George E. Plopper

Adhesion to Vitronectin and Collagen I Promotes Osteogenic Differentiation of Human Mesenchymal Stem Cells.

The mechanisms controlling human mesenchymal stem cells (hMSC) differentiation are not entirely understood. We hypothesized that the contact with extracellular matrix (ECM) proteins normally found in bone marrow would promote osteogenic differentiation of hMSC in vitro. To test this hypothesis, we cultured hMSC on purified ECM proteins in the presence or absence of soluble osteogenic supplements, and assayed for the presence of well-established differentiation markers (production of mineralized matrix, osteopontin, osteocalcin, collagen I, and alkaline phosphatase expression) over a 16-day time course. We found that hMSC adhere to ECM proteins with varying affinity (fibronectin>collagen I≥collagen IV≥vitronectin>laminin-1) and through distinct integrin receptors. Importantly, the greatest osteogenic differentiation occurred in cells plated on vitronectin and collagen I and almost no differentiation took place on fibronectin or uncoated plates. We conclude that the contact with vitronectin and collagen I promotes the osteogenic differentiation of hMSC, and that ECM contact alone may be sufficient to induce differentiation in these cells.

ERK signaling pathways regulate the osteogenic differentiation of human mesenchymal stem cells on collagen I and vitronectin.

Adhesion to the extracellular matrix (ECM) proteins collagen I and vitronectin is sufficient to drive human mesenchymal stem cells (hMSCs) into an osteogenic differentiation pathway, but the mechanisms underlying this stimulation are not well understood. We found that addition of β1 and α vβ3 integrin blocking antibodies inhibited ECM-induced ERK activation, while addition of the MEK inhibitor PD98059 blocked ERK activation, serine phosphorylation of the osteogenic transcription factor runx2/cbfa-1, osteogenic gene expression, and calcium deposition. These results suggest that ERK plays an important role in driving the ECM-induced osteogenic differentiation of hMSC.

Activation of FAK is necessary for the osteogenic differentiation of human mesenchymal stem cells on laminin‐5

Human mesenchymal stem cell (hMSC) differentiation into osteoblasts and the signaling events involved are poorly understood. We recently established that contact with specific extracellular matrix (ECM) proteins, in particular laminin‐5, is sufficient to induce an osteogenic phenotype in hMSC through an extracellular signal‐related kinase (ERK)‐dependent pathway. Activation of ERK 1/2 by laminin‐5 induces phosphorylation of the runx2/cbfa‐1 transcription factor that controls osteogenic gene expression. We hypothesized that focal adhesion kinase (FAK) mediated signaling pathways supply a link between cell surface integrin‐ECM binding and activation of ERK 1/2, and that laminin‐5 promotes its osteogenic effects through this pathway. To test this hypothesis, we plated hMSC on a laminin‐5 matrix in the presence or absence of FAK‐specific small inhibitory RNAs (siRNA), and assayed for phosphorylation of runx2/cbfa‐1 as well as expression of established osteogenic differentiation markers (bone sialoprotein, osteocalcin, alkaline phosphatase, calcium deposition, and mineral:matrix ratio). We found that siRNA treatment reduced total endogenous FAK protein by ∼40%, and reduced FAK phosphorylation on Y397 by ∼33% in cells plated on laminin‐5 for 30 min. SiRNA treated cells exhibited a decrease in ERK 1/2 phosphorylation after 1 h, and reduced serine/threonine phosphorylation of Runx2/Cbfa‐1 after 8 days. Finally, FAK inhibition blocked osteogenic differentiation of hMSC, as assessed by lowered expression of osteogenic genes (RT‐PCR), decreased alkaline phosphatase activity, greatly reduced calcium deposition, and a lower mineral:matrix ratio after 28 days in culture. These results establish FAK as an important mediator of laminin‐5‐induced osteogenic differentiation of hMSC. J. Cell. Biochem. 100: 499–514, 2007.

Enhanced GLT-1 mediated glutamate uptake and migration of primary astrocytes directed by fibronectin-coated electrospun poly-L-lactic acid fibers.

