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Review

Skin Microbiome Shifts in Various Dermatological Conditions

by
Conan H. Lee
1,
Mildred Min
2,3,
Sami S. Jin
4 and
Raja K. Sivamani
2,3,5,6,*
1
School of Medicine, University of California Davis, 4610X St., Sacramento, CA 95817, USA
2
College of Medicine, California Northstate University, 9700 W Taron Dr., Elk Grove, CA 95757, USA
3
Integrative Skin Science and Research, 1495 River Park Drive, Sacramento, CA 95819, USA
4
School of Medicine, University of California San Diego, La Jolla, CA 92093, USA
5
Pacific Skin Institute, 1495 River Park Dr Suite 200, Sacramento, CA 95815, USA
6
Department of Dermatology, University of California-Davis, 3301 C St #1400, Sacramento, CA 95816, USA
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2025, 14(17), 6137; https://doi.org/10.3390/jcm14176137 (registering DOI)
Submission received: 23 July 2025 / Revised: 12 August 2025 / Accepted: 18 August 2025 / Published: 30 August 2025
(This article belongs to the Section Dermatology)
Browse Figure
Versions Notes

Abstract

Background/Objectives: The human skin provides a protective barrier composed of bacteria, fungi, viruses, and archaea that prevents the invasion of harmful organisms. Recent advancements in genomic sequencing have allowed for greater accuracy of species detection. This review aims to summarize the most up-to-date skin microbiome shifts in various dermatological diseases. Methods: A systematic search was conducted to examine microbiome shifts comparing lesional and nonlesional or diseased and healthy skin across various dermatological conditions. A literature search was conducted on PubMed, Web of Science, and Embase Databases from inception through April 2024, yielding 38 studies. Results: Staphylococcus aureus was reported unanimously in all skin conditions. Most studies in this review, except those investigating acne vulgaris, showed a decreased microbiome diversity in diseased skin. Finally, there was a greater shift in the proportion of pro-inflammatory bacterial and fungal strains. Conclusions: The skin microbiome is significantly altered in the progression of numerous dermatological diseases. Diversity of the skin microbiome is decreased, and there is an increased proportion of pro-inflammatory bacterial and fungal strains. The skin microbiome also provides a more comprehensive understanding of the development and progression of many inflammatory skin diseases. Prebiotic treatments may propose a much safer and cheaper alternative to antibiotics, which can have highly toxic side effects and negative implications for public health regarding antibiotic resistance. More research is required to fully understand both the microbiome changes and efficacy and viability of using probiotic treatments to restore the skin microbiome, thereby improving patient outcomes in all dermatological conditions.

1. Introduction

The human skin provides an effective physical barrier that prevents the invasion of harmful organisms and foreign substances. The skin microbiome contains billions of microorganisms composed of bacteria, fungi, viruses, and archaea [1]. The skin microbiome consists mainly of four types of bacteria: Actinobacteria (52%), Firmicutes (24%), Proteobacteria (16%), and Bacteroidetes (6%) [2]. Representatives of Cutibacterium, Staphylococcus, and Corynebacterium genera constitute 45 to 80% of the skin microbiome [3]. These microbes produce antimicrobial peptides that help contribute to inflammatory homeostasis and regulation of immune responses, which are disrupted in diseases presenting with a dysbiosis of the skin microbiome such as acne, atopic dermatitis, psoriasis, and rosacea [4,5].
Currently, there are different methods in characterizing the skin microbiome. One method involves 16S ribosomal RNA (rRNA) sequencing, which uses PCR to amplify the 16S rRNA region with primers [6]. The accuracy of this method can be limited by horizontal gene transfer of various bacteria strains [7]. On the other hand, shotgun whole-genome sequencing (WGS) is a more expensive method that uses random primers to sequence overlapping regions of a genome [8]. A comparative study demonstrated that WGS was more effective than 16S rRNA sequencing, with an enhanced detection of the species, diversity, and prediction of genes [9]. Nonetheless, research surrounding the microbiome is continuously evolving and expanding, and with the advancements in sequencing techniques, there is a more comprehensive understanding of the role of the skin microbiome in dermatological conditions. With these advancements, there is more potential in utilizing the microbiome to treat dermatological diseases. It is also important to highlight the underappreciation of fungi research on inflammatory skin conditions. Expanding the research focus outside of just bacteria will allow us to gain a better understanding of antifungal immunity surrounding T cells and the pathogenesis of many skin conditions [10]. To our knowledge, the last scoping review observing the shift in skin microbiome across multiple dermatological diseases was published in 2018. This scoping review aims to summarize the most recent research to critically analyze and summarize the evidence discussing how the skin microbiome is shifted in various dermatological diseases.

