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Microglia are the resident macrophages of the central nervous system (CNS), which sit in close proximity to neural structures and are intimately involved in brain homeostasis. The microglial population also plays fundamental roles during neuronal expansion and differentiation, as well as in the perinatal establishment of synaptic circuits. Any change in the normal brain environment results in microglial activation, which can be detrimental if not appropriately regulated. Aberrant microglial function has been linked to the development of several neurological and psychiatric diseases. However, microglia also possess potent immunoregulatory and regenerative capacities, making them attractive targets for therapeutic manipulation. Such rationale manipulations will, however, require in-depth knowledge of their origins and the molecular mechanisms underlying their homeostasis. Here, we discuss the latest advances in our understanding of the origin, differentiation, and homeostasis of microglial cells and their myelomonocytic relatives in the CNS.Microglia are the resident macrophages of the central nervous system (CNS), which are uniformly distributed throughout the brain and spinal cord with increased densities in neuronal nuclei, including the Substantia nigra in the midbrain (Lawson et al. 1990; Perry 1998). They belong to the nonneuronal glial cell compartment and their function is crucial to maintenance of the CNS in both health and disease (Ransohoff and Perry 2009; Perry et al. 2010; Ransohoff and Cardona 2010; Prinz and Priller 2014).Two key functional features define microglia: immune defense and maintenance of CNS homeostasis. As part of the innate immune system, microglia constantly sample their environment, scanning and surveying for signals of external danger (Davalos et al. 2005; Nimmerjahn et al. 2005; Lehnardt 2010), such as those from invading pathogens, or internal danger signals generated locally by damaged or dying cells (Bessis et al. 2007; Hanisch and Kettenmann 2007). Detection of such signals initiates a program of microglial responses that aim to resolve the injury, protect the CNS from the effects of the inflammation, and support tissue repair and remodeling (Minghetti and Levi 1998; Goldmann and Prinz 2013).Microglia are also emerging as crucial contributors to brain homeostasis through control of neuronal proliferation and differentiation, as well as influencing formation of synaptic connections (Lawson et al. 1990; Perry 1998; Hughes 2012; Blank and Prinz 2013). Recent imaging studies revealed dynamic interactions between microglia and synaptic connections in the healthy brain, which contributed to the modification and elimination of synaptic structures (Perry et al. 2010; Tremblay et al. 2010; Bialas and Stevens 2013). In the prenatal brain, microglia regulate the wiring of forebrain circuits, controlling the growth of dopaminergic axons in the forebrain and the laminar positioning of subsets of neocortical interneurons (Squarzoni et al. 2014). In the postnatal brain, microglia-mediated synaptic pruning is similarly required for the remodeling of neural circuits (Paolicelli et al. 2011; Schafer et al. 2012). In summary, microglia occupy a central position in defense and maintenance of the CNS and, as a consequence, are a key target for the treatment of neurological and psychiatric disorders.Although microglia have been studied for decades, a long history of experimental misinterpretation meant that their true origins remained debated until recently. Although we knew that microglial progenitors invaded the brain rudiment at very early stages of embryonic development (Alliot et al. 1999; Ransohoff and Perry 2009), it has now been established that microglia arise from yolk sac (YS)-primitive macrophages, which persist in the CNS into adulthood (Davalos et al. 2005; Nimmerjahn et al. 2005; Ginhoux et al. 2010, 2013; Kierdorf and Prinz 2013; Kierdorf et al. 2013a). Moreover, early embryonic brain colonization by microglia is conserved across vertebrate species, implying that it is essential for early brain development (Herbomel et al. 2001; Bessis et al. 2007; Hanisch and Kettenmann 2007; Verney et al. 2010; Schlegelmilch et al. 2011; Swinnen et al. 2013). In this review, we will present the latest findings in the field of microglial ontogeny, which provide new insights into their roles in health and disease. 相似文献
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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). 相似文献
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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. 相似文献
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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. 相似文献
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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). 相似文献
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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. 相似文献
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Melody V. Wu Amar Sahay Ronald S. Duman René Hen 《Cold Spring Harbor perspectives in biology》2015,7(8)
