Analysis of ultra-deep pyrosequencing and cloning based sequencing of the basic core promoter/precore/core region of hepatitis B virus using newly developed bioinformatics tools

The dynamic variation position and predominant quasispecies of hepatitis B virus: Novel predictors of early hepatocarcinoma

To find the predictors of early HCC based on the dynamic changes of HBV quasispecies, this study utilizing the second-generation sequencing (NGS) and high-order multiplex droplet digital PCR (ddPCR) technology to examine the HBV quasispecies in serum of total 247 subjects recruited from high-incidence area of HCC. In the discovery stage, 15 non-synonymous Single Nucleotide Polymorphisms (SNPs) with higher variant proportion in HCC case group were founded (all P<0.05). Furthermore, the variant proportions in some of these SNPs were observed changing regularly within 5 years before the onset of HCC, and 5 of them located in HBX, 2 in HBS and 2 in HBC. The HBV predominant quasispecies and their consensus sequences were identified by genetic evolution analysis, in which the high HBS and HBC quasispecies heterogeneity were found associated with the forming of multifarious quasispecies clones, and the HBX gene had the highest proportion of predominant quasispecies (46.7 % in HBX vs 12.7 % and 13.8 % in HBS and HBC respectively) with the key variations (G1512A, A1630G, T1753C/G/A, A1762T and G1764A) determined. In the validation stage, we confirmed that the combined double mutations of G1512A+A1630G, A1762T+G1764A, and the combined triple mutations of T1753C/G/A + A1762T+G1764A, all expressed higher in early HCC cases when comparing with control group (all P<0.05). We also demonstrated the advantages of ddPCR using in multi-variations detection in large-sample for early HCC surveillance and screening. So we think that the dynamic of key HBV variation positions and their different combinations determined by quasispecies anlysis in this study can act as the novel predictors of early hepatocarcinoma and suitable to popularize and apply in HCC screening.

Analysis of HBV X gene quasispecies characteristics by next-generation sequencing and cloning-based sequencing and its association with hepatocellular carcinoma progression

OBJECTIVES

This study aimed to describe the differences between next-generation sequencing (NGS) and cloning-based sequencing (CBS) in HBX quasispecies research and primitively investigate the relationship between the dominant HBX quasispecies and hepatocellular carcinoma (HCC).

METHODS

A total of 12 serum samples were collected. Serum hepatitis B virus (HBV) DNA was extracted, and the HBV X-region (HBX) was amplified by nested polymerase chain reaction (PCR). The PCR products were simultaneously tested with NGS and CBS to detect quasispecies of the HBX.

RESULTS

A total of 9348 eligible quasispecies sequences were obtained by NGS, which were much larger than the 98 of that by CBS. By the phylogenetic tree, the dominant quasispecies sequence of each sample could be found, although they had several nucleotides differences between the dominant quasispecies sequences found by CBS and NGS. By comparing the quasispecies heterogeneity, it was found that the quasispecies complexity value of HBV X-region obtained by NGS was higher than CBS (P < 0.05). The diversity values, including d, dS, dN, an d d N/ dS obtained by NGS were lower than by CBS (all of P < 0.01). The relativity of Spearman(rs) in d, dS, and dN were statistically significant (rs_ d = 0.865, P = 0.001; rs_ dS = 0.722, P = 0.014; and rs_ dN = 0.738, P = 0.011, respectively). There were 21 different bases between the HBX quasispecies of case A and control B.

CONCLUSION

The results of this can be used as guidance when researchers plan to choose a suitable method to study quasispecies, especially the HBV X gene quasispecies. Some high-risk mutations of HBX quasispecies were also found in this study and their relationship with HCC need deeper exploration.

A computational chemistry perspective on the current status and future direction of hepatitis B antiviral drug discovery

Computational chemical biology, applied to research on hepatitis B virus (HBV), has two major branches: bioinformatics (statistical models) and first-principle methods (molecular physics). While bioinformatics focuses on statistical tools and biological databases, molecular physics uses mathematics and chemical theory to study the interactions of biomolecules. Three computational techniques most commonly used in HBV research are homology modeling, molecular docking, and molecular dynamics. Homology modeling is a computational simulation to predict protein structure and has been used to construct conformers of the viral polymerase (reverse transcriptase domain and RNase H domain) and the HBV X protein. Molecular docking is used to predict the most likely orientation of a ligand when it is bound to a protein, as well as determining an energy score of the docked conformation. Molecular dynamics is a simulation that analyzes biomolecule motions and determines conformation and stability patterns. All of these modeling techniques have aided in the understanding of resistance mutations on HBV non-nucleos(t)ide reverse-transcriptase inhibitor binding. Finally, bioinformatics can be used to study the DNA and RNA protein sequences of viruses to both analyze drug resistance and to genotype the viral genomes. Overall, with these techniques, and others, computational chemical biology is becoming more and more necessary in hepatitis B research. This article forms part of a symposium in Antiviral Research on "An unfinished story: from the discovery of the Australia antigen to the development of new curative therapies for hepatitis B."

