Biology of the TAM Receptors

The TAM receptors—Tyro3, Axl, and Mer—comprise a unique family of receptor tyrosine kinases, in that as a group they play no essential role in embryonic development. Instead, they function as homeostatic regulators in adult tissues and organ systems that are subject to continuous challenge and renewal throughout life. Their regulatory roles are prominent in the mature immune, reproductive, hematopoietic, vascular, and nervous systems. The TAMs and their ligands—Gas6 and Protein S—are essential for the efficient phagocytosis of apoptotic cells and membranes in these tissues; and in the immune system, they act as pleiotropic inhibitors of the innate inflammatory response to pathogens. Deficiencies in TAM signaling are thought to contribute to chronic inflammatory and autoimmune disease in humans, and aberrantly elevated TAM signaling is strongly associated with cancer progression, metastasis, and resistance to targeted therapies.The name of the TAM family is derived from the first letter of its three constituents—Tyro3, Axl, and Mer (Prasad et al. 2006). As detailed in Figure 1, members of this receptor tyrosine kinase (RTK) family were independently identified by several different groups and appear in the early literature under multiple alternative names. However, Tyro3, Axl, and Mer (officially c-Mer or MerTK for the protein, Mertk for the gene) have now been adopted as the NCBI designations. The TAMs were first grouped into a distinct RTK family (the Tyro3/7/12 cluster) in 1991, through PCR cloning of their kinase domains (Lai and Lemke 1991). The isolation of full-length cDNAs for Axl (O''Bryan et al. 1991), Mer (Graham et al. 1994), and Tyro3 (Lai et al. 1994) confirmed their segregation into a structurally distinctive family of orphan RTKs (Manning et al. 2002b). The two ligands that bind and activate the TAMs—Gas6 and Protein S (Pros1)—were identified shortly thereafter (Ohashi et al. 1995; Stitt et al. 1995; Mark et al. 1996; Nagata et al. 1996).Open in a separate windowFigure 1.TAM receptors and ligands. The TAM receptors (red) are Tyro3 (Lai and Lemke 1991; Lai et al. 1994)—also designated Brt (Fujimoto and Yamamoto 1994), Dtk (Crosier et al. 1994), Rse (Mark et al. 1994), Sky (Ohashi et al. 1994), and Tif (Dai et al. 1994); Axl (O''Bryan et al. 1991)—also designated Ark (Rescigno et al. 1991), Tyro7 (Lai and Lemke 1991), and Ufo (Janssen et al. 1991); and Mer (Graham et al. 1994)—also designated Eyk (Jia and Hanafusa 1994), Nyk (Ling and Kung 1995), and Tyro12 (Lai and Lemke 1991). The TAMs are widely expressed by cells of the mature immune, nervous, vascular, and reproductive systems. The TAM ligands (blue) are Gas6 and Protein S (Pros1). The carboxy-terminal SHBG domains of the ligands bind to the immunoglobulin (Ig) domains of the receptors, induce dimerization, and activate the TAM tyrosine kinases. When γ-carboxylated in a vitamin-K-dependent reaction, the amino-terminal Gla domains of the dimeric ligands bind to the phospholipid phosphatidylserine expressed on the surface on an apposed apoptotic cell or enveloped virus. See text for details. (From Lemke and Burstyn-Cohen 2010; adapted, with permission, from the authors.)Subsequent progress on elucidating the biological roles of the TAM receptors was considerably slower and ultimately required the derivation of mouse loss-of-function mutants (Camenisch et al. 1999; Lu et al. 1999). The fact that Tyro3^−/−, Axl^−/−, and Mer^−/− mice are all viable and fertile permitted the generation of a complete TAM mutant series that included all possible double mutants and even triple mutants that lack all three receptors (Lu et al. 1999). Remarkably, these Tyro3^−/−Axl^−/−Mer^−/− triple knockouts (TAM TKOs) are viable, and for the first 2–3 wk after birth, superficially indistinguishable from their wild-type counterparts (Lu et al. 1999). Because many RTKs play essential roles in embryonic development, even single loss-of-function mutations in RTK genes often result in an embryonic-lethal phenotype (Gassmann et al. 1995; Lee et al. 1995; Soriano 1997; Arman et al. 1998). The postnatal viability of mice in which an entire RTK family is ablated completely—the TAM TKOs can survive for more than a year (Lu et al. 1999)—is therefore highly unusual. Their viability notwithstanding, the TAM mutants go on to develop a plethora of phenotypes, some of them debilitating (Camenisch et al. 1999; Lu et al. 1999; Lu and Lemke 2001; Scott et al. 2001; Duncan et al. 2003; Prasad et al. 2006). Almost without exception, these phenotypes are degenerative in nature and reflect the loss of TAM signaling activities in adult tissues that are subject to regular challenge, renewal, and remodeling. These activities are the subject of this review.     

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.     

