Derivation of marker gene signatures from human skin and their use in the interpretation of the transcriptional changes associated with dermatological disorders

Microbe-Host Interaction in Rosacea and its Modulation Through Topical Ivermectin

Rosacea is characterized by inflammatory lesions, often accompanied by an increased density of the common skin mite Demodex folliculorum. Although rosacea shows a high prevalence and significantly affects the quality of life of patients, the underlying mechanisms, especially the role of cutaneous dysbiosis are largely unknown. Hence, we aimed to systematically characterize disease severity of rosacea patients in the context of mite density, the cutaneous microbiome and the host's transcriptome before and after 30 days of topical 1% ivermectin cream treatment. At day 30, a marked decrease in mite density was observed in 87.5% of patients. At day 0, distinct microbial community changes included the decrease in Cutibacterium acnes abundance, while Staphylococcus epidermidis colonization increased when compared to healthy volunteers. Interestingly, the insect symbiont Snodgrassella alvi was recovered from a highly Demodex-colonized patient and eradicated by day 30 of treatment. Although topical ivermectin did not affect bacterial dysbiosis, the host's transcriptome significantly normalized and an "ivermectin transcriptomic signature" was defined. Findings of the present study support that rosacea lesions are associated with dysbiosis. However, improvement of clinical signs during topical ivermectin is not associated with normalization of the bacterial microbiome, but rather a decrease of transcriptomic dysregulation and mite density.

Non-IgE-reactive allergen peptides deteriorate the skin barrier in house dust mite-sensitized atopic dermatitis patients

Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by type 2 cytokine-driven skin inflammation and epithelial barrier dysfunction. The latter is believed to allow the increased penetration of chemicals, toxins, and allergens into the skin. House dust mite allergens, particularly Der p 2, are important triggers in sensitized individuals with AD; the precise actions of these allergens in epithelial biology remain, however, incompletely understood. In this study, we compared the effects of the protein allergen Der p 2 and a mix of non-IgE-reactive Der p 2 peptides on skin cells using patch tests in AD patients and healthy participants. We then analyzed mRNA expression profiles of keratinocytes by single-cell RNA-sequencing. We report that existing barrier deficiencies in the non-lesional skin of AD patients allow deep penetration of Der p 2 and its peptides, leading to local microinflammation. Der p 2 protein specifically upregulated genes involved in the innate immune system, stress, and danger signals in suprabasal KC. Der p 2 peptides further downregulated skin barrier genes, in particular the expression of genes involved in cell-matrix and cell-cell adhesion. Peptides also induced genes involved in hyperproliferation and caused disturbances in keratinocyte differentiation. Furthermore, inflammasome-relevant genes and IL18 were overexpressed, while KRT1 was downregulated. Our data suggest that Der p 2 peptides contribute to AD initiation and exacerbation by augmenting hallmark features of AD, such as skin inflammation, barrier disruption, and hyperplasia of keratinocytes.

Cutaneous lesions in psoriatic arthritis are enriched in chemokine transcriptomic pathways

OBJECTIVES

Skin from people with psoriasis has been extensively studied and is assumed to be identical to skin from those with psoriatic arthritis (PsA). Chemokines and the CC chemokine scavenger receptor ACKR2 are upregulated in uninvolved psoriasis. ACKR2 has been proposed as a regulator of cutaneous inflammation in psoriasis. The aim of this study was to compare the transcriptome of PsA skin to healthy control (HC) skin and evaluate ACKR2 expression in PsA skin.

METHODS

Full-thickness skin biopsies from HC, lesional and uninvolved skin from participants with PsA were sequenced on NovaSeq 6000. Findings were validated using qPCR and RNAscope.

RESULTS

Nine HC and nine paired PsA skin samples were sequenced. PsA uninvolved skin was transcriptionally similar to HC skin, and lesional PsA skin was enriched in epidermal and inflammatory genes. Lesional PsA skin was enriched in chemokine-mediated signalling pathways, but uninvolved skin was not. ACKR2 was upregulated in lesional PsA skin but had unchanged expression in uninvolved compared with HC skin. The expression of ACKR2 was confirmed by qPCR, and RNAscope demonstrated strong expression of ACKR2 in the suprabasal layer of the epidermis in PsA lesions.

