No abstract

Antimicrobial resistance is a serious threat to global public health, but little is known about the effects of microbial control on the microbiota and its associated resistome. Here we compare the microbiota present on surfaces of clinical settings with other built environments. Using state-of-the-art metagenomics approaches and genome and plasmid reconstruction, we show that increased confinement and cleaning is associated with a loss of microbial diversity and a shift from Gram-positive bacteria, such as Actinobacteria and Firmicutes , to Gram-negative such as Proteobacteria . Moreover, the microbiome of highly maintained built environments has a different resistome when compared to other built environments, as well as a higher diversity in resistance genes. Our results highlight that the loss of microbial diversity correlates with an increase in resistance, and the need for implementing strategies to restore bacterial diversity in certain built environments.

MotivationPlasmids and other mobile elements are central contributors to microbial evolution and genome innovation. Recently, they have been found to have important roles in antibiotic resistance and in affecting production of metabolites used in industrial and agricultural applications. However, their characterization through deep sequencing remains challenging, in spite of rapid drops in cost and throughput increases for sequencing. Here, we attempt to ameliorate this situation by introducing a new circular element assembly algorithm, leveraging assembly graphs provided by a conventional de novo assembler and alignments of paired-end reads to assemble cyclic sequences likely to be plasmids, phages and other circular elements.ResultsWe introduce Recycler, the first tool that can extract complete circular contigs from sequence data of isolate microbial genomes, plasmidome and metagenome sequence data. We show that Recycler greatly increases the number of true plasmids recovered relative to other approaches while remaining highly accurate. We demonstrate this trend via simulations of plasmidomes, comparisons of predictions with reference data for isolate samples, and assessments of annotation accuracy on metagenome data. In addition, we provide validation by DNA amplification of 77 plasmids predicted by Recycler from the different sequenced samples in which Recycler showed mean accuracy of 89% across all data types—isolate, microbiome and plasmidome.Availability and ImplementationRecycler is available at http://github.com/Shamir-Lab/RecyclerSupplementary information Supplementary data are available at Bioinformatics online.

Many proteins require the assistance of molecular chaperones in order to fold efficiently. Chaperones are known to mask the effects of mutations that induce misfolding because they can compensate for the deficiency in spontaneous folding. One of the best studied chaperones is the eubacterial GroEL/GroES system. In Escherichia coli, three classes of proteins have been distinguished based on their degree of dependency on GroEL for folding: 1) those that do not require GroEL, 2) those that require GroEL in a temperature-dependent manner, and 3) those that obligately require GroEL for proper folding. The buffering effects of GroEL have so far been observed in experimental regimens, but their effect on genomes during evolution has not been examined. Using 446 sequenced proteobacterial genomes, we have compared the frequency of amino acid replacements among orthologs of 236 proteins corresponding to the three categories of GroEL dependency determined for E. coli. Evolutionary rates are significantly correlated with GroEL dependency upon folding with GroEL dependency class accounting for up to 84% of the variation in amino acid substitution rates. Greater GroEL dependency entails increased evolutionary rates with GroEL obligatory proteins (Class III) evolving on average up to 15% faster than GroEL partially dependent proteins (Class II) and 35% faster than GroEL-independent proteins (Class I). Moreover, GroEL dependency class correlations are strictly conserved throughout all proteobacteria surveyed, as is a significant correlation between folding class and codon bias. The results suggest that during evolution, GroEL-dependent folding increases evolutionary rate by buffering the deleterious effects of misfolding-related mutations.

Motivation: Plasmids and other mobile elements are central contributors to microbial evolution and genome innovation. Recently, they have been found to have important roles in antibiotic resistance and in affecting production of metabolites used in industrial and agricultural applications. However, their characterization through deep sequencing remains challenging, in spite of rapid drops in cost and throughput increases for sequencing. Here, we attempt to ameliorate this situation by introducing a new circular element assembly algorithm, leveraging assembly graphs provided by a conventional de novo assembler and alignments of paired-end reads to assemble cyclic sequences likely to be plasmids, phages and other circular elements. Results: We introduce Recycler, the first tool that can extract complete circular contigs from sequence data of isolate microbial genomes, plasmidome and metagenome sequence data. We show that Recycler greatly increases the number of true plasmids recovered relative to other approaches while remaining highly accurate. We demonstrate this trend via simulations of plasmidomes, comparisons of predictions with reference data for isolate samples, and assessments of annotation accuracy on metagenome data. In addition, we provide validation by DNA amplification of 77 plasmids predicted by Recycler from the different sequenced samples in which Recycler showed mean accuracy of 89% across all data types-isolate, microbiome and plasmidome.