SIMPA simplifies micropipette aspiration to measure multiple samples simultaneously
Assessing the mechanical and rheological features of biological entities like cells, vesicles, and tissues is key to understanding their function. However, the conventional technique for such measurements, micropipette aspiration, requires individual attention for each sample in a tedious process.
Landiech et al. developed the sliding insert micropipette aspiration (SIMPA) method, which enables multiple parallel pipettes integrated into an adjustable microfluidic chip. SIMPA increases efficiency by facilitating simultaneous measurements and opens the possibility for automation with the microfluidic platform.
“Micropipette aspiration is one of the most used techniques to measure important properties such as stretching and bending moduli for lipid vesicles or elasticity and viscosity for cells or cell aggregates,” said author Pierre Joseph. “It measures the response of the cell, vesicle, or tissue to an aspiration applied by a cylindrical pipette. The deformation of the object is quantified by optically measuring the length of its protrusion inside the pipette.”
The team fabricated the microfluidic chip with a polydimethylsiloxane base, enhanced by sliding elements that enable the cylindrical pipettes to fit securely. To test their device, they prewetted the chip and injected the desired sample under microscope supervision. Using image analysis, they quantified the deformation.
“Combining engineering, biophysics, and biology can lead to interesting developments,” said Joseph. “Here, we have developed a method that can quantify mechanical properties for several types of small objects. We are now planning to apply it to understand the biophysics of cell aggregates: how different factors affect the elasticity and viscosity, and how global responses emerge from microscopic interactions between cells.”
Source: “Parallel on-chip micropipettes enabling quantitative multiplexed characterization of vesicle mechanics and cell aggregates rheology,” by Sylvain Landiech, Marianne Elias, Pierre Lapèze, Hajar Ajiyel, Marine Plancke, Blanca González-Bermúdez, Adrian Laborde, Fabien Mesnilgrente, David Bourrier, Debora Berti, Costanza Montis, Laurent Mazenq, Jérémy Baldo, Clément Roux, Morgan Delarue, and Pierre Joseph, APL Bioengineering (2024). The article can be accessed at https://doi.org/10.1063/5.0193333 .