Neutrality in the Metaorganism
Bibliographic record
Abstract
Almost all animals and plants are inhabited by diverse communities of microorganisms, the microbiota, thereby forming an integrated entity, the metaorganism.Natural selection should favor hosts that shape the community composition of these microbes to promote a beneficial host-microbe symbiosis.Indeed, animal hosts often pose selective environments, which only a subset of the environmentally available microbes are able to colonize.How these microbes assemble after colonization to form the complex microbiota is less clear.Neutral models are based on the assumption that the alternatives in microbiota community composition are selectively equivalent and thus entirely shaped by random population dynamics and dispersal.Here, we use the neutral model as a null hypothesis to assess microbiata composition in host organisms, which does not rely on invoking any adaptive processes underlying microbial community assembly.We show that the overall microbiota community structure from a wide range of host organisms, in particular including previously understudied invertebrates, is in many cases consistent with neutral expectations.Our approach allows to identify individual microbes that are deviating from the neutral expectation and are therefore interesting candidates for further study.Moreover, using simulated communities, we demonstrate that transient community states may play a role in the deviations from the neutral expectation.Our findings highlight that the consideration of neutral processes and temporal changes in community composition are critical for an in-depth understanding of microbiotahost interactions.The microbial communities living in and on animals can affect many important host functions, including metabolism [1-3], the immune system [4-6], and even behavior [7,8].The extent and direction of this microbe-mediated influence is often linked to the presence or absence of species and their relative abundances.It is thus paramount to understand how host-associated microbial communities are assembled.A classical explanation for the emergence of a particular ecological community structure posits that every species is defined by
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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 | 0.005 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".