Towards embryonic-like scaffolds for skin tissue engineering: identification of effector molecules and construction of scaffolds

Abstract

Autologous skin grafts are the gold standard for the treatment of burn wounds. In a number of cases, treatment with autologous tissue is not possible and skin substitutes are used. The outcome, however, is not optimal and improvements are needed. Inspired by scarless healing in early embryonic development, we here set out a strategy for the design and construction of embryonic-like scaffolds for skin tissue engineering. This strategy may serve as a general approach in the construction of embryonic-like scaffolds for other tissues/organ. As a first step, key effector molecules upregulated during embryonic and neonatal skin formation were identified using a comparative gene expressing analysis. A set of 20 effector molecules was identified, from which insulin-like growth factor 2 (IGF2) and sonic hedgehog (SHH) were selected for incorporation into a type I collagen-heparin scaffold. Porous scaffolds were constructed using purified collagen fibrils and 6% covalently bound heparin (to bind and protect the growth factors), and IGF2 and SHH were incorporated either individually (~0.7 and 0.4 µg/mg scaffolds) or in combination (combined ~1.5 µg/mg scaffolds). In addition, scaffolds containing hyaluronan (up to 20 µg/mg scaffold) were prepared, based on the up- or downregulation of genes involved in hyaluronan synthesis/degradation and its suggested role in scarless healing. In conclusion, based on a comprehensive gene expression analysis, a set of effector molecules and matrix molecules was identified and incorporated into porous scaffolds. The scaffolds thus prepared may create an 'embryonic-like' environment for cells to recapitulate embryonic events and for new tissues/organs.

Tissue Engineering and Regenerative Repair in Wound Healing

“…The approach described by Uijtdewilligen et al 133 highlights the potential to incorporate ECM proteins and growth factors reflective of the fetal milieu into tissue engineering scaffolds. As previously mentioned, increased fibroblast proliferation and migration with rapid wound healing is characteristic of the fetal regenerative response and the increased cellularity and rate of wound closure achieved through stem cell based therapies, whether BM-MSCs or ASCs, partially recapitulates the fetal response to injury.…”

“…An alternative approach described by Uijtdewilligen et al involves the incorporation of molecules identified to be upregulated during embryonic skin development, including hyaluronan, into a type I collagen-heparin scaffold. 133 Though McDevitt’s group have not yet assessed the regenerative potential of ESC produced ECM and Uijtdewilligen et al employed only type I collagen and should have prioritized type III collagen, in the authors opinions, these approaches represents a significant step towards recapitulation of the fetal dermal environment.…”

Dynamic Expression of Genes Involved in Proteoglycan/Glycosaminoglycan Metabolism during Skin Development

“…Mice aged 90 days (90 days post birth [P90]) were used for timed mating and dorsal skin was collected at 14 days (E14) and 16 days after conception (E16). At E14 hair follicle development is initiated, and at E16 this process is almost completed in combination with a stratified epidermis and organized dermis [ 18 , 19 ]. For the RNA samples of E14, dorsal skin of seven embryos from one female was pooled and used for RNA isolation.…”

“…In addition, skin from 1-day old pups (P1) and adult mice (P90) was collected. At P1 skin is more organized and has been exposed to air [ 18 , 19 ]. For the two dorsal skin samples for P1, three pups from two females were taken per sample.…”

“…Gene Chip Mouse exon 1.0 ST Arrays (Affymetrix, High Mycombe, UK) were used to analyze gene expression for E14, E16, P1, and P90 using 1 μ g of RNA per chip. Expression data were preprocessed to check sensitivity and specificity of the results based on Kadota et al (2009) as shown in Uijtdewilligen et al (2016) [ 18 , 21 ]. Gene level expression data were calculated for the CORE transcripts (probe sets supported by RefSeq mRNAs) using Affymetrix Expression Console software with quantile normalization (all arrays are considered to have an equal intensity distribution), GC-content background correction (probes with high GC-content hybridize better, corrected for with built-in probes with different known GC-contents) and summarization with the RMA algorithm [ 22 ].…”