The skin microbiome and dermatitis in dogs and cats.

The skin is a barrier, and it carries its own microbial community.

The skin is the largest interface between an animal and the world around it. It works as a physical, immune and microbial barrier, regulates temperature and holds water in, and like every other body surface it is covered in microorganisms. That community, the skin microbiome, is not passive baggage. Across humans and dogs it helps modulate the immune response, competes with incoming pathogens and supports normal skin function, and shifts in its makeup have been linked to skin conditions including atopic dermatitis, although whether those shifts are cause or consequence is still unsettled.

For most of the history of veterinary dermatology, what was known about bacteria on the skin came from culture, and culture recovers only the minority of organisms that will grow on a plate. Sequencing changed that. The most detailed description of the healthy canine skin community to date comes from Whittle and colleagues in 2024, who used shotgun metagenomic sequencing, the approach that reads all the DNA in a sample rather than one marker gene, to profile the skin of 72 healthy adult dogs. They sampled four sites on each dog (the ear canal, the interdigital skin of a forepaw, the dorsal lumbar back and the groin) across four breeds, sequencing to a mean depth of 28 million reads per sample. From that they defined a core skin microbiome of 230 bacterial taxa and 1,219 functional gene families that were present across almost every dog and every site.

The practical message is the same one that applies to the gut and the mouth. The canine skin is a distinct microbial world, most of it invisible to a swab and a culture plate, and any account of skin health has to start from that community rather than from a short list of familiar pathogens.

What a healthy dog's skin looks like, in 72 dogs.

In Whittle's 2024 data the healthy canine skin community was dominated by three bacterial phyla: Proteobacteria, which made up 36 to 40 per cent of the community depending on the site, Bacteroidota at 27 to 31 per cent, and Actinobacteriota at 16 to 23 per cent. Together those three accounted for about 85 per cent of the community, with Firmicutes and Fusobacteriota present at lower levels. At the family level the most abundant members were the Porphyromonadaceae, Moraxellaceae and Neisseriaceae, and the single most abundant genus across all sites was a Porphyromonas group, present at roughly 5.7 to 7.2 per cent, followed by Cutibacterium, Sphingomonas and Psychrobacter.

The first thing to note is how rich that community is. Across sites and breeds the Shannon diversity index ranged between 4.56 and 5.64, and the number of species detected ranged from 574 to 885. A healthy patch of dog skin, in other words, is home to hundreds of bacterial species living together, not a thin scattering of a few familiar bugs. That richness turns out to be part of what health is, and its loss is part of what disease looks like.

Two further features are worth drawing out. First, many of the most common core species are organisms usually associated with the mouth, including Porphyromonas gulae, Capnocytophaga canimorsus and Bergeyella zoohelcum. The authors attribute this to the licking and grooming that moves oral bacteria onto the coat, a reminder that the body's microbial communities are connected rather than sealed off from one another. Second, the community is not uniform. Breed and skin site were the main drivers of variation, while sex had no measurable effect. The largest difference between breeds, between Beagles and Norfolk Terriers, accounted for about 6.5 per cent of the variation, and different sites on the same dog carried recognisably different communities: the interdigital skin between the toes, in constant contact with the ground, differed from the more sheltered dorsal back. A healthy skin microbiome is therefore a range rather than a single fixed profile, which matters for anyone trying to say what a departure from health looks like. It also means the sampling site has to be held constant before two readings can be compared.

The healthy community helps keep pathogens out.

Because Whittle's 2024 study read gene function as well as identity, it could ask what the healthy skin community is doing, not just who is present. The most informative finding was that the pathway for the biosynthesis of secondary metabolites, the class of compounds that includes natural antimicrobials, was enriched in the core microbiome. The authors also found the gene cluster for Pep5, a lantibiotic, an antimicrobial peptide first described from a human skin commensal that can inhibit other staphylococci.

Alongside the antimicrobial genes, Whittle's team found genes for the active transport of iron, an element every microbe competes for on the nutrient-poor surface of the skin, and genes for adhesion and biofilm formation that let resident organisms hold their place. Taken together these read as the toolkit of a community built to occupy and defend a surface.

