Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Prediction, screening and characterisation of novel bioactive, tetra-peptide matrikines 3

ABSTRACT: Small peptides with amino acid sequences similar to native skin proteins can beneficially affect clinical appearance (wrinkles) and architecture (collagen and elastic fibre deposition and epidermal thickness). However, the discovery of new cosmetic peptides has not been underpinned by any guiding hypothesis. As endogenous extracellular matrix (ECM)-derived peptides (matrikines) produced during tissue remodelling can influence cell activity, we hypothesised that protease cleavage site prediction can identify putative novel matrikines. This RNA-seq data is the in vivo test part of an in silico to in vivo discovery pipeline, which enables the prediction and characterisation of peptide matrikines with therapeutic potential. We use this pipeline to identify two novel ECM peptides (GPKG and LSVD) which, in combination, act in vitro to enhance the transcription of ECM organisation and cell proliferation genes and in vivo to promote epithelial and dermal remodelling. This pipeline approach can both identify new matrikines and provide insights into the mechanisms underpinning tissue repair.

INSTRUMENT(S): Illumina NovaSeq 6000

ORGANISM(S): Homo sapiens

SUBMITTER: Leo Zeef

PROVIDER: E-MTAB-12704 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:To obtain a separation of the epidermal and dermal compartments in order to examine compartment specific biological mechanisms in the skin we incubated 4 mm human skin punch biopsies in ammonium thiocyanate (NH4SCN). We wanted to test 1) the histological quality of the dermo-epidermal separation obtained by different incubation times 2) the amount and quality of extractable epidermal RNA, and 3) its impact on sample RNA expression profiles assessed by large-scale gene expression microarray analysis in both normal and inflamed skin. At 30 minutes incubation, the split between dermis and epidermis was not always histologically well-defined (i.e. occurred partly intra-epidermally) but varied between subjects. Consequently, curettage along the dermal surface of the biopsy was added to the procedure. This modified method resulted in an almost perfect separation of the epidermal and dermal compartments and satisfactory amounts of high-quality RNA were obtained. Hybridization to Affymetrix HG_U133A 2.0 GeneChips showed that ammonium thiocyanate incubation had a minute effect on gene expression resulting in only one significantly downregulated gene (cystatin E/M). We conclude that epidermis can be reproducibly and almost completely separated from the dermis of 4 mm skin biopsies by 30 min incubation in 3.8% ammonium thiocyanate combined with curettage of the dermal surface, producing high-quality RNA suitable for transcriptional analysis. Our refined method of dermo-epidermal separation will undoubtedly prove valuable in the many different settings, where the epidermal and dermal compartments need to be evaluated separately. Upper buttock skin in 4 healthy subjects was exposed to sodium lauryl sulphate, or sampled directly. For each subject, 4 biopsies were obtained: Two from inflamed skin, and two from adjacent normal skin. One irritated and one normal skin sample was placed directly in RNAlater. The remaining two samples were incubated in ammonium thiocyanate for 30 minutes at RT and then placed in RNAlater without performing any separation of the dermal and epidermal layers. This was done to investigate the effect of 30 minutes treatment with ammonium thiocyanate on both inflamed and non-inflamed skin. Data was normalized with quantile method (matrix 1) Forearm biopsies from 13 volunteers were separated to epidermis and dermis by use of ammonium thiocyanate. For comparison of full skin and epidermis without irritation, data from identical probe sets from HG_U133A 2.0 and HG_U133 plus 2.0 was extracted and normalised as one data set using quantile method (matrix 2).

Dataset Information

Prediction, screening and characterisation of novel bioactive, tetra-peptide matrikines 3

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure