SEB Genotyping: SmartAmp-Eprimer Binary code Genotyping for complex, highly variable targets applied to HBV
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ABSTRACT:
PROVIDER: PRJEB51673 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| HBV_S_subset.fas.gz | Other | |||
| tax_ref_set_SEBGenotyping_table.tsv.gz | Tabular | |||
| ERR9609810.fastq.gz | Fastqsanger.gz | |||
| ERR9609811.fastq.gz | Fastqsanger.gz | |||
| ERR9609812.fastq.gz | Fastqsanger.gz |
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Project description:BackgroundSmartAmp-Eprimer Binary code (SEB) Genotyping is a novel isothermal amplification method for rapid genotyping of any variable target of interest.MethodsAfter in silico alignment of a large number of sequences and computational analysis to determine the smallest number of regions to be targeted by SEB Genotyping, SmartAmp primer sets were designed to obtain a binary code of On/Off fluorescence signals, each code corresponding to a unique genotype.ResultsApplied to HBV, we selected 4 targets for which fluorescence amplification signals produce a specific binary code unique to each of the 8 main genotypes (A-H) found in patients worldwide.ConclusionsWe present here the proof of concept of a new genotyping method specifically designed for complex and highly variable targets. Applied here to HBV, SEB Genotyping can be adapted to any other pathogen or disease carrying multiple known mutations. Using simple preparation steps, SEB Genotyping provides accurate results quickly and will enable physicians to choose the best adapted treatment for each of their patients.
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Project description:Hepatitis B virus (HBV) infection could cause hepatitis, liver cirrhosis and hepatocellular carcinoma. HBV-mediated pathogenesis is only partially understood, but X protein (HBx) reportedly possesses oncogenic potential. Exosomes are small membrane vesicles with diverse functions released by various cells including hepatocytes, and HBV harnesses cellular exosome biogenesis and export machineries for virion morphogenesis and secretion. Therefore, HBV infection might cause changes in exosome contents with functional implications for both virus and host. In this project, exosome protein content changes induced by HBV and HBx were quantitatively analyzed by SILAC/LC-MS/MS. Exosomes prepared from SILAC-labeled hepatoma cell line Huh-7 transfected with HBx, wildtype or HBx-null HBV replicon plasmids were analyzed by LC-MS/MS.
2017-03-29 | MSV000080794 | MassIVE
Project description:Background and Aims Chronic infection with hepatitis B virus (HBV) has been known to cause liver cirrhosis and hepatocellular carcinoma. Although nucleos(t)ide analogs are mainly used for the treatment of HBV, they require long-term administration and may lead to the emergence of drug resistance. Therefore, to identify targets for the development of novel anti-HBV therapies, we screened HBV-suppressive host factors using RNA-bnding protein (RBP) expression plasmids library. Approach and Results We screened the RBP library by generating overexpressing RBP cell lines and observing anti-HBV effect. As a result, we identified NEDD4-binding protein 1 (N4BP1) as a candidate showing anti-HBV effect. In hepatocellular carcinoma cell lines, overexpression of N4BP1 decreased the relaxed circular DNA (rcDNA) levels, while suppression of N4BP1 expression increased rcDNA levels. Restoring N4BP1 expression in N4BP1 knockout cells regained the anti-HBV effect of N4BP1. Next, we constructed KH-like and RNase domain-deficient mutants of N4BP1 and examined their effects on HBV replication, and found that both the KH-like and RNase domains are required for its anti-HBV effect. N4BP1 suppresses the step where pregenomic RNA (pgRNA) is synthesized in the HBV life cycle by promoting degradation of pgRNA. Transcriptome analyses of primary human hepatocytes overexpressing N4BP1 suggested that N4BP1 may have anti-HBV activity independent of other host factors. Conclusions In summary, N4BP1 was found to be a novel anti-HBV factor. N4BP1 inhibited HBV replication by promoting pgRNA degradation.
2025-01-08 | GSE225322 | GEO
Project description:This study aimed to better characterize the repertoire of serum HBV RNAs during chronic HBV infection in humans, which remains understudied. Using RT-PCR, qPCR, RNA-sequencing and immuno-precipitation, we found that (i) >50% of serum samples bore different amounts of HBV replication-derived RNAs (rd-RNAs); (ii) a few samples contained RNAs transcribed from integrated HBV DNA including 5'-HBV-human-3' RNAs (integrant-derived RNAs or id-RNAs) and 5'-human-HBV-3' transcripts as a minority of serum HBV RNAs; (iii) spliced HBV RNAs were abundant in <50% of analyzed samples; (iv) most serum rd-RNAs were polyadenylated via conventional HBV polyadenylation signal; (v) pre-genomic RNA (pgRNA) was the major component of the pool of serum RNAs; (vi) area of HBV positions 1531-1739 had very high RNA reads coverage and thus should be used as a target for detecting serum HBV RNAs; (vii) vast majority of rd-RNAs and pgRNA were associated with HBV virions, but not with unenveloped capsids, exosomes, classic microvesicles or apoptotic vesicles and bodies; (viii) considerable rd-RNAs presence in the circulating immune complexes was found in a few samples; and (ix) serum rcDNA and rd-RNAs should be quantified simultaneously to evaluate HBV replication status and efficacy of anti-HBV therapy with nucleos(t)ide analogs. In summary, sera contain various HBV RNA types of different origin, which are likely secreted via different mechanisms. In addition, since we previously showed that id-RNAs were abundant or predominant HBV RNAs in many of liver and hepatocellular carcinoma tissues comparing to rd-RNAs, there is likely a mechanism favoring the egress of the replication-derived RNAs.
