Autologous Antibody Capture to Enrich Immunogenic Viruses for Viral Discovery

Discovery of new viruses has been boosted by novel deep sequencing technologies. Currently, many viruses can be identified by sequencing without knowledge of the pathogenicity of the virus. However, attributing the presence of a virus in patient material to a disease in the patient can be a challenge. One approach to meet this challenge is identification of viral sequences based on enrichment by autologous patient antibody capture. This method facilitates identification of viruses that have provoked an immune response within the patient and may increase the sensitivity of the current virus discovery techniques. To demonstrate the utility of this method, virus discovery deep sequencing (VIDISCA-454) was performed on clinical samples from 19 patients: 13 with a known respiratory viral infection and 6 with a known gastrointestinal viral infection. Patient sera was collected from one to several months after the acute infection phase. Input and antibody capture material was sequenced and enrichment was assessed. In 18 of the 19 patients, viral reads from immunogenic viruses were enriched by antibody capture (ranging between 1.5x to 343x in respiratory material, and 1.4x to 53x in stool). Enriched reads were also determined in an identity independent manner by using a novel algorithm Xcompare. In 16 of the 19 patients, 21% to 100% of the enriched reads were derived from infecting viruses. In conclusion, the technique provides a novel approach to specifically identify immunogenic viral sequences among the bulk of sequences which are usually encountered during virus discovery metagenomics.     

尝试利用R—Q对应因子分析识别分群融合子代

在特定融合组合的子代群体中,以不同姊妹菌株作为观察样本(n=N),以蛋白质电泳全部谱带泳动率作为指标(p=P),则所对应的谱带光密度扫描峰面积作为其观测值(X)(当某菌株缺乏某条带时,其峰面积记为零),利用R-Q对应因子分析程序,解析这个数据矩阵(X_(nxp))。能够在同一标度的因子平面上考察这一特定融合重组事件发生后,姊妹菌株间和各菌株肉蛋白质谱带位置与含量间以及它们相互之间的多重内在联系,从而推断子代群体与亲本的遗传继承关系。并由此来识别和分群姊妹菌株。这种探索具有拓展数值分类能力和指导融合育种实践的意义。     

Anti-dsDNA Antibody Isotypes in Systemic Lupus Erythematosus: IgA in Addition to IgG Anti-dsDNA Help to Identify Glomerulonephritis and Active Disease

Objectives

To evaluate the role of serum IgG, IgM and IgA anti-dsDNA antibody isotypes in the diagnosis of systemic lupus erythematosus (SLE), and their association with clinical features and disease activity, in a large cohort of SLE patients.

Methods

Sera of 200 SLE patients (mean age 34±10.3 years; 26 male and 174 female; median duration of disease 115 months, range 7–378), and of 206 controls, including 19 Sjögren''s syndrome, 27 rheumatoid arthritis, 26 psoriatic arthritis, 15 idiopathic inflammatory myopathies (IIM), 13 systemic sclerosis, 49 infectious diseases and 57 healthy subjects, were tested for anti-dsDNA IgG, IgM and IgA isotypes.

Results

Selecting a cutoff corresponding to 95% specificity, the sensitivity of IgG, IgM and IgA anti-dsDNA antibodies in SLE was 55%, 30% and 49%, respectively; 12.5%, 1% and 7.5% of SLE patients had positive IgG, IgM or IgA isotype alone, respectively. SLE patients with glomerulonephritis showed higher levels of IgA anti-dsDNA (p = 0.0002), anti-dsDNA IgG/IgM (p = 0.001) and IgA/IgM (p<0.0001) ratios than patients without renal disease. No significant associations have been found between anti-dsDNA isotypes and other clinical features. IgA anti-dsDNA (p = 0.01) (but not IgG or IgM) and IgG/IgM ratio (p = 0.005) were significantly higher in patients with more active disease (ECLAM score >4).

Conclusions

The detection of IgA anti-dsDNA autoantibodies seems to improve our ability to diagnose SLE and to define lupus nephritis phenotype and active disease. By contrast, IgM anti-dsDNA antibodies might be protective for renal involvement. These data support the hypothesis that anti-dsDNA antibody class clustering may help to refine SLE diagnosis and prognosis.     

Haemolytic Disease of the Newborn Caused by Anti-Lan Antibody

The first recorded example of anti-Lan associated with haemolytic disease of the newborn is reported. This emphasizes the importance of screening for atypical antibodies early in pregnancy, even though prophylactic use of anti-D immunoglobulin will eventually reduce the incidence of haemolytic disease due to anti-D antibody.     

