Multiple genetic loci influence vaccine-induced protection against Mycobacterium tuberculosis in genetically diverse mice.

Mycobacterium tuberculosis (M.tb.) infection leads to over 1.5 million deaths annually, despite widespread vaccination with BCG at birth. Causes for the ongoing tuberculosis endemic are complex and include the failure of BCG to protect many against progressive pulmonary disease. Host genetics is one of the known factors implicated in susceptibility to primary tuberculosis, but less is known about the role that host genetics plays in controlling host responses to vaccination against M.tb. Here, we addressed this gap by utilizing Diversity Outbred (DO) mice as a small animal model to query genetic drivers of vaccine-induced protection against M.tb. DO mice are a highly genetically and phenotypically diverse outbred population that is well suited for fine genetic mapping. Similar to outcomes in people, our previous studies demonstrated that DO mice have a wide range of disease outcomes following BCG vaccination and M.tb. challenge. In the current study, we used a large population of BCG-vaccinated/M.tb.-challenged mice to perform quantitative trait loci mapping of complex infection traits; these included lung and spleen M.tb. burdens, as well as lung cytokines measured at necropsy. We found sixteen chromosomal loci associated with complex infection traits and cytokine production. QTL associated with bacterial burdens included a region encoding major histocompatibility antigens that are known to affect susceptibility to tuberculosis, supporting validity of the approach. Most of the other QTL represent novel associations with immune responses to M.tb. and novel pathways of cytokine regulation. Most importantly, we discovered that protection induced by BCG is a multigenic trait, in which genetic loci harboring functionally-distinct candidate genes influence different aspects of immune responses that are crucial collectively for successful protection. These data provide exciting new avenues to explore and exploit in developing new vaccines against M.tb.

Statistical methods for Mendelian randomization in genome-wide association studies: A review.

Genome-wide association studies have yielded thousands of associations for many common diseases and disease-related complex traits. The identified associations made it possible to identify the causal risk factors underlying diseases and investigate the causal relationships among complex traits through Mendelian randomization. Mendelian randomization is a form of instrumental variable analysis that uses SNP associations from genome-wide association studies as instruments to study and uncover causal relationships between complex traits. By leveraging SNP genotypes as instrumental variables, or proxies, for the exposure complex trait, investigators can tease out causal effects from observational data, provided that necessary assumptions are satisfied. We discuss below the development of Mendelian randomization methods in parallel with the growth of genome-wide association studies. We argue that the recent availability of GWAS summary statistics for diverse complex traits has motivated new Mendelian randomization methods with relaxed causality assumptions and that this area continues to offer opportunities for robust biological discoveries.

Host-pathogen genetic interactions underlie tuberculosis susceptibility in genetically diverse mice.

The outcome of an encounter with Mycobacterium tuberculosis (Mtb) depends on the pathogen's ability to adapt to the variable immune pressures exerted by the host. Understanding this interplay has proven difficult, largely because experimentally tractable animal models do not recapitulate the heterogeneity of tuberculosis disease. We leveraged the genetically diverse Collaborative Cross (CC) mouse panel in conjunction with a library of Mtb mutants to create a resource for associating bacterial genetic requirements with host genetics and immunity. We report that CC strains vary dramatically in their susceptibility to infection and produce qualitatively distinct immune states. Global analysis of Mtb transposon mutant fitness (TnSeq) across the CC panel revealed that many virulence pathways are only required in specific host microenvironments, identifying a large fraction of the pathogen's genome that has been maintained to ensure fitness in a diverse population. Both immunological and bacterial traits can be associated with genetic variants distributed across the mouse genome, making the CC a unique population for identifying specific host-pathogen genetic interactions that influence pathogenesis.

Genetic background modifies phenotypic severity and longevity in a mouse model of Niemann-Pick disease type C1.

Niemann-Pick disease type C1 (NPC1) is a rare, fatal neurodegenerative disorder characterized by lysosomal accumulation of unesterified cholesterol and glycosphingolipids. These subcellular pathologies lead to phenotypes of hepatosplenomegaly, neurological degeneration and premature death. NPC1 is extremely heterogeneous in the timing of clinical presentation and is associated with a wide spectrum of causative NPC1 mutations. To study the genetic architecture of NPC1, we have generated a new NPC1 mouse model, Npc1em1PavNpc1em1Pav/em1Pav mutants showed notably reduced NPC1 protein compared to controls and displayed the pathological and biochemical hallmarks of NPC1. Interestingly, Npc1em1Pav/em1Pav mutants on a C57BL/6J genetic background showed more severe visceral pathology and a significantly shorter lifespan compared to Npc1em1Pav/em1Pav mutants on a BALB/cJ background, suggesting that strain-specific modifiers contribute to disease severity and survival. QTL analysis for lifespan of 202 backcross N2 mutants on a mixed C57BL/6J and BALB/cJ background detected significant linkage to markers on chromosomes 1 and 7. The discovery of these modifier regions demonstrates that mouse models are powerful tools for analyzing the genetics underlying rare human diseases, which can be used to improve understanding of the variability in NPC1 phenotypes and advance options for patient diagnosis and therapy.This article has an associated First Person interview with the first author of the paper.

Genetic determinants of gut microbiota composition and bile acid profiles in mice.

