Correlating mechanical and gene expression data on the single cell level to investigate metastatic phenotypes
Katherine M. Young,
Congmin Xu,
Kelly Ahkee,
Roman Mezencev,
Steven P. Swingle,
Tong Yu,
Ava Paikeday,
Cathy Kim,
John F. McDonald,
Peng Qiu,
Todd Sulchek
Affiliations
Katherine M. Young
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 313 Ferst Drive, Atlanta, GA 30332-0535, USA
Congmin Xu
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 313 Ferst Drive, Atlanta, GA 30332-0535, USA
Kelly Ahkee
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 313 Ferst Drive, Atlanta, GA 30332-0535, USA
Roman Mezencev
School of Biology, Georgia Institute of Technology, 313 Ferst Drive, Atlanta, GA 30332-0405, USA
Steven P. Swingle
George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 801 Ferst Drive, Atlanta, GA 30332-0405, USA
Tong Yu
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 313 Ferst Drive, Atlanta, GA 30332-0535, USA
Ava Paikeday
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 313 Ferst Drive, Atlanta, GA 30332-0535, USA
Cathy Kim
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 313 Ferst Drive, Atlanta, GA 30332-0535, USA
John F. McDonald
School of Biology, Georgia Institute of Technology, 313 Ferst Drive, Atlanta, GA 30332-0405, USA
Peng Qiu
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 313 Ferst Drive, Atlanta, GA 30332-0535, USA
Todd Sulchek
Wallace H. Coulter Department of Biomedical Engineering, Georgia Institute of Technology, 313 Ferst Drive, Atlanta, GA 30332-0535, USA; George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, 801 Ferst Drive, Atlanta, GA 30332-0405, USA; Corresponding author
Summary: Stiffness has been observed to decrease for many cancer cell types as their metastatic potential increases. Although cell mechanics and metastatic potential are related, the underlying molecular factors associated with these phenotypes remain unknown. Therefore, we have developed a workflow to measure the mechanical properties and gene expression of single cells that is used to generate large linked-datasets. The process combines atomic force microscopy to measure the mechanics of individual cells with multiplexed RT-qPCR gene expression analysis on the same single cells. Surprisingly, the genes that most strongly correlated with mechanical properties were not cytoskeletal, but rather were markers of extracellular matrix remodeling, epithelial-to-mesenchymal transition, cell adhesion, and cancer stemness. In addition, dimensionality reduction analysis showed that cell clustering was improved by combining mechanical and gene expression data types. The single cell genomechanics method demonstrates how single cell studies can identify molecular drivers that could affect the biophysical processes underpinning metastasis.