Bioengineered fiber substrates are increasingly studied as a means to promote regeneration and remodeling in the injured central nervous system (CNS). Previous reports largely focused on the ability of oriented scaffolds to bridge injured regions and direct outgrowth of axonal projections. In the present work, we explored the effects of electrospun microfibers on the migration and physiological properties of brain astroglial cells. Primary rat astrocytes were cultured on either fibronectin-coated poly-L-lactic acid (PLLA) films, fibronectin-coated randomly oriented PLLA electrospun fibers, or fibronectin-coated aligned PLLA electrospun fibers. Aligned PLLA fibers strongly altered astrocytic morphology, orienting cell processes, actin microfilaments, and microtubules along the length of the fibers. On aligned fibers, astrocytes also significantly increased their migration rates in the direction of fiber orientation. We further investigated if fiber topography modifies astrocytic neuroprotective properties, namely glutamate and glutamine transport and metabolism. This was done by quantifying changes in mRNA expression (qRT-PCR) and protein levels (Western blotting) for a battery of relevant biomolecules. Interestingly, we found that cells grown on random and/or aligned fibers increased the expression levels of two glutamate transporters, GLAST and GLT-1, and an important metabolic enzyme, glutamine synthetase, as compared to the fibronectin-coated films. Functional assays revealed increases in glutamate transport rates due to GLT-1 mediated uptake, which was largely determined by the dihydrokainate-sensitive GLT-1. Overall, this study suggests that aligned PLLA fibers can promote directed astrocytic migration, and, of most importance, our in vitro results indicate for the first time that electrospun PLLA fibers can positively modify neuroprotective properties of glial cells by increasing rates of glutamate uptake.

Novel Image Analysis Approach Quantifies Morphological Characteristics of 3D Breast Culture Acini with Varying Metastatic Potentials

Prognosis of breast cancer is primarily predicted by the histological grading of the tumor, where pathologists manually evaluate microscopic characteristics of the tissue. This labor intensive process suffers from intra- and inter-observer variations; thus, computer-aided systems that accomplish this assessment automatically are in high demand. We address this by developing an image analysis framework for the automated grading of breast cancer in in vitro three-dimensional breast epithelial acini through the characterization of acinar structure morphology. A set of statistically significant features for the characterization of acini morphology are exploited for the automated grading of six (MCF10 series) cell line cultures mimicking three grades of breast cancer along the metastatic cascade. In addition to capturing both expected and visually differentiable changes, we quantify subtle differences that pose a challenge to assess through microscopic inspection. Our method achieves 89.0% accuracy in grading the acinar structures as nonmalignant, noninvasive carcinoma, and invasive carcinoma grades. We further demonstrate that the proposed methodology can be successfully applied for the grading of in vivo tissue samples albeit with additional constraints. These results indicate that the proposed features can be used to describe the relationship between the acini morphology and cellular function along the metastatic cascade.

Inhibition of ERK Promotes Collagen Gel Compaction and Fibrillogenesis to Amplify the Osteogenesis of Human Mesenchymal Stem Cells in Three-Dimensional Collagen I Culture

Tissue morphogenesis remains one of the least understood problems in cell and developmental biology. There is a disconnect between the mechanisms that apply to two-dimensional (2D) cultures and those seen in vivo. Three-dimensional (3D) culture presents a complex stimulus triggering cellular responses that are only partially understood. We compared 2D and 3D cultures of human mesenchymal stem cells in the presence of mitogen-activated protein kinase kinase (MEK) inhibitor, PD98059, to determine the role of extracellular signal-related kinase (ERK) in collagen-induced differentiation. 3D collagen I culture enhanced and accelerated the osteogenic differentiation of human mesenchymal stem cells (hMSC). Contrary to 2D results, the addition of PD98059 induced a significant amplification of osteogenic gene expression and matrix mineralization in 3D cultures. The inhibition of ERK altered cell-mediated compaction, proliferation, and resulted in the development of distinct tissue microstructure. Therefore, we suggest that the ability to reorganize collagen in 3D is an important step in ERK-mediated osteogenic differentiation. This work aims to propose a correlation between osteogenic differentiation and hMSC-directed collagen I remodeling. We present a potential mechanistic link (ERK) through which the three dimensionality of an engineered tissue acts to differentially induce and maintain cellular phenotype during tissue development.

