Expansion of hematopoietic stem cells in vitro as a model system for human tissue engineering

Stem cells: a model for screening, discovery and development of drugs

The identification of normal and cancerous stem cells and the recent advances made in isolation and culture of stem cells have rapidly gained attention in the field of drug discovery and regenerative medicine. The prospect of performing screens aimed at proliferation, directed differentiation, and toxicity and efficacy studies using stem cells offers a reliable platform for the drug discovery process. Advances made in the generation of induced pluripotent stem cells from normal or diseased tissue serves as a platform to perform drug screens aimed at developing cell-based therapies against conditions like Parkinson’s disease and diabetes. This review discusses the application of stem cells and cancer stem cells in drug screening and their role in complementing, reducing, and replacing animal testing. In addition to this, target identification and major advances in the field of personalized medicine using induced pluripotent cells are also discussed.

A new approach to the rationale discovery of polymeric biomaterials

This paper attempts to illustrate both the need for new approaches to biomaterials discovery as well as the significant promise inherent in the use of combinatorial and computational design strategies. The key observation of this Leading Opinion Paper is that the biomaterials community has been slow to embrace advanced biomaterials discovery tools such as combinatorial methods, high-throughput experimentation, and computational modeling in spite of the significant promise shown by these discovery tools in materials science, medicinal chemistry and the pharmaceutical industry. It seems that the complexity of living cells and their interactions with biomaterials has been a conceptual as well as a practical barrier to the use of advanced discovery tools in biomaterials science. However, with the continued increase in computer power, the goal of predicting the biological response of cells in contact with biomaterials surfaces is within reach. Once combinatorial synthesis, high-throughput experimentation, and computational modeling are integrated into the biomaterials discovery process, a significant acceleration is possible in the pace of development of improved medical implants, tissue regeneration scaffolds, and gene/drug delivery systems.

Automated measurement of cell motility and proliferation

Background

Time-lapse microscopic imaging provides a powerful approach for following changes in cell phenotype over time. Visible responses of whole cells can yield insight into functional changes that underlie physiological processes in health and disease. For example, features of cell motility accompany molecular changes that are central to the immune response, to carcinogenesis and metastasis, to wound healing and tissue regeneration, and to the myriad developmental processes that generate an organism. Previously reported image processing methods for motility analysis required custom viewing devices and manual interactions that may introduce bias, that slow throughput, and that constrain the scope of experiments in terms of the number of treatment variables, time period of observation, replication and statistical options. Here we describe a fully automated system in which images are acquired 24/7 from 384 well plates and are automatically processed to yield high-content motility and morphological data.

Results

We have applied this technology to study the effects of different extracellular matrix compounds on human osteoblast-like cell lines to explore functional changes that may underlie processes involved in bone formation and maintenance. We show dose-response and kinetic data for induction of increased motility by laminin and collagen type I without significant effects on growth rate. Differential motility response was evident within 4 hours of plating cells; long-term responses differed depending upon cell type and surface coating. Average velocities were increased approximately 0.1 um/min by ten-fold increases in laminin coating concentration in some cases. Comparison with manual tracking demonstrated the accuracy of the automated method and highlighted the comparative imprecision of human tracking for analysis of cell motility data. Quality statistics are reported that associate with stage noise, interference by non-cell objects, and uncertainty in the outlining and positioning of cells by automated image analysis. Exponential growth, as monitored by total cell area, did not linearly correlate with absolute cell number, but proved valuable for selection of reliable tracking data and for disclosing between-experiment variations in cell growth.

Conclusion

These results demonstrate the applicability of a system that uses fully automated image acquisition and analysis to study cell motility and growth. Cellular motility response is determined in an unbiased and comparatively high throughput manner. Abundant ancillary data provide opportunities for uniform filtering according to criteria that select for biological relevance and for providing insight into features of system performance. Data quality measures have been developed that can serve as a basis for the design and quality control of experiments that are facilitated by automation and the 384 well plate format. This system is applicable to large-scale studies such as drug screening and research into effects of complex combinations of factors and matrices on cell phenotype.

The role of CD34 expression and cellular fusion in the regeneration capacity of myogenic progenitor cells

Characterization of myogenic subpopulations has traditionally been performed independently of their functional performance following transplantation. Using the preplate technique, which separates cells based on their variable adhesion characteristics, we investigated the use of cell surface proteins to potentially identify progenitors with enhanced regeneration capabilities. Based on previous studies, we used cell sorting to investigate stem cell antigen-1 (Sca-1) and CD34 expression on myogenic populations with late adhesion characteristics. We compared the regeneration efficiency of these sorted progenitors, as well as those displaying early adhesion characteristics, by quantifying their ability to regenerate skeletal muscle and restore dystrophin following transplantation into allogenic dystrophic host muscle. Identification and utilization of late adhering populations based on CD34 expression led to differential regeneration, with CD34-positive populations exhibiting significant improvements in dystrophin restoration compared with both their CD34-negative counterparts and early adhering cell populations. Regenerative capacity was found to correspond to the level of myogenic commitment, defined by myogenic regulatory factor expression, and the rate and degree of induced cell differentiation and fusion. These results demonstrate the ability to separate definable subpopulations of myogenic progenitors based on CD34 expression and reveal the potential implications of defining myogenic cell behavioral and phenotypic characteristics in relation to their regenerative capacity in vivo.

Mechanisms of muscle stem cell expansion with cytokines

Stem cell expansion and proliferation are important for cell transplantation and stem cell-mediated applications. While we have demonstrated that muscle stem cells can be obtained from adult skeletal muscle tissue, these cells represent only a small percentage of the muscle-derived cells and require in vitro expansion for successful stem cell-mediated therapies. In this study, we have examined the potential of several cytokines to stimulate stem cell growth by combining a non-exponential mathematical model with a unique cell culture system. The growth kinetics of two populations of muscle stem cells were characterized in culture medium supplemented with epidermal growth factor (EGF), fibroblast growth factor-2 (FGF-2), insulin-like growth factor-1 (IGF-1), FLT-3 ligand, hepatocyte growth factor, or stem cell factor (SCF). The division time (DT) and fraction of mitotically active cells were investigated as key parameters to further understand the mechanism of the expansion of the stem cell populations. Our results show that expansion of the freshly isolated, muscle-derived stem cells (MDSC) occurred by recruiting cells into the cell cycle in the presence of EGF, IGF-1, and SCF. However, expansion of the cultured stem cell clone, MC13, is attributed to a reduction of the length of the cell cycle in the presence of FGF-2, EGF, IGF-1, and SCF. Both MDSC and MC13 growth were inhibited in the presence of FLT-3 ligand by increasing the length of the cell cycle. Our results suggest that EGF, IGF-1, FGF-2, and SCF are important cytokines for stimulating the proliferation of MDSC. In addition, this study illustrates that expansion of stem cells occurs through different mechanisms, which consequently demonstrates the importance of monitoring several parameters of cell growth, such as DT and dividing fraction, following stimulation with growth factors.