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.

Project Highlights:

AFM Experimental Setup
Figure 1 AFM Experimental Setup
Histology images
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.

Relevant Publications:

  1. 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.
  2. Carol L. Keefer and Jaydev P. Desai, “Mechanical phenotyping of stem cells”, Theriogenology, 75, pp. 1426 -1430, 2011.
  3. 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.
  4. 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]