Interference and co-existence of staphylococci and Cutibacterium acnes within the healthy human skin microbiome.

Human skin is populated by trillions of microbes collectively called the skin microbiome. Staphylococcus epidermidis and Cutibacterium acnes are among the most abundant members of this ecosystem, with described roles in skin health and disease. However, knowledge regarding the health beneficial effects of these ubiquitous skin residents is still limited. Here, we profiled the staphylococcal and C. acnes landscape across four different skin sites of 30 individuals (120 skin samples) using amplicon-based next-generation sequencing. Relative abundance profiles obtained indicated the existence of phylotype-specific co-existence and exclusion scenarios. Co-culture experiments with 557 staphylococcal strains identified 30 strains exhibiting anti-C. acnes activities. Notably, staphylococcal strains were found to selectively exclude acne-associated C. acnes and co-exist with healthy skin-associated phylotypes, through regulation of the antimicrobial activity. Overall, these findings highlight the importance of skin-resident staphylococci and suggest that selective microbial interference is a contributor to healthy skin homeostasis.

Macrophages Are Polarized toward an Inflammatory Phenotype by their Aged Microenvironment in the Human Skin.

Aging of the skin is accompanied by cellular as well as tissue environmental changes, ultimately reducing the ability of the tissue to regenerate and adequately respond to external stressors. Macrophages are important gatekeepers of tissue homeostasis, and it has been reported that their number and phenotype change during aging in a site-specific manner. How aging affects human skin macrophages and what implications this has for the aging process in the tissue are still not fully understood. Using single-cell RNA-sequencing analysis, we show that there is at least a 50% increase of macrophages in human aged skin, which appear to have developed from monocytes and exhibit more proinflammatory M1-like characteristics. In contrast, the cell-intrinsic ability of aged monocytes to differentiate into M1 macrophages was reduced. Using coculture experiments with aged dermal fibroblasts, we show that it is the aged microenvironment that drives a more proinflammatory phenotype of macrophages in the skin. This proinflammatory M1-like phenotype in turn negatively influenced the expression of extracellular matrix proteins by fibroblasts, emphasizing the impact of the aged macrophages on the skin phenotype.

Evaluation of Immunomodulatory Responses and Changed Wound Healing in Type 2 Diabetes-A Study Exploiting Dermal Fibroblasts from Diabetic and Non-Diabetic Human Donors.

The dermis is the connective layer between the epidermis and subcutis and harbours nerve endings, glands, blood vessels, and hair follicles. The most abundant cell type is the fibroblast. Dermal fibroblasts have a versatile portfolio of functions within the dermis that correspond with different types of cells by either direct contact or by autocrine and paracrine signalling. Diabetic skin is characterized by itching, numbness, ulcers, eczema, and other pathophysiological changes. These pathogenic phenotypes have been associated with the effects of the reactive glucose metabolite methylglyoxal (MGO) on dermal cells. In this study, dermal fibroblasts were isolated from diabetic and non-diabetic human donors. Cultured dermal fibroblasts from diabetic donors exhibited reduced insulin-induced glucose uptake and reduced expression of the insulin receptor. This diabetic phenotype persists under cell culture conditions. Secretion of IL-6 was increased in fibroblasts from diabetic donors. Increased secretion of IL-6 and MIF was also observed upon the treatment of dermal fibroblasts with MGO, suggesting that MGO is sufficient for triggering these immunomodulatory responses. Remarkably, MIF treatment resulted in decreased activity of MGO-detoxifying glyoxalase-1. Given that reduced glyoxalase activity results in increased MGO levels, these findings suggested a positive-feedback loop for MGO generation, in which MIF, evoked by MGO, in turn blocks MGO-degrading glyoxalase activity. Finally, secretion of procollagen Type I C-Peptide (PICP), a marker of collagen production, was reduced in fibroblast from diabetic donors. Remarkably, treatment of fibroblasts with either MGO or MIF was sufficient for inducing reduced PICP levels. The observations of this study unravel a signalling network in human dermal fibroblasts with the metabolite MGO being sufficient for inflammation and delayed wound healing, hallmarks of T2D.

Modeling transcriptomic age using knowledge-primed artificial neural networks.

