The Reliability of Metagenome-Assembled Genomes (MAGs) in Representing Natural Populations: Insights from Comparing MAGs against Isolate Genomes Derived from the Same Fecal Sample

Abstract

The recovery of metagenome-assembled genomes (MAGs) from metagenomic data has recently become a common task for microbial studies. The strengths and limitations of the underlying bioinformatics algorithms are well appreciated by now based on performance tests with mock datasets of known composition. However, these mock datasets do not capture the complexity and diversity often observed within natural populations, since their construction typically relies on only a single genome of a given organism. Further, it remains unclear if MAGs can recover population variable (e.g., shared by >10% but <90% of the members of the population) as efficiently as core genes (e.g., shared by >90% of the members). To address these issues, we compared the gene variability of pathogenic Escherichia coli isolates from eight diarrheal samples, for which the isolate was the causative agent, against their corresponding MAGs recovered from the companion metagenomic dataset. Our analysis revealed that MAGs with completeness estimates near 95% captured only 77% of the population core genes and 50% of the variable genes, on average. Further, about 5% of the genes of these MAG were conservatively identified as missing in the isolate and were of different (non-Enterobacteriaceae) taxonomic origin, suggesting errors at the genome binning step, even though contamination estimates based on commonly used pipelines were only 1.5%. Therefore, the quality of MAGs may oftentimes be worse than estimated, and we offer examples of how to recognize and improve such MAGs to sufficient quality by -for instance- employing only contigs longer than 1,000bp for binning. IMPORTANCE Metagenome assembly and recovery of metagenome-assembled genomes (MAGs) have recently become common tasks for microbiome studies across environmental and clinical settings. However, to what extent MAGs can capture the genes of the population they represent remains speculative. Current approaches to evaluate MAG quality are limited to the recovery and copy number of universal, housekeeping genes but these genes represent a small fraction of the total genome, leaving the majority of the genome essentially inaccessible. If MAG quality in reality is lower than these approaches would estimate, this could have dramatic consequences for all downstream analyses and interpretations. In this study, we evaluated this issue using a novel approach that employs comparisons of MAGs to isolate genomes derived from the same samples. Further, our samples originated from a diarrhea case-control study, and thus our results are relevant for recovering the virulence factors of pathogens from metagenomic datasets.

Nanopore adaptive sampling: a tool for enrichment of low abundance species in metagenomic samples

“…Such approaches have been applied widely including in the assembly of pathogen genomes from clinical samples [ 2 ], bacterial genomes and gene clusters from the human gut [ 3 ], the rumen microbiome of cattle [ 4 ], and a project which assembled tens of thousands of MAGs by re-analysing over 10,000 previously collected metagenomes [ 5 ]. Nevertheless, despite these successes, some doubts remain about the reliability of MAG approaches when faced with complex populations [ 6 ].…”

Adaptive differentiation and rapid evolution of a soil bacterium along a climate gradient

“…While progress has been made in defining microbial species ( 21 – 23 ), the high genetic heterogeneity within diverse microbial communities, such as soils, convolute the boundaries of the fine-scale patterns of genetic diversity within microbial taxonomic units ( 12 ). For instance, metagenome-assembled genomes are often composed of a composite of strains forming a large population of mosaic genomes ( 24 ) that may not fully capture the diversity of the local population ( 25 ). As such, it remains difficult to study evolutionary rates within microbial communities (however, see refs.…”

A genomic perspective across Earth’s microbiomes reveals that genome size in Archaea and Bacteria is linked to ecosystem type and trophic strategy

“…Aquatic MAGs average 3.1 Mb, host-associated MAGs average 3.0 Mb, and terrestrial MAGs average 3.7 Mb (Figure 1A). It is known that MAG assembly might discriminate against ribosomal RNAs, transfer RNAs, mobile element functions and genes of unknown function (23,24), and also that completeness estimations can be underestimated for streamlined genomes (25). For the 540 mOTUs with MAGs and isolate genomes (Figure 1C), we found that MAGs were estimated on average 3.7% smaller than isolate genomes (Figure S1).…”