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Modeling fibrosis using fibroblasts isolated from scarred rat vocal folds

View Article: PubMed Central - PubMed

ABSTRACT

Following injury, pathologically activated vocal fold fibroblasts (VFFs) can engage in disordered extracellular matrix (ECM) remodeling, leading to VF fibrosis and impaired voice function. Given the importance of scar VFFs to phenotypically appropriate in vitro modeling of VF fibrosis, we pursued detailed characterization of scar VFFs obtained from surgically injured rat VF mucosae, compared to those obtained from experimentally naïve, age-matched tissue. Scar VFFs initially exhibited a myofibroblast phenotype characterized by increased proliferation, increased Col1a1 transcription and collagen, type I synthesis, increased Acta2 transcription and α-smooth muscle actin synthesis, and enhanced contractile function. These features were most distinct at passage 1 (P1); we observed a coalescence of the scar and naïve VFF phenotypes at later passages. An empirical Bayes statistical analysis of the P1 cell transcriptome identified 421 genes that were differentially expressed by scar, compared to naïve, VFFs. These genes were primarily associated with the wound response, ECM regulation, and cell proliferation. Follow-up comparison of P1 scar VFFs and their in vivo tissue source showed substantial transcriptomic differences. Finally, P1 scar VFFs responded to treatment with hepatocyte growth factor and transforming growth factor-β3, two biologics with reported therapeutic value. Despite the practical limitations inherent to working with early passage cells, this experimental model is easily implemented in any suitably equipped laboratory and has the potential to improve the applicability of preclinical VF fibrosis research.

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Analysis of the scar VFF transcriptome(a) Gene ontology-based enrichment analysis of DE genes in scar, compared to naïve, VFFs at P1. Enriched ontology terms are depicted as nodes; highly similar terms are connected by edges. Cellular component terms are green; molecular function terms are red; biological process terms are blue. Node color intensity corresponds to the z-score associated with term enrichment. Node and label font size are proportional to the generality of the term in the underlying ontology. (b) Heat maps showing mean-centered log2-expression data for DE genes associated with the response to wounding, extracellular matrix, and cell division ontology terms. DE genes are ranked by log2 fold change (scar normalized to naïve) along the vertical axis. This experiment was performed with n = 3 biological replicates in the naïve condition and n = 4 biological replicates in the scar condition.
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Figure 4: Analysis of the scar VFF transcriptome(a) Gene ontology-based enrichment analysis of DE genes in scar, compared to naïve, VFFs at P1. Enriched ontology terms are depicted as nodes; highly similar terms are connected by edges. Cellular component terms are green; molecular function terms are red; biological process terms are blue. Node color intensity corresponds to the z-score associated with term enrichment. Node and label font size are proportional to the generality of the term in the underlying ontology. (b) Heat maps showing mean-centered log2-expression data for DE genes associated with the response to wounding, extracellular matrix, and cell division ontology terms. DE genes are ranked by log2 fold change (scar normalized to naïve) along the vertical axis. This experiment was performed with n = 3 biological replicates in the naïve condition and n = 4 biological replicates in the scar condition.

Mentions: Given our experimental data showing differences in the transcription of fibrosis-related genes by naïve and scar VFFs at P1, and the importance of comprehensive characterization of the scar VFF phenotype, we used expression microarrays to profile the scar VFF transcriptome. We prepared P1 naïve and scar VFFs for standard analysis using Affymetrix rat genome expression arrays, evaluated differential expression (DE) using an empirical Bayes approach,40 and conducted enrichment analysis using Gene Ontology (GO) annotations.42 A total of 598 probes, corresponding to 421 unique genes, were DE in the scar VFF condition compared to the naïve control condition. These 421 genes corresponded to enrichment of 73 GO terms (Table S1): the majority (54) of enriched terms were associated with the biological process domain; fewer terms were associated with the cellular component (16) and molecular function (3) domains. Postprocessing of these enrichment data using the REViGO semantic similarity and term redundancy algorithm43 highlighted biological process terms associated with cell division and proliferation, adhesion, and response to wounding; cellular component terms associated with the ECM and cell nucleus; and molecular function terms associated with the ECM and microtubule activity (Figure 4a).


