Identificação e quantificação de cianobactérias presentes em águas doces superficiais por FTIR supervisionada por métodos moleculares.

Abstract

Harmful cyanobacteria blooms are becoming common due climate changes and anthropogenic impacts. The HABs cause severe damages to the environment and to different organisms, including humans and domestic animals. For this reason, it is important to know the harmful cyanobacteria in different biomes to monitor and mitigate the impacts in the environment. The identification of microorganism is still dependent of expensive and time demanding technologies. This study aims to evaluate the use of ATR-FTIR and chemometrics supervised by molecular methods to determine harmful cyanobacteria from raw biomass and correlate the data with physical-chemical parameters of sampling points located in Rio Pardo Valley, RS, Brazil. Physical-chemical parameters were measured. The spectra data, taxa identified, and physical-chemical parameters were analyzed using PCA and OPLS methods. Metagenomic amplicons were analyzed using Dada2 and Phyloseq packages, and taxa determination were performed using CyanoSeq database. A total of 12 genera of harmful cyanobacteria were identified in 14 locations. The genera Sphaerospermopsis had higher abundance in SP14 location being related to the aluminum, iron, and total nitrogen levels. Dolichospermum and Wollea genera were correlated to the concentration of total phosphorus and sodium. The Planktothricoides genera is strongly related to SP01 sampling point due its high relative abundance of 95,15%. All ATR-FTIR/OPLS models resulted in adequate performance for the prediction of abundances and identification from the 12 genera of harmful cyanobacteria investigated by metabarcoding of amplicons from raw biomass. Considering the maximum number of 6 latent variables, the model reached RMSECV values between 1,3.10-5 - 5.3.10-4 with R2 values above 0.99999.