ArtificialFastqGenerator, which takes a reference genome sequence as input and outputs artificial paired-end FASTQ files containing Phred quality scores. Since these artificial FASTQs are derived from the reference genome, it provides a gold-standard for read-alignment and variant-calling, thereby enabling the performance of any NGS pipeline to be evaluated. The user can customise DNA template/read length, the modelling of coverage based on GC content, whether to use real Phred base quality scores taken from existing FASTQ files, and whether to simulate sequencing errors. Detailed coverage and error summary statistics are outputted. Here we describe ArtificialFastqGenerator and illustrate its implementation in evaluating a typical bespoke NGS analysis pipeline under different experimental conditions. ArtificialFastqGenerator was released in January 2012. Source code, example files and binaries are freely available under the terms of the GNU General Public License v3.0. from https://sourceforge.net/projects/artfastqgen/.Pipelines for the analysis of Next-Generation Sequencing (NGS) data are generally composed of a set of different publicly available software, configured together in order to map short reads of a genome and call variants. The fidelity of pipelines is variable. We have developed  Completion of the human genome project (HGP) coupled with developments in sequencing technologies has allowed rapid sequencing of complete human genomes. Most next-generation sequencing (NGS) systems are broadly based on fragmentation of genomic DNA with the oversampling of reads providing the necessary linking information for whole-genome assembly algorithms.ArtificialFastqGenerator software.One source of error in variant-calling is inherent sequencing error in NGS technology . These errors are more likely towards the ends of reads, and in the context of certain sequence motifs ArtificialFastqGenerator takes a reference genome as input and outputs artificial FASTQ files. The user can customise DNA template/read length, gap size between paired-end reads, the modelling of coverage based on GC content, whether to use Phred base quality scores taken from existing FASTQ files, and whether to simulate sequencing errors. Since these artificial FASTQs are derived from the reference genome, the reference genome provides a gold-standard for the variant-calling, enabling evaluation of any pipeline.NGS instruments such as the Illumina Genome Analyzer output reads of nucleotide sequences and corresponding base quality scores, the FASTQ format being the standard text-based representation for these data see . ArtificArtificialFastqGenerator offers advantages over other bioinformatic software tools which generate artificial Illumina reads such as ARTWgSim from the Samtools package MasonSimSeqpIRSArtificialFastqGenerator provides greater flexibility with respect to modelling coverage based on GC content, because the user can assign relevant parameters, rather than them being learned from resequencing data and hence fixed. Secondly, the software produces detailed coverage and error summary statistics . Another distinctive feature is the ability to use real Phred scores taken from existing FASTQ files. By contrast pIRS uses an empirical model which predicts the base-call and Phred score based on read cycle, reference base and quality of the previous cycle.ArtificialFastqGenerator and an evaluation of a typical bespoke NGS analysis pipeline. We investigate how variant-calling results are affected by Phred quality scores and simulated sequencing error in the FASTQs, the presence/absence of different stages in the pipeline, and variant-caller choice.Here, we describe ArtificialFastqGenerator is platform-independent software written in Java SE 6, and is available as open-source from the SourceForge website: https://sourceforge.net/projects/artfastqgen/. The program takes a reference genome sequence in FASTA format as input and outputs artificial paired-end FASTQ files ArtificialFastqGenerator produces a log file of summary statistics for coverage and error generation, and a file documenting start and end indexes in the reference genome of all generated reads.This section mentions user parameters for controlling DNA template/read length, target coverage, whether to take the base quality scores from existing FASTQ files, and whether to simulate sequencing errors based on these scores. ArtificialFastqGenerator generates reads for reference nucleobases which are within a sliding window. The “nucleobaseBufferSize” parameter determines the window's size, and hence also how far right it moves on each occasion.We can consider the reference as a sequence of nucleobases stretching from left to right. In order to maintain a small memory footprint, ArtificialFastqGenerator passes through the region inside the window repeatedly, considering pairs of nucleobase sequences for the generation of paired-end reads. Nucleobase target coverage constraints dictate that eventually, the program will complete a pass through the region without being able to generate any novel reads, and at this point, the window slides right. A nucleobase's coverage is the number of reads in which it appears, so its target coverage is the upper limit on how many reads it can appear in.ArtificialFastqGenerator can only generate right-end reads for the nucleobases at the right end of the window. Hence when the window slides right, it reaches a point at which these nucleobases are at the left end of the window. This then allows left-end reads including these nucleobases to be generated.ArtificialFastqGenerator samples template lengths from a normal distribution. The user can specify the mean and standard deviation of this distribution, and the read length.In paired-end sequencing both ends of a DNA template are sequenced. If read lengths are constant, which is generally the case, then the distance between the two reads is determined by the template length. ArtificialFastqGenerator calculates the region's GC content, and then defines and samples from a normal distribution of coverage levels for regions with this GC content. The software calculates the distribution's mean using a Gaussian function of the GC content. The user can customise the function by setting the coverage mean peak (the height of the bell's peak), the GC content at which this peak occurs (the position of the centre of the peak), and how quickly mean coverage decays (the width of the bell). The user can also specify the standard deviation as a multiple of the mean, and the size of the region for which GC content is calculated.To set a nucleobase's target coverage, The default values of these parameters are based on the results of a capture probe experiment in which 4 samples were sequenced by an Illumina Genome Analyzer ArtificialFastqGenerator assigns every base in every read a high Phred quality score of 40, Sanger-encoding “I”.Alternatively the program can use quality scores from pre-existing FASTQ files. If a generated read is a different length to the one whose quality scores are being used, then the sequence of quality scores is lengthened/shortened accordingly by either duplicating or removing the first base quality score(s). By only altering the beginning of the sequence, the trend for quality scores to deteriorate at the end of reads is preserved.As the default, The error simulator decodes the base's Sanger format encoded Phred quality score  cannot be subjected to error simulation, and are always assigned a very low Phred quality score of 2. There is a user parameter for filtering out reads which contain Ns.ArtificialFastqGenerator logs regional and overall summary coverage statistics, and overall error statistics. The overall error statistics include the total number of reads and nucleobase calls, and the number of these nucleobase calls for which an error was simulated.ArtificialFastqGenerator has a low memory footprint dependent on the user-specified “nucleobaseBufferSize” parameter. On an Intel Xeon X5650 processor , when using real quality scores and simulating sequencing errors, and with the other parameters set to their defaults, it takes around 6 hrs 20 mins to process 1 giga base.ArtificialFastqGenerator FASTQ files to benchmark the performance of a typical NGS pipeline we subjected to scrutiny our current in-house bioinformatic pipeline which is based on the following components:To illustrate the use of FastQCQuality control of raw sequences (FASTQ file reads) using StampyAlignment of reads using Genome Analysis Toolkit (GATK)Local realignment of reads using the PicardMarking/removal of Polymerase Chain Reaction (PCR) duplicates using Recalibration of base quality scores using GATK.Variant Call Format (VCF) file along with features which are indicative of its fidelity e.g. mapping quality of the reads, and whether the variation is seen in only one strand. Filtering based on these features can reduce the number of false-positives (FPs).Variant-calling using GATK or alternatively Platypus To evaluate this NGS pipeline we investigated how variant-calling is influenced by: Phred quality scores; Simulated sequencing errors; Local realignment and recalibration; Variant-caller software (GATK vs. Platypus); Coverage and sequence uniqueness.ArtificialFastqGenerator and the human reference genome (build 37 in FASTA format), we generated two pairs of whole genome FASTQs with different Phred quality score/simulated sequencing error (PE) characteristics: high Phred quality scores (40) with no simulated sequencing errors (PE = 00); Phred quality scores from pre-existing FASTQ files with simulated sequencing errors (PE = 11). All other parameters in ArtificialFastqGenerator were set to their default values . Note that this average is for nucleobases marked as A/C/G/T in the reference genome, not N (unknown). Using the Phred quality scores from the Illumina HiSeq FASTQ data resulted in a simulated sequencing error for approximately 4.5% of all nucleobase calls.QualByDepth < 2.0, RMS MappingQuality < 40.0, FisherStrand > 60.0, HaplotypeScore > 13.0, MappingQualityRankSumTest < −12.5, ReadPosRankSumTest < −8.0; for InDels, QualByDepth < 2.0, ReadPosRankSumTest < −20.0, FisherStrand > 200.0. Platyus automatically applies a filter for each variant call and records whether it passes in the VCF.To investigate the effect of Phred quality scores and simulated sequencing errors on variant calling, we analyzed each pair of whole genome FASTQs using our NGS pipeline. To investigate the effect of local realignment and recalibration, we conducted variant-calling immediately after the alignment stage, and to investigate the effect of variant-caller choice, we used Platypus rather than GATK. We did not implement Syzygy ArtificialFastqGenerator, and to study sequence uniqueness, we used the Broad alignability trackTo examine the basis of genomic regions consistently associated with FP variant calls we investigated the effect of coverage and the level of uniqueness of their composite sequences. Our basic hypothesis was that such regions have reduced coverage and/or reduced sequence uniqueness. To study the effect of coverage, we made use of coverage statistics for every 10000 nucleobases in the reference genome outputted by FP variant