The automated assessment of water quality via saprobity index evaluation by next-generation sequencing of genetic markers of hydrobionts

The freshwater ecosystems are subject to contamination by various natural and anthropogenic pollutants, thus challenging the regular monitoring of the water quality. Besides detecting chemical pollutants, the bioindication allows complex evaluation of the water quality. Here we present an approach for water quality assessment via saprobity index calculation based on next-generation sequencing of the phylogenetic markers of hydrobionts. The developed expert system allows data processing by non-experts in bioinformatics. The approach has been successfully tested on Raifa Lake (Tatarstan Republic, Russia) by using 18S rRNA barcoding of zooplankton. Among 141 species of Crustacea, Copepoda, Rotifera, Ciliophora and Amoebozoa identified, 26 bioindicator species were found. The calculated Shannon’s and Simpson’s indices were 2.206 and 0.646, respectively. The calculated saprobity index was 1.57, indicating the water quality as beta-mesosaprobic (lightly polluted). These results closely match those of the manual evaluation by bioindication (Shannon 2.3, Simpson 0.631, S 1.6). Thus, the automatic data processing decreases time and simplifies the decision-making for water conservation measures. The approach can be applied to any type of freshwater reservoir and is compatible with any genetic marker, organism type, NGS platform and any biological metric of water quality. Our tool is freely available online at https://github.com/A-Sverdrup/water-expert-system.