| Literature DB >> 33825307 |
Eva Aylagas1, Javier Atalah2, Pablo Sánchez-Jerez3, John Pearman2, Nuria Casado3, Jorge Asensi3, Kilian Toledo-Guedes3, Susana Carvalho1.
Abstract
Environmental genomics is a promising field for monitoring biodiversity in a timely fashion. Efforts have increasingly been dedicated to the use of bacteria DNA derived data to develop biotic indices for benthic monitoring. However, a substantial debate exists about whether bacteria-derived data using DNA metabarcoding should follow, for example, a taxonomy-based or a taxonomy-free approach to marine bioassessments. Here, we show case the value of DNA-based monitoring using the impact of fish farming as an example of anthropogenic disturbances in coastal areas and compare the performance of taxonomy-based and taxonomy-free approaches in detecting environmental alterations. We analyzed samples collected near to the farm cages and along distance gradients from two aquaculture installations, and at control sites, to evaluate the effect of this activity on bacterial assemblages. Using the putative response of bacterial taxa to stress we calculated the taxonomy-based biotic index microgAMBI. Then, the distribution of individual Amplicon Sequence Variants (ASVs), as a function of a gradient in sediment acid volatile sulfides was used to derive a taxonomy-free bacterial biotic index, specific for this dataset, using a de novo approach based on quantile regression splines. Our results show that microgAMBI revealed a organically enriched environment along the gradient. However, the de novo biotic index outperformed microgAMBI by providing a higher discriminatory power in detecting changes in abiotic factors directly related to fish production, whilst allowing the identification of new ASVs bioindicators. The de novo strategy applied here represents a robust method to define new bioindicators in regions or habitats where no previous information about the response of bacteria to environmental stressors exists. This article is protected by copyright. All rights reserved.Entities:
Keywords: anthropogenic impacts; biomonitoring; genomic approaches; metabarcoding; molecular methods
Year: 2021 PMID: 33825307 DOI: 10.1111/1755-0998.13395
Source DB: PubMed Journal: Mol Ecol Resour ISSN: 1755-098X Impact factor: 7.090