That points to a role that is easy to overlook: a healthy skin community is not neutral ground but an occupied territory, and its residents actively compete with newcomers. The relevance to disease is direct. Increased abundance of Staphylococcus species, and of Staphylococcus pseudintermedius in particular, is a recognised feature of canine atopic dermatitis, and the authors suggest that antimicrobials produced by ordinary skin residents may help hold S. pseudintermedius in check in a healthy dog. On that reading, part of what protects the skin is simply a full, functioning community, and part of what goes wrong in disease is the loss of that occupancy. It is worth adding the caveat the authors themselves make: this is a map of the healthy state and a plausible mechanism, not proof that dysbiosis causes disease rather than following from it. Whether the microbial shift comes first or the inflamed, barrier-damaged skin does is still an open question.

What changes in skin and ear disease, in 589 dogs.

The largest look at what happens to that community in disease comes from Tang and colleagues in 2020, who analysed 589 canine samples using next-generation sequencing that measured both the relative make-up of the community and its absolute microbial load. The set comprised 332 skin swabs (172 from healthy dogs and 160 from clinically affected dogs) and 257 ear swabs (128 healthy and 129 affected), drawn from 89 breeds. "Clinically affected" was deliberately broad, covering atopic dermatitis, skin allergies, non-healing wounds, pustules and other suspected infections for the skin samples, and otitis externa for the ears.

Two things happened together in disease. First, diversity collapsed. The Shannon diversity index, a standard measure of how many organisms are present and how evenly, fell sharply in affected samples: from about 4.3 to 1.2 in the ear (P less than 0.00001) and from about 4.0 to 1.8 in the skin (P = 0.0017). Affected samples were often dominated by just one or two organisms. Second, the total microbial load rose, and by orders of magnitude. Because the study measured absolute abundance as well as relative make-up, it could show that affected skin carried a median bacterial load around a hundred times higher than healthy skin, and that both bacterial and fungal loads were significantly elevated in disease. Combining the two measures, 78.3 per cent of the clinically affected ear samples showed a microbial overgrowth relative to the healthy range.

The organisms that expanded were a familiar short list: Staphylococcus pseudintermedius, Staphylococcus schleiferi and the yeast Malassezia pachydermatis, alongside several anaerobes. In the skin samples, S. pseudintermedius rose from an average relative abundance of about 6.9 per cent in healthy skin to 45.5 per cent in affected skin, a difference that was highly significant (Wilcoxon P = 8.18 x 10^-31), and S. schleiferi rose from about 2.3 to 34.1 per cent. A point the authors stress is that both bacteria and fungi mattered: a fifth of affected skin samples showed concurrent bacterial and fungal overgrowth, which a bacteria-only or a fungus-only test would miss. The study also surfaced a group of anaerobic organisms, such as Finegoldia magna and Peptostreptococcus canis, that are hard to grow in a diagnostic laboratory and had not been widely recognised as players in canine skin and ear infection, precisely the kind of organism that culture-based testing tends to overlook.

Dysbiosis is a shift in balance, not the arrival of one germ.

It would be easy to read Tang's 2020 findings as a simple story of a pathogen invading, but the data resist that reading, and the resistance is the interesting part. Staphylococcus pseudintermedius is not a foreign organism that appears only in disease. It sits in the healthy skin community too, at low levels: in Tang's healthy skin samples it was among the most common bacteria, and Whittle's healthy dogs carried staphylococci as ordinary residents. What separates health from disease is not the presence of S. pseudintermedius but its overgrowth, and the collapse of the surrounding community that lets it take over.

The co-occurrence analysis made the point sharply. Of all the organisms Tang's team examined, S. pseudintermedius was the only one that showed consistently negative associations with other members of the community, the statistical signature of an organism that displaces its neighbours as it expands. This is why Tang's team argued that neither the relative make-up of the community nor its absolute load told the whole story on its own, and that the two together best described the diseased state. It also fits a wider principle running through microbiome science and echoed in the mouth and gut: disease is more often a property of a whole community losing its balance than of a single culprit arriving. The clinical corollary is that detecting a given organism, on its own, does not confirm that it is causing disease.

Two details reinforce that. Where the diseased communities were not dominated by staphylococci, they were often taken over instead by consortia of anaerobic bacteria, the kind of mixed, oxygen-averse population that tends to accompany biofilms and deeper infection rather than any one named pathogen. And the boundary between health and disease was not absolute: a small number of the clinically healthy dogs carried low-diversity communities that looked, on the sequencing, like early dysbiosis, even though their skin appeared normal on the day. The community can drift before the skin shows it, which is the same lesson the longitudinal work on the canine mouth reached from the other direction.

What skin disease costs dogs and owners, in 200 dogs.

