Nod1 and Nod2 in Innate Immune Responses, Adaptive Immunity and Bacterial Infection
Bibliographic record
Abstract
The last decade has been witness to a number of seminal discoveries in the field of innate immunity. The discovery that microbial molecules and endogenous danger signals can be detected by germ-line encoded receptors has changed the way we study the immune system. Indeed, the characterization of Toll in Drosophila as a sensor of microbial products in 1997 then led to the discovery of a family of Toll Like Receptors (TLRs) in mammals. TLRs are critical for the induction of inflammatory responses and the generation of a successful adaptive immune response. The array of ligands that these transmembrane proteins recognized mediates defense against bacteria, viruses, fungus and parasites, as well as, possibly, cancerous cells. In addition to this membrane-bound family of recognition proteins, two families of pattern recognition receptors have been recently shown to respond to microbial and chemical ligands within the cytosol. These represent the Nod Like Receptors (NLRs) and RIGI-like helicase receptor (RLH) families. Nod1 and Nod2 are members of the NLR family of proteins, which are responsible for the recognition of components derived from the bacterial cell wall, more precisely, moieties of peptidoglycan. As such, Nod1 and Nod2 are implicated in the recognition and the defense against bacterial pathogens. Importantly, the genes encoding these two proteins have also been linked to the etiology of several inflammatory disorders such as Crohn’s disease and asthma. In this thesis, we show that recognition of Nod1 and Nod2 ligands generates a rapid and transient inflammatory response in vivo. When co-injected with a model protein, Nod1 and Nod2 ligands exhibit adjuvant properties that lead to the generation of an antigen-specific Th2 type adaptive immune response. Surprisingly, recognition of the Nod1 ligand in non-hematopoietic cells is critical for the generation of this immune response. In contrast, TLRs classically tip the balance towards a Th1 response and interestingly, co-injection of TLR and Nod ligands synergize to generate a more potent immune response characterized by the generation of Th1, Th2 and Th17 T cell respones. To study the role of Nod1 and Nod2 in the context of a bacterial infection in vivo, we used an intestinal mouse pathogen, Salmonella enterica serovar Typhimurium. We were able to show that Nod1-deficient mice, but not Nod2-deficient mice, are more susceptible to the strain of this bacterium, which enters the host through the active pickup in the intestinal lumen by underlying myeloid cells. This sampling mechanism is mediated by a subset of dendritic cells that populate the intestinal lamina propria. Accordingly, the defect seen in Nod1-deficient mice localizes to the mucosal barrier where these dendritic cells appear to have an impaired response towards the bacteria. Taken together, these results increase our knowledge on the general role of Nod1 and Nod2 in immunity and might generate new avenues of research and potential therapeutic targets.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".