Single Cell Analysis Reveals Concomitant Transcription of Pluripotent and Lineage Markers During the Early Steps of Differentiation of Embryonic Stem Cells

Single-cell RNA-seq reveals novel mitochondria-related musculoskeletal cell populations during adult axolotl limb regeneration process

While the capacity to regenerate tissues or limbs is limited in mammals, including humans, axolotls are able to regrow entire limbs and major organs after incurring a wound. The wound blastema has been extensively studied in limb regeneration. However, due to the inadequate characterization of ECM and cell subpopulations involved in the regeneration process, the discovery of the key drivers for human limb regeneration remains unknown. In this study, we applied large-scale single-cell RNA sequencing to classify cells throughout the adult axolotl limb regeneration process, uncovering a novel regeneration-specific mitochondria-related cluster supporting regeneration through energy providing and the ECM secretion (COL2+) cluster contributing to regeneration through cell-cell interactions signals. We also discovered the dedifferentiation and re-differentiation of the COL1+/COL2+ cellular subpopulation and exposed a COL2-mitochondria subcluster supporting the musculoskeletal system regeneration. On the basis of these findings, we reconstructed the dynamic single-cell transcriptome of adult axolotl limb regenerative process, and identified the novel regenerative mitochondria-related musculoskeletal populations, which yielded deeper insights into the crucial interactions between cell clusters within the regenerative microenvironment.

Of numbers and movement - understanding transcription factor pathogenesis by advanced microscopy

Transcription factors (TFs) are life-sustaining and, therefore, the subject of intensive research. By regulating gene expression, TFs control a plethora of developmental and physiological processes, and their abnormal function commonly leads to various developmental defects and diseases in humans. Normal TF function often depends on gene dosage, which can be altered by copy-number variation or loss-of-function mutations. This explains why TF haploinsufficiency (HI) can lead to disease. Since aberrant TF numbers frequently result in pathogenic abnormalities of gene expression, quantitative analyses of TFs are a priority in the field. In vitro single-molecule methodologies have significantly aided the identification of links between TF gene dosage and transcriptional outcomes. Additionally, advances in quantitative microscopy have contributed mechanistic insights into normal and aberrant TF function. However, to understand TF biology, TF-chromatin interactions must be characterised in vivo, in a tissue-specific manner and in the context of both normal and altered TF numbers. Here, we summarise the advanced microscopy methodologies most frequently used to link TF abundance to function and dissect the molecular mechanisms underlying TF HIs. Increased application of advanced single-molecule and super-resolution microscopy modalities will improve our understanding of how TF HIs drive disease.

A Monte Carlo method for in silico modeling and visualization of Waddington's epigenetic landscape with intermediate details

Waddington's epigenetic landscape is a classic metaphor for describing the cellular dynamics during the development modulated by gene regulation. Quantifying Waddington's epigenetic landscape by mathematical modeling would be useful for understanding the mechanisms of cell fate determination. A few computational methods have been proposed for quantitative modeling of landscape; however, to model and visualize the landscape of a high dimensional gene regulatory system with realistic details is still challenging. Here, we propose a Monte Carlo method for modeling the Waddington's epigenetic landscape of a gene regulatory network (GRN). The method estimates the probability distribution of cellular states by collecting a large number of time-course simulations with random initial conditions. By projecting all the trajectories into a 2-dimensional plane of dimensions i and j, we can approximately calculate the quasi-potential U(x_i,x_j,∗)=-ln P(x_i,x_j,∗), where P(x_i,x_j,∗) is the estimated probability of an equilibrium steady state or a non-equilibrium state. Compared to the state-of-the-art methods, our Monte Carlo method can quantify the global potential landscape (or emergence behavior) of GRN for a high dimensional system. The potential landscapes show that not only attractors represent stability, but the paths between attractors are also part of the stability or robustness of biological systems. We demonstrate the novelty and reliability of our method by plotting the potential landscapes of a few published models of GRN.