用免疫学技术研究两种颗粒体病毒的亲缘关系

从新疆分离的黄地老虎颗粒体病毒（ＡｓＧＶ）和惊纹鸣夜蛾颗粒体病毒（ＡｅＧＶ）除感染各自的分离寄主外,均能感染对方的分离寄主。用琼脂糖双扩散、对流免疫电泳,斑点－酶联免疫吸附和线免疫电泳等免疫学技术检测ＡｓＧＶ和ＡｅＧＶ的免疫学亲缘关系,结果表明二者间存在非常密切的亲缘关系。并对线免疫电泳技术的效用进行了讨论。     

Immunoproteomic to Identify Antigens in the Intestinal Mucosa of Crohn's Disease Patients

Incidences of Crohn disease (CD) have increased significantly in the last decade. Immunoproteomics are a promising method to identify biomarkers of different diseases. In the present study, we used immunoproteomics to study proteins of intestinal mucosal lesions and neighboring normal intestinal mucosa of 8 CD patients. Reactive proteins were validated by Western blotting. Approximately 50 protein spots localized in the 4 to 7 pI range were detected on two-dimensional electrophoresis gels, and 6 differentially expressed protein spots between 10 and 100 kDa were identified. Reactive proteins were identified as prohibitin, calreticulin, apolipoprotein A-I, intelectin-1, protein disulfide isomerase, and glutathione s-transferase Pi. Western blotting was conducted on the intestinal mucosa of another 4 CD patients to validate the reactive proteins. We found that intestinal mucosal lesions had high levels of prohibitin expression. Glutathione s-transferase expression was detected in 100% of the intestinal mucosa examined. Thus, we report 6 autoantigens of CD, including 3 new and 3 previously reported autoantigens. Intelectin-1, protein disulfide isomerase, and glutathione-s-transferases may be used as biomarkers for CD pathogenesis.     

Incorporating Known Genetic Variants Does Not Improve the Accuracy of PSA Testing to Identify High Risk Prostate Cancer on Biopsy

Introduction

Prostate-specific antigen (PSA) testing is a widely accepted screening method for prostate cancer, but with low specificity at thresholds giving good sensitivity. Previous research identified four single nucleotide polymorphisms (SNPs) principally associated with circulating PSA levels rather than with prostate cancer risk (TERT rs2736098, FGFR2 rs10788160, TBX3 rs11067228, KLK3 rs17632542). Removing the genetic contribution to PSA levels may improve the ability of the remaining biologically-determined variation in PSA to discriminate between high and low risk of progression within men with identified prostate cancer. We investigate whether incorporating information on the PSA-SNPs improves the discrimination achieved by a single PSA threshold in men with raised PSA levels.

Materials and Methods

Men with PSA between 3-10ng/mL and histologically-confirmed prostate cancer were categorised as high or low risk of progression (Low risk: Gleason score≤6 and stage T1-T2a; High risk: Gleason score 7–10 or stage T2C). We used the combined genetic effect of the four PSA-SNPs to calculate a genetically corrected PSA risk score. We calculated the Area under the Curve (AUC) to determine how well genetically corrected PSA risk scores distinguished men at high risk of progression from low risk men.

Results

The analysis includes 868 men with prostate cancer (Low risk: 684 (78.8%); High risk: 184 (21.2%)). Receiver operating characteristic (ROC) curves indicate that including the 4 PSA-SNPs does not improve the performance of measured PSA as a screening tool for high/low risk prostate cancer (measured PSA level AU C = 59.5% (95% CI: 54.7,64.2) vs additionally including information from the 4 PSA-SNPs AUC = 59.8% (95% CI: 55.2,64.5) (p-value = 0.40)).

Conclusion

We demonstrate that genetically correcting PSA for the combined genetic effect of four PSA-SNPs, did not improve discrimination between high and low risk prostate cancer in men with raised PSA levels (3-10ng/mL). Replication and gaining more accurate estimates of the effects of the 4 PSA-SNPs and additional variants associated with PSA levels and not prostate cancer could be obtained from subsequent GWAS from larger prospective studies.     

