Regulation of gene expression is a fundamental process in living organisms. This project develops and uses tools allowing the visualization of gene expression, directly in living cells and in real time.
Clonal cells sharing an identical environment differ from each other at the phenotypic and gene expression levels. An important part of this variability comes from stochastic variation at the level of gene transcription and this contributes to phenotypic variability at the level of cells and organisms. However, because of the lack of appropriate technologies, these phenomenon are not well understood. Similarly, despite the fact that transcription is studied for many years and is a key step of gene expression, the dynamic of this process in live cells is poorly characterized.
Understanding transcription at the level of single cells requires tools able to detect and quantify single molecules of mRNAs, both in live and fixed cells. We have developped tools meeting these requirements, which use fluorescent microscopy. Thus, it is now possible to label specific mRNAs in live or fixed cells and to detect every molecule present within cells with a good spatial resolution (50-100nm in fixed cells) and a good temporal resolution (10 images/seconds). For this, we have worked on the labelling method, on image acquisition, and on image analysis algorithms.
In fixed cells we are able to analyze population of hundreds of cells and to count how many mRNA molecules produced from a given gene are present. In live cells, we can visualize mRNA synthesis in real time, as well as the movements of single molecules of RNA polymerases. We have shown that transcription is performed by groups of RNA polymerases, which simulatneously transcribe a given gene. We have measured the size of these groups and the frequency at which they are formed. We have observed that, depending on the case, transcriptional regulation is achieved either by increasing the size of the group of RNA polymerases, of the frequency of the groups. This mode of transcription by groups of polymerases contributes to cell-to-cell variability by increasing the stochastic nature of transcription.
This projects opens new perspectives to understand (i) the regulation of genes implicated in cancer like c-fos, (ii) the phenotypic diversity often observed in population of cancer cells, and (iii) the behavior of some viruses.
FISH-quant: automatic counting of transcripts in 3D FISH images. Nat Methods. 2013, 10:277-8. Mueller F, Senecal A, Tantale K, Marie-Nelly H, Ly N, Collin O, Basyuk E, Bertrand E*, Darzacq X*, Zimmer C*. *: co-corresponding authors.
This publication describes a software that analyses images obtained after detection single mRNA molecules in fixed cells by in situ hybridization.
Real-Time Dynamics of RNA Polymerase II Clustering in Live Human Cells. Science. 2013 Jul 4. [Epub ahead of print]. Cisse II, Izeddin I, Causse SZ, Boudarene L, Senecal A, Muresan L, Dugast-Darzacq C, Hajj B, Dahan M, Darzacq X.
This publication describes the movements of single molecules of RNA polymerase II in live cells. It goes against a previous model, in which many genes were grouped spatially to create transcriptional factories.
Gene expression is a fundamental biological process that was analyzed by decades of genetic and biochemical experiments. As a result, the machineries involved are well characterized biochemically and structurally. However, how gene expression really works in the cell is not well understood. Despite the fairly recent developments of live cell imaging techniques, these have already revealed a number of unexpected results. For instance, it has become apparent that transcription is a discontinuous process, with individual genes pulsing between on and off states, leading to new concepts, such as "transcriptional noise", which represents the cell-to-cell variation in mRNA copy number. More generally, given the small number of molecules per cell involved in gene expression pathways (one or two DNA templates, few molecules of mRNAs), all gene expression processes must be understood at the level of single molecules. Thus, a great challenge is now to measure the activity of single molecular machines in their cellular context.
Techniques to analyze RNA and DNA molecules at the cellular level exist, but in this proposal, we intend to make a technical leap forward to: (i) bring position and distance measurements to the 10-20 nm resolution scale, as opposed to the 200 nm resolution of conventional microscopy; (ii) take the analysis down to the level of single molecules. We will join our distinct expertise to create these tools, and will use them to address three central issues:
First, our ability to point fluorophores with a precision far beyond the diffraction limit will be used to determine mRNA topology, whether it is compact, elongated, or circular. We know that mRNA is circularized to initiate translation, but little other data is available on mRNA topology. We will measure in fixed cells the distances between the 5' and 3' ends of a reporter mRNA, and between one end and a middle region. This will tell us whether the shape of an mRNA depends on its cellular localization. Is mRNA more compact in the nucleoplasm to facilitate diffusion ? Is it unwound to cross the pores, or does it go through as a packed particle ? What is the mRNA topology in the cytoplasm, and in particular, can we visualize circular mRNAs, thereby identifying translated molecules ?
Second, we will analyze the activity of isolated molecules of RNA polymerase II at the level of single-copy genes. To this end, we will use the stochastic fluctuations in transcription initiation to capture the activity of single or very small groups of RNA polymerases on a reporter gene. From this data, we will derive fundamental quantities including: frequency and distribution of initiation events over time; mean and instantaneous elongation rates; frequencies and length of pauses; rates and distribution of 3'-end formation. Results will tell whether these processes are deterministic or stochastic, and to what extent they are regulated. In particular, elongation rates and pause sites have been proposed to regulate alternative splicing and alternative polyA site usage, but there are no direct assays to measure this at the moment.
Third, we will analyze the links between the nuclear position of a gene, its transcriptional activity, and its ability to form loops with its 5' and 3' ends in contact. In yeast, Gal genes relocate to the periphery upon induction. Furthermore, these genes form 5'-3' loops, and these are important for transcriptional memory, i.e. reactivation following a first induction. While gene positioning in yeast has been linked to activity, simultaneous and precise measurements of position and activity by quantitative microscopy methods are still lacking. Similarly, gene topology has been addressed with biochemical methods, which are not sufficiently quantitative and yield only population averages. We will use high resolution imaging approaches to quantify the links between gene positioning, looping, and gene activity.
Monsieur Edouard BERTRAND (CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE - DELEGATION REGIONALE LANGUEDOC-ROUSSILLON) – Edouard.Bertrand@igmm.cnrs.fr
The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.
ENS CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE - DELEGATION REGIONALE ILE-DE-FRANCE SECTEUR PARIS B
CNRS CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE - DELEGATION REGIONALE ILE-DE-FRANCE SECTEUR OUEST ET NORD
CNRS-IGMM CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE - DELEGATION REGIONALE LANGUEDOC-ROUSSILLON
Help of the ANR 550,000 euros
Beginning and duration of the scientific project: - 36 Months