-
[show abstract]
[hide abstract]
ABSTRACT: The extracellular matrix (ECM) is thought to be an essential component of tissue scaffolding and engineering because it fulfills fundamental functions related to cell adhesion, migration, and three-dimensional organization. Natural ECM preparations, however, are challenging to work with because they are comprised of macromolecules that are large and insoluble in their functional state. Functional fragments of ECM macromolecules are a viable answer to this challenge, as demonstrated by the RGD-based engineered scaffolds, where the tri-peptide, Arg-Gly-Asp (RGD), represents the minimal functional unit of fibronectin and related ECM. Laminins (Ln) are main components of epithelial tissues, since they enter into the composition of basement membranes. Application of Ln to epithelial tissue engineering would be desirable, since they could help mimic ideal functional conditions for both lining and glandular epithelial tissues. However, functional fragments of Ln that could be used in artificial settings have not been characterized in detail. In this paper, we describe the production and application of the recombinant LG4 (rLG4) fragment of laminin-332 (Ln-332), and show that it mimics three fundamental functional properties of Ln-332: integrin-mediated cell adhesion, spreading, and migration. Adhesive structures formed by cells on rLG4 closely resemble those formed on Ln-332, as judged by microscopy-based analyses of their molecular composition. As on Ln-332, focal adhesion kinase (FAK) is phosphorylated in cells adhering to rLG4, and colocalized with other focal adhesion components. We conclude that rLG4 could be a useful substitute to recapitulate, in vitro, the tissue scaffolding properties of Ln-332.
Biomaterials 03/2010; 31(19):5110-21. · 7.40 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Mapping quantitative cell traits (QCT) to underlying molecular defects is a central challenge in cancer research because heterogeneity at all biological scales, from genes to cells to populations, is recognized as the main driver of cancer progression and treatment resistance. A major roadblock to a multiscale framework linking cell to signaling to genetic cancer heterogeneity is the dearth of large-scale, single-cell data on QCT-such as proliferation, death sensitivity, motility, metabolism, and other hallmarks of cancer. High-volume single-cell data can be used to represent cell-to-cell genetic and nongenetic QCT variability in cancer cell populations as averages, distributions, and statistical subpopulations. By matching the abundance of available data on cancer genetic and molecular variability, QCT data should enable quantitative mapping of phenotype to genotype in cancer. This challenge is being met by high-content automated microscopy (HCAM), based on the convergence of several technologies including computerized microscopy, image processing, computation, and heterogeneity science. In this chapter, we describe an HCAM workflow that can be set up in a medium size interdisciplinary laboratory, and its application to produce high-throughput QCT data for cancer cell motility and proliferation. This type of data is ideally suited to populate cell-scale computational and mathematical models of cancer progression for quantitatively and predictively evaluating cancer drug discovery and treatment.
Methods in enzymology 01/2009; 467:23-57. · 1.90 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Cell migration is essential in many physiological and pathological processes. To understand this complex behavior, researchers have turned to quantitative, in vitro, image-based measurements to dissect the steps of cellular motility. With the rise of automated microscopy, the bottleneck in these approaches is no longer data acquisition, but data analysis. Using time-lapse microscopy and computer-assisted image analysis, we have developed a novel, quantitative assay that extracts a multivariate profile for cellular motility. This technique measures three dynamic parameters per single cell: speed, surface area, and an in-dex of cell expansion/contraction activity (DECCA). Our assay can be used in combination with a variety of extracellular matrix components, or other soluble agents, to analyze the effects of the microenvironment on cellular migration dynamics in vitro. Our application was developed and tested using A431 and HT-1080 cell lines plated on laminin-332 or fibronectin substrates. Our results indicate that HT-1080 cells migrate faster, have a greater surface area, and have a higher DECCA index than A431 cells on both matrices (for all parameters, p < 0.05). Spearman's correlation coefficients suggest that for these cell lines and matrices, various combinations of the three measurements display low to medium-high levels of correlation. These findings compare well with previous literature. Our approach provides new tools to measure cellular migration dynamics and address questions on the relationship between cell motility and the microenvironment, using only common microscopy techniques, accessible image analysis applications, and a basic desktop computer for image processing.
