Comparative Transcriptomics of Cold Growth and Adaptive Features of a Eury- and Steno-Psychrophile
Bibliographic record
Abstract
Permafrost subzero environments harbor diverse, active communities of microorganisms. However, our understanding of the subzero growth, metabolisms, and adaptive properties of these microbes remains very limited. We performed transcriptomic analyses on two subzero-growing permafrost isolates with different growth profiles in order to characterize and compare their cold temperature growth and cold-adaptive strategies. The two organisms, Rhodococcus sp. JG3 (-5 to 30°C) and Polaromonas sp. Eur3 1.2.1 (-5 to 22°C), shared several common responses during low temperature growth, including induction of translation and ribosomal processes, upregulation of nutrient transport, increased oxidative and osmotic stress responses, and stimulation of polysaccharide capsule synthesis. Recombination appeared to be an important adaptive strategy for both isolates at low temperatures, likely as a mechanism to increase genetic diversity and the potential for survival in cold systems. While Rhodococcus sp. JG3 favored upregulating iron and amino acid transport, sustaining redox potential, and modulating fatty acid synthesis and composition during growth at -5°C compared to 25°C, Polaromonas sp. Eur3 1.2.1 increased the relative abundance of transcripts involved in primary energy metabolism and the electron transport chain, in addition to signal transduction and peptidoglycan synthesis at 0°C compared to 20°C. The increase in energy metabolism may explain why Polaromonas sp. Eur3 1.2.1 is able to sustain growth rates at 0°C comparable to those at higher temperatures. For Rhodococcus sp. JG3, flexibility in use of carbon sources, iron acquisition, control of membrane fatty acid composition, and modulating redox and co-factor potential may be ways in which this organism is able to sustain growth over a wider range of temperatures. Increasing our understanding of the microbes in these habitats helps us better understand active pathways and metabolisms in extreme environments. Identifying novel, thermolabile, and cold-active enzymes from studies such as this is also of great interest to the biotechnology and food industries.
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 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 | 0.001 |
| 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".