Reprogramming of adult human dermal fibroblasts to induced dorsal forebrain precursor cells maintains aging signatures

将成人真皮成纤维细胞重编程为诱导型背侧前脑前体细胞可维持衰老特征

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Abstract

Introduction: With the increase in aging populations around the world, the development of in vitro human cell models to study neurodegenerative disease is crucial. A major limitation in using induced pluripotent stem cell (hiPSC) technology to model diseases of aging is that reprogramming fibroblasts to a pluripotent stem cell state erases age-associated features. The resulting cells show behaviors of an embryonic stage exhibiting longer telomeres, reduced oxidative stress, and mitochondrial rejuvenation, as well as epigenetic modifications, loss of abnormal nuclear morphologies, and age-associated features. Methods: We have developed a protocol utilizing stable, non-immunogenic chemically modified mRNA (cmRNA) to convert adult human dermal fibroblasts (HDFs) to human induced dorsal forebrain precursor (hiDFP) cells, which can subsequently be differentiated into cortical neurons. Analyzing an array of aging biomarkers, we demonstrate for the first time the effect of direct-to-hiDFP reprogramming on cellular age. Results: We confirm direct-to-hiDFP reprogramming does not affect telomere length or the expression of key aging markers. However, while direct-to-hiDFP reprogramming does not affect senescence-associated β-galactosidase activity, it enhances the level of mitochondrial reactive oxygen species and the amount of DNA methylation compared to HDFs. Interestingly, following neuronal differentiation of hiDFPs we observed an increase in cell soma size as well as neurite number, length, and branching with increasing donor age suggesting that neuronal morphology is altered with age. Discussion: We propose direct-to-hiDFP reprogramming provides a strategy for modeling age-associated neurodegenerative diseases allowing the persistence of age-associated signatures not seen in hiPSC-derived cultures, thereby facilitating our understanding of neurodegenerative disease and identification of therapeutic targets.

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