Macrophages serve to maintain organ homeostasis in response to challenges from injury, inflammation, malignancy, particulate exposure, or infection. Until now, receptor ligation has been understood as being the central mechanism that regulates macrophage function. Using macrophages of different origins and species, we report that macrophage elasticity is a major determinant of innate macrophage function. Macrophage elasticity is modulated not only by classical biologic activators such as LPS and IFN-γ, but to an equal extent by substrate rigidity and substrate stretch. Macrophage elasticity is dependent upon actin polymerization and small rhoGTPase activation, but functional effects of elasticity are not predicted by examination of gene expression profiles alone. Taken together, these data demonstrate an unanticipated role for cell elasticity as a common pathway by which mechanical and biologic factors determine macrophage function.

BackgroundCells resident in certain hollow organs are subjected routinely to large transient stretches, including every adherent cell resident in lungs, heart, great vessels, gut, and bladder. We have shown recently that in response to a transient stretch the adherent eukaryotic cell promptly fluidizes and then gradually resolidifies, but mechanism is not yet understood.Principal FindingsIn the isolated human bladder smooth muscle cell, here we applied a 10% transient stretch while measuring cell traction forces, elastic modulus, F-actin imaging and the F-actin/G-actin ratio. Immediately after a transient stretch, F-actin levels and cell stiffness were lower by about 50%, and traction forces were lower by about 70%, both indicative of prompt fluidization. Within 5min, F-actin levels recovered completely, cell stiffness recovered by about 90%, and traction forces recovered by about 60%, all indicative of resolidification. The extent of the fluidization response was uninfluenced by a variety of signaling inhibitors, and, surprisingly, was localized to the unstretch phase of the stretch-unstretch maneuver in a manner suggestive of cytoskeletal catch bonds. When we applied an “unstretch-restretch” (transient compression), rather than a “stretch-unstretch” (transient stretch), the cell did not fluidize and the actin network did not depolymerize.ConclusionsTaken together, these results implicate extremely rapid actin disassembly in the fluidization response, and slow actin reassembly in the resolidification response. In the bladder smooth muscle cell, the fluidization response to transient stretch occurs not through signaling pathways, but rather through release of increased tensile forces that drive acute disassociation of actin.

As cellular models for in vitro liver cancer and toxicity studies, HepG2 and Hep3B are the two most frequently used liver cancer cell lines. Because of their similarities they are often treated as the same in experimental studies. However, there are many differences that have been largely over-sighted or ignored between them. In this review, we summarize the differences between HepG2 and Hep3B cell lines that can be found in the literature based on PubMed search. We particularly focus on the differential gene expression, differential drug responses (chemosensitivity, cell cycle and growth inhibition, and gene induction), signaling pathways associated with these differences, as well as the factors in governing these differences between HepG2 and Hep3B cell lines. Based on our analyses of the available data, we suggest that neither HBx nor p53 may be the crucial factor to determine the differences between HepG2 and Hep3B cell lines although HBx regulates the expression of the majority of genes that are differentially expressed between HepG2 and Hep3B. Instead, the different maturation stages in cancer development of the original specimen between HepG2 and Hep3B may be responsible for the differences between them. This review provides insight into the molecular mechanisms underlying the differences between HepG2 and Hep3B and help investigators especially the beginners in the areas of liver cancer research and drug metabolism to fully understand, and thus better use and interpret the data from these two cell lines in their studies.

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