Assessment of the Cutaneous Hormone Landscapes and Microbiomes in Vulvar Lichen Sclerosus

Vulvar lichen sclerosus (VLS) is a progressive skin disease of unknown etiology. In this longitudinal case-control exploratory study, we evaluated the hormonal and microbial landscapes in 18 postmenopausal women (mean [SD] age: 64.4 [8.4]) with vulvar lichen sclerosus and controls. We reevaluated the VLS patients after 10-14 weeks of daily topical Class I steroid. We found that groin cutaneous estrone was lower in vulvar lichen sclerosus versus controls (-22.33, 95% CI -36.96 to -7.70; P = 0.006); cutaneous progesterone was higher (5.73, 95% CI 3.74 to 7.73; P< 0.0001). Forehead 11-deoxycortisol (-0.24, 95% CI -0.42 to -0.06; P = 0.01) and testosterone (-7.22, 95% CI -12.83 to -1.62; P = 0.02) were lower in disease. With treatment, cutaneous estrone (-7.88, 95% CI -44.07 to 28.31; P = 0.62), progesterone (2.02, 95% CI -2.08 to 6.11; P = 0.29), and 11-deoxycortisol (-0.13, 95% CI -0.32 to 0.05; P = 0.15) normalized; testosterone remained suppressed (-7.41, 95% CI -13.38 to -1.43; P = 0.02). 16S rRNA V1-V3 and ITS1 amplicon sequencing revealed bacterial and fungal microbiome alterations in disease. Findings suggest that cutaneous sex hormone and bacterial microbiome alterations may be associated with VLS in postmenopausal women.

Androgens at the skin surface regulate S. aureus pathogenesis through the activation of agr quorum sensing

Staphylococcus aureus, the most frequent cause of skin infections, is more common in men than women and selectively colonizes the skin during inflammation. Yet, the specific cues that drive infection in these settings remain unclear. Here we show that the host androgens testosterone and dihydrotestosterone promote S. aureus pathogenesis and skin infection. Without the secretion of these hormones, skin infection in vivo is limited. Testosterone activates S. aureus virulence in a concentration dependent manner through stimulation of the agr quorum sensing system, with the capacity to circumvent other inhibitory signals in the environment. Taken together, our work defines a previously uncharacterized inter-kingdom signal between the skin and the opportunistic pathogen S. aureus and identifies the mechanism of sex-dependent differences in S. aureus skin infection.

One-Sentence Summary

Testosterone promotes S. aureus pathogenesis through activation of the agr quorum sensing system.

Saprophytic bacteria and fungi colonize stearoyl coenzyme-A desaturase-1 knockout skin

Lipids synthesized on the skin are critical to the antimicrobial barrier. Skin lipids also facilitate survival of lipophilic skin commensals in an otherwise dry and acidic ecological landscape. Thus, skin-specific stearoyl-coenzyme A desaturase 1 knockout mice (Scd1^ΔK14 ) with sebocyte atrophy and decreased synthesis of monounsaturated fatty acids, triglycerides and wax diesters have dry, inflamed skin. Here, we used 16S rRNA (V1-V2 and V1-V9) and internal transcribed spacer 1 (ITS1) amplicon sequencing to compare bacterial and fungal skin microbiomes between Scd1^ΔK14 mice and wildtype control mice (Scd1^fl/fl ) in a barrier facility. Saprophytic bacteria including Sporosarcina spp. and Staphylococcus lentus and saprophytic fungi including Alternaria infectoria were found in higher relative abundance in the Scd1^ΔK14 group (ANCOM). Analysis of community diversity (Shannon index) revealed greater fungal alpha diversity in the Scd1^ΔK14 group (p = 0.009, Kruskal-Wallis). Principal coordinates analysis (Bray-Curtis dissimilarity) showed that both bacterial (p = 0.002, PERMANOVA) and fungal communities (p = 0.006, PERMANOVA) of the Scd1^ΔK14 group were unique from the wildtype group. Altogether, these results suggest that sebaceous gland-derived lipids normally restrict the skin microbiome, and in the absence of these lipids, a greater diversity of opportunistic organisms are able to colonize the surface of skin.

Small proline-rich proteins (SPRRs) are epidermally produced antimicrobial proteins that defend the cutaneous barrier by direct bacterial membrane disruption

Human skin functions as a physical barrier, preventing the entry of foreign pathogens while also accommodating a myriad of commensal microorganisms. A key contributor to the skin landscape is the sebaceous gland. Mice devoid of sebocytes are prone to skin infection, yet our understanding of how sebocytes function in host defense is incomplete. Here we show that the small proline-rich proteins, SPRR1 and SPRR2 are bactericidal in skin. SPRR1B and SPPR2A were induced in human sebocytes by exposure to the bacterial cell wall component lipopolysaccharide (LPS). Colonization of germ-free mice was insufficient to trigger increased SPRR expression in mouse skin, but LPS injected into mouse skin triggered the expression of the mouse SPRR orthologous genes, Sprr1a and Sprr2a, through stimulation of MYD88. Both mouse and human SPRR proteins displayed potent bactericidal activity against MRSA (methicillin-resistant Staphylococcus aureus), Pseudomonas aeruginosa and skin commensals. Thus, Sprr1a^-/-;Sprr2a^-/- mice are more susceptible to MRSA and Pseudomonas aeruginosa skin infection. Lastly, mechanistic studies demonstrate that SPRR proteins exert their bactericidal activity through binding and disruption of the bacterial membrane. Taken together, these findings provide insight into the regulation and antimicrobial function of SPRR proteins in skin and how the skin defends the host against systemic infection.

Transcriptional Correlates of Tolerance and Lethality in Mice Predict Ebola Virus Disease Patient Outcomes

Host response to infection is a major determinant of disease severity in Ebola virus disease (EVD), but gene expression programs associated with outcome are poorly characterized. Collaborative Cross (CC) mice develop strain-dependent EVD phenotypes of differential severity, ranging from tolerance to lethality. We screen 10 CC lines and identify clinical, virologic, and transcriptomic features that distinguish tolerant from lethal outcomes. Tolerance is associated with tightly regulated induction of immune and inflammatory responses shortly following infection, as well as reduced inflammatory macrophages and increased antigen-presenting cells, B-1 cells, and γδ T cells. Lethal disease is characterized by suppressed early gene expression and reduced lymphocytes, followed by uncontrolled inflammatory signaling, leading to death. We apply machine learning to predict outcomes with 99% accuracy in mice using transcriptomic profiles. This signature predicts outcomes in a cohort of EVD patients from western Africa with 75% accuracy, demonstrating potential clinical utility.