2. Materials and Methods

We adhered to the Preferred Reporting Items for Scoping reviews and Meta-analysis extension for Scoping Reviews (PRISMA-ScR) [11] and consulted with a trained librarian from the University of California, Davis School of Medicine. A systematic search was performed on PubMed/MEDLINE, Web of Science, and Embase with the following keywords: humans AND (microbiome OR microbiota) AND (atopic dermatitis OR psoriasis OR acne OR dermatitis OR rosacea OR hidradenitis suppurativa OR skin) AND (shift OR Change). Specific skin conditions were included in the systematic search based on their high prevalence and clinical impact. We applied database filters to include only records categorized as Book and Documents, Clinical Trials, Meta-Analyses, Randomized Controlled Trials, and Reviews. Eligible studies involved prospective and association-based studies comparing the microbiome analysis of healthy and diseased or lesional or nonlesional skin consisting of published manuscripts in English from database inception to April 2024. Animal studies, case studies, non-English literature, systematic reviews, and studies with absent or unclear findings of skin microbiome analysis were excluded. Two independent reviewers (C.H.L. and M.M.) completed the title and abstract screening using the COVIDENCE online scoping review software platform version 2.0 (Veritas Health Innovation, Melbourne, Australia). The reviewers were blinded by each other’s decisions and discrepancies were resolved through a consensus. Reviewers collected information including author (year), skin disease, sample size, measures (e.g., SCORAD, Shannon Diversity index, PD_whole_tree index), and findings of differences in microbiome profiles and its relative abundance. This review was not registered in PROSPERO or any other registry. This scoping review was conducted in accordance with the PRISMA-ScR guidelines. A completed PRISMA-ScR can be found in the Supplementary and the flow diagram is provided below (Figure 1).

3. Results

The search resulted in 1882 titles. One additional title was identified through citation searching and included for review. After removal of duplicate and ineligible studies, 461 studies were screened for inclusion: 423 studies were excluded due to irrelevancy, and the remaining 38 full-text studies were assessed for eligibility through our inclusion criteria. Nineteen studies were included in this review, and the study characteristics can be found in Table 1.

3.1. Dermatologic Conditions

3.1.1. Acne Vulgaris

Acne vulgaris is the most prevalent chronic inflammatory disease involving Cutibacterium acnes (previously known as Propionibacterium acnes) colonization of the pilosebaceous follicle [31,32]. C. acnes plays a major role in the inflammatory pathogenesis of acne through recruitment of lymphocytes, neutrophils, and macrophages, all of which can further damage the follicular epithelium [33]. Cutibacterium acnes also secretes a lipase that metabolizes triglycerides into glycerol and fatty acids, forming comedones and inflammation of the skin [34].
From our scoping review, there are two studies on the microbiome shifts in acne. Both found an increased amount of Staphylococcus bacteria. A double-blind, split-face RCT investigated the microbiome shift in acne and compared it with unaffected skin [12]. This study had numerical data, showing a 33.87% composition of Staphylococcus in lesional skin compared to 26.85% in nonlesional skin. Additionally, Firmicutes increased with a 52.01% composition in lesional versus 47.01% in nonlesional skin. Proteobacteria was significantly decreased, with 28.90% in lesional skin compared to 34.10% in nonlesional skin. Similar Shannon diversity index scores were reported for both lesional and nonlesional skin.
A prospective pilot study looked at the microbiome of preadolescent acne, comparing diseased skin with healthy controls [13]. The alpha diversity index score was reported to be higher in the diseased state compared to the control in four sites (midline forehead, dorsum of the nose, medial left cheek, and the chin). The retroauricular crease was the only exception in which the alpha diversity score was not higher in the diseased state. Although no numerical data is reported, there was a reported increase in Cutibacterium (Propionibacterium) in diseased versus healthy skin.

3.1.2. Atopic Dermatitis

Atopic dermatitis (AD) is a common inflammatory skin disorder with debilitating rash and pruritus [35]. Historically, microbes such as S. aureus and Malassezia are associated with the pathogenesis of AD [36,37]. Skin colonization by S. aureus has been associated with an increased production of IgE due to targeting of IgE molecules to S. aureus toxins [38,39].
A total of nine studies investigated the microbiome of AD on lesional versus nonlesional and diseased versus healthy skin. All studies agreed that there was a significant reduction in the Shannon diversity index of AD compared to nonlesional or healthy skin. One RCT specifically showed that lesional skin had an index value of 2.9 versus the healthy control, which had an index value of 4.49 [16]. This study also discovered that there was an increased amount of human beta defensin 2 (hBD-2) in lesional skin. A split-face RCT found a negative correlation between the Shannon diversity index and Severity Scoring of Atopic Dermatitis (SCORAD) in lesions of AD [21]. Four studies found an increased amount of S. aureus in lesional skin [14,15,18,19]. Of these four studies, a single-blinded RCT reported nonlesional skin with less than 25% composition of Staphylococci, whereas lesional skin had a composition of 60 to 70%. In another study, there was an increased baseline total bacteria density in diseased skin compared to healthy skin by approximately ten-fold [18]. In the third RCT, S. aureus comprised 72.5% of the whole species in lesional skin, which was significantly higher than in nonlesional skin (p = 0.0014) [19]. The final study demonstrated that the relative abundance of S. aureus in AD patients was significantly higher in lesional (36.35%) and nonlesional (7.20%) compared to healthy controls (2.08%, p < 0.001) [15]. In a non-randomized controlled trial investigating children with AD versus healthy children, CHROMagar analysis of S. aureus and Malassezia demonstrated increased S. aureus (11.0/25 cm2 versus 5.0/25 cm2 in healthy controls) and Malassezia species (1.5/25 cm2 versus 1.0/25 cm2 in healthy controls) in AD skin [20]. Furthermore, two studies correlated severity of AD to total number of S. aureus on lesional skin, demonstrating that the burden of S. aureus may be associated with disease burden [15,20]. Other reports include significantly decreased density in Corynebacterium, Propionibacterium, and Lactobacillus species [16,20,21]. Interestingly, one study focused on the mycobiome differences in lesional versus nonlesional skin in AD [17]. This study found four fungal genera that were present only in lesional skin and these included Alternaria, Coniosporium, Debaryomyces, and Capnodiales. Moreover, there were several bacteria that were significantly correlated with pathogenic fungal species in lesional skin. For example, Corynebacterium kroppenstedtiian and Staphylococcus pettenkoferi were positively correlated with Candida spp., and Pseudomonas spp. were correlated with Aspergillus and Candida spp. [17].

