The mechanical properties of cells influence their cellular and subcellular functions, including cell adhesion, migration, polarization, and differentiation, as well as organelle organization and trafficking inside the cytoplasm. Yet reported values of cell stiffness and viscosity vary substantially, which suggests differences in how the results of different methods are obtained or analyzed by different groups. To address this issue and illustrate the complementarity of certain approaches, here we present, analyze, and critically compare measurements obtained by means of some of the most widely used methods for cell mechanics: atomic force microscopy, magnetic twisting cytometry, particle-tracking microrheology, parallel-plate rheometry, cell monolayer rheology, and optical stretching. These measurements highlight how elastic and viscous moduli of MCF-7 breast cancer cells can vary 1,000-fold and 100-fold, respectively. We discuss the sources of these variations, including the level of applied mechanical stress, the rate of deformation, the geometry of the probe, the location probed in the cell, and the extracellular microenvironment.

Here we investigated the question whether cells, being highly heterogeneous objects, could be described with the elastic modulus (effective Young's modulus) in a self-consistent way. We performed a comparative analysis of the elastic modulus derived from the indentation data obtained with atomic force microscopy (AFM) on human cervical epithelial cells (both normal and cancerous). Both sharp (cone) and dull (2500-nm radius sphere) AFM probes were used. The indentation data were processed through different elastic models. The cell was approximated as a homogeneous elastic medium that had either 1), smooth hemispherical boundary (Hertz/Sneddon models) or 2), the boundary covered with a layer of glycocalyx and membrane protrusions ("brush" models). Consistency of these approximations was investigated. Specifically, we tested the independence of the elastic modulus of the indentation depth, which is assumed in these models. We demonstrated that only one model showed consistency in treating cells as a homogeneous elastic medium, namely, the brush model, when processing the indentation data collected with the dull AFM probe. The elastic modulus demonstrated strong depth dependence in all models: Hertz/Sneddon models (no brush taken into account), and when the brush model was applied to the data collected with sharp conical probes. We conclude that it is possible to describe the elastic properties of the cell body by means of an effective elastic modulus, used in a self-consistent way, when using the brush model to analyze data collected with a dull AFM probe. The nature of these results is discussed.

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When measuring the elastic (Young's) modulus of cells using AFM, good attachment of cells to a substrate is paramount. However, many cells cannot be firmly attached to many substrates. A loosely attached cell is more compliant under indenting. It may result in artificially low elastic modulus when analyzed with the elasticity models assuming firm attachment. Here we suggest an AFM-based method/model that can be applied to extract the correct Young's modulus of cells loosely attached to a substrate. The method is verified by using primary breast epithelial cancer cells (MCF-7) at passage 4. At this passage, approximately one-half of cells develop enough adhesion with the substrate to be firmly attached to the substrate. These cells look well spread. The other one-half of cells do not develop sufficient adhesion, and are loosely attached to the substrate. These cells look spherical. When processing the AFM indentation data, a straightforward use of the Hertz model results in a substantial difference of the Young's modulus between these two types of cells. If we use the model presented here, we see no statistical difference between the values of the Young's modulus of both poorly attached (round) and firmly attached (close to flat) cells. In addition, the presented model allows obtaining parameters of the brush surrounding the cells. The cellular brush observed is also statistically identical for both types of cells. The method described here can be applied to study mechanics of many other types of cells loosely attached to substrates, e.g., blood cells, some stem cells, cancerous cells, etc.

A new approach to bioelectronic Sense-and-Act systems was developed with the use of modified electrodes performing sensing and substance-releasing functions. The sensing electrode was activated by biomolecular/biological signals ranging from small biomolecules to proteins and bacterial cells. The activated sensing electrode generated reductive potential and current, which stimulated dissolution of an Fe(3+)-cross-linked alginate matrix on the second connected electrode resulting in the release of loaded biochemical species with different functionalities. Drug-mimicking species, antibacterial drugs, and enzymes activating a biofuel cell were released and tested for various biomedical and biotechnological applications. The studied systems offer great versatility for future applications in controlled drug release and personalized medicine. Their future applications in implantable devices with autonomous operation are proposed.