The development of 'age clocks', machine learning models predicting age from biological data, has been a major milestone in the search for reliable markers of biological age and has since become an invaluable tool in aging research. However, beyond their unquestionable utility, current clocks offer little insight into the molecular biological processes driving aging, and their inner workings often remain non-transparent. Here we propose a new type of age clock, one that couples predictivity with interpretability of the underlying biology, achieved through the incorporation of prior knowledge into the model design. The clock, an artificial neural network constructed according to well-described biological pathways, allows the prediction of age from gene expression data of skin tissue with high accuracy, while at the same time capturing and revealing aging states of the pathways driving the prediction. The model recapitulates known associations of aging gene knockdowns in simulation experiments and demonstrates its utility in deciphering the main pathways by which accelerated aging conditions such as Hutchinson-Gilford progeria syndrome, as well as pro-longevity interventions like caloric restriction, exert their effects.

A method to analyze the influence of mechanical strain on dermal collagen morphologies.

Collagen fibers and their orientation play a major role in the mechanical behavior of soft biological tissue such as skin. Here, we present a proof-of-principle study correlating mechanical properties with collagen fiber network morphologies. A dedicated multiphoton stretching device allows for mechanical deformations in combination with a simultaneous analysis of its collagen fiber network by second harmonic generation imaging (SHG). The recently introduced Fiber Image Network Evaluation (FINE) algorithm is used to obtain detailed information about the morphology with regard to fiber families in collagen network images. To demonstrate the potential of our method, we investigate an isotropic and an anisotropic ex-vivo dorsal pig skin sample under quasi-static cyclic stretching and relaxation sequences. Families of collagen fibers are found to form a partially aligned collagen network under strain. We find that the relative force uptake is accomplished in two steps. Firstly, fibers align within their fiber families and, secondly, fiber families orient in the direction of force. The maximum alignment of the collagen fiber network is found to be determined by the largest strain. Isotropic and anisotropic samples reveal a different micro structural behavior under repeated deformation leading to a similar force uptake after two stretching cycles. Our method correlates mechanical properties with morphologies in collagen fiber networks.

Single-Cell RNA Profiling of Human Skin Reveals Age-Related Loss of Dermal Sheath Cells and Their Contribution to a Juvenile Phenotype.

The dermal sheath (DS) is a population of mesenchyme-derived skin cells with emerging importance for skin homeostasis. The DS includes hair follicle dermal stem cells, which exhibit self-renewal and serve as bipotent progenitors of dermal papilla (DP) cells and DS cells. Upon aging, stem cells exhibit deficiencies in self-renewal and their number is reduced. While the DS of mice has been examined in considerable detail, our knowledge of the human DS, the pathways contributing to its self-renewal and differentiation capacity and potential paracrine effects important for tissue regeneration and aging is very limited. Using single-cell RNA sequencing of human skin biopsies from donors of different ages we have now analyzed the transcriptome of 72,048 cells, including 50,149 fibroblasts. Our results show that DS cells that exhibit stem cell characteristics were lost upon aging. We further show that HES1, COL11A1, MYL4 and CTNNB1 regulate DS stem cell characteristics. Finally, the DS secreted protein Activin A showed paracrine effects on keratinocytes and dermal fibroblasts, promoting proliferation, epidermal thickness and pro-collagen production. Our work provides a detailed description of human DS identity on the single-cell level, its loss upon aging, its stem cell characteristics and its contribution to a juvenile skin phenotype.

Concomitant DNA methylation and transcriptome signatures define epidermal responses to acute solar UV radiation.

The simultaneous analysis of different regulatory levels of biological phenomena by means of multi-omics data integration has proven an invaluable tool in modern precision medicine, yet many processes ultimately paving the way towards disease manifestation remain elusive and have not been studied in this regard. Here we investigated the early molecular events following repetitive UV irradiation of in vivo healthy human skin in depth on transcriptomic and epigenetic level. Our results provide first hints towards an immediate acquisition of epigenetic memories related to aging and cancer and demonstrate significantly correlated epigenetic and transcriptomic responses to irradiation stress. The data allowed the precise prediction of inter-individual UV sensitivity, and molecular subtyping on the integrated post-irradiation multi-omics data established the existence of three latent molecular phototypes. Importantly, further analysis suggested a form of melanin-independent DNA damage protection in subjects with higher innate UV resilience. This work establishes a high-resolution molecular landscape of the acute epidermal UV response and demonstrates the potential of integrative analyses to untangle complex and heterogeneous biological responses.

General method for classification of fiber families in fiber-reinforced materials: application to in-vivo human skin images.

