Distinct gene loci control the host response to influenza H1N1 virus infection in a time-dependent manner

<p>Abstract</p> <p>Background</p> <p>There is strong but mostly circumstantial evidence that genetic factors modulate the severity of influenza infection in humans. Using genetically diverse but fully inbred strains of mice it has been shown that host sequence variants have a strong influence on the severity of influenza A disease progression. In particular, C57BL/6J, the most widely used mouse strain in biomedical research, is comparatively resistant. In contrast, DBA/2J is highly susceptible.</p> <p>Results</p> <p>To map regions of the genome responsible for differences in influenza susceptibility, we infected a family of 53 BXD-type lines derived from a cross between C57BL/6J and DBA/2J strains with influenza A virus (PR8, H1N1). We monitored body weight, survival, and mean time to death for 13 days after infection. <it>Qivr5</it> (quantitative trait for influenza virus resistance on chromosome 5) was the largest and most significant QTL for weight loss. The effect of <it>Qivr5</it> was detectable on day 2 post infection, but was most pronounced on days 5 and 6. Survival rate mapped to <it>Qivr5</it>, but additionally revealed a second significant locus on chromosome 19 (<it>Qivr19</it>). Analysis of mean time to death affirmed both <it>Qivr5</it> and <it>Qivr19</it>. In addition, we observed several regions of the genome with suggestive linkage. There are potentially complex combinatorial interactions of the parental alleles among loci. Analysis of multiple gene expression data sets and sequence variants in these strains highlights about 30 strong candidate genes across all loci that may control influenza A susceptibility and resistance.</p> <p>Conclusions</p> <p>We have mapped influenza susceptibility loci to chromosomes 2, 5, 16, 17, and 19. Body weight and survival loci have a time-dependent profile that presumably reflects the temporal dynamic of the response to infection. We highlight candidate genes in the respective intervals and review their possible biological function during infection.</p

ATR-FTIR spectroscopy reveals genomic loci regulating the tissue response in high fat diet fed BXD recombinant inbred mouse strains

Background: Obesity-associated organ-specific pathological states can be ensued from the dysregulation of the functions of the adipose tissues, liver and muscle. However, the influence of genetic differences underlying gross-compositional differences in these tissues is largely unknown. In the present study, the analytical method of ATR-FTIR spectroscopy has been combined with a genetic approach to identify genetic differences responsible for phenotypic alterations in adipose, liver and muscle tissues. Results: Mice from 29 BXD recombinant inbred mouse strains were put on high fat diet and gross-compositional changes in adipose, liver and muscle tissues were measured by ATR-FTIR spectroscopy. The analysis of genotype-phenotype correlations revealed significant quantitative trait loci (QTL) on chromosome 12 for the content of fat and collagen, collagen integrity, and the lipid to protein ratio in adipose tissue and on chromosome 17 for lipid to protein ratio in liver. Using gene expression and sequence information, we suggest Rsad2 (viperin) and Colec11 (collectin-11) on chromosome 12 as potential quantitative trait candidate genes. Rsad2 may act as a modulator of lipid droplet contents and lipid biosynthesis; Colec11 might play a role in apoptopic cell clearance and maintenance of adipose tissue. An increased level of Rsad2 transcripts in adipose tissue of DBA/2J compared to C57BL/6J mice suggests a cis-acting genetic variant leading to differential gene activation. Conclusion: The results demonstrate that the analytical method of ATR-FTIR spectroscopy effectively contributed to decompose the macromolecular composition of tissues that accumulate fat and to link this information with genetic determinants. The candidate genes in the QTL regions may contribute to obesity-related diseases in humans, in particular if the results can be verified in a bigger BXD cohort

Bioinformatics tools and database resources for systems genetics analysis in mice—a short review and an evaluation of future needs

