Quantitative proteomics identifies ferritin in the innate immune response of<i>C. elegans</i>
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
When encountering a pathogen, all organisms evoke a protective response by inducing defense mechanisms to help fight off the invader. The invertebrate model organism Caenorhabditis elegans has proven to be valuable for studies of the host response and the small nematode mounts a substantial transcriptional response to numerous pathogens. Here, we use global quantitative proteomics to profile the response to infection with E. coli strain LF82 isolated from patients suffering from Crohn's disease, an inflammatory bowel disease. We show that LF82 infection induces more than one hundred proteins. The response share many functional categories with other innate immunity studies in C. elegans, but also identifies novel host immune effector proteins. We demonstrate functional relevance for four LF82 induced proteins, including a lysozyme and a C-type lectin. The ferritin homolog FTN-2 was shown to be necessary for the full protective response against the Gram-negative LF82 and the Gram-positive pathogen Staphylococcus aureus. This study is the first to demonstrate a role for ferritin in the innate immune response of C. elegans, and our results suggests that quantitative proteomics is an attractive approach for identifying additional components in the complex immune response of the nematode.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it