Gene expression profiling of mouse host response to Listeria monocytogenes infection

Combination of Classifiers Identifies Fungal-Specific Activation of Lysosome Genes in Human Monocytes

Blood stream infections can be caused by several pathogens such as viruses, fungi and bacteria and can cause severe clinical complications including sepsis. Delivery of appropriate and quick treatment is mandatory. However, it requires a rapid identification of the invading pathogen. The current gold standard for pathogen identification relies on blood cultures and these methods require a long time to gain the needed diagnosis. The use of in situ experiments attempts to identify pathogen specific immune responses but these often lead to heterogeneous biomarkers due to the high variability in methods and materials used. Using gene expression profiles for machine learning is a developing approach to discriminate between types of infection, but also shows a high degree of inconsistency. To produce consistent gene signatures, capable of discriminating fungal from bacterial infection, we have employed Support Vector Machines (SVMs) based on Mixed Integer Linear Programming (MILP). Combining classifiers by joint optimization constraining them to the same set of discriminating features increased the consistency of our biomarker list independently of leukocyte-type or experimental setup. Our gene signature showed an enrichment of genes of the lysosome pathway which was not uncovered by the use of independent classifiers. Moreover, our results suggest that the lysosome genes are specifically induced in monocytes. Real time qPCR of the identified lysosome-related genes confirmed the distinct gene expression increase in monocytes during fungal infections. Concluding, our combined classifier approach presented increased consistency and was able to "unmask" signaling pathways of less-present immune cells in the used datasets.

Listeriosis downregulates hepatic cytochrome P450 enzymes in sublethal murine infection

PURPOSE

Listeria monocytogenes (Lm) can cross the intestinal barrier in humans and then disseminates into different organs. Invasion of the liver occurs even in sublethal infections, however, knowledge of affected physiological processes is scarce. This study employed a sublethal murine infection model to investigate liver responses systematically by proteomics.

EXPERIMENTAL DESIGN

Liver samples from three stages of the sublethal infection covering the initial invasion, the peak of infection, and the clearance phase (1, 3, 9 days postinoculation) were analyzed in comparison to samples from noninfected mice. Apart from flow cytometry and RT-PCRs for immune status control, liver responses were analyzed by quantitative peptide sequencing (HPLC-Orbitrap Fusion) using 4-plex iTRAQ-labeling.

RESULTS

Accurate MS characterized about 3600 proteins and statistics revealed 15% of the hepatic proteome as regulated. Immunological data as well as protein regulation dynamics strongly indicate stage-specific hepatic responses in sublethal infections. Most notably, this study detected a comprehensive deregulation of drug metabolizing enzymes at all stages, including 25 components of the cytochrome P450 system.

CONCLUSIONS AND CLINICAL RELEVANCE

Sublethal Lm infection deregulates hepatic drug metabolizing pathways. This finding indicates the need to monitor drug administration along Lm infections, especially in all patients needing constant medication.

Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans

Staphylococcus aureus causes a spectrum of human infection. Diagnostic delays and uncertainty lead to treatment delays and inappropriate antibiotic use. A growing literature suggests the host’s inflammatory response to the pathogen represents a potential tool to improve upon current diagnostics. The hypothesis of this study is that the host responds differently to S. aureus than to E. coli infection in a quantifiable way, providing a new diagnostic avenue. This study uses Bayesian sparse factor modeling and penalized binary regression to define peripheral blood gene-expression classifiers of murine and human S. aureus infection. The murine-derived classifier distinguished S. aureus infection from healthy controls and Escherichia coli-infected mice across a range of conditions (mouse and bacterial strain, time post infection) and was validated in outbred mice (AUC>0.97). A S. aureus classifier derived from a cohort of 94 human subjects distinguished S. aureus blood stream infection (BSI) from healthy subjects (AUC 0.99) and E. coli BSI (AUC 0.84). Murine and human responses to S. aureus infection share common biological pathways, allowing the murine model to classify S. aureus BSI in humans (AUC 0.84). Both murine and human S. aureus classifiers were validated in an independent human cohort (AUC 0.95 and 0.92, respectively). The approach described here lends insight into the conserved and disparate pathways utilized by mice and humans in response to these infections. Furthermore, this study advances our understanding of S. aureus infection; the host response to it; and identifies new diagnostic and therapeutic avenues.

Genetic identification of unique immunological responses in mice infected with virulent and attenuated Francisella tularensis

Francisella tularensis is a category A select agent based on its infectivity and virulence but disease mechanisms in infection remain poorly understood. Murine pulmonary models of infection were therefore employed to assess and compare dissemination and pathology and to elucidate the host immune response to infection with the highly virulent Type A F. tularensis strain Schu4 versus the less virulent Type B live vaccine strain (LVS). We found that dissemination and pathology in the spleen was significantly greater in mice infected with F. tularensis Schu4 compared to mice infected with F. tularensis LVS. Using gene expression profiling to compare the response to infection with the two F. tularensis strains, we found that there were significant differences in the expression of genes involved in the apoptosis pathway, antigen processing and presentation pathways, and inflammatory response pathways in mice infected with Schu4 when compared to LVS. These transcriptional differences coincided with marked differences in dissemination and severity of organ lesions in mice infected with the Schu4 and LVS strains. Therefore, these findings indicate that altered apoptosis, antigen presentation and production of inflammatory mediators explain the differences in pathogenicity of F. tularensis Schu4 and LVS.

