Identifying and tracking mobile elements in evolving compost communities yields insights into the nanobiome.
Bram van DijkPauline BuffardAndrew D FarrFranz GiersdorfJeroen MeijerBas E DutilhPaul B RaineyPublished in: ISME communications (2023)
Microbial evolution is driven by rapid changes in gene content mediated by horizontal gene transfer (HGT). While mobile genetic elements (MGEs) are important drivers of gene flux, the nanobiome-the zoo of Darwinian replicators that depend on microbial hosts-remains poorly characterised. New approaches are necessary to increase our understanding beyond MGEs shaping individual populations, towards their impacts on complex microbial communities. A bioinformatic pipeline (xenoseq) was developed to cross-compare metagenomic samples from microbial consortia evolving in parallel, aimed at identifying MGE dissemination, which was applied to compost communities which underwent periodic mixing of MGEs. We show that xenoseq can distinguish movement of MGEs from demographic changes in community composition that otherwise confounds identification, and furthermore demonstrate the discovery of various unexpected entities. Of particular interest was a nanobacterium of the candidate phylum radiation (CPR) which is closely related to a species identified in groundwater ecosystems (Candidatus Saccharibacterium), and appears to have a parasitic lifestyle. We also highlight another prolific mobile element, a 313 kb plasmid hosted by a Cellvibrio lineage. The host was predicted to be capable of nitrogen fixation, and acquisition of the plasmid coincides with increased ammonia production. Taken together, our data show that new experimental strategies combined with bioinformatic analyses of metagenomic data stand to provide insight into the nanobiome as a driver of microbial community evolution.
Keyphrases
- microbial community
- antibiotic resistance genes
- genome wide
- copy number
- escherichia coli
- genome wide identification
- electronic health record
- cardiovascular disease
- small molecule
- physical activity
- metabolic syndrome
- healthcare
- mental health
- minimally invasive
- dna methylation
- weight loss
- heavy metals
- sewage sludge
- municipal solid waste
- high throughput
- radiation therapy
- machine learning
- transcription factor
- artificial intelligence
- genome wide analysis
- room temperature