The microbial communities that inhabit the distal gut of humans and other mammals exhibit large inter-individual variation. While host genetics is a known factor that influences gut microbiota composition, the mechanisms underlying this variation remain largely unknown. Bile acids (BAs) are hormones that are produced by the host and chemically modified by gut bacteria. BAs serve as environmental cues and nutrients to microbes, but they can also have antibacterial effects. We hypothesized that host genetic variation in BA metabolism and homeostasis influence gut microbiota composition. To address this, we used the Diversity Outbred (DO) stock, a population of genetically distinct mice derived from eight founder strains. We characterized the fecal microbiota composition and plasma and cecal BA profiles from 400 DO mice maintained on a high-fat high-sucrose diet for ~22 weeks. Using quantitative trait locus (QTL) analysis, we identified several genomic regions associated with variations in both bacterial and BA profiles. Notably, we found overlapping QTL for Turicibacter sp. and plasma cholic acid, which mapped to a locus containing the gene for the ileal bile acid transporter, Slc10a2. Mediation analysis and subsequent follow-up validation experiments suggest that differences in Slc10a2 gene expression associated with the different strains influences levels of both traits and revealed novel interactions between Turicibacter and BAs. This work illustrates how systems genetics can be utilized to generate testable hypotheses and provide insight into host-microbe interactions.

Testing Pleiotropy vs. Separate QTL in Multiparental Populations.

The high mapping resolution of multiparental populations, combined with technology to measure tens of thousands of phenotypes, presents a need for quantitative methods to enhance understanding of the genetic architecture of complex traits. When multiple traits map to a common genomic region, knowledge of the number of distinct loci provides important insight into the underlying mechanism and can assist planning for subsequent experiments. We extend the method of Jiang and Zeng (1995), for testing pleiotropy with a pair of traits, to the case of more than two alleles. We also incorporate polygenic random effects to account for population structure. We use a parametric bootstrap to determine statistical significance. We apply our methods to a behavioral genetics data set from Diversity Outbred mice. Our methods have been incorporated into the R package qtl2pleio.

Stable kinetochore-microtubule attachment is sufficient to silence the spindle assembly checkpoint in human cells.

During mitosis, duplicated sister chromatids attach to microtubules emanating from opposing sides of the bipolar spindle through large protein complexes called kinetochores. In the absence of stable kinetochore-microtubule attachments, a cell surveillance mechanism known as the spindle assembly checkpoint (SAC) produces an inhibitory signal that prevents anaphase onset. Precisely how the inhibitory SAC signal is extinguished in response to microtubule attachment remains unresolved. To address this, we induced formation of hyper-stable kinetochore-microtubule attachments in human cells using a non-phosphorylatable version of the protein Hec1, a core component of the attachment machinery. We find that stable attachments are sufficient to silence the SAC in the absence of sister kinetochore bi-orientation and strikingly in the absence of detectable microtubule pulling forces or tension. Furthermore, we find that SAC satisfaction occurs despite the absence of large changes in intra-kinetochore distance, suggesting that substantial kinetochore stretching is not required for quenching the SAC signal.

A strategy to identify dominant point mutant modifiers of a quantitative trait.

A central goal in the analysis of complex traits is to identify genes that modify a phenotype. Modifiers of a cancer phenotype may act either intrinsically or extrinsically on the salient cell lineage. Germline point mutagenesis by ethylnitrosourea can provide alleles for a gene of interest that include loss-, gain-, or alteration-of-function. Unlike strain polymorphisms, point mutations with heterozygous quantitative phenotypes are detectable in both essential and nonessential genes and are unlinked from other variants that might confound their identification and analysis. This report analyzes strategies seeking quantitative mutational modifiers of Apc(Min) in the mouse. To identify a quantitative modifier of a phenotype of interest, a cluster of test progeny is needed. The cluster size can be increased as necessary for statistical significance if the founder is a male whose sperm is cryopreserved. A second critical element in this identification is a mapping panel free of polymorphic modifiers of the phenotype, to enable low-resolution mapping followed by targeted resequencing to identify the causative mutation. Here, we describe the development of a panel of six "isogenic mapping partner lines" for C57BL/6J, carrying single-nucleotide markers introduced by mutagenesis. One such derivative, B6.SNVg, shown to be phenotypically neutral in combination with Apc(Min), is an appropriate mapping partner to locate induced mutant modifiers of the Apc(Min) phenotype. The evolved strategy can complement four current major initiatives in the genetic analysis of complex systems: the Genome-wide Association Study; the Collaborative Cross; the Knockout Mouse Project; and The Cancer Genome Atlas.

Cell aggregation by scaffolded receptor clusters.

The aggregation of cells by lectins or antibodies is important for biotechnological and therapeutic applications. One strategy to augment the avidity and aggregating properties of these mediators is to maximize the number of their ligand binding sites. The valency of lectins and antibodies, however, is limited by their quaternary structures. To overcome this limitation, we explored the use of polymers generated by ring-opening metathesis polymerization (ROMP) as scaffolds to noncovalently assemble multiple copies of a lectin, the tetravalent protein concanavalin A (Con A). We demonstrate that complexes between Con A and multivalent scaffolds aggregate cells of a T cell leukemia line (Jurkat) more effectively than Con A alone. We anticipate that synthetic scaffolds will offer a new means of facilitating processes that rely on cell aggregation, such as pathogen clearance and immune recognition.