Data from: Seasonal shifts in the insect gut microbiome are concurrent with changes in cold tolerance and immunity
Bibliographic record
Abstract
1. Seasonal changes in the environment, such as varying temperature, have the potential to change the functional relationship between ectothermic animals, such as insects, and their microbiomes. Our objectives were to determine: a) whether seasonal changes in temperature shift the composition of the insect gut microbiome, and b) if changes in the microbiome are concomitant with changes in the physiology of the host, including the immune system and response to cold. 2. We exposed laboratory populations of the spring field cricket, Gryllus veletis (Orthoptera: Gryllidae), to simulated overwintering winter and spring, we extracted and sequenced 16S bacterial genomic DNA from cricket guts, to capture seasonal variation in the composition of the microbiome. 3. The composition of the gut microbiome was similar between microcosms, and overall me, where overwintering resulted in permanent changes to these microbial communities. In particular, the abundance of Pseudomonas spp. decreased, and that of Wolbachia spp. increased, during overwintering. 4. Concurrent with overwintering changes in the gut microbiome, G. veletis acquire freeze-tolerance and immune function shifts temporarily, returning to summer levels of activity in the spring. Specifically, haemocyte concentrations increase but survival of fungal infection decreases in the winter, whereas the ability to clear bacteria from the haemolymph remains unchanged. 5. Overall, we demonstrate that the gut microbiome does shift seasonally, and in concert with other physiological changes. We hypothesize that these changes may be linked, and suggest that it will next be important to determine if these changes in the microbiome contribute to host overwintering success.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.002 |
| 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 teacher head, 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".