Further characterization of bovine hepacivirus: Antibody response,course of infection,and host tropism

Bovine hepacivirus (BovHepV) is a recently added member to the growing genus Hepacivirus within the family Flaviviridae. Animal hepaciviruses are rarely characterized so far. Apart from norway rat hepacivirus which represents a promising HCV surrogate model, only equine hepaciviruses have been studied to some extent. BovHepV has been initially identified in bovine samples and was shown to establish persistent infections in cattle. However, consequences of those chronic infections, humoral immune response and the possibility of an extended host spectrum have not been explored so far. Therefore, we here investigated (a) the presence of anti‐NS3‐antibodies and viral RNA in cattle herds in Germany, (b) the course of infection in cattle, and (c) the host tropism including zoonotic potential of bovine hepaciviruses. Our results show that 19.9% of investigated bovine serum samples had antibodies against BovHepV. In 8.2% of investigated samples, viral RNA was detected. Subsequent genetic analysis revealed a novel genetic cluster of BovHepV variants. For 25 selected cattle in a BovHepV positive herd the presence of viral genomic RNA was monitored over one year in two to three months intervals by RT‐PCR in order to discriminate acute versus persistent infection. In persistently infected animals, no serum antibodies were detected. Biochemical analyses could not establish a link between BovHepV infection and liver injury. Apart from a single sample of a pig providing a positive reaction in the antibody test, neither BovHepV‐specific antibodies nor viral RNA were detected in porcine, equine or human samples implying a strict host specificity of BovHepV.     

丙型肝炎病毒不同片段抗体蛋白芯片的制备及评价

目的: 制备丙型肝炎病毒(hepatitis virus C, HCV)不同片段抗体蛋白芯片,并对其临床应用价值进行评价. 方法: 分别取HCV融合抗原及分片段抗原,点至醛基化玻片上,制成HCV不同片段抗体蛋白芯片. 进行抗-HCV(ELISA)试剂和RIBA试剂与蛋白芯片法的比较. 结果: 蛋白芯片的融合抗原检测与ELISA法相比,阴性符合率为93.8 %,阳性符合率为97.1% . 蛋白质芯片分片段检测与ELISA法相比,阴性符合率为96.8 %,阳性符合率为97.1%. 蛋白芯片的融合抗原检测与RIBA法相比,阴性符合率为96.9% , 阳性符合率为98.5 %. 蛋白芯片分片段检测与RIBA法相比,阴性符合率为100%, 阳性符合率为98.5%. 结论: 蛋白芯片法与RIBA试剂检测结果相比较,与RIBA试剂有良好的一致性(P<0.05)),证明其具有良好的检测准确率,并可以降低ELISA法的假阳性.     

丙型肝炎病毒NS5A反式激活蛋白7的重组表达及生物信息学分析

目的 构建丙型肝炎病毒NS5A反式激活蛋白7(NS5ATP7)的原核表达载体,诱导其在大肠埃希菌中的表达,并初步探讨其结构与功能.方法 应用逆转录PCR(RT-PCR)技术,以HepG2细胞mRNA为模板,扩增获得NS5ATP7基因片段,连接到pGEM-T载体,酶切鉴定及测序正确后插入至原核表达载体pET-32a( )中,转化大肠埃希菌BL21,IPTG诱导以获得NS5ATP7融合蛋白的表达,SDS-PAGE、Western blot免疫印迹分析和证实该融合蛋白表达的特异性,并应用生物信息学方法对该融合蛋白的结构和功能进行预测.结果 利用RT-PCR扩增获得大小为891bp的NS5ATP7基因片段,插入pET-32a( )表达载体,转化BL21宿主菌,经IPTG诱导,成功获得了大小为48kD的目的蛋白,Western blot进一步证实了该蛋白具有特异性免疫反应识别.生物信息学预测结果显示此蛋白富含螺旋结构,为非跨膜蛋白,无信号肽.结论 利用大肠埃希菌BL21成功表达了NS5ATP7融合蛋白,结合生物信息学分析结果,为研究NS5ATP7蛋白的免疫原性和生物学特性奠定了基础.     

