ORCID Profile
0000-0002-3736-1841
Current Organisation
University of Oxford
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Publisher: American Society for Microbiology
Date: 10-2016
DOI: 10.1128/JCM.00330-16
Abstract: Affordable next-generation sequencing (NGS) technologies for hepatitis C virus (HCV) may potentially identify both viral genotype and resistance genetic motifs in the era of directly acting antiviral (DAA) therapies. This study compared the ability of high-throughput NGS methods to generate full-length, deep, HCV sequence data sets and evaluated their utility for diagnostics and clinical assessment. NGS methods using (i) unselected HCV RNA (metagenomics), (ii) preenrichment of HCV RNA by probe capture, and (iii) HCV pre lification by PCR implemented in four United Kingdom centers were compared. Metrics of sequence coverage and depth, quasispecies ersity, and detection of DAA resistance-associated variants (RAVs), mixed HCV genotypes, and other coinfections were compared using a panel of s les with different viral loads, genotypes, and mixed HCV genotypes/subtypes [geno(sub)types]. Each NGS method generated near-complete genome sequences from more than 90% of s les. Enrichment methods and PCR pre lification generated greater sequence depth and were more effective for s les with low viral loads. All NGS methodologies accurately identified mixed HCV genotype infections. Consensus sequences generated by different NGS methods were generally concordant, and majority RAVs were consistently detected. However, methods differed in their ability to detect minor populations of RAVs. Metagenomic methods identified human pegivirus coinfections. NGS provided a rapid, inexpensive method for generating whole HCV genomes to define infecting genotypes, RAVs, comprehensive viral strain analysis, and quasispecies ersity. Enrichment methods are particularly suited for high-throughput analysis while providing the genotype and information on potential DAA resistance.
Publisher: Public Library of Science (PLoS)
Date: 10-06-2013
Publisher: F1000 Research Ltd
Date: 13-10-2015
DOI: 10.12688/F1000RESEARCH.7111.1
Abstract: The routine availability of high-depth virus sequence data would allow the sensitive detection of resistance-associated variants that can jeopardize HIV or hepatitis C virus (HCV) treatment. We introduce ve-SEQ, a high-throughput method for sequence-specific enrichment and characterization of whole-virus genomes at up to 20% ergence from a reference sequence and 1,000-fold greater sensitivity than direct sequencing. The extreme genetic ersity of HCV led us to implement an algorithm for the efficient design of panels of oligonucleotide probes to capture any sequence among a defined set of targets without detectable bias. ve-SEQ enables efficient detection and sequencing of any HCV genome, including mixtures and intra-host variants, in a single experiment, with greater tolerance of sequence ersity than standard lification methods and greater sensitivity than metagenomic sequencing, features that are directly applicable to other pathogens or arbitrary groups of target organisms, allowing the combination of sensitive detection with sequencing in many settings.
Publisher: Springer Science and Business Media LLC
Date: 20-04-2016
DOI: 10.1038/NCOMMS11465
Abstract: Nature Communications 6: Article number: 10063 (2015) Published: 21 December 2015 Updated: 20 April 2016 In Supplementary Data 3 of this Article, one of the Staphylococcus aureus accession codes is incorrect, as follows: SRR2101499 should be ERR1197981.
Publisher: Centers for Disease Control and Prevention (CDC)
Date: 04-2016
Publisher: BMJ
Date: 2012
Publisher: Springer Science and Business Media LLC
Date: 2012
Publisher: Massachusetts Medical Society
Date: 26-09-2013
Publisher: Springer Science and Business Media LLC
Date: 18-05-2201
DOI: 10.1038/NG.3304
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Paolo Piazza.