Mutant p53 Gain-of-Function in Cancer

In its wild-type form, p53 is a major tumor suppressor whose function is critical for protection against cancer. Many human tumors carry missense mutations in the TP53 gene, encoding p53. Typically, the affected tumor cells accumulate excessive amounts of the mutant p53 protein. Various lines of evidence indicate that, in addition to abrogating the tumor suppressor functions of wild-type p53, the common types of cancer-associated p53 mutations also endow the mutant protein with new activities that can contribute actively to various stages of tumor progression and to increased resistance to anticancer treatments. Collectively, these activities are referred to as mutant p53 gain-of-function. This article addresses the biological manifestations of mutant p53 gain-of-function, the underlying molecular mechanisms, and their possible clinical implications.Mutations in the TP53 gene, encoding the p53 tumor suppressor, are arguably the most frequent type of gene-specific alterations in human cancer. This attests to the centrality of p53 as a major mainstay in the body’s built-in anticancer defense mechanisms. Not surprisingly, this pivotal role of the wild-type p53 (wtp53) protein in tumor suppression has attracted many researchers to study it in detail, resulting in an avalanche of information and publications. One might expect that, similar to other tumor suppressor genes, the sole outcome of mutations in the TP53 gene will be loss of wtp53 function, characteristically manifested as total lack of p53 expression or production of unstable or truncated mutant proteins. Yet, quite strikingly, the vast majority of cancer-associated p53 mutations actually lead to production of full length protein, typically with only a single amino acid substitution, which tends to accumulate in the tumor cells and reach steady-state levels that greatly exceed those of wtp53 in noncancerous cells (Rotter 1983). This remarkable feature has suggested early on in p53 research that cancer-associated mutant p53 (mutp53) isoforms may be more than just relics of wtp53 inactivation, and may instead play distinctive roles in the tumor cells.In principle, emergence of a p53 mutation within a cell might have three, not mutually exclusive, types of outcome (Michalovitz et al. 1991; Sigal and Rotter 2000; Weisz et al. 2007b). First, such mutation is expected to abrogate the tumor suppressor function of the affected TP53 allele, reducing the overall capacity of the cell to mount a proper p53 response; if both alleles eventually become mutated, or if the remaining allele is lost, such cells will be totally deprived of anticancer protection by p53. Second, many common mutp53 isoforms can exert dominant–negative effects over coexpressed wtp53, largely by forming mixed tetramers that are incapable of DNA binding and transactivation. Hence, even if one wt allele is retained, the cell may be rendered practically devoid of wtp53 function through such mechanism, particularly if the mutant protein is expressed in excess over its wt counterpart. Third, and most relevant for this article, the emergent mutp53 protein might possess activities of its own, often not present in the original wtp53 protein, which can actively contribute to various aspects of tumor progression. Such activities, commonly described as mutp53 gain-of-function (GOF), are the subject of this article. Several recent reviews address in detail the various aspects of mutp53 GOF (Brosh and Rotter 2009; Donzelli et al. 2008; Lozano 2007; Olivier et al. 2009; Peart and Prives 2006; Petitjean et al. 2007; Song and Xu 2007; Strano et al. 2007; Weisz et al. 2007b). Therefore, we focus here mainly on general principles as well as on some of the more recent findings.     

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).     

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.     

Cadherin-mediated Intercellular Adhesion and Signaling Cascades Involving Small GTPases

Epithelia form physical barriers that separate the internal milieu of the body from its external environment. The biogenesis of functional epithelia requires the precise coordination of many cellular processes. One of the key events in epithelial biogenesis is the establishment of cadherin-dependent cell–cell contacts, which initiate morphological changes and the formation of other adhesive structures. Cadherin-mediated adhesions generate intracellular signals that control cytoskeletal reorganization, polarity, and vesicle trafficking. Among such signaling pathways, those involving small GTPases play critical roles in epithelial biogenesis. Assembly of E-cadherin activates several small GTPases and, in turn, the activated small GTPases control the effects of E-cadherin-mediated adhesions on epithelial biogenesis. Here, we focus on small GTPase signaling at E-cadherin-mediated epithelial junctions.Cell–cell adhesions are involved in a diverse range of physiological processes, including morphological changes during tissue development, cell scattering, wound healing, and synaptogenesis (Adams and Nelson 1998; Gumbiner 2000; Halbleib and Nelson 2006; Takeichi 1995; Tepass et al. 2000). In epithelial cells, cell–cell adhesions are classified into three kinds of adhesions: adherens junction, tight junction, and desmosome (for more details, see Meng and Takeichi 2009, Furuse 2009, and Delva et al. 2009, respectively). A key event in epithelial polarization and biogenesis is the establishment of cadherin-dependent cell–cell contacts. Cadherins belong to a large family of adhesion molecules that require Ca²⁺ for their homophilic interactions (Adams and Nelson 1998; Blanpain and Fuchs 2009; Gumbiner 2000; Hartsock and Nelson 2008; Takeichi 1995; Tepass et al. 2000). Cadherins form transinteraction on the surface of neighboring cells (for details, see Shapiro and Weis 2009). For the development of strong and rigid adhesions, cadherins are clustered concomitantly with changes in the organization of the actin cytoskeleton (Tsukita et al. 1992). Classical cadherins are required, but not sufficient, to initiate cell–cell contacts, and other adhesion protein complexes subsequently assemble (for details, see Green et al. 2009). These complexes include the tight junction, which controls paracellular permeability, and desmosomes, which support the structural continuum of epithelial cells. A fundamental problem is to understand how these diverse cellular processes are regulated and coordinated. Intracellular signals, generated when cells attach with one another, mediate these complicated processes.Several signaling pathways upstream or downstream of cadherin-mediated cell–cell adhesions have been identified (Perez-Moreno et al. 2003) (see also McCrea et al. 2009). Among these pathways, small GTPases including the Rho and Ras family GTPases play critical roles in epithelial biogenesis and have been studied extensively. Many key morphological and functional changes are induced when these small GTPases act at epithelial junctions, where they mediate an interplay between cell–cell adhesion molecules and fundamental cellular processes including cytoskeletal activity, polarity, and vesicle trafficking. In addition to these small GTPases, Ca²⁺ signaling and phosphorylation of cadherin complexes also play pivotal roles in the formation and maintenance of cadherin-mediated adhesions. Here, we focus on signaling pathways involving the small GTPases in E-cadherin-mediated cell–cell adhesions. Other signaling pathways are described in recent reviews (Braga 2002; Fukata and Kaibuchi 2001; Goldstein and Macara 2007; McLachlan et al. 2007; Tsukita et al. 2008; Yap and Kovacs 2003; see also McCrea et al. 2009).     