regions.Note that FP variant calls are made when PE = 00 and PE = 11. We refer to genomic regions containing FP variant calls as Imposing real Phred quality scores and simulating sequencing errors is associated with a reduction in FP variant calls. For example, when PE = 00 (and after RDMR), GATK calls 4306 SNPs and 2100 InDels genome-wide, but when PE = 11, it calls 2604 and 1244. While simulating sequencing errors may cause more misaligned reads, fewer are aligned with high confidence, resulting in fewer FP variant calls.We are most interested in the importance of Realignment, Duplicate Marking and Recalibration (RDMR) when PE = 11, because this is the much more realistic case. As hoped, RDMR reduces the number of FP SNPs , but it increases FP InDels .FP variant regions seems to remain the same. This point is illustrated by While different experimental conditions are associated with an increased/decreased number of FP variant calls, the location of Broad alignability track, and then also in expanded regions of length 500 and 1000 bases .The region in ArtificialFastqGenerator can be used to evaluate the performance of an NGS analysis pipeline under different conditions and identify which components of a system may be suboptimal. Furthermore, the strategy provides a means of identifying regions of the genome which may be problematic for any pipeline.Here we have demonstrated that FASTQs generated by Using our own NGS analysis pipeline we investigated how variant-calling is affected by Phred quality scores, sequencing errors, coverage, local realignment and recalibration, and variant-caller algorithm. We found that the number of false-positive variant calls was higher using Platypus rather than GATK for variant-calling, and lower when we used real Phred quality scores and simulated sequencing error. The number of false-positive SNP calls was also lower after local realignment, duplicate marking and recalibration, but unfortunately, the number of false-positive InDels was higher.Although the number of false-positive variant calls varied under different conditions the regions these were associated with were generally the same. We also established that there is no simple straightforward relationship between the presence or absence of false-positive variant calls, and coverage or sequence uniqueness.ArtificialFastqGenerator offers the user control over DNA template/read length, target coverage, whether to use real Phred base quality scores taken from existing FASTQ files, and whether to simulate sequencing errors. Possible future extensions of the software are to offer the user greater choice over quality score generation, and if possible, to improve the accuracy of sequencing error by basing it on more than just the quality scores.In the current guise Figure S1Number of false-positive (FP) variant calls after filtering for chromosomes 1–12; S = SNP; I = InDel; PE = 00 means all Phred scores high (40) & no simulated sequencing errors; PE = 11 means Phred scores from real FASTQ files & simulated sequencing errors; RDMR = local realignment, duplicate marking and recalibration; G = GATK; P = Platypus.(TIFF)Click here for additional data file.Figure S2Number of false-positive (FP) variant calls after filtering for chromosomes 13–22, X and Y; S = SNP; I = InDel; PE = 00 means all Phred scores high (40) & no simulated sequencing errors; PE = 11 means Phred scores from real FASTQ files & simulated sequencing errors; RDMR = local realignment, duplicate marking and recalibration; G = GATK; P = Platypus.(TIFF)Click here for additional data file.Figure S3GATK chromosome 1 SNP calls for different Phred quality score and sequencing error simulation settings; local realignment, duplicate marking and recalibration (RDMR) are applied, as well as variant-call filtering. PE = 00 means all Phred scores high (40) & no simulated sequencing errors; PE = 11 means Phred scores from real FASTQ files & simulated sequencing errors.(TIFF)Click here for additional data file.Figure S4GATK chromosome 1 InDel calls for different Phred quality score and sequencing error simulation settings; local realignment, duplicate marking and recalibration (RDMR) are applied, as well as variant-call filtering; PE = 00 means all Phred scores high (40) & no simulated sequencing errors; PE = 11 means Phred scores from real FASTQ files & simulated sequencing errors.(TIFF)Click here for additional data file.Figure S5GATK chromosome 1 SNP calls for different Phred quality scores and sequencing error simulation settings; local realignment, duplicate marking and recalibration (RDMR) are applied but no variant-call filtering. PE = 00 means all Phred scores high (40) & no simulated sequencing errors; PE = 11 means Phred scores from real FASTQ files & simulated sequencing errors.(TIFF)Click here for additional data file.Figure S6GATK chromosome 1 InDel calls for different Phred quality score and sequencing error simulation settings; local realignment, duplicate marking and recalibration (RDMR) are applied, but no variant-call filtering. PE = 00 means all Phred scores high (40) & no simulated sequencing errors; PE = 11 means Phred scores from real FASTQ files & simulated sequencing errors.(TIFF)Click here for additional data file.Figure S7GATK chromosome 1 SNP and InDel calls when all Phred quality scores high (40) & no simulated sequencing error (PE = 00); local realignment, duplicate marking and recalibration (RDMR) are applied, and also variant-call filtering.(TIFF)Click here for additional data file.Figure S8GATK chromosome 1 SNP and InDel calls when using real Phred quality scores and simulated sequencing errors (PE = 11); local realignment, duplicate marking and recalibration (RDMR) are applied, and also variant-call filtering.(TIFF)Click here for additional data file.Figure S9GATK chromosome 1 SNP calls after applying local realignment, duplicate marking and recalibration (RDMR) versus not; real Phred quality scores and simulated sequencing errors are used (PE = 11), and variant-call filtering is applied.(TIFF)Click here for additional data file.Figure S10GATK versus Platypus chromosome 1 SNP calls when using real Phred quality scores and simulated sequencing errors (PE = 11); local realignment, duplicate marking and recalibration (RDMR) are applied, as well as variant-call filtering.(TIFF)Click here for additional data file.Table S1Coverage statistics for a sample of regions from chromosome 1 of length 10000 bases which produced a relatively high number of FP variant calls ((PDF)Click here for additional data file.Table S2Broad alignability track results for 2 regions containing a cluster of FP SNPs on chromosome 1, and for chromosome 1 as a whole.(PDF)Click here for additional data file.Text S1Short description of the FASTQ format.(PDF)Click here for additional data file.Text S2Description of ArtificialFastqGenerator's user parameters, and how to run a test case.(PDF)Click here for additional data file.


Spontaneous acute exacerbation (AE) of chronic hepatitis B (CHB) is often detrimental but sometimes leads to sustained immune control and disease remission. The efficacy and safety of nucleos(t)ide analogues (NAs) in patients with spontaneous AE of CHB remains unclear.We performed a systematic review and meta-analysis of NAs in patients with spontaneous AE of CHB. We calculated pooled effects of NAs in these patients of each study and conducted quantitative meta-analysis, displaying results using Forest plots.15 studies were included and substantial heterogeneity was noted in the inclusion/exclusion criteria and controls. Pooled data showed no benefit of lamivudine (LAM) vs. untreated controls for transplant-free survival in patients with spontaneous AE of CHB ), hepatic decompensation ) and liver failure owing to AE ) at 3 months. Entecavir achieved even higher short-term mortality than LAM. NAs led to rates of ALT normalization, undetectable HBV DNA, HBeAg loss, HBeAg seroconversion and drug resistance at 1 year in 88%, 61%, 46%, 35% and 5%. Pooled data also showed benefit favoring LAM vs. untreated controls for ALT normalization ) and undetectable HBV DNA ) at 3 months. All NAs were relatively safe and well tolerated.NAs had no obvious impact on short-term survival in patients with AE of CHB, despite of possible better antiviral responses. We suggest additional studies to evaluate the efficacy of other NAs and early introduction of immunosuppressant in combination with NAs. We highlight developing prognostic models to identify predictors of mortality and disease progression for AE of CHB. Chronic hepatitis B virus (HBV) infection is a major global public health problem. It is estimated that approximately over 350 million people worldwide have been chronically infected with HBV Nucleos(t)ide analogues (NAs), having rapid and direct role in suppression of HBV, which hopefully can calm down the immune activity and buy time for the hepatitis to settle, might be the treatment of choice. Although majority of the studies have demonstrated no benefits of NAs therapy on either improvement of short-term survival or protection against rapid progression of the disease to liver failure In the present study, we aim to investigate the efficacy and safety of NAs in the treatment of patients with AE of CHB by performing a systematic review and meta-analysis.Studies of the English/Chinese-language were identified by an electronic search using MEDLINE, EMBASE, ISI Web of Knowledge, English Medical Current Contents (EMCC), China National Knowledge Infrastructure (CNKI), WANFANG Database, the Cochrane Central Register of Controlled Trials and the Cochrane Database of Systematic Reviews. A manual search of abstracts of international liver meetings (from 2006 to 2012) and reference lists of retrieved articles and qualitative topic reviews was also performed. The following key words were searched  with appropriate modification of the PubMed search strategy for other databases:(((hepatitis b virus infection OR chronic hepatitis b virus infection OR chronic hepatitis b) OR “Hepatitis b”[Mesh]) AND (acute flare OR acute flares OR acute exacerbation OR acute exacerbations OR severe acute exacerbation OR severe acute exacerbations) AND ((therapy OR therapies OR treatment OR treatments) OR  OR “lamvudine”[Mesh] OR “adefovir”[Mesh] OR “entecavir”[Mesh] OR “tenofovir”[Mesh] OR “telbivudine”[Mesh])) AND  OR “Mortality”[Mesh] OR “Prognosis”[Mesh] OR “Survival”[Mesh] OR “Survivors”[Mesh] OR “Death”[Mesh] OR “HBeAg”[Mesh])).The literature retrieval, trial selection and data extraction were operated independently by two researchers, reaching to consensus by conferring with each other when discrepancies appeared. In addition, the citations in retrieved publications were also searched manually.The inclusion criteria were included as following: (1) study population: adult CHB patients with spontaneous AE presented with elevation of serum ALT levels to greater than 5 × ULN, studies in patients with SAE of CHB defined as elevation of ALT levels accompanied by jaundice and/or coagulopathy were also included; (2) treatment regimen: oral NAs monotherapy or in combination; (3) study design: any design including retrospective or open-label prospective studies with or without a control group.The following exclusion