Essential role for poly (ADP-ribosyl)ation in mouse preimplantation development

BACKGROUND: Poly (ADP-ribosyl)ation is a covalent modification of many nuclear proteins. It has a strong chromatin modifying potential involved in DNA repair, transcription and replication. Its role during preimplantation development is unknown. RESULTS: We have observed strong but transient synthesis of poly ADP-ribose polymers on decondensing chromosomes of fertilized and parthenogenetically activated mouse oocytes. Inhibition of this transient upregulation with a specific enzyme inhibitor, 3-aminobenzamide, has long-term effects on the postimplantation development of the embryos. In addition, inhibition of poly (ADP-ribosyl)ation at the 4–8 cell stage selectively blocks morula compaction. CONCLUSION: These observations suggest that poly (ADP-ribosyl)ation is involved in the epigenetic chromatin remodeling in the zygote

Bistable Cell Fate Specification as a Result of Stochastic Fluctuations and Collective Spatial Cell Behaviour

BACKGROUND: In culture, isogenic mammalian cells typically display enduring phenotypic heterogeneity that arises from fluctuations of gene expression and other intracellular processes. This diversity is not just simple noise but has biological relevance by generating plasticity. Noise driven plasticity was suggested to be a stem cell-specific feature. RESULTS: Here we show that the phenotypes of proliferating tissue progenitor cells such as primary mononuclear muscle cells can also spontaneously fluctuate between different states characterized by the either high or low expression of the muscle-specific cell surface molecule CD56 and by the corresponding high or low capacity to form myotubes. Although this capacity is a cell-intrinsic property, the cells switch their phenotype under the constraints imposed by the highly heterogeneous microenvironment created by their own collective movement. The resulting heterogeneous cell population is characterized by a dynamic equilibrium between "high CD56" and "low CD56" phenotype cells with distinct spatial distribution. Computer simulations reveal that this complex dynamic is consistent with a context-dependent noise driven bistable model where local microenvironment acts on the cellular state by encouraging the cell to fluctuate between the phenotypes until the low noise state is found. CONCLUSIONS: These observations suggest that phenotypic fluctuations may be a general feature of any non-terminally differentiated cell. The cellular microenvironment created by the cells themselves contributes actively and continuously to the generation of fluctuations depending on their phenotype. As a result, the cell phenotype is determined by the joint action of the cell-intrinsic fluctuations and by collective cell-to-cell interactions

The Origin of Phenotypic Heterogeneity in a Clonal Cell Population In Vitro

BACKGROUND: The spontaneous emergence of phenotypic heterogeneity in clonal populations of mammalian cells in vitro is a rule rather than an exception. We consider two simple, mutually non-exclusive models that explain the generation of diverse cell types in a homogeneous population. In the first model, the phenotypic switch is the consequence of extrinsic factors. Initially identical cells may become different because they encounter different local environments that induce adaptive responses. According to the second model, the phenotypic switch is intrinsic to the cells that may occur even in homogeneous environments. PRINCIPAL FINDINGS: We have investigated the “extrinsic” and the “intrinsic” mechanisms using computer simulations and experimentation. First, we simulated in silico the emergence of two cell types in a clonal cell population using a multiagent model. Both mechanisms produced stable phenotypic heterogeneity, but the distribution of the cell types was different. The “intrinsic” model predicted an even distribution of the rare phenotype cells, while in the “extrinsic” model these cells formed small clusters. The key predictions of the two models were confronted with the results obtained experimentally using a myogenic cell line. CONCLUSIONS: The observations emphasize the importance of the “ecological” context and suggest that, consistently with the “extrinsic” model, local stochastic interactions between phenotypically identical cells play a key role in the initiation of phenotypic switch. Nevertheless, the “intrinsic” model also shows some other aspects of reality: The phenotypic switch is not triggered exclusively by the local environmental variations, but also depends to some extent on the phenotypic intrinsic robustness of the cells

Développement et mise en place d’un système de détection moléculaire pour la tuberculose bovine

