Nonvesicular Lipid Transfer from the Endoplasmic Reticulum

The transport of lipids from their synthesis site at the endoplasmic reticulum (ER) to different target membranes could be mediated by both vesicular and nonvesicular transport mechanisms. Nonvesicular lipid transport appears to be the major transport route of certain lipid species, and could be mediated by either spontaneous lipid transport or by lipid-transfer proteins (LTPs). Although nonvesicular lipid transport has been extensively studied for more than four decades, its underlying mechanism, advantage and regulation, have not been fully explored. In particular, the function of LTPs and their involvement in intracellular lipid movement remain largely controversial. In this article, we describe the pathways by which lipids are synthesized at the ER and delivered to different cellular membranes, and discuss the role of LTPs in lipid transport both in vitro and in intact cells.The endoplasmic reticulum (ER) is a large interconnected membrane network that plays a major role in lipid biosynthesis in eukaryotic cells (Borgese et al. 2006). Newly synthesized lipids at the ER are then delivered to different cellular membranes or organelles, each of which shows unique lipid and protein composition and executes distinct cellular function (Holthuis et al. 2003). The transport of lipids from the ER can be mediated by both vesicular and nonvesicular transport mechanisms. Vesicular transport, as opposed to nonvesicular lipid transport, requires metabolic energy, intact cytoskeleton, and connection to the vesicular transport machinery (Kaplan and Simoni 1985a; Voelker 1990; Vance et al. 1991). Although vesicular lipid transport mediates the bulk transport of many lipids, increasing lines of evidence suggest that nonvesicular lipid transport is the major transport route for certain lipid types (Lev 2010). Nonvesicular lipid transport between membranes could be mediated by spontaneous lipid transport, in which a lipid monomer is diffused through the cytosol from a donor to the acceptor membrane. Given that most cellular lipids are highly hydrophobic, their diffusion through an aqueous phase is very slow and insufficient to support substantial transport of most lipids (Jones and Thompson 1989; Mesmin and Maxfield 2009). Nevertheless, spontaneous lipid transport can be greatly facilitated at membrane contact sites (MCSs) (Levine 2004; Holthuis and Levine 2005) and/or by lipid-transfer proteins (LTPs) (Lev 2010). MCSs are defined as small cytosolic gaps of 10–20 nm between the ER membranes and virtually all cellular organelles (Levine 2004; Lebiedzinska et al. 2009), whereas LTPs are intracellular proteins that can carry a lipid monomer in a hydrophobic pocket and transfer it between membranes through an aqueous phase. LTPs were initially discovered as soluble factors that accelerate the exchange or net transfer of different lipid species between membranes in vitro (Wirtz and Zilversmit 1968). Subsequently, many LTPs have been isolated, cloned, and crystallized. LTPs have been identified in all eukaryotes, in plants, and in bacteria, and according to their sequence and structure similarity have been subdivided into different protein families including SEC14, PITP (phosphatidylinositol-transfer protein), START (StAR-related lipid transfer), GLTP (glycolipid transfer protein), SCP-2 (nonspecific LTPs), and OSBP (oxysterol-binding protein)/ORP (OSBP-related proteins) (D’Angelo et al. 2008). In general, LTPs show specificity for one or more lipid types, and may contain only a single lipid-transfer domain (LTD), or additional structural domains with varying functions (Lev 2010). Over the past 40 years, LTPs have been extensively studied and the major principles of their action mode have been established from both biophysical measurements in vitro and structural data (Lev 2010). Nevertheless, the precise function of LTPs in intact cells remains controversial and a subject of an active field of research. In this article, we briefly describe how lipids are synthesized in the ER and delivered to different target membranes, and discuss how LTPs influence lipid transport in vitro and in intact cells.     

Lipid Transport between the Endoplasmic Reticulum and Mitochondria

Mitochondria are partially autonomous organelles that depend on the import of certain proteins and lipids to maintain cell survival and membrane formation. Although phosphatidylglycerol, cardiolipin, and phosphatidylethanolamine are synthesized by mitochondrial enzymes, phosphatidylcholine, phosphatidylinositol, phosphatidylserine, and sterols need to be imported from other organelles. The origin of most lipids imported into mitochondria is the endoplasmic reticulum, which requires interaction of these two subcellular compartments. Recently, protein complexes that are involved in membrane contact between endoplasmic reticulum and mitochondria were identified, but their role in lipid transport is still unclear. In the present review, we describe components involved in lipid translocation between the endoplasmic reticulum and mitochondria and discuss functional as well as regulatory aspects that are important for lipid homeostasis.Biological membranes are major structural components of all cell types. They protect the cell from external influences, organize the interior in distinct compartments and allow balanced flux of components. Besides their specific proteome, organelles exhibit unique lipid compositions, which influence their shape, physical properties, and function. Major lipid classes found in biological membranes are phospholipids, sterols, and sphingolipids.The major “lipid factory” within the cell is the endoplasmic reticulum (ER). It is able to synthesize the bulk of structural phospholipids, sterols, and storage lipids such as triacylglycerols and steryl esters (van Meer et al. 2008). Furthermore, initial steps of ceramide synthesis occur in the ER providing precursors for the formation of complex sphingolipids in other organelles (Futerman 2006). Besides the export of ceramides, the ER supplies a large portion of lipids to other organelles, which cannot produce their own lipids or have a limited capacity to do so. Organelle interaction and transport of lipids require specific carrier proteins, membrane contact sites, tethering complexes, and/or vesicle flux. These processes are highly important for the maintenance of cell structure and survival but are still a matter of dispute. Most prominent organelle interaction partners are the ER and mitochondria. A subfraction of the ER named mitochondria-associated membrane (MAM) (Vance 1990) was described to be involved in lipid translocation to mitochondria. MAM is part of the ER network, which was shown to be in contact or close proximity to the outer mitochondrial membrane (OMM). Contact sites between MAM and mitochondria were assumed to facilitate exchange of components between the two compartments. Interestingly, MAM harbor a number of lipid synthesizing enzymes (Gaigg et al. 1994). Recently, molecular components governing membrane contact between the two organelles were identified (Dolman et al. 2005; Csordás et al. 2006; de Brito and Scorrano 2008; Kornmann et al. 2009; Friedman et al. 2010; Lavieu et al. 2010), although the specific role of these components in lipid translocation is not yet clear.     

Lipid Simulations: A Perspective on Lipids in Action

In this article, we provide an overview of lipid simulations, describing how a computer can be used as a laboratory for lipid research. We briefly discuss the methodology of lipid simulations followed by a number of topical applications that show the benefit of computer modeling for complementing experiments. In particular, we show examples of cases in which simulations have made predictions of novel phenomena that have later been confirmed by experimental studies. Overall, the applications discussed in this article focus on the most recent state of the art and aim to provide a perspective of where the field of lipid simulations stands at the moment.Lipids are very diverse in their structures and functions (Sackmann 1995; Mouritsen 2005; van Meer 2005). They are a crucial component of numerous biological entities such as membranes, lipoprotein particles, and lipid droplets, and they are involved in numerous cellular functions related to, for example, signaling and energy storage. Importantly, as lipids also compartmentalize biological membranes by creating membrane domains with different physical properties, lipids also affect or even govern membrane proteins and their functionality (McIntosh and Simon 2006; Lingwood and Simons 2010).Although experiments are the cornerstone of lipid research, they are limited in resolution, permitting one to unravel biological phenomena only to a limited extent. Especially difficult to deal with are molecular scales with an objective to probe phenomena in the nanometer regime over timescales less than a microsecond. Molecular simulations, on the other hand, have no such limits with regard to resolution. Validated simulation models can be used to consider all sorts of phenomena, ranging from selectivity of ion channels to interactions of lipids with membrane proteins, and further to nonequilibrium lipid trafficking and domain as well as pore formation (Bjelkmar 2009; Bucher et al. 2010; Fan et al. 2010a,b).The first simulations of lipid systems were performed in the early 1980s (Kox et al. 1980; van der Ploeg and Berendsen 1982, 1983). Starting from those times when solvent-free membranes composed of 32 lipids were simulated for about 80 picoseconds (van der Ploeg and Berendsen 1982), the field of lipid simulations has matured to a stage in which the scales simulated in atomistic detail cover tens of nanometers (about 10⁵–10⁶ atoms) and several microseconds (Bjelkmar 2009; Dror 2009). This progress in atomistic simulations has been supported by the development of coarse-grained models and multiscale simulation techniques able to elucidate phenomena over scales much larger than the molecular ones (Ayton and Voth 2009; Murtola et al. 2009). The currently used particle-based coarse-grained models are appropriate for studies of systems of millions of particles over timescales of the order of 10–100 microseconds (Reynwar et al. 2007; Apajalahti 2010), and the situation continuously improves. Today, simulations can provide a great deal of insight into a variety of phenomena that are not tractable by experiments. Simulations are no longer used as tools for confirming what has been found in experiments; instead they have predictive power, guiding experiments to focus on novel phenomena. Current aims to bridge molecular simulations with computational systems biology foster the field further, coupling molecular and cellular phenomena to one another.In this article, we provide an overview of lipid simulations, describing how a computer can be used as a laboratory for lipid research. We briefly discuss the methodology of lipid simulations followed by a number of topical applications that show the benefit of simulations. The applications given here as examples of simulations’ role for lipid research focus on the most recent state of the art and aim to provide a perspective of where we stand at the moment. A brief discussion of the prospects of lipid simulations closes this article.     