Molecular Mechanisms of Fibroblast Growth Factor Signaling in Physiology and Pathology

Fibroblast growth factors (FGFs) signal in a paracrine or endocrine fashion to mediate a myriad of biological activities, ranging from issuing developmental cues, maintaining tissue homeostasis, and regulating metabolic processes. FGFs carry out their diverse functions by binding and dimerizing FGF receptors (FGFRs) in a heparan sulfate (HS) cofactor- or Klotho coreceptor-assisted manner. The accumulated wealth of structural and biophysical data in the past decade has transformed our understanding of the mechanism of FGF signaling in human health and development, and has provided novel concepts in receptor tyrosine kinase (RTK) signaling. Among these contributions are the elucidation of HS-assisted receptor dimerization, delineation of the molecular determinants of ligand–receptor specificity, tyrosine kinase regulation, receptor cis-autoinhibition, and tyrosine trans-autophosphorylation. These structural studies have also revealed how disease-associated mutations highjack the physiological mechanisms of FGFR regulation to contribute to human diseases. In this paper, we will discuss the structurally and biophysically derived mechanisms of FGF signaling, and how the insights gained may guide the development of therapies for treatment of a diverse array of human diseases.Fibroblast growth factor (FGF) signaling fulfills essential roles in metazoan development and metabolism. A wealth of literature has documented the requirement for FGF signaling in multiple processes during embryogenesis, including implantation (Feldman et al. 1995), gastrulation (Sun et al. 1999), somitogenesis (Dubrulle and Pourquie 2004; Wahl et al. 2007; Lee et al. 2009; Naiche et al. 2011; Niwa et al. 2011), body plan formation (Martin 1998; Rodriguez Esteban et al. 1999; Tanaka et al. 2005; Mariani et al. 2008), morphogenesis (Metzger et al. 2008; Makarenkova et al. 2009), and organogenesis (Goldfarb 1996; Kato and Sekine 1999; Sekine et al. 1999; Sun et al. 1999; Colvin et al. 2001; Serls et al. 2005; Vega-Hernandez et al. 2011). Recent clinical and biochemical data have uncovered unexpected roles for FGF signaling in metabolic processes, including phosphate/vitamin D homeostasis (Consortium 2000; Razzaque and Lanske 2007; Nakatani et al. 2009; Gattineni et al. 2011; Kir et al. 2011), cholesterol/bile acid homeostasis (Yu et al. 2000a; Holt et al. 2003), and glucose/lipid metabolism (Fu et al. 2004; Moyers et al. 2007). Highlighting its diverse biology, deranged FGF signaling contributes to many human diseases, such as congenital craniosynostosis and dwarfism syndromes (Naski et al. 1996; Wilkie et al. 2002, 2005), Kallmann syndrome (Dode et al. 2003; Pitteloud et al. 2006a), hearing loss (Tekin et al. 2007, 2008), and renal phosphate wasting disorders (Shimada et al. 2001; White et al. 2001), as well as many acquired forms of cancers (Rand et al. 2005; Pollock et al. 2007; Gartside et al. 2009; di Martino et al. 2012). Endocrine FGFs have also been implicated in the progression of acquired metabolic disorders, including chronic kidney disease (Fliser et al. 2007), obesity (Inagaki et al. 2007; Moyers et al. 2007; Reinehr et al. 2012), and insulin resistance (Fu et al. 2004; Chen et al. 2008b; Chateau et al. 2010; Huang et al. 2011), giving rise to many opportunities for drug discovery in the field of FGF biology (Beenken and Mohammadi 2012).Based on sequence homology and phylogeny, the 18 mammalian FGFs are grouped into six subfamilies (Ornitz and Itoh 2001; Popovici et al. 2005; Itoh and Ornitz 2011). Five of these subfamilies act in a paracrine fashion, namely, the FGF1 subfamily (FGF1 and FGF2), the FGF4 subfamily (FGF4, FGF5, and FGF6), the FGF7 subfamily (FGF3, FGF7, FGF10, and FGF22), the FGF8 subfamily (FGF8, FGF17, and FGF18), and the FGF9 subfamily (FGF9, FGF16, and FGF20). In contrast, the FGF19 subfamily (FGF19, FGF21, and FGF23) signals in an endocrine manner (Beenken and Mohammadi 2012). FGFs exert their pleiotropic effects by binding and activating the FGF receptor (FGFR) subfamily of receptor tyrosine kinases that are coded by four genes (FGFR1, FGFR2, FGFR3, and FGFR4) in mammals (Johnson and Williams 1993; Mohammadi et al. 2005b). The extracellular domain of FGFRs consists of three immunoglobulin (Ig)-like domains (D1, D2, and D3), and the intracellular domain harbors the conserved tyrosine kinase domain flanked by the flexible amino-terminal juxtamembrane linker and carboxy-terminal tail (Lee et al. 1989; Dionne et al. 1991; Givol and Yayon 1992). A unique feature of FGFRs is the presence of a contiguous segment of glutamic and aspartic acids in the D1–D2 linker, termed the acid box (AB). The two-membrane proximal D2 and D3 and the intervening D2–D3 linker are necessary and sufficient for ligand binding/specificity (Dionne et al. 1990; Johnson et al. 1990), whereas D1 and the D1–D2 linker are implicated in receptor autoinhibition (Wang et al. 1995; Roghani and Moscatelli 2007; Kalinina et al. 2012). Alternative splicing and translational initiation further diversify both ligands and receptors. The amino-terminal regions of FGF8 and FGF17 can be differentially spliced to yield FGF8a, FGF8b, FGF8e, FGF8f (Gemel et al. 1996; Blunt et al. 1997), and FGF17a and FGF17b isoforms (Xu et al. 1999), whereas cytosine-thymine-guanine (CTG)-mediated translational initiation gives rise to multiple high molecular weight isoforms of FGF2 and FGF3 (Florkiewicz and Sommer 1989; Prats et al. 1989; Acland et al. 1990). The tissue-specific alternative splicing in D3 of FGFR1, FGFR2, and FGFR3 yields “b” and “c” receptor isoforms which, along with their temporal and spatial expression patterns, is the major regulator of FGF–FGFR specificity/promiscuity (Orr-Urtreger et al. 1993; Ornitz et al. 1996; Zhang et al. 2006). A large body of structural data on FGF–FGFR complexes has begun to reveal the intricate mechanisms by which different FGFs and FGFRs combine selectively to generate quantitatively and qualitatively different intracellular signals, culminating in distinct biological responses. In addition, these structural data have unveiled how pathogenic mutations hijack the normal physiological mechanisms of FGFR regulation to lead to pathogenesis. We will discuss the current state of the structural biology of the FGF–FGFR system, lessons learned from studying the mechanism of action of pathogenic mutations, and how the structural data are beginning to shape and advance the translational research.     

