Erin E. McClelland

A novel MHC class I–like gene is mutated in patients with hereditary haemochromatosis

Hereditary haemochromatosis (HH), which affects some 1 in 400 and has an estimated carrier frequency of 1 in 10 individuals of Northern European descent, results in multi–organ dysfunction caused by increased iron deposition, and is treatable if detected early. Using linkage–disequilibrium and full haplotype analysis, we have identified a 250–kilobase region more than 3 megabases telomeric of the major histocompatibility complex (MHC) that is identical–by–descent in 85% of patient chromosomes. Within this region, we have identified a gene related to the MHC class I family, termed HLA–H, containing two missense alterations. One of these is predicted to inactivate this class of proteins and was found homozygous in 83% of 178 patients. A role of this gene in haemochromatosis is supported by the frequency and nature of the major mutation and prior studies implicating MHC class Mike proteins in iron metabolism.

Major histocompatibility complex heterozygote superiority during coinfection.

ABSTRACT Genes of the major histocompatibility complex (MHC) play a critical role in immune recognition, and many alleles confer susceptibility to infectious and autoimmune diseases. How these deleterious alleles persist in populations is controversial. One hypothesis postulates that MHC heterozygote superiority emerges over multiple infections because MHC-mediated resistance is generally dominant and many allele-specific susceptibilities to pathogens will be masked by the resistant allele in heterozygotes. We tested this hypothesis by using experimental coinfections with Salmonella enterica (serovar Typhimurium C5TS) and Theilers murine encephalomyelitis virus (TMEV) in MHC-congenic mouse strains where one haplotype was resistant to Salmonella and the other was resistant to TMEV. MHC heterozygotes were superior to both homozygotes in 7 out of 8 comparisons (P = 0.0024), and the mean standardized pathogen load of heterozygotes was reduced by 41% over that of homozygotes (P = 0.01). In contrast, no heterozygote superiority was observed when the MHC haplotype combinations had similar susceptibility profiles to the two pathogens. This is the first experimental evidence for MHC heterozygote superiority against multiple pathogens, a mechanism that would contribute to the evolution of MHC diversity and explain the persistence of alleles conferring susceptibility to disease.

Gender Specific Differences in the Immune Response to Infection

There are many instances where males and females differ in the susceptibility to infections. The reason for these differences in susceptibility is multifactorial. The primary cause is thought to be due to differences induced by sex hormones and their effects on gene expression as well as the immune system, but may also be due to innate physiological differences between males and females. This review summarizes gender specific differences seen in infections caused by bacteria, fungi, parasites and viruses. Ultimately, gender specific differences appear to be dependent on the microbe causing the infection, as not every infection with a specific microbial type results in increased susceptibility of one gender over the other. This suggests that there is an interaction between gender specific immune differences and the specific immune response to individual microbes.

Ab binding alters gene expression in Cryptococcus neoformans and directly modulates fungal metabolism

Abs facilitate humoral immunity via the classical mechanisms of opsonization, complement activation, Ab-dependent cellular cytotoxicity, and toxin/viral neutralization. There is also evidence that some Abs mediate direct antimicrobial effects. For example, Ab binding to the polysaccharide capsule of the human pathogenic fungus Cryptococcus neoformans promotes opsonization but also inhibits polysaccharide release and biofilm formation. To investigate whether Ab binding affects C. neoformans directly, we analyzed fungal gene expression after binding of protective and nonprotective mAbs. The 2 IgM Abs and 1 IgG1 Ab tested each induced different changes in gene expression. The protective IgG1 mAb upregulated genes encoding proteins involved in fatty acid synthesis, the protective IgM mAb downregulated genes encoding proteins required for protein translation, and the nonprotective IgM mAb had modest effects on gene expression. Differences in gene expression correlated with mAb binding to different locations of the capsule. Of the 3 Abs tested, the protective IgG1 mAb bound to C. neoformans closest to the cell wall, produced specific differences in the pattern of phosphorylated proteins, caused changes in lipid metabolism, and resulted in increased susceptibility to the antifungal drug amphotericin B. These results suggest what we believe to be a new mode of action for Ab-mediated immunity and raise the possibility that immunoglobulins mediate cross talk between microbes and hosts through their effects on microbial metabolism.

A haplotype and linkage disequilibrium analysis of the hereditary hemochromatosis gene region.

