10 research outputs found

    IGF1-mediated human embryonic stem cell self-renewal recapitulates the embryonic niche.

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    Our understanding of the signalling pathways regulating early human development is limited, despite their fundamental biological importance. Here, we mine transcriptomics datasets to investigate signalling in the human embryo and identify expression for the insulin and insulin growth factor 1 (IGF1) receptors, along with IGF1 ligand. Consequently, we generate a minimal chemically-defined culture medium in which IGF1 together with Activin maintain self-renewal in the absence of fibroblast growth factor (FGF) signalling. Under these conditions, we derive several pluripotent stem cell lines that express pluripotency-associated genes, retain high viability and a normal karyotype, and can be genetically modified or differentiated into multiple cell lineages. We also identify active phosphoinositide 3-kinase (PI3K)/AKT/mTOR signalling in early human embryos, and in both primed and naĂŻve pluripotent culture conditions. This demonstrates that signalling insights from human blastocysts can be used to define culture conditions that more closely recapitulate the embryonic niche

    Towards clinical application of pronuclear transfer to prevent mitochondrial DNA disease

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    Mitochondrial DNA (mtDNA) mutations are maternally inherited and are associated with a broad range of debilitating and fatal diseases. Reproductive technologies designed to uncouple the inheritance of mtDNA from nuclear DNA may enable affected women to have a genetically related child with a greatly reduced risk of mtDNA disease. Here we report the first preclinical studies on pronuclear transplantation (PNT). Surprisingly, techniques used in proof-of-concept studies involving abnormally fertilized human zygotes were not well tolerated by normally fertilized zygotes. We have therefore developed an alternative approach based on transplanting pronuclei shortly after completion of meiosis rather than shortly before the first mitotic division. This promotes efficient development to the blastocyst stage with no detectable effect on aneuploidy or gene expression. After optimization, mtDNA carryover was reduced to <2% in the majority (79%) of PNT blastocysts. The importance of reducing carryover to the lowest possible levels is highlighted by a progressive increase in heteroplasmy in a stem cell line derived from a PNT blastocyst with 4% mtDNA carryover. We conclude that PNT has the potential to reduce the risk of mtDNA disease, but it may not guarantee prevention

    Towards clinical application of pronuclear transfer to prevent mitochondrial DNA disease

    No full text
    Mitochondrial DNA (mtDNA) mutations are maternally inherited and are associated with a broad range of debilitating and fatal diseases. Reproductive technologies designed to uncouple the inheritance of mtDNA from nuclear DNA may enable affected women to have a genetically related child with a greatly reduced risk of mtDNA disease. Here we report the first preclinical studies on pronuclear transplantation (PNT). Surprisingly, techniques used in proof-of-concept studies involving abnormally fertilized human zygotes were not well tolerated by normally fertilized zygotes. We have therefore developed an alternative approach based on transplanting pronuclei shortly after completion of meiosis rather than shortly before the first mitotic division. This promotes efficient development to the blastocyst stage with no detectable effect on aneuploidy or gene expression. After optimization, mtDNA carryover was reduced to <2% in the majority (79%) of PNT blastocysts. The importance of reducing carryover to the lowest possible levels is highlighted by a progressive increase in heteroplasmy in a stem cell line derived from a PNT blastocyst with 4% mtDNA carryover. We conclude that PNT has the potential to reduce the risk of mtDNA disease, but it may not guarantee prevention

    Molecular Interaction Networks to Select Factors for Cell Conversion

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    The process of identifying sets of transcription factors that can induce a cell conversion can be time-consuming and expensive. To help alleviate this, a number of computational tools have been developed which integrate gene expression data with molecular interaction networks in order to predict these factors. One such approach is Mogrify, an algorithm which ranks transcriptions factors based on their regulatory influence in different cell types and tissues. These ranks are then used to identify a nonredundant set of transcription factors to promote cell conversion between any two cell types/tissues. Here we summarize the important concepts and data sources that were used in the implementation of this approach. Furthermore, we describe how the associated web resource ( www.mogrify.net ) can be used to tailor predictions to specific experimental scenarios, for instance, limiting the set of possible transcription factors and including domain knowledge. Finally, we describe important considerations for the effective selection of reprogramming factors. We envision that such data-driven approaches will become commonplace in the field, rapidly accelerating the progress in stem cell biology.</p
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