criteria were used: (1) non-adult study population, liver transplantation recipients or pregnancy; (2) AE occurring in patients receiving chemotherapy, immunosuppressive therapy or anti-HBV therapy; (3) interferon, traditional Chinese medicine, stem cells or corticoids treatments; (4) co-infection with hepatitis A, C, D, E virus, Epstein-Barr virus, cytomegalovirus or human immunodeficiency virus (HIV); (5) other concomitant liver diseases such as autoimmune hepatitis, alcoholic liver disease, drug-induced liver injury or Wilson’s disease.A quality score for each study was determined using several binomial parameters . ParametEfficacy measures were categorized as: (1) total liver transplant (LT)-free survival rate defined as proportion of patients with AE of CHB surviving without LT; (2) LT-free survival rate of patients with hepatic decompensation and liver failure owing to AE defined as proportion of patients experienced hepatic decompensation or developed liver failure at baseline or during therapy due to clinical deterioration surviving without LT; (3) worsening of liver disease rate defined as proportion of patients developed liver disease worsening manifested by occurrence of hepatic decompensation and liver failure; (4) biochemical, virological and serological: proportion of patients with ALT normalization, undetectable HBV DNA, HBeAg loss and HBeAg seroconversion. The following measures were used for evaluating safety for each drug: (1) proportion of patients with drug related serious adverse events; (2) proportion of patients with confirmed drug resistant HBV determined using direct sequencing or line probe assay.Data were extracted for: (1) study characteristics ; (2) patient demographics ; (3) inclusion and exclusion criteria; (4) treatment details ; and (5) study outcomes of the treatment. Quantitative meta-analysis was conducted using Comprehensive Meta-Analysis . Pooled effects with 95% confidence interval (CI) were reported for the uncontrolled data while odds ratios (OR) with 95% CI were reported for studies with untreated control groups. A P value of less than 0.05 was considered to indicate a statistically significant difference. Heterogeneity was assessed for each analysis using Cochrane’s Q test. A P value less than 0.10 indicated heterogeneity. Meta-analysis was performed using random-effect methods, despite the absence of significant heterogeneity. The potential risk of publication bias was examined using the Egger’s test. Publication bias was indicated if the P value was less than 0.05.15 studies involving a total of 1181 patients fulfilled the criteria for this systematic review and meta-analysis . Most ofBaseline characteristics of the patients enrolled in the studies were shown in Analysis of the pooled open-label data did not show beneficial effects for LAM regarding the total LT-free survival rate in patients with AE of CHB. LAM was associated with a total LT-free survival rate of 97% at 3 months, followed by a decline to 93% at 1 year. Moreover, total LT-free survival rate with LAM was not significantly higher compared to untreated controls at 3 months .In one retrospective study comparing LAM (n = 24) and ETV (n = 10) in patients with 500 IU/L or higher ALT, ETV was not superior to LAM for LT-free survival at 1 year. All patients in both groups survived, despite one LAM-treated patient had HE at baseline Hepatic decompensation owing to AE was defined as significant liver function abnormality as indicated by raised serum bilirubin and prolonged prothrombin time or occurrence of complications such as ascites during the exacerbation period In one retrospective study comparing LAM (n = 117) and ETV (n = 36) in patients with ALT and serum bilirubin increased beyond 10 × and 3 × ULN, respectively, although ETV and LAM were similar in achieving mortality rate between one month and one year , ETV achieved an even higher mortality within the first month compared to LAM historical controls . If only considering liver related mortality, ETV was also likely to exhibit a significantly higher incidence compared to LAM  In a single study of 154 patients with ALT levels greater than 5 × ULN without jaundice or coagulopathy, comparing with untreated controls (n = 52), LAM (n = 102) showed no beneficial effects regarding the protection from progressing to hepatic decompensation. 3 (3%) LAM patients, but none of untreated controls, progressed to hepatic decompensation at 1.5 years Analysis of the pooled open-label data did not show beneficial effect for LAM regarding the proportion of liver failure development in patients with hepatic decompensation. 23 out of 123 LAM patients  with hepatic decompensation developed liver failure during the first month. Moreover, LAM was not effective in reducing the incidence of liver failure in patients with hepatic decompensation at 3 months compared to untreated controls with OR of 0.82  .Worsening of liver disease was also indicated by occurrence of other complications such as variceal bleeding and hepatorenal syndrome. Although one study comparing ETV (n = 36) and LAM (n = 117) showed that the proportion of patients developing variceal bleeding, spontaneous bacterial peritonitis, and hepatorenal syndrome were similar with these two agents, occurrence of HE and ascites were even more common in ETV-treated patients  Analysis of the pooled data showed beneficial effects for NAs in regard to the proportion of patients with ALT normalization, undetectable HBV DNA, HBeAg loss and HBeAg seroconversion . The useIn a prospective clinical trial comparing LAM (n = 117) and ETV (N = 36), the mean ALT levels in both groups decreased rapidly within the first week. ETV was associated with a higher rate of ALT normalization at 1 year, albeit statistically insignificant . ETV also achieved higher rates of undetectable HBV DNA at 6 months and 1 year compared to LAM . But the rates of HBeAg loss and seroconversion were similar at 1 year with these two agents  In a single study, only 2 out of 45 (4%) LAM-treated HBeAg positive patients have achieved hepatitis B surface antigen (HBsAg) seroconversion at 7 years, in spite one of them achieved HBsAg seroconversion during the resuming therapy owing to relapse after discontinuation of the initial therapy None of the studies of LAM or ETV reported any serious adverse events associated with these agents. Elevations in creatine kinase (CK) levels through 1 year were observed in 5 out of 40 (12.5%) LDT-treated patients, one of whom had an elevation of CK to more than 7 × ULN. The elevated CK levels decreased spontaneously during the following 6 months of LDT treatment The pooled rates of drug resistance with LAM were 9% at 1 year, 16% at 2 years and 26% at 3 years, respectively. M204I mutation also developed in only 2.9% of LDT-treated patients at 1 year We assayed the possibility of publication bias using the Egger’s regression test. We did not detect the presence of bias in the meta-analysis of total LT-free survival, rate of progression to hepatic decompensation in patients with AE of CHB and development of liver failure in patients with hepatic decompensation comparing LAM vs. no treatment. But Egger’s regression test suggested the presence of a potential publication bias, a language bias, inflated estimates by a flawed methodologic design in smaller studies, and/or a lack of publication of small trials with opposite results in the meta-analysis of LT-free survival in patients with hepatic decompensation comparing LAM vs. no treatment .AE of CHB is a unique presentation of clinical importance because it may progress to liver failure and deaths, while high ALT level is predictive for favorable responses to anti-HBV treatment LAM was reported to be effective and safe in patients with spontaneous SAE of CHB, even in the presence of hepatic failure in previous studies 9 copies/mL can predict decompensation and be used to identify patients in need of immediate antiviral therapy 9/L) and high serum bilirubin (>172 mmol/L) was also reported to be the only independent factors of mortality 3/mL) was linked to rapid progression to hepatic failure Additionally, the high mortality rate despite NAs treatment could be partially related to the delayed commencement, when the livers of these patients had already undergone massive or submassive hepatic necrosis, as the main determinants for recovery are the rapid cessation of ongoing necro-infammation and liver regeneration. Thus further researches about the prognostic factors that could sensitively mirror the severity of hepatic impairment and possibility of recovery might be warranted. Many prognostic markers, such as serum bilirubin, HBV DNA, platelet (PLT) and PT were researched closely to find the risk of progression. During AE of HBeAg-positive CHB, serum HBV DNA cut-off value of 1.55 × 10Higher ALT reflects a more robust immune clearance of HBV both in the setting of natural course and during therapy Drug related serious adverse event is another important consideration when treating patients with AE of CHB. Drug safety is a particular consideration in patients with hepatic decompensation and impending liver failure who had potential impaired drug metabolism and renal function. In our results, elevation of CK was seen in about 10% of LDT-treated patients, but did not result in medication cessations or dose adjustments. Serious adverse events such as renal insufficiency, mitochondrial toxicity and lactic acidosis were not reported in either LAM or ETV patients. Drug resistance was also much less common in LAM-treated and LDT-treated patients than previous reports Several limitations regarding our systematic review require comment. Firstly, the inclusion criteria, patients number and study design varied greatly among the studies included. The heterogeneity in patient populations leads to a lower level of confidence in the accuracy of the pooled estimates. However, all the study patients had characteristics of AE and we were able to extract the majority parameters of most studies. Secondly, there were only two studies of ETV and one of LDT, and the difference of parameters between them limited our ability to make recommendations regarding these agents. In addition, the definition of hepatic decompensation was variable, however, it manifests impending liver failure. Lastly, we were unable to conduct analysis to reveal the association between the distribution of HBV genotypes and the clinical outcomes.In summary, our results indicated that NAs therapy had no benefit with respect to LT-free survival rate and prevention of disease deterioration of patients with AE of CHB, despite of better biochemical and virological responses. Thus, it might be rational to carefully start to treat these patients without evidence of development or deterioration of hepatic decompensation. And early introduction of immunosuppressive therapy in combination with NAs might offer an alternative for treating patients with hepatic decompensation due to AE. In addition, prognostic models to identify the predictive parameters for disease progression and mortality that can assist management decision might be warranted.Table S1Quality scores of the studies included in this systematic review.(DOC)Click here for additional data file.