丙型肝炎病毒CTL表位基因真核表达载体的构建及稳定转染细胞系的建立

目的构建含丙型肝炎病毒（HCV）复合多表位基因的真核表达载体,转染CHO细胞,建立稳定转染细胞系。方法通过生物信息学预测分析的方法得到涵盖HCV不同基因型与小鼠H2复合体的多个细胞毒性T淋巴细胞（CTL）表位,串联后人工合成基因序列,将其克隆入真核表达载体pEGFP-N3中,然后利用脂质体法转染CHO细胞,通过持续G418筛选建立稳定转染细胞株。最后通过荧光显微镜观察、RT-PCR和Western Blot等方法证实多表位基因的表达。结果所构建的含有HCV复合多表位基因的真核表达载体pEGFP-mEpi在CHO细胞中能稳定表达。结论真核表达载体的成功构建和稳定转染CHO细胞系的建立为进一步研究复合多表位疫苗的基因免疫奠定了基础。     

应用感染性丙型肝炎病毒2a质粒制备小鼠丙型肝炎模型的初步研究

目的制备表达丙型肝炎病毒（HCV）2a型RNA的小鼠模型,为研究HCV高亲和力中和单克隆抗体在体内的病毒清除能力提供可行的动物模型。方法采用引进的HCV 2a型的质粒Jc1,体外表达HCV RNA后转染Huh7细胞,建立可持续感染的Huh7-Jc1丙肝细胞模型。然后以该细胞腹腔注射裸鼠,或以该细胞尾静脉注射裸鼠,并通过小鼠血液中HCV 2a的RNA水平检测,观察小鼠体内的HCV存留情况,以移植未转HCV的Huh7细胞和培养上清为阴性对照。结果建立了可表达HCV RNA和核心蛋白的Huh7-Jc1细胞,且该细胞模型具有一定感染能力,以其培养上清孵育Huh7细胞,可使后者也表达HCV RNA和核心蛋白。BALB/c-nu裸鼠腹腔或尾静脉移植Huh7-Jc1细胞后,裸鼠血清中可检测到HCV RNA的表达。结论显示利用Huh7-Jc1细胞可初步制备表达HCV的丙型肝炎小鼠模型,但高效、长久表达HCV的小鼠模型还有待进一步完善。     

丙型肝炎病毒感染与治疗药物

丙型肝炎病毒（HCV）通过在宿主细胞内持续复制,导致慢性感染。目前用于治疗慢性丙型肝炎（CHC）的药物主要是聚乙二醇干扰素（PEG-IFN）和利巴韦林的联合用药。本文将就HCV的细胞入侵、复制、逃避宿主的固有和获得性免疫,以及抗HCV临床试验药物的最新进展做一综述。     

抑制素对HCV复制的影响

目的研究抑制素(PHB)对HCV复制的影响。方法全长基因组HCV RNA体外转染人肝癌细胞系Huh7.5,构建HCV全基因组细胞模型,分别收集24、48、72、96 h培养上清液检测HCV拷贝数;间接免疫荧光实验检测HCV核心蛋白的表达;透射电镜观察HCV感染细胞Huh 7.5-HCV的超微结构改变,鉴定HCV全基因组细胞模型。采用实时定量PCR、Western Blotting方法研究PHB在Huh 7.5-HCV细胞中的表达情况。应用RNA干扰技术检测PHB对HCV RNA的复制情况。两组间比较采用t检验。结果鉴定结果显示,成功构建HCV全基因组细胞模型。HCV RNA转染Huh7.5细胞24和48 h后,PHB mRNA表达水平分别是13.41±1.35和16.45±1.76,与对照组(1.01±0.57和1.01±0.87)相比差异均有统计学意义(t值分别为29.540、31.361,P值均0.01);PHB蛋白表达水平亦显著高于对照组(P值均0.01)。PHB的RNA干扰质粒(shRNA-PHB)转染Huh7.5-HCV细胞24和48h后,HCV RNA的水平分别为64.32±5.49和84.45±7.06,显著高于对照组(shRNA-control组,10.52±1.57和16.34±2.97,t值分别为29.538、25.908,P值均0.01)。结论 Huh7.5-HCV细胞中PHB表达的升高可能与HCV RNA的感染有关,PHB蛋白对HCV RNA复制有一定的抑制作用。     

《2016年澳大利亚HCV感染管理共识意见》摘译

HCV感染是澳大利亚重要的公共卫生问题,约230 000人会因进展性肝纤维化最终导致肝硬化、肝衰竭甚至肝细胞癌(HCC).在澳大利亚,HCV感染是肝脏疾病需行肝移植的最主要原因.由HCV所致肝脏疾病的负担预计到2030年会增加3倍.然而,HCV感染是可治愈的,且病毒学清除可带来多重临床获益,包括提高生活质量、丧失传染性、肝硬化的逆转,降低肝脏衰竭和HCC的发生,并且降低死亡率.     