Evolutionary Changes of Hepatitis B Virus Pre-S Mutations Prior to Development of Hepatocellular Carcinoma

BACKGROUND AND AIMS

Deletions/mutations in the hepatitis B virus (HBV) pre-S region have been associated with hepatocellular carcinoma (HCC). We aimed to study the evolutionary changes of pre-S mutations prior to HCC development.

METHODS

We studied the HBV pre-S sequences at 1 to 10 years preceding diagnosis of HCC in 74 patients with HBV-related HCC (HCC group). 148 chronic hepatitis B patients matched for sex and age in 2:1 ratio, who had been followed up for at least 3 years without HCC (HCC-free group) were recruited as controls. 56 and 47 patients of HCC and HCC-free groups respectively had serially stored sera for longitudinally examination at 1-3 years, 4-6 years, 7-9 years and ≥10 years prior to the recruitment of the study.

RESULTS

Compared to the HCC-free group, higher frequencies of pre-S deletions and point mutations (at 11 codons) were observed in the HCC group (p<0.05). Multiple logistic regression analysis showed that pre-S deletions, point mutations at codon 51 and 167 were independent factors associated with HCC. Longitudinal observation showed that pre-S deletions and most of the 11 HCC-associated pre-S point mutations existed at least 10 years before HCC development, and were more prevalent preceding HCC development in patients from HCC groups than HCC-free group. The number of HCC-associated pre-S point mutations increased over time preceding HCC development, and correlated positively with the time to HCC diagnosis (r = 0.220, p = 0.005).

CONCLUSIONS

High prevalence and cumulative evolution of pre-S mutations preceding HCC development suggested a possible carcinogenic role of pre-S mutations and their potential application in HCC risk prediction.

Evolutionary Changes of Hepatitis B Virus Pre-S Mutations Prior to Development of Hepatocellular Carcinoma

BACKGROUND AND AIMS

Deletions/mutations in the hepatitis B virus (HBV) pre-S region have been associated with hepatocellular carcinoma (HCC). We aimed to study the evolutionary changes of pre-S mutations prior to HCC development.

METHODS

We studied the HBV pre-S sequences at 1 to 10 years preceding diagnosis of HCC in 74 patients with HBV-related HCC (HCC group). 148 chronic hepatitis B patients matched for sex and age in 2:1 ratio, who had been followed up for at least 3 years without HCC (HCC-free group) were recruited as controls. 56 and 47 patients of HCC and HCC-free groups respectively had serially stored sera for longitudinally examination at 1-3 years, 4-6 years, 7-9 years and ≥10 years prior to the recruitment of the study.

RESULTS

Compared to the HCC-free group, higher frequencies of pre-S deletions and point mutations (at 11 codons) were observed in the HCC group (p<0.05). Multiple logistic regression analysis showed that pre-S deletions, point mutations at codon 51 and 167 were independent factors associated with HCC. Longitudinal observation showed that pre-S deletions and most of the 11 HCC-associated pre-S point mutations existed at least 10 years before HCC development, and were more prevalent preceding HCC development in patients from HCC groups than HCC-free group. The number of HCC-associated pre-S point mutations increased over time preceding HCC development, and correlated positively with the time to HCC diagnosis (r = 0.220, p = 0.005).

CONCLUSIONS

High prevalence and cumulative evolution of pre-S mutations preceding HCC development suggested a possible carcinogenic role of pre-S mutations and their potential application in HCC risk prediction.

