Plasmids Identified in Air Metagenomes

Plasmids were predicted for each assembling by using scripts describing in-depth in Hilpert et al. (Hilpert et al., 2021; Hennequin et al., 2022) and available in github website (https://github.com/meb-team/PlasSuite/). Briefly, contigs were analyzed using both reference-based and reference-free approaches. The databases employed included those for chromosomes (archaea and bacteria) and plasmids from NCBI, as well as the MOB-suite tool (Robertson and Nash, 2018) , SILVA (Quast et al., 2013) and phylogenetic markers harbored by chromosomes (Wu et al., 2013). Two reference-free methods were applied to contigs that were not affiliated with chromosomes (discarded) or plasmids (retained in the first step): PlasFlow (Krawczyk et al., 2018) and PlasClass (Pellow et al., 2020). Viruses were removed by using viralVerify (https://github.com/ablab/viralVerify) (Antipov et al., 2020) that provides in parallel provide plasmid/non-plasmid classification.  The database built for this purpose is available at this address https://github.com/meb-team/PlasSuite/?tab=readme-ov-file#1-prepare-or-download-your-databases  Eukaryotes contaminants were removed by aligning the sequences against NT databases and human chromosomes (GRCh38) with minimap2 with -x asm5 option (Li, 2018). Contigs mapping with an identity of 95% and a coverage of 80% were removed.  the final plasmidome set was clustered by mmseqs (Mirdita, Steinegger and Söding, 2019) with 80% of coverage and 90% of identity (--min-seq-id 0.90 -c 0.8 --cov-mode 1 --cluster-mode 2 --alignment-mode 3 --kmer-per-seq-scale 0.2).