Exposure to elevated relative humidity in laboratory chambers alters fungal gene expression in dust from the International Space Station (ISS)
Bibliographic record
Abstract
Microorganisms are present in all occupied indoor environments, including homes on Earth and within specialized systems like the International Space Station (ISS). Microbes when exposed to excess moisture, such as from an unexpected ventilation system failure, can undergo growth that is associated with material degradation and negative health effects. However, we do not yet understand how exposure of these microbes to excess moisture alters their function. A de novo metatranscriptomic study was performed using dust collected from the US air filtration system of the ISS and incubated in laboratory chambers on Earth at different equilibrium relative humidity (ERH) levels. Changes in fungal function (gene expression) were significantly associated with moisture (adonis2 p = 0.0001). Secondary metabolism and fungal growth genes were upregulated (FDR-adjusted p ≤ 0.001, log2FC ≥ 2) at elevated ERH compared to 50% ERH. Elevated moisture conditions showed upregulation of aflatoxin and fungal allergen genes such as Asp f 4 (log2FC = 26.4, upregulated at 85% ERH compared to 50%) and Alt a 7 (log2FC = 2.98, upregulated at 100% ERH compared to 50%). Our results demonstrate that understanding microbial functional changes in response to elevated moisture will help develop more robust microbial monitoring standards for spacecraft environments to protect astronaut health and spacecraft integrity in low-Earth orbit and beyond.
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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) | 0.001 | 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".