3.1.3. Androgenetic Alopecia

Androgenetic alopecia (AGA) is a progressive hair loss disorder with an influence from predetermined genetics and an excessive response to androgens [40,41]. Recent research has found an increase in C. acnes and Burkholderia in AGA, and an increase in P. acnes may be associated with an elevated immune response and gene expression in the hair follicle [42]. Although increased Malassezia has been associated with disease progression of AGA, studies suggest that a host predisposition in addition to microbiome shift in Malassezia is required for development of AGA [43,44].
One non-randomized control study investigated the microbiome in male AGA patients (n = 12) with stage III–IV alopecia per the Norwood–Hamilton classification [22]. Compared to healthy controls, diseased skin showed a significant increase in C. acnes (84% to 79%) and Stenotrophomanas geniculata (1.6% vs. 0%), and a significant decrease in Staphylococcus epidermidis (10% vs. 12%). Although alpha diversity did not differ, the ratio of C. acnes to S. epidermidis was significantly higher in patients with AGA.

3.1.4. Diaper Dermatitis

Diaper dermatitis (DD), otherwise known as diaper rash, is an acute inflammatory reaction, usually secondary to diaper use. DD occurs in between 7 and 50% of the general population, and mostly in infants and elderly adults affected by urinary incontinence or of sedentary status [45]. A recently recognized component of DD pathogenesis is skin microbiome composition, with pathogenic strains such as Candida albicans and S. aureus being most commonly recognized with the inflammatory response [46].
One 2019 study demonstrated that compared to healthy infants and toddlers, those with DD had a significantly increased Shannon alpha diversity and Choas index, suggesting that increased skin microbiome diversity may play a role in DD [23]. Infants and toddlers with DD had significantly increased abundances of Proteobacteria, Enterococcus, Erwinia, Pseudomonas, Rhodococcus, Acinetobacter, and Ruminococcus and decreased abundances of Clostridium and Actinomyces compared to healthy controls. Furthermore, PCoA distribution in healthy samples were more concentrated than in DD samples, suggesting higher intra-group similarities in healthy skin [23]. Overall, more research into the role of the skin microbiome in DD is needed.

3.1.5. Hand Eczema

Hand dermatitis, also known as hand eczema, is a common, multifactorial disease that is prevalent in 2 to 10% of the general population [47]. Evidence for the role of the skin microbiome in hand dermatitis is still emerging. However, one 2021 study evaluated the differences in skin microbiome profiles between health-care workers with hand eczema and healthy controls [24]. In both parts of the study, there was no difference found in alpha or beta diversity between the two cohorts. There were also no significant differences in bacterial species or genera [24]. A 2022 study demonstrated that the skin microbiome in hand eczema had a lower bacterial alpha diversity compared to healthy skin (p = 0.003) [25]. This study also found that the relative abundance of S. aureus in those with hand eczema was significantly higher than healthy skin (p < 0.001), and that disease severity was correlated with the abundance of S. aureus [25].

3.1.6. Lamellar Ichthyosis

Lamellar Ichthyosis (LI) is a potential life-threatening skin disorder characterized by scaling, hyperkeratosis, and inflammation [48,49]. Current research on LI shows an increase in C. acnes, Staphylococcus, Corynebacterium, and Malassezia [50]. The pathogenesis and profiling of LI has been found to have a T helper 17 cell immune polarization [51,52]. Microbiome studies have indicated that Staphylococci, Corynebacteria, M. slooffiae, and Trichophyton may promote the T helper 17 cell skewing, while C. acnes, M. globosa, and M. sympodialis may support a homeostatic host–microbe interaction [50].
One comparative retrospective study observed the microbiome of patients with LI [26]. The microbiome of diseased skin compared to healthy controls showed an increased amount of methicillin-resistant S. aureus (MRSA), Fusobacterium (16.67% versus 4.17%), Gram-negative rods consisting of Enterobacter, Proteus, and Klebsiella (52.78% versus 51.39%), and fungal population mostly highlighting Candida (22.22% versus 5.56%). On the other hand, there was a decrease in lipophilic diphtheroids (11.11% versus 27.78%), P. acnes (5.6% versus 15.28%), and Micrococci (22.22% versus 36.11%), comparing composition percentages of patients with LI to healthy controls, respectively. MRSA was exclusively seen in patients affected with LI, constituting 33.33% of S. aureus flora.

