DNA metabarcoding—Need for robust experimental designs to draw sound ecological conclusions

DNA metabarcoding, especially when coupled with high-throughput DNA sequencing, is currently revolutionizing our capacity to assess biodiversity across a full range of taxa and habitats, from soil microbes (e.g., Thompson et al., 2017) to large marine fish (e.g., Thomsen et al., 2016), and from contemporary to tens of thousands year-old biological communities (e.g., Willerslev et al., 2003). The breadth of potential applications is immense and spans surveys on the diversity or diet of species native to specific ecosystems to bioindication (Pawlowski et al., 2018). The approach is also especially cost-effective and easy to implement, which makes DNA metabarcoding one of the tools of choice of the 21st century for fundamental research and the future of large-scale biodiversity monitoring programs (reviewed in Bohan et al., 2017; Creer et al., 2016; Taberlet, Bonin, Zinger, Thomsen Nilsson et al., 2019; Dickie et al., 2018; Taberlet et al., 2018). Whether the starting material consists of DNA from bulk samples (community DNA) and/or from environmental DNA (eDNA), all DNA metabarcoding studies rely on a deceptively simple succession of core experimental steps: (a) sampling and preservation of the starting material, (b), DNA extraction, (c) PCR amplification of a taxonomically-informative genomic region, (d) high-throughput DNA sequencing of the amplicons, and (e) sequence analysis using bioinformatic pipelines. Despite this apparent simplicity, each step can potentially introduce its own sources of artifacts and biases (Figure 1). For example, the sampling design might not be effective for capturing the full taxonomic diversity or the ecological processes under study, an undesired bias for studies based on species detection. The availability of DNA in the samples is governed by its production rate, transport and persistence, processes which are all largely dependent on the targeted organisms, their biomass, and the ecosystem considered. A correct assessment of an ecological phenomenon based on DNA metabarcoding require not only implementation of standardized standardized, randomized and repeatable sampling designs and procedures (Dickie et al., 2018), but also consideration of DNA dynamics in the underlying matrix (i.e., in gut, faeces, water or soil matrices from tropical or boreal organisms/ecosystems; Barnes Deagle, Jarman, Coissac, Pompanon, Edgar, 2018; Esling, Lejzerowicz, Schnell, Bohmann, Murray, Coghlan, Schnell et al., 2015). Similarly, the Illumina index located on the P5 sequencing adaptor can be subjected to “index jumps”, resulting in apparent cross-contaminations (Taberlet et al., 2018). This bias happens when several individual Illumina sequencing libraries are pooled and loaded on the same sequencing lane (Kircher, Sawyer, Nilsson et al., 2019; Taberlet et al., 2018). Still, it illustrates that any potential bias must be considered carefully when designing an experimental protocol and when interpreting the results. This is crucial to limit their impact on downstream analyses, and to ensure that the conclusion drawn from such data are authentic. There is now an increasingly diverse range of field, laboratory (e.g., Caporaso et al., 2011; Taberlet et al., 2018; Valentini et al., 2009) and bioinformatics (e.g., Boyer et al., 2016; Caporaso et al., 2010; Dumbrell, Ferguson, Coissac, Riaz, Pollock, Glendinning, Wisedchanwet, Taberlet et al., 2018), and where DNA sequencing costs are rapidly decreasing, we should be always mindful of the adage “better safe than sorry”. This note does not mean to imply that the systematic use of the highest technical and analytical standards is reasonable nor the universal remedy for all the challenges associated with DNA metabarcoding. Rather, we strongly encourage researchers and end-users to adopt reflective decision-making when designing their experiment and to critically appraise their results, with the ultimate aim to prove the robustness and reproducibility of their conclusions.