Towards optimized tissue regeneration: a new 3D printable bioink of alginate/cellulose hydrogel loaded with thrombocyte concentrate

Abstract

Introduction: Autologous platelet concentrate (APC) are pro-angiogenic and can promote wound healing and tissue repair, also in combination with other biomaterials. However, challenging defect situations remain demanding. 3D bioprinting of an APC based bioink encapsulated in a hydrogel could overcome this limitation with enhanced physio-mechanical interface, growth factor retention/secretion and defect-personalized shape to ultimately enhance regeneration.

Methods: This study used extrusion-based bioprinting to create a novel bioink of alginate/cellulose hydrogel loaded with thrombocyte concentrate. Chemico-physical testing exhibited an amorphous structure characterized by high shape fidelity. Cytotoxicity assay and incubation of human osteogenic sarcoma cells (SaOs2) exposed excellent biocompatibility. enzyme-linked immunosorbent assay analysis confirmed pro-angiogenic growth factor release of the printed constructs, and co-incubation with HUVECS displayed proper cell viability and proliferation. Chorioallantoic membrane (CAM) assay explored the pro-angiogenic potential of the prints in vivo. Detailed proteome and secretome analysis revealed a substantial amount and homologous presence of pro-angiogenic proteins in the 3D construct.

Results: This study demonstrated a 3D bioprinting approach to fabricate a novel bioink of alginate/cellulose hydrogel loaded with thrombocyte concentrate with high shape fidelity, biocompatibility, and substantial pro-angiogenic properties.

Conclusion: This approach may be suitable for challenging physiological and anatomical defect situations when translated into clinical use.

Keywords: additive manufacturing; bioprinting; hydrogel; platelet rich fibrin; reconstruction.

FIGURE 1

SEM images of 3D prints with alginate/cellulose hydrogel with PBS (A–D) vs. alginate/cellulose hydrogel loaded with iPRF (E–H). Representative images of the surface in low (A, E) and high (C, G) magnification, as well as sections in low (B and F) and high (D, H) magnification, are shown. Furthermore, histological images of 3D prints with PBS (I) and loaded with PRF (J) after hematoxylin and eosin staining (Bar = 50 µm). XRD Analysis (K): For both groups, broad, amorphous humps around 15°–35°2q represent a nearly full amorphous character of the analyzed samples (grey line: PBS samples, red line: PRF loaded constructs). In the PRF-loaded sample, various peaks appear at 29.3, 39.2, and 47.2°–48.7°2q representing the semi-crystalline character of the bioink itself. (L) In addition to intense water bands, there may be metal hydroxide vibrations or OH-group vibrations associated with polymers shown in the IR spectra (n = 3) for each sample, dashed line: PBS samples, solid line: PRF-loaded constructs).

FIGURE 2

(A) Box plots illustrate the cell viability of L929 cells in the cytotoxicity assays. (according to DIN EN ISO 10993-5). No cytotoxic effects could be observed (as defined by ISO 10993-5 and indicated by a reduction in cell viability of >30% compared to the control). (B) Box plots show high cell viability after 24 h and increased viability after 96 h of incorporated SaOS-2 cells in the PRF-based bioink loaded alginate/cellulose hydrogels via AlamarBlue assay. (C) Box plots demonstrate cell viability and proliferation via Alamarblue assays of the HUVEC-seeded prints. (D) Representative fluorescence microscopic examinations of the GFP transduced HUVECs on the respective samples (PBS hydrogel models left, PRF incorporated prints right) after 24h and 96 h. Boxplot demonstrate growth factor expression of VEGF (E), PDGF (F), and TGF-ß (G) via ELISA of the respective growth factors of the alginate/cellulose hydrogel loaded with PRF bioink (pg/ml, n = 3, means ± SD, *p < 0.05, **p < 0.01, and ns determined by one-way ANOVA).

FIGURE 3

CAM assay to assess pro-angiogenic properties of the PBS and PRF prints in vivo: number of branching points (A) significantly enhanced in hydrogels loaded with PRF vs. PBS hydrogels after 72 h (t72). In contrast, the presence of the PRF loaded prints reduced mean vessel total area (B), but increased total vessel length (C) and mean vessel thickness (D) without reaching statistical significance. Representative images (E) of the hydrogels on the CAM at 72 h (input, left side) and the automatic cell count via respective software (right side) (pg/ml, n = 5, means ± SD,*p < 0.05 and ns determined by one-way ANOVA).

FIGURE 4

Proteome profiles of PRF in the native and 3D forms and the PRF secretome: (A) Heat map depicts the hierarchical clustering of all 225 total proteins based on the log2 protein intensity related to the designated groups. (B) Bar charts show the degree of mean percentage of top abundant proteins in the designated groups. (C) The venn diagram illustrates the total number of proteins identified in all samples after 24 h. PRF_nat: native platelet concentrates; PRF_3D: 3D-printed platelet concentrates; PRF_sec: 3D-PRF secretion/secretome.

FIGURE 5

Differential expression profiles of PRF proteins: Volcano plots illustrate the significantly differentially abundant proteins identified based on the log2 difference in the (A) PRF_sec vs. PRF_3D, (B) PRF_3D vs. PRF_nat and (C) PRF_sec vs. PRF_nat. Significance threshold is at p < 0.05. (D) The heat map depicts the hierarchical clustering of the significantly differentially abundant proteins in the PRF_sec vs. PRF_3D. Upregulated proteins are shown in red, and the downregulated proteins are in green. PRF_nat: native platelet concentrates; PRF_3D: 3D-printed platelet concentrates; PRF_sec: 3D-PRF secretion.

FIGURE 6

Protein-protein interactions (PPIs) of the differentially upregulated secretome proteins: The PPI of the PRF secretome shows the networks of differentially abundant proteins, which were highly increased in abundance in the secretome compared to the 3D PRF. The different color intensities correspond to the degree of differential expression. Proteins are annotated according to their cellular localization and are depicted as different shapes that represent the functional classes of the proteins.

FIGURE 7

Top significant canonical pathways of the PRF secretome: Bubble plot of the top significantly (p < 0.001) enriched canonical pathways associated with the differentially abundant proteins in the PRF secretome. Overall z-scores are represented by the color orange, which indicates activation, blue indicates inhibition of the signaling pathways; and grey indicates not quantifiable activity pattern. The size and color of each bubble represent a number of differentially abundant proteins in each pathway and z-score, respectively.

FIGURE 8

The bar chart depicts the top 15 significant [-log (p-value) > 1.3] biological functions attributed to the differentially abundant PRF secretome proteins. Bars represent the -log (p-value) (left y-axis) and the line represents the activation z-score (right y-axis) of each function and disease.

FIGURE 9

Predicted upstream regulators of the PRF secretome. (A) Bar chart shows the profiles of top selected significant [-log (p-value) > 1.3] upstream regulators associated with the significantly differentially abundant proteins in the PRF secretome. Bars represent the -log (p-value) (left y-axis) and the line represents the activation z-score (right y-axis) of each regulator. (B) Exemplary interaction network profile of TGF-β-regulated differentially expressed secreted proteins. Different shapes represent the various classes of proteins.