Not Just Fat: The Structure and Function of the Lipid Droplet

Lipid droplets (LDs) are independent organelles that are composed of a lipid ester core and a surface phospholipid monolayer. Recent studies have revealed many new proteins, functions, and phenomena associated with LDs. In addition, a number of diseases related to LDs are beginning to be understood at the molecular level. It is now clear that LDs are not an inert store of excess lipids but are dynamically engaged in various cellular functions, some of which are not directly related to lipid metabolism. Compared to conventional membrane organelles, there are still many uncertainties concerning the molecular architecture of LDs and how each function is placed in a structural context. Recent findings and remaining questions are discussed.Lipid droplets (LDs) were recognized as a mere deposit of lipid esters for many years. Recently, LDs have been redefined as authentic organelles that are actively engaged in multiple functions, and these have been reviewed in many recent articles (Murphy 2001; Martin et al. 2006; Ducharme et al. 2008; Fujimoto et al. 2008; Goodman 2008; Olofsson et al. 2008; Thiele et al. 2008; Murphy et al. 2009; Walther et al. 2009; Beller et al. 2010). The name, lipid droplets, implies the opposite: a static and inert nature. Alternative names have been proposed, but lipid droplet is now a generally agreed nomenclature (Martin et al. 2006).LDs are intimately related to many aspects of lipid metabolism. The lipid storage function of LDs is most conspicuous in white adipocytes, which have a gigantic unilocular LD. The regulation of the process of lipid storage and utilization has been the focus of many studies because of the prevalence of obesity, type II diabetes, and metabolic syndrome in the modern world.Besides the canonical lipid-related function, various new functions have been ascribed to LDs more recently, including some that do not appear to be directly related to lipid metabolism. However, both the canonical and noncanonical functions of LDs, are rooted in the unique architecture of LDs. In contrast to other organelles that have aqueous content within a phospholipid bilayer membrane, the basic structure of LDs is thought to be a mass of lipid esters covered by a phospholipid monolayer (Murphy et al. 1999; Tauchi-Sato et al. 2002). In this article, we first review what is known about LD structure and then discuss various functions. We review this information by considering the extent to which the functions can be understood based on the current structural paradigm.     

Dynamic Transbilayer Lipid Asymmetry

Cells have thousands of different lipids. In the plasma membrane, and in membranes of the late secretory and endocytotic pathways, these lipids are not evenly distributed over the two leaflets of the lipid bilayer. The basis for this transmembrane lipid asymmetry lies in the fact that glycerolipids are primarily synthesized on the cytosolic and sphingolipids on the noncytosolic surface of cellular membranes, that cholesterol has a higher affinity for sphingolipids than for glycerolipids. In addition, P4-ATPases, “flippases,” actively translocate the aminophospholipids phosphatidylserine and phosphatidylethanolamine to the cytosolic surface. ABC transporters translocate lipids in the opposite direction but they generally act as exporters rather than “floppases.” The steady state asymmetry of the lipids can be disrupted within seconds by the activation of phospholipases and scramblases. The asymmetric lipid distribution has multiple implications for physiological events at the membrane surface. Moreover, the active translocation also contributes to the generation of curvature in the budding of transport vesicles.A lipid bilayer consisting of phosphatidylcholine (PC) with one saturated and one unsaturated acyl chain is stable, flexible, and semipermeable. It is the simplest model of a biomembrane. In such membranes, PC with a spin label on its choline headgroup diffused rapidly in the plane of the membrane with a diffusion coefficient of 1.8 µm²/sec (Devaux and McConnell 1972). In contrast, PC movement between leaflets, “flip-flop,” was slow with a half-time of >6 h at 30°C (Kornberg and McConnell 1971). Similar half-times for PC flip-flop were measured in erythrocyte membranes, a mammalian plasma membrane with a complex lipid composition (Rousselet et al. 1976; Renooij and Van Golde 1977; van Meer et al. 1980). Interestingly, the erythrocyte membrane maintains an asymmetric lipid distribution across the lipid bilayer with all of its phosphatidylserine (PS) and most of its phosphatidylethanolamine (PE) in the cytosolic leaflet (Bretscher 1972; Verkleij et al. 1973). A critical discussion of these early data and the techniques used can be found in (Op den Kamp 1979).It was then observed that the enrichment of aminophospholipids in the cytosolic leaflet is maintained by an ATP-consuming translocator that flips these lipids from the outer leaflet across the lipid bilayer (Seigneuret and Devaux 1984). The flippase was later identified as a P4-ATPase (Tang et al. 1996; Soupene and Kuypers 2006). Around the same time it was found that an ABC transporter, ABCB4, was involved in transporting PC into the bile (Smit et al. 1993), and studies on the closely related ABCB1 proved that these transporters can translocate lipids across the plasma membrane onto acceptors in the extracellular space (van Helvoort et al. 1996). Finally, evidence was provided for passive, bidirectional movement of lipids across the ER membrane and under some conditions across the plasma membrane, in which cases the responsible proteins have not yet been unequivocally identified (Sanyal and Menon 2009; Bevers and Williamson 2010). Thus, we now have a general picture of how lipid asymmetry is generated, maintained, and disrupted. However, there are still important gaps in our knowledge. For example, the transbilayer orientation of the sterols that make up one-third of the lipids in eukaryotic plasma membranes has still not been resolved satisfactorily. Moreover, we do not understand mechanistically how translocators and exporters work and how their activity is regulated.     

Unconventional Functions for Clathrin,ESCRTs, and Other Endocytic Regulators in the Cytoskeleton,Cell Cycle,Nucleus, and Beyond: Links to Human Disease

The roles of clathrin, its regulators, and the ESCRT (endosomal sorting complex required for transport) proteins are well defined in endocytosis. These proteins can also participate in intracellular pathways that are independent of endocytosis and even independent of the membrane trafficking function of these proteins. These nonendocytic functions involve unconventional biochemical interactions for some endocytic regulators, but can also exploit known interactions for nonendocytic functions. The molecular basis for the involvement of endocytic regulators in unconventional functions that influence the cytoskeleton, cell cycle, signaling, and gene regulation are described here. Through these additional functions, endocytic regulators participate in pathways that affect infection, glucose metabolism, development, and cellular transformation, expanding their significance in human health and disease.The discovery and characterization of clathrin (Pearse 1975) initiated molecular definition of the many endocytosis regulators described in this collection, which mediate the clathrin-dependent and -independent pathways for membrane internalization (see Kirchhausen et al. 2014; Mayor et al. 2014; Merrifield and Kaksonen 2014). In accompanying reviews, we have seen how these endocytic pathways influence nutrition and metabolism (see Antonescu et al. 2014), signal transduction (see Bökel and Brand 2014; Di Fiore and von Zastrow 2014), neuronal function (see Morgan et al. 2013; Cosker and Segal 2014), infection and immunity (see ten Broeke et al. 2013; Cossart and Helenius 2014), tissue polarity and development (see Eaton and Martin-Belmonte 2014; Gonzalez-Gaitan and Jülicher 2014), and migration and metastasis (see Mellman and Yarden 2013). Recently, it has been established that some endocytic regulators have molecular properties that expand their functions beyond endocytosis. These include molecular interactions that affect the microtubule and actin cytoskeletons, nuclear translocation that influences gene regulation, and the formation of membrane-associated scaffolds that serve as signaling and sorting platforms. Through these diverse nonendocytic functions, endocytosis regulators play additional roles in cell division, pathogen infection, cell adhesion, and oncogenesis. In this article, we review the nonconventional behavior of endocytic regulators, first discussing the molecular properties that enable their moonlighting functions and then discussing the cellular processes and disease states that are influenced by these functions.     