Hereditary hemochromatosis is a recessive disease of iron metabolism widely distributed among people of European descent. Most patients have inherited the causative mutation from a single ancestor. In the course of cloning the hemochromatosis gene, genotypes were generated for these samples at 43 microsatellite repeat markers that span the 6.5-Mb hemochromatosis gene region. The data used to reconstruct the ancestral haplotype across the hemochromatosis gene region are presented in this paper. Portions of the ancestral haplotype were present on 85% of patient chromosomes in this sample and ranged in size from approximately 500 kb to greater than 6.5 Mb. Only one marker, D6S2239, was identical by descent on all of the patient chromosomes containing the ancestral mutation. In contrast, only 3 of the 128 control chromosomes, or 2.3%, carried the ancestral mutation and the surrounding ancestral haplotype. To test new methods for gene finding using linkage disequilibrium we analyzed the genotypic data with a multilocus maximum likelihood method (DISMULT) and a single point method (DISLAMB), both written to analyze data generated from multi-allelic markers. The maximum value from DISLAMB analysis occurred at marker D6S2239, which is less than 20 kb from the hemochromatosis gene HFE, consistent with the haplotype analysis. The peak of the multi-point analysis was 700 kb from HFE, possibly due to the nonuniform recombination rates within this large region. The recombination rate appears to be lower than expected centromeric of the HFE gene.

Estimating the Relative Contributions of Virulence Factors for Pathogenic Microbes

ABSTRACT Many pathogenic microbes have multiple virulence factors that can cause damage to the host and thus contribute to an overall virulence phenotype for that organism. Although current techniques are suitable for demonstrating that a particular microbial characteristic contributes to virulence, no formal approach for defining the relative contributions of multiple virulence factors to overall virulence has been proposed. This paper describes the use of multivariate linear regression to estimate the relative contributions of virulence factors to the overall phenomenon of virulence. The approach is illustrated here with sample calculations of the relative contributions of individual Cryptococcus neoformans and Bacillus anthracis virulence factors to the overall virulence phenotype. These calculations were derived from a small underpowered experimental data set for the fungus and two larger sets of randomly generated data for both microbes. The major limitation of this method is a requirement for large data sets of microbial strains that differ in virulence and virulence factor expression. Multivariate linear regression can be used to identify the relative levels of importance of virulence factors in virulence studies, and this information can be used to prioritize antigen identification for vaccine development and the design of antimicrobial strategies that target virulence mechanisms.

HLA class II haplotype and sequence analysis support a role for DQ in narcolepsy

Abstract A systematic haplotype and sequencing analysis of the HLA-DR and -DQ region in patients with narcolepsy was performed. Five new (CA)n microsatellite markers were generated and positioned on the physical map across the HLA-DQB1-DQA1-DRB1 interval. Haplotypes for these new markers and the three HLA loci were established using somatic cell hybrids generated from patients. A four-marker haplotype surrounding the DQB1*0602 gene was found in all narcolepsy patients, and was identical to haplotypes observed on random chromosomes harboring the DQB1*0602 allele. Eighty-six kilobases of contiguous genomic sequence across the region did not reveal new genes, and analysis of this sequence for single nucleotide polymorphisms did not reveal sequence variation among DQB1*0602 chromosomes. These results are consistent with other studies, suggesting that the HLA-DQ genes themselves are among the predisposing factors in narcolepsy.

The role of host gender in the pathogenesis of Cryptococcus neoformans infections.

Cryptococcus neoformans (Cn) is a pathogenic yeast and the cause of cryptococcal meningitis. Prevalence of disease between males and females is skewed, with males having an increased incidence of disease. Based on the reported gender susceptibility differences to Cn in the literature, we used clinical isolates from Botswanan HIV-infected patients to test the hypothesis that different gender environments exerted different selective pressures on Cn. When we examined this data set, we found that men had significantly higher risk of death despite having significantly higher CD4+ T lymphocyte counts upon admittance to the hospital. These observations suggested that Cn strains are uniquely adapted to different host gender environments and that the male immune response may be less efficient in controlling Cn infection. To discriminate between these possibilities, we tested whether there were phenotypic differences between strains isolated from males and females and whether there was an interaction between Cn and the host immune response. Virulence phenotypes showed that Cn isolates from females had longer doubling times and released more capsular glucoronoxylomannan (GXM). The presence of testosterone but not 17-β estradiol was associated with higher levels of GXM release for a laboratory strain and 28 clinical isolates. We also measured phagocytic efficiency, survival of Cn, and amount of killing of human macrophages by Cn after incubation with four isolates. While macrophages from females phagocytosed more Cn than macrophages from males, male macrophages had a higher fungal burden and showed increased killing by Cn. These data are consistent with the hypothesis that differential interaction between Cn and macrophages within different gender environments contribute to the increased prevalence of cryptococcosis in males. This could be related to differential expression of cryptococcal virulence genes and capsule metabolism, changes in Cn phagocytosis and increased death of Cn-infected macrophages.

