Time-series drinking water metagenomes: Assemblies & MAGs

Reconstructing microbial genomes from metagenomic short-read data can be
challenging due to the unknown and uneven complexity of microbial
communities. This complexity encompasses highly diverse populations which
often includes strain variants. Reconstructing high-quality genomes is a
crucial part of the metagenomic workflow as subsequent ecological and
metabolic inferences depend on their accuracy, quality and completeness.
In contrast to microbial communities in other ecosystems, there has been
no systematic assessment of genome-centric metagenomic workflows for
drinking water microbiomes. In this study, we assessed the
performance of a combination of assembly and binning strategies for
time-series drinking water metagenomes that were collected over 6 months.
The goal of this study was to identify the combination of assembly and
binning approaches that results in high quality and quantity
metagenome-assembled genomes (MAGs), representing most of the sequenced
metagenome. Our findings suggest that
the metaSPAdes co-assembly strategies had the
best performance as they resulted in larger and less fragmented assemblies
with at least 85% of the sequence data mapping to contigs greater than
1kbp. Furthermore, a combination of metaSPAdes co-assembly strategies and
MetaBAT2 produced the highest number of medium-quality MAGs while
capturing at least 70% of the metagenomes based on read recruitment.
Utilizing different assembly/binning approaches also assist in the
reconstruction of unique MAGs from closely related species that would have
otherwise collapsed into a single MAG using a single workflow. Overall,
our study suggests that leveraging multiple binning approaches with
different metaSPAdes co-assembly strategies may be required to maximize
the recovery of good-quality MAGs.