Divergent Targets of Aspergillus fumigatus AcuK and AcuM Transcription Factors during Growth <i>In Vitro</i> versus Invasive Disease
Bibliographic record
Abstract
In Aspergillus nidulans, the AcuK and AcuM transcription factors form a complex that regulates gluconeogenesis. In Aspergillus fumigatus, AcuM governs gluconeogenesis and iron acquisition in vitro and virulence in immunosuppressed mice. However, the function of AcuK was previously unknown. Through in vitro studies, we found that A. fumigatus ΔacuK single and ΔacuK ΔacuM double mutants had impaired gluconeogenesis and iron acquisition, similar to the ΔacuM mutant. Also, the ΔacuK, ΔacuM, and ΔacuK ΔacuM mutants had similar virulence defects in mice. However, the ΔacuK mutant had a milder defect in extracellular siderophore activity and induction of epithelial cell damage in vitro than did the ΔacuM mutant. Moreover, overexpression of acuM in the ΔacuK mutant altered expression of 3 genes and partially restored growth under iron-limited conditions, suggesting that AcuM can govern some genes independently of AcuK. Although the ΔacuK and ΔacuM mutants had very similar transcriptional profiles in vitro, their transcriptional profiles during murine pulmonary infection differed both from their in vitro profiles and from each other. While AcuK and AcuM governed the expression of only a few iron-responsive genes in vivo, they influenced the expression of other virulence-related genes, such as hexA and dvrA. Therefore, in A. fumigatus, while AcuK and AcuM likely function as part of the same complex, they can also function independently of each other. Furthermore, AcuK and AcuM have different target genes in vivo than in vitro, suggesting that in vivo infection stimulates unique transcriptional regulatory pathways in A. fumigatus.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".