Retrograde Traffic from the Golgi to the Endoplasmic Reticulum

Proteins to be secreted are transported from the endoplasmic reticulum (ER) to the Golgi apparatus. The transport of these proteins requires the localization and activity of proteins that create ER exit sites, coat proteins to collect cargo and to reshape the membrane into a transport container, and address labels—SNARE proteins—to target the vesicles specifically to the Golgi apparatus. In addition some proteins may need export chaperones or export receptors to enable their exit into transport vesicles. ER export factors, SNAREs, and misfolded Golgi-resident proteins must all be retrieved from the Golgi to the ER again. This retrieval is also part of the organellar homeostasis pathway essential to maintaining the identity of the ER and of the Golgi apparatus. In this review, I will discuss the different processes in retrograde transport from the Golgi to the ER and highlight the mechanistic insights we have obtained in the last couple of years.Proteins that are exposed at the plasma membrane or populate a membrane-bounded organelle are synthesized into the endoplasmic reticulum (ER). In the ER, the folding of these proteins takes place and posttranslational modifications such as N-glycosylation and disulfide bridge formation occur. Upon adopting a suitable, often correct, conformation, proteins destined to locations beyond the ER are concentrated at so-called ER exit sites (ERES) and incorporated into nascent COPII-coated vesicles. These COPII vesicles eventually bud off the ER membrane and are transported to the Golgi (in yeast, Drosophila, and C. elegans) or the ER-Golgi intermediate compartment (in mammalian cells) (Schweizer et al. 1990; Kondylis and Rabouille 2003; Spang 2009; Witte et al. 2011).It is assumed that the vesicle coat is at least partially destabilized through the hydrolysis of GTP by the small GTPase Sar1 (Oka and Nakano 1994; Springer et al. 1999). However, some of the destabilized coat components have to stay on the vesicle until it has reached the Golgi apparatus because coat components participate in the recognition and the tethering process (Barlowe 1997; Cai et al. 2007; Lord et al. 2011; Zong et al. 2012). Subsequently, SNARE proteins on the vesicles (v-SNAREs) zipper up with cognate SNAREs on the Golgi (target SNAREs, t-SNAREs) to drive membrane fusion (Hay et al. 1998; Cao and Barlowe 2000; Parlati et al. 2002). The content of the ER-derived COPII vesicles is thereby released into the lumen of the cis-cisterna of the Golgi apparatus. Most proteins will continue their journey through the Golgi apparatus and encounter further modifications such as extension of the glycosylation tree or lipidation. However, some proteins, especially those involved in the fusion process, i.e., the v-SNAREs or proteins that act as export factors of the ER, such as Vma21, which is essential for export of the correctly folded and assembled V0 sector of the V-ATPase, need to be recycled back to the ER for another round of transport (Ballensiefen et al. 1998; Malkus et al. 2004). Moreover, cis-Golgi proteins are returned to the ER for quality/functional control (Todorow et al. 2000; Sato et al. 2004; Valkova et al. 2011). Finally, some ER-resident proteins, such as the ER Hsp70 chaperone BiP/Kar2, can escape the ER, but are captured at the cis-Golgi by the H/KDEL receptor Erd2 and returned to the ER (Lewis et al. 1990; Semenza et al. 1990; Aoe et al. 1997).Unfortunately, the retrograde transport route is also hijacked by toxins. For example, endocytosed cholera toxin subunit A contains a KDEL sequence and can thereby exploit the system to access the ER (Majoul et al. 1996, 1998). From there, it is retro-translocated into the cytoplasm where it can exert its detrimental function.     

Protein Translocation across the Rough Endoplasmic Reticulum

The rough endoplasmic reticulum is a major site of protein biosynthesis in all eukaryotic cells, serving as the entry point for the secretory pathway and as the initial integration site for the majority of cellular integral membrane proteins. The core components of the protein translocation machinery have been identified, and high-resolution structures of the targeting components and the transport channel have been obtained. Research in this area is now focused on obtaining a better understanding of the molecular mechanism of protein translocation and membrane protein integration.Protein translocation across the rough endoplasmic reticulum (RER) is an ancient and evolutionarily conserved process that is analogous to protein export across the cytoplasmic membranes of eubacterial and archaebacterial cells both with respect to the mechanism and core components. The RER membrane of eukaryotic cells is contiguous with the nuclear envelope and is morphologically composed of interconnected cisternae and tubules. Electron microscope images of mammalian cells and tissues revealed that the cisternal regions of the cytoplasmic surface of the endoplasmic reticulum are densely studded by membrane-bound ribosomes (Palade 1955a,b), giving rise to the term “rough ER.” The RER-bound ribosomes in en face images are often arranged in spirals or hairpins (Palade 1955a; Christensen and Bourne 1999), indicative of polyribosomes that are actively engaged in protein translation.Consistent with this high density of membrane-bound ribosomes, the RER is a major site of protein biosynthesis in eukaryotic cells. The nuclear envelope, the Golgi, lysosome, peroxisome, plasma membrane, and endosomes are biosynthetically derived from the rough ER. The three major groups of proteins that are synthesized by RER-bound ribosomes include secretory proteins, integral membrane proteins destined for ER-derived membranes, and the lumenal-resident proteins of the ER, Golgi, nuclear envelope, and lysosome. For those membranes that are not physically linked to the ER (e.g., the lysosome), integral membrane and lumenal proteins are delivered to their destination by vesicular transport pathways. Bioinformatics analysis of fully sequenced eukaryotic genomes indicates that roughly 30% of open reading frames encode integral membrane proteins (Wallin and von Heijne 1998); hence, a major role of the RER is the biosynthesis of membrane proteins. An important class of membrane proteins that are integrated into the RER has single carboxy-terminal TM spans and are known as tail-anchored (TA) membrane proteins. The posttranslational integration pathway for TA proteins has been a subject of several recent reviews (Borgese and Fasana 2011; Shao and Hegde 2011), thus we will not address the TA pathway in this article.     

