The eukaryome: Diversity and role of microeukaryotic organisms associated with animal hosts
Bibliographic record
Abstract
Abstract Awareness of the roles that host‐associated microbes play in host biology has escalated in recent years. However, microbiome studies have focused essentially on bacteria, and overall, we know little about the role of host‐associated eukaryotes outside the field of parasitology. Despite that, eukaryotes and microeukaryotes in particular are known to be common inhabitants of animals. In many cases, and/or for long periods of time, these associations are not associated with clinical signs of disease. Unlike the study of bacterial microbiomes, the study of the microeukaryotes associated with animals has largely been restricted to visual identification or molecular targeting of particular groups. So far, since the publication of the influential Human Microbiome Project Consortium paper in 2012, few studies have been published dealing with the microeukaryotes using a high‐throughput barcoding ‘microbiome‐like’ approach in animals. Nonetheless, microeukaryotes have an impact on the host physiology and lifestyle and also on the diversity and composition of the wider symbiotic community of bacteria and viruses. Beyond being parasites, microeukaryotes have many different roles in animals. For example, they directly interact with the host immune system in mammals; they have a key role on cellulose degradation, lignocellulose in xylophage termites and cockroaches; and they have an essential role in providing photosynthates to reef‐building corals. Certain microeukaryotic lineages have diversified within hosts more than others. These cases of co‐evolution led to different forms of symbiosis: from mutualism (like Symbiodinium in corals or parabasalians in termites), to commensalism ( Blastocystis in humans) or to strict parasitism (apicomplexans or microsporidians in a broad range of hosts). We will review the ecological context and the evolutionary mechanisms that ended up in these different symbiotic scenarios, across the taxonomic range of both symbionts and their metazoan hosts. Host‐associated microeukaryotes have impacts at many levels, from individual animal health to ecosystems and to agroeconomy. Therefore, it is crucial to have a better understanding of their diversity and roles. Novel methodologies are being developed to access the eukaryotic fraction of the microbiome using high‐throughput methods. From ‐omics, to imaging and barcoding approaches biased against metazoans, these novel methodologies and strategies are helping us to increase and improve our knowledge of microeukaryotes in animal‐associated environments. A free Plain Language Summary can be found within the Supporting Information of this article.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".