CONCLUSION

Chemokines and their receptors are upregulated in lesional PsA skin but relatively unchanged in uninvolved PsA skin. In contrast to previous psoriasis studies, ACKR2 was not upregulated in uninvolved PsA skin. Further understanding of the chemokine system in PsA may help to explain why inflammation spreads from the skin to the joints in some people with psoriasis.

A systems biology approach to better understand human tick-borne diseases

Tick-borne diseases (TBDs) are a growing global health concern. Despite extensive studies, ill-defined tick-associated pathologies remain with unknown aetiologies. Human immunological responses after tick bite, and inter-individual variations of immune-response phenotypes, are not well characterised. Current reductive experimental methodologies limit our understanding of more complex tick-associated illness, which results from the interactions between the host, tick, and microbes. An unbiased, systems-level integration of clinical metadata and biological host data - obtained via transcriptomics, proteomics, and metabolomics - offers to drive the data-informed generation of testable hypotheses in TBDs. Advanced computational tools have rendered meaningful analysis of such large data sets feasible. This review highlights the advantages of integrative system biology approaches as essential for understanding the complex pathobiology of TBDs.

The Spatial Landscape of Progression and Immunoediting in Primary Melanoma at Single-Cell Resolution

Cutaneous melanoma is a highly immunogenic malignancy that is surgically curable at early stages but life-threatening when metastatic. Here we integrate high-plex imaging, 3D high-resolution microscopy, and spatially resolved microregion transcriptomics to study immune evasion and immunoediting in primary melanoma. We find that recurrent cellular neighborhoods involving tumor, immune, and stromal cells change significantly along a progression axis involving precursor states, melanoma in situ, and invasive tumor. Hallmarks of immunosuppression are already detectable in precursor regions. When tumors become locally invasive, a consolidated and spatially restricted suppressive environment forms along the tumor-stromal boundary. This environment is established by cytokine gradients that promote expression of MHC-II and IDO1, and by PD1-PDL1-mediated cell contacts involving macrophages, dendritic cells, and T cells. A few millimeters away, cytotoxic T cells synapse with melanoma cells in fields of tumor regression. Thus, invasion and immunoediting can coexist within a few millimeters of each other in a single specimen.

SIGNIFICANCE

The reorganization of the tumor ecosystem in primary melanoma is an excellent setting in which to study immunoediting and immune evasion. Guided by classic histopathology, spatial profiling of proteins and mRNA reveals recurrent morphologic and molecular features of tumor evolution that involve localized paracrine cytokine signaling and direct cell-cell contact. This article is highlighted in the In This Issue feature, p. 1397.

Aging-Related Impairments to M Cells in Peyer's Patches Coincide With Disturbances to Paneth Cells

The decline in mucosal immunity during aging increases susceptibility, morbidity and mortality to infections acquired via the gastrointestinal and respiratory tracts in the elderly. We previously showed that this immunosenescence includes a reduction in the functional maturation of M cells in the follicle-associated epithelia (FAE) covering the Peyer’s patches, diminishing the ability to sample of antigens and pathogens from the gut lumen. Here, co-expression analysis of mRNA-seq data sets revealed a general down-regulation of most FAE- and M cell-related genes in Peyer’s patches from aged mice, including key transcription factors known to be essential for M cell differentiation. Conversely, expression of ACE2, the cellular receptor for SARS-Cov-2 virus, was increased in the aged FAE. This raises the possibility that the susceptibility of aged Peyer’s patches to infection with the SARS-Cov-2 virus is increased. Expression of key Paneth cell-related genes was also reduced in the ileum of aged mice, consistent with the adverse effects of aging on their function. However, the increased expression of these genes in the villous epithelium of aged mice suggested a disturbed distribution of Paneth cells in the aged intestine. Aging effects on Paneth cells negatively impact on the regenerative ability of the gut epithelium and could indirectly impede M cell differentiation. Thus, restoring Paneth cell function may represent a novel means to improve M cell differentiation in the aging intestine and increase mucosal vaccination efficacy in the elderly.

