Our understanding of host-pathogen interaction is primarily derived from studying how the immune system protects us from a single pathogen. In contrast, it is largely unknown how this response alters the body’s ability to respond to a second infectious agent or the susceptibility to autoimmunity or cancer. Our goal is to investigate the long-term effects of pathogenic challenges on future responses. Currently, we are focusing on changes in the regulatory compartment of the adaptive immune system.

Specifically we aim to:

  1. Analyze how regulatory T cell (Treg) function and the composition of the Treg compartment are affected by different types of infections
  2. Determine how a genetically modified Treg compartment affects susceptibility to infections and autoimmunity
  3. Investigate how previous infections affect the susceptibility to an unrelated secondary challenge
  4. Investigate how co-inhibitory receptors affect pathogen persistence


To achieve this goal we use a wide variety of techniques including:
molecular and biochemical assays, cell culture, flow cytometry, microscopy, immunological assays, animal models (infectious and autoimmune)

The following studies have recently been published:

Common Features of Regulatory T Cell Specialization During Th1 Responses.

Summary by Katharina Littringer:

Common Features of Regulatory T Cell Specialization During Th1 Responses.

CD4+Foxp3+ regulatory T cells (Treg) are essential for maintaining self-tolerance and preventing excessive immune responses. In the course of polarized immune responses, Tregs acquire co-expression of Foxp3 with T helper cell lineage specific transcription factors and homing receptors such as T-bet and CXCR3 during Th1 responses. Specialization into specific subsets is believed to equip Tregs with superior migratory and until now unknown suppressive properties that enable a tailored control of the corresponding immune response.

In this study we defined the signature of Treg cells that specialize during various Th1 polarized infectious challenges of both viral (LCMV, Vaccinia) and bacterial (Legionella pneumophila) orgin and compared it to a Th17 polarized setting induced by Candida albicans infection.We show that Th1 polarized Tregs are equipped with a specific set of co-inihibitory receptors and cytotoxic effector molecules (granzymes) in both mouse and human. While expression of the co-inhibitory receptor Tim-3 is not restricted to Th1 settings we identified the novel co-inhibitory receptor CD85k as well as Lag-3 to be functional predictors of highly suppressive Treg subsets that specifically suppress Th1 effector T cells. The identification of specific markers for Tregs arising in different immune environments is a first step for exploring Tregs therapeutically for selective immune suppression in autoimmunity.

Functional Anti-TIGIT Antibodies Regulate Development of Autoimmunity and Antitumor Immunity.

Congratulations! This publication is among the top 5 most downloaded papers from JI in 2018.

Summary by Michelle Schorer:

Dixon 2018.jpg

TIGIT is a recently discovered co-inhibitory receptor, which is expressed on various immune cells, such as T cells, regulatory T cells and NK cells. Together with CD226 and CD155, TIGIT forms a pathway that regulates T cell mediated immunity. The TIGIT/CD226/CD155 pathway has been implicated to play an important role in various T cell driven autoimmune diseases in humans such as type 1 diabetes, multiple sclerosis and rheumatoid arthritis. Moreover, tumor infiltrating T cells were shown to express high levels of TIGIT in many human tumors.

For this study, we have generated anti-TIGIT antibody clones that show functional (agonistic or blocking) properties in vivo in order to study the immune modulatory properties of TIGIT signaling in both autoimmune and cancer settings. We found that the administration of the agonistic anti-TIGIT antibody modulated autoimmune disease severity, whereas administration of the blocking anti-TIGIT antibody in combination with anti-PD-1 blockade showed a synergic anti-tumor effect in models of colon carcinoma and glioblastoma.