RAD52 is an important but not well characterized homologous recombination repair gene that can bind to single-stranded DNA ends and mediate the DNA-DNA interaction necessary for the annealing of complementary DNA strands. To evaluate the role of RAD52 variants in the response of tumor cells to platinum agents, we investigated their associations with platinum resistance and prognosis in cervical cancer patients. We enrolled 154 patients with cervical squamous cell carcinoma, who had radical surgery between 2008 and 2009, and genotyped three potentially functional RAD52 variants by the SNaPshot assay. We tested in vitro platinum resistance and RAD52 expression by using the MTT and immunohistochemistry methods, respectively. In 144 cases who had genotyping data, we found that both the rs1051669 variant and RAD52 protein expression were significantly associated with carboplatin resistance  and rs10774474 with nedaplatin resistance (P = 0.018). The rs1051669 variant was significantly associated with RAD52 protein expression . When these three RAD52 variants were combined, progression-free survival was lower in patients who carried at least one (≥1) variant allele compared to those without any of the variant alleles (P = 0.047). Therefore, both RAD52 variants and protein expression can predict platinum resistance, and RAD52 variants appeared to predict prognosis in cervical cancer patients. Large studies are warranted to validate these findings. Cervical cancer is the third most commonly diagnosed cancer and the fourth leading cause of cancer death in women, accounting for 9%  of all new cancer cases and 8%  of all cancer deaths among women in 2008 in the world RAD52, as a relatively less well-characterized HRR gene, spans 37.6 kb on chromosome 12p12.2-13 and codes for a protein with 417 amino acids, which can bind to single-stranded DNA ends and mediate the DNA-DNA interaction necessary for the annealing of complementary DNA strands RAD52 mRNAs in BRCA1-defective HCC1937 cells was associated with high sensitivity to platinum-derived compounds RAD52 may be involved in platinum resistance in cancer cells.DNA repair is mainly responsible for repairing and/or removing platinum-DNA adducts. This DNA repair involves the coordinated activities of more than 20 enzymes that remove and restore a segment of DNA containing a bulky adduct RAD52 SNPs with the risk of malignancy RAD52 SNPs with in vitro platinum resistance and prognosis in patients with CSCC.Single nucleotide polymorphisms (SNPs) in genes involved in DNA repair may affect protein binding sites or affinity or cause changes in protein structure and thus may modify gene functions and render cancer cells more sensitive to platinum treatment This project was approved by the Institutional Review Board of Fudan University Shanghai Cancer Center (FUSCC). A written informed consent was obtained from all recruited individuals, and each clinical investigation was conducted according to the principles expressed in the Declaration of Helsinki consent.In the present study, we recruited 154 CSCC patients who had radical hysterectomy and pelvic lymphadenectomy between March 2008 and March 2009 at the Fudan University Shanghai Cancer Center (FUSCC). All cases were histologically confirmed to be squamous cell carcinoma by two gynecologic pathologists (XYT and GY). The detailed clinical information was extracted from the patients’ electronic database at FUSCC and included age, tumor stage , tumor size , pelvic lymph node (LN) metastases, lympho-vascular space invasion (LVSI) and depth of cervical stroma invasion. Patients were followed every three months for the first two years, every six months for the next two years, and annually for the following years thereafter. The analysis of all blood and tissue samples was carried out in a blinded fashion with regard to patients’ chemoresistance and survival status.http://www.ncbi.nlm.nih.gov/projects/SNP), the International HapMap Project database (http://hapmap.ncbi.nlm.nih.gov/) and the SNP function prediction (FuncPred) software (http://snpinfo.niehs.nih.gov/snpfunc.htm) based on four criteria: 1) located at the two ends of the RAD52 gene , 2) had a minor allele frequency of at least 5% in Chinese populations, 3) in low linkage disequilibrium by using an r2 threshold of 0.8 for each other, and 4) predicted as potentially functional SNPs at microRNA (miRNA) binding sites or transcription factor binding sites. As a result, three RAD52 SNPs were selected, and they are rs1051669G>A (3′-UTR), rs10774474A>T (5′-flanking) and rs11571378T>A (5′-flanking).The SNPs were selected from the NCBI dbSNP database  according to the manufacturer’s instructions. DNA purity and concentration were determined by spectrophotometric measurement of absorbance at 260 and 280 nm by Synergy™ 4 Multi-Mode Microplate Reader .The selected SNPs were genotyped using the multiplex SNaPshot assay. The primers for PCR amplification and SNaPshot extension were designed to have an annealing temperature around 60°C using Primer5 software. To test for possible repetitive sequences, primers were aligned with the GeneBank database using the BLAST online tool. AutoDimer Software was used in the detection of potential hairpin structures and possible primer-dimer combinations. All primers were synthesized by Sangon Biotech Co., Ltd. . After amplification and purification, the PCR products were mixed and used as the template in the SNaPshot extension reaction. Then, electrophoresis was performed on the ABI 3130 Genetic Analyzer  to check the quality of PCR products. The genotyping data was finally analyzed by Peak Scanner Software version 1.0 (Applied Biosystems). Ten percent of the samples were randomly selected to be sequenced. As a result, the mean genotyping rate was 93.5% by using the multiplex SNaPshot assay. The discrepancy rate in all positive controls  was less than 0.1%.2) 2) 2) 2) In performing the MTT assay, we considered previously reported peak plasma concentrations (PPCs) for the four selected platinum agents: cisplatin 10 µg/ml  was added into each well at 37°C for 4 h, and then 100µl solution buffer  were added into each well overnight to dissolve formazan crystals. Optical densities (OD570 nm) were measured by Microplate Reader . The inhibition rate was obtained by using the formula of (1−ODplatinum/ODcontrol)×100%.Histopathologically confirmed fresh tumor tissues obtained at surgery were cut into pieces of smaller than 5×5 mm and suspended in the RPMI 1640 medium  supplied with 15% fetal bovine serum  at room temperature. Suspended cancer cells were poured over a 150 µm sterile steel mesh placed in the dish. Percoll discontinuous gradient centrifugation with 400 g was used to separate and purify cancer cells as recommended previously The portions of tumor/normal tissue to be used for the tissue microarray were selected from a representative tumor/normal area in the corresponding H&E stained section of each block by two gynecologic pathologists (XYT and GY). A 10×12 (120 cores) array was made by the Tissue Bank of FUSCC, which also included 17 controls of normal cervical tissues. For each patient, two cores were made from separate sources. IHC was performed on 5 µm-thick tissue sections prepared from formalin-fixed, paraffin-embedded tissue from the constructed tissue microarray block using antibody against RAD52  and ChemMate™ EnVision™ detection kit . A known positive sample was included as a positive control. For the negative control, the primary antibody was replaced with nonimmune rabbit serum.IHC staining results were independently scored by two gynecologic pathologists (XYT and GY), who were blinded to patient information, using BX51 microscope and DP25 cameras . The scoring system was based on both the percentage of positive cells and staining intensity, as described previously Wilcoxon test and Kruskal-Wallis test to compare platinum-inhibition rates for each agent both between the agents and among different groups. Pearson’s χ2-test and logistic regression analysis were also used to evaluate the association between RAD52 genotypes and protein expression. For the survival analysis, progression-free survival (PFS) and overall survival (OS) times were calculated from the date of first surgery to the date of disease recurrence and death, respectively. Patients without progression, lost to follow-up or died from other causes were censored at their last date of record. Kaplan-Meier survival estimate and log-rank test were calculated to evaluate PFS and OS. We performed Cox proportional hazards regression analysis to evaluate the effects of RAD52 genotypes on the cumulative probability of survival in CSCC patients. Each reported P value was two-sided, and P<0.05 was used to infer the statistical significance. All analyses were performed using SAS software .Because the platinum-inhibition rates did not follow normal distributions, we performed the nonparametric Genotyping was unsuccessful in 10 cases after repeated assays. Therefore, the final analysis included 144 CSCC patients, whose clinical and pathological characteristics are summarized in in vitro inhibition rate of cancer cell growth by cisplatin, carboplatin, nedaplatin and oxaliplatin was 80.8%, 34.3%, 76.4% and 52.0%, respectively , except for rs11571378 (P = 0.0004). Overall, the rs1051669A and rs10774474T variant alleles were significantly associated with platinum resistance. Cancer cells with rs1051669AA and rs10774474TT variant homozygotes had lower responses to carboplatin and nedaplatin, respectively . The rs1051669 AA genotype carriers appeared to have increased carboplatin resistance compared with GG/AG genotype ones but this was not statistically significant . There was no significant association between the in vitro inhibition rates and the rs11571378 SNP.All the observed genotype distributions among the patients agreed with the Hardy-Weinberg equilibrium . However, when these three selected RAD52 SNPs were combined, patients carrying at least one (≥1) variant allele  had poorer PFS and OS compared to those without any of the variant alleles . The genotype distributions of the rs1051669G>A, rs10774474A>T and rs11571378T>A SNPs in the RAD52-negative and positive patients are shown in P = 0.013; Wilcoxon test, P = 0.028; To further evaluate biological plausibility underlying the observed association, we performed the IHC analysis of target tissues and found that RAD52 was localized to the nucleus , whose genotype distributions among the patients followed HWE, were independently associated with the in vitro inhibition rates of carboplatin and nedaplatin in CSCC cells, respectively, indicating an important role of RAD52 variants in platinum resistance. Actually, these two SNPs are both predicted as potentially functional. For example, the rs1051669 SNP is located in the 3′- UTR of RAD52 and may be at a miRNA binding site disrupt the miRNA–mRNA interaction and affect the expression of miRNA targeted genes RAD52, which might be a transcription factor binding site to participate in gene regulatory networks, such as DNA repair pathways RAD52-rs1051669 SNP. Interestingly, our genotype-phenotype correlation analyses also demonstrated that the rs1051669 SNP was significantly associated with RAD52 protein expression levels. Therefore, it seems biologically plausible that the RAD52-rs1051669 SNP may be functional by regulating RAD52 expression and thus contribute to platinum resistance in cervical cancer patients.To the best of our knowledge, this is the first study that focused on the predictive value of Kaplan-Meier survival estimates further showed that patients who carried at least one (≥1) variant allele of three RAD52 SNPs had a significantly poorer PFS than those who did not carry any of the variant alleles, indicating the effect of RAD52 SNPs on the prognosis of CSCC patients. Because these variant genotypes may predict the protein expression, we hypothesized that RAD52 protein expression levels may predict survival in cervical cancer. However, in the present study, we did not observe any associations between single SNPs or RAD52 protein expression levels and survival, which might be due to the relatively short follow-up time with limited events of recurrences and deaths. However, some published data on other cancers do support our hypothesis, although no studies on cervical cancer have been published to date. Recently, Jewell et al. reported that the overexpression of RAD52 mRNA could predict poor PFS with a hazard ratio of 4.49 in melanoma and that cancer cells with upregulated genes of DNA repair pathways were likely to be more aggressive RAD52 SNPs, either individually or collectively, may modify gene function and alter RAD52 protein expression levels, thus rendering cancer cell resistant to platinum agents. Larger prospective studies with longer follow-up time are required to validate our findings.In summary,