Rapid Noninvasive Skin Monitoring by Surface Mass Recording and Data Learning

Skin problems are often overlooked due to a lack of robust and patient-friendly monitoring tools. Herein, we report a rapid, noninvasive, and high-throughput analytical chemical methodology, aiming at real-time monitoring of skin conditions and early detection of skin disorders. Within this methodology, adhesive sampling and laser desorption ionization mass spectrometry are coordinated to record skin surface molecular mass in minutes. Automated result interpretation is achieved by data learning, using similarity scoring and machine learning algorithms. Feasibility of the methodology has been demonstrated after testing a total of 117 healthy, benign-disordered, or malignant-disordered skins. Remarkably, skin malignancy, using melanoma as a proof of concept, was detected with 100% accuracy already at early stages when the lesions were submillimeter-sized, far beyond the detection limit of most existing noninvasive diagnosis tools. Moreover, the malignancy development over time has also been monitored successfully, showing the potential to predict skin disorder progression. Capable of detecting skin alterations at the molecular level in a nonsurgical and time-saving manner, this analytical chemistry platform is promising to build personalized skin care.

Single cell transcriptional zonation of human psoriasis skin identifies an alternative immunoregulatory axis conducted by skin resident cells

Psoriasis is the most common skin disease in adults. Current experimental and clinical evidences suggested the infiltrating immune cells could target local skin cells and thus induce psoriatic phenotype. However, recent studies indicated the existence of a potential feedback signaling loop from local resident skin cells to infiltrating immune cells. Here, we deconstructed the full-thickness human skins of both healthy donors and patients with psoriasis vulgaris at single cell transcriptional level, and further built a neural-network classifier to evaluate the evolutional conservation of skin cell types between mouse and human. Last, we systematically evaluated the intrinsic and intercellular molecular alterations of each cell type between healthy and psoriatic skin. Cross-checking with psoriasis susceptibility gene loci, cell-type based differential expression, and ligand-receptor communication revealed that the resident psoriatic skin cells including mesenchymal and epidermis cell types, which specifically harbored the target genes of psoriasis susceptibility loci, intensively evoked the expression of major histocompatibility complex (MHC) genes, upregulated interferon (INF), tumor necrosis factor (TNF) signalling and increased cytokine gene expression for primarily aiming the neighboring dendritic cells in psoriasis. The comprehensive exploration and pathological observation of psoriasis patient biopsies proposed an uncovered immunoregulatory axis from skin local resident cells to immune cells, thus provided a novel insight for psoriasis treatment. In addition, we published a user-friendly website to exhibit the transcriptional change of each cell type between healthy and psoriatic human skin.

The transcriptional signature associated with human motile cilia

Cilia are complex microtubule-based organelles essential to a range of processes associated with embryogenesis and tissue homeostasis. Mutations in components of these organelles or those involved in their assembly may result in a diverse set of diseases collectively known as ciliopathies. Accordingly, many cilia-associated proteins have been described, while those distinguishing cilia subtypes are poorly defined. Here we set out to define genes associated with motile cilia in humans based on their transcriptional signature. To define the signature, we performed network deconvolution of transcriptomics data derived from tissues possessing motile ciliated cell populations. For each tissue, genes coexpressed with the motile cilia-associated transcriptional factor, FOXJ1, were identified. The consensus across tissues provided a transcriptional signature of 248 genes. To validate these, we examined the literature, databases (CilDB, CentrosomeDB, CiliaCarta and SysCilia), single cell RNA-Seq data, and the localisation of mRNA and proteins in motile ciliated cells. In the case of six poorly characterised signature genes, we performed new localisation experiments on ARMC3, EFCAB6, FAM183A, MYCBPAP, RIBC2 and VWA3A. In summary, we report a set of motile cilia-associated genes that helps shape our understanding of these complex cellular organelles.

