Genomic Evidence for Elements of a Programmed Cell Death Pathway In Plasmodium: Exploiting Programmed Parasite Death for Malaria Control?
Bibliographic record
Abstract
Abstract Abstract 4226 Malaria, caused by species of the Plasmodium parasite, remains a major global health burden. To combat the disease, new areas of investigation are constantly developed with a view to understanding the biology of the organism and identifying potential drug targets. A new line of enquiry has emerged concerning the occurrence of parasite programmed cell death (PCD); however, there are conflicting experimental reports regarding the presence and phenotype of PCD in Plasmodium species. Furthermore, very little genomic evidence exists for a PCD pathway in this genus with only caspase-like domains being detected. One reason for the limited availability of genomic data may be the unusual characteristics of the P. falciparum genome, such as the extreme AT bias. In this study we examined the complete genome sequences of four Plasmodium species (P. falciparum, P. vivax, P. yoelii and P. knowlesi) for evidence of a p53-dependant PCD pathway. This pathway is well characterized in animals, and elements of the molecular machinery have been identified in protozoa. In addition, p53-like responses leading to apoptosis (a common PCD phenotype) have been demonstrated in phylogenetically diverse eukaryotes, including animals, protozoa, green algae and plants, suggesting that the origin of p53-initiated PCD is evolutionary ancient leading us to believe that a similar genomic toolkit may exist in Plasmodium. A detailed analysis of the four Plasmodium genomes was performed using an array of computational approaches, which included standard homology methods, phylogenetics, structural models and a novel evolutionary rate-based alignment algorithm FIRE (Functional Inference using the Rates of Evolution), which was developed to identify homologous and analogous genes in organisms with unusual genomes, such as P. falciparum, and hence low sequence similarity. Homology methods uncovered key elements of a classical PCD pathway, including ATM, MDM2, CR6 and three peptidase C14 (catalytic caspase) domains in each of the four Plasmodium genomes. Phylogenetic analysis demonstrated that the peptidase C14 (caspase) domains are evolutionary ancient and cluster with other PCD-related caspases suggesting that they are involved in a PCD pathway as opposed to other cellular functions that may use similar domains. In addition, highly sensitive hidden Markov models retrieved 15 sequences with low similarity to the eukaryotic p53 DNA-binding domain (DBD). Further analysis revealed that two P. falciparum sequences (accession numbers PFE1120w and PF11_0091 in the Plasmodium database www.PlasmoDB.org version 6.5) may be p53 DBD-like sequences. Both have similar evolutionary rates across codons, as well as anti-parallel beta sheet structures with Greek key topology, which are a characteristic feature of known p53 DBDs. Whether either of these proteins has functional significance for the PCD pathway in P. falciparum requires empirical verification. However, these data and the existence of p53-like activity in plants and algae, suggest that this pathway has an ancient origin and provide the first evidence for a p53-dependant PCD pathway in malaria parasites. The presence of this genomic toolkit raises questions regarding the potential role of this pathway in the P. falciparum lifecycle. The phenomenon of programmed parasite death may have adaptive significance and proteins in the PCD pathway may potentially be sufficiently different from the human orthologs, given the low level of sequence similarity. These findings could thus open a new line of investigation for novel malaria drug targets. Disclosures: No relevant conflicts of interest to declare.
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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) | 0.002 | 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".