Validation of COI metabarcoding primers for terrestrial arthropods

Abstract

Metabarcoding can rapidly determine the species composition of bulk samples and thus aids biodiversity and ecosystem assessment. However, it is essential to use primer sets that minimize amplification bias among taxa to maximize species recovery. Despite this fact, the performance of primer sets employed for metabarcoding terrestrial arthropods has not been sufficiently evaluated. This study tests the performance of 36 primer sets on a mock community containing 374 insect species. Amplification success was assessed with gradient PCRs and the 21 most promising primer sets selected for metabarcoding. These 21 primer sets were also tested by metabarcoding a Malaise trap sample. We identified eight primer sets, mainly those including inosine and/or high degeneracy, that recovered more than 95% of the species in the mock community. Results from the Malaise trap sample were congruent with the mock community, but primer sets generating short amplicons produced potential false positives. Taxon recovery from both mock community and Malaise trap sample metabarcoding were used to select four primer sets for additional evaluation at different annealing temperatures (40–60 °C) using the mock community. The effect of temperature varied by primer pair but overall it only had a minor effect on taxon recovery. This study reveals the weak performance of some primer sets employed in past studies. It also demonstrates that certain primer sets can recover most taxa in a diverse species assemblage. Thus, based our experimental set up, there is no need to employ several primer sets targeting the same gene region. We identify several suitable primer sets for arthropod metabarcoding, and specifically recommend BF3 + BR2, as it is not affected by primer slippage and provides maximal taxonomic resolution. The fwhF2 + fwhR2n primer set amplifies a shorter fragment and is therefore ideal when targeting degraded DNA (e.g., from gut contents).

New 16S rRNA primers to uncover Bdellovibrio and like organisms diversity and abundance

“…By designing specific primers, amplification biases were minimized and the recovery of BALOs taxa maximized (Elbrecht et al, 2019). Globally, some of our primers worked properly for the different tested ecosystems and we are confident they could be applied successfully to other systems, even if further testing and optimization may be required.…”

“…Furthermore, Bacteriovorax primer p584F -p874R might also be concerned with most likely Peredibacter being more present than Bacteriovorax as reported by Paix et al (2019). Finally, primers' performance could be related to other reasons that we did not explore here such as DNA polymerase (Śpibida et al, 2017), the number of PCR cycles or the cell GC content (Elbrecht et al, 2019).…”

Putting COI Metabarcoding in Context: The Utility of Exact Sequence Variants (ESVs) in Biodiversity Analysis

“…Some of the early microbiome literature used only a single primer set to produce single amplicon datasets, and this has facilitated large scale studies and brought a measure of standardization to the field (Gilbert et al, 2014;Thompson et al, 2017). There are many examples, however, showing the effect of primer bias for a variety of commonly used metabarcoding primers (Hong et al, 2009;Bellemain et al, 2010;Clarke et al, 2014;Gibson et al, 2014;Elbrecht et al, 2019;Hajibabaei et al, 2019). There is also difficulty in designing "universal" COI primers to capture broad swaths of phylogenetic diversity and a switch to a multi-marker approach has been proposed for assessing animal diversity (Deagle et al, 2014).…”

Ecosystems Monitoring Powered by Environmental Genomics: A Review of Current Strategies with An Implementation Roadmap

“…Nevertheless, multiple studies have shown that there is room for considerable improvements to better bridge the current gaps between taxonomy-dependent molecular and morphology-based approaches. Taxonomic breadth in HTS data could be broadened by carefully designing novel amplification primers (Elbrecht et al, 2019) or using more than one primer pair (Corse et al, 2019). Applying correction factors to read counts, based on established knowledge of the biovolume (Vasselon et al, 2018), the number of copies of the targeted marker (Vetrovský, et al, 2013) or by spiking samples with known internal standard for quantitative determinations (Tkacz et al, 2018;Ji et al, 2019), are all promising methods for resolving these challenges.…”