Corallicolids: The elusive coral-infecting apicomplexans
Bibliographic record
Abstract
Coral reefs are the poster child for ocean biodiversity-a marine equivalent of the terrestrial tropical rainforest in their scientific importance and public perception.Compared with most of the ocean, coral reefs harbour an incredible variety of biodiversity, and this diversity is also fairly well studied so that many of the basic interactions making up the ecosystem are understood at some level.The foundation of the system is obviously coral, particularly reef-building, scleractinian corals.The calcium carbonate skeletons secreted by these animals are literally the bedrock of the reef and create habitats that other reef creatures depend upon [1].At this macroscopic scale, the importance of coral is intuitive to us.However, it's becoming clear that at another, more abstract level, coral reefs are also supported by diverse microscopic communities, some of which play a direct role in coral health and collectively serve as a different kind of ecological foundation for the reef [2].Coral reefs are also a model for understanding symbiosis.The large stony coral you see when diving or snorkeling (Fig 1) is actually a colony of heterotrophic animals, yet the small prey they filter from seawater is insufficient for the massive energy expenditure required to build reefs.For that, they have formed a symbiotic partnership with a lineage of photosynthetic dinoflagellates, the Symbiodiniaceae [3], which harness light energy to fix carbon and feed calcium carbonate production.This coral-microbe symbiosis is clearly important to reef building and coral health, but we are increasingly seeing that it is only one part of the story.Coral is actually home to rich microbial communities that vary with host, location, depth, season, and coral health [4][5][6][7][8][9].Coral health and disease is a topic of growing concern: As corals are challenged by systemic problems relating to warming seas, overfishing, and ocean acidification, the spread of disease has emerged as one important factor in their reaction to these challenges [10,11].Several important coral pathogens have been identified [12], and, recently, a new family of coral-infecting microbe has been discovered by a most unusual means-not by the study of disease or pathology, but as a chance discovery from ecological research [13][14][15].These new intracellular parasites are members of the Apicomplexa, well known as parasitic agents of humans and other animals (e.g., Toxoplasma, Cryptosporidium, or the malaria agent Plasmodium) and are now called Corallicolida [16] (Fig 2). HowAU : Pleaseconfirmthatallheadinglevelsarerepresentedcorrectly:do you discover a eukaryotic parasite from bacterial ecological data?Microbial ecology has long relied on molecular data to survey and distinguish between the vast diversity of microbes in an environment.Decades of study has generated a huge database of environmental sequences, but a disproportionate amount of these data are from bacteria and archaea: In ecology, as in most areas of microbiology, the microbial eukaryotes are relatively unloved and understudied!In this case, ignoring eukaryotes had consequences.Identifying environmental sequence data requires comparisons to accurately curated reference sequences,
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".