Comprehensive skin microbiome analysis reveals the uniqueness of human-associated microbial communities among the class Mammalia
Bibliographic record
Abstract
Abstract Skin is the largest organ of the body and represents the primary physical barrier between mammals and their external environment. The objective of this research was to generate a skin microbiota baseline for members of the class Mammalia, testing the effects of host species, geographic location, body region, and biological sex. The back, torso, and inner thigh regions of 177 non-human mammals were collected to include representatives from 38 species and 10 mammalian orders. Animals were collected from local farms, zoos, households, and the wild. All samples were amplified using the V3-V4 16S rRNA gene region and sequenced using a MiSeq (Illumina). For reference, previously published skin microbiome data from 20 human participants, sampled using an identical protocol to the non-human mammals, were included in the analysis. Human skin was significantly less diverse than all other mammalian orders and the factor most strongly associated with community variation for all samples was whether the host was a human. Within non-human samples, host taxonomic order was the most significant factor influencing the skin community, followed by the geographic location of the habitat. By comparing the congruence between known host phylogeny and microbial community dendrograms, we observed that Artiodactyla (even-toed ungulates) and Perissodactyla (odd-toed ungulates) had significant congruence, providing first evidence of phylosymbiosis between skin communities and their hosts. Significance Skin forms a critical protective barrier between a mammal and its external environment. Baseline data on the mammalian skin microbiome is crucial for making informed decisions related to veterinary research and biodiversity conservation strategies, in addition to providing insight into mammalian evolutionary history. To our knowledge, this study represents the largest mammalian skin microbiota project to date. These findings demonstrate that human skin is distinct, not only from other Primates, but from all 10 mammalian orders sampled. Using phylosymbiosis analysis, we provide the first evidence that co-evolution may be occurring between skin communities and their mammalian hosts, which warrants more in-depth future studies of the relationships between mammals and their skin microbiota.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".