Single-cell RNA sequencing reveals 2D cytokine assay can model atopic dermatitis more accurately than immune-competent 3D setup.

Modelling atopic dermatitis (AD) in vitro is paramount to understand the disease pathophysiology and identify novel treatments. Previous studies have shown that the Th2 cytokines IL-4 and IL-13 induce AD-like features in keratinocytes in vitro. However, it has not been systematically researched whether the addition of Th2 cells, their supernatants or a 3D structure is superior to model AD compared to simple 2D cell culture with cytokines. For the first time, we investigated what in vitro option most closely resembles the disease in vivo based on single-cell RNA sequencing data (scRNA-seq) obtained from skin biopsies in a clinical study and published datasets of healthy and AD donors. In vitro models were generated with primary fibroblasts and keratinocytes, subjected to cytokine treatment or Th2 cell cocultures in 2D/3D. Gene expression changes were assessed using qPCR and Multiplex Immunoassays. Of all cytokines tested, incubation of keratinocytes and fibroblasts with IL-4 and IL-13 induced the closest in vivo-like AD phenotype which was observed in the scRNA-seq data. Addition of Th2 cells to fibroblasts failed to model AD due to the downregulation of ECM-associated genes such as POSTN. While keratinocytes cultured in 3D showed better stratification than in 2D, changes induced with AD triggers did not better resemble AD keratinocyte subtypes observed in vivo. Taken together, our comprehensive study shows that the simple model using IL-4 or IL-13 in 2D most accurately models AD in fibroblasts and keratinocytes in vitro, which may aid the discovery of novel treatment options.

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 promiscuous ancestral enzyme´s structure unveils protein variable regions of the highly diverse metallo-ß-lactamase family.

The metallo-ß-lactamase fold is an ancient protein structure present in numerous enzyme families responsible for diverse biological processes. The crystal structure of the hyperthermostable crenarchaeal enzyme Igni18 from Ignicoccus hospitalis was solved at 2.3 Å and could resemble a possible first archetype of a multifunctional metallo-ß-lactamase. Ancestral enzymes at the evolutionary origin are believed to be promiscuous all-rounders. Consistently, Igni18´s activity can be cofactor-dependently directed from ß-lactamase to lactonase, lipase, phosphodiesterase, phosphotriesterase or phospholipase. Its core-domain is highly conserved within metallo-ß-lactamases from Bacteria, Archaea and Eukarya and gives insights into evolution and function of enzymes from this superfamily. Structural alignments with diverse metallo-ß-lactamase-fold-containing enzymes allowed the identification of Protein Variable Regions accounting for modulation of activity, specificity and oligomerization patterns. Docking of different substrates within the active sites revealed the basis for the crucial cofactor dependency of this enzyme superfamily.

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.

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.

Microbial metaproteome data from decayed beech dead wood.

Wood-decomposition in terrestrial ecosystems is a very important process with huge ecologic consequences. This decomposition process is a combination of biological respiration, leaching and fragmentation, mainly triggered by organismic activities. In order to gain a deeper insight into these microbial communities and their role in deadwood decay, we used metaproteomics. Metaproteomics is an important tool and offers the ability to characterize the protein complement of environmental microbiota at a given point in time. In this dataset, we provide data of an exemplary beech wood log and applied different extraction methods to provide the proteome profile of beech dead wood and their corresponding fungal-bacterial community.

Igni18, a novel metallo-hydrolase from the hyperthermophilic archaeon Ignicoccus hospitalis KIN4/I: cloning, expression, purification and X-ray analysis.

The hyperthermophilic crenarchaeon Ignicoccus hospitalis KIN4/I possesses at least 35 putative genes encoding enzymes that belong to the α/ß-hydrolase superfamily. One of those genes, the metallo-hydrolase-encoding igni18, was cloned and heterologously expressed in Pichia pastoris. The enzyme produced was purified in its catalytically active form. The recombinant enzyme was successfully crystallized and the crystal diffracted to a resolution of 2.3 Å. The crystal belonged to space group R32, with unit-cell parameters a = b = 67.42, c = 253.77 Å, α = ß = 90.0, γ = 120.0°. It is suggested that it contains one monomer of Igni18 within the asymmetric unit.