Serologic Relationship of Coxsackie A16 Viruses from the Epidemic of Hand-Foot-and-Mouth Disease in Japan, 1970, to the Prototype Strain

In 1970, a great outbreak of hand-foot-and-mouth disease (HFMD) due to Coxsackie A16 virus (Cox A16) occurred throughout Japan. When serologic relationship between the viruses isolated during the epidemic and the prototype strain of the serotype was examined by the tube neutralization test, the crude new isolates were found to be poorly neutralized by both an antiserum against the prototype strain and those against the isolates, although they were neutralized significantly in the plaque reduction test. However, about 2% of virus in crude suspensions of the isolates remained unneutralized even in the plaque reduction test and this fraction could be eliminated by filtering the virus materials through a 100 mμ Millipore filter. Therefore, the difficulty in neutralization of the isolates by the tube method could be accounted for by the presence of aggregated viruses. Even when filtered viruses were used, the reciprocal neutralization kinetic studies revealed a significant serological difference between the isolates and the prototype strain. Such serological properties of the isolates were not influenced by the cell types used for virus isolation or passages. All the results suggest that the Cox A16 isolates from the epidemic of HFMD in Japan, 1970, are serologically different from the prototype strain.     

Structural Basis for the Recognition in an Idiotype-Anti-Idiotype Antibody Complex Related to Celiac Disease

Anti-idiotype antibodies have potential therapeutic applications in many fields, including autoimmune diseases. Herein we report the isolation and characterization of AIM2, an anti-idiotype antibody elicited in a mouse model upon expression of the celiac disease-specific autoantibody MB2.8 (directed against the main disease autoantigen type 2 transglutaminase, TG2). To characterize the interaction between the two antibodies, a 3D model of the MB2.8-AIM2 complex has been obtained by molecular docking. Analysis and selection of the different obtained docking solutions was based on the conservation within them of the inter-residue contacts. The selected model is very well representative of the different solutions found and its stability is confirmed by molecular dynamics simulations. Furthermore, the binding mode it adopts is very similar to that observed in most of the experimental structures available for idiotype-anti-idiotype antibody complexes. In the obtained model, AIM2 is directed against the MB2.8 CDR region, especially on its variable light chain. This makes the concurrent formation of the MB2.8-AIM2 complex and of the MB2.8-TG2 complex incompatible, thus explaining the experimentally observed inhibitory effect on the MB2.8 binding to TG2.     

Serological Relationship of the Tacaribe Complex of Viruses to Lymphocytic Choriomeningitis Virus

By means of the indirect fluorescent-antibody test, cross serological reactivity was demonstrated between lymphocytic choriomeningitis (LCM) virus and the viruses of the Tacaribe complex. Antisera to all members of the Tacaribe complex reacted with LCM virus; LCM antisera gave significant staining of Amapari virus, but minimal or inconsistent reactions with Tacaribe virus, and no reaction with two other viruses of the Tacaribe complex. A low level cross-reaction was observed in complement fixation tests of Machupo and Pichinde antisera against LCM antigen. Immunization with Tacaribe and Amapari viruses did not protect mice against challenge with LCM virus. Because of the identical appearance of the virions, the sharing of antigens, and the many biological similarities between LCM and the Tacaribe complex viruses, it is proposed that they be considered as constituting a new taxonomic group of viruses.     

Utilizing Chemical Genomics to Identify Cytochrome b as a Novel Drug Target for Chagas Disease

Unbiased phenotypic screens enable identification of small molecules that inhibit pathogen growth by unanticipated mechanisms. These small molecules can be used as starting points for drug discovery programs that target such mechanisms. A major challenge of the approach is the identification of the cellular targets. Here we report GNF7686, a small molecule inhibitor of Trypanosoma cruzi, the causative agent of Chagas disease, and identification of cytochrome b as its target. Following discovery of GNF7686 in a parasite growth inhibition high throughput screen, we were able to evolve a GNF7686-resistant culture of T. cruzi epimastigotes. Clones from this culture bore a mutation coding for a substitution of leucine by phenylalanine at amino acid position 197 in cytochrome b. Cytochrome b is a component of complex III (cytochrome bc₁) in the mitochondrial electron transport chain and catalyzes the transfer of electrons from ubiquinol to cytochrome c by a mechanism that utilizes two distinct catalytic sites, Q_N and Q_P. The L197F mutation is located in the Q_N site and confers resistance to GNF7686 in both parasite cell growth and biochemical cytochrome b assays. Additionally, the mutant cytochrome b confers resistance to antimycin A, another Q_N site inhibitor, but not to strobilurin or myxothiazol, which target the Q_P site. GNF7686 represents a promising starting point for Chagas disease drug discovery as it potently inhibits growth of intracellular T. cruzi amastigotes with a half maximal effective concentration (EC₅₀) of 0.15 µM, and is highly specific for T. cruzi cytochrome b. No effect on the mammalian respiratory chain or mammalian cell proliferation was observed with up to 25 µM of GNF7686. Our approach, which combines T. cruzi chemical genetics with biochemical target validation, can be broadly applied to the discovery of additional novel drug targets and drug leads for Chagas disease.     

