Scrutinizing key steps for reliable metabarcoding of environmental samples

Abstract

Abstract1. Metabarcoding of environmental samples has many challenges and limitations that require carefully considered laboratory and analysis workflows to ensure reliable results. We explore how decisions regarding study design, laboratory set-up, and bioinformatic processing affect the final results, and provide guidelines for reliable study of environmental samples.2. We evaluate the performance of four primer sets targeting COI and 16S regions characterizing arthropod diversity in bat faecal samples, and investigate how metabarcoding results are affected by parameters including: (1) number of PCR replicates per sample, (2) sequencing depth, (3) PCR replicate processing strategy (i.e. either additively, by combining the sequences obtained from the PCR replicates, or restrictively, by only retaining sequences that occur in multiple PCR replicates for each sample), (4) minimum copy number for sequences to be retained, (5) chimera removal, and (6) similarity thresholds for Operational Taxonomic Unit (OTU) clustering. Lastly, we measure within-and between-taxa dissimilarities when using sequences from public databases to determine the most appropriate thresholds for OTU clustering and taxonomy assignment.3. Our results show that the use of multiple primer sets reduces taxonomic biases and increases taxonomic coverage. Taxonomic profiles resulting from each primer set are principally affected by how many PCR replicates are carried out per sample and how sequences are filtered across them, the sequence copy number threshold and the OTU clustering threshold. We also report considerable diversity differences between PCR replicates from each sample. Sequencing depth increases the dissimilarity between PCR replicates unless the bioinformatic strategies to remove allegedly artefactual sequences are adjusted according to the number of analysed sequences. Finally, we show that the appropriate identity thresholds for OTU clustering and taxonomy assignment differ between markers.4. Metabarcoding of complex environmental samples ideally requires (1) investigation of whether more than one primer sets targeting the same taxonomic group is needed to offset primer biases, (2) more than one PCR replicate per sample, (3) bioinformatic processing of sequences that balance diversity detection with removal of artefactual sequences, and (4) empirical selection of OTU clustering and taxonomy assignment thresholds tailored to each marker and the obtained taxa.

False‐negative detections from environmental DNA collected in the presence of large numbers of killer whales (Orcinus orca)

“…However, in Iceland, conditions were calm and seawater samples were collected from a RIB following long encounters (1-2 hr) with killer whales, but again Feces are considered one of the highest sources of eDNA in environments (Alberdi et al, 2018;Baker et al, 2018;Klymus, Richter, Chapman, & Paukert, 2015), particularly for marine mammals whose feces are known to float (Gillett, Frasier, Rolland, & White, 2010;Stewart, 2019). However, in Iceland, conditions were calm and seawater samples were collected from a RIB following long encounters (1-2 hr) with killer whales, but again Feces are considered one of the highest sources of eDNA in environments (Alberdi et al, 2018;Baker et al, 2018;Klymus, Richter, Chapman, & Paukert, 2015), particularly for marine mammals whose feces are known to float (Gillett, Frasier, Rolland, & White, 2010;Stewart, 2019).…”

“…In addition, increasing the number of PCR replicates may also have increased our chances of finding killer whale DNA, as PCR replicates counteract the effects of PCR stochasticity (Leray & Knowlton, 2015;Taberlet et al, 1996). PCR stochasticity is evident in many eDNA studies whereby a positive detection may only be found in one of several PCRs and/or not in all replicates in the PCR (Alberdi et al, 2018;Biggs et al, 2015;Dejean et al, 2012;Foote et al, 2012;Sigsgaard et al, 2016). PCR stochasticity is evident in many eDNA studies whereby a positive detection may only be found in one of several PCRs and/or not in all replicates in the PCR (Alberdi et al, 2018;Biggs et al, 2015;Dejean et al, 2012;Foote et al, 2012;Sigsgaard et al, 2016).…”

Spatiotemporal and demographic variation in the diet of New Zealand lesser short‐tailed bats (Mystacina tuberculata)

“…Molecular analyses are more sensitive to small, soft, easily digested material than traditional analyses (Clare et al., 2009) but cannot quantify biomass reliably. The primers employed may also preferentially amplify Lepidoptera (Alberdi, Aizpurua, Gilbert, & Bohmann, 2018). While our analysis may underestimate taxa such as Coleoptera and Orthoptera, the effect is likely not large, as these taxa dominated the diet of a beetle specialist in a study employed the same analysis (e.g., Clare, Symondson, & Fenton, 2014).…”

Vertebrate diversity revealed by metabarcoding of bulk arthropod samples from tropical forests

“…Incorporation of additional PCR replicates can increase the probability of amplifying target DNA in low quantity (Alberdi et al, 2018 (Alberdi et al, 2018). A postclustering curation could therefore be applied to identify and delete some of the false positives (Alberdi et al, 2018;Frøslev et al, 2017). To optimize the potential of detecting vertebrate DNA and limit the risk of false positives, another but more costly approach can be to include additional PCR replicates (e.g., five) which then would permit a stricter filtering (e.g., only keeping sequences occurring in min.…”