Human skin cells transformed directly into motor neurons
Ученые впервые «напрямую» превратили кожу в нервные клетки
Ученые впервые применили стволовые клетки для лечения инсульта
Биологи превратили стволовые клетки в структуру, похожую на мозг
A directory of defined factors for direct cell reprogramming
Mogrify uses a network-based algorithm designed to find transcription factors that impart the most influence on changes in cellular state. This website will allow you to explore possible reprogramming experiments, different collections of transcription factors as well as the look at the changes in the regulatory network.
Conversions from the Rackham and Firas et al, Nature Genetics 2016
A predictive computational framework for direct reprogramming between human cell types.
Transdifferentiation, the process of converting from one cell type to another without going through a pluripotent state, has great promise for regenerative medicine. The identification of key transcription factors for reprogramming is currently limited by the cost of exhaustive experimental testing of plausible sets of factors, an approach that is inefficient and unscalable. Here we present a predictive system (Mogrify) that combines gene expression data with regulatory network information to predict the reprogramming factors necessary to induce cell conversion. We have applied Mogrify to 173 human cell types and 134 tissues, defining an atlas of cellular reprogramming. Mogrify correctly predicts the transcription factors used in known transdifferentiations. Furthermore, we validated two new transdifferentiations predicted by Mogrify. We provide a practical and efficient mechanism for systematically implementing novel cell conversions, facilitating the generalization of reprogramming of human cells. Predictions are made available to help rapidly further the field of cell conversion.
- Enabling direct fate conversion with network biology. [Nat Genet. 2016]
March 27, 2016 | Direct Reprogramming
Mogrify – Cell Conversion Made Easy?
Review of “A predictive computational framework for direct reprogramming between human cell types” from Nature Genetics by Stuart P. Atkinson
Blind alleys, one-way streets, and a lot of negative results. Reprogramming experiments come across such problems with unfortunate certainty and, while they are invaluable to the final result, this time could be much better spent. Jose M Polo and Julian Gough sought to reduce the time spent and increase the likelihood of success in direct reprogramming (or transdifferentiation) experiments by creating a predictive computational system which can indicate which reprogramming factors are likely to induce the conversion of one cell type into another.
Their results, published in Nature Genetics, could save both money and time and, in doing so, revolutionize the field of direct reprogramming and boost clinical aspirations for this process .
The computational framework described, known as ‘Mogrify’ to its creators, holds information regarding transcription factors (TFs) which discriminate cell lineages. This includes information on how each TF is regulated, how direct the action of a TF is, and its specificity. With all this information, Mogrify can choose which TFs are likely to combine to activate the pertinent regulatory networks.
After construction, the authors demonstrated Mogrify’s power by testing it against well-understood validated human cell conversions. Mogrify correctly identified:
- NANOG, OCT4, and SOX2 in human induced pluripotent stem cell (hiPSC) production from fibroblasts
- CEBPα and PU.1 in the conversion of B cells and fibroblasts into macrophage-like cells
- Transcription factors known to be important in the conversion of human dermal fibroblasts into cardiomyocytes and hepatocytes
The real test came when the authors attempted “new” cell conversions using TFs generated from Mogrify’s databases. However, Mogrify came through, and correctly identified:
- FOXQ1, SOX9, MAFB, CDH1, FOS, and REL in the conversion of fibroblasts into keratinocytes with the expected morphological and molecular characteristics
- SOX17, TAL1, SMAD1, IRF1, and TCF7L1 in the conversion of keratinocytes into micro¬vascular endothelial cells (iECs) with the expected morphological and molecular characteristics
The authors note that finalizing conditions for cell conversions will still need trial-and-error experimentation as the data input to Mogrify is limited by what we currently understand, their new program will give many a confident head start in reprogramming experiments. There are, however, some other important caveats that the authors identify. Firstly, Mogrify is not designed to identify factors which extinguish a given donor cells signature and, secondly, multiple other factors which can influence cell conversion (e.g. noncoding RNAs, small molecules, epigenetic factors, and signaling pathways) are not incorporated.
However, one cannot help see the usefulness of this network biology approach to transdifferentiation and, as a final bonus to the entire field, Mogrify itself is a free tool for all to use. So get over to www.mogrify.net and see what you can convert today!
- Rackham OJ, Firas J, Fang H, et al. A predictive computational framework for direct reprogramming between human cell types. Nat Genet 2016;48:331-335.
April 6, 2017
What’s the Stem Cells Buzz this Week? – RIG1 and Reprogramming, Optimized MSC Spheroids, hAFS Extracellular Vesicles, and Corneal Epithelial Stem Cell mediated Wound Healing!
A roundup of some the recent stories in the ever-changing world of stem cells and regenerative medicine
Efficient Reprogramming Requires RIG1!
Research from the lab of John P. Cooke (Houston Methodist Research Institute, Houston, TX, USA) has indicated a critical role for innate immune signaling in nuclear reprogramming to pluripotency. In their new STEM CELLSstudy, Sayed et al describe the importance of the retinoic acid-inducible gene 1 receptor (RIG-1)-like receptor (RLR) pathway during reprogramming employing retroviral or modified messenger RNA (mmRNA) approaches. Could manipulation of this pathway make the production of induced pluripotent stem cells more efficient?
Optimizing the Regenerative Potential of MSC Spheroids
Growing mesenchymal stem cells (MSCs) as three-dimensional “spheroids” augments their pro-regenerative capacities. A new study from the team of J. Kent Leach (University of California, Davis, USA) now describes optimal conditions for spheroid growth that enhances anti-inflammatory and proangiogenic potential. Their multivariate analyses (number of cells/spheroid, oxygen tension, and inflammatory stimulus) could make MSC-based treatments more efficient and effective! See STEM CELLS for all the info.
Characterizing Human Amniotic Fluid Stem Cell Extracellular Vesicles
Human amniotic fluid stem cells (hAFS) have shown potential for the treatment of several diseases, mainly through the secretion of pro-regenerative factors. The lab of Sveva Bollini (University of Genova, Italy) has now characterized extracellular vesicles (EV) released by hAFS and demonstrate that EVs contain factors that facilitate significant prosurvival, proliferative, and anti-inflammatory effects. Could hAFS-EVs make up part of a cell-free therapy for a wide range of disorders? See STEM CELLS Translational Medicine now to find out!
Boosting Corneal Epithelial Stem/Progenitor Cells Wound Healing Capabilities
A new STEM CELLS Translational Medicine study from the labs of Patrik Danielson and Qingjun Zhou (Umeå University, Sweden) has recently explored the effects of ascorbic acid (vitamin C) on the wound healing capacity of mouse corneal epithelial stem/progenitor cells, given the high concentrations found in the corneal epithelium of various species. Encouragingly, this new study demonstrates increased corneal epithelial wound healing following vitamin C treatment, suggesting that this simple additive could greatly enhance corneal epithelial stem/progenitor cell therapy.
So that’s a wrap for this week! Please let us know your views on all the stories we have covered here on the Stem Cells Buzz, and please let us know if we have missed anything interesting! Happy reading!