The cells of the human body experience diverse conditions of mechanical stress from the microenvironment originating from the embryonic stage through differentiation into multiple lineages. Lamin A is such a nuclear protein which is expressed in the process of differentiation, unlike B-type lamins which are expressed in the primordial state of development. Lamins are type V intermediate filaments which form an elastic meshwork beneath the inner nuclear envelope thereby providing proper shape and rigidity to the nucleus. Lamins are also involved in chromatin tethering, transcription regulation, DNA replication and damage repair pathways and in a wide range of nuclear functions, thus actively assisting different cellular pathways.

Profound research on lamins has led to the identification of nearly 500 mutations in lamin A alone leading to a plethora of diseases collectively termed as laminopathies. Our laboratory has pioneered the research on structural and functional changes of lamin A mutants leading to Dilated cardiomyopathy (DCM) and muscular dystrophies. We use a diverse array of medium to high-resolution biophysical techniques like Isothermal titration calorimetry (ITC), Dynamic Light Scattering (DLS), and Nuclear Magnetic Resonance (NMR) to investigate structural perturbations and the corresponding thermodynamics of the mutant proteins. Besides these, the Sengupta laboratory has worked out and patented rheological methods to study the viscoelastic behaviour of lamin A proteins. These methods are based on purified proteins or cell culture models. The lab uses high-end confocal & and super-resolution images to probe diverse changes in nuclear envelope and other cellular phenotypes and Fluorescence Correlation Spectroscopy (FCS) to study the dynamics in the confocal volume. We have stepped into an exciting arena of investigating the roles of extracellular matrix (ECM) in transducing the forces to the nuclei of myoblasts reminiscing the microenvironment of the mesoderm in the process of development of muscle fibres. The lab focuses on fabricating ECMs out of PDMS and acrylamide of varying stiffness and topography to mimic such a cellular milieu and culturing myoblasts on top of the engineered surfaces. We notice cytoskeletal reorganization and altered force transmission by Traction Force Microscopy-based calculations. Needless to mention, routine techniques like Western Blot, qPCR, and proteomics back up the data obtained from parallel techniques.

​

One-half of the Sengupta lab also focuses on the roles of differential expression of lamins in neoplastic transformation in ovarian cancer. There have been studies illustrating the role of expression alterations of lamins in the induction of genomic instability contributing to the pathophysiology of cancer progression. We focussed on ovarian cancer where modulation of neoplastic changes has been associated with the extent of alteration in nuclear mechanics and morphology. Initially, we aimed to study the expression and morphometric distribution of nuclear lamin proteins as specific parameters in ovarian cancer and normal tissues. In a pilot study, we investigated the lamin A: B ratio in patient tissue microarray samples and performed exhaustive imaging of ovarian cancer versus normal tissue samples. Based on that, we developed a novel Deep Hybrid Learning model of auto feature extraction from pre-processed images which enabled us to differentiate between cancerous and normal samples successfully with unprecedented speed, precision and robustness. This has been applied for a patent and is foreseen to significantly make the diagnosis and prognosis of cancer faster and better compared to histopathological examinations.  Considering this differential expression and distribution of lamins having major regulatory roles in the progression of ovarian carcinogenesis, we are currently aiming to visualize any changes in the spatial orientation of chromosome territories by 3D FISH followed by confocal imaging and quantitation. We aim to understand the LAD-LAD & and TAD-TAD interactions in ovarian cancer by HiC sequencing and analysis.