Three Dimensional Bioprinting of a Vascularized and Perfusable Skin Graft Using Human Keratinocytes, Fibroblasts, Pericytes, and Endothelial Cells.

Multilayered skin substitutes comprising allogeneic cells have been tested for the treatment of nonhealing cutaneous ulcers. However, such nonnative skin grafts fail to permanently engraft because they lack dermal vascular networks important for integration with the host tissue. In this study, we describe the fabrication of an implantable multilayered vascularized bioengineered skin graft using 3D bioprinting. The graft is formed using one bioink containing human foreskin dermal fibroblasts (FBs), human endothelial cells (ECs) derived from cord blood human endothelial colony-forming cells (HECFCs), and human placental pericytes (PCs) suspended in rat tail type I collagen to form a dermis followed by printing with a second bioink containing human foreskin keratinocytes (KCs) to form an epidermis. In vitro, KCs replicate and mature to form a multilayered barrier, while the ECs and PCs self-assemble into interconnected microvascular networks. The PCs in the dermal bioink associate with EC-lined vascular structures and appear to improve KC maturation. When these 3D printed grafts are implanted on the dorsum of immunodeficient mice, the human EC-lined structures inosculate with mouse microvessels arising from the wound bed and become perfused within 4 weeks after implantation. The presence of PCs in the printed dermis enhances the invasion of the graft by host microvessels and the formation of an epidermal rete. Impact Statement Three Dimensional printing can be used to generate multilayered vascularized human skin grafts that can potentially overcome the limitations of graft survival observed in current avascular skin substitutes. Inclusion of human pericytes in the dermal bioink appears to improve both dermal and epidermal maturation.

Peptide de novo sequencing of mixture tandem mass spectra.

The impact of mixture spectra deconvolution on the performance of four popular de novo sequencing programs was tested using artificially constructed mixture spectra as well as experimental proteomics data. Mixture fragmentation spectra are recognized as a limitation in proteomics because they decrease the identification performance using database search engines. De novo sequencing approaches are expected to be even more sensitive to the reduction in mass spectrum quality resulting from peptide precursor co-isolation and thus prone to false identifications. The deconvolution approach matched complementary b-, y-ions to each precursor peptide mass, which allowed the creation of virtual spectra containing sequence specific fragment ions of each co-isolated peptide. Deconvolution processing resulted in equally efficient identification rates but increased the absolute number of correctly sequenced peptides. The improvement was in the range of 20-35% additional peptide identifications for a HeLa lysate sample. Some correct sequences were identified only using unprocessed spectra; however, the number of these was lower than those where improvement was obtained by mass spectral deconvolution. Tight candidate peptide score distribution and high sensitivity to small changes in the mass spectrum introduced by the employed deconvolution method could explain some of the missing peptide identifications.