3.1.7. Psoriasis

Psoriasis is a chronic, inflammatory skin condition that affects approximately 3% of adults in the United States [53]. Psoriasis is classically characterized by symmetrically distributed well-circumscribed, erythematous scaly plaques involving the extensor surfaces, trunk, and scalp [54]. There is emerging evidence supporting the role of the skin microbiome and mycobiome in disease pathogenesis. For example, studies have demonstrated decreases in microbiome diversity, and altered skin microbiome profiles in psoriasis skin [55].
To the best of our knowledge, there is one study from 2015 that demonstrates shifts in the skin microbiome in psoriatic skin compared to nonlesional or healthy skin. In the 2015 study, psoriatic skin was found to have an increased abundance of Firmicutes phylum and decreased abundance of Proteobacteria phylum compared to healthy controls [27]. Moreover, there were no significant differences noted in Shannon alpha diversity or richness when comparing lesional versus nonlesional skin [27]. More research is needed to identify further shifts in psoriatic skin microbiomes and how these differences may affect therapeutic modalities for psoriasis.

3.1.8. Rosacea

Rosacea is a chronic inflammatory skin condition that commonly affects the nose, chin, cheeks, and forehead characterized with flushing, erythema, telangiectasia, papules, and pustules [56]. Microorganisms on the skin can activate the innate immune system through the production of Toll-like receptor 2 [57]. This receptor can further elicit inflammation, erythema, and telangiectasia [58], which commonly present in rosacea. The pathogenesis of rosacea has also been associated with a decrease in the abundance of Cutibacterium acnes [59]. C. acnes has a protective effect by breaking down the sebum into free fatty acids, which can inhibit biofilm formation by bacteria such as S. epidermidis [60]. This prevents other harmful microorganisms from colonizing the skin.
Two observational case–control studies observed the microbiome shift in patients affected with rosacea and compared it to healthy controls. Both studies found no significant difference in skin microbiome diversity, in which one study looked at Shannon diversity, Chao, and Simpson index. In this study, there was an increased abundance of S. epidermidis (19.64% vs. 6.48%) in diseased skin, and a decreased actinobacteria (69.07% vs. 86.09%), C. acnes (61.79% vs. 79.69%), and firmicutes (8.05% vs. 21.19%) in diseased skin [28]. The other case–control study also found a decrease in C. acnes, but it was only observed in male patients [29]. There was an increase in the relative abundance of C. acnes in female patients. This study looked at alpha and beta diversities and discovered that across all ages, C. acnes remained the most abundant species and Corynebacterium kroppenstedtii was the second most abundant.

3.1.9. Seborrheic Dermatitis

Seborrheic dermatitis (SD) is an inflammatory skin condition that presents with papulosquamous morphology in sebum-rich areas [61]. The pathophysiology of SD highly involves an impaired immune reaction to Malassezia species, which trigger inflammation and hyperproliferation of the epidermis. Specifically, Malassezia degrades the sebum to disrupt the lipid balance of the skin surface [62]. Recent research has linked SD disease states with an increase in Malassezia and Staphylococcus abundance [63,64].
One prospective cohort study looked at the microbiome homeostasis of both bacteria and fungi in seborrheic dermatitis through 16S rRNA sequencing and linear discriminant analysis effect size (LefSe), respectively [30]. Shifts in the microbiome showed an increased amount of five fungal genera (Malassezia, Alternaria, Nagnishia, Hanseniaspora, Cladophialophora) and five bacterial genera (Staphylococcus, Blautia, Bifidobacterium Xylanimicrobium, Fusobacterium, Lysobacter). On the contrary, there was lower enrichment of four fungal genera (Mycosphaerella, Cladosporium, Rhodotorula, Debaryomyces). Finally, there was a significant decrease in Shannon diversity, PD_Whole_tree index, and relative abundance of microorganisms (Table 2).