The community-level science sets up the biology, but for owners and vets the disease is felt as itch, discomfort, sleepless nights and the grind of long-term treatment. That burden has been measured. Noli and colleagues in 2011 applied a validated 15-item quality of life questionnaire to the owners of 200 dogs with a range of skin diseases, scoring both the dog's quality of life and the owner's, together with the owner's sense of the disease's severity.

The questionnaire scored seven aspects of the dog's life and seven of the owner's, from sleep, play and appetite through to time lost, expense and emotional strain, each on a four-point scale. The five diseases with the worst quality of life scores were sarcoptic mange, pododermatitis, complicated atopic dermatitis (atopic dermatitis with secondary pyoderma, Malassezia infection or otitis), pemphigus foliaceus and endocrine alopecia. Owner-perceived severity correlated significantly with both the dog's quality of life (P = 0.002) and the owner's (P = 0.015). One counter-intuitive result stood out: pruritic diseases did not, as a group, score significantly worse than non-pruritic ones (P = 0.19), and some conditions that a clinician might dismiss as cosmetic, such as colour dilution alopecia, drew high distress scores from owners. The burden of a skin disease, in other words, is not read reliably off its clinical appearance, which is precisely the argument for measuring it directly.

The study also asked owners what they would pay for a definitive cure, as a measure of how much the disease weighed on them. Neither the severity of the disease nor its lesion score predicted the answer. What did predict a greater willingness to pay was female sex, younger age and a higher level of education among the owners. The value an owner places on relief, then, tracks who they are more than how bad the vet judges the skin to be, another sign that the disease is lived rather than simply observed.

The same burden in cats, in 185 cats.

The feline side of the quality of life story is better documented than the feline skin microbiome. Noli and colleagues in 2016 developed and validated an equivalent 15-item questionnaire for cats, and applied it across 185 cats with skin disease. In the validation, which compared 45 cats with allergic dermatitis against 39 healthy cats, quality of life scores were significantly worse in the allergic cats than in the healthy ones (P less than 0.0001), confirming that the instrument could tell diseased from healthy animals.

As in dogs, the owner's sense of severity tracked quality of life closely, correlating with the cat's quality of life (r = 0.51, P = 0.0003) and, more strongly, with the owner's own (r = 0.64, P less than 0.0001). The correlation with pruritus was more modest (r = 0.3, P = 0.03), and the veterinary lesion scores, SCORFAD and FeDESI, correlated only weakly and non-significantly with quality of life. The gap between how bad a cat's skin looks to a vet and how much the disease weighs on the household is real and measurable, and it runs in both species.

The reasons cats give owners grief are their own. Allergic skin disease in cats often shows as relentless head and neck itching, over-grooming and self-trauma, and the day-to-day management, medications, dietary changes, Elizabethan collars and repeat clinic visits, is disruptive to an animal that prizes routine and to the person managing it. That the questionnaire could be applied across 185 cats with a range of skin diseases, and still separate allergic cats cleanly from healthy ones, is what makes it a usable measure rather than a curiosity.

Why clearing the skin does not always restore quality of life.

The most useful finding in the quality of life work, and the one most relevant to how skin disease is managed, is that treating the skin successfully does not restore quality of life in equal measure. In Noli's 2011 study, 23 dogs with atopic dermatitis were assessed before and after treatment. Every score improved, but not evenly. The dog's quality of life improved by about 59.5 per cent and the veterinary lesion score (CADESI-03) by about 61.8 per cent, yet the owner's quality of life improved by only 28 per cent. The questions that improved least were those tied to the burden of maintenance therapy: time lost, physical effort and expense. The 2016 cat study reached the same conclusion, with quality of life not driven by the improvement in clinical scores and the therapy-burden questions again improving least.

Noli's 2019 review of this field draws the threads together: across studies, quality of life tends to improve less than clinical measures such as pruritus and lesion scores after treatment, and the likeliest explanation is the ongoing work of managing a chronic disease. For a lifelong condition such as atopic dermatitis, this reframes what success means. Resolving the lesions is necessary but not sufficient; the treatment plan itself, if it is onerous, becomes part of the disease's weight on a household. That is an argument for choosing treatments the owner can actually sustain, and for asking about the owner's experience rather than assuming that a clear skin equals a settled life.

How the severity of skin disease is measured.

Every claim above rests on the tools used to score skin disease, and those tools have been the subject of careful work in their own right. For decades, trials of atopic dermatitis treatments relied on a patchwork of unvalidated scales, which made results hard to compare from one study to the next and held back any pooled analysis. Fixing that meant agreeing on how to measure lesions and itch. For canine atopic dermatitis, the reference lesion score has been the Canine Atopic Dermatitis Extent and Severity Index, most rigorously validated in its third version, CADESI-03. Its thoroughness is also its weakness: a full CADESI-03 requires 248 separate evaluations, which is impractical in a busy consultation.

