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Cell-cell and cell-matrix adhesions are fundamental in all multicellular organisms. They play a key role in cellular growth, differentiation, pattern formation and migration. Cell-cell adhesion is substantial in the immune response, pathogen-host interactions, and tumor development. The success of tissue engineering and stem cell implantations strongly depends on the fine control of live cell adhesion on the surface of natural or biomimetic scaffolds. Therefore, the quantitative and precise measurement of the adhesion strength of living cells is critical, not only in basic research but in modern technologies, too. Several techniques have been developed or are under development to quantify cell adhesion. All of them have their pros and cons, which has to be carefully considered before the experiments and interpretation of the recorded data. Current review provides a guide to choose the appropriate technique to answer a specific biological question or to complete a biomedical test by measuring cell adhesion.

Binding force between biomolecules has a crucial role in most biological processes. Receptor-ligand interactions transmit physical forces and signals simultaneously. Previously, we employed a robotic micropipette both in live cell and microbead adhesion studies to explore the adhesion force of biomolecules such as cell surface receptors including specific integrins on immune cells. Here we apply standard computational fluid dynamics simulations to reveal the detailed physical background of the flow generated by the micropipette when probing microbead adhesion on functionalized surfaces. Measuring the aspiration pressure needed to pick up the biotinylated 10 μm beads on avidin coated surfaces and converting it to a hydrodynamic lifting force on the basis of simulations, we found an unbinding force of 12 ± 2 nN, when targeting the beads manually; robotic targeting resulted in 9 ± 4 nN (mean ± SD). We measured and simulated the effect of the targeting offset, when the microbead was out of the axis (off-axis)of the micropipette. According to the simulations, the higher offset resulted in a higher lifting force acting on the bead. Considering this effect, we could readily correct the impact of the targeting offset to renormalize the experimental data. Horizontal force and torque also appeared in simulations in case of a targeting offset. Surprisingly, simulations show that the lifting force acting on the bead reaches a maximum at a flow rate of ~ 5 μl/s if the targeting offset is not very high (

Although microliter-scale liquid handling with a handheld pipette is a routine task, pipetting nanoliter-scale volumes is challenging due to several technical difficulties including surface tension, adhesion and evaporation effects. We developed a fully automated piezoelectric micropipette with a precision of

A high-throughput label-free resonant waveguide grating biosensor, the Epic BenchTop, was utilized to in situ monitor the adhesion process of cancer cells on Arg-Gly-Asp tripeptide displaying biomimetic polymer surfaces. Using highly adherent human cervical adenocarcinoma (HeLa) cells as a model system, cell adhesion kinetic data with outstanding temporal resolution were obtained. We found that pre-exposing the cells to various concentrations of the main extract of green tea, the (−)-epigallocatechin gallate (EGCG), largely affected the temporal evolution of the adhesion process. For unexposed and low dosed cells, sigmoid shaped spreading kinetics was recorded. Higher dose of EGCG resulted in a complete absence of the sigmoidal character, and displayed adsorption-like kinetics. By using the first derivatives of the kinetic curves, a simple model was developed to quantify the sigmoidal character and the transition from sigmoidal to adsorption-like kinetics. The calculations showed that the transition happened at EGCG concentration of around 60 μg/mL. Using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide end-point assay, we concluded that EGCG is cytostatic but not cytotoxic. The effect of EGCG was also characterized by flow cytometry. We concluded that, using the introduced label-free methodology, the shape of the cell adhesion kinetic curves can be used to quantify in vitro cell viability in a fast, cost-effective, and highly sensitive manner.

Microfluidic devices exploit combined physical, chemical and biological phenomena that could be unique in the sub-millimeter dimensions. The current goal of development of Point-of-Care (POC) medical devices is to extract the biomedical information from the blood. We examined the characteristics of blood flow in autonomous microfluidic devices with the aim to realize sensitive detection of interactions between particulate elements of the blood and the appropriately modified surfaces of the system. As a model experiment we demonstrated the fast analysis of the AB0 blood group system. We observed that the accumulation of red blood cells immobilized on the capillary wall leads to increased lateral movement of the flowing cells, resulting in the overall selective deceleration of the red blood cell flow column compared to the plasma fraction. We showed that by monitoring the flow rate characteristics in capillaries coated with blood type reagents it is possible to identify red blood cell types. Analysis of hydrodynamic effects governing blood flow by Finite Element Method based modelling supported our observations. Our proof-of-concept results point to a novel direction in blood analysis in autonomous microfluidic systems and also provide the basis for the construction of a simple quantitative device for blood group determination.

Current robots can manipulate only surface-attached cells seriously limiting the fields of their application for single cell handling. We developed a computer vision-based robot applying a motorized microscope and micropipette to recognize and gently isolate intact individual cells for subsequent analysis, e.g., DNA/RNA sequencing in 1–2 nanoliters from a thin (~100 μm) layer of cell suspension. It can retrieve rare cells, needs minimal sample preparation and can be applied for virtually any tissue cell type. Combination of 1 μm positioning precision, adaptive cell targeting and below 1 nl liquid handling precision resulted in an unprecedented accuracy and efficiency in robotic single cell isolation. Single cells were injected either into the wells of a miniature plate with a sorting speed of 3 cells/min or into standard PCR tubes with 2 cells/min. We could isolate labeled cells also from dense cultures containing ~1,000 times more unlabeled cells by the successive application of the sorting process. We compared the efficiency of our method to that of single cell entrapment in microwells and subsequent sorting with the automated micropipette: the recovery rate of single cells was greatly improved.

Monocytes, dendritic cells (DCs), and macrophages (MFs) are closely related immune cells that differ in their main functions. These specific functions are, to a considerable degree, determined by the differences in the adhesion behavior of the cells. To study the inherently and essentially dynamic aspects of the adhesion of monocytes, DCs, and MFs, dynamic cell adhesion assays were performed with a high-throughput label-free optical biosensor [Epic BenchTop (BT)] on surfaces coated with either fibrinogen (Fgn) or the biomimetic copolymer PLL-g-PEG-RGD. Cell adhesion profiles typically reached their maximum at ∼60 min after cell seeding, which was followed by a monotonic signal decrease, indicating gradually weakening cell adhesion. According to the biosensor response, cell types could be ordered by increasing adherence as monocytes, MFs, and DCs. Notably, all three cell types induced a larger biosensor signal on Fgn than on PLL-g-PEG-RGD. To interpret this result, the molecular layers were characterized by further exploiting the potentials of the biosensor: by measuring the adsorption signal induced during the surface coating procedure, the authors could estimate the surface density of adsorbed molecules and, thus, the number of binding sites potentially presented for the adhesion receptors. Surfaces coated with PLL-g-PEG-RGD presented less RGD sites, but was less efficient in promoting cell spreading than those coated with Fgn; hence, other binding sites in Fgn played a more decisive role in determining cell adherence. To support the cell adhesion data obtained with the biosensor, cell adherence on Fgn-coated surfaces 30-60 min after cell seeding was measured with three complementary techniques, i.e., with (1) a fluorescence-based classical adherence assay, (2) a shear flow chamber applying hydrodynamic shear stress to wash cells away, and (3) an automated micropipette using vacuum-generated fluid flow to lift cells up. These techniques confirmed the results obtained with the high-temporal-resolution Epic BT, but could only provide end-point data. In contrast, complex, nonmonotonic cell adhesion kinetics measured by the high-throughput optical biosensor is expected to open a window on the hidden background of the immune cell-extracellular matrix interactions.