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.     

Functional Differentiation of Adult-Born Neurons along the Septotemporal Axis of the Dentate Gyrus

Over the past several decades, the proliferation and integration of adult-born neurons into existing hippocampal circuitry has been implicated in a wide range of behaviors, including novelty recognition, pattern separation, spatial learning, anxiety behaviors, and antidepressant response. In this review, we suggest that the diversity in behavioral requirements for new neurons may be partly caused by separate functional roles of individual neurogenic niches. Growing evidence shows that the hippocampal formation can be compartmentalized not only along the classic trisynaptic circuit, but also along a longitudinal septotemporal axis. We suggest that subpopulations of hippocampal adult-born neurons may be specialized for distinct mnemonic- or mood-related behavioral tasks. We will examine the literature supporting a functional and anatomical dissociation of the hippocampus along the longitudinal axis and discuss techniques to functionally dissect the roles of adult-born hippocampal neurons in these distinct subregions.Since the presence of dividing cells in the mostly postmitotic adult brain was first described (Altman and Das 1965), the generation of new neurons in adulthood has been proposed to be involved in a variety of behaviors (Doetsch and Hen 2005; Becker and Wojtowicz 2007; Sahay and Hen 2007; Deng et al. 2010; Ming and Song 2011; Miller and Hen 2014). Adult neurogenesis in the healthy mammalian brain is consistently seen in the subventricular zone (SVZ) of the lateral ventricles and the subgranular zone (SGZ) of the hippocampal dentate gyrus (DG). Recent studies have implicated hippocampal neurogenesis in learning- and memory-related tasks, such as contextual discrimination and spatial navigation and, specifically, in behavioral pattern separation (Clelland et al. 2009; Sahay et al. 2011; Nakashiba et al. 2012; Niibori et al. 2012; see also reviews in Deng et al. 2010; Ming and Song 2011; Marin-Burgin and Schinder 2012), but also in some behavioral effects of antidepressants (Santarelli et al. 2003; see also reviews in Sahay and Hen 2007; Kheirbek et al. 2012; Tanti and Belzung 2013). However, the exact role of adult hippocampal neurogenesis in some of these behaviors has been debated as some studies have shown no effects of altering adult neurogenesis on spatial navigation or antidepressant response. Proposed explanations have included differences in the behavioral tasks used to measure cognition or emotion, motivational state of subjects, species differences, or in how neurogenesis is defined, either as proliferation, survival, or differentiation (see reviews in Zhao et al. 2008; Aimone et al. 2011; Petrik et al. 2012b; Miller and Hen 2014).It must also be noted, however, that these hippocampal neurons are not born into a singular structure. Work in the past several decades has shown that the hippocampus can be divided, not only along the classic trisynaptic loop, but also longitudinally along a septotemporal axis. The septal (dorsal in rodents; posterior in primates) and temporal (ventral in rodents; anterior in primates) poles, as well as potential intermediate zones of the hippocampus, have different anatomic connections and electrophysiological properties, express a gradient of molecular markers, and play different functional roles, such as performance in spatial learning tasks and stress responses (see reviews in Moser and Moser 1998; Fanselow and Dong 2010). Consequently, adult-born neurons in the hippocampal DG may also be segregated along this longitudinal axis, and conflicting functional roles for neurogenesis may be a result of attempting to examine hippocampal neurogenesis as a unitary phenomenon. It is possible that there are intrinsic, cell-autonomous differences in adult-born neurons generated at opposite poles of the DG. An alternative, although not mutually exclusive, hypothesis is that progenitor cells are initially identical, but differentiate in a dissimilar manner as a result of integration into distinct network circuitry. We will, therefore, first discuss heterogeneity of the hippocampus along its longitudinal axis before reviewing differences in neurogenesis between the septal and temporal poles of the DG. As these topics have been reviewed extensively elsewhere (Moser and Moser 1998; Deng et al. 2010; Fanselow and Dong 2010; Koehl and Abrous 2011; Samuels and Hen 2011; Kheirbek et al. 2012; Petrik et al. 2012b), we will not try to exhaustively cover all the current literature. Rather, we attempt to gather key studies examining a septotemporal gradient of the hippocampus and hippocampal neurogenesis. We will then suggest possible approaches to examine neurogenesis in specific subregions of the hippocampal DG. Finally, a short section will examine segregation of the DG along its transverse axis.     

