Gene expression analysis of skin grafts and cultured keratinocytes using synthetic RNA normalization reveals insights into differentiation and growth control

Katayama, Shintaro; Skoog, Tiina; Jouhilahti, Eeva-Mari; Siitonen, H. Annika; Nuutila, Kristo; Tervaniemi, Mari H.; Vuola, Jyrki; Johnsson, Anna; Lönnerberg, Peter; Linnarsson, Sten; Elomaa, Outi; Kankuri, Esko; Kere, Juha

doi:10.1186/s12864-015-1671-5

Cited by 23 publications

(31 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Certain genes, such as LOR (a skin development gene), were upregulated only in SC1, in agreement with research that classifies positive LOR expression as a key developmental marker of healthy skin . In comparison to another cultured keratinocyte‐only HSE model, SC1 had several overlapping genes (including KRT71 , and several similar gene classes between both datasets including C#orf# genes, TRIM# , and LOC# genes), but numerous others which were not mentioned in that analysis . It would be difficult to directly compare these models, as many components are different: SC1 is a 3D HSE with a dermis composed of a silk‐collagen hydrogel material, and also contains dermal fibroblasts, which could influence the RNASeq results.…”

Section: Discussionsupporting

confidence: 68%

Human Skin Equivalents Demonstrate Need for Neuro‐Immuno‐Cutaneous System

et al. 2018

View full text Add to dashboard Cite

There is interest in the neurological and immune components in skin, but most studies only focus on one system at a time, not both. [1,4,16] The in vitro HSE system described herein is a multilayered, full thickness skin model, containing only primary human cells, including human induced neural stem cells (hiNSCs), and tissue-inherent immune cells from lipoaspirate utilized in the hypodermis. [6] In order to compare the effect of the tissue components (i.e., hiNSCs, hypodermis, and the dermis/ epidermis), a parametric study was performed of the system in vitro. Through RNA Sequencing (RNASeq) and protein analysis it was determined that each sample group (dermis/epidermis alone, dermis/epidermis + hiNSCs, etc.) was distinct in terms of functions, gene expression profiles, and enriched biological pathways. Each sample group expressed genes related to several phenomena key to skin biology, including skin development, neuronal system development, inflammation, and immune system process.Through RNASeq, numerous genes were up-or downregulated in a distinct manner with respect to the specific HSE study group (i.e., each HSE group had distinct gene expression) that would not have been possible to identify as quickly or thoroughly by other techniques such as real-time reverse transcriptase polymerase chain reaction (qRT-PCR) or microarrays due to lower sensitivity and throughput. [17,18] Further, RNASeq allowed the identification of genes which may be important for development of an in vitro HSE model, and which were different with the study groups that contained neural or immune components. In comparison to the RNASeq results from less complex skin models (such as a keratinocyte model), the tissue models described herein identified more genes, likely due to the addition of important cell types of the skin including adipose, neural, and immune components. We speculate that such additional complexity and readouts could be useful for studies related to in vitro studies, such as insight into diseases like psoriasis. [19] The skin is a highly organized and complex organ that maintains homeostasis. The neuro-immuno-cutaneous system refers to one of the interconnected systems of the skin, in which neural, immune, and dermal cells, including neuropeptides and cytokines, are in bidirectional communication with A variety of human skin equivalents (HSEs) has been designed for clinical use or for exploratory skin research. In vitro HSE models have been used to target relationships between the skin and nervous or immune systems but have not yet considered the neuro-immuno-cutaneous (NIC) system. In this study, HSEs are described, with and without neural and immune components, to discern these types of effects. These systems are composed of only primary human cells and contain an epidermis, dermis, hypodermis (with immune cells), and human induced neural stem cells for the neuronal component. RNA sequencing is utilized to confirm differences between sample groups and to identify unique or important genes with respect to sample type. O...

show abstract

Section: Discussionsupporting

confidence: 68%

Human Skin Equivalents Demonstrate Need for Neuro‐Immuno‐Cutaneous System

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Cells were then filtered based on different quality parameters calculated for each dataset (Supplementary Figure 2, Supplementary Table 2) Additionally, the output of TraCeR (Stubbington et al 2016) was used to remove cells without a detected TCR sequence, as well as iNKT and γ ∂ T cells (defined as cells with at least one γ and one ∂ chain detected and no αβ pair). Two mouse steady-state skin Treg from the Mouse Melanoma dataset were also removed from posterior analysis because, even though they had reconstructed TCR and expression of expected T cell genes, they also presented transcripts expected to appear in other cell types, possibly keratinocytes or Langerhans cells (Katayama et al 2015;Heng, Painter, and Immunological Genome Project Consortium 2008) (Supplementary Figure 16D).…”

