<figure><img src="image_1.png" /></figure>

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# Environmental DNA approach to assess phytoplankton communities in lake environments

Laurine Viollaz, Frédéric Rimet, Isabelle Domaizon, Christophe Laplace-Treyture, Benjamin Alric

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Laurine Viollaz, Frédéric Rimet, Isabelle Domaizon, Christophe Laplace-Treyture, Benjamin Alric. Environmental DNA approach to assess phytoplankton communities in lake environments. SFE2 Lyon, Oct 2024, Lyon, France. **hal-04814851**

HAL Id: hal-04814851

https://hal.science/hal-04814851v1

Submitted on 2 Dec 2024

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# Environmental DNA approach to assess phytoplankton communities in lake environments

Laurine Viollaz¹, Frédéric Rimet¹,², Isabelle Domaizon¹,², Christophe Laplace-Treyture²,³, and Benjamin Alric¹,²

¹UMR CARRTEL – INRAE, Université Savoie Mont Blanc, 75bis av. de Corzent – CS 50511, FR – 74203 Thonon-les-Bains cedex, France

²ECLA – Pôle R&D Ecosystèmes Lacustres, France

³UR EABX – INRAE, 50 av. de Verdun, FR – 33612 cedex, France

Aquatic ecosystems play an important socio-economic role by providing many services such as water supplies, socio-cultural services and regulation services which can be altered by human activities. The Water Framework Directive (WFD) requires the estimation of the ecosystems ecological status in order to assess the level of anthropogenic impacts in these environments. According to the WFD, assessing of ecological quality of lakes can be done using Quality Biological Elements (QBEs) such as phytoplankton to develop biotic indexes based on morphological identification (Fig. 1a). New Indicators have been successfully developed to assess the ecological quality of lakes based on environmental DNA (eDNA; Fig. 1b).

<figure><img src="image_2.png" /><figcaption>**Figure 1:** Assessment of ecological status of lakes according to the Water Framework Directive.</figcaption></figure>

<figure><img src="image_3.png" /><figcaption>**Figure 2:** Map of sampling sites (year 2022) carried out in France. Each site is represented by red dots. The different Water Agencies are represented by AG (Adour-Garonne), RM (Rhin-Meuse), RMC (Rhône-Méditérannée-Corse), LB (Loire-Bretagne), AP (Artois-Picardie) and SN (Seine-Normandie).</figcaption></figure>

<figure><img src="image_4.png" /></figure>

## For this study, we addressed the following questions :

* Q1 : Why working with the taxonomy-free approach ?

* Q2 : Which pollution gradient can be highlighted ?

* Q3 : Development of the taxonomy-free index

<figure><img src="image_5.png" /><figcaption>**Figure 3:** Percentage of taxonomic assignment of ASVs from kingdom to the specie taxa</figcaption></figure>

<caption>**Figure 4:** Principal Components Analyses on environmental variables. Dots correspond to samples. PO4: orthophosphate, NO3: nitrates, NO2: nitrites, NH4 : ammonium.</caption>

The amount of non-assigned ASV increased from the phylum to species level (40% of increasing). This can be explained by a lack of assigned sequences in reference libraries.

<figure><img src="image_6.png" /></figure>

## Conclusion

* Q1 : the taxonomy-free approach allowed us to take in consideration the entire phytoplankton community, avoiding the gaps of Phytool_V2 reference barcoding library.

* Q2 : a reference nutrients gradient (mainly represented by phosphorus) has been identified and is mostly representative of urban pollution in lakes.

* Q3 : the biotic taxonomy-free index has been successfully developed and can assess efficiently the ecological quality of lakes.

There is a significant relationship between ASV index and environmental gradient (PC1). However, there are over/under-estimation of ecological quality at the extreme values of the gradient (highest and lowest nutrients level).

<figure><img src="image_7.png" /><figcaption>**Figure 5:** Relationship between PC1 and the taxonomy-free index. The blue line corresponds to the linear model. The black line corresponds to the line 1:1. Samples are represented by black dots.</figcaption></figure>

**References** : Canino, A., Bouchez, A., Laplace-Treyture, C., et al. Phytool, a ShinyApp to homogenise taxonomy of freshwater microalgae from DNA barcodes and microscopic observations. Metabarcoding and Metagenomics, 5. 2021; 2039-2205. doi: 10.3897/mbmg.5.74096. Nicolosi Gelis MM, Canino A, Bouchez A, et al. Assessing the relevance of DNA metabarcoding compared to morphological identification for lake phytoplankton 30 monitoring. Sci Total Environ. 2024; 914:169774. doi: 10.1016/j.scitotenv.2023.169774.

**Acknowledgements** : Water Agencies and private laboratories for the sampling of each site required for the analysis.