Metaplasmidome-encoded functions of Siberian low-centered polygonal tundra soils

Abstract

Plasmids have the potential to transfer genetic traits within bacterial communities and thereby serve as a crucial tool for the rapid adaptation of bacteria in response to changing environmental conditions. Our knowledge of the environmental pool of plasmids (the metaplasmidome) and encoded functions is still limited due to a lack of sufficient extraction methods and tools for identifying and assembling plasmids from metagenomic datasets. Here, we present the first insights into the functional potential of the metaplasmidome of permafrost-affected active-layer soil-an environment with a relatively low biomass and seasonal freeze-thaw cycles that is strongly affected by global warming. The obtained results were compared with plasmid-derived sequences extracted from polar metagenomes. Metaplasmidomes from the Siberian active layer were enriched via cultivation, which resulted in a longer contig length as compared with plasmids that had been directly retrieved from the metagenomes of polar environments. The predicted hosts of plasmids belonged to Moraxellaceae, Pseudomonadaceae, Enterobacteriaceae, Pectobacteriaceae, Burkholderiaceae, and Firmicutes. Analysis of their genetic content revealed the presence of stress-response genes, including antibiotic and metal resistance determinants, as well as genes encoding protectants against the cold.

Fig. 1. Depiction of the applied methodology for analyzing the soil metaplasmidome.

Total DNA was extracted from the raw soil and enriched soil. The bacterial abundance was quantified by quantitative PCR (qPCR), and 16S rRNA genes were amplified and sequenced using the Illumina platform. The soil inoculum was dispersed via glass bead treatment. Plasmid DNA was extracted from the enrichment, and the metaplasmidome was sequenced.

Fig. 2. Heat map presenting taxonomic assignments to raw and enriched microbial communities as well as to potential plasmid hosts.

The LCA and best BLAST hit approaches were applied. Cut-off: >0.2%.

Fig. 3. Protein-based similarity network of replication initiation proteins retrieved from metagenome datasets and enrichment-culture metaplasmidomes.

Each node represents a single replication initiation protein (in total 133 proteins were analyzed), while edges correspond to the summarized quantity of reciprocally similar proteins. The colors denote the geography of the plasmids (red: Siberia; blue-green: Arctic; purple: Antarctica). The size of the node is proportional to the value of the betweenness centrality, which corresponds to how much a given node is in-between others, i.e., what is the number of the shortest paths that pass through the node when connecting two other nodes. In addition, nodes were color-shaded by their metagenome ID (Table 1).

Fig. 4. The number of genes from site S9 and S11 classified by COG functional categories.

Letters in square brackets refer to abbreviations for the COG functional categories. *1—posttranslational modification, protein turnover, chaperones, *2—secondary metabolites biosynthesis, transport, and catabolism.

Fig. 5. Stress-response-related gene distribution in enrichments and metagenomic datasets (threshold ident: 50.0%; qcov: 75.0%).

The bubble size denotes the relative abundance of genes related to stress response found in metaplasmidomes from Siberia (green), Arctic plasmids from metagenomes (light blue), and plasmids from Antarctic metagenomes (light yellow). The size of the bubbles defines the relative abundance of stress-related genes observed among plasmidomes from Siberia and those retrieved from the Arctic and Antarctic metagenomic datasets. *corresponds to datasets obtained from enrichment cultures; **corresponds to Samoylov Island metagenomes.