Comparison of Read-Based and Metagenome Assembled Genome-Based Approaches for Characterizing Microbial Taxonomic Profiles in Sulfate-Rich Wastewater Treatment Systems

Metagenomics has gained more attention due to the availability of sequencing technologies, providing an in-depth understanding of microbial communities in a specific environment. Bioinformatics serves as an important step to analyze such complex biological sequences for characterizing taxonomic and functional profiles of the investigated microbiota. Currently, there is no standard method for metagenomic analysis. It is always a question to select an appropriate approach to analyze the metagenome of interest. In addition, a large proportion of data could not be annotated and is often left out from the analysis, especially in an environment that is not well explored. Here we investigated two main strategies for microbial taxonomic profiling in anaerobic sulfate-rich wastewater treatment systems. The read-based approach annotates microbial taxonomy directly for individual reads while the Metagenome Assembled Genome (MAG)-based approach attempts to assemble sequences into genomes before taxonomic classification. Based on the same data pre-processing and reference database of the Genome Taxonomy Database (GTDB), the MAG-based approach utilized almost double the number of sequences compared to the read-based approach. Our results showed that the two approaches provided distinct taxonomic profiles. However, both approaches commonly detected important microbes in the anaerobic sulfate-rich wastewater samples such as those in the genera Desulfovibrio, Desulfomicrobium, and Methanothrix, which are sulfate-reducing bacteria and methanogens, respectively. Moreover, only about half of identified MAGs could be taxonomically classified at the species level. These MAGs would be worth further investigation leading to the discovery of novel species related to sulfate-rich anaerobic digestion.