Nicotiana attenuata plants deficient in jasmonate biosynthesis (irAOC) and empty vector controls (EV) to answer this question. Using both culture-dependent and independent techniques, we characterized root and leaf-associated bacterial communities over five developmental stages, from rosette through flowering of plants grown in their natural habitat. Based on the pyrosequencing results, alpha and beta diversity did not differ among EV and irAOC plants or over ontogeny, but some genera were more abundant in one of the genotypes. Furthermore, bacterial communities were significantly different among leaves and roots. Taxa isolated only from one or both plant genotypes and hence classified as ‘specialists’ and ‘generalists’ were used in laboratory tests to further evaluate the patterns observed from the field. The putative specialist taxa did not preferentially colonize the jasmonate-deficient genotype, or alter the plant's elicited phytohormone signaling. We conclude that in N. attenuata, JA signaling does not have a major effect on structuring the bacterial communities and infer that colonization of plant tissues is mainly shaped by the local soil community in which the plant grows.Jasmonic acid (JA) mediates defense responses against herbivores and necrotrophic pathogens but does it influence the recruitment of bacterial communities in the field? We conducted field and laboratory experiments with transformed  Plants are inhabited by diverse bacterial communities which live in and on the plant's tissues. Bacteria which have been clearly shown to colonize tissues internally are termed “endophytes”; though in literature the term has also been extensively applied to bacteria or DNA extracted from surface-sterilized plant tissue Endophytes or particular bacterial isolates can either have beneficial or detrimental effects on their hosts Bacterial communities are highly diverse among the different tissues, and they are found in seeds, roots, leaves, stems, tubers, ovules and fruits Arabidopsis plants and with contradictory results The phytohormones, salicyclic acid (SA), jasmonic acid (JA) and ethylene (ET) regulate responses to biotic and abiotic stresses Nicotiana attenuata), it was previously shown that the root-associated bacterial community is influenced by ET perception and production In coyote tobacco (N. attenuata (Solanaceae), a tobacco native to the Great Basin Desert that germinates after fires from long-lived seed banks to form monocultures in the nitrogen-rich soils of the post-fire habitat Manduca sexta) and generalist herbivores have been extensively studied M. sexta larvae elicits strong JA signaling which in turn leads to the production of various defense responses In this study, N. attenuata populations N. attenuata plants with normal (EV) and impaired JA-biosynthesis (irAOC) in their natural environment in Utah, USA, and harvested roots and leaves at 5 different developmental stages from rosette through flowering during the 2012 field season. Bacterial communities were retrieved by a combination of culture independent (pyrosequencing) and dependent approaches in-vitro conditions. We investigated the effect of JA signaling on the bacterial colonization, but also if inoculation influenced the levels of JA, SA and ET after elicitation of EV plants by treating fresh puncture wounds with M. sexta oral secretion (OSMS).In this study we used plants differing in endogenous JA levels grown in their native habitat and tested the hypothesis that variation in JA signaling defense pathways, a trait that is known to be variable amongst different genotypes found within native Nicotiana attenuata Torr. ex Watson empty vector plants , 107 from EV leaves  and102 from irAOC leaves . The surface sterilization procedure efficacy was assessed by plating aliquots of the sterile distilled water used in the final rinse onto nutrient agar medium  and incubated as described above. We did not observe any bacterial colonies on control plates.Two days after excavation from the field, bacterial isolation was carried out as described in edia SIM  and glucedia SIM . Plates - CTACCAGGGTAT CTAATCCTG -3′) was conducted with Big Dye Mix , and purification of the sequencing reactions was performed using the Nucleo-SEQ Kit . Analysis of all sequences was carried out in EzTaxon server  were pooled into one DNA sample : the concentration was determined by NanoDrop spectrophotometer, and diluted to a working concentration of 30 ng/µL before combining equal volumes. To evaluate the utility of 3 different primers, rosette-stage leaf and root samples were used. Bacterial 16S rRNA genes variable regions from V4–V9 were amplified by the following 3 primers sets: 515F-806R: GTGCCAGCMGCCGCGGTAA - GGACTACVSGGGTATCTAAT www.researchandtesting.com).Total genomic DNA was extracted from all surface-sterilized root and leaf tissues using FastDNA™ Spin kit for soil . DNA of biological replicates at the respective developmental stages of the EV and irThe QIIME software package was used to analyse the high-quality reads using default parameters for each step AOCL, EVR, irAOCR). QIIME script OTU significance test (ANOVA) was applied to find out whether OTUs based on 97% identity are significantly associated with a specific sample type. The Uni-Frac distance metric was calculated as a measure of bacterial community similarity −1 fresh mass (F-mass) of fresh roots or leaves, root length, plant biomass, leaf-surface area, and phytohormone levels  using Infostat 2010 Primer E software v.6 AOC, called ‘putative specialist’) and seven bacterial strains isolated from both genotypes, dubbed ‘putative generalists’, and Bacillus sp B55 from a previous study as positive control 600  = 1) and transferred to a Magenta™ vessel box  filled with sand  and grown in a Vötsch chamber . For single inoculations, seedlings of each genotype were individually inoculated with one of the selected 18 bacterial isolates or distilled water as control (600  = 1). Two weeks after inoculation the length of the primary roots and the plant biomass were determined and the leaf surface area was analyzed using Adobe Photoshop C5 In order to examine whether JA influences the colonization pattern of bacteria isolated from the field, we selected ten bacterial strains exclusively isolated from either of the plant genotypes  and irAOC plants , respectively. After surface-sterilization, EV seeds were incubated in bacterial solution and germinated as described above. Plants were grown according to M. sexta oral secretion Phytohormone production  was determined in EV plants inoculated with two bacterial isolates retrieved only from EV ; differences were due to discrepancies in bacterial communities among leaves and roots, but not genotypes. These findings are in accordance with the beta-diversity analysis of similarities  were higher in roots compared to leaves, while γ-proteobacteria dominated the bacterial community of leaves. In contrast, candidate division TM7-3 and Acidobacteria bacterial classes were only retrieved from roots across all developmental stages irrespective of genotypes. At genera level, the abundance of 14 OTUs was significantly different among roots and leaves . In summAOC roots  were only recovered from EV plants , while 38 species (227 isolates) were found in both genotypes, and these we considered as generalists. Furthermore, members of the genera Pseudomonas colonized more frequently in EV plants (58 isolates) than irAOC plants (22 isolates) over all developmental stages; whereas, the genera Kocuria was only retrieved from irAOC plants  their difference in abundance in the two genotypes in the pyrosequencing and the culture-dependent approach and b) the beneficial effects of some species described in literature  isolated only from EV plants in the field and two Kocuria species found only in irAOC plants . The production of all three phytohormones significantly increased after elicitation with OSMS compared to wound and water elicitation only   . HoweverIn nature, plants are subjected to various biotic and abiotic stresses throughout their development which in turn may influence the composition of the bacterial communities et al. Culture-independent approaches based on pyrosequencing are influenced by the primers and sequencing depth N. attenuataPseudomonas species decreased over development starting from young to senescent stages et al. Arabidopsis, which were grown in two different soil types in the glasshouse. This study also demonstrates that bacterial communities do not alter over developmental stages. We conclude that plant development does not have a major effect on community composition in native field grown N. attenuata plants.We tested the hypothesis that ontogeny alters community composition of roots and leaves, because inducible defense signaling mediated by JA is known to change dramatically at the rosette-flowering transition in ArabidopsisSerratia and Enterobacter heavily dominated the phyllosphere, while in many other studies Pseudomonas was the dominating genera Rhizobium and Azospirillum (15–25% abundance) which are well-known to dominate the root communities of nitrogen fixing plants may have a positive effect on plant growth and health In contrast to development, tissue type has a major effect on the bacterial community composition , Table 1et al. jar1 harbored significantly lower numbers of culturable bacteria compared to Co1-0 wild type, while a different study with the same Arabidopsis ecotype and a transgenic line impaired in the production of JA biosynthesis could not find any difference in the culturable leaf-associated bacterial communities N. attenuata plants are genetically diverse and individual plants of a population accumulate different amounts of JA after herbivore attack AOC genotypes AOC plants  against pathogens C plants . Unfortunts  established distinct bacterial communities. The colonization of plants by bacterial communities appears to be opportunistic, and mainly depending on the local soil microbe population. However, under specific circumstances (e.g. biotic and abiotic stresses) these opportunistic interactions may become mutualistic and help plants to adapt to these stresses, as has been recently shown by Meldau et al. This study demonstrates that the recruitment of root- and leaf-associated bacterial communities by Figure S1Base position of primers on 16S rRNA and primer comparison with regard to diversity of bacterial classes covered. The variable base positions on the 16S rRNA gene of the three different primer pairs tested . The number of bacterial classes (B), Margalef species richness (C) and Shannon diversity (D) recovered by primer 799F- 1394R was higher than for the two other primer pairs tested. Results are based on a pooled EV leaf and root samples. Abbreviations: R, roots; L, leaves; *, primer pairs selected for further analysis.(TIF)Click here for additional data file.Figure S2Rarefaction curves based on pyrosequencing reads, describing the observed number of operational taxonomic units (OTUs) as a function of the sequencing reads per each root and leaf samples. The OTU richness is higher in roots than leaves. Partial 16S rRNA gene sequences were pooled into single OTUs at the cut off value of 97% similarity. For abbreviations see (TIF)Click here for additional data file.Figure S3Root and leaf bacterial communities are independent of developmental stages. Alpha diversity indices were not significantly different among young and old developmental stages of EV and irAOC genotypes. Samples without stem (Rosette and elongated stage I) were merged as young and plants with elongated stems and flowering  pooled as old. Mean, ±SE, n = 2–3 different letters indicate significant differences, one-way ANOVA with Fisher's PLSD test; P<0.05.(TIF)Click here for additional data file.Figure S4EV and irAOC genotype putative bacterial specialist isolates identified by the culture-dependent technique. Two Pseudomonas species (P. frederiksbergensisA176 (Δ), P. koreensisA21 (Δ)) were only isolated from EV plants, and two Kocuria species  and K. marina D102 (◊)) only from irAOC field-grown plants in high numbers. These taxa were considered as putative specialists on their respective hosts. Mean (±SE), nd, not detected; n = 19. For the experimental set-up, harvest of plants and isolation of bacteria see (TIF)Click here for additional data file.Figure S5Inoculation with putative bacterial specialist isolates did not influence the different phytohormone elicitation. Phytohormone elicitation is independent of putative bacterial specialist inoculation. Elicitation of jasmonic acid , salicylic acid  and ethylene  was not significantly different among plants inoculated with the specialist bacterial isolates from EV and irAOC plants. Experimental design (A): Plants were seed-inoculated with different bacterial strains by incubating the seeds overnight in bacterial suspension (OD600 = 1). Rosette-stage EV leaves were wounded with a fabric pattern wheel followed by the application of oral secretion (OS) of Manduca sexta  or water (Wound + water) to punctured wounds to faithfully mimic M. sexta larva attack. JA levels were measured 60 min and salicylic acid 120 min after treatment. Ethylene accumulated for 5 h after elicitation. Mean ±SE; FM, Fresh mass; n = 5.(TIF)Click here for additional data file.File S1Table S1,S2, S4, S5, S6: Table S1. Average rosette diameter and stalk length of native field grown N. attenuata at the time of harvest. Table S2. Cultured putative specialist and generalist bacterial isolates used in this study. Table S4. Uni-Frac beta diversity is not significantly different among developmental stages of EV and irAOC genotypes tissues indicating that bacterial communities are independent of developmental stages. Table S5. Pairwise ANOSIM did not differ significantly among rosette (young) and elongated, flowering (old) developmental stages. Table S6. List of OTUs significantly different among EV and irAOC leaves and roots at genera (or higher) level retrieved by pyrosequencing.(PDF)Click here for additional data file.Table S3Abundance of culturable bacterial species from surface-sterilized roots and leaves of EV and irAOC genotypes over different plant developmental stages.(XLSX)Click here for additional data file.


