For oxygen sensor calibration, the lid containing sensor was immersed in cell culture medium, and different dissolved O2 concentrations were achieved by purging the solution with mixtures of N2 and O2 gas of known concentrations

For oxygen sensor calibration, the lid containing sensor was immersed in cell culture medium, and different dissolved O2 concentrations were achieved by purging the solution with mixtures of N2 and O2 gas of known concentrations

For oxygen sensor calibration, the lid containing sensor was immersed in cell culture medium, and different dissolved O2 concentrations were achieved by purging the solution with mixtures of N2 and O2 gas of known concentrations. commercially available technologies; second, it can perform simultaneous real-time measurements of oxygen consumption rate (OCR), extracellular acidification rate (ECAR), and mitochondrial membrane potential (MMP)a capability not offered by any 10058-F4 other commercially available technology. Our results revealed substantial diversity in response kinetics of the three analytes in dysplastic human epithelial esophageal cells and suggest the existence of varying cellular energy metabolism profiles and their kinetics among small populations of cells. The technology represents a powerful analytical tool for multiparameter studies of cellular function. Introduction Cellular communication plays a central role in tissue homeostasis and disease states. Cancer is viewed as cells evading normal MAP2K2 cell functionality through complex alterations in their signalling cascades and through cellular communication within the microenvironment1. Most of the current analytical approaches used to understand cancer and other diseases are based on performing assays with large populations of cells (>104). The information obtained with these approaches represents an ensemble average of the response from the entire cell population, while completely obscuring 10058-F4 the details about a possible spectrum of responses due to the presence of aberrant sub-populations of cells or even individual cells2. Elucidating such heterogeneous information about the composition of cell populations has the potential to reveal a detailed view of the disease state in the context of multicellular complexity by providing deep insight into cellular function. Cellular communication can occur in various ways and its role has been demonstrated in a variety of diseases. Mutations in genes encoding proteins of gap junction channels, one form of cellular communication, have been associated with deafness3, and sudden infant death syndrome4, while also being identified as a therapeutic target for reducing the spread of traumatic brain injury5 and heart injury6. Cell-to-cell communication via tight junctions has been shown to play an important role in cell proliferation7 and differentiation7,8, and has been implicated in a variety of diseases including cancer9C13. Cellular communication in cancer plays a key role in the tumor microenvironment facilitating tumor growth and metastasis14,15. The notion of cell-to-cell communication has also been reinforced by the finding that clusters of circulating tumor cells (CTCs)16C19 exhibit a significantly higher metastatic potential as compared to single CTCs20. This indicates that cell-cell interactions play a central role in metastasis formation and development. Developing technological platforms addressing the need of analysing the heterogeneity of cellular function in the presence of cell-to-cell communication represents a formidable challenge. One faces the difficulty of dissecting the responses of individual cells or small populations of cells in a 10058-F4 larger, heterogeneous population of cells with overlapping responses. On the other hand, while single-cell analysis approaches that are based on monitoring cellular function in individual cells in isolation address directly cellular heterogeneity21C25, their main disadvantage is the absence of cellular communication. As a compromise between the analysis of large populations of cells and individual cells, it is conceivable that one can utilize populations of communicating cells that are small enough to alleviate the ensemble averaging effect over thousands of cells with varying responses. Such a modality requires the generation of cell populations containing small, on the order of few to tens of cells, and controllable numbers of cells situated in close proximity, and an analysis system with adequate sensitivity and specificity to detect the relatively 10058-F4 weak signals from such small numbers of cells. Cell patterning using various cell-adhesive proteins, such as laminin for pancreatic cells26, fibronectin for mammalian27, and endothelial cells28 has been reported. In one 10058-F4 such study29 the authors explored the generation of spots of extracellular matrix (ECM) with two different dimensions: 20??20?m, and 40??40?m, for cell localization. It has been shown that the average number of cells per spot for the 20??20?m and 40??40?m geometries was 1.3, and 3.1, respectively. Our group has recently reported a non-contact method for the generation of small (<100 cells/population) populations of epithelial cells with high consistency30. Microcontact printing for developing arrays of cell adhesion regions, and cell adhesion protein for cell adhesion, are the methods of choice to achieve such cell cluster patterning. In this paper, we use cell adhesion promoting proteins for selective adhesion.