Modeling fibrosis using fibroblasts isolated from scarred rat vocal folds
Analysis of the scar VFF transcriptome(a) Gene ontology-based enrichment analysis of DE genes in scar, compared to naïve, VFFs at P1. Enriched ontology terms are depicted as nodes; highly similar terms are connected by edges. Cellular component terms are green; molecular function terms are red; biological process terms are blue. Node color intensity corresponds to the z-score associated with term enrichment. Node and label font size are proportional to the generality of the term in the underlying ontology. (b) Heat maps showing mean-centered log2-expression data for DE genes associated with the response to wounding, extracellular matrix, and cell division ontology terms. DE genes are ranked by log2 fold change (scar normalized to naïve) along the vertical axis. This experiment was performed with n = 3 biological replicates in the naïve condition and n = 4 biological replicates in the scar condition.
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Related In: Results  -  Collection

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Figure 4: Analysis of the scar VFF transcriptome(a) Gene ontology-based enrichment analysis of DE genes in scar, compared to naïve, VFFs at P1. Enriched ontology terms are depicted as nodes; highly similar terms are connected by edges. Cellular component terms are green; molecular function terms are red; biological process terms are blue. Node color intensity corresponds to the z-score associated with term enrichment. Node and label font size are proportional to the generality of the term in the underlying ontology. (b) Heat maps showing mean-centered log2-expression data for DE genes associated with the response to wounding, extracellular matrix, and cell division ontology terms. DE genes are ranked by log2 fold change (scar normalized to naïve) along the vertical axis. This experiment was performed with n = 3 biological replicates in the naïve condition and n = 4 biological replicates in the scar condition.
Mentions: Given our experimental data showing differences in the transcription of fibrosis-related genes by naïve and scar VFFs at P1, and the importance of comprehensive characterization of the scar VFF phenotype, we used expression microarrays to profile the scar VFF transcriptome. We prepared P1 naïve and scar VFFs for standard analysis using Affymetrix rat genome expression arrays, evaluated differential expression (DE) using an empirical Bayes approach,40 and conducted enrichment analysis using Gene Ontology (GO) annotations.42 A total of 598 probes, corresponding to 421 unique genes, were DE in the scar VFF condition compared to the naïve control condition. These 421 genes corresponded to enrichment of 73 GO terms (Table S1): the majority (54) of enriched terms were associated with the biological process domain; fewer terms were associated with the cellular component (16) and molecular function (3) domains. Postprocessing of these enrichment data using the REViGO semantic similarity and term redundancy algorithm43 highlighted biological process terms associated with cell division and proliferation, adhesion, and response to wounding; cellular component terms associated with the ECM and cell nucleus; and molecular function terms associated with the ECM and microtubule activity (Figure 4a).

View Article: PubMed Central - PubMed

ABSTRACT

Following injury, pathologically activated vocal fold fibroblasts (VFFs) can engage in disordered extracellular matrix (ECM) remodeling, leading to VF fibrosis and impaired voice function. Given the importance of scar VFFs to phenotypically appropriate in vitro modeling of VF fibrosis, we pursued detailed characterization of scar VFFs obtained from surgically injured rat VF mucosae, compared to those obtained from experimentally naïve, age-matched tissue. Scar VFFs initially exhibited a myofibroblast phenotype characterized by increased proliferation, increased Col1a1 transcription and collagen, type I synthesis, increased Acta2 transcription and α-smooth muscle actin synthesis, and enhanced contractile function. These features were most distinct at passage 1 (P1); we observed a coalescence of the scar and naïve VFF phenotypes at later passages. An empirical Bayes statistical analysis of the P1 cell transcriptome identified 421 genes that were differentially expressed by scar, compared to naïve, VFFs. These genes were primarily associated with the wound response, ECM regulation, and cell proliferation. Follow-up comparison of P1 scar VFFs and their in vivo tissue source showed substantial transcriptomic differences. Finally, P1 scar VFFs responded to treatment with hepatocyte growth factor and transforming growth factor-β3, two biologics with reported therapeutic value. Despite the practical limitations inherent to working with early passage cells, this experimental model is easily implemented in any suitably equipped laboratory and has the potential to improve the applicability of preclinical VF fibrosis research.

No MeSH data available.


Related in: MedlinePlus