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Mechanical properties have been proven to be a pivotal parameter to enhance our understanding of living systems. While research during the last decades focused on cells and tissues, little is known about the role of organelle mechanics in cell function. Here, mitochondria are of specific interest due to their involvement in numerous physiological and pathological processes, e.g., in the production and homeostasis of reactive oxygen species (ROS). Using real-time fluorescence and deformability cytometry, we present a microfluidic technology that is capable to determine the mechanical properties of individual mitochondria at a throughput exceeding 100 organelles per second. Our data on several thousands of viable mitochondria isolated from rat C6 glial cells yield a homogenous population with a median deformation that scales with the applied hydrodynamic stress. In two proof-of-principle studies, we investigated the impact of exogenously and endogenously produced ROS on mitochondria mechanics. Exposing C6 cells to hydrogen peroxide (H2O2) triggers superoxide production and leads to a reduction in mitochondria size while deformation is increased. In a second study, we focused on the knockout of tafazzin, which has been associated with impaired remodeling of the mitochondrial membrane and elevated levels of ROS. Interestingly, our results reveal the same mechanical alterations as observed after the exposure to H2O2, which points to a unified biophysical mechanism of how mitochondria respond to the presence of oxidative stress. In summary, we introduce high-throughput mechanical phenotyping into the field of organelle biology with potential applications for understanding sub-cellular dynamics that have not been accessible before.
The capability to parameterize shapes is of essential importance in biomechanics to identify cells, to track their motion, and to quantify deformation. While various shape descriptors have already been investigated to study the morphology and migration of adherent cells, little is known of how the mathematical definition of a contour impacts the outcome of rheological experiments on cells in suspension. In microfluidic systems, hydrodynamic stress distributions induce time-dependent cell deformation that needs to be quantified to determine viscoelastic properties. Here, we compared nine different shape descriptors to characterize the deformation of suspended cells in an extensional as well as shear flow using dynamic real-time deformability cytometry. While stress relaxation depends on the amplitude and duration of stress, our results demonstrate that steady-state deformation can be predicted from single cell traces even for translocation times shorter than their characteristic time. Implementing an analytical simulation, performing experiments, and testing various data analysis strategies, we compared single cell and ensemble studies to address the question of computational costs vs experimental accuracy. Results indicate that high-throughput viscoelastic measurements of cells in suspension can be performed on an ensemble scale as long as the characteristic time matches the dimensions of the microfluidic system. Finally, we introduced a score to evaluate the shape descriptor-dependent effect size for cell deformation after cytoskeletal modifications. We provide evidence that single cell analysis in an extensional flow provides the highest sensitivity independent of shape parametrization, while inverse Haralick's circularity is mostly applicable to study cells in shear flow.
Cell mechanical properties reveal substantial information on cell state and function. Utilizing mechanics as a label-free biomarker allows for investigation of fundamental cellular processes as well as biomedical applications, e.g., disease diagnosis. High-throughput methods for accessing the elastic properties of cells in suspension from hydrodynamic deformation in a microfluidic constriction are available with real-time analysis rates of up to 1000 cells per second. However, accessing elastic as well as viscous properties of cells and multicellular systems in suspension as well as adhered to surfaces at high throughput has not been possible so far. In this thesis, I approached this question and developed as well as applied microfluidic and holographic technologies to analyze the viscoelastic properties of single cells and multicellular aggregates, respectively.
First, I demonstrated that real-time deformability cytometry (RT-DC) can be applied in transfusion medicine, where the highest quality standards have to be maintained while blood product release is time-critical. We showed for platelet and red blood cell concentrates as well as for hematopoietic stem cells that their mechanical properties can be used for label-free quality assessment. The results have been published in Lab on a Chip (Aurich et al. 2020).