4. Discussion

This scoping review highlights several key findings regarding the role of skin microbiome in dermatological diseases. Across nearly all skin conditions examined, Staphylococcus aurerus was consistently found to be elevated in diseased skin, suggesting a common microbial signature associated with skin pathology. Most studies, except those focused on Acne vulgaris, also reported decreased microbial diversity in affected skin areas compared to healthy controls. These findings suggest that both microbial imbalance and dominance of pathogenic species, particularly S. aureus, may contribute to disease progression.
Given recent advances in biologics and small molecule therapies targeting the immune mechanisms of skin diseases such as AD and psoriasis [65,66], our review underscores the parallel importance of addressing microbial dysbiosis as part of a comprehensive treatment approach. For example, S. aureus in AD has been shown to secrete virulence factors such as toxins and proteases, which can further aggravate the skin barrier and disrupt the existing immune response [67]. Its frequent dominance in AD often reflects colonization rather than active infection, with pathogenicity varying by strain. CC1, the most common lineage in AD, carries multiple virulence factors (e.g., SEB, SEC, PVL) and shows enhanced fibrinogen binding, potentially contributing to greater disease severity. In contrast, CC30, more often found in healthy skin, produces fewer toxins and demonstrates lower virulence potential. These strain-specific differences underscore the importance of distinguishing colonization from infection when interpreting the role of S. aureus in AD.
Our scoping review identified S. aureus overrepresentation across all skin conditions examined, suggesting that reducing its abundance may be a therapeutic target. Notably, recent studies indicate that other Staphylococci strains can help inhibit S. aureus growth and pathogenicity by blocking quorum sensing—a cell–cell communication process that allows both Gram-negative and Gram-positive bacteria to regulate their gene expression [68,69]. With most studies, except those investigating acne vulgaris, showing a decreased microbiome diversity in diseased skin, restoring a balanced skin microbiome may help limit S. aureus burden and support skin health. However, caution is warranted in attributing a causative role to S. aureus. The microbiome differences observed between diseased and healthy skin may be a consequence of underlying pathology rather than its initiating factor. This distinction is critical when considering therapeutic strategies aimed at reducing S. aureus abundance or restoring microbial diversity. While the evidence suggests the potential of commensal-mediated quorum sensing inhibition to curb S. aureus pathogenicity, it remains unclear whether such modulation can alter disease trajectory. Addressing this uncertainty will require well-designed longitudinal and interventional studies to determine whether shifts in microbial composition actively drive disease progression and to evaluate the efficacy of targeted interventions, including probiotics, in improving patient outcomes.
The topic of altering the skin microbiome naturally leads to the discussion of oral and topical antibiotics. Oral probiotics, on the other hand, have shown promising results to become a viable therapeutic option for treating acne vulgaris while reducing the number of adverse events associated with prolonged use of antibiotics [70]. Such adverse events include drug fever, rash, lipodystrophy, nausea, vomiting, Stevens–Johnson syndrome, ototoxicity, and hypersensitivity reactions [71]. Finally, the use of antibiotics brings upon an urgent public health issue—antibiotic resistance [72]. The chronic usage of antibiotics has led to the development of drug-resistant diseases which claim over 700,000 lives annually [73]. The need to utilize non-antibiotic treatment has never been greater. Given the more recent research results and a stronger understanding in the increases and decreases in specific bacterial and fungal strains associated with respective skin diseases, probiotics hold potential in alleviating and restoring the microbiome of diseased skin. Although both topical and oral probiotics can help restore the skin microbiome, challenges in utilizing topical probiotics include environmental conditions that can prevent colonization of the probiotic [74].
Current biotic treatments that modulate the skin microbiome include topical and oral probiotics. Probiotics are live, nonpathogenic microorganisms that can help improve the skin microbiome balance and homeostasis [75]. Although additional research is needed to confirm the efficacy of probiotics, both topical and oral probiotics have been found to be effective in treating inflammatory skin diseases and may potentially improve wound healing and treatment of skin cancer [76]. An important theory of the alteration of skin microbiome through biotic treatment is the gut–skin axis, a co-dependent relationship between the gut microbiome and skin health. Dysbiosis of both the skin and the gut presents an immune imbalance, which can further progress the development of inflammatory skin diseases [77]. In addition, metabolites produced by the gut microbiome can disrupt the skin microbiome through the accumulation of bacterial toxins, antigens, and pathogens that can penetrate the epidermal barrier through blood circulation [78]. Both animal and human studies have demonstrated that probiotics could help improve inflammatory skin conditions such as psoriasis through the suppression of pro-inflammatory cytokines [79,80]. Clinical trials on the development of AD in infants found that probiotic supplementation can help reduce the risk of developing AD and respiratory allergic diseases in the future [81,82]. Probiotics are viable treatments and should be used as a safer and more financially reasonable alternative to antibiotics. However, variability in formulations, dosing, and study design limits broad generalization of these results. Hence, the concept that probiotics serve as a safer, cost-effective alternative to antibiotics remain a hypothesis requiring further validation. Nevertheless, the accumulating body of preliminary evidence, coupled with the expanding toolkit of microbiome-based therapeutics, provides a strong foundation for future clinical research to more precisely define the role of probiotics and related interventions in dermatologic care.
The studies reviewed here predominantly utilized 16S and ITS sequencing methodologies. There are several methodologies that can be utilized for microbiome-based sequencing such as 16S, ITS, short vs. long chain reads, and shotgun whole-genome sequencing, each with its benefits and limitations. 16S sequencing can identify bacteria at the genus and species level but typically cannot resolve to the strain level, and it cannot detect fungi or yeast. ITS sequencing, in contrast, can identify fungi and yeast but not bacteria [1]. Short-read 16S sequencing is faster but offers lower taxonomic resolution, whereas long-read 16S sequencing can achieve strain-level resolution but still cannot assess fungi or yeast and typically requires more time and resources. Shotgun whole-genome sequencing provides the most comprehensive profile, enabling strain-level identification across bacteria, fungi, and yeast, but it is more costly and computationally demanding [2].

5. Future Studies

Future work should extend beyond live probiotics to systematically investigate postbiotic and synbiotic approaches. Postbiotics—non-viable microbial products such as short-chain fatty acids, bacteriocins, and extracellular vesicles—offer advantages including improved stability, easier storage, and reduced infection risk [75,76,77,78]. Synbiotics may provide additive benefits by combining probiotics with prebiotics that support their activity.
Innovative delivery strategies also warrant exploration. Jiang et al. (2024) demonstrated that low-frequency ultrasound (LFS) enhances dermal penetration and directly modulates keloid fibroblast biology via Piezo1 activation, influencing calcium influx, migration, collagen production, and apoptosis [83]. Pairing LFS with microbiome-derived metabolites could both improve cutaneous delivery and engage fibroblast signaling pathways in fibrotic skin disease. Given the historical difficulty in distinguishing white patchy skin lesions, the utilization of deep convolutional neural networks may assist researchers in improving their analysis of various dermatological conditions especially when comparing lesions with or without the transformer modules applied [84]. To further fine-tune the microbiome research, a Cross-Modal Causal Representation Learning framework can be supplemented to reduce bias from microbiome feature sets [85].
Another priority is microbiome-informed risk prediction for immune-related adverse events. In pembrolizumab-induced psoriasis, Th17/IL-23-driven inflammation was identified, but microbial contributions remain unexamined [86]. Prospective immune checkpoint inhibitor cohorts with longitudinal gut and skin microbiome profiling, metabolomics, and immune phenotyping could identify predictive microbial signatures, enabling targeted preventive interventions with postbiotics or synbiotics.
Finally, emerging spatial and single-cell technologies—including spatial transcriptomics, single-cell RNA sequencing, and spatial metagenomics—can map microbe–host interactions in situ [87]. Applying these to lesional and perilesional skin would clarify how microbial shifts shape local immune and stromal environments, accelerating the shift from generalized supplementation to precise, mechanism-guided, and personalized microbiome-based dermatologic therapies.

