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Beyond taxonomy: Validating functional inference approaches in the context of fish-farm impact assessments
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  • Olivier Laroche,
  • Xavier Pochon,
  • Susanna Wood,
  • Nigel Keeley
Olivier Laroche
Institute of Marine Research

Corresponding Author:olli.laroche@gmail.com

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Xavier Pochon
Cawthron Institute
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Susanna Wood
Cawthron
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Nigel Keeley
Institute of Marine Research
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Abstract

Characterization of microbial assemblages via environmental DNA metabarcoding is increasingly being used in routine monitoring programs due to its sensitivity and cost-effectiveness. Several programs have been developed recently which infer functional profiles from 16S rRNA gene data using hidden-state prediction (HSP) algorithms. These might offer an economic and scalable alter-native to shotgun metagenomics. To date, HSP-based methods have seen limited use for benthic marine surveys and their performance in these environments remains unevaluated. In this study, 16S rRNA metabarcoding was applied to sediment samples collected at 0 and ≥ 1200 m from Norwegian salmon farms, and three metabolic inference approaches (PAPRICA, PICRUSt2 and TAX4FUN2) evaluated against metagenomics and environmental data. While metabarcoding and metagenomics recovered a comparable functional diversity, the taxonomic composition differed be-tween approaches, with genera richness up to 20× higher for metabarcoding. Comparisons between the sensitivity (highest true positive rates) and specificity (lowest true negative rates) of HSP-based programs in detecting functions found in metagenomics data ranged, respectively, from 0.52 and 0.60 to 0.76 and 0.79. However, little correlation was observed between the relative abundance of their specific functions. Functional beta-diversity of HSP-based data was strongly associated with that of metagenomics (r ≥ 0.86 for PAPRICA and TAX4FUN2) and responded similarly to the impact of fish farm activities. Our results demonstrate that although HSP-based metabarcoding approaches provide a slightly different functional profile than metagenomics, partly due to recovering a distinct community, they represent a cost-effective and valuable tool for characterizing and assessing the effects of fish farming on benthic ecosystems.
21 Sep 2020Submitted to Molecular Ecology Resources
12 Oct 2020Submission Checks Completed
12 Oct 2020Assigned to Editor
10 Nov 2020Reviewer(s) Assigned
19 Feb 2021Review(s) Completed, Editorial Evaluation Pending
19 Mar 2021Editorial Decision: Revise Minor
31 Mar 2021Review(s) Completed, Editorial Evaluation Pending
31 Mar 20211st Revision Received
04 May 2021Editorial Decision: Accept
Oct 2021Published in Molecular Ecology Resources volume 21 issue 7 on pages 2264-2277. 10.1111/1755-0998.13426