Long-read Oxford Nanopore sequencing has democratized microbial genome sequencing and enables the recovery of highly contiguous microbial genomes from isolates or metagenomes. However, to obtain near-finished genomes it has been necessary to include short-read polishing to correct insertions and deletions derived from homopolymer regions. Here, we show that Oxford Nanopore R10.4 can be used to generate near-finished microbial genomes from isolates or metagenomes without short-read or reference polishing.
New lineages of SARS-CoV-2 are of potential concern due to higher transmissibility, risk of severe outcomes, and/or escape from neutralizing antibodies. Lineage B.1.1.7 (the Alpha variant) became dominant in early 2021, but the association between transmissibility and risk factors, such as age of primary case and viral load remains poorly understood. Here, we used comprehensive administrative data from Denmark, comprising the full population (January 11 to February 7, 2021), to estimate household transmissibility. This study included 5,241 households with primary cases; 808 were infected with lineage B.1.1.7 and 4,433 with other lineages. Here, we report an attack rate of 38% in households with a primary case infected with B.1.1.7 and 27% in households with other lineages. Primary cases infected with B.1.1.7 had an increased transmissibility of 1.5–1.7 times that of primary cases infected with other lineages. The increased transmissibility of B.1.1.7 was multiplicative across age and viral load.
Long-read Oxford Nanopore sequencing has democratized microbial genome sequencing and enables the recovery of highly contiguous microbial genomes from isolates or metagenomes. However, to obtain near-perfect genomes it has been necessary to include short-read polishing to correct insertions and deletions derived from homopolymer regions. Here, we show that Oxford Nanopore R10.4 can be used to generate near-perfect microbial genomes from isolates or metagenomes without shortread or reference polishing.
Motivation
Despite recent advancements in sequencing technologies and assembly methods, obtaining high-quality microbial genomes from metagenomic samples is still not a trivial task. Current metagenomic binners do not take full advantage of assembly graphs and are not optimized for long-read assemblies. Deep graph learning algorithms have been proposed in other fields to deal with complex graph data structures. The graph structure generated during the assembly process could be integrated with contig features to obtain better bins with deep learning.
Results
We propose GraphMB, which uses graph neural networks to incorporate the assembly graph into the binning process. We test GraphMB on long-read datasets of different complexities, and compare the performance with other binners in terms of the number of High Quality (HQ) genome bins obtained. With our approach, we were able to obtain unique bins on all real datasets, and obtain more bins on most datasets. In particular, we obtained on average 17.5% more HQ bins when compared to state-of-the-art binners and 13.7% when aggregating the results of our binner with the others. These results indicate that a deep learning model can integrate contig-specific and graph-structure information to improve metagenomic binning.
Availability
GraphMB is available from https://github.com/MicrobialDarkMatter/GraphMB
Cable bacteria of the Desulfobulbaceae family are centimeter-long filamentous bacteria, which are capable of conducting long-distance electron transfer. Currently, all cable bacteria are classified into two candidate genera: Candidatus Electronema, typically found in freshwater environments, and Candidatus Electrothrix, typically found in saltwater environments. This taxonomic framework is based on both 16S rRNA gene sequences and metagenome-assembled genome (MAG) phylogenies. However, most of the currently available MAGs are highly fragmented, incomplete, and thus likely miss key genes essential for deciphering the physiology of cable bacteria. Also, a closed, circular genome of cable bacteria has not been published yet. To address this, we performed Nanopore long-read and Illumina short-read shotgun sequencing of selected environmental samples and a single-strain enrichment of Ca. Electronema aureum. We recovered multiple cable bacteria MAGs, including two circular and one single-contig. Phylogenomic analysis, also confirmed by 16S rRNA gene-based phylogeny, classified one circular MAG and the single-contig MAG as novel species of cable bacteria, which we propose to name Ca. Electronema halotolerans and Ca. Electrothrix laxa, respectively. The Ca. Electronema halotolerans, despite belonging to the previously recognized freshwater genus of cable bacteria, was retrieved from brackish-water sediment. Metabolic predictions showed several adaptations to a high salinity environment, similar to the “saltwater” Ca. Electrothrix species, indicating how Ca. Electronema halotolerans may be the evolutionary link between marine and freshwater cable bacteria lineages.
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