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. 相似文献
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The Wnt pathway is a major embryonic signaling pathway that controls cell proliferation, cell fate, and body-axis determination in vertebrate embryos. Soon after egg fertilization, Wnt pathway components play a role in microtubule-dependent dorsoventral axis specification. Later in embryogenesis, another conserved function of the pathway is to specify the anteroposterior axis. The dual role of Wnt signaling in Xenopus and zebrafish embryos is regulated at different developmental stages by distinct sets of Wnt target genes. This review highlights recent progress in the discrimination of different signaling branches and the identification of specific pathway targets during vertebrate axial development.Wnt pathways play major roles in cell-fate specification, proliferation and differentiation, cell polarity, and morphogenesis (Clevers 2006; van Amerongen and Nusse 2009). Signaling is initiated in the responding cell by the interaction of Wnt ligands with different receptors and coreceptors, including Frizzled, LRP5/6, ROR1/2, RYK, PTK7, and proteoglycans (Angers and Moon 2009; Kikuchi et al. 2009; MacDonald et al. 2009). Receptor activation is accompanied by the phosphorylation of Dishev-elled (Yanagawa et al. 1995), which appears to transduce the signal to both the cell membrane and the nucleus (Cliffe et al. 2003; Itoh et al. 2005; Bilic et al. 2007). Another common pathway component is β-catenin, an abundant component of adherens junctions (Nelson and Nusse 2004; Grigoryan et al. 2008). In response to signaling, β-catenin associates with T-cell factors (TCFs) and translocates to the nucleus to stimulate Wnt target gene expression (Behrens et al. 1996; Huber et al. 1996; Molenaar et al. 1996).This β-catenin-dependent activation of specific genes is often referred to as the “canonical” pathway. In the absence of Wnt signaling, β-catenin is destroyed by the protein complex that includes Axin, GSK3, and the tumor suppressor APC (Clevers 2006; MacDonald et al. 2009). Wnt proteins, such as Wnt1, Wnt3, and Wnt8, stimulate Frizzled and LRP5/6 receptors to inactivate this β-catenin destruction complex, and, at the same time, trigger the phosphorylation of TCF proteins by homeodomain-interacting protein kinase 2 (HIPK2) (Hikasa et al. 2010; Hikasa and Sokol 2011). Both β-catenin stabilization and the regulation of TCF protein function by phosphorylation appear to represent general strategies that are conserved in multiple systems (Sokol 2011). Thus, the signaling pathway consists of two branches that together regulate target gene expression (Fig. 1).Open in a separate windowFigure 1.Conserved Wnt pathway branches and components. In the absence of Wnt signals, glycogen synthase kinase 3 (GSK3) binds Axin and APC to form the β-catenin destruction complex. Some Wnt proteins, such as Wnt8 and Wnt3a, stimulate Frizzled and LRP5/6 receptors to inhibit GSK3 activity and stabilize β-catenin (β-cat). Stabilized β-cat forms a complex with T-cell factors (e.g., TCF1/LEF1) to activate target genes. Moreover, GSK3 inhibition leads to target gene derepression by promoting TCF3 phosphorylation by homeodomain-interacting protein kinase 2 (HIPK2) through an unknown mechanism, for which β-catenin is required as a scaffold. This phosphorylation results in TCF3 removal from target promoters and gene activation. Other Wnt proteins, such as Wnt5a and Wnt11, use distinct receptors such as ROR2 and RYK, in addition to Frizzled, to control the the cytoskeletal organization through core planar cell polarity (PCP) proteins, small GTPases (Rho/Rac/Cdc42), and c-Jun amino-terminal kinase (JNK).Other Wnt proteins, such as Wnt5a or Wnt11, strongly affect the cytoskeletal organization and morphogenesis without stabilizing β-catenin (Torres et al. 1996; Angers and Moon 2009; Wu and Mlodzik 2009). These “noncanonical” ligands do not influence TCF3 phosphorylation (Hikasa and Sokol 2011), but may use distinct receptors such as ROR1/2 and RYK instead of or in addition to Frizzled (Hikasa et al. 2002; Lu et al. 2004; Mikels and Nusse 2006; Nishita et al. 2006, 2010; Schambony and Wedlich 2007; Grumolato et al. 2010; Lin et al. 2010; Gao et al. 2011). In such cases, signaling mechanisms are likely to include planar cell polarity (PCP) components, such as Vangl2, Flamingo, Prickle, Diversin, Rho GTPases, and c-Jun amino-terminal kinases (JNKs), which do not directly affect β-catenin stability (Fig. 1) (Sokol 2000; Schwarz-Romond et al. 2002; Schambony and Wedlich 2007; Komiya and Habas 2008; Axelrod 2009; Itoh et al. 2009; Tada and Kai 2009; Sato et al. 2010; Gao et al. 2011). This simplistic dichotomy of the Wnt pathway does not preclude some Wnt ligands from using both β-catenin-dependent and -independent routes in a context-specific manner.Despite the existence of many pathway branches, only the β-catenin-dependent branch has been implicated in body-axis specification. Recent experiments in lower vertebrates have identified additional pathway components and targets and provided new insights into the underlying mechanisms. 相似文献
13.
