Enhanced translation expands the endo-lysosome size and promotes antigen presentation during phagocyte activation
Bibliographic record
Abstract
The mechanisms that govern organelle adaptation and remodelling remain poorly defined. The endo-lysosomal system degrades cargo from various routes, including endocytosis, phagocytosis, and autophagy. For phagocytes, endosomes and lysosomes (endo-lysosomes) are kingpin organelles because they are essential to kill pathogens and process and present antigens. During phagocyte activation, endo-lysosomes undergo a morphological transformation, going from a collection of dozens of globular structures to a tubular network in a process that requires the phosphatidylinositol-3-kinase-AKT-mechanistic target of rapamycin (mTOR) signalling pathway. Here, we show that the endo-lysosomal system undergoes an expansion in volume and holding capacity during phagocyte activation within 2 h of lipopolysaccharides (LPS) stimulation. Endo-lysosomal expansion was paralleled by an increase in lysosomal protein levels, but this was unexpectedly largely independent of the transcription factor EB (TFEB) and transcription factor E3 (TFE3), which are known to scale up lysosome biogenesis. Instead, we demonstrate a hitherto unappreciated mechanism of acute organelle expansion via mTOR Complex 1 (mTORC1)-dependent increase in translation, which appears to be mediated by both S6Ks and 4E-BPs. Moreover, we show that stimulation of RAW 264.7 macrophage cell line with LPS alters translation of a subset but not all of mRNAs encoding endo-lysosomal proteins, thereby suggesting that endo-lysosome expansion is accompanied by functional remodelling. Importantly, mTORC1-dependent increase in translation activity was necessary for efficient and rapid antigen presentation by dendritic cells. Collectively, we identified a previously unknown and functionally relevant mechanism for endo-lysosome expansion that relies on mTORC1-dependent translation to stimulate endo-lysosome biogenesis in response to an infection signal.
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.
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 | 0.000 |
| 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".