A microbial mandala for environmental monitoring: Predicting multiple impacts on estuarine prokaryote communities of the Bay of Biscay

Abstract

Routine monitoring of benthic biodiversity is critical for managing and understanding the anthropogenic impacts on marine, transitional and freshwater ecosystems.However, traditional reliance on morphological identification generally makes it costprohibitive to increase the scale of monitoring programmes. Metabarcoding of environmental DNA has clear potential to overcome many of the problems associated with traditional monitoring, with prokaryotes and other microorganisms showing particular promise as bioindicators. However, due to the limited knowledge regarding the ecological roles and responses of environmental microorganisms to different types of pressure, the use of de novo approaches is necessary. Here, we use two such approaches for the prediction of multiple impacts present in estuaries and coastal areas of the Bay of Biscay based on microbial communities. The first (Random Forests) is a machine learning method while the second (Threshold Indicator Taxa Analysis and quantile regression splines) is based on de novo identification of bioindicators. Our results show that both methods overlap considerably in the indicator taxa identified, but less for sequence variants. Both methods also perform well in spite of the complexity of the studied ecosystem, providing predictive models with strong correlation to reference values and fair to good agreement with ecological status groups. The ability to predict several specific types of pressure is especially appealing. The cross-validated models and biotic indices developed can be directly applied to predict the environmental status of estuaries in the same geographical region, although more work is needed to evaluate and improve them for use in new regions or habitats.

Global Trends of Benthic Bacterial Diversity and Community Composition Along Organic Enrichment Gradients of Salmon Farms

“…Since its first isolation in Chile in 1989, the bacterium has been reported in Norway, Scotland, Greece, Canada, and the United States, among others ( Marshall et al, 2014 ). While Desulfuromonadaceae (iron-reducing bacteria and SRBs) were more abundant in unperturbed sediments in studies of Dowle et al (2015) and Aylagas et al (2017) , the same family was indicating perturbed coastal sediment conditions ( Lanzen et al, 2020 ), pollution from oil drilling in offshore sediments ( Nguyen et al, 2018 ), and organically enriched sediments ( Julies Elsabé et al, 2012 ; Aranda et al, 2015 ). Likewise, Syntrophobacteraceae were found in undisturbed sediments as well as at sites with high organic enrichment ( Choi et al, 2018 ).…”

“…Desulfobacteraceae are able to metabolize a high variety of carbon sources and hydrogen ( Isaksen and Teske, 1996 ; Schwartz and Friedrich, 2006 ) and are involved in a variety of processes regarding biodegradation of pollutants, organic matter turnover, and sulfur and carbon cycles ( Zhang et al, 2008 ). They were also associated with metal-contaminated coastal sediments ( Lanzen et al, 2020 ). Metals in aquaculture sediments may originate from dietary additives in feed (enriched with zinc and iron; Maage et al, 2001 ) and anti-fouling coatings (including copper) to prevent biofouling of cage structures, although this practice in Canada is giving way to automated net washing systems that use high pressure and saltwater.…”

“…Pirellulaceae react sensitively to lower pH values, as are typical of near-field sites ( Usharani, 2019 ), and Planctomycetaceae dislike eutrophic conditions that can be found in closer vicinity to salmon cages ( Li et al, 2017 ). Accordingly, these bacterial taxon groups are common members of natural benthic bacterial communities ( Lanzen et al, 2020 ). Also, the obligate aerobe Flammeovirgaceae, which are chemoheterotrophic microbes and very common in marine environments ( Yoon et al, 2011 ), prefer the oxygenated, less organically enriched sediments of far-field sites.…”

Environmental DNA for biomonitoring

“…The ability of de novo prokaryotic bioindicators to predict multiple anthropogenic impacts on estuarine and coastal benthic communities is demonstrated by Lanzén, Mendibil, Borja, & Alonso-Sáez (2021). The authors compare their results to the traditional macrofauna-based indices and discuss various advantages of using microbial bioindicators as they are more sensitive to different abiotic pressures.…”

Grab what you can—an evaluation of spatial replication to decrease heterogeneity in sediment eDNA metabarcoding

“…Hence, for metazoan metabarcoding studies using e.g., the COI marker, a common strategy is to recover the animals from the sediment prior to DNA extraction (e.g., Atherton & Jondelius, 2020 ; Elbrecht & Leese, 2015 ; Faria et al, 2018 ; Fonseca et al, 2010 ; He, Sutherland & Abbott, 2021 ; Lejzerowicz et al, 2015 ). Conversely, when extracting eDNA directly from sediment, it is more common to use molecular markers that target microorganisms, such as the eukaryotic 18S rRNA or the prokaryotic 16S rRNA genes (e.g., Guardiola et al, 2016 ; Keeley, Wood & Pochon, 2018 ; Lanzén et al, 2016 ; Lanzén et al, 2020 ; Sinniger et al, 2016 ; Stoeck et al, 2018 ). In several recent sediment extract studies using multiple markers, however, ribosomal markers have been supplemented with e.g., COI with promising results ( Atienza et al, 2020 ; Laroche et al, 2020 ; Macher et al, 2018 ; Mauffrey & Cordier, 2020 ).…”