Evidence on how a conserved glycine in the hinge region of HapR regulates its DNA binding ability: lessons from a natural variant

HapR has been recognized as a quorum-sensing master regulator in Vibrio cholerae. Because it controls a plethora of disparate cellular events, the absence of a functional HapR affects the physiology of V. cholerae to a great extent. In the current study, we pursued an understanding of an observation of a natural protease-deficient non-O1, non-O139 variant V. cholerae strain V2. Intriguingly, a nonfunctional HapR (henceforth designated as HapR(V2)) harboring a substitution of glycine to aspartate at position 39 of the N-terminal hinge region has been identified. An in vitro gel shift assay clearly suggested the inability of HapR(V2) to interact with various cognate promoters. Reinstatement of glycine at position 39 restores DNA binding ability of HapR(V2) (HapR(V2G)), thereby rescuing the protease-negative phenotype of this strain. The elution profile of HapR(V2) and HapR(V2G) proteins in size-exclusion chromatography and their circular dichroism spectra did not reflect any significant differences to explain the functional discrepancies between the two proteins. To gain insight into the structure-function relationship of these two proteins, we acquired small/wide angle x-ray scattering data from samples of the native and G39D mutant. Although Guinier analysis and indirect Fourier transformation of scattering indicated only a slight difference in the shape parameters, structure reconstruction using dummy amino acids concluded that although HapR adopts a "Y" shape similar to its crystal structure, the G39D mutation in hinge drastically altered the DNA binding domains by bringing them in close proximity. This altered spatial orientation of the helix-turn-helix domains in this natural variant provides the first structural evidence on the functional role of the hinge region in quorum sensing-related DNA-binding regulatory proteins of Vibrio spp.     

Genetic basis of autoantibody positive and negative rheumatoid arthritis risk in a multi-ethnic cohort derived from electronic health records

Discovering and following up on genetic associations with complex phenotypes require large patient cohorts. This is particularly true for patient cohorts of diverse ancestry and clinically relevant subsets of disease. The ability to mine the electronic health records (EHRs) of patients followed as part of routine clinical care provides a potential opportunity to efficiently identify affected cases and unaffected controls for appropriate-sized genetic studies. Here, we demonstrate proof-of-concept that it is possible to use EHR data linked with biospecimens to establish a multi-ethnic case-control cohort for genetic research of a complex disease, rheumatoid arthritis (RA). In 1,515 EHR-derived RA cases and 1,480 controls matched for both genetic ancestry and disease-specific autoantibodies (anti-citrullinated protein antibodies [ACPA]), we demonstrate that the odds ratios and aggregate genetic risk score (GRS) of known RA risk alleles measured in individuals of European ancestry within our EHR cohort are nearly identical to those derived from a genome-wide association study (GWAS) of 5,539 autoantibody-positive RA cases and 20,169 controls. We extend this approach to other ethnic groups and identify a large overlap in the GRS among individuals of European, African, East Asian, and Hispanic ancestry. We also demonstrate that the distribution of a GRS based on 28 non-HLA risk alleles in ACPA+ cases partially overlaps with ACPA- subgroup of RA cases. Our study demonstrates that the genetic basis of rheumatoid arthritis risk is similar among cases of diverse ancestry divided into subsets based on ACPA status and emphasizes the utility of linking EHR clinical data with biospecimens for genetic studies.     

Partitioning Heritability of Regulatory and Cell-Type-Specific Variants across 11 Common Diseases

Regulatory and coding variants are known to be enriched with associations identified by genome-wide association studies (GWASs) of complex disease, but their contributions to trait heritability are currently unknown. We applied variance-component methods to imputed genotype data for 11 common diseases to partition the heritability explained by genotyped SNPs (hg2) across functional categories (while accounting for shared variance due to linkage disequilibrium). Extensive simulations showed that in contrast to current estimates from GWAS summary statistics, the variance-component approach partitions heritability accurately under a wide range of complex-disease architectures. Across the 11 diseases DNaseI hypersensitivity sites (DHSs) from 217 cell types spanned 16% of imputed SNPs (and 24% of genotyped SNPs) but explained an average of 79% (SE = 8%) of hg2 from imputed SNPs (5.1× enrichment; p = 3.7 × 10⁻¹⁷) and 38% (SE = 4%) of hg2 from genotyped SNPs (1.6× enrichment, p = 1.0 × 10⁻⁴). Further enrichment was observed at enhancer DHSs and cell-type-specific DHSs. In contrast, coding variants, which span 1% of the genome, explained <10% of hg2 despite having the highest enrichment. We replicated these findings but found no significant contribution from rare coding variants in independent schizophrenia cohorts genotyped on GWAS and exome chips. Our results highlight the value of analyzing components of heritability to unravel the functional architecture of common disease.     

