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Bessarab, I.

Publications and source records attributed to Bessarab, I..

2 recordsLinked to original sources

Improving recovery of member genomes from enrichment reactor microbial communities using MinION--based long read metagenomics

New long read sequencing technologies offer huge potential for effective recovery of complete, closed genomes. While much progress has been made on cultured isolates, the ability of these methods to recover genomes of member taxa in complex microbial communities is less clear. Here we examine the ability of long read data to recover genomes from enrichment reactor metagenomes. Such modified communities offer a moderate level of complexity compared to the source communities and so are realistic, yet tractable, systems to use for this problem. We sampled an enrichment bioreactor designed to target anaerobic ammonium-oxidising bacteria (AnAOB) and sequenced genomic DNA using both short read (Illumina 301bp PE) and long read data (MinION Mk1B) from the same extraction aliquot. The community contained 23 members, of which 16 had genome bins defined from an assembly of the short read data. Two distinct AnAOB species from genus Candidatus Brocadia were present and had complete genomes, of which one was the most abundant member species in the community. We can recover a 4Mb genome, in 2 contigs, of long read assembled sequence that is unambiguously associated with the most abundant AnAOB member genome. We conclude that obtaining near closed, complete genomes of members of low-medium microbial communities using MinION long read sequence is feasible.

genomics

MEGAN-LR: New algorithms allow accurate binning and easy interactive exploration of metagenomic long reads and contigs

BackgroundThere are numerous computational tools for taxonomic or functional analysis of microbiome samples, optimized to run on hundreds of millions of short, high quality sequencing reads. Programs such as MEGAN allow the user to interactively navigate these large datasets. Long read sequencing technologies continue to improve and produce increasing numbers of longer reads (of varying lengths in the range of 10k-1M bps, say), but of low quality. There is an increasing interest in using long reads in microbiome sequencing and there is a need to adapt short read tools to long read datasets.\n\nMethodsWe describe a new LCA-based algorithm for taxonomic binning, and an interval-tree based algorithm for functional binning, that are explicitly designed for long reads and assembled contigs. We provide a new interactive tool for investigating the alignment of long reads against reference sequences. For taxonomic and functional binning, we propose to use LAST to compare long reads against the NCBI-nr protein reference database so as to obtain frame-shift aware alignments, and then to process the results using our new methods.\n\nResultsAll presented methods are implemented in the open source edition of MEGAN and we refer to this new extension as MEGAN-LR (MEGAN long read). We evaluate the LAST+MEGAN-LR approach in a simulation study, and on a number of mock community datasets consisting of Nanopore reads, PacBio reads and assembled PacBio reads. We also illustrate the practical application on a Nanopore dataset that we sequenced from an anammox bio-rector community.

bioinformatics