Forcing neural progenitor cells to cycle is insufficient to alter cell-fate decision and timing of neuronal differentiation in the spinal cord

<p>Abstract</p> <p>Background</p> <p>During the development of the nervous system, neural progenitor cells can either stay in the pool of proliferating undifferentiated cells or exit the cell cycle and differentiate. Two main factors will determine the fate of a neural progenitor cell: its position within the neuroepithelium and the time at which the cell initiates differentiation. In this paper we investigated the importance of the timing of cell cycle exit on cell-fate decision by forcing neural progenitors to cycle and studying the consequences on specification and differentiation programs.</p> <p>Results</p> <p>As a model, we chose the spinal progenitors of motor neurons (pMNs), which switch cell-fate from motor neurons to oligodendrocytes with time. To keep pMNs in the cell cycle, we forced the expression of G1-phase regulators, the D-type cyclins. We observed that keeping neural progenitor cells cycling is not sufficient to retain them in the progenitor domain (ventricular zone); transgenic cells instead migrate to the differentiating field (mantle zone) regardless of cell cycle exit. Cycling cells located in the mantle zone do not retain markers of neural progenitor cells such as Sox2 or Olig2 but upregulate transcription factors involved in motor neuron specification, including MNR2 and Islet1/2. These cycling cells also progress through neuronal differentiation to axonal extension. We also observed mitotic cells displaying all the features of differentiating motor neurons, including axonal projection via the ventral root. However, the rapid decrease observed in the proliferation rate of the transgenic motor neuron population suggests that they undergo only a limited number of divisions. Finally, quantification of the incidence of the phenotype in young and more mature neuroepithelium has allowed us to propose that once the transcriptional program assigning neural progenitor cells to a subtype of neurons is set up, transgenic cells progress in their program of differentiation regardless of cell cycle exit.</p> <p>Conclusion</p> <p>Our findings indicate that maintaining neural progenitor cells in proliferation is insufficient to prevent differentiation or alter cell-fate choice. Furthermore, our results indicate that the programs of neuronal specification and differentiation are controlled independently of cell cycle exit.</p

Structure tensor based analysis of cells and nuclei organization in tissues

International audienceMotivation: Extracting geometrical information from large 2D or 3D biomedical images is important to better understand fundamental phenomena such as morphogenesis. We address the problem of automatically analyzing spatial organization of cells or nuclei in 2D or 3D images of tissues. This problem is challenging due to the usually low quality of microscopy images as well as their typically large sizes. Results: The structure tensor is a simple and robust descriptor that was developed to analyze textures orientation. Contrarily to segmentation methods which rely on an object based modelling of images, the structure tensor views the sample at a macroscopic scale, like a continuum. We propose an original theoretical analysis of this tool and show that it allows quantifying two important features of nuclei in tissues: their privileged orientation as well as the ratio between the length of their main axes. A quantitative evaluation of the method is provided for synthetic and real 2D and 3D images. As an application, we analyze the nuclei orientation and anisotropy on multicellular tumor spheroids cryosections. This analysis reveals that cells are elongated in a privileged direction that is parallel to the boundary of the spheroid. Availability: Source codes are available at http://www.math.univ-toulouse.fr/~weiss

Deep and Clear Optical Imaging of Thick Inhomogeneous Samples

Inhomogeneity in thick biological specimens results in poor imaging by light microscopy, which deteriorates as the focal plane moves deeper into the specimen. Here, we have combined selective plane illumination microscopy (SPIM) with wavefront sensor adaptive optics (wao). Our waoSPIM is based on a direct wavefront measure using a Hartmann-Shack wavefront sensor and fluorescent beads as point source emitters. We demonstrate the use of this waoSPIM method to correct distortions in three-dimensional biological imaging and to improve the quality of images from deep within thick inhomogeneous samples

Live cell division dynamics monitoring in 3D large spheroid tumor models using light sheet microscopy

<p>Abstract</p> <p>Background</p> <p>Multicellular tumor spheroids are models of increasing interest for cancer and cell biology studies. They allow considering cellular interactions in exploring cell cycle and cell division mechanisms. However, 3D imaging of cell division in living spheroids is technically challenging and has never been reported.</p> <p>Results</p> <p>Here, we report a major breakthrough based on the engineering of multicellular tumor spheroids expressing an histone H2B fluorescent nuclear reporter protein, and specifically designed sample holders to monitor live cell division dynamics in 3D large spheroids using an home-made selective-plane illumination microscope.</p> <p>Conclusions</p> <p>As illustrated using the antimitotic drug, paclitaxel, this technological advance paves the way for studies of the dynamics of cell divion processes in 3D and more generally for the investigation of tumor cell population biology in integrated system as the spheroid model.</p