Molecular Characterization of a Bovine Enteric Calicivirus: Relationship to the Norwalk-Like Viruses

Jena virus (JV) is a noncultivatable bovine enteric calicivirus associated with diarrhea in calves and was first described in Jena, Germany. The virus was serially passaged 11 times in colostrum-deprived newborn calves and caused diarrheal disease symptoms at each passage. The complete JV genome sequence was determined by using cDNA made from partially purified virus obtained from a single stool sample. JV has a positive-sense single-stranded RNA genome which is 7,338 nucleotides in length, excluding the poly(A) tail. JV genome organization is similar to that of the human Norwalk-like viruses (NLVs), with three separate open reading frames (ORFs) and a 24-nucleotide sequence motif located at the 5′ terminus of the genome and at the start of ORF 2. The polyprotein (ORF 1) consists of 1,680 amino acids and has the characteristic 2C helicase, 3C protease, and 3D RNA polymerase motifs also found in the NLVs. However, comparison of the N-terminal 100 amino acids of the JV polyprotein with those of the group 1 and group 2 NLVs showed a considerable divergence in sequence. The capsid protein (ORF 2) at 519 amino acids is smaller than that of all other caliciviruses. JV ORF 2 was translated in vitro to produce a 55-kDa protein that reacted with postinfection serum but not preinfection serum. Phylogenetic studies based on partial RNA polymerase sequences indicate that within the Caliciviridae JV is most closely related to the group 1 NLVs.     

Using Genetic Prediction from Known Complex Disease Loci to Guide the Design of Next-Generation Sequencing Experiments

A central focus of complex disease genetics after genome-wide association studies (GWAS) is to identify low frequency and rare risk variants, which may account for an important fraction of disease heritability unexplained by GWAS. A profusion of studies using next-generation sequencing are seeking such risk alleles. We describe how already-known complex trait loci (largely from GWAS) can be used to guide the design of these new studies by selecting cases, controls, or families who are most likely to harbor undiscovered risk alleles. We show that genetic risk prediction can select unrelated cases from large cohorts who are enriched for unknown risk factors, or multiply-affected families that are more likely to harbor high-penetrance risk alleles. We derive the frequency of an undiscovered risk allele in selected cases and controls, and show how this relates to the variance explained by the risk score, the disease prevalence and the population frequency of the risk allele. We also describe a new method for informing the design of sequencing studies using genetic risk prediction in large partially-genotyped families using an extension of the Inside-Outside algorithm for inference on trees. We explore several study design scenarios using both simulated and real data, and show that in many cases genetic risk prediction can provide significant increases in power to detect low-frequency and rare risk alleles. The same approach can also be used to aid discovery of non-genetic risk factors, suggesting possible future utility of genetic risk prediction in conventional epidemiology. Software implementing the methods in this paper is available in the R package Mangrove.     

Using Linkage Analysis to Detect Gene-Gene Interaction by Stratifying Family Data on Known Disease,or Disease-Associated,Alleles

Detecting gene-gene interaction in complex diseases is a major challenge for common disease genetics. Most interaction detection approaches use disease-marker associations and such methods have low power and unknown reliability in real data. We developed and tested a powerful linkage-analysis-based gene-gene interaction detection strategy based on conditioning the family data on a known disease-causing allele or disease-associated marker allele. We computer-generated multipoint linkage data for a disease caused by two epistatically interacting loci (A and B). We examined several two-locus epistatic inheritance models: dominant-dominant, dominant-recessive, recessive-dominant, recessive-recessive. At one of the loci (A), there was a known disease-related allele. We stratified the family data on the presence of this allele, eliminating family members who were without it. This elimination step has the effect of raising the “penetrance” at the second locus (B). We then calculated the lod score at the second locus (B) and compared the pre- and post-stratification lod scores at B. A positive difference indicated interaction. We also examined if it was possible to detect interaction with locus B based on a disease-marker association (instead of an identified disease allele) at locus A. We also tested whether the presence of genetic heterogeneity would generate false positive evidence of interaction. The power to detect interaction for a known disease allele was 60–90%. The probability of false positives, based on heterogeneity, was low. Decreasing linkage disequilibrium between the disease and marker at locus A decreased the likelihood of detecting interaction. The allele frequency of the associated marker made little difference to the power.