An experimental test of the influence of microbial manipulation on sugar kelp ( <i>Saccharina latissima</i> ) supports the core influences host function hypothesis
Bibliographic record
Abstract
ABSTRACT Kelp are valued for a wide range of commercial products and their role in kelp forest ecosystems, making kelp cultivation a rapidly expanding economic sector. Microbes associated with kelp and other macroalgae play a critical role in processes such as nutrient exchange, chemical signaling, and defense against pathogens. Thus, manipulating the microbiome to enhance macroalgal growth and resilience is a promising yet underexplored approach for sustainable kelp cultivation. The core microbiome hypothesis suggests that the bacteria that are consistently found on a host (the core microbes) are likely to have a disproportionate impact on host biology, making them an attractive target for microbiome manipulation. In this study, we surveyed wild Saccharina latissima and their surrounding environment to identify core bacterial taxa, compared them to cultivated kelp, and experimentally tested how cultured bacterial isolates affect kelp development. We found that core bacteria are nearly absent in cultivated juvenile sporophytes in nurseries, but eventually colonize them after outplanting to ocean farm sites. Bacterial inoculants had both positive and negative effects on kelp development. Notably, the strength of association of a bacterial genus with kelp in the wild positively correlated with its impact on gametophyte settlement and sporophyte development in kelp co-culture experiments, aligning with predictions from the core microbiome influences host function hypothesis. These findings affirm the feasibility of using microbial manipulations to improve current kelp aquaculture practices and provide a framework for developing these techniques. IMPORTANCE Microorganisms consistently associated with hosts are widely thought to be more likely to impact host biology and health. However, this intuitive concept has not been experimentally evaluated. This study formalizes this concept as the Core Microbiome Influences Host Function hypothesis and experimentally tests this hypothesis in sugar kelp (Saccharina). The distribution of bacteria on wild kelp and core microbes was first identified by compiling a broad dataset of the kelp microbiome sampled across space and time. Bacterial cultures were isolated from the surface of sugar kelp and individually grown in laboratory co-culture with sugar kelp spores to assess the ability of bacterial isolates to influence kelp growth and development. In support of the core influences host function hypothesis, isolates belonging to bacterial genera that are more strongly associated with wild sugar kelp are more likely to influence development in laboratory experiments.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".