Following the terrestrial tracks of<i>Caulobacter</i>- redefining the ecology of a reputed aquatic oligotroph
Bibliographic record
Abstract
For the past 60 years Caulobacter spp. have been commonly attributed an aquatic and oligotrophic lifestyle yet are not uncommon in nutrient-rich or soil environments. This study evaluates the environmental and ecological associations of Caulobacter to reconcile past evidence, largely limited to culturing and microscopy, with currently available metagenomic and genomic data. The distribution of Caulobacter species and their characteristic adhesion-conferring genes, holdfast (hfaAB), were determined using collections of 10,641 16S rRNA gene libraries (196 studies) and 2625 shotgun metagenomes (190 studies) from a range of terrestrial and aquatic environments. Evidence for ecotypic variation was tested in 26 genomes sourced from soil, rhizosphere, plant, groundwater, and water. Caulobacter were, on average, fourfold more relatively abundant in soil than in aquatic environments, and abundant in decomposing wood, compost, and particulate matter (in air and water). Caulobacter holdfast genes were 35-fold more abundant in soils than aquatic environments. Ecotypic differences between soil and aquatic Caulobacter were evident in the environmental associations of several species and differences in genome size and content among isolates. However, most abundant species were common to both environments, suggesting populations exist in a continuum that was evident in the re-analysis of studies on the temporal dynamics of, and sources of bacterioplankton to, lakes and rivers. This study provides a new perspective on the ecological profile of Caulobacter, demonstrating that members of this genus are predominantly soil-borne, possess an overlooked role in plant matter decomposition and a dependency on water-mediated dispersal.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".