Cell adhesion & migration 04/2008; 2(2):127-36. · 1.82 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: The overall mechanisms governing the role of laminins during osteogenic differentiation of human mesenchymal stem cells (hMSC) are poorly understood. We previously reported that laminin-332 induces an osteogenic phenotype in hMSC and does so through a focal adhesion kinase (FAK) and extracellular signal-related kinase (ERK) dependent pathway. We hypothesized that this is a result of integrin-ECM binding, and that it occurs via the known alpha3 LG3 integrin binding domain of laminin-332. To test this hypothesis we cultured hMSC on several different globular domains of laminin-332. hMSC adhered best to the LG3 domain, and this adhesion maximally activated FAK and ERK within 120 min. Prolonged culturing (8 or 16 days) of hMSC on LG3 led to activation of the osteogenic transcription factor Runx2 and expression of key osteogenic markers (osterix, bone sialoprotein 2, osteocalcin, alkaline phosphatase, extracellular calcium) in hMSC. LG3 domain binding did not increase matrix mineralization, demonstrating that the LG3 domain alone is not sufficient to induce complete osteogenic differentiation in vitro. We conclude that the LG3 domain mediates attachment of hMSC to laminin-332 and that this adhesion recapitulates most, but not all, of the osteogenic differentiation associated with laminin-5 binding to hMSC.
Experimental Cell Research 03/2008; 314(4):763-73. · 3.58 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: The SWA2/AUX1 gene has been proposed to encode the Saccharomyces cerevisiae ortholog of mammalian auxilin. Swa2p is required for clathrin assembly/dissassembly in vivo, thereby implicating it in intracellular protein and lipid trafficking. While investigating the 287-residue N-terminal region of Swa2p, we found a single stably folded domain between residues 140 and 180. Using binding assays and structural analysis, we established this to be a ubiquitin-associated (UBA) domain, unidentified by bioinformatics of the yeast genome. We determined the solution structure of this Swa2p domain and found a characteristic three-helix UBA fold. Comparisons of structures of known UBA folds reveal that the position of the third helix is quite variable. This helix in Swa2p UBA contains a bulkier tyrosine in place of smaller residues found in other UBAs and cannot pack as close to the second helix. The molecular surface of Swa2p UBA has a mostly negative potential, with a single hydrophobic surface patch found also in the UBA domains of human protein, HHR23A. The presence of a UBA domain implicates Swa2p in novel roles involving ubiquitin and ubiquitinated substrates. We propose that Swa2p is a multifunctional protein capable of recognizing several proteins through its protein-protein recognition domains.
Proteins Structure Function and Bioinformatics 04/2004; 54(4):784-93. · 3.39 Impact Factor
-
[show abstract]
[hide abstract]
ABSTRACT: Mapping quantitative cell traits (QCT) to underlying molecular defects is a central challenge in cancer research because heterogeneity at all biological scales, from genes to cells to populations, is recognized as the main driver of cancer progression and treatment resistance. A major roadblock to a multiscale framework linking cell to signaling to genetic cancer heterogeneity is the dearth of large-scale, single-cell data on QCT-such as proliferation, death sensitivity, motility, metabolism, and other hallmarks of cancer. High-volume single-cell data can be used to represent cell-to-cell genetic and nongenetic QCT variability in cancer cell populations as averages, distributions, and statistical subpopulations. By matching the abundance of available data on cancer genetic and molecular variability, QCT data should enable quantitative mapping of phenotype to genotype in cancer. This challenge is being met by high-content automated microscopy (HCAM), based on the convergence of several technologies including computerized microscopy, image processing, computation, and heterogeneity science. In this chapter, we describe an HCAM workflow that can be set up in a medium size interdisciplinary laboratory, and its application to produce high-throughput QCT data for cancer cell motility and proliferation. This type of data is ideally suited to populate cell-scale computational and mathematical models of cancer progression for quantitatively and predictively evaluating cancer drug discovery and treatment.
Methods in Enzymology.
