Angiogenic Peptide Nanofibers Improve Wound Healing in STZ-Induced Diabetic Rats

Low expressions of angiogenic growth factors delay the healing of diabetic wounds by interfering with the process of blood vessel formation. Heparin mimetic peptide nanofibers can bind to and enhance production and activity of major angiogenic growth factors, including VEGF. In this study, we showed that heparin mimetic peptide nanofibers can serve as angiogenic scaffolds that allow slow release of growth factors and protect them from degradation, providing a new therapeutic way to accelerate healing of diabetic wounds. We treated wounds in STZ-induced diabetic rats with heparin mimetic peptide nanofibers and studied repair of full-thickness diabetic skin wounds. Wound recovery was quantified by analyses of re-epithelialization, granulation tissue formation and blood vessel density, as well as VEGF and inflammatory response measurements. Wound closure and granulation tissue formation were found to be significantly accelerated in heparin mimetic gel treated groups. In addition, blood vessel counts and the expressions of alpha smooth muscle actin and VEGF were significantly higher in bioactive gel treated animals. These results strongly suggest that angiogenic heparin mimetic nanofiber therapy can be used to support the impaired healing process in diabetic wounds. © 2016 American Chemical Society

Maximum Composite Likelihood trees.

<p>(A) Putative Deformed wing virus (DWV) sequences. (B) Kashmir bee virus (KBV) sequences from <i>Vespula vulgaris and Apis mellifera</i> sampled (bold) and the best matching sequences on GenBank, together with their accession numbers and host species. The trees were based on 2000 bootstraps of a general time-reversible model with gamma distribution and invariant sites parameters (GTR + G(0.48) +I(200); lnL −550.04) for DWV and a general time-reversible model (GTR; lnL −195.50) for KBV in MEGA6. The estimates of levels of support shown below the nodes are bootstrap values greater than 50%. The trees are drawn to scale, with branch lengths measured in the number of substitutions per site.</p

The number of microbial taxa observed from the previously published literature and proteomics methods.

<p>(A) The number of microbial taxa observed in published studies examining <i>V</i>. <i>germanica</i> and <i>V</i>. <i>vulgaris</i>. The numbers at the top of the bars represent the number of published studies, e.g. there were nine published papers examining fungal in wasps from the invaded range. Inset is a graph showing the non-significant relationship (p≥0.218) between the number of taxa found and the number of studies for each microbial group. (B) Results from our proteomics survey of microbes associated with wasps from the native and invaded range. No viruses were observed in the proteomics analysis. The “other” category is from peptides indicating the presence of taxa including amoeba (<i>Acanthamoeba</i> sp.), a protozoan (<i>Babesia</i> sp.), and tapeworm (<i>Taenia</i> sp.).</p

Microbial communities in wasp samples from the four countries.

<p>(A) A Venn diagram showing the overlap and distinctiveness of microbial taxa from common wasps in the native (England and Belgium) and invaded range (New Zealand and Argentina). A total of 131 peptides from distinct microbial taxa were observed. Of these 131 microbial taxa, 39 taxa were shared between all countries, but different countries had between 9–14 distinct taxa. (B) Rarefaction curves showing the similarity of microbial taxa accumulation with increasing peptides sampled.</p

Sample locations for common wasps from the native (England and Belgium) and invaded range (New Zealand and Argentina).

<p>Twenty adult <i>V</i>. <i>vulgaris</i> worker wasps were collected from each of the four countries. In some cases, multiple wasps were collected in the same area, but never from the same nest. For Argentina, the restricted sampling area represents the latitudinal limits of their distribution at the time of sampling in 2013. Common wasps are distributed throughout New Zealand.</p

Maximum Composite Likelihood tree for putative 16S <i>Nosema</i> sequences from <i>Vespula vulgaris</i> sampled (bold) and the best matching sequences on GenBank, together with their accession numbers and sample collection locations (where available).

<p>The tree was based on 2000 bootstraps of a general time-reversible model with gamma distribution and invariant sites parameters (GTR + G(0.69) +I(0.0); lnL −928.456) in MEGA6. The estimates of levels of support shown below the nodes are bootstrap values greater than 50%. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site.</p

Maximum Composite Likelihood tree for putative Actinobacteria sequences from <i>Vespula vulgaris</i> sampled (bold) and the best matching sequences on GenBank, together with their accession numbers and host species.

<p>The tree was based on 2000 bootstraps of a general time-reversible model with gamma distribution and invariant sites parameters; lnL −559.13) in MEGA6. The estimates of levels of support shown below the nodes are bootstrap values greater than 50%. The tree is drawn to scale, with branch lengths measured in the number of substitutions per site. Often GenBank sequences were equally well matched to the sequences from <i>V</i>. <i>vulgaris</i> and those displayed on the tree are not exhaustive (e.g. the Ireland sample matched equally well to multiple <i>Arthrobacter</i> sp.).</p