CC002/Unc females are mouse models of exercise-induced paradoxical fat response

Exercise results in beneficial health outcomes and protects against a variety of chronic diseases. However, U.S. exercise guidelines recommend identical exercise programs for everyone, despite individual variation in responses to these programs, including paradoxical fat gain. Experimental models of exercise-induced paradoxical outcomes may enable the dissection of underlying physiological mechanisms as well as the evaluation of potential interventions. Whereas several studies have identified individual mice exhibiting paradoxical fat gain following exercise, no systematic effort has been conducted to identify and characterize models of paradoxical response. Strains from the Collaborative Cross (CC) genetic reference population were used due to its high levels of genetic variation, its reproducible nature, and the observation that the CC is a rich source of novel disease models, to assess the impact genetic background has on exercise responses. We identified the strain CC002/Unc as an exercise-induced paradoxical fat response model in a controlled voluntary exercise study across multiple ages in female mice. We also found sex and genetic differences were consistent with this pattern in a study of forced exercise programs. These results provide a novel model for studies to determine the mechanisms behind paradoxical metabolic responses to exercise, and enable development of more rational personalized exercise recommendations based on factors such as age, sex, and genetic background.

Methyl-CpG binding domain protein-1 polymorphisms impact immune homeostatic levels of IgG

Host immunity plays a key role in protection against infection, however, there is significant individual-to-individual variation in the induction and quality of immune response that is driven in part by genetic factors. A growing body of evidence suggests that variation in immune status prior to specific insult may influence subsequent response to vaccination or pathogen challenge. Therefore, understanding the variation in immune status prior to specific insult is necessary for assessing variability in immune response to vaccination or pathogen challenge. The Collaborative Cross (CC) mouse population is a genetically diverse population that was designed to mimic the genetic and phenotypic diversity that is observed in humans and allows us to investigate mechanistically the contribution of genetics to complex phenotypes. Consequently, we asked whether there was variation in antibody levels in 57 CC strains prior to pathogen challenge and if that variation was associated with specific genetic factors. To assess this, we measured antibody levels for IgM, total IgG, IgG1, IgG2a, IgG2b, and IgG2c by ELISA and mapped quantitative trait loci (QTL) associated with variation in antibody concentrations. We observed substantial variation in all antibody isotypes measured. We also identified a suggestive (p=0.1) QTL on chromosome 18. Allele effects show that the C57Bl/6J allele at the locus of interest is linked to higher levels of total IgG. Subsequent analysis of genes under the QTL identified Methyl-CpG binding domain protein-1 (Mbd1) as the most promising candidate gene associated with total IgG variation. Ongoing studies are evaluating the role of Mbd1 in the regulation of total IgG production.

Toward Personalized Gene Therapy: Characterizing the Host Genetic Control of Lentiviral-Vector-Mediated Hepatic Gene Delivery

The success of lentiviral vectors in curing fatal genetic and acquired diseases has opened a new era in human gene therapy. However, variability in the efficacy and safety of this therapeutic approach has been reported in human patients. Consequently, lentiviral-vector-based gene therapy is limited to incurable human diseases, with little understanding of the underlying causes of adverse effects and poor efficacy. To assess the role that host genetic variation has on efficacy of gene therapy, we characterized lentiviral-vector gene therapy within a set of 12 collaborative cross mouse strains. Lentiviral vectors carrying the firefly luciferase cDNA under the control of a liver-specific promoter were administered to female mice, with total-body and hepatic luciferase expression periodically monitored through 41 weeks post-vector administration. Vector copy number per diploid genome in mouse liver and spleen was determined at the end of this study. We identified major strain-specific contributions to overall success of transduction, vector biodistribution, maximum luciferase expression, and the kinetics of luciferase expression throughout the study. Our results highlight the importance of genetic variation on gene-therapeutic efficacy; provide new models with which to more rigorously assess gene therapy approaches; and suggest that redesigning preclinical studies of gene-therapy methodologies might be appropriate.

