VSG switching in <i>Trypanosoma brucei</i>: antigenic variation analysed using RNAi in the absence of immune selection
Bibliographic record
Abstract
Trypanosoma brucei relies on antigenic variation of its variant surface glycoprotein (VSG) coat for survival. We show that VSG switching can be efficiently studied in vitro using VSG RNAi in place of an immune system to select for switch variants. Contrary to models predicting an instant switch after inhibition of VSG synthesis, switching was not induced by VSG RNAi and occurred at a rate of 10(-4) per division. We find a highly reproducible hierarchy of VSG activation, which appears to be capable of resetting, whereby more than half of the switch events over 12 experiments were to one of two VSGs. We characterized switched clones according to switch mechanism using marker genes in the active VSG expression site (ES). Transcriptional switches between ESs were the preferred switching mechanism, whereby at least 10 of the 17 ESs identified in T. brucei 427 can be functionally active in vitro. We could specifically select for switches mediated by DNA rearrangements by inducing VSG RNAi in the presence of drug selection for the active ES. Most of the preferentially activated VSGs could be activated by multiple mechanisms. This VSG RNAi-based procedure provides a rapid and powerful means for analysing VSG switching in African trypanosomes entirely in vitro.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".