Learning the cell cycle with a game: Virtual experiments in cell biology

Cell Cycle Learn (CCL) is a learning game designed for undergraduate students in Biology to learn common knowledge about the cell-division cycle along with practical skills related with setting up an experiment and the scientific method in general. In CCL, learners are guided through the process of formulating hypotheses, conducting virtual experiments and analysing the results in order to validate or invalidate the hypotheses. The game has been designed in the University of Toulouse and introduced last year as part of the curriculum of a cellular biology class. This paper presents early results of an evaluation of the game enabled by questionnaires filled by the participants and game data collected during the training sessions. The results demonstrate with examples that both types of data can be used to assess the game's utility

Genetic variability of transcript abundance in pig peri-mortem skeletal muscle: eQTL localized genes involved in stress response, cell death, muscle disorders and metabolism

<p>Abstract</p> <p>Background</p> <p>The genetics of transcript-level variation is an exciting field that has recently given rise to many studies. Genetical genomics studies have mainly focused on cell lines, blood cells or adipose tissues, from human clinical samples or mice inbred lines. Few eQTL studies have focused on animal tissues sampled from outbred populations to reflect natural genetic variation of gene expression levels in animals. In this work, we analyzed gene expression in a whole tissue, pig skeletal muscle sampled from individuals from a half sib F2 family shortly after slaughtering.</p> <p>Results</p> <p>QTL detection on transcriptome measurements was performed on a family structured population. The analysis identified 335 eQTLs affecting the expression of 272 transcripts. The ontologic annotation of these eQTLs revealed an over-representation of genes encoding proteins involved in processes that are expected to be induced during muscle development and metabolism, cell morphology, assembly and organization and also in stress response and apoptosis. A gene functional network approach was used to evidence existing biological relationships between all the genes whose expression levels are influenced by eQTLs. eQTLs localization revealed a significant clustered organization of about half the genes located on segments of chromosome 1, 2, 10, 13, 16, and 18. Finally, the combined expression and genetic approaches pointed to putative <it>cis</it>-drivers of gene expression programs in skeletal muscle as <it>COQ4 </it>(SSC1), <it>LOC100513192 </it>(SSC18) where both the gene transcription unit and the eQTL affecting its expression level were shown to be localized in the same genomic region. This suggests <it>cis</it>-causing genetic polymorphims affecting gene expression levels, with (e.g. <it>COQ4</it>) or without (e.g. <it>LOC100513192</it>) potential pleiotropic effects that affect the expression of other genes (cluster of <it>trans</it>-eQTLs).</p> <p>Conclusion</p> <p>Genetic analysis of transcription levels revealed dependence among molecular phenotypes as being affected by variation at the same loci. We observed the genetic variation of molecular phenotypes in a specific situation of cellular stress thus contributing to a better description of muscle physiologic response. In turn, this suggests that large amounts of genetic variation, mediated through transcriptional networks, can drive transient cell response phenotypes and contribute to organismal adaptative potential.</p

Lightsheet fluorescence microscopy images deblurring with background estimation

International audienceThe deblurring of microscopy images has received a lot of attention in past decades, especially with regularisation involving the Total Variation semi-norm. In this paper we propose the evaluation of 3D point spread function space-invariant restauration methods with background estimation for 3D light sheet fluorescence microscopy images. A 3D image model for synthetic static multicellular tumor spheroids is introduced, allowing a more realistic evaluation for the proposed methods, underlining better results with low SNR values. Encouraging results on real data of cancer cells cultured as multicellular tumor spheroids are also presented

Restauration 3D en imagerie fluorescente par feuille de lumière avec implantation sur GPU

International audienceLight sheet fluorescence microscopy is a recent and promising technology which allows a selective illumination of biologic samples. For this modality we propose to use a GPU-implanted fast deconvolution algorithm, to be used with fusion methods. The proposed algorithm can deblur an image with1000×1000×100voxels in less than 5 minutesL’imagerie microscopique à feuille de lumière est une technologie très récente et prometteuse permettant une illumination sélective des échantillons biologiques étudiés. Pour cette technique nous proposons l’implantation sur GPU d’un algorithme de déconvolution rapide, complétant des méthodes par fusion. L’algorithme proposé permet en pratique de déconvoluer des images de taille1000×1000×100en des temps inférieurs à 5 minutes