Transcriptional profiles of WNV neurovirulence in a genetically diverse Collaborative Cross population

West Nile Virus (WNV) is a mosquito-transmitted virus from the Flaviviridae family that causes fever in 1 in 5 infected people. WNV can also become neuro-invasive and cross the blood-brain barrier leading to severe neurological symptoms in a subset of WNV infected individuals [1]. WNV neuro-invasion is believed to be influenced by a number of factors including host genetics. In order to explore these effects and recapitulate the complex immune genetic differences among individuals, we studied gene expression following WNV infection in the Collaborative Cross (CC) model. The CC is a mouse genetics resource composed of > 70 independently bred, octo-parental recombinant inbred mouse lines [2]. To identify the individual host gene expression signatures influencing protection or susceptibility to WNV disease and WNV neuroinvasion, we used the nanostring nsolver platform to quantify gene expression in brain tissue isolated from WNV-infected CC mice at days 4, 7 and 12 post-infection [3]. This nanostring technology provided a high throughput, non-amplification based mRNA quantitation method to detect immune genes involved in neuro-invasion. Data was deposited into the Gene Expression Omnibus (GEO) under accession GSE85999.

Identifying protective host gene expression signatures within the spleen during West Nile virus infection in the collaborative cross model

Flaviviruses are hematophagous arthropod-viruses that pose global challenges to human health. Like Zika virus, West Nile Virus (WNV) is a flavivirus for which no approved vaccine exists [1]. The role host genetics play in early detection and response to WNV still remains largely unexplained. In order to capture the impact of genetic variation on innate immune responses, we studied gene expression following WNV infection using the collaborative cross (CC). The CC is a mouse genetics resource composed of hundreds of independently bred, octo-parental recombinant inbred mouse lines [2]. To accurately capture the host immune gene expression signatures of West Nile infection, we used the nanostring platform to evaluate expression in spleen tissue isolated from CC mice infected with WNV over a time course of 4, 7, and 12 days' post-infection [3]. Nanostring is a non-amplification based digital method to quantitate gene expression that uses color-coded molecular barcodes to detect hundreds of transcripts in a sample. Using this approach, we identified unique gene signatures in spleen tissue at days 4, 7, and 12 following WNV infection, which delineated distinct differences between asymptomatic and symptomatic CC lines. We also identified novel immune genes. Data was deposited into the Gene Expression Omnibus under accession GSE86000.

Systems biology: A tool for charting the antiviral landscape

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Conventional approaches overlook the complexity of the antiviral response.

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Systems biology approaches provide a comprehensive and unbiased analysis.

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The Collaborative Cross studies how host genetics influences antiviral immunity.

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Transcriptomics is a powerful tool to study tissue and cellular antiviral responses.

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Single cell analysis allows for discrimination between bystander and infected cells.

The host antiviral programs that are initiated following viral infection form a dynamic and complex web of responses that we have collectively termed as “the antiviral landscape”. Conventional approaches to studying antiviral responses have primarily used reductionist systems to assess the function of a single or a limited subset of molecules. Systems biology is a holistic approach that considers the entire system as a whole, rather than individual components or molecules. Systems biology based approaches facilitate an unbiased and comprehensive analysis of the antiviral landscape, while allowing for the discovery of emergent properties that are missed by conventional approaches. The antiviral landscape can be viewed as a hierarchy of complexity, beginning at the whole organism level and progressing downward to isolated tissues, populations of cells, and single cells. In this review, we will discuss how systems biology has been applied to better understand the antiviral landscape at each of these layers. At the organismal level, the Collaborative Cross is an invaluable genetic resource for assessing how genetic diversity influences the antiviral response. Whole tissue and isolated bulk cell transcriptomics serves as a critical tool for the comprehensive analysis of antiviral responses at both the tissue and cellular levels of complexity. Finally, new techniques in single cell analysis are emerging tools that will revolutionize our understanding of how individual cells within a bulk infected cell population contribute to the overall antiviral landscape.