Tissue-Specific Enrichment of Lymphoma Risk Loci in Regulatory Elements

Though numerous polymorphisms have been associated with risk of developing lymphoma, how these variants function to promote tumorigenesis is poorly understood. Here, we report that lymphoma risk SNPs, especially in the non-Hodgkin’s lymphoma subtype chronic lymphocytic leukemia, are significantly enriched for co-localization with epigenetic marks of active gene regulation. These enrichments were seen in a lymphoid-specific manner for numerous ENCODE datasets, including DNase-hypersensitivity as well as multiple segmentation-defined enhancer regions. Furthermore, we identify putatively functional SNPs that are both in regulatory elements in lymphocytes and are associated with gene expression changes in blood. We developed an algorithm, UES, that uses a Monte Carlo simulation approach to calculate the enrichment of previously identified risk SNPs in various functional elements. This multiscale approach integrating multiple datasets helps disentangle the underlying biology of lymphoma, and more broadly, is generally applicable to GWAS results from other diseases as well.     

Immunoassay for Capsular Antigen of Bacillus anthracis Enables Rapid Diagnosis in a Rabbit Model of Inhalational Anthrax

Inhalational anthrax is a serious biothreat. Effective antibiotic treatment of inhalational anthrax requires early diagnosis; the further the disease has progressed, the less the likelihood for cure. Current means for diagnosis such as blood culture require several days to a result and require advanced laboratory infrastructure. An alternative approach to diagnosis is detection of a Bacillus anthracis antigen that is shed into blood and can be detected by rapid immunoassay. The goal of the study was to evaluate detection of poly-γ-D-glutamic acid (PGA), the capsular antigen of B. anthracis, as a biomarker surrogate for blood culture in a rabbit model of inhalational anthrax. The mean time to a positive blood culture was 26 ± 5.7 h (mean ± standard deviation), whereas the mean time to a positive ELISA was 22 ± 4.2 h; P = 0.005 in comparison with blood culture. A lateral flow immunoassay was constructed for detection of PGA in plasma at concentrations of less than 1 ng PGA/ml. Use of the lateral flow immunoassay for detection of PGA in the rabbit model found that antigen was detected somewhat earlier than the earliest time point at which the blood culture became positive. The low cost, ease of use, and rapid time to result of the lateral flow immunoassay format make an immunoassay for PGA a viable surrogate for blood culture for detection of infection in individuals who have a likelihood of exposure to B. anthracis.     

Analysis of anti-tumor antibodies in mice and rabbits induced by monoclonal anti-idiotope antibodies

Eight different mouse monoclonal anti-idiotope antibodies (mAb2) generated against a mouse monoclonal anti-human melanoma proteoglycan Ag (MPG) antibody (mAb1), MEM136, were tested for their ability to induce anti-MPG responses in mice and rabbits. All Ab2 were idiotypically cross-reactive and combining site-specific as demonstrated by competitive cross-inhibition studies and their ability to inhibit the binding of MEM136 to the melanoma cells, Colo38. However, only two Ab2, IM32 and IM06, were able to induce specific anti-TAA-specific (Ab1') responses in rabbits. When IM32 and IM06 were tested in allogeneic stains of mice for the induction of anti-MPG responses, only IM32 produced an Ab1' response. In mice, the Ab3 response induced by IM32 is idiotypically cross-reactive with its Ab1. Furthermore, the IM32-induced murine Ab3 and MEM136 recognized a similar MPG epitope on the melanoma cells because the Ab3 inhibited the binding of MEM136 to melanoma cells. The Ab3 induced by IM32 and IM06 in rabbits also recognized a similar epitope as the Ab1. In rabbits, the Ab3 response induced by IM32 and IM06 were idiotypically cross-reactive with each other. However, additional studies indicated that the majority of Ab3 induced by IM32 were IM32 Id-specific and lacked IM06 idiotopes. Further experimentation indicated that IM32-induced rabbit Ab3 were biologically active as demonstrated by the ability of the Ab3 to inhibit melanoma cell invasion in a Matrigel assay.     

Proteins encoded in genomic regions associated with immune-mediated disease physically interact and suggest underlying biology

Genome-wide association studies (GWAS) have defined over 150 genomic regions unequivocally containing variation predisposing to immune-mediated disease. Inferring disease biology from these observations, however, hinges on our ability to discover the molecular processes being perturbed by these risk variants. It has previously been observed that different genes harboring causal mutations for the same Mendelian disease often physically interact. We sought to evaluate the degree to which this is true of genes within strongly associated loci in complex disease. Using sets of loci defined in rheumatoid arthritis (RA) and Crohn's disease (CD) GWAS, we build protein-protein interaction (PPI) networks for genes within associated loci and find abundant physical interactions between protein products of associated genes. We apply multiple permutation approaches to show that these networks are more densely connected than chance expectation. To confirm biological relevance, we show that the components of the networks tend to be expressed in similar tissues relevant to the phenotypes in question, suggesting the network indicates common underlying processes perturbed by risk loci. Furthermore, we show that the RA and CD networks have predictive power by demonstrating that proteins in these networks, not encoded in the confirmed list of disease associated loci, are significantly enriched for association to the phenotypes in question in extended GWAS analysis. Finally, we test our method in 3 non-immune traits to assess its applicability to complex traits in general. We find that genes in loci associated to height and lipid levels assemble into significantly connected networks but did not detect excess connectivity among Type 2 Diabetes (T2D) loci beyond chance. Taken together, our results constitute evidence that, for many of the complex diseases studied here, common genetic associations implicate regions encoding proteins that physically interact in a preferential manner, in line with observations in Mendelian disease.