PhD Research
Read about my latest work.
Developing systemic models to understand cellular mechanotransduction processes.
Introduction
Human mesenchymal stem cells (hMSCs) are adherent multipotent adult stem cells present in the bone marrow and blood. They can differentiate to connective tissue lineages like fat, muscle and bone (which originate in the mesenchyme), depending on the mechanical properties of their microenvironment. This process of sensing and responding to the extracellular mechanical cues is known as mechanotransduction. Adipogenic lineage (fat) is preferred on soft substrates, whereas osteogenic lineage (bone) is favoured on stiff substrates.
Systems Biology is the holistic study of complex biological systems by connecting the genotype of the system to its phenotype. It aims to characterize system-level input-output relationships through modelling techniques.
What is Mechanobiology?Mechanobiology is the field encompassing study of mechanical forces on cellular properties and functions. Evidence indicates that such forces are crucial in guiding cellular behaviour, and defects in the transduction of these forces can lead to many diseases like muscular dystrophies and even cancer. Over the past two decades, researchers have identified various mechanical signals affecting hMSC behaviour, like substrate stiffness, nanotopography, adhesion area and ligand availability, but an often overlooked property is the viscoelasticity of the substrate. It has been shown to influence hMSC behaviour, like its spreading area, proliferation capability, motility rate, and lineage specification.
Quantifying cell membrane fluctuations on viscoelastic substrates
My colleagues in Prof. Majumder’s Lab at IIT Bombay observed an unusual “wobbling” of the cell membrane when the cells were plated on viscoelastic substrates. These dynamic oscillations were not observed on purely elastic substrates; and it is hypothesized that viscoelastic creep, and subsequent loss of traction at the cell-substrate adhesion junctions may lead to such membrane fluctuations. Manually selecting the cell boundary for hundreds of images would be extremely time-consuming, hence I resorted to MATLAB to develop a fast and robust image processing algorithm that would automatically extract cell boundary.
Cell plated on an elastic substrate does not show "wobbling".
Cell plated on a viscoelastic substrate shows "wobbling".
An eight-step image segmentation technique was used to extract peripheries from time-lapse images of these cells and quantify the fluctuations. A robust test statistic, the root mean squared error of fluctuations, was distilled from this time-series perimeter data, which provided a measure for the fluctuations in these cells. Finally, a hypothesis test indeed confirmed a statistically significant difference between the wobbling of cell membranes on elastic substrates as opposed to viscoelastic substrates. Thus, this standardized routine eliminated human bias and provided a swift and reproducible solution to quantify the visual observations.
Vision
Building large-scale models to study emergent properties of complex multi-input multi-output systems is the crux of systems biology. The vision for my Ph.D. therefore, is to expand upon the current network, and develop a unified model mapping multiple mechanical cues to observed cellular responses, gaining a holistic understanding of hMSC mechanobiology. Such models are pivotal in their role as predictive and optimization tools to address many open questions in stem cell biology. It is only after creating such models, will we be able to harness their power in designing improved substrates and scaffolds, and reducing the time required for ex vivo expansion of hMSCs towards a chosen lineage, thereby contributing immensely towards regenerative therapies and healthcare.
PhD Supervisors and Collaborators
Prof. K.V. Venkatesh is a pioneer in the areas of Systems Biology, network analysis and modeling, Synthetic Biology and metabolic and regulatory networks research in India with more than a decade of experience. He has more than a hundred peer reviewed publications, won several awards and has guided several doctoral, masters and bachelors theses. He has contributed significantly to research in the areas of quantification of biological networks including genetic, signaling and metabolic pathways. He has also contributed extensively towards the broad field of metabolic engineering and his group has developed steady state gene expression simulators, methods to quantify phenotypic space and complete whole-body metabolic model for humans. His research work has been well received by biologists and the results have been used to demonstrate the principles deciphered in his Lab in many biological systems, which is reflected in his citation in journals such as Nature, Nature Reviews, Nature Genetics, Nature Neuroscience, Journal of Biological Science and New Scientist.
Prof. Abhijit Majumder has been working in the field of cell mechanics, and how different mechanical aspects of the cellular microenvironment influence and control cellular behaviour and stem cell fate. His lab, "M-Lab", captures the four major areas of his work: materials, matrix, mechanics and microfluidics. He has also contributed towards employing microfabricated structures and microfluidic channels to capture the effect of small scale geometry and fluid flow on cells. The knowledge gained would help in designing efficient scaffolds for tissue engineering, cell delivery systems for stem cell based treatments and might indicate new treatment target to control diseases related to cellular migration including cancer, and also help understand the role of mechanics in pattern formation, development and many pathological conditions.