Genome Wide Identification of SARS-CoV Susceptibility Loci Using the Collaborative Cross

New systems genetics approaches are needed to rapidly identify host genes and genetic networks that regulate complex disease outcomes. Using genetically diverse animals from incipient lines of the Collaborative Cross mouse panel, we demonstrate a greatly expanded range of phenotypes relative to classical mouse models of SARS-CoV infection including lung pathology, weight loss and viral titer. Genetic mapping revealed several loci contributing to differential disease responses, including an 8.5Mb locus associated with vascular cuffing on chromosome 3 that contained 23 genes and 13 noncoding RNAs. Integrating phenotypic and genetic data narrowed this region to a single gene, Trim55, an E3 ubiquitin ligase with a role in muscle fiber maintenance. Lung pathology and transcriptomic data from mice genetically deficient in Trim55 were used to validate its role in SARS-CoV-induced vascular cuffing and inflammation. These data establish the Collaborative Cross platform as a powerful genetic resource for uncovering genetic contributions of complex traits in microbial disease severity, inflammation and virus replication in models of outbred populations.

Self-Management and Transition Readiness Assessment: Development, Reliability, and Factor Structure of the STARx Questionnaire

INTRODUCTION

The Self-Management and Transition to Adulthood with Rx=Treatment (STARx) Questionnaire was developed to collect information on self-management and health care transition (HCT) skills, via self-report, in a broad population of adolescents and young adults (AYAs) with chronic conditions.

METHODS

Over several iterations, the STARx questionnaire was created with AYA, family, and health provider input. The development and pilot testing of the STARx Questionnaire took place with the assistance of 1219 AYAs with different chronic health conditions, in multiple institutions and settings over three phases: item development, pilot testing, reliability and factor structuring.

RESULTS

The three development phases resulted in a final version of the STARx Questionnaire. The exploratory factor analysis of the third version of the 18-item STARx identified six factors that accounted for about 65% of the variance: Medication management, Provider communication, Engagement during appointments, Disease knowledge, Adult health responsibilities, and Resource utilization. Reliability estimates revealed good internal consistency and temporal stability, with the alpha coefficient for the overall scale being .80. The STARx was developmentally sensitive, with older patients scoring significantly higher on nearly every factor than younger patients.

CONCLUSION

The STARx Questionnaire is a reliable, self-report tool with adequate internal consistency, temporal stability, and a strong, multidimensional factor structure. It provides another assessment strategy to measure self-management and transition skills in AYAs with chronic conditions.

New Metrics for Evaluating Viral Respiratory Pathogenesis

Viral pathogenesis studies in mice have relied on markers of severe systemic disease, rather than clinically relevant measures, to evaluate respiratory virus infection; thus confounding connections to human disease. Here, whole-body plethysmography was used to directly measure changes in pulmonary function during two respiratory viral infections. This methodology closely tracked with traditional pathogenesis metrics, distinguished both virus- and dose-specific responses, and identified long-term respiratory changes following both SARS-CoV and Influenza A Virus infection. Together, the work highlights the utility of examining respiratory function following infection in order to fully understand viral pathogenesis.

Broad blockade antibody responses in human volunteers after immunization with a multivalent norovirus VLP candidate vaccine: immunological analyses from a phase I clinical trial

BACKGROUND

Human noroviruses (NoVs) are the primary cause of acute gastroenteritis and are characterized by antigenic variation between genogroups and genotypes and antigenic drift of strains within the predominant GII.4 genotype. In the context of this diversity, an effective NoV vaccine must elicit broadly protective immunity. We used an antibody (Ab) binding blockade assay to measure the potential cross-strain protection provided by a multivalent NoV virus-like particle (VLP) candidate vaccine in human volunteers.

METHODS AND FINDINGS

Sera from ten human volunteers immunized with a multivalent NoV VLP vaccine (genotypes GI.1/GII.4) were analyzed for IgG and Ab blockade of VLP interaction with carbohydrate ligand, a potential correlate of protective immunity to NoV infection and illness. Immunization resulted in rapid rises in IgG and blockade Ab titers against both vaccine components and additional VLPs representing diverse strains and genotypes not represented in the vaccine. Importantly, vaccination induced blockade Ab to two novel GII.4 strains not in circulation at the time of vaccination or sample collection. GII.4 cross-reactive blockade Ab titers were more potent than responses against non-GII.4 VLPs, suggesting that previous exposure history to this dominant circulating genotype may impact the vaccine Ab response. Further, antigenic cartography indicated that vaccination preferentially activated preexisting Ab responses to epitopes associated with GII.4.1997. Study interpretations may be limited by the relevance of the surrogate neutralization assay and the number of immunized participants evaluated.