Characterization of disease-specific cellular abundance profiles of chronic inflammatory skin conditions from deconvolution of biopsy samples

BACKGROUND

Psoriasis and atopic dermatitis are two inflammatory skin diseases with a high prevalence and a significant burden on the patients. Underlying molecular mechanisms include chronic inflammation and abnormal proliferation. However, the cell types contributing to these molecular mechanisms are much less understood. Recently, deconvolution methodologies have allowed the digital quantification of cell types in bulk tissue based on mRNA expression data from biopsies. Using these methods to study the cellular composition of the skin enables the rapid enumeration of multiple cell types, providing insight into the numerical changes of cell types associated with chronic inflammatory skin conditions. Here, we use deconvolution to enumerate the cellular composition of the skin and estimate changes related to onset, progress, and treatment of these skin diseases.

METHODS

A novel signature matrix, i.e. DerM22, containing expression data from 22 reference cell types, is used, in combination with the CIBERSORT algorithm, to identify and quantify the cellular subsets within whole skin biopsy samples. We apply the approach to public microarray mRNA expression data from the skin layers and 648 samples from healthy subjects and patients with psoriasis or atopic dermatitis. The methodology is validated by comparison to experimental results from flow cytometry and immunohistochemistry studies, and the deconvolution of independent data from isolated cell types.

RESULTS

We derived the relative abundance of cell types from healthy, lesional, and non-lesional skin and observed a marked increase in the abundance of keratinocytes and leukocytes in the lesions of both inflammatory dermatological conditions. The relative fraction of these cells varied from healthy to diseased skin and from non-lesional to lesional skin. We show that changes in the relative abundance of skin-related cell types can be used to distinguish between mild and severe cases of psoriasis and atopic dermatitis, and trace the effect of treatment.

CONCLUSIONS

Our analysis demonstrates the value of this new resource in interpreting skin-derived transcriptomics data by enabling the direct quantification of cell types in a skin sample and the characterization of pathological changes in tissue composition.

A core transcriptional signature of human microglia: Derivation and utility in describing region-dependent alterations associated with Alzheimer's disease

Growing recognition of the pivotal role microglia play in neurodegenerative and neuroinflammatory disorders has accentuated the need to characterize their function in health and disease. Studies in mouse have applied transcriptome-wide profiling of microglia to reveal key features of microglial ontogeny, functional profile, and phenotypic diversity. While similar, human microglia exhibit clear differences to their mouse counterparts, underlining the need to develop a better understanding of the human microglial profile. On examining published microglia gene signatures, limited consistency was observed between studies. Hence, we sought to derive a core microglia signature of the human central nervous system (CNS), through a comprehensive analysis of existing transcriptomic datasets. Nine datasets derived from cells and tissues, isolated from various regions of the CNS across numerous donors, were subjected independently to an unbiased correlation network analysis. From each dataset, a list of coexpressing genes corresponding to microglia was identified, with 249 genes highly conserved between them. This core signature included known microglial markers, and compared with other signatures provides a gene set specific to microglia in the context of the CNS. The utility of this signature was demonstrated by its use in detecting qualitative and quantitative region-specific alterations in aging and Alzheimer's disease. These analyses highlighted the reactive response of microglia in vulnerable brain regions such as the entorhinal cortex and hippocampus, additionally implicating pathways associated with disease progression. We believe this resource and the analyses described here, will support further investigations to the contribution of human microglia in CNS health and disease.

