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. 2016 Mar;81:104-113.
doi: 10.1016/j.biomaterials.2015.12.004. Epub 2015 Dec 14.

Protein Turnover During in Vitro Tissue Engineering

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Free PMC article

Protein Turnover During in Vitro Tissue Engineering

Qiyao Li et al. Biomaterials. .
Free PMC article

Abstract

Repopulating acellular biological scaffolds with phenotypically appropriate cells is a promising approach for regenerating functional tissues and organs. Under this tissue engineering paradigm, reseeded cells are expected to remodel the scaffold by active protein synthesis and degradation; however, the rate and extent of this remodeling remain largely unknown. Here, we present a technique to measure dynamic proteome changes during in vitro remodeling of decellularized tissue by reseeded cells, using vocal fold mucosa as the model system. Decellularization and recellularization were optimized, and a stable isotope labeling strategy was developed to differentiate remnant proteins constituting the original scaffold from proteins newly synthesized by reseeded cells. Turnover of matrix and cellular proteins and the effects of cell-scaffold interaction were elucidated. This technique sheds new light on in vitro tissue remodeling and the process of tissue regeneration, and is readily applicable to other tissue and organ systems.

Keywords: Acellular scaffold; Protein turnover; Reseeding; Stable isotope labeling; Tissue remodeling; Vocal fold fibroblast; Vocal fold mucosa.

Figures

Fig. 1
Fig. 1
Summary of the entire experimental workflow. Vocal fold mucosae (VFM) are decellularized using one of five strategies for 2-7 d. Vocal fold fibroblasts (VFFs) are isotopically labeled for sufficient time to ensure full-proteome incorporation of 13C6-Lys and 13C6-Arg. Next, the labeled VFFs are seeded and cultured for up to 6 w in decellularized VFM, with liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based analysis at each of 6 w. Representative cell proliferation and new ECM synthesis are shown for 0, 3, and 6 w timepoints only. VFE, vocal fold epithelial cell; ECM, extracellular matrix.
Fig. 2
Fig. 2
Comparison of five decellularization strategies. (a) Flowchart summarizing the five strategies. (b) Quantitative hydroxyproline and sulfated glycosaminoglycan (sGAG) concentrations for each decellularization strategy compared to native tissue control (n = 3 biological replicates, each with n = 3 technical replicates). *, P < 0.05 versus native condition; n.s., non-significant difference; error bars, s.e.m. (c) Pentachrome-stained sections of native and decellularized porcine VFM. Collagen is yellow; elastin is black; arrows indicate residual cells. H&E- and Alcian Blue-stained sections are shown in Supplementary Fig S1. Scale bar, 50 μ m.
Fig. 3
Fig. 3
Comparison of five reseeding strategies. (a) Schematic illustrating the five strategies plus negative control condition. (b) H&E-stained sections of recellularized porcine VFM, 3 w post-seeding. No seeding control is also shown. Tissue orientation matches that shown in panel (a); cells were seeded on the tissue surface corresponding to the top of each image. Arrows indicate cells lodged at the basement membrane in strategy 1; dashed lines indicate polymerized collagen in strategy 5. Scale bar, 100 μm. (c) Mean and maximum cell migration observed for each seeding strategy, 3 w post-seeding (n = 3 biological replicates, each with n = 3 technical replicates). *, P < 0.05 compared to both strategy 3 and 4; n.s., non-significant difference; error bars, s.e.m. (d) H&E-stained sections of recellularized human VFM (strategy 3), 3 and 6 w post-seeding. No seeding control is also shown. Scale bar, 100 μ m.
Fig. 4
Fig. 4
Proteomic analysis of native, decellularized, and recellularized (6 w post-seeding) human VFM. (a) Venn diagram summarizing number of protein identifications for each condition. (b) Functional enrichment analysis of the 160 proteins exclusively identified in the recellularized condition. Enriched gene ontology terms are depicted as nodes connected by arrows that represent hierarchies and relationships between terms. Node size is proportional to the number of proteins assigned to a given term; node color represents the Benjamini Hochberg-corrected P value corresponding to enrichment of the term. Functionally related terms are labeled and grouped using green ovals. Biogenesis terms are enlarged for better visualization. (c) Venn diagram summarizing number of matrisome protein identifications for each condition. (d) Stacked bar graph showing distribution of MS intensity among the six matrisome subcategories.
Fig. 5
Fig. 5
Percentage of light or heavy protein intensity, out of total protein intensity of each sample at each time point, for (a) matrisome proteins and (b, c) cellular proteins during 6 w in culture (n = 4 biological replicates, each with n = 2 technical replicates). The 0 w, and 3 w and 6 w control samples were generated by mixing cells and scaffold at the peptide level. *, P < 0.05 for comparisons between experimental and control samples at 3 and 6 w; error bars, s.e.m.
Fig. 6
Fig. 6
Synthesis of matrisome proteins. (a) Fold change in heavy (newly synthesized) protein intensity for each of the six matrisome subcategories compared to 0 w control. Turnover is shown for proteins associated with the following core matrisome subcategories: (b) collagens, (c) ECM glycoproteins, and (d) proteoglycans. Turnover is plotted as the percentage of heavy intensity out of total intensity for each individual protein. (e) Percentage of heavy, light, or total (heavy + light) intensity for the proteoglycan decorin (DCN), out of total protein intensity of each sample at each time point. (f) Immunoblots showing total DCN abundance. MS data (a-e) were collected on n = 4 biological replicates, each with n = 2 technical replicates; immunoblots (f) were performed using n = 3 biological replicates; error bars, s.e.m. (b-e). The discrepancy in initial time point in panels (e) and (f) is because the 0 w MS data were generated following peptide-level sample preparation, meaning that no directly comparable protein samples were available for immunoblotting.

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