Structural Components of Synaptic Plasticity and Memory Consolidation

Consolidation of implicit memory in the invertebrate Aplysia and explicit memory in the mammalian hippocampus are associated with remodeling and growth of preexisting synapses and the formation of new synapses. Here, we compare and contrast structural components of the synaptic plasticity that underlies these two distinct forms of memory. In both cases, the structural changes involve time-dependent processes. Thus, some modifications are transient and may contribute to early formative stages of long-term memory, whereas others are more stable, longer lasting, and likely to confer persistence to memory storage. In addition, we explore the possibility that trans-synaptic signaling mechanisms governing de novo synapse formation during development can be reused in the adult for the purposes of structural synaptic plasticity and memory storage. Finally, we discuss how these mechanisms set in motion structural rearrangements that prepare a synapse to strengthen the same memory and, perhaps, to allow it to take part in other memories as a basis for understanding how their anatomical representation results in the enhanced expression and storage of memories in the brain.Santiago Ramón y Cajal (1894) used the insights provided by his remarkable light microscopic observations of neurons selectively stained with the Golgi method to propose the first cellular theory of memory storage as an anatomical change in the functional connections between nerve cells, later called synapses (Sherrington 1897). For most of the last century, chemical synapses were thought to convey information in only one direction—from the presynaptic to the postsynaptic neuron. It now is clear that synaptic transmission is a bidirectional and self-modifiable form of cell–cell communication (Peters et al. 1976; Jessell and Kandel 1993). This appreciation of reciprocal signaling between pre- and postsynaptic elements is consistent with other forms of intercellular communication and provides a conceptual framework for understanding memory-induced changes in the structure of the synapse. Indeed, an increasing body of evidence suggests that trans-synaptic signaling and coordinated recruitment of pre- and postsynaptic mechanisms underlie consolidation of both implicit and explicit forms of memory storage (Marrone 2005; Hawkins et al. 2006; Bailey et al. 2008).Studies in a variety of systems have found that molecular mechanisms of consolidation and long-term storage of memory begin at the level of the synapse. Existing proteins are modified, signals are sent back to the nucleus so that specific genes are expressed, and gene products are transported back to the synapse where the local synthesis of new protein is triggered to allow for the remodeling, addition, and elimination of synapses (Bailey and Kandel 1985; Bailey et al. 1996; Kandel 2001; Bourne and Harris 2008, 2012). These structural components of synaptic plasticity are thought to represent a cellular change that contributes to both implicit and explicit memory consolidation (Greenough and Bailey 1988; Bailey and Kandel 1993; Bailey et al. 2005; Bourne and Harris 2008, 2012). The association between alterations in the structure and/or number of synapses and memory storage has led to numerous studies regarding the signaling pathways that might couple molecular changes to structural changes. In addition, parallel homeostatic mechanisms have been identified that can trigger synaptic scaling, which serves to stabilize the strengthened synapses while weakening or eliminating other synapses, thus providing specificity during memory consolidation (Bourne and Harris 2011; Schacher and Hu 2014).In this review, we compare and contrast structural changes at the synapse during both implicit and explicit memory consolidation, as well as the molecular signaling pathways that initiate the learning-induced structural changes versus those that serve to maintain these changes over time. Toward that end, we will focus on two experimental model systems and several prototypic forms of synaptic plasticity that we have worked on and that have been extensively studied as representative examples of memory storage: long-term habituation and sensitization of the gill-withdrawal reflex in Aplysia. These are examples of implicit memory consolidation and hippocampal-based long-term potentiation (LTP) and long-term depression (LTD), as candidate mechanisms for the synaptic plasticity underlying explicit memory storage in mammals. These will serve as useful points of comparison to consider similarities, differences, and still-existing limitations in our understanding of the functional significance of the structural synaptic plasticity recruited during the consolidation of both implicit and explicit forms of memory.     

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).     

