Heterochromatin Protein 1β (HP1β) has distinct functions and distinct nuclear distribution in pluripotent versus differentiated cells

Background: Pluripotent embryonic stem cells (ESCs) have the unique ability to differentiate into every cell type and to self-renew. These characteristics correlate with a distinct nuclear architecture, epigenetic signatures enriched for active chromatin marks and hyperdynamic binding of structural chromatin proteins. Recently, several chromatin-related proteins have been shown to regulate ESC pluripotency and/or differentiation, yet the role of the major heterochromatin proteins in pluripotency is unknown. Results: Here we identify Heterochromatin Protein 1β (HP1β) as an essential protein for proper differentiation, and, unexpectedly, for the maintenance of pluripotency in ESCs. In pluripotent and differentiated cells HP1β is differentially localized and differentially associated with chromatin. Deletion of HP1β, but not HP1aα, in ESCs provokes a loss of the morphological and proliferative characteristics of embryonic pluripotent cells, reduces expression of pluripotency factors and causes aberrant differentiation. However, in differentiated cells, loss of HP1β has the opposite effect, perturbing maintenance of the differentiation state and facilitating reprogramming to an induced pluripotent state. Microscopy, biochemical fractionation and chromatin immunoprecipitation reveal a diffuse nucleoplasmic distribution, weak association with chromatin and high expression levels for HP1β in ESCs. The minor fraction of HP1β that is chromatin-bound in ESCs is enriched within exons, unlike the situation in differentiated cells, where it binds heterochromatic satellite repeats and chromocenters. Conclusions: We demonstrate an unexpected duality in the role of HP1β: it is essential in ESCs for maintaining pluripotency, while it is required for proper differentiation in differentiated cells. Thus, HP1β function both depends on, and regulates, the pluripotent state

A user-centred approach to unlock the potential of non-invasive BCIs: an unprecedented international translational effort

Non-invasive Mental Task-based Brain-Computer Interfaces (MT-BCIs) enable their users to interact with the environment through their brain activity alone (measured using electroencephalography for example), by performing mental tasks such as mental calculation or motor imagery. Current developments in technology hint at a wide range of possible applications, both in the clinical and non-clinical domains. MT-BCIs can be used to control (neuro)prostheses or interact with video games, among many other applications. They can also be used to restore cognitive and motor abilities for stroke rehabilitation, or even improve athletic performance.Nonetheless, the expected transfer of MT-BCIs from the lab to the marketplace will be greatly impeded if all resources are allocated to technological aspects alone. We cannot neglect the Human End-User that sits in the centre of the loop. Indeed, self-regulating one’s brain activity through mental tasks to interact is an acquired skill that requires appropriate training. Yet several studies have shown that current training procedures do not enable MT-BCI users to reach adequate levels of performance. Therefore, one significant challenge for the community is that of improving end-user training.To do so, another fundamental challenge must be taken into account: we need to understand the processes that underlie MT-BCI performance and user learning. It is currently estimated that 10 to 30% of people cannot control an MT-BCI. These people are often referred to as “BCI inefficient”. But the concept of “BCI inefficiency” is debated. Does it really exist? Or, are low performances due to insufficient training, training procedures that are unsuited to these users or is the BCI data processing not sensitive enough? The currently available literature does not allow for a definitive answer to these questions as most published studies either include a limited number of participants (i.e., 10 to 20 participants) and/or training sessions (i.e., 1 or 2). We still have very little insight into what the MT-BCI learning curve looks like, and into which factors (including both user-related and machine-related factors) influence this learning curve. Finding answers will require a large number of experiments, involving a large number of participants taking part in multiple training sessions. It is not feasible for one research lab or even a small consortium to undertake such experiments alone. Therefore, an unprecedented coordinated effort from the research community is necessary.We are convinced that combining forces will allow us to characterise in detail MT-BCI user learning, and thereby provide a mandatory step toward transferring BCIs “out of the lab”. This is why we gathered an international, interdisciplinary consortium of BCI researchers from more than 20 different labs across Europe and Japan, including pioneers in the field. This collaboration will enable us to collect considerable amounts of data (at least 100 participants for 20 training sessions each) and establish a large open database. Based on this precious resource, we could then lead sound analyses to answer the previously mentioned questions. Using this data, our consortium could offer solutions on how to improve MT-BCI training procedures using innovative approaches (e.g., personalisation using intelligent tutoring systems) and technologies (e.g., virtual reality). The CHIST-ERA programme represents a unique opportunity to conduct this ambitious project, which will foster innovation in our field and strengthen our community

Farnesylated Nuclear Proteins Kugelkern and Lamin Dm0 Affect Nuclear Morphology by Directly Interacting with the Nuclear Membrane

Nuclear shape changes are observed during a variety of developmental processes, pathological conditions and ageing. Here, the molecular mechanism is analyzed how the farnesylated nuclear proteins interact with the nuclear envelope and deform the phospholipid bilayer

