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| Status |
Public on Jul 19, 2024 |
| Title |
An Efficient Direct Conversion Strategy to Generate Functional Astrocytes from Human Adult Fibroblasts |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
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| Summary |
Direct reprogramming approaches offer an attractive alternative to stem-cell-derived models, allowing the retention of epigenetic information and age-associated cellular phenotypes, as well as a fast method to reach a target cell type. Several groups have previously generated multiple neuronal subtypes, neural progenitor cells, oligodendrocytes, and other cell types directly from fibroblasts. Other groups have had success at the efficient conversion of embryonic fibroblasts to astrocytes but have not yet achieved similar conversion efficiency for adult human fibroblasts. In order to generate astrocytes for the study of adult-stage disorders, we developed an improved direct conversion strategy employing a combination of small molecules to activate specific pathways that induce trans-differentiation of human adult fibroblasts to astrocytes. We demonstrate that this method produces mature GFAP+/S100β+ cells at high efficiency (40-45%), comparable to previous studies utilizing embryonic fibroblasts. Further, Fibroblast-derived induced Astrocytes (FdiAs) are enriched for markers of astrocyte functionality, including ion-channel buffering, gap-junction communication, and glutamate uptake; and exhibit astrocyte-like calcium signaling and neuroinflammatory phenotypes. RNA-Seq analysis indicates an adult rather than fetal astrocytic gene expression signature, with a greater correlation to temporal lobe astrocytes. Fibroblast-derived induced astrocytes provide a useful tool in studying the adult brain and complement existing in vitro models of induced neurons (iNs), providing an additional platform to study late-stage brain disorders.
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| Overall design |
Fibroblasts (Day 0), and FdiAs at different stages of conversion (Day 10, 30 and 50) were fixed and processed for single-cell RNA-seq using a combinatorial indexing approach to assess gene expression profiles of induced cells.
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| Contributor(s) |
Bhaskar U, Carless MA, Kos MZ |
| Citation missing |
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| Submission date |
Jul 15, 2024 |
| Last update date |
Jul 19, 2024 |
| Contact name |
Melanie Anita Carless |
| E-mail(s) |
melanie.carless@utsa.edu
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| Organization name |
The University of Texas at San Antonio
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| Street address |
One UTSA Circle
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| City |
San Antonio |
| State/province |
Texas |
| ZIP/Postal code |
78249 |
| Country |
USA |
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| Platforms (1) |
| GPL24676 |
Illumina NovaSeq 6000 (Homo sapiens) |
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| Samples (1) |
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| Relations |
| BioProject |
PRJNA1136014 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE272279_RAW.tar |
347.5 Mb |
(http)(custom) |
TAR (of CSV) |
SRA Run Selector |
| Raw data are available in SRA |
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