Sexual Conflict between Parents: Offspring Desertion and Asymmetrical Parental Care

Parental care is an immensely variable social behavior, and sexual conflict offers a powerful paradigm to understand this diversity. Conflict over care (usually considered as a type of postzygotic sexual conflict) is common, because the evolutionary interests of male and female parents are rarely identical. I investigate how sexual conflict over care may facilitate the emergence and maintenance of diverse parenting strategies and argue that researchers should combine two fundamental concepts in social behavior to understand care patterns: cooperation and conflict. Behavioral evidence of conflict over care is well established, studies have estimated specific fitness implications of conflict for males or females, and experiments have investigated specific components of conflict. However, studies are long overdue to reveal the full implications of conflict for both males and females. Manipulating (or harming) the opposite sex seems less common in postzygotic conflicts than in prezygotic conflicts because by manipulating, coercing, or harming the opposite sex, the reproductive interest of the actor is also reduced. Parental care is a complex trait, although few studies have yet considered the implications of multidimensionality for parental conflict. Future research in parental conflict will benefit from understanding the behavioral interactions between male and female parents (e.g., negotiation, learning, and coercion), the genetic and neurogenomic bases of parental behavior, and the influence of social environment on parental strategies. Empirical studies are needed to put sexual conflict in a population context and reveal feedback between mate choice, pair bonds and parenting strategies, and their demographic consequences for the population such as mortalities and sex ratios. Taken together, sexual conflict offers a fascinating avenue for understanding the causes and consequences of parenting behavior, sex roles, and breeding system evolution.Sexual conflict over care is a type of evolutionary conflict that emerges from the different interests of males and females in regard to parental care (Trivers 1972; Clutton-Brock 1991; Chapman et al. 2003; Arnqvist and Rowe 2005). The conflict arises when the young benefit from the effort of either parent, but each parent pays only the cost of its own effort, so that each parent would have higher fitness if the other parent provides more care (Houston et al. 2005; Lessells 2006; Klug et al. 2012). Conflict refers to the way selection acts on the two sexes that have different optimum values in parental provisioning; between the two optima, sexually antagonistic selection operates (Lessells 2012). Sexual conflict over care can be seen as tug-of-war, because each parent is tempted to pull out of care leaving the other parent to provide more care for the young (Székely et al. 1996; Arnqvist and Rowe 2005; Lessells 2012).Sexual conflict over care seems to be the rule rather than the exception. The conflict may be resolved by one or both parents failing to adopt the optimal parenting for their mate and nonetheless remaining in conflict, or by both parents adopting the optima that suit their mate (i.e., exhibit the maximum provisioning possible). Examples of the latter conflict resolution (whereby the conflict is completely wiped out) are exceedingly rare and seem to be limited to three scenarios. First, conflict over care is not expected in obligate monogamy by both males and females so that the lifetime reproductive successes of both parents are identical. This may occur in semelparous organisms (i.e., both the male and the female put their resources into a single breeding event) or in iteroparous organisms with lifelong exclusive monogamy. Second, males and females might be genetically identical, so even though one or both sexes are polygamous, polygamy would benefit the same genome whether it is in the male or the female phenotype. Third, parental care is cost-free and thus parents provide maximum level of care (P Smiseth, pers. comm.). However, few, if any, organisms fit these restrictive assumptions, and thus conflict-free parenting seems exceedingly rare in nature: (1) some level of polygamy (by males, females, or both sexes) appears to be widespread; (2) the reproduction by genetically identical individuals (clones) as separate sexes (males and females) seems unlikely although not impossible if sex is determined environmentally; and (3) care provisioning, as far as we are aware, does have costs that discourage parents from providing their absolute maxima for a given batch of offspring.Parents may have conflicting interest over caring or deserting the young, the amount of care provided for each young, the number of simultaneous