Physical model of the cell nucleus mechanics: towards a chip-based diagnostic of premature cellular aging

Host laboratory and collaborators

Emmanuèle Helfer / CINaM /

Jean-François Rupprecht / CPT /


Even in good health cells progressively decline in their functions, in a normal process called cellular aging (or senescence). The process may happen prematurely in some pathological diseases, inducing symptoms akin to diabetes and/or cardiovascular dysfunction. Studies of rare premature aging syndromes like Progeria have identified a pathway to senescence related to a defect in lamin A, a major constituent of the nuclear lamina. This protein meshwork, part of the nuclear envelop, controls the shape of the cell nucleus and provides its mechanical rigidity. Using microfluidic tools and physics-based modelling, we will establish the correlation between well-characterized senescence of premature aging syndromes and the mechanical properties of nuclei. Combination with genetic and cell biology approaches will allow studying mechanotransductive effects, i.e. phenotype alterations. Experimental results will be integrated into a multiscale rheological model, in order to establish a phase diagram between rheological properties and pathology level.


Premature aging, nucleus mechanics, lamin mutations, mechanotransduction, microfluidics, viscoelasticity, theory and numerical simulations, machine learning


The aim of the project is to correlate the well-scored senescence of premature aging syndromes with the cell nucleus rheological properties. From combined experiments and modelling on cells from patients affected by these pathologies we will establish a complete set of quantitative, biological and physical data and infer mechanical criteria, beyond the usual nucleus shape one, for cell type classification.

Proposed approach (experimental / theoretical / computational)

Cell lines with controlled senescence (lamina defective or biochemically treated) will be provided by a collaborating biologist (C. Badens, Marseille Medical Genetics (MMG), La Timone campus). Experiments – Microfluidic experiments on single cell/nucleus will be conducted to assess nucleus shape, fragility and deformability, and correlate nucleus rheological properties with lamina defect level. Another setup will mimic the situation in a blood vessel to characterize the response of endothelial cells to shear flow, with healthy or abnormal lamina.
Modelling and computing – We will develop a physical model connecting the global nuclear rheology to the dynamics of the local lamina meshwork. Deep learning will be included in the data analysis process to design new experiments optimized for data classification and to determine rheological criteria specific of the cell pathological state.


The project is based on a tight collaboration between the groups of Emmanuèle Helfer, biophysicist at CINaM, and of Jean-François Rupprecht, theoretician at CPT, and includes a collaboration with Catherine Badens, biologist at MMG. This interdisciplinary consortium provides a combination of techniques, expertise and knowledge from different scientific fields and cultures. The project involves microfluidic device design and fabrication, cell senescence characterization, use of high-speed videomicroscopy, development of image analysis tools, and interpretation of experimental data using theoretical arguments and numerical simulations. The collaborating groups will continuously interact to link experimental results and theoretical approaches, leading to establishment of a clear phase diagram of the pathology level as function of the nucleus mechanics. Such diagram will then allow assessment of senescence degree of patients with unknown condition by simple measurement of their nucleus mechanical response.

Expected profile

The PhD candidate should preferentially be a physicist with some knowledge in programming or a theoretician with strong interest towards experimental approaches. She or he must be motivated to work at the interface of physics and biology as she/he will handle biological samples and perform both experiments and computations.