PSXIII-8 Metagenomics Analysis of the Healthy Feline Fecal Microbiota using Illumina Whole Genome Shotgun Sequencing.
Bibliographic record
Abstract
The microbial community inhabiting the gastrointestinal tract provides many roles in animal health, disease, and nutrition. The microbial community’s composition and metabolic function has not been studied in depth in healthy domestic cats. In order to research, treat, and prevent diseased states further, a comprehensive characterization of the healthy baseline feline gastrointestinal microbial community is required. Fourteen healthy lean client-owned cats, 2–7 years old, with body condition scores of 4–5 on a 9-point scale, from Guelph, Ontario Canada, participated. Cats were fed a veterinary diet at maintenance energy requirement for four weeks. Fecal samples were collected at the end of the four week period, genomic DNA was extracted, and DNA was whole-genome shotgun sequenced with Illumina NextSeq500 platform. Data was analyzed through MG-RAST, a bioinformatics pipeline, to determine bacterial phylogenetic composition and metabolic functional capacity. The phylogenic composition identified four predominant bacteria phylum: Firmicutes (34.32%), Bacteroidetes (30.72%), Actinobacteria (19.4%), and Proteobacteria (10.37%). Within Firmicutes, classes Clostridia (20.55%) and Bacilli (9.08%) were most prevalent. Within Bacteroidetes, the class Bacteroidia (29.48%) dominated. Archea, Eukaryota, and Viruses were minor microbial constituents (2%). Major functional metabolic categories included carbohydrate, protein, DNA and RNA metabolisms (16.3%, 10.34% 6.07%, and 4.54% respectively); clustering-based subsystems (12.69%); amino acids and derivatives (9.22%); cofactors, vitamins, prosthetic groups, and pigments (4.69%); and cell wall and capsule (4.44%). Future efforts focused on providing deeper coverage of the feline gastrointestinal microbiome are warranted. These study demonstrate a need for further investigation to evaluate the effects of age, genetics, diet, probiotics, environment, and disease on the feline gastrointestinal microbiome. This study’s results will serve as baseline values for future feline microbiota research.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".