Recovery of 447 Eukaryotic bins reveals major challenges for Eukaryote genome reconstruction from metagenomes

Abstract

An estimated 8.7 million eukaryotic species exist on our planet. However, recent tools for taxonomic classification of eukaryotes only dispose of 734 reference genomes. As most Eukaryotic genomes are yet to be sequenced, the mechanisms underlying their contribution to different ecosystem processes remain untapped. Although approaches to recover Prokaryotic genomes have become common in genome biology, few studies have tackled the recovery of Eukaryotic genomes from metagenomes. This study assessed the reconstruction of Eukaryotic genomes using 215 metagenomes from diverse environments using the EukRep pipeline. We obtained 447 eukaryotic bins from 15 classes (e.g., Saccharomycetes, Sordariomycetes, and Mamiellophyceae) and 16 orders (e.g., Mamiellales, Saccharomycetales, and Hypocreales). More than 73% of the obtained eukaryotic bins were recovered from samples whose biomes were classified as host-associated, aquatic and anthropogenic terrestrial. However, only 93 bins showed taxonomic classification to (9 unique) genera and 17 bins to (6 unique) species. A total of 193 bins contained completeness and contamination measures. Average completeness and contamination were 44.64% (σ=27.41%) and 3.97% (σ=6.53%), respectively. Micromonas commoda was the most frequent taxa found while Saccharomyces cerevisiae presented the highest completeness, possibly resulting from a more significant number of reference genomes. However, mapping eukaryotic bins to the chromosomes of the reference genomes suggests that completeness measures should consider both single-copy genes and chromosome coverage. Recovering eukaryotic genomes will benefit significantly from long-read sequencing, intron removal after assembly, and improved reference genomes databases.

Identifying Eukaryotes and Factors Influencing Their Biogeography in Drinking Water Metagenomes

“…Despite the recent growing attention, eukaryotic-focused metagenomics is not as well established compared to the prokaryotic or viral counterparts, with studies reporting its complexity with current approaches. 22 Likely, the combination of multiple strategies, as done in EUKsemble, and the use of novel approaches, such as dedicated assembly workflows and the further exploitation of assembly graph information, 128 would enable improvements in eukaryotic-focused metagenomics. For example, a novel pipeline for eukaryotic gene calling combining several previous tools has shown improved performances with respect to previous methods, allowing its use for the analysis of large-scale data.…”

“…However, this comes with the drawback of reduced detection limits as compared to amplicon sequencing approaches . Further, metagenomic approaches can prove challenging when dealing with complex genomes such as the eukaryotic ones, especially for organisms with low relative abundances, , such as those expected for DWDS eukaryotes. In addition, eukaryotic-focused data analysis workflows are relatively less developed compared with those targeting prokaryotes or viruses and no extensive comparison among the different options has been conducted, limiting their use to study the DWDS microbiome.…”

Identifying eukaryotes in drinking water metagenomes and factors influencing their biogeography

“…Despite the recent growing attention eukaryotic-focused metagenomics is not as well established compared to the prokaryotic or viral counterparts, with studies reporting its complexity with current approaches 18 . Compared to prokaryotes and viruses, both the reference data and the option of tools available for eukaryotes is limited, further exacerbating the complexity of the reconstruction of their genomes.…”

“…In contrast, shotgun DNA sequencing (i.e., metagenomics) alleviate these limitations by direct sequencing of extracted genetic material collected in the sample and allowing genome and metabolic reconstructions of detected microorganism 15 ; this comes with the drawback of reduced detection limits as compared to amplicon sequencing approaches 16 . Further, metagenomic approaches can prove challenging when dealing with complex genomes such as the eukaryotic ones, especially in case of organisms with low relative abundances 17,18 . In addition, eukaryotic-focused data analysis workflows are relatively less developed in comparison with prokaryotic or viral ones and no extensive comparison among the different options has been conducted.…”