How much is enough? Effects of technical and biological replication on metabarcoding dietary analysis

Implementing cost‐effective monitoring programs for wild bees remains challenging due to the high costs of sampling and specimen identification. To reduce costs, next‐generation sequencing (NGS)‐based methods have lately been suggested as alternatives to morphology‐based identifications. To provide a comprehensive presentation of the advantages and weaknesses of different NGS‐based identification methods, we assessed three of the most promising ones, namely metabarcoding, mitogenomics and NGS barcoding. Using a regular monitoring data set (723 specimens identified using morphology), we found that NGS barcoding performed best for both species presence/absence and abundance data, producing only few false positives (3.4%) and no false negatives. In contrast, the proportion of false positives and false negatives was higher using metabarcoding and mitogenomics. Although strong correlations were found between biomass and read numbers, abundance estimates significantly skewed the communities' composition in these two techniques. NGS barcoding recovered the same ecological patterns as morphology. Ecological conclusions based on metabarcoding and mitogenomics were similar to those based on morphology when using presence/absence data, but different when using abundance data. In terms of workload and cost, we show that metabarcoding and NGS barcoding can compete with morphology, but not mitogenomics which was consistently more expensive. Based on these results, we advocate that NGS barcoding is currently the seemliest NGS method for monitoring of wild bees. Furthermore, this method has the advantage of potentially linking DNA sequences with preserved voucher specimens, which enable morphological re‐examination and will thus produce verifiable records which can be fed into faunistic databases.

Section: Discussionmentioning

confidence: 99%

Evaluating next‐generation sequencing (NGS) methods for routine monitoring of wild bees: Metabarcoding, mitogenomics or NGS barcoding

Gueuning

Ganser

Blaser

et al. 2019

“…This has been tested for some COI markers with positive results (Clarke et al, ). We also did not do any PCR replicates because recent studies have shown that, for faecal samples, variation in prey species composition among PCR replicates is much smaller than variation among samples (Mata et al, ). Amplification success was checked by visually inspecting 2 μl of each PCR product on a 2% gel stained agarose (GelRed Biotium).…”

Section: Methodsmentioning

confidence: 99%

“…This only happened for negative controls and taxa specific markers (IN16STK, ZBJ, and trn L), meaning that all samples contained amplifiable DNA. For the remaining ones, we removed from each PCR product all ESVs that had a read count <1% of the total number of reads of that PCR (Mata et al, ). This should allow the removal of most PCR and sequencing errors that still passed the ‘obiclean’ denoising step.…”

Section: Methodsmentioning

confidence: 99%

Advancing the integration of multi‐marker metabarcoding data in dietary analysis of trophic generalists

Silva

Mata

Lopes

et al. 2019

Self Cite

119

The application of DNA metabarcoding to dietary analysis of trophic generalists requires using multiple markers in order to overcome problems of primer specificity and bias. However, limited attention has been given to the integration of information from multiple markers, particularly when they partly overlap in the taxa amplified, and vary in taxonomic resolution and biases. Here, we test the use of a mix of universal and specific markers, provide criteria to integrate multi‐marker metabarcoding data and a python script to implement such criteria and produce a single list of taxa ingested per sample. We then compare the results of dietary analysis based on morphological methods, single markers, and the proposed combination of multiple markers. The study was based on the analysis of 115 faeces from a small passerine, the Black Wheatears (Oenanthe leucura). Morphological analysis detected far fewer plant taxa (12) than either a universal 18S marker (57) or the plant trnL marker (124). This may partly reflect the detection of secondary ingestion by molecular methods. Morphological identification also detected far fewer taxa (23) than when using 18S (91) or the arthropod markers IN16STK (244) and ZBJ (231), though each method missed or underestimated some prey items. Integration of multi‐marker data provided far more detailed dietary information than any single marker and estimated higher frequencies of occurrence of all taxa. Overall, our results show the value of integrating data from multiple, taxonomically overlapping markers in an example dietary data set.

“…To estimate the contributions of treatments and replicates to variation in community composition among units, we adopted the procedure of Mata et al (), based on nonparametric permutational multivariate analysis of variance (PERMANOVA), using the adonis function (Oksanen et al, ). Specifically, we modelled the contribution of five components: (a) sites; (b) subsampling day within sites; (c) extraction method within subsampling day; (d) extraction replicate within extraction method; and (e) PCR replicate within extraction replicate.…”

Section: Methodsmentioning

confidence: 99%

Have the cake and eat it: Optimizing nondestructive DNA metabarcoding of macroinvertebrate samples for freshwater biomonitoring

Martins

Galhardo

Filipe

et al. 2019

Self Cite

DNA metabarcoding can contribute to improving cost‐effectiveness and accuracy of biological assessments of aquatic ecosystems, but significant optimization and standardization efforts are still required to mainstream its application into biomonitoring programmes. In assessments based on freshwater macroinvertebrates, a key challenge is that DNA is often extracted from cleaned, sorted and homogenized bulk samples, which is time‐consuming and may be incompatible with sample preservation requirements of regulatory agencies. Here, we optimize and evaluate metabarcoding procedures based on DNA recovered from 96% ethanol used to preserve field samples and thus including potential PCR inhibitors and nontarget organisms. We sampled macroinvertebrates at five sites and subsampled the preservative ethanol at 1 to 14 days thereafter. DNA was extracted using column‐based enzymatic (TISSUE) or mechanic (SOIL) protocols, or with a new magnetic‐based enzymatic protocol (BEAD), and a 313‐bp COI fragment was amplified. Metabarcoding detected at least 200 macroinvertebrate taxa, including most taxa detected through morphology and for which there was a reference barcode. Better results were obtained with BEAD than SOIL or TISSUE, and with subsamples taken 7–14 than 1–7 days after sampling, in terms of DNA concentration and integrity, taxa diversity and matching between metabarcoding and morphology. Most variation in community composition was explained by differences among sites, with small but significant contributions of subsampling day and extraction method, and negligible contributions of extraction and PCR replication. Our methods enhance reliability of preservative ethanol as a potential source of DNA for macroinvertebrate metabarcoding, with a strong potential application in freshwater biomonitoring.