CoSE · plant spaceflight biology

A gas-transport model predicts the Arabidopsis spaceflight transcriptome, and illumination separates six flight contrasts

Plants flown on the ISS grow inside enclosures, and almost nobody measures the atmosphere inside them. A simple mass balance, with an assumed canister headspace, says an illuminated sealed canister draws itself down toward the CO2 compensation point within minutes — in the ground control as much as in flight, which is exactly why it disappears from the contrast that gets published.

Everything below runs in your browser. The model is the same code that produced the figures, ported to JavaScript and checked against the Python to 1e-6.

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The model, live

A Farquhar–von Caemmerer–Berry C3 model with the Rubisco oxygenation term explicit, solved for the supply-equals-demand operating point. Boundary-layer conductance gbl comes from LunarLeaf-CFD; everything else is yours to move.

Presets
Solid lines use your current settings. The marker is the operating point the model solves for. Drag canister CO2 down and watch the oxygenation fraction climb — that is the enclosure effect.

Reproduce the result that refuted our own hypothesis

We expected microgravity's boundary-layer penalty to amplify as CO2 ran out. Set canister CO2 high, note the gap between the two gravity traces below, then drag it down to 70. The gap closes: with no assimilation there is no flux across the boundary layer, so there is nothing for gravity to impede.

What each enclosure does to the air

From LunarLeaf-CFD, a validated lattice-Boltzmann solver. All runs are in microgravity, so the differences here are hardware, not gravity.

Measured at

The seven-minute drawdown in a lit BRIC canister is a mass balance between photosynthetic uptake and enclosure volume, with an assumed 30 mL headspace; it comes from a zero-dimensional model in LunarLeaf-CFD, not from the lattice-Boltzmann runs above. It is therefore essentially gravity-independent — it happens in the ground control too, and cancels out of flight-versus-ground.

What OSD-522 measured

Layer Highlight a gene set

Non-significant points are subsampled so the page stays quick — but every member of every gene set and pathway is forced into the plot regardless of significance, so highlighting always shows the whole set. A feature can still be measured without being plottable: a volcano needs a y-value, and DESeq2's independent filtering leaves some transcripts with a fold change but no adjusted p. The caption says when that happens.

Gene-set response across the six flight contrasts

Median shift against all other genes, per set, per study. Blue is down in flight, red is up, white is no change. Click any row to highlight that set in the volcano above. Hover a cell for n, shift and p.

Columns are grouped illuminated first, then dark, as in Figure 7d. Values come from results/tables/T11_hardware_ladder.tsv.

Where the loci go: transcript → protein → pathway

Show ribbon width = number of loci

Pathway integration

PaintOmics, organism ath, KEGG + MapMan, all three layers. Of 232 pathways, 32 reach combined p < 0.05 — and glyoxylate and dicarboxylate metabolism, the photorespiration map, ranks 214th of 232, in the bottom 8 %, the least enriched of any pathway the model made a claim about.

Metabolite hubs

The least circular result available: the compounds are predicted, but the differentially expressed genes counted around them are measured.

Six contrasts from five studies, and the axis that separates them

The model predicted an ordering across enclosure types. Illumination separated the six contrasts completely on starvation over photosynthesis, though not on every contrast; the enclosure gradient did not hold. Both are shown.

Contrast

Which studies, and which were left out