ECM-aware cell-graph mining for bone tissue modeling and classification

Pathological examination of a biopsy is the most reliable and widely used technique to diagnose bone cancer. However, it suffers from both inter- and intra- observer subjectivity. Techniques for automated tissue modeling and classification can reduce this subjectivity and increases the accuracy of bone cancer diagnosis. This paper presents a graph theoretical method, called extracellular matrix (ECM)-aware cell-graph mining, that combines the ECM formation with the distribution of cells in hematoxylin and eosin stained histopathological images of bone tissues samples. This method can identify different types of cells that coexist in the same tissue as a result of its functional state. Thus, it models the structure-function relationships more precisely and classifies bone tissue samples accurately for cancer diagnosis. The tissue images are segmented, using the eigenvalues of the Hessian matrix, to compute spatial coordinates of cell nuclei as the nodes of corresponding cell-graph. Upon segmentation a color code is assigned to each node based on the composition of its surrounding ECM. An edge is hypothesized (and established) between a pair of nodes if the corresponding cell membranes are in physical contact and if they share the same color. Hence, multiple colored-cell-graphs coexist in a tissue each modeling a different cell-type organization. Both topological and spectral features of ECM-aware cell-graphs are computed to quantify the structural properties of tissue samples and classify their different functional states as healthy, fractured, or cancerous using support vector machines. Classification accuracy comparison to related work shows that the ECM-aware cell-graph approach yields 90.0% whereas Delaunay triangulation and the simple cell-graph approach achieves 75.0 and 81.1% accuracy, respectively.

Multiway modeling and analysis in stem cell systems biology

BackgroundSystems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.). A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models) can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells.ResultsWe applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC) models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a collagen I substrate accelerated the osteogenic differentiation induced by a static collagen I substrate.ConclusionOur results suggest gene- and protein-level models whereby stem cells undergo transdifferentiation to osteoblasts, and lay the foundation for mechanistic, hypothesis-driven studies. Our analysis methods are applicable to a wide range of stem cell differentiation models.

Phenylboronic acid selectively inhibits human prostate and breast cancer cell migration and decreases viability

We compared the in vitro effect of boric acid (BA) versus phenylboronic acid (PBA) on the migration of prostate and breast cancer cell lines and non-tumorigenic cells from the same tissues. Treatment at 24 hours with BA (≤ 500 µM) did not inhibit chemotaxis on fibronectin in any cell line. However, treatment over the same time course with concentrations of PBA as low as 1 µM significantly inhibited cancer cell migration without effecting non-tumorigenic cell lines. The compounds did not affect cell adhesion or viability at 24 hours but did alter morphology; both decreased cancer cell viability at 8 days. These results suggest that PBA is more potent than BA in targeting the metastatic and proliferative properties of cancer cells.

Proteomics reveals multiple routes to the osteogenic phenotype in mesenchymal stem cells

BackgroundRecently, we demonstrated that human mesenchymal stem cells (hMSC) stimulated with dexamethazone undergo gene focusing during osteogenic differentiation (Stem Cells Dev 14(6): 1608–20, 2005). Here, we examine the protein expression profiles of three additional populations of hMSC stimulated to undergo osteogenic differentiation via either contact with pro-osteogenic extracellular matrix (ECM) proteins (collagen I, vitronectin, or laminin-5) or osteogenic media supplements (OS media). Specifically, we annotate these four protein expression profiles, as well as profiles from naïve hMSC and differentiated human osteoblasts (hOST), with known gene ontologies and analyze them as a tensor with modes for the expressed proteins, gene ontologies, and stimulants.ResultsDirect component analysis in the gene ontology space identifies three components that account for 90% of the variance between hMSC, osteoblasts, and the four stimulated hMSC populations. The directed component maps the differentiation stages of the stimulated stem cell populations along the differentiation axis created by the difference in the expression profiles of hMSC and hOST. Surprisingly, hMSC treated with ECM proteins lie closer to osteoblasts than do hMSC treated with OS media. Additionally, the second component demonstrates that proteomic profiles of collagen I- and vitronectin-stimulated hMSC are distinct from those of OS-stimulated cells. A three-mode tensor analysis reveals additional focus proteins critical for characterizing the phenotypic variations between naïve hMSC, partially differentiated hMSC, and hOST.ConclusionThe differences between the proteomic profiles of OS-stimulated hMSC and ECM-hMSC characterize different transitional phenotypes en route to becoming osteoblasts. This conclusion is arrived at via a three-mode tensor analysis validated using hMSC plated on laminin-5.