Endogenous and exogenous factors driving bacterial community composition in aquatic ecosystems
Bibliographic record
Abstract
The bacterial community (BC) composition in various habitats, ranging from ecosystems to host anatomy, plays an important role in determining the nature and role of BC function in the ecosystem or host. However, the relative importance of host endogenous and environmental exogenous factors in determining the composition of the BC in aquatic habitats (e.g., freshwater lakes, fish hosts) remains poorly understood. To address this knowledge gap, this thesis makes several contributions to the estimation of the relative effects of endo-exogenous factors in driving the BC composition in aquatic ecosystem. To test the impact of biotic and abiotic factors on aquatic bacterial biodiversity, I collected water samples from sixty southern Ontario lakes and their BC and microbial eukaryotic community (MEC) compositions were determined using high throughput metabarcode sequencing of 16S and 18S rRNA gene fragments. Additionally, I sampled skin and gut BCs belonging to 17 fish species from 11 families (7 orders) at three distinct Laurentian Great Lakes (LGLs) habitats (Detroit River, Lake Erie, Lake Ontario) along with the associated aquatic BCs at those sites. These data allowed me to assess the extent to which host habitat and phylogeny predict gut and skin BC similarity. Finally, to address the effect of host microbiome on gene expression pattern, I manipulated the gut BC in Chinook salmon (Oncorhynchus tshawytscha) families using antibiotic and probiotic treatments (with healthy controls) and assessed host gene expression using transcriptome sequencing (RNA-Seq) on hindgut tissue samples to identify differentially expressed (DE) host genes. Using a combination of parametric and non-parametric modelling, I showed deterministic processes (exogenous) prevail in shaping BC assembly in freshwater lakes, but that a combination of habitat-specific (e.g., microbial diversity associated with water) and species-specific (e.g., host ancestry, genotype, or diet) factors shape and promote divergence or convergence of the microbiome BC across host fish species. Additionally, I showed that daily administration of antibiotics and probiotics resulted in significant and predictable changes in fish gut and the surrounding aquatic microbiota. Normal microbiota depletion by antibiotics generally led to downregulation of immune response gene and upregulation of apoptotic processes, while probiotic treatment affected post-translation modification and inflammatory response genes (over-expressed). While these effects were mostly due to microbiome-mediated mechanisms, host-related mechanisms were also detected (i.e., family effects).In general, my thesis showed that BC composition in fish and lakes is regulated by assembly rules driven by exogenous abiotic and biotic factors (e.g., habitat, geography, microbial biodiversity, diet) and endogenous species-specific related factors (e.g., genetics, physiology, immunity). My work thus supports the deterministic view of BC composition variation across diverse habitats.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".