EHP 119(8):1077–1083; Ayotte et al.]. The results suggested an inhibitory effect of methylmercury on paraoxonase 1 (PON1), an enzyme whose activity may protect against cardiovascular problems. They also hinted unexpectedly that dietary nutrients, especially selenium, may counteract effects of methylmercury on PON1 activity. PON1 breaks down the oxidized lipids that may promote atherosclerosis.Inuit people living in Canada’s Nunavik region consume large doses of methylmercury through their traditional diet, mostly from sea mammal meat. A new study set out looking for evidence of links between these native communities’ exposure to the toxic metal and heart diseases [The researchers collected blood plasma samples from nearly 900 people living in about 500 households in different communities across Nunavik. Each person provided biological samples and completed surveys on their medical history, diet, and lifestyle habits.in vitro studies. So the researchers turned to multivariate statistics to untangle other factors that might confound the mercury/PON1 relationship. These include intake of omega-3 polyunsaturated fatty acids (n-3 PUFAs) and selenium, important nutrients provided by the traditional Inuit diet.A simple correlation analysis indicated that higher blood mercury was associated with higher PON1 activity, contrary to findings from earlier In the multivariate model, higher blood mercury levels were associated with decreased PON1 activity whereas higher blood levels of n-3 PUFAs and selenium were associated with increased PON1 activity. The researchers also observed that PON1 activity decreased with age of participants, as previously reported in other populations.muktuk (skin and fat). The researchers suggest that n-3 PUFAs and selenium in the Inuit diet may offset the inhibition of PON1 activity by methylmercury.Fish and sea mammal fats carry n-3 PUFAs that are beneficial for heart health, and have been known for some time to be a key nutrient in the traditional Inuit diet. This diet also includes such high-selenium foods as beluga whale But as native populations shift to “modern” diets—for example, eating more fast food and prepackaged meals—the dietary balance between these nutrients and methylmercury could change, the researchers caution. For instance, if an individual consumes less dietary selenium, the negative effects of methylmercury may intensify. The researchers emphasize that followup studies are necessary to monitor dietary changes and cardiovascular health among these Arctic communities.


Modern functional genomics uncovered numerous functional elements in metazoan genomes. Nevertheless, only a small fraction of the typical non-exonic genome contains elements that code for function directly. On the other hand, a much larger fraction of the genome is associated with significant evolutionary constraints, suggesting that much of the non-exonic genome is weakly functional. Here we show that in flies, local (30–70 bp) conserved sequence elements that are associated with multiple regulatory functions serve as focal points to a pattern of punctuated regional increase in G/C nucleotide frequencies. We show that this pattern, which covers a region tenfold larger than the conserved elements themselves, is an evolutionary consequence of a shift in the balance between gain and loss of G/C nucleotides and that it is correlated with nucleosome occupancy across multiple classes of epigenetic state. Evidence for compensatory evolution and analysis of SNP allele frequencies show that the evolutionary regime underlying this balance shift is likely to be non-neutral. These data suggest that current gaps in our understanding of genome function and evolutionary dynamics are explicable by a model of sparse sequence elements directly encoding for function, embedded into structural sequences that help to define the local and global epigenomic context of such functional elements. function-selection gap can be attributed to sequences that facilitate the physical organization of functional elements, such as transcription factor binding sites, within chromosomes. We exemplify this by studying in detail the sequences embedding small conserved elements (CEs) in Drosophila. We show that, while CEs have typically high AT content, high GC content levels around them are maintained by a non-neutral evolutionary balance between gain and loss of GC nucleotides. This non-uniform pattern is highly correlated with nucleosome organization around CEs, potentially imposing an evolutionary constraint on as much as one quarter of the genome. We suggest this can at least partly explain the above function-selection gap. Weak evolutionary constraints on “structural” sequences  may affect genome evolution just like structural motifs shape protein evolution.A key challenge in functional genomics is to predict evolutionary dynamics from functional annotation of the genome and vice versa. Modern epigenomic studies helped assign function to numerous new sequence elements, but left most of the genome essentially uncharacterized. Evolutionary genomics, on the other hand, consistently suggests that a much larger fraction of the un-annotated genome evolves under selective pressure. We hypothesize that this  The molecular function of metazoan genomes has been studied extensively in the last decades, using progressively more extensive and sensitive techniques for profiling genome activity, modeling epigenomic organization and perturbing genome sequences. Genomes have been found to encode regulatory information affecting diverse functions, including gene expression, chromatin structure, recombination and replication. Despite this progress, only a small percentage of the e.g., fly, or human genome is annotated specifically with a well-defined molecular role. Comparative genomics and population genetics studies, however, estimate that 10–15% Saccharomyces cerevisiae, which is 200-fold smaller than the human genome, is packed with genes (covering 73% of the genome) leaving almost all of the intergenic genome to be in close proximity (89% within 1 kb or less) to a transcription start site or 3′ UTR element. Nevertheless, regulatory sequences with direct functional annotation (e.g. transcription factor binding sites) cover just a small minority of the implicated regulatory sequence. The remaining sequences have seemingly little encoding specificity and are typically viewed as wrappers for the “real” regulatory encoding or evolutionary leftovers of ancient functional sequences. Recent progress with the mapping and analysis of local chromatin structure next to transcription start sites showed that nucleosome packaging is correlated with transcription, and likely affecting gene expression and other biological processes. These data suggest that the functionality of regulatory sequences is modulated by the organization of nucleosomes around or over them in-vitro and in-vivo) The genome of the yeast Drosophila genome is 10-fold larger than the yeast and 20-fold smaller than the human genome. The fly genome was one of the first to be screened genetically and sequenced completely Larger genomes encode regulatory information in a more dispersed and sparse fashion. The Drosophila melanogaster, we support the idea that about 25% of the fly non-exonic genome consists of sequences that embed highly conserved elements, and likely to evolve under weak selection that maintains localized GC content . According to our model, a punctuated GC content increase around CEs is created and stabilized by the evolutionary dynamics of compensatory GC loss and GC gain substitutions. Considering structural and epigenomic constraints in models of genome evolution may contribute significantly to our understanding of genome function and how this function evolves.In this study, we show that a substantial fraction of the fly genome is likely to evolve under “structural” constraints. We identify putative regulatory sequences by screening highly conserved elements using our recently published parameter rich probabilistic evolutionary model Genome composition is associated with the underlying genomic functional annotation across multiple taxa, from yeast to mammals Drosophila genomes was designed to take full account of substitution rates variation among lineages and genomic contexts Drosophila species. This modeling and inference strategy ensures proper control for global biases in substitution rates at high or low GC content regions. We defined foci of genomic conservation as contiguous regions showing at least two-fold decrease in normalized divergence, identifying 67780 conserved elements (CEs) with an average size of 50 bp . These conserved elements are enriched within enhancer associated transcription factors binding sites , PH, H3K27Me3, and H3K9Me3 (see methods)). We derived classes of CEs that were associated with several previously characterized epigenetic behaviors, including classes associated with promoter marks . To veriDrosophila genomes. We reconfirmed that on a scale of 1 kb, substitutions of the same type tend to cluster together  were not found to be frequent in these loci. Despite the seemingly specific enrichment of CA repeats in the context of CEs, normalization of microsatellite frequency given the observed nucleotide compositions around CEs n, (CAA)n, (A/T)n) are in fact enriched around CEs at remarkably similar levels. This suggests that enrichment of simple repeats is a general property of the sequences flanking CEs, and is unrelated to the properties of particular dinucleotides. Several mechanisms may underlie this phenomenon, including higher rates of short insertion and deletion mutations in regions with an active chromatin structure The analysis discussed above focused on evolutionary dynamics at the nucleotide composition level. This approach provides the simplest description of the structure and evolution of sequences embedding CEs in flies, but it may be biased or incomplete if more complex sequence elements are evolving non-neutrally around CEs. Indeed, several frequent sequence motifs, most notably poly-A/T tracts and CA repeats were suggested before to modulate genome structure through regulation of epigenomic organization Drosophila data are also active around regulatory elements in mammalian genomes, although their intensity may be decreased due to the sparser genomic structure. Indeed, recent reports on the evolutionary dynamics near mammalian nucleosomes Finally, we surveyed the association between local GC content and allele frequencies in human and mouse, aiming to test if similar trends as those defining the embedding of CEs in flies may affect mammalian genome structure. In mammalian genomes functional elements are sparser, and the estimated overall evolutionary constraint is considerable Drosophila species, with epigenomic data and sequence analysis to show how highly localized, 30–70 bp conserved elements (CEs) in the non-exonic fly genomes are embedded into the genomic sequence in an organized and structured fashion. We showed that CEs are typically located within a few hundred bp of elevated GC content regions, but that the CE itself is punctuating this pattern with a sharp increase in AT content. The substitution patterns supporting this highly non-uniform organization are modulating the processes of GC gain and GC loss such that the immediate flanking of the conserved elements has GC gaining substitutions in relative excess. We discovered local compensatory coupling of GC gaining and GC losing substitution on a scale of up to 20–40 bp . Furthermore, analysis of polymorphic sites identified a remarkable association between highly local (20 bp) GC content and the allele frequencies of GC gaining and GC losing mutations, a phenomenon that is recapitulated