Gut content metabarcoding of specialized feeders is not a replacement for environmental DNA assays of seawater in reef environments

PeerJ. 2023 Sep 27:11:e16075. doi: 10.7717/peerj.16075. eCollection 2023.

Abstract

In tropical marine ecosystems, the coral-based diet of benthic-feeding reef fishes provides a window into the composition and health of coral reefs. In this study, for the first time, we compare multi-assay metabarcoding sequences of environmental DNA (eDNA) isolated from seawater and partially digested gut items from an obligate corallivore butterflyfish (Chaetodon lunulatus) resident to coral reef sites in the South China Sea. We specifically tested the proportional and statistical overlap of the different approaches (seawater vs gut content metabarcoding) in characterizing eukaryotic community composition on coral reefs. Based on 18S and ITS2 sequence data, which differed in their taxonomic sensitivity, we found that gut content detections were only partially representative of the eukaryotic communities detected in the seawater based on low levels of taxonomic overlap (3 to 21%) and significant differences between the sampling approaches. Overall, our results indicate that dietary metabarcoding of specialized feeders can be complimentary to, but is no replacement for, more comprehensive environmental DNA assays of reef environments that might include the processing of different substrates (seawater, sediment, plankton) or traditional observational surveys. These molecular assays, in tandem, might be best suited to highly productive but cryptic oceanic environments (kelp forests, seagrass meadows) that contain an abundance of organisms that are often small, epiphytic, symbiotic, or cryptic.

Keywords: Adaptation; Chaetodon lunulatus; Coral reefs; Environmental DNA; Reef fish; South China Sea.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Anthozoa* / genetics
  • Coral Reefs
  • DNA, Environmental*
  • Ecosystem
  • Seawater

Substances

  • DNA, Environmental

Associated data

  • Dryad/10.5061/dryad.dbrv15f5x

Grants and funding

This study was funded by the Australian Research Council Linkage Projects (LP160100839 and LP160101508) to Joseph D. DiBattista and Michael Bunce, a Dongsha Atoll Research Award under funding (108-2119-M-110-005) issued by the Ministry of Science and Technology to Joseph D. DiBattista and Shang-Yin Vanson Liu, as well as a Curtin University Early Career Research Fellowship to Joseph D. DiBattista. We also acknoweldge support from the Pawsey Supercomputing Centre with funding from the Australian Government and the Government of Western Australia. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.