CONCLUSIONS

Vaccination with a multivalent NoV VLP vaccine induces a broadly blocking Ab response to multiple epitopes within vaccine and non-vaccine NoV strains and to novel antigenic variants not yet circulating at the time of vaccination. These data reveal new information about complex NoV immune responses to both natural exposure and to vaccination, and support the potential feasibility of an efficacious multivalent NoV VLP vaccine for future use in human populations.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01168401.

Host genetic diversity enables Ebola hemorrhagic fever pathogenesis and resistance

Existing mouse models of lethal Ebola virus infection do not reproduce hallmark symptoms of Ebola hemorrhagic fever, neither delayed blood coagulation and disseminated intravascular coagulation nor death from shock, thus restricting pathogenesis studies to nonhuman primates. Here we show that mice from the Collaborative Cross panel of recombinant inbred mice exhibit distinct disease phenotypes after mouse-adapted Ebola virus infection. Phenotypes range from complete resistance to lethal disease to severe hemorrhagic fever characterized by prolonged coagulation times and 100% mortality. Inflammatory signaling was associated with vascular permeability and endothelial activation, and resistance to lethal infection arose by induction of lymphocyte differentiation and cellular adhesion, probably mediated by the susceptibility allele Tek. These data indicate that genetic background determines susceptibility to Ebola hemorrhagic fever.

A comprehensive collection of systems biology data characterizing the host response to viral infection

The Systems Biology for Infectious Diseases Research program was established by the U.S. National Institute of Allergy and Infectious Diseases to investigate host-pathogen interactions at a systems level. This program generated 47 transcriptomic and proteomic datasets from 30 studies that investigate in vivo and in vitro host responses to viral infections. Human pathogens in the Orthomyxoviridae and Coronaviridae families, especially pandemic H1N1 and avian H5N1 influenza A viruses and severe acute respiratory syndrome coronavirus (SARS-CoV), were investigated. Study validation was demonstrated via experimental quality control measures and meta-analysis of independent experiments performed under similar conditions. Primary assay results are archived at the GEO and PeptideAtlas public repositories, while processed statistical results together with standardized metadata are publically available at the Influenza Research Database (www.fludb.org) and the Virus Pathogen Resource (www.viprbrc.org). By comparing data from mutant versus wild-type virus and host strains, RNA versus protein differential expression, and infection with genetically similar strains, these data can be used to further investigate genetic and physiological determinants of host responses to viral infection.

Annotation of long non-coding RNAs expressed in collaborative cross founder mice in response to respiratory virus infection reveals a new class of interferon-stimulated transcripts

The outcome of respiratory virus infection is determined by a complex interplay of viral and host factors. Some potentially important host factors for the antiviral response, whose functions remain largely unexplored, are long non-coding RNAs (lncRNAs). Here we systematically inferred the regulatory functions of host lncRNAs in response to influenza A virus and severe acute respiratory syndrome coronavirus (SARS-CoV) based on their similarity in expression with genes of known function. We performed total RNA-Seq on viral-infected lungs from eight mouse strains, yielding a large data set of transcriptional responses. Overall 5,329 lncRNAs were differentially expressed after infection. Most of the lncRNAs were co-expressed with coding genes in modules enriched in genes associated with lung homeostasis pathways or immune response processes. Each lncRNA was further individually annotated using a rank-based method, enabling us to associate 5,295 lncRNAs to at least one gene set and to predict their potential cis effects. We validated the lncRNAs predicted to be interferon-stimulated by profiling mouse responses after interferon-α treatment. Altogether, these results provide a broad categorization of potential lncRNA functions and identify subsets of lncRNAs with likely key roles in respiratory virus pathogenesis. These data are fully accessible through the MOuse NOn-Code Lung interactive database (MONOCLdb).

