Tropomyosin Isoforms Specify Functionally Distinct Actin Filament Populations In Vitro.

Actin filaments assemble into a variety of networks to provide force for diverse cellular processes [1]. Tropomyosins are coiled-coil dimers that form head-to-tail polymers along actin filaments and regulate interactions of other proteins, including actin-depolymerizing factor (ADF)/cofilins and myosins, with actin [2-5]. In mammals, >40 tropomyosin isoforms can be generated through alternative splicing from four tropomyosin genes. Different isoforms display non-redundant functions and partially non-overlapping localization patterns, for example within the stress fiber network [6, 7]. Based on cell biological studies, it was thus proposed that tropomyosin isoforms may specify the functional properties of different actin filament populations [2]. To test this hypothesis, we analyzed the properties of actin filaments decorated by stress-fiber-associated tropomyosins (Tpm1.6, Tpm1.7, Tpm2.1, Tpm3.1, Tpm3.2, and Tpm4.2). These proteins bound F-actin with high affinity and competed with α-actinin for actin filament binding. Importantly, total internal reflection fluorescence (TIRF) microscopy of fluorescently tagged proteins revealed that most tropomyosin isoforms cannot co-polymerize with each other on actin filaments. These isoforms also bind actin with different dynamics, which correlate with their effects on actin-binding proteins. The long isoforms Tpm1.6 and Tpm1.7 displayed stable interactions with actin filaments and protected filaments from ADF/cofilin-mediated disassembly, but did not activate non-muscle myosin IIa (NMIIa). In contrast, the short isoforms Tpm3.1, Tpm3.2, and Tpm4.2 displayed rapid dynamics on actin filaments and stimulated the ATPase activity of NMIIa, but did not efficiently protect filaments from ADF/cofilin. Together, these data provide experimental evidence that tropomyosin isoforms segregate to different actin filaments and specify functional properties of distinct actin filament populations.

Architecture dependence of actin filament network disassembly.

Turnover of actin networks in cells requires the fast disassembly of aging actin structures. While ADF/cofilin and Aip1 have been identified as central players, how their activities are modulated by the architecture of the networks remains unknown. Using our ability to reconstitute a diverse array of cellular actin organizations, we found that ADF/cofilin binding and ADF/cofilin-mediated disassembly both depend on actin geometrical organization. ADF/cofilin decorates strongly and stabilizes actin cables, whereas its weaker interaction to Arp2/3 complex networks is correlated with their dismantling and their reorganization into stable architectures. Cooperation of ADF/cofilin with Aip1 is necessary to trigger the full disassembly of all actin filament networks. Additional experiments performed at the single-molecule level indicate that this cooperation is optimal above a threshold of 23 molecules of ADF/cofilin bound as clusters along an actin filament. Our results indicate that although ADF/cofilin is able to dismantle selectively branched networks through severing and debranching, stochastic disassembly of actin filaments by ADF/cofilin and Aip1 represents an efficient alternative pathway for the full disassembly of all actin networks. Our data support a model in which the binding of ADF/cofilin is required to trigger a structural change of the actin filaments, as a prerequisite for their disassembly by Aip1.

Dynamic reorganization of the actin cytoskeleton.

Cellular processes, including morphogenesis, polarization, and motility, rely on a variety of actin-based structures. Although the biochemical composition and filament organization of these structures are different, they often emerge from a common origin. This is possible because the actin structures are highly dynamic. Indeed, they assemble, grow, and disassemble in a time scale of a second to a minute. Therefore, the reorganization of a given actin structure can promote the formation of another. Here, we discuss such transitions and illustrate them with computer simulations.