Beyond in-phase and anti-phase coordination in a model of joint action

In 1985, Haken, Kelso and Bunz proposed a system of coupled nonlinear oscillators as a model of rhythmic movement patterns in human bimanual coordination. Since then, the Haken–Kelso–Bunz (HKB) model has become a modelling paradigm applied extensively in all areas of movement science, including interpersonal motor coordination. However, all previous studies have followed a line of analysis based on slowly varying amplitudes and rotating wave approximations. These approximations lead to a reduced system, consisting of a single differential equation representing the evolution of the relative phase of the two coupled oscillators: the HKB model of the relative phase. Here we take a different approach and systematically investigate the behaviour of the HKB model in the full four-dimensional state space and for general coupling strengths. We perform detailed numerical bifurcation analyses and reveal that the HKB model supports previously unreported dynamical regimes as well as bistability between a variety of coordination patterns. Furthermore, we identify the stability boundaries of distinct coordination regimes in the model and discuss the applicability of our findings to interpersonal coordination and other joint action tasks

Quantitative nucleolar proteomics reveals nuclear re-organization during stress- induced senescence in mouse fibroblast

<p>Abstract</p> <p>Background</p> <p>Nucleolus is the most prominent mammalian organelle within the nucleus which is also the site for ribosomal biogenesis. There have been many reports indicating the involvement of nucleolus in the process of aging. Several proteins related to aging have been shown to localize in the nucleolus, which suggests the role of this organelle in senescence.</p> <p>Results</p> <p>In this study, we used quantitative mass spectrometry to map the flux of proteins into and out of the nucleolus during the induction of senescence in cultured mammalian cells. Changes in the abundance of 344 nucleolar proteins in sodium butyrate-induced senescence in NIH3T3 cells were studied by SILAC (stable isotope labeling by amino acids in cell culture)-based mass spectrometry. Biochemically, we have validated the proteomic results and confirmed that B23 (nucleophosmin) protein was down-regulated, while poly (ADP-ribose) polymerase (PARP) and nuclear DNA helicase II (NDH II/DHX9/RHA) were up-regulated in the nucleolus upon treatment with sodium butyrate. Accumulation of chromatin in the nucleolus was also observed, by both proteomics and microscopy, in sodium butyrate-treated cells. Similar observations were found in other models of senescence, namely, in mitoxantrone- (MTX) treated cells and primary fibroblasts from the Lamin A knockout mice.</p> <p>Conclusion</p> <p>Our data indicate an extensive nuclear organization during senescence and suggest that the redistribution of B23 protein and chromatin can be used as an important marker for senescence.</p

Early In Vitro Differentiation of Mouse Definitive Endoderm Is Not Correlated with Progressive Maturation of Nuclear DNA Methylation Patterns

The genome organization in pluripotent cells undergoing the first steps of differentiation is highly relevant to the reprogramming process in differentiation. Considering this fact, chromatin texture patterns that identify cells at the very early stage of lineage commitment could serve as valuable tools in the selection of optimal cell phenotypes for regenerative medicine applications. Here we report on the first-time use of high-resolution three-dimensional fluorescence imaging and comprehensive topological cell-by-cell analyses with a novel image-cytometrical approach towards the identification of in situ global nuclear DNA methylation patterns in early endodermal differentiation of mouse ES cells (up to day 6), and the correlations of these patterns with a set of putative markers for pluripotency and endodermal commitment, and the epithelial and mesenchymal character of cells. Utilizing this in vitro cell system as a model for assessing the relationship between differentiation and nuclear DNA methylation patterns, we found that differentiating cell populations display an increasing number of cells with a gain in DNA methylation load: first within their euchromatin, then extending into heterochromatic areas of the nucleus, which also results in significant changes of methylcytosine/global DNA codistribution patterns. We were also able to co-visualize and quantify the concomitant stochastic marker expression on a per-cell basis, for which we did not measure any correlation to methylcytosine loads or distribution patterns. We observe that the progression of global DNA methylation is not correlated with the standard transcription factors associated with endodermal development. Further studies are needed to determine whether the progression of global methylation could represent a useful signature of cellular differentiation. This concept of tracking epigenetic progression may prove useful in the selection of cell phenotypes for future regenerative medicine applications

Hierarchical Models in the Brain

This paper describes a general model that subsumes many parametric models for continuous data. The model comprises hidden layers of state-space or dynamic causal models, arranged so that the output of one provides input to another. The ensuing hierarchy furnishes a model for many types of data, of arbitrary complexity. Special cases range from the general linear model for static data to generalised convolution models, with system noise, for nonlinear time-series analysis. Crucially, all of these models can be inverted using exactly the same scheme, namely, dynamic expectation maximization. This means that a single model and optimisation scheme can be used to invert a wide range of models. We present the model and a brief review of its inversion to disclose the relationships among, apparently, diverse generative models of empirical data. We then show that this inversion can be formulated as a simple neural network and may provide a useful metaphor for inference and learning in the brain

Mechanisms and models of somatic cell reprogramming

Whitehead Institute for Biomedical Research (Jerome and Florence Brill Graduate Student Fellowship)National Institutes of Health (U.S.) (US NIH grant RO1-CA087869)National Institutes of Health (U.S.) (US NIH grant R37-CA084198)National Science Foundation (U.S.) (NSF Graduate Research Fellowship)National Institutes of Health (U.S.) ((NIH) Kirschstein National Research Service Award,1 F32 GM099153-01A1)Vertex Pharmaceuticals Incorporated (Vertex Scholar