Fiber structures play a major role for the function of fiber-reinforced materials such as biological tissue. An objective classification of the fiber orientations into fiber families is crucial to understand its mechanical properties. We introduce the Fiber Image Network Evaluation Algorithm (FINE algorithm) to classify and quantify the number of fiber families in scientific images. Each fiber family is characterized by an amplitude, a mean orientation, and a dispersion. A new alignment index giving the averaged fraction of aligned fibers is defined. The FINE algorithm is validated by realistic grayscale Monte-Carlo fiber images. We apply the algorithm to an in-vivo depth scan of second harmonic generation images of dermal collagen in human skin. The derived alignment index exhibits a crossover at a critical depth where two fiber families with a perpendicular orientation around the main tension line arise. This strongly suggests the presence of a transition from the papillary to the reticular dermis. Hence, the FINE algorithm provides a valuable tool for a reliable classification and a meaningful interpretation of in-vivo collagen fiber networks and general fiber reinforced materials.

Multi-omics network analysis reveals distinct stages in the human aging progression in epidermal tissue.

In recent years, reports of non-linear regulations in age- and longevity-associated biological processes have been accumulating. Inspired by methodological advances in precision medicine involving the integrative analysis of multi-omics data, we sought to investigate the potential of multi-omics integration to identify distinct stages in the aging progression from ex vivo human skin tissue. For this we generated transcriptome and methylome profiling data from suction blister lesions of female subjects between 21 and 76 years, which were integrated using a network fusion approach. Unsupervised cluster analysis on the combined network identified four distinct subgroupings exhibiting a significant age-association. As indicated by DNAm age analysis and Hallmark of Aging enrichment signals, the stages captured the biological aging state more clearly than a mere grouping by chronological age and could further be recovered in a longitudinal validation cohort with high stability. Characterization of the biological processes driving the phases using machine learning enabled a data-driven reconstruction of the order of Hallmark of Aging manifestation. Finally, we investigated non-linearities in the mid-life aging progression captured by the aging phases and identified a far-reaching non-linear increase in transcriptional noise in the pathway landscape in the transition from mid- to late-life.

Noise reduction and quantification of fiber orientations in greyscale images.

Quantification of the angular orientation distribution of fibrous tissue structures in scientific images benefits from the Fourier image analysis to obtain quantitative information. Measurement uncertainties represent a major challenge and need to be considered by propagating them in order to determine an adaptive anisotropic Fourier filter. Our adaptive filter method (AF) is based on the maximum relative uncertainty δcut of the power spectrum as well as a weighted radial sum with weighting factor α. We use a Monte-Carlo simulation to obtain realistic greyscale images that include defined variations in fiber thickness, length, and angular dispersion as well as variations in noise. From this simulation the best agreement between predefined and derived angular orientation distribution is found for evaluation parameters δcut = 2.1% and α = 1.5. The resulting cumulative orientation distribution was modeled by a sigmoid function to obtain the mean angle and the fiber dispersion. A comparison to a state-of-the-art band-pass method revealed that the AF method is more suitable for the application on greyscale fiber images, since the error of the fiber dispersion significantly decreased from (33.9 ± 26.5)% to (13.2 ± 12.7)%. Both methods were found to accurately quantify the mean fiber orientation with an error of (1.9 ± 1.5)° and (2.3 ± 2.1)° in case of the AF and the band-pass method, respectively. We demonstrate that the AF method is able to accurately quantify the fiber orientation distribution in in vivo second-harmonic generation images of dermal collagen with a mean fiber orientation error of (6.0 ± 4.0)° and a dispersion error of (9.3 ± 12.1)%.

Mitochondrial Morphologies Driven by Energy-Consuming Cell Sites in a Spatially and Time-Resolved Quality Model.

Mitochondria are the energy plants of eukaryotic cells. Mitochondrial network morphologies are essential for the energy supply of eukaryotic cells. However, the associated dynamics are not yet fully understood. They behave as a dynamic network that adapts to the cell's environment and its energetic needs. Various processes such as mitochondrial fission and fusion, mitochondrial recycling, repair mechanisms, and oxidative stress influence the state of the mitochondrial network. Here, we introduce a novel time-dependent and spatially resolved quality model on mitochondrial morphology. The interplay between the mitochondrial network and energy-consuming cell sites is modeled by biophysical interactions of quality-dependent mitochondrial clusters in the presence of adenosine triphosphate (ATP) consumers represented by Mie potentials. Mitochondria are modeled as simplified ballistic particles that move within the cytoplasm of a virtual cell, and connect and divide by inelastic collisions. With this model, we investigate the coupling of mitochondrial dynamics with oscillating cell functions, representing diverse global states of the energetic architecture in the cell. Our simulations based on a generalized cell reveal a perinuclear condensation of mitochondria during phases of high-energy demand. Furthermore, quality-increasing mechanisms disclose the benefits of high mitochondrial masses. Simulations reveal that varying energy demands modeled by oscillations of ATP consumers alter the morphology of the network. Phases of high-energy consumption lead to interconnected network structures and perinuclear condensation of mitochondria. The model explains quality-increasing benefits of high mitochondrial masses.