During a meeting of the SYSGENET working group ‘Bioinformatics’, currently available software tools and databases for systems genetics in mice were reviewed and the needs for future developments discussed. The group evaluated interoperability and performed initial feasibility studies. To aid future compatibility of software and exchange of already developed software modules, a strong recommendation was made by the group to integrate HAPPY and R/qtl analysis toolboxes, GeneNetwork and XGAP database platforms, and TIQS and xQTL processing platforms. R should be used as the principal computer language for QTL data analysis in all platforms and a ‘cloud’ should be used for software dissemination to the community. Furthermore, the working group recommended that all data models and software source code should be made visible in public repositories to allow a coordinated effort on the use of common data structures and file formats

The proteolytic activation of (H3N2) influenza A virus hemagglutinin is facilitated by different type II transmembrane serine proteases

Cleavage of influenza virus hemagglutinin (HA) by host cell proteases is necessary for viral activation and infectivity. In humans and mice, members of the type II transmembrane protease family (TTSP), e.g., TMPRSS2, TMPRSS4, and TMPRSS11d (HAT), have been shown to cleave influenza virus HA for viral activation and infectivity in vitro. Recently, we reported that inactivation of a single HA-activating protease gene, Tmprss2, in knockout mice inhibits the spread of H1N1 influenza viruses. However, after infection of Tmprss2 knockout mice with an H3N2 influenza virus, only a slight increase in survival was observed, and mice still lost body weight. In this study, we investigated an additional trypsin-like protease, TMPRSS4. Both TMPRSS2 and TMPRSS4 are expressed in the same cell types of the mouse lung. Deletion of Tmprss4 alone in knockout mice does not protect them from body weight loss and death upon infection with H3N2 influenza virus. In contrast, Tmprss2-/- Tmprss4-/- double-knockout mice showed a remarkably reduced virus spread and lung pathology, in addition to reduced body weight loss and mortality. Thus, our results identified TMPRSS4 as a second host cell protease that, in addition to TMPRSS2, is able to activate the HA of H3N2 influenza virus in vivo

When the optimal is not the best: parameter estimation in complex biological models

Background: The vast computational resources that became available during the past decade enabled the development and simulation of increasingly complex mathematical models of cancer growth. These models typically involve many free parameters whose determination is a substantial obstacle to model development. Direct measurement of biochemical parameters in vivo is often difficult and sometimes impracticable, while fitting them under data-poor conditions may result in biologically implausible values. Results: We discuss different methodological approaches to estimate parameters in complex biological models. We make use of the high computational power of the Blue Gene technology to perform an extensive study of the parameter space in a model of avascular tumor growth. We explicitly show that the landscape of the cost function used to optimize the model to the data has a very rugged surface in parameter space. This cost function has many local minima with unrealistic solutions, including the global minimum corresponding to the best fit. Conclusions: The case studied in this paper shows one example in which model parameters that optimally fit the data are not necessarily the best ones from a biological point of view. To avoid force-fitting a model to a dataset, we propose that the best model parameters should be found by choosing, among suboptimal parameters, those that match criteria other than the ones used to fit the model. We also conclude that the model, data and optimization approach form a new complex system, and point to the need of a theory that addresses this problem more generally

Influenza A virus-derived defective interfering particles for antiviral treatment

Here, we report on genetically engineered, propagation-incompetent influenza A virus (IAV) particles, so-called defective interfering particles (DIPs) that have been suggested as a promising novel antiviral agent. Typically, IAV DIPs harbor a large internal deletion in one of their eight genomic viral RNA (vRNA) segments. Further, DIPs are capable of hijacking cellular and viral resources upon co-infection with fully infectious standard virus (STV), resulting in an antiviral effect. Besides this replication interference, DIP infection also stimulates innate immunity, adding to the antiviral efficacy. So far, DIPs were produced in embryonated chicken eggs. To improve scalability and flexibility of processes as well as to increase product quality, we established a cell culture-based DIP production system [1,2]. This includes the development of a genetically engineered virus-cell propagation system that allows production of DIPs without the need to add infectious STV to complement missing gene functions of DIPs. Specifically, the MDCK suspension cell line generated expresses the PB2 protein [2], encoded by segment 1 (S1) of IAV, which is not expressed by “DI244” - a prototypic, well-characterized DIP harboring a deletion in S1. Using this cell culture-based production process in batch [2,3] and perfusion mode [4] at laboratory scale, we show that we can achieve very high DI244 titers of up to 2.6E+11 DIPs/mL. Infections of mice demonstrated that intranasal administration of the produced DI244 material resulted in no apparent toxic effects and in a full rescue of mice co-treated with an otherwise lethal dose of IAV [2]. Please click Download on the upper right corner to see the full abstract

