Origin of Robustness in Generating Drug-Resistant Malaria Parasites
Bibliographic record
Abstract
Biological robustness allows mutations to accumulate while maintaining functional phenotypes. Despite its crucial role in evolutionary processes, the mechanistic details of how robustness originates remain elusive. Using an evolutionary trajectory analysis approach, we demonstrate how robustness evolved in malaria parasites under selective pressure from an antimalarial drug inhibiting the folate synthesis pathway. A series of four nonsynonymous amino acid substitutions at the targeted enzyme, dihydrofolate reductase (DHFR), render the parasites highly resistant to the antifolate drug pyrimethamine. Nevertheless, the stepwise gain of these four dhfr mutations results in tradeoffs between pyrimethamine resistance and parasite fitness. Here, we report the epistatic interaction between dhfr mutations and amplification of the gene encoding the first upstream enzyme in the folate pathway, GTP cyclohydrolase I (GCH1). gch1 amplification confers low level pyrimethamine resistance and would thus be selected for by pyrimethamine treatment. Interestingly, the gch1 amplification can then be co-opted by the parasites because it reduces the cost of acquiring drug-resistant dhfr mutations downstream in the same metabolic pathway. The compensation of compromised fitness by extra GCH1 is an example of how robustness can evolve in a system and thus expand the accessibility of evolutionary trajectories leading toward highly resistant alleles. The evolution of robustness during the gain of drug-resistant mutations has broad implications for both the development of new drugs and molecular surveillance for resistance to existing drugs.
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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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".