Actinorhodopsins: proteorhodopsin‐like gene sequences found predominantly in non‐marine environments
Bibliographic record
Abstract
Proteorhodopsins are light-energy-harvesting transmembrane proteins encoded by genes recently discovered in the surface waters of the world's oceans. Metagenomic data from the Global Ocean Sampling expedition (GOS) recovered 2674 proteorhodopsin-related sequences from 51 aquatic samples. Four of these samples were from non-marine environments, specifically, Lake Gatun within the Panama Canal, Delaware Bay and Chesapeake Bay and the Punta Cormorant Lagoon in Ecuador. Rhodopsins related to but phylogenetically distinct from most sequences designated proteorhodopsins were present at all four of these non-marine sites and comprised three different clades that were almost completely absent from marine samples. Phylogenomic analyses of genes adjacent to those encoding these novel rhodopsins suggest affiliation to the Actinobacteria, and hence we propose to name these divergent, non-marine rhodopsins 'actinorhodopsins'. Actinorhodopsins conserve the acidic amino acid residues critical for proton pumping and their genes lack genomic association with those encoding photo-sensory transducer proteins, thus supporting a putative ion pumping function. The ratio of recA and radA to rhodopsin genes in the different environment types sampled within the GOS indicates that rhodopsins of one type or another are abundant in microbial communities in freshwater, estuarine and lagoon ecosystems, supporting an important role for these photosystems in all aquatic environments influenced by sunlight.
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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 | 0.001 |
| 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 | 0.001 |
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".