Next Generation Sequencing-Based Investigation of Potential Patient-to-Patient Hepatitis C Virus Transmission during Hemodialytic Treatment

Zhao, Qi; Wen, Yujie; Jiang, Yan; Zhang, Chen; Yang, Li; Zhang, Guiyun; Zhang, Lei; Qiu, Maofeng

doi:10.1371/journal.pone.0147566

Cited by 5 publications

(4 citation statements)

References 17 publications

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“…Some genes are known to harbor important genetic diversity such as the neuraminidase in the case of influenza A or the use of the env, gag, and pol genes to characterize sequence diversity in HIV-1 isolates. 26,27 Another interesting example is HCV which is also well known for the high mutation rates and where genotyping efforts have focused on different proteins, including NS5A, 28 NS5B, 29 the E1 and/or E2, 29,30 or even a composite fragment from short segments derived from the NS3, NS5A, and NS5B genes. 31…”

Section: Molecular Markers In Virologymentioning

confidence: 99%

Use of profile hidden Markov models in viral discovery: current insights

Reyes¹,

Alves²,

Durham³

et al. 2017

AGG

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Sequence similarity searches are the bioinformatic cornerstone of molecular sequence analysis for all domains of life. However, large amounts of divergence between organisms, such as those seen among viruses, can significantly hamper analyses. Profile hidden Markov models (profile HMMs) are among the most successful approaches for dealing with this problem, which represent an invaluable tool for viral identification efforts. Profile HMMs are statistical models that convert information from a multiple sequence alignment into a set of probability values that reflect positionspecific variation levels in all members of evolutionarily related sequences. Since profile HMMs represent a wide spectrum of variation, these models show higher sensitivity than conventional similarity methods such as BLAST for the detection of remote homologs. In recent years, there has been an effort to compile viral sequences from different viral taxonomic groups into integrated databases, such as Prokaryotic Virus Orthlogous Groups (pVOGs) and database of profile HMMs (vFam) database, which provide functional annotation, multiple sequence alignments, and profile HMMs. Since these databases rely on viral sequences collected from GenBank and RefSeq, they suffer in variable extent from uneven taxonomic sampling, with low sequence representation of many viral groups, which affects the efficacy of the models. One of the interesting applications of viral profile HMMs is the detection and sequence reconstruction of specific viral genomes from metagenomic data. In fact, several DNA assembly programs that use profile HMMs as seeds have been developed to identify and build gene-sized assemblies or viral genome sequences of unrestrained length, using conventional and progressive assembly approaches, respectively. In this review, we address these aspects and cover some up-to-date information on viral genomics that should be considered in the choice of molecular markers for viral discovery. Finally, we propose a roadmap for rational development of viral profile HMMs and discuss the main challenges associated with this task.

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Section: Molecular Markers In Virologymentioning

confidence: 99%

Use of profile hidden Markov models in viral discovery: current insights

Reyes¹,

Alves²,

Durham³

et al. 2017

AGG

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“…These limitations make massively parallel sequencing methods an attractive alternative for the study of complex virus populations [ 17 ]. Indeed, next-generation sequencing (NGS) has been successfully applied in a wide range of HCV analyses, including characterization of virus transmission [ 18 ] and positions of mutation (hot spot) in NS3/4A protease [ 19 ].…”

Section: Introductionmentioning

confidence: 99%

Detection of Natural Resistance-Associated Substitutions by Ion Semiconductor Technology in HCV1b Positive, Direct-Acting Antiviral Agents-Naïve Patients

Marascio

Pavia

Strazzulla

et al. 2016

IJMS

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Naturally occurring resistance-associated substitutions (RASs) can negatively impact the response to direct-acting antivirals (DAAs) agents-based therapies for hepatitis C virus (HCV) infection. Herein, we set out to characterize the RASs in the HCV1b genome from serum samples of DAA-naïve patients in the context of the SINERGIE (South Italian Network for Rational Guidelines and International Epidemiology, 2014) project. We deep-sequenced the NS3/4A protease region of the viral population using the Ion Torrent Personal Genome Machine, and patient-specific majority rule consensus sequence summaries were constructed with a combination of freely available next generation sequencing data analysis software. We detected NS3/4A protease major and minor variants associated with resistance to boceprevir (V36L), telaprevir (V36L, I132V), simeprevir (V36L), and grazoprevir (V36L, V170I). Furthermore, we sequenced part of HCV NS5B polymerase using Sanger-sequencing and detected a natural RAS for dasabuvir (C316N). This mutation could be important for treatment strategies in cases of previous therapy failure.

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“…In the past, there were quite some concerns regarding viral transmission associated to the dialysis procedure itself. However, this was only documented in a small number of patients and following current hygienic protocols viral transmission is supposed to be extremely rare . HCV infection may also contribute to or even directly cause renal diseases for example by triggering membranoproliferative glomerulonephritis linked to type II mixed cryoglobulinemia or by an acceleration of artherogenesis.…”

mentioning

confidence: 99%