (OTU) of micro-organisms in soil and litter respond to soil physicochemical properties; whether OTU diversities and community composition in soil and litter are correlated with each other; and whether they respond in a similar way to soil properties. Methods. We used recently inferred OTUs from high-throughput metabarcoding of the 16S (prokaryotes) and 18S (eukaryotes) genes to estimate OTU diversity (OTU richness and effective number of OTUs) and community composition for prokaryotes and eukaryotes in soil and litter across four localities in Brazilian Amazonia. All analyses were run separately for prokaryote and eukaryote OTUs, and for each group using both presence-absence and abundance data. Combining these with novel data on soil chemical and physical properties, we identify abiotic correlates of soil and litter micro-organism diversity and community structure using regression, ordination, and variance partitioning analysis. Results. Soil organic carbon content was the strongest factor explaining OTU diversity (negative correlation) and pH was the strongest factor explaining turnover for prokaryotes and eukaryotes in both soil and litter. We found significant effects also for other soil variables, including both chemical and physical properties. The correlation between OTU diversity in litter and in soil was non-significant for eukaryotes and weak for prokaryotes, suggesting that diversity of in one substrate should not be used as a proxy for diversity in the other. The community compositions of both prokaryotes and eukaryotes were more separated for habitat type than for substrate (soil and litter). Discussion. In spite of the limited sampling (four localities, 39 plots), our results provide a broad-scale view of the physical and chemical correlations of soil and litter biodiversity in a longitudinal transect across the world’s largest rainforest. Our methods help to understand links between soil properties, OTU diversity patterns, and community composition and turnover. The lack of strong correlation between OTU diversity in litter and in soil suggests independence of diversity drives of these substrates and highlights the importance of including both measures in biodiversity assessments. Massive sequencing of soil and litter samples holds the potential to complement traditional biological inventories in advancing our understanding of the factors affecting tropical diversity.
Constructing networks has become an indispensable approach in understanding how different taxa interact. However, methodologies vary widely among studies, potentially limiting our ability to meaningfully compare results. In particular, how network architecture is influenced by the extent to which nodes are resolved to either taxa or taxonomic units is poorly understood. To address this, here we collate nine datasets of ecological interactions, from both observations and DNA metabarcoding, and construct networks under a range of commonly-used node resolutions. We demonstrate that small changes in node resolution can cause wide variation in almost all key metric values, including robustness and nestedness. Moreover, relative values of metrics such as robustness were seen to fluctuate continuously with node resolution, thereby potentially confounding comparisons of networks, as well as interpretations concerning their constituent ecological interactions. These findings highlight the need for care when comparing networks, especially where these differ with respect to node resolution.
