Immune system | EPFL Graph Search

The immune system is a network of biological processes that protects an organism from diseases. It detects and responds to a wide variety of pathogens, from viruses to parasitic worms, as well as cancer cells and objects such as wood splinters, distinguishing them from the organism's own healthy tissue. Many species have two major subsystems of the immune system. The innate immune system provides a preconfigured response to broad groups of situations and stimuli. The adaptive immune system provides a tailored response to each stimulus by learning to recognize molecules it has previously encountered. Both use molecules and cells to perform their functions. Nearly all organisms have some kind of immune system. Bacteria have a rudimentary immune system in the form of enzymes that protect against viral infections. Other basic immune mechanisms evolved in ancient plants and animals and remain in their modern descendants. These mechanisms include phagocytosis, antimicrobial peptides calle

Investigation of transcriptional partners and genes downstream of Foxn1

Zineb Bekkali

The thymus is the second fundamental organ of the immune system after the bone marrow; it is the essential for T cell maturation and repertoire selection. The function of the thymus critically depends on the thymic epithelium, which is structured in two distinct regions: The cortex and the medulla. The knowledge about molecular mechanisms involved in thymus development is limited. However, some evidences suggest that the Hox, Pax, Six, Eya, Gcm2, FGFs and Foxn1 are key players in thymus organogenesis. Foxn1 is essential for thymic epithelial cell development but its exact role is still unknown. The null mutation in the transcription factor Foxn1 generates the nude phenotype of athymia and hairlessness. The aim of our laboratory is to better understand thymus development and specially focuses on the Foxn1 function. The aim of this project is then to investigate target genes and transcription partners of Foxn1 as a transcriptional factor. As a transcription factor, Foxn1 protein should be able to bind with DNA but should also interact with other proteins such as cofactors in order to activate its target genes. At present, the transcriptional partners of Foxn1 are completely unknown in the literature and the proteinprotein interaction databases. The experimental approach proposed here is the standard method for identification of unknown transcriptional partners: Immunoprecipitation (IP) followed by a mass spectrometry analysis. The list of protein candidates can then be validated by Western blotting. We identified the right antibodies to use for this procedure and optimised protocols for the IP. We also performed a mass spectrometry analysis that was not conclusive, however, the platform is now established to complete this analysis. Only little is known about genes up- or down-stream Foxn1. Some genes such as FgfR2IIIb, DLL4 and CCL25 are believed to be up-regulated by Foxn1. Our laboratory has generated a revertible hypomorphic allele of Foxn1 and have used this to obtain a series of six allelic combinations at Foxn1. These mice, expressing different levels of Foxn1, are a very useful tool in order to investigate target genes of Foxn1. In particular, we wish to investigate whether different Foxn1 targets are activated at different Foxn1 levels. 6 To reach this objective, the proposed approach is the comparison of gene expression profiles of thymic epithelial and mesenchymal cells of the allelic series at two different time points E13.5 and E15.5 using a Solexa tool called SAGE (Serial Analysis of Gene Expression). As preliminary analysis before the global gene expression analysis, we have determined expression profiles of several genes across the allelic series by quantitative PCR. Our findings suggest that DLL4, CCL25, FgfR2IIIb, FGF10 and possible Pax1 are direct or indirect targets of Foxn1 activated at different levels of Foxn1. DLL4 and CCL25 seem to be involved in lymphocyte attraction and maturation. FgfR2IIIb appears to be important for thymic epithelium differentiation and development by increasing the sensitivity of epithelial cells to FGF10 signalling. Finally, Pax1 is possibly required downstream of Foxn1 for terminal differentiation of cortical thymic epithelial cells

2009

The double-edged toxins

Mario Gonzalo Garcia Arraez

Many insect species are associated with endosymbiotic bacteria which have the particularity of living within host tissues. Endosymbionts benefit from this stable and nutritious environment, while providing ecological advantages to their host, such as protection against parasites or thermal tolerance. Spiroplasma poulsonii is an endosymbiotic bacterium that infects natural populations of Drosophila melanogaster. Spiroplasma poulsonii lacks a cell wall, a fact that renders it invisible to the host immune system and allows it to thrive in the host hemolymph. It invades the female germline by co-opting the hostâs yolk transport and uptake machinery, which ensures its vertical transmission. Its efficient transmission is associated with a phenotype called male-killing, whereby infected male embryos die during their early development while infected females survive. The mechanisms that ensure the stability of Drosophila-Spiroplasma symbiosis are increasingly well understood, but the bacterial genes involved remain poorly known because of the intractability of Spiroplasma. This project aims at better characterizing the Drosophila-Spiroplasma interaction, with particular focus on the bacterial side. In the first part, I developed a method to cultivate Spiroplasma poulsonii in vitro by optimizing a commercially available medium. This culture method allowed comparing the transcriptome of in vitro grown versus host-grown Spiroplasma, enabling us to identify putative genes involved in the interaction with the host. Interestingly, inside its insect host, S. poulsonii up-regulates genes coding for toxins of the Ribosomal Inactivating Protein (RIP) family. RIPs were previously known for their role in host protection against macro-parasites, such as wasps and nematodes. Their up-regulation in unparasitized hosts compared to culture was thus peculiar, raising the question what effect these RIPs have on host biology. Thus, in the second part, I studied the function of S. poulsonii RIPs in the absence of parasites. I showed that two of them are constantly expressed within the host and provide evidence that these toxins shorten host life span and increase embryonic mortality. Interestingly, the expression of RIPs was more toxic to male embryos than females, suggesting that RIPs contribute to S. poulsonii-induced male-killing. Last, I studied the D. melanogaster response to RIPs, and how the host mitigates the deleterious effects of these toxins by up-regulating the cytosolic chaperone Heat-Shock-Protein 70B (HSP70B). This protein carries out essential functions in protein homeostasis under normal and stressful conditions such as folding, refolding, or increasing the half-life of proteins. Interestingly, up-regulation of Hsp70B in the presence of RIPs results in an increased lifespan and in a better tolerance to heat stress, which may be ecologically advantageous. Altogether, this work illustrates how Spiroplasma-derived RIP toxins can differentially affect Drosophila depending on the ecological context, ranging from beneficial upon parasite infection or heat shock to detrimental in the absence of such environmental pressures.

EPFL2018

Statistical Analysis of Chao’s Immune System Simulation

Eric Winnington

Modeling the immune system (IS) means putting together a set of assumptions about its components (cells and organs) and their interactions. Simulations of a model show joint behavior of the components, which for complex realistic models is often impossible to find analytically. Simulations allow us to experiment on how initial concentrations and properties of the immune cells and viruses impact the IS behavior, and gain better quantitative and qualitative insight into how the IS works and why different behavior patterns occur. A simulation, once it has been created, must be reviewed both statistically and analytically as well as validated from the biological point of view. We analyzed Chao’s immune system simulation [1][2] from a statistical and analytical point. We explicited both the Markov chain which was simulated and the underlying process on which Chao’s stage-structured approach was built. Furthermore, we established a test protocol for timestep validation which Chao’s simulator passed. We evaluated Chao’s simulator’s dependence on the random number generator, which was shown to be negligible. Finally, we evaluated the simulator output and our major result is the discovery of a secondary response to a primary infection, an occurrence is not shown in Chao’s dissertation. A tertiary response to the infection is never possible due to the size of the secondary response caused by memory cells.

2005