6. Limitations

It is important to note the variability in each study’s design and methods. While some studies utilized a randomization process, many were non-randomized or involved either a comparative retrospective study or prospective pilot study. In addition, most studies had an intervention with a treatment. Since we were only interested in the microbiome shift due to the dermatological disease itself, we looked solely at the pre-treatment microbiome diversity and density. Therefore, a lot of data was not provided regarding statistical analysis and comparisons of the pre-treatment microbiome. To note specifically in Section 3, some studies only have observational increases or decreases in compositions of the microbiome. Most of the studies decided to utilize 16S rRNA sequencing, which is a limitation because 16S rRNA sequencing only captures bacteria, whereas the skin microbiome consists of not only bacteria, but also bacteriophages, fungi, and archaea. One study did not have access to ample resources and therefore utilized qualitative bacterial cultures and sensitivity from swabs instead of 16S rRNA sequencing. Finally, there is a significant limitation in the characterization of healthy, lesional, and nonlesional skin. There should be a difference in the microbiome of nonlesional versus healthy skin. Some studies did not have a healthy control and instead looked at lesional versus nonlesional areas for comparisons in the microbiome composition and density.

7. Conclusions

In conclusion, the skin microbiome is significantly altered in the progression of numerous dermatological diseases. Diversity of the skin microbiome is decreased, and there is a greater shift in the proportion of pro-inflammatory bacterial and fungal strains. The microbiome offers valuable insight into disease mechanisms and may guide targeted interventions for inflammatory skin disorders. While preliminary evidence supports probiotic use for microbiome restoration, further research is essential to confirm efficacy, optimize formulations, and define clinical indications. Advancing this field could ultimately improve patient outcomes across a broad spectrum of dermatologic conditions.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/jcm14176137/s1.

Author Contributions

Conceptualization, C.H.L.; methodology, C.H.L. and M.M.; formal analysis, C.H.L., M.M. and S.S.J.; data curation, C.H.L. and M.M.; writing—original draft preparation, C.H.L., M.M. and S.S.J.; writing—review and editing, R.K.S.; supervision, R.K.S. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not Applicable.

Informed Consent Statement

Not Applicable.

Data Availability Statement

Data can be provided upon request.

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
rRNARibosomal RNA
WGSWhole-genome sequencing
PRISMA-ScRPreferred Reporting Items for Scoping reviews and Meta-analysis Extension for Scoping Reviews
MRSAMethicillin resistant staphylococcus aureus
LILamellar Ichthyosis
RCTRandomized-controlled trial
ADAtopic dermatitis
AGAAndrogenetic alopecia
LefSeLinear discriminant analysis effect size
SDSeborrheic dermatitis
SCORADShannon diversity index and Severity Scoring of Atopic Dermatitis
hBD-2Human beta defensin 2
DDDiaper dermatitis