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. 相似文献
14.
Animals evolved in seas teeming with bacteria, yet the influences of bacteria on animal origins are poorly understood. Comparisons among modern animals and their closest living relatives, the choanoflagellates, suggest that the first animals used flagellated collar cells to capture bacterial prey. The cell biology of prey capture, such as cell adhesion between predator and prey, involves mechanisms that may have been co-opted to mediate intercellular interactions during the evolution of animal multicellularity. Moreover, a history of bacterivory may have influenced the evolution of animal genomes by driving the evolution of genetic pathways for immunity and facilitating lateral gene transfer. Understanding the interactions between bacteria and the progenitors of animals may help to explain the myriad ways in which bacteria shape the biology of modern animals, including ourselves.The first bacteria evolved more than 3 billion years ago and dominated the biosphere continually thereafter, shaping the environment in which animals would eventually evolve more than 2 billion years later (Narbonne 2005; Knoll 2011). Because animals evolved in seas filled with bacteria and have lived in close association with bacteria throughout their evolutionary history, it is likely that diverse interactions with bacteria (including predation on bacteria, harboring bacterial commensals, and infection with bacterial pathogens) influenced animal origins. Nonetheless, although the potential contributions of global environmental change and genome evolution to animal origins have received a fair amount of attention (Hoffman et al. 1998; Knoll and Carroll 1999; Knoll 2003; King 2004; Canfield et al. 2007; Shen et al. 2008; Srivastava et al. 2008, 2010; Richter and King 2013), relatively little is known about how the interactions of animal progenitors with the abundant bacteria in their environment may have influenced the evolution of animals (McFall-Ngai 1999; Moran 2007; Hughes and Sperandio 2008; McFall-Ngai et al. 2013). We review here the current state of knowledge about ancient bacterial interactions and consider how these associations may have shaped the biology and evolution of the earliest animals. 相似文献
15.
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). 相似文献
16.
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. 相似文献
17.
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). 相似文献
18.
19.
Eukaryotic genomes are composed of genes of different evolutionary origins. This is especially true in the case of photosynthetic eukaryotes, which, in addition to typical eukaryotic genes and genes of mitochondrial origin, also contain genes coming from the primary plastids and, in the case of secondary photosynthetic eukaryotes, many genes provided by the nuclei of red or green algal endosymbionts. Phylogenomic analyses have been applied to detect those genes and, in some cases, have led to proposing the existence of cryptic, no longer visible endosymbionts. However, detecting them is a very difficult task because, most often, those genes were acquired a long time ago and their phylogenetic signal has been heavily erased. We revisit here two examples, the putative cryptic endosymbiosis of green algae in diatoms and chromerids and of Chlamydiae in the first photosynthetic eukaryotes. We show that the evidence sustaining them has been largely overestimated, and we insist on the necessity of careful, accurate phylogenetic analyses to obtain reliable results.Today it is widely accepted that photosynthesis originated in eukaryotes by the endosymbiosis of a cyanobacterium within a heterotrophic eukaryotic host. This occurred in a lineage that subsequently diversified to give rise to the three contemporary groups of primary photosynthetic eukaryotes: Viridiplantae (including green algae and land plants), Rhodophyta and Glaucophyta, grouped collectively within a unique eukaryotic superphylum called Archaeplastida (Adl et al. 2005) or Plantae (Cavalier-Smith 1982). Recently, a second case of primary endosymbioses has been unveiled thanks to the characterization of Paulinella chromatophora, a filose amoeba that hosts a cyanobacterium with a reduced genome that has been described as “a plastid in the making” (Marin