The technology changing how we study cells

Researchers from the University of Twente have developed a new analysis method to rapidly study millions of individual cells and the proteins they secrete to form tissues. The researchers termed their method Extracellular Protein Identification Cytometry (EPIC). "This changes the way we can study living matter and has many potential uses such as driving fabrication of replacement organs, and accelerating development and testing of medicines”, says researcher Marieke Meteling. Her work has recently been published in the prestigious scientific journal Advanced Materials.

The tissues that make up your organs consist of cells within an extracellular matrix that is produced by the cells. This matrix is not only important for how the cells function but is also an important biomarker for various diseases. Although several techniques exist to analyse this matrix, these approaches are either slow or offer poor resolution, and many require tissue destruction. This has limited the clinical and societal impact of these applications.

UT researchers from the lab of Prof. Leijten combined advanced microfluidic technology and biomaterial science with an existing measurement technique named flow cytometry to allow for the world-first high-throughput, high-resolution screening platform for the quantification of extracellular matrix.

Applications

For the successful engineering of living tissues, creation of disease models, realistic testing of drugs, and development of regenerative medicine, it is essential that cells produce the intended type of extracellular matrix. EPIC can reveal how individual cells create and modify their surroundings and do this for a large number of cells.

“Researchers can now study important questions such as what percentage of cells is affected by a drug, and why certain cells are sensitive or not to a specific treatment”, explains Meteling. EPIC can provide new insights into the tissue formation process, or how tissue destruction by specific cells occurs or is altered by treatments. These insights could advance treatments for diseases like osteoarthritis, fibrosis, and cancer.

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