Immune Cell Gene Signatures for Profiling the Microenvironment of Solid Tumors

The immune composition of the tumor microenvironment regulates processes including angiogenesis, metastasis, and the response to drugs or immunotherapy. To facilitate the characterization of the immune component of tumors from transcriptomics data, a number of immune cell transcriptome signatures have been reported that are made up of lists of marker genes indicative of the presence a given immune cell population. The majority of these gene signatures have been defined through analysis of isolated blood cells. However, blood cells do not reflect the differentiation or activation state of similar cells within tissues, including tumors, and consequently markers derived from blood cells do not necessarily transfer well to tissues. To address this issue, we generated a set of immune gene signatures derived directly from tissue transcriptomics data using a network-based deconvolution approach. We define markers for seven immune cell types, collectively named ImSig, and demonstrate how these markers can be used for the quantitative estimation of the immune cell content of tumor and nontumor tissue samples. The utility of ImSig is demonstrated through the stratification of melanoma patients into subgroups of prognostic significance and the identification of immune cells with the use of single-cell RNA-sequencing data derived from tumors. Use of ImSig is facilitated by an R package (imsig). Cancer Immunol Res; 6(11); 1388-400. ©2018 AACR.

Plausibility of the zebrafish embryos/larvae as an alternative animal model for autism: A comparison study of transcriptome changes

Autism spectrum disorder (ASD) is a serious neurodevelopmental disorder characterized by impaired or abnormal social interaction and communication and by restricted and repetitive behaviour. ASD is highly prevalent in Asia, Europe, and the United States, and the frequency of ASD is growing each year. Recent epidemiological studies have indicated that ASD may be caused or triggered by exposure to chemicals in the environment, such as those in the air or water. Thus, toxicological studies are needed to examine chemicals that might be implicated. However, the experimental efficiency of existing experimental models is limited, and many models represent challenges in terms of animal welfare. Thus, alternative ASD animal models are necessary. To address this, we examined the efficacy of the zebrafish embryo/larva as an alternative model of ASD. Specifically, we exposed zebrafish to valproic acid (0, 12.5, 25, 50, or 100 μM), which is a chemical known to induce autism-like effects. We then analysed subsequent developmental, behavioural, and transcriptomic changes. We found that 100 μM and 50 μM valproic acid decreased the hatching rate and locomotor activity of zebrafish embryos/larvae. Transcriptomic analysis revealed significant alterations in a number of genes associated with autism, such as adsl, mbd5, shank3, and tsc1b. Additionally, we found changes in gene ontology that were also reported in previous studies. Our findings indicate that zebrafish embryos/larvae and humans with ASD might have common physiological pathways, indicating that this animal model may represent an alternative tool for examining the causes of and potential treatments for this illness.

SaVanT: a web-based tool for the sample-level visualization of molecular signatures in gene expression profiles

Background

Molecular signatures are collections of genes characteristic of a particular cell type, tissue, disease, or perturbation. Signatures can also be used to interpret expression profiles generated from heterogeneous samples. Large collections of gene signatures have been previously developed and catalogued in the MSigDB database. In addition, several consortia and large-scale projects have systematically profiled broad collections of purified primary cells, molecular perturbations of cell types, and tissues from specific diseases, and the specificity and breadth of these datasets can be leveraged to create additional molecular signatures. However, to date there are few tools that allow the visualization of individual signatures across large numbers of expression profiles. Signature visualization of individual samples allows, for example, the identification of patient subcategories a priori on the basis of well-defined molecular signatures.

Result

Here, we generate and compile 10,985 signatures (636 newly-generated and 10,349 previously available from MSigDB) and provide a web-based Signature Visualization Tool (SaVanT; http://newpathways.mcdb.ucla.edu/savant), to visualize these signatures in user-generated expression data. We show that using SaVanT, immune activation signatures can distinguish patients with different types of acute infections (influenza A and bacterial pneumonia). Furthermore, SaVanT is able to identify the prominent signatures within each patient group, and identify the primary cell types underlying different leukemias (acute myeloid and acute lymphoblastic) and skin disorders.

Conclusions

The development of SaVanT facilitates large-scale analysis of gene expression profiles on a patient-level basis to identify patient subphenotypes, or potential therapeutic target pathways.

Electronic supplementary material

The online version of this article (10.1186/s12864-017-4167-7) contains supplementary material, which is available to authorized users.