Year: 2022
Type: article
Abstract: Dynamically controlling cell-material interactions has a strong potential for advancing many cell-based technologies, including cell detection and cell sorting systems. To this end, fundamental studies that provide insights into how cells respond biologically to physico-chemical cues are necessary. Studies show that biological responses, such as cytoskeletal reorganization alter the overall viscoelastic properties of cells. Here, we monitored, in real time, and non-invasively, the evolution of the viscoelastic properties of yeast cells as a function of medium ionic strength (IS). Measurements were performed on SiO2-coated sensor surfaces using the quartz crystal microbalance with dissipation monitoring (QCM-D). Our results indicate that, for every adhesion phase, the cell stiffness decreases with increasing IS. This trend was consistent across the various cell concentrations studied. In terms of cell-substrate interactions, we show that a high IS promotes cell adhesion for all cell concentrations, including ultra-low concentrations. Our results also show that while the adhesion signal decreases with cell concentration for each IS, only temporal and close to noise-level adhesion signals were measured in ion-free medium irrespective of the cell concentration. We also show that cell adhesion rates are higher in physiological ionic strengths compared to cells in higher ionic strengths. Finally, from a cell detection perspective, the results reveal that for very low cell concentrations, large signal enhancements can be achieved by measuring the same concentration in a higher ionic strength. This result also applies for measurements on gold surfaces; thus, we suggest ionic tuning as a strategy for promoting trace-level cell detection in biosensors and cell sorting applications.
Source: Physics in Medicine
Institution: KU Leuven
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $1,380
Funder: KU Leuven
Award: G784094351
OpenAlex ID: W4224903164