Effects of Membrane Trafficking on Signaling by Receptor Tyrosine Kinases

The intracellular trafficking machinery contributes to the spatial and temporal control of signaling by receptor tyrosine kinases (RTKs). The primary role in this process is played by endocytic trafficking, which regulates the localization of RTKs and their downstream effectors, as well as the duration and the extent of their activity. The key regulatory points along the endocytic pathway are internalization of RTKs from the plasma membrane, their sorting to degradation or recycling, and their residence in various endosomal compartments. Here I will review factors and mechanisms that modulate RTK signaling by (1) affecting receptor internalization, (2) regulating the balance between degradation and recycling of RTK, and (3) compartmentalization of signals in endosomes and other organelles. Cumulatively, these mechanisms illustrate a multilayered control of RTK signaling exerted by the trafficking machinery.At the cellular level, receptor tyrosine kinases (RTKs) need to be properly localized to function as signal-receiving and signal-transmitting devices (Lemmon and Schlessinger 2010). To receive signals (i.e., to bind extracellular ligands), RTKs have to be exposed at the surface of the plasma membrane. To transmit signals after ligand binding by RTKs, appropriate signaling components have to be available within intracellular compartments: in the cytoplasm, in association with membrane-bound organelles and in the cell nucleus. Importantly, the intracellular distribution of RTKs and their associated partners is not static but undergoes dynamic changes in different phases of signaling, as reflected for example by endocytic internalization of activated RTKs (Scita and Di Fiore 2010). Therefore, to function properly, the whole RTK signaling machinery within the cell has to be organized and tightly controlled both in space and in time. This organization and control are ensured by intracellular trafficking machineries, mainly by membrane transport systems such as endocytosis and secretion but also by other distribution systems (e.g., responsible for nucleocytoplasmic shuttling of proteins).Recent years have brought increasing evidence that intracellular membrane trafficking, in particular endocytic internalization, degradation, and recycling, can profoundly affect the signaling properties of RTKs (Mukherjee et al. 2006; Abella and Park 2009; Lemmon and Schlessinger 2010; Scita and Di Fiore 2010; Grecco et al. 2011; Sigismund et al. 2012). The changes in the amounts of RTKs at the cell surface can alter the cellular responses when ligands are abundant (Grecco et al. 2011). In turn, the presence of a given RTK at the plasma membrane is determined by the rates of three trafficking processes: delivery of newly synthesized molecules by the secretory pathway, their internalization (occurring for both ligand-bound and ligand-free molecules), and endocytic recycling. Although the molecular details concerning the regulation of RTK delivery to the plasma membrane are not well known, numerous studies document various mechanisms by which internalization and recycling of RTKs can be modulated, thus affecting the signaling outputs (Le Roy and Wrana 2005). In addition to the regulation of RTKs at the cell surface, trafficking processes control the intracellular fate of endocytosed RTKs. Following internalization, RTKs can be either targeted for lysosomal degradation, or recycled back to the plasma membrane (Mukherjee et al. 2006; Abella and Park 2009; Scita and Di Fiore 2010). The first route results in the termination of signaling, whereas the second allows for sustained signaling if the ligand is available. Usually degradation and recycling of a given RTK can occur simultaneously but the balance between them is crucial to determine the net signaling output. Again, the molecular mechanisms that can shift the fate of internalized RTKs between degradation and recycling, thus changing RTK signaling, have begun to emerge in recent years (Polo and Di Fiore 2006; von Zastrow and Sorkin 2007; Sorkin and von Zastrow 2009; Sigismund et al. 2012). Finally, in contrast to an early view that only RTKs present at the plasma membrane are signaling competent, it is now accepted that in many cases activated RTKs can emit signals also after internalization into intracellular compartments (Miaczynska et al. 2004b; Miaczynska and Bar-Sagi 2010; Platta and Stenmark 2011). In some cell types (e.g., in neurons), such “signaling endosomes” are crucial for signal propagation within the cell and for the final cellular response. Moreover, endosomes can serve as platforms for amplification and compartmentalization of signals emitted by RTKs (Sadowski et al. 2009; Platta and Stenmark 2011).In this article, I will review factors and mechanisms that modulate RTK signaling by (1) affecting receptor internalization, (2) regulating the balance between degradation and recycling of RTK, and (3) compartmentalization of signals in endosomes and other organelles. As the membrane trafficking system of a cell is highly interconnected and can be considered a global dynamic continuum, it is important to note that often one primary alteration at a given stage of RTK trafficking may affect other transport steps or compartments, thus causing generalized changes in the intracellular routing and signaling of RTKs.     

Neuronal Signaling through Endocytosis

The distinctive morphology of neurons, with complex dendritic arbors and extensive axons, presents spatial challenges for intracellular signal transduction. The endosomal system provides mechanisms that enable signaling molecules initiated by extracellular cues to be trafficked throughout the expanse of the neuron, allowing intracellular signals to be sustained over long distances. Therefore endosomes are critical for many aspects of neuronal signaling that regulate cell survival, axonal growth and guidance, dendritic branching, and cell migration. An intriguing characteristic of neuronal signal transduction is that endosomal trafficking enables physiological responses that vary based on the subcellular location of signal initiation. In this review, we will discuss the specialized mechanisms and the functional significance of endosomal signaling in neurons, both during normal development and in disease.Endocytosis is a basic cellular process that has been conserved and adapted from single cell eukaryotes through humans (reviewed in Mellman 1996; Mukherjee et al. 1997). The fundamentals of endosomal recycling and degradation are the same in neurons as in other cell types (reviewed in Yap and Winckler 2012). However, the endocytic machinery is particularly important in neurons, as specialized vesicles are engaged in releasing neurotransmitters and in subsequent membrane retrieval (reviewed in Saheki and De Camilli 2012; von Zastrow and Williams 2012). Furthermore, endocytosis of neuronal growth factor receptors regulates where and when signaling cascades are initiated (reviewed in Hupalowska and Miaczynska 2012). Here we will discuss how the endocytic process in neurons is adapted so that vesicles can travel through the extensive span of neuronal axons and dendrites, and convey spatial information.     

Signaling at the Golgi

The protein processing and trafficking function of the Golgi is intimately linked to multiple intracellular signaling pathways. Assembly of Golgi trafficking structures and lipid sorting at the Golgi complex is controlled and coordinated by specific phosphoinositide kinases and phosphatases. The intra-Golgi transport machinery is also regulated by kinases belonging to several functionally distinct families, for example, MAP kinase signaling is required for mitotic disassembly of the Golgi. However, the Golgi plays an additional, prominent role in compartmentalizing other signaling cascades that originate at the plasma membrane or at other organelles. This article summarizes recent advances in our understanding of the signaling network that converges at the Golgi.The Golgi apparatus is a dynamic structure that constantly exchanges proteins and lipids with other organelles. It is critical for organellar homeostasis that the different trafficking routes at the Golgi are precisely regulated. For example, the sorting and transport functions of the Golgi must be correctly coordinated with the overall activity of the secretory pathway. In addition, changes in Golgi structure and morphology are tightly controlled, which is particularly critical during mitosis, when the Golgi complex becomes disassembled for proper distribution between the dividing cells. It is therefore not surprising that diverse sets of signaling factors localize at the Golgi and control its function and shape.Phosphoinositide lipids have emerged as particularly important regulators of Golgi function. Reversible phosphorylation of the inositol headgroup of phosphatidylinositol creates seven distinct phosphoinositide species (Di Paolo and De Camilli 2006). These molecules serve as signal transducers at virtually every cellular membrane but have a particularly important role in controlling membrane traffic (Di Paolo and De Camilli 2006). A critical property of phosphoinositides is their tightly regulated spatial distribution. Recent studies have uncovered concentrated pools of these lipids at individual membranes including the Golgi (Roy and Levine 2004; De Matteis et al. 2005; Varnai and Balla 2008). Phosphoinositides often act in cooperation with small Ras-type GTPases and the interplay between phosphoinositides and GTPases from the ADP-ribosylation factor (Arf) and Ras-related in brain (Rab) families is essential for Golgi function (Behnia and Munro 2005; Mayinger 2009). How the lipid kinases and phosphatases that regulate Golgi phosphoinositides interact with other signaling pathway remains a challenging area of research.Whereas phosphoinositide signaling pathways are mainly controlled via extracellular signals that transmit metabolic status and growth conditions, Golgi function can also be regulated by signals that originate at other secretory organelles. Enhanced biosynthesis and processing of secretory proteins at the ER induces the activation of a signaling network that modulates intra-Golgi traffic and overall capacity of secretion (Sallese et al. 2009).Finally, there is mounting evidence that the Golgi serves as an important signaling platform for numerous signaling cascades that originate at the plasma membrane. The discovery that components of the Ras and the protein kinase A (PKA) pathways reside at the Golgi indicates that this organelle plays an important role in compartmentalizing signal transduction pathways (Quatela and Philips 2006; Sallese et al. 2009). This article will review our current understanding of signaling at the Golgi and also highlight the relevance of these processes for human disease.     

