Insights into the diversity of NOD-like receptors: Identification and expression analysis of NLRC3, NLRC5 and NLRX1 in rainbow trout
Bibliographic record
Abstract
Nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) are efficient soluble intracellular sensors that activate defense mechanisms against pathogens. In teleost fish, the involvement of NLRs in the immune response is not well understood. However, recent work has evidenced the expression of different NLRs in response to some pathogen associated molecular patterns (PAMPs). In the present work, the cDNA sequence encoding three new NOD-like receptors were identified in Oncorhynchus mykiss, namely OmNLRC3, OmNLRC5 and OmNLRX1. Results showed that their sequences coded for proteins of 1135, 836 and 1010 amino acids, respectively. The deduced protein sequences of all receptors showed characteristic domains of this receptor family, such as leucine rich repeats and NACHT domain. Phylogenetic analysis revealed a high degree of identity with other NOD-like receptors and they are clustered into different families. Transcript expression analysis indicated that OmNLRs are constitutively expressed in liver, spleen, intestine, gill, skin and brain. OmNLR expression was upregulated in kidney and gills from rainbow trout in response to LPS. In order to give new insights into the function of these new NLR members, an in vitro model of immune stimulation was established using the rainbow trout cell line RTgill-W1. Expression analysis revealed that RTgill-W1 overexpressed proinflammatory cytokines in response to LPS and poly I:C alongside with a differential overexpression of OmNLRC3, OmNLRC5 and OmNLRX1. The expression of OmNLRC5 was further verified at the protein level by immunofluorescence. Finally, the effect of the overexpressed cytokines on the OmNLR expression by RTgill-W1 cells was assessed, suggesting a regulatory mechanism on OmNLRC3 expression. Overall, results suggest that O. mykiss NOD-like receptors could play a key role in the defense mechanisms of teleost through PAMP recognition. Future studies will focus on gills which could be related with a key sensor mucosal system in one of the most environmentally fish exposed tissues.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".