Background
Cells in the human body continually receive mechanical signals (pressure, stretching, compression, etc.) from their surroundings and must respond appropriately to them. This process, known as mechano-transduction, is not yet fully understood. A key emerging idea is that the cell nucleus and the DNA inside it play a crucial role in how cells "sense" and respond to environmental changes. Until now, there hasn't been enough data to study this process in detail.
Our group, the Paulsen and Progida group, has recently produced groundbreaking data that, for the first time, provides a view of how the cell nucleus and the DNA inside it reorganize when cells experience different levels of compressive forces (see illustration below). These data show significant changes in the three-dimensional (3D) organization of genes and subsequent alterations in gene expression. However, we still need to understand how the entire genome is reorganized in response to these compressive forces. Understanding genome 3D reorganization in response to mechanical forces is vital, as it can uncover insights into cellular behavior, disease mechanisms, and maybe even reveal new therapeutic targets for conditions like cancer (which often has a compromised response to mechanical inputs).
Fig. 1: A: Illustration of how a cell can receive compressive forces from its environment. The nucleus is shown, with chromosomes indicated with distinct colors. B: Illustration/model of how compression can lead to three-dimensional redistribution of chromosomes and their genes, with consequences on gene expression. Fig. adapted from Uhler & Shivashankear (2018)
Aim of this Master project
In this exciting bioinformatics and computational project, the student (together with the supervisor) will generate models of the 3D genome in cells subjected to compressive forces. Supported by the supervisor and other researchers in the Paulsen and Progida groups, the student will develop and use computational modeling tools to characterize and analyze how cell compression can lead to changes in 3D genome organization. This is an opportunity to contribute to characterization of new, unknown cellular processes in the human body.
Prerequisites
- The student will be trained in understanding the data, and in the tools we use to analyze the data.
- The student needs to know some programming (for example Python and/or C++) and must have an interest in computational analyses
Contact & questions
Jonas Paulsen (group leader and supervisor): jonas.paulsen@ibv.uio.no, tlf: 41147241
Cinzia Progida: cinzia.progida@ibv.uio.no