Precore/Core Region Mutations in Hepatitis B Virus DNA Predict Postoperative Survival in Hepatocellular Carcinoma

Hepatitis B virus (HBV) DNA is prone to mutations because of the proofreading deficiencies of HBV polymerase. We have identified hepatocellular carcinoma (HCC) survival-associated HBV mutations in the X protein region of HBV DNA. In the present study, we extend our research to assess HCC survival-associated HBV mutations in the HBV precore/core (PreC/C) region. The PreC/C region was amplified and sequenced and the HBV mutations were identified according to the NCBI database (http://www.ncbi.nlm.nih.gov/genome/5536). The relationships between the mutations in the PreC/C region and HCC survival were analyzed. Survival curves were generated using the Kaplan-Meier method, and comparisons between the curves were made using the log-rank test. Multivariate survival analysis was performed using a Cox proportional hazards model. After adjusting for clinical characteristics, the 1915, 2134, 2221, 2245 and 2288 mutational sites were identified as statistically significant independent predictors of HCC survival by multivariate survival analysis using a Cox proportional hazards model. In addition, the mutational site of 1896 was identified for its association with survival at a borderline significance level. A total of five mutations in the precore/core region were identified as independent predictors of postoperative survival in HCC patients. The analysis of HBV DNA mutations may help identify patient subgroups with poor prognosis and may help refine therapeutic decisions regarding HCC patients.

Bioinformatics tools for small genomes, such as hepatitis B virus

DNA sequence analysis is undertaken in many biological research laboratories. The workflow consists of several steps involving the bioinformatic processing of biological data. We have developed a suite of web-based online bioinformatic tools to assist with processing, analysis and curation of DNA sequence data. Most of these tools are genome-agnostic, with two tools specifically designed for hepatitis B virus sequence data. Tools in the suite are able to process sequence data from Sanger sequencing, ultra-deep amplicon resequencing (pyrosequencing) and chromatograph (trace files), as appropriate. The tools are available online at no cost and are aimed at researchers without specialist technical computer knowledge. The tools can be accessed at http://hvdr.bioinf.wits.ac.za/SmallGenomeTools, and the source code is available online at https://github.com/DrTrevorBell/SmallGenomeTools.

A deep-sequencing method detects drug-resistant mutations in the hepatitis B virus in Indonesians

OBJECTIVE

The long-term administration of a nucleos(t)ide analogue (NA) for the treatment of chronic hepatitis B may encourage the emergence of viral mutations associated with drug resistance. Minor populations of viruses may exist before treatment, but are difficult to detect because of technological limitations. Identifying minor viral quasispecies should be useful in the clinical management of hepatitis B virus (HBV) infection.

METHODS

Six treatment-naïve Indonesian patients with chronic HBV infection participated in this study. The polymerase region of the HBV genome, including regions with known drug-resistant mutations, was subjected to capillary sequencing and MiSeq sequencing (Illumina). Mutations were analyzed with Genomics Workbench software version 6.0.1 (CLC bio).

RESULTS

The mean mapping reads for the six samples was 745,654, and the mean number of amplified fragments ranged from 17,926 to 25,336 DNA reads. Several known drug-resistant mutations in the reverse transcriptase region were identified in all patients, although the frequencies were low (0.12-1.06%). The proportions of the total number of reads containing mutations I169L/M, S202R, M204I/L or N236S were >1.0%.

CONCLUSION

Several known NA-resistant mutations were detected in treatment-naïve patients in Indonesia using deep sequencing. Careful management of such patients is essential to prevent drug-resistant mutations from spreading to other patients.

Clinical application of estimating hepatitis B virus quasispecies complexity by massive sequencing: correlation between natural evolution and on-treatment evolution

AIM

To evaluate HBV quasispecies (QA) complexity in the preCore/Core regions in relation to HBeAg status, and explore QA changes under natural evolution and nucleoside analogue (NUC) treatment.

METHODS

Ultra-deep pyrosequencing of HBV preCore/Core regions in 30 sequential samples (baseline [diagnosis], treatment-free, and treatment-nonresponse) from 10 retrospectively selected patients grouped according to HBeAg status over time: HBeAg+ (N = 4), HBeAg- (N = 2), and fluctuating HBeAg (transient seroreversion/seroconversion pattern) (N = 4). QA complexity was defined by Shannon entropy, mutation frequency, nucleotide diversity, and mutation frequency of amino acids (MfAA) in preCore and Core.

RESULTS

The QA was less complex in HBeAg+ than in HBeAg- or fluctuating HBeAg. High complexity in preCore was associated with decreased viral replication (preCore MfAA negatively correlated with HBV-DNA, p = 0.005). QA complexity in the treatment-free period negatively correlated with values seen during treatment. Specific variants were mainly selected in the Core region in HBeAg- and fluctuating HBeAg patients, suggesting higher immune pressure than in HBeAg+.

CONCLUSIONS

The negative correlation between QA natural evolution and on-treatment evolution indicates the importance of pre-treatment QA study to predict QA changes in NUC nonresponders. Study of QA complexity could be useful for managing HBV infection.