Section: Scrna-seq Quality Controlmentioning

confidence: 99%

Single cell transcriptomics of regulatory T cells reveals trajectories of tissue adaptation

Miragaia

Gomes

Chomka

et al. 2017

Preprint

152

View full text Add to dashboard Cite

SummaryNon-lymphoid tissues (NLTs) harbour a pool of adaptive immune cells, the development and phenotype of which remains largely unexplored. Here, we used single-cell RNA-seq to characterise CD4 + regulatory (Treg) and memory (Tmem) T cells in mouse skin and colon, the respective draining lymph nodes and spleen. From this data, we modelled a continuous lymphoid-to-NLT trajectory for Treg, and reconstructed the mechanisms of cell migration and NLT adaption. This revealed a shared transcriptional programme of NLT priming in both skin and colon-associated lymph nodes, followed by tissue-specific adaptation. Predicted migration kinetics were validated using a melanoma-induction model, emphasizing the relevance of key regulators and receptors, including Batf, Rora, Ccr8, Samsn1 . Finally, we profiled human blood and NLT Treg and Tmem cells, identifying cross-mammalian conserved tissue signatures. In summary, we have identified molecular signals mediating 1 . CC-BY 4.0 International license not peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was . http://dx.doi.org/10.1101/217489 doi: bioRxiv preprint first posted online Nov. 22, 2017; NLT Treg recruitment and tissue adaptation through the combined use of computational prediction and in vivo validation.

show abstract

“…We collected samples from the psoriatic lesional and non-lesional skin from patients and healthy skin from controls. We also employed data normalization with synthetic spike-in RNA, which enables more accurate comparison of gene expression in heterogeneous samples where total mRNA levels per cell may be highly different 10 11 12 . Our results show the power of RNAseq over the microarray studies, providing a more comprehensive view of altered signaling pathways both in non-lesional and lesional psoriatic skin.…”

mentioning

confidence: 99%

NOD-like receptor signaling and inflammasome-related pathways are highlighted in psoriatic epidermis

Tervaniemi

Katayama

Skoog

et al. 2016

Sci Rep

Self Cite

View full text Add to dashboard Cite

Psoriatic skin differs distinctly from normal skin by its thickened epidermis. Most gene expression comparisons utilize full-thickness biopsies, with substantial amount of dermis. We assayed the transcriptomes of normal, lesional, and non-lesional psoriatic epidermis, sampled as split-thickness skin grafts, with 5′-end RNA sequencing. We found that psoriatic epidermis contains more mRNA per total RNA than controls, and took this into account in the bioinformatic analysis. The approach highlighted innate immunity-related pathways in psoriasis, including NOD-like receptor (NLR) signaling and inflammasome activation. We demonstrated that the NLR signaling genes NOD2, PYCARD, CARD6, and IFI16 are upregulated in psoriatic epidermis, and strengthened these findings by protein expression. Interestingly, PYCARD, the key component of the inflammasome, showed an altered expression pattern in the lesional epidermis. The profiling of non-lesional skin highlighted PSORS4 and mitochondrially encoded transcripts, suggesting that their gene expression is altered already before the development of lesions. Our data suggest that all components needed for the active inflammasome are present in the keratinocytes of psoriatic skin. The characterization of inflammasome pathways provides further opportunities for therapy. Complementing previous transcriptome studies, our approach gives deeper insight into the gene regulation in psoriatic epidermis.

show abstract

Gene expression analysis of skin grafts and cultured keratinocytes using synthetic RNA normalization reveals insights into differentiation and growth control

Cited by 23 publications

References 49 publications

Human Skin Equivalents Demonstrate Need for Neuro‐Immuno‐Cutaneous System

Human Skin Equivalents Demonstrate Need for Neuro‐Immuno‐Cutaneous System

Single cell transcriptomics of regulatory T cells reveals trajectories of tissue adaptation

NOD-like receptor signaling and inflammasome-related pathways are highlighted in psoriatic epidermis

Contact Info

Product

Resources

About