Dispersal and Distribution of Thermophilic Endospores in Deep-Sea Ecosystems
Bibliographic record
Abstract
The distance-decay relationship is a central concept in biogeography and spatial biodiversity, describing how two distinct entities decrease in similarity as the distance between them increases. The decay of community similarity with geographical distance is driven by multiple factors, such as gene drift, environmental selection, and the accumulation of mutations over time. While the distance-decay relationship has been recognized for several decades, there are certain circumstances where the biogeographical patterns of certain species and communities cannot be predicted by this relationship. The example addressed in this project is the case of thermophilic endospore-forming bacteria found in permanently cold deep ocean sediments. Thermophilic endospores (thermospores) are routinely found on the deep ocean floor, a permanently cold environment that does not support their metabolic activity (Hubert et al. 2009). Thermospores are metabolically dormant states developed by some thermophilic bacteria having optimal growth temperatures between 40°C and 70°C. There is evidence that these heat-loving bacteria originate from the deep subsurface and are transported upward to the deep ocean via geological features of the oceanic crust including geofluid fluxes in high-temperature axial systems and natural hydrocarbon seeps (Gittins et al. 2022). Due to the ability of endospores to stay viable for thousands of years and resist a wide range of physicochemical stressors, they can disperse over long distances while remaining unaffected by changing factors such as selection, drift, or mutation (Gittins et al. 2022; Fig. 1). Consequently, these thermospores have the potential to challenge the distance-decay relationship and exhibit unique biogeographical patterns. This work quantifies endospores in sediment cores at and around hydrocarbon seeps using cores from deep-sea Scotian Slope sediments. Given the challenge of quantifying specific groups of endospores (e.g., thermophiles but not mesophiles), high-temperature germination assays that allow tracking of an exponential increase in signal as spores in marine sediment samples germinate and grow can be used. Distinct exponential increases can be attributed to different populations of germinated thermospores in the post-germination growth phase and are being monitored through measurements of sulfate reduction rates (using radiolabelled 35 SO 4 ), strain-specific quantitative PCR (qPCR), and fluorescence in-situ hybridization (FISH) (Rezende et al. 2017). These measurements revealed growth dynamics enabling an estimation of the initial cell numbers using exponential functions. These approaches are being applied to samples obtained via push coring using a remotely operated vehicle at different distances from deep sea hydrocarbon seeps, to test for the presence of abundance gradients of different thermospores. Current results already show a difference in thermospore abundance between sites at different distances from the seep. Quantitative tracking of the dispersal of thermospores by oceanic currents in the deep sea provides an excellent opportunity to investigate their distribution and potential to colonize more remote habitats, improving the understanding of microbial biodiversity and biogeography on our planet. By investigating thermospores and their interactions with the geophysical features of the deep sea and deep subsurface, this study aims to challenge the canonical idea that speciation occurs with distance and presents new perspectives on the theme of microbial biogeography. The evidence supporting the subsurface origin of thermophilic endospores, along with the proposed model for their dispersal and distribution, will contribute toward improving an integrated understanding of ecology and geology and their intersection in the microbial realm.
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 | 0.000 | 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) | 0.001 | 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 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".