Molecular computing based on enzymes or nucleic acids has attracted a great deal of attention due to the perspectives of controlling living systems in a way we control electronic computers. Enzyme-based computational systems can respond to a great variety of small molecule inputs. They have an advantage of signal amplification and highly specific recognition. DNA computing systems are most often controlled by oligonucleotide inputs/outputs and are capable of sophisticated computing, as well as controlling gene expressions. Here, we developed an interface that enables communication of otherwise incompatible nucleic acid and enzyme computational systems. The enzymatic system processes small molecules as inputs and produces NADH as an output. The NADH output triggers electrochemical release of an oligonucleotide, which is accepted by a DNA computational system as an input. This interface is universal since the enzymatic and DNA computing systems are independent of each other in composition and complexity.

Here we show that the surface of human cervical epithelial cells demonstrates substantially different fractal behavior when the cell becomes cancerous. Analyzing the adhesion maps of individual cervical cells, which were obtained using the atomic force microscopy operating in the HarmoniX mode, we found that cancerous cells demonstrate simple fractal behavior, whereas normal cells can only be approximated at best as multifractal. Tested on ~300 cells collected from 12 humans, the fractal dimensionality of cancerous cells is found to be unambiguously higher than that for normal cells.

M aterials that efficiently release biological molecules or therapeutic chemicals on demand using exposure to remotely controlled and safe external sources of energy, such as magnetic fields, could find applications for drug delivery 1 , biotechnology 2,3 and biosensors 4 . Because live tissue and synthetic polymers are not responsive to weak magnetic fields, the development of magnetic-field-responsive soft materials has been reported by combining magnetic nanoparticles and stimuli-responsive soft materials 5 . Magnetic nanoparticles interact with magnetic fields and transduce magnetic field energy into physical or chemical changes in the soft material. Materials that control enzymatic processes are one example of such soft materials. Enzymes are extensively used to change or degrade colloidal particles, capsules, and their assemblies to trigger release of the cargo via biocatalytic reactions 6,7 .In all eukaryotes, metabolic pathways are precisely organized and regulated. This precise control is based in part on the high selectivity of biocatalytic reactions and controlled transport of chemicals and biomacromolecules across membranes that compartmentalize cells, organelles and organs. Highly selective biocatalysis alone cannot orchestrate complex systems of biochemical reactions without the supporting role of signal-triggered synthesis, release, secretion, conversion and degrading processes that take place in different compartments in cells and organs. Despite being highly selective, enzymes cannot provide 100% selectivity. In particular, enzymes could interact with a number of substrates of a similar chemical structure (for example, proteases are highly promiscuous catalysts), be degraded by other enzymes or even by self-digestion upon secretion into a complex biological environment, or undergo undesired aggregation, crystallization or nonspecific adsorption, which would strongly damage the efficiency of the biocatalytic process. However, the overall high specificity of biocatalytic processes is strengthened by localizing the enzymatic reactions within a specific environment and spatial compartments.Inspired by this hierarchical design in live systems, diverse stimuli-responsive functional materials have been reported, involving various architectures that respond to changes in magnetic fields [8][9][10] . However, it remains challenging to create a reactive system that preserves enzyme molecules from destructive environments and undesired interactions while being able to initiate the designated reaction when needed. Different approaches have been developed to preserve enzymes for storage and delivery before activating them on demand in a magnetic field at the targeted location. A number of studies aimed at controlling the kinetics of biocatalytic reactions in model systems [11][12][13][14][15] have explored magnetic-field-triggered changes of the local concentration and mobility of enzymes. However, it is difficult to apply many of such approaches to live tissue because of limitations associated with degradat...