[
Curr Biol,
2009]
BACKGROUND: Generation of membrane curvature is critical for the formation of plasma membrane protrusions and invaginations and for shaping intracellular organelles. Among the central regulators of membrane dynamics are the BAR superfamily domains, which deform membranes into tubular structures. In contrast to the relatively well characterized BAR and F-BAR domains that promote the formation of plasma membrane invaginations, I-BAR domains induce plasma membrane protrusions through a poorly understood mechanism. RESULTS: We show that I-BAR domains induce strong PI(4,5)P(2) clustering upon membrane binding, bend the membrane through electrostatic interactions, and remain dynamically associated with the inner leaflet of membrane tubules. Thus, I-BAR domains induce the formation of dynamic membrane protrusions to the opposite direction than do BAR and F-BAR domains. Strikingly, comparison of different I-BAR domains revealed that they deform PI(4,5)P(2)-rich membranes through distinct mechanisms. IRSp53 and IRTKS I-BARs bind membranes mainly through electrostatic interactions, whereas MIM and ABBA I-BARs additionally insert an amphipathic helix into the membrane bilayer, resulting in larger tubule diameter in vitro and more efficient filopodia formation in vivo. Furthermore, FRAP analysis revealed that whereas the mammalian I-BAR domains display dynamic association with filopodia, the C. elegans I-BAR domain forms relatively stable structures inside the plasma membrane protrusions. CONCLUSIONS: These data define I-BAR domain as a functional member of the BAR domain superfamily and unravel the mechanisms by which I-BAR domains deform membranes to induce filopodia in cells. Furthermore, our work reveals unexpected divergence in the mechanisms by which evolutionarily distinct groups of I-BAR domains interact with PI(4,5)P(2)-rich membranes.
[
MicroPubl Biol,
2019]
Nematodes, such as the model organism Caenorhabditis elegans, communicate environmental and developmental information with conspecifics through a class of small-molecule pheromones termed ascarosides (Butcher, 2017; Chute and Srinivasan, 2014; Ludewig and Schroeder, 2013). Nematodes share ascaroside signaling pathways (Choe et al., 2012), but are also capable of eavesdropping on chemical signals of predatory species (Liu et al., 2018). Ascarosides signal vast arrays of information, either individually or as blends, based on concentration, sex, physiological state, and other ascarosides sensed (McGrath and Ruvinsky, 2019; Pungaliya et al., 2009; Srinivasan et al., 2008; Srinivasan et al., 2012). For instance, octopamine-succinylated ascaroside #9 (osas#9) is able to signal starvation conditions in the absence of other ascarosides (Artyukhin et al., 2013).C. elegans (Cel) is an androdioecious species, with the majority of the natural population comprised of self-fertilizing hermaphrodites, and a small proportion (<0.2%) being male (Hodgkin et al., 1979). There are two other similarly androdioecious species in the genus, C. briggsae (Cbr) and C. tropicalis (Ctr). All three species evolved their hermaphroditism separately and uniquely (Ellis and Lin, 2014). Of the male-attracting ascarosides secreted by C. elegans (ascr#2, ascr#3, ascr#4, and ascr#8), ascr#8 is the most potent (Pungaliya et al., 2009). Since ascr#8 is a male attractant in this hermaphroditic species, we asked if other hermaphroditic species retained the ability to attract males using this cue. Males from the gonochoristic (male-female) sister species to C. briggsae and C. tropicalis C. nigoni (Cni) and C. wallacei (Cwa), respectively were also assayed for their ability to respond to ascr#8. The closest relative of C. elegans, the gonochoristic C. inopinata (Cin, formerly C. sp. 34), which has been recently characterized (Kanzaki et al., 2018), was also tested, along with the JaponicaGroup gonochoristic species C. japonica(Cja) and C. afra(Caf).Dwell times were analyzed as previously described using a Spot Retention Assay (Narayan et al., 2016). Dwell times were transformed using a Base 2 Exponentiation (2n, wherein n is equal to the raw dwell time value) to generate only non-zero data in order to calculate fold-changes. The Logbase2 of the fold-changes was then calculated to normalize the data. All data sets were first checked for normality using a DAgostino
[
Methods Mol Biol,
2015]
Optogenetics was introduced as a new technology in the neurosciences about a decade ago (Zemelman et al., Neuron 33:15-22, 2002; Boyden et al., Nat Neurosci 8:1263-1268, 2005; Nagel et al., Curr Biol 15:2279-2284, 2005; Zemelman et al., Proc Natl Acad Sci USA 100:1352-1357, 2003). It combines optics, genetics, and bioengineering to render neurons sensitive to light, in order to achieve a precise, exogenous, and noninvasive control of membrane potential, intracellular signaling, network activity, or behavior (Rein and Deussing, Mol Genet Genomics 287:95-109, 2012; Yizhar et al., Neuron 71:9-34, 2011). As C. elegans is transparent, genetically amenable, has a small nervous system mapped with synapse resolution, and exhibits a rich behavioral repertoire, it is especially open to optogenetic methods (White et al., Philos Trans R Soc Lond B Biol Sci 314:1-340, 1986; De Bono et al., Optogenetic actuation, inhibition, modulation and readout for neuronal networks generating behavior in the nematode Caenorhabditis elegans, In: Hegemann P, Sigrist SJ (eds) Optogenetics, De Gruyter, Berlin, 2013; Husson et al., Biol Cell 105:235-250, 2013; Xu and Kim, Nat Rev Genet 12:793-801, 2011). Optogenetics, by now an "exploding" field, comprises a repertoire of different tools ranging from transgenically expressed photo-sensor proteins (Boyden et al., Nat Neurosci 8:1263-1268, 2005; Nagel et al., Curr Biol 15:2279-2284, 2005) or cascades (Zemelman et al., Neuron 33:15-22, 2002) to chemical biology approaches, using photochromic ligands of endogenous channels (Szobota et al., Neuron 54:535-545, 2007). Here, we will focus only on optogenetics utilizing microbial rhodopsins, as these are most easily and most widely applied in C. elegans. For other optogenetic tools, for example the photoactivated adenylyl cyclases (PACs, that drive neuronal activity by increasing synaptic vesicle priming, thus exaggerating rather than overriding the intrinsic activity of a neuron, as occurs with rhodopsins), we refer to other literature (Weissenberger et al., J Neurochem 116:616-625, 2011; Steuer Costa et al., Photoactivated adenylyl cyclases as optogenetic modulators of neuronal activity, In: Cambridge S (ed) Photswitching proteins, Springer, New York, 2014). In this chapter, we will give an overview of rhodopsin-based optogenetic tools, their properties and function, as well as their combination with genetically encoded indicators of neuronal activity. As there is not "the" single optogenetic experiment we could describe here, we will focus more on general concepts and "dos and don'ts" when designing an optogenetic experiment. We will also give some guidelines on which hardware to use, and then describe a typical example of an optogenetic experiment to analyze the function of the neuromuscular junction, and another application, which is Ca(2+) imaging in body wall muscle, with upstream neuronal excitation using optogenetic stimulation. To obtain a more general overview of optogenetics and optogenetic tools, we refer the reader to an extensive collection of review articles, and in particular to volume 1148 of this book series, "Photoswitching Proteins."