Origin and Evolution of the Self-Organizing Cytoskeleton in the Network of Eukaryotic Organelles

The eukaryotic cytoskeleton evolved from prokaryotic cytomotive filaments. Prokaryotic filament systems show bewildering structural and dynamic complexity and, in many aspects, prefigure the self-organizing properties of the eukaryotic cytoskeleton. Here, the dynamic properties of the prokaryotic and eukaryotic cytoskeleton are compared, and how these relate to function and evolution of organellar networks is discussed. The evolution of new aspects of filament dynamics in eukaryotes, including severing and branching, and the advent of molecular motors converted the eukaryotic cytoskeleton into a self-organizing “active gel,” the dynamics of which can only be described with computational models. Advances in modeling and comparative genomics hold promise of a better understanding of the evolution of the self-organizing cytoskeleton in early eukaryotes, and its role in the evolution of novel eukaryotic functions, such as amoeboid motility, mitosis, and ciliary swimming.The eukaryotic cytoskeleton organizes space on the cellular scale and this organization influences almost every process in the cell. Organization depends on the mechanochemical properties of the cytoskeleton that dynamically maintain cell shape, position organelles, and macromolecules by trafficking, and drive locomotion via actin-rich cellular protrusions, ciliary beating, or ciliary gliding. The eukaryotic cytoskeleton is best described as an “active gel,” a cross-linked network of polymers (gel) in which many of the links are active motors that can move the polymers relative to each other (Karsenti et al. 2006). Because prokaryotes have only cytoskeletal polymers but lack motor proteins, this “active gel” property clearly sets the eukaryotic cytoskeleton apart from prokaryotic filament systems.Prokaryotes contain elaborate systems of several cytomotive filaments (Löwe and Amos 2009) that share many structural and dynamic features with eukaryotic actin filaments and microtubules (Löwe and Amos 1998; van den Ent et al. 2001). Prokaryotic cytoskeletal filaments may trace back to the first cells and may have originated as higher-order assemblies of enzymes (Noree et al. 2010; Barry and Gitai 2011). These cytomotive filaments are required for the segregation of low copy number plasmids, cell rigidity and cell-wall synthesis, cell division, and occasionally the organization of membranous organelles (Komeili et al. 2006; Thanbichler and Shapiro 2008; Löwe and Amos 2009). These functions are performed by dynamic filament-forming systems that harness the energy from nucleotide hydrolysis to generate forces either via bending or polymerization (Löwe and Amos 2009; Pilhofer and Jensen 2013). Although the identification of actin and tubulin homologs in prokaryotes is a major breakthrough, we are far from understanding the origin of the structural and dynamic complexity of the eukaryotic cytoskeleton.Advances in genome sequencing and comparative genomics now allow a detailed reconstruction of the cytoskeletal components present in the last common ancestor of eukaryotes. These studies all point to an ancestrally complex cytoskeleton, with several families of motors (Wickstead and Gull 2007; Wickstead et al. 2010) and filament-associated proteins and other regulators in place (Jékely 2003; Richards and Cavalier-Smith 2005; Rivero and Cvrcková 2007; Chalkia et al. 2008; Eme et al. 2009; Fritz-Laylin et al. 2010; Eckert et al. 2011; Hammesfahr and Kollmar 2012). Genomic reconstructions and comparative cell biology of single-celled eukaryotes (Raikov 1994; Cavalier-Smith 2013) allow us to infer the cellular features of the ancestral eukaryote. These analyses indicate that amoeboid motility (Fritz-Laylin et al. 2010; although, see Cavalier-Smith 2013), cilia (Cavalier-Smith 2002; Mitchell 2004; Jékely and Arendt 2006; Satir et al. 2008), centrioles (Carvalho-Santos et al. 2010), phagocytosis (Cavalier-Smith 2002; Jékely 2007; Yutin et al. 2009), a midbody during cell division (Eme et al. 2009), mitosis (Raikov 1994), and meiosis (Ramesh et al. 2005) were all ancestral eukaryotic cellular features. The availability of functional information from organisms other than animals and yeasts (e.g., Chlamydomonas, Tetrahymena, Trypanosoma) also allow more reliable inferences about the ancestral functions of cytoskeletal components (i.e., not only their ancestral presence or absence) and their regulation (Demonchy et al. 2009; Lechtreck et al. 2009; Suryavanshi et al. 2010).The ancestral complexity of the cytoskeleton in eukaryotes leaves a huge gap between prokaryotes and the earliest eukaryote we can reconstruct (provided that our rooting of the tree is correct) (Cavalier-Smith 2013). Nevertheless, we can attempt to infer the series of events that happened along the stem lineage, leading to the last common ancestor of eukaryotes. Meaningful answers will require the use of a combination of gene family history reconstructions (Wickstead and Gull 2007; Wickstead et al. 2010), transition analyses (Cavalier-Smith 2002), and computer simulations relevant to cell evolution (Jékely 2008).     

Metabolic Stress in Autophagy and Cell Death Pathways

Growth factors and oncogenic kinases play important roles in stimulating cell growth during development and transformation. These processes have significant energetic and synthetic requirements and it is apparent that a central function of growth signals is to promote glucose metabolism to support these demands. Because metabolic pathways represent a fundamental aspect of cell proliferation and survival, there is considerable interest in targeting metabolism as a means to eliminate cancer. A challenge, however, is that molecular links between metabolic stress and cell death are poorly understood. Here we review current literature on how cells cope with metabolic stress and how autophagy, apoptosis, and necrosis are tightly linked to cell metabolism. Ultimately, understanding of the interplay between nutrients, autophagy, and cell death will be a key component in development of new treatment strategies to exploit the altered metabolism of cancer cells.Although single-celled organisms grow and proliferate based on nutrient availability, metazoan cells rely on growth factor input to promote nutrient uptake, regulate growth and proliferation, and survive (Raff 1992; Rathmell et al. 2000). Access and competition for these signals are critical in developmental patterning and to maintain homeostasis of mature tissues. Cells that do not receive proper growth factor signals typically atrophy, lose the ability to uptake and use extracellular nutrients, and instead induce the self-digestive process of autophagy as an intracellular energy source before ultimately undergoing programmed cell death. Cancer cells, in contrast, often become independent of extracellular growth signals by gaining mutations or expressing oncogenic kinases to drive intrinsic growth signals that mimic growth factor input, which can be the source of oncogene addiction. Growth factor input or oncogenic signals often drive highly elevated glucose uptake and metabolism (Rathmell et al. 2000; DeBerardinis et al. 2008; Michalek and Rathmell 2010). First described in cancer by Warburg in the 1920s, this highly glycolytic metabolic program is termed aerobic glycolysis and is a general feature of many nontransformed proliferative cells (Warburg 1956; DeBerardinis et al. 2008).Nutrient uptake and aerobic glycolysis induced by growth signals play key roles in cell survival (Vander Heiden et al. 2001). Manipulating cell metabolism as a means to promote the death of inappropriately dividing cells, therefore, is a promising new avenue to treat disease. Targeting the altered metabolism of cancer cells in particular is of great interest. It is still unclear at the molecular level, however, how inhibiting or modulating cell metabolism leads to apoptosis, and how these pathways may best be exploited (Dang et al. 2009; Wise and Thompson 2010).Growth factor or oncogenic kinases promote multiple metabolic pathways that are essential to prevent metabolic stress and may be targets in efforts to link metabolism and cell death (Vander Heiden et al. 2001). Decreased glucose metabolism on loss of growth signals leads to decreased ATP generation as well as loss in generation of many biosynthetic precursor molecules, including nucleic acids, fatty acids, and acetyl-CoA for acetylation (Zhao et al. 2007; Wellen et al. 2009; Coloff et al. 2011). Glucose is also important as a precursor for the hexosamine pathway, to allow proper glycosylation and protein folding in the endoplasmic reticulum (Dennis et al. 2009; Kaufman et al. 2010). If glucose metabolism remains insufficient or disrupted, the cells can switch to rely on mitochondrial oxidation of fatty acids and amino acids, which are energy rich but do not readily support cell growth and can lead to potentially dangerous levels of reactive oxygen species (Wellen and Thompson 2010). Amino acid deficiency can directly inhibit components of the signaling pathways downstream from growth factors and activate autophagy (Lynch 2001; Beugnet et al. 2003; Byfield et al. 2005; Nobukuni et al. 2005). Finally, hypoxia induces a specific pathway to increase nutrient uptake and metabolism via the hypoxia-inducible factor (HIF1/2α) that promotes adaptation to anaerobic conditions, but may lead to apoptosis if hypoxia is severe (Saikumar et al. 1998; Suzuki et al. 2001; Fulda and Debatin 2007).Typically a combination of metabolic stresses rather than loss of a single nutrient input occur at a given time (Degenhardt et al. 2006) and autophagy is activated to mitigate damage and provide nutrients for short-term survival (Bernales et al. 2006; Tracy et al. 2007; Altman et al. 2011; Guo et al. 2011). Autophagy is a cellular process of bulk cytoplasmic and organelle degradation common to nearly all eukaryotes. Unique double-membraned vesicles known as autophagosomes engulf cellular material and fuse with lysosomes to promote degradation of the contents (Kelekar 2005). Described in greater detail below, autophagy can reduce sources of stress, such as protein aggregates and damaged or dysfunctional intracellular organelles, and provide nutrients during times of transient and acute nutrient withdrawal.Despite the protective effects of autophagy, cells deprived of growth signals, nutrients, or oxygen for prolonged times will eventually succumb to cell death. Apoptosis is the initial death response on metabolic stress and is regulated by Bcl-2 family proteins. In healthy cells, antiapoptotic Bcl-2 family proteins, such as Bcl-2, Bcl-xl, and Mcl-1, bind and inhibit the multidomain proapoptotic proteins Bax and Bak (van Delft and Huang 2006; Walensky 2006; Chipuk et al. 2010). In metabolic stress, proapoptotic “BH3-only” proteins of the Bcl-2 family are induced or activated and bind to and inhibit the antiapoptotic Bcl-2 family proteins to allow activation of the proapoptotic Bax and Bak (Galonek and Hardwick 2006). The BH3-only proteins Bim, Bid, and Puma can also directly bind and activate Bax and Bak (Letai et al. 2002; Ren et al. 2010). Active Bax and Bak disrupt the outer mitochondrial membrane (termed mitochondrial outer-membrane permeabilization, or MOMP) and release several proapoptotic factors including cytochrome-C that activate the apoptosome that in turn activates effector caspases to cleave a variety of cellular proteins and drive apoptosis (Schafer and Kornbluth 2006). In cases in which these apoptotic pathways are suppressed, metabolic stress can instead lead to necrotic cell death (Jin et al. 2007).     

