Sustained Growth and Terpenoid Indole Alkaloid Biosynthesis in the Medicinal Plant Catharanthus roseus under Simulated Microgravity
Bibliographic record
Abstract
As humanity prepares for long-duration space missions, sustainable life-support systems that integrate food, oxygen, and pharmaceutical production are essential. Catharanthus roseus ( C. roseus ), a medicinal plant that produces clinically important terpenoid indole alkaloids (TIAs) such as the anticancer drugs vinblastine and vincristine, offers unique potential for in situ therapeutic biomanufacturing. However, whether specialized metabolism can be maintained under microgravity (MG) remains unclear. Here, we demonstrate that C. roseus can complete its full life cycle under simulated MG using a three-dimensional (3D) clinostat. MG-grown plants showed increased biomass and successfully flowered. Morphological and transcriptomic analyses revealed that MG induces developmental changes and broad transcriptional reprogramming, particularly in auxin signaling, oxidative stress responses, and meristem regulatory pathways. Single-cell transcriptomic integration revealed that MG-responsive genes are enriched in mesophyll, epidermal, and idioblast cells, which are key sites of TIA biosynthesis. Importantly, MG had only modest effects on TIA production. Expression of core biosynthetic genes remained essentially unchanged, and metabolomic analyses confirmed that catharanthine and vindoline levels were stable in young leaves. At the same time, vinblastine and anhydrovinblastine showed slight reductions in mature tissues. Collectively, our findings provide scientific evidence that a pharmacologically valuable plant can reproduce and maintain specialized metabolism under microgravity analog conditions. C. roseus thus emerges as a promising dual-use crop for future space-based life-support systems, capable of contributing both to crew health and therapeutic self-sufficiency.
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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) | 0.000 | 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".