Imaging and Modeling - CNRS, URA 2582  

  HEADChristophe ZIMMER (Dr.) /
  MEMBERSChristophe ZIMMER (Dr.), chargé de recherches IP / Tarn DUONG (Dr.), postdoc IP / Mickaël LELEK (Dr.), ingénieur de recherches IP / Marie-Anne LIN, secrétaire de direction / Mathieu SORNAY, stagiaire (étudiant M1) / Emmanuelle DORNE, stagiaire (étudiante M1) / Anne DE SEPTENVILLE, stagiaire (étudiante M2)

  Annual Report

Our group develops computational techniques to describe and model cell biological processes based on imaging data. We currently focus on the three-dimensional organization of the genome inside the nucleus, which plays a role in gene expression, DNA repair and replication. Despite its functional importance, nuclear organization remains largely uncharted, owing to several technical limitations such as the limited resolution of light microscopy and insufficient statistics. We therefore develop new techniques to describe the nuclear architecture with higher accuracy, using a combination of high-throughput image analysis and state of the art optical microscopy, and thanks to collaborations with wet biology groups. Our goal, beyond a quantitative description, is a mechanistic and predictive model of chromosome organization and dynamics.

Another related focus of our group is the development of super-resolution microscopy techniques based on the accurate positioning of individual photoswitchable molecules.

Results obtained in 2008: High resolution mapping of gene territories in living yeast cells

We have developed and validated a computational technique, which automatically analyses images of thousands of nuclei and generates high resolution maps of gene territories in the yeast Saccharomyces cerevisiae (Berger et al., 2008). Applying this method, we found that several genomic loci are confined to ’gene territories’ much smaller than the nucleus, which can be remodelled during transcriptional activation. We revealed a territorial organization of genes significantly more pronounced than observed before. These results and the technique are likely to have important implications for understanding gene expression and DNA repair. This work also shows how mere computational means can overcome standard limitations of light microscopy.

Keywords: Computational imaging, nuclear organization, yeast, super-resolution microscopy


Figure 1: Territorial organization of genes in the yeast nucleus. The centre of the image shows probability density maps of several genomic loci (including a telomere a green and a ribosomal gene in yellow). The background shows typical images of yeast cells from which these maps were automatically computed. The circle indicates the approximate nuclear size, with a radius of 1 µm.


Berger, A.B., Cabal, G.G., Fabre, E., Duong, T., Buc, H., Nehrbass, U., Olivo-Marin, J.C., Gadal, O., and Zimmer, C. (2008). High-resolution statistical mapping reveals gene territories in live yeast. Nature Methods, vol. 5 , pp. 1031-37. PMID: 18978785.

Cabal, G., Genovesio, A., Rodriguez-Navarro, S., Zimmer, C., Gadal, O., Lesne, A., Buc, H., Feuerbach-Fournier, F., Olivo-Marin, J.-C., Hurt, E.C., and Nehrbass, U. (2006). SAGA interacting factors confine sub-diffusion of transcribed genes to the nuclear envelope. Nature, 441, 770-3. PMID: 16760982.

B. Zhang, J. Enninga, J-C. Olivo-Marin and C. Zimmer(2006). Automated super-resolution detection of Fluroescent Rods in 2D, Proc. IEEE International Symposium on Biomedical Imaging, 1296-99.

M. de Moraes Marim, B. Zhang, J-C. Olivo-Marin, C. Zimmer (2008). Improving single particle localization with an empirically calibrated Gaussian kernel. IEEE International Symposium on Biomedical Imaging, pp. 1003-1006.

C. Zimmer, B. Zhang, A. Dufour, A. Thebaud, S. Berlemont, V. Meas-Yedid and J-C. Olivo-Marin (2006). On the digital trail of mobile cells, IEEE Signal Processing Magazine, vol. 23, pp. 54-62.

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Activity Reports 2009 - Institut Pasteur
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