Systems approaches to Coronavirus pathogenesis

Coronaviruses comprise a large group of emergent human and animal pathogens, including the highly pathogenic SARS-CoV and MERS-CoV strains that cause significant morbidity and mortality in infected individuals, especially the elderly. As emergent viruses may cause episodic outbreaks of disease over time, human samples are limited. Systems biology and genetic technologies maximize opportunities for identifying critical host and viral genetic factors that regulate susceptibility and virus-induced disease severity. These approaches provide discovery platforms that highlight and allow targeted confirmation of critical targets for prophylactics and therapeutics, especially critical in an outbreak setting. Although poorly understood, it has long been recognized that host regulation of virus-associated disease severity is multigenic. The advent of systems genetic and biology resources provides new opportunities for deconvoluting the complex genetic interactions and expression networks that regulate pathogenic or protective host response patterns following virus infection. Using SARS-CoV as a model, dynamic transcriptional network changes and disease-associated phenotypes have been identified in different genetic backgrounds, leading to the promise of population-wide discovery of the underpinnings of Coronavirus pathogenesis.

Specific mutations in H5N1 mainly impact the magnitude and velocity of the host response in mice

BACKGROUND

Influenza infection causes respiratory disease that can lead to death. The complex interplay between virus-encoded and host-specific pathogenicity regulators - and the relative contributions of each toward viral pathogenicity - is not well-understood.

RESULTS

By analyzing a collection of lung samples from mice infected by A/Vietnam/1203/2004 (H5N1; VN1203), we characterized a signature of transcripts and proteins associated with the kinetics of the host response. Using a new geometrical representation method and two criteria, we show that inoculation concentrations and four specific mutations in VN1203 mainly impact the magnitude and velocity of the host response kinetics, rather than specific sets of up- and down- regulated genes. We observed analogous kinetic effects using lung samples from mice infected with A/California/04/2009 (H1N1), and we show that these effects correlate with morbidity and viral titer.

CONCLUSIONS

We have demonstrated the importance of the kinetics of the host response to H5N1 pathogenesis and its relationship with clinical disease severity and virus replication. These kinetic properties imply that time-matched comparisons of 'omics profiles to viral infections give limited views to differentiate host-responses. Moreover, these results demonstrate that a fast activation of the host-response at the earliest time points post-infection is critical for protective mechanisms against fast replicating viruses.

Modeling host genetic regulation of influenza pathogenesis in the collaborative cross

Genetic variation contributes to host responses and outcomes following infection by influenza A virus or other viral infections. Yet narrow windows of disease symptoms and confounding environmental factors have made it difficult to identify polymorphic genes that contribute to differential disease outcomes in human populations. Therefore, to control for these confounding environmental variables in a system that models the levels of genetic diversity found in outbred populations such as humans, we used incipient lines of the highly genetically diverse Collaborative Cross (CC) recombinant inbred (RI) panel (the pre-CC population) to study how genetic variation impacts influenza associated disease across a genetically diverse population. A wide range of variation in influenza disease related phenotypes including virus replication, virus-induced inflammation, and weight loss was observed. Many of the disease associated phenotypes were correlated, with viral replication and virus-induced inflammation being predictors of virus-induced weight loss. Despite these correlations, pre-CC mice with unique and novel disease phenotype combinations were observed. We also identified sets of transcripts (modules) that were correlated with aspects of disease. In order to identify how host genetic polymorphisms contribute to the observed variation in disease, we conducted quantitative trait loci (QTL) mapping. We identified several QTL contributing to specific aspects of the host response including virus-induced weight loss, titer, pulmonary edema, neutrophil recruitment to the airways, and transcriptional expression. Existing whole-genome sequence data was applied to identify high priority candidate genes within QTL regions. A key host response QTL was located at the site of the known anti-influenza Mx1 gene. We sequenced the coding regions of Mx1 in the eight CC founder strains, and identified a novel Mx1 allele that showed reduced ability to inhibit viral replication, while maintaining protection from weight loss.