For RT-DC and many other methods based on hydrodynamic deformation, the constriction size has to be adapted to the objects of interest to allow for a shear-induced deformation. We introduced virtual fluidic channels, which are established by two co-flowing aqueous polymer solutions. Virtual fluidic channels can be precisely adjusted in their cross section, allowing for mechanical phenotyping of single cells as well as cell clusters or tissue spheroids in one microfluidic system. Importantly, measurements can also be performed in standard microfluidic geometries beyond soft lithography, e.g., in the cuvette of a flow cytometer. For cell spheroids as a model system for multicellular aggregates, we show a 10-fold lower Young's modulus of the tissue compared to single-cell mechanics, suggesting cell-cell and cell-matrix interactions being potential contributors to the mechanics of multicellular aggregates. Our work on virtual fluidic channels has been published in Nature Communications (Panhwar et al. 2020).
Within this thesis, I expanded the high-throughput elastic phenotyping performed by RT-DC towards viscoelastic cell properties by developing dynamic real-time deformability cytometry (dRT-DC). Dynamic tracking of cells while passing the microfluidic constriction allows to access steady-state (elasticity) and time-dependent (viscosity) material properties for a complete viscoelastic characterization of cells in suspension at high throughput. I introduced a shape mode decomposition based on a Fourier transformation, which allows to disentangle the superimposed stress responses to an extensional stress at the channel inlet and a constant shear stress in the channel. These hydrodynamic stress distributions are present in almost every microfluidic channel geometry. From the separated stress responses, viscoelastic material properties can be determined independent of cell shape.
We demonstrated experimentally the sensitivity of dRT-DC to cytoskeletal alterations and confirmed the validity of the method by reference measurements on calibrated hydrogel beads. In our work, we also presented a viscoelastic fingerprint of the major subpopulations of peripheral blood: erythrocytes, granulocytes, and peripheral blood mononuclear cells (PBMCs) (e.g., lymphocytes and monocytes), all characterized by the same method. The technique and the results have been published in Nature Communications (Fregin et al. 2019).
In cell mechanical methods based on hydrodynamic deformation, cell shape is usually monitored while a stress is applied. For extraction of material properties as well as for studying shape dynamics, it is essential to describe cell shape yielding highest strain differences for a given microfluidic system and experimental setting. Using dRT-DC, I compared nine different shape descriptors to analyze cell deformation in an extensional as well as shear flow. A relaxation time analysis was performed on different levels of data aggregation from single cells to an ensemble scale. I demonstrated that the steady-state deformation can be predicted from stress response curves without them reaching the steady-state. This is important for cell mechanical measurements in microfluidic systems as the characteristic times are unknown in general and as the channel length is fixed. In addition, by introducing a cut-off criterion for how much of the response trace needs to be captured within the channel, the analysis time per cell can be reduced while material properties can still be extracted. Performing simulations, I compared the accuracy of relaxation times extracted from ensemble and single-cell studies under experimental conditions. Introducing a scoring system to evaluate which combinations of shape descriptors and analysis strategies provide biggest effect size, we concluded that single-cell analyses in an extensional flow are most sensitive to cytoskeletal modifications independent of shape parametrization. The manuscript was submitted to the Biophysical Journal.
Finally, I translated the fast non-contact cell mechanical probing from suspension to adherent cells. No such technology has been available and with the majority of cells being adherent, a robust label-free method for mechanophenotyping at high-throughput is required. Within this thesis, I have introduced and realized a new concept: holographic vibration spectroscopy (HVS), where adherent cells are mechanically excited on a vibrating surface while their height oscillations are measured optically. Analysis is done in an interferometric heterodyne setup by using frequency multiplexing and time-averaged holography in off-axis configuration. Based on interference images captured by a high-speed complementary metal-oxide-semiconductor (CMOS) camera, I established a mathematical model to reconstruct the vibration amplitude of adherent cells as well as their retardation phase compared to the exciting vibration. From the amplitude and phase response, viscoelastic parameters can be derived, which have to be investigated in subsequent studies.
In summary, I introduced in my work two high-throughput methods for the viscoelastic characterization of suspended as well as adherent cells while highlighting applications in tissue mechanics and transfusion medicine that are relevant not only in basic but also in translational research.