et al. 2005; Keeling and Archibald 2008; Nowack et al. 2008). Primary endosymbioses resulted in the establishment of plastids with two membranes. However, a vast variety of eukaryotes possess plastids with three or more membranes. They derive from the endosymbioses of primary photosynthetic eukaryotes within other eukaryotic cells (Delwiche 1999; Keeling 2013). Such secondary endosymbioses have spread photosynthesis across the eukaryotic tree, either by the endosymbiosis of red or of green algae. Whereas it is almost certain that secondary endosymbioses of green algae occurred twice (in euglenids and chlorarachniophytes), secondary red algal plastids are found in a variety of alveolates, stramenopiles, cryptophytes, and haptophytes, and the number of red algal endosymbioses at the origin of these groups has been matter of intense debate (Baurain et al. 2010; Keeling 2010, 2013; Burki et al. 2012b). Moreover, the existence of tertiary endosymbioses (namely, the symbiosis of a secondary photosynthetic eukaryote within another eukaryotic cell) and of plastid replacements makes the picture of plastid evolution in eukaryotes even more complex. Dinoflagellates, some of which have replaced their ancestral red algal plastids by green algae, diatoms, haptophytes, or cryptophytes, are paradigmatic examples of such complex situations (Keeling 2013).The evolution of plastids has been studied using genes from the plastid genome as well as typical eukaryotic nuclear genes, which allow inferring the phylogenies of both the plastids and their hosts. The use of those markers has led to interesting discoveries, such as the monophyly of the Archaeplastida (Moreira et al. 2000; Rodríguez-Ezpeleta et al. 2005) or the difficulties in reconciling the plastid and host histories in eukaryotes with red algal plastids (Baurain et al. 2010; Burki et al. 2012b). However, a third class of genes can also provide useful complementary information: the genes of plastid origin retrieved within the nuclear genome of the host. In fact, contemporary plastids have small genomes, which is due to the fact that most of the original cyanobacterial symbiont genes were lost or transferred to the host nucleus (by a process called endosymbiotic gene transfer, EGT) during the evolution of plastids (Weeden 1981; Martin et al. 1998). These transfer events are not restricted to plastid endosymbioses—the same phenomenon occurred during the endosymbiosis that gave rise to the mitochondria (Gray et al. 1999; Burger et al. 2003).EGT genes may serve to study the evolutionary history of plastids and, in particular, the presence of cryptic endosymbioses. In fact, species that had a plastid in the past but lost photosynthesis may have conserved genes of plastid origin in their nuclear genomes. This has been shown for a variety of nonphotosynthetic eukaryotes, such as, for example, apicomplexan parasites (Fast et al. 2001; Roos et al. 2002; Williams and Keeling 2003; Huang et al. 2004), perkinsids (Stelter et al. 2007; Matsuzaki et al. 2008; Fernández Robledo et al. 2011) or nonphotosynthetic dinoflagellates (Sanchez-Puerta et al. 2007; Slamovits and Keeling 2008), and green algae (de Koning and Keeling 2004). Although much more controversial, potential EGTs have also been used to propose a photosynthetic ancestry for ciliates (Reyes-Prieto et al. 2008) or that algae with secondary plastids of red algal origin, such as diatoms and chromerids, may have contained green algal endosymbionts in their past (Moustafa et al. 2009; Woehle et al. 2011). Likewise, several dozens of potential EGTs have been detected in algae and plants that appear to have been acquired from Chlamydiae, a group of parasitic bacteria (Huang and Gogarten 2007; Becker et al. 2008; Moustafa et al. 2008), which led to proposing that cryptic chlamydial endosymbionts may have helped to establish the first plastids, in particular, by providing essential functions for plastid activity (Greub and Raoult 2003; Ball et al. 2013; Baum 2013).We revise here some of these cases of cryptic endosymbiosis, with special attention on the difficulties in accurately detecting EGT and the importance of proper phylogenetic analysis and of an adequate taxonomic sampling to achieve that task. 相似文献
20.
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. 相似文献