Fibronectins,Their Fibrillogenesis,and In Vivo Functions

Fibronectin (FN) is a multidomain protein with the ability to bind simultaneously to cell surface receptors, collagen, proteoglycans, and other FN molecules. Many of these domains and interactions are also involved in the assembly of FN dimers into a multimeric fibrillar matrix. When, where, and how FN binds to its various partners must be controlled and coordinated during fibrillogenesis. Steps in the process of FN fibrillogenesis including FN self-association, receptor activities, and intracellular pathways have been under intense investigation for years. In this review, the domain organization of FN including the extra domains and variable region that are controlled by alternative splicing are described. We discuss how FN–FN and cell–FN interactions play essential roles in the initiation and progression of matrix assembly using complementary results from cell culture and embryonic model systems that have enhanced our understanding of this process.As a ubiquitous component of the extracellular matrix (ECM), fibronectin (FN) provides essential connections to cells through integrins and other receptors and regulates cell adhesion, migration, and differentiation. FN is secreted as a large dimeric glycoprotein with subunits that range in size from 230 kDa to 270 kDa (Mosher 1989; Hynes 1990). Variation in subunit size depends primarily on alternative splicing. FN was first isolated from blood more than 60 years ago (Edsall 1978), and this form is called plasma FN. The other major form, called cellular FN, is abundant in the fibrillar matrices of most tissues. Although FN is probably best known for promoting attachment of cells to surfaces, this multidomain protein has many interesting structural features and functional roles beyond cell adhesion.FN is composed of three different types of modules termed type I, II, and III repeats (Fig. 1) (Petersen et al. 1983; Hynes 1990). These repeats have distinct structures. Although the conformations of type I and type II repeats are maintained by pairs of intramodule disulfide bonds, the type III repeat is a 7-stranded β-barrel structure that lacks disulfide bonds (Main et al. 1992; Leahy et al. 1996, 1992) and, therefore, can undergo conformational changes. FN type III repeats are widely distributed among animal, bacterial, and plant proteins and are found in both extracellular and intracellular proteins (Bork and Doolittle 1992; Tsyguelnaia and Doolittle 1998).Open in a separate windowFigure 1.FN domain organization and isoforms. Each FN monomer has a modular structure consisting of 12 type I repeats (cylinders), 2 type II repeats (diamonds), and 15 constitutive type III repeats (hexagons). Two additional type III repeats (EIIIA and EIIIB, green) are included or omitted by alternative splicing. The third region of alternative splicing, the V region (green box), is included (V120), excluded (V0), or partially included (V95, V64, V89). Sets of modules comprise domains for binding to other extracellular molecules as indicated. Domains required for fibrillogenesis are in red: the assembly domain (repeats I_1-5) binds FN, III_9-10 contains the RGD and synergy sequences for integrin binding, and the carboxy-terminal cysteines form the disulfide-bonded FN dimer (‖). The III_1-2 domain (light red) has two FN binding sites that are important for fibrillogenesis. The amino-terminal 70-kDa fragment contains assembly and gelatin-binding domains and is routinely used in FN binding and matrix assembly studies.Sets of adjacent modules form binding domains for a variety of proteins and carbohydrates (Fig. 1). ECM proteins, including FN, bind to cells via integrin receptors, αβ heterodimers with two transmembrane subunits (Hynes 2002). FN-binding integrins have specificity for one of the two cell-binding sites within FN, either the RGD-dependent cell-binding domain in III₁₀ (Pierschbacher and Ruoslahti 1984) or the CS1 segment of the alternatively spliced V region (IIICS) (Wayner et al. 1989; Guan and Hynes 1990). Some integrins require a synergy sequence in repeat III₉ for maximal interactions with FN (Aota et al. 1994; Bowditch et al. 1994). Another family of cell surface receptors is the syndecans, single-chain transmembrane proteoglycans (Couchman 2010). Syndecans use their glycosaminoglycan (GAG) chains to interact with FN at its carboxy-terminal heparin-binding (HepII) domain (Fig. 1) (Saunders and Bernfield 1988; Woods et al. 2000), which binds to heparin, heparan sulfate, and chondroitin sulfate GAGs (Hynes 1990; Barkalow and Schwarzbauer 1994). Syndecan binding to the HepII domain enhances integrin-mediated cell spreading and intracellular signaling, suggesting that syndecans act as coreceptors with integrins in cell–FN binding (Woods and Couchman 1998; Morgan et al. 2007).A major site for FN self-association is within the amino-terminal assembly domain spanning the first five type I repeats (I_1-5) (Fig. 1) (McKeown-Longo and Mosher 1985; McDonald et al. 1987; Schwarzbauer 1991b; Sottile et al. 1991). This domain plays an essential role in FN fibrillogenesis. As a major blood protein, FN interacts with fibrin during blood coagulation, also using the I_1-5 domain (Mosher 1989; Hynes 1990). As fibrin polymerizes, factor XIII transglutaminase covalently cross-links glutamine residues near the amino terminus of FN to fibrin α chains (Mosher 1975; Corbett et al. 1997). The amino-terminal domain has multiple binding partners in addition to FN and fibrin; these include heparin, S. aureus, and other bacteria, thrombospondin-1, and tenascin-C (Hynes 1990; Ingham et al. 2004; Schwarz-Linek et al. 2006). Adjacent to this domain is the gelatin/collagen-binding domain composed of type I and type II modules (Ingham et al. 1988). This domain also binds to tissue transglutaminase (Radek et al. 1993) and fibrillin-1 (Sabatier et al. 2009). Within the 15 type III repeats reside several FN binding sites that interact with the amino-terminal assembly domain as well as three sites of alternative splicing that generate multiple isoforms. At the carboxyl terminus is a pair of cysteine residues that form the FN dimer through antiparallel disulfide bonds (Hynes 1990). This dimerization may be facilitated by disulfide isomerase activity located in the last set of type I repeats (Langenbach and Sottile 1999).The diverse set of binding domains provides FN with the ability to interact simultaneously with other FN molecules, other ECM components (e.g., collagens and proteoglycans), cell surface receptors, and extracellular enzymes (Pankov and Yamada 2002; Fogelgren et al. 2005; Hynes 2009; Singh et al. 2010). Multitasking by FN probably underlies its essential role during embryogenesis (George et al. 1993). Furthermore, FN''s interactions can be modulated by exposure or sequestration of its binding sites within matrix fibrils, through the presence of ECM proteins that bind to FN, or through variation in structure by alternative splicing.     

