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Which technique, classical microscopy or 16S/18S metabarcoding, provides the most accurate representation of environmental variability in a multiuse reservoir for assessing phytoplankton communities?

Grant number: 23/13394-9
Support Opportunities:Scholarships in Brazil - Scientific Initiation
Start date: March 01, 2024
End date: February 28, 2025
Field of knowledge:Biological Sciences - Ecology
Principal Investigator:Hugo Miguel Preto de Morais Sarmento
Grantee:Eloisa Hummer
Host Institution: Centro de Ciências Biológicas e da Saúde (CCBS). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil

Abstract

Phytoplankton, composed of microscopic photosynthetic organisms, play fundamental roles in biogeochemical cycles and serve as the base of food webs. Phytoplankton populations respond to environmental changes, serving as indicators of water quality. Comparative studies have shown that the analysis of phytoplankton communities through the observation of morphological characters in an inverted optical microscope (the "classical" method) or metabarcoding through the sequencing of 18S amplicons (which capture eukaryotic organisms) and 16S amplicons (which capture prokaryotic organisms, as well as chloroplasts of autotrophic eukaryotes) can be used in the monitoring of aquatic ecosystems. However, these methods describe the environment differently, and determining which is most suitable for aquatic environmental monitoring remains a challenge. In this study, data obtained by microscopy and sequencing of 62 samples collected monthly by the Broa/Lobo Reservoir Microbial Observatory (BroaMO) will be used. The samples were analyzed using optical microscopy and sequencing of 18S and 16S rRNA amplicons. The dynamics in community composition will be studied and related to environmental variables through multivariate analyses. A comparison among the three methods will be performed to determine which method best predicts the dynamics of the aquatic environment and water quality. The hypothesis is that the molecular method will provide different information about species composition and abundance compared to microscopy and will explain environmental variations more effectively.

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