To address that, Plant and colleagues in 2012 developed and validated a shorter tool, the Canine Atopic Dermatitis Lesion Index (CADLI), in 57 atopic dogs. The CADLI correlated strongly with the full CADESI-03 (r = 0.84, P less than 0.001), agreed closely between different observers (r = 0.91) and on repeat scoring by the same observer (r = 0.98), and took on average 1.9 minutes to complete against 12.6 minutes for CADESI-03. Alongside lesion scores, pruritus is measured with owner-rated visual analogue scales. The effort to standardise all of this culminated in the work of Olivry and colleagues in 2018, whose COSCAD'18 project, run through the International Committee of Allergic Diseases of Animals, defined a core outcome set for canine atopic dermatitis trials: skin lesions scored with CADESI4 or CADLI, pruritus with a 10-point visual analogue scale, and the owner's global assessment of treatment efficacy. Consistent tools are what allow results from different studies to be compared at all, and they are the reason the numbers in this post can be read side by side.

The skin barrier and hydration, in 18 atopic cats.

The microbiome does not sit on inert skin. In atopic dermatitis the physical barrier itself is often compromised, and a leaky barrier and a disturbed microbial community tend to travel together, each plausibly worsening the other. One way to measure barrier function is skin hydration, read with a corneometer. Szczepanik and colleagues in 2017 examined this in 18 European shorthair cats with confirmed atopic dermatitis, measuring hydration at seven body sites and comparing it with the SCORFAD and FeDESI lesion scores.

The results were mixed and honestly reported. There were some positive correlations between lesion severity and hydration, for the SCORFAD score at the axilla, thorax and forelimb and for FeDESI at the axilla and lumbar sites, but the overall relationship between clinical scores and hydration was limited. The clearest single signal was at the concave pinna, the inner ear flap, where FeDESI scores correlated negatively with hydration (r = 0.47), leading the authors to suggest the pinna as a useful site for assessing skin barrier function in cats.

The value of the study is less any one correlation than the reminder that the microbial and the physical sides of skin health are measured with different instruments and are still being connected. A weakened barrier lets water out and, plausibly, lets the microbial balance drift, while an overgrown community and its inflammation can degrade the barrier in turn. Which comes first is the same unresolved question raised earlier, and it is why the honest framing keeps barrier and microbiome as two linked but separately measured parts of the same disease rather than collapsing one into the other.

What we know about cats, and what we do not.

It is worth being plain about the state of the evidence, because the two halves of this post rest on very different footings. The clinical burden of skin disease in cats is documented: the 2016 quality of life work covered 185 cats, and the barrier study, though small, adds real feline data. The skin microbiome, by contrast, has been characterised mainly in dogs. Whittle's core skin microbiome and Tang's health-versus-disease comparison are both canine studies, and there is no comparable metagenomic map of the healthy or diseased feline skin community in the evidence reviewed here.

So the honest position is this. In dogs, the direction of change is reasonably clear: a diverse, protective community in health, and a narrowed, overgrown one in skin and ear disease. In cats, the disease is real and its burden is measurable, but whether the feline skin microbiome shifts in the same way remains an open question rather than a settled finding. The cat is not simply a small dog in this respect; its skin, coat and grooming differ, and its microbial community may differ too. Saying so is more useful than assuming the canine pattern carries across unchanged, and it marks out exactly where more feline research is needed.

Where BAARK fits.

The bottom line.

Healthy canine skin carries a structured, diverse microbial community that does more than sit there: it competes with opportunistic pathogens and helps keep organisms such as Staphylococcus pseudintermedius in check. In skin and ear disease that community narrows sharply, its total load climbs, and a few organisms, chiefly S. pseudintermedius and the yeast Malassezia pachydermatis, overgrow, so the change is one of lost balance rather than a single invading germ. Allergic skin disease also carries a heavy and measurable cost for dogs, cats and their owners, one that clearing the visible lesions only partly relieves, because the burden of long-term treatment lingers after the skin looks better. The feline skin microbiome, unlike the feline experience of skin disease, has barely been mapped. Reading a microbial community directly, by sequencing rather than by culture or by eye, is the thread that ties this emerging skin science to the way the gut and oral communities are already being profiled.