Quality Control of Mitochondrial Proteostasis

A decline in mitochondrial activity has been associated with aging and is a hallmark of many neurological diseases. Surveillance mechanisms acting at the molecular, organellar, and cellular level monitor mitochondrial integrity and ensure the maintenance of mitochondrial proteostasis. Here we will review the central role of mitochondrial chaperones and proteases, the cytosolic ubiquitin-proteasome system, and the mitochondrial unfolded response in this interconnected quality control network, highlighting the dual function of some proteases in protein quality control within the organelle and for the regulation of mitochondrial fusion and mitophagy.In all cellular compartments, correct protein folding is critical to maintain cellular homeostasis. In cases where proteins become misfolded or damaged, it is imperative that they are turned over and removed to prevent the formation of toxic folding intermediates or the accumulation of aggregates to levels that can be deleterious for the cell. Several neurodegenerative diseases share a common pathogenic mechanism, which involves the formation of fibrillar aggregates of a particular protein that can accumulate in the cytosol, the nucleus, or the mitochondria. Examples of this include accumulation of the amyloid-β peptide in Alzheimer’s disease (Kayed et al. 2003; Tanzi and Bertram 2005), accumulation of α-synuclein in Parkinson’s disease (Spillantini et al. 1997; Zarranz et al. 2004), and aggregation of a mutant form of the huntingtin protein caused by extended polyglutamine stretches in Huntington’s disease (DiFiglia et al. 1997). Although the exact mechanism of pathogenesis for these diseases remains unresolved, mitochondrial dysfunction is implicated in their progression, which may in turn be responsible for the loss of neurological cell populations because of their sensitivity and requirement for functional mitochondria (Rodolfo et al. 2010).The evolution of mitochondria began approximately 1.5 billion years ago after an α-proteobacterium was engulfed by a preeukaryotic cell (Gray et al. 1999). Since that time, mitochondria have retained two phospholipid bilayers that segregate two aqueous compartments, the mitochondrial intermembrane space (IMS) and the mitochondrial matrix (Palade 1953). Mitochondria are found in essentially all eukaryotic cells and play integral roles in a number of the cell''s metabolic pathways. For example, mitochondria are the key players in cellular ATP production through an elaborate respiratory chain network found in the organelles inner membrane (IM) (Mitchell 1961; Leonard and Schapira 2000). Mitochondria are also required for the β-oxidation of fatty acids, Fe-S biosynthesis, and Ca²⁺ homeostasis (Pinton et al. 1998; Rizzuto et al. 2000; Lill 2009; Modre-Osprian et al. 2009). Moreover, mitochondria are key regulators of programmed cell death and they participate in developmental processes as well as aging (Singh 2004; Green 2005).In contrast to early depictions of mitochondria as singular kidney bean shaped entities, it is now well established that mitochondria form elaborate, reticular networks in many tissues (Bereiter-Hahn 1990). The ability of mitochondria to form such networks arises from two major factors: (1) Specialized machineries in the mitochondrial outer membrane (OM) and the IM allow mitochondria to fuse and divide and (2) mitochondria are able to be shuttled along cytoskeletal elements (Anesti and Scorrano 2006; Hoppins et al. 2007). This plasticity of mitochondria ensures that they are able to respond to different cellular cues, which is potentially important for their numerous functions. In different cell types, mitochondria adopt varying morphologies (Kuznetsov et al. 2009). For example, in cultured fibroblasts mitochondria form extensive reticular networks, whereas in neuronal cells, mitochondria can be found enriched at areas of high-energy demand, including presynaptic termini, axon initial segments, and growth cones. Furthermore, in muscle cells, mitochondria adopt a very uniform intermyofibrillar conformation (Vendelin et al. 2005). The dynamic nature of mitochondria provides an explanation as to how they adopt varying organizations in different cell populations. The importance of mitochondrial networks is highlighted by the fact that mutations in components involved in maintaining mitochondrial dynamics results in neurodegenerative diseases (Chan 2006; Olichon et al. 2006; Knott et al. 2008; Martinelli and Rugarli 2010; Winklhofer and Haass 2010).     