mates, the size and sex ratio of their brood, and the synchronization of birth for a clutch or litter of young (Westneat and Sargent 1996; Houston et al. 2005; Klug et al. 2012; Lessells 2012). Conflict between parents over care is usually labeled as a postzygotic conflict although resources had been already allocated into the gametes before fertilization as part of parental provisioning (Clutton-Brock 1991); other examples of postzygotic conflicts include infanticide and genomic imprinting (Chapman et al. 2003; Tregenza et al. 2006; Lessells 2012; see Palombit 2014).Studies of conflict over care are fascinating for at least four major reasons. First, parental care is diverse. There is great variation both between and within species in the types of care provided, duration of care, and the sex of the care-providing parent (Wilson 1975; Clutton-Brock 1991; McGraw et al. 2010; Royle et al. 2012), and sexual conflict is thought to be one of the main drivers of this diversity. Second, parental care is one of the core themes in breeding systems and sex role evolution, and it is increasingly evident that parental care can only be understood by dissecting the entangled relationships between ecological and life-history settings, and the variety of mating and parenting behavior (Székely et al. 2000; Webb et al. 2002; Wedell et al. 2006; Jennions and Kokko 2010; Klug et al. 2012). Third, parental care was (and is) one of the test beds of evolutionary game theory. Numerous models have been developed to understand how parents interact with each other and with their offspring (Trivers 1972; Maynard Smith 1977; Houston and Davies 1985; Balshine-Earn and Earn 1998; McNamara et al. 1999, 2000; Webb et al. 1999; Johnstone and Hinde 2006; Johnstone et al. 2014). Parental care research is one field in which empiricists are extensively testing the predictions of evolutionary game theoretic models in both the laboratory and wild populations (Székely et al. 1996; Balshine-Earn and Earn 1998; Harrison et al. 2009; Klug et al. 2012; Lessells 2012; van Dijk et al. 2012), although the congruence between theoretical and empirical work is not as tight as often assumed (Houston et al. 2013). Finally, parental care—wherever it occurs—is often a major component of fitness, because whether the offspring are cared for or abandoned has a large impact on their survival, maturation, and reproduction (Smiseth et al. 2012). Therefore, parental care (or the lack of it) may have an impact on population productivity and population growth and influences the resilience of populations to various threats (Bessa-Gomes et al. 2004; Veran and Beissinger 2009; Blumstein 2010). Thus, understanding the behavioral interactions between parents and the fitness implications of these interactions is highly relevant for population dynamics and biodiversity conservation (Alonzo and Sheldon 2010; Blumstein 2010).Sexual conflict over care has been reviewed recently (van Dijk and Székely 2008; Lessells 2012; Houston et al. 2013). Here, I focus on three issues that have not been extensively covered by previous reviews: (1) why sexual conflict over care occurs in some environments, whereas in others parental cooperation appears to dominate; (2) how can one detect sexual conflict over care; and (3) what are the implications of sexual conflict over care for macroevolution. I view causes and implications of parental care primarily from empirical perspectives; there are excellent reviews on the rich theoretical literature (Lessells 2006, 2012; Klug et al. 2012; Houston et al. 2013). My intention is not to be comprehensive; instead, I use selected examples to illustrate salient features of conflict over care. I focus on ecological and evolutionary aspects; for a discussion of the genetic and neuroendocrine bases of parental care, see Adkins-Regan (2005), McGraw et al. (2010), and Champagne and Curley (2012). I prefer to use the term “parental care” instead of “parental investment,” because the latter, as admitted by Trivers (1985), is extremely difficult to estimate empirically and thus may have a limited use in empirical studies (Mock and Parker 1997; McGraw et al. 2010). The term “parental investment” can be deceptive, if used without directly demonstrating the full costs of care. The term “parental care” is less restrictive, because it refers to any form of parental behavior that appears to increase the fitness of an offspring and is likely to have evolved for this function (Clutton-Brock 1991; Smiseth et al. 2012). In this review, I focus on families in the narrow sense (i.e., two parents and their offspring), although in numerous organisms the families are more extensive and may include several generations of offspring living together and/or unrelated individuals that assist the parents rearing the young.     