Expulsion of Trichuris muris is associated with increased expression of angiogenin 4 in the gut and increased acidity of mucins within the goblet cell

Background

Trichuris muris in the mouse is an invaluable model for infection of man with the gastrointestinal nematode Trichuris trichiura. Three T. muris isolates have been studied, the Edinburgh (E), the Japan (J) and the Sobreda (S) isolates. The S isolate survives to chronicity within the C57BL/6 host whereas E and J are expelled prior to reaching fecundity. How the S isolate survives so successfully in its host is unclear.

Results

Microarray analysis was used as a tool to identify genes whose expression could determine the differences in expulsion kinetics between the E and S T. muris isolates. Clear differences in gene expression profiles were evident as early as day 7 post-infection (p.i.). 43 probe sets associated with immune and defence responses were up-regulated in gut tissue from an E isolate-infected C57BL/6 mouse compared to tissue from an S isolate infection, including the message for the anti-microbial protein, angiogenin 4 (Ang4). This led to the identification of distinct differences in the goblet cell phenotype post-infection with the two isolates.

Conclusion

Differences in gene expression levels identified between the S and E-infected mice early during infection have furthered our knowledge of how the S isolate persists for longer than the E isolate in the C57BL/6 mouse. Potential new targets for manipulation in order to aid expulsion have been identified. Further we provide evidence for a potential new marker involving the acidity of the mucins within the goblet cell which may predict outcome of infection within days of parasite exposure.

Microarray Evaluation of the Listeria monocytogenes Infection and Amoxicillin Treatment in Mice

By using Affymetrix Mouse Genome Arrays and 20 biological replicates per experimental condition, the predictive value of liver and blood gene expression profiles previously identified was validated as predictive of Listeria monocytogenes infection severity (lethal and nonlethal infection). The ability of these genes to predict the outcome of antibiotic treatment was also assessed. Lethally infected BALB/c mice were treated with amoxicillin at 10 or 20 mg/kg; only the higher dose prevented death. The liver genes predicted that 70% of the animals treated at 10 mg/kg, but only 25% of the mice treated at 20 mg/kg, belonged to the lethal infection group, and this prediction was similar to the ultimate mortality outcome. These results confirm the value of microarrays as tools to predict host response to infection and efficacy of antibacterial therapy. These results might lead to applications that would help clinicians to adjust antibiotic dosages for efficient treatment but yet without toxicity.

Multifaceted transcriptional regulation of the murine intestinal mucus layer by endogenous microbiota

The intestinal mucus layer and endogenous microbiota are strongly intertwined and this contributes to the maintenance of the epithelial barrier and ultimately of gut homeostasis. To understand the molecular foundations of such relationship, we investigated if the nature of the microbiota transcriptionally regulates mucus layer composition in vivo. We found that the expression of mucins 1 to 4 and trefoil factor 3 was down-regulated in the ileum and colon of conventional and reconventionalized mice compared with germ-free animals. Conversely, very limited colon-restricted changes in transmembrane mucins were detected in mice colonized with human adult or baby microbiota. Moreover, by microarray analysis, the murine endogenous microbiota was found to modulate genes putatively involved in mucin secretion. These findings show that a well-established microbial community participates in the regulation of the gut mucus layer and that its composition and adequacy to the host are key factors in this process.

High Copper Selectively Alters Lipid Metabolism and Cell Cycle Machinery in the Mouse Model of Wilson Disease

Copper is essential for human physiology, but in excess it causes the severe metabolic disorder Wilson disease. Elevated copper is thought to induce pathological changes in tissues by stimulating the production of reactive oxygen species that damage multiple cell targets. To better understand the molecular basis of this disease, we performed genome-wide mRNA profiling as well as protein and metabolite analysis for Atp7b-/- mice, an animal model of Wilson disease. We found that at the presymptomatic stages of the disease, copper-induced changes are inconsistent with widespread radical-mediated damage, which is likely due to the sequestration of cytosolic copper by metallothioneins that are markedly up-regulated in Atp7b-/- livers. Instead, copper selectively up-regulates molecular machinery associated with the cell cycle and chromatin structure and down-regulates lipid metabolism, particularly cholesterol biosynthesis. Specific changes in the transcriptome are accompanied by distinct metabolic changes. Biochemical and mass spectroscopy measurements revealed a 3.6-fold decrease of very low density lipoprotein cholesterol in serum and a 33% decrease of liver cholesterol, indicative of a marked decrease in cholesterol biosynthesis. Consistent with low cholesterol levels, the amount of activated sterol regulatory-binding protein 2 (SREBP-2) is increased in Atp7b-/- nuclei. However, the SREBP-2 target genes are dysregulated suggesting that elevated copper alters SREBP-2 function rather than its processing or re-localization. Thus, in Atp7b-/- mice elevated copper affects specific cellular targets at the transcription and/or translation levels and has distinct effects on liver metabolic function, prior to appearance of histopathological changes. The identification of the network of specific copper-responsive targets facilitates further mechanistic analysis of human disorders of copper misbalance.

Host gene expression profiling in pathogen–host interactions

Microarray technology is a powerful high-throughput tool for the analysis of host-pathogen interactions that permits simultaneous interrogation of the transcriptional status of thousands of genes. Emerging topics from microarray-based studies employing diverse pathogens and cell types suggest an initial common host response largely characterised by features of the innate immune response. However, specific host gene expression patterns that reflect differences between bacteria of related genera, different species of a particular genus, as well as strains within a single species can also be discerned. These differences are indicative of virulence determinant functions and suggest adaptive survival strategies. These studies have led to a more comprehensive understanding of the host response and identified new avenues of research for potential control strategies against pathogens.