No abstract

Stochasticity in gene expression, protein or metabolite levels contributes to cell-cell variations, the analysis of which could lead to a better understanding of cellular processes and drug responses. Current technologies are limited in their throughput, resolution (in space, time, and tracking individual cells instead of population average) and the ability to control cellular environment. A few microfluidic tools have been developed to trap and image cells; however, in most designs available to date, there is a compromise among loading efficiency, speed, the ability to trap single cells, and density or number of trapped cells. To meet the needs of single-cell imaging studies, we developed a microfluidic platform for high-throughput capture and imaging of thousands of single cells. The optimized trapping mechanism enables 95% of the traps to be occupied with single cells, with a trap density of 860 traps / mm2. The dense array allows up to 800 cells to be imaged simultaneously with a 4× objective and a typical camera setup. Capture occurs with low shear and 94% viability after 24h. This platform is compatible with other upstream microfluidic components for complex cell stimulation patterns, and we show here the ability to measure heterogeneity in calcium oscillatory behavior in genetically identical cells and monitor kinetic cellular response to chemical stimuli.

The bone marrow niche for mesenchymal stem cells (MSCs) contains different amounts of bone and fat that vary with age and certain pathologies. How this dynamic niche environment may affect their differentiation potential and/or healing properties for clinical applications remains unknown, largely due to the lack of physiologically relevant in vitro models. We developed an enabling platform to isolate and study effects of signaling interactions between tissue-scale, laminated hydrogel modules of multiple cell types in tandem. We applied this platform to co-and tri-culture of primary human MSCs, osteoblasts, and adipocytes over 18 days in vitro. Each cell type was analyzed separately with quantitative polymerase chain reaction (qPCR) and histochemistry for several mesenchymal lineage markers. Distinct expression dynamics for osteogenic, adipogenic, chondrogenic, and myogenic transcriptional regulators resulted within each cell type depending on its culture setting. Incorporating this data into multivariate models produced latent identifiers of each emergent cell type dependent on its co-or triculture setting. Histological staining showed sustained triglyceride storage in adipocytes regardless of culture condition, but transient alkaline phosphatase activity in both osteoblasts and MSCs. Taken together, our results suggest novel emergent phenotypes for MSCs, osteoblasts, and adipocytes in bone marrow that are dependent on and result in part from paracrine interactions with their neighboring cell types.

Adoptive T-cell transfer therapy relies upon in vitro expansion of autologous cytotoxic T cells that are capable of tumor recognition. The success of this cell-based therapy depends on the specificity and responsiveness of the T cell clones before transfer. During ex vivo expansion, CD8؉ T cells present signs of replicative senescence and loss of function. The transfer of nonresponsive senescent T cells is a major bottleneck for the success of adoptive T-cell transfer therapy. Quantitative methods for assessing cellular age and responsiveness will facilitate the development of appropriate cell expansion and selection protocols. Although several biomarkers of lymphocyte senescence have been identified, these proteins in isolation are not sufficient to determine the age-dependent responsiveness of T cells. We have developed a multivariate model capable of extracting combinations of markers that are the most informative to predict cellular age. To acquire signaling information with high temporal resolution, we designed a microfluidic chip enabling parallel lysis and fixation of stimulated cell samples on-chip. The acquisition of 25 static biomarkers and 48 dynamic signaling measurements at different days in culture, integrating single-cell and population based information, allowed the multivariate regression model to accurately predict CD8؉ T-cell age. From surface marker expression and early phosphorylation events following T-cell receptor stimulation, the model successfully predicts days in culture and number of population doublings with R 2 ‫؍‬ 0.91 and 0.98, respectively. Furthermore, we found that impairment of early signaling events following T cell receptor stimulation because of long term culture allows prediction of costimulatory molecules CD28 and CD27 expression levels and the number of population divisions in culture from a limited subset of signaling proteins. The multivariate analysis highlights the information content of both averaged biomarker values and heterogeneity metrics for prediction of cellular age within a T cell population.

The differentiation of pluripotent stem cells as embryoid bodies (EBs) remains a common method for inducing differentiation toward many lineages. However, differentiation via EBs typically yields a significant amount of heterogeneity in the cell population, as most cells differentiate simultaneously toward different lineages, while others remain undifferentiated. Moreover, physical parameters, such as the size of EBs, can modulate the heterogeneity of differentiated phenotypes due to the establishment of nutrient and oxygen gradients. One of the challenges in examining the cellular composition of EBs is the lack of analytical methods that are capable of determining the phenotype of all of the individual cells that comprise a single EB. Therefore, the objective of this work was to examine the ability of a microfluidic cell trapping array to analyze the heterogeneity of cells comprising EBs during the course of early differentiation. The heterogeneity of single cell phenotype on the basis of protein expression of the pluripotent transcription factor OCT-4 was examined for populations of EBs and single EBs of different sizes at distinct stages of differentiation. Results from the cell trap device were compared with flow cytometry and whole mount immunostaining. Additionally, single cells from dissociated pooled EBs or individual EBs were examined separately to discern potential differences in the value or variance of expression between the different methods of analysis. Overall, the analytical method described represents a novel approach for evaluating how heterogeneity is manifested in EB cultures and may be used in the future to assess the kinetics and patterns of differentiation in addition to the loss of pluripotency.