Critical Roles for LIGHT and Its Receptors in Generating T Cell-Mediated Immunity during Leishmania donovani Infection

LIGHT (TNFSF14) is a member of the TNF superfamily involved in inflammation and defence against infection. LIGHT signals via two cell-bound receptors; herpes virus entry mediator (HVEM) and lymphotoxin-beta receptor (LTβR). We found that LIGHT is critical for control of hepatic parasite growth in mice with visceral leishmaniasis (VL) caused by infection with the protozoan parasite Leishmania donovani. LIGHT-HVEM signalling is essential for early dendritic cell IL-12/IL-23p40 production, and the generation of IFNγ- and TNF-producing T cells that control hepatic infection. However, we also discovered that LIGHT-LTβR interactions suppress anti-parasitic immunity in the liver in the first 7 days of infection by mechanisms that restrict both CD4+ T cell function and TNF-dependent microbicidal mechanisms. Thus, we have identified distinct roles for LIGHT in infection, and show that manipulation of interactions between LIGHT and its receptors may be used for therapeutic advantage

Genes from Chagas Susceptibility Loci That Are Differentially Expressed in T. cruzi-Resistant Mice Are Candidates Accounting for Impaired Immunity

Variation between inbred mice of susceptibility to experimental Trypanosoma cruzi infection has frequently been described, but the immunogenetic background is poorly understood. The outcross of the susceptible parental mouse strains C57BL/6 (B6) and DBA/2 (D2), B6D2F1 (F1) mice, is highly resistant to this parasite. In the present study we show by quantitative PCR that the increase of tissue parasitism during the early phase of infection is comparable up to day 11 between susceptible B6 and resistant F1 mice. A reduction of splenic parasite burdens occurs thereafter in both strains but is comparatively retarded in susceptible mice. Splenic microarchitecture is progressively disrupted with loss of follicles and B lymphocytes in B6 mice, but not in F1 mice. By genotyping of additional backcross offspring we corroborate our earlier findings that susceptibility maps to three loci on Chromosomes 5, 13 and 17. Analysis of gene expression of spleen cells from infected B6 and F1 mice with microarrays identifies about 0.3% of transcripts that are differentially expressed. Assuming that differential susceptibility is mediated by altered gene expression, we propose that the following differentially expressed transcripts from these loci are strong candidates for the observed phenotypic variation: H2-Eα, H2-D1, Ng23, Msh5 and Tubb5 from Chromosome 17; and Cxcl11, Bmp2k and Spp1 from Chromosome 5. Our results indicate that innate mechanisms are not of primary relevance to resistance of F1 mice to T. cruzi infection, and that differential susceptibility to experimental infection with this protozoan pathogen is not paralleled by extensive variation of the transcriptome

Syndromics: A Bioinformatics Approach for Neurotrauma Research

Substantial scientific progress has been made in the past 50 years in delineating many of the biological mechanisms involved in the primary and secondary injuries following trauma to the spinal cord and brain. These advances have highlighted numerous potential therapeutic approaches that may help restore function after injury. Despite these advances, bench-to-bedside translation has remained elusive. Translational testing of novel therapies requires standardized measures of function for comparison across different laboratories, paradigms, and species. Although numerous functional assessments have been developed in animal models, it remains unclear how to best integrate this information to describe the complete translational “syndrome” produced by neurotrauma. The present paper describes a multivariate statistical framework for integrating diverse neurotrauma data and reviews the few papers to date that have taken an information-intensive approach for basic neurotrauma research. We argue that these papers can be described as the seminal works of a new field that we call “syndromics”, which aim to apply informatics tools to disease models to characterize the full set of mechanistic inter-relationships from multi-scale data. In the future, centralized databases of raw neurotrauma data will enable better syndromic approaches and aid future translational research, leading to more efficient testing regimens and more clinically relevant findings