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.     

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).     

Origin of Microglia: Current Concepts and Past Controversies

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.     

Is Sexual Conflict an “Engine of Speciation”?

At the end of the last century, sexual conflict was identified as a powerful engine of speciation, potentially even more important than ecological selection. Earlier work that followed—experimental, comparative, and mathematical—provided strong initial support for this assertion. However, as the field matures, both the power of sexual conflict and constraints on the evolution of reproductive isolation as driven by sexual conflict are becoming better understood. From theoretical studies, we now know that speciation is only one of several possible evolutionary outcomes of sexual conflict. In line with these predictions, both experimental evolution studies and comparative analyses of fertilization proteins and of species richness show that sexual conflict leads to, or is associated with, reproductive isolation and speciation in some cases but not in others. Increased genetic variation (especially in females) without reproductive isolation is an underappreciated consequence of sexually antagonistic selection.By the end of 1990s, studies of sexual conflict and sexually antagonistic coevolution moved to the forefront of experimental and theoretical research in evolutionary biology (Rice and Holland 1997; Holland and Rice 1998; Rice 1998). Although the potential evolutionary importance of sexual conflict was anticipated and articulated from a theoretical point of view by Geoff Parker 20 years earlier (Parker 1979), the explosive interest in this topic was a result of groundbreaking experimental work with Drosophila melanogaster by Bill Rice (1993, 1996), which directly showed high potential for sexually antagonistic coevolution.Sexual conflict is a special case of intragenomic conflict (Rice and Holland 1997; Rice 1998; Crespi and Nosil 2013). Sexual conflict occurs if the interests of the sexes with regard to certain aspects of reproduction differ (Parker 1979; Arnqvist and Rowe 2005). Ultimately, sexual conflict arises because of the differences in the roles played by the sexes in the process of reproduction, which in turn lead to the differences between the sexes in the costs and benefits of mating and reproduction (Bateman 1948; Trivers 1972; Parker 1979). Sexual conflict can occur over mating rate (Rice and Holland 1997; Holland and Rice 1998; Rice 1998), offspring size (Haig 2000), parental care (Smith and Härdling 2000; Barta et al. 2002), the use of sperm (Ball and Parker 2003), epigenetic control of development (Rice et al. 2012), etc.Sexual conflict can occur through two genetic routes (Chapman and Partridge 1996; Parker and Partridge 1998). Within-locus conflict occurs when the locus controls a trait expressed in both sexes and the optimum trait values differ between the sexes. As a result, optimizing the trait value in one sex will lead to a fitness reduction in the other sex. Within-locus conflict can be resolved via a number of mechanisms, including the evolution of sex linkage, sex-specific expression of genes, gene duplication, and condition dependence (Bonduriansky and Chenoweth 2009; van Doorn 2009). Between-locus conflict occurs when there are two different (sets of) traits each expressed in one sex only but affecting the fitness of both sexes in opposite directions. In this case, adaptive changes in a trait of one sex cause deleterious fitness consequences for the other sex, which can be negated by the evolution in a trait of the other sex, which in turn will cause deleterious fitness consequences for the first sex. For example, males can evolve adaptations increasing their mating rate, which would be detrimental for females who would then evolve some counteradaptations to decrease the mating rate (Rice 1996).One particularly exciting idea that has emerged from studies of sexual conflict and sexually antagonistic coevolution is that sexual conflict can be an important “engine of speciation” (Rice 1996, 1998; Howard et al. 1998; Parker and Partridge 1998). In standard modern perspective, speciation is a result of genetic divergence between populations accompanied by the evolution of reproductive isolation (Howard and Berlocher 1998; Schluter 2000; Coyne and Orr 2004; Dieckmann et al. 2004; Gavrilets 2004). Genetic divergence can be driven by a variety of evolutionary factors, including mutation, random genetic drift, and natural, sexual, and social selection. Reproductive isolation can follow from a variety of mechanisms, resulting in incompatibilities (including genetic, developmental, morphological, ecological, and behavioral) of males and females from diverging populations or in a reduced fitness of their offspring. As was argued by Rice (1998), Parker and Partridge (1998), and others (e.g., Howard et al. 1998), sexual conflict can contribute to these processes in a number of ways.Below, I briefly summarize several, mostly verbal, theories of biological diversification caused by sexual conflict and then move to discussing some of the more concrete mathematical models and empirical data and patterns.     