Enhanced Induction of Definitive Endoderm Differentiation of Mouse Embryonic Stem Cells in Simulated Microgravity

Directed in vitro differentiation of pluripotent stem cells toward definitive endoderm (DE) offers great research and therapeutic potential since these cells can further differentiate into cells of the respiratory and gastrointestinal tracts, as well as associated organs such as pancreas, liver, and thyroid. We hypothesized that culturing mouse embryonic stem cells (mESCs) under simulated microgravity (SMG) conditions in rotary bioreactors (BRs) will enhance the induction of directed DE differentiation. To test our hypothesis, we cultured the cells for 6 days in two-dimensional monolayer colony cultures or as embryoid bodies (EBs) in either static conditions or, dynamically, in the rotary BRs. We used flow cytometry and quantitative polymerase chain reaction to analyze the expression of marker proteins and genes, respectively, for pluripotency (Oct3/4) and mesendodermal (Brachyury T), endodermal (FoxA2, Sox17, CxCr4), and mesodermal (Vimentin, Meox1) lineages. Culture in the form of EBs in maintenance media in the presence of leukemia inhibitory factor, in static or SMG conditions, induced expression of some of the differentiation markers, suggesting heterogeneity of the cells. This is in line with previous studies showing that differentiation is initiated as cells are aggregated into EBs even without supplementing differentiation factors to the media. Culturing EBs in static conditions in differentiation media (DM) in the presence of activin A reduced Oct3/4 expression and significantly increased Brachyury T and CxCr4 expression, but downregulated FoxA2 and Sox17. However, culturing in SMG BRs in DM upregulated Brachyury T and all of the DE markers and reduced Oct3/4 expression, indicating the advantage of dynamic cultures in BRs to specifically enhance directed DE differentiation. Given the potential discrepancies between the SMG conditions on earth and actual microgravity conditions, as observed in other studies, future experiments in space flight are required to validate the effects of reduced gravity on mESC differentiation.

Unravelling the complexity of signalling networks in cancer: A review of the increasing role for computational modelling

Cancer induction is a highly complex process involving hundreds of different inducers but whose eventual outcome is the same. Clearly, it is essential to understand how signalling pathways and networks generated by these inducers interact to regulate cell behaviour and create the cancer phenotype. While enormous strides have been made in identifying key networking profiles, the amount of data generated far exceeds our ability to understand how it all "fits together". The number of potential interactions is astronomically large and requires novel approaches and extreme computation methods to dissect them out. However, such methodologies have high intrinsic mathematical and conceptual content which is difficult to follow. This review explains how computation modelling is progressively finding solutions and also revealing unexpected and unpredictable nano-scale molecular behaviours extremely relevant to how signalling and networking are coherently integrated. It is divided into linked sections illustrated by numerous figures from the literature describing different approaches and offering visual portrayals of networking and major conceptual advances in the field. First, the problem of signalling complexity and data collection is illustrated for only a small selection of known oncogenes. Next, new concepts from biophysics, molecular behaviours, kinetics, organisation at the nano level and predictive models are presented. These areas include: visual representations of networking, Energy Landscapes and energy transfer/dissemination (entropy); diffusion, percolation; molecular crowding; protein allostery; quinary structure and fractal distributions; energy management, metabolism and re-examination of the Warburg effect. The importance of unravelling complex network interactions is then illustrated for some widely-used drugs in cancer therapy whose interactions are very extensive. Finally, use of computational modelling to develop micro- and nano- functional models ("bottom-up" research) is highlighted. The review concludes that computational modelling is an essential part of cancer research and is vital to understanding network formation and molecular behaviours that are associated with it. Its role is increasingly essential because it is unravelling the huge complexity of cancer induction otherwise unattainable by any other approach.

Reconstructing Lineage Hierarchies of Mouse Uterus Epithelial Development Using Single-Cell Analysis

The endometrial layer comprises luminal and glandular epithelia that both develop from the same simple layer of fetal uterine epithelium. Mechanisms of uterine epithelial progenitor self-renewal and differentiation are unclear. This study aims to systematically analyze the molecular and cellular mechanisms of uterine epithelial development by single-cell analysis. An integrated set of single-cell transcriptomic data of uterine epithelial progenitors and their differentiated progenies is provided. Additionally the unique molecular signatures of these cells, characterized by sequential upregulation of specific epigenetic and metabolic activities, and activation of unique signaling pathways and transcription factors, were also investigated. Finally a unique subpopulation of early progenitor, as well as differentiated luminal and glandular lineages, were identified. A complex cellular hierarchy of uterine epithelial development was thus delineated. Our study therefore systematically decoded molecular markers and a cellular program of uterine epithelial development that sheds light on uterine developmental biology.

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Single-cell transcriptome of mouse uterine epithelial development is provided

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Epithelial progenitors during early development of uterine epithelia is identified

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Molecular cascades orchestrating uterine epithelial development are dissected

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Cellular hierarchical map of uterine epithelial development is reconstructed