in analysis of human and mouse data.We have combined inference of context-dependent substitution rates in GC content is amongst the most thoroughly explored and modeled genomic phenomena. It is known to be correlated with recombination rates n and other microsatellite repeats n, but few (TA)n) evens out when considering the nucleotide composition in these regions. Instead of enrichment for specific repeats, that could have suggested these elements have specific functional roles, we observed consistent increase in the frequency of all microsatellites families. In contrast to the patterns of punctuated GC content increase discussed above, CE-linked repeat elements could not be associated with signatures of non-neutral evolution. We therefore hypothesize that the accumulation of microsatellites around CEs is explained by either an increased mutation rate, or decrease in the efficiency of purifying selection due to the powerful evolutionary dynamics and epigenomic characteristics of functional elements.While multiple lines of evidence  suggested that the evolution of sequences surrounding functional elements in flies is affected by selection, complete characterization of the evolutionary dynamics in these regions is still challenging. For example, powerful selection on the functional elements themselves may result in recurrent selective sweeps or other effects originating from the linkage between the elements' cores and their sequence contexts. These may alter the divergence and polymorphism patterns around the cores of functional elements. Furthermore, DNA replication and repair processes may be affected by the element's polarized chromatin structure, resulting in higher or lower rate of mutation, or in variation of the mutation spectrum. Our data suggest that these considerations play a major role in at least one aspect of the sequence composition around functional elements, namely, the documented enrichment of (CA)codes that facilitate their functions, but in order to transform these codes into physical molecules, sequences must also contain structural elements that allow the codes to be interpreted Drosophila. We hypothesize that classical enhancer elements, which encompass several hundred base pairs and are capable of driving tissue specific transcription or repression given appropriate trans- factor activity, may contain one or few small (order of 10 bp) code words capable of recruiting such factors, embedded into larger and more diffused sequences that support the epigenetic organization of the enhancer region. Such epigenetic organization may involve local nucleosome occupancy and stability, as well as more complex interaction of the enhancer with remote elements , gene annotation data and annotation of repetitive elements were downloaded from the UCSC genome browser The epigenomic data was smoothed by averaging the data values in each non-overlapping adjacent twenty base pairs. DHS data were then smoothed in 200 bp windows (with overlaps). All data were then normalized using the following non parametric transformation:DHS sites were defined as TSS distal non exonic loci (TSS distance>1000) of DNase I levels higher than the 0.992 percentile in at least one of the embryonic stages . Note that this set was defined to represent the distribution of active regulatory regions, but is not intended to be generating an exhaustive set of elements. We used only TSS distal to DHS solely for the purpose of comparison between DHS and TSS patterns. dRing peaks were defined as non-exonic loci with dRing levels higher than the 0.995 percentile in S2 or BG3 cell lines. H3K27Ac peaks were defined as non-exonic loci with H3K27Ac levels above the 0.995 percentile in one or more embryonic stage .Drosophila clade (http://compgenomics.weizmann.ac.il/tanay/?page_id=169). As described in Chachick et al Drosophila lineages) and the number of substitution expected given the probabilistic model. By comparing observed and expected number of substitutions in overlapping windows of 20 bp we estimated the degree of evolutionary conservation while controlling for biases associated with variable divergence rates in different nucleotide contexts.We used our recently described context-dependent substitution model to compute conservation scores at one bp resolution across the Conserved hotspots were defined as non-exonic loci where the estimated number of observed substitutions is two-fold smaller from the expected number of substitutions. Following expansion of each hotspot by 10 bp to each direction we merged resulting overlapping intervals. Conserved elements (CEs) were then defined as unified genomic intervals spanning over 30 bp. Average profile of observed and expected divergence scores around regulatory elements are shown in Given a loci set L we define, for each genomic location i its minimal distance from L as:Nucleotide composition profiles of Enrichment scores of several epigenetic marks over CE were calculated by taking the average enrichment values of 9 epigenetic marks: DHS (embryonic stage 10), H3K4Me1 , H3K4Me3 , H3K27Ac , ORC , SuHw -HB.S2 of modEncode), PH (4–12-h) 2 microsatellites (e.g. (CA)n, (GA)n). These sequence elements generate strong signatures that were studied separately tely see . After eWe used our context aware and lineage specific evolutionary probabilistic model to estimate posterior probabilities for individual nucleotides Depending on the analysis, loci were further grouped to compute the evolutionary trends around them.D. melanogaster and D. yakuba were extracted from the fly 12 species multiple alignment, omitting loci of insertion and deletion between these species. We computed the GC content difference at each locus  as follows:Aligned sequences of We then selected a distance parameter d, excluded loci of NA values, and computed the coupling score for d as:g scores  assumingD. yakuba lineage. Non exonic genomic sequences were screened for loci of GC gain and GC loss on the D. yakuba lineage by the following criteria:To validate the spatial association between GC gain and GC loss substitutions, we used posterior substitution probabilities, computed as outlined above, and focused on the dynamics in the We then estimated the rate of different substitution types (gaining GC or losing GC), conditioned on the existence of GC gain or loss event within a distance (one sided) of at most d nucleotides :http://www.hgsc.bcm.tmc.edu/projects/dgrp/freeze1_July_2010/). This dataset D. melanogaster lines. SNPs of more than two distinct alleles were excluded. To minimize the contribution of sequencing errors, we also excluded very rare SNPs (p<0.01) and SNPs with low average coverage (<10). We defined the major and minor alleles of each locus by their relative abundance in the population. Non exonic and non-repetitive SNPs were divided into 20 bins by the local GC content (20 bp) of their genomic location according to the reference genome.Fly SNP data were downloaded from DGRP website :For further control, SNPs were divided into cubic bins by the local GC content of two scales: 20 bp (20 bins)×200 bp (5 bins)http://hapmap.ncbi.nlm.nih.gov/downloads/genotypes. Mouse SNP http://www.sanger.ac.uk/resources/mouse/genomes/. SNPs that fell within repetitive elements (as defined by UCSC genome browser) were excluded. We defined the major and minor alleles of each locus by their relative abundance in the population. Non-exonic and non-repetitive SNPs were divided into cubic bins by the regional GC content of two scales: 20 bp (5 bins)×1 kb (5bins).Human SNP data Frequency of rare allele of a N→N′ SNP is defined as:Figure S1drosophila species as a function of distance from the nearest TSS. While the divergence is lower near TSSs (more conserved), the 1 kb region upstream to TSS is highly diverged comparing to the background rate of evolution, reaching the maximum rate ∼150 bp upstream to TSS. E) Enrichment of transcription factor binding sites in CEs. Enrichment of REDfly experimentally validated transcription factor binding sites Fly regulatory elements are characterized by increased GC content and non-uniform evolutionary dynamics. A–C) Nucleotide composition around regulatory elements is shown versus the distance (x-axis) to the center of the nearest peak of A) H3K4Me1, B) H3K27Ac and C) dRing. The data showed that GC content is enriched over a region spanning ∼0.5 kb around regulatory elements of different classes. D) Increased substitution rates in fly promoters. Shown is substitution probability inferred from analysis of 12 (TIF)Click here for additional data file.Figure S2Classes of CE sequence compositions support the universality of the punctuated GC elevation pattern. CEs were clustered using k-means given their nucleotide composition patterns . Shown a(TIF)Click here for additional data file.Figure S3melanogaster group lineages. Solid lines are color coded according to the substitution types A→C (black), A→G (red), A→T (green), C→A (blue), C→G (cyan), C→T (magenta). Dotted lines represent the complementing mutations. B) Association between GC gain and loss. We quantified the spatial coupling between GC gain and loss substitutions over the D. yakuba lineage, by estimating the rate of one type of substitution , conditioned on the existence of another type of substitution at a certain distance from it  Inferred substitution rates around CEs. Shown are substitution rates of all mutation types versus the distance from the nearest center of conserved element averaged over the  X axis, . The rat(TIF)Click here for additional data file.Figure S46 B) (AT)3 or (TA)3 C) (CA)3 or (AC)3 D) (GA)3 or (AG)3. Due to their strong enrichment around CEs, the sequence flanking e.g., CA repeats are highly implicated in conservation. As shown in Divergence rates around microsatellites. Observed divergence rates (solid curves) and expected divergence rates  versus the distance (x-axis) to the nearest A) (A)(TIF)Click here for additional data file.Figure S5A–B) Polymorphism patterns in human (A) and mouse (B) support non neutral evolution of GC content in mammals. Shown is the frequency of rare alleles p of different mutation types (rows) versus local (20 bp) GC content (X-axis). Analysis is stratified over regional (1 kb) GC content (columns of panels). Gray curves represent 95% binomial confidence intervals. While biased gene conversion or recombination intensities are known to be correlated with GC content and can thereby indirectly contribute to the association between GC content and the frequency of rare alleles, the data here suggest that small scale GC content is significantly linked with an increase in rare allele frequency independently of these effects. C) Large fraction of the genome is affected by conserved elements and associated structural sequences. Percentages of Exonic DNA , CEs  CE surrounding  and remaining DNA (60.9 Mb 50.5%). More than 33% of the non-exonic sequences are CE associated sequences.(TIF)Click here for additional data file.Table S1Enrichment of different epigenetic marks over CEs. Log2 ratios of averages of 315 analyzed epigenomic marks (column A) between CEs and randomized intervals of the same lengths (column B) and comparing to the regional levels  of the same marks (column C).(XLS)Click here for additional data file.Table S2Epigenomic CEs cluster xii lacks enrichment of epigenetic marks over. Similar to S1, but here enrichment of epigenomic marks are only for CE's within epigenomic cluster xii. The table shows that enrichments are significantly low comparing to overall enrichments.(XLS)Click here for additional data file.Table S3Exhaustive 6-mer screen around conserved elements. Frequency of each 6-mer within CEs and at 50 bp distance bins around conserved elements.(XLS)Click here for additional data file.


