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Fulltext Contaminating viral sequences in high-throughput sequencing viromics: a linkage study of 700 sequencing libraries

Asplund M, Kjartansdóttir KR, Mollerup S, Vinner L, Fridholm H, Herrera JAR, et al.

Clin Microbiol Infect, 2019 Oct;25(10):1277-1285.
PMID: 31059795 DOI: 10.1016/j.cmi.2019.04.028

OBJECTIVES: Sample preparation for high-throughput sequencing (HTS) includes treatment with various laboratory components, potentially carrying viral nucleic acids, the extent of which has not been thoroughly investigated. Our aim was to systematically examine a diverse repertoire of laboratory components used to prepare samples for HTS in order to identify contaminating viral sequences.
METHODS: A total of 322 samples of mainly human origin were analysed using eight protocols, applying a wide variety of laboratory components. Several samples (60% of human specimens) were processed using different protocols. In total, 712 sequencing libraries were investigated for viral sequence contamination.
RESULTS: Among sequences showing similarity to viruses, 493 were significantly associated with the use of laboratory components. Each of these viral sequences had sporadic appearance, only being identified in a subset of the samples treated with the linked laboratory component, and some were not identified in the non-template control samples. Remarkably, more than 65% of all viral sequences identified were within viral clusters linked to the use of laboratory components.
CONCLUSIONS: We show that high prevalence of contaminating viral sequences can be expected in HTS-based virome data and provide an extensive list of novel contaminating viral sequences that can be used for evaluation of viral findings in future virome and metagenome studies. Moreover, we show that detection can be problematic due to stochastic appearance and limited non-template controls. Although the exact origin of these viral sequences requires further research, our results support laboratory-component-linked viral sequence contamination of both biological and synthetic origin.
Fulltext Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage

Hendriksen RS, Munk P, Njage P, van Bunnik B, McNally L, Lukjancenko O, et al.

Nat Commun, 2019 03 08;10(1):1124.
PMID: 30850636 DOI: 10.1038/s41467-019-08853-3

Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use metagenomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR.
Fulltext High-Throughput Sequencing-Based Investigation of Viruses in Human Cancers by Multienrichment Approach

Mollerup S, Asplund M, Friis-Nielsen J, Kjartansdóttir KR, Fridholm H, Hansen TA, et al.

J Infect Dis, 2019 09 13;220(8):1312-1324.
PMID: 31253993 DOI: 10.1093/infdis/jiz318

BACKGROUND: Viruses and other infectious agents cause more than 15% of human cancer cases. High-throughput sequencing-based studies of virus-cancer associations have mainly focused on cancer transcriptome data.
METHODS: In this study, we applied a diverse selection of presequencing enrichment methods targeting all major viral groups, to characterize the viruses present in 197 samples from 18 sample types of cancerous origin. Using high-throughput sequencing, we generated 710 datasets constituting 57 billion sequencing reads.
RESULTS: Detailed in silico investigation of the viral content, including exclusion of viral artefacts, from de novo assembled contigs and individual sequencing reads yielded a map of the viruses detected. Our data reveal a virome dominated by papillomaviruses, anelloviruses, herpesviruses, and parvoviruses. More than half of the included samples contained 1 or more viruses; however, no link between specific viruses and cancer types were found.
CONCLUSIONS: Our study sheds light on viral presence in cancers and provides highly relevant virome data for future reference.

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