Identification and Resolution of Microdiversity through Metagenomic Sequencing of Parallel Consortia.
William C NelsonYukari MaezatoYu-Wei WuMargaret F RomineStephen R LindemannPublished in: Applied and environmental microbiology (2015)
To gain a predictive understanding of the interspecies interactions within microbial communities that govern community function, the genomic complement of every member population must be determined. Although metagenomic sequencing has enabled the de novo reconstruction of some microbial genomes from environmental communities, microdiversity confounds current genome reconstruction techniques. To overcome this issue, we performed short-read metagenomic sequencing on parallel consortia, defined as consortia cultivated under the same conditions from the same natural community with overlapping species composition. The differences in species abundance between the two consortia allowed reconstruction of near-complete (at an estimated >85% of gene complement) genome sequences for 17 of the 20 detected member species. Two Halomonas spp. indistinguishable by amplicon analysis were found to be present within the community. In addition, comparison of metagenomic reads against the consensus scaffolds revealed within-species variation for one of the Halomonas populations, one of the Rhodobacteraceae populations, and the Rhizobiales population. Genomic comparison of these representative instances of inter- and intraspecies microdiversity suggests differences in functional potential that may result in the expression of distinct roles in the community. In addition, isolation and complete genome sequence determination of six member species allowed an investigation into the sensitivity and specificity of genome reconstruction processes, demonstrating robustness across a wide range of sequence coverage (9× to 2,700×) within the metagenomic data set.
Keyphrases
- antibiotic resistance genes
- genetic diversity
- mental health
- healthcare
- single cell
- genome wide
- microbial community
- poor prognosis
- electronic health record
- risk assessment
- single molecule
- machine learning
- gene expression
- human health
- dna methylation
- big data
- cross sectional
- mass spectrometry
- structural basis
- clinical evaluation