Mitochondrial Evolution

Viewed through the lens of the genome it contains, the mitochondrion is of unquestioned bacterial ancestry, originating from within the bacterial phylum α-Proteobacteria (Alphaproteobacteria). Accordingly, the endosymbiont hypothesis—the idea that the mitochondrion evolved from a bacterial progenitor via symbiosis within an essentially eukaryotic host cell—has assumed the status of a theory. Yet mitochondrial genome evolution has taken radically different pathways in diverse eukaryotic lineages, and the organelle itself is increasingly viewed as a genetic and functional mosaic, with the bulk of the mitochondrial proteome having an evolutionary origin outside Alphaproteobacteria. New data continue to reshape our views regarding mitochondrial evolution, particularly raising the question of whether the mitochondrion originated after the eukaryotic cell arose, as assumed in the classical endosymbiont hypothesis, or whether this organelle had its beginning at the same time as the cell containing it.In 1970, Lynn Margulis published Origin of Eukaryotic Cells, an influential book that effectively revived the long-standing but mostly moribund idea that mitochondria and plastids (chloroplasts) evolved from free-living bacteria via symbiosis within a eukaryotic host cell (Margulis 1970). The discovery in the 1960s of DNA within these organelles together with the recognition that they contain a translation system distinct from that of the cytosol were two of the observations that Margulis marshaled in support of the endosymbiont hypothesis of organelle origins. Indeed, throughout her career, Margulis forcefully argued that symbiosis is a potent but largely unrecognized and unappreciated force in evolution (Margulis 1981). Technological developments in DNA cloning and sequencing in the 1970s and 1980s opened the way to the detailed characterization of mitochondrial genomes and genes, and the generation of key molecular data that were instrumental in affirming a bacterial origin of the mitochondrial and plastid genomes, allowing researchers to pinpoint the extant bacterial phyla to which these two organelles are most closely related. Over the past several decades, numerous reviews have documented in detail the biochemical and molecular and cell biological data bearing on the endosymbiont hypothesis of organelle origins (Gray 1982, 1983, 1989a,b, 1992, 1993, 1999; Gray and Doolittle 1982; Wallace 1982; Cavalier-Smith 1987b, 1992; Gray and Spencer 1996; Andersson and Kurland 1999; Gray et al. 1999, 2001, 2004; Lang et al. 1999; Andersson et al. 2003; Burger et al. 2003a; Bullerwell and Gray 2004). Various endosymbiotic models proposed over the years have been comprehensively critiqued (Martin et al. 2001), while the debates surrounding the endosymbiont hypothesis have been recounted in an engaging perspective that traces the development of ideas regarding organelle origins (Sapp 1994). Within a historical context, the present article emphasizes more recent data and insights that are relevant to continuing questions regarding how mitochondria originated and have since evolved.     

Replicating Damaged DNA in Eukaryotes

DNA damage is one of many possible perturbations that challenge the mechanisms that preserve genetic stability during the copying of the eukaryotic genome in S phase. This short review provides, in the first part, a general introduction to the topic and an overview of checkpoint responses. In the second part, the mechanisms of error-free tolerance in response to fork-arresting DNA damage will be discussed in some detail.Before eukaryotic cells divide, the successful completion of DNA replication during S phase is essential to preserve genomic integrity from one generation to the next. During this process, the replication apparatus traverses in the form of bidirectionally moving forks to synthesize new daughter strands. Cells use several means to ensure faithful copying of the parental strands—first, by means of regulatory mechanisms a correctly coordinated replication apparatus is established, and second, a high degree of fidelity during DNA synthesis is maintained by replicative polymerases (Kunkel and Bebenek 2000; Reha-Krantz 2010). However, under several stressful circumstances, endogenously or exogenously induced, the replication apparatus can stall (Tourriere and Pasero 2007). Mostly, structural deformations in the form of lesions or special template-specific features arrest the replication process, activate checkpoint pathways and set in motion repair or tolerance mechanisms to counter the stalling (Branzei and Foiani 2009; Zegerman and Diffley 2009). Basic replication mechanism, its regulatory pathways and means to tolerate DNA damage are largely conserved across eukaryotic species (Branzei and Foiani 2010; Yao and O’Donnell 2010). Understanding the mechanisms involved may enable therapeutic intervention to several human conditions arising from an incomplete replication or from the inability to tolerate perturbations (Ciccia et al. 2009; Preston et al. 2010; Abbas et al. 2013). Enhanced replication stress has also been commonly identified in precancerous lesions, and the inactivation of checkpoint responses coping with this presumably oncogene-induced condition is considered necessary to establish the fully malignant phenotype (Bartkova et al. 2005; Negrini et al. 2010).It is not possible to treat this topic in a comprehensive manner in the allotted space; the reader is referred to excellent recent reviews for more details (Branzei and Foiani 2010; Jones and Petermann 2012). We will attempt to provide an overview of the various strategies that a eukaryotic cell invokes to avoid problems caused by replication stress related to DNA damage and, if problems arise, to tolerate damage without endangering the entire process of genome duplication. In this context, we will only give a brief outline of checkpoint responses that are discussed in more detail in Sirbu and Cortez (2013) and Marechal and Zou (2013). Also, a detailed discussion of translesion synthesis can be reviewed in Sale (2013).     