Identification of Molecular Distinctions Between Normal Breast-Associated Fibroblasts and Breast Cancer-Associated Fibroblasts

Stromal fibroblasts influence the behavior of breast epithelial cells. Fibroblasts derived from normal breast (NAF) inhibit epithelial growth, whereas fibroblasts from breast carcinomas (CAF) have less growth inhibitory capacity and can promote epithelial growth. We sought to identify molecules that are differentially expressed in NAF versus CAF and potentially responsible for their different growth regulatory abilities. To determine the contribution of soluble molecules to fibroblast–epithelial interactions, NAF were grown in 3D, transwell or direct contact co-cultures with MCF10AT epithelial cells. NAF suppressed proliferation of MCF10AT in both direct contact and transwell co-cultures, but this suppression was significantly greater in direct co-cultures, indicating involvement of both soluble and contact factors. Gene expression profiling of early passage fibroblast cultures identified 420 genes that were differentially expressed in NAF versus CAF. Of the eight genes selected for validation by real-time PCR, FIBULIN 1, was overexpressed in NAF, and DICKKOPF 1, NEUREGULIN 1, PLASMINOGEN ACTIVATOR INHIBITOR 2, and TISSUE PLASMINOGEN ACTIVATOR were overexpressed in CAF. A higher expression of FIBULIN 1 in normal- than cancer-associated fibroblastic stroma was confirmed by immunohistochemistry of breast tissues. Among breast cancers, stromal expression of Fibulin 1 protein was higher in estrogen receptor α-positive cancers and low stromal expression of Fibulin 1 correlated with a higher proliferation of cancer epithelial cells. In conclusion, expression profiling of NAF and CAF cultures identified many genes with potential relevance to fibroblast–epithelial interactions in breast cancer. Furthermore, these early passage fibroblast cultures can be representative of gene expression in stromal fibroblasts in vivo

XGAP: a uniform and extensible data model and software platform for genotype and phenotype experiments.

We present an extensible software model for the genotype and phenotype community, XGAP. Readers can download a standard XGAP (http://www.xgap.org) or auto-generate a custom version using MOLGENIS with programming interfaces to R-software and web-services or user interfaces for biologists. XGAP has simple load formats for any type of genotype, epigenotype, transcript, protein, metabolite or other phenotype data. Current functionality includes tools ranging from eQTL analysis in mouse to genome-wide association studies in humans.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

A comparative evaluation of various invasion assays testing colon carcinoma cell lines

Various colon carcinoma cell lines were tested in different invasion assays, i.e. invasion into Matrigel, into confluent fibroblast layers and into chicken heart tissue. Furthermore, invasive capacity and metastatic potential were determined in nude mice. The colon carcinoma cells used were the human cell lines Caco-2, SW-480, SW-620 and HT-29, and the murine lines Colon-26 and -38. None of the human colon carcinoma cells migrated through porous membranes coated with Matrigel; of the murine lines, only Colon-26 did. When incubated in a mixture of Matrigel and culture medium non-invading cells formed spheroid cultures, whereas invading cells showed a stellate outgrowth. Only the heterogeneously shaped (epithelioid and stellate) cells of SW-480 and SW-620 and the spindle-shaped cells of Colon-26 invaded clearly confluent skin and colon fibroblasts as well as chicken heart tissue. However, when transplanted into the caecum of nude and syngeneic mice, all the lines tested were invasive with the exception of Caco-2 cells. We conclude that the outcome of in vitro tests measuring the invasive capacity of neoplastic cells is largely dependent on the test system used. Invasive capacity in vitro is strongly correlated with cells having a spindle cell shape, vimentin expression and E-cadherin down regulation. In contrast, HT-29 and Colon-38 cells having an epithelioid phenotype were clearly invasive and metastatic in vivo, but not in vitro. © 1999 Cancer Research Campaig