La tuberculose bovine (TB) est une maladie zoonotique à déclaration obligatoire justifiant un engagement financier et humain de l’Etat sur des actions de surveillance et de lutte en élevage, dont l’agent causal majeur est Mycobacterium bovis. Avec un taux de prévalence au niveau du cheptel faible (< 0.01%), la France est considérée indemne de tuberculose bovine (OIT) par l’Union Européenne depuis 2001. Néanmoins, depuis 2004 avec l’intensification du plan de surveillance, il est observé une recrudescence de la TB dans certaines régions mettant ainsi en péril ce statut OIT. M. bovis, dont le réservoir principal est le bovin, est capable d’infecter un très large spectre de mammifères dont l’homme et de persister dans l’environnement. La circulation de la TB est multifactorielle, le rôle de la faune sauvage et de l’environnement restant à déterminer. Le plan de surveillance de la TB chez les bovins est basé sur un système de dépistage/abattage programmé au niveau national, avec l’inspection/détection de lésions évocatrices de TB à l’abattoir, qui sont prélevées, analysées par histologie et mises en culture (selon la méthode officielle de la Directive européenne 64/432). M. bovis est une bactérie à croissance lente (3 mois), ce qui implique une chaine de diagnostic pouvant aller jusqu’à 6 mois avec des outils diagnostic ante-/post-mortem, qui présentent souvent un manque de spécificité au regard de la diversité du genre Mycobacterium. Dans un contexte de faible prévalence, le diagnostic de la TB doit être rapide, fiable et simple dans le but de faciliter la gestion de la crise et limiter les pertes économiques. Dans ce mémoire de diplôme EPHE, je présente l’élaboration d’un système de détection et d’identification des mycobactéries impliquées ou interférant dans le diagnostic de la TB à l’aide d’une méthode PCR et du spoligotypage. L’identification par PCR en temps réel des bactéries repose sur l’amplification de 9 cibles génétiques selon une validation réalisée suivant la norme NF-U-47-600. L’analyse des échantillons par spoligotypage a été axée sur l’optimisation de la méthode pour la rendre applicable directement à des ADN extraits de prélèvements (animal ou environnemental).L’association des 2 méthodes de détection moléculaire a permis d’une part d’augmenter la sensibilité du diagnostic chez l’animal avec l’identification dans 95% des cas des mycobactéries tuberculeuses incriminées mais également l’identification d’autres actinomycétales responsables de réactions croisées dans les tests ante-mortem. Les méthodes développées ont par ailleurs permis la réalisation d’essais préliminaires dans l’étude de l’élaboration d’un vaccin oral chez les blaireaux. Il a permis également la détection de l’agent causal de la maladie dans des prélèvements de l’environnement prouvant ainsi le rôle de ceux-ci dans des cycles de transmission multifactoriels-multi-hôtes.En conclusion, les méthodes de détection moléculaire développées dans le cadre de ce projet permet au Laboratoire National de Référence (LNR) d’accélérer la chaine de diagnostic et de gestion de la maladie ainsi que d’améliorer les connaissances sur les mécanismes de transmission de la tuberculose bovine

Hypoxic culture conditions enhance the generation of regulatory T cells

International audienc

Stochastic Fluctuations and Distributed Control of Gene Expression Impact Cellular Memory

International audienceDespite the stochastic noise that characterizes all cellular processes the cells are able to maintain and transmit to their daughter cells the stable level of gene expression. In order to better understand this phenomenon, we investigated the temporal dynamics of gene expression variation using a double reporter gene model. We compared cell clones with transgenes coding for highly stable mRNA and fluorescent proteins with clones expressing destabilized mRNA-s and proteins. Both types of clones displayed strong heterogeneity of reporter gene expression levels. However, cells expressing stable gene products produced daughter cells with similar level of reporter proteins, while in cell clones with short mRNA and protein half-lives the epigenetic memory of the gene expression level was completely suppressed. Computer simulations also confirmed the role of mRNA and protein stability in the conservation of constant gene expression levels over several cell generations. These data indicate that the conservation of a stable phenotype in a cellular lineage may largely depend on the slow turnover of mRNA-s and proteins

The “extrinsic” model.

<p><b>A</b>: Simulations with the “extrinsic” model using increasing values of N_ex. Note the increasing proportion and clustering of type A (red) cells with increasing N_ex. In all simulations N_{max death} = 40 was used. <b>B</b>: Analysis of type A cell distribution as a function of average migration velocity and varying N_ex using the standardized nearest neighbour distance. Type A cells were clustered (<i>w</i><1) at all but small average velocity values at all N_ex values analysed.</p

The “hybrid extrinsic-intrinsic” model.

<p><b>A.</b> Cells migrate, divide and die under the same conditions as in the “extrinsic” and “intrinsic” models. The phenotypic switch of each cell is dependent on the local cell density as in the “extrinsic” model, but the cells encountering a favourable microenvironment undergo phenotypic change with probabilities p_AtoB and p_BtoA. B: Results of a typical simulation of the “hybrid” model during the growth phase and at equilibrium. Note the simultaneous presence of small clusters and dispersed single type A cells. p_AtoB = 0.7 and p_BtoA = 0.4. C: The distribution of the number of neighbours around the A and B cells (left and right respectively) in the hybrid model. The average number of neighbours and the standard deviation are indicated for each panel. Note the more dispersed distribution of type A cell neighbours. D: Analysis of the spatial distribution randomness of SP and MP cells using Ripley's L statistics. The upper panel shows the type A cell L-function (red line) with values larger than 0 and outside the range defined by the upper-and lower-envelope functions (black line) (this indicates significant clustering of type A cells at small R distances). The type B cells (green line) are randomly distributed, because the L(h) values are close to 0 at all scales (R).</p