Glial Cell Development and Function in Zebrafish

The zebrafish is a premier vertebrate model system that offers many experimental advantages for in vivo imaging and genetic studies. This review provides an overview of glial cell types in the central and peripheral nervous system of zebrafish. We highlight some recent work that exploited the strengths of the zebrafish system to increase the understanding of the role of Gpr126 in Schwann cell myelination and illuminate the mechanisms controlling oligodendrocyte development and myelination. We also summarize similarities and differences between zebrafish radial glia and mammalian astrocytes and consider the possibility that their distinct characteristics may represent extremes in a continuum of cell identity. Finally, we focus on the emergence of zebrafish as a model for elucidating the development and function of microglia. These recent studies have highlighted the power of the zebrafish system for analyzing important aspects of glial development and function.Following the pioneering work of George Streisinger in the early 1980s, the zebrafish has emerged as a premier vertebrate model system (Streisinger et al. 1981). A key strength of the zebrafish is that the embryos and early larvae are transparent, allowing exquisite cellular analysis of many dynamic processes, including cell migration, axonal pathfinding, and myelination, among many others (e.g., Gilmour et al. 2002; Lyons et al. 2005; Czopka et al. 2013). The zebrafish also has many advantages for large-scale genetic studies, including relatively small size and rapid development, high fecundity, and the ability to manipulate the ploidy of gametes and early embryos (Kimmel 1989). Through the 1980s and early 1990s, insightful studies of several interesting mutations elegantly exploited these experimental advantages (e.g., Kimmel et al. 1989; Ho and Kane 1990; Hatta et al. 1991; Grunwald and Eisen 2002), attracting many researchers from other fields to the zebrafish system. Following the explosion of interest in the zebrafish in the 1990s, advances in many areas have added to the strengths of the system, including large-scale screens that identified thousands of new mutations (Driever et al. 1996; Haffter et al. 1996), rapid transgenesis (Kawakami et al. 2004), new methods for imaging and tracking all cells during development (Huisken 2012), genetic mapping and sequencing to identify genes and mutated loci (Postlethwait et al. 1994; Howe et al. 2013), optogenetic methods to control neural activity (Portugues et al. 2013), the advent of targeted nucleases to create mutations in genes of interest (Huang et al. 2011; Sander et al. 2011; Bedell et al. 2012; Chang et al. 2013; Hwang et al. 2013), and small molecule screening approaches to isolate compounds with novel biological activities in vivo (Peterson and Fishman 2011).Many fundamental similarities in physiology and body plan unite the zebrafish and other vertebrates (Kimmel 1989). In addition, analysis of genes and genomes has revealed that sequence, expression, and function of many genes are conserved among zebrafish and other vertebrates (Postlethwait and Talbot 1997; Howe et al. 2013). Thus, insights from studies in zebrafish will apply broadly to other vertebrates, including humans. On the other hand, there are important genetic, genomic, and physiological differences among vertebrates. It is, therefore, important to keep possible differences in mind and to recognize that analyzing the diversity among different species may enhance overall understanding of important processes. For example, zebrafish and other teleosts have a much more extensive regenerative ability than mammals, so that studies of fin, heart, and spinal cord regeneration in zebrafish may suggest avenues toward new therapeutic approaches in humans (Gemberling et al. 2013; Becker and Becker 2014).In this review, we provide an overview of different types of glia in the zebrafish, with a focus on some recent studies that highlight the power of the zebrafish system to analyze different aspects of glial development and function.     

Endocytosis,Signaling, and Beyond

The endocytic network comprises a vast and intricate system of membrane-delimited cell entry and cargo sorting routes running between biochemically and functionally distinct intracellular compartments. The endocytic network caters to the organization and redistribution of diverse subcellular components, and mediates appropriate shuttling and processing of materials acquired from neighboring cells or the extracellular milieu. Such trafficking logistics, despite their importance, represent only one facet of endocytic function. The endocytic network also plays a key role in organizing, mediating, and regulating cellular signal transduction events. Conversely, cellular signaling processes tightly control the endocytic pathway at different steps. The present article provides a perspective on the intimate relationships that exist between particular endocytic and cellular signaling processes in mammalian cells, within the context of understanding the impact of this nexus on integrated physiology.Molecular mechanisms governing the remarkable diversity of endocytic routes and trafficking steps are described elsewhere in the literature (see Bissig and Gruenberg 2013; Henne et al. 2013; Burd and Cullen 2014; Gautreau et al. 2014; Kirchhausen et al. 2014; Mayor et al. 2014; Merrifield and Kaksonen 2014; Piper et al. 2014). Moreover, these have been the focus of many studies in the last 30 years, and the topic has been covered by many excellent reviews, making it unnecessary for us to dwell on this aspect any further here (see, for instance, Howes et al. 2010; McMahon and Boucrot 2011; Sandvig et al. 2011; Parton and del Pozo 2013). Herein, we will instead concentrate our attention on how cellular regulatory mechanisms control endocytosis, as well as on how endocytic events impinge on cell functions. Emphasis will be placed, although not exclusively, on studies that analyze cellular networks using holistic approaches and in vivo analysis. Our aim is to give the reader a flavor of the deep embedding of endocytic processes within cellular programs, a concept we refer to as the endocytic matrix (Scita and Di Fiore 2010).