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.     

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.     

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.     

Bacterial Influences on Animal Origins

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.     

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.     

Evolutionary Forces Shaping the Golgi Glycosylation Machinery: Why Cell Surface Glycans Are Universal to Living Cells

Despite more than 3 billion years since the origin of life on earth, the powerful forces of biological evolution seem to have failed to generate any living cell that is devoid of a dense and complex array of cell surface glycans. Thus, cell surface glycans seem to be as essential for life as having a DNA genetic code, diverse RNAs, structural/functional proteins, lipid-based membranes, and metabolites that mediate energy flux and signaling. The likely reasons for this apparently universal law of biology are considered here, and include the fact that glycans have the greatest potential for generating diversity, and thus evading recognition by pathogens. This may also explain why in striking contrast to the genetic code, glycans show widely divergent patterns between taxa. On the other hand, glycans have also been coopted for myriad intrinsic functions, which can vary in their importance for organismal survival. In keeping with these considerations, a significant percentage of the genes in the typical genome are dedicated to the generation and/or turnover of glycans. Among eukaryotes, the Golgi is the subcellular organelle that serves to generate much of the diversity of cell surface glycans, carrying out various glycan modifications of glycoconjugates that transit through the Golgi, en route to the cell surface or extracellular destinations. Here I present an overview of general considerations regarding the selective forces shaping evolution of the Golgi glycosylation machinery, and then briefly discuss the common types of variations seen in each major class of glycans, finally focusing on sialic acids as an extreme example of evolutionary glycan diversity generated by the Golgi. Future studies need to address both the phylogenetic diversity the Golgi and the molecular mechanisms for its rapid responses to intrinsic and environmental stimuli.Every eukaryotic cell is covered with a dense and complex array of glycans, which also feature prominently in extracellular matrix and secreted soluble molecules (Varki and Sharon 2009). The bulk of these glycans are synthesized by the Golgi (Emr et al. 2009; Varki et al. 2009a), and a significant percentage of the genes in the typical eukaryotic genome are dedicated to these glycosylation functions (Henrissat et al. 2009). Other articles on this topic address the primary biochemical pathways involved (Stanley 2011), transport mechanisms that expose the transiting cargo to the ordered sequence of glycosidases and glycosyltransferases that carry out the modifications to the bound oligosaccharides (Glick and Luini 2011; Banfield 2011), genetic diseases that can affect the Golgi glycosylation system (Freeze and Ng 2011), and the evolution and diversity of Golgi apparatus structure in eukaryotes (Klute et al. 2011). Here I consider the Golgi glycosylation machinery from an evolutionary perspective, asking why it is universal to eukaryotes, how it has changed and been modified over evolutionary time, and why this machinery has diverged so much between different taxa. Some figures in this article are from Essentials of Glycobiology, the first open access textbook (http://www.ncbi.nlm.nih.gov/bookshelf/br.fcgi?book=glyco2). The reader is referred to the relevant articles in Essentials of Glycobiology (Varki and Sharon 2009; Varki et al. 2009a; Freeze and Elbein 2009; Varki and Lowe 2009) for further information about some of the points made here, as well as to some other articles in the textbook on related topics (Stanley et al. 2009; Brockhausen et al. 2009; Schnaar et al. 2009; Ferguson et al. 2009; Freeze and Haltiwanger 2009; Stanley and Cummings 2009; Varki and Schauer 2009; Hascall and Esko 2009; Esko et al. 2009).     

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.     

Wnt Signaling in Vertebrate Axis Specification

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.     

