Mitchell-Riley syndrome iPSCs exhibit reduced pancreatic endoderm differentiation due to a mutation in .

Mitchell-Riley syndrome (MRS) is caused by recessive mutations in the regulatory factor X6 gene () and is characterised by pancreatic hypoplasia and neonatal diabetes. To determine why individuals with MRS specifically lack pancreatic endocrine cells, we micro-CT imaged a 12-week-old foetus homozygous for the nonsense mutation c.1129C>T, which revealed loss of the pancreas body and tail.

Long-Term Culture of Self-renewing Pancreatic Progenitors Derived from Human Pluripotent Stem Cells.

Pluripotent stem cells have been proposed as an unlimited source of pancreatic β cells for studying and treating diabetes. However, the long, multi-step differentiation protocols used to generate functional β cells inevitably exhibit considerable variability, particularly when applied to pluripotent cells from diverse genetic backgrounds. We have developed culture conditions that support long-term self-renewal of human multipotent pancreatic progenitors, which are developmentally more proximal to the specialized cells of the adult pancreas.

An interplay between extracellular signalling and the dynamics of the exit from pluripotency drives cell fate decisions in mouse ES cells.

Embryonic Stem cells derived from the epiblast tissue of the mammalian blastocyst retain the capability to differentiate into any adult cell type and are able to self-renew indefinitely under appropriate culture conditions. Despite the large amount of knowledge that we have accumulated to date about the regulation and control of self-renewal, efficient directed differentiation into specific tissues remains elusive. In this work, we have analysed in a systematic manner the interaction between the dynamics of loss of pluripotency and Activin/Nodal, BMP4 and Wnt signalling in fate assignment during the early stages of differentiation of mouse ES cells in culture.

Single cell lineage analysis of mouse embryonic stem cells at the exit from pluripotency.

Understanding how interactions between extracellular signalling pathways and transcription factor networks influence cellular decision making will be crucial for understanding mammalian embryogenesis and for generating specialised cell types in vitro. To this end, pluripotent mouse Embryonic Stem (mES) cells have proven to be a useful model system. However, understanding how transcription factors and signalling pathways affect decisions made by individual cells is confounded by the fact that measurements are generally made on groups of cells, whilst individual mES cells differentiate at different rates and towards different lineages, even in conditions that favour a particular lineage.

A membrane-associated β-catenin/Oct4 complex correlates with ground-state pluripotency in mouse embryonic stem cells.

The maintenance of pluripotency in mouse embryonic stem cells (mESCs) relies on the activity of a transcriptional network that is fuelled by the activity of three transcription factors (Nanog, Oct4 and Sox2) and balanced by the repressive activity of Tcf3. Extracellular signals modulate the activity of the network and regulate the differentiation capacity of the cells. Wnt/β-catenin signaling has emerged as a significant potentiator of pluripotency: increases in the levels of β-catenin regulate the activity of Oct4 and Nanog, and enhance pluripotency.

Dissecting ensemble networks in ES cell populations reveals micro-heterogeneity underlying pluripotency.

Analysis of transcription at the level of single cells in prokaryotes and eukaryotes has revealed the existence of heterogeneities in the expression of individual genes within genetically homogeneous populations. This variation is an emerging hallmark of populations of Embryonic Stem (ES) cells and has been ascribed to the stochasticity associated with the biochemical events that mediate gene expression. It has been suggested that these heterogeneities play a role in the maintenance of pluripotency.

A systematic screen for protein-lipid interactions in Saccharomyces cerevisiae.

Protein-metabolite networks are central to biological systems, but are incompletely understood. Here, we report a screen to catalog protein-lipid interactions in yeast. We used arrays of 56 metabolites to measure lipid-binding fingerprints of 172 proteins, including 91 with predicted lipid-binding domains.