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Jcm 14 06137 g001
Figure 1. PRISMA-ScR flow diagram.
Figure 1. PRISMA-ScR flow diagram.
Jcm 14 06137 g001
Table 1. Summary table of the studies included in the scoping review.
Table 1. Summary table of the studies included in the scoping review.
AuthorDiseaseFemale to Male Ratio (F to M)Mean Age (Years) ± SDStudy DesignComparison GroupsSample Size, nMethod of SequencingIncreasedDecreasedOther Changes
Dreno [12]Acne15 to 1123 ± 6.5DB, split-face RCTLesional vs. nonlesional2616S rRNA sequencingIncreased Staphylococcus (33.87% vs. 26.85%) and Firmicutes (52.01% vs. 47.01%) in lesional skinDecreased Proteobacteria (34.10% vs. 28.90%) in lesional skinSimilar Shannon alpha diversity index score
Coughlin [13]Acne Vulgaris12 to 4NAProspective Pilot StudyHealthy vs. diseased1616S rRNA sequencingIncreased Staphylococcus and Propionibacterium in diseased skinN/AAlpha diversity was higher in diseased skin four sites (midline forehead, dorsum of the nose, medial left cheek, and chin)
Callewaert [14]AD24 to 29NADB RCTLesional vs. nonlesional53DNA extraction, 16S rRNA V4 amplicon sequencing via Quantitative PCRStaphylococcus aureus in lesional skin Lower Shannon alpha diversity index score in lesional skin
Khadka [15]AD21 to 2111RCTHealthy vs. diseased4216S rRNA sequencingIncreased S. aureusDecreased Shannon alpha diversityRelative abundance of S. aureus positively correlated with disease severity as measured by SCORAD (rho = 0.545)
S. epidermidis and S. hominis were inversely correlated with SCORAD
Lee [16]ADNA28.3 for healthy, 34.2 for severe ADRCTHealthy vs. diseased2016S rRNA sequencingNADecreased Cutibacterium and Lactobacillus in diseased skinIncreased Human beta defensin 2 (hBD-2) and lower Shannon diversity index score in lesional skin
Chandra [17]AD32 to 1710.5Non-RCTLesional vs. nonlesional4916S rRNA sequencing, ITS1 RNA gene showed fungal composition analysisIncreased Alternaria, Coniosporium, Debaryomyce, CapnodialesNAGram-positive Corynebacterium kroppenstedtiian and Staphlycoccus pettenkoferi showed significantly positive correlations with pathogenic Candida species in lesional skin; Pseudomonas spp. correlated significantly with pathogenic Aspergillus and Candida spp.
Gonzalez [18])ADNANASingle-blind RCTHealthy vs. diseased3516S rRNA sequencingIncreased Staphylococcus aureus and Staphylococcus species in lesional skin. Nonlesional generally had less than 25% composition of Staphylococci whereas lesional skin had 60–70%.Decreased Corynebacterium and Propionibacterium in diseased skinIncreased baseline total bacteria density by approximately 10-fold, and decreased community richness and Shannon diversity index in diseased skin
Kwon [19]ADNANARCTLesional vs. nonlesional1816S rRNA sequencingIncreased Staphylococcus aureus, Staphylococcus species in lesional skinDecreased Shannon Diversity in lesional skinHaemophilus parainfluenzae, Streptococcus pseudopneumoniae, P. acnes, and Corynebacterium pseudogenitalium showed significant negative correlations with S. aureus in lesional skin
Krzysiek [20]ADNAMedian, 6.8 for AD group, 8.7 for healthyNon-RCTHealthy vs. diseased60CHROMagar plates for S. aureus and MalasseziaIncreased Staphylococcus aureus, Staphylococcus species in AD skin; Increased Malassezia species in AD skinDecreased Corynebacterium urealyticum in AD skinThe number of S. aureus on lesional skin positively correlated with severity of disease according to validated scoring systems
Zeng [21]AD4 to 817.08 ± 6.72Split side RCTLesional vs. nonlesional1216S rRNA sequencingNANALower Shannon alpha diversity index score and negative correlation between SCORAD and Shannon diversity index score in lesional skin
Filaire [22]Androgenetic Alopecia0 to 2450.5 ± 3.2 for AGA, 48.6 ± 2.1 for healthyNon-RCTHealthy vs. diseased2416S rRNA sequencing, ITS1 rRNA sequencingIncreased Cutibacterium acnes (84% vs. 79%) and Stenotrophomanas geniculata (1.6% vs. 0%) in diseased skinDecreased Staphylococcus epidermidis (10% vs. 12%) in diseased skinAlpha diversity did not differ and ratio of Cutibacterium acnes to Staphylococcus epidermidis was significantly higher in diseased skin
Zheng [23]Diaper DermatitisNANANon-RCTHealthy vs. diseased8516S rRNA sequencingSignificantly increased Shannon diversity and Chao index (richness)
Significantly increased Proteobacteria, Enterococcus, Erwinia, Pseudomonas, Rhodococcus, Acinetobacter, and Ruminococcus		Significantly decreased Clostridium and ActinomycesPCoA distribution in healthy samples were found to be more concentrated, indicating higher intra-group similarities
Kuwatsuka [24]Hand Eczema1 to 034.3Non-RCTHealthy vs. diseased1616S rRNA sequencingNANANo difference in alpha or beta diversity between hand eczema and control groups
Norreslet [25]Hand Eczema28 to 2240.1 ± 11.7Non-RCTHealthy vs. diseased5016S rRNA sequencingSignificantly increased S. aureus in diseased skin versus healthy controlsDecreased bacterial alpha diversity in diseased skinDisease severity was correlated with abundance of S. aureus
Singh [26]Lamellar Ichthyosis9 to 1835.56 weeksComparative retrospective studyHealthy vs. diseased27Qualitative bacterial culture and sensitivities from swabsIncreased methicillin resistant Staphylococcus aureus (MRSA), Fusobacterium (16.67% vs. 4.17%), Gram-negative rods consisting of Enterobacter, Proteus, and Klebsiella (52.78% vs. 51.39%), and fungal population mostly involving Candida (22.22% vs. 5.56%) in diseased skinDecreased lipophilic diphtheroids (11.11% vs. 27.78%), Propionibacterium acnes (5.6% vs. 15.28%), and Micrococci (22.22% vs. 36.11%) in diseased skinMRSA exclusively seen in LI patients constituting 33.33% of Staphylococcus aureus flora
