The ribosomal RNA transcription landscapes of <i>Plasmodium falciparum</i> and related apicomplexan parasites
Bibliographic record
Abstract
Ribosome biogenesis is essential for the rapid proliferation and life cycle transitions of Plasmodium falciparum, the causative agent of malaria. In eukaryotes, ribosomal RNA synthesis is carried out by RNA polymerase I (Pol I), highly specialized transcriptional machinery. This review provides a comparative analysis of Pol I transcription apparatus in yeast and humans, serving as a reference framework to examine its evolutionary divergence in P. falciparum and related apicomplexans and alveolates. Bioinformatic analyses revealed that some of these organisms lack any identifiable homologues or orthologs of several canonical eukaryotic transcription factors essential for Pol I-mediated transcription, including initiation factor RRN3, activator UBF, and all specific subunits of the promoter recognition complexes. Interestingly, the parasite retains core Pol I subunits, incorporating unique parasite-specific structural domains characterized through AI-based protein complex modeling of P. falciparum Pol I. These adaptations may compensate for the absence of traditional regulatory factors, enabling the parasite to employ distinct mechanisms for promoter recognition and transcription initiation. The substantial differences between parasite and host Pol I transcription machinery create potential targets for therapeutic intervention with parasite-specific elements representing potential drug targets. By integrating evolutionary, structural, and functional perspectives, this review advances our understanding of Pol I transcription in alveolates and its implications for the development of novel antimalarial strategies.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".