In individuals coinfected with the defective hepatitis Delta virus (HDV) the small HDV-RNA-genome and Delta antigen circulate as ribonucleoprotein complexes within HBsAg subviral particles. We addressed the question whether subviral HBsAg particles may carry in the same way cellular microRNAs (miRNAs) which are released into the bloodstream within different subcellular forms such as exosomes and microvescicles. Circulating HBsAg particles were isolated from sera of 11 HBsAg carriers by selective immunoprecipitation with monoclonal anti-HBs-IgG, total RNA was extracted and human miRNAs were screened by TaqMan real-time quantitative PCR Arrays. Thirty-nine human miRNAs were found to be significantly associated with the immunoprecipitated HBsAg, as determined by both comparative DDCT analysis and non-parametric tests  with respect to controls. Moreover immunoprecipitated HBsAg particles contained Ago2 protein that could be revealed in ELISA only after 0.5% NP40. HBsAg associated miRNAs were liver-specific  as well as immune regulatory (most frequent = miR-106b and miR-223). Computationally predicted target genes of HBsAg-associated miRNAs highlighted molecular pathways dealing with host-pathogenHepatitis B virus (HBV) produces high quantities of subviral surface antigen particles (HBsAg) which circulate in the blood outnumbering virions of about 1\10The finding that HBsAg particles carry selective pools of hepatocellular miRNAs opens new avenues of research to disentangle the complex interactions between host and HBV and provides a non invasive tool to study the physiopathology of liver epigenetics. Yields of serum HBsAg depletion were then calculated as % ratio between OD values of starting sera and corresponding leftovers. Results were confirmed by quantitative Architect HBsAg assay (Abbott Laboratories) Western blotting analysis was performed on all samples or on pooled samples, in order to evaluate possible serum contaminants by exosomes. In particular, protein lysates were prepared in 1% SDS-lysis buffer supplemented with protease inhibitors. Lysates were mixed with 1 volume of 2× SDS sample buffer, denatured, loaded on 12%SDS-PAGE, and blotted onto nitrocellulose filters . Filters were hybridized with one of the following primary antibodies: mouse monoclonal anti-HBs , rabbit polyclonal anti-CD63  or rabbit monoclonal  anti-Ago2. This was followed by hybridization with secondary anti-mouse or anti-rabbit HRP-conjugated antibody , and detection of chemiluminescent reaction .Serial 1\10 dilutions (in PBS with an without 0.5% NP40 detergent) of the immunoprecipited fractions (IP) from HBsAg positive and negative sera were tested for Ago2 protein using the 96-well microplates of the HBsAg Elisa Kit  coated with monoclonal anti-HBs antibody.The assay was carried out according to the protocols of the manufacturer's taking care to maintain the same incubation time for all the samples in testing. IP sample dilutions were incubated for 120 min at 37°C and after washing additional incubations for 60 min at 37°C were performed respectively for rabbit anti-Ago2 HRP conjugated antibody and rabbit anti-CD63 HRP conjugated antibody, used as control. After the cromogen\substrate incubation optical density was measured using a calibrated microplate reader equipped with a 450 nm filter and a second filter (620–630 nm) for banking and the S\N 2.1 ratio as positive\negative cut-off.spike-in miRNA  before RNA isolation following the manufacturer's protocol. The quantity and quality of RNA samples were assessed either by spectrophotometer at OD260/280 (NanoDrop Technologies Inc.) or with Quant-iT RiboGreen RNA assay (Invitrogen). Profiling of miRNAs was carried out using TaqMan-based real time quantitative PCR  as previously described T values with and without the pre-amplification step and a very good reproducibility (data not shown). Pre-amplified products of reverse transcription were finally mounted on 384 microfluidic cards containing the TaqMan Low Density Arrays  for amplification. RT-qPCR reactions were run on ABI Prism 7900HT equipped with SDS software v2.3. Screening of miRNAs in control immunoprecipitates  was used to determine aspecifically immunoprecipitated serum miRNAs for the comparative ΔΔCT analysis of data.Total RNA was isolated from all samples  by the mirVana miRNA Isolation kit (Ambion). After treatment with the mirVana miRNA Isolation kit lysis buffer, samples were added with 3.5 femtomolar 10 using miR-181a and miR 182c as internal references http://microrna.samger.ac.uk/). The miRNA levels were calculated according to ΔCT values where ΔCT = mean −Ct of target miRNA.Quantification of miR122 levels was performed in duplicate on pellets and sera of HBsAg positive and negative subjects by TaqMan qRT-PCR assay on an Applied BioSystems 7300 HT thermocycler as previously reportedT values were calculated using the SDS software v.2 and exported as “Amplification Data” text files for each sample. Exported data were processed with Excel. The global raw CT values are available in a matrix format as tab delimited text file. As long as each miRNA in each sample was considered as detected only for values of CT<35 T≥35 were replaced with the chosen threshold of CT = 35. Normalization was performed against spike-in ath-miR-159a: the mean of ath-miR-159a amplifications (two for each sample loaded and amplified on the 384 microfluidic card) was used as the computed control, and the change in cycling threshold was calculated for each miRNA (ΔCT = CT_miRNA−CT_ath).Raw CT calculations were generated from ΔCT values. In particular, unsupervised hierarchical clustering either on the whole miRNA dataset or on significant miRNAs was performed by using the uncentered Pearson correlation coefficient and complete linkage. When comparing two groups, a non-parametric Mann-Whitney test was used to rank differentially expressed miRNAs, as required by data normality. For all tests, a p<0.05 was considered significant.Both statistical analyses  and the comparative ΔΔCT method as in the following algorithm: a) since all control immunoprecipitation samples clustered together and were clearly separated from the HBs-IP+ samples (T) was calculated across the calibrator subset ; c) the HBsAg positive pellets (n = 11) were considered as target subsets, and ΔCT values in each sample were compared to average ΔCT values of the calibrator subset to generate ΔΔCT values; d) ΔΔCT values were then used to calculate the relative quantities (RQ = 2−ΔΔCt) between the calibrator group and the target subsets. For rendering reasons, RQ values were rescaled in a logarithmic scale (base 10); e) we choose a cutoff of 0.5 Log(RQ) corresponding to 3.16 RQ, so that only RQs above this threshold were taken into account; these selected RQs were used for studying the distribution of HBsAg-associated miRNAs among different hepatitis B infection and disease phases.The pools of miRNAs associated with immunoprecipitated HBsAg were determined by the comparative ΔΔCT analysis was aimed at defining the circulating HBsAg-miRNA signature, we made further selection on miRNAs as follows: a) only those miRNAs with RQs that were successfully selected as described above in at least 2 of the profiled HBsAg positive IP samples were further considered; b) next, average RQs of such selected miRNAs were calculated across the target HBsAg positive IP samples along with SD and represented as rescaled logarithmic base 10 plot.When the comparative ΔΔCT values calculated across the target HBsAg positive IP samples versus the average ΔCT values calculated across the calibrator control HBsAg negative immunoprecipitates.A further refinement of the overall circulating HBsAg-miRNA signature was made by selecting miRNAs with a non-parametric Mann-Whitney test (p<0.05) on the average Chttp://www.targetscan.org), taking into account only conserved target sites. Predicted genes were then ranked on the basis of a combined parameter  obtained by multiplying the TargetScan total context score by the number of conserved sites. To avoid exceeding the number of both gene list and predicted pathways, only targets with multiplicative values ≤−1 were selected and used as input list for functional pathway exploration by Ingenuity Pathway Analysis (IPA) software . IPA-generated top-ranked pathways were determined on the basis of the incidence of predicted miRNA targets in a list of canonical pathways provided by the IPA software. Canonical pathways thus obtained were ranked according to their significance in a Fisher exact test (p<0.05).Targets prediction was performed for each HBsAg-associated miRNA of the overall circulating HBsAg-miRNA signature by TargetScanHuman, release v5.1  profiling studies, high yields were important to meet sensitivity of real time quantitative PCR (RT-qPCR). To this aim, sepharose-protein G resin was employed as solid phase for the immunoprecipitation reaction because of its high IgG binding capacity, which allowed for both efficient elimination of IgG contaminants from sera as well as quantitative depletion of HBsAg from sera. Best immunoprecipitation conditions were obtained by comparing different antibody-to-resin ratios (from 1 µg to 10 µg of antibody every 200 µl of sepharose-protein G slurry) as well as different starting dilutions of sera . In order to evaluate best quantitative yields and determine reproducibility of HBsAg recovery from sera, we measured serum HBsAg depletion before and after each immunoprecipitation by a commercial HBsAg-specific Elisa. For each immunoprecipitation condition considered, analysis was taken on both individual and pooled samples. As long as we found that best working antibody-to-resin ratio was 5 µg of antibody every 200 µl of sepharose-protein G slurry (not shown), we kept this parameter for further fine tuning of the immunoprecipitation conditions , and purity of HBsAg preparations was as important as quantitative high yields. Therefore, in setting the HBsAg isolation conditions, a series of control immunoprecipitations were also undertaken to assess possible serum contaminants and improve specificity. Western blotting analysis indicated that HBsAg protein were not present into the immunoprecipitated fractions of control IPs .We looked for the presence of RISC-associated Argonaute2 (Ago2) protein into the immunoprecipitated fractions by Western blotting, and we found that Ago2 was associated with HBsAg positive IP , but notBased on these overall results, the best HBsAg isolation condition  was used throughout the whole study as it provided highest HBsAg immunoprecipitation yields, optimal specificity, as well as purity.T) expression values. Raw CT data were then computationally processed as described in spike-in ath-miR-159a as internal standard. The choice was compelled by our experimental system (virus-related particles), which rendered impractical the use of established human endogenous/housekeeping genes , as well as by the fact that to date no established viral miRNA gene from HBV has been assayed and measured. Moreover, the use of HBV-DNA amplification by RT-qPCR was considered inefficient because a) the HBs-immunoprecipitation involved all the repertoire of HBsAg-positive circulating particles, namely virions and defective particles, with great variability of the two fractions from sample to sample; b) viral load (HBV-DNA serum levels) varies in relation to HBV infection and disease phase. On the contrary, the exogenous standard ath-miR-159a assured for technical normalization while being independent of biological variability, and its use as normalization factor was validated in our hands by convergent results with the global mean approach (not shown) which has recently been accepted for miRNA profiling of biological systems lacking endogenous controls.To evaluate the presence of human miRNAs within immunoprecipitated HBsAg fractions, we used RT-qPCR methodology associated with TaqMan miRNA Arrays which encompass 664 mature miRNAs from the Sanger mirBase v.10.1. The whole repertoire of human miRNAs was screened in each sample by RT-qPCR to obtain raw cycle-threshold (CT) for unsupervised hierarchical clustering  built up on the result of the HCL analysis. These observations indicated the presence of human miRNAs specifically associated with immunoprecipitated HBsAg particles and prompted us to characterize miRNA profiling.When analyzing normalized expression values  values which describe the ratio of miRNA average expression levels between each target HBsAg positive IP sample and the calibrator subset. Only RQs whose value overwhelmed a fixed threshold of 3.16 (corresponding to a more than three-fold expression level in each HBsAg positive IP sample with respect to control IPs) were further selected. As further stringency in the comparative DDCT analysis, we considered only those miRNAs with successfully selected RQs in at least 2 of the profiled HBsAg positive IP samples. Finally, average RQs of thereby selected miRNAs were calculated across the target HBsAg positive IP samples along with SD, and represented as rescaled logarithmic base 10 plot  and lymphocytes  On the basis of these considerations, the analysis of target genes of HBsAg-associated miRNAs and the related functional pathway analysis provided results which are strongly compatible with the biological activity of the identified miRNAs. In fact, computationally predicted target genes of HBsAg-associated miRNAs appeared significantly involved into molecular mechanisms canonically dealing with host-virus interaction, such as clathrin-mediated endocytosis, virus entry, and dendritic cell maturation. Interestingly, the finding that host-virus interaction pathways are over-represented among predicted targets of HBsAg associated-miRNAs suggests the intriguing hypothesis that circulating HBsAg particles carrying host cellular miRNAs might have an important role in the complex mechanisms of viral spreading, persistence and pathogenesis. This hypothesis is consistent with the evidence that HBsAg serum levels, resulting from the equilibrium between virus and host's immune system, vary in the different phases of HBV infection and reach the lowest values in the inactive HBsAg carriers In conclusion, the finding that HBsAg particles carry hepatocellular miRNAs opens new avenues of research to disentangle the complex interaction between host and HBV. HBsAg associated-miRNAs might play a pivotal role in viral persistence and help to explain the clinical evidence that the most efficient immune control of HBV infection associates with the loss of serum HBsAg. Profiling the in vivo HBsAg-associated miRNAs dynamics in different cohorts of HBsAg carriers provides a unique model for studing the epigenetics of liver physiopathology in viral and non viral diseases.