Identification of novel proteins and mRNAs differentially bound to the Leishmania Poly(A) Binding Proteins reveals a direct association between PABP1, the RNA-binding protein RBP23 and mRNAs encoding ribosomal proteins
Bibliographic record
Abstract
Poly(A) Binding Proteins (PABPs) are major eukaryotic RNA-binding proteins (RBPs) with multiple roles associated with mRNA stability and translation and characterized mainly from multicellular organisms and yeasts. A variable number of PABP homologues are seen in different organisms however the biological reasons for multiple PABPs are generally not well understood. In the unicellular Leishmania, dependent on post-transcriptional mechanisms for the control of its gene expression, three distinct PABPs are found, with yet undefined functional distinctions. Here, using RNA-immunoprecipitation sequencing analysis we show that the Leishmania PABP1 preferentially associates with mRNAs encoding ribosomal proteins, while PABP2 and PABP3 bind to an overlapping set of mRNAs distinct to those enriched in PABP1. Immunoprecipitation studies combined to mass-spectrometry analysis identified RBPs differentially associated with PABP1 or PABP2, including RBP23 and DRBD2, respectively, that were investigated further. Both RBP23 and DRBD2 bind directly to the three PABPs in vitro, but reciprocal experiments confirmed preferential co-immunoprecipitation of PABP1, as well as the EIF4E4/EIF4G3 based translation initiation complex, with RBP23. Other RBP23 binding partners also imply a direct role in translation. DRBD2, in contrast, co-immunoprecipitated with PABP2, PABP3 and with RBPs unrelated to translation. Over 90% of the RBP23-bound mRNAs code for ribosomal proteins, mainly absent from the transcripts co-precipitated with DRBD2. These experiments suggest a novel and specific route for translation of the ribosomal protein mRNAs, mediated by RBP23, PABP1 and the associated EIF4E4/EIF4G3 complex. They also highlight the unique roles that different PABP homologues may have in eukaryotic cells associated with mRNA translation.
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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 | 0.000 |
| 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 | 0.001 |
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".