Metagenomics Strain Resolution on Assembly Graphs

Abstract

We introduce a novel bioinformatics pipeline, STrain Resolution ON assembly Graphs (STRONG), which identifies strains de novo, when multiple metagenome samples from the same community are available. STRONG performs coassembly, followed by binning into metagenome assembled genomes (MAGs), but uniquely it stores the coassembly graph prior to simplification of variants. This enables the subgraphs for individual single-copy core genes (SCGs) in each MAG to be extracted. It can then thread back reads from the samples to compute per sample coverages for the unitigs in these graphs. These graphs and their unitig coverages are then used in a Bayesian algorithm, BayesPaths, that determines the number of strains present, their sequences or haplotypes on the SCGs and their abundances in each of the samples. Our approach both avoids the ambiguities of read mapping and allows more of the information on co-occurrence of variants in reads to be utilised than if variants were treated independently, whilst at the same time exploiting the correlation of variants across samples that occurs when they are linked in the same strain. We compare STRONG to the current state of the art on synthetic communities and demonstrate that we can recover more strains, more accurately, and with a realistic estimate of uncertainty deriving from the variational Bayesian algorithm employed for the strain resolution. On a real anaerobic digestor time series we obtained strain-resolved SCGs for over 300 MAGs that for abundant community members match those observed from long Nanopore reads.

Generation of lineage-resolved complete metagenome-assembled genomes by precision phasing

“…Even though bins are often generalized to represent distinct microbial taxonomic units in a sample, they are rarely assumed to accurately represent true, genetically distinct microbial populations in a sample. This problem has been addressed by multiple studies 11,12 , and precise definitions for individual, highly resolved MAGs remain contextual to each study. Similar to one of these studies 11 , we focus on generating separate representative reference genomes for distinct microbial lineages within an individual metagenome, which we define as "lineage-resolved MAGs" 1,13 .…”

“…This problem has been addressed by multiple studies 11,12 , and precise definitions for individual, highly resolved MAGs remain contextual to each study. Similar to one of these studies 11 , we focus on generating separate representative reference genomes for distinct microbial lineages within an individual metagenome, which we define as "lineage-resolved MAGs" 1,13 . Combined with prior definitions of SCG quality metrics, we further extend the term to "lineage-resolved complete MAGs" for all such assemblies which have high degrees of SCG completeness (> 90%), low degrees of SCG redundancy (< 10%), and the separation of all observable variant lineages of microbial taxa into individual MAGs.…”

Automated strain separation in low-complexity metagenomes using long reads

“…DESMAN 8 managed to reconstruct haplotypes of core genes but not entire genomes. STRONG 9 addressed some of DESMAN limitations and is able to determine the number and sequence of strains in a metagenome-assembled genome by exploiting the co-assembly graph over the predicted single-copy-gene sequences and using a novel variational Bayesian algorithm. ConStrains 10 quantifies and reconstructs conspecific (relative to the same species) strain variations by mapping reads on a species-based marker gene set and providing a SNP-based model for each of the identified strains.…”

Space, time and microdiversity: towards a resolution revolution in microbiomics

“…For instance, in light of the increasing amount of sequencing data, graph-based approaches represent an opportunity to rethink the mainstream data structures encoding genomic information (Mustafa et al, 2017;Karasikov et al, 2020). As we continuously uncover microbial microdiversity, leading to a steady growth of intra-specific gene pools and information on genome-scale structural variations, graphs emerge as an inevitable alternative for representing microbial pan-genomes (Gautreau et al, 2020;Brown et al 2020;Quince et al, 2020).…”

“…As we continuously uncover microbial microdiversity, leading to a steady growth of intra‐specific gene pools and information on genome‐scale structural variations, graphs emerge as an inevitable alternative for representing microbial pan‐genomes (Gautreau et al ., 2020; Brown et al . 2020; Quince et al ., 2020).…”