Metabolite Profiling of Social Spiders (<i>Stegodyphus dumicola</i>) along a Climate Gradient
Bibliographic record
Abstract
Social spiders of the genus Stegodyphus live in colonies of hundreds of individuals, and in close association with microorganisms, that encompass bacterial endosymbionts and diverse bacteria and fungi in their nests. Social spiders are highly inbred due to a strictly inbreeding mating system resulting in extremely low genetic variation on all levels. Conventionally, inbreeding results in severe fitness loss through expression of deleterious alleles and the random loss of alleles. However, social spiders are evolutionary old, ecologically successful, and spread over multiple climate zones in nature. We hypothesize that social spiders cope with environmental challenges by producing low molecular weight metabolites; some of these metabolites may also be produced by symbiotic bacteria, thus helping their host to adapt to different environmental conditions. Irrespective the origin of the compound, they should be reflected in the spiders’ metabolite profiles. Social spiders were sampled in triplicates from three populations along a climate gradient in Namibia, Southern Africa. Whole animals were extracted with methanol and water, and the lyophilized extracts were analyzed by GC-MS and 1H-NMR. Metabolite profiles were highly reproducible within each population, while they showed remarkable differences between the three populations; one possible reason may be adaptation of the spider-microbe system to the local climate. To test this hypothesis, we are currently performing a controlled lab experiment assessing temperature tolerance and potential for adaptation of the three field populations along with their microbiome and metabolite profile.
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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 | 0.001 | 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".