312 research outputs found

    Gauge your phage: benchmarking of bacteriophage identification tools in metagenomic sequencing data

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    BackgroundThe prediction of bacteriophage sequences in metagenomic datasets has become a topic of considerable interest, leading to the development of many novel bioinformatic tools. A comparative analysis of ten state-of-the-art phage identification tools was performed to inform their usage in microbiome research.MethodsArtificial contigs generated from complete RefSeq genomes representing phages, plasmids, and chromosomes, and a previously sequenced mock community containing four phage species, were used to evaluate the precision, recall, and F1 scores of the tools. We also generated a dataset of randomly shuffled sequences to quantify false-positive calls. In addition, a set of previously simulated viromes was used to assess diversity bias in each tool’s output.ResultsVIBRANT and VirSorter2 achieved the highest F1 scores (0.93) in the RefSeq artificial contigs dataset, with several other tools also performing well. Kraken2 had the highest F1 score (0.86) in the mock community benchmark by a large margin (0.3 higher than DeepVirFinder in second place), mainly due to its high precision (0.96). Generally, k-mer-based tools performed better than reference similarity tools and gene-based methods. Several tools, most notably PPR-Meta, called a high number of false positives in the randomly shuffled sequences. When analysing the diversity of the genomes that each tool predicted from a virome set, most tools produced a viral genome set that had similar alpha- and beta-diversity patterns to the original population, with Seeker being a notable exception.ConclusionsThis study provides key metrics used to assess performance of phage detection tools, offers a framework for further comparison of additional viral discovery tools, and discusses optimal strategies for using these tools. We highlight that the choice of tool for identification of phages in metagenomic datasets, as well as their parameters, can bias the results and provide pointers for different use case scenarios. We have also made our benchmarking dataset available for download in order to facilitate future comparisons of phage identification tools

    Noise reduction strategies in metagenomic chromosome confirmation capture to link antibiotic resistance genes to microbial hosts

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    The gut microbiota is a reservoir for antimicrobial resistance genes (ARGs). With current sequencing methods, it is difficult to assign ARGs to their microbial hosts, particularly if these ARGs are located on plasmids. Metagenomic chromosome conformation capture approaches (meta3C and Hi-C) have recently been developed to link bacterial genes to phylogenetic markers, thus potentially allowing the assignment of ARGs to their hosts on a microbiome-wide scale. Here, we generated a meta3C dataset of a human stool sample and used previously published meta3C and Hi-C datasets to investigate bacterial hosts of ARGs in the human gut microbiome. Sequence reads mapping to repetitive elements were found to cause problematic noise in, and may importantly skew interpretation of, meta3C and Hi-C data. We provide a strategy to improve the signal-to-noise ratio by discarding reads that map to insertion sequence elements and to the end of contigs. We also show the importance of using spike-in controls to quantify whether the cross-linking step in meta3C and Hi-C protocols has been successful. After filtering to remove artefactual links, 87 ARGs were assigned to their bacterial hosts across all datasets, including 27 ARGs in the meta3C dataset we generated. We show that commensal gut bacteria are an important reservoir for ARGs, with genes coding for aminoglycoside and tetracycline resistance being widespread in anaerobic commensals of the human gut

    Carbon induced extreme ultraviolet (EUV) reflectance loss characterized using visible-light ellipsometry

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    Carbon deposition on extreme ultraviolet (EUV) optics was observed due to photon-induced dissociation of hydrocarbons in a EUV lithography environment. The reflectance loss of the multilayer mirror is determined by the carbon layer thickness and density. To study the influence of various forms of carbon, EUV-induced carbon, hot filament and e-beam evaporated carbon were deposited on EUV multilayer mirrors. Spectroscopic ellipsometry was used to determine the carbon layer thickness and the optical constants ranging from ultraviolet to near infrared. The carbon density (and thus reflectance loss) was determined from the optical constants using both Bruggeman's effective medium approximation and the Clausius–Mosotti equation. Both approaches result in a similar EUV reflectance loss, with an accuracy of about 4%. The application of this process to ultrathin carbon films is further discussed

    Integration of vanHAX downstream of a ribosomal RNA operon restores vancomycin resistance in a susceptible Enterococcus faecium strain

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    During the genomic characterisation of Enterococcus faecium strains (n = 39) collected in a haematology ward, we identified an isolate (OI25), which contained vanA-type vancomycin resistance genes but was phenotypically susceptible to vancomycin. OI25 could revert to resistance when cultured in the presence of vancomycin and was thus considered to be vancomycin-variable. Long-read sequencing was used to identify structural variations within the vancomycin resistance region of OI25 and to uncover its resistance reversion mechanism. We found that OI25 has a reduced ability to positively regulate expression of the vanHAX genes in the presence of vancomycin, which was associated with the insertion of an IS6-family element within the promoter region and the first 50 bp of the vanR gene. The vancomycin-resistant revertant isolates constitutively expressed vanHAX genes at levels up to 36,000-fold greater than OI25 via co-transcription with a ribosomal RNA operon. The vancomycin-resistant revertants did not exhibit a significant growth defect. During VRE outbreaks, attention should be paid to contemporaneous vancomycin-susceptible strains as these may carry silent vancomycin resistance genes that can be activated through genomic rearrangements
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