Specificity of Intramembrane Protein–Lipid Interactions

Our concept of biological membranes has markedly changed, from the fluid mosaic model to the current model that lipids and proteins have the ability to separate into microdomains, differing in their protein and lipid compositions. Since the breakthrough in crystallizing membrane proteins, the most powerful method to define lipid-binding sites on proteins has been X-ray and electron crystallography. More recently, chemical biology approaches have been developed to analyze protein–lipid interactions. Such methods have the advantage of providing highly specific cellular probes. With the advent of novel tools to study functions of individual lipid species in membranes together with structural analysis and simulations at the atomistic resolution, a growing number of specific protein–lipid complexes are defined and their functions explored. In the present article, we discuss the various modes of intramembrane protein–lipid interactions in cellular membranes, including examples for both annular and nonannular bound lipids. Furthermore, we will discuss possible functional roles of such specific protein–lipid interactions as well as roles of lipids as chaperones in protein folding and transport.Our concept of biological membranes has markedly changed in the last two decades, from the fluid mosaic model (Singer and Nicolson 1972), in which the membrane was thought to be formed by a homogenous lipid fluid phase with proteins embedded, to the current model that lipids and proteins are not homogenously distributed, but have the ability to separate into microdomains, differing in their protein and lipid compositions. A well established example of domains are lipid rafts (see Box 1 for definitions). Raft domains are described as dynamic domain structures enriched in cholesterol, sphingolipids, and membrane proteins (Brown and London 1998; Simons and Ikonen 1997) that have an important role in different cellular processes (Lingwood and Simons 2010). Formation of domains within cellular membranes has been extensively investigated over the past years leading to various models that differ in the primary forces involved in the formation and the recruitment of surrounding membrane components into such domains.

BOX 1.

Definitions

Annular Lipids/Lipid Shell

An annular lipid shell is formed when selected lipid classes or molecular species bind preferentially to the hydrophobic and/or hydrophilic surfaces of a membrane protein. Per definition these lipids show markedly reduced residence times at the protein–lipid interface as compared to bulk lipids.

Bulk Lipids

Lipids within the membrane that diffuse rapidly in the bilayer plane and show a low residence time at the protein–lipid interface following random collisions. Typical diffusion coefficients for bulk lipids in a liquid disordered phase are in the range of D_L = 7×10⁻¹² m²/sec (DOPC) (Filippov et al. 2003).

Hydrophobic Mismatch

A term to describe any deviation from the compatibility of the hydrophobic surface of membrane proteins (their TMDs) to the vertically and laterally encountered hydrophobic surfaces of the lipid bilayer in biological membranes. In the case of a hydrophobic mismatch, the resulting energy penalty may cause the recruitment of a suitable local lipid environment, the deformation of the membrane and/or in conformational changes of the protein to achieve a status of hydrophobic match (for advanced reading, see Killian 1998).

Lateral Pressure Field/Profile of Membranes

Biological membranes can be considered as the “solvent” for membrane proteins that are embedded in them. The lateral pressure profile (Ω(z)) describes the force or pressure that is exerted by the membrane on the matter residing inside it. This pressure is modulated by different extents of lipid–lipid interactions and asymmetries across and within the bilayer, which in turn results in varying lateral pressures that may locally correspond to several hundreds of atmospheres.

Lipid Rafts

Sterol and sphingolipid-dependent microdomains that form a network of lipid–lipid, protein–protein, and protein–lipid interactions; involved in the compartmentalization of processes such as signaling within biological membranes.

Liquid-Disordered Phase (I_d)

A predominantly fluid phase of lipids, characterized by a high degree of mobility (cis-gauche flexibility of acyl chains; lateral diffusion) and a high content of short and/or unsaturated fatty acyl chains.

Liquid-Ordered Phase (I_o)

A liquid crystalline phase (that displays physical properties of both liquids and of solid crystals), characterized by a high degree of acyl chain order (“packing”), a reduced lateral mobility of lipid and protein molecules, and a reduction in the elasticity of the membrane as a result of specific interactions between sterols and phospholipids containing long, saturated acyl chains and/or glycosphingolipids.

Microdomains

Membrane compartments of distinct lipid and protein composition that may modulate the enzymatic functions of membrane proteins.

Molecular Lipid Species

Individual members of a lipid class that differ in their fatty acid composition.