Martin [27]Psoriasis22 to 3259 ± 13Non-RCTLesional vs. nonlesional5416S rRNA sequencingIncreased Firmicute phylum compared to healthy controlsDecreased Proteobacteria phylum compared to healthy controlsNo significant differences in Shannon diversity or richness between lesional and nonlesional skin
Xiong [28]Rosacea26 to 18Median, 27 for rosacea, 26 for healthyObservational case–controlHealthy vs. diseased4416S rRNA sequencingIncreased Staphylococcus epidermidis (19.64% vs. 6.48%) in diseased skinDecreased actinobacteria (69.07% vs. 86.09%), Cutibacterium acnes (61.79% vs. 79.69%), and firmicutes (8.05% vs. 21.19%) in diseased skinNo significant difference in diversity, statistically insignificant differences in Shannon diversity, Chao, and Simpson index
Rainer [29]Rosacea28 to 10NA, range 23–65Observational case–controlHealthy vs. diseased3816S rRNA sequencingIncreased relative abundance of Cutibacterium acnes in diseased skin of female patients (29.7% vs. 27.8%)Decreased relative abundance of Cutibacterium acnes in diseased skin of male patients (23.8% vs. 57.5%)Across all age groups, Cutibacterium acnes remained the most abundant species and Corynebacterium kroppenstedtii the second. No significant differences in ecologic diversity of microbiota
Yu [30]SDNANAProspective CohortHealthy vs. diseased9216S rRNA sequencing, LEfSe analysisIncreased amount of 5 fungal genera (Malassezia, Alternaria, Nagnishia, Hanseniaspora, Cladophialophora) and 5 bacterial genera (Staphylococcus, Blautia, Bifidobacterium Xylanimicrobium, Fusobacterium, Lysobacter) in diseased skinDecreased enrichment in 4 fungal genera (Mycosphaerella, Cladosporium, Rhodotorula, Debaryomyces) in diseased skinDecreased Shannon diversity, PD_whole_tree index, and relative abundance of microorganisms in diseased skin
Table 2. Summary table of all dermatological conditions.
Table 2. Summary table of all dermatological conditions.
DiseaseIncreasedDecreasedOther Changes
AcneIncreased Staphylococcus, Firmicutes, and CutibacteriumDecreased ProteobacteriaInconclusive Shannon alpha diversity score differences
Atopic DermatitisIncreased Staphylococcus aureus, Staphylococcus species, Alternaria, Coniosporium, Debaryomyce, Capnodiales, and Malassezia speciesDecreased Cutibacterium, Lactobacillus, Corynebacterium, and PropionibacteriumDecreased Shannon diversity index
Androgenetic AlopeciaIncreased Cutibacterium acnes (84% vs. 79%) and Stenotrophomanas geniculata (1.6% vs. 0%)Decreased Staphylococcus epidermidis (10% vs. 12%)Alpha diversity did not differ and ratio of Cutibacterium acnes to Staphylococcus epidermidis was significantly higher in diseased skin
Diaper DermatitisIncreased Proteobacteria, Enterococcus, Erwinia, Pseudomonas, Rhodococcus, Acinetobacter, and RuminococcusSignificantly decreased Clostridium and ActinomycesSignificantly increased Shannon diversity and Chao index (richness). PCoA distribution in healthy samples were found to be more concentrated, indicating higher intra-group similarities.
Hand EczemaIncreased S. aureusNADecreased bacterial alpha diversity in diseased skin. Disease severity was correlated with abundance of S. aureus. No difference in alpha or beta diversity between hand eczema and control groups.
Lamellar IchthyosisIncreased methicillin resistant Staphylococcus aureus (MRSA), Fusobacterium (16.67% vs. 4.17%), Gram negative rods consisting of Enterobacter, Proteus, and Klebsiella (52.78% vs. 51.39%), and fungal population mostly involving Candida (22.22% vs. 5.56%)Decreased lipophilic diphtheroids (11.11% vs. 27.78%), Propionibacterium acnes (5.6% vs. 15.28%), and Micrococci (22.22% vs. 36.11%)MRSA exclusively seen in LI patients constituting 33.33% of Staphylococcus aureus flora
PsoriasisIncreased Firmicute phylumDecreased Proteobacteria phylumNo significant differences in Shannon diversity or richness
RosaceaIncreased Staphylococcus epidermidisDecreased Cutibacterium acnesNo significant difference in diversity, statistically insignificant differences in Shannon diversity, Chao, and Simpson index
Seborrheic DermatitisIncreased amount of 5 fungal genera (Malassezia, Alternaria, Nagnishia, Hanseniaspora, Cladophialophora) and 5 bacterial genera (Staphylococcus, Blautia, Bifidobacterium Xylanimicrobium, Fusobacterium, Lysobacter)Decreased enrichment in 4 fungal genera (Mycosphaerella, Cladosporium, Rhodotorula, Debaryomyces)Decreased Shannon diversity, PD_whole_tree index, and relative abundance of microorganisms in diseased skin
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Lee, C.H.; Min, M.; Jin, S.S.; Sivamani, R.K. Skin Microbiome Shifts in Various Dermatological Conditions. J. Clin. Med. 2025, 14, 6137. https://doi.org/10.3390/jcm14176137

AMA Style

Lee CH, Min M, Jin SS, Sivamani RK. Skin Microbiome Shifts in Various Dermatological Conditions. Journal of Clinical Medicine. 2025; 14(17):6137. https://doi.org/10.3390/jcm14176137

Chicago/Turabian Style

Lee, Conan H., Mildred Min, Sami S. Jin, and Raja K. Sivamani. 2025. "Skin Microbiome Shifts in Various Dermatological Conditions" Journal of Clinical Medicine 14, no. 17: 6137. https://doi.org/10.3390/jcm14176137

APA Style

Lee, C. H., Min, M., Jin, S. S., & Sivamani, R. K. (2025). Skin Microbiome Shifts in Various Dermatological Conditions. Journal of Clinical Medicine, 14(17), 6137. https://doi.org/10.3390/jcm14176137

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