Host responses to an infectious agent are highly variable across the human population, however, it is not entirely clear how various factors such as pathogen dose, demography, environment and host genetic polymorphisms contribute to variable host responses and infectious outcomes. In this study, a new in vivo experimental model was used that recapitulates many of the genetic characteristics of an outbred population, such as humans. By controlling viral dose, environment and demographic variables, we were able to focus on the role that host genetic variation plays in influenza virus infection. Both the range of disease phenotypes and the combinations of sets of disease phenotypes at 4 days post infection across this population exhibited a large amount of diversity, reminiscent of the variation seen across the human population. Multiple host genome regions were identified that contributed to different aspects of the host response to influenza infection. Taken together, these results emphasize the critical role of host genetics in the response to infectious diseases. Given the breadth of host responses seen within this population, several new models for unique host responses to infection were identified.

Genetic analysis of complex traits in the emerging Collaborative Cross

The Collaborative Cross (CC) is a mouse recombinant inbred strain panel that is being developed as a resource for mammalian systems genetics. Here we describe an experiment that uses partially inbred CC lines to evaluate the genetic properties and utility of this emerging resource. Genome-wide analysis of the incipient strains reveals high genetic diversity, balanced allele frequencies, and dense, evenly distributed recombination sites-all ideal qualities for a systems genetics resource. We map discrete, complex, and biomolecular traits and contrast two quantitative trait locus (QTL) mapping approaches. Analysis based on inferred haplotypes improves power, reduces false discovery, and provides information to identify and prioritize candidate genes that is unique to multifounder crosses like the CC. The number of expression QTLs discovered here exceeds all previous efforts at eQTL mapping in mice, and we map local eQTL at 1-Mb resolution. We demonstrate that the genetic diversity of the CC, which derives from random mixing of eight founder strains, results in high phenotypic diversity and enhances our ability to map causative loci underlying complex disease-related traits.

Beneficial fitness effects are not exponential for two viruses

The distribution of fitness effects for beneficial mutations is of paramount importance in determining the outcome of adaptation. It is generally assumed that fitness effects of beneficial mutations follow an exponential distribution, for example, in theoretical treatments of quantitative genetics, clonal interference, experimental evolution, and the adaptation of DNA sequences. This assumption has been justified by the statistical theory of extreme values, because the fitnesses conferred by beneficial mutations should represent samples from the extreme right tail of the fitness distribution. Yet in extreme value theory, there are three different limiting forms for right tails of distributions, and the exponential describes only those of distributions in the Gumbel domain of attraction. Using beneficial mutations from two viruses, we show for the first time that the Gumbel domain can be rejected in favor of a distribution with a right-truncated tail, thus providing evidence for an upper bound on fitness effects. Our data also violate the common assumption that small-effect beneficial mutations greatly outnumber those of large effect, as they are consistent with a uniform distribution of beneficial effects.

High frequency of mutations that expand the host range of an RNA virus

The ability of a virus population to colonize a novel host is predicted to depend on the equilibrium frequency of potential colonists (i.e., genotypes capable of infecting the novel host) in the source population. In this study, we investigated the determinants of the equilibrium frequency of potential colonists in the RNA bacteriophage 6. We isolated 40 spontaneous mutants capable of infecting a novel Pseudomonas syringae host and sequenced their host attachment genes to identify the responsible mutations. We observed 16 different mutations in the host attachment gene and used a new statistical approach to estimate that 39 additional mutations were missed by our screen. Phenotypic and fitness assays confirmed that the proximate mechanism underlying host range expansion was an increase in the ability to attach to the novel host and that acquisition of this ability most often imposed a cost for growth rate on two standard hosts. Considered in a population genetic framework, our data suggest that host range mutations should exist in phage populations at an equilibrium frequency (3 x 10(-4)) that exceeds the phage mutation rate by more than two orders of magnitude. Thus, colonization of novel hosts is unlikely to be limited by an inability to produce appropriate mutations.