Mechano-Genomics Group Projects

Mechano-genomics of cellular ageing and rejuvenation

Team: Luezhen Yuan (PhD student), Trinadh Rao (Postdoctoral fellow)

Cellular ageing results in major alterations in nuclear mechanotransduction pathways and genome programs. In recent work, we demonstrated that mechanical signals can reprogram and rejuvenate ageing human fibroblasts. However, the cytoskeletal remodelling mechanisms facilitating the activation of nuclear mechanotransduction pathways and how the 3D chromatin architecture regulates such cell-state transitions during cellular ageing and rejuvenation are still unclear. Towards this, we use single cell fluorescence imaging and gene expression profiles combined with chromosome painting and conformation assays to unravel the nuclear mechanotransduction pathways and transcription dependent alterations in 3D chromosome organization during cellular ageing and rejuvenation.

Implanting reprogrammed and rejuvenated cells for skin tissue regeneration

Team: Tina Pekec (Postdoctoral fellow), Bibhas Roy (Scientist)

Cellular ageing result in progressive decline of tissue architecture and function. For example, in skin tissues, the fibroblast cell number in the dermis reduces with ageing leading to altered extra cellular matrix properties, increased local rigidity of the extra-cellular matrix and decreased elastic response of the dermis. Towards this, we are exploring if implanting the mechanically rejuvenated patient specific aged human dermal fibroblasts could provide robust tissue regeneration models for clinical applications. In particular, using aged ex vivo human skin models, we study the cell-fate decisions and the extracellular matrix remodelling properties of the mechanically reprogrammed and rejuvenated fibroblasts after implantation.

Role of tissue compression on chromatin organization and gene expression

Team: Raj Gupta (PhD student), NN (Postdoctoral fellow)

Tissue compression is ubiquitous in biological systems. In recent studies, we showed that compressive load results in differential condensation of chromatin structure and that the mechanical state of cells regulate cytokine dependent gene expression programs. However, the coupling between tissue compression and single-cell chromatin organization and how soluble biochemical signals within the tissue microenvironment regulate compression dependent gene expression programs is poorly understood. In the next phase, we plan to setup well characterized titrated compressive loads for single cells, combined with soluble cytokine signals, to study the biophysics of chromatin condensation and its impact on gene expression.

Nuclear mechano-pathology of tumor microenvironment

Team: Saradha Venkatachalapthy (PhD student), Paulina Schärer (Technician)

Tumor microenvironment is characterized by complex mechano-chemical interactions between cancer cells, extracellular matrix and the resident stromal cells. We recently demonstrated that nuclear morphometrics and chromatin condensation patterns, obtained using single-cell imaging combined with machine learning methods, provide robust mechano-genomic score (MGS) to classify normal and cancer cells at various stages of breast tumor progression. In the next phase, we are exploring if the MGS score on human breast tumor biopsies, combined with multi-color immunofluorescence and spatial transcriptomics, could provide mechanistic insights on the nuclear mechano-pathology of tumor microenvironment.

Chromatin biomarkers for early cancer diagnostics

Team: Daniel Paysan (PhD student), Kiran Challa (Postdoctoral fellow)

Growth of solid tumours have been shown to secrete complex signals; including DNA, exosomes and diffusible signalling molecules within the tissue microenvironments. Importantly, some of these signals are also present in circulating blood resulting in the development of liquid biopsies for early cancer prognosis. Our recent studies demonstrate that cells exhibit subtle chromatin structural alterations, when subjected to cytokine signals. We hypothesize that the chromatin structure of circulating blood cells may be poised for tumor signals and could therefore serve as potential biomarker. Towards this, we are exploring single-cell fluorescence imaging combined with sequencing and machine learning methods to develop robust chromatin biomarkers using liquid biopsies for early cancer diagnostics.