Nonannular Lipids

Lipids that specifically interact with membrane proteins are neither bulk lipids, nor do they belong to the shell/annulus of lipids that surround the membrane protein. These nonannular lipids often reside within membrane protein complexes, in which they may fulfill diverse functions ranging from structural building blocks to allosteric effectors of enzymatic activity (see text). Nonannular lipids bind to distinct hydrophobic sites of membrane proteins or membrane protein complexes.According to one model, membrane domains can form by specific protein–protein interactions (Douglass and Vale 2005). This model is based on single-molecule microscopy experiments. In these studies, single fluorophores were chemically attached to specific proteins, and the dynamics of individual proteins was tracked by monitoring the fluorescent probe. In this kind of set up, a dynamic behavior of lipids is not assessed. Here, proteins involved in signaling processes are trapped within interconnected microdomains created by specific protein–protein interactions, probably involving additional scaffolding proteins. The proteins of such domains can exchange with the surrounding membrane area at individual kinetics, some components are immobile over minutes, and others can diffuse rapidly.Another model emphasizes the importance of lipid–lipid interactions, initiating the formation of subdomains of defined lipid compositions. Transmembrane proteins then can be attracted to such subdomains via various specific interactions with lipids. The resulting lipid–protein complexes then eventually coalesce to form larger lipid–protein assemblies (Anderson and Jacobson 2002).The idea of lipid-dependent domain formation is inherent to the biophysical properties and therefore to the complex lipid composition of cellular membranes that include up to a thousand lipids that vary in structure (van Meer et al. 2008). This wide range of lipid species has been proposed to facilitate the “solvation” of membrane proteins. Taken into account the sum of lipid species present in a cellular membrane, it is important to understand the different interactions and affinities within the bilayer between different lipids. Molecular dynamics simulations have been successfully employed to investigate lipid interactions between different lipid species and found specific interactions of various lipid classes and molecular species (Hofsass et al. 2003; Niemela et al. 2004, 2006, 2009; Pandit et al. 2004; Zaraiskaya and Jeffrey 2005; Bhide et al. 2007). These results are supported and expanded by recent data from our group that suggest a specific order of interactions of sphingomyelin species with cholesterol in membranes (A.M. Ernst, F. Wieland, and B. Brügger, unpubl.). At low cholesterol concentrations, some sphingomyelin species preferentially interact with cholesterol, whereas others prefer their kin. At higher cholesterol concentrations, all sphingomyelin species investigated display an increased affinity for the sterol. These findings open the possibility of differentiated pathways of self-assembly of microdomains, dependent on molecular lipid species.In the present article the various modes of intramembrane protein–lipid interactions in cellular membranes (Fig. 1) will be discussed. This includes possible functional roles of such specific protein–lipid interactions.Open in a separate windowFigure 1.Intramembrane protein–lipid interactions within a cell membrane. (A) Bulk lipids; (B) annular lipids; (C) nonannular lipids/lipid ligands. For details see text.     

Architecture of the Mammalian Golgi

Since its first visualization in 1898, the Golgi has been a topic of intense morphological research. A typical mammalian Golgi consists of a pile of stapled cisternae, the Golgi stack, which is a key station for modification of newly synthesized proteins and lipids. Distinct stacks are interconnected by tubules to form the Golgi ribbon. At the entrance site of the Golgi, the cis-Golgi, vesicular tubular clusters (VTCs) form the intermediate between the endoplasmic reticulum and the Golgi stack. At the exit site of the Golgi, the trans-Golgi, the trans-Golgi network (TGN) is the major site of sorting proteins to distinct cellular locations. Golgi functioning can only be understood in light of its complex architecture, as was revealed by a range of distinct electron microscopy (EM) approaches. In this article, a general concept of mammalian Golgi architecture, including VTCs and the TGN, is described.In 1898 Camillo Golgi was the first to visualize, describe, and ultimately name the Golgi complex. Using a histochemical impregnation method causing the reduction and deposition of silver, he defined the Golgi in neuronal cells as a reticular apparatus stained by the “black reaction” (Golgi 1898). In the 1950s, the first ultrastructural images of the Golgi were revealed using the then newly developed electron microscope (EM) (Dalton 1954; Farquhar and Rinehart 1954; Sjostrand and Hanzon 1954; Dalton and Felix 1956), reviewed by Farquhar and Palade (1981). In 1961, the thiamine pyrophosphatase reaction developed by Novikoff and Goldfischer allowed cytochemical labeling of Golgi membranes, which revealed the ubiquitous cellular distribution of this organelle (Novikoff and Goldfischer 1961). In the many years of ultrastructural research that have followed, the visualization of the Golgi has gone hand-in-hand with the developing EM techniques.The intriguing structural complexity of the Golgi has made it one of the most photographed organelles in the cell. However, a full understanding of Golgi architecture is hard to deduce from the ultrathin (70–100 nm) sections used in standard transmission EM preparations. Rambourg and Clermont (1974) were the first to investigate the Golgi in three dimensions (3D), using stereoscopy (Rambourg 1974). In this approach a “thick” (150–200 nm), EM section is photographed at two distinct angles, after which the pairs of photographs are viewed with a stereoscope. Over the years, stereoscopy was applied to a variety of cells and has greatly contributed to our current understanding of Golgi architecture (Lindsey and Ellisman 1985; Rambourg and Clermont 1990; Clermont et al. 1994; Clermont et al. 1995). An alternative approach to study 3D structure is serial sectioning, by which a series of adjacent (serial) thin sections are collected. The Golgi can be followed throughout these sections and be constructed into a 3D model (Beams and Kessel 1968; Dylewski et al. 1984; Rambourg and Clermont 1990). In the nineties, 3D-EM was boosted by the introduction of high-voltage, dual axis 3D electron tomography (Ladinsky et al. 1999; Koster and Klumperman 2003; Marsh 2005; Marsh 2007; Noske et al. 2008), which allows the analysis of sections of up to 3–4 µm with a 4–6 nm resolution in the z-axis. The sections are photographed in a tilt series of different angles, which are reconstructed into a 3D tomogram that allows one to “look beyond” a given structure and reveals how it relates to other cellular compartments.Membranes with a similar appearance can differ in protein content and function. These differences are revealed by protein localization techniques. Therefore, in addition to the “classical” EM techniques providing ultrastructural details, EM methods that determine protein localization within the context of the cellular morphology have been crucial to further our understanding on the functional organization of the Golgi. For example, by enzyme-activity-based cytochemical staining the cis-to-trans-polarity in the distribution of Golgi glycosylation enzymes was discovered, reviewed by Farquhar and Palade (1981), which was key to understanding the functional organization of the Golgi stack in protein and lipid glycosylation. With the development of immunoEM methods, using antibodies, the need for enzyme activity for protein localization was overcome. This paved the way for the localization of a wide variety of proteins, such as the cytoplasmic coat complexes associated with the Golgi (Rabouille and Klumperman 2005).A logical next step in EM-based imaging of the Golgi would be to combine protein localization with 3D imaging, but this is technically challenging. A number of protocols enabling protein localization in 3D have recently been described (Trucco et al. 2004; Grabenbauer et al. 2005; Gaietta et al. 2006; Zeuschner et al. 2006; Meiblitzer-Ruppitsch et al. 2008), but these have only been applied in a limited manner to Golgi studies. Another approach that holds great potential for Golgi research is correlative microscopy (CLEM). Live cell imaging of fluorescent proteins has revolutionized cell biology by the real time visualization of dynamic events. However, live cell imaging does not reveal membrane complexity. By CLEM, live cells are first viewed by light microscopy and then prepared for EM (Mironov et al. 2008; van Rijnsoever et al. 2008). When coupled with the recent introduction of super resolution light microscopy techniques for real time imaging, the combination with EM for direct correlation with ultrastructural resolution has great potential (Hell 2009; Lippincott-Schwartz and Manley 2009).The 100th anniversary of the discovery of the Golgi, in 1998, triggered a wave of reviews on this organelle, including those focusing on Golgi architecture (Rambourg 1997; Farquhar and Palade 1998). More recent reviews that describe Golgi structure in great detail are provided by Marsh (2005) and Hua (2009). In this article, the most recent insights in mammalian Golgi architecture as revealed by distinct EM approaches are integrated into a general concept.     

