Evaluating <i>cpn60</i> for high-resolution profiling of the mammalian skin microbiome and detection of phylosymbiosis
Bibliographic record
Abstract
Despite being the most widely used phylogenetic marker for amplicon-based profiling of microbial communities, limited phylogenetic resolution of the 16S rRNA gene limits its use for studies of host-microbe co-evolution. In contrast, the cpn60 gene is a universal phylogenetic marker with greater sequence variation capable of species-level resolution. This research compared mammalian skin microbial profiles generated from cpn60 and 16S rRNA gene sequencing approaches, testing for patterns of phylosymbiosis that suggest co-evolutionary host-microbe associations. An ~560 bp fragment of the cpn60 gene was amplified with universal primers and subjected to high-throughput sequencing. Taxonomic classification of cpn60 sequences was completed using a naïve-Bayesian QIIME2 classifier created for this project, trained with an NCBI-supplemented curated cpn60 database (cpnDB_nr). The cpn60 dataset was then compared to published 16S rRNA gene amplicon data. Beta diversity comparisons of microbial community profiles generated with cpn60 and 16S rRNA gene amplicons were not significantly different, based on Procrustes analysis of Bray-Curtis and UniFrac distances. Despite similar relationships among skin microbial profiles, improved phylogenetic resolution provided by the cpn60 gene sequencing permitted observations of phylosymbiosis between microbial community profiles and their mammalian hosts that were not previously observed with 16S rRNA gene profiles. Subsequent investigation of Staphylococcaceae taxa using the cpn60 gene showed increased phylogenetic resolution compared the 16S rRNA gene profiles, revealing potential co-evolutionary host-microbe associations. Overall, our results demonstrate that 16S rRNA and cpn60 marker genes generate comparable microbial community composition patterns while cpn60 better facilitates analyses, such as phylosymbiosis, that require increased phylogenetic resolution.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".