Cell adhesion is an essential process for any living cell. It is critical for cell differentiation, division, migrationand specialization. Dysfunction of cell adhesion is a hallmark of various pathological phenotypes, includingchronic kidney diseases, cancer, and many others. In the effort to discover new disease treatments andimprove our basic understanding of single cell properties there is a strong demand for methods permitting rapidand accurate single cell adhesion measurements. Unfortunately, current technologies are lacking since theyonly measure adhesion in entire cell populations (e.g., microfluidics, spin disks) rather than individual cells, aretoo complex or costly (e.g., atomic force microscopy, optical tweezers) for widespread adoption, requiresophisticated functionalized surfaces (traction force microscopy), or probe only targeted receptors (celladhesive force microscopy) that precludes measuring total cell adhesion potential. Therefore, there is a greatneed for an automated, high-throughput and cost-efficient platform capable of simultaneously measuring singlecell adhesion for a large population of cells. Here, we propose to develop a novel methodological approachutilizing simple disposable microfluidics cassettes (MiCs), oscillation driven cell shifts, and a conversion ofeach individual cell track to adhesion force via machine learning algorithms. Our initial studies provide strongsupport for the feasibility of the approach. This one-year Phase I project will result in a fully functionalinstrument through the development and integration of its critical components, which include a programmablecell shift actuator (BioShake), disposable MiCs, cell adhesion analysis algorithms, and software (SA1). Inaddition, the entire workflow and proof of principle experiments will be performed using multiple cell lines withvarious adhesive properties (SA2). We anticipate that the fully developed mature product will provide a highimpact tool to promote mechanobiology studies on the key role of cell adhesion in health and disease,including such pathological conditions, such as cancer, thus facilitating further fundamental studies in cellbiology and translational research.
Public Health Relevance Statement: NARRATIVE
Measurement of single cell adhesion is essential for understanding fundamental cell function and important for
identifying new diagnostic markers and drug targets; however, actual tools to perform automated and high-
throughput measurements of multiple single cells do not exist. Here we propose a new approach that permits
adhesion measurements of multiple single cells within a short time in a simple format compatible with any
inverted microscope. The main goals of this Phase I project are to develop all key components for a new
analytical platform that will allow measuring single cell adhesion (SA1), and then to test the resulting
instrument in multiple cell lines (SA2).
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