The Dynamic Nature of Human Dermal Fibroblasts Is Defined by Marked Variation in the Gene Expression of Specific Cytoskeletal Markers

LIFE-BASEL(2022)

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摘要
The evidence for fibroblast heterogeneity is continuously increasing, and recent work has shed some light on the existence of different sub-populations of fibroblasts in the human skin. Although we now have a more precise understanding of their distribution in the human body, we do not know whether their properties are predictive of where these cells derive from or whether these sub-types have functional consequences. In this study, we employed single-cell transcriptomics (10X Genomics) to study gene expression and segregate fibroblast sub-populations based on their genetic signature. We report the differential expression of a defined set of genes in fibroblasts from human skin, which may contribute to their dynamicity in vivo and in vitro. We show that the sub-population of fibroblasts expressing cytoskeletal markers, such as ANXA2, VIM, ACTB, are enriched in an adult skin sample. Interestingly, this sub-population of fibroblasts is not enriched in a neonatal skin sample but becomes predominant when neonatal fibroblasts are cultivated. On the other hand, the fibroblast sub-populations expressing COL1A1 and ELN are enriched in neonatal skin but are reduced in the adult skin and in fibroblasts from neonatal skin that are cultured in vitro. Our results indicate that fibroblasts are a dynamic cell type, and while their genetic make-up changes markedly, only a handful of genes belonging to the same functional pathway govern this alteration. The gene expression pattern of cytoskeletal markers may help in identifying whether the fibroblasts were isolated from an adult or an infant or whether they were cultivated, and this information could be useful for quality control in clinics and in cell banking. Furthermore, this study opens additional avenues to investigate the role of these markers in defining the complexity of human dermal fibroblasts.
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关键词
human fibroblasts, gene expression, heterogeneity, single-cell transcriptomics, cytoskeletal markers
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