The Bank Vole (Clethrionomys glareolus)—Small Animal Model for Hepacivirus Infection

Many people worldwide suffer from hepatitis C virus (HCV) infection, which is frequently persistent. The lack of efficient vaccines against HCV and the unavailability of or limited compliance with existing antiviral therapies is problematic for health care systems worldwide. Improved small animal models would support further hepacivirus research, including development of vaccines and novel antivirals. The recent discovery of several mammalian hepaciviruses may facilitate such research. In this study, we demonstrated that bank voles (Clethrionomys glareolus) were susceptible to bank vole-associated Hepacivirus F and Hepacivirus J strains, based on the detection of hepaciviral RNA in 52 of 55 experimentally inoculated voles. In contrast, interferon α/β receptor deficient C57/Bl6 mice were resistant to infection with both bank vole hepaciviruses (BvHVs). The highest viral genome loads in infected voles were detected in the liver, and viral RNA was visualized by in situ hybridization in hepatocytes, confirming a marked hepatotropism. Furthermore, liver lesions in infected voles resembled those of HCV infection in humans. In conclusion, infection with both BvHVs in their natural hosts shares striking similarities to HCV infection in humans and may represent promising small animal models for this important human disease.     

Decision tree algorithm predicts hepatocellular carcinoma among chronic hepatitis C patients following viral eradication

Successful eradication of the hepatitis C virus (HCV) cannot eliminate the risk of hepatocellular carcinoma (HCC). Next-generation RNA sequencing provides comprehensive genomic insights into the pathogenesis of HCC. Artificial intelligence has opened a new era in precision medicine. This study integrated clinical features and genetic biomarkers to establish a machine learning-based HCC model following viral eradication. A prospective cohort of 55 HCV patients with advanced fibrosis, who achieved a sustained virologic response after antiviral therapy, was enrolled. The primary outcome was the occurrence of HCC. The genomic signatures of peripheral blood mononuclear cells (PBMC) were determined by RNA sequencing at baseline and 24 weeks after end-of-treatment. Machine learning algorithms were implemented to extract the predictors of HCC. HCC occurred in 8 of the 55 patients, with an annual incidence of 2.7%. Pretreatment PBMC DEFA1B, HBG2, ADCY4, and posttreatment TAS1R3, ABCA3, and FOSL1 genes were significantly downregulated, while the pretreatment ANGPTL6 gene was significantly upregulated in the HCC group compared to that in the non-HCC group. A gene score derived from the result of the decision tree algorithm can identify HCC with an accuracy of 95.7%. Gene score = TAS1R3 (≥0.63 FPKM, yes/no = 0/1) + FOSL1 (≥0.27 FPKM, yes/no = 0/1) + ABCA3 (≥2.40 FPKM, yes/no = 0/1). Multivariate Cox regression analysis showed that this gene score was the most important predictor of HCC (hazard ratio = 2.38, 95% confidence interval [CI] = 1.06-5.36, P = 0.036). Combining the gene score and fibrosis-4 index, a nomogram was constructed to predict the probability of HCC with an area under the receiver operating characteristic curve up to 0.950 (95% CI = 0.888-1.000, P = 7.0 × 10^-5). Decision curve analysis revealed that the nomogram had a net benefit in HCC detection. The calibration curve showed that the nomogram had optimal concordance between the predicted and actual HCC probabilities. In conclusion, down-regulated posttreatment PBMC TAS1R3, ABCA3, and FOSL1 expression were significantly correlated with HCC development after HCV eradication. Decision-tree-based algorithms can refine the assessment of HCC risk for personalized HCC surveillance.