The Dark mAtteR iNvestigator (DARN) tool: getting to know the known unknowns in COI amplicon data

Abstract

The mitochondrial cytochrome C oxidase subunit I gene (COI) is commonly used in environmental DNA (eDNA) metabarcoding studies, especially for assessing metazoan diversity. Yet, a great number of COI operational taxonomic units (OTUs) or/and amplicon sequence variants (ASVs) retrieved from such studies do not get a taxonomic assignment with a reference sequence. To assess and investigate such sequences, we have developed the Dark mAtteR iNvestigator (DARN) software tool. For this purpose, a reference COI-oriented phylogenetic tree was built from 1,593 consensus sequences covering all the three domains of life. With respect to eukaryotes, consensus sequences at the family level were constructed from 183,330 sequences retrieved from the Midori reference 2 database, which represented 70% of the initial number of reference sequences. Similarly, sequences from 431 bacterial and 15 archaeal taxa at the family level (29% and 1% of the initial number of reference sequences respectively) were retrieved from the BOLD and the PFam databases. DARN makes use of this phylogenetic tree to investigate COI pre-processed sequences of amplicon samples to provide both a tabular and a graphical overview of their phylogenetic assignments. To evaluate DARN, both environmental and bulk metabarcoding samples from different aquatic environments using various primer sets were analysed. We demonstrate that a large proportion of non-target prokaryotic organisms, such as bacteria and archaea, are also amplified in eDNA samples and we suggest prokaryotic COI sequences to be included in the reference databases used for the taxonomy assignment to allow for further analyses of dark matter. DARN source code is available on GitHub at https://github.com/hariszaf/darn and as a Docker image at https://hub.docker.com/r/hariszaf/darn.

The bacterial hitchhiker’s guide to COI: Universal primer-based COI capture probes fail to exclude bacterial DNA, but 16S capture leaves metazoa behind

“…5A, B). This shines a particularly bright spotlight on the inaccuracy of a popular COI primer used in metazoan metabarcoding applications, an issue that has not gone unnoticed in recent literature (Deagle et al 2014, Collins et al 2019, Zafeiropoulos et al 2021. Admittedly, the ability of metazoan COI primers to amplify microbial DNA has been known for over a decade (Siddall et al 2009).…”

“…Admittedly, the ability of metazoan COI primers to amplify microbial DNA has been known for over a decade (Siddall et al 2009). Although broadscale biodiversity estimates can be obtained when using universal COI primers (e.g., Chapters II-III, Grey et al (2018), Zafeiropoulos et al (2021)), their bias towards bacterial templates can lead to severe impacts on future metabarcoding efforts, for instance by causing bacterial sequences mislabelled as eukaryotic taxa to be entered into reference databases (Siddall et al 2009, Mioduchowska et al 2018. One way to address this nontarget amplification is to develop new primers, however this usually comes with a cost on the universality (Elbrecht and Leese 2017, Marquina et al 2018, Sultana et al 2018, Collins et al 2019.…”

“…Kruskal-Wallis tests and paired Wilcoxon rank sum test with raw eDNA as reference group were calculated for each of the kingdoms. Furthermore, the Unassigned ASVs were taxonomically placed using the Dark mAtteR iNvestigator tool (DARN, Zafeiropoulos et al (2021)) in order to gain a better understanding of the ASVs that could not be assigned using the basic taxonomic assignment method. The placed Unassigned ASVs were qualitatively assessed using the kronaplot visualisations.…”

“…Analysing eDNA present in highly diverse marine samples is associated with wellknown challenges, especially when targeting metazoans. For example, the proportion of available eukaryotic DNA in a marine environmental sample can be overrun by orders of magnitude more of genetic material from microbial origins (Stat et al 2017, Zafeiropoulos et al 2021. Additionally, a recent study comparing the effectiveness of metabarcoding water eDNA samples against bulk samples has demonstrated large discrepancies in the biodiversity obtained between these two methods (Hajibabaei et al 2019), noting especially the inability of eDNA metabarcoding to detect key indicator species.…”

“…Yet, this complicates the development of universal primers aimed at amplifying COI for a broad range of taxa in a single metabarcoding effort (Collins et al 2019). These universal primers for COI are often highly degenerated, which can lead to high levels of nontarget amplification, and therefore reduce the efficiency of metabarcoding, as well as introduce primer bias during amplification (Elbrecht and Leese 2015, Collins et al 2019, Zafeiropoulos et al 2021. For marine eDNA samples it is not uncommon to have over 50% of the resultant Actual Sequence Variants (ASVs) or molecular operational taxonomic units (mOTUs) assigned to bacterial origins (Zafeiropoulos et al 2021).…”