Place Cells,Grid Cells,and Memory

The hippocampal system is critical for storage and retrieval of declarative memories, including memories for locations and events that take place at those locations. Spatial memories place high demands on capacity. Memories must be distinct to be recalled without interference and encoding must be fast. Recent studies have indicated that hippocampal networks allow for fast storage of large quantities of uncorrelated spatial information. The aim of the this article is to review and discuss some of this work, taking as a starting point the discovery of multiple functionally specialized cell types of the hippocampal–entorhinal circuit, such as place, grid, and border cells. We will show that grid cells provide the hippocampus with a metric, as well as a putative mechanism for decorrelation of representations, that the formation of environment-specific place maps depends on mechanisms for long-term plasticity in the hippocampus, and that long-term spatiotemporal memory storage may depend on offline consolidation processes related to sharp-wave ripple activity in the hippocampus. The multitude of representations generated through interactions between a variety of functionally specialized cell types in the entorhinal–hippocampal circuit may be at the heart of the mechanism for declarative memory formation.The scientific study of human memory started with Herman Ebbinghaus, who initiated the quantitative investigation of associative memory processes as they take place (Ebbinghaus 1885). Ebbinghaus described the conditions that influence memory formation and he determined several basic principles of encoding and recall, such as the law of frequency and the effect of time on forgetting. With Ebbinghaus, higher mental functions were brought to the laboratory. In parallel with the human learning tradition that Ebbinghaus started, a new generation of experimental psychologists described the laws of associative learning in animals. With behaviorists like Pavlov, Watson, Hull, Skinner, and Tolman, a rigorous program for identifying the laws of animal learning was initiated. By the middle of the 20th century, a language for associative learning processes had been developed, and many of the fundamental relationships between environment and behavior had been described. What was completely missing, though, was an understanding of the neural activity underlying the formation of the memory. The behaviorists had deliberately shied away from physiological explanations because of the intangible nature of neural activity at that time.Then the climate began to change. Karl Lashley had shown that lesions in the cerebral cortex had predictable effects on behavior in animals (Lashley 1929, 1950), and Donald Hebb introduced concepts and ideas to account for complex brain functions at the neural circuit level, many of which have retained a place in modern neuroscience (Hebb 1949). Both Lashley and Hebb searched for the engram, but they found no specific locus for it. A significant turning point was reached when Scoville and Milner (1957) reported severe loss of memory in an epileptic patient, patient H.M., after bilateral surgical removal of the hippocampal formation and the surrounding medial temporal lobe areas. “After operation this young man could no longer recognize the hospital staff nor find his way to the bathroom, and he seemed to recall nothing of the day-to-day events of his hospital life.” This tragic misfortune inspired decades of research on the function of the hippocampus in memory. H.M.’s memory impairment could be reproduced in memory tasks in animals and studies of H.M., as well as laboratory animals, pointed to a critical role for the hippocampus in declarative memory—memory, which, in humans, can be consciously recalled and declared, such as memories of experiences and facts (Milner et al. 1968; Mishkin 1978; Cohen and Squire 1980; Squire 1992; Corkin 2002). What was missing from these early studies, however, was a way to address the neuronal mechanisms that led information to be stored as memory.The aim of this article is to show how studies of hippocampal neuronal activity during the past few decades have brought us to a point at which a mechanistic basis of memory formation is beginning to surface. An early landmark in this series of investigations was the discovery of place cells, cells that fire selectively at one or few locations in the environment. At first, these cells seemed to be part of the animal’s instantaneous representation of location, independent of memory, but gradually, over the course of several decades, it has become clear that place cells express current as well as past and future locations. In many ways, place cells can be used as readouts of the memories that are stored in the hippocampus. More recent work has also shown that place cells are part of a wider network of spatially modulated neurons, including grid, border, and head direction cells, each with distinct roles in the representation of space and spatial memory. In this article, we shall discuss potential mechanisms by which these cell types, particularly place and grid cells, in conjunction with synaptic plasticity, may form the basis of a mammalian system for fast high-capacity declarative memory.     

Metabolic Stress in Autophagy and Cell Death Pathways

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