Automated Characterization of Biological Specimens using Atomic Force Microscopy (AFM) - From Cells to Tissue (Rajarshi Roy)
Motivation: The goal of this project to mechanically phenotype individual mouse embryonic stem cells (mESC). Pluripotent embryonic stem cells (ESC) have a strong potential for therapeutic use in treatment of disease (e.g., heart disease, Parkinson's, and spinal cord injuries). Therefore, we are interested in the use of haptics-enabled AFM monitoring to develop improved methods for targeting ESC differentiation for diagnostic and therapeutic purposes and monitoring cellular responses to environmental stimuli. Using this approach, we envision being able to distinguish different types of cells: differentiated vs. undifferentiated, live vs. fixed, and cardiac vs. neuronal differentiated cells. Just as cell markers at the end points (through fluoroscopy) can serve as a unique signature for a particular cell type, we envision adding to this a “haptics” marker, which can be used to monitor the cell during the process of lineage differentiation.
The other goal of this project is to characterize the malignancy in human breast tissue. Much of the difficulty in rendering consistent evaluation of pathological tissue specimens arises from qualitative impressions of observers. Hence, a quantitative phenotype to automatically characterize the type and stage of cancer base upon an objective measure of its morphology and mechanical properties could provide insight regarding the changes that occur in the tissue environment during the course of disease onset and progression. We use breast tissue cores fixed on microscope slides using Tissue Microarray Technology (TMA) during AFM based experiments. The objective of this study is to to model the behavior of malignant and benign regions in the breast tissue specimens in epithelial and stromal regions. during force-indentation studies. However, this system suffers from lack of high-throughput, as each point has to be sampled individually. Therefore, there is a need to automate the process of quantifying the tissue environment. To address this shortcoming, we have developed an image-guided robotic system that automatically characterizes the regions of interest based on the image information in the tissue microarray.
- Mechanical Characterization of Mouse Embryonic Stem cells (mESC): We conducted several indentation studies on undifferentiated and early differentiating (6 days under differentiation conditions) mESC using the atomic force microscope (AFM) system. The experimental data was analyzed by various contact models that can be used to accurately model the geometry of the AFM tip and mESC interaction. With the choice of appropriate contact model, we can determine the accurate stiffness of the cell membrane and hence provide accurate force feedback to the user. Further, our results confirm that the mechanical property of undifferentiated mESC is different from differentiating (6th day) mESC.
- Mechanical Chharacterization of Normal and Epithelial Breast Tissue: We have performed characterization studies on TMA cores of normal and cancerous breast tissue samples in stromal and epithelial regions using AFM. On analyzing the AFM data using Hertzian and pointwise modulus analysis, we have observed cancerous tissue to exhibit significantly lower elastic modulus compared to normal tissue in epithelial and stromal regions. We also found non-linear behavior in stromal tissue for cancerous and stromal regions, suggesting the need to develop non-linear constitutive models for accurate material property extraction from AFM data.
- Automated vision-guided navigation of TMA slide underneath AFM tip: Tissue microarrays typically consist of AFM cores 0.6 Ám, typically many orders larger than the range of automated positioning microscope stages. To address this, we used a image-guided robotic assembly consisting of a micromanipulator MP-285, and a custom-made end-effector for holding the TMA slide. Using template matching methods, we developed an algorithm to accurately position a given region of interest (ROI) underneath the AFM tip under high and low magnifications.
- Robust Estimation of Contact-Point in AFM Experimental Data: One of the challenges in AFM data analysis of relevance to both cells and tissue is an objective identification of the point when the AFM tip touches the specimen being indented. Typically for soft samples like live cells, the transition from non-contact to the contact regime is a smooth one with noise corrupting the transition zone from contact non-contact to the contact regime. We developed a impedance-based experimental setup to identity the contact location between tip and tissue. For automated data analysis, we are currently working towards the development of a mathematical model to estimate the contact point in the presence of variability in calibration of the spring constant of the AFM tip.
|Figure 1 AFM Experimental Setup|
|Figure 2 Histology images (20X magnification) cropped from four representative A8 and A13 are regions with normal epithelial and cancerous epithelial tissue respectively. A22 and A12 are regions with normal stromal and cancerous stromal tissue respectively.|
- Anand Pillarisetti, Jaydev P. Desai, Hamid Ladjal, Andrew Schiffmacher, Antoine Ferreira and Carol L. Keefer, “Mechanical Phenotyping of Mouse Embryonic Stem Cells: Increase in Stiffness with Differentiation”, Cellular Reprogramming, 13(4): 371-380, 2011.
- Carol L. Keefer and Jaydev P. Desai, “Mechanical phenotyping of stem cells”, Theriogenology, 75, pp. 1426 -1430, 2011.
- Rajarshi Roy, Wenjin Chen, Lei Cong, Lauri Goodell, David Foran, Jaydev P. Desai, “Towards Automated Mechanical Characterization of Biological Samples Using Atomic Force Microscopy (AFM)”, In 4th Annual Dynamic Systems and Control Conference, Arlington, VA, USA, Oct 31 - Nov 2, 2011.
- Rajarshi Roy, Wenjin Chen, Lauri Goodell, Jun Hu, David Foran, Jaydev P. Desai, “Microarray-facilitated Mechanical Characterization of Breast Tissue Pathology Samples using contact mode Atomic Force Microscopy (AFM)”, In Third IEEE/RAS-EMBS International Conference on Biomedical Robotics and Biomechatronics - BioRob 2010, Tokyo, Japan, September 26-29, 2010. [Full Text]