Molecular Basis of the Core Structure of Tight Junctions

The morphological feature of tight junctions (TJs) fits well with their functions. The core of TJs is a fibril-like proteinaceous structure within the lipid bilayer, the so-called TJ strands. TJ strands in apposing plasma membranes associate with each other to eliminate the intercellular space. A network of paired TJ strands generates a continuous belt that circumscribes each cell to establish the diffusion barrier to the solutes in the paracellular pathway throughout the cellular sheet. Identification and characterization of TJ-associated proteins during the last two decades has unveiled the nature of TJ strands and how they are spatially organized. The interplay between integral membrane proteins, claudins, and cytoplasmic plaque proteins, ZO-1/ZO-2, is critical for TJ formation and function.Tight junctions (TJs) are fascinating structures in terms of their function and morphology. In 1963, using ultrathin-section electron microscopy, Farquhar and Palade described the fine structure of TJs together with adherens junctions (AJs) and desmosomes at the most luminal side of the lateral membrane (Farquhar and Palade 1963). In addition, they demonstrated insightfully that TJs function as permeability seals for mass tracers. Indeed, the structure of TJs observed in electron microscopy indicates that TJs could physically restrict the leak of solutes through the intercellular space. However, physiological studies at the same time revealed that solute transport occurred via the intercellular space in a variety of epithelial cells. A resolution of these different views of TJ function comprises the current concept that the TJ regulates the diffusion of solutes with size and charge selectivity and that it is functionally different in physiologically diverse epithelial cell types (Powell 1981; Anderson and Cereijido 2001). To understand the molecular mechanism controlling TJ structure and function, it is important to determine their molecular composition and organization.Although purification of TJs is difficult, Stevenson and Goodenough developed an isolation method for a TJ-enriched plasma membrane fraction from rodent liver. They discovered the first TJ-associated protein, ZO-1, in 1986 by generating monoclonal antibodies against this fraction (Stevenson et al. 1986). Since then, many molecular components of TJs have been identified using immunological approaches or searches for binding proteins with known molecules, which have enabled detailed molecular cell biological analyses of TJs. Among the TJ-associated proteins, the claudin family of membrane proteins identified in 1998 by the Tsukita group are key molecules in the architecture and barrier function of TJs (Furuse et al. 1998a). Functional analyses of claudins have allowed remarkable progress in the development of a comprehensive understanding of the molecular basis of the ultrastructure and physiological characteristics of TJs (Van Itallie and Anderson 2006; Furuse and Tsukita 2006; Angelow et al. 2008). In addition, the cytoplasmic plaque proteins associated with TJs are important in regulating TJ architecture (Guillemot et al. 2008).In this article, we present the molecular basis for the core structure of TJs based on recent progress in functional analyses of TJ-associated proteins. The current molecular basis of TJ physiology is covered in detail in Anderson and Van Itallie (2009).     

Molecular Bases of Cell–Cell Junctions Stability and Dynamics

Epithelial cell–cell junctions are formed by apical adherens junctions (AJs), which are composed of cadherin adhesion molecules interacting in a dynamic way with the cortical actin cytoskeleton. Regulation of cell–cell junction stability and dynamics is crucial to maintain tissue integrity and allow tissue remodeling throughout development. Actin filament turnover and organization are tightly controlled together with myosin-II activity to produce mechanical forces that drive the assembly, maintenance, and remodeling of AJs. In this review, we will discuss these three distinct stages in the lifespan of cell–cell junctions, using several developmental contexts, which illustrate how mechanical forces are generated and transmitted at junctions, and how they impact on the integrity and the remodeling of cell–cell junctions.Cell–cell junction formation and remodeling occur repeatedly throughout development. Epithelial cells are linked by apical adherens junctions (AJs) that rely on the cadherin-catenin-actin module. Cadherins, of which epithelial E-cadherin (E-cad) is the most studied, are Ca²⁺-dependent transmembrane adhesion proteins forming homophilic and heterophilic bonds in trans between adjacent cells. Cadherins and the actin cytoskeleton are mutually interdependent (Jaffe et al. 1990; Matsuzaki et al. 1990; Hirano et al. 1992; Oyama et al. 1994; Angres et al. 1996; Orsulic and Peifer 1996; Adams et al. 1998; Zhang et al. 2005; Pilot et al. 2006). This has long been attributed to direct physical interaction of E-cad with β-catenin (β-cat) and of α-catenin (α-cat) with actin filaments (for reviews, see Gumbiner 2005; Leckband and Prakasam 2006; Pokutta and Weis 2007). Recently, biochemical and protein dynamics analyses have shown that such a link may not exist and that instead, a constant shuttling of α-cat between cadherin/β-cat complexes and actin may be key to explain the dynamic aspect of cell–cell adhesion (Drees et al. 2005; Yamada et al. 2005). Regardless of the exact nature of this link, several studies show that AJs are indeed physically attached to actin and that cadherins transmit cortical forces exerted by junctional acto-myosin networks (Costa et al. 1998; Sako et al. 1998; Pettitt et al. 2003; Dawes-Hoang et al. 2005; Cavey et al. 2008; Martin et al. 2008; Rauzi et al. 2008). In addition, physical association depends in part on α-cat (Cavey et al. 2008) and additional intermediates have been proposed to represent alternative missing links (Abe and Takeichi 2008) (reviewed in Gates and Peifer 2005; Weis and Nelson 2006). Although further work is needed to address the molecular nature of cadherin/actin dynamic interactions, association with actin is crucial all throughout the lifespan of AJs. In this article, we will review our current understanding of the molecular mechanisms at work during three different developmental stages of AJs biology: assembly, stabilization, and remodeling, with special emphasis on the mechanical forces controlling AJs integrity and development.     

Lysosomal Lipid Storage Diseases

Lysosomal lipid storage diseases, or lipidoses, are inherited metabolic disorders in which typically lipids accumulate in cells and tissues. Complex lipids, such as glycosphingolipids, are constitutively degraded within the endolysosomal system by soluble hydrolytic enzymes with the help of lipid binding proteins in a sequential manner. Because of a functionally impaired hydrolase or auxiliary protein, their lipid substrates cannot be degraded, accumulate in the lysosome, and slowly spread to other intracellular membranes. In Niemann-Pick type C disease, cholesterol transport is impaired and unesterified cholesterol accumulates in the late endosome. In most lysosomal lipid storage diseases, the accumulation of one or few lipids leads to the coprecipitation of other hydrophobic substances in the endolysosomal system, such as lipids and proteins, causing a “traffic jam.” This can impair lysosomal function, such as delivery of nutrients through the endolysosomal system, leading to a state of cellular starvation. Therapeutic approaches are currently restricted to mild forms of diseases with significant residual catabolic activities and without brain involvement.Lysosomal lipid storage diseases are a group of inherited catabolic disorders in which typically large amounts of complex lipids accumulate in cells and tissues. Macromolecules such as complex lipids and oligosaccharides are constitutively degraded in the acidic compartments of the cell, the endosomes, and lysosomes, into their building blocks. The resulting catabolites are exported to the cytosol and reused in cellular metabolism. When lysosomal function is impaired because of a defect in a catabolic step, degradation cannot proceed normally and undegraded compounds accumulate. Lysosomal lipid storage diseases comprise mainly the sphingolipidoses, Niemann-Pick type C disease (NPC), and Wolman disease, including the less severe form of this disease, called cholesteryl ester storage. NPC is a complex lipid storage disease mainly characterized by the accumulation of unesterified cholesterol in the late endosomal/lysosomal compartment (Bi and Liao 2010). The sphingolipidoses are caused by defects in genes encoding proteins involved in the lysosomal degradation of sphingolipids (Kolter and Sandhoff 2006). First reports on these diseases were given more than a century ago. Already in 1881, Warren Tay described the clinical symptoms of a disease, which is today called Tay-Sachs disease (Tay 1881). After Christian de Duve discovered the lysosome in 1955 (de Duve 2005), Henri-Géry Hers established the first correlation between an enzyme deficiency and a lysosomal storage disorder (Pompe’s disease) in 1963 (Hers 1963). In the following decades, the enzymes and cofactors deficient in the sphingolipidoses have been identified. Though lysosomal lipid storage diseases have been known for a long time, treatment is only available for a few mild forms of the diseases, such as the adult forms of Gaucher disease (Barton et al. 1991). For several lysosomal storage diseases, therapies like enzyme replacement or bone marrow transplantation are in the clinical trial stage (Platt and Lachmann 2009). For a long time, lysosomal diseases have been considered a problem of superabundance (storage) in which the storage material can slowly spread to other cellular membranes, impairing their function. More recently, it came into focus that massive storage prevents lysosomal functions such as nutrition delivery through the endolysosomal system, leading to a state of cellular starvation. In mouse models of both GM1 and GM2 gangliosidoses iron is progressively depleted in brain tissue. Administration of iron prolonged survival in the diseased mice by up to 38% (Jeyakumar et al. 2009).