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  • Title: Genetic diversity and composition of a plasmid metagenome from a wastewater treatment plant.
    Author: Schlüter A, Krause L, Szczepanowski R, Goesmann A, Pühler A.
    Journal: J Biotechnol; 2008 Aug 31; 136(1-2):65-76. PubMed ID: 18603322.
    Abstract:
    Plasmid metagenome nucleotide sequence data were recently obtained from wastewater treatment plant (WWTP) bacteria with reduced susceptibility to selected antimicrobial drugs by applying the ultrafast 454-sequencing technology. The sequence dataset comprising 36,071,493 bases (346,427 reads with an average read length of 104 bases) was analysed for genetic diversity and composition by using a newly developed bioinformatic pipeline based on assignment of environmental gene tags (EGTs) to protein families stored in the Pfam database. Short amino acid sequences deduced from the plasmid metagenome sequence reads were compared to profile hidden Markov models underlying Pfam. Obtained matches evidenced that many reads represent genes having predicted functions in plasmid replication, stability and plasmid mobility which indicates that WWTP bacteria harbour genetically stabilised and mobile plasmids. Moreover, the data confirm a high diversity of plasmids residing in WWTP bacteria. The mobile organic peroxide resistance plasmid pMAC from Acinetobacter baumannii was identified as reference plasmid for the most abundant replication module type in the sequenced sample. Accessory plasmid modules encode different transposons, insertion sequences, integrons, resistance and virulence determinants. Most of the matches to Transposase protein families were identified for transposases similar to the one of the chromate resistance transposon Tn5719. Noticeable are hits to beta-lactamase protein families which suggests that plasmids from WWTP bacteria encode different enzymes possessing beta-lactam-hydrolysing activity. Some of the sequence reads correspond to antibiotic resistance genes that were only recently identified in clinical isolates of human pathogens. EGT analysis thus proofed to be a very valuable method to explore genetic diversity and composition of the present plasmid metagenome dataset.
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