Methylation profiling identifies two subclasses of squamous cell carcinoma related to distinct cells of origin.

Cutaneous squamous cell carcinoma (cSCC) is the second most common skin cancer and usually progresses from a UV-induced precancerous lesion termed actinic keratosis (AK). Despite various efforts to characterize these lesions molecularly, the etiology of AK and its progression to cSCC remain partially understood. Here, we use Infinium MethylationEPIC BeadChips to interrogate the DNA methylation status in healthy, AK and cSCC epidermis samples. Importantly, we show that AK methylation patterns already display classical features of cancer methylomes and are highly similar to cSCC profiles. Further analysis identifies typical features of stem cell methylomes, such as reduced DNA methylation age, non-CpG methylation, and stem cell-related keratin and enhancer methylation patterns. Interestingly, this signature is detected only in half of the samples, while the other half shows patterns more closely related to healthy epidermis. These findings suggest the existence of two subclasses of AK and cSCC emerging from distinct keratinocyte differentiation stages.

Inhibition of Human Tyrosinase Requires Molecular Motifs Distinctively Different from Mushroom Tyrosinase.

Tyrosinase is the rate-limiting enzyme of melanin production and, accordingly, is the most prominent target for inhibiting hyperpigmentation. Numerous tyrosinase inhibitors have been identified, but most of those lack clinical efficacy because they were identified using mushroom tyrosinase as the target. Therefore, we used recombinant human tyrosinase to screen a library of 50,000 compounds and compared the active screening hits with well-known whitening ingredients. Hydroquinone and its derivative arbutin only weakly inhibited human tyrosinase with a half-maximal inhibitory concentration (IC50) in the millimolar range, and kojic acid showed a weak efficacy (IC50 > 500 µmol/L). The most potent inhibitors of human tyrosinase identified in this screen were resorcinyl-thiazole derivatives, especially the newly identified Thiamidol (Beiersdorf AG, Hamburg, Germany) (isobutylamido thiazolyl resorcinol), which had an IC50 of 1.1 µmol/L. In contrast, Thiamidol only weakly inhibited mushroom tyrosinase (IC50 = 108 µmol/L). In melanocyte cultures, Thiamidol strongly but reversibly inhibited melanin production (IC50 = 0.9 µmol/L), whereas hydroquinone irreversibly inhibited melanogenesis (IC50 = 16.3 µmol/L). Clinically, Thiamidol visibly reduced the appearance of age spots within 4 weeks, and after 12 weeks some age spots were indistinguishable from the normal adjacent skin. The full potential of Thiamidol to reduce hyperpigmentation of human skin needs to be explored in future studies.

Fragmentation of the mitochondrial network in skin in vivo.

Mitochondria form dynamic networks which adapt to the environmental requirements of the cell. We investigated the aging process of these networks in human skin cells in vivo by multiphoton microscopy. A study on the age-dependency of the mitochondrial network in young and old volunteers revealed that keratinocytes in old skin establish a significantly more fragmented network with smaller and more compact mitochondrial clusters than keratinocytes in young skin. Furthermore, we investigated the mitochondrial network during differentiation processes of keratinocytes within the epidermis of volunteers. We observe a fragmentation similar to the age-dependent study in almost all parameters. These parallels raise questions about the dynamics of biophysical network structures during aging processes.

An integrative metabolomics and transcriptomics study to identify metabolic alterations in aged skin of humans in vivo.

BACKGROUND: Aging human skin undergoes significant morphological and functional changes such as wrinkle formation, reduced wound healing capacity, and altered epidermal barrier function. Besides known age-related alterations like DNA-methylation changes, metabolic adaptations have been recently linked to impaired skin function in elder humans. Understanding of these metabolic adaptations in aged skin is of special interest to devise topical treatments that potentially reverse or alleviate age-dependent skin deterioration and the occurrence of skin disorders. RESULTS: We investigated the global metabolic adaptions in human skin during aging with a combined transcriptomic and metabolomic approach applied to epidermal tissue samples of young and old human volunteers. Our analysis confirmed known age-dependent metabolic alterations, e.g. reduction of coenzyme Q10 levels, and also revealed novel age effects that are seemingly important for skin maintenance. Integration of donor-matched transcriptome and metabolome data highlighted transcriptionally-driven alterations of metabolism during aging such as altered activity in upper glycolysis and glycerolipid biosynthesis or decreased protein and polyamine biosynthesis. Together, we identified several age-dependent metabolic alterations that might affect cellular signaling, epidermal barrier function, and skin structure and morphology. CONCLUSIONS: Our study provides a global resource on the metabolic adaptations and its transcriptional regulation during aging of human skin. Thus, it represents a first step towards an understanding of the impact of metabolism on impaired skin function in aged humans and therefore will potentially lead to improved treatments of age related skin disorders.