Major Histocompatibility Complex-Dependent Susceptibility to Cryptococcus neoformans in Mice

ABSTRACT To evaluate the role of major histocompatibility complex (MHC) genes in the resistance to Cryptococcus neoformans, we conducted infection experiments in MHC-congenic strains of mice. Significant MHC-dependent susceptibility differences were found among homozygotes and heterozygotes. This study is the first experimental demonstration of MHC-dependent susceptibility to C. neoformans infections in mice and indicates that MHC genes can be important in host resistance.

Coping with Multiple Virulence Factors: Which Is Most Important?

Despite being a time when genomics and proteomics are becoming popular modes of scientific inquiry, most microbe-centric researchers continue to use reductionism to study virulence by identifying the microbial characteristics associated with virulence and characterizing each independently. Reductionism is a critical and remarkably powerful tool for determining the contribution of a single virulence factor to the overall virulence phenotype. However, the approach has the following limitation: most pathogenic microbes possess numerous attributes that contribute to virulence, and this virulence is a microbial trait that is expressed only in a susceptible host. Unfortunately, it is often very difficult, if not impossible with current technology, to study combinations of virulence factors simultaneously, especially at the molecular level. Hence, new tools are needed to study the larger picture of virulence in a pathogenic organism and to better understand how the host and microbe interact. And while computer modeling, genomics, and proteomics contribute much to the larger picture of virulence, a more accessible method is available via multivariate statistics. Consider two microbes: Cryptococcus neoformans and Bacillus anthracis. For C. neoformans, at least a half-dozen cellular attributes have been associated with virulence, including the polysaccharide capsule, melanin production, phospholipase secretion, mating factor, laccase, and urease [1]. Similarly, for B. anthracis the poly-D-glutamic acid capsule, lethal toxin, edema factor, and anthrolysin are each associated with the virulence phenotype [2,3]. Since immune responses to virulence factors often negate the virulence phenotype, vaccines often target virulence factors, as is the case for both C. neoformans and B. anthracis. In addition, the highly successful vaccines to Streptococcus pneumoniae and Haemophilus influenzae type B elicit antibodies to their polysaccharide capsules. In the same way, toxoid vaccines protect against tetanus and diphtheria by eliciting neutralizing antibody responses. Consequently, an investigator may want to prioritize the relative importance of virulence factors that contribute to the overall virulence phenotype, especially when designing new vaccines or antimicrobial drugs. However, to our knowledge, no methods have been developed to accomplish this. Fortunately, the goal of prioritizing virulence factors for an individual microbe is similar to problems that have been encountered and solved in other disciplines where investigators have had to confront phenomena caused by multiple components. Sophisticated statistical methods have been developed to approach these problems and are applicable to the problem of microbial virulence. A commonly used statistical tool is multivariate linear regression analysis (MLRA), which has found a myriad of uses in the social sciences, biology, and medicine. For example, MLRA has been used to study aspects of school readiness such as the prediction of learning-related skills in children [4], factors that contribute to smoking in youths [5], the degree and location of white matter changes in patients with Alzheimer disease [6], and whether hand lead contamination is associated with blood lead contamination [7]. MLRA simultaneously assesses the relationships of many independent variables to one dependent variable, and can easily be used to examine the relative contribution of microbial virulence factors to virulence. In fact, MLRA can be used to rank virulence factors in disease importance. There are three different kinds of MLRA: standard multiple regression, sequential (hierarchical) regression, and statistical regression [8]. In standard multiple regression, all independent variables are entered together so that the relative contribution of each independent variable to the dependent variable is assessed at the same time. Thus, standard regression illustrates how much of the dependent variable is explained by each of the independent variables at once. In hierarchical regression, the independent variables are entered in different steps in a specific order, with the order of entry resulting from theoretical or logical importance. Thus, hierarchical regression allows the investigator to examine the unique contribution of each independent predictor variable to the variance in the dependent variable, while taking into account the contribution of previously identified independent variables. In statistical regression, the independent variables are entered or removed in different steps, in an order that is specified by statistical criteria. Thus, statistical regression is useful for selecting which independent variables best predict the dependent variable when there is no theoretical rationale for a priori prioritization [8]. Depending on how much information is available on certain microbial virulence factors, and the focus of the research question, investigators can use any or all of the different kinds of MLRA. One limitation of MLRA is the need for an adequate sample size. A general rule of thumb is that ten data points