2023-02-26 | GSE224901 | GEO
Project description:BackgroundMetabolomics datasets are often high-dimensional though only a limited number of variables are expected to be informative given a specific research question. The important task of selecting informative variables can therefore become complex. In this paper we look at discriminating between two groups. Two tasks need to be performed: (i) finding variables which differ between the two groups; and (ii) determining how the selected variables can be used to classify new subjects. We introduce an approach using minimum classification error rates as test statistics to find discriminatory and therefore informative variables. The thresholds resulting in the minimum error rates can be used to classify new subjects. This approach transforms error rates into p-values and is referred to as ERp.ResultsWe show that non-parametric hypothesis testing, based on minimum classification error rates as test statistics, can find statistically significantly shifted variables. The discriminatory ability of variables becomes more apparent when error rates are evaluated based on their corresponding p-values, as relatively high error rates can still be statistically significant. ERp can handle unequal and small group sizes, as well as account for the cost of misclassification. ERp retains (if known) or reveals (if unknown) the shift direction, aiding in biological interpretation. The threshold resulting in the minimum error rate can immediately be used to classify new subjects. We use NMR generated metabolomics data to illustrate how ERp is able to discriminate subjects diagnosed with Mycobacterium tuberculosis infected meningitis from a control group. The list of discriminatory variables produced by ERp contains all biologically relevant variables with appropriate shift directions discussed in the original paper from which this data is taken.ConclusionsERp performs variable selection and classification, is non-parametric and aids biological interpretation while handling unequal group sizes and misclassification costs. All this is achieved by a single approach which is easy to perform and interpret. ERp has the potential to address many other characteristics of metabolomics data. Future research aims to extend ERp to account for a large proportion of observations below the detection limit, as well as expand on interactions between variables.
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2022-07-15 | GSE208115 | GEO
Project description:The tumor microenvironment (TME) is a crucial mediator of tumor progression and treatment response. Here, we compare the immune microenvironments of HBV and non-HBV-HCC and investigate the reason for the persistence of HBV infection in the liver. We combine the Viral-Track method with single-cell RNA sequencing and profile the transcriptomes of 71,466 cells from HBV and non-HBV-HCC patients. In addition to hepatocytes and macrophages, HBV transcripts were also detected in T and B cells using the Viral-Track method, confirming the HBV-lymphotropic nature for the first time in scRNA-sequencing data. HBV-HCC tumors have reduced levels of CD4+ Tregs, NK, macrophages, dendritic cells (DCs), and increased malignant hepatocytes compared with non-HBV tumors. Notably, we explicitly reported the enrichment of metallothioneins (MTs), particularly MT1G expression in HBV-related HCC TAMs, which was associated with a worse prognosis. HBV-tumor-infiltrated CD8+ T cells exhibited a cytotoxic dysfunctional T cell phenotype, characterized by upregulated MDK and CTLA4 expression and reduced IFN-γ production, unlike the non-HBV-HCC. Additionally, HBV-HCC exhibited immunosuppressive ligand-receptor interactions, whereas non-HBV-HCC exhibited antitumor ligand-receptor interactions. Our comprehensive understanding of the HBV HCC ecosystem by viral-track integrated scRNA sequencing analysis provides deeper insights into immune evasion mechanisms and HBV lymphotropism associated with viral persistence.
2025-06-11 | GSE282343 | GEO
Project description:Hepatitis B Virus constitutes a major threat to global public health by infecting hepatocytes, initiating and driving the progress to end-stage liver disease and liver cancer. Curing treatment for HBV infection is yet unavailable, mainly due to unmet gaps in current understanding of HBV-host interaction. Here, multi-omics interrogations were conducted to generate the first landscape of HBV-induced global changes in host transcriptome, translatome and proteome, which identified multiple translatomic events that HBV orchestrated to remodel host proteostasis networks and afford micro-environments essential for HBV proliferation and persistence.
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Project description:To determine host factors that regulate HBV, cells positive for and negative for HBV were compared. We identified three transcription regulators (HNF4A1, HNFA2, HNFA3) that support HBV replication
2017-09-07 | GSE72779 | GEO