Impaired glyoxalase activity is associated with reduced expression of neurotrophic factors and pro-inflammatory processes in diabetic skin cells.

Patients suffering from type II diabetes develop several skin manifestations including cutaneous infections, diabetic dermopathy, diabetic bullae and acanthosis nigricans. Diabetic micro- and macroangiopathy as well as diabetic neuropathy are believed to play a crucial role in the development of diabetic skin disorders. A reduced cutaneous nerve fibre density was reported in diabetic subjects, which subsequently leads to impaired sensory nerve functions. Using an innervated skin model, we investigated the impact of human diabetic dermal fibroblasts and keratinocytes on porcine sensory neurons. Diabetic skin cells showed a reduced capacity to induce neurite outgrowth due to a decreased support with neurotrophic factors, such as NGF. Furthermore, diabetic keratinocytes displayed insulin resistance and increased expression of pro-inflammatory cytokines demonstrating the persistent effect of diabetes mellitus on human skin cells. Dysregulations were related to a significantly reduced glyoxalase enzyme activity in diabetic keratinocytes as experimentally reduced glyoxalase activity mimicked the increase in pro-inflammatory cytokine expression and reduction in NGF. Our results demonstrate an impaired crosstalk of diabetic skin cells and sensory neurons favouring hypo-innervation. We suggest that reduced methylglyoxal detoxification contributes to an impaired neurocutaneous interaction in diabetic skin.

Reduced DNA methylation patterning and transcriptional connectivity define human skin aging.

Epigenetic changes represent an attractive mechanism for understanding the phenotypic changes associated with human aging. Age-related changes in DNA methylation at the genome scale have been termed 'epigenetic drift', but the defining features of this phenomenon remain to be established. Human epidermis represents an excellent model for understanding age-related epigenetic changes because of its substantial cell-type homogeneity and its well-known age-related phenotype. We have now generated and analyzed the currently largest set of human epidermis methylomes (N = 108) using array-based profiling of 450 000 methylation marks in various age groups. Data analysis confirmed that age-related methylation differences are locally restricted and characterized by relatively small effect sizes. Nevertheless, methylation data could be used to predict the chronological age of sample donors with high accuracy. We also identified discontinuous methylation changes as a novel feature of the aging methylome. Finally, our analysis uncovered an age-related erosion of DNA methylation patterns that is characterized by a reduced dynamic range and increased heterogeneity of global methylation patterns. These changes in methylation variability were accompanied by a reduced connectivity of transcriptional networks. Our findings thus define the loss of epigenetic regulatory fidelity as a key feature of the aging epigenome.

Quality Saving Mechanisms of Mitochondria during Aging in a Fully Time-Dependent Computational Biophysical Model.

Mitochondria are essential for the energy production of eukaryotic cells. During aging mitochondria run through various processes which change their quality in terms of activity, health and metabolic supply. In recent years, many of these processes such as fission and fusion of mitochondria, mitophagy, mitochondrial biogenesis and energy consumption have been subject of research. Based on numerous experimental insights, it was possible to qualify mitochondrial behaviour in computational simulations. Here, we present a new biophysical model based on the approach of Figge et al. in 2012. We introduce exponential decay and growth laws for each mitochondrial process to derive its time-dependent probability during the aging of cells. All mitochondrial processes of the original model are mathematically and biophysically redefined and additional processes are implemented: Mitochondrial fission and fusion is separated into a metabolic outer-membrane part and a protein-related inner-membrane part, a quality-dependent threshold for mitophagy and mitochondrial biogenesis is introduced and processes for activity-dependent internal oxidative stress as well as mitochondrial repair mechanisms are newly included. Our findings reveal a decrease of mitochondrial quality and a fragmentation of the mitochondrial network during aging. Additionally, the model discloses a quality increasing mechanism due to the interplay of the mitophagy and biogenesis cycle and the fission and fusion cycle of mitochondria. It is revealed that decreased mitochondrial repair can be a quality saving process in aged cells. Furthermore, the model finds strategies to sustain the quality of the mitochondrial network in cells with high production rates of reactive oxygen species due to large energy demands. Hence, the model adds new insights to biophysical mechanisms of mitochondrial aging and provides novel understandings of the interdependency of mitochondrial processes.